advances in technology innovation, vol. 1, no. 2, 2016, pp. 50 52 50 copyright © taeti tubular steel arch stabilized by textile membranes ondrej svoboda, josef machacek* czech technical university in prague, faculty of civil engineering, prague, czech republic. received 17 february 2016; received in revised form 01 april 2016; accepted 06 april 2016 abstract tubular steel arch supporting textile membrane roofing is investigated experimentally and numerically. the stabilizat ion effects of the text ile membrane on in-p lane and out-of-plane behavior of the arch is of primary interest. first a model of a large membrane structure tested in laboratory is described. prestressed membranes of pvc coated polyester fabric ferrari ® précontraint 702s were used as a currently standard and excellent material. the test arrangement, loading and resulting load/deflection values are presented. the supporting structure consisted of two steel arch tubes, outer at edge of the membrane and inner supporting interior of the membrane roofing. the stability and strength behavior of the inner tube under both symmetrical and asymmetrical loading was monitored and is shown in some details. second the sofistik software was employed to analyze the structural behavior in 3d, using geometrically nonlinear analysis with imperfections (gnia). the numerical analysis , fe mesh sensitivity, the membrane prestressing and common boundary conditions are validated by test results. finally a parametrical study concerning stability of mid arch with various geometries in a membrane structure with several supporting arches is presented, with recommendations for a practical design. keywords : text ile membranes, prestressing, steel arch, arch stabilizat ion, gnia, tests 1. introduction design of steel structures cooperating with tsf (tensioned fabric structures) requires geometrically and materially non-linear analysis with imperfect ions (gmnia). the essential in such analysis is an appropriate input of the membrane material behavior; see [1], [2], [3], [4], etc. while membrane surface is exclusively tensioned, supporting steelwork is most often exposed to a compression and/or bending. this type of loading, in combination with slender steel elements, results into stability problems . usually the membrane represents a spring support for the steel structure and the complex structure need to be designed using proper software package allowing integrated modelling, e.g. easy [5], sofistik [6], etc., while a separated modelling of the membrane and steelwork is rather limited [7]. th is paper demonstrates significant stabilizing effects of membranes to the respective supporting steelwork, based on numerical parametrical studies validated by tests. 2. validation by tests the tested membrane structure supported by two steel tube arches is shown in fig. 1. the membrane is pvc coated polyester fabric ferrari ® précontraint 702s (with braking loadings in both warp and fill direct ions sult ≈ 56 kn/m, working loading smax = sult/5 ≈ 11.2 kn/m and suitable prestressing up to pmax = smax/5 ≈ 2.24 kn/m). principal dimensions of the vertical inner tubular arch of ø 26.9x3.2 [mm] are lxh = 4500x1200 [mm], while outer tubular arch has inclination of 60° in respect to horizontal. fig. 1 the layout of the tested model * corresponding author, email: machacek@cvut.fsv.cz advances in technology innovation, vol. 1, no. 2, 2016, pp. 50 52 51 copyright © taeti the shape and cut of the membranes resulted from formfinder software [8] and the membranes were prestressed roughly with p ≈ 0.2 kn/m. the investigation concerned exclusively the inner steel arch to find stabilizing effect of the membrane to its nonlinear behavior. first the inner arch alone (without fastening the membrane) was loaded and second, after the membrane assembly, the complete membrane structure. for loading calibrated pouches with steel pellets were used and suspended from seven points of the arch (for the symmetrical loading see fig. 2) or from four points in case of asymmetrical loading. fig. 2 symmetrical loading of the tested model during the tests the deflections and stresses were carefu lly monitored in 9 locations (with no. 4 at midspan). in this paper the symmetrical test and deflections only are described due to a space limit . the deflections (vertical in fig. 3 and transverse in fig. 4) demonstrate that the arch without membrane buckled out-of-plane at total loading of f0 = 5.5 kn, with vertical deflection along all span down, while the test of the arch stabilized by the membrane was terminated under total load of fm = 8.3 kn, showing the enormous stabilizing effect of the membrane. fig. 3 symmetrical loading vertical deflections fig. 4 symmetrical loading – transverse deflections sofistik software [6] was used to perform gnia (using n-r iteration) both for the inner arch alone and the complete membrane structure, employing orthotropic model with 5 parameters according to [3]. various meshing of the membrane was analysed (square sizes of 25, 50, 100 and 200 [mm]) with differences ≤ 0.2 % and optimum size o f 50 mm was used in the analysis. the equilibrium state and final unloaded shape of the membrane structure was found under initial sofistik software calculations. both arch alone analysis and membrane with the two arches were performed and results compared with tests showing excellent agreement. the results of gnia for the symmetrical loading under various prestress of the membrane p [kn/m] are shown in fig. 8 and with the prestress of 0.2 kn/m (corresponding to test) justify use of the model for fo llowing parametric studies. fig. 5 comparison of the test and gnia vertical deflections under various prestressing 3. parametrical studies in-plane and out-of-p lane stability of 132 central arches in the 5 arches assembly (see fig. 5), where the edge arches were continuously transversely supported, have been studied under various geometries, loadings and membrane prestressing. more details and results are ready for publication, but due to limited space not shown here. advances in technology innovation, vol. 1, no. 2, 2016, pp. 50 52 52 copyright © taeti fig. 5 mid-arch with out-of-plane buckling 4. conclusions (1) the effect of text ile membranes on both in-plane and out-of-plane supporting arch stability and strength is enormous. (2) gnia (by sofistik) proved to be adequate, provided the right value of the membrane prestressing is used. (3) large parametric studies of barrel membrane structures supported by a row of steel arches show enormous increase of both in-plane and particularly out-of-plane buckling loads in comparison to the ones of an arch alone. provided the outer arches are transversely supported, the out-of plane buckling of the mid arches due to membrane support may always be neglected. acknowledgement this work was supported by the czech grant agency; grant gacr no. 105/13/25781s. references [1] s. kato, t. yoshino, and h. minami, “formulat ion of constitutive equations for fabric membranes based on concept of fabric lattice model,” engineering structures, vol. 21, pp. 691-708, 1999. [2] p. gosling, “basic philosophy and calling notice,” tensinet analysis & material working group, tensinews, vol. 13, pp. 12-15, 2007. [3] c. galliot and r. h. luchsinger, “a simple model describing the non-linear b iaxial tensile behaviour of pvc/coated polyester fabrics for use in finite element analysis,” comp. structures, vol. 90, pp. 438-447, 2009. [4] j. b. pargana and w. m. a. leitao, “a simplified stress-strain model for coated plain-weave fabrics used in tensioned fabric structures,” engineering structures, vol. 84, pp. 439-450, 2015. [5] “technet gmbh berlin-stuttgart,” http://www.technet-gmbh.com, 2016. [6] “sofistik 2014,” http://www.sofistik.de/, 2015. [7] d. jermoljev and j. macháček, “implement ation of non-metallic membranes into steel supporting structures ,” proc. recent advances in mechanics and materials in design, ponta delgada, pp. 907-908, july 2015. [8] “formfinder software gmbh, wien,” http://www.formfinder.at/main/software/, 2015.  advances in technology innovation, vol. 2, no. 1, 2017, pp. 25 28 25 ewma controller with concurrent adjustment for a high-mixed production process shui-pin lee department of industrial management, chien hsin university of science and technology, taoyuan, taiwan. received 22 february 2016; received in revised form 15 april 2016; accepted 17 april 2016 abstract the exponentially weighted moving average (ewma) feedback controller is a very popular run-to-run (rtr) process control scheme in the semiconductor industry. traditionally, the manufacturing environment was simplified as a single product and single tool process. in the feedback control, the adjustment of the recipe for the next run is related to the deviation of the current output against the desired target. however, in a commercial foundry, every tool always works for many products. it is called a multiple products and single tool (mpst) process. the challenge of this process is how to adjust the recipes among different products in a production row. in this study, a modified threaded ewma feedback controller, the ewma with concurrent adjustment, is proposed to deal with the issue of multiple products in a tool. when the process disturbances follow an ima(1,1) time series model, the stability of the proposed method will be proven. the optimum discount factors of the proposed ewma controller will be investigated by several simulations in terms of the number of multiple products, their distribution and the scheduling of the process. moreover, according to results of the performance comparisons with threaded ewma, the proposed controller is advantage in the large number of multiple products and in low-frequency products. keywords: ewma, run-to-run, feedback controller, high-mixed production process, concurrent adjustment 1. introduction run-to-run (r2r) process controller has been a conversional quality control technique in semiconductor manufacturing process. it was purposed by integrating statistical process control (spc) and engineering process control (epc) for overcoming the shift or gradually drift in the complex manufacturing process [1-2]. in most semiconductor manufacturing process, the run-to-run process controller for adjusting the input recipe is based on a known prediction model. assume that the i/o relationship of the siso process is linear, the process outputs ( 𝑦𝑡 ) can be expressed as follows: 0 0 1t t ty x     (1) where 𝑥𝑡−1 denotes the process input at run t that has been adjusted after its previous output 𝑦𝑡−1 obtained, 𝛼0 and 𝛽0 are the intercept and slope parameters, respectively, and 𝜖𝑡 denotes the process disturbances. the next process input at run 𝑡 + 1 will be adjusted by: t t a x b    (2) where τ is the process target, 𝑏 is the estimate of the slope 𝛽 and 𝑎𝑡 is the new estimate of 𝛼0 by using the following ewma formula:    1 11t t t ta y bx a      (3) typically, the researches related to the topic of how to enhance the performances of r2r controller are very restricted in a single product and single tool (spst) production environment. however, in many real commercial production processes, a tool will produce several different products. the same type of products might not be produced in-a-row. the kind of manufacturing * corresponding author, email: shuipin@uch.edu.tw advances in technology innovation, vol. 2, no. 1, 2017, pp. 25 28 26 copyright © taeti mode is often called a multiple-productmultiple-tool (mpmt) or a high-mixed production process. the foundries in taiwan are the typical examples of the high-mixed manufacturing mode. the manufacturing environment consists of multiple products passing through a sequence of batch processing steps being that are out by multiple parallel tools. recently, r2r control implementation in a mpmt environment has been discussed by many authors [3-5]. most of these works have attempted to identify parameters that can characterize the product and tool states. however, information is never shared between products or tools in such an approach. thus, epc or spc are ineffective for low frequency products. lee et al. [6] proposed a cumulative sum-type statistical process control for a mpmt process to detect substantial changes in tool and product effects. the estimate of gain parameter will be updated after signals. the recipes of inactive products will be adjusted if spc emits a signal. for statistical significance, the signal is related to the number of different products. in this short paper, the ewma with concurrent adjustment algorithm for a multiple products and single tool (mpst) process is proposed for inactive products. such that, when those products become active, their corresponding recipes can reflect the effect of the tool change. the organization of the paper is as follows. the proposed ewma with concurrent adjustment algorithm is introduced in section 2. in section 3, the stability condition of the proposed method and the evaluation of its performance will be shown. conclusions were then drawn in section 4. 2. ewma controller with concurrent adjustment if we assume the initial estimates of parameters α and β of (1) are correct, the input recipe will be set �̃� = 𝜏−𝛼 𝛽0 for all runs to make the expected output meet the process target. without loss generality, we can simplify (1) by the following expression: 0 1t t ty x   (4) assume that there are j products will be produced in a tool. let 𝑥𝑗,𝑡−1and 𝑦𝑗,𝑡denote the process input and output at run 𝑡. since a tool just can produce one product at each run, the product index 𝑗 is a function of 𝑡. the product 𝑗 is active at run 𝑡, but other 𝐽 − 1 products are inactive. in this paper, the i/o relationship of the mpst environment is , , 1 ,j t j j t j ty x   (5) where 𝛽𝑗 denotes the slope parameter with respect to product 𝑗 and 𝜖𝑗,𝑡 denotes the process disturbance. denote 𝛽𝑗 = 𝛽0𝑓𝐽 , where 𝛽0 denotes the nominal tool effect parameter and 𝑓𝑗 denotes the nominal product effect for product 𝑗 about the reference product. moreover, we take the contrast 𝑓1 = 1 for identifiability. denote 𝑏𝑗,0 as the initial estimate of 𝛽𝑗 , 𝑗 = 1, ⋯ , j then 𝑏1,0 is also the estimate of 𝛽0 and the estimates of the nominal product effects are 𝑓𝑗 = 𝑏𝑗,0 𝑏1,0 . hence, the initial prediction model can be expressed as follows:  , , 1 0 , 1 ˆ|j t j t j j te y x b f x  (6) for the current active product 𝑗, its recipe can be adjusted by , , 0 , ˆ t j t j t j a x b f    (7) where 𝑎𝑗,𝑡 = 𝑎𝑗,𝑡−1 + 𝜔 (𝑦𝑗,𝑡 − 𝜏𝑡) is the formal ewma formula, but for the inactive products 𝑗′ ≠ 𝑗. we propose the concurrent adjustment ', ', 1j t j t ta a c  (8) where𝑐𝑡 = 𝜔 (𝑦𝑗,𝑡 − 𝜏𝑡) and𝜗denotes the concurrent factor. 3. results and discussion the offset of the process output can be expressed by       1 1 0,2 , , 1, 2 0, 0, , , 0, , 1 1 1 j j l l j l j l j l j j t j j lj t h h j j h j l j t j h j t h y y c b c b b b                        (9) where 𝑙 denotes the series index of product 𝑗, advances in technology innovation, vol. 2, no. 1, 2017, pp. 25 28 27 copyright © taeti ∅𝑗 = (1 − 𝜔𝛽0,𝑗 𝑏0,𝑗 ) denote the stable factors, 𝐶𝑗,𝑙 = ∑ 𝑐𝑖 𝑡−1 𝑖=𝑡−ℎ𝑙 𝑗 denotes the cumulative deviation from target and 𝐵 denotes the backward operator. when the process disturbances is an ima (1, 1), or a arma (p, q), the variance of the process output is bounded if |∅𝑗| is smaller than 1 for all 𝑗. according to several simulations in different conditions of the production environment, 𝜔 = 0.2 and 𝜗 = 1.0 are suggested. the performance of the proposed method was evaluated based on the criteria of the relative efficiency, the ratio of mean square errors of the proposed method to that of the threaded ewma controller under the same conditions. fig. 1 shows the results of the relative efficiency comparisons no matter what product scheduling (random or concentration) is, what the number of product types (2 or 4) is and what the magnitude of slope shift is, fig. 1 explicitly shows the proposed method is better than the threaded ewma controller. fig. 1 the relative efficiency of the ewma controller with concurrent adjustment with respect to the threaded ewma controller 4. conclusions in this paper, the ewma with concurrent adjustment algorithm control was proposed for a multiple products process. the exact expression of the process output of the proposed control algorithm is derived. hence, its stability conditions can be obtained. based on several numerical simulations,𝜔 = 0.2 and 𝜗 = 1.0 are suggested for the discount factor of ewma controller and concurrent factor when the process disturbances are a white noise series. compare to the threaded ewma controller in different production scheduling, the advantage of the ewma with concurrent adjustment is increasing in terms of the magnitude of the slope shift. moreover, the larger the number of product types, the bigger the advantage. acknowledgement the support of the minister of science and technology (taiwan), under grant most 104-2221-e-231-005 is gratefully acknowledged. references [1] a. ingolfsson a and e. sachs, “stability and sensitivity of an ewma controller,” journal of quality technology, vol. 25, pp. 271-287, 1993. [2] e. sachs, a. hu, and e. ingolfsson, “run by run process control: combining spc and feedback control,” ieee transactions semiconductor manufacturing, vol. 8, pp. 26-43, 1995. [3] a. v. prabhu and t. f. edgar, “a new state estimation method for high-mix semiconductor manufacturing processes,” journal of process control, vol. 19, pp. 1149-1161, 2009. [4] m. d. ma, c. c. chang, d. s. h. wong, and s. s. jang, “threaded ewma controller tuning and performance evaluation in a high-mixed system,” ieee transactions semiconductor manufacturing, vol. 22, pp. 1-5, 2009. [5] a. j. pasadyn and t. f. edga, “observability and state estimation for multiple product control in semiconductor manufacturing,” ieee transactions semiconductor manufacturing, vol. 18, pp. 592-604, 2005. [6] s. p. lee, d. s. h. wong, c. i. sun, w. h. chen, and s. s. jang, “integrated statistical process control and engineering process advances in technology innovation, vol. 2, no. 1, 2017, pp. 25 28 28 copyright © taeti control for a manufacturing process with multiple tools and multiple products,” journal of industrial and production engineering, vol. 32, no. 3, pp. 174-185, 2015.  advances in technology innovation, vol. 1, no. 2, 2016, pp. 46 49 46 copyright © taeti study of injection molding warpage using analytic hierarchy process and taguchi method dyi-cheng chen*, chen-kun huang department of industrial education and technology, national changhua university of education, changhua, taiwan. received 22 february 2016; received in revised form 09 april 2016; accepted 12 april 2016 abstract this study integrated analytic hierarchy process and taguchi method to investigate into injection mold ing warpage. the warpage important factor will be elected by analytic hierarchy process (ahp), the ahp h ierarchy analysis factor from documents collected and aggregate out data, then through the expert questionnaire delete low weight factor. finally, we used taguchi quality engineering method to decide injection molding optimized combination factors. furthermore, the paper used injection pressure, holding pressure, holding time, mold temperature to analyze four factors, three levels taguchi design data. moreover, the paper discussed the reaction of each factor on the s / n ratio and analysis of variance to obtain the best combination of minimal warpage. keywords: injection molding, analytic hierarchy process (ahp), taguchi method 1. introduction plastic molding methods are injection molding, extrusion molding, blow molding, co-injection molding method, gas-assisted molding method, of which the injection molding method is the most widely used plastic molding technology. kamaruddin [1] used taguchi to improve mixed plastic products. the analysis of the results shows that the optimal combination for low shrinkage are low melting temperature, high injection pressure, low holding pressure, long holding time and long cooling time. shuaib [2] performed to determine the factors that contribute to warpage for a thin shallow injection-molded part. the process used taguchi and anova technique. the result shows that by s/n response and percentage contribution in anova, packing time has been identified to be the most significant factors on affecting the warpage on thin shallow part. radhwan et al. [3] applied taguchi method for the optimization of selected process parameters such as the mold temperature, melt temperature, packing pressure, packing time, and cooling time. the s/n ratio and analysis of variance were utilized to see the most significant factors contributing to shrinkage. nasir et al. [4] designed mold in single and dual type of gate in order to investigate the deflection of warpage for thick component in injection molding process. opasanon and lertsanti [5] implemented the analytic hierarchy process (ahp) to evaluate and rank the importance of the logistics issues according to the needs and requirements of the company’s policy makers. four criteria considered in the ahp include cost, responsiveness, reliability, and utilization. kil et al. [6] study to identify the major variables identified as important for considering the stabilization of slope revegetation based on hydro seeding applications and evaluate weights of each variable using the analytic hierarchy process (ahp). this study integrated analytic hierarchy process and taguchi method to investigate into injection molding warpage. 2. results and discussion of ahp and taguchi method 2.1. analytic hierarchy process (ahp) in this study, injection mold ing gather relevant informat ion, collate and analyze the relevant factors. as shown in the present study hierarchical structure shown in fig. 1. in this study, interviews the way interviews professors from this and related industry contains several interviews with scholars states to carry out * corresponding author, email: dcchen@cc.ncue.edu.tw http://xueshu.baidu.com/s?wd=author%3a%28nasir%2c%20s.m.%29%20&tn=se_baiduxueshu_c1gjeupa&ie=utf-8&sc_f_para=sc_hilight%3dperson advances in technology innovation, vol. 1, no. 2, 2016, pp. 46 49 47 copyright © taeti private visits to the volume. fig. 1 hierarchy architecture diagram using microsoft excel software to analyse all questionnaires, one of the factors to estimate the impact of the overall configuration of the inner surface of the weight value, you can understand the factors within all facet degree of importance the key factors for overall warpage of inject ion molding, as a result as shown in table 1. table 1 the overall weight table main weight secondary eight overall weight a. pressure a1 0.52 0.25 (1) 0.48 a2 0.34 0.16 (2) a3 0.12 0.06 (8) b. time b1 0.44 0.13 (3) 0.29 b2 0.19 0.05 (9) b3 0.22 0.06 (7) b4 0.13 0.03 (10) c. temperature c1 0.29 0.06 (6) 0.22 c2 0.34 0.07 (5) c3 0.35 0.05 (4) 2.2. taguchi design of experiment (1) choose quality characteristics in order to measure the output quality and characteristics from desired value, taguchi has utilized the signal-to-noise ratio; s/n. s/n ratio also used to classify the results and evaluates them to determine the optimum parameters. there are three s/n ratio’s characteristics; the nominal the better, the smaller the better and the higher the better. since this research is carried to reduce warpage, the smaller the better characteristic has been chosen and it is expressed as :          n i iy n ns 1 21 log10/ (1) yi represents the observation, n is the number of tests in one trial. (2) choose control factor as shown table 2, there are four factors identified to be the parameters in this research. they are the injection pressure (a), packing pressure (b), packing time (c),and the mold temperature (d).taguchi method is used to analyze these four injection molding process parameters based on three-level design of experiments and orthogonal array l9(3 4 ) is created . the levels, factors and orthogonal array variance and the combination are shown in table 3 respectively. table 2 selected factors and levels factor level 1 level 2 level 3 a. injection pressure 100 110 120 b. packing pressure 65 75 85 c. packing time 7 9 11 d. mold temperature 80 90 100 table 3 combination of parameters in orthogonal array variance a b c d 1 100 65 7 80 2 100 75 9 90 3 100 85 11 100 4 110 65 9 100 5 110 75 11 80 6 110 85 7 90 7 120 65 11 90 8 120 75 7 100 9 120 85 9 80 (3) experimental data analysis after moldex3d analysis, the results of the experiment to measure out the amount of warpage calcu lated s/n ratio, calcu lated by equation (1) s/n rat io of each group, as shown in table 4. in table 4 can be obtained by injection molding of each factor on the table and the amount of warpage of the reaction the reaction diagram, as shown in table 5 and figure 2. in smaller quality characteristics s / n rat io greater the better quality characteristics, according to tables and graphs can identify the best factor level combination a3b2c3d1, injection pressure 120mpa, packing pressure 75mpa, packing time 11sec, mold temperature 80℃. table 4 results of s/n and warpage of results a b c d warpage s/n advances in technology innovation, vol. 1, no. 2, 2016, pp. 46 49 48 copyright © taeti (mm) ratio 1 1 1 1 1 0.0684 23.2989 2 1 2 2 2 0.0688 23.2482 3 1 3 3 3 0.0722 22.8293 4 2 1 2 3 0.0788 22.0695 5 2 2 3 1 0.0555 25.1141 6 2 3 1 2 0.0764 22.3381 7 3 1 3 2 0.0621 24.1382 8 3 2 1 3 0.0830 21.6184 9 3 3 2 1 0.0602 24.4081 ave. 0.0694 23.2292 table 5 the response table of s/n ratio a b c d level 1 23.13 23.17 22.42 24.27 level 2 23.17 23.33 23.24 23.24 level 3 23.39 23.19 24.03 22.17 effect 0.26 0.16 1.61 2.10 rank 3 4 2 1 combination a3 b2 c3 d1 fig. 2 s / n ratio reaction (4) analysis of variance (anova) analysis of variance (anova, analysis of variance) is mainly determined change of each factor on the quality characteristics variation effect, which is another way to find the most influential factor for the entire experiment, in order to assess the experimental error. table 6 initial variance analysis results of the present experiment. table 6 the first analysis of variance factor ss dof variance a 0.1173 2 0.05866 b 0.0438 2 0.02189 c 3.8826 2 1.94131 d 6.6239 2 3.31196 other 0.0000 0 0.000 total 10.6676 8 1.33345 in table 6 that the variance b factor holding pressure variation compared to the number of other factors to low, so the integration of this factor to the error vector for a second analysis of variance. table 7 shows d factor for the ent ire injection mold ing mold temperature have a significant impact, accounting for 62.1% of the overall experiment, followed by c packing time and a. injection pressure. in table 5 choose the best combination a3b2c3d1 for mold flow analysis again to verify that the best combination of parameters, the optimum amount of warpage results about 0.0549 mm are shown in table 8. fig. 3 shows the simulation of best combination a3b2c3d1. table 7 the second analysis of variance factor ss dof var. f-ratio confi dence ρ% a 0.117 2 0.0586 2.68 72.81% 1.09 b pooled c 3.882 2 1.9413 88.69 99.99% 36.4 d 6.623 2 3.3119 151.3 99.99% 62.1 error 0.043 2 0.0218 *at least 99% confidence total 10.66 8 table 8 best combination of parameters a b c d warpage combination 120 mpa 75 mpa 11 sec 80 ℃ 0.0549 fig. 3 simulation of combination a3b2c3d1 3. conclusions the paper used taguchi quality engineering method to decide injection molding optimized combination factors. the results have shown that: (1) the best factor level combination a3b2c3d1, inject ion pressure 120mpa, packing pressure 75mpa, packing time 11sec, mold temperature 80 ℃; (2) the entire injection molding mold temperature have a significant impact, accounting for 62.1% of the overall experiment; and (3) the optimum amount of advances in technology innovation, vol. 1, no. 2, 2016, pp. 46 49 49 copyright © taeti warpage results about 0.0549 mm. references [1] s. kamaruddin, “application of taguchi method in the optimization of inject ion mould ing parameters for manufacturing products from plastic blend,” international journal of engineering & technology, vol. 2, no. 6, dec. 2010. [2] n. a. shuaib, “warpage factors effectiveness of a thin shallow injection-molded part using taguchi method,” international journal of engineering & technology ijet-ijens, vol. 11, no. 1, feb. 2011. [3] h. radhwan, m. t. mustaffa, a. f. annuar, h. azmi, and m. z. zakaria, “an optimization of shrinkage in injection molding parts by using taguchi method,” journal of advanced research in applied mechanics, vol. 10, no. 1, pp. 1-8, 2015. [4] s. m. nasir, k. a. is mail, z. shayfull, and n. a. shuaib, “comparison between single and multi gates for min imization of warpage using taguchi method in injection mold ing process for abs material,” key engineering materials, vol. 594-595, pp. 842-851, 2013. [5] s. opasanon and p. lertsanti, “impact analysis of logistics facility relocation using the analytic hierarchy process (ahp),” international transactions in operational research, pp. 325–339, 2013. [6] s. h. kil, k. l. dong, j. h. kim, m. h. li, and g. neman “utilizing the analytic hierarchy process to establish weighted values for evaluating the stability of slope revegetation based on hydroseeding applications in south korea,” sustainability, vol. 8, p. 58, 2016.  advances in technology innovation, vol. 1, no. 2, 2016, pp. 41 45 41 copyright © taeti experimental investigation into mechanical properties of nanomaterial-reinforced table tennis rubber yu-fen chen1,*, jian-hong wu2, chen-chih huang 3 1 office of physical education, national formosa university, yunlin, taiwan. 2 taiwan semiconductor manufacturing company limited, hsinchu, taiwan. 3 department of sport, health & leisure, wufeng university, chiayi county, taiwan . received 02 february 2016; received in revised form 28 march 2016; accepted 02 april 2016 abstract a new table tennis rubber is prepared consisting of carbon nanotubes, zinc oxide and titanium oxide added to a mixture of natural and synthesized rubber. the nano-reinforced rubber is attached to wooden table tennis blades and patterned with four different surface structures, namely flat, long pimples, short pimples and medium pimples. the results show that of the five rubbers, the nano-reinforced rubber with a flat surface offers a significantly improved elastic and mechanical performance. keywords: table tennis rubber, surface modification, carbon nanotube, zinc oxide, titanium oxide 1. introduction polymer compound materials have many advantages over traditional engineering metals and alloys, including a high strength, a low weight, good resilience, a low cost, and superior chemical resistance. consequently, the synthesis and characterization of polymer composites has attracted significant attention in the literature [1-3]. furthermore, with the advancement of nanotechnology, nanometer-scale materials are now used widely throughout the text iles, biomedical, agricultural, industrial, electronics and energy generation fields. many studies have shown that nanoparticle addition provides an effective means of altering the mechanical properties of compound materials, thereby improving the performance of existing products or paving the way for the development of new ones [4-5]. polymer compound materials have found extensive use in the sports equipment field. for example, the rackets used by table tennis players were orig inally made simply o f wood, and hence games were played at slow speed with a lack of spin. in the 1920s, however, european manufacturers attached a rubber skin to the bat; thereby enabling players to strike the ball with a far greater velocity and to exert a higher degree of control over the ball trajectory [6-7]. in later years, japanese manufacturers replaced the rubber skin with innovative polymer compound materials; lead ing to a further significant improvement in p layer performance [8-10]. the literature contains many investigat ions into polymer compound materials and rubber modificat ion. however, the modification o f polymer composite materials fo r sporting applicat ions has thus far attracted relat ively little attention. accord ingly , the present study develops a new rubber material for table tennis rackets consisting of a mixture of carbon nanotubes (cnts), zinc oxide (zno) and titanium oxide (tio2) added to natural and synthesized rubber. the nano-reinforced rubber is attached to wooden table tennis paddles and patterned with four different surface structures, namely flat , long pimples, short pimples and medium pimples. the restitut ion coefficient and mechanical properties (y ield stress, elastic modulus and shear modulus) o f the four nano-reinforced rubbers are then investigated and compared with those of a flat non-reinforced rubber skin. * corresponding author, email: yvonne@nfu.edu.tw advances in technology innovation, vol. 1, no. 2, 2016, pp. 41 45 42 copyright © taeti 2. experimental process 0.035 g cnts, 0.105 g tio2 and 0.175 g zno were added to a 35-g mixture of natural and synthesized rubber. the nano-reinforced rubber was glued to wooden table tennis blades and patterned with four different surface structures, namely flat, short pimples, long pimples and medium pimples, as shown in figs. 1(a)~(d), respectively. (a) flat (b) short pimples (c) long pimples (d) medium pimples fig. 1 the different surface structures of nano reinforced rubber 2.1. restitution coefficient the restitution coefficients of the nano-rein forced rubber skins were evaluated in a wind-less environment using the experimental setup shown in fig. 2. in each test, a table tennis ball was placed at a height of 300 mm above the racket and was then dropped vertically onto the racket surface. the rebound height of the ball was recorded using a high-speed camera and the restitution coefficient of the rubber was then computed as height drop height rebound e . for each rubber, the restitution coefficient was calculated in three separate tests and then averaged to obtain a final representative value. fig. 2 experimental setup used for restitution coefficient testing 2.2. mechanical properties the mechanical properties of the nano-rein forced rubber skins were evaluated using the material testing system (mts 810) shown in fig. 3. test specimens with dimensions of 150 mm x 3 mm x 1 mm (length x width x th ickness) were p repared . each specimen was extended at a constant rate of 10 -1 s -1 until the point of fracture. the load and d isp lacement values were meas ured continuously during the test, and were then used to compute the elastic modulus and shear modulus of the rubber in accordance with basic engineering theory. the mts system comprised three components, namely: power unit: a hydraulic power system used to actuate the system. load unit: a stand-alone testing unit consisting of a load frame, crosshead lifts and locks, actuators, servo-valves, transducers and grip controls. advances in technology innovation, vol. 1, no. 2, 2016, pp. 41 45 43 copyright © taeti control unit: a control system used to coordinate and control the power unit and load unit. fig. 3 mts system used for mechanical p roperty testing 3. results and discussion 3.1. restitution coefficient fig. 4 shows the restitution coefficients of the four nano-reinforced rubbers. as expected, the restitution coefficient has a value of less than 1 for all five skins; indicating a non-fully -elastic collision between the ball and the racket. notably, the nano-reinforced rubbers all yield a slightly higher reinstitution coefficient than the non-reinforced skin. in other words, all four rubbers have a higher elasticity than the original skin. the performance improvement is particularly apparent for the three reinforced rubbers with pimples-out surface patterns. fig. 4 restitution coefficients of nano reinforced rubbers and non-reinforced rubber 3.2. stress-bearing capability fig. 5 shows the yield stress values of the nano-rein forced and non-reinforced rubbers. (note that the stress values indicate the maximum stress recorded in the tensile tests, i.e., the stress at which specimen failure occurred.) as shown, the flat nano-reinforced rubber has a maximum stress of approximately 8.03 mpa. by contrast, the non-reinforced rubber has a maximum stress of around 7.04mpa. in other words, the reinforced rubber has an improved stress-bearing capability, and thus provides a better wear resistance. notably, however, the pimples-out rubbers all have a lower stress-bearing capability than the non-reinforced rubber. the loss in strength is particularly apparent in the rubber with a long-pimple structure. fig. 5 stress-bearing capabilities of nano reinforced rubbers and non-reinforced rubber 3.3. elastic modulus for each rubber, the elastic modulus was computed as ε = slope = ∆𝜎 ∆𝜖 = (𝜎2− 𝜎1) (𝜖2 𝜖1⁄ )⁄⁄ . the corresponding results are shown in fig. 6. it is seen that the flat nano-reinforced rubber has an elastic modulus of approximately 1.8. for the non-reinforced flat rubber, the elastic modulus is equal to approximately 1.09. in other words, the addition of cnts, zno and tio2 is beneficial in improving the stiffness of the rubber skin. however, the use of a pimples -out surface pattern greatly reduces the rubber stiffness. for example, the nano-reinforced rubber with a long-pimple structure has an elastic modulus of just 0.13, i.e., around 8 times lower than that of the non-reinforced flat rubber skin. advances in technology innovation, vol. 1, no. 2, 2016, pp. 41 45 44 copyright © taeti fig. 6 elastic modulus values of nano-reinforced rubbers and non-reinforced rubber 3.4. shear modulus for each rubber, the shear modulus was computed as g=e/2(1+v), where v is the poisson ratio (the values of the poisson ratio for the present rubbers is 0.45). as shown in fig. 7, the shear modulus of the flat nano-reinforced rubber (0.6) is around 50% higher than that of the flat non-reinforced rubber (0.4). in other words, the reinforced rubber has a significantly improved shear resistance. however, for all the pimples-out rubbers, the shear modulus is lower than that of the non-reinforced rubber. consequently, these skins are more prone to shear damage, and therefore fail at a lower maximum stress (see fig. 4). fig. 7 shear modulus values of nanoreinforced rubbers and non-reinforced rubber 4. conclusions this study has synthesized a new table tennis rubber consisting of natural and synthesized rubber reinforced with a mixture of carbon nanotubes (cnts), zinc oxide (zno) and titanium oxide (tio2). reinforced rubber skins have been attached to wooden table tennis paddles and patterned with four different surface structures, namely flat, long-pimple, short-pimple and medium-pimple. the restitution performance and mechanical properties of the various rubbers have been evaluated and compared with those of a flat non-reinforced rubber skin. the experimental results have shown that the flat nano-rein forced rubber outperforms the non-reinforced rubber in terms of a higher restitution coefficient, a superior stress -bearing capability, and an improved stiffness. as a result, it provides several important practical advantages over the non-reinforced rubber, including a superior elasticity and an improved wear resistance (i.e., a longer service life). the pimples-out reinforced rubbers provide a slightly higher elasticity than either of the two flat rubbers. however, the elasticity improvement is obtained at the expense of significantly lower mechanical properties. as a result, the pimple-based coatings are less practical for real-world table tennis applications. acknowledgement the authors gratefully acknowledge the experimental assistance provided to this study by professor s.c. lin of the department of power mechanical engineering at nat ional formosa university, taiwan. furthermore, the preparation of the rubbers used in the present study by training co. ltd, taiwan, is also greatly appreciated. references [1] n. r. park, i. y. ko, j. m. doh, w. y. kong, j. k. yoon, and i.j. shon, “rapid consolidation of nanocrystalline 3ni-al2o3 composite from mechanically synthesized powders by high freguency inductiion sintering,” materials characterization, vol. 61, no. 3, pp. 227-282, march 2010. [2] r. ritasalo, x. w. liu, o. soderberg . a . kes ki-honkola, v. pitkanen , “the microst ructural effects on the mechanical and thermal p ropert ies o f pu lsed elect ric curren t. s intered cu -al2 o3 compos ites,” proced ia engineering, vo l. 10, pp . 124-129, 2011. [3] g. z. zhao, l. s. d. s. zhang, x. feng, s. yuan, and j. zhou, “synergistic effect of nanobarite and carbon black fillers in natural rubber matrix,” materials and design, vol. 35, pp. 847-853, march 2012. advances in technology innovation, vol. 1, no. 2, 2016, pp. 41 45 45 copyright © taeti [4] m. jayalakshmi, n. venugopal, k. phan i raja, and m. mohan rao, “nano sno2 al2o3 mixed oxide and sno2al2 o3-carbon composite oxides as new and novel electrodes fo r supercapacitor app lications,” journal of power sources , vo l. 158, pp. 1538-1543, august 2006. [5] c. l. arqu imedes, v. c. adilon, j. r. isaias, m. lilia, b. carrillo, and z. m. elv ira , “synthesis of γ-al2o3 nanopowder by the sol-gel method: effect o f different acid p recursors on the superficial, morpholog ical and structural p ropert ies,” journal of ceramic processing research , vol. 9, no. 5, pp. 474-477, 2008. [6] x. p. zhang and h. wu, “an experimental investigation into the in fluence of the speed and spin by ball of different diameters and weight,” science and racket sports, london, pp. 206-208, 1998. [7] y. féry and l. crognier, “on the tact ical significance of game situations in anticipating ball trajecto ries in tennis,” research quarterly for exercise and sport, vol. 72, no. 2, 2001. [8] m. dicks, k. davids, and c. button, “representative task designs for the study of perception and action in sport. international journal of sport psychology,” vol. 40, no. 4, pp. 506-524, 2009. [9] r. a . pinder, i. renshaw, k. davids, and h. kerherve, “princip les for the use of ball project ion machines in elite and developmental sport programs ,” sports medicine, vol. 41, no. 10, pp. 793, 2011. [10] g. tenenbaum, t. sar-el, and m. bar-eli, “anticipat ion of ball locat ion in low and high-skill performers : a developmental perspective,” psychology of sport and exercise, vo l. 1, no. 2, pp. 117-128, october 2000.  advances in technology innovation, vol. 2, no. 2, 2017, pp. 29 33 29 investigation of a ball screw feed drive system based on dynamic modeling for motion control yi-cheng huang*, xiang-yuan chen department of mechatronics engineering, national changhua university of education, changhua, taiwan. received 01 february 2016; received in revised form 28 april 2016; accepted 02 may 2016 abstract this paper examines the frequency response relationship between the ball screw nut preload, ball screw torsional stiffness variations and table mass effect for a single-axis feed drive system. identificat ion for the frequency response of an industrial ball screw drive system is very important for the precision motion when the vibration modes of the system are critical for controller design. in this study, there is translation and rotation modes of a ball screw feed drive system when positioning table is actuated by a servo motor. a lumped dynamic model to study the ball nut preload variation and torsional stiffness of the ball screw drive system is derived first. the mathematical modeling and numerical simulat ion provide the informat ion of peak frequency response as the different levels of ball nut preload, ball screw torsional stiffness and table mass. the trend of increasing preload will indicate the abrupt peak change in frequency response spectrum analysis in some mode shapes. this study provides an approach to investigate the dynamic frequency response of a ball screw drive system, which provides significant information fo r better control performance when precise motion control is concerned. keywords: ball nut preload, ball screw drive system, dynamic modeling 1. introduction precision computer numerical control (cnc) machines are widely used in modern industry for mass production. the ball screws are widely applied in the linear actuators of machinery and equipment because of the high efficiency, less backlash, easy lubrication, and easy maintenance. since ball screw play a significant role in converting rotary motion into linear mot ion preloading is effective to eliminate backlash and increase the stiffness of ball screw for precision motion concerns. the dynamic frequency responses of the feed drive system depends on the stiffness combinations of the ball screw, ball nut, fixed support bearings, the flexible coupler and the stiffness between the ball screw and the working table. such frequency response results from the axial mode shapes and torsional mode shape of the ball screw drive system when it is actuated by servo motor. each mode shape affects and determines the motion control frequency response bandwidth when the control speed is limited and becomes a critical issue. the working table mass and the bolt stiffness between the machine bed base and attached ground floor also plays an important role for the frequency response when the vibration mode of the cnc machine is concerned with precision accuracy. as in intelligent control field, the control signals that fed into the controlled plant are based on the feedback control error that should be learnable. therefore, some control efforts [1-2] are focused the design of the bandwidth of the filter that can filter out the un-learnable errors contents and can be get back to control system for bettering control h istory. since the bandwidth of controlled system determines the motion speed response and its performance. the lumped dynamic model derivation is significant in determin ing the bandwidth for motion control law that can be used for controller design. since such frequency contents of compensated error are suggested to be within the bandwidth when control signals are actuating. th is paper will derive the dynamic model of the ball screw feed drive system first and examine the relationship between the ball screw preload variation, ball screw torsional stiffness and effect of table mass. * corresponding author, email: ychuang@cc.ncue.edu.tw advances in technology innovation, vol. 2, no. 2, 2017, pp. 29 33 30 copyright © taeti simulation results will unveil the frequency response of the translational and torsional peak modes. numerical simulat ion shows stable convergence by using hybrid particle swarm optimization of iterative learning control [2] on this developed ball screw drive system. 2. mathematical model and numerical simulation 2.1. dynamic model of the ball screw drive system to model the feed drive system, th is paper set differnt stiffness of the ball nut stiffness for different preload between the ball screw shaft and the ball nut. the presetting preload value can be deployed by inserting different ball size for single ball nut design or using disk spring that applied to the ball screw when double ball nut is the preference. fig. 1 shows the picture of the in-lab single-axis feed drive p latform. to analyze the dynamic characteristic of the ball screw system under different preload and varying table mass, the feed drive system is modeled by a lumped parameter system shown in fig. 2. fig. 2 is the schematic illustration for the single-axis ball screw feed drive system. in general, mechanical systems have three passive linear components. the spring and the mass are energy-storage elements, while the viscous damper is the dissipated energy. both of the rotational and translation mechanical system modeled below are actuated by the servo motor torque, indicated as t. as the same derivation in [3], the overall stiffness of a ball screw feed drive system can be determined by the stiffness of the ball screw itself, which is comprised of the ball screw shaft, the ball nut, supporting bearings of the ball screw, and the stiffness between the ball screw and the working table. )( t bm gkmmqmmj      (1) 𝐽𝑏 × �̈�𝑚 + 𝑄𝑚 × �̇�𝑏 + 𝑅 × [𝐾𝑛 × (𝑅 × 𝜃𝑏 + 𝑋𝑏 − 𝑋𝑡 )] = 𝐾𝑔 × (𝜃𝑚 − 𝜃𝑏 ) (2) 𝑀𝑏 × �̈�𝑏 + 𝐵𝑏 × (�̇�𝑏 − 0) + 𝐾𝑒 × (𝑋𝑏 − 0) + 𝐾𝑛 × (𝑅 × 𝜃𝑏 + 𝑋𝑏 − 𝑋𝑡 ) = 0 (3) tx b x b rnk txtbtxtm )( )0(     (4) rearranging eqs (1)-(4), we have [ 𝑀𝑡 0 0 0 0 𝑀𝑏 0 0 0 0 𝐽𝑏 0 0 0 0 𝐽𝑚 ] × [ �̈�𝑡 �̈�𝑏 �̈�𝑏 �̈�𝑚] + [ 𝐵𝑡 0 0 0 0 𝐵𝑏 0 0 0 0 𝑄𝑏 0 0 0 0 𝑄𝑚 ] × [ �̇�𝑡 �̇�𝑏 �̇�𝑏 �̇�𝑚] + [ 𝐾𝑛 −𝐾𝑛 −𝐾𝑛𝑅 0 −𝐾𝑛 𝐾𝑒 + 𝐾𝑛 𝐾𝑛𝑅 0 −𝐾𝑛𝑅 𝐾𝑛𝑅 𝐾𝑔 +𝐾𝑛𝑅2 −𝐾𝑔 0 0 −𝐾𝑔 𝐾𝑔 ] × [ 𝑋𝑡 𝑋𝑏 𝜃𝑏 𝜃𝑚 ] = [ 0 0 0 𝑇 ] (5) where the stiffness matrix is different from [3]. fig. 1 the in-house single axis platform fig. 2 illustration for the schematic d iagram of the single-axis lumped parameters ball screw drive system advances in technology innovation, vol. 2, no. 2, 2017, pp. 29 33 31 copyright © taeti 2.2. numerical simulation table 1 list the simulated parameters and associated values used in eqs (1)-(4). the dynamic equation of the single-axis feed drive system model with varied p reload and table mass can be expressed in a compact form: [𝑀]{�̈�} + [𝐶]{�̇�} + [𝐾]{𝑢} = 𝑓 (6) where [m], [c], and [k] are the 4x4 square matrices, referred as the mass (or the moment of inertia), the viscous damping, and the stiffness matrices, respectively. {u} represents a four degree of freedom model. it consists with the xt , xb , θb , and θm for the displacement of the working table, axial displacement of the ball screw, rotation angle of the ball screw, and the rotation angle of the motor, respectively. table 1 important parameters of ball screw drive system parameters value working table mass (mt) 47.09kg ball screw mass (mb) 9kg inertia moment of the motor (jm) 4.45× 10−4kgm2 inertia moment of the ball screw (jb) 1.3× 10−3kgm2 equivalent axial stiffness of ball screw shaft (ke) 1.8663× 107n/m stiffness of the ball nut (kn) 2.3345× 108n/m torsional stiffness of the ball screw (kg) 3.49× 108n/m viscous damping coefficient of the guide way of the working table (bt) 10n s/m viscous damping coefficient of the supporting bearing of the ball screw (bb) 10n s/m rotational viscous damping coefficient of the motor (qm) 0n ms rotational viscous damping coefficient of the support bearing of ball screw (qb) 0n ms angle conversion axial displacement of the constant (r) 0.0025 motor torque (t) 1.8× 10−3nm/𝑠2 displacement of the working table (xt) state variable (m) axial displacement of the ball screw (xb) state variable (m) rotation angle of the motor (θm) state variable (rad) rotation angle of the ball screw (θb) state variable (rad) the homogeneous solution of eqs (5) represents the transient response of the lumped system whereas the forcing function of applied motor torque renders the table positioning. homogeneous solution of the equation (2.1.5) results in four eigenvectors v1, v2, v3, and v4 associated with each eigenvalue ( λ = ω2 ) of 3.2124 × 104 , 3.3322 × 106 , 1.0699 × 1011 ,3.421 × 107(rad2/s2). v1={ −0.7299 −0.6836 0 0 }v2={ 0.1762 −0.9844 0 0 } v3 ={ 0 0 0.9482 −0.3176 }v4={ 0 0 0.7067 0.7076 } (7) the four eigenvectors corresponding to the eigen frequencies of 28.52 hz, 290.52 hz, 52059 hz, 930.9 hz w is calculated by 2% of the rated dynamic load. these eigenvectors represent the mode shapes of the ball screw feed drive system. the first three significant eigen frequencies are related to the three resonant frequencies. the first and second modes are from the axial vibration. the third mode is from the torsional vibration. in eqs (7), the first mode of the working table and the ball screw is moving in phase while the second mode is moving out of phase. fig. 3 shows the bode plot of the dynamic system based on different kn values. the preload variation is simulated from 2%, 4%, 6%, 8% to 10% of the rated dynamic loading of the ball screw. fig. 3 bode plot of the ball screw drive system based on the preload value of 2%(blue), 4%(green), 6%(red), 8%(cyan) and 10%(purple) of the rated dynamic loading advances in technology innovation, vol. 2, no. 2, 2017, pp. 29 33 32 copyright © taeti enlargement of the first, second and third modes of the bode plot, the three frequencies are ranging from 30.5 hz to 30.8 hz, 294 hz to 380 hz and 52000 hz to 55000 hz respectively. it is obvious that the second translational mode will be affected more than the first mode when the ball nut preload is vary ing. the solution of the fourth mode is about 930 hz, the contribution of this mode is not significant even though the preload is varied. fig. 4 the enlargement of the first mode of the bode plot in fig. 3 based on different ball nut stiffness fig. 5 the enlargement o f the second mode of the bode plot in fig. 3 based on different ball but stiffness fig. 6 the en largement of the third mode of bode plot in fig. 3 based on different ball nut stiffness as stated, the third eigenvector indicates the torsional vibration. since the servo motor drives the ball screw through a coupler providing damping and stiffness. the torsional stiffness of the ball screw is investigated by calculating kg by πdr 4g/32l . fig. 7 shows the variations of kg in the range of ± 10%. as shown, the third mode demonstrates large frequency shift with increasing the torsional stiffness of the ball screw. fig. 8 indicates the frequency shift is range from 50700 hz to 58000 hz, while the first and second modes are not changed noticeably. fig. 7 bode plot of the ball screw torsional stiffness 100%( blue), 105%(green), 110%(red), 95%(cyan), 90%( purple) fig. 8 the enlargement of the torsional mode of the bode plot in fig. 7 based on different ball screw torsional stiffness figs. 9-11 detail the effect of the table mass. the characteristic frequency shifts from the 24hz to 30.5hz when the table mass increases from 47.09 kg to 94.18 kg. as predicted, the table mass preserves the effect on the first bandwidth in the translational mode and some effect on the second mode. increasing table mass does not affect the bandwidth of the third torsional mode. fig. 12 shows the numerical simulation plot of the convergence error when the ball screw drive system is controlled by hybrid particle swarm optimization for the dynamic bandwidth tuning of an iterative learning control. advances in technology innovation, vol. 2, no. 2, 2017, pp. 29 33 33 copyright © taeti fig. 9 bode plot of the working table mass 47.09kg(blue), 70.63kg(green), 94.18kg(red) fig. 10 the en largement of the first mode of the bode plot in fig. 9 based on different working table mass fig. 11 the enlargement of the second mode of the bode plot in fig. 9 based on different working table mass fig. 12 plot of a convergence error of the numerical s imulat ion by using hpso-ilc [2] for ball screw drive system 3. conclusions a lumped dynamic model fo r describing different ball nut preload level, ball screw torsional stiffnesss and the table mass effects of the ball screw feed drive system is derived and numerically simulated. based on the different percent of the preload and table mass, the frequency spectrum analysis of the numerical simulation provides the limits and constraints of bandwidth tuning for motion control applications. the preload variation can be diagnosed by the peak frequency change and the magnitude of the peak frequency in a specific frequency range when the axial mode or the torsional mode is excited. the derivation and numerical simulation results of the lumped dynamic model provides significant informat ion in determining the zero phase bandwidth tuning. application of a hybrid particle swarm optimization iterat ive learning control law deploys successfully when the frequency contents of the compensated error was constrained in every control actuation. acknowledgement this work was supported by most grant 104-2221-e-018-015 for which the authors are very much grateful. references [1] m. s. tsai, c. l. yen, and h. t. yau, “integration of an empirical mode decomposition algorithm with iterative learn ing control for h igh-precision machining,” ieee/asme transaction on mechatronic, vol. 18, no. 3, pp. 878-886, 2013. [2] y. c. huang, y. w. su, and p. c. chuo, “iterative learn ing control bandwidth tuning using the part icle s warm opt imizat ion techn ique fo r h igh p recis ion mot ion,” microsystem technologies. doi: 10.1007/ s00542-015-2649-6, 2015. [3] g. h. feng and y. l. pan, “investigation of ball screw preload variation based on dynamic modeling of a preload adjustable feed-drive system and spectrum analysis of ball-nuts sensed v ib rat ion s ignals,” international journal of machine tools & manufacture, vol. 52, no. 1, pp. 85-96, 2012.  advances in technology innovation, vol. 2, no. 4, 2017, pp. 126 129 126 high-temperature corrosion of t22 steel in n2/h2s-mixed gas min jung kim, dong bok lee* school of advanced materials science and engineering, sungkyunkwan university, suwon 16419, south korea. received 06 october 2016; received in revised form 29 december 2016; accepted 16 january 2017 abstract astm t22 steel (fe-2.25cr-1mo in wt.%) was corroded at 600 and 700 o c for 5-70 h under an atmospheric pressure that consisted of n2-(0.5. 2.5)%h2s-mixed gas. t22 steel corroded rapidly, forming outer fes scales and inner (fes, fecr2o4)-mixed scale. the formation of the outer fes scale facilitated the oxidation of cr to fecr2o4 in the inner scales. since the nonprotective fes scale was present over the whole scale, t22 steel displayed poor corrosion resistance. keywords : fe-cr-mo alloy, t22 steel, corrosion, h2s gas, sulfidation 1. introduction the integrated gasification combined cycle (igcc) power plants are operating in u.s., japan, germany, and netherlands. it is a new technology that turns coal into synthesis gas (syngas) and produces the electricity. it promises low emissions and improved efficiency compared to conventional coal-fired power plants that produce the electricity directly by burning coals [1]. however, one of the main problems in igcc is the corrosion occurring by the syngas in a gasification unit, because the syngas consisted primarily of the extremely corrosive h2s gas. this limits the operating temperature and the process efficiency of the igcc power plants. it is noted that the h2s gas has been a major concern in oil refinery plants, high-temperature gas turbines, and petrochemical units. h2s gas dissociates into sulfur and hydrogen ions, and reacts with the steel according to the reaction; h2s+fe → fes+h2 [2-4]. generally, most sulphides are highly nonstoichiometric, and ionic diffusion in the scales is hence quite fast [5,6]. sulfidation is therefore a quite serious problem. hydrogen also significantly decreases the corrosion resistance and mechanical properties of the steel [7-10]. in this study, t22 steel was corroded at 600 and 700 oc for up to 70 h in n2-(0.5, 2.5)%h2s-mixed gas in order to understand its corrosion behavior in the h2s-mixed gas. this is important in igcc power plants, oil refinery plants, high-temperature gas turbines, and petrochemical units. although the oxidation behavior of t22 steel was extensively studied [11-12], little is reported about the high-temperature corrosion behavior of t22 steel in h2s-mixed gas. the purpose of this study is to investigate the corrosion behavior of t22 steel in n2/h2s-mixed gas. 2. method t22 steel plate with a nominal composition of fe-2.25cr-1.0mo-0.45mn-0.3si-0.12c in wt% were cut into a size of 2x10x15 mm 3 , ground up to a 1000-grit finish with sic paper, ultrasonically cleaned in acetone, corroded, and inspected to examine its corrosion behavior. each sample was suspended by a pt wire in a quartz reaction tube positioned vertically inside the hot zone of the vertical electrical furnace, and corroded at 600 and 700 o c for up to 70 h in n2-(0.5, 2.5)%h2s-mixed gas maintained at 1 atm. the employed n2 gas was 99.999% pure, and h2s gas was 99.5% pure. the corroded samples were characterized by a scanning electron microscope (sem; jeol jem-2100f operated at 200 kev), an x-ray diffractometer (xrd) with cu-kα radiation operating at 40 kv and 300 ma in θ/2θ configuration, and an electron probe microanalyzer (epma). 3. results and discussion the corrosion kinetics of t22 steel in n2-(0.5, 2.5)%h2s gas are depicted in fig. 1. weight gains were the sum of weight gain due to scaling and weight loss due to scale spallation. they increased with an increase in the temperature and the h2s concentration. the fastest corrosion rate was observed in the sample corroded at 700 o c in n2-2.5%h2s-mixed gas. the almost linear, large weight gains depicted in fig. 1 indicate vastly fast corrosion kinetics for all the samples. it is noted that local cracking, partial spallation and void formation in the formed scales were unavoidable for all the samples, including at 600 o c in n2-2.5%h2s-mixed gas for 70 h. such scale failure became more serious as corrosion progressed. although t22 steel displayed reasonable oxidation resistance in the oxidizing atmospheres, it was non-protective in the harsh h2s-mixed corrosion environment. fig. 1 weight gains of t22 steel at 600 and 700 o c in n2-(0.5, 2.5)%h2s-mixed gas fig. 2(a) indicates that t22 steel consisted mainly of α-fe. the other minor phase, perlite, was not detected fig. 2(a) due to its small amount. in this study, the corrosion at 600 and 700 o c for 5-70 h in n2-(0.5, 2.5) %h2s-mixed gas inevitably led to the formation of the outer fes scale and the inner (fes, fecr2o4)-mixed scale. fig. 2(b) indicates the outer fes scale that formed after corrosion at 700 o c for 20 h in n2-2.5%h2s gas. the outer, non-adherent fes scale was detached off by slightly hitting the sample, and the inner scale was x-rayed as shown in fig. 2(c). this revealed the inner (fes, * corresponding author. email: dlee@skku.ac.kr http://en.wikipedia.org/wiki/coal http://en.wikipedia.org/wiki/syngas http://en.wikipedia.org/wiki/syngas http://en.wikipedia.org/wiki/gasification advances in technology innovation, vol. 2, no. 4, 2017, pp. 126 129 127 copyright © taeti fecr2o4)-mixed scale, along with the α-fe matrix phase. the amount of cr in t22 steel was not large enough to completely cover the matrix surface with the protective cr2o3 scale. t22 steel reacted with the h2s gas to form fes, releasing hydrogen according to the equation; fe(s) +h2s (g) → fes(s) +h2 (g). since fes has a very high concentration of cation vacancies, it grew fast to form the outer scale through the outward diffusion of fe 2+ ions [9]. the formation of fes decreased the sulfur potential, and thereby the oxygen potential underneath, facilitating the formation of the oxides in the inner scale, as shown in fig. 2(c). the minor alloying elements such as mo and mn in t22 steel tended to be expelled from the inner scale, due to their small amount or activity. the distribution of alloying elements depends on the thermodynamic stability of corresponding oxides or sulfides and activity of concerning elements. the impurity oxygen in n2-(0.5, 2.5) %h2s-mixed gas reacted with t22 steel according to eqs. (1) and (2). fe(s)+1/2 o2 (g) → feo(s), (1) 2cr(s)+3/2 o2 (g) → cr2o3(s). (2) thermodynamically, the oxides are generally more stable than the corresponding sulfides. the spinel is formed by diffusion of fe 2+ from feo to cr2o3 oxides through spinel accompanied by diffusion of hole and evolution of oxygen gas at feo/spinel interface. the fe 2+ reacts with cr2o3 to produce spinel at the spinel/cr2o3 interface, and cr 3+ d iffuses with hole to the cr2o3/gas interface in order to keep electro-neutrality [13]. the formed feo and cr2o3 oxides particles, the solid-state reaction occurred to form the more stable fecr2o4 spinel scale, which gradually dispersed in external oxide layer. fecr2o4 spinel reacted with feo and cr2o3 according to the equation. feo(s)+ cr2o3(s) → fecr2o4(s) fig. 2 xrd patterns of t22 steel. (a) before corrosion, (b) the outer scale, and (c) the inner scale that formed after corrosion at 700 o c for 20 h in n2-2.5%h2s gas the morphology of surface scales that formed on t22 steel after corrosion in n2-0.5%h2s gas is shown in fig. 3. from the early corrosion stage at 600 o c, fes platelets progressively protruded through the ensuing outward diffusion of fe 2+ ions over the smooth underlying scale (figs. 3(a) and (b)). they spalled off easily due to their fast growth rate and incorporation of hydrogen released from the h2s gas. the formed scales were quite fragile so that cracks were seen in fig. 3(a). at 700 o c, the fes platelets grew to coarse, protruded fes grains, as shown in fig. 3(c). as corrosion progressed, fes grains grew bigger, leading to the generation of cracks in the surface fes scale (fig. 3(d)). the eds analysis indicated that the outer scale and the inner scale consisted primarily of fes (figs. 3(e) and (f)), respectively. fig. 3 sem top view of the scales that formed on t22 steel after corrosion in n2-0.5%h2s gas. (a) at 600 o c for 5 h, (b ) at 600 o c for 40 h, (c) at 700 o c for 5 h, (d) at 700 o c for 40 h, (e) eds spectrum of spot ①, (f) eds spectrum of ② the morphology of surface scales that formed on t22 steel after corrosion in n2-2.5%h2s gas is shown in fig. 4. from the early corrosion stage at 600 o c, coarse, facetted fes grains covered the whole surface (fig. 4(a)). they continuously grew bigger as the corrosion progressed (figs. 4(b)-(d)). in fig. 4(d), cracks propagated interand trans-granularly. with the increase of concentration of the h2s gas from 0.5 to 2.5 %, the grains at the surface of the scale became much coarser as shown in figs. 3 and 4, indicating that the h2s gas accelerated corrosion. advances in technology innovation, vol. 2, no. 4, 2017, pp. 126 129 128 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti fig. 4 sem top view of the scales that formed on t22 steel after corrosion in n2-2.5%h2s gas. (a) at 600 o c for 5 h, (b ) at 600 o c for 40 h, (c) at 700 o c for 5 h, (d) at 700 o c for 40 h. fig. 5 shows sem/eds analytical results of t22 steel after corrosion in n2-0.5%h2s gas at 600 o c for 70 h. the scale consisted of about 120 μm-thick outer scale, and about 70 μm-thick inner scale. the outer scale was detached from the inner scale, and vertical cracks were seen in the inner scale, owing to the large stress arisen by (1) the mis match in the thermal expansion coefficients among the outer scale, inner scale, and the matrix, (2) the difference in the growth rates of various oxides and sulfides, and (3) the hydrogen dissolution in the scale. the eds analysis indicated that the outer scale and the inner scale consisted primarily o f fes (fig. 5(b)), and (fes, fecr2o4) (fig. 5(c)), respectively. this was consistent of the xrd results depicted in fig. 2. fes platelets protruded over the outer fes scale (fig. 5(a)). fig. 5 sem/eds analytical results of t22 steel after corrosion in n2-0.5%h2s gas at 600 oc for 70 h. (a) cross-sectional image, (b) eds spectrum of spot ①, (c) eds spectrum of ②. 4. conclusions t22 steel was corroded at 600 and 700 o c for up to 70 h in n2/h2s-mixed gas under total pressure of 1 atm. the corrosion occurred almost linearly through the sulfidation, together with oxidation to a less extent. the outer scale consisted primarily of fes that formed by the outward diffusion of fe 2+ ions. the inner (fes, fecr2o4)-mixed scale formed by the inward diffusion of predominantly sulfur and a small amount of oxygen. the outer scale kept growing outwards during corrosion. the formed scales were non-adherent, and susceptible to cracking. since the nonprotective fes scale was present over the whole scale, t22 steel displayed poor corrosion resistance in n2/h2s-mixed environments at high temperatures. hence, pack-cementation, hot dipping, plasma evaporation, plating techniques were developed in order to improve its corrosion resistance. acknowledgement this research was supported by basic science research program through the national research foundation of korea (2016r1a2b1013169) funded by the ministry of education. references [1] r. a. meyers, encyclopedia of physical science and technology, 3rd ed., usa; academic press, 2001. [2] n. birks, g. h. meier, and f. s. pettit, introduction to high temperature oxidation of metals, 2nd ed., usa: cambridge university, 2006. [3] d. young, high temperature oxidation and corrosion of metals, uk: elsevier, 2008. [4] a. m. mebel, and d. y. hwang, “theoretical study of the reaction mechanism of fe atoms with h2o, h2s, o2 and h + ,” the journal of physical chemistry a, vol. 105, pp. 7460-7467, 2001. [5] s. mrowec and k. przybylski, “transport properties of sulfide scales and sulfidation of metals and alloys,” oxidation of metals, vol. 23, pp. 107-139, 1985. [6] s. mrowec, t. walec, t. werber, “high-temperature sulfur corrosion of iron-chromium alloys,” oxidation of metals, vol. 1, pp. 93-120, 1969. [7] s. mrowec and m. wedrychowska, “kinetics and mechanism of high-temperature sulfur corrosion of fe-cr-al alloys,” oxidation of metals, vol. 13, pp. 481-504, 1979. [8] t. liu, c. wang, h. shen, w. chou, n. y. iwata, and a. kimura, “the effect of cr and al concentration on the oxidation behavior of oxide dispersion strengthened ferritic alloys,” corrosion science, vol. 76, pp. 310-316, 2013. [9] m. danielewski, s. mrowec, and a. stołosa, “sulfidation of iron at high temperatures and diffusion kinetics in ferrous sulfide,” oxidation of metals, vol. 17, pp. 77-97, 1982. [10] d. b. lee, m. a. abro, p. yadav, s. h. bak, y. shi, and m. j. kim, “corrosion of fe-9%cr-1%mo steel at 600 and 700 o c in n2/(0.5, 0.25)%h2s-mixed gas,” journal of the korea institute of surface engineering, vol. 47, pp. 147-151, 2016. [11] j. purbolaksono, j. ahmad, a. khinani, a. ali, and a. z. rashid, “failure case studies of sa213-t22 steel tubes of boiler through computer simulations ,” journal http://pubs.acs.org/journal/jpcafh http://www.springerlink.com/content/?author=s.+mrowec http://www.springerlink.com/content/?author=k.+przybylski http://pubs.acs.org/journal/jpcafh http://pubs.acs.org/journal/jpcafh http://www.sciencedirect.com/science/article/pii/s0950423009000916 http://www.sciencedirect.com/science/article/pii/s0950423009000916 advances in technology innovation, vol. 2, no. 4, 2017, pp. 126 129 129 copyright © taeti of loss prevention in the process industries, vol. 23, pp. 98-105, 2010. [12] b. s. sidhu and s. prakash, “high-temperature oxidation behavior of nicra1y bond coats and stellite-6 plasma-sprayed coatings,” oxidation of metals, vol. 63, pp. 241-259, 2005. [13] k. nagata, r. nishiwaki, y. nakamura, and t. maruyama, “kinetic mechanisms of the formations of mgcr2o4 and fecr2o4 spinels from their metal oxides metals oxides,” solid state ionics, vol. 49, pp. 161-166, 1991.  advances in technology innovation, vol. 2, no. 2, 2017, pp. 46 50 46 assessment of arteriovenous shunt pathway function and hypervolemia for hemodialysis patients by using integrated rapid screening system wei-ling chen1, chia-hung lin1, chung-dann kan2,* 1 department of engineering and maintenance, kaohsiung veterans genera l hospital, kaohsiung, taiwan. 2 division of cardiovascular surgery, department of surgery, national cheng kung university hospital, college of medicine, national cheng kung university, tainan, taiwan. received 06 january 2016; received in revised form 25 march 2016; accepted 01 april 2016 abstract currently, the hemodialysis patients received body weight measurement by themselves, vital sign checking by nursing staffs before dialysis. whenever, the arteriovenous routes with problems doubted, the patients needed to be referred to surgeon for vascular echography checking and then to be corrected. how to integrate these three tasks in one time is a very important issue. the project proposes to combine our previous study of audio-phono angiographic technology in detecting vascular stenosis with rapid screening system to evaluate dialysis patients’ arteriovenous routes function and their status of excess body fluids: inspecting and integrating the blood pressure, body weight, and fistula function work into a rapid screening system, and using the quantization of fistula phono angiography pitch to achieve assessing arteriovenous routes. future hoping is developed a complete integrated intelligence system by combining the arteriovenous fistula signal processing with feature extraction with wireless sensor network technology. keywords: arteriovenous shunt, screening system, hypervolemia, dual-core embedded system 1. introduction chronic kidney disease is a global public health problem with high morbidity and mortality. treatment of end-stage renal disease (esrd) typically involves a kidney transplant or dialysis, which assists damaged kidneys in removing waste and excess fluid from the body. in taiwan, the incidence and prevalent rates of esrd were the highest in the world [1], hemodialysis is the most common choice for esrd patients. however, to perform a hemodialysis, surgeons must create pathological fistulas to provide vascular access routes for treating esrd. arteriovenous access (ava) stenosis is regarded as the primary cause of ava dysfunction in hemodialysis patients and a common occurrence in patients undergoing extended hemodialysis therapy. according to nkf-doqi guidelines [2], regular monitoring and surveillance of ava function is mandatory. basically, ava is a continuous circuit that starts and ends at the heart; it is not simply an anastomosis. moreover, clin ical assessments are based on a physical examination of ava. three physical examination steps are look, feel, and listen. clin ically, ava flow rates must reach 600–1000 ml/min for hemodialysis treatment to be considered efficient. this high-flow volume causes vibration of the vascular wall, which then transmitted to the skin surface, manifesting as a palpable thrill o r audible bruit [3]. the state of body water is an important factor in the routine hemodialysis (hd) treatment and post-dialysis healthcare. hypervolemia is a medical condition as excess body water in the blood, leading to increases in body sodium (na) content and a consequent increase in ext ra-cellular body water. when dialysis patients suffer from hypertension will increase in weight and peripheral edema in the legs and arms [4-6]. the purpose of this paper is to combine our previous study of audio-phonoangiographic technology in detecting vascular stenosis with rapid screening system to evaluate dialysis * corresponding author, email: kcd56@mail.ncku.edu.tw advances in technology innovation, vol. 2, no. 2, 2017, pp. 46 50 47 copyright © taeti fig. 1 block diagram of the rapid screening system patients’ arteriovenous routes function and their status of excess body fluids: inspecting and integrating the blood pressure, body weight, and fistula function work into a rapid screening system, and using the quant izat ion o f fistu la phonoangiography pitch to achieve assessing arteriovenous routes. the feasibility of the integrated rapid screening system will be provide an easy operational instrument for efficacious and real time monitoring arteriovenous routes (fig.1). first, the screening system employed national instruments (ni) myrio dual-core embedded microprocessor system integrated with system sensors, software, wireless/wired communications, and output display unit in developing a system which is suitable for rapid screening on hemodialysis units. second, the screening system is to use audio signal feature extraction algorithms, fuzzy algorithms, and excess body fluid assessment methods on starting begin human status checking. using vascular echography results as of the narrow criterion to establish the judgment database, and create an alert threshold as indicators of future development, therefore, to achieve the best diagnostic work. future hoping is developed a complete integrated intelligence system by combining the arteriovenous fistula signal processing with feature extraction with wireless sensor network technology. 2. method 2.1. preliminary diagnosis and classification in clinical research, the degree of narrowing of normal vessels has been used as an index for the degree of ava in patients. examination results have been used as a reference to confirm the dos according to x-ray or sono images. for the measurement segment a site-e site (fig. 2), the dos is defined as follows [7-9]. (a) the detection site (b) sono image of an abnormal blood vessel (c) spectrum of short-time fourier transform (d) spectrum of fourier transform fig. 2 sono angiography and spectrum analysis in clinical reasearch advances in technology innovation, vol. 2, no. 2, 2017, pp. 46 50 48 copyright © taeti %100)1(% 2 2  d d dos (1) %)%(% postpre dosdosdos  (2) 2.2. design of fuzzy petri nets (fpns)screening system based on fractional-order dynamic error regarding the surgical outcomes of the 42 patients, the overall pre-pta dos% was above 80%, which was regarded as the reference level, whereas the post-pta dos% was distributed across three groups (i.e., > 50%, 30%–50%,<30%). no statistical significance was observed between the groups at the a sites and v sites (p > 0.05). therefore, the correlation between dos% and index  is stronger at the v sites than at the a sites [7]. exponent regression was used to model the relationship between dos% and index  and between dos% and index . the prediction model fit a nonlinear curve passing directly through all of the experimental data, as shown in fig. 3(a). the correlation between dos and index  at the v site can be expressed as: dos% = 0.1914  exp(0.2333), r 2 = 0.3802 (3) (a) dos % versus index  at the v site (b) evaluation of the severity of ava stenosis fig. 3 evaluation of the severity of ava stenosis at the v site with dos % versus index exponential regression was used to perform a least squares curve fit, which min imized the sum of the squares of the deviations of the experimental data values extracted from the prediction model, thereby obtaining the examination criteria for the predict ion. fig. 3(b) depicts the range of pre-pta dos residuals (class i:  < 3, class ii: 3 <  < 5, and class iii:  > 5), which were used as a baseline for evaluating the post-pta dos residuals. we also compared the preand post-pta  indices monthly and determined the ideal ranges for evaluating the severity of ava stenosis in the order of class iii ( < 3), class ii (3 <  < 5), and (class i:  > 5). (1) a gaussian membership function can be parameterized by mean (mean = 0–6) and standard deviation (1 = 2 = 3 = … = r = 0.3802) by applying equation (4). ] )( exp[ 2 2 r r r mean      (4) (2) fig. 4 depicts the gaussian membership functions for the three classes. through this approach, we obtained seven membership functions r, r = 1, 2, 3, …, 7, with specific ranges denoted as r. the cf of each input in the various ranges is within the range of [0,1]. the fpn can perform fuzzy inference calculations to evaluate the dos for each proposition specified by a clinical physician. assume that for the degree of proposition cm (classes i–iii), m = 1, 2, 3, and place pm is associated with the proposition dm = m(pm), m = 1, 2, 3.. fig. 4 gaussian membership functions for the three classes of dos advances in technology innovation, vol. 2, no. 2, 2017, pp. 46 50 49 copyright © taeti 3. results and discussion 3.1 feasibility tests with the proposed screening system fig. 5(a) and (b ) show the overall test results ; compared with the dos% results, the accuracy is 85.71% with six failures. the measurement sites, quantification errors, and undetected stenosis could affect the efficiency of the proposed method. the study used at least two 8-second records from the measurement site of 21 patients (i.e ., preand post-pa). we determined three dos classes. the terms ul, l, and vl correspond to monotonically decreasing curves that define the degree of certainty. the output of function m may be an arb itrary curve that can be defined as a function that must vary between 0.3679 and 3.000. the place pm can determine the dos level, and more likely closes to value 1, 2, or 3 for the goal proposition. if p lace pm is only partially similar, its value is less than 1 and it gradually decays to 0. from these results, we determined the function of avs, which can be evaluated using the proposed diagnosis system. (a) feasibility diagnosis results for the 42 tests (b) degree of stenosis (dos) versus pm fig. 5 feasibility diagnosis results for the 42 tests, and the degree of stenosis (dos) versus pm due to variations in the frequency spectra of the various classes and differences among the patients, the characteristic frequencies occupy a range of frequency bands, with some characteristic frequencies overlapping or crossing bands. phys icians determined the final degree of certainty as a function of the variance in frequency and magnitude. however, obtaining the diagnosis results required an off-line analysis. traditional petri nets (pns) require constant transitions and weighted parameters ( and w), and they encounter difficulty in handling variance in the frequency spectra. pns were considered appropriate for processing binary data in t rue–false decisions, on–off switching, and automatic control applications [10]. comparing fpns with pns, the inference rules in the knowledge base of the rule-based system are both modeled. fpns use the cf of the fuzzy inference rules and weights of the propositions by using binary data and can automatically perform weighted fuzzy reasoning calculations for analyzing spectral variance. thus, the proposed rule-based diagnosis system can perform fuzzy inference calculat ions in a flexible and intelligent manner. 3.2. long-term examination using frequency parameter-based fuzzy petri net a 54-year-old female patient undergoing hemodialysis treatment with an avg (right forearm loop) agreed to part icipate in a long-term examination. data were collected between june 25, 2011, and july 11, 2012. in a routine monitoring cycle, monthly e xaminations were performed to evaluate avg function. over 3 months of observation, the first characteristic frequency gradually increased from 68 to 170 hz (fig. 6). on september 6, 2011, the patient presented with a severe avg occlusion, and a physician confirmed class ii stenosis. ultrasonic examination indicated a dos% of 66% at the measurement site, and the patient received pta treatment. the three characteristic frequencies were 170, 425, and 681 hz. fig. 6 long-term examination at v site from june 25, 2011, to september 6, 2011 advances in technology innovation, vol. 2, no. 2, 2017, pp. 46 50 50 copyright © taeti 4. conclusion in an embedded system development environment, we used four fundamental arithmet ic and logical-reasoning operations to configure the combinational logics or asics, and then embedded the intelligent algorithms into a compact chip. the proposed diagnosis system allows rule-based configuration and automatic weighted fuzzy reasoning calculations. flexib le and intelligent algorithms require no iteration for updating system weights. therefore, this system can handle complex configuration designs and is appropriate for the short design cycle of prototype implementation, testing, debugging, and modification. currently, graphical user interfaces of windows-based applications enable reprogramming and have flexible architectures that facilitate the rapid development of customized asics. the proposed fpn algorithm can be implemented using four fundamental operations with specific data structures. therefore, it can also be implemented with the four fundamental operations. by combining an fpn and logical operation functions, the proposed diagnosis system provides a promising means for implementing a portable monitor for avs evaluation in home care. acknowledgement this study is supported in part by the research grant of kaohsiung veterans general hospital (vghks105-070) and the ministry of science and technology, taiwan (most), under contract number: most105-2218-e-075b -001. references [1] a. j. collins et al., “usrds 2012 annual data report: atlas of chronic kidney disease and end-stage renal disease in the united states,” american j. kindeny diseases, vol. 59, pp. 342, 2012. [2] n. k. foundation, “kdoqi clinical practice guidelines and clinical practice recommendations for 2006 updates: hemodialysis adequacy, peritoneal dialysis adequacy and vascular access,” am. j. kidney dis., vol. 48, pp. 1-322, 2006. [3] f. loth, p. f. fischer, and h. s. bassiouny, “blood flow in end-to-side anastomoses,” annu. rev. fluid mech., vol. 40, pp. 367-393, 2008. [4] p. w. chamney, k. matthias, c. rode, w. kleinekofort, and v. w izemann, “a new technique for establishing dry weight in hemodialysis patients via whole body bioimpedance,” kidney international, vol. 61, pp. 2250-2258, 2002. [5] a. h. tzamaloukas, g. h. murata, d. j. vanderjagt, k. s. serv illa, and r. h. glew, “body composition evaluation in peritoneal dialysis pat ients us ing anthropo metric formulas estimat ing body water,” advances in peritoneal dialysis, vol. 19, pp. 212-216, 2003. [6] r. agarwal, “hypervolemia is associated with increased mortality among hemodialysis patients,” hypertension, vol. 56, pp. 512-517, 2010. [7] y. c. du, w. l. chen, c. h. lin, c. d. kan, and m. j. wu, “residual stenosis estimation of arteriovenous grafts using a dual channel honoangiography with fract ional-o rder features,” ieee journal of biomedical and health informat ics, vol. 18, no. 2, pp. 703-713, 2014. [8] w. l. chen, c. h. lin, t. chen, p. j. chen, and c. d. kan, “phono angiography with a fractional order chaotic system a new and easy algorithm in analyzing residual arteriovenous,” medical & biological eng & computing, vol. 51, pp. 1011-1019, 2013. [9] w. l. chen, c. h. lin, t. chen, p. j. chen, and c. d. kan, “stenosis detection using burg method with autoregressive model for hemodialysis patients,” journal of medical and biomedical engineering, vol. 33, no. 4, pp. 356-362, 2013. [10] r. s. lees and c. f. dewey, “phono angiography: a new noninvasive diagnostic method for studying arterial d isease,” proceedings of the national academy of sciences, vol. 67, no. 2, pp. 935-942, 1970.  advances in technology innovation, vol. 2, no. 3, 2016, pp. 68 72 68 spatial and spectral nonparametric linear feature extraction method for hyperspectral image classification jinn-min yang*, shih-hsuan wei department of mathematics education, national taichung university of education, taichung, taiwan. received 02 may 2016; received in revised form 21 june 2016; accepted 21 june 2016 abstract feature extraction (fe) or dimensionality reduction (dr) plays quite an important role in the field of pattern recognition. feature extraction aims to reduce the d imens ionality of the high-d imens ional dataset to enhance the classification accuracy and foster the classification speed, particularly when the training sample size is small, namely the small sample size (sss) problem. remotely sensed hyperspectral images (hsis) are often with hundreds of measured features (bands) which potentially provides more accurate and detailed information for classification, but it generally needs more samples to estimate parameters to achieve a satisfactory result. the cost of collect ing ground-t ruth o f remotely sensed hyperspectral scene can be considerably difficult and expensive. therefore, fe techniques have been an important part for hyperspectral image classification. unlike lots of feature extraction methods are based only on the spectral (band) information of the training samples, some feature extraction methods integrating both spatial and spectral information of training samples show more effective results in recent years. spatial contexture information has been proven to be useful to improve the hsi data representation and to increase classification accuracy. in this paper, we propose a spatial and spectral nonparametric linear feature extraction method for hyperspectral image classification. the spatial and spectral information is extracted for each training sample and used to design the within-class and between-class scatter matrices for constructing the feature extraction model. the experimental results on one benchmark hyperspectral image demonstrate that the proposed method obtains stable and satisfactory results than some existing spectral-based feature extraction. keywords: feature extraction, hyperspectral image, dimensionality reduction, classification, small sample size problem 1. introduction remotely sensed hyperspectral images (hsis) are often with hundreds of measured features (spectral bands) potentially provides more accurate and detailed informat ion for classification and widely used in environmental mapping, geological research, and mineral identification in recent years. the cost of collecting ground-truth of remotely sensed hyperspectral image can be considerably d if f icu lt and e xpens ive. ther efo re, f e techniques have been an important part for hyperspectral image classification. in general feature extraction (fe) or dimensionality reduction (dr) plays quite an important role in the field of pattern recognition. linear discriminant analysis (lda) [1] is one of the most well-known linear feature extraction methods and has been successfully applied to many fields. the purpose of lda is to find a linear t ransformat ion matrix that can be used to project data from a h igh-dimensional space into a low-dimensional subspace to mitigate the so-called curse of dimensionality [2], [3] or the hughes phenomenon [4], [5]. the hughes phenomenon describes that the ratio of the number of train ing samples and the number of features must be maintained at or above some minimum value to achieve statistical confidence [5]. otherwise, the classification accuracy will decline with an increase in the dimensionality of data to some extent. however, it is not necessary to have sufficient training samples to keep the ratio in a high-dimensional classification task. therefore, by featu re ext ract ion, the rat io can be relat ively en larged and the curs e o f dimensionality can therefore be improved, this will result in an enhancement of classification accuracy. meanwhile, the computational time can be reduced as well. * corresponding author, email: jinnminyang@mail.ntcu.edu.tw advances in technology innovation, vol. 2, no. 3, 2016, pp. 68 72 69 copyright © taeti bas ically , lda has th ree inherent deficiencies in dealing with classificat ion problems. first, lda is only well-suited for normally distributed data [1]. if the distributions are significantly non-normal, the use of lda cannot be expected to accurately indicate which features should be extracted to preserve complex structures needed for classification. second, since the rank of between-class scatter matrix is the number o f classes minus one [1], the number of features can be extracted at most remains the same. third, the singularity problem arises when dealing with high-dimensional and small sample size (sss) data [1, 3, 6-7]. nonparametric linear discriminant analysis such as nonparametric discriminant analysis (nda) [1], nonparametric weighted feature extract ion (nwfe) [6] and cosine-based feature extraction (cnfe) [7] provide solutions for circumventing the previously mentioned problems. the aforementioned fe methods are spectral-based algorithms; in other words, they measure similarity in the spectral space. using only spectral informat ion to classification tasks is insufficient. spatial contexture information has been proven to be useful to improve the classification of hsi data in recent years [8]-[9]. in the paper, a nonparametric feature extraction method, integrating both spectral and spatial information, is proposed. the rest of this paper is organized as follows. the proposed method and its experiment are described in section 2. the experimental results and discussion are provided in section 3. finally, section 4 gives some conclusions of the paper. 2. method the goal of fe is to find a transformation matrix a which maximizes the class separab ility in the transformed space, where and denote the within-class and between-class scatter matrices, respectively. that is (1) the maximizat ion of (1) is equivalent to solving the generalized eigenvalue decomposition problem where denotes the dimensionality of the transformed space, represent the eigen-pair of , and . thus, the transformation matrix a = [v1,… , v𝑃 ] can be obtained. the proposed spatial and spectral feature e xtraction method includes two parts, one idea is to incorporate the spatial information into the within -class and scatter matrix design, and the other idea is to incorporate another scatter matrix to regularize the within -class scatter matrix. 2.1. the nonparametric linear discriminate analysis the within-class matrix and between-class scatter matrix o f the nonparametric linear discriminant feature extract ion (nlda) are defined as follows, respectively. (2) (3) where and denote the local mean of training sample corresponding to the th class and th class, respectively. the local mean of is computed by its -nearest neighbors ( nns) in the same class or in the different classes as shown in (4). (4) 2.2. the spatial and spectral nonparametric linear discriminate analysis the within-class matrix and between-class scatter matrix o f the spatial and spectral nonparametric linear d iscriminan t featu re extraction (ssnlda) are defined as follows, respectively.             1 1 i t l s s i i i iw i n i i is x x x xp m m       (5)             1 1 1 inl l t s s i i i i i j jb i j j i s x x x xp m m         (6) where and denote the local mean of training sample corresponding to the th class and th class, respectively. the local mean of is computed by utilizing the advances in technology innovation, vol. 2, no. 3, 2016, pp. 68 72 70 copyright © taeti spectral weighted local mean and spatial weighted local mean , as shown in (7). (7) where (8) with (9) and (10) with (11) and denotes the coordinate of training sample , the parameter . another part of is the distance scatter matrix introduce in [8]. based on a window, a training sample and its pixel neighbors form a local patch , where the odd number is the width of the neighborhood window. the scatter matrix and (12) where s = 𝑧2 − 1 , and . parameter reflects the degree of filtering. regularization is employed to improve the singularity problem in ssnlda. the within-class scatter matrix is replaced by (13) where denotes the diagonal parts of a matrix and . 2.3. dataset the indian pines image, mounted from an aircraft flown at 65000-ft altitude and operated by the nasa/jet propulsion laboratory, with the size of 145 × 145 pixels has 220 spectral bands measuring approximately 20 m across the ground. we have also reduced the number of bands to 200 by removing bands covering the region of water absorption: 104-108, 150-163, and 220. there are 16 classes in the data set. the total number of samples is 10249, ranging from 20 to 2455 in each class. in figure 1, the left and right images depict the false color composition of three sample bands 50, 27 and 17 and its ground truth of the indian pines dataset, respectively. fig. 1 the left figure depicts indian pines image of band 50, 27 and 17; the right one shows its ground truth. 2.4. experiment design three different cases, each class with 5 (case i), 10 (case ii), and 20 (case iii) training samples are investigated to discover the effect on the sizes of training samples in the experiments. the remain ing samples are employed as the test samples. the cases i and ii are the so-called il l-posed and poorly pos ed class ificat ion problems [7], respectively. they are challenging cases in the field of pattern recognition. in each case, the training and testing datasets are randomly selected. we will repeat each case for 10 times and report the averaged overall accuracy (oa) and standard deviation. two other linear feature extraction methods, cnfe and nwfe, are utilized to compare the classification performance with the proposed ssnlda. the 1-nearest neighbor (1nn) classifier is employed. in ssnlda, we adopt a window to form a local patch and the values of , and  are set as 0.5. advances in technology innovation, vol. 2, no. 3, 2016, pp. 68 72 71 copyright © taeti table 1 graph representations class # pixels class name 1 46 alfalfa 2 1428 corn-notill 3 830 corn-mintill 4 237 corn 5 483 grass-pasture 6 730 grass-trees 7 28 grass-pasture-mowed 8 478 hay-windrowed 9 20 oats 10 972 soybean-notill 11 2455 soybean-mintill 12 593 soybean-clean 13 205 wheat 14 1265 woods 15 386 buildings-grass-trees-drives 16 93 stone-steel-towers 3. results and discussion table 2 lists the best classification accuracies of the three cases of the indian pines dataset. as we can see from the table, 1nn classifier with ssnlda features can achieve better results than with cnfe and nwfe features. ssnlda provides about 6% improvement as compared with the other two methods. meanwhile, the standard deviations is smaller as well. fig. 2 demonstrates the variations of oas with the reduced dimensions where 5, 10 and 20 training samples are utilized. the proposed ssnlda significantly outperform the other two methods. fig. 3 shows the classification map of the indian pines scene using 1nn classifier for 20 training samples case. the dimensionality of the reduced space is 30. as shown in fig. 3, the 1nn classifier with ssnlda feature can get better results. table 2 classification accuracies (in percent) in indian pines scene case fe oa±std (#features) nwfe 63.03±4.68(28) cnfe 65.10±4.91(15) ssnlda 71.05±3.28(28) nwfe 72.82±2.28(29) cnfe 75.67±1.77(29) ssnlda 81.79±1.81(30) nwfe 80.15±1.76(28) cnfe 81.93±2.17(28) ssnlda 88.08±1.21(30) fig. 2 classification results on the indian pines dataset for the three feature extraction method. (a) nwfe (b) cnfe (c) ssnlda (d) ground-truth fig. 3 classification maps of the indian pines scene using 1nn classifier for 20 training samples case. 4. conclusions in this paper, a spectral and spatial information-based nonparametric feature extraction ssnlda is proposed. from the above results, we find ssnlda can achieve more stable and effective results. in most of cases, 1nn classifier with ssnlda features can obtain better results than other spectral-based fe, cnfe and nlda, particularly when the training sample size is quite small. acknowledgement this study is supported by ministry of science and technology, r.o.c., under the contract number of most 104-2221-e-142005. references [1] k. fukunaga, introduction to statistical pattern recognition, 2nd ed., new york: academic press, 1990. advances in technology innovation, vol. 2, no. 3, 2016, pp. 68 72 72 copyright © taeti [2] r. o. duda, p. e. hart, and d. g. stork, pattern classification, 2nd ed., new york: john wiley & sons, 2001. [3] s. j. raudys and a. k. jain, “small sample size effects in statistical pattern recognition: recommendations for practitioners ,” ieee transaction on pattern analysis and machine intelligence, vol. 13 no. 3, pp. 252-264, 1991. [4] d. a. landgrebe, signal theory methods in multispectral remote sensing, new jersey: john wiley and sons, 2003. [5] p. k. varshney and m. k arora, advanced image processing techniques for remotely sensed hyperspectral data, new york: springer, 2004. [6] b. c. kuo and d. a. landgrebe, “nonparametric weighted feature extract ion for classification,” ieee transaction on geoscience and remote sensing, vol. 42, no. 5, pp. 1096-1105, 2004. [7] j. m. yang, p. t. yu, and b. c. kuo, “a nonparametric feature extraction and its application to nearest neighbor classification for hyperspectral image data,” ieee transactions on geoscience and remote sensing, vol. 48, no. 3, pp. 1279-1293, 2010. [8] y. zhou, j. peng, and c. l. ph ilip chen, “dimension reduction using spatial and spectral regularized local discriminant embedding for hyperspectral image classification,” ieee transactions on geoscience and remote sensing, vol. 53, no. 2, pp. 1082-1095, 2015. [9] h. pu, z. chen, b. wang, and g. m. jiang, “a novel spatial–spectral similarity measure for dimensionality reduction and classification of hyperspectral imagery,” ieee transactions on geoscience and remote sensing, vol. 52, no. 11, pp. 7008-7022, 2014. [10] hyperspectral remote sensing scenes, [online]. available: http://www.ehu.eus/ccwintco/index.php?titl e=hyperspectral_remote_sensing_scenes. [accessed 24 may 2016]  advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 international flipped class for chinese honors bachelor students in the frame of multidisciplinary fields: reliability and microelectronics olivier bonnaud1,2,3,*, yves danto3,4, yinghui kuang5, li yuan5 1 department of sensors and microelectronics, ietr, university of rennes 1, rennes, france. 2 gip-cnfm (national coordination for education in microelectronics and nanotechnologies), grenoble, france . 3 department of reliability, ims, university of bordeaux, bordeaux, france. 4 south-east university (seu), nanjing, jiangsu, china. 5 chien-shiung wu college (honors), south-east university (seu), nanjing, jiangsu, china. received 21 july 2017; received in revised form 19 september 2017; accepted 28 december 2017 abstract this paper reports an innovative pedagogic experience performed at south-east university (seu) with electrical engineering bachelor honors students (computer science, mechanics, and electronics). the purpose was to develop their motivation and to make them aware of the strategic importance of two aspects of electronic engineering i.e. integrated technologies and reliability assessment of devices and systems. the pedagogical approach was based on a flipped class and learning by project that consisted to involve the students in the two topics. after s everal lectures on the fundamentals of microelectronics and reliability of electronics components performed by foreign professors, twelve groups of five students were built. each group had to develop one topic, chosen for its strategic importance. thus, from a given set of main literature references, the students prepared during three days a twelve pages report and an oral presentation, both in english language. results were generally very good. most of the students succeeded in addressing issues that were completely new for them. they clearly built by themselves the skills allowing understanding of all the important aspects of the topics they had to approach. this paper gives details on the organization, the content and the final evaluation. keywords: pedagogical innovation, learning by project, flipped classes, microelectronics, reliability, transdisciplinary approach, international teaching 1. introduction this paper reports an innovative pedagogic experience performed at south -east university (seu) of nanjing (jiangsu, china) with engineering bachelor honors students (computer science, mechanics, bio -medical engineering and electronics). the purpose was to develop their motivation and to make them aware of the strategic importance of two aspects of electro nics engineering i.e. integrated technologies and reliability assessment of devices and systems. indeed, while electronics is driv ing most of human activities sectors, it becomes very important to highlight the major issues of advanced technologies and very high reliability levels of devices and systems. in addition, the evolution of the technologies allows an increasingly spreading of the applications. there are today many fields of application of the electronics in the new concepts of smart connected obje cts and internet of things (iot). the main well-known application domains are health, transport, communications, security, energy and environment with the microelectronics at the heart of the systems [1]. this means as well an increasingly multidisciplinary * corresponding author. e-mail address: olivier.bonnaud@univ-rennes1.fr advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 copyright © taeti 127 approach in the pedagogical strategy and an innovative behavior of the future graduate and post -graduate [2]. the evolution of the content of the engineering formations must answer progressively to this new trend of the technics. with the same goal, a transverse discipline that manages crucially the use of a product, is the reliability, discipline that becomes a major objectiv e of all the products that are becoming more and more complex. reliability is applied at multiple levels of complexity. the simples t case corresponds to a discrete object, for example an elementary transistor. higher complexity appears in integrated circuits that can contain several billion elementary transistors. the worst situation is related to huge systems, for example data centers that can contain millions of complex integrated circuits, each of which is built of billions of elementary transistors! these two subjects are therefore part of the objectives for students and the challenge is to choose the best pedagogical way to acquire these skill. the pedagogical approach was based on a flipped class and learning by project that consisted to involve the students in the two topics with a major part of their personal investment. after several lectures on the fundamentals of microelectro nics and reliability of electronics components performed by two foreign professors in english language, twelve groups of five students were built. each group had to develop one topic, chosen for its strategic importance, such as the reliability of the spac e electronics, the data centers, the challenge of very high density packaging, but also the huge development of connecting objects, the ulsi and the large area electronics. thus, from a given set of main literature references, the students have to prepare during five days a twelve pages report and an oral presentation, both in english language. after a short presentation of the context, the paper deals with the organization of these international flipped classes, the content of the personal works in the both specialties, an analysis of the main results, and a description of the evaluation of the questionnaire filled by the students . 2. honors bachelor the honors bachelor students are highly selected students that are supposed to produce an efficient work and t o continue in post graduate studies. they are rigorously selected at the entrance and are enrolled in an institute, in this case, the chien-shiung wu college. all the students are selected on the basis of a good capability to work in english language. they are thus expected to attend to lectures and seminars performed by foreign teachers. the students are also able to write documents in english, even if with scientific purpose they have to learn new vocabulary adapted to the domain. there are several promot ions spread in four main disciplines: computer science, electrical engineering, mechanics and bio -medical engineering. the managers of the bachelor degree have the possibility to organize specific modules, with the goal to make aware the students in high technologies with a new pedagogical approach. thus the concept of flipped classes was adopted. two groups of thirty students were built, the first one having the objective to study the new field of microelectronics, the second the new field of reliab ility. as it is well known, many applications in engineering are increasingly involving smart connected objects based on microelectronics systems [3]. two aspects are thus very important: the technics and technologies that are at the core of the systems [4], and the reliability [5] that is one of the main parameters that characterize good products adapted for their mission profiles. these two fields are today a significant component of the background of engineers. they are also at the heart of th e future challenge of the technological innovation. that is the reason of the choice of these topics for the students at the level of the third year of the bachelor:  microelectronics and nanotechnologies: engineering sciences at the heart of the smart connected objects and of their applications,  the reliability challenge for advanced technologies: a critical concern for research, production, economy and modern society . advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 copyright © taeti 128 these two topics are selected by sixty students of the institute. in order to maintain a high motivation of the students, they build by themselves six groups of five students with the objective to work on one of the proposed topics . 3. awareness to microelectronics and to the reliability the evolution of the fields of microelectronics and nanotechnologies has presently two main orientations: on the one hand, the ultra large scale integration following the famous moore’s law [6] with finfet or fdsoi technologies [7], and on the othe r hand, the heterogeneous technology approach that inserts the new devices in systems, mainly the smart connected objects based on integrated technologies but also on large area electronics, on thin film technologies, on sensors and actuators that can be linked to the applications. sensors may concern the physical, chemical, spatial and b iological detections, while the actuators can drive mechanical, fluidic, optical, thermal mechanisms that are involved in the monitoring of many security or medical equipment. the evolution of these technologies corresponds to a new law of evolution, named “more than moore” and includes system in package, systems on chip involving the third dimension and even lab -on-chip. fig. 1 shows the classical representation of the moore’s law issue of the ipc report [8]. fig. 1 moore’s law representation: the exponential increasing of the integration was verified during more than fifty years, even if the slope was a little bit smaller than the predicted one by g. moore in 1965! (after ipc report [8]) this evolution is also a consequence of the fabulous improvement of the design tools, in the frame of the computer aided design approach. these tools are able to design and simulate very complex circuits with billions of elementary devices (mainly transistors) but also imply the integration of many new functions in heterogeneous technologies. these last are combining electronics functions with either mechanical elements and optical devices, or functionalized surfaces able to detect chemical or biological species. besides, a multidisciplinary approach is increasingly needed in order to develop in the frame of research and development team’s new products in many domains of applications such as health, transport, communications, security, energy and environment with the microelectronics in the heart of the systems [1]. this combination of these knowledge and multidisciplinary competences is the engine of the innovation. thus, it is a real challenge to form the young to this new app roach. in parallel, the increasing complexity generates new problematic that is linked to the mission profiles of the products, the ageing, the security of the systems that are all gathered in the reliability domain. it is more and more important to evaluat e the meantime to failure of each product (mtbf), and more especially the failure in time parameter (fit) that must be very low even in a reliable complex system. this parameter is strongly function of the environment that can be harsh in many applications. this behavior corresponds to the presence or the variation of the parameters such as, temperature, humidity, electromagnetic advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 copyright © taeti 129 radiation, particle bombardment, electrical stress (high voltage or high current), mechanical vibrations, mechanical stress, chemical or aggressive ambiances, etc. fig. 2(1) shows the classical variation of the failure rate in function of the time. the analysis of the reliability consists to understand the three main stages of the evolution, the early infant failure rate, the normal failure and the end of life failure. however, for so complex integrated electronic devices, the question of obtaining very high yield production levels has imposed strategies of total quality management in the devices processing, with a drastic reduction of latent defects and infant failures at the first stage of the devices life time. furthermore, as electronics systems are now driving almost all sectors of human activities, their reliability is now one of the main factors conditioning their life safety. thus , the classical “bath” shaped failure rate curve is being targeted in an almost constant “zero” failure rate, up to the end of life time, as shown fig. 2(2). the solutions to reach such results are difficult to derive and need to develop particular skills for engineers . fig. 2 failure analysis: 1) classical bathtub failure rate evolution (blue); 2) almost constant zero failure rate. the second curve is the targeted behaviour of the innovative circuits and systems (red) these two topics are selected by sixty students of the institute. in order to maintain a high motivation of the student, they build by themselves six groups of five students with the objective to work on one proposed topic . 4. organization of the flipped classes the modules are organized on two weeks. the students are shared into two classes of thirty students, divided into six groups of five students each. the face-to-face duration between students and teachers is about twelve hours. the personal work of each student is approximately five times higher. it includes bibliography research, analysis of the given documents, compilation of the research by the group, repartition of the work, organization of a report, redaction of the manuscript, preparation of the oral presentation involving classical tools such as powerpoint diaporama. more or less, the presentation is half an hour that means a very precise duration and a clear sharing of the intervention by the five speakers . the students did not yet have solid experience in both areas. as a result, the beginning of both modules was devoted to several lectures that explain to students the context of the disciplines and their main principles. from this approach, the s tudents are selecting their subject after the second conference. each group had to develop one topic, chosen for its s trategic importance, such as the reliability of the space electronics, the data centers, the challenge of very high density packaging, but also the huge development of connecting objects, the ulsi and the very large area electronics. thus, from a given set of main literature references, the students prepared during three days a twelve pages report and an oral presentation, both in english language. advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 copyright © taeti 130 5. effective works of the students the students had to prepare their presentations. the subjects of the presenta tion and of the short report cover the most important aspects of the field, i.e., the evolution of the integration, the development of new technologies, the extension of the field of applications, more especially in the evolution of the connecting objects and of internet of things (iot) on the following topics for the microelectronics field:  new technologies for the future integration,  evolution of mems,  large area electronics,  microelectronics for telecommunications,  connecting object for environment application  the substrates for integrated microelectronics and solar cells . for the reliability, the subjects cover the main types of applications on the devices and on the systems:  the reliability of the space electronics,  the harsh environments: reliability impact on electronics devices ,  the reliability of data centers,  the challenge of the very high density packaging,  the dielectric degradation and breakdown.  the radiation effects. 6. survey based on a questionnaire: main results in order to have a good appreciation on the pedagogic efficiency of the approach, the students were asked on the several points of the experience. ten questions were directly focused on the organization and on the content of both modules :  adequacy of the topics to the curricula of the bachelor students ,  diversity of the subjects with the curricula (engineering),  duration of the modules that were concentrated on two weeks only,  organization (lectures, schedule, presentations),  quality of the evaluation of the work (marks obtained by the students),  originality of the pedagogical approach,  contribution to the awareness of the technological challenges ,  improvement of the general skills and knowledge,  relevance of an oral presentation,  impact on english language practice. the answers were shared in five types: very bad, bad, good, very good and excellent. the results are anonymous in order to avoid any limitation on the student side. in addition, a case was reserved to free comments. very few students have filled this case. among the sixty students, fifty eight have answered. thus, the return percentage is 96.7% that represents a real significant sampling of appreciations. fig. 3 shows the histograms of the answers for the two modules . advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 copyright © taeti 131 fig. 3 cumulated answers of the survey. on the ten questions (300 answers), for both specialities, the students found the approach very good in average. a large majority has considered that the foreign language was not a drawback. only two students had some bad feeling on the modules (organization and interest) for both specialties, the students found the approach very good in average; more than 70% have considered the experience very good or excellent. in the free comments, no remark on the amount of personal work they had to do. they well accept the approach mainly due to a good motivation and probably for its novelty, for them. a large majority has considered that the foreign language was not a drawback. only two students among the fifty-eight had some bad feeling of the modules (organization and interest). fig. 4 results of the survey. general appreciation of the students on the two modules. only two students among fifty -eight were not satisfied of the modules and of the flipped class approach fig. 5 result of the survey on the opportunity to reproduce this experience for the next promotion. only three students among fifty-eight have considered that the modules could be cancelled next year fig. 4 shows the general evaluation of the modules. a large majority was very satisfied and more (a majority of excellent!). its represents more than 80%. this is a proof that the two modules have answered to a need that was very appreciated by the students. on the basis of these results, a specific question about the reproduction of the same modules for the next promotion was asked. a large majority of the answers was “yes”. fig . 5 shows the histogram of these answers. advances in technology innovation, vol. 3, no. 3, 2018, pp. 126 132 copyright © taeti 132 among fifty eight students, only 3 estimated that the experience is not interesting for the new students. in other words, 94% of the students found that this experience can be reproduced for the future honors . 7. conclusions results were generally very good. most of the students succeeded in addressing issues that were completely new for them. they clearly built by themselves the skills allowing understanding of all the important aspects of the topics they had to app roach. they were able to highlight the main problems to solve, to improve the current solutions, and to perfo rm a presentation in english. in conclusion, such a self-made intermediate project by the students has been very beneficial to introduce new teaching sessions related to the new concepts applied to advanced microelectronic technologies and high reliabilit y devices, within the framework of international studies. this approach is included in the updated strategy for higher education oriented towards innovation [9]. the french national network of microelectronics, gip-cnfm [10-11], has adopted this strategy for many years. more recently, the chinese government [12] has also followed this evolution . acknowledgment the authors want to thank the colleagues with south-east university that helped them for the pedagogic and administrative organization of this work. special thanks to lorraine chagoya-garzon, executive assistant of the gip-cnfm, for the technical support in the redaction of this paper. references [1] o. bonnaud and l. fesquet, “multidisciplinary topics for the innovative education in microelectronics and its applications,” proc. of 14th international conf. information technology based higher education and training , 2015, pp. 1-5. [2] o. bonnaud and l. fesquet, “innovating projects as a pedagogical strategy for the french network for education in microelectronics and nanotechnologies,” proc. of ieee international conf. microelectronic systems education, 2013, pp. 5-8. [3] o. bonnaud and l. fesquet, “communicating and smart objects: multidisciplinary topics for the innovative education in microelectronics and its applications,” proc. of international conf. information technology based higher education and training, june 2015, pp. 1-5. [4] g. matheron, keynote, microelectronics evolution, european, microelectronics summit, paris, 2014. [5] f. jensen, electronic component reliability: fundamentals, modelling, evaluation, and assurance, 1st ed., wiley, 1996. [6] g. e. moore, “cramming more components onto integrated circuits,” electronics magazine, vol. 38, no. 8, pp. 114-117, 1965. [7] o. bonnaud and l. fesquet, “trends in nanoelectronic education from fdsoi and finfet technologies to circuit design specifications,” proc. 10th european workshop on microelectronics education, may 2014. [8] m. swaminathan and j. m. pettit, 3rd system integration workshop, 2011. [9] o. bonnaud and l. fesquet, “the new strategy based on innovative projects in microelectronics and nanotechnologies,” ecs journal of solid state science and technology, vol. 2, no. 11, pp. 1-7, 2013. [10] “cnfm: coordination nationale pour la formation en microélectronique et en nanotechnologies,” http://www.cnfm.fr. [11] o. bonnaud and p. gentil, “gip-cnfm: a potential model for micro and nanoelectronics education, invited communication, design and technology of integrated systems in nanoscale era,” proc. design and technology of integrated systems , march 2008. [12] o. bonnaud and l. wei, “a way to introduce innovative approach in the field of microelectronics and nanotechnologies in the chinese education system,” proc. of engineering and technology innovation, vol. 4, pp. 19-21, 2016.  advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 performance evaluation of mqtt as a communication protocol for iot and prototyping yuya sasaki 1,* , tetsuya yokotani 2 1 graduate school of electrical engineering and electronics,kanazawa institute of technology, ishikawa, japan 2 department of electronics, information and communication engineering, college of engineering, kanazawa institute of technology, ishikawa, japan received 03 march 2018; received in revised form 05 august 2018; accepted 14 september 2018 abstract the hypertext transfer protocol (http) has been widely used as a communication protocol for internet access. however, for internet of things (iot) communication, which is expected to grow in the future, http requires a large overhead and cannot provide efficiency. in order to solve this problem, lightweight communication protocols for iot have been discussed. in this paper, we clarify some problems of http for iot and propose mq telemetry transport (mqtt), which is a promising candidate for the iot protocol, after conducting a performance comparison with http. keywords: iot, http, mqtt, lightweight protocol, performance evaluation 1. introduction in recent times, there have been numerous discussions on the internet of things (iot) worldwide [1-2]. a large number of iot devices are connected to networks, and iot devices collect data from various sensors. though the data size of sensor devices is very small, it is communicated in large quantities through the network. currently, internet access requires tcp/udp/ip and application protocols over these protocols. amongst the application protocols, hypertext transfer protocol (http) [3] is common. it is applied for general internet access. in iot communication, a large number of devices communicate using very small data packets. when http is applied to iot communication, protocol overhead causes serious degradation of performance. moreover, the ip address in iot is thought to depend on the physical location and causes complexity in network control. in order to solve these problems, data aware networking (dan), [4] e.g., information centric networking (icn) [5-6], named data networking (ndn) [7], and content centric networking (ccn) [8], is being considered and discussed to be used as the architecture of iot. mq telemetry transport (mqtt) [8] is categorized as dan. mqtt has been developed for iot. protocol overhead is reduced, and information is transferred in a name-based system referred to as topical. it is not required that the address in mqtt depends on the physical location as the ip address. offered traffic in the network is reduced to transfer information. this paper describes, performance evaluation of iot communication based on mqtt, and compares the performance of http and mqtt protocol. this paper reports prototyping of iot devices based on mqtt and http. finally, it proposes using a combination of mqtt and conventional ip. 2. related technologies and standardization trends in order to realize iot communication, active discussions have been held between the industry, academia, and government. discussions on various topics such as technology development, international standardization strategy, and * corresponding author. e-mail address: b6700656@planet.kanazawa-it.ac.jp advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 22 promotion of demonstration experiments are held by the iot promotion consortium [10]. in this section, taking these arguments into consideration, we summarize the discussion on environmental in this paper. 2.1. communication network for iot the communication network scenario for iot is reported in [11]. fig. 1 shows the system configuration required for realizing iot communication. in fig. 1, the area network is introduced for iot communication. however, wide area network infrastructure coexists with various services of legacy and iot. an outline of the communication protocol is shown in fig. 2. in the wide area network infrastructure, ip communication is widely spread. presently, iot communication cannot be differentiated from ip communication. however, http has been used for wide internet access, and every time information is accessed, a need for a three-way handshake with the tcp is required. in case of iot communication, a large number of small packets are generated because they handle traffic from the sensors. in the case of http, a large communication capacity is required to attach a header to each of them. for this reason, as shown in fig. 2, lightweight protocol for iot communication is necessary. fig. 1 system configuration of iot fig. 2 outline of communication protocol including for iot 2.2. international standardization trend the discussion on international standardization of lightweight protocol for iot is summarized in this section. the iot standardization can be represented as shown in fig. 3. discussions have been made on the architecture and requirements of communication systems in iso/iec, jtc1/sc41, and itu-t sg13. among them, there is a need for a lightweight protocol with low overhead. specifically, instead of using iot devices information processing infrastructure application gateway sensor etc… optical communication wireless communication area network (lan, han, pan, ban, …) optical communication wireless communication wide area network infrastructure optical communication legacy application protocol (http, ftp, smtp, etc...) lightweight protocol (mqtt, etc…) tcp/ip, udp/ip physical layer, data link layer wireless transmission protocol 6lowpan/udp, zigbee, etc… legacy communication communication for iot wide area network infrastructure area network advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 23 location-dependent information such as ip address, “name-based access method” that directly accesses information is regarded to be more efficient. these are classified as icn. for example, [4] defines a framework for it. discussions have been made on the detailed methods, such as irtf and onem2m forum standards [12-13]. mqtt discussed in this paper is also regarded as an effective method. fig. 3 standardization overview on iot 3. overview of http and mqtt in this section, http and mqtt are summarized with respect to communication sequences. 3.1. overview of http the http protocol is used for the communication of information written in hypertext markup language (html). as a feature, in order to obtain information, it is necessary to specify the information location. uniform resource locator (url) is used to specify the address of that information. in principle, it conducts stateless communication. connection/disconnection of a communication session is performed every time information is accessed. however, when http is operated over tcp/ip, reliable communication is provided. http communicates with two responses, http request and http response. the http communication sequence is shown in fig. 4. fig. 4 communication sequences on http 3.2. overview of mqtt mqtt is a communication protocol of the publish /subscribe type, and the client communicates via mqtt broker [14]. as a feature of mqtt, the fixed header of the mqtt packet is a minimum of two bytes. mqtt uses proprietary name-based methods called topics to transfer information. a topic does not depend on the physical location of the ip address. the network load can be reduced by routing. from fig. 5, topic has a hierarchical structure. there are three types of topic iec iso de jure itu-t sg13, sg20 jtc 1 / sc41 vertical architecture platform type architecture forum ietf, irtf, w3c, ieee, aioti, ….. onem2m architecture · requirements detailed provision · protocol specification syn syn ack device server ack http request http response fin ack ack fin ack ack dns advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 24 designation methods such as a perfect match, forward match, and partial match. moreover, mqtt can set three levels of delivery guarantee. therefore, it can be set according to the importance of communication. from the sequence diagram of fig. 6, mqtt does not connect/disconnect the session for each communication; however, it keeps a communication session connected. therefore, the communication session is simplified and communication wastage is reduced. from these features, mqtt applies to iot communication, small fixed header size, and it is thought that the communication becomes lightweight from retention of communication sessions. fig. 5 structural example of topic fig. 6 communication sequences on mqtt 4. comparison of http and mqtt traffic in iot communication, when a large number of devices are connected, overhead is caused. it causes problems such as network delay and server load. therefore, we evaluate their performance from the viewpoint of traffic and examine the suitable protocol for iot [15-16]. 4.1. definition of the network model fig. 7 shows the network model for the comparison with http and mqtt for communication traffic. in fig. 7, it is assumed that some devices such as sensors are connected to the server. it is a model that receives data from some sensor device via server. fig. 7 network model 4.2. http traffic http is applied to the network model of fig. 7, and traffic in data send/receive is calculated as follows. from the communication sequence of fig. 4, each communication packet is summed, and the obtained traffic is taken as traffic in one communication. here, the size of http request/response packets is set to 300 bytes each. it is assumed that 100 and 1000 sensor devices are connected to the transmitting devices. its payload size is 0 bytes. sensor temperaturecamera floor1 room1 *writing example of topic sensor/temperature/room1 room2 room3 etc… publish broker connect connack publish puback subscribe connect connack publish puback subscribe subback device1 device2 device n server user device advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 25 4.3. mqtt traffic mqtt is applied to the network model of fig. 7, and the traffic is calculated [17]. from the communication sequence of mqtt in fig. 6, the sum of packet sizes of mqtt packets is taken as traffic of one communication. consider the case of operating on tcp/ip, one communication is from the publish devices to reception of data on the subscribe devices. table 1 shows each header size of mqtt. table 1 mqtt packet type message type bytes connect 14 connack 4 publish 6 + topic(1chara/byte) puback 4 subscribe 7 + topic(1chara/byte) suback 5 4.4. comparison result of http and mqtt traffic fig. 8 traffic volume of http and mqtt the traffic of http and mqtt as discussed in section 4-2 and 4-3 are as shown in fig. 8. from this, compare the traffic on http and mqtt, as the communication increases, difference in traffic between http and mqtt increases, and when communication occurs 30 times, mqtt becomes about 1/5 of the traffic compared to http. as can be seen from fig. 8, in mqtt, the traffic of both 500 and 1000 devices connected to the server is less than half of the traffic connected with 500 devices by http. therefore, it can be understood from this that traffic can be reduced using mqtt in iot communication. 5. comparison of network resources 5.1. definition of network resources by comparing the network resources of http and mqtt, we present the definition of network resources. it is defined as the occupation time in server from the start of communication to the end of device (fig.9). fig. 9 definition of network resources 0 5000 10000 15000 20000 25000 30000 0 5 10 15 20 25 30 tr af fi c [k b ] number of communications http 500devices http 1000devices mqtt 500devices mqtt 1000devices communication start communication end information access occupy resources advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 26 5.2. measurement of access delay time in order to calculate network resources, we measure the access delay in actual communication [15] [18]. for verification, we used raspberry pi as a device and wireshark [19] of packet capture software to measure the communication access delay time (fig. 10). fig. 10 network configuration of access delay measurement in the case of http communication, the access delay time is measured when the server is accessed from the pc to acquire data. in the case of mqtt communication, the access delay time is measured from the publish device to the subscribe device via the mqtt broker. fig. 11 http access delay time fig. 12 mqtt access delay time pc (wireshark) http server http communication mqtt broker (wireshark) subscribe devicepublish device mqtt communication http request http response publish publish 4.909 4.91 4.911 4.912 4.913 4.914 4.915 4.916 4.917 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ti m e[ s] number of communications ave： 4.9115[s] 0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ti m e[ s] number of communications ave： 0.00106[s] advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 27 the results of the access delay time measurement of http and mqtt are shown in fig. 11 and 12. communication was carried out 20 times each, and the average was calculated. in http (fig. 11), the access delay was about 4.91 s on an average. in mqtt (fig. 12), the average was about 0.00106 s. in the first instance of communication for the mqtt, access delay is large in order to establish a communication session. because of looking at each sequence, in http, a delay of about 4.8 to 4.9 s occurs when a finack packet of a session disconnection request from a server is sent. this delay is considered to be a processing delay or keep time by using the server software. that does not mean that such delays will occur in all http communications. however, even if we subtract about 4.9 seconds from the measured http access delay time, we found that there is about 10 times short access delay time of mqtt communication. there are differences in the size of each protocol, in the case of http, it seems that there was a big difference in the access delay time owing to differences such as connection/disconnection of communication sessions. 5.3. required network resources next, network resources shown in fig. 9 are evaluated. we assume that access to information follows poisson distribution and time required for access follows an exponential distribution of average access time obtained in section 5-2. in addition, capacity of network resources is assumed to be sufficiently large. in this case, if the device generating information is k, it is represented by m/m/∞//k (finite population model). equilibrium state probability in this model is pk, the arrival rate of the information is λ, assuming that the average processing time is h, necessary network resource n is expressed by eq (1). 𝑁 =∑𝑘 ⋅ 𝑝𝑘 = ∑ 𝑘 ⋅ (𝜆ℎ)𝑘 ( 𝑘 𝑘 )𝑘 𝑘=0 (1 + 𝜆ℎ)𝑘 𝑘 𝑘=0 = 𝑘 ⋅ 𝜆ℎ 1 + 𝜆ℎ (1) fig. 13 shows the numerical calculation using arrival rate λ as a parameter with respect to equation (1). as can be seen from fig. 13, the mqtt requires less network resources for http. fig. 13 comparison of network resources 6. affinity with ip the internet is currently based on ip communication. however, the movement of devices frequently occurs in iot communication. assuming this, since ip communication depends on the location, smooth communication cannot be obtained. therefore, network architectures such as dan attract attention [4] [20]. we consider the relationship of mqtt with ip when applied to a wide area network. it is assumed that mqtt is applied to a wide area network, as shown in fig. 14. it is assumed that there are multiple mqtt brokers in many devices. 0 2000 4000 6000 8000 10000 12000 5 30 55 80 105 130 155 180 r es o u rc es [ s] arrival rate http(k=5000) http(k=10000) mqtt(k=5000) mqtt(k=10000) advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 28 in this scenario, there are two possible routing problems. case 1, the publish devices connected to the mqtt broker and the subscribe devices communicate. if devices that want to obtain data are connected to another mqtt broker, the connection needs to be changed. however, publish devices do not know to which mqtt broker the subscribe device is connected. case 2, the publish device has multiple sensors. for each sensor data, the publish device sends data to the mqtt broker. at this time, it is unknown where the subscribe device is divided for each sensor data is connected. fig. 14 wide-area network configuration of mqtt as a solution to these problems, there is a method of connecting the mqtt broker in a ring shape. alternatively, data may be sent to all adjacent mqtt brokers. in this case a large overhead will occur. therefore, it may be possible to link topic and ip and perform routing using a mechanism like dns. therefore, when mqtt is used assuming a wide area network, it is difficult to communicate with only name-based routing that is independent of ip [21] [22]. it is similar to the above routing mechanism, and mqtt has another version for wireless sensor network mqtt-sn (mqtt for sensor networks). for routing, a predefined topic id and short topic are introduced. therefore, there is a feature where mapping is done automatically by informing the topic id and topic to the client, gateway, and broker in advance without setting it. it has already been thought that when a name and address are attached independently, it can be further simplified or linked to another id or the likes. this idea is not limited to mqtt; it can be said that it is common to name-based protocols. as a more sophisticated mechanism, it is conceivable that a name is automatically allocated in name-based routing. 7. conclusions tu-t y. 3033 defines four goals and twelve design goals that reflect the new requirements of future network, which specifies the framework of dan [4]. the essence of dan is name-based communication that routes data objects in the network by name or identifier, and the name-based communication allows dan to locate data objects irrespective of the location. name-based communication has received considerable attention as it guarantees the continuation of communication without being interrupted by the change of data object position [23]. in this paper, we evaluate the performance from a viewpoint of traffic volume, access delay, and network resources on overhead with both the http and the mqtt protocols applied to the iot platform and compare them. from this, it is found that mqtt is superior to http when applied to iot. however, for this network model, as shown in fig. 7, and in wide area iot networks, as discussed in section 6, it is necessary to study the problem caused by transfer of name-based information future works. case1 (publish) case1 (subscribe) × case2 sensor1,2,,n (publish) ?? ? ? case2 sensor1 (subscribe) case2 sensor2 (subscribe) connect brokers to each other ： mqtt broker ： device advances in technology innovation, vol. 4, no. 1, 2019, pp. 21 29 29 references [1] d. miorandi, s. sicari, f. d. pellegrini, and i. chlamtac, “internet of things: vision, applications and research challenges,” ad hoc networks, vol. 10, no. 7, pp. 1497-1516, september 2012. 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[23] j. lópez, m. arifuzzaman, l. zhu, z. wen, and s. takuro, “seamless mobility in data aware networking,” proc. 2015 itu kaleidoscope: trust in the information society, ieee press, december 2015, pp. 1-7. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=7112413 https://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=7112413  advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 projecting the mental model of social networking site usage chun-hui wu1,*, yih-her yan2 , kuen-ming shu3 1 department of information management, national formosa university, yunlin, taiwan, roc. 2 department of electrical engineering, national formosa university, yunlin, taiwan, roc. 3 department of mechanical and computer-aided engineering, national formosa university, yunlin, taiwan, roc. received 02 june 2017; received in revised form 27 july 2017; accepted 11 august 2017 abstract the growth of online social networking sites (sns) has created a new world of connection and communication for online users. sns usage has become an important part of people’s daily lives. this study aims to obtain new insights towards sns usage behaviour. based on participants’ mental models, it is hoped to make more clear exposition about their perceptions and experiences as well as to explore what factors affect their behaviour for using social networking sites. a blend of qualitative methodologies was adopted for data collectio n and analysis, including the zaltman metaphor elicitation technique (zmet) method, the laddering technique, and the means-end chain theory. the results of this study show that the most important values of using sns include its convenience, maintaining relationship, gaining relaxation, as well as reaching coherence. additionally, participants pointed out they cared about their online privacy issues very much and had found some potential dangers; however, they continued to use these sites because of the great benefits and enjoyment. keywords: social networking sites, projective technique, zaltman metaphor elicitation technique, mental model, means-end chain theory 1. introduction with the advancement and attractiveness of web 2.0 technology, online social networking sites (snss) such as facebook, google+, instagram, twitter, and line, have emerged as rapidly growing mechanisms that allow users to communicate with each other for sharing information, posting videos, pictures, comments, and messages at any time and from any places around the world. snss usage has become increasingly more influential on most internet users’ daily lives and radically have changed how they spend their time online. as snss continue to evolve at a breakneck speed, so does the usage gro wth on the respective platforms. according to the 2016 nielsen company’s report [1], the global average time spent per person on social networking sites is now nearly five and half hours per month. in addition, researchers from the pew research center’s in ternet found that nearly 80 percent of online adults used social networking sites, and almost 88% of teens and young adults were a member of at least one social network [2-3]. social networking sites support individuals to present themselves, articulate their social networks, and establish or maintain connections with others not only in forming but also maintaining relationships. in recent years, these sites have been the * corresponding author. e-mail address: melody@nfu.edu.tw tel.: +886-5-6315741; fax: +886-5-6364127 advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 copyright © taeti 37 fastest-expanding websites [4]. the growth of online social networks has created a new world of connection and communication for online users. however, it is not only changing how online users interact with one another, but also changing how business es touch with their consumers. the popularity of social networking is increasing very rap idly, and, therefore, businesses are turning to these platforms in order to promote their products and to reach potential consumers. this is new opportunities for busines ses to communicate with consumers for gaining much more transparency and ultimately to build profitable relationships with their consumers. it is predicted that us advertisers will reach $2.6 billion to place advertises on social networking sites by the end of 2012, up more than $1.2 billion from 2008 [5]. this progress illustrates the increasing influence of social networking sites in modern business environment. these phenomena have attracted much attention of practitioners and researchers to question what factors may influence the usage behavior on snss [6-7]. yet despite this interest, there seems to be very limited understanding of users’ mind map. essentially, a clear understanding of users’ thoughts and feelings could help businesses better allocate funds appropriately to effective factors and redesign or eliminate non-effective factors. by being aware of how mental models impact users’ understanding of snss can help businesses better apply marketing strategies that are consistent with users’ expectations and behaviour in social media [8]. this study, therefore, sets out to explore the following research questions: what are the mental models of online users toward the value of social networking sites? this study aimed to obtain new insights towards social networking sites usage behavior. based on participants’ mental models, it is hoped to make more clear exposition about their perceptions and experiences as well as to explore what factors may has an impact on their behavior for using social networkin g sites. an interpretative approach by means of the zaltman metaphor elicitation techniqu e (zmet), a projective technique, was conducted to a university context. 2. the projective technique the projective technique is a blend of three qualitative methodologies including the zmet method, the laddering technique, and the means-end chain theory. 2.1. the zaltman metaphor elicitation technique for understanding users’ actual thoughts toward social networking sites, the projective technique, zmet, was selected. the rationale for using zmet to collect and analyze data is that the zmet process of th inking about and searching for images is able to bring hidden, unconscious thoughts to the surface [9]. the zmet method provides opportunity for researchers to lo ok at the phenomena in more varied and deeper ways than is possible through other traditional qualitative methods. most qualitative research techniques, such as case study and focus groups, depend on verbal communication as a data-collection method. however, for more than 80% of people communication being nonverbal and non -linear [10], verbal-based interactions with subjects may result in an incomplete communication. additionally, people decision -making and behavior are guided by largely hidden experiences because probably 95% of all cognition is unconscious [11]. thus, the way in which thoughts occur may be very different from the way in which they are communicated. cognitive scientists claims that people think in images, not words; however lots of today’s qualitative research techniques rely on verbal-centric communication (i.e., literal, verbal language) as a data collection method [10, 12]. as subjects are better able to transmit their thoughts and feels in nonverbal terms, combining nonverbal images with verbal communication is able to generate a more meaningful message than totally relying on verbal communication. in this regard, zmet was designed to be a more precise research tool which can make up the deficiencies in current qualitative research methods . advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 copyright © taeti 38 zmet is a hybrid methodology, which integrates the visual projection technique, in -depth personal interview, and a range of qualitative data-coding method, such as categorization, abstraction of categories, and comparison of instances within data to elicit the metaphors, constructs, and mental models that drive consumers’ thinking and beha vior. for improving qualitative research, zmet uses multidisciplinary ideas such as cognitive neuroscience, neurobiology, art critique, literary criticism, v isual anthropology, visual sociology, the philosophy of mind, art therapy, and psycholinguistics to combine knowledge from the social sciences, biological sciences, and the humanities. metaphors, photo analysis, and narrating are key concepts used in zmet, and each adds value to this research process. this technique achieves high validity since issues a nd structures emerge from the data collected by the respondents themselves. therefore, zmet has been employed in numerous academic studies. in addition, it has gained considerable interest and been used in over 20 countries around the world by the world's leading companies, such as at&t, coca-cola, motorola, american express, to explore consumer and organizational issues [9]. 2.2. the means-end chain theory and the laddering technique the means-end theory sustains that the way participants relate to topics can be represented by a hierarchical model of three interconnected levels: attributes, consequences, and values [13-14]. the zmet approach can offer a deeper and richer understanding of the important personal constructs elicited through laddering process [15]. the analysis of the means-end data comprised of three stages. at the first stage, the coding of sequences of attributes, consequences and values (the ladders) takes place in the results of zmet process. the second stage involves the development of meaningful categories by grouping together phrases with identical meanings. the identification of categories is by a-c-v phrases and key words that participants used during the zmet interviews and from concepts derived from the literature review. the s tudy will follow an iterative process of recoding data, splitting, combining categories and generating new or dropping existing categories, followed by an aggregation of codes for individual means –end chains across participants. finally, two hierarchical value maps (hvm) of teachers and students will be generated. the map consists of nodes, which stand for the most important attributes/consequences/values (conceptual meanings) and lines, which represent the linkages between the concepts. the map graphically sums up the information collected during the zmet interviews . 3. research methodology to address the research question, a qualitative research framework is presented in fig. 1. in order to capture the mental of online users who were using social networking sites, a blend of qualitative methodologies including the zmet method, means-end approach, and laddering process were used for data collection and analysis . online users were interviewed with the zmet approach and laddering process individual mental models consensus maps zmet laddering zmet laddering value consequence attribute value consequence attribute mec theory mec theory select participants using rpii questionnaire fig. 1 research framework advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 copyright © taeti 39 this study had the zmet approach as theory basis, combining means-end approach and laddering process to analyze the high involvement people thoughts and feelings for snss usage. according to this method, we could realize the correlation about snss attributes, usage consequences, and ultimate values. qualitative-based procedures were selected for this study for three reasons. first, this study seeks to deeply better understand what is actually happening within social networking sites. secon d, it is hoped to obtain more in-depth information that may be difficult to convey quantitatively. third, zmet method provides opportunity for researchers to look at the phenomena in more varied and deeper ways than is possible through other traditiona l qualitative method. 3.1. selecting participants in this study, the revised personal involvement inventory (rpii) questionnaire was utilized to help find a representative sample of facebook users, who meet the requirements for the research objective and have a high relevance. the rpii is illustrated in table 1. after qualifying for participation using rpii, a total of 12 facebook users are recruited to participate in our study. for understanding users’ actual thoughts toward social networking sites, the projective technique, zmet, was selected. the rationale for using zmet to collect and analyze data is that the zmet process of thinking about and searching for images is able to bring hidden, unconscious thoughts to the surface [9]. the zmet method provides opportunity for researchers to look at th e phenomena in more varied and deeper ways than is possible through other traditional qualitative methods. twelfth qualitative interviews based around the zmet approach were used for this study including 12 users who have highly participated in social networking sites were conducted. table 1 rpiirevised personal involvement inventory 1 unimportant : : : : : : important 2 boring : : : : : : interesting 3 irrelevant : : : : : : relevant 4 unexciting : : : : : : exciting 5 means nothing : : : : : : means a lot to me 6 unappealing : : : : : : appealing 7 mundane : : : : : : fascinating 8 worthless : : : : : : valuable 9 uninvolving : : : : : : involving 10 need : : : : : : not needed participants will be instructed to gather eight to ten pictures that represent their t houghts and feelings about social networking sites. these pictures could come from any source, including photographs, magazines, books, newspapers, or catalogues, and the instructions will be given seven to ten days prior to the interview. participants were contacted one or two days before their interview to confirm their understanding of the task and the whole processes, and each interview took approximately two hours in a quiet room and were recorded. storytelling 1 missed issues and images 2 sorting task 3 construct elicitation 4 opposite images 5 consensus maps 10 the vignette 9 the summary image 8 sensory images 7 most representative picture 6 fig. 2 the ten core steps in implementing zmet advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 copyright © taeti 40 during the two-hour zmet interview, ten steps in the zmet method are summarized as follow and shown as fig. 2. (1) storytelling: provides participants with an opportunity to tell their stories(as shown in table 2) because human memory and communication is story-based. (2) missed issues and images: participants describe any issues for which they are unable to find a picture to obtain and explain their relevance. (3) sorting task: participants are asked to sort their pictures into meaningful piles. (4) construct elicitation: the laddering technique is used to elicit basic constructs and their relationships. participants’ pictures serve as stimuli. (5) opposite images: respondent describes pictures that represent the opposite of the task. (6) most representative picture: participants indicate the picture that is most representative. (7) sensory images: descriptions are elicited of what does and does not describe the taste, touch, smell, sound, color, and emotion of the concept being explored. (8) the summary image: respondent, with scissors used to cut photos, creates a summary image. (9) the vignette: participant is asked to create a story or short imaginary video that communicates important issues related to the topic under consideration. (10) consensus maps: all the respondents’ mental maps were merged to a consensus map. table 2 storytelling images briefly description image description privacy i do care about online privacy issues very much. there are various threats that people may encounter on social media. for avoiding dangers, great skills and caution are required for using social networking sites. otherwise, it is easy to observe or monitor other users’ emotional state and interactive statuses. addiction similar to drug addiction, many users are addicted or obsessed with facebook and have difficulty logging off even after they have been on for hours. convenience sns is like a convenience store that is available 24 hours a day and offers everything from hot meals to package delivery. for example, facebook is convenient because we can log into it anywhere, on a pc or on a mobile phone. it is helpful and convenient in ways that it helps users find friends, lets our current friends suggest some people we may know but have not already added. 3.2. data analysis participants’ feelings, thoughts, and behaviors were analyzed based on means-end chain theory. all interviews were recorded and later transcribed to enable empirical content analysis for achieving means-end chains. each means-end chain links the relationships between attributes, consequences, and values (a-c-v), it can also analyze the emotion product attributes brings to the consumers, what overall value thinking [16]. the link is shown in fig. 3. advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 copyright © taeti 41 attributes (means) consequence (means)(end) values (end) fig. 3 means-end chain connects relations between attributes/consequence/values a means-end chain links attributes of the social network sites, consequences of these attributes to participants, and the personal values that the consequences reinforce. next, each participant’s transcripts were read to discover the relationships between attributes, consequences, and values. a participant’s sequence of attributes, consequences, and values (a -c-v) is called a means-end chain and represents a perceptual orientation of decision criteria. finally, a serious of a-c-v chains were merged together to derive individual mental models and the aggregate consensus maps of all participants. a consensus map represents the main concepts identified by all participants and the linkages between the concepts as reflected in their interviews. the consensus map (see fig. 4) in this study resulted from the linkages between system attributes, usage consequences, and personal values. this consensus map presented over 80% of all constructs mentioned by each one participant. sharing consequences values attributes newsfeed maintaining relationship perceived easy of use recording and storing reconnecting with friends interactive with others gaining relaxation convenience reaching coherence the wall fb platform blog games chatroom activity groupssharing fig. 4 the mental model towards social networking sites 4. findings and conclusions the zmet method provides a good way for understanding consumers’ cognition and projecting consumers’ behaviour. therefor, research data were collected with the zmet method to understand users ’ insights toward using social networking sites more thoroughly and more deeply. the analytical results show that the majority of respondents in this study indicated the most important value of social networking sites includes its convenience, maintaining relationship, gaining relaxation, as well as reaching coherence. this study’s findings were consistent with p revious research of of social networking sites [17-19]. additionally, respondents pointed out they cared about their online privacy issues very much and had found some potential dangers. however, they still continued to use social networking sites. the main reason is the perceived benefit and enjoyment providing by social networking sites are greater than perceived potential dangers for most respondents. the benefits of social networking service usage include formal educational outcomes, informal education and learning, creativity, individual identit y and self-expression, strengthening social relationships, belonging and collective identity, building and strengthening communities, civic and political participation, self-efficacy and wellbeing. advances in technology innovation, vol. 3, no. 1, 2018, pp. 36 42 copyright © taeti 42 references [1] sean casey, “the 2016 nielsen social media report,” http://www.nielsen.com/us/en/insights/reports/2017/2016-nielsen-so cial-media-report.html, 2017. 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[19] o. kwon and y. wen, “an empirical study of the factors affecting social network service use,” computers in human behavior, vol. 26, no. 2, pp. 254-263, march 2010.  advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 piglets comfort with hot water by biogas combustion under controllable ventilation cheng-chang lien1,*, ching-hua ting2, jun-han mei3 1 department of biomechatronic engineering, national chiayi university, chiayi, taiwan, roc. 2 department of mechanical and energy engineering, national chiayi university, chiayi, taiwan, roc. 3 graduate student, department of bioelectromechanical engineering, national chiayi university , chiayi, taiwan, roc. received 05 june 2017; received in revised form 23 august 2017; accepted 13 september 2017 abstract the purpose of this study is to develop a hot-water heating system for pig farms which use biogas as the energy source while the air quality is regulated using an inverter-controlled fan. the biogas is a by-product from the 3-stage wastewater treatment process in regular p ig farms. the b iogas is burned for hot water which is circulated to warm piglet compartments with regulated, forced ventilation. the hot water is connected to a heat exchanger and hot air is hence blown into the pigsty. to maintain the pigsty at a comfort atmosphere, ventilation is regulated using an inverter-controlled fan. the mechanical ventilation is to be optimized as a compromise between indoor air quality and ventilation rate. the temperature uniformity and air quality in the p igsty is to be secured for comfortability. experimental results show that hot water circu lating at 0.043 m 3 /min and 60°c could keep the pigsty at 28°c for a stocking density of 1.77 pig/m 2 . forced ventilat ion of 1.7 ach (air change rate per hour) at 28°c could keep the pigsty comfort in terms of indoor temperature, relative humidity, and carbon -dioxide concentration. keywords: biogas, piglets, hot-water heating system, force ventilation 1. introduction biogas is the combustible gas generated through the microorganism fermentation of organic waste under the anaerobic environment. it is one of the renewable energy to replace the requirement of future energy resource, the generated volume will be affected along with the factors of solid ingredients, fermented temperature, humidity, ph value, microbial strains and fermentation time of fermented organic matter so that the compositions are not exactly the same. the main constituent of biogas is methane (ch4) which is around 55-70%, carbon dioxide (co2) approximately 30-40%, 0.2-05% of hydrogen sulfide (h2s), and very small amounts of carbon monoxide, n itrogen and ammonia etc. direct emission of methane in the atmosphere will cause the global greenhouse effect growing in intensity, and the capability of causing the greenhouse effect per unit of methane is 23 times of carbon d ioxide, its harm to the earth environment for direct emission of biogas cannot be ignored indeed [1-4]. the process of 3-stage wastewater treatment facility promoted in the pig farms of taiwan includes the three stages of solid-liquid separation of excreta, anaerobic treatment and aerob ic treatment, and large amount of biogas is generated during the anaerobic process, however most of p ig husbandry in taiwan does not utilize the b iogas but emits to the atmosphere directly. as pointed out from the research, the methane content as generated from p ig sewage is higher than what is generated from the waste of crop farm, each hog sewage with the weight of 60 kg is able to generate approximately 0.23 m 3 biogas per * corresponding author. e-mail lanjc@mail.ncyu.edu.tw advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 87 day. biogas has high heating value and the fuel characteristics as well, it has been considered as the energy resource worth to promote and utilize, after biogas is burned, methane becomes the carbon dioxide which is able to lower the greenhouse effect, if the heat energy generated from the burned biogas is able to utilize, it may save significant energy, therefore, through th e utilization of biogas energy, the requirement of energy saving and carbon reduction can be achieved synchronously [5]. pig let will be weaned about four weeks after birth, the piglet just off from the weaning is very sensitive to the temperature in pigsty, if the daily temperature in p igsty drop is over 2°c, it will introduce the group diarrhea and respiratory diseases , and significantly affect the growth performance for p iglet. therefore, the temperature control in pigsty is one of the key factors for enhancing the production performance and economic benefit of p ig farms [6]. the ventilat ion of p igsty can be categorized as the natural ventilation and forced ventilation (mechanical ventilation). the main purpose of ventilation is to supply the oxygen required for the an imal breathing, remove the excess heat and moisture, p lus reduce the dust and limit the generation of harmful gases, such as ammonia and carbon dioxide etc. as pointed from the research, the staffs of livestock farm shall not expose to the environmental with the concentration of carbon dioxide (co2) over 1500 ppm and concentration of ammonia (nh3) over 7 ppm, the effective ventilat ion system shall be able to provide the best microclimate condition for the working area o f p ig farmers and animal living area [7-8]. the design of heat preservation facility for piglets in netherlands is to use the hot air from underground tunnels exchanged heat through the hot-water pipes to heat and preserve the heat for the piglet living area [9]. the purpose of this research is to develop a set of hot-water heating system using biogas as the fuel, and take the advantage of biogas energy generated from the 3-stage wastewater treatment process and apply it to pig farms for the heat preservation of piglets. ut ilize the burning of biogas and heating the water, delivered to the pigsty via pipeline, the hot-water flow blowers to blow the hot air through the air heater and exchanges heat in the pigsty to proceed the heating preservation for piglets, the pigsty collocates with the inverter fan to proceed the mechanical ventilation test with different forced ventilation temperature and regular ventilation percentage, and explore against the temperature uniformity and air quality in the pigsty. 2. material & method 2.1. experimental equipment the biogas generated from the pen manure of pig farms through the anaerobic fermentation process treatment, use the pipeline delivered/centralized to store in the red mud rubber bags, since the biogas contains the hydrogen sulfide which is corrosive to the metal equipment, use the blower to draw the biogas with the averagely negative pressure of 0.2 mpa through the biogas purification device to remove the hydrogen sulfide in the biogas, and then deliver to the biogas burning furnace a s the source of burning energy. the schematic image of biogas burning hot-water piglet heat preservation system is shown in the fig. 1. the implementation of biogas burning hot-water heat preservation system can be categorized as the biogas hot-water heating device, enclosed pigsty heat preservation system and inverter fan control system. the biogas hot-water heating device includes the biogas-burning furnace, electrical auxiliary heating device and hot-water storage tank. inside the main body of biogas-burning furnace is able to store approximately 0.7 m 3 water, and 52 pcs of stainless steel pipes are installed as the passage for hot air, when the biogas furnace is burned/heated from the bottom, the heated area will be able to increase via t he hot air passed through the hot air passage, so that the heating efficiency is enhanced and the temperature of hot-water increases rapidly, while an electrical auxiliary heating device is added to deal with the situation of insufficient b iogas volume, and the temperature sensor of hot-water is installed to measure the hot-water temperature (tw), so that the heating device is able to operate year-round. advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 88 when the thermocouple temperature o f air (tc) in the enclosed pigsty is lower than the default temperature (tset), the piglet heat preservation system starts the external circu lation, deliver the hot-water through the inverter motor and enter into the circulation-type blower in the pigsty to proceed the heat exchange, heat up the air inside the pigsty by blowing the hot air in order to achieve the effect of temperature control and heat preservation in the pigsty. since the pigsty is an enclosed space, the ventilation system is required to ventilate and change air in order to avoid the high concentration of noxious gas in the pig sty, this research uses the inverter fan control system to perform the ventilat ion and air change of p igsty, the inverter fan system consists of 2 inverter fans with the ventilation efficiency of 0.64 m 3 /s (slf-730, autofan, korea) collocating with the inverter control system (ecs-3m, varifan, usa), plus integrates the default temperature (tw) and the defaulted setting of air temperature in the pigsty (tset) together with the low limit air temperature setting function. fig. 1 schematic image of biogas burning hot-water piglet heat preservation system 2.2. experimental methods please locate fig. 2. under the text this research uses temperature/humid ity sensing recorder (u10-003, hobo-onset, usa) and carbon dioxide sensing recorder (attach with temperature/humidity sensing, telaire 7001, telaire, usa) to measure the air temperature, humid ity and concentration of carbon dioxide in the pigsty. their planned locations are shown in the fig. 2. temperature/humid ity sensing recorders are located left front (lf), left rear (lr), right front (rf) and right rear (rr) separately, their height from the raising bedding is 80 cm, the height from the raising bedding is 25 cm for rear front down (rfd) and right rear down (rrd), the carbon dioxide sensing recorder is erected at the central location of p igsty, the height from the raising bedding is 90 cm, it is able to measure the central air temperature (tm), central relative humid ity (rhm) and concentration of carbon dioxide (co2) of central location in the pigsty simultaneously, both temperature/humidity sensing recorders and carbon dioxide sensing recorde r are configured to record the data once every 30 seconds. fig. 2 schematic image of temperature/humidity sensing recorders and carbon dioxide sensor location in enclosed pigsty advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 89 the stocking density of piglets in the pigsty is 1.77 pig/m 2 , it is assumed that the pigsty is fully enclosed and the air amount flowed into the pigsty (qin) is equal to the air amount flowed out from the pigsty (qout), while define the air change rate per hour (ach) in the enclosed pigsty is the times that the outside air amount of pigsty to replace the equivalent amount of volume space in the pigsty, its calculation formula is shown as eq. (1). ach = qv / v (1) in which, ach: air change rate in p igsty (time/hr), qv: air amount flowed into pigsty from outside of pigsty per hour (m 3 /hr), v: total volume of enclosed pigsty is 287.28 m 3 , when perform the ventilation and air change at the regular ventilation percentage of 10%, 20% and 30%, after conversion, its ventilation and air change rate is 1.7 ach, 3.4 ach and 5.1 ach separately. the hot-water temperature (tw) configured at experiment is 60°c, hot-water flow rate is 0.043 m 3 /min and the default temperature in the pigsty (tset) is 28°c, and collocate with the inverter fan control system to perform the ventilation and air change to maintain the air quality. as to the setting part of forced ventilation temperature, when the inside air temperature of pigsty is higher than the forced ventilation temperature, then start the inverter fan, continue to operate with the bleed air rate of 1.27 m 3 /s until the thermocouple temperature in the pigsty (tc) consistent with the forced ventilation temperature, and the stop. as to the setting part of regular ventilation percentage, the ventilation and air change cycle is once per 10 minutes, if the configured ventilation percentage is 10%, the inverter fan operates 1 minute and then stops for 9 minutes, if the configured ventilation percentage is 30%, the inverter fan operates 3 minutes and then stops for 7 minutes. the calculation method of temperature uniformity (tu) is to take the air temperature of different measuring location to subtract the air temperature of central location (tm) separately, then select the average value of two maximum air temperature difference, this average value is the temperature uniformity, shown as eq. (2). tu = (td1+td2)/2 (2) in which, td1: largest air temperature difference between different measuring location and central location (°c), td2: second largest air temperature difference between different measuring location and central location (°c). this research performs the ventilation and air change of enclosed pigsty by using the biogas burning hot -water heat preservation system collocated with the inverter fan, and performs the experiment in the pigsty with stocking density of 1.77 pig/m 2 , measures the air temperature, humid ity and concentration of carbon dioxide at d ifferent location in the pigsty, the forced ventilation temperature configured by the inverter fan is 28°c, and changes the air change rate of ventilat ion to 1.7 ach, 3.4 ach and 5.1 ach separately, from the calculated temperature uniformity, exp lore if the air temperature distribution in the pigsty is uniform or not, and illustrates if the air quality is suitable or not by the concentration of carbon dioxide in the pigsty. 3. results & discussion when the forced ventilation temperature is 28°c and air change rate of regular ventilat ion is 3.4 ach, the typical diagram of time variation of the right front (rf), right rear (rr) and right front down (rfd), right rear down (rrd) temperature in t he pigsty versus the outside temperature of pigsty (t0) for 4 consecutive days is shown as fig. 3, it can be seen from fig. 3a, the outside temperature fluctuation of t0 is more obvious in the day and night. the temperature of right front is slightly greater than temperature of right rear in the night which indicates that the pigsty has greater impact by the hot air blown from the air heater. however, on the whole, the temperature change of rf and rr is not much , it indicates that the overall temperature advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 90 change in the pigsty is quite stable. the temperature change of rfd and rrd can be considered as the temperature change of activity range for p iglets, therefore, it can be seen from fig. 3b, the temperature variat ion curves of rfd and rrd nearly overlap which indicates that the temperature change of activity range for the piglets in the overall pigsty is quite consistent. (a) rf, rr and outside temperature (to) (b) rfd, rrd and outside temperature (t o) fig. 3. typical d iagram of rf, rr, rfd and rrd versus outside temperature of pigsty (t0) for 4 consecutive days under 28°c for forced ventilation temperature and 3.4 ach for regular ventilation under the condition of 28°c for the forced ventilation temperature and 3.4 ach for the air change rate of regular ventilation, the typical diagram of time variation of the right front (rf), right rear (rr), left front (lf) and left rear (lr) temperature in the pigsty for 4 consecutive days is shown as fig. 4, it can be seen from the figure, the temperature ch ange of right front (rf) and left front (lf), right rear (rr) and left rear (lr) nearly overlap which indicates that the temperature change of left and right sides on the pigsty is quite consistent. fig. 4 typical d iagram of rf, rr, rr and lr versus outside temperature of p igsty (t0) for 4 consecutive days under 28° c for forced ventilation temperature and 3.4 ach for regular ventilation. advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 91 under the condition of 28°c for the forced ventilation temperature, the statistic table of temperature and relative humidity for the right front (rf), right rear (rr), left front (lf), left rear (lr), right front down (rfd) and right rear down (rrd) to the different air change rate of regular ventilat ion is shown as table 1. it can be seen that the temperature of each location in the pigsty is quite close to the defaulted temperature of 28°c in the p igsty which indicates that the temperature change in the overall pigsty is quite uniform and stable, however, the temperature of rfd and rrd is slightly lower than 28°c, its temperature difference is only 0.29°c ~1.39°c approximately. it can also be seen that since the location of rr and lr are more close to the inverter fan, rr and lr has higher relat ive humidity as relat ive to rf and lf, however, the relat ive humidity of piglet growth area (rfd, rrd) does not change along with the air change rate of regular ventilation i.e . maintains between 80%-89%. table 1 under 28°c for the forced ventilation temperature, at the d ifferent air change rate o f regular ventilation, the statistic table of temperature and relative humid ity for its right front (rf), right rear (rr), left front (lf), left rear (lr), right front down (rfd) and right rear down (rrd) temperature (°c) air change rate per hour (ach) relative humility (%) air change rate per hour (ach) 1.7 ach 3.4 ach 5.1 ach 1.7 ach 3.4 ach 5.1 ach rf 30.17±0.86 *1 29.57±0.84 30.09±0.74 rf 66.76±9.69 75.71±9.21 65.37±7.37 rr 28.29±0.39 28.71±0.40 28.24±0.28 rr 77.05±6.30 81.67±6.02 77.23±4.57 lf 29.93±0.73 29.44±0.71 *2 lf 69.26±9.05 77.91±8.74 *2 lr 28.32±0.44 28.82±0.43 28.02±0.30 lr 84.96±8.92 86.37±2.77 83.40±2.05 rfd 27.03±0.52 27.71±0.53 27.12±0.43 rfd 87.41±3.74 89.29±4.57 84.91±2.79 rrd 26.61±0.73 27.59±0.62 26.89±0.50 rrd 81.83±4.72 83.79±4.28 80.02±3.42 *1 : mean ± std *2 : lost data due to bit off by the piglets. under the condition of 28°c for the forced ventilation temperature and 3.4 ach for the regular ventilat ion, the typical diagram of central temperature (tm), concentration of carbon dioxide in the pigsty and outside temperature of pigsty (to) is shown as fig. 5. it can be seen from the figure, the central temperature (tm) does not have the great fluctuation along with the outside temperature change of pigsty, its temperature value stably maintains around 28°c. the concentration of carbon dioxide changes along with the t ime and has the significant fluctuation, it shall be relat ive to the lifestyle of p iglets. as shown in the figure, the sudden drop of carbon dioxide (arrow 1) is caused due to the owner entered into the pigsty to observe the night life situation of piglets; the sudden drop of rear section (arrow 2) is caused due to the owner entered into the pigsty for cleaning. fig. 5 typical diagram of central temperature (tm), concentration of carbon dioxide and outside temperature of pigsty (t0) for 4 consecutive days under 28°c for forced ventilation temperature and 3.4 ach for regular ventilation at the condition of 28°c for the forced ventilat ion temperature, the statistic of central temperature (tm), temperature error rate, central relative humid ity (rhm) and concentration of carbon dioxide (co2) in the pigsty under the different air change rate of regular ventilation is shown as table 2. it can be seen from the table, under the different setting of air change rate for regular ventilation, central temperature (tm) is stable between 28°c-29°c and the standard deviation is very small, it is indicated that the temperature change in the pigsty is quite s table, and the temperature error rate is around 1.93%-3.88%, this also indicates advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 92 that the temperature control of this heat preservation system is quite stable. the central relative humid ity (rhm) is stable between 73.11%-82.21% at different air change rate of regular ventilat ion, and the concentration of carbon dioxide is maintained under 1000 ppm. when the air change rate of regular ventilation is 5.1 ach, the concentration of carbon dioxide in the pigsty is very close to the outdoor concentration of carbon dioxide, the air quality in the pigsty is good. table 2 statistic of central temperature (tm), temperature error rate, central relat ive humid ity (rhm) and concentration of carbon dioxide (co2) in pigsty at 28°c for forced ventilation temperature under different air change rate of regular ventilation air change rate per hour (ach) 1.7 ach 3.4 ach 5.1 ach tm(°c) 28.49±0.52 29.09±0.46 28.79±0.31 e. r. * (%) 1.93%±1.68% 3.88%±1.65% 2.83%±1.12% rhm(%) 73.11±12.94 77.19±15.99 82.21±8.54 co2(ppm) 896.26±145.08 598.57±294.02 406.80±108.18 * e. r. : error rate (%) =[(tset-tm) /tset]*100% , tset =28°c take the measured temperature of rf, rr, lf, lr, rfd & rrd and the central temperature (tm) to perform the calculation of temperature uniformity, the results are shown as table 3, it can be seen from the table, at the defaulted temperature 28°c in the pigsty, the temperature uniformity of enclosed pigsty under different air change rate of regular ventilation is between 0.99°c -1.78°c, under the condition of 3.4 ach for the air change rate of regular ventilat ion and 28° c for the forced ventilation temperature have better temperature uniformity inside the pigsty. table 3 temperature uniformity in enclosed pigsty under the different air change rate of regular ventilation at 28°c for forced ventilation temperature air change rate per hour (ach) 1.7 ach 3.4 ach 5.1 ach temperature uniformity (°c) 1.78 0.99 1.6 4. conclusions the stoking density of piglets in the enclosed pigsty is 1.77 pig/m 2 , under the setting of 28°c for both defaulted air temperature and forced ventilation temperature in the pigsty, collocate with different air change rate of regular ventilation, i.e. 1.7 a ch, 3.4 ach and 5.1 ach to perform the experiment. the concentration of carbon dioxide at different air change rate of regular ventilation are lower than 900 ppm, it is able to stably maintain the temperature, relative humidity and concentration of carbon dioxide in the nursery, and achieve the effective heat preservation effect, and maintain the good air quality in the pigsty. when the air change rate of regular ventilation is configured as 5.1 ach, the concentration of carbon dioxide in the pigsty is quite close to the 400 ppm concentration of carbon dioxide outside the nursery, it is indicated that the air quality in the pigsty is very good. as known from the experimental results, this biogas burn ing hot-water system co llocating with inverter fan to perform the ventilation in enclosed the pigsty, the temperature change in the pigsty is quite un iform, apply to the heat preservation for the enclosed pigsty is feasible and efficient. references [1] p. v. rao, s. b. saroj, r. dey, and s. mutnuri “biogas generation potential by anaerobic digestion for sustainable energy development in india,” renewable and sustainable energy reviews , vol. 14, no. 7, pp. 2086-2094, september 2010. [2] m. van haren and r. fleming, “electricity and heat production using biogas from the anaerobic digestion of livestock manure-literature review,” university of guelph, ridgetown college, 2005. [3] j. b. holm-nielsen, t. a. seadi, and p. oleskowicz-popiel, “the future of anaerobic digestion and biogas utilization,” bioresource technology, vol. 100, no. 22, pp. 5478-5484, november 2009. advances in technology innovation, vol. 3, no. 2, 2018, pp. 86 93 copyright © taeti 93 [4] r. c. saxena, d. k. adhikari, and h. b. goyal, “biomass-based energy fuel through biochemical routes: a review,” renewable and sustainable energy reviews , vol. 13, no. 1, pp. 167-178, january 2009. [5] c. c. su, c. m. hong, m. t. koh, and s. y. sheen, “swine waste treatment in taiwan,” department of livestock management, taiwan livestock research institute, 1994. [6] h. pandorfi and i. j. o. da silva, “evaluation of the behavior of pig lets in d ifferent heating systems using analysis of image and electronic identification,” agricultural engineering international, 2005. [7] k. donham, p. haglind, y. peterson, r. rylander, and l. belin, “environmental and health studies of farm workers in swedish swine confinement buildings ,” british journal of industrial medicine, vol. 46, no. 1, pp. 31-37, january 1989. [8] a. j. heber, j. q. ni, b. l. haymore, r. k. duggirala, and k. m. keener, “air quality and emission measurement methodology at swine fin ishing buildings ,” transactions of the american society of agricultural engineers , vol. 44, no. 6, pp. 1765-1778, january 2001. [9] g. p. a. bot and j. h. m. metz, “measurement, evaluation and control of the microclimate in rooms for weaned piglets ,” in: a. v. van wagenberg, j. m. aerts, a. van brecht, e. vranken, t. leroy, d. berckmans, “climate control based on temperature measurement in the animal-occupied zone of a pig room with ground channel ventilation,” transactions of american society of agricultural engineers, vol. 48, pp. 111-125, january 2005.  advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 design and analysis of a water channel for characterization of low reynolds number flows judah d. rutledge, jesse j. french* department of mechanical engineering, letourneau university, longview, texas , usa. received 21 july 2017; received in revised form 05 september 2017; accepted 13 december 2017 abstact a water channel for performing flow v isualization and studying scale models in flu id mechanics was designed, analyzed, and fabricated with commercially availab le components . the material cost of the channel is 10% of the leading educational units, and the fabrication processes required for channel construction are basic and typical of local craftsmen in developing countries. both structural analysis and flow rate calculations were performed to verify the functionality of the tunnel. hand calculations and finite element analysis were used to model stress and deflection in the channel floor under hydrostatic loads. these were used to select a polycarbonate panel thickness that will withstand the hydrostatic and hydrodynamic loads on the channel floor and walls for a projected useful lifespan of 40 years. the water channel has a test section area that is 30 cm by 42 cm and up to 1 m long. the system pump is capable of generating incident flows of up to 7.1 cm/sec in the test section. the channel is also designed to be upgraded with a tow carriage, allowing for flow v isualization as well as fully submerged and partially submerged models with reynolds or froudes number dependent studies. keywords: fluid mechanics, aerodynamics, water tunnel, laminar flow, scale model, education 1. introduction in order to perform scale model tests that can be correlated with the behavior of prototypes in a real world environment, engineers make use of controlled environments to simulate or duplicate the conditions experienced by a component in operation. since in-situ testing can often be prohibitive in terms of both cost and time, significant time and attention are given to the scale model testing of prototype. additionally, scale models can be used to test and observe phenomena that are unmanageable or that happen at rates humans cannot typically observe in real time, be it a phenomenon that occurs in fractions of a second, such as vortices traveling down the length of a swept wing, or that takes months to develop , as in erosion case studies [1]. finally, scale models are invaluable for gaining deeper understanding of the physical phenomenon being explored. this application, in particular, is invaluable for higher education institutions. for products finding application in the realm of fluid mechanics, wind and water tunnels are the primary means for achieving the repeatability and control required for such tests. water tunnels, specifically, are used when testing phenomena related to marine or aquatic applications ; they are also used in aerodynamics when detailed flow visualizat ion is necessary. there are several companies that have designed excellent water tunnels for research and education [2]. however, these water tunnels can be expensive and difficult to acquire in developing nations . because of this, a water tunnel was designed using commercially availab le components with the end goal of manufacturing an adequate but affordable solution for studying fluid mechanics. such a tunnel design is affordable, can offer opportunities to smaller institutions in first world countries and to * corresponding author. e-mail address: jessefrench@letu.edu advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 102 institutions in developing countries worldwide, and benefits the local economy in the country of construction. this paper describes the economic considerations, the construction of this device, and the structural and flow analysis for the design. 2. manufacturing and cost a cad model h ighlighting standard water channel components of the channel assembly is shown in fig. 1 [3]. the channel structure is constructed in two separate components, both of which are welded out of a36 steel and powder-coated for corrosion resistance. the first component is the channel frame. the frame is constructed out of angle iron in the corners and reinforced with square tubing every 40 cm along the length of the channel to support the sidewalls and to mitigate deformation of the tunnel. these supports also serve to attach fixtures to the channel for model specific tests, for mounting photography equipment, or for attaching rails for a towing carriage or for wave generation. the second compone nt is the work bench. the work bench provides a stable work p lace for tests and supports the channel tank, which weighs 370 kilograms when filled to capacity. the bench has four adjustable feet which allow for accurate levelling of the channel assembly. th e channel itself is 2.4 meters long with a test section that is 100 cm long and a 30 cm x 40 cm. cross-section. the rectangular channel design simplifies construction, though some flow conditioning is lost without a contraction. fig. 1 cad model of the water channel assembly only materials and manufacturing methods commonly available in developing nations were used for constructing the channel. the work bench and frame were constructed with a36 rectangular steel tubing and powder coated to mitigate corrosion due to contact with water, though the appropriate primer and paint coat would also be adequate. the channel walls and floor were constructed from polycarbonate panels. the bench and frame were welded using gas metal arc weld ing, though the thickness of steel used can also be stick-welded or oxy-fuel welded if other forms of arc weld ing are not available. in order to resist distortion and leaking, the enclosure was bonded with scigrip 16, and sealed along the inner seams with a masterseal np1, a polyurethane sealant rated for continuous water immersion. the channel was plumbed with standard pvc pipes and fittings, and a centrifugal pump was sourced to power the flow loop. the total construction time of the channel from was 2.5 months. fig. 2 shows the finished channel with the flow conditioners in place. a cost analysis shows that the channel is highly affordable when compared to the typical cost of an educational water tunnel, which is in the $20,000 range. because labor for the construction was a portion of this project, only the material purchases are used to determine the baseline cost of producing a channel unit. the breakdown of material costs is shown in table 1. the total cost of producing the water channel is 1609.09 usd, which is roughly 10% of the cost for purchasing a commercially produced tunnel for education and research [4]. advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 103 fig. 2 completed water channel assembly table 1 material purchase costs for the water channel component unit cost q ty component cost .375x48x96" lexan sheet 567.00 1 417.00 .375x24x48 sheet 178.21 1 137.24 masterseal np1 tube 5.36 3 16.08 scigrip 16 can 12.51 1 12.51 teflon tape roll 1.48 1 1.48 silicone gasket unit 2.4 2 4.80 2 in x 10 ft pvc pipe unit 8.37 2 16.74 2 in socket female x npt male unit 1.17 2 2.34 2 in socket femal x npt female unit 1.2 2 2.40 2 in 90 deg elbow unit 0.98 6 5.88 pvc primer & cement pack 8.81 1 8.81 2 in threaded adaptor unit 1.32 2 2.64 pvc primer & cement pack 8.81 1 8.81 garboard drain plug unit 10.17 1 10.17 rubber gasket unit 12.91 2 25.82 pentair 011515 whisper flow unit 664.75 1 664.75 wiring cable feet 2.32 15 34.80 wiring plug unit 19.97 1 19.97 double pole toggle switch unit 5.98 1 5.98 switch junction box unit 5.95 1 5.95 8x32 stainless steel screws bag/24 6.48 1 6.48 3/8 inch bolt unit 1.61 4 6.44 1"x2"x14 gauge steel tubing 24' stick 31.00 3 93.00 .75"x.75"x11 gauge steel angle 24' stick 18.00 2 36.00 1"x1"x14 gauge steel tubing 20' stick 21.00 3 63.00 total cost 1609.09 3. structural analysis both hand calculations and finite element analysis (fea) were used for the structural analysis of the channel. aspects of the channel that were analyzed for failu re include crit ical components such as the table legs, the channel ribs, and the enclosure. material selection was performed based primarily on availability and cos t, and mathemat ical analyses were performed to determine if the selection was adequate. in order to guarantee that the tank geometry was not compromised, stress and distortion calculations were performed on the frame, the channel walls, the channel floor, and the work bench. advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 104 fig. 3 plate boundary conditions for floor and ends of channel fig. 4 hydrostatic pressure on water channel panel in most of the channel design, the limit ing factor was not structural integrity, but was instead deflection. even if the maximum stresses in a test fixture are relatively s mall, deflections in the structure can be sufficiently large to affect the geometry of the test section and introduce error in the test data. a secondary concern with deflection is the visual detect ion by the operator. visible deflection can detract attention from the test and reflect poorly on the quality of construction of the testing device. because of the magnitude of the deflections caused by the hydrostatic loads in the channel, visual deflect ion was the most prominent concern for all o f the items evaluated. the maximum deflection allowed for any channel co mponent was 0.1 inches (2.5 mm), which is detectable with measurement devices but is not a misalignment typically visib le upon simple observation. the stress and deflection calculations for the floor channel are presented here as a case study of the methods used. in order to choose the thickness of polycarbonate used for the channel floor and size, the floor panel between two support beams was modeled as a rectangular p late for maximum stress and maximum deflection calculations. both hand calculations were performed using roark’s formulas for stress and strain [5], and various fea models were created using comsol multiphysics 5.1. based on the frame geometry, the plate length and width for one section of the channel are 16 inches and 12 inches respectively. thicknesses of 1/4, 3/8, and 1/2 inch were considered for deflection and stress . since the channel walls were originally only going to be sealed, not bonded to the floor, they were not considered fixed to the floor, resulting in these sides being simply supported. where the panel is supported by a frame rib is considered fixed since the loading opposite of the span is nearly symmetrical. these boundary conditions, then, represent the most severe loading condition, that which is at the ends of the channel where three sides of the plate are simply supported, and only the side that is supported by a span of the tunnel is assumed to be cantilevered (fig. 3). for the hand calculations, table 11.4.3 was referred to in roark’s formulas for stress and strain . this describes the maximum stress and maximum deflection as a function of plate geometry, the material properties, and an applied, constant pressure. because the maximum deflection and stress in plates with straight boundaries are determined numerically, no expression for deflect ion and stress as a function of position is derived. instead, the dimensionless ratio, 𝑎/𝑏 is used to characterize plates through a range of aspect ratios and derive empirical constants used in conjunction with the plate thickn ess and material properties to estimate maximum stres s and deflection according to eqs. 4.1 and 4.2. 2 2max qb t    (1) 4 3   max qb y et   (2) here 𝑞 is a constant hydrostatic pressure equal to the depth of the water times its specific gravity (fig. 4), 𝐸 is young’s modulus, and 𝑏 and 𝑡 are the width and thickness of the plate, respectively. the final variab les in these equations, 𝛽 and 𝛼, are functions of the aspect ratio, 𝑎/𝑏 , and are determined by interpolating values from table 11.4.3 in roark’s. the provided tables are fo r a poisson’s ratio of 0.3. according to the handbook, the returned deflect ion will be accurate to with in 8%, and the maximum calculated stress to within 15% [5]. advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 105 fig. 5 fea results for stress distribution on for the channel floor (psi) the same boundary conditions and geometry were used for the fea analysis using comsol. since roark’s analysis is based on a poisson’s ratio of 0.30, and the actual poisson’s ratio for polycarbonate is 0.37, fea mode ls were run for both poisson’s ratios of 0.3 and 0.37 in order to compare the effects of poisson’s ratio on the stress and deflection and determine if roark’s can still be used as an accurate approximation (fig. 5). the hand calculations and the fea models showed a lower correlation for the maximum displacement (table 2), but high correlation for the maximum stress (table 3). the maximum error between roark’s and comsol for a po isson’s ratio of 0.30 was 3% for stress and 18% for displacement. modifying po isson’s ratio did not significantly affect the stress or displacement, changing the stress and displacement values by about 1% and 5% respectively. based on this, the tables in roark’s handbook for stress and strain of rectangular plates can be used for similar designs where an fea package is not available. the most important result from this analysis, however, is that the displacement of both the 3/8 inch and the 1/2 inch panel is within the allowable limit of 2.5 mm. since the 3/8 panel fulfilled the strength and deflection requirements, and the cost difference between the 3/8 inch and the 1/2 inch panels was significant, the 3/8 inch panel was selected for the channel enclosure. table 2 maximum deflection for channel floor [mm] roark’s comsol (nu = 0.30) comsol (nu = 0.37) percent difference [%] cm vs. r (nu=0.30) nu=0.30 vs. nu=0.37 1 /4 inch 3.83 4.47 4.24 14.3 5.4 3 /8 inch 1.13 1.34 1.27 15.7 5.5 1 /2 inch 0.47 0.572 0.542 17.8 5.5 table 3 maximum stress for the channel floor [kpa] roark’s comsol (nu = 0.30) comsol (nu = 0.37) percent difference [%] cm vs. r (nu=0.30) nu=0.30 vs. nu=0.37 1 /4 inch 5615 5587 5559 0.5 0.5 3 /8 inch 2495 2424 2450 2.9 1.1 1 /2 inch 1413 1401 1414 0.9 0.9 because the prolonged loading nature of a hydrostatic pressure vessel makes such structures susceptible to creep when constructed from polymers, a creep rupture stress analysis was also performed on the panel [6]. a literature review for the creep rupture properties of polycarbonate showed that available plots only predicted the creep rupture strength out to 45,000 hours, or approximately 5 years [7]. however, since the creep rupture stress curve for polycarbonate showed a highly linear trend on a logarithmic scale, an ext rapolation out to one more order of magnitude was also performed. these estimat ions predicted that the panel has a very high factor of safety with respect to creep rupture over the channel’s design life. the creep rupture strength at five years is 49,000 kpa, and the estimated the rupture strength decreases to 43,000 kpa at 40 years of continuous loading. still, the panel stress at 40 years is only 6% of the estimated rupture strength for this loading period. this estimation produces a factor of safety of 16.7, ind icating that the channel floor and walls are not at risk of failing due to creep. advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 106 4. flow rate analysis when determining the channel flow rate, two systems were considered: a pump providing constant flow rate and a surge tank which could potentially provide higher flow rates for a short period of time. the flow rate calculat ions for both systems were performed based on the dynamic head source and pipe and fitting frict ion factors determined from the literature. because the pump and hardware used were specified in english units, all head and flow rate calculations were performed in the same, and the final flow velocity in the channel test section was then converted into centimeters per second. 4.1. surge tank flowrate the surge tank flow rate calculations were performed for a surge tank located nominally 10 feet (3 m) above the pipe entering the channel. this head was assumed to be constant, regardless of the level of water in the 200 liter drum chosen as the surge tank. in order to calculate flow rate, an energy balance was performed between the barrel outlet and the channel inlet using the dynamic head, elevation change, and frictional loss coefficients for each component in the system (eq. 3). here, 𝑃/𝛾 is the dynamic head, 𝑙 and 𝐷 are the length and diameter of the pipe, and 𝑓 and 𝐾𝐿 are frictional loss coefficients (fig. 6). the loss coefficients for pipe fittings, ∑𝐾𝐿 , are reynolds number independent and obtained from tables in fundamentals of fluid mechanics by munson, et. al. [8]. the loss coefficient in the pipe, 𝑓, is reynolds number dependent and was determined using the method outlined by lewis. f. moody for pipe flow friction factors [ 9]. as recommended by munson, et. al., the pipe was assumed to be smooth, therefore the ratio of the equivalent roughness pipe diameter, 𝜖/𝐷 , was equal to zero. 22 2 2 1 1 2 2 1 2 2 2 2 2 l k vp v p v l v z z f g g d g g          (3) velocity at the entrance and exit of the pipe is constant, and the equation simplifies to: 22 1 2 2 l k vl v f d g g z    (4) from this, the velocity of the water in the pipe can be solved for as: 1 2 2 l p z g l f k d v   (5) fig. 7 shows the iterat ive process used for calculating water velocity in the channel pipe. first, a frictional loss coefficient, 𝑓(𝑅𝑒 ), is assumed. from this, the velocity in the pipe is calculated using eq. 5, and the flow reynolds number is calculated for this velocity and pipe diameter: ( ) p dv re v    (6) fig. 6 surge tank geometry and loss coefficients fig. 7 logic diagram for determining velocity from constant head advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 107 by referring to a moody flow chart, this reynolds number is then used to determine a new frictional loss coefficient. this process is repeated until the loss coefficient converges to a value. the last calculated velocity is then the velocity in the p ipe and is used to determine the flowrate in the water channel. using this approach, the pipe flow velocity was determined to be 233 in/s in the channel pipes, which corresponds to a speed of 8.3 cm per second in the water tunnel. 4.2. pump flowrate the pentair whisperflo 011515, rated at 1.5 kw of power, was selected as the second candidate for running the water channel. the flow rate generated by the pump in the water tunnel is calculated with a procedure similar to that used for the surge tank calculations, the primary d ifference being that a pump does not provide a constant head. therefore, the pump head, 𝐻(𝑄), had to be incorporated into the iterative solution for channel flow. the dynamic head generated by a pump is dependent on flow rate, which introduces another step in the iterative process used to determine the speed of the water channel. since a dynamic head, 𝑃1 /𝛾, is present because of the pump, but there is no net change in elevation by the water across the flow loop (fig. 8), eq. 3 takes on the form: 22 1 2 2 l k vp l v h f d g g     (7) in order to determine the flow rate generated by the whisperflo 011515, the dynamic head was assumed to be equal to the head drop across the piping of the water tunnel, and the pressures at the entrance and exit of the channel were assumed to be equal to atmospheric pressure. because flow rate, head, and viscous friction are interrelated, an iterat ive solving approach was once again implemented (fig. 9), where the flow rate was determined from the pump performance curve fo r the whisperflo 011515 (fig. 10). in order to solve for the flowrate, a dynamic head of 20 ft was assumed, and the flowrate was determined from the pump performance curve. the pipe frict ion factor was calcu lated from the moody chart for this reynolds number, and the actual head was calculated from 𝑉𝑝 and 𝑓. flow rate was determined for this new calculated head, and the process was iterated until the calcu lated head converged to 10.9 ft o f water. from this head, the velocity in the pipes was determined to be 208 in/s, and the calculated speed in the water channel was 7.4 cm/s. according to these calculations, the surge tank and the whisperflo generate water speeds in the channel that vary by only 0.9 cm/second. therefore, there is no significant advantage to constructing a surge tank for attaining greater flow rates. additionally, implementing a surge tank requires the design, construction, and space allocation of a tower to support the wat er, and a surge tank will not generate a truly steady flow, since the level in the surge tank changes the actual head by 40% as it drains. finally, this design would not be capable of continuous operation, would require significant modificat ion to change the functionality from a flow channel to a tow channel and would still require the purchase of a pump to move water from the bottom reservoir up to the surge tank. since all of these factors are resolved by using a pump to continuously power the syst em, and the flow rate gain from using a surge tank is negligib le, a pump was selected as the head source for generating flow in the water channel. these calculations were validated after the channel was completed. the flow velocity distribution had a maximum speed of 7.1 cm/second in the center and 5.6 cm/second near the walls within the boundary layer. fig. 8 channel pump head and loss coefficients fig. 9 logic d iagram to calcu late velocity generated by pump advances in technology innovation, vol. 3, no. 3, 2018, pp. 101 108 copyright © taeti 108 fig. 10 performance curve for the pentair whisperflo line of pool pumps. curve i corresponds to the model 011515 [10] 5. conclusions a water channel for flow visualizat ion and scale model testing was successfully designed and manufactured using components and manufacturing methods that are globally availab le. structural analysis and flow rate calculations were used to predict tunnel performance based on available materials. a high correlation was found between fea models and the hand calculations using standard texts. flow estimat ions using pipe flow and pipe fitt ing friction factors were used to predict the dynamic head source for the water channel. maximum flow rate calculations correlated closely to measured velocities in the test section. the frame and work bench are welded from mild steel, and the channel t est section is constructed from clear polycarbonate. the channel workbench footprint is one meter wide and 2.4 meters long, and the test section is 100 cm long with a 30 cm x 40 cross-section. the total cost of materials for manufacturing the channel was 1609.09 usd. this water channel provides an economic alternative for education or basic research of low reynolds number flows. references [1] r. i. emori and d. j. schuring, scale models in engineering: fundamentals and applications, great britain : a. wheaton & co. ltd., 1977. [2] rolling hills research, “water tunnel model 0710,” www.rollinghillsresearch.com/water_tunnels/model_0710.html [3] engineering laboratory design, inc., “water tunnels,” http://www.eldinc.com/pages/0246;watertunnels/ [4] y. farsiani and b. r. elb ing “characterization of the custom-designed, high reynolds number water tunnel,” proc. of the asme fluids engineering division meeting, 2016. [5] w. c. young and r. g. budynas, flat plates, 7th ed. new york: mcgraw hill, 2002. [6] j. jansen, “understanding creep failure of plastics,” plastics engineering, society of plastics engineers, 2015. [7] p. j. gramann, j. cruz, and j. a. jansen, “lifetime prediction of plastic parts,” proc. in annual technical conference, 2012, pp. 1313-1318. [8] b. r. munson, d. f. young, and t. h. okiishi, “fundamentals of fluid mechanics dimensional analysis of pipe flow,” 6th ed. new jersey: john wiley & sons, inc., 2002. [9] l. f. moody, “friction factors for pipe flow,” transactions of the american society of mechanical engineers, pp. 671-682, 1944 [10] whisperflo high performance pump, “whisperflo curves,” http://www.pentairpool.com/products/index.html.  advances in technology innovation, vol. 2, no. 4, 2017, pp. 113 118 113 securing ad hoc wireless sensor networks under byzantine attacks by implementing non-cryptographic methods shabir-sofi1,*, roohie-naaz2 1 department of information technology, national institute of technology srinagar, india. 2 department of computer sciences & engineering, national institute of technology srinagar, india . received 10 december 2016; received in revised form 16 february 2016; accepted 08 march 2017 abstract ad hoc wireless sensor network (wsn) is a collection of nodes that do not need to rely on predefined infrastructure to keep the network connected. the level of security and performance are always somehow related to each other, therefore due to limited resources in wsn, cryptographic methods for securing the network against attacks is not feasible. byzantine attacks disrupt the communicat ion between nodes in the network without regard to its own resource consumption. this paper discusses the performance of cluster based wsn comparing leach with advanced node based clusters under byzantine attacks. this paper also proposes an algorithm for detection and isolation of the compromised nodes to mit igate the attacks by non-cryptographic means. the throughput increases after using the algorithm for isolation of the malicious nodes, 33% in case of gray hole attack and 62% in case of black hole attack. keywords : byzantine attacks, cluster based wireless sensor network, advanced node, gray hole, black hole, non-cryptographic 1. introduction wireless sensor network (wsn) is a type of ad hoc networks having large number of the nodes. the nodes of the wsn may be static or mobile as in case of other ad hoc networks. the wireless sensor networks pose unique challenges as the sensor nodes are limited in their energy, computation and communicat ion capabilities. a lso, the sensor nodes are deployed in inaccessible areas to monitor physical environment. the sensor nodes may be thousands in number to co llect ively monitor an area. as a result, the existing security mechanisms are inadequate [1]. since all the nodes in an area usually detect common phenomenon, this leads to high data redundancy. to save energy and prolong network lifetime, an efficient way is to aggregate the raw data before they are transmitted to the base station as the sensor nodes are resource limited and energy constrained. data aggregation is an essential paradigm to eliminate data redundancy and reduce energy consumption [2-3]. the level of security and performance are somewhat related to each other. a wsn applicat ion usually requires different functionalities, sensing, storing data, and data communicat ion. sensing usually require a large number of nodes to ensure coverage and few resources on each node. in contrast, data transmission and data storage require more system resources. data aggregation is an essential parad igm to eliminate data redundancy and reduce energy consumption. the data ag-gregation is used in wsn to reduce the communication overhead and prolong the network lifetime. however, an adversary may compromise some nodes and use them to forge false values as the aggregation result. for securing data aggregation, we need to detect the malicious nodes which add to overhead due to encryption, decryption and sharing of keys. tiered network design with functional partit ion prolongs network lifet ime instead of homogeneous network. clustering in wsn, where groups of sensor nodes select their cluster head depending on the energy level [4, 14] or in some applications the cluster can be fixed at the time of deployment [5]. whether the cluster head is pre-decided or selected by the individual nodes of the group the network will be ad hoc in either case. for many applicat ions, the sensed readings are sens itive and thus demand for data security, confidentiality, integrity and freshness. however, the tight resource constraints of wireless sensors restrict the adoption of traditional computation intensive algorithms. a compromised storage agent may reveal its saved readings, drop important readings, compose forged data readings and reply old data readings. without carefully designed security enhancements, the above attacks can leave the network useless in a hostile environment. there is no secure boundary in ad hoc networks, making the network susceptible to attacks, since ad hoc networks suffer from all-weather attacks which may come from any node in the network. there are other link attacks also which can jeopardize the ad hoc network [6]. these include eavesdropping, active interfering and leakage of secret informat ion, data tampering, message reply, message contamination and denial of service attacks . the attacks where aim is to gain control over wsn nodes by some unrighteous means and then using these compromised nodes to execute further malicious actions. the threats of such attacks are usually from inside the network and these threats are more dangerous than the threats from outside the network. these attacks are diff icult to detect as they come from compromised nodes , which behave well before they are compromised. a good example of this type of threats comes from the potential byzantine failures encountered in the routing protocol for the ad hoc networks. in a byzantine failu re, a set of nodes are compromised in such a way that the incorrect and malicious behaviour cannot be directly detected because of the cooperation among these compromised nodes when *corresponding author. email: address:shabir@nitsri.net tel.: +91-9419009971 advances in technology innovation, vol. 2, no. 4, 2017, pp. 113 118 114 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti they perform malicious behaviours. the compromised nodes may seemingly behave well; however they may actually make use of the flaws and inconsistencies in the routing protocol to undetectable destroy the routing fabric of the network, generate and advertise new routing information that contain non-existent link, provide fake link state information, o r even flood other nodes with routing traffic. it is common in ad hoc networks that benign failures such as path breakages, transmission impairments and packet dropping, happen frequently. hence malicious failures will be more difficult to detect especially when adversaries change their attack pattern and their attack target in different periods of time. 1.1. attacks in ad hoc networks there are numerous types of attacks in ad hoc network, which may be classified into two types, external attacks and internal attacks. external attack, in which the attacker aims to cause congestion propagate fake routing informat ion or d isturb nodes from providing services. in internal attack, in which the adversary wants to gain access to the network act ivities, either by some impersonation or by directly compromising a current node and using it as basis to conduct its malicious behaviors [7]. in an internal attack adversary can capture some nodes in the network and make them look like benign nodes, these nodes join the network as the normal nodes and begin to conduct the malicious behaviors like propagating fake routing informat ion and begin inappropriate priority to access some confidential informat ion [22]. the internal attacks are sometimes more severe threat to the security than external attacks as they are difficult to detect at an early stage. 1.2. routing attacks routing attacks are classified into two categories: attacks on routing protocols and attacks on packet forwarding. the main influences brought by the attacks on routing include network partit ion, route loop, resource deprivation and route hijack. because of the mobility and constantly changing topology of the mobile ad hoc networks, it is very difficult to validate all the route messages as a result, impersonating another node to spoof route message, advertising false route metric to misrepresent topology, flooding route discovery, modifying route reply message, generating bogus route error to disrupt a working route, suppressing route error to mislead others may occur. in packet forwarding/delivery selfishness and denial-of-serv ice are the two main strategies applied for the attack. 1.3. byzantine attacks when a network device suffers a byzantine fault it is assumed to be controlled by an adversary who uses the device to disrupt the network [16]. the goal of the byzantine node is to disrupt the communicat ion of other nodes in the network, without regard to its own resource consumption. these cause byzantine failu res which include the omission failures and commission failures. as for instance in omission failures if a node fail to receive a request or fail to send a response and in commission failures if a node process a request incorrectly or sending an incorrect or inconsistent response to a request. in ad hoc networks, the byzantine attacks are as: black hole attack, gray hole attack, flood rushing attack and wormhole attack. wireless sensor networks are favorite targets of byzantine attacks because of their limited dynamic topology etc. [21]. 1.4. black hole attack it is a basic byzantine attack [9] where adversary stops forwarding data packets, but still participates in the routing protocol correctly. as a result, whenever the adversarial node is selected as part of a path by the routing protocol, it prevents communication on that path. most routing protocols are disrupted by black hole attacks because they render the normal methods of route maintenance useless . 1.5. gray hole attack it is a special case of black hole attack where an attacker could create a grey hole, in which it is selectively drops some packets but not others, for example forwarding some packets but not data packets[10]. 1.6. wormhole attack if more than one node is compromised, it is reasonable to assume that these nodes interact in order to gain an additional advantage. this allows the adversary to perform a more effective attack. one such attack is byzantine wormhole where two adversaries tunnel packets between each other in order to create a shortcut (or wormhole) in the network. the adversaries can send a route request and discover a route across the ad hoc network, then tunnel packets through the non-adversarial nodes to execute the attack. the adversaries can use the low cost appearance of the wormhole links in order to increase the probability of being elected as part of the route and then attempt to disrupt the network by dropping all of the data packets. the wormhole attack is strong attack which can be performed even if only two nodes are compromised. 1.7. flood rushing attack a flood rushing attack [12] explo its the flood duplicate suppression technique used by many routing protocols. this attack takes place during the propagation of legit imate flood and can be seen as a “race” between the legitimate flood and the adversarial variant of it. if an adversary successfully reaches some of its neighbors with its own version of the flood packet before they receive a version through a leg itimate route, then those nodes will ignore the legitimate version and will propagate the adversarial version. th is may result in the continual ab ility to establish an adversarial-free route, even when authentication techniques are used. when a node wants to send a packet, it will send route request packet and if it receives a route reply first from a normal behaving node, then everything will work fine. however, if it gets reply from an attacker node, all the packets will not reach the destination or there may be selective dropping. in both the cases the delivery ratio will decrease. therefore, identification of such nodes is the first step in preventing their participation in the data transfer. also, a route reply from an attacker node can advances in technology innovation, vol. 2, no. 4, 2017, pp. 113 118 115 copyright © taeti reach the source node earlier than a normal node if it is near to the source node. since each node in a homogeneous wsn, acts as router, the data transmission from source to the gateway occurs via different sensor nodes, while in case of heterogeneous network the indiv idual nodes may or may not participate in the routing process . the homogenous wsn can be treated as a special case of ad hoc networks where the number o f nodes is very large as compared to the ad hoc network. the detection and isolation of an attacker node is difficult. also, the packet delivery ratio will be lesser. in heterogeneous wsn the nodes are grouped in clusters and each node in the cluster transmits its data via the cluster head (ch) [4, 14]. since the nodes in cluster are fewer as compared to the nodes in a homogeneous wsn the chances of detection and isolation of the attacker node are more. karlof et al. [13] proposed selective forwarding attack for the first time in wireless sensor networks and suggested that multipath forwarding to counter the attack. but, the algorithm fails to suggest a method to isolate the attacking node. marti et al. [11] p roposed a technique called watchdog, in which a node continuously monitors the neighboring nodes to which the packet is sent and to check whether the packet is fo rwarded or not. but the algorithm fails to detect the attacker in the presence of selective forwarding attack. 2. comparison leach and advanced node in fig. 1, leach vs. advanced node based network the probability of sustaining the black hole or gray hole attack is more in the advanced node based network as compared to leach based network. also the life cycle of the nodes in advanced node based network is more than the leach based network. during the cluster head s election process and after becoming cluster head the node consume almost n+1 times the energy consumed by an individual sensor node. since data aggregation as well as the routing of the other informat ion from and to the nodes is carried through the cluster head, in addition to its own sensing and data transmission which leads to quicker energy depletion. fig. 1 advanced node based protocol vs. leach protocol. (energy in mah and time in days with 1 hour operation for each sensor node) 3. results and discussion in this work, we develop a non-cryptographic type of defense by checking the forwarding of the upstream nodes by overhearing their transmission. we consider ad hoc on demand vector routing protocol to implement these attacks. in the black hole attack, a node will part icipate in routing but will drop all the packets it receive [11]. the malicious node will always advertise in the network that it has a fresher route to the destination by setting the s equence number to a large value and will reply to the broadcast route request packet before other nodes send a reply. thus, the attacker node will attract all the traffic in its transmission range towards itself and then drop the packets. this type of situation will decrease the packet delivery rat io, but at the same time the energy of the black node will decrease rapidly resulting in self-immolation of the node. however, during the time of the data transmission the other nodes which send the packet to the black node will result in decrease of their energy due to repeated transmissions for the same packet. th is will decrease their energy and result in reduced life cycle of the node. in gray hole attack, the attacker node drop selective packets according to some criteria or randomly [4]. this type of attack is difficult to detect, especially in wireless scenario where packets are dropped because of the congestion, channel capacity etc. this algorithm is based on the probability of attack which depends on the ratio of number of packets to the number of packets transmitted. if the probability of attack is greater than the probability of black hole attack and it is true twice then the attack is black hole attack and if the probability of attack is greater than the probability of gray hole attack and it is true twice then the advances in technology innovation, vol. 2, no. 4, 2017, pp. 113 118 116 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti attack is gray hole attack. after the detection of the attack all the nodes are sent a broadcast not to include the node in any future routing for transmission of packets. the complete algorithm for different scenario is given as under: scenario: (as shown in fig. 2) case 1: homogeneous ad hoc or wireless sensor network wireless sensor network is a large network of sensors which have the ability to communicate with each other. these sensor nodes are transmitting the data from one sensor to another for further transmission to the sink node. in ad hoc networks ad hoc on demand vector is a source initiated advanced on demand routing protocol. each sensor node has a routing table that stores the information of the next hop node to route the destination. when a source node wants to route a packet to sink node, it uses the specified route if a fresh route to the sink is not available otherwise it will update its table for shortest route by the route discovery using route request message to its neighboring nodes. in gray-hole attack the malicious node selectivity or randomly forwards packets passing through it. sink node after receiving packet from the source node, unicast (route reply) message en-route neighboring node from which it receives the packet. in black-hole attack, the malicious node pretends as if it has the shortest path to the sink node and drops all the packets. case 2: heterogeneous wireless sensor network with leach based cluster head the wireless sensor network is partitioned into clusters and each cluster consists of a group of sensor nodes which may or may not transmit data to the destination via the neighboring nodes. mostly, the nodes communicate directly with the cluster head. the cluster head is chosen which is having the maximum energy level amongst the cluster nodes. as in leach the process of selecting or electing a cluster head is repeated after a certain interval of time. the number of nodes in a cluster is less as compared to the case 1 [14]. but the gray-hole and black-hole attack is possible if the nodes communicate with the cluster head via intermediate or neighboring nodes. also, the attacks are possible if the node which acts as cluster head is compromised. the severity of the attack may be manifold as all the data packets from each and every node will be dropped. case 3: heterogeneous wireless sensor networks with advanced node as cluster head the wireless sensor network is partitioned into clusters as in case of case 2 but the cluster head is predefined and the advanced node which acts as a cluster head is presumed to have higher energy, processing power and range [5] as compared to the normal sensor nodes. the possibility of gray-hole and black-hole attacks is less as compared to the case 1 or case 2. as it will be difficult to compromise the cluster head which is responsible for the transmission of the data from the nodes to the gateway. all the nodes will directly communicate with the cluster head, but as a special case the nodes may also communicate with the cluster head via the intermediate or neighboring nodes within that cluster. in the earlier case, the probability of compromising a node is lesser. also, it is possible to use the cryptographic algorithms like key exchange mechanisms between the nodes and the cluster head during data transmission. 4. algorithm for detection and isolation of byzantine nodes by non-cryptographic methods in either case of byzantine attacks, gray-hole o r black-hole attack, the detection of the type of attack is first step. after we know the type of attack our next pr iority is to identify the compromised nodes in the network. the algorithm detects these nodes by non-cryptographic methods, checking the forwarding of the nodes by overhearing their transmission and isolation of these nodes so that cannot take part in routing. the scenario is shown in fig. 2. fig. 2 gray-hole and black-hole attack detection and isolation scenario 4.1. assumptions before the implementation of the algorithm we have taken certain assumption. since there are many other factors which could cause the change in the throughput which we have taken as solely by the byzantine attacks. like con-gestion due to buffer overflow is not insignificant, as we need to restrict the upstream node from delivering packets when the downstream node does not have sufficient space. (b) in p ractical cases black hole attack may not drop all the packets; it has its dependence on other factors as well. (c) as the signal power decreases the range is also decreased, but in case of wsn, the nodes are at a very short distances for a decrease in energy is not affected too much extend as compared to long distance communication. (d) in multi-hop communicat ion each node maintains the table of the routing informat ion during the transmission of packets, but here each node will be having additionally the attack table, this may add some overhead to the packets . a. no packet is dropped due to buffer overflow b. black-hole attack drops all the packets it receives c. range is not getting affected by decrease in the energy level of a node d. each node will maintain an attack table notation and parameters nid node identifier nt total no. of packets transmitted by a node nd total no. of packets dropped by a node nl total packet loss nl= ntnd pa probability of packets successfully received pb probability of presence of black-hole pg probability of presence of gray-hole pa= nl/ nt nr reporter node na attacker node ch cluster head cid cluster id advances in technology innovation, vol. 2, no. 4, 2017, pp. 113 118 117 copyright © taeti 4.1.1. algorithm for homogeneous network for a particular interval: 1. calculate value ofnl nl = nl nd; 2. define values of pb and pg //threshold values as per the scenario 3. calculate pa pa = nl/ nt; 4. if (pa >= 2pb){ then broadcast packets to all ns and rs with nid of both reporter node and attacker node. type –of-attack = b;} else if (pa >= 2pg){ broadcast packets to all ns and rs with nid of both reporter node and attacker node. type-of-atack = g;} else if (pa>pg and pa >pb){ broadcast packets to all ns and rs with nid of both reporter node and attacker node. type-of-attack = g;} else{ print(“no attacker node found”); and broadcast nid of sender node to all ns and rs”. type-of-attack = nil;} 4.1.2. algorithm dedicated cluster head assumption is that cluster heads are pre assigned with identified cluster nodes. for a particular cluster and for a particular interval: 1. assign a node cid with maximum power 2. calculate value of nl for that particular cluster nl = nt – nl; 3. define value of pb and pg for a cluster 4. calculate pa pa = nl/nt; 5. if (pa >= 2pb){ broadcast packets to all ns, rs and ch with nid of both nr and na type-of-attack = b;} else if (pa >= 2pg){ broadcast packets to all other ns, rs and ch with nid of both nr and na type-of-attack = g;} elseif (pa >pg and pa >pb){ broadcast to all ns, rs and chs of cluster with n id of both nr and na type-of-attack = g;} else{ print (“no attack found”) 4.1.3. algorithm heterogeneous network assumption is that network is div ided into clusters <=100. for a part icular cluster and for a part icular interval: 1. choose a node randomly as ch and assign cid 2. calculate value of nl for that particular cluster nl = nt – nd; 3. define value of pb&pg for a cluster. 4. calculate pa pa = nl/nt; 5. if (pa >= 2pb){ if (attacker nid = cid of ch){ broadcast packets to all other chs with cid of attacker ch type-of-attack = b;} else { broadcast packets to all ns, rs and ch with nid of both nr& na. type-of-attack = b;} elseif( pa>= 2pg){ if (attacker nid = cid) { broadcast packets to all chs with cid of attacker ch type-of-attack = g;} else{ broadcast packets to all ns and rs and to ch of cluster with nid of both nr and na type-of-attack = g;} } else if (pa>pg and pa>pb){ if(attacker nid = cid){ broadcast packets to all other chs with cid of attacker ch type-of-attack = g;} else{ broadcast packets to all ns, rs& ch with nid of both nr and na type-of-attack = g;} } else{ print(“no attack found”); and broadcast nid of sender node to all ns, rs and chs type-of-attack = nil; } 5. results based on the algorithm for detection and isolation from the simulation results as is evident from the fig. 4 throughput vs. time. in itially, we simulate the network with no attack; the throughput is 90-95%. then, as we introduce the black hole attack in the network, throughput decreases to 3%-5%. now, as the network uses the isolation algorithm, throughput increases to 67%. similarly in advances in technology innovation, vol. 2, no. 4, 2017, pp. 113 118 118 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti case of gray hole attack, initially we simulate the network without attack and the throughput is 90-95%. then, we introduce the gray hole attack and the throughput decreases to 35%-50%. after using the isolation algorithm the throughput increases to 88%. fig. 3 time(s) vs. throughput (%) fig. 4 time vs. throughput (%) 6. conclusion as shown in fig. 3 and fig. 4, there is remarkab le improvement in the throughput after using the proposed al-gorithm for isolation of the malicious nodes. the algorithm will be more suited to the applications were we require to have energy efficient design. since the algorithm is a non-cryptographic one and purely depend on the probability of packets successfully received, therefore probability of presence of black hole nodes and probability of presence of gray ho le nodes may vary in some cases. but the algorithm will be useful for the sensor networks where we can't use the cryptographic algorithms to tackle the security problem due to the fact that increased processing and communication time will increase the energy consumption. if we part itioned the network into clusters then the gray hole or the b lack hole attack will remain confined to its own cluster only without affecting the other clusters in the network till the cluster head itself is not compromised. but if we use the advanced node in the network as a cluster head then the probability of cluster head to be compromised will be lesser due to the fact that the node is predefined cluster head and we can also use the cryptographic mechanis ms like the key exchange etc. for secure transmission with the processing to be done centrally at the cluster head (advanced node), as it is having higher processing, communication and energy as compared to the member nodes of the cluster. references [1] a. perrig, j. stankovic, and d. wager, “security in wireless sensor networks,” communication of the acm, vol. 47, no. 6, pp. 53-57, june 2004. [2] d. estrin, r. govindan, and j. heidemann, s. kumar, “next century challenges: scalable coordination in sensor networks,” proc. acm international conf. mobile computing and networking, acm press, 1999, pp. 263-270. [3] y. yu, b. krishnamachari, v. k. prasanna, “energy-latency tradeoffs for data gathering in wireless sensor networks,” proc. ieee computer and communication societies, ieee press, 2004. [4] s. e. khediri, n. nasri, a. wei, and a. kachouri, “a new approach for clustering in wireless sensors networks based on leach,” procedia computer science, vol. 32, pp. 1180-1185, 2014. [5] s. a. sofi and r. naaz, “energy efficient routing protocol for structured deployment of wireless sensor networks,” international conf. next generation networks, iet press, september 2010, p. 10. [6] s. sofi, e. malik, r. baba, h. baba, and r. mir, “analysis of byzantine attacks in ad hoc networks and their mitigation,” international conf. computing and information technology, february 2012, pp.794-799. [7] w. li and a. joshi, “security issues in mobile ad hoc net works a survey,” https://pdfs.semanticscholar.org/b221 /99c61df5445836c5f1bbd0ea6f02dabefd6b.pdf, 2007. [8] y. c. hu, a. perrig, and d. b. johnson, “rushing attacks in wireless ad hoc network routing protocols ,” proc. 2nd acm workshop on wireless security, acm press, 2003, pp. 30-40. [9] c. karlof and d. wagner, “secure routing in wireless sensor networks: attacks and countermeasures,” ad hoc networks, vol. 1, no. 2, pp. 293-315, 2003. [10] s. marti, t. j. giuli, k. lai, and m. baker, “mitigating routing misbehavior in mobile ad-hoc networks,” proc. 6th annual international conf. mobile computing and networking, pp. 255-265, august 2000. [11] h. li, k. li, w. qu, and i. stojmenovic, “secure and energy efficient data aggregation with malicious aggregator identification in wireless sensor networks,” future generation computer systems, vol. 37, pp. 108-116, 2014. [12] y. zhao, y. zhang, z. qin, and t. znati, “a co-commitment based secure data collection scheme for tiered wireless sensor networks,” journal of systems architecture , vol. 57, no. 6, pp. 655-662, 2011. [13] manju, s. chand, and b. kumar, “improved-coverage preserving clustering protocol in wireless sensor networks,” international journal of engineering and technology of innovation, vol. 6, no. 1, pp. 16-29, 2016. [14] r. duche and n. sawade, “energy efficient fault tolerant sensor node failure detection in wsns,” international journal of engineering and technology of innovation, vol. 6, no. 3, pp. 190-210, 2016. [15] m. abdelhakim, l. e. lightfoot, j. ren, and t. li, “distributed detection in mobile access wireless sensor networks under byzantine attacks,” ieee transactions on parallel and distributed systems, vol. 25, no. 4, pp. 950-959, april 2014. [16] m. young and r. boutaba, “overcoming adversaries in sensor networks: a survey of theoritical models and algorithm approaches for tolerating malicious interferences,” ieee communications survey and tutorials, vol. 13, no. 4, 2011.  advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 prediction primary available blend biodiesel of waste oil from aurantiochytrium sp. for general diesel engines shu-yao tsai1, hsiang-yu lin2, guan-yi lu1, chun-ping lin1,* 1 department of health and nutrition biotechnology, asia university, taichung, taiwan, roc. 2 department of neonatology, children’s hospital, china medical university hospital, taichung, taiwan, roc. received 05 june 2017; received in revised form 27 july 2017; accepted 11 august 2017 abstract chemical and enzyme transesterification were compared by discussing preliminary transesterification of waste oil of aurantiochytrium sp., which was then used in transesterification for the primary available blend biodiesel for a general diesel engine in this study. we made progress on the winterized characteristics of the waste oil’s biodiesel of aurantiochytrium sp. and its biodiesel, which included the reactivity parameters and properties. this approach led to the development of a novel idea for the evaluation of kinetic parameters of winterization, along with obtaining the suitable operation and storage conditions of biodiesel. therefore, the waste oil of aurantiochytrium sp. could be developed for biodiesel production and successfully made into a suitable blend diesel. overall, we acquired the best condition of mixtures and the highly mixed rate of petrodiesel: biodiesel = 80 : 20 (activation energy of winterization 21.32 kj/mol; onset temperature of winterization -4.15 °c; heat of combustion 43.15 mj/kg; kinematic viscosity 3.51 mm 2 /s; flash point 67.5 °c), which was an appropriate blend biodiesel from the waste oil’s biodiesel of aurantiochytrium sp. keywords: waste oil, aurantiochytrium sp., biodiesel, winterization, blend biodiesel 1. introduction this study focused on aurantiochytrium sp., which is a type of microalgae, the oil of which is refined for docosahexaenoic acid (dha) for incorporating into health food or food additives [1]. more than 20 mass% of the solid waste of aurantiochytrium sp. is discarded as rubbish under current operating procedures in food factories. in this study, we implemented the preliminary transesterification of solid waste of aurantiochytrium sp., to determine the advantages and disadvantages of chemical and enzyme transesterification. chemical [1-7] and enzyme [8-15] transesterification were compared to discuss the preliminary transesterification of waste oil of aurantiochytrium sp., which could then be beneficially used in the development of transesterification for an available mixture of biodiesel. the main stages of chemical transesterification are as follows [1-7]: (a) saponification fixes the fatty acids, which are used for enhancing the yield of the transesterification reaction and removing impurities, glycerol, and free fatty acid; (b) reduction reaction, which reverts the fatty acids for convenient converting to biodiesel; and (c) acid-catalysed reaction, which makes the fatty acids and methanol for fully transesterifying into the fatty acid methyl ester. the main stages of enzyme transesterification are as follows: (a) triglyceride hydrolysis by hydrolytic enzymes is * corresponding author. e-mail address: cp.lin@asia.edu.tw tel.: +886-4-23323456; fax: +886-4-23321206 advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 18 used for enhancing the yield of the transesterification reaction and removing impurities, glycerol, and free fatty acid [14]; and (b) immobilized enzyme reacts with the fatty acid, which reverts the fatty acids for converting to biodiesel [15]. we also developed the winterized characteristics of the waste oil’s biodiesel of aurantiochytrium sp. and its biodiesel, which included the reactivity parameters and properties [16-18]. differential scanning calorimetry (dsc) was used to obtain the winterization temperature and the other detailed enthalpy of the exothermicity of the biodiesel (b100) and the various proportion of biodiesel for mixing with petrodiesel (b0). the parameters and reactivity properties could be applied to the designs of the operation, application, and transportation safety conditions [1, 16-17]. it is an important project for developing high quality available blend biodiesel from the waste oil of aurantiochytrium sp. an available blend of biodiesel has the appropriate heat of combustion, kinematic viscosity [16], and storage safety [18]. it is an important performance indicator of biodiesel for mixing with b0, which is concerned with effective fuel for diesel engines. here, the heat of combustion, kinematic viscosity, and storage safety of blend biodiesel were tested by dsc [16-17], flash point tester [18], viscometer [19-20], and oxygen bomb calorimeter [21-23], and these were also compared to the various proportions of b100 for mixing with b0. then, the best condition of mixtures was obtained as an available blend diesel of waste oil’s biodiesel of aurantiochytrium sp. 2. experimental and method 2.1. samples the waste oil of aurantiochytrium sp., which was supplied directly from vedan enterprise corp. in taiwan, was stored frozen at –20 °c. the original fatty acid profile of waste oil was conducted by gas chromatography (gc) analysis [24]. 2.2. transesterification first, the fixed fatty acid composition was saponified with the three equivalents of sodium hydroxide under ca. 90 °c for three hours. then, the impurities, the free fatty acids, glycerol, and microalgae cell wall were removed to form the waste oil soap. the oil soap was included in the further transesterification. we then obtained a high purity fatty acid for the next step of the reduction reaction. second, the reduction reaction was mixed with sulphuric acid to form fatty acids under 85 °c for three ho urs. finally, the acid-catalysed reactions were mixed with dil. sulphuric acid (less than 0.02 mass% ratio of fatty acid) and methanol (fatty acids: methanol = 1:5, an amount of methanol more than five-times that of the fatty acids is better) under reflux overnight [1]. for preparation of the 0.1 m of disodium hydrogen phosphate-sodium dihydrogen phosphate buffer solution, the buffer solution was maintained at ph 7. candida rugose is a type of hydrolytic enzyme of lipase, which showed the preferred results of the hydrolysis reaction under a ph 7 buffer solution [8-15]. a 0.1 mass % of c. rugose was mixed with solid waste oil of aurantiochytrium sp. (triglycerides), and then the mixture was conducted for 260 rpm and stirring for 12 hours under isothermal 35 °c. from the above results, we removed the solid product and the oil layer of the upper layer (fatty acids), and then mixed this with c. antarctica (lipase acrylic resin of immobilized enzyme) (less than 2 mass% ratio of fatty acid) [15], methanol (fatty acids : methanol = 1:1), and isooctane (fatty acids: isooctane = 2:1) using a reflux apparatus under the isothermal conditions of 35 °c for 260 rpm and stirred for 16 hours . 2.3. gas chromatography (gc) analysis gas chromatography (gc) analysis fatty acid methyl esters (fames) were analysed by gas chromatograph agilent 6890n (agilent technologies, usa) equipped with a flame ionization detector (gc-fid) and a restek rt-2340 nb cap. column (105 m × advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 19 0.25 mm × 0.20 µm). the oven temperature was initially set at 170 °c and then programmed to 250 °c using helium as the carrie r gas, at a flow rate of 1.1 ml/min and held for 30 min. the injector and detector temperatures were 250 °c. the split ratio was 1:80. fatty acids were identified by comparing the retention time of fame peaks with supelco 37 fame mixture standards (sigma) [1, 16, 24]. 2.4. differential scanning calorimetry (dsc) tests the temperature–programmed screening experiments were performed with dsc ta q20-rcs90 (ta instruments, usa). for the dsc analysis on the samples sealed in 20 μl aluminium pans, the lid was pressed onto the crucible using the pressure of a heavy mechanical force, and the seal tightened the crucible; the test cell was then sealed manually by a special tool equipped with ta’s dsc [1, 16]. approximately 1.7 mg to 2.5 mg of the sample was used for obtaining the experimental data. the b0 and b100 of the dynamic tests of the scanning rate selected for the programmed temperature ramp were 2, 4, 6, and 8 °c/min and b2-b50. the scanning rate selected for comparing the programmed temperature ramp was 4 °c/min for the range of temperatures cooling down from 30 °c to -40 °c for each for each winterization phase behaviour experiment. in all of studies with the dsc thermal analysis, high purity nitrogen was the purge gas, and the flow rate was 50 ml/min. 2.5. diesel, biodiesel, and blend biodiesel winterization kinetic evaluation here, the proto-kinetic equation was applied to evaluate the winterization of the phase transfer for the exothermic reaction as follows [17]: 1 2 0 (1 ) ae n nrt ir k e      (1) where ea is the activation energy, k 0 is the pre-exponential factor, r is the ideal gas constant, α is the degree of conversion of a reaction or stage, and n1 and n2 are the reaction order of the phase transfer of the winterized exothermic reaction [17]. 2.6. biodiesel and blend biodiesel kinematic viscosity measurement the kinematic viscosity measurement is important for diesel engine fuel, and it is also an important indicator for biodiesel. to charge the sample into the viscometer, we placed the viscometer into the holder for fixing and inserted it into the consta nt temperature bath. the viscometer holder fit a cannon-fenske routine viscometer 75 u534 (cannon instrument company, usa) [16, 19]. we aligned the viscometer vertically in the bath by means of a small plumb bob in the tube. approximately 10 minutes was allowed for the sample to come to the bath temperature of 40 °c. we repeated this process three times for each sample to measure the efflux time and check the run. 2.7. biodiesel and blend biodiesel heat of combustion measurement the heat of combustion analysis of the samples involved a parr 1341 oxygen bomb calorimeter instrument (parr instrument company, usa) [16, 21-22]. we did a heat of combustion analysis for all of the samples as follows. to prepare, the water temperature was approximately 1.5 °c below room temperature, for which it was not necessary to use exactly 2 kg, but the amount selected must be duplicated within ±0.5 g for each experiment. we opened the filling connection control valve slowly and watched the gauge as the bomb pressure rose to the desired filling pressure (usually 30 bar, but never more than 40 bar). then, we closed the control valve. instead of weighing the bucket, it was filled from an automatic pipette or from any other volume tric device if the repeatability of the filling system was within +/– 0.5 ml and the water temperature was held within a 1 ºc range. we advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 20 let the stirrer run for 5 minutes to reach equilibrium before starting a measured run [16, 21-22]. approximately 0.5 g of all of the samples was used for acquiring the experimental data. at the end of this period, we recorded the time on the timer of the parr 6775 digital thermometer and read the temperature. 2.8. flash point measurement the flash point was determined by hfp 360 pensky-marten flash point tester (walter herzog gmbh, germany), which met the requirements of the astm d93b standard [23, 25], and it was used to estimate the flash points of the b0, b100, and the various proportions of b100 for mixing with b0. the astm d93 test method was applied to measure the flash points for each sample [23, 25]. the tester amalgamated control devices programmed the instrument to heat the sample at a specific designated rate within a temperature range close to the expected flash point. the flash point was automatically tested by using an ignit er at specified temperature test intervals. 3. results and discussion 3.1. the results of transesterification from the sequences of the saponification, reduction reaction, and acid-catalysed reactions, which were conducted for the full process of transesterification, and excluding the impurities, the free fatty acids, and glycerol, we successfully obtained the biodiesel of waste oil of aurantiochytrium sp. [1, 16]. fig. 1(a) shows the fatty acid profile of waste oil from gc analysis, which verified the fatty acid composition of the waste oil and confirmed that the amount of palmitic acid and dha was more than 75 mass% of total fatty acids [1]. in addition, from fig. 1(b), the c14-c24 of the fatty acids were more than 92 mass% of the total fatty acid methyl ester profile by chemical transesterification, but via the enzyme transesterification, they were only 60 mass%. (a) fatty acid composition of waste oil (b) fatty acid methyl ester composition of waste oil fig. 1 fatty acid and fatty acid methyl ester composition of waste oil of aurantiochytrium sp fig. 2 shows that the dsc tests programmed temperature ramps were 2, 4, 6, and 8 °c/min for the range of temperatures cooling from 30 to -40 °c for each b0 and b100 experiment, respectively. moreover, figs . 2 (a) and 2 (b) show the onset temperature of ca. -6 °c and 20 °c for the winterization of b0 and b100, respectively. b100 was the onset temperature (ca. 20 °c) of winterization slightly below room temperature, which would clog the oil lines and affect the diesel engine pe rformance at the low ambient temperature. advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 21 (a) b0 for the range of temperatures cooling down from 30 to -40°c with scanning rates of 2, 4, 6, and 8 °c/min (b) b100 for the range of temperatures cooling down from 30 to -40°c with scanning rates of 2, 4, 6, and 8 °c/min fig. 2 dsc thermal curves of heat flow versus temperature 3.2. kinetic parameter of winterization table 1 comparisons of the b0 and b100 kinetic parameters for the evaluation with scanning rates of 2, 4, 6, and 8 °c/min kinetic parameter sample condition a 2 4 6 8 ln(k0)/ln(1/s) b b0 7.6886 7.0606 6.8166 8.0858 ea c 26.7237 23.8218 22.5479 24.1341 n1 d 1.1179 1.1126 1.0977 1.1352 n2 e 1.0108 1.2552 1.1630 2.7679 δη f 5.1302 7.6498 7.0392 11.0410 ln(k 0)/ln(1/s) b100 4.1213 4.5116 4.4545 4.7674 ea 14.8082 14.2822 14.2331 14.6001 n1 1.1501 1.1493 1.1126 1.1045 n2 2.0334 2.5039 2.0072 1.9112 δη 169.0000 179.6522 162.9779 168.3870 the b0 and b100’s kinetic parameters of winterization were evaluated as listed in table 1. from table 1, we compared the ea and of winterization, b0 and b100 ca. 24 kj/mol and 14 kj/mol, respectively. we found that the simulation method of applying the proto-kinetic equation could be appropriately used in the exothermic reaction for winterization of waste oil’s biodiesel of aurantiochytrium sp. moreover, from table 1, the results of the parameter evaluation for proto-kinetic simulation demonstrated that the model provided much more consistent results for b0 and b100. therefore, while analysing the b0 and b100 kinetic parameters of winterization, we obtained a better model by proto-kinetic simulation in this study. similar to the various proportions of b100 for mixing with b0 of b2-b50 blend biodiesel, table 2 and fig. 3 show that the dsc onset temperature, peak maximum temperature and enthalpy measured for the b2-b50 clearly discriminated the differences. fig. 3 shows that there was an onset temperature from ca. -6 °c to 6 °c for the winterization of b2-b50 by dsc analyses. an important characteristic of a good blend biodiesel is the ability to avoid the winterization phenomenon under the low ambient temperature. therefore, while at the ambient low temperature, a reliable blend biodiesel cannot be solidified in the pipeline and tank, wh ich could cause engine failure [1, 16]. in contrast to tables 1 and 2, we observed the results of the proto-kinetic simulation for b0–b100, in which the kinetic parameters provided clear and specific results. the ea values of b0-b100 were in the range of 23.82–14.28 kj/mol. moreover, table 2 shows that the result was explicit: b0-b100 of ea, along with the higher proportion of b100, became smaller. from the above results of the kinetic parameter evaluation of winterization, we obtained the highly proportio nal mixture of b100, which was easy for winterizing the blend biodiesel. advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 22 table 2 results of dsc test and proto-kinetic equation simulation from b2 to b50 kinetic parameters for the evaluation at a scanning rate of 4 °c/min sample b2 b5 b8 b10 b20 b30 b50 mass a 2.0 2.0 2.0 2.0 2.0 1.9 2.0 exoto b -6.22 -4.85 -5.71 -5.34 -4.15 -1.03 6.09 exotp c -7.31 -14.54 -14.50 -12.66 -7.67 -1.78 5.70 exoδh d 10.40 13.50 19.00 22.70 34.20 46.90 81.10 ln(k 0)/ln(1/s) e 7.9899 6.9724 6.5301 6.3565 6.6144 6.3312 5.2386 ea f 26.8404 23.6787 23.0120 22.4650 21.3152 21.3428 18.7669 n1 g 1.0718 1.1073 1.0886 1.0935 1.1686 1.1335 1.1055 n2 h 0.6631 1.8153 0.9095 1.0190 1.6253 1.4865 2.2704 δη i 11.2995 18.4967 19.3829 23.1463 34.9629 47.6906 82.7576 fig. 3 dsc thermal curves of heat flow versus temperature for the b2-b100 for the range of temperatures cooling down from 30 to -40 °c with a scanning rate of 4 °c/min 3.3. the results of kinematic viscosity measurement from fig. 4, we obtained the b0-b100 of the kinematic viscosity average values range from 3.14 mm 2 /s to 4.35 mm 2 /s. generally, the biodiesel would be a fuel for a diesel engine. the kinematic viscosity range followed the astm d6751 and en 14214 specification standards [23, 24], from 1.9 mm 2 /s to 6 mm 2 /s and from 3.5 mm 2 /s to 5.0 mm 2 /s, respectively. it was too thin for b2-b10 as a blend biodiesel for en 14214 specification standards, and it could not provide the appropriate lubrication of diesel engines. we also observed that b20-b100 (3.51-4.35 mm 2 /s), whose values of kinematic viscosity were included in a suitable range, was also concerned with the effective fuel for diesel engine, such as the winterization, the heat of combustion, the f lash point, and the storage conditions of blend biodiesel (see fig . 4). then, the best conditions of the mixtures were obtained as an available blend biodiesel in this study. 3.4. heat of combustion measurement we obtained the best condition of mixtures and the maximum proportion of biodiesel as a good blend biodiesel of waste oil’s biodiesel. in this study, for the heat of combustion of blend biodiesel, the basic value was b0 (43.98 kj/g), and this value was used as a comparison benchmark for other diesels. from fig. 4, we obtained the heat of combustion and showed that b100, b50, and b30 were less than the others, which also showed that they were unsuitable for a blend biodiesel. from the comparisons of all samples heat of combustion, the mixed ratio of blend biodiesel smaller than b20 was acquired. this was the fuel that was suit able for use in compression ignition diesel engines in this study. meanwhile, from fig . 4, we observed the b2-b20 (43.30-43.15 mj/kg), whose values of heat of combustion were included in the suitable range, and this also showed that the highly mixed ratio of b lend biodiesel was b20 (43.15 mj/kg) in this study. advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 23 biodiesel (mass%) 0 20 40 60 80 100 f la sh p o in t (o c ) 40 60 80 100 120 140 160 180 200 220 k in e m a ti c v is c o si ty ( m m 2 /s ) 2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 h e a t o f c o m b u st io n ( m j/ k g ) 38 39 40 41 42 43 44 flash point flash point regr. r 2 = 0.948, y=1.26x+48.74 kinematic viscosity kinematic viscosity regr. r 2 = 0.968, y=0.01x+3.20 heat of combustion heat of combustion regr. r 2 = 0.975, y=-0.05x+43.75 fig. 4 heat of combustion, kinematic viscosity, and flash points of various proportions of b0 for mixing with b100 3.5. flash point measurement here, the results of the flash point tests of b0, b100, and the various proportions of b100 for mixing with b0 also followed the u.s. department of transportation (dot 49 cfr 173.120) regulations [18]. from fig. 4, we obtained the b0-b100 of the flash point temperature range from 45 °c to 184 °c, individually. from fig. 4, we also observed the b2-b100 (63-184 °c) of flash points were all above 60.5 °c. this temperature of flash points exceeded the safety condition that was related to a suitable fuel fo r diesel engine. this study also showed that adding the waste oil’s biodiesel of aurantiochytrium sp. could increase the storage and transport safety of diesel. the above transesterified results of fatty acid via gc analyses and dsc tests repeatedly corroborated the accuracy of the transesterification and the specific characteristic, proving that waste solid byproducts of aurantiochytrium sp. oil formed biodiesel. then, by conducting the dsc, bomb calorimeter, viscometer, and flash point tester, we compared the winterization, kinematic viscosity, and heat of combustion of the various proportions of b100 for mixing with b0, which could establish the best conditions of the mixture b20 as an available blend biodiesel. 4. conclusions the waste oil of aurantiochytrium sp. can be developed for biodiesel production and successfully made into a suitable blend biodiesel. we obtained the best conditions of mixtures and the highly mixed rate of b20 (ea of winterization 21.32 kj/mol at dsc scanning rate 4 °c/min; onset temperature of winterization -4.15 °c at dsc scanning rate 4 °c/min; heat of combustion 43.15 mj/kg; kinematic viscosity 3.51 mm 2 /s; flash point 67.5 °c) as an appropriate blend biodiesel from the waste oil’s biodiesel of aurantiochytrium sp. thus, from a green energy perspective, this project addressed the problem of “will not be occupied” arable land, ease of management, and ease of extensive cultivation for the production of biomass. we will enhance the transesterification technology for the waste oil of aurantiochytrium sp. to find improved energy efficiency, a less polluting method, and appropriate chemical and physical stabilities, which will be used in the mass production of green energy in future work. advances in technology innovation, vol. 3, no. 1, 2018, pp. 17 25 copyright © taeti 24 acknowledgements the authors are indebted to the donors of national science council (nsc), taiwan, r.o.c. under the contract nos.: most 105-2221-e-468-001& most 102-2221-e-468-001-my2 and the department of medical research, china medical university hospital, china medical university, taiwan, r.o.c. under the contract no.: dmr-100-165 for financial support. in addition, we are grateful to vedan enterprise corp. in taiwan for providing the microalgae oil and 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[25] g. knothe, “analyzing biodiesel: standards and other methods ,” journal of the american oil chemists ' society, vol. 83, no. 10, pp 823-833, october 2006.  advances in technology innovation, vol. 2, no. 1, 2017, pp. 01 07 1 assessment of a charge transport model for ldpe through conduction current measurement anggie chandra kusumasembada 1,* , gilbert teyssedre 2 , severine le roy 2 , laurent boudou 2 , ngapuli irmea sinisuka 1 1 department of electrical engineering, bandung institute of technology, bandung, indonesia. 2 laplace (laboratoire plasma et conversion d’energie), université de toulouse, cnrs, ups, inpt; 118 route de narbonne, f-31062 toulouse cedex 9, france. received 31 march 2016; received in revised form 01 may 2016; accepted 02 may 2016 abstract conduction current measurements have been widely used to characterize charge transport behavior in insulating materials. however, the interpretation of transport mechanisms and more generally of non-linear processes from current measurements alone is not straightforward. for this reason, space charge measurements, on the one hand, and models of charge transport encompassing charge generation, trapping and transport have been developed. the completeness and accuracy of a model can be assessed only if a substantial range of stress conditions, being field and temperature for the current topics, is available. the purpose of this communication is to enrich the investigation of low density polyethylene ldpe insulation material characteristic using conduction current measurement. measurements were conducted on 250 μm thick ldpe samples, for dc fields in the range 2 to 50 kv/mm and for temperatures from 20 to 70°c. experimental data, i.e. transient current in charge/discharge and quasi-steady state currents are compared to the prediction of a bipolar transport model that has been developed over the last years and fitted to the case of ldpe. the deviation of model results is substantial, with essentially an overestimation of the non-linearity of the current-field dependence. these differences are discussed along with prospects from improving the model. aside from these modelling approaches, we show that thermal preconditioning of samples appears to be influential in the measured apparent conductivity. keywords: ldpe, conduction current, charge transport 1. introduction investigation on polyethylene material as electrical insulating material receives significant attention as its demand increases, especially since polyethylene is more and more used in high voltage dc cables application. current understandings regarding charge transport and mechanisms related to space charge will benefit for reaching better performance and reliable hvdc insulation systems. low density polyethylene (ldpe) as part of polyethylene group is the main concern in this paper. ldpe charge transport characterization by conduction current has been conducted in various researches. charging mechanism characteristics by means of threshold representation [1, 2] on space charge features provides one way to describe its character. comparison between polymers was also conducted, as ldpe vs hdpe – i.e. high density pe [2], ldpe vs. ldpe + antioxidant vs. xlpe – i.e. crosslinked pe [3], and xlpe vs epdm, i.e. rubber with ethylene-propylene-diene monomer [4]. the purpose of this paper is to enrich study regarding ldpe charge transport by presenting measurement results on charging and discharging currents and comparing results with an already available model of conduction based on bipolar charge generation and transport. the model has been parameterized and refined over the years and encompass charge injection, charge transport and charge recombination [5, 6, 7]. its optimization is based on experimental results relevant to charging/discharging current, space charge measurements and electroluminescence. * corresponding author, email: anggi.kusumasembada@gmail.com advances in technology innovation, vol. 2, no. 1, 2017, pp. 01 07 2 copyright © taeti along these objectives, preconditioning factors that influence the measurement and how modelling reacts to it are also investigated. indeed, variations in preconditioning is considered as time elapsed before measurement once the sample is set to a given temperature, or previously applied electrical stress in the course of measurements. this could explain variations observed in output results. the model that has been developed can indeed integrate to some extent this thermo-electrical history. 2. experimental procedure 2.1. conduction current measurements ldpe material was considered for the conducted investigation. ldpe without antioxidant, provided by borealis, was chosen. for the measurement, ldpe pellets were first press-moulded to be prepared as plaque specimen. plaque sample was processed at 140 °c under a pressure of 3 bars for 20 minutes. completed samples are disks of 8 cm in diameter with 250 ± 10 μm in thickness. kapton was used as template and pressing layer during press moulding, the template was arranged to create plaques of 250 μm thickness. for ensuring measurement contact, each sample was provided with gold electrodes by sputtering, the gold layer has 5 cm in diameter and 30nm in thickness. a silicone layer was laid at the periphery of the electrode to avoid edge effects. several samples were prepared to be tested in different thermal preconditioning procedure: no thermal preconditioning, 1-hour, <52 hours, and >52 hours thermal conditioning. conduction current measurements were registered in air at 3 different temperatures (30, 50, 70° c) and 13 values of the applied electric fields (2, 4, 6, 8, 10, 13, 16, 19, 22, 25, 30, 40, 50 kv/mm). the sample was clamped between two brass electrodes with polished surface. the current was recorded through a keithley 617 ammeter with a 2 s dwelling time under charging state for 3 hours, and discharging state for 1 hour. extracted quantities mainly are transient currents and quasi steady state current, which will be derived as current density and conductivity. current density from transient current measurement provides information related to conduction mechanism, current density is deduced by the following equation: 𝐽(𝑡) = 𝐼(𝑡) 𝐴 (1) where i(t) is the measured current and a the area of electrode (20 cm²). conductivity value of the insulation is calculated using the following equation: 𝜎 = 𝐽∞ 𝐸0 (2) where j∞ is the steady state current density, e0 the applied field. in this work, the current values utilized in current density equation are quasi steady state current values which were taken during the last 800 s of the 10800 s measurement time of charging current measurement. 2.2. model the model features bipolar transport and trapping of electrons and holes. the model was created to fit experimental measurement of current, space charge, thermos-stimulated currents, electroluminescence, etc. [6, 8]. fig. 1 below illustrates the schematic representation of the model for ldpe [5]. it is a two levels model for each kind of carriers, defining so 4 kinds of species: mobile and trapped electrons and same for holes. fig. 1 physical model schematic the set of equations constituting the model is common to transport models in dielectric media, being liquids, solids or gases: transport of electrons and holes, neglecting diffusion: 𝑗𝑒(𝑥) = 𝜇𝑒𝑛𝑒𝜇(𝑥)𝐸(𝑥) (3) 𝑗ℎ(𝑥) = 𝜇ℎ𝑛ℎ𝜇(𝑥)𝐸(𝑥) (4) where μe is the electron mobility, μh the hole mobility, neμ the mobile electron density, nhμ the mobile hole density, e the electric field, and x the spatial coordinate. advances in technology innovation, vol. 2, no. 1, 2017, pp. 01 07 3 copyright © taeti poisson’s equation: 𝜕𝐸(𝑥) 𝜕𝑥 = 𝜌(𝑥) 𝜀 (5) where ε is the dielectric permittivity, ρ the net charge density. the conservation equation, meaning that local variations of density of given specie are due to transport or to variation as a source: 𝜕𝑛𝑖(𝑡) 𝜕𝑡 + 𝜕𝑗𝑖(𝑥) 𝜕𝑥 = 𝑠𝑖 (6) where s encompasses the source terms (i.e. trapping, detrapping, and recombination process). those source terms have for example the following form for mobile electrons: 𝑠1 = −𝑆1𝑛ℎ𝑡𝑛𝑒𝜇 − 𝑆3𝑛ℎ𝜇𝑛𝑒𝜇 − 𝐵𝑒𝑛𝑒𝜇 (1 − 𝑛𝑒𝑡 𝑛0𝑒𝑡 ) + 𝑣. 𝑒𝑥𝑝 ( 𝑤𝑡𝑟𝑒 𝑘𝑏𝑇 ) 𝑛𝑒𝑡 (7) si is the recombination coefficient, be the trapping coefficient for electrons and bh the trapping coefficient for holes. densities of trapped holes and electrons are stated with net and nht, while maximal trap densities of electrons and holes are stated by n0et and n0ht. w𝑡𝑟𝑒 is the detrapping barrier height. modeling of charge injection during applied voltage at each electrode is expressed with the following equation, for electrons as an example: 𝐽𝑒(0) = 𝐴𝑇2𝑒𝑥𝑝 (− 𝑤𝑒 𝑘𝑇 ) ⌊𝑒𝑥𝑝 ( 𝑒 𝑘𝑇 √ 𝑒𝐸(0) 4𝜋𝜀 ) − 1⌋ (8) equation for charge extraction at the other side is written as follows: 𝐽𝑒(𝑑) = 𝜇𝑒𝑛𝑒𝜇(𝑑)𝐸(𝑑) (9) the total current density through the material which incorporates the electrons and holes current density follows: 𝐽(𝑡) = 1 𝐷 ∫ (𝐽𝑒(𝑥, 𝑡) + 𝐽ℎ(𝑥, 𝑡) 𝐷 0 )𝑑𝑥 (10) latest refinements incorporated into the model concern the use of langevin-type recombination, where the recombination coefficients are function of the mobility of the carriers [8]. the mobility is a constant effective mobility that already takes into account the possible trapping and detrapping of charges into shallow traps. 3. results and discussion 3.1. transient current measurements 0 3600 7200 10800 0 50 100 150 200 c u rr e n t (p a ) time (s) 2 to 50kv/mm fig. 2 charging current transient in 250 μm thick ldpe plaque measured at 30°c for 13 different values of the applied field ranging from 2 to 30kv/mm (cf. §2.1) 10000 10400 10800 0 10 20 30 q u a s i s te a d y s ta te c u rr e n t (p a ) time (s) 2 kv/mm 4 kv/mm 6 kv/mm 8 kv/mm 10 kv/mm 13 kv/mm 16 kv/mm 19 kv/mm 22 kv/mm 25 kv/mm 30 kv/mm 40 kv/mm 50 kv/mm fig. 3 quasi steady-state charging current in 250 μm thick ldpe plaque measured at 30°c (long time data of fig. 2) transient current measurements were realized on ldpe and examples of the results obtained at 30°c are shown in fig. 2 and fig. 3. fig. 2 depicts a quickly reducing current magnitude toward a steady state. fig. 3 focuses on the longer time region in which current have been averaged for plotting the characteristics. the current appears indeed steady at this scale. in fig. advances in technology innovation, vol. 2, no. 1, 2017, pp. 01 07 4 copyright © taeti 2 and 3, some noise is detected for high field steps possibly due to some micro-discharges in the high voltage range (all measurements were realized in air at atmospheric pressure). however this noise does not have substantial impact on estimated conductivity. we shall see later on that the present charge time configuration (3 hours) is not sufficient to achieve steady state. 3.2. precondition effect on measurement substantial change in time in the conductivity has been reported recently depending on pre-annealing time of ldpe and crosslinked polyethylene (xlpe) by h. ghorbani [9]. indeed, aside from the apparent decrease in conductivity as a function of stressing time measured at 50°c, there was also a decrease in conductivity with the pre-storage time at 50°c before the measurements. similarly, montanari et al. [3] reported on a decrease in the transient currents measured at room temperature when ldpe or xlpe samples have been previously thermally annealed for 90h at 50°c [3]. the current decrease was all over the measurement time of 3h. as measurements realized here are relatively long (50h per temperature step) when realizing consecutively the all set of polarization/depolarization steps, there can be an evolution of the conductivity due to this conditioning. 30 40 50 60 70 10 -16 10 -15 c o n d u c ti v it y (  -1 .m -1 ) temperature (°c) set a set b 1 0 t o 5 0 k v /m m fig. 4 comparison of conductivity with varying preconditioning of ldpe plaque sample under various applied field. set a was conducted continuously for the 3 temperatures with same sample (sample 1), while set b was conducted with a different fresh sample for each temperature value. quasi steady current values plotted in fig. 4 were obtained for the following cases: (a) set a: same sample stressed successively in the different field steps and different temperatures (30, then 50 and 70°c); (b) set b: one different sample for the different temperature levels. in all the results, the apparent conductivity for the fresh sample is higher than the one for the previously stressed. quantitatively the difference between the two steps is a drop of the conductivity by about 30 to 50% after pre-stressing. the variation is about the same for 50 and 70°c. the trends are consistent with the previously reported results. however, the situation is a bit more complicated in the present case compared to results of h. ghorbani as here the history concerns both the thermal and electrical conditioning: both are likely to decrease conductivity for different reasons: (a) electrical pre-stressing may generate space charge into the insulation, e.g. close to the injecting electrode: this will act as counter-field for further charge injection and is a process that can explain the decay in time of the current. if trapped charges are stable, the memory effect will be generated owing to the pre-existing charge. a transport model might anticipate such features. (b) thermal pre-stressing can induce drying/outgassing of sample if some residues are present, and/or change of the morphology as crystallinity. substantial changes of crystallinity were reported h. ghorbani [9] for the long term testing at 50°c on ldpe and xlpe. crystallinity of ldpe increases as heat treatment time lengthened. this can in turn alter the electrical response of the material. one way to distinguish morphological vs. residue effects would be to probe again samples one exposed to ambient conditions. 3.3. current vs. field characteristics several works have reported on the threshold of current vs. field for various specimens such as: xlpe, rubber, hdpe, and ldpe [2-4]. the current density is plotted as a function of field following this 'threshold' representation – i.e. log-log plot in fig. 5. samples did not undergo thermal preconditioning before measurements apart from the stabilization time at the set temadvances in technology innovation, vol. 2, no. 1, 2017, pp. 01 07 5 copyright © taeti perature. it can be seen that the j-e curves of sample 2 (50° c) and sample 3 (70° c) starts unlike temperature-field characteristics of polyethylene. indeed, the current tend to drop while increasing the applied field, which is an unexpected behavior. the effect is not observed for the measurement at 30°c. the explanation for the effect is most probably the one described above, i.e. a conditioning effect at the measurement temperature: as measurement at each voltage level requires 4 h time, these conditioning effects can be significant. beyond a field of 10kv/mm, the curves for the different temperatures have similar shapes. 1 10 100 10 -10 10 -9 10 -8 10 -7 2.8 2.3 2.3 c u rr e n t d e n s it y ( a /m ²) applied field (kv/mm) 30°c 50°c 70°c (1) fig. 5 current density log-log plot for ldpe plaque specimens. electrical threshold are defined by applying fitting lines the slope of j-e plot as in fig. 5 should define whether ohmic conduction or ionic or space charge limited conduction [10] take place in the transport processes. current density plot in this work shows variation of the slope as field increases. notably for 30°c data, the characteristic changes from a nearly ohmic regime (slope close to 1) to highly non-linear regime with a slope estimated to 2.3. the threshold takes place at about 13 kv/mm where charge transport behavior of ldpe changes. for higher temperature, it is difficult to decide if the threshold varies owing to the evolution in time of the response of the material. 4. comparison to model outputs 4.1. model results fig. 6 shows a comparison between experimental and simulated current transients obtained at 20°c. it must be stressed here that the model has been applied with the currently available data set of coefficients, see [5], best fitted to measurements at room temperature, but without any attempt of later optimization of the parameters. 0 3600 7200 10800 10 -10 10 -9 10 -8 10 -7 2 6 10 16 22 30 c u r r e n t d e n s it y ( a /m ²) time (s) fig. 6 transient current density vs. time: comparison between actual measurements symbols and simulation (solid lines) at 20° c for fields of 2, 6, 10, 16, 22 and 30 kv/mm as shown in the legend results for the lower voltage are relatively noisy owing to the fact that the average current is small, of the order of 0.2 pa in average at long time. it can be seen from fig. 6 that at measurement time longer than 2000 s, charge transport characteristics appear differently between lower field and higher field. simulation result at 20 °c shows increasing transient current as applied voltage rises. results from the model reveal a steep transient in the first minutes followed by a slower transient over 1 h for the step at 2kv/mm and this step is not so pronounced for higher fields. the steeper decay is due to the fact that an initial density of charges is supposed to be present in the material and this was to cope with experimental electroluminescence measurements [5]. these pre-existing charges move under the effect of the applied field. the slower decay in current results from the injection at the electrode, followed by transport and trapping of the both type of carriers. for the other steps in field, the preexisting charge is that computed along the depolarization stages following the previous steps. at this stage of the model, orientation polarization processes are not included: they could be present and at the origin of the decay in the experimental current. advances in technology innovation, vol. 2, no. 1, 2017, pp. 01 07 6 copyright © taeti 4.2. discussion as stated above, the transient part of the charging current has several reasons for being not reproduced, notably the fact that the orientation polarization contributions are not included in the model. this has been done recently in the case of poly (ethylene naphthalate), a polymer known for having strong dipolar response. impedance spectroscopy data available in the frequency domain have been fitted to known relaxation functions according to identified relaxation processes. then it was converted to the time domain and this orientation polarization contribution could be treated separately from the transport aspects. the translation to the case of ldpe is not straightforward, as it is a non-polar material and therefore polarization if any has to be related to polar residues as oxidized groups for example. second, the weak magnitude of such processes would make it tricky to analyze in the frequency domain for conversion in the time domain. so, we are currently not in position to explicitly dissociate orientation polarization from space charge processes in ldpe. this, all the more that efforts in parameterizing the model at short time have been put more on electroluminescence features – reflecting charge recombination processes than on transient current. the behavior at long time should in principle fit more directly to the experimental. however, comparing between experiment and simulation, the difference almost reaches one decade in quasi steady state part for 2 kv/mm. with increasing field, the difference tends to be less, but still is by a factor 2 for 30kv/mm. so, on the all, the model tend to over-estimate the non-linearity of the response of the material. this is so while the rough material for making films is the same as that used for preparing samples on which the model is based. one could argue on the necessity of refining the model such as integrating polarization and using the latest developments in the physical hypotheses in it [8]. however, we would like to make the point on the experimental features. the main differences, regarding current measurement results are that previous experiments [5] were achieved in dry atmosphere instead of air. although polarization was 3 h, the selected field values for long polarization protocols were much coarser with data at 10, 40, 60 and 80kv/mm. presently, the first source of inconsistency to be fixed is the difference in experimental results regarding conductivity data, which were an order of magnitude higher in [7-5]. one possible route is the method of preparation of the films: ghorbani [9] showed that the nature of the films used as cover layer may indeed have a great influence on conductivity values. these results point on the carefulness to be given in the preparation of samples and measurements on insulating materials, and more generally on the definition of the system that we intend to probe and model. electrode nature and processing conditions constitute full field of potential discrepancy between experimental results. 5. conclusions our purpose in this paper was to assess the robustness of the outputs of a charge transport model by comparing the model predictions to a set of experimental data obtained at various fields and temperatures on ldpe. current-voltage characteristics reveal once more that a threshold at around 10kv/mm define a change in conduction mechanisms beyond which conductivity is clearly non-linear. experimental data obtained at 20 °c have revealed a substantial deviation from results expected from the transport model. perhaps one of the first conclusions is that one to be extremely careful in defining the system, i.e. material, processing, electroding, conditioning and measurement conditions as they may greatly impact the results. second, there is interesting memory or pre-conditioning effects to control and understand. part of it is of pure electrical nature, as previous charging effects on a given characteristic. in principle, if the model is complete, it should predict charge storage and subsequent impact on transport. a more difficult case to handle is thermal preconditioning effects, which are revealed here through a decrease of the measured current, but that would demand further investigation as its origin can be multiple, resorting to physical evolution of the structure or to moieties evacuation. acknowledgement one of the author, 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[10] g. teyssedre and c. laurent, “charge transport modeling in insulating polymers: from molecular to macroscopic scale,” ieee trans. dielectr. electr. insul., vol. 12, pp. 857-875, 2005.  advances in technology innovation, vol. 2, no. 4, 2017, pp. 119 125 119 copyright © taeti a cnn based approach for garments texture design classification s. m. sofiqul islam, emon kumar dey*, md. nurul ahad tawhid, b. m. mainul hossain institute of information technology, university of dhaka, bangladesh. received 03 october 2016; received in revised form 04 february 2017; accepted 08 february 2017 abstract identifying garments texture design automatically for recommending the fashion trends is important nowadays because of the rapid growth of online shopping. by learning the properties of images efficiently, a machine can give better accuracy of classification. several hand-engineered feature coding exists for identifying garments design classes. recently, deep convolutional neural networks (cnns) have shown better performances for different object recognition. deep cnn uses multiple levels of representation and abstraction that helps a machine to understand the types of data more accurately. in this paper, a cnn model for identifying garments design classes has been proposed. experimental results on two different datasets show better results than existing two well-known cnn models (alexnet and vggnet) and some state-of-the-art hand-engineered feature extraction methods. keywords: cnn, deep learn ing, a lexnet, vggnet, texture descriptor, garment categories, garment trend identification, design classification for garments 1. introduction online shopping is popular nowadays. customer select products from the web pages according to their choice and that can help to predict the direction of trends. if a retailer knows popular design styles of clothing products, it can increase the production of those styles to achieve more profit. therefore, if a system can classify the garments products according to different style, texture, size etc., it can automatically suggest different products to the customers based on their choices. the system proposed in this paper, can classify clothes according to textures. effective design classification based on textures, local spatial variations of intensity or colour in images has been an important topic of interest in the past decades. a successful classification, detection or segmentation requires an efficient description of image textures. to fulfil this purpose, lots of well-known hand-engineered feature extraction methods such as census transform histogram (centrist) [1], local binary pattern (lbp) [2], histogram of oriented gradient (hog) [3] etc., are exist. lbp gains popularity because of their computational simplicities and better accuracies. but, it is very sensitive to uniform and near uniform region. ltp [4], completed local binary pattern (clbp) [5] can handle this issue more accurately. between these two methods, clbp is better choice because this method is rotation invariant. centrist [1] has gain popularity by incorporating spatial pyramid (sp) structure. but, most recently completed centrist (ccentrist) and ternary centrist (tcentrist) [6] gained high accuracies for garments design classification. although several hand-engineered feature extraction approaches exist for garments design classification, deep learning is rarely used in this field. our goal is to apply appropriate deep learning model to measure the performance of garments design identification based on textures. in recent year, deep learning has become popular in the field of machine learning and computer vision. using large architectures with numerous features, many deep learning models achieve high performance in the field of object detection, text classification, image classification, face verification, gender classification, scene-classification, digits and traffic signs recognition, etc. some of the available deep learning models are alexnet [7], vggnet [9], berkeley-trained models [10], places-cnn model [8], places-cnds models on scene recognition [11], models for age and gender classification [12], googlenet model [13], etc. these methods have achieved dramatic improvements and attracted considerable interest in both the academic and industrial communities. in general, deep learning algorithms attempt to learn hierarchical features, corresponding to different levels of abstraction. each of these models concerned about some specific issues: preventing over-fitting, connection of nodes between adjacent layers, large learning capacity, etc. several factors need to be considered for working with deep learning network such as availability of large training set, powerful gpu for training and testing, better model regularization strategies, the amount of training time that one can tolerate, etc. the major contributions of this paper are as follows. (1) in this paper, a b rief review on existing well known hand-engineered feature ext raction methods for garments design class identification has been conducted. (2) this research has applied some existing deep convolutional neural network models for classifying the clothing products on some datasets and compared the results with several state-of-the-art hand-engineered feature extraction methods. (3) a new deep convolutional neural network model has been proposed for classifying garments design class. this proposed model is applied on two different datasets and has found a remarkable output. the rest of the paper is structured as follows. section 2 and section 3 describe the background studies and the methodology respectively. section 4 has presented the experimental results and finally section 5 concluded the overall work with necessary explanation. 2. background studies in this section, some existing garments clothing segmentation and classification strategies have been described. some existing deep learning models; that have *corresponding author. email: emonkd@iit.du.ac.bd advances in technology innovation, vol. 2, no. 4, 2017, pp. 119 125 120 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti been used for several applications in computer vision are also narrated in this section. 2.1. garment product segmentation and identification yamaguchi et al. [14] proposed a method for clothing parsing. for this work, they created fashionista dataset consisting of 158,235 images. from this dataset, they selected 685 images for training and testing their system. they identified 14 different parts of a body and different clothing regions. in [15], they deal with clothing parsing problem using retrieval based approach. their proposed approach focused on pre-trained global clothing models, local clothing models, and transferred parse. authors found that their proposed final parse achieve 84.68% parsing accuracy. menfredi et al. [16] proposed a new approach for automatic garments segmentation and classification. they classified garments into nine different classes such as skirts, shirt, dresses, etc. for this work, authors used a projection histogram for extracting few specific garments. they divided the whole image into 117 cells and group them into 3*3 cells. they computed hog features [17] from each cell and the orientations are grouped into nine bins. they used multiclass linear support vector for training. serra et al. [18] did similar type of work, where authors used conditional random field (crf) for divided outfits. vittayakorn et al. [19] used five different features such as color, texture, shape, parse and style descriptor to identify three different visual trends, namely floral print, pastel color and neon color from runway to street fashion. however, using more color and design classes would be more beneficial in this field. kalantidis et al. [20] proposed a system to identify the relevant product where they firstly estimated the pose of a person from an input image and then segmented the clothing area such as shirt, tops, jeans, etc. finally, they applied an image retrieval technique which is 50 times faster than [14] for identifying similar clothes for each class. gallagher et al. [21] used grab cut algorithm for identifying a person by segmenting the clothing parts. bourdev et al. [22] proposed a new method for detecting some attributes and type of cloths from an input image. here attributes are gender, hair style and types of clothes such as t-shirts, pants, jeans, and shorts etc. for this work, they created a dataset consisting of 8000 people images with annotation. 2.2. texture based classification nowadays, garments design classification based on texture has become more popular and there are several existing well known methods such as histogram of oriented gradients (hog), local binary pattern (lbp), features wavelets transform, noise adaptive binary pattern (nabp), gabor filters, scale-invariant feature transform (sift) etc. recently, lbp has become popular because of its computational simplicity. lbp was proposed for describing the local structure of an image and it has been used in several areas such as facial image analysis, including face detection, face recognition and facial expression analysis, demographic (gender, race, age, etc.) classification, moving object detection, etc. however, lbp is very sensitive in uniform and near uniform regions. in the last few years, lots of researches have been done by modification of lbp to improve the performance. such as derivative-based lbp, dominant lbp, rotation invariant, center-symmetric lbp, etc. tan and triggs [4] proposed a new texture based method local ternary patterns (ltp), which can tolerate noises up to a certain level. they used a fixed threshold (±5), for making ltp more discriminant and less sensitive to noise in a uniform region. there are also several other methods that can handle noises in different application areas, such as the methods described by jun et al. [25]. they proposed local gradient pattern (lgp) for texture based face detection. this method is a variant of lbp and uses adaptive threshold for code generation. guo et al. [5] proposed completed local binary pattern (clbp), which incorporates sign, magnitude and center pixel information. this method is rotation invariant and capable of handling the fluctuation of intensity. wu et al. [1] proposed census transform histogram (centrist) which is very similar to lbp and mainly work as a visual descriptor for recognizing scene categories. centrist proposes a spatial representation based on a spatial pyramid matching scheme (spm) [26] to capture global structure from images. centrist uses total 31 blocks to avoid the artefacts. dey et al. [6] proposed two new descriptors for garments design class identification namely completed centrist (ccentrist) and ternary centrist (tcentrist). these descriptors are based on completed local binary pattern (clbp), local ternary pattern (ltp) and census tranformed histogram (centrist). authors applied these two descriptors on two different publically available databases and achieve nearly about 3% more accuracy than the existing state-of-the art methods. 2.3. deep learning this sub-section, will describe some deep learning techniques for garments design classification. deep network learn features automatically from large number of unlabelled data, hence more useful hidden discriminative features are extracted. it has achieved popularity in classic problems, such as speech recognition, object recognition and detection, natural language processing, etc. convolutional neural networks (cnn) is now being used in several image, pattern and signal processing researches. liu et al. [33] introduced au-aware deep networks (audn) by constructing a deep architecture for facial expression recognition. for extracting high level features from each au-aware receptive fields (aurf), they used restricted boltzmann machine (rbms). later, this technique was applied on three expression database namely ck+, mmi and sfew. results achieved from this technique were better or at least competitive. however, this method fails when several kinds of challenging images (e.g., the subjects have higher expression non-uniformity, most of them have moustache and wear accessories such as glasses) are appeared. krizhevsky et al. [7] proposed a new cnn architecture which achieved top-1 and top-5 error rates of 37.5% and 17.0% on the test data. however, there is still an open issue that, if a single convolutional layer is removed, network’s performance is degraded. here, authors did not use any unsupervised pretraining data to simplify this work but it could be more helpful if the computational power and size of the network were increased. dey et al. [6] used deep learning model in texture based garments design classification. in their experiment, using berkeley-trained model [10], they obtained advances in technology innovation, vol. 2, no. 4, 2017, pp. 119 125 121 copyright © taeti 73.54% accuracy in clothing attribute dataset. however, they claimed that accuracy might be improved by changing layers and other related issues. zhoub et al. [8] proposed a technique which extracted the difference between the density and diversity of image datasets. here, authors used cnn to learn deep features for scene recognition tasks. for their dataset vgg s-16 models achieved 88.8% accuracy in top-5 val/test. however, there exist some difficulties such as the variability in camera poses, decoration styles or the objects that appear in the scene. lao et al. [27] used convolutional neural network for fashion class identification. authors divided their work into four parts those are multiclass classification of clothing type; clothing attribute classification; clothing retrieval of nearest neighbours; and clothing object detection. for this work they used apparel classification with style (acs), clothing attribute (ca) and colourful-fashion (cf) datasets and found 50.2% and 74.5% accuracy for clothing style classification and clothing attribute datasets. hu et al. [28] used deep convolutional neural networks for high-resolution remote sensing (hrrs) scene classification. for this work, they proposed two models for extracting cnn features from different layers. authors also used convolutional feature coding scheme for aggregating the dense convolutional features into a global representation. their proposed two models achieved remarkable performance and improved the state-of-the-art by a significant margin. for garments design class identification many approaches have been proposed. but, there are only a few works that have been conducted based on deep learning. this research has experimented different deep learning methods for identifying different garments design class based on textures. 3. methodology this section describes the methodology for identifying the garments design classes. basic steps of the procedure are shown in fig. 1. input images are firstly segmented and classified into several classes based on their texture design. after that, these images are separated for training, validation and testing from each of the class. proposed model is then applied alongside with two well-known deep convolutional neural network (cnn) models alexnet and vgg_s in two different garment datasets for the purpose of training and testing. finally, the accuracy of proposed system is compared with the existing models. we have also compared the results with traditional state-of-the-arts hand-engineered feature extraction method. alexnet and vgg_s have been chosen in this work because of their computational simplicity and better performance in several areas. they work well on unsupervised dataset. these two models can handle over-fitting problem when working with large dataset by using data augmentation technique. besides, these two models use a recently-developed regularization method called "dropout" that is proven to be very effective. these two models gained significant results in challenging benchmarks on image recognition and object detection. brief descriptions about these two models alongside our proposed model are described in the following sub-sections. fig. 1 basic steps of our working procedure fig. 2 the full architecture of alexnet model 3.1. alexnet model alexnet model was proposed by krizhevsky et al. [7]. there are three types of layer in a deep convolution neural network; such as convolution layer, pooling layer and fully-connected (fc) layers. full architecture of alexnet model was created by combining these three layers. in this architecture, there are total eight learned layers: five convolutional layers and three fully connected layers. convolution layer is the core building block and each of those convolution layer consists of some learnable filters. filters size are different from one another. full alexnet architectural model is shown in fig. 2. first convolution layer takes the input images by resizing each of the images into 224×224 with 96 kernels. the second layer takes the input from first convolution layer with 256 kernels after passing through a pooling layer. pooling layer operates independently and reduce the amount of parameters and computation in the network. hence, control the over-fitting problems. in this architecture, the third, fourth and fifth layers are connected to one another without any connection of pooling layers. the third layer consists of 384 kernels which takes input from the output of second layer. the fourth layer has 384 and fifth layer contains 256 kernels. each of last three fully connected layers contains 4096 neurons. the output of the last fully connected layer is sent as input to a 1000 way softmax layer which produces a distribution over the 1000 class labels. here, multinomial logistic regression is also used for maximizing the training cases. 3.2. vggnet model chatfield et al. [9], based on caffe toolkit proposed three different architectures of deep cnn models: vgg_f, vgg_m and vgg_s; each of which explores a different speed/accuracy trade-off: (1) vgg_f: this cnn arch itecture is almost similar to alexnet. but vgg_f contains smaller number of filters and small stride in some convolutional layers. (2) vgg_m: it is a medium size cnn which is very similar proposed by zeiler et al. [30]. the 1 st convolution layer of this network has s maller stride and pooling layer. 4th convolution layer use smaller numbers of filters for balancing the computational speed. (3) vgg_s: this architecture is relat ively slow than vgg_f and vgg_m and it is a simplified version of accurate model in the over-feat framework which has six convolutional layers. fig. 3 shows the full architecture of vgg_s model. it has taken the first five layers from the original model and has a smaller number o f filters in 5th layer. it has large pooling size in 1st and 5th convolutional layer than vgg_m. this model has been used to evaluate the garments design advances in technology innovation, vol. 2, no. 4, 2017, pp. 119 125 122 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti class identification. as depicted in fig. 3, this vgg_s model contains five convolution layers with s maller number of filters in the 5th layer and three fully connected layers. there are another two models based on vggnet namely vgg-vd16 and vgg-vd19. between alexnet and vgg_s models, the main difference is that vgg_s model has small stride in some convolutional layers and pooling size is large attached with the 1st and 5th convolutional layer. here, fully-connected layers 6 and 7 are regularized using dropout and the last layer acts as a mult i-way soft-max classifier. fig. 3 the full architecture of vgg_s model fig. 4 the full architecture of our proposed model 3.3. proposed transferred cnn for classifying garments design class, a new scenario has been proposed in this paper based on alexnet, to observe the performance and effectiveness of deep features by total nine learned layers. among these layers five of these layers are convolutional layer and remaining four are fully connected layers. like alexnet, first convolution layer of proposed model takes the input images by filtering each of the images into 224×224 size with 96 kernels. the second layer takes the input from first convolution layer after passing through a pooling layer. pooling layers are added after first, second and fifth convolution layer like alexnet. a new fully connected layer (fc3) which takes input from the output of second fully connected layer (fc2) has been added in this proposed model. output of the last layer (fc4) is connected to a softmax layer for classifying the categories. the proposed model used data augmentation technique to reduce overfitting in the training stage. because, recent works show that data augmentation also helps to improve classification performance [7]. the full architecture of the proposed model is shown in fig. 4. 3.4. datasets fig. 5 example of clothing attribute dataset: column 1 to 6 represents example of floral, graphics, plaid, solid color, spotted and stripe respectively fig. 6 example images from fashion dataset: each of the row represents jeans, leather, print, single co lor and stripe category respectively two publicly available datasets : fashion [31] and clothing attribute datasets (cad) [32] that was originally created for garment product recognition have been considered for this research. from fashion dataset, 5400 images are manually selected and categorized into five design classes, namely “single color” (2440 images), “print” (1141 images), “stripe” (565 images), “jeans” (614 images) and “leather” (640 images). again from clothing attribute dataset; 1575 images and manually selected and categorized into six different categories; after segmenting garments area from the original dataset. the categories are “floral” (69 images), “graphics” (110 images), “plaid” (105 images), “spotted” (100 images), “striped” (140 images) and “solid” advances in technology innovation, vol. 2, no. 4, 2017, pp. 119 125 123 copyright © taeti pattern (1051images). original cad contain 1856 different images with 26 ground truth clothing attributes such as necktie, color, pattern etc. fig. 5 and fig. 6 show some sample images from “fashion” and “clothing attribute” datasets used in our work. table 1 describes proper training and validation samples about clothing attribute and fashion datasets. for clothing attribute dataset, different training and validation samples has been used; such as 10, 20, 30 images per class for training and validation, and rest of the images for testing to identify the classification results. in fashion dataset, 60, 100, 200 and 300 images are used for training and 10, 10, 20 and 30 images for validation and rest of the images for testing respectively. table 1 dataset used for experiments sample with different training and validation samples databases clothing attribute dataset (cad) fashion dataset classes 6 5 total samples 1575 5400 training sample/class i)10 ii) 20 iii) 30 i) 60 ii) 100 iii) 200 iv) 300 validation sample/class i) 10 ii) 20 iii) 30 i) 10 ii) 10 iii) 20 iv) 30 4. experimental result this section describes the experimental detail and divided into two sub-sections. first sub-section discusses about the implementation environment and next one describes the results. 4.1. implementation environment experimentation environment for this research has been set by following a straightforward process. we fine-tuned the caffenet [29] model and use ubuntu 12.4 operating system. this research considered high speed gpu for making the computation faster. because cpu is nearly ten times slower than gpu for working with large datasets and complex cnn. nvidia geforce gtx 950 4gb gpu and intel core i7 processor has been used for faster training and testing. 4.2. experimental result and discussion this research mainly experimented on two existing deep convolutional neural network models alongside with the proposed model on fashion dataset and clothing attribute dataset. performance of the proposed deep learning model has been compared with the existing models and also with some existing well-known hand-engineering feature extraction approaches for garment design class identification. different training, validation and testing sample from two different datasets have been used and shown in table 1. the training and testing results of alexnet, vgg_s and proposed model are provided in table 2, table 3, table 4, and table 5. these accuracies are calculated based on the training, validation samples/class used for each dataset. from table 3 and fig. 7 it can be found that in most of the cases vgg_s performs better than alexnet model. table 2 recognition rate (%) in training phase of cad dataset models training sample validation sample results cad with 6 classes alexnet 10 10 75.1 20 20 75.6 30 30 75.5 vgg_s 10 10 76.2 20 20 76.5 30 30 76.6 proposed model 10 10 77.2 20 20 77.3 30 30 77.7 table 3 recognition rate (%) in testing phase of cad dataset models training sample validation sample results cad with 6 classes alexnet 10 10 75.3 20 20 75.5 30 30 75.6 vgg_s 10 10 76.5 20 20 76.4 30 30 76.8 proposed model 10 10 77.1 20 20 77.4 30 30 77.8 table 4 recognition rate (%) in training phase of fashion dataset dataset models training sample validation sample results fashion dataset with 5 classes alexnet 60 10 74.3 100 10 75.9 200 20 78.1 300 30 81.5 vgg_s 60 10 75.3 100 10 76.8 200 20 78.6 300 30 82.7 proposed model 60 10 76.6 100 10 78.1 200 20 81.1 300 30 84.1 table 5 recognition rate (%) in testing phase of fashion dataset dataset models training sample validation sample results fashion dataset with 5 classes alexnet 60 10 74.8 100 10 76.6 200 20 79.1 300 30 81.8 vgg_s 60 10 76.1 100 10 77.3 200 20 80.8 300 30 82.9 proposed model 60 10 76.7 100 10 78.1 200 20 82.7 300 30 84.5 using clothing attribute dataset, alexnet and vgg_s model of cnn shows maximum 75.6% and 76.8% accuracies respectively while our proposed model of cnn achieved 77.8% accuracy. on the other hand, using fashion dataset with 5 different classes, 81.8% accuracy has been achieved using alexnet and 82.9% accuracy using vgg_s respectively and advances in technology innovation, vol. 2, no. 4, 2017, pp. 119 125 124 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti our proposed model achieved 84.5% accuracy. from table 3 and table 5, it is clear that more training sample increase the accuracy. table 6 and table 7 describe the experimental results using seven different hand-engineered feature extraction methods which are hog, gist, lgp, centrist, tcentrist, ccentrist, and nabp on clothing attribute dataset and fashion dataset. for these methods support vector machine (svm) was used for classification purpose. table 6 experimental results of different methods for clothing attribute dataset method accuracy hog 63.76% gist 72.31% lgp 65.55% centrist 71.97% tcentrist 74.48% ccentrist 74.97% nabp 74.18% berkeley 73.54% alexnet (30) 75.6% vgg_s (30) 76.8% proposed model 77.8% table 7 experimental results of different methods for fashion dataset method accuracy hog 79.15% gist 81.67% lgp 79.79% centrist 79.72% tcentrist 84.07% ccentrist 84.23% nabp 83.22% alexnet 81.8% vgg_s 82.9% proposed model 84.5% table 6 also shows the result of three deep learning models berkeley, alexnet, vgg_s along with our proposed model for clothing attribute dataset. from this table, it is clear that performance of different deep learning models are better than any hand-engineering feature extraction method for clothing attribute dataset. table 7 shows that, for fashion dataset our proposed method performs better. though alexnet and vgg_s show slightly less accuracy than tcentrist, ccentrist and nabp. fig. 7 comparison between alexnet, vgg s and our proposed models for clothing attribute dataset fig. 8 comparison between alexnet, vgg s and our proposed models for fashion dataset 5. conclusion in this paper, some deep cnn models for identifying garments design class along with our proposed cnn have been used and also the results are compared with several hand-engineered feature extraction methods. using two different datasets , this proposed deep convolutional neural network with five convolutional layers and four fully connected layers shows better performance than some existing deep convolutional model as well as several hand-engineered feature extraction methods. fc layers and convolutional layers used in a deep cnn represent the features more elaborately, which are stronger than any of hand-engineered feature extraction techniques. 77.8% accuracy has been achieved on clothing attribute dataset with 6 different classes and 84.5% accuracy on fashion dataset containing 5 texture design categories using the proposed model. when a database contains more generic properties for every class, then a deep network can extract the generic features easily and accurately. it is mentioned earlier that the used datasets were manually categorized in different clothing product classes and used only a few numbers of classes. for this reason, the classes contain less generic properties most of the time. additional fc layer used in the proposed model helps the model to understand the features from these datasets more accurately. this research work will help other future researchers for choosing 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[26] s. lazebnik, c. schmid and j. ponce, “beyond bags of features: spatial pyramid matching for recognizing natural scene categories,” proc. ieee computer society conference on computer vision and pattern recognition (cvpr'06), ieee press, pp. 2169-2178, 2006. [27] b. lao and k. jagadeesh, “convolutional neural networks for fashion classification and object detection,” http://cs231n.stanford.edu/reports/blao_kjag_cs23 1n_finalpaperfashionclassification.pdf, june 26, 2016. [28] f. hu, g. s. xia, j. hu and l. zhang, “transferring deep convolutional neural networks for the scene classification of high-resolution remote sensing imagery,” remote sensing, vol. 7, no. 11, pp. 14680-14707, 2015. [29] y. jia, e. shelhamer, j. donahue, s. karayev, j. long, r. girshick, s. guadarrama and t. darrell, “caffe: convolutional architecture for fast feature embedding,” proc. 22nd acm international conference on multimedia, acm, pp. 675-678, 2014. [30] m. d. zeiler and r. fergus, “visualizing and understanding convolutional networks,” proc. european conference on computer vision, springer international publishing, pp. 818-833, 2014. [31] m. manfredi, c. grana, s. calderara and r. cucchiara, “a complete system for garment segmentation and color classification,” machine vision and applications, vol. 25, no. 4, pp. 955-969, 2014. [32] h. chen, a. gallagher and b. girod, “describing clothing by semantic attributes,” proc. european conference on computer vision, springer berlin heidelberg, pp. 609-623, 2012. [33] m. liu, s. li, s. shan and x. chen, “au-aware deep networks for facial expression recognition,” proc. 10th automatic face and gesture recognition (fg), ieee press, pp. 1-6, 2013.  advances in technology innovation, vol. 1, no. 1, 2016, pp. 21 24 21 copyright © taeti participatory communication referred to meta-design approach through the flexpeaker™ application of innovative material in exhibition design pei-hsuan su department of visual communication design, national taiwan university of arts, new taipei city, taiwan. received 22 february 2016; received in revised form 10 may 2016; accepted 15 may 2016 abstract modelling a communication system in material culture today always involves with objects, people, organizations, activit ies and interrelationships among them. the researcher suggests bringing together stakeholders engaged to exchange ideas, which the interactions relate to mult iple professions and disciplines in a participatory scope of communication system. owing to the invention of dig ital media , the status quo of images and sounds has revolutionized and caused changes of the mode of art exhib itions that produce activities and aesthetic concepts in terms of numerical representation, modularity, automation, visual variability and transcoding. underly ing a participatory-design approach, the research emphasizes a co-creative meta-interpretation of museum’s visitors. in addition, the research delves further into the use of new media-flexpeaker™ [itri], as the carrier. combin ing art and design with innovative technology, the research focuses on examining design objects and innovative material which are applied in new media art and exh ibition, in the hope to find new angles of participatory interpretation of the “integrated innovation” in curating an exhibition. keywords: communication system, participatory design, exhibit design, flexible speaker 1. introduction intertwined within a participatory communication system nowadays, the invention of digital media has revolutionized the quality of images and sounds. it has also changed the way of images and sounds in which they are contemplated, and the mode of art exh ibit ions that produce activities and esthetics concepts, because of the applications of “numerical representation, modularity, automation, v isual variability and transcoding” in this new media age [1]. in fact, the reproductability of digital technology leads to the hyper-real scenes where images and sounds are produced, copied and stimulated in a way that mimet ic cannot be told apart from the original. combin ing art and design with innovative technology, my research focuses on examining design objects and material innovation which are applied in new media art and exhib ition, in the hope to find new angles of participatory interpretation of the “integrated innovation” in curating an exhibition. the researcher emphasizes how to bring in museum’s visitors’ co-creation and meta-interpretation on the exhib ition site. the research delves further into the application of certain a new media-flexpeaker™ [itri], as the carrier. for instance, the social context and historical data are visualized and transcoded into specific images and life photography printed upon both sides of the surface of flexpeaker™, as well as with sound effects to stimulate visitors' imagination of the events, the time and the underlying environment at the e xh ib ition spaces in sun yun-suan memorial museum in taipei [2]. therefore, the exhib ition devices and design objects do help visitors to realize the significance of diverse elements of sounds, images and historical-documentary data in relation to its cultural-heritage representation. * corresponding author, email: sherriesutaipei@gmail.com advances in technology innovation, vol. 1, no. 1, 2016, pp. 21 24 22 copyright © taeti 2. method this participatory communication study is based upon how to employ participatory design in the art exh ibitions and museum spaces. as the matter of fact, much emphasis has been placed on design methods such as co-creation but even that has been largely limited to the involvement of visitors as participants. in addition, most of us get used to know the idea of hardware-oriented or professionally dominated des ign, so that we do think of visitors must adapt to the technology and the expertise must be shared with same background knowledge. however, the researcher would like to notify that museum’s curators get to employ so-called “participatory design” during curating time which focuses on systematic exhib it development to envision context within design thinking and practices . fundamentally different from creating complete settled–up exhib it systems, the curators need to consider a defining activity for empowering part icipation, aimed at creating certain interactive design devices as the exhibits, for other visitors. in addition, based on the idea of “participatory design,” through focusing on general exhib ited structures interacted with visiting processes rather than on fixed exh ibited objects and contents, the museum visitors may get deeper involved and achieve to the “world-as-experienced situated action” later engaged in the exh ib it design system. here we anticipate the participatory nature applied in exhibit design and the transition to more autonomous action for discovery by museum visitors. this method releases more power to the visitors to enhance their engagement while building up an exhibit system. 3. innovative electronic material of flexible speaker there are numerous technologies and products related to flexible electronics. flexib le electronics is sort of general term for using organic material, printing manufacturing process, electron ic circuit, optoelectronic components, or the technology of setting on flexib le substrate with low cost and the characteristics of being flexible [3]. in specific , the researcher introduces here the flexpeaker™ as one kind of significant innovative electronic materials. it developed by flexib le electronics pilot lab of itri, taiwan; flexpeaker™ is one of flexib le electronics applications , which helps itri received the wall street journal’s 2009 technology innovation award [4] [5]. the technology utilizes paper and metal layers as the material with a thickness of less than 0.1 cm and uses standard printing for large-size paper-thin flexib le speaker mass production. the great sound quality covers a range of 20 to 200 khz. it is especially good for high-frequency sounds such as the chirps of birds and insects, where fidelity equals or exceeds that of conventional speakers [6]. in addition, the flexpeaker™ uses only 10% as much power of conventional speakers, making it environmentally friendly. the new technology will bring the acoustic speaker industry into a brand-new era, and help create revolutionary consumer products such as memory cards with voice capabilit ies and ultra-thin mp3 p layers. it could even be incorporated into other products that are integrated into exhib it designs, green buildings, electric vehicles, entertainment and medical devices. the technology of flexpeaker™ will help create new lifestyles and cater to the pursuit of personalized, social and cultural, as well as humanized applications [7]. 4. results and discussion for the pulse o f the t imes and trends, the researcher would like to discuss how the curators has employed integrated innovation in exhibit ion design, since 2014, and delving further into the new media as the carrier in sun yun-suan memorial museum, taipei. new shapes of exh ibition objects have served as communicat ion media so that the images and sounds can be mixed used on the creations, and formed by projecting, framing, in laying, attaching, hanging, and erecting (fig.1). there are mixing of innovative technologies and devices installed in the exh ibition room. for instances, the curator uses one ultra-short throw projector, hidden rightly in the rear of one piece of the glass-board, to deliver information that represents a virtual television screen on the glass (fig. 2 & 3) . in fact, the device o f the “ultra-short throw pro jector” was developed by delta electronics, inc., taiwan. advances in technology innovation, vol. 1, no. 1, 2016, pp. 21 24 23 copyright © taeti fig. 1 the diversity of exhib ition sites at sun yun-suan memorial museum in taipei fig. 2 using one “ultra -short throw projector” to deliver information which was hided rightly in the rear of the glass-board fig. 3 representing a virtual television screen in the front of the glass-boards in the exhib it room fig. 4 life photography printed upon both sides of the surface of paper-thin flexpeaker™ to dedicate that sun leaded taiwan power company in restoring the power network in taiwan in addition, the curator introduces the economic-industrial contribution of the ex-premier of r.o.c., sun, yun-suan, who managed a staff of several hundred at taipan power company, and was able to get 80% of the power network in taiwan (destroyed during the world war ii) restored in five months in the year of 1946 [8]. his biographical social-contextual data are visualized and transcoded into specific images and life photography printed upon both sides of the surface of paper-thin flexpeaker™ (fig. 4) as well as with sound effects to stimulate visitors’ imagination of the events, the time and the underlying environment. therefore, sun yun-suan memorial museum came out the integration of arts-design-expertise in creating new exhibit experiences with technology. 5. conclusions referred to the idea of participatory exhibit-design, the sun yun-suan memorial advances in technology innovation, vol. 1, no. 1, 2016, pp. 21 24 24 copyright © taeti museum helps its visitors to take part in the experience of converging sound, images and documentary data by mixing a series of contemporary innovative technologies and devices. the reproduction of contemporary sounds and images leads to the hyperreal scenes at the exh ibit ion spaces in the museum where sounds and images are produced, copied and stimulated in a way that mimetic cannot be told apart from the orig inal data. just as “simulations” of jean baudrillard [9], the digital visual communicat ion media and digital interface changed into various ways and forms. however, it shows the hybrid of contemporary images and sounds. the creations are within the range of the post-modernism, which stress on the interdisciplinary and inter-textual of semiotic translations. with a collaborative multi-disciplinary schema, we have the comprehensive knowledge and means address to problems. here the curators need to work with historians, visual designers, web developers, user experience designers, and information designers in o rder to enhance the exhibit design can be extremely powerful in creating the kinds of tools or vehicles that visitors will not only need but will be able to effectively use. there is critical to employing a meta-design framework, ensuring that the exh ibit environment enables end-users to engage in in formed part icipation. the communicat ion system and devices developed in the exhib ition should be integrated in consultation with those end-users, as museum’s visitors. acknowledgement the support of the 2014-2015 itri’s curating team working with the sun yun-suan memorial museum is gratefully acknowledged. references [1] l. manovich, the language of the new media, new york: mit press, 2001. [2] p. h. su, “the aesthetics on meta-interpretation and hyperreal: an experimental converging practice of sounds, images and data applied in sun yun-suan memorial museum, taipei,” sid 2015 conference of sounds, images and data, new york university, steinhardt school, u. s., july 2015. [3] j. c. yeh, “the applicat ions of flexib le electronics go everywhere in the future,” compotech china, pp. 39-41, oct. 2011. (in chinese) [4] itri, flexib le electronics pilot lab. retrieved from https://www.itri.org.tw/eng/content/msgpi c/contents.aspx?siteid=1&mmmid=6177 54414641431112&msid=6177544376336 12573 (2016/ 02). [5] itri, “2012 itri forum: new technologies and venture capital.” no.69, 2nd quarter 2012. retrieved from: https://www.itri.org.tw/eng/content/public ations/contents.aspx?&siteid=1&mmmid =617731525164776565&msid=61776236 2453772447 (2016/ 02). [6] itri, innovations and applications_smart living_smart endpoints_ flexpeaker™. retrieved from: https://www.itri.org.tw/eng/content/msgpi c01/contents.aspx?siteid=1&mmmid=62 0651706136357202&msid=62102402525 7654754 (2016/ 02). [7] itri, “kevin kelly: ‘i was amazed by itri’s innovations.’” no.69, 2nd quarter 2012. retrieved from https://www.itri.org.tw/eng/content/public ations/contents.aspx?&siteid=1&mmmid =617731525164776565&msid=61776236 3015606130 (2016/ 02). [8] e. l. yang, the biography of sun yun-suan, taipei: common wealth magazine press, 1989. (in chinese) [9] j. baudrillard, simulacra and simulat ion (sheila glaser trans), u. s.: university of michigan press, 1994. (original work published in 1981).  advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 improving activated sludge wastewater treatment process efficiency using predictive control ioana nascu1, ioan nascu2,* 1 artie mcferrin department of chemical engineering, texas a&m, college station tx, usa. 2 department of automation, technical university of cluj-napoca, romania. received 05, june 2017; received in revised form 07, june 2017; accepted 09, july 2017 abstract this paper investigates the performance of a new predict ive control approach used to improve the energy efficiency and effluent quality of a conventional wastewater treatment plant (wwtp). a modified variant of the well-known generalized predictive control (gpc) method has been applied to control the dissolved oxygen concentration in the aerobic bioreactor of a wwtp. the quadratic cost function was modified to a positional implementation that considers control signal weighting and not its increments, in ord er to minimize the control energy. the activated sludge process (asp) optimizat ion using the proposed variant of the gpc algorithm provides an improved aeration system efficiency to reduce energy costs. the control strategy is investigated and evaluated by performing simulations and analyzing the results. both the set point tracking and the regulatory performances have been tested. moreover, the effects of some tuning parameters are also investigated. the results show that this control strategy can be efficiently used for dissolved oxygen control in wwtp. keywords: predict ive control, process optimization, process model, wastewater treatment plant, activated sludge treatment 1. introduction wastewater treatment plants are key infrastructures for ensuring a proper protection of our environment. biological treatment is an important and integral part of any wwtp. the activated sludge process is the most commonly used technology to treat sewage and industrial wastewaters due to its flexibility, high reliability and cost-effectiveness, as well as its capacity of producing high quality effluent. an overv iew of the activated sludge wastewater treatment process mathemat ical modeling is presented in [1] and application of asp models can be found in [2]. the asps are d ifficult to be controlled because of their complex and nonlinear behavior. however, the optimal control of the biological reactors plays an important role in t he operation of a wwtp and the efficiency of most wwtp is an important issue still to be improved . a good control of wwtp processes could lead to better water quality and to an efficient use of energy [3-4]. this research area is a key part of keeping the environment clean and nowadays has received great emphasis due to the strict regulations fo r the discharged water. many of the wwtp are operated in a less -than-optimal manner with respect to both treatment and energy efficiency, causing high costs and inefficient operation in order to meet the regulations. * corresponding author. e-mail address: ioan.nascu@aut.utcluj.ro tel.: +40-264-40122 advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 60 the dissolved oxygen concentration has a major impact in the activated sludge process. to control the dissolved oxygen concentration, the amount of air provided by the blowers in the aeration tank is modified. the activated sludge process is the most energy consuming processes in the whole wwtp, nearly half of the energy consumed in a wwtp being used in the aeration tank. an over dosage of aeration is unwanted because it brings increased costs and just little or even no gain in the quality of water. for values of dissolved oxygen concentration in the aeration tank above 2 mg/l, the increase of the aeration flow begins to have a lower effect in the quality of effluent and at values of 4-6 mg/ l doesn’t have any effect. in the absence of adequate control systems, to reduce the effect o f disturbances on the flow or load of the effluent, it is sometimes preferred to operate at high concentrations of dissolved oxygen in the aerat ion tank. using the blowers in manual operation at constant flow rates during the periods of reduced wastewater intake will produce a loss of energy. thus, optimizing the aerat ion process defines an important objective to reduce energy consumption and improve energy efficiency. several strategies have been proposed for controlling the dissolved oxygen concentration. some researchers have focused on the importance of well -tuned models and simulation p latforms in the process of designing the controllers for the dissolved oxygen concentration [5-6]. other researchers have focused on designing multip le model controllers instead of nonlinear complex ones [7]. nevertheless, because of the high nonlinearit ies of the process, robust controllers are required to maintain an optimum setpoint, regardless of the changes in the operating point. such control strategies have also been proposed, including adaptive [8-9], predict ive [10-11], fuzzy [12] or fractional order piμdλ control [13]. optimizing and maintaining the dissolved oxygen set point define important objectives for researchers in wwtp c ontrol. optimization of the dissolved oxygen set point is not the purpose of this paper. in practice, an appropriate dissolved oxygen set point is determined either manually by experienced operators or automatically through optimization algorithms. in this paper, we assume the appropriate set point is prescribed by the optimizing part of a mult ilayer hierarchical control structure and the proposed control system will be responsible for forcing the plant to follow this set -point. a modified variant of the well-known generalized predict ive control method [14] has been applied to control the d issolved oxygen concentration in the aeration tank of an activated sludge process . the asp process optimization using the proposed variant of the gpc algorithm provides an improved aeration system efficiency to reduce energy costs. the gpc algorithm is well known and consists of applying a control sequence that minimizes a quadratic cost function defined over a prediction horizon. the consideration of weighting o f control increments in the cost function in gpc allows an incremental implementation which ensures offset-free reference tracking and disturbance rejection but does not provide minimizat ion of the control energy. to alleviate the above mentioned limitat ion, the aim of this paper is to propose a different variant of the quadratic cost function. in order to minimize the control energy, the quadratic cost function was modified to a positional implementation that considers control signal weighting and n ot its increments. to evaluate the performance of the proposed design for asp process optimizat ion, simulat ion results are presented and discussed in detail. the asp process was first modeled and the models were calibrated and validated based on a combination of laboratory tests and plant operating measured data. the proposed control strategy is investigated and evaluated by performing simulations and analyzing the results. both the set poin t tracking and the regulatory performances have been tested. moreover, the effects of some tuning parameters are also investigated. the results show that this control strategy ca n be efficiently used for dissolved oxygen control in wwtp. 2. process description and modeling the activated sludge wastewater treatment processes are very complex, with large, uncontrollable input disturbances, significant nonlinearities and characterized by uncertainties regarding their parameters. the most widely used models to describe these processes is the activated sludge model nr.1 (asm1) proposed by the international water association (iwa) [15]. having thirteen state variables and eight dynamic processes, this model is highly complex, but it provides deep insight in advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 61 the behavior of the process. since the model also contains a large number of b iokinetic and stoichiometries parameters, for control purposes it is necessary to simplify it into a simpler model, especially if a hierarchical control structure is used. the modelling process and the model calibration are made based on data obtained from a conventional activated sludge system operating under aerobic conditions and whose main purpose is to ensure the removal o f colloidal and dissolved carbonaceous organic matter. the res idual water that needs to be treated is coming from a factory that processes and is painted cotton, a milk factory and from domestic households. fig. 1. wwtp's biological treatment process schematic configuration. the wastewater first enters the aerated bioreactor where the treatment based on asp takes place. the clear water and the sludge are separated due to gravity in the secondary settler. in order to keep b iological sustainability, the act ive sludge is recirculated and the bioreactor is aerated using an aeration network where air is being blown with fine bubbles. in our previous work [16-17] we have developed a reduced model to the asp based wastewater treatment process where the simplest possible case was taken into consideration. only the removal of organic matter is considered, while bio logical phosphorus and nitrogen removal is neglected. the following components are treated in the model: one organic matter component, one microorganism component and dissolved oxygen. for the model used in this paper, two processes are considered to take place in the aeration tank: the reduction of organic substance in heterotrophic aerobic bacteria and the reduction of ammonia n itrogen with autotrophic aerobic bacteria. the carbonaceous conversion is integrated in a consistent manner with the transformations of nitrogen. the following components are treat ed in the model: one organic matter component, two nitrogen components, two microorganism components and dissolved oxygen. the developed model is based on the following assumptions: the content of the aeration tank is considered perfect stirred; there are no d irections in the secondary settler; the biomass concentration in the effluent is negligible; the oxygen concentration and substrate are neglected in the recycled sludge; the active sludge is the only recycled component into the aeration tank. in this case, there are 6 equations. that can be written for the aeration tank considered as a completely mixed reactor. eqs. (1-6) correspond to the mass balance eqs. for:heterotrophic (1) and autotrophic (2) b iomass, biodegradable substrate (3), ammonia nitrogen (4), nitrite and nitrate nitrogen (5) and dissolved oxygen(6) concentration. ( ) ( ) ( ) ( )(1 ) ( ) [ ( ) ( ) ] ( )b,h r b,h b,h h ha h b,h dx t = r d t x t d t +r x t + m t +m t b x t dt     (1) ( ) ( ) ( ) ( )(1 ) ( ) [ ( ) ] ( )b,a r b,a b,a a a b,a dx t = r d t x t d t +r x t + m t b x t dt    (2) ( ) ( ) ( ) ( ) ( )[( ) ( ) ( )]s h ha b,h s sin h ds t m t +m t = x t d t 1+r s t +s t dt y   (3) bioreactor, s,x,do settler, xr recycled sludge, xr, rd waste sludge, x, βd aeration,w influent, sin, d, doin effluent se, (1-β)d advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 62 , , ( ) 1 1 = ( ) ( ) ( ) ( ) ( )[(1 ) ( ) ( )] 2.86 no ha b h a b a no noin h a ds t yh m t x t m t x t d t r s t s t dt y y       (4) ( ) 1 [ ( ) ( )] ( ) ( ) ( ) ( ) ( )[(1 ) ( ) ( )]nh xb h ha bh xb a ba nh nhin a ds t = -i m t +m t x t i + m t x t d t +r s t +s t dt y (5) 1( ) ( ) ( ) (1 ) ( ) ( ) ( )[(1 ) ( ) ( )] [ ( )]h in maxh b,h a b,a h a yddo t 4.57 = m t x t m t x t d t +r do t +do t ++aw do do t dt y y       (6) the mass balance equations for the recycled biomass are: )())(()()1)(( )( ,, , txrtdtxrtd dt tdx hrbshbs hrb   (7) , , , ( ) ( )(1 ) ( ) ( )( ) ( ) rb a s b a s rb a dx t d t r x t d t r x t dt     (8) under steady state conditions, from mass balance equations in the settling tank the resulting concentrations in the effluent ssef, snhef and snoef are: ( ) (1 ) ( )sef ss t = +r s t (9) ( ) (1 ) ( )nhef nhs t = +r s t (10) (t)s r)+(1(t)s nonoef  (11) the equations for the heterotrophic growth of the biomass in aerobic (µh) and anoxic (µha) conditions are: h hmax , ( ) ( ) ( ) ( ) ( ) s s s o h s t do t t k s t k do t      (12) h a hmax , ( ) ( ) ( ) ( ) ( ) ( ) s oh no g s s o h no no s t k s t t k s t k do t k s t          (13) while the equation for the growth of autotrophic mass µa is: )( )( )( )( (t) , hmaxa tdok tdo tsk ts aonhnh nh      (14) where xb,h and xb,a represent the active heterotrophic and autotrophic biomass concentration, ss, snh, sno, and do concentration of b iodegradable organic matter, ammonia nitrogen, n itrite -n itrate, and dissolved oxygen in the aerated bioreactor, ssin, snhin, and snoin concentrations in the influent, xrb,h and xrb,a recycled heterotrophic and autotrophic biomass concentrations, d and ds dilution rates (ratio of influent flow to volume of the aerated bioreactor and settler), w aeration rate, α oxygen transfer rate, r the ratio of recycled sludge flow to influent flow, β the ratio of waste flow to influent flow, ya autotrophic biomass yield factor, yh heterotrophic biomass yield factor, ixb conversion coefficient for the nitrogen mass, koh and koa oxygen saturation coefficients at half for heterotrophic/autotrophic biomass, knh and kno ammonia and nitrate saturation coefficients at half for autotrophic biomass, ks organic substrate saturation coefficient, ηg correct ion coefficient for µh in anoxic conditions. this model has 8 state variables: xb,h, xb,a, xrb,h, xrb,a, ss, snh, sno, and do. the kinetic and stoichiometric parameters values obtained after the model calibrat ion are: bh=0.034; ba=0.002; yh=0.54; ya=0.13; ixb=0.068; α =0.016; domax=10; ηg =0.8; µhmax=0.127; µamax=0.02; koh=0.2, koa=0.4; ks=130; kno=0.9; knh=1; β =0.015. advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 63 3. control strategy the aeration system, the b lower and p iping model and the proportional–integral–derivative (pid) control of the air flow is presented in [18-19]. following this work, this paper investigates the performance of a modified variant of the well-known generalized pred ictive control (gpc) method to control the dissolved oxygen concentration (do) in the aerated bioreactor of an activated sludge process , considered as process output variable (fig. 2). we assume that the appropriate set point for the dissolved oxygen concentration is given and the predict ive control system is used to maintain this set point. the aeration air flow (w) is considered as manipulated variable. fig. 2 predictive control schemes the generalized predictive controller is one of the most relevant design methods of model-based pred ictive control (mbpc). the standard gpc synthesis is based on a linear p rocess model, carima controlled auto-regressive integrated moving-average, a quadratic cost function and a control law, both using an incremental structure (the actual control signal increment δuis computed) [14]. th is incremental implementation ensures offset-free behavior in closed loop control systems. the activated sludge process is the most energy consuming processes in the whole wwtp, nearly half of the energy consumed in a wwtp being used for the aeration. an important step in developing the proposed control strategy is the reparametrizat ion of the cost function in the pred ictive algorithm to contain a measure of energy consumed by aeration process. this could exploit the fluctuation of operating conditions by realizing significant energy savings. since the aeration air flow w is the manipulated variable resulted from the controller output u, to minimize the aeration flow and not its variations the reparametrized cost function of the predictive algorithm has to contain the controller output u, instead of the control output increment δu. this will lead to a positional implementation based on a positional form for the process model and controller cost function. consider the following modified mbpc cost function: 2 1 2 2 1 2 1 ( , , ) [ ( ) ( )] [ [ ( 1)] unn u r j n j j n n n e y t j y t j u t j                   (15) where: y r is the future reference sequence, n1 is the minimum costing horizon, n2 is the maximum costing horizon, nu is the control horizon,and ρ is a control-weighting coefficient. the use of the carma process model instead of the carima model : 1 1 1( ) ( ) ( ) ( ) ( ) ( )a q y t b q u t k c q e t     (16) will lead to a positional form for the controller and therefore the controller will not have an integrator. for simplicity, in this development c (q -1 )=1 is chosen. to derive a j step ahead predictor of the process output y(t+j), on considers the polynomial identity:` advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 64 1 1 11 ( ) ( ) ( )j j je q a q q f q     (17) where ej(q -1 ) and fj(q -1 ) are polynomials uniquely defined, given a(q -1 ) and the prediction interval j, o f degree j and respectively n (n the process order). based on eq. (16) and eq. (17) we obtain: 1 1 1 1( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )j j jy t j e q b q u t j k f q y t e q e t j          (18) the optimal predictor, given measured data up to time t (including t) is written as: 1 1 1( | ) ( ) ( ) ( ) ( ) ( ) ( )j j jy t j t g q u t j k f q y t e q e t j         (19) where )()()( 111   qbqeqg jj (20) for simplicity, in the derivation below, n1 is set to 1, n2 to n, nu to n and k to 1. for j = 1,...,n, the optimal predictor eq. (18) can be written:: 1 0 1 0 1( ) ( ) [ ( ) ] ( ) ( ) ( ) ( )1 1y t 1 g u t g q g u t f y t e q e t 1         (21) 1 1 1 1 0 2 1 0 2( ) ( ) ( ) [ ( ) ] ( 1) ( ) ( ) ( ) ( )1 2y t 2 g u t g u t 1 g q q g g u t f q y t e q e t 2                (22) 1 ( 1) 1 0 1 ( ) ( ) ( ) [ ( ) ... ] ( 1) ( ) ( ) ( ) ( ) n n-1 0 n n 1 n n y t n g u t ... g u t n 1 g q q g g u t n f q y t e q e t n                        (23) on observe that the predictor y (t+j), consists of three terms: one including the past known control actions and the filtered measured process outputs, the second depending on future control actions which must be determined and the third, depending on the future noise signals. let f( t+j) be the component of y (t+j), which includes all the known terms at a timely moment: 1 1 0 11 ( ) ( )f(t ) [g (q ) g ]u t f y t    (24) 1 1 1 2 1 0 2( 2) [ ( ) ] ( 1) ( ) ( )f t g q q g g u t f q y t        (25) 1 ( 1) 1 0( ) [ ( ) ... ] ( 1) ( ) ( )n 1 n n nf t n g q q g g u t n f q y t            (26) then eq. (19) can be rewritten in the vectorial form: efugy  (27) where y, u, f and e are vectors of the form: [ ( 1), ..., ( )] , x 1ty y t y t n n    (28) [ ( ), ..., ( 1)] , x 1tu u t u t n n   (29) [ ( 1), ..., ( )] , x 1tf f t f t n n    (30) 1 1 1[ ( ) ( 1), ..., ( ) ( )] , x 1 t ne e q e t e q e t n n      (31) and the matrix g is then lower triangular of dimension n x n : advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 65                   03n2n1n 012 01 0 g...ggg ............... 0...ggg 0...0gg 0...00g g (32) for n u < n the matrix g is then of dimension n x n u:                   nung...ggg ............... 0...ggg 0...0gg 0...00g g 3n2n1n 012 01 0 (33) and y, u, f and e are vectors of the form: [ ( 1), ..., ( )] , x1ty y t y t n n   (34) [ ( ), ..., ( 1)] , x1t u uu u t u t n n   (35) [ ( 1), ..., ( )] , x1tf f t f t n n   (36) 1 1 1[ ( ) ( 1), ..., ( ) ( )] , x1 t ne e q e t e q e t n n      (37) the cost function becomes: ( ) [( ( ) ] [( ( ) ]) ) t tt t u r r r r j 1,n,n = e y y + u = e gu+ f +egu+f +e+ uy y y yu u  (38) assuming that e[e t u]=0, e[e]=0, and e[e t e] is not affected by u, the first derivative of the previous equation gives: [ ( ) ] [( ) ( )] t t t r r j = 2e gu+ f +e + iu = 2e g+ i u+ f y yg g g u     (39) for the first derivatal ive equate zero the control vector u is obtained: 1( ) ( )t t ru g g i g y f    (40) only the first element of u vector, u(t), must be determined and this value represents the current controller output: )()( fytu r t  (41) where α t = [α 1... α n] is the first row of the (g t g+ρi) ­1 g t matrix. note that if the equation for the calculation of the controller output (u) has the same form as that for the incremental gpc algorithm (δu), the diophantine equation form and calculat ion of polynomials ej and gj is different. 4. simulation results the assessment of the developed control system is done through numerical simulation in matlab/simulink environment. the nonlinear model of the activated sludge wastewater treatment process given by eqs. (1)-(14) was used to simulate the process dynamics. in the gpc algorithm the pred iction of the process output is based on a linear process model. to obtain the linear state space model and the transfer function from w to do the model was linearized aroun d an operating point. an eighth order transfer function was obtained. to reduce its order to two, from the linear state space model a balanc ed advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 66 state-space realizat ion was first computed and then the smallest 6 diagonal entries of the balanced grammians were eliminated using modred. similar results were obtained using the input and output data obtained during simulat ions of the nonlinear model dynamics for small variations around the considered operating point and a recursive least square algorithm to estimate a second order discrete transfer function. the steady state values of the input variables are: do=0.064[h -1 ]; doin0=0.5[mg/l]; sin0=765[mg/l]; w0=100[m 3 /h] and r0=0.8. the steady state value for the considered process output is do0 =1.36 mg/ l. the aeration air flow (w) is considered as the manipulated input, the other inputs being considered as disturbances. the air flow values were limited between wmin = 50m 3 /h and w max =210m 3 /h. the controller design parameters are: n=6, nu=1, sampling period ts= 0.01 h. different aspects, such as setpoint changes and effects of load disturbances , have been analyzed. in fig. 3 the setpoint tracking for a step from do0 =1.36 mg/l to do1 = 2mg/l in do setpoint at the time moment t=1h is presented. all the process inputs excepting the manipulated input have been considered as constants and equal to their steady state values. using the original gpc control algorithm that has an incremental form there is no steady s tate error between the process output (continuous line) and the setpoint. the developed gpc control algorithm has a positional form and the steady state error is increasing with the value o f the control-weighting coefficient, ρ( dotted line). however, it can be observed that with the increasing value of this coefficient, the aeration air flow w is decreasing and also the total amount of air consume d to reach the new setpoint. fig. 3 setpoint tracking performances for process output (do) and contro l output (w). incremental gpc continuous line, positional gpc for different values of the control-weighting coefficient (ρ) dotted line for the next simulation scenarios a constant setpoint is considered and the regulatory performance during a simulation test when the disturbances presented in fig. 4 (a step disturbance with an amplitude equal to 10% of the steady state value sin0, from t=10h to t=20h) and fig. 5 (random d isturbances for a large simulation time) are applied on the most significant input for the process output: influent organic matter concentration ssin. fig. 4 regulatory performances. step ssin input disturbances fig. 5 regulatory performances. random ssin input disturbances 1 1.2 1.4 1.6 1.8 2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 t [ h ] d o [ m g / l ] ro=0.002 ro=0.003 ro=0.004 incremental gpc positional gpc, ro=0.001 1 1.2 1.4 1.6 1.8 2 100 120 140 160 180 200 t [ h ] w [ m 3 / h ] incremental gpc positional gpc, ro=0.001 ro=0.002 ro=0.004 ro=0.003 advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 67 fig. 6 shows the regulatory performance during simulat ion test when the disturbances presented in fig. 4 are applied. using the incremental gpc control algorithm, there is no steady state error between the process output (continuous line) and the setpoint. using the positional gpc control algorithm the steady state error in the process output is increasing with the value of the control-weighting coefficient, ρ (only the case ρ=0.002 is shown by dotted line in the figure). with the increasing value of this coefficient, the aeration air flow w is decreasing and also the total amount of air consumed to reject the disturbance. as can be seen in the figure representing the control output w, the surplus of air needed to reject the disturbance using a positional gpc control algorithm (dotted line) represents 72% of the surplus of air needed to reject the disturbance using incremental gpc (continuous line). of course it needs to consider the disadvantage of the steady state error and of the response time. fig. 6 regulatory performances fo r step disturbances presented in fig . 4, process,output (do) and control output (w). incremental gpc continuous line, positional gpc with ρ=0.002 dotted line, no control dashed line. fig. 7 shows the regulatory performance during simulat ion test when the disturbances presented in fig. 5 are applied. three cases are presented: (i) control using positional gpc (dotted line), (ii) control using incremental gpc (continuous line) and (iii) no control (dashed line). the do setpoint is fixed at 2 mg/l and is kept constant during the simulation. the disadvantage of using the positional gpc is the steady state error and the advantage is a low power consumption. therefore, choosing the control-weighting coefficient value will be based on compromise between performance and power consumption. in the case of fig. 7, the average amount of air necessary for aeration is 2647 cubic meters daily if incremental gpc control is used. positional gpc with a value ρ=0.002 leads to an average amount of air necessary for aeration of 2348 cubic meters daily. considering the percentage, this means 88% of the average amount of air necessary for aeration using incremental gpc, i.e. a 12% reduction in air flow. the blowers operate under a predictable set of laws concerning speed, power and pressure. in accordance with affinity laws, flow is proportional to motor speed; and power is proportional to the cube of motor speed. this means that already min imal reductions in blower air flow can provide savings in energy consumption. reducing the blower air flow by 12% decreases the power requirement by 32%. fig. 7 regulatory performances for load disturbances presented in fig . 5, process output (do) and control output (w). incremental gpc continuous line, positional gpc with ρ=0.002 dotted line, no control dashed line. 10 15 20 25 30 100 110 120 t [ h ] w [ m 3 / h ] no control incremental gpc positional gpc, ro=0.002 10 15 20 25 30 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 t [ h ] d o [ m g / l ] positional gpc, ro=0.001 no control incremental gpc 0 200 400 600 800 1000 1200 1 2 3 4 5 d o [ m g / l ] t [ h ] incremental gpc no control positional gpc, ro=0.002 0 200 400 600 800 1000 1200 60 80 100 120 140 w [ m 3 / h ] t [ h ] no control incremental gpc positional gpc, ro=0.002 advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 68 5. conclusions the wastewater treatment plants are considered complex processes due to the strong nonlinearit ies, large variable time constants and continuous perturbations present in the influent. this study evaluates the performance of a positional gpc control algorithm for the dissolved oxygen concentration in the activated sludge process of a wwtp. both the setpoint tracking and the regulatory performances have been tested and compared with those obtained using the incremental gpc. the design parameters for both controllers are the same and the simulations provide information on the compromise between control performances (steady state error and response time) and savings in energy consumption. the aerat ion flow and, by default, the b lower’s speed is allowed to be lowered when the operating conditions of the wwtp permit. the power consumed by blowers is proportional to the cube of air flow. this means that already min imal reductions in blo wer air flow can provide savings in energy consumption. since the presented control system is responsible for forcing the plant to follow the setpoint prescribed by the optimizing part of a mult ilayer hierarchical control structure, it remains to be analyzed in what degree the overall performances of the hierarchical control system will be affected by the steady state error of this control loop. acknowledgement the support of the romanian national authority for scientific research, uefiscdi, under grant caseau 274/2014 and pn-iii-p2-2.1-ci-2017-0202 is gratefully acknowledged. references [1] u. jeppsson, “modelling aspects of wastewater treatment processes,” ph.d. thesis, dept. of industrial electrical eng. and automation, lund university, sweden, 1996. [2] d. brjdanovic, s. c. f. meijer, c. m. lopez-vazquez, c. m. hooijmans, m. c. m. van loosdrecht, “applications of activated sludge models,” london:iwa publishing, 2015. [3] r. katebi, m. a. johnson, and j. w ilkie, control and instrumentation for wastewater treatment plants, springer, london, 2012. [4] m. a. brdys, m. grochowski, t. gminski, k. konarczak, and m. drewa, “hierarch ical predict ive control o f integrated wastewater treatment systems,” control engineering practice, vol. 16, no. 6, pp. 751-767, june 2008. [5] n. s. iordache, c. petrescu, g. necula, and busuioc, “municipal wastewater treatment improvement using computer simulating, advances in waste management,” proc. the 4th wseas international conf. waste management, water pollution, air pollution, indoor climate (wwai’10), may 2010, pp. 95-100. 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[11] i. naşcu and i. naşcu, “modelling and optimizat ion of an activated sludge wastewater treatment process ,” european symp. computer aided process engineering, ieee press, december 2016, pp. 1159-1164. https://www.google.ro/search?newwindow=1&sa=n&hl=ro&biw=1476&bih=770&tbm=bks&tbm=bks&q=inauthor:%22reza+katebi%22&ved=0ahukewijnzr89rxjahwh_q4khcbbcreq9agiajaj https://www.google.ro/search?newwindow=1&sa=n&hl=ro&biw=1476&bih=770&tbm=bks&tbm=bks&q=inauthor:%22jacqueline+wilkie%22&ved=0ahukewijnzr89rxjahwh_q4khcbbcreq9agibdaj http://www.sciencedirect.com/science/article/pii/b9780444634283501983 advances in technology innovation, vol. 3, no. 2, 2018, pp. 59 69 copyright © taeti 69 [12] c. belch ior, r. araújo, and j. landeck, “dissolved oxygen control of the activated sludge wastewater treatment process using stable adaptive fuzzy control,” computers and chemical engineering, vol. 37, pp. 152-162, february 2012. [13] g. harja, i. nascu, c. muresan, and i. nascu, “improvements in dissolved oxygen control of an activated sludge wastewater treatment process,”circuits systems and signal processing, vol. 35, no. 6, pp. 2259-2281, june 2016. [14] d. w. clarke, c. mohtadi, and p. tuffs, “generalized predictive control part 1. the basic algorithm,” automatica, vo l. 23, no. 2, pp. 137-148, march 1987. [15] w. gujer, m. henze, t. mino, and m. van loosdrecht, activated sludge models asm1, asm2, asm2d and asm3, iwa publishing, 2000. [16] s. cristescu, i. naşcu, and i. naşcu, “sensitivity analysis of an activated sludge model for a qastewater treatment plant,” proc. international conf. system theory, control and computing, pp. 595-600, october 2015. [17] i. muntean, r. both, r. crisan, and i. nascu, “ rga analysis and decentralized control for a wastewater treatment plant,” proc. the ieee international conf. industrial technology, march 2015, pp. 453-458. [18] g. harja, c. mureşan, g. vlad and i. naşcu, “ fract ional order pi control strategy on an activated sludge wastewater treatment process,” 17th international conf. system theory, control and computing (icstcc), ieee press, october 2015. [19] g. harja, g. vlad, and i. naşcu. “dissolved oxygen control strategy for an activated sludge wastewater treatment process ,” recent advances in electrical engineering series. proc. the 19th international conf. systems (cscc'15), ju ly 2015 pp. 453-458. http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.grigore%20vlad.qt.&newsearch=true  advances in technology innovation, vol. 2, no. 3, 2016, pp. 85 88 85 the innovative bike conceptual design by using modified functional element design method nien-te liu1,*, chang-tzuoh wu2 1 department of product design, shu-te university, kaohsiung, taiwan. 2 department of industrial design, kaohsiung normal university, kaohsiung, taiwan. received 29 january 2016; received in revised form 27 april 2016; accepted 02 may 2016 abstract the purpose of the study is to propose a new design process by modifying functional element design approach which can commence a large amount of innovative concepts within a short period of time. firstly, the original creative functional elements design method is analyzed and the drawbacks are discussed. then, the modified is proposed and is divided into 6 steps. the creative functional element representations, generalization, specialization, and particularization are used in this method. every step is described clearly, and users could design by following the process easily. in this paper, a clear and accurate design process is proposed based on the creative functional element design method. by fo llowing this method, a lot of innovative bicycles will be created quickly. keywords: conceptual design, functional element design method, generalizat ion, specialization, particularization 1. introduction design in b lack box is the most commonly used in practical design. but, it is not popular for study and learning [1]. in this study, we analyze functional elements and try to solve the black box problem of creating new concepts for innovative bicycles. every innovative bicycle has one or more creat ive functional elements. if we choose several suitable creative function elements in our design, then we can come up with a new and creative bicycle. liu and wu have proposed the representations for bicycle characteristics, but the process for bicycle design is not mentioned in the study [3]. this paper proposes representations for bicycles. by using symbols representations, bicycles can be represented simple and quickly for innovation design. ke considers bicycle to be a module product. thus , in terms of d ifferen t des ign and combination in spare parts and components, there are four factors that can directly impact on the difference of the class level and price of a bicycle: function, material, appearance and manufacturing quality. in his study, he also mentions that in defin ing the position of a new product, three indexes as new material, new function and new purpose can serve as the course of research and development [4]. therefore, in the creative design of b icycles, function and material are very important factors. in the study of ma, it has proposed that module design is a concept of introducing part/component module into the design process and to s imp li fy and organ ize various components/parts by application of systematic method. in so doing, it can raise the functional performance and adaptability of bicycles so as to satisfy the application requirements [5]. in the study, it disintegrates a bicycle into various ele ment component modules with each component represent ing one funct ion . accordingly, a component can also be regarded as one functional element. in hung’s study, he divides a bicycle into five components as frame structure, front, rear suspension mechanisms, steering handler, and seat for engaging conceptual design. in the final stage, he conducts a concrete integral design of integrating various systems by establishing an in tegrat ion p rocess th rough app ly ing morphological matrix [6]. in terms of shortfall, since his design divides a bicycle into five components, which constrains the definition of bicycles into a narrow one and easy to limits the * corresponding author, email: ntliu@stu.edu.tw advances in technology innovation, vol. 2, no. 3, 2016, pp. 85 88 86 copyright © taeti design result, rendering an unfavorable impact on the creative design. in his study, he has proposed that the future development of bicycles can be divided into five categories: 1) use of new materials, 2) addition of new functions, 3) new rid ing ways, 4) introduction of new electronic products, 5) dedicated developed products depending on respective market requirements. his research has proposed that in the future creative design of bicycles, addition of new functions is an indispensable link. thus, it is very important to more focus on choice and integration of new functional elements in the design process. ji has categorized the spare parts/ components of a bicycle according to function into the following six major systems: 1) transmission system, 2) steering system, 3) wheel system, 4) braking system, 5) vehicle frame structure system, 6) gear system, [7]. chang categories on bicycle composition, he divides the functions of a bicycle into seven major systems: 1) trans mission system, 2) steering system, 3) wheel system, 4) braking system, 5) structure system, 6) fitting system, 7) accessory system [2]. at present, the traditional methods used for designing bicycles lack analysis and induction, it much limits the design development with creative concept. this study would continue the former research about the design process for innovative bikes [2]. the purpose of this paper is to help designers to produce their creat ive design concepts by applying massive support of functional elements in a short time and modified the proposed design process. 2. functional elements representation this research collects 242 award works of bicycle products between 1996 and 2006 from the bicycle design competit ions. the bicycle design competit ion is sponsored by the department of industrial technology, min istry of economic affairs, r. o. c. and managed and produced by the cycling & health tech industry r&d center. the first such competition was the "1996 taiwan creative bicycle design competition." the study sort out these award works into a comparison table on functional elements according to year sequence order and serial number. the award works were preliminarily categorized into “standard” and “specific” categories. “standard category” means a normal bicycle category and is similar to the market-sale rid ing bikes in structure which signifies a bike with simple change of appearance and style. “specific category” is comparatively different to the riding way, structure and functions of market-sale bikes, such as contractible, different way of storage, or addition/subtraction of certain functions. cite bike for example, we do a functional nature analysis. before such functional element analysis, we define various elements as shown in the symbol figure. each functional element has its own represent symbol. the batch number for addition of function p can be known in the categories of standard and specific types. addition of function p shows the addition and subtraction change for many bike designs. therefore, we give these serial numbers as p01, p02, p03 … in our analysis process [2]. for transform a bicycle into a symbolized representation, a process is suggested here: 1. take a picture of a bicycle; 2. find functional elements of the bicycle; 3. mark symbols on every functional elements of the bicycle; 4. check and note the connecting relationship between every two functional elements. by the process, every bicycle has its own symbolized representations by the functional elements. take a normal bicycle as an example, we mark various functional element symbols on the bike, and then connect and define the relationship between various functional elements. under normal circumstance, when various functional elements are inseparable, we use solid line to show the connection between various functions, which indicates their d irect connection; when it is indirectly driven by chain-like object, we then use a solid line with an arrow. the arrow points at functional elements from human-driven end. accordingly, we can have a functional element representation as shown in fig. 1 [2].where means seat, means control, means single wheel, and means driven by human power. fig. 1 functional element representation of a normal bicycle advances in technology innovation, vol. 2, no. 3, 2016, pp. 85 88 87 copyright © taeti existing bicycles symbolized bicycles atlas of generalized bicycles atlas of feasible specialized bicycles creative functional element representations combinations generalized bicycles generalization atlas of feasible bicycle innovative bicycles design requirements and constraints specialization design characteristics particularization existing bicycles 3. original design process the orig inal innovational design process for bicycle is proposed in liu’s research [2], but the design process is not clear enough to operate step by step. the design process is proposed and shown as fig. 2. fig. 2 the bicycle design process using functional element representation in the first step, the designers’ descriptions for design theme are necessary. the theme is decided by personal preferences or design constraints. the description is more clearly, the selecting of functional elements is more easy and fast. in the second step, functional elements are chosen in accordance with the contents described. the constraints of combination of a bicycle need to be considered. so, some elements are necessary. in the third step, functional element symbols are arranged fo r new des ign concepts . according to designers ’ need for creative functional elements, relative positions are arranged. here designers need understand the rat ional ru les o f b icycles fo r arrang ing functional elements. finally, according bicycle’s creative functional element symbol table, the representations obtained from previous step are transformed into new design concept of bicycles. 4. modified design process for the design process mentioned above, there are some p laces interpret unclear thus designer will be hard to work following the process step by step. therefore, the modified design process is proposed and shown as fig. 3. fig. 3 the modified design process description of design theme choice of functional elements arrangement of space position of functional elements realization design using creative functional elements advances in technology innovation, vol. 2, no. 3, 2016, pp. 85 88 88 copyright © taeti in step 1, a designer needs choose an existing bicycle for developing. by analyzing the exis ting bicycles, design characteristics are collected. by creative functional elements representations, bicycles are symbolized. in s tep 2, s ymbolized b icycles are generalized. every symbol is meaningful for symbolized bicycles. by generalization, every symbol would be changed to a non-meaningful symbol. in step 3, from generalized b icycles and combination, different topology could be used for deigning. thus, atlas of generalized bicycles is obtained. in s tep 4, by specializat ion , every non meaningful symbol in atlas of generalized b icycles is assigned a creative functional element one by one. during assigning process, des ign requ irements and const rain ts are considered at the same time. atlas of feasible specialization bicycles are obtained in this step. in step 5, feasible specializat ion bicycles are particularized. the form of all bicycles can be observed easily. in step 6, by deleting the existing bicycle in atlas of feasible bicycle in step 5, innovative bicycles are obtained. 5. conclusions the approach proposed by this research is to modified functional elements design method for bicycle design. the advantage of this approach is the possibility of creating more concepts easily, but the original process, designer is hard to follow step by step for designing. in this paper, a modified process is proposed and divided into 6 steps clearly. the creative functional element representations, generalization, specialization, and particularizat ion are used in this method. when designing innovative bicycles, designers just need finish the process and innovative bicycles will be obtained. acknowledgement the support of the minister of education (taiwan), under grant most 104-2221-e 366-009 is gratefully acknowledged. references [1] n. f. m. roozenburg, j. eekels, product design: fundamentals and methods, wiley, 1995. [2] n. t. liu, c. t. wu, and y. c. lin, “the study on the innovation bicycle design using functional element characteristics,” applied mechanics and material, vol. 764-765, pp. 383-387, 2015. [3] n. t. liu and c. t. wu, “on the symbolized representation of innovative bicycle with functional elements characteristics for creative design,” transaction of the canadian society for mechanical engineering, vol. 37, no. 3, pp. 949-957, 2013. [4] c. m. ke, “viewing bicycle design by product status,” bicycle industry, vol. 33, pp. 38-43, 2001. [5] c. h. ma, t. h. lin, and y. c. huang, “theory and application on module design model – case study on bicycle,” journal of industrial design, vol. 109, pp. 127-134, 2003. [6] t. d. hung, “creative design on two-wheel bike system,” institute of mechanical and mechatronics engineering, nat ional sun yat-sen university, 2005. [7] y. h. ji, “creative design on bike’s speed -changing dev ice,” inst itute o f mechanical and mechatronics engineering, national sun yat-sen university, 2002.  advances in technology innovation, vol. 2, no. 3, 2016, pp. 89 94 89 biosignal –based multimodal biometric system kuk won ko and sangjoon lee* school of mechanical and ict convergence engineering, sun moon university, s. korea. received 02 may 2016; received in revised form 25 june 2016; accepted 26 june 2016 abstract this study concerns personal identification based on electrocardiogram (ecg) and photoplethysmogram (ppg) signals. we manufactured a bio-signal measurement system that can simultaneously measure ecg and ppg signals, using which three channels of ecg signal and one channel of ppg signal were acquired from the right-hand index finger of a total of 33 subsets for 3 minutes. lead-i signal of the three-channel ecg signal and the one-channel ppg signal were selected for recognition. for each subject, 160 heartbeats were automatically separated from the acquired bio-signals, and a total of 21 features, comprising 15 ecg features, 4 ecg-related ppg features, and 2 features concerning ppg only, were extracted from each heartbeat. letting the 21 features form a single data point, heartbeat features of each subset were used as the training data for a support vector machine (svm) classifier, with the number of data points being adjusted from 10 to 80, and the data points (80 – 150) other than the training data were used as the testing data, in order to investigate the recognition performance indices. as a result, the proposed algorithm showed high recognition performance of 99.28% accuracy, 0.88% frr, 0.85% far, 99.28% sensitivity, and 99.31% specificity, when there are 80 training data points. moreover, even when there are 10 training data points, the proposed algorithm showed the performance of 92.77% accuracy, 7.23% frr, 6.29% far, 92.77% sensitivity, and 93.21% specificity, which can be evaluated as an extremely high recognition performance considering that there was a total of 4,950 testing data points. keywords: biometric, pattern recognition, personal identification 1. introduction following the rapid recent advances in information technology (it), the demand for biometric recognition technology is increasing for the purpose of information security and the prevention of privacy invasion. fingerprints, iris, facial features, dorsal metacarpal veins of the hand, or gait, which are the intrinsic features of human body, are used as the main elements of existing recognition systems. biological features for b iometric recognition can be selected the characteristics that have almost no variation with time, or reflect slow variation with time. this study introduces a multimodal biometric system and algorithm based on electrocardiogram (ecg) and photoplethysmogram(ppg) signals. it is known that there are around 80,000 – 100,000 contractions in a healthy heart in o rder to circulate the blood in at ria to the vessels of the entire body, within 0.1% cases of which exh ibit abnormal ecg waveforms. moreover, ecg s ignals are known to be regular and convenient for pattern classification compared to other bio-signals. ppg signals are bio-signals that are linked with ecg signals, and also represent the state of b lood vessels of the subject with heart contraction. furthermore, while ecg and ppg waveforms of an indiv idual subject vary slightly at each time, these signals have the characteristics of unchanging overall pattern. the first study on recognition systems based on bio-signals was introduced by lena biel [1] in 2001, followed by few researchers around the world. john m. irvine [2] showed the effectiveness of ecg for personal identification even when the heart is in a stressed state (excitement or exercise). in addition, t. w. shen [3], steven a. israel [4], konstantinos n. and plataniotis[5] introduced personal identification algorithms based on ecg. the proposed algorithm is based on the detection of feature points from ecg and ppg signals obtained simultaneously, and a total of 21 features are automatically ext racted, including 15 features from the ecg heartbeat signals * corresponding author, email: mcp94lee@sunmoon.ac.kr advances in technology innovation, vol. 2, no. 3, 2016, pp. 89 94 90 copyright © taeti separated from the overall ecg signal, and 6 features from ppg signal, in order to promote the real-t ime operation of the recognition algorithm. the proposed algorithm adopts down slope trace waveform (dstw) method [6], which shows high peak detection rate, for the detection of p, q, r, s, and t points of the ecg signal. for pattern recognition, one-against-one support vector machine (svm) algorithm was used, which shows excellent recognition results in various fields, and is capable of multi-class classification. 2. method 2.1. bio-signal measurement system while the previous ecg recognition and disease detection algorithms can be assessed in terms of validity by using existing public database files such as mit ecg database for verification, there is no public database that includes a simultaneous measurement of ppg s ignals linked with ecg signals. therefore, the hardware for simultaneous measurement of ecg and ppg signals was manufactured for the acquis ition of b io-signals for the recognition algorithm in this study. fig. 1 ecg and ppg measurement system blockdiagram fig. 1 shows the block diagram and the photograph of the manufactured ecg and ppg measurement system hardware. ecg was measured in three channels (la-ra, ll-la, and ra-ll) based on the willem einthoven triangle method. moreover, low-pass filters and high-pass filters with cutoff frequencies of 0.16hz and 160hz, respectively, were implemented in hardware, with the total amplification gain of the ecg signal being 1500, as shown in (a-b) and (a-c) of fig. 1. for ppg measurement, the output signal from the filter and the original signal were d ifferentially amplified by implementing a high-pass filter with cutoff frequency of 0.1 hz in o rder to prevent the saturation due to the dc offset from the light output during amplification, as shown in the ppg measurement hardware in fig. 1. moreover, a band-pass filter with cutoff frequencies of 0.1hz and 8hz was designed and implemented. fig. 2 shows an actual measured signal being displayed and stored on pc. fig. 2 measurement software 2.2. peak detection from ecg and ppg signals through dstw fig. 3 dstw peak detection method[6] peaks are detected from the ecg signal by generating dstw, as shown in fig. 3, in order to firstly detect the r peaks in ecg, which are convenient to detect [6]. after the r peak is detected as shown in fig. 4, q, s, p, t, and end of t are sequentially detected in accordance with a given detection rule (eqs. 15). fig. 4 results from the detection of fiducial points from ecg signal (p, q, r, s, t, te) (subject 4) advances in technology innovation, vol. 2, no. 3, 2016, pp. 89 94 91 copyright © taeti fig. 5 results from the detection of ppg peaks (onset, peak) (subject 4) the points to be detected from the ppg signal were selected to be the onset points, which are the initial points, and ppg peaks. onset peaks are used to detect the fiducial points in accordance with g iven ru les (eq. 6), after the ppg peak has been detected as shown in fig. 5.    q k index( [ ]), min arg x n for  r k 30 n r(k)   (1)    s k index( [ ]), min arg x n for    r k n r k 30   (2)     p k index( ), max arg x n for  q k 60 n q(k)   (3)     t k index( ), max arg x n for    s k n s k 100   (4)     k index( ), end min t arg x n for    t k n t k 50   (5)     onset k index( ), min arg p n for    k 100 n k peak peak ppg ppg   (6) where k denotes the indices of each peak from one to m (1≤k≤m), and n denotes the indices of the sampled data for x(n) and p(n). the actual data were sampled at 250 hz, and n=1 implies 4 ms 〖 (t〗 _s=1/f_s ) 2.3. feature extraction as shown in fig. 6, the features for b iometric recognition can be extracted by detecting the six types of ecg peaks and the two types of ppg peaks. for this algorithm, a total of 21 features were established by extracting 15 types of ecg features, 3 types of ppg features, and 3 types of features relating to both ecg and ppg. 2.4. support vector machine for classification svm is a new genre of learning systems for pattern recognition, devised by corters and vapnik [7]. while svm did not receive much attention initially, it is recently being used in various fields including bio informatics, character recognition, handwriting recognition, facial recognition, and object recognition, and is widely used for supervised pattern recognition owing to its excellent performance. fig. 6 extraction of 21 features from ecg and ppg peak detection the train ing and classificat ion algorithm for the proposed algorithm was based on one-against-one multi-class svm algorithm, which is not affected by the curse of dimensionality. 160 peaks were detected (p, q, r, s, t, and tend) from the ecg signals simultaneously acquired from each of the 33 test subjects, and, likewise, 160 peaks (onset, and ppgpeak ) were detected from the ppg signals, forming a set of 21 features for each peak. from each of the 34 dataset files, the first (10-80) features were used as the training data, and the other (140 – 80) features were used as the testing data. moreover, we examined the difference in recognition rate between the case where only ecg features are considered, and the case where both ecg and ppg features are considered. 3. results and discussion 3.1. testing method for the experiment, the testing data were not provided with any informat ion for recognition, and the average and standard deviation of the performance evaluation elements were investigated, such as accuracy, sensitivity, specificity, false reject ion rate (frr), and false acceptance rate (far) of the result with varying number of training data points. the formulae for frr and far are shown in eqs. 13 and 14, respectively. for biometric recognition systems, it is common to measure the equal error rate (err) performance index, which is where frr and far coincide, and this was achieved by analyzing the frr and far, and the resulting err and receiver operating characteristic (roc) curve while increasing the threshold value fo r the distance measurement algorithm for the decision of recognition from a lower value to a higher value [14]. advances in technology innovation, vol. 2, no. 3, 2016, pp. 89 94 92 copyright © taeti frr = 𝑁𝑤 𝑁𝑡 × 100 (7) far = tr−tn tr × 100 (8) where nw is number of wrong recognition, nt is number of testing data for target subject, tr is total recognition number for taget subject, tn is testing data number. moreover, the sensitivity and specificity of the proposed algorithm were investigated using the true positives (tp), the false positives (fp), and the false negatives (fn). for a biometric recognition algorithm, tp, fp, and fn are defined as follow:  tp (true positive): number of accurately recognized test subjects.  fp (false positive): number of falsely recognized test subjects. (the number of data points classified as the subject in question – tp)  fn (false negative): the number of subject data points that should have been recognized, however, were not recognized. (the number of testing data points from each subject -tp) sensitivity and specificity are defined by eqs. 9 and 10 below, respectively. sensitivity = tp tp+ fn × 100 (9) specificity = tp tp+ fp × 100 (10) 3.2 testing result table 1 recognition performance indices with both ecg and ppg signals used ppg and ecg features analysis and multi class classifier training number 10 20 30 40 50 60 70 80 accuracy (%) avr 92 95 96 97 97 98 99 99 std 10 9.0 5.7 4.8 2.6 2.0 1.6 1.6 frr (%) avr 7.2 4.7 3.1 2.4 2.6 1.2 0.8 0.8 std 10 9.0 5.7 4.8 2.6 2.0 1.5 1.6 far (%) avr 6.7 4.3 2.8 2.3 2.3 1.1 0.8 0.8 std 7.8 6.8 4.9 3.6 2.8 2.0 1.3 1.5 sensitivity (%) avr 93 95. 96 97 98 98 99 99 std 10 9.0 5.7 4.8 2.6 2.0 1.6 1.6 specificity (%) avr 93 95 97 97 98 98 99 99 std 7.8 6.8 4.9 3.6 2.8 2.0 1.4 1.5 fig. 7 roc curve with varying training data size (15 ecg features used only) fig. 8 roc curve with varying training data size (21 ecg and ppg features used) fig. 7 shows the performance indices of recognition using a mult i-class svm classifier with 15 ecg features detected from the actual measurement data from 33 test subjects. 89.92% accuracy, 10.08% frr, 9.79% far, 89.92% s ens it iv ity , and 90. 21% s pecific ity were observed when the classifier is trained with 80 heartbeat data obtained from the ecg s ignals advances in technology innovation, vol. 2, no. 3, 2016, pp. 89 94 93 copyright © taeti from each subject. this result corresponds to the recognit ion with respect to 2,640 tes t ing heartbeat data from a total of 33 ecg signals. the proposed algorithm was tested based on a total of 21 feature points, by adding the 6 ppg feature points measured simultaneously from the same subject to the 15 ecg feature points. recognition performance indices, which are shown in table 1, d isplayed the results of 99.28% accuracy, 0.88% frr, 0.85% far, 99.28% sensitivity, and 99.31% specificity. this is the performance when 80 training data points from the ecg and ppg signals measured from 33 test subjects are used, and 2,970 testing data points were used overall. moreover, as shown in tab le 1 and fig. 8, the accuracy index shows the high performance of 92.7% even when 10 training data points are applied out of the 160 heartbeat data from each subject (4,950 testing heartbeat data). the result of the above test is better than or equal to the performance o f the e xis t ing common recognit ion s ys tems , and the recognit ion performance is observed to be extremely higher compared to the previous test. therefore, it can be deduced that the consideration of the features of two types of signals for the design of b iometric recognition systems leads to a higher recognition performance than when a single type of signal is used. 4. conclusions this paper concerns the implementation of a multi-modal biometric recognition system and algorithm, wherein ecg and ppg signals were used for the recognition. since there is no previous database where ecg and ppg signals are linked, a biometric system that is capable of actual ecg and pp g meas urements was manufactured, and three channels of ecg signal and one channel of ppg signal were acquired from a total of 33 subjects for 3 minutes. lead-i signal of the three channels of ecg signals only and the 1-channel ppg signal were selected for recognition. with the ecg signals acquired from each sub ject , 160 heartbeats were separated and 15 ecg features were ext racted from each heartbeat. moreover, 4 ppg features related to ecg and 2 features of ppg only were selected, so that a total of 21 features were used for the recognition. the recognition performance indices of the proposed biometric recognition system were investigated by adjusting the number of train ing heartbeat data between 10 and 80. the performance indices of the recognition based on ecg features only were found to be 89.92% accuracy, 10.08% frr, 9.79% far, 89.92% sensitivity, and 90.21% s pecificity . furthermore, the perfor mance indices of the recognition combining ppg were found to be 99.28% accuracy, 0.88% frr, 0.85% far, 99.28% sensitivity, and 99.31% specificity, when there are 80 heartbeat data for training, which indicate an ext remely high recognition performance. therefore, it can be deduced that the use of the features of a combination of more than two bio-signals can lead to a higher recognition performance than the use of a single bio-signal. moreover, the recognition system based on the combination of the two signals exhibits the performance of 92.77% accuracy, 7.23% frr, 6.29% far, 92.77% sensitivity, and 93.21% specificity, even when 10 heartbeat data are used for training, which can be viewed as an extremely high recognition performance, considering that there were 4,950 testing heartbeat data. acknowledgement this work was supported by the human res ource train ing program for regional innovation and creativity through the ministry of education and national research foundation of korea (nrf-2014h1c1a1066998). references [1] l. biel, et al., “ecg analysis: a new approach in human identification,” ieee trans act ions on inst rumentat ion and measurement, vol. 50, no. 3, pp. 808-812, 2001. [2] j. m. irv ine, et al., “eigenpulse: robust human identification from cardiovascular function,” pattern recognition, vol. 41, no. 11, pp. 3427-3435, 2008. [3] t. w. shen and w.j. tompkins, “biometric statistical study of one-lead ecg features and body mass index (bmi),” 27th annual international conference engineering in medicine and biology society, ieee press, september, 2005. [4] s. a. israel, et al., “ecg to identify individuals,” pat tern recognit ion , vo l. 38, no . 1, pp . 133-142, 2005. [5] k. n. plataniotis, d. hatzinakos, and j. k. m. lee, “analysis of human electrocard iogram ecg for b iometric recognit ion ,” proc. o f advances in technology innovation, vol. 2, no. 3, 2016, pp. 89 94 94 copyright © taeti biometrics symposiums, baltimore, usa, 2006. [6] j. kim, et al., “an event detection algorithm in ecg with 60hz interference and baselinewandering,” proceedings of the 2nd internat ional conference on interact ion sciences, information technology (icis ‘09), culture and human new york, ny, usa, 2009. [7] c. cortes, and v. vapnik, “support-vector network,” machine learn ing, vol. 20, no. 3, pp. 273-297, 1995.  advances in technology innovation, vol. 2, no. 1, 2017, pp. 22 24 22 experimental study of leaching and penetration of nitrite ions in nitrite-type repair materials on the surface of concrete masumi inoue 1,* , heesup choi 1 , yuhji sudoh 2 , and koichi ayuta 1 1 department of civil and environmental engineering, kitami institute of technology, hokkaido, japan. 2 chemicals division. basic chemicals department, nissan chemical industries, ltd., tokyo, japan. received 29 january 2016; received in revised form 25 march 2016; accepted 28 march 2016 abstract this study aimed to clarify the leaching properties of nitrite ions in nitrite-type repair materials exposed to rainfall. repaired concrete specimens were prepared for leaching tests using a lithium nitrite solution, and the amounts of leaching and penetration of nitrite ions were measured under simulated rainfall. the results demonstrated that the amount of leaching could be controlled by using polymer cement paste and mortar surface coatings containing lithium nitrite solution, and by using polymer cement mortar surface coatings following direct lithium nitrite solution coatings. furthermore, the amount of nitrite ion leaching in all cases was lower than the discharge standard value established by the water pollution control law. keywords: nitrite-type repair material, nitrite ion, leaching, penetration, polymer cement mortar, polymer cement paste 1. introduction in general, nitrite-type repair materials are commonly used for the purpose of minimizing of corrosion of reinforcements in concrete structures. it is widely known that nitrite ions effectively regenerate passive films on reinforcement surfaces of concrete as they penetrate the surrounding areas [1-3]. however, since nitrite ions easily dissolve in water, there is concern that they can be leached from the surfaces of repair materials upon exposure to rainfall. the aim of this study was to elucidate the leaching properties of nitrite ions in nitrite-type repair materials exposed to rainfall. repaired concrete specimens were prepared for leaching tests using a lithium nitrite solution, and the amounts of leaching and penetration of nitrite ions were measured under simulated rainfall conditions. 2. method the repair methods, which used a 40% water solution composed of lithium nitrite (ln40), are shown in table 1. these methods are widely used in repair work sites. the repaired concrete specimen is shown in fig. 1. the water-cement ratio was 60%. the specimen was demolded one day after casting, cured in water (20±1 °c) until the age of seven days, and then stored in room-temperature conditions (20±1 °c and 50±5% relative humidity). after curing, the test surface was polished with a sand paper, and cleaned via air-cleaning, and the specimens were repaired using ln40. after repairing, the repaired specimens were cured in room-temperature conditions (20±1 °c and 50±5% relative humidity) for seven additional days. the specimen surfaces excluding test surfaces were coated with an epoxy resin in order to prevent nitrite ion penetration. the installation conditions of the specimens are shown in fig. 2. specimens were installed at a 35° angle and attached to an acrylic plate on the side. in the leaching test, distilled water simulating rainfall was sprayed to the specimen test surfaces. the amount of water sprayed each day was 1.86 g/mm 2 , a value reflecting the av* corresponding author, email: m-inoue@mail.kitami-it.ac.jp advances in technology innovation, vol. 2, no. 1, 2017, pp. 22 24 23 copyright © taeti erage annual rainfall in japan (about 1,700 mm). a wet-dry cycle consisted of one day of spraying and three days of drying, a pattern reflecting the average annual rainfall in japan (about 128 days). the wet-dry cycle was repeated for one year (91 cycles). distilled water was sprayed every two hours from 10:00 am to 4:00 pm on a spraying day. the amount of water sprayed each time was 0.465 g/mm 2 (a quarter of 1.860 g/mm 2 ). distilled water flowing down the test surface was collected after every spraying, and the leached nitrite ion (no2 ) concentration was measured using ion chromatography. in the penetration test, distilled water simulating rainfall was sprayed using the same method as the leaching test. however, the no2 concentration in the repair material and repaired concrete was measured at 6 months (45 cycles) and 1 year (91 cycles). table 1 repaired concrete specimens name of specimen repair method no2 solid amount (g) leaching penetration n non repair 0 ln coating of ln40 6.26 0.70 lnpcp surface coating by pcp*1 using ln40 (thickness:2mm) 12.4 1.34 lnpcm surface coating by pcm*2 using ln40 (thickness:5mm) 22.9 2.54 ln+pcm surface coating by pcm*2 after coating of ln40 (thickness:5mm) 6.26 *1: polymer cement paste, *2: polymer cement mortar table 2 leaching ratio of no2 amount of leaching to no2 solid amount after 91cycles repair method ln ln pcp ln pcm ln +pcm no2 solid amount in repair material (g) 6.3 12.4 22.9 6.3 after 91 cycles no2 leaching (g) 1.39 0.52 0.93 0.49 no2 leaching ratio (%) 22.2 4.2 4.1 7.8 (a) leaching test (b) penetration test fig. 1 specimen overview fig. 2 installation conditions of specimens 3. results and discussion the no2 concentration changes found in the leaching test are shown in fig. 3, and the ratio of no2 amount of leaching to no2 solid amount after 91cycles is shown in table 2. the no2 leaching amount of ln was largest after every cycle, and the leaching ratio of no2 solid amount after 91 cycles was about 22%. the no2 leaching amount of ln+pcm after one cycle decreased by about 70% compared with that of ln. this is because the no2 leaching was controlled by the pcm coating. on the other hand, the no2 leaching amount of lnpcm was larger than that of lnpcp. however, the leaching ratio of no2 solid amount of lnpcm was almost same as that of lnpcp, as shown in table 2. this implies that there is no actual difference between the leaching properties of lnpcp and lnpcm. it was confirmed that the no2 concentration in all the repair methods changed at roughly 10 cycles. afterwards, the change in no2 concentration was small. although small amounts of no2 were detected, the concentrations of all repair methods after 10 cycles were almost same as that of n (non-repair). therefore, it is thought that no2 hardly leached after 10 cycles for this experimental range of conditions. considering the discharge standard of the water pollution control law, the no2 leaching amount of all cases in advances in technology innovation, vol. 2, no. 1, 2017, pp. 22 24 24 copyright © taeti every cycle was smaller than that of the discharge standard value (329 ppm). the ratio of no2 amount of leaching and penetration to no2 solid amount in repair materials after 91 cycles is shown in fig. 4. the no2 penetration and leaching ratio of ln were about 74% and 22%, respectively. on the other hand, in the case of lnpcp and lnpcm, both addition ratios of the amount of ion penetration in concrete and residual ions in the repair materials were about 90%. furthermore, both leaching ratios were equal to about 4%. therefore, it is thought that no2 leaching can be controlled using pcp or pcm containing ln40. the total ratios of no2 amounts of leaching and penetration including residual ions in repair materials were about 93-96%, and there was little difference between no2 solid amount of repair material and total no2 solid amount after 91 cycles. however, the difference was within the range of measurement error of ion chromatography. therefore, it is thought that the behavior internal and external of no2 in nitrite-type repair materials was mostly evaluated. fig. 3 change of no2 concentration in leaching test 4. conclusions the aim of this study was to clarify the leaching properties of nitrite ions in nitrite-type repair materials upon exposure to rainfall. repaired concrete specimens were prepared using lithium nitrite solution for leaching tests, and the amounts of leaching and penetration of nitrite ions were measured under simulated rainfall. the following conclusions were drawn from the investigation. 1) it was confirmed that the no2 concentration in all repair methods changed at approximately cycle 10. subsequent changes in no2 concentration were small. 2) the no2 leaching amounts of all repair methods in all cycles were smaller than that of the discharge standard value. 3) the no2 leaching can be controlled using pcp and pcm surface coatings with the addition of ln40 and surface coating by pcm after direct coating with ln40. fig. 4 ratio of no2 amount of leaching and penetration to no2 solid amount in repair materials after 91 cycles references [1] a. m. rosenberg, et al., “a corrosion inhibitor formulated with calcium nitrite for use in reinforced concrete,” astm, stp 629, pp. 89-99, 1977. [2] a. kobayashi, s. ushijima, i. kamuro, and m. koshikawa, “a study on the protection of steel in concrete by penetrative corrosion inhibitor,” journal of japan society of civil engineers, vol. 1990, no. 420, pp. 51-60, 1990. [3] t. hori, s. yamasaki, and y. masuda, “a study on the corrosion inhibiting effect of mortar with high nitrite content,” concrete research and technology, vol. 5, no. 1, pp. 89-98, 1994.  advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 reliability study of gan-on-sic hemt rf power amplifiers m. bakowski 4,*, j. lang 1 , j-k. lim 4 , j. hellén 3 , t. m. j. nilsson 3 , b. schodt 5 , r. poder 5 , i. belov 2 , p. leisner 1 1sp technical research institute of sweden, box 857, 501 15 borås, sweden. 2jönköping university, school of engineering, box 1026, 551 11 jönköping, sweden. 3saab ab, solhusgatan 10, 412 76 gothenburg, sweden. 4rise acreo ab, box 1070, 164 25 kista, sweden. 5sp technical research institute of sweden, a.c. meyers v. 15, 2450 copenhagen, denmark. received 21 july 2017; received in revised form 13 september 2017; accepted 19 september 2017 abstract the rf power amplifier demonstrators containing each one gan-on-sic, hemt, chz015a-qeg, from ums in smd quad-flat no-leads package (qfn) were subjected to thermal cycles (tc) and power cycles (pc) and evaluated electrically, thermally and structurally. two types of solders, sn63pb36ag2 and lead-free snagcu (sac305), and two types of tim materials, nanotim and tgontm 805, for pcb attachment to the liquid cold plate were tested for thermo-mechanical reliability. changes in the electrical performance of the devices, namely the reduction of the current saturation value, threshold voltage shift, increase of the leakage current and degradation of the hf performance were observed as a result of an accumulated current stress during pc. no significant changes in the investigated solder or tim materials were observed. keywords: gan-on sic, hemt, rf power amplifier, thermo-mechanical and electrical reliability 1. introduction radio frequency (rf) power amplifiers are used to convert a low-power signal into a higher power signal that drives the antenna of a transmitter. there are two trends in the rf amplifier applications. the first is replacing silicon-based transistors, such as ldmos fets, with gan high electron-mobility power transistors (hemt). this trend is observed, for example, in telecom applications. the second trend is a transition from gaas devices to gan-on-sic hemts, which is observed in the applications with higher demands on output power and reliable high temperature operation, such as military applications. the motivation for this study is the replacement of gaas transistors with gan-on-sic devices in rf power amplifiers in order to satisfy demands for higher output power, higher operating temperature (<200c) and higher system efficiency [1]. reliability of wbg semiconductors and especially of gan hemts is of primary importance and a subject of increasing number of investigations [2-6]. the subject of investigations is most often devices themselves. the objectives of this investigation are to experimentally investigate thermo-mechanical robustness of rf power amplifiers including packaged hemt devices assembled on pcb boards and exposed to power cycling (pc) and thermal cycling (tc) and to evaluate prospective thermal management methods including thermal interface materials (tim) by experiment and simulation. to satisfy environmental demands, there is also need for investigation of thermo-mechanical behavior of modern lead-free solder alloys in harsh environments. * corresponding author. e-mail address: mietek.bakowski@ri.se tel.: +46-70-7817760; fax: +46-8-7517230 advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 158 2. experimental in total 50 rf amplifier demonstrators were assembled for the study. they consisted each of an 8 cu-layer pcb board with a simplified hf design containing one gan-on-sic, hemt, chz015a-qeg, from ums in smd quad-flat no-leads package (qfn). two types of solders, sn63pb36ag2 and lead-free snagcu (sac305), and two types of tim materials, nanotim and tgontm 805, for pcb attachment to the liquid cold plate were tested for thermo-mechanical reliability. in 8 cu-layer pcb (25x35 mm) layers 2 and 7 contain solid cu while layers 3 to 6 contain a 25% symmetrical cu-layers with daisy chains. the outer material is ro4350 and material in-between cu-layers is fr4. the transistor area (3.5x3.5 mm) is covered by 0.3 wide cu-plated vias distributed with 0.5 mm spacing center to center (fig. 1). 24 demonstrators were subjected to thermal stress by 2300 thermal cycles (tc) between -20°c and 80°c and remaining 26 were subjected to the electrical and thermal stress by power cycling (pc) with drain current of 100 ma at a drain voltage of 45 v and cycle time of 2 min. hf characterization of all the boards was done before subjecting them to the thermal and electrical stresses. all the devices were also subjected to static electrical characterization by measuring threshold voltage and output and voltage blocking characteristics. the static electrical and hf characterizations were performed again after 2300 cycles of tc stress and after 1100, 4700 and 14500 cycles of pc stress. in addition, failure analysis was performed on the tc and pc stressed demonstrators by using optical microscopy and 2d x-ray microscopy. (a) cross-section (b) top view fig. 1 rf amplifier demonstrators the main reason for the tc tests was to test the reliability of the solder joints. the suggested tests were based on standard ipc 785, treating hemt devices and solder. one thermal cycle took 113 min. one month of the accelerated test is equal to about one year of use in field conditions. the temperature in the chamber and the temperature on at least one board were recorded during the whole test. fig. 2 pc arrangement on a liquid cold plate and tc arrangement in climatic chamber advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 159 the main reason for the pc tests was to investigate degradation of the transistor package, including the die, solder joints and tim during cyclic heating and cooling. the temperature distribution on the hemt package and pcb was measured several times during the test by thermal imaging and by thermocouples. power cycling was performed at room temperature with demonstrator boards mounted on a liquid cold plate. the cycle time was set to 2 min and total number of cycles corresponds to 20 years of use. the boards were id labeled and underwent a screening procedure under which some were visually inspected, powered up and investigated with x-ray. after finishing tc and pc tests selected boards were visually inspected in white light, x-rayed and a couple of boards were subjected to cross-section investigations for failure analysis. 3. results the results of electrical and hf characterization show clearly changes and degradation in device performance as a function of the number of the pc cycles and accumulated current stress time. an increase of the leakage current is observed also after tc tests. no significant differences between the boards equipped with different solder and tim materials were observed which means that the observed changes in performance are due to the degradation of the hemt devices. 3.1. pc tests 26 boards were mounted on a cold plate (water cooling with a flow of 0.015 l/s) with thermal paste between the al-plate of the demonstrator and the cold plate. the transistors were exposed to drain voltage of 45 v and a varying gate voltage of -1.9 v to – 3.0 v. at -1.9v the gate was opened yielding a drain current of ~100 ma. an equal on/off sequence of total 2 min was repeated in total 14 500 times to correspond to 20 years of use. the 26 boards were divided into two groups connected in parallel and run with one power supply per group. the experimental set-up is shown in fig. 2. 3.1.1. output characteristics typical output characteristics of the investigated devices are shown in fig. 3 after various numbers of pc cycles. the summary of values of saturated drain current before and after 14500 cycles of pc is shown in fig. 4 for three groups of boards having different solder and tim materials (sn63pb36ag2&tgon805, sac305&tgon805 and sac305&nanotim). the saturated drain current values were taken for therain voltage vds=10 v and gate voltage vgs=0.8 v. a reduction in value of the saturation current is about 16 %, regardless of the type of the solder or tim material used. the observed reduction in the value of saturation current (vds=10 v, vgs=0.8 v) is about 5, 12 and 16 % after 1100, 4700 and 14500 cycles of pc stress, respectively. voltage, v 0 2 4 6 8 10 12 14 c u rr e n t, m a 0 100 200 300 400 500 pre-stress 1100 power cycles 4700 power cycles 14500 power cylces v gs = 0.8 v v gs = 0.6 v v gs = 0.4 v v gs = 0.2 v i sat at v gs = 0.8 v, v ds = 10 v device type s at ur at ed d ra in c ur re nt , m a 340 360 380 400 420 440 460 480 500 520 sn63pb36ag2 snagcu (sac305) nano tim before pc after pc fig. 3 typical output characteristics measured on the same device after various numbers of power cycles fig. 4 saturation current values measured before and after 14500 cycles of pc stress advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 160 the time dependence of the saturation current values is attributed to the degradation of the hemt characteristics and is discussed further in the discussion section below. 3.1.2. threshold voltage shift the threshold voltage was measured at vds=45 v by sweeping gate voltage, vgs, from -7 v to 0 v. the threshold voltage value was taken as a gate voltage corresponding to drain current ids=10 ma. there is a clear tendency of the threshold voltage shift towards more negative values showed by devices from different groups (sn63pb36ag2&tgon805, sac305&tgon805 and sac305&nanotim) as shown in fig. 5. the shift is by -0.1 to -0.15 v from the typical value of about -2.25 v. v th at 10 ma device type t h re s h o ld v o lt a g e , v -2,8 -2,6 -2,4 -2,2 -2,0 before pc after pc sn63pb36ag2 snagcu (sac305) nano tim fig. 5 threshold voltage values measured before and after 14500 cycles of pc stress 3.1.2. leakage current the leakage current is less well behaved. there are devices with relatively small change in leakage current but also devices which show an increase in leakage current by a factor larger than 2, as a result of the pc stress. the typical forward blocking characteristics of the devices after varying numbers of power cycles are shown in fig. 6. the measurements were done sweeping drain voltage, vds, up to 100 v with gate voltage vgs=-7 v. the devices display high values of leakage current with the relatively strong dependence on the drain voltage. fig. 6 typical forward blocking characteristics of the investigated hemt devices after consecutive series of power cycles (vgs=-7 v) the summary of the leakage current data as a function of a number of power cycles is discussed in the discussion section below. 3.2. tc tests 24 boards were exposed to 2300 temperature cycles of ∆t=100 °c between -20 °c to +80 °c in a temperature chamber. the ramping up/down slope was around 2-3 °c/min and the dwell time was 15 min. 12 boards had lead solder material and 12 advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 161 boards had lead free solder material. the two kinds of boards (lead & lead free) were evenly mixed over the grid in the chamber as shown in fig. 2. the boards were electrically characterized before and after the thermal cycles. 3.2.1. saturation current and threshold voltage figure 7 shows summary of saturated drain current and threshold voltage values for the boards with lead free solder. results show only minor changes after tc stress. the data for the reference boards with lead solder are very similar. these changes could be possibly related to the deterioration of the solder joints, however, no change in the joints was observed when performing material analysis. visual inspection as well as 2d x-ray imaging was performed on all the thermally cycled demonstrators. no failures related to the soldering were revealed during both tc and pc experiments. fig. 7 saturated drain current value and threshold voltage value before and after tc stress 3.2.2. leakage current a significant increase of leakage current was observed in almost all the devices after the tc test as shown in figs 8 and 9. the mechanism behind this behavior is not clear. fig. 8 typical blocking characteristics of the investigated hemt devices before and after 2300 thermal cycles of tc fig. 9 leakage current before and after 2300 cycles of tc stress 3.3. hf performance the rf measurements were performed using a network analyzer and registering s parameter values corresponding to the frequency of 1.3 ghz as shown in fig. 10. results of hf measurements show a slight decrease in s11 (return loss) and s21 (gain) parameters from -10.91±0.23 to -10.0±0.21 and from 16.04±0.24 to 15.51±0.28, respectively, after pc stress (measurement conditions vds=45 v, ids=100 ma, power level 5 dbm, 1.3 ghz). the summary of forward gain results (s21) is presented in fig. 11 and the summary of forward gain and return loss for sac305 boards is shown in fig. 12. overall, the high frequency measurements show a slight performance degradation of the power cycled boards and the same trend is observed for the demonstrators with lead free and lead solder. advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 162 fig. 10 measurement of s21 (upper curve) and s11 (lower curve) parameters in the frequency range 30 khz to 3 ghz fig. 11 forward gain (s21) of boards with standard and lead-free solder before and after 14500 cycles of pc stress fig. 12 forward gain (s21) and return loss (s11) of all boards with led-free solder before and after pc stress 3.4. thermal modeling fig. 13 ir measurement and cfd simulation advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 163 temperature distribution measured with ir camera and result of cfd calculation are shown in fig. 13 for dissipated power of 7.2 w (steady state) with tcoolant=11 °c, tamb=21 °c. a good qualitative agreement has been obtained between measurements and simulations. the coolant flow of 0.15-0.19 m/s is optimal for the set-up. other simulation results are that influence of using different solder materials is less than 1°c and that the newly developed nanotim results in 7°c lower temperature compared to commercially available tgon 805. validation of the transient cfd model is demonstrated in fig. 14 and fig. 15. fig. 14 test board with attached thermocouples fig. 15 simulated and measured temperature on chip and on pcb board (b) under tc pulse the significant finding shown in fig. 16 is that temperatures at different soldering locations of qfn hemt package are very different. it is important to take that into consideration when establishing and modeling reliability of soldered joints. fig. 16 temperature at the qfn package and at pcb obtained from ir measurements 3.5. material analysis to reveal possible failures in solder joints, the packages were inspected with sem and 2d x-ray, fig. 17 and fig. 18. no obvious visual damage to the test pcbs was identified and no significant failure modes for the solder joints or component cases were revealed after pc and tc tests. advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 164 fig. 17 sem images of a cross section of failed power cycled and thermally cycled devices with sac 305 fig. 18 2dx-ray images of a cross section of failed power cycled and thermally cycled devices with sac 305 4. discussion the electrical parameters that are clearly influenced by the pc are the saturation value of the drain current and leakage current. the drain saturation and leakage currents of all the devices show logarithmic dependence on the stress time (number of pulses), as can be seen in figs 19 and 20. this is an indication that the changes are most probably related to charge trapping at the near interfacial trapping sites located in the algan layer or in the passivation layer. assuming trapping sites are distributed in distance from the specific interface and that charging is governed by the tunneling mechanism leads to the logarithmic dependence of the accumulated charge on charging time [6]. this is because the charge transfer to the trapping sites becomes less efficient, as trapping sites closest to the interface become occupied, due to exponentially decaying tunneling probability with distance. the same time dependence is then reproduced by drain saturation current and leakage current given relatively linear dependence of these two parameters on the interface charge. fig. 19 saturated drain current value versus number of power cycles fig. 20 leakage current value versus number of power cycles advances in technology innovation, vol. 3, no. 4, 2018, pp. 157 165 copyright © taeti 165 also tc has influence on leakage current as can be seen in figs. 8 and 9. however no significant influence of the tc on the remaining parameters was registered (fig. 7). investigated devices show high leakage currents and soft blocking characteristics that seem to be easily influenced by thermal and electrical stress. some of the experienced device failures are most probably related to the device voltage blocking properties. in total 11 boards failed during the tests, 10 out of 26 tested boards failed during the pc runs and 1 out of 24 tested boards failed during the tc run. 5. conclusions changes in electrical performance of the devices namely reduction of the drain current saturation value, threshold voltage shift, increase of the leakage current and degradation of the hf performance were observed as result of an accumulated current stress during pc tests. the most significant changes were observed in the drain saturation current and in the leakage current of the devices. the changes in these two parameters seem to be logarithmic in time and indicate that the mechanism behind them is charging of near interface states either in the algan layer or in the passivation by tunneling. a high rate of failures (40%) was observed in the pc tests. the failures are predominantly related to the same mechanism that governs the increase of the leakage current. also thermo-mechanical stress due to tc resulted in the increase of the leakage current of the devices. no significant visual damages in the investigated solder or tim materials were visually observed in electron microscopy and 2d x-ray microscopy after pc and tc tests. acknowledgments the support of vinnova, sweden ś innovation agency, and sweden energy authority of this project with number 2014-05667, is acknowledged. references [1] u. k. mishra, l. shen, t. e. kazior, and y. f. wu, “gan-based rf power devices and amplifiers,” proc. the ieee, vol. 96, no. 2, pp. 287-305, february 2008. [2] h. kim, v. tilak, b. m. green, j. a. smart, w. j. schaff, j. r. shealy, and l. f. eastman, “reliability evaluation of high power algan/gan hemts on sic substrate,” physica status solidi (a), vol. 188, no. 1, pp. 203-206, november 2001. [3] y. c. chou, d. leung, i. smorchkova, m. wojtowicz, r. grunbacher, l. callejo, q. kan, r. lai, p. h. liu, d. eng, and a. oki, “degradation of algan/gan hemts under elevated temperature lifetesting,” microelectronics reliability, vol. 44, no. 7, pp. 1033-1038, july 2004. [4] e. zanoni, g. meneghesso, m. meneghini, a. stocco, f. rampazzo, r. silvestri, i. rossetto, and n. ronchi, “electric-field and thermally-activated failure mechanisms of algan/gan high electron mobility transistors,” ecs transactions, vol. 41, no. 8, pp. 237-249, 2011. [5] g. meneghesso, m. meneghini, d. bisi, r. silvestri, a. zanandrea, o. hilt, e. bahat-treidel, f. brunner, a. knauer, j. wuerfl, and e. zanoni, “gan-based power hemts: parasitic, reliability and high field issues,” ecs transactions, vol. 58, no. 4, pp. 187-198, 2013. [6] a. barnes, esccon 2013, 12-14 march 2013, esa/estec, holland. [7] f. b. mclean, h. e. boesch, j. m. mcgarrity, and r. b. oswald, “rapid annealing and charge injection in al2o3 mis capacitors,” ieee transactions on nuclear science, vol. 21, no. 6, pp. 47-55, december 1974.  advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 application of rotating arms type permanent magnet motor chih-chiang hong 1,* , deng-maw tsai 2 department of mechanical engineering, hsiuping university of science and technology, taichung, taiwan, roc received 17 april 2018; received in revised form 15 june 2018; accepted 14 july 2018 abstract the present application related to a rotating arm type permanent magnet motor, in particular to a permanent magnet motor that was actuated by the action of the magnetic forces of a permanent magnet stator of a stator module and two thin ring permanent magnets of a rotor module. the purpose of present permanent magnet motor was to provide the torque produced by a magnetic force of the magnetic energy of a stator to drive the rotation of the rotor. the rotating arm type permanent magnet motor comprised an external support frame base, a stator module and a rotor module. the external support frame base included an upper frame, a lower frame and two side frames. the stator module included an elastic metal plate cantilever arm and a permanent magnet stator. the rotor module included a rotating shaft, a double arc shaped rotating arms type support frame, and two thin ring permanent magnets. magnet material n45h (sintered nd–fe–b) was used for the permanent magnets of stator and rotor. the values of magnetic forces (attraction force and exclusion force) were inverse proportional to the position distances of poles (n pole and s pole) above the top level of thin ring permanent magnets, e.g. c= 12mm. the greater value of magnetic forces got the faster rotation speed. the values of magnetic forces could produce the good enough torque for the thin ring permanent magnets to rotate the shaft when position b= 8mm better than that when position b= 17mm. in the future, with the help of using an external swing motion of electrical controlled swing-type device to produce complete rotation, the present permanent magnet motor might save electricity and power sources. some preliminary rotation speed data of rotating shaft in a permanent magnet motor were obtained and presented with manually controlled. keywords: rotating arms type, permanent magnet motor, stator, rotor 1. introduction some kinds of power sources including electric power, water power, wind energy and solar power are used and applied in many fields. the electric power is generated in power plant that usually operated and supplied by fossil fuel. electricity is used as a power in the electromagnetic motor to transfer electrical energy into mechanical energy and drive the movement of mechanism into the forms of rotation, vibration and linear motions. in 2018, woodford [1] presented the movement rule, rotational work and motor type for the electromagnetic motor. in 2018, liu et al. [2] presented the motor's efficiency and working capacity of electromagnetic-fluid-thermal simulations for the permanent magnet linear motor (pmlm). water power is used to generate electricity in water storage reservoir, water usually used and operated through the dam were built in the valley and water flows all year round in the rivers. wind energy and solar power are usually used in the fields of renewable energy sources (res) for better friendly life of the natural environment. in 2016, boie et al. [3] presented an integration analysis for the developments of res and electricity market in north african (na). also, improving electric motor efficiency * corresponding author. e-mail address: cchong@mail.hust.edu.tw tel.: +886-919037599; fax: +886-4-24961187 advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 38 is more interested in a permanent magnet motor to save energy and reduce energy consumption. in 2015, sun and zhang [4] introduced a novel bi-directional energy conversion system to provide high efficiency of voltage on permanent magnet direct current (dc) motor by using a super-capacitor rather than a battery. there are some control applications in the type of permanent magnet synchronous motor (pmsm), permanent magnet brushless direct current (pmbldc) motor, linear motor, stepper motor and alternating current motor. in 2013, ramírez-leyva et al. [5] used a power electronics texas instruments experimental system to validate the passivity strategy of a pmsm speed control. higher performance of the controller can be reached by using the pmsm. in 2012, demirtas and karaoglan [6] used the response surface methodology (rsm) to obtain the proportional integral controller coefficients in a pmbldc motor. some optimal parameter values are found by using the rsm tuning. in 2009, hassanpour isfahani and vaez-zadeh [7] presented the high efficiency, high power factor and high power density of line start permanent magnet electric synchronous motors to reduce the energy consumption. for the fans, compressors and pump applications which move a fluid, the load torque is proportional to the square of the rotational speed. in 2008, ganssle et al. [8] described the rotor with alternating north and south poles in permanent magnet stepper motor. as the coils are energized by electric, the rotor is pulled around. in 2007, bolund et al. [9] gave an overview of flywheel technology and application, and studied the flywheel rotor stored the kinetic energy in high voltage motor/generators for renewable energy generation. in 2006, matsuura [10] reviewed the nd–fe–b (neodymium-iron-boron) sintered magnets for the applications of industrial motor, automobile and electric appliances. some improvements of permanent magnet properties still undergoing invented. in 2004, compter [11] presented the six degrees of freedom of movement control for the electro-dynamic planar motor with moving coils to generate two directional movements. in 2002, coey [12] reviewed the permanent magnet applications of the magnetic force effects in three types of magnetic fields, for actuators, motors, generators and sensors in uniform magnetic field, for controlling beams, bearings and mineral separations in non-uniform magnetic field, and for magnetometers, switchable clamps and metal separation in time-varying magnetic field. in 2013, chowdhury [13] introduced the kinetics and multidisciplinary enterprise future in molecular motor. it would be a challenge intended to drive a motor without using external electric power or gas power for the better living environment in the future. the author presented and published the us patent for the manuscripts. in 2016, hong [14] presented the rotating arm type permanent magnet motor in the patent us 2016/0094095 a1. the author also presented some papers about the investigations of permanent magnet and magnetostrictive materials. in 2014, hong [15] completed the simple design and application of a bending type segment permanent magnet actuator with n45h (sintered nd–fe–b) material. in 2013, hong [16] used the terfenol-d material to design and construct the application of a magnetostrictive actuator. in 2013, hong [17] studied the transient response of magnetostrictive functionally graded material (fgm) square plates under rapid heating with the generalized differential quadrature (gdq) method. in 2012, hong [18] used the gdq method to investigate the rapid heating induced vibration of magnetostrictive fgm plates. it is interesting to investigate and develop a new rotating arm type permanent magnet motor that comprising an external support frame base, a stator module and a rotor module. the purpose of this paper is to investigate the possible rotational motion of permanent magnet motor. in the future, with the help of using an external swing motion of electrical controlled swing-type device to produce complete rotation, the present permanent magnet motor might save electricity and power sources. 2. design and construction new design and application of permanent magnet motors were developed and constructed as shown in fig. 1. the rotating arm type permanent magnet motor comprising an external support frame base, a stator module and a rotor module. the external support frame base included an upper frame, a lower frame and two side frames. each of the upper and lower frames had a through hole formed at a position near a center position, and the bearing was installed in the center position. the rectangular block made in aluminum material with outer dimensions 220 mm  100 mm  20 mm was used as the frame advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 39 base, and used the copper wire cutoff manufacturing machine to cut off the rectangular inner block with dimensions 180 mm  80 mm  20 mm. drilled the through holes 𝜙8 mm in the central position for rolling bearings and rotating shaft to be installed into the positions. the rolling bearings with outer diameter 𝜙8 mm, inner diameter 𝜙5 mm and length 2mm were used to fix rotated shaft. the rotating shaft made in aluminum material with diameter 𝜙5 mm, length 150mm was used to perform the rotational motion. the rotor module included a rotating shaft, a double arc shaped rotating arms type support frame, and two thin ring permanent magnets, wherein a left and right bracket was installed onto the left and right side of the double arc shaped rotating arms type support frame, respectively, and a center hole was formed at the center of the double arc shaped rotating arms type support frame, and the thin ring permanent magnet was an n45h permanent magnet. in each side of the double arc shaped rotating arms type support frame with outer diameter 𝜙76 mm, inner diameter 𝜙66 mm, arc angle 240°, made in aluminum material was shown in fig. 2. two thin (2mm thickness) ring permanent magnets were fixed onto each side surface of the double arc shaped rotating arms type support frame, respectively. the stator module included an elastic metal plate cantilever arm and a permanent magnet stator, wherein the elastic metal plate cantilever arm was a sus304 stainless steel plate, and the permanent magnet stator was also an n45h permanent magnet. permanent magnet n45h also called “neo” or “nd-fe-b” magnets were used for the magnet material. the thin ring permanent magnet n45h with outer diameter 𝜙76 mm, inner diameter 72mm, height 10mm as shown in fig. 3 was provided by mag city co., ltd. company located in taiwan. the permanent magnet stator with 11mm arc length, 10mm height and 2 mm thickness thin permanent magnet was shown in fig. 4 and placed in the proper position away from the top of the rotating shaft. currently to interpret the matter of designs, the permanent magnet stator was placed simply at the tip of rectangular 63 mm  12 mm  1 mm stainless steel sus304 strip that was fixed simply together with the cantilever two-layer strip bounded by rectangular 320 mm  23 mm  1 mm stainless steel sus304 was shown in fig. 5. fig. 1 simple construction of rotating arms type permanent magnet motor fig. 2 double arc shaped rotating arms type support frame fig. 3 thin ring permanent magnet n45h advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 40 fig. 4 top view of two thin ring permanent magnets and permanent magnet stator fig. 5 front view of two thin ring permanent magnets and permanent magnet stator declaration of the test methods was stated as follows; some of international standard test methods were usually used such as astm and iso standards that define the precision way by liu et al. [19] in 2011. in this paper did not use any international standard tests for the convenient, only personal investigation view of doe method was used to find the preliminary and fundamental results. locations of permanent magnets in rotor and stator modules were stated as follows, generally, the permanent magnet material n45h was very brittle and working in the general temperature 25°c of environment. for the installation of rotor module, two thin ring permanent magnets were simply fixed at left and right surfaces respectively onto the double arc shaped rotating arms type support frame with the locations that were defined in the fig. 5 (wherein a was the distance between an edge of the left thin ring permanent magnet and rotating shaft center, b was the distance between an edge of the right thin ring permanent magnet and rotating shaft center, and c was the distance between the permanent magnet stator and the upper surface of the double arc shaped rotating arms type support frame). the local cartesian coordinate z-axis was in the direction of rotating shaft, x -axis and y-axis were perpendicular to the rotating shaft. usually, thin ring permanent magnet 1 of rotor module was horizontally located at a position from its right side of ring to the left side of x -axis. thin ring permanent magnet 2 of rotor module was horizontally located at b position from its left side of ring to the right side of x-axis. the center of each one thin ring permanent magnets was located in the y-axis. the permanent magnet stator was placed vertically above the rotating shaft and located at c position to the top surface of the double arc shaped rotating arms type support frame. the magnetic force direction of thin ring permanent magnets of rotor module was in the z -axis, e.g. the upper half of thin ring permanent magnet was s pole, thus the lower half of thin ring permanent magnet was n pole. the placements of two thin ring permanent magnets were installed with an opposite polarity with respect to each other, e.g. the s pole of thin ring permanent magnet 1 was directed upward, thus the n pole of thin ring permanent magnet 2 was directed upward. the magnetic force direction of permanent magnet stator was also in the z -axis, e.g. the upper half of permanent magnet stator was n pole, thus the lower half of permanent magnet stator was s pole. advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 41 3. results and discussion permanent magnet rotating test was stated as follows, when the permanent magnet stator properly approached to above of the rotating shaft and located at c position, the exclusion force came from the s pole of permanent magnet stator and the s pole of thin ring permanent magnet 1, in the same time in the opposite side of the double arc shaped rotating arms type support frame, the attraction force came from the s pole of permanent magnet stator and the n pole of thin ring permanent magnet 2, the torque produced from the exclusion force, attraction force and ring positions a, b with respect to z -axis, thus the shaft began to rotate. the magnetic forces came from the thickness sides of permanent magnet stator (2mm) could be neglected by properly using the storage energy effect of fly wheel devices for thin ring permanent magnets. after half rotation of shaft, the attraction force came from the s pole of permanent magnet stator and the n pole of thin ring permanent magnet 2, in the same time in the opposite side of the double arc shaped rotating arms type support frame, the exclusion force came from the s pole of permanent magnet stator and the s pole of thin ring permanent magnet 1, the torque produced again from the attraction force, exclusion force and thin ring permanent magnets positions a, b with respect to z -axis, thus the shaft continued to rotate and completed a whole rotation. the two thin ring permanent magnets rotated as a flywheel to store its energy. with the help of flywheel energy storage, magnetic torque came from the magnetic energy and flexible function came from the stainless steel sus304 strips, the shaft continued easily and possibly to complete the next rotation. fig. 6 simply geometry of nd-fe-b magnets with meshes in the quickfield software fig. 7 torque and magnet field of nd-fe-b magnets in the quickfield software it would be better to have simulation data to validate the experimental results, the simulation of magnetic forces for the permanent magnet would be found in the commercial programs, e.g. quickfield, comsol, maya and ansys. it was available to use the quickfield student edition 6.3 sp1 software for the magnetostatics study to simulate the torque in the dominated-simply geometry of nd-fe-b magnets with meshes as shown in fig. 6. the torque and magnet field of nd-fe-b magnets in the quickfield software were shown in fig. 7, the mechanical torque t= -0.0031619 nm was found for the nd-fe-b magnets with coercive force hc= 653000a/m. the permanent magnet motor rotation test successively rotated with manually controlled the permanent magnet stator to provide the forward and backward of swings and had the following preliminary data. to investigate the effect of positions of permanent magnet stator on the rotation speed of rotating shaft, considering the positions a= 8mm, b= 13mm, c= 12-50mm, the variation of rotating shaft rotation speed (rpm) vs. c (mm) was shown in fig. 8 with manually controlled. the rotation speed values of rotating shaft were increasing with c values decreasing. because the values of magnetic forces (attraction force and exclusion force) were inverse proportional to the position distances of poles (n pole and s pole) above the top level of thin ring advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 42 permanent magnets, e.g. c= 12mm. the greater value of magnetic forces got the faster rotation speed. the rotation speed values of rotating shaft would be zero when c= 0mm, because the values of magnetic forces could not produce enough torque for the thin ring permanent magnets to rotate the shaft. when the permanent magnet stator was in the position c=12mm, the rotation speed value of rotating shaft was 24 rpm. to investigate the effect of positions of two thin ring permanent magnets on the rotation speed of rotating shaft, considering the positions a= 8mm, b= 8-17mm, c= 12mm, the variation of rotating shaft rotation speed (rpm) vs. b(mm) was shown in fig. 9 with manually controlled. the rotation speed values of rotating shaft were also increased from 10 rpm to 36 rpm with b values decreasing from 17mm to 8 mm. when the thin ring permanent magnet 2 was in the position b=8mm, the rotation speed value of rotating shaft was 36 rpm. the positions in equal distance of two thin ring permanent magnets a=b=8mm with respect to z-axis were in good position to provide the rotating shaft more easily to rotate. because the values of magnetic forces could produce the good enough torque for the thin ring permanent magnets to rotate the shaft when position b= 8mm better than that when position b= 17mm. fig. 8 rotating shaft rotation speed (rpm) vs. c (mm) with manually controlled fig. 9 rotating shaft rotation speed (rpm) vs. b (mm) with manually controlled in conventional, a motor was a mechanical device that converts energy (created by air, electricity or liquid) into motion and torque. the simple rotating arm type permanent magnet motor was a new, different design of the conventional motor. the present permanent magnet motor provided the torque produced by a magnetic force of the magnetic energy of a stator to drive the rotation of the rotor. this rotating arm type design and construction of the permanent magnet motor would be used as a basic method to form some usual rotating arm type permanent magnet engine in the future. the rotating arm type permanent magnet motor might be developed to produce a suitable shaft rotation speed and also had the load torque capability at the forthcoming time. 4. conclusions a new successful and simple rotating arms type design and application is introduced for the permanent magnet motor that is constructed by the action of the magnetic forces of a permanent magnet stator of a stator module and two thin ring permanent magnets of a rotor module. the permanent magnet motor rotation test successively rotated with manually controlled the permanent magnet stator to provide the forward and backward of swings and had the preliminary data. when the two thin ring permanent magnets locate in the equal distance with respect to rotate shaft axis, it is in good position to provide the rotating shaft more easily to rotate. the importance of this application might be contributed to the pollution reduction of mechanical part innovation designs in the green energy. the rotating arm type permanent magnet motor can produce complete rotation with a suitable motion controller in the future. for example, electrical controlled swing-type device would be applied as the kinetic energy input system to produce completely rotation with its own magnetic energy for the permanent magnet driving 0 6 12 18 24 10 15 20 25 30 35 40 45 50 ro ta ti o n s p ee d ( rp m ) (mm) 0 6 12 18 24 30 36 42 8 10 12 14 16 18 ro ta ti o n s p ee d ( rp m ) (mm) advances in technology innovation, vol. 4, no. 1, 2019, pp. 37 43 43 motor. also the swing-type device would be used and applied to the input force forms of natural wave produced from ocean, lake and river. the electrical controlled swing-type device would be used to provide the forward and backward of swings for the permanent magnet stator. the main contributions of this paper might be presented an approach method of advanced designs in the energy saving for permanent magnet motor. acknowledgement the completion of this application was made possible by a grant nsc 102-2221-e-164-003 from ministry of science and technology (most), taiwan, roc. references [1] lectric motors,” https://www.explainthatstuff.com/electricmotors.html, april 4, 2018. 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[11] i. j. c. compter, “electro-dynamic planar motor,” precision engineering, vol.28, no. 2, pp. 171–180, 2004. [12] j. m. d. coey, “permanent magnet applications,” journal of magnetism and magnetic materials, vol. 248, pp. 441–456, 2002. [13] d. chowdhury, “stochastic mechano-chemical kinetics of molecular motors: a multidisciplinary enterprise from a physicist’s perspective,” physics reports, vol. 529, pp. 1–197, 2013. [14] c. c. hong, rotating arms type permanent magnet motor. united states patent application publication hong, us 20160094095a1, mar. 2016. [15] c. c. hong, “application of a bending type segment permanent magnet actuator,” materials science: an indian journal, vol. 11, no. 9, pp. 311–315, 2014. [16] c. c. hong, “application of a magnetostrictive actuator,” materials & design, vol. 46, pp. 617–621, 2013. 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[19] p. liu, r.l. browning, h.j. sue, j. li and s. jones, “quantitative scratch visibility assessment of polymers based on erichsen and astm/iso scratch testing methodologies,” polymer test, vol. 30, pp. 633–640, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 efficacy of nanocutting fluids in machiningan experimental investigation vamsi krishna pasam1,*, padmini rapeti2, surendra babu battula2 1department of mechanical engineering, national institute of technology, warangal, telangana state, india. 2department of industrial engineering, gitam institute of technology, gitam university, visakhapatnam, andhra pradesh, india. received 21 july 2017; received in revised form 10 october 2017; accepted 23 october 2017 abstract this paper presents the experimental investigations on the performance of eco-friendly vegetable oil based nanofluids in turning operation. cutting temperatures, cutting forces, tool wear and surface roughness under constant cutting conditions are measured during machining. the influence of nanofluids prepared from nanoboric acid (nba) and carbon nanotubes (cnt) mixed separately with coconut oil (cc), on machining performance is examined. comparative analysis of the results obtained is done under dry, soluble oil (sl) and lubricant environments at 0.25% nano particle inclusions (npi). to understand the influence of npi, the experiments are conducted using ccnba and cccnt at varying npi also. application of cccnt resulted in improved machining performance compared to ccnba . reduction in cutting temperatures, main cutting force, tool wear and surface roughness is approximately 13%, 37.5%, 44% and 40% respectively by the application of cccnt compared to dry machining. thus application of ccnba and cccnt at 0.5% npi is more effective in improving machining performance. keywords: nanocutting fluids, vegetable oil, mql, surface roughness 1. introduction cutting fluids have been most frequently used from the perspective of cooling and lubricating actions during machining in manufacturing industry. the number of investigations revealed that application of conventional cutting fluids hinders the ecological balance and negatively affects the safety of operators [1-2]. these investigations led to the search for environmentally benign cutting fluids. this resulted different alternatives to conventional cutting fluids in terms of cryogenic cooling, vegetable oils, solid lubricant, nanofluids, and minimum quantity lubrication (mql) technique. being biodegradable, operator friendly, abundantly available and affo rdable, vegetable oils have been thoroughly experimented to examine their applicability in machining operations. rapeseed oil, coconut oil, sunflower oil etc., are some of the vegetable oils which caught the sight of researchers giving rise to interesting results. investigations on the effect of new formulations of vegetable oils on surface integrity and part accuracy in reaming and tapping operations with aisi 316l stainless steel were done. vegetable oil based cutting fluids exhibited better performance than mineral oils by way of tool life, tool wear, cutting forces and chip formation [3].the applicability of coconut oil as a base fluid in industrial applications was examined and machining performance was improved and compared to conventional cutting fluid [4]. solid lubricant assisted machining has evolved as one of the novel techniques. graphite, boric acid, and mos2 are some of the solid lubricants which have improved * corresponding author. e-mail address: vamsikrishna@nitw.ac.in advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 79 tribological properties that have grabbed the attention of tribologists. owing to these properties, solid lubricants aid in wear reduction. these materials are characterized by weak atomic interactions between their layered structures, allowing low shear strength. improvement in process using graphite, caf2, baf2 and mos2 in grinding operation was reported [5-6]. an attempt was made to use graphite as a solid lubricant to reduce the heat generation at the milling zone [7], resulting in remarkable reduction of cutting force, specific energy and surface roughness. comparative analysis of machining with a cutting fluid in terms of cutting forces, surface quality and specific energy using graphite and mos2 during end milling process revealed encouraging results with solid lubricants [8]. experiments were conducted to assess the performance of solid lubricants during hard turning while machining bearing steel with mixed ceramic inserts at different cutting conditions and tool geometry [9]. it was reported that surface finish improved from 8 to 15% with the use of solid lubricants compared to dry hard turning. investigations on the performance of boric acid in machining revealed that, process performance improved with reduced particle size while using dry solid lubricants. cutting forces, cutting temperatures and tool flank wear were reduced and surface finish improved [10]. in view of enhanced thermo physical properties of nanofluids, various studies to evaluate these properties of nanofluids like specific heat and thermal conductivity were conducted and sufficient improvement in thermal and physical properties of nanofluids was observed [11-13]. in this context, cnts (carbon nanotubes) with enhanced mechanical, optical and chemical characteristics enable their application in machining operations. cnts have a high surface to volume ratio, good electrical conductivity and more over their linear geometry makes their surface highly accessible to the electrolyte. the strength to we ight ratio of cnt is 500 times greater than aluminum. analysis of surface characteristics of the tool steel material using multiwall carbon nanotubes to improve the surface finish of material to nano level was done [14]. carbon nanotubes are special interes ts to researchers because of the novel properties like extraordinary strength, unique electrical properties and efficient con duction of heat. depending on the available literature, it has been found that nanofluids have a much higher and strongly temperature-dependent thermal conductivity at very low particle concentrations than conventional fluids. mql is a promising technique of applying lubricants during machining, which minimizes the usage of cutting fluid and reducing the cost of manufacturing. research works conducted to examine the nature of the mql technique during turning operation revealed that mql reduces induced thermal shock and helps to increase the workpiece surface integrity in situations of high tool pressure [15]. extensive research was carried out to analyze the performance of different types of nanofluids prepared from al2o3, zno, nano diamond particles in mql grinding [16]. it was concluded by using nanofluids as lubricants basic properties and machining parameters showed considerable improvement. experimental investigation on the performance of nano boric acid suspensions in sae-40 and coconut oil showed that nano solid lubricant suspensions in vegetable oil improved the performance parameters during turning of aisi 1040 steel [17]. the affirmative aspects of nano solid lubricants, vegetable oils through mql technique are being explored by researchers worldwide in order to bring out environmentally safe and user friendly cutting fluids to overcome the disadvantages of conventional ones. in this context, the present work is an attempt to investigate the affect of vegetable oil based nanofluid s on machining parameters. nano boric acid and cnt are used as suspensions (0.25% by weight) in coconut oil and machining is carried out at constant cutting conditions. cutting forces, cutting temperatures and surface roughness are measured and compared in dry machining environment; using soluble oil, and two nanofluids prepared. 2. materials and methods the present work deals with the application of two nanofluids namely ccnba (coconut oil + nanoboric acid) and cccnt (coconut oil + cnt) which are used as lubricants during machining. other lubricant environments considered include dry advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 80 machining, cc (coconut oil) and conventional soluble oil (sl) to perform comparative analysis of the performance of nanofluid s. nano boric acid suspensions are added to coconut oil on weight percentage basis (0.25% to 1%) and mixed manually. to enable proper dispersion of nanoparticles in coconut oil, sonication is done for a period of one hour. thus, two nanofluids namely ccnba and cccnt are prepared and applied as cutting fluids during turning. all the machining experiments are conducted on psg-124 lathe with a carbide tool (nc6110); heat treated aisi 1040 steel of 30±2 hrc is used as work piece(30mm diameter and 100mm length). cutting temperatures during turning are sensed by embedded thermocouple (k-type shielded) placed at the bottom of the tool insert in the tool holder. details of machining are consolidated in table 1. cutting force (fz) is tracked and recorded online using kistler 5070 dynamometer. tool flank wear is measured with tool makers microscope, cutting temperatures are measured with embedded thermocouple, surftest – sj301 with stylus radius 0.0025 mm and cut-off length 0.8 µm was employed for measuring average surface roughness (ra). the values are recorded thrice and average is considered to avoid discrepancies in measurement. machining is initially conducted under dry condition, followed by application of sl, cc, ccnba, cccnt as cutting fluids one after the other. cutting fluids are supplied using the mql technique with a flow rate of 10 ml / minute. experiments are conducted at constant cutting conditions (speed: 560 rpm; feed: 0.14mm; depth of cut: 0.5 mm) and 0.25% npi followed by varying npi. machining conditions are chosen referring to previous literature [17, 21]. cutting temperatures, cutting forces, tool flank wear and surface roughness are measured during all the cases and comparative analysis reflecting the performance of nanofluids with other cases is done. schematic representation of experimentation is given in fig. 1. table 1 machining environment cutting conditions speed : 60m/min ; feed : 0.14mm/rev ; depth of cut :0.5 mm npi 0.25%, 0.5%, 0.75%, 1% mql flow rate 10ml/min lubricant environment a. dry, sl, cc, ccnba, cccnt at 0.25% npi b. ccnba & cccnt at varying npi tool pslnr 2020 k12 cutting tool cnmg120408 nc6110 (coated carbide) cutting tool geometry -60, -60, 00, 60, 60, 60, 0.8mm fig. 1 schematic representation of experimental work advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 81 3. results and discussion machining is carried out in dry environment and using sl, cc,ccnba,cccnt as cutting fluids. the results reflecting the variation of cutting temperature, cutting forces (fz) and surface roughness (ra) with respect to time during dry and other environments are presented and discussed in the following sect ions. 3.1. cutting temperatures variation of cutting temperatures with machining time is presented in fig. 2. it is observed that cutting temperatures increased with increase in time for all the lubricant environments. cc, cccnt and ccnba are effective in reducing temperatures when compared to dry machining and sl assisted machining. the affirmative behavior of cc can be attributed to the presence of saturated fatty acids to an extent of 90% and length of carbon chains of cc which belongs to medium chain category (6-12 carbons). the chemical composition and fatty acid profile of cc are the primary reasons behind its performance as cutting fluid. molecular structures of vegetable oils like cc are termed as triacylglicerides. they contain medium chain of fa tty acids (mcfa 6 to 12 carbons length) which are joined at the hydroxyl groups (oh) through ester linkages. cc with high % of sfa and mcfa, at higher temperatures enables formation of a stable film which separates the surfaces in contact [18, 19] exhibits good wettability. thus, its interfacial properties are enhanced, which plays vital role in lubricant application. [20].the phenomenon of format ion of cc film on the metallic surface is more significant in case of vegetable oils like cc. this behavior of cc is accelerated by the additions of nanoparticles (ccnba and cccnt) [21]. the reasons behind cooling property of nanofluids is the increase in thermal conductivity and heat transfer coefficient which improve the heat dissipation capacity of nanofluids, thus reducing cutting temperatures at machining zone. owing to these reasons, nanoparticles in cc tend to reduce cutting temperatures. the performance of cccnt is found to be slightly better by way of reduction in cutting temperatures due to its thermal p roperties [22]. the percentage improvement in the reduction of cutting temperatures by using vegetable oil based nanocutting fluids is found to be 13% compared to dry machining. thus it can be inferred that vegetable oil based nanofluids are more efficient in reducing cutting temperatures. fig.2 variation of cutting temperatures with machining time (speed: 560 rpm; feed: 0.14mm/rev; depth of cut : 0.5mm; npi : 0.25%) 3.2. cutting forces cutting force (fz) is measured at constant cutting conditions and the variation with machining time is shown in fig. 3. it is noticed that, performance of cc, ccnba and cccnt is effective in reducing fz compared to dry and sl assisted machining. cutting forces are reduced because of the reduction in coefficient of friction between rubbing surfaces by the application of cc and cc based nanofluids. cc has strong intermolecular interactions get stuck to metallic surfaces resulting in a consistent lubricant layer which persists longer even at high temperatures. the film formation ability is found to be more pronouncing with advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 82 cc which comprise of mcfa and which have high amounts of sfa [23]. another reason which influences reduction in cutting force is viscosity of nanofluids. when viscosity is low heat dissipation capacity of nanofluid increases and when viscosity is high the ability of a nanofluid to form a consistent film separating both the surfaces in contact during machining gets enhan ced [24-25]. thus, the coefficient of friction between the surfaces in contact reduces which in turn leads to reduction in cutting forces. in the present case, it is found that this phenomenon is more pronouncing by the application of cccnt compared to all the other lubricant environments. the percentage improvement in reduction of cutting force with cccnt is approximately 37.5% compared to dry machining. fig. 3 variation of cutting force with machining time (speed : 560 rpm; feed : 0.14mm/rev; depth of cut : 0.5mm; npi : 0.25%) 3.3. tool wear tool wear measured corresponds to tool flank wear which is measured after every pass. the readings are recorded by using olympus analysis software. the tool is set on the adjustable table of the sc30 optical microscope such that the cutting edge of the tool is just above the focus of 5x and 10x zoom lenses. tool wear is marked at different zones to get the precise value of wear. the measured tool flank wear is tracked after every turn and average tool wear is taken and graphs are plotted. it is seen from fig. 4 that tool wear has decreased from dry machining to cccnt assisted machining. machining is influenced by high amounts of heat generated at the two deformation zones, which are termed as primary and secondary. this heat induces high temperatures in tool and workpiece. endowed with better thermal conductivity, enhanced heat transfer rate, cc based nanofluids lead to tool wear reduction [25]. this is accelerated by sfa and mcfa of cc due to which stable film of nano -lubricant persists as discussed in section 3.2. this in turn reduces the shear res istance along the interface and the nano-lubricant film separates the tool-work interfaces, which reduces plastic contacts tending to lower the tool wear [26-27]. compared to dry machining cccnt is observed to reduce tool wear to an extent of 44%. fig. 4 variation of tool wear with cutting fluid environment (speed : 560 rpm; feed : 0.14mm/rev; depth of cut : 0.5mm; npi : 0.25%) advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 83 3.4. surface roughness results of surface roughness (ra) measurement are shown in fig. 5. it is observed that the surface roughness is very high during dry machining, followed by sl assisted machining. cc performed midway between ccnba and cccnt in improving surface quality. the application of ccnba and cccnt resulted in reduced surface roughness compared to other environments. significant reduction in ra is obtained by the application of cccnt. lubricity of cc, high chemical affinity of nanoparticles towards ferrous surfaces results in covering the valleys between asperities and pores on the surface of workpiece during machining [27]. improved cooling and lubrication of nanofluids, impart better surface quality to the workpiece by reducing cutting temperature, cutting forces and tool wear. thus , the application of coconut oil based nanofluids imparts good surface quality to machined surface. an improvement of 40% in the reduction of surface roughness is observed by the application of cccnt compared to dry machining. fig. 5 comparasion of surface roughness in different lubricant environments(speed : 560 rpm; feed : 0.14mm/rev; depth of cut : 0.5mm; npi : 0.25%) 3.5 influence of nanoparticle inclusions fig. 6 variation in machining performance with npi (speed : 560 rpm; feed : 0.14mm/rev; depth of cut : 0.5mm ) advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 84 the variation of cutting temperatures, cutting forces, tool wear and surface roughness with varying npi is presented in fig. 6(a) to fig. 6(d). it can be visualized that up to 0.5% npi substantial improvement in machining is possible by reduction in temperatures, forces, tool wear and surface roughness by applying both types of nanofluids. cccnt at 0.5% has exhibited better machining performance compared to that of ccnba at 0.5% npi. this can be attributed to the phenomenon of agglomeration which affects the uniform dispersions in base oil with increase in npi [26-27]. thus, formation of a consistent nano lubricant separating the surfaces in contact is hindered. thus , beyond 0.5% npi reduction in cutting temperatures, cutting forces, tool wear and surface roughness is not evident. 4. conclusions the effectiveness of vegetable oil based nanocutting fluids ccnba, cccnt is examined in this work. comparative analysis of machining performance of these nanofluids using pure vegetable oil, soluble oil and dry states is done and the following conclusions are drawn: (1) vegetable oil based nanocutting fluids are found to be effective in reducing cutting temperatures, cutting forces, tool wear and surface roughness compared to dry machining and soluble oil assisted machining . (2) application of ccnba and cccnt as cutting fluids during machining resulted in better machining performance than that of cc based machining. (3) on the total cccnt with 0.5% npi is found to exhibit better effectiveness compared to all the cutting fluid environments . (4) percentage improvement in machining performance by the application of cccnt in reducing cutting temperatures, main cutting force, tool wear and surface roughness is observed to be 13%, 37.5%, 44% and 40% respectively compared to dry machining. references [1] e. o. bennett and d. l. bennett, “occupational airways diseases in the metal working industries,” tribology international, vol. 18, no. 3, pp. 169-176, june 1985. [2] w. bartz, “ecological and environmental aspects of cutting fluids,” lubrication engineering, vol. 57, pp. 13-16, march 2001. [3] w. belluco, and l. de chiffre, “surface integrity and part accuracy in reaming and tapping stainless steel with new vegetable based cutting oils,” tribology international, vol. 35, no. 12, pp. 865-870, december 2002. [4] n. h. jayadas and k. prabhakaran nair, “coconut oil as base oil for industrial lubricantsevaluation and modification of thermal, oxidative and low temperature properties ,” tribology international, vol. 39, no. 9, pp. 873-878, september 2006. [5] s. shaji and v. radhakrishnan, “analysis of process parameters in surface grinding with graphite as lubricant based on taguchi method,” journal of materials processing technology, vol. 141, no. 1, pp. 51-59, october 2003. [6] a. venugopal and p. v. rao, “performance improvement of grinding of sic using graphite as a solid lubricant,” materials and manufacturing processes, vol. 19, no. 2, pp. 177-186, february 2004. [7] n. suresh kumar reddy and p. v. venkateswara rao, “performance improvement of end milling using graphite as a solid lubricant,” materials and manufacturing processes , vol. 20, no. 4, pp. 673-686, february 2005. [8] n. s. kumar reddy and p. v . rao, “experimental investigation to study effect of solid lubricants on cutting forces & surface quality in end milling,” international journal of machine tools & manufacture, vol. 46, no. 2, pp. 189-198, february 2006. [9] d. singh and p. v. rao, “performance improvement of hard turning with solid lubricants ,” international journal of advanced manufacturing technology, vol. 38, no. 5-6, pp. 529-535, august 2008. [10] p. vamsi krishna and d. n. rao, “the influence of solid lubricant particle size on machining parameters in turning,” international journal of machine tools and manufacture, vol. 48, no. 1, pp. 107-111, january 2008. [11] a. r. moghadassi, s. m. hosseini, d. henneke, and a. elkamel, “a model of nanofluid effective thermal conductivity based on dimensionless groups,” journal of thermal analysis and calorimetry, vol. 96 , no. 1, pp. 81-84, april 2001. advances in technology innovation, vol. 3, no. 2, 2018, pp. 78 85 copyright © taeti 85 [12] y. hwang, h. s. park, j. k. lee, and w. h. jung, “thermal conductivity and lubrication characteristics of nanofluids,” current applied physics, vol. 6, no. 1, pp. 67-71, august 2006. [13] p. k. devdatta, k. praveen namburu, and k. debendra das, “comparison of heat transfer rates of different nanofluids on the basis of the mouromtseff number,” electronics cooling, vol. 13,no. 3, pp. 28-32, august 2007. [14] s. prabhu and b. k. vinayagam, “afm investigation in grinding process with nanofluids using taguchi analysis,” international journal of advanced manufacturing technology , vol. 60, no. 1-4, pp. 149-160, april 2012. [15] a. attanasio, m. gelfi, c. giardini, and c. remino, “minimum quantity lubrication in turning,” wear, vol. 260, pp. 333-338, february 2006. [16] b. shen, a. shih, and s. c. tung, “application of nanofluids in minimum quantity lubrication grinding ,” tribology & lubrication technology, vol. 51, pp. 730-737, october 2008. [17] p. vamsi krishna, r. r. srikant, and d. nageswara rao, “experimental investigation on the performance of nanoboric acid suspensions in sae-40 and coconut oil during turning of aisi1040 steel,” international journal of machine tools & manufacture, vol. 50, no. 10, pp. 911-916, october 2010. [18] sapna johnson and nirmali saikia, “fatty acid profiles of edible oils and fats in india,” centre for science and environment, cse/pml/pr-32/, pp. 1-42, 2009. [19] l. horary and e. richler, “bio-based lubricants and greases : technology and products,” john wiley and sons, vol. 17: tribology in practice series. [20] h. thomas and w. apple, “proceedings: american oil chemists society,” monograph, aocs, p. 91, 1991. [21] g. krishna mohana rao, r. padmini, and p. vamsi krishna, “performance evaluation of eco-friendly nanofluids in machining,” proc. 1st international conf. aeronautical and mechanical engineering, pp. 221-229, 2013. [22] s. shaikh, k. lafdi, and r. ponnappan, “thermal conductivity improvement in carbon nanoparticle doped pao oil: anexperimental study,” journal of applied physics, vol. 101, no. 6, pp. 064302(1-7), march 2007. [23] m. h. cetin, b. ozcelik, e. kuram, and e. demirbas, e, “evaluation of vegetable based cutting fluids with extreme pressure and cutting parameters in turning of aisi 304l by taguchi method,” journal of cleaner production, vol. 19, no. 17-18, pp. 2049-2056, november-december 2011. [24] p. sivashanmugam, “application of nanofluids in heat transfer applications,” an overview of heat transfer phenomena, october 2012. [25] s. a. lawal, i. a. choudary, and y. nukman, “application of vegetable oil-based metal working fluids in machining ferrous metalsa review,” international journal of machine tools & manufacture, vol. 52, no. 1, pp. 1-12, january 2012. [26] w. yu, and h. xie, “a review on nanofluids: preparation, stability mechanisms and applications ,” journal of nanomaterials, vol. 2012, pp.1-17, 2012. [27] a. erdemir, “solid lubricants and self lubricating films,” modern tribology handbook, argon national library, 2001.  advances in technology innovation, vol. 1, no. 1, 2016, pp. 25 27 25 copyright © taeti buckling experiment on anisotropic long and short cylinders atsushi takano department of mechanical engineering, kanagawa university , yokohama, japan. received 02 february 2016; received in revised form 22 march 2016; accepted 25 march 2016 abstract a buckling experiment was performed on anisotropic, long and short cylinders with various radius-to-thickness ratios. the 13 cylinders had symmetric and anti-symmetric layups, were between 2 and 6 in terms of the length-to-radius ratio, between 154 and 647 in radius-to-thickness ratio, and made of two kinds of carbon fiber reinforced plastic (cfrp) prepreg with high or low fiber modulus. the theoretical buckling loads for the cylinders were calculated from the previously published solution by using linear bifurcation theory considering layup anisotropy and transverse shear deformat ion and by using deep shell theory to account for the effect o f length and compared with the test results. the theoretical buckling loads for the cy linders were calculated from the previously published solution by using linear bifurcation theory considering layup anisotropy and transverse shear deformation and by using deep shell theory to account for the effect of length. the knockdown factor, defined as the ratio of the experimental value to the theoretical value, was found to be between 0.451 and 0.877. the test results indicated that a large length-to-radius ratio reduces the knockdown factor, but the radius-to-thickness ratio and other factors do not affect it. keywords: buckling, cylinders, anisotropy 1. introduction many buckling tests have been performed on orthotropic and anisotropic cylinders , which are often made from cfrp. as summarized by the author [1] and as shown in fig. 1, the values of the knockdown factor have been calculated from these tests are scattered between 50% and 100%. fig. 1 knockdown factor and r/t [1] note that the theoretical buckling loads were calculated by using the solution with the least amount of simplificat ion in the linear b ifurcation theory from among the previously published solutions [2]. the previous experiments and evaluations, however, main ly concentrated on the effect of the radius to thickness ratio (r/t). recently, long cfrp cy linders have started to be used in large satellites [3], but no information is yet availab le on the effect of length on the knockdown factor. thus, buckling tests were performed on long and short cfrp cy linders, and the results were used to calculate the knockdown factors. 2. method 2.1. making specimens the cfrp prepregs used to make the cylinders were tr350j075s, el = 114.7gpa (hereafter called “tr”) and hsx350c075s, el = 260.3gpa (hereafter called “hsx” ); both were made by mitsubishi rayon co., ltd. here, el is the longitudinal young’s modulus measured in a tensile test, and the transverse young’s modulus et and shear modulus glt were assumed to be 6 gpa and 4gpa, respectively. * corresponding author, email: atakano@kanagawa-u.ac.jp advances in technology innovation, vol. 1, no. 1, 2016, pp. 25 27 26 copyright © taeti the test specimens (cfrp cylinders) were made in-house by hand-layup. cfrp prepregs were layered manually on an alumin ium mandrel (150 mm in diameter), and heat shrinkable tape was wound around them. the layup sequence is shown in table 1. the cfrp prepregs on the mandrel were thermally cured in an oven kept at 130°c for 2 hours. the cured cylinders were cut by grinders, and both ends were bonded to steel rings by epoxy adhesive. to prevent thermal residual stress on the cylinders, the curing of the epoxy adhesive was conducted at room temperature. twelve sheets of three-axis strain gages were bonded on the top and bottom (5 mm from the steel end rings) and middle (the center of the length) of the cylinders in the circumferential direction, each separated by 90°. 2.2. test method a typical compression test configuration is shown in fig. 2. section paper was laid under the specimen to align the centers of the cylinder and the universal testing instrument (shimadzu ag-i 100kn). to make the load uniform, a rubber sheet and a silicone rubber sheet were laid on the top end of the cylinder, a 20 mm thick stainless plate was put over the sheets, and a rubber sheet was laid on the bottom end of the cy linder. to minimize the offset of the load, a small compression load was applied, and the strain outputs in the middle were checked. when a significant difference between the strains was observed, the location of the cylinder on the universal testing instrument was adjusted. when the difference between the strains no longer changed or a large offset was observed between the centers of the cylinder and the universal testing instrument, however, the difference between the strains was ignored and the test proceeded to the next step. fig. 2 photograph of buckling test the half level compression test (applying half the expected buckling load, including 0.5 of the knockdown factor) was performed to check for anomalies in the data. after that, the full level compression test was performed to buckle the cylinder. load was applied until the cross-head displacement reached 1.5 of the buckling displacement. 3. results and discussion typical load and displacement results are shown in fig. 3 and 4. fig. 3 tr 6 ply, l/d=1, gap allowed. fig. 4 tr 6 ply, l/d=3, gap allowed. table 1 summarizes the test results. note that an extremely low knockdown factor 0.397 was caused by 8mm of offset load, and the modified knockdown factor considering the offset is 0.481. accordingly, the knockdown factors are scattered between 0.451 and 0.877. the knockdown factors of the longer cylinders are lower than those of the shorter cylinders, while other factors (symmetric or anti-symmetric, ply gap, fiber modulus and l/r) seem to have no effect on the trend. thus, a regression analysis with categorical variab les was conducted to check the effects. the results are shown in table 2. a regression analysis can be used instead of an analysis of variance (anova) when the sample size is unbalanced like in this case. here, r/t (thickness) and the symmetric or anti-symmetric factor are advances in technology innovation, vol. 1, no. 1, 2016, pp. 25 27 27 copyright © taeti multicollinear; thus, the symmetric or anti-symmetric factor should be excluded from the regression analysis. table 1 summary of the test results table 2 regression tables the mean of the knockdown factors is 0.611 with 0.02% of p-value, and it is smaller than 5% (standard statistical criteria); hence, the value is statistically significant. other effects, however, are not significant because their p-values are higher than 5%. only the p-value of l/r, which is 19.23%, is smaller than the others. the mean of the knockdown factors is 0.627 for l/r=2 and 0.537 for l/r=6. the s maller value is 14.4% smaller than the larger value. thus, the length may affect the knockdown factor. to clarify its effect, more buckling tests are required. 4. conclusions thirteen buckling tests were performed on symmetric and anti-symmetric, long and short cylinders to investigate effect of varying the length. the difference in the mean knockdown factor between lengths was found to be 14.4%. a regression analysis, however, indicated that the difference was not statistically significant. more buckling tests considering other factors should be conducted in order to find the cause of the scatter in the knockdown factor. references [1] a. takano, “statistical knockdown factors of buckling anisotropic cylinders under axial compression,” journal of applied mechanics, vol. 79, 051004, pp 1-17, 2012. [2] a. takano, “improvement of flügge’s equations for buckling of moderately thick anisotropic cylindrical shells,” aiaa journal, vol. 46, no. 4, pp. 903-911, 2008. [3] y. takano, t. masai, h. seko, a. takano, and m. miura, “development of the lightweight large composite-honeycomb-sandwich central cylinder for next-generation satellites,” aerospace technology japan, vol. 10, pp. 11-16, 2012. theory p a [n] test p a [n] tr 6 ply l/r=2 (-70/70/0/0/70/-70) 0.488 136 21983 13197 0.600 gap tr 6 ply l/r=4 (-70/70/0/0/70/-70) 0.488 287 21986 11870 0.540 gap tr 6 ply l/r=6 (-70/70/0/0/70/-70) 0.488 436 21987 11537 0.525 gap hsx 6 ply l/r=2 (-70/70/0/0/70/-70) 0.349 136 21123 12997 0.615 gap hsx 6 ply l/r=6 (-70/70/0/0/70/-70) 0.349 443 21873 12647 0.578 gap hsx 3 ply l/r=2 (-70/0/70) 0.175 148 2060 1806 0.877 overlap hsx 3 ply l/r=6 (-70/0/70) 0.175 443 2061 1437 0.697 overlap tr 6 ply l/r=2 (-70/70/0/0/70/-70) 0.488 136 21983 12665 0.576 overlap tr 6 ply l/r=6 (-70/70/0/0/70/-70) 0.488 436 21987 8738 0.397 * overlap hsx 6 ply l/r=2 (-70/70/0/0/70/-70) 0.349 136 21123 10366 0.491 overlap hsx 6 ply l/r=6 (-70/70/0/0/70/-70) 0.349 436 21873 9875 0.451 overlap hsx 2 ply l/r=2 (-50/50) 0.116 136 964 583 0.605 overlap hsx 2 ply l/r=6 (-50/50) 0.116 436 944 464 0.492 overlap *note: 8mm of load offset was observed and modified knockdown factor considering the offset load is 0.481. specimen name layip sequence thickness t [mm] length l [mm] buckling load ply gap or overlap knockdown factor coefficients std error t p-value lower 95% upper 95% intersept 0.611 0.095 6.459 0.02% 0.393 0.829 gap/overlap -0.052 0.080 -0.646 53.62% -0.236 0.133 tr/hsx 0.047 0.087 0.542 60.28% -0.154 0.249 l /r -0.025 0.017 -1.424 19.23% -0.065 0.015 r /t 0.000 0.000 0.782 45.70% 0.000 0.001  advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 cae analysis of secondary shaft systems in great five-axis turning-milling complex cnc machine chih-chiang hong1,*, cheng-long chang1, chun-chen huang2, chi-ching yang3, chien-yu lin4 1 department of mechanical engineering, hsiuping university of science and technology , taichung, taiwan, roc. 2 department of industrial engineering and management, hsiuping university of science and technology, taichung, taiwan, roc. 3 department of electrical engineering, hsiuping university of science and technology, taichung, taiwan, roc. 4 l&l machinery industry co., ltd, taichung, taiwan, roc. received 12 february 2017; received in revised form 12 april 2017; accepted 23 april 2017 abstract the commercial computer aided engineering (cae) software is used to analyze the linear-static construction, stress and deformation fo r the secondary shaft systems in great five-axis turning-milling complex computer numerical control (cnc) machine. it is convenient and always only three dimensional (3d) graphic parts needed firstly prepared and further more detail used for the commercial cae. it is desirable to predict a deformed position for the cut tool under external pressure loads in the working process of cnc machine. the linear results for static analysis of stresses, displacements in corresponding to the screw shaft locates at top, medium and bottom positions of the secondary shaft systems are obtained by using the simulation module of solidworks® . keywords: cae, static analysis, linear analysis, solidworks, shaft systems, stress analysis, cnc 1. introduction there are many computer aided engineering (cae) commercial software used to develop and design the computer numerical control (cnc) machine for saving the cost of production. in 2016, afkhamifar et al. [1] used the finite element method (fem) analysis to s imulate the position error of the tooltip in the 3-axis vertical milling machin ing centers cnc series. in 2015, max et al. [2] used catia® and nx™ software to create 3d models for the teaching and studies of fem analysis in the cnc milling machine. in 2014, altintas et al. [3] simulated and optimized the cutting process in the virtual machining (vm) of cnc system. in 2014, soori et al. [4] developed a vm software and created machined parts in the virtual environments for 3-axis cnc. in 2013, chang [5] introduced computer-based technology in the vm to provide a relatively low setup cost when compared with physical cnc. in 2012, wang et al. [6] used software ansys® (one of the fem codes) to compute the static-structural results of the frame and tool carrier for the hydraulic swing-type plate shears of cnc equipments. there are also some other commercial cae software used in the structural analysis for the engineering system, for example: solidw orks® , creo® , inventor® , freecad (an open-source), abaqus® , hypersizer® and midas® etc.. in 2016, mackrell [7] introduced the multi-mechanics module o f software abaqus® for engineer used to work and design in the field of cae. in 2013, paulo et al. [8] used software abaqus® to simulate mechanical behavior for the stiffened aluminum panels. in 2010, younis [9] presented the autodesk software inventor® used for the structural simulat ion in the engineering. to execute the fourth industrial revolut ion for the cnc systems, the design and analysis experiences of cae are novel for the conventional company. in 2016, hong et al. [10] presented the static-structural cae analysis of great five-axis turning-milling complex machine for the cnc system with the solidworks® simulation module. simple, clear and easy steps in the simulated process are the specific reason of selecting solidworks software for present work. educational version of * corresponding author. e-mail address: cchong@mail.hust.edu.tw advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti 44 solidw orks 2014 software has been used for conducting the present simulation. in this paper, the linear static stresses and displacements of secondary shaft system of the cnc machines are studied more details and obtained with the solidw orks® simulat ion module. the maximum values of stress and displacement are usually provided to give a basic data for the detail construction of cnc machine. the highlight notes of this paper are also included as follows: (1) it is helpful for engineers to investigate great five-axis turning-milling complex cnc machine data under cae analysis. (2) commercial cae solution for the secondary shaft systems under external pressure loads is provided. (3) the linear results are provided by using the simulation module of solidworks® . for the meaning of "great five-axis" in this study usually notes that bigger dimensions of work piece e.g. length 5000 mm, diameter 950 mm than s maller one can be machined at working t ime by the five axes: x-axis, y-axis, z-axis (three translations), a-axis and b-axis (two rotations) of working platform which moving respectively to the cutting tools. in 2015, yang et al. [11] presented the general stiffness model of rigidity for tool path planning in five-axis cnc machin ing to restrain the chatter of the machine. in 2015, wagner [12] p resented an optimization computer aided design (cad)/computer aided manufacture(cam)/ cae technique for the processing of cutting tool of the complex 3d surfaces on 5 axes cnc machines. the main novelty of their research is used the commercial cae simulation module to investigate the linearly static structure analysis in cnc machine for t ime saving and obtain the basic data for the construction of cnc machine parts. in general, the using of commercial cae software have the trustable and acceptable experience in the data, but the cost of module software is respectively higher when compared with personal developed software. usually the c ommercial cae software e.g. solidworks® used for the educational version has the great discount in the universities and schools. the main scope of this research is to use the reasonable cost of commercial cae software to save developing time of software and find the useful data of computation. there are some commercial cae softwares in educational version had by the university e.g. catia® , ansys® and solidworks® . they are all very good commercial cae softwares to provide the calculation solution. when the commercial cae software had for the industry is usually very expensive and needed some teaching courses to provide for the user. to choose which type of commercial cae software is very important based on the user’s like of industrial company when the researcher and teacher of university are in the corporation relationship. the advantages of this paper in comparison with the other researches performed in this subject are the using solidworks® simulation module is also used by the employee of industrial company, the upgrading of new cnc machine design performed by the owners of industrial company and the reliable data calculated from the commercial cae software. 2. method the steps of simulation with the software solidworks® simulation module in the static structural linear analysis and the general matrix equation of mathematical model were used in the computer program to solve for stress and displacement results by hong et al. [10] as follows.     fuk  (1) where [k ] is material stiffness matrix, {u} is displacement vector, {f} is external load vector. it is necessary to prepare the assembling 3d parts of the secondary shaft systems as shown in fig. 1. the dimensions of main parts are provided for the secondary shaft system is 1397mm 845mm 1426mm. the main components of secondary shaft system are screw shaft and base. the tool is fixed on the end of screw shaft to provide dril ling and milling functions. the secondary shaft system can be rotated by the base in rotational motion with respect to y axis. it is necessary to define the individual material of assembl ing 3d parts for the secondary shaft systems. the main materials of the secondary shaft system are cast steel. the yield stress of cast steel material is 241mpa. to present normal working in the cnc machine, the value of working stress in each material of components should under its yield stress value. advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti 45 three contact boundary conditions (b. c.) of secondary shaft systems are used to computed and analyzed for corresponding to the screw shaft locates at top, medium and bottom positions with 100mm apart along y axis, respectively. the boundary conditions of the secondary shaft s ystem for the base are four sides in clamp b.c. and shown in fig . 2. external pressure loads on left-end of screw shaft and hydraulic pressure loads on the base in secondary shaft system for the screw shaft locates at top position typically is also shown. mesh of grids in the secondary shaft system is shown in fig. 3 and fig. 4. mesh of grids with parameter element length equal to 27.21mm based on curvature mesh is shown in fig . 3, also with proper mesh controlled base on the size of parts, medium mesh dens ity and used to generate a proper mesh of grids in the computation and analyses. a typical mesh of g rids in secondary shaft system for the screw shaft locates at top position is sh own in fig. 4. a table is provided to define the characteristics of materials used in the simulation as shown in table 1. fig. 1 assembling 3d parts of the secondary shaft system (a) contact b.c. for the screw shaft locates at top position (b) contact b.c. for the screw shaft locates at medium position (c) contact b.c. for the screw shaft locates at bottom position (d) four sides in clamp b.c. for the base fig. 2 boundary conditions in the secondary shaft system external pressure loads on left-end of screw shaft and hydraulic pressure loads on the base in secondary shaft system for the screw shaft locates at top position typically is also shown. mesh of grids in the secondary shaft system is shown in fig . 3 and fig. 4. mesh of grids with parameter element length equal to 27.21mm based on curvature mesh is s hown in fig. 3, also with proper mesh controlled base on the size of parts, medium mesh density and used to generate a proper mesh of grids in the computation and analyses. a typical mesh of g rids in secondary shaft system for the screw shaft locates at to p position is shown in fig. 4. a table is provided to define the characteristics of materials used in the simulation as shown in table 1. advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti 46 table 1 characteristics of materials component material dimensions yield stress screw shaft carbon steel 1397mm 220mpa ψ303mm base cast steel 1042mm 241mpa 815mm 231mm sliding box 1 1023 carbon steel 600mm 282mpa 540mm 350mm sliding box 2 carbon steel 600mm 220mpa 540mm 350mm fig. 3 mesh of grids parameters in the secondary shaft system fig. 4 typical grids in the secondary shaft system 3. results and discussion firstly, used the solidw orks® simulation module to obtain the stresses and displacements of static results due to external pressure loads (10mpa perpendicular to xy plane, parallel to x axis and y axis, respectively) on left-end of the screw shaft and hydraulic p ressure loads (10mpa on the base) of secondary shaft system. the external loads and their positions are determined in table 2. static stress and displacement results of secondary shaft system for screw shaft locates at top position are shown in fig. 5 and fig. 6, respectively. the maximum value 131mpa of stresses is found in the area of base and the maximum value 0.522mm of displacements is found in the top area of secondary shaft system. the maximum value (131mpa) of stress due to external pressure loads (10mpa in x, y and z) and hydraulic pressure loads (10mpa) are less than yield stress value 241mpa, so the parts of machinery are in safety condition. it suggests that the machinery of secondary shaft system can stand 10mpa external loads. a linear analysis is considered and clarified that the behavior of structure is also linear in fact, for the maximum value 0.522mm of displacements found in the top area of secondary shaft system is very much less than the dimension length 1397mm of the screw shaft. advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti 47 table 2 external loads and their positions external load position value direction external pressure loads on left-end of the screw shaft 10mpa perpendicular to xy plane external pressure loads on left-end of the screw shaft 10mpa parallel to x axis external pressure loads on left-end of the screw shaft 10mpa parallel to y axis hydraulic pressure loads on top of the base 10mpa parallel to y axis fig. 5 stress for the screw shaft locates at top position fig. 6 displacement for the screw shaft locates at top position fig. 7 stress for the screw shaft locates at top position fig. 8 displacement for the screw shaft locates at top position secondly, the simplicity stresses due to the same external p ressure loads (10mpa) place on left -end of screw shaft are studied, when the screw shaft locates at top, medium and bottom positions of the secondary shaft system, respectively. static stress and displacement results for the screw shaft locates at top position are shown in fig. 7 and fig. 8, respectively . fig. 9 stress for the screw shaft locates at medium position fig. 10 displacement for the screw shaft locates at medium position advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti 48 the maximum value 64mpa of stresses is found in the area of base and the maximum value 0.1012 mm of displacements is found in the left-end area of screw shaft and in the left-top-end area of frame. static stress and displacement results for the screw shaft locates at medium position are shown in fig. 9 and fig. 10, respectively. the maximum value 61mpa of stresses is found in the area of base and the maximum value 0.0864 mm of displacements is foun d in the left-end area of screw shaft. static stress and displacement results for the screw shaft locates at bottom position are shown in fig . 11 and fig. 12, respectively. the maximum value 67mpa of stresses is found in the area of base and the maximum va lue 0.07839mm of displacements is found in the left-end area of screw shaft. the maximum value (0.1012mm) of d isplacement due to static-uniform pressure external loads (10mpa) can be occurred at the left-end area of screw shaft, so the cut tool deflection in the secondary shaft system should be reconsidered for the accuracy operation and safety condition . fig. 11 stress for the screw shaft locates at bottom position fig. 12 displacement for the screw shaft locates at bottom position fig. 13 stress for the screw shaft fig. 14 displacement for the screw shaft fig. 15 stress for the sliding box 1 fig. 16 displacement for the sliding box 1 thirdly, the screw shaft in the detail studies are investigated due to the same external pressure loads (10mpa perpendicular to xy p lane, parallel to x axis and y axis, respectively) on left -end of the screw shaft. static stress and displacement results for the screw shaft are shown in fig. 13 and fig. 14, respectively. the maximum value 65mpa of stresses is found in the corner area of shaft and the maximum value 0.058mm of displacements is found in the left -end area of the screw advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti 49 shaft. the sliding box in the detail studies are investigated due to the s ame external pressure loads (10mpa downward to z axis) on the one-end-side of slid ing box. static stress and displacement results for the sliding box 1 material are shown in fig . 15 and fig. 16, respectively. fig. 17 stress for the sliding box 2 fig. 18 displacement for the sliding box 2 the maximum value 309mpa of stresses is found in the sliding-groove area of box and the maximum value 0.046 mm of displacements is found in the front-central area of the sliding box. the maximum value (309mpa) of stress due to external pressure loads (10mpa downward to z axis) is g reater than yield stress value 282mpa, so the sliding box of machinery is in un-safety condition. it suggests that the machinery of the slid ing box 1 material can't exceed 10mpa external loads. it is more interesting to observe some places/spots where there are some stress concentrations that will occur due to different material properties. static stress and displacement results for the slid ing box 2 material are shown in fig. 17 and fig. 18, respectively. the maximum value 2126mpa of stresses is found in the sliding-groove area of box and the maximum value 0.05221 mm of displacements is found in the front-central area of the sliding box. the maximum value (2126mpa) of stress due to extern al pressure loads (10mpa downward to z axis) is much greater than yield stress value 220mpa (almost 10 times), so the sliding box of machinery is in un-safety condition. in the linear analysis, it suggests that the machinery of the slid ing box 2 material can't exceed 1mpa external loads. more informat ive with further analysis related to this study would be the cut position on th e screw shaft in the milling process simulation subject. it would be interesting to investigate the optimize variable pitch fo r the cut under the milling and turning processes with considering the effects of stress and displacement . 4. conclusions in this paper, the static linear stress and displacements of secondary shaft system under external pressure loads in cnc machines are obtained with the simulation module of solidworks® . under the action values of external pressure loads 10mpa and hydraulic pressure loads 10mpa, when the screw shaft locates at top position, the maximum value 131mpa of stresses is found in the area of base and the maximum value 0.522mm of d isplacements is found in the top area of secondary shaft system. the maximum values of stress and displacement are usually provided to give a basic data for the detail and good construction of secondary shaft system, so the cnc machine can present in normal working condition. acknowledgement the completion of this paper was enabled by a grant 105-iem-1244 from hsiuping university of science and technology, taiwan, roc. references [1] a. afkhamifar, d. antonelli, and p. chiabert, “variational analysis for cnc milling process,” procedia cirp, vol. 43, pp. 118-123, 2016. advances in technology innovation, vol. 3, no. 1, 2018, pp. 43 50 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti 50 [2] a. max, v. lašová, and š. pušman, “enhancement of teaching design of cnc milling machines,” procedia social and behavioral sciences, vol. 176, pp. 571-577, 2015. [3] y. altintas, p. kersting, d. biermann, e. budak, b. denkena, and i. lazoglu, “virtual process systems for part machining operations,” cirp annals manufacturing technology, vol. 63, no. 2, pp. 585-605, 2014. [4] m. soori, b. arezoo, and m. habibi, “virtual machining considering dimensional, geometrical and tool deflection errors in three-axis cnc milling machines,” journal of manufacturing systems, vol. 33, no. 4, pp. 498-507, 2014 [5] k. h. chang, “chapter 2 virtual machining,” in product manufacturing and cost estimating using cad/cae, pp. 39-93, 2013. [6] y. wang, b. cui, k. li, t. zhang, and z. zhang, “structural analysis and experimental research of an cnc hydraulic swing-type plate shears,” aasri procedia, vol. 3, pp. 414-420, 2012. [7] a. mackrell, “multiscale composite analysis in abaqus: theory and motivations,” reinforced plastics, 2016. [8] r. m. f. paulo, f. teixeira-dias, and r. a. f. valente, “numerical simulation of aluminium stiffened panels subjected to axial compression: sensitivity analyses to initial geometrical imperfections and material properties,” thin-walled structures, vol. 62, pp. 65-74, 2013. [9] w. younis, “chapter 15 dp13 assembly optimization: structural optimization of a lifting mechanism,” up and running with autodesk inventor simulation 2011 (second edition) a step-by-step guide to engineering design solutions, pp. 353-372, available online 26 may 2010. [10] c. c. hong, c. l. chang, and c. y. lin, “static structural analysis of great five-axis turning-milling complex cnc machine,” engineering science and technology, an international journal, vol. 19, no. 4, pp. 1971-1984, 2016. [11] c. yang, z. liqiang, and l. dong, “general stiffness model for five-axis cnc machining,” international journal of research in engineering and science, vol. 3, no. 8, pp. 43-47, 2015. [12] e. wagner, “a new optimization cad/cam/cae technique for the processing of the complex 3d surfaces on 5 axes cnc machines,” procedia technology, vol. 19, pp. 34-39, 2015. template encit2010 advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 the innovative design of the massage mechanisms for massage chair tzu-hsia chen 1* , long-chang hsieh 2 1 department of mechanical engineering, minghsin university of science and technology, taiwan, roc 2 department of power mechanical engineering, national formosa university, yunlin, taiwan, roc received 05 june 2017; received in revised form 09 july 2017; accepted 29 july 2017 abstract the purpose of this paper is to synthesize all the feasible designs of massage mechanisms (including dof=2 and 3) for the massage chair, based on the modified yan’s creative design methodology. first, the topological structure and motion characteristics of existing massage mechanisms are analyzed and its design requirements and constraints are specified mechanisms with beating and kneading functions are mechanisms with 2 degrees of freedom (dof). then, 14 design concepts are generated. one of the design concepts is curried cut, including kinematic design, engineering drawing, and the prototype manufacture. the simulation result showed that new design can produce a wider range of non-uniform output motion than the extiting design. keywords: beating massage, innovative design, kneading massage, massage-mechanism, yan’s creative design methodology 1. introduction due to busy lifestyles in modern days, insufficient time for sports leads to physical illness. recently, because of the rising economic level and health awareness, the concept of “health protection” is well-known. the massage chair is one of the most popular health products. the action of the massage chair is to mimic the massage therapist. with the progress of the society, the demands of the massage chair became more diversified. when people lie on the massage chair, they can enjoy the massage pressure to eliminate muscle fatigue, relieve pressure, and relax. in general, there are two different modes of the massage chairs, like beating massage and kneading massage, and both of them promote the body health. the massage mechanism can be a planar mechanism [1-2] or spatial mechanism [3-5]. this paper focuses on the systematic design of spatial massage mechanism which provides beating massage and kneading massage, including the concept design, the kinematic analysis, the engineering drawing, engineering design and manufacture of a prototype. first, we analyze the topological structure and motion characteristics of the existing massage mechanisms and conclude its design requirements and constraints. all existing massage mechanisms with beating and kneading functions are mechanisms with 2 degrees of freedom (dof). the purpose of this paper is to synthesize all the feasible designs of massage mechanisms (including dof =2 and dof =3). then, based on the design requirements and constraints also modified yan’s creative design methodology [6-11], we can synthesize all feasible design concepts of massage-mechanisms for the massage chair. therefore, one design concept is chosen for the engineering design and prototype manufacture. the beating and kneading massage traces of this new design is simulated by “cosmos” software to verify the new feasibility of design. 2. existing designs before implementing an innovative design, the structure of the massage mechanism must be collected and analyzed from academic papers, catalogues, and technical reports. based on the analysis results, the massage mechanism can be * corresponding author. e-mail address: summer34134@gmail.com tel.: +886-3-559-3142 ext. 3023; fax: +886-3-557-3797 advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 2 classified as the planar mechanism or spatial mechanism. fig. 1 shows the patent [1] which is the planar mechanism and provides the kneading massage. fig. 1 improvement structure of massage chair [1] fig. 2 shows the patent [3] which is a spatial mechanism and provides the beating and kneading massages. fig. 2(c) shows its corresponding kinematic skeleton. according to fig. 2, the mechanism has 6 links and 6 joints (5 revolute pairs and 1 spherical pair) and belongs to the spatial mechanism. in the 1st input motion, link 2 provides a beating function and in the 2nd input motion, link 6 provides a kneading function. (a) beating massage (b) kneading massage (c) kinematic skeleton fig. 2 improved double drive system of massage chair [3] the mobility of the spatial mechanism can be obtained by following eq. (1). f 6( ) in j i f    (1) where n is the number of links, j is number of joints, and fi is the degrees of freedom of joint i. the mechanism shown in fig. 2 has 6 links, 6 joints (5 revolute pairs and 1 spherical pair), according to the equation of mobility, we get: 6( ) 6(6 6 1) 8 2f n j i f i           (2) 3. creative mechanism design methodology the design concept is the initial stage of the engineering design process and also the most difficult part. all existing massage mechanisms with beating and kneading functions are mechanisms with 2 degrees of freedoms (dof). the purpose of this paper is to synthesize all the feasible designs of the massage mechanism (including dof =2 and dof =3). for the mechanisms with 3 dof, there must be 1 redundant degree of freedom. there is no existing mechanism dof =3) which can provide beating massage and kneading massage, therefore, yan’s creative design methodology [6-10] must be modified. fig. 3 shows the modification of yan’s creative design methodology, and the steps are as follows: advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 3 fig. 3 modified yan’s creative design methodology [7] (1) identify the existing designs (dof =2) with required design specifications that designers would like to have, and conclude the topological characteristics of these designs. (2) according to the topological characteristics, identify the mobility of the mechanism and its corresponding link and joint types. (3) synthesize the atlas of generalized chains that can be used to design massage mechanism with beating and kneading massages for the massage chair. (4) assign types of members and joints to each generalized chain obtained in step 3, to have the atlas of feasible specialized chains based on the algorithm of specialization to meet needed design requirements and constraints. (5) particularize each feasible specialized chain obtained from step 4 to its corresponding kinematic skeleton, to have the atlas of massage mechanism with beating and kneading massages for the massage chair. 3.1. topological characteristics the first step of the modified creative design methodology is to define the design specifications of mechanical devices that design engineers would like to generate. if there is no special consideration, the degree of freedom of a mechanism is equal to the number of independent inputs for the constraint motion. if the degree of freedom is larger than the number of independent inputs, in general, the mechanism will have unconstraint motion. nevertheless, if the excess degree of freedom is the redundant degree of freedom, it will not affect the moving of other links, the mechanism will still have constraint motion and will still be useful. the purpose of this paper is to invent the massage mechanism with 2 and 3 degrees of freedoms (dof) to provide beating and kneading functions. in this paper, we only concern the mechanism with revolute and spherical pairs. according to eq. (1), if n=6, j=6, jr=5, and js=1, the corresponding generalized chain (6, 6) has 2 degrees of freedom. and, according to eq. (1), if n=5, j=5, jr =3, and js =2, the corresponding generalized chain (5, 5) has 3 degrees of freedom. the results are shown in table 1. advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 4 table 1 taxonomy of swarm-based routing protocols degrees of freedom (f) number of links (n) number of joints (j) number of revolute pairs (jr) number of spherical pairs (js) 2 6 6 5 1 3 5 5 3 2 next, the massage mechanisms with beating and kneading functions should have the following topological characteristics: (1) it must be a spatial mechanism (l = 6). (2) it must have 2 input links and 1 output link (massage link). (3) it has a ground link to support or constrain other links. (4) the joints are constrained to be revolute and spherical pairs. (5) for the mechanism with 2 dof, it will have at least 1 spherical pair. (6) for the mechanism with 3 dof, it will have at least 2 spherical pairs. 3.2. atlas of generalized chain (a) (5, 5) generalized chain (b) (6, 6) generalized chain fig. 4 generalized chains for massage mechanism the second step of the modified creative design methodology is to synthesize all possible generalized chains which can be used to synthesize the desired mechanism. there is only 1 generalized chain with 5 links and 5 joints and only 1 generalized chain with 6 links and 6 joints. fig. 4 shows the generalized chains for massage mechanisms. 3.3. design requirements and design constraints design requirements and constraints are determined based on the concluded topological structures. the design requirements and constraints of massage mechanisms for massage chair are: (1) there must be a ground link (gr), first input link for kneading function (i1), second input link for beating function (i2), output link (massage link) (om). (2) the ground link (gr) must be adjacent to 2 input links (i1 and i2) with revolute pairs. (3) the ground link (gr) cannot be incident to spherical pair. (4) the output link (om) can’t be incident to 2 spherical pairs at the same time. (5) for the mechanism with 2 dof, (6, 6) generalized chain must have 5 joints (jr) and 1 spherical pair (js). (6) for the mechanism with 2 dof, (5, 5) generalized chain must have 3 joints (jr) and 2 spherical pairs (jr). (7) for the mechanism with 3 dof, 2 spherical pairs must be adjacent and cause 1 redundant degree of freedom. 3.4. specialization the third step of the modified creative design methodology is to assign specific types of members and joints to each available kinematic chain, subject to certain design requirements to have specialized chains. the specializing steps for massage mechanism are: advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 5 (1) for each generalized chain, identify the ground link (gr) for all possible cases. there are 2 possible identifications as shown in figs. 5(a) and 5(b). (2) for each case obtained in step 1, identify the first input link (kneading function) (i1) and the second input link (beating function) (i2). for the specialized chains as shown in figs. 5(a) and 5(b), based on the design requirements, there are 2 possible identifications show in figs. 6(a) and 6(b). (3) for each case obtained in step 2, identify the output link (massage link om). for the specialized chains shown in figs. 5 (a) and 5(b), based on the design requirements, there are 5 possible identifications show in figs. 7(a)-7(e) (4) for each case obtained in step 3, identify the corresponding revolute pairs (denoted by ○) and spherical pairs (denoted by ●). for (5, 5) generalized chain, there are 2 feasible specialized chains shown in figs. 8(a) and 8(b). for (6, 6) generalized chain, there are 12 feasible specialized chains shown in figs. 9(a)-9(e). (a) (b) fig. 5 identify ground link (gr) (a) (b) fig. 6 identify first input link (kneading function) (i1) and second input link (beating function) (i2) (a) (b) (c) (d) (e) fig. 7 identify output link (massage link) (om) (a) (b) fig. 8 atlas of feasible specialized chain of (5, 5) generalized chain advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 6 (a) (b) (c) (d) (e) (f) (g) (i) (j) (k) (l) (m) fig. 9 atlas of feasible specialized chain of (6, 6) generalized chain 3.5. particularization (a) (b) fig. 10 atlas of feasible massage mechanisms of (5, 5) generalized chain (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) fig. 11 atlas of feasible designs for massage mechanism of (6, 6) generalized chain advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 7 for each feasible specialized chain, it can be particularized into its corresponding kinematic skeleton. particularization is the reverse process of generalization and can be done by applying the generalizing rules in reverse order. figs. 10(a) and 10(b) show 2 feasible massage mechanisms of (5, 5) generalized chain and figs. 11(a)-11(l) show 12 feasible massage mechanisms of (6, 6) generalized chain. the design concept, shown fig. 11(a), is the same as the existing design in fig. 2. therefore, only 11 new designs are synthesized from (6, 6) generalized chain and 2 new designs are synthesized from (5, 5) generalized chain. in this paper, we synthesize 13 new designs of massage mechanisms for the massage chair. 4. engineering design and dynamic simulation after an innovative design, the next step is engineering design. due to the reason of manufacture cost, fig.10 (a) is selected as a design example to carry out, and its solid model is drawn and shown in fig. 12. fig. 13 shows its trace which is simulated by “cosmos”. table 2 shows the comparisons of existing design and new design. according to table 2, we get that new design has larger massage trace than the existing design. if we adjust the initial phase of the kneading input, the range of massage trace will become smaller. table 2 also shows that if the initial phase of the kneading input is increased 7⁰, the corresponding kneading trace is almost close to the existing design. fig. 14 ~16 shows the traces of the new design, respectly. fig. 12 engineering drawing of the design concept shown in fig. 10(a) (a) projection on xy plane (b) projection on xz plane fig. 13 kneading trace of upper roller table 2 the comparisons of existing design and new design kneading massage dispalcement location existing design (initial phase 0) new design (initial phase 0) new design (initial phase 7 of kneading input) x upper roller 2(mm) 2(mm) 2(mm) lower roller 2(mm) 8(mm) 2(mm) y upper roller 7(mm) 11(mm) 7(mm) lower roller 7(mm) 11(mm) 7(mm) z upper roller 21(mm) 41(mm) 22(mm) lower roller 33(mm) 50(mm) 33(mm) beating massage x upper roller 2(mm) 2(mm) lower roller 2(mm) 8(mm) y upper roller 10(mm) 11(mm) lower roller 10(mm) 11(mm) z upper roller 1(mm) 1(mm) lower roller 1(mm) 1(mm) ｘ-ｙ 平面軌跡圖 126 128 130 132 134 136 138 140 179 181 183 185 187 189 191 193 ｘ ｙ ｚ-ｙ平面軌跡圖 108 113 118 123 128 133 138 143 148 153 158 -85 -80 -75 -70 -65 -60 -55 -50 -45 -40 -35 z y advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 8 (a) projection on xy plane (b) projection on xz plane fig. 14 kneading trace of lower roller (a) projection on xy plane (b) projection on xz plane fig. 15 beating trace of upper roller (a) projection on xy plane (b) projection on xz plane fig. 16 beating trace of lower roller 5. conclusions in this paper, the new designs of massage mechanisms have been generated by the systematic design methodology. first, the design requirements and design constraints are summarized based on existing designs. then, according to modified yan’s design methodology, 13 new design concepts synthesized. one of the new design concepts is selected as a design example and verified by kinematic simulation. the simulation result showed that the new design can produced a wider range of non-uniform output motion than the existing design. conflicts of interest the authors declare no conflict of interest. x-y 平面軌跡圖 6 8 10 12 14 16 18 20 180 182 184 186 188 190 192 194 x y z-y 平面軌跡圖 -20 -10 0 10 20 30 40 -90 -80 -70 -60 -50 -40 -30 z y x-y 平面軌跡圖 128 130 132 134 136 138 140 142 179 181 183 185 187 189 191 193 x y z-y 平面軌跡圖 128 130 132 134 136 138 140 142 -66 -64 -62 -60 -58 -56 -54 -52 z y x-y 平面軌跡圖 8 10 12 14 16 18 20 22 180 182 184 186 188 190 192 194 x y z-y 平面軌跡圖 8 10 12 14 16 18 20 22 -81 -79 -77 -75 -73 -71 -69 -67 z y advances in technology innovation, vol. 4, no. 2, 2019, pp. 116 124 9 references [1] h. c. chen, improvement of massage chair structure, roc patent, m268028, june 21, 2005. [2] r. c. bai, massage chair with 3d kneading, beating and pressing functions, roc patent, m518561, march 11, 2016. [3] h. j. chang, improved double drive system of massage chair, roc patent, m289645, april 21, 2006. [4] k. b. chen and m. g. fang, massaging apparatus for massage chair, roc patent, i542341, july 21, 2016. [5] r. y. chen, massaging apparatus for massage chair, roc patent, i547273, september 01, 2016. [6] h. s. yan and l. c. hsieh, “conceptual design of gear differentials for automotive vehicles,” journal of mechanical design, vol. 116, no. 2, pp. 565-570, 1994. [7] h. s. yan, “creative design of mechanical devices,” singapore; new york: springer, 1998. [8] h. s. yan, “a methodology for creative mechanism design,” mechanism and machine theory, vol. 27, no. 3, pp. 235242, may. 1992. [9] l. c. hsieh and t. h. chen, “the systematic design of link-type optical fiber polisher with single flat,” journal of advanced science letters, vol. 9, no. 1, pp. 318-324, april 2012. [10] l. c. hsieh, t. h. chen, and s. j. wei, “the innovative design of wheelchair with lifting and standing functions,” proceeding of engineering and technology innovation, vol. 4, pp. 10-12, 2016. [11] w.h. hsieh and s.j. chen, “innovative design of cam-controlled planetary gear trains,” international journal of engineering and technology innovation, vol. 1, no. 1, pp. 01-11, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 1, no. 2, 2016, pp. 53 57 53 copyright © taeti improved svm classifier incorporating adaptive condensed instances based on hybrid continuous-discrete particle swarm optimization chun-liang lu1,*, tsun-chen lin2 1department of applied information and multimedia, ching kuo institute of management and hea lth, keelung, taiwan. 2department of computer and communication engineering, dahan institute of technology, hualien, taiwan. received 20 sep 2016; received in revised form 24 sep 2016; accepted 28 sep 2016 abstract in recent years, support vector machine (svm) based on empirical risk minimization is supervised learning model which has been successfully used in the classification and regression. the standard soft-margin svm trains a classifier by solving an optimization problem to decide which instances of the training data set are support vectors. however, in many real applications, it is imperative to perform feature selection to detect which features are actually relevant. in order to further improve the performance, we propose the adaptive condensed instances (aci) strategy based on the hybrid particle swarm optimization (hpso) algorithm for the svm classifier design. the basic idea of the proposed method is to adopt hpso to simultaneously optimize the aci and svm kernel parameters for the classification accuracy enhancement. the numerical experiments on several uci benchmark datasets are conducted to find the optimal parameters for building the svm model. experiment results show that the proposed framework can achieve better performance than other published methods in literature and provide a simple but subtle strategy to effectively improve the classification accuracy for svm classifier. keywords : hybrid particle swarm optimizat ion (hpso), adaptive condensed instances (aci), support vector machine (svm) 1. introduction support vector machine (svm) was originally proposed by vapnik [1] which is a powerful classification method with state-of-the-art performance in machine learning theory, has drawn considerable attentions due to its high generalization ability for a wide range of applications including speaker recognition [2], bioinformatics [3] and text categorization [4]. in many pattern classification tasks, we are confronted with the problem that the input space is high dimensional and to find out the combination of original input features which contribute most to the classification is crucial. the computational cost of classification grows heavily with data dimension size, making feature selection an important issue for the svm. the feature selection mechanism falls into three categories: filtering, wrapper, and embedded methods [5]. filters generally involve a non-iterative computation on the original features, which can execute very fast, but not usually optimal since the learning algorithm are not taken into account. wrapper methods usually achieve better results than filters since they are tuned to the specific interactions between the classifier with original feature set and very computationally intensive. finally, unlike filters and wrappers, the embedded techniques simultaneously determine features and classifier during the training process but the computational time is smaller than wrapper methods. feature selection problem is a challenging task because there can be complex interaction among features . therefore, an exhaustive search is practically impossible, and the efficient global search technique is needed. evolutionary computation (ec) are well known heuristic approaches global search ability such as simulated annealing (sa) [6], genetic algorithm (ga) [7], and particle swarm optimization (pso) [8], have gained a lot of attention from researchers in the area. compared with other ec algorithms such as sa and ga, pso is computationally less expensive and can converge more quickly. a ga-based feature selection method, which optimized both the feature selection and parameters for svm, was proposed by huang [9], and the authors pointed out that the algorithm may work superior to the conventional grid search method. however, the treatment of these redundant or irrelevant instances is not taken into account in the classification procedure. in this paper, the effectively adaptive condensed instances (aci) strategy that we previously published [7] is applied to decide which instances of the training data set are support vectors for coping with the problem mentioned above. short communications of the early stages of this work have appeared in [7]. here we significantly extend our approach to account for the relevant instances selection during the svm training process. in order to further improve the classification performance, the aci strategy based on the hybrid particle swarm optimization (hpso) algorithm is proposed for the svm classifier design. several uci benchmark datasets are conducted to validate the effectiveness and the experiment results show that the proposed framework can achieve better performance than other ga-based existing methods in literature. the remainder of this paper is organized as follows. section 2 describes the related work including the basic pso and svm classifier. section 3 illustrates particle representation, hybrid pso with disturbance operation, aci scheme and the proposed framework for the svm classifier. section 4 provides the experiment results, and conclusions are made in section 5. 2. related work 2.1. particle swarm optimization (pso) algorithm the pso algorithm, which is originally developed by kennedy and eberhart [10], is a search algorithm modeling the social behavior of birds within a flock. in the pso algorithm, individuals referred to as particles, are flown through hyper dimensional search space. pso is easy to implement, few parameters to ad just, and usually faster convergence rates *corresponding author, email: leucl@ems.cku.edu.tw advances in technology innovation, vol. 1, no. 2, 2016, pp. 53 57 54 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti than other evolutionary algorithms. during the optimization procedure, particles communicate good positions to each other and adjust position according to their history experience and the neighboring particles. the basic concept of the pso algorithm is illustrated as follow: 1 1 1 2 2 ( ) ( ) k k k k id id id id k k id id v w v c r pb x c r gb x            (1) 1 1k k k id id idx v x   (2) where 1,2,...,d d , 1,2,...,i n , and d is the dimension of the search space, n is the population size, k is the iterative times; k idv is the i-th particle velocity, k idx is the current particle solution, the i-th particle position is updated by equation (2). k idpb is the i-th particle best ( bestp ) solution achieved so far; k idgb is the global best ( bestg ) solution obtained by any particle in the population; 1r and 2r are random values in the range [0,1] for denoting remembrance ability. both of 1c and 2c are learning factors, w is inertia factor. a large inertia weight facilitates global exploration, while a small one tends to local exploration. generally, the value of each component in v can be clamped to the range [− maxv , maxv ] for controlling excessive roaming of the particle outside the search space. the pso procedure is organized in the following sequence of steps. step 1: initialize: randomly generating initial particles. step 2: fitness evaluation: calculate the fitness values of each particle in the population. step 3: update: compare fitness values of each particle to update the velocity and position by using equation (1) and (2). step 4: termination criterion: repeat the step 2 to step 3 until the number of iteration reaches the pre-defined maximum number or a termination criterion is satisfied, and the best solution bestg is displayed. 2.2. support vector machine (svm) classifier support vector machine (svm) have drawn much attention due to their good performance and solid theoretical foundations [11]. the main concepts of svm are to first transform input data into a higher dimensional space by means of a kernel function and then to find an optimal separating hyper-plane between the two data sets. a practical difficulty of using svm is the selection of parameters such as the penalty parameter c of the error term and the kernel parameter  in rbf kernel function. the appropriate choice of parameters is to get the better generalization performance. the description of svm is as follows. given a set of training data 1( , , )px x with corresponding class labels 1( , , )py y and { 1, 1}iy    . the svm attempts to find a decision surface ( )f x , to jointly maximize the margin between the two classes and minimize the classification error on the training set. 1 ( ) ( , )p i i ii f x y k x x b    (3) where k is a kernel function, i is the lagrange multiplier corresponding to the i-th training data ix and b is the bias. the simple kernel is the inner product function ˆ ˆ( , ) ,k x x x x which produces the linear decision boundaries. nonlinear kernel function maps data points to a high-dimensional feature space as linear decision spaces. two commonly used kernels are the polynomial kernel ˆ( , )pk x x and the radial basis function (rbf) kernel ˆ( , )rk x x . the integer polynomial order  in pk and the width factor  in rk are hyper-parameters which are tuned to a specific classification problem.  ˆ ˆ( , ) 1 ,pk x x x x    (4) 2ˆ ˆ( , ) x x rk x x e    (5) 3. method since the optimal hyper-plane obtained by the svm depends on only a small part of the data points (support vectors), it may become sensitive to noises or outliers in the training set. in this section, the aci scheme based on hybrid pso (hpso) is proposed to tackle feature selection, condensed instances extraction and parameters setting simultaneously for svm. the particle representation, fitness definition, disturbance strategy for pso operation, aci scheme and the proposed hybrid framework for svm are described as follows. 3.1. particle representation this study used the rbf kernel function for the svm classifier to implement our proposed method. the rbf kernel function requires two parameters c and  should be set. using the adaptively condensed instance rate for aci scheme and the rbf kernel for svm, these three parameters cond ,c , and features used as input attributes must be optimized simultaneously for our proposed hybrid system. the particle, therefore, is comprised of four parts, cond , c ,  are the continuous variables and the features mask are the discrete variables. table 1 shows the particle representation of our design. table 1 the hybrid particle representation as shown in table 1, the representation of particle i with dimension of 3fn  , where fn is the number of features that varies from different datasets, ,1 ,~ fi i nx x are the features mask, , 1fi nx  indicates the parameter value cond , , 2fi nx  represents the parameter value c and , 3fi nx  denotes the parameter value . fitness function f is the guide of hpso operation to maximize the classification accuracy and minimize the number of selected features. cca is the svm classification accuracy, if denotes the feature mask which 1 represents the feature i is selected and 0 indicates that feature i is not selected. thus, the particles with high classification accuracy and a small number of features produce a high fitness value and affect particle’s positions on the next iteration. considering the tradeoff between the classification accuracy and selected feature number, these two weight 1w and 2w values can be adjusted according to the preference for svm classifier design. advances in technology innovation, vol. 1, no. 2, 2016, pp. 53 57 55 copyright © taeti 1 1 2 1 fn i i f w acc w f              (6) 3.2. pso with disturbance operation in the discrete pso, the particle’s personal best and global best is updated as in continuous value. the major different between discrete pso with continuous version is that velocities of the particles are rather defined in terms of probabilities that a bit whether change to one. by this definition, a velocity must be restricted within the range min max[ , ]v v . this can be accomplished by a sigmoid function ( )s v , and the new particle position is calculated using the following rule: if 1 min max( , )k idv v v  then 1 1 max minmax(min( , ), )k k id idv v v v  , where 1 1 1( ) 1 k id k id v s v e      (7) if 1( ) ( )k idrand s v  , then 1 1k idx   ; else 1 0k idx   . the function ( )ids v is a sigmoid limiting transformation and ( )rand is a random number selected from a uniform distribution in [0, 1]. note that the discrete pso is susceptible to a sigmoid function ( )s v saturation which occurs when velocity values are either too large or too small. for a velocity of zero, it is a probability of 50% for the bit to flip. according to the searching behavior of pso, the bestg value will be an important clue in leading particles to the global optimal solution. it is unavoidable for the solution to fall into the local minimum while particles try to find better solutions. in order to allow the solution exploration in the area to produce more potential solutions, a mutation-like disturbance operation is inserted between eq. (1) and eq. (2). the disturbance operation random selects k dimensions (1 k problem dimensions) of m particles (1m particle numbers) to put gaussian noise into their moving vectors (velocities). the disturbance operation will affect particles moving toward to unexpected direction in selected dimensions but not previous experience. it will lead particle jump out from local search and further can explore more diversity of searching space. 3.3. adaptive condensed instances (aci) scheme the effectively aci scheme that we previously published in [7] is extended to decide which instances of the training data set are support vectors. the adaptively condensed instances coefficient in the data reduced process is flexible to edit out noisy samples, reduce the superfluous data points and make the svm less sensitive to noises and outliners. the adaptively condensed instances coefficient [0,1]cond  is defined as the ratio of the selected number of condensed instances to overall dataset. the aci scheme is described as follows. step 1: initialize: randomly generating initial instance set. step 2: condense: to decide whether all samples have been achieved the user defined threshold cond . if so, terminate the process; otherwise, go to step 3. step 3: extend: if there are any un-condensed instances, using the nearest neighbor voting to renew the condensed instances; otherwise, no more new data is joined and go to step 2. 3.4. the proposed framework for svm classifier based on the particle representation, fitness definition, pso with disturbance operation and aci scheme mentioned above, details of the proposed hybrid framework for svm procedure from step 1 to step 9 are described as follows. step 1: data preparation given a dataset d is considered using the 10 fold cross validation to split the data into 10 groups. each group contains training and testing sets. the training and testing sets are represented as traind and testd , respectively. step 2: hybrid pso initialization and parameters setting set the pso parameters including the number of iterations, number of particles, velocity, particle dimension, disturbance rate, and weight for fitness. generate initial hybrid particles comprised of the features mask, cond , c and  . step 3: condensed instances selection via the aci scheme according to the condensed instances coefficient cond represented in the particle and calculated from step 2, when all the condensed instances are computed, the nearest neighbor voting is used to renew the condensed instances set. step 4: feature scaling feature scaling is to properly reveal the interactions between features and to avoid attributes in greater numeric ranges dominating those in smaller numeric ranges. normalization by eq. (8) can be linearly scaled to range [-1, +1] or [0, 1], where ( )j ia x is the original attribute value of feature ix , ' ( )j ia x is scaled value, max j and min j correspond to the maximum and minimum values for ja over all samples. ' ( ) min ( ) , max min j i j j i j j a x a x i     (8) step 5: feature selection according to the feature mask, which is represented in the particle from step 2, is to select input features for training set traind and testing set testd . the selected features subset can be denoted as _f traind and _f testd , respectively. step 6: to train and test for svm classifier for the parameters cond , c and  which are represented in the particle, to train the svm classifier on the training dataset _f traind , then the classification accuracy cca for svm on the testing dataset _f testd can be evaluated. step 7: fitness evaluation for each particle, the fitness value is to be calculated by the eq. (6). the optimal fitness value can be stored on the evolution process of pso to search for the better fitness of particle in the next particles evolution procedure. step 8: termination criteria when the number of iteration reaches the pre-defined maximum number or a termination criterion is satisfied, the best solution bestg is obtained, and the program ends; otherwise, go to the next step. advances in technology innovation, vol. 1, no. 2, 2016, pp. 53 57 56 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti step 9: hybrid pso operation in the evolution process, discrete-valued and continuous-valued dimension of hpso with the disturbance operator continued to be applied for searching better particle solutions. 4. experiment results 4.1. dataset and system description to measure the performance of the developed hybrid framework, several real benchmark datasets in table 2 are conducted to verify the effectiveness of performance. these table 2 the uci benchmark datasets [7] datasets are partitioned using the 10-fold cross validation. our implementation platform was implemented on matlab 2013, by extending the libsvm which is originally designed by chang and lin [12]. through initial experiment, the parameter values of the pso were set as follows. the swarm size is set to 100 particles. the searching ranges of continuous type dimension parameters are: [0,1]cond  , 2 4[10 ,10 ]c  and 4 4[10 ,10 ]  . the discrete type particle for features mask, we set min max[ , ] [ 6,6]v v   , which yields a range of [0.9975,0.0025] using the sigmoid limiting transformation by eq. (7). both the cognition learning factor 1c and the social learning factor 2c are set to 2. the disturbance rate is 0.05, and the number of generation is 500. the inertia weight factor min 0.4w  and max 0.9w  . the linearly decreasing inertia weight is set as eq. (9), where nowi is the current iteration and maxi is the pre-defined maximum iteration. according to the fitness function defined by eq. (6), set the accuracy’s weight 1 0.8w  and the feature’s weight 2 0.2w  . max max min max ( )nowi w w w w i    (9) table 3 the parameters setting for pso and ga in [9], the authors presented the ga-based method without aci mechanism for searching the bestc ,  , and features subset. the existing ga-svm method without aci scheme deals solely with feature selection and parameters optimization by means of genetic algorithm, and the treatment of these redundant or noisy instances in a classification process did not be taken into account. our proposed hybrid framework has been tested fairly extensively and compared with these approaches including both ga-svm and pso-svm approaches without aci mechanism. furthermore, the comparison of pso and ga technique with the aci scheme for svm is also presented. while applying ga algorithm, a number of parameters are required to be specified. the two algorithms (both pso and ga) are run for the same number of fitness function evaluations. table 3 summarized the parameters used for pso and ga technique. the empirical results are reported in section 4.2. 4.2. result and comparison the results obtained by the developed hpso-aci-svm approach are compared with those of ga-svm proposed by huang et al. [9] without aci scheme. taking the heart disease dataset, for example, the classification accuracy cca , number of selected features fn , and the best parameters cond , c ,  for each fold are shown in table 4. for the hpso-aci-svm method, average classification accuracy rate is 96.87%, and average number of features is 4.9. for the ga-svm without aci approach, its average classification accuracy rate is only 94.81%, and average number of features is 5.6. table 4 comparison for hpso-aci-svm and ga-svm table 5 comparison for hpso-aci-svm, pso-svm and ga-svm advances in technology innovation, vol. 1, no. 2, 2016, pp. 53 57 57 copyright © taeti table 5 shows the summary results for the average class ification accuracy rate of the hpso-aci-svm hybrid framework and pso-svm, ga-svm without aci method on six uci datasets. in table 5, the classification accuracy rate is represented as the form of ‘average standard deviation’. to highlight the advantage, we used the non-parametric wilcoxon signed rank test for all of the datasets. in table 5, the p-values of hpso-aci-svm versus pso-svm and ga-svm are smaller than the statistical significance level of 0.05 except iris dataset. that is to say, the developed hpso-aci-svm yields higher classification accuracy rate across different datasets to enhance the performance for the svm. further, under our proposed hybrid framework with aci mechanism, the performance of both pso and ga optimization techniques in terms of the average classification accuracy rate _ ccavg a and the average number of selected features _ favg n is compared. in table 6, the hpso exhibits slightly higher classification accuracy and fewer selected features than ga. it is observed that, from an evolutionary point of view, the performance of the hpso is better than ga. however, the results indicate that both pso and ga algorithms can be used in optimizing the parameters under our developed hybrid framework to effectively improve the classification accuracy for svm classifier design. table 6 comparison for hpso-aci-svm and ga-aci-svm 5. conclusion for svm classifier, it is imperative to perform feature selection to detect which features are actually relevant. in this study, the effectively adaptive condensed instances (aci) strategy is applied to decide which instances of the training data set are support vectors. furthermore, we propose the aci scheme based on the hybrid particle swarm optimization (hpso) algorithm to simultaneously optimize the condensed instances and svm kernel parameters for the classification accuracy enhancement. several uci benchmark datasets are conducted to validate the effectiveness of the proposed method, and the experiment results show that the proposed hybrid framework can achieve better performance than other existing methods in literature. investigating more large scale dataset as well as combining other heuristic algorithm for hybrid system may be interesting future work. references [1] v. n. vapnik, "an overview of statistical learning theory," ieee transactions on neural networks, vol. 10, pp. 988-999, 1999. [2] i. j. ding, c. t. yen, and d. c. ou "a method to integrate gmm, svm and dtw for speaker recognition," international journal of engineering and technology innovation, vol. 4, pp. 38-47, 2014. [3] r. kothandan and s. biswas, "identifying micrornas involved in cancer pathway using support vector machines," computational biology and chemistry, vol. 55, pp. 31-36, apr. 2015. [4] b. ramesh and j. g. r. sathiaseelan, "an advanced multi class instance selection based support vector machine for text classification," procedia computer science, vol. 57, pp. 1124-1130, 2015. [5] x. zhang, g. wu, z. dong and c. crawford, "embedded feature-selection support vector machine for driving pattern recognition," journal of the franklin institute, vol. 352, pp. 669-685, 2015. [6] s.w. lin, z. j. lee, s. c. chen and t. y. tseng, "parameter determination of support vector machine and feature selection using simulated annealing approach," applied soft computing, vol. 8, pp. 1505-1512, 2008. [7] c. l. lu, i. f. chung and t. c. lin, "the hybrid dynamic prototype construction and parameter optimization with genetic algorithm for support vector machine," international journal of engineering and technology innovation, vol. 5, pp. 220-232, 2015. [8] b. sahu and d. mishra, "a novel feature selection algorithm using particle swarm optimization for cancer microarray data," procedia engineering, vol. 38, pp. 27-31, 2012. [9] c. l. huang and c. j. wang, "a ga-based feature selection and parameters optimization for support vector machines," expert systems with applications, vol. 31, pp. 231-240, 2006 [10] j. kennedy and r. c. eberhart, "a discrete binary version of the particle swarm algorithm," in proceedings of the world on systematics, cybernetics and informatics, vol. 8, pp. 4104-4109, 1997. [11] v. vapnik, the nature of statistical learning theory, new york: springer-verlag, 1995. [12] c. c. chang, and c. j. lin, "training nu-support vector regression: theory and algorithms," neural computation, vol. 14, pp. 1959-1977, 2002. advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 a differential evolution optimization approach for parameters estimation of truncated and censored failure time data chanan s. syan, geeta ramsoobag * department of mechanical and manufacturing engineering university of the west indies, st. augustine, trinidad, west indies. received 05 june 2017; received in revised form 07 september 2017; accepted 14 september 2017 abstract most practically collected datasets are plagued with issues of incompleteness and inaccuracies which will cause erroneous reliability modeling and poor maintenance decisions. this work outlines an investigation into the use of heuristic techniques to estimate the parameters of a stochastic life distribution by using failure data with truncation and censoring. a maximum likelihood estimation (mle) approach was utilized in which the loglikelihood function is modified to account for the truncation and censoring factors. a differential evolution (de) algorithm developed in matlab r2013a minimizes the negative log likelihood (nll) function and obtains optimum parameters for the 2 parameters (2-p) weibull distribution. results obtained from a series of designed experimental tests generalized the relationship between the increasing levels of truncation and censoring individually on the β and η parameters. the impact of the modified nll technique was examined under cases of left truncated and right censored (ltrc) data through evaluations of the mse metric which were compared to estimations made under the normal nll equation. truncation and censoring percentages were increased from 0% to 50% for testing the modified nll approach. it is clear from the low mse values (error) that this approach is successful at estimating the parameters closer to the true values. this approach was applied to failure data of a gas engine power generator utilized in offshore gas production. the results were compared with those obtained from traditional weibull analysis in the reliasoft weibull/alta package. keywords: heuristics, truncation, censoring, maximum likelihood estimation, reliability analysis 1. introduction maintenance optimization algorithms have now become an indispensable tool that asset intensive organizations utilize to reduce costs and increase profit margins. a significant aspect of this process entails the collection and analysis of lifetime data. weibull analysis and other data fitting methods compose the basis of interpretations for equipment degradation over time. however, a drawback of these analyses is the dependency on accurately collected and complete datasets [1]. in many cases, the quality of failure time data has been a major cause for concern. truncation, censoring or even missing events are a few of the problems with most practically collected data [2]. in many analyses, these factors are unaccounted and risk impacting failure predictions. this further impacts the accuracy of maintenance planning in the optimization stages. the popularity of such data in engineering and other fields such as medical sciences has prompted several areas of research to address the above mentioned issues [3-4]. maximum likelihood estimation (mle) has been ubiquitous in such cases. its adaptability towards treating with truncated and censored data is noted in a number of past publications [5-6]. * corresponding author. e-mail address: chanan.syan@sta.uwi.edu tel.: +1 868 662 2002 ext. 82074 advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 186 traditionally adopted gradient based methods have been utilized to maximize the likelihood function established. in this regard, the predominance of issues such as trapping at local maxima or minima is noted, leading to failure of convergence in many cases [7]. heuristics have been proposed for a number of years to estimate function parameters with much success [8]. a novel aspect of the work reported in this paper investigates the applicability and accuracy of extending heuristic global optimization techniques towards the likelihood function. this would alleviate the issues that have been mentioned while providing simplicity in dealing with the complex function which traditional techniques are not able to address. section 2 of this paper details the findings of past literature; section 3 defines the methodology which was undertaken in the current study; section 4 outlines the results illustrating the truncation and censoring impact and application to a real case study of an offshore gas power generator. section 5 draws conclusions to date from the results and presents future research work. 2. literature research 2.1. left truncation and right censoring although there are various categories of incomplete datasets, the current work targets three specific classifications namely left truncated, right censored, and left truncated and right censored (ltrc) data. for defining these three (3) classifications, consider failure time data collected from 100 identical power transformers between the period 1980 and 2008. the classification of failure cases can be completely defined by four (4) categories as illustrated in fig. 1. failure case 1 represents the class of right censored data which remains in operation at the end of the observation period of 2008. case 2 is a left truncated observation occurring between installation year and prior to the end of the observation period. case 3 illustrates a combined class of left truncation and right censoring. case 4 represents a transformer which was installed and failed prior to observation and as a result no data is available. case 4 is termed as missing data. fig. 1 classification of truncated and censored data [9] the issue of ltrc data has been explored widely in the fields of medicine and is becoming increasingly popular in engineering applications. perhaps the most popular technique was applied by balkrishnan and mitra [5] and liu [10] which involved parameter estimation through a modified likelihood function for ltrc data. an expectation maximization (em) and newton raphson (nr) algorithm was used for comparison purposes to execute the optimization of the estimated function. mitra [11] used this approach to estimate the parameters of a weibull, gamma and log-normal distribution for simulated ltrc failure times with characteristics of that as defined by hong [2] for power transformers. furthermore, emura and shiu [9] adopted and transformed the maximization approach through the use of a one-step nr algorithm for simplicity. although significant developments have been made drawbacks are apparent in terms of complexity, nonconvergence and local maxima or minima trapping when dealing with gradient decent based optimization techniques [7]. advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 187 2.2. heuristics optimization techniques differential evolution heuristic techniques are a branch of evolutionary algorithms which perform global optimization searches based on stochastic evolution rather than gradient based decent [12]. for this reason, such techniques remain unaffected by the drawbacks of traditional search techniques. genetic algorithms (ga), particle swarm optimization (pso) and simulated annealing (sa) are amongst some of the more popularly applied algorithms for parameter estimation purposes. the differential evolution (de) algorithm was developed by storn and price in the nineties as a recent advancement in this area [13-14]. de offers the advantage of determining global minima/maxima points despite the selection of initial values, fast convergence and fewer limitations of control parameters [15]. das et al. [16] presented an exhaustive survey on des and their adaptations over the years. furthermore, wang and huang [17] applied de to estimate stochastic parameters illustrating the change in population probability density function (pdf) upon crossover, mutation and selection operations. lobato et al. [18] compared de to sa for the estimation of radiative properties through an inverse problem approach. 2.3. maximum likelihood estimation the mle method as defined by scholz [19] is as follows: consider a random vector of observations x = (x1, x2,…,xn) defined by the joint probability distribution function over the n dimensional euclidean space rn. the likelihood function is defined as given in eq. (1). 𝐿𝑥(𝜃) = ∏ 𝑓(𝑥𝑖; 𝜃1, 𝜃2, … , 𝜃𝑟) 𝑤ℎ𝑒𝑟𝑒 𝜃1, 𝜃2, 𝜃3, … , 𝜃𝑟 𝑎𝑟𝑒 𝑡ℎ𝑒 𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑠 𝑜𝑓 𝑡ℎ𝑒 𝑑𝑖𝑠𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛𝑛 𝑖=1 (1) the pdf for 2-p weibull with θ= (β, η) is given in eq. (2) below. 𝑓(𝑥; 𝛽, 𝜂) = 𝛽 𝜂 ( 𝑥𝑖 𝜂 ) 𝛽−1 𝑒 −( 𝑥𝑖 𝜂 ) 𝛽 (2) substitution of eq. (2) into eq. (1) and taking logs we obtain eq. (3) as shown below. 𝐿𝐿(𝑥𝑖: 𝛽, 𝜂) = 𝑛 (𝑙𝑜𝑔 𝛽 𝜂 ) + ∑ {(𝛽 − 1) 𝑙𝑜𝑔 ( 𝑥𝑖 𝜂 ) − ( 𝑥𝑖 𝜂 ) 𝛽 } 𝑛 𝑖=1 (3) the log-likelihood function is extended to include left truncated and right censored data with truncation indicator, ν, and censoring indicator, 𝛿, as shown in eq. (4) [11]. both indicators are binary in nature [1,0] with 𝜈𝑖 𝑜𝑟 𝛿𝑖 = 0 if the sample element is truncated or censored and 𝜈𝑖 𝑜𝑟 𝛿𝑖 = 1 if it is not. mitra [11] tested the approach using multiple unit systems where in some cases the dataset belonging to a single unit may or may not be truncated or censored. for a truncated unit, the truncation time is given by 𝜏𝑖. 𝐿(𝛽, 𝜂) = ∑ 𝛿 {𝑙𝑜𝑔𝛽 − 𝑙𝑜𝑔𝜂 + (𝛽 − 1)𝑙𝑜𝑔 𝑥𝑖 𝜂 }𝑛 𝑖=1 − ( 𝑥𝑖 𝜂 ) 𝛽 + ∑ (1 − 𝜈) ( 𝜏 𝜂 ) 𝛽 𝑛 𝑖=1 (4) although de has been applied extensively towards parameter estimation its extension in the context of dealing with incomplete datasets is yet to be investigated. thus, the main focus of the current work is to analyze the application of the de heuristic global optimization technique for parameter determination purposes as applied to truncated and censored datasets. the modified mle technique will be implemented within the de algorithm to account for the incomplete data. 2.4. mean squared error performance metric past authors have often implemented the mean squared error (mse) metric for determining the levels of success attained through their approaches [2, 9, 11]. mse estimates the error between the predicted and true values as represented in the undermentioned eq. 5. for n estimates, if xîis the vector of estimates and xiis the vector of true values then the mse is calculated as: 𝑀𝑆𝐸 = 1 𝑛 ∑ (𝑋�̂� − 𝑋𝑖) 2𝑛 𝑖=1 (5) advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 188 3. methodology matlab r2013a software was utilized for coding the de algorithm in the current study. the algorithm would refer to the normal and modified nll equations with the aim being to minimize the function and follows the standard flow diagram proposed by storn and price [13]. to effectively test the capability of estimating the parameters with minimum error, data were simulated using reliasoft’s weibull/alta monte carlo simulation (mcs) package. this approach also allowed for comparative testing with both complete and incomplete datasets. complete datasets were firstly simulated with the choice of beta values selected to cover cases of reliability growth (β<1) and reliability degradation (β>1). for many industrial systems a combination of static and rotational equipment typically coexists. thus to properly represent the failure nature for both types, beta values of 0.6, 2.5 and 4.5 were randomly selected. table 1 shows the full composition of the data simulation program. additionally, four sample sizes of 20, 100, 150 and 200 were selected in the current study. in comparison to previous work, this range of sample sizes is smaller. however, this was the choice in the current work since much of the practical data collected from the industry conform to sample sizes within the range of 20-200. thus, to allow for conformity in the practical application section similar sample sizes were selected. since the mcs allowed for different levels of censoring to be included, censored samples corresponding to 5%, 20% and 50% for each weibull parameter vector set and sample size were also simulated. all data generations were then exported, chronologically ordered and then artificially left truncated by omitting the initial number of failures corresponding to the truncation percentage as a function of sample size. a total of 384 tests were performed, and the mse values were calculated for each dataset tested. fig. 3 and fig. 5 illustrate a comparison of the pdf plots for the true and estimated weibull parameters. table 1 dynamics of the simulated datasets used for testing the de algorithm parameter varied # of variations details references weibull distribution parameter vector 3 beta, β=0.6 , eta, η=500 beta, β=2.5, eta, η=2500 beta, β=4.5, eta, η=4000 [20] sample size 4 20, 100,150 and 200 n/a percentage censoring 4 0%,5%, 20% and 50% [5], [7], [11] percentage truncation 4 0%,5%, 20% and 50% [5], [7], [11] total # of datasets 192 total # of tests 384 (normal and modified nll) 4. results 4.1. truncation effect (a) effect of truncation percentages on beta and eta estimates with normal nll (b) effect of truncation percentages on beta and eta estimates with modified nll fig. 2 effect of truncation percentages of beta and eta values 2000 2200 2400 2600 2800 0 1 2 3 0 5 20 50 et a (η /h rs ) b e ta ( β ) beta20 beta100 beta150 beta200 eta20 eta100 eta150 eta200 advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 189 (a) effect of increased truncation percentages on the pdf curve with normal nll l (b) effect of increased truncation percentages on the pdf curve with modified nll fig. 3 effect of increased truncation percentages on the pdf curve the individual effect of truncation and censoring percentages was investigated initially. fig. 2 shows the impact when using (a) the normal nll and (b) the modified nll functions for varying percentages of truncation. the true beta and eta values for the data were 2.5 and 2500 hours respectively and the results are displayed for all sample sizes. the estimated values of β and η have surpassed the true values when utilizing the normal nll function. significant improvement can be noted with the use of the modified nll equation in fig. 2(b). the values for beta and eta are estimated much closer to the true values even at increased levels of truncation. the accuracy of the estimates is, however, dependent on the sample size. at larger sample sizes of 150 and 200 the accuracy of estimation was higher as expected. fig. 3 further illustrates the overall effect of left truncation on the weibull pdf, where it can be noted that the truncation percentage increases, the distribution is shifted to the right indicating increased characteristic life. therefore, as the truncation percentage increases, the errors in characteristic life would also increase. larger truncation percentages cause inaccurate magnification in β values resulting in the higher failure rate than the true value, again introducing errors in reliability of the asset. 4.2. the censoring effect figs. 4(a) and 4(b) illustrate the impact of right censoring on both beta and eta parameters for true beta =2.5 and true eta=2500 for all sample sizes. an increase in the beta values and reduction in the eta values were noted with increasing percentages of censoring. increased values of beta indicate a higher failure rate for the asset than the true value while decreasing eta implies a reduction in characteristic life. the censoring impact is noted in the pdf curve as illustrated in fig. 5(a) as it shifts it to the left along the time axis. this reduction in eta decreases the characteristic life and exaggerates the state of unreliability. utilization of the de algorithm has proven effective in nullifying the effects of censoring as demonstrated in fig. 5(b). there is a minimal impact on the pdf curves even at a high percentage of censoring. an added benefit noted with the use of the de algorithm was its ability to enforce repeatability in the results. under different internal parameters, the de algorithm shows no variation in the results, indicating that it is robust. (a) effect of censoring percentages on beta and eta values with normal nll (b) effect of censoring percentages on beta and eta values with modified nll fig. 4 effect of censoring percentages on beta and eta values 0 1000 2000 3000 0 2 4 6 0 5 20 50 et a (η /h rs ) b e ta ( β ) beta20 beta100 beta150 beta200 eta20 eta100 eta150 eta200 0 2000 4000 0 1 2 3 0 5 20 50 et a (η /h rs ) b e ta ( β ) beta20 beta100 beta150 beta200 eta20 eta100 eta150 eta200 advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 190 (a) effect of increased censoring percentages on the pdf curve with normal nll (b) effect of increased censoring percentages on the pdf curve with normal nll fig. 5 the effect of increased censoring percentages on the pdf curve. 4.3. left truncation and right censoring (a) mse values for sample size 20 with normal nll equation (b) mse values for sample size 100 with normal nll equation (c) mse values for sample size 150 with normal nll equation (d) mse values for sample size 200 with normal nll equation fig. 6 mse values for three simulated weibull parameter vector sets under varying combinations of truncation and censoring the majority of testing investigated different percentage combinations of ltrc data. comparison of the estimates illustrated the benefits when utilizing the modified nll equation and de algorithm. table 2 summarizes the results of mse for different distribution parameters at increasing combinations of truncation and censoring. although the percentages of truncation were increased from 5% to 50%, the increase in the mse values remained low, indicating that the estimated 0 200 400 600 800 1000 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta =4.5 and true eta=4000 hrs true beta=2.5 and true eta = 2500 hrs true beta=0.6 and true eta =500 hrs 0 5000 10000 15000 20000 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta =4.5 and true eta =4000 hrs true beta = 2.5 and true eta = 2500 hrs true beta = 0.6 and true eta = 500 hrs 0 5000 10000 15000 20000 25000 30000 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta = 4.5 and true eta= 4000 hrs true beta = 2.5 and true eta = 2500 hrs true beta = 0.6 and true eta = 500 hrs 0 5000 10000 15000 20000 25000 30000 35000 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta = 4.5 and true eta = 4000 hrs true beta = 2.5 and true eta = 2500 hrs true beta = 0.6 and true eta= 500 hrs advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 191 values are much closer to the true values. a range of the mse from 0.89 to 16,133 was obtained in the case of true β=0.6 and true η=500 under the normal nll while a range from 0.13 to 5.97 was noted under the modified nll and de algorithm for truncation and censoring percentages increasing from 0% to 50%. similar ranges were obtained with the other weibull parameter vector sets as well. the reduction in mse levels were noted for all sample sizes tested. table 2 shows the results for sample size of 100. in the current work, a smaller range of sample sizes was tested compared to past publications. this was done to make the practical and simulated datasets of similar sizes for comparison purposes. table 2 mse values for normal and modified nll equations at sample size 100 for combinations of percentage truncation and censoring (%t/%c) mean squared error (mse) true β=0.6 and true η=500 true β=2.5 and true η=2500 true β=4.5 and true η=4000 percentage truncation/percentage censoring 0/0 5/5 20/20 50/50 0/0 5/5 20/20 50/50 0/0 5/5 20/20 50/50 normal nll 0.89 54.0 1220 16133 0.115 53.7 1221 12599 0.17 53.8 1220.6 5313.7 modified nll 0.13 5.09 5.51 5.97 0.116 4.78 5.39 6.00 0.17 4.78 5.39 6.01 the reduction and stabilization of mse values are noted in fig. 7 (a)-(d). the larger differences which were noted across the weibull distributions at higher percentages of censoring were also minimized. in addition, contrary to fig. 6 which shows a steady increase in the mse for increasing sample sizes, these values have remained consistently lower throughout all sample sizes when the modified nll and de algorithm are implemented. this indicates a much more precise and accurate estimation to the true values. (a) mse values for sample size 20 with modified nll equation (b) mse values for sample size 100 with modified nll equation (c) mse values for sample size 150 with modified nll equation (d) mse values for sample size 200 with modified nll equation fig. 7 mse values for three simulated weibull parameter vector sets under varying combinations of truncation and censoring 0 2 4 6 8 10 12 14 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta=4.5 and true eta =4000 hrs true beta= 2.5 and true eta=2500 hrs true beta=0.6 and true eta=500 hrs 0 5 10 15 20 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta=4.5 and true eta=4000 hrs true beta=2.5 and true eta=2500 hrs true beta=0.6 and true eta=500hrs 0 5 10 15 20 25 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta=4.5 and true eta=4000 hrs true beta=2.5 and true eta=2500hrs true beta=0.6 and true eta=500hrs 0 2 4 6 8 10 12 14 0 ,0 5 ,5 2 0 ,2 0 5 0 ,5 0 0 ,5 0 ,2 0 0 ,5 0 5 ,0 2 0 ,0 5 0 ,0 5 ,2 0 5 ,5 0 2 0 ,5 5 0 ,5 2 0 ,5 0 5 0 ,2 0 m se percentage truncation/percentage censoring, %t/%c true beta=4.5 and true eta=4000hrs true beta=2.5 and true eta=2500hrs true beta=0.6 and true eta=500hrs advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 192 4.4. practical application the data used for the practical validation was the failure times relating to an offshore platform gas engine generator. the power generator is a critical asset on the self-sustainable platform since it provides a source of power to many other pieces of equipment. since the failure time data from the organization’s computer maintenance management system (cmms) is incomplete, modified approaches are required to account for these deficiencies. traditional weibull analysis has been performed on the generator by using reliasoft’s weibull/ alta software package. subsequently, the dataset with n=40 was, then, entered into the developed algorithm and tested to determine the estimated parameters of beta and eta which would account for the ltrc effect. fig. 8 illustrates the obtained results and compares it to the traditional weibull analysis. since there is no information on the failures prior to the observable period, the truncation percentage was calculated by using time. the number of failures obtained during an eight-year observable period from 2007 to 2014 was used to estimate the numbers of failures missing over a five-year period. however, it should be noted that this truncation percentage is calculated on the assumption of a constant failure rate. to validate this assumption, a graphical cumulative failures versus time trend test was performed on the data for which the correlation coefficient (r2) was found to be 97%. this allows for reasonable justification of the assumption and calculation of the truncation percentage. the final values noted were 40% left truncation and 5% right censoring. the estimated values of beta and eta were found as 3.32 and 91,058 hours respectively under the de algorithm and modified nll as opposed to 4.13 and 95,747 hours under the traditional approach based on the normal nll equation not considering the truncation and censoring impact. since the percentage of truncation is 40% whilst the censoring impact is only 5% the increases in both beta and eta values are higher than the values obtained under the developed de with modified nll equation. this is similar to the demonstrated cases of truncation impact in the experimental study in section 4.1, where increases in both beta and eta values were noted with higher levels of truncation. fig. 8 pdf comparison plot of traditional weibull testing and the modified approach for a power generator 5. conclusions much of the maintenance databases are plagued with truncated, censored, or missing data, thus the accurate prediction is hampered leading to the poor maintenance decisions. reductions in the mses show that the parameter estimations are much closer to the true values when using the differential evolution (de) algorithm approach for comprehensive range of combinations of ltrc. results from experimentation with the individual effect of increasing percentages of truncation highlighted a general tendency to progressively overestimate the values of both β and η. in the case of censored data, while the β value is increased, the η value decreased with larger percentages of censoring. under the practical application, a difference of 0.81 was noted in the β parameter and 4,689 hours for η. both values were greater under the normal nll (traditional technique) as was illustrated in cases with larger values of truncation (40%) present in the data. both values advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 193 remained greater than 1 indicating the asset was in a state of reliability degradation. the algorithm has provided a simple and efficient way of correcting such issues. the use of the current approach however requires knowledge of the number of data points missing as illustrated in the practical application which may not always be available. the future work will target further improvement and refinement of the algorithm so that these data points can be estimated more accurately. acronyms mle maximum likelihood estimation de differential evolution nll negative log-likelihood ll log-likelihood mse mean squared error 2-p 2 parameters ltrc left truncated and right censored em expectation maximisation nr newton raphson mcs monte carlo simulation pdf probability density function ga genetic algorithms pso particle swarm optimisation sa simulated annealing cmms computer maintenance management system notations β beta parameter η eta parameter θ parameter vector for 2-p weibull distribution (β, η) n sample size of data points xi data point i from sample x vector of data points ν truncation indicator τ censoring indicator lx(θ) likelihood equation r2 correlation coefficient references [1] a. h. c. tsang, w. k. yeung, a. k. s. jardine, and b. p. k. leung, “data management for cbm optimization,” journal of quality in maintenance engineering, vol. 12, no. 1, pp. 37-51, 2006. [2] y. hong, “reliability prediction based on complicated data and dynamic data,” ph.d. dissertation, iowa state univ., iowa, 2009. [3] a. carrión, h. solano, m. l. gamiz, and a. debón, “evaluation of the reliability of a water supply network from rightcensored and left-truncated break data,” water resources management, vol. 24, no. 12, pp. 2917-2935, september 2010. [4] m. lopez, m. elisa, r. cao, and i. v. keilegom, “smoothed empirical likelihood confidence intervals for the relative distribution with left‐truncated and right‐censored data,” canadian journal of statistics, vol. 38, no. 3, pp. 453-473, august 2010. [5] n. balakrishnan and d. mitra, “likelihood inference based on left truncated and right censored data from a gamma distribution,” ieee transactions on reliability, ieee press, july 2013, pp. 679-688. [6] b. bhattacharya, d. l. shrestha, and d. p. solomatine, “neural networks in reconstructing missing wave data in sedimentation modelling,” in proc. 30th congress of international association of hydraulic engineering and research (iahr), ieee press, august 2003, pp. 209-216. [7] n. balakrishnan and d. mitra, “some further issues concerning likelihood inference for left truncated and right censored lognormal data,” communications in statistics-simulation and computation, vol. 43, no. 2, pp. 400-416, may 2013. [8] g. d. maringer, portfolio management & heuristic optimization, 2nd ed. new york: springer us, 2006. [9] t. emura and s. k. shiu, “estimation and model selection for left-truncated and right-censored lifetime data with application to electric power transformers analysis,” communications in statistics-simulation and computation, ieee press, march 2016, pp. 3171-3189. [10] j. liu, “analyzing left-truncated right-censored data with uncertain onset time with parametric models,” ph.d. dissertation, the university of texas school of public health, 2012. advances in technology innovation, vol. 3, no. 4, 2018, pp. 185 194 copyright © taeti 194 [11] d. mitra, “likelihood inference for left truncated and right censored lifetime data,” ph.d. dissertation, mc master univ., 2013. [12] x. l. dong, s. q. liu, t. tao, s. p. li, and k. l. xin, “a comparative study of differential evolution and genetic algorithms for optimizing the design of water distribution systems,” journal of zhejiang university science a, vol. 13, no. 9, pp. 674-686, september 2012. [13] r. storn and k. price, “differential evolution-a simple and efficient heuristic for global optimization over continuous spaces,” journal of global optimization 11, vol. 11, no. 4, pp. 341-359, december 1997. [14] j. tvrdik, “competitive differential evolution and genetic algorithm in ga-ds toolbox,” technical computing prague, humusoft press, 2006, pp. 99-106. [15] d. karaboga and s. ö kdem, “a simple and global optimization algorithm for engineering problems: differential evolution algorithm,” turkish journal of electrical engineering & computer sciences, january 2004, pp. 53-60. [16] d. swagatam, s. s. mullick, and p. n. suganthan, “recent advances in differential evolution-an updated survey,” swarm and evolutionary computation, vol. 27, pp. 1-30, april 2016. [17] w. ling and f. huang, “parameter analysis based on stochastic model for differential evolution algorithm,” applied mathematics and computation, vol. 217, no. 7, pp. 3263-3273, december 2010. [18] f. s. lobato, v. steffen jr, and s. n. j. antônio, “a comparative study of the application of differential evolution and simulated annealing in radiative transfer problems,” journal of the brazilian society of mechanical sciences and engineering, vol. 32, pp. 518-526, december 2010. [19] f. w. scholz, “maximum likelihood estimation,” encyclopedia of statistical sciences, john wiley and sons, inc., 1985. [20] r. b. abernethy, the new weibull handbook, 2nd ed. texas: barringer & associates, 2006.  advances in technology innovation, vol. 2, no. 2, 2017, pp. 40 45 40 position control and novel application of scara robot with vision system hsiang-chen hsu1,2,*, li-ming chu3, zong-kun wang2 and shu-chi tsao2 1 department of industrial management, i-shou university, kaohsiung, taiwan. 2 department of mechanical and automation engineering, i-shou university, kaohsiung, taiwan. 3 department of mechanical engineering, southern taiwan university of science and technology, tainan, taiwan. received 02 february 2016; received in revised form 27 april 2016 accepted 02 may 2016 abstract in this paper, a scara robot arm with vision system has been developed to improve the accuracy of pick-and-place the surface mount device (smd) on pcb during surface mount process. position of the scara robot can be controlled by using coordinate autocompensation technique. robotic movement and position control are auto-calculated based on forward and inverse kinemat ics with enhanced the intelligent image vision system. the determined x-y position and rotation angle can then be applied to the desired pick & p lace location for the scara robot. a series of experiments has been conducted to improve the accuracy of pick-and-place smds on pcb. keywords : scara, pick-and-place, forward and inverse kinematics, vision system 1. introduction industrial heavy duty manipulator such as selective compliance assembly robot arm (scara) is an automatic device which is capable to carry and move components /devices/ parts in the manufacturing process. the first scara robot was invented by professor hiroshi makino from university o f yamanashi, japan in 1978 [1]. fig.1 demonstrates the basic structure includes kinetic 4-axis and 4-dof, translation on x, y, z and rotation about vertical z-axis. two-link compliant arms with rotated wrist behave somewhat like the human arm that joints allow the arm to move vertically and horizontally in a limited space. scara was specially designed for precision devices fig. 1 the first scara robot by hiroshi makino [1] assembly, especially place a pinned component in a hole. a typical scara robot is a stationary robot arm including base, elbow, vertical extension and tool roll and comprising both rotary and prismat ic joints. scara robots may vary in size and shape but they all are consistent in a unique 4-axis motion [2]. w ith this distinguished feature, scara particularly fits the pick-and-place surface mount devices on pcb (printing circuit board) and move-to-take delicate silicon wafers or glass panels on magazine. scara robot was introduced in seiko watch assembling lines in 1981 and since then industrial scara robot has been widely used in electronic, semiconductor, automobile, electronic, plastic, food and pharmaceutical factories [3] all over the world. scara robot is the principle use of robotics field and most of the domain of robotics field is on industry and academia. the control system of industrial scara robot is a highly non-linear, * corresponding author, email: hchsu@isu.edu.tw advances in technology innovation, vol. 2, no. 2, 2017, pp. 40 45 41 copyright © taeti strong coupling and time-vary ing systems [4]. kinemat ics modeling is one of the key technologies to verify the model. many researchers and engineers [5-6] have presented the manipulating ability of robotic mechanis ms in pos itioning and orienting end-effectors and propose a measure of manipulability. the motion trajectory of a robot arm is calcu lated using the geometric analysis. the pid control techniques [7] have been proposed to solve the nonlinearity issue with acceptable results to control the movement of robot arms. the motion trajectory of a robot arms is calcu lated using the geometric analysis with matlab software. the performance of industrial heavy duty robots working in unstructured environments can be improved using visual perception and learning techniques [7-10]. the object recognition is accomplished using an artificial neural network (ann) arch itecture. a novel technique used in the assembly lines integrates computer vision to capture the shape of the objects, online grasp determination based on that shape, and image-based control for grasp execution. visual servoing system [8] consists of high-speed image processing, kinematics, dynamics, control theory, and real-time computing to control the position and orientation of a robot with respect to an object. furthermore, the color of objects could also be considered and included in the image-base system. the developed image processing and workpiece recognition algorithm is based on labview vision development module [9]. later, like two eyes on human, two cameras are developed to detect the robotic arm movement in 3-d space. in this system, the robotic arm is controlled and moved, and after mathematic calcu lations the precise position of the motors is calculated to reach the designated position [10]. the automation in surface mount precision assembly lines often consists of scara robots equipped with grippers, image v ision system and linked by motorized conveyances. in this system, the combination of high performance motion control with integrated vision guidance and conveyor tracking are demonstrated. the robotic arms are used for the pick-and-place of the smt components. the placement system on printed circuit board (pcb) is mainly influenced by the surface mount device (smd) robots and the production environment in assembly line. temperature on the reflow process is often above 250 o c which easily distorts the tray. the deformed tray would result in misalignment of the placement system. the yield rate is consequently descended and the cost would be enormous. the purpose of this paper is to improve the accuracy of the placement system on pcb during surface mount process . coordinate auto-compensation technique on deformed t ray is developed to control the position of scara robots equipped with image vision system. robotic movement and position control are calculated based on forward and inverse kinematics . 2. theoretical development fig. 2 illustrates the coordinate system of random point located on pcb (x, y) with respect to robotic arm. fig. 2 random point (x, y) on pcb 2.1. forward kinematics location of end effector can be determined by the length of robotic arm and rotation angle of each axis 𝑋 = 𝐿1𝑐𝑜𝑠𝜃1 + 𝐿2𝑐𝑜𝑠(𝜃1 + 𝜃2 ) (1) 𝑌 = 𝐿1𝑠𝑖𝑛𝜃1 + 𝐿2𝑠𝑖𝑛(𝜃1 + 𝜃2 ) (2) where l1, l2 are robotic arm length, and 1, 2 are rotation angle of each axis advances in technology innovation, vol. 2, no. 2, 2017, pp. 40 45 42 copyright © taeti 2.2. inverse kinematics rotation angle of each axis can be determined by the coordinate system of end point . 2 2 2 2 1 1 2 2 1 2 cos 2 x y l l l l       (3)     1 2 21 1 1 2 2   tan tan l siny x l l cos                       (4) 2.3. compensation for image and distance coordinate fig. 3 demonstrates the captured image of pixel with respect to distance (1 pixel equals to 0.01 mm). the origin o f d istance coordinate is located in the center of image coordinate and then pixel (320, 240) would be the same as distance (3.2mm, 2.4mm). fig. 3 image/distance coordinate system 2.4. compensation for deformed pcb tray coordinate fig. 4 presents the compensation for deformed pcb tray coordinate. assuming the pcb tray offset 1 mm due to thermal induced warpage, the coordinate of random point in image capture system is determined. 𝑋2 = 𝑃𝐶𝐵 𝑋 + 𝑃𝑖𝑥𝑒𝑙 𝑋 (5) 𝑌2 = 𝑃𝐶𝐵 𝑌 + 𝑃𝑖𝑥𝑒𝑙 𝑌 (6) where x1=28.2, y1=52.4 are system default parameters. after mathemat ical calculation, the placement coordinates are 𝑋 = 𝑋2 − 𝑋1 (7) 𝑌 = 𝑌2 − 𝑌1 (8) fig. 4 schematic illustration of pcb coordinate system 2.5. image processing grayscale dig ital image is a range of shades of gray without apparent color. the reason for differentiating gray images is that only specify a single intensity value for each pixel, i.e. less informat ion for each pixel. in order to reduce the complexity of post-processing grayscale image scheme is applied to capture the characteristic image. the hough transform is a technique which can be used to isolate features of a particular shape, such as line, circle, ellipse, etc., within an image. based on hough transform, circular detection on labview vision assistant is applied to determine the p recise position on deformed pcb. 3. structure of improved placement system 3.1. hardware description a toshiba scara robot (#sr-424shp) with control card (#piso-ps400) shown in fig.5 is employed in this study. fig. 6 illustrates smd components placed on pcb with tray (carrier). the placement system on trial run conveyer is presented in fig. 7. advances in technology innovation, vol. 2, no. 2, 2017, pp. 40 45 43 copyright © taeti fig. 5 toshiba scara robot (#sr-424shp) fig. 6 smd components on pcb with tray (carrier) fig. 7 placement system on trial run conveyor the overall placement system also consists of trial run conveyor for pcb tray, smd co mponents feeder, buzzer, 3 cylinders (baffle, push and charge-in). 2 cameras (coordinate auto-compensation and poka-yoke), 3 sensors with arduino uno and a lighting system (top and broadside). all smd components are held in specific trays which are loaded in upstream vibratory parts feeding stations. 3.2. software development the control software used in this study is labview 2012 and labview vision assistant 2012. 4. results and discussion coordinate compensation system for smd placement and starved feeding (queliao) auto-detection system have been developed in this paper. in the first, anchor point on pcb was shot by camera and the offset amount on pcb was then calculated by compensation of the image and distance coordinate. the precise location on pcb for components placement was then determined. for queliao and those parts did not place in the desired position, the developed system can also sound a buzzer signal on the control annunciator panel and warn the upstream feeding stations to load smd components. fig. 8 flow chart of coordinate compensation system for smd placement fig. 8 and fig. 9 present the flow chart for coordinate compensation system and queliao auto-detection system, respectively. fig. 10 demonstrates the accuracy of smd components pick-and-place improved by the developed algorithm. the accuracy on auto assembly (99.73%) has been dramatically improved after teaching mode (78.66%). start capture smd image grayscale digital image hough transform calculation pixel position for point (x, y) stop advances in technology innovation, vol. 2, no. 2, 2017, pp. 40 45 44 copyright © taeti fig. 9 flow chart of queliao auto-detectionsystem fig. 10 accuracy of smd components pick-and-place 5. conclusions in this paper, an improved pick-and-place smd on pcb system has been accomplished by using scara robot and machine v ision. the result has shown that 97.33% yield rate was achieved and more than 2% of erro r could be eliminated by improving the hardware of system. besides top lighting camera, anchor point on the skewed pcb tray can be calibrated and revised by a broadside webcam. remote operation using wireless network is feasible. acknowledgement the authors would like to express their appreciation to ministry of science and technology, taiwan, roc, for financial supports under project no. most103-2221-e-214-018 and most104-2221-e-214-051. appreciation is also extended to oriental semiconductor electronic, ltd. for carrying out all the experiments. references [1] scara, the robot hall of fame, power by carnegie mellon, http://www.robothalloffame.org/inductees/ 06inductees/scara.html [2] a. burisch, j. wrege, a. raatz, j. hesselbach, and r. degen, “parvus – miniaturised robot for improved flexibility in micro production,” assembly automation, vol. 27, no. 1, 1980. [3] s. k. dwivedy and p. eberhard, “dynamic analysis of flexible manipulators, a literature review,” journal of mechanism and machine theory, vol. 41, no. 7, pp. 749-777, 2006. [4] a. visioli and g. legnani, “on the trajectory tracking control of industrial scara robot manipulators,” ieee transactions on industrial electronics, vol. 49, no. 1, pp. 224-232, 2002. [5] g. s. huang, c. k. tung, h. c. lin, and s. h. hsiao, “inverse kinematics analysis trajectory planning for a robot arm,” proceedings of 8th asian control conference (ascc 2011), kaohsiung, taiwan, pp. 965-970, may 2011. [6] j. fang and w. li, “four degrees of freedom scara robot kinematics modelling and simulation analysis,” international journal of computer, consumer and control, vol. 2, no. 4, pp. 20-27, 2013. [7] f. escobar, s. díaz, c. gutiérrez, y. ledeneva, c. hernández, d. rodríguez, and r. lemus, “simulation of control of a scara robot actuated by pneumatic artificial muscles using rnapm,” journal of applied research and technology, vol. 12, no. 5, pp. 939-946, 2014. [8] s. h. han, w. h. see, j. lee, m. h. lee , and h. hashimoto, “image-based visual servoing control of a scara type dual-arm robot,” ieee international symposium on industrial electronics, cholula, puebla, mexico, vol. 2, pp. 517-522, dec. 2000. [9] h. zhu, j. xu, d. he, k. xing, and z. chen, “design and implementation of the moving workpiece sorting system based on labview,” 26th chinese control and decision conference start image captured image mask advanced morphology stop part analysis http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=21159 advances in technology innovation, vol. 2, no. 2, 2017, pp. 40 45 45 copyright © taeti (2014 ccdc), changsha, china, pp. 5034-5038, may 2014. [10] r. szabo and a. gontean, “robotic arm control with stereo vision made in labwind ows/cvi,” 38th international conference on telecommunications and signal processing (tsp), prague, czech, pp. 1-5, july 2015.  advances in technology innovation, vol. 1, no. 2, 2016, pp. 33 37 33 copyright © taeti innovation management of stock trading system yi-ping lee* department of business administration national chung hsing university , taichung, taiwan. received 01 april 2016; received in revised form 08 may 2016; accepted 12 may 2016 abstract stock trading market fluctuated wild ly, which affect a country's economic and business operation. one of the important factor in stock trading system is price change limit, in the case of taiwan is 7 percent ups and downs per day. nowadays stock price change limit is set by the government, and that is based on the economic development of the country, but this price change limit is not the same with business’s view point. basically business is a private owned property, and the authority of business have to responsible for the performance of operation. release part control right of the price change limit to business by an innovation management way, which method allow companies decide 1 to 2 percent ups and downs price change limit, but this rate is still under the control of government. innovation stock trading system will activate the trading of stock market. keywords: innovation management, per day stock trading price change limit, business operation, business management. 1. introduction it is easy to achieve the goal of the national wild regulatory compliance of stock trade system, but the d isadvantage of this way is likely to ignore the changing factors of economic environment and mission of stock trading participants. there are too many d iversity in the stock trading participants, such as government focus on control and management, but business focus on the survive of competit ion, except this, there are different industry characteristics, size of firm, purpose of raising funds for each f irm, different way of enterprise in management of control enterprise and investors may have different goal of investment. for the better development of stock trade market, we need multip le stock change range controls to satisfy multiple stock trading conditions. the common reference of stock trading system is per day’s price change limit, the other is buy and sale a stock in the same day, most government will expand or shrink the price change limit rate to active or tighten the stock market trading volume, on the other hand, government will tighten the trading system by limit trad ing a stock in the same day, that is partial way of government’s control to the stock trading market. every country have its own different stock trading range limits, stock trading market may be a country's economic showcase, china’s stock change range usually keep as ten percent, but they tried a system named circu it breaker system(cbs) in recent years to stop the trade in stock market. traders of chinese stock trade with technical analysis, they will make a strategy decision by observe and analyze transactions before they choose to buy or sale stocks, (hui qu, xindan li, 2014). there is no daily stock trade range limit in the u.s. stock market, but in japan has taken level d istance formula for daily trade range. individual traders of stock market are still be the majority of investor of stock market, those investor’s values perception also affect the stock market trading patterns and frame, (jamdee sutthisit, shengxiong wu, bing yu, 2012). stock market will be affected by external events, and the stock daily change range limit (sdcrl) of stock also affect the manner and degree of reaction to those events (gregory j. kuserk, peter r. locke, 1996), utility of sdcrl in stock market is an stop point of event reaction in trading, with which to forbid event over reaction in a transaction day, this is investors point of view in stock trading, the price change range limit will fit the issue of risk preference in a stock market, investors of risk preference will make trading decision connect with the sdcrl, then the situation of a stock * corresponding author, email: yiping727@yahoo.com.tw advances in technology innovation, vol. 1, no. 2, 2016, pp. 33 37 34 copyright © taeti market will face the familiar group member in a short time, and that is an sudden impact to stock market, and this impact will low down the stability of stock trading, most governments and investors dislike this situation, especially in a down stage stock market. usually, sdcrl is a mandatory regulation of the government, but the rapid and p luralis m changes in the market are unpredictable and turmoil. there should have many different purposes in raise capital, business may raise capital for scale reason in expand market, some are raise capital for cut into overseas markets, the same point to most business are for continuing operations (guy, john, 1995). investors choose favor stock market and business to invest, thus, establish a stock trading system with sdcrl partial control by business will fit the multip le need of stock trading market, and which is consistence with government, business owner and investors. (eugene f. fama, james d. macbeth). profitability usually associated with investor’s reward and business growth (merton h. miller, myron s. scholes, 1982), business and investors plays an important role of the stock trading process, but the change in stock price limits have no room for them to express their opinion, if they can show what they want to frame a d iversified stock trad ing system, may them will have their idea, such as the high ranking manager can set his operation project into relevant thinking (guy, john, 1995). there are a lot of prior research focus on the range of sdcrl, some of them are remove of the sdcrl in stock trading, but we d id not find a research discuss about the sdcrl partial decide by the business, this research first pioneer made this claim for business owner have the right to claim his idea of sdcrl. which will create diversity and vibrant stock trade market. 2. different approach design-related factors of business partial controlled sdcrl operation step of sdcrl is pre file by the business first, and government will rev iew the application, if it is permitted, govern can send a set account and password, business have to public the informat ion the same time as the government before a setting period of time, after that, then can directly get into the account to change the sdcrl to what they want, and this change of sdcrl can’t be revise before due time, for the reason of it is a public information, any change should have prepare time for participants. if the pre file of sdcrl be rejected, which should have an explanation of for what reason, business have to follow and revise as the order of rejection, until it is permitted. if the business do not want to make any change of the sdcrl, this decision will be respect and kindly treated. the business’s sdcrl is licensed by the government, which is set for a period of time, and this could be one year or half year, it is up to the application and government’s permission, and the range of sdcrl could be 1 to 2 percent, in the case of taiwan sdcrl is 7 percent, which can be decided by business highest upward to 9 percent or lowest down to 5 percent, the adjustment of sdcrl is up to the business’s strategy and need of operation. 2.1. government’s point of views to sdcrl the responsibility of government is provide an efficient economic environment to business and investors, and that is good to the whole national economic participants, include the benefit of non-stock trading part ies, except that, this environment will let business easy in raise necessary fund to expend scale and investors have multip le choice in buy and sell trade in stock market. nowadays information engineering technology is fully developed, it is easy to set prior filing license in government stock exchange. the business can set a sdcrl as his will before a government allowed t ime and range, and that sdcrl will work as setting at due time. the advantage of designed new sdcrl to government are create an activate and multip le stock market, which let the business have more space to create commercial chances, sprit of economic freedom let business have space to thinking, creating and chances to win, if the government accept the idea of sdcrl, the cost most are to control computer setting, but the benefit of new sdcrl will created millions of chances. if a business did not set such a sdcrl at permitted time, that will be treat as the business advances in technology innovation, vol. 1, no. 2, 2016, pp. 33 37 35 copyright © taeti give up the right of business setting sdcrl, this business’ sdcrl will be the original value of government set sdcrl. business partial controlled sdcrl was authorized and allowed by the government, which is still under the controlled of the government, when stock market is upward, if trend of upward will hurt the national economic seriously, the government can withdraw granted the rights and order the business or direct amend the business set sdcrl, then the government can change it to an acceptable sdcrl in that period of time, until the economic recovered. 2.2. business’s point of views to sdcrl business was born to win benefit and avoid risk, and they will take best care of themselves, new sdcrl let the business have chance to do and choose risk avoidance, if business operate an expand strategy, he can choose highest range of sdcrl, or business can operate an traditional way by choose lowest range of sdcrl. if permitted, business will make some distance of adjustments of its sdcrl, the adjustment can show the business character and style in the stock trading market, this can be a kind of corporate governance, and the pre -filing adjustment is already pre filed to the government. the effect of business controlled sdcrl is when an upward stock market, the b iggest sdcrl will strengthen buy power, if the business want to expand the business scale, he can choose and strategy higher sdcrl, this sdcrl reflect the idea of business owner and his logical model, that is a kind of business operation strategy, which activate the business world, there are a lot business in the world, not only different in size, policy, but also in culture background and industry, we can mix all different factors to create an colorful business world. basically, business owned stock are open trade in the market, thus, the price of a stock should be some distance protect by the business, if the price is abnormally upward or downward for reasons very often, which will be a sign of under value or over value of the business stock, and the other condition is the opportunist try to control and gain benefit from this business stock, thus, business need to develop its trading strategy in keep an amount of stock and capital to buy and sale its stock, that is the trade strategy to that business. short term trading is a common phenomenon to a stock with extraord inary profit, but this kind of short term trad ing just like double edge sword, which company with both benefit and hurt, thus, business have some d istance of responsibility to protect shareholder from bubble crash. usually, stock price shot up for the announcement of dividends, business can make a strategy of dividends announcement to achieve the goal of raise capital, on the other hand, release of dividends will slow down the business’ growth. the advantage of new designed sdcrl to business is it can be used to persuade customers, stockholder and investors by diversities of strategy in sdcrl, if this strategy been testified and last for a long period of time, which will be treated as a reliab le sign by business related parties, after that, no matter loan to the bank or new international investment will be treat the same as reliable. 2.3. investors’ point of views to sdcrl the effect of new designed sdcrl in investors are in buy and sale decision, if in an upward stock market, new designed sdcrl will strength the power of buy action, and if in downward stock market, the biggest of sdcrl will strengthen the power of investor in sale action. if investors are risk preference, they will choose the business with high sdcrl, especially in an upward stock market, if investors are risk avoidance, they will choose a lower sdcrl, for the new designed sdcrl let business have chance to create investors’ need space in risk return. 3. discussion this research discuss the adjustment of sdcrl, which can distinguish the business's economic condition and demand, as an example, if both filing and audit system are set to a period of one year, then, near next year will be a new cycle for both business and government to rethink about the decision of setting sdcrl, if it is really good to the participants and government, why not set it be a longer t ime, the best point is this stock system testified by most business’s thinking. advances in technology innovation, vol. 1, no. 2, 2016, pp. 33 37 36 copyright © taeti 3.1. different mission of stock trading participants all upper factors are fulfilled depend on the condition of the country and companies, for both of these two group have different mission to exercise, and theses missions have big difference between them. business want to raise funds to invest in the industry and survive in the market competit ion, or business may declare dividends higher in a setting time to attract investors (merton h. miller, kevin rock, 1985), may that is a way of interaction between companies and investors, and these upper actions are focus on increase influence of business (merton h. miller, myron s. scholes, 1982). mission of government is based on whole national economic and regulation setting, this is not for a single industry or company, but different industry may be huge difference, such as bank want higher interest rate, but foreign trade industry is totally different, they need lower interest rate to strengthen the power of export ability, on the other hand, about the individual investors, they also have different preferences and needs on stock investment (eugene f. fama,1971), may some people tend to risk preference, except that, there still exist different way of measure risk to gain profit from stock market, thus, it is hard to have a qualitative rules or principles of sdcrl in stock trade market, which can include and cover all situation, one size of sdcrl for stock trade is a single standard of sdcrl, which is hard to fits so many different groups and cover there necessities. 3.2. innovation of sdcrl our innovated approach, allowing the original sdcrl in stock market be more lively, diverse thinking achieve simultaneous sound be organized in stock trad ing market by corporate governance, with which to active capital transactions purposes. if the business have a strong self-confidence, the business can choose the biggest sdcrl in stock trading market, or some business hope stable environment to grow, then he can choose a minimum sdcrl to reduce business fluctuations. the upper description is match the spirit of our idea, then business can choose a stable environment without too strong vibration to them in operation, (michael c. jensen, william h. meckling, 1976), lowest sdcrl will be best choice. on the other side, the government still can control the sdcrl from policy and economic way to satisfy what is necessary for the country, three win is the goal of this research. after the atlas of new designs is obtained, a detailed design can be carried out by selecting one from the atlas. 4. conclusions there are positive implication of analysis in new innovative stock trade system, which is good not only the national economic but also to business and individual investors. integration of all ideas to establish a new stock trading system, combine all opinions of all stock trade participants, it is possible to form a consensus and generate mutual trust of all parties to create biggest wealth, (cam caldwell, mark h. hansen (2010). 4.1. stock trading efficiency for the goal of improve the existing rig idities stock trad ing policy, especially in nowadays’ hard environment, investors need to face waves of stock trade decline, not only the government or investors are helpless, new method can improve some of the missing, we wish all part ies of the stock trading market are action in accordance with the wishes of themselves without prejudice to national economic interests, most important is the way to achieve effective of stock trading. further, the government still can increase or decrease the proportion of control in sdcrl when necessary. 4.2. government’s control right different stock have its best sdcrl in adjustments, in the case of financial stocks are large amount transaction in daily stock trade, we can set a smaller proportion of the amount sdcrl for them to adjust, one percent is better for huge enterprises in setting sdcrl, and perspective traditional industry would be better to have substantial authorizat ions, such as 1.5 percent of sdcrl. the government can always open or tighten the magnitude authorization. business can base on the economic environment to set timely favorable ad justment to create the advances in technology innovation, vol. 1, no. 2, 2016, pp. 33 37 37 copyright © taeti best living environment, namely with the method to achieve win -win situation to all trade member. 4.3. suggestion of sdcrl every business have its own way to measure performance (stephen j. brown, jero ld b. warner, 1980), consider about the business ’s need in raise fund and individual investor’s goal, except that, investors have it’s different goal, thus, we need a d iversify stock trade mechanism. from business’s point of view in governance have to consider about the best and least risk way to raise fund (robert s. hamada, 1971), firm have to win profit from the market, investors have different preference of his goal, combine three part ies necessary with suggested sdcrl stock trade system, include government regulation, business and individual investor’s goal, this article suggest a new stock trade system, the strength of the new system distinguished different trade member and it’s goal. th is paper suggested that the sdcrl principally decided by the government, but allow businesses adjust according to their own need. possible future research design for this issue may focus on the scope of empirical study of sdcrl t rading system.in this paper, the result has shown that the new designs can produce a more wide range sdcrl of non-uniform stock trading system motion than the existing stock trading system. references [1] c. caldwell and m. h. hansen, “trustwor thiness, governance, and wealth creation,” journal of business ethics, vol. 97, no. 2, pp. 173-188, 2010. [2] e. f. fama, “the behavior of stock-market prices,” the journal of business, vol. 38, no. 1, pp. 34-105, 1965. [3] e. f. fama, “risk, return, and equilibrium,” journal of political economy, vol. 79, no. 1, pp. 30-55, 1971. [4] e. f. fama and j. d. macbeth, “risk, return, and equilibrium: empirical tests,” the journal of political economy, vol. 81, no. 3, pp. 607-636, 1973. [5] g. j. kuserk and p. r. locke, “market making with price limits,” the journal of future market, vol. 16, no. 6, pp. 677-696, 1996. [6] j. guy, “making: the role of governance,” journal of financial planning, vol. 8, no. 1, pp. 34, 1995. [7] h. m. markowitz, “foundations of portfolio theory,” the journal of finance, vol. 46, no. 2, pp. 469-477, 1991. [8] h. qu and x. li, “building technical trading system with genetic programming: a new method to test the efficiency of chinese stock markets,” computational economics , vol. 43, pp. 301-311, 2014. [9] j. sutthisit, s. wu, and b. yu , “positive feedback trading in chinese stock markets: empirical evidence from shanghai, shenzhen, and hong kong stock exchanges,” journal of financial and economic pract ice, vol. 12, no. 1, pp. 34-57, 2012. [10] m. e. cekirdekci, and v. iliev, “trad ing system development: trad ing the opening range breakouts,” degree of bachelor of science, worcester polytechnic institute (wpi), 2010.  advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 a comparison of automotive waste heat recovery systems madhusudan raghavan 1,*, yong sheng he 2 1general motors r&d center, pontiac, mi 48340, usa 2general motors global propulsion systems, milford, mi 48380, usa received 05 june 2017; received in revised form 09 december 2017; accepted 05 january 2018 abstract the purpose of this research study is to assess schemes for recovering energy that is lost via an automobile’s exhaust. three systems for waste heat recovery, viz., (1) electric turbo-compounding, (2) organic rankine cycles, and (3) thermoelectrics are studied. this involves detailed computer simulations of the waste heat recovery systems, integrated within a vehicle propulsion system operating over certification driving cycles. the simulations suggest that fuel economy improvements of 3-5% could be achieved by converting waste heat into useful work. keywords: waste heat recovery systems, turbo-compounding, organic rankine cycle, thermoelectrics 1. introduction fig. 1 transportation sector energy use (mmbtu, million btus) per capita the international energy outlook [1] offers the following forecasts regarding population growth and energy consumption in the future. global population grows 28% from 6.9 billion in 2010 to 8.8 billion in 2040. population remains concentrated in asia and africa. their shares of the global population are 70% in 2010 and 72% in 2040. most other regions continue to grow through 2040. projected gdp rises by an average of 3.6% per year globally from 2010 to 2040, ranging from a high of 5.7% for china to a low of 0.7% for the middle east. total world marketed energy will grow by 56% from 2010 to 2040, from 524 quads to 820 quads (quad = quadrillion btu) with transportation sector projected usage shown in fig. 1. against this backdrop of increasing population, energy consumption, urbanization, congestion and pollution, we are looking at ways to improve vehicle fuel economy by minimizing automotive engine fuel consumption. in raghavan [2], we explored * corresponding author. e-mail address: madhu.raghavan@gm.com tel.: +1 248 930 5248 advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 196 mechanical hybrid solutions to improving propulsion system efficiency. in the present work we have explored three thermal schemes for automotive waste heat recovery (a) electric turbo-compounding, (b) organic rankine cycles, and (c) thermoelectrics, in the context of vehicle simulations on certification drive cycles. the difference between this work and prior studies is that in each case we have sized the respective system for vehicle implementation and we evaluate the efficacy of each system over the various certification drive cycles with numerous transients, as opposed to running each system at its best steady-state operating point. our modeling tools are sufficiently detailed that we are able to base our architecture decisions on the simulation outcomes. we present the results of these studies and offer a comparative assessment of these 3 systems. 2. electric turbo-compounding electric-assisted turbocharging systems were developed previously for diesel engines as described in hopmann et al., [3], millo et al., [4], and balis et al., [5]. this kind of system consists of an electric machine integrated into the turbocharger shaft. the electric machine can work as a motor to improve transient response or work as a generator to recover energy. a turbo-compounding system with an extra downstream turbo-generator to recover waste energy was designed for diesel engines, see vuk [6]. different types of electric turbo-compounding systems (etc) were compared for turbocharged gasoline energy exhaust heat recovery as discussed by wei et al., [7]. the system that we investigated is shown in fig. 2. in order to increase the flexibility of the exhaust energy recovery and minimize the energy loss, the turbo-generator may be driven by a variable nozzle turbine (vnt). fig. 2 etc system with vnt at engine low load or high speed operating conditions, the throttle would be partly or fully closed to transfer the exhaust energy to the turbo-generator. at engine low speed and high load operating conditions, the vnt nozzle would be partly or fully closed to ensure enough exhaust energy flows through the turbocharger turbine. the performance of the etc system was studied on a 1.8-liter in-line four-cylinder turbocharged and intercooled four-stroke gasoline engine (compression ratio of 9:1, rated power of 125 kw at 5500 rpm and maximum torque of 235 nm at 2000~4000 rpm). the turbine of the turbo-generator was designed to meet the engine full-load power requirement, and the turbine geometry was optimized for better engine part-load efficiency, as discussed in zhuge et al., [8]. the optimized turbo-generator turbine parameters are as follows: inlet tip radius 23.5 mm, inlet hub radius 23.5 mm, inlet blade height 4.0 mm, inlet blade angle 0°, exit tip radius 19 mm, exit hub radius 7 mm, exit blade angle 70°, number of blades 12, volute radius 40.5 mm, volute area 245 mm2. the gasoline engine was modelled using the engine 1d simulation software tool, gt-power, including gas exchange, fuel combustion, heat transfer, and waste energy recovery by both the turbocharger for intake compression and the turbo-generator for electric power generation. the compressors and turbines were modeled with turbo through-flow models based on compressor two-zone models and the turbine mean-line flow models, instead of using compressor and turbine performance maps. this model-based method allowed engine system optimization by adjusting the design parameters of the compressor and advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 197 turbine. this was critical to achieve the optimal performance of the etc system. a vehicle model of a typical passenger car was used to evaluate the etc system performance under us06 and ftp75 drive cycles in gt-drive. parameters of the vehicle were as follows: vehicle mass 3150 lb, vehicle frontal area 1.997 m2, vehicle drag coefficient 0.348, final drive gear ratio 3.55, final drive efficiency 0.97, tire rolling radius 289.7 mm, tire rolling resistance factor 0.0122. table 1 shows our key simulation results. the mechanical power output from the engine and the electric power output from the turbo-generator were both considered in evaluating the overall fuel efficiency of the engine with the etc system. fig. 3 shows electric power generated by the turbo-generator during the us06 driving cycle. the key takeaway from this exercise was that a turbo-compounding system sized for a mid-sized vehicle offered a 1.6% fuel economy improvement for the ftp75 city cycle, no improvement on the highway cycle and a 4.48% improvement on the us06 cycle. these fuel economy improvements were computed by placing the turbo-generator output on the 12v electrical bus so that this recovered energy could either be stored in a 12v (li-ion) battery or directly offset the electrical accessory loads by reducing the electrical generator load. table 1 drive cycle results for turbo-generator certification cycles us06 ftp75 average engine power output (kw) 15.1 4.76 average electric power output (kw) 1.05 0.297 improvement of fuel efficiency (%) 4.48 1.61 fig. 3 electric power generation [watts] on us06 3. organic rankine cycles a simplified schematic of a rankine cycle power generator is shown in fig. 4. for a vehicle application, the available heat energy from the hot exhaust gas of an internal combustion engine ( inq ) could be utilized to vaporize the working fluid to drive a turbine for power generation. the organic rankine cycle (orc) uses an organic compound as the working fluid. this class of fluid, typically a refrigerant, requires much less input energy to boil and is thus potentially better suited to applications where the quality of the waste heat is variable, as in an automotive application. it also freezes at a much lower temperature, which is another advantage. kadota et al., [9], used engine coolant and exhaust heat along with a water-based rankine system incoporating an axial piston expander with a motor/generator. they claimed a system efficiency of 13%. ringler et al., [10], also used coolant and exhaust heat with a vane expander. the working fluid was water and ethanol and they claimed a 16% system efficiency. teng et al., [11], used the egr heat and exhaust heat as the heat source. their working fluid was ethanol and they used a turbine for expansion. they claimed an estimated efficiency of 14%. briggs et al., [12], used exhaust heat as the heat source on a r245a based system that operated in the supercritical region with an efficiency of 13.7%. advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 198 fig. 4 rankine cycle schematic under steady-state operating conditions, a rankine cycle waste heat recovery (whr) system can achieve relatively high efficiency levels. given a fixed temperature differential and sufficient system warm-up time, the efficiency levels quoted are the highest that can be achieved. however, it is unlikely such levels are possible under transient vehicle operating conditions and typical usage profiles for light-duty vehicles. to obtain a more realistic assessment of in-vehicle operating efficiency, a dynamic model of the organic rankine cycle system was investigated at gm r&d using the amesim software environment. the model is shown schematically in fig. 5. the rankine system has 6 main components: an evaporator (or boiler), a turbine expander with a bypass, a condenser, a receiver and pump. the receiver is also commonly referred to as a surge tank. fig. 5 amesim organic rankine cycle model the amesim model is a full two-phase flow transient model that allows analysis of component sizing, refrigerant charge determination, and component behavior including heat exchanger (hex) effectiveness as a function of temperature, and heat exchanger wall and fluid temperatures. an example of the model output is shown in fig. 6, which represents system operation on the us06 cycle. the expander and condenser power are shown as negative values while the evaporator and pump power are positive. the expander peak power reaches 2 kw based on a heat input into the evaporator of approximately 15 kw. the heat advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 199 input to the evaporator is extracted from the engine exhaust gas and transferred to the rankine cycle working fluid via a gas-liquid heat exchanger. we decided not to use the heat from the engine coolant to keep the mechanical circuitry simple. the intermittent nature and variability of the on-cycle exhaust gas heat is evident from the evaporator power input. fig. 6 modeled dynamic orc whr operation power fig. 7 location of orc system on vehicle fig. 8 exhaust gas heat loss schematic using actual vehicle experimental data, an exhaust gas model was implemented and tuned to provide a reasonable estimate for the exhaust gas temperature. the vehicle data was obtained from a buick lacrosse equipped with belt alternator starter (bas) mild hybrid system. fig. 7 shows the locations in the vehicle of the catalyst-out (red dot) and resonator-in (blue dot) temperatures used to tune the exhaust model. the location of the whr system evaporator is assumed to be downstream of the catalytic converter and resonator, in the approximate location of the blue dot. we anticipate the evaporator heat exchanger to be about the size of a shoe-box. advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 200 the exhaust temperature model is based on the simple heat loss model shown in fig. 8. the exhaust gas loses heat to the exhaust pipe, which in turn loses heat to the environment. inputs are the exhaust flow rate and the fraction of the exhaust power reaching the whr system. taking a control volume around a section of pipe, the heat transfer is approximated by the equation: ( )p gas exhaust pipe pipe gas pipemc t q h a t t    (1) where m is the exhaust gas mass flow, cp is the exhaust gas specific heat, exhaust q is the exhaust gas heat power and hpipe is the convection coefficient for heat transfer between the gas and the pipe wall. there are two temperature states, the exhaust gas temperature tgas and the pipe wall temperature tpipe. the exhaust mass flow is estimated from the air fuel ratio and fuel rate reported by the engine subsystem from the vehicle model. using estimates of the heat power into the exhaust system derived from the test data, different exhaust temperature model tunings were developed for the city, highway and us06 cycles to match the test data trends of the catalyst-out temperature as much as possible. our choice of powertrains was influenced by the question of how best to utilize the power generated by a whr system. the power is generated mechanically but delivering it directly to a drive shaft introduces some complications which require redesign of the driveline components. converting the whr system’s mechanical output to electricity is more easily accomplished in principle (e.g. via a generator), and this energy may be readily used on the electrical system of a mild hybrid vehicle. the vehicle model that we used, had an 8kw evaporator, an 85% efficient isentropic expander, r600a as the working fluid and an 89% electric generator to convert expander shaft power into electricity on a 4000-lb test weight class (twc) suv vehicle. the whr system added 35 kg to the mass of the vehicle and this was accounted for in our modeling, as was the thermal inertia of the system. additionally the condenser was treated as integrated with the radiator in the vehicle, so no additional cooling capacity was added to support whr system operation. table 2 drive cycle results for orc whr certification cycles ftp city ftp highway us06 average evaporator temperature (oc ) 157.8 178.0 175.5 average exhaust gas temperature (oc ) 394.0 453.9 542.2 fuel economy improvement (%) 2.7 5.1 4.6 the resulting whr system efficiencies and fuel economy improvement over the baseline mild hybrid model are shown in table 2. since the operation of the whr system actually hinders engine warm up during cold start, a by-pass valve was used to avoid the whr system during start up. the integrated whr/vehicle model provides a more realistic assessment of the on-cycle fuel economy benefits of an orc whr system. in the mild-hybrid vehicle, the engine is on as long as the vehicle is in motion, providing longer engine-on time. the engine is also running at lower cycle average efficiencies, leading to more waste heat and higher exhaust temperatures. with higher exhaust temperatures, the average evaporator temperature increases, leading to higher carnot and actual system efficiency. the study also showed that the large estimated steady state efficiencies are difficult to achieve if the vehicle operation is highly transient. higher efficiencies may be obtainable in off-cycle conditions like long-distance steady-state high-speed cruising. 4. thermoelectrics a thermoelectric converter (tec) is shown schematically in fig. 9. the tec is constructed of p-type and n-type semiconductor thermoelectric (te) materials connected electrically in series and thermally in parallel via hot and cold junctions. the operating principle is the seebeck effect by which a temperature differential between the hot and cold junction causes current to flow across an electrical load connected, generally for convenience, to the cold junctions. the current flow advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 201 results from the voltage potential difference across the te material induced by the temperature differential. the teg is a collection of tecs plus the heat exchangers and other power electronics required to make a working whr system. there have been numerous prior studies on waste heat recovery systems based on thermoelectric generators (tegs) for potential automotive applications. see for example, hussain et al., [13], lagrandeur et al., [14], and stobart et al., [15]. at gm r&d, we explored the use of teg electrical power derived from waste heat to try and achieve a 5% fuel economy gain on the us06 drive cycle. the amount of electrical power required suggested that a vehicle with some degree of powertrain electrification would be required to use the power generated to displace fuel. the 5% fuel economy improvement target required that the cycle average power output from the teg be 1.6 kw. as a potential target application we selected a mild hybridized full-size truck (fst), as the large engine offers good opportunities for waste heat harvesting. fig. 9 thermoelectric converter schematic in this study, a simulink vehicle model was used to simulate the behaviour of an integrated teg whr system to evaluate fuel economy improvement, in the presence of transient effects, such as unsteady heat input, system warm-up, and thermal inertia. for the hybrid vehicle, the power bus distributes power between electrical subsystems such as the high voltage energy storage system and other components on the bus, such as a teg. the teg model is connected to the vehicle power bus similar to other components such as the power steering, the cooling fan, the vacuum pump, the air-conditioner, and the dc/dc converter. the vehicle model provides instantaneous exhaust power, coolant temperature, and fuel flow rate to the teg model subsystems. the fuel flow rate is used to estimate the exhaust mass flow using the approximation that the mass flow rate is proportional to the air/fuel ratio (afr). the exhaust mass flow and the exhaust power are inputs to the exhaust gas temperature estimation model. the teg physics are modelled in the lumped-parameter teg subsystem model, which receives exhaust gas temperature at the teg inlet, the exhaust mass flow, and the coolant temperature as inputs. it outputs electrical power, which is optionally scaled by an efficiency factor (value of 0.9) to reflect losses in the electrical power transfer to the bus. the details of the above model are as follows. given an average teg power output requirement of 1.6 kw for the mild hybrid truck, and a 10% conversion efficiency teg , the average teg heat power input required is 16.5kw, from the following equation. teg outteg integ p p   (2) the teg system efficiency, teg , is a function of the tec module efficiency, the heat exchanger effectiveness and any power conditioning (pc) efficiencies: hextecpcteg   (3) advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 202 the tec efficiency is calculated from the following equation, where ht is the hot junction temperature, ct is the cold junction temperature and the mean temperature t = 0.5*( ht + ct ). 1 1 ( )( ) 1 h c tec c h h t tzt t t zt t       (4) in the above, zt is the dimensionless thermoelectric figure of merit based on the intrinsic properties of the te materials. assuming a drive cycle average tc of 100 deg c and th of 400 deg c, a representative zt is approximately 0.9 for the te material being developed for gm r&d. thus, tec = 0.1743. assuming average power conditioning efficiency ( pc ) of 95% (dc/dc converters) and heat exchanger effectiveness of 0.6 (i.e., hex = 60%), the overall teg efficiency, teg , is 9.9% which has been rounded to 10%. thus, for the fst, the average teg input power required is 16.5 kw, assuming a 10% teg level conversion efficiency. the average engine exhaust heat power is approximately 27 kw, assuming 30% of the fuel energy is dissipated as exhaust heat. the teg model is designed to capture spatial temperature distribution effects in the teg. a tec array is represented by a single thermal capacitance node representing the hot sink for the array, again using the electrical analog for the heat transfer model, shown in fig. 10. heat transfer from the exhaust gas heat exchanger to the hot sink is represented by a thermal resistance r_ex_hs. the heat transfer into the tec and out to the coolant is represented by r_hs_cool + rte. since each array is thermally connected to adjacent arrays, the heat transfer between adjacent arrays, j, and k, is modeled by thermal resistance r_hs_jtok. the temperature at the hot sink, t_hs_j, is determined by the state equation (eq. (5)). the resistance data is given in table 3. ( _ _ _ _ ) ( _ _ _ _ ) ( _ _ _ _ ) ( _ _ _ _ ) _ _ _ _ _ _ _ _ dq t ex j t hs j t hs i t hs j t hs j t hs k t hs j t cool j dt r ex hs r hs jtok r hs jtok r hs cool         (5a) dt jhsdt hsmc dt dq p __ *__ (5b) where cp_m_hs is the specific heat of the tec material. fig. 10 resistor diagram model for tec table 3 tec heat transfer model electric analog parameters thermal resistance parameter value hsexr __ 0.04123 k/w ter 0.25 k/w coolhsr __ 0.0041 k/w jtokhsr __ 0.047 k/w advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 203 hsmcp __ 1021 j/k fig. 11 teg2 schematic of physical arrangement the teg is made up of 7 arrays as shown in fig. 11. the power output section incorporates experimental data from the skutterudite material made on the kg scale for the gm r&d project. curve fits for these data produced the following equations for the seebeck coefficient and resistivity: n-type material 77210 5601.33690.53437.3)(   etetetn (6a) 78212 2490.76386.19721.6)(re   etetetln p-type material 57210 2320.31472.64724.4)(   etetetp (6b) 68211 4659.22302.23142.1)(re   etetetlp the tecs’ open circuit voltage is defined by eq. (7),   ht ct n ht ct poc dttndttnv )()(  (7) where n is the number of te leg pairs in series, np, is the temperature dependence of the seebeck coefficient, and tc and th are the cold and hot junction temperatures, respectively, such that th tc = junct . the total electrical resistance of the te module is calculated from eq. (8),             2 )(re)(re 2 )(re)(re mod cnhncphp tltltltl a nl r (8) where l is the te module leg length and a is the leg’s cross sectional area. for the simulation, n = 32, l = 0.004m and a = 0.000016m2. in order to calculate voc, we integrate  tp and  tn from eqs. (6a) and (6b): ht ct ht ct oc tet e t e tet e t e v                       72 7 3 10 52 7 3 10 5601.3 2 3690.5 3 3437.3 2320.3 2 1472.6 3 4724.4 (9 ) the total power per tec array is then computed by combining the powers of the various individual modules. in the vehicle model the power generated by the teg appears as surplus power which can be used as needed. the model contains an exhaust bypass control to prevent the peak hot junction temperature from exceeding a preset limit by diverting flow from going into the teg. the exhaust backpressure model also causes exhaust to bypass the teg if the predicted back-pressure exceeds 5 kpa. we simulated several drive cycles using the above model. results from the us06 cycle are advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 204 shown in fig. 12. key points to note are as follows. the modelled exhaust gas temperature at the teg inlet is the blue curve, the exhaust gas heat power into the teg is the red curve, and the corresponding teg output power is in green. the orange curve shows the teg output power assuming a constant exhaust gas temperature of 800oc at the teg inlet. this is an upper bound on the teg output power. the teg hot side and cold side temperatures are shown respectively by the purple (te_hot) and teal (te_cold) curves. from the green (actual) and orange (max output) lines, we observe that the maximum teg output capability is reached between 270 sec and 420 sec on the high-speed portion of the us06 drive cycle. the actual fe gains over the us06 cycle are shown in table 4. the fe improvements were close to zero for the ftp city and highway cycles. the us06 result showed a fuel economy improvement of approximately 2% but fell considerably short of the 5% goal. fig. 12 mild hybrid fst with teg whr system table 4 us06 drive cycle results for teg engine output (kj) fe gain (%) no teg (basesline) 15756 0 teg 15441 2.0 5. conclusions in this study, three different waste heat recovery systems (electric turbo-compounding, organic rankine cycle, and thermoelectrics) were explored and their potential to improve vehicle fuel economy were evaluated. (1) the electric turbo-compounding system with a turbo-generator driven by a vnt, when applied to a mid-size 3150-lb vehicle, showed fuel economy gains of 1.6% on the ftp city cycle, 0% on the ftp highway cycle and 4.5% on the us06 cycle, respectively. (2) the organic rankine cycle system, with r600a as the working fluid, improved the fuel economy of a mild hybrid 4000-lb suv vehicle by 2.7% on the ftp city cycle, 5.1% on the ftp highway cycle, and 4.6% on the us06 cycle. (3) the thermoelectric generator system, when applied to a mild hybrid 6500-lb full-size truck, provided little or no fuel economy improvement on the ftp city and highway cycles, and a 2% fuel economy improvement on the us06 cycle. while we do not claim that these trends will be the same for all applications (heavy duty trucks may show a different trend), we are reasonably confident (based on the fidelity of our sub-system models) that the above numbers are representative and accurate for light duty vehicle applications. integrated whr/vehicle system models are essential to providing realistic assessment of the on-cycle fuel economy benefits of the various whr systems. specific introductions of these systems in the light duty vehicle market will be determined by the cost-benefit ratios of the respective technologies. advances in technology innovation, vol. 3, no. 4, 2018, pp. 195 205 copyright © taeti 205 references [1] “u. s. energy informationadministration(eia),” http://www.eia.gov/forecasts/archive/ieo13/pdf/0484(2013).pdf, 2013. [2] m. raghavan, “propulsion architectures using mechanical energy storage,” proc. the institution of mechanical engineers, part k: journal of multi-body dynamics, vol. 230, no. 3, pp. 242-250, 2016. [3] u. hopmann and m. c. algrain, “diesel engine electric e-turbo compound technology,” sae technical paper, 2003. [4] f. millo, f. mallamo, e. pautasso, and g. ganio mego, “the potential of electric exhaust gas turbocharging for hd diesel engines,” politecnico di torino, sae technical paper, 2006. [5] c. balis, c. middlemass, and s. m. shahed, “design & development of e-turbo for suv and light truck applications,” conf. deer 2003: garrett engine boosting systems, june 23, 2003. [6] c. t. vuk, “electric turbo-compounding a technology whose time has come,” proc. deer, diesel engine emissions reduction conference, 2003, august 21-25. [7] w. wei, w. zhuge, y. zhang, and y. he, “comparative study on electric turbo-compounding systems for gasoline engine exhaust energy recovery,” university of amsterdam, asme paper gt2010-23204, 2010. [8] w. zhuge, l. huang, w. wei, y. zhang, and y. he, “optimization of an electric turbo-compounding system for gasoline engine exhaust energy recovery,” the university of hong kong, department of mechanical engineering, sae technical paper, 2011. [9] m. kadota and k. yamamoto, “advanced transient simulation on hybrid vehicle using rankine cycle system,” sae international journal of engines, vol. 1, no. 1, pp. 240-247, 2008 [10] j. ringler, m. seifert, v. guyotot, and w. hubner, “rankine cycle for waste heat recovery of ic engines,” sae international journal of engines , vol. 2, no. 1, pp. 67-76, 2009 [11] h. teng, j. klaver, t. park, g. l. hunter, and b. van der velder, “a rankine cycle system for recovering waste heat from hd diesel engines whr system development,” sae technical paper, 2011 [12] t. e. briggs, r. wagner, k. d. edwards, s. curran, and e. nafziger, “a waste heat recovery system for light duty diesel engines,” oak ridge national laboratory, sae technical paper, 2010. [13] q. hussain, d. brigham, and j. maranville, “thermoelectric exhaust heat recovery for hybrid vehicles,” sae international journal of engines, vol. 2, no. 1, pp. 1132-1142, 2009. [14] j. lagrandeur, d. crane, and a. eder, “vehicle fuel economy improvement through thermoelectric waste heat recovery,” 2005 diesel engine-efficiency and emissions research (deer) conference, chicago, il, august 2008. [15] r. stobart, g. dong, j. li, and m. a. wijewardane, “performance analysis of tegs applied in the egr path of a heavy duty engine for a transient drive cycle,” gt suite conference, october 2011. https://www.eia.gov/ http://www.eia.gov/forecasts/archive/ieo13/pdf/0484(2013).pdf https://saemobilus.sae.org/search/?op=doauthsearch&auth=millo%2c%20f.&subscribedonly=true https://saemobilus.sae.org/search/?op=doauthsearch&auth=nafziger%2c%20eric&subscribedonly=true  advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 changes of e-kers rules to make f1 more relevant to road cars albert boretti 1, 2,* 1 department of mechanical and aerospace engineering, benjamin m. statler college of engineering and mineral resources, west virginia university, morgantown, usa. 2 military technological college, muscat 111, oman. received 27 october 2016; received in revised form 21 march 2017; accepted 05 april 2017 abstract today’s f1 hybrid cars are based on very similar power units made up of about the same internal combustion engine (ice) and energy recovery system (ers). because of restrictive design rules permitting too much fuel per race, the internal combustion engine is not particularly fuel efficient. the methodology is based on lap time simulations and telemetry data for a f1 h car covering one lap of the monaco grand prix. the methodology is based on lap time simulations and telemetry data for a f1 h car covering one lap of the monaco grand prix. the present limit o f 100 kg of fuel per race is excessive. the low power energy recovery system is used strategically rather than fuel savings recovering very little braking energy. the 4 mj of storable energy is used only when it is s trategically needed. the 2 mj of recoverable energy allowed per lap are almost never collected. to return to be technically attractive, f1 should permit much more freedom in the definit ion of the ice and the ers. as the goal of the ru les should be lowering the fuel consumption while keeping technical and sporting interest high, the best solution is more freedom to achieve the fastest car within more stringent limits of fuel economy. a real limit to the total fuel consumption for a race track like monte carlo should be not more than 80 kg of fuel. this would translate in more energy recovery to the ers per lap and better fuel efficiency of the ice and will certainly help more the design of passenger cars. keywords: hybrid cars, kinetic energy recovery systems, motorsport, f1, le mans 1. introduction today f1 racing cars, similarly to other popular racing car series, are hybrid cars as the environmental concern must be at least apparently the driving force for every sport activity. the power unit now comprises an internal combustion engine and an energy recovery system. the energy recovery system in theory should recover the waste energy, mostly kinetic, to reduce the fuel energy supply to the internal combustion engine. background informat ion on kinetic en ergy recovery systems for racing cars can be found in [1], while the specific internal combustion engines and kinetic energy recovery systems (kers) fo r 2014 f1 cars are discussed in [2-4]. the fuel saving goal is however practically eluded by the most part of the f1 teams. the kinetic energy recovery system is indeed mostly used strategically to boost the performance of a car, being , otherwise, the internal combustion engine not that powerful as it was in the recent past, by discharging the energy storage in selected lap and not certainly charging and discharging the energy storage every single lap . the lack of freedom given to engineers to develop a technical solution delivering a target fuel economy is the reason why f1 is not technically challenging in a way that may be beneficial to road transport while being attractive to the motor enthusiasts. purpose of the manuscript is to suggest changes of the technical regulations that could improve the energy * corresponding author. e-mail address: a.a.boretti@gmail.com advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 27 copyright © taeti recovery and the fuel conversion efficiency of the internal combustion engine for a better fuel economy while permitting top-class motorsport performances. it is shown how a more restrictive total fuel usage per race and more freedom to develop the internal combustion engine and the energy recovery system may benefit the interest towards the racing event and the value of the technical development for production cars . 2. lmp1-h vs. f1 hybrid 2015 the latest 2015 le mans race was dominated by the porsches and the audis battling until the very end of the race, with four class 1 le mans prototype hybrid (lmp1-h) car manufacturers, the two german plus the japanese toyota and nissan, proposing for the event very d ifferent technical solutions for what concerns the internal combustion engine (ice), diesel or gasoline, d ifferent displacement, turbo or naturally aspirated, and the energy recovery system (ers), electric or mechanic or electro-mechanic, o f different powers and different energy storage. the rules set different limitations to the fuel flow rate per different ers energy storage limits and fuel selection. these rules give the lmp1 -h engineers the freedom to develop different ices and different erss. the developments of alternative solutions are ultimately what are needed to make the race event attractive to the motor enthusiast and be relevant, in long term perspective, to the design of every day passenger cars. the same technical enthusiasm does not certainly apply to todays’ f1 hybrids. ref. [4] provides an assessment of the differe nt kers options available in class 1 le mans proto-type hybrid (lmp1-h). fig. 1 f1 kers (es+mgu-k) and e-boost/whr (es+mgu-h) from [5] todays’ f1 hybrids have power units where similarly to lmp1-h the ice is one element of the power unit that also includes an ers. table 1 recalls the present specifications of the ice and the ers. the ers includes two motor generator units (mgu) linked to an energy store (es) recharged by the braking work and eventually the waste heat. the four power unit components, plus the ice and the turbocharger are the six separate elements making a power unit. four of each element are available to each driver per season without incurring in a grid penalty. during a race, drivers may use steering wheel controls to switch to different power unit settings, or to change the rate of ers energy harvest. fig. 1 (from [5]) presents the f1 kers (es+mgu-k) and e-boost/whr (es+mgu-h). the set-up of the power unit of a f1 hybrid is therefore in principle not that far from the one of the porsche 919 h winner of the last le mans 2015 race. the d ifference is , however, substantial when the details are considered. f1 is much better for what concerns the turbocharger, as the mgu-h fitted to the turbocharger shaft and connected to the es gives wider opportunities than having just a power turbine downstream of the traditional turbocharger turbine to recover a minimal amount of waste heat at the expenses of increased back flow. however, f1 hybrids are less flexible under all the other aspects. in f1, the turbocharged 1.6-litre v6 engines are pretty much the same for every team. not only same d isplacement and (about) same fuel, but also same number of cylinders, same 90-degree v angle, same rev limiter at 15,000 rpm, same four poppet valves per cylinder, same direct fuel in jection, same single fixed geometry turbocharged, same bore, same stroke, same crankcase height, almost everything the same to deliver about the same 600 hp or 447 kw of top brake power, with brake mean effective pressure and brake specific fuel consumption curves also expected to be very similar. advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 28 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti the 600 hp or 447 kw are the values of peak power claimed by the most part of the teams for the 2014 season. the fuel flow rate is limited to 100 kg/h, that considering a lower heating value for gasoline of 44.5 mj/kg translates in a maximum fuel power of 1236 kw or 1658 hp, for a peak power efficiency of the ice of 600/1658 = 36.2%. per rumors, a couple of teams outperforming the others this 2015 season could have moved around this limit prompting the federation to seek for remedy. if the fuel flow meter is placed in a certain location of the fuel line, there is always the opportun ity to accumulate fuel downstream of the flow meter, and, therefore, en joy an instantaneous flow rate delivered by the high-pressure fuel injectors more than the instantaneous contemporary reading of the ambient pressure flow meter flow rate . table 1 data of power units of 2015 f1 hybrid cars internal combustion engine displacement 1.6 liters rev limit 15,000 rpm pressure charging single turbocharger, unlimited boost pressure (but maximum 3.5 bar due to fuel flow limit) fuel flow limit 100 kg/h (but not at the injectors) permitted fuel quantity per race 100 kg configuration 90° v6 number of cylinders 6 bore 80 mm stroke 53 mm crank height 90 mm number of valves 4 per cylinder, 24 total exhausts single exhaust outlet, from turbine on car center line fuel direct fuel injection number of power units permitted per driver per year 5 energy recovery systems mgu-k rpm max 50,000 rpm mgu-k power max 120 kw energy recovered by mgu-k max 2 mj/lap energy released by mgu-k max 4 mj/lap mgu-h rpm unlimited energy recovered by mgu-h unlimited every percentage point increment o f the ice fuel conversion efficiency everything but difficult to achieve would t ranslate in an increase of the peak power of 12 kw or 17 hp. similarly, any percentage increase of the instantaneous flow rate to the injectors would translate in an increment of the instantaneous peak power of 4.5 kw or 6 hp. as an additional measure to temporarily increase the peak power, the mgu-h can drive the turbocharger compressor that, otherwise, only depends on the gas expansion through the turbine that is also translating in back pressure for the engine. this can make plausible the large r peak power outputs rumored for 2015. in addition to the maximum fuel flow rate, below 10,500 rpm the fuel mass flow must not exceed q = 0.009 n +5.5, with n the engine speed in rpm and q in kg/h. in addition to the fuel flow limiter placed along the fuel line, the 2014 and 2015 season have seen the introduction of a total fuel per race capped at 100 kg, or 4,450 mj of fuel energy per race, that is certainly a driver for much better fuel economies, but not certainly that strong. this fuel limit properly redefined may be the driver for a better product. fully integrated with the ice is the ers that increases the unit’s overall efficiency by recovering the waste energy from the brakes and the exhaust. the recovery of the exhaust energy is , however, simply the turbocharger turbine that may deliver energy to the energy store that is not delivered to the turbocharger compressor. the ers accounts for an additional 120 kw or 160 hp to deliver about the same power output of the past 2.4 liters v8 engines naturally aspirated. the ers comprises two motor generator units (mgu-k and mgu-h), plus the energy store. the motor generator units convert mechanical and heat energy to electrical energy and vice versa. the mgu-k converts the car kinetic energy generated under braking into electricity while it acts as a motor under acceleration returning power to the drivetrain . the mgu-h converts the exhaust heat into advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 29 copyright © taeti electricity but only through the turbocharger, i.e. only recovers the very s mall amount of energy in the turb ine that would b e otherwise waste-gated when more than the compressor demands. the stored energy can be used to power the mgu-k. the mgu-h controls the speed of the turbo and the power from to and from the turbocharger shaft. the mgu-h may supply the extra energy needed at the compressor when the turbine energy is not enough, as for example in low speed operating points or during accelerations, in this case ad-dressing the turbolag issues. it may also recover the extra energy available at the turbine otherwise waste-gated. the mgu-h may increase the power o f the ice at any speed by precise extra boost, operating in the best point of the map, with supply or withdraw of ext ra energy. while the e-boost technology is certainly not new [10-15], the precise boost of the f1 mgu-h linked to the es of the kers may certainly improve the overall power and energy management of the vehicle. apart from the same design of the mgu and es purely electric, are the energy and power limits of the es and the mgu -k that makes a huge difference vs. the lmp1-h cars. while lmp1-h cars have maximum released energy of 2, 4, 6 or 8 mj/ lap and unlimited released power, in f1 a maximum of 4 mj per lap can be transferred from the es to the mgu -k and then the drivetrain, but only a maximum of 2 mj per lap can be transferred from the mgu-k to the es. more than that, the maximum power of the mgu-k is limited to only 120 kw or 160 hp, while the lmp1-h all have powers of the mgu-k more than 185 kw up to a maximum of 550 kw considered for the nissan gt -r lm nismo. the low power in addition to the limited energy is what makes the fuel saving kinetic energy recovery very difficult. as braking of f1 cars usually occurs with powers largely exceeding the propulsive power, up to about 2,000 kw the low power mgu-k must be recharged carefu lly, as this recharge t ranslates in a lap time penalty. in f1, the mgu-k is limited to recover 2 mj of energy per lap while the mgu-k may then supply a maximum of 4 mj per lap to the drivetrain but the maximum power in and out is limited to 120 kw (160 hp). th is means that the ers is more strategic rather than energy sav ing, as it can be certainly used to save or gain positions or improve the time of an indiv idual lap, while it is still not convenient and not encouraged to recover and reuse the braking energy at any lap as it would be the case if the fuel energy saving wo uld be the real issue. table 2 summary table of 2015 lmp1-h and f1-h power and energy rules (a) limited to <300 kw in 2016. (b) no driver. (c) with driver lmp1-h (le mans race track) f1-h no ers ers options released energy mj/lap 0 < 2 < 4 <6 < 8 <4 recovered energy mj/lap 0 <2 released power kw 0 unlimited(a) unlimited(a) unlimited(a) unlimited(a) 120 kw car mass kg 850(b) 870(b) 870(b) 870(b) 870(b) 702(c) petrol energy mj/lap 150.8 146.3 141.7 137.2 134.9 max petrol flow kg/h 95.6 93 90.5 87.9 87.3 100 petrol capacity carried on-board l 66.9 66.9 66.9 66.9 66.9 fuel technology factor 1.061 1.061 1.061 1.061 1.061 na k technology factor 1 0.983 0.983 0.983 1 diesel energy mj/lap 142.1 140.2 135.9 131.6 127.1 max diesel flow kg/h 83.4 83.3 81 78.3 76.2 diesel capacity carried on-board l 54.8 54.8 54.8 54.8 54.8 table 2 presents a summary of the 2015 lmp1-h and f1-h power and energy rules. in case of one lap of the monaco grand prix, 3.337 km long, a f1 of curb weight 702 kg less the driver weight may use 1.28 kg or 57 mj of fuel energy, i.e . 17 mj/km. in case of one lap of the le mans race, the circuit de la sarthe is 13.629 km long; a lmp1-h of curb weight 870 kg may only use 134.9 mj of fuel energy, i.e. 9.9 mj/km. even if it is not desirable for energy saving to switch on the mgu-k at end of straight for a small-time interval before the driver hits the frict ion brakes, this is what presently makes the largest contribution to the amount of energy available to t he es in f1. the overall lap t ime may also be faster with this strategic recharge because of the faster acceleration up to speed on the advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 30 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti next straight may more than compensates for the lost time. this technique is not , however, in the direct ion of improving the fuel economy, as the direct path engine to wheels is much more efficient than the path engine to mgu-k to es to mgu-k to wheels. the mgu-h is in theory uncapped, and an unlimited amount of energy can be t ransferred between the mgu-h and the es and/or the mgu-k. the mgu-h technology is still far from being fu lly developed, but it is expected to help more in terms of ice output by precise boost rather than recovery of waste heat. the use of mgu-h and mgu-k and es may permit fu rther enhanced energy and power management. 3. energy analysis of a f1 2015 lap of monte carlo to understand the present status of energy recovery and fuel economy, telemetry and lap time simulat ions may help. the selected race track is monte carlo. the circuit de monaco is a street circuit of length 3.34 km. the total dis tance is 78 laps or 260.52 km. if we do consider the last 5 years of the monte carlo competit ion, 3 with the naturally aspirated 2.4 liters v8 and a very small mgu-k of 60 kw, and the latest 2 with the turbocharged 1.6 liters v6 with the larger but still small present mgu-k of 120 kw, clearly the latest f1 are much slower than their predecessors no matter the claim of preserving the maximum power output to preserve performances. in 2011, with sunny, fine and dry conditions, the best qualifying time for pole position was 1:13.556 while the fastest lap during the race was 1:16.234. in 2012, with warm and sunny conditions, about same fine conditions except the threat of showers at the end of the race, the best qualifying time fo r pole position was 1:14.381 while the fastest lap during the race was 1:17.296. in 2013, with sunny and dry conditions, the best qualifying time fo r pole position was 1:13.876 while the fastest lap during the race was 1:16.577. during the first season with the new rules, in 2014 with sunny and dry conditions, the best qualifying time for pole position was 1:15.989 while the fastest lap during the race was 1:18.479, roughly 2 seconds slower. finally, this year, 2015, with sunny and dry conditions, the best qualifying time fo r pole position was 1:15.098 while the fastest lap during the race was 1:18.063. therefore, the new ru les have certainly slowed down the cars . some improvements have however been achieved in terms of fuel economy, even if the 100 kg of ma ximum fuel per a race is not yet the driving force for the further development of the ice and the ers to drastically reduce the fuel consumption. telemetry and lap time simulations may be used to compute the likely performances of f1cars during one lap. the dynamic of racing cars and the equations governing the motion of the car are proposed in [6]. the specific software used in t his paper, [7], is very simple but reliable. not having too much of supporting information as detailed dig itized telemetry data and vehicle parameters, more complicated approaches as for example [8] only introduces additional difficulties to define the many other additional parameters involved in the simulat ion. the code [7] solves the newton’s equations of motion in the three directions for a point moving along a curved path. the minimum weight of the car including the driver but not the fuel was 690 kg in 2014 and it is 705 kg in 2015. the weight of the car is , therefore , taken here equal to 720 kg. for what concerns the aerodynamic d rag, we approximate the aerodynamic drag fo rce as ½∙ρ·v2· cd·a, where ρ is the air density, cd is the drag coefficient and a is the frontal car area, and the lift force as ½∙ρ·v2· cl·a where cl is the lift coefficient. we take ρ=1.29 kg/m3, cd=0.85 and cl=2.4 when a=1.5 m2 for the specific very low speed circu it. as the drag force dramat ically impact on the energy requested by a f1 car to cover a lap, the above far from accurate values certainly impact on the accuracy of the energy computation. the simulat ions require definition of few additional parameters, as the tires radius, the lift (downforce) coefficient, the rolling resistance and the longitudinal and lateral friction of tires, the gear ratios of the sequential gearbox, the final d rive ratio, the drive efficiency and a grip ratio, in addition to the specification of the engine power curve and obviously of the race t rack. advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 31 copyright © taeti while some of the latest lap time simulation codes as [8] also account for lateral and longitudinal weight transfer, real t ire effects as camber, slip rat io and slip angle, temperature and pressures, vehicle yaw over-steering or under-steering and, finally banking and grade on the track, the code [7] does not. today’s most sophisticated lap time simulation tools are fully integrated with the vehicle management and data acquisition systems. while these tools are very accurate, they also rely on the in -deep knowledge of the detailed vehicle operation that is proprietary data of only the teams. without this in -deep knowledge, they are only more complicate without being more accurate than [7]. fig. 2 lump mass model of a f1 car fig. 2 presents the lump mass model of a f1 car. the three-dimensional computation of the car aerodynamic with moving wheels and ground is proposed in [9]. the aerodynamic simulations return drag and lift coefficients to be used in the model. the car is modelled as a particle moving along a curved path subject to propulsive and braking forces. th is simplified model permits a straightforward evaluation of the energy flow of the car covering one lap of a race track. the newton’s equations of motion are solved for the longitudinal, lateral and vertical directions . (a) velocity vs. distance of a f1 car (b) longitudinal acceleration vs. distance of a f1 car fig. 3 velocity and longitudinal acceleration vs. distance of a f1 car covering one qualifying lap at monte carlo fig. 3(a) presents the velocity vs. distance from telemetry and from the simulation, and fig. 3(b) presents the longitudinal acceleration. the telemetry informat ion was digitized from an image, and , therefore, suffers of poor resolution. lap time is 1:15:100. this optimum lap is covered by using the ice and the electric energy the simulat ion produces one velocity value every half a meter of the race track, but the differences in between the two traces are not only due to the different resolution, but also to the model not fully tunable by lack of knowledge of the vehicle parameters and limited by the simplified mathemat ics. the lap time is 1:15:100. this optimum lap is covered by using 13 mj of ice fuel energy delivered with up to a power of 450 kw depending on engine speed plus 4 mj of electric energy delivered with up to a power of 120 kw. advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 32 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti (a) propulsive vs. distance of a f1 car (b) braking powers and propulsive, braking and recoverable energy vs. distance of a f1 car fig. 4 propulsive and braking powers and propulsive, braking and recoverable energy vs. distance of a f1 car covering one qualifying lap at monte carlo figs. 4(a) and 4(b) p resent the propulsive and braking powers and propulsive, braking and recoverable energy vs. distance of a f1 car covering one lap at monte carlo as detailed in fig. 3. lap time is 1:15:100. this optimum lap is covered by using the ice and the electric energy. the propulsive energy is 17.69 mj; the braking energy is 9.20 mj and the theoretically recoverable energy is 1.99 mj. the graphical comparison of telemetry and model results shows a good accuracy. this comparison is usually enough for this kind of simulat ions and perfectly aligned with the scope of the paper aimed to discuss changes of rules rather than the accuracy of lap time simulations . (a) velocity vs. distance of a f1 car (b) longitudinal acceleration vs. distance of a f1 car fig. 5 velocity and longitudinal acceleration vs. distance of a f1 car covering one standard race lap at monte carlo (a) propulsive vs. distance of a f1 car (b) braking powers and propulsive, braking and recoverable energy vs. distance of a f1 car fig. 6 propulsive and braking powers and propulsive, braking and recoverable energy vs. distance of a f1 car covering one standard race lap at monte carlo advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 33 copyright © taeti figs. 5 and 6 p resent same results of fig. 3 and 4 with a different set up permitting 1.6 s slower lap t imes. in fig. 5, lap time is 1:18:700. this lap is covered by using the ice energy only. the grip is reduced 9% vs. the qualify ing conditions reflecting tire usage. in fig. 6, lap t ime is 1:18:700. this lap is covered by using the ice energy only. the grip is reduced 9% vs. the qualifying conditions reflecting t ire usage. the propulsive energy is 16.12 mj; the braking energy is 8.38 mj and the theoretically recoverable energy is 2.00 mj. 4. discussion traditional limit ing factors fo r the mgu-k braking energy recovery are the power o f the unit, the total energy storage, the balance in between the front and rear axle b raking and the balance in between mgu -k and friction braking. certain ly, energy storage at powers much higher than 120 kw also has some downfall for an f1 car. the aero drag is so huge that there is much less energy available at very high vehicle speeds. furthermore, the very high energy numbers only last for a fraction of second. however, the much higher power and energy storage limits permitted in the lmp1-h series certainly show the way to move. if the energy input from the mgu-k to the es may not exceed 2mj in any one lap and energy released from the es to the mguk may not exceed 4mj in any one lap, this means that the continuous use of the kers is eventually limited to just the 2mj recovered and reused per lap, while in the strategic use of the kers, the 4mj could be made available in a lap providing in the previous lap there has been no discharge of the kers. this does not help the fuel economy. from a global fuel energy perspective, the total fuel available to cover the 78 laps or 260.52 km in monte carlo is 100 kg. this translates roughly in 1.28 kg per every lap of 3.34 km. by assuming a lower heating value for gasoline of 44.5 mj/kg, this translates in a maximum fuel energy supply of 57.0 mj per lap. the power unit energy requested per lap is less than 16.1 mj. this translates in an average fuel efficiency of only 28.2% requested to the engine without any working kinetic energy recovery. by recovering the 2 mj per lap with the mgu-k, this efficiency could be further reduced to an even smaller 24.7%. these efficiencies are everything but great. while better estimations may certainly follow the use of the telemetry data and the lap time simulations tools the teams do have, when considering the 1.5 liters v6 turbo engines of the prev ious turbo era almost 30 years ago were already operating with efficiencies well above 30% in a range of operating points of interest, it does not seem that th e 100 kg per race is a really an up-to date limit set to push forward the boundaries of energy efficiency, as the teams may easily ach ieve th e 28.2% efficiency and avoid recovering the braking energy in normal laps, recharging the es only strategically and using the mgu-k only when needed to gain/defend a position. the previous analyses are done without any inclusion of the drag reduction system (drs). this overtaking aid permits a driver within one second of a rival car within designated drs act ivation zo nes to alter the angle of the rear wing flap, reducing drag coefficient and thereby achieving a temporary speed advantage. the drs has no relevant impact on the fuel economy. regarding the energy flow through the mgu-h, any transformation of energy type, for example mechanical to electrical to chemical back to electrical and back to mechanical occurs with efficiency far from unity. how powerful is today’s power unit of hybrid f1 when compared with traditional powertrains of the past is a question difficult to answer. for market ing purposes, it is common to claim that today’s power units have the peak power of the ice, plus the peak power of the mgu-k, with the mgu-h possibly further increasing the power of the ice by precise extra boost. the ice delivers power to the wheels as a function of the speed of the crankshaft. the 450 kw of peak power are obtained at high speeds approaching the speed limiter and certain ly not at low speeds. the mgu-k also delivers power to the wheel, but the 120 kw of peak power are now available at any speed of the crankshaft. advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 34 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti the best use of the mgu-k is to produce a faster acceleration after a bend and not to increase the top speed on a straight. the mgu-h of untapped power does not deliver any power to the wheels. the mgu-h is only linked to the turbocharger, and may only help the ice to deliver more power by spinning faster the turbine above the balance in between gas expansion in the turbine and air compression in the compressor. if the mgu-k power is supplied at low speed, then the equivalent torque of the engine drastically improves. today’s power unit of hybrid f1 are by far less powerful of past traditional powert rains, but certain ly have much better torque. 5. conclusions to return to be technically attractive, f1 should permit much more freedom in the defin ition of the ice and the ers. as the goal of the rules should be the lowering the fuel consumption while keeping high the technical and sporting interest, the best solution is more freedom to achieve the fastest car within more stringent limits of fuel economy. this would benefit the racing and the everyday car. a real limit should be set to the maximum amount of fuel to be used for a fixed distance race, and the engineers should be , then, left free to develop the hybrid power unit with at the most a prescribed displacement of the engine. the present limit of 100 kg of fuel per race does not force the teams to recover the 2 mj of energy every lap, and does not force them to use the fuel much more efficiently within the internal combustion engine that what is common practice since decades. a real limit to the total fuel consumption for a race like monte carlo should be not more than 80 kg of fuel, that would require the recovery of the 2 mj of energy every lap and an average fuel efficiency of the ice of 30.9%, everything but impossible to reach with today’s technologies, but certainly much better than what is presently delivered by today’s f1 internal combustion engines. alternatively, the teams could continue to use only strategically the mgu-k not as a fuel saving measure, but they should, then, improve their internal combustion engines to an average fuel efficiency of 35.2%. these numbers will certainly need the development of novel strategies that may help the design o f passenger cars. references [1] a. boretti, kinetic energy recovery systems for racing cars, pennsylvania: society of automotive engineering (sae) international, 2013. [2] a. boretti, “kers braking for 2014 f1 cars,” society of automotive engineering (sae) technical paper 2012-01-1802, september 17, 2012. [3] a. boretti, “f1 2014: turbocharged and downsized ice and kers boost ,” world journal of modelling and simulation, vol. 9, no. 2, pp. 150-160, 2013. [4] a. boretti and i. aris, “regenerative braking of a 2015 lmp1-h racing car,” society of automotive engineering (sae) technical paper 2015-01-2659, september 27, 2015. [5] m. petrány, “how formula one's amazing new hybrid turbo engine works,” http://jalopnik.com/how-formula-ones-amazi ng-new-hybrid-turbo-engine-works-1506450399, january 22 2014. [6] w. f. milliken and d. l. milliken, race car vehicle dynamics, pennsylvania: society of automotive engineering (sae) international, 1995. [7] “optimumg-vehicle dynamics solutions,” http://www.optimumg.com, 2017. [8] “lapsim-professional racing simulation software,” http://www.lapsim.nl, 2014. [9] m. s. al muharrami et al., “study of open and closed wheels aerodynamic of racing cars in wind tunnels with movable ground at different car speeds,” 18 th australasian fluid mechanics conference, australia, december 2012. [10] u. hopmann and m. algrain “diesel engine electric turbo compound technology,” society of automotive engineering (sae) technical paper 2003-01-2294, june 23, 2003. [11] f. millo, f. mallamo, e. pautasso and g. ganio mego, “the potential of electric exhaust gas turbocharging for hd d iesel engines,” society of automotive engineering (sae) technical paper 2006-01-0437, april 3, 2006. [12] s. ibaraki, y. yamashita, k. sumida, h. ogita, and y. jinnai, “development of the “hybrid turbo,” an electrically assisted turbocharger,” mitsubishi heavy industries, ltd. technical review, vol. 43, no. 3, september 2006. http://jalopnik.com/how-formula-ones-amazing-new-hybrid-turbo-engine-works-1506450399 http://jalopnik.com/how-formula-ones-amazing-new-hybrid-turbo-engine-works-1506450399 http://www.optimumg.com/ http://www.lapsim.nl/ advances in technology innovation, vol. 3, no. 1, 2018, pp. 26 35 35 copyright © taeti [13] a. patterson, r. tett and j. mcguire, “exhaust heat recovery using electro-turbogenerators,” society of automotive engineering (sae) technical paper 2009-01-1604, may 13, 2009. [14] t. katrašnik et al., “an analysis of turbocharged diesel engine dynamic response improvement by electric assisting systems,” journal of engineering for gas turbines and power, vol. 127, no. 4, pp. 918-926, july 2005. [15] n. terdich and r. martinez-botas, “experimental efficiency characterization of an electrically assisted turbocharger,” society of automotive engineering (sae) technical paper 2013-24-0122, september 8, 2013. definitions/abbreviations a acceleration lmp1-h le mans prototype 1 hybrid e energy m mass e-kers electric kers mgu motor-generator unit ers energy recovery system mgu-k driveline mgu es energy store mgu-h turbocharger mgu f force p power ice internal combustion engine r force kers kinetic energy recovery systems v velocity iv introduction to the first issue editor-in-chief, prof. wen-hsiang hsieh on behalf of the editorial board, i am delighted to announce the publication of the inaugural issue of advances in technology innovation (aiti), published by the taiwan association of engineering and technology innovation (taeti). aiti is an international, multidiscipline, peer-reviewed scholarly journal, published quarterly for researchers, developers, technical managers, and educators in the field of engineering and technology innovation. the journal is intended as an outlet for scientists and academicians all over the world to share, promote, and discuss the newest finding, issues and developments with the community. aiti is now accepting submissions from perspective authors to be considered for publication and included in the future issues of the journal. articles of original research, reports, reviews, and commentaries are welcomed by aiti. for more information about the journal or the submission process, please visit the journal’s website. it is a great pleasure to include in the first issue of aiti, six papers written by leading researchers in the international community. i would like to thank all these authors for their wonderful papers, and we also believe that they will make this into a valuable source for researchers and practitioners. the efforts of many people have made this journal possible. first, special thanks must be given to the editorial board. they have helped to define the role of the journal, the review process, the format, and the content of the journal. next, i would like to acknowledge the reviewers for their timely and comprehensive reviews. finally, i must be grateful to the staffs of the editorial office, who have worked for so many months to compile this first issue and complete the website.  advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 development of an automated measurement system for checking irradiation non-uniformity of solar simulators chen-huei hsieh * , xui-ze zh department of automation engineering & institute of mechatronoptic systems, chien-kuo technology university, changhua, taiwan, roc received 02 june 2017; received in revised from 13 june 2017; accepted 23 august 2017 abstract generally, for some solar simulator manufactures, the measurement of irradiation non-uniformity is made by placing a pv cell artificially and point by point on each measuring point on the solar module. it records each corresponding output voltage of pv cell. it is time-consuming and easy to produce measurement error. if either an xy table or a multi-axis robot is applied in this case, it is ot only expensive but also difficult to carry and setup. hence, an innovative and automated measurement system, which consists of both a self-developed smart robot and a monitoring and control system, is proposed in this paper to solve aforementioned problems. the monitoring and control system, i.e., constructed by a pc and a self-developed labview-based application program, plays the role of remotely commanding the operation mode of a robot, receiving the irradiance data being transmitted from the robot and calculating the irradiation non-uniformity. once the irradiation non-uniformity is calculated, some operations are made to adjust the irradiation parameters of the solar simulator such that the irradiation non-uniformity can meet the specification, i.e., 2%, 5%, 10% for class a, b or c of solar module, respectively. keywords: solar simulator, pv cell, solar module, irradiation non-uniformity, measurement 1. introduction recently, many works of literature have paid much attention to develop or design the solar simulator [1-6]. polly et al. [1] presented a dual source solar simulator. to test meteorological radiation, sun et al. [2] designed the optical system of the solar simulator. domínguez et al. [3] presented a solar simulator for measuring the performance of large area concentrator photovoltaic (cpv) modules. a new economical large-scale multiple-lamp solar simulator has been designed and constructed by meng et al. [4] to provide a test platform for the simulation of solar radiation at the earth's surface. a low-cost and portable solar simulator by using led (light-emitting diode) lamps has been proposed by kohraku and kurokawa [5]. besides, sabahi et al. [6] designed and constructed an efficient large-scale solar simulator to investigate solar thermal collectors. to measure the characteristic parameters, such as maximum power output [7], operating temperature [8] etc., of solar module more accurate, an efficient multiple-lamp solar simulator has been employed to irradiate the surface of the solar module. before that, the irradiation parameters of the solar simulator need to be checked in advance, such as irradiation non-uniformity, irradiation stability, and so on. the qualification of solar simulator was specified in iec standard 60904-9, and it specified that at least 64 points irradiance on the surface of a solar module is required to be measured. generally, the solar module consists of 6 x 10 or 6 x 12 pv (photovoltaic) cell and each of them is 200mm*200mm in dimension. before checking the irradiation non-uniformity, these 64 points irradiance need to be measured in advance. and then, the irradiation non-uniformity is checked based on these data according to a non-uniformity formula. * corresponding author. e-mail address: chhsieh@ctu.edu.tw tel.: +886-4-7111111 ext. 2416 http://ieeexplore.ieee.org/document/6316346/ advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 148 the study of [9] pointed out that the most commonly used irradiance non-uniformity measurement methods were “mechanical scanning”, “optical tracing”, and “reference correction”, etc. however, they can not meet the requirement of measuring the non-uniformity of pulse simulator. in [9], a measurement system based on the “shutter method” has been proposed to accomplish an irradiance non-uniformity measurement of pulse simulator. for some solar simulator manufactures, to measure the irradiation non-uniformity, the measurement of irradiance on the irradiated surface of the solar module is made by placing a pv cell artificially and point by point on each measuring point on the surface of the solar module. and then, it records each corresponding output voltage of pv cell. it is time-consuming and easy to produce measurement error. in the way of “mechanical scanning”, if either an xy table or a multi-axis robot is applied to achieve this automated measurement process, it is not only expensive but also difficult to carry and setup. therefore, it is urgent to develop a portal and automated measurement system for checking irradiation non-uniformity of the solar simulator. the purpose of this paper is to propose an innovative and automated measurement system for checking the irradiation non-uniformity of the solar module. this paper is organized as follows. section 2 gives a profile of the proposed system hardware structure. section 3 describes the system software, including graphic user interface (gui), the pc program and the arduino program. in section 4, the experimental results are presented to demonstrate that the proposed scheme is capable of checking the irradiation non-uniformity of the solar module. conclusions are made in section 5. 2. profile of the system structure fig. 1 sketch of robot fig. 2 moving paths for robot the automated measurement system proposed in this paper consists of both a small and smart robot (320mm x 320mm x 75mm) and a monitoring and control pc. in a mechanism, the robot has been well designed for only moving along either the vertical or the horizontal path to avoid turning and to promote position ability. functionally, it is capable of loading a pv cell on its top and moving automatically on a sheet of poster paper which is covered on the surface of the to-be-measured solar module and laid out with several pre-designed tracking paths and position points for the robot. the designed sketch of the robot is shown in fig. 1, and the poster paper (192mm x 96mm) being laid out with tracking paths and position points are advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 149 shown in fig. 2. in fig. 2, there are 6 horizontal paths and 12 vertical paths. the line-tracking sensor h and the line-tracking sensor v are, respectively, employed for the robot to move along the horizontal path and the vertical path. when the robot moves along a horizontal path, once the line-tracking sensor v senses the vertical path the robot stops for a moment and the irradiance on the surface of the solar module is acquired and stored in the eeprom of arduino mega [10]. the similar working principle is applicable to move along vertical paths for the robot. the structure of the proposed automated measurement system is shown in fig. 3, and serial peripheral interface (spi) signal between the rf module and the arduino mega/uno [10] is further shown in fig. 4. the pv cell detects the irradiance on the irradiated surface of the measuring location of the solar module and its output voltage is sent to an analog input (ai) of arduino mega. the control signals from the pc include operation mode, i.e., automation mode and manual mode, position location, start/restart measurement, start transmission, dc motor control and stepping motor control, can be transmitted through the rf modules located on both the pc side and the robot side. in fig. 1, two sets of dc motors including transmission gears are employed to drive four wheels for driving the robot to move along the horizontal direction, and the other two sets of dc motors including transmission gears are employed to drive four wheels for driving the robot to move along the vertical direction. moreover, two sets of stepping motors including transmission mechanism are employed to control the mechanism which switches either horizontal moving drive wheel or vertical moving drive wheel to contact the floor. fig. 5 reveals this switching effect. on the other side, the monitoring signal from arduino mega like irradiance data being acquired can be transmitted to the pc. since the rf module only has spi, the feedback data transmitted from arduino can not be transferred to pc. an arduino uno is used to bridge the spi of rf module and the usb of pc. spi rf module b arduino mega 2560 monitoring and control pc arduino uno spi usb rf module b push buttom/ switch line-tracking sensor ai di spi di motor driver motor driver dc motor*2 stepping motor*2 pv cell robot spi do do fig. 3 structure of the proposed system hardware rf module (si-4432) adruino mega/uno sdo sdi sck nsel nirq miso mosi sck ss int 0 fig. 4 spi between the rf module and the arduino mega/uno fig. 5 sketch of the robot advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 150 the main facilities and modules being required for the proposed system are as follows. (1) one pc is used as monitoring and control station. (2) labview 2015 for the design of gui and the communication with the arduino mega. (3) one arduino uno connected with the pc via usb and with the rf module (si4432) via spi. (4) the robot controlled by arduino mega makes it move in horizontal and vertical on the top surface of solar module. (5) one rf module (si4432) connected with the arduino mega via spi. (6) one pv cell connected with arduino mega via ai. (7) two sets of line-tracking sensors connected with arduino mega via digital input (di) are used to sense the horizontal path and vertical path, respectively. (8) two sets of dc motor drivers connected with arduino mega via digital output (do) are used to drive four dc motors for driving the robot to move along horizontal and vertical direction, respectively. (9) two sets of stepping motor drivers connected with arduino mega via do are used to drive two stepping motors for switching either horizontal moving drive wheel or vertical moving drive wheel to contact with floor. 3. description of the system software the system software includes the monitoring and control program in pc and the control and communication program in arduino uno/mega. the monitoring and control program in pc includes gui and the program of commanding robot and receiving measured data from the robot via wireless communication. on the other hand, the robot is controlled by the arduino mega which includes control program and the program to communicate with the arduino uno via the rf module b. the arduino uno functionally acts as the bridge between the pc and the arduino mega. thus, the program in it is used to communicate with the pc via usb and communicate with the arduino mega via the rf module a. 3.1. description of gui the labview-based gui builds up the friendly human operation interface and the communication mechanism between the pc and the robot. from the monitoring and control panel in the pc, shown in fig. 6, the remote connection between the pc and the robot will be achieved immediately once the “start measurement” button is pressed. the gui can determine the operation mode of the robot, i.e., automation model and manual mode. fig. 6 monitoring and control panel in the pc 3.2. illustration of pc programming the programming of pc is responsible for transmitting the control signals to the arduino mega and also receiving data from the arduino mega. besides, the receiving data transferred from the arduino mega are also integrated into gui in pc. the main procedures in pc are briefly described as follows, and its flowchart is shown in fg. 7. advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 151 start input measuring parameters input specified position transmite specicied position (row, col) move to specified position? receive the measured data from arduino mega end robot operates in automation mode receive all the measured data from arduino mega complete transmission? compute and display nonuniformity complete all the measured points? display the measured data restart measurement ? start measurement ? stop system? restart measurement ? connection ready? auto/manual mode? no yes no yes no yes no yes no no yes no yes yes automanual fig. 7 flowchart of the labview programming (a) set com port for the serial communication and determine the transmission rate, i.e., baud rate (bit per second), as 9600 that need to match the arduino uno transmission rate. (b) set the specification of solar module, i.e., the number of pv cells that a solar module includes. for example, 6 rows x 12 columns means that a solar module has 72 pv cells. (c) check if the wireless communication connection is ready. if yes, turn on “communication ready” indicator and go to the next step. otherwise, repeat step (c). (d) in this step, two operation branches work independently as follows. branch 1: manual mode (i) check if the manual mode is requested. if yes, go to the next step. otherwise, go back to step (d). (ii) set the specified position on the solar module, i.e., the row number and the column number. (iii) check if the “start measurement” button is pressed. if yes, transmit the manual command code and the specified position to the arduino uno and go to next step. otherwise, the same procedure is repeated. (iv) check if the specified position is reached. if yes, turn on the “position ready” indicator and go to the next step. otherwise, the same procedure is repeated. (v) receive the measured data from the arduino uno. (vi) check if the measured data is received. if yes, display the measured data and go to the next step. otherwise, go to step (v). advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 152 (vii) check if the “restart measurement” button is pressed. if yes, go to the next step (ii). otherwise, go to step (e). branch 2: automation mode (i) check if the automation mode is requested. if yes, go to the next step. otherwise, go back to step (d). (ii) check if the “start measurement” button is pressed. if yes, transmit automation command code to the arduino uno. otherwise, the same procedure is repeated. (iii) check if the measurement of all the measuring points is completed. if yes, turn on “measurement completion” indicator and go to the next step. otherwise, the same procedure is repeated. (iv) check if the “start transmission” button is pressed. if yes, go to the next step. otherwise, the same procedure is repeated. (v) receive all the measured data, i.e., the irradiance on the solar module, from the arduino uno. (vi) check if all the measured data are received. if yes, turn on “transmission completion” indicator go to the next step. otherwise, go to step (v). (vii) display all the measured data on gui, compute irradiation non-uniformity and display it, and save the data measured at this time in a file. the formula to compute irradiation non-uniformity is described as follows.          irradianceirradiance irradianceirradiance minmax minmax uniformity-non (1) (e) check if the “stop” button, i.e., the button to stop system, is pressed. if yes, stop the measurement system. otherwise, go to step (b) 3.3. illustration of the arduino programming there are programs in both the arduino mega and the arduino uno need to be designed and their illustration are, respectively, illustrated as follows: (1) illustration of the arduino uno programming the arduino uno is employed to bridge the communication between the rf module with spi interface and the pc with a usb interface. the programming flowchart is shown in fig. 8. the main procedures are briefly described as follows. (a) set the transmission rate, i.e., baud rate (bit per second), as 9600 that need to match the pc transmission rate. (b) check if wireless communication connection is ready. if yes, turn on “communication ready” indicator and go to the next step. otherwise, the same procedure is repeated. (c) receive command code (sent from pc) and transmit it to the arduino mega. (d) check if the “start transmission” flag is activated. if yes, receive the measured data from the arduino mega and transmit them to pc and go to the next step. otherwise, the same procedure is repeated. (e) check if the “restart measurement” flag is activated. if yes, go to step (b). otherwise, the same procedure is repeated. (2) illustration of the arduino mega programming the arduino mega is employed to control the robot for executing manual or automation operation according to the command code transmitted from pc, to acquire the output voltage of pv cell via ai, and to feedback the acquired data to pc. the programming flowchart is shown in fig. 9. the main procedures are briefly described as follows. (a) check if the wireless communication connection is ready. if yes, turn on “communication ready” indicator and go to the next step. otherwise, the same procedure is repeated. (b) compare if the command code is manual or automated. two operation branches work independently as follows. advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 153 (c) check if the “start measurement” flag is activated. if yes, go to the next step. otherwise, the same procedure is repeated. branch 1: manual mode (i) control the robot to move to the specified measuring point. (ii) acquire the output voltage of pv cell, i.e., the irradiance on the solar module, via ai and transmit the acquired data to pc. (iii) go to step (a). branch 2: automation mode (i) acquire the output voltage of pv cell i.e., the irradiance on the solar module, via ai. (ii) control the robot to move to the next measuring point that is the required point belongs to the programmed path in automation operation. (iii) store the acquired data in the eeprom of the arduino mega. (iv) check if the measurement of all the measuring points is completed. if yes, transmit all the acquired data stored in eeprom to the pc and go to step (a). otherwise, go to step (i). start connection ready? receive command code transmit command code to arduino mega start transmission? receive measured data from arduino mega and transmit them to pc restart measurement yes no yes no yes no compare command code? position to the specified measuring point store in eeprom acquire pv cell output voltage via ai acquire pv cell output voltage via ai position to next measuring point transmit the acquisition data to arduino uno complete measurement? start transmission? transmit the acquisition data to arduino uno no no yes yes manual auto start set start point row 1, col 1 connection ready? yes no fig. 8 flowchart of the arduino uno programming fig. 9 flowchart of the arduino mega programming advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 154 4. experimental results and discussion the experiment of this new approach is implemented in a chamber which is equipped mainly with a solar simulator used to irradiate the solar module and a platform used to load a solar module. this chamber is shown in fig. 10. fig. 10 a chamber (1) connect pc to the robot the first step to implement the proposed system is to connect pc to the robot. once the labview-based gui is activated, shown in fig. 6, the connection will be operated immediately whenever the arduino mega is standby. fig. 11 indicates the implementation status after completing this step. fig. 11 setup of the system connection (2) implement automation operation the implementation of the automation operation, shown in fig. 12, shows the measured data, i.e., the irradiance on the solar module, the maximum and minimum value of them and the irradiation non-uniformity. fig. 12 operational results of automation mode advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 155 (3) implement manual operation the implementation of the manual operation is shown in fig. 13. it shows the number of pv cells, which a solar module has, the specified measuring point (row number and column number) and the measured data from that point are shown in “receive data” field. fig. 13 operational results of manual mode (4) measuring time the experimental results about the measuring time and the moving velocity which the robot operates in automation mode are shown in table 1. generally, if the measurement of irradiation non-uniformity is made by placing a pv cell artificially and point by point on each measuring point on the solar module, each measuring point takes 20 seconds in average to measure. thus, it will totally need 1440 seconds to complete measuring one solar module which is 6 rows x 12 columns in the specification. the measuring time obtained by using the proposed system is significantly improved as compared with that by artificial measurement. table 1 measuring time and moving velocity specification of solar module measuring time (sec) moving velocity (mm/sec) 6 rows x 10 columns 210 56.47 6 rows x 12 columns 240 56.03 5. conclusions in this paper, an innovative and automated measurement system for checking the irradiation non-uniformity of the solar simulator is proposed. the feasibility of this new approach has been demonstrated by implementing the experiment in a chamber with a solar simulator and a test platform. furthermore, the experimental results have shown that the proposed system has merits of meeting the miniaturization and portability demands, low setup cost and higher measuring efficiency. references [1] s. j. polly, z. s. bittner, m. f. bennett, r. p. raffaelle, and s. m. hubbard, “development of a multi-source solar simulator for spatial uniformity and close spectral matching to am0 and am1.5,” ieee international conf. on photovoltaic specialists, ieee press, june 2011, pp. 1739-1743. [2] m. sun, g. zhang, b. yang, x. tao, and g. ding, “optical system design of solar simulator for testing meteorological radiation instrument,” international conf. on optoelectronics and microelectronics, ieee press, october 2012, pp. 600 603. [3] c. domínguez, i. antón, and g. sala, “solar simulator for concentrator photovoltaic systems,” optics express, vol. 16, no. 19, pp. 14894-14901, 2008. [4] q. meng, y. wang, and l. zhang, “irradiance characteristics and optimization design of a large-scale solar simulator,” solar energy, vol. 85, no. 9, pp. 1758-1767, september 2011. [5] s. kohraku and k. kurokawa, “new methods for solar cells measurement by led solar simulator,” proc. of 3rd world conf. on photovoltaic energy conversion, ieee press, may 2003, pp. 4-7. http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.stephen%20j.%20polly.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.zachary%20s.%20bittner.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.mitch%20f.%20bennett.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.ryne%20p.%20raffaelle.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.seth%20m.%20hubbard.qt.&newsearch=true http://ieeexplore.ieee.org/document/6186290/ http://ieeexplore.ieee.org/document/6186290/ http://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=6177424 http://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=6177424 http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.mingjiao%20sun.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.guoyu%20zhang.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.bin%20yang.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.xue%20tao.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.guipeng%20ding.qt.&newsearch=true http://ieeexplore.ieee.org/document/6316346/ http://ieeexplore.ieee.org/document/6316346/ http://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=6296429 advances in technology innovation, vol. 3, no. 4, 2018, pp. 147 156 copyright © taeti 156 [6] h. sabahi, a. a. tofigh, i. m. kakhki, and h. bungypoor-fard, “design, construction and performance test of an efficient large-scale solar simulator for investigation of solar thermal collectors,” sustainable energy technologies and assessments, vol. 15, pp. 35-41, june 2016. [7] j. dubard, j. r. filtz, v. cassagne, and p. legrain, “photovoltaic module performance measurements traceability: uncertainties survey,” measurement, vol. 51, pp. 451-456, may 2014. [8] r. eke, a. s. kavasoglu, and n. kavasoglu, “design and implementation of a low-cost multi-channel temperature measurement system for photovoltaic modules,” measurement, vol. 45, no. 6, pp. 1499-1509, june 2012. [9] y. yuan, y. yang, and z. ya, “research of solar simulator irradiance non-uniformity measurement,” ieee international conf. on electronic measurement & instruments, ieee press, october 2011, pp. 307-310. [10] “arduino mega 2560 rev3,” products retrieved from https://store.arduino.cc/usa/arduino-mega-2560-rev3, june 1, 2017. http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.yafei%20yuan.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.yiqiang%20yang.qt.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22authors%22:.qt.zhang%20ya.qt.&newsearch=true http://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=6030004 http://ieeexplore.ieee.org/xpl/mostrecentissue.jsp?punumber=6030004 https://store.arduino.cc/usa/arduino-mega-2560-rev3  advances in technology innovation, vol. 1, no. 2, 2016, pp. 38 40 38 copyright © taeti predictive adaptive control of an activated sludge wastewater treatment process ioana nascu1,2, ioan nascu3,*, grigore vlad4 1 department of chemical engineering, centre for process systems engineering (cpse), imperial college london, u.k. 2 artie mcferrin department of chemical engineering, texas a&m, college station tx, usa . 3 department of automation, technical university of cluj-napoca, romania. 4 icpe bistrita, romania. received 22 february 2016; received in revised form 28 march 2016; accepted 30 march 2016 abstract this paper presents an application regarding a model based predictive adaptive controller used to improve the effluent quality of a conventional activated sludge wastewater treatment process. the adaptive control scheme consists of two modules: a robust parameter estimator and a predictive controller. the controller design is based on the process model obtained by recursive estimation. the performances of the adaptive control algorithm are investigated and compared to the non-adaptive one. both the set point tracking and the regulatory performances have been tested. the results show that this control strategy will help overcome the challenge for maintaining the discharged water quality to meet the regulations. keywords: wastewater treatment, predictive control, adaptive control, parameter estimation 1. introduction wastewater treatment plants (wwtps) are key infrastructures for ensuring a proper protection of our environment. the biological treatment is an important part of any wwtp and the activated sludge process is the most common biotreatment process used to treat sewage and industrial wastewaters. conventional activated sludge systems are focused on the removal of carbonaceous organic matter. these biological processes are nonlinear and complex, representing a challenge from the control point of view due to the enhanced environmental regulations related to the effluent quality and the large variat ions in the influent flow rates and concentrations [1]. an overview of the activated sludge wastewater treatment process mathematical modeling is presented in [2]. a variety of control strategies for wwtp were proposed in the available literature: conventional pid control, fuzzy control, predict ive and optimal control [3,4], all of them presenting good performances in a certain operating point. the control strategy proposed in this paper takes into consideration the controller adaptation to the process parameter changes caused by high variations in the influent flow rate or concentration. the purpose of this paper is to investigate the performance of an adaptive control algorithm (agpc) based on the generalized pred ictive control (gpc) method [5]. the performances of the agpc algorithm are investigated on an activated sludge wastewater treatment process. therefore, the activated sludge process was first modeled and the model was calibrated and validated based on a combination of laboratory tests and plant operating measured data, available from romanofir wwtp. 2. process description and modeling the model of the process was developed based on data obtained from an operational wwtp. the biological treatment process of this wwtp is a conventional activated sludge system with two components: a bioreactor operating under aerobic conditions and a settler (fig. 1). a widely used model to describe the dynamics of bio logical treatment processes is * corresponding author, email: ioan.nascu@aut.utcluj.ro advances in technology innovation, vol. 1, no. 2, 2016, pp. 38 40 39 copyright © taeti the activated sludge model nr.1 (asm1) [6]. since this model is complex, containing a large number of state variables and parameters, it is necessary to simplify it into a simpler model, more suited for control purposes. considering only two material components , a soluble substrate and a particulate biomass component, the mathemat ical model of the biological treatment process for the removal of organic matter will be composed of a set of four non-linear differential equations, three equations for the aerated bioreactor and one for the settler. the process model and the sensitivity analysis are described in greater detail in [7]. fig. 1 biological treatment process schematic 3. adaptive control algorithm the adaptive control scheme consists on two modules: a robust parameter estimator and a model based predictive controller. the controller design is based on certainty equivalence princip le, the estimates of the process model parameters are used instead of the unknown true values in the control law design. the controller design is based on the process model obtained by recursive estimation. 3.1. controller design the gpc design procedure is well described in the literature [5]. the key idea is to min imize the following cost function:       un j n nj r jtuj jtyjtyj 1 2 2 )]1()[([ )]()([ 2 1  (1) where: δ is the differencing operator 1-q -1 , yr is the future reference sequence and n1 the minimum costing horizon, n2 the maximum costing horizon, nu the control horizon and ρ(j) the control-weighting sequence are the controller design parameters. 3.2. parameter estimation to estimate the parameters of the plant model, a version of the standard recursive least square algorithm (rlsa) was used. the use of the basic identification scheme may lead to unstable adaptive process control. for practical implementations of adaptive control strategies, this scheme must be modified in order to provide a robust parameter estimator. the parameter estimation algorithm includes data normalization, a dead zone, a forgetting factor and data prefiltering [8]. 4. simulation results the simulations were carried out in the matlab environment and the closed loop controllers performances for the concentration of organic matter (ss), considered as controlled process output, were investigated. the aeration flow (w) was considered the manipulated input. the nonlinear model o f the b iological treatment process was used to simulate the process dynamics. to obtain the transfer function from w to ss the model was linearized around the nominal operating point (the influent organic matter concentration ssin=765mg/ l). the second operating point was considered for a lower influent organic matter load, ssin=300 mg/l. performances for effluent organic matter concentration ssef which is more relevant were determined and plotted. fig. 2 setpoint tracking performances. agpc-continuous line, gpc-dotted line in fig. 2 setpoint tracking performances of the adaptive predictive controller (agpc) and predictive controller (gpc) for the second operating point can be compared. performances are appreciably improved in the agpc case (continuous line) because the estimator will correct the model parameter values and will adapt the controller to this situation. 45 50 55 60 65 70 75 80 120 121 122 123 124 125 t [ h ] s s e f [m g /l ] advances in technology innovation, vol. 1, no. 2, 2016, pp. 38 40 40 copyright © taeti fig. 3 presents the regulatory performances during simulation tests when the disturbances are applied on the influent organic matter concentration ssin. the ss setpoint is fixed such as the regulations for the organic matter concentration in discharged water are met most of the time (ss effluent (cco-cr) <125 mg/ l). also in this case agpc has slightly improved performances. fig. 3 regulatory performances . agpc continuous line, gpc dotted line 5. conclusions in this paper, the performances of an adaptive model based predictive control strategies for the organic matter concentration in the effluent of the b iological t reatment process of a wwtp have been evaluated. simulation studies were based on the non-linear model, obtained from mass balance equations and they have indicated that the proposed control method performs well and can be easily used. both the setpoint tracking and the regulatory performances have been investigated. the regulations for the organic matter concentration in discharged water are satisfied in a high percentage. acknowledgement the support of the romanian nat ional authority for scientific research, uefiscdi, under grant caseau 274/2014, is gratefully acknowledged. references [1] r. katebi, m. a. johnson, and j. wilkie, “control and instrumentation for wastewater treatment plants,” springer, london, 2012. [2] u. jeppsson, “modelling aspects of wastewater treatment processes,” ph.d. thesis, dept. of industrial electrical eng. and automation, lund university, sweden, 1996. [3] m. a. brdys, m. grochowski, t. gminski, k. konarczak, and m. drewa, “hierarchical predictive control of integrated wastewater treatment systems,” control eng. pract., vol. 16, no. 6, pp. 751-767, june 2008. [4] b. holenda, e. domokos, a. rédey, and j. fazakas, “dissolved oxygen control of the activated sludge wastewater treatment process using model predictive control,” computers and chemical engineering, vol. 32, pp. 1278-1286, 2008. [5] d. w. clarke, c. mohtadi, and p. tuffs, “generalized predictive control part 1. the basic algorithm,” automatica, vol. 23, no. 2, pp. 137-148, 1987. [6] m. henze, w. gujer, t. mino, and m. van loosdrecht, “activated sludge models asm1, asm2, asm2d and asm3,” iwa publishing, london, 2000. [7] s. cristescu, i. naşcu, and i. naşcu, “sensitivity analysis of an activated sludge model for a qastewater treatment plant,” proc. international conference on system theory, control and computing, pp. 595-600, oct. 2015. [8] i. nascu, adaptive control, mediamira, cluj-napoca, 2002. 200 250 300 350 400 118 119 120 121 122 t [ h ] s s e f [m g /l ] https://www.google.ro/search?newwindow=1&sa=n&hl=ro&biw=1476&bih=770&tbm=bks&tbm=bks&q=inauthor:%22reza+katebi%22&ved=0ahukewijnzr89rxjahwh_q4khcbbcreq9agiajaj https://www.google.ro/search?newwindow=1&sa=n&hl=ro&biw=1476&bih=770&tbm=bks&tbm=bks&q=inauthor:%22jacqueline+wilkie%22&ved=0ahukewijnzr89rxjahwh_q4khcbbcreq9agibdaj  advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 61 advanced manufacture of spiral bevel and hypoid gears vilmos simon department of machine and product design, budapest university of technology and economics, hungary. received 20 january 2016; received in revised form 27 may 2016; accepted 02 june 2016 abstract in this study, an advanced method for the manufacture of spiral bevel and hypoid gears on cnc hypoid generators is proposed. the optmal head-cutter geometry and machine tool settings are determined to introduce the optimal tooth surface modifications into the teeth of spiral bevel and hypoid gears. the aim of these tooth surface modifications is to simultaneously reduce the tooth contact pressure and the transmission errors, to maximize the ehd load carrying capacity of the oil film, and to minimize power losses in the oil film. the proposed advanced method for the manufacture of spiral bevel and hypoid gears is based on machine tool setting variation on the cradle-type generator conducted by optimal polynomial functions and on the use of a cnc hypoid generator. an algorithm is developed for the execution of motions on the cnc hypoid generator using the optimal relations on the cradle-type machine. effectiveness of the method was demonstrated by using spiral bevel and hypoid gear examples. significant improvements in the operating characteristics of the gear pairs are achieved. keywords : manufacture, spiral bevel and hypoid gears, load distribution, ehd lubrication, cnc generator 1. introduction the new cnc hypoid generators have made it possible to perform nonlinear correct ion motions for the cutting of the face-milled and face-hobbed spiral bevel and hypoid gears. several studies investigated freeform cutting methods using such machines. among them, shih and fong [1] proposed a flank-correct ion methodology derived direct ly from the six-axis cartesian-type cnc hypoid generator. a polynomial representation of the universal mot ions of machine tool settings on cnc machines was proposed by fan in ref. [2]. chen and wasif [3] presented a new mathematical model to calculate the cutter system location and orientation and a generic post-processing method to establish the machine kinematic chain and to compute the coordinates of the machine axes for the face-milling process on cnc machines. zhang et al. [4] derived the relative mot ion relat ion among the virtual cradle, generating gear, cutter and workpiece on the cnc hypoid generator. to achieve maximum life in a gear set, appropriate bearing pattern location with low tooth contact pressure and low loaded transmiss ion error must coexists. the maximum tooth contact pressure and t rans mission erro r depend substantially on tooth geometry. in order to reduce the tooth contact pressure and the transmission errors, and to decrease the sensitivity of the gear pair to errors in tooth surfaces and to the relative positions of the mating members, carefully chosen tooth surface modifications are usually applied to the teeth of one or both mating gears. as a result of these modifications, a point contact replaces the theoretical line contact of the fully conjugated tooth surfaces. these modifications are introduced into the gear tooth surfaces by applying the appropriate machine tool setting for the manufacture of the pinion and the gear and/or by using a head-cutter with optimized geometry. the new cnc hypoid generators have made it possible to perform vary ing correction motions during the cutting of face-milled and face-hobbed spiral bevel and hypoid gears. in this paper, a method is presented to determine optimal head-cutter geometry and optimal polynomial functions for the conduction of machine tool setting variat ion in pinion teeth finishing simultaneously reducing maximum tooth contact pressure and transmission errors, maximizing ehd load carry ing capacity of the oil film, and min imizing the power losses in the oil film. the developed optimization procedure relies heavily on the loaded tooth contact analysis for the predict ion of maximum tooth contact pressure and trans* corresponding author, email: simon.vilmos@gt3.bme.hu advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 62 copyright © taeti mission errors and on the elastohydrodynamic lubrication analysis for the calculat ion of ehd load carrying capacity of the oil film, and power losses in the oil film. the load distribution and transmission error calculation method e mployed in this study was developed by the author of this paper [5, 6]. the ehd lubrication calculat ions are based on the method presented in refs. [7, 8] the optimization is based on machine tool setting variation on the cradle-type generator conducted by optimal polynomial functions and on optimal head-cutter geometry. in the second step an algorithm is developed for the execution of motions on the cnc hypoid generator using the relat ions on the crad le -type machine. effectiveness of the method was demonstrated by using spiral bevel and hypoid gear examples. significant reductions in the maximum tooth contact pressure and transmission errors, and improvements in lubricat ion performances were obtained. 2. manufacture of spiral bevel and hypoid gears on cradle-type generator the concept of an imaginary generating crown gear is used in the generating cutting process of the face -hobbed spiral bevel and hypoid pinion and gear teeth (fig. 1). the machine tool settings are: the t ilt angle of the cutter spindle with respect to the cradle rotation axis (κ), the swivel angle of cutter tilt (μ), the radial machine tool setting (e), and the tilt d istance from t ilt centre to re ference plane o f head-cutter (hd). to obtain the tooth surface in the generating process, the work gears are rolled with the imaginary generating gear. the coordinate systems  eeee z,y,xk and  iiii z,y,xk are attached to the head-cutter and to the pinion/gear, respectively. the teeth-surfaces of the pinion and of the gear are defined by the following system of eqs. (9)-(10):           , 1 , , 0 3 2 1 4 3 2 1 i e ig h rd t i i i i i c c ec c           r m m m m m m m r    , 0 0 0 i c i c c  v e (1) to co generated gear generating crown gear (c) (t) (w) c0y e 01y c0x head cutter ty t0y tz ' tz t0x tx ' t0z fig. 1 spiral bevel gear hobbing 2.1. variation of machine tool setting parameters the variations of the tilt and swivel angles, tilt d istance, radial machine tool setting, and the ratio of roll are conducted by polynomial functions of fifth-order:       1 10 1 10 1 10 10 11 12 2 5 15 .... c c c c c c c c c c                        1 10 1 10 1 10 20 21 22 2 5 25 .... c c c c c c c c c c                        1 10 1 10 1 10 30 31 32 2 5 35 .... c c c c c c dh c c c c                       1 10 1 10 1 10 40 41 42 2 5 45 .... c c c c c c e c c c c                        1 10 1 10 1 10 1 50 51 52 2 5 55 .... c c c c c c gi c c c c                  (2) where 1c is the angle of rotation of the imaginary generating crown gear in pin ion tooth surface generation. therefore, the maximum too th con tact pressure, maximum transmission error, ehd load carrying capacity, and frict ion factor depend on 33 manufacture parameters: advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 63 copyright © taeti   1 2 55 max max 0 1 0 , , , prof prof ji t ij i j mp r r p p r c                  1 2 55 2max 2max 0 1 0 , , , prof prof ji t ij i j mp r r r c                      1 2 55 0 1 0 , , , prof prof ji t ij i j mp r r w w r c                  1 2 55 0 1 0 , , , prof prof ji t t t ij i j mp r r f f r c                (3) 2.2. the optimization of machine tool settings and head-cutter geometry an optimization method is applied to systematically define optimal head-cutter geometry and machine tool settings to simultaneously minimize maximum tooth contact pressure and angular displacement error o f the driven gear, to maximize the ehd load carrying capacity of the oil film, and to minimize power losses in the oil film. the proposed optimization procedure relies heavily on the loaded tooth contact analysis for the prediction of maximum tooth contact pressure and transmission errors and on the ehd lubrication analysis to calculate the ehd load carrying capacity of the oil film, and the frict ion factor. the employed methods are developed in refs. [5 8] the goal of the optimization is to minimize tooth contact pressure and transmission errors, to maximize the ehd load carrying capacity of the oil film, and to minimize power losses in the oil film while keeping the loaded contact pattern inside the physical tooth boundaries of the pinion and the gear. the applicab le object ive functions can be expressed as       max 2max max 0 2max 0 p mp mp mp p f c c p          (4)       0 0 t w f t mpmp mp fw f c c w f     (5) where 0maxp and 0max2 are the maximum tooth contact pressure and transmission error, 0w and 0tf are ehd load carry ing capacity of the oil film and the friction factor obtained for the initial values of manufacture parameters; pc , c , wc , and fc are non-negative weight coefficients, expressing their relative importance. the proper constraints are due to the requirements that the contact pattern remains inside the possible contact area defined by load distribution calculation and inside the physical tooth boundaries of the pinion and the gear. it leads to the requirement that the contact load outside the instantly possible contact area should be zero. therefore, the constraint can simply be denoted by   0mpc  (6) where c is the total o f tooth surface po ints with instantaneously not exist ing contact loads. therefore, it depends on the tooth surface topography th rough the manufacture parameters mp. the optimization p roblem formulated according to eqs. (4), (5), and (6) is a nonlinear constrained optimization problem. functions  mpf and  mpc are not available analytically, they exist numerically through the load distribution calculation and ehd lubrication analysis. therefore, the computer simulat ion of load distribution and ehd lubrication must be run, repeatedly, in order to compute the various quantities needed by the optimization algorithm. the load distribution calculation and the ehd lubrication analysis are based on highly nonlinear systems of equations. an approximate and iterative technique is used to perform the load distribution calculation and the ehd lubricat ion analysis. this causes that the calculation of partial derivatives for gradient-based optimization algorithms to be quite impractical. for this reason, a nonderivative method is selected to solve this particular optimizat ion problem. here, the pattern search method is used. advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 64 copyright © taeti 3. manufacture of face-hobbed hypoid gears on cnc hypoid generator the cnc machine for generation of spiral bevel and hypoid gears is provided with six degrees-of-freedom for three rotational mot ions ( ,  ,  ), and three translational motions (x, y, z, fig. 5). the six axes of cnc generator are directly driven by the servo motors and able to implement prescribed functions of motions. the face-hobbing method requires simultaneous six-axis control (the face-milling method requires only five-axis control). the following coordinate systems are applied to describe the relations and motions in the cnc generator (fig. 2) : coord inate s ystems  tttt z,y,xk and  iiii z,y,xk are rig id ly connected to the head-cutter and the pinion/gear, respectively. the coordinate transformat ion from system tk to system ik performs the following equation: i0 iy , y cy y t0z , x cx i0x t0x co 1o tio z ix t0y iz i0 cz ,z tz ty tx head-cutter workpiece fig. 2 machine-tool setting for pinion tooth-surface finishing on cnc gnerator       0 , , , i i ti cnc t t ti t x y z         r m m m r μ r (7) the location and the orientation of the tool with respect to the pinion/gear are given in coordinate systems that are represented for a conventional, crad le-type generator (fig. 1). an algorithm is developed for the execution of motions on the cnc generator using the relations valid for the cradle-type machine. this algorithm is based on the conditions that the relative position of the axes of the head-cutter and the pinion rotations, 0tz and 0iy , and the axial relative position of the head-cutter and the pinion/gear should be the same whether the pinion/gear is cut on a cradle-type or on a cnc hypoid generator. to ensure the same relative position of the two axes, 0tz and 0iy , on both the cradle-type and cnc hypoid generating machines, the elements of the coordinate transformation matrices should be equal. on the basis of eqs. (1) and (7) the following condition should be satisfied:        0 00 00 0234120 ,,, t tt z tti z tcccii z i zyx em emmmmme r rr    (8) the same relative position of the head-cutter and the pinion along their axes in the case of both machines, is satisfied by applying the following condition       0 2 1 4 3 2 0 0 0 t t t o o i i i c c c t o ti t         r m m m m m r m r (9) 4. results and discussion a computer p rogram was developed to implement the formulation provided above. by applying this program the optimal machine tool settings were calcu lated and functions were developed for the execution of motions on the cnc hypoid generator using the relations on the cradle-type machine. fig. 3 tooth contact pressure distribution in hypoid gear pair when the pinion and gear tooth surfaces are fully conjugate the load distribution calculat ion was performed for 21 instantaneous positions of the pinion and the gear rolling through a mesh cycle. the tooth contact pressure distributions along the potential contact lines for 21 instantaneous positions and for all the adjacent tooth pairs engaged for a part icular position of the mat ing advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 65 copyright © taeti members, fo r the case when no modificat ions are introduced into the pinion teeth of the hypoid gear pair, namely straight-lined head-cutter profile and the basic values of machine tool settings are applied, are shown in fig. 3. in this case the pinion and gear tooth surfaces are fu lly conjugate. the obtained maximum tooth contact pressure is 369.5 mpa and the maximum angular displacement error of the driven gear is 8.87 arcsec. the tooth contact pressure distribution for the case when the pinion teeth are manufactured by the head-cutter of optimized geometry and by optimal variation in machine tool settings governed by eq. (2) is shown in fig. 4. it can be observed that the maximum tooth contact pressure is reduced to mpa4.332pmax  and the maximum transmission error to secarc79.0max2  . similar reductions in the maximum tooth contact pressure and in the maximum displacement error of the driven gear are obtained in the case of a spiral bevel gear pair (figs. 5 and 6). fig. 4 tooth contact pressure distribution in hypoid gear pair when the pinion tooth is manufactured by the head-cutter of optimized geometry and by optimal variation in machine tool settings fig. 5 tooth contact pressure distribution in the spiral bevel gear pair when the pinion and gear tooth surfaces are fully conjugate fig. 6 tooth contact pressure distributions along the potential contact lines when the pinion tooth is manufactured by opt imized head-cutter and machine tool settings fig. 7 pressure distribution in the oil film in spiral bevel gear pair for the basic values of machine tool setting parameters fig. 8 pressure distribution in the oil film in the spiral bevel gear pair for the optimal values of machine tool setting parameters by applying the optimal combination of head-cutter geometry and machine tool settings the lubrication performances of the spiral bevel gear pair are improved. in figs. 7 and 8 it can be considered that there is a considerable increase in the ehd load carrying capacity and reduction in the power losses in the oil film. advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 66 copyright © taeti -50 0 50 100 150 200 250 227 228 229 230 231 232 233 234 235 236 237 238  [deg.]  , [ d eg .] , x ,y ,z [ m m ]]   x y z fig. 9 motion graphs for the cnc hypoid generator for fin ishing the pinion in function of the rotation angle of the head-cutter on the cnc generator -0,04 -0,03 -0,02 -0,01 0 0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 -15 -10 -5 0 5 10 15  t [deg.]  x ,  ,  [ d eg .] ,  x ,  y ,  z [ m m ]    x y z fig. 10 differences in motions on the cnc hypoid generator as results of using head-cutter o f opt imized geometry, optimal polynomial functions for the conduction of variation in machine tool settings and modified roll fo r pin ion tooth flank generation the graph shown in fig. 9, represent the execution of motions on the cnc hypoid generator for finishing the pinion teeth governed by eq. (2). the variat ion in mot ion parameters is expressed in function of the rotation angle of the head -cutter on the cnc generato r. the differences in the values of mot ion parameters on the cnc hypoid generator, as results of using optimal polynomial functions for the conduction of variat ion in machine tool settings and modified roll for p inion tooth flank generation, are shown in fig. 10. 5. conclusions an advanced method for the manufacture of spiral bevel and hypoid gears on cnc hypoid generator is presented. the optimal head-cutter geometry and machine tool settings are determined to introduce the optimal tooth modifications into the teeth of spiral bevel and hypoid gears in order to reduce the tooth contact pressure and transmission errors , to maximize the ehd load carry ing capacity of the oil film, and to minimize power losses in the oil film. the method is based on machine tool setting variation on the cradle-type generator conducted by polynomial functions of fifth-order. an algorithm is developed for the execution of mot ions on the cnc hypoid generator using the optimal relations on the cradle-type machine. by applying the head-cutter of optimal geometry and the optimal variation in machine tool settings the following operating parameters are improved: (1) in the case of the hypoid gear pair moderate reduction in the maximum tooth contact pressure of 10% and a drastic reduction in the transmission errors of 91% were obtained. (2) for the spiral bevel gear pair significant reductions in the maximum tooth contact pressure of 62% and in the transmission errors of 73% were achieved. (3) the ehd load carrying capacity of the oil film is drastically increased for 252% and the power losses in the oil film are reduced for 61% in the case of the spiral bevel gear pair. references [1] y. p. shih and z. h. fong, “flank correction for spiral bevel and hypoid gears on a six-axis cnc hypoid generator,” asme journal of mechanical design, vol. 130, pp. 062604-1-8, 2008. [2] q. fan, “tooth surface error correction for face-hobbed hypoid gears,” asme journal of mechanical design, vol. 132, pp. 011 004-1-8, 2010. [3] z. c. chen and m. wasif, “a generic and theoretical approach to programming and post-processing for hypoid gear machin ing on multi-axis cnc face-milling machines,” internat ional journal o f advanced manufacturing and technology, vol. 81, pp. 135-148, 2015. advances in technology innovation, vol. 2, no. 3, 2017, pp. 61 67 67 copyright © taeti [4] w. zhang, b. cheng, x. guo, m. zhang, and y. xing, “a motion control method for face hobbing on cnc hypoid generator,” mechanism and machine theory, vol. 92, pp. 127-143, 2015. [5] v. simon, “load distribution in hypoid gears,” asme journal of mechanical design, vol. 122, no. 4, pp. 529-535, 1998. [6] v. simon, “load distribution in spiral bevel gears,” asme journal of mechanical design, vol. 129, pp. 201-209, 2007. [7] v. simon, “elastohydrodynamic lubricat ion of hypoid gears,” proc. of third international power trans miss ion and gearing conference, asme journal of mechanical design, vol. 103, pp. 195-203, 1981. [8] v. simon, “influence of machine tool setting parameters on ehd lubrication in hypoid gears,” mechanism and machine theory, vol. 44, pp. 923-937, 2009. [9] v. simon, “influence of tooth modificat ions on tooth contact in face-hobbed spiral bevel gears,” mechanism and machine theory, vol. 46, pp. 1980-1998, 2011. [10] v. simon, “opt imization of face-hobbed hypoid gears,” mechanism and machine theory, vol. 77, pp. 164-181, 2014.  advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 flowfield analysis of a pneumatic solenoid valve sheam-chyun lin1,*, yu-ming lin1, yu-song haung1, cheng-liang yao2, bo-syuan jian2 1 department of mechanical engineering, national taiwan university of science and technology, taipei, taiwan 2 metal industries research & development centre, kaohsiung, taiwan, r.o.c. received 21 july 2017; received in revised from 24 july 2017; accepted 17 september 2017 abstract pneumatic solenoid valve has been widely used in the vehicle control systems for meeting the rapid -reaction demand triggered by the dynamic conditions encountered during the driv ing course of vehicle. for ensuring the safety of human being, the reliable and effect ive solenoid valve is in great demand to shorten the reaction time and thus becomes the topic of this research. th is numerical study chooses a commercial 3/2-way solenoid valve as the reference valve for analysing its performance. at first, cfd software fluent is adopted to simulate the flow field associated with the valve configurat ion. then, the comprehensive flow v isualization is implemented to identify the locations of adverse flow patterns. accordingly, it is found that a high-pressure region exists in the zone between the nozzle exit and the top of the iron core. thereafter, the nozzle diameter and the distance between nozzle and spool are identified as the important design parameters for improving the pressure response characteristics of valve. in conclusion, this work establishes a rigorous and systematic cfd scheme to evaluate the performance of pneumatic solenoid valve. keywords: pneumatic solenoid valve, compressible numerical simulat ion, transient characteristics, pressure-rising process 1. introduction pneumatic system has been used extensively in many areas of industrial applicat ions, such as automation control, medical instruments, and control unit of the vehicle. it is essential to choose an appropriate valve as the interface to electronic controls for performing the required adjustments or actions in accordance to its function design. among the automobile safety system, an accurate and reliab le pneumatic solenoid valve with a short response time is crit ical in the anti-lock braking system (known as abs), which offers improved vehicle control and decreases stopping distance. therefore, the understanding on the flow patterns inside the solenoid valve is in great demand to shorten the reaction time, and thus becomes the goal of this research. usually, servo valve and on–off valve are two types of electro-pneumatic valves used in controlling the pneumatic actuator. the expensive servo valves with complex structure are used to achieve the high linear control accuracy. on the other hand, due to the low cost, compact size, and simple structure, the fast-switching on–off valves have received considerable attention in vehicle industry and researchers [1-4]. in 2006, topçu et al. [5] develops the simple, inexpensive fast-switching valve for applications of pneumatic position control. four prototype valves have been built and the basic mode of operation confirmed. in addit ion, the switching characteristics of the on–off valve with 2/2-way function has been investigated both theoretically and experimentally. simulated results of the valves dynamics were in agreement with the experimental results, and thus the validity of the proposed mathematical model was confirmed. * corresponding author. e-mail address: sclynn@mail.ntust.edu.tw tel.: +886-2-7376453; fax: +886-2-27376460 advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 134 as expected, the magnetic field has a dominant influence on the response characteristics of a solenoid valve. thus, an optimal design of the magnetic field of a high-speed response solenoid valve is executed by tao et al. [6]. they used the finite element method to optimize the solenoid valve for achiev ing larger magnetic force and low power v ia the changes on parameters and materials. later, wang et al. [7] investigated influences of cross-sectional area of the iron core and ampere turn on the static electromagnetic characteristics through numerical simulation. they found that the ampere turn has great effect on electromagnetic force for the magnetic saturation phenomenon. besides, the simulation method is validated by the experiment. as regards the flow field analysis, several cfd reports [8-12] are focused on analyzing the flow field inside the valve. peng et al. [8] adopted the commercial cfd software fluent to establish cfd model for simulat ing the inner flow field of a servo valve when the valve spool is located in certain positions. also, several improvements in the core shape of valve are raised and evaluated via the established numerical model. later, ma and sun [9] used cfd software fluent to simulate the static and dynamic flow fields of an electromagnetic valve. the function between the mass flow rate and the drop of pressure through the electromagnetic valve was obtained from the results of static flow field simulat ion. from the numerical simulation of the unsteady flow, the valve closed procedure was calculated. the results indicate that the inner flow field numerical simulation of the valve by fluent can reflect its working procedure. more recently, in 2016, liu et al. [10] conducted a research on a solenoid valve used in the hydraulic control system. based on the conditions occurring in the operation of the hydraulic drive system, the thermal field o f the head is analyzed b y ansys. it is illustrated that the solenoid valve has a good performance under high temperature condition. they presented a method to monitor the performance of the valve while the reactor is working. from the previous papers, it is demonstrated that numerical simulation can be adopted as a reliable and useful tool in the valve design. later, liu et al. [11] p resented a nonlinear dynamic model of a large flow solenoid with the mult i-physics dynamic simulat ion software called simulat ionx. the dynamic characteristics of this solenoid valve are analyzed and validated by comparing the test and cfd results. in fact, computational flu id dynamics (cfd) is increasingly being used as a reliable method for determin ing performance characteristics of other valve. farrell et al. [12] executed a series of cfd investigation on characterizing the opening and closing of check valves. they adopted cfx which is a part o f the ansys suite of finite element programs, to predict and characterize the performances of swing check and lift check valves. also, the good agreements are found via comparing the available test data of the modeled valves with the numerical results . fig. 1 methodology of this numerical simulation over a pneumatic solenoid valve advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 135 therefore, th is computational flu id dynamics (cfd) study chooses a commercial 3/2-way solenoid valve, which is used extensively in vehicle control system, to examine its dynamic performance. at first, flow-field simulation associated with the valve construction is executed by using the commercial cfd code ansys fluent. then, the comprehensive flow visualization is implemented to identify the locations of adverse flow patterns, which are critical for proposing the improving alternatives. also, the flowchart for this valve research is illustrated in fig. 1 2. working principle of charging process and description of physical model 2.1. working principle of charging process fig. 2 shows the overall valve system, which is composed of the solenoid valve, p iston connector, connecting duct, and the outlet vessel. it is necessary to describe the working principle for the pressure-rise process of solenoid valve in brief. for increasing pressure to its setting value for activating the abs system, a h igh-pressure (10.1 bar) air source is connected to the nozzle inside the top portion of valve (see fig. 3). thus, this big pressure difference generates a chocking situation (sonic speed at the nozzle exit ) and an in flow with the constant mass flow rate at the beginning of this filling process. however, after the vessel pressure reaches a fixed value (near 52.8 % of the source pressure), the flow rate of this inlet airstream becomes smaller with a rising vessel pressure. finally, this process ends when vessel pressure is equivalent to the pressure source . fig. 2 overall system of the pneumatic solenoid valve fig. 3 open mode of the pneumatic solenoid valve clearly, this charging process is an unsteady flow undergoing a significant pressure variation; thus the transient simulation and compressible assumption are needed to realize the complicate physical phenomena. however, it is known that the unsteady cfd simulation not only needs a high-performance server with huge memory resource, but also takes a much longer cpu time to obtain the result. thus, the steady simulation is carried out on the complete valve system with an opened vessel end in this study for evaluating the flow patterns inside the geometry. thereafter, a comprehensive analysis of the flow pattern inside of the valve system is executed via the simulation outcomes for finding out the modification possibilities. advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 136 2.2. description of physical model the actual valve configuration is quiet complex and difficult to establish a numerical model fo r cfd simulation. thus, proper simplifications on the cad file are needed to attain an effective numerical model, which is div ided into several portions with d ifferent grid densities as indicated in fig. 4(a). generally, to capture the actual physical phenomenon precisely, the intense grid distribution is placed on regions with an abrupt property variat ion on velocity, pressure, or direct ion. for the valve considered here, as illustrated in fig. 4(b), these locations include the nozzle, the s mall clearance between nozzle exit and the armature, expansion part in the connector, and junction between the connecting pipe and the vessel. the total grid number of this numerical model is 8.6 million. (a) overall system of the valve (b) connecting duct to the vessel fig. 4 grid system of the pressure-increasing process for a pneumatic solenoid valve 3. numerical scheme this study simulates the complex flow patterns inside the electromagnetic valve by utilizing the commercial computational fluid dynamics (cfd) software fluent [13] to solve the fully three-dimensional compressible navier-stokes equations with the standard k-ε turbulence model. also, the semi-implicit method for pressure-linked equations (simple) [14] is implemented to solve the velocity and pressure coupling calculation for steady cases. hence, the flow v isualization inside the valve can be performed and observed carefully to locate the reversed flow p atterns. in this work, several appropriate assumptions and boundary conditions were made to simulate the actual flow patterns inside a ceiling fan. they are described as : (1) inlet boundary condition: the inlet boundary condition of valve is set as pabs=11 bar for serving as an extremely high-pressure input. (2) outlet boundary condition the outlet boundary condition at the right wall of vessel is set as the atmospheric pressure. (3) wall boundary condition this numerical model sets the no-slip boundary condition on the solid surfaces of the solenoid valve system. all kinds of flowing flu id problems are determined by physical principles, which are expressed in conservative form for mathematical description. they are mass equation (continuity equation) and momentum equ ation. moreover, as the fluid is under the turbulent condition, the additional turbulent equation is needed to incorporate with the governing equations. the continuity and momentum equations in conservation form are expressed as follows: (1) continuity conservative equation m i i s x u t       )( (1) here iu is the velocity,  is the density, and ms is the source term. advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 137 (2) momentum conservative equation iiiii fgpuuu t     )()()(  (2) where p is the static pressure, 𝜏𝑖𝑗 is the stress tensor, and ρ𝑔𝑖 and 𝐹𝑖 are gravitational and external body forces, respectively. also, the k-ε turbulence model is utilized to solve the navier-stokes equations. with respect to the incompressible flow and no source condition under the steady-state, the momentum equation is:      ji jl l ij i j j i ji ji j i uu xx u x u x u xx p uu x u t                                         3 2 (3) note that eq. (3) is called the reynolds-averaged navier-stokes (rans) equation, where the reynolds stress -ρui ′uj ′ should be appropriately modeled by the boussinesq hypothesis [15] for relat ing to the mean velocity gradients . the advantage of this approach is the relatively low computational cost associated with the computation of the turbulent viscosity. the k-ε model computes the turbulent viscosity as a function of turbulence kinetic energy k and turbulence dissipation rate ε: (4) (5) (6) where 𝐺𝑘 = 𝑢𝑖( ∂𝑢𝑖 ∂𝑥𝑗 + ∂𝑢𝑗 ∂𝑥𝑖 ) ∂𝑢𝑖 ∂𝑥𝑗 is the turbulent kinetic energy generated by the mean velocity gradients. 𝐶1𝜀 , 𝐶2𝜀 , 𝐶𝜇 , 𝜎𝐾 , and 𝜎𝜀 are model constants with the fo llowing empirically derived values: 𝐶1𝜀= 1.44, 𝐶2𝜀= 1.92, 𝐶𝜇= 0.09, 𝜎𝐾= 1.0 and 𝜎𝜀= 1.3, respectively [16]. 4. numerical simulations and discussions                                   k jk t j i i g x k x k x k t     k c k gg xxxt k j t j i i 2 21                                         2 ct  (a) overall velocity distribution (b) region associated with nozzle exit (c) expansion part of the valve connector (d) connecting duct to the storage vessel fig. 5 velocity distribution for the pressure-rising process inside a pneumatic solenoid valve advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 138 this numerical study chooses a commercial 3/2-way solenoid valve as the reference valve for analy zing its performance. firstly, cfd software fluent is adopted to simulate the steady flow field associated with the valve configuration. later, with the aids of analyzing numerical results, the comprehensive flow visualization is implemented to identify the locations of adverse flow patterns, which are critical for proposing the improving alternatives. hence, the thorough realization on performance features of this valve is attained. fig. 5(a) shows the overall velocity distribution inside this pneumatic solenoid valve. the high-pressure incoming air stream flows into the valve through the nozzle and undergoes an accelerating and expanding process. then, this high-speed stream at the nozzle exit enters the small clearance between the nozzle and the armature. certainly, the compressed air hits the armature strongly and directly before it flows into the inner space of valve. as indicated in fig. 5(b), there are several significant circu lations occurred in the right portion while a much weaker circu lation exists in the right part , which is due to an air outlet provided by the connector. later, owing to the stepwise geometry inside the connector, expansion and circulation are observed in these area-enlarging locations (see fig. 5c). finally, the compressed air reaches the 1-liter vessel via the connecting duct with a small cross section. certain ly, as demonstrated in fig. 5(d), two circulat ions generate on both sides of the incoming air flow. in addition, the pressure distribution in the overall system of this pneumatic solenoid valve is illustrated in fig. 6(a). obviously, the pressure trend decreases along the flow path from the nozzle, the connector, the connecting duct, and the storage vessel as expected. certain ly, the most dramatic pressure variation occurs inside the nozzle and region near the clearance between nozzle and armature as indicated in fig. 6(b). as a result, the comprehensive flow visualizat ion yields the locations of adverse flow patterns, also, circulation and reserved flows are observed at region near the nozzle exit, expansion part of valve connector, and junction of the connecting duct to vessel. the above informat ion is crit ical for proposing the improving alternatives. accordingly, the nozzle diameter and the d istance between nozzle and spool top are identified as t he important design parameters to enhance the pressure response characteristics of valve. (a) overall system (b) region near the nozzle exit inside the valve fig. 6 pressure distribution for the pressure-rising process inside a pneumatic solenoid valve advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 139 5. conclusions the flow patterns and response characteristics of a 3/2-way solenoid valve under the charging mode are analyzed in this numerical investigation. with the aids of comprehensive flow visualizat ion, the locations of adverse flow mechanis ms are realized and identified as the foundation for further modifications on its reaction performance. it fo llows that the locations of circulat ion and reserved flows are observed at region near the nozzle exit, expansion part of valve connect or, and junction of the connecting duct to the storage vessel. also, it is found that a high-pressure region exists in the reg ion between the nozzle exit and the top of iron core. accordingly, the nozzle diameter and the distance between nozzle and spool top are recognized as the important design parameters for improving the pressure response characteristics of solenoid valve. clearly, the reaction time can be reduced by increasing the nozzle diameter with an appropriate d istance between nozzle and spool top. moreover, the charging time for th is valve is estimated successfully via a transient cfd calculation in an acceptable deviation from test result. in conclusion, this work demonstrates a rigorous and systematic cfd scheme to evaluate the performance characteristics and to provide important information on key design parameters of the pneumatic solenoid valve nomenclature cμ、c1ε、c2ε constants of standard turbulent k-ɛ model ρ fluid density gk turbulent kinetic energy generated by the mean velocity gradients ρa air density t time 𝜏𝑖𝑗 shear stress tensor u absolute velocity tensor σk prandtl constant of turbulent kinetic equation μ turbulent viscosity σε prandtl constant of turbulent dissipation equation references [1] r. b. van varseveld and g. m. bone, “accurate position control of a pneumatic actuator using on/off solenoid valves ,” ieee/asme transactions on mechatronics, pp. 195-204, september 1997. [2] a. gentile, n. i. giannoccaro, and g. reina, “experimental tests on position control of a pneumatic actuator using on/off solenoid valves,” industrial technology, pp. 555-559, december 2002. [3] g. belforte, s. mauro, and g. mattiazzo, “a method for increasing the dynamic performance of pneumat ic servo systems with digital valves,” mechatronics, vol. 14, no. 10, pp. 1105-1120, december 2004. [4] t. a. parlikar, w. s. chang, y. h. qiu, m. d. seeman, and d. j. perreault, “design and experimental implementation of an electromagnetic engine valve drive,” ieee/asme transactions on mechatronics, pp. 482-494, october 2005. [5] e. e. topçu, i̇. yüksel, and z. kamış, “development of electro-pneumatic fast switching valve and investigation of its characteristics,” mechatronics, vol. 16, no 6, pp. 365-378, july 2006. [6] g. tao, h. y. chen, y. y. j, and z. b. he, “optimal design of the magnetic field of a h igh-speed response solenoid valve,” journal of materials processing technology, vol. 129, no. 1-3, pp. 555-558, october 2002. [7] l. wang, g. x. li, c. l. xu, x. xi, x. j. wu, and s. p. sun, “effect o f characteristic parameters on the magnetic properties of solenoid valve for high-pressure common rail diesel engine,” energy conversion and management, vol. 127, pp. 656-666, november 2016. [8] z. f. peng, c. g. sun, r. b. yuan, and p. zhang, “the cfd analysis of main valve flow field and structural optimizat ion for double-nozzle flapper servo valve,” procedia engineering, vol. 31, pp. 115-121, 2012. [9] y. x. ma and d. c. sun, “the numerical simulation of the flow field in an electromagnetic valve,” machine tool & hydraulics, vol. 36, no. 1, pp. 111-113, january. 2008. [10] q. f. liu, f. l. zhao, and h. l. bo, “numerical simulation of the head of the direct action solenoid valve under the high temperature condition,” 24th international conf. on nuclear engineering, asme press, june 26-30, 2016. [11] z. liu, x. han, and y. f. liu, “dynamic simulation of large flow solenoid valve,” international mechanical engineering congress and exposition, asme press, november 11-17, 2016. [12] r. farrell, l. i. ezekoye, and m. rain, “check valve flow and disk lift simulation using cfd,” 2017 pressure vessels and piping conf. paper, asme press, july 16-20, 2017. [13] ansys fluent user’s guide-14.5, ansys inc, 2012. [14] b. e. launder and d. b. spalding, lectures in mathematical & models of turbulence, london, england, july 1972. advances in technology innovation, vol. 3, no. 3, 2018, pp. 133 140 copyright © taeti 140 [15] j. o. hinze, turbulence, mcgraw-hill publishing co, 1975. [16] s. v. patankar and d. b. spalding, “a calculation procedure for heat mass and momentum transfer in three-dimensional parabolic flows,” international journal of heat mass transfer, vol. 15, no. 10, pp. 1787-1806, october 1972.  advances in technology innovation, vol. 2, no. 2, 2017, pp. 51 55 51 simulation of desiccant cooling kamaruddin a.1,*, aep s. uyun1, alie bamahry2 and rino imanda2 1 the graduate school/renewable energy, darma persada universityjl. indonesia 2 graduate student, the graduate school/renewable energy, darma persada university, indonesia received 09 march 2016; received in revised form 30 april 2016; accepted 05 may 2016 abstract desiccant cooling system has been an attractive topic for study lately, due to its environmentally friendly nature. it also consume less electricity and capable to be operated without refrigerant. a simulation s tudy was conducted using 1.5 m long ducting equipped with one desiccant wheel, one sensible heat exchanger wheel, one evaporative cooling chamber and two blowers and one electric heater. the simulation study used 8.16 m/s primary air, the drying coefficient from desiccant wheel, k1=2.1 (1/s), mass transfer coefficient in evaporative cooling, k2=1.2 kg vapor/s, heat transfer coefficient in desiccant wheel, h1=4.5 w/m 2 o c, and heat transfer coefficient in sensible heat e xchanger wheel h2= 4.5 w/m 2 o c. the simulat ion results show that the final temperature before entering into the air conditioning room was 25 o c and rh of 65 %, were in accordance with the indonesian comfort index. keywords: desiccant wheel, desiccant cooling, evaporative cooling, sensible heat exchanger wheel, silica gel 1. introduction indonesia lies in the tropic where the average air temperature is around 30 o c and rh around 80% all year round. under this weather condition it is not fit for people to work in the office or stay at home. therefore, there is an urgent need for air conditioning facilities in order to be able to live in a better condition. there is also need for industry to increase their productivity by creating better working environment. as the current air conditioning system requires high electricity consumption which requires high fossil fuel input, there is a need to find alternative for the conventional air conditioning system. the best option would be a desiccant cooling system which does not need refrigerant for operating the system. through the manipu lation of air condition using silica gel it is possible to create a comfort condition of a room. research on this type of air conditioning system is new in indonesia and very rare if any attempt to apply the system in indonesia. research by chadi maalouf. at al in france (2006) indicated that by using solar energy they were capable to construct adsorption cooling system for application in several city in france. daou et al. (2004) and jurinak (1982) have conducted research to determine the performance of an adsorption cooling machine using silica gel the pennington cycle. rajat subhra das et al. (1995) study the application of solar energy for liquid desiccant cooling system in india two dimensionless parameters enthalpy and moisture effect iveness are taken as performance indices of the absorber. the performance of the overall system is presented in terms of its cooling capacity, moisture removal rate and cop (coefficient of performance). davangere et al. (1999) had applied a desiccant cooling system with capacity 10 kw (2.85 ton refrigeration) assisted by vapor compression machine. the resulting room temperature 26.7 o c with humidity ratio of w=0.01183 kg/kg dry air for the condition florida which have outside air of 36 o c. they conducted analysis using psychrometric chart and the result of their simulation works were applied to four cities in the usa. bellia, et al (2000) had studied several hybrids cooling system using various desiccant wheels and using desicalc tm computer program and applied to four cities in italy. they concluded that the maximum saving in cost was 22%, and for the theater the saving were greater from 23% to 38% with electricity saving of up to 55%. the purpose of the study is to obtain mathematical model for the purpose of simulation of desiccant cooling system. * corresponding author, email: kamaruddinabd@gmail.com advances in technology innovation, vol. 2, no. 2, 2017, pp. 51 55 52 copyright © taeti 2. the working principle of a desiccant cooling system fig. 1 shows the major component of a desiccant cooling system which comprises of a desiccant wheel containing silica-gel, sensible heat exchanger wheel, a hot water heater supplied from solar co llector, b lowers and evaporative cooler (pons and kodama, 2014). outside air is introduced through point (1) passing the hot desiccant wheel where the humid ity is reduced to point (2). the air will further passed through the sensible heat exchanger (point 3) where its temperature will be reduced while keeping its rh constant. from the sensible heat exchanger the air will be introduced into the evaporative cooling where its temperature will be reduced by its rh will be increased (point 4). when entering the room the temperature and rh will reach 26 o c and 55 %, respectively, a comfortable condition for air conditioning. the air condition in the desiccant cooling system can also be traced using the psychometric chart in fig.2. from the room under condition of point (5) the air will be passed again through the evaporative cooling unit which will reduced its temperature and increase its rh. after passing through the sensible heat exchanger its temperature will increase while its rh is kept constant as in point (6). after passing through the heater, the air temperature increase again heating the desiccant wheel to the condition as point (8). after passing the desiccant wheel the air will gain moisture due to evaporation from the desiccant wheel and it temperature will drop. fig. 1 main component of desiccant cooling system (cnrs-limsi and kumamoto university, 2014) fig. 2 air condition in a psychometric chart (cnrs-limsi and kumamoto university, 2014) 3. mathematical modelling if m is the total mass of air in the duct and x is the humid ity ratio then the humidity ratio change along the z axis of the total length of 1.5 m of the duct can be calculated using the following mass balance equations m 0.5z0 f/)(1  orvmemk dz dx 　 (1) m 1.5z 1.1for /)(  vmsxxc dz dx (2) to calculate the change in temperature along the duct from the in let to the duct out let and energy balance will be used. m 0.5z0.0for )1(11   ttxaxh dt dz x dz dt mcp (3) m 1.1z0.5for )2(22   ttxaxh dt dz x dz dt mcp (4) 1.5mz1.1for )(   sttevh dt dz x dz dt mcp (5) for the condition of the return air from the air condition room, the following mass balance equation will be used. advances in technology innovation, vol. 2, no. 2, 2017, pp. 51 55 53 copyright © taeti m 1.1z 1.5for /)(  vmsxxc dz dx (6) m 0.0z0.5 f /)(1   or vmemk dz dx (7) from the energy balance the following relation can be obtained 1.5mz1.1for )(   sttevh dt dz x dz dt mcp (8) m 0.8z1.1for )2(22   ttxaxh dt dz x dz dt mcp (9) )2(22 2 22 ttxaxh dt dtx xcpxm  (10) mz thxthxahxh dz dt mcp 5.08.0for )(   (11) m 0.0z0.5for )1(11   ttxaxh dt dz x dz dt mcp (12) )1(11 1 11 txtxah dt xdt xcpxm  (13) the amount of heat supplied from solar collector can be calculated using the fo llowing equations. )( tatcacluacradiqu  (14) )( hxttcwcpwmqu   (15) 4. system simulation with the use of parameters listed in table 1, a simulation study was conducted. the results are as shown in fig. 4 for humidity rat io change along the duct and in fig. 5 showing the temperature change. table 2 shows simulation data for solar collector hot water supply. table 1 simulation data quantity quantity quantity m=0.06kg ts=23 o c hev=3.7 (w) v= 8.16 m/s ax1=4.5 m 2 mx2=1.25 kg k1=0.5 (1/s) ax2=1.5 m 2 cpx2=0.897 kj/kg o c k2= 0.5 (kg vapor/s) h1=4.5 w/m 2 c ahx=1.5 m 2 xs=0.007 h2=4.5 w/m 2 c hhx=3.5 w/m 2 o c me=7(%db) tx3=68 o c thx=68 o c mx1=2.3 kg cpx1=0.921 kj/kg o c table 2 data for solar collector heating mw (kg/s) cpw(kj/kg o c) irad (w/m 2 c) 15 4.19 600 ac (m 2 ) ul (w/m 2 c) 1.64 4.5 change in absolute humid ity of incoming outside air is presented in fig. 3 while the change in the incoming air temperature is shown in fig. 5 below. fig. 3 change of entering air humidity ratio across the duct fig. 4 change of entering air temperature from duct inlet 0 0.005 0.01 0.015 0.02 0 0.20.40.60.8 1 1.21.4 h u m id it y ra ti o ( kg va p o r/ kg d ry a ir ) distance from duct inlet(m) 0 20 40 60 0 0.2 0.4 0.6 0.8 1 1.2 1.4a ir t e m p e ra tu re (o c ) distance from duct inlet (m) advances in technology innovation, vol. 2, no. 2, 2017, pp. 51 55 54 copyright © taeti for the returning air from the room its humidity ratio and temperature change are as shown in fig. 6 and 7. fig. 5 change in returning humidity ratio along the duct fig. 6 change in air temperature leav ing the conditioned room to achieve solar collector temperature of 75 o c there is a need to supply 651.9 watt of energy and if this heat is supplied to the heater in the form of heat exchanger so that heat exchanger temperature can reach 65 o c the rate of water flow should be kept at 15 kg/s this temperature will be used to heat the desiccant wheel to drive the moisture out from the desiccant. if the results of humidity ratio change and the air temperature change along the duct are plotted in the psychrometric chart the results is shown as in fig. 8. fig. 7 change in air condition along the duct as plotted in the psychrometric chart (davanagere dkk, 1999) as shown here the air condition entering the room has achieved the comfort condition of 25 o c and rh of 65% (see point 4). 5. conclusions 1) it was possible to develop mathematical model for desiccant cooling. 2) simulation results using 0.35 x 0.35 m cross section and length of 1.5 m, with air flow rate of 0.5kg/m 2 s, and with heater temperature of 68 o c and using desiccant wheel, a sensible heat exchanger wheel and evaporative cooling it was possible to create comfort air condition of 25 o c and rh 65%. 3) it was necessary to supply heat from solar collector having area of 1.64 m 2 with average solar irradiation of 600 w/m 2 and water flow rate 15 kg/s in order to produce the necessary heating temperature of 68 o c. acknowledgement the authors wish to extend their g ratitude to the directorate general of higher education for providing a research grant under contract no.104/k3/km/2015, february 23, 2015 and to darma persada university research institute and public empowerment and cooperation through contract no: 022/ sp3 / lp2mk / unsada/ii/2015 february 23, 2015. nomenclature ac = area of solar collector (m 2 ) ax1 = heat transfer surface of the desiccant (m 2 ) ax2 = surface heat transfer of the sensible heat exchanger (m 2 ) c = mass transfer coefficient in the evaporative cooler (kg/s.) cp = specific heat of the air (kj/kg o c) cpx1 = specific heat of desiccant (kj/kg o c) cpx2 = specific heat of sensible heat exchanger (kj/kg o c) h1 = heat transfer coefficient of the desiccant wheel (w/m 2 o c) h2 = heat transfer coefficient of the sensible heat exchanger (w/m 2 o c) hhx = heat transfer coefficient of the heater (w/m 2 o c) 0 0.01 0.02 0.03 1.5 1.3 1.1 0.9 0.7 0.5 0.3 0.1 h u m id it y ra ti o (k g va p o r/ kg d ry a ir ) distance from duct inlet (m) 0 20 40 60 80 1.5 1.3 1.1 0.9 0.7 0.5 0.3 0.1 a ir t e m p e ra tu re (o c ) distance from duct inlet(m) advances in technology innovation, vol. 2, no. 2, 2017, pp. 51 55 55 copyright © taeti hev = rate of heat transfer with the evaporative cooling (w) irad = solar irradiation (w/m 2 ) k1 = desorption constant (1/det.) m = mass of air (kg) mx1 = mass of desiccant wheel (kg) mx2 = mass of sensible heat exchanger wheel (kg) m = moisture content of desiccant (%db) me = equilib rium moisture content of desiccant (%db) qu = usefull energy from the sun (watt) ta = ambient temperature ( o c) tc = collector temperature ( o c) thx = heat exchanger temperature ( o c) ts = temperature of evaporative cooling ( o c) tx1 = desiccant temperature ( o c) tx2 = temperature of sensible heat exchanger ( o c) ul = overall loss coefficient of the collector (w/m 2 c) v = air flow rate (m/det.) references [1] l. bellia, p. mazzei, f. min ichiello, and d. palma, “air conditioning systems with desiccant wheel foritalian climates,” international journal on architectural science, vol. 1, no. 4, pp. 193-213, 2000. [2] c. maalouf, e. wurtz, and f. a llard, “evaluation of the cooling potential of a dessicant evaporative cooling system using the simspark env ironment ,” utap, university of reims, campus du moulin de la housse, reims, france, chadi. maalouf@ univ-reims.fr. [3] b. s. davangere, s. a. sherief, and d. y. goswami, “feasibility study of solar desicant air-conditioning system–part 1. psychrometric and analysis of the condition -ed zone,” international journal of energy research, vol. 23, no. 1, pp. 7-21, 1999. [4] k. daou, r. z. wang, and z. z. xia, “desiccant cooling air conditioning: a review,” renewable & sustainable energy reviews, vol. 10, no. 2, pp. 55-77, 2016. [5] m. m. s. dezfouli, s. mat, g. pirasteh, k. s. m. sahari, k. sopian, and m. h. ruslan, “simulation analysis of the four configure tions of solar desiccant cooling system using evaporative cooling in tropical weather in malaysia,” international journal of photoenergy, vol. 2014, http://dx.doi.org/10.1155/2014/843617 [6] s. p. halliday, c. b. beggs, and p. a. sleigh, “the use of solar desiccant cooling in the uk: a feasibility study,” applied thermal engineering, vol. 22, no. 12, pp.1327-1338, 2002. [7] l. hernandez, j. heywood, a. kumar, and y. roman, solar desiccant air conditioner, http://solar.sdsu.edu/final docs/solar air conditioning final report 490b.pdf, visited april, 2014. [8] j. j. jurinak, “open cycle desiccant cooling component models and system simulat ions,” ph. d. thesis, dept. mech. eng., university of wisconsin-madison. [9] s. jain , p. l. dhar, “evaluat ion o f solid-desiccant-based evaporative cooling cycles for typical hot and humid climates ,” international journal of refrigerat ion, vol. 18, no. 5, pp. 287–296, 1995. [10] m. pons, and a. kodama, “second law analysis of the open cycles for solid desiccant air-conditioners,” c.n.r.s.l.i.m.s.i., france and kumamoto univers ity, japan , https://perso.limsi.fr/mpons/dsopen.htm, visited april 2014  advances in technology innovation, vol. 1, no. 1, 2016, pp. 16 20 16 copyright © taeti innovation management of patent commercialization yi-ping lee* department of business administration national chung hsing university, taichung, taiwan. received 01 april 2016; received in revised form 10 may 2016; accepted 13 may 2016 abstract patent commercialization is an important issue to most country, for only 0.3 percent of patent have commercialized in the world. researchers try hard to enhance the rate of patent commercialization. this paper focus on innovation of organization and management to enhance the rate of patent commercialization. which is based on team work and plan to promote step by step, for most patent owner develop patent but do not equally put effort on patent commercialization, and that is waste precious time and resource. this research directly analysis government published patent secondary data and the other part is questionnaires survey to patentees, with which to find best way of patent commercialization. keywords: patent commercializat ion, patent management, strategy of commercialization 1. introduction corresponding to the number of patents increased rapidly in the whole world during recent years, this phenomenon imply that the world people are pay attention to the influence of intellectual property rights . most country build a good national patent environment to provide creative and competitive resource, the less barriers of patent commercialization removed, and the higher rate of patent commercialization will be. patent system protect inventor’s interest from patent infringement, which means one who produce or sale patent product without authorization, he will be punished by pay loss of patentee’s damage or more seriously treble fined for h is behavior of patent right infringement. another way of patent use is the patent owner can exercise his patent right in attack and defense in a compete war, he can use the patent right to beat competitors in the market, the value of patents value may up to millions dollars, or much more than that, upper concepts highlight the reason and importance of patent commercialization. patent number keep on increase but the rate of patent commercializat ion still low, average rate of patent commercialization in the whole world are only near 0.3 percent. innovation is a global trend for most inventor, patentees pass the patent examination by long time research and continuously improvement to inventions, but after a lot challenge and then gain the patent right. the process of patent application need about 3 more years, if the inventor is lucky enough, he may pass patent examination in first time, or he have to file roundtrip several times. patentee have to pay an annual fee annually to maintain his patent right is another barrier of patent commercialization. why patentee shelved commercialization action after owned the patent? most inventors are top cleaver in their domain of industry, they can solve very complex technic problem, because patent should satisfy factors of useful, novelty and non-obvious, all these three factors have to testified by the patent examiner through precedent examination, there can’t have any precedent be find in any other patent database of the whole world, or else the patent examiner will turn down the patent application. every cases of patent application are need a lot of resources from government and individuals, all front end process before patentee own his patent, regardless technic development or patent application are need to pay money, furthermore, patent maintenance fees pay annually increasing is money consuming. since patent product’s life cycle need continuously pay money from the beginning of patent invention to the patent right perished. an obscure question need to find the answer and why? the question is the patent pay compared with the outcome of value is extremely inequivalent, which imply that the patentee gain * corresponding author, email: yiping727@yahoo.com.tw advances in technology innovation, vol. 1, no. 1, 2016, pp. 16 20 17 copyright © taeti nothing in the end of patent life cycle, are they really want to pay price and without gain any benefit? we can trace back to the meaning of patent right to find the answer, here the answer should be very clear, the patent right originally mean the patentee have the right to exclusive others to infringe his patent right by the government authority, except that, the patentee have the right to sale the patent right, produce the product, if the patentee can do one of upper things, he will not be gain nothing from patent, this identify that most patentees are want gain benefit from patents but inability to do something have his patent commercialized. most patentee was numb about keep on pay fees annually after gain patent right, outcome of patents is zero year after year, in particu lar, they still have no active action of patent commercialization, which is not match the rule of investment, what are they work for is the question, how to solve the problem is the goal of this paper. this paper focus on the secondary data of government intellectual property to analysis and find partial factors of patentee’s inability of patent commercialization. 2. literature review and hypotheses china is in response to the global trends, they establish a an modern patent system in recently years, which is pave with international standards, with which to imply patent protection (lulin gao, 2008), it is difficu lt to have patents commercialized is a long term phenomenon in the world, may the reason of inadequate equipment or lack of incentive for commercialization (avimanyu datta, 2012), commercialization of university inventions (yonghong wu, 2013) basically patent inventors almost are excellent and cleaver, but in the link of patent commercialization are transfixed and s ilently endure no recovery and obtained repeatedly in long-term of non-use patent investment, this situation is not only a country’s problem, there are almost the same in the world, which waste a large amount of national resources of examination and indiv idual’s monetary or time resources, this is really an pract ical and academic issue, for the benefit of all country and patentee, unravel the patent commercialization problem and do good to society and patentee in the same time, this article as the results prevail for understanding patent commercialization of patentees. first, patent commercialization factors clarify, second, succeeded experience highlighting. 3. research frame and hypothesis this paper have the operational definition on research facets as follow, which include patent number, patent of commercialization, organization, p romotion action and investment of fund and time are computable from data or questionnaire. all patent data are collect from intellectual property office, ministry of economic affairs (moea), fo r some of the private informat ion should collect from individuals, such as investment of fund or time, and both of upper two main factors are set to computable number in different facets. patent commercialization was composed of several factors, which include human resource of promotion, action of promotion, investment of fund and time etc. all factors are affect the patent commercialization rate, thus, hypothesis as follow, fo r patent commercializat ion was calculated on patent and commercialized patent, thus, the quantity of patent in equation’s denominator will affect the result of patent commercialization rate. for patent commercialization is so difficult, thus it should be promoted by organized team, basically, the more employee member work together, the outcome of that team will be better. h1: the more quantity of patent number in patent data, the lower o f patent commercialization rate. h2a: the more quantity of employee number in organization of patent commercialization, the higher of patent commercializat ion rate. h2b: the more quantity of action in patent commercialization, the higher of patent commercialization rate. h3a: the more quantity of fund in investment of patent commercialization, the higher of patent commercialization rate. h3b: the more quantity of time in investment of patent commercialization, the higher of patent commercialization rate. advances in technology innovation, vol. 1, no. 1, 2016, pp. 16 20 18 copyright © taeti 4. method due to research the individual patents commercialization, this research focus on the process and case of patent commercialization, because the rate of 0.3 percent patent commercialization is now exist the same in most country, thus, every successful experience will be very precious, we visit the patentee to find detail and factors of these patent commercialization(nicole ziegler, 2013). this research focus on patent owner, up to now, all cases are from taiwan patentee, and the patentee have the level of own about 100 patents, and the rate of patent commercializat ion over 5 percent, compare with the common patent commercialization rate with 0.3 rate, 5 percent could be a very successful and precious experience, fo r these case much better than common cases about ten times of commercialization rate. the method of analysis was adopt statistical package for the social sciences (spss) in analysis, secondary data and questionnaire was use in research reliability and validity, we exclude the invalid sample. variab le define and evaluation in this research was use patent number of patentee owned, individual patent commercializat ion rate was set and calculated from government published patent data number (pdn) divided by number of patentee commercialized patent (pcn), the same as total number of patent commercialization rate was averaged upper two factors to gain complex commercialization rate. pcr=pn/pcn (1) the patent commercialization rate was affected by patent promotion (pp), and which was composed by two factors, first, promotion organization, second, promotion action, and promotion organizat ion and management, promotion organizat ion was define as the have tax pay for salary and number of patent promotion employee (ppe), action of promotion(ap) was define as have record of application of government subsidiary (ags), records of patent t transaction (pt) in platform or produce of patent product(ppp), promotion time consuming(ptc), invest in capital(ic) etc. patent strategy was adapt from questionnaire to the patentee, such as how much fund put to commercialization (fpc) his patent, and how many patent is plan to commercialization (ppc), ppe=sa*ne (2) ap=ags+pt+ppp+ptc (3) pcs=ic+it (4) 4.1. secondary data analysis all cases are selected by the level of the patentee have higher rate of patent commercialization, if a case can achieve this level, this kind of case have ten times of pcr than usually patentee have, and far exceed most country’s pcr. thus, for two reason of this research design, first, near 100 patents owner and 5 percent of pcr are strictly level for most patent owner, most patent owner in the world a re in the situation of pcr lower than 0.3 percent, thus, the level of 5 percent pcr should be reliable fo r the test and study, first of all, in the first section, we choose the r&d team member less than 10 employee, for most patentee are individual inventor, we will limited our range for the study be exactly right to most patentee, thus, in the first section the participant will not be a firm level r&d operation. 4.2. primary questionnaire data analysis through phone call and e-mail to confirm the visit date and time, then have face to face questionnaire discussion with the patentee, furthermore, we visit the patent product factory and discuss with the manager and sales, questionnaire was design as likert 5.0 scale, this process can be part of further internal empirical. 4.3. cases study case 1 have a research and development team, which is organized by about 5 people and led by a professor/dr. who is a professor of national university, and serve in department of brain neurology, through over 26 years of work and research from day to night, the professor/patentee own and partially involved 93 patents, most patents are medical equipment, he chaired his research team, focus on invention and patent design. case 2 have a research and development team, which is organized usually by about 2 to 5 people and led by a professor who is a professor of national university too, and serve in department of material science, through about 11 year research, the patentee own and part ially involved 172 patents. advances in technology innovation, vol. 1, no. 1, 2016, pp. 16 20 19 copyright © taeti case 3 do not have a research and development team, who usually innovation by himself, through over 12 years of research, the patentee own and partially involved 72 patents, all patent are through long term and continuous work and study, keep on try and error to win the patent, after this stage, patentee develop an partner owned product manufactory. table 1 patent case analysis patentee a b c patent domain medical equipment material science multiple domain patent quantity 93 172 72 new invented 85 172 24 new design 8 0 25 new type 0 0 1 patentee research duration 1999-2015 2004-2015 2004-2016 patentee research year 26 11 12 commercial quantity 5 7 32 commercial rate 18.50% 24% 44% highest invention quantity in a year 15 45 22 patent applied by university 76 150 0 patent applied by group 7 15 23 patent applied by individual 10 7 49 average year to own patent 3.2year 4.5year 7.2month 5. results and discussion faith and determination be possible oobstacle to patentee in attempt to promote patent, plan and execute are main affect factors, patentee’s faith of patent commercialization, faith and commitment of a person's attempt to complete plan (ajzen1985). possible future research design for this issue, the research design may focus on case study and questionnaire, include government officer, business manager, stock investors and experts, for all these people are important member patent commercialization. after the research of data analysis, a successful patent commercializat ion are have a team to support the action of patent commercialization, which include research and development, promotion member of commercialization, financial support and market ing. if with a team operation continuously, especially on the promotion work, then, patent would be possible be commercialized, else, most patentee focus on research and development, there almost have no resource and promotion action have put in, thus, lack of promotion action in commercialization is the main reason exist low rate of patent commercialization. 6. conclusions in this paper, three new way of the patent commercialization have been generated in this research. the feasibility of the new method is verified by. the result has shown that the new designs can produce a more wide range of non-uniform output motion than the existing design. therefore, they are better alternat ives for driving a variable speed input mechanism. references [1] a. datta, r. reed, and l. jessup, “factors affecting the governance of innovation commercialization: a theoretical model,” journal of business and management, vol. 18, no. 1, 2012. [2] gerald, udell, m. hignite, “new product commercialization: needs and strategies,” the journal of applied management and entrepreneurship, vol. 12, pp. 75-92, 2007. [3] l. gao, research technology management, china’s patent system and globalization, 51.6, pp. 34-37, 2008. advances in technology innovation, vol. 1, no. 1, 2016, pp. 16 20 20 copyright © taeti [4] n. l. vanderford, l. t. weiss, “heidi l. weiss ic-based cancer research commercialization,” public library of science (plos), vol. 8, no. 8, p. e72268, 2013. [5] n. macias, c. knowles, f. kamke, and a. kutnar, “commercialization potential of viscoelastic thermal compressed wood: insights from the us forest products industry,” forest products journal, vol. 61, no. 7, pp. 500-509, 2011. [6] n. zieg ler, f. ruether, m. a. bader, and o. gassman, “creating value through external intellectual property commercialization: a desorptive capacity view,” the journal of technology transfer, vol. 38, no. 6, pp. 930-949, 2013. [7] y. wu, e. w. welch, and w. l. huang, “commercializat ion of university inventions: individual and institutional factors affecting licensing of university patents,” technovation, vol. 36-37, pp. 12-25, 2013. [8] r. ghafele and b. gibert, “ip commercialization tactics in developing country contexts,” journal of management and strategy, vol. 5, no. 2, pp. 1-15, 2014. [9] h. s. yan and w. r. chen, “on the output motion characteristics of variable input speed servo-controlled slider-crank mechanis ms,” mechanism and machine theory, vol. 35, pp. 541-561, 2000. [10] h. s. yan, m. c. tsai, and m. h. hsu, “an experimental study of the effects of cam speeds on cam-follower systems,” mechanism and machine theory, vol. 31, pp. 397-412, 1996.  advances in technology innovation, vol. 2, no. 4, 2017, pp. 99 104 99 harvesting atmospheric ions using surface electromagnetic wave technologies louis wai yip liu*, qingteng zhang, yifan chen department of electrical and electronics engineering, southern university of science and technology, xili, nanshan, shenzhen, china. received 19 november 2016; received in revised form 08 march 2017; accepted 08 march 2017 abstract for the first time, this paper discloses the use of flowing water for capturing atmospheric ions into a dc electricity. the proposed methodology can be employed to neutralize the positively charged pollutants in air, which are believed to be harmful to our health. methodology: atmospheric ions can be collected by a negatively charged antenna which comprises a dielectric layer sandwiched between a top aluminium layer and a bottom lead plate. the top aluminium layer is used to collect the ambient protons, whilst the bottom lead plate is negatively charged by a negative static electricity extracted from flowing water. the voltage has been measured between the top aluminium layer and the bottom lead plate with and without any sunlight. results: without any uv light or other electromagnetic disturbance, the generated voltage has rapidly increased from 200 mv to 480 mv within 5 seconds if the bottom lead plate is connected to the negative ion source. without the negative ion source, however, the output voltage fell to around 10 mv and any significant voltage rise can be observed even in the presence of an uv light. conclusions: capturing atmospheric ions is technically feasible. measured results suggest that, when used in conjunction with a negative ion source, the proposed device can harvest atmospheric ions without any uv light. keywords: cosmic rays, surface plasmon polarition, surface plasmonic resonance, kelvin water dropper, kelvin thunder 1. introduction solar energy has been proposed as an alternative to fuel based energy sources which release tons of pollutants to our atmosphere on a daily basis. however, conventional solar cells are usually inactive before 6 am or after 6 pm. there have been many suggestions to overcome this issue. one suggestion is to use molten salts to store the sun's heat during the day so that power can be obtained by cooling during the evening time [1, 2]. french national center for scientific research and the university of tokyo has suggested mounting a solar panel in a high-fly ing balloon to tap solar energy above the clouds [2]. unfortunately, neither of these solutions can be carried easily with household facilities . what is little known is an energy source known as cosmic rays. cosmic rays which come from exploding stars from light years away can be harvested during the evening time. cosmic rays are ionizing particles of cosmic origin traveling at near the speed of light [3-5]. the majority of cosmic particles are the nuclei of atoms, mostly protons. as these cosmic particles penetrate into the ionosphere, they induce nuclear-electromagnetic cascade ionizing air molecules all the way down to the surface of the earth. the earth is an entity carrying negative charges, which repels the negative ions on the surface of earth. as a result of the earth's intrinsic negativity, air pollution and the cosmic ray induced ionization, the density of these positive ions in the lower atmosphere becomes 10-20% higher than the negative ions. the surface of the earth, these positive ions mainly include positively charged dusts, bacteria, pollen, chemicals and fumes. the buildup of these excessive pos itive ions can be removed and turned into energy when they are attracted to an artificial source of negative charges. if these negative charges are freely abundant, then the amount of energy generated will be positively associated with the density of positive ions in the regions where atmospheric ions is to be harvested. the most basic atmospheric ion collector was invented by nikola tesla in 1901 [6-7]. in his atmospheric ion collector, an antenna is used to collect cosmic particles or positive ions. the antenna comprises a sheet of optically smooth metal completely encapsulated in a dielectric. the antenna serves two purposes: 1) it collects the ultraviolet radiations in the form of surface electromagnetic waves; and 2) it attracts atmospheric ions. the captured radiations or a positive ion increases the voltage of the antenna with respect to the service earth connection. the condenser connected between the antenna and the earth has a high capacitance, thereby creating a high electrostatic suction to attract ions at high altitudes. when the voltage is high enough, it charges up a capacitor or a battery. some researchers have replicated the tesla's experiment with limited success [8-13]. however, this kind of atmospheric ion collectors do not work well when placed at low altitudes, where the density of the atmospheric ions is simply too low. in the field of astrophysics, cosmic radiations are usually detected using a scintillator [14]. for example, an array of scintillator surface detectors samples the footprint of the cosmic-ray shower when it reaches the earth's surface. a fluorescence telescope is used to measure the scintillation light generated as the shower passes through the atmosphere. while this technique is highly useful for the purposes of detection of cosmic rays, it may not be readily useful for neutralization of positively charged pollutants at low altitudes. for the first time, this paper proposes a novel collector which uses flowing water as an energy source to capture positively atmospheric ions on the surface of the earth. *corresponding author. email: liaowy@sustc.edu.cn advances in technology innovation, vol. 2, no. 4, 2017, pp. 99 104 100 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti 2. proposed antenna for collecting positively charged air ions to harvest atmospheric ions, it is important to understand which frequency bands are available for direct energy harvesting. these frequency bands will determine what metal is to be used for the antenna (i.e. the part for capturing cosmic radiations). fig. 1 shows a spectrum of radiations from outer-space. it can be seen from fig. 1 that ultraviolet radiations are the only frequency band at which ionizing energy can be conveniently captured at the ground level [15]. these ultraviolet radiations are mainly of solar origin. a small amount of atmospheric ions come from these ultraviolet radiations. the oxygen and ozone molecules in the atmosphere absorb most of the cosmic radiations from outer-space, including the x-rays and gamma-rays from the galaxy. there is no direct access to the primary cosmic particles on the surface of the earth. however, it is incorrect to assume that atmospheric ions cannot be harvested on the surface of the earth. the nuclei, the x-rays and the gamma-rays from the galaxy constantly induce cosmic cascades in the ionosphere, releasing a large amount of energetic ions that are far more penetrating. fig. 1 available spectrum for energy harvesting [15] to maximize the energy which can be harvested, therefore, the antenna should be designed in such a way that it can capture not only ultraviolet radiations from the sun, but also the free ions that are moving randomly in the atmosphere. these two requirements can be easily fulfilled by following the following design strategies: (1) the incoming uv light must be captured in the form of surface electromagnetic waves, which is concentrated on the surface. either aluminum or silver should be used as the metal for capturing ultravio let lights because these two metals naturally have a surface plasmonic resonance frequency right at the ultraviolet band; and (2) on the other hand, the metal for the antenna, which can be aluminum or silver, should be biased to certain voltage so that it naturally attracts the nearby atmospheric protons. this can be done by connecting the metal indirectly to a source of negative charges. (3) the induced current must be directed from the positive end, which is the antenna in this case, towards the negative end, which is the source of negative charges. this can be done with a h igh reverse breakdown voltage. (4) the surface area of the antenna should be as large as possible in ways to maximize the chance of ionization. (5) all the metal used in the co llector should not be exposed and should be dielectrically coated in a way to minimize the charge leakage. fig. 2 antenna for capturing atmospheric positive ions and cosmic particles when the bottom lead plate is negatively charged by a negative ion source, the top aluminum layer will be electrostatically induced to a positive potential. if the top aluminum layer is fully covered by the dielectric coating, then the surface of the top dielectric coating will become negative. the atmospheric positive ions will be attracted to the surface of the top dielectric coating and the top aluminum layer will be further charged positively by electrostatic induction. when the potential difference between the top aluminum layer and the bottom lead plate exceeds the threshold voltage of the diode, a current will form. in addition to the atmospheric positive ions, some other cosmic-ray induced particles or ultraviolet radiations from the sun also play a role in ionization. the fast-moving particles in these radiations will be slowed down significantly as they reach the top dielectric layer. the cosmic radiations are ionizing. when the atmospheric ions reach the aluminum layer, ionization is expected to occur. the energy that is created due to this ionization process is mainly electromagnetic in nature. this electromagnetic energy can either be trapped as a result of the intrinsic localized surface plasmon resonance in aluminum or be transmitted as a surface electromagnetic wave, also known as surface plasmon polariton. surface electromagnetic wave differs from the conventional electromagnetic wave in that the former propagates along the interface between two different media whilst the latter propagates through the 3d dimensional space. unlike the conventional electromagnetic wave, which is radiating in all directions, surface electromagnetic waves tend to be transmitted in a more concentrated manner. the efficiency of this surface plasmon polaritan can be optimized by making sure the antenna reaches the surface plasmonic resonance. the surface plasmon resonance occurs when the leaky modes are minimum and the propagation modes are maximum, according to [16]. in the structure as shown in fig. 2, a complete surface plasmon resonance condiadvances in technology innovation, vol. 2, no. 4, 2017, pp. 99 104 101 copyright © taeti tion will occur mainly at the interface between the top dielectric layer and the aluminum layer (also referred as mi structure) and, to some extent, in the high-k material between the aluminum layer and the bottom lead plate (also referred as mim structure). during surface plasmon resonance, most of the energy will concentrate in the horizontal direction in the forms of propagation modes and there should be very little leakage in the form of radiations in the vertical direction. 2.1. surface plasmon resonance for the mi structure to attain surface plasmon resonance condition in the mi structure (that is, the interface between the top dielectric layer and the aluminum layer), the criterion shown in eq. (1) and (2) must be met, according to [16]: εa aa+ εbab= 0 (1) where εa and εb are respectively the dielectric constants of the dielectric coating and the aluminum layer. aa and ab are respectively the thicknesses of the dielectric coating and the aluminum layer. the dielectric constant of aluminum is obtained according to the drude's model. at uv-c band frequencies, the dielectric constant of aluminum is about -12. dielectric constant of the top dielectric layer is in the neighborhood of 3. the aluminum thickness b is about 100 microns. according to eq. (1), since a layer of pmma of 30 micron in thickness has been coated on the top of the aluminum layer. the other condition required for surface plasmon resonance in the mi structure is [16]: k a εa + kb εb = 0 (2) where ka and kb are propagation constants for top dielectric layer a and the aluminum layer b. they can be computed using the following mathematical relationships [16]: k a 2= k x 2− εa k 0 2 (3) kb 2= k x 2− εb k 0 2 (4) ko is the propagation constant of vacuum in the horizontal axis. k x is the propagation constant in the direct ion of propagation. 2.2. surface plasmon resonance for the mim structure to attain this resonance condition in the mim structure (that is, the high-k dielectric between the aluminum layer and the bottom lead p late), the following criterion shown in eq. (5) and (6) must be met. the first condition is [16]: εb ab+ εc ac+ εd ad= 0 (5) where εb , εc and εd are respectively the dielectric constants of the aluminum layer, the high-k material and the bottom lead plate. in addition, ab, ac and ad are respectively the thicknesses of the aluminum layer, the high-k material and the bottom lead p late. dielectric constant of the high-k material is in the neighborhood of 10. the thickness of the bottom lead plate d is about 300 microns. according to eq . (5), the thickness of the high-k material should be 72 microns. the other condition required for surface plasmon resonance in the mim structure is [16]: kb εb + k c εc + k d εd = 0 (6) where kb , kc and kd are respectively propagation constants for the aluminum layer, the high-k material and the bottom lead plate. 3. negative ion source to counter balance the incoming positive charges accumulated on the top of the antenna, there must be a corresponding negative charge source. this negative charge source can be generated through frictions between two insulators. in this work, the two insulators are water and plastic. fig. 3 illustrates the whole system for harvesting energy from cosmic radiations and atmospheric ions. the sub-system highlighted by the box on the left is the negative ion source capable of generating a negative voltage with respect to the ground out of flowing water. in the negative ion source as shown in fig. 3, the ends of the plastic tube act as the water inlet and the water outlet. the water inlet and the water outlet are respectively fastened with metal ring a and metal ring b. these metal rings never touch water but, between the metal rings and the flowing water, the dielectric material must have a high dielectric constant. between these two metal rings, pin a, pin b and the ground pin are nailed into the plastic tube, submerging into the water flowing through the plastic tube. pin a is wired to metal ring b, whilst pin b is wired to metal ring a. the ground pin, gnd, is wired to the metal faucet. the ground pin can also be shorted to pin a without negatively affecting the measured results. since water is an insulator, running water through the plastic tube will generate static electricity in the inner surface of the plastic tube. assume that the water running at the region close to metal ring a is positively charged. metal ring a will be electrostatically induced to a negative potential, whilst pin a will carry a positive potential. since pin a is wired to metal ring b, the water at the region close to metal ring b and pin b will be negatively charged. the wire connection between pin b and metal ring a forms a positive feedback which amplifies their negative potential. by the same token, the wire connection between pin a and metal ring b forms another positive feedback, amplifying their positive potential. fig. 3 schemat ic view of the prototype modeling the whole atmospheric ions collecting system advances in technology innovation, vol. 2, no. 4, 2017, pp. 99 104 102 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti as shown in fig. 3, the ions in water tend to have a short-circuit effect on the pathway between pin a and the ground and on the pathway between the ground and pin b. to increase the negative charge for the antenna, it is important to decrease the mobility of ions in the region between pin a and the ground or in the region between pin b and the ground. 4. measurements the prototype as shown in fig. 3 has been constructed and its performance has been measured with and without sunlight in the eleventh floor of a building based in shenzhen. we have used a voltmeter (rigol dm3051) to measure the voltage across the diode as shown in fig. 3 at different times of the day. during the measurement, all the sources of electromagnetic disturbance has been removed, or placed very far away from the proposed system, to rule out any possibility of any non-cosmic energy source. the measurement setup is illustrated in fig. 4. the same measurement was taken repeated every lunch break and evening throughout the last month of autumn. our findings are summarized in the following table: table 1 measured voltage across the diode when the water was running at 150 cm 3 per second situations general o bservations final voltage starting voltage starting voltage between the top al layer and the ground with sunlight voltage rose steadily for 5 seconds ~680 mv 200 mv 350 mv without any sunlight voltage rose steadily for 5 seconds ~450 mv 200 mv 350mv fig. 4 measurement setup the voltage between pin a and the ground pin of the proposed negative ion source was very stable and it tends to increases when the water flow rate increases. when water flow rate increases, the final voltage across the diode also increases with approximately a delay of 2 seconds. this is due to the fact that the atmospheric ions that can be harvested are positively associated with quantity of negative charges from the negative ion source. when the bottom lead plate is disconnected from the negative ion source, however, the output voltage fell to around 10 mv and no significant voltage rise can be observed even in the presence of an uv light. the voltage between the top aluminium layer and the ground connection has been successfully used to charge up a 470 uf capacitor. the experimental setup was found to be highly sens itive to external electromagnetic disturbance. it was found that placing a lit compact fluorescent next to the proposed antenna can cause huge jump in the measured voltage. 5. discussions in this work, the process of ion harvesting, which is mainly driven by flowing water, does not necessitate consumption of fuels to operate. this water can flow from natural sources, including waterfalls, springs, heavy rainfall, tidal waves or rivers. flowing water carries ions which can be further polarized in the proposed negative ion source. the ions from the proposed negative ion source contribute to a potential difference which can be further increased by connecting the proposed negative ion source in series. the end result is that the output voltage will increases, depending on how many of these proposed negative ion source are connected in series. table 1 shows that the output voltages measured with and without sunlight are clearly very different. sunlight, background radiations or other forms of electromagnetic disturbance can lead to increased voltage across the diode, suggesting that there are indeed background radiations or atmospheric ions being captured. the quantity of the negative charges from the negative ion source determines how much and how fast the energy from atmospheric ions can be captured into a dc electricity. unlike a conventional solar panel, this energy can be continuously harnessed throughout the day. in general, the purer the water is, the more negative charges can be generated from the negative ion source. impure water contains ions which neutralize the generated electrostatic charges. however, our latest experimental results suggest that sea water yields a much higher voltage. increasing the ionization rate is the key to improve the efficiency of an atmospheric ion collector. the expression for rate of ionization at different altitudes, q(h) or different phases of solar cycle can be summarized by the following equation [17-21]: q(h)= ∑ i∫ ei ∞ ∫ a= 0 2π ∫ θ= 0 π 2 + δθ d(i)(e)( de dh ) (i) sin (θ )dθ dade q (7) where (de/dh) are ionization losses [23-24] of particles of type i, a is the azimuth angle and θ is the angle towards the vertical. dh takes into account that at a given height h that the particles can penetrate from the space angle (0, hmax=90+dθ ), which is g reater than the upper hemisphere angle (0, 90) for flat model. di((e) is the cosmic ray differential spectrum that can be used to calculate cosmic rays during different phases of solar cycle [16-18]. advances in technology innovation, vol. 2, no. 4, 2017, pp. 99 104 103 copyright © taeti ionizat ion in the atmosphere takes place as a result of cosmic radiat ions or ultraviolet radiations. mounting the atmospheric ion collector at high altitudes in theory can lead to higher ionization rates. mounting a device at high altitudes is not always practically rea listic. however, there are alternatives. at ground levels, air pollution is major source of positive ions that can be easily captured using the proposed device. other ionizat ion sources include the ultraviolet radiations from sporadic solar energetic particles, cosmic rays and the ions due to the natural radioactivity of the soil which is blamed for the unwanted radon gas. ultrav iolet radiations tend to be intensive in ozone depleted regions, where the air is usually saturated with positively charged air pollutants. during the process of electricity generation using the proposed technology, the negative charges from the proposed atmospheric ion collector will neutralize the positively charged pollutants in air to some extent. whether the energy comes from uv light, cosmic rad iations or from positively charged pollutants, the total of the energy that can be captured depends very much on the sun and the detectable solar activity. hence, it also depends on the diurnal (time of day) effect and a seasonal effect. levels of ionization tend to be low during the winter t ime because the sun is farther away. the activity of the sun is also associated with the sunspot cycle. there will be more solar rad iations when the sun is active. positive ions are known to be detrimental to our health. the atmospheric positive ions are electrostatically attracted to the body, which naturally carries negative charges, and cause oxidative damages. there have been published reports on the link between lack of negative ions in the body and ailments, including headaches, and/or fatigue [23-24]. in 2013, the international agency for research on cancer (iarc) even classified these particulates as a carcinogen [23]. in its evaluation, the iarc showed an increasing risk of lung cancer with increasing levels of exposure to outdoor air pollution and particulate matter. the process of energy harvesting, which is mainly driven by gravity, involves neutralization of atmospheric positive ions. harvesting atmospheric ions in areas plagued by air pollution is one of the few solutions to nullify the harmful effects of the excessive accumulation of positively charged pollutants in the atmosphere. 6. conclusions in this paper, we have proposed the use of flowing water for capturing atmospheric ions into a dc voltage. measurement has been performed with and without any sunlight. measured results suggest that atmospheric ions can be harvested to an observable extent by the proposed atmospheric ion collectors with or without a sunlight. the harvested energy is positively associated with the purity of water and the quantity of the negative charges from the negative ion source. acknowledgment this work is supported by sustech teaching innovation funds (jg201505), national natural science foundation of china (61401191), guangdong natural science funds for distinguished young scholar (2015a030306032), sustc funds (frgsustc1501a-51, frg-sustc1501a-65), and shenzhen science and technology innovation committee funds (jcyj20150331101823678). references [1] k. sheikh, “new concentrating solar tower is worth its salt with 24/7 power,” scientific american, 2016. [2] d. biello, “how to use solar energy at night,” https://www.scientificamerican.com/article/how-to-us e-solar-energy-at-night/, 2009. [3] h. v. cane and d. lario, “an introduction to cmes and energetic particles,” space science review, vol. 123, no. 1, pp. 45-56, 2006. [4] l. liu and p. solis, “the speed and lifetime of cosmic ray muons,” mit undergraduate, 2010. [5] n. tesla, “the eternal source of energy of the universe, origin and intensity of cosmic rays,” new york, 1932. [6] p. i. y. velinov, s. asenovski, k. kudela, j. lastovicka, l. mateev, a. mishev, and p. tonev, “impact of cosmic rays and solar energetic particles on the earth's ionosphere and atmosphere,” journal of space weather and space climate, vol. 3, 2013. [7] n. tesla, method of utilizing radiant energy, u.s. patent, 685,958, nov. 25, 1901. [8] h. plauson, conversion of atmospheric electric energy, u.s. patent, 1540998, jun. 9, 1925. [9] h. plauson, improvement in electric motors, british patent, 157,262, jul. 10, 1922. [10] h. plauson, process and apparatus for converting static atmospheric energy into dynamic electrical energy of any suitable high periodicity, british patent, 157,263, jul. 10, 1922. [11] w. i. pennock, apparatus for collecting atmospheric electricity, u.s. patent, 911,260, feb. 2, 1909. [12] l. g. smith, ionospheric battery, u.s. patent, 3,205,381, sep. 7, 1965. [13] t. yuki, method and apparatus for capturing an electrical potential generated by a moving air mass, u.s. patent, 533,237, jan. 15, 1985. [14] g. f. knoll, radiation detection and measurement, 4th ed. wiley, 2010. [15] http://ecuip.lib.uchicago.edu/multiwavelength-astrono my/images/infrared/history/transmission-page.jpg [16] a. i. smolyakov, “resonant modes and resonant transmission in mult i-layer structures,” progress in electromagnetics research, vol. 107, pp. 293-314, 2010. [17] v. perez, d. d. alexander, w. h. bailey, “air ions and mood outcomes: a review and meta-analysis”, bmc psychiatry, vol. 13, no. 1, p. 29, 2013. [18] r. a. baron, g. w. russel, and r. l. arms , “negative ions and behavior: impact on mood, memory, and aggression among type a and type b persons,” journal of personality and social psychology, vol. 48, no. 3, pp. 746-754, 1985. [19] s. wu, f. deng, j. huang, h. wang, m. shima, x. wang, y. qin, et al., “blood pressure changes and chemical constituents of particulate air pollution: results from the healthy volunteer natural relocation (hvnr) study,” environmental health perspectives, vol. 121, no. 1, pp. 66-72, 2013. [20] m. buchvarova and p. i. y. velinov, “empirical model advances in technology innovation, vol. 2, no. 4, 2017, pp. 99 104 104 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti of cosmic ray spectrum in energy interval 1 mev-100 gev during 11-year solar cycle,” advances in space research, vol. 45, no. 8, pp. 1026-1034, 2010. [21] r. sternheimer, “in fundamental principles and methods of particle detection,” methods of experimental physics, vol. v, a. nuclear physics, edited by l.c.l., yuan, and c. s. wu, new york, london, academic press, 1961. [22] m. ackermann, m. ajello, a. allafort, l. baldini, j. ballet, and g. barbiellini, et al., “detection of the characteristic pion-decay signature in supernova remnants”, science magazine, vol. 339, p. 807, 2013. [23] d. loomis, w. huang, and g. chen, “the international agency for research on cancer (iarc) evaluation of the carcinogenicity of outdoor air pollution: focus on china,” chin j cancer, vol. 33, no. 4, pp. 189-196, 2014. [24] k. sakakibara, “influence of negative ions on drivers,” r & d review of toyota crdl, vol. 37, no. 1, 2002.  advances in technology innovation, vol. 3, no. 4, 2018, pp. 179 184 evaluation of infill effect on mechanical properties of consumer 3d printing materials gabriel a. johnson, jesse j. french * department of mechanical engineering, letourneau university, longview, texas, usa received 20 july 2017; received in revised form 04 december 2017; accepted 05 december 2017 abstract during the additive manufacturing “boom” of the last decade, consumer level 3d printers have kept pace with commercial/industrial printers, both in numbers and features. however, in material characterization data, the access to date for the consumer has significantly lagged behind. consumer level 3d printers provide a significant asset to entrepreneurs, small businesses, universities, college students, and hobbyists due to the low initial capital cost and relatively low operational costs. commercial grade 3d printers and the associated filaments sold for their use typically have well documented material properties and print parameters. consumer 3d printers, however, typically have limited or no access to mechanical test data for their materials. this paper describes the work of the authors to fill the existing knowledge gap in the mechanical properties of consumer level 3d printer filament. astm tensile (d638) tests were performed on samples produced by two commercially available 3d printers. the materials tested include pla, abs, petg, various nylons, polycarbonate/abs, and asa filaments. samples were printed with infill percentages ranging from 15% to 100% to test for tensile properties. keywords: additive manufacturing, polymers, 3d printing, tensile testing, thermoplastics 1. introduction additive manufacturing, often referred to as 3d printing, gives companies and individuals the ability to rapidly design, test, and improve concepts, as well as the ability to mass-produce components. commercial machines, while expensive to own and operate, produce consistent and reliable printed components due to the mechanical testing and process optimization performed along with the development of the printer. thus far, the testing and process optimization for consumer-level machines has lagged. since some consumer 3d printing is employed by hobbyists, the strength of available printing materials has been considered irrelevant. however, for those producing load-bearing components with consumer-level 3d printers, the strength of printing-compatible materials are important. fig. 1 infill comparison for printed components * corresponding author. e-mail address: jessefrench@letu.edu advances in technology innovation, vol. 3, no. 4, 2018, pp. 179 184 copyright © taeti 180 astm (american society of testing and materials) standard d638, standard test method for tensile properties of plastics, was used as a guide for the testing procedure [1]. for this work, the infill percentages shown in fig. 1 were tested. the 15%-90% samples were a triangular infill, with infill lines at 0°, +60°, and -60° relative to the principle axis of the tensile specimen. due to the nature of the slicing software, the 100% sample had to be printed with solid layers in a ±45° orientation, relative to the principle axis of the specimen. although each material is printed at different temperatures with different travel speeds according to the needs of the material, the final geometry allows for direct comparison between materials. 2. materials tested in total, seven materials were tested for a total of three companies. polylactic acid (pla) is a common material for 3d printing [2]. it is relatively easy to print, but is somewhat brittle and has a low service temperature. acrylonitrile butadiene styrene (abs), often used for injection molded components, is likely the most common thermoplastic in use today [2]. abs can be more difficult to print due to layer bonding and warping issues, but has improved mechanical properties over the pla. polyethylene terephthalate glycol (petg), a thermoplastic co-polyester, is quickly becoming a more common material for 3d printing [3]. acrylonitrile styrene acrylate (asa) is a uv-stable thermoplastic, often used in the marine, auto, and rv industries due to its weathering resistance [4]. asa is similar to abs in terms of mechanical properties and printing parameters. polycarbonate/abs (pc/abs) is a blended thermoplastic, designed for high-heat applications [5]. pc/abs also has a high tendency to warp, though an enclosed build volume reduces the tendency to warp. petg produces parts with little to no warping, but can have a poor surface finish if improper printer settings are used. pla, abs, and petg were all purchased from the company makergeeks. the asa and pc/abs were purchased from another company. the nylon materials tested were all produced by the company taulman3d. nylon materials are known for their strength, chemical, and thermal resistance. nylon 645 is a specially designed nylon 6/9, optimized for improved tensile strength and improved optical clarity [6]. nylon 910 is a special form of nylon developed by taulman3d expressly for the purpose of 3d printing. it is extremely tough, strong, and resistant to high temperatures [6]. table 1 shows a summary of the published material properties for the materials tested in this work. σy is the yied stress, or the stress at which the material begins to rupture, leading to failure. table 1 approximate material properties of printed materials, taken from various sources material density [g/cm3] σy [mpa] modulus [gpa] failure strain [%] pla [12] 1.29 44.8 3.8 23.1 abs [13] 1.07 43.3 2.3 24.8 asa [4] 1.08 44.6 2.3 34.1 pc/abs [5] 1.17 56.0 2.7 63.3 petg [3] 1.27 65 3.0 109.0 nylon 6/6 [9] 1.14 75 2.8 50 3. specimen production the specimens tested in this work were produced using two commercially available printers, shown in fig. 2. table 2 shows a summary of the printing parameters used for each material and indicates which machine printed each sample. the pla, abs, petg, and nylon materials were printed from nominal 2.85mm printer filament, while the asa and pc/abs were printed from nominal 1.75mm printer filament. the dimensions of the samples were taken from the type 1 sample defined by the astm standard [1]. this specimen type was chosen since it is large enough for the printing infill to become a predominate component of the specimen strength. in fig. 2, the left image is of a commercially available, consumer-grade 3d printer, while the right image is of a printer constructed by the author from a kit of parts. simplify3d was used as the slicing software and all the printer gcode files were produced through it. samples were produced in groups of three according to infill percentage, labeled, and organized by sample type. samples with apparent flaws in the test section or radius, as well as samples that were warped, were reprinted. in order to improve print quality, all materials were dried for at least 24 hours in a desiccant-filled box advances in technology innovation, vol. 3, no. 4, 2018, pp. 179 184 copyright © taeti 181 heated to 45°c. filament drying is optional for some materials, but abs, asa, petg, nylon, and pc/abs materials are hydroscopic and must be dried prior to printing [7]. some materials with a high possibility of warping, such as the nylons or abs, were printed with a brim; a single-layer feature added by the slicing software to increase the bed contact area, thereby increasing adhesion and reducing warping. aside from the printing parameters mentioned in table 2, all samples were printed with three top/bottom layers, three perimeters, and a triangular infill pattern. the 100% infill samples were printed solid by forcing the slicing software to make top/bottom layers through the whole thickness of the part. the print cooling fan was used for pla, abs, and petg in order to improve the surface finish. previous work by lanzotti indicates that the number of external perimeters has a much larger effect on tensile strength than layer thickness, so layer thickness was chosen according to material-specific best practice [8]. (a) abs 15, 30, and 50% specimens mid-print on printer 1 (b) pc/abs 90% specimens min-print on printer 2 fig. 2 print parameters for all materials table 2 print parameters for all materials material printer temperatures [℃] (hot end/ bed) layer height [mm] print speed [mm/s] pla 1 215/70 0.21 45 abs 1 250/110 0.22 40 petg 1 245/70 0.25 45 nylon 910 1 235/100 0.25 30 nylon 645 1 235/110 0.25 20 asa 2 245/110 0.20 35 pc/abs 2 285/115 0.25 30 4. test method fig. 3 specimen loaded in tensile testing machine, prepared for test fig. 4 crazing marks visible on outside of abs 50% infill sample advances in technology innovation, vol. 3, no. 4, 2018, pp. 179 184 copyright © taeti 182 after printing, samples were removed from the print bed, post-processed to remove the brim (if present), labeled according to material, infill percentage, and specimen number, measured with digital calipers, and then tested. testing was performed using a mti 5k bench-top universal testing system fitted with serrated-jaw tensile grips and an epsilon strain extensometer rated for 10% strain. samples were loaded into the jaws, checked for vertical alignment, and then tested at a crosshead travel speed of 50 mm/min, as specified by the astm standard for rigid polymers [1]. fig. 3 shows an example of a specimen loaded in the tensile testing machine, prior to testing. after specimen failure, the extensometer was removed from the specimen and the specimen removed from the tensile jaws. failed specimens were retained for photography and analysis. due to supply limitations, only three samples each material was tested unless the sample needed to be retested due to a test failure. 5. results fig. 7 shows a summary of these results, comparing average tensile data from all materials tested. as expected, the tensile yield strength of the samples was directly affected by infill percentage. at 15% infill, all seven materials had a yield stress less than 25 mpa. the pc/abs was the strongest at 15% infill, while asa, abs, and nylon 910 tied for the lowest yield strength at 15% infill. as the infill percentage increased, the range of yield strengths also increased. at 30% infill pla had a yield strength of 30.1 mpa, while the nylon 910 had a yield strength of 13.1 mpa. the 50% infill samples had a tighter range of tensile strengths, varying from 30mpa (pc/abs) to 15.6 mpa (nylon 910). above 50% infill, the yield strengths began to increase significantly. at 75% infill, the petg had an average tensile yield strength of 36.1 mpa while the asa had an average tensile yield strength of 19.1 mpa. finally, at 100% infill, the nylon 910 had an average yield stress of 69.9 mpa, making it the strongest material tested. pla, which was the weakest material at 100% infill, had an average yield stress of 32.98 mpa. on an individual-material level, nylon 910 was the most affected by infill percentage; 12.7 mpa at 15% infill to 69.9 mpa at 100% infill, a difference of 57.2 mpa. pla, while weaker overall, varied considerably less than the nylon 910; 18.4 mpa at 15% infill to 32.9 mpa at 100% infill, a difference of 14.5 mpa. at 30% infill, the pla had the highest tensile strength of 30.1 mpa, a value higher than the 50% and 75% infill tensile strengths for the same material. petg varied from 16.4 mpa at 15% infill to 51.8 mpa at 100% infill, a variance of 35.4 mpa. fig. 5 comparison of ductile (top) and brittle (bottom) failure modes for two petg specimens. the top specimen is 100% infill while the bottom sample is 30% infill the modulus of elasticity is also dependent on infill percentage. as the infill percentage increases, so does the modulus. this effect can be seen in fig. 6, which show a comparison of different infill percentages within the petg material. the slope of the elastic region of the data line is the modulus of elasticity, which increases as the infill percentage increases. for the petg, the modulus increased from 0.69 gpa to 1.85 gpa as the infill percentage increased from 15% to 100%. fig. 5 shows how the 30% petg sample failed with almost no deformation, while the 100% sample exhibited necking prior to failure. nylon 910 varied from 0.34 gpa to 2.44 gpa as the infill increases from 15% to 100%. the remaining materials also indicate modulus dependence on infill percentage. advances in technology innovation, vol. 3, no. 4, 2018, pp. 179 184 copyright © taeti 183 in some materials, the infill percentage affected the failure mode of the specimens. for example, in fig. 5, the petg 100% infill specimen failed in a ductile manner, as indicated by the severe necking in the center of the reduced section. the bottom specimen in fig. 5, which was a petg 30% infill specimen, failed in a more brittle manner. these failure modes are supported by the data from petg tests shown in fig. 6; the curve for the 30% specimen fails without much plasticity (failure at 3.22% strain) while the 100% curve indicates plastic deformation (failure at 11.3% strain). the nylon 910 failed in a similar manner, though all of the 910 samples had some degree of plasticity prior to failure. all infill percentages of the pla samples failed in a brittle manner, with no visible necking or deformation prior to failure. the abs samples showed evidence of crazing, a change in color due to mechanical deformation, prior to failure [9]. fig. 4 shows an example of the crazing on an abs sample, as well as a cross section of the failed component. of particular interest in fig. 4 is the alignment of the crazing marks with the infill lines. the top of fig. 4 shows a cross section of the same sample shown in the center of fig. 4. many of the specimen failures occurred along an infill line, indicating that the infill pattern may cause a stress concentration. fig. 6 comparison of tensile data for petg samples. legend format: petg[% infill]-[sample number] fig. 7 average tensile strengths for all materials tested at a variety of infill percentages fig. 8 comparison of required infill percentages for same component strength while the 100% infill specimens are consistently the strongest, solid components take more time and material to produce. there exists a “sweet-spot,” a point at which material and time costs are minimized while component strength is maximized. for evaluation of this sweet-spot, consider a cube with 60mm sides (216 cm3 volume), that needs to have a tensile strength of at least 30 mpa. if any of the materials tested in this work were available, each would require a different infill percentage to achieve this strength. since the volume of polymer filament required directly affects the cost of printed components, required polymer volume is an important design consideration. fig. 8 represents this concept graphically, showing that in order to reach the desired tensile strength, different infill percentages need to be used depending on the material used. not represented in fig. 8, but still of importance to anyone designing a printed component, are the ultimate strain of the plastic, chemical resistance, and thermal-mechanical properties. evaluating the effect of infill on these mechanical properties is beyond the scope of this work. advances in technology innovation, vol. 3, no. 4, 2018, pp. 179 184 copyright © taeti 184 6. conclusions the data presented from this research provides a design basis for the designer seeking to create a component with a specific loading requirement. this project tested seven materials from three manufacturers of polymer filament. two consumer-grade, open-sourced 3d printers were used to fabricate the tensile specimens. at 100% infill, nylon 910 had the highest tensile strength at 69 mpa, while pla was the weakest at 33 mpa. as the infill percentage decreased, the range of tensile strengths for all materials was more tightly grouped, indicating that infill percentage has a significant impact on tensile strength. infill percentage was also found to affect modulus, elongation, and failure mode. references [1] astm, astm d638-14: standard test method for tensile properties of plastics, 2014. [2] lulzbot, “filament guide,” https://devel.lulzbot.com/filament/archive/lulzbot_3d_printing_filament_guide.pdf. [3] o. olabisi and k. adewale, handbook of thermoplastics, 2nd ed. boca raton: crc press, taylor & francis group, 2016. [4] 3dxtech, “3dxmax asa 3d filament,” http://www.3dxtech.com/content/asa_filament_v2.1.pdf. [5] 3dxtech, “3dxmax pc/abs 3d filament,” http://www.3dxtech.com/content/pc-abs_filament_v2.1.pdf. [6] taulman3d, “main features,” http://taulman3d.com/main-features.html. [7] t. landry, “beat moisture before it kills your 3d printing filament,” https://www.matterhackers.com/news/filament-and water. [8] a. lanzotti, m. grasso, g. staiano, and m. martorelli, “the impact of process parameters on mechanical properties of parts fabricated in pla with an open-source 3-d printer,” rapid prototyping journal, vol. 21, no. 5, pp. 604-617, 2015. [9] f. p. beer, e. r. johnston, j. t. dewolf, and d. f. mazurek, mechanics of materials, new york: mcgraw-hill, 2012. [10] matweb, “overview of materials for polylactic acid (pla) biopolymer,” http://www.matweb.com. [11] matweb, “overview of materials for acrylonitrile butadiene styrene (abs), molded,” www.matweb.com.  advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 implementation of adaptive embedded controller for a temperature process j. satheesh kumar 1,* , deepu sankar 2 1 department of electronics and instrumentation, dayananda sagar college of engineering, bangalore, india 2 department of electronics and instrumentation, karunya university, india received 08 december 2017; received in revised from 11 april 2018; accepted 18 august 2018 abstract the paper proposed and carried out an adaptive embedded control strategy with the help of arduino open hardware platform. the proposed control strategy is to carry out a cost-effective interface between the simulation software and a real-time process. the data acquisition and control is done with the help of arduino uno which has been interfaced with matlab simulink the control algorithms developed in simulink model can be downloaded into the arduino uno, working as a standalone controller. in this paper, various control algorithms are used to control the temperature process, including embedded modified model reference adaptive control (mmrac). its performance is compared to other control algorithms. the result shows that the mmrac scheme improves the transient performance of the temperature control system. keywords: embedded, control, matlab, simulink, mrac 1. introduction nowadays, the automation and control of most of the real-time systems are achieved by using a computer connected through the expensive data acquisition system (das). the specification and requirement of das depend on the software being used. the proposed methodology uses a low-cost das and an embedded system to develop a controller that can give better performance. the development of das and the controller in the same hardware improves the compactness of the proposed system. in this paper, the arduino uno micro controller is used for the development of das and controller. the control algorithm is developed using matlab simulink tool. tawanda [1] presented similar algorithm developments using simulink. the matlab simulink provides a platform to interface simulink with arduino uno through arduino io library and support package. the development of the control algorithm in the embedded system has become simpler by this approach. the early versions of the embedded target devices for simulink tool are expensive. the real-time interface (rti) developed by arduino uno, is cost effective. five different control algorithms, namely proportional control (p), proportional-integral control (pi), proportional integral derivative control (pid), model reference adaptive control (mrac) and mmrac were developed to control a temperature process using simulink. there are two ways to test the developed algorithm in real-time. one method is to use the arduino union, along with the matlab simulink running on the pc. another way is to use arduino uno as a standalone controller in real time. in the second case, after downloading the control algorithms in arduino uno microcontroller, the computer can be disconnected from it. the second method provides the flexibility of using the arduino uno as a standalone embedded controller. this embedded controller is used to control the temperature process in real-time environment. * corresponding author. e-mail address: jsatheeshngl@gmail.com tel: +91-9003368217 advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 95 the pid controller is used in process industries to control various processes. based on the necessity and nature of the process, the adaptive controller is considered as a suitable controller for many processes. mrac is one such adaptive controller. several adaptive control structures are discussed by [2] and [3]. the robustness of the control system are improved by combining both pid and adaptive control action. the result presented by [4] shows the improved performance by the addition of pid in adaptive control. a modified control scheme of mrac is discussed in this paper. in the modified mrac, pid controller action is included. the error given to the pid controller is derived from the model output and the process output. the combined action of the pid controller and mrac drives the final control element in the process. this adaptive controller will give better settling time and efficiency compared to mrac. therefore an arduino aided mmrac is another main aspect of the paper. the most significant property of a real-time interface in matlab simulink and arduino uno helps in the development of standalone controller. hence this work is identified as an adaptive embedded controller for a temperature process. 2. simulink-arduino real time interface matlab and simulink have been associated with engineering and academic world as a design and development tool. the method of linking, design, and development into the real-time process in an optimized way is a challenging task. standard data acquisition cards are available to facilitate the real-time interface. data acquisition systems for matlab are discussed in [5]. software specific data acquisition systems are used in many cases; however, these das can only be used in a specific software application and may not be compatible with other applications, and such systems are presented in the article [6]. matlab provides the platform to interface the simulink with the real-time process through the arduino io package or arduino support package. the simulink model can be developed using the arduino io library blocks. the required control algorithms are developed using simulink and arduino support package. the arduino support package converts the simulink model to code, which runs directly on arduino uno. therefore the arduino uno can be disconnected from the host computer, and it controls the real-time process independently. 3. experimental analysis the experiment is conducted in a thermal process analyzer, it includes a thyristor controlled electric furnace and an air blower. the air blower acts as a load variable in the process. the blower speed can be varied manually to introduce the disturbance. the controlled variable is the furnace temperature and the manipulated variable is the control voltage, to the thyristor-based power control system. fig. 1 block diagram of thermal process control systems the above mentioned experimental setup is the prototype of a thermal process. the control system block diagram for the thermal system is shown in fig. 1. according to the desired temperature, the control voltage is determined from the control advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 96 algorithm, which is present in the microcontroller. the temperature measurement is made with the help of lm35 precision integrated-circuit temperature sensor. the output voltage of this sensor is linearly proportional to the centigrade temperature and the scale factor is 10mv per degree centigrade. the temperature range of this sensor is -55°c to 150°c. the measured temperature is acquired with arduino uno which is a microcontroller based on the atmega328. a thyristor-based power control circuit is used to regulate the temperature of the furnace. the control voltage for the thyristor-based power control circuit determines the temperature of the furnace by regulating the ac supply voltage using a pulse width modulation method. the control voltage is obtained from the arduino uno. typically the control voltage is an analog signal. since arduino uno supports only digital outputs an external digital to analog convertor (dac) is used. dac circuit is designed using dac0808 which is an 8-bit monolithic digital-to-analog converter. the control voltage from dac is given to a thyristor-based power control for proper temperature regulation. 4. embedded adaptive controller the possibilities of embedded controller implementation using simulink are summarized in this section. the real-time implementation of an adaptive controller using simulink requires a target device. the various kinds of target devices compatible with simulink are micro controllers, digital signal processors (dsp) and xpc target. most of the target devices are costly and unbearable for a smaller level projects. the real-time control by xpc target using simulink is developed as mentioned in [7] and [8]. the xpc target devices are compatible with high-performance industrial computers. the dsp based embedded platform provides the facility of model conversion from simulink to real-time environment. it gives the flexibility of an interfacing more number of peripheral devices. among these target devices, microcontrollers are the cheapest device used in an embedded system. in microcontroller category also various processors are available, some of the processors are atmega, arm processors, etc. the arm processor-based embedded adaptive controller is developed as presented in [9]. arduino is one of the microcontrollers used for the development of embedded controllers. control algorithm development by arduino integrated development environment (ide) is discussed in [10]. through ide, arduino can be programmed using embedded programming. the ide based control algorithm development is a bit complex and time-consuming. the simulink model-based program is not possible with ide. the arduino support package facilitates the simulink model-based programming in arduino. in this paper, a control algorithm is implemented in arduino uno using the arduino support package. the process temperature is read by ic-based temperature sensor lm35. arduino reads the temperature of the thermal system through its pin number 1. since the arduino is having 10-bit analog to digital convertor (adc), the maximum adc value is 1024 and the reference is given 5v. the scaling has to be done properly to get the process temperature. as per the data sheet, the output of lm35 is 10mv/ºc. the actual temperature is found by eq. (1). 5 ( c) 0.483 1024 0.01 out out v t v      (1) where 𝑉𝑜𝑢𝑡 is the output of lm35 in decimal equivalent. the equivalent temperature value is given to the control algorithm to compute the required control signal. the control signal is sent to its digital output pins as shown in fig. 2. the control signal generated is converted into 8-bit data and is given to 8 digits write blocks. integer to bit converter block demands only integer values, hence a rounding function is used before it. the 8-bit conversion requires the multiplication of the control signal with constant so that the 0-5v will be converted to 0-255. the multiplication constant 51 is chosen to convert 0-5 range to 0-255 range. the 8-bit digital outputs are sent to digital pins 4, 5, 6, 7, 10, 11, 12 and 13 of arduino. the thyristor-based control circuit requires an analog voltage. hence these digital signals are converted into analog signal by a digital to analog convertor (dac). an external dac is used for this conversion. advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 97 fig. 2 data acquisition system 4.1. implementation of p, pi, and pid controllers fig. 3 p, pi & pid controllers using simulink arduino support package the real-time implementation of p, pi and pid controllers using simulink arduino support package is shown in fig. 3. the developed control algorithm is downloaded into arduino to work as a standalone controller. all the three control functions are achieved using the same matlab subfunction by properly enabling the proportional, integral and derivative gains. the setpoint is given to pin number 2 of the arduino uno using a potential divider circuit. this circuit provides the output in the range of 0-5v to pin number 2 of arduino uno. the provision for adjusting the setpoint is also properly scaled based on eq (1). the integral controller may experience the integral windup in real-time process control. the pid control algorithm includes the anti-reset windup algorithm to reduce integral windup. the data acquisition system for the thermal process shown in fig. 3 is illustrated in fig. 2. advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 98 4.2. development of mathematical model for the temperature process the laboratory-based temperature process analyzer consists of a smaller size furnace. the operating region is in between 25°c to 80°c. process reaction curve method is used to find the mathematical model of the process. the feedback in fig. 3 is removed. the initial steady state is noted. a step input of known magnitude is given to pin number 2 of the arduino at time t1. the time at which the process variable begins to change is noted as t2. the process variable is allowed to reach the new steady state. the difference between t1 and t2 is the dead time of the process. the change in the process variable is computed by subtracting the new steady state of the initial steady state. time taken by the response to reach 63.2% of process variable change is noted as t3. the time constant of the process is the difference between t3 and t2. the process gain is calculated by dividing the magnitude of the final steady state by the magnitude of the change in step input. the derived model is a first-order system with the dead time process. the model of the system is given in eq. (2). 101.2 ( ) 55 1 se g s s    (2) 4.3. implementation of model reference adaptive control adaptive control is one of the widely used control strategies to design advanced control systems for better performance and accuracy [11]. model reference adaptive control (mrac) is a direct adaption strategy with an adjustable mechanism to adjust controller parameters. the implementation of mrac for the first order process is carried out as discussed in [12]. the mrac works on the principle of adjusting the control parameters so that the output of the actual plant tracks the output of a reference model having the same reference input [13]. the implementation of mrac and the design of adjustment mechanisms are referred to from [14]. the reference model is used to give an ideal response of the adaptive control system to the reference input. the controller is usually described by a set of adjustable parameters. in this paper two adjustable parameters, θ1 and θ2 are used to describe the control law. adaptive mechanism is used to alter the parameters of the controller so that the actual plant could track the reference model. mathematical approaches like mit rule, lyapunov theory, and theory of augmented error can be used to develop the adjusting mechanism. since the experimental thermal process is a first order system, mit based mrac for a first order system is followed for the development of controllers. the model of the temperature process and the reference model are given in eqs. (3) and (4). ( ) g( ) ( ) y s b s u s s a    (3) where y is the output from the process and u is the control input to the process. ( ) ( ) ( ) m m m c m y s b g s u s s a    (4) where my is the reference model output and the 𝑢𝑐 is the command signal to the reference model. the controller equation is given in eq. (5). 1 2 cu u y  (5) where 1 and 2 are the controller parameters, y is the measured temperature and u is the controller output. advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 99 fig. 4 mrac using simulink arduino support package as per the mit rule, the controller parameter has to be changed in the direction of the negative gradient of cost function j. the cost function is chosen in this application is given in eq. (6) and the rate of change of controller parameter is described in eq. (7) e    is known as sensitivity derivative. 21 2 j e (6) ' ' d j e e dt            (7) where e is the error given in eq. (8). me y y (8) where y is the process output and it is described by eq. (9). from eqs. (3) and (5), y is derived. 1 2 c b y u s a b      (9) the controller parameters are obtained from eqs. (8) and (9). the denominators of sensitivity derivatives are approximated as per eq. (12). 1 2 c e b u s a b       (10) advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 100 2 2 e b y s a b       (11) 2 ms a b s a    (12) the mit rule is applied to determine the controller parameters. the sensitivity parameters given in eqs. (10) and (11) are substituted in eq. (7) to find out the controller parameters. the parameters b and ma are combined with adaptation gain ' . the equations for updating the controller parameter 1 are given in eqs. (13) and (14). similarly, the other controller parameter 2 is updated using eqs. (15) and (16). '1 m c c m m d ab u e u e dt s a s a                       (13) 1 m c m a u edt s a             (14) '2 m m m d ab y e y e dt s a s a                       (15) 2 m m a y edt s a             (16) where  is the adaptation gain, cu is command signal, e is an error and y is the measured process variable. practical implementation leads to integral windup due to the integrator present in the equations. hence anti-reset windup is also included in the control algorithm. the reason for reset windup is the accumulation of the input to the integrator. the accumulated value leads to the saturation of the controller output. the anti-reset algorithm helps to remove the integral windup. the anti-reset windup procedure includes a saturation block, which limits the controller output. the controller output before the saturation block is subtracted from the controller output after the saturation block. the subtracted output is added to the input of the integrator. this procedure will not allow the integrator to accumulate its output. this procedure doesn’t have any effect till the controller output is below the saturation value because the subtracted value before and after the saturation block is zero. once the controller output begins to increase from the maximum value, the anti-reset windup procedure will start functioning. the same anti reset procedure is used in all the controller implementations described in this paper. the controller implementation is shown in fig. 4. the control signal from the algorithm is limited to 5v using the saturation block in the simulink. as shown in fig. 2, this output from the saturation block is converted into corresponding digital output. using a dac the digital output is converted to analog and given to the thyristor-based power control circuit to control the furnace temperature. 4.4. implementation of modified model reference adaptive control in order to improve the transient performance of the control system, the mrac scheme is modified [15]. in the modified mmrac, classical pid control action is also included. the modified controller output u is derived as per the eq. (17). the controller parameters 1 and 2 have the same purpose similar to the mrac. the mmrac is developed by subtracting the effect of pid controller action from the mrac [16]. 1 2 c p i d de u u y k e k edt k dt            (17) advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 101 where pk , ik and dk are the proportional, integral and derivative gains for the pid controller. the optimal values of pid controller parameters are appropriately chosen to provide the best process regulations. fig. 5 mmrac using simulink arduino support package even though many tuning procedures are available, choosing pid controller parameters is a challenging task for control engineers, hence for a real-time process, control engineers prefer trial and error method [17]. the derivative action of pid control improves the predictive nature of the control system and improves the speed of response. it predicts future controlled output by computing the rate of change of error and accordingly takes the control action to minimize the error. the integral action removes the offset in the controlled variable. the integral windup due to the integral action is removed by the anti-reset windup procedure mentioned in the previous section. hence the modified control scheme includes all the advantages of pid control and mrac. the integrator's used in the computation of 1 and 2 also produces reset windup; hence the same anti-reset windup procedure is followed to remove the integral windup. the real-time implementation of the modified model reference adaptive controller is shown in fig. 5. the control algorithm is developed using simulink arduino support package. the real-time interface is developed by the help of analog input block and the digital output block. the data acquisition system for the thermal process analyzer is developed in the subsystem as shown in fig. 2. the setpoint of the standalone mmrac is set with the help of the knob present in the hardware. the value set by the user is read by the controller and it is properly converted into engineering units. the control algorithm compares both the reference model output and the actual process output. the computed controller parameters force the process to follow the reference model. the computation is based on eq. (17) so that the change in the controller parameter minimizes the error. according to the control algorithm, the desired control signal is sent to the thyristor-based power control circuit to control the temperature. advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 102 5. results and discussion the classical pid controller algorithm and model-based algorithm was developed in this research. real-time implementation using the microcontroller is simplified by this approach. the experimental setup shows the actual electric furnace with a blower. the thyristor-based power control circuit, controller implementation using simulink and the arduino uno with the peripheral circuits are also depicted in fig. 6. the control algorithms developed in this work are p controller, pi controller, pid controller, mrac and mmrac. the required control algorithm was downloaded into the arduino uno hardware. the electric furnace was allowed to settle at two different temperatures 40°c and 60°c. the controller performance was observed by plotting the response of the temperature control system with respect to time. the transient performance of the system is analyzed for all the controllers. fig. 6 experimental setup 5.1. controller observation and response the following control algorithms p, pi, pid, mrac, and mmrac were implemented in real time. a comparative analysis has been made using the available data. the temperature of the furnace is plotted in graphs with respect to time. the response of the furnace for the setpoint of 40°c is shown in fig. 7. since the setpoint is 40°c and it is closer to the room temperature, the process takes around 20 seconds to reach the setpoint. the rise time of the process varies with respect to the controllers used. the response of the furnace for the setpoint of 60°c is shown in fig. 8. since the process lag for the electric furnace is considerably high, it takes around 200 seconds to reach the setpoint. the time from 200 seconds to 380 seconds is used for the comparative analysis. fig. 7 comparative response of furnace for 40°c setpoint fig. 8 comparative response of furnace for 60°c setpoint 5.2. performance analysis the performance of the controller is analyzed using the settling time. the tolerance limit for the settling time is 1%. the comparative analysis is listed in table 1. the mmrac in real time shows better performance when compared with other advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 103 controllers. the other performance metrics are not considered, because except for pi and pid controllers, other controllers have very negligible oscillations or zero oscillations around the setpoint. so there is no overshoot or negligible overshoot for proportional control, mrac and mmrac. the settling time of the process using mrac and mmrac, for the setpoint of 40°c is less than the rise time. the settling time and rise time are the same for the process using mrac and mmrac, for the setpoint of 60°c. in all operating regions, mrac and mmrac respond quickly to the process parameter changes and take the corrective action. table 1 performance analysis controller set point = 40°c set point = 60°c settling time (sec) rise time (sec) settling time (sec) rise time (sec) p 100 100 320 370 pi 80 30 230 240 pid 60 20 220 230 mrac 40 50 220 220 mmrac 20 30 210 210 6. conclusions the arduino open hardware platform is used as a low-cost data acquisition system and controller. p, pi, pid, mrac, and mmrac are implemented in the arduino microcontroller using matlab simulink. the performance analysis is made in terms of settling time. the developed embedded controller provides the platform to implement any type of complex control algorithms. this will help in the field of process control to implement complex algorithms with low-cost devices. the embedded based mmrac controller shows better performance over the other controllers mentioned in this paper. hence, the system under study is best suited for mmrac. this work may be extended by developing intelligent controller using the arduino microcontroller. implementing complicated algorithms can be simplified by using the real-time interface developed in this paper. hence the proposed methodology will be beneficial to academic institutions and research organizations in testing and implementing various sophisticated algorithms. conflicts of interest the authors declare no conflict of interest. references [1] t. mushiri, a. mahachi, and c. mbohwa, “a model reference adaptive control system for the pneumatic valve of the bottle washer in beverages using simulink,” proc. international conference on sustainable materials processing and manufacturing (smpm 17), elsevier, january 2017, pp. 364-373. 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[6] s. humayun, maria mehmood, and faran mahmood, “developing a labview and matlab-based test bed for data acquisition, analysis and calibration of frequency generators over gpib,” international journal of computer applications, vol. 40, pp. 11-15, february 2012. [7] handbook of networked and embedded control systems. birkhauser boston, university of maryland, 2008. [8] d. hercog, a. rojko, m. curkovic, b. gergic, and k. jezernik, “embedded platform for rapid implementation of local and remote motion control experiments,” przeglad elektrotechniczny, vol. 87, pp. 73-76, march 2011. [9] m. engin, “design and control applications of mechatronic systems in engineering,” 1st ed. london: intec, 2017. advances in technology innovation, vol. 4, no. 2, 2019, pp. 94-104 104 [10] a. m. el-nagar, “embedded intelligent adaptive pi controller for an electromechanical system,” isa transactions, vol. 64, pp. 314-327, september 2016. 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[17] l. guessas and k. benmahammed, “adaptive backstepping and pid optimized by genetic algorithm in control of chaotic,” international journal of innovative computing information and control, vol. 7, pp. 5299-5312, september 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 2, no. 2, 2017, pp. 34 39 34 synchronized injection molding machine with servomotors sheng-liang chen, hoai-nam dinh*, van-thanh nguyen institute of manufacturing information and systems, national cheng kung university, tainan, taiwan received 30 march 2016; received in revised form 25 april 2016; accepted 01 may 2016 abstract injection mold ing machine (imm) is one of the most important equipment in plastic industry. as a cyclic process, injection molding can be divided into three steps includes filling process, packing-holding process and cooling process, among which filling process and packing process are both most important phases for the quality of part, and the corresponding crucial process variables are injection velocity and packing pressure in filling and packing phases. moreover the determining a suitable injection time, screw position and cavity pressure for transfer from injection velocity control to packing pressure control which is commonly called filling to packing switchover point is also critical for high quality part. this study is concerned with two research aspects: double servomotors synchronization control for injection unit, and filling to packing switchover methods. the simulation result of switching method based on injection time and ball screw position those are similar, and the result of switching method based on the cavity pressure that is better. keywords: servo motors, synchronization, velocity to pressure switchover, pressure control, injection molding machine. 1. introduction injection mold ing machine used servo motor to save energy and suit for precise products. plastic in jection molding an extensive range of modern injection molding machines means that most custom mold ing requirements can be met. plastic inject ion moldings will be manufactured using the most cost effective production methods. the injection process included heating process and injecting the material into the mold [1]. the process produces are very quickly with great accuracy. it is widely accepted that all-electric injection molding machines are the most energy efficient of the three technologies [2]. in [3], there analysis and give some solution about clamping system. hydrau lically driven injection translates the movement offering high force combined with high speed or electric servomotors has created the groundwork for realizing linear electromechanical screw movement with stronger force and more accurate. in this research, we focus only 2 phases, filling phase and packing phase, each of them has distinct control requirement and how to switchover from one to other. in the filling phase, the position and velocity of the in jection screw are controlled ensure the correct melt front velocity. at the beginning of the packing phase, the cavity pressure is controlled at a higher boost pressure to ensure correct part weight. after that, the cavity pressure is controlled at a lower pressure to maintain the part quality and avoid over packing. it ends after the gate freezes off. 2. methodologies and system modelling design 2.1. methodologies control of an in jection mold ing machine consists of many aspects. however, in this research we focus on designing controller for injection unit and techniques in filling phase and packing phase. the required injection force is so large but servo motor is employed that means designing control system for inject ion unit is extremely important. even an injection molding machine with perfect in jection unit control system but that does not mean the product quality is assured. as discussed previously, to achieve high quality product, the process variable, cavity pressure is controlled. and the most difficult but most important in controlling cavity pressure is how to switchover from filling phase to packing phase. when the required inject ion force or pressure is so large but because of energy saving, cost effective, environment pollution and flexi* corresponding author, email: dinhhoainam52@gmail.com advances in technology innovation, vol. 2, no. 2, 2017, pp. 34 39 35 copyright © taeti ble, the servo drive is a good choice for the injection unit drive system. however, the servo drive has power limitation, if the capacity of the injection mold ing machine is huge so one servo motor cannot supply enough power and it costs a lot. that is why double servo motor is employed in the inject ion unit drive system. how to make them go smoothly with the same mot ion is one of the research objectives and the other is in vestigat ing some methods to switchover between filling phase and packing for our application. the specific objectives of the present work are:  design a control system to control two servo motors move with the same motion. double servo motors drive the in jection unit and they are controlled in order to achieve a high stable large injection force or pressure.  investigate some methods of switchover filling controlling and packing controller. 2.2. system modelling design fig. 1 the schematic of the injection molding control system [4] the present work uses pc-based control system. the servo drives communicate with the controller via ethernet. the controller sends command to the servo drives and receives the encoder feedback signals from the servo drives. the cavity pressure is measured by a load cell and it communicates with the controller v ia rs232. the data are monitored on the screen and can be collected by input output programming. the control algorithms and the human machine interface are written in visual c # 2005, as shown the overall in jection molding control system in fig. 1. servo motor system identification and characterizat ion: the first step in the system identification stage is collecting data that are input and output in operat ing system. then system identification is done by using the system identification toolbox in matlab. the transfer functions in z domain are obtained. the systems here consist of servo drive and servo motor, and the velocity controller is integrated in the driver. so, the transfer functions are the velocity closed loops. system identificat ion verificat ion: verify the system identification result by comparing simulation and experiment. that means with the same commands one passes by the physical system the others passes by the transfer function, and then compare the outputs . control system design: the transfer functions of two servo motors are obtained; control theory is applied to design the control system. more specific, first, design individual motor controller and then design controller for double servomotors control system. all steps are simulated in matlab and simulink. after that, the controller algorithms are written in computer programs, the performance of the controllers are tested, and the controller parameters can be tuned and adjusted. with acceptable synchronous error, two servomotors are connected to a timing belt and this system will drive a ball screw. 3. double servomotors control system 3.1. control system design according to the different parameters of system are input, are calculated and converted from control signals to drive motors, then applied to machine. four servo motors control moving p laten slip on main t ie bar. servo motor as drive in jection machine, servo motor speed stability and high precision position control, in addition to control effect of allowing high reproducibility can also fine-tune the speed control and position control. fig. 2 structure of motors block control in injection machine advances in technology innovation, vol. 2, no. 2, 2017, pp. 34 39 36 copyright © taeti the purpose of motion control system is used to calculate the random variable consists of slide motion, velocity. developing state-space form, the governing equations can be written by using the rotational speed and electric current are the state variables. u l i l r l k i k j b idt d m mm m                                   1 0 (1) 𝑦 = [1 0] [ 𝜔𝑚 𝑖 ] (2) where l is the winding inductance, r is the winding resistance, b is damping coefficient, i is the current, u is the armature voltage, k is the torque gain, 𝜔𝑚 is the rotational velocity, j is the armature (rotating part of motor) moment of inertia. some experiences have done, we find the transfer function of two servo motors with 2000rpm, and position outputs are measured. the transfer functions from velocity command to velocity output of two ac servo motors can be expressed in laplace variable s. 243.002812.0 06412.062.14 21    ss s g (3) 4279.06198.0 708.123.14 22    ss s g (4) the cross coupled control system min imizes synchronous errors in mult i-axis mot ion control system [5]. it is common used in cnc motion control system. technology of cross couple control is developed for multi axis [6]. the parallel technique control in mult i parallel system was proposed [7]. the technique used feedback signal as positional signal and velocity signal to modify the command signal. this control has simple structure, and easy to implement. however, some possible effects can decrease the performance of this control method, for example, unmatched sinusoidal disturbances; reduction degrades the stability, unmatched model. utilize the advantages of the control methods above, combination between them was made. the new synchronous controller is mentioned in [8]. th is controller can overcome the difficulty of the master slave control method and utilize the advantages of the synchronous controller and the relative dynamic stiffness motion control. we have realized that cross-coupled control is used to increase the coupling relationship between axes. it also makes the capacity of disturbance better, decrease the error model. however, the measuring performance cannot improve in each axis. enconder 1/s controller1 c1(s) filter1 motor 1 g1(s) angular velocity angular position+ enconder 1/s controller1 c2(s) filter2 motor 2 g2(s) angular velocity angular position + position average fig. 3 block diagram of cross-coupling controller of two motor the errors of coupling axis are determined by the difference between the angular position and the average angular position. to tracking the same trajectory input, where appropriate filter s . in this case the control laws adopted for all system 4. pressure control and velocity to pressure switch control 4.1. velocity to pressure after two servomotors are synchronized, we connect them to a ball screw by a timing belt in fig. 4 [9]. assume that, the gear ratio is unity, the pitch radius of the ball screw is equal to the shaft radius of the motor, and the thread lead of the ball screw is 5mm. so now, the motion command of the ball screw can be computed from the motion command of the motor. the ball screw position x and the ball screw linear velocity v are expressed by the following equations. fig. 4 schematic of the injection unit drive system [9]   360 h x mm (5) advances in technology innovation, vol. 2, no. 2, 2017, pp. 34 39 37 copyright © taeti   / dx v mm s dt  (6) in which, θ is the motor position in degree, and h is the thread lead of the ball screw in mm. when ball screw move, the cavity pressure will be changed when the mold is closed. assume we can measure the cavity press by a load cell. but the difficulty is how to call calculate the pressure command. in this study we don’t jump into the theoretical way, for example, with a given material, mold, and parameters of the mechanisms we have to calculate the pressure command via mathematics way. but we will use a practical approach. because the servomotors are stet-upped in the velocity control mode that means the final command to the driver is velocity command, so the pressure command has to be transferred into the velocity command. the relationship between them is found by finding the relationship between the pressure feedback and the velocity feedback. the velocity of the ball screw is computed from its position by taking a discrete derivative. the procedure to connect pressure to velocity is shown in fig. 5. fig. 5 conversion of pressure into velocity procedure 4.2. pressure control cavity pressure measurement is crucial for process parameter. the flow of the plastics is increase in high pressure injection. in low pressure case, the flow of the p lastic also reduces . and the cavity pressure during the packing phase is the key variab le to ensure the complete filling and the weight of the final product. but we can see the performance of the pressure controller in a whole cycle. a pressure controller is designed to make sure the output cavity pressure follow the command cavity pressure command. the closed loop pressure is show in fig. 6. the pressure controller is a simple p roportional controller and the proportional gain is tuned by try-and-error method. fig. 6 the closed loop pressure 4.3. switchover from velocity to pressure filling to packing switchover is known as velocity to pressure switchover, where velocity refers to injection velocity and pressure to packing pressure. in the filling phase, the velocity of the inject ion screw is controlled ensure the correct melt front velocity. at the beginning of the packing phase, the cavity pressure is controlled at a higher boost pressure to ensure correct part weight. after that, the cavity pressure is controlled at a lower pressure to maintain the part quality and avoid over packing. it ends after the gate freezes off. the velocity to pressure switchover structure is shown in fig. 7. the most important in velocity to pressure switchover is how to locate the switching point. if switchover occurs too late, cause an over-packed cavity, characterized by a pressure peak in the packing phase. the pressure peak will not reduce to the lower holding pressure until the switchover because the high injection pressure is still applied after volumetric filling. switching over early may generate an under-packed cavity, characterized by a pressure drop in the packing phase. load cell function change unit from pressure to velocity kp driver position velocity pressure fig. 7 flow chart of inject processing machine as we know that the reference input command is velocity, but output is pressure. therefor we must find the relation between velocity and pressure. following [6], relation between displacement, axial motor input differential pressure and flow rate is founded as 1 2 1 ( ) [ ( ( )) ( ) 2 ( ( )) ( )] q t g y t ps p t g y t ps p t     (7) where q(t ), p(t) are flow rate and d ifferential pressure of motor input, ps is source pressure, g1(y(t)), g2(y(t)) are conductance of all edges of value calculates by advances in technology innovation, vol. 2, no. 2, 2017, pp. 34 39 38 copyright © taeti   1 2 ( ( )) ( ( )) 0 ( ) gk y t b if y t b g y t if y t b         (8) 2 2 ( ( )) ( ) ( ( )) 0 ( ) gk y t b if y t b g y t if y t b        (9) 5. simulation and experiment results the present work uses pc-based control system. the servo drives communicate with the controller via ethernet. the controller sends command to the servo drives and receives the encoder feedback signals from the servo drives. hardware is use in this study is provided by foxnum company. it includes controller, servomotors and servo drivers . servo driver can connect to controller via a communication card comm3. the simulation stage follows the control system design stage. we show the s imulation results step-by-step, the error of master and slave motors in fig. 8. w ithout synchronous controller, the error will increase. in fact, even we select the same motors, but it will happen. with synchronous controller, the error is compensated. that makes the error reduce so much. the performance of the closed loop pressure with the proportional gain kp = 2.0 is show in fig. 8. at the beginning of the cycle, the output pressure cannot track the pressure command but when time goes on nearly 2seconds, the output can track the command. it is easy to recognize that in the injection phase the system is a non-linear system that is why only a simple proportional controller cannot deal with. however, our purpose is to control the cavity pressure during the packing phase, and at this interval, time is larger than 2 second, the out pressure can follow the pressure command. if the system is non-linear in any phase, especially in packing phase, we must take its properties into account. until now, we can just only make sure two motors can tracking the command. how is about the synchronous position error between them? we cannot predict it in the physical system, because when some controllers are employed, they will take action every t ime to compensate the errors. even the feedback controller can eliminate the steady sate error, the feed forward controller can reduce the tracking error, but at the transient state, two motor response very differently. using synchronous controller to decrease the synchronous error of motors fig. 8 performance of the closed loop pressure fig. 9 synchronous error with synchronous controller and without synchronous controller fig. 10 synchronous position error, without synchronous controller and with synchronous controller from fig. 10 we get the comparison the maximum absolute of synchronous error between using with synchronous controller and using without synchronous controller. fig. 11 tracking position error of motor 1 and motor 2 advances in technology innovation, vol. 2, no. 2, 2017, pp. 34 39 39 copyright © taeti we may consider now, when the synchronous controller is added into the system, it has effect on the performance of the overall control system or not? so, we have to study about some properties of the overall system. two important properties of a control system are time response and tracking erro r. so, we can see time response of motor 1 and motor 2 in fig. 10 and fig. 11. the position errors of two motors have a little suddenly values. the overall control is better than using open loop controller. table 1 the value of synchronous position error system without synchronous controller with synchronous controller maximum absolute of synchronous error 2.0304 0 1.2300 0 6. conclusions this research focuses on two subjects: (1) design and implement control algorithm for double servo motors and their application to the injection unit control system. in particu lar, the present work utilizes these advanced algorithms on the injection unit that is driven by double servo motors; and (2) investigate some methods to switchover from filling phase to packing phase for our application. the accomplishments in this research involve modelling, control algorithm implementat ion , s imulat ing , and experimental implementation. control system can be made more intelligently with artificial intelligence techniques. the advent of low cost very large scale integrated microprocessor and the proficiency of hardware, control algorithms can be implemented in the hardware to get high response and performance. references [1] “injection molding” http://www.custompar tnet.com, 2009. [2] a. kanungo and e. swan, “all electric injection molding machines: how much energy can you save?” proceedings from the thirtieth industrial energy technology conference, new orleans, la, usa, may 6-9, 2008. [3] f. johannaber, “injection molding machines: a user’s guide,” 3rd ed. hanser munich vienna: new york, 1994. [4] “f70i injection molding machine control sy stem” http://www.foxnum.com/product021_en.aspx [5] y. koren,, “cross-coupled biaxial computer control for manufacturing systems ,” journal of dynamic systems, measurement, and control, vol. 102, no. 4, pp. 265-272, 1980. [6] marvin h.cheng, cheng-yi chen and aniruddha mitra, “synchronization controller synthesis of mult i-axis mot ion system,” international journal of innovative computing information and control, vol.7, pp. 918-921, july 2011. [7] o. s. kwon, s. h. choe, and h. heo, “a study on the dual-servo system using improved cross-coupling control method,” 10th international conference on environment and electrical engineering (eeeic’11), may 2011, pp. 1-4. [8] m. f. hsieh, c. j. tung, w. s. yao, m. c. wu and y. s. liao, “servo design of a vertical axis drive using dual linear motors for high speed electric discharge machining,” international journal of machine tools and manufacture, vol. 47, no. 3-4, pp. 546-554, 2007. [9] n. akasaka, “a synchronous position control method at pressure control between multi-ac servomotors driven in inject ion molding machine,” in sice 2003 annual conference, vol. 3, pp. 2712-2719, aug. 2003.  advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 effects of unsteady aerodynamic pressure load in the thermal environment of fgm plates chih-chiang hong* department of mechanical engineering, hsiuping university of science and technology, taichung, taiwan, roc. received 13 august 2017; received in revised form 14 october 2017; accepted 20 october 2017 abstract the effects of unsteady aerodynamic pressure load with varied shear correction coefficient on the functionally graded material (fgm) plates are investigated. thermal vibrat ion is studied by using the first -order shear deformation theory (fsdt) and the generalized differential quadrature (gdq) method. usually, in the fgm analyses, the computed and varied values of shear correction coefficient are the function of the total thickness of plates, fgm power law index, and environment temperature. the effects of environment temperature and fgm power law index on the thermal stress and center deflection of airflow over the upper surface of fgm plates are obtained and investigated. in addition, the effects , with and without the fluid flow over the upper surface of fgm plates, on the center deflection and normal stress are also investigated. keywords: aerodynamic pressure, varied shear correction coefficient, fgm, thermal vibration, gdq 1. introduction there are some investigations of aerodynamic pressure load on the functionally graded material (fgm) p lates and shells. in 2015, fazelzadeh et al. [1] studied the effects of volume fraction, aspect ratio and non-dimensional in-plane forces on the nanocomposite fgm plates under the action of supersonic aerodynamic pressure. in 2015, lee and kim [2] investigated the structure characteristics of fgm panels under supersonic aerodynamic force. in 2013, rafiee et al. [3] calculated and studied the nonlinear vib ration of piezoelectric fgm shells under combined electrical, thermal, mechanical and aerodynamic loading. in 2012, ghadimi et al. [4] investigated and studied the thermal flutter characteristics of cantilever fgm plates under supersonic aerodynamic loads. in 2012, prakash et al. [5] computed and investigated the large amplitude flexural v ibration characteristics of fgm plates with supersonic airflow by using the finite element method (fem). in 2008, sohn and kim [6] presented and examined the thermal buckling and flutter characteristics of fgm panels under aero -thermal loads. in 2007, fazelzadeh and hosseini [7] studied and investigated a turbo-machinery fgm rotating blades beam under supersonic aero-thermo-elastic loading. in 2007, wu et al. [8] calcu lated and analyzed the dynamic stability of fgm plates subjected to aero-thermo-mechanical loads by using the moving least squares differential quadrature method. in 2007, navazi and haddadpour [9] investigated the aero-thermo-elastic stability margins of fgm plates and panels in the supersonic flow. in 2006, prakash and ganapathi [10] investigated supersonic flutter behavior of fgm plates and flat panels by using the fem . there are some computational investigations of generalized differential quadrature (gdq) in the composited fgm plates and shells. in 2017, hong [11] investigated the effects of varied shear correction on flutter value of the center deflection and the thermal v ibration of fgm shells in an unsteady supersonic flow. in 2015, tornabene et al. [12] presented a survey of strong formulat ion fem focused on the numerical investigation of differential quadrature method. in 2014, hong [13] studied the thermal v ibration and transient response of terfenol-d fgm plates by using the gdq method and considering the first -order * corresponding author. e-mail address: cchong@mail.hust.edu.tw advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 110 shear deformat ion theory (fsdt) model and the varied modified shear correct ion factor effects. in 2014, hong [14] investigated the rapid heating induced vibration of terfenol-d fgm circular cylindrical shells by using the gdq method and without considering the effects of shear deformation. in 2013, hong [15] presented the thermal vib ration of terfenol-d fgm shells by using the gdq method and also without considering the effects of shear deformat ion. in 2012, hong [16] studied the thermal vibrat ion of rapid heating for terfenol-d fgm plates by using the gdq method and considering the fsdt effects. in 2009, tornabene and viola [17] presented the free vibration analysis of fgm panels and shells by using the gdq method and considering the fsdt model. it is interesting to study and investigate the thermal stresses and center deflection of gdq computations by considering the fsdt and the varied effects of the shear correct ion coefficient of airflow over the upper surface of fgm plates with four edges in simply supported boundary conditions. environment temperature and fgm power law index two parametric effects on the thermal stress and center deflection of airflow over the upper surface of fgm plates are also obtained and investigated. the effects of with and without the fluid flow over the upper surface of fgm plates on the center deflection and normal stress are also calculated. fig. 1 fluid flow over the upper surface of two-material fgm plates 2. formulation for fluid flow over the upper surface of two-material fgm plates is shown in fig. 1 with thickness h1 of fgm material 1 and thickness h2 of fgm material 2. the material properties are considered in the most dominated property young’s modulus efgm of fgm with standard variation fo rm of power law index rn, the others of material properties are assumed in the simple average form [18]. the properties of indiv idual constituent material of fgm are functions of enviro nment temperature t. the time-dependent, linear fsdt equations of displacements u, vand w\ of fgm plates are assumed in the following [19]. ),,(),,(0 tyxztyxuu x (1) ),,(),,(0 tyxztyxvv y ),,( tyxww  where u 0 and v 0 are d isplacements in the x and y axes direction, respectively, w is t ransverse displacement in the z axis direction of the middle-plane of plates,  x and  y are the shear rotations, t is time. the normal stresses (σ𝑥 and σ𝑦 ) and the shear stresses (σ𝑥𝑦 , σ𝑦𝑧 andσ𝑥𝑧) in the fgm plate under temperature d ifference ∆𝑇 for the k th layer can be obtained as follows [20-21]. )()( 662616 262212 161211 )( k xyxy yy xx kk xy y x t t t qqq qqq qqq                                         (2) )()(5545 4544 )( kxz yz kkxz yz qq qq                        advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 111 where α𝑥 and α𝑦 are the coefficients of thermal expansion, α𝑥𝑦 is the coefficient of thermal shear, �̅�𝑖𝑗 is the stiffness of fgm plates. ε𝑥, ε𝑦 and ε𝑥𝑦 are in-p lane strains, not negligible ε𝑦𝑧 and ε𝑥𝑧 are shear strains. the temperature difference between the fgm plate and curing area is given by the following equation. ),,(),,( 1*0 tyxt h z tyxtt  (3) in which t0 and t1 are temperature parameters in functions of x, y, and t, h * is the total thickness of plates. the dynamic equilibrium d ifferential equations of flu id flow over the upper surface of fgm plates can be represented and obtained in matrix fo rm [15, 21]. in the matrix elements, there are some coefficients (aij, bij, dij), (i,j = 1,2,6), ai*j*,(i * , j * = 4, 5) with partial derivatives of displacements and shear rotations . the external loads are subjected to f1,..., f5 with partial derivatives of thermal loads (𝑁, 𝑀), mechanical loads (p1, p2, q) and inertia terms (𝜌, h, i). in which (aij, bij, dij), ai*j*, f1,..., f5 and (𝜌, h, i) are in the following expressions. 11 p y n x n f xyx        (4) 22 p y n x n f yxy        22 2 3 ** hzhz t w m u x w m u qf              y m x m f xyx      4 y m x m f yxy      5 , dzztqqqmn xyy h h xxx ),1()(),( 1612 2 2 11 * *     (5) dzztqqqmn xyyx h hyy ),1()(),( 2622 2 2 12 * *    dzztqqqmn xyyx h hxyxy ),1()(),( 6626 2 2 16 * *    * * 22 2 ( , , ) (1, , ) , ( , 1,2,6) h ij ij ij ijh a b d q z z dz i j    * ** * * * * *2 2 , ( , 4,5) h hi j i j a k q dz i j   (6) dzzzih h h ),,1(),,( 22 2 0 * *  (7) in which 𝑘𝛼 is the shear correction coefficient, 𝜌0 is the density of ply. the values of 𝑘𝛼 are usually functions of h * , t, and rn. q is the aerodynamic pressure load for the unsteady, in viscid fluid flow over the upper surface of fgm plate with free stream density 𝜌∞ , velocity 𝑈∞ , and mach number 𝑀∞ . advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 112 the simple forms of �̅� 𝑖𝑗 and �̅�𝑖∗𝑗∗for fgm plates were introduced by shen [22] in 2007 and used to calculate normal, shear stresses and aij. the modified shear correction factor 𝑘𝛼 can be derived and obtained directly from the total strain energy principle derivation as follows for the fgm plates [13] by considering the varied value effect of 𝑘𝛼 on the plates. * 1 fgmzsv k h fgmziv   (8) in which the expressions of fgmzsv and fgmziv are functions of h * , rn, the poisson’s ratios vfgm, the young’s modulus of the fgm constituent materials e1 and e2 of the fgm plates, respectively. the dynamic gdq d iscrete equations in matrix notation can be derived and obtained for the dynamic equilibrium differential equations by considering four sides simply supported, fluid flow over the upper surface of fgm plates. the gdq method was presented by shu and richards in 1990 [13, 23-25]. 3. computational results to study and obtain the gdq results of varied shear correct ion coefficient calcu lations with plates layers in the stacking sequence (0°/0°), under four sides simply supported boundary condition, no in-plane distributed forces (p1 = p2 = 0) and under the external aerodynamic pressure load (q) of airflow over the upper surface of fgm plates with 𝜌∞ = 0.00000678𝑙𝑏/𝑖𝑛3, 𝑈∞ = 23304𝑖𝑛 /𝑠 and 𝑀∞ = 2 at altitude 50,000ft. the following coordinates xi and yi for the grid points numbers n and m of fgm plates are used 1 0.5 [1 cos( )] , 1, 2, ..., 1 i i x a i n n       (9) 1 0.5 [1 cos( )] , 1, 2, ..., 1 j j y b j m m       the displacement and temperature of thermal vibrat ions are used in time sinusoidal form as follows for a simple case study. )sin()],(),([ 0 tyxzyxuu mnx  (10) )sin()],(),([ 0 tyxzyxvv mny  )sin(),( tyxww mn * * 2 2 2 ( , ) sin( ) ( , ) cos( ) mn mn mnz h z h u uw x y q t w x y t m x m                 (11) 0 1* [ ( , ) ( , )]sin( ) z t t x y t x y t h    (12) and with the temperature parameter in the following simple vibration 0),(0 yxt (13) )/sin()/sin(),( 11 byaxtyxt  in which 𝜔𝑚𝑛 is the natural frequency in mode shape numbers m and n of the plates, γ is the frequency of applied heat flux, �̅�1 is the amplitude of temperature. advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 113 the sus304 (stainless steel) for fgm material 1 and the si3n4 (silicon nitride) for fgm material 2 are used in the numerical gdq computations. firstly, the dynamic convergence study of center deflection amplitude w (a/2, b/2) (unit mm) in airflow over the upper surface of fgm plates are obtained in table 1 by considering the varied effects of shear correction coefficient and with h * = 1.2 mm, h1 = h2 = 0.6 mm, m = n = 1, rn =1, 𝑘𝛼 = 0.149001, t = 100k, 1 100t k , t = 6s. the error accuracy is 7.2e-05 for the center deflection amplitude of a / b = 1, a / h * =10. the 17×17 grid point can be considered in the good convergence result and treated in the following gdq computations of time responses for deflection and stress of fgm plates. it might be mentioned that the deformations of plates usually increase with the increasing a / h * for the cases of non thermal loads. however, in the table1 shows the absolute values of center deflection for thin a / h * =100 are much smaller than that for thick a / h * =10 and 5 due to the phenomenon effect of thermal loads. in the fgm plates (𝐵𝑖𝑗 ≠ 0), varied values of 𝑘𝛼 are usually functions of h * , rn and t. for a / h * =10, a / b = 1, h * from 0.12mm to 2.4 mm, h1 = h2, calculated values of 𝑘𝛼 under t =100k are shown in table 2, used for the gdq and shear calculations. for h * = 0.12mm, values of 𝑘𝛼 (from 0.109359 to 1.08902) are increasing with rn (from 0.1 to 2). for h * = 1.2mm, values of 𝑘𝛼 (from 0.891024e-01 to 0.508881) are increasing with rn (from 0.1 to 10). for h * = 2.4mm, values of 𝑘𝛼 (from 0.836925e-01 to 0.118029e-02) are small decreasing with rn (from 0.1 to 10). usually, the values of 𝑘𝛼 are dominantly in the inverse proportion to h * at a given values of rn and t, e.g. values of 𝑘𝛼 (firstly 0.109359, then 0.891024e-01, finally 0.836925e-01) are decreasing with h * (from 0.12mm, then 1.2mm to 2.4mm) at rn = 0.1 and t =100k. table 1 dynamic convergence of airflow over the upper surface of fgm plates a / h * gdq method deflection w (a/2, b/2) at t = 6s 𝑁 × 𝑀 a / b = 0.5 a / b = 1 a / b = 2 100 13 × 13 0.166916e-18 -0.864896e-16 -0.113379e-14 15 × 15 0.166916e-18 -0.864895e-16 -0.113379e-14 17 × 17 0.166914e-18 -0.864888e-16 -0.113378e-14 14 13 × 13 -0.270625e-14 -0.436330e-12 -0.948251e-10 15 × 15 -0.270623e-14 -0.436326e-12 -0.947482e-10 17 × 17 -0.270623e-14 -0.436324e-12 -0.944192e-10 10 13 × 13 -0.190895e-13 -0.318221e-11 -0.674404e-09 15 × 15 -0.190895e-13 -0.318221e-11 -0.673224e-09 17 × 17 -0.190893e-13 -0.318244e-11 -0.674404e-09 8 13 × 13 -0.703716e-13 -0.118106e-10 -0.323377e-08 15 × 15 -0.703718e-13 -0.118357e-10 -0.466268e-08 17 × 17 -0.703708e-13 -0.118450e-10 -0.595615e-08 5 13 × 13 -0.108713e-11 -0.170468e-09 0.259696e-06 15 × 15 -0.108830e-11 -0.167507e-09 0.271164e-06 17 × 17 -0.108713e-11 -0.174309e-09 0.278226e-06 table 2 varied shear correction coefficient 𝑘𝛼 vs. rn under t =100k h* (mm) 𝑘𝛼 rn = 0.1 rn = 0.2 rn = 0.5 rn = 1 rn = 2 rn = 5 rn = 10 0.12 0.109359 0.140739 0.288792 0.687883 1.08902 0.989219 0.878104 1.2 0.891024e-01 0.939102e-01 0.111874 0.149001 0.231364 0.415802 0.508881 2.4 0.836925e-01 0.828082e-01 0.815941e-01 0.796610e-01 0.632624e-01 0.219191e-01 0.118029e-02 secondly, the amplitude of center deflection w (a/2, b/2) (unit mm) for the airflow over the upper surface of fgm plates is calculated. fig. 2 shows the response values of center deflection amplitude w (a/2, b/2) (unit mm) versus time t in fgm plate for a / h * =10, 14 and th in a / h * = 100, respectively, a / b = 1, h * = 1.2 mm, h1= h2= 0.6mm, rn = 1, 𝑘𝛼 = 0.117077, t =653k , 𝑇1=100k, starting time t = 0.001s and t =0.1s-3.0s with time step is 0.1s. the absolute value of center deflection amplitude is 7.04e-12mm occurs at t = 0.2s, the steady state value of center deflection is -4.54e-12mm for a / h * =10. the absolute value of center deflection amplitude is 1.31e-12mm occurs at t = 0.1s, the steady state value of center deflection is -6.21e-13mm for a / h * =14. the absolute values of center deflection for thin a / h * =100 are much smaller than that for a / h * =10 and 14. advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 114 (a) w (a/2, b/2)versus t for a / h * = 10 (b) w (a/2, b/2)versus t for a / h * = 14 (c) w (a/2, b/2) versus t for a / h * = 100 fig. 2 w (a/2, b/2) versus t for a / h * = 10, 14 and 100 (a) x  versus z for a / h * = 10 (b) xz  versus z for a / h * = 10 (c) x  versus t for a / h * = 10 (d) x  versus t for a / h * = 14 fig. 3 stresses versus z and t for a / h * = 10, 14 and 100 (continued) -1.0e-11 -5.0e-12 0.0e+00 5.0e-12 0 0.5 1 1.5 2 2.5 3 w (a/2, b/2) t -2.5e-12 -1.3e-12 0.0e+00 1.3e-12 2.5e-12 0 0.5 1 1.5 2 2.5 3 w (a/2, b/2) t -2.5e-12 -1.3e-12 0.0e+00 1.3e-12 2.5e-12 0 0.5 1 1.5 2 2.5 3 w (a/2, b/2) t -1.2e-03 -8.0e-04 -4.0e-04 1.0e-19 4.0e-04 8.0e-04 -0.5 -0.25 0 0.25 0.5 𝜎𝑥 z / h* -1.6e-12 -1.2e-12 -8.0e-13 -4.0e-13 -0.5 -0.25 0 0.25 0.5 𝜎𝑥z z / h* -9.20e-04 -9.15e-04 -9.10e-04 -9.05e-04 -9.00e-04 0 0.5 1 1.5 2 2.5 3 𝜎𝑥 t -9.140e-04 -9.135e-04 -9.130e-04 -9.125e-04 -9.120e-04 0 0.5 1 1.5 2 2.5 3 𝜎𝑥 t advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 115 (e) x  versus t for a / h * = 100 fig. 3 stresses versus z and t for a / h * = 10, 14 and 100 normal stress 𝜎𝑥 and shear stress 𝜎𝑥𝑧 are three-dimensional components and usually in functions of x, y, and z. typically their values vary through the plate thickness for the airflow over the upper surface of fgm plates. fig. 3(a) shows the normal stress 𝜎𝑥 (unit gpa) versus z and fig. 3 (b) shows the shear stress 𝜎𝑥𝑧 (unit gpa) versus z at center position (x = a / 2, y = b / 2) of plates, respectively at t = 0.1s, a / h * =10 and a / b = 1. the absolute value (9.15e-04 gpa) of normal stress 𝜎𝑥 at z = 0.5h * is found in the much greater value than the value (1.3e-12 gpa) of shear stress 𝜎𝑥𝑧 at z = 0.5h * , thus the normal stress 𝜎𝑥 can be treated as the dominated stress for the airflow over the upper surface of fgm plates. figs. 3(c)-3(e) shows the time responses of the dominated stresses 𝜎𝑥 (unit gpa) at the center position of outer surface z = 0.5h * as the analyses of deflection case in fig. 2 for l / h * =10, 14 and thin l / h * =100, respectively. the maximum absolute value of stresses 𝜎𝑥 is 9.15e-04 gpa occurs constantly in the periods t =0.2s-3s for l / h * =10. fig. 4 shows the center deflection amplitude ( / 2, / 2)w a b (unit mm) versus t for all different values rn (from 0.1 to 10) of fgm plates calculated and varied values of k  , for the airflow over the upper surface of fgm plates * / 10l h  , / 1a b  , * h = 1.2 mm, 1 h = 2 h = 0.6 mm, 1 100t k , at 3t  s. the maximum value of center deflection amplitude is 1.22e-11mm occurs at 653t k for rn = 10. the center deflection amplitude values are all small, decreasing versus t from 653t k to 1000t k , for rn = 2, 5 and 10, they can withstand for higher temperature ( 1000t k ) of environment. the center deflection amplitude values are all small, increasing versus t from 653t k to 1000t k , for rn = 0.1, 0.2 and 0.5. fig. 4 w (a/2, b/2) versus t fig. 5 shows the dominated stresses x  (unit gpa) at the center position of outer surface * 0.5z h versus t for all different values rn of fgm plates as the analyses of deflection case in fig. 4. the absolute values of dominated stresses x  versus t are increasing (from 100t k to 653t k ) and then decreasing (from 653t k to 1000t k ) for rn = 1, all decreasing (from 100t k to 1000t k ) for rn = 10, all increasing (from 100t k to 1000t k ) for rn = 0.1, 0.2, 0.5 and 2. -9.1250e-04 -9.1225e-04 -9.1200e-04 0 0.5 1 1.5 2 2.5 3 𝜎𝑥 t -1.5e-11 -1.0e-11 -5.0e-12 0.0e+00 5.0e-12 1.0e-11 1.5e-11 0 250 500 750 1000 rn=10 rn=5 rn=2 rn=1 rn=0.5 rn=0.2 rn=0.1 w (a/2, b/2) t advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 116 fig. 5 x  versus t the effects of with and without the fluid flow over the upper surface of fgm plates on the center deflection and normal stress for / 1a b  , * h = 1.2 mm, 1 h = 2 h = 0.6 mm, 1 n r  , k  = 0.117077, 653t k , 1 100t k are also considered as follows. the fig. 6 (a) shows the response values of center deflection amplitude ( / 2, / 2)w a b (unit mm) versus time t for * / 10a h  with and without airflow over the upper surface of fgm plates. the absolute values of center deflection amplitude for without airflow (0.111079 mm) are much greater than that with airflow (5.26e-14 mm) at t = 0.001s for * / 10a h  . fig. 6 (b) shows the normal stress x  (unit gpa) versus z at the center position ( / 2, / 2x a y b  ) of plates at t = 0.001s for * / 10a h  with and without airflow over the upper surface of fgm plates. the normal stresses are almost in the same values for with ( x  =-9.12e-04 gpa at * 0.5z h ) and without ( x  =-9.25e-04 gpa at * 0.5z h ) airflow cases. (a) w (a/2, b/2) versus t for a / h * = 10 (b) w (a/2, b/2) versus t for a / h * = 10 fig. 6 w (a/2, b/2) versus t and x  versus z for a / h * = 10 with and without airflow 4. conclusions in this study, the gdq solutions have been obtained and investigated for the deflections and stresses in the thermal vibration of fgm plates by considering the varied effects of shear correction coefficient and the airflow over the upper surface of fgm plates. the gdq results have shown that varied values of k  are usually functions of * h , rn and t. the absolute value of center deflection amplitude is 7.04e-12 mm occurs at t = 0.2s for * / 10a h  at 653t k . the center deflect ion amplitude values are all small and decreasing versus t from 653t k to 1000t k , for rn = 2, 5 and 10, the fgm plates also can withstand for higher temperature environment. references [1] s. a. fazelzadeh, s. pouresmaeeli, and e. ghavanloo, “aeroelastic characteristics of functionally graded carbon nanotube-reinforced composite plates under a supersonic flow,” computer methods in applied mechanics and engineering vol. 285, pp. 714-729, march 2015. -1.1e-03 -1.0e-03 -9.0e-04 -8.0e-04 -7.0e-04 -6.0e-04 -5.0e-04 0 250 500 750 1000 rn=10 rn=5 rn=2 rn=1 rn=0.5 rn=0.2 rn=0.1 𝜎𝑥 t -0.20 -0.15 -0.10 -0.05 0.00 0.05 0 0.5 1 1.5 2 2.5 3 without air flow with air flow w (a/2, b/2) t -1.2e-03 -8.0e-04 -4.0e-04 1.0e-19 4.0e-04 8.0e-04 -0.5 -0.25 0 0.25 0.5 without air flow with air flow 𝜎𝑥 z / h* advances in technology innovation, vol. 3, no. 3, 2018, pp. 109 117 copyright © taeti 117 [2] c. y. lee and j. h. kim, “evaluation of homogenized effective p roperties for fgm panels in aero-thermal environments,” composite structures, vol. 120, pp. 442-450, february 2015. 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[25] c. shu and h. du, “implementation of clamped and simply supported boundary conditions in the gdq free vibration analyses of beams and plates,” international journal of solids and structures , vol. 34, no. 7, pp. 819-835, march 1997.  advances in technology innovation, vol. 2, no. 3, 2016, pp. 95 98 95 zinc sulfide buffer layer for cigs solar cells prepared by chemical bath deposition rui-wei you, yen-pei fu* department of materials science and engineering, national dong-hwa university, hualien, taiwan received 21 march 2016; received in revised form 28 may 2016; accepted 02 june 2016 abstract in this study, zns thin films were successfully synthesized by chemical bath deposition (cbd) with starting materials of nh2-nh2, sc(nh2)2, and znso4‧7h2o. zns thin films were deposited with different time on glass substrates by cbd at 80 o c and ph=9. based on x-ray diffraction (xrd) patterns, it is found that the zns thin films exh ibit cubic polycrystalline phase. it was found that the optimum deposition time is 90 min for preparing zns thin film that is suitable as buffer layer for cuin1-xgaxse2 solar cells. the thin film deposited for 90 min has high transmittance up to 80% in the spectra range from 350 nm to 800 nm, and the optical band gap is about 3.59 ev. keywords : zns, buffer layer, chemical bath deposition, thin film solar cells , optical property 1. introduction zinc sulfide is a wide-band-gap semiconductor with a range of potential applications in optoelectronic devices. generally, in thin film so lar cells based on cuins2, cuinse2 , cu(in,ga)se2, cu(in,ga)(sse)2, (cigsse), the buffer layer is mainly the ii-vi type semiconductor, such as cadmium sulfide (cds) and zinc sulfide (zns) thin film [1]. the buffer layer with ii-vi type semiconductor is a direct gap semiconductor. the band gap of cadmium sulfide is 2.26~2.5 ev, and zinc sulfide is larger than 3.5 ev [2]. the highest efficiency is up to 19.9%, if the cuin1-xgaxse2 thin film solar cell combined with cadmium sulfide buffer layer at present [3]. for fear of cadmium (cd) toxicity damages our environment, we have to choose a free-cadmium process for preparation of buffer layer. we utilize zinc sulfide as buffer layer and the efficiency of cuin1-xgaxse2 thin film solar cell with zinc sulfide buffer layer is up to 18.6% [4]. consequently, there is no toxicity in the use of zinc sulfide and that can lower and lighten the influence on the environment. the buffer layer located between zno windows layer (n-type semiconductor) and cuin1 -xgaxse2 absorp t ion layer (p -type semiconductor) is able to eliminate the band discontinuity. the zns buffer layer requires high optical transmission and allows photon to reach absorption layer to excite electron, and then electron-hole pairs (ehp) are generated. if the buffer layer is too thick, photoelectron can’t pass through the layer and reach to electrodes. on the contrary, the layer is too thin that couldn’t separate absorption layer and transition conduction electric layer (tco). for better performance, the thickness of thin film should be controlled in the range of 30-50 nm. chemical bath deposition (cbd) method has been used for many years to prepare zns large-area and uniform thin film, and it can be prepared under room temperature [5]. utilizing the cbd method produces nano-structure thin film of zinc sulfide with smooth surface and uniform composition, and it improves the efficiency of cuin1-xgaxse2 thin film solar cell. in this study, we attempt to prepare the uniform zinc sulfide thin film by cbd technique using nh3oh, nh2-nh2, sc(nh2)2, and znso4•7h2o as s tart ing materials , and invest igate its characterizations such as structural, compositional and optical properties. 2. method in this study, zns thin film buffer layer prepared by chemical bath deposition process . zinc su lfate (znso4 •7h2 o) and th iourea (sc (nh2)2) were used as the source of zinc ions and sulfide ions, respectively. the reaction s o* corresponding author, email: ypfu@mail.ndhu.edu.tw advances in technology innovation, vol. 2, no. 3, 2016, pp. 95 98 96 copyright © taeti lu t ion was obtained by mixing 0.1m znso4•7h2o, 0.3m sc(nh2)2 , and 1.5m n2h4, whereby hydrazine (n2h4) was used as a complex agent. the ph of the reaction solution was adjusted to 9 by ammonia (nh3oh), reaction solution temperature was controlled at 80 o c and the rotational speed of stirrer was controlled in 50 rpm. soda-lime g lass substrates were used as substrates for the deposition of zns films. before deposition, the substrates were ultrasonically cleaned with acetone, rinsed with deionized water and dried in air. to investigate the effect of deposition time on properties of zns, the substrates were collected every 30 minutes in which the deposition-time is set in the range of 30 to 180 min. then these samples were cleaned by deionized water and dried with a n2 gas stream. in order to obtain crystalline zns, these as-deposited zns specimens required a post-annealing in a tube furnace for l h under ar atmosphere at 300 o c. the average roughness of the zns films was investigated by surface profile measuring system (alpha-step, veeco dektak 3 st). the co mposition of zns thin films was analyzed by energy dispersive spectrometer (eds, horiba noran instrument). the crystalline phase of the annealed zns films were characterized by x-ray diffractometer (xrd, rigaku d/ max-2500 v) with a wavelength of 1.5406å from the cukα radiation with 2θ ranging from 20 o to 60 o . opt ical p ropert ies o f th in films were characterized by an uv-vis spectrometer (jasco v-650 spectrophotometer). the band gaps (eg) of zns films were determined by the relat ionship of the transmittance and thickness of the film. 3. results and discussion fig. 1 shows x-rays diffraction of the zinc sulfide thin film annealed at 300 o c for 1 h under argon atmosphere. zns exists with two structures, one is cubic with zinc-blende type the other is hexagonal with wurtzite type. zns thin films prepared via the chemical bath deposited are highly disordered, but it can be transformed into a wurtzite-2h phase by annealing [6]. göde et al. reported that an amorphous zns film obtained at bath temperature of 60–70 o c and a wurtzite-2h phase acquired at 80 o c [7]. in this study, zns thin film prepared by cbd is zinc-blend type with cubic structure being in correspondence with jcpds card no. 79-043. the xrd pattern reveals a wide diffraction peak from 25 o to 30 o . there are three d iffraction peaks corresponding to (111), (220) and (311); however, the diffract ion peaks in (200) and (311) are not clear indicating the zinc sulfide thin film with low crystallization. fig. 1 x-rays diffraction pattern of zns thin film at deposition time of 90 min, then annealed at 300 o c for 1h under ar atmosphere to understand the effect of the deposition time on the composition of films, the energy dispersive spectrometer (eds) was used to analyze the atomic rat io of zn/s listed in table 1. it is found that the ratio of zn/s is close to 1 for films with various deposition times. table 1 the composition ratio of zn/s at different deposited time composition deposition time (min) 30 60 90 120 150 180 zn (atom %) 50.4 51.9 50.3 51.2 50.8 49.8 s (atom %) 49.6 48.1 49.7 48.8 49.2 50.2 fig. 2 the thickness of zns films as a function of deposition time, after annealing at 300 o c for 1 h under ar atmosphere advances in technology innovation, vol. 2, no. 3, 2016, pp. 95 98 97 copyright © taeti fig. 2 shows the zns film thickness as a function of deposition time. apparently, the relation between thickness and deposition time is divided into two stages, the first stage is the linear growth for thin film and the thickness grows from 124 nm to 252 nm in the period of 30 ~ 120 min. however, the second stage is the exponential growth; the thickness significantly increases from 352 nm to 750 nm for deposition time from 120 to 180 min. at the second stage, the zns film undergoes homogeneous nucleation. as deposition time increasing above 150 min, homogeneous particles begin to deposit on the substrate leading the significant enhancement in g rowth rate of thin film. tab le 2 is zns thin film thickness and roughness as function of deposition time. the average roughness of film for deposition time of 30 min is significantly high due to the facts that the heterogeneous deposition on substrate is still not uniform at the initia l stage. as deposition time from 30 to 120 min, the roughness is relatively lower and the thin films become uniform gradually. when deposition time for 180 min, the rate of homogeneous deposition on substrate increased, and the average roughness of zns film is increased up to 94 nm. table 2 the thickness and average roughness for zns films with different deposition time deposition time (min) 30 60 90 120 150 180 thickness (nm) 124 160 249 252 358 750 average roughness (nm) 87 30 58 34 32 94 fig. 3 shows the optical transmittance in the wavelength range of 300 800 nm for the zns films deposited on the sodium glass substrates as a function of different deposition time. the zns films reveled h igh optical trans mittance in the range of 70 ~ 80% at visib le wavelength; therefore, the films are suitable as buffer layers in cigs-based solar cells. the h ighest transmittance of 85% is located about wavelength of 425 nm for deposition time of 90 min. as deposition time increased from 90 to 150 nm, the absorption edge shifted gradually from 400 nm to 500 nm. the sharp absorption feature is due to the uniform zns thin films and the low concentration of defects in the films. however, as the deposition time increased, th ickness became th icker, and more homogeneous particles deposited on the glass substrate leading the optical transmittance lower than 80% for films that deposition time is above 90 min. based on optical results, the film deposited for 90 min exhibited good optical propert ies, and the shortest wavelength of adsorption edge, which could make cigs solar cell with a higher short circuit density (vsc) [8]. fig. 3 transmission spectra of zns thin films at different deposition time on g lass substrates. bath conditions: [znso4] =0.1m, [sc(nh4)]=0.3m, [nh2-nh2]=1.5m, ph=9 the optical band gap of zns films could be obtained using the tauc relationship revealed as follows [9]. αhν= a(hν-eg) n (1) where a is a constant, h is planck’s constant, v is the photon frequency, eg is the optical band gap energy, and n is 1/2, respectively. the band gap value was determined from the intercept of the straight-line portion o f the (αhν) 2 against the graph on the hν-axis. the band gap values of the zns thin films prepared by cbd with various deposition time are revealed in table 3. the band gap values are greater than 3.5 ev for the films deposited from 30 to 120 min. higher band gap values could match well with cigs solar cell, and the solar cells gain better quantum efficiency [10]. table 3 the band gap for zns thin films with various deposition time deposition time (min) 30 60 90 120 150 180 band gap (ev) 2.57 3.53 3.59 3.54 3.45 3.30 advances in technology innovation, vol. 2, no. 3, 2016, pp. 95 98 98 copyright © taeti 4. conclusions in this study, the zns thin films with sphalerite structure prepared by chemical bath deposition using zinc sulfate, thiourea, and complex of hydrazine as starting materials. the thickness of zns thin film varies with deposition time from 124 nm of 30 min to 750 nm of 180 min. the zns films reveled h igh optical transmittance in the range of 70 ~ 80% at visible wavelength. the band gap values for zns films are in the range of 2.57 ~ 3.61 ev. based on the results, the following bath conditions, [znso4]=0.1m, [sc(nh4)]=0.3m, [nh2-nh2] [ =1.5m, ph=9 and t=80 o c deposited for 90 min, revealed the optimum zns film properties, which is suitable as buffer layer for cuin1-xgaxse2 solar cells, and the properties of the film are described as follows. (1). xrd pattern reveals a cubic zinc b lend structure with the typical composition rat io of zn/s = 50.3:49.7, which is very close to the stoichiometry of the zns compound. (2). the highest transmittance of 85% is located about wavelength of 425 nm and the optical band gap is about 3.59 ev. references [1] a. wei, j. liu, m. zhuang, and y. zhao, “preparation and characterizat ion of zns thin films prepared by chemical bath deposition,” materials science in semiconductor processing, vol. 16, pp. 1478-1484, december 2013. [2] b. g. streetman and s. k. banerjee, “solid state electron devices,” 6th edition, pearson prentice hall, new jersey, pp. 158-208, 2006. [3] i. repins, m. a. contreras, b. egaas, c. dehart, j. scharf, c. l. perkins, b. to, and r. noufi, “accelerated publication 19.9% efficient zno/cds/cuingase2 solar cell with 81.2% fill facto r,” progress in photovoltaics: research and applications 16, pp. 235, 2008. [4] r. n. bhattacharya and k. ramanathan, “cu (in,ga)se2 thin film solar cells with buffer layer alternative to cds,” solar energy, vol. 77, pp. 679-683, 2004. [5] j. liu, a. wei, and y. zhao, “effect of different complexing agents on the properties of chemical-bath-deposited zns thin films,” j. alloys compd., vol. 588, pp. 228-234, 2014. [6] i. o. oladeji and l. chow, “synthesis and processing of cds/zns mult ilayer films for solar cell application,” thin solid films, vol. 474, pp. 77-83, 2005. [7] f. göde, c. umus, and m. zor, “investigations on the physical properties of the polycrystalline zns thin films deposited by the chemical bath deposition method,” j. cryst. growth, vol. 299, pp. 136-141, 2007. [8] s. w. shin, s. r. kang, k. v. gurav, j. h. yun, j. h. moon, j. y. lee, and j. h. kim, “a study on the improved growth rate and morphology of chemically deposited zns thin film buffer layer for thin film solar cells in acid ic medium,” so lar energy, vol. 85, pp. 2903-2911, 2011. [9] s. w. sh in, g. l. agawane, m. g. gang, a. v. moholkar, j. h. moon, j. h. kim, and j. y. lee, “preparat ion and characteristics of chemical bath deposited zns thin films : effects of d ifferent complexing agents,” j. alloys compd., vol. 526, pp. 25-30, 2012. [10] r. n. bhattacharya, k. ramanathan, l. gedvilas, and b. keyes “cu(in,ga)se2 thin-film solar cells with zns(o,oh), zn–cd–s(o,oh), and cds buffer layers,” j. phys. chem. solids, vol. 66, pp. 1862-1864, 2005.  advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 105 numerical study of the operation of motorcycles covering the urban dynamometer driving schedule albert boretti* department of mechanical and aerospace engineering, benjamin m. statler college of engineering and mineral resources, west virginia university, morgantown, wv 26506, usa received 02 september 2016; received in revised form 24 october 2016; accepted 25 october 2016 abstract it is shown, for the most challenging case of a cruiser motorcycle of low weight-specific and displacement-specific power and torque, that the tuning for better top end performances is irrelevant for the operation over the driving schedule used for certification. during the certification test, the engine only operates in the low speeds and loads portion of the map. it is concluded that any statement about motorcycles’ pollution and fuel consumption should be only based on the measurement of their regulated emissions through proper chassis dynamometer tests, possibly redefining the driving schedule to better represent real driving conditions. keywords : motorcycles, pollutant emissions, driv ing cycles, aftermarket tuners, real driving conditions 1. introduction the actual operation of motorcycles covering emission and fuel economy cert ification cycles has been brought back to the attention of lawmakers, original equipment manufacturers and the general public by the recent ban of harley-davidson (hd) aftermarket electronic control units (ecu) tuners in the united states of america (us). the use of aftermarket ecu tuners does not necessarily translate in worse regulated pollutant emissions as otherwise alleged by the us environmental protection agency (epa). actually, these devices are more likely not relevant to any claim concerning emissions. the ecu tuners are simple corrections of the fuel injection parameters to deliver air-to-fuel (afr) ratio that may increase throttle response, power/torque output and overall ride ability. their target is mostly the steady wide open throttle (wot) operation of the engine, i.e. the high load operation, as well as the high speed operation, plus the sharp accelerations. 5 years. they are not supposed to satisfy the emission rules of the time they were certified after the 5 years. therefore, it does not make any sense to discuss the pollutant emissions of motorcycles older than 5 years with or without ecu tuners fitted. however, the retuning of an old engine may in principle offer the opportunity to introduce some improvements rather than declines in performances, power and torque, as well as fuel economy and pollutant emissions, as the old factory calibration does not necessarily represent the best choice of engine controlling parameter on a specific motorcycle more than 5 years old. according to epa rules, new motorcycles are tested on a driving cycle, where the engine delivers the power needed for the motorcycle to fo llow a low velocity schedule with everything but sharp accelerations and everything but high speeds. hence, engines able to deliver much larger power and torque outputs operate significantly far from high load and high speed during the cert ification cycle, changing their load and speed much slower than what they could do, and reaching top power and torque outputs very far from their theoretical maximum. for a gasoline fueled motorcycle having a three-way catalytic converter (tw c), port fuel injection and an oxygen sensor feed back to the ecu, any change of the controlling parameters returning a closer to stoichiometric air-fuel-ratio is not expected to translate in any worsening of the emissions. only operating the engine richer for increased power and torque output at higher loads and speeds may have pollutant emissions and fuel economy downfalls in these operating points. fig. 1 p resents the typical efficiency map of a catalytic converter. the emission reduction of a typical port fuel injected, homogeneous charge, and gasoline engine is based on the efficient operation of the twc that require a close to stoichiometry air-to-fuel ratio. th is is obtained by operating the fuel injectors to deliver a stoichiometric mixture as monitored by the exhaust oxygen sensor feed-back. around the stoichiometric point (a/f=14.63), all the three pollutants (hc, co and no) are almost totally removed (>95 %).a slightly richer mixture translates in more co and hc but not no. a slightly leaner mixture translates in more no but not co and hc. the engine operation in super sport, touring and cruiser motorcycles covering the epa urban dynamo meter driving schedule (udds, 40 cfr part 86, appendix i to part 86 dynamometer schedules) will be considered in the paper. cruiser motorcycles are specific models designed with engines having low end specific performances, i.e . small d isplacement specific torque and power, small weight specific torque and power, low speed, if compared to touring and obviously super sport bikes. cru isers have large torques only because of the large displacement. *corresponding author, email: a.a.boretti@gmail.com advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 106 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti fig . 1 conversion curves for hc, co and no as a funct ion of the air/ fuel ratio , for a port fuel injected gasoline engine fitted with a twc removed (>95 %) 2. epa motorcycles’ emission rules street motorcycles’ emissions are regulated under section 202 of the clean air act. background information on emission rules for motorcycles sold in the us may be found in [1, 2]. table 1 (from [1]) summarizes the emission limits to be satisfied during chassis dynamometer testing of the motorcycle. st reet motorcycles’ emissions were regulated by a single unchanging set of standards for all model years from 1978-2005. in 2004, epa established 2 tiers of conventional pollutant exhaust emissions standards. tier 1 came into effect in 2006. in 2010, standards for class iii motorcycles were updated to tier 2 standards. only class iii motorcycles having a displacement in excess of 279 cm 3 are considered here, as the street motorcycle market is mostly made by super sport and touring bikes. scooters are not considered. highway motorcycles exhaust emission standards only apply since 1978. before 1978 there were no emission standards a motorcycle was requested to comply with. the standards applied first to new gasoline fueled motorcycles (since december 31, 1977). then, later on, the standards were also applied to new, methanol-fueled motorcycles (since december 31, 1989), to new, natural gas-fueled and liquefied petroleum gas-fueled motorcycles (since december 31, 1996) and finally new motorcycles regardless of fuel (since 2006). the table also includes useful life and warranty period. they are expressed in years and kilometers, and whichever comes first limits the need of compliance. the term “useful life” [3] does not mean that a motorcycle must be scrapped or turned over to the government after certain mileage limits are reached. it does not mean that a vehicle is no longer useful or that the vehicle must be scrapped once these limits are reached. the term has no effect on the owners’ ability to ride or keep their motorcycles for as long as they want. the current useful life for motorcycles with engines over 279 cm 3 is 5 years or 30,000 kilometers (about 18,640 miles), whichever first occurs. the test procedures for motorcycles from my 1978 and later are detailed in 40 cfr part 86 subpart f. fig. 2 presents the cycle. this cycle is characterized by low speeds. fig. 2 udds velocity schedule http://www.intechopen.com/books/diesel-engine-combustion-emissions-and-condition-monitoring/nox-storage-and-reduction-for-diesel-engine-exhaust-aftertreatment#f1 advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 107 copyright © taeti table 1 emission standards in the us (from [1]) year class engine size (cm 3 ) hc (g/km) hc + nox (g/km) co (g/km) useful life warranty 1978-2005 i 50-169 5.0 12.0 5 / 12,000 5 / 12,000 ii 170-279 5 / 18,000 5 / 18,000 iii 280+ 5 / 30,000 5 / 30,000 2006+ i-a < 50 1.0 1.4 12.0 5 / 6,000 5 / 6,000 i-b 50-169 1.0 1.4 12.0 5 / 12,000 5 / 12,000 ii 170-279 1.0 1.4 12.0 5 / 18,000 5 / 18,000 2006-2009 iii (tier 1) 280+ 1.4 12.0 5 / 30,000 5 / 30,000 2010+ iii (tier 2) 280+ 0.8 12.0 5 / 30,000 5 / 30,000 3. hd clean air act settlement the u.s. epa and the u.s. department of justice (doj) announced on august 18, 2016 a settlement with hd companies, that required the companies to stop selling and to buy back and destroy “illegal tuning devices that in-crease air pollution from their motorcycles”, and to sell only tuning devices that are cert ified to meet clean air act emissions standards. hd was also requested to pay a $12 million civ il penalty and spend $3 million on a project to mitigate air pollution through a project to replace conventional woodstoves with cleaner-burning stoves in local communities. epa alleges that hd vio lated the clean air act by manufacturing and selling about 340,000 devices, known as tuners that “allow users to change how a motorcycle’s engine functions”. according to epa “these changes can cause the motorcycles to emit higher amounts of certain air pollutants than they would in the original configuration that hd certified with epa”. according to epa, since january 2008, hd manufac-tured and sold tuners that allow users to modify “certain aspects of a motorcycles’ emissions control system”. according to epa, these modified settings increase power and performance, but also increase the motorcycles’ emissions of hydrocarbons and nitrogen oxides (nox). the claim of vio lations is not based on any chassis dy-namometer measurements of the performances of motorcycles not having exceeded the useful life of 5 years or 30,000 km tested first without, and then with the kit fitted, to prove that a specific motorcycle model was not compliant because of the fitting of a specific kit. 4. street performance tuners the screamin' eag le street performance tuner is a performance engine management system for electronic fuel inject ion (efi) equipped harley davidson models [5-7]. the kit utilizes a wide-band oxygen sensor feedback to provide continuous air-to-fuel rat io (afr) tuning corrections based upon riding conditions. the kit is aimed to deliver increased throttle response and torque, improved overall ride ability and performance, as well as a smoother and cooler running engine. in many cases, the kit helps improving fuel economy, depending upon the bike’s configuration and the set-up of the afr targets. afr targets set to richer values than the stock levels to gain performance may result in moderate decrease in fuel economy. the street tuner permits limited tunability within the emissions range to optimize drivability without compromising emission, but it is obviously intended to work outside the closed loop portion of the engine map where the afr is ensured to be about stoichiometric for the best operation of the three-way-catalytic converter. fig. 3 typical afr map of a large hd cruiser with a big v-twins engine advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 108 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti a typical tuners fuel map of a large hd cruiser is provided in [7] and reproduced in fig. 3. the engine is a big v-twins engine (twin cam 96, 96.96 cubic inch or 1,584 cm 3 ).these engines are characterized by much smaller specific torque and power density than the average super sport and touring bikes. maximum power (but at the wheels, where it is typically 10-15% smaller than at the crank) is only 68 hp @ 5,000 rpm, while maximum torque (also at the wheel) is 110 n m @ 3,000 rpm. this engine powers motorcycles of 307.5 kg wet weight including oil and gas. only above 80% map (roughly 50% throttle) and 4,000 rpm, where the engine does not operate during typical driving cycles including the cert ification cycle, the afr is made rich. different “stages” of tuning are considered in [7]. the stage 2 is an upgrade that includes new cams. the stage 1 is upgrade also requiring exhaust and air cleaner. both these upgrades are valid 50-state legal modification. the air fuel map of [7] has the cells in red with the stoichiometric 14.6 afr in them over the low speed low load portion of the map that is relevant to the emission certification. both stage 1 and stage 2 tunings do not affect this area. the ecu runs in closed loop mode looking at the oxygen sensor to satisfy the optimal composition of the exhaust gases for the twc to reduce the tail p ipe emissions. in [7], the engine works closed loop to 3,750 rpm and to 80 kpa of manifo ld absolute pressure (map). the ecu uses manifo ld pressure from the map sensor to determine the actual engine load rather than the throttle. throttle position does not relate linearly to the map sensor reading. 80 kpa map is typically around 40% throttle. ref. [7] assumes the oem afr table is same or very similar of fig. 3, but may obviously differs outside the 3,750 rpm and 80 kpa area. therefore, tuners are possibly delivering same afr vs. map and speed of the oem in the low map and low speed area of emissions’ control, and then they differ. it is worth to mention that usually steady state afr maps do not need fuel rich conditions except than approaching wot conditions, i.e. close to the maximum loads for any speed. the fuel rich mixture at speed exceeding 3,750 rpm any load seems quite questionable. the tuner operates rich everywhere out of the closed loop area very likely because the injection system is everything but effective in delivering the amount of fuel needed when the throttle opens sharply. even racing engines these days go rich only approaching wot conditions at any speed, as even these extreme engines run slightly lean part load to reduce unnecessary fuel consumption. in addition to the afr map, ref. [7] also provides the bias tables and the ignition advance map for the hd stage 1 and stage 2 bikes. it is not the object of the paper to enter more in details of the specific tunings, only to show in the next section how the operation of a motorcycle over a driving schedule for emission certification never utilizes the high loads or high speeds parts of the map that are the ultimate goal of tuning an engine for mostly improving power and torque output. 5. method map based computer models are used to investigate the operation of an engine when the motorcycle is covering a driving schedule. vehicle driv ing cycle simulat ions have been around for many years. basic solutions of the new-ton’s equation of motion fo r a vehicle following a pre-scribed velocity schedule returns the instantaneous power requested to the engine with a simplified modelling of transmission losses, aerodynamic and rolling resistance, and vehicle and engine inertia. trans mission ratios then also return the speed requested to the engine. interpolating the steady state maps of brake specific fuel consumption or specific emissions, it is then possible to evaluate the fuel consumption and the pollutant emissions on a driving cycle. for cold start, correction curves are needed. for the interested reader, these simulat ions are presented in [12-24]. to simplify, a driving cycle simulator solves the newton’s equation of motion. if fp,e is the engine propulsive force and fb,f is the friction brake force, it is: fp,e-fb,f-fa-fr= m∙a (1) with m the mass, a the acceleration, =dv/dt, with v velocity of the motorcycle and t the time, fa the aerodynamic drag force, =½∙ρ∙v 2 ∙cd∙a, with ρ air density, cd drag coefficient (always positive for a retard ing force) and a reference area, fr the rolling resistance force, an empirical function of the speed of the motorcycle. in terms of powers, by multiplying for the speed of the motorcycle, it is then pp,e -pb,f = m∙v∙dv/dt +½∙ρ∙v 3 ∙cd∙a+pr (2) the above propulsive power is computed at the wheel. the power of the engine at the crankshaft pb is larger than the power at the wheel pp,e to include the transmission efficiency η. the speed of rotation of the engine is then obtained by the speed of the motorcycle by considering tire radius, gear and gear ratios. the gear is determined by an upshift/downshift strategy. from a velocity schedule v(t), it is thus possible to compute the instantaneous power pp,e and pb,f, and from pp,e, then the power pb and the speed n that the engine must provide. when m∙v∙dv/dt +½∙ρ∙v 3 ∙cd∙a+pr ≥0 , equation (2) returns pp,e with pb,f=0. when m∙v∙dv/dt +½∙ρ∙v 3 ∙cd∙a+pr <0, equation (2) returns pb,f with pp,e=0. pb,f represents in this case not only the actual power dissipated in the friction brakes p * b,f , but also the negative power requested to motor the engine at the given speed n (engine brake). engine performances are typically defined in terms of power pb, torque tb and brake mean effect ive pressure bmep. the power pb is proportional to the product of torque tb and speed n. the bmep is proportional to the ratio of torque tb and total displaced volume vd. engine data are provided as the wide open throttle torque output tb vs. speed n, plus the maps of specific fuel consumption and pollutant emissions vs. bmep and n. this way the driving cycle simulator returns the fuel economy and the pollutant emissions during warmed-up cycles, with empirical penalty functions needed for cold-start cycles. advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 109 copyright © taeti the model simulates a motorcycle performing a test cycle. the udds is considered. the cycle is everything but aggressive, and it is characterized by mostly low speed. in the udds cycle, fig. 2, only in one of the acceleration, cruise and deceleration schedules it is requested a bike velocity of 90 km/h, and in only 3 other areas the bike reaches a speed above 50 km/h but less than 60 km/h. figs. 4, 5 and 6 present reference data of bmep, torque and power vs. engine speed and throttle opening % for the typical large cruiser considered here, having a low displacement specific power and torque, low maximum speed. the engine is 1,300 cm 3 and it is fitted on a heavy motorcycle of weight 380 kg including the driver during the simulated chassis dynamometer test. fig. 4 typical brake mean effective pressure map of a large cruiser motorcycle fig. 5 typical torque map of a large cruiser motorcycle fig. 6 typical power output map of a large cruiser motorcycle advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 110 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti table 2 model parameters rated engine speed 6,500 rpm upshift 4,000 rpm downshift 2,000 rpm ratio of 1 st gear 9.312 ratio of gear 2 6.421 ratio of gear 3 4.774 ratio of gear 4 3.926 ratio of gear 5 3.279 ratio of gear 6 2.79 motorcycle weight 377 kg engine power at rated speed 55 kw tire rolling radius 457.2 mm tire rolling resistance factor 0.0122 engine displacement 1,304 cm 3 engine inertia 0.05 kg-m 2 frontal area 0.2 m 2 coefficient of drag 0.6 wheelbase 2 m initial engine speed 1,500 rpm initial gear number 1 table 2 presents the relevant model parameters, id le speed, rated engine speed and engine power at rated speed, upshift and downshift speed, that may differ at every gear, ratios of 1 st to 6 th gear (if a 6 gear transmission is considered as it is in this case), motorcycle weight, tire ro lling radius, tire ro lling resistance factor, engine displacement, engine inertia, frontal area, coefficient of drag, wheelbase, initial engine speed and gear number. 6. results and discussion the engine map bmep (brake mean effect ive pressure) vs. engine speed at different loads is the one of fig. 4, where the load is expressed in terms of acceleration pos ition (ap). fig. 7 presents the computed operating points, while fig. 8 presents the computed time d istribution on engine map of the operating points of a large cruiser motorcycle covering the udds cycle. the engine operates below 2.5 bar bmep and below 4,000 rpm over the cycle. every map point above these values has time d istribution zero, i.e . whatever could be the emission in these points, and this has no effect on the regulated emissions. the most part of the time the engine is idling. then, when delivering an output, the engine is always operating well below 2.5 bar bmep and 3,750 rpm. fig. 7 typical operating points of a large cruiser motorcycle covering the udds cycle fig. 8 typical t ime distribution on engine map of the operating points of a large cru iser motorcycle covering the udds cycle advances in technology innovation, vol. 2, no. 4, 2017, pp. 105 112 111 copyright © taeti in terms of performances, today’s super sport, touring and cruiser bikes may have very high specific power and torque densities. as hd does not provide online informat ion about power and torque figures, typical performance parameters are proposed for other manufacturers. the 998 cm 3 yamaha yzf r-1 [9], one of the most powerful super sport bikes, has for example 200 hp/ liter revving 13,500 rpm. the specific torque is less exceptional, as the result of the tuning for high speeds , but still 112 n m/liter revving 11,500 rpm. the wet weight including full oil and fuel tank is 199 kg. th is bike has a top speed of 300 km/h. as an example of touring bikes, the 1,298 cm 3 yamaha fjr1300a [10] has 112 hp/liter revving 8,000 rpm and 106 n m/liter revving at 7,000 rpm. the wet weight (including full oil and fuel tank) is 289 kg. this bike has a top speed of 245 km/h. finally, as a typical cruiser, the 1,304 cm 3 yamaha xvs1300 custom [11] has 56 hp/ liter revving 5,500 rpm and 79 n m/liter revving 3,000 rpm. the wet weight including full oil and fuel tank is 293 kg. this b ike has a top speed of 175 km/h. therefore, in normal driving correctly accounted for emission regulations, motorcycles work very far from their potentials. the most part of the motorcycles in the super sport and touring classes are usually more performant than the cruisers. they have much larger power and torque to weight ratio, as they are much lighter, and also have much larger displacement specific power and torque. the most part of the super sport and touring motorcycles are therefore working even farther away from their h ighest speed and highest load points where they may operate off-stoichiometry during typical driving cycles including the udds emission cycle. the results proposed in the previous section are therefore a worst case scenario. 7. conclusions it is pure speculation to claim that ecu tuners can cause the motorcycles to emit higher amounts of certain air pollutants than they would in the orig inal cert ified configuration without even mentioning the specific motorcycle where the tuners are fitted. in princip le, ecu tuners are not expected to affect any regulated emission. if fitted to motorcycles having exceeded the useful life, presently defined as 5 years or 30,000 kilometers (about 18,640 miles) whichever first occurs, as these motorcycles are not presently expected to comply with any emission rule, having or no the tuners makes no difference. for new motorcycles, the ecu tuners are expected to modify the afr only at the higher loads and speeds that are very far from the area of operating points that are designed closed loop stoichiometric, to comply with the emission rules properly using the twc. old and new motorcycles cannot be claimed a-priori not compliant without providing any evidence of failure to perform as required by regulation, and obviously they cannot be claimed not compliant if there is no rule to comply with. any statement about motorcycles’ pollution and fuel consumption should be only based on the measurement of their regulated emissions through proper chassis dynamometer tests. the results emphasize the importance of real world driving in motorcycles. the paper shows that the ecu tuners have no effect on the presently regulated pollutants emission, even if modifying the afr certainly lead to change in emission performance of the vehicles. while the ecu tuners may not affect the pollutants emission under well-constraint laboratory certification tests, they certainly change the emissions over real world driving. the paper therefore emphasizes the importance of the inclusion of real world driving in emission certification tests. the introduction of better emission certification tests will ultimately translate in superior fuel conversion efficiencies of the internal combustion engine over the full range of loads and speeds, for example also simply adopting jet ignition and direct injection [25], plus the hybridizat ion of the power train, for example with a flywheel or a li-ion battery based kinetic energy recovery system [26]. references [1] “us epa light -duty veh icles and t rucks emiss ion standards,” h ttps ://www.epa.gov/emiss ion -standar ds-reference-gu ide/ light -duty -veh icles-and-t rucks emission-standards, retrieved august 31, 2016. 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[26] a. borett i, “comparison of regenerat ive b raking efficiencies o f my2012 and my2013 nissan leaf,” internat ional journal o f engineering and technology innovat ion , vo l. 6, no . 3, pp . 214-224, 2016.  advances in technology innovation, vol. 2, no. 1, 2017, pp. 08 12 8 the tangent medial circles inside the region defined by hermite curve tangent to unit circle ching-shoei chiang computer science and information management, soochow university, taipei, taiwan. received 19 february 2016; received in revised form 08 april 2016; accepted 10 april 2016 abstract the design of curves, surfaces, and solids are important in computer aided geometric design (cagd). images, surround by boundary curves, are also investigated by many researchers. one way to describe an image is using the medial axis transform. under this consideration, the properties of the boundary curves tangent to circles become important to design for 2d images. in this paper, we want to find the medial axis transform (mat) for a special class of region, which is bounded by unit circle and the curves whose end points is on a the circle, and endpoints tangent vectors are parallel to the tangent of circle at the end points. during the process, we want find the medial circle tangent to other medial circle, until we reach the medial circle whose center is the center of the osculating circle for the point with local maximum curvature. there are 4 cases, symmetric/non-symmetric region with singular point/local maximum curvature point, and proposed algorithm for these 4 cases. we introduced algorithm for this 4 cases in this paper. keywords: medial axis transform, hermite curve, computer geometric modeling 1. introduction the 2d image can be stored by many different ways, including its boundary curves, a medial axis curves with radius function, union of many primitive figures, and so on. there are many researchers use different curves to simulate different images. for example, cinque, levialdi and malizia [1] uses cubic bezier curve to do the shape description. yang, lu and lee[2] use bezier curve to approach the shape description for chinese calligraphy characters. chang and yan[3] derived an algorithm to approach the hand-drawn image by using cubic bezier curve. cao and kot[4] derived an algorithm to do data embedding in electronic inks without losing data. the boundary curves can be also used to derived the offset curves and medial axis of an images[5], and also to simulate the nature objects, such as flowers[6]. in this paper, we would like to investigate the cubic hermite curves, where the end points are on a unit circle, and its end points tangent line is parallel to the tangent line of circles. using these properties, with more constraints on the singular point or maximum curvature at specified parameter, we survey the couture of the curves, so that the design of the curve may be simplify by giving constraint. 2. definition and theorem let introduce the hermite curve first. given two points p0 and p1 , with two associated tangent vectors and v1 , the hermite curve c(t) defined as (see fig. 1): fig. 1 hermite curve to simplify our problem, we assume that the end points p0 and p1 are on the unit circle, the first point p0 =(-1,0), and the second point p1 =(-cosθ , sinθ). it’s associated tangent vectors parallel to (0,1) and (sinθ , cosθ ). we have the following definition for this curve. * corresponding author, email: chiang@scu.edu.tw advances in technology innovation, vol. 2, no. 1, 2017, pp. 08 12 9 copyright © taeti definition 1: two points p0 =(-1, 0), p1 =(-cosθ , sinθ ) on the unit circle with its associated tangent vector v0=α0(0,1), v1=α1(sinθ , cosθ ) produced a hermite curve, we call it unit circle hermite curve, denoted h1(t;θ,α0,α1), where α0>0, α1>0, 0<t<1, 0<θ<2π. notice that for the general case, we can always convert the design problem into the design problem for h1(t;θ,α0,α1). we can always translate the center of current medial axis circle to the origin, scale the radius into one and rotate the circle so that the first boundary point is on (-1,0). we call this process the standardization of the problem. after we solve the problem, produce the curve we want, we can always inverse the rotate, scale, and translate process, to see the designed curves for the original design problem. in [7], we have the following two theorems: theorm 1: let c(t)=h1(t;θ,α0,α1), then c'(t)=(x′(t),y′(t)) =(0, 0) ↔ α0b(t)=α1d(t) =a(t) tan ( θ 2 ) , where a(t) =6t(t-1), b(t)=(3t-1) (t-1), d(t)=t(3t-2). we would like to find the ma and mat for the region bounded by the hermite curve with the circular arc from (-cosθ, sinθ) to the point (-1,0) rotate about the origin clockwise, we call this region r(t;θ,α). theorem 2: let the hermite curve c(t)=(x(t),y(t))= h1(t;θ,α0,α1), if the local maximum curvature is at t0, then (x'(t0)y'''(t0)-x'''(t0)y'(t0))(x'(t0)2+y'(t0)2)-3(x'(t0)y ''(t0)-x''(t0)y'(t0))(x'(t0)x''(t0)+y'(t0)y''(t0))=0. notice that this equation has degree 5 in t, which means there are 5 local maximum/minimum curvatures on the curve. the ma is very sensitive to its boundary, so many researcher use approximated ma instead. in pattern recognition, the important information for the region is easier to capture by using approximated ma. although it could have more than one local maximum curvature in our region, which means more than one end point of the mat in the region, we would like to find one endpoint in the region, so that the ma of the region has only two end points (one is on the singular point, or the center of the osculating circle associated with the boundary curve with local maximum curvature, the other one is on the origin). in this paper, we use ma to represent the approximated ma. we start simple case here. let’s start from the case α0=α1=α. let’s also assume that all points on the curve is outside the unit circle and the curve has no self-intersection. the ma of a region is easy to find if we know the region is symmetric to a line, so we have the following theorem: theorem 3: the curve c(t)=h1(t;θ,α,α) is symmetric to the line y= (−tan θ 2 )x. furthermore, c(t) and c(1-t) are symmetric points. proof: let t = tan θ 2 , we have c(t)+c(1−t) 2 = αtt(t−1)−1 1+t2 . obviously, this point is on the line y=tx. notice that this line y=tx passing through c(1/2). notice further that because c(t) and c(1-t) are symmetric points, so the point c(1/2) is a singular point, or c(t) is a vertex of the curve, which means c(1/2) is a singular point, or has constant curvature, or has local maximum/minimum curvature. with the symmetric property, we know the ma of the region is on the line (−tan θ 2 )x. we would like to find the ma point from its footpoint c(t) or c(1-t), we have the following theorem: theorem 4: the medial axis (xm, ym) associated with c(t)=(x(t),y(t)), where 0<t<1/2 is (to simplify the representation of the equation, we eliminate the parameter t for x, y, x′, y′, xm, ym and rm): (xm, ym) = (x,y)∙(x′,y′) (1,t)∙(x′,y′) (1,t) and rm = | (1,t)∙(−y,x) (1,t)∙(x′,y′) | ‖(x′, y′)‖ where ∙ is the inner product of two vectors, |a| is the absolute value of a, and ||(x,y)|| is the norm of the vector, t=−tan θ 2 . with the ma point and its distance to its footpoint, we find mat of the region. we also call mat the medial axis circles in this paper. notice that (xm(0), ym(0)) = (xm(1), ym(1))=(0,0). 3. algorithm and experimental result in this paper, we want find the medial axis circles inside the region, and all medial axis advances in technology innovation, vol. 2, no. 1, 2017, pp. 08 12 10 copyright © taeti circles tangent with its neighbors. in our assumption, we can always find one end points of the mat. in some case, there is singular point exist, the singular point is the end point of the mat branch (the other one is on the origin). on the other case, we can always find a point with local maximum curvature; we use the center of its osculating circle as the end point of the mat branch. how to find normal point of the mat? consider the end ma point we find, either singular point or points with local maximum curvature. assume it has parameter tend, 0<tend<1, c(t)=(x(t),y(t)) and we want find t1 and t2, 0<t0<tend and tend<t1<1, so that c(t1) and c(t2) are footpoints of a ma point (x,y), from the property of ma point, we have: (x-x(t0),y-y(t0))․(x′(t0),y′(t0))=0 (x-x(t1),y-y(t1)) ․ (x′(t1),y′(t1))=0 ((x-x(t0)) 2 +(y-y(t0)) 2 =(x-x(t1)) 2 +(y-y(t1)) 2 the first two equations indicates that the line through ma point and its footpoints perpendicular to tangent of the footpoint on the curve. the third equation indicates that the distances from ma point to its two footpoints are equal. now we have 3 equations, and 4 variables, which are x, y, t0 and t1. given t0, we can find the ma point (x, y) and t1. the idea to solve the system of equation is: algorithm 1: finding one ma point. 1. solve (x,y) by cramer’s rule from the first 2 equations, and x, y has two variables t0 and t1. 2. substitute the value x, y into the third equations, and leave one equation with 2 variables t0 and t1. 3. given t0, we have one equation with one variable t1, so we can find solutions for t1. with careful selection of t1, we find the ma points with its two footpoints. the above idea solves the mat (ma with radius function) for one specified point. as long as we know the parameter for the end point, we can always find all mat for parameter from 0 to tend. we would like to find not only one ma point, but also its ma circle tangent to current ma circles. we proposed two methods to find next ma circle. one method solve the problem algebraically, and the other method using an algorithm with binary search to approach the result. the first method only suitable for the symmetric case, which means the case with α0=α1. on the case that α0=α1=α, we want find the next circle tangent to the first circle, which centered at (0,0) with radius 1 in the very beginning. from theorem 4, we know the curve whose parameter t associate a mat circle (xm, ym, rm), we assume the next circle whose associated boundary parameter is t, so we want to find the circle tangent to the unit circle centered at the origin. the constraints we give is the distance between the centers of two circle is equal to the sum of the radius of two circles. that is, ‖ (x𝑚, y𝑚)‖ = rm + 1. to find the medial axis circle (xm, ym, rm) associated with c(t)=(x(t),y(t)), where 0<t<1/2, tangents to the unit circle centered at the origin, we have to solve a one parameter equation with degree 10. because the solutions for this equation are sensitive to its coefficient, we did not implement this method. we use the binary search strategy instead. algorithm 2: finding the next ma point (eps is a small number): # current ma circle is (x,y,r) with parameter t. the return value is next ma circle (x1, y1, r1) and t1 1. set the tmin=t, the current parameter value, and tmax is the parameter value for the end ma point. 2. let dist (distance between two centers) be 2, and srad (the sum of the radius of two circles) be 1. 3. while |dist – srad| > eps and |tmax-tmin| < eps : tt = (tmin+tmax)/2 find the mat (x1, y1, r1) for the parameter tt # (from algorithm 1). find dist, srad from these two circles. if dist srad > eps, then tmax = tt if dist srad < -eps, then tmin = tt 4. the value x1, y1, r1 is the ma circle we find. from the above algorithm, we can find the next ma circles for the parameter t. however, when the parameter t value close to the parameter associate with the local maximum curvature, it can only produce circles intersect with previadvances in technology innovation, vol. 2, no. 1, 2017, pp. 08 12 11 copyright © taeti ous circle, which means it cannot find more circle tangent to current circle, and "inside" the hermite curve. from the theorem describes in the last section, with the idea mentioned above, we give 4 examples in this section. the first two examples is for the symmetric boundary curve where α0=α1=α, for boundary curve with singular point and with local maximum curvature respectively. the third and fourth cases are for the non-symmetric boundary curve, also for boundary curve with singular point and with local maximum curvature respectively. example 1: (symmetric curve with singular point): given θ=5/9, t=0.5, we can find α0=α1=7.15025. the associated mat is shown in fig. 2. fig. 2 symmetric region with singular point example 2: (symmetric curve with local maximum curvature): given θ=5/6, α0=α1=8, the associated mat is shown in fig. 3. fig. 3 symm. region with localmaximum curvature in fig. 3(a), we find one ma circle tangent to the original one. we can find the next circle tangent to the red curve and the hermite cuve, however, this circle is not totally “inside” the hermit curve. on this case, we draw the osculating circle associated with the hermite curve at local maximum curvature (see figure 3(b)). notice that the above two examples has the properties that the ma points are on one straight line.the design requirements and design constraints are summarized based on the characteristics of the mechanism. example 3: (non-symmetric curve with singular point): given θ =5/6, t=0.4, we find α0=44.78461, α1=16.79423. the associated mat is shown in fig. 4. fig. 4 non-symm. region with singular point example 4: (non-symmetric with local maximum curvature): given θ=7/6, α0=18, α1=6, the associated mat is shown in fig. 5. fig. 5 non-symm. region with maximum curvature in fig. 5, the same as fig 3, the last circle is associated with the hermite curve at local maximum curvature. 4. conclusions the unit circle hermite curve, h1(t;θ,α0,α1), can be used to design curves and images. on many cases, the singular point may be needed to be considered. for example, the chinese characters may have cusp on the boundary. before the design of the character, the relationship between the parameter value and the contour of the boundary curve is important. when we give two values of the parameters for h1(t;θ,α0,α1) curve, the can find the other two values with simple computation. when we define a curve, the only memory we need is 7 locations to store these 4 parameters, and other 3 parameters for the standardization process. so, the design process advances in technology innovation, vol. 2, no. 1, 2017, pp. 08 12 12 copyright © taeti saved not only the time, but also the memory. when we find the ma circles inside the region bounded by unit circle and h1(t;θ,α0,α1), it is possible that the last circle intersects the osculating circle at the local maximum curvature. the osculating circle associated with end mat point of the region, so it is better to show this circle, so that the mat of the region also contains the end mat point. there are more constraints we can used to design the curves. for example, the maximum curvature happened at t0, the curve passing through a point p0 , the curve tangent to a line l0 , and so on. we believe the result will as simple as the case we introduced here. we can also consider the inverse process, that is, from circles tangents to each other, and find its boundary hermite curve. we will leave this for further research. acknowledgement this work was supported in part by the national science council in taiwan under grants most 104-2221-e-031-001. references [1] l. cinque, s. levialdi, and a. malizia, “shape description using cubic polynomial bezier curves,” pattern recognition letters, vol. 19, pp. 821-828, 1998. [2] h. m. yang, j. j. lu, and h. j. lee, “a bezier curve-based approach to shape description for chinese calligraphy characters,” proceedings of the sixth international conference on document analysis and recognition, pp. 276-280, 2001. [3] h. h. chang and h. yan, “vectorization of hand-drawn image using piecewise cubic bezier curves fitting,” pattern recognition, vol. 31, no. 11, pp. 1747-1755, 1998. [4] h. cao and a. c. kot, “lossless data embedding in electronic inks,” ieee transactions on information forensics and security, vol. 5, no. 2, pp. 314-323, 2010. [5] l. cao, z. jia, and j. liu, “computation of medial axis and offset curves of curved boundaries in planar domains based on the cesaro’s approach,” computer aided geometric design, vol. 26, no. 4, pp. 444-454, 2009. [6] p. qin, and c. chen, “simulation model of flower using the integration of l-systems with bezier surfaces,” international journal of computer science and network security, vol. 6, no. 2, pp. 65-68, 2006. [7] c. s. chiang and l. y. hsu, “describing the edge contour of chinese calligraphy with circle and cubic hermit curve,” computer graphics workshop, july 2013. [8] c. s. chiang, “the medial axis transform of the region defined by circles and hermit curve,” international conference on computer science and engineering (iccse), pp. 22-24, july, 2015.  advances in technology innovation, vol. 3, no. 3, 2018, pp. 141 146 a novel stretch sensor to measure venous hemodynamics syrpailyne wankhar 1,*, albert a. kota 2, dheepak selvaraj 2 1 department of bioengineering, christian medical college and hospital, vellore, india . 2 department of vascular surgery, christian medical college and hospital, vellore, india. received 21 july 2017; received in revised form 10 october 2017; accepted 23 october 2017 abstract chronic venous insufficiency is a debilitating condition causing varicose veins and venous ulcers. the pathophysiology includes reflux and venous obstruction. the diagnosis is often made by clinical examination and confirmed by venous doppler studies. plethysmography helps to quantitatively examine the reflux and diagnose the burden of deep venous pathology to better understand venous hemodynamics, which is not elicited by venous duplex examination alone. however, most of these tests are qualitative, expensive, and not easily available. in this paper, we demonstrate the potential use of a novel stretch sensor in the assessment of venous hemodynamics during different maneuvers by measuring the change in calf circumference. we designed the stretch sensor by using semiconductor strain gauges pasted onto a small metal bar to form a load cell. the elastic and velcro material attach ed to the load cell form a belt. it converts the change in limb circumference to a proportional tension (force of distension) when placed around the calf muscle. we recorded the change in limb circumference from arrays of stretch sensors by using an in-house data acquisition system. we calculated the venous volume (vv), venous filling index (vfi), ejection fraction (ef) and residual venous volume (rvv) on two normal subjects and on two patients to assess venous hemodynamics. the values (vv > 60 ml, vfi < 2ml/s, ef > 60%, rvv < 35%) in normal subjects and (vv < 60 ml, vfi > 2ml/s, ef < 60%, rvv > 35%) in patients were comparable to those reported in the literature. keywords: stretch sensor, venous hemodynamic, plethysmography, venous duplex 1. introduction the pathophysiology of reflux and venous obstruction due to chronic venous insufficiency is a debilitating condition causing varicose veins and venous ulcers. the diagnosis is often made by clinical examination and confirmed by venous doppler studies [1-2]. there are three systems in the venous circulation of the lower extremity namely superficial, deep veins , and perforators. normal physiology allows blood to flow from superficial to deep veins via perforators and then returns the blood to the heart in unidirectional flow. when there is damage to the valves, blood can flow bidirectionally, causing the volume overload in the lower extremities leading to the pathological changes. the goal of further evaluation is to characterize the misdirect ion of venous blood volume [2-3]. it is, therefore, crucial to study the venous hemodynamic, which is not elicited by venous duplex examination alone. plethysmography helps us to quantitatively examine the reflux and diagnose the burden of deep venous pathology (degree of venous obstruction, ejection capacity of calf muscle pump). different plethysmographic measurement of venous reflux includes strain -gauge plethysmography (sgp) using silastic conductor tube which is stretched by a change in calf circumference. this , in turn, increases the resistance resulting in a voltage * corresponding author. e-mail address: sy rpailyne@cmcvellore.ac.in advances in technology innovation, vol. 3, no. 3, 2018, pp. 141 146 copyright © taeti 142 change which is acquired for further analysis. the disadvantage of this technique is that it is susceptible to degrade over time resulting in the change in conductivity of the silastic conductor. impedance plethysmography (ipg), on the other hand, results in a change in resistance due to change in limb circumference which is directly proportional to relative volume change [4]. the disadvantage of this method is that it is cumbersome as it is sensitive to sensor placement. photoplethysmography (ppg) is another method which uses a light source in the infrared wavelength to emit light into the tissue. the light is absorbed by t he blood and whatever is reflected or transmitted is measured by a reflective/transmis sive based photo detector, and net absorption is displayed as a line tracing [4]. the disadvantage of this method is that it is also sensitive to sensor placement. dielect ric elastomer described in [5], uses a flexible capacitor with stretchable dielectric attached to 2 parallel plate electrodes. when the electrodes are pulled uniaxially or biaxially, it changes the area and thickness of the sensor (stretch mode) resulting in the change in capacitance. one of the major drawbacks of this sensor is that the accuracy is affected by speed and, therefore, the capacitive based stretch sensor requires good circuit design to achieve better accuracy [5]. the ‘stretchsense’, based on this principle is commercially available. however, it is expensive. air plethysmography (apg) is considered as the gold standard. it uses a 30-40 cm length air cuff that is attached to the lower leg from knee to ankle. the low-pressure cuff provides a precise quantitative evaluation of volume changes of the entire lower leg [4]. although apg is considered the gold standard, it is not readily available because it is expensive. as discussed, there are different techniques available such as ppg, ipg, apg etc. however, most of these tests are qualitative, expensive, and not easily available [4-9]. in this paper, we demonstrate the measurement of venous volume using arrays of the novel stretch sensor and thereby enable us in developing a novel prototype instrument for measuring venou s hemodynamic. 2. design methodology end-supported-centre loaded load cell was constructed using semiconductor strain gauges (bcm strain gauges b2-120-p-3) and an aluminum bar (31 mm x 5 mm x 3 mm) as described by wankhar et al. [9]. a pair of strain gauges pasted on the top face and bottom face of the beam will experience tension and compression respectively. these strain gauges along with fixed resistors form a wheatstone bridge to give an output voltage proportional to the bending of the beam. the output of the strain gauge bridge connects to a dc bridge amplifier for further processing. eq. (1) is the standard form of the strain on the surface of the beam as measured by the strain gauges for centre-loaded end supported beam: 2 4 l fl l e bh   (1) 3.1. static calibration of the stretch sensor static calibration of the overall stretch sensor consisting of the load cell attached to the velcro (rigid) and elastic (spring) material was done. offset correction was done before measurements were taken. the change in length due to stretching of the elastic band was recorded by using an in-house data acquisition system ‘cmcdaq’. the setup for measuring venous volume by measuring the change in calf circumference using arrays of 3 stretch sensors is shown in fig. 1. this is a novel prototype instrument for quantifying venous function. the total volume measured by the stretch sensor is calculated using eq . (2): 2 2 2 1 1 1 2 2 2 3 3 3 4 (2 2 2 ) h v c c c c c c c c c               (2) where, h = height of the stretch sensor belt, c = change in circumference measured by the stretch sensor advances in technology innovation, vol. 3, no. 3, 2018, pp. 141 146 copyright © taeti 143 fig. 1 setup for measuring venous volume by measuring change in calf circumference using arrays of stretch sensors 3.2. measurement of venous volume using the novel stretch sensor for measuring venous volume, the subject performed different maneuvers as described in [1, 10]. at the beginning of the experiment, the subject was asked to lie down in a supine position. the subject’s leg to be assessed was lifted to 45° angle for about a minute so that the veins are emptied and then the leg was placed back in the initial position. this was done to lower the venous pressure in the legs to a zero line (pressure) of the right atrium (≈ 0 mmhg) which was recorded as baseline volume us ing an in-house data acquisition system [10]. then the subject was asked to stand slowly and load on the non -assessed leg. the assessed leg was in non-weight bearing position so that the leg venous pressure increases due to the hydrostatic column of blood extending from the right atrium to the assessed leg [10]. the blood volume increases as the veins are elastic and this change in volume was recorded. fig. 2 illustrates the different parameters as measured by the novel stretch sensor during different maneuvers. the measurement between baseline volume in the supine position (‘1’) and the erect volume plateau is known as venous volume (vv'). we also determined the venous refilling time (vft90), which is the time from which the volume increases from baseline (‘2’) to 90% vv and venous filling index (vfi) was calculated using eq. 3(a). the volume then increases till it plateaus (‘3’). during this time, the subject was in a standing position and supported only on the non -assessed leg. then, the subject was asked to weight bear both legs and performed a single plantar flexion (‘4’). the subject then unloads the assessed leg (non-weight bearing stance, ‘5’) again. this produced a change in the volume called the ejection volume (ev). ejection fraction (ef) was then calculated using eq. 3(b). now the subject was asked to perform the same maneuver (plantar flexion) 10 times (‘6’), which caused a larger volume reduction. the residual volume (rv) was measured as the difference between the volume after 10 plantar flexions and the baseline volume. the residual volume fraction (rvf) was calculated by dividing rv by vv as given by eq. 3(c). fig. 2 change in venous volume during different maneuvers measured by the stretch sensors advances in technology innovation, vol. 3, no. 3, 2018, pp. 141 146 copyright © taeti 144 the equations for calculating vfi, ef, and rvf are as follows : 90 90% vv vfi vft  (3a) 100 ev ef vv  (3b) 100 rv rvf vv  (3c) 3. results 3.1. static calibration of the stretch sensor the overall stretch sensor is non-linear in its characteristics because of the properties of elastic band attached to the belt as shown by the static calibration curve in fig. 3. fitting a linear equation to the data by linear regression from a single sensor is shown in fig. 3 (a). eqs. (4) and (5) provide the relationship between force and change in length of the stretch sensor belt. 0.915 0.1065y x  (4) with r 2 = 0.9652 3.1445 7.0357y x  (5) with r 2 = 0.9972, where y is force and x is change in length. similarly, linear equation to the data by linear regression from all other sensors shown in fig. 3 (b) is given by eqs. (6), (7), (8), and (9) for sensors 2 and 3 respectively. 0.9142 0.1155y x  (6) with r 2 = 0.9418 3.1928 6.9242y x  (7) with r 2 = 0.9982 0.9274 0.1118y x  (8) with r 2 = 0.9555 3.0342 6.4521y x  (9) with r 2 = 0.9976, where y is force and x is change in length. for all applications, the stretch sensor is pre-loaded/stretched to a length change of 2 cm or more, indicating the region of operation is in the second part of the curve with r 2  0.9972 (fig. 3(a)). (a) static calibration curve of one stretch sensor (b) static calibration curve of all 3 stretch sensors fig. 3 static calibration curve of one stretch sensor and all 3 stretch sensors advances in technology innovation, vol. 3, no. 3, 2018, pp. 141 146 copyright © taeti 145 3.2. measurement of venous volume using the novel stretch sensor we calculated venous volume (vv), venous filling index (vfi), ejection fraction (ef) and residual venous volume (rvf) on two normal subjects (1male, 1female) and two patients (2 males). fig. 4 shows the changes in venous volume during different maneuvers measured by the stretch sensors for venous hemodynamic assessment on one normal subject. the calculated parameters were vv = 100 ml, vfi = 1 ml/s, ef = 84.4%, and rvf = 14.9% in a male subject, and vv = 65 ml, vfi = 0.5 ml/s, ef = 61%, and rvf = 29.7% in a female subject. similarly, fig. 5 shows the changes in venous volume during different maneuvers measured by the stretch sensors on one patient. the calculated values were vv = 51 ml, vfi = 4.6 ml/s, ef = 40%, and rvf = 41%, and vv = 55 ml, vfi = 5.6 ml/s, ef = 58%, and rvf = 38% in 2 male patients respectively. the measured parameters that quantify venou s function on 2 healthy subjects (vv > 60 ml, vfi < 2 ml/s, ef > 60 %, rvf< 35%) and 2 patients (vv < 60 ml, vfi > 2 ml/s, ef < 60%, rvf> 35%) were comparable to those reported in the literature [3, 7-8, 11]. fig. 4 changes in venous volume during different maneuvers measured by the stretch sensors on a normal subject (vv=100 ml, vfi=1 ml/s, ef=84.4%, rvf = 14.9%) fig. 5 changes in venous volume during different maneuvers measured by the stretch sensor on a patient (vv=51 ml, vfi=4.6 ml/s, ef=40%, rvf=41%) 4. discussion fig. 4 and fig. 5 show noticeable differences in the waveform which is evident from the calculated values of vv, vfi, ef, and rvf. however, the very distinctive region in the waveform is also the regular peak seen with each tip toe during repeated pla ntar flexion in a normal subject and random peaks in a patient. the random peaks with each tip toe may be due to the inability of the calf muscle to contract normally because of the pathological changes in the venous system of the lower extremities. this also means that there is an indirect effect of the deep veins which are entirely encased within the muscle and bone. since the calf muscle (pump) is not capable of functioning normally, this would result in the pooling of blood as evident from the data (rvf > 35%) shown in fig. 4. in the normal situation, when the calf muscle contracts, the pressure in the deep veins increases to nearly 250 mmhg allowing the ejection of blood to the heart uni-directionally [12]. this is possible since the ejection fraction of the calf muscle pump is 65 % as compared to thigh pump which is only 15 % [12]. in our study, the venous duplex was also performed on patients and it showed (i) increased superficial reflux, (ii) no deep venous reflux, (iii) no deep venous thrombosis and (iv) increased perforator reflux. the increased perforator reflux could possibly be attributed to valvular incompetence in the perforators. this would further result in increased superficial reflux due to retrograde flow from the perforators to the sup erficial veins when the pressure in the deep veins increases during muscle contraction (vfi = 4.6 ml/s, minor reflux) in one of the patient [11]. in summary, we demonstrated the assessment of venous hemodynamic by using the stretch sensors, which has not been reported in the literature. the belt can be used with great ease besides; it can provide continuous information about the dynamic movement or changes in limb circumference over time. this is desirable in a clinical setting that requires simple and fast means of assessment as well as meaningful information. advances in technology innovation, vol. 3, no. 3, 2018, pp. 141 146 copyright © taeti 146 5. conclusions commercially available air plethysmograph (apg) which is used as a standard tool for assessment of venous hemodynamic is very expensive for a low income and developing country like india. we have shown the possibility of measuring venous volume and therefore, assessment of venous hemodynamic by using arrays of the novel stretch sensors along the calf muscle. although the result looks promising, more data collection is required for validating the novel device for its applications in clinical settings. references [1] r. a. oliveira, n. barros jr., and f. miranda jr., “variability of venous hemodynamics detected by air plethysmography in ceap clinical classes,” jornal vascular brasileiro, vol. 6, no. 4, pp. 359-365, december 2007. [2] c. wittens, a. h. davies, n. bæ kgaard, et al., “editor’s choice management of chronic venous disease: clinical practice guidelines of the european society for vascular surgery (esvs),” european journal of vascular and endovascular surgeryg, vol. 49, no. 6, pp. 678-737, june 2015. [3] v. ibegbuna, k. t. delis, and a. n. nicolaides, “haemodynamic and clinical impact of superficial, deep and perforator vein incompetence,” european journal of vascular and endovascular surgeryg, vol. 31, no. 5, pp. 535-541, may 2006. [4] a. n. nicolaides and d. s. sumner, investigations of patients with deep vein thrombosis and chronic venous insufficiency , la: med-orion publishing, january1991. [5] b. o’brien, t. gisby, and i. anderson, “stretch sensors for human body motion,” proc. spie, vol. 9056, pp. 905618-1-905618-9, 2014. [6] s. raju, “new aproaches to the diagnosis and treatment of venous obstruction,” journal of vascular surgery, vol. 4, no. 1, pp. 42-54, july 1986. [7] e. criado, m. a. farber, w. a. marston, et al., “the role of air plethysmography in the diagnosis of chronic venous insufficiency,” journal of vascular surgery, vol. 27, no. 4, pp. 660-670, april 1998. [8] b. b. lee, a. n. nicolaides, k. myers, et al., “venous hemodynamic changes in lower limb venous disease: the uip consensus according to scientific evidence,” international angiology, vol. 35, no. 3, pp. 236-352, june 2016. [9] s. wankhar, a. a. kota, and d. selvaraj, “a versatile stretch sensor for measuring physiological movement using a centre loaded, end supported load cell,” journal of medical engineering and technology, vol. 41, no. 5, july 2017. [10] j. j. bergan and n. bunke-paquette, the vein book, 2nd ed., usa: oxford university press , 2014. [11] m. l. katz, a. j. comerota, and r. kerr, “air plethysmography (apg): a new technique to evaluate patients with chronic venous insufficiency,” the journal of vascular technology, vol. 15, pp. 23-27, 1991. [12] m. h. meissner, “lower extremity venous anatomy,” seminars in interventional radiology, vol. 22, no. 3, pp. 147-156, 2005.  advances in technology innovation, vol. 2, no. 4, 2017, pp. 130 132 130 oxidation of titanium and ti/ (tib+tic) composite poonam yadav , dong bok lee * school of advanced materials science and engineering, sungkyunkwan university, suwon 16419, south korea. received 09 october 2016; received in revised form 29 november 2016; accepted 30 november 2016 abstract titanium and titanium matrix composite reinforced with 10 vol. % (tib+tic) (10tmc) were oxidized at 700, 800 and 900 o c for 30, 50 and 70 h, and their oxidation behavior was studied. oxidation of ti and 10tmc in air led to the formation of rutile-tio2 without any other oxides. the oxide scale thickened with an increase in the oxidation time and temperature. significant growth of the rutile oxide caused thermal stresses which generated during oxidation and voids formed at the scale/matrix interface, and the oxide scales were susceptible to cracking. keywords : titanium, titanium matrix composite, oxidation, oxide scale 1. introduction titanium and titanium alloys are light in weight, have high tensile strength, toughness, and excellent corrosion resistance. they are widely used for highly demanding structural parts such as aircrafts, chemical plants, automotive, ocean engineering, oil refinery, biomaterials, highly stressed components, and military applications [1-3]. recently, the introduction of particulates or continuous fibers with low density and high elastic modulus into titanium alloys has further improved the specific modulus, specific strength, creep resistance, wear resistance, and the service temperatures [4-8]. in order to utilize the titanium matrix composites (tmc) for industrial purpose, the oxidation study is imperative. in this study, the oxidation behavior of titanium and titanium matrix composite reinforced with 10 vol.% (tib+tic) particulates (hereafter, designated as 10tmc) were investigated after isothermally oxidizing at 700-900 o c for 30-70 h in air. particulate reinforced titanium matrix composites have attracted considerable attentions. 2. experimental titanium and the mold for tmcs were prepared by a common casting technique [9]. prepared mold was mounted in the vacuum induction melting furnace. after that, b4c (99% purity, 1500 mm, 150 mm and 0.5 mm) was added to pure ti (99% purity, grade 2), following which the synthesis of the tmcs was carried out using vacuum induction melting. the pressure of the furnace atmosphere was held at 1.33 x 10 -1 pa and charged with inert argon gas at a pressure of 4.9 x 10 3 pa. the oxide mold was super-heated sufficiently to overcome the problem of low viscosity of tmcs, and then 1.88 mass% b4c was added to the pure ti in the graphite crucible in order to form the 10 vol% of (tib+tic) reinforcement [9]. ti and 10tmc samples were cut to 10x10x2 mm 3 in size, mechanically polished, and ultrasonically cleaned with ethanol solution. research materials were oxidized at 700, 800 and 900 o c for 30, 50 and 70 h in air. following oxidation process, matrix phases and oxide scales were investigated using scanning electron microscopy (sem) equipped with energy dispersive spectroscopy (eds), x-ray diffraction (xrd) using cu-kα radiation operated at 40 kv and 100 ma. the matrix grain sizes were measured through the conventional mean-linear-intercept method using sem. the vickers microhardness was measured with a load of 100 n for 5 sec for more than 5 points on each sample at ambient temperature. 3. results and discussion fig. 1 shows the x-ray diffraction patterns of the oxide scales formed after isothermal oxidation at 800 o c for 70 h. fig. 1 x-ray diffraction patterns after oxidation at 800 o c for 70 h. (a) titanium, (b) titanium matrix composite rein-forced with 10 vol.% (tib+tic) fig. 2 sem image after oxidation at 900 °c. titanium for (a) 30 h, (b) 50 h, and (c) 70 h. titanium matrix composite reinforced with 10 vol.% (tib+tic) for (d) 30 h, (e) 50 h, and (f) 70 h *corresponding author, email: dlee@skku.ac.kr advances in technology innovation, vol. 2, no. 4, 2017, pp. 130 132 131 copyright © taeti 100µm (b) scale epoxy matrixvoids cracks 100µm (c) scale epoxy matrixvoids cracks 100µm (a) scale epoxy matrix voids cracks 20µm (d) scale epoxy matrix voids cracks 20µm (e) scale epoxy matrix voids cracks 20µm (f) scale epoxy matrix voids cracks 50 h 30 h 70 h 10%tmc pure ti for titanium and 10tmc, the oxide scales consisted of rutile-tio2 without any other oxides. apparently, boron and carbon in (tib+tic) evaporated during oxidation. sem micrographs are shown in fig. 2. the oxide grain size of 10tmc increased with an increase of an oxidation time more rapidly than that of pure titanium. particularly, the coarse rutile-tio2 grains formed on 10tmc after oxidation at 900 °c for 70 h were noticeable. fig. 3 shows the grain evolution of oxide grains that formed on 10tmc as a function of the oxidation temperature. the grain size has increased proportionally to the oxidation temperature, owing to the increased reaction and diffusion rates at high temperature. fig. 3 sem image of oxide scales formed on titanium ma-trix composite reinforced with 10 vol.% (tib+tic) after oxidation for 70 h at (a) 700 °c, (b) 800 °c, and (c) 900 °c fig. 4 sem cross-section image after oxidation at 900 °c. titanium for (a) 30 h, (b) 50 h, and (c) 70 h. titanium matrix composite reinforced with 10 vol.% (tib+tic) for (d) 30 h, (e) 50 h, and (f) 70 h fig. 4 shows the cross-section of titanium and 10tmc after oxidation at 900 o c for 30, 50, and 70 h. as the oxidation reaction proceeded, oxide layer formation has generated stresses, which induced cracking and delamination of the oxide scale. these effects in voids formation at scale/metal interface that could act as stress concentration sites. voids apparently formed owing to the significant outward diffusion of ti ions to form thick tio2 oxide scale. the average thickness of the oxide scale was 340 μm (fig. 4(a)), 350 μm (fig. 4(b)), 400 μm (fig. 4(c)), 125 μm (fig. 4(d)), 170 μm (fig. 4(e)), and 190 μm (fig. 4(f)). the addition of 10 vol. % (tib+tic) beneficially improved the oxidation resistance of the ti metal. during the initial stage of oxidation, oxygen is absorbed on the surface of the metal by physisorption. the oxygen molecules dissociate creating oxygen anions through a chemisorption process until a monolayer of oxide is formed. fig. 5 shows the sem/eds analysis results of 10tmc after oxidation at 700 °c for 70 h. the oxide scale was 7 μm-thicks (fig. 5(a)). unlike in the fig. 4, the oxide scale was dense, adherent, and crack-free owing to the slower growth rate and less thermal stresses generated during oxidation. fig. 5 titanium matrix composite reinforced with 10 vol.% (tib+tic) after oxidation at 700 °c for 70 h. sem cross-section, (b) eds line profiles along a-b vickers microhardness of 10tmc was measured at the surface of the formed oxides as a function of the oxidation time and temperature, and presented in fig. 6. during the early stage of oxidation, the microhardness increased at each temperature owing to the formation of thin hard oxide scale. the microhardness increased with higher oxidation temperature. however at the later stage of oxidation, the microhardness decreased to a certain extent. fig. 6 microhardness of titanium matrix composite rein-forced with 10 vol.% (tib+tic) [top of the surface] as a function of oxidation time and temperature advances in technology innovation, vol. 2, no. 4, 2017, pp. 130 132 132 copyright © taeti copyright © taeti copyright © taeti copyright © taeti copyright © taeti it is clear that, the hardness increases with temperature as well as with the oxidation time, up to 30 hrs. further oxidation causes the hardness to decrease; this may be attributed to stress relieving of the oxide grains arisen during heating stage of the oxidation process which induce cracking and delamination of the oxide scale. an evident matching with the results obtained from density; as the density increases, the hardness increases. 4. conclusions the oxidation behavior of titanium and 10tmc was investigated after isothermal oxidation at 700, 800 and 900 o c up to 70 h. the xrd analysis revealed that the oxide scale consisted of rutile-tio2.the scale thickness, growth and thermal stress increased with the increase in the oxidation time and temperature. the oxidation at 900 o c for 70 h led to the cracking and void formation in the oxide scale as well as around the oxide scale/matrix interface. microhardness of the oxide scale increased for the short stage of oxidation (30 h) and decreased for at the longer oxidation times (70 h) due to the stress-relieving arisen by the oxide grain growth. acknowledgement this work was supported under the framework of international cooperation program managed by national research foundation of korea (2016k2a9a1a01952060). references [1] m. yamada, “an overview on the development of titanium alloys for non-aerospace application in japan,” material science and engineering a, vol. 213, pp. 8-15, 1996. [2] m. peters, j. hemptenmacher, j. kumpfert, and c. leyens, titanium and titanium alloys: fundamentals and applications, germany: wiley-vch, pp. 1-36, 2003. [3] s. r. seagle, “the state of the usa titanium industry in 1995,” material science and engineering a, vol. 213, pp. 1-7, 1996. [4] s. abkowitz, p. f. weihrauch, s. m. abkowitz, and h. l. heussi, “the commercial application of low-cost titanium composites,” journal of metals, vol. 47, pp. 40-41, 1995. [5] s. ranganath, “a review on particulate-reinforced titanium matrix composites,” journal of materials science, vol. 32, pp. 1-16, 1997. [6] f. h. froes, “recent advances in titanium metal matrix composites,” usa, tms, warrendale, pa, 1995. [7] t. yamamoto, a. otsuki, and k. ishihara, “synthesis of near net shape high density tib/ti composite,” material science engineering a, vol. 239, pp. 239-240, 1997. [8] d. b. lee, y. c. lee, and d. j. kim, “the oxidation of tib2 ceramics containing cr and fe,” oxidation of metals, vol. 56, pp. 177-189, 2001. [9] b. j. choi and y. j. kim, “effect of b4c size on tensile property of (tib+tic) particulate rein-forced titanium matrix composites by investment casting,” materials transactions, vol. 52, pp. 1926-1930, 2011. http://link.springer.com/journal/11085 http://link.springer.com/journal/11085  advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 point-structured human body modeling based on 3d scan data ming-june tsai 1,* , hsueh-yung lung 1 1department of mechanical engineering, national cheng kung university , tainan, taiwan. received 05 june 2017; received in revised form 13 september 2017; accepted 20 september 2017 abstract a novel point-structured geometrical modelling for realistic human body is introduced in this paper. this technique is based on the feature extraction from the 3d body scan data. anatomic feature such as the neck, the arm pits, the crotch points, and other major feature points are recognized. the body data is then segmented into 6 major parts. a body model is then constructed by re-sampling the scanned data to create a point-structured mesh. the body model contains body geodetic landmarks in latitudinal and longitudinal curves passing through those feature points. the body model preserves the perfect body shape and all the body dimensions but requires little space. therefore, the body model can be used as a mannequin in garment industry, or as a manikin in various human factor designs, but the most important application is to use as a virtue character to animate the body motion in mocap (motion capture) systems. by adding suitable joint freedoms between the segmented body links, kinematic and dynamic properties of the motion theories can be applied to the body model. as a result, a 3d virtual character that is fully resembled the original scanned individual is vividly animating the body motions. the gaps between the body segments due to motion can be filled up by skin blending technique using the characteristic of the point-structured model. the model has the potential to serve as a standardized datatype to archive body information for all custom-made products. keywords: 3d body model, body motion animation, feature recognition 1. introduction human body modeling is the act that creates a proper shape description for a specific human body. the shape description is a geometrical representation in the 3d computer environment and, usually, combined with skin coloring and texture mapping to perform more realistic results. a convenient way to obtain a realistic representation of human body in the virtual world is using 3d dig itizing technique [1]. recently, a number of 3d scanning systems with the ability to quickly and easily obtain digital human body model are now commercially availab le [2-5]. however, the scanned point cloud is commonly scattered and unorganized, and only very little semantic information involved. processing the raw data, therefore, is a crucial task in the extendable utilit ies of the human body scans. a number of data processing for human body scans, such as the data segmentation for significant parts, the indication of landmarks and feature points, and the dimension measurements, have now been proposed [6-9]. it is obvious that the key point to turn the raw scanned data into useful informat ion should be by means of feature recognition, data extraction, and symbolization. the feature ext raction plays an important ro le not only in the description of human body, but also in the anthropometric analysis of human factor designs. recently, a novel method of body feature extract ion from a marker-less scanned body was presented [10-11], in which the description of human body features are interpreted into logical mathemat ical defin itions. tsai and fang [12] patented a feature based data structure for computer manikin. accordingly, the body scanned d ata are segmented into 6 six parts: head, torso, two arms and two legs. each part can be encoded into a range image format, and then the feature points and curves are recognized according to the gradient of the gray scale in the range image format. a point -structured * corresponding author. e-mail address: mjtsai@mail.ncku.edu.tw advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 2 geometric model is constructed by re-sampling the original 3d scanned data into an interweaving geodetic latitudinal and longitudinal curves, and then achieving an accurate model to describe the human body . there is also an increasing demand for realistic human animation models in various applications such as interactive computer games, virtual reality, and movie amusement industry. although an artificial model is able to serve as useful animation tool to control articu lated mot ions and body surface deformat ions according to different body postures, it is still required a large degree of skill and manual intervention for more realistic. however, it resembles to nobody. currently, a lo t of studies on human motion capture and analysis have been presented [13-16]. so far, there is no direct way to use the personalized body model to animate his own body motion. it is persuasive that using the body model created from the scanned human body data to animate his own personalized body motions will yield a more realistic result without laborious motion retargeting intervention because it is a d irect and an efficient way to exhib it precious body motions. by appropriately addin g joint freedoms between the body links to cons truct a kinematic model, the point-structured geometric models obtained by scanned data can naturally and exactly be animated. in this paper, we have also shown that the skin gaps between the body segments due to motion can be filled up by dual quaternion linear blending using the characteristic of the point-structured model. 2. point-structured geometric model the surface informat ion of human body can be obtained quickly and easily by using 3d scanning technology. however, the scanned data points without further processing are un-organized and are too huge to be directly used in practice. therefore, a proper way of the data processing with the ability to reduce the amount of cloud points while ext racting the significant characteristics of human body will be extremely beneficial for further applicat ions. such a process can be achieved by employing the computational geometry and image processing techniques on the scanned point cloud. according to the geometric characteristics of human body, it is general to divide the body into six topological parts: head, torso, two arms and two legs. the arms can be segmented from the body by the armpit, and the legs can be segmented by the crotch. in the following, we only illustrate the method of point-structured modeling for the torso. 2.1. feature recognition the outside contour of a human body is a very complex smooth surface, and it is difficult to be described and represented clearly without the help of some body significant features. by the way, the dimensional measurements of the body used in garment design and anthropometric surveys are always dependent on the feature points and feature lines. however, it seems that there is no unanimity on the definit ions of these specific body features in the literatures [17-18]. in order to ext ract these feature lines and feature points from the 3d scanned point cloud automatically, the semantic definit ions of body features are needed to be interpreted into the mathemat ical definit ions. a number of methods based on the image processing techniques, computational geometry and computer graphics have been used to identify these features from the 3d scanned points. and the developed algorithms fo r searching these features automatically have been presented in [10-12]. the body feature lines searching result by [11] is shown in fig. 1(a). a point-structured model of the torso is developed using the concept of geodetic coordinate, which is similar to the longitudinal and latitudinal lines of the earth. it means that the longitudinal cu rves include all the feature curves in the vertical direction of the torso, whereas the latitudinal curves contain all the feature girth lines of the body. therefore, all the significant features can be preserved well in such a point-structured representation. the girth lines in horizontal are important in the description of body curve. consequently, a total of 60 sections are arranged in the representation as shown in fig. 1(b). exc ept advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 3 for the already ext racted feature g irths which have been assigned as specific orders, the others between each interval are needed to be re-sampled by the method of interpolation from the original 3d scanned point cloud. the interpolation is conducted with a uniform distribution within each interval. front centerline upper neck line lower neck line shoulder line shoulder girth armpit girth bust girth under bust girth waist girth mid-waist girth hip girth crotch girth side line side line armhole armhole princess lines princess lines shoulder line back centerline 6 0 g ir th s (a) body feature lines searching result by [11] (b) arrangement of structured girth lines fig. 1 body feature lines obtained from the 3d body scanned point cloud and the re-sampled girth lines 2.2. structured points in general, there are a total of 80 structured points (0~79) used to characterize the circumference of each latitudinal g irth line. some specific structured points are needed to correspond to some feature points, respective. it means that they are assigned to locate on the longitudinal feature lines. for example, the structured points along the armpit girth are illustrat ed in fig. 2. therefore, each structure point has a body geodesic coordinates (bgc) (g, h). where g designates the number of the girth that the point is located; and h is the order of the point on the girth, which also denotes the number of the longitudinal curve. for example, the two po ints with numbers (38, 10) and (38, 70) represent the left and right bust points, which are very important landmarks of the human body. the bgc are standardized and normalized in our body model regardless of the gender, age, shape and race of the human. similarly, the structured points between two adjacent feature points are also generated by interpolation with a uniform distribution. it is clear that the point densities of these intervals are different. the reason is for the curve section with a larger curvature to have more points used for proper representation. fig. 2 structured points of the armpit girth line [12] 2.3. processing result the process to obtain the point-structured model of human body is very sophisticated. for the torso, a lot o f significant features with special geometric propert ies are needed to be recognized. based on these features, the concept of longitude and latitude are applied to construct the point-structured torso model. as a result, a feature-based bgc data structure is included in the point-structured model. such a concise representation, as shown in fig. 3, contains all the body features, anthropometric data, and body shape in the torso, it just like a body atlas that can be readily extracted as needed . advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 4 fig. 3 point-structured torso model and its polygonal mesh in contrast to the torso, to obtain the point-structured models of the two arms and two legs are simpler. the arm can be divided into upper arm and lower arm by the elbow girth. due to the cylindrical shape of arm, its point -structured model can be constructed by using several girth lines distributed along the cylindrical axis. likewise, the point -structured model of the leg can be conducted by the same way. a more detailed statement of the model construction is shown in [19]. finally, a fu ll 3d point-structured body model consisting of only 10,214 structured points is obtained and is shown in fig. 4. the body model is also called the body geometric model (bgm). (a) point cloud (b) point-structured model (c) meshed by triangulation fig. 4 a 3d bgm 3. animation model it is demonstrated in this section how to converse the bgm into a kinematic model that can be used for animation purpose. before the 3d body scanned points can be used for animation, the scanned points should be put in well-organized order, this is our bdm. however, the bgm still cannot be animated because it has no joint freedom. it means that the segmentation of the body scanned data should be according to the anatomical structure for jo int arrangement. by the way , a joint model with high degrees of freedom is required for performing much more human-like motion. with the kinemat ic analysis based on the joint model, it is not difficult to converse the bgm into an articulated kinemat ic model (bkm). fortunately, the bgm has been segmented according to the anatomic feature at some joint positions. we just need to add appropriate joint freedoms between the adjacent body links. a realistic human kinematic body can be built for motion animation . 3.1. segmentation a virtual human model to perform much more human-like mot ion is generally dependent on how many degrees of freedom (dofs) it has. in order to achieve highly realistic human animation, the whole bgm is further divided into 23 parts as advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 5 shown in fig. 5. these parts will be viewed as the body links, and a suitable number of joint freedoms are assigned to each of adjacent links. then, the joint-link kinematic model (bkm) is constructed for human mot ion animat ion. the jo int -link hierarchical structure is modeled by five kinematic chains. the first chain consists of hip, waist, chest, neck, and head. the hip is the base frame in this hierarchical structure. chains 2 and 3 are composed of the scapula, upper arm, lower arm, hand and fingers on the left and right, respectively. the left and right thighs, lower legs, feet and toes are the links of chain 4 and 5, respectively. please note all of these links come from the point-structured bgm which is constructed by the 3d scanned data of a specific person. so far, we have finished a compact static bgm with personal shape and appearance. for human animat ion, the only requirement is to use the bkm of the specific person and then animate these segmented link models by applying the motion data. left toe left foot left lower leg left thigh left fingers left hand left lower arm left upper arm left scapula head neck right toe right foot right lower leg right thigh right fingers right hand right lower arm right upper arm right scapula chest waist hip fig. 5 segmentation for articulated human model 3.2. kinematic model according to the anatomical structure of human body, the type-1 bkm in this study is conducted by 5 kinematic chains with a total of 48 degrees of freedom, not counting the 6 dof in the pelvis. the pelvis is considered as the based link of the body, which has 6 dof with respect to the fix coordinate system, and all the other joint freedoms are computed based on this link. however, human body has many more jo int freedoms that performs very complex body motion. it is familiar that more dofs will lead to a more realistic motion. however, too many dofs also involve a rise in complexity and computational cost. it is a trade-off that which kind of kinematic model is good enough for what kind o f body motion. in our study, it is believed that 48 joint freedoms are suitable for animating most of the body motions . (a) segmented body model (b) bkm with 48 dofs (c) bkm with 31 dof fig. 6 joint arrangement of the articulated models [20] advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 6 as shown in fig. 6, there are 20 jo ints arranged in the different locations on the bkm. the four jo ints at l_grasp, r_grasp, l_toe and r_toe each has one dof only. there are 8 jo ints with two dofs, i.e . l_elbow, l_wrist, l_knee, l_ankle, r_elbow, r_wrist, r_knee and r_ankle. the three-dof joints are l_shoulder, l_leg, r_shoulder and r_leg. all of these joints are regarded as revolute jo ints. subsequently, the four joints (neck, waist, l_scapula and r_scapula) are modeled as four-dof joints composed of three revolute freedoms and one pris matic freedom sliding along the last rotational axis. consequently, the model possesses totally 48 dofs in the 20 jo ints. other kinematic models with different number of joint freedoms can be created, e.g. the type-2 bkm shown in fig. 6(c), which has 31 dof to simulate a conventional humanoid robot. it is difficu lt to locate the jo int axes at exact position and orientation since the real human joints are not simply the rev olute or pris matic. if the human movements can be captured by a precision motion tracker, it is possible to locate the joint axes accurately. however, using a good bkm with enough joint freedoms, people can replicate the mot ion without problem. that is why the realistic human animation can be carried out by using the motion capture system. therefore, the motion data recorded from a mot ion capture system p lays an important role to produce highly realistic human animations. based on the bgm and bkm, tsai and lung [20] employs a self-made mot ion capture system to acquire the space information of all links, and then use the method of two-phased optimization to solve the joint angles via inverse kinematics. besides, an intelligent body motion processing system (ibmps) has also been developed by tsai and lung [21 ]. the result shows that highly realistic human animat ions can be achieved using the ibmps. while apply ing the original motion data to bgm and the joint angles to the bkm, the comparison for four postures is shown in fig. 7, in which all of these body segments are displayed without any blending function for the joint deformations . fig. 7 motion captured model compared with the model after optimization [21] 3.3. skin blending because the segmented body parts are viewed as the links which are usually treated as rig id bodies, it is in ev idence the relative movement of two ad jacent links will cause some kinds of splits or penetrations on the joint position, which are in-appropriate for looking in an animation system. in order to have a more authentic appearance, blending function is employed on the structure points to overcome this problem. fig . 8 illustrated the effect of the blending function. it is obvious that the gaps at the joints (between the adjacent links) have been filled s moothly. the skin b lending is fu lfilled by employing sclerp (quaternion spherical linear interpolation) by using constant volume of the links as the constraint before and after blending. as a result, it yields a highly realistic representation with the blending. since the bgm contains the information of skin location, we will know how to move the structure point by studying the skin deformat ion during a body movement. this is another benefit of using the point-structured bgm. advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 7 fig. 8 the effectiveness of blending function 4. conclusions human body modeling is now a very hot research topic. to produce highly realistic 3d human an imation is very useful for many applications. reality is always dependent on both of the realistic appearance and movements. in this paper, we use the point-structured modeling method to maintain the real boy shape and reduce the amount of data points considerably. we also construct appropriate bkm to achieve the highly authentic body motion replication. it demonstrated that such a point structured human body model is very useful in the dig ital human body modeling and realistic body motion animat ion. the body model can also be used as a mannequin in garment industry, or as a manikin in v arious human factor design since it contains all the body dimensions, shape, as well as all body features . acknowledgements this research was supported by the project of national science council, (project number: nsc 99-2221-e-006-018-my3), and ministry of science and technology of taiwan (pro ject number: most 103-2221-e-006-024) which are greatly appreciative. references [1] m. petrov, a. talapov, t. robertson, a. lebedev, a. zhilyaev, and l. polonskiy, “optical 3d dig itizers: bring life to the virtual world,” ieee computer graphics and application, vol. 18, no. 3, pp. 28-37, may 1998. [2] cyberware, http://www.cyberware.com, 2012. [3] tc2, http://www.tc2.com, 2012. [4] vitus, http://www.vitronic.de, 2012. [5] creaform, http://www.creaform3d.com, 2012. [6] j. h. nurre , j. connor, e. a. lewark, and j. s. collier, “on segmenting the three-dimensional scan data of a human body,” ieee transactions on medical imaging, vol. 19, no. 8, pp. 787-797, august 2000. [7] x. ju, n. werghi, and j. p. siebert, “automatic segmentation of 3d human body scans,” proc. of iasted int. conf. on comp. graphics and imaging, 2000. [8] k. robinette, m. boehmer, and d. burnsides, “3-d landmark detection and identification in the caesar pro ject,” proc. 3rd int. conf. on 3-d digital imaging and modeling, pp. 292-298, 2001. [9] r. p. pargas, n. j. staples, and j. s. davis, “automatic measurement extract ion for apparel from a three -dimensional body scan,” optics and lasers in engineering, vol. 28, no. 2, pp. 157-172, september 1997. [10] m. j. tsai, z. p. chen, and y. s. liu, “a study on the automatic feature search from 3d body scanners,” proc. of the 20th national conference, society of chinese mechanical engineering, taipei, december 2003. advances in technology innovation, vol. 3, no. 1, 2018, pp. 01 08 copyright © taeti 8 [11] i. f. leong, j. j. fang, and m. j. tsai, “automatic body feature extract ion from a marker-less scanned human body,” computer-aided design, vol. 39, no. 7, pp. 568-582, july 2007. [12] m. j. tsai and j. j. fang, feature based data structure for computer manikin, us patent, 7,218,752 b2, may 15 2007. [13] l. a. wang, w. m. hu, and t. n. tan, “recent development in human motion analysis,” pattern recognition, vol. 36, no. 3, pp. 585-601, march 2003. [14] j. k. aggarwal and q. cai, “human motion analysis: a review,” computer vision and image understanding, vol. 73 , no. 3, pp. 428-440, march 1999. [15] t. b. moeslund and e. granum, “a survey of computer vision -based human motion capture,” computer vision and image understanding, vol. 81, no. 3, pp. 231-268, march 2001. [16] r. poppe, “vision-based human mot ion analysis: an overview,” computer vision and image understanding, vol. 108, no. 1-2, pp. 4-18, october-november 2007. [17] international organization for standardization, garment construction and anthropometric surveys – body dimensions, reference no. 8559-1989, switzerland: iso, 1989. [18] astm, standard termino logy relat ing to body dimensions for apparel sizing, astm designation: d 5219-99, usa, 1999. [19] m. j. tsai, h. w. lee, and h. y. lung, “feature-based data structure for digital manikin,” u.s. patent , us 20130069936 a1, march 21, 2013. [20] m. j. tsai and h. y. lung, “two-phase optimized inverse kinematics for motion replication of real human models,” journal of the chinese institute of engineers, vol. 37, no. 7, pp. 899-914, april 2014. [21] m. j. tsai, j. h. chao, and t. w. yang, “construction of a general motion editing system for human body and humanoid robots,” proc. asme 2014 int. design engineering technical conf. & computers and information in engineering (idetc/cie 2014), asme press, august, 2014, pp. v01at02a072.  advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 single-crossarm stainless steel stayed columns radek pichal, josef machacek* faculty of civil engineering, czech technical university in prague, prague, czech republic. received 05 june 2017; received in revised form 04 july 2017; accepted 11 august 2017 abstract stability and strength of imperfect stayed columns are studied in 3d using ansys software. following three tests of stayed columns with a reasonable geometry, the numerical modelling is validated and subsequently compared with available analytical and numerical 2d results. arrangement and values of prestressing of ties and initial deflections of the columns affecting the nonlinear stability problem are discussed in a detail. the effect of nonlinear stress -strain relationship corresponding to common stainless steel material is shown, with respect to loading level corresponding to loss of the column stability. the assembly technique of the stayed columns is taken into account, comparing the method and stability/strengths of columns with fixed or sliding stays in the connection to the central crossarm. finally some recommendations concerning the analysis and use of such stayed columns are given. keywords: stayed columns, stainless steel, prestressing, nonlinear buckling, nonlinear material, sliding stays 1. introduction extremely slender compression columns are required particularly in unique structures both by architects and investors. however, the slenderness is limited by a required strength and possible deflections due to buckling. well-known solution for the problem are frequently used prestressed stay columns, made usually from a central slender column, several lateral crossarms each with two planar arms (arranged in a plane with the column) or crossarms in space with three (arranged in 120º) or four (arranged in 90º) arms and prestressed stays formed by cables or rods, see fig. 1. (a) grande arche, paris (b) parc del centre del poblenou, barcelona (c) estádio algarve, faro fig. 1 examples of the stayed columns used in famous structures * corresponding author. e-mail address: machacek@fsv.cvut.cz tel.: +420776562811 advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 10 analytical analysis of the stayed columns with multiple pin-connected crossarms and validated by tests was developed by chu and berge [1] in the sixtieth. following analytical research by other authors was accomplished by smith et al. [2] and ha fez et al. [3]. they analyzed a stayed column with one central crossarm rigidly connected (welded) to the column. the column was ideally straight and concentrically loaded, the stays were fixed to the crossarm in ideally hinge connection and the buckling was supposed to occur in the plane of the crossarm member. they analyzed planar arrangement (with two arms of the crossarm) but the solution covered also space arrangement with 4 arms positioned in 90º (fig. 2). the analysis resulted into critical (buckling) loading for an arbitrary stays prestressing, considering symmetrical or antisymmetrical mode of buckling. however and more important, they also discovered three zones of the behavior depending on the level of the stays prestressing: zone 1 (up to tmin), where the prestressing in the stays disappears when the applied load is less or equal to the euler load (ncr = ne); zone 2 (up to an optimal prestressing topt), where the stays remain effective until the applied load triggers a buckling; zone 3 (above topt), where all the stays remain active (in tension) even after buckling. higher prestressing than topt increases the column loading and, therefore, decreases the critical column load ncr, see fig. 2. n n stays a , e crossarm a , i , e s s a a a column a , i , ec c c x z y t t t t l a aa a n [kn] t t 3toptmin n cr,max n = n cr,min e opt t ~ 0 .4 t o p t z o n e 1 zone 2 zone 3 a b cr critical load n by hafez et al.cr max n for 2a/l = 0.2 max n for 2a/l = 0.1 (a) geometry of the stayed column (b) critical and maximal loadings fig. 2 geometry, critical and maximal loading acc. to wadee et al. (see later) for initial deflection wo = l/200 vs stays prestress numerous other authors investigated influence of initial imperfections (e.g. wong and temple [4], chan et al. [5]). important findings resulted from the later, concerning recommendations for the maximal loading vs optimal pretension of imperfect columns, stay areas and crossarm lengths with respect to buckling modes and, therefore, resulting maximal loading. another study of buckling and postbuckling behavior of “nearly perfect” prestressed stayed columns was presented by saito and wadee [6]. they used both analytical and numerical (abaqus software) analysis and drew attention to stable post-buckling paths in zone 1 and initial part of zone 2, while unstable post-buckling path in zone 3. they also mentioned a danger resulting from changes in the ambient temperature, necessity of modelling in 3d and in [7] studied significance of interactive buckling in a column with one central crossarm (combination of symmetrical and antisymmetrical modes of buckling). two tests of prestressed stayed columns with a reasonable size of l= 12 m and a = 600 mm were performed by araujo et al. [8]. the specimen were placed in horizontal position, the first one with negligible prestressing while the second with typica l prestressing. significant increase of maximal loading in comparison with the capacity of a column without any sta ys was affirmed. the research was accompanied with numerical analysis and parametric studies on values of initial deflections and diameter of stays (cables or rods), while using ansys software. extension of the studies (with a use of tests by servitova and machacek [9]) the authors published in [10]. large experimental analysis of imperfect prestressed stayed columns with one central crossarm was presented by osofero et al. [11]. totally 18 specimens in vertical position with length of l = 2800 mm and variable arms a = 100 ÷ 420 mm were tested. a knife-edge support of the central column forced the buckling into the prescribed plane by either in symmetric or antisymmetric mode, depending mostly on ratio l/a. the tests provided the actual maximal loads nmax depending on the stays prestress t є (0, 4topt), and pointed out to interactive buckling mode for cases where symmetric and antisymmetric buckling loads approximately coincided. advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 11 complex numerical analysis of imperfect prestressed stayed columns resulting in the design recommendations was published by wadee et al. [12]. they analyzed planar stayed columns with three levels of initial deflection amplitudes (l/200, l/400, l/1000) for symmetrical and antisymmetrical buckling modes, using abaqus software. after some adjustments to correlate the numerical values with test data, the results are presented for strengths of the columns in a normalized form of nmax/ncr, symmetrical (for 2a/l < 0.175) and antisymmetrical (for 2a/l > 0.175) modes of buckling and four levels of the stays prestressing: zone 1 (t < tmin), zone 2a (t є(tmin, 0,4topt)), zone 2b (t є(0,4topt, topt)) and zone 3 (t є(topt, 3topt)). the results enabled a determination of approximations for maximal ultimate strength nmax for an arbitrary prestressing up to 3topt (shown for two common values of 2a/l in fig. 2, but looking at the picture be aware of the relation to ncr on vertical axis). this article presents a numerical approach of prestressed stainless steel stayed columns with one central crossarm in 3d validated by own tests. the emphasis is laid on nonlinear behavior of the material, space direction of the column buckling and boundary sliding conditions of stays at the crossarm. 2. experiments, numerical modelling and model validation four tests of stainless steel stayed columns with a reasonable length l = 5000 mm were performed at the lab of the czech technical university in prague [9]. the main column was fitted with hinges at both ends (see fig. 3 (a), (b)). the parameters according to fig. 2 were identical for all tests and as follows: the central tube ø 50x2 [mm] (l = 5000 mm, ac = 302 mm 2 , ic = 87009 mm 4 , ec,ini = 184 gpa), the crossarm tubes ø 25x1.5 [mm] (a = 250 mm, aa = 111 mm 2 , ia = 7676 mm 4 , ea,ini = 184 gpa), the stays are macalloy cables 1x19 stainless steel ø 4 mm (ls = 2513 mm, as = 12.6 mm 2 , es,ini = 200 gpa). the stays in all tested columns were sliding at steel saddles of crossarms. material of both tubes was tested in a hydraulic testing machine on a weakened cross-section machined from the full cross sections according to fig. 3(b). the stress-strain relationship of the stainless steel material (1.4301) was derived as an average from three such coupon tensile measurements. it should be noted that initial youn g’s modulus for the stays was accepted in the following numerical analysis due to rather low stresses at collapse loadings, while multilinear isotropic hardening according fig. 3 (a) for the central column and crossarms . 0.002 0.004 0.006 0.008 200 300 400 500 0 0 100 tensile test [mpa]  = 434.1 mpa ansys modelling 0.2 e = 184.0 gpa in e e1 2 e n e 3 e 4 e 5 (a) tested column in the frame position (b) detail of the hinge at supports and central column tensile specimen (c) stress-strain diagram of the austenitic grade 1.4301 stainless steel material fig. 3 assembly and material testing advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 12 after assembly of each of the stayed columns a careful measurements of the space initial deflections was recorded using 3d scanning and electric potentiometers (for more details see [9]). because the initial deflection values of the unprestressed c olumns exceeded in some columns the limits prescribed by en 10219-2 (i.e. l/500), the imposed prestressing was slightly uneven in the four stays to result in the later shown acceptable final initial deflections under each of the selected prestressing. ansys software was used for numerical analysis of both tests and in the following parametrical studies. 3d model was formed using for the central and crossarm tubes beam188 and for cable stays link180 (and no -compression option) elements, all embodying large deflections and material nonlinearity. the steel saddles at tips of the crossa rms were modelled using shell281 elements (fig. 4 (a)) with various frictions coefficients between the saddles and cable stays. after fe meshing the division employed in the analysis was l/250, a/25 and shell elements with area of approx. 23 mm 2 . prestressing of the stays was achieved by a respective thermal change and external loading of the column by an axial displacement x. (a) fe modelling of saddles (b) column 1: comparison of test and ansys analysis fig. 4 ansys detailed modelling and validation with ratio 2a/l = 0.1 and initial deflections roughly in one half wave shape, all the final deflections at the tests and numerical analysis followed the first buckling mode, i.e. one half wave. results of tests and validation of numerical approach is sh own for all 4 tests, using friction coefficient between the saddles and cable stays ν = 0.1 (common for steel-steel friction). column 1: the total applied prestressing in all four stays was 4t = 5.44 kn. the prestressing in each of the 4 stays was slightly different to receive required global imperfection, which in this case had amplitudes at midspan of w0y = 1.9 mm and w0z = 8.3 mm. the test exhibited linear behavior up to approx. 15 kn, followed by a rapid growth of deflection up to maximal ultimate loading of nmax,exp = 17.7 kn and terminated due to enormous deflection, see fig. 4 (b). numerical analysis in 3d covered the initial deflections of one half-sine shape with the above given amplitudes and initial total prestressing 4t, requiring slightly different prestressing in each of the four stays. the comparison of test and numerical analysis is shown in fig. 4 with good agreement. column 2: the total applied prestressing in this case was 4t = 4.54 kn, arranged in the similar procedure as for the column 1, resulting in initial deflections with the mid-span amplitudes w0y = 3.8 mm and w0z = 19.9 mm. up to the external load of 12.5 kn the behavior was nearly linear, followed by enormous increase of deflections and maximal ultimate load of 14.9 kn, when the t est was terminated. here the numerical maximal loading exceeded the test value of approx. 9 %, which was assigned to difficulties with modelling of various prestressing of the 4 stays and keeping the deflections as in the test. column 3: first, column 3a was tested without stays (in the lab reality with attached, but slacked stays). the amplitudes of initial deflections at midspan were w0y = 0.3 mm and w0z = 1.4 mm. the test was terminated due to sudden increase of central deflection (see fig. 5 (b)) under loading nmax,exp  6.5 kn, while common euler’s critical load is ne = 6.3 kn (the difference amounts for 2.8 %). numerical analysis of initially deflected column without stays gives nmax = 6.0 kn < ne. saddle stay crossarm advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 13 (a) comparison of test and ansys analysis for column 2 (b) comparison of test and ansys analysis for column 3 fig. 5 comparison of test and ansys analysis second, the stays in the column 3b were slightly prestressed with total value of 4t = 3.9 kn and resulting final central amplitudes of initial deflections were w0y = 0.5 mm and w0z = 2.2 mm. this test was terminated due to enormous deflections, giving maximal ultimate load nmax = 16.2 kn. instead of numerical analysis of the slightly prestressed column the results of the column with fully slacked (unprestressed) stays is shown for comparison in fig. 5 (b). the numerical results with nmax = 17.0 kn revealed a small “jump” at point a on the load-deflection curve at the level of critical loading, when a buckling activated initially slacked stays on the concave side of the column. the positive influence of the unprestressed stays on the ultimate loading is, therefore, confirmed in agreement with results of [12]. comparison of results of the three tests with the proposed numerical modelling is satisfying an d justifies use of the model for the following numerical studies . 3. critical and maximal loading in 2d and 3d, material nonlinearity numerical analysis of the prestressed stayed columns needs to respect the 3 zones according to the prestress of stays (see fig. 2). as explained in the introduction, the behavior in the zone 2 involves sudden change of the assembly inner energy due to the central column buckling and instant activating of stays on convex side of the column. therefore, linear buckling analysis can’t be used and geometrically nonlinear one is necessary. however, in such case gnia (geometrically nonlinear analysis with imperfections) need to be used, with negligible initial deflections. in the study were considered values of w0y = w0z = l/500000 = 0.01 mm. direction of maximal deflections in all former described tests was into space (i.e. between the axes y, z). the question arose, whether solution in 3d with the corresponding initial deflections in both axes y, z gives lower critical/maximal loadings. the studied stayed column had the same geometry as in chapter 2, but with fixed stays at the crossarms: the central tube ø 50x2 [mm], the crossarm tubes ø 25x1.5 [mm] the stays as macalloy cables ø 4 mm. stainless steel material with e = 200 mpa was considered for all the central tube, crossarms and stays (here as an initial value due to low stresses). comparison of results for 2d an alysis according to [3] and fem in 3d with four amplitudes of initial deflections (w0 = 0.01 mm, 0.05 mm, 0.10 mm and 25 mm) is shown in table 1. the greatest amplitude corresponds to the design recommendation of eurocode en 1993-1-1 for cold-formed tubes and elastic analysis (l/200 = 25 mm). both symmetric (one half wave initial deflection) and antisymmetric (two half waves with half amplitudes of initial deflection) were analyzed to determine topt and corresponding maximal critical loading or maximal strength nmax of imperfect column in the prestressing range up to 3topt, fig. 6. advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 14 table 1 influence of initial deflection w0, comparison of 2d and 3d analysis, material nonlinearity w0 [mm] symmetrical initial deflections antisymmetrical initial deflections nmax [kn] topt [kn] nmax,sym [kn] topt [kn] nmax,anti [kn] 0 (2d) 1.41 39.79 1.30 36.79 36.79 0.01 (3d) 1.51 39.73 1.35 36.18 36.18 0.05 (3d) 1.58 39.25 1.43 35.77 35.77 0.10 (3d) 1.61 38.62 1.52 35.43 35.43 25.0 (3d) 22.74 24.84 22.74 0.01 (stainless steel) 1.51 36.54 1.27 31.58 31.58 25.0 (stainless steel) 19.57 19.92 19.57 after analysis of the results , it was concluded (see the first two rows in table 1), that 2d and 3d results, in spite of various directions of buckling (in direction of arms for 2d and into the space in 3d), provide nearly identical critical/strength values. this conclusion may be considered not only for the “ideal” column (i.e. for critical loading), but also for maximal ultimate loading (strength of imperfect stayed columns). the last row of the table 1 presents results for the same stayed column as above but made from stainless steel ma terial as in the tests (see chapter 2). it means that for central column and crossarms instead of constant e = 200 mpa the respective v alues of e1 = 184 mpa, e2 etc. (see fig. 3) were employed. the results for nmax are significantly lower for the stainless steel material and simple reduction from elastic behavior using initial ratio e1/e  0.92 is not sufficient. the gmnia results for stainless steel material are shown in fig. 6 (b). it is obvious that for the given geometry, design initial deflections l/200 and decisive role of symmetric initial deflections (because 2a/l = 0.1 < 0.175), the ratio nmax/ncr is similar to the one given in [12]. w 0 w 0 w 0 5 0 0 0 250250 x y,z x symmetrical mode antisymmetrical mode (a) initial deflection shape (b) comparison of values for “ideal” (w0 = l/500000) and initially deflected (w0 = l/200) stainless steel stayed column fig. 6 gmnia results for “ideal” and imperfect stayed column the changes in deflection shape for such large antisymmetric initial deflections with an increase of prestressing are highlighted by points 1 and 2 in fig. 6. the antisymmetric initial mode (however not decisive in this geometry) is changed after prestressing to an interactive one up to the point 1 and then, from point 2, to antisymmetric one again (see fig. 7) . point 1 point 2 fig. 7 deflection shapes for antisymmetric initial deflections and prestressing corresponding to points 1, 2 advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 15 4. support of stays at crossarms the stays are formed either by rods or cables. using rods naturally requires fixed fastening to the crossarms, but cables may be fastened either by forked terminal (i.e. fixed) or run continuously over saddles. in the tests described in chapter 2, the saddles were used, enabling balancing tension in both parts of the respective stay after exceeding frictio n between the saddle and the cable, see fig. 8 (a). such arrangement is advantageous from assembly point of view and saving cable sockets, but obviously reduces in some way strength of the stayed column system. sliding stays fixed stays crossarm leg stay stay crossarm leg saddle forked socket (a) support at crossarm (b) influence of cable slip at saddles fig. 8 alternatives and value of support conditions at crossarm the friction between the saddles and cables may vary between from nearly zero (when using teflon -like lining) and common value for steel-steel contact of ν = 0.10. to analyze the influence of the cable slip at saddles safely, very low friction coefficient ν = 0.01 was used and results are shown in fig. 8 (b). the columns with geometry given in chapter 3 and initial deflection of the central column w0 = l/500000 were analyzed using gmnia. from comparison of results is obvious that the different behavior arises at antisymmetrical mode of buckling only, were reduction of maximal critical load is substantial. extensive studies concerning prestressed stayed columns with sliding stays and required necessary initial deflections are in progress . 5. conclusions the proposed numerical ansys model was successfully validated by comparison with the four tests of stainless steel stayed columns of reasonable geometry and various prestressing of stays . the detailed studies resulted into the following conclusions: (1) the stayed column even with unprestressed stays (slacked stays) provides significantly higher maximal ultimate loading in comparison with simple column without stays due to activating of stays at the concave side of the column during the buckling. (2) the 2d planar analysis (fe or analytical one) with a buckling in the direction of the arms supplies nearly identical results concerning optimal prestressing, maximal critical and maximal ultimate loading as the 3d space analysis with buckling into space (in between the arms of the crossarm). (3) using nonlinear (stainless steel) material in stayed columns requires gmnia and proper introduction of stainless steel stress-strain relationship. (4) maximal ultimate loading (strengths nmax) of a stayed column must be analyzed with initial deflections of appropriate amplitude and shape. with reasonable amplitudes (e.g. l/200 for cold-formed tubes required by eurocode 3) and common ratios 2a/l, both symmetric and antisymmetric initial deflections may be decisive and corresponding ratios nmax/ncr be greater (for low prestressing) or much lower (for great prestressing) than 1. (5) continuous stays, running over saddles, may be advantageous for assembly, but when antisymmetric buckling is predominant, a strong reduction in maximal ultimate loading need to be expected . advances in technology innovation, vol. 3, no. 1, 2018, pp. 09 16 copyright © taeti 16 acknowledgement the support of the czech grant agency grant gacr no. 17-24769s is gratefully acknowledged. references [1] k. h. chu and s. s. berge, “analysis and design of struts with tension ties ,” journal of the structural division asce, vol. 89, no. st1, pp. 127-163, february 1963. [2] r. j. smith, g. t. mccaffrey, and j. s. ellis, “buckling of a single-crossarm stayed column,” journal of the structural division asce, 11071 st1, pp. 249-268, january 1975. [3] h. h. hafez, m. c. temple, and j. s. ellis, “pretensioning of single-crossarm stayed columns,” journal of the structural division asce, 14362 st2, pp. 359-375, february 1979. [4] k. c. wong and m. c. temple, “stayed columns with initial imperfections,” journal of the structural division asce, 108 st7, pp. 1623-1640, 1982. [5] s. l. chan, g. shu, and z. lü, “stability analysis and parametric study of pre-stressed stayed columns,” engineering structures, vol. 24, no. 1, pp. 115-124, january 2002. [6] d. saito and m. a. wadee, “post-buckling behaviour of prestressed steel stayed columns,” engineering structures, vol. 30, no. 5, pp. 1224-1239, may 2008. [7] d. saito and m. a. wadee, “numerical s tudies of interactive buckling in prestressed steel stayed columns,” engineering structures, vol. 31, no. 2, pp. 432-443, february 2009. [8] r. r. araujo, s. a. l. andrade, p. c. g. s. vellasco, j. g. s. silva, and l. r. o. lima, “experimental and numerical assessment of stayed steel columns,” journal of constructional steel research, vol. 64, no. 9, pp. 1020-1029, september 2008. [9] k. servitova and j. machacek, “analysis of stainless steel stayed columns ,” proceedings 6 th intern. symp. steel structures, korean society of steel construction, seoul, pp. 874-881, 2011. [10] l. r. o. lima, p. c. g. vellasco, and j. g. s. silva, “numerical modelling of prestressed stayed stainless steel columns ,” tubular structures xiv, taylor and francis, london, pp. 377-382, 2012. [11] a. i. osofero, m. a. wadee, and l. gardner, “experimental study of critical and post-buckling behaviour of prestressed stayed steel columns,” journal of constructional steel research, vol. 79, pp. 226-241, december 2012. [12] m. a. wadee, l. gardner, and a. i. osofero, “design of prestressed stayed columns ,” journal of constructional steel research, vol. 80, pp. 287-298, january 2013. [13] r. pichal and j. machacek, “3d stability of prestressed stayed columns ,” proceedings 22 nd intern. conf. engineering mechanics, inst. of thermomechanics, academy of sciences of the czech republic, svratka, pp. 462-465, 2016. [14] r. pichal and j. machacek, “buckling and post-buckling of prestressed stainless steel stayed columns ,” procedia engineering, vol. 172, pp. 875-882, 2017.  advances in technology innovation, vol. 1, no. 2, 2016, pp. 29 32 29 copyright © taeti reduction of residual stresses in sapphire cover glass induced by mechanical polishing and laser chamfering through etching shih-jeh wu1,*, hsiang-chen hsu1,2 and wen-fei lin3 1 department of mechanical and automation engineering, i-shou university, kaohsiung, taiwan. 2 department of industrial management, i-shou university, kaohsiung, taiwan. 3 department of material science and engineering, i-shou university, kaohsiung, taiwan. received 02 february 2016; received in revised form 30 march 2016; accepted 02 april 2016 abstract sapphire is a hard and anti-scratch material commonly used as cover glass of mobile devices such as watches and mobile phones. a mechanical polishing using diamond slurry is usually necessary to create mirror surface. additional chamfering at the edge is sometimes needed by mechanical grinding. these processes induce residual stresses and the mechanical strength of the sapphire work p iece is impaired. in this study wet etching by phosphate acid process is applied to relief the induced stress in a 1” d iameter sapphire cover glass. the sapphire is polished before the edge is chamfered by a picosecond laser. residual stresses are measured by laser curvature method at different stages of machining. the results show that the wet etching process effectively relief the stress and the laser machining does not incur serious residual stress. keywords : picosecond laser, laser curvature method, residual stress, stress relief, wet etching, sapphire 1. introduction sapphire is the material to cover glasses that are scratch and impact-resistant, yet flexib le despite the introduction of tempered glass such as corning ® gorilla . in addition to the use for watch glasses or as cover or filter glasses for camera lenses, now it is being tried for cell phone displays as well. sapphire glass is made of colorless plates of synthetic corundum, i.e . minerals produced with molten aluminum oxide (al2o3). in fact, sapphire glass does not have a glass-like amorphous structure, but rather a crystalline structure. with a hardness of 9 on the mohs scale, sapphire is one of the hardest transparent materials next to diamond [1, 2]. sapphire has very wide optical trans mission band from uv to near-infrared, (0.15-5.5 µm)[2]. with its particu lar properties, sapphire glass offers advantages over the chemically hardened glass often used in the display industry. traditional methods for machining sapphire glass are generally mechanical grinding and polishing. optical fabrication processes of these operations lead to the creation of surface and sub-surface defect and residual stresses [3, 4]. maybe in micro-size, these defects degrade the strength and the performance of functional materials. another new development of sapphire machining is laser cutting. laser machining is superior to conventional mechanical methods in terms of flexib ility and edge quality when right laser type and proper beam processing is applied. mechanical saw creates micro cracks at edges as the speed is high which in turn deteriorates the bending strength. however, laser thermal effect can also induce stress which is not desirable either. a few methods can be applied to eliminate the above consequential effect from polishing process, namely, trad it ional loose-abrasive polishing, wet etching, and dry plas ma etching [5-7]. the first method typically integrates a polishing step into the grinder itself, which offers the advantage of integrating the damage removal into the grinder tool and builds upon * corresponding author, email: wsj007@isu.edu.tw https://en.wikipedia.org/wiki/uv https://en.wikipedia.org/wiki/near-infrared advances in technology innovation, vol. 1, no. 2, 2016, pp. 29 32 30 copyright © taeti traditional chemical mechanical polishing (cmp) technology. however, it has the disadvantage of low removal rates and perpetuates the surface profile. the second method uses familiar wet-etching processes to remove surface damage. wet chemical etching is one of the most common thinning techniques. to etch one side o f the work piece, the workpiece is immersed in etching solution e.g. dilute hydrofluoric acid (dhf). the other side is protected either by additional layers, or by applying special chucks allowing the p rocessing of work piece . the th ird method uses atmospheric dry plasma etching to remove surface damage. this method has the advantage such as the surface damage is removed, the edges are improved by rounding the sharp edge, and the surface roughness can be controlled where needed for adhesion [7]. in this paper we demonstrate a production machining and compare the residual stresses after different reliev ing process. the sapphire is polished before the edge is chamfered by a picosecond laser. residual stresses are measured by laser curvature method [8] at different stages of machining. the results show that the wet etching process effectively relief the stress and the laser machining does not incur serious residual stress. 2. method the schematic of the sapphire glass samples under process is as shown in fig. 1. the sapphire samples are in 1” diameter. the sapphire glass samples were po lished by cmp before the edge is chamfered by a picosecond laser and then they under wet etching different processes i.e., wet etching by dhf and dry plasma etching. residual stresses are measured by laser curvature method at different stages of machining. the schematic of the optical setup is shown in fig. 2. the line deflection (bow) was fig. 1 schematic of the sapphire glass samples under process first measured across the center of the sample (initially flat before machining) as shown in fig. 3. the stress can be then estimated by the curvature. a diagrammatic sketch is shown in fig. 4. fig. 2 optical setup of the laser curvature method fig. 3 line deflection (bow) measured across the center of the sample 3d stress map fig. 4 a diagrammatic sketch of the 3d stress map by the laser curvature method advances in technology innovation, vol. 1, no. 2, 2016, pp. 29 32 31 copyright © taeti 3. results and discussion the average surface roughness by different methods of burnish is shown in fig. 5. from low to high the roughness can be listed sequentially : mechanical polishing, dry etching, wet etching and thermal annealing. however, the difference within acceptable range. the line deflections of the mechanically polished sapphire glass sample (1.44mm thickness) before and after laser chamfering are as shown in fig. 6. there is a tensile stress residing the measured surface. interestingly, the laser machining does relief the residual stress induced. this mat be due to the instantaneous temperature rise during laser irradiation which leads an annealing effect. fig. 5 average roughness by different methods of burnish fig. 6 bow of the mechanically polished sapphire glass sample (1.44mm thickness) before and after laser chamfering the bow of the mechanically polished and laser machined sapphire glass sample (0.4mm thickness) after dry plasma etching is as shown in fig. 7. the influence of residual stress on surface deflection is more prominent in thinner sapphire glass. before the etching the deflection is not symmetrical and irregular while it converts to a symmetrical shape and the maximal deflect ion at the center increases slightly from 0.7 to 0.8 μm after 300 seconds as a results of stress relaxation. the deflection at the center then starts to drop to 0.5 μm until 360 seconds has passed. at this stage the stress has been relieved to the full extent. fig. 7 bow of the mechanically polished and laser machined sapphire glass sample (0.4mm thickness) after plasma dry etching bow of the mechanically polished and laser machined sapphire glass sample (0.4mm thickness) after wet etching by dhf is as shown in fig. 8. the deflect ion is irregular before the wet etching similar to dry etching. after the wet etching starts the bow turns to the other direction i.e., from concave to convex. as the etching process progresses the deflection drops until after 180 seconds the maximal deflection remains the same at 0.57 μm. it is believed the residual stress is relieved to the full extent. the reason for the change of concavity is that before the polishing process the sapphire glass is not evenly cut or ground and the work p iece retains its original shape after stress is relieved. fig. 8 bow of the mechanically polished and laser machined sapphire glass sample (0.4mm thickness) after wet etching by dhf advances in technology innovation, vol. 1, no. 2, 2016, pp. 29 32 32 copyright © taeti the optical t ransmission and reflection ratio before and after wet etching are as shown in fig. 9. there is not much difference in reflection, however, the transmission is improved. fig. 9 the optical transmission and reflection ratio before and after wet etching 4. conclusions in this paper, we demonstrate a production machining and compare the residual stresses after different reliev ing process. the laser chamfering does not incur further stress, on the contrary, it somehow reduces the stress. both dry and wet etchings are effective in relief of residual stress induced by mechanical polishing. also the etching process did not impair the transparency of the sapphire glass. ball-on-ring test is proposed to confirm the effect of residual stresses on the strength of the sapphire work pieces before and after wet etching. acknowledgement the authors would like to express their appreciation to ministry of science and technology, taiwan, roc, for financial supports under project no. most103-2221-e-214-018, most104-2221-e-214-051 and most104-2632 e-214-002. special appreciation is also extended to e&r engineering corp. for carrying out all the experiments. references [1] “gorilla glass success, what is sapphire glass?” http://www.corning.com/news_center/features/ gorillaglasssuccess.aspx, corning incorporated. [2] “everything you wanted to know about sapphire glass, but were afraid to ask, ” http://www.cultofmac.com/267068/everyth ing-wanted-know-sapphire-glass-afraid-ask -qa/. [3] d. wang, j. lee, k. holland, t. bibby, s. beaudoin, and t. cale, “von mises stress in chemical‐mechanical polishing processes,” j. electrochem. soc., vol. 144, no. 3, pp. 1121-1127, 1997. [4] g. kermouche, j. rech, h. hamdi, and j. m. bergheau, “on the residual stress field induced by a scratching round abrasive grain,” wear, vol. 269, no. 1-2, pp. 86-92, may 2010. [5] c. landesberger, c. paschke, and k. bock, “influence of wafer grinding and etching techniques on the fracture strength of thin silicon substrates,” advanced materials research, vol. 325, pp. 659-665, 2011. [6] k. gurnett and t. adams, “ult ra-thin semiconductor wafer applications and processes,” iii-vs review, vo l. 19, pp. 38– 40, 2006. [7] z. j. pei, g. r. fisher, and j. liu, “grinding of silicon wafers: a rev iew from historical perspectives,” international journal of machine tools and manufacture, vol. 48, pp. 1297-1307, 2008. [8] j. wang, p. shrotriya, and k. s. kim, “surface residual stress measurement using curvature interferometry,” experimental mechanics, vol. 46, pp. 39-46, 2006.  advances in technology innovation, vol. 2, no. 2, 2017, pp. 56 60 56 the research of infrared thermal image diagnostic model for building external wall tiles li-wei chiang*, sy-jye guo department of civil engineering, national taiwan university, taipei 106, taiwan, roc. received 22 february 2016; received in revised form 29 april 2016; accepted 04 may 2016 abstract this study focuses on a deterioration diagnostic standard and inspection time for external wall t iles. the study was carried out using a tap tone test, followed by fast fourier transform and pattern recognition to analyse the tapping results. based on the test results, the study recommends that for frequencies between 200 and 800 hz on the spectrogram, it can be deduced that a cavity is present in the tiles. the study was carried out using infrared thermal imaging record to deteriorat ion and normal t ile position. this study observed temperature changes per hour, it is obvious temperature difference with deterioration tiles and normal tiles between 09: 00-11: 00 (east), 10:00-14:00 (west), 10:00-12:00 (south) and 11:00-13:00 (north), the study was calculated that the average temperature difference of 1.0 degrees. this study suggests that the best experimental inspection time is 09: 00-14:00. exclude the impact of external factors, if the temperature d ifference more than 1.0 degrees, it can be deduced that a cavity is present in the t iles, and this can be used as basis for determining tile deterioration. keywords: external wall tiles, infrared thermal image inspection, tap tone inspection, temperature difference, inspection period 1. introduction in taiwan, there has experienced frequent safety incidents involving the external walls of buildings recent years. the most common incidents include falling tiles, falling advertising signage and falling exposed pipelines, all seriously impacting the surrounding environment and public safety. on march 14, 2015, a tile falling incident in taipei city, taiwan, resulted in a fatality. according to the taipei city government statistics, there were 1188 buildings listed for control as important cases with spalling wall tiles. the government of kaohsiung city, taiwan investigated the 6492 apartment buildings with six or more floors in the city. there were 859 buildings with t iles spalling. kaohsiung city government listed 367 buildings as important cases for control. according to research data (chang, 2008), construction in taiwan peaked in the years 1981 and 1994. according to this research, taiwanese buildings experience significant deteriorat ion after 30 years. safety check requirements for taiwanese buildings should thus peak in 2011 and 2024. integrating news relating to fatalities in tile-falling incidents in taiwan, this research sees an immediate need for a complete diagnostic mechanism and preventive method for the further occurrences of such public safety incidents. to effectively drive external wall replacement safety checks and studies on evaluation systems, the industry requires relevant empirical results and evaluation criteria. th is study aims to e mploy data collection and empirical research to provide a basis of reference and an evaluation method for use in external wall tile diagnosis. 2. method 2.1. tap tone method this study used sounding diagnosis to complement the visual diagnosis method. the tap tone diagnostic method is the most convenient, economical and widely used evaluation method for inspecting surface defects. tile inspection is normally combined with other inspection methods (such as the visual inspection method) as a basis for inspection of the condition of wall tile deterioration. * corresponding author, email: d99521007@ntu.edu.tw advances in technology innovation, vol. 2, no. 2, 2017, pp. 56 60 57 copyright © taeti the theory behind the tap tone diagnostic method is associated with determinations made through sound frequency. besides pitch, sound also has intensity and tone. generally speaking, pitch, intensity (loudness) and timbre are the three main elements of sound. the pitch of a sound is determined by its frequency of vibration. a higher frequency of vibration indicates a higher pitch, and a lower frequency of vibration indicates a lower p itch. the intensity of sound is determined by the vibration magnitude (amplitude) of the sound wave. higher amplitudes equate to more powerful sound waves, and thus louder sounds. observing the different sounds generated from tapping on normal and deteriorated tiles with a tap tone diagnosis stick, this study uses a fast fourier transform to determine a spectrogram. frequency (hz, x-coordinate) and amplitude (v, y-coordinate) are used to form the basis for determin ing the degree of tile deterioration. spectrograms from the tap tone diagnosis are shown in fig. 3 and fig. 4. the spectrogram's peak and trough for normal tiles show stable frequency (fig. 1), while deteriorated tiles show apparent instability (fig. 2). fig. 1 transformed spectrum for a tap tone diagnosis on normal tile fig. 2 transformed spectrum for a tap tone diagnosis on deteriorated tiles fig. 3 test procedure 2.2. infrared thermal image method this study uses the infrared thermal imaging to detect building external wall tiles. infrared thermal imaging method is use natural sunlight, which allows the building wall tile temperature changes. in general, if there is no concrete position defect (bulging phenomenon), infrared thermal imaging d isplays a consistent surface color. since the defective portion and the normal portion of different thermal conductivity, this study used infrared thermal imaging device to measurements the temperature difference to determine peeling. selected object confirm the external wall tiles surface moist condition tap tone diagnosis and consistent strength tap tone record results marking on the external wall, to records the deterioration and normal tiles adjust the machine parameters temperatures every 30 minutes, record the normal and deterioration position of the infrared thermal imaging photos flir tools soft to analysis tile temperature advances in technology innovation, vol. 2, no. 2, 2017, pp. 56 60 58 copyright © taeti in this study, every 30 minutes to record the external wall t iles temperature of the building, from 09:00 to 17:00, then through the analysis of temperature-t ime curve to discuss the best measurement time. when detecting the position of internal defects, the temperature deterioration of the position will be higher than other normal area in the day heating period (08:00-11:00), on the contrary, when the cooling time in the day (16:00-19:00), the degradation position will lower temperature than the normal position. and then, this study used tap tone diagnostic method to confirm the deterioration of the range. 3. results and discussion 3.1. tap tone diagnosis results the study carried out tap tone diagnosis on 2 buildings. there are 63 areas of deterioration out of 126 tap tone diagnostic tests. the study deems the first peak of the spectrogram as noise, the beginning of the second wave as the start point of deteriorat ion sound, and its end point as the end point of the deterioration sound. the spectrogram is then segmented by lattice points. further statistical analysis of the 126 deteriorated areas shows that the average start point of deteriorated tiles is 239hz, while that for the end point is 761hz. the deterioration extent is indicated by the shaded portion. the study suggests that upon tap tone diagnosis, if the fast fourier transform graph shows a frequency from 200 to 800 hz, it can be speculated that there is a cavity in the tiles. if tap tone diagnosis is required, it is suggested to tap at least 5 spots on the facade to increase overall detection accuracy. the study tentatively recommends that if the tile deterioration ratio e xceeds 50%, immediate overall facade renovation of the building should be carried out. if the tile deterioration ratio is less than 50%, then safety measures to prevent surrounding objects from falling should be immediately imposed. this study investigated 2 building cases in the national taiwan university. this study used lattice segmentation method for analyzing 126 tiles deterioration image spectrums. it is found that the deterioration of the tiles starts at frequency average about 240hz and ends at about 760hz. deterio ration hatched range shown in table 1 and table 2. table 1 case a of tap tone diagnosis results case a table 2 case b of tap tone diagnosis results case b advances in technology innovation, vol. 2, no. 2, 2017, pp. 56 60 59 copyright © taeti the study conso lidates resu lts and recommendations of visual inspection and taps tone diagnosis, and proposes a diagnostic criteria and standard operating procedures for external wall tile deterioration diagnosis of taiwan buildings. 3.2. infrared thermal image diagnosis results fig. 4 case a external wall tiles infrared images (sp1: deterioration, sp2: normal) according to statistics , the study found that the east tiles maximum temperature is 2.0 degrees, occurred at 9: 00-10: 00. the west tiles maximum temperature is 1.3 degrees, occurred at 12: 00-13: 00. the south tiles maximum temperature is 1.3 degrees also, occurs at 11: 00-12: 00. the north tiles maximum temperature is 1.2 degrees, occurred at 12: 00-13: 00. in this study, the statistics of the external wall temperature, an average temperature d ifference of 1 degree results. this study suggests that the threshold can be used as observation fig. 5 case a temperature difference of east external wall tiles fig. 6 case a temperature difference of west external wall tiles fig. 7 case a temperature difference of south external wall tiles fig. 8 case a temperature difference of north external wall tiles this study analyzed the average of daily temperature difference, the temperature difference if more than one degree, and in the best time of observation of this study suggests, it can be speculated that there is deterioration of tile production. aggregated data are shown in table 3. table 3 the investigation time and threshold of external wall tiles east west south north maximum temperature difference 2.0 1.3 1.3 1.2 average temperature difference 1 0.9 1.1 0.9 recommendation inspection time 09-11 12-14 10-12 11-13 advances in technology innovation, vol. 2, no. 2, 2017, pp. 56 60 60 copyright © taeti 4. conclusions since the construction boom in the 1970s in taiwan, many build ing external wall have suffered natural deterioration, and many incidents of external wall tiles falling have occurred, with some even resulting in fatalities. as the number of such cases has increased, a complete external wall tile d iagnostic system is required. this study proposes public safety visual diagnostic models for external wall tiles of build ings, including tap tone and infrared thermal image diagnostic concepts, diagnostic method and diagnostic evaluation reference datum. it also offers a infrared thermal images method for external wall tiles, as well as suggesting the adoption of tap tone diagnosis on tiles that potentially have significant impact on public safety. it also verifies the developed evaluation model, and proposes countermeasures and recommendations for deterioration conditions. based on the test results, the study recommends that for frequencies between 200 and 800 hz on the spectrogram, it can be deduced that a cavity is present in the tiles, and this can be used as basis for determining tile deterioration. the study was carried out using infrared thermal imaging record to deteriorat ion and normal t ile position. th is study observed temperature changes per 30 mins, it is obvious temperature d ifference with deteriorat ion tiles and normal tiles between 09: 00-11: 00 (east), 10:00-14:00 (west), 10:00-12:00 (south) and 11:00-13:00 (north), the study was calculated that the average temperature d ifference of 1.0 degrees. this study suggests that the best experimental inspection time is 09: 00-14:00. exclude the impact of external factors, if the temperature d ifference more than 1.0 degrees, it can be deduced that a cavity is present in the t iles, and this can be used as basis for determining tile deterioration. acknowledgement this research was supported by the ministry of science and technology (most 103-2221-e -002-171), and sinotech foundation for research and development of engineering sciences and technologies. references [1] l. w. chiang, s. j. guo, c. y. chang, and t. p. lo, “the development of a diagnostic model for the deterioration of external wall tiles of aged buildings in taiwan,” journal of asian architecture and build ing engineering, vol. 15, no.1, pp. 111-118, january 2016. [2] l. w. chiang, s. j. guo, and c. y. chang, “the model of visual inspection for building external wall deterioration tiles,” journal of architecture, vol. 87, pp. 49-66, 2014. (in chinese) [3] e. d. km, “service life prediction for buildings exposed to severe weather,” journal of asian architecture and building engineering, vol. 10, no.1, pp. 211-215, 2011. [4] f. tong, s. k. tso, and x. m. xua, “tile-wall bonding integrity inspection based on time-domain features of impact acoustics,” journal of sensors and actuators a 132, pp. 557-566, 2006. [5] u. taketo, k. kato, and s. hirono, non-destructive of the concrete structure, tokyo: morikita publishing co., ltd, 2000.  advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 analysis of 2017 gartner’s three megatrends to thrive the disruptive business, technology trends 2008-2016, dynamic capabilities of vuca and foresight leadership tools kaivo-oja jari 1 , theresa lauraéus 2,* 1 ffrc, tse, department of future, university of turku, rehtorinpellonkatu 3, 20014 turun yliopisto, turku, finland 2 department of information and services, aalto university, runeberginkatu 22-24, 00076 aalto, helsinki, finland received 03 may 2018; received in revised form 05 august 2018; accepted 22 september 2018 abstract nowadays, digitalization is the key element of business competition. this paper analyzes the concept of dynamic capabilities in the context of technological and business digitalization. we investigate the dynamic competence needed to create and manage a new digital business, which is emerging from the technological transformation. firstly, in this paper, we analyze the data of gartner hype cycles 2008-2017. thus, we present a comparative analysis of the changes in the gartner hype cycle. secondly, our aim is to present gartner ś three distinct megatrends. we will present a summary of these gartner evaluations and discuss key tendencies and trends of technological changes. thirdly, the special focus of this article is the challenges of orchestration of dynamic capabilities in the special conditions of vuca business disruptive business competition. further, we define the role of competence gap identification inside a firm. finally, we are presenting some useful tools to manage dynamic capabilities. keywords: digitalization, three digitalization megatrends, vuca business environment, digital business management, dynamic capabilities, business leadership tools, gartner ś hype curve and digital technology trends, the foresight management tools 1. introduction we will present the foresight tools for innovation, knowledge and corporate management. the management tools for corporate innovation, foresight, which help leaders to manage vuca into consideration, especially in the conditions of hyper-competition and technological digitalization. in this paper, the authors link this discussion to the vuca approach. the authors note that if corporations create corporate strategies with old-fashioned approaches without the vuca approach, most “strategic plans” are having low value-added. in many cases, corporate foresight is ineffective and unsatisfactory for leaders. in this paper, the author presents a new corporate foresight framework, which is more relevant for corporations and takes current technology transformation more seriously. they also present some management tools of foresight, which help leaders manage volatility, uncertainty, complexity, and ambiguity into consideration, especially in the conditions of hyper-competition and technological disruption. key issues in modern vuca management are agility (a response to volatility), information knowledge management (a response to uncertainty), restructuring (a response to complexity), and experimentation (a response to ambiguity). 2. theory 2.1. disruptive technologies the importance of new technologies for society arises from the discovery that ideas and their implementation generate growth and well-being [1]. how can managers know if the technology will disrupt their organization and firm? the definition * corresponding author. e-mail address: theresa.lauraeus@aalto.fi advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 106 of disruptive technology relates closely to the disruptive innovation concept of christensen (1997) [2]. bower and christensen, (1995) [3] described a new idea that has long affected the considerations of business sustainability: the notion that new technologies can create new markets, radically change, or disrupt, the status quo in existing markets. useful foresight tools are: challenging tools, decision-making tools, aligning tools, learning tools, and the ability to combine these management tools in the practices of corporate management and leadership. the general conclusion of the paper is that corporate leaders must reinvent strategic planning, framing it to the vuca conditions and simply-be more strategic. especially the technological transformation with artificial intelligence (ai) and robotics is changing many basic assumptions of business management and strategic planning. we have known for a while that disruptive technologies [3, 4, 5] fundamentally change the ways people live and work and how businesses operate, and disruptive technological changes ultimately affect the global economy. existing disruptive innovation theory [2, 6] focuses on key issues like market characteristics, new markets, and low-end innovations. disruptive innovations [6] are new services and products that initially gain a market share at the bottom end of the market by making a product or service available to a new group of “low-end” consumers. they are less wealthy or skilled than consumers of such products have been historically. one definition of a disruptive innovation [4, 6, 7-11] focuses on the functional quality and cost of innovation. this definition defines disruptive innovations as an innovation with a “good enough” functionality that has a low cost [4, 6, 7-11]. theoretically, the lower quality and lower priced innovation incrementally [3, 6] improve until eventually, the innovation competes with market-leading products, thus strongly disrupting the market status quo [3, 6]. the other definition of disruptive innovations does not focus on an innovation's cost or quality, but on market characteristics. 2.2. gartner ś hype cycle phases the hype cycle for emerging technologies report is the longest-running annual gartner hype cycle [12-21] providing a cross-industry perspective on the technologies and trends that business strategists, chief innovation officers, r&d leaders, entrepreneurs, global market develops, and emerging-technology teams should consider in developing emerging-technology portfolios. the theories behind the hype-cycle, fenn and raskino [22] argue that three human nature phenomena are responsible for the curve’s shape: attraction to novelty, social contagion, and heuristic attitude in decision making. adamuthe, tomke & thampi [23] study among the others, the description of hype-cycle phases [24] given by j. fenn [24]: 1. technology/innovation trigger phase: a breakthrough, public demonstration, product launch or other event generates significant press and industry interest. 2. peak of inflated expectations phase: during this phase of over-enthusiasm and unrealistic projections, a flurry of well-publicized activity by technology leaders results in some successes but more failures as the technology is pushed to its limits. the only enterprises making money are conference organizers and magazine publishers. 3. trough of disillusionment phase: because the technology does not live up to its over inflated expectations, it rapidly becomes unfashionable and the press abandons the topic. 4. slope of enlightenment phase: focused experimentation and solid hard work by an increasingly diverse range of organizations lead to a true understanding of the technology’s applicability, risks, and benefits. commercial off-the-shelf methodologies and tools become available to ease the development process. 5. plateau of productivity phase: the real-world benefits of the technology are demonstrated and accepted. tools and methodologies are increasingly stable as they enter their second and third generation. the final height of the plateau varies whether the technology is broadly applicable or benefits only a niche market. http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 107 fig. 1 hype cycle for emerging technologies 2016 [20] 2.3. the use of life cycle measures how should organizations and individuals use the hype cycle and deal with the expectations of novel disruptive innovations? [22] first of all, a company can find individual product opportunities. secondly, through segmentation analysis [22], it can build a deeper understanding of its customers that revealed significant opportunities. a company can know the special “golden” shopper segments. thirdly, organizations can respond effectively to competition [22, 25]. and finally, a company is able to identify and introduce new businesses. the hype cycle helps explain why people adopt, abandon or ignore innovations. too many organizations are tempted to jump into innovation prematurely, at the phase of peak of inflated expectations [22, 25], while others wait too long. adopting innovation without understanding the hype cycle [22, 26] can not lead to good decisions and waste of r&d money. 3. results 3.1. understanding the dynamics of technological disruption: comparing the gartner ś hype cycle between years 2008 and 2016 in year 2008, the hype cycle includes: erasable paper printing system, context delivery architecture, behavioral economics, mobile robotics, augmented reality, surface, computers, cloud computing, 3d printing, microblogging, green it, social computing platforms, solid-state drives, public virtual world, web 2.0, service-oriented business applications, virtual assistance, rfid, corporate blogging, idea management, social network analysis, electronic paper, tablet pc, soa, location-aware applications, basic web applications. in the year 2016: the 16 new technologies included in the hype cycle for the first time. these technologies include 4d printing, general-purpose machine intelligence, 802.11ax, context brokering, neuromorphic hardware, data broker paas (dbrpaas), personal analytics, smart workspace, smart data discovery, commercial uavs (drones), machine learning, nanotube electronics, software-defined anything (sdx), enterprise taxonomy and ontology management, blockchain, connected home. in addition, some earlier items stay: the volumetric displays, brain-computer interface, visual personal assistants, affective computers, iot platforms, gestore control devices, micro data centers, smart robotics, machine learning, autonomous vehicles, natural-language question answering, augmented reality, virtual reality. the gartner [27]. sees leading revolution is the smart machine technologies, which will revolutionize manufacturing and its related industries include the following: smart dust, machine learning, virtual personal assistants, cognitive expert advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 108 advisors, smart data discovery, smart workspace, conversational user interfaces, smart robots, commercial uavs (drones), autonomous vehicles, natural-language question answering, personal analytics, enterprise taxonomy and ontology management, data broker paas (dbrpaas), and context brokering. emerging technologies are enabling entirely new business models, driving a platform revolution. platform-enabling technologies making new business models possible, include neuromorphic hardware, quantum computing, blockchain, iot platform, software-defined security and software-defined anything (sdx). summary: some technologies of the year 2008 hype cycle were foresighted very well and they are nowadays very popular: tablet pcs, internet of things, cloud services, 3d printers even in the libraries of finland, solid state drive is well foresight, and also augmented reality is coming fast. in the year 2016: fourteen technologies were taken off the hype cycle including hybrid cloud computing, consumer 3d printing, enterprise 3d printing, and speech-to-speech translation because they are not hyped anymore. additional technologies removed from the hype cycle include 3d bioprinting systems for organ transplant, advanced analytics with self-service delivery, bioacoustic sensing, citizen data science, digital dexterity, digital security, internet of things, neuro business, people-literate technology. summary: some technologies of the year 2008 hype cycle were foresighted very well and they are nowadays very popular: tablet pcs, internet of things, cloud services, 3d printers, even in the libraries of finland, solid state drive is well foresight, and also augmented reality is coming fast. in the year 2016: fourteen technologies were taken off the hype cycle including hybrid cloud computing, consumer 3d printing, and enterprise 3d printing, and speech-to-speech translation because they are not hyped anymore. additional technologies removed from the hype cycle include 3d bioprinting systems for organ transplant, advanced analytics with self-service delivery, bioacoustic sensing, citizen data science, digital dexterity, digital security, internet of things, neuro business, people-literate technology. 3.2. gartner [27] identifies three megatrends that will drive digital business into the next decade fig. 2 hype cycle for emerging technologies, 2017 [21]. note: paas = platform as a service; uavs = unmanned aerial vehicles the first megatrend is artificial intelligence (ai) everywhere. it means transparently immersive experiences and digital platforms are the trends that will provide unrivaled intelligence, create profoundly new experiences and offer platforms that allow organizations to connect with new digital business environments. http://www.gartner.com/smarterwithgartner/the-disruptive-power-of-artificial-intelligence/ http://www.gartner.com/smarterwithgartner/transform-business-outcomes-with-immersive-technology/ http://www.gartner.com/smarterwithgartner/enterprise-architects-define-digital-platforms/ http://www.gartner.com/smarterwithgartner/enterprise-architects-define-digital-platforms/ http://www.gartner.com/smarterwithgartner/8-dimensions-of-business-ecosystems/ advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 109 the emerging technologies of the hype cycle is the longest-running annual gartner hype cycle [21]. it provides an important cross-industry perspective on the digital environment and disruptive technologies [28]. the hype cycle also shows the trends for global market developers, chief innovation officers, and r&d leaders. it is important for digital business strategists and digital entrepreneurs to develop digital – and emerging-technology portfolios. the emerging technologies hype cycle is unique among most gartner hype cycles [21]. there are insights at least 2,000 technologies and they are seeking emerging technologies and digital trends. the emerging technologies hype cycle focuses on the technologies, which promise a high degree of competitive advantage over the next 5 to 10 years (fig. 1). when we focus on technology innovation, it is significantly important to evaluate these high-level trends and the featured technologies, as well as the potential impact on their businesses. in addition to the potential impact on businesses, these trends provide a significant opportunity for enterprise architecture leaders to help senior business and it leaders respond to digital business opportunities and threats by creating signature-ready actionable and diagnostic deliverables that guide investment decisions. 3.2.1. ai everywhere ai everywhere: artificial intelligence technologies will be the first technology megatrends. ai will be the most disruptive class of technologies because ai will include radical computational power, unprecedented advances, near endless amounts of data in the digital networks. thus, organizations with ai technologies will have harnessed data in order to adapt new situations and solve digital problems that no one has ever encountered previously. in this ai theme, the companies that are seeking advance, consider should following the disruption technologies: deep learning, artificial general intelligence, autonomous vehicles, deep reinforcement learning, commercial uavs (drones), cognitive computing, smart robots, conversational user interfaces, machine learning, enterprise taxonomy, ontology management, smart dust, and smart workspace. 3.2.2. transparently immersive experiences transparently immersive experiences: the digital technology is coming more and more human-centric to the point where it will introduce transparency between people, businesses and things. this relationship will become significantly important when the evolution of digital technology becomes more contextual and adaptability in the workplace or at home. the most important thing is interacting with people and new businesses. the critical technologies of transparently immersive experiences includes: connected home, human augmentation, 4d printing, augmented reality (ar), computer-brain interface, nanotube electronics, virtual reality (vr), and volumetric displays. 3.2.3. digital platforms digital platforms: the emerging technologies require enabling foundations, which will provide characteristics like: enough data volume, advanced computing power, and ubiquity-enabling ecosystems. the ecosystem-enabling platforms allow entirely new business models between humans and digital technology. the innovative digital platform technologies include: iot platform, serverless paas, neuromorphic hardware, quantum computing, 5g, digital twin, edge computing, blockchain, and software-defined security. these three digital megatrends include the human-centric enabling technologies within transparently immersive experiences: most important are smart workspace, augmented reality, virtual reality, connected home, and the growing brain-computer interface. then, we are becoming the edge of digital technologies that are pulling the other trends along the hype cycle. http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp http://www.gartner.com/technology/research/hype-cycles/?cm_sp=sr-_-hc-_-btn http://www.gartner.com/it-glossary/digital-business/ http://www.gartner.com/it-glossary/digital-business/ http://www.gartner.com/smarterwithgartner/artificial-intelligence-and-the-enterprise/ http://www.gartner.com/smarterwithgartner/the-road-to-connected-autonomous-cars/ http://www.gartner.com/smarterwithgartner/let-machine-learning-boost-your-business-intelligence/ http://www.gartner.com/smarterwithgartner/control-the-connected-home-with-virtual-personal-assistants/ http://www.gartner.com/it-glossary/human-augmentation/ http://www.gartner.com/smarterwithgartner/exploring-augmented-reality-for-business-and-consumers/ http://www.gartner.com/it-glossary/computer-brain-interface/ http://www.gartner.com/it-glossary/nanotube/ http://www.gartner.com/it-glossary/vr-virtual-reality/ http://www.gartner.com/it-glossary/volumetric-displays/ http://www.gartner.com/it-glossary/volumetric-displays/ http://www.gartner.com/it-glossary/quantum-computing/ http://www.gartner.com/it-glossary/quantum-computing/ http://www.gartner.com/smarterwithgartner/5g-whos-in-the-drivers-seat/ advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 110 the emerging technologies of ai everywhere are moving fast through the hype cycle. those technologies are key enablers to create transparent and immersive experiences such as deep learning, autonomous learning, and cognitive computing. finally, digital platforms are rapidly moving up the hype cycle. the new innovative it realities provide the underlining platforms that will fuel the future. this future set of technologies includes quantum computing and blockchain, which will create the most transformative and dramatic impacts in the next 5 to 10 years. these three megatrends show that the more companies are able to make technology an integral part of employees', partners' and customers' experiences, the more they will be able to connect in new and dynamic ways to employees', partners' and customers' ecosystems and platforms. for digitalization management and technology leadership, it is important to understand the opportunities and threats affecting digital business. further, it is significant to take the lead in technology-enabled business innovations and help organizations define an effective digital business strategy. 3.3. corporate foresight, management and leadership tools since the late 1980s, the term “foresight” has been used to describe activities which inform decision-makers by improving the inputs about the long-term future of an organization [29-31]. the term foresight and strategic or corporate foresight need to be briefly discussed. the term foresight has been used since the late 1980s to describe an inherently human activity [32]. the term strategic, organizational or corporate foresight has been used to describe future research activities in corporations [32] or organizations. martin [33] and coates [34] emphasize that foresight deals with the long-term future and vecchiato [35] use strategic foresight deliberately to emphasize the tight relationship between foresight and strategy formulation (rohrback and gemüden) [36]. academic studies have generated knowledge on the need for corporate foresight systems (rohrback and gemüden, ruff) [36, 37] and the value contribution of strategic foresight [38] (e.g. vecchiato and roveda, burt and van der heiden). fig. 3 framework showing relationships in the vuca environment. modification of [40] in fig. 3, we have figured out key elements of the competitive landscape which are relevant to the vuca environment. globalization, hyper-competition and rapid technological change create key pre-conditions in the vuca environment. the key challenge for leaders is to change, the threats of the competitive landscape to opportunities. the role of mindsets is very important in this respect. a global mindset or the ability to view the world using a broad perspective converts globalization threats into growth opportunities by thinking beyond geographic boundaries, valuing integration beyond across borders and advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 111 appreciating regional and cultural diversity. an innovation mindset is a mental framework that fosters the development and implementation of new ideas. a virtual mindset or the ability of managers to hand over their companies ́activities to hyper competition [39] and external providers, turns hyper-competition into prospects for growth by facilitating flexibility and responsiveness. finally, a collaborative mindset means willingness allowing companies or corporations to engage in business partnerships. collaboration mindset integrates all the other mindsets, which can lead to synergy by business complementarities [40]. we can conclude that these four critical mindsets help corporations to manage disruptive technological innovations. the ability to change threats into opportunities is a critical asset in the vuca conditions. 3.4. the novel vuca challenges for corporate leadership and management in fig. 4, we present a novel synthesis about the vuca challenges and key solutions. the volatility of the environment requires agility on organizational culture. the uncertainty of the environment requires updated information and knowledge management. the complexity of the environment requires active restructuring of corporate organization. the ambiguity of the environment requires experimentation of management activities in the corporations. 3.5. foresight tools important for the vuca environment fig. 4 the vuca challenges and key solution concepts the term vuca has gained currency in the military during the late 1990s to describe an environment of volatility, uncertainty, complexity, and ambiguity. it reflects a shift from traditional cold war military conflicts to asymmetric warfare with agile dispersed opponents fighting under different rules for causes we do not fully understand. business condition is increasingly encountering vuca conditions as well and this poses deep new challenges. after short-run pressures are in conflict with long-run challenges. peter drucker [41] was one of the first to emphasize that management is doing things right and that leadership is about doing the right things [41]. however, in the vuca conditions, it is not easy to define, what are the right things and how to do things in the right ways. in recent manage and leadership literature, krupp and schoemaker [42] have presented a comprehensive answer, the sig discipline model to meet the vuca challenge. in fig. 5 the model is presented. fig. 5 the six disciplines [42] advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 112 table 1 the tools relevant to the vuca environment, relevant foresight tools and the key functions of foresight tools inside corporations tools relevant to the vuca environment relevant foresight tools the key functions inside corporations anticipating tools statistical forecasting tools, especially based on probability analysis identify risks and emerging new mark-markets interpreting tools statistical forecasting tools, risk analysis, especially based on probability analysis expert and crowdsourcing methods (delphi methodology and crowdsourcing techniques) analytical reflection of the results of anticipating tools creation of “big picture” of markets and corporate stakeholders challenging tools weak signal and wild card analyses, creativity tools, the analyses of desirability and feasibility, mirroring and benchmarking tools, technology roadmaps, trend and scenario analyses, competitor analyses identify alternatives and uncertainties in the environments eliminate the conceptional problems of group thinking amplify weak and strong signals decision-making tools priority setting tools, multi-objective decision-making tools, and models dr. z methodology and analysis: 1. don t́ rock the boat, 2. joining forces, 3. go it alone, 4. look for a friend and 5. fight the good fight. help decision-makers to be future-oriented decision-makers enable decision making with identifying options and comparing alternative options relevant for corporations pre-condition to the use of decision-making tools is to link challenging tools to decision-making tools aligning tools stakeholder analysis tools action planning deep dialogue tools bridging differences and understanding stakeholders learning tools organization of simultaneous experiments experimental fast learning tools (“valid experiments” and “robust experimental designs”) fast learning organization tools (“easy and quick experiment set-up” and “experimental data available quickly and automatically”) deep learning tools based on ai. create strong passions for experimentation and learning inside a corporation combination tools transcendent leadership tools transcendent leadership combines (1) leadership of self, (2) leadership of others and (3) leadership of the organization in this paper, we are not discussing all the elements of the six disciplines. we focus on the foresight aspects of corporate leadership. however, from fig. 5 we can learn the following messages. leaders and managers can develop their ability and capabilities [42]. the practical recommendations: (1) anticipate changes in the market environment by staying closely connected with customers, partners and competitors, rather than becoming disconnected and reactive. (2) interpret a wide array of data and viewpoints rather than looking only for evidence that confirms their prior beliefs. (3) challenge assumptions and the status quo by surrounding themselves with people who think outside the box and open to new ideas. (4) decide what to do after examining their options and then the courage to get it done than waffling or belaboring the decision-making process. (5) align the interests and incentives of stakeholders based on understanding different views, rather than relying on their power or position. (6) learn from success and failure by experimenting, making small bets, and mining the lessons from both the good and the bad outcomes to create quick learning cycles. in table 1, we have reported the tools relevant to the vuca environment, relevant foresight tools and the key functions of tools inside corporations. this table 1 summarizes the insights of krupp and schoemaker [41], but includes some additional remarks of the authors. especially we have clarified and defined the issue of key foresight tool and key functions of foresight tools inside corporations in this table. advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 113 these methodologies are discussed widely in the fields of futures studies and foresight [29, 31-32, 41-45]. the table above refers to the use of these futures oriented methodologies. 4. conclusions this paper contributes academically and practically to the discussion of digitalization and disruptive technologies. digital and disruptive technologies drive most economic growth and productivity. further, we practically analyzed and dis-empirical demonstration of the difference between gartner ś hype curve years 2008 and 2016. some technologies of the year 2008 hype cycle were foresighted very well, and they are nowadays very popular: tablet pcs, internet of things, cloud services, 3d printers, solid state drive is well foresight, and the augmented reality is coming fast. compared to the year 2016: fourteen technologies were taken off the hype cycle, and the 16 new technologies included in the hype cycle for the first time in the year 2016. gartner ś hype curve helps the leaders to understand the dynamics of technological disruption, which is extremely important for corporate leaders to be able to foresight the future. the three megatrends of digital business are ai everywhere, transparently immersive experiences, and digital platforms. the digital platforms are rapidly moving up on the hype cycle. the new innovative it realities provide the underlining platforms that will fuel the future. this future set of technologies includes quantum computing and blockchain, which will create the most transformative and dramatic impacts in the next 5 to 10 years. these three megatrends show that the more companies are able to make technology an integral part of employees', partners', and customers' experiences, the more they will be able to connect in new and dynamic ways to employees', partners', customers' ecosystems, and platforms. this paper combines the discussions of technological disruption, gartner ś hype curve, and the vuca environment and leadership. in the vuca conditions, leaders and managers need a new arsenal of foresight and management tools and methods. this paper elaborates some key theoretical approaches and practical solutions to the corporations facing turbulent vuca conditions. these tools can be classified to anticipation tools, interpreting tools, challenging tools, decision-making tools, aligning tools, learning tools, and combination tools. in this paper, we focus on the foresight aspects of corporate leadership. the practical recommendations for leaders: a) stay closely connected with customers, partners and competitors, b) interpret a wide array of data and viewpoints, c) challenge assumptions, d) decide what to do and then encourage personal, e) align the interests and incentives of stakeholders, f) learn from success and failure to create quick learning cycles. with the systematic application of these tools, corporate leaders and managers can face the vuca tests of surviving in the markets, where globalization, hyper-competition, fast turbulent technological changes test corporations and create increasing volatility, uncertainty, complexity, and ambiguity. already awareness of these vuca conditions and possible tools are important issues. many corporate leaders and managers need an updated understanding of these issues. global mindset, virtual mindset, innovation mindset, and collaboration mindset are key issues in the vuca environment. this paper helps corporate leaders and managers to understand key issues relevant to these mindsets, especially for an innovation mindset. conflicts of interest the authors declare no conflict of interest. advances in technology innovation, vol. 4, no. 2, 2019, pp. 105-115 114 references [1] c. jones, growth and ideas, ch. 16 in handbook of economic growth 1b, aghion p. and s. durlauf, internet article published in elsevier b.v, 2005. 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[45] k. haegman, e. marinelli, f. scapalo, a. ricci, and a. sokolov, “quantitative and qualitative approaches in future-oriented technology analysis (fta): from combination to integration?” technological forecasting & social change, vol. 80, no. 3, pp. 386-397, 2013. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (ccby) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 1, no. 1, 2016, pp. 13 15 13 copyright © taeti composite elements for biomimetic aerospace structures with progressive shape variation capabilities alessandro airoldi*, paolo bettini, matteo boiocchi, giuseppe sala department of aerospace science and technologies , politecnico di milano, italy received 01 february 2016; received in revised form 11 march 2016; accepted 02 april 2016 abstract the paper presents some engineering solutions for the development of innovative aerodynamic surfaces with the capability of progressive shape variation. a brief introduction of the most significant issues related to the design of such morphing structures is provided. thereafter, two types of structural solutions are presented for the design of internal compliant structures and flexible external skins. the proposed solutions explo it the properties and the manufacturing techniques of long fibre reinforced plastic in order to fulfil the severe and contradictory requirements related to the trade-off between morphing performance and load carrying capabilities . keywords: morphing structures, composite structures, chiral topologies, corrugated laminates 1. introduction morphing structures have been intensively studied in the last decades in the aerospace field, with the objective of developing innovative, more flexib le and efficient methods to change the shape of aerodynamic surfaces. imitation of nature plays an important role in conceiving such type of structures, since organisms have solved the problems related to flight control and adaptation to different flight phases without the use of rigid moveable surfaces , which are currently used in aircraft. for instance, a flexib le wing with the capability of shape variation can increase the curvature, when higher lift is required at low velocity, whereas, at high speed, curvature can be reduced to decrease drag (1). another concept, called “chiral sail” is proposed in (2) and is based on wing with a central morph ing part that increases its camber when angle of attitude is changed (fig. 1). th is can lead to noticeable advantages for the surfaces that generate the forces for the stabilization of a vehicle, like the tail empennages of aircraft. indeed, these surfaces could be reduced with overall weight saving and drag reduction. however, although morphing is an appealing concept, there are critical engineering issues to be solved for the development of such type of structures, which are hereby summarized in the following point: a) compliance of structures must be finely tuned to accomplish shape variations induced by aerodynamic loads (passive morphing) or of actuators (active morphing). b) shape can vary but must retain the aerodynamic efficiency, without angular points, surface waviness, and anomalous modification of profiles . c) aerodynamic loads acting in morphing directions must be transmitted, so that morph ing structures must exhib it flexib ility and strength at the same time (passive morphing), or reacted by load bearing actuators (active morphing). d) stiffness and strength in non-morphing directions must be maximized to avoid the need of additional structural parts that would increase structural weight, thus reducing or eliminating the advantages of morphing concepts. fig. 1 variable camber wing with central morphing part * corresponding author, email: alessandro.airoldi@polimi.it advances in technology innovation, vol. 1, no. 1, 2016, pp. 13 15 14 copyright © taeti in the following sections, two concepts will be presented to fulfill the aforementioned severe and contradictory requirements. 2. composite chiral structures chiral topologies are special non centre-symmetric geometries that consist of circular elements, called nodes, connected by straight ligaments (fig. 2-a). their deformation mechanis m leads to a transverse expansion, when a tensile load is applied, and a contraction, under the action of a compressive load (fig. 2-b). hence, if the chiral tessellation is considered as a meta-material, it turns out to be characterized by a negative poisson’s ratio (auxet ic behavior). such response avoids the development of localized displacements and weak points, and allows the achievement of controlled shape variations, as it is shown in fig. 2-c, referred to deformation modes of the chiral sail depicted in fig. 1. for such reasons, chiral topologies were proposed to develop the internal structure of morph ing airfoils [1], but manufacturing of chiral honeycombs represent a critical problem for application to real world structures. the process devised at politecnico di milano (4), allows the production of composite chiral elements by means of a procedure based on the bonding of composite units , which are produced in a prev ious step and then uniformly pressed together during bonding by means of elastomeric inserts (4,5). the resulting composite chiral elements can be produced with very thin ligaments and different types of composite materials, thus enhancing the design flexib ility o f the concept. some examples of manufactured chiral elements are provided in fig. 3. fig. 2 chiral topologies (a) deformation mechanis m (b) and deformation mode of a chiral airfoil (c) fig. 3 composite chiral honeycomb (a)and composite chiral rib for the chiral sail concept (b) 3. composite corrugated laminates the development of morphing surfaces always requires the development of a flexib le skin to collect aerodynamic forces . the requirements presented in the introduction are valid also for the skin, which has to undergo large recoverable strains, carrying and transmitting aerodynamic pressures to the internal structure. moreover, in traditional aeronautical constructions, skin also provides a valuable contribution to structural stiffness, so that optimal solutions should present adequate structural response in non-morphing directions. composite corrugated laminates have been proposed (6) to develop skins thanks to their inherent anisotropy that allow high compliance and strains at failure in corrugation directions, and noticeable stiffness and strength in non-morphing directions (fig. 4-a). fig. 4 corrugated laminate (a) composite chiral rib for the chiral sail (b) unfortunately, the usage of composite corrugated laminates as morphing skin has a major drawback represented by the surface irregularities that increase aerodynamic drag and reduce the generated lift (7). for such a reason, a solution was developed at politecnico d i milano (8) to integrate in the corrugated laminate an elastomeric layer, supported by honeycomb inserts (figs. 4-b and 4-c). the developed skin system was tested up to elongation of 20% (fig. a b advances in technology innovation, vol. 1, no. 1, 2016, pp. 13 15 15 copyright © taeti 4-d), proving that the elastomeric layer provides a smooth efficient aerodynamic surface without interfering with the mechanical response of corrugated laminates. the composite corrugated laminates can be designed with appropriate lay-up and guarantee very high bending stiffness in non-morphing directions and even a not negligible shear stiffness, which can exceed 50% of the shear stiffness obtained by a conventional panel of the same weight and lay-up (8). 4. concluding remarks the development of innovative solutions for internal structure and skin of morphing aerodynamic surface has been accomplished by jointly explo iting special structural geometries and the properties of composite materials. the presented solutions fulfil the peculiar requirements of morphing structures and have been applied to develop a demonstrator of the chiral sail concept, which is shown in fig. 5, in order to assess technological feasib ility, functional aspects and structural response. fig. 5 chiral sail demonstrator references [1] d. bornengo, f. scarpa, and c. remillat, “evaluation o f hexagonal chiral structure for moprh ing airfoil concept,” journal of aerospace engineering, vol. 219, pp. 185-192, 2005. [2] a. airo ldi, m. crespi, g. quaranta, and g. sala, “design of a morphing airfo il with composite chiral structure,” journal of aircraft, vol. 49, no. 4, pp. 1008-1019, 2012. [3] p. pan ichelli, a. gilardelli, a. airo ldi, g. quaranta, and g. sala, “morphing composite structures for adaptative high lift devices,” proc. 6th int. conference mechanics and materials in design, ponta delgada, azores, pp. 26-30 july 2015 [4] p. bettin i, a. airoldi, g. sala, l. di landro, m. ruzzene, and a . spadoni, “composite chiral structures for morphing airfoils: numerical analyses and development of a manufacturing process,” composites part b engineering, vol. 41, no. 2, pp. 133-147, 2010. [5] a. airoldi, p. bettini, p. panichelli, and g. sala, “chiral topologies for composite moprh ing structures – part ii: novel configurations and technological process”, physica statu solidi (b), vol. 252, pp. 1446-1454, july 2015 [6] t. yokozeki, s. takeda, t. ogasawara, and t. ishikawa, “properties of corrugated composites for candidate flexible wing structures,” composites part a: applied science manufacturing, vol. 37, no. 4, pp. 1578-1586, 2006. [7] y. xia, o. bilgren, and m. i. friswell, “the effects of corrugated skins on aerodynamic performances,” journal of intelligent material systems and structures, vol. 25, no. 7, pp. 786-794, 2014. [8] s. fournier, a. a irold i, e. borlandelli, and g. sala, “flexib le composite supports for morph ing skins,” proc. xxii aidaa conference, naples, italy, pp. 9-12, 2013.  advances in technology innovation, vol. 2, no. 1, 2017, pp. 13 17 13 the study of the microbes degraded polystyrene zhi-long tang, ting-an kuo, and hsiao-han liu * department of biological science & technology, i-shou university, kaohsiung, taiwan, roc. received 30 january 2016; received in revised form 28 march 2016; accepted 30 march 2016 abstract under the observation that tenebrio molitor and zophobas morio could eat polystyrene (ps), we setup the platform to screen the gut microbes of these two worms. to take advantage of that tenebrio molitor and zophobas morio can eat and digest polystyrene as its diet, we analyzed these special microbes with ps plate and ps turbidity system with time courses. there were two strains tm1 and zm1 which isolated from tenebrio molitor and zophobas morio, and were identified by 16s rdna sequencing. the results showed that tm1 and zm1 were cocci-like and short rod shape gram-negative bacteria under microscope. the ps plate and turbidity assay showed that tm1 and zm1 could utilize polystyrene as their carbon sources. the further study of ps degraded enzyme and cloning warrants our attention that this platform will be an excellent tools to explore and solve this problem. keywords: polystyrene, tenebrio molitor, zophobas morio, 16s rdna sequencing 1. introduction currently, the most popular method to decompose polystyrene was the thermal decomposition method, but this method would produce large amounts of dioxin and cause serious pollution to the environment [1, 2]. all these thermal methods faced an interaction with the polymer breakdown products which could lead to the formation of well-known dioxin precursors such as halogenated phenols should also be taken into account when evaluating the impact of bfr-treated materials on the environment [1]. however, the recent research directions of polystyrene degradation will be that use the way of biological decomposition, and these methods would reduce the waste polystyrene and dioxin. the approach of biodegradation of polystyrene was initiated in 1979, all bio-species show a very low degraded ability with c 14 -labelled plastic[3]. the best result from sludge microbes degraded the polystyrene for 0.57% after 11 weeks. the other species degraded less than 0 to 0.3% after 35 days. most organisms were not able to degrade ps. to take advantage of ps-eating mealworms, yang et.al. test the consumption of the ps[4]. furthermore, they explored the gut of mealworms, and identified of novel bacteria yt2 which belongs to exiguobacterium sp. and other 12 isolates based on its 16s rrna sequences[5, 6]. however, their methods for further identification and characterization of ps degrading enzyme of these microbes were not easy. our motivation of this study is to establish a more efficient and easy platform to study the ps degraded microbes within these worms. we utilize the mealworms (tenebrio molitor) as well as superworms (zophobas morio) for screening the ps eating microbes. furthermore, the microbes in this study were decomposing more quickly than previous studies. the setup of this novel screening platform will be an excellent tool to explore and solve the further study of ps degraded enzyme. the aims of this study is to isolate the polystyrene degrading microbes from the gut of t. molitor and z. morio, and the following methods will be used to exam ps-degrading ability of these microbes[7]. 2. method 2.1. preparation of ps emulsion and ps plate to prepare the ps emulsion, we dissolve the 7.5g ps powder by 50 ml chloroform. then transferred this solution to a 250 ml glass bottle with 100 ml basal medium (1.6g k2hpo4,1g (nh4)2so4,0.2g kh2po4,0.2g mgso4·7h2o,0.1g nacl,0.015g cacl2,0.01g feso4·7h2o/1000 ml) and biodegradable detergent[7]. next transferred the ps emulsion to 4℃ for 2 days. * corresponding author, email: hansliu@isu.edu.tw advances in technology innovation, vol. 2, no. 1, 2017, pp. 13 17 14 copyright © taeti after 2 days, we put the ps emulsion in hood to volatilize the organic solvents. the preparation of ps agar plate is to transfer 50 ml ps emulsion to a 100 ml glass bottle with 50 ml basal media and 0.75 g agar, sterile for 15 min at 121℃ and pour plate as general agar plates[7]. 2.2. isolation of ps degrading microbes a group of 20 mealworms and superworms separated fed with polystyrene as a sole diet for 3 weeks was collected, and washed out as a gut microbes’ suspension with basal medium. at first these gut microbes’ suspension was plating on the basal agar plate incubating for 24 h at 37℃ in aerobic and anaerobic conditions, and the microbes on the basal agar plate are collected. and then transferred the microbes on the basal agar plate to ps plate with yeast extract incubating for 24 h at 37℃ as above conditions. finally, the microbes on the ps agar plate are collected and the pure colonies were preserved for the following experiments. 2.3. bacteria strain characterization and 16s rdna sequencing there were two strains tm1 and zm1 which isolated from tenebrio molitor and zophobas morio, and were identified by gram staining, tsi agar test and 16s rdna sequencing. the genomic dna of the bacteria strains for 16s rdna sequencing were extracted by genomic dna extraction kit (thermo fisher scientific). the 16s rdna gene was amplifying by 27f-degl (5′-agrgttygatymtggctcag-3′) and 1492r (5′-ggttaccttgttacgactt-3′)[8]. the sequences were compared with 16s ribosomal rna sequences on the 16s rrna database using the basic local alignment search tool (blast) in ncbi. 2.4. turbidity assay turbidity assay was a method following the measurement that chua et.al. used[7]. this method could measure the ps-degrading ability of these microbes, and it was a quantitative indicator of the ps degradation as well. to quantify ps degrading activity, 1 ml of an overnight liquid culture of tm1 and zm1 in ps medium was mixed with 20 ml of basal medium containing 0.5 ml 0.75 % ps emulsion and incubated at 37℃ for following time courses. the ps degrading activity was measured spectrophotometrically at 600 nm. to observe the utilization of ps emulsion and ps degrading microbes’ suspension will be at 0.2, 4, 6, 24, 48 h respectively. 3. results and discussion 3.1. isolation and enrichment of ps degrading microbes after 3 weeks, the tenebrio molitor and zophobas morio were dissected and then the guts of the worms were prepared for the gut microbes’ suspension. the gut microbes’ suspension was transferred to the basal agar plate incubating for 24 h at 37℃ with different yeast extract concentration. the result showed that all of the agar plates have many colonies on basal agar (fig. 1). fig. 1 gut microbes plated on the basal agar plate (a) microbes from the gut of tenebrio molitor incubate with yeast extract (0.05g/l). (b) microbes from the gut of tenebrio molitor incubate with yeast extract (0.1g/l). (c) microbes from the gut of zophobas morio incubate with yeast extract (0.05g/l). (d) microbes from the gut of zophobas morio incubate with yeast extract (0.1g/l) advances in technology innovation, vol. 2, no. 1, 2017, pp. 13 17 15 copyright © taeti all of the colonies on the basal agar plate were rinsed with saline and collected. the suspension was plated on the ps plate incubating for 24 h at 37°c with different yeast extract concentration. the result showed that all of the agars have white colonies (fig. 2). the pure colonies were isolated by streaking plate method until the pure colonies were obtained (fig. 3). fig. 2 gut microbes plated on the ps agar plate (a) microbes from the gut of tenebrio molitor incubate with yeast extract (0.1g/l). (b) microbes from the gut of tenebrio molitor incubate with yeast extract (0.05g/l). (c) microbes from the gut of zophobas morio incubate with yeast extract (0.1g/l). (d) microbes from the gut of zophobas morio incubate with yeast extract (0.05g/l) fig. 3 pure colonies were isolated by streak plate method (a) pure colonies of tm1 incubate at anaerobic condition. (b) pure colonies of tm1 incubate at aerobic condition. (c) pure colonies of zm1 incubate at anaerobic condition. (d) pure colonies of zm1 incubate at aerobic condition to confirm that our ps plate could grow only the ps degrading microbes, we cultured different bacteria on ps plate and found that only the microbes which have the ability of ps degradation could grow on the ps plate (fig. 4). the final result showed that only the tm1 and zm1 can grow on the ps plate. fig. 4 the ps plate culture with different bacteria: zm1, tm1, s. aureus, dh5  (e. coli), lactobacillus 3.2. turbidity assay for the ps-degrading ability of the tm1 and zm1 the colonies from two strains tm1 and zm1 were added to the ps emulsion to confirm their ability of ps degrading. (fig. 5). the result showed that the degrading ability of tm1 and zm1 with yeast extract had more degrading activities than which that without yeast extract. fig. 5 turbidity assay (a) turbidity assay of tm1, zm1 at aerobic condition with or without yeast extract (0.5g/l) (b) turbidity assay of tm1, zm1 at anaerobic condition with or without yeast extract (0.5g/l). advances in technology innovation, vol. 2, no. 1, 2017, pp. 13 17 16 copyright © taeti 3.3. bacteria strain characterization and 16s rdna sequencing by gram staining, the tm1 and zm1 are showed both gram negative bacteria. and in the result of tsi agar test, we can confirm that the tm1 and zm1 are not the same bacteria strain (table 1). from tsi agar result, the tm1 could be alcaligenes sp., pseudomonas sp., or acinetobacter sp., and zm1 could be klebsiella pneumoniae. howerver, from 16s rdna data, the tm1 could be aeromonas sp., and zm1 could be klebsiella pneumoniae (fig. 6). this final confirmation of tm1 strain needs more accurate identification of other method. table 1 the results of tsi agar test tm-1 zm-1 slant alkaline acid butt alkaline acid h2s no no gas production no yes possible species alcaligenes pseudomonas acinetobacter klebsiella (a) description max score total score query cover e value ident accession aeromonas taiwanensis strain a2-50 16s ribosomal rna gene, partial sequence 928 928 92% 0.0 84% nr 116585.1 aeromonas sanarellii strain a2-67 16s ribosomal rna gene, partial sequence 922 922 92% 0.0 84% nr 116584.1 aeromonas dhakensis strain p21 16s ribosomal rna gene, complete sequence 922 922 92% 0.0 84% nr 042155.1 aeromonas hydrophila strain dsm 30187 16s ribosomal rna gene, complete sequence 922 922 92% 0.0 84% nr 119190.1 (b) description max score total score query cover e value ident accession klebsiella pneumoniae strain dsm 30104 16s ribosomal rna gene, partial sequence 1857 1857 99% 0.0 99% nr 117683.1 fig. 6 the blast results of 16s rdna sequencing.(a) the blast result of 16s rdna sequencing of tm1(b) the blast result of 16s rdna sequencing of zm1 4. conclusions in this paper, we setup the ps degrading screening platform, which successfully select the tm1, zm1 from worms’ gut. the characteristic of tm1 and zm1 have been identified through gram staining, tsi agar test, 16s rdna sequencing. this will be the first reported strain from the mealworm and superworm. in the turbidity assay, we can first time show that yeast extract will be a very important co-factor for the tm1 and zm1 with more efficient ps degrading ability. the further study of ps degraded enzyme and cloning from tm1 and zm1 warrants our attention that this platform will be an excellent tools to explore and solve this problem. acknowledgement the support of the minister of science and technology, roc (taiwan), under college student research scholarship 104-2815-c214-010-b is gratefully acknowledged. references [1] k. desmet, m. schelfaut, and p. sandra, “determination of bromophenols as dioxin precursors in combustion gases of fire retarded extruded polystyrene by sorptive sampling-capillary gas chromatography–mass spectrometry,” journal of chromato-graphy a, vol. 1071, pp. 125-129, april 4, 2005. [2] h. nishizaki, k. yoshida, and j. wang, “comparative study of various methods for thermogravimetric analysis of polystyrene degradation,” journal of applied polymer science, vol. 25, pp. 2869-2877, 1980. [3] d. kaplan, r. hartenstein, and j. sutter, “biodegradation of polystyrene, poly (metnyl methacrylate), and phenol formaldehyde,” applied and environmental microbiology, vol. 38, pp. 551-553, 1979. [4] y. yang, j. yang, w. m. wu, j. zhao, y. song, l. gao, r. yang, and l. jiang, “biodegradation and mineralization of polystyrene by plastic-eating mealworms: part 1. chemical and physical characterization and isotopic advances in technology innovation, vol. 2, no. 1, 2017, pp. 13 17 17 copyright © taeti tests,” environmental science & technology, vol. 49, pp. 12080-12086, 2015. [5] j. yang, y. yang, w. m. wu, j. zhao, y. song, l. gao, r. yang, and l. jang, “biodegradation and mineralization of polystyrene by plastic-eating mealworms. 2. role of gut microorganisms (supporting information),” environmental science and technology, vol. 49, no. 20, october, 2015. [6] t. k. chua, m. tseng, and m. k. yang, “degradation of poly (ε-caprolactone) by thermophilic streptomyces thermoviolaceus subsp. thermoviolaceus 76t-2,” amb express, vol. 3, p. 8, 2013. [7] b. van den bogert, w. m. de vos, e. g. zoetendal, and m. kleerebezem, “microarray analysis and barcoded pyrosequencing provide consistent microbial profiles depending on the source of human intestinal samples,” applied and environmental microbiology, vol. 77, pp. 2071-2080, 2011.  advances in technology innovation, vol. 1, no. 1, 2016, pp. 01 06 1 copyright © taeti the effect of the curvature-rate on the response of local sharp-notched sus304 stainless steel tubes under cyclic bending kuo-long lee1, shih-bin chien2, and wen-fung pan 3,* 1 department of innovative design and entrepreneurship management, far east university , tainan, taiwan. 2,3 department of engineering science, national cheng kung university, tainan, taiwan . received 20 january 2016; received in revised form 24 march 2016; accepted 28 march 2016 abstract in this study, the response of local sharp-notched sus304 stainless steel tubes with different notch depths of 0.2, 0.4, 0.6, 0.8 and 1.0 mm subjected to cyclic bending at different curvature-rates of 0.0035, 0.035 and 0.35 m -1 s -1 were experimentally investigated. the tube bending machine and curvature-ovalization measurement apparatus, which was designed by pan et al. [1], were used for conducting the curvature-controlled cyclic bending. for a constant curvature-rate, the moment-curvature curve revealed that the cyclic hardening and became a steady loop after a few bending cycles; the notch depth had almost no influence on the curves. moreover, the ovalizat ion-curvature curve increased in an increasing and ratcheting manner with the number of bending cycles. large notch depths resulted in larger ovalization of the tube cross-section. in addition, for a constant notch depth, higher curvature-rates led to larger cyclic hardening and faster increasing of ovalization. keywords: local sharp notch, sus304 stainless steel tubes, notch depth, curvature-rate, cyclic bending, moment, curvature, ovalization 1. introduction it is well known that the bending of circular tubes results in the ovalization (change in the outer diameter div ided by the original outer diameter) of the tube cross-section. this ovalization increases slowly during reverse bending and continuous cyclic bending and, in turn, results in the deterioration of the circular tube, which buckles when the ovalization reaches some critical value. the circu lar tube is severely damaged during buckling and cannot bear the load, which ultimately results in obstruction and leakage of the material being transported. as such, a complete understanding of the response of the circular tube to cyclic bending is essential for industrial applications. in 1998, pan et al. [1] designed and set up a new measurement apparatus. it was used with the cyclic bending machine to study various kinds of tubes under different cyclic bending conditions. for instance, pan and her [2] investigated the response and stability of 304 stainless steel tubes that were subjected to cyclic bending with different curvature-rates, lee et al. [3] studied the influence of the do/t ratio on the response and stability of circular tubes that were subjected to symmetrical cyclic bending, lee et al. [4] experimentally exp lored the effect of the do/t ratio and curvature-rate on the response and stability of circular tubes subjected to cyclic bending, and chang and pan [5] discussed the buckling life estimat ion of circu lar tubes subjected to cyclic bending. experimental investigations have shown that some engineering materials, such as 304 stainless steel, 316 stainless steel and high-strength titanium alloy, change mechanical properties (yield strength, hardening, ductility… etc.) under different strain-rates or stress-rates. therefore, once a tube which is fabricated by aforementioned materials is manipulated under cyclic bending at different curvature-rates, the response and collapse of tubes for each * corresponding author, email: z7808034@email.ncku.edu.tw advances in technology innovation, vol. 1, no. 1, 2016, pp. 01 06 2 copyright © taeti curvature-rate are expected to be generated differently. pan and his co-workers have investigated the influence of curvature-rate on the response and collapse of sus304 stainless steel tubes (pan and her [2]), titanium alloy tubes (lee and pan [6]) and 316l stainless steel tubes (chang et al. [7]) subjected to cyclic bending. however, all of their investigations considered tubes with a smooth surface. if a tube with a notch is considered, the response should be different from a tube with a smooth surface. in this study, the response for local sharp notched sus304 stainless steel tubes subjected to cyclic bending at different curvature-rates is discussed. a four-point bending machine (shaw and kyriakides [8], lee et al. [3]) was used to conduct the cyclic bending test. a curvature ovalization measurement apparatus (coma) designed and reported previously by pan et al. [1] was used to control and measure the curvature. for local sharp-notched tubes, five different notch depths, 0.2, 0.4, 0.6, 0.8 and 1.0 mm, were considered in this study. in addition, three different curvature-rates, 0.0035, 0.035 and 0.35 m -1 s -1 , were controlled. the magnitude of the bending moment was measured by two load cells mounted in the bending device, and the magnitudes of the curvature and ovalization of the tube cross-section were measured by coma. 2. experiment local sharp-notched sus304 stainless steel tubes with five different notch depths were subjected to cyclic bending at three different curvature-rates by using a tubebending device and a curvature-ovalization measurement apparatus in this study. detailed descriptions of the device, apparatus, materials, specimens and test procedures are given as follows . 2.1. bending device fig. 1 shows a picture of the bending device. it is designed as a four-point bending machine, capable of apply ing bending and reverse bending. the device consists of two rotating sprockets resting on two support beams. heavy chains run around the sprockets and are connected to two hydraulic cylinders and load cells forming a closed loop. each tube is tested and fitted with solid rod extension. the contact between the tube and the rollers is free to move along axial direct ion during bending. the load transfer to the test specimen is in the form of a couple formed by concentrated loads from two of the rollers. once either the top or bottom cylinder is contracted, the sprockets are rotated, and pure bending of the test specimen is achieved. reverse bending can be achieved by reversing the direction of the flow in the hydraulic circuit. detailed description of the bending device can be found in shaw and kyriakides [8] and lee et al. [3]. fig. 1 a picture of the bending device fig. 2 a picture of the coma 2.2. curvature-ovalization measurement apparatus (coma) the coma, shown in fig. 2, is an instrument used to measure the tube curvature and ovalizat ion of a tube cross -section. it is a lightweight instrument, which is mounted close to the tube mid-span. there are three inclinometers in the coma. two inclinometers are fixed on two holders, which are denoted side-inclinometers. these holders are fixed on the circular tube before the test begins. from the fixed distance between the two side inclinometers and the angle change detected by the two side-inclinometers, the tube curvature can be derived. in addition, a magnetic detector advances in technology innovation, vol. 1, no. 1, 2016, pp. 01 06 3 copyright © taeti in the middle part of the coma is used to measure the change of the outside diameter. a more detailed description of the bending device and the coma is given in pan et al. [1]. 2.3. material and specimens the circu lar tubes used in this study were made of sus304 stainless steel. the tubes’ chemical composition is cr (18.36%), ni (8.43%), mn (1.81%), si (0.39%), …., and a few other trace elements, with the remainder being fe. the ultimate stress, 0.2% strain offset the yield stress and the percent elongation are 626 mpa, 296 mpa and 35%, respectively. the raw smooth sus304 stainless steel tube had an outside diameter do of 36.6 mm and wall thickness t of 1.5 mm. the raw tubes were machined on the outside surface to obtain the desired local notch depth a of 0.2, 0.4, 0.6, 0.8 and 1.0 mm. fig. 3 shows a schematic drawing of the local sharp-notched tube. according to the drill of the machine, the corresponding surface diameters b were 0.6, 1.2, 1.8, 2.4 and 3.0 mm, respectively. fig. 3 a schematic drawing of the local sharp notched tube 2.4. test procedure the test involved a curvature-controlled cyclic bending. the controlled-curvature ranges were from  0.015 to  0.45 m -1 and three different curvature-rates of the cyclic bending test were 0.0035, 0.035 and 0.35 m -1 s -1 . the magnitude of the bending moment was measured by two load cells mounted in the bending device. the magnitudes of the curvature and ovalizat ion of the tube cross-section were measured by the coma. 3. results and discussion fig. 4 shows a typical set of experimentally determined moment (m) curvature () curve for local sharp-notched sus304 stainless steel tubes, with notch depth of a = 0.2 mm, subjected to cyclic bending under the curvature-rate of 0.0035 m -1 s -1 . the tubes were cycled between  =  0.3 m -1 . however, the tube exh ibits cyclic hardening and becomes stable after a few cycles. since the notch is small and local, the notch depth has almost no influence on the m- curve. therefore, the m- curves for different values of a are not shown in this paper. fig. 4 experimentally determined moment (m) curvature () curve for local sharp notched sus304 stainless steel tube, with notch depth of a = 0.2 mm, subjected to cyclic bending under the curvature-rate o f 0.035 m -1 s -1 figs. 5(a)-(b) present experimentally determined moment (m) curvature () curve for local sharp-notched sus304 stainless steel tubes, with notch depth of a = 0.2 mm, subjected to cyclic bending under the curvature-rate of 0.0035 and 0.35 m -1 s -1 , respectively. it is evident that the m- curves shown in figs. 4, 5(a) and 5(b) are very similar. however, higher curvature-rates lead to higher magnitude of the maximum moment at the maximum curvature. the maximum moments of 303, 316 and 325 n-m correspond to the curvature-rates of 0.0035, 0.035 and 0.35 m -1 s -1 , respectively. the highest and lowest curvature-rates have 100 times difference. but, the maximum moment only increases 7.3%. due to similar phenomenon, the experiment results of the m- response for local sharp-notched sus304 stainless steel tubes with a = 0.4, 0.6, 0.8 and 1.0 mm under cyclic bending at the curvature-rates of 0.0035, 0.035 and 0.35 m -1 s -1 are omitted in this paper. advances in technology innovation, vol. 1, no. 1, 2016, pp. 01 06 4 copyright © taeti (a) (b) fig. 5 experimentally determined moment (m) curvature () curve for local sharp notched sus304 stainless steel tubes , with notch depth of a = 0.2 mm, subjected to cyclic bending under the curvature rates o f (a) 0.0035 and (b) 0.35 m -1 s -1 figs. 6(a)-(e) depict the experimentally determined ovalizat ion of the tube cross-section (δdo/do) versus the applied curvature () for local sharp-notched sus304 stainless steel tubes , with notch depths a of 0.2, 0.4, 0.6, 0.8 and 1.0 mm, respectively, subjected to cyclic bending at the curvature-rate of 0.035 m -1 s -1 . the ovalization is defined as δdo/do where do is the outside diameter and δdo is the change in the outside diameter. it can be seen that the ovalization increases in a ratcheting manner with the number of bending cycles. higher a of the notch tube leads to a more severe unsymmetrical trend of the δdo/do- curve. in addition, higher a of the notch tube causes greater ovalizat ion of the tube cross-section. the maximum ovalizations of 0.0023, 0.0025, 0.0026, 0.0027 and 0.0028 fo r the curvature of -0.3 m -1 at the 6 th cycle correspond to notch depths a of 0.2, 0.4, 0.6, 0.8 and 1.0 mm, respectively. (a) (b) (c) fig. 6 experimentally determined ovalization of the tube cross-section (δdo/do) versus the applied curvature () for local sharp notched sus304 stainless steel tubes , with notch depths of a = (a) 0.2, (b) 0.4, (c) 0.6, (d) 0.8 and (e) 1.0 mm, subjected to cyclic bending under the curvature rate of 0.035 m -1 s -1 (continued) advances in technology innovation, vol. 1, no. 1, 2016, pp. 01 06 5 copyright © taeti (d) (e) fig. 6 experimentally determined ovalization of the tube cross-section (δdo/do) versus the applied curvature () for local sharp notched sus304 stainless steel tubes , with notch depths of a = (a) 0.2, (b) 0.4, (c) 0.6, (d) 0.8 and (e) 1.0 mm, subjected to cyclic bending under the curvature rate of 0.035 m -1 s -1 figs. 7(a)-(b) depict the experimentally determined ovalizat ion of the tube’s cross-section (δdo/do) versus the applied curvature () for local sharp-notched sus304 stainless steel tubes, with notch depth of a = 0.2 mm, subjected to cyclic bending under the curvature-rates of 0.035 and 0.35 m -1 s -1 , respectively. it can be noted that a higher degree of ovalizat ion can be noticed under higher curvature-rates. the maximum ovalizations of 0.0018, 0.0023 and 0.0028 for the curvature of -0.3 m -1 at the 6 th cycle correspond to the curvature-rates of 0.0035, 0.035 and 0.35 m -1 s -1 , respectively. the highest and lowest curvature-rates have 100 t imes difference. but, the maximum moment increases 55.6 %. it is concluded that the curvature-rate has a strong influence on the δdo/do- curve. again, due to similar results, the experimental results of the δdo/do- response for local sharp-notched sus304 stainless steel tubes with notch depths of 0.4, 0.6, 0.8 and 1.0 mm under the curvature-rates of 0.0035 and 0.35 m -1 s -1 are omitted in this paper. (a) (b) fig. 7 experimentally determined ovalization of the tube cross-section (δdo/do) versus the applied curvature () for local sharp-notched sus304 stainless steel tubes, with notch depths of a = 0.2 mm, subjected to cyclic bending under the curvature-rate of (a) 0.0035 and (b) 0.35 m -1 s -1 4. conclusions the response of local sharp-notched sus304 stainless steel tubes with d ifferent notch depths subjected to cyclic bending at different curvature-rates was experimentally investigated in this study. based on the experimental results, the following important conclusions can be drawn: advances in technology innovation, vol. 1, no. 1, 2016, pp. 01 06 6 copyright © taeti (1) it is found from the m- curves that the local sharp-notched sus304 stainless steel tubes with any notch depth at any curvature-rate exh ibits cyclical hardening and gradually steady after a few cycles under symmetrical curvature-controlled cyclic bending. (2) it can be seen that a higher curvature-rate leads to a higher magnitude of the moment. in addition, the curvature-rate has a slight influence on the m- curves (figs. (4), 5(a) and 5(b)). (3) it is observed from the δdo/do- curves that the ovalization of the tube cross -section increases in an unsymmetrical and ratcheting manner with the number of cycles. higher a leads to more severe unsymmetrical trend of the δdo/do- curve. (4) it can be seen that a higher curvature-rate leads to a greater ovalization of the tube cross-section. in addition, the curvature-rate has a strong influence on the δdo/do- curves (figs. 6(a), 7(a) and 7(b)). acknowledgement the support of the national science council (taiwan), under grant nsc 102-2221 e-006-037 is gratefully acknowledged. references [1] w. f. pan, t. r. wang, and c. m. hsu, “a curvatureovalization measurement apparatus for circular tubes under cyclic bending,” experimental mechanics , vol. 38, no. 2, pp. 99-102, 1998. [2] w. f. pan and y. s. her, “viscoplastic collapse of thinwalled tubes under cyclic bending,” journal of engineering materials and technology, vol. 120, no. 4, pp. 287-290, 1998. [3] k. l. lee, w. f. pan, and j. n. kuo, “the influence of the diameter-to-thickness ratio on the stability of circular tubes under cyclic bending,” international journal of solids and structures, vol. 38, no. 14, pp. 2401-2413, 2001. [4] k. l. lee, w. f. pan, and c. m. hsu, “experimental and theoretical evaluations of the effect between diameter-tothickness ratio and curvature-rate on the stability of circular tubes under cyclic bending,” jsme international journal, series a, vol. 47, no. 2, pp. 212-222, 2004. [5] k. h. chang and w. f. pan, “buckling life estimation of circular tubes under cyclic bending,” international journal of solids and structures, vol. 46, no. 2, pp. 254-270, 2009. [6] k. l. lee and w. f. pan, “viscoplastic collapse of titanium alloy tubes under cyclic bending,” structural eng ineering and mechanics, vol. 11, no. 3, pp. 315-324, 2001. [7] k. l. lee, c. m. hsu, s. r. sheu, and w. f. pan, “viscoplastic response and collapse of 316l stainless steel tubes under cyclic bending,” steel and composite structures, vol. 5, no. 5, pp. 359-374, 2005. [8] p. k. shaw and s. kyriakides, “inelastic analysis of thin-walled tubes under cyclic bending,” international journal of solids and structures, vol. 21, no. 11, pp. 1073-1110, 1985.  advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 design and testing of a remote deployable water purification system powered by solar energy amber e. keith, jesse j. french * department of mechanical engineering, letourneau university, longview, texas, usa received 20 july 2017; received in revised form 05 september 2017; accepted 15 january 2018 abstract the design of an all-inclusive, self-sufficient, sustainable water purification system for application in developing regions of the world can improve living conditions for people world-wide, especially in regions where access to clean drinking water is limited or unavailable. according to the world health organization, the 2015 global census estimated that 663 million people worldwide live without access to safe drinking water sources [1]. an estimated 315,000 children die each year from diarrheal diseases caused by lack of clean water and poor sanitation [2]. based on these statistics, an all-inclusive, self-sufficient, remote-deployable water purification system has been designed, constructed, and tested to validate the concept of a renewable energy system. the system is integrated into a standard 20-foot shipping container for ease of deployment worldwide. once situated in the operating area, the shipping container is used as the system shelter and solar panels are mounted to the roof at a location-dependent fixed angle. the solar panels are connected to a battery bank which operates the system. the water purification process utilizes a five-step progression which filters the contaminated freshwater, removing suspended particles and bacteria from the water and purifying the water to the standards of the epa safe drinking act [3]. testing verifies the capability of the solar panels to generate enough electricity to power the system and recharge the battery bank. the solar panel array has the rated power output of 2,320 watts. the water purification operates on a maximum of 97.9 watts of available power. with the fully charged battery bank, the water purification system can operate for 24-hours without additional solar input. with a freshwater source, the purification system can yield up to 440 liters of water per hour. keywords: renewable energy, solar power, clean water, water purification, self-sufficient 1. introduction without water, a person will die of dehydration within three days [4]. without water, crops cannot be grown and starvation can result. though over 70% of the earth’s surface is covered in this vital source of life, clean drinking water is scares [2]. freshwater, water that is not full of dissolved salts, makes up only about 2.5% of the water source on the entire planet [5]. of that 2.5%, only about half of that is accessible for use [5]. according to the world population clock, there is currently 7.5 billion people on the plant with a projected population reaching 8 billion by the year 2023 and 10 billion by the year 2056 [6]. those 7.5 billion people must share the one percent of available freshwater on the world for drinking, cooking, and cleaning. unfortunately, the distribution of drinking water is not proportional to the distribution of the population [7]. some areas enjoy a surplus of water, whereas others have significant shortages [7]. as can be seen in fig. 1, the water * corresponding author. e-mail address: jessefrench@letu.edu advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 31 scarcity is very drastic, especially for desert regions such as central africa. according to many sources, including lifewater, a non-profit working to end the global water and sanitation crisis, water and poverty are mutually dependent [8]. in areas where access to clean drinking water has been introduced, the quality of life of the people also increases [8]. fig. 1 global water scarcity [9] an estimated six to eight million people die from water-related diseases each year [10]. inventor of the segway, dean kamen, once said, “we could empty half the hospital beds in the world by just giving people clean water” [11]. dean kamen has gone on to design the slingshot water purification system which uses a vapor distillation method to bring about this goal to reduce the number of people in hospital beds, simply by improving access to clean water [11]. water shortages are not the only shortage affecting the developing world. the international energy agency has estimated that 1.2 billion people worldwide live without access to electricity [12]. seventeen percent of the global population lives without electricity, even for simple household illumination, cellphone charging, or computer use. by proving a system that generates excess electricity after purifying water, two global issues can be solved with a single system. 2. system design the sustainable purification system (sps) is powered solely by renewable resources to provide access to clean drinking water limited electricity to underdeveloped regions around the world. for simplicity of deployment and maintenance, the water purification system has been designed to be chemical-free, since access to chemicals in remote locations would be nearly impossible and not cost-effective. the minimum desired purified water output is 150 liters per day. this is a sufficient water output for a 50-person community with the assumption that each resident receives 3-liters of purified water per day. further testing has been conducted to determine the exact potential output for the system based on optimum solar conditions and power supplied from the battery bank. the water purification system is powered by eight 290 watt solar panels mounted on the roof of the shipping container. the solar panels are mounted at a fixed angle of 30.0°. this angle was chosen based on the latitudinal position of the testing location. electricity generated by the solar panels is directed through a charge controller, which will either utilize the power for pumping and purifying water or for charging the on-board battery bank. excess electricity is available for system, lighting and installed outlets for powering electronics such as cellphones. the sps container can be seen in fig. 2 with the solar array mounted on the roof at the fixed angle. the system is monitored by the charge controller which is designed to keep the battery bank from dropping below a 50% charge value in order to preserve the lifespan of the deep-cycle batteries. an arduino-based controller monitors the battery voltage and water levels in order to automatically produce water, as needed. if the battery bank drops below 50% capacity, the arduino controller will shut off the system to prevent over-discharge. the charge controller and arduino for the system can be seen in fig. 3 below. advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 32 fig. 2 sustainable purification system shipping container enclosure fig. 3 arduino and charge controller setup for the sustainable purification system fig. 4 water purification system with labeling the system design for purification is broken into three main sub-systems: pumping, purification, and storage. the five stages of filters can be seen in fig. 4. first, the water is pumped from the source; whether a deep or shallow well, river, lake, or sea. the pump is a fully submerged pump that is coupled with a flow switch to turn off the pump when insignificant water is available. next, the water proceeds through the three-stage purification system: filtration, sterilization, and purification. the entire design is constructed into a custom workbench to contain the components. the filtration stage includes three filters types: sand, spin-down, and two cartridge filters. the water flows through the sand filter to remove large particulates, such as dirt and leaves. this filter is designed to process up to 30,000 liters of water at up to 140 liters per minute. the spin-down filter is a 15-micron screen to remove particles left behind after the sand filter. the final stage is a set of cartridge filters remove down to five microns and then one-micron sized particles. any particulate remaining after the filtration stage is less than one micron in size. for comparison, a human hair is about 75 microns in size [13]. next is the sterilization phase. a uv lamp provides fluence to the water to kill bacteria and viruses. the bacteria and viruses are not removed in this stage, just eradicated. in the final purification phase, the water passes through a rapidpure filter system. this stage filters particles down to 1.75 microns and then implements a positive charge to remove additional particles. advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 33 this final phase removes 99.9% of bacteria, 99.9% of viruses, and 99.8% of cyst. the rapidpure filter also reduces the concentration of bromine, chlorine, iodine, lead, penicillin, and other various heavy metals. at this time, the water is safe to drink and flows into the storage tank. 3. experimental procedure testing was conducted to determine the rate of purification to determine how much water the system could purify in a full eight-hour cycle of operation. the power requirements for the individual components of the system were also characterized. to determine the system power requirements, the charge controller was set in the float state with the batteries fully charged. this means that all power generated would be used for powering the system and not for additional charging of the battery bank. to ascertain how much power was used by the system, the purification system cycled ten liters of water. the charge controller displays the amperage draw of the system and the overall voltage. by knowing the amperage and voltage of the system, the power draw can be calculated with ohm’s law: 𝑐𝑢𝑟𝑟𝑒𝑛𝑡 [𝐴] × 𝑣𝑜𝑙𝑡𝑎𝑔𝑒 [𝑉] = 𝑝𝑜𝑤𝑒𝑟 [𝑊]. fig. 5 digital flow meter installed in system between the purification system and storage tank fig. 6 k24 digital flow meter with 3d printed adapters the pump is rated for a maximum flow rate of 7.0 liters per minute when the pump is at a head of 20 feet. this means that if the pump is operating at peak performance, then in a single hour, the system should theoretically cycle 420 liters of water. this provides three liters of water per resident for up to 140 people per hour. for flow rate testing, the k24 turbine digital flow meter was placed in-line with the system between the rapidpure filters and the storage tank as seen in fig. 5. the k24 digital flow meter has one-inch british standard pipe (bsp) threads on both ends of the display for the inlet and outlet. the hose between the final stage of the purification system and the storage tank is ¾ -inch clear tubing. the solution to convert the 1-inch bst to 3/4-inch barb hose fitting was a series of three transition adapters. since bsp is not a standard size available in the united states, the adapters were 3d printed and threaded together with sealing tape to prevent leaking between the adapters. advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 34 the flowmeter displays the flow rate and number of liters that have passed through the system. during testing, the flow rate was recorded periodically during a continuous twenty-minute system operation. the k24 digital flowmeter can be seen fig. 6 in with the three types of transition adapters labeled. 4. results and discussion 4.1 water purification rates during testing for system operations, data was recorded for elapsed time and liters cycled. the digital flowmeter displayed a consistent 7.1 liters per minute flow rate during the entire period. after an elapsed time of thirteen and a half minutes, a full 100-liters had been processed through the system. at the conclusion of testing, 147.4 liters of water had been purified. this is slightly higher than the predicted 140 liters from the expected flow rate. this testing was conducted under optimum conditions since the overall head of the pump is less than 20 feet. extrapolating the testing results, it is estimated that the system can purify up to 440 liters per hour. if the system operates for 8 hours a day, up to 3,520-liters water can successfully be purified in a single day of operations. since the design parameter is to provide 3-liters of clean drinking water to each resident, the current system is properly sized for a 1,000-person community. the predicted verse the actual volume of purified water compared to elapsed time can be seen in fig. 7. as shown in the graph, the flow rate of the water purification is linear. fig. 7 volume of purified water vs. elapsed time 4.2 power consumption table 1 current and power draw for system components control system uv filter pump whole system current [a] 0.7 1.4 2.4 3.6 voltage [v] 27.2 27.2 27.2 27.2 power draw [w] 19.04 38.08 65.25 97.92 the power system requires 24v of direct-current [dc] electricity. the charge controller displays a constant system voltage of 27.2v, which is the charging voltage of the storage batteries. table 1 shows a summary of the amperage and power draw of different combinations of system components. the arduino controller and charge controller are continuously operated, so the current draw is constant at 0.7a. the 19w power draw from the control system is required for system monitoring and operations. most of the purification system is passive and does not require electricity; the uv filter being the only component that requires power to function. with the uv filter operation and the pump turned off, the system requires 38w of power to 0 20 40 60 80 100 120 140 160 0 5 10 15 20 w at er v o lu m e [l ] elapsed time [min] flowrate predicted vs. actual volume predicted volume [l] actual volume [l] advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 35 operate. this scenario, however, is impractical since without the pump, no water is actively passing the uv filter. the next evaluation was with the pump functioning and the uv filter turned off. the pump combined with the control system draws 2.4a for a power draw of 65w. finally, with all components of the system functioning, the current draw raises to 3.6a and requires 97.9w of power. the graph in fig. 8 displays the power draw of the various components with the power draw from the control system being constant. fig. 8 power requirements as additional components are activated; cumulative effect on the overall power draw the system power draw is significantly less than the overall power potential of the solar array. excess power generated can be utilized for charging the battery bank for use when the solar insolation is minimal. in the case where the battery bank is already fully charged and the sun is out to continue generating power, excess electricity. potentially, surplus power generated could be utilized for charging cell phones or powering household lighting; however, first priority of the system is to keep the battery bank at full charge in case of insufficient sun for power generation for operating the system. 5. conclusion with the self-contained system integrated into the shipping container, the water purification system can be deployed, set up, and operated wherever in the world there is a need for clean water and access to solar energy. the current water purification system is operational and sufficient for providing clean drinking water to a small community anywhere in the world provided there is an accessible source of fresh water for filtration. through testing, it has been demonstrated that the solar array provides more than sufficient power to operate the water purification system, with the excess being used to charge the battery bank. with a fully charged battery bank, the system can be operated full 24-hour period without solar input. this system can be designed and optimized for any application and for a variety of locations. the solar array can be expanded and the fixed mounted angle of the panels is customized to the final destination, based on the latitude of the location. through the research and development of the sustainable purification system, a practical system is built and tested which is relevant to the global water crisis. references [1] who library cataloguing-in-publication data, “progress on sanitation and drinking water-2015 update and mdg assessment,” pp. 17-35, 2015. [2] “statistics-the hard facts behind the crisis,” http://www.wateraid.org/what-we-do/the-crisis/statistics. february 24,2017. 0 10 20 30 40 50 60 70 80 90 control system uv filter pump whole system p o w er d ra w [ w ] power draw vs. system components pump uv filter control system advances in technology innovation, vol. 4, no. 1, 2019, pp. 30 36 36 [3] “safe drinking water act,” https://www.epa.gov/sdwa, 2002. [4] c. binns, “how long can a person survive without water? ” http://www.livescience.com/32320-how-long-can-a-person survive-without-water.html, november 30, 2012. [5] h. perlman, “how much water is there on, in, and above the earth ” http://water.usgs.gov/edu/earthhowmuch.html, december 2, 2016. [6] “current world population,” http://www.worldometers.info/world-population december 11, 2016. [7] b. chaouchi, a. zrelli, and g. slimane, “desalination of brackish water by means of a parabolic solar concentrator,” desalination, vol. 217, no. 1, pp. 118-126, 2007. [8] “water and poverty,” https://lifewater.org/blog/water-poverty/, december 26, 2017. [9] managing water under uncertainty and risk, the united nations world water depvelopment report 4, paris, unesco, 2012. [10] “water facts and figures,” http://www.unwater.org/water-cooperation-2013/water-cooperation/facts-and-figures/en/, 2013. [11] s. nasr, “how the slingshot water purifier works,” http://science.howstuffworks.com/environmental/green-tech/ remediation/slingshot-water-purifier.htm, july 27, 2009. [12] “energy poverty,” http:// www.iea.org/topics/energypoverty/, january 10, 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 3, no. 2, 2018, pp. 9499 ball nut preload diagnosis of the hollow ball screw through support vector machine yi-cheng huang*, jing-hong zheng department of mechatronics engineering, national changhua university of education, changhua, taiwan . received 21 july 2017; received in revised form 17 september 2017; accepted 18 november 2017 abstract this paper studies the diagnostic results of hollow ball screws with different ball nut preload through the support vector machine (svm) process. the method is testified by considering the us e of ball screw pretension and different ball nut preload. svm was used to discriminate the hollow ball screw preload status through the vibration signals and servo motor current signals. maximum dynamic preloads of 2%, 4%, and 6% ball screws were predesig ned, manufactured, and conducted experimentally. signal patterns with different preload features are separated by svm. the irregularity development of the ball screw driving motion current and rolling balls vibration of the ball screw can be discriminated via svm based on complexity perception. the experimental results successfully show that the prognostic status of ball nut preload can be envisaged by the proposed methodology. the smart reasoning for the health of the ball screw is available based on class ification of svm. this diagnostic method satisfies the purposes of prognostic effectiveness on knowing the ball nut preload status. keywords: ball nut preload, ball screw, support vector machine 1. introduction precision cnc machines are widely used in modern industry for mass production. recently, many strategies have been proposed to diagnose machine status, providing operators with important information to extending the machine’s useful lifespan. chen and lee [1] established a prognostic system to acquire and analyze vibration signals corresponding to various ball screw states. calculated results are saved in a database, and a training model is established using several classification methods. since ball screws are widely used in linear actuators for various types of machinery and equipment. preloading is an effective means to eliminate the backlash and increase the stiffness of the ball screw for precision motion, thus maximizing efficiency [2]. preload loss leads to a lower natural frequency, lower stiffness, oscillatory positioning, and chance of rapid downtime in the manufacturing process. some methods proposed for tuning preload values are time consuming and incur increased downtime, thus raising the need to predict the ball screw nut preload status during machine operation. fault diagnosis with most acquired signals requires the assistance of conventional fourier transform or discrete wavelet transform in the frequency and time domains [3-4]. however, for many real applications, the signals are multi-components and are often corrupted by noise. as mentioned, loss of ball screw preload not only decreases the bandwidth of the frequency response spectrum but also reduces positioning accuracy. accordingly, industrial mass production applications would benefit from the lifetime prediction for ball screw preload loss status, but few studies have focused on this topic. the complexity of a ball screw with * corresponding author. e-mail ychuang@cc.ncue.edu.tw advances in technology innovation, vol. 3, no. 2, 2018, pp. 9499 copyright © taeti 95 preload in operation is highly nonlinear and non-stationary. traditional entropy measurements quantify only the regularity (predictability) of a time series on a single scale. no straightforward correlation exists, however, between regularity and complexity. this study applies support vector machine (svm) [5-8] to classify the complexity of finite length time series. this computational tool has been applied successfully both to physical data sets, and can be used with a variety of measures of different patterns. the feature patterns of preload status are determined and abstracted via the function of svm. svm analysis is used to discriminate the prognostic preload status of ball screws in this preliminary study 2. dynamic model of the ball screw drive system to model the feed drive system, this paper sets different ball nut stiffness for different preload between the ball screw shaft and the ball nut. the presetting preload value can be deployed by inserting different ball size for single ball nut design or using disk spring that applied to the ball screw when double ball nut is the preference. fig. 1 shows the picture of the in-lab single-axis feed drive platform. to analyze the dynamic characteristic of the ball screw system under different preload and varying table mass, the feed drive system is modeled by a lumped parameter system shown in fig . 2. fig. 2 is the schematic illustration for the single-axis ball screw feed drive system. in general, mechanical systems have three passive linear components. the spring and the mass are energy-storage elements, while the viscous damper is the dissipated energy. both of the rotational and translation mechanical system modeled below are actuated by the servo motor torque, indicated as t. the overall stiffness of a ball screw feed drive system can be determined by the stiffness of the ball screw itself, which is comprised of the ball screw shaft, th e ball nut, supporting bearings of the ball screw, and the stiffness between the ball screw and the working table [9]. xxrkxbxm tbbntttt )()0(   (1) 0)()0()0(  tbbnbebbbb xxrkxkx bxm  (2) ) θ(θk)] xxθ(r[krθqθj bmgtbbnbbbb   (3) tkqj bmgmmmm  )(   (4) rearranging eqs. (1)-(4), we have                                                                                                            t rr r e r m b b t gg gngn nnn nnn m b b t m b b t m b b t m b b t r 0 0 0 00 0 0 000 000 000 000 000 000 000 000 x x kk kkkkk kkkk kkk x x q q b b x x j j m m 2 n               (5) (a) the in-house single axis platform (b) the picture of the acceleration sensor attached to the ball nut fig. 1 photo of the in-lab single axis servo drive system and the acceleration sensor attached to the ball nut advances in technology innovation, vol. 3, no. 2, 2018, pp. 9499 copyright © taeti 96 fig. 2 illustration for the schematic diagram of the single-axis lumped parameters ball screw drive system 3. support vector machine conventionally, there are many possible linear classifiers that can be divided into two different featured data. svm provides a method that can maximize the margin in between two separated data. one of linear or nonlinear classifiers is termed the optimal separating hyperplane, as shown in fig. 3. intuitively, one would expect margin boundary to generalize well as opposed to the other possible boundaries . fig. 3 illustration for the seperating hyperplane for linear (left) and nonlinear (right) svm 4. experiment results fig. 4 linear svm kernel function for vibration signals by 5 minutes running with 2 % preload ball nut by pretension of 5μ and 20μ of the ball screw fig. 5 linear svm kernel function for vibration signals by 30 minutes running with 2 % preload ball nut by pretension of 5μ and 20μ of the ball screw advances in technology innovation, vol. 3, no. 2, 2018, pp. 9499 copyright © taeti 97 figs. 4-5 show the hyperplane divides pretension of 5μ (with + mark in red color) and 20μ(with * mark in green color) into two half-spaces when the table with 2 % ball nut preload was operated by 5 and 30 minutes, respectively. though using one sensor signals, the classification rate is not very high. nevertheless, it can be used as the initial decision boundary of a binary classifier when the cnc table does the repetitive backward and forward motion consecutively under 30 minutes. fig. 6 shows that deploying such linear decision boundary can’t classify the two pretensions by 60 minutes using svm’s linear kernel function. the average classification rate was only 79 %, 69 % and 48 % by running cnc table with 5, 30 and 60 minutes , respectively. since 2 % preload ball screw was treated as the preload loss condition while 4 % one was in the standard condition. after consecutive 30 minutes operation, the increasing temperature distribution of the ball screw causes the pretension effect loss and less mechanical complexities sensed by vibration sensor naturally. from figs. 4-6, the experimental results illustrate the thermo expansion around the ball nut and ball screw renders the diagnosis effect on the classification of the ball pretension vanished . fig. 6 linear svm kernel function for vibration signals by 5 minutes running with 2 % preload ball nut by pretension of 5μ and 20μ of the ball screw fig. 7 linear svm kernel function from vibration signals by 5 minutes running with 4 % preload ball nut by pretension of 5μ and 20μ of the ball screw research study here is aim to produce a classifier that can work well on different ball nut preload situations when they are applied by different ball screw pretensions. figs. 7-8 show the hyperplane divides pretension of 5μ (with + mark in red color) and 20μ(with * mark in green color) into two half-spaces when the table with 4 % ball nut preload was operated by 5 and 30 minutes, respectively. the linear classifier is termed the optimal separating hyperplane when the machine was operated by 30 minutes. the maximum margin (maximizes the distance between the 5μand 20μ) is in fig. 8 with 100 % average precision classification. experimental results show based on standard preload, the conventional warm-up procedure in industry can do the machine diagnosis with two different pretension on the ball screws by vibration signals. since different pretension creates different ball screw stiffness in axial direction, the svm can generate very good classification by standard operations. nevertheless, in fig. 9, after 60 minutes, the separating hyperplane generated by linear kernel function of svm can’t determine the pretension features by classification. the average precision classification was only 48 % and 54 % by running cnc table with 5 and 60 minutes , respectively. the reason was that due to the initial 5 minutes, the 4 % ball nut preload dominated the total stiffness of the ball screw. after 60 minutes operation, the increasing temperature of the ball screw renders the ball screw pretension effect diminished and the stiffness of the ball nut and the blurred vibration signals were loss thereof. fig. 10 shows using linear svm kernel function can’t separate the 2 % and 6 % ball nut preload features when the cnc table was running after 30 minutes for each ball screw pretension fixed at 5μ and 20μ. nevertheless, using nonlinear radial basis function (rbf) svm kernel function, the features patterns in fig. 11 can be separated. such promising results were based on the nonlinear kernel function. heuristically, one or more sensors can facilitate the svm classification and toward successfully. advances in technology innovation, vol. 3, no. 2, 2018, pp. 9499 copyright © taeti 98 fig. 8 linear svm kernel function from vibration signals by 30 minutes running with 4 % preload ball nut by pretension of 5μ and 20μ of the ball screw fig. 9 linear svm kernel function from vibration signals by 60 minutes running with 4 % preload ball nut by pretension of 5μ and 20μ of the ball screw (a) for separating 2 % and 6 % preload ball nut with pretension of 5μ of the ball screw (b) for separating 2 % and 6 % preload ball nut with pretension of 20μof the ball screw fig. 10 linear svm kernel function from vibration signals by 30 minutes running (a) for separating 2 % and 6 % preload ball nut with pretension of 5μ of the ball screw (b) for separating 2 % and 6 % preload ball nut with pretension of 20μ of the ball screw fig. 11 nonlinear rbf svm kernel function from vibration signals by 30 minutes running advances in technology innovation, vol. 3, no. 2, 2018, pp. 9499 copyright © taeti 99 5. concluding remarks this research uses the s ignal analysis techniques by svm to detect the preload status of hollow ball screw nuts. different ball screw pretensions and ball nut preload in a one axis machine tool feed drive table were studied. both the highly nonlinear processing svm methods and linear hyper plane were used to diagnose the machinery health status . vibration measure was used to dynamically quantify the hollow ball screw’s complexity and identify the irregular development of the ball nut preload. experimental results show the sensed vibration signals of the preload features were extracted clearly with standard 4 % preload when the cnc table was operated by 30 minutes. compensated positioning technique by ball screw pretension with 5μ and 20μ was not significantly contaminated by cnc 30 minutes operation time by linear svm prognostic diagnosis when the ball nut preload was 4 %. nonlinear rbf svm was able to separate the 2 %ball nut preload 6 % ball nut preload when the cnc table was operated by 30 minutes. heuristically, with more sensors, the svm can facilitate the bettering classification and toward high precision classification. future work will combine the vibration signals and motor current signals as new training data through the support vector machine process . acknowledgement this work was supported by most grant 106-2218-e-018-001 for which the authors are very much grateful. references [1] y. chen and j. lee, “methodology for ball screw component health assessment and failure analysis ,” proc. the asme international science and engineering conference, vol. 2, pp. v002t02a031-1v002t02a031-9, 2013. [2] h. shimoda, “stiffness analysis of ball screws-influence of load distribution and manufacturing error,” international journal of the japan society for precision engineering, vol. 33, no. 3, pp. 168-172, november 1999. [3] p. c. tsai, c. c. cheng, and y. c. hwang, “ball screw preload loss detection using ball pass frequency ,” mechanical systems and signal processing, vol. 48, no. 1-2, pp. 77-91, october 2014. [4] c. g. zhou, h. t. feng, z. t. chen, and y. ou, “correlation between preload and no-load drag torque of ball screws,” international journal of machine tools & manufacture, vol. 102, pp. 35-40, march 2016. [5] s. r. gunn, “support vector machines for classification and regression,” univ. of southampton, faculty of engineering, science and mathematics school of electronics and computer science, technical report, may 10, 1998. [6] a. smola and s. v. n. vishwanathan, introduction to machine learning, cambridge university press, 2008. [7] c. cortes and v. m. vapnik, “support-vector networks,” machine learning, vol. 20, no. 3, pp. 273-297, september 1995. [8] s. j. wang, a. mathew, y. chen, l. f. xi, l. ma, and j. lee, “empirical analysis of support vector machine ensemble classifiers,” expert system with applications vol. 36, no. 3, pp. 6466-6476, april 2009. [9] y. c. huang and x. y. chen, “investigation of a ball screw feed drive system based on dynamic modeling for motion control,” advances in technology innovation, vol. 2, no. 2, pp. 29-33, 2017.  advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 computer science and information management, soochow university, taipei, taiwan received 17 march 2019; received in revised form 29 august 2019; accepted 02 october 2019 doi: https://doi.org/10.46604/aiti.2020.819 abstract computer aided geometric design employs mathematical and computational methods for describing geometric objects, such as curves, areas in two dimensions (2d) and surfaces, and solids in 3d. an area can be represented using its boundary curves, and a solid can be represented using its boundary surfaces with intersection curves among these boundary surfaces. in addition, other methods, such as the medial-axis transform, can also be used to represent an area. although most researchers have presented algorithms that find the medial-axis transform from an area, a algorithm using the contrasting approach is proposed; i.e., it finds an area using a medial-axis transform. the medial-axis transform is constructed using discrete points on a curve and referred to as the skeleton of the area. subsequently, using the aforementioned discrete points, medial-axis circles are generated and referred to as the muscles of the area. finally, these medial-axis circles are blended and referred to as the blended boundary curves skin of the area; consequently, the boundary of the area generated is smooth. keywords: medial-axis transform, hermite curve, bezier curve, computer-aided geometric design 1. introduction in the domain of computer-aided geometric design, an area can be represented using various methods, such as via its boundary curves, via its medial-axis transform [1], or via set operations, such as union, intersection, and difference, of numerous primitive geometric objects. to describe a curve or area in two dimensions (2d), researchers attempted to use different curve representations in different applications. for example, cinque, levialdi, and malizia [2] used a cubic bezier curve to describe the shape via its boundary curve with orientation. yang, lu, and lee [3] used a bezier curve to describe the shape of chinese calligraphy characters [4]. chang and yan [5] derived an algorithm to simulate hand-drawn images using a cubic bezier curve. cao and kot [6] derived an algorithm to embed data using electronic inks without the loss of data. furthermore, algorithms were proposed to derive the interior/exterior offset curves and medial axis of an area using the boundary curves [7]. in 3d, surface representations are used to simulate natural objects, such as flowers [8]. in addition, the circle packing problems, i.e., the arrangement of circles with same or different radii inside a specified area, were also investigated by researchers [9-11]. in this study, methods are proposed to grow an area. an area is initialized using two approaches, one with the use of medial-axis circles, and the other via points on a curve. subsequently, the algorithms are proposed to grow the areas using the initialized area. given a cubic bezier curve with n discrete points on it, n circles are attempted to find centered at these n points with different radii, such that the neighboring circles are tangent to each other. this is the initial area that is constructed from a curve that has points on it. next, the area along different directions is grown; the first direction is along the two end points of the curve, as depicted in fig. 1(a); the second direction is along the two sides of the curve, as depicted in fig. 1(b). a single circle is also considered to be an initial area, in this case; the area then grows along different directions, as depicted in fig. 1(c). * corresponding author. e-mail address: chiang@gm.scu.edu.tw tel.: +886-2-23111531 ext. 3801; fax: +886-2-23756878 area-construction algorithms using tangent circles ching-shoei chiang * , hung-chieh li advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 127 the initial area generated by the aforementioned curve is referred to as the skeleton of initial area, this curve is referred to as the skeleton of the initial area and these circles as the muscle of the initial area. the union of all the muscles is referred to as the central muscle of the area. upon extending the area along different directions, the circular arc connecting two tangent circles needs to be blended such that the boundary of the extended area is smooth. the entire process, from skeleton to muscles, and, subsequently, from muscles to skins, leads to the generation of the desired area. the generation of the skeleton and skin is simple. therefore, the extension of the muscles is mainly emphasized. in the first section, the problem is illustrated. in the second section, an algorithm is proposed to generate the central muscles, and in the third section, the extending of the muscles is introduced from one side of the skeleton, or from every direction of a circle muscle. the conclusions are presented in the last section. (a) along two end points of the central muscle (b) along one side of the central muscle (c) along multiple directions of a circle fig. 1 muscle growth 2. generating central muscles consider the following problem. given n distinct ordered points pi, where i = 0, …, n, a set of circles has to be found, ci, whose circles are centered at these points pi, and each circle is tangent to its neighboring circles. in this problem, there are n+1 variables (ri, where i = 0, …, n) with only n constraint equations (li = dist(pi, pi+1), i = 0, …, n–1). therefore, one more constraint equation needs solving the aforementioned problem. the following algorithm can be obtained by inputting the value r0: algorithm 1: 1. input the distinct ordered points, i.e., p0, p1, …, pn. 2. input r0 3. for i in 0, 1, …, n–1: 4. calculate ri+1 = li – ri, where 0 < r0 < l0 although the neighboring circles are tangents to each other, two neighbors of the same circle cannot be ensured that they would not intersect each other. therefore, to avoid the aforementioned intersection, constraints are placed on the radius of each circle using the following theorems: theorem 1: given pi, where i = 0, ..., n, if ci-1 did not intersect ci+1, where i = 1,.., n–1, then ri > (li-1+li-dist(pi+1,pi-1))/2. (see fig. 2) proof: the result is derived directly from the following equation: dist (pi+1, pi-1)> ri-1+ri+1, where ri-1=li-1–ri and ri+1=li–ri. advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 128 theorem 1 is used to calculate the lower bound of the radius of circle centered at pi, and these radii are denoted by mri, where i = 1,…, n–1. notably, li-1+li-dist (pi+1,pi-1)>0 by triangle inequality. consider the case wherein two circles ci = c (pi, mri) and ci+1 = c(pi+1, mri+1) , where i = 1, …, n–2 intersect each other; therefore, it is impossible to find a set of circles that are tangents to each other, i.e., the circles do not intersect each other. therefore, the following example is provided: fig. 2 intersection of two neighboring circles (a) invalid input (b) minimal radius (c) cj-1 is tangent to cj+1 (d) better result fig. 3 circles with different radii example 1: given four points, namely, p0 = (0, 0), p1 = (2, 5), p2 = (4, –5), and p3 = (8, 2). the minimal radius can be calculated, called mri, for p1, p2, and p3 as mr1 = 4.59, mr2 = 5.78, and mr1 + mr2 > l1 = 10.198, respectively (see fig. 3(a)). in this case, irrespective of the values are assigned to r1 and r2, there is always the case wherein c0 intersects c2 or c1 intersects c3. example 2: using the input p0 = (0, 0), p1 = (2, 1), p2 = (4, –1), p3 = (6, 1), and p4 = (8, 0), mr1, mr2, and mr3 are calculated as 0.47, 0.82, and 0.47, respectively, and the circles centred at pi with radius mri are depicted in fig. 3(b). assuming j to be the index of the maximum value of mri, rj = mrj can be set. consequently, other radii are calculated starting from rj, and rj+1, rj+2, …, rn and rj-1, rj-1, …, r0 are also calculated using an approach similar to that used in algorithm 1. accordingly, it yields the following algorithm: algorithm 2: 1. input the distinct ordered points, i.e., p0, p1, …, pn. check whether the input is appropriate for the algorithm. if the input is inappropriate, a new set of points is requested for as the input data. 2. calculate mri, where i = 1, ..., n–1. compute index j for max{mri, where i = 1, …, n–1}. set rj = mrj. 3. from rj, repeat rk+1 = lk – rk for k = j, …, n–1. 4. from rj, repeat rk-1 = lk-1 – rk for k = j, …, 1. in this case, the circles are found with pj as their centers and mrj their radii, where mrj + mrj+1 < lj. a set of radius rk is found, where k=1,2, …, j-1, j+1, …n, such that the circles will not intersect locally (ck-1 and ck are tangent to each other, and cj and ck+1 are also tangent to each other; in addition, ck-1 and ck+1 may be tangent to each other but cannot intersect otherwise). for the case rj = mrj, circle cj-1 will be tangent to cj+1, as depicted in fig. 3(c). advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 129 example 3: using the same input as that used in example 2, r2 = mr2 = 0.82 was fixed and r3 and r4 was calculated to be 2 and 0.24, respectively. in addition, r1 and r0 are equal to 2 and 0.24, respectively, as depicted in fig. 3(c). the radius of cj is increased to avoid c j-1 and cj+1 being tangents to one another, as depicted in fig. 3(c). a “better” chain of circles must be produced, such that all circles ci-1 and ci+1 on the chain are separated locally. the “better” chain of circles may be the case wherein the radii of circles are within a small range. theoretically, to minimize the value of max {ri, i=0, n} – min {ri, i=0, n}. using the algorithm, all mri are calculated, where i = 1, …, n–1, and mci, where mci are the circles centered at pi with radius mri. if mci-1 did not intersect mci+1, where i = 1, …, n–1, a set of ri is found, such that ci is tangent to ci+1 with the property that ci-1 did not intersect ci+1. moreover, rj has both a lower bound, i.e., mrj, and an upper bound, which could be min{dist(pj, pj+1)-rj+1, dist(pj, pj-1)-rj-1}; notably, upon increasing rj, circles mcj-1 and mcj+1 will not intersect each other. the radius was discretized from its lower bound to upper bound and tried each case and, subsequently, produced the “better” chain of circles satisfying the case wherein max{ri, i=0, n} – min{ri, i=0, n} was minimum. therefore, there is the following algorithm can be found: algorithm 3: 1. input the distinct ordered points, i.e., p0, p1, …, pn. check whether the input is appropriate for the algorithm. if the input is not appropriate, ask for a new set of points as the input. 2. calculate mri, where i = 1,.., n–1. compute index j for max{mri, where i=1,.., n–1}. set upper = min{li–mri+1, li-1–mri-1} 3. set m such that it divides r from its lower bound to upper bound into m+1 values. 4. for rj from mrj to its upper bound with step (upper – mrj)/m 4.1 from rj, repeat rk+1 = lk – rk for k = j, …, n–1. 4.2 repeat rk-1 = lk-1 – rk for k = j, …, 1. 4.3 calculate max {rj} – min {rj} for j = 1, …, n–1. memorize k when max {rk} – min {rk} is minimum. example 4: using the same input as that used in example 2 to have the lower and upper bounds for r2 (0.82, 2.36). this range linearly was discretized into 11 different radii and observed that when r2 =1.44, a “better” chain of circles was produced. the result is depicted in fig. 3(d). a sequence of points, p = [p0, p1, …, pn] is used to produce the associated radii for point pi using the above algorithm. p is called the skeleton/bone of the area. the produced circles are referred to as the muscles of the area. if the path that connects these ordered points pi has a sharp angle, it is highly probable that the circles generated using algorithm 3 intersect other circles locally. to avoid the aforementioned situation, skeleton must be constructed using points on bezier or hermite curve. consider the case wherein points lie on a bezier curve b(t), where t is equal to 0, 0.25, 0.5, 0.75, and 1.0. the points are used on the curve as the input for algorithm 3. example 5: consider the bezier curve whose control polygon is denoted by [p0, p1, p2, p3], where p0 = [0, 0], p1 = [2, 6], p2 = [7, –1], and p3 = [9, 3]. the control polygon and bezier curve are depicted using gray line and red curve, respectively, in fig. 4. using algorithm 3, the muscles are calculated to be c(0, 0, 1.969), c(1.969, 2.438, 1.164), c(4.5, 2.25, 1.374), c(7.03, 1.688, 1.219), and c(9.0, 3.0, 1.147), as depicted using green circles in fig. 4. the case is selected wherein the difference between the maximum radius and minimum radius is minimum. notably, the polygon that connects points b(0), b(0.25), b(0.5), b(0.75), and b(1.0) did not have sharp angles, and the values of mri, where i =1, 2, and 3, are considerably small, i.e., 0.32, 0.007, and 0.199, respectively. mc1 and mc3 are depicted as left and right red circles in fig. 4. advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 130 fig. 4 skeleton on bezier curve 3. generating external muscles after generating the central muscles the generation of external muscles is launched. for this, continuous circles that are tangents to one side of the central muscle must be produce, as depicted in fig. 1(b). consider 3 circles c0, c1, and c2, as depicted in fig. 5. a sequence of circles wants finding, such that the following conditions are satisfied: the first circle c0 is tangent to c0 and c1; the last circle cn is tangent to c1 and c2; circle ci between c0 and cn is tangent to c1 and its neighbors ci-1 and ci+1, as depicted in fig. 5(a). fig. 5(b) and fig. 5(c) depicts the cases for n = 0 and n = 1. algorithms are developed for this case in this section. two subcases are considered, the first case wherein circles ci, where i = 0, …, n, have the same radius, and the second case wherein the radii of these circles have the arithmetic progression property. the first case is started from considering the case wherein a circle is tangent to 3 circles, as depicted in fig. 5(a); this case comprises a well-known problem called apollonius’s problem, which has 8 solutions. on the basis of the orientation of circles (a circle oriented clockwise has positive radius, and that oriented counter-clockwise has negative radius), the problem can be simplified by solving a quadratic equation. after solving the equation, two circles are founded, one contains all the three circles, and the other contains none of the three circles. the wanted circle, in this case, is the one that contains none of the three circles. (a) n+1 circles (b) one circle (c) two circles fig. 5 construction of circles along one side for finding a circle that is tangent to the three circles, the problem can be solved algebraically. assume that the three circles have (xi, yi) as their centers and ri as their radii, where i = 1, 2, and 3. the circle centered at (x, y) with radius r is tangent to these three circles. therefore, there are three equations as (x – xi) 2 + (y – yi) 2 = (r – ri) 2 , where i = 0, 1, and 2, with three variables x, y, and r. because each of the aforementioned three equations are of degree two, they should have eight solutions in total. these three equations are referred to as eq0, eq1, and eq2. notably, by performing eq0 – eq1, the terms with degree two are eliminated, and, accordingly, the equation obtained is a linear equation. the system of equation can be simplified {eqn0, eqn1, eqn2} into {eqn0, eqn0 – eqn1, eqn0 – eqn2}, where the new system of equation is of degrees two, one, and one, respectively; therefore, the number of solutions becomes two. in the algorithm, the binary approach is used to find the radius of the tangent circle. this algorithm is introduced because it can be easily extended to the case with more circles, as depicted in fig. 5(b) and 5(c). before the algorithm, there are the following theorems. theorem 2: three circles are tangent to each other, and their radii are x, y, and z. furthermore, the angle  of the triangle that is formed by connecting their centers has the opposite side of length y + z, as depicted in fig. 6(a). then: advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 131 2 2 cos( ) x xy xz yz a x xy xz yz        (1) proof: the result is derived directly from the cosine theorem, that is, (y + z) 2 = (x + y) 2 + (x + z) 2 – 2(x + y)(x + z)cos(). using the equation in theorem 2, there are four variables, namely, x, y, z, and , with one equation. given any three variables, the fourth one can be calculated. assume that there are two circles with radii x and y, and angle . accordingly, radius z can be calculated. besides, if x and y are known, and assumed radius z,  can be calculated as well. (a) one circle tangent to two circles (b) one circle tangent to three circles fig. 6 relation between radii and angles now, consider 3 circles ci, where i = 0, 1, and 2. assume that c0 is tangent to c1 and that c1 is tangent to c2. in addition, assume that the circle that is tangent to c0, c1, and c2 has radius r. from this assumption and considering fig. 6(b), angles 1 and 2 can be calculated using the equation in theorem 2, and, subsequently, their sum is compared with the angle between vectors p0 – p1 and p2 – p1. if the sum is less than the angle between the vectors, radius r enlarged, and if the sum is greater than the angle between the vectors, radius r reduced, until the solution is found within a tolerance. this aforementioned idea can be implemented using the following algorithm: algorithm 4: 1. input three circles c0, c1, and c2. #assume that c0 is tangent to c1 and that c1 is tangent to c2. 2. calculate the angle between vectors p0-p1 and p2-p1, and refer to it as . 3. set r, rmin, and rmax as 1, 0, and 999, respectively. 4. set eps = 0.001 5. calculate angles 1 and 2 using the assumed radius r. 6. while |1 + 2 – | > eps: if 1 + 2 > : rmax = r r = (rmax + rmin)/2 else: rmin = r r = (rmax + rmin)/2 7. display the result. advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 132 example 5: consider three circles c0 (–4, 3, 3), c1 (0, 0, 2), and c2 (4, 0, 2). notably, c0 is tangent to c1 and c1 is tangent to c2. circle c0 (2, 6.60, 4.90) is found, as depicted in fig. 7(a). now consider the case wherein n+1 circles want adding. in this case, the first circle c0 is tangent to c0 and c1; the last circle cn is tangent to c1 and c2; circle ci between c0 and cn is tangent to both c1 and its neighbors ci-1 and ci+1, as depicted in fig. 5(c). a similar idea as that for algorithm 4 can be applied. in algorithm 4, the sum of two angles, 1 and 2, are compared with angle , and now the sum of n + 2 angles is compared with angle . it is referred to as the extended algorithm 4. example 6: using the same input as that used in example 5, 2 circles that are tangent to each other want finding, where the first circle is tangent to c0 and c1 and the second circle is tangent to c1 and c2. using the extended algorithm 4, these two circles are found centered at (0.047, 3.045) and (2, 2, 97) each of radius r = 1.046, as depicted in fig. 7(b). example 7: given three circles c0 (–4, –3, 3), c1 (0, 0, 2), and c2 (4, 0, 2). using the extended algorithm 4, 5 circles are found between c0 and c2, such that these 5 circles are tangent to c1. the circles are found centered at (–2.697, 0.513), (– 2.031, 1.846), (–0.767, 2.636), (0.723, 2.648), and (2.0, 1.88) each of radius 0.745, as depicted in fig. 7(c). (a) one circle (b) two circles (c) five circles fig. 7 tangent circles with similar radii (a) 2 circles with dr = 0.5 (b) 5 circles with dr = 0.2 (c) 5 circles with dr = 0.25 fig. 8 tangent circles with different radii let people consider the case wherein the radii of the circles along one side of initial area are in an arithmetic progression. assume that dr is the common difference. accordingly, the first circle has radius r; the second circle has radius r – dr; the third circle has radius r – 2*dr, …, and so on. using the binary approach as that employed in algorithm 4, to find 2 or 5 tangent circles, examples 8 and 9 are referred to as depicted in fig. 8(a) and (b), respectively. example 8: using the same input data as those used in example 5 and setting dr = 0.5, two circles are found: c0 (0.31, 3.31, 1.32) and c1 (2.0, 1.99, 0.82), as depicted in fig. 8(a). example 9: using the same input data as those used in example 7 and setting dr = 0.2, 5 circles are found: c0 (–3.03, 1.09, 1.22), c1 (–1.43, 2.66, 1.02), c2 (0.41, 2.79, 0.82), c3 (1.64, 2.04, 0.62), and c4 (2.14, 1.13, 0.42), as depicted in fig. 8(b). upon increasing dr, the difference between the radii of c0 and c4 is also increased. the difference can be seen in radii by comparing fig. 8(c), where dr = 0.25, with fig. 8(b), where dr = 0.2. now, consider the case wherein the external muscle/circle grows along every direction of a muscle/circle, as depicted in figs. 1(c) and fig. 9. in this case, a list of angles is needed; the list indicates the direction along which new circles want advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 133 extending. the extension might have no solution. consider a unit circle centered at the origin, with the list of angles, alist, where the first element in alist is 0. other cases can be converted into this situation by translating, rotating, and scaling the circles in the problem. with this initial condition, it yields the following algorithm: fig. 9 growth direction of circles algorithm 5: (eps is a considerably small number) 1. input c(0,0,1) and a list of angles, alist. the length of alist denotes len(alist) 2. assume the initial radius of the first circle along the x+ axis, and refer to it as r0. 3. calculate r1 using the equation in theorem 2 with the angle data provided by alist. continue this process until all r i, where i = 1, 2, …, len(alist) – 1 have been calculated. 4. calculate the sum of the angles between the angle generated by connecting the center of three circles as c0cc1, c1cc2, …, cncc0, and refer to it as rsum. 5. while abs(rsum – 2)>eps: if rsum > 2: reduce the assumed radius r0 else: increase the assumed radius r0. example 10: assuming the input as alist=[0, 90, 180, 270], the four circles obtained are c(4, 0, 3), c(0,3,2), c(–4, 0,3), and c(0, –3, 2), as depicted in fig. 10(a). notably, the radii of these circles are not the same, although their directions of extension are east, north, west, and south, respectively. there are more than one solution, and the algorithm finds an appropriate one. (a) four directions (b) five directions fig. 10 grow external muscle example 11: assuming the input as alist=[0, 72, 144, 216, 288], the five circles obtained are c(2.5, 0, 1.5), c(0.73, 2.42, 1.36), c(–2.02, 1.47, 1.5), c(–1.91, –1.39, 1.36), and c(0.77, –2.38, 1.5). to generate skin to wrap an area, such as the area in figs. (7)-(10), the interior and exterior circle muscles must be identified. for two exterior muscles tangents to one another, the skin to connect these two circles can be easily produced. a advances in technology innovation, vol. 5, no. 2, 2020, pp. 126-134 134 circular arc is an appropriate choice to blend these two circles, provided the radii of the circles contain the circular arc. using the chosen radius, both the center of the circle and the start/end angle of the circular arc can be easily obtained. 4. conclusion and future research tangency among circles has numerous important applications, such as in packing problems. although most researchers concentrate on finding circles inside an area, a contrasting approach is employed by constructing the area inside out, from a 1d curve (skeleton) to 2d area (union of circles/muscles), in order to ensure a smooth boundary area (g 1 -continuity boundary curve). the algorithm used to extend the area is based on the binary approach, and it can be easily used for growing areas. future research will emphasize on the design of area-growth directions. for example, the area generated from piecewise cubic bezier curve, so that the whole area is extended to produce an elongated area, certain data structures, such as medial-axis transforms, can be easily generated. the other example is to automatically grow an area to approach a bounded one. acknowledgment this work was supported in part by the national science council in taiwan under grant most 104-2221e-031-005. conflicts of interest the authors declare no conflict of interest. references [1] c. s. chiang, “the medial axis transform of the region defined by circles and hermit curve,” international conference on computer science and engineering (iccse), july 22-24 2015. [2] l. cinque, s. levialdi, and a. malizia, “shape description using cubic polynomial bezier curves,” pattern recognition letters, vol. 19, pp. 821-828, 1998. [3] h. m. yang, j. j. lu, and h. j. lee, “a bezier curve-based approach to shape description for chinese calligraphy characters,” proceedings of the sixth international conference on document analysis and recognition, pp. 276-280, 2001. [4] c. s. chiang and l. y. hsu, “describing the edge contour of chinese calligraphy with circle and cubic hermite curve,” 2013 computer graphics workshop, july 2013. [5] h. h. chang and h. yan, “vectorization of hand-drawn image using piecewise cubic bezier curves fitting,” pattern recognition, vol. 31, no. 11, pp. 1747-1755, 1998. [6] h. cao and a. c. kot, “lossless data embedding in electronic inks,” ieee transactions on information forensics and security, vol. 5, no. 2, pp. 314-323, 2010. [7] l. cao, z. jia, and j. liu, “computation of medial axis and offset curves of curved boundaries in planar domains based on the cesaro’s approach,” computer aided geometric design, vol. 26, no. 4, pp. 444-454, 2009. [8] p. qin and c. chen, “simulation model of flower using the integration of l-systems with bezier surfaces,” international journal of computer science and network security, vol. 6, no. 2, pp. 65-68, 2006. [9] g. l. orick, k. stephenson, and c. collins, “a linearized circle packing algorithm,” computational geometry 64, pp. 13-29, 2017. [10] o. angel, t. hutchcroft, a. nachmias, and g. ray, “unimodular hyperbolic triangulations: circle packing and random walk,” inventiones mathematicae 206.1, pp. 229-268, 2016. [11] k. e. stange, “the sensual apollonian circle packing,” expositiones mathematicae 34.4, pp. 364-395, 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 energy-effective predictive temperature control for soy mash fermentation based on compartmental pharmacokinetic modelling sophia ferng1, ching-hua ting2,*, chien-ping wu2, yung-tsong lu3, cheng-kuang hsu1, robin yih-yuan chiou1 1 department of food science, national chiayi university, chiayi, taiwan, roc. 2 department of mechanical and energy engineering, national chiayi university, chiayi, taiwan, roc. 3 department of biomechatronic engineering, national chiayi university, chiayi, taiwan, roc. received 07 june 2017; received in revised form 05 september 2017; accepted 02 october 2017 abstract compartment modelling has been successfully used in pharmacokinetics to describe the kinetics of drug distribution in body tissues. in this study, the technique is adopted to describe the dynamics of temperature response and energy exchange in a soy mash fermentation system. the object ive is to provide a precise temperature-controlled atmosphere for effect ive fermentation with the premise of energy saving. in analogy to pharmacokinetics, water and mash tanks are treated as compartments, energy flow as drug delivery, and the temperature as the drug concentration in a specific compartment. the model allows us to estimate the time of injecting a certain amount of energy to a specific tank (compartment) in a cost-effective way. thus, model-based temperature control and energy management can be possible. keywords: soy mash fermentation, temperature, predictive control, energy-effective, compartment model 1. introduction soy sauce was invented by the chinese about 3500 years ago, and the modern producing technology was developed by the japanese about 500 years ago. the production consists of solid -state fermentation, mash fermentation, and flavouring. the quality and cost of a soy sauce product are mainly determined by the mash fermentation stage. in tradit ion, soy mash is placed in a pottery tank which is exposed to sunshine for 4~12 months. the duration of exposure under the sun is season-dependent as the enzyme and the microbes in the mash are sensible to temperature variations [1-4]. despite the cost raised by a longer fermentation time and more manpower, tradit ional soy sauces still deserve of popularity as their special flavours are superior to cheap, chemical ones. because the mash fermentation is manipulated outdoors, the processes of fermentation are easily affected by the climate, and the mash is vulnerable to alien contamination [5]. this may lead to a produce with unstable quality and alien contamination. to overcome this problem, we moved the fermentation from outdoors to indoors and controlled the fermentation climate [5], as shown in fig. 1. in the system, the pottery containing soy mash is bathed in a water tank and the temperature of the batching water is regulated to meet the requirements of various fermentation stages [5-6]. it has been demonstrated that a controlled fermentation climate can create a well environment fo r the enzymes and microbes participating in mash fermentation [7-8]. thus, the produce can arrive at a better quality in a shorter time in comparison with the traditional approach [9]. * corresponding author. e-mail address: cting@mail.ncyu.edu.tw tel.: +886-5-2717642; fax: +886-5-2717561 advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 71 fig. 1 setup of the energy-saving soy sauce fermentation system [5]. as fig. 1 illustrates, the system consists of a heat pump which supplies hot water circulation fo r regulat ing the fermenter with desired temperature settings. the system is controlled with a programmable logic controller (plc) and supervised with an industrial personal computer (ipc). the current principle of operation is to let the heat pump work at noontime for the benefit of a better operational efficiency and the hot water produce is stored in a storage tank for later use, usually in night time . the plc manipulates the solenoid valves and the circulation pump once the temperature of the mash is below a certain level. these two solenoid valves assure correct water flow directions. hot water will circulate for 3 min for adequate heat injection into the soy mash. the duration was determined through experimental studies via trial-and-error. fig. 2 demonstrates the temperature profiles of the soy mash, the atmosphere, and the circu lation water. clearly, the mash can ferment at an environment with a more stable temperature regardless of a vary ing atmospheric climate. though, the temperature variation in the fermenter has been improved to be with in 1°c, much improved regardless of vary ing climate, it still fluctuates as a result of simple on/off control using solenoid valves. (a) temperature responses of the traditional procedure (b) temperature responses of on/off control fig. 2 the temperature profiles of the soy mash, the atmosphere, and the water in the bathing tank the price of electricity is different between peak and off-peak times. the heat pump has a maximum efficiency at noontime. however, the demand of hot water circulation is usually in night time, several hours after the hot water preparation. the stored hot water will inevitably lose some heat to the space before being consumed. there should be an optimum time of operat ing the heat pump in term of electricity cost [10-12]. it would be possible to operate the heat pump at a most cost-effective way if we can determine when hot water circulation is demanded. the objective of this study is to develop a temperature and energy prediction model using the compartment modelling technique which has been successfully used in pharmacology for drug administration [13]. as the system described in fig. 1, we can partition the system into several unique compartments and describe mathematically the energy exchanges among the advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 72 compartments. in analogy to pharmacokinetics, the water storage tanks and the fermentation tanks are treated as compartments, energy exchange among tanks and the atmosphere as drug delivery, the temperature as drug concentration, electrical energy injected into the heat pump can be treated as a dose input. we can estimate energy flows, temperatures responses, and hence, electricity consumption. based on this, we can determine the best time of heat pump operation and control the time and duration of hot water circulat ion using simple and cheap solenoid valves. hence, the profit can be promoted as a result of better and efficient fermentation without too much of energy consumption and therefore , secured environmental affect. accordingly, a compromise can be arrived at among economy, ecology, and energy (3e). 2. materials and methods 2.1. compartment modelling fig. 3 illustrates the proposed compartment model. the heat pump is identified as an energy supply to the hot water circulat ion system. the soy mash pot (compartment 2) is bathed in hot water (compartment 1). there is heat exchange in between. compartment 1 will inevitably loss heat to the atmosphere. compartment 3 stores hot water produce from the heat pump. heat energy is supplied from compartment 3 to compartment 1 via water circulation. cooled water is to be circulated back to compartment 3 from compartment 1. compartment 1 is equipped with a well-designed stirrer that mixes incoming hot water and the existing cool water efficiently. in other word, energy is in jected into compartment 1 as a dose bolus rather than via heat transfer. thus, there is no 𝑘31 and 𝑘13 correlation in between. to simplify the problem, the storage tank (compartment 3) is treated as an infinite tank comparing to compartment 1. since the hot water storage tank is well insulated, no-heat-loss is assumed, ie. 𝑘30 = 0 . eq. (1) describes the dynamics of energy transfer based on the compartmental model; where 𝑇1 is the temperature o f compartment 1, 𝑇2 is the temperature of compartment 2, and r(t) is the injected energy dose:    1 10 12 1 21 2 2 12 1 21 2 dt r t k k t k t dx dt k t k t dx               (1) 𝑘12：the transfer constant of heat in circulation water transfer to soy mash (𝑠−1) 𝑘21：the transfer constant of heat in soy mash transfer to circulation water (𝑠−1) 𝑘10：the transfer constant of heat in circulation water dissipate into the air (𝑠−1) 𝑘30：the transfer constant of heat in storage water dissipate into the air (𝑠−1) fig. 3 the proposed compartment model 2.2. determination of system parameters fig. 4 shows the experimental setup for determin ing the k coefficients. tanks were filled with water of different temperatures and hence, energy flowed from high temperature to low temperature sites. temperature responses were recorded every 10 min till thermodynamic equilibrium. acquired data were fitted to first-order equations using the matlab curve fitting toolbox. advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 73 (a) for 𝑘12 (b) for 𝑘21 (c) for 𝑘10 fig. 4 experimental setups for determining the k coefficients other parameters to be determined are the volume of the circulat ion water, the volume of the soy mash and the hot water circulation time. 2.3. energy consumption cost function the heat pump extracts energy from the air to heat up water. the ambient temperature is the key factor that influences the efficiency of heat pump operation [11]. the higher the ambient temperature is, the higher the heat pump efficiency. hence to operate the heat pump at noontime will have the maximum operational efficiency. however, the noontime is categorized as a peak t ime in electricity pricing, ie. the p rice of electricity is h igher than other times. the mash fermentation tank will have a lower temperature at n ight time and therefore, the hot water prepared at noontime is not used for several hours. in other word, the hot water produced by the heat pump at noontime will loss a big amount of energy to the atmosphere. thus, it may be more profitable by operating the heat pump away from noontime as a compromise among electricity price, heat pump efficiency, and energy loss. accordingly, an energy consumption cost function is to be developed to account for the efficiency of the heat pump, the electricity pricing policy, and the heat loss of the hot water storage tank. 3. results and discussion 3.1. system parameters temperature responses were acquired with a sampling period of 10 min for 6 h which is long enough for the system to reach thermodynamic equilibrium. the acquired data are fitted to a first-order equation using the matlab curve fitting toolbox. fig. 5 shows the temperature responses. (a) for 𝑘12 (b) for 𝑘21 (c) for 𝑘10 fig. 5 temperature responses for determining the compartment-model coefficients fig. 5(a) is the temperature profile for 𝑘12 and can be described as: 𝑇 = 5.727𝑒 −𝑡 7.143⁄ + 39.37 °c (2) with a t ime resolution of 10 min (600 s). the t ime constant is 7.143 × 600 = 4285.8 s and its reciprocal gives 𝑘12 = 2.33 × 10−4 𝑠−1. advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 74 fig. 5(b) is the temperature profile for 𝑘21 and can be described as: 𝑇 = 9.86𝑒−𝑡 5.821⁄ + 36.52 °c (3) the time constant is 5.821 × 600 = 3492.6 s and its reciprocal gives 𝑘12 = 2.86 × 10−4 𝑠−1. fig. 5(c) is the temperature profile for k 10. the bathing tank is cladded with a good insulation material. hence as the profile shows, this is a very slow heat transfer system. it took 11 days to reach thermodynamic equilibrium and resulted in 1716 record ings. these data are down-sampled with a factor of 50. the profile can be described with first -order dynamics, as: 𝑇 = 18.85𝑒 −𝑡 8.523⁄ + 28.81 °c (4) the new sampling period is 60 × 10 × 50 = 3 × 104 s , the time constant is 8.523 × 30000 = 255690 s , and the coefficient is 𝑘10 = 3.91 × 10−6 𝑠−1. 3.1.1. other constants compartment 1 has a space of 220 litres for circulat ion water and compartment 2 accommodates 160 litres of soy mash. 3.1.2. thermodynamics of the circulation water the purpose of water circulat ion control is to regulate the temperature of the soy mash in compartment 2 through controlling the heat in jected into compartment 1. fig. 6 illustrates the conceptual thermodynamics of the two compartments. compartment 1 has a water d istributor designed to mix the incoming water with the existing one in an effective way. hence the two media are assumed to mix instantaneously. the first law of thermodynamics describes the heat balance of the thermodynamic system, as: 𝑄𝑖𝑛 + 𝑄𝑜𝑟𝑖𝑔𝑖𝑛 − 𝑄𝑜𝑢𝑡 = 𝑄𝑓𝑖𝑛𝑎𝑙 (5) fig. 6 heat balance in the batching tank substituting 𝑄 = 𝑚 × ℎ𝑓 to eq. (4) and discretizing give, �̇�ℎ × ∆𝑡 × ℎ𝑓 (𝑇ℎ ) + 𝑚𝑏 × ℎ𝑓 (𝑇𝑏,𝑘−1) − �̇�ℎ × ∆𝑡 × ℎ𝑓 (𝑇𝑏,𝑘−1) = 𝑚𝑏 × ℎ𝑓 (𝑇𝑏,𝑘 ) (6) with �̇�ℎ the circulating water flow rate, ℎ𝑓 the enthalpy of water at a specific temperature, 𝑚𝑏 the mass of the bathing water, 𝑇ℎ the temperature of the incoming hot water, 𝑇𝑏 the temperature of the bathing water, ∆𝑡 the heating duration, and k the time stamp. the enthalpy can be approximated with the specific heat, ie. ℎ𝑓 ≅ 𝐶𝑝 × 𝑇 , hence eq. (6) can be rewritten as: �̇�ℎ × ∆𝑡 × 𝐶𝑝 × 𝑇ℎ + 𝑚𝑏 × 𝐶𝑝 × 𝑇𝑏,𝑘−1 − �̇�ℎ × ∆𝑡 × 𝐶𝑝 × 𝑇𝑏,𝑘−1 = 𝑚𝑏 × 𝐶𝑝 × 𝑇𝑏,𝑘 (7) rearranging the above gives the temperature response: 𝑇𝑏 ,𝑘 − 𝑇𝑏,𝑘−1 = ∆𝑇𝑏 = �̇�ℎ×∆𝑡 𝑚𝑏 (𝑇ℎ − 𝑇𝑏,𝑘−1) (8) the following values are used for simulation validation: �̇�ℎ = 10kg/min, ∆𝑡 = 3 min, 𝑚𝑏 = 220 kg, 𝑇ℎ = 47℃ . the water storage tank (compartment 3) has a capacity of 1500 lit res and only 30 litres are demanded for the circulat ion. advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 75 hence it is reasonable to assume a constant 𝑇ℎ . the initial temperature of the bathing water 𝑇𝑏,k−1 is assumed as 36.8°c. substituting the above values into eq. (8) results in ∆𝑇𝑏 = 1.39°c , ie. a 3-min heat in jection heats up the bathing water by 1.39°c . this information will be used in compartment modelling. 3.1.3. validation the compartment model of fig. 3 was validated using the matlab simbiology toolbox using the parameters identified in section 3. fig. 7 shows simulation and actual responses . there is a strong degree of coherence in between. this promising result indicates that the proposed compartment model can effectively describes the energy flows of the fermentation system. fig. 7 simulation and actual responses it is clear that the t iming of operating the heat pump is the key issue of saving energy cost for the fermentation system. the timing should account for the operational efficiency, electricity pricing, and heat losses from tanks. thus, the above three factors are transcribed as an energy cost function: minimising the function for the least energy bill. in this study, the heat pump was set to produce hot water at 47℃. the energy for 1 litre of hot water produce is: 𝑄 = 𝑚 × 𝐶𝑝 × ∆𝑇 = 1 × 4.2 × (47 − 𝑇𝑡 ) = 197.4 − 4.2 𝑇𝑡 (9) with 𝑇𝑡 the temperature of the water in the storage tank, which can be estimated using the compartment model . the performance of a heat pump is described with the so-called coefficient of performance (cop). it is a ratio of the heat generated, q, by the heat pump to the energy consumed, w, by the heat pump [14], as: 𝐶𝑂𝑃 = 𝑄 𝑊 (10) the work done by the heat-pump compressor is: 𝑊 = 𝑄 𝐶𝑂𝑃 = 197.4−4.2 𝑇𝑡 𝐶𝑂𝑃 𝑘𝐽 (11) the cop coefficient is sensitive to the ambient temperature 𝑇𝑎 . table 1 lists the cops of the heat pump (chp-80y, sun tech, taiwan). the hotter the ambient is, the larger the cop. table 1 cops of the heat pump at different ambient temperatures ambient (°m) -20 -15 -10 -5 0 2 7 10 16 20 25 30 35 43 cop 2.2 2.4 2.6 2.5 2.6 2.8 3.7 4.0 4.2 4.3 4.4 4.5 4.4 4.3 advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 76 the compressor of the heat pump is assumed to have an efficiency η=0.9. the work demanded by the heat pump to produce 1 litre of hot water is: 𝑊𝑖 = 𝑊 𝜂 = 197.4 − 4.2 𝑇𝑡 𝐶𝑂𝑃 ÷ 0.9 = 219.33 − 4.67 𝑇𝑡 𝐶𝑂𝑃 kj (12) or in kwh, as: 𝑊𝑖 = 219.33 − 4.67 𝑇𝑡 𝐶𝑂𝑃 ÷ (3.6 × 103 ) = 0.060925 − 0.001297 𝑇𝑡 𝐶𝑂𝑃 𝐾𝑊𝐻 (13) the cost c, in ntd, that the heat pump take to produce 1 litre of hot water is: 𝐶 = 𝐸 𝐶𝑂𝑃 (0.060925 − 0.001297 𝑇𝑡 ) (14) where e is the price of unit kwh in ntd/kw h, a value varies at peak and off-peak times. table 2 shows the pricing policy of taiwan power company (tpc). the above cost function is a function of the time of heat pump operation (transcribed as cop and e) and heat losses from the storage tanks (transcribed as 𝑇𝑡). table 2 pricing policy of taiwan power company 4. conclusions we have built a compartment model for describing temperature response, heat exchange, and energy demand of a soy mash fermentation system. there is a strong coherence between simulat ion and actual results. simulation results show that the model can accurately predict the trend of temperature response. thus, our next work is to implement model -based predictive temperature control based on the developed compartment model. this will g ive a more precise temperature control. the model also describes the heat exchange, or energy flow, between tanks (compartments). this feature allows us to estimate the optimum t ime of running the heat pump. hence we can arrive at a p romising temperature control with an economic electricity bill. acknowledgements this work was sponsored by the ministry of science and technology of the roc (taiwan) government under the grant most 105-2221-e-415-030, and by the research center for energy technology and strategy of national chengkung university, taiwan, roc. references [1] n. w. su, m. l. wang, k. f. kwok, and m. h. lee, “effects of temperature and sodium chloride concentration on the activities of proteases and amylases in soy sauce koji,” journal of agricultural and food chemistry, vol. 53, no. 5, pp. 1521-1525, march 2005. [2] y. zhu and j. tramper, “koji: where east meets west in fermentation,” biotechnology advances, vol. 31, no. 8, pp. 1448-1457, december 2013. summertime non-summertime peak time 07:30~22:30 3.24 3.18 00:00~07:30 22:30~24:00 00:00~07:30 22:30~24:00 sun and off-peak day mon~fri sat 2.06 1.39 1.33 all day 1.39 1.33 off-peak time off-peak time half-peak time 07:30~22:30 1.39 1.33 2.14 off-peak time advances in technology innovation, vol. 3, no. 2, 2018, pp. 70 77 copyright © taeti 77 [3] j. s. lee, s. j. rho, y. w. kim, k. w. lee, and h. g. lee, “evaluation of biological activities of the short -term fermented soybean extract,” food science and biotechnology, vol. 22, no. 4, pp. 973-978, august 2013. [4] c. cui, m. zhao, d. li, h. zhao, and w. sun, “biochemical changes of traditional chinese -type soy sauce produced in four seasons during processing,” cyta journal of food, vol. 12, no. 2, pp. 166-175, october 2014. [5] s. h. ferng, c. p. wu, y. t. lu, w. h. huang, t. c. lin, c. k. hsu, j. s. ju, and c. h. ting, “automatic control of soy mash fermentation for performance promotion using green energy with energy conservation,” the 8th international symp. machinery and mechatronics for agriculture and biosystems engineering (ismab), niigata, japan, may 2016. [6] t. r. chen, and r. y. y. chiou, “microbial and compositional changes of inyu (black soybean sauce) broth during fermentation under various temperature conditions ,” journal of the chinese agricultural chemical society, vol. 34, no. 2, pp. 157-164, 1995. [7] x. gao, c. cui, h. zhao, m. zhao, l. yang, and j. ren, “changes in volatile aroma compounds of traditional chinese-type soy sauce during moromi fermentation and heat treatment,” food science and biotechnology, vol. 19, no. 4, pp. 889-898, 2010. [8] n. w. su, m. l. wang, k. f. kwok, and m. h. lee, “effects of temperature and sodium chloride concentration on the activities of proteases and amylases in soy sauce koji,” journal of agricultural and food chemistry, vol. 53, pp. 1521-1525, august 2005. [9] n. x. hoang, s. ferng, c. h. ting, w. h. huang, r. y. y. chiou, and c. k. hsu, “optimizing the initial moromi fermentation conditions to improve the quality of soy sauce,” lwt food science and technology, vol. 74, pp. 242-250, december 2016. [10] t. olsson, “evaluating machine learning for predicting next-day hot water production of a heat pump,” 2013 fourth international conf. power engineering, energy and electrical drives (powereng), may 2013. [11] j. cummings and c. withers, “energy savings and peak demand reduction of a seer 21 heat pump vs. a seer 13 heat pump with attic and indoor duct systems,” us department of energy, march 2014. [12] m. kassai, “a developed method for energy saving prediction of heat -and energy recovery units ,” energy procedia, vol. 85, pp. 311-319, january 2016. [13] w. b. runciman and r. n. upton, anaesthetic pharmacology review: pharmacokinetics , castle house publications, 1994. [14] c. m. faye, d. p. jerald, d. s. jeffrey, heating, ventilating, and air conditioning: analysis and design, 6th ed. john wiley & sons, 2004.  advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 a study on aluminum pad large deformation during copper wirebonding for high power ic package hsiang-chen hsu1,2,*, shaw-yuan wang1, and li-ming chu3,4 1 department of mechanical and automation engineering, i-shou university, kaohsiung, taiwan, roc. 2 department of industrial management, i-shou university, kaohsiung, taiwan, roc. 3 interdisciplinary program of green and information technology, national taitung university, taitung, taiwan, roc. 4 department of applied science, national taitung university, taitung, taiwan, roc. received 21 july 2017; received in revised form 09 september 2017; accepted 13 september 2017 abstract in this paper, a 3-d finite element prediction on aluminum pad squeeze during the copper wire bonding process for high power ic package is presented. ansys parametric design language (apdl) has been implemented on modelling, mesh density, boundary condition (bc), impact stage and contact mode for the first bond process. the ansys/ls-dyna solver is applied to solve dynamics and ls-prepost is used to observe the predicted large plastic deformation on bond pad and stress on microstructure under pad. in view of high power ic package, larger diameter of copper wire is required for electric loading for its low cost. in this research, a large diameter of 2 mil (50 um) uncoated pure copper (4n) wire is applied to simulate first bond impact-contact process. as the scale double enlarged, the problems encountered in simulation are usually evident. preliminary results on impact stage demonstrate that ne gative volume/hourglass on large distortion can be solved by tune-up inertial contact settings and mesh density. however, sever hourglass defect would occur on ultrasonic stage and remain a pending problem. a series of prediction has been conducted on the first bond process during impact stage and the results can then be applied to the dynamic wirebonding assembly process . keywords: copper wirebonding, large plastic deformation, impact-contact, hourglass defect 1. introduction although several advanced interconnection techniques have been developed recently [1-3], the wire bonding process is still widely used in semiconductor packaging industries for its easy application and low cost. thermosonic bonding (t/s bonding) technique [4] has shown better reliability and good interconnection among all wirebonding processes. the 4n (99.99%) thin gold wire (1mil diameter) is commonly used in wirebonding process because it has mechanically good elongation and electrically low resistivity [5]. bonding wire usually divided into three different zones, namely free air ball (fab), haz (heat affected zone) and as-drawn wire due to the effect of efo (electric flame-off). the material behavior of three zones in gold wire has been fully investigated by many earlier works [5-6]. however, elastic modulus (e) and poisson’s ratio (υ) at leveled working temperature for fab and haz on gold wire as well as cu wire are still scarcely known. the micro -vickers indentation test was applied to obtain the vickers hardness (hv) and then transfer to ultimate tensile stress (uts). while the surface tensile strength can be determined by nano-indentation test. the thermo-tensile mechanical attributes were measured by our self-designed pull test fixture. * corresponding author. e-mail address: hchsu@isu.edu.tw advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 52 as the price of gold (au) increases, the subs titute material was focused on pd-coated cu wire or bare cu wire just for cost down. the aluminum (al) pad has been replaced by al-cu pad in accordance with cu material property in the wire bonding process. it is also an excellent replacement for au wire due to its similar electrical properties. self inductance and self capacitance are nearly the same for au and cu wire. however, the higher rigidity and more hardness [6-7] results in easily squeeze out the bond pad around the smashed ball, as shown in fig. 1. another issue is more bonding power and higher working temperature required in cu wire bonding process. the dielectric material in circuit under pad (cup) for wafer technology node (<60 nm) is low-k material and for wafer technology node (<28 nm) is ultra low-k material. because the low-k/ultra low-k material (nano-porous silicon oxide) is brittle, copper wirebonding process easily damaged the inter-metal dielectric (imd) layer, which is demonstrated in fig. 2. fig. 1 large deformation and squeeze out bond pad near ball bond [8] fig. 2 micro cracks occurred in imd layer beneath the bond pad [8] another advantage of cu wire is lower resistivity. hence, cu wire is a very common interconnected media used for high power transmission. although ultra-thin diameter of wire (0.8 mil (20 m)) has been applied to asic ic or memory ic, large diameter of copper wire (2 mil (50 m)) is still used on high power ic. size effects for larger diameter are visible. reliability on bond pad squeeze and cup micro-crack are much more overt. these attract many researchers and scholar attention on copper wire high power ic package. because the complete mechanism of the wire bonding process includes z-motion, impact and ultrasonic vibration stages [9-10], many material properties of bond wire were scarcely realized. the wirebonding is therefore essentially difficult to simulate by numerical approach. few papers [11-12] published the reliability of wirebonding process using finite element analysis (fea) software ansys/ls-dyna. however, some of the bonding material data in these papers were numerical assumption. with sufficient experimental material properties obtained in this research, both 2d and 3d fea models were developed to predict the dynamic response of the wire bonding process. 2. experimental works tensile mechanical properties of thin 4n au wire and cu wire before/after efo (electrical flame-off) have been investigated by self-design pull test fixture. microstructure characteristics of fab and haz are also carefully examined. the mechanical tensile properties for such ultra-thin wire are difficultly evaluated in traditional pull test. hence, microtensile tests have been carried out by employing the instron-3365 universal test system with 5n±0.5% load cell and self-designed pull test fixtures. thermal effects (25, 125 and 200 o c) on material properties are taken into account. the chamber needs to be specially processed with nitrogen gas to avoid oxidization for cu wire. it has been reported that the plastic behavior and fracture will occur in the haz area when external loading is applied. it is , therefore, clear that the breakage sites of efo wire are in the neck somewhere between haz and fab. fig. 3 schematically illustrates the self-designed pull test fixtures for the haz. advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 53 fig. 3 self-designed tensile test fixtures for the neck (haz) 2.1. micro mechanical tensile test fig. 4 and fig. 5 show the temperature effects on stress -strain curves for as-drawn and efo bare cu wire. fig. 4 micro-tensile mechanical properties at different temperature for as-drawn bare cu wire fig. 5 micro-tensile mechanical properties at different temperature for efo bare cu wire true stress-strain ( t t ) relationships from plastic deformation to necking can be evaluated from engineering stress-strain curves ( - ). by power law in eq. (1), n tt k  (1) where n is the hardening index and k is the coefficient of strength. the value of hardening index is 10  n which is shown to be a key factor for fea simulation. taking logarithm on both sides tt nk  logloglog  (2)         d d d d n ij ij     )log()log( )log()log( )(log )(log (3) for strain-rate effect, m t k    (4)                                            12 12 12 12 ,, log log loglog loglog log log ln ln              ttttttm (5) advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 54 from the above figures, true stress -strain mechanical properties in this study is listed in table 1, where e is young’s modulus, y is yield strength, ts is tensile strength and f is failure strain. from equation (2), hardening index n and coefficient of strength k can be quickly determined as 408 mpa. table 1 true stress-strain mechanical properties material density (g/cm 3 ) poisson’s ratio young’s modulus(gpa) yield stress (mpa) tangent modulus (gpa) elongation (%) n copper ball (200℃) 19.3 0.43 30 110 0.30 12 al-pad 2.71 0.33 69 400 1.38 13 passivation 1.31 0.24 32 350 3.20 3 low-k imd 2.00 0.30 18 80 1.80 3 copper via 8.91 0.38 121 330 0.60 3 oxide 2.64 0.32 66 430 6.60 3 usg 2.00 0.23 80 380 8.00 3 al-cu pad 2.85 0.31 100 400 610 0.054 die 2.33 0.23 161 2.2. finite element prediction both 2-d and 3-d finite element models based on fea software ansys/ls-dyna codes are developed to simulate the wirebonding process. the geometry of the overall structure was first built to create models. since fea prediction also focuses on the strain/stress beneath the bond pad, the entire microstructure of cu/low-k layer should be well defined. fig. 6 and fig. 7 present the 2d fea geometry, microstructure of cu/low-k imd and 3d fea solid model, respectively. because the accurate material properties should be reflected as inputs for precise finite element analysis, the above experimental measured data can then be directly applied to the existing fea model. a fine mesh scheme is required to evaluate large plastic deformations on mashed fab with a sufficient accuracy. it should be noted that the small contact region between capillary and fab is always collapsed, which resulted in the so-called hourglass mesh or zig-zag patch during iteration approach. this happens on hexahedral 3d solid reduced integration elements in fea model and needed to be re-meshed very frequently. in addition, the precise dimension for fea model should be carefully measured. table 2 lists the modal cart of capillary (tool) and table 3 specifies the dimension of cu/low-k imd microstructure beneath the bond pad. the diameter of cu wire is 50 m and 85 m of fab (free air ball). fig. 6 finite element 2d copper wirebonding model. fig. 7 finite element 3d copper wirebonding model. advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 55 table 2 detail charts for capillary descriptions dimensions diagram of capillary tip diameter (t) 188um hole diameter (h) 58um chamfer diameter (b) 81um inside chamfer (ic) 11um inside chamfer angle (ca) 90° face angle (fa) 22° outside radius (or) 38um table 3 detail dimension for microstructure beneath the bond pad length(um) width(um) height(um) pad 146 73 5.2 passivation 146 73 4.58 low-k imd 146 73 4 copper via 14 14 4 oxide 146 73 1.8 die 146 73 1.8 2.3. physical mechanism the bonding process is simulated in three steps. in the first step, the capillary (also refer to the “tool”) push fab downward 10 m within 0.7 ms to touch the pad. second, the tool is continuously pushing fab impact pad and the contact face/length between ball and pad became welded. the third step provides a slightly downward force and ultrasonic vibration, which refers to 120 khz frequency, 1 μm amplitude within 4 ms vibration time. loading for the tool is: (1) y-travel and impact time is 0.3 ms, (2) the vertical displacement is 36 m, (3) the horizontal displacement is 2 m. fig. 8 demonstrates the key physical mechanism in wirebonding process fig. 8 capillary displacement physical mechanism 2.4. boundary conditions all the boundary conditions based on the wirebonding physical process for 3d predicted fea model are illustrated in fig. 9. the bottom surface of fea model is assumed to be fixed. advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 56 fig. 9 boundary conditions for the predicted 3d fea model 3. result and discussion 3.1. squeeze-out bond pad fig. 10 fea predicted wirebonding model larger plastic deformation occurred in the area under smashed fab. fig. 10 displays the predicted results for fea wirebonding model. as can be seen, the largest deformation took place in 2 regions: (1) contact area between capillary and fab, and (2) contact area between fab and bond pad. negative volume, zig-zag patch and hourglass elements are always happening and producing meaningless results during numerical iterations. mesh density and element shape in the largest deformation regions are particularly addressed to avoid numerical iteration errors. squeeze-out bond pad can be controlled by giving the optimal conditions in fea model. fig. 11 presents the predicted maximum squeeze-out bond pad. fig. 11 predicted maximum squeeze-out bond pad advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 57 3.2. predicted effective stress once the bond pad squeeze has been optimized, special attentions are focused on the dynamic response beneath the bond pad. fig. 12 shows the predicted effective stress vs. time history in low-k imd layers and the predicted effective stress contours is shown in fig. 13. fig. 12 predicted maximum effective stress vs. time history in low-k microstructure fig. 13 predicted maximum effective stress at the end of impact motion 3.3. parametric studies an increase in the bond pad would result in a decrease both in the maximum effective stress in the bond pad and the squeeze-out bond pad. on the contrary, an increase in the bond pad would result in an increase in the maximum effective stress in the low-k imd microstructure. table 4 lists predicted results as the bond pad height is increased . table 4 predicted maximum effective stress for different bond heights. bond pad height (m) 5.2 6.2 7.2 maximum effective stress (mpa) on bond pad 131 111 109 squeeze-out bond pad (m) 2.22 1.44 1.34 maximum effective stress (mpa) in low-k imd 96.69 96.76 98.88 4. conclusions in this paper, the predicted copper wirebonding proces s for high power ic based on fea model has been developed. the insight of the physical mechanism of wirebonding process has also been explored. the experiment works on micro mechanical tensile test and true stress-strain relationships for cu wire have been determined. with these material properties, the fea predicted wirebonding model becomes feasible and numerical simulation errors have been fixed in this research. parametric stu dy reveals an increase in the bond pad height would reduce the large plastic deformation as well as the maximum effective stress on the bond pad. the predicted results can be directly applied to the practical assembly process . advances in technology innovation, vol. 3, no. 2, 2018, pp. 51 58 copyright © taeti 58 references [1] y. j. lin, c. kang, l. chua, w. k. choi, and s. w. yoon, “advanced 3d ewlb-pop (embedded wafer level ball grid array-package on package) technology,” proc. 66 th electronic components and technology conference, may 2016, pp. 1772-1777. 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[12] r. c. j. wang, c. c. lee, l. d. chen, k. wu, and k. s. chang-liao, “a study of cu/low-k stress-induced voiding at via bottom and its microstructure effect,” microelectronic reliability, vol. 46, no. 9-11, pp.1673-1678, september-november 2006. http://www.springerlink.com/content/?author=yuan-tin+wang  advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 a cloud information platform for 3d printing rehabilitation devices ta-cheng chen 1,2,* , yi-wen chen 2 , yen-shan chen 2 , yun-tzu kuo 1 1 3d printing research center, asia university, taichung, taiwan, roc 2 department of information management, national formosa university, yunlin, taiwan, roc received 04 may 2018; received in revised form 13 august 2018; accepted 24 december 2018 abstract due to the problems of current population aging, occupational injuries and traffic accidents have led to an increasing number of elder people who are physically disabled in taiwan. these persons, mostly seek medical treatment from medical institutions to help restore them to their premorbid level. therefore the number of patients who go to medical institutions is gradually increasing and the splinting is largely applied in the medical cares. 3d printing technology has been widely used in the medical industry in recent years, especially in the development of rehabilitation devices. up until now, to produce the customized splint requires either face to face communication or messaging software by relevant parties. due to the complexity of the medical process, it is often time-consuming for occupational therapists to discuss the medical records with the splint design engineers via the above mentioned means. the other difficulty is that data management becomes a real problem. medical communication and information management are thus the most urgent issues that need to be investigated. in this study, we applied the information technology and cloud-based technology to design a simple and user-friendly web-based interface for making 3d printing splint. this web-based interface utilizes cloud-based technology to provide an information platform for communication and co-management between the relevant stakeholders. the aim of this study is to make system management, retrieving patients’ information and browsing 3d graphics be more convenient for users, and thus to improve the efficiency and effectiveness of producing splints based on the proposed system. keywords: 3d printing, rehabilitation devices, splint, cloud, information platform 1. introduction the 3d printing technology has been applied to the medical field in recent years. this technology has partially solved several problems raised from stuffiness, clothing, and uncomfortable level of wearing the traditional medical assistive devices, such as splints. moreover, 3d printing technology has achieved a further breakthrough of advocating the effective of reducing patients’ feelings of inferiority when wearing an assistive splint. thus, 3d printing has become a feasible solution in solving the aforementioned problems through the production of improved splints. although there are many various medical information systems in medical applications, most of them are the kind of information sharing systems to share the patients’ medical records. however, there are very few information system platforms developed for the purpose of medical device manufacturing and little information about functional treatment units. therefore, doctors and occupational therapist must rely on paper works, telephones, face to face or additional use of communication software to communicate with each other so that such communication process is time consuming. with the 3d printing technology, the splint production method has been transformed from hand-made to digital production. without the information, communication platform, to check the blue print of the splint on the platform by all the related medical care parties becomes * corresponding author. e-mail address: tchen@nfu.edu.tw advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 74 impossible. it makes everyone have to communicate with each other by using traditional ways. the process for completing a customized splint by using 3d printing technology is complicated. at first, after diagnosis and medical treatment, doctor keys in all the diagnostic information on the window of patient rehabilitation treatment card through the computer. next, based on the doctor’s diagnosis, the 3d model of the splint has to be designed by the designers and then assessed by the therapist. while the 3d model is approved, the 3d printing process of the splint is then activated. however, during the process, the related personnel must communicate with each other, check the best parameter settings of the 3d graphic in details and discuss and amend repeatedly. the communication methods of the existing medical clinic are using the telephone, messaging software or face to face to communicate. since the medical personnel are too busy to discuss freely in the scene. using the current communication ways as described above without seeing 3d graphics, it will cause many difficulties in expression and make the related data is hard to be managed and stored properly. therefore, this study is to turn the workflow of the 3d printed rehabilitation products into the clouding computerized processes. the information sharing platform enables various parties to cooperate in making a more perfect splint for patients. based on the proposed system, a multi-directional communication and information transmission pipeline can be built so that it makes all the operations with better efficiency and effectiveness. the purposes of this research are illustrated as follows: (1) the electronic system has been adopted instead of using paper files to reduce the unnecessary waste of resources. (2) to explore how to use the information platform to improve the original work situation in the hospital. (3) design the 3d printing assistive device splint cloud information platform to solve the previous problems such as management and communication inconveniences to enhance the efficiency of personnel. 2. literature review a rehabilitation assistive device refers to any device or product used to maintain or improve the quality of life and movement ability of people with disabilities [1]. among the several health care aids, splints have been widely used in medical departments, such as rehabilitation and orthopedics, due to time constraints [2]. a splint is a kind of rehabilitation equipment, used outside of the human body, mainly for the fixation, or protection limbs [3]. splints are used not only to improve the discomfort of limbs, but also to help people to use their limbs normally. compared to the splint made of plaster, we need a lighter, cleaner, and air-permeable splint. so, we can say that the plaster should be taken place by the good ones. creating splints are one of the professional skills of occupational therapists. a splint can be made from a wide variety of materials. a traditional splint is usually made of low-temperature thermoplastic medical materials [4] and can be tailored to individual limb curves. this feature solves the gypsum breathable problem, reduces the burden of patients wearing splint, and makes wound dressing or cleaning of the skin around the wound convenient [5]. however, the traditional splint materials are not waterproof, prone to allergies, difficult to shape on the limbs, and cannot hollow out any position on the splint surface [6]. with 3d printing technology, all kinds of graphics can be generated directly through 3d graphics software design, without restrictions on size, shape, and color. it has a high degree of freedom and complexity in design, so it is more convenient for the production of small-scale limb splint, and can also improve the patient's fit and comfort when using a splint. with the advantage of 3d printing, the pre-opening hole position and the whole mesh pattern are corrected directly in the splint design, as shown in fig. 1. this helps to improve splint's breathable and the waterproof function so that it will reduce the skin irritation or ulceration of the affected body area. using 3d printing technology, it can avoid unnecessary waste of materials and reduce the production costs. after forming 3d printing splints, these splints do not need special maintenances [7]. so, 3d printing technology has become a significant issue of producing splint to an occupational therapist. the differences between the traditional splints and the 3d printing splints are illustrated in table 1. advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 75 fig. 1 the production process of 3d printing splint sequence diagram [7] table 1 comparison of traditional splints and 3d printing splints traditional splints 3d printed splints production methods manual 3d printer time to use shorter longer breathable medium height customized low height waterproof no yes suitability to smaller limbs low height complexity low height the introduction of 3d printing has brought many possibilities to the medical treatment. in recent years, various 3d printing medical devices have been developed in medical clinics, such as teeth, tracheal scaffold, splint and so on. these splints are the harness and used in the external body. the purposes of these devices are for treating, immobilizing, or protecting the function of damaged body parts [3]. during the manufacturing of 3d printing splints, all the assigned personnel need to discuss the 3d graphics with one another. however, the current method that uses considerable paperwork delivery fails to meet the demand to check the 3d graphics of splints. the process requires the use of messaging software, telephone call, or face-to-face discussion among personnel. these inefficient methods will cause communication inconvenience, management problems, and 3d graphics browsing difficulty. in the research on medical information transmission, yang and liu imported a device for the traditional manual work mode of nurses and developed a nursing information system [8]. this device assists in daily works by using a computer or network. the results showed that the device could reduce overtime rate and unnecessary waste of materials, make the patient information inquiry convenient, and improve work efficiency. tian et al. showed that the use of electronics to improve medical image processing operations could reduce patient waiting time and accurately manage the medical graphics data to promote high-quality service [9]. doel et al. combined medical image processing operations with cloud technology to assist the data storage, management, and analytical tasks of medical images on the web [10]. this process allows health care personnel and researchers to share the medical image data conveniently. as previously mentioned, electronics and cloud technology will be the necessary tools for future development in the medical industry. recently, umair and kim proposed an online 3d printing service platform and cooperated with medical clinics who are interested in 3d printing [11]. through this platform, the information about 3d printing medical-related data and medical clinics can be provided. furthermore, the platform can provide knowledge and production of 3d printing medical material information to patients and medical clinics. however, the purpose of the present study is focused on the medical assistive device splint production in health care clinics without outsourcing. therefore, we integrated the entire operation data of medical doctors, occupational therapists, and 3d printing engineers. these professionals could comfortably and easily use the platform for job processing and information sharing by using related technologies. in addition, we designed the splint cloud information platform of a 3d printing assistive device to improve the splint manufacturing efficiency. designing a web-based interface that allows the users to get started quickly and promote the usage intention must be investigated. if the system interface is poorly designed, it will reduce the usage intention of the users. therefore, laurel and mountford proposed that human–computer design principles are mainly divided into: (1) user-oriented design. (2) interfaces consistency. (3) graphical representations. (4) multiple views [12]. advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 76 li proposed that the expression clearly can enhance the usage intention of the users. besides, before developing the system, the requirements should be clarified [13]. booch proposed that unified modeling language(uml) which is the visualized language for developing software and uses different diagrams to describe the system requirement through different viewpoints [14]. the diagrams of uml can be divided into: (1) use case diagram. (2) class diagram. (3) component diagram. (4) activity diagram. (5) collaboration diagram. (6) sequence diagram. (7) statechart diagram. (8) deployment diagram. uml is using the standard diagrams to simplify the lengthy text statements and allows the system developers, designers and users to understand the cognition of system framework, flow path, and all aspects quickly [15]. 3. research approach fig. 2 the production process of 3d printing splint sequence diagram the present day, there was no jointed managed pipeline for the transmission of the splints production information, so this study cooperated with the medical clinics and learned the current processes and methods of producing 3d printing splint in person in a medical clinic. we used the information technology and cloud technology to solve the previous paper waste, both sides communication, browsing 3d graphics and managing medical data difficultly and other problems. we explored the workflow of producing splints in the hospital in this study. the basic functional items in the workflow for producing the 3d printing rehabilitation splints are: (1) patient data records (2) medical records (3) information about the splint creation (4) upload 3d splint drawing file (5) execution of 3d printing (6) query 3d printing splint information (7) advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 77 account management (8) splint category (9) message bulletin (10) permission control. based on the above functions are defined for each item, the users of the system are then clarified with the corresponding various authorities. they are as follows: (1) medical unit doctor. (2) medical unitnurse. (3) medical unit occupational therapist. (4) splint design units3d graphics engine. (5) 3d printing unit 3d printing engineer. (6) platform system manager administrator. in this study, the system demand analysis and design use the uml to explain the platform design, as described as follows. during the initial visit of the patient, the doctor must collect the patient’s basic data. then, the doctor creates a patient treatment record and selects the suitable splint. subsequently, the occupational therapists establish the splint production contents in accordance with the splint specification, which is established by the doctor, and assist in splint production. next, the splint designer starts to draw the 3d graphics of the customization splint based on the splint production contents. following design completion, the 3d graphics are uploaded into the splint version management in the platform. the occupational therapists will check whether the design is a 3d graphics; otherwise, the splint designer must upload again the data after correction until it passes the verification stage. after passing the verification, the splint designer sends the 3d graphics to the 3d printing engineers. the engineers will receive the printing details and produce it. afterward, the generated splint will be checked by the occupational therapists. if the splint is not in accordance with the specifications, it must be returned to the splint designers, who will upload the 3d graphics files until the finished product passes verification. finally, the case is terminated by the occupational therapists. the 3d printing splint production process is shown in fig. 2. 4. platform design fig. 3 forestage platform framework diagram the proposed system platform in this study is divided into two major parts, namely, the forestage system and backstage management. when entering the proposed system, the platform will lead the users to the forestage or backstage screen on the basis of the users’ status. the users of the cloud information platform forestage of the 3d printing rehabilitation device are advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 78 doctors, nurses, physical therapists, and 3d graphics and printing engineers. the process structure of the system forestage is shown in fig. 3. there are four functional sections in the forestage, they are “patient list”, “splint production”, “3d printing splint”, and “about the system” respectively. the corresponding web interface is shown as fig. 5. moreover, the system platform administrator has the highest login authority of the backstage. the backstage structure is illustrated in fig. 4, and there are four main functional sections including “splint kind setting”, “account management”, “web page function setting” and “about the system”. the two major functions (forestage and backstage) describe the structure of the proposed cloud information platform, for which all the different roles of users can use the platform to produce the customized splint for each of the patients. fig. 4 backstage framework diagram the system requirements in this study are presented on the web platform. in general, the planning of the platform includes the following five major parts which are described in the forestage and backstage of the cloud information platform as follows: (1) basic data about patient management: all the medical care data of the patient, including the following four functional pages as shown in fig. 5. (a) the basic data of patients: the basic data for recording the patients. (b) treatment record: the treatment records of the patients, including medical information, diagnostic logs out and treated areas for the occupational therapist to know the treatment demands of patients. (c) splint production: records of splint specification and 3d graphics file management for every patient. this information also provides 2d and 3d graphics uploading, browsing, and leaving a message. the details are illustrated in fig. 7. (d) 3d printing splint: 3d printing splint for the 3d printing engineer to receive the 3d model printing information. advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 79 (2) categories of splint setting: manage the information of various 3d printing splint. see fig. 6. (3) account management: it is the basic users’ data and the authority in the platform as shown in fig. 8. (4) permission settings of pages and function: for setting the permission of all users as shown in fig. 9. (5) about the system: it is the announcement pages of the internal information and its declaration of the internal information and its records the usage condition of the platform. in the process of making a splint for a patient, all the data are divided into four major items, one of which is the patient's basic information, the second is the patient's medical record, the third is the splint production menu, and the fourth is the 3d printing detailed information. the medical personnel can view the contents of the patient’s case as needed. in terms of interface design, the button conforms to the "representation of content in graphics" and "content must be clear" as mentioned in the literature, as shown in fig. 5. fig. 5 basic data of patient management fig. 6 categories of splint setting this content in fig. 6 is designed as a backstage administrator to manage the information of the 3d printed splint category. from this page, the administrator can edit and add the type, location, laterality, coverage, knuckle range and whether the secondary wood is still in use to provide the front-end medical staff to select the appropriate splint for the patient. when making a secondary wood, it needs to be revised after discussion. a secondary wood production requires several versions. advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 80 therefore, this study divides the splint production menu into two parts: the secondary wood production content and the secondary splint production version management, so as to reduce the complexity of the user browsing. the contents of the splint production include the name of the physical therapist responsible for the case, the functional therapist number, the medical institution, the functional therapist's diagnosis, the type and side of the splint, the printing materials of the splint, and the uploaded image of the injured part of the patient, delete, download, and provide image zoom browsing, physical therapist notes, and status display. and we also need to consider the possibility that the patient temporarily changed his/her mind not to use 3d printed splint during the production process. therefore, the “void button” is given to stop the subsequent actions, as shown in fig. 7. fig. 7 production of splint fig. 8 account management advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 81 this function page in fig. 8 is a page for the background manager to manage employee data, which is divided into two parts: the employee's basic data and permission settings. employee basic information includes user account information and employee basic information. the account information includes the employee account number, password setting, and consideration of personnel transfer. therefore, the user status field is provided to control whether the user has the right to use the platform, and the corresponding authority is given to the user. the way to query personnel is to query the name, account number, job title, subordinate unit and status, so that the user can quickly search for the required information. since this platform has many patient privacy information, it is necessary to provide permission settings for the administrator to control. therefore, we make the platform users use the functionality of the page to be restricted by permissions. each person's authority is given the corresponding authority according to the set role. the page and function permissions are based on the content of the function, such as basic patient information, medical records, splint production, 3d printed splint, the backstage of the about system, the splint settings, personnel data management, role permissions settings. if there are special functions, the extended permission function is given to the user for additional settings, as shown in fig. 9. fig. 9 permission settings of pages and function 5. conclusions and future researches three-dimensional printing is a digitized manufacturing technology; thus, manufacturing using such technology is made by computer drawing software and then produced by using the 3d printing machine. the assigned personnel need to browse the 3d graphics files in the manufacturing process; however, the personnel must face several unpleasant situations, such as unnecessary resource waste, 3d graphics management, information transmission, and communication without the use of the information platform. it will be very easy to cause the mistakes during the communication and file transmission. therefore, in this study, we introduce the flow of utilizing 3d printing device in hospital, and utilize the cloud technologies and uml to design the information platform and then constructed it. in this study, the cloud information platform for 3d printing assistive device splint can provide browsing functions of 3d graphics, feedback mechanism, and automatic managing function efficiently. this platform can prevent un-necessary wastes of the paperwork in delivery of documents, mistakes caused by browsing 3d graphics with wrong patient, and the difficulties in communication and document management. the proposed platform can also improve the splint production efficiency (see table 2). from table 2, we can see the comparison of before and after while using the proposed information platform. advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 82 table 2 comparison table of before and after use the information platform before implementing of information platform after implementing of information platform information transfer method paper network browse 3d graphics method face to face communication / other web-based browse in this study platform communication channel face to face communication / telephone/ messaging software in this study platform data management the manual way of management an automatic way of management in this study, the cloud information platform of the 3d printing rehabilitation device is designed and constructed with the cooperation of many doctors in the medical clinics. in literature, many scholars have confirmed that the use of electronic and cloud technology in medical operations can effectively help medical personnel to file, find, save and operate their daily operations. however, the effectiveness of using the platform in medical clinics should be investigated in the future. and it needs to verify whether the process of introducing 3d printed rehabilitation device in medical care is suitable or not. thus, we aspire that the use of the system can be used in medical clinics in future research and perform further verification and improve the operating efficiency of the splint production. 6. acknowledgments the authors would like to thank all the colleagues and students who contributed to this study. this research is supported by the ministry of science and technology, taiwan, r.o.c. under grant no. most 106-2632-e-468-001. conflicts of interest the authors declare no conflict of interest. references [1] b. r. bryant and p. c. seay, “the technology-related assistance to individuals with disabilities act: relevance to individuals with learning disabilities and their advocates,” journal of learning disabilities, vol. 31, no. 1, pp. 4-15, january 1998. 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[11] m. umair and w. s. kim, “an online 3d printing portal for general and medical fields,” proc. computational intelligence and communication networks (cicn), 2015 international conference, ieee press, march 2015, pp. 278-282. advances in technology innovation, vol. 4, no. 2, 2019, pp. 73-83 83 [12] b. laurel and s. j. mountford, “the art of human-computer interface design,” addison-wesley longman publishing co., inc., 1990. [13] j. w. li, “a study on the user interface for hand-held products: pda as example,” master’s thesis, department of design, dy university, 2003. [14] g. booch, “the unified modeling language user guide, pearson education india,” 2005. [15] w. d. shen, “the campus property management system-analysis, design and implementation using uml,” master’s thesis, department of computer science and information engineering, tamkang university, 2008. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 73 copyright © taeti optimization of ducted propeller design for the rov (remotely operated vehicle) using cfd aldias bahatmaka1,*, dong-joon kim2 , deddy chrismianto3 1 interdiciplinary program of marine design convergence, pukyong national university, busan, korea. 2 department of naval architecture and marine systems engineering, pukyong national university, busan, korea. 3 department of naval architecture, diponegoro university, semarang, indonesia. received 09 march 2016; received in revised form 19 june 2016; accepted 21 june 2016 abstract the development of underwater robot technology is growing rapidly. for reaching the best performance, it is important that the innovation on rov should be focused on the thruster and propeller. in this research, the ducted propeller thruster is used while three types of shuskhin nozzle are selected. the design is compared in accordance with the thruster that has been made as the propulsion device of underwater robots. each type of the thruster model indicates different force and torque. for the analysis, each model is built in computer aided design (rhinoceros) program packages and computational fluid dynamics (cfd) to find the most optimal model which can produce the h ighest thrust. among the entire model, the kaplan series (ka5-75) with the type c of nozzle has the highest thrust which is 2.53 n or 25.24% of ext ra thrust. for the optimization o f thrust, genetic algorithms (ga) is used. the ga can search for parameters in large mult i-d imensional design space. thus, the principle can be applied for determining the initial propeller that produces optimum thrust of rov. the ga has successfully shown able to obtain an optimal set parameters for propeller characteristics with the best performance. keywords : remotely operated vehicle (rov), ducted propeller, cfd, genetic algorithms nomenclature ae propeller expanded area a0 propeller disk area ctn regression coefficient of thrust coefficient cqn regression coefficient of torque coefficient d diameter propeller j advance coefficient kt thrust coefficient kq torque coefficient n propeller blade pitch p/d pitch diameter ratio q torque (nm) sn exponent of j t thrust tn exponent of p/d un exponent of ae/a0 vn exponent of z z number of blades ρ density of water 1. introduction remotely operated vehicle (rov) is an instrument formed min i-sized submission vehicle. rov is usually used to explore underwater photography, military operation and underwater pipeline repairing. rov is used for activit ies small cave. rov is designed to have abilities of seabed rescue operations and repairing o f seabed objects from the surface [1]. underwater robo t is des igned and manufactured abso lu tely requ ires many supporting components to improve the operation to perform a variety missions. thruster is one component that has function as locomotor of underwater robot to maneuver horizontally when it moves forward and backward and also to maneuver vertically to moves up and down [2]. * corresponding author, email: bahatmaka.aldias@gmail.com advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 74 copyright © taeti the first proposal to use a screw propeller appears to have been made in england by hooke in 1680, and its first actual use is generally attributed to colonel stevens in a stream-driven boat at new york in 1804. in 1828 a vessel 18 m (60 feet) long was successfully propeller by a screw propeller designed by ressel. the screw propeller has reigned supreme in the realm of marine propulsion. it has proved extraord inarily adaptable in meeting the incessant quest for propellers to deliver more and more thrust under increasingly arduous conditions [3]. the genetic a lgorithms is one of method that has tool for optimization for many difficult optimization problem with mult iple object ives. ga methods were shown to be able to replace the traditional computation method and design charts. in this case, for determining the in itial propeller that optimum for rov thruster is difficult. for selecting the init ial propeller, used optim tools in genetic algorithms, the result will be found directly and efficiently. however, the traditional design charts method and previous ga methods were limited in considering or maximum hydrodynamic aspect alone, such as hydrodynamic efficiency, and the thrust coefficient, etc. hence, the goals of the present research are: to determine the optimum value o f thrust for rov thruster using 3 parameters are pitch diameter rat io, e xpanded blade area ratio, and rotational speed of propeller. applying ga methods to propeller design with consideration of thrust for reach ing the best performance of propeller. 2. method the computational flu id dynamics (cfd) [4], is one branch of fluid mechanics that uses numerical methods and algorithms to solve and analyse problems related to flu id flow the purpose of cfd is to predict accurately on fluid flow, heat transfer, and chemical reactions in complex systems, which involve one or all the above phenomena. 2.1. rov design in this research, rov project in fig. 1 has been designed and which has dimension as shown as the table 1. table 1 principle dimensions of rov item unit length 601.87 mm beam 409.20 mm height 290.00 mm mass (on air) 13.70 mm weight 5.00 n fig. 1 rov project design 2.2. propeller design the propeller d imension and geometry design are listed in the table 2. table 2 principle dimensions of propeller item unit diameter 130.00 mm pitch 78.00 mm amount of blade 5 blades expanded bar 0.75 rake of angle (b5-75) 10.00 degree rake of angle (ka5-75) 15.00 degree rotational speed 300.00 rpm density of water 1.025 kg/m3 in this case, the propeller dimension was chosen by the product sold in the market. and using this dimension, propeller was designing in cad model. for the design used 2 types of design, b-series (b5-75) as shown in fig. 2 and kaplan-series (ka5-75) as shown in fig. 3. advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 75 copyright © taeti fig. 2 b-series (b5-75) fig. 3 kaplan-series (b5-75) 2.3. numerical method and bboundary conditions in this steps, for the numerical on analysis was using computational fluid dynamics method. several steps for calculat ions such as: geometry, mesh, setup, solution, and result. boundary condition was calcu lating for the open water propeller [5]. the boundary condition can be shown in fig. 4. fig. 4 boundary condition of open water propeller 2.4. validation of thruster in this research to validate the result of the test model, used the software test result that already exis t and was conduct ed by mulyowidodo, k. et al in bandung technology institute indonesia. validation of underwater thruster for shrimp rov-itb is used to determine the exact boundary condition for using on the boundary condition when analyzing 3 models for rov thruster using cfd-based software. reference is taken from the validated model for the testing thruster. used propeller type of ka5-75 series and based on the theory of wageningen [6], the open water propeller characteristics conventionally were presented in form of the thrust and torque coefficient kt and kq in term of the advance coefficient j, where 2 4t t k n d  (1) 2 5q t k n d  (2) av j nd  (3) the characteristics of the ship’s propeller for open water test condition are as represented in kt-kq-j chart. type of each propeller is having the characteristic curves of different performance. it can be shown in fig. 5. fig. 5 kt-kq-j chart 2.5. geometry design of nozzle for the calcu lation of nozzle, shushkin nozzle has been chosen which developed (prof.dr.-ing. h. heuser, 1982). the nozzle design is shown in fig. 6. advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 76 copyright © taeti fig. 6 pressure process and flow contraction at the nozzle propeller compared the size of kort nozzle tipe a: ld/dp =0,75; di /dp = 1.015; limits: 20mm <(di –dp) < 60 mm; da/di = 1,25; la/ld = 0,53; lp/ld = 0,27, lv/ld = 0,40; lh/ld = 0:33 the size of kort nozzle tipe b: ld/dp = 0,75; di/dp = 1,015; limits: 20mm < (di –dp) < 60 mm; da/di = 1,25; dk/di = 1,02; dr/di = 1,035; la/ld = 0,32; lp/ld = 0,25, lv/ld = 0,425; lh/ld = 0,325; lk/lh = 0,925 the size of kort nozzle tipe c : ld/dp = 0,75; di/dp = 1,015; limits: 20mm < (di –dp) < 60 mm; da/di = 1:20; dk/di = 1,015; dr/di = 1,030; la=ld = 0,50; lp/ld = 0,50; lv/ld = 0,40; lh/ld = 0,35; lk/lh = 0,880 2.6. preliminary propeller design the preliminary propeller design problem is described in detail in the principles of naval architecture [3]. here is the basic design or initial design of propeller with the principal dimension as: (dependent variables) diameter : 130.00 mm amount of blades (z) : 5 blades rake of angle : 15.00 degree material : mn.bronze (2) density of water : 1.025 kg/m3 (independent variables) p/d : 0.60; 0.65; 0.70 ae/a0 : 0.75; 0.80; 0.85 rotational speed (n) : 5 rps; 10 rps; 15 rps 2.7. performance of computation selecting from a propeller series is a simple method to design a propeller. among the series propeller is one of the most often used and studied. and selection of the blade was improved later. the thrust and torque coefficient can be expressed as the table 3. table 3 regression coefficients and exponents of kt-kq n ctn sn tn un vn n cqn sn tn un vn 1 0.00880496 0 0 0 0 1 0.00379368 0 0 0 0 2 −0.204554 1 0 0 0 2 0.00886523 2 0 0 0 3 0.166351 0 1 0 0 3 −0.032241 1 1 0 0 4 0.158114 0 2 0 0 4 0.00344778 0 2 0 0 5 −0.147581 2 0 1 0 5 −0.0408811 0 1 1 0 6 −0.481497 1 1 1 0 6 −0.108009 1 1 1 0 7 0.415437 0 2 1 0 7 −0.0885381 2 1 1 0 8 0.0144043 0 0 0 1 8 0.188561 0 2 1 0 9 −0.0530054 2 0 0 1 9 −0.00370871 1 0 0 1 10 0.0143481 0 1 0 1 10 0.00513696 0 1 0 1 11 0.0606826 1 1 0 1 11 0.0209449 1 1 0 1 12 −0.0125894 0 0 1 1 12 0.00474319 2 1 0 1 13 0.0109689 1 0 1 1 13 −0.00723408 2 0 1 1 14 −0.133698 0 3 0 0 14 0.00438388 1 1 1 1 15 0.00638407 0 6 0 0 15 −0.0269403 0 2 1 1 16 −0.00132718 2 6 0 0 16 0.0558082 3 0 1 0 17 0.168496 3 0 1 0 17 0.0161886 0 3 1 0 18 −0.0507214 0 0 2 0 18 0.00318086 1 3 1 0 19 0.0854559 2 0 2 0 19 0.015896 0 0 2 0 20 −0.0504475 3 0 2 0 20 0.0471729 1 0 2 0 21 0.010465 1 6 2 0 21 0.0196283 3 0 2 0 22 −0.00648272 2 6 2 0 22 −0.0502782 0 1 2 0 advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 77 copyright © taeti table 3 regression coefficients and exponents of kt-kq (continued) n ctn sn tn un vn n cqn sn tn un vn 23 −0.00841728 0 3 0 1 23 −0.030055 3 1 2 0 24 0.0168424 1 3 0 1 24 0.0417122 2 2 2 0 25 −0.00102296 3 3 0 1 25 −0.0397722 0 3 2 0 26 −0.0317791 0 3 1 1 26 −0.00350024 0 6 2 0 27 0.018604 1 0 2 1 27 −0.0106854 3 0 0 1 28 −0.00410798 0 2 2 1 28 0.00110903 3 3 0 1 29 −0.000606848 0 0 0 2 29 −0.000313912 0 6 0 1 30 −0.0049819 1 0 0 2 30 0.0035985 3 0 1 1 31 0.0025983 2 0 0 2 31 −0.00142121 0 6 1 1 32 −0.000560528 3 0 0 2 32 −0.00383637 1 0 2 1 33 −0.00163652 1 2 0 2 33 0.0126803 0 2 2 1 34 −0.000328787 1 6 0 2 34 −0.00318278 2 3 2 1 35 0.000116502 2 6 0 2 35 0.00334268 0 6 2 1 36 0.000690904 0 0 1 2 36 −0.00183491 1 1 0 2 37 0.00421749 0 3 1 2 37 0.000112451 3 2 0 2 38 5.65229e−05 3 6 1 2 38 −2.97228e−05 3 6 0 2 39 −0.00146564 0 3 2 2 39 0.000269551 1 0 1 2 40 0.00083265 2 0 1 2 41 0.00155334 0 2 1 2 42 0.000302683 0 6 1 2 43 −0.0001843 0 0 2 2 44 −0.000425399 0 3 2 2 45 8.69243e−05 3 3 2 2 46 −0.0004659 0 6 2 2 47 5.54194e−05 1 6 2 2 as the functions of the blade number, blade area ratio, p itch ratio and advance coefficient [4]: 39 1 0 untn sn vne t tn n ap k c j z d a             (4) 47 1 0 untn sn vne q qn n ap k c j z d a             (5) where ctn and cqn are the regression coefficients of the thrust and torque coeffficients, repectively; sn, tn, un, and vn are the exponents of j, p/d, ae/a0, and z, respectively. 2.8. genetic algorithms (ga) the basic theory, genetic algorithms are search algorithms based on the mechanics of natural selection and natural genetics. they combine survival of the fittest among string structure with structured yet randomized informat ion exchange to inform a structure algorithms with some of the innovative flair of human search. in every generation, a new set of artificial creatures (strings) is created using bits and pieces of the fittest of the old man; an occasional new part is tried for good measure. while randomized, genetic algorithms are no simple random walk. they efficiently exp loit historical informat ion to speculate on new search points with expected improved performance. genetic algorithms have been developed by john holland [7]. based on the theory, the research was conducted with the set of parameters dependent and independent variables. for the first steps were identifying variab les and functions, the propeller of remotely operated vehicle (rov) , there are three variable that we could change randomly as like as p/d (p itch ratio ), ae/a0 (e xpanded blade area rat io), and n (rotational speed). using the three variables, we would get the value of kt and kq. thus, the thrust (t) and torque (q) can be expressed as: function:  2 4 tt k n d (6)  2 5 qq k n d (7) the fitness function we can select the eqs. (6) and (7), then used the regression table (3) to produce the thrust and torque coefficients. advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 78 copyright © taeti fitness function: 39 1 0 untn sn vne t tn n ap k c j z d a             (8) 47 1 0 untn sn vne q qn n ap k c j z d a             (9) the constraint function, used three variables (p/d, ae/a0, n) can be created as: constraint function: 0.60 0.70 p d   (10) 5 15n  (11) 2.9. optimization for the process of optimization shown in fig. 7, used optimization tools that supported by matlab program for the solution of genetic algorithms method. in this case, ga apply to know how is the optimum thrust for the in itial propeller using the parameters and all parameters setup for ga is shown in table 4. table 4 setting up the ga parameters ga parameters population size = 20 number of generations = 80 selection: stochastic uniform crossover rate = 0.8 crossover function: scattered mutation rate = 0.2 fig. 7 flowchart of genetic algorithms advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 79 copyright © taeti 2.10. cfd analysis type a nozzle fig. 8 meshing of type a for b-series (b5-75) fig. 9 meshing of type a for kaplan-series (ka5-75) type b nozzle fig. 10 meshing of type b for b-series (b5-75) fig. 11 meshing of type b for kaplan-series (ka5-75) the process of analysis for the nozzle design has been conducted. there were some different results for the meshing process of all nozzle’s type. for the type a for b-series (b5-75) shown in fig. 8, it has 845,769 nodes and kaplan-series (k5-75) shown in fig.9 has 702,840 nodes. the type b for b-series (b5-75) shown in fig.10, it has 1,146,817 nodes and kaplan-series (k5-75) shown in fig.11 has 1,007,934 nodes. the type c for b-series (b5-75) shown in fig.12, it has 1,343,789 nodes and kaplan-series (k5-75) shown in fig.13 has 1,206,703 nodes. type c nozzle fig. 12 meshing of type c for b-series (b5-75) fig. 13 meshing of type c for kaplan-series (ka5-75) streamline simulation for the simulat ion of streamline, the input for all types were same, and the rotational speed was 300rpm. the results of streamline from type a nozzle for b-series (b5-75) shown in fig.14, type a nozzle for kaplan-series (ka5-75) shown in fig.15, type b nozzle for b-series (b5-75) shown in fig.16, type b nozzle fo r kaplan-series (ka5-75) shown in fig.17, type c nozzle for b-series (b5-75) shown in fig.18, type a nozzle for kaplan-series (ka5-75) shown in fig. 19. advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 80 copyright © taeti type a nozzle fig. 14 streamline of type a for b-series (b5-75) fig. 15 streamline of type a for kaplan-series (ka5-75) type b nozzle fig. 16 streamline of type b for b-series (b5-75) fig. 17 streamline of type b for kaplan-series (ka5-75) type c nozzle fig. 18 streamline of type c for b-series (b5-75) fig. 19 streamline of type c for kaplan-series (ka5-75) from all the figures, it can be seen that the type c of nozzle was the highest of thrust than type a or type b. pressure contour type a nozzle fig. 20 pressure contour of type a for b-series (b5-75) fig. 21 pressure contour of type a for kaplan-series (ka5-75) advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 81 copyright © taeti type b nozzle fig. 22 pressure contour of type b for b-series (b5-75) fig. 23 pressure contour of type b for kaplan-series (ka5-75) type c nozzle fig. 24 pressure contour of type c for b-series (b5-75) fig. 25 pressure contour of type c for kaplan-series (ka5-75) this process was indicating the pressure distribution on the blade area. the results of pressure contour from type a nozzle for b-series (b5-75) shown in fig. 20, type a nozzle for kaplan-series (ka5-75) shown in fig. 21, type b nozzle for b-series (b5-75) shown in fig. 22, type b nozzle for kaplan-series (ka5-75) shown in fig. 23, type c nozzle for b-series (b5-75) shown in fig. 24, type a nozzle for kaplan-series (ka5-75) shown in fig. 25. 3. results and discussion from the analysis of cfd method, it can be seen on the table 5. for the changes of the force as clearly shown in fig. 26, and the changes of the torque shown in fig. 27. table 5 results of force (t) and torque (q) type of models force (t) (n) torque (q) (nm) b-series (b5-75) propeller without nozzle 1.67 0.016 nozzle a 2.06 0.020 nozzle b 2.12 0.021 nozzle c 2.26 0.023 kaplan (ka5-75) propeller without nozzle 2.02 0.020 nozzle a 2.34 0.022 nozzle b 2.50 0.023 nozzle c 2.53 0.024 fig. 26 chart of force (t) analysis on 300rpm advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 82 copyright © taeti fig. 27 chart of torque (q) analysis on 300rpm in this paper, we have described the specification and the design concepts of ducted propeller as the thruster of rov (remotely operated vehicle). there were several designs of the ducted propeller. total o f models were 6 models, b-series (b5-75) and kaplan-series (ka5-75) with nozzle’s type a, b, and c. based on the simulations which were conducted, can be concluded that the highest of force (t) was model of kaplan-series (ka5-75) with type c of nozzle. the model could produce 2.53 n, or 25.24% of ext ra thrust. the lowest of torque (q) was model of b-series (b5-75) with type a of nozzle. thus the best model will be used for rov thruster is model of kaplan-series (ka5-75) with type c of nozzle. in other hand, the model also was conducted for analysis using other software, was used star ccm+ for checking the value of the force (t) and the torque (q). the geometry shown in fig. 28, the mesh scene as shown in fig. 29, and the results could be seen in fig. 30 for the streamline simulation and for the pressure contour shown in fig. 31. geometry fig. 28 geometry of ducted propeller in star ccm+ generating mesh fig. 29 mesh scene in star ccm+ streamline simulation fig. 30 streamline simulation in star ccm+ pressure contour fig. 31 pressure contour in star ccm+ based on the simulation results both of ansys cfx and star ccm+ is almost same value, the difference of the force (thrust) is around 5%. it means, the analysis of ducted propeller is enough satisfied and accurate. it can be seen on the table 6. table 6 comparison results results ansyscfx star ccm+ force (t) 2.53 2.66 torque (q) 0.024 0.033 advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 83 copyright © taeti optimization in the previous chapter has been obtained the model that will be used for the rov (remotely operated vehicle). the model is the kaplan-series with type c nozzle. further, the optimization analysis can be applied to get the optimal of thrust for this case. with the fitness function and constraints from the table 7, the results can be exported by genetic algorithms as shown in fig. 32. table 7 output of optimum thrust iteration p/d ae/a0 n(rev/s) 51 0.60 0.79 5.00 at the 51 iterat ion using ga, the thrust will be optimum when the value of p/d (pitch ratio) is 0.60, ae/a0 is 0.79 and the value of rotational speed is 5 rev/s. based on the results from the table 8, the thrust is increasing 27.43% from 2.530 n to 3.224 n. and it means the optimization of the thrust for the ducted propeller of rov is reached and satisfied. fig. 32 fitness value through the generations final results table 8 comparison the final results result original new differences force (n) 2.530 3.224 +27.43% torque (nm) 0.024 0.032 +33.33% 4. conclusions in this paper, about a study on development of the propulsion device for the rov (remotely operated vehicle). the cfd method has been demonstrated to be more effective as the problem solver fo r determining the optimum thrust of rov. the nozzle can produce the extra thrust for the propeller. cfd model shows these results. the comparison of propeller types such as b-series (b5-75) and kaplan-series (ka5-75) shows that kaplan-series (ka5-75) has stronger thrust than b-series (b5-75) and the streamline simulation shows these results also. the highest thrust (t) is fro m the model kaplan-series (k5-75) with type c of nozzle. the model can produce 2.53 n or 25.24% of extra thrust. the ga is applied for optimization design of the initial p ropeller dimension and the results show that it is good for this kind of the problems . the optimization method ga is easy to use as optimum solution in multi-dimensional using three variables such as p/d (pitch rat io), ae/a0 (expanded blade area ratio), and n (rotational speed) are affecting to the result of the thrust. from the results of optimizat ion, the thrust is optimum when the value of p/d is 0.60, ae/a0 is 0.79 and the value of rotational speed is 5 rev/s or 300 rpm. in this research, for the optimizat ion of the ducted propeller for rov has been proposed and provides the solution to the problem of rov thruster. therefore, cfd method and ga optimization can be employed due to its ability to solve the problem and its performance mentioned above especially for the best performance of ducted propeller. acknowledgement the authors would like to thanks fo r the support of the bk21 p lus madec human resource development group in 2016, pukyong national university, without their help, this paper could not be submitted. references [1] d. christ, roberto, l. wern li sr, robert, the rov manual,user guide for observation, united kingdom: burlington, 2007. [2] s. a. sharkh, m. r. harris, r. m. crowder, p. h. chappell, r. l. stoll, and j. k. sykulski, “design considerations for electric drives for the thrusters of unmanned underwater vehicles,” the 6th european conference on advances in technology innovation, vol. 2, no. 3, 2016, pp. 73 84 84 copyright © taeti peer electronics and application, vol. 3, pp. 799-804, 1995. [3] v. manen, j. d., and p. v. ossanen, principles of naval architecture, volume ii: resistance, propulsion, and vibration, 2nd ed., new jersey: society of naval architects and marine engineers, 1988. [4] g. kuiper, “new developments and propeller design,” journal of hydrodynamics, ser. b, vol. 22, no. 5, pp. 7-16, 2010. [5] parra and carlos, “numerical investigation of hydrodynamic performances of marine propeller,” master thesis, galati university, 2013. [6] m. m. bernitsas, d. ray, and p. kinley, “kt, kq, and efficiency curves for the w ageningen b-series p ropellers ,” michigan univ., dept. of naval arch itecture and marine eng., usa, 1981. [7] goldberg and e. david, “genetic algorithms in search, optimizat ion, and machine learning,” alabama univ., usa, 1953.  advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 a gi proposal to display ecg digital signals wirelessly real-time transmitted onto a remote pc marius-corneliu rosu1,*, hamed yassin-kassab1, adriana iliesiu 2, serban georgica obreja3 1 department of applied electronics and information engineering, univers ity politehnica of bucharest, romania. 2 department of cardiology, university carol davil of bucharest, romania. 3 department of telecommunications , university politehnica of bucharest, romania. received 21 july 2017; received in revised form 26 september 2017; accepted 17 december 2017 abstract the sensors, as wireless communication system, comply the 7-layer model open systems interconnection (osi). in this paper, a point-to-point transmission model was used. the ecg signal is transmitted from the router sensor (rs) to an end coordinator node (cn) plugged-in to the laptop via usb port; rs acquires ecg signal in analogical mode, and is also responsible with sampling, quantization and sending it wirelessly direct to cn. the distance between rs and cn is a single-hop transmission, and does not exceed the range of the xbees2pro transceivers . the communication protocol is zigbee. remote viewing of the transmitted signal is performed on a graphical interface (gi) written under matlab, after the signal has been digitized; the choice of matlab was motivated by future developments. particular aspects will be highlighted, so that the reader to be edified about the results obtained during laboratory experiments. recording demonstrate that the purpose exposed in title has been reached: direct link in real-time was established, and the digital ecg signal received is reconstituted accurately on matlab gi; signal received on laptop is compared with the analog signal displayed on oscilloscope. keywords: gi, real-time ecg, wireless-transmission, zigbee, matlab 1. introduction remote viewing of a digital signal is performed on a graphical interface (gi), written in a programming language, enabling the entire signal overview and detailed views. visualization by gi, it showed to be faster than standard methods. different levels of visualization and fast navigation in bio-signals are essential conditions for a gi. many expectations are demanded from specialists when is used a software for more tasks. the truth sometimes looks quite different: the software does not work as is expected, and because of some bugs unpleasant consequences and unwanted effects will occur. gi is usually the main interface; the only one can say between the user and the given system. traditionally testing with gi is done manual involving money and time; that's why the results are often unreliable. so better for testing are specialized software which can avoid these problems and time period to enter on market can be shorted. thus, scripting language for gi should allow rapid testing and debugging as well as the possibility to check gi with dedicated programs . * corresponding author. e-mail address: marius-corneliu.rosu@sdettib.pub.ro advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 119 1.1. graphical interface design issues engineering for gi becomes a subject in the software industry starting with 90s. gi had replaced the text -based interface (tbi) with one based on graphics, and for users it becomes more intuitive and easier to work with . in [1], it is shown the need to transpose the tbi to the gi platform in an automatic way. this must include the gi builder and compiler code for event-driven language c/c++. applications that use gi are created based on processes requirements, and during development these may change. typically, gi are modeled as state machines defined by windows, widgets, widgets parameters and values; usually shaping gi starts from implementing requirements which a system must meet. long-term bio-signals' acquisitions are the main sources of informations about the patient's condition . hence, a broad set of issues into a gi design must be harmonized. modeling was also an important obstacle in the tests performed on the basis of patterns because they were not used more intensively in the industry. it has been shown, however, that in well-defined applications, models generation methods can be used with good results. consequently, the automatic generation of models has become widely used in designers thinking. various techniques used to generate models of gi are synthesized in table1. for a more thorough documentation, the reader is guided to consult the reference [2]. in table1, most techniques require human intervention; the effective implemented solution largely depends on the degree of human intervention. stages of drafting, in short, are the following: (1) design and modeling of the main components for optimal response of the monitored system (ms). (2) establishing of minimum parameters required to cover the ms. (3) generate automatically if possible with a predetermined method (e.g. supervised learning) the pattern of algorithms and test parameters. (4) testing the monitored system by running the generated patterns and parameters. to explore the events, gi inputs must be stimulated while outputs return the results; also, the created gi for the ms, permit to check the implementation (software or hardware) for the system requirements. 2. signal consideration various technologies are needed to develop an effective gi as discussed in the previous chapter; design and development require a multidisciplinary approach. long-term acquisitions of bio-signals are important; they constitute the main source of information on the patients' condition. visualization tools are also important: they allow the inspection of complex bio-signals in a fast manner and friendly use. in terms of scope, this paper aims to depict the possibility of using the programs dedicated mainly to signal processing (matlab this case). in terms of variety, bio-signs are impossible to classify rigorously: the only certainty is that these are with very low values (the useful ecg signal, between -2 and +2mv) , while interferences, artifacts, and noises, distort them, having a major influence (e.g. electrods offset level between -300 and +300mv). a bio-signals classification is not universally valid. in fig. 1, we drew a classification attempt, and fig. 2 illustrates once again that it is practically unachievable for a strict and unique classification. from these, ecg signal is graph transposition of heart electrical activity, and the mechanical activity of the heart is somewhat regular with the exception of being patients with cardiovascular disease (cvd), so ecg may be considered a quasi-periodic waveforms. particularities can be summarized as follows: advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 120 (1) ecg is ideally for electronic reporting (2) ecg signals are weak; (3) bad influences have interferences, artifacts, and noises; (4) bandwidth is considered depending on the intended purpose, monitoring or diagnosis (5) some areas of the ecg signal frequencies must be preserved; fig. 1 bio-signals wave shapes attempt classification fig. 2 second approach for bio-signal classification (after [3]) note: in figures are indicated, heart rate fc, respiratory rate fr, and other additional information advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 121 table 1 techniques for generating gi models task. gi models technique name description remarks 1 manual modeling modeling the test system; defining the required test area; control of entry, while on exit is observed the events using test scripts; the model represents the real situation and test scripts that generates him; system testing by the so-called compliance testing requirement specifications, interface, and so on, should accurately describe the behavior of the system; requirements are shown in natural language by texts and diagrams; just persons with analytical abilities can create a formal and structured model 2 automatic modeling the initial objectives of model are reduced; enables implementation of the compliance testing requirements; the model is basically a reverse engineering task; implementation is the source for redesign of the work; can reveal bugs that cause accidents in implementations 3 semi-automatic modeling modeling techniques, performed most part automatically are assisted manually by a person during the process; revised, corrected and extended manually after generating the initial model. 4 reverse engineering extract design artifacts, and derive abstractions less dependent of implementation. there are two approaches: static, analyzing source code or binary representation, without running the system, while dynamic, examines the external behavior of the system by running it . 5 static analysis built for important elements of source code figure behavioral and structural; several issues make the static analysis a complicated task: inheritance, polymorphism, and dynamic binding, make difficult to know which methods are going to be executed; that's why for this, the method was not successful in generating patterns for gi testing purposes. 6 dynamic source code instrumentation analysis during the execution of a system, observations are made by instrumentation instructions implemented as source code, which can be on gi controlled and observed source code is the best way to get information, because the level of abstraction and sources of information are controlled by reverse engineering; 7 dynamic byte code analysis it is used to avoid repeated operations less invasive than source code can be used in java 8 dynamic gi apis the technique is used to collect information on gi status, and to control the gi from one state to another the model was created for understanding the behavior of the original gi, in aiming to build the correct shell; it is used an independent source code for interaction. 9 manual gi exploration techniques explore manually by the user the implemented gi, while the background process record user actions. all capture or playback gi tests tools, utilizes manual methods of exploration; model is used to generate test cases able to find errors. 10 fully automated gi exploration techniques generation of gi testing models; gi models are obtained as well as runtime behavior automatically. the process works in ripping mode, starting with first gi window and continuing by opening all other sub-windows; the behavior of the structure and execution of gi are extracted. 11 user-assisted gi automated exploration techniques it is a mix between automatic exploration and user-assisted manual exploration. it consists of three phases: 1. extracting structural information about each gi window; 2. interaction with gi; 3. takeover of behavioral information through automatic process. the model is used for abstract cases. 12 feedback gi refinement all the processes described above can be improved by this technique; this technique requires that an initial test case or suite to be created, manually or automatically, and to be run on software. various sources of feedback are possible, e.g. the code coverage report. feedback serves to enhance the gi model, allowing for better test coverage and test generation with lower costs of execution 3. motivation and previous achievements the increasing of hardware applications in medicine had generated the issues of visualization into a manner that can be understood by the human brain; signal analysis in medicine has now become a method of interpretation and research since it can offer feedback on the patient's condition or state of the experiment by processing it . so, viewing and processing techniques advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 122 involve researchers or clinicians direct in selecting interesting parts of analyzed bio -signal. the acquisition on a longer period of time is a method that allows continuous monitoring, and was proposed in [4]; the method has, however, barriers consisting of vast amounts of end point with double column. it becomes important for remote monitoring continuous real-time view. design of visualization tools is related to a correct choice of data information storage structure; signals must be recorded in a format that gives possibility for posteriori data accessing. several standards for storing biological data and inter-communication have been developed over time. a standard format that allows saving the data on multiple channels is european data format (edf), and it is described in [5, 6]. division of health science and technology from massachusetts institute of technology (mit) developed research resources for an online investigation that can be applied to complex biological signals [7]; it consists of the following main components: (1) physiobank is the online database of physiologic signals; (2) physiotoolkit, is the bio-signal analysis tools: the ecg data stored in edf format can be viewed in the edf browser, an open source tool that allows signal processing, such as filtering, power spectrum, or heart rhythm; (3) physionet the web forum [8]; the gi's requirments for viewing and processing of the long term bio-signals are not easy to be achieved. other ideas in visualizing large data sets, but not for bio-signals, is web mapping services consisting in a multilevel visualization of an very large datasets; another area requiring long-term visualization are algorithms for data mining [9]. displayed solutions described above refer to portions of signal finite in time. for bio -signs with virtually infinite duration, ecg in this paper, visualization imposes a new concept of gi' s that have to display in real-time the monitored signal wirelessly transmitted. 4. the concept biological signals can be acquired through various methods. as was mentioned, visualization, analysis, and processing, are essential in long term monitoring. in this paper, we intend to see a new possibility for building a gi by using other resources than the classic ones. 4.1. data file formats it should be recalled once again that in long term monitoring, the amount of received information is enormous. also, the data format in a standardized mode will facilitate cooperation and exchange of data between centers; a brief list of formats is described in further:  *.txt: text, known by users as computer files, with a wide use, those are basic file system; can be accessed and modified thru text editors. disadvantage: slow access in data;  *.edf: edf is just a basic format to archive and exchange bio-signals; sampling frequencies and physical sizes are not imposed. disadvantage: implementation of edf unit is time consuming task ;  *.dat: physiobank is characterized by the archive of physiologic signals recorded digital. each physio -bank is possible to have more than one record divided in three files: *.hea file header information; name or url short text file describing signals; *.dat – binary signal file containing digital samples;  *.h5: hdf5 hierarchical data format 5 for storing and managing data with simple structure that include: datasets and groups;  *.mat: matlab format, the most known in biomedical engineering area; data are saved in binary. even though is not open source, it is a powerful tool; since ecg acquisition we made is under matlab format, the idea was to try to realize a gi also under matlab tool. advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 123 4.2. basis idea as the ‘tmtools’ command in matlab is used to establish the communication via usb port between an oscilloscope and a pc, we began to wonder if a similar issue can be applied to a cn plugged by usb onto a remote pc, which acts as server and workstation for the received signal. the only requirement self-imposed is the ability to view in real-time the signal received which is transmitted in digital domain between a router and a coordinator node; the last one is connected to the remote pc via a usb port. it is known that matlab provides programs and basic commands that can be modified for the aimed purpose. thus, if the ecg samples from oscilloscope acquisition were made possible via the usb port in matlab, the same thing was wanted and in reverse operation, to display the signal wirelessly received by the coordinator, in a gi written under matlab; the choice was motivated by flexibility and adaptability to future developments. for this, however, we are required the following checks : (1) if the serial device send data in "lines", through a line terminator character; (2) how many bytes is expected to be read each time by the serial port; verification of the above can be done by following the instructions set forth in [10]. since most usb drivers include the ability to act as a "virtual serial port" or "virtual com port" (vcp), this feature can be used to establish communication with the matlab interface. in windows, drivers for vcp are sometimes a separate feature or require additional installation steps ; once installed, serialdatastream function is responsible for receiving and processing a continuous stream of data from a device connected to a usb. some aspects must be specified so that the reader to be cleared up about how the connectivity can be established between coordinator and pc via usb interface: (1) first, it should be remembered that due to micro-processor adc module in sensor node, wireless transmission it will be made in the digital domain; (2) in matlab must be connected an object with fopen(obj) command, so that serial communication with coordinator via usb to be possible; (3) obj from command fopen(obj) is defined at least by the parameters: '#com port', 'baudrate', and 'databits'; (4) before running the script should be checked which ‘#com port' was allocated to coordinator, otherwise matlab will not know how to communicate, displaying an error in command window; further, writing in matlab of gi is given by the instructions of reference [11]. 4.3. wireless test results setting and configuration of sensors are important; sensor dedicated to ecg signal was designed for zigbee protocols communications. the channel access technology method was preferred to connect the wireless devices “point to point”; mac protocols thru data-link layer are responsible to allocate resources for this task (osi level 2). fig. 3 shows that used transceivers were wirelessly connected, and fig. 4 shows the coordinator hardware connected directly to the laptop via usb port; the appropriate mac address also can be readable. settings were made also in the xctu configuration software. a direct link has been established in real time between sensors; fig.5 represents snapshots after recording during laboratory experiments , and the received signal is reconstituted accurately on gi written in matlab. on router at mode setting was made, while for coordinator api mode setting was chosen; additional information and a quick reference guide for xbees2pro transceivers used can be downloaded from [12]. advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 124 on the other hand, energy consumption must be well controlled; controllers and radios devices are the main consumers while memory and sensors are in lower position. those demands come because of the generic implemented solutions limited efficiency, and without taking into account the requirements of limited energy resources, wearable systems cannot b e developed. fig. 3 xbees2pro link connection fig. 4 coordinator node plugged into laptop fig. 5 photos of laptop screen; ecg signal can be distinguished 5. conclusions and future work considering the problems with the viewing and processing bio-signals in the long term, and the importance of ecg signal in healthcare. this paper has presented a gi proposal to display ecg digital signal wirelessly transmitted onto a remote pc using matlab toolbox. some requirements should be considered so that the communication to be established successfully via usb; they were detailed in chapter 4. advances in technology innovation, vol. 3, no. 3, 2018, pp. 118 125 copyright © taeti 125 further, writing and developing of gi will be made depending on the complexity and number of determinations that are intended to be made in real time. so, viewing the transmitted digital signal must be performed on a gi which must be friendly and easy to use. at the same time, the end user must have the opportunity of immediate determinations of the main characteristics of the signal (e.g. rr distance in ecg). also, future gi improvements should enable the designer to carry out immediately at minimal cost. channel access technology method was preferred for point to point wireless connection; data -link layer thru mac protocols has the responsibility to allocate resources for this task (osi level 2). thanks to flexibility and adaptability, programs and functions for an automatic processing routine in parameters of interest in ecg signal will be added. this paper discusses traditional methods for gi and proposes a new approach of a program dedicated more to processing and less for interfaces. the challenges in this direction remain undetermined, the rate of renewal of wireless technologies b eing very dynamics; tiny devices are able to improve the daily life and to ensure a better monitoring of patients . references [1] g. antoniol, r. fiutem, e. merlo, and p. tonella, “application and user interface migration from basic to visual c++,” proc. 11th international conference on software maintenance, 1995, pp. 76-85. [2] a. kull, “automatic gui model generation: state of the art,” proc. ieee 23rd international symp. software reliability engineering workshops, november 2012, pp. 207-212. [3] e. kaniusas, “biomedical signals and sensors i,” chp. 1 biological and medical physics, biomedical engineering, berlin: springer-verlag, 2012. [4] h. kayyali, s. weimer, c. frederick, c. martin, d. basa, j. juguilon, and f. jugilioni, “remotely attended home monitoring of sleep disorders,” telemedicine and e-health, vol. 14, no. 4, pp. 371-374, may 2008. [5] “edf-european data format,” http://www.edfplus.info/. [6] b. kemp and j. olivan, “european data format “plus” (edf+), an edf alike standard format for the exchange of physiological data,” clinical neurophysiology, vol. 114, no. 9, pp. 1755-1761, september 2003. [7] g. b. moody, r. g. mark, and a. l. goldberger, “physionet: a web-based resource for the study of physiologic signals ,” ieee engineering in medicine and biology magazine, vol. 20, no. 3, pp. 70-75, may 2002. [8] “physionet the research resource for complex physiologic signals,” http://www.physionet.org/. [9] n. kumar, n. lolla, e. keogh, s. lonardi, and c. a. ratanamahatana. “time-series bitmaps: a practical visualization tool for working with large time series databases ,” proc. of siam international conference on data mining, april 2005, pp. 531-535. [10] “warning: unsuccessful read: matching failure in format,” http://stackoverflow.com/questions/35671418/warning-unsucce ssful-read-matching-failure-in-format, february 29, 2016. [11] m. a. hopcroft, “serialdatastream,” https://www.mathworks.com/matlabcentral/fileexchange/31958-serialdatastream/cont ent/serialdatastream.m, march 20, 2012. [12] “xbee s2 quick reference guide,” https://www.tunnelsup.com/xbee-guide/, november 30, 2012.  advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 prestressed stainless steel stayed columns with two crossarms josef machacek * , radek pichal faculty of civil engineering, czech technical university in prague, prague, czech republic received 03 may 2018; received in revised form 09 july 2018; accepted 11 august 2018 abstract the efficiency of prestressed stayed elements when designing very slender steel columns was proved for both stability and strength capacity of the columns. with an increasing number of crossarms placed along the length of the column the effectiveness is further growing in comparison to a stayed column with just one crossarm. first the stability of an “ideal” (perfect) prestressed stayed column with two crossarms is investigated analytically. similar principal behavior as in the case of prestressed stayed columns with just one crossarm is confirmed and the three zones depending on the value of prestressing are revealed. expressions for minimal, optimal and maximal prestress are derived analytically. after receiving critical buckling value of the stayed column with the two crossarms without any prestressing by linear buckling analysis (lba), the maximal critical buckling loading of the column under optimal prestressing is derived. the results are fully demonstrated on a practical example. second the strength capacity of such column but with relevant initial deflections is investigated by the geometrically and materially nonlinear analysis with imperfections (gmnia) using ansys software. comparisons of critical and strength values under various prestressing are analyzed with respect to a practical design. finally some recommendations for following studies and practical use are given. keywords: stayed columns, two crossarms, stainless steel, prestressing, nonlinear buckling 1. introduction extremely slender columns suffer with a low strength capacity due to buckling. a smart solution of the problem provide prestressed stayed steel elements. the crossarms connected by prestressed cables or rod stays with the column ends rapidly increase both the critical column load and its collapse capacity, see fig. 1. (a) grande arche, paris (b) parc del centre del poblenou,barcelona (b) estádio algarve, faro fig. 1 examples of structures using stayed columns * corresponding author. e-mail address: machacek@fsv.cvut.cz tel.: +420776562811 http://www.google.co.uk/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahukewjbrq7x--xmahxjarqkhvkoa0uqjrwibw&url=http://www.panoramio.com/photo/23176377&psig=afqjcngtsigt8tuugzpmiuutij4dvvqfvw&ust=1463741361896792 advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 2 the prestressed stayed columns with just one crossarm were deeply investigated analytically, numerically and experimentally within several last decades. among others, the milestones were achieved by smith et al. [1] and hafez et al. [2], who discovered the three zones of behavior depending on the prestressing level of the stays and wadee et al. [3], who investigated the maximal load capacity. these results are roughly demonstrated in fig. 2, where the “zones” may be explained as follows: zone 1 (up to tmin), where the prestressing in the stays disappears when the applied load is less or equal to the euler load (ncr = ne); zone 2 (up to an optimal prestressing topt), where the stays remain effective until the applied load triggers a buckling; zone 3 (above topt), where all the stays remain active (in tension) even after the buckling. higher prestressing than topt increases the column loading and, therefore, decreases the critical column load ncr. n n stays a , e crossarm a , i , e s s a a a column a , i , ec c c x z y t t t t a aa a l approx. maximum capacity n n [kn] t t 3toptmin n cr,max n = n cr,min e opt t ~ 0 ,4 t o p t approx. maximum capacity n z o n e 1 z o n e 2 z o n e 3a b cr critical load n by hafez et al.cr approx. maximum capacity n by wadee et al.approx. maximum capacity nmax (a) planar (b) spatial (c) relationship of critical load vs prestressing fig. 2 stayed columns with one central crossarm deep investigations covering critical values, initial imperfections or maximal capacity of the stayed columns with just one crossarm were provided by wong and temple [4], chan et al. [5], saito and wadee [6], [7], experimental and numerical investigations by araujo et al. [8], servitova and machacek [9], lima et al. [10], osofero et al. [11], ribeiro et al. [12], serra et al. [12] and were mostly commented also by the authors in [14], [15], [16], [17]. 1 6 4 m a a a a stays a , e crossarms a , i , e s s a a a column a , i , ec c c l a a  n n a a a a a a ti ti titi ti ti ti ti (a) mast according to vojevodin (b) double stayed prestressed column (c) geometry of the column fig. 3 stayed columns with two crossarms nevertheless, both researchers and designers were aware of a greater capacity of the prestressed stayed columns with more than one crossarm since the origin of the studies (see several masts designed by vojevodin [18], fig. 3). while this knowledge was supported by numerical analysis and some tests (e.g. khosla [19], jemah and williams [20]), the more deep investigation was performed in the last years only. martins et al. [21] tested double crossarm stayed tube columns with a total length of 18 m, two different column cross-section diameters and various prestressing. the tests provided valuable experimental data for axial shortening and lateral deflections under loading. yu and wadee [22] investigated numerically triple crossarm stayed columns using abaqus software. apart from varying the entry data concerning ratio of the column length to crossarms, diameter of cable stays and value of prestressing, the “efficiency indicators” were used to optimize the total design advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 3 and optimal prestressing. for the same columns these authors [23] further developed a nonlinear analytical model verified by abaqus nonlinear analysis, studied parametrically buckling modes and drew attention to the possibility of a mode jumping. lapira et al. [24] analyzed triple crossarm prestressed stayed columns and also columns with additional stay system located in the middle quarters of the system. they derived analytical formulas in 3d for maximal critical values, corresponding optimal and any other prestressing, which verified by fem using abaqus software. in this paper the authors follow-up the mentioned previous investigations concerning stayed columns with just one crossarm and analyze 3d prestressed stainless steel stayed columns with two crossarms in accordance with fig. 3, both analytically for “ideal” (perfect) column and numerically for “ideal” or imperfect column using ansys software. 2. stability behavior of an “ideal” prestressed stayed columns with two crossarms the three approaches leading to the determination of critical loads are presented. first the geometrical analysis based on a geometry and equilibrium conditions, second linear buckling analysis (which however, as shown later, can be used for unprestressed columns only) and third the finite element method (fem) using geometrically nonlinear analysis with imperfections (gnia). 2.1. geometrical analysis first the “ideal” (perfect) column is analyzed in the similar way as was done for just one single crossarm by smith et al. [1] and hafez et al. [2]. the geometrical analysis of a stayed column in accordance with fig. 3 is based on a change of element lengths due to axial deformation at the instant of buckling. the fundamental assumptions of the derivation are: the column is perfectly straight and concentrically loaded. the connections between column and crossarms are assumed to be rigid and between the stays and column/crossarms are assumed as ideal hinges. the maximal buckling load of the central column is assumed to be obtained by linear buckling analysis (lba) for the column without any prestressing. this analysis assumes the stays active both in tension and compression, while neglecting buckling of stays. the axial deformations of the column and crossarms are not considered in lba, however, need to be considered for analytical derivation of the magnitude of tension in the stays. the changes of element lengths at the instant of buckling are shown in fig. 4. the shortening of the outside and central stays gives: 1 2 6 6 3 c c c se ca c cacos ( tg )sin cos sin cos                    and 3 c sm    (1) a ti ti sina cosa ti (a) axial changes (b) outside stay element (c) force resolution fig. 4 axial compression changes of the column and force resolution in the crossarm advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 4 the spatial column has 4 stays (n = 4), the planar one 2 stays (n = 2). the initial axial force in the column, ni, induced by the initial stay pretension, ti, and final one, nf, after the application of the external load, na, are: i in nt cos and 4f a f a fn n nt cos n t cos     (2) the stiffness of the column, kc, of the crossarm member, kca, and of the stay, ks, are: l ea k cc c  ; ca caac ca l ea k  ; s ss s l ea k  (3) after evaluation of the shortening of the column, elongation of the crossarm member and shortening of the stay, the decrease of the tension in the stays and substitution of these values in eq. (1) gives: 12 21 3 3 a i f a ,n c s c ca n cos t t n c ncos sin k k k k               (4) after some substitutions the final tension in the stays, nf, may be written as:   21 3 f i f i c s ca n nt cos cos t t sin k k k              (5) for the applied (external) load, na, the substitution into eq. (2) yields:     2 22 1 1 3 a f i f i ,n c s ca ncos n n nt cos n nt cos c sin k k k                         (6) using these formulas, the behavior of the stayed column with the two crossarms may be described similarly as behavior of the column with just one crossarm. in fig. 5 the resulting three zones of behavior with respect to value of prestressing are shown. also, for a column with two crossarms analyzed in following paragraphs (see the entry data given in paragraph 2.2) the buckling modes and critical loads of unprestressed column are shown. n [kn] t t 3toptmin n cr,max n = n cr,min e opt zo n e 1 zone 2 zone 3 cr n cr, t=0 (a) initial pretension (b) ncr,1,t=0 = 44.43 kn ncr,2,t=0 = 72.12 kn ncr,3,t=0 = 91.90 kn fig. 5 initial pretension vs buckling load and example of the first three buckling modes corresponding to the later analyzed column using lba zone 1: the initial prestressing is small (tf ≤ tmin) and after external loading disappears. the column behaves as unstayed and buckles at the euler load, ne. minimal prestressing, tmin, corresponding to this behavior, follows from eq. (4): advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 5 2 2 l ie nn cc ecr   ; n cc nenai c l ie cncntt ,12 2 ,1,1min   (7) zone 2: the prestressing is larger than the minimal one but smaller than the optimal one, tmin < tf < topt. after triggering of buckling the prestressing in the stays disappears (tf = 0), but the stays at convex side will become active immediately. the resulting critical load, ncr, will be higher than euler’s one and according to eq. (4) will correspond to prestressing ti: n i acr c t nn ,1  (8) maximal critical load, ncr,max, follows from eq. (6), after substituting for na = ncr,n,t=0, where the latter is the value of critical load received from lba for fully active stays without any prestressing (ti = 0), see fig. 5: n, t,n,cr fmax,cr c n nn 2 0  (9) corresponding optimal prestressing is given by: ncropt cnt ,1max, (10) zone 3: the prestressing is larger than the optimal one. after buckling the stays remain in a tension and the critical load falls off due to respective force components in the stays. the residual tension in the stays follows from eqs. (5) and (9) as:    ,max ,max 32 cos cos cos 1 sin 3 r i cr i i cr i c s ca t t n nt t n nt c k k k                  (11) the critical load in zone 3 can be obtained from eq. (6) after substituting for na = ncr and nf = ncr,max:   nicrcr ctnnn ,2max, cos (12) 2.2. numerical stability analysis using 3d gnia the analytical investigation of the critical load based on geometrical analysis of an “ideal” (perfect) central column may be verified by using fem. in the field of prestressed elements the stability behavior in the full range of prestressing can’t be solved by linear buckling analysis (lba) but due to the sudden change of inner energy at the instant of buckling the geometrically nonlinear analysis with imperfections (gnia) is necessary (see, saito and wadee [5] or previous articles of the authors, e.g. [15], [17]). under a small prestressing the stays at buckling become slacked and the ones at convex side are immediately activated (zones 1 and 2). if all the stays, both at convex and concave sides are activated, the column behavior corresponds to the zone 3. the actual behavior of the stayed column with the two crossarms was therefore investigated by using ansys software in 3d and geometrically nonlinear analysis with imperfections (gnia). the results are demonstrated on the same example as analyzed by the authors in [16], however, now with the two crossarms instead of one crossarm. the entry data (length, area, second moment of area, modulus of elasticity) are as follows, see fig. 3: central stainless steel tube ø 50x2 [mm]: l = 5000 mm, ac = 302 mm2, ic = 87009 mm4, ec = 200 gpa. crossarm stainless steel tubes ø 25x1.5 [mm]: a = 250 mm, aa = 111 mm2, ia = 7676 mm4, ea = 200 gpa. advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 6 stays as macalloy cables 1x19 stainless steel ø 4 mm: ls = 2513 mm, as = 12.6 mm2, es = 200 gpa. substituting these values into the formulas presented in chapter 2.1 yields: the invariables: c1,4 = 0.0351, c2,4 = 1.1612. critical loads and prestressing (using ncr,1,t=0 = 44.43 kn from lba, see fig. 5): ne = 6870 n; tmin = 241 n; ncr,max = 38262 n; topt = 1343 n; ncr,3topt = 25925 n. the ansys model involved beam188 elements for the central and crossarm tubes and link180 elements for the cable stays, with the same boundary conditions as mentioned in the chapter 2.1 (connections between column and crossarms are assumed to be rigid, between stays and column/crossarms are ideal hinges). the meshing study resulted into division of l/250 and a/25 as satisfactory one. first, the required initial deflections were introduced, followed by the relevant prestressing of stays through their thermal change (i.e. by cooling). finally, axial deflections to the central column (giving an external load) up to collapse were imposed. a standard newton-raphson iteration was used. to verify the analytical values, first gnia was used, with elastic material behavior, followed by gmnia for stainless steel material. for the stability analysis the “ideal” column was analyzed, the initial imperfections need to be negligible, therefore infinitesimal deflections were employed with the amplitude of w0 = l/500000 = 0.01 mm (in the 3d as w0y = w0z = w0/√2) for both symmetric and antisymmetric modes, see fig. 6. n n x z y l w 0 w /2 0 w /2 0 (a) stayed column (b) initial deflections (c) gnia results fig. 6 initial deflections w0 = l/500000 for “ideal” column and gnia results (identical for both initial deflection modes) the resulting load-prestressing relationship received from the gnia is presented in fig. 6. the curves for critical and maximal loading were received from rather lengthy numerical calculations of 26 prestressing values (in reality cooling of the stays), each with 1000 of compression steps. in low prestressing, roughly up to 1.6 kn, when at the instant of attaining the critical load (i.e. when the tension in all stays become zero) the both stays at the convex side become active in tension (while at concave side being slacked) and the maximal (capacity) load of the “ideal” column becomes higher than the critical one. with higher value of prestressing the all four stays remain in some tension (zone 3) and both critical and maximal values are identical (show also the explanation in fig. 8 for gmnia). comparison of analytical and numerical (gnia) values is rather difficult (see fig. 6) but the analytical values, i.e. ncr.analyt = 38262 n at prestressing of topt,analyt = 1343 n, may be compared with the gnia ones when the stays on the concave side at the buckling don‘t slacken and critical and maximal loads merge together, i.e. ncr,gnia = 38200 n at prestressing of topt,gnia = 1599 n, being acceptable. nevertheless, gnia maximal load for “ideal” column of roughly 52618 n arises at prestressing of 9808 n. it should be noted, that deflected shape for both modes of negligible initial deflection are identical, after ncr = 47852 n first interactive (in combination of symmetric and antisymmetric mode), after prestressing of t = 9808 n becomes antisymmetrical. advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 7 3. maximal loading of an imperfect prestressed stayed columns with two crossarms the investigation of a maximal loading (strength capacity) of a compression element requires the modelling of a real, imperfect column. the initial imperfections in such stayed columns were introduced in accordance with eurocode en 1993-1-1 as equivalent initial deflections with amplitude w0 = l/200 = 25 mm (valid for cold-formed thin-walled tubes and elastic analysis). the deflection was considered again in the spatial direction, i.e. with w0y = w0z = w0/√2. the first two modes of initial deflections were considered only, in accordance with figure 5: antisymmetrical with the amplitude w0,l/2 = l/400 and symmetrical with the amplitude w0 = l/200. l l (a) antisymmetrical initial deflection (b) symmetrical initial deflection fig. 7 gnia critical and maximal capacity for the initial deflection w0 = l/200 the gnia for the above analyzed example with the same stainless steel elastic modulus (according to en 1993-1-4) e = 200 gpa resulted in various prestressing into values presented in fig. 7. as in the lba the decisive mode proved to be the antisymmetric one, giving maximal loading nmax = 31988 n at prestressing of ti = 8353 n. another study employed gmnia (geometrically and materially nonlinear analysis with imperfections), differing just in using the nonlinear material behavior as tested by the authors in [16], resulting in the stress-strain relationship acc. to fig. 8. (a) stress-strain relationship of the stainless steel material (b) load-axial deflection curve for prestressing of ti = 1278 n (c) corresponding tension fig. 8 example of forces in the stays 0.002 0.004 0.006 0.008 200 300 400 500 0 0 100 test [mpa]  = 434.1 mpa ansys 0.2 e = 184.0 gpa in e e1 2 e n e 3 e 4 e 5 advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 8 again both the “ideal” (perfect) central columns with infinitesimal amplitude of initial deflections w0 = l/500000 = 0.01 mm were analyzed (an example of one analysis under initial prestressing of ti = 1278 n is shown for illustration in fig. 8). the results for the critical loads (concerning “ideal” stayed columns) for antisymmetrical initial deflections now partly differ from results in the same column but with symmetrical initial deflections, show in fig. 9. nevertheless, the important value of ncr,gmnia = 34429 n at prestressing of topt,gmnia = 1583 n corresponds well with the former gnia ncr,gnia = 38000 n at prestressing topt,gnia = 1599 n, considering the ratio of the elastic moduli in gnia/gmnia as ein/e = 184/210 = 0.92. a simple reduction using this factor gives ncr,gnia,e=184 mpa = 38000·0.92 = 34960 n which differ from ncr,gmnia = 34429 n by 1.5 %. (a) antisymmetrical initial deflection (b) symmetrical initial deflection fig. 9 gmnia results for the “ideal” column with initial deflections w0 = l/500000 the gmnia results of the real column with an amplitude of initial deflection of w0 = l/200 = 25 mm are shown in fig. 10. in comparison with gnia (fig. 7) the maximal (capacity) loadings are significantly lower due to nonlinear stress-strain relationship of the stainless steel material. the decrease of the maximal loading for decisive antisymmetrical initial deflection mode from 31988 n to 25040 n gives 27.7 %, while for symmetric initial deflection mode the drop from 41544 n to 34000 n is 22.2 %. l l (a) antisymmetrical initial deflection (b) symmetrical initial deflection fig. 10 gmnia critical and maximal capacity for the initial deflection w0 = l/200 4. conclusions the paper investigates prestressed stainless steel stayed columns with two crossarms, located at the thirds of the central column length. in the first part the analytical stability of an “ideal” column is investigated. based on 2d geometrical analysis the behavior of the column is described for an arbitrary prestressing and general geometry. similarly as in the case of the stayed columns with just one central crossarm the three zones according to the extent of prestressing are revealed and formulas for minimal and maximal critical loadings in 2d and 3d together with “optimal” prestressing are derived. the resulting formulas are applied to a practical example, which has all the geometric and material characteristics the same as for the stayed column which was investigated both experimentally and theoretically by the authors in the past, presented e.g. in [17]. the only difference consists in the two crossarms in the thirds of the column length instead of just one central crossarm. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 0 2000 4000 6000 8000 10000 critical load (w0 = l/500000) maximal load (w0 = l/500000) stay prestressing [n] e xt e rn al lo ad [ n ] 34429 n 1 5 8 3 n 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 0 2000 4000 6000 8000 10000 critical load (w0 = l/500000) maximal load (w0 = l/500000) stay prestressing [n]stay prestressing [n] 16 61 n e xt e rn al lo ad [ n ] 35000 n advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 9 numerical analysis started with a linear buckling analysis (lba) under zero prestressing and stays active in compression, giving critical loadings and deflection modes required for the use in the above analytical solution. subsequently a 3d model in ansys software was prepared to analyze both the stability of “ideal” (perfect) column and maximal loading (column capacity) of the “real” (imperfect) stayed column. the “no compression option” for the stays was adopted to simulate any slackening of these elements and respective initial deflections were introduced: infinitesimal ones for critical loadings in the case of “ideal” column (l/500000) and required ones according to eurocode 1993-1-1 for imperfect column (l/200 for thin-walled cold-formed members). the initial deflection modes were introduced in accord with lba either as antisymmetrical one with two half sine waves or symmetrical one with the full sine wave. the main results of the investigation may be summarized as follows: (a) the analytical formulas for the double crossarm prestressed stayed columns concerning minimal and optimal prestressing giving maximal critical analytical loading were derived. (b) numerical modelling (using ansys software) of the column with a practical size was presented for a verification of the analytical approach. it was shown, that the stability behavior of an “ideal” prestressed column is more complex in comparison to the simple analytical approach and a postcritical behavior even for “ideal” column need to be evaluated. nevertheless, the analytical value of the maximal critical loading was well comparable with the numerical one for the prestressing when the stays on the concave side at buckling do not slacken. (c) numerical analysis using gnia with the initial deflections of the main column corresponding to thin-walled cold-formed tubes (with amplitude l/200) gives significantly lower maximal (capacity) loading in comparison with the critical loading. this decrease in the comparison with analytical critical loading in the specified shown example is at 84 % and in comparison to maximal loading of “ideal” column is roughly at 61 %. (d) considering gmnia with the stainless steel material nonlinearity leads to even greater reduction in comparison to the former values. the decrease of maximal (capacity) loading due to initial lower young’s modulus and due to material nonlinearity is another 27.7 %. (e) finally the comparison of effectivity between the stayed column with just one crossarm (see [17]) and the column with the two cross arms (with the above specified geometry otherwise unchanged) in the gnia shows due to adding the second crossarm increase of both critical loading of “ideal” column and maximal loading of imperfect column. the increase of the critical loading is 21.0 % (from 31580 n to 38200 n) and increase of the maximal loading is 63.5 % (from 19570 n to 31988 n). although the presented percentage values are perfectly valid just for the specific geometry only, the higher efficiency of the two crossarms is undisputable and may provide designers with a guidance for more economical and reliable design. acknowledgement support of the czech grant agency grant gacr no. 17-24769s is gratefully acknowledged. references [1] r. j. smith, g. t. mccaffrey, and j. s. ellis, “buckling of a single-crossarm stayed column,” journal of the structural division asce, pp. 249-268, january 1975. [2] h. h. hafez, m. c. temple, and j. s. ellis, “pretensioning of single-crossarm stayed columns,” journal of the structural division asce, pp. 359-375, february 1979. [3] m. a. wadee, l. gardner, and a. i. osofero, “design of prestressed stayed columns,” journal of constructional steel research, vol. 80, pp. 287-298, janury 2013. advances in technology innovation, vol. 4, no. 1, 2019, pp. 1 10 10 [4] k. s. wong and m. c. temple, “stayed columns with initial imperfections,” journal of the structural division asce, pp. 1623-1640, 1982. [5] s. l. chan, g. p. shu, and z. t. lü, “stability analysis and parametric study of pre-stressed stayed columns,” engineering structures, vol. 24, no. 1, pp. 115-124, january 2002. [6] d. saito and m. a. wadee, “post-buckling behaviour of prestressed steel stayed columns,” engineering structures, vol. 30, no. 5, pp. 1224-1239, may 2008. [7] d. saito and m. a. wadee, “numerical studies of interactive buckling in prestressed steel stayed columns,” engineering structures, vol. 31, no. 2, pp. 432-443, february 2009. [8] r. r. araujo, s. a. l. andrade, p. d. s. vellasco, j. g. s. silva, and l. r. o. lima, “experimental and numerical assessment of stayed steel columns,” journal of constructional steel research, vol. 64, no. 9, pp. 1020-1029, september 2008. [9] k. servitova and j. machacek, “analysis of stainless steel stayed columns,” proc. 6th intern. symp. steel structures, korean society of steel construction, seoul, 2011, pp. 874-881. [10] l. r. o. lima, p. c. g. vellasco, and j. g. s. silva, “numerical modelling of prestressed stayed stainless steel columns,” tubular structures xiv, taylor and francis, september 2012, london, pp. 377-382. [11] a. i. osofero, m. a. wadee, and l. gardner, “experimental study of critical and post-buckling behaviour of prestressed stayed steel columns,” journal of constructional steel research, vol. 79, pp. 226-241, december 2012. [12] d. m. ribeiro, p. c. g. s. vellasco, r. r. araujo, l. r. o. lima, and a. t. silva, “numerical assessment of stayed austenitic steel columns,” proc. of eurosteel 2017, copenhagen, september 2017. [13] m. serra, a. shahbazian, l. s. silva, l. marques, c. rebelo, and p. c. g. s. vellasco, “a full scale experimental study of prestressed stayed columns,” engineering structures, vol. 100, pp. 490-510, october 2015. [14] r. pichal and j. machacek, “stability of stainless steel prestressed stayed columns,” proc. 21 st international. conference engineering mechanics 2015, svratka, czech republic may 2015, pp. 230-231. [15] r. pichal and j. machacek, “3d stability of prestressed stayed columns,” proc. 22 nd intern. conf. engineering mechanics, may 2016, pp. 462-465. [16] r. pichal and j. machacek, “buckling and post-buckling of prestressed stainless steel stayed columns,” engineering structures and technologies, vol. 9, no. 2, pp. 63-69, june 2017. [17] r. pichal and j. machacek, “single-crossarm stainless steel stayed columns,” advances in technology innovation, vol. 3, no.1, pp. 9-16, 2018. [18] a. a. vojevodin, “experience from prestressed mast structures (article in russian: opyt iz sooruzenija shprengelnych macht),” vestnik svjazi, no. 5, 1956. [19] c. m. khosla, “buckling loads of stayed columns using the finite element method,” electronic theses and dissertations, dept. civil and env. eng., university of windsor, windsor, on, 1975. [20] a. k. jemah and f. w. williams, “parametric experiments and stayed columns with slender bipods,” international. journal of mechanical sciences, vol. 32, no. 2, pp. 83-100, 1990. [21] j. p. martins, a. shahbazian, l. s. silva, c. rebelo, and r. simoes, “structural behavior of prestressed stayed columns with single and double cross-arms using normal and high strength steel,” archives of civil and mechanical engineering, vol. 16, no. 4, pp. 618-633, september 2016. [22] j. yu and m. a. wadee, “optimal prestressing of triple-bay prestressed stayed columns,” structures, vol. 12, pp. 132-144, november 2017. [23] j. yu and m. a. wadee, “mode interaction in triple-bay prestressed stayed columns,” international journal of non-linear mechanics, vol. 88, pp. 47-66, january 2017. [24] l. lapira, m. a. wadee, and l. gardner, “stability of multiple-crossarm prestressed stayed columns with additional stay systems,” structures, vol. 12, pp. 227-241, november 2017. [25] r. pichal and j. machacek, “buckling and postbuckling behaviour of stainless steel stayed double crossarm prestressed compression elements,” proc. 24th internatioal. conf. engineering mechanics 2018, svratka, may 2018, pp. 681-684. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 a controlled fermentation environment for producing quality soya sauce sophia ferng 1 , wei-hua huang 1 , chien-ping wu 2 , yung-tsong lu 2 , cheng-kuang hsu 1 , robin yih-yuan chiou 1 , ching-hua ting 2,* 1 department of food science, national chiayi university, chiayi 600, taiwan, roc 2 department of mechanical and energy engineering, national chiayi university, chiayi 600, taiwan, roc received 04 may 2018; received in revised form 10 july 2018; accepted 15 august 2018 abstract soy sauce fermentation under controlled temperature is a way to shorten the fermentation time. an energy-saving fermentation system was developed to power a heat pump for maintaining the temperature of sauce moromi at 37±1°c during fermentation. the chemical properties of the sauce moromi and the sensory properties of the soy sauce produced using the controlled fermentation system were evaluated and compared to those of the sauce moromi fermented outdoors without temperature control. the sauce moromi processed using the controlled fermentation system had significantly higher total nitrogen, formal nitrogen, amino nitrogen, reducing sugar and organic acid contents than the moromi fermented outdoor. however, no significant difference was found in overall liking score between two soy sauces. the soy sauce fermented under the control temperature showed higher brix and salt concentration, but lower ph value than the sauce fermented outdoor. it was possible that the beneficial effects of reducing sugar and organic acid contents were rebuffed by the disadvantage of salt concentration. it was concluded that a controlled fermentation environment deserves the potential to produce a high quality soy sauce. keywords: soy sauce, moromi fermentation, quality promotion, controlled environment 1. introduction soy sauce has been the most important seasoning in the orient [1]. it is prepared from a mixture of steam-cooked soybean and roasted wheat with koji mold aspergillus oryzae or a. solace. in sauce moromi fermentation, the proteins and polysaccharides in the moromi are hydrolyzed by the fungal protease and amylase to form different types of small nitrogen compounds and sugars, such as amino acids and reducing sugars. the maillard reaction between amino acids and reducing sugars during moromi fermentation results in the unique flavor of soy sauce [2, 3]. cooking raw soy sauce with sugar improves the maillard reaction and further enriches the sensory properties of the soy sauce. the fermentation of soy sauce using the traditional method generally takes from six months to one year [4, 5]. the fermentation time can be shortened if the fermentation temperature is control artificially. young and wood (1974) reported that if the fermentation temperature was controlled at 35-40°c, it took only 3-4 months to ferment the sauce moromi. reference [2] stated that 45°c was an important temperature for sauce moromi fermentation. soy sauce making under controlled temperature required energy input. hence under the consideration of energy saving, we desii was fermented in a pottery tank to preserve the flavor of the sauce, (2) heat pump was 3-4 times more efficient in its use of elecgned an energy-saving fermentation system to transfer solar energy to electric power for a heat pump and used hot water to maintain the temperature of sauce moromi at 37±1°c during fermentation. the advantages of this system were: (1) the moromtric power than a simple electrical resistance heater, and (3) heat transfer was more efficient by using water as the medium. * corresponding author. e-mail address: cting@mail.ncyu.edu.tw advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 12 the changes of chemical properties of the sauce moromi in the solar energy system were determined and the sensory properties of the soy sauce made from the system were also assessed to evaluate the potential of suing solar energy to produce a high quality soy sauce. 2. materials and methods 2.1. raw materials and chemicals soybean and wheat were purchased from a local farmer in chiayi city, taiwan and immediately stored in a refrigerator at 4°c prior to use. the koji mold (aspergillus oryzae) was purchased from a supplier (chuan feng microbe co., taichung city, taiwan). all of the chemicals used in the analysis were of analytical grade. 2.2. koji fermentation for koji production, raw soybeans were first washed and soaked in water for 24 h at 4°c and then steamed at 121°c for 20 min. wheat was roasted for 30 min at 140°c and then cracked into 4 or 5 pieces per kernel accompanied by smaller particles of wheat flour. roasted wheat and steamed soybeans were mixed at a ratio of 1:2 (w/w). the mixture was then inoculated with 0.1% (w/w) of a. oryzae (approximately 10 8 spores g -1 ), and subsequently dispersed onto perforated stainless steel trays (68 x 44 x 3 cm). each tray was loaded with the mixture to around 3 cm thickness and incubated at 30 ± 3°c. the preparation of koji was completed in 60–72 h when the culture began turning into greenish yellow in color. the koji was stored at 4°c until use. 2.3. moromi fermentation fig. 1 setup of the energy-saving soy sauce fermentation system. fig. 1 illustrates the structure of the temperature-controlled fermentation system. a 160 l pottery tank that accommodates soy mash is bathed in a stainless tank (diameter 84 cm and height 65 cm) full of circulating water for temperature control of the mash. temperatures inside and outside of the pottery tank are to be measured for on-line fermentation temperature control and off-line analysis. the hot, circulating water was prepared using a heat pump powered by a solar power generator and energy management system developed in house. the energy system trades with the electricity grid to assure a safe and yet economical power supply for the process. hot water is to be prepared in the hottest hours of a day for the interest of optimum heat pump efficiency. a programmable logic controller (plc) performs controls and an industrial personal computer (ipc) executes system monitoring and data acquisition. finished koji was put in the pottery tank and then mixed with 18% saline at a weight ratio of 1: 2. a stainless steel cover was made for the mash tank with one hole in the center to the insert thermocouple for measuring the central temperature of the mash, another annulus cover was used to prevent the evaporation of water out of the stainless steel tank. the system was instructed to maintain the central temperature of the mash at 37c+1°c. during the first week of fermentation, the mash was stirred for 3 min once every day and then once a week for the remaining period. the total fermentation period was 13 weeks. advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 13 2.4. microbe analytical methods determination of microorganism changes: the 10-fold-concentrated cells were serially diluted (10 0 to 10 -6 ) in 0.85% sterile saline solution, and 100 µl of properly diluted samples were spread by pca agar media and incubated at 30~35°c for 1~2 days for the total viable count. diluted sample (100 µl) were spread by ym agar plate media (bd difco, franklin lakes, nj, usa), and then incubated for 1 day at 30°c for the counting of yeast. whereas mrs agar plate media (bd difco, franklin lakes, nj, usa) for the counting of lactic acid bacteria, which were incubated for 2–3 days at 30°c in an anaerobic condition (anaeropack, mitusubishi kagaku, kogyo, tokyo, japan). the colonies formed (25–250) were calculated as log cfu per milliliter of soy sauce [7]. 2.5. chemical analytical methods determination of total nitrogen: total nitrogen was determined according to the aoac standard [8] with a little modification. three milliliters of the sample, 1g of catalyst (k2so4/cuso4.5h2o = 10:1), and 20 ml of concentrated h2so4 were added into a digestion tube and then heated for 6 h at 450°c for digestion. when the digestion was completed, 25 ml of diluted sample was mixed with 25 ml of 30% naoh and subjected to distillation. the distillate was absorbed with 25 ml of 0.1 n h2so4. the content of total nitrogen was determined by back-titrating h2so4 with 0.1 n naoh. determination of formal nitrogen and ammonium nitrogen: formal nitrogen and ammonium nitrogen were determined according to the chinese national standard [9]. to determine formal nitrogen, diluted sample and formalin solution were adjusted to ph 8.1, then 20 ml of formalin solution was mixed with 25 ml of diluted samples for 3 min, and titrated to ph 8.1 with 0.01 n naoh. amino nitrogen was determined by subtracting ammonium nitrogen from formal nitrogen according to the cns [9]. determination of ph: the ph values of the soy sauce samples were measured with a pb-10 ph meter (sartorius, göttingen, germany). determination of organic acid content: organic acid content as lactic acid was determined by alkali titration. to determine total acidity as lactic acid, 25 ml of properly diluted sample was titrated with 0.1 n naoh to ph 8.1. determination of reducing sugar: the reducing sugar (rs) in the samples was determined by the 3,5-dinitrosalicylic acid (dns) method [10] with a little modification. dns reagent, which contained (w/v) 1% dns, 2% naoh and 30% sodium potassium tartrate, was prepared by dissolving each component in distilled water. one milliliter of the sample diluents were mixed with 1 ml of dns reagent and then kept in a boiling water bath for 5 min to colorize. after cooling with cold water, 5 ml of distilled water was added and the od540 nm was measured by using distilled water as a blank control. the standard glucose solutions were used to make a calibrated curve for quantitative analysis. determination of browning: the level of browning was determined using the method of reference [11]. the absorbance of moromi samples was measured at od555 nm. determination of sodium chloride concentration: sodium chloride content was determined by volumetric titration with agno3 using the mohr’s method (hamilton & simpson, 1964). a 1 ml of 0.25 m k2cro4 was added into 250 ml flask containing 10 ml of properly diluted sample, then titrated with 0.01 n agno3 until the appearance of brownish color. the standard curve of nacl was prepared with 10–25% (w/v) of nacl solutions. 2.6. sensory evaluation there was a total of 4 different soy sauces under sensory evaluation. the moromi samples from temperature-controlled brewing mash (tcm) and traditional brewing mash (tbm) fermented for 3 months were pressed, and then cooked with sugar (sauce moromi: sugar = 100 g: 10 g) and water (sauce moromi : water =100 g: 40 g) till the added water evaporated out. after cooling down the mixture, ethanol (sauce moromi : ethanol = 100 g: 1 g) was added, filtered with cheese cloth and clarified the advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 14 mixture additionally by sedimentation. after bottling, the soy sauces were autoclaved at 85°c for 30 min. these soy sauces were labeled as samples of tcm-3 and tbm-3. a soy sauce made from tcm without the addition of sugar during cooking and without the addition of ethanol was labeled “tcm-3-raw” as a raw soy sauce. finally, a commercial soy sauce was served as a standard soy sauce which was selected from a very popular brand in taiwan. the color, flavor, taste, savor and overall palatability of soy sauce samples was evaluated by a panel of 60 untrained volunteers. soy sauce samples (10 ml) were prepared in small white plastic discs bearing 3-digit random numbers and presented them to the panelists in random order. the program started with observation of the color, smell of the flavor and taste of the relish by eating some cool noodle with the samples then scored their preferences based on 9-point hedonic scale. 2.7. statistical analysis the data were analyzed by analysis of variance (anova), and significant differences in mean values among data were determined at p < 0.05 by duncan’s multiple-range tests using spss 20 (spss inc., chicago, il). 3. results and discussion 3.1. the changes of microbe counts in the mash during moromi fermentation (a) viable bacteria (b) yeast (c) lactic acid bacteria fig. 2 changes in total (a), (b), and (c) of traditional brewing mash (tbm) and temperature control brewing mash (tcm) during moromi fermentation. ○: tbm; ●: tcm. data are presented as mean±standard deviation (n=3). *,** a significant difference between tbm and tcm at the level of p<0.05 and p<0.01, respectively. the unique flavor of moromi is attributed to lactic acid bacteria in the first stage of moromi fermentation, resulting in decreased ph in moromi to 6.0 or below, at which yeast starts to propagate [13]. fig.1 shows the changes of total viable bacteria, yeast, and lactic acid bacteria of traditional brewing mash (tbm) and temperature control brewing mash (tcm) during moromi fermentation. the total viable bacteria and yeast counts in both tbm and tcm went down and then went up, and then decreased gradually with fermentation time (fig. 2a, fig. 2b). the lowest total viable bacteria and yeast counts in tbm occurred at 5 weeks, while tcm had the lowest counts at 3 weeks. similar changes in total viable bacteria and yeast counts in black soybean moromi were reported [14]. the decrease of total viable bacteria and yeast counts in the initial stage of moromi fermentation was due to the inhibitory effects of high salt concentration in the moromi and low ph induced by lactic acid bacteria [15]. advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 15 no significant changes in the count of lactic acid bacteria in both tbm and tcm were found from 1 week to 9 weeks, and then the count decreased slightly by fermentation time (fig. 2c). in general, there were no significant differences in the yeast and lactic acid bacteria counts between tbm and tcm. the results indicated that the moromi fermentation under control temperature at 37°c did not influence the growths of yeast and lactic acid bacteria compared to the traditional fermentation method that took place at outdoor without temperature control. 3.2. the changes of chemical properties of the mash during moromi fermentation during moromi fermentation process, the proteins of soybean and wheat were hydrolyzed by protease of microbes into small fragments of peptides, amino acids and ammonia. therefore, total nitrogen, formal nitrogen and amino nitrogen contents were often used as quality indexes for sauce moromi [14, 16]. changes in total nitrogen, formal nitrogen, and amino nitrogen contents of tbm and tcm during moromi fermentation are shown in fig. 3a it was found that total nitrogen content increased during moromi fermentation in both tcm and tbm, and their marked increases were noted within 3 weeks fermentation (fig. 3a). tcm showing a higher increase rate compared to tbm indicates that fermentation at 37°c could promote the protease activities and enhance the rate of protein hydrolysis than traditional fermentation method. both formal nitrogen and amino nitrogen contents in tcm increased almost linear with fermentation time up to 7 weeks and then leveled off as the fermentation process continue (fig. 3b, fig. 3c). like the total nitrogen content, both formal nitrogen and amino nitrogen contents were higher in tcm than those in tbm. the results suggested that moromi fermentation at the elevated controlled temperature (37°c) would promote the proteases activities to hydrolyze soybean and wheat proteins into different types of small nitrogen compounds. our data agreed with reference [2], where they stated that high temperature, peculiarly the temperature of 45°c, was a very useful method to promote the proteases in the koji to solubilize and hydrolyze soy proteins efficiently. reference [17] reported that black soybean sauce fermented at 50°c had higher total nitrogen content but lower formal nitrogen content compared to the sauce fermented at 30°c, outdoor or indoor. however, reference [18] compared moromi fermentation at 25, 35, 45 and room temperature, and found that fermentation temperature did not affect total nitrogen content. (a) total nitrogen (b) formal nitrogen (c) amino nitrogen fig. 3 changes in (a), (b), and (c) of traditional brewing mash (tbm) andtemperature control brewing mash (tcm) during moromi fermentation. ○: tbm, ●: tcm. data are presented as mean±standard deviation (n=3). advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 16 fig. 4 shows the changes of ph and organic acid in tbm and tcm. the ph values decreased gradually in both tbm and tcm (fig. 4a). the rate of decrease in tcm was higher than that in tbm. the mash with a low ph value had the advantage of preventing the contamination of unwanted microbes and maintaining the condition well-suited for the action of yeast. in general, the accumulation of free fatty acids, amino acids, and peptides containing carbolylic side chains as the results of hydrolysis of raw materials, the autolysis of microbial cells, as well as the microbial fermentation of carbohydrates, which may account for the decline of ph during moromi fermentation [3, 11, 19]. the accumulation of organic acid in tcm was greater than that in tbm, and the results agreed with more rapid decrease of ph in tcm than in tbm (fig. 4b). (a) ph (b) organic acid fig. 4 changes in (a) and (b) of traditional brewing mash (tbm) and temperature control brewing mash (tcm) during moromi fermentation. ○: tbm, ●: tcm. data are presented as mean ± standard deviation (n=3). fig. 5 changes in reducing sugar content of traditional brewing mash (tbm) and temperature control brewing mash (tcm) during moromi fermentation. ○: tbm, ●: tcm. data are presented as mean ± standard deviation (n=3). fig. 6 change in browning of traditional brewing mash (tbm) and temperature control brewing mash (tcm) during moromi fermentation.the higher the od555 nm value, the higher the browning level. ○: tbm, ●: tcm. data are presented as mean ± standard deviation (n=3). during moromi fermentation, amylases from the microbes hydrolyze the starch in soybean and wheat moromi to form advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 17 small sugars [2, 17]. therefore, reducing sugar can be used as a quality indicator for sauce moromi. reducing sugar content is also a very important attribute regarding to the sensory properties of soy sauce. it can react with amino acids to form maillard’s compounds and produce unique flavor of soy sauce. the reducing sugar content in tcm increased almost linearly during fermentation; however, the content in tbm increased up to 7 weeks and then leveled off (fig. 5). tcm had higher reducing sugar content than tbm; therefore, tcm also showed greater browning reaction than tbm after 3 weeks fermentation (fig. 6). our data showed that tcm had higher total nitrogen, formal nitrogen, amino nitrogen, organic acid and reducing sugar contents than tbm. this was because the proteases and amylases showed higher activity at the elevated controlled temperature (37°c) and hydrolyzed the proteins and starch in soybean and wheat moromi to form different types of small nitrogen compounds and sugars. and based on these chemical indexes, it was clear that tcm had higher quality properties than tbm. 3.3. sensory properties of tcm and tbm soy sauces the sensory scores of four different soy sauces are shown in table 1. the color, flavor, texture, savor and overall liking scores in the tested soy sauces showed very high agreement; therefore, the overall liking score alone could be used to describe the overall sensory preference of the tested soy sauces. the overall liking score could be classified into three groups: the commercial soy sauce showing the highest overall liking scores, followed by tbm-3 and tcm-3, and tcm-3-raw. the commercial product is a very popular blend in taiwan, and the formulation may include certain ingredients specifically for improving the flavor properties. therefore, it was not a surprise to see that the commercial product received the highest score in all the sensory properties. for other soy sauces, only additional 10% sugar was added before cooking and then 1% ethanol was added after cooking, while only water was added during the cooking stage and no ethanol was added for tcm-3-raw. table 1. hedonic rating scores by sensory evaluation sample colour flavour texture savour overall tbm-3 5.72 b 5.32 b 5.25 b 5.29 b 5.31 b tcm-3-raw 5.49 b 4.58 c 4.55 c 4.71 bc 4.63 c tcm-3 5.65 b 5.45 b 5.22 b 5.29 b 5.43 b commercial 6.45 a 6.46 a 6.51 a 6.35 a 6.57 a a, b, c, different letters indicate significant difference in a column (p<0.05). table 2. correlation coefficients between chemical properties and the overall sensory score total nitrogen formal nitrogen amino nitrogen salinity brix reducing sugar ph organic acid overall favourite total nitrogen 1 formal nitrogen 0.09 1 amino nitrogen 0.09 1.00 1 salinity -0.26 0.84 0.84 1 brix 0.49 -0.51 -0.49 -0.43 1 reducing sugar 0.31 -0.90 -0.90 -0.81 0.76 1 ph -0.15 0.61 0.64 0.30 -0.59 -0.78 1 organic acid 0.67 -0.55 -0.56 -0.56 0.75 0.86 -0.81 1 overall favourite 0.32 -0.91 -0.91 -0.86 0.74 0.99 -0.71 0.82 1 tcm-3 and tbm-3 were produced from 3 month-fermented tcm and tbm, respectively, with the addition of 10% sugar to the sauce prior to the cooking process and then 1% ethanol were added after cooling down. based on the results obtained from the moromi fermentation, it was clear that tcm showed better chemical properties than tbm; however, the overall liking scores between tcm-3 and tbm-3 did not differ significantly. it was possible that different chemical properties contributed differently to human mouth’s perception, and the contributions from certain chemical properties were evened by other chemical properties. it was also possible that the addition of sugar prior to cooking and also the addition of ethanol concealed the differences in the chemical properties and resulted in the same level of the overall liking score. advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 18 tcm-3-raw was produced from 3 month-fermented tcm with the addition of only water during cooking. without extra sugar to promote the maillard reaction, tcm-3-raw received a lower overall liking score than tcm-3 the chemical properties of four soy sauces shown in table 2, and the correlation coefficients of the chemical properties and the overall liking scores are shown in table 3. compared to the chemical properties of other soy sauces, the commercial soy sauce had lower formal nitrogen, amino nitrogen and salt concentration but high brix, reducing sugar and organic acid contents. this agreed with the correlation coefficients between the overall liking score and chemical properties, significant negative coefficients for formal nitrogen content (r = -0.88), amino nitrogen content (r = -0.87) and salt concentration (r = -0.88), but significant positive coefficients for brix (r = 0.81), reducing sugar content (r = 0.996) and organic acid content (r = 0.76). tcm-3 had a higher salt concentration, reducing sugar and organic acid contents than tbm-3; however, there was no significant difference in all the sensory scores. it was possible that the beneficial effects of reducing sugar and organic acid contents were rebuffed by the disadvantage of high salt concentration. with the addition of sugar and ethanol, tcm-3 showed higher brix, reducing sugar and organic acid contents than tcm-3-raw. thus, tcm-3 was expected to gain higher sensory scores than tcm-3-raw. during soy sauce making, it is a general practice to add sugar during cooking to promote the maillard reaction and to enhance the flavor properties of soy sauce. it is well know that free amino acids are the main sources contributing to the flavor of soy sauce [20]. free amino acid contents in the four different soy sauces were determined using hplc and the results are shown in fig. 7. in all soy sauces, glu had the highest content (about 14-20%) followed by asp and leu (fig. 7a). the free amino acid profile was similar to the data reported reported data [21]. it was noted that the commercial soy sauce had the lowest glu, asp and leu, while tcm-3-raw showed the highest contents. the sum of 17 measured amino acid content was calculated and the data indicated that the commercial soy sauce had the lowest total amino acid content, while tcm-3-raw had high total amino acid content. (a) total free amino acid contents (b) individual free amino acid contents fig. 7 (a) and (b) in five different soy sauces. tbm-3: tbm at 3 months; tcm-3: tcm at 3 months; tcm-3-raw: raw soy sauce made from tcm at 3 months without the addition of sugar and ethanol; tcm-3: tcm at 3 months; commercial soy sauce: a very popular soy sauce in taiwan. data are presented as mean + standard deviation (n=2). total nitrogen, formal nitrogen and amino nitrogen contents are often served as quality indexes of soy sauces and the decision making in the selection of ending time for the moromi fermentation process. during fermentation, amino acid reacted by reducing sugar to form maillard compounds, such as pentosidine, carboxymethyllysine and furosine, and these compounds further enriched the flavor of soy sauce [22, 23]. in this study, we found a strong correlation (r = 0.996) between the overall advances in technology innovation, vol. 4, no. 1, 2019, pp. 11 20 19 liking score of soy sauces and reducing sugar; however, the correlation was insignificant for total nitrogen content (table 3). nevertheless, even negative correlation coefficient was found between the overall liking score and formal nitrogen content (r = -0.88), as well as amino nitrogen content (r = -0.87). moreover, the total free amino acid content and individual glu, asp and leu all correlated negatively with the overall liking score of the soy sauces. the question need to be addressed was why formal nitrogen and amino nitrogen contents are considered as quality indexes for soy sauce, but these contents in the tested soy sauce were negative correlated with the sensory scores. it was noted that all 17 measured free amino acid contents in tcm-3 were lower than tcm-3-raw indicating that it must have a significant factor resulted in such differences in all different types of free amino acids. since the difference in tcm-3 and tcm-3-raw was with or without the addition of extra sugar during cooking to promote the maillard reaction, it was suggested that free amino acids in tcm-3 interacted with sugars to form maillard compounds and thus the levels of measurable free amino acids decreased in tcm-3 but it also resulted in better sensory properties in tcm-3. based on the results, it was concluded that the maillard reaction took place during the cooking process is a critical attribute to sensory properties of soy sauces. 4. conclusions under the considerations of energy saving and hygienic improving, a solar energy system was designed for soy sauce making. electricity converted from the solar energy was used to power a heat pump that supplies hot circulating water for fermentation temperature control. hot water was prepared at noon and then stored and circulated (normally at night time) for temperature control. this scheme assures an energy-saving fermentation process. the sauce moromi fermented at the system showed better chemical properties than the traditional brewing moromi. therefore, the use of solar energy system has the potential to produce a high quality soy sauce under an energy-saving stance. acknowledgement this work was sponsored by the ministry of science and technology of the roc (taiwan) government under the grant most 103-2221-e-415 -016. references [1] d. fukushima, “soy proteins for foods centering around soy sauce and tofu,” journal of the american oil chemists’ society, vol. 58, no. 3, pp. 346-354, march 1981. 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[23] p. c. chao, c. c. hsu, and m. m. yin, “analysis of glycative products in sauces and sauce-treated foods,” food chemistry, vol. 113, no. 1, pp. 262-266, 2009. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 a multichannel mac protocol for iot-enabled cognitive radio ad hoc networks chien-min wu * , yen-chun kao, kai-fu chang department of computer science and information engineering, nanhua university, chiayi, taiwan received 17 march 2019; received in revised form 13 may 2019; accepted 21 august 2019 doi: https://doi.org/10.46604/aiti.2020.3946 abstract cognitive radios have the ability to dynamically sense and access the wireless spectrum, and this ability is a key factor in successfully building internet-of-things (iot)-enabled mobile ad hoc networks. this paper proposes a contention-free token-based multichannel mac protocol for iot-enabled cognitive radio ad hoc networks (crahns). in this, secondary users of crahns detect activity on the wireless spectrum and then access idle channels licensed by primary users. crahns are divided into clusters, and the channel to use for transmission is determined dynamically from the probability of finding idle primary-user channels. the token-based mac window size is adaptive, with adjustment according to actual traffic, which reduces both end-to-end mac contention delay and energy consumption. high throughput and spatial reuse of channels can also be achieved using a dynamic control channel and dynamic schemes for contention windows. we performed extensive simulations to verify that the proposed method can achieve better performance in mobile crahns than other mac schemes can. keywords: internet of things iot, medium access control, cognitive radio ad hoc networks, multichannel, mac, contention-free 1. introduction internet of things (iot) is a global network of devices, each with a unique address and links to other devices. it allows devices (and their users) to communicate with other devices/users at any time, independent of location, network, or service provider. in recent years, the iot has become a topic of intense interest within the field of communication technology. in machine-to-machine (m2m) communication with portable devices, communication methods that depend on maintaining a fixed location will not meet the needs of human users, who will want to move the devices, so communication on the so-called internet of mobile things has become a common application [1]. iot applications such as smart sensors, smart home applications, and monitoring devices must be connected by wireless transmission technology to achieve ubiquitous information access and seamless communication if they are to fulfill the promise of the iot [2]. mobile ad doc networks use a peer-to-peer, infrastructure-free decentralized wireless network and are easy to construct. because of this, there are many practical uses for such networks, including for personal and home use, military use, and facilitation of emergency rescue operations. the nodes of such networks can be m2m iot nodes such as smartphones and smart-sensor nodes. a mobile ad hoc network (manet) is a typical example of an iot-enabled mobile network [3-4]. so-called cognitive radios can make networks more efficient. the main feature of cognitive radio is that it can both sense and access different channels on the wireless spectrum. when a part of the spectrum licensed by primary users (pus) is idle, secondary users (sus) can take advantage of this. sus temporarily uses the licensed spectrum to complete communication * corresponding author. e-mail address: cmwu@nhu.edu.tw tel.: +886-5-6315368; fax: +886-5-6314486 advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 46 without interfering with pus and without interfering with other sus, thereby improving the utilization of the wireless spectrum. this concept is part of the next generation of network technology and is known as dynamic spectrum access to form cognitive radio networks. a network of iot devices with cognitive radios will be able to use a dynamic spectrum access scheme to find an available channel in a way that does not interfere with pus’ ability to rely on iot communication within manets. in [5-6], the authors proposed a busy tone-based mac protocol. this protocol uses data-transmission priority to reduce delay. nodes access a channel by checking the broadcast busy tone and then transmitting data when the channel is available. the busy tone prevents the channel from being temporarily grabbed by a general data node. however, under this method, when the amount of data (such as multimedia materials) to be transmitted increases, the functionality of the busy tone will not be sufficient, and the amount of delay for data and multimedia delivery will not be guaranteed. in time-dynamic multiple access (tdma) schemes, as a method to optimize resource utilization, each node is assigned a time slot to avoid collisions caused by contention. in [7], the author proposed a decentralized tdma mechanism for adaptive control of data traffic. in [8], the authors proposed the tdma-based “distributed packet reservation multiple access” (d-prma) scheme, in which higher transmission priority is given to data and multimedia nodes than to general data nodes. however, the number of time slots allocated to the data and multimedia nodes in d-prma is determined from the total number of nodes, meaning that when the number of nodes increases, the system will not scale well. in another approach, a tdma mechanism that combines data and multimedia transmission in a hybrid mac protocol based on the carrier-sense with multiple access with collision avoidance protocol (i.e., csma/ca) has been proposed [9] for ensuring the quality of service (in terms of time delay) for data and multimedia nodes and maximizing channel utilization for general data transmission. in [10-11], the authors suggest that the contention-window size in the mac protocol should be adjusted according to node density and node movement speed to ensure that system performance is not degraded owing to changes in data traffic. clustering is the process of partitioning nodes in a network into many clusters for the purpose of improving system performance. in general, the clustering of nodes that sense the wireless network can improve the scalability and stability of the system. clustering also provides opportunities for nodes in clusters to cooperate on channel sensing and access [12-13]. in an iot-based wireless sensor network using tdma, the nodes are partitioned into multiple clusters. a mac protocol to reduce energy consumption and delays by collecting data within clusters (intra-cluster data) and between clusters (inter-cluster data) has been proposed [14]. ieee 802.11ah is a mac protocol that operates over long distances at low frequencies with low power consumption and allows for a large number of m2m iot nodes [15]. however, the mac protocols in [14-15] cannot satisfy the need for differentiated quality-of-service (qos) within iot manets. an opportunistic spectrum access mac protocol has also been proposed for a cluster-based multichannel wireless network [16]. the authors prove that the nodes using this protocol must repeatedly contend without clustering. multiple occurrences of contention lead to increased delays in data delivery, and increased delays reduce system performance. in [17], the authors proposed a token-based mac protocol (ta-mac) for a mobile network. ta-mac operates in a fixed channel and two-hop environment. however, in real environments, channels are a relatively rare and valuable resource. thus, most systems do not have a fixed channel on which they operate. in [18], the authors proposed a distributed mac protocol (dah-mac) for a manet. however, dah-mac can only be used in a fully interconnected one-hop environment and only in a single-channel environment. in practice, general manets are multi-hop and multichannel environments. toward addressing the deficits of existing protocols, in this paper, a contention-free token-based mac protocol is proposed for an iot-enabled multichannel multi-hop manet based on cognitive radio. in the proposed protocol, the nodes will be divided into some clusters, and the proposed contention-free reservation mechanism is based on a token ring to ensure qos for iot delay. advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 47 the remainder of this paper is organized as follows. the system model is introduced in section 2. the detailed token-based mac protocol for iot-enabled manets is introduced in section 3. performance evaluation is discussed in section 4, and the final section presents our conclusions. 2. system model in [17], the authors proposed a token-based adaptive mac protocol (ta-mac) for an iot manet. ta-mac can be used only in an existing single-channel and two-hop environment. however, in the real world, channels are a relatively rare and valuable resource. thus, most systems do not operate on a fixed channel, and the system performance when using a single channel will be much poorer than that when using multiple channels. pu gw su pu su fig. 1 system model for cr-based iot-enabled multichannel manet the use of multiple channels will solve the problems associated with the single-channel restriction if the contention among cognitive radio (cr) devices can be overcome in a cr-based iot-enabled manet. furthermore, though ta-mac can be applied to two-hop environments, there are still many problems to be solved before ta-mac can be applied in multichannel and multi-hop manets. these questions include avoiding interference with channel use by pus, switching between pu channels, and ensuring qos. the system model for a cr-based iot-enabled multi-channel manet is shown in fig. 1. 2.1. clustering in the paper, a cr-based mac protocol will be designed for iot multichannel and multi-hop manets. in these networks, the system nodes will be partitioned into several one-hop clusters, meaning the nodes in each cluster must be completely interconnected within the node. each cluster node will sense the pu channels. the idle pu channel with the highest probability of being successfully used will be chosen as the data channel, ensuring the best stability of the obtained data channel. the cluster formation and cluster head are determined by the degree of importance [18]. 2.2. dynamic data channel the token-based mac protocol presented in this paper is based on the tdma scheme. each su in the token-based mac protocol must receive a token to transmit a message. in traditional tdma, each node can transmit messages in its designated time slots, which are assigned in advance. in the proposed system, the receiver and transmitter information will be included in the token and exchanged with the next transmitter. when a node receives a token, it checks the destination address to see whether the address matches its own. if the destination address is not the node’s address, the node discards the token; otherwise, it accepts the token. choosing the data channel is done via a dynamic scheme, with the choice determined by the probability of successfully picking an idle pu channel. only one transceiver is used for each su node to reduce the hardware cost and improve the practical application. the cluster heads will sense the pu channels, and one of the idle channels will be selected as the data channel. the cluster head then broadcasts the data channel to the cluster members by use of a hello frame. the chosen channel is the dynamic data channel. advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 48 3. detailed token-based mac protocol for iot-enabled manet in this paper, time is divided into a number of superframes, each of which has two phases (fig. 2). table 1 shows the symbols used in the data-channel design for our proposed token-based mac protocol. fig. 2 data-channel design of cr-based iot-enabled multichannel manet table 1 symbols used in describing data-channel design for our proposed token-based mac protocol togt length of sub-periods to gateway fromgm number of mini-slots from gateway fromgt length of sub-periods from gateway intram number of mini-slots inside cluster intrat length of sub-periods inside cluster vt length for each data time slot togn number of sub-periods to gateway tog tog vm n t length of togt fromgn number of sub-periods from gateway fromg fromg vm n t length of fromgt intran number of sub-periods inside cluster intra intra vm n t length of intrat togm number of mini-slots to gateway chthresholdp success probability threshold 3.1. control channel in fig. 2, the reservation period is divided into three sub-periods: togt , fromgt , and intrat . the sub-periods have togn , fromgn , and intran time slots, respectively. each time slot of togt , fromgt , and intrat contains some mini-time slots, named togm , fromgm , and intram , respectively. each mini-time slot has length vt , indicating that each node can send data within the slot vt period if the token is obtained at this time. therefore, the lengths of togt , fromgt , and intrat are tog tog vm n t , fromg fromg vm n t , and intra intra vm n t , respectively. in the sub-period togt , su nodes send data to the su gateway in the same cluster, and the gateway node acts as the relay node for multi-hop connections. in the sub-period, the su gateway sends data to su nodes in the same cluster. in the sub-period intrat , sus transmits (pairwise) within the same cluster. when the su source node and the su destination node are not in the same cluster, an appropriate token must be acquired before the end of the two sub-periods togt and fromgt , and the data is then sent in each of the selected sub-time slots togm and fromgm . if the su source node and the su destination node are advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 49 in the same cluster, then an appropriate token is acquired and transmission is completed in the sub-period intrat . whenever a su node sends data, the token is also sent in a round-robin scheme; the token contains the id of the next su node. the selection of the next su node is determined by the su sender that holds the token. the token is preferentially sent to a su node that has not yet obtained the token during the superframe to ensure that allocation of transmission opportunities is fair. 3.2. detailed token-based mac protocol for iot-enabled manet algorithm 1 shows pseudocode for selection of the dynamic data channel in the token-based mac protocol. algorithm 2 shows pseudocode for our proposed token-based mac protocol in cognitive radio ad hoc networks (crahns). algorithm 1: dynamic data channel selection in token-based mac protocol.  clusters formation completed.  each su node sends an important degree to its one-hop neighbors.  the su node with the highest degree of importance among one-hop neighbors is chosen as headsu and announces itself as the cluster head.  the data channel is each cluster will be selected by the cluster head according to an important degree for each channel. if pu active on equals data channel then. headsu searches a new data channel according to an important degree. else continue end if algorithm 2: token-based mac protocol in crahns.  initially, the frame lengths of togt , fromgt , and intrat are equal  isu judges its own role and waits for a token in the sub-periods togt , fromgt , and intrat .  isu checks the number of token accesses among one-hop neighbors, using a token-ring node table  isu sends the token to the next su, choosing the su with the lowest number of token accesses 3.3. sensing-window phase the time-synchronization function of ieee 802.11 is used for synchronization, and the cluster head transmits a hello frame to all cluster members. in previous studies, it is typical to switch to each potential channel when searching for a channel, but listening to each channel consumes more energy than selective listening. additionally, sensing each pu channel may fail due to sudden activity by a pu or to sensing errors. each su must thus check for each pu in each time slot in the sensing-window phase. the duration of each sensing time slot is about the same as the round-trip time when the su listens for a pu. therefore, we will use the probability of success to decide whether to listen to each channel; this proposed scheme reduces energy consumption. the number of time slots in the sensing-window phase is the number of pu channels. each cluster head can adjust its success probability threshold ( chthresholdp ) so as to achieve the highest efficiency. if a su cannot find a pu spectrum to use during the duration of the beacon interval, then this su must find a pu channel during the next beacon interval. each communication will be attempted a maximum of three times. after three failures, communication is advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 50 considered to have failed. when communication has failed, it can remain and contend with other communications in later windows. 3.4. reservation-period phase the reservation period divides the time into a number of time slots and is subdivided into three sub-periods. any node that wants to transmit data must take turns during this period so as to achieve fairness in a probabilistic sense. a su node that obtains the token can transmit data, with the token piggybacked on the data. the token is granted to the next node based on a fairness scheme. if a node is given the token but has no data to transmit, the token is passed to the next node. 3.5. mac protocol dynamic-data-channel table maintenance and frame design to follow the above steps, each su node must maintain a channel-status recording table, a hello recording table, and a token-ring node table. in the iot-based multichannel manet, the hidden problems of inter-cluster and intra-cluster communications can be overcome by the tdma scheme, and qos for data transmission delay can be ensured. in addition, the proposed method also reduces energy consumption by nodes and increases system throughput. table 2 symbols used in control frames for our proposed token-based mac protocol hellosuccessn number of successes chsuccessp probability of successful channel hellofailn number of failures chthresholdp minimum critical probability hellosuccessp probability of success idneighbor number of one-hop neighbors id dvc id for dynamic data channel tokennum number of access tokens received idhead id for cluster head role role of neighbor node chsuccessn number of successes for each channel intra intra vm n t length of intrat chfailn number of failures for each channel chthresholdp success probability threshold idnode id for the node status join, leave, or dissolve in the cluster idnexthop node id of the next-hop idxsu ids for su neighbor sendersu su sender slotreserve number of reserved time slots receiversu su receiver nbrihead number of the neighbor cluster for idhead respower remaining battery energy nbridvc data channel id 3.5.1. hello recording table each su node must maintain a hello recording table that records the number of successes ( hellosuccessn ), the number of failures ( hellofailn ), and the probability of success ( hellosuccessp ). the hello recording table has the following fields (see fig. 3): iddvc , idhead , hellosuccessn , hellofailn , and hellosuccessp . iddvc is the dynamic data channel selected by the cluster head. idhead is the id of the cluster head. iddvc idhead hellosuccessn hellofailn hellosuccessp fig. 3 hello recording table 3.5.2. channel-status recording table (csrt) iddvc idhead chsuccessn chfailn chsuccessp chthresholdp fig. 4 channel-status recording table the cluster head maintains a csrt, which contains the number of successes ( chsuccessn ) and failures ( chfailn ) for each advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 51 channel. the su node selects a channel according to the probability of success. iddvc is the dynamic-data channel selected by cluster head. idhead is the id of the cluster head. chsuccessp indicates the success probability for one channel. chthresholdp indicates the minimum threshold for the success probability of one channel. the csrt has the following fields (see fig. 4): iddvc , idhead , chsuccessn , chfailn , chsuccessp , and chthresholdp . 3.5.3. token-ring node table (trnt) each su node must maintain a trnt to record the status of the tokens in the neighbor nodes in the cluster. the trnt has the following fields (see fig. 5): iddvc , idhead , idneighbor , tokennum , and role . iddvc is the id of the data channel selected by cluster head. idhead is the id of the cluster head. idneighbor contains a list of the ids for one-hop neighbor nodes. tokennum indicates the number of times that the su node received the token. role indicates whether the node is a cluster head, or cluster member or cluster gateway. iddvc idhead idneighbor tokennum role fig. 5 token-ring node table 3.5.4. frame format hello frame: the synchronization frame sent by the cluster head to the su neighbor node. the frame includes two fields (see fig. 6): iddvc and idhead . iddvc is the id of the data channel selected by the cluster head. idhead is the id of the cluster head. iddvc idhead fig. 6 hello format announce frame: a node is to join or leave the cluster or, for the cluster head, to dismiss the cluster. including the following fields: iddvc , idhead , idnode , and status (fig. 7). iddvc is the id of the data channel selected by the cluster head. idhead is the id of the cluster head. idnode is the node id. status indicates whether the node wants to join, leave, or dissolve the cluster. iddvc idhead idnode status fig. 7 announce format the token frame is the format of the field is as follows (see fig. 8): idnexthop iddvc idhead sendersu receiversu 1idsu －－ idnsu idnsu idnsu slotreserve respower nbridvc nbrihead －－ nnbrdvc nbrn head fig. 8 token format there is the node id of the next hop. iddvc is the id of the data channel selected by the cluster head. idhead is the id of the cluster head. sendersu is the sending su . receiversu is the receiving su . 1, ,id idnsu su are the ids of the su neighbors. slotreserve is the number of contiguous time slots that one su can occupy. respower is the battery energy remaining in the su advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 52 transmitting node nbridvc is the id of the data channel selected by the cluster head of the neighboring cluster i . nbrihead is the id of the cluster head of the neighboring cluster i . 4. performance evaluation in our simulation, 10 different topologies are created using 10 different seeds. the results of our simulation show the average values of the 10 different seeds. the simulation is implemented in the c programming language and run on the linux operating system. the traffic is assumed to be uniformly distributed across all nodes with various overall loads. the number of new connections per second is given as an arrival rate. the number of terminated connections per second is given as a departure rate. the multiplicative inverse of the departure rate is also the average lifetime of a connection. “pu on” indicates that a pu is in the active state. “pu off” indicates that a pu is in the idle state. energy detection is easy to implement and commonly used as a spectrum-sensing scheme for sus to sense the active status of pus [19]. the pu active/non-active state is randomly determined in our simulation. the sus is not always-on (i.e., not always transmitting messages), and the number of transmitting sus is not constant. therefore, the number of active pus and sus is not constant, which makes the token-based mac protocol proposed in this paper scalable. because the resources of pus are assigned to and paid for by particular communities (companies, etc.), control by a pu is not impossible in real applications, with the consequence that cognitive radio is a key component of good performance by iot-enabled manets. in all cognitive-radio applications, each node can use two transceivers for transmitting and receiving. in this paper, we need only one transceiver to support both transmission and receiving; we do not need two separate channels. in some scenarios, such as a large assembly, a parade, or a downtown area, there may be hundreds of devices. in the previously described scenario, the requirements for channel bandwidth were high but temporary. in all scenarios, channels are limited resources and controlled by some pus. therefore, a key factor effectively delivering on the promise of the iot is the cognitive radio technique. in our simulation, the number of sus was set to 400 and the number of pus to 8. the transmission ranges for sus and pus were 200 m and 300 m, respectively. the bounding region has dimensions 600 x 600 m 2 . the mean “pu on” duration is 300 s. table 3 shows the parameter values used in the simulation of our proposed token-based mac protocol. table 3 parameter values for our simulation of the proposed token-based mac protocol simulation time 10000 s number of pus 8 number of sus 400 departure rate 0.5 bounding region 600 m*600 m arrival rate 1, …………, 512 transmission range of su 200 m pu sensing error 0%, 10%, 20%, 30% transmission range of pu 300 m mean duration of “pu on” 300 s number of active pus 0, 1, 3 number of seeds 10 the channel spatial reuse,  , is defined as the number of ssu that can simultaneously use one idled licensed channel. we define ɛ as follows: 1 1 1 ( , ) ( ) n m singlei j n multiplei c i j c i         (1) therefore, the throughput per contention window size for this crahn, denoted by  , is defined as follows: [ ] [ ](( 1) data s vacant data ctrl t e ch r e t r n r      (2) advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 53 where datar is the data rate for a pu licensed channel, ctrlr is the data rate for a control channel, st is the duration of each time slot, and  e t is the average duration of a beacon interval for the token-based mac. from fig. 9, we know that the token-based mac produced the highest spatial reuse of channels when the arrival rate was 512. we observed that the highest channel spatial reuse in the token-based mac was 4.33 (corresponding to a channel-detection probability = 1.0 and active pus = 1). fig. 9 comparison of channel spatial reuse in token-based mac as a function of arrival rate under different probabilities of channel detection in a multichannel crahn fig. 10 shows the throughput in the token-based mac as a function of the arrival rate in a multichannel crahn. we observed that the highest throughput in the token-based mac was 8,768 bps under an arrival rate of 256 (corresponding to a channel-detection probability = 1.0 and active pus = 1). fig. 10 comparison of throughput in token-based mac as a function of arrival rate under different probabilities of channel detection in a multichannel crahn fig. 11 shows the average mac contention delay per hop in token-based mac as a function of the arrival rate in a multichannel crahn. the average mac contention delay per hop for token-based mac ranged from 12.61 to 14.59 slots (corresponding to a probability of channel detection = 1.0 and active pus = 1) as a function of arrival rate. advances in technology innovation, vol. 5, no. 1, 2020, pp. 45-55 54 fig. 11 comparison of mac contention delay per hop in token-based mac as a function of arrival rate under different probabilities of channel detection in a multichannel crahn 5. conclusions this paper proposed a protocol that used a token-based dynamic-data channel and dynamic-contention window to achieve high channel spatial reuse, high throughput, energy-efficiency, and a low mac contention delay. in this paper, the proposed token-based mac scheme effectively achieved not only lower mac delay but also better per-hop energy efficiency. the simulation results had a best channel spatial reuse for token-based mac of 4.33, a maximum throughput of 8,768 bps under an arrival rate of 256, and a mac contention delay per hop of 12.61 to 14.59 slots, with the probability of channel detection at 1.0 and number of active pus at 1 for all of these values. it is notable that the channel spatial reuse and throughput decreased when the probability of channel detection decreased. conflicts of interest the authors declare no conflict of interest. acknowledgement the authors would like to thank the editor and the reviewers for their valuable comments and suggestions. this work is supported by ministry of science and technology, 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[19] x. l. huang, g. wang, f. hu, and s. kumar, “stability-capacity-adaptive routing for high-mobility multihop cognitive radio networks,” ieee transactions vehicular technology, vol. 60, no. 6, pp. 2714-2729, july 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 a study on heading and attitude estimation of underwater track vehicle dae-hyeong ji, hyeung-sik cho * , sang-ki jeong, ji-youn oh, seo-kang kim and sam-sang you division of mechanical engineering, korea maritime and ocean university, busan, korea received 03 may 2018; received in revised form 05 august 2018; accepted 24 october 2018 abstract in this paper, we studied the designing and manufacturing of an underwater track vehicle (utv) that can be operated in the underwater environment. we designed the electrical and control system for precise operation of the utv and conduct test operation by using the utv. we developed an attitude reference system (ars) that was composed of the ring laser gyro (rlg) sensor, a geomagnetic sensor, and usbl sensor to estimate precise heading and attitude of the utv. an inertial navigation system (ins) is developed to be combined with the developed ars. also, the ins navigation is configured by supplementing the usbl sensor information. we design a controller for a precise trajectory and attitude tracking by installing the ars on the utv. in this paper, we used an extended kalman filter in the ins to estimate the position and attitude of the utv. the ars is studied to obtain more precise sensor information in an uncertain environment underwater. performance tests of the developed ins using the utv are conducted and the results show that the system has the best performance. keywords: ring laser gyro(rlg), ultra-short baseline(usbl), attitude reference system(ars), inertial navigation system(ins), extended kalman filter(ekf) 1. introduction many kinds of research have been conducted to develop an underwater platform and are capable of observing and moving the ocean with abundant resources and energy [1-2]. fig. 1 is an example of an underwater platform being developed from observation and operation in the water. motion modeling of such an underwater tracked vehicle has been carried out [3]. one of the critical technologies of this marine observation and work platforms is to measure their direction and location information accurately. fig. 1 underwater work platform * corresponding author. e-mail address: hchoi@kmou.ac.kr advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 85 it is very important to obtain the heading information of the navigation sensor to measure its position and the travel direction. among the navigation sensors, ring laser gyro (rlg) is the key sensor to obtain the heading information. attitude reference system (ars) is a sensor system that obtains the heading and position information by using a gyro sensor and geomagnetic sensor [4-6]. [7] implemented mems inertial sensors, the error correction, and algorithms for high performance as the sensor needed to develop low cost and high-performance ars. also, to calculate the posture by integrating the gyro sensor value has a disadvantage is that it drifts due to sensor drift. so, [8] recently implemented ars by using an acceleration sensor and gyro sensor to overcome this drawback of the combination of various sensors. [9] estimated the posture of marg (magnetic, angular rate, and gravity) sensor information of ekf by using quaternion. [10] conducted a study to follow the position of rov in usv by combining imu and usbl. in this paper, we presented the underwater navigation of the underwater track vehicle (utv) which can move on the sea floor. the ars of the hull, which is an important factor of the underwater navigation, were constructed using rlg and a magnetometer. also, a small utv was designed and fabricated to verify the actual sea area of the constructed underwater navigation system. the utv is designed to be able to move on land and sea and to mount various navigational sensors such as gps, depth, imu, usbl on the hull. this paper is organized as follows. section 2 of this paper describes the outline and specifications of the designed utv. section 3 describes the implementation of ars using rlg and magnetometer information. in section 4, the implemented ars was attached to the test-bed and the experiment was performed through the correct step. in section 5, we concluded this paper. 2. underwater track vehicle a small utv was designed to verify the excellent performance of the developed underwater navigation system through experiments in the water tank and the sea area. the designed utv is shown in fig. 2(a). it is a structure equipped with an infinite orbit for movement on the land and seafloor. the external shape is designed to have a length of 1200mm, the endpoint distance of both endless tracks is 700mm and the distance from the bottom to the top is 800mm. depends on the control method, a total of two motors control each caterpillar individually and can be turned forward / backward and left / right. the utv also has various navigational sensors such as gps, depth, imu, and usbl. the picture of the utv is shown in fig. 2(b) and the total weight is about 80kg. the utv is transported to the experimental sea by the ship in the sea area test and is designed to be operated by the power supply and communicate by using the tether cable by descending to the sea floor through the crane in the target sea area. route control and tracking operation are carried on by applying the designed underwater navigation system to utv. (a) design utv (b) produced utv fig. 2 underwater track vehicle advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 86 3. attitude reference system ars, which is an essential sensor in the underwater navigation of utv, was constructed using rlg and a magnetometer. the development of the ars is as follows. 3.1. configuration of the ars the ars is composed of rlg and magnetometer and the addition of the navigation algorithm. the ars using rlg has a problem of integration error of data due to time increase. to reduce the accumulation of integration error, we constructed an extended kalman filter algorithm using gyro data, acceleration data, and geomagnetism data. the block diagram that corrects the integration error accumulation of the sensor data using the extended kalman filter is shown in fig. 3. fig. 3 structure of ars algorithm fig. 3 is a method of calibrating using acceleration and external geomagnetism data. the angular velocity of rlg is integrated by using the relation between euler angle and angular velocity, and the data of roll, pitch, and yaw derived are corrected by the extended kalman filter. the reason for using a similar sensor, gyro, and geomagnetism is to utilize the advantages of each sensor [10-11]. yaw data from the geomagnetic sensor are sensitive to the surrounding magnetic field and has a large error. also, it is greatly affected by the surrounding environment. to grasp this characteristic, we experimented with the characteristics of the geomagnetic sensor and constructed the experimental apparatus using the gyro and acceleration sensor to compare with the experimental data. 3.2. ars testbed the testbed created for the performance test of the ars consists of rlg, mems type attitude, heading reference system (ahrs) that provides information on acceleration data and sensor module including the geomagnetic sensor. the storage and computation of the test device data were handled using an embedded linux processor. fig. 4 shows a diagram of the configuration of the ars. fig. 4 ars diagram advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 87 in fig. 4, the ahrs, gps, and imu sensor data is used for the algorithm that is ported to the embedded linux. the computed data and the stored data are sent to the computer that stores the data in rf wireless communication. to extract the data from the sensors, a device that provides motion was created in the form of a rotating table. the developed equipment is shown in fig. 5. the rotating table was constructed by applying a servo motor with a resolution of 0.088° and arm-m4 series micro-controller was used to configure the system to control the rotation speed and the rotation angle of the motor precisely. the rotating table is shown in fig. 5. the control system of the rotating table is shown in fig. 6. fig. 5 ars test-bed(left) & rotating table(right) fig. 6 composition of turntable control system (a) result of stop test (b) result of exercise test fig. 7 analyze the geomagnetic sensor the performance of the ars placed on the table using the rotating table was tested and the data of the geomagnetic sensor were analyzed. the data of the geomagnetic sensor are shown in fig. 7 as a result of repeated rotation test at the stopping state and the constant angle. as shown in fig. 7, the heading error in the static state of the geomagnetic sensor is shown in fig. 7(a), advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 88 the minimum angle is 0.1° and the maximum angle is 0.3°. as shown in fig. 7(b), the result of each repeated experiment (0°-20°) showed an error of 2.4° or more. also, the overall error in 10 times independent geomagnetic sensor tests did not deviate significantly from the above graph, but the mean range of errors varied finely depending on the surrounding environment. therefore, geomagnetic data in the absence of motion does not show large error, but the operation in the system cannot guarantee data in the system. in an environment that exerts a magnetic force on the periphery, the error value is not linear, so it is found difficult to use by itself. the rlg has a significant advantage that it is not affected by the surrounding magnetic environment. however, since the angular velocity information is provided, integration is required to obtain each information. at this time, the cumulative error occurs with time due to integration. in this experiment, the euler angular data obtained by converting the rlg rotation experiment results into the euler angles and integrating them are shown in fig. 8. it shows the integration error of about 1.5 degrees due to the accumulation of the integration error when the angular velocity of the ring laser gyro is converted into the euler angle and the result is tested for about 10 minutes. fig. 8 result of rlg sensor test magnetic force profoundly influences the geomagnetic sensor. therefore, we designed the system that uses only the sensor providing initial yaw angle information, constructs the ars using the rlg sensor, and processes the sensor data with the extended kalman filter (ekf). the ekf algorithm is constructed as follows. in this system, the state variable of the ekf is denoted by x = [𝜙 𝜃 𝜓]. the system model shows the relationship between the gyro acceleration and the euler angle as shown in eq. (1) [12].   1 sin tan cos tan sin tan cos tan 0 cos sin cos sin 0 sin sec cos sec sin sec cos sec p p q r q w q r w f x w r q r                                                                        (1) since the nonlinear function 𝑓(𝑥) cannot be applied to the ekf, the 𝑓(𝑥) of eq. (1) is partially differentiated for each state variable to obtain the jacobian as eq. (2). 1 1 1 2 2cos tan sin tan sin sec cos sec 0 2 2 2 sin cos 0 0 cos sec sin sec sin sec tan cos sec tan 0 3 3 3 f f f q r q r f f f a q r q r q r f f f                                                                              (2) the ekf is an algorithm for discrete-time. therefore, when the eq. (2) is discretized, the system matrix a is expressed by eq. (3). advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 89 a i dt a   (3) in eq. (3), dt is the sample time and i is the identity matrix. the acceleration and geomagnetism data are used as the correction values and are calculated as shown in eq. (4). 0 sin 0 cos sin 0 cos cos fx u w v p g fy v w u q g fz w v u r g                                                             (4) about 1 1sin sin cos fy fx mag kg g                   ， ， 1 mag mag mag k k   (5) in eq. (4), ϕ and θ are calculated approximately by acceleration and the calculated ϕ and θ have large errors. the correction data ψ is obtained by using the geomagnetism data as shown in eq. (5). by subtracting the first measured data from the measured geomagnetism data, a change in angle can be obtained. the data ψ including the integration error of the rlg is corrected using the angular variation of the geomagnetism data. next, the measured model equation (z) can be calculated from the acceleration data and the geomagnetism data as shown in eq. (6) to measure all three state variables. therefore, it can be expressed by eq. (6). 1 0 0 0 1 0 0 0 1 z v hx v                           (6) eq. (6) does not need to find a jacobian in a linear form with measured values. finally, the system noise covariance and the measurement noise covariance q, r matrix can be measured close to the real one by having equipment that can accurately measure signal characteristics and rlg characteristics. however, since the measurement pieces of equipment are costly, the q and r matrices are considered as design factors and the performance trends are observed and determined. the system design and matrices used for the ekf are obtained through eqs. (1)-(6) and the calculation is performed by applying the ekf according to calculation order. 4. experiments and considerations of ars 4.1. calibration of the ars the corrected data using the correction algorithm was verified by comparing the experimental data. the data was obtained at a sampling time of 100 hz and data of 12, 6400 pieces in about 21 minutes. the measured data are shown in fig. 9 as a graph. in fig. 9, the three graphs located on the left side are rlg data alone and euler angles are converted and integrated. in this case, an integration error of about 2.4° to 3.7° occurred for about 20 minutes. however, after applying the ekf, the integral error hardly occurred. the offsets are 0.3° and 1.2°, respectively, at the roll and pitch angles, are the error with the mechanism that fixes the rlg. next, an experiment was conducted to evaluate the error of posture by rotating forward and backward by repeating the attitude constantly. experiments were carried out in the range of -30° to 0° for a period using the experimental setup of fig. 5. advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 90 about 500,000 data were received for about 83 minutes with a sampling time of 100hz. the measured data are shown in figs. 10-11 are shown. fig. 9 attitude correction in the stationary state in fig. 10, the uncorrected yaw data exhibited an error of more than about 12° during rotation of about -30° to 0° for about 83 minutes. fig. 11 is a graph of geomagnetism data used as correction data. since there is no integration as shown in the graph, there is no integration error. however, it shows a measurement error of 6° to 7° by repeatedly rotating about -30° to 0° for about 83 minutes. fig. 10 yaw angle of raw gyro fig. 11 yaw angle of raw magnetometer the results are shown in fig. 12 as a result of fusing data of figs. 10-11 with an extended kalman filter. in fig. 12, it is shown that there is a slight error in the starting position and the final position due to the mechanical error of the rotating table advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 91 system. therefore, as shown in fig. 12, there is a slight error in the position of the start point and the end position. however, the results of the whole experiment are shown in figs. 10-11 and it can be confirmed that the proposed algorithm does not diverge for about 83 minutes. fig. 12 yaw angle of calibrated ars 4.2. test of platform the calibrated ars was applied to the actual moving platform (utv) to check the performance of the ars under study. the turntable test showed satisfactory performance for the ars under study. however, in application to an actual platform, the performance is affected by the actuating mechanism that generates many vibrations during movement is shown in fig 13; it might cause a little more positioning and attitude errors. fig. 13 test-bed for ars fig. 14 outdoor driving test fig. 15 result of outdoor driving test advances in technology innovation, vol. 4, no. 2, 2019, pp. 84-93 92 the configuration of the utv consisted of the rlg constituting the ars and the correction geomagnetic sensor tcm-3. the ars was installed in the waterproof housing of the utv. also, a similar mems type imu was installed and all the obtained data is recorded using rf wireless communication system in real time. the ars has been developed for underwater usage. however, it is difficult to verify the performance under the water. therefore, the land test was carried out to confirm the performance. the scene of the outdoor test is shown in fig. 14 and the results are shown in fig. 15. fig. 15 shows the result of applying the algorithm and the result of non-using the algorithm. the graph without the algorithm (red color) diverges from the heading angle. during the 10-minute test time, the cumulative error occurred at about 2 °. since the error due to integration increases rapidly with time, data that do not apply the algorithm will quickly diverge in the future. therefore, the current test results show approximately 2° difference between using and non-using the algorithms. if the test is performed for a long time, the error due to integration will increase. despite a lot of vibration while driving on uneven surfaces, the heading data of the ars showed an error of about 0.02° to 0.5°, which is quite small. 5. conclusions in this paper, ars which can acquire the attitude of the underwater vehicle is an essential factor in underwater navigation and is designed by using rlg and magnetometer. also, a small utv was designed and fabricated to verify the performance of the designed underwater navigation system through a water tank and sea area experiment. in the study, the extended kalman filter was used to reduce the integration error of data over time, which is the biggest problem of ars using rlg. then, by using this, an algorithm that efficiently removes the integration error of the yaw angle by correcting it through the fusion of the gyro, acceleration, and geomagnetism data was studied and was implemented in the system. through the turntable experiment, it was confirmed that the cumulative error accumulation amount before the correction was more than 12° in the result of about 83 minutes. the geomagnetism data to correct this error also showed measurement error more than 6° to 8°. as a result of calibrating the gyro data and geomagnetism data with the extended kalman filter, the postural error of about 0.2° to 0.4° in the experiment over 1 hour occurred. this error is also assumed to be caused by the mechanical part of the experimental equipment. the algorithm of the ars was verified by the ars applied to the test-bed. it can be seen that only a slight error of about 0.02° to 0.4° occurred in the straight running of approximately 100m. however, due to the nature of the integral error that rapidly diverges instantaneously, many platform application tests in various situations are required. acknowledgments this research is a part of the project national research foundation of korea (nrf-2016r1a2b4011875) and a part of project titled “r&d center for underwater construction robotics”, south korea (pjt200539), funded by the ministry of oceans and fisheries (mof). conflicts of interest the authors declare no conflict of interest. references [1] t. s. kim, i. s. jang, c. j. shin, and m. k. lee, “underwater construction robot for rubble leveling on the seabed for port construction,” 14th international conference on control, automation and systems, 2014, pp. 1657-1661. 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[13] t. h. chung, k. w. song, and b. j. chang, “design of the kalman filter for transfer alignment of strapdown inertial navigation system,” journal of institute of control, robotics and systems, 1991, pp. 142-146. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 machine vision and deep learning based rubber gasket defect detection chao-ching ho * , eugene su, po-chieh li, matthew j. bolger, huan-ning pan graduate institute of manufacturing technology and department of mechanical engineering, national taipei university of technology, taipei, taiwan received 17 may 2019; received in revised form 08 august 2019; accepted 18 october 2019 doi: https://doi.org/10.46604/aiti.2020.4278 abstract this study develops an automated optical inspection system for silicone rubber gaskets using traditional rule-based and deep learning detection techniques. the specific object of interest is a 5 mm × 10 mm × 5 mm mobile device power supply connector gasket that provides protection against foreign body inclusion and water ingression. the proposed system can detect a total of five characteristic defects introduced during the mold-based manufacture process, which range from 10-100 μm. the deep learning detection strategies in this system employ convolutional neural networks (cnn) developed using the tensorflow open-source library. through both high dynamic range image capture and image generation techniques, accuracies of 100% and 97% are achieved for notch and residual glue defect predictions, respectively. keywords: traditional rule-based strategy, deep learning, convolutional neural networks (cnn), image recognition, image processing, deep residual learning 1. introduction mobile device designers and manufacturers have made considerable efforts to increase the "ruggedness" of their products. one such effort has been the industry-wide adoption of the international electromechanical commission (iec) published inclusion protection (ip) that rates electronic devices according to their protection against solid inclusion and water ingression. as mobile device components have become smaller and ip ratings higher, it has become necessary for manufacturers to be able to detect defects that are a few micrometers in size. defect detection at this scale requires automated optical inspection techniques as traditional instrument-aided methods have been rendered obsolete. the demand for silicone rubber-based components in the mobile device industry to provide tight seals to prevent foreign body inclusion and water ingression has been a boost for taiwanese manufacturers. the strength of taiwanese science and engineering has proved fundamental for the development and manufacture of natural and synthetic rubber products that require complex chemical refinement, bridging, and coloring sequences. rubber mold manufacturing techniques can be broadly classified into three categories: sheet molding, injection molding, and extrusion molding, each of which introduces characteristic defects at varying rates and distributions. as mobile device designers have decreased component size and increased ruggedness requirements, manufacturers have realized the necessity of automated optical inspection techniques for detecting defects a few micrometers in size. furthermore, the non-invasive nature of optical inspection techniques provides the speed necessary for mass manufacturing. in 1980, a. cornforth and c. james proposed a rubber gasket inspection system to identify the void and lamination disband errors between the nylon tip and the rubber ring using an ultrasonic device [1]. recently, systems have been developed for the prediction of silicone rubber solidification time through the optical measurement thickness [2]. furthermore, optical * corresponding author. e-mail address: hochao@ntut.edu.tw advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 77 inspection-based systems to inspect the bubbles present in solid and liquid silicone rubber in the molding process have also been developed [3]. machine vision measurement provides a non-invasive inspection process widely deployed in a broad range of smart manufacturing systems [4-6], e.g. leather production and manufacturing [7], leather defect-recognition [8], solenoid manufacturing [9], and in-process led chip mounting alignment [10]. all the examples mentioned above feature dim and low reflective surface materials which make the proper illumination for defect detection difficult. in our previous study [11], we found that while machine vision-based systems are capable of defect classification performance, the performance of these systems was affected by variation in lighting conditions, and these systems were incapable of qualitative defect detection. therefore, to ensure the homogeneity of the silicone rubber gaskets with its isolated components, a specified on-line measurement system for this application was developed in this study as shown in fig. 1. this study develops a fully automated optical inspection system for silicone rubber mobile device power supply connector gaskets. the defect detection application employs traditional rule-based and deep learning detection methods. recently, several studies have been conducted on the application of deep learning methods for machine vision-based optical inspection systems [12-16]. (a) the silicone rubber gaskets. (b) inclusion (c) notches (d) inner residual glue fig. 1 examined rubber gaskets (a) inclusion defects (b) skewness fig. 2 two types of side layer defects for the silicone rubber gaskets from side-view 2. rule based image detection methodology the mobile device power supply gasket inspection unit has two separate image capture stations, one is the top view and the other is the side view station as shown in fig. 2. the top view station is used to examine three defects: outer ring inclusion, inner ring notches, and inner ring residual glue, whereas, the side view station checks for two defects: top edge inclusion and metal contact leg skewness. 2.1. top-view station the top view station captures the inspected object images using a basler aca2500-14μm monochrome area scan industrial camera, fitted with a 50 mm cctv lens. at the time of inspection, the camera was set to a ×0.343 zoom for a 16 × 12 mm² sensor size and a precision of 6.4 μm/pixel. advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 78 the top view station begins by acquiring multi-exposure images of the silicone rubber seal rings. the image processing application then creates both a contour approximation and a convex hull representation of the outer seal ring. as the eccentricity and straightness of the outer seal ring are rotation invariant, the application uses horizontal and vertical projections to segment the image. the application then calculates the difference in the segmented contour and convex hull representations to predict manufacturing defects as shown in fig. 3. because the top view optical inspection application does not use morphological operations or filtering, the image preserves the geometry of the inspected object at the pixel level. thus, the application can correctly detect inclusion defects as small as 60 μm in size. it is found that traditional rule-based image processing techniques are unable to accurately detect notch and inner residual glue defects because these defects are more qualitative in nature, thereby making them more suitable for deep-learning approaches. fig. 3 top view flowchart using traditional rule based image processing strategy 2.2. side-view station the second inspection station uses a basler ca1600-20μm monochrome area scan industrial camera equipped with an open four-view mirror to capture four side views. while the four-view mirror reduces the overall number of stations needed in the system, it increases the pre-processing time necessary to divide the distinct views as shown in fig. 4. as illustrated in fig. 5(a), the side view defect detection application first partitions the image using a predetermined region of interest (roi). while this roi attempts to consider most variations in the power supply gasket placement, excessively skewed or absent gaskets may lead to unpredictable results. the application uses a binary threshold to the roi. the image processing application segments the image via horizontal projection techniques, which include additional parameters in the segmentation routine to control the magnitude of separation or overlap between the images as presented in fig. 5(b). additionally, a separate metal connection leg absence defect detection application is implemented using contour finding techniques. as shown in fig. 6, the routine centroid calculations are allowed for the labeling of contour centroids to check for potential skew detection. fig. 4 side view flowchart with using traditional rule-based strategy advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 79 (a) side view of region of interest. (b) four view segmentation. fig. 5 region of interest and image segmentation (a) the front metal connection leg absence defect (b) the back metal connection leg absence defect fig. 6 leg absence defect detection using contour finding techniques the flow chart of top edge inclusion detection provides an intuitive explanation of the application logic. as the roi is determined from the orientation of the top edge and subsequent affine transformation, the top edge defect detection allows improper placement of the power supply gasket on the fixture. the roi is narrowed to account for the entire top edge and does not prevent errors that may arise when executing the inclusion finding a routine. the top edge material defects are observed by comparing the contour and convex hull representations of the top edge plastic material, as shown in fig. 7. fig. 7 the detected top edge material defects 3. deep learning approach the top view defect detection application is improved by adding images and type labels to provide a labeling framework for potential machine learning applications. therefore, quantitative information for more qualitative surface defects, namely inner ring notches and residual glue defects [17-18] were provided. to detect the surface type defects of the silicone rubber gaskets which have a rough and dim texture, a multi-exposure technique is used to enhance the illumination and highlight the defects. these multi-exposure images are then included in the dataset and trained in a 50-layer resnet network [19-20]. the pixel size range of the defects is limited to avoid the feature vanishing during the convolution operations of the network and to front back advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 80 allow for more accurate discernment between the background and the defects. moreover, the deep learning approach can indicate the defect types and defect positions within the predicted image. 3.1. deep learning network structure fig. 8 the employed deep learning framework table 1 resnet-50 structure layer name output size resnet 50-layer inputs 224 × 224 × 3 conv1 112 × 112 × 64 7 × 7, 64, stride 2 pool1 56 × 56 × 64 3 × 3 max pool, stride 2 conv2.x 28 × 28 × 256 1 1, 64 3 3, 64 1 1, 256               × 3, stride 2 conv3.x 14 × 14 × 512 1 1,128 3 3,128 1 1, 512             × 4, stride 2 conv4.x 7 × 7 × 1024 1 1, 256 3 3, 256 1 1,1024               × 6, stride 2 conv5.x 7 × 7 × 2048 1 1, 512 3 3, 512 1 1, 2048             × 3, stride 1 pool5 1 × 2048 reduce mean conv6 1 × 2 1 × 1, 1000, stride 1 table 2 rmpnet-50 structure layer name output size resnet 50-layer inputs 112×112× 3 conv1 56 × 56 × 64 7 × 7, 64, stride 2 pool1 56 × 56 × 64 3 × 3 max pool, stride 2 conv2.x 28 × 28 × 256 1 1, 64 3 3, 64 1 1, 256               × 3, stride 2 conv3.x 14 × 14 × 512 1 1,128 3 3,128 1 1, 512             × 4, stride 2 conv4.x 7 × 7 × 1024 1 1, 256 3 3, 256 1 1,1024               × 6, stride 2 conv5.x 7 × 7 × 2048 1 1, 512 3 3, 512 1 1, 2048             × 3, stride 1 pool5 1 × 2048 reduce mean conv6 1 × 6 1 × 1, 6, stride 1 resnet is chosen as the deep residual network because its residual architecture effectively overcomes the vanishing gradient and explosion issues. as the resnet in tensorflow pre-training models and related high-level libraries are available in the open-source community, many comparative data for resnet are available for industrial use. the network proposed in this paper uses a multi-class classifier constructed with resnet 50-layer architecture. part of the resnet structure is modified by reducing the size of the receptive field, and the size of the feature map increased as shown in tables (1)-(2), respectively. the proposed pmpnet network can be seen in fig. 8. the size of the input picture of our proposed network was 112 × 112 pixels, and there is no max-pooling layer. advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 81 fig. 9 the labelled defect types for deep learning 3.2. training and dataset for deep learning network the image of the surface defect and its annotation mask are labeled using the patch-based method. fig. 9 shows the original image and the labeled defect types for deep learning. this work uses the tensorflow open-source software library to develop a deep learning network and the corresponding training classifier. in addition to distinguishing the defects, this proposed method can also identify non-defective background images to increase detection accuracy. the training process is divided into two steps. the first step used the pre-trained model of resnet v1 50-layers for transfer learning. it only trained for five epochs and updated the parameters of the last layer of the convolutional neural network layer. the parameters of the remaining network layers are fixed, the batch size was set to 64, the learning rate is set to 0.001, and the weight decay is set to 0.0004. the second step trained for 50 epochs and updated all network layer parameters, the batch size was set to 64, the learning rate is set to 0.0001, and the weight decay is set to 0.0004. the normalized exponential function is used as the basis of confidence for classifying in the last layer of the network. it is an extension of the sigmoid function and can be termed as the softmax function: 0 j j h j c h j softmax e e    (1) furthermore, mean square error (mse) is used to evaluate the loss function. mse is expressed as: 2 1 1 ˆ( ) n i i i mse n y y    (2) in this study, a common data augmentation method such as mirroring and up and down flipping is used for image preprocessing. 3.3. defect prediction for deep learning network the cutting principle of defect detection is the same as the labeling dataset strategy, although the method and parameters were slightly different. the original large image is cut into several 112 × 112 segment patches in the stride of 64 and the trained defect classifier is used to predict the patches. the fused feature map of the defect category is normalized into a gray-scale map. as deep learning method requires a large amount of data to achieve accurate and efficient results. each silicon rubber gaskets advances in technology innovation, vol. 5, no. 2, 2020, pp. 76-83 82 is rotated by a mechanical turntable to acquire more image data from different lighting angles. the feature map corresponding to different colors according to different types of detected defects is shown in fig. 10. during the prediction stage, the accuracies of the notch and residual glue defects were 97% and 80%, respectively. after rotating the objects under inspection at different angles, a series of images are obtained from different angles for the rubber gasket under evaluation. the collected images are analyzed for deep learning and the classification is chosen with voting. after voting, the prediction accuracies of the notch and residual glue defects were 100% and 97%, respectively. compare to the traditional rule-based image detection approach, the deep learning approach has high classification performance. it can detect non-contour defects (i.e., notches and residual glue) and achieve valid prediction results. fig. 10 the fused feature map after deep learning prediction 4. conclusions in this paper, defect detection for mobile device power supply connector gaskets using rule-based and deep learning image processing techniques is presented. using a rules-based approach, outer ring inclusion and metal contact leg absence defects with 100% accuracy are successfully identified. the inner ring surface notch and residual glue defect detection applications are developed using deep learning approaches. using the pmpnet framework, the overfitting phenomenon is avoided during all the proposed training steps, and the prediction accuracies of 100% and 97% are reached for the notch and residual glue defects, respectively. the high accuracy online inspection system for silicon rubber gaskets is implemented by fusing two different strategies successfully. due to misjudgments caused by the instability of the light source, both approaches are desirable to help determine the stability of the light source processing before the light source correction mechanism. however, these two approaches require manual input to help to evaluate the value of the result. further studies can be investigated to acquire feedback during the training process which will allow computers to make the decisions. acknowledgments the authors would like to thank all of those reviewers who have provided helpful suggestions. we would also like to thank pioneer material precision technology for providing all the experiment samples. conflicts of interest the authors declare no conflict of interest. references [1] a. cornforth and c. james, “ultrasonic system for the inspection of rubber gaskets,” ndt international, vol. 13, no. 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[20] r. f. wei and y. b. bi, “research on recognition technology of aluminum profile surface defects based on deep learning,” materials, vol. 12, no. 10, may 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 6__aiti#5635__191-198 advances in technology innovation, vol. 6, no. 3, 2021, pp. 191-198 effects of bi 3+ ion-doped on the microstructure and photoluminescence of la0.97pr0.03vo4 phosphor hao-long chen1, hung-rung shih2, sean wu3, yee-shin chang4,* 1department of mechanical engineering, national pingtung university of science and technology, pingtung, taiwan 2department of mechanical and computer-aided engineering, national formosa university, yunlin, taiwan 3department of digital game and animation design, tungfang design university, kaohsiung, taiwan 4department of electronic engineering, national formosa university, yunlin, taiwan received 04 may 2020; received in revised form 04 may 2021; accepted 05 may 2021 doi: https://doi.org/10.46604/aiti.2021.5635 abstract the objective of this paper is to enhance the emission intensity of la0.97pr0.03vo4 single-phased white light emitting phosphor. the bi3+ ion-doped la0.97pr0.03vo4 single-phased white light emitting phosphors are synthesized using a sol-gel method. the structure and photoluminescence properties of (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphor are also examined. the xrd results show that the structure of la0.97pr0.03vo4 phosphors with different concentrations of bi3+ ion doping keeps the monoclinic structure. the sem results show that the phosphor particles become smoother when the bi3+ ion is doped. the excitation band for la0.97pr0.03vo4 phosphor exhibits a blue shift from 320 nm to 308 nm as the bi3+ ion contents are increased. the maximum emission intensity is achieved for a bi3+ ion content of 0.5 mol%, which is about 30% greater than that with no bi3+ ion doped. the cie chromaticity coordinates are all located in the near white light region for different bi3+ ion-doped la0.97pr0.03vo4 phosphors. keywords: sol-gel method, pr3+ ion, sensitizer, phosphors, flux 1. introduction rare-earth ion-doped oxide-based phosphors have been the subject of many studies because of their excellent optical properties [1]. they are widely used in various optical devices, such as plasma display panels (pdps), field emission displays (feds), and light-emitting diodes (leds) [2]. white light-emitting diodes (w-led) perform better than traditional incandescent and fluorescent lamps [3-4]. a w-led is produced using a blue ingan chip with commercial y3al5o12:ce3+ (yag:ce) yellow-emitting phosphors [5-6]. unfortunately, this combination yields a low color-rendering index because there is no red-light-emitting component [7-8]. recent advances in single-phased white light emitting phosphors, [9-10] have many applications for w-leds. for the vanadate groups, lanthanum orthovanadates (lavo4) has many applications. lanthanum orthovanadates have two types of crystal structure: monoclinic (m-) monazite and tetragonal (t-) zircon [11-12]. monoclinic lavo4 is the thermodynamically stable state, and m-monazite based materials are used in laser host materials [13], solar cells [14], and thin film phosphors [15]. a previous study results show that the cie chromaticity coordinate is located in the white light region with x = 0.388 and y = 0.367 when the m-monazite lavo4 is doped with pr3+ ion at a concentration of 3 mol% produced using a sol-gel method [16]. * corresponding author. e-mail address: yeeshin@nfu.edu.tw advances in technology innovation, vol. 6, no. 3, 2021, pp. 191-198 the sol-gel method requires a low synthesis temperature, achieves higher purity, mixes activators well, and produces nano-scale particle powders [17-18]. many studies enhance the photoluminescence properties of phosphors and improve the particle morphology by flux addition or by doping with different radius ions [19-20]. doping with different radius ions is the simplest and most effective method. for example, the emission intensity for bala1.5eu0.5zno5 phosphors with 70 mol% ba2+ ion substituted by sr2+ ion is 62% greater than that for phosphors with no sr2+ ions, and 33% greater than that for commercial red sulfide phosphors [zns:(mn2+, te2+)] [20]. in order to increase the emission intensity of la0.97pr0.03vo4 phosphor, the bi3+ ion-doped la0.97pr0.03vo4 phosphors are synthesized using a sol-gel method in this study. the crystal structure, surface morphologies, and the photoluminescence properties of bi3+ ion-doped la0.97pr0.03vo4 phosphors are also determined. 2. experimental method (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphors are synthesized using a sol-gel method with the raw materials of ammonium metavanadate (nh4vo3), lanthanum acetate [la(ch3co2)3], and praseodymium acetate [pr(ch3co2)3]. these starting materials with a purity of 99.99% are supplied by aldrich chemical company, inc. a solution of ammonia (nh4oh) is added to the nh4vo3 solution to accelerate dissolution, and the lanthanum acetate and praseodymium acetate are separately dissolved in deionized water. citric acid is used as the raw material and mixed using di water as a solvent. after mixing, the solution is stirred and heated at 120°c for 5 h, and then is placed in an oven at 120°c for drying. finally, the powders are calcined in a furnace at 950°c for 6 h in air using a heating rate of 4°c /min. the structural characterization of these samples is analyzed by x-ray powder diffraction (xrd, bruker axs), using cukα radiation with a source power of 30 kv and a current of 20 ma. the morphologies of the phosphor powder are determined using the scanning electron microscopy (fe-sem, hitachi s4800-i). a hitachi u-3010 uv visible spectrophotometer is used to measure the optical absorption behavior of the (la0.97-ybiy)pr0.03vo4 phosphor. the samples are placed inside a closed quartz glass and measured from 200 to 700 nm at room temperature. both of the excitation and the emission spectra for the phosphors are measured at room temperature using a hitachi f-7000 fluorescence spectrophotometer with a 150 w xenon arc lamp as the excitation source. 3. results and discussion the surface morphologies of the phosphor particles must be as smooth as possible, with a high degree of crystallization, to ensure good photoluminescence efficiency. 3.1. xrd and fe-sem characterization the x-ray powder diffraction patterns for (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphors calcined at 950°c in air for 6 h using a sol-gel method are shown in fig. 1. the crystal structure of different concentrations of bi3+ ion-doped la0.97pr0.03vo4 phosphors is monoclinic for lavo4 (jcpds no. 70-2392). there is no secondary phase if the bi3+ ion concentration is increased because the bi3+ ion (1.03å) and la3+ ion have similar radii (1.032å) [21] and the same valence. therefore, a solid solution is formed when the la3+ ion is substituted by bi3+ ion in the host material. fig. 2 shows the fe-sem surface morphologies of (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphors calcined at 950°c for 6 h in air. the particle shapes are irregular and there are aggregations. for the bi3+ ion concentration is 0.5 mol%, the particles become smooth, granular, and more uniform in size. a liquid-phase sintering behavior is observed when the bi3+ ion concentration is more than 0.5 mol% because the bi3+ ion oxidizes with o2ion to form bi2o3 during the calcination process in air. bi2o3 has a lower melting point of 815°c and acts as a flux in the calcination process, so the phosphor particles coagulate 192 advances in technology innovation, vol. 6, no. 3, 2021, pp. 191-198 due to the surface tension of the liquid when the fluxes melt. the melted fluxes also enable the phosphor particles to slide and rotate easier, so there is greater particle-particle contact and particle growth increases [22]. when the fluxes melt sufficiently, the liquid-phase sintering leads metal oxide particles to aggregate. fig. 1 the x-ray diffraction patterns of (la0.97-ybiy)pr0.03vo4 phosphors calcined at 950°c for 6 h in air (a) 0 mol% (b) 0.2 mol% (c) 0.5 mol% (d) 1 mol% fig. 2 fe-sem micrographs of la0.97pr0.03vo4 doped with various bi3+ ion concentrations calcined at 950°c for 6 h in air 3.2. luminescence properties the absorption spectra of (la0.97-ybiy)pr0.03vo4 phosphors calcined at 950°c for 6 h in air are shown in fig. 3. for la0.97pr0.03vo4 phosphor, there are two broad absorption peaks in the absorption spectrum from 200 to 350 nm, which correspond to the o2and v5+ charge transfer for the vo4 3internal anions [23-25]. the absorption band from 280 to 350 nm centered at 315 nm is attributed to the 4f-5d characteristic transition absorption of a pr3+ ion because typical pr3+-activated oxide phosphors always demonstrate strong 4f-5d transition band absorption at approximately 200-330 nm [26-27]. there are small absorption peaks from 440 to 500 nm and 580 to 620 nm, respectively, which are corresponding to the inner 4f orbital characteristic transition of the pr3+ ion. the different concentrations of bi3+ ion do not affect the curves shape but do affect the intensities of the excitation and emission peaks. fig. 4 shows the excitation spectra for (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphor calcined at 950°c for 6 h in air. the signals are detected at 489 nm. there are two excitation bands in the excitation spectra. the first one from 200 to 350 nm centered at 315 nm is attributed to the charge transfer from the oxygen ligands to the central vanadium atom inside the vo4 3− 193 advances in technology innovation, vol. 6, no. 3, 2021, pp. 191-198 anionic group, which overlaps the 4f-5d characteristic transition of the pr3+ ion at the absorption band in (la0.97-ybiy)pr0.03vo4 phosphor. the other one centered at 448 nm is attributed to the 3h4→ 3p2 electronic transition of the pr3+ ion inner 4f orbital [28]. fig. 3 absorption spectra for (la0.97-ybiy)pr0.03vo4 phosphors that are calcined at 950°c for 6 h fig. 4 excitation spectra for (la0.97-ybiy)pr0.03vo4 phosphors that are calcined at 950°c for 6 h (the signals are detected at 489 nm) the intensity of the excitation peak increases significantly if la0.97pr0.03vo4 is doped with 0.5 mol% of bi3+ ion and then decreases as the bi3+ ion concentrations increases further. it is due to the extra absorption involving the bi-o component in addition to the v-o charge transfer bands. in this study, the excitation wavelength is 315 nm, which is in good accordance with the 1s0→ 3p1 transition (a-band) for the electron level transition of bi3+ ion [29]. therefore, the role for bi3+ ion-doped la0.97pr0.03vo4 phosphor in this study is to be a sensitizer. the excitation peak intensities are decreased when the bi3+ ion concentration is higher than 0.5 mol%, because an increase in the bi3+ ion concentration causes the phosphor particles to aggregate. it can dissipate the absorbed energy in the form of non-radiation rather than transfer it to the pr3+ ions [30]. however, it can be observed that there is a blue shift for the excitation band from 320 nm to 308 nm as the bi3+ ion contents increased. this may be the reason for the special empirical rule, that is substitutions of the dodecahedral la3+ by larger ions leading to spectral red shift and smaller ions leading to blue shift for most of the phosphor modification system [31]. fig. 5 shows the emission spectra for (la0.97-ybiy)pr0.03vo4 phosphors calcined at 950°c for 6 h in air under an excitation of 315 nm. at 315 nm excitation, there is no emission peak of the bi3+ ion observed in the emission spectra, but there are emission peaks in the visible light region at 480-520, 530-570, 580-610, 610-620, and 625-650 nm, which respectively correspond to the 3p0→ 3h4, 3p0→ 3h5, 1d2→ 3h4, 3p0→ 3h6, and 3p0→ 3f2 electron transitions of pr3+ ions. the 1d2→ 3h4 transition is more intense than that for 3p0→ 3h4 at a low doping concentrations of pr3+ ion (x = 0.005-0.02), but the intensity decreases if the pr3+ ion concentration increases further (x = 0.03-0.1) [32]. it is due to the difference in the ionic radii of la3+ 194 advances in technology innovation, vol. 6, no. 3, 2021, pp. 191-198 ion and pr3+ ion, which may compress the pr-o bond in the host lattice when a slight pr3+ ion concentration doped. this results in a strong crystal field effect causing the stark splitting of the multiplet structure which leads the 4f-5d state of the pr3+ ion to shifts to a lower energy state that is closer to the 1d2 state, causing the emission intensities of the 1d2→ 3h4 transition to be higher than that of 3p0→ 3h4 transition. the results for this study show that the 3p0→ 3h4 transition is greater than the intensity of the 1d2→ 3h4 transition because the pr3+ ion concentration is fixed of 3 mol%. therefore, the cie chromaticity coordinates are located in the white light region (x = 0.388, y = 0.367). fig. 5 emission spectra for (la0.97-ybiy)pr0.03vo4 phosphors calcined at 950°c for 6 h under an excitation of 315 nm according to the results in the emission spectra, the intensity of emission peaks increases as the concentrations of bi3+ ion in la0.97pr0.03vo4 phosphor increase. the co-doped with bi3+ ions can increase an absorption in the ultraviolet region (315 nm) because the bi3+ ion acts as a sensitizer in the la0.97pr0.03vo4 phosphor. a good sensitizer absorbs the excitation energy and transfers energy to a luminescent center (activator), but does not play a role as a luminescent or quenching center. more energy is absorbed and transferred to the pr3+ ions via the bi3+ ion, so the emission intensity of the la0.97pr0.03vo4 phosphor increases. there is a maximum intensity of emission peak when the bi3+ ion concentration is 0.5 mol%. these results show that the sensitization effect of bi3+ ion on the pr3+ emission behavior varies with the bi3+ ion concentrations. as can be seen in the emission spectra, the emission peak appearances are attributing to the characteristic electronic transition of pr3+ ion. there is no bi3+ ion emission peak observed, because the bi3+ acts as a sensitizer for doping in the la0.97pr0.03vo4 phosphor. the excitation wavelength, 315 nm, is not only absorbed by lavo4 host, but also absorbed by bi3+ sensitizer and pr3+ ion, respectively. the 4f-5d characteristics transition absorption of pr3+ ion usually overlaps with the oxygen ligands to the central vanadium atom inside the vo4 3− anionic group. therefore, the energy (315 nm) is supposed firstly to be absorbed by the lavo4 host, bi3+ ion, and the pr3+ ion to the conduction band, the 3p1 level, and the 4f-5d state, respectively. the energy in the 4f-5d state of pr3+ ion relaxes to a lower state of 3p0, and both of the energies in the conduction band and the 3p1 level are all transferred to the 4f-5d state of the pr3+ ion. simultaneously, these energies from 4f-5d state relaxes rapidly to the lowest emission level, 3p0 and 1d2, via non-radiative transition, and finally transits from 3p0 to the 3hj, j=4, 5, 6 and the 3f2 state, respectively, and from 1d2 to 3h4 state. the mechanism for energy absorption and transfer for la0.97pr0.03vo4 phosphor doped with bi3+ ion is shown in fig. 6. fig. 7 shows the cie color coordinate diagrams for (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphors, y = 0.005, 0.01, 0.02, 0.03, 0.05, and 0.1. for the la0.97pr0.03vo4 phosphor with no bi3+ ion doped, the emission color is in the near white light region with the cie chromaticity coordinates of (x = 0.388, y = 0.367). for phosphors that are doped with bi3+ ions, different concentrations of bi3+ ion do not affect the shape of curves, but the intensity of the emission spectra changes. therefore, the cie color coordinates for la0.97-ybiypr0.03vo4 phosphor are all located in the near white light region. 195 advances in technology innovation, vol. 6, no. 3, 2021, pp. 191-198 fig. 6 the mechanism for the absorption of energy and transfer for la0.97pr0.03vo4 phosphors doped with bi3+ ion under an excitation wavelength of 315 nm fig. 7 cie color coordinate diagrams for (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphor 4. conclusions the (la0.97-ybiy)pr0.03vo4 (y = 0-0.05) phosphors were synthesized using a sol-gel method at a calcination temperature of 950°c for 6 h in air. when doped with bi3+ ions, the crystal structure of (la0.97-ybiy)pr0.03vo4 is monoclinic structure of lavo4, and there are no secondary phases. the surface morphologies of (la0.97-ybiy)pr0.03vo4 phosphors become smoother and more granular as the bi3+ ion concentration increases. the role for a bi3+ ion in the la0.97pr0.03vo4 phosphor system not only can be a flux, but also acts as a sensitizer. under excitation at 315 nm, the emission intensity increases as the concentration of the bi3+ ion 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[32] l. g. teoh, m. t. tsai, y. c. chang, and y. s. chang, “photoluminescence properties of pr3+ ion-doped yinge2o7 phosphor under an ultraviolet irradiation,” ceramics international, vol. 44, no. 3, pp. 2656-2660, february 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 198  advances in technology innovation, vol. 1, no. 1, 2016, pp. 07 12 7 copyright © taeti benefit analysis of emergency standby system promoted to cogeneration system shyi-wen wang department of electrical engineering, chienkuo technology university, changhua, taiwan. received 03 march 2016; received in revised form 25 april 2016; accepted 30 april 2016 abstract benefit analysis of emergency standby system combined with absorption chiller promoted to cogeneration system is introduced. economic evaluations of such upgraded projects play a major part in the decisions made by investors. time-of-use rate structure, fuel cost and system constraints are taken into account in the evaluation. therefore, the problem is formulated as a mixed-integer programming problem. using two-stage methodology and modified mixed-integer programming technique, a novel algorithm is developed and introduced here to solve the nonlinear optimization problem. the net present value (npv) method is used to evaluate the annual benefits and years of payback for the cogeneration system. the results indicate that upgrading standby generators to cogeneration systems is profitable and should be encouraged, especially fo r those utilities with insufficient spinning reserves, and moreover, for those having difficu lty constructing new power plants. keywords: emergency standby system, cogeneration system, time-of-use rate structure, mixed-integer programming, nonlinear optimization 1. introduction a marked increase in the cost of constructing a generation, transmission and distribution system have also resulted in higher demand charges to customers in the past few years. to reduce the system's peak load and therefore reduce the system's idle stand-by capacity, seasonal and time-of-day (or peak-load pricing) rate structures are usually applied by the utilities. this has increased the benefit of peak shaving by using dispersed-storage-and-generation (dsg) systems [1]. when made a part of an energy management system (ems)[2] or distribution dispatch center (ddc) of a utility system, dsg may provide benefits to utilities by reducing system peak load, improving reliability, and increasing operation efficiency, which implies that the opportunity cost of generation can thus be reduced by the dsg. cost reductions or avoided costs result from saving of both capital carrying charges and operation expenses. however, additional capital investment will be required fo r the dsg, so the benefit obtained by the utility should be shared with participating customers to promote the dsg. two customer incentives for dsg are that it allows a time-of-use (tou) rate structure based on the peak-load pricing theory and reduced fuel costs. considering the tremendous quantities of waste heat generated in the production of electricity, it is apparent that there is an opportunity to save fuel by a cogeneration system (cgs). cgs can be described as the simultaneous generation of electrical or mechanical power and usable energy by a single energy conversion system [3]. it has long been common here and abroad. currently, there is renewed interest in cgs because the overall energy efficiencies are claimed to be as high as 70 to 85%. reducing the cost of electricity for industrial and commercial users, reliev ing excessive demand on utilit ies, and using fuel efficiently are certainly worthwhile goals. however, carefu l planning in design and operation is necessary to meet these goals. therefore, in this paper, a novel optimal operation scheme for small cogeneration systems that are upgraded from standby generators is introduced. * corresponding author, email: wshin@ctu.edu.tw advances in technology innovation, vol. 1, no. 1, 2016, pp. 07 12 8 copyright © taeti 2. method fig. 1 illustrates the structure of a small cgs investigated in this paper. the sample cgs system is upgraded from a 100 kw gas-engine-driven standby generator by adding an absorption refrigerator and other necessary accessories. the hot-water capacity of this absorption refrigerator is 50 rt. the electricity demands of the system are usually supplied from a public electric utility. however, the cogenerator may operate in a parallel manner to optimize the energy supplies of both the electricity and cooling demands for some suitable time period. in order to optimize the operation procedure, the parameters of the system are obtained by field testing the sample cgs under fu ll and some partial load conditions. on the basis of the data of the field tests, the fuel cost curve of this system can be obtained by the curve-fitting techniques as shown in fig. 2 by the dotted line when the fuel cost is 7.84 nt$/m 3 . in th is system the heat recovered by the absorption chiller is transformed to equivalent power and so is deducted from the power demand of the cen t rifugal ch iller. on the gas engine absorption chiller exhaust boiler centrifigual chiller gcity gas generator purchased electricity mixing tank pump water steam exhaust air exh aust air space cooling demand exhaust air electricity demand fig. 1 structure of a gas-engine cogeneration system fig. 2 fuel-cost curve of the sample cgs system contrary, for the conventional standby generator the on ly output is electric power. its power output curve is also shown in fig. 2 for comparison with that of the cgs. 2.1. problem formulation for customers with a cgs that is upgraded from a standby generator, the total operating cost can be expressed simply as the sum of the payments for electricity to the electric utility and for gas consumption to the gas company. the monthly electricity cost that is the cost function of the optimal operation scheduling of a cgs is proposed as follows:     ),0(++ + +),( 30 24 1 cddmaxrcdr hppsd tphpocpsf mpcd gigiii i igigii      (1) where i: time interval psi: pseudo switch used to indicate the on/off (1/0) status of cgs during time interval i oc(pgi, hgi): operation cost of the cgs during time interval i (nt$/h) pgi: output power of the cgs during time interval i (kwh) hgi: equivalent power of recovered heat of the cgs during time interval i (kwh) tpi: tou rate structure during time interval i (nt$/kwh) di: demand during time interval i (kwh) rcd: rate when demand is under the contract capacity rp: rate if demand exceeds contract capacity cd: contract capacity dm: monthly maximum demand on the basis of the formulat ion of the cost function, the optimal operation scheme of the sample cgs and the optimal use of power fro m the utility can therefore be determined, ultimately, so as to minimize the monthly electricity cost. control variables of this optimization problem include binary and continuous variables that correspond to the on/off status and the load level of cgs, respectively. thus, this problem is formulated as a mixed-integer programming problem. 2.2. optimal operation scheme using a two-stage methodology and a modified mixed-integer programming technique, 0 50 100 150 200 250 300 20 40 60 80 100 120 140 c o st ( n t /h ) power output (kw/h) sta n… advances in technology innovation, vol. 1, no. 1, 2016, pp. 07 12 9 copyright © taeti a novel algorithm is developed and introduced here to solve the nonlinear optimization problem. in the first stage, the reduction of the capacity charge for power due to the decrease of contract capacity caused by installation of the cgs is not take into consideration. therefore, at this stage a linear programming algorithm can be applied. however, in the second stage the neglected factor is taken into account and the decomposition and alternative policy method is adopted [4]. the total operating cost of cgs during each time interval can be expressed as :   )p(dtppocf giiigii  1,2...24i  (2) where pgi is the sum of the electric power and heat output of the cgs. the heat should be converted to its equivalent electric power before the summat ion can be made. the fuel cost curve shown in fig. 2 can therefore be formulated as : oc(p ) k p k p kgi 1 gi 2 gi 3     2 1,2...24i  (3) the coefficients k1, k2, and k3 depend on the type, capacity, and maker of the cgs. substituting (3) into (2), and then minimizing the obtained equation by linear programming techniques, the optimal operating capacity of the cgs for each time interval can be obtained as follows: p (k tp ) / (2k )giom 2 i 1  i 1,2...24 (4) from (4), it is clear that fuel cost (k1,k2) and tou rate structure (tpi) are two important factors in determining the optimal operation capacity. the constraint of the generator output of the cgs is p p pgmin giom gmax  i 1,2...24 (5) where pgmin ： minimum generator output of the cgs pgmax ： maximum generator output of the cgs the minimum and maximum outputs of the sample cgs are 30 kw/h and 150 kw/h, respectively. the time interval is set to one hour in this paper. the optimal operation benefit during each time interval can therefore be expressed as: be tp p oc(p )iom i giom giom   i 1,2...24 (6) equation (6) shows that the optimal operating benefit is gained from the difference between the savings gained by reducing the electricity charge and the cost of operating the cgs. the following steps describe the optimal operation scheme in which the benefit gained by the reduction of contracted electricity capacity is considered: step 1: evaluate the optimal operating capacity using (4). in this step, the reduction of the electricity capacity charge due to the decrease of contract capacity made possible by installation of the cgs is neglected. step 2: sort the hourly loads so that they are in descending order, that is d dj j+1 j 1,2,...23 (7) and record the corresponding hour of each hourly load. the demand differences between maximum hourly load and every hourly load can be calculated as: ed d dj 1 j 1   j 1,2,...23 (8) in which d1 is the maximum hourly load. therefore, if the reduction of the electricity demand charge due to the decrease of contract capacity made possible by installation o f the cgs is neglected, the optimal operating capacity of the cgs during each pseudo time period (j) is : p max(p ,ed )gj gjom j j 1,2,...23 (9) step 3: the optimal operating benefits for various operating hours are advances in technology innovation, vol. 1, no. 1, 2016, pp. 07 12 10 copyright © taeti be tp p oc(p ) + r ed / 30k j gj gj j 1 k cd k      k 1,2,...24 (10) step 4: select the maximum operating benefit from step 3. be max(be )max k k 1,2,...24 (11) therefore, the optimal operation scheme of the cgs for each pseudo time is : 1,...24+kk,=j 1,2,...k=j 0 p p gj gj     (12) step 5: reorder (12) by the actual t ime order using the record built at step 2. the daily maximum demand can be decreased as : )pmax(dd giimd  i 1,2,...24 (13) step 6: print out the optimal operation schedule, operation benefit, daily maximum demand, and then stop the process. 3. results and discussion on the basis of the proposed algorithm, a program has been developed. three sample customers: a hotel, a hospital and an office building are used to demonstrate the proposed algorithm. the sample cgs is assigned to operate six months per year, from june through september in all cases. tou rates of taipower are applied for all sample customers. furthermore, the cgss of the hotel and hospital are assumed to operate 30 days a month and 24 days for that of the office building. 3.1 the demand pattern of sample customers fig. 3 shows the daily demand patterns for air conditioning, electricity, and total demand of the three sample customers in the summer. relatively larger hourly demands for electricity occur in the sample hotel in the period between 11:30 and 23:00, and the total demand holds almost constant between 11:00 and 21:00. on the other hand, the total demand of the sample hospital is almost constant between 9:00 and 21:00. there are lunch hours between 12:00 and 14:00. the demands of the sample office building are more concentrated, and result in a lower load factor. (a) hotal (b) hospital (c) office building fig. 3 daily demand patterns on the summer 3.2 optimal operation capacity of the sample cgs fig. 4 shows the optimal operation capacity and operation benefit for various fuel costs. for example, fig. 4-(a) indicates that if the fuel cost is 6.272 nt$/m 3 the optimal operation capacity is 53 kw/h and operation benefit is negative (-72). therefore, it is not worthwhile to operate the cgs in off-peak periods. fig. 4-(b) shows that the operation benefit is positive for peak periods. hence it is worthwhile to operate the sample cgs when the fuel cost is lower than 8 nt$/m 3 . for example, if fuel cost is 6.272 nt$/m 3 , the optimal operation capacity is 150 kw/h, that is, the maximum capacity of the sample cgs. in this case the operation benefit is 62 nt$/h. advances in technology innovation, vol. 1, no. 1, 2016, pp. 07 12 11 copyright © taeti (a) off-peak period (tou rate structure is 0.77 nt$/kwh) (b) peak period (tou rate structure is 1.89 nt$/kwh) fig. 4 optimal operation capacity and operation benefit for tou rate structure of taiwan 3.3 optimal operation scheme of sample customers figs. 5 show the opt imal operat ion scheme for fuel costs o f 9.408 nt $/m 3 . for each hourly load, op t imal generat ing capacity of cgs, and the amount o f power being purchased are shown. fig . 5-(a) shows that the maximum daily operat ion benefit o f the sample hotel is p roduced by operat ing the cgs eleven hours (from 12:00 to 22:00) per day . the generat ing capacit ies at t ime intervals 14, 15, 17, and 18 are lower than opt imal capacity . hence, the generat ing capacit ies o f the cgs are set at the opt imal capacity , that is , 117.99 kw /h . 3.4 economic analysis the net present value (npv) method is used to evaluate the annual benefits and years of payback [5]. fig. 6 shows the annual benefits of using the cgs for the sample customers at various fuel costs. in general, the more the load coincides in t ime is, the greater the benefit obtained. the numerical results of the payback analysis for the sample customers are shown in fig. 7. (a) hotel (b) hospital (c) office building fig. 5 optimal operation scheme at fuel cost 9.408 nt$/m 3 fig. 6 annual benefit advances in technology innovation, vol. 1, no. 1, 2016, pp. 07 12 12 copyright © taeti fig. 7 return of investment for various fuel cost 4. conclusions a novel optimal operation scheme for small cogeneration systems upgraded from standby generators has been introduced in this paper. on the basis of the proposed algorithm, a p rogram has been developed. then three sample customers are used to demonstrate the proposed algorithm. the benefits and cos ts of these sample cases are examined. the fuel cost, time-of-use rate structure and system constraints are taken into account in the evaluation. the results indicate that upgrading standby generators to cogeneration systems is profitable and should be encouraged, especially for those utilit ies with insufficient spinning reserves, and moreover, for utilit ies having difficulty constructing new power plants. acknowledgement the support of the ministry of science and technology (taiwan), under grant most 104-2221-e-270-001 is gratefully acknowledged. references [1] t. gonen, electric power distribution system engineering, new york: mcgraw-hill, 2008. [2] r. c. dugan, m. f. mcgranaghan, s. santoso, and h. w. beaty, electrical power systems quality, new york: mcgraw-hill, 2004. [3] public utility regulatory po licies act, report no. 95-1750, conference report, oct. 10, 2001. [4] s. ashok and r. banerjee, “optimal operation of industrial cogeneration for load management,” ieee trans. power syst., vol. 18, no. 2, pp. 931-937, may 2003. [5] k. methaprayoon, w. j. lee, s. rasmiddatta, j. r. liao, and r. j. rose, “multistage artificial neural network short-term load fo recasting engine with front-end weather forecast,” ieee trans. ind. appl., vol. 43, no. 6, pp. 1410–1416, nov./dec. 2007. [6] c. t. hsu, c. s. chen, and c. h. lin, “electric power system analysis and design of an expanding steel cogeneration plant,” ieee trans. ind. appl. , vol. 47, no. 4, pp. 1527-1535, jul./aug. 2011. [7] c. h. hsu, “a graph representation for the structural synthesis of geared kinematic chains ,” journal of the franklin institute, vol. 330, pp. 131-143, jan. 1992. 1___aiti#6939__199-212 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 tea verification using triplet loss convolutional network kun-yi chen1, chi-yu chang1, zhi-ren tsai1, chun-ting lee 2 , zon-yin shae1,* 1 department of computer science and information engineering, asia university, taichung, taiwan 2 department of psychology, asia university, taichung, taiwan received 30 december 2020; received in revised form 17 august 2021; accepted 18 august 2021 doi: https://doi.org/10.46604/aiti.2021.6939 abstract to solve tea image classification problems, this study focuses on triplet loss convolutional neural network to classify six high-mountain oolong tea classes. in the experiment, instead of using traditional deep learning training approach for local feature of tea images, an innovative image verification approach is proposed to learn the global feature of tea images by integrating the distributed tea leaves’ features of all tea sub-images and using a majority voting mechanism to do classification. the results show that the proposed approach can work for small sample size dataset and have higher accuracy than normal transfer learning approach. the average accuracy of the proposed approach achieves 99.54%. keywords: convolutional neural network, tea image classification, tea image verification, triplet loss 1. introduction tea is a vital export product for many countries to sustain their economic growth. each year, there are at least six million tons of tea were produced globally [1]. in taiwan, the price difference between high quality tea and inferior quality tea often reaches hundreds of us dollars. however, farmers who produce high quality tea often suffer from tea mixing issue, i.e., some middlemen mix the inferior quality tea with high quality tea and re-sell it as high quality tea products to earn extra margins. this can jeopardize the sustainability of local tea markets because of losing customers’ trust. to help tea famers deal with this issue, tea industry conventionally applies biochemical techniques, such as dna markers, mass spectrometry, gas-chromatography, or high performance liquid chromatography, to analyze tea samples and trace their original sources [2-3]. however, due to the fact that these techniques are time-consuming and have high costs, computer vision approaches were proposed in recent years as an alternative way to complement their disadvantages; the computer vision approaches often combine with signal processing algorithms or machine learning algorithms to extract tea image features [4-6]. this research aims to develop an image verification approach through majority voting mechanism, which can learn the global feature of tea images by integrating all tea sub-images’ features, in order to help smallholder tea farmers address tea mixing issue. by using image cropping and majority voting, the proposed approach can work for small sample size dataset and have higher accuracy than traditional deep learning training approach. the remainder of this study is arranged as follows. section 2 explains how the initial experiment and two observations influence the proposed experiment design. section 3 describes tea dataset details. sections 4 and 5 show the proposed approach for tea image classification and its algorithms. section 6 describes the whole image-preprocessing process, including the standardized procedure for photograph tea images and detailed image processing method. sections 7 and 8 present the proposed model architecture and experiment results. finally, section 9 concludes the study. * corresponding author. e-mail address: zshae1@asia.edu.tw tel.: +886-4-2332 3456 #1729 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 2. initial experiment and observations there are six high-mountain oolong tea classes in this study (for detailed dataset description, see section 3). the initial attempt to classify these tea classes is to use normal transfer learning training approach (fig. 1), which has three parts: image pre-processing, image augmentation, and model training. in the experiment, four pre-trained models (pre-trained weight using imagenet), i.e., xception, vgg16, inceptionv3, and inceptionresnetv2 models [7-10], are used to classify tea classes. the overall transfer-learning model architecture with its parameters and neural layer information can be seen in fig. 2. the first part in fig. 1 is image pre-processing, where all tea images are resized to 299 × 299 pixel size with three color channels. the second part, data augmentation, is used to mitigate small data size issue. data augmentation methods used in the experiment including randomly image rotation (0 ~ 30 degree), randomly horizontal flip, and randomly vertical flip. through initial experiment, the result shows that the normal transfer learning training approach performs poorly for tea image classification task (table 1). in table 1, the first column displays several pre-trained deep learning models applied for tea classification. the third column shows the test accuracy of each trained model. the result shows that none of these models’ accuracy is greater than 70%, which suggests that the normal transfer learning training approach is not suitable for the dataset in this study. table 2 shows models’ hyperparameters; the same hyperparameters are used for all models. the low accuracy issue can be explained from two perspectives. first, the small data size used to train models can result in model overfitting. as illustrated in fig. 3, the model overfitting tendency can be observed from the changes of validation loss, which shows that the training data is not enough. the reason of only using 360 tea images is that the application scenario of the study is to develop a tea image verification technique for smallholder tea farmers. therefore, small data size is inevitable in this study and becomes a research problem to be solved via algorithm design. second, there may be some distinct properties between traditional images and tea images such that the normal transfer learning approaches do not work. here, traditional image means the images without distributed objects, such as tea leaves. to examine the rationality of the above-mentioned explanations for low accuracy, two observations are conducted. fig. 1 normal transfer learning approach in this study fig. 2 architecture of additional four dense layers table 1 classification accuracy of training and testing data for oolong tea dataset in different pre-trained models using transfer learning pre-trained models accuracy of training data accuracy of testing data xception 73.75% 60.00% vgg16 65.83% 69.99% inceptionv3 25.00% 20.00% inceptionresnetv2 18.75% 16.67% 200 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 table 2 parameters and hyperparameters of models transfer learning weight loss function optimization function additional dense layers epochs learning rate imagenet categorical cross-entropy rmsprop 4 500 1e-5 fig. 3 historical loss values in training process of inceptionv3 model using normal transfer learning approach for the first observation, two algorithms, i.e., gradcam++ and smoothgrad [11-12], are used to visualize the pre-trained artificial intelligence (ai) model’s activation map and saliency map. in fig. 4, there are three images presenting goldfish, dog, and tea. the goldfish and dog images are defined as traditional images because they do not include distributed objects as targets to be classified. the result of activation map and saliency map shows that: for traditional deep learning training approach, the model initially learns the low level local features from the image, such as edge and color, then integrates these low level local features into high level features, such as noses, eyes, and ears, and finally recognizes the image as an object, such as a dog’s face or a goldfish. however, unlike traditional images, tea image do not have local features, as shown in the activation map and saliency map. tea image’s global feature is distributed into many objects, such as tea leaves and sticks. therefore, these distributed objects’ feature need to be captured so that the image can be classified into the class it belongs to. fig. 4 activation map and saliency map of gradcam++ and smoothgrad visualization algorithms for the second observation, a tea image is cropped into many sub-images, and all sub-images look similar (fig. 5). it can be seen that in a hypothetical feature space, the tea sub-images that belong to the same image should cluster together as their feature properties are statistically similar. to examine this idea, k-means are used to find the five most significant colors in the two tea classes (class 0 and class 3), and t-distributed stochastic neighbor embedding (t-sne) algorithm is applied to plot these color feature vectors on a two-dimentional map (fig. 6). each dot in the figure represents a single sub-image. the red dots represent class 0’s cropped images and the blue dots represent class 3’s sub-images. the result suggests that the same class’s sub-images will cluster together in the feature space, and the two tea classes can be classified by using only tea color information. 201 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 fig. 5 tea sub-images that belong to the same image fig. 6 t-sne plot of two tea classes using the five most significant color information the first observation using model visualization algorithms shows that the feature property between tea image and traditional image are different, i.e., distributed objects’ feature property (tea images) versus non-distributed objects’ feature property (traditional images). the second observation using k-means clustering algorithm and t-sne algorithm finds that tea sub-images which belong to the same tea class have similar feature property, and suggests that: (1) small sample size problem may partially be solved by cropping every image into sub-images without distorting original tea image’s property; (2) by leveraging tea image’s unique characteristics, a new prediction method can be used to improve model’s performance (see section 5.3.). these two observations support the idea that there exist some distinct properties between traditional images and tea images thus traditional deep learning training approach is not suitable to train tea images. 3. dataset there are six high-mountain oolong tea classes’ samples collected in the study (table 3 and fig. 7). each tea class has 60 images. 48 images are split for training set, 6 images are split for validation set, and 6 images are split for testing set. there are several reasons that make this dataset a challenging model training task for tea image classification comparing to the datasets of previous tea image classification studies [4-5, 13-16]. first, all tea classes belong to the same tea type (high-mountain oolong tea), meaning that all tea classes have the same tea product processing procedure. second, among tea classes, only class 3 has different tea varieties. in addition, tea class 0, 1, and 2 belong to the same tea variety and they are planted in the same mountain; the only difference among them is their mountain adrets, meaning that they receive different sunlight degrees and angles while growing. finally, the small data sample size is challenging. it is known that deep learning models perform well when trained with large amount of data and perform poorly when the training data size is small, so why in this study the small sample size dataset is used to train model? the main reason is that this study’s application scenario is for smallholder tea farmers whose tea products often go through middlemen before reach consumers, thus the amount of tea products each farmer can produce for every season is low. therefore, it is reasonable to expect that the amount of image data obtained from original tea products is rather little. 202 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 table 3 information of six high-mountain oolong tea classes tea classes tea varieties places of origin note class 0 chin-shin-oolong hehuan mountain, nantou county adret: north class 1 chin-shin-oolong hehuan mountain, nantou county adret: east class 2 chin-shin-oolong hehuan mountain, nantou county adret: southwest class 3 taiwan tea experiment station (ttes) no. 12 zhushan township, nantou county class 4 chin-shin-oolong ali mountain, chiayi county class 5 chin-shin-oolong lugu township, nantou county (a) class 0 (b) class 1 (c) class 2 (d) class 3 (e) class 4 (f) class 5 fig. 7 images of six high-mountain oolong tea classes 4. experiment design fig. 8 shows the overflow of the proposed approach to solve model convergence problem. this approach has five stages: image acquisition, image pre-processing, model training, and model evaluation. there are three innovative parts in the proposed approach. first, in image pre-processing stage, a tea image cropping process is added to get tea sub-images. second, in model training stage, convolutional neural network (pre-trained inceptionv3 model) and xgboost (extreme gradient boost tree) algorithm [3] are combined as a single model. third, in model evaluation stage, instead of inputting sub-images directly to the trained model for prediction, a majority voting mechanism is added to evaluate model performance. fig. 8 the proposed approach for tea image classification 5. algorithms 5.1. triplet loss triplet loss is a metric learning [17]. it selects three tea images (�����, �����, and �����) from any two tea classes, where ����� is called anchor image, ����� is called positive image, and ����� is called negative image; ����� and ����� belong to the same tea class and ����� belongs to a different tea class. the training goal is to minimize the l2 distance between anchor image and positive image (��,� ��� ������ � ������) as they are same tea class images, and maximize the l2 distance between anchor image and negative image (��,� ��� ������ � ������) as they are different tea categories images. in order to enlarge the learned distance between ��,� ��� and ��,� ���, a margin which is greater than 0 is also added: , , ( ) ( ) n a p a n i i i margind d +  − + ∑ (1) 203 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 when using triplet loss in model training, one tea class is labeled as positive category and other five tea classes are labeled as negative category. since there are six tea classes, six models can be trained, each time assigning one class as positive category and other five classes as negative category. for example, if tea class 0 is labeled as positive category, then tea class 1 ~ class 5 will be labeled as negative category. 5.2. majority voting after a test image is cropped into multiple tea sub-images and input to the trained model for evaluation, the majority voting mechanism will calculate how many percentage of tea sub-images are predicted as positive category and negative category, and the model’s accuracy is obtained (algorithm 1). for example, if a model is trained as class 0 being positive category and class 1 ~ class 5 being negative category; when a test image that belongs to class 0 is input, its sub-images predicted as class 0 will be counted as positive category, and its sub-images predicted as class 1 ~ class 5 will be counted as negative category. if the same tea sub-images’ feature properties are statistically similar as fig. 7 shows, most class 0’s sub-images should be predicted as positive category in this example (fig. 9). algorithm 1: majority voting abbreviations pc: positive category nc: negative category ppos: prediction percentage of sub-images input: tea images in the test set output: model’s accuracy 1 true_positive = 0 2 false_positive = 0 3 true_negative = 0 4 false_negative = 0 5 for each_image in test_set: 6 if image’s_label == pc: 7 if ppos_in_pc > ppos_in_nc: 8 true_positive += 1 9 else: 10 false_positive += 1 11 if image’s_label == nc: 12 if ppos_in_nc > ppos_in_pc: 13 true_negative += 1 14 else: 15 false_negative += 1 16 model_accuracy = ���_���� ��� � ���_���� ��� � ��_ �� _�����_������ � 100% fig. 9 illustration of how majority voting works if the second observation is correct 204 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 6. image-preprocessing 6.1. data acquisition due to tea image’s sensitivity to brightness, shadow, and angle rotation changes, a standard operation procedure (sop) is set to photograph the tea leaves. if tea image quality is low, then it is difficult to converge the model. (1) sop goal: get a batch of clear and high-resolution tea photos with uniform brightness. (2) tools: 1. a paper box, having a size of 1/4 a4 paper area (fig. 10). 2. a table lamp. 3. six zipper storage bags. 4. a camera. in this study, iphone 7 plus camera is used. the information about this camera are as follows: a. dual 12mp wide-angle and telephoto cameras. b. wide-angle: ƒ/1.8 aperture; telephoto: ƒ/2.8 aperture. c. 2x optical zoom. d. autofocus with focus pixels. e. automatic exposure control. f. backside illumination sensor. g. hybrid ir filter. (3) procedure: 1. preparation stage: a. pour tea leaves from the vacuum packaging into a zipper storage bag. b. put table lamp at paper box’s left side. 2. photograph stage: a. pour tea leaves from the zipper storage bag into paper box. b. shake the paper box to spread the tea leaves evenly on the paper. c. photograph the tea leaves using camera. each image must have good focus, high resolution, and uniform brightness. d. repeat above steps (step a ~ c) until the desired image number is achieved. e. finally, check image quality. replace unqualified image with new image. fig. 10 paper box template 6.2. image pre-processing there are three steps in tea image pre-processing stage: step 1: assume an image’s size is x × y, where x is the shorter side. (in this study, the image resolution is 3412 × 1920 pixels.) this image is cropped into x × x (fig. 11). step 2: the second step is cropping the surrounding 100 pixels of image, in order to remove the paper box wall part in the image (fig. 12) to get a new image (image size: (x-200) × (x-200)) and resize the new image to 1536 × 1536 pixels (fig. 13). 205 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 step 3: the third step is cropping the square image into multiple 450 × 450 pixels sub-images where each sub-image is cropped for every 20 pixels spacing. the image cropping procedure serves two purposes: the first purpose is to examine the effectiveness of majority voting, which originates from the second observation; the second purpose is for data augmentation, which increases data sample size by cropping image into sub-images. finally, all sub-images are resized into 224 × 224 pixels and converted into gray scale images (figs. 14 and 15). these final gray scale sub-images will be input to the model for training. fig. 11 step 1 in image pre-processing stage fig. 12 the paper box wall part in the tea image fig. 13 step 2 in image pre-processing stage fig. 14 step 3 in image pre-processing stage (a) class 0 (b) class 1 (c) class 2 (d) class 3 (e) class 4 (f) class 5 fig. 15 oolong tea classes gray scale sub-images 206 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 7. experiment 7.1. machine learning model the whole model is composed of two sub-models: the first sub-model is a pre-trained inceptionv3 model (weight: imagenet) plus three additional layers, and the second sub-model is xgboost model. fig. 16 shows overall model architecture and layer shape information. table 4 and table 5 show the two sub-models’ parameters and hyperparameters. in training process, n 224 × 224 pixels gray scale training sub-images are input to the pre-trained inceptionv3 model conducting transfer learning. after the first trained sub-model is obtained, these n sub-images are input to the first trained sub-model for prediction, and n 128-dimentional embedding vectors are obtained. finally, these vectors are input to train the xgboost model. fig. 16 model architecture and neural layer shape table 4 parameters and hyperparameters of inceptionv3 model optimization function epochs learning rate loss function triplet loss threshold value inceptionv3 adaptive moment estimation (adam) 5000 1e-6 triplet loss 0.001 table 5 parameters and hyperparameters of xgboost model model class number tree depth epochs learning rate tree number of boosting iterations xgboost 6 20 500 0.1 20 7.2. hardware and software programs are run on nvidia dgx-1 machine, which has 8 gpus (tesla v100-sxm2) and 80 cpus (20-core intel® xeon® e5-2698). for software, python v3.6.7 is used with modules tensorflow (1.15.0), xgboost (v0.90), ipython (v7.5.0), matplotlib (v3.1.0), scikit-learn (v0.19.1), pandas (v0.24.2), and numpy (v1.16.2). 207 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 8. experiment results table 6 shows the experiment result using the proposed approach. the test accuracy of all models is greater than 97%, which is better than normal transfer learning training approach. fig. 17 shows the majority voting result of class 0 ~ class 5 oolong tea test images using “class 0 as positive category” model, which shows that the test sub-images that belong to class 0 get higher prediction percentage in positive category and the test sub-images that belong to class 1 ~ class 5 get the higher prediction percentage in negative category. in each sub-plot, the x-axis is test image sequence and y-axis is sub-images prediction percentage of positive category and negative category. positive category label is presented as red dots and negative category label is presented as blue dots. fig. 17 suggests that the second observation is correct, meaning that the tea sub-images that belong to the same image have similar property, thus they should cluster together on the feature space. this implies that if an image belongs to positive category, most of its sub-images should be predicted as positive category. in the appendix, figs. 18-22 show the majority voting results of class 0 ~ class 5 oolong tea test images using class 1 ~ class 5 as positive category models. table 7 shows the result comparison between the proposed work and the previous work. table 8 shows other model’s performance using class 0 as positive category. table 6 classification accuracy of testing data using the proposed approach and other publications’ results pre-trained inceptionv3 models accuracy of testing data class 0 as positive category 100.00% class 1 as positive category 97.22% class 2 as positive category 100.00% class 3 as positive category 100.00% class 4 as positive category 100.00% class 5 as positive category 100.00% (a) class 0 (b) class 1 (c) class 2 (d) class3 (e) class 4 (f) class 5 fig. 17 the sub-images prediction percentage results of class 0 ~ class 5 oolong tea test images using “class 0 as positive category” model 208 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 table 7 the comparison between the proposed work and the previous work ref. models tea types total sample number average accuracy this work pre-trained inceptionv3 model + xgboost + majority voting 6 high-mountain oolong tea classes (among them, 5 classes belong to the same tea variety.) 360 images 99.54% [4] 12-layer convolutional neural network 3 tea classes including green tea, oolong tea, and black tea 900 images 98.33% [5] histogram equalization + gray-level co-occurrence matrix + support vector machine (svm) 10 tea classes from different brands and origins, including 1 white tea, 2 different kinds of flowering tea, 2 different kinds of green tea, 1 oolong tea, and 4 different varieties of black tea 3000 images 94.64% [15] principal component analysis + linear discriminant analysis 5 green tea classes from different varieties, brands, and origins 120 images 98.33% [16] fuzzy svm + winner-take-all method 3 tea classes including green tea, oolong tea, and black tea 300 images 97.77% table 8 classification accuracy of testing data using the proposed approach pre-trained models accuracy of testing data (class 0 as positive category) vgg16 100.00% xception 100.00% inceptionresnetv2 100.00% 9. conclusions this study proposed an image verification approach to improve deep learning model’s performance. the result outperforms normal transfer learning training approach in the challenging tea dataset. future studies can explore feature engineering methods to extract tea image’s feature properties and complement the lack of interpretability of deep learning model. in addition, the proposed approach may have broader application to other crop types, such as rice, coffee bean, wheat seed, etc., which seem to have similar distributed objects’ feature with tea images. acknowledgments this research is partially supported by the ministry of science and technology through both the center of precision medicine research and artificial intelligence research center of asia university taiwan under the grants ski most 110-2321-b-468-001, most 110-2321-b-468-001, and 108-2511-h-468-001-my3. conflicts of interest the authors declare no conflict of interest. references [1] v. voora, s. bermúdez, and c. larrea, “global market report: tea,” https://www.iisd.org/publications/global-market-report-tea, december 16, 2019. [2] w. pongsuwan, e. fukusaki, t. bamba, t. yonetani, t. yamahara, and a. kobayashi, “prediction of japanese green tea ranking by gas chromatography/mass spectrometry-based hydrophilic metabolite fingerprinting,” journal of agricultural and food chemistry, vol. 55, no. 2, pp. 231-236, january 2007. [3] w. shao, c. powell, and m. n. clifford, “the analysis by hplc of green, black and pu’er teas produced in yunnan,” journal of the science of food and agriculture, vol. 69, no. 4, pp. 535-540, december 1995. [4] y. d. zhang, k. muhammad, and c. tang, “twelve-layer deep convolutional neural network with stochastic pooling for tea category classification on gpu platform,” multimedia tools and applications, vol. 77, no. 17, pp. 22821-22839, september 2018. [5] y. chen, “identification of tea leaf based on histogram equalization, gray-level co-occurrence matrix and support vector machine algorithm,” international conference on multimedia technology and enhanced learning, april 2020, pp. 3-16. 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[10] c. szegedy, s. ioffe, v. vanhoucke, and a. alemi, “inception-v4, inception-resnet and the impact of residual connections on learning,” https://arxiv.org/pdf/1602.07261.pdf, august 23, 2016. [11] r. r. selvaraju, m. cogswell, a. das, r. vedantam, d. parikh, and d. batra, “grad-cam: visual explanations from deep networks via gradient-based localization,” ieee international conference on computer vision, october 2017, pp. 618-626. [12] d. smilkov, n. thorat, b. kim, f. viégas, and m. wattenberg, “smoothgrad: removing noise by adding noise,” https://arxiv.org/pdf/1706.03825.pdf, june 12, 2017. [13] l. zhang, advances in forest management under global change, london: intechopen, 2020. [14] x. li, p. nie, z. j. qiu, and y. he, “using wavelet transform and multi-class least square support vector machine in multi-spectral imaging classification of chinese famous tea,” expert systems with applications, vol. 38, no. 9, pp. 11149-11159, september 2011. 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[17] f. schroff, d. kalenichenko, and j. philbin, “facenet: a unified embedding for face recognition and clustering,” ieee conference on computer vision and pattern recognition, june 2015, pp. 815-823. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). appendix the appendix shows the sub-images’ prediction percentage results of class 0 ~ class 5 oolong tea test images using class 1 ~ class 5 as positive category models (figs. 18-22). (a) class 0 (b) class 1 (c) class 2 (d) class3 (e) class 4 (f) class 5 fig. 18 the sub-images prediction percentage results of class 0 ~ class 5 oolong tea test images using “class 1 as positive category” model 210 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 (a) class 0 (b) class 1 (c) class 2 (d) class3 (e) class 4 (f) class 5 fig. 19 the sub-images prediction percentage results of class 0 ~ class 5 oolong tea test images using “class 2 as positive category” model (a) class 0 (b) class 1 (c) class 2 (d) class3 (e) class 4 (f) class 5 fig. 20 the sub-images prediction percentage results of class 0 ~ class 5 oolong tea test images using “class 3 as positive category” model 211 advances in technology innovation, vol. 6, no. 4, 2021, pp. 199-212 (a) class 0 (b) class 1 (c) class 2 (d) class3 (e) class 4 (f) class 5 fig. 21 the sub-images prediction percentage results of class 0 ~ class 5 oolong tea test images using “class 4 as positive category” model (a) class 0 (b) class 1 (c) class 2 (d) class3 (e) class 4 (f) class 5 fig. 22 the sub-images prediction percentage results of class 0 ~ class 5 oolong tea test images using “class 5 as positive category” model 212 microsoft word 3-aiti#5966 21-30.docx advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 corona and electric field distribution analysis in 400 kv line insulators ragaleela dalapati rao 1,* , padmanabha raju chinda 1 , meduri kiran 2 1 department of electrical & electronics engineering, p.v.p siddhartha institute of technology, vijayawada, india 2 electrical design engineer, leoni, waterloo, canada received 03 july 2020; received in revised form 17 september 2020; accepted 05 november 2020 doi: https://doi.org/10.46604/aiti.2021.5966 abstract the performance of insulator strings in transmission lines can be improved by corona rings owing to their electric field grading property. the insulation performance of the string depends on the corona ring parameter settings. in this study, the design of a corona ring for a 400 kv non-ceramic overhead line insulator is presented. two parameters were altered during the investigation, ring measurement (r) and ring tube breadth (r) while maintaining a constant ring height (h). based on electric field distribution, the proposed composite insulators were compared with glass insulators. simulation studies were performed for the insulator strings, including corona rings with different design parameters. the corona discharge and optimal configuration results were analyzed, and it was found that the electric field was lower with composite insulators. keywords: corona ring, electric field distribution, potential distribution, glass insulators, silicon rubber insulators, comsol software 1. introduction insulators can be categorized into suspension and line post insulators [1]. suspension insulators (such as porcelain and glass) are mainly used for stress stacking. however, generally non-ceramic insulators (ncis) are used these days. nci’s are also called polymeric or composite insulators. silicon rubber has good electrical properties and climate obstruction properties over a wide range of temperatures and is utilized in lodging. it is resistant to oxidation and deterioration from ultraviolet radiation and has low surface vitality. these properties settle on the silicon rubber and it can be effectively used for electrical insulators [2]. previous studies have shown that the electric field distribution along composite insulators can be enhanced by incorporating various corona ring designs, which can also limit the corona ring related issues. extremely strong electric fields can offer ascent to a group of ionization in the encompassing air that comes full circle in the arrangement of corona releases [3]. one of the key procedures engaged with the inception and improvement of releases is the ionization of particles and atoms by high vitality electrons. without any extremely applied electric field, the electrons move arbitrarily colliding with the gas atoms [4]. within the sight of the electric field, be that as it may, the electrons are excited by the electric field and velocity toward the field [5]. the corona discharge occurs on the transmission-line conductors when the strength of the electric field on the conductor surface is greater than a specific value. this results in power loss, audible noise, production of gaseous effluents, and light [6]. in non-uniform fields, the self-sustained release is constrained within the air gap, and the corona discharge occurs as a result of the “partial breakdown”. there are various modes of the corona discharge: alternating current (ac) corona and direct current (dc) corona. the underlying process of the ac corona discharge in every half cycle of the ac power frequency is fundamentally the same as those under dc voltages of the same polarity. under ac * corresponding author. e-mail address: raga_233@yahoo.co.in tel.: +91-9949418868 advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 22 voltage, the corona initially shows up in the negative half cycle as trichel streamers. as the voltage is increased, trichel streamers begin to spark. in the following positive half cycle, the breakdown streamer follows the sparkle corona [7]. the positive corona discharge is a significant source of the radio interference voltage (riv) and audible noise, and it causes deterioration of the rubber housing on the ncis. therefore, the corona should be avoided as much as possible while avoiding too much over-designed. contingent upon the utilization and physical layout of a silicon insulator, a corona ring is generally introduced at the transmission line end to ensure line voltages of 230 kv. nevertheless, the utilization of corona rings decreases the dry arcing separation of insulators. therefore, it is important to structure the corona ring for the ideal review of the electric stress along the insulator. this study investigates the electric field and potential distributions of glass and silicon rubber insulators. the results are obtained by utilizing the comsol multi-physics software. the simulation results demonstrate that for the values acquired for the silicon rubber insulator with a corona ring (particularly for 220kv), the potential distribution along the insulator can be improved. moreover, the electric stress can be decreased further for the insulator with the corona rings, compared with those of the insulators without corona rings and glass insulators [8]. to comprehensively understand the corona mechanisms and provide potential mitigation solutions, the corona onset and corona ring optimization are discussed in section 2. the comsol modeling assumptions, related specifications, and the simulation results, including electric field, and potential distributions are provided in section 3. the corona ring design is optimized based on 15 different ring sizes. the conclusion in section 4 summarizes this study. 2. corona onset the corona onset is defined as the occurrence of a self-sustained discharge. townsend’s law defines: (1) the ionization coefficient α as the number of electron-particle sets formed in the gas by a single electron traveling through a unit distance separation toward the development of the electron. (2) the attachment coefficient � as the likelihood that a free electron will join itself to an unbiased molecule to form a negative particle while moving through a unit distance separation through the gas toward the applied electric field. therefore, the equation can be expressed as dxxndn ))(( ηα −= (1) where α is the ionization coefficient and � is the attachment coefficient. integrating eq. (1) on both sides: x 0 dn (α η)dx n(x) = −∫ ∫ (2) therefore, eq. (2) becomes: 0 ( ) 0 x dx n n e −∫= α η (3) where n0 is the number of electrons at x=0. now, if the electric field intensity is strong enough, the total number of electrons below approaches infinity (that is self-sustained discharge), thereby causing breakdown: advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 23 0 0 ( ) 1 x dx n n e − = ∫− α η γ (4) in other words, the breakdown occurs when 0 ( ) 1 x dx e −∫= α η γ (5) where � is the secondary ionization coefficient in eqs. (4) and (5) [6]. as defined above, the corona onset is characterized as the phenomenon of a self-sustained discharge. an observational equation was proposed in a previous study [9] based on smooth cylindrical conductors given in eq. (6) [6]: 0 [1 ]a gc c c c e me r = +δ δ (6) where egc is the corona onset gradient in kv/mm e0c is an empirical constant of 2.11 kvrms/mm ca is an empirical constant that peek [9] determined to be 0.301 cm -1/2 m is the conductor irregularity factor δ is the relative air density, and rc is the radius of the conductor in meters for the purpose of simulations in this study, a corona inception threshold of 2.2kv-rms/mm has been considered [10]. 2.1. corona ring designs fig. 1 corona ring sizes along with their part numbers [11] as a result of all the negative corona effects, an attempt has been made to control the field distribution along the strings through the corona rings [12] and to protect the insulator string from direction power arcs [13]. standard corona rings [14-15] (manufactured by hubbell power systems inc.) for transmission insulators are shown in table 1 and fig. 1 [11]. (where kip is kilo pound and kn is kilo newton). advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 24 table 1 standard transmission corona rings by hubbell line voltage (kv) recommended corona rings based on line voltage corona ring part numbers ground end line end 25kip, 30kip, 120kn, 133kn 50kip, 160kn, 210kn ground end line end ground end line end 220/230 none 8 inches (203mm) 2717613001 2717613002 330/345 none 12 inches (305mm) 2717053001 2717053002 400 8 inches (203mm) 12 inches (305mm) 2717613001 2717053001 2717613002 2717053002 500 8 inches (203mm) 15 inches (381mm) 2717613001 2717513001 2717613002 2717513002 2.2. corona ring optimization as shown in fig. 2 [10], the different specifications of corona rings are given below [16]: (1) ring measurement (r) (2) ring tube breadth (r) (3) position of the ring in its vertical plane (h) fig. 2 corona ring optimization specifications [17] fig. 3 new vs. old corona rings [18] by changing any one or a combination of these specifications, the resulting electric field distribution can be modified [19-22]. in this study, it is assumed that h is a constant and the r and r values are optimized. before the further discussion on advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 25 the simulation parameters and optimization, it is worthwhile to present a laboratory case study on a 133 kv dead-end line insulator. to demonstrate the effect of corona on small and large ring sizes, the ring sizes of 4 inches and 8.25 inches have been considered. two different ring diameters have been considered as shown in fig. 3 [7]. table 2 illustrates that the smaller old design based ring (4 inches) clearly exhibits more corona activities compared with the new design based ring (8.25 inches) for 133kv and 146kv, as observed using a laboratory camera. table 2 laboratory results comparing new and old design based corona rings with old corona ring (4 inches) with new corona ring (8.25 inches) 133kv (100% voltage) 146kv (110% voltage) 3. results and analysis in this study, the overall analysis can be divided into two categories. one part of the analysis is based on the comparison between the glass and silicon suspension insulators to study the electric field distribution (part 1). the other part (part 2) of the analysis considers the silicon suspension insulators with corona ring optimization for 15 different ring sizes. the modeling assumptions of the suspension insulators are outlined in table 3. the mesh settings [23] for both glass and silicon rubber insulators are shown in figs. 4-6. the materials used for the simulations are listed in table 4 [24-25]. the finite element analysis in comsol has been performed using stationary and frequency domain (60 hz) solvers. table 3 modeling assumptions of suspension insulators insulator number length (mm) glass 20 (cap-and-pin) 3400 silicon rubber 50 (identical silicon sheds) 1700 fig. 4 mesh settings advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 26 fig. 5 glass insulator meshing fig. 6 silicon rubber insulators with corona ring meshing table 4 materials used in simulations materials electrical characteristics relative permeability (µr) electrical conductivity (σ) relative permittivity (εr) steel aisi 4340 1 4.032e6 s/m 1000 silicon 1 1e-12 s/m 3 glass (quartz) 1 1e-14 s/m 4.2 air 1 0 s/m 1 3.1. part 1 the electric field distribution and potential distribution of glass insulators for the different scenarios are shown in figs. 7-8 (comsol screenshots). the electric field and potential distributions of silicon rubber insulators for the different scenarios are shown in figs. 9-10. the 3-d plots of these insulators are shown in figs. 11-12. the maximum electric field of the glass insulator on the line-end conductor is obtained at 14.83kv/mm corresponding to r = 11 mm and h = -3400 mm as shown in fig. 7. similarly, fig. 9 shows the maximum electric field on the line-end conductor of the silicon rubber insulator, obtained at 3.03 kv/mm, corresponding to r = 18 mm and h = -1700 mm. (a) streamlines (b) overall (c) ground end (d) line end fig. 7 electric field distribution of glass insulators for different scenarios therefore, from these figures, it is noted that silicon rubber insulators are prone to less stress (minimum electric field distribution) and the improvement of potential distribution along the insulator is contrasted with that of the glass insulators. advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 27 because the maximum surface conductor electric field is higher than the corona inception threshold of 2.2 kv/mm in the silicon rubber insulator, the corona discharge will be observed. accordingly, the application of corona rings to silicon rubber insulators is discussed in section 3.2. (a) overall (b) ground end (c) line end fig. 8 potential distribution of glass insulators for different scenarios (a) overall (b) ground end (c) line end fig. 9 electric field distribution of silicon insulators for different scenarios (a) overall (b) ground end (c) line end fig. 10 potential distribution of silicon insulators for different scenarios (a) electric field distribution (b) potential distribution fig. 11 3-d plot of glass insulators advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 28 (a) electric field distribution (b) potential distribution fig. 12 3-d plot of silicon rubber insulators 3.2. part 2 for optimization, different corona ring diameters have been considered and compared (from table 1). [11]. comsol simulations have been performed for each ring specification and the corresponding obtained results are summarized in table 5. table 5 comparison of different corona rings ring # dimension characteristics ring position (h) maximum e (kv/mm) ring measurement (r) ring tube breadth (r) without ring 3.03 ring #1 32 inches (816 mm) 2.44 inches (62 mm) -1650 mm 1.82 ring #2 28 inches (711 mm) 2.44 inches (62 mm) -1650 mm 1.73 ring #3 24 inches (610 mm) 2.44 inches (62 mm) -1650 mm 1.96 ring #4 20 inches (508 mm) 2.44 inches (62 mm) -1650 mm 1.79 ring #5 16 inches (406 mm) 2.44 inches (62 mm) -1650 mm 1.77 ring #6 12 inches (305 mm) 2.44 inches (62 mm) -1650 mm 1.81 ring #7 8 inches (203 mm) 2.44 inches (62 mm) -1650 mm 2.37 ring #8 6 inches (152 mm) 2.44 inches (62 mm) -1650 mm 1.81 ring #9 32 inches (816 mm) 3.44 inches (87 mm) -1650 mm 1.77 ring #10 28 inches (711 mm) 3.44 inches (87 mm) -1650 mm 1.79 ring #11 24 inches (610 mm) 3.44 inches (87 mm) -1650 mm 3.00 ring #12 20 inches (508 mm) 3.44 inches (87 mm) -1650 mm 2.42 ring #13 16 inches (406 mm) 3.44 inches (87 mm) -1650 mm 1.77 ring #14 12 inches (305 mm) 3.44 inches (87 mm) -1650 mm 1.79 ring #15 8 inches (203 mm) 3.44 inches (87 mm) -1650 mm 1.67 fig. 13 corona ring results of electric field distribution fig. 13 illustrates the electric field distribution results. the following points may be noted from the results: (1) the electric field (1.67 kv/mm) is minimum in the case of ring #15 where the ring diameter is 8 inches and the ring tube is 3.44 inches. (2) of the 15 rings simulated, 3 rings are observed to be still above the corona inception threshold: ring #7, ring #11, and ring #12. advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 29 4. conclusions in this study, the electric field distribution and potential distribution over two suspension-type insulators (glass and nci (silicon rubber)) connecting to 400 kv transmission systems were studied. the most commonly used silicon rubber insulators are prone to corona damages and they are generally used along with suitable corona rings with appropriate specifications to ensure voltages above 230 kv. it is recommended that these simulations be accompanied by laboratory tests on various corona rings to confirm the simulations results. the outcomes were empowered for also investigation toward thusly. from table 6, it can be seen that the estimations of the maximum electric field stress acquired by optimizing the corona ring are within the corona inception threshold value and are indeed very low when compared with the values obtained for the insulators without corona rings. from the results, it can be observed that the potential distribution along the insulator can be increased and the electrical stress can be minimized by adding a corona ring. it can be concluded that the corona ring can enhance the lifetime of an insulator. in future studies, the effect of air temperature, humidity, and icing on the corona-related phenomena of the standard silicon rubber insulators with corona rings should be investigated. table 6 summary of corona ring optimization for silicon rubber insulator ring # ring measurement (r) ring tube breadth (r) maximum e (kv/mm) description without ring 3.03 above corona inception threshold ring #15 8 inches (203 mm) 3.44 inches (87 mm) 1.67 minimum e conflicts of interest the authors declare no conflict of interest. references [1] r. a. bernstorf, “insulators 101 design criteria,” ieee pes t&d 2010, april 2010, pp. 1-5. [2] s. ilhan, a. ozdemir, and h. ismailoglu, “impacts of corona rings on the insulation performance of composite polymer insulator strings,” ieee transactions on dielectrics and electrical insulation, vol. 22, no. 3, pp. 1605-1612, june 2015. [3] p. alotto and l. codecasa, “corona discharge simulation of multi conductor electrostatic precipitators,” ieee transactions on magnetics, vol. 52, no. 3, pp. 1-4, march 2016. [4] p. wang, y. zhao, f. lv, k. li, and y. ding, “distribution of electric field and structure optimisation on the surface of a ±1100 kv smoothing reactor,” iet science, measurement & technology, vol. 13, no. 3, pp. 441-446, may 2019. [5] x. zhao, x. yang, j. hu, h. wang, h. yang, q. li, et al., “grading of electric field distribution of ac polymeric outdoor insulators using field grading material,” ieee transactions on dielectrics and electrical insulation, vol. 26, no. 4, pp. 1253-1260, august 2019. [6] r. lings, epri ac transmission line reference book—200 kv and above, 3rd ed. ca: palo alto, 2005 [7] r. anbarasan and s. usa, “electrical field computation of polymeric insulator using reduced dimension modeling,” ieee transactions on dielectrics and electrical insulation, vol. 22, no. 2, pp. 739-746, april 2015. [8] f. huo, p. zhang, y. yu, q. liu, l. chu, and x. wang, “electric field calculation and grading ring design for 750 kv four-circuits transmission line on the same tower with six cross-arms,” the journal of engineering, vol. 2019, no. 16, pp. 3155-3159, march 2019. [9] f. w. peek jr, dielectric phenomena in high voltage engineering, mcgraw-hill press, new york, 1929. [10] b. m'hamdi, m. teguar, and a. mekhaldi, “optimal design of corona ring on hv composite insulator using pso approach with dynamic population size,” ieee transactions on dielectrics and electrical insulation, vol. 23, no. 2, pp. 1048-1057, april 2016. [11] hubbell power systems inc., “recommended corona ring installation table”, november 10, 2019 http://www.hubbellpowersystems.com/insulators/trans/suspension/quadrisil/corona.asp. advances in technology innovation, vol. 6, no. 1, 2021, pp. 21-30 30 [12] s. ilhan and a. ozdemir, “380 kv corona ring optimization for ac voltages,” ieee transactions on dielectrics and electrical insulation, vol. 18, no. 2, pp. 408-417, april 2011. [13] e. brasca, e. comellini, and d. dell'olio, “power arc on insulator strings: testing procedures and design of guard devices for hv transmission lines,” ieee transactions on power apparatus and systems, vol. pas-89, no. 3, pp. 420-428, march 1970. [14] t. doshi, r. s. gorur, and j. hunt, “electric field computation of composite line insulators up to 1200 kv ac,” ieee transactions on dielectrics and electrical insulation, vol. 18, no. 3, pp. 861-867, june 2011. [15] j. wang, b. yue, x. deng, t. liu, and z. peng, “electric field evaluation and optimization of shielding electrodes for high voltage apparatus in ±1100 kv indoor dc yard,” ieee transactions on dielectrics and electrical insulation, vol. 25, no. 1, pp. 321-329, february 2018. [16] s. heshmatian and a. gholami, “adjusting the electric field and voltage distribution along a 400 kv transmission line composite insulator using corona ring,” 2015 2nd international conference on knowledge-based engineering and innovation (kbei), november 2015, pp. 196-201. [17] w. sima, f. p. espino-cortes, e. a. cherney, and s. h. jayaram, “optimization of corona ring design for long-rod insulators using fem based computational analysis,” conference record of the 2004 ieee international symposium on electrical insulation, october 2004, pp. 480-483. [18] m. farzaneh and w. a. chisholm, insulators for icing and polluted environments, ieee press, wiley, 2009. [19] m. bouhaouche, a. mekhaldi, and m. teguar, “improvement of electric field distribution by integrating composite insulators in a 400 kv ac double circuit line in algeria,” ieee transactions on dielectrics and electrical insulation, vol. 24, no. 6, pp. 3549-3558, december 2017. [20] m. kanyakumari, r. s. shivakumara aradhya, h. jangawala, and g. k. xianghe, “control of electric field and voltage distribution of a 765kv system polymeric insulator used in indian transmission systems,” 2012 ieee 10th international conference on the properties and applications of dielectric materials, july 2012, pp. 1-4. [21] c. zachariades, s. m. rowland, i. cotton, v. peesapati, and d. chambers, “development of electric-field stress control devices for a 132 kv insulating cross-arm using finite-element analysis,” ieee transactions on power delivery, vol. 31, no. 5, pp. 2105-2113, october 2016. [22] c. guo, l. liu, h. yu, y. ma, h. mei, and l. wang, “electric field distribution calculation and analysis of composite insulators operating on double circuit transposition tower in 500kv transmission lines,” 2019 2nd international conference on electrical materials and power equipment (icempe), april 2019, pp. 486-489. [23] m. bouhaouche, a. mekhaldi, and m. teguar, “composite insulators in a 400 kv ac line in algeria for improving electric field distribution,” 2018 international conference on electrical sciences and technologies in maghreb (cistem), october 2018, pp. 1-5. [24] a. hassanvand, h. a. illias, h. mokhlis, and a. h. a. bakar, “effects of corona ring dimensions on the electric field distribution on 132 kv glass insulator,” 2014 ieee 8th international power engineering and optimization conference (peoco2014), 2014, pp. 248-251. [25] r. kacprzyk and w. bretuj, “photoconduction in outdoor insulation materials,” ieee transactions on dielectrics and electrical insulation, vol. 24, no. 2, pp. 1045-1050, april 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 frame-synchronous blind audio watermarking for tamper proofing and self-recovery hwai-tsu hu * , ying-hsiang lu department of electronic engineering, national i-lan university, yilan, taiwan received 25april 2019; received in revised form 28 may 2019; accepted 22 august 2019 doi: https://doi.org/10.46604/aiti.2020.4138 abstract this paper presents a lifting wavelet transform (lwt)-based blind audio watermarking scheme designed for tampering detection and self-recovery. following 3-level lwt decomposition of a host audio, the coefficients in selected subbands are first partitioned into frames for watermarking. to suit different purposes of the watermarking applications, binary information is packed into two groups: frame-related data are embedded in the approximation subband using rational dither modulation; the source-channel coded bit sequence of the host audio is hidden inside the 2 nd and 3 rd -detail subbands using 2 n -ary adaptive quantization index modulation. the frame-related data consists of a synchronization code used for frame alignment and a composite message gathered from four adjacent frames for content authentication. to endow the proposed watermarking scheme with a self-recovering capability, we resort to hashing comparison to identify tampered frames and adopt a reed–solomon code to correct symbol errors. the experiment results indicate that the proposed watermarking scheme can accurately locate and recover the tampered regions of the audio signal. the incorporation of the frame synchronization mechanism enables the proposed scheme to resist against cropping and replacement attacks, all of which were unsolvable by previous watermarking schemes. furthermore, as revealed by the perceptual evaluation of audio quality measures, the quality degradation caused by watermark embedding is merely minor. with all the aforementioned merits, the proposed scheme can find various applications for ownership protection and content authentication. keywords: blind audio watermarking, lifting wavelet transform, 2 n -ary adaptive quantization modulation, rational dither modulation, tamper proofing, self-recovery 1. introduction in the age of cloud sharing and mobile access, digital resources (such as speech, image, audio and video files) on the internet keep increasing dramatically in recent years. ironically, owing to the availability of convenient computer software, tampering multimedia data is also rampant nowadays. protection against intellectual property infringement thus becomes an important issue. digital watermarking is considered a promising countermeasure to cope with this issue [1-2]. digital watermarks can be embedded in noise-tolerant multimedia signals to fulfill the goals of content authentication, copyright protection, covert communication, etc. based on the information required for extraction, watermarking schemes can be divided into non-blind and blind categories. non-blind schemes require the original image and/or watermark for extraction, whereas blind schemes require neither. depending on the application scenario, audio watermarks can also be classified as robust or fragile. robust watermarking is meant to be resilient to modification attempts, whereas fragile watermarking makes the embedded information sensitive to any modifications [3]. among the audio watermarking schemes developed for content authentication, the early purpose of the embedded watermark was focused on the detection and localization of tampered area [4-6]. * corresponding author. e-mail address: hthu@niu.edu.tw tel.: +886-3-9317343; fax: +886-3-9369507 advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 19 a potential application of fragile watermarking in the field of audio processing is the self-recovery technique, which embeds a watermark into the audio itself to combat the tampering situations. the embedded watermark is often a compressed version of the original content generated via data compression and coding schemes. the amount of the watermark that survives the tampering can help the receiver to not only locate the tampering areas but also to recover the lost content with a certain quality. a few self-recovery schemes for image signals have been proposed so far, such as [7-10]. speech signal self-recovery was also attempted in [11-13]; nonetheless, studies of the self-recovery schemes for audio signals were relatively limited. the method proposed in [14] divides the audio into 4 segments and embeds the feature parameters of every segment into the less significant bits (lsbs) of another randomly selected segment. for this method, self-recovery is feasible only if the lsbs are completely retrievable. by contrast, the method in [15] embeds the control bits for self-recovery in the integer discrete cosine transform (intdct) domain and then employs a compressive sensing technique to retrieve the tampered intdct coefficients. although this method is capable of recovering the audio signal tampered by content replacement attacks, it can only restore the attacked signals up to 0.6 % with acceptable quality. furthermore, the size of the replaced segment must remain identical to enable tampering detection and signal recovery. in fact, it is more common to encounter a situation where the replaced segment holds a different size. the method in [16] attempts to solve such a size discrepancy problem using a synchronization strategy. however, the adopted synchronization strategy appears oversimplified. when the length of the received audio signal is shorter than that of the original, it simply adds a set of zeros at the end of the audio instead of aligning the signal back to the correct position. one common drawback of the foregoing audio watermarking schemes for self-recovery is that they all lack the countermeasures to cope with cropping and/or time-shifting attacks. a minor time mismatch can disrupt the watermark extraction for subsequent self-recovery. motivated by the work done in [14-16], we propose an efficient blind audio watermarking scheme that is capable of achieving tamper proofing and self-recovery in the presence of arbitrary content replacement attacks. the remainder of this paper is organized as follows. section 2 presents two watermarking schemes designed for attaining frame-synchronous blind audio watermarking in the lifting wavelet domain. section 3 outlines the procedures used in watermark embedding and extraction. the framework for self-recovery is discussed in section 4. section 5 evaluates the proposed scheme in terms of imperceptibility, temper proofing, self-recovery, and processing time. in order to illustrate the advantages of the proposed scheme more clearly, section 5 also provides a comparative evaluation between the proposed self-recovery scheme and the one in [16]. finally, conclusions are given in section 6. 2. lwt-based watermarking schemes among the transforms used to perform audio watermarking, dwt appears to be the most popular due to its perfect reconstruction and good multi-resolution characteristics. in particular, many dwt-based schemes take advantage of quantization index modulation (qim) [17] to achieve effective watermark embedding. to reduce computational and memory overhead, we adopted a lifting scheme to implement the dwt in this study. a lifting wavelet transform (lwt) comprises three steps: split, prediction, and update for signal decomposition, and another three steps: update, prediction, and merge are needed for signal reconstruction. the lwt saves computational time and enables frequency localization to overcome the weakness of the traditional wavelet. it is regarded as the second-generation wavelet transform [18]. fig. 1 presents the procedural flow for watermark generation and embedding. as illustrated in the right branch of fig. 1, we first apply a 3-level lwt to decompose a host audio signal into one approximation subband and three detail subbands, each corresponding to a specific frequency range. in particular, the daubechies-8 basis [19] is used as a wavelet function in the process of lwt. note that audio watermarking is preferably implemented in low-frequency subbands with relatively high intensity, as these subbands are more tolerable to signal alteration with less impairment in perceptual quality. theoretically, for audio sampled at 44.1 khz, the 3rd -level approximation subband spans a frequency range from 0 to 2756 (= 322050 / 2 ) hz, advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 20 which is suitable for robust watermarking. hence, in our design the approximation subband is reserved for embedding the crucial information including synchronization code, frame index, and hash data derived from the channel-coded bit stream. the 2nd and 3rd -level detail subbands are used to hide fragile watermarks that is responsible for data authentication and signal recovery. fig. 1 watermark generation and embedding 2.1. rational dither modulation following the application of lwt to the audio signal, we employ the rational dither modulation [20, 21] to carry out binary embedding in the approximation subband. let (3) ( )ac n denote the thn coefficient in the -level approximation subband. by referring to the qim [17], the embedding of a binary bit  ( ) 0,1aw n  into (3) ( )ac n can be formulated as   (3) ( )(3) (3) ( ) ( ) ( ) 1 ˆ ( ) sgn ( ) ( ) 2 2 2 a na a a n a k c n w n c n c n w n                  (1) where  sgn  ,  ,    represent the sign, absolute, and floor functions, respectively. ( )n stands for the step size for quantizing coefficients. the subscript ‘a’ in the symbol ( )aw n implies the targeted approximation subband wherein the watermark bit is embedded and extracted. the use of the magnitude rather than amplitude in eq. (1) aims at excluding the trouble of sign flipping. in accordance with the formulation in eq. (1), the watermarking error, which is defined as the difference between (3)ˆ ( )ac n and (3) ( )ac n , can be assumed to have a uniform distribution over ( ) ( )/ 2, / 2n n     with a variance of 2 ( ) /12n . one of the key features of the rdm lies in the acquisition of ( )n , which is recursively derivable from previous coefficients through      1010log 1/121/2 2 (3) 20 ( ) 1 1 ˆ ( ) 10 repf b l n a i c n i l             (2) 3rd advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 21 where l stands for the length of the involved coefficients. similar to the manner in [20, 21], the embedding strength is adaptively controlled at the maximum tolerable level of the human auditory system [22, 23]. the term   2010 repf b signifies a multiplicative factor for adjusting the embedding strength. ( )repf b is the auditory masking threshold in unit of decibel for the bark scale repb . ( ) 0.275 15.025rep repf b b      (3) with  representing a clearance gap for imperceptibility. repb can be obtained from a representative frequency repf using the following empirical formula [24]:    1 1 213tan 0.00076 3.5tan ( / 7500)rep rep repb f f   (4) here we chose the center of the -level approximation subband as the representative frequency, i.e. 3 1 0.5 2 2 s rep f f    (5) where sf is the sampling frequency. overall, eq. (2) jointly takes into account of the psychoacoustic features (i.e., ( )repf b ), the quantization error distribution (i.e.,  1010log 1/12 ), and the root-mean-square of previously processed coefficients (i.e., (3)ˆ{ ( ) 1, , }ac n i i l  ). the watermark extraction in rdm requires the derivation of quantization step ( )n based on the same formula presented in eq. (2). subsequent to the acquisition of the 3 rd -level approximation coefficient (3) ( )ac n , the bit ( )aw n residing in (3) ( )ac n can be determined by (3) ( ) ( ) ( ) mod 2 0.5 ,2 a a n c n w n             (6) where  mod ,x y denotes the modulo operation, which returns the remainder after the division of x by y . the tilde symbol atop a participating variable implicates the effect due to possible attacks. 2.2 n 2 -ary adaptive quantization index modulation analogous to rdm, the n 2 -ary adaptive quantization index modulation (aqim) modifies the coefficient magnitude according to a n 2 -ary number  ( ) 0,1, ,2 1n dw n   .   ( ) ( ) ( ) ( ) ( ) 1 ˆ ( ) sgn ( ) max 0, ( ) 2 2 2 j dj j d k d d k dn n k c n w n c n c n w n                      (7) where max  denotes the maximum value drawn from a set of data. ( ) ( )j dc n is the thn coefficient in the thj -level detail subband. the floor function within the above equation may, however, render a negative value that is illegitimate to the definition of a magnitude. in case a negative outcome occurs, we simply replace the negative value with zero. in contrast to the case in rdm, the quantization step k is computed from the energy of all the coefficients in a frame indexed by an integer k . given that the watermarking errors maintain a power ratio  in decibels, the relationship betwee k and  can be mathematically expressed as follows: 3rd advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 22       1 2 ( ) 0 10 1 2 ( ) ( ) 0 1 2 ( ) 0 2 1 ( ) 10 1 ˆe ( ) ( ) 1 ( ) /12 f c f l j d if l j j d d ic l j d if k c i l c i c i l c i l                    (8) where fl is the frame length. cl denotes the number of the coefficients involved in the quantization. basically, c fl l . by referring to eqs. (3) and (4), the value of  can also be estimated as  10( ) 10log 1/12repf b    (9) in [20, 25-27], it was demonstrated that the quantization step size can be adaptively retrieved from a watermarked audio as long as the energy level remains unchanged throughout the watermarking process. the modification on ( ) ( )j dc n in eq. (7) inevitably cause variations in energy, which makes the retrieved k different from the one used in watermark embedding. thus, the recovered watermark bits may become inaccurate. this conflict can be settled by first minimizing the overall energy variation of the first cl coefficients and then tuning the other coefficients in the range between 1cl  and fl . more specifically, we first sort the coefficient magnitudes, termed ( )( ) ( )j i d il c l  , in descending order: 0 1 1 1 ˆ ˆ ˆ ˆ ˆ( ) ( ) ( ) ( ) ( ) ci i ll l l l l           (10) where il , which is drawn from  0,1, , 1cl  , signifies the index associated the thi largest magnitude. when applying eq. (7) to the th il coefficient, the optimal solution 1( )il is ( ) 1 ˆ ˆ( ) ( ) ( )j i i d il l c l   (11) and the suboptimal 2 ( )il becomes    ( ) 2 ˆ ˆ ˆˆ( ) , if ( ) ( ) & ( ) ( ) ˆ( ) , otherwise. j i k i d i i k i i k l l c l l l l               (12) in general, coefficients with large magnitudes contribute more variations in energy. to minimize the overall energy variation in a frame, we select between 1( ) 'il s and 2( ) 'il s for the coefficient magnitudes in the top ol ranks.         11 2 2 2 2 0, , 1 0 {1,2} ˆˆ arg min ( ) ( ) ( ) ( ) o i i o o i ll i n i i i i n i l i i l n n l l l l                 (13) subject to the constraint that the accumulated energy must be less than the overall energy, i.e.       1 11 1 1 2 2 2 2 2 ( ) ( ) ( ) 0 0 0 ˆ( ) ( ) ( ) ( ) ( ) f fc c c i o c l ll l l j j j n i i d i d d i i l i i l i l l c l c i c i                   (14) the search for  ˆ in in this study is done by a brutal force approach. thus, the required computation is exponentially proportional to ol . this study chooses ol as 8. substituting ˆ ( ) in i for the magnitudes in  ˆ( ) 0 1i ol i l    , i.e. advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 23 ˆ ˆ ˆ( ) ( ) ( ) ii i n il l l    , yields the least energy variation achievable by the ol coefficients. once the magnitude for the th il coefficient is determined, the corresponding detail coefficients can be modified as follows:    ( ) ( ) ˆ ( ) ˆ ( ) sgn ( ) ; 0,1, , 1; 0,1, , 1 ( ) ij j d i d i c i c i l c l c l i l l l l          (15) where  represents an infinitesimal number added to the denominator to avoid dividing by zero. the violation of the constraint (14) implies that the energy collected from the first cl coefficients exceeds the total amount. it will be impossible to compensate for the excessive portion by regulating the energy over the remaining coefficients, i.e.,  ( ) 1( ) , , , 1j d c c fc i i l l l  . in case the inequality (14) cannot maintain after adjusting the first ol coefficients, we then proceed with the next ol coefficients in the top ranks, i.e.,  ( )ˆ ( ) , ,2 1j d i o oc l i l l  , and rerun the adjustment process. previously altered detail coefficients in the sorted sequence shall remain intact. the adjustment process continues until the constraint shown in eq. (14) is satisfied. finally, to ensure a perfect match with the original energy level, we use the remaining ( )f cl l coefficients to absorb the energy discrepancy       1/2 1 1 2 2 ( ) ( ) ( ) ( ) 0 0 1 2 ( ) ˆ( ) ( ) ˆ ( ) ( ) ; , , 1. ( ) f c f c l l j j d d j j i i d d c fl j d i l c i c i c k c k k l l c i                          (16) after completing the watermark embedding, we reconstruct the audio by taking the inverse lwt with respect to all subband coefficients. to retrieve the embedded watermark bits from the watermarked audio, we follow the same steps used in the embedding process. the quantization step size k can be obtained using eqs. (8). the thi 2 -aryn number, termed ( )dw i , is determined based on the qim rule: ( ) ( ) ( ) mod 2 0.5 ,2 j d n n d k c i w i             (17) 3. self-recovery framework one of the main features of the proposed watermarking scheme is the self-recovery capability. in order to achieve tamper proofing and self-recovery concurrently, we incorporate the source-channel coding and hashing techniques into the proposed watermarking scheme. the basic idea is to use the frame-partitioned source-channel coded data as the watermark in the embedding phase, and examine the watermark for tamper detection and self-recovery in the extraction phase. in this study, we adopt a mpeg-1 audio layer iii codec (termed mp3 for short) to perform a lossy data-compression of the host audio. in consideration of the limited watermarking capacity, the audio signal is encoded at a very low bitrate of 16 kilobits per second (kbps). this is actually achieved by down-sampling the audio by a factor of 4 and then applying the mp3 codec to convert the audio to a bit stream of 64 kbps. the bit stream is further divided into frames of size 2448 (=21538), which can be regarded as 2 message words, each containing 153 bytes. in this study, reed-solomon (rs) codes on the galois fields 8(2 )gf [28] are employed to recover the information destroyed by tampering attempts. for each message word, we use a  255,153 rs code to form an augmented word of length 255. this arrangement enables the rs code to correct 51   255 153 / 2  errors in a row of 255 symbols. in other words, the tolerable tampering rate of the applied rs code is 20% (i.e., 51/255). as a result, the number of bits that were supposed to advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 24 embed in each frame is expanded from 2448 to 4080 (=22558). given that the sampling rate of the audio is 44100 hz, this amount of binary bits shall be embedded into a frame with its length no less than 441002448/16000. hence we choose the frame length as 6656 samples and embed 4080 bits into the 3 rd and 2 nd -level detail subbands after performing 3-level lwt decomposition. as shown in fig. 2, the 3 rd and 2 nd -level detail subbands respectively consist of 832 and 1664 coefficients in each frame. we tactically embedded 816 octal numbers (3 bits per coefficient) into the 3 rd -level detail subband and 1632 binary bits (1 bit per coefficient) into 2 nd -level detail subband using the 2 -aryn aqim discussed in section 2, thus rendering a total of 4160 bits to accommodate the need of channel-coded data for audio recovery. the extra 80 bits (= 4160 4080 ) are reserved for the need of file headers. also note that we have applied a distinct 2 -aryn aqim to each detail subband. the use of 8-ary aqim in the 3 rd -level detail subband stems from the consideration that this subband usually contains relatively higher intensity than that found in the 2 nd -level detail subband. according to the formula for 2 -aryn aqim given in eq. (8), a high energy level also leads to a large quantization step that is supposedly more capable of resisting against malicious attacks. 4. procedures for watermark embedding and extraction 4.1. watermark embedding the procedure for watermarks embedding is detailed in the following. step. 1: apply the 64 kbps mp3 codec to a down-sampled audio signal and convert the output file into a bit stream. compose the bit sequence as an array of message words with a size of 153 bytes (or equivalently counted as 153 8-bit symbols). step. 2: append the parity symbols to each message word after applying a  255,153 rs encoder. step. 3: the symbols are scrambled among words via the use of .1key . this operation allows the rs code to detect and correct symbol errors in the corrupted word. step. 4: divide the message array into groups, each holding 4 consecutive words. for each group,  record the frame index as a 16-bit integer and encode this integer using a  31,16 bch encoder [29].  record the total number of frames as a 16-bit integer and encode this integer using a  31,16 bch encoder.  use . 2key to randomly permute the symbol sequence in each message word.  apply the md5 hash algorithm [30] to the first 153 symbols in each word and draw 16 hash bits from each hashed output to form a composite hash representation of 64 bits.  pack the frame-related information as a bit sequence of length 128, as shown in fig. 2. step. 5: perform 3-level lwt on the host audio step. 6: partition the coefficients in each subband into frames. for a frame length of 6656 audio samples, there are 832 and 1664 coefficients contained in the 3rd and 2nd-level subbands, respectively. step. 7: distribute the channel-coded symbols obtained in steps. 3 and 4 to the audio frames. for each frame,  embed the synchronization code and frame-related information alternately into the 3rd-level approximation subband.  embed 2448 bits into the 3rd-level detail subband using 8-ary aqim.  embed 1632 bits into the 2nd-level detail subband using binary aqim. step. 8: take inverse lwt to obtain the watermarked audio. advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 25 fig. 2 arrangement of watermark bits 4.2. watermark extraction fig. 3 outlines the procedure for watermark extraction, tampering detection, and self-recovery. the required steps are outlined as follows: step. 1: conduct 3-level lwt. step. 2: extract the embedded bits from the approximation subband using rdm discussed in section 2. step. 3: apply a matched filter to the extracted bit sequence. the synchronization code in reverse order serves as the filter coefficients. given that  ( ) 0,1n  denotes the synchronization code of length syncl , feeding the extracted ( )aw n into the matched filter results in, fig. 3 block diagram of watermark extraction for tampering detection and audio recovery    1 0 ( ) 2 ( 1 ) 1 2 ( ) 1 syncl sync a i m n l i w n i         (18) ideally, a salient peak of value syncl occurs whenever ( )aw n perfectly matches with the synchronous code. 255 bytes 255 bytes 255 bytes 255 bytes : : : 255 bytes 255 bytes 255 bytes 255 bytes advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 26 step. 4: for each frame,  retrieve the frame-related data and the hash bits from two consecutive frames; acquire the number of total frames and frame index using a  31,16 bch decoder.  extract 2448 bits from the 3rd-level detail subband using 8-ary aqim.  extract 1632 bits from the 2nd-level detail subband using binary aqim.  rearrange these (2448+1632) bits as two words, each comprising 255 8-bit symbol (1 byte per symbol).  place these two words in the corresponding index entry. step. 5: use . 2key to restore the symbol sequence in each message word. step. 6: use .1key to restore the original permutation of the symbol array. step. 7: pass the message word to the rs decoder to obtain the source-coded audio symbols. step. 8: generate the hash bits from each word using the md5 hash algorithm and compare these bits with those recorded in the approximation subband. if the hash bits are identical, the symbol sequence is assigned to the location indicated by the frame index. otherwise, the frame is labeled as tampered at the receiver. step. 9: use a mp3 decoder to decompress the audio signal from the extracted watermark bits and up-sample the output by a factor of 4. step. 10: if the audio frame has been tampered, then we substitute the up-sampled audio signal for the tampered audio content. since the rs decoding process is capable of removing 51 (=  255 153 / 2 ) errors in a row of 255 symbols, tampering is recoverable as long as the tampering rate is below 0.2 (=51/255); otherwise, the rs decoder and recovery process fail. 5. performance evaluation the test materials in the following experiments comprised twenty-four 30-second music clips collected from a variety of compact discs, including vocal arrangements and ensembles of musical instruments. the music clips can be classified into four categories: classical (3), pop (7), rock (7), soundtracks (7). all audio signals were sampled at 44.1 khz with 16-bit resolution. the parameters used in the proposed watermarking scheme were set as follows: 2  , 0 8l  , 128syncl  ; repf  1378.1, 4134.4, and 8268.8 hz for the 3 rd -level approximation subband, 3 rd -level detail subband, and 2 nd -level detail subband, respectively; the back-tracing length l used in the rdm was set to 416. 816cl  and 832fl  were chosen for the 8-ary aqim in the 3 rd -level detail subband, while 1632cl  and 1664fl  were for the binary aqim in the 2 nd -level detail subband. 5.1 imperceptibility test the quality of the watermarked audio signal was evaluated using the snr defined in eq. (19) along with the perceptual evaluation of audio quality (peaq) metric [31].   2 10 2 ( ) 10log ˆ( ) ( ) n n s n snr s n s n              (19) advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 27 where ( )s n and ˆ( )s n denote the original and watermarked audio signals, respectively. the peaq simulates the subjective evaluation of human subjects. it renders an objective difference grade (odg) between -4 and 0, signifying a perceptual impression from “very annoying” to “imperceptible”. in this study, the peaq metric for the imperceptibility test was an implementation released by the tsp lab at mcgill university [32]. table 1 summarizes the experiment results with respect to the test materials. for each audio signal of 30 seconds long, there are over 198 frames of size 6656 can be embedded and at least 99 of them contain the synchronization code. embedding the synchronization codes and frame-related data into the 3 rd -level approximation subband rendered an average snr of 28.34 db, which led to an average odg score around -0.30. the subsequent embedding of the channel coded symbols into the 3 rd and 2 nd -level detail subbands brought the snr to 27.36 db and caused the odg to slightly drop to -0.44. such a result suggests that the proposed watermarking schemes merely have minor influence on perceptual quality. moreover, for all audio files in the test, the embedded synchronization codes were perfectly detected using the matched filter. fig. 4 shows one such example, wherein the peaks with a height of 128 repeatedly appear for every 1664 approximation coefficients. table 1 quality measures of the watermarked audio after applying rdm and 𝟐𝑵-ary aqim to the audio signals quality measure rdm (in 3 rd -level app. subband) n 2 -ary aqim (in 3 rd & 2 nd -level detail subbands) rdm+ n 2 -ary aqim snr [db] mean 28.34 35.59 27.36 standard deviation 0.25 3.92 0.46 odg mean -0.30 -0.22 -0.44 standard deviation 0.38 0.26 0.43 (a) audio siganl (b) output of the matched fliter fig. 4 matched filtering with respect to the watermark bits obtained by the rdm 5.2 tamper detection and recovery a representative audio signal was employed to demonstrate the competence of the proposed scheme for tampering detection and localization. we conducted three types of attacks (namely, deletion, substitution, and insertion) on the audio signal with the self-recovering watermark embedded. the deletion attack cropped the leading 25000 samples of the watermarked audio signal. the substitution attack replaced the watermarked audio signal with zero over the range between 325001 and 375000. for the insertion attack, we appended 50000 samples of random noise at the end of the watermarked audio signal. both the substitution and insertion attacks represent possible attempts on counterfeiting the audio signal. advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 28 (a) audio with fragile watermarks embeded (b) tampered audio (c) output of the matched fliter fig. 5 illustration of three types of tampering attack (a) audio with fragile watermarks embeded (b) tampered audio (c) recoverd audio fig. 6 illustration of tampering detection and audio signal recovery fig.5 (a) and (b) respectively present the original and tampered watermarked audio signals. the watermark bits hidden in the 3 rd -level approximation subband are extracted, bipolarized (i.e.,    0,1 1,1  ), and finally fed into a matched filter. fig. advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 29 5 (c) depicts the output of the matched filter. a sharp peak with its magnitude greater than a predefined threshold (e.g., 80) can serve as an indicator to demarcate the frame boundary. the tampered signal is then processed using the watermark extraction and self-recovery procedures discussed in sections 2-4. more specifically, subsequent to frame synchronization, the hash bits are used to verify the veracity of individual frame content. as shown in fig. 6(b), a nonzero level (delineated as a bold solid red line) signifies intact frames and a zero level specifies the occurrence of tampering. all the data extracted from the 2 nd and 3 rd -level detail subbands are then employed to reconstruct an mp3 decompressed version of the audio signal. eventually, the lost contents in the tampered frames are replaced by the reconstructed ones, which are drawn in red in fig. 6(c). this typical example demonstrates that our scheme not only accurately locates the tampered audio frames but also possesses a self-recovering capability. 5.3 processing time the proposed self-recovery scheme comprises five basic modules to carry out watermark embedding. the first module involves source-channel encoding and hashing technique jointly used to constitute the bit sequence for audio recovery. as the watermarking is accomplished in three low-to-middle frequency subbands, we need a 3-level lwt and another inverse lwt to decompose and recompose the audio signal. these two transformations are extra computational burdens for the watermarking performed in the lwt domain. the operations situated in between the lwt and ilwt contain two sorts of watermark embedding, namely, the synchronization code sequence in the 3rd level approximation subband and the channel-coded bit stream in both the 2nd and 3rd detail subbands. as for the process of watermark extraction, we only need a 3-level lwt to decompose the watermarked audio. the detection of the synchronization code enables the alignment of frame boundary, which facilitates the watermark retrieval in the 2nd and 3rd detail subbands. possible errors in the watermark bits shall be amended with the assistance of the rs channel coder. eventually, the veracity and integrity of the received audio can be authenticated using hashing comparison. table 2 processing time required for each program module in watermark embedding and extraction processes program modules in watermark embedding processing time [sec] mean standard deviation conduct (1) data encoding & hashing (2) bit arrangement 6.377 0.193 perform lwt 0.947 0.009 embed sync_code using rdm 0.780 0.019 embed channel-coded data using aqim 2.852 0.075 perform ilwt 0.954 0.008 overall 11.910 0.258 program modules in watermark extraction processing time [sec] mean standard deviation perform lwt 0.957 0.013 align frames via the detection of sync_code 0.027 0.007 extract watermark (coded data) 0.029 0.004 perform channel-decoding and hashing comparison 1.267 0.037 restore the tampered signal if necessary overall 2.281+ 0.048+ we implemented the proposed watermarking algorithm in a matlab environment operating with a 4 ghz intel(r) core(tm) i7-4790k cpu and 32 gb ram. table 2 lists the average computation time for the twenty-four 30-second audio signals in the test set. in general, it takes 11.91 seconds to complete the watermark embedding for an audio file of 30 second long. among the five modules in the whole process, the data encoding and hashing consume about 53.54% of the computational time. the actual embedding in lwt subbands requires 5.533 seconds in total. compared to the lengthy computation required in the embedding process, the time spent on watermark extraction is greatly reduced while extracting watermark bits from the 2nd and 3rd detail subbands using aqim. advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 30 5.3 comparative evaluation in order to illustrate the advantages of our proposed scheme more clearly, we make a comparison between ours and the scheme proposed by gomez-ricardez and garcia-hernandez in [16]. the scheme in [16] is chosen for comparison based on the following two similarities. first, just like the manner we have done in this study, it employs a channel coder to protect the watermark. second, this scheme is also claimed to be robust against the content replacement attack if the affecting portion is less than 20% of the whole audio. table 3 summarizes the comparison. the method in [16] is indeed capable of restoring the substituted segment when the size of substitution remains unchanged. restoring the audio segment destroyed by the insertion attack is also possible if the tampered area is accurately located and the whole audio is properly trimmed and aligned. however, dealing with the deletion attack is problematic. for example, deleting a small section of the audio in the middle, then shifting the remaining part ahead, and finally padding zeros at the end can easily cripple the watermark extraction for the scheme in [16]. the cause is ascribable to the fact that the deletion misplaces a large portion of the watermarked audio and thus devastates the channel code information. for the same sake, the scheme in [16] cannot survive the cropping or time-shifting attacks, which are known to disrupt the frame synchronization for correct watermark extraction. by contrast, with the incorporation of the self-synchronization feature discussed in section 2, the proposed scheme can withstand all the aforementioned attacks (i.e., insertion, deletion, substitution, cropping, and time-shifting). table 3 comparison results attack types resistance the proposed scheme in [16] cropping / time shifting yes no deletion yes no substitution yes partially feasible insertion yes partially feasible lsb erasure yes no another advantage of the proposed scheme is that it is quite capable of resisting against minor attacks such as lsb erasure. table 4 presents the extraction results when 1 and 2 lsbs are deliberately obliterated. the results indicate that even in the case of 2 lsbs erasure the proposed scheme can perfectly extract 19 out of 24 embedded watermarks from the 2nd detail subband. moreover, because the maximum ber (i.e., 1.172%) is less than 20% 1/8, the reed-solomon code capable of correcting 20% erroneous 8-bit symbols is sufficient to recover the original watermark bits. table 4 comparison results # of erasure bits erase 2 lsbs erase 1 lsb embedding location 2nd detail subband 3rd detail subband 2nd detail subband 3rd detail subband # of watermarks without errors 19 21 22 23 # of watermarks with errors 5 3 2 1 largest ber among the watermarks with errors 1.172% 0.081% 0.223% 0.001% 6. conclusion in this paper, we have proposed a novel watermarking scheme to not only authenticate the veracity and integrity of the received audio but enable the recovery of tampered contents via the exploitation of source-channel coding. after the application of 3-level lwt to the audio signal, the proposed scheme performed two types of watermarking processes in a frame-synchronous manner. a compressed version of the original signal protected with the rs code was embedded into the 3 rd and 2 nd -level detail subbands using 2 -aryn aqim, while the frame-related data and hash bits were embedded into the 3 rd -level approximation subband using rdm. the experiment results indicated that the watermark embedding resulted in an average snr of 27.36 db and an average odg score around -0.44 for a test set of twenty-four audio clips, suggesting that the advances in technology innovation, vol. 5, no. 1, 2020, pp. 18-32 31 watermarked audio is nearly perceptually indistinguishable from the original one. in the phase of watermarking extraction, the rdm proved to be effective in tracking synchronization codes, thus facilitating the frame alignment and watermark extraction. the 2 -aryn aqim also demonstrated its competence in performing multi-bit data hiding in the lwt domain. more importantly, the ability of tracing frame boundaries empowered the proposed scheme to combat with the cropping and replacement attacks that no previous self-recovery watermarking schemes could easily handle. as there is plenty of room for hiding extra information in the 3 rd -level approximation subband, our future work will be focused on adding other robust watermarks to reinforce copyright protection. conflicts of interest 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[32] p. kabal, “an examination and interpretation of itu-r bs.1387: perceptual evaluation of audio quality,” tsp lab technical report, dept. electrical & computer engineering, mcgill university, 2002. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 photovoltaic power control using fuzzy logic and fuzzy logic type 2 mppt algorithms and buck converter bachar meryem * , naddami ahmed, fahli ahmed department of electrical engineering, hassan first university, settat, morocco received 13 march 2019; received in revised form 22 april 2019; accepted 25 may 2019 abstract this work presents the analysis, design, simulation and hardware implementation of the classical fuzzy logic (fl) and the proposed fuzzy logic type 2 (flt2) mppt techniques for standalone pv system. fl and flt2 mppt algorithms are simulated via matlab/ simulink and implemented via labview software and compactrio hardware, in different climatic conditions. also, they are compared to the incremental conductance (inc) mppt algorithm, one of the most common used mppt techniques. the studied system consists of pv array, dc/dc converter, mppt controller, batteries and load. the pv array is connected to the dc / dc buck converter that works based on the output pulses of the mppt controller to make the pv system operates at the maximum power point (mpp). thereafter, based on the simulations and the experimental results, a comparison is made to be useful for mppt designers and researchers in this area. keywords: photovoltaic panel, fuzzy logic, fuzzy logic type 2, matlab/simulink 1. introduction solar energy is a renewable, non-polluting and economical source of energy which allows obtaining electricity from the solar irradiation using photovoltaic (pv) cells [1, 2]. despite its advantages, solar energy has a remarkable disadvantage. one of the most relevant problems is that solar energy is intermittent. therefore, the power produced by pv panels is influenced by the climatic conditions (irradiation and temperature) and the load impedance [3, 4]. generally, the intersection of the load and pv panel characteristics is too far from the mpp, thus, it is important to insert a dc/dc converter, between the load and the pv source, for the impedance matching [5]. maximum power point tracking (mppt) algorithms are used for the pursuit of mpp in different climatic conditions [6], by adjusting the duty cycle of the dc/dc converter. generally, the system consists of a pv array, a dc/dc converter, a load and finally batteries. nowadays, several techniques of mppt exist such as perturb and observe (p&o) [7, 8], incremental conductance (inc) [5, 9], constant voltage (cv), open circuit voltage (ocv), and fuzzy logic (fl) [10-12]. mppt algorithms can be distinguished by operating principle, performance, complexity, response time, cost and more. the classic fuzzy logic (fl), introduced in 1965 by lotfi zadeh, allows the representation and processing of imprecise knowledge based on linguistic terms. it relies on human reasoning to convert a linguistic command into an automatic command to control complex systems [13, 14]. fuzzy type 2 (flt2) [15], the proposed mppt technique, is based on fl. it supports uncertainties using three-dimensional membership functions. * corresponding author. e-mail address: meryem.bachar@gmail.com tel.: +212523492455; fax: +212(0)523490354 advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 126 in this work, the authors present a comparative study of three mppt algorithms (fuzzy logic, fuzzy logic type 2 and incremental conductance). matlab/simulink environment is used for simulation studies and labview software for experimental tests. this paper is organized as follows: section ii explains the operating principle of a photovoltaic cell and gives the i-v and p-v characteristics of the studied pv array. section iii deals with dc/dc converters and focuses on the dc/dc buck converter, used in this paper. section iv studies the role of mppt algorithms and explain fl and flt2 mppt algorithms. section v presents the simulation results of the photovoltaic system with fl, flt2, and inc algorithms and gives a comparison of them. finally, section vi presents the experimental results of the three studied algorithms by using labview software and compactrio hardware. 2. photovoltaic module in order to study the behaviour of photovoltaic cell, we can model it by an electric circuit, as shown in fig. 1. pv cell usually consists of an iph current generator, which models the conversion of light radiation into electricity, a diode d which represents the pn junction, a parallel resistor rsh and a series resistor rs [16, 17]. fig. 1 electric circuit of pv cell the current generated by the photovoltaic cell is calculated by eq. (1): ph d shi i i i   (1) eq. (1) can be rewritten by eq. (2) [18]: 0 s sh sh v ir rq s ph v ir i i i e r                     (2) the terms iph, i0, q, a, k, t are the photodiode current, the inverse saturation current, the electron charge, the ideality factor of the pn junction, the boltzmann constant and the temperature of pv cell, respectively. 3. dc/dc buck converter fig. 3 dc/dc buck converter a dc/dc converter is used to convert a dc input voltage to a modified dc output voltage [20]. currently, several dc/dc converters exist such as: buck, boost, buck-boost and full bridge [21, 22]. in this paper, the dc/dc buck converter, advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 127 which allows for a lowered voltage, is used. it usually consists of a switch, a diode, a capacitor, and an inductance, as shown in fig. 2 [23]. when the switch s is closed, during the period αt, the diode d is blocked and the voltage across the converter is given by: l e sv v v  (3) when the switch s is open, during the period (1-α) t, the diode is on and the voltage across the converter is given by: l ev v  (4) the voltage passing through the inductance l is given by the following relation: l ldi v l dt  (5) the relationship between the input voltage and the output voltage of the buck converter is given in eq. (6): s ev v (6) where α is the duty cycle with 0 <α <1. from eq. (7), we can rewrite the inductance as follows:   1l l e s s r di l v v v dt f i     (7) the value of the capacity is given by the eq. (8):   r s r r i f c v i esr    (8) the terms fs, ir, vr and esr are switching frequency, ripple current, ripple voltage and effective series resistance, respectively. the switch s is a mosfet controlled by an mppt controller which will be detailed in the following part. 4. maximum power point tracking algorithms (mppt) climate changes during the day influence the power produced by the pv panel. therefore, the operating point does not intersect with the mpp, which causes a loss of power. it is then essential to extract the novel mpp using mppt algorithms. they are used to vary the equivalent resistance of the load to extract the maximum power by automatically varying the duty cycle of the dc/dc converter [10]. nowadays, several methods of mppt exist and can be classified by their tracking techniques to: (1) methods with constant parameters such as constant voltage [24], open circuit voltage [25] and short circuit voltage [26]. (2) methods with trial and error such as the only-current photovoltaic, perturb and observe [28] and dc-link capacitor drop [29]. (3) methods with mathematical calculation such as curve fitting [30], differentiation method and incremental conductance [31, 32]. (4) methods with intelligent prediction such as fuzzy logic control and neural network [33]. in this work, the authors compare two fuzzy logic controls (classic fuzzy logic (fl) and fuzzy logic type 2 (flt2)) with the incremental conductance, in different cases of irradiation. advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 128 4.1. classical fuzzy logic (fl) the fuzzy logic algorithm is an intelligent technique. it does not require exact knowledge of the photovoltaic system, which makes its use simple. in addition, it is a robust and powerful technique [34]. a fuzzy controller typically consists of four parts: fuzzification, inference, rule base, and defuzzification, as shown in fig. 4. fig. 3 the fuzzy logic controller diagram in this paper, the inputs of the fl controller are the error and the change of error derror. they are given by the eqs. (9) and (10):           1 1 p k p k error k v k v k      (9) ( ) ( ) ( 1)derror k error k error k   (10) where k, p, and v are the sampling time, the pv panel power and the pv panel voltage, respectively. in the fuzzification stage, the digital inputs are converted into seven linguistic variables that are: positive big (pb), positive medium (pm), positive small (ps), zero (ze), negative small (ns), negative medium (nm), and negative big (nb). fig. 4 and fig. 5 present the linguistic variables of the error and derror. fig. 4 the input of fuzzy logic controller (error) fig. 5 the input of fuzzy logic controller (derror) it is important to understand how the system works to create the rules. in this work, the inference engine based on mamdami method applies 49 rules in the form of if-then as explained in table 1. advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 129 table 1 fuzzy logic rule base error derror pb pb pm ps ze ns nm pm ze ze ze nb nb nb ps ze ze ze nm nm nm ze ze ze ze ns ns nm ns ns ns ze ze ze ps nm pm pm ps ns ze ps nb pm pm pm pb ze ze based on these rules, the change in the duty cycle is calculated. the output, as presented in fig. 6, has 7 levels: positive big (pb), positive medium (pm), positive small (ps), zero (ze), negative small (ns), negative medium (nm), and negative big (nb). in the defuzzification stage, the output is converted to a numerical variable to provide an analog signal. thus, the duty cycle of dc/dc buck converter is varied to reach the mpp. fig. 6 the output of fuzzy logic controller (duty cycle) 4.2. fuzzy logic type 2 (flt2) fuzzy logic type 2 (flt2), noted  , models uncertainty better than conventional fuzzy logic. it is characterized by a three-dimensional membership function ( , )u x y . flt2 can be expressed by eq. (11): ( , ) , xx x u j u x y u x        ,  0,1xj  (11) where x, jx, and ∬ are the primary variable, the primary membership of x and the union of all the cartesian product elements on x, respectively. each three-dimensional membership function has superior and inferior membership functions represented by classical fuzzy logic. the interval between the inferior and superior membership functions is called footprint of uncertainty (fou). it is the new third dimension of the flt2 which gives more precision, compared to the classical fuzzy logic [35]. the block diagram of the flt2, presented in fig. 7, contains five parts: fuzzification, inference engine, rule base, reducer type, and defuzzification. fig. 7 the fuzzy logic type 2 controller diagram advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 130 in the fuzzification stage, the two digital inputs (error and derror) are converted into 3 linguistic variables which are: positive (p), zero (z), and negative (n). each variable has two levels: lower u and higher l. the variables then become (pl, pu); (zl, zu), and (nl, nu). the inputs used in this paper are shown in fig. 8 and fig. 9. fig. 8 membership function for error fig. 9 membership function for derror the structure of the rules remains exactly the same in the case of fl algorithm. table 2 summarizes the rules used in the employed flt2 controller. table 2 the rule table of flt2 controller error derror p z n p pb pm z z nm z nm n z n n the inference engine combines fuzzy rules to perform a transformation from fuzzy sets in the input space to fuzzy sets in the output space. there are several methods of inference such as the max-min inference method (mamdami), the max-product inference method (larsen) and the and inference method (sugeno). in this paper, the sugeno method is used. the output of the inference engine block is equal to the weighted average of the output of each fuzzy rule. the flt2 controller differs from the fl by the output processing module which consists, in this case, of two blocks: type reducer and defuzzification. for an flt2 system, each output set of a rule is type 2. consequently, the type reducer is used to get a classic set from the type 2 output sets. the classic set obtained from the type reducer is converted into a well-defined numerical value, in the defuzzification step, to control the dc/dc buck converter. as numerical value ca of the output, it can be obtained by the eq. (12): 1 1 ( ) ( ) ( ) n k kà k a n kà k y u y c x u y      (12) where n, y, and uӑ are, respectively, the number of rules, the output, and the membership function. the simulation results of the two algorithms studied will be presented in the following section. in addition, they will be compared to the inc algorithm. 5. simulation results in this part, the simulation results, under matlab/simulink, are presented. the system, shown in fig. 11, is composed of six tesla solar modules (solar ts250-p150-60), a dc/dc buck converter, mppt controller and four series batteries (48v-165ah). the pv panel characteristics are presented in table 3. advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 131 table 3 the specifications of the pv panel parameter value pm 255 w imp 8.32 a vmp 30.6 v isc 8.75 a vsc 37.6 v rsh 529.6538 ω rs 0.29192 ω module efficiency 15.58% fl, flt2, and inc mppt algorithms are tested via the matlab/simulink environment in the case of stable and variable irradiation. fig. 10 the global system in matlab/simulink 5.1. uniform irradiation the simulations of the pv system with the fl, flt2, and inc algorithms are done under uniform irradiation (880w/m²) and fixed temperature (26°c). the voltage and the current of the pv array are used as inputs to calculate the error and the variation of error that represent the input of the fl an flt2 controllers as shown in fig. 11 and fig. 12. they are designed following the steps in the previous section. fig. 11 fl algorithm in matlab/simulink advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 132 fig. 12 flt2 algorithm in matlab/simulink fig. 13 the pv voltage with inc, fl, and flt2 mppt algorithms fig. 14 the pv current with inc, fl, and flt2 mppt algorithms fig. 15 the pv power with inc, fl, and flt2 mppt algorithms fig. 13, fig. 14, and fig. 15 present pv voltage, pv current and pv power, respectively. fig. 15 shows that the power obtained by inc oscillates between 1265 and 1272w and the mpp is reached at t=0.25s. with fl, the power is equal to 1300w at time t=0.17s. it reaches the mpp and remains stable. by using an flt2 controller the mpp is reached at time t=0.08s with advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 133 remarkable stability. the maximum power is 1335w, which offers better results than those of the fl and inc controllers in terms of speed and output power. fig. 16 shows the output voltage of the dc/dc buck converter. fig. 16 the output voltage of buck converter with inc, fl, and flt2 mppt algorithms 5.2. non-uniform irradiation to test the performance of the three algorithms in different climatic conditions, non-uniform irradiation is applied to the input of the pv array. the irradiation takes 880w/m 2 at the beginning of the simulations. after t=3.2 s, it rapidly decreases to 310w/m 2 and returns to the initial state. fig. 17, fig. 18, and fig. 19 show the voltage, current, and power generated from the pv array with the three algorithms (flt2, fl, inc) in the case of variable irradiation. after the disturbance, the flt2 controller shows a better performance in term of response time, stability and generated power. fig. 17 the pv voltage with inc, fl, and flt2 mppt algorithms fig. 18 the pv current with inc, fl, and flt2 mppt algorithms advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 134 fig. 19 the pv voltage with inc, fl, and flt2 mppt algorithms fig. 20 shows the variation of the output voltage of the buck converter in the case of variable irradiation. fig. 20 the output voltage of buck converter with inc, fl, and flt2 mppt algorithms 6. experimental results in order to verify the real working of the studied mppt algorithms, a hardware setup was implemented, as shown in fig. 21. fig. 21 experimental setup with the pv array the setup consists of six tesla solar modules (solar ts250-p150-60), a dc/dc buck converter, compactrio controller, national instrument modules, irradiation sensor (irrb2 thies), temperature sensor (lm35) and load. for voltage measurement, ni 9225 (analog input module, 300vrms) is connected in parallel with the pv array. ni 9247 (analog input module, 50 arms) is connected in series with the pv array to sense the current. all sensed data is given to the national instrument compactrio ni 9025, an embedded real-time controller. it controls the mosfet of the dc/dc buck converter using ni 9474. the studied algorithms are programmed and implemented using labview software. labview is a graphical software from ni for system design, measurement, and control. the choice of this software is based on the ease of implementation of the program in the ni hardware as well as its simple interface of programming and use. advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 135 to read the experimental results, the front panel of labview software is used. the observed parameters, collected from the compactrio are irradiation, temperature, pv current, pv voltage, pv power and buck voltage, as presented in fig. 22. fl, flt2, and inc are tested via labview environment in the case of stable and variable irradiation. those experiments were done on may 2, 2019, on a sunny day. the measured parameters are shown in the figures below. fig. 22 labview front panel of the mppt algorithms 6.1. uniform irradiation the experiment of the pv system with the fl, flt2, and inc algorithms are done under uniform irradiation (880w/m²) and fixed temperature (26°c). fig. 23 experimental results of inc mppt algorithm at stable climatic conditions fig. 24 experimental results of fl mppt algorithm at stable climatic conditions fig. 25 experimental results of flt2 mppt algorithms at stable climatic conditions advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 136 fig. 23, fig. 24 and, fig. 25 present inc, fl and flt2 experimental results, respectively. fig. 23 shows that the power obtained by inc oscillates between 1217. with fl, the power is equal to 1271w. it reaches the mpp and remains stable. by using an flt2 controller, the mpp reaches 1335w, which offers better results than those of the fl and inc controllers in terms of speed and output power. 6.2. non-uniform irradiation to test the performance of the three algorithms in different climatic conditions, a variation of the incidence angle of irradiation was made. the irradiation takes 880w/m 2 at the beginning of the simulations. after t=3.2 s, it rapidly decreases to 310w/m 2 and returns to the initial state. the variation of the irradiation was obtained by the change of solar incidence angle. fig. 26, fig. 27, and fig. 28 show the experimental results of inc, fl, and flt2 mppt algorithms in the case of variable irradiation. after the disturbance, the flt2 controller shows a better performance in term of response time, stability and generated power. fig. 26 experimental results of inc mppt algorithm at variable irradiation fig. 27 experimental results of fl mppt algorithm at variable irradiation fig. 28 experimental results of flt2 mppt algorithm at variable irradiation 7. discussion from the previous simulations and experimental tests, we can see that the studied mppt controllers make it possible to reach the mpp in the case of fl, flt2, and inc algorithms. in the case of stable and variable irradiation, flt2 controller is faster than fl and inc controllers. in addition, the power obtained with flt2 controller is higher. the number of rules in the fl controller is very high, which stabilizes the system around the mpp but, at the same time, makes the controller more complex and increases the calculation time while the flt2 controller uses a minimized number of rules with lower and upper standard deviations to help avoid uncertainties and reduce computation time. unfortunately, flt2 controller is more difficult to use and understand than fl controller. advances in technology innovation, vol. 4, no. 3, 2019, pp. 125-139 137 the results of this work are presented in table 4. it gives the pv power and the efficiency of the three controllers. the difference between experimental results and simulations is due to several factors such as measurement errors and losses in the conversion chain. table 4 simulation and experimental results of inc, fl and flt2 mppt algorithms simulation results experimental results techniques pv power (w) efficiency (%) pv power (w) efficiency (%) inc 1265-1272 94.22 1217 90.14 fl 1300 96.29 1271 94.14 flt2 1335 98.81 1288 95.40 8. conclusions the objective of this paper is to extract the maximum power of a photovoltaic system using fl, flt2, and inc mppt algorithms. the proposed system was studied under two different conditions; fix and variable irradiation. matlab/simulink environment is used for simulation studies and labview software for experimental tests. the simulation results and experimental tests show that the best mppt technique is flt2. it shows high performance and gives a good track 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[35] m. s. fadali, s. jafarzadeh, and a. nadeh, “fuzzy tsk approximation using type-2 fuzzy logic systems and its application to modeling a photovoltaic array,” proc. american control conference, pp. 6454-6459, july 2010. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-aiti#5407 01-10.docx advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 non-linear finite element analysis of rc deep beam using cdp model pramod rai * span systems international co. ltd., phayathai, bangkok, thailand received 19 march 2020; received in revised form 23 july 2020; accepted 20 august 2020 doi: https://doi.org/10.46604/aiti.2021.5407 abstract finite element analysis (fea) is widely adopted these days to investigate relatively heavy structures such as reinforced concrete (rc) deep beam, which requires a higher investment of resources. this research aims to investigate a numerical modeling technique applicable to study the nonlinear behavior of rc deep beams by using fea based on the software, abaqus. the nonlinear behavior of an rc deep beam adapted from an earlier research work is captured by using the uniaxial compressive and tensile stress-strain relationship and damage parameters of concrete. the response of the fe model is verified with the experimental results in terms of the load to midspan deflection curve and damage distribution. the ultimate shear capacity predicted by the fe model is 0.75% lower, and the corresponding displacement is 6.92% higher than the experimental results. the adopted modeling technique and the constitutive concrete models demonstrate the promising results indicating its possibilities for the investigation of rc structures. keywords: nonlinear finite element, reinforced concrete deep beam, concrete damage plasticity, abaqus 1. introduction the 3-dimensional finite element modeling (fem) of rc structural systems or components can reflect the behaviors close to the experimental tests. however, the realistic simulation of concrete material is complicated when it deals with the nonlinear behavior of the materials. most importantly, the nonlinear constitutive characteristics of concrete, tension cracks, compression crushing, and bonding between steel and concrete, etc. cause difficulties in the modeling of rc [1-2]. nevertheless, with the proper understanding of such subject matters and following appropriate modeling techniques, the fem can be used to investigate and realize the behaviors of the rc structures that are even difficult to produce and test in the laboratory environmental conditions a deep beam is a widely used structural component in rc buildings these days, especially in high-rise buildings, such as footings, foundation pile caps, floor diaphragms, shear walls, etc. a typical rc deep beam constructed in the department of civil engineering, kasetsart university, thailand is shown in fig. 1. according to aci 318-14 [3], a deep beam is defined as the structural member having a shear span-to-depth (a/h) ratio less than 2 and having a clear span not exceeding four times the overall member depth (l/h<4). due to the nonlinear strain distribution over the depth, the bernoulli hypothesis is not valid in these beams. furthermore, deep beams are relatively difficult and require a higher investment of resources to investigate through the experimental test. for instance, performing an experimental study of deep beam requires high capacity test setup, more instrumentation, and higher human and financial resources. besides, the strength of the deep beam is altered by the size of the specimen, precisely * corresponding author. e-mail address: pramodwrai@gmail.com tel.: +064-940-7662 advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 2 fig. 1 a typical rc deep beam in an rc building fig. 2 a cracking in rc bent caps [5] referred to the size effect [4]. thus, any kind of alternation in dimensions of the beam results in a complicated scenario. fig. 2 shows a typical failure of the rc deep beam. the flexural-shear cracks in an rc deep beam propagating from the girder loading points to the supporting column [5]. abaqus, a fea based on software package, has dedicated its effort in the modeling of the concrete material models that have proven to be effective in realistic simulations by several researchers [2, 6-7]. mainly, two approaches have been adapted by the researchers for the investigation of concrete material: a smeared crack model and concrete damage plasticity (cdp) model. according to the user’s manual, the first approach can be applied for the models subjected to monotonic loading, while the other can be used in monotonicity as well as cyclic loading scenario [8]. several studies have been performed successfully by using both material models, and the cdp model is used in this study. the cdp model adopts the yield function given by lubliner et al. [9], and the other adopts the yield function modified by lee and fenves [10], in which the yield surface is defined in the plane stress and deviatoric plane conditions. earij et al. [7] investigated the behaviors of rc beams by using a dynamic explicit procedure together with the cdp model to simulate the loading-unloading–reloading behavior of the beams and to predict their crack patterns. mohamed, shoukry, and saeed [2] studied the rc deep beams with web openings under static loading conditions. hamoda et al. [11] performed the numerical assessments of rc beams with distributed depths along with experimental verification. likewise, hamdolah, kuang, and bijan [12] verified the predictability of the model by simulating the behavior of four full-scale and the exterior wide beam-column connections tested under reversed cyclic loadings. similarly, nzabonimpa, hong, and kim [13] used the cdp model to reproduce the experimental response of the mechanical beam-column joints of precast based frames. the authors also proposed a nonlinear finite element model based on cdp for the precast concrete beam-column jointed by mechanical plates. genikomsou and polak [14] performed 3-dimensional analyses of rc slab-column connections under static and pseudo-dynamic loadings to investigate their failure modes in terms of the ultimate loads and cracking patterns. it also reported that with the appropriate modeling of element size and mesh, and the constitutive modeling of concrete, the cdp model could predict the punching shear response of the slabs. to note, all the above-mentioned studies have emphasized that an accurate prediction of the concrete behavior could not be achieved by using the cdp model unless the appropriate parameters are carefully chosen, and the hardening/softening rules are applied with proper conception. the main objective of this study is to demonstrate a complete 3-dimensional fe modeling technique, including a reliable constitutive model and damage parameters of concrete, and to simulate the nonlinear behavior of rc deep beams by using the cdp model available in abaqus. the investigation adopts the damage parameter proposed by birtel and mark [15] which has rarely been used for the simulation of real structures. the devised technique and the material models are validated by using the result obtained from the experimental results available in the literature in terms of load-to-midspan deflection and damage patterns. advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 3 2. experimental study the experimental test of an rc deep beam carried out by demir, caglar, and ozturk [16] was adopted as the reference for the numerical modeling in this investigation. the geometry of the reference beam named db60/1.86-c1/sr is shown in fig. 3. according to the reference, the beam specimen was designed per the requirements given in the aci 318-14 code for rc deep beams and in a way that nodes and ties had adequate strengths to ensure the shear failure. the adequate sizes of load and support plates were selected to supply the sufficient confinement at nodes and thus to skip the failure. likewise, the standard ribbed reinforcing bars are used in the specimen to avoid failure at the nodes. the horizontal web reinforcement was spaced at 160 mm, and the vertical stirrups were spaced at 180 mm. fig. 3 the detailed drawings of the specimens (units in cm except for diameter of reinforcement in mm) [16] the 28-day compressive strength of the concrete (fc’) used in the specimen obtained from the compressive strength test of the cylinder is 18.1 mpa. comparably, the yield strength of tension reinforcement (6-22 mm in diameter) is 482 mpa, whereas the yield strength compression reinforcement (2-12 mm in diameter) and web reinforcements (8 mm in diameter) are 421 mpa. the beam specimen was subjected to a monotonic vertical static loading at the midspan via a hydraulic cylinder, and the applied load was measured through a load cell placed between the hydraulic cylinder and the specimen. the vertical displacements occurring at the bottom of the specimen were measured by the linear potentiometer. the beam supports consisted of a pin and a roller in the test. moreover, the top and bottom surfaces of the specimen at supports were tied and fastened to each other through steel rods to prevent the out-of-plane movement as shown in fig. 4. fig. 4 the test setup and measurement devices [16] the load to the midspan deflection curve of the beam specimen obtained from the experimental test of the beam specimen is illustrated in fig. 5. since the tabular data of the beam specimen was not provided in the reference study, the curve was traced manually from the available research paper. according to the reference study, the critical cracking load corresponding to the initiation of the first shear crack of the specimen is equal to 235 kn. beyond that point, the diagonal cracks initiated advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 4 simultaneously in both the shear spans throughout the strut axes. with further increase in the applied load, the gradual increase of the diagonal crack widths was observed until a sudden and brittle shear failure of the beam specimen occurred upon reaching the ultimate load-bearing capacity of struts. the failure mode of the beam specimen is a diagonal splitting failure at the ultimate stage. fig. 5 the experimental load to the midspan deflection response of the beam specimen [16] 3. finite element modeling 3.1. material modeling two types of techniques are available in abaqus for the simulation of concrete behavior: a smeared crack model and a cdp model [8]. the cdp model of concrete requires the concrete compressive and tensile constitutive relationship, cracking and crushing damage parameters, and other material parameters, such as the dilation angles, eccentricity, biaxial compressive strength to uniaxial compressive strength ratio, the coefficient k, and viscosity parameters [8]. various researchers have provided the reference values for the above-mentioned fea parameters. for instance, nzabonimpa, hong, and kim [13] have adopted the dilation angle values from 30⁰ to 56⁰ in order to calibrate the simulation of the beam-column joints. similarly, hamdolah, kuang, and bijan [12] have recommended the values in the range of 38⁰ to 42⁰. the various parameters obtained from several trials and adopted in this research are demonstrated in table 1. table 1 the cdpm parameters for concrete materials in abaqus parameter value description � 33 dilation angle � 0.1 eccentricity ���/��� 1.16 the ratio of initial equibiaxial compressive strength to initial uniaxial compressive strength. ( �) 0.667 the ratio of the second stress invariant to the tensile meridian � 0.001 viscosity parameter there are several analytical constitutive models suggested for concrete materials. the stress-strain curve of the concrete in compression used in this investigation is illustrated in fig. 6. the stress-strain relationship that was first proposed by popovics [17] and later modified by thoronfeldt et al. [18] was adopted in this research. according to this model, the stress-strain relationship of concrete in compression is obtained by: ' 0 0 ( ) ( 1) ( ) c c c c nc c nf f n = − + ε ε ε ε (1) 0 100 200 300 400 500 600 700 0 2 4 6 8 l o ad [ k n ] midspan displacement [mm] experiment advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 5 where �� and ��� are the compressive strength and strain corresponding to maximum stress, respectively. the ‘n’ in eq. [3] is defined by [1, 18]: 3 '0.4 10 ( ) 1.0cn f psi − = × + (2) the stress-strain relationship of concrete in tension is assumed to be linear up to the uniaxial tensile strength. the stress-strain curve of the concrete in tension and used in this investigation is shown in fig. 7. for the tension softening part, the relation is determined by using the exponential function proposed by belarbi and hsu [19-20] as demonstrated in eq. (3) and eq. (4): c t e if= ≤σ ε ε ε (3) 0.4( ) t t tif= > ε σ σ ε ε ε (4) '4700 ( ) c c e f mpa= (5) where the modulus of the elasticity of the concrete is determined by using the equation prescribed in aci 318-14 as expressed in eq. (5). the tensile strength of concrete is determined by: '0.62 ( ) t c f mpa=σ (6) similarly, the tensile strength of concrete and the corresponding strain is obtained by: t t c e = σ ε (7) the steel reinforcements and steel plates are modeled as elastic-perfectly plastic materials with the yield strength of 482 mpa and the poisson’s ratio value of � = 0.3 behaving similarly in tension and compression. the poisson’s ratio used for the concrete is equal to 0.18. fig. 6 the concrete uniaxial compressive stress-strain diagram fig. 7 the concrete uniaxial tensile stress-strain diagram in addition to the constitutive model and cdp parameters, the cdp model of concrete material in abaqus requires the definition of the compression and tension damage parameters which take account of the concrete crushing and cracking behavior, respectively. these damage parameters can take values, 0 and 1 represent no damage and fully damaged condition of the concrete, respectively. the damage parameters in compression and tension are defined based on the equation given by birtel and mark [15] and expressed by eq. (8) and eq. (9), respectively. 0 5 10 15 20 0 0.002 0.004 0.006 0.008 0.01 s tr es s [m p a] strain 0 1 2 3 0 0.002 0.004 0.006 0.008 0.01 s tr es s [m p a] strain advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 6 1 1 1 1 ( 1) c c c pl c c c c e d e b − − = − − + σ ε σ (8) 1 1 1 1 ( 1) t c t pl t t c t e d e b − − = − − + σ ε σ (9) the damage parameters in compression and tension are illustrated in fig. 8 and fig. 9, respectively. the coefficients b� and b� take values in the range of 0 to 1. birtel and mark [15] suggested b� = 0.7 and b� = 0.1 respectively, based on the experimental test results. however, after numbers of trials, the values b� = 0.7 and b� = 0.4 are found to provide a convergent solution for the fe model adopted in this study. fig. 8 the uniaxial compression damage parameter of concrete fig. 9 the uniaxial tension damage parameter of concrete 3.2. element type and meshing scheme the steel reinforcements are modeled by using a 2-node truss element (t3d2), and the concrete is modeled by using an 8-node solid finite element (c3d8). similarly, the solid finite element is used to define the plates at supports and the loading point. a parametric investigation is performed to find the most accurate mesh size for the fe model. as a result, an optimum mesh size is determined as 40 mm with an aspect ratio of nearly 1. a 3d model of the meshed concrete beam is shown in fig. 10. all the reinforcements and plates are meshed with a finite element size of 40 mm. fig. 10 the 3d model of the beam with the embedded rebar 3.3. material bonding and boundary conditions the steel reinforcements are embedded inside the concrete solid elements which don’t allow the slip of the reinforcement. when the truss element of reinforcement is embedded inside the host concrete solid element, the translation degrees of freedom of the embedded node are constrained to be the interpolated values of the corresponding degrees of freedom of the host 0 0.25 0.5 0.75 1 0 0.005 0.01 0.015 0.02 d c plastic strain 0 0.25 0.5 0.75 1 0.000 0.005 0.010 0.015 0.020 d t cracking strain advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 7 elements [8]. further, the contact between the surfaces of concrete and the steel plates is assigned as the tie constraint. a surface-based tie constraint in abaqus ties the two separate surfaces together so that there is no relative motion between them; thus, the translational and rotational motion, as well as all other active degrees of freedom, are equal for the paired surfaces [8]. at one of the end supports, the translation degrees of freedom are constrained in all directions, which represents the pinned-support, whereas at the other end, the translational and rotational degrees of freedom in the xand y-direction are made free, which represents a roller support condition. 4. results and discussion the comparison between the load to the midspan deflection response obtained from the experimental test, and the fea result is demonstrated in fig. 11. in the initial loading stage, the response of the specimen from both approaches is very close to each other. when the applied load is close to the value of the critical cracking load, 235 kn (fig. 11), the load-to-midspan response of the fe model begins to become slightly stiffer than the test result. the difference in the stiffness continues almost near to the ultimate loading stage. however, shortly after the ultimate loading stage, the responses of the beam specimen from both approaches abruptly decline and indicate the brittle shear failure modes. fig. 11 the comparison of the experimental results with fea eir widths continue after the critical cracking loading stage. nevertheless, such kind of micro-crack effects is not included in the fe model [8]. the higher stiffness in the response of the fe model, compared to the experimental test, nearly after the critical loading stage (fig. 11) have resulted due to the occurrence of the micro-cracks in the concrete material during the experiment. when the applied load is increased further, the stiffness of the fe model begins to reduce gradually and is close to the experimental test result. such a reduction in stiffness in the fe model is caused by the increase in the magnitude of the principal strains responsible for the diagonal tensile failure and the compression crushing of the concrete material as depicted by the stress-strain relationship in fig. 6 and fig. 7. as the value of the maximum principal strain (tensile strain) exceeds the strain value corresponding to the tensile strength of the concrete, and the minimum principal strain (compressive strain) value exceeds the strain value corresponding to the compressive strength of the concrete, the stiffness of the beam initiates to reduce. this is the reason for the decrease in the stiffness of the fe model at the higher loading stage. when the applied load reaches 659 kn, the stiffness of the fe model drops suddenly and indicates the brittle shear failure. the corresponding midspan deflection is equal to 5.41 mm. in the experimental test results, the ultimate shear failure of the beam specimen occurrs at 664 kn, and the midspan displacement at this stage is 5.06 mm. thus, the ultimate loading capacity predicted by the fe model is 0.75 % lower, and the corresponding midspan displacement is 6.92 % higher than the experimental test results. it is evident that the fe model reflects the load to the midspan behavior of the deep beam close to the experimental test results. especially, the ultimate shear failure behavior of the experimentally tested beam specimen is reflected precisely by the fe model. 0 100 200 300 400 500 600 700 0 1 2 3 4 5 6 7 l o ad [ k n ] midspan displacement [mm] experiment fea advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 8 in addition to the load to midspan response, the damage distributions of the experimentally tested specimen during the ultimate loading stage are compared to the simulated model. the ultimate failure damage during the experimental test is illustrated in fig. 12, in which the diagonal shear crack running from the loading point to the support diagonally can be seen clearly. according to the reference, the beam specimen fails in the diagonal splitting failure mode. the damage distribution in the fe model in terms of the maximum principal plastic strain (pe-max. principal) is shown in fig. 13, and the directions of such strains are presented graphically in fig. 14. on the basis of the user’s manual, the value of the maximum principal plastic strain is the main indicator of crack initiation in the concrete damage plasticity model in abaqus. fig. 12 the ultimate failure damage of the specimen in the tests [16] fig. 13 the ultimate failure damage of the specimen in the fe model in terms of the maximum principal plastic strain fig. 14 the direction of the maximum principal plastic strain at the ultimate loading stage cracks initiate when the values of the maximum principal plastic strains are positive, and the direction of the cracks is perpendicular to the direction of these strains [8]. the damage distribution visualized in fig. 13 and fig. 14, in which the maximum principal plastic strains are vastly concentrated in the midlength of the diagonal strut, resembles with the experimentally observed damage in fig. 12. the direction of the critical shear crack, running from loading point to the support and responsible for the ultimate failure of the beam, in fig. 14 is closely perpendicular to the directions of strains depicted in fig. 12. additionally, the contour plots of the minimum principal plastic strain (pe-min. principal) and its direction are depicted in fig. 15 and fig. 16, respectively. in another perspective, fig. 16 shows the path in which the applied load travels from the loading point to the supports. the compression struts manifesting the bottle-shaped diagonal struts and indicating a clear behavior of an rc deep beam can be seen in fig. 16. to sum up, it can be argued that the fe model successfully replicate the damage distribution that is manifested by the rc deep beam specimen during the ultimate loading stage of the experimental test. advances in technology innovation, vol. 6, no. 1, 2021, pp. 01-10 9 fig. 15 the ultimate failure damage of the specimen in the fe model in terms of minimum principal plastic strain fig. 16 the direction of the minimum principal plastic strain at the ultimate loading stage 5. conclusions this paper demonstrated a finite element modeling technique that can be applied for nonlinear analysis of reinforced concrete structures. particularly, the simulation technique focused on the nonlinear behavior of concrete which was based on the cdp material model available in the fea based software, abaqus. an rc deep beam specimen tested experimentally in an earlier research study was simulated, and the output results were achieved under a considerable degree of accuracy. the simulated fe model presented the excellent agreement with the experimentally tested beam specimen which manifested the brittle shear failure at the ultimate failure stage. while the ultimate load-carrying capacity of the beam specimen predicted by the fe model was lower by 0.75%, the corresponding displacement was higher by 6.92% compared to the experimental test results. the constitutive models and damage parameters for the concrete that are proposed by earlier researchers and adopted in this research demonstrated the adequacy in reflecting the precise behavior of the rc deep beam. the damage distribution predicted by the fe model was close to the damage that occurred during the ultimate failure loading stage of the experimental test. additionally, the constitutive model and damage parameters of the concrete material adopted in this study can be applied for the investigation of various rc structures including the parameterized nonlinear finite element analysis to investigate the nonlinear behavior of rc deep beams. conflicts of interest the author declares no conflict of interest. references [1] y. dere, a. asgari, e. d. sotelino, and g. c. archer, “failure prediction of skewed jointed plain concrete pavements using 3d fe analysis,” engineering failure analysis, vol. 13, no. 6, pp. 898-913, september 2006. 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[17] s. popovics, “a numerical approach to the complete stress-strain curve of concrete,” cement concrete research, vol. 3, no. 5, pp. 583-599, september 1973. [18] e. thorenfeldt, a. tomaszewicz, and j. j. jensen, “mechanical properties of high-strength concrete and applications in design,” symposium on utilization of high-strength concrete (stavanger, norway), tapir, trondheim, norway, 1987. [19] a. belarbi and t. t. hsu, “constitutive laws of concrete in tension and reinforcing bars stiffened by concrete,” structural journal, vol. 91, no. 4, pp. 465-474, july 1994. [20] x. b. d. pang and t. t. hsu, “behavior of reinforced concrete membrane elements in shear,” structural journal, vol. 92, no. 6, pp. 665-679, november 1995. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 4-aiti#5476 31-38.docx advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 multicriteria decision analysis on information security policy: a prioritization approach jonathan salar cabrera 1,* , ariel roy luceño reyes 2 , cindy almosura lasco 1 1 institute of computing and engineering, davao oriental state college of science and technology, philippines 2 college of information and computing, university of southeastern philippines, philippines received 06 april 2020; received in revised form 08 august 2020; accepted 11 october 2020 doi: https://doi.org/10.46604/aiti.2021.5476 abstract security is the most serious concern in the digital environment. to provide a sound and firm security policy, a multi-holistic approach must be considered when making strategic decisions. thus, the objective of this study was to evaluate the information security (is) and decision making of davao oriental state university (dorsu) using the analytic hierarchy process (ahp) approach. the four aspects of is, namely, the technology, management, economy, and culture were used with the three is components consisting of confidentiality, integrity, and availability to implement the ahp. the results showed that the technology and management have higher significant values than the economic and cultural aspects. meanwhile, for the is components, the integrity signifies the highest priority followed by confidentiality, lastly, and availability. these results emphasize an imbalance in implementing is policy, which must be addressed to ensure that the data integrity, confidentiality, and availability are balanced, particularly during the information exchange transactions. keywords: analytic hierarchy process, evaluation process, information security, prioritization 1. introduction data is an essential element in the organization that needs to be protected. therefore, attacks usually focus on the internal controls of the organization that enables the hampering of information. such views on the importance of data-enabled modern organizations to take an advanced step in ensuring that data is protected from unauthorized access. this involves integrating technology and the employment of governance and policy enforcement mechanisms to guarantee data protection and compliance. first-world countries like the usa and the united kingdom have been strengthening their laws and regulations on information security (is) to prevent unwanted events such as the recent facebook–cambridge analytica data scandal. it is unfortunate that, in the philippines, the current setting of its is law does not conform yet to the current trend of the is environment. however, in terms of is control and security, organizations can follow international standards. deciding to make the best decision of what security policies to implement is a challenging task, especially when there are several aspects to consider. in the fast-changing information age, the is policy in the organization is also evolving to catch-up with the change. subsequently, all possible options in the is aspects should be considered to develop effective and appropriate policy. literature shows that is developments mainly focused on technical and managerial aspects [1]. however, in the information age, information technology is merely affecting cultural and economic aspects. combining cultural, economic, technology, and management aspects into is-related decisions expand the views from different perspectives. hence, a suitable and appropriate method is highly required to analyze by incorporating those aspects carefully. thus, mcda is highly recommended. * corresponding author. e-mail address: jonathan.cabrera@doscst.edu.ph advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 32 in this paper, the ahp approach under mcda is used to evaluate the is decision making of davao oriental state university (dorsu). section 2 describes the related literature of the components and aspects of the information security applied in this study. section 3 discussed the methodology with the mcda-ahp evaluation together with partial results as the steps progress. the results and discussions are discussed in section 4, whereas the conclusion and the recommendations are given in section 5. 2. literature review it is necessary to briefly review the elements of the information system to fully understand the importance of information security. typically, information systems in an organizational setting are blends of software, hardware, and telecommunications networks to collect, produce, and distribute a useful data [2]. on the other hand, is is defined as creating a set of practices that keeps the information and information systems secure from the unauthorized access, usage, leakage, retardation, alteration, or destruction [3-4]. with the significance of the information security, its role is vital due to the digitalization of the business processes of the organization. sharing information using various information technologies provides risk. as a result, security is highly needed. in the fast-changing information era, is plays an important role that the organization should put is as a priority to secure thrust in the digital environment. further, works about information show various matters concerning is policy [5-7]. the confidentiality, integrity, and availability (cia) triad is considered as the core principle of is [8]. however, as stated in the five pillar information assurance data security model [9-10], a continuous debate suggests that aside from confidentiality, integrity, and availability, the is core principle can still be extended to include authenticity and non-repudiation features. cia, or often called the security triad, should always fulfill to achieve the is objectives in the organization. confidentiality, as the first component of the cia triad, denotes thwarting the information leakage to adversaries which is very essential in maintaining the secrecy of personal information held by the system [8]. integrity, on the other hand, is the second component of the cia triad and lies in upholding and assuring the truthfulness and dependability of data. this component denotes that modifications on data must not be made without authorization or proper consent to conduct data changes. aside from the confidentiality, it is necessary that is must provide a message integrity, which refers to ensuring that messages have never been modified, altered or tampered with [8]. lastly, the availability, the third out of three components of the cia triad, is thought as a must since it is significant for any information system to be accessible whenever it is needed. it means that the proper functionality of the computing systems which are to store, process, access, and protect the information must be maintained to ensure the accessibility of security controls and communication channels at all times. guaranteeing availability also encompasses prevention from denial-of-service attacks [8]. subsequently, the cia is always a part of the is aspects, referring to the perspectives of the organization or business. mostly, the organization focuses on the management and technical aspects of is [1]. furthermore, recent studies are giving high emphasis on cultural [11] and economic aspects [12] in the information security. in general, aspects of the information security can be categorized into the technology, management, culture, and economy. technology is the most vital guard to ensure the security of information [13]. since the start of the digital age, apprehensions were mostly directed to safeguarding information, and technology, which includes hardware, information/data, and applications. computers, wired/wireless networks, and internet security were amongst the primary concern [14]. likewise, the management in information security is all about ensuring information handling in the organization. while the economy is another crucial aspect of is, it has been recently recognized that economic concerns play a noteworthy role in warranting the level of security measures within an organization [1]. by disregarding the different economic aspects involved in is which includes investment, incentives, and financial information sharing, it will be difficult to determine the economic benefit of such protections [15]. accordingly, a measurement of the economic aspect of is can be done quantitatively. last of all, the cultural aspect of information security refers to human attributes such as behaviors, attitudes, and values that contribute to the protection of all kinds of information in advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 33 a given organization [16]. it is also the least important aspect in almost all organizations. in addition, as stated by ngo et al. [17], information security culture is formed by the conventional conduct and actions of workforces and the organization as a whole, and how things are done. in overall assessment in the information security aspect, the three components (i.e., confidentiality, integrity, and availability) should exist altogether to guarantee that the information is confident in terms of protecting disclosure of information, without any alteration or modification by unauthorized actions as well as it is available when required by authenticated person or systems [13]. 3. methodology information security policies are critical because they must be able to review the risk appetite of an organization's management. the proper evaluation of is policies will not only address the need of an organization to create a mechanism that protects it from internal and external threats, but also help in directing a managerial mindset on implementing security within the organization [18]. hence, with such high regard on the safety, the methodology of this paper is focused mainly on evaluating is policy using the ahp framework under mcda concepts as shown in fig. 1. this approach has three levels: goal, criteria, and indicators. the goal is top-level, which specifies the objective of this paper: the information security policy evaluation; the second level is the criteria, which are four aspects of the information security policy; and last but not least, the indicators which are the three security components. fig. 1 mcda-ahp framework for information security policy assessment mcda is a useful and valuable tool when applying complex decisions. using a structured approach, mcda analyzes and measures a series of alternatives or criteria to discern their relative importance and identify which criterion is the most significant. likewise, the ahp is an mcda approach and a decision support tool introduced by saaty [19-20]. ahp is a hierarchical approach tool used to solve complex decision problems. the ahp hierarchy is a top to bottom approach, from the top is the goal, criteria are in the middle, and at the bottom is the indicators presented in fig. 1 [21]. the weights of each criterion and indicators must be determined using pairwise comparisons. the weights of the criteria and indicators show the importance of decision making. there are six steps to process a complex problem using ahp [19, 22]. as described in the paper of cabrera & lee [21], the first step is when the problem has already been identified, break the problem down into its component factors. second, these component factors are arranged and constructed into a hierarchy, then a pairwise comparison matrix is built on the third step. hence, the decision-makers (dm) can systematically assess the alternatives for each of the chosen criteria or indicators. during the fourth step, the weights of each criterion are calculated based on the values assigned by the dm and on the fifth step, the results are then analyzed to establish the prioritization of the criteria and indicators. after that, the consistency is checked to determine the reliability of the results. advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 34 the consistency ratio (cr) is the key component of ahp. the cr should be less than 10%, so that the comparison matrix is considered acceptable, and the judgements of the dm are reliable (see sub-section 3.3 for the computation). the succeeding sub-sections are the processes to come up with the acceptable relative weights in every criterion and indicators. 3.1. pairwise comparison in order to use the ahp, a pairwise comparison matrix must be conducted first. this was done by comparing each criterion of the study based on saaty’s scale [19] as displayed in table 1. the results were in integer values (i.e., 1 to 9). the higher number means that the chosen factor is more important than the other. table 1 the fundamental scale and its description as described by cabrera & lee [21] scale judgement of preference description 1 equally important two factors contribute equally to the objective 3 moderate experience and judgement slightly favor one over the other 5 strong experience and judgement strongly favor one over the other 7 very strong experience and judgement very strongly favor one over the other 9 extremely important the evidence favoring one over other is of the highest possible validity 2, 4, 6, 8 intermediate values when compromise is needed 3.2. normalization the normalization in ahp is a probability assigned to the suitability of each alternative. this step used the normalized matrix. this matrix is used to add the values in each column. in the pairwise comparison matrix, the entry in each column is divided by the sum of the column. then, the result will be input in the corresponding cell in the normalized matrix. if the total value in the column is 1, the results in all cells in the column are normalized values as described in eq. (1). finally, the priority vector (pv) (i.e., the weights of the criterion or indicator) is computed by dividing the sum of the column of the matrix by the number of criteria used (n), as shown in eq. (2), the cij in eq. (1) refers to the value of a criterion or indicator in the pairwise comparison matrix. the xij is the normalized score, while pvij refers to the weights of each criterion or indicator. the pvs give the relative importance weights of the criteria or indicators. 1 / n ij ij ij i x c c = = ∑ (1) 1 / n ij ij j pv x n = =∑ (2) 3.3. consistency analysis the consistency analysis (ca) is the last process in ahp. in order to derive the cr, the ca process has to undergo three steps. the first step is to calculate the consistency measure (cm) which can be obtained through multiplying the pairwise matrix with the pv. the result is then divided into the weighted sum vector with its criterion weights. the second step is calculating the consistency index (ci) as described in eq. (3). the λmax refers to the sum of the cm divided by the n (i.e., number of criteria or indicators). finally, the cr is computed by the ci over the ri as described in eq. (4). max( ) / ( 1)ci n n= − −λ (3) /cr ci ri= (4) the λmax values are set to 4.03, 3.01, 3.01, 3.04, and 3.07 for the goal, technology, management, economy, and culture, respectively. the values of the random index (ri) developed by saaty [20]and its corresponding number of compared criteria are 0.00, 0.58, 0.90, 1.12, 1.24, 1.32, and 1.41 for the 2, 3, 4, 5, 6, 7, and 8, respectively. advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 35 4. results and discussion the advantage of ahp is the ability to quantify the inconsistency in the judgment of the decision-makers. as stated by saaty [19, 22], the cr should be less than ten percent (10%) to guarantee that the decision is reasonably correct. if inconsistency occurs, the survey should be repeated until the cr is less than ten percent (10%). the survey should be repeated in cases where cr is less than ten percent to guarantee the level of consistency at an acceptable level. the researchers fulfilled the pairwise comparison matrix from the survey conducted to the it head of the davao oriental state university. the it head is responsible for managing and supervising the it functions of the university, which includes one main campus and three external campuses, situated on different municipalities in the province of davao oriental. as of this writing, the university has an overall population of approximately 10,000 students with all these data stored in the electronic school's management system (esms) and access to the school's e-learning management system (elms) that are both administered and managed by the information technology services unit. there were five comparison matrices created, representing the it head's opinion in the current is policy implementations according to the ahp framework. in terms of the is policy, the technology criterion is highly prioritized, followed by management, economy, and cultural aspect, respectively as shown in table 2. table 2 matrix concerning the goal criteria t m e c technology (t) 1 2 3 4 management (m) 0.5 1 2 3 economy (e) 0.33 0.5 1 2 culture (c) 0.25 0.33 0.5 1 sum 2.08 3.83 6.5 10 moreover, tables 3-6 show the importance of the three alternatives (i.e., confidentiality, integrity, and availability) for every single criterion. in the technology perspective, integrity is highly prioritized followed by availability and confidentiality. in the case of management, the topmost priority is the integrity. the next is the confidentiality and the last is the availability. finally, economically and culturally speaking, the confidentiality indicator is prioritized followed by the integrity and availability. table 3 pairwise comparison matrix concerning technology criteria c i a confidentiality (c) 1.00 0.33 0.50 integrity (i) 3.00 1.00 2.00 availability (a) 2.00 0.50 1.00 sum 6.00 1.83 3.50 table 4 pairwise comparison matrix concerning the management criteria c i a confidentiality (c) 1.00 0.50 2.00 integrity (i) 2.00 1.00 3.00 availability (a) 0.50 0.33 1.00 sum 3.50 1.83 6.00 table 5 pairwise comparison matrix concerning the economy criteria c i a confidentiality (c) 1.00 3.00 5.00 integrity (i) 0.33 1.00 3.00 availability (a) 0.20 0.33 1.00 sum 1.53 4.33 9.00 table 6 pairwise comparison concerning the culture criteria c i a confidentiality (c) 1.00 3.00 4.00 integrity (i) 0.33 1.00 3.00 availability (a) 0.25 0.33 1.00 sum 1.58 4.33 8.00 on the other hand, tables 7-11 show the normalized matrix derived from tables 2-6, respectively, which are the pairwise comparison matrices. table 7 shows the percentage value of the criteria concerning the goal. it is revealed that technology is the dominant aspect of the overall is policy perspectives, which accounted for 47% followed by 28%, 16%, and 10% for the management, economy, and culture. advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 36 furthermore, tables 8-11 represent the pv (i.e., weight) of the three alternatives (i.e., confidentiality, integrity, and availability). table 8 shows that integrity is rank first with a 54% allocation in choosing the technology aspect in is. the availability and confidentiality are only 30% and 16%, respectively. also, the management aspect, integrity is prioritized first with 54% followed by confidentiality with 30% and 16% for availability (see table 9). from the economic point of view, the confidentiality is significantly vital with an accounted value of 63%, while the integrity and availability are 26% and 11%, respectively as shown in table 10. looking at the cultural perspective, as shown in table 11, confidentiality is highly emphasized with a value of 61%. the next is 27% for integrity and 12% for availability. table 7 normalized matrix with the relative weights concerning the goal criteria t m e c total pv cm t 0.48 0.52 0.46 0.40 1.86 0.47 4.05 m 0.24 0.26 0.31 0.30 1.11 0.28 4.04 e 0.16 0.13 0.15 0.20 0.64 0.16 4.02 c 0.12 0.09 0.08 0.10 0.38 0.10 4.02 sum 1.00 1.00 1.00 1.00 1.00 table 8 normalized matrix with the relative weights concerning the technology indicators c i a total pv cm c 0.17 0.18 0.14 0.49 0.16 3.00 i 0.50 0.55 0.57 1.62 0.54 3.01 a 0.33 0.27 0.29 0.89 0.30 3.01 sum 1.00 1.00 1.00 1.00 table 9 normalized matrix with the relative weights concerning the management indicators c i a total pv cm c 0.29 0.27 0.33 0.89 0.30 3.01 i 0.57 0.55 0.50 1.62 0.54 3.01 a 0.14 0.18 0.17 0.49 0.16 3.00 sum 1.00 1.00 1.00 1.00 table 10 normalized matrix with the relative weights concerning the economy indicators c i a total pv cm c 0.65 0.69 0.56 1.90 0.63 3.07 i 0.22 0.23 0.33 0.78 0.26 3.03 a 0.13 0.08 0.11 0.32 0.11 3.01 sum 1.00 1.00 1.00 1.00 table 11 normalized matrix with the relative weights concerning the culture indicators c i a total pv cm c 0.63 0.69 0.50 1.82 0.61 3.13 i 0.21 0.23 0.38 0.82 0.27 3.07 a 0.16 0.08 0.13 0.36 0.12 3.02 sum 1.00 1.00 1.00 1.00 to determine the correctness of the percentage value stipulated in the previous paragraph, cr has to be computed. the cr was found to be 1.1%, 0.8%, 0.8%, 3.3%, and 6.4% for the goal, technology, management, economy, and culture, individually. the cr results specify that in the pairwise comparison and it showed that there is an adequate level of coherency. thus, it can be concluded that the values are coherently acceptable. the last goal of the analysis is to generate global or overall priorities as the final weight of the indicators. the result is shown in table 12 and fig. 2 and 3. based on the results, it can be concluded that integrity is observed as the main priority as compared to confidentiality and availability. integrity accounted for 47%, while confidentiality and availability were 32% and 22%, respectively as shown in fig. 3. advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 37 table 12 the overall weight of the indicators goal confidentiality integrity availability overall technology 0.075 0.254 0.141 0.470 management 0.084 0.151 0.045 0.280 economy 0.101 0.042 0.018 0.161 culture 0.061 0.027 0.012 0.100 overall 0.321 0.473 0.216 fig. 2 overall rating on information security aspects fig. 3 overall rating on information security components in the information security aspects, the evaluation result showed that technology is the most important followed by the management while the economic and cultural aspects of is gained the third and fourth spots, correspondingly. as evident to its overall ratings, particularly, dorsu has placed more serious concern on technology with 47% of the ratings, as compared to management with 28%, the economy with 16%, and 10% for culture (see fig. 2). the result reflects that the dorsu implementation for information security policy is imbalanced. various literature shows the importance of cultural [11, 23-25] and economic aspect [12, 16] as the basis on the effective and balances information security policy implementations. the result also shows that information security is a challenging issue in dorsu governance. 5. conclusions and recommendations this study gives a good reason for the application of the ahp approach in the evaluation of is policy. integrating multiple criteria and indicators in the mcda shows a tangible advantage. the mcda-ahp approach showcases the ability to check the inconsistency judgement of the decision-makers in a various criteria scenario. what is more, this approach also displays that decision-makers will be assisted in evaluating the implementation of the is policy. in the aspect of is, technology is found to be the highest priority. likewise, concerning the is component, integrity signifies the highest priority followed by confidentiality and availability. based on the results of this paper, the following recommendations are identified. first, improve the employee’s security awareness by providing training to achieve a comprehensive is culture in the organization. second, economic aspects should be addressed as part of the important factors in is policy. finally, it is essential to note that data integrity, confidentiality, and availability should be balanced, particularly during information exchange transactions bound outside in the organization’s computer networks [26]. other mcda approaches like analytic network process (anp) and fuzzy ahp/anp can also be explored in the future to validate the result in other perspectives. besides, expanding the number of respondents that will include all known decision-makers in the organization that may or may not have an it background in order to give a generalized and holistic view of the result. advances in technology innovation, vol. 6, no. 1, 2021, pp. 31-38 38 conflicts of interest the author declares no conflict of interest. references [1] r. anderson, “why information security is hard: an economic perspective,” proc. annual computer security applications conference, december 2001, pp. 358-365. 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[26] j. hwang and i. syamsuddin, “information security policy decision making: an analytical hierarchy process approach,” third asia international conference on modeling & simulation, may 2009, pp. 158-163. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 dynamic biometric signature an effective alternative for electronic authentication vladimír smejkal 1,* , jindřich kodl 2 1 moravian university college olomouc, olomouc, czech republic. 2 authorized expert of cryptology and information systems security, prague, czech republic. received 07 june 2017; received in revised form 13 june 2017; accepted 23 december 2017 abstract the use of dynamic biometric methods for the authentication of people provides significantly greater security than the use of the static ones. the variance of individual dynamic properties of a person, which protects biometric methods against attacks, can be the weak point of these methods at the same time. this paper summarizes the results of a long-term research, which shows that a dbs demonstrates practically absolute resistance to forging and that the stability of signatures provided by test subjects in various situations is high. factors such as alcohol and stress have no influence on signature stability, either. the results of the experiments showed that the handwritten signature obtained through long practice and the consolidation of the dynamic stereotype, is so automated and stored so deep in the human brain, that its involuntary performance also allows other processes to take place in the cerebral cortex. the dynamic stereotype is composed of psychological, anatomical and motor characteristics of each person. it was also proven to be true that the use of different devices did not have a major impact on the stability of signatures, which is of importance in the case of a blanket deployment. the carried out experiments conclusively showed that the aspects that could have an impact on the stability of a signature did not manifest themselves in such a way that we could not trust these methods even used on commercially available devices. in the conclusion of the paper, the possible directions of research are suggested. keywords: biometric authentication methods, dynamic biometric signature, electronic signature, authentication 1. introduction one negative aspect of the current trend of connecting ever more devices in cyberspace (primarily thanks to the internet of things) is the increased risk of them being attacked and exploited. all devices and all information systems must, therefore, be constructed from the very start to be secure against possible risks. the key assumptions for constructing secure information systems are ensuring the quality identification and authentication of people, assets, and events in the system – on the one hand to prevent cyber attacks and other criminal activities in cyberspace, and on the other to record all incidents and their circumstances. this is an important tool for investigation, and also a source of feedback for improving security measures. the opinion that multifactor authentication is essential to ensure an adequate level of security for information systems is already practically universal [1]. it is also necessary to understand that in open systems we do not ensure proper data protection only through integrity and trust, but a sophisticated authentication process is a very important point in terms of the protection of * corresponding author. e-mail address: smejkal@znalci.cz. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 167 data, respectively the assets of the subject in question. it is only possible to launch the authorisation process which will provide the authenticated person with access to ict services after successful and reliable authorization. the used authentication methods should meet the requirements for variability both from the perspective of the technologies and used systems and from the perspective of the users themselves. the proposed solutions must also respect the legislation in force in different countries and permit the execution of legal acts according to the intentions of both sides. the authentication methods must provide a high level of protection against their breaking or exploitation, while at the same time remaining user-friendly. they must be secure, easy to use, unobtrusive and also have reasonable implementation costs. the addition of an extra factor for authentication also brings an increase in the technological, organization, and primarily financial demands of such a solution. hence, this field is still being developed, and the search for the “holy grail of authentication” continues. in particular, at a time when there is more and more emphasis on protection of personal data with concurrent pressure to both simplify and make the process of identification and authentication more pleasant for the user. for these reasons, it is important to focus on the issue of multifactor authentication, in particular, those where biometric methods play an important role. 2. biometric authentication methods biometry is a set of scientific findings, which focuse on the investigation and subsequent practical use of measurable characteristics of living organisms with the aim of unequivocally identifying them ( first identification) or verifying them ( then authentication) [2]. biometric authentication methods appear to be a reasonable compromise between demands on users and/or tools for authentication while not reducing the level of security. there are many biometric methods, but they can basically be split into three groups: (1) static (2) static with testing for the presence of a person (3) dynamic we must make a fundamental distinction between static and dynamic methods, where static methods are basically a continuation of the authentication principle that the user “has something”, even if this means something that is a part of their physiology. this means that there remains a risk of the falsification of biometric information (faking fingerprints, iris image, etc.) or their use through coercion. hence, for example, at the current time, the authentication methods used for mobile telephones can serve at most only to reassure users or for simple “superficial” protection. dynamic authentication methods have been arousing interest. we can assume a higher level of protection from abuse, as we are moving from the variant that the user “has something” to the variant in which the user “knows something” and, what is more, they “do not know what they know”. these are processes where the primary impulse arises in the central nervous system in the human brain with a predefined intensity and duration. the nervous system then activates the relevant muscles in a defined order, so that the user can perform a certain activity a signature, a certain gait, a gesture, and so on. in this case, therefore, biometry is based on the characteristics of a person’s behavior. the use of static methods connected with a test for the presence of a (living) person is something of an intermediate step. this is usually performed by detecting body temperature or, at a more sophisticated level, by detecting the circulation of blood in vessels or by measuring oxyhaemoglobin concentration. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 168 for each method, there are several characteristics that will determine its usefulness. these are, in particular: accuracy and reliability (expressed through parameters such as frr, far, fer, fir, fmr, fnmr [3]), security (protection against forgery and coercion, as well as against attacks on biometric images and samples), user acceptability, costs of acquisition and operation, etc. sometimes, these qualities can be directly in opposition a simpler, and more accurate method might be easier to attack (e.g. the faking of fingerprints). depending on the number of features used for recognition biometric systems, we can use a unimodal method (if only one of the biometric characteristics is used), or a multimodal one (if more than one characteristic is used). 3. dynamic biometric signature a dynamic biometric signature appears increasingly appropriate to authenticate people and also documents containing important information. it contains information about how the signature was created, and thus reflects characteristics of the signers, their habits and behavior, as well as the fact that they made the signature consciously. these characteristics represent a biometric footprint that is unique for each person and cannot be reproduced by a forger (unlike the actual image of the signature itself, which only makes up one of the parameters of the biometric footprint). these include the basic features of a handwritten signature: • the duration of the signature process, including the periods between strokes • points and curves in different parts of the signature • the pressure exerted by the pen on the pad during different parts of the signature • the overall size of the signature • the form and shape of the signature • the length and angle of lines, arcs and curves, the number of loops • the speed of individual stokes, acceleration and deceleration one of the important attributes of a dbs is that it contains not only the element that the writer is alive, but also the fact that the signature was created by the writer consciously. therefore, there is no need to develop additional mechanisms to test whether the subject is present, alive, or not unlike with static biometric methods (checking the print of a finger, palm, iris etc.). it is also legally beneficial, in that we can rely on the (theoretically rebuttable) assumption that people knew what they were signing [4]. a special tablet (pad) is currently used for scanning a dbs. when acquiring signature data, biometric data [mostly x(t), y(t), p(t), t)] are also acquired. this biometric information is also used to calculate additional parameters, defined using the iso/iec 19794-11 standard [5]. this standard contains a description of the mandatory parameters and formats of the biometric data. the system then scans the parameters of the signature, adds them to the information from the signed document, for example, the user name, current time and date, and about the device used. these data are encrypted and create the so-called biometric data that are sent for further processing. in this way, we acquire authentication data for the signer with subsequent securing against forgery. at the same time, the process simulates the standard process of a traditional signature. a dbs may be used as a handwritten signature, but it is also possible to use it in the form of a one-off password or graphical pattern that the user writes on the sensor or shows with a gesture for example using a mobile phone. a dbs would appear to be an effective alternative to the only technology used for electronic signatures to date a signature based on asymmetric cryptography. it can be used with an advantage in cases when advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 169 the implementation of certificates (partly due to their limited validity period) and the secure “concealment” of private keys significantly interfere with the normal activities of signers. from the perspective of users, it is also the most pleasant method, as the act of signing is something we do today and every day without needing any special knowledge, skills or the ownership of any secret. handwritten signatures are also one of the most socially accepted biometric features. 4. risks involved with the use of a dynamic biometric signature recently, the static authentication tools provided by the makers of mass-used devices (mobile phones, laptops, etc.), such as fingerprint, palm or face scanners have been accepted in a sickly optimistic way. at the same time, the successful cases of attacking these devices are known. e.g. [18-21]. (new authentication tool face id on iphone x has also been subjected to attacks since it was released. they have been unsuccessful so far [22], but according to the authors, it is only a matter of time (and money). perhaps, the attacks failed because of the fact that face id is not a mere static method. greater safety of the new authentication method is based on the fact that face id revolutionizes authentication on iphone x, using a state-of-the-art truedepth camera system made up of a dot projector, infrared camera, and flood illuminator, and is powered by a11 bionic to accurately map and recognize a face. these advanced depth-sensing technologies work together to securely unlock iphone, enable apple pay, gain access to secure apps, and many more new features. face id projects more than 30,000 invisible ir dots. the ir image and dot pattern are pushed through neural networks to create a mathematical model of your face and send the data to the secure enclave to confirm a match while adapting to physical changes in appearance over time. all saved facial information is protected by the secure enclave to keep data extremely secure, while all of the processing is done on device and not in the cloud to protect user privacy. face id only unlocks iphone x when customers look at it, and it is designed to prevent spoofing by photos or masks [23]. an infrared camera, then, captures the distortion of that grid as the user rotates his or her head to map the face's 3-d shape a trick similar to the kind now used to capture actors' faces to morph them into animated and digitally enhanced characters. [24]. despite the high level of quality of face id that greatly eliminated the possibility of forgery (falsifying the sample), the weaknesses of static biometric methods remain the same. table 1 comparison of dynamic and static biometric authentication methods property static methods dynamic methods forgery (imitation) yes no stealing (reuse) yes no compulsion yes complicated possibility of revocation (substitution by a different sample) no partially impact of the internal state of an organism no no impact of the environment no no ageing very little has not been studied change as a result of illness or injury yes yes inability to use (for objective reasons) improbable in the case of a serious disorder, e.g. inability to write (agraphia or dysgraphia). critics of this method of identification, respectively authentication of people point to the lower credibility of a dbs arising from insufficient uniqueness of generated signature samples in particular in connection with the possible change in the motor skills of people as they age or due to stress, the “rationalization” (simplification) of the signature due to the increasing skill of the writer after numerous repetitions, etc. the experiments described below show that this is not true. table 1 contains the comparison of selected properties of dynamic and static biometric authentication methods in terms of safety and protection against abuse. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 170 the second main counterargument is the need for high security for the database of signature samples, respectively biometric samples when signing. this is another separate issue [6]. 4.1. dbs credibility regarding the first objection, it is important to state that the dbs rests on the repeated performance of the same movement. it means a handwritten signature, which is considered to be a highly-qualified movement, during which some general laws apply, and where the latest research shows that some basic characteristics of a signature, respectively its characteristic parameters, can be determined and described mathematically:  the 2/3 pl (power law) states the known effect of the curvature of trajectory on the speed of movement, and the momentary angular velocity is proportionate to the momentary curvature with a 2/3 power relationship. a study focusing on the issue of handwriting, and its compliance with the 2/3 pl has confirmed the relationship between the trajectory of the curvature of the writing and the speed of movement [7, 17].  the principle of isochrony applies to the temporal characteristics of human movement and describes the invariance of the time to perform a movement in relation to its amplitude, meaning that the duration of a movement remains almost the same irrespective of its scope. this fundamental also applies for smaller parts of the assessed movement, which means that this part of the movement can be geometrically changed (for example enlarged), while the time to complete this sub-movement remains the same.  another easy to observe a feature of human movement is its smoothness. the minimum jerk model enables the assessment of trajectory creation, where the sections of a movement are examined in relation to the maximized smoothness. (jerk is a vector-based physical quantity characterizing movement, and describes the rate of change of acceleration.) the natural laws indicated above, which are discussed in studies for activities connected with writing, can also be naturally applied to the handwritten signature. studies have also shown that for samples of a signature or even of only its part, the time pattern of determined sections remains the same, irrespective of changes in geometry. hence, changes in movement caused by emotions or stress will not impact the overall timing of the movement (in our case the signature). thus, as soon as identification points are determined for a handwritten signature, the time relationship between them will always remain the same [8-11]. 4.2. dbs forgery when trying to forge a signature, the forger must contend with the speed profile of the original. even if the image is the same, the velocity profile will differ with a level of probability approaching one. it is important to note that a certain variability is actually permitted for the coordinates (x, y), while the time relationship between these through points must remain unchanged. small changes in the geometric shape of the signature (amplitude, scale) are not significant compared to the actual timing of the movement. an attempt at forging a signature must always be visible at the time level, and this especially if the forger only has access to the visual form of the signature [6]. as a part of the research performed by the authors in 2014, the characteristics of a dbs during an attempt at forging the signature of another person whose signature sample was available as an image were examined, inter alia. 102 university students of different ages took part in the test. the test subjects were supplied with a sample of the signature of a bank client, who had made the signature during a standard transaction. the forgers were given both the first and second names of the signer. in this phase of the test, the test subjects had the chance to practice the signature before imitating it and thus create as advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 171 convincing copies as possible. the signature training was done on paper, and also on a signing pad (in this phase the result of the signing was not scanned). after the training, the test subjects were tasked with imitating the signature sample five times with the maximum possible accuracy. fig. 1 shows that the attempt at imitating the client’s signature according to the sample reveals diametrical differences in terms of the time taken to create the sample and the forgery, while at first glance they appear very similar: fig. 1 time: the original signature above, the forgery below it is clear at first glance how long it took to create the forged signature; without mentioning the detailed differences in the individual time sections. when analyzing the scope of the performed signature (according to the number of image points), we see the different progress of the individual characteristics – for example, speed in fig. 2: fig. 2 writing speed: the original signature above, the forgery below a handwriting expert was also involved in the experiments and was provided with the forgery attempts produced by the test subjects. the analysis focused on assessing the compliance between the signatures created by the test subjects and the bank client’s signature. the results confirmed the conclusions arising from the data acquired by the validation server. the results of the examined set of signatures showed that out of the 190 forgeries, not even a short-term rehearsal of the signature to be forged was successful [12]. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 172 the experiments showed that the biometric data acquired during the creation of the signature provide such a set of information that enables an unequivocal opinion during subsequent verification in the case of a dispute over the authenticity of a signature. it was shown that the manufacturer’s software can be used to process these data. the configuration of the data that influences the amounts of the calculated indicators cannot – with the exception of the acceptance level – be changed in the programs delivered by the manufacturer. the configuration of the compliance level that results in agreement/rejection/non-rejection of a validated dbs will have to be addressed in the validation server, where it is possible to set the acceptable level according to the determined policy of the dbs operator. one interesting result of the experiments is that it will only be necessary to use the results and conclusions of an analysis of biometric data performed by a handwriting expert in extreme cases of the verification of the authenticity of a signature, while it is usually enough to deploy the validation server. in such a case, the biometric data are an ideal source of information for the handwriting expert compared to a situation in which they can only use two short texts, namely signatures on paper, for a comparison [12]. 4.3. dbs stability for different people other research assessed the stability of a dbs across a heterogenous set of tested people. three hypotheses were formulated: i. when using a standard (routine) signature, there is a high degree of similarity among individual signatures. the signatures are stable and display a small degree of variability. ii. this also applies to special circumstances, such as drunkenness, stress or other influences. iii. for some people, even the falsified (intentionally changed by them) signatures display a high degree of stability. a total of 10 signatures were recorded on the form from each person within the framework of the testing of the group of heterogeneous people. people signed in the usual standard manner during the first six signatures (hereafter simply referred to as the “authentic signatures”). they were, then, called upon during the next four signatures to try to change the signatures in such a way so that they could object that they were not the authors of the signatures during any eventual verification of authenticity (hereafter simply referred to as the “inauthentic signatures” or the “falsified signatures”). this involves a fairly typical variant where the first 6 signatures are completely routine, while the signatures starting with the seventh are falsifications of the person’s own signature (the person was asked to sign the same name, but different) with certain variability. after testing the group of 24 people which included:  people aged 12 to 92.  people with a primary, secondary and tertiary education (university students and graduates, including postgraduate education).  people working both manually and mentally.  the following evaluation was performed. a total of 240 results were acquired when comparing the authentic signatures, 138 when comparing the inauthentic signatures and 444 when comparing the authentic and inauthentic signatures with each other. the first finding involved the fact that in most people the first signature undertaken on the sensor showed a high degree of variance of compliance in relation to the other signatures, which is a consequence of the necessity of getting used to the method of signing on the sensor. for this reason, the first signature of each person was always omitted from the evaluation which resulted in the evaluated set of data being more homogeneous (with a smaller variance and standard deviation). advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 173 it was found that the degree of compliance (stability) for authentic signatures is substantially higher than for inauthentic signatures, and this with a level of significance of 0.01. 4.4. the influence of the consumption of alcohol on a dbs the testing of influences on the biometric signature’s dynamic was carried out on a group of 9 university educated people with an average age of 35.2 ± 14.2 (for 22 to 60). the measurement (signatures and filling in the tests) was carried out in a restaurant during its regular operations, i.e. in an environment with significant background noise. all 9 people carried out 2 x 10 signatures (before and after drinking alcohol). people who did not reach a breath alcohol concentration of at least 1‰ were eliminated from further processing. during the course of the experiment, which lasted 4 hours, 6 people reached an average breath alcohol level of 1.4 ± 0.2 ‰ (from 1.0 to 1.7‰). the measurements were taken using an alcoscan al9000l (korea) digital alcohol tester. people took the brickemkamp-zillmer variant d2 attention test at the beginning and the end of the measuring. the d2 selective attention test is a widely used test in psychological diagnostics. it enables the evaluation of the attention, performance (speed) and error rate under time pressure. it is appreciated for its stable results and the high mutual correlation of the individual evaluated parameters. we used the brickenkamp-zillmer d2 test, published in association with the hogrefe gottingen publishing house [13]. the speed of performance after the consumption of alcohol did not change in a demonstrable manner. on the other hand, the number of errors after the consumption of alcohol increased by more than twice (2.4x). the error rate with consistent results was statistically evaluated using a paired t-test and welch’s test comparing the characteristics before (b as before) and after (a as after) the consumption of alcohol and a significant difference was found in the error rate (ch%) and in the attention variability (vs) at a level of significance of 0.05. the degree of compliance of the signatures after the consumption of alcohol at a level of significance of 1% does not differ from the degree of compliance of the signatures before the consumption of alcohol, not even in the case of people who displayed a significant increase in errors during the attention test. it has been demonstrated that: i. when using the standard (routine) signature, there is a high degree of similarity between the individual signatures for a particular person. the signatures of individual persons are stable and they display only a small degree of variability. the signature is a stable tool for the identification and authentication of a person. ii. (a) in some people, even their falsified (intentionally changed by them) signatures display a high degree of stability. (b) in some people, these falsified signatures are not sufficiently distinguishable from the authentic signatures. iii. the influence of alcohol on the realization of routine (authentic) signatures has not been proven. even in cases where people displayed a high degree of stability in their inauthentic signatures, the dynamic parameters of the data which were received during the creation of the dbs provide sufficient room for their analysis by a trained person or a handwriting expert, who has a significant amount of information available of the sort which is simply unable to be acquired when comparing classic signatures on paper [14]. it is common for the person providing a signature to be exposed to stress, and one reason for this is the importance of the situation in which they are appending the signature. after all, stress and very often negative stress are the most common emotions in human life. for this reason, we were interested in whether and in what way stress influences the quality and constancy of a dbs. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 174 in our experiments, we used the extreme situations in which test subjects in survival courses (”x-tream” course) at the university of defence of the czech republic found themselves [15]. test subjects undertook a series of demanding tasks and gradually reached a level of stress and physical and mental exhaustion, hunger, sleep deprivation and therefore stress. we originally formulated two hypotheses: i. stress does not influence the stability of a signature. ii. there is a significant correlation between performances achieved in a d2 attention test and the stability of a dbs. the tests incorporated in our experiment included a brickenkamp-zillmer d2 attention test and provided ten signatures on a signotec tablet that reads the biometric characteristics of a signature. equipment and procedures were the same as before. [14] each test subject undertook the tests before the load commenced (at the beginning of the survival course), in the middle of the course and at the end – indicated as s(tart), m(iddle), f(inish). a total of 26 people took part. the results of our experiments showed that even though the physical and mental load on the test subjects rose, the stability of their dynamic biometric signatures was high or actually improved during the experiment. the variability of the signatures of most individual people did not differ significantly at individual stages. it was also again confirmed that the use of a 1st signature as “practice”, not included in the results, reduces the variability of signatures among all the test subjects. hypothesis i., that stress has no influence on the stability of a signature, was confirmed, at a significance level of 0.01. hypothesis ii., that there is a significant correlation between performances achieved on a d2 attention test and the stability of a dbs, was not confirmed. it can be assumed that a signature, as a stereotype embedded in the central nervous system over the long-term, can be influenced by outside factors to a lesser extent than specific activity performed at a stage of stress. we consider the stability of a dbs to be confirmed to such an extent by the range of experiments which we conducted [4, 6, 12, 14] to be able to use this method to identify and authenticate people or the documents which they have signed with a high degree of reliability and verifiability. 4.5. stability of a dynamic biometric signature created on various devices within further experiments, we focused on examining whether the use of various devices for dbs scanning affects the stability of a dbs of the signer. in our experiments, we used all the available pads produced by signotec, which differ from each other in terms of their design, the size of the signature field, resolution, sampling rate, and even the scanning method used – a regular pen or a special pen using the ert (electromagnetic resonance technology). the purpose of the experiments was to show the possible change of the stability of a dbs of a signer depending on the scanning device. as the sample represented people of both sexes aged 20 to 65, the size of the heterogeneous sample used was statistically representative enough. the following hypotheses were formulated: i. the participants will cope with the difficulties connected with the changing circumstances of the signing depending on the technical design of the pad in a different way: h0 the stability of signatures of a particular person on each device does not significantly change (mean and variance of the degree of compliance of signatures for each device belonging to the same basic set). h1 there is a statistically significant difference in the means and variances of the degree of compliance of signatures of a particular person on individual devices. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 175 ii. the stability of signatures achieved on individual devices will statistically significantly differ: h0 the mean degree and variance of compliance of signatures for each device do not significantly change (mean and variance of the degree of compliance of signatures for each device belonging to the same basic set). h1 there is a statistically significant difference in the means and variances of the degree of compliance of signatures on individual devices. 4.5.1. testing of hypothesis i the result characterizing the technology as a whole, i.e. without differentiation of types of devices and signers (i.e. for all people on all devices) is as follows see table 2: table 2 summary results on the degree of compliance of signatures x [%] m2 σ [%] 79.330 173.290 13.164 the selective mean of the degree of compliance of signatures came under an accepted level of compliance of biometric signatures 60% only in case of two people. in order to test the homogeneity of variances of the degree of compliance of signatures of each participant on all devices, the bartlett's test was used [25]. the values in the b test ranged from 20.341 to 609.934, i.e. the p-value was between 0.000 and 0.005. for all participants, the null hypothesis was, therefore, rejected at the significance level 0.01 and thus at the significance level 0.05 (as the p-value was <0.01 for all participants). using the cochran-cox test [26], a pair of devices, where the hypothesis on the compliance of means of the degree of compliance was rejected at the significance level 0.01, was found for each participant. the simple sorting test (analysis of variance, anova) that would keep the probability of error of the first kind at the level 0.05 or 0.01 could not be used with regard to the results of the bartlett's test. we can conclude that the participants coped badly with various designs of devices. this is due to the fact that selective variances of the degree of compliance are significantly different for all participants on individual devices, and there are also differences in means of compliances. 4.5.2. testing of hypothesis ii the following values of selective means and unbiased estimates for variances of the degree of compliance of signatures were detected on the stated devices see table 3 below: table 3 selective means and unbiased estimates for variances of the degree of compliance the signotec device and scanning method x [%] s2 alpha ert 80.342 113.019 delta ert 76.749 238.268 gamma ert 78.971 232.027 omeganew td 76.022 228.052 omegaold td 83.002 125.844 sigmalite wd 77.097 148.574 sigmanew td 85.233 139.194 sigmaold td 77.195 120.338 compliance of variances was verified by the bartlett's test (b = 13.597, k-1 = 7, α = 0.01 and 0.05, p-value = 0.059), so the hypothesis on the compliance of all variances was accepted at the significance level 0.01 and at the significance level 0.05. advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 176 the simple sorting test (anova) [26] gave the following results f = 2.565, k = 7, n-k = 306, p-value = 0.014, α = 0.01 and 0.05, f0.01= 2.700 and f0.05= 2.039, where f1-α (k-1, n-k) is (1-α) quantile of the fisher-snedecor distribution for the significance level α, so compliance of all means was accepted at the significance level 0.01 and rejected at the significance level 0.05. the results of the scheffe's test of multiple comparisons [27] would enable to determine between which two above-mentioned means the statistically significant differences exist. the scheffe's test accepts the equality of all 28 pairs of means of the degree of compliance of signatures at the significance level 0.01 and 0.05 (28 is the number of possible options for all pairs of devices). when using different devices, there were found no differences between the mean values of the degree of compliance (x) and values of the variance of the degree of compliance (σ2) that is at the significance level 0.05 for variances and at the significance level 0.01 for means. it can, therefore, be noted that, despite the technological differences between individual devices, the stability of signatures (indicated by variance) does not change when changing the device. also, the degree of compliance of signatures on all devices does not statistically significantly differ at the significance level 0.01. the experiment brought the following results: hypothesis i. – the participants will cope with the difficulties connected with the changing circumstances of the signing depending on the technical design of the pad in a different way: the null hypothesis h0 claiming that the stability of the signatures of a particular person on each device does not significantly change that is at the significance level 0.01 and thus at the significance level 0.05, was disproved. a pair of devices, where the hypothesis on the compliance of means of the degree of compliance was rejected at the significance level 0.01, was found for each participant. therefore, the hypothesis h1 claiming that there is a statistically significant difference in the means and variances of the degree of compliance of signatures of a particular person on individual devices was confirmed. hypothesis ii. – the stability of signatures achieved on individual devices will statistically significantly differ: the null hypothesis h0 claiming that the mean degree and variance of compliance of signatures for each device do not significantly change, because there were found no differences between the values of means and variances of the degree of compliance when using different devices, that is at the significance level 0.05 for variances and at the significance level 0.01 for means, was confirmed. a detailed description of the experiment can be found in the report from [28]. 5. conclusions dbs has been an important alternative to classic electronic signatures based on cryptographic methods. it can be used with an advantage in cases when the implementation of certificates (partly due to their limited validity period) and the secure “concealment” of private keys significantly interferes with the normal activities of signers. from the perspective of users, it is also the most pleasant method, as the act of signing is something we do today and every day without needing any special knowledge, skills or the ownership of any secret. handwritten signatures are also one of the most socially accepted biometric features[16]. through the implemented tests, the authors of this paper have shown that the level of compliance, stability, and imperviousness to influence during the creation of signatures performed by the test subjects in different situations is high. a dbs shows practically absolute resistance to imitation, and the stability of signatures made by the test subjects in different advances in technology innovation, vol. 3, no. 4, 2018, pp. 166 178 copyright © taeti 177 situations is high. factors such as alcohol and stress have no influence on signature stability either. the results of the experiments have shown that a handwritten signature acquired through long practice and the compaction of the dynamic stereotype, which is composed of the physiological, psychological, anatomical and motor characteristics of each person, is automatic to such an extent and stored deep in the human brain, that its involuntary performance enables other processes to take place concurrently in the cortex. a dbs is not a replacement for a cryptographic electronic signature, but an important alternative that can be used in cases when the use of certificates, the secure storage and “policing” of private keys, etc. would significantly impact routine and stable processes, and potentially form a barrier discouraging normal users (contracting parties). its advantage over a cryptographic electronic signature, when a computer de facto does the signing, is the existence of this “handwritten” quality, which is only ensured through a legal declaration when a private key is used. in further research, the authors want to focus on other possible impacts occurring as a result of the external factors that can influence the process of signing, e.g. a change in the body position. they will also take into account the additional authentication options and abilities to imitate a dbs, this time not as a static image of the signature, but in a process of monitoring and imitating its dynamics. references [1] v. smejkal and j. kodl, “development trends of electronic authentication,” proc. of the 42nd annual conf. 2008 ieee international carnahan conf. on security technology, ieee press, october 2008, pp. 1-6. [2] r. rak, v. matyáš, and z. říha, “biometry and identity in forensic and commercial applications,” grada publishing, 2008. [3] m. gamassi, m. lazzaroni, m. misino, v. piuri, d. sana, and f. scotti, “accuracy and performance of biometric systems,” proc. of the 21st ieee instrumentation and measurement technology conf. (ieee cat. no. 04ch37510), ieee press, november 2004, pp. 510-515. [4] v. smejkal and j. kodl, “strong authentication using dynamic biometric signature,” proc. of 45th annual 2011 ieee international carnahan conf. on security technology (iccst), ieee press, october 2011, pp. 340-344. [5] iso/iec 19794-11:information technology. biometric data interchange formats, part 11: signature/sign processed dynamic data, ieee standard, 2013. 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[10] a. j. thomassen and h. l. teulings, “time, size and shape in handwriting: exploring spatio-temporal relationships at different levels,” time, mind, and behavior, springer berlin heidelberg, pp. 253-263, 1985. [11] y. wada and m. kawato, “a theory for cursive handwriting based on the minimization principle,” biological cybernetics, vol. 73, no. 1, pp. 3-13, june 1995. [12] v. smejkal and j. kodl, “assessment of the authenticity of dynamic biometric signature,” the results of experiments. proc. of 48th annual 2014 ieee international carnahan conf. on security technology (iccst), ieee press, october 2014, pp. 45-49. [13] r. brickenkamp and e. zillmer, d2-test of attention, seattle: hogrefe & huber, 1998. 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[22] a. greenberg, “we tried really hard to beat face id-and failed (so far),” https://www.wired.com/story/tried-to-beat-face-i d-and-failed-so-far/. [23] the future is here: iphone x. apple inc. press release, september 2017. [24] a. greenberg, “how secure is the iphone x's faceid? here's what we know,” https://www.wired.com/story/iphone-x-facei d-security/. [25] g. w. snedecor and w. g. cochran, “statistical methods. eighth edition,” iowa state university press, 1989. [26] w. g. cochran and g. m. cox, experimental & designs, 2nd ed. new york: john wiley and sons, 1957. [27] h. scheffé, the analysis & variance, new york: john wiley and sons, 1999. [28] v. smejkal, j. kodl, l. sieger, f. hortai, and p. tesař, “stability of a dynamic biometric signature created on various devices,” ieee press, december 2017.  advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 robust adaptive depth control of hybrid underwater glider in vertical plane ngoc-duc nguyen 1 , hyeung-sik choi 2,* , han-sol jin 2 , jiafeng huang 2 , jae-heon lee 2 1 department of electrical and information engineering, seoul national university of science and technology, seoul, korea 2 department of mechanical engineering, korea maritime and ocean university, busan, korea received 25 december 2019; received in revised form 22 march 2020; accepted 09 june 2020 doi: https://doi.org/10.46604/aiti.2020.4142 abstract hybrid underwater glider (hug) is an advanced autonomous underwater vehicle with propellers capable of sustainable operations for many months. under the underwater disturbances and parameter uncertainties, it is difficult that the hug coordinates with the desired depth in a robust manner. in this study, a robust adaptive control algorithm for the hug is proposed. in the descend and ascend periods, the pitch control is designed using backstepping technique and direct adaptive control. when the vehicle approaches the target depth, the surge speed control using adaptive control combined with the pitch control is used to keep the vehicle at the desired depth with a constant cruising speed in the presence of the disturbances. the stability of the proposed controller is verified by using the lyapunov theorem. finally, the computer simulation using the numerical method is conducted to show the effectiveness of the proposed controller for a hybrid underwater glider system. keywords: nonlinear robust adaptive control, depth control, hybrid underwater glider, buoyancy engine 1. introduction underwater glider (ug) is the new type of autonomous underwater vehicle (auv). ug has some advantages over the conventional auv. the first innovation is that it can use low energy to survey the large area of ocean and another feature is that it can glide extremely quietly under the ocean. therefore, there are many researches on this vehicle not only in oceanography but also in military purposes. in [1], a stable gliding condition was derived and an lqr controller was designed for a sawtooth depth of ug using the equilibrium point in the stable condition. a model predictive control was developed in [2] for ug to compensate for the drift due to external disturbances. in [2], the simulation and experiment studies were carried out to find the optimal pitch angle in gliding motion for the maximum speed. in [4], an energy optimal depth controller was developed for a long-range autonomous underwater vehicle with applications to hybrid ug during the level flight. a robust integral sliding mode with a super-twisting algorithm was proposed in [5] for the trajectory tracking problem of autonomous ug with environmental disturbances. in [6], the optimal control of an ug vehicle was proposed using linear quadratic regulator strategy. a new optimal three-dimensional path planning method was developed in [7] for the minimum energy consumption for ugs. in [8], a self-searching optimal control was proposed for pitch-keeping control of ug during descent and ascent under ocean currents and noise disturbances. a novel control algorithm was presented in [9] using reinforcement learning with active disturbance rejection control (adrc) and it was compared with the classical adrc by simulation of ouc-iii glider. in [10], a new hybrid heading tracking control algorithm was proposed using adaptive fuzzy incremental pid and anti-windup compensator to improve the heading control of ugs. a dynamic surface decoupling control algorithm using * corresponding author. e-mail address: hchoi@kmou.ac.kr tel.: +8210-5581-2971 advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 136 adrc was proposed in [11] and sea trial results also were presented here with some improvements in overshoot and settling time. in [12], an lqr controller to maintain the sawtooth vertical movement in the gliding motion of ug was presented with the reduced order luenberger observer for estimating the gravity center and buoyancy mass. in [13], to realize the precise navigation for the developed hybrid ug, an attitude reference system was composed of a ring laser gyroscope and a geomagnetic sensor was presented applying extended kalman filter algorithm. in addition, a ray-type shape underwater glider with robust adaptive heading control using propellers was developed and tested in the sea trials [14]. among those gliders, the depth control problem is still a challenging problem. the purpose of this study aims at the depth control of the hug using a combination of the pitch and speed controls, robust to disturbances will be designed. in this research, to contribute to the control design of the torpedo-shaped hybrid underwater glider (hug) with buoyancy engine and propeller, the adaptive robust depth control is proposed for depth keeping control against unknown parameters and environmental disturbances. this controller is designed based on the lyapunov stability theorem and the backstepping technique for underactuated dynamics like hug. the hydrodynamic coefficients of this vehicle were obtained from [15] due to the similar torpedo shape and similar design dimension. the heave motion is controlled through pitch control and speed control with the line-of-sight guidance law. to see the effectiveness of this proposed controller for depth keeping control, the computer simulation using matlab is performed and the stable performance is guaranteed. 2. vertical model of hybrid underwater glider : : surge roll u p kx z n m y : : sway pitch v q : : heave yaw w r body-fixed coordinate system north-east-down coordinate system    0y o 0x 0z e x y z (a) earth-fixed and body-fixed coordinate system (b) developed hug in the field test fig. 1 hybrid underwater glider to find the position of the ug; first, the relationship between the body-fixed coordinate and earth-fixed coordinate is expressed using the angle of the hull and the acceleration as in fig.1. for this, heading and attitude sensors are in the glider [16]. the vertical dynamics of hug can be expressed in the kinematic and kinetic model as eq. (1) [17]. ( ) ( ) ( )       t e jv m c v d v v g j       (1) where 𝜂 = [𝑥 𝑧 𝜃]𝑇 is the position and orientation of the vehicle in inertial frame 𝐸𝑥𝑦𝑧 in fig. 1; 𝜈 = [𝑢 𝑤 𝑞]𝑇 is the translation and angular velocity in the body-fixed frame 𝑂𝑋0𝑌0𝑍0 in fig. 1; 𝐽 is jacobian matrix; 𝑀 = 𝑀𝑅𝐵 + 𝑀𝐴 is the inertia matrix; 𝐶(𝜈) = 𝐶𝑅𝐵(𝜈) + 𝐶𝐴(𝜈) is the coriolis and centripetal matrix; 𝐷(𝜈) is hydrodynamic damping matrix; 𝑔(𝜂) is the gravitational matrix; 𝜏 is the external forces and moments; 𝑔0(𝜂) is the ballast forces and moments which are generated by buoyancy engine in the hybrid underwater glider (hug); 𝜏𝑒 is the environment disturbances. to obtain the detail dynamic, one can expand eq. (1) into eq. (2), while the dynamic coefficients are obtained from the remus auv model [15] which has the same hull dimension as the developed hug. advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 137     22 | | 2 cos sin sin cos | | ( )sin sin q u euu g g w wuu w g gq q x u v z u v q u mz q mx q mwq z wq z x u u w b m z q m x w mx z q mz q muq x                                         | | | | cos| | ( )cos | | ( )sin ( )cos eww yy q u ww g w w q u qq g g q eqb b gi m uq z w w w b q mz u qw w qu m w z wu z qu x uw m q q z w z b x w x b mx                             (2) as this time, 𝑋�̇�, 𝑍�̇�, and 𝑀�̇� are the added mass coefficients; 𝑋𝑢, 𝑍𝑤, and 𝑀𝑞 are linear damping coefficients; 𝑋|𝑢|𝑢, 𝑍|𝑤|𝑤, and 𝑀|𝑞|𝑞 are nonlinear damping coefficients; 𝑊 and 𝐵 are the weight and buoyancy force respectively in the neutral buoyancy condition; 𝑥𝑔 and 𝑧𝑔 are coordinates of gravity center in the body-fixed frame; 𝑥𝑏 and 𝑧𝑏 are coordinates of buoyancy center in the body-fixed frame; 𝜏𝑤 is the control force from buoyancy engine; 𝑚 and 𝐼𝑦𝑦 are the vehicle mass and the y-axis inertia; 𝜏𝑞 is the control moment from mass-shifter; 𝜏𝑤 is the buoyancy force generated by the pump inside hug body; 𝜏𝑢 is the thruster force; 𝜏𝑒𝑢, 𝜏𝑒𝑤 , and 𝜏𝑒𝑞 are disturbances from ocean currents and wave and [𝜏𝑒𝑢 𝜏𝑒𝑤 𝜏𝑒𝑞]𝑇 = 𝐽𝑇𝜏𝑒. m g 2 c r  bu sealed at atmosphere pressure, 1atmsealed at atmosphere pressure, 1atm o-ringo-ring seawaterseawater motor and gearmotor and gear ball-screwball-screw fig. 2 buoyancy engine diagram in this hug system, the buoyancy engine will let the water in or out by moving piston along the cylinder as revealed in fig. 2. during this process, the volume of this vehicle will decrease or increase according to the position of the piston. if the weight is equal to the buoyancy force in the neutral condition, this glider descends when its volume is reduced and ascends toward the water surface when its volume is increased. in order to specify the force that this buoyancy engine can produce, the travel distance of the piston and the radius of cylinder should be defined. the buoyancy force is equal to the weight of seawater going in or out and it is indicated in eq. (3). as this point, in fig. 2, 𝑢𝑏 is the position of piston; 𝑅𝑐 is the radius of the cylinder; 𝜌 is the density of seawater; 𝑔 is the gravitational acceleration. during the operation of the buoyancy engine, the center of the buoyancy is shifted along the 𝑂𝑥0 axis by eq. (4). 2 w b cu r g   (3) 2 2 ( ) 2 b c b p b c b nb u r u x x r u v      (4) where, 𝑋𝑝 is the position of the piston in the neutral position along the 𝑂𝑥0 axis in the body-fixed frame; 𝑉𝑛𝑏 is the volume of the vehicle in the neutral condition of the buoyancy engine. the movable mass in fig. 3 can move along the ox0 axis; therefore, the center of gravity in this axis 𝑥𝑔 can be defined as: stat stat m m g m x m u x m   (5) advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 138 where, 𝑚𝑠𝑡𝑎𝑡 = 𝑚 − 𝑚𝑚 is the static mass; 𝑚𝑚 is the weight of the movable mass; 𝑢𝑚 is the position of the moving mass; 𝑥𝑠𝑡𝑎𝑡 is the position of the static mass and it is assumed to be very small because the origin of body-fixed frame is located near to the center of gravity. furthermore, 𝑥𝑔 can be approximated as:. m g m m x u m  (6) the moment produced from the mass-shifter can be computed by the product of the net buoyancy force and the location of the center of gravity as found in eq. (7). in addition, the moment of inertia is also changed because of the change in mass distribution following eq. (8). 𝐼𝑛𝑦 is the moment of inertia in the neutral condition of moving mass. m q g m m wx w u m    (7) 2 ( )yy ny m m mi i m u sgn u (8) m g moving massmoving mass mu motor and gearmotor and gear ball-screwball-screw fig. 3 mass shifter diagram 3. depth control 3.1. pitch control the pitch angle in the proposed design of the hug is changed by controlling the moving mass position and the pitch angle dynamics can be described as eq. (9), which are from eq. (2).  33 2 system 1: system 2: , , q eq q m q f           (9) where 33  qym i m (10) 2 ( ) ( ) ( )sin ( )cos            g g w w q u g b g bq q f mz u qw mx w qu m w z wu z qu x uw m q q z w z b x w x b  (11) in this system, the buoyancy force is only controlled by on and off mode for descending and ascending. therefore, the moment produced by moving mass is used and designed using the adaptive backstepping technique for the vertical dynamics. two differential equations in eq. (9) are considered as two subsystems for the backstepping control. for one equation, the virtual control law is set for 𝑞𝑑 so that 𝜃 → 𝜃𝑑 as 𝑡 → ∞, and then the control moment 𝜏𝑞 is designed for controlling 𝑞 → 𝑞𝑑 as 𝑡 → ∞. the errors of system 1 and 2 are defined in: 1 2 d d e e q q         (12) error dynamics of the pitch dynamics are defined as below: 1 2d d d de q e q          (13) advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 139 the error dynamics in eq. (13) can be stabilized by designing 𝑞𝑑 = �̇�𝑑 − 𝑘1𝑒1 with the positive control gain, 𝑘1. then, the error dynamics of system 1 can be obtained as: 1 1 1 2e k e e  (14) derivative of the virtual control is: 2 1 1 1 2d dq k e k e   (15) error dynamics of the subsystem 2 is obtained as: 33 33 33 2 332 d q eqd m qm e m q m q f       (16) using the sliding mode control technique for finding the control law for pitch control, one can choose the lyapunov function for this system as below: 2 2 1 2 1 33 2 2 2 2 1 1 1 2 2 2 v e m e a p a   (17) where 𝑌2𝑎2 = −𝑓2 + 𝑚33�̇�𝑑; 𝑃2 = 𝐼9×9 is the identity matrix; �̃�2 = �̂�2 − 𝑎2; 𝑌2 = [�̇� �̇� 𝑞𝑢 𝑤𝑢 𝑞𝑤 |𝑞|𝑞 𝑠𝑖𝑛𝜃 𝑐𝑜𝑠𝜃 �̇�𝑑] is the regressive vector for updating the parameter vector 𝑎2 defined as: 32 3[ ( )( )( ) ( ) ( ) ]            t g g w g q u w g g b g bq q a mz mx m mx z x z mz m z w z b x w x b m (18) the derivative of the above lyapunov function is expanded in eq. (19). to stabilize the dynamics in this equation, the control input is designed as eq. (20) with the saturation function in the switching control. 2 1 2 1 1 1 2 2 2 2 2 2ˆ( ) t q eqv k e e e e y a a p a         (19) 2 2 2 2 2 1 2 2 ˆ ˆ ( )q eq e y a k e e k sat       (20) substituting the control law (20) into the first derivative of the lyapunov function (19) will result to: 2 2 12 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 ˆ ˆ( ) ( )eq eq e v k e k e k e sat e e y a a p a           (21) by choosing the adaption law as �̇̂� = −𝑃2𝑌2 𝑇𝑒2, the derivative of 𝑉2can be derived as: 2 2 2 2 1 1 2 2 2 2 2 2 ˆ( ) ( )eq eq e v k e k e k e sat e        (22) it is observed that if 𝑘2∆ > 𝐹𝑒𝑞 and |𝜏𝑒𝑞 − �̂�𝑒𝑞| ≤ 𝐹𝑒𝑞, then �̇�2 ≤ −𝑘1𝑒1 2 − 𝑘2𝑒2 2 ≤ 0. here, 𝐹𝑒𝑞 is defined relating with the environmental condition. following the direct lyapunov method for v2, the control law (20) is proved to be globally asymptotically stable (gas). 3.2. speed control the vehicle speed will be controlled by thruster attached at the tail of hug. the speed dynamics will be investigated to carry out the speed controller. the system 3 is defined as eq. (23) which is the 4th equation in eq. (2). advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 140  311system 3: , , sinw u eum u f           (23) where 11  um m x (24) 2 3 ( ) ( ) ( )sin       g g q w u u f mz q mx z q m z wq x u u w b  (25) the speed error is defined as: 3 de u u  (26) and the speed error dynamics can be formulated as: 11 3 11 3 11sinw ud dm e m u u f m u        (27) the lyapunov candidate can be designed as: 2 1 3 11 3 3 3 3 1 1 2 2 tv m e a p a  (28) where 113 [ ( )( ) ( ) ]        t g g q w wu u a mz mx z m z x b w m (29) 3 3 3ˆ a a a (30) furthermore, its derivative is formulated as eq. (31) using the dynamics in eq. (27). 1 3 3 3 3 3 3 3( )u euv e y a a p a       (31) where 𝑌3 = [�̇� 𝑞2 𝑤𝑞 |𝑢|𝑢 𝑠𝑖𝑛𝜃 �̇�𝑑]. the speed control law can be designed as: 3 3 3 3 3 3 3 ˆ ˆ ( )u eua e y k e k sat      (32) applying this control law into (31) yields: 2 13 3 3 3 3 3 3 3 3 3 3 3 3 ˆ ˆ( ) ( ) t eu eu e v k e k sat e e e y a a p a          (33) the last two term in eq. (25) can be eliminated by choosing �̇̂�3 = −𝑃3𝑌3 𝑇𝑒3, then �̇�3 can be reformulated as: 2 3 3 3 3 3 3 3 3 ˆ( ) ( )eu eu e v k e k sat e e       (34) if the control gain 𝑘3δ is chosen as: 3 | |ˆeu euk     (35) then, the derivative of the lyapunov function 𝑉3 is negative definite as: advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 141 2 3 3 3 3 3 3 2 3 3 ˆ (n.d) eu euv k e k e e k e       (36) this control law is proved to be gas using lyapunov function 𝑉3 as shown in eq. (28). 3.3. los depth-keeping guidance for navigation of the hug, a line of sight (l.o.s) method based on the calculated heading angle was used [18]. the line-of-sight (los) guidance in fig. 4 is applied for path following control for the vertical plane. it is assumed that the position information of the hug is available from the inertial navigation system. then, a two-dimensional los guidance is constructed to apply the desired pitch angle 𝜃𝑑 to the controller. the way-point in the los guidance is given by the operator and it contains 2 components, 𝑥𝑘 and 𝑧𝑘. the path variables by the previous waypoint and the current waypoint are defined by 𝑥𝑘, 𝑧𝑘, 𝑥𝑘−1 and 𝑧𝑘−1. by solving eqs. (37)-(38) for the virtual los point (𝑥𝑙𝑜𝑠, 𝑧𝑙𝑜𝑠), the desired pitch angle can be computed by eq. (39). 𝐿𝑝𝑝 is the length of the vehicle; 𝑛 is the positive gain that combines with 𝐿𝑝𝑝 to define the los radius. 2 2 2( ) ( ) ( )pplos losz z x x nl    (37) 1 1 1 1 los k k k los k k k z z z z x x x x          (38) arctan          los d los z z x x  (39) robust adaptive control huglos disturbance , d d x z d   , ,x z  e , ,u w q parameter adaptation d u fig. 4 algorithm of depth control for the energy efficient operation, hug will glide down by only using the buoyancy engine and mass shifter. when it reaches the desired depth, the depth control is applied to keep it at the desired depth. the adaptation law is used to estimate the nonlinear unknown term in the pitch and surge dynamics. the estimation algorithm for the unknown parameters is used in the control action while stabilizing the dynamics. furthermore, the sliding mode control is used to deal with the environmental disturbances from currents and waves. in the following section, the simulation of the diving, depth-keeping and redurfacing are presented. 4. simulation and discussion in order to validate the good performance of the proposed depth control, the simulation of heaving motion control of the hug is presented using the matlab with the vehicle parameters which is presented in table 1. the descending and ascending motion is actuated by only buoyancy engine and mass shifter. when the hug goes down close to the desired depth, the buoyancy engine is controlled to stay in the neutral buoyant condition or zero net buoyancy. the thruster and mass shifter are used to drive the vehicle along the desired depth with the designed speed. in this simulation, the desired depth is 200 m advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 142 ( 1 2 200 z z m ), the length of trajectory distance is 300 m, the desired speed is 2 knots ( 1 /du m s ). also, environmental distrubances are chosen as the sine function with the magnitude of 2n, -1n and 2nm (  | | 2 1 2 t e   ) for 𝐸𝑥, 𝐸𝑧 and 𝐸𝑦 axes respectively. table 1 vehicle parameters parameters value parameters value parameters value m 70kg 𝑋�̇� −9.3 × 10−1kg 𝑍|𝑤|𝑤 −1.31 × 102kg/m 𝐼𝑦𝑦 1.29kgm2 𝑍�̇� −3.55 × 101kg 𝑀�̇� −4.88kgm2/rad 𝑚𝑚 1.5kg 𝑍�̇� −1.93kgm/rad 𝑀�̇� −1.93kgm 𝑊 − 𝐵 ±0.7kg 𝑋|𝑢|𝑢 −3.9kg/m 𝑀|𝑞|𝑞 −1.88 × 102kgm2/rad2 the hug dives with −30° pitch angle to the depth of 200 m, then it will use the thruster to keep at the constant depth, and after moving 300 m at the desired depth it will ascends with a positive pitch angle of 30° ( 30d ). fig. 5 is indicated that hug glides down with the small oscillation due to the environment effects. this phenomenon can be observed in the pitch tracking control in fig. 6. at the desired depth, the output of los guidance is seen as the wave form because of the sine function of the disturbances. it shows that the control law drives the hug to track the path of los guidance very well in the presence of disturbances. fig. 5 trajectory of hug with environmental disturbances (a) longitudinal coordinate (b) depth (c) heading performance in depth control fig. 6 the position and orientation of hug advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 143 fig. 7 is described velocities of the vehicle in the body-fixed coordinates. the speed control results are presented for the surge velocity 𝑢 with the desired speed is 1 m/s. it is noted that the speed control is only used in the cruise period. the robust adaptive speed control shows good tracking performance along the desired trajectory under the bounded disturbances. additionally, the control force and torque for the depth control are simulated in fig. 8. the control force of the buoyancy engine is limited in the range from -2 n to 2 n. the range of the pitching torque generated by mass shifter is in the range from -20 nm to 20 nm. (a) speed control performance (b) sway velocity (c) pitch velocity fig. 7 velocities of the hug in the body-fixed coordinates (a) net buoynacy force (b) moment induced by moving mass (c) thruster force during the depth control fig. 8 force and moment from the robust adaptive controller as stated above, the stability proof is revealed that the errors are bounded in fig. 9. 𝑒1 and 𝑒2 are from pitching control system, and they show good convergence performance, even though the desired angle changes due to the los guidance and external disturbance effects. especially, during the transition period from gliding to cruising or vice versa, 𝑒1 and 𝑒2 can quickly converge near to zero in fig. 9. for speed control, the convergence only appears in the cruising mode while keeping the advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 144 (a) pitch angle error (𝑒1 is pitch angle error) (b) virtual control error (𝑒2 is the virtual control error) (c) speed control error in the desired depth (𝑒3 is the speed control error) fig. 9 the tracking errors from 3 sub-controller in crusing period hug to the desired depth of 200 m. in the desired depth, the speed of the vehicle is controlled at a constant value of 1 m/s or 2 knots. at the same time, the error converges quickly close to zero in fig. 9. fig. 10 the parameter adaptation of vector �̂�2 fig. 11 the parameter adaptation of vector �̂�3 two main adaptation processes are indicated in fig. 10 for vector 𝑎2 and 𝑎3 respectively. there are 9 parameters in vector 𝑎2 (18) and 6 parameters in vector 𝑎3 (29). parameters 7 and 8 of vector 𝑎2 in fig. 10 are sensitive to the external disturbances with the wave curve updating process. these parameters are defiend as –(zgwzbb) and (xgwxbb) respectively in advances in technology innovation, vol. 5, no. 3, 2020, pp. 135-146 145 (18). these terms are from the restoring moment due to the change of the gravity center and buoyancy center. in addition, in vector 𝑎3, there is one parameter that proportionally adapts to the change of disturbances, which is parameter 4 defined as 𝑋|𝑢|𝑢 in the damping force in the system 3. this phenomenon is shown in fig. 11, parameter 4 shows the waving curve in the speed control. 5. conclusions in this study, the depth control for nonlinear vertical dynamics of the hybrid underwater glider was proposed and its performance was validated through simulations. the robust adaptive control law has presented the stable performance against the parameter change and external disturbance. it is guaranteed that the error is close to zero as the time go to infinite. according to the direct lyapunov method, the stability of this control law has been established and proved. the depth control algorithm uses the los guidance law for keeping the hug to the desired depth. the computer simulation using matlab was performed to verify the good and stable performance of depth keeping control using the proposed control algorithm. in the future research, this algorithm will be implemented in the developed hug at the laboratory and, the water tank and sea trials of the hug employing the proposed depth control will be carried out. acknowledgement this study is part of a project supported by the civil-military dual-use technology “data collection system with underwater glider” (grant no. 19-sn-mu-01) and a government project entitled “development of hybrid underwater drone for accurate inspection of the underwater pipeline and cable”. conflicts of interest the authors declare no conflict of interest references [1] m. g. joo and z. qu, “an autonomous underwater vehicle as an underwater glider and its depth control,” international journal of control, automation and systems, vol. 13, no. 5, pp. 1212-1220, july 2015. [2] i. abraham and j. yi, “model predictive control of buoyancy propelled autonomous underwater glider,” proc. of the american control conference, july 2015, pp. 1181-1186. [3] s. k. jeong, h. s. choi, j. h. bae, s. s. you, h. s. kang, s. j. lee, et al., “design and control of high speed unmanned underwater glider,” international journal of precision engineering and manufacturing-green technology, vol. 3, no. 3, pp. 273-279, july 2016. [4] b. claus and r. bachmayer, “energy optimal depth control for long range underwater vehicles with applications to a hybrid underwater glider,” autonomous robots, vol. 40, no. 7, pp. 1307-1320, february 2016. [5] m. mat-noh, m. r. arshad, and r. mohd-mokhtar, “nonlinear control of autonomous underwater glider based on super-twisting sliding mode control (stsmc),” 7th ieee international conference on system engineering and technology, october 2017, pp. 71-76. 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[18] d. jung, s. hong, j. lee, h. cho, h. choi, and m. vu, “a study on unmanned surface vehicle combined with remotely operated vehicle system,” proceedings of engineering and technology innovation, 2018, vol. 9, no. 7, pp. 17-24, july 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 3__aiti#7309__157-168 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 design philosophy for buildings’ comfort-level performance nanang gunawan wariyatno1,2, han ay lie1, fu-pei hsiao3, buntara sthenly gan4,* 1civil engineering department, faculty of engineering, universitas diponegoro, semarang, indonesia 2civil engineering department, faculty of engineering, universitas jenderal soedirman, purwokerto, indonesia 3national center for research on earthquake engineering, tainan, taiwan 4department of architecture, college of engineering, nihon university, koriyama, japan received 15 march 2021; received in revised form 27 april 2021; accepted 28 april 2021 doi: https://doi.org/10.46604/aiti.2021.7309 abstract the data reported by japan meteorological agency (jma) show that the fatal casualties and severe injuries are due to heavy shaking during massive earthquakes. current earthquake-resistant building standards do not include comfort-level performance. hence, a new performance design philosophy is proposed in this research to evaluate the quantitative effect of earthquake-induced shaking in a building. the earthquake-induced response accelerations in a building are analysed, and the response accelerations related with the characteristic property of the building are used to evaluate the number of seismic intensity level (sil). to show the indispensability of the newly proposed comfort-level design philosophy, numerical simulations are conducted to evaluate the comfort level on different floors in a building. the results show that the evaluation of residents’ comfort levels should be considered in the current earthquake-resistant building design codes. keywords: comfort-level, seismic intensity level (sil), quantification, earthquake, design philosophy 1. introduction japan is susceptible to strong earthquakes and volcanic eruptions owing to its location at the junction of four active tectonic plates: the pacific, north american, eurasian, and philippine plates. since the 19th century, 20% of the recorded strong earthquakes worldwide with a magnitude larger than six on the richter scale have occurred in japan [1]. the technological development of earthquake-resistant buildings in japan started in 1891 during the meiji era. in 1919, the first law related to the construction of earthquake-resistant buildings was issued. japan’s design codes are readjusted and renewed whenever a massive earthquake with a high number of casualties occurs. to prevent the collapse of buildings, the latest design codes require that structures should undergo plastic deformations while behaving elastically under small to moderate earthquake conditions. this new design method is effective for conserving human lives in the case of building collapse. however, it does not consider the possibility of deaths due to non-structural failure induced by vibration and shaking. japan’s early warning technology, which was managed by japan meteorological agency (jma), has become very sophisticated based on japan’s experience with mitigating earthquake disasters. this study presents a new and universal design philosophy for quantifying shakings and vibrations during earthquakes based on the jma method. the evaluation process involves the determination of seismic intensity level (sil) with the primary purpose of defining countermeasures or preventive actions for minimizing the number of human casualties. * corresponding author. e-mail address: gan.buntarasthenly@nihon-u.ac.jp tel.: +81-24-9568735 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 there is plenty of existing literature on the earthquake-resistant buildings and the mitigating earthquake disasters. however, to the best of authors’ knowledge, there is no literature on evaluating the comfort-level performance of buildings against the shakings during earthquakes. during the occurrences of earthquakes, sil values are calculated immediately from the earthquake wave information at the ground of every recording station during an earthquake. higher floors in high-rise buildings will experience more vigorous shaking than the ground. therefore, the present work will expand sil’s application from ground shaking to specific floors in a general building. 2. statistics on human casualties, building collapse, and damage for 23 years (since 1996), jma has collected data from 153 locations, including the seismic magnitude, sil, number of human casualties, and building damage or collapse due to significant earthquakes [2-3]. excluding the 2011 tohoku earthquake in which the human casualties and building damage/collapse were primarily due to the tsunami, the comparison between the number of human casualties (death or injured) and the number of buildings that collapsed or were damaged are presented in fig. 1. fig. 1 statistical data on human and building casualties due to earthquakes [2, 4] as shown in fig. 1, the number of injured people is significantly larger than the number of deaths or missing people, and the ratio has increased over the years. however, the number of collapsed buildings’ ratio to the number of damaged structures was far lower. the earthquake-resistant design standards provide excellent earthquake resistance in relation to just the building’s strength. on the contrary, the deaths and injuries are not mainly due to building collapse [5]. strong earthquakes that cause vibrations can result in injuries and fatalities [6-7]. thus, structural damage plays a crucial role in the number of human casualties during earthquakes [8]. the design codes, which only focus on a structure’s strength, do not suffice to protect inhabitants from injury. the behavior of buildings with the reinforced concrete subjected to lateral loads has been tested to evaluate their strengths [9-11]. the casualties attributable to the extensive shaking of a non-collapsed or damaged building should be considered. fig. 2 shows the relationship between the earthquakes’ magnitude on the richter scale and sil [2, 12-13]. as shown in fig. 2, the recorded magnitudes at earthquakes’ epicenters on the richter scale and sil deviate from their linear relationship [2, 14-15]. the non-linear relationship between the magnitudes and sil is caused by the location of the earthquake recording stations where sil is calculated depending on soil conditions, distances, and depths from the earthquake epicenter. hence, the proposed new seismic-performance design code for casualties attributable to non-collapsed structures should be based on sil values, instead of earthquakes’ magnitude. sil values provide a realistic representation of the real shaking because the effects of the building’s distance from the epicenter, the soil conditions, the buildings’ 1 10 100 1000 10000 100000 1000000 1995 1998 2001 2004 2006 2009 2012 2014 2017 f at al it ie s/ in ju rr ie s an d st ru ct u ra l da m ag e/ fa il u re (l o g sc al e) year structural damage injuries structural failure dead and/or missing 158 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 characteristics, the earthquake’s magnitude, and human perceptions of the shaking phenomena due to the earthquake are considered. the quantification of human perceptions during shaking provides accurate scientific information of the buildings’ residents. fig. 2 relationship between the magnitude on the richter scale and sil [2, 4] 3. about sil before 1996, in japan, sil was qualitatively estimated based on human perceptions, and the numbers of casualties attributable to earthquakes were considered secondary information. since then, attempts have been made to evaluate sil quantitatively. jma compiled the data from approximately 4000 sil observation stations throughout japan (recently added by fire and disaster management agency (fdma)). sil has been widely utilized in japan to broadcast quick and informative earthquake warnings to the entire country through the television for disaster mitigation when an earthquake hits the country [2, 16-18]. table 1 presents the descriptions of sil values with the corresponding sil (computed m-sil) ranges in 10 categories based on human perceptions and buildings’ damage level. table 1 descriptions of sil (freely translated from japanese) sil m-sil human perception and reaction 0 0–0.4 imperceptible to people. 1 0.5–1.4 felt slightly by a few people inside a quiet room of a building. 2 1.5–2.4 felt by some people inside a quiet room of a building. 3 2.5–3.4 felt by most people in a building. 4 3.5–4.4 most people are startled, hanging objects such as lamps swing significantly, and unstable ornaments may fall. 5 weak 4.5–4.9 many people are frightened and feel the need to hold onto something stable. dishes in cupboards and items on bookshelves may fall. unsecured furniture may move, and unstable furniture may topple over. 5 strong 5.0–5.4 many people find that it is difficult to walk without holding onto something stable. dishes in cupboards and items on bookshelves are more likely to fall. unsecured furniture may topple over. unreinforced concrete-block walls may collapse. 6 weak 5.5–5.9 people find that it is difficult to remain standing. unsecured furniture moves and topples over. doors may become stuck shut. wall tiles and windows may sustain damage and fall. in wooden houses with low earthquake resistance, tiles may fall, and buildings may lean or collapse. 6 strong 6.0–6.4 people find that it is difficult to move without crawling. people may be thrown from their position. most unsecured furniture move and are more likely to topple over. wooden houses with a low earthquake resistance are more likely to lean or collapse (compared with previous cases). large cracks may occur, as well as large landslides and collapses. 7 ≥ 6.5 wooden houses with low earthquake resistance are even more likely to lean or collapse. wooden houses with a high earthquake resistance may lean. the majority of reinforced concrete buildings with low earthquake resistance will collapse. 3.0 4.0 5.0 6.0 7.0 8.0 9.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 e ar th qu ak e m ag ni tu de ( m ar ch 1 99 6 ju ne 2 01 8) seismic intensity level (march 1996 june 2018) 159 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 additionally, modified mercalli intensity (mmi) is used to classify the shaking effects on humans. although the mmi scale has 12 intensity scales with pictorial illustrations and simple explanations regarding the effects of shaking on humans, the perceptions are essentially qualitative [19-22]. because sil can be evaluated quantitatively, it is an essential evaluation tool in designing buildings to reduce the seismic intensity and the number of human casualties. it should be noted that the sil values are calculated immediately from the earthquake wave information at every recording station during the earthquake. it is most likely that higher floors in high-rise buildings will experience higher shaking sil than the ground, hence more human casualties were due to the unmitigated design of the buildings. 4. calculating sil (m-sil) the procedure for computing m-sil value (the calculated sil value) of the jma intensity scale was presented in [13]. a brief explanation is presented herein for clarity. first, the fast fourier transform (fft) is applied to each of the threecomponent acceleration recorded in the frequency domain of the ground responses [18]. the bandpass filters given in eqs. (1)-(6) are then applied to the frequency domain of the three-component accelerations. after the filters are applied, the frequency domain’s accelerations are transformed back to the time domain. the normalized vectored composition of the three components is used to calculate the amplitude of the acceleration. the intensity is automatically calculated using threecomponent ground acceleration records after the application of a band pass filter [13], as follows: 1 2 3λ λ λ λ= × × (1) 1 1 f λ = (2) 2 4 6 8 10 12 2 1 0.694 0.241 0.0557 0.009664 0.00134 0.000155y y y y y yλ = + + + + + + (3) 38 3 1 f eλ −= − (4) 10 f y = (5) where � represents the dominant frequency, �� represents the filter on-period effect, �� represents the high-cut filter, and �� represents the low-cut filter. by using the filtered time-domain acceleration and its vectored acceleration, m-sil can be determined by using eq. (6). ( )0.3m-sil 2log 0.94a= + (6) where ��.� is the lowest maximum acceleration of a continuously total duration of 0.3 seconds around the peak acceleration response. according to previous studies [5, 23], ��.� must be determined at the lowest maximum acceleration of a continuously total duration of 0.3 seconds around the absolute values of peak acceleration response. the sil value can be classified by using the computed m-sil value as shown in table 1. fig. 3 illustrates the way to determine the ��.� values. fig. 3(a) shows the band pass filtered absolute acceleration response in the time domain. the dotted line defines the lowest maximum acceleration ��.� of a continuously total duration of 0.3 seconds around the peak acceleration. in the second method, ��.� can also be determined by plotting the cumulative duration against the vectored acceleration, as shown in fig. 3(b). the lowest maximum acceleration ��.� can be determined at the cumulative duration of 0.3 seconds. 160 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 (a) fft spectrum of response acceleration (b) cumulative duration of fft spectrum fig. 3 illustrative response acceleration for calculating ��.� 4.1. implementation of quantitative sil in seismic-performance design the implementation of the quantitative values m-sil derived from eq. (6) should be implemented into the performance design of buildings. fig. 4 shows a flowchart of the proposed seismic-performance design concept. fig. 4 flowchart of the proposed comfort-level performance design using sil 4.2. numerical simulation to demonstrate the effectiveness and usefulness of the proposed method, a numerical simulation is performed on a building. numerical simulations have been proven to be a sophisticated method for evaluating the seismic performance of steel structures [24-25]. fig. 5 shows three prototypes of a two-story steel frame structure. these three prototypes of the same structural members’ steel structures are evaluated and classified according to their strengthening methods. the first structure uses moment-resisting frame (mrf) method, the second structure uses concentrically braced frame (brf) method, and the third structure uses mrf equipped with base isolation (bi) system. the columns are wf 250×250×8×13 sections, and the beams and bracings are wf 250×125×6×9 sections. all structural members are made of grade a36 steel. the span in all the directions is 4.00 m, with a floor-to-floor height of 3.50 m (fig. 5). the bi structure has a typical bi rubber bearing. the strengthening methods of the three structures are designed to fulfill the earthquake-resistant design required by the building codes. vectored acceleration [gal ] c u m m ul at iv e d ur at io n [s ] t a a0.3 t = 0.3 sec time history response analysis of building (dynamic analysis during the earthquake wave) input: earthquake wave analysis model (building + soil + foundation) output: building responses （acceleration, velocity, displacement） response acceleration response displacement calculate the value of a0.3 (jma) determine the dominant period, tdom (using fft) plot (tdom, a0.3) onto the sil graph of jma 161 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 (a) perspective view of three prototypes of two-story steel frame structures (b) three prototypes of two-story steel frame structures fig. 5 types of building strengthening for sil evaluation the structures are assumed to be located on soft soil as this type of soil shakes the most during earthquakes. fig. 6 shows a prior-selected response spectrum that is used to generate artificial earthquake waves. the response spectrum is obtained from semarang (smg), a city in central java (7.0051° s, 110.4381° e). in this study, several earthquake waves [26-27] recommended for seismic-performance evaluation are considered for simulation purposes. the response spectrum (fig. 6) is used to generate artificial earthquake waves following the corresponding earthquake waves as tabulated in table 2. in the present numerical simulation, the earthquake waves are used for comparison purposes. to develop and check the consistency of the measured and computed signal processing of the earthquake waves, data consistency assessment function (dcaf) [28-29] is recommended. table 3 shows the maximum acceleration, the lowest maximum acceleration ��.�, and the m-sil calculated using eq. (6) at smg location for different earthquake waves in table 3. it can be observed that the values of m-sil shown in table 3 are determined to be about 5.4 in order to fit with the selected response spectrum of smg. the three structural prototypes are analyzed by using the linear material dynamic time-history analysis with the input earthquake waves taken from the artificial acceleration time-history as shown in table 2. fig. 6 response spectrum for soft soil of smg location 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 0.5 1 1.5 2 2.5 3 3.5 4 sp ec tr al a cc el er at io n [ g a l ] period t [s] a s 162 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 table 2 artificial acceleration time-history at smg site earthquake year magnitude artificial acceleration time-history big bear 1992 6.46 el centro 1940 6.95 kobe 1995 6.90 loma prieta 1989 6.93 morgan hill 1984 6.19 mammoth lake 1980 6.06 northridge 1994 6.69 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0 10 20 30 40 50 60 a cc el er at io n [g a l] time [s] 163 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 table 3 values of m-sil at smg location (ground) earthquake sampling location maximum acceleration [gal] lowest maximum acceleration ��.� [gal] m-sil big bear-smg 280 178 5.4408 el centro-smg 290 173 5.4161 kobe-smg 300 206 5.5677 loma prieta-smg 310 189 5.4929 morgan hill-smg 320 187 5.4837 mammoth lake-smg 310 173 5.4161 northridge-smg 290 166 5.3802 (a) displacement-time response (b) fft spectrum fig. 7 rooftop response (using el centro-smg earthquake wave) table 4 tdom calculation results using fft earthquake sampling location axis floor mrf brf bi tdom tdom tdom [s] [s] [s] big bear x roof 0.356 0.145 2.114 2nd 0.356 0.145 2.114 y roof 0.475 0.130 2.048 2nd 0.475 0.130 2.048 el centro x roof 0.370 0.147 2.260 2nd 0.370 0.147 2.260 y roof 0.468 0.127 2.260 2nd 0.468 0.127 2.260 kobe x roof 0.377 0.144 2.114 2nd 0.377 0.144 2.114 y roof 0.471 0.128 2.114 2nd 0.471 0.128 2.114 loma prieta x roof 0.360 0.148 2.114 2nd 0.360 0.148 2.114 y roof 0.462 0.133 2.114 2nd 0.462 0.133 2.114 morgan hill x roof 0.364 0.144 2.114 2nd 0.364 0.144 2.114 y roof 0.465 0.124 2.114 2nd 0.465 0.124 2.114 mammoth lake x roof 0.354 0.143 2.260 2nd 0.354 0.143 2.260 y roof 0.478 0.134 2.185 2nd 0.478 0.134 2.185 northridge x roof 0.354 0.149 2.114 2nd 0.354 0.149 2.114 y roof 0.493 0.132 2.114 2nd 0.493 0.132 2.114 -35 -25 -15 -5 5 15 25 35 0 10 20 30 40 50 60 d is pl ac em en t [m m ] time [s] mrf brf bi 0 2000 4000 6000 8000 10000 12000 14000 0.01 0.1 1 10 | y ( fr eq u en cy ) | frequency [hz] mrf brf bi 164 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 table 5 sil evaluation of the rooftop floor earthquake sampling location axis floor mrf brf bi tdom a0.3 jma tdom a0.3 jma tdom a0.3 jma (s) (gal) sil (s) (gal) sil (s) (gal) sil big bear x roof 0.356 702.58 6 strong 0.145 567.61 5 strong 2.114 22.05 4 2nd 405.20 6 weak 393.82 5 strong 15.98 3 y roof 0.475 749.33 6 strong 0.130 507.91 5 strong 2.048 31.61 4 2nd 500.03 6 strong 367.23 5 weak 28.26 4 el centro x roof 0.370 757.04 6 strong 0.147 478.93 5 strong 2.260 15.30 3 2nd 438.34 6 weak 338.93 5 weak 14.68 3 y roof 0.468 702.20 6 strong 0.127 475.62 5 strong 2.260 26.61 4 2nd 433.15 6 weak 367.74 5 strong 25.64 4 kobe x roof 0.377 522.19 6 weak 0.144 502.98 5 strong 2.114 18.90 4 2nd 332.22 6 weak 340.01 5 strong 14.87 3 y roof 0.471 700.58 6 strong 0.128 442.08 5 strong 2.114 26.64 4 2nd 402.12 6 weak 324.12 5 weak 25.98 4 loma prieta x roof 0.360 688.63 6 strong 0.148 512.13 5 strong 2.114 18.13 4 2nd 422.38 6 weak 382.89 5 strong 16.06 3 y roof 0.462 682.83 6 strong 0.133 468.15 5 strong 2.114 32.05 4 2nd 404.61 6 weak 344.48 5 weak 30.43 4 morgan hill x roof 0.364 770.13 6 strong 0.144 475.01 5 strong 2.114 18.70 4 2nd 401.77 6 weak 328.11 5 weak 15.69 3 y roof 0.465 685.59 6 strong 0.124 439.83 5 strong 2.114 30.88 4 2nd 385.01 6 weak 325.90 5 weak 29.45 4 mammoth lake x roof 0.354 770.13 6 strong 0.143 531.88 5 strong 2.260 22.02 4 2nd 401.77 6 weak 367.21 5 weak 15.24 3 y roof 0.478 701.33 6 strong 0.134 534.70 5 strong 2.185 26.17 4 2nd 442.03 6 weak 381.01 5 weak 27.35 4 northridge x roof 0.354 687.90 6 strong 0.149 538.96 5 strong 2.114 19.89 4 2nd 406.55 6 weak 372.79 5 strong 16.00 3 y roof 0.493 764.98 6 strong 0.132 489.06 5 strong 2.114 28.86 4 2nd 456.38 6 weak 357.85 5 weak 28.17 4 the displacement response on every floor in the buildings is analyzed using the time-history analysis [30] with a particular earthquake wave input. we determine the dominant period tdom on every floor in the buildings from the history of displacement response. fig. 7 shows the representative displacement responses on the rooftop of three buildings under evaluation using the el centro-smg earthquake wave as the input. a standard fft is performed on the time against displacement response relationship [31-32] to determine the buildings’ time dominant period (fig. 7(a)). fig. 7(b) presents the resulting fft spectrum of the displacement time response of three evaluated buildings using the el centro-smg earthquake wave as the input. table 4 shows the time-dominant period tdom based on the fft calculation, and table 5 presents the sil values for each floor obtained from the lowest maximum acceleration ��.�. in this simulation, the rooftop floor has a higher acceleration ��.� than the second floor for all types of prototypes and all time-history earthquakes in both xand y-axis directions. the acceleration is directly correlated to the sil value. a higher ��.� acceleration resulted in the higher sil value calculated from the acceleration to time-dominant period relationship is plotted in fig. 8 [4]. the results show that the bi prototype has the lowest ��.� acceleration and sil value. the sil value ranges from 3 to 4, corresponding to an ��.� in the range of 15-32 gal. for the mrf prototype, sil ranges from 6 weak to 6 strong, corresponding to 332-770 gal. the brf prototype has an ��.� in the range of 324-539 gal, and sil ranges from 5 strong to 5 weak. a graphical representation of the sil curves as a function of the time-dominant period and maximum acceleration ��.� for the el centro-smg case is shown in fig. 8. an examination of these graphs reveals that the range of the curve corresponds to the ��.� and time-dominant period (tdom) of the prototypes. 165 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 fig. 8 sil as a function of the dominant period and acceleration [2, 33] as shown in fig. 8, the sil values’ categorization between lines is based on a more significant value than the lower sil values. for example, for the bi frame, the x-direction response is designated as sil-3, whereas in reality, the condition closely approaches sil-4. nevertheless, the classification assigns sil to 3. this might lead to improper simulated behavior because the structure closely resembles sil-4. it is suggested that the bandwidth between sil categories should be proposed based on either a mathematical study or an experimental study. the results of the numerical simulation reveal that the strengthening method significantly affects the sil value. bi significantly reduces and stabilizes the sil of every floor, while mrf results in a less sensitive response to sil in all directions. furthermore, these observations suggest that sil is significantly affected by the frame’s configuration and displacement direction, in contrast to the acceleration response. 5. conclusions a method for quantifying sil based on the acceleration and dominant period on every floor of a structure was proposed and demonstrated. the proposed design philosophy for buildings’ comfort-level performance is inherently a new and universal design philosophy that can be applied to different building codes and various earthquake waves. one of the advantages of this sil calculation method is that it can quantify the shaking on each floor of a building during earthquakes, which will aid the quantitative measuring of the residents’ comfort levels. the proposed sil-based performance evaluation is beneficial in the planning, designing, and strengthening stages of building constructions. the silbased method for calculating the level of shaking can also be used to quantitatively evaluate the performance of newly developed earthquake-resistant building reinforcement equipment. additionally, the present proposed method can monitor the shaking in buildings during earthquakes so that suitable measures can be taken quickly. considering the significant potential of the proposed sil method for quantifying the level of shaking, the residents’ comfort level should be accounted for in current earthquake-resistant design building codes. 6. future recommendation experimental works on building prototypes have to be conducted to precisely verify the quantitative shaking intensity level for research directions. for practical applications, the present proposed method could be beneficial for the following: 0.1 1 10 100 1000 10000 0.01 0.1 1 10 100 a cc el er at io n [g a l ] dominant period tdom [s] mrf x y bi x y 0. 3 a 166 advances in technology innovation, vol. 6, no. 3, 2021, pp. 157-168 (1) in the planning and designing stages, to predict the quantitative shaking that will occur in the building on different floors. 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[33] “seismic intensity level and acceleration, weather and earthquakes, seismic intensity information 2003,” http://www.jma.go.jp/en/quake/quake_sindo_index.html, 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 168 template encit2010 advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 consensus via adaptive gain controllers considering relative distances for multi-agent systems shun ito 1,* , kazuki miyakoshi 1 , hidetoshi oya 1 , yoshikatsu hoshi 1 , shunya nagai 2 1 graduate school of integrative science and engineering, tokyo city university, tokyo, japan 2 department of information systems creation, kanagawa university, kanagawa, japan received 25 april 2019; received in revised form 11 june 2019; accepted 28 july 2019 abstract in this paper, for multi-agent systems (mass) with leader-follower structures, we present a linear matrix inequality (lmi)-based design method of an adaptive gain controller considering relative distances between agents. the proposed adaptive gain controller consists of fixed gains and variable ones tuned by time-varying adjustable parameters. the objective of this paper is to derive enough conditions for the existence of the proposed adaptive gain controller which achieves consensus for each agent. the advantages of the proposed adaptive gain controller are as follows; the proposed controller can be obtained by solving lmi, and the proposed control system can achieve consensus and formation control, even if uncertainties are included in the information for relative distances. in this paper, we show that the design problem of the proposed adaptive gain controller can be reduced to the solvability of lmi. finally, simple numerical examples are included to illustrate the effectiveness of the proposed adaptive gain controller for mass. keywords: multi-agent systems (mass), consensus, relative distance, adaptive gain controller, linear matrix inequality (lmi) 1. introduction when we consider designing control systems for dynamical systems, it is necessary to derive a mathematical model for the controlled system, and one can see that optimal control is well known to be a powerful strategy in modern control theory. lq regulator for linear systems is a typical controller, and it ensures asymptotical stability for closed-loop systems with good robustness provided that a mathematical model for a control system describes precisely [1,2]. however, there always exist some gaps between the mathematical model and the controlled system, and the gaps are referred to as “uncertainty”. therefore, controller design methods dealing with uncertainties explicitly have been required, and robust control for uncertain dynamical systems has been extensively studied. one can see that robust control can be classified into “robust stability analysis” and “robust stabilization”, and lots of existing results for robust control strategies have been presented [3-6] and quadratic stabilizing controllers and control are well known robust control strategies[7,8]. note that the conventional robust controller consists of fixed gains which are derived by considering the worst-case variations for uncertainties. in contrast with the conventional robust control with fixed gains, some researchers have presented variable gain robust controllers for uncertain systems [9-11]. such variable gain robust control strategies are more flexible and adaptive comparing with the conventional robust control with fixed gains. on the other hand, the practical systems in modern society have become large-scale and complex due to rapid development of technologies, and such systems are referred to as “large-scale interconnected systems”. since it is difficult to apply centralized control strategies to such large-scale interconnected systems, design problems of decentralized control for *corresponding author. e-mail address: g1881842@tcu.ac.jp advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 235 large-scale interconnected systems have been well studied (see [12] and references therein). for instance, one can see that large interconnected power distribution systems which have strong interactions, transportation and traffic systems with lots of external signals, water systems which are widely distributed in the environment, energy systems, communication systems and so on are large-scale systems. moreover, formation control has recently attracted much attention, and a multi-agent system, in general, can be described as a network of a few of coupled dynamic units that are called agents. the design problems of formation control for mass are considered as one of the decentralized control problems and it is well-known that mass can achieve various task efficiently. for design problems of formation control for mass, the consensus problem has received a lot of attention, because this problem has drawn substantial attention from various fields such as vehicle formations, unmanned aerial vehicles, mobile robots, sensor networks, and so on. moreover, a consensus which means the states of all agents are driven to a common state by implementing distributed protocols is well accepted as one of the most important and fundamental problem in formation control. thus, a large number of existing results for consensus problem have been presented (e.g. [13-16]). in the work of olfati-saber et al. [13], the consensus problem for a network of first-order integrators with directed information flow and fixed/switching topology has been studied, and convergence analysis of a consensus protocol for a class of networks of dynamic agents with fixed topology have been shown [14]. zhang and tian have studied the mean-square consensus for mass composed of second-order integrators [15], and the matrix inequalitybased stabilization condition and consensus algorithm for mass have been presented [16]. also, a number of the existing results for the leader-follower consensus for mass has been presented([17-19]). “leader-follower” refers to defining a leader (whether real or virtual) and controlling another agent (follower) to follow the leader. in these results for consensus problem for mass, controllers have fixed gain parameters only, and relative distances between agents cannot be considered explicitly. there are few results of the consensus problem via adaptive gain-based controller considering relative distances between agents for mass. from the above, this paper deals with a consensus problem for mass with leader-follower structures. in this paper, we present a design method of an adaptive gain controller giving considering relative distances between agents. the adaptive gain controller consists of fixed gains and variable ones tuned by time-varying adjustable parameters. in this paper. we show that enough conditions for the existence of the proposed adaptive gain controller can be reduced to linear matrix inequality (lmi). the proposed adaptive gain control strategy has advantages as follows; the proposed controller design approach can handle relative distances between agents explicitly. furthermore, even if the information for relative distances between the other agents and the leader is unknown, but their upper bounds are known, the controller can achieve consensus. furthermore, the proposed consensus control system can be designed by solving lmi. finally, simple numerical examples are included to illustrate the effectiveness of the proposed formation control systems. 2. preliminaries this chapter shows the mathematical notation used in this paper. m n represents an m-by-n real matrix, and ni represents an n-dimensional identity matrix. for matrix a , ta and 1a represent transpose and inverse. for a square matrix a , 0( 0)a a  indicates that a is positive definite (positive semidefinite) and 0( 0)a a  is negative definite (negative semidefinite). c is the norm of any matrix c . 1 2( , ,..., )ndiag a a a gives a diagonal block matrix with matrices ia (i = 1, 2, ..., n) on the diagonal. element * in the matrix represents a symmetric element. if a is a m×n matrix and b is a p×q matrix, the kronecker product a b is defined as follows; 11 1 1 n mnm mp nq a b a b a b a b a b             (1) advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 236 moreover, in this paper, we express the information path between agents based on graph theory [20]. the graph is collection of vertices and edges, and the notation of a graph is ( , ) , where {1,2,..., }n is the set of n vertices in the graph, and  is the set of edges connecting the vertices. note that there are two types of graph, i.e. undirected graph and directed one. in this paper, we consider the directed graph. furthermore, we introduce an adjacency matrix , a degree matrix and a graph laplacian in order to express the graph algebraically. the adjacency matrix represents the adjacency relation of each vertex of the graph. in the graph ( , ) for a pair ( , )i j  that is, there is an edge from j to i the vertex i is said to be adjacent to j . in this case, the adjacent set of vertices i is  | ( , )i j i j   , and the elements ija of ija    is defined as 1 if( , ) and 0 otherwise ij i j i j a      (2) additionally, in the directed graph ( , ) , the in-degree of a vertex represents the number of edges incoming to the vertex and it is denoted as in id . conversely, out-degree means the number of edges outgoing from a vertex. then for the graph ( , ) , the degree matrix n n and the graph laplacian are defined as 1 2( , ,..., )ndiag a a a (3)  (4) furthermore, the following useful lemma is used in this paper: lemma 1 [21]: for arbitrary vectors and  , matrices g and h with appropriate dimensions, the following inequality holds: 2 2t tgh g h    (5) 3. problem formulation fig. 1 multi-agent system in this paper in fig.1, the triangle “ i ” represents i -th agent(i=1,2,3). moreover “ l ” means the leader and the others are followers, and arrows indicate communication paths. then, the adjacency matrix , the degree matrix , and the graph laplacian in fig.1 can be obtained as 0 0 0 2 0 0 2 0 0 1 0 1 , 0 2 0 , 1 2 1 1 1 0 0 0 2 1 1 2                                   (6) now we assume that i -th agent ( ,2,3i l ) can be described as the following state equation: advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 237 ( ) ( ) ( ) ( 1,2,3)i i i d dt x t ax t bu t i   (7) where ( ) n ix t  and ( ) m iu t  are the vectors of the state and the control input, and the state ( ) n ix t  is given by  ( ) ( ) ( ) ( ) ( ) t i xi xi yi yix t x t v t x t v t (8) i.e. the state ( )xix t (resp. ( )yix t ) is the position in x-axis (resp. y-axis), and ( )xiv t (resp. ( )yiv t ) is velocity in x-axis (resp. yaxis) for the i -th agent. in (7), l na  and l mb  are the system parameters which are defined as 0 1 0 0 0 0 0 0 0 0 1 0 , 0 0 0 1 0 0 0 0 0 0 0 1 a b                          (9) here, in order to consider the relative positions between agents, we introduce the following vectors:  ˆ ˆ t i xi xi yi yid d v d v (10) where xid (resp. yid ) is the desired relative position in x-axis (resp. y-axis) between the i -th agent and the leader agent. similarly, ˆxiv and ˆyiv are the target velocity. note that one can see that 0ld . here, we consider the difference between the actual position of the agent ( ( ))ix t and the desired relative position between the leader and the follower id as a new state of the system. from (7), the state equation of each follower considering the relative positions from leader to follower is expressed as    ( ) ( ) ( ) ( 1,2.3)i i i i i d x t d a x t d bu t i dt      (11) by introducing the additional state vector ( )ix t described as   ( ) ( ) ˆ( ) ( ) ( ) ( ) ˆ( ) ( ) ( ) ( ) xi xi xi xi xi xi i i yi yi yi yi yi yi i x t d x t v t v v t x t d x t v t v v t x t x t d                                (12) then one can see from (11) and (12) that the following state equation can be obtained: ( ) ( ) ( )i i i d dt x t ax t bu t  (13) summarizing the state equations of all agents, we get the following total system: ( ) ( ) ( )t t d dt x t a x t b u t  (14) where , , ( )t ta b x t and ( )u t are matrices and vectors given by     3 3 2 3 2 3 0 0 0 0 0 0 , b 0 0 0 0 0 0 ( ) ( ) ( ) ( ) , ( ) ( ) ( ) ( ) t t t t t t t t t t l l a b a i a a i b b a b x t x t x t x t u t u t u t u t                             (15) advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 238 next, we consider the control input ( )u t . note that consensus problem, “consensus” for agents means that the following relation for i  and j  holds:  lim ( ) ( ) 0i j t x t x t    (16) if 2 4f  is the consensus gain, it is known that the consensus input for ( )ix t , ( )fiu t is given by [22].  ( ) ( ) ( ) i fi i j j u t f x t x t    (17) in the case of this paper, ( )fiu t is calculated as follows: 2 2 3 3 2 3 ( ) 0 ( ) ( ( ) 2 ( ) ( )) ( ) ( ( ) ( ) 2 ( )) fl f l f l u t u t f x t x t x t u t f x t x t x t          (18) namely,  2 3 ( ) ( ) ( ) ( ) t t t t f fl f f u t u t u t u t can be represented by the following matrix-vector form: 2 3 0 0 0 ( ) ( ) 2 ( ) ( ) ( ) 2 ( ) l f x t u t f f f x t f x t f f f x t                    (19) additionally, let ( )ku t be the state feedback input for stabilization of the system. by using the feedback gain matrix 2 4( )ku t  , the state feedback input ( )ku t can be written as ( ) ( ) ( )ku t i k x t (20) finally, we introduce a compensation input v(t) and consider the following control input: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 0 0 0 0 0 2 ( ) 2 ( ) 2 2 k f t u t u t u t v t i k x t f x t v t k f k f f x t f f f d v t f f k f f f f                                      (21) where  2 3 ( ) ( ) ( ) ( ) t t t t l v t v t v t v t . note that the design method for the compensation input v(t) and the gain matrices 2 4k  and 2 4f  is discussed in the next section. from (14) and (21), we have 2 3 0 0 0 0 0 2 2 2 2 0 0 0 0 ( ) 0 0 0 * 0 ( 2 ) ( ) 2 * * ( 2 ) ( ) ( ) ( )( ) ( ) l t tt k d f k f f f f f dt f f k f f f f a bk x t a bf b k f bf x t bf bf a bf bf b k f x t b x t d v tx t a x t                                                                             2 3 2 2 2 3 3 3 2 3 0 0 * 0 ( ) 2 * * 0 0 ( ) ( ) ( ) ( ) (2 ) ( ) ( ) ( 2 ) l k l l f f d b bf d b v t bf bf bf d b a x t bv t bf a bf x t bv t bf d d bf bf a x t bv t bf d d                                                           (22) in (21), ka and fa are the matrices described as ka a bk  , 2ka a bk bf   . advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 239 from the above, the controller design objective in this study is to derive the consensus gain 2 4f  , the feedback gain 2 4k  and compensation input 6( )v t  so that the asymptotic stability of the closed-loop system of (22) is guaranteed. 4. main results in this section, the design method of the feedback gain 2 4k  , the consensus gains 2 4f  and the compensation input 2( ) ( ,2,3)iv t i l  is shown. we give the following theorem for determining these parameters of the overall system (22). theorem 1. consider the overall system of (14) and the control input of (21). if there exist solutions 0s  , kw and fw of following lmi condition: 11 12 13 22 23 33 11 12 13 22 33 23 * 0 * * , 2 , 2 2 , k k t t t t t k k k t t t t t t t k k f f f f a a bk a a bk bf sa as w b bw w b sa as w b bw bw w b w b bw                                            (23) then the compensation input ( )v t is designed as follows, 2 2 2 3 22 23 3 3 2 32 3 0 ( ) ( ) ( ) ( ) 2 ( ) ( )( ) ( ) 2 ( ) ( ) t tl t t t t t t v t f b px t v t v t fd dm b px t b px tv t f b px t fd dm b px t b px t                                 (24) where the matrix p is given by 1p s and the feedback gain matrix k and the consensus one f are designed as 1 kk w s (25) 1 ff w s (26) moreover, by applying the control input of (27) with the compensation input ( )v t of (24) the gain matrices k (25) and f (26) to the overall system of (14), asymptotic stability of the closed-loop system of (22) is guaranteed. proof: using a positive definite symmetric matrix 4 4tp p   , we introduce the following quadratic function as a candidate for lyapunov function: 3( , ) ( ) ( ) ( )tv x t x t i p x t  (27) the time derivative of the quadratic function along the trajectory of the closed-loop system of (22) satisfies  3 3( , ) ( ) ( ) ( ) ( ) ( ) ( )t td d d v x t x t i p x t x t i p x t dt dt dt     (28) advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 240 as is well known, the stability condition for the closed-loop system is ( , ) 0 d dt v x t  (29) and the time derivative of the quadratic function along the trajectory of the closed-loop system of (22) can be written as 2 2 3 3 3 2 3 3 2 2 3 3 0 0 ( ) ( , ) ( ) ( ) (2 ) ( ) ( ) ( ) ( 2 ) 0 0 ( ) ( ) ( ) ( ) ( ) (2 ) ( ) t k l f f k l t f f a bv t d v x t bf a bf x t bv t bf d d i p x t dt bf bf a bv t bf d d a bv t x t i p bf a bf x t bv t bf d d bf bf a bv t b                                                 2 3 2 2 3 2 2 3 3 2 3 3 ( 2 ) ( ) ( ) * ( ) ( ) ( ) ( ) (2 ) ( ) (2 ) ( ) ( 2 ) ( ) t t t t t k k t t t t f f t f f l l t t t t t f d d a p pa f b p f b p x t pbf a p pa f b p pbf x t pbf a p pa v t v t x t p b v t f d d p b v t f d d v t f d d v t f                                                    2 3 ( ) ( 2 ) t x t d d                (30) where 12 12 tp  is the following symmetric positive definite matrix: 3 0 0 * 0 * * t p p i p p p              (31) here, by introducing the matrix ( , , )p k f and the scalar function ( , , ( ))p f v t which are defined as         2 2 3 2 2 3 3 2 3 3 2 3 2 2 3 2 3 2 3 ( ) ( ) ( , , ( )) ( ) ( ) (2 ) ( ) (2 ) ( ) ( ) ( 2 ) ( ) ( 2 ) 2 ( ) ( ) 2 ( ) 2 ( ) 2 ( ) 2 t l l t t t t t tt l l v t v t p f v t x t p b v t f d d p b v t f d d x t v t f d d v t f d d pb pbv t x t pb pb v t f d d x t pb pb v t f d d                                             3( ) t x t   (32) ( , , ) * * * t t t t t k k t t t f f t f f a p pa f b p f b p p k f a p pa f b p pbf a p pa                  (33) one can see that the stability condition for the closed-loop system of (22) is reduced to ( , ) ( ) ( , , ) ( , , ( )) 0td v x t x t p k f p f v t dt     (34) namely, if the matrix ( , , )p k f is negative definite and ( , , ( ))p f v t < 0 are satisfied, then the quadratic function ( , )v x t becomes a lyapunov function. for leader agent, there is no need the compensation input, i.e. ( ) 0lv t  then we have      2 2 2 3 2 2 2 2 2 3 2 3 3 2 3 3 3 3 2 3 3 3 ( ) ( ) 0 ( ) ( ) (2 ) ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) 2 ( ) l l t t t t t t t t t t t t t t t pbv t t pb v t f d d x t v t b px t d f b px t d f b px t t pb v t f d d x t v t b px t d f b px t d f b px t                       (35) where ( )i t ( ,2,3)i l is the i -th term in the right-hand side of (32). since ( ) 0lv t  , we consider the design problem of 2 ( )v t and 3( )v t . let 3( )t be an auxiliary input for reducing the effect of 3d . in this paper, 3d means the relative position advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 241 between the leader and the follower 3, and it is unknown to the follower 2. the follower 2 can obtain the information for the upper bound 3dm for the relative position, i.e. 3dm satisfies 3 3d dm . therefore, we consider 2 2 3( ) 2 ( )v t fd t   (36) and one can see that for the third term in the right-hand side of 2 ( )t in (35) the following inequality holds: 3 2 3 2 3 2 ( ) ( ) ( ) t t t t t t d f b px t d f b px t dm f b px t     (37) thus, by selecting 3( )t defined as 2 3 3 22 2 ( ) ( ) ( ) ( ) t t t t f b px t t dm b px t b px t    (38) we can obtain 2 2 2 2 3 2 2 2 2 3 22 2 ( ) ( ) 2 ( ) ( ) ( ) 2 ( ) ( ) ( ) 0 t t t t t t t t t t f b px t t d f b px t dm x t pb b px t d f b px t dm f b px t b px t                  (39) similarly, we consider the following compensation input for follower 3: 3 3 2( ) 2 ( )v t fd t   (40) for the third term in the right-hand side of 3( )t in (35), we find that the inequality 2 3 2 3 2 3 ( ) ( ) ( ) t t t t t t d f b px t d f b px t dm f b px t     (41) is satisfied, and thus 2 ( )t is designed as 3 2 2 32 3 ( ) ( ) ( ) ( ) t t t t f b px t t dm b px t b px t    (42) then we can obtain the following inequality: 3( ) 0t  (43) consequently, if ( )v t is designed as 2 2 2 3 22 23 3 3 2 32 3 0 ( ) ( ) ( ) ( ) 2 ( ) ( )( ) ( ) 2 ( ) ( ) t tl t t t t t t v t f b px t v t v t fd dm b px t b px tv t f b px t fd dm b px t b px t                                 (44) then we have advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 242  2 3( , , ( )) 2 ( ) ( ) 0p f v t t t     (45) once again considering the asymptotic stability condition of (34), the quadratic form term of ( )x t should satisfy ( ) ( , , ) ( ) 0tx t p k f x t  (46) the inequality of (46) is equivalent to the following condition; ( , , ) 0p k f  (47) in order to design the consensus gain f , and the feedback gain k , we introduce the symmetric positive definite matrix s satisfying 1s p and change of variables 2 4 kw ks   and 2 4 fw fs   . moreover, preand post-multiplying (47) by 3( )i s , we get. 11 12 13 22 23 33 11 3 3 0 0 0 0 * 0 * * 0 * * * ** * * 0 * * ( , 2 ) , ( ) ( , , )( ) t t t t t k k t t t f f t f f k k t t t k k a p pa f b p f b ps s s a p pa f b p pbf s s sa p pa a a bk a a bk bf sa as w b bw i s p k f i s                                                             12 13 22 33 232 2 , t t k t t t t t t t k k f f f f w b sa as w b bw bw w b w b bw                  (48) this inequality of (48) is linear matrix inequality (lmi) for s , kw and fw . if the solution of the lmi of (48) exists, the asymptotic stability of the closed-loop system of (22) is guaranteed, and the feedback gain k and the consensus gain f can be obtained as 1 1, k fk w s f w s   (49) from the above discussion, the proof of theorem1 is accomplished. remark 1: in this paper, we approached the case of network topology such as fig.1 as an example, but the other topological structures can be handled if similar theoretical development is applied. however, it is inevitable that lmi will increase in size and complexity by the number of agents and the topology becomes complicated. remark 2: when the relative position between the leader and the follower is considered explicitly, it is often uncertain or unknown about the relative position between the leader and the other followers. thus, construction of the state equation is generally not easy. as a result, there are not much exiting results which have explicitly dealt with the relative position in the dynamics as far as we know. on the other hand, in this study, it is possible to discuss lmi-based control system design that clearly indicates relative positional relationship by adding an input using the maximum value of relative distance that is known when performing the desired formation. 5. numerical simulation firstly, by solving lmi (48), we have symmetric positive definite matrices 4 4s  , 4 4p  and matrices 2 4 kw  and 2 4 fw  which are given by advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 243 1 3 3 1 3 3 3 3 1 3 3 1 1.1574 4.2577 10 2.0326 10 3.4553 10 4.2577 10 1.1574 3.4553 10 2.0326 10 2.0326 10 3.4553 10 1.1574 4.2577 10 3.4553 10 2.0326 10 4.2577 10 1.1574 s                                        (50) 1 1 4 3 1 1 3 4 4 3 1 1 3 4 1 1 9.9925 10 3.6760 10 2.3596 10 2.4249 10 3.6760 10 9.9925 10 2.4249 10 2.3462 10 2.3596 10 2.4249 10 9.9925 10 3.6760 10 2.4249 10 2.3462 10 3.6760 10 9.9925 10 p                                        (51) 3 18 3 1.1651 1.9053 9.7081 10 1.6958 10 9.7077 10 2.1926 1.1651 1.9053kw                 (52) 6 1 6 1 6 1 6 1 6.9246 10 7.9258 10 6.9246 10 5.6843 10 6.9246 10 5.6843 10 6.9246 10 7.9258 10 fw                      (53) then the feedback gain 2 4k  and the consensus gain 2 4f  can be calculated as 2 3 1 1.8646 2.3321 1.4595 10 6.8409 10 8.2057 10 2.1978 1.8699 2.3327 k                 (54) 1 1 1 1 1 1 1 1 2.9273 10 7.9213 10 2.1088 10 5.6819 10 2.1088 10 5.6819 10 2.9274 10 7.9213 10 f                      (55) in this example, initial values for the closed-loop system of (22) are selected as follows; 2 3 5 6 1 2 4 2 (0) , (0) , (0) 3 0 2 2 3 4 lx x x                                (56) furthermore, let ( )r t be the leader’s reference input and ( )lx t be ( ) ( ) ( )l lx t x t r t  . in this example, ( )r t gives the leader to go around a circle of radius 3 with 20[s]. also, give 2d and 3d are so that the followers 2 and 3 leaves the leader by (2, 2) and (-2, 2).         2 3 3cos 0.1 2 2 0.3sin 0.1 0 0 ( ) , , 2 23sin 0.1 0 00.3cos 0.1 t t r t d d t t                                      (57) additionally, 2dm and 3dm are selected as 2 3 6dm dm  . the simulation result of this numerical example is shown in figs. 2 7. in figs.2 5, show the state trajectory of each agent and the shape of the formation every 5[s]. figs.6 and 7 show the time histories of each agent in the x and y-axes, respectively. from figs.2-5, we can see that the leader follows the given trajectory, and the followers 2 and 3 follow the desired relative position. also, from fig.6 and fig.7, looking at the transition of the position coordinates of each agent, it can be seen that the follower moves away from the leader's movement locus by the desired position as time passes. namely, it can be said that the proposed formation control system has been designed, and thus we have shown the effectiveness of the proposed formation control systems. advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 244 fig. 2 movement of each agent in 0[s] fig. 3 movement of each agent in 10[s] fig. 4 movement of each agent in 20[s] fig. 5 movement of each agent in 40[s] fig.6 time histories of xix (t) fig.7 time histories of yix (t) 6. conclusions in this paper, we present a design method of an adaptive gain controller considering relative distances between agents for mass with leader-follower structure. the proposed adaptive gain controller consists of the state feedback laws with fixed gains and compensation input with adaptive gains which are adjusted by updating rules. we have shown that the sufficient conditions for the existence of the proposed adaptive gain controller are reduced to the solvability of lmi, i.e. the proposed controller can be designed by using software such as matlab’s lmi control toolbox, scilab’s lmitool and so on. in the proposed control strategy, there is no need the information on the target value of the other followers and the information about the upper bound on relative positions is only required. furthermore, the effectiveness of the proposed formation control system has been shown through a simple numerical example. advances technology innovation, vol. 4, no. 4, 2019, pp. 234-246 245 the future research subjects are an extension of the proposed design to such a broad class of systems as discrete-time systems and output feedback systems. moreover, for the proposed adaptive gain controller, improvement of transient performance and guaranteeing disturbance attenuation level are our important future research subjects. additionally, we will study the conservativeness of the proposed controller design and extend the proposed controller synthesis to such a broad class of control systems as a formation for mass consisting of more general agent’s dynamics with uncertainties and consensus via output feedback controllers. conflicts of interest the authors declare no conflict of interest. references [1] m. norton, modern control engineering, pergamon press, 1972. 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(in japanese) copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 an intelligent optimization system of micro electroforming process for the mesh filter wen-chin chen 1,* , pao-wen lin 2 , shi-bo lin 1 , kuan-ming lin 3 , yun-ru chang 4 1 department of industrial management, chung hua university, hsinchu, taiwan 2 ph.d. program of technology management, chung hua university, hsinchu, taiwan 3 department of foreign languages and literatures, chung hua university, hsinchu, taiwan 4 languages center, chung hua university, hsinchu, taiwan received 12 april 2019; received in revised form 19 may 2019; accepted 17 july 2019 abstract this research integrates the taguchi method, analysis of variables (anova), back-propagation neural networks (bpnn), and hybrid pso-ga to develop an intelligent optimization system of micro electroforming process for the mesh filter. from the outset of discussions with engineers in terms of past related literature survey of the micro electroforming process, the quality characteristics of product and control variables can be well ascertained, then transforming the problem of multiple quality characteristics into a single quality characteristic via the taguchi method and anova. however, the optimal parameter settings (solution) through the taguchi experimental planning is still belong to a discrete optimal solution which is impossible to meet the process stability and quality goals. therefore, this study first identifies the initial weight of bpnn，using hybrid pso-ga with multilayer perceptron (mlp)，in order to improve training efficiency and precision of bpnn. furthermore, the study constructs the signal-to-noise (s/n) ratios (bpnns/n) and quality predictors (bpnnq) based on hybrid pso-ga and bpnn with the experimental data. the optimal parameter settings are obtained through a combination of bpnns/n and bpnnq with modified pso-ga. finally, confirmation experiments are performed to assess the effectiveness of the proposed system. the results show that the proposed system can create the best performance, and the optimal parameters not only enhance the stability in the micro electro forming process but also effectively improve the product quality. keywords: taguchi method, bpnn, pso-ga, micro electroforming, mlp 1. introduction recently the technology of micro electroforming process has been widely used, and the mesh process can be mainly divided into the photolithography process and the micro electroforming process, having been widely used recently. and the process parameter control directly affects product quality and cost. the photolithography process consists of three main components: coating photoresist, exposure, and development. in order to obtain higher resolution, some baking and cooling steps are also adopted in the photolithography process. in the current technology, of photolithography process, entirely seven steps are required in the process: cleaning the substrate, pre-baking, coating the photoresist, soft-baking, exposure, development, and hard-baking. when the photolithography process parameters are not well controlled, defects such as the * corresponding author. e-mail address: wenchin@chu.edu.tw tel.: +886-3-5186585; fax: +886-3-5186575 advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 212 excessive image size variation, poor transfer rate, and even transfer failure may occur; therefore, the photoresist must be stripped and the previous process repeated until the inspection is completed. then, the semi-finished mold core formed by photolithography is subjected to a micro-electroforming process. the micro electroforming process consists of five main components: electroforming, photoresist stripping, finished stripping, cleaning and hard baking. as to the current technology of electrochemical micro-electroforming process for making molds, when the process parameters are not well controlled, problems such as the product forming failure and excessive size variation will be directly caused and hence the loss due to the fact that the product will not pass the quality inspection and cannot be reworked. therefore, to improve yield and reduce cost, the parameter setting of the micro electroforming process control factors are even more important. since the micro electroforming process can be applied to a variety of materials, and there are many types and formulations of chemical electroforming fluids, many scholars are devoted to studying the interaction between various chemical electroforming fluids and materials and the related physical phenomena in the process [1-8]. however, through the analysis of the materials, a suitable combination of electroforming liquid and materials, a better process and product quality, and the better process parameters combination all can be obtained. if an inappropriate combination of process parameters is used, it can lead to product defects and excessive process variations. in the past, some scholars adopted the taguchi experimental design method to explore the correlation between process parameters and quality [9-11].however, the taguchi experimental design is a discrete method for solving single quality characteristics, and only the local optimal solution of the pre-selected parameter level can be obtained specific to a single quality characteristic, but not the global continuous optimal solution. therefore, it is necessary to combine the experimental design, smart predictors and applications of related theories for optimization to search for the best combination of process parameters by numerical simulation and prediction[12-14].the above studies only focused on optimizing the process parameters for product quality characteristics, but they did not assess the stability of the process in the micro electroforming process. therefore, this study proposes an intelligent optimization system to find optimal process parameters of multiple quality characteristics in the micro electroforming process. firstly, the taguchi method is used to determine the best combination of parameter settings by calculating the signal-to-noise (s/n) ratio from the experimental data. the highest s/n ratio value is employed to decide the best settings for quality responses. significant factors are determined through analysis of variance (anova). the s/n ratio predictor (bpnnsn) and quality predictor (bpnnq) are constructed by bpnn. in the first stage optimization, bpnns/n is coupled with ga in order to minimize the variations of the process. in the second stage optimization, the optimal parameter settings are obtained via a combination of bpnns/n, bpnnq and hybrid ga-pso. finally, two confirmation experiments are conducted to assess the effectiveness of the proposed intelligent optimization system. this study focuses on not only the optimal process parameters to improve the multiple qualities, but also the stability of the process to enhance the productivity. the research has been motivated by the current development of ai, big data, internet of things (iot) and cloud computing worldwide in general, which especially play their important roles in the future industrial automation systems. 2. research methodologies in this study, an intelligent optimization system is proposed for the micro electroforming process of the mesh filter. the research integrates the taguchi method, anova, bpnn, the improved hybrid pso-ga, statistical process control and other related technologies to obtain the optimization for multi-objective micro-electroforming process. and it has enabled product quality to be maintained within acceptable quality ranges and made the micro electroforming process more stable. firstly, based on the literature reviews and discussions with engineers on the influence of process parameters to their quality characteristics, the control parameters and level are selected for the taguchi orthogonal table experiment. then the electroforming experiment is proceeded in the customized electroforming tank for the research. the micro electroforming workpiece is the mesh filter. in order to ensure that the product can be supplied to the manufacturer's required size advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 213 specifications, a discussion with the manufacturer is proceeded, obtaining a product diameter of 555±3μm and a deviation of quantity specification within 5% of the product thickness. therefore, the quality characteristics are set to the diameter roundness and thickness uniformity. after literature reviews and discussions with a number of experts and engineers, the control factors selected for the experiments are the temperature of the electroforming liquid, current density, cathode size, the distance between the anode and the cathode, and oscillating rate. to acquire more accurate data, the study has to consider the lesser number of experimental control factors and standards, so the taguchi l18 (2 1 x 3 4 ) orthogonal table is used for the experiment, in which the temperature of the casting liquid is set at two levels and the remaining control factors are set at three levels. however, the taguchi experimental design is a discrete method for solving single quality characteristics, and only the local optimal solution of the pre-selected parameter level can be obtained specific to a single quality characteristic, but not the global continuous optimal solution. in addition, since the combination of process parameters obtained from the taguchi experimental planning cannot meet both the stability of the micro electroforming process and the best quality of the product, a two-stage optimization must be carried out. the first stage is to obtain the measurement data of the diameter and thickness of the mesh filter by experiments. next, for the taguchi data analysis, the problem of multi-objective quality characteristics needs to be transformed into a single quality characteristic, so that the based-on data can be further analyzed accordingly. the data analysis includes factor response graph analysis and variance analysis, and the relationships between the s/n ratios and the quality characteristics of the experimental control factors can be known. using the s/n ratio factor reaction map, we can find important control factors that have a significant impact on the quality characteristics and classify the control factors to optimize the two steps of the taguchi process. firstly, the step uses the first type factor to modulate the s/n ratios to the maximum value for the purpose of reducing the process variation. secondly, the step adjusts the second type of factor level to approximate the average value of the quality characteristic to the target value. finally, the third type of factor is used to reduce production costs. based on the steps, a set of optimal process parameters of taguchi can be obtained, which can be used as the initial value of the optimization of the second stage. through the factor response analysis and the analysis of the variance, the significant control factors found will be adjusted as the basis of the subsequent solution parameters. in the second stage, the parameter combination obtained by the taguchi experimental planning is used as the basis to establish the s/n ratio predictor (bpnns/n) and quality predictor (bpnnq). however, the initial weight value of the bpnn is often generated in a random manner, and the initial weight value affects the network training speed and prediction accuracy; therefore, this study uses the improved hybrid pso-ga combined with multilayer perceptron (mlp) to obtain and preserve the initial weight required for bpnn. this method not only improves the training speed of bpnn, but also increase the predictive power of it. in this stage, the process parameter combination obtained in the first stage is used as the initial value, and the s/n ratio predictor and the quality predictor are combined with the hybrid pso-ga for global search to find the process parameters that best meet the quality specifications and the most stable quality. the mesh microstructure diameter size target is 555 μm, and the acceptable thickness deviation is within 5%. for the diameter roundness, the measurement method is divided into twenty areas, as shown in fig. 1. the measurement of five points in each area is averaged, thus the measurement can better determine the exact roundness of diameter. formula for roundness is as shown in eq. 1.for the thickness uniformity, the measurement method is divided into 20 points for the inner and outer regions, as shown in fig. 2, taking the percentage of thickness deviation inside and outside. 20 5 1 1 1 d d 20 5 ij i j      (1) dij is the measured value of the mesh microstructure diameter; d is the diameter roundness of the mesh quality characteristics; measuring area has 20 measuring points in five zones; and j is the number of measuring points. the main advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 214 purpose of this study is to find out the optimal process parameter combination of the micro electroformed mesh, so that its quality is within the desired range, and the product tends to stabilize and reduces the non-performing rate. the thickness uniformity is shown as eq. 2. t = 1 𝑇𝑀𝑎𝑥 − 𝑇𝑀𝑖𝑛 ∙ 1 4 × 5 × ∑ |∑ 𝑇𝑂𝑖𝑗 − ∑ 𝑇𝐼𝑖𝑗 5 𝑘=1 5 𝑗=1 | 4 𝑖=1 (2) t is the thickness uniformity of the mesh quality characteristics as shown in equation 2. the maximum thickness measurement value is 𝑇𝑀𝑎𝑥 =max (𝑇𝑂𝑖𝑗 , 𝑇𝐼𝑖𝑗 ); the minimum value is 𝑇𝑀𝑖𝑛 =min ( 𝑇𝑂𝑖𝑗 , 𝑇𝐼𝑖𝑗 ); 𝑇𝑂𝑖𝑗 is the thickness measurement of the outer ring; 𝑇𝐼𝑖𝑗 is the thickness measurement of the inner ring; i is the measuring area; and j is the number of measurement points. fig. 1 schematic diagram of mesh diameter measurement fig. 2 schematic diagram of mesh thickness 3. results and discussion 3.1. taguchi experiment in this study, the micro electroforming product is the mesh filter. in order to ensure that the product can be supplied to the manufacturer's required size specifications, a discussion with the manufacturer is proceeded, obtaining a product diameter of 555±3μm and a deviation of quantity specification within 5% of the product thickness. the quality characteristics are diameter roundness and thickness deviation. in addition, the experimental control factors are defined as following five experimental control factors: temperature of the electroforming liquid (tl) (℃), current density (cd) (a/ dm 2 ), cathode size (cs) (dm 2 ), the distance between the anode and the cathode (dac) (cm), and oscillating rate (or) (rate/min). the range of adjustment parameters and the control factor level settings are shown in table 1. the five experimental control factors in this study uses l18(2 1 x 3 4 ) orthogonal table. as shown in table 2, the micro electroforming is performed on a customized experimental machine, and the data of the diameter roundness and the thickness deviation are obtained by measurement, and the s/n ratios are calculated. the diameter roundness adopts the first type formula of the eyesight characteristic, and the thickness deviation adopts the small characteristic formula. 18 groups from no.1 to no.18 are the taguchi experimental data; 5 groups from no. 19 to no. 23 are randomly generated. for the quality characteristic of diameter, the equation of type i formula of the nominal-the-best is used as shown in eq. 3. as for a deviation of quantity specification within 5% of the product thickness, the smaller-the-better is used as shown in eq. 4. the experimental product is shown in fig. 3. ])log[(10 )( log10/ 221 2 smy n my ns n i i      (3) )log(10log10/ 221 2 sy n y ns n i i    (4) where yi is the response value of a specific treatment under i replications, n is the number of replications, y is the average of all yi values, and sis the standard deviation of all yi values. advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 215 table 1 showing different crystal growth methods, growth time and approximate sizes of the grown crystal experimental control factors range level 1 level 2 level 3 tl 40-50 40 50 cd 1-5 1.00 3.00 5.00 cs 1-4 1.00 2.25 4.00 dac 9-12 9.0 10.5 12.0 or 20-52 20 36 52 table 2 the results of the diameter and thickness deviation of the taguchi experiment no average diameter (x) (μm) thickness deviation (y) (%) σ(x) σ(y) s/n ratiofor x s/n ratio for y 1 554.310 0.0237 0.1114 0.0018 3.1114 32.4771 2 554.447 0.0303 0.2542 0.0017 4.3085 30.3453 3 555.780 0.0271 0.1100 0.0020 2.0726 31.3317 4 554.330 0.0139 0.2128 0.0016 3.0610 37.0848 5 554.837 0.0315 0.1332 0.0015 13.5251 30.0174 6 555.117 0.0295 0.0907 0.0020 16.6066 30.5767 7 553.903 0.0106 0.1570 0.0022 -0.8895 39.2921 8 555.467 0.0326 0.1986 0.0025 5.8971 29.7218 9 555.347 0.0292 0.1986 0.0019 7.9694 30.6632 10 554.257 0.0171 0.2194 0.0012 2.2136 35.3380 11 554.690 0.0308 0.3568 0.0019 6.5092 30.2133 12 555.700 0.0303 0.0954 0.0024 3.0181 30.3316 13 554.380 0.0081 0.1153 0.0018 4.0044 41.6647 14 554.807 0.0391 0.1069 0.0012 13.1148 28.1516 15 555.067 0.0303 0.1097 0.0024 17.8310 30.3329 16 553.923 0.0072 0.1222 0.0014 -0.6972 42.6330 17 554.577 0.0321 0.1914 0.0023 6.6586 29.8436 18 554.833 0.0367 0.2775 0.0024 9.7959 28.6889 19* 554.767 0.0282 0.1168 0.0016 11.6699 30.9735 20* 555.550 0.0219 0.2117 0.0012 4.5930 33.1608 21* 555.107 0.0408 0.1570 0.0020 14.4356 27.7712 22* 554.740 0.0359 0.1153 0.0024 10.9205 28.8752 23* 553.997 0.0074 0.2084 0.0019 -0.2124 42.3435 fig. 3 the experimental product 3.2. variation of ph value in the water storage tank this study aims to find an optimal combination of process parameters that meet the multi-objective quality. however, taguchi’s experimental design belongs to a single quality response and discrete optimization method, and only can derive local advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 216 optimal solution of pre-selected parameter level value for a single quality characteristic. therefore, it is necessary to first transform and integrate the problem of multiple quality objectives of diameter and thickness deviation into a problem of single quality objective, and then to conduct subsequent data analysis based on the experimental data. data analysis includes factor response analysis and anova in order to understand the relationships between experimental control factor pairs of s/n ratio and quality characteristics. s/n ratio response chart can identify important control factors with more significant effects on s/n ratios, while the use of quality characteristics response chart can screen control factors with more significant effects on quality characteristics. the taguchi optimization process parameter combination can be used as the initial value for subsequent optimization, while the significant control factors found by factor response analysis and anova are chosen as the basis for adjusting the process parameters for subsequent optimization. the method is to integrate the individual offsets of the quality characteristics of the diameter and thickness deviation into a total offset to achieve a single target quality. the calculation of the integrated diameter and thickness deviation into a single target quality is as follows [15]: (1) the calculation of the total offset taking the taguchi experimental product as an example, the diameter size of the experimental product is measured as x, and the target value of the quality characteristic is 555μm, so the diameter offset is x-555μm; the thickness deviation measurement is y, and the target value of the quality characteristic is 0%, so the measured value is the thickness deviation offset. thus, the same measurement unit (x-555) and y are assumed to be two vectors, so the vector sum z is its total offset. the calculation is as follows: total offset z = ((x 555) 2 +y 2 ) 1/2 (5) (2) the calculation of the total standard deviation in the taguchi experiment, if the standard deviation of a certain group of diameter is σ(x), and the standard deviation of thickness is σ(y), then the total standard deviation σ(x+y) is as follows 2 2 (x y) (x) (y) 2 cov(x,y)       (6) (3) conduct factors response analysis via anova and main effects plot the s/n ratio response factor table of integrating into a single quality and the main effects plot for s/n ratios of total bias are demonstrated in the study. the factor response chart shows that a set of taguchi optimal process parameter combination can be obtained to meet the multiple quality characteristics. this study will denote the minimum process variation and optimal quality characteristic, and the optimal parameter combination of taguchi experiment and anova. table 3 anova of the total offset quality characteristics df seq ss adj ss adj ms f p contribution significant tl 1 0.00999 0.00999 0.00999 0.34 0.578 0.64% no cd 2 0.39617 0.39617 0.19808 6.67 0.020 25.40% yes cs 2 0.78652 0.78652 0.39326 13.24 0.003 50.42% yes dac 2 0.07188 0.07188 0.03594 1.21 0.347 4.61% no or 2 0.05761 0.05761 0.02880 0.97 0.420 3.69% no error 8 0.23764 0.23764 0.02971 15.24% total 17 1.55980 s = 0.172352, r-sq = 84.76%, r-sq(adj) = 67.62% this integrated diameter and thickness deviation offset becomes the total offset, which is a quality characteristic of single target quality. since the smaller the value is, the better the result will be, the s/n ratio chooses the smaller-the-better formula. for the anova of the total offset of quality characteristics, the significant influence factors are selected according to the advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 217 contribution. first, the two control factors of cathode size (50.42%) and current density (25.40%) are spotted, as shown in table 3. the above two control factors have a significant influence on the quality characteristics and can provide the basis for subsequent optimization of the adjustment process parameters. the optimal parameter combination of the taguchi method is shown in table 4. table 4 optimal parameter combination optimal parameter tl cd cs dac or 50 3.00 4.00 9 20 3.3. using mlp combined with hybrid pso-ga to find the initial weight of bpnn as a consequence of using the taguchi experimental analysis, the optimal combination of parameters obtained is the discrete parameter combination established by the original taguchi experimental design, and the quality may not reach the target value. therefore, the research uses the backpropagation neural network (bpnn) to construct the s/n ratio predictor and quality predictor, combining the improved hybrid pso-ga optimized in this study. moreover, in terms of the taguchi experimental analysis, the optimized combination of parameters is used as the initial value of the algorithm search. furthermore, it is hoped to find a set of continuous type of best combination of parameters that can achieve process stability and quality objectives. however, when the traditional bpnn is in sample training, the initial weight is often generated randomly, and it will affect the training speed and accuracy of the neural network. therefore, this study proposes to use the improved pso-ga combined with mlp to solve the initial weight value of bpnn and to find a better set of adaptation as the initial weight value of bpnn. the study uses bpnn to build the s/n ratio predictor and quality predictor, using the improved pso-ga combined with mlp to find the better initial weight for the s/n ratio predictor and quality predictor respectively.the objective function is defined in eq. 7. min 𝑓(w) = 1 36 ∑ ∑(𝑑𝑘 𝑝 − 𝑦𝑘 𝑝 (w))2 2 𝑘=1 18 𝑝=1 (7) where p represents number of pth sample, k represents kth quality characteristic, 𝑑𝑘 𝑝 represents the target value of bpnn indexed by k , 𝑦𝑘 𝑝 (𝑊) represents the output value of mlp indexed by k, w is mlp’s weights. through using mlp and eq. 7 with the modified pso-ga to solve optimization weights, better weight values can often be found. 3.4. establishing s/n ratio predictor and quality predictor the study uses bpnn to establish the s/n ratio predictor and quality predictor. the input values of the s/n ratio predictor and quality predictor are the normalized values of the 18 groups of parameters of the taguchi experiment, and the output value of the predictor is the normalized value of the s/n ratio and the average value of the quality characteristics in the taguchi experiment. in addition, the 19th to 23rd groups in the taguchi experiment are used as the testing data of bpnn. in order to enable bpnn to training convergence, this study adopts the weighting solution of mlp-pso-ga, stated in the previous section, as the initial value of bpnn for training. the s/n ratio predictor training uses 1053 generations, training rmse to be 0.0004940, and testing rmse to be 0.0259. the quality predictor takes 968 generations; the training rmse is 0.00082261, and the test rmse is 0.0253. the error of the predicted value of the two predictors is analyzed within the acceptable range by comparing the error between the predictors and the actual values. 3.5. two-stage process parameter optimization in the first stage, the experiment focuses on maximizing the s/n ratio. the constructed s/n ratio predictors are combined with a ga to identify the process parameter combination with the minimum variance and the most robust process so that the s/n ratio values of diameter roundness (mm) and thickness deviation must be maximized. the taguchi optimal parameter advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 218 combination is used as the initial value to carry out the full range global search for the six control factors. the fitness function of ga is presented as follows: max snod, snot s.t. 40≤ x1 ≤ 50, 1≤ x2 ≤ 5, 1≤ x3 ≤ 4, 9≤ x4 ≤ 12, 20≤ x5 ≤ 52, (8) where x(x1, x2, x3, x4, x5) is the process parameter(control factor), snod is the s/n ratio of diameter predicted by de-normalized bpnns/n, and snot is the s/n ratio of thickness deviation predicted by de-normalized bpnns/n. five control factors are temperature of the electroforming liquid (x1), current density (x2), cathode size (x3), the distance between the anode and the cathode (x4), and oscillating rate (x5). this numerical analysis is to conduct the global search for all control factors and obtained the process parameter combination of the first stage multi-objective s/n ratio maximization. the optimal parameter combinations are: x1=49.582, x2=2.152, x3=3.545, x4=9.004, and x5=51.912. min f2 (x) = (yod－555) 2 max snod, snot s.t. yot ≤ 0.01 8≤ x2 ≤ 28, 62≤ x3 ≤ 78 (9) where x(x2,x3)is the process parameter (control factor), yod is the output value of diameter quality predictor after de-normalization, and yot is the output value of thickness deviation quality predictor after de-normalization, and 555 is the target value of diameter quality characteristic, and 0.01 is the target value of thickness deviation quality characteristic as smaller as possible. the main control factors are x2is current density and x3 is cathode size. by conducting a global search for the two significant control factors of the second stage, and combining bpnns/n and bpnnq with modified pso-ga, this study can obtain the process parameter combination meeting the multi-objective quality and minimizing variation. the optimal process parameter combination is shown in table 5. table 5 optimal parameter combination (two-stage process) optimal parameter tl cd cs dac or 49.582 2.002 3.85 9.004 51.912 3.6 confirmation of experiment and discussion due to the accuracy set by the operating machine, the optimized parameter values must be rounded up according to the limits set by the machine. the finally confirmed experimental parameters are shown in table 6. the experimental data will be confirmed according to the above-mentioned quality evaluation methods, and the comprehensive evaluation and comparison tables of the quality of the diameter and thickness will be separately compiled, as shown in table 7 and table 8. the product quality characteristics and ideal functions of this study are based on the manufacturer's requirements for product quality. the diameter roundness specification is 555 ±0.3 μm (target value: 555 μm, tolerance: ±3 μm), and the thickness deviation specification is 5% and expectedly smaller. (target value: 0μm). additionally, for the diameter quality characteristics, the multi-quality optimized cpk value is 1.69, which is much larger than the 0.70 of the taguchi method, and the average diameter value is also the closest to the target value. the standard deviation of 0.058 is also lower than 0.132 of the taguchi method. it is found that the two-stage optimization is better. moreover, for the thickness quality characteristics, after the two-stage optimization, the thickness deviation is reduced from the taguchi method, 0.0281, to 0.0191; the standard deviation is also reduced from 0.0075 of the taguchi method to 0.0036. it can be seen that after the two-stage optimization, not only the diameter is closer to the target value, but also the thickness deviation is reduced, and the process is more stable. the results show that the two-stage optimization is better in the comprehensive evaluation of each quality. advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 219 table 6 optimal parameters and machine settings tl cd cs dac or taguchi + anova 50 3.00 4.00 9 20 machine settings 50 3.00 4.00 9 20 two-stage optimization 49.582 2.002 3.850 9.004 51.912 machine settings 50 2.00 4.00 9 52 table 7 a comprehensively evaluation & comparison table of diameter quality cpk average standard deviation taguchi + anova 0.70 554.980 0.132 two-stage optimization 1.69 555.004 0.058 table 8 a comprehensively evaluation & comparison table of thickness quality average standard deviation taguchi + anova 0.0281 0.0075 two-stage optimization 0.0191 0.0036 3.7. process parameters and quality characteristics analysis fig. 4 the effect of current density and cathode size on diameter s/n ratio this section discusses the relationship between process parameters and quality characteristics. the process parameter control factors of this experiment are the temperature, current density, cathode size, distance between cathode and anode, and oscillating rate. according to previous investigation, the current density and cathode size are the most significant factors for the process parameters in this research; therefore, this study uses those factors as variation factors for more in-depth analysis. the cathode size, the cathode-anode distance, and the oscillating rate are fixed according to the optimum parameters of the taguchi experimental analysis, and their values are 50° c, 9 cm and 20 times / min respectively. when the s/n ratio predictor and the quality predictor are used as the variation factors for the predicted current density and the cathode size, the output of the predictor is shown in figs. 4 to 7. as what is shown from figures 4 and 5, for the diameter roundness s/n ratio, the smaller the value of the current density and the larger the value of the cathode size are, the greater the influence on the s/n ratio is. therefore, if it is desired that the diameter roundness s/n ratio can achieve better results, the current density and cathode size parameters are respectively lowered and increased to perform better. for the thickness deviation s/n ratio, the smaller the current density and the larger the cathode size are, the greater the influence on the thickness s/n ratio is. it is clearly observed that the current density interacts with the cathode size. therefore, if a thickness s/n ratio is desired to obtain a better result, the adjustment of the current density should be considered, followed by the cathode size. in addition, as seen from fig. 6 and fig. 7, if the value of the current density is lower and the value of the cathode is higher, the influence on the diameter roundness and thickness deviation is more obvious. thus, if the product process requires a larger size, the parameters with lower current density adjustment and higher cathode size adjustment can obtain better results. the diameter quality characteristic required for this experiment in this research is 555μm; and the thickness quality characteristic is the smaller the better. according to the advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 220 trend graph of the diameter quality predictor, the drop point is between the current density of 1~2 a/dm 2 and the cathode size is about 3~4 dm 2 , and according to the trend graph of the thickness quality predictor, the drop point is about between 1~3 a/dm 2 (current density) and 3.5~4 dm 2 (cathode size). therefore, in this study, the optimal parameters of the s/n ratio predictor and the quality predictor are obtained by the hybrid pso-ga. the best parameters are current density 2.00 a/dm 2 and cathode size 4 dm 2 . fig. 5 the effect of current density and cathode size on thickness s/n ratio fig. 6 the effect of current density and cathode size on the diameter fig. 7 the effect of current density and cathode size on thickness 4. conclusions the micro electroforming technology has been widely adopted, and the industry has higher and more requirements for the product precision. how to set appropriate process parameters to meet the quality requirements and improve the production efficiency and process stability often bothers the engineers. therefore, if the optimal process parameters can be found, it will improve product quality and reduce costs. to this end, this research studies the intelligent optimization system of the micro electroforming process parameters for the mesh filter, using the systematic optimization method to effectively find the optimal combination of process parameters. after the actual verification, for the diameter quality characteristics, the multi-quality optimized cpk value is 1.69, which is much larger than the 0.70 of the taguchi method, and the average diameter value is also the closest to the target value. the standard deviation of 0.058 is also lower than 0.132 of the taguchi method. for the thickness quality characteristics, the thickness deviation is reduced from the taguchi method, 0.0281, to 0.0191; the standard advances in technology innovation, vol. 4, no. 4, 2019, pp. 211-221 221 deviation is also reduced from 0.0075 of the taguchi method to 0.0036. therefore, accordingly, the results suggest that t he proposed intelligent optimization system not only makes the diameter closer to the target value but also reduces the thickness deviation and makes the process more stable. conflicts of interest the authors would like to thank material and chemical research laboratories of industrial technology research institute (itri) in taiwan for providing equipment and technical support. references [1] m. kim, j. y. lee, s. c. kwon, d. kim, i. g. kim, and y. choi, “application of small angle neutron scattering to analyze precision nickel mesh for electro-magnetic interference shielding formed by continuous electroforming technique,” physica b: condensed matter, vol. 385-386, no. 2, pp. 914-916, november 2006. 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[15] l. v. candioti, m. m. de zan, m. s. camara, and h. c. goicoechea, “experimental design and multiple response optimization using the desirability function in analytical methods development,” talanta, vol. 124, pp. 123-138, june 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 application-based online traffic classification with deep learning models on sdn networks lin-huang chang 1,* , tsung-han lee 1 , hung-chi chu 2 , cheng-wei su 1 1 department of computer science, national taichung university of education, taichung, taiwan 2 department of information and communication engineering, chaoyang university of technology, taiwan received 19 december 2019; received in revised form 10 march 2020; accepted 03 july 2020 doi: https://doi.org/10.46604/aiti.2020.4286 abstract the traffic classification based on the network applications is one important issue for network management. in this paper, we propose an application-based online and offline traffic classification, based on deep learning mechanisms, over software-defined network (sdn) testbed. the designed deep learning model, resigned in the sdn controller, consists of multilayer perceptron (mlp), convolutional neural network (cnn), and stacked auto-encoder (sae), in the sdn testbed. we employ an open network traffic dataset with seven most popular applications as the deep learning training and testing datasets. by using the tcpreplay tool, the dataset traffic samples are re-produced and analyzed in our sdn testbed to emulate the online traffic service. the performance analyses, in terms of accuracy, precision, recall, and f1 indicators, are conducted and compared with three deep learning models. keywords: software defined network, network traffic classification, deep learning, tensorflow 1. introduction artificial intelligence (ai) has been one of the hottest topics currently. machine learning (ml), which is a subset of ai and adjusts itself in response to the data it is exposed to, will enable the machines to improve at the task with experience. among different machine learning schemes, shallow neural networks, such as backpropagation neural network, bayesian network, support vector machine (svm), and c4.5 decision tree, are commonly used to build traffic classifiers for network services in many machine learning-based classification schemes. due to the continuous expansion of network and considerable deployment of the internet of things (iots), great amount of data and information have been collected and consequently promoted the arrival of the big data era. furthermore, with the significant promotion in processing speed of computing hardware such as graphics processing unit (gpu) and tensor processing unit (tpu), the deep learning (dl) using deep neural networks, which provide higher classification accuracy than the shallow neural networks, have been the major focus on ml. the promising ml techniques, such as deep neural networks provides a good opportunity and key to the data-driven machine learning algorithms in the network field. on the other hand, more and more application services have emerged over the internet. the network management issues, including quality of service (qos) setting, network policy, network security as well as intrusion detection, majorly depend on the accuracy of network traffic classification for applications. the emerged applications or services may not be identified by * corresponding author. e-mail address: lchang@mail.ntcu.edu.tw tel.: +886-4-22183812; fax: +886-4-22183580 advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 217 the traditional schemes, such as simply checking source/destination ip addresses in the network layer or source/destination port numbers as well as protocols in the transport layer, because they might pass through different network address translation (nat) or virtual private network (vpn), or they may not utilize the standard port numbers or fields. therefore, to provide proper qos for a specific application, it might need to manually verify or identify the network application packets. these processes will significantly reduce the efficiency of network traffic processing and consequently increase the overall delay and processing loading. furthermore, the development of software defined network (sdn) has made network management more effective and efficient [1-2]. unlike traditional networks, sdn separates the network layer into a data plane and a control plane which could be a logical control unit and programmable. the flexibility and programmability of the sdn architecture design make the network routing and management easier and more efficient, especially for the design and handling of network classification which enables the optimal network solutions, such as configuration and resource allocation. the centralized sdn controller is able to collect various real-time network data due to its global network view. the ai techniques can then be applied to the sdn networks by employing network optimization and data analysis based on the real-time and historical sdn network data. therefore in this paper, we propose an application-based online and offline traffic classification with deep learning models on sdn networks. we design the deep learning models resigned in the sdn controller. the sdn controller establishes the match fields of the flow entry and sends them to the open virtual switch (ovs). it also extracts traffic statistics data from the ovs switch. the server ip addresses and transport port numbers of each flow plus the statistics data are designed to be the input features for the deep learning models. the remaining sections of this paper are organized as follows. we describe the protocols, standards, tools, and related research reviews in section 2. section 3 addresses the experimental settings and model design. in section 4, we present the experimental result and performance analysis in this paper followed by the conclusion and future works in section 5. 2. related work we first review some protocols, standards as well as related tools used in this paper. we also survey some literature related to this research. the following subsections will address the brief discussion of each subject. 2.1. deep learning review dl [3], rather than a task-specific algorithm in the ml series, is a broader representation of learning data. the dl aspect includes supervised, semi-supervised, or unsupervised learning. dl can be applied for classification, clustering, and regression. with classification, dl is able to learn the correlation between data and labels, which is known as supervised learning. for some applications, it is not required or unable to know the labels of the data in advance. learning without labels is called unsupervised learning. with clustering, dl does not require labels to detect similarities among groups of data. with regression, the dl is exposed to enough of the right data. it is able to establish correlations between present events and future events. this predictive analytics is different from the classification which might be called a static prediction. given a time series, dl can run regression by reading lots of data from the past and predict some data likely to occur in the future. dl architectures, including convolutional neural network (cnn), deep neural networks (dnns) and recurrent neural network (rnn), multilayer perceptron (mlp), long short-term memory (lstm), and stacked auto-encoder (sae), have been applied to different fields such as computer vision, audio recognition and natural language processing, etc. some of dl models or implementations have achieved comparable or even superior results as compared to human experts. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 218 in this paper, we apply the tensorflow [4] neural network modules as the dl platform for our application-based online traffic classification. the major programming language and development of tensorflow is python. tensorflow supports application programming interfaces (apis) such as keras [5], with the advantage of easy operation, modular design, and flexible scalability, as the high-level development interface. keras, working in conjunction with the back-end tensorflow engine, provides functional apis for building models, training models, evaluating models, as well as predicting results. 2.2. openflow protocol openflow [6] is one of the most dominated sdn communication protocols. by using the software programming, openflow supports the control and communication of the rules signaling and flows forwarding from the centralized controller southbound to the sdn switch. the northbound apis from the control plan to the management plan, on the other hand, is defined to be used for application service and operation management. several consoles, such as ryu [7], floodlight, and opendaylight, have been developed to support openflow. we apply the ryu controller which supports openflow up to versions 1.5 to define the framework of the sdn networks in this research. ryu, being a component-based sdn framework, provides software components with well-defined api, which is easy for developers to create new control applications and network management. it also supports various communication protocols for network devices management, such as openflow and of-config. 2.3. tcpreplay tools tcpreplay [8], an open-source utility, is used to edit and replay captured network packets. it has been used primarily to replay malicious traffic patterns for network intrusion detection. we apply tcpreplay to replay the network traffics of the real-world dataset and inject them into the sdn network environment in this research. 2.4. iscx dataset the iscx [9] dataset, collected by the canadian cyber security institute, is a network traffic dataset used by many universities, companies, and independent researchers around the world. in this paper, we apply the iscx dataset as our training dataset and offline testing dataset. 2.5. survey on ai applied to sdn and related review the flexibility and programmability of the sdn network make the traffic classification, routing optimization, qos/qoe prediction, resource management, and security easier and more efficient. with the advantage of the sdn global network view, the centralized sdn controller is able to collect various real-time and historical network data from the sdn switches at per port and per-flow granularity levels and consequently, we can apply the ai techniques on the sdn networks by employing network optimization and data analysis. we will provide a brief survey of ai or ml techniques applied to the sdn network, including traffic classification, routing optimization, qos/qoe prediction, and security [10]. first, traffic classification techniques in sdn networks include a port-based approach, deep packet inspection (dpi), and ai or ml [11-12]. the port-based approach will not be effective when most applications recently utilize dynamic ports as tcp or udp port numbers. the dpi approach results in high computational cost or difficult pattern update because all traffic flows need to be checked or updated for the exponential growth of applications. currently, more and more encrypted packets of various applications make the dpi approach even impractical. ai or ml techniques are applied to extract knowledge from the traffic flows in sdn, thus ai or ml-based approaches are able to classify encrypted packets correctly with the lower computational cost. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 219 deep learning models have been applied to network traffic classification currently. the research in [13] introduced a sae-based scheme to classify unencrypted data flows. however, their scheme was only applied to unencrypted traffic and could not be deployed to the encrypted data. besides, the dataset used in their research was not open to the public. the research in [14] proposed a scheme to identify encrypted traffic based on sae and cnn models. the research in [15] proposed three deep learning based models, including mlp, sae, and cnn for traffic classification. they developed their models based on all encrypted streaming packets from the open source dataset. however, their research, including training and prediction models, could not be applied to the real network traffic or emulated online flows because they only conducted the offline dataset analysis. secondly, the routing optimization issues in sdn networks typically employ the shortest path first (spf) algorithm and heuristic algorithms [16]. the spf algorithm is a best-effort routing scheme. it is unable to utilize the best network resources due to the simplicity of the algorithm. the high computational cost however would be the shortcoming of heuristic algorithms [17], such as ant colony optimization algorithm. the introduction of ai or ml to the route optimization in sdn can be considered as a decision-making policy which does not need a complex mathematical model once the model has been trained. the reinforcement learning could be an effective mechanism which may provide a near-optimal routing decision quickly. thirdly, based on qos/qoe prediction, the sdn network operators or service providers are able to provide suitable services to the customers according to their expectations which consequently increase customer satisfaction and service. the authors in [18] have proposed a traditional m/m/1 network model and neural network model to train the model with traffic load and overlay routing policy and then to estimate the network delay. the authors in [19] have focused on the qoe prediction for video streaming service in the sdn network by correlating the qos parameters with the qoe values. they applied a supervised learning model to estimate the mean opinion score (mos) value according to the sdn network parameters, such as delay, jitter, and bandwidth, to adjust video parameters, such as bitrate and resolution, in the sdn controller and consequently improve the qoe of users’ experience. lastly, security is always an important issue in sdn network research and operation. intrusion detection system (ids) is an important mechanism and system for network security which in general consists of signature-based ids and anomaly-based ids according to how they identify network attacks [20]. because the signature-based ids has some shortcomings, such as signature update difficulty and high time consumption for all signatures comparison, most researches focus on the anomaly-based ids. the anomaly-based ids is a flow-based traffic identification which in general inspects the packet header information based on flow-granularity information, while the signature-based ids being a payload-based identification which needs to inspect the whole payload of packets. the supervised learning algorithms of ai or ml techniques are often applied in anomaly-based ids by training a predefined model to identify intrusions and normal flows. again, the global view and programmability of sdn networks will facilitate the ai or ml-based ids because of its simplicity and flexibility of data collection and attack reaction, respectively. with proper feature selection and feature extraction, many studies have been conducted for ai or ml-based ids in sdn networks. the authors in [21] employed the data preprocessing, decision-making subsystem, and response subsystem for their predictive data model as a threat-aware ids in sdn. they used a forward feature selection strategy to select appropriate feature sets in the data preprocessing subsystem, applied the decision tree and random forest algorithms to detect malicious flows in the predictive data modeling subsystem, and then employed the reactive routing to install different flow rules and types based on the detection results in the decision making and response subsystems. the authors in [22] used five flow features, including source/destination ip, source/destination port, and packet length, to predict malicious flows for their proposed hmm-based network ids. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 220 in this paper, we will mainly focus on the deep learning models applied to the traffic classification, especially application-based traffics, in the realm of sdn. the sdn switches send the traffic statistics and packet_in messages to the sdn controller for features extraction, which include server ip and port of each flow plus the statistics data. the sdn controller with deep learning models, including mlp, cnn, and sae models, will conduct the application-based traffic classification for each flow by establishing the match fields of the flow. 3. experimental settings and model design 3.1. experimental setting fig. 1 illustrates the network topology for our proposed sdn network testbed. as shown in fig. 1, we first apply the iscx dataset [9] to emulate the offline and online network traffic by injecting them into tcpreplay to reproduce the client/server communications in the sdn testbed. as mentioned earlier, the iscx dataset, including vpn and non-vpn datasets, was collected by the canadian institute for cybersecurity at the university of new brunswick. both vpn and non-vpn datasets consist of six application services, including skype, facebook, hangouts, youtube, and etc. internet router ova ryu controller tcpreplay host1 tcpreplay host2 fig. 1 network topology of the sdn testbed in this research, we deploy tp-link tl-wr1043nd as the open virtual switch (ovs) based on the openflow protocol for the sdn data plan. the ovs is implemented and installed using openwrt [23]. the ryu controller [7] is used in this paper to define the framework of the sdn networks. as defined by openflow standard, whenever a new coming packet does not match any flow entry in the flow table of ovs, the ovs switch will trigger the packet_in mechanism and send it to the ryu controller as routing setting request. for all packets in the same flow, only one packet_in message is sent to the controller for the same flow. in this research, besides the packet_in message for each flow, we also collect the flow statistics data. for the openflow statistics mechanism, the ovs sends the periodical statistics reports to the controller in response to the controller’s statistics request. the ovs statistics reported in 1sec interval, including flow statistics, table statistics, port statistics, queue statistics, group statistics, and meter statistics, could be used as the deep learning features for traffic flow behavior learning. the flow statistics data combined with the packet_in message will be the learning features of the deep learning models designed in the ryu controller for a specific flow. for each sdn flow, keeping the session connected, the ovs statistics report will be sent to the ryu controller continuously in 1sec interval. this will avoid the stochastic learning results due to inconstant or random statistics reports. because of the traffic flow characteristics of sdn networks, the processing data including packet_in message and statistics data in 1sec interval for deep learning in this research is less than the traditional traffic classification which processes data from all packets. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 221 3.2. data pre-processing in this paper, the dataset was collected in a precise and pre-defined amount and the experiments were conducted for three different deep learning models ten times. most input data are the features with a one-hot input scheme except two features, i.e. byte counts and packet counts, which will be discussed in more detail shortly. since deep learning is a mathematical operation of non-linear regression, it is necessary to limit the eigenvalues input to the classification model to a fixed range. therefore, the keys and values are stored in mapping mode using hash handles, and minmaxscaler in scikit-learn [24] to normalize the values and scale them to the range of 0 to 1. the minmaxscaler is shown in eq. (1), where xi represents the selected feature value, xnom represents the normalized value of one specific feature, and min(x) and max(x) are the minimum and maximum values of the feature, respectively. ( ) ( ) ( ) [0, 1] i x nom x x x min x max min     (1) table 1 shows the iscx dataset used in this experiment, which is injected into tcpreplay to emulate the offline and online network for the client/server communications in the sdn testbed. there are six applications, including facebook, gmail, hangouts, netflix, skype, and youtube, for each vpn and non-vpn dataset in the iscx dataset. for the skype application, the dataset was further divided into two classes, skypeaudio and skypevideo. table 1 dataset used in deep learning model labels applications training data amount validation data amount testing data amount facebookchat facebook 9981 1109 11091 gmailchat gmail hangoutchat hangout netflix netflix skypeaudio skype skypevideo youtube youtube table 2 examples of selected features and labels data # top1 top2 top3 top4 top5 top6 … top305 other byte count packet count labels 1 0 0 0 0 0 0 … 0 0 0.08 0.08 skypeaudio 2 1 0 0 0 0 0 … 0 0 5.87 0.16 skypeaudio 3 0 0 0 0 0 0 … 0 0 0.12 0.12 skypeaudio 4 1 0 0 0 0 0 … 0 0 7.57 0.14 skypeaudio 5 1 0 0 0 0 0 … 0 0 8.12 0.15 skypeaudio 6 0 0 0 0 0 0 … 0 0 0.06 0.06 netflix 7 1 0 0 0 0 0 … 0 0 152.17 0.9 skypevideo … … … … … … … … … … … … … 8 0 0 0 0 0 0 … 0 0 0.09 0.09 hangoutchat 9 0 0 0 0 0 0 … 0 0 0.21 0.1 hangoutchat 10 0 0 0 0 0 0 … 0 0 10.89 0.06 netflix 11 0 0 0 0 0 0 … 0 0 0.06 0.06 youtube 12 0 0 0 0 0 0 … 0 0 0.08 0.08 skypeaudio 13 0 0 0 0 0 0 … 0 0 1.53 6 gmailchat 14 0 0 0 1 0 0 … 0 0 1.36 9 gmailchat 15 0 0 0 0 0 0 … 0 0 0.06 1 netflix 16 0 0 0 0 0 0 … 0 0 2.54 7 facebookchat 17 0 1 0 0 0 0 … 0 0 0.5 1 gmailchat … … … … … … … … … … … … … advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 222 so, we will have seven labels for all deep learning models. the total amount of training dataset is 11090, with which 90% of them is used for the deep learning training process and 10% of them is used for the deep learning validation process. the total amount of testing dataset is 11091, which is also injected into tcpreplay and then replayed one by one to emulate the online traffic in the sdn network. because we emulate the real traffic by using the iscx open-source dataset, the dataset packets are handled as tcpreplay pcap packets. the packet_in messages due to the flow mismatch in ovs switch and the periodical statistics data responded from ovs switch to the controller are collected on the ryu controller. the server ip addresses and transport port numbers in each flow and the byte counts and packet counts collected from statistics data are selected as the deep learning features in our designed models. the server ip addresses and transport port numbers are handled using the one-hot input scheme. table 2 shows the examples of the selected features and labels in our designed application-based deep learning models. the top 305 most frequent server ip addresses and transport port numbers are selected as the one-hot input for deep learning models. the other column in one-hot input is used for any other ip or port number, not in the top 305 most frequent lists. 3.3. deep learning model design in this paper, we apply three deep learning models, including cnn, mlp, and sae models, for our application-based offline and online traffic classification. 3.3.1. mlp model input layer ae1 hiden ae1 output output layer 32 units ae1 input ... ... ... ... fig. 2 mlp deep learning in our model the first deep learning model we apply in this research is the multilayer perceptron (mlp) model. the designed mlp deep learning model, shown in fig. 2, employs back-propagating supervised learning techniques in artificial neural networks. it consists of an input layer, three hidden layers followed by a dropout layer, and an output layer. the input layer consists of 305 one-hot inputs representing the most frequent server ip addresses and transport port numbers plus one other column one-hot input representing the less frequent server ip addresses and port numbers from the packet_in headers. besides, two inputs are representing the byte counts and packet counts in every one-second periodical statistics data. each of the three hidden layers is composed of 256 neurons. the dropout layer is used to prevent the overfitting issue. the output layer consists of seven neurons, and the softmax function is applied as a classifier for the mlp deep learning model. 3.3.2. sae model in this research, we also apply the stacked autoencoder (sae) as one of the deep learning training models. the proposed sae architecture, containing one single encoding and decoding, is illustrated in fig. 3. the encoders of sae deep learning model, used for dimension reduction or feature extraction, contains 32 neurons in this paper. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 223 input layer ae1 hiden ae1 output output layer 32 units ae1 input ... ... ... ... fig. 3 sae deep learning in our model 3.3.3. cnn model the third deep learning model we apply in our deep learning training is the cnn model which is a typical deep learning model used for classification. the designed cnn model is specified in fig. 4 which consists of three convolution layers, three max-pooling layers as well as one fully connected layer with relu function acting as an activation function, followed by a dropout layer and an output layer. the convolution layer uses 64 filters to process input data. again, the dropout layer is used to handle the overfitting issues. input layer ... max1 poolconv1 layer max2 poolconv2 layer conv3 layer full connect 64 filter 64 filter 64 filter output layer max3 pool d r o p o u t r e lu 2 pool size 2 pool size 2 pool size ... ... ... ... ... ... fig. 4 cnn deep learning in our model 3.3.4. deep learning model training parameters the training dataset is divided in 9:1 ratio into training and verification processes for all three mlp, ase and cnn models in our deep learning training processes. the training parameters, such as epochs, batch size, learning rate, as well as optimizers, of our deep learning models are tabulated in table 3. table 3 deep learning model training parameters models epochs batch rate optimizers mlp 100 512 0.01 adam sae cnn 4. experimental result and analysis 4.1. offline training result in this paper, we first apply three deep learning models, including mlp, sae, and cnn models, for our application-based offline traffic classification. for the model training of offline deep learning processes, the training history for three different deep learning models is presented in fig. 5. the experimental results of the training history include the accuracy and loss advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 224 function evolution for both training and validation processes. the accuracy and loss rate within ten epochs of validation process for cnn deep learning model is about 94.95% and 20.26%, respectively. the cnn deep learning model shows fairly steady convergence within ten epochs. however, the loss function of validation process keeps almost unchanged after ten epochs and even goes little bit higher than that of training process. this could be due to the overfitting issue. it might need further optimization of the cnn parameters to reduce the overfitting issue. fig. 5 offline training results for three different deep learning models the accuracy and loss rate within ten epochs of validation process for mlp deep learning model is about 94.95% and 17.63%, respectively. there are some turbulences in training and validation processes after ten epochs. however, it achieves steady convergence after about 30 epochs. the accuracy and loss rate within ten epochs of the validation process for sae deep learning model is about 94.86% and 19.638%, respectively. unlike mlp model, the sae deep learning model shows fairly good convergence within five to ten epochs. this could be due to the fine-tuning training mechanism of the sae pre-training. however, more training epochs, less than 20 epochs, are enough for them to obtain similar error rates. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 225 table 4 offline training result for different models cnn-1d mlp sae training process accuracy 93.35% 93.21% 93.13% training loss rate 16.77% 16.40% 15.97% validation process accuracy 94.86% 94.59% 94.86% validation loss rate 19.64% 15.69% 19.64% the offline training results for three different deep learning models, mlp, sae, and cnn, are summarized in table 4. more than 93% accuracy is achieved for all three different models. the offline training time, directly measured from the system, for cnn, mlp and sae models are 1,518, 111, 25 sec, respectively. the complexity of ml models, especially for the deep learning models, has been significantly increasing over recent years. this is mainly due to the increasing number of deep learning network layers and the volume of dataset which consequently increases the computational cost corresponding to the execution time required training a deep learning network. fortunately, this computational cost is only effective during offline training phase. in this research with online traffic classification in sdn during testing phase, the execution time to identify an application for each flow is within few seconds which is relatively small. the trained models for online testing can reach a very high confidence on classification within several statistics data which was collected in every second. the detailed online testing results will be discussed in the next sub-section. 4.2. online testing result as mentioned earlier, we have injected the iscx dataset into tcpreplay host and then replayed them one by one according to the same processing time and sequence to emulate the online traffic for the client/server communications in the sdn testbed. the server ip addresses and transport port numbers in each flow and the byte counts and packet counts collected from statistics data are stored and selected in ryu controller for further data pre-processing so that the server ip addresses and transport port numbers can be handled using one-hot input scheme. for online testing, we use other dataset files with the same applications and pre-processing as the training model to match the input size of the training model. in order to response to the unknown applications, we add a server to mirror packet in message in controller. the mirror server will label the online applications or services for predicted result comparison. furthermore, in the case of vast amount of packets or flows injected into the ovs switch, such as abnormal intrusion, the mirror server can play a role of ovs buffering through the dropping of the vast injected packets on ovs switch to avoid the bandwidth exhaustion. because of the limitation of the processing speed of the ryu controller and ovs switch hardware, we might encounter statistics packets drop or tcpreplay packets drop when the testing dataset injected into the ovs switch according to the same processing time and sequence. therefore, the incomplete dataset due to the packets drop might cause the accuracy decline of the online prediction for different deep learning models as compared with the offline cases. in fig. 6, we illustrate the predicted result, in terms of confusion matrix, of application-based online traffic classification with mlp deep learning model. the diagonal values in the matrix correspond to the true positives of the predicted result of facebookchat, gmailchat, handoutschat, netflix, skypeaudio, skypevideo, and youtube categories, respectively. from the illustration shown in fig. 6, the number of false positives between skypeaudio and skypevideo categories is relatively high. this is understandable because the flows from these two categories own the same server ip and transport port features. the only possible features which we can identify could be byte counts. however, the dynamic encoding schemes of the audio and video could dim the byte count feature. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 226 the numbers of false positives between netflix and skypeaudio or between youtube and skypeaudio also show relatively higher ratio. although the server ip addresses are different for these applications, the similar multimedia behavior in terms of byte counts and packet counts features for deep learning will lead the miss-identification of such streaming category to the skypeaudio category. as a simple deep back-propagating learning technique, the mlp deep learning model may suffer from such miss-identification easily. therefore, a relatively higher error rates were observed between skypeaudio and skypevideo or between netflix and skypeaudio applications. however, we still achieve about 87% accuracy on average for application-based online traffic classification with mlp deep learning model. especially, we conduct the application services with very similar characteristics, such as multimedia, audio and video streaming, which could be very difficult for network traffic classification. fig. 6 confusion matrix of mlp online test result fig. 7 confusion matrix of sae online test result the predicted result, in terms of confusion matrix, of application-based online traffic classification with sae deep learning model is illustrated in fig. 7. similarly, the number of false positives between skypeaudio and skypevideo categories is relatively high again for the sae deep learning model. the numbers of false positives between netflix and skypeaudio or between youtube and skypeaudio also shows relatively higher ratio. because the sae deep learning model uses encoder and decoder for learning, the selected features need to be further adjusted to distinguish the similar streaming behavior between skypeaudio and skypevideo categories or among different multimedia streaming properties. fig. 8 confusion matrix of cnn online test result besides, the predicted result, in terms of confusion matrix, of application-based online traffic classification with cnn deep learning model is illustrated in fig. 8. similarly, the numbers of false positives between skypeaudio and skypevideo categories are relatively high for the cnn deep learning model. the numbers of false positives between netflix and advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 227 skypeaudio or between youtube and skypeaudio also show relatively higher ratio which is believed due to the similar multimedia behavior in terms of byte counts and packet counts features for deep learning. the average accuracy for application-based online traffic classification with cnn deep learning model is about 87.3%. in this paper, we reduce the problem of multiclass classification to multiple binary classification problems by using one vs rest transformation technique [25]. the one vs rest transformation technique will treat a single classifier per class with the predicted labels of that class as positive samples and all other predicted labels as negatives. thus, four indicators, accuracy, precision, recall, and f1, were calculated using the confusion matrix to evaluate the performance of application-based online traffic classification with different deep learning models. the online testing result with four indicators in our sdn testbed is shown in table 5. table 5 online testing result for different models accuracy precision recall f1-score cnn 87.208% 85.142% 84.428% 84.857% mlp 87.167% 84.428% 87.714% 84.714% sae 87.079% 85.142% 84.285% 84.714% based on the experimental results, the average accuracies for different deep learning models are about the same, 87%, which is smaller than our offline training result, above 93%. due to the hardware limitation, we might encounter possible statistics packets drop or tcpreplay packets drop when the testing dataset injected into the ovs switch according to the same processing time and sequence. consequently, the incomplete dataset due to the packets drop might cause the accuracy decline of the online prediction for different deep learning models as compared with the offline cases. on the other hand, the increasing number and variation of application services might increase the difficulty on application-based online traffic classification on sdn networks with deep learning models. although the numbers of false positives between skypeaudio and skypevideo categories are relatively high and the numbers of false positives between netflix and skypeaudio or between youtube and skypeaudio also show relatively higher ratio for all deep learning models, the values of precision, recall and f1-score are all above 84% and quite close to the accuracy value. as we commented, the application services conducted in this paper with very similar characteristics, such as multimedia, audio and video streaming, could be very difficult for network traffic classification. however, with the help of deep learning models, including cnn, mlp and sae, the average online testing accuracies for all models are all above 87% with quite close precision, recall and f1-score values. 5. conclusions deep learning techniques have become one of the most interesting and practical topics being applied on all kinds of fields, such as computer vision, audio recognition and natural language processing. in this paper, we have proposed an application-based online and offline traffic classification, based on deep learning mechanisms, over sdn testbed. the designed deep learning architecture and scheme consists of three deep learning models, mlp, sae, and cnn, in the sdn testbed. we have applied an open network traffic dataset with seven most popular applications as the deep learning training and testing datasets. by using the tcpreplay tool, the dataset traffic samples are re-produced and analyzed in our sdn testbed to emulate the online traffic service. we have conducted performance analysis, in terms of accuracy, precision, recall, and f1 indicators, and compared the results with three deep learning models. the offline training results have achieved more than 93% accuracy on identifying seven popular applications for all three different models. furthermore, we have achieved 87% accuracy for the application-based online testing prediction. advances in technology innovation, vol. 5, no. 4, 2020, pp. 216-229 228 in the future, we will correlate the deep learning parameters, models and accuracy to improve the overall learning performance. the real online packets measurement and analysis in sdn network will be conducted in the next step. the network slicing in sdn network with qos mechanism followed by successful traffic classification could be the further research. acknowledgement this research was supported by research grants from ministry of science and technology, taiwan (most 107-2221-e-142-002-my2) as well as mobile broadband promotion project, ministry of education, taiwan (no. 1070208431g). conflicts of interest the 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[25] m. l. zhang and z. h. zhou, “a review on multi-label learning algorithms,” ieee transactions on knowledge and data engineering, vol. 26, no. 8, pp. 1819-1837, august 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-aiti#5597 203-215.docx advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 thai voice-controlled analysis for car parking assistance in system-on-chip architecture sethakarn prongnuch 1,* , suchada sitjongsataporn 2 1 department of computer engineering, suan sunandha rajabhat university, bangkok, thailand 2 department of electronic engineering, mahanakorn university of technology, bangkok, thailand received 29 april 2020; received in revised form 26 june 2020; accepted 10 august 2020 doi: https://doi.org/10.46604/aiti.2020.5597 abstract this paper introduces an analysis of thai speech recognition for controlled car parking assist in the system-on-chip architecture. the objective is to investigate the male and female voice command signals, including thai and english words, issued by the native thai users. hardware and software co-design by the xilinx vivado are designed on an arm multicore processor and a reconfigurable system on a zybo board. the experiments for thai and english word recognition are conducted by using the mel-frequency cepstral coefficient approach and presented in the form of spectrograms. the comparison of a voice command via bluetooth and a reference command stored on an sd card and the zybo embedded board on a miniature electric vehicle is verified with the pearson’s correlation coefficient (pcc). the experimental results show the accuracies of the received thai/english, male/female, and indoor/outdoor voice commands as compared with the reference voice commands in the noisy surroundings. hence, our system can support thai/english and male/female voice commands to perform a set of actions for maneuvering a car by the pcc. keywords: speech recognition, voice-controlled parking assist, reconfigurable embedded systems, system-on-chip 1. introduction with the increasing number of automobiles in crowded cities, the number of parking lot accidents that drivers troubles while parking on the rooftop under possible space restrictions have also increased. traffic accidents during parking include hitting, denting, and being scratched. drivers often encounter difficulties while maneuvering a vehicle adjacent to a narrow space and the roof of a building. for instance, a parking deck located on a roof may pose some dangers because of the short rooftop barrier as shown in fig. 1(a). in 2019, car crash news [1-3] from thailand described the case of a vehicle plunging from a parking building in thailand as the driver applied the wrong gear [2]. the indianapolis star news also reported incidents of cars plunging from parking garages and that 46 accidents across the united states have been recorded in the last two decades[1, 3]. many devastating incidents have been identified to be cased by elderly drivers who accidentally stepped on the accelerator instead of the brakes. hence, to ensure safety, using the parking assist outside a car may be preferable. fig. 1(b) shows a driver worrys about maneuvering a vehicle because of the narrow space restrictions. using a voice-controlled assist outside the car would be the safer option because the driver can see obstacles on the road. a parking assist is a voice-controlled vehicle maneuvering system functioning at low velocities. the system can detect the parking space and ensure safety while parking. however, the existing parking assist systems are mostly used inside a car, * corresponding author. e-mail address: sethakarn.pr@ssru.ac.th tel.: +662-1-601435; fax: +662-1-601440 advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 204 thereby limiting effectivity. hence, to improve the parking skills of the driver, yukawa [4] proposed using the reverse parking direction through the auditory assistance approach. several studies have also proposed parking assist systems, such as an autonomous path planning in the narrow environments [5], a surround-view parking system [6], and a voice-controlled embedded system for parking a prototype car [7-8]. (a) reverse parking on the roof (b) voice-controlled car parking assist fig. 1 voice-controlled car parking assist the need to minimize drive disruption in the operation of the car led by honda [9] use analog control to assist the driver in operating the car more confidently. this usability will be adopted for aging owners. a voice-controlled interface will be built-in to encourage the interaction of humans and smart applications that understand voice commands boosted by the use of speech recognition. to ensure their safety and well-being, drivers can employ the car parking assist while maneuvering the car from the outside so that they would have an unobstructed view around the car. the idea of the parking assist is an exterior usage from the safety control. in this paper, we propose a voice-controlled parking system for an automatic car parking assist that comprises a communication system adapted to receive a set of voice commands. we also evaluate thai speech recognition for voice-controlled car parking assist in system-on-chip architecture on a prototype electric vehicle. previous studies have proposed various approaches regarding driver assistance. in [10], the authors proposed a parking-space detection system for occupancy by using bluetooth communication and arduino-based sensor devices. other studies have also presented advances in voice-based recognition. in [11], a bias analysis of recognition phrases that utilized the accent of the southeast region for smartphone interaction with a voice personal assistant was performed. the preliminary results were found to be skewed towards the voices of individuals. in [12], a raspberry pi-based voice-controlled car using the baidu speech recognition technology and tested with remote control interaction was presented. in [13], the interoperability of speech recognition in romanian for voice-controlled appliances in smart buildings was explored. in [14], a voice-based unmanned aerial vehicle approach using the mfcc analysis of semantic identification was introduced. the experiments in previous studies have shown that the mfcc was capable of voice command recognition. the paper is organized as follows. section 2 describes speech recognition shortly, and section 3 outlines briefly the pearson’s correlation coefficient. section 4 introduces the proposed voice-controlled car parking assist. section 5 presents the experimental results and performance. section 6 concludes the paper. 2. speech recognition speech signal [15] refers to a sequence of encoding message symbols as shown in fig. 2. the speech recognition system begins by transforming the speech waveform into the sequence of a discrete vector. then, a recognizer is used as a mapping tool for the discrete speech vector, which is underlined by a sequence of symbols. feature extraction is the method of reducing the number of features from the measured input signal, which leads to the identification of the speaker. advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 205 fig. 2 speech recognition system 2.1. feature extraction fig. 3 illustrates the feature extraction process. an acoustic signal is converted to digitize the features. then, the pre-emphasis procedure is implemented to enhance the signal to noise ratio in the higher frequencies. the window framing and fast fourier transform (fft) are performed to avoid discontinuities. the mel-frequency cepstrum coefficients (mfcc) technique [16] is used to extract the features as an envelope of the spectrum in the cepstral domain. the transformed acoustic signals are obtained based on their features in the time and frequency domains. in relation to establishing the feature vector [17], the spectrogram is modified through a short-time fourier transform (stft) to demonstrate the features of the acoustic signal in the time-frequency domain applied through the mfcc approach. fig. 3 feature extraction process using the mel-frequency cepstral coefficient approach 2.2. short-time fourier transform and spectrogram the stft of a signal is represented as [18]: { }( ) ( , ) ( , ) ( ) ( ) j n n stft x k m x m x k w k w e ∞ − =−∞ ≡ ≡ −∑ φφ φ (1) where ���� and ���� are the input signal and window, respectively. the spectrogram is the square of the stft magnitude and is calculated as: { } 2 ( ) ( , ) ( , )spectogram x k m x m≡φ φ (2) 2.3. mel-frequency cepstral coefficients the mfcc is the real cepstrum of a windowed short-time signal developed from the fft [17]. its difference from the real cepstrum is assumed to be the characteristic of the auditory system by using a nonlinear frequency scale. for the pre-emphasis process, the first order high-pass filter is performed as in [18]: ( ) ( ) ( 1), 0.9 1.0y k x k x n= − − ≤ ≤γ γ (3) advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 206 where ����, ����, and � are the input signal, output signal, and filter coefficient, respectively. the discrete fourier transform input signal can be computed as [16]: 21 0 ( ) ( ) , 0 j nkk n dft k x k x k e n n −− = = ≤ ≤∑ π (4) the n-point hamming window function can be expressed as: 2 ( ) cos( ), 0 1 1 n w k n n n = − ≤ ≤ − − π α β (5) where � = 0.54 and � = 0.46. mel-scale filter bank is modified by binding the frequencies onto the mel-scale in the frequency domain as [17]: ( ) 1127 ln(1 ) 700 mel = + ω ω (6) we define a filter bank with m filters as: 0, ( 1) ( 1) , ( 1) ( ) ( ) ( 1) ( ) ( 1) , ( ) ( 1) ( 1) ( ) 0, ( +1) m n m n m m n m m m h n m n m n m m m n m < −  − − − < < − − =  − − ≤ ≤ +  + −  > ω ω ω ω ω ω ω ω ω ω ω ω (7) where 1 ≤ � ≤ �, m is the total number of filters in the frequency band, and ��∙� is the mel-scale frequency. the log-energy at the output of the filter bank may be expressed as: 1 2 0 ( ) ln( ( ) ), 0 n dft k s m x k n m − = = ≤ <∑ (8) the discrete cosine transform (dct) is operated to achieve the ��� cepstral coefficients �� as: 1 0 ( 0.5) ( )cos( ), 1, 2, , m r m r m c s m r r m − = − = =∑ … π (9) where ���� is the logarithm of the mel spectrum, and r is the total number of cepstral coefficients. the speech recognition procedure typically uses the 13-cepstrum coefficients. 3. pearson’s correlation coefficient following [18], we consider the signal in the time domain as: ( ) ( ) ( )t t t= +y x η (10) where ���� , ���� , and ���� are the signal from the microphone, reference, and noise signals, respectively. thus, the covariance matrix of the signal from the microphone can be expressed as: { } { } { }( ) ( ) ( ) ( ) ( ) ( )t t t y xe t t e t t e t t η+ +y y x x η η≃ i ≃ i i ≃r r r (11) advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 207 where ℝ! and ℝ" are the covariance matrices of ���� and ���� , respectively, the operator #$⋅& is defined as an expectation operator. the input signal to noise ratio can be defined as: 2 2 xisnr = η σ σ (12) where '! ( and ') ( are the variances of ���� and ���� as '! ( = #$�(���& and '! ( = #$*(���&, where ���� and *��� are the reference and noise signals in the time domain respectively. we focus on how to estimate ���� from the observations by using pcc on the most interesting signals. the pcc (pxy) is a measurement of the linear correlation between two random variables, ���� and +���, which is defined as in [16]: { }( ) ( )t xy x y e y t y t p ⋅ = ⋅σ σ (13) where #$+,��� ⋅ +���& is the crosscorrelation between ���� and +���. the square of pearson’s correlation coefficient (spcc) is computed as: { } 2 2 2 2 ( ) ( )t xy x y e y t y t p  ⋅ = ⋅σ σ (14) where '! ( and '( are the signal variance of ���� and +���, respectively, and can be presented as: { }2 ( ) ( )t x e x t x tσ = ⋅ (15) { }2 ( ) ( )t y e y t y tσ = ⋅ (16) the important property of spcc is 0 ≤ .!( ≤ 1. the spcc indicates the linear relationship between two random variables, ���� and +���. if .!( is equal to zero, ���� and +��� are uncorrelated. the value of .!( is closer to 1, which means ���� and +��� have strong correlations. the pcc (.!-) is reformulated by substituting the estimates of the covariance and variance with the method of a sum over the samples, which can be obtained by: ( ) ( ) 2 22 2 i i i i xy i i i i n x y x y p n x x n y y − =  − −   ∑ ∑ ∑ ∑ ∑ ∑i (17) where n is the size of the sample, �/ and +/ are the individual sample points at index i. 4. proposed voice-controlled car parking assist in this section, we present the voice-controlled car parking assist system. the system consists of hardware and software co-design with a systems-on-chip architecture [19]. the system design is composed of four parts: a zybo board, an arduino uno board, a bluetooth module, and the sensors. advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 208 4.1. hardware co-design system fig. 4 is the overview of the hardware co-design system, which comprises six hardware installations for exterior usage: a bluetooth device, a motor device, a buzzer, a servo motor managed through an arduino uno, and two ultrasonic sensors. the bluetooth device collects the input voice command data and then transmits it to other devices. fig. 4 overview of the system fig. 5 xilinx vivado design architecture advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 209 we apply the xilinx vivado [19] shown in fig. 5, which includes the x software development kit (xdsx) software design tool on the reconfigurable areas inside the zybo board, zynq7 system for the interior usage combined with an arm multicore and a reset system, advanced extensible interface (axi) interconnect, fixed i/o, ddr ram, and six hardware devices. 4.2. software co-design system the flow chart of the proposed system is shown in fig. 6. initially, the headset bluetooth microphone receives english or thai voice command data, which are then sent to an application on a smartphone for pre-processing. then, the zybo fpga embedded board checks the received voice command and compares the command with the reference stored in the micro sd card. the arm main processor on the zybo board reads the voice input and compares it with the original voice by using the pcc function defined in eq. (17). finally, the results are compared to match the control commands to regulate the peripherals, which include the arduino board, the dc motor, and the buzzer. the final step involves the car moving by the voice-controlled assist. fig. 6 flow chart of the proposed system 5. experimental results and performance this section expounds on the experimental results and the performance evaluation for the voice-controlled car parking assist. 5.1. simulation results this section provides the analysis results of thai female and male voice signals in the form of the spectrograms by using the mfcc approach. the voice signals features are normally operated in the time and frequency domains. hence, to form the feature vector [20], a spectrogram using stft to form the acoustic features in the time-frequency domain is provided, and the mfcc approach is utilized following [21]. advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 210 table 1 the parameters of feature extraction parameter value in unit length of thai female and male voice data per instance 1 second sampling frequency �01� 48 khz/44 khz fft size per frame 512 frame length �23� 25 milliseconds frame shift �4 23� 10 milliseconds number of filter banks 20 number of cepstral coefficients 13 the experiments for thai female and male speech recognition are studied to establish the investigation process. table 1 shows the parameters used for the feature extraction that were obtained by using computer simulations. figs. 7-12 depict the spectrograms of the various thai female and male voices tested and compared with the reference voice data. the words consist of six thai and english words of the basic commands for the proposed voice-controlled car parking assist, including “56”/“go”, “789:”/“back”, “;<=9 ”/“right”, “>9: ”/“left”, “58?@”/“ready”, and “a:bc”/“stop”. (a) thai male outdoor voice (b) thai male original voice (c) thai female outdoor voice (d) thai female original voice fig. 7 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “56” or “go” in thai (a) thai male outdoor voice (b) thai male original voice (c) thai female outdoor voice (d) thai female original voice fig. 8 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “789:” or “back” in thai (a) thai male outdoor voice (b) thai male original voice fig. 9 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “kkwa” or “right” in thai advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 211 (c) thai female outdoor voice (d) thai female original voice fig. 9 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “kkwa” or “right” in thai (continued) (a) thai male outdoor voice (b) thai male original clear voice (c) thai female outdoor voice (d) thai female original clear voice fig. 10 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “>9:” or “left” in thai (a) thai male outdoor voice (b) thai male original clear voice (c) thai female outdoor voice (d) thai female original clear voice fig. 11 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “58?@” or “ready” in thai (a) thai male outdoor voice (b) thai male original clear voice (c) thai female outdoor voice (d) thai female original clear voice fig. 12 mel-frequency cepstral coefficients computed from male and female speech signals shown in the form of spectrograms of “a:bc” or “stop” in thai 5.2. hardware implementations the proposed hardware co-design system was implemented with zybo and arduino boards installed in a 234×434 mm scale electric vehicle as shown in fig. 13. the properties of the scale electric vehicle are as follows: the motor type is a dc advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 212 motor gear, the maximum gross vehicle weight is 1.75 kg, the kerb weight is 1.38 kg, the wheelbase is 257 mm, the radius of the turning wheel is 22 mm, the tire type is rubber, and the size of the front/rear wheel is 163/161 mm. (a) 234×434 mm scale electric vehicle (b) zybo and arduino boards implementation inside fig. 13 zybo and arduino boards for installation on a small-scale electric vehicle (a) first page of the application (b) tap the microphone icon to record the voice command (c) send the voice command data via bluetooth to start the systems fig. 14 application design of the proposed voice-controlled car parking assist interface on the smartphone advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 213 a prototype application was developed. the application design of the proposed voice-controlled car parking assist interface on the smartphone is provided in fig. 14. the first page of the voice-user interface is shown in fig. 14(a); the driver taps the microphone icon to record the voice command depicted in fig. 14(b) to control car parking; the recorded voice command data are sent through bluetooth, which is indicated in fig. 14(c), to start the voice-controlled car parking assist. the reference command patterns are stored on an sd card in the zybo fpga-embedded board and loaded into the memory while running the software. a comparator using pcc shown in (16) checks the reference command patterns and compares the patterns with the voice command data received via bluetooth device. all results are transmitted to control the motor drive and the servo motor. the prototype electric vehicle in fig. 13 will perform a set of actions that involve moving forward/backward, turning right/left, ready, and stop as shown in table 2. table 2 demonstrates the comparison of thai and english voice commands used for maneuvering an automobile. table 2 set of thai and english word command used for maneuvering a miniature electric vehicle a set of actions thai word command english word command moving forward “56” “go” moving backward “789: ” “back” turning right “;<=9 ” “right” turning left “>9: ” “left” ready “58?@ ” “ready” stop “a:bc ” “stop” for the experimental operations, six voice commands in thai and english were used, including “ 56 ”/“go”, “789: ”/“back”, “;<=9”/“right”, “say”/“left”, “58?@”/“ready”, and “a:bc”/“stop”. we concentrated on the experimental testing of the proposed voice-controlled car parking assist while the driver issuing the commands through the smartphone is outside the car. tables 3 and 4 show the pcc (.!-) and spcc (.!() of the received thai/english, male/female, and outdoor/indoor voice commands compared with the reference thai and english original clear voice commands stored on the sd card in the zybo board. table 5 illustrates the percentage accuracies of thai and english voice commands in a noisy environment. table 3 pcc (.!-) and spcc (.!() of the received thai/english male/female outdoor commands compared with the reference voice commands stored on the sd card in the zybo board “56” “go” “789:” “back” “;<=9” “right” “say” “left” “58?@” “ready” “a:bc” “stop” male: .! 0.981 0.904 0.900 0.865 0.923 0.889 0.902 0.877 0.909 0.847 0.915 0.916 .!( 0.963 0.817 0.808 0.749 0.852 0.791 0.814 0.769 0.826 0.718 0.836 0.839 female: .! 0.932 0.934 0.866 0.978 0.859 0.924 0.904 0.910 0.874 0.913 0.957 0.920 .!( 0.869 0.872 0.786 0.956 0.738 0.853 0.818 0.829 0.765 0.833 0.916 0.847 table 4 pcc (.!-) and spcc (.!() of the received thai/english male/female indoor commands compared with the reference voice commands stored on the sd card in the zybo board “56” “go” “789:” “back” “;<=9” “right” “say” “left” “58?@” “ready” “a:bc” “stop” male: .! 0.929 0.951 0.939 0.973 0.924 0.952 0.953 0.972 0.913 0.969 0.902 0.983 .!( 0.862 0.905 0.881 0.947 0.854 0.906 0.908 0.945 0.834 0.939 0.813 0.966 female: .! 0.927 0.934 0.969 0.969 0.927 0.912 0.920 0.910 0.965 0.934 0.998 0.967 .!( 0.859 0.872 0.939 0.939 0.860 0.832 0.846 0.827 0.931 0.872 0.995 0.935 table 5 percentage accuracies of thai and english voice commands in a noisy environment “56” “go” “789:” “back” “;<=9” “right” “say” “left” “58?@” “ready” “a:bc” “stop” %accuracy 89 90 90 87 89 89 89 88 90 85 91 92 advances in technology innovation, vol. 5, no. 4, 2020, pp. 203-215 214 6. conclusions in this study, voice interfaces are used to control a car parking assist based on the word command patterns of thai/english and males/females. gender analysis was used as the basis for an mfcc technique to extract the features represented in the spectrogram of thai/english and male/female word recognition through stft. the simulation results indicate the better accuracies of the received thai/english, male/female, and indoor/outdoor commands as compared with the reference voice commands. the results of experimental tests with thai and english voice commands for maneuvering a miniature electric vehicle using the pcc and the spcc of thai/english, male/female, and indoor/outdoor voice commands were also shown. our research contributes to the literature on thai speech recognition and the performance of the proposed voice-controlled parking assist in noisy environments. this study is also expected to provide parking assistance to ensure drivers’ safety and well-being through testing and implementation in commercial eco-cars in the future. acknowledgments we would like to thank thodsaporn chuatai, jakkit wongtewee, and thatthep pansungnoen of the department of computer engineering, faculty of industrial technology, suan sunandha rajabhat university in bangkok, thailand for their support. conflicts of interest the authors declare that there is no conflict of interest regarding the publication of this paper. references [1] d. johnson, “2 people dead after car falls 4 stories from downtown indianapolis parking garage,” https://fox59.com/news/2-people-dead-after-car-falls-4-stories-from-downtown-indianapolis-parking-garage/, october 23, 2019. 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[21] siri team, “personalized hey siri,” machine learning journal, vol. 1, no. 9, april 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 5___aiti#7835_in press advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 optimization of superplastic forming process of aa7075 alloy for the best wall thickness distribution manh tien nguyen 1,* , truong an nguyen 1 , duc hoan tran 1 , van thao le 2 1 faculty of mechanical engineering, le quy don technical university, ha noi, viet nam 2 advanced technology center, le quy don technical university, ha noi, viet nam received 02 june 2021; received in revised form 27 july 2021; accepted 28 july 2021 doi: https://doi.org/10.46604/aiti.2021.7835 abstract this work aims to optimize the process parameters for improving the wall thickness distribution of the sheet superplastic forming process of aa7075 alloy. the considered factors include forming pressure p (mpa), deformation temperature t (°c), and forming time t (minutes), while the responses are the thinning degree of the wall thickness ε (%) and the relative height of the product h*. first, a series of experiments are conducted in conjunction with response surface method (rsm) to render the relationship between inputs and outputs. subsequently, an analysis of variance (anova) is conducted to verify the response significance and parameter effects. finally, a numerical optimization algorithm is used to determine the best forming conditions. the results indicate that the thinning degree of 13.121% is achieved at the forming pressure of 0.7 mpa, the deformation temperature of 500°c, and the forming time of 31 minutes. keywords: superplastic forming, wall thickness distribution, optimization, response surface, aa7075 alloy 1. introduction aa7075 is an aluminum alloy with outstanding mechanical properties such as high strength, light weight, and corrosion resistance. therefore, aa7075 alloy is widely used in the aerospace and automotive industries. this alloy has been used to replace high strength steel on most types of cars and commercial aircraft [1-2]. however, the deformability of this alloy is limited at room temperature. the elongation to fracture for tensile tests of this alloy was achieved below 10% at room temperature (20°c), resulting in its limited applicability in forming processes. to improve its deformability, other forming methods have been used to expand the application of the alloy. superplastic forming (spf) is one of the widely used methods. spf is conducted within a limited range of conditions such as material microstructure, strain temperature, and strain rate. when conditions of spf are met, the material will achieve a degree of deformation many times greater than that of the normal strain condition. in uniaxial tension, the elongations in excess of 200% are usually indicative of superplasticity [3-6]. the forming process for hollow parts from a flat sheet or a pre-profile blank or a tube blank under the action of compressed air pressure is one of the spf methods. the received product may have a shape of forming tools [7-9]. this process can bring some attractive advantages, including large deformation ability, complex products, and a simple or no forming tools required. moreover, the spf technology has a great advantage in the production of single or small series of complex parts from high strength materials. however, this technology also has serious disadvantages that are an uneven distribution of wall thickness after the deformation process greatly affects the quality and working ability of the product [10-11]. * corresponding author. e-mail address: nguyenmanhtiengcalmta@gmail.com tel.: +84 977 817 623 advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 the spf by compressed air pressure depends on many parameters such as forming pressure, deformation temperature, forming time, tool size, coefficient of friction, back pressure, etc. [12-15]. the degree of influence of each parameter on the deformation ability is significantly different. the wall thickness distribution of the product is the prioritized criterion in terms of the formed part quality. several studies on improving the distribution of the wall thickness have been carried out. shojaeefard et al. [16] have studied the effect of the die entry radius and the interfacial friction coefficient on the required forming time and thickness distribution of the product. their results have shown that with lower friction coefficients, the sensitivity of the formed part thinning factor to the die entry radius variations is high. it was also concluded that a larger die entry radius along with a lower friction coefficient leads to a shorter forming time and a more uniform final part thickness distribution. jarrar [17] found that for free-bulge forming process of aa5083 at 500°c, single-, two-, and three-step isobaric forming process produce the same part thickness uniformity within shorter forming time compared to the forming process at a constant maximum strain rate. kumaresan et al. [18] performed the finite element simulation using abaqus software to evaluate the deviation of the thickness distribution between the simulation and experiment. the process parameters selected for simulation include pressure, forming time, and initial sheet thickness. also, balasubramanian et al. [19] experimentally and numerically studied the three-stage forming process. discontinuities in the thickness of the formed profile have been observed due to the transition of radius from one stage to the next. results of this study have revealed that an optimum pressure of 0.5 mpa for achieving uniform thickness in the profile exists. alirezaiee et al. [10] proposed a new method to produce a part with a fairly uniform thickness distribution. in their proposed method, a die having a movable segment is used. by moving this segment during the process, the part is formed during two stages and final thickness distribution is controlled. one of the factors affecting the forming process, which has also been mentioned in many studies, is the change in the microstructure of the material during the spf process. since the grain size is a preliminary criterion for obtaining superplasticity in any material, its stability at the deformation temperature plays a significant role. the deformation ability of the material will be significantly reduced as the average grain size increases during the spf process [20-21]. moreover, abnormal grain growth is also a major metallurgical aspect in superplastic deformation [22-23]. however, the aforementioned publications indicated that the process parameter optimizations for sheet spf processes about the formed part quality have not been thoroughly investigated. recently, many technological solutions have been researched to improve the thinning degree of the wall thickness and increase the product quality. the new spf process was developed based on the back pressure principle. besides hardware developments, forming parameter optimization is still an effective approach in terms of costs and time. the aa7075 high-strength aluminum alloy was selected as the workpiece material due to its wide industrial applications. this work aims to optimize the process parameters for improving the wall thickness distribution of the sheet spf process of aa7075 alloy. the considered factors include forming pressure p (mpa), deformation temperature t (°c), and forming time t (minutes), while the responses are the thinning degree of the wall thickness ε (%) and the relative height of the product h*. first, a series of experiments are conducted in conjunction with the response surface method (rsm) to render the relationship between inputs and outputs. subsequently, an analysis of variance (anova) is conducted to verify the response significance and parameter effects. finally, a numerical optimization algorithm is used to determine the best forming conditions. 2. research methodology 2.1. optimization problem the thinning degree of the wall thickness ε (%) is one of the important criteria with regard to the quality of spf products. the goal of the current work is to optimize the process parameters, including forming pressure, deformation temperature, and forming time for minimizing the thinning degree. the schematic diagram of the sheet spf process under the action of 252 advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 compressed air pressure is depicted in fig. 1. the die is fastened by bolts, and the pneumatic tube into the die is welded with a sealing cap. the 45 steel is selected as the die material due to the medium forming temperature. the die and the stroke sensor are placed in the furnace during deformations. fig. 1 schematic diagram of the sheet spf process as shown in table 1, the limits of variables are denoted as -1, 0, and +1 for the lower value, middle value, and higher value, and the input variables are denoted as a for forming pressure (mpa), b for deformation temperature (°c), and c for forming time (min). the parameter ranges are determined based on the references [7, 11, 24]. consequently, the optimizing issue is to find the minimum thinning degree based on the optimization process parameters [25]. table 1 levels and their values of the process parameters symbol parameters level -1 level 0 level +1 p a: forming pressure (mpa) 0.7 0.8 0.9 t b: deformation temperature (°c) 500 515 530 t c: forming time (min) 20 30 40 2.2. optimization framework in the box-behnken design (bbd), three levels for each design parameter or factor are required, with all design points lying on the same sphere and with at least three or five runs at the center point. bbd is applied instead of the full-factorial one to decrease the number of experiments and ensure the predicting accuracy. the predictive mathematical model of the thinning degree is then developed with respect to process parameters using rsm [26-28]. subsequently, a fitness analysis is conducted in order to investigate the significance of the proposed model and the factor is chosen. to solve the optimization problem, an advanced technique entitled desirability function (df) is adopted for obtaining optimal values. in addition to the design points, a set of random points are checked to see if there is a more desirable solution. the influence of the parameters on the objective function will help the technology design process. the feasible solutions could be obtained with a minimal cost, from a problem that potentially has a great number of solutions [29-30]. as a result, an integrative approach combining bbd, rsm, and df can be considered a powerful method to find global optimal process parameters with a smaller number of experiments as well as less computational effort. 3. experimental procedures the experimental specimens are cut from a flat sheet of the thickness of 1.2 mm to have a diameter of 50 mm. the material used in this study is an aa7075 alloy. the chemical composition of the aa7075 alloy listed in table 2 is expressed in weight percent (%wt). the aa7075 alloy is prepared to fine stable grain size with an average grain size of about 13 µm. the experimental tests are carried out under spf conditions. the experimental equipment system is shown in fig. 2. 253 advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 table 2 chemical composition of the analyzed aa7075 alloy zn mg cu fe cr ti zr mn si al 5.35 2.34 1.32 0.30 0.22 0.04 0.0027 0.024 0.05 balance fig. 2 the experimental equipment system the deformed specimens are exhibited in fig. 3. the position of wall thickness measurement is determined as shown in fig. 4. at that position, the thinning degree is the greatest. the wall thickness values are measured by a jena universal microscope. the overall height of the product is determined and shown in fig. 5. the average response values are observed repeatedly three times. the experimental data of the thinning degree of the wall thickness ε and the relative height of the product h* are exhibited in table 2. the thinning degree of the wall thickness is the ratio between the amount of thinning at a dangerous position and the thickness calculated according to the law of constant volume. the relative height of the product is the ratio between the overall height hi and outside diameter dp of the part. fig. 3 the specimens after spf processes fig. 4 the position of wall thickness measurement of deformed specimens fig. 5 determination of the overall height hi and outside diameter dp of the product 254 advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 4. results and discussion 4.1. model fitness investigation in this study, anova is used to determine the adequacy and significance of models. in addition, it is used to evaluate the effect of lack-of-fit on the models and the significance of the individual model coefficient. there are 15 test trials performed based on the design of the experiment method as shown in table 3. anova results of the thinning degree and relative height are shown in table 4 and table 5. the significant coefficients are selected based on the p-values of the parameters considered. the parameters are modeled using a confidence level of 95%. hence, the factors with p-values less than 0.05 are considered significant. table 3 experimental results number of experiments factor 1 factor 2 factor 3 responses a: forming pressure (mpa) b: deformation temperature (°c) c: forming time (min) r1: thinning degree ε (%) r2: relative height of the product h* 1 -1 -1 0 13 0.25 2 +1 -1 0 15 0.32 3 -1 +1 0 16.8 0.30 4 +1 +1 0 16.5 0.37 5 -1 0 -1 16.5 0.34 6 +1 0 -1 17.8 0.27 7 -1 0 +1 17 0.40 8 +1 0 +1 18 0.49 9 0 -1 -1 17.8 0.30 10 0 +1 -1 18.4 0.42 11 0 -1 +1 17 0.33 12 0 +1 +1 20 0.45 13 0 0 0 17.4 0.48 14 0 0 0 17.2 0.48 15 0 0 0 17 0.44 table 4 anova result for thinning degree model source sum of squares degree of freedom mean square f-value p-value significance model 33.48 9 3.72 38.16 0.0004 significant a-a 2.00 1 2.00 20.51 0.0062 b-b 9.90 1 9.90 101.55 0.0002 c-c 0.2813 1 0.2813 2.88 0.1502 ab 1.32 1 1.32 13.56 0.0142 ac 0.0225 1 0.0225 0.2308 0.6512 bc 1.44 1 1.44 14.77 0.0121 a² 7.50 1 7.50 76.90 0.0003 b² 0.7477 1 0.7477 7.67 0.0394 c² 8.87 1 8.87 90.98 0.0002 residual 0.4875 5 0.0975 lack-of-fit 0.4075 3 0.1358 3.40 0.2358 not significant pure error 0.0800 2 0.0400 corrected total 33.97 14 r² 0.9856 adjusted r² 0.9598 predicted r 2 0.8028 adequate precision 27.7014 255 advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 as shown in table 4 and table 5, the f-values 38.16 and 25.93 indicate the significance of the quadratic models. in these models, all the single terms (p, t, and t) and quadratic terms (p 2 , t 2 , and t 2 ) are found to be significant model terms. the insignificant terms (pt, pt, and tt) should be eliminated in the design space in order to save computational time. additionally, the r 2 -value of the thinning degree is 0.9856, indicating that 98.56% of the total variations are explained by the model. the r 2 -value of the relative height is 0.9790, indicating that 97.9% of the total variations are explained by the model. moreover, the comparison results from the adjusted r 2 -value and predicted r 2 -value using anova indicate that the quadratic model is more accurate than the linear one. adequate precision is used to measure the signal to noise ratio. the ratio greater than 4 is desirable. in the thinning degree model and the relative height model, the adequate precisions are 27.7014 and 15.1235 respectively, indicating adequate signals. these models can be used to navigate the design space. the lack-of-fit is not significant relative to the pure error. non-significant lack-of-fit is good. table 5 anova result for relative height model source sum of squares degree of freedom mean square f-value p-value significance model 0.0836 9 0.0093 25.93 25.93 significant a-a 0.0036 1 0.0036 10.08 10.08 b-b 0.0136 1 0.0136 37.99 37.99 c-c 0.0162 1 0.0162 45.21 45.21 ab 0.0006 1 0.0006 1.74 1.74 ac 0.0121 1 0.0121 33.77 33.77 bc 0.0009 1 0.0009 2.51 2.51 a² 0.0285 1 0.0285 79.64 79.64 b² 0.0103 1 0.0103 28.85 28.85 c² 0.0009 1 0.0009 2.45 2.45 residual 0.0018 5 0.0004 lack-of-fit 0.0009 3 0.0003 0.7115 0.7115 not significant pure error 0.0009 2 0.0004 corrected total 0.0854 14 r² 0.9790 adjusted r² 0.9413 predicted r 2 0.8039 adequate precision 15.1235 4.2. model for thinning degree and relative height the models of thinning degree and relative height are developed in terms of input parameters using rsm. from the experimental values, the coefficients of the regression equations are calculated. the regression coefficients of insignificant terms are eliminated based on anova results. consequently, the regression response surface models showing the thinning degree of the wall thickness ε and the relative height h* are expressed by eq. (1) and eq. (2) which show the final equation in terms of coded factors. 2 2 2 17.2 0.5 1.1125 0.1875 0.575 0.075 0.6 1.425 0.45 1.55 a b c a b a c b c a b c ε = + × + × + × − × × − × × + × × − × − × + × (1) 2 2 2 0.4633 0.02112 0.0412 0.045 0.0125 0.55 0.015 0.0879 0.0529 0.0154 * a b c a b a c b c a b c h = + × + × + × − × × + × × − × × − × − × − × (2) fig. 6(a) and fig. 6(b) represent the normal probability curves for thinning degree and relative height respectively to check the adequacy of models. as all points are in a straight line, it can be concluded that the models are adequate [29-30]. 256 advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 (a) thinning degree (b) relative height fig. 6 residual plots for the developed models 4.3. factor effect analysis 4.3.1. effect of process parameters on thinning degree ε the effects of process parameters on the objective are investigated using the contour plots (2d and 3d) which are considered in full parameter ranges, at each level of the focal position. fig. 7 shows that an increase of the forming time results in a decreased thinning degree, until the optimum value of around 30 min. the thinning degree is then increased with the continuous increase of the forming time. besides, when the strain temperature increases from 500°c to 530°c, the degree of thinning increases. this phenomenon can be explained as follows. when the forming time and deformation temperature increase, the grain grows faster. therefore, it reduces the deformation rate and deformation degree of the specimens. the degree of thickness distribution becomes uneven, the thinning degree at the dangerous position will increase [7, 11, 24]. as shown in fig. 7, when the forming pressure increases, the thinning degree increases. however, when the pressure increases beyond 0.8 mpa, the thinning degree of the wall thickness at the dangerous position decreases. this phenomenon can be explained as follows. when the strain rate is high, the time is not enough for the corresponding diffusion process to create the planes favorable for sliding, so the stress increases and the deformation degree of the specimen decreases [24]. (b) 3d interaction plots of forming pressure and deformation temperature fig. 7 effect of processing parameters on the thinning degree 257 (a) 2d perturbation plot of process parameters advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 (c) 3d interaction plots of forming pressure and forming time (d) 3d interaction plots of forming time and deformation temperature fig. 7 effect of processing parameters on the thinning degree (continued) 4.3.2 effect of process parameters on the relative height of product h* in fig. 8, it is shown that the influence of process parameters including forming pressure, deformation temperature, and forming time leads to the relative height of the product. as the forming pressure and deformation temperature increase, the relative height increases. however, when the forming pressure and strain temperature increase to a certain value, the relative height of the product tends to decrease. because of this, the higher strain rate and high temperature will make the grain microstructure of the material grow, reducing the possibility of deformation [24]. the forming time increases (from 20 to 40 min), and the relative height of the product increases accordingly. besides, with a long forming time, the thinning degree of the wall thickness increases. this may result in product destruction. (b) 3d interaction plots of forming pressure and deformation temperature (c) 3d interaction plots of forming pressure and forming time (d) 3d interaction plots of forming time and deformation temperature fig. 8 effect of processing parameters on the relative height of the product 258 (a) 2d perturbation plot of process parameters advances in technology innovation, vol. 6, no. 4, 2021, pp. 251-261 5. optimization results after building the statistical regression equation showing the relationship between process parameters and process response, the equation is used to solve the optimization problem. according to the discussion above, it can be concluded that the process parameters of forming pressure, deformation temperature, and forming time have significant and complex effects on the thinning degree of the wall thickness model. the optimization issue can be solved using rsm. table 6 shows that the thinning degree of the wall thickness ε of 13,121% is observed at p = 0.7 mpa, t = 500°c, and t = 31 min, respectively. table 6 optimization results using rsm constraints name goal lower limit upper limit lower weight upper weight importance a:a in range 0.7 0.9 1 1 3 b:b in range 500 530 1 1 3 c:c in range 20 40 1 1 3 r1 minimize 13 20 1 1 3 solutions number a b c r1 desirability selection 1 0.700 500.000 31.006 13.121 0.983 selected 2 0.700 500.000 31.123 13.121 0.983 3 0.700 500.013 30.671 13.125 0.982 4 0.700 500.000 30.806 13.126 0.982 5 0.700 500.000 31.616 13.127 0.982 6. conclusions in this study, an integrative approach using the physical experiment, rsm model, and the df algorithm was used to optimize the process parameters concerning the thinning degree of the wall thickness. the relationship between process parameters and the thinning degree was constructed through rsm and experimental data. df was applied to determine the optimal design variables and the response. the main conclusions from the research results of the current work can be drawn as follows: (1) the thinning degree is decreased with a higher value of the forming time until it reaches the optimal points. with increased factors, the thinning degree increases. additionally, an increased forming pressure or deformation temperature results in a higher thinning degree value. 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[30] c. s. syan and g. ramsoobag, “a differential evolution optimization approach for parameters estimation of truncated and censored failure time data,” advances in technology innovation, vol. 3, no. 4, pp. 185-194, october 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 261 6___aiti#8509___216-227 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 optimization of centrifugal pump based on impeller-volute interactions maitrik shah*, beena baloni, salim channiwala department of mechanical engineering, sardar vallabhbhai national institute of technology, gujarat, india received 19 september 2021; received in revised form 06 december 2021; accepted 07 december 2021 doi: https://doi.org/10.46604/aiti.2022.8509 abstract the design and off-design performance of a centrifugal pump largely depends on geomechanical parameters. this study aims at enhancing the performance by optimizing three geomechanical parameters of impeller-volute interactions. the present optimization is carried out using the taguchi method combined with a numerical approach. a comparison between the base and optimized pumps is presented under the design and off-design conditions based on numerical and experimental analyses. the numerical results reveal that, compared to the base pump, the optimized pump shows the improved performance through uniform pressure distribution in the impeller, the reduced low-pressure region towards a blade’s leading edge, and the stable total pressure at the impeller-volute interaction zone. the experimental results suggest that the optimized pump covers a wider range of operation, and its best efficiency point (bep) is 10%, 5%, and 12% higher in flow rate, head, and efficiency, as compared to the base one. keywords: centrifugal pump, optimization, design of experiment, experimental analysis, numerical analysis 1. introduction a centrifugal pump, which is the highly recommended and utilized pump to date, is a principal member of the power-consuming turbomachine family. it is widely used in industrial areas such as water, processing, and chemical industries to increase fluid pressure. it occupies a large share of electricity consumption of the world’s total generated electricity. therefore, high pump efficiency is essential in reducing power requirements and reaping economic benefits. the constructive geometry of the centrifugal pump is developed with its rotor (impeller) and stator (volute). the fluid energy is enhanced by the conversion of mechanical work in the impeller, whereas the volute does energy transformation to further enhance the pressure energy of the fluid. there are two methods for improving the centrifugal pump performance in general. the first is to investigate the impact of a single parameter or structure. the second is to examine the combined effects of various parameters on the pump performance using computational equations or algorithms. many studies have concentrated on enhancing the pump efficiency by optimizing the construction of centrifugal pumps, which allows for the hydraulically smooth fluid flow and mechanically stiff operating behavior. the impeller and volute in a centrifugal pump assembly can significantly influence the pump performance. researchers have conducted the impeller optimization followed by the volute or diffuser optimization, but the impeller and volute optimization have never been conducted together. also, in the studies of impeller optimization, the researchers concentrated on the main parameters of blades, i.e., the meridional shape, wrap angle, thickness, total number, inlet-outlet angle, width at inlet-outlet, profile curvature, shape of leading edge (le), and trailing edge (te). for the volute optimization, the researchers focused on the volute inlet width, cross-section shape, tongue angle, outlet position, and diffuser cone angle. * corresponding author. e-mail address: maitrikshah2006@gmail.com tel: +91-972-5852858 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 in the impeller optimization design, the pump hydraulic performance is more influenced by the number of blades and the exit blade angles. literature suggests that the generated head is linearly proportional to the number of blades and not apparent with the impeller outlet width [1]. the pump’s flow rate decreased due to the increased blockage areas by increasing the blade numbers of the impeller [2]. also, the friction and mixing losses are increased with more blades. elyamin et al. [3] found that the pump performance was improved with seven blades than nine blades in the impeller. the blades with small exit angles outperform the blades with large exit angles. the wear on the blade outlet can be diminished with the reduced blade exit angles [4]. the increment in te blade angle resulted in 2.32% higher hydraulic efficiency [5]. the rounding with a fillet radius of 3.5 mm at te improved the pump efficiency by more than 10% for a high-flow centrifugal mixed flow pump [6]. the bezier curve optimization in impeller design enhanced the efficiency of a double suction centrifugal pump [7]. subsequently, bee colony algorithms improve the impeller design by optimizing the structural characteristics of the impeller’s inlet-outlet, such as diameter, width, and blade angle. derakhshan et al. [8] found that the pump efficiency was enhanced by 3.59% for the optimized centrifugal pump. in the work of xu et al. [9] and liet al [10], the orthogonal table method was used to optimize the centrifugal pump performance, which improved efficiency and reduced critical net positive suction head (npshc) by 3.09% and 1.45 meters, respectively. sekino et al. [11] performed the optimization design for the double suction centrifugal pump with the help of design of experiments (doe) and computational fluid dynamics (cfd). the results showed a 4% rise in efficiency. in addition, the optimization of volute reduced the internal cross-sectional area to 90% of the primary volute, resulting in an increment in head and efficiency for the optimized impeller model [12]. a low specific speed centrifugal pump with several volute configurations (spiral, concentric, and double) and two distinct impeller designs (four and five blades) was evaluated to optimize the impeller and volute together. baun et al. [13] found a 5% head gain and a corresponding efficiency gain for a five-blade impeller with spiral volute. in the radial flow low specific speed (ns) centrifugal pump, the generated radial force was high at a high flow rate. therefore, stepanoff [14] suggested a volute design with a circular cross-section that provided better hydraulic performance and lower radial force, especially at a high flow rate [15]. the mixing losses at the impeller-volute interaction zone were measured by the entropy generation and minimized by the optimum selection of the design variables established with the help of an orthogonal matrix [16]. the literature shows that understanding and handling the design parameters can give a better and more optimized design. however, there is a need to focus on the combined effect of the impeller and volute design parameters for optimizing the centrifugal pump. therefore, the present study incorporates numerical and experimental analyses to optimize the pump performance using taguchi’s orthogonal techniques, based on the parameters such as the volute inlet width to impeller outlet width ratio b3/b2, number of blades z, and blade outlet angle β2. 2. numerical simulation the numerical analysis approach with the help of the reynolds averaged navier-stokes (rans) equation is a widely used tool for visualizing the flow inside the 3d flow domain. the present numerical analysis is carried out for a single-stage centrifugal pump having a specific speed of 22.5 (metric unit). its impeller and volute are designed based on meridional plane velocity and constant velocity methods, respectively. the geometrical model of the single-stage radial flow centrifugal pump follows iso 2858 [17]. the main geometric parameters of the impeller and volute are obtained using the creo parametric tool and are shown in table 1. the computational model consists of an impeller, volute, suction pipe, and discharge pipe, as shown in fig. 1. the numerical analysis is performed with the help of ansys commercial software packages for grid generation and cfd setup. the unstructured computational grid is selected due to less computational time and is developed separately by the ansys meshing tool for suction pipe, impeller, volute, and discharge pipe. special attention is given to mesh quality for impeller and 217 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 volute grid generation. the inflation method is used for mesh generation at the fluid-structure interaction areas for calculating the structure’s effect on the fluid flow region. the accuracy of the numerically obtained results depends on the quality of the computing grid, especially in the situation of dominating the decelerating flow in the pump. the grid refining increases the computational time and is critical near the impeller wall region due to mesh freezing. in the present work, the fluid domain has y + values of 20 to 50 in critical areas for better accuracy of findings [18]. the expansion ratio is 1.5 near the impeller and volute wall, and the maximum aspect ratio is 150. the first layer height is 10e-4 m close to the wall, and the number of inflation layers is 10. the grid convergence study is carried out with eight different grids (0.5, 0.75, 1.5, 2.15, 1.5, 3.01, 3.5, and 4 million), as shown in fig. 2. the grid convergence test is performed between the pump efficiency and the grid elements [18]. fig. 2 reveals that the efficiency variation is within 0.9% for a 3.5 million grid. the larger mesh sizes increase the computational time with no significant change in pump efficiency. therefore, 3.5 million grid elements are selected for simulation. multiple frames of reference are applied to stationary and rotating fluid domains. the suction pipe, volute, and discharge pipe are set as stationary frames, and the impeller is designated as a rotating frame at 2930 rpm. the interface between two stationary components is set to the general grid connection, and the stationary-rotary domain is set to the rotor-stator “frozen rotor” interface [18]. a fluid is defined as water at 25 o c. the boundary conditions are applied as total pressure (1.01325 bar) at the inlet and mass flow rate (13.8611 kg/sec) at the outlet [19]. a frozen rotor is used to define the sliding interface. the control volume’s surface roughness is set at 50 µm. the pump’s physical surfaces are configured as no-slip walls [20], and the conventional wall function is applied to the turbulent flow near-wall. the rng k-ɛ model is used for the present analysis [19]. for the convergence criterion, the equation of residual’s root-mean-square (rms) value for all sets of the rans equation must be at least 1.0e-6. the hydraulic design is created to provide a broader operational range without recirculation and to achieve the operating range of best efficiency point (bep). when q << qopt, cfd studies are required for higher partial flow rates. the variable mass flow is applied to an outlet boundary condition for a full outlet diameter (od) of impeller. the numerical results are discussed and compared with experimental results in section 5. table 1 centrifugal pump parameters parameters value parameters value impeller suction eye diameter, d1 (mm) 80 impeller blade number, z (nos.) 7 impeller outlet diameter, d2 (mm) 172 impeller blade thickness, δ (mm) 4 impeller outlet width, b2 (mm) 14 volute base diameter, d3 (mm) 189 impeller blade inlet angle, β1 (°) 24 volute inlet width, b3 (mm) 23 impeller blade outlet angle, β2 (°) 36 volute tongue angle, φo (°) 24 impeller blade wrap angle, φ (°) 127 volute outlet diameter, dd (mm) 65 70 75 80 85 90 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 p u m p e ff ic ie n cy η % grid elements (million) fig. 1 the fluid domain of centrifugal pump fig. 2 grid convergence test 218 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 3. orthogonal optimization taguchi’s orthogonal array-based doe technique is used to optimize the centrifugal pump model. the orthogonal table approach helps analyze the impact of specified parameters on the model. the principle of this approach is to determine a few parameters from experimental factors through an orthogonal array and simulate the results. these results are based on the effect of each parameter on the aggregate findings and the selection of the optimal parameter combination. in the current study, the performance of the base pump can be improved by a steeper performance curve. it can be achieved by modifying the blade number, impeller blade outlet width, and blade outlet angle [21]. the radial and semi-axial impellers (with a specific speed, 10 < nq < 120) are designed with 5 to 7 blades [21]. the small blade number means minor blockage due to blade thickness. the small values of blade number reduce the power overload and increase the pump efficiency. the small blade number also decreases the pump shut-off head. therefore, the blade numbers z selected for the current study are 5, 6, and 7. the outlet angles β2 of radial impellers with 5 to 7 blades are commonly in the range of 12° to 45°, including the deviation angle (predominantly 19° to 36°) [21]. matching outlet blade angle and outlet width is an optimization task for increasing the efficiency and stability of the q-h curve. the lower the impeller blade outlet angle, the steeper the performance characteristics and the lower the impeller flow coefficient. the selected blade angles β2 in the current optimization study are 12°, 19°, and 36°. the optimized opening width of the volute inlet and impeller outlet will reduce shock losses. gülich [21] has suggested that the volute inlet width to impeller outlet width ratio b3/b2 should be in the range of 1.25 to 2.5. thus, in the present optimization study, the proportion of b3/b2 is selected in the range of 1.64, 2, and 2.33. the doe techniques are used to create the orthogonal tables of the three chosen parameters. table 2 shows the selected three distinct levels for each element. nine groups of orthogonal test methods are built up according to the l9 orthogonal table and are represented in table 3. a numerical analysis is performed in ansys cfx for nine orthogonal design scheme parameters. the numerical results are utilized to determine the best parameter combinations. table 4 shows the head, efficiency, and percentage of total pressure loss in the volute for nine orthogonal design methods. the numerical findings are used to determine the optimal combination of the lowest and highest best parameters, known as the s/n ratio, which is expressed by eqs. (1) and (2), respectively. the response table for each quality characteristic is prepared to find the best combination of parameters depending on each quality characteristic’s s/n ratio and contribution, as shown in table 5. ( )21 10logs = y n n − ∑ (1) 2 1 1 10logs = n n y  −     ∑ (2) the response table for each quality characteristic is prepared to find the best combination of parameters depending on each quality characteristic’s s/n ratio and contribution, as shown in table 5. the sequence in which parameters have an impact on head, efficiency, and volute loss follows a3-b3-c1, a3-b1-c2, and a1-b1-c1, respectively. the results of all three configurations are compared with numerical simulation. the maximum centrifugal pump efficiency with minimum total pressure loss in volute is the selection criteria for the optimal sets. therefore, the minimum losses are obtained with the combination of a1-b1-c1. the change in head, efficiency, and total pressure drop occurs in volute for a3-b3-c1 (+2.9%, -1.06%, and +17.63%) and a3-b1-c2 (+3.8%, -1.29%, and +12.12%), as compared to the optimum combination parameters a1-b1-c1. the uniform flow results in an efficient flow. the optimized models propose the ratio of volute inlet width to impeller outlet width b3/b2 = 2, blade outlet angle β2 = 19°, and blade number z = 6. 219 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 table 2 factor levels in orthogonal experiments level factor a b c z (nos.) b3/b2 β2° 1 6 2 19 2 5 1.64 12 3 7 2.33 36 table 3 design of an orthogonal table table 4 numerical results of orthogonal designs scheme serial number design parameters scheme head (m) efficiency η (%) total pressure drops in volute (%) a b c z (nos.) b3/b2 β2° 1 a1 b1 c1 6 200 19 1 41.97 85.16 6.35 2 a1 b2 c2 6 167 12 2 40.34 83.76 6.83 3 a1 b3 c3 6 233 36 3 42.63 81.32 8.55 4 a2 b1 c2 5 200 12 4 40.68 85.88 6.97 5 a2 b2 c3 5 167 36 5 40.54 82.31 8.23 6 a2 b3 c1 5 233 19 6 40.11 85.09 6.80 7 a3 b1 c3 7 200 36 7 39.98 85.09 7.34 8 a3 b2 c1 7 167 19 8 45.21 83.55 7.15 9 a3 b3 c2 7 233 12 9 44.35 84.95 7.71 table 5 response table for different quality characteristics levels maximum variation in the head (h) at the pump outlet maximum variation in the pump efficiency η (%) minimum variation in the total pressure po (%) loss inside the volute a b c a b c a b c 1 32.39 32.23 32.54 38.42 38.63 38.55 -17.13 -16.74 -16.60 2 32.14 32.46 32.41 38.53 38.40 38.57 -17.27 -17.36 -17.10 3 32.69 32.53 32.26 38.54 38.46 38.37 -17.38 -17.68 -18.09 delta 0.56 0.30 0.28 0.12 0.22 0.20 0.25 0.93 1.49 rank 1 3 2 3 1 2 3 2 1 % contribution 1 0.55 0.50 0.52 1 0.91 0.17 0.63 1 4. experimental test setup experimental analysis of the centrifugal pump is carried out in submerged conditions as per iso 9906 [22]. fig. 3 represents a line diagram for the experimental setup and the tested centrifugal pump. the total head is measured by a pressure transducer installed before the valve. an electromagnetic flowmeter is used to measure the flow and is installed after the valve in the discharge line. the centrifugal pump is driven by an electric motor having a rated capacity of 415 voltage, 15 hp power output, and 2930 rpm. table 6 shows the specifications of the instruments used for the experimental test setup. (a) line diagram of the experimental setup (b) tested centrifugal pump fig. 3 experimental setup 220 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 table 6 specification of instruments measured parameter equipment name range least count accuracy pressure pressure transducer 0 to 5 bar 0.001 ± 0.2% flow rate electromagnetic flowmeter 0 to 217 m 3 /hr 0.06 ± 0.2% voltage voltmeter 50 to 450 v 0.01 v ± 0.2% power factor, cos ϕ cos phi meter 0.1 to 0.99 0.001 ± 0.1% current ammeter 0.250 a to 80 a 0.001 a ± 0.2% watt energy meter 24 w to 24 kw 1 w ± 0.2% shaft speed slip speed meter 1800 to 3000 rpm 1 rpm ± 0.2% the uncertainty in the overall measured efficiency is calculated by the kline and mcclintock uncertainty method [23]. the uncertainty in the overall efficiency is ± 2.24% and within the permissible limit, i.e., ± 4.0%, as per iso 9906 grade 2 [22]. the repeatability of the experimental setup is checked and found in an acceptable range of 95% confidence limits. 5. results and discussion taguchi’s orthogonal array-based design of experiment technique and ansys cfx simulation are performed to optimize the selected base centrifugal pump. based on the optimization results, a further comparison is made between the base and optimized case under the design and off-design conditions. the characteristics of pump performance are measured and plotted for both the pumps based on the results of numerical simulation and experimental analysis. at first, the numerical simulation for the base and optimized pump are carried out at 0.6 qd, 0.8 qd, 1.0 qd, and 1.2 qd. the simulation results are analyzed and discussed based on the internal flow behavior within the impeller and fluid domain. an experimental analysis is also carried out with both the pumps to get the performance parameters for the experimental operating range, i.e., the shut-off to maximum flow rate. the results are discussed below. 5.1. results of numerical simulation the numerical analysis is used to evaluate and compare the internal flow behavior of the optimized pump and the base pump. the characteristics of pump performance are measured with contour plots for 0.6 qd, 0.8 qd, 1 qd, and 1.20 qd flow conditions. fig. 4 depicts the static pressure distribution at the mid-span of impeller and volute for the base and optimized pump under the design and off-design conditions. the pressure progressively rises along with the impeller blade path and reaches a peak at te. as in the passage of the impeller, the mechanical energy is converted into the hydraulic energy of the fluid. uniform pressure distribution is shown in the impeller flow path for the design flow, and non-uniform pressure distribution is visualized for the off-design flow near the blade’s le and te areas. the pressure is lowest towards the blade’s le areas in the base pump and optimized pump (p1, p1’, q1, q1’, r1, r1’, s1, and s1’ in figs. 4(a)-(h), respectively), where cavitation may arise [24]. the pressure is uniformly distributed in the volute flow path and reaches the peak in the volute diffuser outlet. the convergence of kinetic energy to pressure energy of the fluid takes place into volute flow passage. the non-uniform pressure cloud is observed at the impeller-volute interaction (mixing) zone in the base pump, while the uniform one is visualized in the optimized pump (p2, p2’, q2, q2’, r2, r2’, s2, and s2’ in figs. 4(a)-(h), respectively). despite the high pressure in the base pump volute, the secondary flow losses and the non-uniformity of the flow at the impeller outlet increase and the energy stratification decreases [3]. the result shows higher energy loss in the base pump rather than the optimized pump. in the case of the base configuration, one can observe the same high-pressure contours near the outlet periphery of impeller blade passage as well as the inlet of volute passage (p3, q3, r3, and s3 in figs. 4(a)-(d), respectively). at the same time, the pressure distribution is more uniform at the rotor-stator interaction zone in the optimized pump (p3’, q3’, r3’, and s3’ in figs. 4(e)-(h), respectively). the non-uniform pressure contours at the rotor-stator interaction zone lead to the extreme pressure 221 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 pulsation, unsteady forces, and shock losses with vibration in the impeller [25]. overall, a more uniform flow is observed at the optimized pump’s design and off-design condition than the base pump. however, the pressure distribution is more consistent at both impellers’ design conditions than off-design conditions. the effect of the blade number (z), blade exit angle (β2°), and width ratio (b3/b2) on the vortex formation and losses in the mixing zone by velocity contours in volute and vectors in the impeller are represented in fig. 5. the base model results in the high fluid flow velocity and the increased blade friction losses, whereas the optimum model enables the energy stratification inside the flow path and vortex formation near the impeller exit [3]. the intensity of the vortex is higher at a lower flow rate, which disappears at the design and high flow rate conditions [26]. (it is seen from figs. 5(a), (b), (e), and (f), respectively.) the vortex formation in the impeller passages influences the pump’s developed pressure head and efficiency [27]. the higher velocity gradient at volute zone in the base model (l1, m1, n1, and o1 in figs. 5(a)-(d), respectively) results in the hydraulic excitation forces and more mixing losses than the optimized case (l1’, m1’, n1’, and o1’ in figs. 5(e)-(h), respectively). the uniform accelerating vector pattern observed following the impeller throat passage in the optimized pump (1.0 qd and 1.2 qd) and base pump (1.2 qd) illustrates the absence of vortex, reduction in hydraulic flow losses, and increase in efficiency. in general, the non-uniformity in flow-velocity is higher at the off-design flow than the design flow, which results in the generation of the vortex (figs. 5(a), (b), (c), (e), and (f), respectively). fig. 6 reveals a higher value of total pressure in the base pump compared to the optimized pump. however, one can also observe high variations of total pressure across the zone of impeller-volute interaction (a1, a2, b1, b2, c1, c2, d1, and d2 in figs. 6(a)-(d), respectively). it indicates more hydraulic losses in the base pump, whereas the more uniform total pressure is observed at the impeller-volute interaction zone for the optimized case (a1’, a2’, b1’, b2’, c1’, c2’, d1’, and d2’ in figs. 6(e)-(h), respectively). the higher the total pressure variation, the more the hydraulic losses [3]. results suggest that the rise in pressure head is with the increase in blade number, the width ratio influences the mixing losses, and the smaller blade exit angle gives better performance of the pump. the optimized pump shows lower losses and better efficiency compared to the base pump because of the balance between the selected parameters. (a) 0.6 qd (base) (b) 0.8 qd (base) (c) 1.0 qd (base) (d) 1.2 qd (base) (e) 0.6 qd (optimized) (f) 0.8 qd (optimized) (g) 1.0 qd (optimized) (h) 1.2 qd (optimized) fig. 4 pressure distribution in the base and optimized pump impellers p1 p2 p3 q3 q2 q1 r1 r2 r3 s1 s2 s3 p1’ p2’ p3’ q3’ q2’ q1’ r1’ r2’ r3’ s1’ s2’ s3’ 222 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 (a) 0.6 qd (base) (b) 0.8 qd (base) (c) 1.0 qd (base) (d) 1.2 qd (base) (e) 0.6 qd (optimized) (f) 0.8 qd (optimized) (g) 1.0 qd (optimized) (h) 1.2 qd (optimized) fig. 5 mid-span velocity distribution in the volute and vector distribution in the impeller of the base and optimized pumps (a) 0.6 qd (base) (b) 0.8 qd (base) (c) 1.0 qd (base) (d) 1.2 qd (base) (e) 0.6 qd (optimized) (f) 0.8 qd (optimized) (g) 1.0 qd (optimized) (h) 1.2 qd (optimized) fig. 6 total pressure distribution in the volute and impeller mid-span of the base and optimized pump a2 a1 b1 b2 c2 c1 d1 d2 a2’ a1’ b1’ b2’ c2’ c1’ d1’ d2’ vortex vortex vortex vortex vortex m1 m1’ n1 n1’ o1 o1’ l1’ l1 223 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 5.2. results of experimental analysis the results of numerical analysis suggest better flow conditions in the optimized pump than the base pump. the experimental investigation is carried out to better understand the actual flow within the pump domain, and the results are plotted in a non-dimensional form. tests are performed with the base and optimized centrifugal pump, as shown in fig. 7. both pumps have the same specific speed, and geometrical parameters except the parameters considered for optimization. table 7 represents the variable geometric parameters details for the base and optimized centrifugal pump. experimental analysis is carried out in submerged conditions as per iso 9906 for a complete operating range of centrifugal pumps, i.e., from shut-off to maximum flow conditions [16]. fig. 8 represents the variation of the non-dimensional head for different non-dimensional mass flow rates throughout the operating range of the base and optimized pump. the figure reveals that the optimized pump covers a wider range of mass flow with a higher developed head than the base pump. at bep, the optimized pump has the flow with 1.13 qd and head with 0.97 hd, which is higher about 10% and 5.4% of the base pump’s flow and head, respectively. the pump efficiency is calculated based on the ratio of pump output power to the pump input power [1]. the variation in efficiency at non-dimensional flow rates is shown in fig. 9. one can observe a wider plateau of efficiency (η) curve in the case of the optimized pump. in the base one, the width of the plateau is reduced a lot. better efficiency is observed in the case of the optimized pump compared to the base pump. fig. 9 reveals that the optimized pump efficiency (η) is 72% which is 12% higher than the base pump value, i.e., 60%, at bep. the experimental readings show a high amount of power consumption by the base pump to achieve the desired output compared to the optimized pump. it leads to reducing the pump efficiency. the losses in the base pump indicate higher secondary flow losses at the impeller outlet to the volute inlet as justified in numerical results. the head and efficiency plots suggest better flow conditions and performance in the case of the optimized pump compared to the base one [16]. therefore, one can summarize that an appropriate selection of optimization parameters helps enhance the pump’s performance. fig. 10 compares the numerical and experimental heads developed at four abreast flow rates. the figure suggests a minor deviation at a low flow rate, which increases at a higher flow rate. the maximum variation of 3.2% is observed for the flow rate 1.2 qd. (a) base impeller (b) base volute (c) optimized impeller (d) optimized volute fig. 7 the base and optimized centrifugal pump table 7 details of variable geometrical parameters module parameters value base case optimized case impeller b2 14 mm 19 mm β2 36° 19° z 7 (nos.) 6 (nos.) volute b3 23 mm 38 mm b3/b2 1.64 2 224 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 6. summary and conclusions in the present study, three design parameters are chosen for orthogonal design experiments, and the ideal combination of parameters is decided using numerical simulation data. the numerical results reveal that the pressure cloud generated between the rotor-stator interaction zone leads to the increased total pressure loss and high energy loss in the base pump. there is a significant impact of the vortex formation observed at low flow rates and diminished at high flow rates. the base and optimized pump’s experimental performance are carried out to check the performance enhancement of the base pump by optimization. the finding of this study can be summarized as follows. (1) the width ratio b3/b2 has the most significant impact on the flow rate by minimizing the shock and secondary flow losses. also, the number of blades z strongly influences the head, and the blade outlet angle β2 has a strong impact on the pump efficiency. (2) the optimized pump gives a wider range of operation with an increase of 10%, 5%, and 12% in flow rate, head, and efficiency, respectively, as compared to the base centrifugal pump. [1.02 qd, 0.92 hd] [1.13 qd, 0.97 hd] 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0.0 0.3 0.5 0.8 1.0 1.3 1.5 1.8 2.0 2.3 2.5 h ea d , h /h d mass flow, q/qd base pump optimize pump base pump bep optimize pump bep [1.02 qd, 0.60 ηpump] [1.13 qd, 0.72 ηpump] 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.0 0.3 0.5 0.8 1.0 1.3 1.5 1.8 2.0 2.3 2.5 e ff ic ie n cy , η (1 0 0 % ) mass flow, q/qd base pump optimize pump base pump bep optimize pump bep 0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 0.6 0.8 1.0 1.2 h ea d , h /h d mass flow, q/qd experiment head simulation head fig. 8 variation in non-dimensional mass flow v/s head fig. 9 variation in non-dimensional mass flow v/s efficiency fig. 10 numerical and experimental head comparison of the optimized pump 225 advances in technology innovation, vol. 7, no. 3, 2022, pp. 216-227 acknowledgments the authors would like to thank arvind pumps pvt. ltd., ahmedabad, india, for facilitating testing facilities. conflicts of interest the authors declare no conflict of interest. references [1] g. peng, s. hong, h. chang, z. zhang, and f. fan, “optimization design of multistage pump impeller based on response surface methodology,” journal of theoretical and applied mechanics, vol. 59, no. 4, pp. 595-609, 2021. 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[27] r. tao, x. zhao, and z. wang, “evaluating the transient energy dissipation in a centrifugal impeller under rotor-stator interaction,” entropy, vol. 21, no. 3, 271, march 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 227  advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 a research survey of electronic commerce innovation: evidence from the literature kai-yu tang 1 , chun-hua hsiao 2,* , mei-chun chen 3 1 department of international business, ming chuan university, taipei, taiwan 2 department of marketing, kainan university, taoyuan, taiwan 3 department of information management, vanung university, taoyuan, taiwan received 11 april 2019; received in revised form 11 june 2019; accepted 02 july 2019 abstract the development of technology has ignited many innovations in business management, especially in the electronic commerce area. the essential example, that is, online stores and online shopping, is a critical evolution and innovation from traditional brick-and-mortar stores to clicks and mortar. following previous research (van oorschot et al.), this present study adopted bibliometric and keyword analysis to review the main characteristics of electronic commerce innovations. focused on the academic sources, the research data used in this study were searched for and collected from the web of science (wos), a renowned academic database which covers the most influential research journals in electronic commerce. based on a combination of several keywords related to “innovation” and “electronic commerce,” the keyword search in the wos was conducted in may 2019. as a result, a total of 334 research articles related to electronic commerce innovations were collected. derived from the bibliometric analysis, some keywords that were seldom used in the earlier decade (2000-2009), but which rapidly grew in use in the recent decade (2010-2018) were found, including m-commerce, platforms, social commerce, online review, and co-creation. in addition, the top 10 influential articles listed in each of the two decades were identified. the results show some of the research trajectories in ec innovations. in the first decade (2000-2009), the top 10 papers focused on traditional it adoption, such as self-service technology, enterprise resource planning systems, and the adoption of general attitude-intention theories such as the technology acceptance model. in the recent decade (2010-2018), researchers have shown more diverse interest in innovative ec applications, such as rfid applications, cloud computing, crowdsourcing, etc. accompanying these ec innovation contexts, in addition to general attitude-intention theories, more theories such as signaling theory, have been adopted. keywords: electronic commerce innovations, research trajectory, systemic literature survey 1. introduction nowadays, one may see many innovations in the development of electronic commerce (ec). for example, bhattacherjee [1] introduced some e-commerce brokerage services, and eastin [2] provided some examples of web technologies applied to consumers’ purchasing behavior, such as online shopping, online banking, and even online investing. indeed, these ec innovations have become part of our daily life. in recent studies, researchers have brought more advanced and innovative ideas into ec business research. while cui et al [3] mentioned some benefits of ec innovations in growing economies in rural china, escobar-rodríguez and bonsón-fernández [4] pointed out other ec applications in the spanish fashion industry. more recently, vakulenko et al. [5] offered the possibility to create an e-customer journey map through innovative management of *corresponding author. e-mail address: maehsiao@gmail.com tel.: +886-3-341-2500; fax: +886-3-3412430 advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 248 ec services. these original ideas have acted as a lighthouse for ec business, shedding light on the next-generation ec innovations. however, few studies have focused on the analysis of ec innovations from an academic viewpoint. it is especially necessary because the rigorous nature of academic research has enhanced the reliability of the innovations in real business practices. moreover, researchers can follow some performance indicators of scientific research, such as times cited per year, to identify and trace the high impact ideas, ec innovative business models or practices. three purposes of this study were therefore formed as follows. first is ranking the most productive countries and journal publications in the ec innovations literature; second is identifying the most influential research articles across two decades of observation (the first decade: 2000-2009; the recent decade: 2010-2018); and the last one is highlighting the most critical innovative practices of ec in the two decades of research. 2. data and methods 2.1. the process of data inclusion in this paper, a systematic approach for data inclusion was adopted to achieve the above three research questions. the first process of data inclusion was to identify the keywords related to innovation and electronic commerce from the literature. the selection of keywords referred to previous review studies in the fields of innovation management and electronic commerce. in the field of innovation management, randhawa et al. [6] reviewed “open innovation” in product innovation research. using bibliometric analysis, van oorschot et al. [7] analyzed the “innovation adoption” literature with the issue of technology and social change. in electronic commerce literature, akter and wamba [8] provided a systematic review of “e-commerce” in electronic markets. han et al. [9] conducted a literature survey of “social commerce” in e-commerce research. more recently, gursoy’s [10] presented a critical review to highlight the importance of consumers’ “online review” in ec platforms. as such, we adopted the most popular terminology used in the above reviews, such as “innovative,” “innovation,” “electronic commerce,” “e-commerce,” “e-tailer,” “social commerce,” and “online review” as the keywords for this search. the second step was to select the sourcing database. the web of science (wos) was selected as the primary source as it covers the most influential ec journals in the categories of business, management, and information science, including the international journal of electronic commerce, electronic commerce research and applications, and mis quarterly. as such, the above seven terms were used as keywords for searching for high-quality electronic commerce innovation research in terms of citation counts. (brouthers et al.) next, two researchers carefully removed those redundant and incomplete items selected during the search. a final total of 334 articles published from 2000 to 2018 were obtained as the literature of research interest. the process of data inclusion was completed on 22 may 2019. more information for the selection of highly cited articles and keywords is provided below. 2.2. the selection of high impact articles in this study, the numbers of articles published and their authorship were counted and are shown in table 1. note that only the number of non-repeated authors was reported to show the trend of researchers involved in the field. as shown in table 1, a total of 118 articles with 256 authors in the first decade were found (2000-2009). furthermore, figure 1 shows a highly correlated pattern of publications between the numbers of published papers and involved authors, with a pearson correlation coefficient of 0.98. the scale of publications increased to 216 articles and 558 authors in the recent decade (2010-2018), which approximately doubled the number of articles and authors in the first decade. the growth of authors involved in the ec innovation research in the last five years (2014-2018, as shown in fig. 1) is especially noteworthy, indicating the great attraction of ec innovation research to academics. in this study, we adopted a bibliometric analysis to identify the most influential among the 334 articles for each decade. the main idea of bibliometric analysis is to reveal the impact of scientific advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 249 publications. the two often-used bibliometric indicators, total times cited (citations) and times cited per year (average citations), were to identify the most influential articles of ec innovation. all 334 articles in this analysis had received a total of 13,858 citations. the citation information was also collected from the wos document by document, providing evidence of the most critical practices in electronic commerce innovation. the pilot results of the selection of high impact articles are shown in the next section. furthermore, based on the calculation of total citations received by journal publications and the country in which the researchers are affiliated, the indicator of scientific performance (i.e., h-index) was also provided for the analysis of the most high-impact journals and productive countries in the field. table 1 trend of ec innovation research: articles published and authors involved year articles published authors (non-repeated) 2000 5 8 2001 13 31 2002 8 13 2003 11 31 2004 12 20 2005 14 33 2006 14 30 2007 11 22 2008 9 19 2009 21 49 sub-total (2000-2009) 118 256 2010 28 63 2011 15 36 2012 19 55 2013 11 23 2014 13 24 2015 26 71 2016 31 86 2017 38 94 2018 35 96 sub-total (2010-2018) 216 558 total (2000-2018) 334 814 fig. 1 the trend of ec innovation research: articles and authors 2.3. keyword analysis following previous scientometric research [11], we used a keyword analysis to decompose the most valuable content of the corpus from these 334 ec innovation articles. all the wording in the title, keyword, and abstract were gathered. some insignificant stop words were excluded, such as “and,’’ “at,” ‘‘in,” “above,” “under,” and so on. other terms with similar meanings in the context of ec innovation were aligned, for example, “electronic commerce,” “e-commerce,” “innovation,” and “innovations.” next, a process of scraping common terms was conducted to help identify those keywords which are discriminative for representing the main characteristics of ec innovation research. advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 250 after the list of keywords was aligned, each keyword was then matched and counted if it appeared in a particular article. note that each article may have multiple keywords. only the keywords which appeared in different articles were counted and accumulated; however, those keywords repeatedly used in a single article were counted once. accordingly, a total of 5,211 keywords were obtained. based on the frequency count, the most critical keywords with significant growth trends and decline trends were selected. a further comparison of selected keywords for the two periods of research (period i: 2000-2009, and period ii: 2010-2018) was conducted to identify the research trends in ec innovation. 3. results and discussion in line with the three purposes of this research, the results of the research survey in ec innovation literature are presented. first is the publication patterns in the ec innovation research, including the most productive countries, influential journals, and representative keywords that are frequently used. second is the most influential research articles in the first decade: 2000-2009. and the last one is the most influential research articles in the recent decade: 2010-2018. further discussions of the research changes over the past two decades are also provided. 3.1. the most productive country and journal publications in the ec innovation literature 3.1.1 . the most productive countries to measure each country’s productivity, only the first authors’ country affiliation was counted because the first author has a major contribution to the research. if the first author has multiple affiliations, the main affiliation was manually checked and coded. as a result, a total of 39 countries were found and listed in ec innovation publications as shown in table 2. we also found that authors from the first 10 countries contributed over 105 articles and 158 articles, accounting for over 89% and 73% of the total publications in the periods of 2000-2009 and 2010-2018, respectively. therefore, these countries were labeled as the top 10 productive countries in ec innovation research, namely the usa, taiwan, china, the uk, canada, australia, south korea, portugal, germany, and spain. to highlight the impact of the top 10 countries, the total citations received are included in parentheses. for example, usa (7309) means that all of the articles published by the authors affiliated with the usa received 7,309 citations in total. fig. 2 visualizes the distribution of ec innovation research with the number of publications, showing the publication trends of the most productive countries in ec innovation across the two phases (2000-2009 and 2010-2018). table 2 the most influential countries in the field of ec innovation # country (citations) number of articles published h-index active years 2000-2009 2010-2018 total trends 1 usa (7903) 59 52 111 (↓) 45 2000-2018 2 taiwan (1032) 15 18 33 (↑) 14 2004-2018 3 china (971) 3 34 37 (↑) 13 2003-2018 4 uk (773) 15 10 25 (↓) 11 2001-2018 5 canada (706) 4 5 9 (↑) 15 2001-2018 6 australia (392) 6 6 12 (-) 10 2000-2016 7 south korea (278) 2 6 8 (↑) 5 2004-2016 8 portugal (277) 0 5 5 (↑) 4 2014-2018 9 germany (212) 0 8 8 (↑) 5 2011-2018 10 spain (198) 1 14 15 (↑) 7 2008-2018 more specifically, the result indicates that over one-third of the publications were from the usa in terms of the total number of articles from 2000 to 2018, (n = 111, 33%); the usa also ranked as the most productive country in period i (n = 59, 50%), but not in period ii (n = 52, 24%). it shows a decreasing trend of ec innovation research in usa publications. however, the overall 7,903 citations of the usa were ranked as the first place, revealing that us researchers have a significant impact both in the quantity and quality of ec innovation research. we also found that the uk ranked second in the period i (n = 15, 13%) in terms of publications, but dropped rapidly in period ii (n = 10, 5%). this trend indicates that the researchers affiliated advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 251 with the usa and the uk have dominated the ec innovation research, but an increasing number of researchers from other countries have since joined the field. note that australia’s researchers showed a balanced performance in ec innovation across the two decades. fig. 2 the most productive country in the ec innovation research on the other hand, a growth pattern of ec innovation publications appeared in the remaining countries, led by taiwan. researchers from taiwan have been ranked as the second most productive academics in terms of overall citations received (1,032 times). a total of 15 articles published in period i (2000-2009) and 18 articles in period ii (2010-2018), demonstrating a growth trend of taiwan’s ec innovation research. china ranked third in terms of total citation times. china researchers published three articles in period i, and rapidly developed to the second in period ii (n = 34, 16%). the fifth to tenth countries are canada (#5), south korea (#7), portugal (#8), germany (#9), and spain (#10), while australia (#6) showed a balanced performance in ec innovation. all of them have ec innovation articles in both stages. the following countries (i.e., germany (#9) and portugal (#8)), however, started to publish ec innovation articles in 2011 and 2014, individually. this reveals that some potential research issues from europe and latin america are also worthy of follow-up attention. 3.1.2 the most influential journals fig. 3 the most influential journals in the ec innovation research table 3 shows the most influential journals in the ec innovation research between 2000 and 2018. based on brouthers et al.’s suggestion [12], the rankings of the most influential journals are based on the total number of citations, not on journal ranking or the number of journals published. as such, the results showed that the four journals grew in terms of publication trends ranked by citations received, while another four declined. as a leading journal with a growth trend, mis quarterly (misq) ranked first, with 39 articles receiving 3,729 citation counts, and the h-index was 24. the results suggest the importance of misq in ec innovation research. similarly, the following three journals with growth trends were information & management (7→10), the international journal of electronic commerce (5→12), and technological forecasting and social advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 252 change (4→9). the first two journals published at least 17 articles on ec innovation and received about a thousand citations each. technological forecasting and social change was active between 2004 to 2018 with 13 ec innovation articles published among which, focusing on the new applications of ec, wang et al.’s research [13] titled “understanding the determinants of rfid adoption in the manufacturing industry” was the most cited (176 citations). table 3 the most cited journals in the field of ec innovation # journal title (citations) number of articles published h-index active years 2000-2009 2010-2018 total trends 1 mis quarterly (3729) 8 31 39 (↑) 24 2002~2018 2 information & management (1482) 7 10 17 (↑) 12 2002~2016 3 international journal of electronic commerce (972) 5 12 17 (↑) 12 2000~2018 4 information systems research (949) 3 3 6 (-) 5 2001~2018 5 journal of marketing (556) 2 2 (↓) 2 2005~2009 6 management science (485) 2 2 4 (-) 4 2006~2017 7 internet research (456) 11 5 16 (↓) 11 2000~2018 8 organization science (428) 4 1 5 (↓) 5 2001~2017 9 technovation (399) 4 4 (↓) 4 2006~2009 10 technological forecasting and social change (329) 4 9 13 (↑) 6 2004~2018 note that the abbreviations of journal titles. misq is mis quarterly; i&m is information and management; ijec is international journal of electronic commerce; isr is information systems research; jm is journal of marketing; ms is management science; ir is internet research; os is organization science; tfsc is technological forecasting and social change. the remaining journals have mostly shown a downward trend in terms of the number of publications, including journal of marketing, internet research, organization science, and technovation. based on the analysis, only two articles related to ec innovation were published in the journal of marketing; however, the influence was considerable. for example, meuter et al.’s research [14] “choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies” was cited 2005 times, while li et al.’s article [15] “internet auction features as quality signals” was cited 68 times. the two articles pointed out some innovations of alternative service delivery modes and quality signals of the internet auction. these findings can be considered as the research fronts of the online-to-offline model and online review for online shopping. internet research published 16 articles on ec innovation, suggesting that the ec research has become mature and that researchers have turned their interest to new topics in the field. the publication trend of two journals was stagnant, but still active in recent years (information systems research: 2001-2018; management science: 2007-2017) and they received a number of citations from follow-up studies (information systems research: 949 times; management science: 485 times). the changes in publication patterns for the top 10 journals are also presented in figure 3. 3.1.3 the most frequently used keywords further analysis of publication patterns was conducted by using keyword analysis. in this study, a total of 5,210 keywords were obtained, among which 3,785 were found to show an increasing trend (more frequently used in the recent decade than in the earlier one), and the remaining 1,425 showed a decreasing trend. twenty keywords that represent some unique attributes and which are frequently used in the ec innovation research are listed in table 4. the values in each cell are the counts of keywords which appeared in the ec innovation research. the larger the values are, the more frequently the keywords were used in the research articles. in this study, non-repeated counts are presented, showing the mainstreams of ec innovation that most research focused on. two different research trends of keywords were interpreted as follows. advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 253 (a) keywords with increasing trends in this study, the counts of most keywords increased. for example, the top two keywords (i.e., innovation and e-commerce) that were used for searching the research data are listed in italics in the parentheses. overall, these two keywords have been most frequently used by researchers: 233 (67%) and 172 (51%) times, respectively. this result provides evidence of content validity for our research data in the ec innovation area. however, the growth trend of these two keywords is different across two research decades. “innovation” was the most adopted keyword in the period i (n=85, 2000-2009) and period ii (n=148, 2010-2018). this indicates a significant growth of “innovation” in the ec innovation research. on the other hand, “e-commerce” appeared as the second most highly used keyword in the first decade (n=82), but the growth in number (n=90) in the recent decade was not as active as that of “innovation.” the following five keywords (#1-5) show the domain-specific characteristics of ec innovation research, namely “model” (173), “data” (121), “implications” (114), “online” (112), and “technology” (105). the first four keywords almost doubled from the first to the present decade (55->118; 35->86; 29->85; 23->89), while the growth of “technology” (40->65) was relatively stable. this result suggests the need for and importance of scholarly research in ec innovation, such as research models, data-driven evidence, online applications, managerial implications for real business operations, and new technologies. the next 10 keywords that rarely appeared in the earlier stage (2000-2009) but which were highly researched in the recent decade (2010-2018) are marked in table 4 (#6-15). they are “m-commerce,” “china,” “platforms” (0->11); “amazon,” “devices,” “image,” “shopping experience” (0->10); “social commerce,” “online review” (0->8), and “co-creation” (0->6). most of the above keywords revealed the emerging applications of ec innovations (e.g., m-commerce, platforms, devices, social commerce, online review, co-creation), while others highlighted the great consumption market, china, and the leading ec company, amazon. it is also interesting to note that “image” and “shopping experience” are specific contexts of consumers’ reviews conducted online. consumers in the digital age are used to shopping online via their smartphones. the images and reviews posted by other consumers have become the first impression of the products they search for. these are popular topics in ec innovation research. table 4 a list of keywords used in the ec innovation articles: comparison of two decades # year counts (all years) 2000-2009 2010-2018 ∆ (innovation) 233 85 148 63 (e-commerce) 172 82 90 8 1 model 173 55 118 63 2 data 121 35 86 51 3 implications 114 29 85 56 4 online 112 23 89 66 5 technology 105 40 65 25 6 m-commerce 11 0 11 11 7 china 11 0 11 11 8 platforms 11 0 11 11 9 amazon 10 0 10 10 10 devices 10 0 10 10 11 image 10 0 10 10 12 shopping experience 10 0 10 10 13 social commerce 9 0 9 9 14 online review 8 0 8 8 15 co-creation 6 0 6 6 16 internet 61 34 27 -7 17 b2b 24 13 11 -2 18 b2c 15 9 6 -3 19 travel agency 5 5 0 -5 20 internet banking 2 2 0 -2 advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 254 (b) keywords with decreasing trends note that two main keywords used for the search are listed in italics in the parentheses. the following are the most often used keywords with increasing trends (#1-5); ten keywords that seldom appeared in the earlier stage (2000-2009), but were highly researched in the recent decade (2010-2018) were marked (#6-15); the last five keywords, on the other hand, were found to have a decreasing trend of use in recent ec innovation research (#16-20). table 4 a list of keywords used in the ec innovation articles: comparison of two decades # details of the earlier decade (2000-2009) 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 4 11 7 9 8 9 10 6 7 14 5 13 5 7 9 9 10 7 5 12 1 3 3 3 2 5 9 9 6 5 10 2 0 2 3 3 4 4 5 3 3 8 3 0 1 1 3 3 5 4 3 3 6 4 0 1 1 3 2 4 2 2 0 8 5 2 4 5 4 3 2 7 4 3 6 6 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 0 16 3 6 0 6 5 3 3 1 1 6 17 2 1 1 2 2 1 2 1 0 1 18 0 1 1 1 0 1 1 2 0 2 19 0 2 0 0 0 0 0 0 1 2 20 0 0 0 1 1 0 0 0 0 0 # details of the recent decade (2010-2018) 2010 2011 2012 2013 2014 2015 2016 2017 2018 21 8 14 7 10 17 22 25 24 18 8 8 4 5 8 13 16 10 1 12 10 7 8 6 15 16 20 24 2 8 7 8 5 6 10 13 13 16 3 14 5 2 2 5 12 11 16 18 4 9 6 4 3 4 12 16 20 15 5 9 7 3 2 4 14 7 9 10 6 0 0 1 0 1 2 2 4 1 7 1 0 1 1 1 1 3 1 2 8 0 1 0 0 0 0 2 5 3 9 1 1 1 0 1 1 0 3 2 10 0 0 1 0 0 2 1 3 3 11 1 0 0 1 0 2 4 2 0 12 1 3 0 0 1 1 0 0 4 13 0 1 0 0 0 1 3 2 2 14 2 0 0 0 1 1 1 2 1 15 1 1 1 0 0 1 1 1 0 16 5 3 4 2 1 3 3 2 4 17 2 0 0 1 1 1 4 1 1 18 1 2 0 1 0 0 2 0 0 19 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 ∆: the difference in keyword counts between the earlier decade (2000-2009) and the recent one (2010-2018). the last five keywords, on the other hand, showed a decreasing trend in recent ec innovation research (#16-20), including “internet” (34->27), “b2b” (24->13), “b2c” (15->9), “travel agency” (5->0), and “internet banking” (2->0). advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 255 although the keyword “internet” appeared in 61 articles from 2000 to 2018, it is clear that the figure significantly decreased in recent ec innovation research. we argue that the reason is due to the development of advanced technology. the internet-based environments for commerce have become more general than in the 1990s (the age of the rise of the internet). likewise, ec business models have developed from some essential business to business (b2b) and business to consumer (b2c) models to an integrated model, such as the online-to-offline model (o2o). many industries were also affected and forced to change by the emerging ec innovations, for example, travel agencies versus online travel platforms, and the applications of internet banking versus mobile banking apps that are used on smartphones. 3.2. the most influential research articles in the first decade: 2000-2009 table 5 top 10 research articles of ec innovations in the first decade (2000-2009) # authors title journal main innovations in ec category cites (avg.) 1 [16] understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior mis quarterly (2006) theory of planned behavior; perceived behavioral control; self-efficacy; controllability; technology acceptance model; trust; electronic commerce; consumer behavior information science; management 842 (64.8) 2 [17] post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry information systems research (2005) technology diffusion; innovation; e-business; it investment; usage; value; back-end integration; firm performance; resource-based view; international perspective information science 530 (37.9) 3 [14] choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies journal of marketing (2005) service delivery modes; self-service technologies; customer trial business & economics 488 (34.9) 4 [18] enticing online consumers: an extended technology acceptance perspective information & management (2002) electronic markets; innovation diffusion; online retailing; technology acceptance model; virtual store information science; management 503 (29.6) 5 [19] the process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business management science (2006) technology diffusion; innovation assimilation; assimilation process; e-business; competition; firm size; technology integration; international perspective operations research & management science 371 (28.5) 6 [20] the effects of personalization and familiarity on trust and adoption of recommendation agents mis quarterly (2006) trust; electronic commerce; adoption; personalization; familiarity; cognitive trust; emotional trust; recommendation agent; delegation information science; management 338 (26) 7 [21] shaping up for e-commerce: institutional enablers of the organizational assimilation of web technologies mis quarterly (2002) web technology; web implementation; it management; innovation assimilation; structuring actions information science; management 359 (21.1) 8 [22] shopping motivations on internet: a study based on utilitarian and hedonic value technovation (2007) internet shopping; utilitarian motivation; hedonic motivation; shopping motivation; search intention; purchase intention engineering & industrial; management 188 (15.7) 9 [23] informational cascades and software adoption on the internet: an empirical investigation mis quarterly (2009) e-commerce; herding; informational cascades; decision making; network effects; word-of-mouth; software download; online communities; online user review information science; management 143 (14.3) 10 [24] a model of organizational integration, implementation effort, and performance organization science (2005) integration; interdependence; performances; erp implementation; electronic integration management 196 (14) ∆: the difference in keyword counts between the earlier decade (2000-2009) and the recent one (2010-2018). after counting the total and average citations of influential papers in terms of highly cited papers, we identified the top 10 research articles related to e-commerce applications across the two decades. table 5 lists the top 10 highly cited articles along with authors, title, the published journal, main keywords, and citations from 2000-2009. in the following, we will summarize research outlines from the top three articles. as seen in table 5, pavlou and fygenson’s article emerged as the most influential paper in terms of total citations (842) and average citations per year (64.8) [16]. they proposed an integrated model to predict ec adoption based on renowned theories, such as the theory of reasoned action (tra), the theory of planned behavior (tpb), and the technology acceptance model (tam). in addition, other factors including technological characteristics, consumer skills, time and monetary resources, and product characteristics also contributed to the prediction of ec adoption. ranked 2 nd with total citations of 530 and average citations per year of 37.9, zhu and kraemer’s research [17] focused on the post-adoption of the e-retailing industry. based on the innovation diffusion theory (idt) and the resource-based theory, three perspectives of factors including technological, organizational, and environmental factors were employed to accomplish the research purpose. as self-service technologies (sst) have become increasingly popular, meuter et al. [14] adopted variables advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 256 (e.g., role clarity, motivation, and ability) obtained from the consumer readiness theory to investigate their influences on consumer trials of sst. as we look inside the articles in the first decade, most of the top 10 highly cited papers are attributed to both the information science and management categories [16-18, 20-21, 23]. in terms of research type, all of them are empirical studies investigating consumers, and only three cover the subject of the organization [15, 19, 24]. in the research contexts, except for the applications of self-service technology (sst) [14] and recommendation agents (ras) [20], most studies applied to ec adoption, including software adoption such as erp [24]. note that four of the top 10 articles are published in the prestigious journal, mis quarterly [16, 20-21, 23]. note that a total of 118 research articles published from 2000 to 2009. the most influential articles (top 10) are listed above. the ranking of the top 10 articles was sorted by the times cited per year (average citations), which is presented in parentheses in the citation column. 3.3. the most influential research articles in the recent decade: 2010-2018. table 6 top 10 research articles of ec innovations in the recent decade (2010-2018) # authors title journal main innovations in ec category cites (avg.) 1 [25] what makes a helpful online review? a study of customer reviews on amazon.com mis quarterly (2010) electronic commerce; product reviews; search and experience goods; consumer behavior; information economics; diagnosticity information science; management 615 (68.3) 2 [26] business models: origin, development and future research perspectives long range planning (2016) business models of innovation, change & evolution, performance & controlling and design. business; development studies; management 124 (41.3) 3 [27] assessing the determinants of cloud computing adoption: an analysis of the manufacturing and services sectors information & management (2014) cloud computing; it adoption; diffusion of innovation (doi); technology-organization-environment (toe) information science; management 177 (35.4) 4 [28] co-creation: toward a taxonomy and an integrated research perspective international journal of electronic commerce (2010) active consumption; co-creation; consumer roles; e-commerce research; taxonomic frameworks business & economics 240 (26.7) 5 [29] trust, satisfaction, and online repurchase intention: the moderating role of perceived effectiveness of e-commerce institutional mechanisms mis quarterly (2014) e-commerce; trust; online repurchase intention; e-commerce; institutional mechanisms; moderation analysis; partial least square modeling information science; management 109 (21.8) 6 [30] what signal are you sending? how website quality influences perceptions of product quality and purchase intentions mis quarterly (2011) signaling theory; signals; cues; website quality; ecommerce; perceived quality; credibility; information asymmetries information science; management 162 (20.3) 7 [31] an integrative model of consumers' intentions to purchase travel online tourism management (2015) innovations diffusion theory; intentions to purchase; online travel shopping; social media; technology acceptance model; theory of reasoned action; theory of planned behaviour hospitality, leisure, sport & tourism; management 81 (20.3) 8 [13] understanding the determinants of rfid adoption in the manufacturing industry technological forecasting and social change (2010) radio frequency identification; technology-organization-environment framework; technology adoption; innovation adoption business; regional & urban planning 176 (19.6) 9 [32] task design, motivation, and participation in crowdsourcing contests international journal of electronic commerce (2011) analyzability; autonomy; co-creation; crowdsourcing; extrinsic motivation; intrinsic motivation; tacitness; task design; variability business & economics 123 (15.4) 10 [33] harnessing the influence of social proof in online shopping: the effect of electronic word of mouth on sales of digital microproducts international journal of electronic commerce (2011) digital microproducts; digital products; electronic word of mouth; ewom; social proofs business & economics 116 (14.5) compared with the articles on ec innovation from 2000 to 2009, the top 10 articles of ec innovation in the recent decade seem to have received fewer citations in terms of both total and average per year citations, with the exception of the top one article. as seen in table 6, mudambi and schuff’s [25] article, ranked as number one, received a total of 615 citations and 68.3 average citations per year. they worked on the critical issue regarding the success of ec business. collected from more than advances in technology innovation, vol. 4, no. 4, 2019, pp. 247-259 257 1,500 reviews from amazon across six products, they found some decisive factors including extremity, review depth, and product type. amblee and bui [33] also targeted amazon’s consumers but worked on another important issue of social influence, i.e., electronic word of mouth (ewom). wirtz et al. [26] presented a position paper (ranked 2 nd ) to articulate the development, evolution, and future research of business models. from the organization perspective, oliveira et al. [27] investigated over 350 firms to assess the determinants of cloud computing adoption based on the theories of diffusion of onnovation theory (doi) and technology-organization-environment (toe). the above are the research outlines of the top three articles. overall, in the recent decade, fives articles were attributed to the business category [13, 26, 28, 32-33], four to the information science management category [25, 27, 29-30], and one to the hospitality & tourism category [31], showing that the ec innovations have been widely applied to various fields. in terms of research type, eight out of 10 articles are empirical research, and only two are qualitative research. while wirtz et al. [26] systematically reviewed the research on business models, zwass [28] conducted a taxonomy of co-creation, another emerging topic. with regard to the research topics, more diverse and innovative themes can be found in the last decade, such as rfid adoption, cloud computing [27], co-creation [28], extrinsic cue signals [30], online travel [31], crowdsourcing contests [32], and recommendation systems [33]. among the top 10 articles, two well-known journals, misq and ijec, each published three articles. note that a total of 216 research articles were published from 2010 to 2018. the most influential articles (top 10) are listed above. the ranking of the top 10 articles was sorted by the times cited per year (average citations), which is presented in parentheses in the citation column. 4. conclusions in line with the main research interest, we have concluded some differences in the development of ec innovation (tables 5 and 6) between the two decades. in summary, the main research streams in the past decade (2010-2018) are more diverse and extensive than the research in the previous decade (2000-2009) in terms of the research categories, research types, and research topics. first, more ec innovation studies were attributed to business and economics fields than to information science and management categories. next, considering the research type, qualitative studies such as research reviews and position papers have emerged in the past decade, indicating that the ec innovation research has matured in recent years. finally, in terms of ec innovation topics, the sst and erp were the foci of research in the early decade, but more innovative applications appeared as hot topics in recent years such as cloud computing, co-creation, and crowdsourcing. we have also identified some theories other than traditional attitude-intention models (e.g., tra, tpb, tam, and idt) that have been used in the contexts of new ec applications over the past decade, including technology-organization-environment (toe), signaling theory, extrinsic and intrinsic motivations, and theory of job design. conflicts of interest the authors declare no conflict of interest. references [1] a. bhattacherjee, “acceptance of e-commerce services: the case of electronic brokerages,” ieee transactions on systems, man, and cybernetics, vol. 30, no. 4, pp. 411-420, 2000. 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[33] n. amblee and t. bui, “harnessing the influence of social proof in online shopping: the effect of electronic word of mouth on sales of digital microproducts,” international journal of electronic commerce, vol. 16, no. 2, pp. 91-113, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v8n2(2023)-aiti#8364(111-120).docx advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 short-term rainfall prediction using supervised machine learning nusrat jahan prottasha1,*, anik tahabilder2, md kowsher3, md shanon mia1, khadiza tul kobra1 1department of computer science, daffodil international university, dhaka, bangladesh 2department of computer science, wayne state university, detroit, michigan, usa 3department of computer science, stevens institute of technology, hoboken, new jersey, usa received 30 august 2021; received in revised form 16 may 2022; accepted 02 june 2022 doi: https://doi.org/10.46604/aiti.2023.8364 abstract floods and rain significantly impact the economy of many agricultural countries in the world. early prediction of rain and floods can dramatically help prevent natural disaster damage. this paper presents a machine learning and data-driven method that can accurately predict short-term rainfall. various machine learning classification algorithms have been implemented on an australian weather dataset to train and develop an accurate and reliable model. to choose the best suitable prediction model, diverse machine learning algorithms have been applied for classification as well. eventually, the performance of the models has been compared based on standard performance measurement metrics. the finding shows that the hist gradient boosting classifier has given the highest accuracy of 91%, with a good f1 value and receiver operating characteristic, the area under the curve score. keywords: rain prediction, machine learning, supervised classification, agriculture resource, crops yield 1. introduction agriculture plays a vital role in the development of many developing countries [1]. iot-based smart agriculture model is being implemented worldwide to increase crop yields. the use of intelligent tools in farming can increase the production of crops and also minimize the damage due to disasters. the economy of south asian countries, including bangladesh, india, china, and pakistan, depends more on agriculture. but there are always some natural disasters, including rain and floods, that create huge demolition of crops and property. therefore, a good rain prediction model is necessary to forecast the rain to reduce the risk to life and also to maintain the agriculture farms in a better way. in addition, a rain prediction model helps farmers take early flood measurements and properly manage water resources. observing the significance of rain prediction, researchers have developed a lot of devices to predict rainfall, but none of them is worth noting in terms of short-term rain prediction. hence, it has not been adopted eventually by the end-level user to forecast the rain situation. however, machine learning techniques can make a more accurate prediction because of their underlying technology. researchers have implemented neural networks (nn) in rainfall prediction and showed that the nn-based model usually exceeds the performance of the numerical weather prediction model. this study aims to develop a short-term rain prediction model that can effectively and accurately predict rainfall. in this proposed work, several relevant machine learning models have been used to predict rainfall, and finally, a performance comparison has been made to determine the best suitable model. * corresponding author. e-mail address: jahannusratprotta@gmail.com advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 112 in this project, the twenty-nine most optimistic classifiers have been used from eleven different categories. all these models have been trained and tested with a relevant rainfall dataset to implement this prediction model. the data was collected from a popular and recognized public repository and split into training, validation, and testing data. since the raw data came from natural weather resources, it has been preprocessed before going to the training phase. a few preprocessing techniques have been implemented to prepare the raw data, such as missing value check, feature selection, features scaling, dimension reduction, etc. after analyzing all the models and comparing them, it was found that the hist gradient boosting classifier (hgbc) has shown the highest accuracy of 91%. a lot of other models have shown the second-highest accuracy of 90%. the contribution of this paper can be summarized below: (1) a pipeline for estimating rain prediction has been developed. (2) diverse types of classifiers have been used to ensure the best model that suits diverse types of data. (3) a comparison among all trained models has been described to measure the comparative performance. the rest of the sections of this paper is organized as follows. section 2 explains the related work of various classification techniques for rainfall prediction. section 3 describes the major technology components used, including the dataset, preprocessing, and algorithm. section 4 describes the methodology that has been used to solve the proposed problem. later on, section 5 contains the experiments and the results. this article is wrapped up in section 6 by discussing the conclusion and future works. 2. related work a country’s agriculture largely depends on rain, and there is a lot of research on forecasting rain. all the earlier methods of rain forecasting are mainly statistical and numerical analysis based [1]. also, some methods predict the rain by analyzing radar images. denœux and rizand [2] have proposed a model that performs deep learning-based analysis on radar images to predict rainfall. however, with the recent advancement of machine learning, many new machine learning-based models have been proposed for rainfall prediction. researchers like shah et al. [3] have developed a simple polynomial regression-based model to predict the rain to benefit agricultural products. asha et al. [4] have proposed a hybrid machine learning classification model for predicting rainfall, and it has shown better performance than the ordinary ml-based model. sakthivel and thailambal [5] have also demonstrated such a hybrid approach for rain prediction, predicting continuous long period rainfall. naidu et al. [6] presented the changes in rainfall patterns in numerous agro-climatic zones using machine learning approaches. besides, dinh et al. [7] have used a support vector machine (svm)-based method to measure the rain forecast and the soil erosion due to the rain. on the other hand, abdel-kader et al. [8] showed a vigorous hybrid technique by particle swarm optimization (pso) and multi-layer perceptron (mlp) for the prediction of rainfall. also, samsiahsani et al. [9] evaluated many machine learning classifiers based on malaysian data for rainfall prediction. similar models have been developed to predict the flood forecast due to heavy rainfall and ocean waves. luk et al. [10] mentioned data scarcity as a limitation in modeling such a predictive model. abbot and marohasy [11] have shown the application of nn in rainfall prediction based on a dataset from queensland, australia. among the short-term prediction models, a model by shah et al. [12], is a good invention for predicting very short-term rainfall. on the other hand, some researchers focused on heavy rainfall only. research by sangiorgioet al. [13] has made improvements in determining heavy rainfall based on water vapor measurement using a nn-based model. han et al. [14] have mentioned the limitations of such a predictive model for forecasting rainfall and flood by determining the major uncertainties. advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 113 unlike those works, in this project, several rain-forecasting models for upcoming rain prediction have been developed using twenty-nine different machine learning classifiers. additionally, their performances have also been compared, and hence the best machine learning model for rain prediction has been determined. 3. dataset and algorithm description the structural dataset and algorithms are a machine learning model’s two most essential parts. this section will provide a brief description of the dataset and algorithm. the features of the dataset will be discussed in more details form. then the data preprocessing steps will also be explained in the subsequent section. finally, all the algorithms that have been used to make the models will be described in brief. 3.1. dataset to implement the proposed model, the rain prediction database from kaggle has been used. the dataset [15] comprises the precipitation estimation from the years 1901 to 2015 for each state of australia. each observation contains 19 qualities (person-months, annual, and combinations of 3 continuous months) for subdivisions. the rain prediction unit mentioned in the dataset is measured in millimeters (mm). table 1 summarizes the dataset and its features. the feature name and the description of the feature are shown in the left column and the right-side column, respectively. the dataset is robust and has an adequate number of observations and features, which ensures the quality of the data and guarantees a model with good accuracy if modeled properly. table 1 the description of the dataset feature details description of the feature location this is the name of the location maxtemp max temperature recorded in degrees centigrade mintemp min temperature recorded in degrees centigrade windgustspeed the speed of wind gust in km per hour windgustdir the direction of the strongest wind gust windspeed9am wind speed averaged over 10 minutes before 9 a.m. winddir9am the direction of the wind gust at 9 a.m. windspeed3pm averaged wind speed over 10 min before 3 p.m. winddir3pm the direction of the wind gust at 3 p.m. humidity9am relative humidity at 9 a.m. measured in percentage humidity3pm relative humidity at 3 p.m. measured in percentage temp9am the temperature at 9 a.m. measured in degrees celsius temp3pm the temperature at 3 p.m. measured in degrees celsius pressure9am atmospheric pressure at 9 a.m. measured in hpa pressure3pm atmospheric pressure at 3 p.m. measured in hpa rainfall the rainfall recorded for the day (mm) raintoday if precipitation in the 24 h to 9 a.m. exceeds 1 mm it will be 1, otherwise 0 (mm) rain tomorrow if it will rain or not on the next day, it is output as binary target variable 3.2. pre-processing data preprocessing is a crucial step that helps improve the quality of data to advance the extraction of important bits of knowledge from the data. it refers to preparing the raw data in a format that will be neat, clean, and understandable to the machine learning model. advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 114 the flowchart of data preprocessing steps is illustrated in fig. 1. in the subsequent section. after the data is collected, it goes through a cleaning process, and then the missing values are handled logically. then the data encoding is performed, and important features get selected. eventually feature scaling process is used to bring all the features on a similar scale, and 10-fold cross-validation (cv) is implemented. each stage of data preprocessing is described elaborately below. data cleaning is the method of preparing data for analysis by removing or adjusting incorrect, fragmented, unimportant, duplicated, or improperly organized data. it includes further tuning of data by fixing spelling, and syntax errors, and adjusting mistakes, such as dealing with empty data, invalid values, and recognizing duplicate data points. there were some missing, some duplicates, some invalid, and some incomplete values in this dataset. the following actions have been taken to correct those data. (1) a part of the data points is repeated in row and column segments. hence, all the duplicate data was removed, and only a single instance was kept. (2) a few rows and columns were almost empty. that corresponding row or column has been removed from the dataset. (3) some instances were shown to have some invalid values. that instance was also deleted to make the dataset solid and readable. fig. 1 the entire data preprocessing procedure missing values are a common occurrence in the dataset. therefore, they need to be handled to prepare the dataset properly. if the data cannot pass the statistical test, then it is removed from the dataset. besides, most predictive algorithms can't handle any missing value. hence, this issue must be solved before the data is fed into the model. in most machine learning work, people utilize various techniques such as mean, median, and mode methods to handle missing values. but the most appropriate method for managing missing data is to remove the full row for categorical features and replace the missing data with the nearest neighbors for numerical data. the k-nearest neighbors (knn)-based imputation method has been implemented in this work for a more accurate missing value imputation. the not-a-number (nan) data has been replaced by getting the nearest value by considering the three neighbors. categorical data could be a subjective feature whose values are taken by label encoding or one-hot representation. it implies that categorical data must be encoded into numbers before it is fed to the model. in the dataset, there are six categorical factors “location,” “windgustdir,” “winddir9am,” “winddir3pm,” “raintoday,” and “rain tomorrow.” one hot encoding is one of the most popular methods for encoding categorical variables, which has been used in this project. it is one of the widespread approaches, and it works well unless the categorical variables count is too high. it makes a new binary column for each category, demonstrating the presence of each possible value from the categorical data. feature selection is the strategy to figure out highly related input variables when creating a predictive model. reducing the number of input variables is desirable to reduce the computational cost in modeling and increase the model’s performance. the dataset contains 21 components, and the p-value has been tested to check the probability of the null hypothesis. features advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 115 with a p-value less than 0.05 have been discarded. after checking multicollinearity, a vital separation is maintained from those components which appear redundant and don’t back the p-value assumption. besides, to handle the numerical feature, the pearson correlation coefficient has been used, which is characterized within condition-1, and for categorical features, anova-f has been used, which is described as: ( ) ( ) ( ) ( ) 1 2 2 1 1 n i i i n n i i i i x x y y r x x y y = = = − − = − −    (1) after performing the feature selection, eighteen features were kept, including location, mintemp, maxtemp, rainfall, windgustdir, windgustspeed, winddir9am, windspeed9am, windspeed3pm, humidity9am, humidity3pm, pressure9am, pressure3pm, temp9am, temp3pm, raintoday, and rain tomorrow. the numerical data are mostly skewed or nonstandard deviation in data analysis due to outliers, multi distributions, exceptionally exponential distributions, and more. this issue was solved by changing the numeric value into a categorical feature. to implement this method, a discretization process that changes over the numerical value into different distribution work has been applied as shown below: ( ) ( ) ( ) ( ) 2 1 2 1 / 1 / n k g i n k g i n x x k f x x n k = = − − = − −   (2) feature scaling is one of the significant procedures required to standardize the independent features of the working dataset. there are different strategies for feature scaling such as min-max scaling, variance scaling, standardization, mean normalization, unit vectors, etc. in this work, min-max scaling has been used as a feature scaling method, and the exchange range has been set between 0 and 1. mathematical formulla of the min-max scaling has been described as: ( ) ( ) ( ) min max min x x x x x − ′ = − (3) cv is a resampling method to train, test, and validate the model using different data in each iteration. there are lots of cv methods to perform this operation. this paper uses a 10-fold cv technique where the whole dataset is separated into ten folds. each section is used either for training, validation, or test set. after data preprocessing, there were 142193 rows as samples and 17 columns as features. 3.3. algorithms a few of the most suitable machine learning and deep learning-based models have been implemented to build the best model. some of them are neighbor relationship-based, some are naive bayes (nb) theory-based, some are based on svm, and so on. table 2 shows a summary of all the algorithms that have been used in this research. for the knn, five neighbors have been considered to find the similarity. for mlp, the learning rate is 0.001 with two hidden layers of 56 units. for radius learning, the radius value was set to 0.1. the gini index has been used to split decisions between the decision tree and the random forest tree. table 2 the summary of the algorithm used methodology algorithms methodology algorithms neighbors classifier k-nearest neighbors discriminant analysis classifier linear discriminant analysis radius neighbors classifier quadratic discriminant analysis advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 116 table 2 the summary of the algorithm used (continued) methodology algorithms methodology algorithms neighbors classifier nearest centroid support vector machine classifiers linear svc ensemble classifiers adaboost classifier linear svc bagging classifier nu svc gradient boosting classifier linear model stochastic gradient descent classifier hist gradient boosting classifier ridge classifier random forest classifier ridge classifier cv naive bayes classifiers bernoulli nb passive aggressive classifier multinomial nb logistic regression cv categorical nb logistic regression complement nb perceptron gaussian nb impact learning [16] semi-supervised classifiers label propagation gaussian process classifiers radial basis function label spreading neural network mlp classifier 4. methodology to complete the whole workflow, a total of four steps have been executed: data collection and preprocessing, training model using supervised learning methods, testing, and performance analysis. a popular and acceptable dataset from the kaggle platform [11] has been adopted for this project. this dataset was split into three parts: the training part, the validation part, and the testing part. after gathering all raw data, the dataset goes through data preprocessing steps, which have been used to make the dataset outliers-free and more solid. these data preprocessing steps also help in increasing the performance of the models [17]. as a result, diverse preprocessing methods such as cleaning data, missing value checks, handling the categorical data, feature selection, and feature scaling have been applied. the machine learning models are made by training with the data preprocessed earlier. the training and testing methods of all those models are different. from all the training methods, 29 classifiers have been used so that the performance can be compared and the best suitable model can be selected. most of the models listed in the table showed good performance, but some didn’t fit very well. the complete methodology of this proposed model is shown in fig. 2. fig. 2 the overview of the methodology of the proposed work 5. experiments and results the model was built and then trained with the preprocessed dataset. in this section, the performances of all the algorithms have been compared. besides, various experimental parameter has been tuned for performance analysis and evaluation. in addition, the experimental setup to accomplish the entire task has also been described. for this model, 11 statistical performance metrics have been considered for performance analysis and comparison. advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 117 the whole work has been completed in google colab, and python has been provided as a simulation environment by google. a machine learning framework named sci-kit learns and deep learning framework keras have also been used to implement the classification algorithm. in addition, the matplotlib library for data visualization, graphical representation, and data analysis has been used in this project. table 3 the summary of the algorithms that have been used in this research model accuracy f1 score rs ps fbs hl js mc auc bac cks neighbors classifier knc 0.868 0.752 0.672 0.749 0.809 0.202 0.604 0.468 0.749 0.689 0.411 nc 0.813 0.719 0.663 0.661 0.749 0.257 0.561 0.378 0.74 0.68 0.338 rnc 0.803 0.708 0.654 0.648 0.736 0.267 0.55 0.356 0.731 0.671 0.316 ensemble classifiers adc 0.893 0.802 0.72 0.791 0.856 0.177 0.656 0.559 0.797 0.737 0.507 bc 0.894 0.802 0.72 0.793 0.857 0.176 0.657 0.561 0.797 0.737 0.508 gbc 0.904 0.818 0.734 0.812 0.875 0.166 0.675 0.594 0.811 0.751 0.54 hgbc 0.91 0.833 0.751 0.817 0.885 0.16 0.692 0.619 0.828 0.768 0.569 rfc 0.907 0.823 0.737 0.819 0.881 0.163 0.68 0.604 0.814 0.754 0.549 naive bayes classifiers mnb 0.811 0.718 0.662 0.659 0.747 0.259 0.56 0.376 0.739 0.679 0.335 conb 0.733 0.686 0.679 0.63 0.712 0.337 0.512 0.36 0.756 0.696 0.297 cnb 0.731 0.686 0.683 0.632 0.713 0.339 0.512 0.365 0.76 0.7 0.299 gnb 0.695 0.66 0.669 0.618 0.692 0.375 0.482 0.336 0.746 0.686 0.263 cc 0.899 0.813 0.731 0.799 0.866 0.171 0.668 0.58 0.808 0.748 0.529 semi-supervised classifiers lp 0.884 0.787 0.712 0.758 0.832 0.186 0.64 0.521 0.789 0.729 0.476 ls 0.902 0.816 0.733 0.808 0.872 0.168 0.673 0.589 0.81 0.75 0.536 discriminant analysis classifier lda 0.901 0.817 0.736 0.802 0.869 0.169 0.673 0.588 0.813 0.753 0.537 qda 0.708 0.656 0.641 0.603 0.684 0.362 0.483 0.294 0.718 0.658 0.237 svm classifiers lsvc 0.902 0.812 0.727 0.811 0.872 0.168 0.669 0.586 0.804 0.744 0.529 nusvc 0.899 0.809 0.726 0.802 0.865 0.171 0.665 0.576 0.803 0.743 0.522 sgdc 0.894 0.795 0.709 0.8 0.857 0.176 0.65 0.555 0.786 0.726 0.496 rdc 0.9 0.802 0.714 0.813 0.867 0.17 0.658 0.572 0.791 0.731 0.511 rdcv 0.9 0.802 0.714 0.813 0.867 0.17 0.659 0.572 0.791 0.731 0.511 pac 0.85 0.623 0.568 0.767 0.709 0.22 0.506 0.322 0.645 0.585 0.202 lrcv 0.9 0.815 0.733 0.801 0.868 0.17 0.671 0.584 0.81 0.75 0.533 lr 0.901 0.815 0.733 0.802 0.869 0.169 0.672 0.585 0.81 0.75 0.534 pr 0.804 0.716 0.666 0.653 0.742 0.266 0.556 0.373 0.743 0.683 0.332 il 0.902 0.813 0.727 0.811 0.872 0.168 0.669 0.586 0.804 0.744 0.53 gaussian process classifiers gpc 0.903 0.818 0.736 0.807 0.873 0.167 0.675 0.592 0.813 0.753 0.54 neural network classifier mlpc 0.906 0.833 0.757 0.805 0.879 0.164 0.691 0.613 0.834 0.774 0.568 advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 118 here, the twenty-nine most suitable machine learning models have been used to predict the rainfall possibility. a total of 11 statistical measurements have been considered and listed in table 3. the table shows that the hgbc has predicted the best accuracy of 0.91, and the f1 score is 0.833. the random forest tree classifier has obtained the best accuracy of 0.907 with an f1 score is 0.823 from the branch of ensemble classifiers. the mlpc has acquired good accuracy, which is 0.906, along with an f1 score of 0.833 from the section of the nn classifier. moreover, from the section on the neighbor’s classifier, it can be noticed that the knc has shown the best accuracy of 0.868, and the f1 score is 0.752. also, from the section on nb algorithms, cc has shown the best accuracy of 0.899 and its f1 score is 0.813 among all nb classifiers. after that, ls also has placed the best accuracy of 0.902, and its f1 score is 0.816 from the branch of semi-supervised classifiers. besides, it can also be seen from the discriminant analysis section that the linear discriminant analysis has proved the best position of accuracy, 0.901, with an f1 score of 0.817. fig. 3 comparison of accuracy among the models next, lsvc also has the best accuracy of 0.902, and its f1 score is 0.812 from the branch of svm classifiers. finally, gpc has figured out the best accuracy result is 0.903 with an f1 score of 0.818 from the section of gaussian process classifiers. all-inclusive, by analyzing all the sections of algorithms for the rain prediction model, it came out that the hgbc is the winner with an accuracy of 0.91, and the f1 score is 0.833. fig. 3 shows the accuracy comparison among all the models. a roc curve is a graph showing the performance of a classification model at all classification thresholds. most of the algorithms show a high chance that the classifier will be able to distinguish the positive class values from the negative class values. 6. conclusion and future work in this work, a machine learning model has been presented that can determine whether it will rain or not on the very next day. real data from australia has been adopted from the kaggle platform and implemented in the model. this data-driven model is more accurate than any other statistical or numerical-based model. the primary purpose here is to find the best classifiers for predicting rainfall. for this reason, various machine learning classifiers have been implemented. eventually, the most significant performance metrics have been compared, including accuracy, f1 scores, roc, auc, and hgbc have shown the best accuracy with a good score. all the models used here have been trained based on the dataset of a particular zone. therefore, rain prediction accuracy may vary depending on the dataset characteristics. training this model with a dataset that has a sample collected from diverse places can make this model more general and suitable for all locations in this world. this proposed model will be able to forecast the rain for the short-term, specifically for the next day. a new model can be built that will predict the rain for the long term in the future. combining this two may build a complete solution for rain prediction. moreover, this machine learning-based model may not be easily useable for general people. therefore, mobile and advances in technology innovation, vol. 8, no. 2, 2023, pp. 111-120 119 computer apps can be built so those general people can easily use them. a deep learning and nn model approach can be used to improve the result. undoubtedly, there is a plan to evaluate the other country’s data for forecasting the rain using this model. thus, this model is expected to be a universal and easy rain prediction tool for ordinary people. nomenclature hgbc hist gradient boosting classifier bc bagging classifier roc receiver operating characteristic gbc gradient boosting classifier auc area under the curve rfc random forest classifier nn neural networks mnb multinomial naive bayes svm support vector machine conb complement naive bayes pso particle swarm optimization cnb categorical naive bayes classifier mlp multi-layer perceptron gnb gaussian naive bayes mm measured in millimeters cc calibration classifier cv cross-validation lp label propagation knn k-nearest neighbors ls label spreading nan not-a-number lda linear discriminant analysis nb naive bayes qda quadratic discriminant analysis rs recall score lsvc linear support vector classifier ps precision score nusvc nu support vector classification fbs f-beta score sgdc stochastic gradient descent classifier hl hamming loss rdc ridge classifier js jaccard score rdcv ridge classifier cv mc matthew’s correlation pac passive aggressive classifier bac balanced accuracy lrcv logistic regression cv cks cohen’s kappa lr logistic regression knc k neighbors’ classifier pr perceptron classifier nc nearest centroid il impact learning rnc radius neighbor’s classifier gpc gaussian process classifier adc adaboost classifier mlpc multi-layer perceptron classifier conflicts of interest the authors declare no conflict of 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[17] c. v. z. zelaya, “towards explaining the effects of data preprocessing on machine learning,” ieee 35th international conference on data engineering, pp. 2086-2090, april 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 innovative design of an elliptical trainer with right timing of the foot trajectory fu-chen chen 1,* , yih-fong tzeng 2 , meng-hui hsu 1 1 department of mechanical engineering, kun shan university, tainan, taiwan 2 department of mechatronics engineering, national kaohsiung university of science and technology, kaohsiung, taiwan received 05 march 2020; received in revised form 06 may 2020; accepted 10 june 2020 doi: https://doi.org/10.46604/aiti.2020.5645 abstract the existing elliptical trainer cannot provide the user with the real jogging exercising mode and does not meet the principles of ergonomics. the purpose of this paper is to propose and study an innovative elliptical trainer that imitates the right timing of the foot trajectory while jogging. first of all, this study proposes and illustrates the structure and function of the innovative elliptical trainer with quick-return effect. then, by using vector-loop method and motion geometry of the mechanism, the proposed innovative mechanism is studied kinematically. a design example is presented for interpreting the design process. at last, the foot trajectory of the innovative elliptical trainer is analyzed and confirmed. the simulation results confirm that the timing of the foot trajectory of the foot support members satisfies the principles of ergonomics, and keeps the user’s legs from injury. keywords: innovative design, mechanism design, kinematics, elliptical trainer 1. introduction jogging is a popular exercise, but it is known that the jogger’s knees may suffer from significant impact especially at the time when the user’s foot hits the ground. the knees could be injured after constantly taking the impacts for a period of time. it has been estimated that between 65-70% of runners will suffer an overuse injury in their lower extremities [1]. about 30 million americans run for recreation or competition. each year between 1/4 and 1/2 of runners lead to serious injury and cause a change in exercise or training [2-4]. therefore, the elliptical trainer is developed to guide the users’ feet to follow a track such that impact forces are minimized and the knees are well protected from being injured. research on the lower extremity movements and forces generated during exercise on the elliptical trainer have demonstrated the elliptical motion which produces lower impact forces than treadmill running during elliptical exercise and walking [5-7]. there are many patents about elliptical trainers, but few researches are studied on the mechanism design of elliptical trainer. shyu et al. [8] presented a novel design of adjustable elliptical trainer and the parameters that affect the elliptical path and inclined angle of the foot trajectory are investigated. knutzen et al. [9] studied the influence of ramp position on joint biomechanics with adjusting the ramp setting during elliptical trainer exercise. although quite a few kinematic structures have been used on the design of elliptical trainers, few of these apparatuses give pedal paths that might boost the lower extremity kinematics of gaits near the ground. nelson and burnfield [10] proposed a novel design method for elliptical exercisers and created a foot trajectory that more closely mimics the lower extremity kinematics of gait. this design includes the substitution * corresponding author. e-mail address:fcchen@mail.ksu.edu.tw tel.: +886-6-2050496; fax: +886-6-2050509 advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 191 of a modified cardan gear system for the typical crank. yin [11] used adams to simulate the dynamics of elliptical exerciser and accurately describe its performance and the characteristic curves of some major components. on conventional elliptical trainer, the joints connecting the flywheel to two supporting members are placed on the flywheel with a 180° phase angle. therefore, when one of the user’s feet is at the front end of a pedal trajectory and about to support the user’s weight, the other is at the rear end of the pedal trajectory as shown in fig. 1(a). in other words, the supporting travel a1 and the striding travel a2 of the pedal trajectory a have almost the same path length. critics of the elliptical trainer have expressed concerns that the foot trajectory seems unergonomic and could cause the knee to harmful loads, resulting in injury [4]. the foot trajectories during treadmill walking or running are tracked by using webcam technology [12] and wearable wireless ultrasonic sensor network [13]. the foot trajectory of real jogging is shown in fig. 1(b). when one of the user’s feet is at the front end of the trajectory and starts supporting the user’s weight, the other one has not yet reached the rear end of the trajectory but still on the way of its backward path. in fact, it could not begin to move forward until it reaches the rear end of the trajectory. as shown in fig. 1(b), the path length of the supporting travel b1 should be shorter than that of the striding travel b2. as a result, the conventional elliptical trainer cannot provide the user with the real jogging exercising mode and does not meet the principles of ergonomics. (a) conventional trajectory (b) real jogging trajectory fig. 1 foot trajectory quick return mechanisms can be seen in every corner of engineering industry in various machines such as shaper, stamping press, power-driven reciprocating saw and so on. several structures of the quick-return mechanisms can be found [14-15], including crank-shaper mechanisms, whitworth mechanism and offset crank-slider mechanism. quick-return mechanisms are usually used in machine tools for the intention of providing the reciprocating cutting tool a slow cutting stroke and a quick return stroke with a constant angular speed of the driving flywheel. the ratio of the time required for the cutting stroke to the time required for the return stroke is called the time ratio (tr) and is greater than unity [15]. the study of quick-return mechanisms has been investigated by quite a few researchers, and many important contributions have been accomplished. dwivedi [16] modified the whitworth quick-return mechanism to construct a high-velocity impacting press. the impacting press machine includes a whitworth quick-return mechanism comprising a crank and a drive arm together with a variable speed d.c. motor, and a flywheel. this study also analyzes the reasons of the unbalanced forces of this high velocity machine and manages to reduce the forces delivered to the foundations. fung et al. [17-18] derived the governing equation of a quick-return mechanism by using the finite element method (fem) with time-dependent length and hamilton's principle. hsieh and tsai [19] proposed a novel design for quick-return mechanism that combines a generalized oldham coupling and a slider-crank mechanism. the proposed quick-return mechanism is more compact and can be balanced easier than a conventional design. chen et al. [20] proposed an elliptical trainer that composes of a conventional elliptical trainer and a draglink mechanism to generate a quick-return effect in order to mimic the timing of the foot trajectory while jogging. but the design procedures are too complicated, it is difficult for the designers to adjust the dimension to meet the timing of the foot trajectory while jogging. advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 192 the purpose of this study is to propose an innovative elliptical trainer that takes advantage of an inverted slider-crank mechanism to imitate the timing of the pedal trajectory and study the kinematics of the design. by using the inverted slider-crank mechanism, the design procedures are simple and easy to adjust the dimension to meet the requirement of time ratio in the proposed design. 2. innovative elliptical trainer (a) innovative design (b) detail drawing when right foot at a front end (c) detail drawing when right foot at a rear end fig. 2 innovative elliptical trainer the innovative elliptical trainer proposed in this study is illustrated in fig. 2. the design comprises a frame, two flywheels, two swing handles, two foot support members, two sliders and a timing adjustment wheel. a sliding branch is created on each of the flywheels. each of the foot support members connects to a respective flywheel. when the flywheel rotates about its pivot, the foot support member moves along a closed pedal trajectory c. the pedal trajectory c comprises a supporting travel c1 (from p1 to p3) and a striding travel c2 (from p3 to p1). the timing adjustment wheel rotates about a fixed pivot on the frame. advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 193 a right slider sliding along the sliding branch on the right flywheel connects to the right side of the timing adjustment wheel. on the contrary, a left slider sliding along the sliding branch on the left flywheel connects to the left side of the timing adjustment wheel. the right and left sliders are connected to the same timing adjustment wheel only with 180° phase angle. the motion of the elliptical trainer is described as follows. fig. 2 shows that a user stands on the two foot support members, where the right foot support member is pedaled by the user’s right foot and located at a front end p1, and the left one is pedaled by the user’s left foot and located at a point p3. accordingly, when the foot support member pedaled by the user’s right foot is pedaled downward, the right flywheel with the sliding branch is driven to rotate about its fixed pivot. therefore, the timing adjustment wheel is driven to rotate according to the relative movement between the right slider and the sliding branch of the right flywheel. then, the timing adjustment wheel drives the left flywheel with the sliding branch to rotate according to the relative movement between the left slider and the sliding branch of the left flywheel so as to guide the left foot support member pedaled by the user’s left foot to move upward. furthermore, when the foot support member pedaled by the user’s right foot finishes the supporting travel c1 and reaches the point p3, the foot support member pedaled by the user’s left foot is guided to finish the striding travel c2 and reaches the front end p1. the quick-return effect is further explained as follows. when the timing adjustment wheel rotates 180° clockwise (𝑎1 + 𝛽1 = 180° in fig. 2(b) and 2(c)), the respective angle that the right flywheel rotates is less than 180° (𝑎2 + 𝛽2 = 180° in fig. 2(b) and 2(c)). therefore, the rotational speed of the timing adjustment wheel is faster than that of the right flywheel when the foot support member pedaled by the user’s right foot moves within the supporting travel c1. the foot support member pedaled by the user’s right foot is located at the point p3 rather than at the rear end p2 when the foot support members pedaled by the user’s left foot just reaches the front end p1 of the pedal trajectory c. as the user’s left foot reaches the supporting travel c1, the user’s right foot begins to lift backward and upward. as a result, the user can shift his weight from one leg to the other before both his two legs are extended to their respective extreme positions so that the user is protected from muscle sore and pain. the timing of pedal trajectory c generated by the proposed elliptical trainer is closer to that in the real jogging and meets the principles of ergonomics. 3. motion geometry of the quick-return effect the skeleton drawing of the proposed innovative elliptical trainer assembly is shown in fig. 3. from the vector loop diagram of the innovative elliptical trainer mechanism in fig. 4, the following two vector loop equations can be derived as: 2 4 1r r r 0   (1) 5 6 7 8 9r r r r r 0     (2) decomposing the vectors in eq. (2) into x and y scalar components, the equations become 5 5 6 6 7 7 8r cos r cos r cos r 0      (3) 5 5 6 6 7 7 9r sin r sin r sin r 0      (4) where 𝜃𝑖 is the position angle of vector �̅�𝑖and the angle is defined positive when measured counterclockwise. when the foot support member is at the front end p1 of the pedal trajectory in fig. 2, the position angles of flywheel and foot support link are the same (as shown in figs. 3 and 5(a)), i.e. 𝜃5 = 𝜃6. substituting this into eqs. (3) and (4) yields ( )  5 6 5 7 7 8r r cos r cos r  (5) ( ) = +5 6 5 7 7 9r r sin r sin r  (6) squaring eqs. (5) and (6) and adding them together yields advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 194 7 7acos +b sin +c 0   (7) where 7 8a 2r r (8) 7 9b 2r r (9) c ( )    2 2 2 2 7 8 9 5 6r r r r r (10) by solving eq. (7), the position angle of the handle, 𝜃7, is obtained as: ( )       2 2 2 1 7 b a b c 2tan c a  (11) from eqs. (5) and (6), the angle of the flywheel, 𝜃5, can be expressed as: 1 7 7 9 5 7 7 8 r sin r tan r cos r        (12) fig. 3 skeleton drawing of the innovative elliptical trainer assume that the angle between the flywheel and the sliding branch is 𝑎, as shown in figs. 3-5. when the foot supporting member is at the front end p1 of the pedal trajectory (position 𝑎0𝑎1𝑏0𝑐1𝑑1𝑑0) in fig. 3, the position angle of sliding branch, 𝜃4, can be found by 4 5    (13) by decomposing the vectors in eq. (1) into x and y scalar components and rearranging them yields 2 2 4 4 1r cos r cos r   (14) 2 2 4 4r sin r sin  (15) squaring eqs. (14) and (15) and adding them together yields ( )   2 2 2 4 1 4 4 1 2r 2r cos r r r 0 (16) advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 195 fig. 4 vector loop diagram (a) right foot at a front end (b) right foot at a rear end fig. 5 detail drawing of inverted slider-crank mechanism by solving eq. (16), the length of vector, 𝑟4, is obtained as: ( ) ( )    2 2 2 4 1 4 1 4 1 2r r cos r cos r r  (17) from eqs. (14) and (15), the position angle of the timing adjustment wheel, 𝜃2, can be expressed as: 1 4 4 2 4 4 1 r sin tan r cos r      (18) similarly, when the foot support member is at the rear end p2 of the pedal trajectory (position 𝑎0𝑎2𝑏0𝑐2𝑑2𝑑0) in fig. 3, the difference between the position angles of flywheel and foot support link is 180° (as shown in figs. 3 and 5(b)), i.e. 𝜃6 = 𝜃5 − 𝜋. substituting this into eqs. (3) and (4) and yields ( )  5 6 5 7 7 8r r cos r cos r  (19) ( ) = +5 6 5 7 7 9r r sin r sin r  (20) squaring eqs. (19) and (20) and adding them together yields 7 7acos +b sin +c 0   (21) where advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 196 7 8a 2r r (22) 7 9b 2r r (23) c ( )    2 2 2 2 7 8 9 5 6r r r r r (24) by solving eq. (21), the position angle of the handle, 𝜃7, is obtained as: ( )       2 2 2 1 7 b a b c 2tan c a  (25) from eqs. (19) and (20), the angle of the flywheel, 𝜃5, can be expressed as: 1 7 7 9 5 7 7 8 r sin r tan r cos r        (26) as the foot support member is at the rear end p2 of the pedal trajectory in fig. 3, the position angle of the sliding branch, 𝜃4, can be obtained from eq. (13). since the position angle of 𝜃4 is known, the length of vector 𝑟4, 𝑟4, and the position angle of the timing adjustment wheel, 𝜃2, can be obtained from eqs. (17) and (18) as well. assume that ∅12 is the angular displacement of the flywheel as the pedal trajectory moves from the front end p1 to the rear end p2, and ∅21 is from the rear end p2 to the front end p1. the summation of these two angles is 360°, that is 12 21+ 2   (27) time ratio (tr) is the ratio of the time required for the slow stroke to the time required for the quick stroke. if the timing adjustment wheel runs at constant velocity, the time ratio tr can be expressed as: 12 21 tr    (28) assume the time ratio is known, then the rotation angles of the two strokes of the foot trajectory between two extreme positions can be expressed as: 21 2 1 tr     (29) 12 212    (30) as the pedal trajectory moves from the front end p1 to the rear end p2, the flywheel rotates with respect the fixed pivot and the rotation angle is approximately 180°. when the pedal position is at the front end p1, assume that the position angle of the sliding branch (link 4) is perpendicular downwards as shown in fig. 5(a). at this time, 𝜃41 denotes the position angle of the sliding branch and is equal to −90° while the position angle of timing adjustment wheel (link 2) is denoted as 𝜃21. when the pedal position is at the rear end p2, assume that the position angle of the sliding branch is perpendicular upwards as shown in fig. 5(b). at this time, 𝜃42 denotes the position angle of the sliding branch and is equal to 90° while the position angle of timing adjustment wheel is denoted as 𝜃22. from the geometry of the inverted slider-crank mechanism in fig. 5, the position angles of the timing adjustment wheel, 𝜃21 and 𝜃22, are symmetrical. therefore, 𝜃22 = −𝜃21 and the lengths of vector 𝑟4 at these two position are the same. furthermore, ∅21 can be expressed as: 21 22 21 21 22         (31) when the time ratio (tr) is known, the position angle of the timing adjustment wheel can be calculated from eqs. (29) and (31). advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 197 furthermore, when the pedal position is at the front end p1 and the position of the sliding branch is downwards, i.e., 𝜃41 = −90°, the position angle of timing adjustment wheel 𝜃2 is equal to 𝜃21. it can be observed that there are three unknown variables (𝑟1, 𝑟2, 𝑟4) in eqs. (14) and (15). assume that the length of the fixed link, 𝑟1, is known, the length of the link 2, 𝑟2, can be obtained as: 1 2 21 r r cos  (32) as the pedal trajectory moves from the front end p1 to the rear end p2, the flywheel rotates with respect to the fixed pivot and the rotation angle of the flywheel is approximately 180°. according to the assumption above, the relationship between the stroke angles (∅12 and ∅21) and the length ratio (𝑟2/𝑟1) of the timing adjustment wheel to the fixed link is shown in fig. 6(a). fig. 6(a) shows the stroke angle ∅12 is larger than the stroke angle ∅21. the smaller the length ratio is, the larger the stroke angle ∅12 is and the smaller the stroke angle ∅21 is. however, when the length ratio of the timing adjustment wheel to the fixed link is increased, the difference between the stroke angles ∅12 and ∅21 is reduced. the relationship between the time ratio and the length ratio is shown in fig. 6(b). from fig. 6(b), the smaller the length ratio of the timing adjustment wheel to the fixed link is used, the larger the time ratio becomes. on the contrary, the larger the length ratio is used, the smaller the time ratio becomes. by using fig. 6(b), it can be used to select proper length ratio to generate desired time ratio. (a) stroke angles (b) time ratio fig. 6 stroke angles and time ratio 4. kinematic analysis when the dimensions of the elliptical trainer mechanism and the position angle of the timing adjusting wheel 𝜃2 are known, the complete kinematic analysis and pedal trajectory can be derived and calculated. from eqs. (14) and (15), the position angle of the sliding branch, 𝜃4, can be expressed as: 1 2 2 4 2 2 1 r sin tan r cos r      (33) by expressing the eq. (2) into x and y scalar component equations and rearranging, the equations become 6 6 7 7 8 5 5r cos r cos r r cos     (34) 6 6 7 7 9 5 5r sin r sin r r sin     (35) where 𝜃5 = 𝜃4 + α. squaring eqs. (34) and (35) and adding them together yields advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 198 7 7acos +b sin +c 0   (36) where a ( ) 7 8 5 52r r r cos (37) b ( ) 7 9 5 52r r r sin (38) 2 2 2 2 2 5 6 7 8 9 5 8 5 5 9 5c r r r r r 2r r cos 2r r cos        (39) by solving eq. (36), the position angle of the handle, 𝜃7, is obtained as: ( )       2 2 2 1 7 b a b c 2tan c a  (40) from eqs. (34) and (35), the angle of foot support link, 𝜃6, can be found by 1 7 7 9 5 5 6 7 7 8 5 5 r sin r r sin tan r cos r r cos            (41) differentiating eqs. (14) and (15) with respect to time yields velocity equations as: ( ) ( ) ( )  2 2 2 4 4 4 4 4r sin r sin cos r     (42) ( ) ( ) ( )  2 2 2 4 4 4 4 4r cos r cos sin r     (43) when the velocity of timing adjusting wheel �̇�4 is known. by using gauss-jordan method to solve eqs. (42) and (43), �̇�4 and �̇�4 can be obtained as: ( )  2 2 4 4 2 4 r cos r     (44) ( )  4 2 2 4 2r r sin    (45) differentiating eqs. (42) and (43) with respect to time yields velocity equations as: ( ) ( ) ( )  6 6 6 7 7 7 5 5 5r sin r sin r sin      (46) ( ) ( ) ( )   6 6 6 7 7 7 5 5 5r cos r cos r cos      (47) where �̇�5 = �̇�4. by using gauss-jordan method to solve eqs. (46) and (47), �̇�6 and �̇�7 can be obtained as: ( ) ( )    5 5 7 4 5 6 7 6 r sin r sin       (48) ( ) ( )    5 5 6 7 5 6 7 6 r sin r sin       (49) therefore, the pedal position (𝑥𝑝, 𝑦𝑝) with respect to the fixed pivot of the flywheel can be expressed as: p 5 5 6 p 6x r cos r cos   (50) p 5 5 6 p 6y r sin r sin   (51) differentiating eqs. (50) and (51) with respect to time yields the pedal velocity as: advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 199 p 5 5 5 6 p 6 6x r sin r sin      (52) p 5 5 5 6 p 6 6y r cos r cos     (53) 5. design example and discussion to explain the design procedure of the proposed innovative mechanism, a design example is presented here for illustration. referring to a conventional design, assume that the parameters 𝑟5, 𝑟6, 𝑟7, 𝑟8 and 9r are 28.0 cm, 134.0 cm, 93.0 cm, 143.0 cm and 82.0 cm respectively. using eqs. (11) and (12), the angles 𝜃7 and 𝜃5 are calculated as 𝜃7 = −78.37°and 𝜃5 = −3.22° respectively. assume that the position angle of the sliding branch is 𝜃4 = 𝜃41 − 90° when the foot support member is at the front end of the pedal trajectory. the angle between the flywheel and the sliding branch can be calculated from eq. (13) as α = 𝜃5 − 𝜃4 = −86.78°. assume that the time ratio (tr) is 2.0, the angles ∅21 = 120°, ∅12 = 240°and 𝜃22 = −𝜃21 = 60° can be obtained from eqs. (29)-(31). finally, assume that fixed length 𝑟1is 13.0 cm, then the length of link 2 can be computed from eq. (32) as 𝑟2 = 26.0 cm. by using the vector-loop method and the kinematic analysis, motion simulation of pedal trajectory is carried out to validate the feasibility of the proposed innovative mechanism. the pedal trajectories of a conventional and the proposed design are shown in fig. 7. the pedal trajectories are drawn and dotted whenever the timing adjustment wheel is angular displaced with 10° increment. in fig. 7(a), for the conventional elliptical trainer, the distance between any adjacent points near the front and rear ends of the pedal trajectory is shorter and that in the middle of the supporting and striding travel is longer. in fig. 7(b), for the proposed design, the distance between any adjacent points near the bottom of pedal trajectory is shorter and that near the top is longer. if the timing adjustment wheel is operated at a constant speed, the speed of the foot near the front and rear ends is slower and that in the middle of the supporting and striding travels is faster for the conventional elliptical trainer. however, the speed of the foot at the bottom of the pedal trajectory is slower and that at the top is quicker for the proposed design. (a) conventional design (b) proposed design fig. 7 pedal trajectory fig. 8 pedal velocity advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 200 assume that the timing adjustment wheel runs at 60.0 rpm, the velocity of the pedal on the foot support member is shown in fig. 8. when the timing adjustment wheel is at about 60° and 250° of the conventional design, i.e. near the front and rear ends of trajectory, the pedal velocity is about 65.0 cm/sec. one the contrary, when the flywheel is at about 150° and 340°, i.e. in the middle of the supporting and striding travels, the pedal velocity is about 175.0 cm/sec. the pedal velocity of the conventional design is not same as the real jogging. however, when the timing adjustment rotates from 60° to 300° in the proposed design, i.e. near the bottom part of pedal trajectory, the pedal velocity changes between 65.0~120.0 cm/sec. when the flywheel is between 300° and 60°, i.e. near the top part of pedal trajectory, the pedal velocity varies between 65.0~350.0 cm/sec. the maximum speed during the striding travel is 3 times than that during the supporting travel. therefore, the average velocity of pedal trajectory on the supporting travel is slower than that on the striding travel. by using the quick-return effect of the inverted slider-crank mechanism, the timing of the pedal trajectory in this innovative design is more similar to the one in real jogging and meets the principles of ergonomics. when using this proposed innovative elliptical trainer design, the user can shift his body weight from one leg to the other before both of his legs extend to their extreme positions. compared to the conventional design, such a motion pattern proposed in this study can protect the user from suffering muscle sore and pain. by using a 3d cad design software, solidworks, the solid model of this innovative design is constructed and shown in fig. 9. for the sake of showing the structure of the innovative design, the flywheel is drawn as a crank in fig. 9. the cad prototype can be used for assembly, simulation and fabrication in order to confirm its feasibility and expedite the commercialization. (a) top view (b) isometric view fig. 9 cad solid model of the innovative elliptical trainer 6. conclusions the purpose of this paper is to propose and study an innovative elliptical trainer that imitates the timing of the foot trajectory during jogging. the procedures for the design of elliptical trainer with required time-ratio are illustrated. the pedal trajectory and the kinematics of the innovative elliptical trainer are analyzed and simulated. the results of the simulation confirm that the velocity of pedal trajectory on the supporting travel in the proposed design is slower than that on the striding travel. therefore, the proposed innovative design that mimics the timing of the foot trajectory can satisfy the design requirements and fit the principles of ergonomics for the joggers. based on the results of this investigation, the foot trajectory and the workload of this design can be further modified by adjusting the dimension, the ramp setting and the resistance of the motion. as for the dynamics of the innovative elliptical trainer and its test data under iso standard [21], they will be studied, collected and optimized in the future when the prototype is constructed. conflicts of interest the authors declare no conflict of interest. advances in technology innovation, vol. 5, no. 3, 2020, pp. 190-201 201 references [1] j. h. hoeberigs, “factors related to the incidence of running injuries,” sports medicine, vol.13, no. 6, pp. 408-422, november 1992. 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[21] stationary training equipment part 9: elliptical trainers, additional specific safety requirements and test methods, iso 20957-9, pp. 1-14, 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://www.scientific.net/author/jenq_huey_shyu_1 https://www.scientific.net/author/ching_kong_chen https://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22first%20name%22:%22yongbin%22&searchwithin=%22last%20name%22:%22qi%22&newsearch=true&sorttype=newest https://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22first%20name%22:%22cheong%20boon%22&searchwithin=%22last%20name%22:%22soh%22&newsearch=true&sorttype=newest https://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22first%20name%22:%22erry%22&searchwithin=%22last%20name%22:%22gunawan%22&newsearch=true&sorttype=newest https://ieeexplore.ieee.org/search/searchresult.jsp?searchwithin=%22first%20name%22:%22kay-soon%22&searchwithin=%22last%20name%22:%22low%22&newsearch=true&sorttype=newest  advances in technology innovation, vol. 6, no. 2, 2021, pp. 67-73 influence of cold sensation on plantar tactile sensation for young females tianyi wang 1,* , shima okada 1 , masaaki makikawa 1 , masayuki endo 2 , yuko ohno 3 1 department of robotics, faculty of science and engineering, ritsumeikan university, shiga, japan 2 department of children and women’s health, graduate school of medicine, osaka university, osaka, japan 3 department of mathematical health science, graduate school of medicine, osaka university, osaka, japan received 14 december 2020; received in revised form 31 january 2021; accepted 04 march 2021 doi: https://doi.org/10.46604/aiti.2021.6863 abstract cold sensation (cs) is a cold feeling on people’s hands or feet; this is a well-known health problem for young females. plantar tactile sensation plays an important role in postural control and is affected by skin temperature. however, there is no research focusing on the relation between cs and plantar tactile sensation. in this study, we address the question of whether the cs influences plantar tactile sensation. 32 non cold sensation (non-cs) and 31 cold sensation (cs) young females have participated in this research. a tactile sensation test was conducted at five plantar points (first and fifth toes, first and fifth metatarsal heads, and heel). experimental results showed that although there was no significant difference at the first and fifth toes as well as the first metatarsal head and heel, the sensation threshold at the fifth metatarsal head for cs was lower than the non-cs (21.61 ± 8.10 μm, 27.42 ± 11.02 μm respectively, p < 0.05). it was concluded that plantar tactile sensation for young females with cold sensation was more sensitive compared to healthy subjects. keywords: cold sensation, plantar sensation 1. introduction cold sensation (cs) is frequently observed in females [1]. previous studies reported that about 50% of women over 50 years suffered from cs [2]. cold sensation is a cold feeling at extremities, under the environment where healthy people dose not feel cold [3]. although cs is not perceived as a remarkable symptom [4], it has been proved that cs is not only related to higher frequency of chronic disease, but also associated to health problems during daily life [5]. cold sensation patients frequently complain of cold on their feet. the feet are direct and often the only interface between the human body and the ground [6]. along with the visual and vestibular systems, feedback provided from the somatosensory system at feet plays an important role in postural control [7]. the foot is able to recognize mechanical stimuli through cutaneous mechanoreceptors located in the epidermis and dermis of glabrous skin [8]. there are four types of cutaneous mechanoreceptors: merkel's disk, ruffini's corpuscles, meissner corpuscles, and pacinian corpuscles. except for meissner corpuscles, where the skin temperature will not affect its function, it was reported that cooling the skin reduced the cutaneous sensation and firing response of mechanoreceptors [9]. previous research has revealed the relation between the foot sole temperature and plantar cutaneous sensation only through a passive cooling method such as cold pack [9]. it is still unclear whether cs patients have lower tactile sensation. we consider that knowledge about the relation between cold sensation and plantar tactile sensation will provide useful information for the necessary and appropriate health care for cs patients. * corresponding author. e-mail address: t-wang@fc.ritsumei.ac.jp advances in technology innovation, vol. 6, no. 2, 2021, pp. 67-73 68 as a consequence, the purpose of this paper is to investigate the relation between cold sensation and plantar tactile sensation. this paper consists of five parts. section 2 describes the human subjects and the method. results are shown at section 3. section 4 discusses the experimental results and section 5 concludes this paper. 2. subjects and method 2.1. human subjects we asked sixty-three female students (age: 21.5 ± 1.7 years, height: 157.92 ± 6.07 cm, weight: 51.45 ± 6.16 kg, body mass index: 20.60 ± 2.03 kg/m 2 ) with regular menstrual cycles to participate in the experiment. no subject reported any history of endocrinopathy, cardiovascular disease, gynecological conditions, or connective tissue disease. subjects were required to abstain from alcohol and caffeine for at least one day and from any food at least 2 h before the experiment. before the experiment, all subjects were informed of the purpose and process of this study and provided written informed consent. subjects were free to withdraw from the study at any time. this study was approved by the ethics committee on osaka university hospital (no. 19162, august 2019). the subjects with cold sensation was defined according to our previous study [10]. 2.2. experiment environment the experiment was performed from 2019 july 31 to 2019 october 21, 10:00 to 16:00. the experiment was only conducted during follicular phase; taking consideration about the body temperature fluctuates depending on the phase of the menstrual cycle. local temperature during the experiment was from 30.1 ± 12.3 °c to 22.8 ± 4.7 °c, average 26.9 ± 4.4 °c [11]. the indoor temperature was 24.6 ± 0.6 °c, humidity was 54.5 ± 12.3%. 2.3. plantar cutaneous sensation test tsuneya et al. [12] reported that insufficient toe contact, also known as floating toe, was observed in 76.2% of females and particularly on the fifth toe. as insufficient toe contact could reduce experiment accuracy, before the plantar cutaneous sensation test, we first perform a foot pressure distribution test to check whether subjects' plantar could fully contact the ground. fig. 1 describes the method and example of the foot pressure distribution test. fig. 1(a) shows the overview of foot pressure measurement. i-scan150© nitta pressure sensor sheet (165 × 165 × 0.1 mm) was used to measure the subjects' dominant feet. this sensor sheet contains 1,936 sensor points, and the high resolution could satisfy the need. fig. 1(b) described two types of foot pressure distributions. in this study, if the subject's toe was well contacted, it was defined normal; if any toe was not well contacted, it was defined floating toe and we did not test the plantar tactile sensation at the toe. (a) method for measuring foot pressure distribution (b) left: normal foot pressure distribution; right: fifth toe floating fig. 1 foot pressure distribution test fig. 2 shows an overview of the plantar tactile sensation test. fig. 2(a) shows the system overview of plantar tactile sensation testy system. in this study, © asuka electri, a plantar tactile stimulation platform (400 × 400 × 75 mm) was advances in technology innovation, vol. 6, no. 2, 2021, pp. 67-73 69 utilized. this system mainly comprises three parts: a sensation stimulation platform, a response button, and a computer for motor control and data processing. fig. 2(b) showed the mechanism of plantar tactile stimulation. the contact part is driven using a miniature linear guide with a motor-ball screw system, which can provide variable ranges from 5 to 2000 μm and velocity of shearing movement from 0.1 to 250 mm/s [13]. (a) system overview of plantar tactile sensation test system (b) mechanism of plantar tactile stimulation fig. 2 plantar tactile sensation test system plantar sensation test points are shown in fig. 3(a). in this research, five plantar points were selected as test points. to eliminate serial effects, the stimulation order was set as 1: first toe, 2: heel, 3: fifth toe, 4: first metatarsal head, 5: fifth metatarsal head [14]. white circles denote the test points, and the dotted line with a single arrow denotes the stimuli order. fig. 3(b) describes how to define the sensation threshold. first row denotes the stimulation level; second row shows the subject’s feeling at the feet; third row shows the response to stimulation. twenty stimulation levels were set for the experiment. the subjects were told to press the response button as fast as they can after they felt the movement of the contact part. if they felt the movements and continuously pressed the response button three times, stimulation at the first time when the response button was pressed was defined as the threshold at that plantar point. all tests were conducted on the subjects' dominant feet. (a) foot map with test points and stimuli order (b) method for defining sensation threshold fig. 3 test points and sensation threshold table 1 threshold, stimulation time, and frequency for each stimulation level. level 1 2 3 4 5 6 7 8 9 10 threshold (μm) 5 10 15 20 25 30 35 40 45 50 time (msec) 2 4 6 8 10 12 14 16 18 20 frequency (hz) 500 250 167 125 100 83 71 63 56 50 level 11 12 13 14 15 16 17 18 19 20 threshold (μm) 55 60 65 70 75 80 85 90 95 100 time (msec) 22 24 26 28 30 32 34 36 38 40 frequency (hz) 45 40 38 36 33 31 29 28 26 25 table 1 shows details of the twenty stimulation levels. stimulation range (threshold) was set as 5 μm, 10 μm, 15 μm, …, 90 μm, 95 μm, 100 μm, with the same velocity of 5 mm/s. thus, stimulation time and frequency can be calculated as following: 2 /time threshold velocity  (1) 1/frequency time (2) advances in technology innovation, vol. 6, no. 2, 2021, pp. 67-73 70 2.4. data analysis plantar tactile threshold data were obtained from a special software (“stimulation threshold” ©asuka electri). the student's t-test was used to test the significance of difference between two groups, with the significance level set at 5%. the t-test was performed using matlab r2020a © mathworks. 3. results the subjects’ basic information is summarized in table 2. bar charts in fig. 4 show the results of plantar tactile sensation. left part is the result of sensation threshold, and the right part is the result of response frequency. the horizontal axis shows the amplitude of threshold and frequency, and the vertical axis represents different test points. gray bars represent the non-cs group, and white bars indicate the results of the cs group. notice that the number of test points at the fifth toe (point 3) was different from others. after checking the foot pressure distribution, the floating toe at fifth toe was observed in 9 subjects in the non-cs group and 14 subjects in the cs group. thus, only 23 non-cs subjects and 17 cs subjects had the plantar sensation of fifth toe (point 3). although there was no significant difference of stimulation threshold at first toe, heel, fifth toe or first metatarsal head (p > 0.05), the threshold at the fifth metatarsal head (point 5) for the cs group was significantly lower than the non-cs group (21.61 ± 8.10 μm, 27.42 ± 11.02 μm, respectively, p < 0.05). as regards to stimulation frequency, the metatarsal parts (points 4 and 5) for the cs group showed higher amplitudes than the non-cs group (p < 0.05), 112.94 ± 45.64 hz and 90.87 ± 32.61 hz at point 4, 127.44 ± 35.02 hz and 106.80 ± 44.80 hz at point 5. table 2 age, physical characteristics of subjects. non-cs (n = 32) cs (n = 31) p value age (years) 21.09 ± 1.80 21.97 ± 1.52 < 0.05 height (cm) 158.70 ± 6.28 157.11 ± 5.84 0.30 weight (kg) 52.39 ± 7.04 50.47 ± 5.03 0.22 bmi (kg/m 2 ) 20.75 ± 2.01 20.48 ± 2.08 0.60 value: mean ± standard deviation bmi: body mass index fig. 4 result of threshold and frequency to plantar tactile sensation fig. 5 shows the result of the threshold–frequency plot of the plantar sensation and response ranges for three mechanoreceptors. the blue square represents the meissner corpuscle, the orange square represents the pacinian corpuscle, and the green square represents the ruffini ending. markers in red and blue represent the data of the non-cs and cs groups, respectively. the dashed line is the characteristic curve of threshold–frequency and plotted using the data shown in table 1. standard deviations for the threshold and frequency were plotted in black solid lines. the frequency range of the meissner corpuscle was 3–100 hz, ruffini ending was 15–400 hz, and pacinian corpuscle was 10–500 hz [15]. advances in technology innovation, vol. 6, no. 2, 2021, pp. 67-73 71 fig. 5 threshold–frequency of plantar tactile sensation for the non-cs and cs groups 4. discussion according to the results of the tactile sensation test, the threshold at the fifth toe (point 3) was higher than the other four points both for cs and non-cs groups. ino et al. [14] tested the plantar sensation at the same points in this research and observed that the fifth toe had the highest plantar detection threshold, followed by the first metatarsal head. surprisingly, we observed that young females with cs had a lower tactile threshold at the foot sole, opposite to the findings in the previous study. in [2], we reported that plantar sensation thresholds were higher for the cs group (n = 18) than the non-cs group (n = 11) and that young females with cs were less sensitive at the foot than the healthy subjects. however, the definition of cs in the previous study was completely different in [2]. we used a cooling recovery test to check whether subjects’ plantar temperature could return to a particular level after cooing the feet with 15 °c cold water. although cold water stimulation has been proved as an effective approach to defining cs, we did not crosscheck the result with either the questionnaire or the thermal check methods. thus, we considered that subjects diagnosed with cs in the previous study were different from the cs group in this research. as previously mentioned, there are four types of mechanoreceptors distributed on the plantar glabrous skin. they are physiologically classified according to their adaption characteristics and the size of the receptive fields [16]: merkel's disk, which are slow adapting receptors with small receptive fields (sa ⅰ), generally provide information on indentation and press; ruffini's corpuscles, which are slow adapting receptors with large receptive fields (sa ⅱ), can detect skin stretching; meissner corpuscles, which are fast-adapting receptors with small receptive fields (fa ⅰ), is more responsive to tactile events such as the motion or slippage of an object across the skin; pacinian corpuscles, which are faster adapting receptors with large receptive fields (fa ⅱ), is well known as a mechanoreceptors responding to vibration. according to the result shown in fig. 5, all markers were located at the threshold--frequency response areas of pacinian corpuscles and ruffini endings (orange and green squares). only the markers representing the fifth toes (rhombus in blue and red) and the first metatarsal head of the non-cs (red circle) group were located at the areas of all three mechanoreceptors. according to the movement of the contact part, mechanical stimulation herein involved a multi-sensory approach, including skin motion, stretch, and vibration. thus, it is reasonable to consider that fa ⅰ, fa ⅱ, and sa ⅱ mechanoreceptors participated in the role of sensing the tiny movement of the contact part. in a 2002 study, shimojo et al. outlined that meissner corpuscles receive no effect from skin temperature [17]. despite the receptive fields of pacinian corpuscles being the largest among these four mechanoreceptors, fa ⅱ only takes up 12% of all foot sole cutaneous mechanoreceptors (43 in 364) [18], and the distribution of fa ⅱ along the foot sole is lower than those for advances in technology innovation, vol. 6, no. 2, 2021, pp. 67-73 72 other mechanoreceptors at the same sole area [6]. above all, fast-adapting mechanoreceptors have little influence on plantar tactile sensation for the cs group herein. strzalkowski et al. [19] reported that there were 74 sa ⅱ cutaneous mechanoreceptors among all 364 feet sole cutaneous mechanoreceptors, which was higher than sa ⅰ (63) and fa ⅱ (43). moreover, according to viseux’s work [6], the percentage distribution of sa ⅱ at the metatarsal head was higher than that at the toes and the heel. compared with skin motion and vibration, the metatarsal head seems to be more sensitive to skin stretching. in contrast, it was noticed that lowering the skin temperature enhanced the impulse firing of ruffini endings [18]. thus, it was suspected that the low foot skin temperature for the cs group increased the impulse firing of sa ⅱ mechanoreceptors, thereby improving foot tactile sensation. the mechanical properties of the skin may also partially explain some difference in sensation threshold between the cs and the non-cs groups. cs patients had higher skin hardness at the foot sole [20]; compared with the toes and the heel, the highest skin hardness was observed at the fifth metatarsal head [21]. meanwhile, it was hypothesized that when skin hardness increases, it was easier to have stress concentration and increased sensation at the finger [22].thus, another possible reason to explain the finding in this study is: for young females with cs, lower plantar sensation threshold, namely more sensitivity at the foot, is possibly due to the higher skin hardness at the fifth metatarsal head. the ability to detect tiny movements such as slippage varies if the stimuli direction changes [17]. specifically, the threshold of detecting slippage increases from the vertical to the horizontal direction. in this research, all subjects were asked to put their feet on the test platform along the same direction of contact part movement. thus, discussing the effect of stimulation direction on the sensation threshold was difficult. we will investigate this aspect in a future study. another current technical problem is that controlling the surface temperature of the sensation test platform is difficult. a difference in temperature between the subject's foot sole and contact area may influence the test result. although no subject reported a cold feeling when they put her foot on the test platform during the experiment, the method of avoiding cooling the foot from the experiment equipment should be focused on in a future study. 5. conclusions in this paper, plantar tactile sensation for young females with cold sensation was studied. the experiment results demonstrated that the sensation threshold at the fifth metatarsal head for the cold sensation group was lower than the non-cold sensation group. enhanced impulse firing due to the lower skin temperature and higher skin hardness were considered the reasons for young females with cold sensation being more sensitive. conflicts of interest the authors declare no conflict of interest. references [1] y. m. hur, j. h. chae, k. w. chung, j. j. kim, h. u. jeong, j. w. kim, et al., “feeling of cold hands and feet is a highly heritable phenotype,” twin research and human genetics, vol. 15, no. 2, pp. 166-169, april 2012. 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[20] a. ushiroyama, “clinical analysis and treatment of hiesho,” journal of clinical and experimental medicine, vol. 215, no. 11, pp. 925-929, 2005. (in japanese) [21] y. jammes, m. viala, w. dutto, j. p. weber, and r. guieu, “skin hardness and epidermal thickness affect the vibration sensitivity of the foot sole,” clinical research on foot & ankle, vol. 5, no. 3, pp. 1-5, august 2017. [22] h. jeong, m. kaneko, m. higashimori, and k. matsukawa, “improvement of tactile sensitivity under pressing a finger base,” transactions of the society of instrument and control engineers, vol. 43, no. 11, pp. 973-979, november 2007. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://tenki.jp/past/2019/07/weather/6/30/47772/ http://www.tmd.ac.jp/med/phy1/ptext/somat_1.html  advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 the design of mold clamping mechanisms with two dead-position configurations tzu-hsia chen 1,* , long-chang hsieh 2 1 department of mechanical and computer-aided engineering, feng chia university, taiwan 2 department of power mechanical engineering, national formosa university, taiwan received 28 april 2019; received in revised form 08 june 2019; accepted 11 july 2019 doi: https://doi.org/10.46604/aiti.2020.4164 abstract blow-molding machines are divided into two types: (1) rotary type blow-molding machine, and (2) linear type blow-molding machine. good kinematic characteristics of mold clamping mechanism is the goal pursued by manufacturers of blow-molding machine. traditionally, the mold clamping mechanism has only one dead-position configuration for the mold in the closed position. when the mold is in the open position, the mold clamping mechanism does not have dead-position configuration. this study focuses on the design of mold clamping mechanisms with two dead-position configurations when the mold is in open and closed positions. firstly, with reference to the existing patents, based on the yan's creative design methodology, four design concepts of mold clamping mechanisms are synthesized. then, according to the studies on kinematics of mechanisms, three mold clamping mechanisms with two dead-position configurations are also synthesized. the results of this paper will enhance the research and development (r&d) capability of the mold clamping mechanisms to improve industrial competitiveness. keywords: blow-molding machine, conceptual design, creative design, dead-position configuration, mold clamping mechanism 1. introduction due to the reason that the usage of polyethylene terephthalate (pet) bottles is more and more widely, how to increase the production of pet bottles has become a major issue for the manufacturers. the requirements of the blow-molding machine will be stricter than ever. in order to improve the stability of the production of pet bottles, reducing the vibration and noise during the production process, extending the life of the machine, it is necessary to analyze the kinematics of mold clamping mechanism. good kinematic characteristics of mold clamping mechanism is the goal pursued by manufacturers. blow-molding machines are divided into two types: (1) rotary type blow-molding machine as shown in fig. 1 (a), and (2) linear type blow-molding machine as shown in fig. 1 (b). the motion of linear blow-molding machine is linear and reciprocated. the mold clamping mechanisms for linear type blow-molding machine are simple, stable, and reliable. figs. 2 (a) and 2 (b) show the linear type blow-molding machine and its mold clamping mechanism. traditionally, the mold clamping mechanism of linear type blow-molding machine has only one dead-position configuration for the mold in the closed position. when the mold is in the open position, the mold clamping mechanism does not have dead-position configuration. it results poor kinematic characteristics (larger or infinite acceleration), and causes blow-molding machine unstable. for the mold clamping mechanisms with two dead-position configurations in open and closed positions, it will have better kinematic characteristics (smaller max. acceleration), and causes blow-molding machine more stable. * corresponding author. e-mail address: summer34134@gmail.com tel.: +886-4-2451-7250 ext.3501 advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 34 (a) rotary type blow-molding machine (b) linear type blow-molding machine fig. 1 types of blow-molding machines (a) linear blow-molding machine (b) mold clamping mechanism fig. 2 linear blow-molding machine this study focuses on the design of mold clamping mechanisms with two dead-position configurations for linear blow-molding machine. firstly, by referring to the existing patents [1-7] and the studies on the creative design [8-13], four feasible design concepts of mold clamping mechanisms are synthesized. then, according to the studies on kinematics of mechanisms [14-20], three mold clamping mechanisms with two dead-position configurations are also synthesized. when the advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 35 mold is in open and closed positions, the mold clamping mechanism will stay in the state of dead-position configuration (meanwhile, the mechanism is converted to desired structure). hence, the mold clamping mechanisms with two dead-position configurations have the advantage of more safety. the results of this research can be used as reference when designing the real mold clamping mechanism and enhance r&d capability of the mold clamping mechanisms to improve industrial competitiveness. 2. existing design (a) clamping mechanism (b) kinematic skeleton fig. 3 the mode clamping mechanism of servo-drive type injection molding machine [1] (a) opening/closing mechanism (b) kinematic skeleton fig. 4 driving device of controlling mode opening and closing for plastic molding machine [2] advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 36 lots of researches have been done about the topological characteristics for mold clamping mechanisms. fig. 3 [1] and fig. 4 [2] show planar mechanisms with 6 links and 7 joints. for the mold clamping mechanism shown in figs. 3 and 4, the mold clamping mechanism has a dead-position configuration when the mold is in the closed position. however, when the mold is in the open position, the mold clamping mechanism does not have dead-position configuration. the purpose of this paper is to design the mold clamping mechanism having dead-position configurations when the mold is in the open and closed positions. the mobility of planar mechanism can be obtained by following equation. f=3(n-j-1)+σfi (1) where n is number of links, j is number of joints, and fi is the degrees of freedom of joint i. the mechanisms, shown in figs. 3 and 4, have 6 links, 7 joints (5 revolute pairs and 2 prismatic pair), according to equation of mobility, we get: f=3(n-j-1)+σfi =6(6-7-1)+7=+1 (2) the topological characteristics of mode clamping mechanisms for linear blow-molding machine are concluded as follows: (1) it consists of 6 members and 7 joints. (2) it has ground link (gr, member 1), input slider (sin, member 2), first connecting rod (member 3), rocker (member 4), second connecting rod (member 5), and output slider (sout, member 6). (3) it has 7 joints including 5 revolute joints (jr) and 2 prismatic joints (jp). (4) it is planar mechanism with 1 degree of freedom. according to above reasoning, fig. 5 shows the corresponding generalized chain of the patent [2] shown in fig. 4. fig. 5 generalized chain of the mode clamping mechanism [2] 3. conceptual design in 1998, professor yan proposed a creative design methodology [8], shown in fig. 6, to create all feasible design concepts for mechanical devices. the steps are: step 1: identify the topological characteristics based on the existing designs with required design specifications. step 2: select any existing design and transform it into its corresponding generalized chain. step 3: synthesize all generalized chains that have the same numbers of links and joints as the generalized chain obtained in step 2. step 4: assign types of links and joints to each generalized chain obtained in step 3, to have the atlas of feasible specialized chains based on the algorithm of specialization to meet the design requirements and constraints. step 5: particularize each feasible specialized chain obtained from step 4 to its corresponding schematic format of mechanical device, to have the atlas of mechanical devices. advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 37 fig. 6 yan’s creative design methodology [8] 3.1 atlas of kinematic chain according to the process of number synthesis, 2 kinematic chains with 6 links and 7 joints, shown in fig. 7, are synthesized. (a) 6-1 (b) 6-2 fig. 7 atlas of (6, 7) kinematic chains 3.2 design requirements and constrains based on the concluded topological characteristics of existing designs, the design requirements and constrains of the mode clamping mechanisms are concluded as follow: (1) there must be a ground link (gr), input slider (sin,), output slider (sout). (2) the ground link as the frame must be ternary link. (3) the ground link (gr) must be adjacent to input slider (sin) and output slider (opening/closing mold, sout) with prismatic pair. (4) input slider (sin) and output slider (sout) can’t be in the same circuit with 1 degree of freedom. (5) the mode clamping mechanism only includes prismatic pair (jp) and revolute pair (jr). (6) the mode clamping mechanism must have 2 prismatic pairs. 3.3 specialization subject to certain design requirements and constraints, the specializing steps for mode clamping mechanism are concluded as follow: existing designs generalization topological characteristics generalized chains number synthesis atlas of kinematic chains specialization design requirement and constraints atlas of feasible specialized chains particularization atlas of designs advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 38 (1) for each generalized (kinematic) chain, identify the ground link (gr) for all possible cases. (2) for each case obtained in step 1, identify input slider (sin, denoted by thick black line ) and output slider (sout, denoted by thick black line ). (3) for each case obtained in step 3, identify the corresponding revolute pair (denoted by ○) and prismatic pair (denoted by ●). based on the design requirements and constraints, 3 feasible specialization chains, shown in figs. 8(a), 8(b), and 8(c), are generated by the process of specialization. (a) 6-1-1 (b) 6-2-1 (c) 6-2-2 fig. 8 atlas of (6, 7) feasible specialized chains 3.4 particularization for each feasible specialized chain, it can be particularized into its corresponding kinematic skeleton by the reverse process of generalization. for the feasible specialized chains shown in figs. 8 (a) ~8 (c), their corresponding kinematic skeletons of mode clamping mechanisms are shown in figs. 9 (a)~9 (c). according to the kinematic skeletons shown in figs. 9 (a) ~9 (c), one possible multiple-joint mechanism is synthesized and shown in fig. 9 (d). (a) mechanisms (i) (b) mechanisms (ii) (c) mechanisms (iii) (d) mechanisms (iv) fig. 9 atlas of feasible mold clamping mechanisms of (6, 7) generalized chain 4. clamping mechanisms with two dead-position configurations 4.1 case i fig. 10 (a) and 10 (b) show the mode clamping mechanism (i) and its corresponding vector coordinate system of the mechanism shown in fig. 9 (a). according to fig. 10 (b), the mechanism has two independent vector loops (vector loops 1 and 2). vector loops 1 and 2 can be expressed as follows: (3) 2 3 4 0ar r r   advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 39 (4) according to fig. 10 (b), θ4a＝θ4b+α and θ4c＝θ4a-π+β are the given conditions. if we substitute them into the above equations, then the components x and y can be expressed as: (5) (6) (7) (8) (a) kinematic skeleton (b) vector coordinate system fig. 10 mold clamping mechanism (i) (a) closed position (dead-position configuration, line l1) (b) open position (dead-position configuration, line l2) fig. 11 mold clamping mechanism (i) with two dead-position configurations if r2y＝153.5mm, r3＝176mm, r4a＝190mm, r4b＝r5＝250mm, α=30⁰, then r4c＝127.78mm and β=101.97⁰. according to eqs. (5) ~ (8), we get: (1) if θ4b＝0⁰ (θ4a＝30⁰), then θ3＝-19.41⁰, r2x＝-1.45mm, θ4c＝θ4a-π+β＝-48.03⁰, θ5＝0⁰, and r6＝500mm. fig. 11 (a) shows the corresponding dead-position configuration (line l1) of mode clamping mechanism at closed position. (2) if θ4b＝60⁰ (θ4a＝90⁰), then θ3＝11.97⁰, then r2x＝-171.22mm, θ4c＝θ4a-π+β＝11.97⁰, θ5＝-60⁰, and r6＝250mm. fig. 11(b) shows the corresponding dead-position configuration (line l2) of mode clamping mechanism at open position. according to figs. 11 (a) and 11 (b), the complete mechanism of mode clamping mechanism (i) with two dead-position configurations are shown in figs. 12 (a) and 12 (b). 4 5 6 0br r r   2 3 3 4 4cos cos 0x a ar r r    2 3 3 4 4sin sin 0y a ar r r    4 4 5 5 6cos cos 0b br r r    4 4 5 5sin sin 0b br r   advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 40 (a) closed position (dead-position configuration, line l1) (b) open position (dead-position configuration, line l2) fig. 12 complete mechanism of mold clamping mechanism (i) with two dead-position configurations 4.2 case ii fig. 13 (a) and 13 (b) show the mode clamping mechanism and its corresponding vector coordinate system of the mechanism shown in fig. 9 (b). according to fig. 13 (b), the mechanism has two independent vector loops (vector loops 1 and 2). vector loops 1 and 2 can be expressed as follows: (a) kinematic skeleton (b) vctor coordinate system fig. 13 mold clamping mechanism (ii) (9) (10) according to fig. 13 (b), θ3c＝θ3a+π-β are the given conditions. if we substitute them into the above equations, then the components x and y can be expressed as: (11) (12) (13) 2 3 4 0ar r r   4 3 5 6 0cr r r r    2 3 3 4 4cos cos 0x a ar r r    2 3 3 4 4sin sin 0y a ar r r    4 4 3 3 5 5 6cos cos cos 0c cr r r r      advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 41 (14) if r2y＝162.8mm, r4＝94mm, r3a＝162.8mm, r3c＝156mm, r5＝250mm, and β=90⁰, according to eqs. (11) ~ (14), we get: (1) if θ4＝0⁰, then θ3a＝-90⁰, r2x＝94mm, θ3c＝θ3a+π-β＝0⁰, θ5＝0⁰, and r6＝500mm. fig. 14 (a) shows the corresponding dead-position configuration of mode clamping mechanism at closed position. (2) if θ4＝60⁰, then θ3a＝-30⁰, r2x＝-93.99mm, θ3c＝θ3a+π-β＝60⁰, θ5＝-60⁰, and r6＝250mm. fig. 14 (b) shows the corresponding dead-position configuration of mode clamping mechanism at open position. according to figs. 14 (a) and 14 (b), the complete mechanism of mode clamping mechanism (ii) with two dead-position configurations are shown in figs. 15 (a) and 15 (b). (a) close position (dead-position configuration, line l1) (b) open position (dead-position configuration, line l2) fig. 14 mold clamping mechanism (ii) with two dead-position configurations (a) closed position (dead-position configuration, line l1) (b) open position (dead-position configuration, line l2) fig. 15 complete mechanism of mold clamping mechanism (ii) with two dead-position configurations 4.3 case iii fig. 16 (a) and 16 (b) show the mode clamping mechanism and its corresponding vector coordinate system of the mechanism shown in fig. 9 (c). according to fig. 16 (b), the mechanism has two independent vector loops (vector loops 1 and 2). vector loops 1 and 2 can be expressed as follows: 4 4 3 3 5 5sin sin sin 0c cr r r     advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 42 (a) kinematic skeleton (b) vector coordinate system fig. 16 mold clamping mechanism (iii) (a) close position (dead-position configuration, line l1) (b) open position (dead-position configuration, line l2) fig. 17 mold clamping mechanism (iii) with two dead-position configurations (15) (16) according to fig. 16(b), θ4b＝θ4a-π+β are the given conditions. if we substitute them into the above equations, then the components x and y can be expressed as: (17) (18) (19) (20) if r2y＝120mm, r3＝120mm, r4a＝250mm, r4b＝120mm, r5＝250mm, and β=90⁰, according to eqs. (17) ~ (20), we get: (1) if θ5＝0⁰, then θ4a＝0⁰, r2x＝380mm, θ4b＝θ4a-π+β＝-90⁰, θ3＝0⁰, and r6＝500mm. fig. 17(a) shows the corresponding dead-position configuration of mode clamping mechanism at closed position. 5 4 6 0ar r r   2 3 4 6 0br r r r    5 5 4 4 6cos cos 0a ar r r    5 5 4 4sin sin 0a ar r   2 3 3 4 4 6cos cos 0x b br r r r     2 3 3 4 4sin sin 0y b br r r    advances in technology innovation, vol. 5, no. 1, 2020, pp. 33-44 43 (2) if θ5＝-60⁰, then θ4a＝60⁰, r2x＝42.15mm, θ4b＝θ4a-π+β＝-30⁰, θ3＝-30⁰, and r6＝250mm. fig. 17(b) shows the corresponding dead-position configuration of mode clamping mechanism at open position. according to figs. 17(a) and 17(b), the complete mechanism of mode clamping mechanism (iii) with two dead-position configurations are shown in figs. 18(a) and 18(b). according to fig. 18(b), the mold is damaged because of too large stroke of the input slider, so it is not a good design. (a) closed position (dead-position, line l1) (b) open position (dead-position, line l2) fig. 18 complete mechanism of mold clamping mechanism (iii) with two dead-position configurations 5. conclusions traditionally, the mold clamping mechanism does not have dead-position configuration for the mold in the open position. this study focuses on the design of mold clamping mechanisms with two dead-position configurations when the mold is in open and closed positions. firstly, by referring to the existing patents and the studies on the creative design, four feasible design concepts of mold clamping mechanisms are synthesized. then, according to the studies on kinematics of mechanisms, three mold clamping mechanisms with two two dead-position configurations are also synthesized. because of too large stroke of input slider, the design case iii is not good. only two mold clamping mechanisms with two two dead-position configurations (case i and case ii) can be used to design the real mold clamping mechanism for linear blow-molding machine. the results of this research will enhance r&d capability of the mold clamping mechanisms to improve industrial competitiveness. acknowledgement the authors are grateful to chum-power machinery co., ltd. for the support of this research under 107af094. conflicts of interest the authors declare no conflict of interest. references [1] g. x. lai, w. f. su and g. x. lin, the mode clamping mechanism of servo-drive type injection molding machine, taiwan patent, 542097, jul. 11, 2003. 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[20] f. c. chen, y. f. tzeng, and w. r. chen, “on the mechanism design of an innovative elliptical exerciser with quick-return effect,” international journal of engineering and technology innovation, vol. 8, no. 3, pp. 228-239, 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 remote monitoring for the operation status of cnc machine tools based on html5 yu-shun wang, ling-song he * , zhi-qiang gao, jun-feng wang, yang-fan cao school of mechanical science and engineering, huazhong university of science and technology, wuhan, china received 23 april 2019; received in revised form 10 may 2019; accepted 28 july 2019 abstract in order to improve the accuracy of remote monitoring of computer numerical control (cnc) machine tools and reduce the difficulty of monitoring; a remote monitoring method for cnc machine tools based on html5 is proposed in this paper. the core idea of this method is to record external sensor information and internal working condition information in the same time, and then visualize the information in multiple directions. monitoring accuracy is improved through the combined use of internal and external information. in response to the difficult problem of traditional method monitoring; the internal working condition information, external sensor information, 3d model and multimedia information of cnc machine tools are jointly visualized. the 3d model synchronous motion is driven by real-time working condition data. remote low-latency multimedia information transmission is implemented by using cloud live broadcast technology. keywords: cnc machine tool, remote monitoring, html5, 3d model 1. introduction intelligent manufacturing, as the core of industry 4.0, has been the focusing research of global manufacturing field in recent years. as a “mother machine”, the cnc machine tool is the core equipment for intelligent manufacturing. its monitoring of operation status and adaptive control are critical to intelligent manufacturing. as a means of monitoring, the operation status of cnc machine tools and remote monitoring have attracted attention of many researchers. for traditional remote monitoring of cnc machine tools, the monitoring of operation status and fault diagnosis are realized by monitoring the external sensor information (e.g., vibration, sound, current, temperature). however, the sensor signal is the physical quantity measured indirectly. it can only represents the state of the sensor, but not the whole cutting process. in addition, the stability and reliability of the sensor signal can be easily affected by the complex working environment of the cnc machine tool (e.g., electromagnetic, temperature, external noise), which can easily prone to misjudgment [1]. moreover, the data acquisition of the internal operating conditions is ignored, which lead to lack of data (e.g., g code, axis position, feed rate, spindle speed) guidance during condition monitoring and fault diagnosis. therefore, it is not possible to understand the state and the process of processing in a short time, which can easily lead to misjudgment. simultaneously, the degree of data visualization is limited and the interactive operations in data analysis was scanty. in recent years, researchers have investigated in a lot of energy to break through the limits of traditional cnc machine tool monitoring methods. in 2016, avic proposed a four-layer cyber physical system (cps) cnc machining process intelligent platform, which could monitor the machine tool in real time and realize ultra-low delay transmission of processing * corresponding author. e-mail address: helingsong@hust.edu.cn tel.: +86-13554303940 advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 261 data and high-fidelity 3d visualization and reproduction [2]. in 2017, eun-young heo et al. proposed a process monitoring system combined with virtual machining that simulates the nc tool path cutting process through virtual machining to predict the static and dynamic characteristics of the operation [3]. the real-time diagnosis was realized by combining the internal working condition data and sensor data of the cnc machine tool with the predicted virtual machining data. in the same year, yi cai et al. merged sensor data and information to build a digital twin virtual machine for network physical manufacturing, which was used for the diagnosis and prediction of cnc machine faults [1]. the above researches all used the working condition information and external sensor information as main data source, which could significantly improve the accuracy of monitoring. however, the cross-platform, visualization, and interaction of the designed system need to be further improved. in view of the advantages of hyper text markup language (html5) can supports the multi-device cross-platform operation, responsive web design, instant update, better interaction, and good support for audio and video[4, 5], a remote monitoring method for cnc machine tools based on html5 is proposed in this paper. this method used the working condition information and external sensor information inside the open cnc system as the main data source, and monitored the machine tool through internal and external information fusion to improve the monitoring accuracy. visualize with html5, make full use of its high-level support for 2d charts, 3d models, audio and video visualization tools, and multi-dimensional visualization of data to reduce the difficulty of monitoring. 2. overall system design the design concept for the overall architecture of the system was the cps model [1-2, 6]. a four-layer architecture based on device awareness layer, network layer, data layer and visualization layer was built, and its system architecture is shown in fig. 1. fig. 1 system architecture the internal working condition data, external sensor data, and multimedia data are acquired through the device sensing layer in this system. the data is collected and parsed, and then the processed data was transmitted to the data layer through the network layer to complete the data service and data storage. the core of the remote monitoring system is the visualization layer. the data processed by the data layer is again transmitted to the visualization layer via the network layer, and the multi-level visual monitoring of the data is completed and the corresponding analysis and processing are performed. it can also provide operators with more real-time, more comprehensive, more decision-making reference value cnc machining process information. this helped the operator to strengthen the monitoring and fault analysis of the real-time operating state of the machine during the entire machining process. advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 262 3. system implementation 3.1. data acquisition and transmission the first thing that the remote monitoring system needs is the acquisition and transmission of data. the data collected mainly includes three categories: working condition data acquired from the cnc machine controller, external sensor data acquired from the data acquisition card, and multimedia data acquired from the camera and the microphone, as shown in fig. 2. fig. 2 data acquisition and transmission real-time data acquisition is achieved by transferring data from the network layer to the data layer for data services and data storage. data services are responsible for high-reliability, low-latency transmission of high-capacity, high-real-time data and data pretreatment. the temporary storage and persistent storage of data were mainly completed by data storage. since the transmission control protocol (tcp) has the characteristics of acknowledgment response and retransmission control, both the working condition data and the external sensor data are transmitted based on the tcp to ensure high reliability of data. both temporary storage and persistent storage are used. temporary storage is mainly used for caching and was realized by redis database. since the data in redis is stored in ram, the read/write speed is fast, and the low-latency transmission of the data can be ensured, which could ensure the real-time monitoring. in addition, in order to ensure that the users use the data on demand, the pipeline technology in redis [7] is used to decouple the coupling between the data and the user. different data can be obtained according to different monitoring contents. for persistent storage, the mongodb database is used. the content of the redis database is synchronized to the database by means of master-slave synchronization, which facilitated later playback. the transmission of multimedia data is performed by using web real-time communication (webrtc) technology, and network address translation (nat) penetration is used to ensure low latency of multimedia data transmission. 3.2. 3d model driven by real-time data traditional 3d models are rarely introduced in remote monitoring. even if it has been introduced, it is only used for virtual simulation, and seldom moved synchronously with physical devices. the design of introduce 3d models into the monitoring interface and then use the real-time data to drive 3d model motion had its unique advantages. on the one hand, it added visualization of tool position data and tool trajectory during monitoring, always feedback the current artifact appearance to the monitor, and could view the artifact in all directions by dragging and zooming. on the other hand, by monitoring the processing process, the abnormal position could be quickly located (through the internal working condition data) when signal anomaly. then, the abnormal position could be mapped in real time by 3d model, which could simplify the positioning processing and reduce the difficulty of fault monitoring. in the three-dimensional display of remote monitoring of cnc machine tools, web graphics library (webgl) was responsible for loading and controlling the 3d model, and the browser provided the operating environment [7-8]. in order to advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 263 facilitate the control of the 3d model, it has been divided into different components according to the motion mode, and then webgl is used to “virtual assembly” according to its relative position. the mapping relationship between the component and the driving data is established to realize the motion of the assembled cnc machine model through real-time data driving, as shown in fig. 3. fig. 3 mapping of real-time data and 3d model the cnc machine is ready to add the corresponding blank from the blank stock as required. after the tool is calibrated, the data corresponding to g54 in the cnc machine controller is acquired, which was the real workpiece zero point. by establishing a mapping with the zero point of the virtual machine tool workpiece, the mapping relationship between the virtual machine tool and the physical machine tool could be established, thereby realizing the initialization of the data driven model. the mapping equation is as follows: 54 300v r gx x x    (1) 54 1160v r gy y y   (2)  54 83.8v r g workpiecez z z h    (3) 0.3 2 / 360v rs s      (4) where xv, yv, zv, sv is corresponding to the x, y, z axis position and spindle speed in the virtual machine tool respectively; xr, yr, zr, sr is corresponding to the x, y, z axis position and spindle speed in the physical machine tool respectively; xg54, yg54, zg54 is corresponding to the workpiece zero position on the physical machine respectively; hworkpiece is the height of the workpiece in the virtual machine. after the virtual machine model is initialized and the mapping relationship is established, the real-time spindle speed s and the x, y, z axis position could be obtained and used to drive the model motion in real time, as shown in fig. 4. when the initialization of the data-driven model was completed, the machine zero point, tool parameters, and tool initial position could advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 264 be obtained. after the table position is partially magnified, the appearance of the workblank could be observed. the real-time data could drive the model to observe the current tool position. after processing, the final rendering of the part could be observed. fig. 4 processing renderings of real-time data driven parts 3.3. low latency video the general architecture of video surveillance in traditional remote monitoring systems are content delivery network (cdn), real time messaging protocol (rtmp) and http live streaming (hls), with a delay of more than 3 seconds, which cannot meet the current requirements for monitoring in real-time. this system drew on the idea of interactive live broadcast, using webrtc technology to control the average delay to about 200ms to realize the real time of video monitoring, as shown in fig. 5. the data transmission is mainly divided into two parts. one was the transmission of signaling, which is realized by exchange the session information, network configuration, media configuration, etc. between the two ends of the peer to peer (p2p) through the cloud platform, and finally the nat penetration is achieved. then a peer-to-peer connection between the device collection end and the kurento server, between the kurento server and the viewer is established [9-11]. another part is the transmission of the video stream. this part directly transmited data through the p2p channel. when the video data is collected by the device, the video is uploaded to the kurento streaming server via the p2p channel, and then the viewer and the kurento terminal are respectively transmitted via the p2p channel. due to the video passes through the p2p channel in both transmissions, there is a small delay and realized low delay of video monitoring. fig. 5 architecture diagram of video monitoring 3.4. remote monitoring prototype system based on html5 based on the above theoretical basis, a remote monitoring prototype system based on html5 is developed, as shown in fig. 6. the monitoring system is mainly used for real-time monitoring and fault diagnosis of cnc machine tools. advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 265 the monitoring system visualizes the data in multiple directions, including data display, 2d controls, 3d models, and audio and video. data presentations are intuitive enough to know their specific values, but they did not apply to data that is large in volume or needs to understand trends. the two-dimensional control is realized by html5 canvas technology, which is used to dynamically generate raster-based images [12]. it could be used for a wide range of purposes, such as the dial could directly display the value (more suitable for occasions with slower data changes) and reflectes the trend of change, the chart could display the corresponding waveform directly and switched the different display forms of the data by performing corresponding data processing. the 3d model could be intuitively perceived by the monitor. by driving the 3d model with real data, it is possible to quickly locate the specific machining position and observe the motion, such as linear or circular motion, face milling or shoulder milling. in addition, omnidirectional, multi-angle observations could be performed by rotating the 3d model. through audio and video, you could understand the specific processing environment and reduce the difficulty of monitoring through both visual and auditory aspects. in this design, different visualization methods were adopted for different types of data, which reduced the difficulty of monitoring. fig. 6 interface of remote monitoring prototype system based on html5 4. case study the cutting stability during metal cutting directly affects the machining accuracy and machining efficiency of the machine tool, so real-time monitoring of cutting stability is a key means to evaluate the quality of part machining [13]. the greatest influence on cutting stability was the cutting chatter. cutting chatter refers to a kind of violent self-excited vibration caused by the characteristics of the processing system under the action of no external force during the cutting process[14]. this experiment uses the prototype system to monitor the stability during the process of milling the three-layer pagoda, and analyzes the cause, time and position of the stability problem in time to provide assistance for the rapid diagnosis and analysis. a three-axis vertical milling machine equipped with huazhong cnc system was used in this experiment. the cutting and tool parameters are shown in table 1. during the experiment, the vibration and sound signal waveforms changed significantly at a certain moment, and the phenomenon is shown in fig. 7. by comparing the vibration sound waveforms of fig. 7 (a) and (b), the following characteristics were obtained: from the time domain perspective, the amplitude in the fig. 7 (b) is larger; from the frequency domain perspective, the frequency advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 266 domain in the fig. 7 (a) is more discrete. there was no obvious maximum value, and there is a significant peak in the intermediate frequency domain of fig. 7 (b). by listening to the audio data transmitted from the microphone, the sound at time in fig. 7 (b) is sharper, and it is possible to guess that chatter may occur at that moment. at this time, combined with the internal working condition data of g code, axis position data and the visualization of the video and 3d model, it could be found that the running track and the cutting parameters of the workpiece had not changed at this time, and the vibration and sound waveform were proved. the difference is not caused by the change of the running track and the cutting parameters of the workpiece. it could be confirmed that the waveform change at this time is caused by the chatter. table 1 cutter, cutting and workpiece parameters of a three-axis vertical milling machine cutter parameters diameter (mm) 10 helix angle 45° edge number 3 material cemented carbide cutting parameters feed rate (mm) 1/6 axial depth (mm) 7 radial depth (mm) 0.3~0.9 workpiece parameters size (mm) 50*50*50 material aluminum 7075 (a) before chatter (b) chatter fig. 7 cuttig stability experiment vibration frequency domain vibration time domain sound time domain sound frequency domain vibration time domain vibration frequency domain sound time domain sound frequency domain advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 267 in addition, when the chatter is successfully monitored, if only the vibration and sound waveforms of the external sensor are passed, it was not possible to quickly locate the position where the chatter occurs and the cause of the chattering. at this time, through the video and data-driven 3d model, the tool trajectory can be visualized in real time, and the chatter position could be quickly located, which played a positive role for subsequent observation and analysis. when the processing is completed, the vibration pattern could be clearly observed by observing the above-mentioned located position under the microscope, as shown in fig. 8. by real-time acquisition and visualization of the internal data of the cnc controller in cnc machine tool, it is possible to obtain internal operating conditions such as spindle rotation speed, feed rate, and override when chattering occurs. this helped to understand the cause of the chatter and provided guidance for suppressing chatter. it is easy to judge the machining abnormality by the external sensor signal in this experiment. at this time, the internal condition data could be combined to determine the type of abnormality as chatter. the accuracy of the monitoring is improved. there are a variety of visualization methods in this monitoring system, which could help to quickly locate abnormal positions. in addition, it helped to grasp the information of cnc machine tool conditions at all times, which reduced the difficulty of subsequent fault analysis and diagnosis. video model partial enlargementmachined part normal surface flutter surface fig. 8 processed workpiece and detailed vibration lines 5. conclusions a method based on html5 for remote monitoring of cnc machine tools is proposed in this paper. this method improved the accuracy of monitoring by combining the internal working condition data of cnc machine tools with external sensor data. a variety of visualization methods, such as data display, 2d controls, 3d models, and audio and video were used to reduce the difficulty of monitoring and analysis. based on this, a prototype system is developed and the corresponding experiments are carried out. the results indicated that the system can significantly improve the accuracy of monitoring and reduce the difficulty of monitoring and analysis. this monitoring system could improve workpiece quality and fault diagnosis accuracy significantly. conflicts of interest the authors declare no conflict of interest. references [1] y. cai, b. starly, p. cohen, and y. s. lee, “sensor data and information fusion to construct digital-twins virtual machine tools for cyber-physical manufacturing,” procedia manufacturing, vol. 10, pp. 1031-1042, 2017. [2] x. h. li and w. y. li, “the research on intelligent monitoring technology of nc machining process,” procedia cirp, vol. 56, pp. 556-560, 2016. advances in technology innovation, vol. 4, no. 4, 2019, pp. 260-268 268 [3] e. y. heo, h. lee, c. s. lee, d. w. kim, and d. y. lee, “process monitoring technology based on virtual machining,” procedia manufacturing, vol. 11, pp. 982-988, 2017. [4] z. lei, w. hu, and h. zhou, “deploying web-based control laboratory using html5,” 2016 13th international conference on remote engineering and virtual instrumentation (rev), madrid, pp. 69-73, 2016. [5] y. sheng, j. huang, f. zhang, y. an, and p. zhong, “a virtual laboratory based on html5,” 2016 11th international conference on computer science & education (iccse), nagoya, pp. 299-302, 2016. 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[10] sredojev, d. samardzija, and d. posarac, “webrtc technology overview and signaling solution design and implementation,” in 2015 38th international convention on information and communication technology, electronics and microelectronics (mipro), 25-29 may 2015, piscataway, nj, usa, 2015. [11] k. i. z. apu, n. mahmud, f. hasan, and s. h. sagar, “p2p video conferencing system based on webrtc,” 2017 international conference on electrical, computer and communication engineering (ecce), cox's bazar, pp. 557-561, 2017. [12] s. dumke, h. riemann, t. bluhm, r. daher, m. grahl, m. grün, a. holtz, j. krom, g. kühner, h. laqua, m. lewerentz, a. spring, and a. werner, “next generation web based live data monitoring for w7-x,” fusion engineering and design, vol. 129, pp. 16-23, 2018. [13] z. yongliang and l. zhiyuan, “stability and online monitoring of cutting chatter: a review,” applied mechanics and materials, vol. 121-126, pp. 377-81, 2011. [14] k. j. li, y. x. liu, and z. zhao, “research in multiple factors vibration controlling of cnc milling machine,” 2011 fourth international conference on intelligent computation technology and automation, shenzhen, guangdong, pp. 472-475, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 velocity field around a rigid flapping wing with a winglet in quiescent water srikanth goli 1,* , arnab roy 1 , subhransu roy 2 1 department of aerospace engineering; 2 department of mechanical engineering, indian institute of technology, kharagpur, west bengal, india received 23 august 2019; received in revised form 07 december 2019; accepted 12 march 2020 doi: https://doi.org/10.46604/aiti.2020.4674 abstract this study investigated the effect of a winglet on the velocity field around a rigid flapping wing. two-dimensional particle image velocimetry was used to capture the velocity field of asymmetric one-degree-of-freedom flapping motion. a comparison was conducted between wings with and without a winglet at two flapping frequencies, namely 1.5 and 2.0 hz. the effect of the winglet on the velocity field was determined by systematically comparing the velocity fields for several wing phase angles during the downstroke and upstroke. the presence of a winglet considerably affected the flow field around the wingtip, residual flow, and added mass interaction. the added mass was lower and residual flow was weaker for the wings with a winglet than for the wings without a winglet. the added mass and velocity magnitudes of the flow field increased proportionally with the flapping frequency. keywords: square wing, flapping motion, winglet, one-degree-of-freedom flapping, piv, velocity field 1. introduction winglets are employed in modern aircraft for improving aerodynamic performance. winglets were first proposed by whitcomb in the 1970s for improving the aerodynamic efficiency by reducing the drag induced [1-2]. many studies have reported the advantages of different winglet sizes and shapes, especially multiwinglets [3-7]. the winglet concept is based on birds’ feathers. birds such as eagles, hawks, condors, vultures, and ospreys have feathers on their wings [8], which orient them horizontally and vertically in flight to form slotted tips for reducing the induced drag [9]. winglets attached to wingtips are widely used in commercial and transport aircraft. in addition to numerous fixedand rotary-wing aircraft, micro air vehicles (mavs) have been extensively developed in the last two decades. the flapping-wing mav (fwmav) design is gaining popularity due to its many advantages. natural flyers have various desirable features, such as high maneuverability and perching and hovering capabilities. these features are difficult to achieve in fixedand rotary-wing aircraft. however, they can be easily achieved in fwmavs. thus, fwmavs are effective for surveillance and reconnaissance missions. fwmav development has accelerated considerably during the last two decades, and many new technologies have been incorporated into fwmav design. similar vehicles used in water-based applications are called micro underwater vehicles. the unsteady flow field around the flapping wings and its effect on the configuration fluid dynamics are not well understood. detailed understanding of the flow field is essential for improving the efficiency of small-scale flapping-wing vehicles and thus maximizing their endurance. * corresponding author. e-mail address: srikanthgoli.ind@gmail.com advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 260 qualitative information on the flow field around the flapping wing of insects and mechanical flyers has been reported in [10-13] from studies conducting smoke flow visualization and particle image velocimetry (piv) studies. although natural flyers often exhibit flapping motion with multiple degrees of freedom, most studies have focused on one-degree-of-freedom flapping motion. in [14-16], the one-degree-of-freedom flapping motion, force and moments associated with different flapping frequencies, and wing aspect ratios were investigated. studies should be conducted on simple configurations to obtain a fundamental understanding of complex flow. to the best of the authors’ knowledge, the flow field around a flapping wing with a winglet has not yet been investigated. the present study compared the velocity fields generated by rigid flapping wings with and without a winglet. the motivation of using winglets in a flapping motion was to recreate the motion of natural flyers (with feathers). the advantages associated with winglets have been proven for fixed-wing configurations. the experiments conducted in this study involved one-degree-of-freedom flapping motion that was achieved using a four-bar mechanism. the flapping mechanism was identical to that used in goli et al. [13]. the velocity field was obtained using two-dimensional piv measurements. a square planform wing (ar = 1.0) with and without a winglet was studied at two flapping frequencies (f = 1.5 and 2.0 hz). piv measurements were made to capture the velocity field in the mid-chord plane of the flapping wing. 2. experimental system (a) flapping motion (b) wing with a winglet (unit: mm) fig. 1 schematic of the flapping motion of a rigid wing (a) parts of the experimental system (b) dimensions of the experimental tank and flapping mechanism fig. 2 schematic of the experimental setup advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 261 details regarding the flapping mechanism, water tank, fabrication materials, piv measurements, and experimental procedure are presented in the papers of goli et al. [17-19]. an overview of the experimental system is presented in the following. in this study, a one-degree-of-freedom flapping motion [fig. 1(a)] was achieved using a four-bar mechanism (see [13] for dimensions). the wings had a thickness of 1.5 mm and were made of perspex acrylic. a schematic of a wing with a winglet is displayed in fig. 1(b). experiments were conducted in a water tank in which the flapping mechanism was fully immersed, as displayed in fig. 2. piv measurements were performed by illuminating the mid-chord of the wing to capture details of the flow field along the wing span direction. the wing dimensions and operating conditions are presented in table 1. table 1 wing dimensions and operating conditions case span (mm) chord (mm) thickness (mm) ar f (hz) winglet attached ϕa (degree) ϕb (degree) i-w 40 40 1.5 1.0 1.5 yes 59.5 −14.5 i 40 40 1.5 1.0 1.5 no 59.5 −14.5 ii-w 40 40 1.5 1.0 2.0 yes 59.5 −14.5 ii 40 40 1.5 1.0 2.0 no 59.5 −14.5 3. results and discussion 3.1. comparison of the velocity fields for wings with and without a winglet at f = 1.5 hz (cases i-w and i) figs. 3 and 4 display the velocity fields during the downstroke and upstroke of the flapping cycle, respectively, for the two cases at f = 1.5 hz. the parameter ϕ represents the flapping angle [fig. 1(a) and table 1], whereas ϕ* represents the normalized flapping angle. the parameter ϕ* varies from 0 to 1 from the beginning to the end of each stroke. the values of the flapping angle ϕ and normalized flapping angle ϕ* are illustrated in figs. 3 and 4. the downward and upward arrows in the top right corner of the aforementioned figures indicate downstroke and upstroke, respectively. in a quiescent fluid, wing flaps do not exhibit cross-flow perpendicular to the piv image plane. thus, the vortices and shear produced by the wing are not convected downstream but reside in the region in which the wing flaps. such reminiscent features form residual flow in the wake of the wing. for example, a wing that executes a downstroke encounters the residual or wake flow formed during the previous upstroke. during an upstroke, the wing encounters the residual or wake flow from the previous downstroke. when a wing flaps through residual or wake flow, the following events occur simultaneously: (i) the wing recovers energy from energetic structures in the wake flow. this event is termed the wake capture mechanism. (ii) the wing modifies existing flow structures through strain, rotation, and displacement effects. this process is repeated during wing flapping. an accelerating or decelerating wing must move some volume of the surrounding fluid with it as it moves. the mass of this dragged fluid is called the added mass, which can be substantial when the wing moves through a heavy fluid. consequently, a large force must be exerted on the wing to move this additional mass along with the wing mass. the added mass always opposes the accelerating or decelerating motion of the wing. for both cases illustrated in fig. 3, a fluid jet was observed at the lower side of the wing that moved in a nearly upward direction at the beginning of the downstroke (ϕ = 58.50°). when a winglet was used, the residual flow was localized and concentrated below the wing. when no winglet was used, the residual flow was more spread out and angled outward. the residual flow occupied approximately the unit span length for the winglet case and twice the unit span length for the no winglet case. a wingtip vortex formed when no winglet was used but not when a winglet was used. from ϕ = 58.50° to ϕ = 53.50°, the wing traveled through the wake, and the fluid jet continued to move in a nearly vertical direction in both cases. the passage of the wing through the residual flow led to wake capture. no clear wingtip vortex was formed in the winglet case, whereas a clear wingtip vortex was formed in the no winglet case. the wing dragged the fluid on its advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 262 upper surface due to suction. the width of the residual flow was lower in both cases. specifically, the width of the residual flow was less than the unit span length for the winglet case and less than twice the unit span length for the no winglet case. when ϕ was changed from 53.50° to 47.50°, the wingtip vortex became visible for the winglet case. in the winglet case, the wingtip vortex emerged from the tip of the winglet. in both cases, the residual flow weakened, moved along the vertical direction, and escaped around the wingtip. moreover, the strength of the added mass gradually increased around the upper surface of the wing due to the suction induced by the wing movement. when ϕ was 39.50°, the residual flow of the winglet case nearly crossed the lower surface and moved past the wingtip along the vertical direction. in the no winglet case, the residual flow crossed the wingtip, moved vertically with a component directed toward the right, and remained widely spread. (a) case i-w when ϕ = 58.50° (b) case i when ϕ = 58.50° (c) case i-w when ϕ = 55.50° (d) case i when ϕ = 55.50° (e) case i-w when ϕ = 53.50° (f) case i when ϕ = 53.50° (g) case i-w when ϕ = 47.50° (h) case i when ϕ = 47.50° (i) case i-w when ϕ = 44.50° (j) case i when ϕ = 44.50° (k) case i-w when ϕ = 41.50° (l) case i when ϕ = 41.50° (m) case i-w when ϕ = 39.50° (n) case i when ϕ = 39.50° (o) case i-w when ϕ = 36.50° (p) case i when ϕ = 36.50° fig. 3 velocity field for cases i-w and i (with and without a winglet, respectively) when f = 1.5 hz during the downstroke advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 263 (q) case i-w when ϕ = 22.50° (r) case i when ϕ = 22.50° (s) case i-w when ϕ = 07.50° (t) case i when ϕ = 07.50° (u) case i-w when ϕ = −11.50° (v) case i when ϕ = −11.50° (w) case i-w when ϕ = −14.50° (x) case i when ϕ = −14.50° fig. 3 velocity field for cases i-w and i (with and without a winglet, respectively) when f = 1.5 hz during the downstroke (continued) the extent of interaction between the residual flow and added mass was influenced strongly by the wingtip geometry. from the beginning of the downstroke, the residual flow was dispersed widely in the no winglet case. the wingtip vortex was detached and located at a distance of approximately one wingspan from the wingtip when ϕ = 44.50°. the added mass and residual flow without any hindrance through the gap located between the detached wingtip vortex and the wingtip. the movement of the added mass toward the wingtip diverted the residual flow; thus, the added mass moved vertically with a component directed toward the right. in the winglet case, the added mass stagnated at the inner corner of the winglet. consequently, a portion of the added mass could not mix with the residual flow. the added mass above the winglet tip crossed over and joined the residual flow, and the resultant mass moved vertically upward after turning around the outer corner of the wingtip. the impeded interaction between the added mass and residual flow led to a nearly vertical upward-moving residual flow, which was dispersed to a small extent. thus, in both the cases, the interaction between the added mass formed above the upper surface of the wing and the residual flow below the lower surface of the wing reoriented the wing tip flow. the presence or absence of a winglet considerably affected the flow field around the wingtip, residual flow, and added mass interaction. in the winglet case, when ϕ was 58.50°–36.50°, a weak wingtip vortex was formed. this vortex almost maintained its original spatial location with respect to the tip of the winglet. the wingtip flow moved further upward along the outer surface of the winglet. it could not curl around the wingtip because of the presence of the winglet. the wingtip flow energized the shear layer originating from the tip of the winglet and the weak wingtip vortex. these flow features were distinct from those in the no winglet case. in the winglet case, when ϕ = 22.50°, the wingtip vortex was almost completely absent; however, the strength of the shear layer was maintained. the shear layer acted as a barrier between the added mass flow on its inner side above the upper surface of the wing and the wingtip on its outer side. the added mass and wingtip flow moved almost tangentially to the shear layer but had enhanced shear in opposite directions. the presence of the shear layer resulted in less entrainment and mass transfer between the wingtip flow and added mass region. consequently, the added mass grew to a limited extent in the winglet case. thus, a strong residual flow led to a strong wingtip flow that considerably influenced the added mass. advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 264 when ϕ was 22.50°, the residual flow was weak in the winglet and no winglet cases. thus, wake capture can be considered to end at ϕ = 22.50°. in the winglet case, the interaction between the residual flow and added mass became weaker at angles beyond this angle. when ϕ was 7.50°, no interaction was observed between the residual flow and freshly generated added mass in either case. the added mass in the winglet case was less than that in the no winglet case. from ϕ = 7.50° to the end of the stroke at ϕ = −14.50°, the velocity magnitude in the added mass region increased in both the cases. pockets were found in the added mass region in which flow curled in the opposite direction due to kh instability. a weaker wingtip vortex was formed in the winglet case than in the no winglet case. a strong wingtip vortex consumes considerable energy. if this energy cannot be recovered, the energy lost that must be compensated for through high-energy input from the flapping mechanism. the wingtip vortex is expected to produce a large force on the wing, which improves the wing’s lifting capability. however, the aforementioned force can also increase the power consumption. these factors could be the reasons why natural flyers have winglets in the form of feathers in the outboard section of their wings. (a) case i-w when ϕ = −13.50° (b) case i when ϕ = −13.50° (c) case i-w when ϕ = −10.50° (d) case i when ϕ = −10.50° (e) case i-w when ϕ = −04.50° (f) case i when ϕ = −04.50° (g) case i-w when ϕ = −00.50° (h) case i when ϕ = −00.50° (i) case i-w when ϕ = 03.50° (j) case i when ϕ = 03.50° (k) case i-w when ϕ = 13.50° (l) case i when ϕ = 13.50° (m) case i-w when ϕ = 17.50° (n) case i when ϕ = 17.50° (o) case i-w when ϕ = 21.50° (p) case i when ϕ = 21.50° fig. 4 velocity fields for cases i-w and i (with and without a winglet, respectively) when f = 1.5 hz during the upstroke advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 265 (q) case i-w when ϕ = 27.50° (r) case i when ϕ = 27.50° (s) case i-w when ϕ = 46.50° (t) case i when ϕ = 46.50° (u) case i-w when ϕ = 57.50° (v) case i when ϕ = 57.50° (w) case i-w when ϕ = 59.50° (x) case i when ϕ = 59.50° fig. 4 velocity fields for cases i-w and i (with and without a winglet, respectively) when f = 1.5 hz during the upstroke (continued) fig. 4 indicates that at the beginning of the upstroke at ϕ = −13.50°, a wingtip vortex formed in both cases because the residual flow on the upper surface of the wing curled around the wingtip as the wing traveled back (stroke reversal). in the winglet case, the flow crossed over the winglets and formed a wingtip vortex. in the no winglet case, the flow moved smoothly without being impeded. the velocity magnitude in the winglet case was less than that in the no winglet case. the orientation of the residual flow appeared to be nearly horizontal in both cases. the orientation of the residual flow at the beginning of upstroke was different from that of the residual flow at the beginning of the downstroke due to kinematic asymmetry. the residual flow in the winglet case was less than that in the no winglet case, because less added mass was formed in the previous downstroke than in the previous upstroke. the suction effect was initiated on the lower surface of the wing in both cases. this effect resulted in the neighboring fluid being dragged close to the lower surface of the wing. a similar phenomenon occurred during the downstroke. when ϕ was −10.50°, the wingtip vortex was already enlarged in both cases. considerably less residual flow occurred in the winglet case than in the no winglet case. in the winglet case, the residual flow on the upper surface of the wing covered approximately 70% of the wingspan toward the wingtip. in the no winglet case, the coverage of the residual flow was approximately 90%. this result differs from that obtained for the downstroke. in this phase, the wing traveled through its wake and experienced wake capture. the residual flow velocities were low in the winglet case. the added mass increased due to suction on the lower surface of the wing in both cases. from ϕ = −10.50° to ϕ = −4.50°, the wingtip vortex continued to grow in both cases. the residual flow decreased in both cases and was located near the wingtip. however, the interaction between the residual flow and wingtip vortex was different in the two cases. in the winglet case, the residual flow was smooth and nearly horizontal because the wingtip vortex was distinct, large, and attached to the wingtip. in the no winglet case, the residual flow curled and acquired a counter-rotating nature because the wingtip vortex was small, was marginally detached, and provided a path for fluid to pass through and interact with the residual flow in the wing region. the residual flow continued to be strong in the no winglet case. in both cases, the wing continued to travel through its wake. advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 266 when ϕ was −0.50°, the wingtip vortex in the winglet case had appearance similar to an inverted six, was large, and was located close to the wingtip. in the no winglet case, the wingtip vortex moved away from the wingtip. the formed wingtip vortex cores were nearly stationary in the winglet case. by contrast, in the no winglet case, the wingtip vortex was shifted along the x-axis away from the wingtip. the wing traveled through its wake in both cases. the residual flow in the winglet case was considerably weaker than that in the no winglet case. the amount of added mass formed due to suction increased in both cases. the added mass in the winglet case was less than that in the no winglet case. during the upstroke, an anchored wingtip vortex played an active role in creating a barrier that restricted the movement of the added mass. a similar phenomenon was observed during the downstroke. the residual flow curled around the wingtip, moved downward along the outer surface of the winglet, and energized the shear layer originating from the wingtip. when ϕ was 03.50°, the wingtip vortex was distorted in both cases due to the shear interaction of the residual flow. the location of the core of the wingtip vortex with respect to the wingtip was almost unchanged in the winglet case, and the wingtip vortex continued to grow close to the wingtip. in the no winglet case, the wingtip vortex moved along the x-direction away from the wingtip. the wing continued to travel in its wake. the residual flow in the winglet case was weaker than that in the no winglet case. when ϕ was 13.50°, the wingtip vortex in the winglet case appeared to be stretched similarly to a rubber band and acted as a barrier between the residual flow and added mass, which moved in opposite directions. during the upstroke, the opposite-movement adjacent regions of the flow field energized the shear layer. a similar phenomenon was observed during the downstroke. the barrier effect restricted the movement of the added mass. in the no winglet case, the wingtip vortex was distorted and moved far away from the wingtip. thus, the added mass in the no winglet case increased, because the suction effect of the moving wing resulted in additional fluid being dragged toward the lower surface of the wing due to entrainment. residual flow still existed in both cases, and its strength was lower in the winglet case than in the no winglet case. in both cases, the effect of the wake was weakened. when ϕ was 21.50°, the added mass increased further in both cases. the added mass was considerably lower in the winglet case than in the no winglet case due to the barrier effect. weak residual flow existed far away from the wing. in both cases, the wing did not pass through its wake. this condition was considered the end of wake capture. when ϕ was 27.50°, the added mass in the winglet case was concentrated below the wing due to the barrier effect of the shear layer. in the no winglet case, the added mass bifurcated and moved toward the residual flow located away from the wing surface. when ϕ was 46.50°, the width of the added mass increased in the winglet case. moreover, the shear layer barrier vanished. therefore, the added mass had the freedom to move out from the wingtip circumference or wing-sweeping region. in the no winglet case, the width of the added mass increased and it moved out of the wing-sweeping region. no residual flow existed in the winglet case. in the no winglet case, weak residual flow existed far away from the wing and had no influence on the wing and added mass. from ϕ = 46.50° to the end of the stroke at ϕ = 59.50°, the added mass increased and moved vertically in both cases. the added mass was concentrated below the wing in the winglet case but widely spread in the no winglet case. 3.2. effect of flapping frequency the flow field characteristics for cases i-w and i were compared with those for cases ii-w and ii to determine the effect of flapping frequency on the flow field characteristics. advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 267 the velocity fields of wings with and without a winglet were compared at two flapping frequencies. the results indicated that the flow features were predominantly similar in the different cases, as discussed in section 3.1. the added mass and velocity magnitude increased with the flapping frequency. figs. 5 and 6 depict the velocity fields at the beginning of the downstroke and upstroke, respectively, when f = 1.5 and 2.0 hz. the detailed flow field features at discrete flapping angles corresponding to cases ii-w and ii are not presented here for brevity. (a) case i-w (b) case i (c) case ii-w (d) case ii fig. 5 comparison of the velocity fields in different cases at the beginning of the downstroke (ϕ = 58.50°) (a) case i-w (b) case i (c) case ii-w (d) case ii fig. 6 comparison of the velocity field in different cases at the beginning of the upstroke (ϕ = −13.50°) 4. conclusions goli et al. described the generic flow field behavior around a rigid flapping wing without a winglet [17-19]. the present study compared the velocity fields of wings with and without a winglet. the effect of the winglet on the velocity field was determined by systematically comparing the velocity fields for several wing phase angles during the downstroke and upstroke. the effects of the winglet on the velocity field can be summarized as follows: (1) in the winglet case, the wingtip vortex did not form clearly at the beginning of the downstroke. a weak wingtip vortex formed later in the stroke and appeared to remain anchored to the tip of the winglet. a strong shear layer formed at the tip of the winglet. in the no winglet case, the wingtip vortex formed at the beginning of the downstroke and remained distinct and strong. it detached from the wingtip and created a wide passage for interaction between the added mass and residual flow. during the upstroke, the wingtip vortex was well defined in both cases. in the winglet case, the wingtip vortex remained close to the wing, whereas in the no winglet case, the wingtip vortex detached early and moved far away from the wing. (2) the added mass was less in the winglet case than in the no winglet case. this result was obtained because the shear layer originating from the tip of the winglet during the downstroke and the wingtip corner during the upstroke reduced entrainment. the reduction in the entrainment impeded the growth of the added mass. (3) at the beginning of the downstroke, the residual flow in the winglet case was spread close to the wingtip over a distance of approximately one unit span length at the level of the wingtip. in the no winglet case, the residual flow was spread over advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 268 twice the wingspan with an angular orientation of approximately 20° downward relative to the wingtip level. the residual flow was nearly horizontal at the beginning of the upstroke in both cases. the residual flow in the winglet case was weaker than that in the no winglet case due to the lower added mass formed in the previous downstroke in the winglet case. (4) the added mass and velocity magnitude of the flow field increased with an increase in the flapping frequency. overall, the flow features at the two considered frequencies were predominantly similar. the velocity field has a major effect on wing performance. this behavior must be studied in detail when designing air vehicles. the evolution of vortex structures during wing stroke, kinetic energy variation, added mass, force or torque, strain, rotation and displacement effects, and wing performance will be investigated in a future study to comprehensively determine the effects of a winglet on wing performance. acknowledgment this research was funded through projects sponsored by the following agencies: (i) the aeronautics r&d board, government of india (sanction letter no. ardb/01/1031864/m/i), and (ii) the department of science and technology, government of india [sanction letter no. sr/fst/eti-386/2014 (g)]. conflicts of interest the authors declare no conflicts of interest. references [1] r. t. whitcomb, “a design approach and selected wing-tunnel results at high subsonic speeds for wing-tip mounted winglets,” washington, united states, technical report nasa tn d-8260, july 01, 1976. [2] s. g. fletcher and p. f. jacobs, r. t. whitcomb, “a high subsonic speed wind-tunnel investigation on a representative second-generation jet transport wing,” washington, united states, technical report nasa tn d-8264. july 01, 1976. [3] i. kroo, drag due to lift: concepts for prediction and reduction, annual review of fluid mechanics, 2001. [4] h. d.cerón-muñoz and f. m. catalano, “experimental analysis of the aerodynamic characteristics adaptive of multi-winglets,” the proceedings of the institution of mechanical engineers, part g: journal of aerospace engineering, vol. 220, no. 3, pp. 209-215, march 2006. [5] d. p. coiro, f. nicolosi, f. scherillo, and u. maisto, “design of multiple winglets to improve turning and soaring characteristics of angelo d’ arrigo’s hang-glider: numerical and experimental investigation” in: xix conggresso nazionale aidaa 17-21 september 2007 aerotecnica missili e spazio., vol. 87, no. 2, pp. 74-85, may 2008. [6] m. berens, “potential of multi-winglet systems to improve aircraft performance,” doctoral thesis, technical univ of berlin, germany, 2008. [7] g. srikanth and b. surendra, “experimental investigation on the effect of multi-winglets,” international journal of mechanical and industrial engineering, vol. 1, no. 1 pp. 43-46, january 2011. [8] m. j. smith, n. komerath, r. ames, o. wong, and j. pearson, “performance analysis of a wing with multiple winglets,” in: 19th aiaa applied aerodynamics conference, anaheim, ca, usa, june 2001, pp. 1-10. [9] v. a. tucker, “gliding birds: reduction on induced drag by wing tip slots between the primary feathers,” the journal of experimental biology, vol. 180, no. 1, pp. 285-310, july 1993. [10] k . kitagawa, m. sakakinara, and m. yasuhara. “visualization of flapping wing of the drone beetle,” journal of visualization, vol. 12, no. 4, pp. 393-400, december 2009. [11] y. liu, b. cheng, and x. deng. “an application of smoke-wire visualization on a hovering insect wing,” journal of visualization, vol. 16, no. 3, pp. 185-187, auguest 2013. [12] h. ren, y. wu, and p.g. huang. “visualization and characterization of near-wake flow fields of a flapping-wing micro air vehicle using piv,” journal of visualization, vol. 16, no. 1, pp. 75-83, february 2013. [13] s. goli, a. roy, d. k. patel, and s. roy, particle image velocimetry measurements of rigid and flexible rectangular wings undergoing main flapping motion in hovering flight, fluid mechanics and fluid power-contemporary research, 2017. [14] y. s. hong and a. altman, “lift from spanwise flow in simple flapping wings,” journal of aircraft, vol. 45, no. 4, pp. 1206-1216, july 2008. advances in technology innovation, vol. 5, no. 4, 2020, pp. 259-269 269 [15] h. hu, a. g. kumar, g. abate, and r. albertani, “an experimental investigation on the aerodynamic performances of flexible membrane wings in flapping flight,” aerospace science and technology, vol. 14, no. 8, pp. 575-586, december 2010. [16] k. mazaheri and a. ebrahimi, “experimental study on interaction of aerodynamics with flexible wings of flapping vehicles in hovering and cruise flight,” archieve of applied mechanics, vol. 80, no. 11, pp. 1255-1269, november 2010. [17] s. goli, a. roy, and s. roy, “vortex filamentation and fragmentation phenomena in flapping motion and effect of aspect ratio and frequency on global strain, rotation and enstrophy,” international journal of micro air vehicles, vol. 11, pp. 1-30, january 2019. [18] s. goli, s. s. dammati, a. roy, and s. roy, “coherent structures in the flow generated by rigid flapping wing in hovering flight mode,” iop conference series: materials science and engineering, vol. 402, no. 1, pp. 1-18, 2018. [19] s. goli, s. s. dammati, a. roy, and s. roy, “vortex identification and proper orthogonal decomposition of rigid flapping wing,” international journal of fluid mechanics research (accepted). 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 adaptation of the higher education in engineering to the advanced manufacturing technologies olivier bonnaud 1,2,* , ahmad bsiesy 3,4 1 department of sensors and microelectronics, ietr, university of rennes 1, 35042 rennes, france 2 national coordination for education in microelectronics, gip-cnfm, 38016 grenoble, france 3 university grenoble alpes, cnrs, ltm, f-38000 grenoble, france 4 cime nanotech, university grenoble-alpes, 38016 grenoble, france received 25 april 2019; received in revised form 07 july 2019; accepted 02 november 2019 doi: https://doi.org/10.46604/aiti.2020.4144 abstract the 21st century will be the era of the fourth industrial revolution with the progressive introduction of the digital society, with smart/connected objects, smart factories that are driven by robotics, the internet of things (iot) and artificial intelligence. manufacturing is expected to be performed by smart factories, i.e. the industry 4.0, which is the outcome of steady development of information technology associated with new objects and systems that can automatically supervise and fulfil manufacturing tasks. the industry 4.0 concept relies largely on the ability to design and manufacture smart and connected devices that are based on microelectronics technology. this evolution requires highly-skilled technicians, engineers and phds, all of them well prepared for research, development and manufacturing. their training, which combines knowledge and the associated compulsory know-how, is becoming the main challenge for the academic world. the curricula must therefore include the basic knowledge and associated know-how training in all the specialties of the field. the software and hardware tools used in microelectronics education are becoming highly complex and expensive that the most viable solution for practical training is to share technical facilities and human resources. this strategy has been adopted by the french microelectronics education network, which includes twelve universities and two industrial unions. by sharing human resources and technical facilities, the cnfm network was able to minimize the costs and to train future graduates on up-to-date tools similar to those used in companies. this paper aims to show how the strategy adopted by the french network can help meeting the needs of the future industry 4.0. several examples of innovative activities developed in this strategy will be given. keywords: industry 4.0, microelectronics, engineering education, network structuring, multidisciplinarity 1. introduction the evolution towards digital societies implies a revolution in the industry that relies largely on the tremendous growth of microelectronics, which is at the heart of the internet of things (iot) [1-2]. indeed, the rapid development of microelectronics [3] has made it possible to achieve fast computing, high-speed data processing and communications, and also more sensitive detection and more effective actuation [4]. today, all these functions are integrated in the connected objects that apply to all major societal activities [5], from communications to health, safety, transport, energy [6-7], as well as production in the new industrial scheme [8]. in fact, modern industry takes advantage of intelligent robots [9-10] that are well adapted to the * corresponding author. e-mail address: olivier.bonnaud@univ-rennes1.fr advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 66 production environment and have a core based on connected objects. as a result, industry is increasingly dependent on iot, which is necessary to govern the design of new products, their production, as well as to control the flow of raw materials and manufactured objects. all these production and management functions are part of what is known as smart factory industry 4.0 [8]. in this field, engineers, technicians and phd grade holders must be integrated into this design and manufacturing chain. the skills of these actors must combine the knowledge and practical know-how or skills that are essential when manufacturing a real object integrated into its environment and with a well-defined mission profile [11]. electronic hardware platforms (microprocessors, microcontrollers, sensors, actuators, etc.) are at the heart of the smart factory and they are provided by microelectronics industry [12]. higher education programs in engineering must therefore contain the basic knowledge and associated know-how in the following specialties: analog and digital electronics, signal processing, sensors and actuators, on-board electronics, energy harvesting systems, communications, transmission protocols and human-machine communication systems (vision, sound, touch, etc.) [6]. these specialties must meet the future needs of a connected society: low power, high speed, reproducibility, quality, safety, reliability, and low cost. a transformation of higher education is a major challenge to meet the needs of companies and research centers with a permanent behavior oriented towards innovation. this paper addresses these different aspects. 2. microelectronics and iot as mentioned above, microelectronics and its evolution towards nanotechnologies are the driving force behind the evolution towards the digital society and future industry 4.0. over the past sixty years, the integration of elementary devices into integrated circuits, mainly transistors, has grown exponentially, primarily due to the decrease in the lateral dimension of elementary devices. this evolution followed the famous moore's law [3]. nowadays, the minimum dimension entered within the nanometre scale, which is why we are now talking about nanotechnologies. on the one hand, the reduction in size was governed by a better control of the stages of the manufacturing process gradually involving the self-assembly of nano-objects and thin films. on the other hand, the size has also decreased due to the increase in the computing capacity that led to the improvement in the design of increasingly complex circuits. the consequence of this unprecedented evolution is that the lateral dimensions of the devices are currently approaching the inter-atomic distance. thus, the decrease in the size of the elementary transistors and thus the increase in the integration density of the transistors reach a physical limit. however, since the early 2000s, the introduction of the third dimension has provided a new way to further increase integration density. indeed, this approach is based on stacking of elementary devices and circuits on the surface of the previous circuits. this is carried out by involving new deposition techniques of thin films, and the technique of stacking of the circuits themselves based on the thinning of the substrates followed by a sticking process [13-14]. fig. 1 illustrates these two developments. the number of elementary devices in the most advanced electronic systems can count up to several billions [3]. fig. 1 moore’s law [3] and “more than moore” evolution [13]. systems on chip (soc) and systems in package (sip) open the way for connected objects [14] advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 67 thanks to this integration scheme, many electronic functions have been developed and by combining several technological processes, the extension to multi-physical systems has become possible. for example, micro-electro-mechanical systems (mems) technology opened the way to create many types of sensors and actuators. the possibility to gather several functions allows the creation of systems on chips (soc) and systems in package (sip) which are the cornerstone of new connected objects. indeed, the connected objects are a combination of several functions that are summarized in fig. 2 [5-6]. they may contain sensors, actuators, signal processing modules, analog/digital and digital/analog converters, energy harvesting cells, and communication modules. depending on the application domain, sensors and actuators are multidisciplinary [15]. with these new systems, the fields of application can cover all societal needs such as communications, health, environment, energy, transport, agriculture, and the new industry 4.0, which is covered in this document and that requires advanced manufacturing technologies. fig. 2 simplified architecture of a connected object with its main functions [6] to summarize, the microelectronics and the associated new connected objects, allow the complexity of the architecture and the systems, increasingly involve multidisciplinary approach, and can be applied to large spectrum of societal needs in the so-called internet of everything or ioe [16-17]. the human resources associated with this field, i.e. the engineers, technicians, and operators working in the manufacturing have to acquire skills corresponding to knowledge and know-how of the field, associated with capabilities of team working. 3. advanced manufacturing technologies and constraints advanced manufacturing technologies should involve many objects, including robots and connected environments. this environment must be secure and reliable in terms of physical objects, intellectual property, data protection and monitoring. for designers and manufacturers, this means a lot of works are dedicated to the safety and reliability of objects and microelectronic circuits, as well as to data transmission and the reduction of possible interferences in the signals. all these points put high challenges on microelectronic devices, circuits and systems. another aspect is less visible but of ever-increasing importance. it is the energy consumption of all these objects within the iot framework. fig. 3 shows the expected evolution of iot energy consumption over the next 20 years. growth is exponential and iot electrical power consumption is expected to reach 15,000 gw in 2040, which is the global energy consumption from all sources (nuclear, oil, gas and renewable energy) by 2018 [18], while the global average power consumption should reach about 125,000 gw [19-20]. it is clear that the planet will not be able to reach this level of production and the reasonable solution is to significantly reduce the consumption of each connected object by a factor of more than 10 and probably close to 100 after 2040. the solutions to this issue require deep changes in current microelectronics field. it is still necessary to reduce the consumption of each elementary device thanks to nanotechnology development, optimize the number of components in the advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 68 circuits, create new architectures that sequentially activate the useful zones by putting all the others on standby, i.e. to move from synchronous architectures to asynchronous ones in order to minimize the consumption of the clocks, combine different technologies (ulsi, thin film technologies, organic technologies) and improve the transmission and reception efficiency in signal transmissions, to mention only the most obvious ones. fig. 3 projected annual energy consumption over the next 20 years, equivalent to the world average annual capacity in 2018, all energy sources cumulated (after [20]) creating electronic circuits in heterogeneous technologies and multidisciplinary applications, improving safety, controlling energy consumption are the challenges that future technicians, engineers and phds will have to face. they must therefore be prepared through initial and lifelong training adapted to this evolution. university training in engineering must therefore meet these needs. the french network for education in microelectronics and nanotechnology (cnfm) [21], created in the early 1980s and moving from microelectronics to nanotechnology in the 2000s [22], has adopted a strategy in this direction. 4. french higher education network in microelectronics 4.1. the cnfm french network higher education in microelectronics in france is coordinated by a 35-years old national network, the cnfm, funded by the ministry of higher education with an official structure called “groupement d'intérêt public” (gip) [21-22]. this network was created to share education facilities (platforms) containing expensive micro and nano-fabrication equipment and tools, that require high operating costs. these shared open facilities allow offering practical training to all academic institutions in france that become users of the platforms for training their students in know-how. foreign academic institutions are also users of the platforms in the frame of cooperation agreements. this network is composed of twelve academic members who are respectively in charge of the twelve common centers spread over the french territory as shown in fig. 4, each center being common to several academic institutions located in the same geographic area. the twelve cnfm common centers (red labels) manage platforms i.e. technical facilities for practical hands-on training. among the eighty technical platforms, 7 cleanrooms are mainly dedicated to education (red stars). national services for cad (computer-aided-design) tools provided by the montpellier cnfm common center are dedicated to all the national community and foreign partners of the network. two industrial unions and especially the most representative association acsiel alliance electronics consortium [23] are also the members of the cnfm body. they represent more than 150 industrial sites (orange and green circles). the presence of industrial partners ensures strong links between academic training and industrial needs. indeed, industrial partners provide the cnfm network with the necessary valuable advice on the nature of skills and competencies needed by the work market. hereafter, we will present what we think to be the main characteristics of a good education approach able to ensure i) a high quality of the content, ii) a know-how on updated and industrial tools, iii) an international recognition of the diploma, iv) and sustainability meeting the needs of advanced manufacturing technologies. advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 69 fig. 4 map of the french academic and industrial activities in microelectronics [21] the main company sites are identified by orange circles. the twelve common centres of the cnfm (red circles and red stars) manage practical training platforms and are located throughout the metropolitan area. for their practice in cleanroom, students travel from their institution to closest cnfm centres (blue lines). 4.2. the missions and the strategy of the cnfm network as previously mentioned, the very essence of the gip-cnfm network is to share technical platforms, which include technological processes, cad, characterizations, and test, because of their very high equipment and operating costs. in addition, sharing pedagogical approaches between educators, and applying good practices towards students trained in initial training or even in lifelong learning (lll) is also a main educational target. collaboration within the network exists in several forms, via:  the sharing and common use of technological and design platforms,  the collaborative work in the context of national, or international, multi-year projects,  three-day educational workshops and brainstorming seminars involving teachers, researchers and technical collaborators, as well as industry representatives. these joint activities allow the exchange of knowledge and practices in order to produce and disseminate knowledge and know-how to the entire academic community [24] as well as to foster an innovative approach that is mandatory for advanced manufacturing technologies. 4.3. cnfm strategy with industry the main point of the gip-cnfm's strategy is to pool technology, design, characterisation and testing platforms in the broad field of electronics, microelectronics and nanotechnologies. this network provides a permanent link between the academic world and the industrial world that can reflect its needs in the short, medium and long term. the technological advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 70 platforms are accessible to all students, whatever their level from undergraduate to post-doctoral students, which allows them to acquire essential know-how in addition to the theoretical knowledge acquired either in traditional form (courses) or in the form of online tools, such as moocs [25-26]. since electronics and microelectronics are at the heart of the majority of innovative connected objects, the training strategy aims to provide skills and know-how in these fields [27] but also in the fields of application such as communication, health, environment, transport, etc. [15]. the existence of multidisciplinary platforms open to initial and lifelong learning must make it possible to meet the needs of industry in terms of the quality and relevance of curricula content. the close link within the cnfm network between academia and industry makes it possible to jointly define learners' needs, build curricula adapted to the objectives and ensure learning that includes both the knowledge and know-how required for a successful 21st century industry [27]. 4.4. collaboration within the network and international extension collaboration within the network exists in several forms, on the one hand through the sharing and common use of technological and design platforms, and on the other hand through collaborative work in the context of national, or international, multi-year projects and through the organisation of steering committees, national educational workshops and reflection seminars, particularly within the framework of the network's orientation council. these joint activities allow for the exchange of knowledge and practices in order to produce and disseminate knowledge and know-how to the entire academic community. this good practice of networking is not so familiar within the french academic world and serves as an example to other fields both in france and also abroad. the use of platforms shared by several academic institutions allows users from different backgrounds and belonging to different institutions to meet and collaborate while acquiring know-how that is essential for all. 5. some answers to the needs of companies involved in manufacturing with the objective of best meeting the needs of manufacturing industry, several parameters and qualities must be taken into account following several brainstorming meetings during 2018 and 2019. their objective is to adapt the training of technicians, engineers and phds, who will have to get along well with companies in industry 4.0. in the qualities required, we find constants, new approaches, and skills. 5.1. adaptation of the content the main aim is to cover the entire design and manufacturing chain of the connected objects that will be at the heart of 21st century industry. the programmes should therefore contain the basic knowledge and associated know-how in the following specialities: analog and digital electronics, signal processing, sensors and actuators, embedded electronics, energy harvesting systems, communications, transmission protocols and human-machine communication systems (vision, sound, touch, etc.). thanks to the annual funding provided by the cnfm to innovative education projects in the frame of the finmina project [28], the platforms are permanently up-dated with new practice in accordance with the evolution of the techniques and the fields of application [29]. these specialities must meet the future requirements of a connected society, namely: low power, low consumption, speed, reliability, low cost. in fact, the 80 platforms cover the entire microelectronics spectrum. 5.2. learning environment the objective of the existing network is to provide a learning environment that allows the trainees to be immersed in a technological environment that prepares them for the industrial environment of the 21st century and more particularly for advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 71 industry 4.0. indeed, the current centres include seven cleanrooms that condition users to the requirements of advanced technologies, namely, cleanness concept, adapted clothing, handling with dedicated tools or robots. indeed, the current centres include seven clean rooms that show the users the requirements of advanced technologies: cleanliness concept, adapted clothing, handling with dedicated tools and robots. they allow the use of high chemical purity products to minimize the contamination of integrated electronic devices, and the use of complex equipment that allows the creation of thin layers with thickness control at the atomic scale. the platforms associated with these cleanrooms allow a multidisciplinary orientation by the realization of mems (micro-electrical-mechanical-systems), biomems (biological mems), omems (optical mems), intended for sensors or actuators of connected objects [4]. computer-aided design of electronic systems uses industrial software to acquire concepts that capture high-level abstract models. these electronic systems are usually described by the means of advanced computer languages (such as vhdl) that design the functionalities, and non-functional specifications such as electrical consumption, safety, reliability and performance. due to the complexity of integrated systems, design requires the juxtaposition of many skills and know-how, which implies teamwork and therefore collective problem solving. team project training must meet these requirements and becomes an essential form of the pedagogical approach. within the network, all colleagues apply these principles in the educational programmes of their partner institutions, which automatically implement an experimental approach. 5.3. delivery mechanisms as already mentioned above, the first objective of the network is to provide the corresponding knowledge and know-how. given the organisation of the network, teachers and learners interact face-to-face on concrete issues. indeed, any practical activity is closely supervised because of the complexity, impact and dangerousness of the equipment used. this strong support in practical activities can be compensated by more autonomy in acquiring basic knowledge using online tools such as moocs [26, 30], serious games [31] and flipped classrooms [32]. these tools can also be adapted to prepare practical activities (practical training, supervised projects, etc.) in order to optimize the presence on the platforms and minimize their cost. the introduction of virtual and augmented reality or artificial intelligence can be considered as part of a constructive cooperation between the existing cnfm network and other networks with these competences. 5.4. assessment since practical activities in a high-tech environment are automatically supervised by a tutor or teacher, the evaluation must first be done by the supervisor. however, as these activities are generally carried out in groups, it is quite possible to exploit the group dynamic and its self-assessment, which can be included in experience reports drawn up at the end of their practical training on platforms. 5.5. recognition the official cnfm training network is made up of service units (or cnfm poles), which are not a priori authorised to deliver a diploma. diplomas, certificates or titles are awarded by the academic institutions to which the student users are attached. however, as part of lifelong learning, certificates may be issued specifying the objectives, content and quality of the work carried out on the cnfm platforms. it is expected that the network will become a certification body specifically designed for the training of employees of companies using the network's resources. 5.6. quality the content of the essentially practical activities are established in connection with academic training on the one hand and with companies for their employees on the other. this approach ensures content quality. at the end of practical training, advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 72 particularly for continuing training (lll), questionnaires are drawn up to check that the actual training is in line with the objectives defined in advance and that the trainees' perception is correct. a debriefing at the end of the training session should also allow trainers to justify certain approaches that would not have been perceived in the same way by users. 5.7. sustainability of the education network the cnfm network's strategy, which makes it possible to pool resources and maintain good matching with the needs of the socio-economic world, can only be achieved by keeping platform equipment and study topics at the highest level. the field of microelectronics has been evolving very rapidly for decades and training must also keep the pace. thus, this policy requires financial support to update the hardware and software that academic bodies currently have difficulty in assuming despite the pooling organised by the network, which however makes it possible to limit the cost. it is necessary to consider at national and european levels, that the training needs of companies are specifically supported within the framework of industrial sectors with dedicated funding from both public bodies and companies. 6. adaptation of the technical content by the cnfm network 6.1. new technical challenges as a result of the analysis of the context, the technical challenges that the future engineers and doctors will have to face appear at different levels in order to improve the electrical behaviour and the electrical energy consumption of the future connected objects included in robots or cobots, and involved in the advanced manufacturing. their interventions should occur at the level of the elementary devices, of electronic functions and circuits and at the level of systems, as follows:  continuation of the miniaturization of elementary devices, minimizing consumption both in the on-state (ron) and off-states (leakage),  reduction of switching and static losses of power components,  introduction of the third dimension to improve circuit integration in minimizing interconnection losses and improving reliability,  new circuit architectures able to control active and stand-by zones,  new circuit concepts allowing the generalization of asynchronous control of all elementary electronic function, minimizing the synchronous power supply by the clocks of all transistors,  implementation of low temperature and large area technologies,  development of low power sensors and actuators,  optimization of communication devices and protocols to limit the occupation of frequency bands and the data flow. it is clear that all these topics will need capabilities of team working and some multidisciplinary skills for the actors [34]. the choice of the practice of the network thanks to the annual calls organized by the network council is deliberately oriented towards these technical challenges. in the following we give several examples adapted to this strategy. 6.2. example of innovative practice provided by the cnfm centres several examples of realization by students in the cnfm centres during the last years are given. the scope is wide and we highlight only a few images that are representative of the orientation towards advanced manufacturing technologies. fig. 5 shows the designed and fabricated objects and mentions the corresponding cnfm centre of realization. advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 73 fig. 5 examples of objects, designed, fabricated and characterized in the microelectronics centres these examples show the complexity of the practice training on the different platforms, the multidisciplinarity of the realizations which are adapted to the local context of the microelectronic centres: computer-aided-design of new architectures for low consumption circuits [33], new sensors and micro-electrical-mechanical systems (mems), new nano-devices involving nanowire-based transistors and two-dimensional graphene-based transistors, radio-frequency waveguides for transceivers, electronics on plastics (plastronics), and lab-on-chip. depending on the complexity of the realization, the students can acquire the knowledge in less than one week in general initial formation, or during several weeks in the frame of projects that are more specialized. the students are using the design tools and the clean-room and characterization facilities of the different centres and of the national services for cad software [34]. 6.3. example of innovative practice provided by the centers since 2011-2012, more than 100 innovative projects have been launched by the cnfm centres. the users, mostly master's and engineering degree students, have experience in practical training and more particularly on innovative subjects. fig. 6 shows the evolution of the network activities over the past seven years. fig. 6 innovative practice on the platforms of the cnfm network over the past six academic years thanks to the national finmina programme [28], more than 6,000 students have acquired experience and know-how on new technological or design tools that meet the new needs of industrial and societal applications. about 1,000 are users of the platforms during their phd, and about 300, mainly employees of companies, are in lifelong learning in a thematic reconversion cycle. advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 74 7. conclusions the emergence of advanced manufacturing technologies in industry 4.0 requires an increasing adaptation of the training of engineers and technicians in the field of microelectronics to ensure that they acquire the skills and know-how necessary for the ever-changing iot technologies. the adaptation of training, which must meet quality and efficiency criteria, to the acquisition of skills and know-how is essential to meet economic, industrial and social needs [35]. the french microelectronics and technology training network, with the help of its twelve common platforms with a national mission, enables innovative practical activities to be set up using high-performance tools. this approach, considered original by the international academic community and highly appreciated by french industry, can serve as an example for other foreign countries. acknowledgment the authors want to thank all the members of the french gip-cnfm network for they contribution to many innovative realizations. this work is financially supported by french higher education ministry and by idefi-finmina program (anr-11-idfi-0017). a special thanks to l. chagoya-garzon, secretary of gip-cnfm for her fruitful advice for the proof reading of this paper. conflicts of interest the authors declare no conflict of interest. references [1] h. chaouchi, “the internet of things: connecting objects,” iste ltd, john wiley & sons, may 2010. [2] m. burgess, “what is the internet of things?,” wired magazine, https://www.wired.co.uk/article/internet-of-things-what-is-explained-iot, february 16, 2018. [3] g. e. moore, “cramming more components onto integrated circuits,” electronics magazine, vol. 38, no. 8, pp. 114-117, 1965. [4] v. sharma and r. tiwari, “a review paper on “iot” & its smart applications,” international journal of science, engineering and technology research, vol. 5, no. 2, february 2016. [5] a. schütze, n. helwig, and t. schneider,“sensors 4.0-smart sensors and measurement technology enable industry 4.0,” journal of sensors and sensor systems, vol. 7, no. 1, pp. 359-371, may 2018. [6] o. bonnaud, “new approach for sensors and connecting objects involving microelectronic multidisciplinarity for a wide spectrum of applications,” international journal of plasma environmental science and technology, vol. 10, no. 2, pp. 115-120, december 2016. [7] g. matheron, “microelectronics evolution, keynote, european, microelectronics summit,” paris, france, november 2014. [8] b. p. santos, f. c. santos, and t. m. lima, “industry 4.0: an overview,” proceedings of the world congress on engineering, vol. 2, 2018. [9] m. peshkin and j. e. colgate, “cobots,” industrial robot, vol. 26, no. 5, pp. 335-341, 1999. [10] å . f. berglund, f. palmkvist, p. nyqvist, s. ekered, and m. å kerman, “evaluating cobots for final assembly,” procedia cirp, vol. 44, pp. 175-180, 2016. [11] o. bonnaud and l. fesquet, “practice in microelectronics education as a mandatory complement to the future numeric-based pedagogy: a strategy of the french national network,” international kes conference on smart education and smart e-learning, springer, cham, pp. 1-8, may 2016. [12] m. mckellop, “the future of the semiconductor industry is the internet of things,” the burn-in, https://www.theburnin.com/industry/semiconductors-internet-of-things/, november 28, 2018. [13] r. r. tummala and m. swaminathan, system on package, miniaturization of the entire system, mcgraw-hill education, the1st edition, may 2008. [14] t. simonite, “moore’s law is dead. now what?,” mit technology review, https://www.technologyreview.com/s/601441/moores-law-is-dead-now-what/, may 13, 2016. advances in technology innovation, vol. 5, no. 2, 2020, pp. 65-75 75 [15] o. bonnaud, “the multidisciplinary approach: a common trend for ulsi and thin film technology,” ecs transaction, vol. 67, no. 1, pp. 147-158, 2015. [16] technopedia, “internet of everything (ioe),” https://www.techopedia.com/definition/30121/internet-of-everything-ioe, 2019. [17] idc, “what the iot market has in store for europe in 2019,” https://uk.idc.com/trends/predictions, january 30, 2019 [18] enerdata, “global energy statistical yearbook 2019,” https://yearbook.enerdata.net/total-energy/world-energy-production.html, march 2019. [19] international energy agency, “world energy outlook 2019,” https://www.iea.org, january 2019. [20] enerdata, “world energy production,” https://yearbook.enerdata.net/total-energy/world-energy-production.html, 2019. [21] cnfm, “coordination nationale pour la formation en microélectronique et nanotechnologies,” www.cnfm.fr; gip-cnfm, march 2019. [22] o. bonnaud, p. gentil, a. bsiesy, s. retailleau, e. d. gergam, and j. m. dorkel,“gip-cnfm: a french education network moving from microelectronics to nanotechnologies,” proceeding of ieee global engineering education conference; amman, jordan, pp. 122-127, april 2011. [23] acsiel alliance é lectronique, “components and systems alliance for electronics industry in france,” http://www.acsiel.fr/en-gb/index.aspx, 2019. 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[28] finmina, “formations innovantes en microélectronique et nanotechnologies,” http://www.cnfm.fr/?q=fr/pr%c3%a9sentation_finmina, innovative training for microelectronics and nanotechnologies march 2019. [29] o. bonnaud, l. fesquet, p. nouet, and t. m. brahim, “finmina: a french national project to promote innovation in higher education in microelectronics and nanotechnologies,” international conference on information technology based higher education and training, york, uk, proceeding of ithet 2014, september 11-13, 2014. [30] o. bonnaud, “new vision in microelectronics education: smart e-learning and know-how, a complementary approach,” international kes conference on smart education and smart e-learning, pp. 267-275, 2019. [31] f. bruguier, p. benoit, l. dalmasso, b. pradarelli, and l. torres, “amuse: un escape game pour l’enseignement de la sécurité numérique,”, proceeding of 15th jpcnfm 2018, saint-malo, france, vol.15, november 2018. (french) [32] o. bonnaud, y. danto, y.kuang,and y. li, “international flipped class for chinese honors bachelor students in the frame of multidisciplinary fields: reliability and microelectronics,” advanced in technology innovation, vol. 3, no. 3, pp. 126-132, 2018. [33] o. bonnaud and l. fesquet, “innovation for education on internet of things,” proceeding of engineering and technology innovation, vol. 9, pp. 1-8, 2018. [34] o. bonnaud and l. fesquet, “communicating and smart objects: multidisciplinary topics for the innovative education in microelectronics and its applications,” proceeding of 15th international conference information technology based higher education and training, ieee press, pp. 1-5, august 2015. [35] o. bonnaud, “mandatory matching between microelectronics industry and higher education in engineering toward a digital society,” smart education and e-learning 2019, springer, singapore, vol. 24, pp. 255-266, 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 2, no. 1, 2017, pp. 18 21 18 optimal warranty length and selling price to maximize the profit yu-hung chien 1,* , chung-piao chiang 2 1 department of applied statistics, national taichung university of science and technology, taichung, taiwan. 2 graduate institute of physical education, national taiwan sport university, taoyuan, taiwan. received 22 february 2016; received in revised form 15 april 2016; accepted 18 april 2016 abstract this study focuses on the problem of determining the optimal coverage period and selling price of warranted products from the manufacturer’s perspective. we first consider how to maximize the profit per unit under the assumption that the product can be sold or the demand is independent of the warranty policy. then we try to maximize the total profit for a planning period for the case where the demand for the product depends on the warranty coverage period and selling price. since the warranty period and the selling price should be positively correlated, we first solve the profit maximization problem with the warranty depended demand under the constraint that the selling price is a linear function of the warranty coverage period (warranty based pricing). furthermore, we investigate the case when such a constraint is removed (non-warranty-based pricing). optimizing on two independent decision variables, the coverage period and the selling price, certainly improves the total profit. under the two variable optimal conditions, it is observed that while the positive relationship between the optimal coverage period and the optimal price is confirmed, it is more complex than a linear one. we also find that the profit advantage for the non-warranty-based pricing over the warranty-based pricing is more significant for shorter coverage period. however, when the coverage period exceeds a threshold value, such a profit advantage becomes insignificant. the results of this study provide practitioners with useful insights in designing the profit optimal product warranty in highly competitive market. keywords: warranty, profit maximization, repair, replacement, renewable, optimization, price 1. introduction in today’s highly competitive market of consumer products, product warranties become an important criterion that distinguishes good and poor quality products. a warranty satisfying customer well can enhance customer willingness of purchasing, hence stimulate customer demand. this is because that a comprehensive warranty that covers a longer period implies a higher quality of the product. therefore, manufacturers try to offer a variety of warranties to expand the market share as consumers consider warranties as one of most important aspects in deciding which product to be purchased. however, a more attractive (or better customer service) warranty also implies higher service costs for manufacturers. as the product becomes more complex and expensive, the coverage of the warranty is required longer. an obvious trade-off between the benefit and cost of a warranty for a manufacturer is a critical issue for both academic researchers and practitioners. in the past decade, most of studies in the literature focused on the issue of how to minimize the warranty cost via preventive maintenance. shafiee and chukova (2013) provided a survey in this area from 2001 to 2011. there are relatively fewer works addressing both benefit and cost aspects of a product warranty. in fact, the marginal benefit can well exceed the marginal cost when the warranty coverage period is not long enough. for example, murthy et al. (2004) pointed out that on average the marginal profit for product with a warranty is about 30% compared with 10% without a warranty. in addition, * corresponding author, email: yhchien@nutc.edu.tw advances in technology innovation, vol. 2, no. 1, 2017, pp. 18 21 19 copyright © taeti a warranty with more comprehensive and longer coverage period helps build up the company and product image that may have the same positive effects of advertisement on future demand. thus, a good warranty benefits both consumer and manufacturers. as mentioned before, there are not many studies on determining product warranty parameters with consideration of its effects on market demand. glickman and berger (1976) is one the earliest papers on the effects on consumer demand of warranty parameters. they addressed the problem of determining the optimal price and the warranty period and considered demand function of market statistic in which the demand decreases exponentially with price and increases exponentially with the warranty length (coverage period). applications of the demand function of this form can be found in the literature such as mitra and jayprakash (1997). ladany and shore (2007) also consider a cobb-douglas-type demand function in determining the optimal warranty period, they presented a review on manufacturer’s pricing strategies for supply chain with warranty period-dependent demand. from the consumer’s perspective, the longer the warranty period is, the better the after-sales service is. however, a longer warranty period implies a higher expected warranty cost to the manufacturer. this is particular true for the renewing free-replacement warranty (rfew) under which the product must be replaced with a new one and a new full warranty period if the product fails within the warranty period offered. since the purpose of refw is to ensure a product to function for the entire warranty period, the length of the warranty period can be viewed as a measure of the product’s quality and reliability. in addition, due to its cost implication to a manufacturer, we can assume that there is a positive correlation between the selling price and the warranty period. in this paper, we first find the optimal warranty period or selling price to maximize the profit of a sold product. another issue we address is the impact of the rfew on the customer demand. it is reasonable to assume that the warranty period and the customer demand can be positively correlated for a certain range of the selling price. to model such a relation, we utilize the cobb-douglas-type demand function of selling price and warranty period to determine the optimal or profit maximization warranty period and/or selling price for the manufacturer 2. mathematical formulation consider a product with a random life-time of x. let f(x), f(x) (=p(x  x)), )(xf (=1 f(x)), and )(xr ( )()( xfxf ) be the probability density function (pdf), cumulative distribution function (cdf), survival function (sf), and failure rate function (fr) of x, respectively. let w be the period of the rfew and pc be the selling price of the product. we first assume that there is a positive linear relation between the selling price and w or pc a+bw. such an assumption has been made in ladany and shore (2007). under this assumption, we can find the optimal w to maximize the profit of a sold product. 2.1. unit profit maximization for a product sold denote by y the number of failures (replacements) of a sold product within the rfrw. according to the scheme of rfrw, the probability mass function of y can be expressed as           .1 if ),( ,0 if ),( ywfwf ywf yyp y (1) let cr be the replacement cost when the product fails within the rfrw period. based on (1), the expected cost of rfrw is )( )( )()( wf wf cyecwc rr  (2) thus the expected profit for the product sold is )( )( )()( wf wf cbwawccw rp  (3) let * 0w be the maximize of (3) or  * 0w  ww 0max  . if the failure rate is an increasing function (ifr), we can establish the following properties. property 1. for a product sold with the rfrw, if the selling price is a linear function of the warranty period, the profit maximization * 0w has the following properties: advances in technology innovation, vol. 2, no. 1, 2017, pp. 18 21 20 copyright © taeti (i) if rcbr )0( , then 0* 0 w and  * 0w 0)0(  a ; (ii) if rcbr )0( ， then  * 00 w exists and unique, and   aw * 0 . this proposition indicates that there exists a finite warranty period that maximizes the profit and the profit of selling one product is at least a. whenever the initial failure rate exceeds a threshold (or rcbr )0( ), the rfrw should not be provided or 0* 0 w and the unit profit is still at least a. 2.2. total profit maximization for products sold in a planning period now we solve the profit maximization problem when the impact of the rfrw on the customer demand is taken into account. let )(wq denote the quantity sold in a planning period for products sold under rfrw. it is assumed that the demand depends on the warranty period w and is modeled as cobb-douglas-type function:  )()()( wcwq p (4) where 0 , 0 , 0 . denoting the total profit for the period by )(w , we have )()()( wwqw   (5) denote the profit maximal warranty period by *w or )(max)( 0 * ww w   . we can obtain the following result. property 2. for the product with an rfrw, if the selling price is a linear function of w and the demand function is given in (4), then there exists a unique and finite w that maximizes the total profit for a planning period. 2.3. total profit maximization without warranty-based pricing now we assume that both the price and the warranty period are decision variables for maximizing the total profit for a planning period. the total profit function ) ,( wc p can be written as ) ,( wcp ) ,() ,( wcwcq pp         )( )( )()( wf wf ccwc rpp  (6) where 0 , 0 and 0 . we can show that there exists an optimal solution to (6). property 3. for the profit function ) ,( wc p given in (6), under the condition 01 , if there exist ( * pc , *w ) satisfying )( )( 1 * ** wf wrw           and )( )( 1 * * * wf wfc c r p     , then ( * pc , *w ) maximize ) ,( wc p or ) ,( max) ,( 0 ,0 ** wcwc pwcp p   . an interesting finding here is that when both the price and warranty period are decision variables, the optimal warranty period *w only depends on the demand function parameters of  and . it does not even depend on the replacement cost. specifically, as  increases both *w and * pc increase; as  decreases both *w and * pc decrease. these relations are intuitive. now we solve the profit maximization problem when the impact of the rfrw on the customer demand is taken into account. let )(wq denote the quantity sold in a planning period for products sold under rfrw. it is assumed that the demand depends on the warranty period w and is modeled as cobb-douglas-type function: 3. numerical illustration and sensitivity analysis assume that lifetime of the product x has a weibull distributed survival function   xxf  exp)( (7) where scale parameter and shape parameter are 1 and 2 , respectively. clearly, such a distribution has the ifr property. advances in technology innovation, vol. 2, no. 1, 2017, pp. 18 21 21 copyright © taeti our first numerical example is the one with the warranty-based pricing and is based on the set of parameters as 0.1rc , 0.1a , 2.0b , 10 , 5.0 , and 5.0 . the unit profit function and its derivative can be shown. the decreasing first-order derivative of the unit profit function shows the concavity of the function. thus the first-order derivative condition will give the global optimal point. the total profit )(w and its derivative are shown below respectively, which indicate that a unique optimal warranty period exists although the profit function has both convex and concave sections. next we consider the case where both the selling price and the warranty period are decision variables for maximizing the total profit. the optimal * pc , *w and ) ,( ** wc p are computed under various  and  , presented in table 1. table 1 the optimal w * , c * p and π (𝑐𝑝 ∗ , 𝑊∗) under various 𝛽 and 𝛾   1.1 1.2 1.3 1.4 1.2 2.446 2175.7 12.330 1.680 47.451 7.176 1.262 8.4862 5.3544 0.935 2.4447 4.6083 1.4 2.645 6002.0 14.865 1.839 85.281 8.0364 1.423 14.247 5.6810 1.117 4.3440 4.6343 1.6 3.000 44561. 22.517 2.109 253.33 10.553 1.680 34.270 6.7785 1.386 10.198 5.0772 4. conclusions in this paper, we have studied the problem of joint determination of the optimal selling price of a product and the optimal warranty period offered at no extra charge with the product as an incentive to the consumer. expected demand in our model was taken to be the cobb-douglas type demand function. structural and insightful properties of the optimal results are obtained and compared analytically. our study provides a useful quantitative tool for sellers to decide price and warranty length for products sold. acknowledgement the support of the ministry of science and technology, under grant nsc 102 2221 e 025 004 my3 is gratefully acknowledged. references [1] t. s. glickman and p. d. berger, “optimal price and protection period decisions for a product under warranty,” management science, vol. 22, pp.1381-1389, 1976. [2] s. p. ladany and h. shore, “profit maximizing warranty period with sales expressed by a demand function,” quality and reliability engineering international, vol. 23, pp. 291-301, 2007. [3] a. mitra and g. p. jayprakash, “market share and warranty costs for renewable warranty programs,” international journal of production economics, vol. 50, pp. 155-168, 1997. [4] d. n. p. murthy, o. solem and t. roren, “product warranty logistics: issues and challenges,” european journal of operational research, vol. 156, pp. 110-126, 2004. [5] m. shafiee and s. chukova, “product warranty logistics: issues and challenges,” european journal of operational research, vol. 229, pp. 561-572, 2013.  advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 innovative strategy to meet the challenges of the future digital society olivier bonnaud * department of sensors and microelectronics, ietr, university of rennes 1, 35042 rennes, france national coordination for education in microelectronics, gip-cnfm, 38016 grenoble, france received 12 november 2020; received in revised form 30 december 2020; accepted 04 february 2021 doi: https://doi.org/10.46604/aiti.2021.6724 abstract today, we are experiencing a societal revolution with the development of digital technologies, and it brings new challenges. indeed, the number of connected objects, intelligent sensors and iots are increasing exponentially. the same goes for the resulting energy consumption. beyond 2030, without a radical transformation of communication technologies and protocols, the digital world will be at an energy dead end. all these objects are physically realized with microelectronic devices and systems. this analysis of the microelectronics community has led the french government to recognize an electronics sector that is becoming a priority area of industrial policy. the strategic committee of this sector has proposed innovations applied to the entire digital chain including all facets of the microelectronics field and human skills and know-how. the technological and energy issues are thus presented, and the proposed solutions were addressed. they concern both technological and human aspects. this paper ends by giving examples of the implementation of innovative approaches which essentially include the electronic functions involved in connected objects and which are intended to bring the know-how of future actors in the field. keywords: digital society, microelectronics, multidisciplinarity, energy challenge, higher education training 1. introduction it is globally recognized that we are experiencing a societal revolution with the development of digital technologies, connected objects and the internet of things (iot) [1]. while this rapid evolution may seem easy and problem-free, in reality, it raises new and extremely important challenges. indeed, the number of connected objects, smart sensors, artificial intelligence systems (ai) and iots is growing exponentially. all these objects, functions and systems take part in the industrial revolution 4.0. [2], which will involve many robots, collaborative robots [3], connected monitoring, and management. as a consequence, the resulting energy consumption of this digital world is growing exponentially as well. all of these objects and systems are physically realized using microelectronic and nanotechnological devices, circuits and systems, as well as smart sensors and actuators, opening the way to multidisciplinary applications [4]. beyond 2030, without a radical transformation of technologies and communication protocols, the digital world will be in an energy dead-end and most likely also in a digital security dead-end [5]. this analysis by the microelectronics community has led to the french government's recognition of an electronics sector that is becoming a priority axis of industrial policy [6]. a strategic sector committee has been set up, bringing together industry representatives, researchers and academic forces in the field of electronics and microelectronics. it acts as a structure for brainstorming and positions itself as a force for proposals to government ministries. it highlights innovative topics applied to the entire digital chain and which are part of the technical challenges. they will be applied to elementary components and to the architectures of electronic circuits and systems for the detection, processing and storage of information as well as signal * corresponding author. e-mail address: olivier.bonnaud@univ-rennes1.fr advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 107 transmission. if these topics seem to be part of a classical approach, in practice the concepts to be implemented are new. indeed, designers and manufacturers have tried in the past to bring new products with new functions to the market as quickly as possible, regardless of energy consumption and environmental impact. their approach has been to implement the existing product using ip (intellectual property) and through improved integration, the size of the circuits and systems has not increased. in addition, in order to produce faster and cheaper, many companies have ceased their activities and relocated the manufacture of electronic devices and systems abroad, particularly, to the far east. while this approach seems very good economically, in the long term it means a loss of skills and foreign dependency that can affect strategic sectors. this evolution generates new challenges that lead to a new strategy. this strategy must respond to an increase in human skills and know-how, both qualitatively and quantitatively, in order to meet these challenges. the main objective of this work is to describe the strategy adopted by the french industrial electronics sector and by the national academic network in charge of higher education in the field of electronics, microelectronics and nanotechnologies, in order to meet the challenges on both levels. the first one deals with the technological aspect with an innovative approach that particularly decreases the power consumption of all iot applications. note that the new connected objects are designed to save energy in many societal applications related to transportation or smart home for example [4]. the second one is the human aspect in the framework of improving knowledge and know-how in order to reduce the shortage of skills in this exponentially growing field. future actors will have to ensure innovation in connected objects and their applications in all sectors of society. thus, this document focuses successively on the strategy set-up by the microelectronics industry sector in france, on the detailed description of the technological and energy challenges that highlight human needs, and finally on the actions carried out within the national training network in microelectronics and nanotechnologies to train future actors in this field. special attention is paid to the current contribution to training and to the innovation strategy that needed to meet future challenges. 2. digital society and microelectronics links in order to fully understand the importance of the strategy and the challenges in the field of microelectronics, this first part deals with the situation of the field in the context of the future digital society. this evolution is global. however, in order to describe concrete actions, the case of france is highlighted. 2.1. dependence of the digital society on the electronics sector the revolution of smart and connected objects coupled with the energy transition is affecting all sectors of industry and the growth of the next few decades will belong to those who can benefit from these technological innovations based on electronics [6]. electronics is the essential industrial base for the production of digital equipment and systems. the electronics industries thus take a central place in the french industrial landscape and are at the heart of the digital transformation [7]. after several years of reflection and consultation, the electronics industry sector was found on march 15, 2019 by the general directorate of enterprises within the ministry in charge of economy, finance and industry [8]. the “electronic sector” is therefore at the heart of the societal evolution towards digital and connected objects (iot, internet of things, internet of every-thing!). in france, it represents 1,100 companies and 230,000 jobs for a turnover of 15 billion euros [6]. in order to meet the challenges, this sector must master the 4 complementary pillars which are: (1) technologies and electronic components including intelligent sensors to create data, (2) the connected objects to process, transmit and develop the associated services, (3) power electronics to support the energy transition and the development of electric mobility, (4) cybersecurity to build the confidence necessary for the development of electronic technologies in industry (cyber-physical systems). advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 108 2.2. major role of microelectronics, microand nanotechnologies within this sector, microelectronics occupies a central place since all the objects involved in smart and connected objects are made up of electronic components, circuits and systems. the great majority of which are integrated and carry embedded software that provides the intelligence of the application devices. in addition, many new systems include passive devices and micromechanical elements for sensing or actuations. to resume, the connected objects are primarily made up of multiple microelectronic, microtechnological and communications devices [9] that are judiciously combined in a full system. this evolution has been made possible by the fabulous growth of microelectronic integration over the last sixty years. the number of elementary components in an integrated circuit has increased from a few units to a few billion thanks to the reduction of lateral dimensions in a plane [10]. unfortunately, this reveals a physical limitation related to the distance between atoms and the quantum effects attached to them. but about fifteen years, this limitation has been overcome by playing on the third dimension [11], which makes it possible to have integrated systems of several thousand functions that can each contain billions of elementary components [12]. these results make it possible to have data processing systems in fabulous quantities in ever shorter times and have paved the way for connected objects, iot, ai and the industrial revolution 4.0. all these aspects are taken into consideration in the strategy at the national level. 2.3. main objectives resulting from the analysis of the french electronics sector the french electronics sector has established a strategic committee composed mainly of industrial members but also of academic members. the main goal of this strategic committee is to develop activities capable of meeting the challenges mentioned above. the committee has thus identified four key priorities in its work: (1) maintaining excellence in key digital technologies by increasing r&d&i efforts and developing strategic partnerships; (2) adapting skills by anticipating changing needs (employment and skills) and by developing work-linked training offer; (3) promoting competitive "made in france" electronics manufacturing; (4) positioning the sector as a key player in the digital transformation by supporting smes in other sectors. within the framework of these priorities, the strategic committee set up four working groups in 2019 that produced several documents proposing priority actions and objectives. the first priority directly concerns the purely technological aspects with the associated constraints and challenges. it mainly concerns the policy towards research laboratories and research development departments of companies. the second priority relates to the adaptation of skills and know-how, which presents a challenge in terms of training content at all levels and the number of people trained. everything possible must be done to achieve these objectives that are: (1) raising young people's awareness of the field in order to make it more attractive, (2) initial training from technician to engineer level, (3) advanced training through research to develop innovation, (4) life-long training to enable the company's employees to adapt to innovative technologies. it is clear that we will focus on these two priorities that directly involve universal strategy and actions. to this end, it is useful to detail the different areas of scientific and technical expertise and know-how. in other words, we need to highlight the technical and technological connected objects and challenges advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 109 3. connected objects and challenges the digital society and future industry 4.0 are based on internet of things (iot). in terms of physical support, the basic system is the connected object that gathers many electronic functions. in addition, the connected object fills also a mission of control, monitoring processes or robots. in order to well select the skills and the orientation of the training, it is useful to highlight the several associated works, limitations and related challenges. 3.1. usual architecture of a connected object the first mission of a connected object is to retrieve a physical, chemical or biological quantity by means of a sensor that transforms it into an electrical signal, amplifies and treat the signal, transmits it remotely to a processing system in order to have a feedback through the whole chain that can correct the original quantity. it is thus composed of an on-site part, a remote part and a communication system between the two. the connected objects must perform functions such as detecting a physical, chemical or biological analogue signal, transforming it into digital signals via converters, storing and transmitting it via communication protocols, receiving it in databases and data centers, analysis processing centers, and performing the return chain to an actuator that can control the application phenomenon. thus, all these objects have a common architecture as shown in fig. 1, which includes sensors and actuators, electronic modules for signal processing, data transmission and reception modules, but also devices for monitoring, visualization, alarms, memorization, energy recovery and storage, etc. [9]. fig. 1 schematic architecture of a connected object. many electronic functions are involved in the full system 3.2. multiplication of connected objects and sensors as already mentioned, the enormous integration capacity of microelectronics allows multiplying not only the connected objects, but also the sensors and the iot [13]. the number of these functions and objects is growing exponentially, as shown in fig. 2 [14]. it is interesting to note that the development of heterogeneous integration has led to the development of sensor design and fabrication. for example, about thirty sensors are installed in a regular cell phone, while seventy are wired in a standard car. fig. 2 exponential growth rate of the number of iot, connected objects and sensors; a direct effect of the microelectronics integration growth advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 110 3.3. energy consumption challenges the consequence of this exponential growth is that the energy consumed by connected objects is also growing exponentially and is becoming globally preponderant [15] as it will be shown below. indeed, one gigabyte of data downloaded from the internet sums up to 5.12 kwh [16]; loading a film online (equivalent to a 5gb dvd) consumes 25 kwh! according to recent literature, the contribution to this consumption is distributed as shown in fig. 3: fig. 3 allocation of power consumption due to connected objects and iot 48% by data centers (servers, routers); 38% by the end user (computer, smartphone, display, battery charging, screen power supply, life boxes, etc.); 14% for communications (cables, optical fibers, repeater-amplifiers, hertzian or satellite transmissions). fig. 4 expected exponential growth of the iot electrical energy consumption without any change in the technologies of iot and connected objects this distribution is approximate since some functions can be assigned to two different sectors. however, the total appears to be correct. as shown in fig. 4, the electricity consumption due to iot is multiplied by 2 each 4 years. in 2018, the electrical energy consumed by the implementation of connected objects reached 2,900 twh, which corresponds to a permanent production of 320 gw out of the 8,800 annual hours and represents 11% of the world's electrical energy consumption [17]. at the beginning of 2020, the consumption was equivalent to about 3 times the energy consumption of world air traffic as shown fig. 4. let us notice that due to the global pandemic linked to “covid-19”, the extrapolation of global air traffic beyond 2020 has been strongly affected since these curves were drawn. assuming current technologies are maintained, this global energy consumption could reach 124,600 twh in 2040, which represents a permanent production of 15,000 gw or 15,000 nuclear reactors. this energy consumption is also equivalent to the global energy production in 2018, regardless of its source and form [18]. it is clear that this situation will become unrealistic and that major changes will have to be made in the design, technology, energy consumption of connected objects, the organization of manufacturing (industry 4.0.) and the transfer and storage of data. in practice, the energy consumption of all physical objects will have to be considerably reduced. the first approach will consist in reducing the consumption of microelectronic devices and circuits, which account for a contribution close to 60%. assuming that the reduction gradually reaches a factor of 10 over the next 20 years, we can expect an evolution of iot-related advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 111 energy consumption as shown in fig. 5. global electrical consumption and iot consumption in dash lines are issued of fig. 4. knowing that iot consumption does not depend only on the hardware, instead of undergoing a growth in a ratio of 32, we should limit this growth with a ratio of 6.5. the annual electrical energy consumption of iot is expected to reach nineteen thousand terawatt-hours, which is more appropriate for the planet (full lines) and therefore more realistic. however, global consumption of electrical energy will in any case be twice as high as it is today. fig. 5 expected iot consumption and global electrical energy consumption in 2040. decreasing significantly the consumption of electronics devices and circuits (dash line to solid line), should allow to limit the global electrical energy consumption to 57,000 twh a year by 2040 3.4. induced challenges on microelectronics technologies, integration, consumption, multidisciplinarity in order to achieve this reduction by a factor of 10, many challenges will have to be met. the challenges of the discipline thus appear at different levels. the works of the french microelectronics network and of the working group of the strategic committee of the industrial sector have concluded on the priorities. although already presented in a previous document [18], it is however useful to recall the enumeration of the major points [13]: (1) the further miniaturization of elementary components in order to minimize their consumption both in operation and off-state by reducing leakage currents (tunnel effect); (2) improving the performance of power components and their circuits in order to reduce both switching and static losses. these properties are very important for servers and data centers which have a huge permanent energy consumption; (3) the uses of the third dimension to improve circuit integration in order to minimize interconnection losses and improve reliability. extensive studies will be required to control the power density to be dissipated in these three-dimensional structures; (4) modification of the circuit architecture to separate useful active zones from zones that can be put on standby, a way to significantly decrease the permanent energy consumption of circuits; (5) the generalization of asynchronous control which should minimize the important losses linked to the synchronous power supply by the clocks of all the transistor control electrodes; (6) the implementation of new low-temperature and/or large-area technologies involving new materials (inorganic or organic) for which the electrical consumption can be several orders of magnitude lower; (7) the development of sensors and actuators in specific low-power technologies. these technologies will be able to be integrated thanks to the rapid growing heterogeneous integration, presently. several of them will involve a multidisciplinary approach related to the application domain; (8) optimization of communication devices and protocols to limit frequency band occupation and data flow to keep only the useful according to the mission profile. all these topics are introduced in the strategy of the microelectronics industry sector and the national training network. advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 112 3.5. present shortages in human skills revealed by the strategic committee the technical and technological challenges can only be met if the future technicians, engineers, teachers and doctors are capable of dealing with the subjects mentioned and providing innovative solutions that meet the requirements. it is therefore necessary to provide initial and continuing training adapted to this evolution and allowing them to acquire a good basic knowledge of the technique but also the know-how indispensable for design and production [19]. due to the increasing complexity of the discipline, training must be able to cover the basic knowledge that will have to be redefined, but also the acquisition of skills in highly specialized areas. this necessitates the adaptation of study content by introducing new concepts and pedagogical approaches, including more practical learning, but also a strong awareness of multidisciplinarity in relation to the fields of application [20], project-based learning and the ability to work and innovate in a multidisciplinary team. currently, at the global level, companies in the electronics and microelectronics sector report a lack of applications in many skilled jobs. training must fill this gap in the job market. this aim is in line with the missions of the french higher education training network in the field of microelectronics. 4. the national microelectronics network in the electronics sector 4.1. constitution of the cnfm network as already presented in the previous paper (18), this network is entitled cnfm for national coordination for training in microelectronics and nanotechnologies [21], with an official structure as a gip (for public interest group). it is composed of twelve academic members who are respectively in charge of twelve common centers spread over the french territory, each center being common to several academic institutions located in the same geographic area [22]. the twelve cnfm common centers manage platforms and their technical facilities for practical hands-on training. among the eighty technical platforms, 7 cleanrooms are mainly dedicated to education, but also allow research and transfer activities. national services for cad (computer-aided-design) tools provided by the montpellier cnfm common centers are dedicated to all the national community and foreign partners of the network. two industrial unions and especially the most representative association acsiel alliance electronics consortium [23] are also the members of the cnfm body and involved in the national electronic sector policy. they represent more than 150 industrial sites. 4.2. concept and objective of the cnfm network the true essence of the gip-cnfm network is to share technical platforms, which include technological processes, cad, characterizations, and test. this sharing is mandatory due to the very high costs of equipment and functioning expenses. in addition, sharing pedagogical approaches between educators, and applying good practices towards students in initial training or even in life long learning [24] is also a main educational target. fig. 6 the microelectronic network is at the heart of the master plan. innovative practice enables the know-how of future players in the electronics sector to be developed advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 113 the objective of the existing network is to provide a learning environment that allows the trainees to be immersed in a technological environment that prepares them for the industrial environment of the 21st century and more particularly for industry 4.0. thanks to an eight years project entitled finmina [25], the policy of permanent innovation in the twelve centers of the network was boosted. it allowed to develop innovative platforms with original practice all along the eight years, from 2012 to 2019 [26]. the strategy was therefore to create new practical training courses in line with the advent of the digital society. fig. 6 summarizes the strategy to address the technological challenges while addressing the human challenges. 4.3. main know-how training activities in the majority of cases, the innovative character of the training activities stems from the research activities carried out by the teacher-researchers of the academic institutions and members of the network. this research is very often conducted in partnership with corporate research and development centers, which makes it possible to direct them towards the expressed by the sector. fig. 7 summarizes the two indicators of the network combining skills and objectives based on an innovative approach. fig. 7 positioning of the cnfm training network in the electronics sector strategy. innovation must improve skills in the priority actions of the electronics sector another point that needs to be stressed is the necessary complementarity of knowledge and know-how across the skill set [27-28]. this complementarity is more essential in the engineering disciplines and more particularly in microelectronics and whatever the technologies [29]. various examples of platform realizations and practical work that were recently set-up by the network are given below. they address all the mentioned aspects of the evolution towards digital, knowing that a good digital technology must solve many problems related to the analogue properties of electronics! they also concern the variety of application fields, which implies the use of physical/electronic, chemical/electronic, biological/electronic transducers, which are mostly miniaturized and integrated. subjects range from classical electronics to microelectronics and nanotechnologies, from very low power to high power, including fast communication electronics and embedded electronics, systems-on-a-chip, lab-on-a-chip, and digital security systems, which gives them a multidisciplinary aspect. subjects range from classical electronics to microelectronics and nanotechnologies, from very low power to high power, including fast communication electronics and embedded electronics, systems-on-a-chip, lab-on-a-chip, and digital security systems, which gives them a multidisciplinary aspect [29]. these techniques can implement multi-physical design tools, integrated silicon technologies, but also technologies based on new inorganic compound and organic materials and large-area thin-film devices for display or energy harvesting [30]. finally, they also involve digital security (in the material and equipment meaning), reliability, and testing whether electrical, physical or physical-chemical from the human to the atomic scale. 4.4. main results on innovative strategy of the network detailed information on these activities is available on the network's website [22] and examples have already been presented in the literature according to their subject matter [28-31]. fig. 8 shows several results of the innovative training strategy, which were provided by the network's inter-university centers. the topics concern technologies, designs, advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 114 characterizations, sensors and systems with a multidisciplinary approach as mentioned in the main objectives. on each selected image, the name of the center and the subject are displayed. all innovative practice topics are validated by the representative of the microelectronics industry in the framework of the general assembly of the official structure of the network (gip-cnfm), whose president is also the president of the french union of the microelectronics industry. fig. 8 example of practice realizations by students in several network’s microelectronics inter-university centers. for each picture, the name of the center and the topic are displayed in fact, more than 80 practical and innovative learning platforms have been set up within the network over the last decade. every year, nearly 6,000 users come to acquire know-how on these evolving platforms, with another 11,000 coming to the centers to acquire basic or awareness-raising know-how. this approach has an international interest, especially in china [32-33]. 5. conclusions in an environment of continuous and tremendous technological evolution for more than 60 years, the field of microelectronics allows the development of connected objects and the advent of industry 4.0 applied to many areas (iot) that are experiencing exponential growth. the societal stakes are considerable, and everything must be done to limit the energy consumption of the communicating systems that will invade our daily lives. these challenges will be met thanks to high-quality, innovative training to improve the performance of the associated electronics, which must on the one hand meet these economic and societal requirements, and on the other hand be in line with the priorities of the electronics industry, which has been undergoing restructuring since 2019. the gip-cnfm, a joint national training structure, by providing students and technical staff of industrial companies with skills and know-how in the field, is positioning itself as a major player in symbiosis with the world of industry and research, and is helping to prepare for the future by increasing the pool of trainees both qualitatively and quantitatively. acknowledgment the authors want to thank all the members of the french gip-cnfm network for they contribution to many innovative realizations. this work was financially supported by french higher education ministry and by idefi-finmina program (anr-11-idfi-0017). a special thanks to l. chagoya-garzon, secretary of gip-cnfm for her fruitful advice for the proof reading of this paper. advances in technology innovation, vol. 6, no. 2, 2021, pp. 106-116 115 conflicts of interest the authors declare no conflict of interest. references [1] m. burgess, “what is the internet of things?” wired magazine, https://www.wired.co.uk/article/internet-of-things-what-is-explained-iot, february 16, 2018. 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[32] o. bonnaud and l. wei, “a way to introduce innovative approach in the field of microelectronics and nanotechnologies in the chinese education system,” proceedings of engineering and technology innovation, vol. 4, pp. 19-21, october 2016. [33] o. bonnaud, y. danto, y. h. kuang, and l. yuan, “international flipped class for chinese honors bachelor students in the frame of multidisciplinary fields: reliability and microelectronics,” advances in technology innovation, vol. 3, no. 3, pp. 126-132, march 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 the impact of coating ingredients on the aging resistance of topcoat paints by model trees tzu-tsung wong * , shih-hsuan hung institute of information management, national cheng kung university, tainan, taiwan received 20 may 20xx; received in revised form 15 july 2020; accepted 14 september 2020 doi: https://doi.org/10.46604/aiti.2021.5307 abstract topcoat paint is mainly composed of resin and pigment and hence its quality highly depends on the type and proportion of these two ingredients. this study aims at testing the formula of the topcoat paint for finding one that can achieve better quality for anti-aging. various formulas of paint are applied on boards that will be put into ultraviolet accelerated test machines to simulate weathering tests. the gloss and color, before and after the tests, are collected and numerical prediction method m5p is used to grow model trees for discovering the key factors affecting aging. based on the structure and the linear regression models in the trees, a better topcoat paint should be composed of a high proportion of resin and generally a low proportion of pigment. good types of resin and pigment are also identified for keeping color and gloss. keywords: accelerated aging test, linear regression, model tree, numeric prediction, topcoat paint 1. introduction buildings are usually covered by paint to enhance their looking and durability. there are two main categories of paint: undercoating and topcoating. topcoat paint can protect buildings from erosion and the function of undercoat paint is to increase the adhesion of topcoat paint. the life of a building is thus primarily determined by the quality of topcoat paint. the two main materials for composing paint are resin and pigment. the type and proportion of these two ingredients have a great impact on the appearance and aging-resistance properties of topcoat paint. if the relationship between the ingredients and the aging properties can be determined, an enterprise will be able to produce a topcoat paint that can satisfy the requirements of a customer at a relatively low cost. the coating on objects is critical to the protection of the objects and hence this kind of the issue has been studied in several applications [1-4]. accelerated tests were generally adopted to obtain observations for studying the properties of paints [5-7]. resin and pigment are the two main ingredients of paints. many recent studies attempted to explore the individual impact of resin [8-9] or pigment [10-14]. these two ingredients can also be considered together to determine the performance of coatings [15-17]. none of those previous studies applied numeric prediction methods to analyse the impact of resin and pigment on the aging properties of paints. the purpose of this paper is to explore the various formulas of topcoat paint. the data collected for various formulas will be analysed by a numeric prediction method that can produce a tree structure with multiple linear regression models. the tree and the regression models can be helpful in finding the attributes that are critical to the properties of topcoat paint. these results can be employed to compose the topcoat paint for satisfying customer needs. * corresponding author. e-mail address: tzutsung@mail.ncku.edu.tw tel.: +886-6-2757575; fax: +886-6-2362162 advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 40 2. data collection the three factors that can affect the life of paint are solar radiation, temperature, and humidity, and solar radiation has the most significant impact. better quality of resin and pigment can enhance the aging-resistant properties of paint. a company uses three types of resin r1, r2, and r3 and three types of pigment p1, p2, and p3 provided by different vendors to produce paint. the proportion of the resin in a formula can be between 30% and 60%, and this value for pigment is generally between 15% and 35%. the four attributes for determining the aging-resistant properties of paint are shown in table 1. the number of possible combinations resulting from the four attributes is 3435 = 180. the paint of each combination will be applied on two boards to collect their data for the aging resistance; accordingly, the number of instances in a data set will be 360. note that the two proportions x2 and x4 are considered as continuous attributes for analysing their impact on the age-resistant properties. table 1 the attributes for determining the aging-resistant properties of paint attribute possible values x1 (resin type) r1, r2, r3 x2 (resin proportion) 30%, 40%, 50%, 60% x3 (pigment type) p1, p2, p3 x4 (pigment proportion) 15%, 20%, 25%, 30%, 35% the lifetime of a system is the duration for the system to operate normally. however, the degradation of the coating in a building occurs gradually as time goes by. the age of paint is thus represented by its colour and gloss. an aluminium board coating by paint will be dried naturally for a week. then its colour and gloss will be measured and recorded as c0 and g0, separately. fig. 1 shows the colour meter to evaluate the colour in a board. for the sake of simplicity, the colour of all formulas is set to be white. a smaller value implies that the white colour is brighter. similarly, the gloss of a board is measured by the gloss meter shown in fig. 2. the gloss values of five fixed positions in a board are measured, and their average will be the gloss level of the board. fig. 1 the colour meter fig. 2 the gloss meter after the initial color c0 and gloss g0 of each board had been obtained, the 360 boards were put into ultraviolet accelerated test machines for t hours. then the color and gloss of each board were measured again as before, and they were denoted as c1 and g1, respectively. this testing process in the ultraviolet accelerated test machines lasted 5t hours, and every board was taken out the machine for measuring color and gloss every t hours. the exposure conditions of the machine were set to be the cycle 2 of x2.1 given in astm g154-16 provided by astm international. let cj and gj be the color and the gloss of a board at jt hours for j = 1, 2, 3, 4, 5. the color difference for jt hours was calculated as dj = cj-c0, and the gloss retention rate for jt hours was computed as ej = gj/g0. the data set for color difference collected at jt hours was denoted as dj in which every instance was represented as <x1, x2, x3, x4, dj>. similarly, the data set for gloss retention rate collected at jt hours was denoted as ej in which every instance was represented as <x1, x2, x3, x4, ej>. let the paint coating in a board be the formula with 40% type r1 resin and 30% type p2 pigment. the color and gloss measured after one-week natural drying are c0 = 0.1 and g0 = 60, individually. after the board is put into an ultraviolet accelerated test machine for 2t hours, its color and gloss becomes c2 = 0.5 and g2 = 51, separately. the instances for this board advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 41 in data sets d2 and e2 are <r1, 0.4, p2, 0.3, 0.4> and <r1, 0.4, p2, 0.3, 0.85>, respectively. it is possible that the aging-resistant properties of formula may degrade slowly at the beginning while its degrading becomes quick after a fixed time point or vice versa. the 10 data sets can provide this kind of information to satisfy the needs of topcoat paints. 3. model trees and data analysis linear regression is the most popular tool for numeric prediction. it provides a linear model to analyze the relationships between independent variables and a dependent variable. when the instances in a data set are not collected from the same population, the prediction error resulting from single linear regression model is generally large. more powerful tools for numeric prediction are therefore developed to make more accurate predictions [18-21]. the model tree proposed by quinlan [19] has a tree structure and multiple linear regression models for numeric prediction and interpretation, and its prediction error is generally far smaller than that resulting from single linear regression model. this tool has been employed in several recent applications for numeric prediction [22-26]. this section will briefly describe the way for building a model tree from a data set. the evaluation and the interpretation of a model tree will also be introduced. 3.1. model trees it is similar to decision trees, model trees have a tree structure that contains internal nodes for branching and leaf nodes for prediction. every leaf node in a model tree has a linear regression model to predict the class value of any instance reaching this node. the attribute chosen for branching is determined by its standard deviation reduction. the domain of a continuous attribute is divided into ten equal-width intervals by nine splitting points. the expected standard deviation of the class value for every binary branching on each of the nine splitting points is calculated and the one with the smallest expected standard deviation will be the best splitting point for this attribute. the one that has the smallest expected standard deviation on the class value among all attributes is chosen for branching. after the tree is fully grown, a linear regression model is derived for each node based on the instances reaching that node. the regression models in internal nodes will be used for pruning and the regression models in leaf nodes are employed for predicting the class value. a discrete attribute with m possible values is replaced by m-1 synthetic binary attributes. the expected standard deviation of the class value for every binary attribute can be calculated to determine whether this attribute should be chosen for binary branching in an internal node. example 1 given below shows the way to interpret the learning results for discrete attributes. example 1: suppose that a data set has one continuous attribute x1 and one discrete attribute x2 with four possible values a, b, c, and d for predicting class value y. the order of these values is c, d, a, b based on their average class value summarized from the data set; i.e., values c and b have the largest and the smallest average class values, respectively. then the three synthetic binary attributes for replacing x2 are given in table 2. if the attribute value of x2 appears in a binary attribute, the value of this binary attribute equals 1 and equals zero otherwise. for example, an instance <0.4, d> will be replaced by <0.4, 1, 0, 0>. let the linear regression equation in the leaf node reaching by this instance be y = 1.26x1 – 0.35d-a-b + 0.082b. then the predicted class value of this instance is y = 1.260.4 – 0.351 + 0.0820 = 0.154. table 2 the synthetic binary attributes for replacing the discrete attribute x2 in example 1 attribute value d-a-b a-b b a 1 1 0 b 1 1 1 c 0 0 0 d 1 0 0 advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 42 3.2. evaluation and interpretation a small prediction error is the primary concern for numeric prediction. since the color difference and the gloss retention rate have different scales, an evaluation measure should be able to indicate whether a formula of topcoat paint can achieve a small prediction error on both aging-resistance properties. relative absolute error (rae) and root relative squared error (rrse) are therefore adopted for performance evaluation. let yi and yi ’ be the actual and the predicted class value of instance i. then these two measures are calculated as: || || rae ' yy yy ii iii    (1) and 2 2' )( )( rrse yy yy ii iii    (2) where y is the average class value. these two evaluation measures have been normalized, and hence they can be employed to compare the prediction error between the color difference and the gloss retention rate. like decision trees, the branching attributes in a model tree determine the leaf node in which an instance will reach. moreover, the linear regression models in leaf nodes will show critical attributes and their impact level on the dependent variable. there are five model trees for the color difference and similarly for the gloss retention rate. the five model trees for each aging-resistant property will be put together to analyze the critical attributes and their impact levels. those results can be helpful to know which kind of formula will be better for aging resistance. 4. experimental results as described in section 2, the color and gloss of each board were measured for every t hours. the value of t was set to be 250 hours; therefore, the data were collected at 0, 250, 500, 750, 1000, and 1250 hours. the class values in the data sets d1 through d5 and e1 through e5 are collected by this way, and they are divide into two groups for the color difference and the gloss retention ratio. these two groups of data sets will be analyzed by the function m5p with default settings provided by the software weka in the following two subsections for drawing conclusions. only the analysis on the data sets d2 and e2 obtained at 500 hours will be shown in detail because their learning results are simpler for interpretation. then the five data sets in each group will be put together for identifying the critical attributes of topcoat paint in anti-aging. since estimating the lifetime of topcoat paint is not the goal of this study, setting t = 250 hours ensures that enough data can be collected within reasonable time. 4.1. color difference table 3 the characteristics of the five model trees for colour difference data set d1 d2 d3 d4 d5 rae 81.7% 76.2% 75.2% 74.2% 73.9% rrse 86.1% 84.8% 80.8% 80.6% 79.3% branching attributes x1, x2, x3 x1, x2, x3 x1, x2, x3 x1, x2, x3 x1, x2, x3, x4 tree size 8 4 9 8 8 the prediction error and the size of the five model trees for the color difference are summarized in table 3 in which tree size represents the number of leaf nodes. both the relative absolute error and the root relative square error are getting smaller as advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 43 the number of testing hours is increasing. the prediction on color difference is more accurate on the topcoat paint exposing longer. attribute x4 appears only in the tree structure for data set d5. this suggests that pigment proportion is the least important among the four attributes. the model tree and its corresponding linear regression models for data set d2 are shown in fig. 3 and table 4, separately. attribute x4 (pigment proportion) is the only one that is not chosen for branching; consequently, it is less important than the other three attributes in determining the color difference of topcoat paints. according to the four linear regression models, the overall coefficients for resin types r1, r2, and r3 are 0, -0.0670 + 0.0950 = 0.0280, and -0.1665 0.0670 + 0.0184 + 0.0950 + 0.0184 + 0.0310 = -0.0697, respectively. these imply that the best and the worst resin types for reducing color difference are r3 and r2, respectively. since the four coefficients for resin proportion are all negative, higher resin proportion is better for reducing color difference. similar to resin types, the overall coefficients for pigment types p1, p2, and p3 are 0, 0.0314, and 0.4623, respectively. the priority order for pigment types is thus p1, p2, and p3. the three coefficients for pigment proportion are all positive; therefore, the pigment proportion should not be high for maintaining the color of topcoat paint. fig. 3 the model tree grown from data set d2 table 4 the linear regression models for the model tree given in fig. 3 attribute lm1 lm2 lm3 lm4 r2-r3 -0.0670 0.0950 r3 -0.1655 0.0184 0.0184 0.0310 x2 -0.0032 -0.0013 -0.0008 -0.0006 p3-p2 0.0122 0.0064 0.0064 0.0064 p2 0.0116 0.2462 -0.0472 0.2203 x4 0.0004 0.0004 0.0136 constant 0.7149 0.6290 0.5873 0.3376 the above analysis is applied to all of the five model trees for the color difference and the results are summarized in table 5. when the testing time is more than 500 hours, the best and the worst resin types are r1 and r2, respectively. higher resin proportion is definitely beneficial for maintaining the color of topcoat paints. the ranks of pigment types are consistent all the time. table 5 also suggests that the pigment proportion should not be high. according to the experimental results given in table 5, the best formula for the color of topcoat paint is the combination of a high proportion of r1 resin and a low proportion of p1 pigment. table 5 the summarization of the linear regression models for colour difference data set d1 d2 d3 d4 d5 rank of resin types r2, r1, r3 r1, r3, r2 r1, r3, r2 r1, r3, r2 r1, r3, r2 resin proportion negative negative negative negative negative rank of pigment types p1, p3, p2 p1, p3, p2 p1, p3, p2 p1, p3, p2 p1, p3, p2 pigment proportion negative positive positive positive positive advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 44 4.2. gloss retention ratio table 6 shows the prediction errors and the sizes of the five model trees for the gloss retention rate. the testing time in the machines seems to have almost no impact on the prediction error. all five models trees have branching attributes resin type (x1); as a result, it is the most important attribute for gloss. pigment type (x3) and pigment proportion (x4) become more important as exposing time is getting longer. note that the prediction errors for the gloss retention rate are all smaller than those given in table 3 for the color difference. table 6 the characteristics of the five model trees for gloss retention rate data set e1 e2 e3 e4 e5 rae 65.3% 59.5% 68.3% 65.1% 65.4% rrse 68.9% 61.5% 70.9% 67.5% 67.7% branching attributes x1, x2, x3 x1, x2, x4 x1, x2, x3, x4 x1, x3, x4 x1, x2, x3, x4 tree size 8 6 6 5 8 the model tree and its corresponding linear regression models for data set e2 are shown in fig. 4 and table 7, respectively. the only attribute that is not chosen for branching is x3 (pigment type), and hence it is less important than the other three attributes in determining the gloss of topcoat paints. a small color difference is preferred, while better topcoat paint should have a larger gloss retention rate. the coefficients for resin types r1, r2, and r3 calculated from linear regression model lm1 in table 7 are 1.6714+0.7991 = 2.4705, 1.6714, and 0, respectively. as a result, the best and the worst resin types for maintaining gloss are r1 and r3, respectively. the same result can be obtained from the other five linear regression models. the four coefficients for resin proportion are all positive; accordingly, higher resin proportion is better for the gloss retention rate. the coefficients for pigment types p1, p2, and p3 calculated from lm1 are 21.9847-17.9402 = 2.0445, 21.9847, and 0, respectively; consequently, the priority order is p2, p1, p3. although the six linear regression models do not have a consistent rank on pigment types, most of them follow this order. half of the six coefficients for pigment proportion are positive. it is thus inconclusive in determining the impact of pigment proportion on the gloss of topcoat paint. fig. 4 the model tree grown from data set e2 table 7 the linear regression models for the model tree given in fig. 4 attribute lm1 lm2 lm3 lm4 lm5 lm6 r2-r1 1.6714 1.6714 1.6714 0.8849 0.8849 0.8849 r1 0.7991 0.7991 0.7991 1.1751 1.1751 1.1751 x2 0.1615 0.3795 0.2530 0.2476 0.4002 0.2023 p2-p1 21.9847 2.5062 -16.0532 11.8200 -5.8016 6.1060 p1 -17.9402 -7.3138 24.6857 -3.3163 5.7759 -4.3692 x4 -0.1888 -1.0879 -0.9935 0.3213 0.4718 0.0083 constant 58.7103 78.9668 80.5453 59.4366 44.5479 73.7545 advances in technology innovation, vol. 6, no. 1, 2021, pp. 39-46 45 the above analysis is applied to all of the five model trees for the gloss retention rate, and the results are summarized in table 8. the best and the worst resin types are r1 and r3, respectively. similar to the analysis performed for the color difference, higher resin proportion is definitely beneficial for maintaining the gloss of topcoat paint. it seems that p2 is the best among the three pigment types for the gloss retention rate. the proportion of pigment in composing topcoat paint should depend on the types of resin and pigment. based on the results obtained from table 8, the best formula for the gloss of topcoat paint is the combination of high proportion r1 resin and generally low proportion p2 pigment. table 8 the summarization of the linear regression models for gloss retention rate data set e1 e2 e3 e4 e5 rank of resin types r1, r2, r3 r1, r2, r3 r1, r2, r3 r1, r2, r3 r1, r2, r3 resin proportion positive positive positive positive positive rank if pigment types p3, p1, p2 p2, p1, p3 p2, p1, p3 p2, p1, p3 p2, p3, p1 pigment proportion negative inconclusive inconclusive inconclusive negative 5. conclusions in this paper, the aging-resistance properties of topcoat paint measured by its color and gloss are investigated by numeric prediction methods. a formula of topcoat paint is mainly composed of resin and pigment. this study analyzed 180 possible formulas of resin type, resin proportion, pigment type, and pigment proportion to determine their impact on the aging-resistance properties. ultraviolet accelerated test machines were the devices for testing the paint covered in aluminum boards to collect their color differences and gloss retention rates for every 250 hours. the data collected at the same time are gathered in a file to grow a model tree for studying the impact of the four attributes for composing topcoat paint. the experimental results on the five data sets for the color difference consistently indicate that the best formula is the combination of a specific type of resin with a high proportion and a specific type of pigment with a low proportion. the experimental results on the five data sets for the gloss retention rate have the same conclusion on the resin type and resin proportion. however, the best pigment types for color and retention are different and the pigment proportion for gloss generally depends on the other three attributes. the information obtained in this study could be helpful in finding better formulas to satisfy the needs of customers and in choosing vendors who provide resin and pigment. the lifetime of topcoat paint is another key factor in determining its 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[26] z. s. khozani, k. khosravi, b. t. binh, b. klove, w. h. m. w. mohtar, and z. m. yaseen, “determination of compound channel apparent shear stress: application of novel data mining models,” vol. 21, no. 5, pp. 798-811, 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 3___aiti#8538___105-117 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 an integrated approach towards efficient image classification using deep cnn with transfer learning and pca rahul sharma * , amar singh department of computer applications, lovely professional university, jalandhar, india received 22 september 2021; received in revised form 21 october 2021; accepted 22 october 2021 doi: https://doi.org/10.46604/aiti.2022.8538 abstract in image processing, developing efficient, automated, and accurate techniques to classify images with varying intensity level, resolution, aspect ratio, orientation, contrast, sharpness, etc. is a challenging task. this study presents an integrated approach for image classification by employing transfer learning for feature selection and using principal component analysis (pca) for feature reduction. the pca algorithm is employed for reducing the dimensionality of the features extracted by the vgg16 model to obtain a handful of features for speeding up image reorganization. for multilayer perceptron classifiers, support vector machine (svm) and random forest (rf) algorithms are used. the performance of the proposed approach is compared with other classifiers. the experimental results establish the supremacy of the vgg16-pca-multilayer perceptron model integrated approach and achieve a reorganization accuracy of 91.145%, 95.0%, 92.33%, and 98.59% on fashion-mnist dataset, orl dataset of faces, corn leaf disease dataset, and rice leaf disease datasets, respectively. keywords: dimensionality reduction, feature extraction, image recognition, pca, transfer learning 1. introduction manual image recognition by experts suffers from different limitations, e.g., time-consuming, human error, biased opinion, non-availability of experts, etc. nowadays, automated image recognition technology appears in many aspects of day-to-day tasks and plays a very important role in education, face recognition, medical disease diagnosis, agricultural activities, driverless cars, advertising, image restoration, etc. automated solutions are very useful for amateurs as well as field experts. with the advances in technology, the widespread use of image capturing and processing devices enabled people to capture, share, search, and retrieve images. image recognition helps identify and analyze the objects and use the learned knowledge for decision making. the objective of image recognition is to label a given image into class among a set of pre-defined classes. to accurately label an image, the extraction of useful image features is very important. features represent the patterns of the object in the image and are used for recognition. there are different methods for feature extraction from images such as grayscale feature extraction, the use of mean pixel values of channels, and edge feature extraction. the grayscale feature extraction uses a single channel as an input, and the number of features will be the same as the number of pixels. mean pixel values of channels generate a matrix using the pixel values from three channels. thus, the number of features remains the same and the pixel values of all three channels are considered. the edge features extraction method extracts edges as features and uses that as the input for the model. edges can be extracted by using different algorithms, e.g., prewitt edge detection, sobel edge detection, * corresponding author. e-mail address: prof.sharma.rahul@gmail.com tel.: +91-7006957906; fax: +91-1922-234315 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 laplacian edge detection, canny edge detection, etc. low-level features of an image can also be extracted by using different techniques, e.g., histogram of oriented gradients (hog), generalized search tree (gist), scale-invariant feature transform (sift), speeded up robust feature (surf), etc [1]. training image classification algorithms by using these hand-crafted features is time-consuming and requires technical expertise. the pretrained convolution neural network (cnn) models are trained using large, distributed, and standard datasets. the weights learned by the pretrained model can be reused to solve a similar problem. transfer learning employing the pretrained cnn enables filters to extract valuable characteristics from images [2]. the cnn model has different layers such as the convolutional layer, pooling layer, dropout layers, non-linear layers, and fully connected layers. the feature maps of these layers can be viewed and give a distinct representation of the input image. the vgg16 architecture is employed to extract important features of images [3]. to improve the space and time complexity, principle component analysis (pca) is applied as feature reduction technique. deep learning techniques are successfully applied for solving the problems related to healthcare, agriculture, engineering, entertainment, music composition, advertising, signal processing, image recognition, robotics, image coloring, image captioning, etc. the application of machine learning techniques for solving real-time applications efficiently and accurately is gaining importance. real-time applications often require handling huge data. extracting significant features and reducing noise are required for improving computational speed and accuracy. some of the current work in this field includes handling multi-sensor data for chatter detection using metaheuristic algorithms and recursive feature elimination [4], feature selection using fuzzy entropy measures with a similarity classifier [5], effective feature selection using enhanced pca [6], artificial bee colony for feature selection of breast cancer data [7], etc. recent studies have integrated deep learning with the internet of things (iot) for performing real-time complex sensing and recognition tasks. iot applications generate a huge volume of data that requires preprocessing and dimensionality reduction. some of the tasks involving iot and deep learning include reducing the energy consumption of iot enabled devices [8], online automated monitoring of cyber-attacks [9], automatic online detection of defects in gas-insulated switchgear [10], anomaly prediction in iot networks [11], real-time monitoring of agriculture fields [12], etc. the main objective of this study is to propose an efficient and accurate approach for image recognition based on the integrated approach. some of the challenges faced by deep learning image classifiers are computationally expensive, energy-intensive, and time-consuming, and have high memory requirements. thus, there is a need for scaling up the performance of image classifiers and overcoming the bottlenecks faced during model training and image classification. the proposed approach reduces the computational complexity and maintains high classification accuracy. the contribution of the work is summarized in the following points. (1) an integrated approach is proposed employing deep learning for feature extraction, pca for feature reduction, and image classification module with multilayer perceptron, support vector machine (svm), and random forest (rf). (2) the accuracy of multilayer perceptron, svm, and rf classifiers is enhanced by tuning their hyperparameters using a grid search algorithm. (3) with the pca reduced features, efficient utilization of computation resources is conducted with the improved computational efficiency of model training and testing. this study is organized as follow. section 2 presents literature review. section 3 introduces transfer learning, the pca algorithm, and the proposed image classification approach. section 4 presents the results and discussion. finally, section 5 presents the conclusion. 106 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 2. related work several techniques were proposed for image classification. kaur et al. [13] explored various pretrained cnn models for the classification of magnetic resonance brain images. their proposed pretrained deep cnn models were demonstrated. the authors explored 8 different pretrained cnn models out of which the alexnet model illustrated best classification accuracy. pires de lima et al. [14] presented remote-sensing image classification using transfer learning. their cnn models trained on diverse natural image datasets gave better results for remote-sensing image classification tasks. the study demonstrates that the pretrained model trained on a generalized dataset can be accurately applied to remote-sensing image classification. the results show that the pretrained models can easily be used for feature extraction of the unseen images related to different domains. xue et al. [15] presented an ensemble learning strategy based on inception-v3, xception, vgg16, and resnet-50 cnn models. the ensemble learning technique employed a weighted voting approach with an accuracy of 98.61%. the high computational requirements of the classifier which used four pretrained models as base learners are one of the limitations of their proposed approach. garcia-dominguez et al. [16] proposed an automatic optimum image feature selector and classification open-source tool “frimcla” [16]. the tool based upon the statistical study automatically selects the feature extraction and classification techniques. for feature selection, the pretrained models as well as traditional methods are explored. transfer learning techniques are popularly used for feature selection in computer vision. sert and boyacı [17] presented a feature fusion transfer learning-based approach for the recognition of sketch drawings. for improving the efficiency of feature reduction, pca was proposed. the selected features were input to svm for classification. the proposed approach was able to classify freehand sketches of the sketchy dataset with an accuracy of 97.91%. chen et al. [18] proposed an automated robot arm control program enabling human-robot interaction using the yolov4 algorithm. eight different hand gestures were recorded in a controlled laboratory environment and image features were classified by employing a deep cnn. the proposed approach classified the images accurately and the recognized hand gestures were used to control robot arm movement. khan et al. [19] presented an improved saliency-based segmentation technique for the extraction of the infected area of cucumber leaves. the deep neural networks vgg-vd-19 and vgg-s, m, f were employed for the extraction of useful features. subsequently, the features obtained were fused and were used for image classification by svm with an accuracy of 98.08%. kaur et al. [20] employed the pretrained model alexnet to identify the patients with parkinson disease. the final layers of the model were modified and the transfer learning-based model was able to diagnose the disease with an accuracy of 89.23%. li et al. [21] presented a shallow vgg16 neural network-based approach for plant disease detection. the block of the vgg16 pretrained model was used for the extraction of prominent image features. the pca reduced features were input to svm or rf algorithms. experimental results illustrate that the simple shallow neural network and statistical machine learning algorithms are very useful for plant disease detection. sujatha et al. [22] presented the analysis of different machine learning and pretrained deep learning algorithms for the classification of diagnosis of citrus plant diseases. the experimental work shows that deep learning algorithms performed better than machine learning algorithms for disease classification. the vgg16 model outperformed other classifiers (vgg19, inception-v3, rf, stochastic gradient descent, and svm). behera et al. [23] presented papaya maturity stage prediction models using k-nearest neighbor (knn), svm, naïve bayes, and deep learning neural networks (alexnet, vgg16, vgg19, googlenet, resnet50, etc). both the vgg16 and vgg19 models were able to classify papaya images with an accuracy of 100%. the vgg19 model achieved 100% training accuracy in 10 epochs. chiu et al. [24] proposed an efficient method for predicting breast cancer on the dataset obtained from university hospital care of coimbra. for reducing the dimensionality of the dataset, the pca algorithm was used. the features were extracted by using a transfer learning neural network and 107 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 classification by svm. loey et al. [25] presented a hybrid approach employing the pretrained cnn model resnet50 for feature extraction of the images of real-world masked face dataset (rmfd), simulated masked face dataset (smfd), and labelled faces in the wild (lfw) dataset. the extracted features were classified by svm decision tree and ensemble learning techniques. using the proposed approach, the svm model classified rmfd with 99.64%, smfd with 99.49%, and lwf with 100% accuracy. bhagwat et al. [26] presented a review of traditional machine learning and deep learning techniques for early and accurate detection of plant diseases. early detection of plant diseases is a challenging task that needs to be addressed for precision agriculture. deep learning architectures illustrate their significance for important feature extraction and classification. deep neural networks require large datasets for training. collecting a large dataset is very time-consuming and expensive. transfer learning using pretrained models (e.g., single-shot multibox detector, vggnet, resnet50, inceptionv2, googlenet, mobilenet, etc.) is very useful to overcome these limitations and recognize the plant diseases with high accuracy. training a deep learning model with large data of diverse examples is highly desirable to avoid over-fitting. generally, the aim is to develop a model which generalizes well on the unseen test data by minimizing both the bias and variance. to solve a complex problem, the model needs to learn more parameters so that the data size for training increases. transfer learning is commonly employed to solve computer vision problems with a small dataset, and the acquisition of more data is time-consuming or expensive. ren et al. [27] demonstrated accurate image classification employing transfer learning algorithms on small or poor image datasets. the minimum data size requirements for the training transfer learning model were explored. the proposed model was able to be trained using small, poor-resolution, unfavorably cropped, or rotated images. transfer learning algorithm was able to achieve above 75% accuracy with different data sizes. weimann et al. [28] presented a transfer learning-based approach for the classification of atrial fibrillation. the cnn model was first trained on a large public dataset and then the weights learned were fine-tuned on a small dataset of atrial fibrillation. the proposed approach employing transfer learning improved the performance of the cnn model by 6.57%. liu et al. [29] presented an automatic manufacturing defect detection system with limited training samples employing transfer learning. the proposed model was able to extract the discriminative features and was able to detect defects with an accuracy of 99% improving the model accuracy by 11%. li et al. [30] proposed an approach demonstrating the usefulness of transfer learning to train deep learning models on small training data for the diagnosis of covid-19. the transfer learning using the chexnet model already trained for the classification of chest x-ray images was employed. the already learned knowledge was fine-tuned on the limited covid-19 dataset. the proposed approach outperformed several other methods. the first few layers of a deep cnn model extract generic features, and the final layers extract the specific features of an image. yosinski et al. [31] discussed the applicability of transferring features from the base task to the target task. the generalization performance of the model is enhanced by transferring features from the base layers. the performance is enhanced when the base task and target task are similar. using the pre-learned weights for the neural network is better than initializing the weights randomly. mahajan et al. [32] discussed an efficient plant species recognition model which used transfer learning for feature extraction and enhanced multiclass adaptive boosting for image classification. the open-source plant species dataset flavia was used in the study. using 10-fold cross-validation, an accuracy of 95.85% was achieved. singh et al. [33] applied a novel nature-inspired multi-population parallel three-parent genetic algorithm (p3pga) for the optimization of routing problems in wireless mesh networks. the p3pga benchmarked tests on cec-2014 tests and their application for finding minimum cost routes illustrate faster convergence time compared to other popular nature-inspired algorithms. the optimization techniques enhance the performance of image classification algorithms. table 1 presents some of the recent studies on feature extraction, feature reduction, and classification. 108 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 table 1 description, technique, and limitation of recent studies ref. description technique limitation [34] real-time accurate and efficient monitoring of water quality of water resources for decision making long short-term memory recurrent neural networks (lstm rnns), pca, linear discriminate analysis (lda), and independent component analysis (ica) for feature reduction classification performance is not tested using deep learning classifiers. [35] non-linear ensemble learning for improving feature extraction and forecasting the carbon price deep learning, lstm, rf, rnn, and bagging algorithm the proposed ensemble learning approach needs to select optimal models rather than random selection. [36] covid-19 prediction by inspecting x-ray images transfer learning feature extraction resnet18, resnet50, resnet101, vgg16, vgg19, and svm for classification with an accuracy of 94.7% the severity of the disease is not detected. [37] detection of alzheimer disease by classification of functional mri images knn, svm, decision tree, lda, rf, and cnn limited dataset is used. [38] detection of external defects in the tomatoes resnet18, resnet34, resnet50, resnet101, resnet152, grid search with a high accuracy of 94.6% deep autoencoders and one-class classifiers used for improving accuracy need to be explored. the classifiers need to be generalized. [39] selection of optimum features for medical image classification gray level co-occurrence matrices (glcm), grey-level run length matrix (glrlm), crow search optimization algorithm for feature selection, and deep learning further segmentation and feature reduction are needed. [40] detection of pain intensity by analyzing facial expressions vgg-face for feature extraction, pca for improving computational efficiency, and lstm for classification a limited number of images and non-availability of a standard dataset [41] transfer learning for image classification of caltech 101 dataset vgg19, sift, surf, oriented fast and rotated brief (orb), shi-tomasi corner detector algorithm for feature extraction, gaussian naïve bayes, decision tree, rf, and xgbclassifer for classification multiple feature extraction techniques are required for improving accuracy and required more computational resources. the vgg16 architecture proposed by simonyan et al. [42] secured the first place in the object localization track of the imagenet challenge and was able to detect an object within an input image with high accuracy. in the image classification track of the imagenet challenge, the vgg16 neural network achieved 92.7% top-5 test accuracy for classifying over 14 million images belonging to 1000 different classes. the vgg16 model was tested with voc-2007, voc-2012, caltech-101, and caltech-256 benchmarked datasets. the experimental results illustrate that the vgg16 network can generalize well to the unseen data. 3. materials and methods 3.1. transfer learning using deep convolutional neural networks the already trained models are very useful to overcome the limited training dataset challenge by reusing the knowledge already learned from large training samples. the transfer learning using cnn models reuses the knowledge learned by the neural network trained on a large dataset and applies the knowledge for solving another problem. vgg16, vgg19, resnet50, resnet101, inceptionv3, densenet121, xception, etc are some of the popular neural network architectures which have demonstrated excellent image classification performance. in this study, the vgg16 model as shown in fig. 1 is used for the extraction of useful image features. fig. 1 vgg16 network architecture as a feature extractor 109 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 the vgg16 model architecture has 13 convolution layers of 3 × 3 filters stacked together along with 5 max-pooling layers of the size 2 × 2. after the last max-pooling layer, there are three dense layers. vgg16 uses the relu activation function and softmax layer in the final dense layer. the imagenet pretrained model vgg16 has fewer tunable hyperparameters and achieves high classification accuracy. the low-level features already learned by a pretrained model are used for learning another problem. the extracted features are input to pca to select the most relevant features, enhance the performance, and reduce the training time. 3.2. the pca algorithm pca was introduced by karl pearson [43]. pca is also known as hotelling transform (ht) and is a very popular dimensionality reduction technique used effectively in the areas of image and signal processing. pca is used for reducing the size of the feature vectors that are used for object recognition and object classification. pca can be implemented using eigenvalues decomposition (evd) or singular value decomposition (svd). pca transforms the feature vectors with a large number of correlated variables into a smaller number of uncorrelated variables also known as principal components (pcs). consider a dataset having k images with n = n × n pixels, the dataset is represented by d = n × k matrix where di represents the ith row of the matrix or ith image of the dataset. algorithm 1 gives the pca algorithm. algorithm 1: pca step 1: for i = 1 to n, calculate the mean of di using eq. (1): 1== ∑ i k ij j d k µ (1) step 2: shift the origin to the mean of the data by subtracting the mean �� from each column vector ��� as shown in eq. (2): φ = −ij ij id µ (2) step 3: compute the covariance matrix of mean-centered data using eq. (3): = φφt c (3) where t represents the transposition matrix. step 4: find eigenvalues ��, ��, ��, …, � and eigenvectors ��, ��, ��, …, � of c where �� > �� > �� > … � . step 5: arrange the eigenvectors in descending order and return top k eigenvalues corresponding to k number of the largest eigenvalues also known as pcs. the pca algorithm is a popular dimensionality reduction technique which transforms a large set of correlated variables into fewer uncorrelated variables. pca computes uncorrelated variables by transforming the data to a new coordinate system maintaining as much variance as possible. pca is employed for reducing a large number of image features into the reduced one-dimensional feature set representation (i.e., pcs) as shown in fig. 2. pca flat image 1d vector of length 1 × n (spatial domain) 1d vector of length 1 × k (where k < n) (pca space) fig. 2 pca feature reduction 110 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 for a given set of data, pca finds a new axis system defined by the principal directions of variance. suppose the dataset has 400 images of the size 256 × 256, then the size of the data matrix will be 400 × (256 × 256) = 400 × 65536. therefore, for each of the 400 images, the data matrix will have 65536 columns. the size of the covariant matrix and transformation matrix becomes 65536 × 65536. now, using pca, 50 columns of the transformation matrix corresponding to the 50 largest eigenvalues are selected. then, the size of the reduced transformation matrix p is computed as 65536 × 50. the next step is to obtain the transformed dataset t using eq. (4). × ×= φ s n n k t p (4) the size of the transformed dataset is 400 × 50. thus, the initial data matrix of the size 400 × 65536 is reduced to the new representation, i.e., the transformed matrix t of the size 400 × 50. 3.3. the proposed approach in this section, the proposed approach for image classification is described in details. deep neural networks extract useful feature maps for the recognition of images. recent studies in computer vision have successfully used cnn for feature representation. building and training an efficient cnn from scratch requires technical and domain expertise. designing an optimized cnn architecture for a real-world computer vision task is a complicated and time-consuming task. in this study, the vgg16 architecture is employed for feature extraction. the weights of the convolution base layers of the vgg16 model are reused and are not updated. the vgg16 neural network processes the input image to extract activation maps that describe features in an image [44]. the features are extracted from the block5_pool layer of the vgg16 architecture. the features of the images extracted from the vgg16 model are converted into a vector of 32768 numbers. the pca feature reduction technique is employed to reduce the dimensionality of vgg16 features and at the same time maintain the distinctive properties of the features thereby improving the training/prediction time. the reduced features are fed to the multilayer perceptron model or svm model. the hyperparameters of these image classifiers are optimized using a grid-search algorithm [45]. fig. 3 shows the proposed image recognition approach. fig. 3 the proposed image recognition approach (fashion-mnist dataset) 3.4. datasets the proposed image classification approach is validated on four different image datasets, namely, orl dataset of faces, fashion-mnist dataset, corn leaf disease dataset, and rice leaf disease dataset. the training and testing datasets are randomly divided in the ratio of 80:20. some of the sample images of the dataset are shown in fig. 4. 111 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 s1/2 s2/3 s3/8 s7/10 s6/5 s8/7 s10/4 s15/7 (a) orl dataset of faces dress coat pullover bag pullover coat ankle boot shirt (b) fashion-mnist dataset blight common rust gray spot health (c) corn leaf diseases dataset bacterail blight blast brown spot tungro (d) rice leaf disease dataset fig. 4 sample images of datasets table 2 dataset images used for the evaluation of the proposed approach image dataset training images testing images total images orl 160 40 200 corn leaf disease 3350 838 4188 rice leaf disease 4105 1027 5132 fashion-mnist 60000 10000 70000 table 2 shows the number of training and testing images of different datasets used for the evaluation of the proposed approach. in this study, 10 different images of each of 20 distinct subjects from the orl dataset are used. the orl database includes grayscale face images of 92 × 112 pixels collected in varying lighting conditions with similar backgrounds. the dataset captures different facial expressions of persons organized in a directory for each subject with names in the format s1, s2, s3, etc. fashion-mnist is a standard dataset having 60000 grayscale images of 28 × 28 pixels corresponding to 10 different types of clothing. fashion-mnist dataset is popularly used for benchmarking computer vision and deep learning algorithms. 4. results and discussion as discussed in section 4, the images are fed to the vgg16 models for feature extraction. the extracted features represent useful information required for image classification. the features are classified using multilayer perceptron, svm, and rf image classifiers. the hyperparameters of these classifiers are optimized by using a grid search algorithm. the multilayer perceptron model is trained for 50 epochs. the svm algorithm used in the study is evaluated by fitting 5 folds for each of the 50 candidates totaling 250 fits. the hyperparameters optimized by the grid search algorithm for svm are c = 1, gamma = 0.01 and kernel = 'rbf' when the orl images are classified using vgg16 features. the accuracy and time of image classification are recorded and are shown in table 3. 112 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 dimensionality reduction is required for improving the performance of the model. linear discriminate analysis (lda), as well as pca, can be used for feature reduction. lda uses class information to obtain new features whereas pca evaluates pcs by making use of variance matrix, covariance matrix, eigenvector, and eigenvalues of each feature. pca is used to speed up the computation and improve the performance of the image classifier. figs. 5-6 give the pca reduced features representation of corn leaf disease dataset and fashion-mnist dataset respectively. the evaluated pcs are input to multilayer perceptron, svm, and rf classifiers. tables 4-6 show the classification time and the accuracy of the multilayer perceptron, svm, and rf classifiers respectively. with 100 pcs, the multilayer perceptron gives the best accuracy and outperforms the svm and rf classifiers. the image classification performance recorded in table 3 and table 4 demonstrate that the proposed approach reduces the computational complexity of the image classifiers. for example, for the classification of rice leaf disease test images, vgg16 and multilayer perceptron give an accuracy of 97.27% whereas using the proposed approach with 100 pcs the classification accuracy of 98.93% is achieved. in addition, the improvement in classification time by 107.17 seconds is also observed. table 3 image classification without pca dataset artificial neural network (ann) support vector machine (svm) random forest (rf) accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) orl 95.0 6.45 92.5 0.82 92.5 120.45 corn leaf disease 89.14 142.8 88.78 55 86.51 123.56 rice leaf disease 93.81 140.4 98.54 61.2 97.27 121.4 fashion-mnist 91.56 174.26 90.1 110.3 87.78 153.41 (a) pc = 2 (b) pc = 3 fig. 5 corn leaf disease dataset (a) pc = 2 (b) pc = 3 fig. 6 fashion-mnist dataset 113 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 table 4 accuracy/time of multilayer perceptron classifier (20 epochs) using pca features dataset pc = 10 pc =20 pc =50 pc =100 accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) orl 87.5 1.74 90.0 1.81 92.2 1.83 95.24 1.898 corn leaf disease 83.05 10.05 85.08 10.84 86.99 10.91 92.36 10.95 rice leaf disease 93.86 10 95.33 10.82 97.27 11.018 98.93 14.23 fashion-mnist 75.11 15.35 81.45 17.75 84.15 18.45 92.93 19.68 table 5 accuracy/time of svm classifier using pca algorithm dataset pc = 10 pc = 20 pc = 50 pc = 100 accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) orl 82.50 1.83 85.5 2.02 90.01 3.30 92.2 4.5 corn leaf disease 81.503 1.89 83.89 2.47 87.11 3.8 89.14 5.15 rice leaf disease 72.15 5.56 80.62 6.73 85.78 8.84 92.11 11.88 fashion-mnist 71.54 11.56 76.15 12.67 83.57 15.86 89.15 18.65 table 6 accuracy/time of rf classifier using pca algorithm dataset pc = 10 pc = 20 pc = 50 pc = 100 accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) accuracy (%) time (sec) orl 77.50 1.14 92.5 1.9 87.5 2.7 90.05 3.45 corn leaf disease 78.64 1.47 85.91 1.93 86.04 2.41 88.07 4.52 rice leaf disease 75.17 3.25 78.57 4.84 83.74 5.42 88.12 9.19 fashion-mnist 73.21 10.67 75.95 9.41 81.21 13.47 84.37 15.62 (a) orl dataset of faces (b) corn leaf disease dataset (c) rice leaf disease dataset (d) fashion-mnist dataset fig. 7 confusion matrix of different datasets 114 advances in technology innovation, vol. 7, no. 2, 2022, pp. 105-117 fig. 7 shows the confusion matrix of the datasets which can be used for evaluating the performance of the proposed approach. a confusion matrix is very useful for evaluating performance measures like accuracy, precision, sensitivity, specificity, negative predictive value, etc. learning redundant and less relevant information does not give generalized results. training models with higher dimension data can suffer from overfitting. the experimental result illustrates that the proposed approach improves the performance of classifiers. 5. conclusions efficiently classifying images and avoiding overfitting is a challenging task. in this study, an efficient approach employing the vgg16 model for feature extraction and pca for feature reduction was presented. the extracted features were classified without applying feature reduction techniques and the results were recorded. the performance of the model was improved by integrating the pca feature reduction algorithm. the features extracted by the vgg16 model were fed to pca, and the optimum number of pcs for achieving the best accuracy was evaluated. for the classification of images, the features extracted by the vgg16 model were classified using multilayer perceptron, svm, and rf algorithms. the proposed approach employing transfer learning was validated using four benchmarked image datasets, considering performance metrics. the proposed approach accurately classified the images with improved computational efficiency compared to other methods with the same hardware resources. the models trained using pca-reduced features demonstrated significant improvement in running speed. the scope of the proposed framework can further be expanded by optimizing the pcs by using nature-inspired search and optimization algorithms. furthermore, the feature extracted by transfer learning-based neural networks can be fused or an ensemble model can be explored to enhance the accuracy of the classifier. moreover, fuzzy rough sets, ranking-based models, and regularized regression models will be researched for feature selection enhancing the performance of image classifiers. conflicts of interest the authors declare no conflict of 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[45] l. yao, z. fang, y. xiao, j. hou, and z. fu, “an intelligent fault diagnosis method for lithium battery systems based on grid search support vector machine,” energy, vol. 214, 118866, january 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 117  advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 development of a cost-effective design of a p-v ventilated greenhouse solar dryer for commercial preservation of tomatoes in a rural setting ebangu orari benedict 1,2,* , dintwa edward 1 , motsamai seraga oboetswe 1 1 department of mechanical engineering, university of botswana, gaborone, botswana 2 department of biosystems engineering gulu university, gulu, uganda received 28 march 2019; received in revised form 16 may 2019; accepted 09 july 2019 abstract commercial preservation of agro-produce by solar drying entails using large-scale dryer units that are generally not affordable by potential users in a rural setting. the objective of this study was to design a photo-voltaic greenhouse solar drying unit with air convection powered by a photovoltaic system as part of a research study to develop a cost-effective commercial solar dryer for the preservation of tomatoes in a rural setting. the design methodology involved. first, the determination of thermophysical properties of local tomatoes and predicting its drying model. second, determination of design parameters; design equations, design conditions and assumptions, and psychrometric analysis. third, application of the design parameters under the climatic conditions of botswana to produce the embodiment of design with the drawings and specifications for a solar hot air dryer unit of 2000 kg batch-load of wet tomatoes. this drying unit is integrated into a solar collector with a cost-friendly thermal energy storage system to store solar energy during the day for use after sunset for better performance. keywords: commercial preservation, thermo-physical properties, embodiment of design, thermal energy storage system 1. introduction the discussion on applicable methods to alleviate the high global postharvest losses, 30-50 %, that negatively impact on the agro-produce value chain is on-going [1]. recent research work has focused on using renewable energy technologies for drying of agro-produce as the preservation method to reduce postharvest losses [2-3]. solar dryers have therefore increasingly become popular especially on account of their relative costs of investment and operation [4-7]. however solar dryers are scarce in botswana despite the endowment with abundant sunshine [8]. this study aims at developing a suitable solar dryer for use in botswana to preserve fruits and vegetables, particularly tomatoes. drying of tomatoes for commercial purpose in a rural set up requires the use of tunnel or greenhouse types of solar dryers. in this paper, the design of a forced convection solar dryer ventilated by fans operated by a photo-voltaic system is presented. various designs of solar dryers for the preservation of fruits and vegetables have been reported in the literature [9]. experiments were carried out on solar drying of pineapple using a solar tunnel dryer, the version of the original hohenheim type solar dryer in bangladesh [10]. this dryer had a transparent polyethylene covered flat plate collector and a drying tunnel. hot air was supplied to the drying tunnel using fans operated by a solar module. however, the tunnel dryer design had limited batch capacity for large scale commercial drying of products. design innovations have been made aimed at increasing the capacity and efficiency of solar dryers. a solar dryer with reverse flat-plate collector absorber to receive concentrated solar irradiation at a higher temperature to increase the efficiency of the dryer was developed [11]. the geometrical construction and manual tracking of the sun rays were the major challenges * corresponding author. e-mail address: benebangu@yahoo.com tel.: +267-76675111 advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 223 of this technology. a solar dryer comprising a flat plate collector that used mirror reflectors to enhance the capture of solar irradiance at the solar heater unit of a mixed-mode greenhouse dryer was designed and constructed [12]. the dryer was tested by successful drying of bananas and tomatoes. however, to track the sunshine, the mirrors needed to be continuously adjusted during the day and this presents a labor intensive activity. a large scale polycarbonate covered greenhouse / tunnel type solar dryer using forced convection air flow was developed [13]. it was tested for performance and it did demonstrate the potential for drying chilli, coffee and banana. this dryer design had the potential to be developed to dry, at large scale, tomatoes and other horticultural products if auxiliary energy source was incorporated into the dryer system to enable drying without interruption. janjai [14], developed and tested at field level a large-scale solar green-house dryer with a loading capacity of 1000 kg of fruits or vegetables. this greenhouse dryer had a parabolic shape and was covered with polycarbonate sheets. the dryer was backed up by the use of lpg gas energy source and its ventilation fans were powered by photo-voltaic, p-v, module. it was used to dry bananas, coffee, chilli, tomatoes, and other fruits and vegetables. the solar greenhouse dryer was easy to construct and was suitable for commercial-scale applications because of the fast drying rate. however, a cheaper source of auxiliary energy than lpg gas could reduce the operational cost of the dryer. from the reviews of the greenhouse solar dryer technologies, sdts, summarized in table 1, great effort has been put to develop greenhouse solar dryers for fruits and vegetables but few designs have been developed and tested for commercial drying of tomatoes in a rural setting where affordability of the technology is a matter of great concern. table 1 summary of material properties year year highlights 2016 hii, et al. [15] development and recent trends in greenhouse sdts 2016 hawlader, et al. [16] solar tunnel greenhouse type of sdt 2017 sengar and kothari [17] thermal modeling and performance evaluation of arch shape greenhouse for nursery raising 2017 atalay, et al. [18] modeling of the drying process of apple slices: application with a solar dryer and the thermal energy storage system. 2019 badaoui et al. [19] experimental and modelling study of tomato pomace waste drying in a new solar greenhouse: evaluation of new drying models 2019 román‐roldán, et al. [20] computational fluid dynamics analysis of heat transfer in a greenhouse solar dryer “chapel‐ type” coupled to an air solar heating system thermo-physical properties of the material to be dried define the boundary conditions for the drying process. density, specific heat capacity, heat conductivity, thermal diffusivity, moisture content are the properties of tomatoes were assessed from the literature and also determined by laboratory experiments. the experiments were necessary because although the tomato varieties prevalent in botswana are of mexico native origin, solanum lycopersicum, their properties could vary due to climatic and ecological conditions the six common varieties grown in botswana are money maker, expresso, heinz 1379, zeal, zest, and six pack. the farmers in botswana have ranked the zeal variety as the best variety [21]. 2. design methodology the design methodology considers the conceptual design of a phot-voltaic air fan ventilated dome-shaped design of a greenhouse solar dryer for large scale drying of tomatoes. hence the thermo-physical properties are determined in the first step. the design equations and design calculations are discussed in the second step and the embodiment of design is handled in the final step. the flow diagram of the design process is depicted in fig. 1. 2.1. determination of thermophysical properties of tomatoes the experimental setup for determination of moisture content was in respect of an oven drying method used to determine the moisture content of sliced tomatoes. the oven dryer apparatus (carbolite-gero gmbh co., kg 30-3000 °c) was used to dry the tomato samples. it was set to operate at a temperature of 105°c, and the air in the oven was set to ventilate at 1.1 m/s. a calibrated electronic balance type: snowrex lv-6b was used for measurement of weight. advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 224 fig. 1 flowchart of the design methodology 2.2. experimental procedure tomato samples of the zeal variety that is most prevalent in botswana were procured from gaborone supermarkets and used as the material for determining the moisture content of the tomato for drying. the tomatoes were first washed with running water. no chemical pre-treatment of the samples was done. a vegetable cutting knife was used to cut the tomato samples to halfslices of about 25 mm diameter. these slices were weighed and placed inside the oven dryer. the oven-method procedure of the hot air oven method according to acac 1990 for determination of moisture content of sliced tomato was followed. the initial weight of each tomato-slice sample with its containment was recorded after determining the weight of the empty container. then the instant weights of each sample were recorded on an hourly basis while drying in the oven. the decreasing masses of the sample slices were monitored to a final stable weight by means of a calibrated digital balance. the end of drying was reckoned by uniform constant weight readings. weight loss was determined at 60-minute intervals during drying. visual inspection of color and texture was relied upon to confirm the dried status of the tomato slices [22]. 2.3. the design equations moisture content was calculated as the ratio of weight loss during the drying period with the weight of the wet or the dry weight of the sample. the value of moisture content usually expressed in percentage, %, or in decimal values, was thus presented either on a wet basis, wb , or dry basis, db . the value of moisture content usually expressed in percentage, %, or in decimal values, was thus presented either on a wet basis, wb or dry basis, db . the moisture content, wet-basis, and moisture content dry-basis were evaluated [23] by o d wb o w w m w   (1) o d db d w w m w   (2) where ow is the weight of the wet material and dw is the weight of the dry material. the relationship between wbm and dbm can be given by two expressions of moisture content of agricultural materials as follows 1 wb db wb m m m   (3) advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 225 1 db wb db m m m   (4) the moisture content at time t during drying, tm , is evaluated by [22]. ( 1) 1t t i o w m m w          (5) where im is the initial moisture content, db , tw is the instant weight of the sample, ow is the initial weight of the sample. the moisture ratio rm is a function of time that rationally defines the moisture content of the drying process. since fm is relatively negligible in comparison to im and tm . rm is approximately given as the ratio given by [23]. t f t r i f i m m m m m m m     (6) the mass of the moisture to be removed from the food product is calculated by berichte [24] ( ) 100 p i f w f m m m m m    (7) where, pm , is the initial mass of the product to be dried, wm is the mass of water to be removed from the wet material, im is the initial moisture content, % dry basis, fm is the equilibrium or final moisture content, % dry basis. latent heat of vaporization was calculated by [25]. 34.186 10 (597 0.57 )prl tv    (8) where vl is the latent heat of vaporization of water and prt is the drying temperature in °c of the material to be dried. the quantity of heat energy required for drying a given quantity of food materials can be approximated using the basic energy balance equation for the evaporation of water was given norton and sun by [26] 1 2( )wq m l m c t tv a pa   (9) where vl =latent heat of vaporization of water in kj/kg, wm is the mass of water evaporated from the food item, am is the mass of drying air, 1 2( )t t is the difference between initial and final temperatures of the drying air respectively, in kelvin, pac is the specific heat capacity of drying air at constant pressure kj/kg k. the enthalpy h of air was approximated [27] by 1006.9 (2512131.0 1552.4 )h t w t   (10) where t is the temperature of drying air, °c, and w is the humidity ratio of water vapor, in one kg of dry air. the amount of water in food and agricultural materials affects the quality and perishability of the material. the indicator for perishability of the material is wa the water activity. it is the level of availability of moisture to support degradation like microbial action. the water activity is evaluated as [28] advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 226 w o p a p  (11) where p is the partial pressure of water above the material surface and, op is the partial pressure of pure water under the same conditions as the food. the water activity can also be evaluated using the empirical formula [29] by 1 exp[ exp(0.914 0.5639ln )] 100 rh db e w m     (12) where dbm is the moisture content dry basis in kg water vapor/kg pure water and, rhe is the relative humidity of the air surrounding the food at which the material neither gains nor loses its natural moisture and is in equilibrium with the environment. the average drying rate rd for drying the food was evaluated by [26] w r d m d t  (13) where wm is the mass of moisture removed from the food and dt is the drying time in hours. the mass flow rate, am of the air needed for drying, is given by [26] ( ) r a f i d m w w   (14) where rd is the average drying rate, iw is the initial humidity ratio, kg h2o/kg dry air, fw is the final humidity ratio, kg h2o/kg dry air. the volumetric airflow rate av in m3/hr is evaluated by a a a v m   (15) the total useful thermal energy of the drying air, e in joules, required to evaporate the water is given [30] by = ( )a f i de m h h t (16) where the air mass flow rate is am in kg/hr, ih and fh are the final and initial enthalpy of drying air and ambient air respectively in j/kg of dry air and, dt is the drying time in hours the dryer area was calculated from the equation by [31] de a i (17) where the area of the dryer cover is da in m2, i is the total incident radiation on the greenhouse dryer surface during the drying period, and  is the dryer efficiency which is between 30-50% [32]. the vent area va was determined by the ratio of the volumetric flow rate of air inside the dryer av to wind velocity wv by advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 227 a v w v a v  (18) 2.4. psychrometric chart thermodynamic parameters were obtained by use of psychrometric calculator developed from psychrometric charts that describe the thermodynamic process of hot air drying [33]. the most common dehydration processes use hot air as the drying medium as the air delivers heat to the product in order to evaporate moisture. the properties of air, most easily understood by psychrometric relationships are critical to understanding the process of evaporation. the dry air can be visualized as a gaseous solution of dry gases in constant proportions and water vapor in varying amount. at least two properties of air must be known in order to use the chart to characterize the drying air. amongst the properties of air that are critical to drying are absolute humidity, enthalpy or heat content, specific volume, and relative humidity. the thermodynamic changes that take place in a solar dryer include heating depicted line a-b of fig. 3 whereby there is a rise in temperature from ta to tb at constant absolute humidity. the relative humidity reduces from ha to hb. this is followed by the heating phase depicted by line b-c whereby the air picks up moisture from the product and the temperature drops from the drying temperature attained by air inside the dryer tb to exit temperature tc. in this process, the relative humidity increases from hb to hc. the humidity ratio will increase from hb to hc. the initial enthalpy, ha, will change to hc at c’. table 2 psychrometric values of drying air item temperature-dry basis in °c relative humidity in % enthalpy in kj/kg humidity ratio in kg/kg specific volume in m 3 /kg ambient temperature 24 55 53.70 0.0116 0.9695 solar collector outlet air 45 21.09 82.36 0.0143 0.913 dryer outlet air 37 50.0 89.28 0.0202 0.890 table 3 design conditions and assumptions s/no items condition and assumption 1 location: botswana, gaborone, university of botswana elevation:1005 m, 24.56 0s, 25.92 0e 2 material for drying tomato 3 drying period using solar energy exclusively, dt , the average bright sunshine hours in a day 30 4 loaded mass, pm kg/batch 2000 5 initial moisture content, mi, %, bw , measured in the laboratory 96 6 final moisture content, mf, %, bw , evaluated using equation 1 at wa =0.55 12 7 average ambient air temperature, tam 0 c 24 8 average ambient relative humidity, rh, % 44 9 maximum allowable temperature, tprmax, 0 c 60 10 maximum allowable product temperature, tpr, 0 c 45 11 specific heat capacity of tomato slices cpp, kj/kg 4.080 12 average incident solar radiation, in mj m 2 /day 21.6 13 wind speed, vw, km/h, from gaborone weather forecast 6 14 collector efficiency.  =25-50 % [32] 30 15 the thickness of half sliced tomato, m 0.03 the changes in the drying air are evaluated by the assistance of the psychrometric chart/calculator. this thermodynamic data is given in table 2. these parameters are used in the design process. the assumption was made that there was no heat loss between the collector and drying chamber; the solar collector outlet temperature was assumed to be equal to the dryer inlet temperature. the conditions and assumptions for the design calculations are given in table 3. advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 228 fig. 3 the principle of the psychrometric chart 3. results and discussions 3.1. the tomato thermo-physical properties of tomatoes the thermophysical properties were determined in respect of moisture content, density, specific heat capacity, heat capacity and conductivity for the zeal tomato variety. table 4 gives the results of weight measurements during oven drying. table 4 weight of tomato samples during oven drying expired hours w1, g w2, g w3, g w4 average, g m (t) mrexp 0 63 61 66 63.3 24.01 1 1.05 48 36 50 44.7 16.64 0.69 2.08 32 34 38 34.7 12.69 0.53 3.17 28 30 34 30.7 11.11 0.46 3.95 25 28 30 27.7 9.93 0.41 4.7 22 24 27 24.3 8.61 0.36 5.69 17 21 24 20.7 7.16 0.3 6.75 14 17 20 17.0 5.71 0.24 7.05 9 13 16 12.7 4 0.17 7.95 4 10 12 8.7 2.42 0.1 8.86 3 6 8 5.7 1.24 0.05 9.11 3 7 7 5.7 1.24 0.05 9.72 3 7 7 5.7 1.24 0.05 fig. 4 determination of the initial moisture content of tomato samples fig. 5 moisture content mt, db and mt, wb, wet and dry basis advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 229 the results depicted in fig. 4 shows the curves of reducing weight for samples of tomato drying samples. the initial moisture content, wet basis, wb, was determined using equation 2 as 87%, 90%, and 96%, and for tomato samples sample ts1, sample ts2, and sample ts3, respectively. the moisture content for the local botswana tomato in this study was taken as 96% as it was the highest value from the samples that were analyzed. mass of tomato was measured using a weighing digital scale and volume was determined by displacing water from a calibrated flask by the tomato sample. hence the density of the local zeal variety tomato was determined. fig.5 depicts the moisture ratio tm , bw , and tm , db , calculated from the average weight measurements of the oven drying process using eq. (5), the moisture content wet basis was determined using eq. (3). fig. 6 shows the moisture ratio determined from the tomato oven drying experiment using the approximate eq. (6). by use of excel curve fitting solver, the predicted moisture ratio for this drying process was modeled as curve expon mrexp. fig. 6 mrexp determined from experiment and the fitted mrpred the moisture ratio model is given in table 5 for oven drying of tomato slices at 105°c and air velocity of 1.1 m/s was derived by curve fitting model of excel software, is the newton model with regression coefficient r 2 =0.921. table 5 tomato moisture ratio model model formula exp( )mr kt  k r 2 model  exp 0.285mrpred t  0.285 0.921 newton specific heat capacity and thermal conductivity were obtained from the literature [34, 35]. the thermophysical properties of the zeal tomato used in this study are given in table 6. table 6 properties of the round ripe red zeal tomato grown in botswana weight in gram s volume, cm 3 density, kg/m 3 specific heat capacity, kj/kg °c thermal conductivity, w/m k diffusivity in m 2 /s*e-7 initial moisture content, % final moisture content, % 132 130.1 1014 4.080 0.59 1.44 96 12 3.2. design assumptions and calculations the results of calculations done on the basis of equations given in section are summarized in table 7. the parameter of interest is the top area of the solar energy interface. by the determined value of the area, the researcher was able to proceed to complete the design based on priorities for the design concept and other engineering design parameters and procedure and to give specifications of the components and materials to be used. table 7 design assumptions and calculations s/no description equation value 1 mass of water to be evaporated from 2000 kg of fresh tomatoes, and 50 kg for prototype, mw. in kg using equation 4.5 1795 2 latent heat of vaporization in mj using equation 4.6 2.390 3 the energy required for evaporating water from the product, in mj using equation 4.7 4.562 advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 230 table 7 design assumptions and calculations (continue) s/no description equation value 4 equilibrium relative humidity, in % erh=aw*100% using equation 4.10 55 5 initial humidity ratio, wi from psychrometric chart/www.psychrometric-calculator.com. 0.0143 6 final humidity ratio, wf from psychrometric chart/www.psychrometric-calculator.com. 0.0202 7 enthalpy, hi, initial enthalpy of ambient air, kj/kg/kgda from psychrometric chart/www.psychrometric-calculator.com. 82.36 8 enthalpy, hf of final moist air kj/kg/kgda from psychrometric chart/www.psychrometric-calculator .com. 89.28 9 average drying rate mdr for td=10 hours per day for 3 days, kg/hr using equation 4.11 59.85 10 airflow rate, ma, kg/hr using equation 4.12 10144.07 11 volumetric air flow rate, va in m 3 /min using equation 4.13 141.0 12 total useful energy, e in mj using equation 4.14 2105.909 13 greenhouse top area ad m2 using equation 4.15 324.98 14 greenhouse with floor area af m2 of dimensions of about 13 m widths by 25m length af=ad 325 15 the linear air flow rate in m/s conversion of va over the flow area 0.007 16 the vent area av m2 when wind velocity vw is 6 km/h using equation 4.16 1.41 17 the diameter of a cylindrical vent d m d=2*sqrt av/π 1.34 3.3. design features and material specifications table 8 specifications of major items of the designed greenhouse dryer s/no item description specification 1 polyethylene ultra violet resistant cover clear 2-3 mm thick film 2 horizontal floor area 325 m 2 . 3 the volume of greenhouse dryer 1035 m 3 4 drying table for tomato slices plastic mesh on an aluminum frame 5 photovoltaic, p-v unit 100-watt, 100 ah solar battery 6 air fan unit 150 m 3 /min 7 inlet/outlet ducts diameter aluminum 1340 mm (a) the isometric drawing (b) top view (c) back view (d) front view fig. 7 drawings of the design of the ventilated greenhouse dryer showing the different views the final drawings of the ventilated greenhouse solar dryer were prepared using solid works software and ansys modeller 17.2. centrifugal blow fan is fitted at the inlet and the exhaust fan of the same rating is fitted at the outlet to exit the drying air. these fans are powered by a photovoltaic system, not shown in the drawing. the dryer base is covered with checked aluminum plate, painted black and is insulated from the ground. inside the dryer is the drying rack where half-sliced tomatoes for drying are laid. the greenhouse is covered by polyethylene ultra-violet film and entry to the inside of the dryer is accessed by opening the door in the front side. the design drawings are given in fig. 7. the major components are listed in table 8. 3.4. cost-effectiveness of design the final design of the greenhouse solar dryer is to be integrated with a solar collector with a thermal energy storage system to enable the drying process to continue after sunset. sensible heat storage, shs, systems are relatively simple and advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 231 relatively of lower cost compared to chemical or latent thermal energy storage systems [36]. solid sensible heat storage system using granite rock as the thermal storage material has been identified for use in the design of the thermal energy storage system. in comparison with latent and thermo-chemical optional thermal energy storage systems, the use of sensible rock thermal energy storage system is the most cost-effective as regards technical, cost and environmental criteria. the classification of the shs system using rock material that is low cost, ready availability, negligible maintenance, and operational cost would result in a relatively low-cost solar collector. when the solar collector with the tes system is integrated into the greenhouse unit, the technology becomes cost-effective to fulfill the main objective of commercial drying of tomatoes even after sunset in a rural setting. fig. 8 depicts the schematic drawing of the design of the greenhouse solar dryer with the proposed solar collector. fig. 8 schematic design drawing of the p-v ventilated greenhouse solar hot air tomato dryer 3.5. design materials in selecting the design materials, consideration of their effectiveness and price was made. the ventilated greenhouse dryer’s cover material was chosen based on suitability to interface with the incident solar radiation, strength and price. plastic films and sheets are relatively cheaper than glass. generally, plastics may have long-wave transmittance of up to 0.4 with a maximum temperature of 120°c. for application in low-temperature drying, a maximum of 60°c, the ultra-violet resistant polycarbonate material was recommended but it was scarce in botswana. polyethylene ultra-violet resistant film, 2-4mm thickness, was alternatively available in gaborone and was thus chosen. the insulation material was required for the base of the dryer. the base comprising of an insulated slab made of polyurethane foam, pur/pir that is frequently employed in storage tanks was recommended. the insulation material has an extremely low thermal conductivity of 0.02-0.026w/m k possess excellent mechanical strength, exceptional durability, and moisture resistant. the insulation material was cost-effective and easy to install. the output of the solar collector was the drying air that flowed to the drying chamber via a duct, aluminium and galvanized-tin ducts are the two standard most common materials for fabricating ducts because of their high optical reflectance. aluminum is light-weight, has a low density of about third of other metals. it has a high thermal conductivity of about three times that of steel and can be easily fabricated and installed on-site. however, the galvanized tin duct was relatively cheaper than the aluminium duct and was recommended as the ducting material. airflow inside the solar dryer was taken care of by the use of a solar photo-voltaic, p-v module. the solar panel system was incorporated in the design as part of the dryer technology and was used to power the fanning system for a controlled operation depending on insolation levels. a solar battery 0f 100 ah in the p-v system of one 100 w panel was to be used to store energy in order to save on the high operational cost of using electricity. advances in technology innovation, vol. 4, no. 4, 2019, pp. 222-233 232 4. conclusions the following conclusions were made from the development of the design of the solar dryer unit: (1) the thermo-physical properties of the tomato were determined as weight: 132 g, volume: 130.1 cm3, density: 1014 kg/m3, specific heat capacity: 4.080 kj/kg °c, thermal connectivity: 0.59 w/m k, diffusivity: 1.44e-7 m/s2, initial moisture content: 96% wb , and final moisture content: 12 % wb . (2) the moisture ratio curve for drying tomato slices at a temperature of 105°c and air velocity of 1.5 m/s, under oven-drying, was fitted to the newton model with regression coefficient r2=0.921 using excel software. the drawings of the design of the p-v powered forced convection commercial solar drying unit was produced. locally procured materials were specified in the design consistent with the objective of producing a cost-effective solar dryer. the solar dryer was designed as a mixed-mode type to operate continuously using direct sunshine during the day and stored solar energy at night to dry tomatoes. the design was done under the assumptions and conditions of botswana. in the finalization stage of the design process, all the parameters were applied to produce the embodiment of design with the design drawings and specifications of the ventilated greenhouse solar dryer unit. this unit will be integrated into the solar collector with a solar energy storage system for use after sunset. conflicts of interest the authors declare no conflict of interest. acknowledgment the authors of this paper acknowledge mobility to enhance training of engineering graduates in africa, metega for funding of the post graduate study program at the university of botswana under which this study was made possible. references [1] w. h. organization, “the state of food security and nutrition in the world 2018: building climate resilience for food security and nutrition,” food & agriculture organization of the united nations, 2018. 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[36] b. amer, m. hossain, and k. gottschalk, “design and performance evaluation of a new hybrid solar dryer for banana,” energy conversion and management, vol. 51, pp. 813-820, 2010. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 nonlinear dynamic analysis of direct acting tensioner of an offshore floating platform zong-yu chang 1,* , xin duan 1 , zhong-qiang zheng 1 , lin zhao 1 , yu-hu yang 2 , xian-yi zhou 1 , peng zhu 1 , jing-wen he 1 1 college of engineering, ocean university of china, qingdao, china 2 laboratory of mechanism theory and equipment design of ministry of education, tianjin university, tianjin, china received 08 august 2019; received in revised form 25 december 2019; accepted 16 may 2020 doi: https://doi.org/10.46604/aiti.2020.4529 abstract the offshore floating platform is the key equipment in offshore and gas development. the significant heave motions occur with the excitation of wind and waves, which will affect the safety of a riser system. a direct acting tensioner can be applied to reduce the effects on the riser system and be widely used on different kinds of offshore platforms. based on the analysis of the structure and working principle of a direct acting tensioner (dat), the nonlinear dynamic performance of dat riser system was studied. additionally, the dynamic model of the dat riser system is established and the dynamic response was gained by the numerical integration method. the differences of dynamic responses were compared between a linear model and a nonlinear model. the response on different side of the equilibrium position is asymmetric because of the nonlinear stiffness of dat. the results can be helpful for the design of dat. keywords: direct acting tensioner, nonlinear dynamic model, accumulator 1. introduction the explorations of oil and gas in the ocean have been rapidly developed in recent years [1]. various offshore floating platforms are widely used in the deep sea oil and gas exploration [2]. the offshore floating platform undergoes significant heave motion with the excitation of waves, which may lead to a huge pulling force or a riser connecting to the seabed buckled. as a result, it brings about serious accidents. the riser tensioner can reduce the influence of the platform's heave motion on the riser by controlling the relative displacement of the offshore floating platform and the riser, which can ensure that the riser does not buckle due to compression, and does not damage abruptly due to excessive tension [3]. as shown in fig. 1, the riser tensioner can be classified as a wireline riser tensioner system (wrt) and a direct acting tensioner system (dat) [4]. the wireline riser tensioner system is revealed in fig. 1(a). and the direct acting tensioner system is shown in fig. 1(b). the wireline riser tensioner system needs frequent maintenance because the wireline easily worn. the direct acting tensioner system is directly connected to the riser and the platform, which has high reliability and long service life. therefore, direct acting tensioners are welcomed by the industry [5]. scholars have carried out related researches on the performance of riser tensioners. xu [6] used a constant tension model to simulate the riser tensioner, and analyzed the deformation and movement of the riser by applying constant tension to the riser and ignoring the tension change caused by the platform heave motion. yong [7] and liu [8] applied a linear spring to * corresponding author. e-mail address: 854127780@qq.com advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 183 simulate the tensioner. it is shown that the tensioner can reduce the influence of the heave motion on the riser to a certain extent. however, the nonlinear stiffness characteristics of the direct-acting tensioner cannot be reflected by the linear spring model. the stiffness of the hydro-pneumatic tensioner will be changed with different stroke. hatleskog [9] analyzed the nonlinear stiffness characteristics of the hydro-pneumatic tensioner and compared with results of the linear spring simulation. the results are indicated that the nonlinear characteristics of the tensioner can improve the compensation performance of the tensioner, thus the nonlinear characteristics of the tensioner cannot be ignored. zhang [10] analyzed the parameters which will affect the compensation performance of the direct-acting riser tensioner. researches demonstrated that the accumulator volume will influence the compensation performance. (a) wireline riser tensioner system (b) direct acting tensioner system fig. 1 wireline riser tensioner system and direct acting tensioner system hyewon lee [11] considered the characteristics of hydro-pneumatic tensioners, and established a mechanical analysis model of the offshore floating platform-direct acting tensioner-riser system. seung-ho ham [12] used a multibody dynamics system to analyze the movement of riser tensioners. studies have shown that accumulator volume and wave amplitude are important parameters affecting the compensation performance of tensioners. the previous analysis method ignored the effect of the tensioner on the riser tension change, applied directly to a constant tension on the top of the riser to simulate the tensioner to solve the dynamic response. in order to solve the above problems, in this study, the dynamic model of the marine riser system has been established. the nonlinear stiffness characteristics caused by the hydraulic and pneumatic system of the direct acting tensioner have been considered in the model. the dynamic response of the system has been solved based on numerical analysis methods. furthermore, the influence of nonlinear stiffness on response has been analyzed. 2. structure and principle of direct acting tensioner fig. 2 the marine riser system inner pipe tensioner riser string lmrp bop stack gps-satellit advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 184 the structure of the marine riser system is shown in fig. 2. the upper end of the riser includes the inner pipe and outer pipe connected by a telescopic joint. the inner pipe and the floating platform are connected while the outer pipe has a lower flex joint connected to the lower marine riser package (lmrp) of the blowout preventer (bop) stacked on its lower end. the direct acting tensioner acts on the outer pipe of the riser through a tensioner ring, which is shown in fig. 3. fig. 3 direct acting tensioner system the direct acting tensioner is mainly composed of three parts: support frame, hydraulic cylinder, and tensioner ring. the support frame of the tensioner is installed on the platform. the accumulator provides power to compensate for the riser heave motion through the expansion and contraction of the hydraulic cylinder. 3. dynamic analysis of the marine riser system 3.1. the analysis of tensioner performance fig. 4 the structure of direct acting tensioner system table 1. the parameters of hydraulic cylinder component specifications value unit accumulator volume 3.2 m 3 initial pressure 190.2 bar hydraulic cylinder piston diameter 470 mm piston rod diameter 400 mm piston mass 2510 kg the structure of the hydraulic cylinder is shown in fig. 4 and the parameters of the hydraulic cylinder are shown in table 1. the rodless chamber is connected to the accumulator. the gas change process satisfies the conditions of the adiabatic process; therefore, it is suitable for the equation of state for the ideal gas. v is the volume of the accumulator gas. p is the gas pressure of the accumulator. v0 is the initial volume of the gas, and p0 is the initial pressure of the gas. according to the equation of state for the ideal gas, the four variables satisfy the equations as: support frame hydraulic cylinder tensioner ring hydraulic cylinder accumulator v p gas oil advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 185 kk pvvp 00 (1) the pressure p is: 0 0 0 0 0 ( ) = ( ) k k p v v p p p v v a x   (2) where ap is the piston diameter; x is the displacement of the piston and the hydraulic cylinder force fi is: 0 0 0 ( ) k p i p p v f p v a x a p a   (3) 4 1 i i f f   (4) where f is the tensioner force. the relationship between tensioner force and the displacement of the piston is shown in fig. 5. fig. 5 the relationship between force and displacement of hydraulic cylinder it is obvious that the relationship between force and displacement is nonlinear. in addition, the magnitude of stiffness is transforming with the change of the displacement. 1.4 0 1 0 1 1 1 p p a pf k l x a x / v                (5) the stiffness curve is shown in fig. 6. fig. 6 the relationship between stiffness and displacement of riser-direct acting tensioner system 3.2. dynamics modeling of the riser system the model of direct acting riser tensioner with the floating platform and riser system is shown in fig. 2. the tensioner applies tension to the riser through the tensioner ring to suppress the heave motion of the riser. the scheme of the dynamic model is indicated in fig. 7. advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 186 fig. 7 dynamics model of the marine riser system generally, the tilt angle for the hydraulic cylinders of the direct-acting tensioner is small. the effect on the tilt angle of the hydraulic cylinders on the lateral direction can be neglected. under the excitation of the wave, the heave motion of platform can be assumed simple harmonic as a . based on eq. (3), the tension of the tensioner f against the riser can be calculated and the motion of system can be written as: 4 4 1 1 ( ) ri i i i mx f mg c x a k x         (6) axx  (7) xkf rr  (8) where m and kr respectively represent the riser mass and stiffness. x and fr are the heave motion and tension of the riser respectively. i and ci represent the number of hydraulic cylinders and the hydraulic cylinder damping coefficient, respectively. the parameters of riser tensioner-riser system are shown in table 2. table 2. the parameters of riser tensioner riser system specifications value unit riser mass 7.49×10 5 kg number of hydraulic cylinders 4 riser stiffness 3430 kn/m hydraulic cylinder damping coefficient 967 n/(m/s) 4. dynamic response analysis of the marine riser system 4.1. dynamic response analysis of the riser (a) the tension of the riser in presence or absence of the tensioner (b) the heave motion of the riser in presence or absence of a tensioner fig. 8 riser response comparison with or without compensation advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 187 the results of this part are obtained under the heave motion of the platform where the motion height (h) = 5m, and the period (t) = 20s [13]. the response of the riser is shown in fig. 8. fig. 8(a) shows the tension response of the riser with or without rise tensioner. fig. 8(b) reveals the heave motion of the riser with or without tensioner. according to the figure, it can be seen that with the riser tensioner, the oscillation magnitude of tension and heave motion is reduced obviously about 30% and 50%. 4.2. analysis of nonlinear characteristics of riser tensioner in order to simplify the analysis, the nonlinear model of the riser tensioner can be equivalently linearized. when the displacement range of the piston is from -8m to 8m, the linear fitting curve is obtained as fig. 9. the difference between linear and nonlinear model can be seen in this figure. fig. 9 linear fit of hydraulic cylinder (a) heave motion of riser with 3 meter displacement excitation (b) tension of riser with 3 meter displacement excitation (c) heave motion of riser with 10 meter displacement excitation (d) tension of riser with 10 meter displacement excitation fig. 10 riser response based on the two models, the responses of tension force and heave motion of riser are shown in figs. 10-11 with heave motion amplitude 3 m and 10 m of the platform. fig. 10(a) and 10(b) are the heave motion and tension of the riser with 3 meter displacement excitation. fig. 10(c) and (d) are the heave motion and tension of the riser with 10 meter displacement excitation. x(m) f (n ) advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 188 from fig. 10(a) and 10(b), under the small amplitude motion of the platform, the results of the linear model and the nonlinear model agree extremely well. it is suggested that under small amplitude excitation, the linear model can be used instead of the nonlinear model however, when the platform motion reaches large amplitude, there are significant differences between the results of nonlinear model and linear model. it is obvious that the tension curve and motion curve is no longer symmetric in positive and negative directions for the nonlinear model. the responses of the marine riser system with four different amplitudes heave motion of the platform are calculated as figs. 11-12. fig. 11 presents the vertical displacement of the riser and fig. 12 indicates the tension of the riser. as shown in figs. 11-12, the degree of symmetric is increased with the amplitude of the platform motion and the nonlinearity of hydraulic cylinder. fig. 11 the vertical displacement of riser fig. 12 the tension of riser an index of asymmetric is carried out to represent the degree of asymmetric. what is more, the equilibrium position is assumed to be the steady state when the platform is not moving. the index s is defined as the ratio between the positive displacement and the negative displacement of the riser as: p n x s x  (9) where xp is the positive displacement the riser, xn is the negative displacement. the index of asymmetry degree with the different exciting displacement of platform is shown in fig. 13. the comparison of positive displacement and negative displacement is shown in fig. 13. the index of asymmetry degree with the different exciting displacement of platform is shown in fig. 14. fig. 13 comparison of positive displacement and negative displacement fig. 14 asymmetry index with different heave excitation as referred in section 3, the stiffness of the riser tensioner decreases with the increase of the displacement of the riser. the stiffness in a negative direction is larger than the one in a positive direction. therefore, the tensioner has a small displacement and large tension force in the negative direction. it would be beneficial for avoiding the buckling of the rise and keeping fairly tension force on the riser ring. advances in technology innovation, vol. 5, no. 3, 2020, pp. 182-189 189 5. conclusion in this study, the dynamic simulation of the marine riser system is carried out, and the dynamic response of the marine riser system is analysed. dynamic model is established including the floating platform, rise tensioner and riser ring. the simplified model of dat with pneumatic system is developed and the nonlinear stiffness of the riser tensioner is considered. through the numerical simulation, the vertical motion of the marine riser system and the tension of the riser with different wave conditions are analysed. in low-amplitude wave conditions, the system response of the model considering nonlinear stiffness of dat is similar to the result of the linear model; in high -amplitude wave conditions, the significant difference exists between the linear model and the nonlinear model. the asymmetrical response can be seen obviously in the nonlinear model. an index to represent the degree of asymmetry is carried out. the calculation suggests that with the increase in the heave motion amplitude of offshore, the asymmetrical degree will increase. the nonlinear characteristic of direct acting tensioner could be useful to prevent the buckling of the riser. in order to further improve the compensation performance of the riser tensioner, the impact of the riser hysteresis effect on the riser response should be analysed next. at the same time, most of the researches on the nonlinear stiffness characteristics of the riser tensioner are still in the theoretical research simulation stage. a test device should be established in the future to verify the effect of the tensioner nonlinear stiffness on its compensation performance in the experiment. conflicts of interest the authors declare no conflict of interest. references [1] t. wang and y. liu, “dynamic response of platform-riser coupling system with hydro-pneumatic tensioner,” ocean engineering, vol. 166, pp. 172-181, october 2018. [2] b. chen, j. yu, y. yu, l. xu, h. wu, and z. li, “modeling approach of hydro-pneumatic tensioner for top tensioned riser,” journal of offshore mechanics and arctic engineering, vol. 140, no. 5, october 2018. [3] r. g. pestana, f. e. roveri, r. franciss, and, g. b. ellwanger, “marine riser emergency disconnection analysis using scalar elements for tensioner modeling,” applied ocean research, vol. 59, pp. 83-92, september 2016. [4] j. k. woodacre, r. j. bauer, and r. a. irani, “a review of vertical motion heave compensation systems,” ocean engineering, vol. 104, pp. 140-154, august 2015. [5] y. wu, “a new operability and predictability enhanced riser control system for deepwater marine operation: an integrated riser hybrid tensioning system,” ph.d. dissertation, dept. elect. eng., the university of texas at austin, 2015. 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[11] h. lee, m. i. roh, s. h. ham, and s. ha, “dynamic simulation of the wireline riser tensioner system for a mobile offshore drilling unit based on multibody system dynamics,” ocean engineering, vol. 106, pp. 485-495, september 2015. [12] s. h. ham, m. i. roh, and j. w. hong, “dynamic effect of a flexible riser in a fully connected semisubmersible drilling rig using the absolute nodal coordinate formulation,” journal of offshore mechanics and arctic engineering, vol.139, no. 5, october 2017. [13] w. shisheng, x. bin, and l. xinzhong, “the motion response analysis of deep water typical tlp in environment conditions of south china sea,” shipbuilding of china, vol. 52, no. 1, pp. 94-101, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 transmission wheeling pricing in embedded cost using modified amp-mile and mva utility factor methods gaurav jain 1,* , dheeraj kumar palwalia 2 , anuprita mishra 3 1,2 department of electrical engineering, rajasthan technical university, kota, india 3 department of electrical engineering, technocrats institute of technology, bhopal, india received 11 january 2019; received in revised from 27 february 2019; accepted 28 march 2019 abstract transmission wheeling pricing is one of the decisive aspects of present open access electricity market. various methods are available for transmission; however, no method is proved to diverse operating conditions of the power system. these methods are not able to quantify the full recovery of embedded cost. all the variables i.e. remaining charges, used circuit capacity are not counted in the existing methods. this paper explicates two methods, modified amp-mile method, and mva utility factor method, to recover the embedded cost. modified amp-mile method is a customized form of existing amp-mile method. in the mva utility factor method, cost allocation is based on marginal participation (mp). it evaluates the cost, using sensitivity analysis of network power. the proposed methods are tested on an ieee 6-bus system and further verified on hadoti region real 37-bus system. all the results are presented in full recovery model (frm) and partial recovery model (prm). keywords: transmission wheeling pricing, embedded cost recovery, open access, power system economics 1. introduction in reference to the indian electrical network, power plant and electrical utilities are connected to the same transmission network. a nodal point is required to decide transmission pricing by independent power producers and electrical utilities both. the action of one buyer creates an effect on other participants; hence practical cost allocation becomes difficult to investigate [1]. however, transmission cost allocation is a complicated issue in deregulated power system [2]. in past years, different methods for allocation of transmission cost in electric networks are proposed by researchers. capacity usage related to each transaction is calculated for all transmission lines by applying existing methods i.e. average participation method, marginal participation method, distribution factors, equivalent bilateral exchange method, z-bus method, and cooperative game theory. in open access, electricity market allotment of embedded cost is one of the important aspects [3]. each utility has to find a solution with the characteristics of its transmission system and degree of deregulation adopted. various methods are employed at all operational conditions of diverse power systems to obtain such a solution. no technique is capable of evaluating the entire embedded cost. any usage-based cost allocation method must contain three features, i.e. accurate algorithms for transmission usage evaluation, equitable allocation rules and full recovery of embedded cost. based on the above features, cost allocation signifies to identify cost causer for incurring these costs. to determine the causer may be complicated because the non-linear nature of power flow equalities causes difficulty to nature of power flow equations [4]. *corresponding author. e-mail address: jaingauravrtu@gmail.com tel.: +91-9414982965; +91-9602410960 advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 178 existing methodologies used for transmission wheeling pricing are classified into rolled-in methods and usage-basedmethods. the rolled-in methods do not provide price signals that are cost reflective and are subdivided into two methods, i.e. postage stamp method and contract path method. in postage stamp method, electric utilities allocate the fixed cost among its users having firm contracts [5]. whereas, in contract path method [6] managed power would be confined to an artificially specified path through the transmission system. on the other hand, usage-based methods require power flow execution of the transmission system and divided into various sub-categories, i.e. mw-mile, modulus, mva-mile, and amp-mile methods. mw-mile methodology [7] is the pricing strategy for the recovery of fixed transmission costs on the basis of actual power flow of the transmission network. in the modulus method, all mediators have to pay for the actual capacity use and additional reserve [8]. mva-miles method is an augmented version of mw-miles; it takes into account the range of the use of network due to their active and reactive power injection/drawn [9]. whereas, amp-mile method is based on the current flow in the system. marginal participation (mp) methods dominate tracing flow methods as there is no electrical principle behind the tracing flow [10]. it is implemented where tracing flow is significantly less. it allocates transmission charges to either generators or demand nodes. the allocation between generators and demands is decided exogenously, therefore it distorts the vocational signal. it assigns power flow sensitivity in each line due to power injection at each bus and the network usage cost. sensitivities or utility factors evaluated as per mp are used to predict the changes in losses, voltages and different branch flow due to change in loads and generations [11]. these sensitivities capture the effects of unbalanced network parameters, load and generator locations. in marginal participation methods, the amp-mile method is enough to attain the aim for the transmission network. even though it has some limitation, i.e. it cannot be implemented on ehv networks and cannot allocate entire embedded cost. hence, additional charges are required to be imposed on agents. in practice, the extent of use (eu) is never 100% of the circuit’s capacity. therefore, the grid looks underutilized and lastly service cost based on the network usage will be smaller than embedded cost. other costs are incurred through supplementary charges [12]. in transmission wheeling, there are many challenges occur to find out proper coat allocation. some challenge is to promote the efficiency of the day-to-day operation of the bulk power market. to resolve the problem of signal locational advantages for investment in generation and demand. to increase the investment in the transmission system for saving customer cost in the energy market. recover the costs of existing transmission assets, which has been investment by the transmission company. in transmission pricing, incremental cost is directly available from economic dispatch. these pricing methods are well suited for rapid on line costing, but limited to presenting economic effects on the wheeling utility’s production cost and total system losses. the main focus is to find ways and means to generate and inject more competition, thereby forcing the conventional monopolistic power market to a competitive market. the transmission of open access has been introduced into the electric power supply industry to alter the traditionally monopolized market. it is desired that transmission prices and payment do not disturb decisions for new generation investment, for generator and for consumer demand. at same time charging must be achieved in a simple and fair form, realistic and adequate for real-time application as well as transparent enough to be politically acceptable. in wheeling,methodology compute a high priority problem due to growth in transmission facilities, cost differentials between utility companies, and dramatic growth in non-utility generation capacity. the modified amp method in the full recovery model and mva utility factor method in full/partial recovery model is analyzed in this paper. cost comparison analysis of the different method is show benefits of modified amp method in transmission pricing. the embedded cost allocations using a different method at different percentage loading are evaluated. a real 37-bus system and ieee 6-bus system network is used in the case study to prove efficiency and applicability of the proposed method. in this paper, the nonlinearity of sensitivity indices of modified amp method and mva utility factor has been established and analyzed. advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 179 2. wheeling pricing methodologies the pricing methodology adopted by each utility is depending on the characteristic of the transmission or distribution network. therefore, a particular pricing methodology cannot be applied for all conditions as each methodology has its specific characteristics. deregulated environment reduces the tariff for consumers and improves the efficiency for power suppliers in the long run. transmission pricing has been categorized on the basis of their operating principles i.e. marginal/incremental cost-based pricing [13], embedded cost-based pricing [14], and combination of embedded with incremental cost-based pricing [15]. table 1 literature methodology in embedded wheeling pricing from past to present s.no year author literature points of embedded wheeling pricing 1 1989 d. shrimohammadi • analysis of mw-mile method • cost allocated is proportional to the mw flows • this method doesn’t take care of reactive power • fail to reflect technical operational conditions of network 2 2001 chingtzong su, and ji-horngliaw • analysis of mva-mile method • considering apparent power (mva) for wheeling pricing • more reasonable and valid than the commonly used mw-mile method • unable to consider direction of reactive power flow • not providing true pricing 3 2006 yog r. sood • modified analysis in mw-cost method or mva-cost method • instead of multiplying the changes in the flow in the facility by length, it is multiplied by its cost unlike mw-mile or mva-mile method 4 2006 f. li • analysis of mw + mvar-mile • this method takes care of power factor of network users • it separates the mw and mvar power flows • distinguishes direction of reactive power flow • acknowledges full cost-benefit of network users, especially dg 5 2009 paul m. sotkiewicz and j.mario vignlo • analysis of amp-mile method • cost allocation is based on amp flow caused by individual customer • explicitly account for counterflows and reward dg • drafts the direction of reactive power • but applicable only on distribution network 6 2007-2010 florin and cutsem, xiao and mccalley, k. singh • analysis of congestion management in transmission pricing • probabilistic risk indices to assess real power level security system • congestion management in deregulation environment by utilizing impedance matrix 2.1. marginal/ incremental cost-based pricing methods marginal pricing or marginal wheeling rates are also called an extension of the spot-pricing theory. spot pricing is a method for pricing electricity that maximizes the economic efficiency of the power system [16]. it is difficult to estimate transmission pricing using marginal cost based pricing method as the income would not be sufficient for financing the investment. however, a theory of social benefit, which maximizes real-time price of real and reactive powers, is considered [17]. it flattens the peak power demand and fills the valley of demand. the allocation of transmission payments among different agents depends upon the total energy consumed. an algorithm for optimal pricing includes transmission cost beside generation cost in electricity supply. the report of optimal pricing calculation has to be sent to all the participants. the marginal cost could be minimized with the inclusion of facts devices in an overloaded transmission system. facts devices can change power flows by using system parameters. using spot pricing and marginal cost theories active and reactive power transition costs is calculated while voltage-dependent load models were observed [18]. incremental cost methodologies are defined in two parts as short run and long run cost. short run marginal/incremental cost or spot pricing is economic. it has some bidding to power transmission systems such as entire transmission costs not recovered, the charges acquired exceedingly volatile, rationale for transmission charges and the transmission system is frequently not in most favorable condition, etc. on the other hand, long-run incremental cost methodology depends on forecast advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 180 data with uncertainties. it is difficult to obtain convincing prices as many non-deterministic factors are involved [19]. all system costs (existing transmission system, operation, and expansion) are allocated among the system users in proportion to their eu (extent of use) of the transmission resources. the charge for basic transmission service is usually the component of overall transmission service charges. 2.2. embedded cost-based pricing methods embedded cost is defined as the revenue required paying for all existing or any new facilities added to the power system during the contract for transmission service. in general form adequate remuneration of transmission systems and easy to implement. the embedded cost methods allocate the total system cost among the transmission customers, based on extent of use (eu) rule. in embedded methods, all system costs (existing transmission system, operation, and expansion) are allocated among the system users in proportion to their extent of use (eu) of the transmission resources. they can be classified as rolled-in methods and usage-based methods. the main shortcoming of the rolled-in methods is ignorance of actual system operation. as a result, they are likely to send incorrect economic signals to transmission customers. but this problem has overcome by usage-based methods as it evaluates eu in the framework of either load flow or optimal power flow. embedded costs methods are used by the utilities to allocate existing transmission facilities to the transmission wheeling transaction. table 1 represents the literature survey of embedded wheeling pricing. this table easily describes embedded wheeling cost strategy in electricity market from past to present stage. 2.2.1. active power flow based methods the capacity of transmission network used for a transaction is a function of the magnitude of electric power, transmission lines length, and facilities involved in the active power transaction. capacity value provides an equitable means of allocating the cost of transmission facilities among users of the firm transmission service. it takes full account of current generation cost and capacities as well as the transmission of the demand in space and time. the mw-mile method is used to evaluate the transmission pricing leads to the effective recovery of all embedded costs. it includes an analysis of relative reliability contributions of each generator to the unscheduled transmission capacity in a circuit. all transmission users are liable to wages the actual use of capacity and transmission reserves. in practice, it is improper for those who make limited usage of the network. 2.2.2. real power flow based methods j. bialek proposed a tracing flow method for evaluating the flow of electricity through power networks [20]. it allows quantification of active or reactive power flows from a particular source to a specific load, the contribution from each generator, power load flow and losses in a line. kirschen’s method is based on the solution of a series of load flows. it calculates the contribution of the generator to the loads, line flows and transmission pricing. j. bialek proposed another tracing flow methodology is known as unifying tracing-based methodology of transmission pricing for inter-system trades. it is easy, transparent and fast. it can also deal effectively with circular flows. an up-gradation of mw-mile method was introduced in the year 2001. the upgrade technique is called a mva-mile method which reflects the eu of transmission facilities in the system. it enforces to power flow and considers apparent power. it is reasonable and valid in comparison to the commonly used mw-mile method, but big wheeling charge may pick up the total generation cost. monetary path method is also based on tracing flow concept, which proposes an even measurement for transmission usages by active and reactive powers. reactive power allocation method determines real and imaginary currents to handle the system losses and loop flow. the traces from current sources to current sinks are then converted to power contributions. mva method is economic to resolve difficult reactive power pricing and costing issues. all the methods are based on tracing flow concept for usage quantification. advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 181 2.3. composite embedded and marginal cost-based pricing methods tthis methodology includes both the existing system cost and marginal costs of transmission transactions to evaluate the collective transmission pricing part by embedded cost and marginal pricing method. the marginal cost based pricing is used to transmission price services. it requires supplement revenue generation as a pricing scheme is not able to care financially to the transmission service providers. this approach discriminates between operating and embedded costs. it develops separate methods in respect of each of these components. the capacity utilized as well as consistency benefits derived by different users for investment recovery payout of charges for investment recovery are considered. it also includes marginal pricing approach to the recovery of operating cost. it is a simple novel method used for topological analysis of power flows based transmission supplement charge allocation in the network. its result is positive in counter-flow contributions from all the users. revenue of transmission company divided into marginal cost and supplementary charges. the marginal cost is evaluated by frm model to estimate the total transmission cost (cost allocation and remaining charges). in supplementary charges, the cost is evaluated by prm model. whereas, locational charges and post stamp charges method is used to estimate the supplementary charges. both methods are used to evaluate remaining charges in supplementary cost. the supplementary charges are allocated in real power as well as reactive power load through mw-mile, mva-mile method. this charge for usage of a separate transmission asset is divided into a locational and non-locational component. wheeling charging strategy and unused capacity of the asset are shown in fig. 1. fig. 1 wheeling charging strategy 2.4. amp-mile method the amp-mile method is an embedded cost allocation method for the medium voltage distribution network. it is based on the extent of use (eu) for circuits is measured in terms of the contribution of each customer to the current flow i.e. the power to current distribution factors (apidflk t & rpidflk t ), at any instant of time. it is the least control of system stability (steady state and transient) in the distribution system. current capacity increases up to the thermal limit. so current flows may attribute network customers, therefore method is acknowledged as “amp-mile” or “i-mile” methodology [1]. thus different extent of use (eu) is found out using current distribution factors and used to accomplish allocation of cost. unambiguously accounts for flow direction to provide better long-term price signals and to alleviate potential constraints [20]. steps to allocate embedded cost, as well as remaining cost are as follows advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 182 t t t lk k lk t l apidf pl aeoul ai   (1) t t t lk k lk t l apidf pg aeoug ai   (2) t t t lk k lk t l rpidf ql reoul ai   (3) t t t lk k lk t l rpidf qg reoug ai   (4) where, 𝐴𝐸𝑜𝑈𝐿𝑙𝑘 𝑡 is active eu of circuit 𝑙 at time 𝑡 due to demand at 𝑘𝑡ℎ bus, 𝐴𝐸𝑜𝑈𝐺𝑙𝑘 𝑡 is active eu of circuit 𝑙 at time 𝑡 due to generation at 𝑘𝑡ℎ bus, 𝑅𝐸𝑜𝑈𝐿𝑙𝑘 𝑡 is reactive eu of circuit 𝑙 at time 𝑡 due to demand at 𝑘𝑡ℎ bus, 𝑅𝐸𝑜𝑈𝐺𝑙𝑘 𝑡 is reactive eu of circuit 𝑙 at time 𝑡 due to generation at 𝑘𝑡ℎ bus, 𝐴𝑃𝐼𝐷𝐹𝑙𝑘 𝑡 is active power to current distribution factor of circuit 𝑙 at time 𝑡 due to demand at 𝑘𝑡ℎ bus, 𝑅𝑃𝐼𝐷𝐹𝑙𝑘 𝑡 is active power to current distribution factor of circuit 𝑙 at time 𝑡 due to demand at 𝑘𝑡ℎ bus. various methods are not able to quantify the eu of a transmission network for both active and reactive power flows. the amp-mile method became the base of the research. limitations of amp-mile method have been identified through numerical value. based on these corrections modified amp-mile method is proposed. it recommends applicability on ehv networks by putting more prominence on stability limits. a step ahead introduced a new usage-based cost allocation techniquemva utility factor method with two models: full recovery and partial recovery model. it carries the advantages of modified amp-mile method. it is based on marginal participation; therefore obtained utility factors are prone to the choice of slack bus. therefore distinct slack bus notion has been proposed to allocate the embedded cost of ehv networks. distinct slack bus notion is different from dispersed slack bus concept. the intermediate stages of nonlinear sensitivities are found using modified nr based load flow. the relationship between flow and power injection/withdrawal is nonlinear. the novel sensitivity patterns could assist iso to forecast day-ahead transmission. in full recovery model total eu for all the lines remains unity under all loading conditions. 3. proposed methodology the amp-mile method has some limitations. when the system has fully loaded this method do not recover the full embedded cost. it is relevant only on radial networks since currents are comparative to the thermal capacity of the distribution network (high r/x ratio). it is stated that circuit currents are an approximately linear function of active and reactive power at the bus in a radial network. in amp-mile a reconciliation factor is needed to find eu factors for a given line sum to unity. it confers only two types of sensitivities (eq.(5)) in the form of transmission factors cupf (current utility active factor) and cuqf (current utility reactive factor). the common transmission factor for demand/generation transmutation at the same bus with a difference of sign. l dk l gk i p i p     (5) l dk l gk i q i q     (6) where, 𝐼𝑙is the absolute value of the current through circuit l, 𝑃𝑑𝑘 is the active power withdrawal due to demand at 𝑘𝑡ℎ bus, 𝑃𝑔𝑘 is the active power withdrawal due to generation at 𝑘𝑡ℎ bus, 𝑄𝑑𝑘is the reactive power withdrawal due to demand at 𝑘𝑡ℎ bus, 𝑄𝑔𝑘 is the reactive power withdrawal due to generation at 𝑘𝑡ℎ bus. advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 183 3.1. modified amp-mile method the modified amp-mile method identifies the nonlinear or linear nature of sensitivities depending on location and topological conditions. its charges allocation has not been stable at variable load levels and different period of time. it indicates that the current sensitivity indices cupftlk and cuqftlk are exhibiting nonlinear nature with respect to active and reactive powers (injection/withdrawal) at a bus of ehv network. modified nr based load flow is used to find current sensitivity indices. in the modified amp-mile method, reconciliation factor is not required to furnish the total eu for a given line equal to unity. it selects new distinct slack bus perception to resolve the load flow values. entire embedded cost of ehv networks is allocated by using non-linear sensitivities and new distinct slack bus notion. if a system has large chances of increase in load and generation on the same bus, comparisons could be made between ∂il ∂pdk⁄ and ∂il ∂pgk⁄ . therefore, current sensitivity indices are expressed as t ldk l dk cupf i p   (7) t lgk l gk cupf i p   (8) t ldk l dk cuqf i q   (9) t lgk l gk cuqf i q   (10) where, 𝐶𝑈𝑃𝐹𝑙𝑑𝑘 𝑡 is current utility active factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎ demand bus at 𝑡𝑡ℎinstant, 𝐶𝑈𝑃𝐹𝑙𝑔𝑘 𝑡 is current utility active factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎ generator bus at 𝑡𝑡ℎ instant, 𝐶𝑈𝑄𝐹𝑙𝑑𝑘 𝑡 is current utility reactive factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎ demand bus at 𝑡𝑡ℎinstant, 𝐶𝑈𝑄𝐹𝑙𝑔𝑘 𝑡 is current utility reactive factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎ generator bus at 𝑡𝑡ℎinstant. the applicability of the modified amp-mile method is on ehv networks, by putting more prominence on stability limits, instead of thermal capability. in eq. (5), there should be dissimilarity between cupflk t and cuqflk t for load/generation given in eqs. (7-10). the expressions of dissimilar eu’s are where, 𝐴𝐸𝑈𝐷𝑙𝑘 𝑡 is active extent of use by 𝑘𝑡ℎ bus demand for 𝑙𝑡ℎ line at 𝑡𝑡ℎ instant, 𝐴𝐸𝑈𝐺𝑙𝑘 𝑡 is active extent of use by 𝑘𝑡ℎ bus generation for 𝑙𝑡ℎ line at 𝑡𝑡ℎ instant, 𝑅𝐸𝑈𝐷𝑙𝑘 𝑡 is reactive extent of use by 𝑘𝑡ℎ bus demand for 𝑙𝑡ℎ line at 𝑡𝑡ℎ instant, 𝑅𝐸𝑈𝐺𝑙𝑘 𝑡 is reactive extent of use by 𝑘𝑡ℎ bus generation for 𝑙𝑡ℎ line at 𝑡𝑡ℎ instant, 𝑃𝑑𝑘 𝑡 is active demand on 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑃𝑔𝑘 𝑡 is active generation on 𝑘𝑡ℎ bus at 𝑡𝑡ℎinstant, 𝑄𝑑𝑘 𝑡 is reactive demand on 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑄𝑔𝑘 𝑡 is reactive generation on 𝑘𝑡ℎ bus at 𝑡𝑡ℎinstant, 𝐼𝑙 𝑡 is absolute current in 𝑙𝑡ℎ line at 𝑡𝑡ℎinstant. the reconstruction of the algorithm to evaluate cupflk t and cuqflk t inherently attributes the efficacy of slack bus power. it provides true sensitivities, re-establishing and offered a close approximation of circuit currents. the expression of the absolute value of il t will turn to substitute used circuit cost at tth instant (uccl t) equal to unity to find the allocation of embedded cost. consequently adapted circuit cost at tthinstant (accl t) would be equal to ccl t and therefore the relation of locational charges change as given below ? ) t t t t t t lk ldk dk l l dk dk l aeud cupf p i i p p i      (11) ? ) t t t t t t lk lgk gk l l gk gk l aeug cupf p i i p p i      (12) ? ) t t t t t t lk ldk dk l l dk dk l reud cuqf q i i q q i      (13) ? ) t t t t t t lk lgk gk l l gk gk l reug cuqf q i i q q i      (14)   1 nbus t t t t t t t t t l ldk dk lgk gk ldk dk lgk gk k i cupf p cupf p cuqf q cuqf q          (15) advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 184 where, 𝐴𝐿𝑘 𝑡 is active locational charge due to active demand on 𝑘𝑡ℎ bus at 𝑡𝑡ℎinstant, 𝐴𝐺𝑘 𝑡 is active locational charge due to active generation on 𝑘𝑡ℎ bus at𝑡𝑡ℎinstant, 𝑅𝐿𝑘 𝑡 is reactive locational charge due to reactive demand on 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑅𝐺𝑘 𝑡 is reactive locational charge due to reactive generation on 𝑘𝑡ℎ bus at 𝑡𝑡ℎinstant, 𝐶𝐶𝑙 𝑡 is a level cost for each hour. the expression of remaining circuit charges (𝑅𝐶𝐶𝑡) are so the total cost of the modified amp-mile method in the full recovery model is the modified amp-mile method increases allocation equivalent to full recovery model in proportion to assorted eu’s. the eu’s of all circuits would be unity under all loading conditions and no need to calculate remaining (supplementary or non-vocational) charges. therefore, keeping ucc equal to unity and evaluate transmission charges plus capacity charges simultaneously. transmission network participants have to pay for used/unused capacity in proportion to their eu. it is justified by the need for system meeting reliability, stability and security criteria for all customer. 3.2. mva utility factor method the mva utility factor method allocates the entire embedded cost of transmission networks. it carries the advantages of previously discussed modified amp-mile method. the non-linear patterns of mva utility factors have been furnished and distinct slack bus notion has been promoted to allocate the embedded cost of power networks. it provides better promises for payments to counterflow creators and gives assurance for prudent implementation. in the proposed technique individual participant’s impact on the system is recognized through mva flow caused by them. therefore, a method is called an mva utility factor method. it is a significant method because no question arises in relation to current limits for the reason that mva flows can be increased under specified constraints of the power network. it wiped out limits of the modified amp-mile method and exploits load flow and derives non-linear sensitivities (mvauf). this illustrates a true understanding of the network and causes a fair allocation. in mva utility factor method, unequal sensitivities at a bus having active/reactive generation and load are represented as [21]. where, 𝑀𝑉𝐴𝑃𝑈𝐹𝑙𝑑𝑘 𝑡 is mva utility active factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎ bus demand at 𝑡𝑡ℎinstant, 𝑀𝑉𝐴𝑃𝑈𝐹𝑙𝑔𝑘 𝑡 is mva utility active factor of 𝑙𝑡ℎ line w.r.t.𝑘𝑡ℎ bus generator at 𝑡𝑡ℎinstant, 𝑀𝑉𝐴𝑄𝑈𝐹𝑙𝑑𝑘 𝑡 is mva utility reactive factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎ bus demand at 𝑡𝑡ℎ instant, 𝑀𝑉𝐴𝑄𝑈𝐹𝑙𝑔𝑘 𝑡 is mva utility reactive factor of 𝑙𝑡ℎline w.r.t.𝑘𝑡ℎbus generator at 𝑡𝑡ℎinstant. 1   linen t t t k lk l l al aeud cc    (16) 1 linen t t t k lk l l ag aeug cc    (17) 1 linen t t t k lk l l rl reud cc    (18) 1 linen t t t k lk l l rg reug cc    (19) 1 [ ] 0 linen t t t l l l rcc cc cc     (20) ? t t t t k k k k total cost al ag rl rg    (21) t t lgk ldkmvapuf mvapuf  (22) t t lgk ldkmvaquf mvaquf  (23) advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 185 the transmission network though ehv network does not follow the same for some of the generator buses using load flow. it obtains either equal or unequal sensitivities at generator buses in ehv networks. therefore, eqs. (22-23) does not reflect true operating conditions. many cost allocation methodologies suggested following load flow to avoid unequal sensitivities. it established four different utility factors corresponding to generator buses in ehv networks irrespective of equal or unequal sensitivities. mva flow of a line can be expressed using utility factors of eqs. (24-27) are where, 𝑀𝑉𝐴𝑙 𝑡 is the absolute value of mva through circuit l, 𝑃𝑑𝑘 𝑡 is the active power withdrawal due to demand at 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑃𝑔𝑘 𝑡 is the active power withdrawal due to generation at 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑄𝑑𝑘 𝑡 is the reactive power withdrawal due to demand at 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑄𝑔𝑘 𝑡 is the reactive power withdrawal due to generation at 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant. formulation of mvauf’s is evaluated using modified nr based load flow. thus attributes the effect of slack bus power. these buses are self-regulating and bounds for each of the generators. it maintains a constant voltage at buses; consequently, no change in line flow occurs due to change in a reactive generation. expression of absolute mva in lthline at tthinstant (mval t) are the mvauf’s from eqs. (24-27) are employed for the evaluation of eou by each participant, equations given as: it is concluded that total eu due to all participants is unity even though the system is not fully loaded. this methodology is utilized to develop two types of allocation models; partial recovery model (prm) and full recovery model (frm). 3.2.1. partial recovery model (prm) in this modal, a part of the embedded cost is allocated on the basis of electricity usage and remaining charges are imposed on the participants. the two types of charges are; pubc: charge allocated to participants based on the real usage of the network. rc: this portion of allocation reflects a charge to recover the cost of the unused network capacity. it is revealing the security issue of the power system and has to be imposed on all participants. expressions of pubc and rc are: t t t ldk l dk mvapuf mva p   (24) t t t lgk l gk mvapuf mva p   (25) t t t ldk l dk mvaquf mva q   (26) t t t lgk l gk mvaquf mva q   (27) 1 nbus t t t t t t t t t l ldk dk lgk gk ldk dk lgk gk k mva mvapuf p mvapuf p mvaquf q mvaquf q          (28) t t t t lk ldk dk l aeud mvapuf p mva  (29) t t t t lk lgk gk l aeug mvapuf p mva  (30) t t t t lk ldk dk l reud mvaquf q mva  (31) t t t t lk lgk gk l reug mvaquf q mva  both models by a utility depend on its transmission system and extent of deregulation espoused. (32) 1 nline t t t dk lk l l pubcp aeud acc    (33) advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 186 where, 𝑃𝑈𝐵𝐶𝑃𝑑𝑘 𝑡 is partial recovery usage-based charges for active demand on 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑃𝑈𝐵𝐶𝑃𝑔𝑘 𝑡 is partial recovery usage-based charges for active generation on 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑃𝑈𝐵𝐶𝑄𝑑𝑘 𝑡 is partial recovery usage-based charges for reactive demand on 𝑘𝑡ℎ bus at 𝑡𝑡ℎ instant, 𝑃𝑈𝐵𝐶𝑄𝑔𝑘 𝑡 is partial recovery usage-based charges for reactive generation on 𝑘𝑡ℎbus at 𝑡𝑡ℎ instant. let 𝐶𝐶𝑙 𝑡 is levelized hourly cost of 𝑙𝑡ℎcircuit and annual circuit cost will be𝐶𝐶𝑙 𝑡 × 8760.then corresponding adapted circuit cost 𝐴𝐶𝐶𝑙 𝑡 at 𝑡𝑡ℎ instant is where𝑈𝐶𝐶𝑙 𝑡 is the used circuit capacity of line 𝑙 for time 𝑡, and defined by where 𝐶𝐴𝑃𝑙 is mva capacity of the line. the remaining charge (rc) express as 3.2.2. full recovery model (frm) accomplishes total recovery of embedded cost by substituting 𝑈𝐶𝐶𝑙 𝑡 unity in eq. (37); consequently, 𝐴𝐶𝐶𝑙 𝑡 would be equal to 𝐶𝐶𝑙 𝑡. expressions of fubc are: where 𝐹𝑈𝐵𝐶𝑃𝑑𝑘 𝑡 is full recovery usage-based charges for active demand on 𝑘𝑡ℎbus at 𝑡𝑡ℎinstant, 𝐹𝑈𝐵𝐶𝑃𝑔𝑘 𝑡 is full recovery usage-based charges for active generation on 𝑘𝑡ℎbus at 𝑡𝑡ℎinstant, 𝐹𝑈𝐵𝐶𝑄𝑑𝑘 𝑡 is full recovery usage-based charges for reactive demand on 𝑘𝑡ℎbus at 𝑡𝑡ℎinstant, 𝐹𝑈𝐵𝐶𝑄𝑔𝑘 𝑡 is full recovery usage-based charges for reactive generation on 𝑘𝑡ℎbus at 𝑡𝑡ℎinstant. in frm, the eq. (38) for remaining charges can be modified accordingly and expressed as: using an analysis of both methodologies a flow chart is shown in fig. 2. data input and newton raphson analysis is the same in both methods. current utility factor logic has been used in mod amp mile method similarly; 1 nline t t t gk lk l l pubcp aeug acc    (34) 1 nline t t t dk lk l l pubcq reud acc    (35) 1 nline t t t gk lk l l pubcq reud acc    (36) t t t l l lacc ucc cc  (37) /t t l l lucc mva cap (38) 1 nline t t t l l l rc cc acc       (39) 1 nline t t t dk lk l l fubcp aeud cc    (40) 1 nline t t t gk lk l l fubcp aeug cc    (41) 1 nline t t t dk lk l l fubcq reud cc    (42) 1 nline t t t gk lk l l fubcq reug cc    (43) 1 0 nline t t t l l l rc cc cc        (44) advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 187 mva sensitivity analysis has been used to calculate the mva utility factor method. used circuit capacity (ucc=1) unity value is used to calculate annual circuit cost which is defined frm wheeling value in both methods. mva utility factor prm model represent adapted circuit cost to evaluate cost allocation (ca) and remaining charges (rc) in the network. start input bus data, line data, unit cost of transmission line calculate cost of each transmission line and perform base case load flow using newton raphson method modified amp-mile method mva utility factor method find four different’s mvapuf value by varying demands / generations at all respective buses formulate the total mva by using demand/ generation sensitivity value calculate extent of use of each transmission line by individual generator and load find four different’s current utility cupf value by varying demands / generations at all respective buses partial recovery model full recovery model calculate annual circuit cost using used circuit capacity(ucc=1) calculate partial recovery cost allocation (ca) charges based on actual usage of the network (pubc) calculate adapted circuit cost (acc) find the remaining charges(rc) calculate total wheeling cost(rc+ca) in prm model stop print results calculate full recovery cost allocation (ca) charges based on actual usage of the network (fubc) calculate total wheeling cost(ca) in frm model formulate the total current (i) by using demand/ generation sensitivity value calculate extent of use of each transmission line by individual generator and load find the locational charges using used circuit capacity (ucc=1) calculate total wheeling cost using frm model fig. 2 flow chart of mod amp-mile and mva utility factor methods 4. case study and results the proposed methodologies have to be employed on some real-time system or ieee standard bus system to prove its efficiency and reliability. in this paper, a real-time 37 bus system and one ieee standard 6 bus system is used as a case study and respective results are discussed. in the case study, modified amp-mile method is applied using full recovery modal, whereas, mva utility factor method is applied using both modals i.e. full and partial recovery modal. single line diagram of real-time 37 bus system is shown in fig.3. the system has 2 generation bus and 48 transmission corridors at 220 kv and 132 kv voltage level. the generation capacity of 1300 mw is assumed as base load condition and total load connected on the system is 911 mw. it is assumed in this analysis that load customer would pay 100% of the transmission cost of services to the transmission utility. the annual revenue requirement of transmission facility is 843.56 crs-inr. the embedded cost to be allocated is assumed proportional to the length of individual transmission lines in rupee/hr. the comprehensive detail and various parameters of the 37 bus system are given in table 2. data of total load connected is collected of each feeder whereas, bus data represent the bus voltage, active/reactive value of generated power and total load connected in different buses. in line data values represent the load connection information for every node , value of the impedance in each line of the system and line charging value in the transmission network. voltage and power factor value is collected for evaluating the bus data. advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 188 fig. 3 north indian real test system (power map of 37 bus hadoti region) table 2 cost of generation and load (rupee / hr.) for real 37 bus system bus data of 37-bus transmission system line data of 37-bus transmission system bus no. bus voltage power generated load node connection impedance(p.u.) line charging magnitude angle p q p q from to r x (p.u.) b/2 (pu) (deg) (mw) (mvar) (mw) (mvar) 1 2 0.00024 0.001275 0 1 1 0 1300 0 0 0 1 5 0.0056 0.02975 0 2 1.01 0 0 0 0 0 1 3 0.00896 0.0476 0 3 1.02 0 0 0 0 0 2 6 0.00672 0.0357 0 4 1 0 0 0 0 0 2 15 0.0306397 0.0794612 0 5 1.02 0 0 0 0 0 2 21 0.0132314 0.0343144 0 6 1 0 0 0 0 0 2 22 0.01001 0.02596 0 7 1 0 0 0 18 7.1 2 23 0.0206388 0.0535248 0 8 0.98 0 0 0 28 10.17 2 7 0.0295022 0.0765112 0 9 0.99 0 0 0 10 3.3 2 18 0.03822 0.09912 0 10 0.98 0 0 0 20 7.27 2 36 0.000455 0.00118 0 11 0.98 0 0 0 20 7.24 3 4 0.00456384 0.0242454 0 12 0.99 0 0 0 26 8.52 3 8 0.0352625 0.09145 0 13 1 0 0 0 20 6.57 3 17 0.00864045 0.0224082 0 14 1.03 0 0 0 14 4.61 3 35 0.000455 0.00118 0 15 0.98 0 0 0 40 11.68 4 28 0.01630064 0.0865972 0 16 0.98 0 0 0 20 5.82 4 9 0.0186732 0.0484272 0 17 1 0 0 0 35 12.69 4 12 0.05027295 0.1303782 0 18 1 0 0 0 25 9.87 4 13 0.03069976 0.079617 0 19 0.98 0 0 0 30 7.53 4 17 0.0142506 0.0369576 0 20 0.98 0 0 0 40 10.04 4 19 0.03586401 0.09301 0 21 1 0 0 0 42 16.6 4 34 0.000455 0.00118 0 22 1 0 0 0 80 31.64 5 15 0.00728 0.01888 0 23 0.99 0 0 0 85 33.6 6 31 0.00738848 0.0392513 0 24 0.98 0 0 0 29 7.28 6 21 0.0219583 0.0569468 0 25 1 0 0 0 20 4.98 6 23 0.0219583 0.0569468 0 26 0.99 0 0 0 35 8.76 6 24 0.0281372 0.0729712 0 27 1 0 0 0 30 7.53 6 37 0.000455 0.00118 0 28 1 0 300 0 0 0 8 9 0.175266 0.0454536 0 29 1.02 0 0 0 0 0 8 10 0.0219947 0.0570412 0 30 0.98 0 0 0 35 8.76 8 11 0.053235 0.13806 0 31 1.02 0 0 0 0 0 12 14 0.0344799 0.0894204 0 32 0.98 0 0 0 25 6.25 15 16 0.02548 0.06608 0 33 1 0 0 0 35 8.76 18 20 0.02002 0.05192 0 34 1 0 0 0 42 13.8 19 20 0.02928289 0.0759424 0 35 1 0 0 0 25 9.09 20 24 0.0228046 0.0591416 0 36 1 0 0 0 50 19.75 20 25 0.0154245 0.040002 0 37 1 0 0 0 32 8.02 20 30 0.0250068 0.0648528 0 22 23 0.00455 0.0118 0 advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 189 table 2 cost of generation and load (rupee / hr.) for real 37 bus system (continued) 24 31 0.0153517 0.0398132 0 25 29 0.0336245 0.087202 0 26 29 0.0104923 0.0272108 0 27 29 0.0173628 0.0450288 0 28 29 0.00668 0.0354875 0 29 31 0.0079472 0.0422195 0 29 33 0.000455 0.00118 0 30 32 0.042345868 0.1098533 0 30 31 0.00637 0.01652 0 4.1. non-linear nature of sensitivity indices load flow is being used either for transmission network or ehv network to obtain equal sensitivities and unequal sensitivities. an inequality in curve nature is depending upon magnitude. whereas, magnitude depending on the choice of slack bus, location of generator bus and transmission line.during load flow, any bus can be assigned as a slack bus. load flow neglects longitudinal resistance, the conductance of network elements, reactive power flow and considers all voltages equal to unity. in result, the magnitude of injection/withdrawal variation at any generation bus directly influences loss compensation. lines connected to the slack bus would have different flow variations and lines away from the slack bus would have less impact. the equivalent feature is narrated in rudnick’s method [4]. the evaluation of the total impact of injection/withdrawal of electrical power is independent for each bus. amount of allocation depends on currency cost impact. at bus payments are made by the utility to participants, reflecting the proposed technique identifies the negative eu due to reactive demand. (a) non linear cupf t 1g1 for 37 bus system (b) non linear cupf t 21d10 for 37 bus system (c) non linear cupft9d7 for 37 bus system (d) non linear cuqft16d9 for 37 bus system fig. 4 nonlinear cupf curve of generation and load in 37 bus system fig. 4(a-d) shows the nonlinear sensitivity behavior curves for modified amp-mile method. the real or reactive mva sensitivities would not be identical at generator buses. it exhibits nonlinear nature of sensitivities depending upon location and topological conditions. fig. 4(a-d) shows the nonlinear sensitivity curves for mva utility factor method. the estimation and recognition pattern for mvauf’s of non-linear lines with respect to different injections/withdrawals at each bus is obtained with the help of the nr algorithm. moreover, allocated charges would not radically be stable over differing load level due to advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 190 non-linear sensitivities. patterns of sensitivities assessed for variation of p and q at all buses for different loading by employing load flow analysis. the sensitivity patterns have many advantages for a deregulated market. (a) provide price signals for the future generation/demand expansion. (b) forecast transmission pricing, if used along with eu values. (c) congestion anticipation and used to manage congestion either by curtailing the demand. (d) assist iso to carry out the day ahead scheduling in the deregulated electricity market. (a) non linear mvapuft16g1 for 37 bus system (b) non linear cupft21d10 for 37 bus system (c) non-linear cupft9d7 for 37 bus system (d) non-linear cuqft16d9 for 37 bus system fig. 5 nonlinear mvapuf curve of generation and load in 37 bus system 4.2. cost allocation andcost curve evaluate the total cost in rupee/hr by using mathematical operation of both the proposed methods. for ieee 6 bus standard system, comparison of the proposed model (partial recovery model and full recovery model) has been brought down. cost allocated (ca), remaining charge (rc), and embedded cost (ec) are to be compared for at all buses by employing different techniques. table 3 shows the comparison of all the costs including rc and % ec of each bus. by observing table 3, execution of the mva utility factor method causes a striking reduction in cost allocated to bus 1 (slack bus), as positive payments by all other methods are turning to negative payments. likewise, cost allocation is negative to bus 5 load and positive to the first generator in amp-mile method. it shows reflecting payments are made by transmission utility to load and recovered from generators, which seems unjustified. this problem gets resolved through proposed mva utility factor method using either partial recovery model or full recovery model. realization of proposed modified amp-mile and mva utility factor method proved to be superior over mw-mile method, mva-mile method, and amp-mile method. its advantages like frm of ehv networks contrasting amp-mile tackles reactive power unlike mw-mile and anticipates the direction of reactive power not like mva-mile. the cost to be allocated in modified amp-mile and mva utility factor method is assumed proportional to the length of transmission lines in rupee/hr. in ieee 6 bus system the total cost evaluated in modified amp-mile and mva utility factor methods in frm condition is 5435 rupee/hr. whereas, in prm condition, mva utility factor allocated cost is 948.137 rupee/hr. it has been observed from table 2, that 100% cost is assigned advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 191 as cost allocated or zero amount as remaining charges in modified amp-mile and mva utility factor method (frm only). all the other existing methods along with proposed mva utility factor method (prm) have a significant amount as remaining charges. hence, these methods do not allocate 100% embedded cost. the negative sign represent the return cost given by the transmission company. table 3 comparison of cost allocation in ieee 6-bus system by different methodologies under 100% loading bus no. mw-mile (rupee/hr.) mva-mile (rupee/hr.) ampmile (rupee/hr.) amp-mile (lf) (rupee/hr.) modified amp-mile (rupee/hr.) mva uf method (prm) (rupee/hr.) mva uf method (frm) (rupee/hr.) bus 1 281.5 27.1 239.31 206.0269 1001.3 -119.75 -286.9 bus 2 145.8 227.9 19.65 -99.7790 -485.1 66.96 69.1 bus 3 350.0 487.2 116.36 -152.8764 -1050.8 133.47 814.7 bus 4 254.7 411.7 100.47 253.0793 -103.1 220.202 664.0 bus 5 588.8 592.9 -13.13 440.9396 4519.0 388.798 3024.7 bus 6 553.7 400.3 2.04 271.1701 1553.6 258.456 1149.4 ca 2174.5 2146.6 462.67 918.5604 5435 948.137 5435 rc 3260.5 3288.4 4972.33 4516.4396 0 4486.86 0 %ec 40 39.5 8.51 16.90 100 17.45 100 the locational and remaining charges allocation at different loadings has been estimated using diverse cost allocation techniques. the evaluated cost allocated under the different percentage of base case (bc) loading conditions by different methodologies is shown in table 4. it has been observed that the cost allocation by employing modified amp-mile method is constant for all loading conditions. the percentage embedded cost is 100% are zero remaining charges are allocated in modified amp-mile method irrespective of loading of the system. hence, modified amp-mile method is seen to be the most excellent method for full recovery modal only, under each loading condition. before evaluating the cost of the system, check the degree of congestion at bc loading specifically for overloading, to keep the system secured. table 4 embedded cost (rupee/hr.) allocation in ieee 6-bus system by different methods at different % loading methods loadings 50% 75% 100% 125% 150% mw-mile 1488.6 1860.6 2174.5 3045.2 2980.0 rem. cost (mw) 3946.4 3574.4 3260.5 2389.8 2455 mva-mile 1288.8 1672.6 2146.6 4100.3 3371.6 rem. cost (mva) 4146.2 3762.4 3288.4 1334.7 2063.4 amp-mile (base) 190.153 252.19 462.67 713.08 1107.6 rem. cost(i-mile) 5244.8 5182.8 4972.33 4721.9 4327.4 amp-mile(lf) 882.8 847.6 918.56 1098.9 1264.1 rem. cost (amp-mile(lf)) 4552.2 4587.4 4516.44 4336.1 4170.9 mod. amp-mile 5435.0 5435.0 5435.0 5435.0 5435.0 rem. cost (mod. amp-mile) 0 0 0 0 0 any generator bus can be assigned as a slack bus for estimation of cost and to find cuf’s. consider another generator bus as the new slack bus and then cost allocation associated withthe new slack bus has been evaluated. all the costs, ca, rc, and %ec has been evaluated for the new slack bus by employing different methodologies and compare the results as shown in table 5. the utilities have a different region with significant local load and generation. the injection in a given region may cause an increment in the circuit flows all around the country. resulting tariffs are sometimes nonspontaneous with generators that are close to load centers in a given region receives high tariffs. therefore the currency cost impact of the different slack bus by implementing distinct slack bus notion is used. results for depiction on the ieee 6 bus system are given in table 4 at base case (bc) loading. embedded cost is evaluated using modified amp-mile and mva utility factor method for 37 bus system in a similar manner employed in ieee 6 bus system. frm costs were evaluated using both the above method are shown in table 6 (a) and advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 192 table 6(c). whereas, prm costs are shown in table 4 (b) for mva utility factor method only. table 4 illustrates the generation and load cost allocates at different buses for active and reactive power. the allocations by frm at all busses are given in table 6(a) and (c). table 5 cost impact (rupee/ hr) of the new slack bus at 100% base bus no. amp-mile (lf) slack bus -bus1 mod. amp-mile slack bus-bus1 amp-mile(lf) slack bus –bus 2 mod. amp-mile slack bus –bus 2 bus 1 206.0269 1001.3 60.4148 360.1 bus 2 -99.7790 -485.1 234.5645 1042.3 bus 3 -152.8764 -1050.8 -87.6418 -2317.3 bus 4 253.0793 -103.1 144.6832 -272.8 bus 5 440.9396 4519.0 344.1372 4615.5 bus 6 271.1701 1553.6 157.5987 2007.2 ca 918.5604 5435 853.7567 5435 rc 4516.4396 0 3727.4866 0 %ec 16.90 100 15.71 100 it has been observed that the payments are made by transmission utility to participants due to the counter flow of power. in 37 bus system, the total cost evaluated is 13699 rupee /hr. in modified amp-mile and mva utility factor methods (frm condition only.) whereas, in prm condition, mva utility factor allocated cost is12699 rupee/hr. in table 6 real 37 bus system frm model are recover the full allocation cost (ac) in both the technique. this result analysis represents the beneficial effect of the proposed work. the remaining charges are also calculated by the postage stamp method. compare the remaining charges cost in ieee 6 bus and real 37 bus system. the low remaining charges in real 37 bus test system are showing the good stability in pricingwheeling market. that is more beneficial for generators and consumer in the electrical energy market (real-world strategies). (a) modified amp-mile cost curve using frm in 6 bus system (b) mva utility factor cost curve using prm & frm in 6 bus system (c) modified amp-mile cost curve using frm in 37 bus system (d) mva utility factor cost curve using prm & frm in 37 bus system fig. 6 prm and frm cost curves of mva utility factor methods advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 193 table 6 cost of generation and load (rupee / hr.) for real 37 bus system (a)modified amp-mile cost (frm) (b) mva utility factor cost(prm) (c) mva utility factor cost (frm) bus active active reactive bus active active reactive bus active active reactive no. load gen load no. load gen load no. load gen load 1 0 -24761 0 1 0 7371 0 1 0 4155 0 2 0 0 0 2 0 0 0 2 0 0 0 3 0 0 0 3 0 0 0 3 0 0 0 4 0 0 0 4 0 0 0 4 0 0 0 5 0 0 0 5 0 0 0 5 0 0 0 6 0 0 0 6 0 0 0 6 0 0 0 7 306.5 0 102.1 7 69.996 0 10.63 7 352.1 0 53.52 8 1832.8 0 339.4 8 311.17 0 48.64 8 674.9 0 103.3 9 495.7 0 39.2 9 48.233 0 5.087 9 -6 0 -8.438 10 1570.8 0 308.8 10 285.67 0 42.96 10 763.2 0 110.2 11 1929.3 0 397.1 11 380.01 0 56.01 11 1153.3 0 164.8 12 1892.2 0 236 12 294.2 0 37.56 12 359.9 0 45.51 13 1459.2 0 181.8 13 160.03 0 18.95 13 358.8 0 38.64 14 1372.9 0 210.7 14 226.81 0 27.36 14 632.1 0 70.26 15 404.9 0 46.7 15 124.06 0 10.79 15 529.7 0 46.38 16 507.9 0 70.7 16 132.13 0 11.11 16 597.2 0 50.32 17 1413.5 0 157.8 17 159.57 0 29.63 17 56.7 0 22.32 18 -272.2 0 -31.5 18 127.24 0 17.02 18 237.7 0 37.08 19 -1100.4 0 -165.4 19 270.3 0 22.51 19 797.9 0 64.66 20 -52.1 0 -51.6 20 311.26 0 22.83 20 617.9 0 54.82 21 -326.2 0 -17.3 21 34.024 0 3.751 21 -56.1 0 -11.68 22 37 0 -11.5 22 132.65 0 34.6 22 59.7 0 28.67 23 209.8 0 -74.8 23 203.7 0 51.1 23 142.4 0 48.96 24 997 0 74.2 24 160.32 0 9.624 24 121.6 0 1.48 25 202.8 0 -14.9 25 122.56 0 9.513 25 238.3 0 19.57 26 1384.6 0 49.9 26 95.874 0 8.288 26 130.1 0 7.14 27 1290.4 0 54.1 27 110.22 0 8.769 27 221.2 0 12.6 28 0 11822 0 28 0 162.1 0 28 0 289.1 0 29 0 0 0 29 0 0 0 29 0 0 0 30 1441.2 0 54.3 30 161.64 0 8.622 30 -119.7 0 -35.27 31 0 0 0 31 0 0 0 31 0 0 0 32 1623.4 0 154.4 32 267.23 0 16.05 32 457.1 0 10.19 33 1252.2 0 45.4 33 47.783 0 5.438 33 -1.6 0 -0.64 34 2253.4 0 253.3 34 189.05 0 21.16 34 -38.8 0 -4.04 35 656.5 0 93.1 35 79.808 0 15.34 35 30.3 0 11.71 36 1.4 0 1.1 36 4.022 0 0.582 36 -4.9 0 -0.71 37 14.6 0 1336 37 71.246 0 1.159 37 14.6 0 -9 total 22799.1 -12939 3839 total 4580.8 7533.1 555.1 total 8321.6 4445 933.3 cost cost cost ca 13699 ca 12669 ca 13699 rc 0 rc 1030 rc 0 %ec 100 %ec 92.48 %ec 100 fig. 6 show cost curve nature of prm and frm for mva utility factor method, whereas, only frm for modified amp-mile method. fig. 6(a) and (b) are drawn by using data of table 3, whereas, fig. 6(c) and (d) are drawn by using data of table 6. the price instability significantly affects the results of both the proposed methods. fundamentally modified amp-mile and mva utility method shows different characteristics with the fluctuations in demand. therefore, transmission price and demand are the essential characteristics for the estimation of cost allocation. variations in the curve are depending on the magnitude. proposed methodologies are fair, accurate and feasible for estimation of cost if the cost allocation is prepared as per the demand. mva utility factor technique is simple in application and provides price signals. the dissimilarity in the cost curve shown in fig. 6(b) is due to prm allocation is 17.45% of the entire embedded cost and remaining 82.55% allocate through supplementary charges, whereas, frm allocated 100% embedded cost for both the methods. similarly, in fig. 6(d), frm allocates 100% embedded cost, but prm allocates 92.48% of the entire embedded cost. in prm energies due to the amount of allocation in both the models depends on circuit capacity. the decrement proportionality is with used circuit advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 194 capacity (ucc), which is always less than unity. hence, the quality of decrement may cause a disparity in the sign of allocation of both the model as shown in fig. 6. in results, current utility factor and eu’s are also used in both techniques. implementation of this technique proved to be superior over mw-mile and mva-mile method along with full recovery. table 7 shows the current utility factor and eu’s of reactive power, reflecting the direction of reactive power. through cost allocation by these existing methods appear to be uniform but due to mentioned limitations well through-out to be inexcusable. table 7 current utility factors and eu’s for reactive load at bus 34 of 37 bus system line no. 𝜕𝐼𝑙 𝜕𝑄𝑑34⁄ extent of use of load 34 line no. 𝜕𝐼𝑙 𝜕𝑄𝑑34⁄ extent of use of load 34 line no. 𝜕𝐼𝑙 𝜕𝑄𝑑34⁄ extent of use of load 34 1 0.0006 0.0020 17 -0.0001 -0.0046 33 0.0000 0.0000 2 0.0000 0.0000 18 0.0002 0.0052 34 0.0002 0.0219 3 0.0027 0.0332 19 0.0001 0.0057 35 0.0008 0.0524 4 0.0002 0.0040 20 -0.0009 0.0167 36 0.0003 -0.0481 5 0.0000 0.0000 21 -0.0005 0.2119 37 0.0001 -0.0009 6 0.0001 0.0027 22 0.0045 0.1239 38 0.0003 -0.0385 7 0.0001 0.0013 23 0.0000 0.0000 39 0.0001 0.0025 8 0.0000 0.0000 24 0.0002 0.0871 40 0.0001 -0.0021 9 0.0000 0.0000 25 0.0001 0.0124 41 0.0002 -0.0023 10 0.0002 0.0076 26 -0.0002 0.0049 42 0.0000 0.0000 11 0.0000 0.0000 27 0.0002 0.0163 43 0.0000 0.0000 12 0.0014 0.4823 28 0.0000 0.0000 44 0.0003 -0.0009 13 0.0005 0.0108 29 -0.0001 -0.0090 45 0.0001 -0.0003 14 0.0007 0.0381 30 0.0001 0.0051 46 0.0000 0.0000 15 0.0001 0..0047 31 0.0001 0.0050 47 0.0000 0.0000 16 0.0013 -0.0053 32 0.0001 0.0076 48 0.0002 0.0042 by evaluating the non-linear curve, cost allocation, remaining charges, current utility factor, and eu’s. some important factors are originated. both methods recover 100 embedded costs in a comparison to the existing method. when compare the ieee 6-bus and 37-bus system in mvapuf prm model. the cost allocation value is 17.45% and 92.48 % respectively. therefore 37-bus practical system cost allocation is more suitable as a comparison to the ieee system. so both methodologies are reliable for the practical transmission network. the non-linear nature of curve is used to assessing true portrayal of operating condition load flow has followed to develop fair allocation. the sensitivity patterns can help iso to forecast day-ahead transmission cost as well as plan for day-ahead setting up of open access electricity market. 5. conclusions in open access, electricity market allotment of embedded cost is one of the momentous facets. the two methodologies for allocation of the embedded cost of transmission network i.e. modified amp-mile method and mva utility factor method with two models: full recovery and partial recovery, has been employed in this paper.  the proposed method exploits marginal participation in the load flow framework. the nonlinear sensitivities for the current utility of active and reactive powers have been discussed in this paper. the nonlinear sensitivities in power networks which are used to anticipate congestion and transmission price forecasting.  fair cost allocation in the presence of nonlinear sensitivities is solved by employing proposed modified amp-mile methodology. it is implemented on prices and sensitivities with respect to injections/withdrawals of power in the modern electricity market.  mva utility method in two different modals i.e. frm and prm is employed for estimation of fair cost allocation. non-linear sensitivities and distinct slack bus notion are promoted to allocate the partial or entire embedded cost of the transmission network. advances in technology innovation, vol. 4, no. 3, 2019, pp. 177-196 195  results show that the wheeling charges for modified amp-mile and mva utility factor method have approached more close solutions to mw-mile, mva-mile and amp-mile methods for the 6-bus and 37-bus test system.  comparison of other existing techniques for ieee 6-bus system confirms the effectiveness of the proposed method. the impact of loading on cost allocation by different methods has also been discussed.  both methodologies also justify new distinct slack bus notion and negative payment to evaluate currency cost impact as choice of slackbus affects cost allocation.  proposed methods allocate 100% embedded cost and zero remaining charges. the outcomes of standard ieee 6-bus and real-time 37-bus systems show the validity and efficacy of the proposed techniques. conflicts of interest “the authors declare no conflict of interest.” references [1] p. m. sotkiewicz and j. m. vignolo, “allocation of fixed costs in distribution networks with distributed generation,” ieee transaction on power systems, vol. 21, no. 2, pp. 639-652, may 2006. 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[29] m. hossain, k. tushar, and c. assi, “optimal energy management and marginal cost electricity pricing in micro grid network,” ieee transactions on industrial informatics, vol. 13, no. 6, pp. 3286-3298, december 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 implementation of 20 nm graphene channel field effect transistors using silvaco tcad tool to improve short channel effects over conventional mosfets vinod pralhad tayade 1, 3, * , swapnil laxman lahudkar 2 1department of electronics and telecommunication engineering, aissms institute of information technology, pune, india 2department of electronics and telecommunication engineering, jspm’s imperial college of engineering and research, pune, india 3department of electronics and telecommunication engineering, government polytechnic, nashik, india received 17 july 2021; received in revised form 01 september 2021; accepted 02 september 2021 doi: https://doi.org/10.46604/aiti.2021.8098 abstract in recent years, demands for high speed and low power circuits have been raised. as conventional metal oxide semiconductor field effect transistors (mosfets) are unable to satisfy the demands due to short channel effects, the purpose of the study is to design an alternative of mosfets. graphene fets are one of the alternatives of mosfets due to the excellent properties of graphene material. in this work, a user-defined graphene material is defined, and a graphene channel fet is implemented using the silvaco technology computer-aided design (tcad) tool at 100 nm and scaled to 20 nm channel length. a silicon channel mosfet is also implemented to compare the performance. the results show the improvement in subthreshold slope (ss) = 114 mv/dec, ion/ioff ratio = 14379, and drain induced barrier lowering (dibl) = 123 mv/v. it is concluded that graphene fets are suitable candidates for low power applications. keywords: graphene, mosfet, silvaco tcad, graphene fet, 2d low power design, 2d-material 1. introduction conventional metal oxide semiconductor field effect transistors (mosfets) have a limitation when scaled down to nanometer channel lengths. their performance is degraded and short channel effects emerge, which degrade the overall performance of devices. the circuit designed using the scaled device consume more static and dynamic power. hence, the era of conventional mosfets has come to an end and the device design community is in search of an alternative of conventional mosfets. it is important to search for a convincing material, which can be used at small channel lengths. graphene is a promising material due to its higher mobility, better electrical conductivity, and better thermal conductivity. the implementation of this atomically thin material needs to be defined in the silvaco technology computer-aided design (tcad) tool for any further use of graphene material applications. the purpose of this study is to investigate and use the significant properties of the promising graphene material as a channel to replace conventional mosfets. the mobility of graphene material is high, and hence it can be used as a channel material for small geometry devices. the work on graphene channel fets is still in its initial stage, as it needs to further improve and optimize the ion/ioff ratio, subthreshold slope (ss), and drain induced barrier lowering (dibl) of these short channel parameters. in the present scenario, graphene fets are the demanding devices for low power, radio frequency (rf), * corresponding author. e-mail address: taydevinod@gmail.com tel.: +91-9766334676 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 biosensor circuits, and high-speed analog very-large-scale integration (vlsi) designs. one major concern for designing graphene fets is the availability of software tools because graphene is not available in conventional tcad tools such as the silvaco tcad and synopsys sentaurus tcad tools. hence, one purpose of the study is to add graphene as a user-defined material in the silvaco tcad tool, which can be used for any applications. the study is organized as follows. section 2 presents the detailed literature review. section 3 describes the design methodology used for implementation. section 4 provides the design of 100 nm fet using silicon and graphene material channels, defining the graphene material in the silvaco tcad tool. section 5 discusses the scaling of the device to 20 nm fet using silicon and graphene material channels. section 6 focuses on the results and the comparison with other published results. finally, the study is concluded. 2. literature review in 2015, international technology road map for semiconductors (itrs) discussed various emerging transistor structures in nano-scales [1]. graphene fets are one of the suitable candidates for future high-density and high-speed circuits [2]. graphene fets are designed by using top gate, bottom gate, and side gate approach to improve device parameters. various substrate materials like silicon substrates, sic substrates, and hexagonal boron nitride (hbn) substrates are reported as per the study. a bi-layer graphene sheet or graphene nanoribbon (gnr) is used to introduce the bandgap in a graphene fet due to which it becomes a suitable candidate for digital applications [3]. initially, novoselov et al. [4] extracted graphene from carbon and proposed that graphene could be the best possible metal for fet applications. in addition to the scalability to true nanometer sizes, graphene also offers linear current-voltage (i-v) characteristics, ballistic transport, and huge sustainable currents (9108 a/cm2). graphene transistors show a rather modest on-off resistance ratio, which is a natural drawback of a material having zero bandgaps [4] schwierz [5] focused on graphene transistors’ status, prospects, and problems. the author reported the classification and detailed analysis of various graphene transistors developed in recent years. the challenge of graphene fets is the opening of the bandgap of the defined size and the reliable approach compatible with standard semiconductor processing steps. for logic operations, a bandgap of 0.4 ev or more will be required [5]. marmolejo-tejada et al. [6] presented a study of gnr based fets. the authors concluded that gnr-fets can be used for switching applications, and can offer a high ion/ioff ratio and the ss near its ideal value [6]. chen et al. [7] proposed a simulation program with integrated circuit emphasis (spice) compatible model of mos type gnr-fets with doped reservoirs, currents, and charge models which closely match with numerical tcad simulations. they observed that gnr-fets are promising compared to silicon complementary metal oxide semiconductors (cmos) since these devices have either lower power or lower delay. gnr-fets are still promising candidates for low-power applications [7]. chen et al. [8] proposed a bi-layer graphene-based electrostatically doped tunnel field effect transistor (bed-tfet), and studied the operation principle of the bed-tfet and its performance sensitivity to the device design parameters. agarwal et al. [9] proposed a bi-layer graphene tunneling field effect transistor (blg-tfet) suitable for digital cmos logic circuits. a bandgap opening is induced in blg using both top-bottom asymmetric chemical doping and vertical electric field. the proposed blg-tfet shows better characteristics for ultralow-power applications, specifically in low to medium-speed applications [9]. lv et al. [10] proposed segmented edge saturation (ses) as a novel method to design high-performance tfets using smooth gnr. both high on-to-off current (ion/ioff) ratio and large ion are obtained [10]. rassekh and fathipour [11] reported a junctionless transistor (jlt) at 10 nm gate length, which is suitable for low power applications. the authors reported few parameters, i.e., ion/ioff ratio = 4.2 × 104, threshold voltage (vth) = 327 mv, dibl = 218 mv/v, ss = 109.9 mv/dec., and the comparison is carried out with silicon-on-insulator (soi) fin-shaped field effect 20 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 transistors (finfets) [11]. boukortt et al. [12] reported a soi n-channel finfet using the silvaco tool at 8 nm gate length, and demonstrated the effects of gate work function on various parameters. the authors reported few parameters such as ss = 63.13 mv/dec, ion/ioff ratio = 106, and dibl = 85.30 mv/v [12]. pravin et al. [13] demonstrated the effectiveness of using a high-k dielectric material. the authors used hfo2 material as dielectrics instead of sio2. these authors observed that dibl is reduced by 61.5%, delay is reduced by 4%, and ion/ioff ratio is equal to 109.[13]. ning et al. [14] demonstrated a flexible fet using the chemical vapor deposition (cvd) technique. the proposed fet exhibits ion/ioff ratio = 400 on a bending surface [14]. he et al. [15] studied the temperature effect on graphene fets for rf applications. the authors found that graphene fets could be used up to 200°c temperature using sic substrates [15]. tamersit and djeffal [16] reported gnr-fets using graded gate engineering. the implemented device shows considerable improvement in ss, voltage gain, and cutoff frequency as compared to normal gnr-fets [16]. in another implementation, tamersit [17] observed that in gnr-fets, short channel parameters can be improved by using the junctionless and multigate technology. the author reported the improvement in ss, dibl, and threshold voltage roll-off [17]. radsar et al. [18] reported the performance improvement in gnr-fets by changing the gate dielectrics with high dielectric coefficient material lanthanum aluminate. the authors observed the improvement in ion/ioff ratio, ss, and dibl as compared to other dielectric materials [18]. fahad et al. [19] solved analytical models from gnr-tfets using schrodinger equations. the designed form channel length is 20 nm. the authors found close agreement of ion/ioff ratio and ss with a numerical quantum simulation method [19]. the graphene and sio2 oxide interface can also degrade the performance of the device due to the mismatch of structure and tunneling of hot electrons into the oxide [20]. it leads to the degradation of drain current (id) and vth. hence, to improve these parameters, it is proposed that the use of hfo2 having high-k could be a suitable material as an oxide [21]. for the fabrication of graphene layers on silicon substrates, a rapid cvd system is used. using this system, a graphene layer having the thickness in 2 to 3 nm can be formed. this represents that the layer of graphene material on the silicon substrate offers the expected mobility for graphene channel fets. the rapid cvd fabricated the graphene material to be used as channel material, which is equivalent to 1 nm atomic thick layer. with reference to this, in the proposed research work, the graphene material thickness is considered to be 1.5 to 2 nm [22]. 3. design methodology the id of conventional mosfets depends on various parameters. as per eq. (1), it is observed that id is directly proportional to the mobility of electrons (µn) and applied drain-source voltage (vds) for n-channel mosfets. id is inversely proportional to the channel length (l). when scaling of mosfets is carried out at that time, the channel length is reduced in nanometer size and vds is also reduced. due to the reduction in vds, the overall power consumption of the device reduces, and id also degrades. hence, to improve id, the mobility of electrons can be increased, but the mobility of silicon material is limited. to increase the mobility, a new promising material graphene is used in this design, which has a mobility of 30000 cm2/v.s. due to the increase in mobility, the performance of the device can be improved. the short channel parameter ss is directly proportional to depletion capacitance (cd) and inversely proportional to oxide capacitance (cox) as per eq. (2). to improve ss to its ideal value of 60 mv/dec., cox can be reduced by changing the dielectric material used under the gate terminal. in this design, hfo2, the dielectric material is used to improve ss. the improvement in ss also improves the ion/ioff ratio of the device, which is an essential factor for the digital logic application of the device and low power consumption. dibl is another short channel effect that depends on vds and vth as per eq. (3). dibl can be controlled by improving vth, which again depends on channel materials and oxide materials. in this research work, the effect of graphene material as a channel is studied, and the simulation results are obtained using the silvaco tcad tool. the four designs are discussed in further sections. 21 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 2. ( ) . .[2( ) ] 2 ox d gs ds ds n c w i lin v vt v v l     (1) 60(1 ) d ox c ss c   (2) dd low th th high low dd dd v v dibl v v    (3) 4. design of device having 100 nm channel length 4.1. design of silicon mosfet with 100 nm channel length the silicon channel mosfet is designed by using the dimensions as per the standard examples from the silvaco tcad tool. fig. 1 shows the designed structure of 100 nm channel length device. the total length of the device in x-direction is 500 nm and the height of the device in y-direction is 65 nm, thus a proper aspect ratio is maintained. the source terminal length in x-direction ranges from 0 nm to 200 nm, and the contact of source ranges from 0 nm to 100 nm, as shown in fig. 1. the channel region ranges from 200 nm to 300 nm with a height of 15 nm. the drain region ranges from 300 nm to 500 nm, and the drain contact ranges from 400 nm to 500 nm in x-direction. a sio2 dielectric material is deposited with 2.5 nm thickness. it ranges from 175 nm to 325 nm over the channel region. a polysilicon contact of 2.5 nm thickness is used to apply gate voltage. the bulk starts from 20 nm to 65 nm in y-direction. the default body voltage is zero. fig. 1 silicon channel mosfet with 100 nm channel length 4.2. simulation results of 100 nm mosfet the designed 100 nm mosfet is simulated, and various parameters are extracted. initially, the drain current to gate-source voltage (id-vgs) characteristic is plotted. vth is extracted from this plot, the observed value is vth = 0.303v. for dibl extraction, the device is simulated for two different drain-drain voltage (vdd), i.e., vdd(min) = 0.1 v and vdd(max) = 1 v. the obtained dibl value is 0.0279 mv/v. the ss value, which decides the speed of the device, is observed to be 79.72 mv/dec (near its ideal value of 60 mv/dec). ion/ioff ratio is obtained by finding the values of ion at vdd = 1 v and ioff at vdd = 0 v. the ratio observed is 1.73e10, which is higher enough to switch off the device and for low leakage current. fig. 2 shows the id-vgs characteristics. fig. 3 shows the id-vds characteristics to plot and find the saturation slope. the three curves for three different gate voltages are plotted: vgs1 = 0.3 v, vgs2 = 0.6 v, and vgs3 = 1 v. the observed saturation slope value is 2.78e-05. from the characteristics, it is observed that the device offers a very low id for vgs1 = 0.3 v and vgs2 = 0.6 v, and offers sufficient id for vgs3 = 1 v. 22 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 4.3. design of graphene fet with 100 nm channel length the graphene material is not directly available in the silvaco tcad tool for simulation purposes. hence, the design of the graphene channel fet is implemented using the silvaco tcad tool by adding graphene as a user-defined material. graphene is an extract of carbon having very high carrier mobility and a 2-d structure. to implement graphene fet using silvaco tcad, one major issue is that graphene needs to be directly available in the tool. hence, the user needs to define a user-defined material by changing the properties of the existing material. in the silvaco tool, various materials are available which can be used as an alternative of graphene. one attempt has been reported by mobarakeh et al. [23]. a 3c-sic material is used as a graphene channel. another design using the silvaco tcad user-defined material is demonstrated by kuang et al. [24]. in silvaco tcad, three materials have the properties which are close to that of graphene material, as shown in table 1. in this work, insb is used as a base material because it has low energy bandgap and higher electron and hole mobility, which is the closest to the properties of graphene material. table 1 different material parameters which are close to graphene material [25] material eg (ev) mun (cm 2 /v.s) mup (cm 2 /v.s) nc (per cc) nv (per cc) ni (per cc) vsatn (cm/s) vsatp (cm/s) 3c-sic 2.2 1000 50 6.59e+18 1.68e+18 1.1 2.00e+7 1.00e+6 insb 0.17 78000 750 4.16e+16 6.35e+18 1.92e+16 1.00e+6 1.00e+6 inas 0.35 33000 460 9.33e+16 8.12e+18 9.99e+14 1.00e+6 1.00e+6 note: eg is energy bandgap; mun is the mobility of electronics; mup is the mobility of holes; nc is the effective density of state (conduction band); cc is cubic per centimeter; nv is the effective density of state in valence band; ni is intrinsic carrier concentration; vsatn is the saturation velocity of electrons; vsatp is the saturation velocity of holes. as per the syntax of user-defined materials, the following statement is included in the code. this statement includes the properties of the user-defined graphene material: “material material = graphene eg300 = 0.7 affinity = 4.07 mun = 30000 mup = 30000 nc300 = 4.16e16 nv300 = 6.35e18 index.file = graphene.nkuser.group = semiconductor user.default = insb”. in this statement, a .nk file for graphene material is formed by preparing a table of 499 entries of wavelength and its corresponding refractive index. as demonstrated by weber [26], the energy bandgap for this simulation is considered 0.7 ev. from these different experiments carried out by han et al. [27] and chen et al. [28], it is observed that in gnr, if the ribbon width is reduced below 20 nm, then a sufficient energy bandgap can be achieved, and hence the nanoribbon device can be used as the switching device. 1.00e-14 1.00e-12 1.00e-10 1.00e-08 1.00e-06 1.00e-04 1.00e-02 1.00e+00 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 d ra in c u rr en t (a /µ m ) gate voltage (v) 1.00e-24 1.00e-21 1.00e-18 1.00e-15 1.00e-12 1.00e-09 1.00e-06 1.00e-03 1.00e+00 0 0 .0 1 0 .0 3 0 .0 5 0 .1 0 .2 0 .3 0 .4 0 .5 0 .6 0 .7 0 .8 0 .9 1 d ra in c u rr en t (a /µ m ) drain voltage (v) si_100 nm vgs1 = 0.3 v si_100 nm vgs2 = 0.6 v si_100 nm vgs3 = 1 v fig. 2 id-vgs characteristics of si-channel mosfet (100 nm) fig. 3 id-vds with three values of vgs and y-axis with log scale 23 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 4.4. defining graphene structure fig. 4 shows the original structure of 100 nm silicon mosfet, which is modified to form the graphene fet. all dimensions are as per the silicon 100 nm design; only the channel material from 200 nm to 300 nm in x-direction and the one from 5 nm to 20 nm in y-direction are replaced with the user-defined graphene material. fig. 5 shows the id-vgs curve by varying the vgs values from 0 v to 1 v with a step of 0.1 v. it has a close agreement with conventional mosfets. fig. 6 shows the family of id-vds curve for three different gate voltages, i.e., vgs1 = 0.3 v, vgs2 = 0.6 v, and vgs3 = 1 v. this curve shows that the graphene fet enters into the saturation region and works like a normal silicon mosfet. fig. 4 structure of 100 nm graphene channel fet fig. 5 id-vgs curve for 100 nm graphene channel fet 5. design of device having 20 nm channel length 5.1. design of graphene fet with 20 nm channel length the graphene channel mosfet is designed. as shown in fig. 7, the original 100 nm device is scaled down to 20 nm device by keeping the aspect ratio. the total length of the device in x-direction is 100 nm and the height of the device in y-direction is 13 nm, thus a proper aspect ratio is maintained. the source terminal length in x-direction ranges from 0 to 40 nm and the contact of the source ranges from 0 to 20 nm. the channel region is formed between 40 nm to 50 nm in x-direction with a height of 20 nm in y-direction. the drain region starts from 60 nm and ends at 100 nm, and the drain contact starts from 80 nm to 100 nm in x-direction. hfo2 dielectric material is deposited with 2 nm thickness; it ranges from 37.5 nm to 62.5 nm over the channel region. the contact of 2 nm thickness is used to apply gate voltage. the bulk starts from 4 nm to 13nm in y-direction. the default body voltage is zero. fig. 8 shows id-vgs characteristics of the graphene fet for vds = 0.8 v, and fig. 9 shows id-vds characteristics for three different gate voltages, i.e., vgs1 = 0.3 v, vgs2 = 0.6 v, and vgs3 = 0.8 v. the device offers more id for vgs = 0.8 v. 1.00e-13 1.00e-12 1.00e-11 1.00e-10 1.00e-09 1.00e-08 1.00e-07 1.00e-06 1.00e-05 1.00e-04 1.00e-03 1.00e-02 1.00e-01 1.00e+00 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 d ra in c u rr en t (a /µ m ) gate voltage (v) 1.00e-15 1.00e-14 1.00e-13 1.00e-12 1.00e-11 1.00e-10 1.00e-09 1.00e-08 1.00e-07 1.00e-06 d ra in c u rr en t (a /µ m ) drain voltage (v) drain current (vgs1 = 0.3 v) drain current (vgs2 = 0.6 v) drain current (vgs3 = 1 v) fig. 6 id-vds characteristics for three gate voltages 24 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 fig. 7 structure of 20 nm graphene channel fet fig. 8 id-vgs curve of 20 nm graphene channel fet 5.2. design of 20 nm silicon channel mosfet the implementation of a 20 nm silicon channel mosfet is designed and simulated to compare to the results with the 20 nm graphene channel fet. the structure is shown in fig. 10. the channel is replaced with silicon material and hfo2 is used as the dielectric. in the id-vgs characteristics for vds = 0.8v, id increases linearly with an increase in vgs after vth. in the id-vds curve for vgs1 = 0.3 v, vgs2 = 0.6 v, and vgs3 = 0.8 v, the small geometry silicon device enters into the saturation region after a pinch-off point. the characteristics of the 20 nm silicon channel mosfet are embedded with the 20 nm graphene fet design in the result section. fig. 10 structure of 20 nm silicon channel fet 1.00e-07 1.00e-06 1.00e-05 1.00e-04 1.00e-03 1.00e-02 1.00e-01 1.00e+00 0.00 0.08 0.16 0.24 0.32 0.40 0.48 0.56 0.64 0.72 0.80 d ra in c u rr en t (a /µ m ) gate voltage (v) -1.00e-03 0.00e+00 1.00e-03 2.00e-03 3.00e-03 4.00e-03 5.00e-03 6.00e-03 7.00e-03 0 0 .0 1 0 .0 1 0 .0 2 0 .0 4 0 .0 8 0 .1 6 0 .2 4 0 .3 2 0 .4 0 .4 8 0 .5 6 0 .6 4 0 .7 2 0 .8 d ra in c u rr en t (a /µ m ) drain voltage (v) drain current (vgs1 = 0.3 v) drain current (vgs2 = 0.6 v) drain current (vgs3 = 1 v) fig. 9 id-vds curve for three different values of vgs 25 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 6. results and discussion 6.1. discussion of 100 nm channel length design the simulation of both the silicon channel and graphene channel fets is carried out. for the supply voltage of 1 v, it is observed that the graphene fet shows ss = 68.45 mv/dec. and the silicon fet shows ss = 79.6 mv/dec. the ss of graphene fet is close to the ideal value of 60 mv/dec. hence, it is a suitable candidate for low-power applications. another short channel parameter dibl is also reduced to a value of 202 mv/v in the graphene fet as compared to 279 mv/v in the si-mosfet, which is better for stable operation of the device. the ion/ioff ratio of graphene fet is observed equal to55962, which is still less than that of silicon mosfet, so it needs to be improved further. the id(max) of silicon mosfet is more than that of graphene fet. table 2 shows a comparison of all parameters. in the graphene fet design, by changing gate dielectric material from sio2 to hfo2, the improvement in parameters is observed. fig. 11 shows overlay characteristics of both fets. from the characteristics, it is observed that the si-mosfet offers more current for different gate voltages; hence, further scaling of these two devices is carried out and a 20 nm fet is designed to observe and improve short channel effects. from table 2, it is observed that graphene material can be used as a channel material to replace silicon because the behavior of the graphene fet is found to be identical to conventional mosfets. the id of silicon fet is more than that of graphene fet due to the large channel length and sufficient bandgap of silicon material. the ss in graphene fet for hfo2 dielectric material is observed to be 68.45 mv/decade. it is due to an increase in cox, which depends on dielectric material and oxide thickness (tox). as the dielectric constant of hfo2 is high and tox is only 2.5 nm which is low, the cox value increases. as per eq. (2), ss depends on cox. the ss decreases due to an increase in the cox value. this decrease in ss is close to the ideal value of ss. the ion/ioff ratio is still more in the silicon fet due to the high ion caused by the sufficient bandgap available in silicon material. the dibl is reduced in the graphene fet due to more control of gate voltage on channel carriers because of better conductivity of graphene material and high-k gate dielectric material. fig. 11 overlay characteristics of 100 nm si-mosfet and graphene fet table 2 comparison of silicon and graphene channel mosfets at 100 nm gate length device/parameter si-mosfet graphene fet (with sio2) graphene fet (with hfo2) channel length (nm) 100 100 100 vdd(max) (v) 1 1 1 electron mobility (cm2/v.s) 1000 30000 30000 hole mobility (cm2/v.s) 500 30000 30000 bandgap (ev) 1.08 0.7 0.7 channel material silicon graphene graphene gate dielectric material sio2 sio2 hfo2 vth (v) 0.303 0.322 0.357 subthreshold swing (mv/dec) 79.6 93.0 68.45 id(max) (a/µm) 0.000122 2.18e-08 1.69e-6 ion/ioff 1.73e10 984.21 55962.56 dibl (mv/v) 279 202 202 1.00e-24 1.00e-21 1.00e-18 1.00e-15 1.00e-12 1.00e-09 1.00e-06 1.00e-03 1.00e+00 d ra in c u rr en t (a /µ m ) drain voltage (v) si_100 nm vgs1 = 0.3 v si_100 nm vgs2 = 0.6 v si_100 nm vgs3 = 1 v gr_100 nm vgs1 = 0.3 v gr_100 nm vgs2 = 0.6 v gr_100 nm vgs3 = 1 v 26 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 6.2. discussion of 20 nm channel length design the implemented graphene channel fet and silicon channel fet at 20 nm channel length are compared as shown in table 3. it is observed that the graphene fet offers vth = 0.040 v, and silicon mosfet offers vth = 0.021 v. the observed ss is 114 mv/dec in the graphene fet and 115 mv/dec in the silicon mosfet. these values need further improvement. the id value is more in the graphene fet for vds = 0.8 v, as compared to the silicon mosfet. the observed ion/ioff ratio is 14379, which shows the improvement in the graphene fet, so it is suitable for low power applications. the observed dibl in the graphene fet is 123 mv/v, which is less than that of the silicon channel mosfet. the current work is also compared with the already published work, and it can be seen that the graphene fet shows the improvement in id(max) due to the high mobility of graphene material and dibl parameters. fig. 12 shows the comparison curve of id-vgs for vds = 0.8 v. it is observed that the graphene fet offers a high id value for the same voltage of vds as compared to the silicon mosfet. fig. 13 shows the combined curve of id-vds for three different gate voltages. the comparison shows that the graphene fet offers more id than the silicon mosfet, which is a benefit for the high-speed operation of the device. as per table 3, the id(max) is the highest as compared to others due to the excellent electrical conductivity of graphene material and higher mobility. however, due to this, there is an increase in ss, which is still lower than that of the silicon fet. the id of the silicon fet decreases due to short channel effects. the ion/ioff ratio of the graphene fet increases due to the low leakage in graphene material in “off” conditions. the high value of ion also contributes to the increase of this ratio. the dibl parameter of the graphene fet is also lower than that of the si-mosfet due to the better control of gate voltage on the channel in the short device. the id of the graphene fet is the highest among all published results shown in table 3 due to the higher mobility of graphene material. ss, dibl, and ion/ioff ratio needs to be further improved for low power applications. table 3 comparison of the parameters in graphene and silicon mosfets device si-mosfet (this work) graphene fet (this work) soi-jlt [11] finfet [12] gnr-tfet [19] channel length (nm) 20 20 10 8 20 vdd(max) (v) 0.8 0.8 0.8 0.9 0.1 electron mobility (cm2/v.s) 1000 30000 1000 1000 not mentioned hole mobility (cm2/v.s) 500 30000 500 500 not mentioned bandgap (ev) 1.08 0.7 1.08 1.08 0.289 base material silicon user-defined graphene silicon silicon graphene gate dielectric material hfo2 hfo2 hfo2 sio2 sio2 vth (v) 0.0218 0.040 0.327 subthreshold swing (mv/dec.) 115 114 109.9 63.13 27.4 id(max) (a/µm) 0.0027 0.00638 330 × 10-6 0.00001 4.4 × 10-6 ion/ioff 6401 14379 420000 106 116 dibl (mv/v) 129 123 218 85 fig. 12 comparison curve of id-vgs for vds = 0.8 v 0.00e+00 2.00e-04 4.00e-04 6.00e-04 8.00e-04 1.00e-03 1.20e-03 1.40e-03 0 0 .0 8 0 .1 6 0 .2 4 0 .3 2 0 .4 0 .4 4 0 .4 8 0 .5 6 0 .6 4 0 .7 2 0 .8 d ra in c u rr en t (a /µ m ) gate voltage (v) drain current (gr_20 nm) drain current (si_20 nm) 27 advances in technology innovation, vol. 7, no. 1, 2022, pp. 19-29 fig. 13 combined curve of id-vds for three different gate voltages 7. conclusions the silvaco tcad tool does not have an inbuilt graphene material; hence, a user-defined graphene material is added in this study. this material is formed by using the parameters of the existing materials, which are close to that of graphene, and the simulation is carried out. the first graphene channel fet with 100 nm channel length is implemented using hfo2 material as the dielectric under gate terminal, and compared with another implementation of 100 nm silicon channel fet. the results are in good agreement with each other. the high dielectric material hfo2 offers less leakage current; hence, it improves the ion/ioff ratio of the device. the graphene fet has improved ss and dibl parameters. to study the short channel effects, further scaling of the graphene fet is carried out to the 20 nm channel length. this small channel device also shows the improvement in dibl, ss, and id(max) over the 20 nm silicon fet and other published results. the saturation curves of the both are plotted and compared, and it is observed that the graphene fet provides more id as compared to the silicon mosfet. as a high ion/ioff ratio is observed, it is concluded that the graphene channel fet can be a perfect replacement for a conventional silicon mosfet at a small channel length for low power and high-speed applications. further improvement of the implemented fet using the user-defined graphene material could be achieved by using a double gate structure. conflicts of interest the authors declare no conflict of interest. references [1] the international technology roadmap for semiconductors, “international technology roadmap for semiconductors 2.0, 2015 edition, beyond c-mos,” https://www.semiconductors.org/wp-content/uploads/2018/06/6_2015-itrs-2.0-beyond-cmos.pdf, 2015. 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[28] z. chen, y. m. lin, m. j. rooks, and p. avouris, “graphene nano-ribbon electronics,” physica e: low-dimensional systems and nanostructures, vol. 40, no. 2, pp. 228-232, december 2007. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 29 template encit2010 advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 optimizing engine start systems with application to sailing/coasting and mild hybridization madhusudan raghavan * propulsion systems research lab, general motors r&d, warren, michigan, usa received 25 april 2019; received in revised form 23 june 2019; accepted 20 august 2019 doi: https://doi.org/10.46604/aiti.2020.4148 abstract engine start systems are key to providing a good customer experience for today’s drivers. considerable effort goes into ensuring a smooth and quiet engine start, especially in vehicles equipped with start/stop systems. we present two novel mechatronic starters that are designed to improve start quality by enabling faster and quieter engine starts. in the first proposed concept, the traditional alternator is replaced with a motor/generator unit that is capable of exerting positive torque on the engine as needed, in addition to the conventional power generation function. the motor/generator is selectively connected to the crankshaft via a selectable geared or belted connection to enable different operating modes. this starter executes a 400 ms faster start for a typical engine when compared to a conventional 12v starter. we also present a second starter that uses an integrated two-speed gear train to crank the engine. the cranking gear ratio is changed from the initial high ratio to a lower ratio once the engine starts to spin. this ratio change allows the starter motor to continue to operate in a favorable torquespeed zone and push the engine to a higher pre-ignition rpm than a conventional starter, resulting in a quieter, smoother start. we also present results from incorporating the belted/geared starter concept in vehicles with sailing/coasting mode as well as in mild hybrid propulsion systems. sailing/coasting mode of operation is enabled by the quick engine re-start capability of this starter allowing seamless switching between fuelled and unfuelled engine operation. such an operation could reduce fuel consumption by about 3-6% on the nedc driving cycle, without regenerative braking. one may further hybridize the propulsion system by adding a battery for storing regenerative braking energy. using such an architecture, a 6-8% fuel economy improvement on the wltp certification driving cycle may be achieved, depending on voltage and power levels implemented, as well as energy storage systems included. keywords: start/stop, mild hybrid, silent start, sailing/coasting 1. introduction transportation is the source of approximately 25% of greenhouse gas (ghg) emissions worldwide. with population growth and increased energy use and travel, transportation emissions are growing very fast [1]. these include both motor vehicles and air transport. these ghg challenges are being tackled by the introduction of low carbon fuels, electrification of the propulsion system, and increased renewable electricity generation from wind and solar. some of these initiatives are yet to see widespread adoption due to associated system cost. in this framework, light or mild electrification (under 50v) of the propulsion system appears to have mass-market potential because of the favorable value proposition ratio it offers. smooth, fast engine starts are critical elements of such mild hybrid systems. * corresponding author. e-mail address: madhu.raghavan@gm.com tel.: +1 248 930 5248 advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 2 a start/stop system switches off the engine when the vehicle comes to a stop, thereby eliminating the consumption of fuel and the release of emissions during engine idling. however, this creates the need for fast engine restart systems to achieve satisfactory tip-in response when the driver depresses the accelerator to drive away. reference [2] performs an assessment of various start/stop systems and investigates the delay in tip-in response and launch performance when the driver depresses the accelerator when the engine is off. reference [3] describes experiments to study the difference in particulate mass emissions for gdi engines with and without start/stop systems. they found that the additional starts with start/stop systems did not significantly increase the particulate mass emissions. reference [4] presents a coupled magneticthermal model to study the reason for the damage of the starter motor of a start/stop system of a city bus. reference [5] describes the testing of idle-stop systems to see whether real-world fuel savings of such systems are in line with those predicted by the epa fuel economy certification cycles. their results suggest that in many cases the idle stop systems show minimal benefits on the epa cycles but deliver considerable fuel savings during real-world operation. reference [6] describes a novel start/stop system that injects compressed air into appropriate cylinders in the engine to get the engine spinning before it is fueled and sparked. they claim that such a system could potentially replace the conventional starter. reference [7] studies the operation of engine starts and stops in electrified propulsion systems with a focus on the effects of engine temperature on engine cranking torques and start-up emissions. they suggest that it may be advisable to take into consideration engine temperature while crafting engine start/stop strategies. reference [8] describes advancements in lead-acid battery technology, in particular, enhanced flooded batteries and absorbent glass mat batteries, driven primarily by the projected growth in start/stop system market volumes. reference [9] quantifies the co2 potential of start/stop systems by comparing two diesel-powered vehicles in urban driving conditions. one of them has a conventional propulsion system and the other one has a start/stop system. co2 reductions of as much as 20% were obtained with the start/stop system. reference [10] describes a 36v belted alternator starter system with a 7 kw mgu installed on a 1.9l four-cylinder engine. this enhanced start/stop system delivers 12-14% fuel economy improvement on the ftp city cycle and about 1% improvement on the ftp highway cycle. reference [11] describes the creation of a nonlinear control algorithm to execute smooth stops and restarts on a diesel engine, wherein the cranking torques are much higher than for a gasoline engine due to the higher compression ratio. reference [12] describes a 12v belted alternator starter system that can execute engine start/stop functions as well as improve engine responsiveness by means of torque addition to the driveline during transient maneuvers. reference [13] investigates various light electrification architectures ranging from 12v start/stop systems to 48v electrified transmissions, to assess their optimality when applied to a range of vehicle types and motor/generator locations. reference [14] investigates engine start quality, nvh, and cranking speed, and presents experimental data showing that faster cranking is better. in the present work, we describe two new starter concepts that yield fast, smooth, the engine starts suitable for future products. we also show how these starters may be integrated into propulsion architectures to yield fuel economy improvements via sailing/coasting and mild hybridization. 2. mechatronic starter for geared/belted operation in this section, we describe a novel starter system with unique functional operating characteristics. it is created by replacing the traditional alternator with a motor/generator unit (mgu) of approximately the same physical size. this mgu may be used to perform the engine starting functions. since the alternator interacts with the crankshaft via the accessory belt, the mgu can also interact with the crankshaft via this same belt. we include a dual tensioner on this accessory belt as the mgu exerts a negative torque while generating electricity and a positive torque while executing engine starts or driveline torque boosting. the dual tensioner ensures proper belt operation under these different operating conditions. for situations wherein, belt-based engine starting is not advisable (e.g., in extremely cold weather when ice may form on the belt), we need advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 3 to retain the services of a geared conventional starter. however, with an innovative mechatronic arrangement, we may potentially eliminate this conventional starter by making the mgu play the role of a geared starter. such an arrangement is shown in fig. 1, with the mechatronic device of interested being indicated by the dashed rectangle. fig. 1 engine with a geared/belted mechatronic starter it is shown in considerably more detail in fig. 2 and in a kinematic diagram format in fig. 3. it is comprised of 2 solenoids which act on yokes, causing a pair of pinion gears to move outwards. as indicated via the red and blue color coding, the solenoids cause their respective pinions to move outwards when actuated, assisted by the lever action of the yokes. when the solenoids are not energized the pinions return to their default positions via return springs. the pinions are mounted on a splined shaft, so they rotate with the shaft but can also translate axially relative to the shaft, as dictated by the solenoids. this translation is coupled with a slight rotation due to the spline angle. the shaft with the splines is mounted to ground (in this case the engine block) via bearings (a revolute joint). the purpose of this mechatronic device is to selectively connect the mgu to the crankshaft flywheel when needed. the pinion gear on the right (in fig. 1) engages with a gear mounted on the mgu. the pinion gear on the left engages with the flywheel which is integral with the crankshaft. thus, this arrangement creates a geared connection between the mgu and crankshaft and the mgu can now execute a geared start similar to the conventional starter. this arrangement thus eliminates the need to carry a conventional starter in addition to the mgu. fig. 2 mechatronic devices to connect the motor/generator to the flywheel to avoid an overconstrained system, an electric clutch is introduced between the mgu and accessory belt sprocket. when the mgu is “geared” to the flywheel, this clutch is opened and the mgu does not exert any torque on the accessory belt. after the geared engine start is executed, and the solenoids are de-energized, the mgu is no longer connected to the flywheel. at this time, the clutch may be engaged to connect the mgu to the belt to allow generation or torque boosting as advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 4 appropriate. thus, the mechatronic arrangement of figs. (2)-(3) enables a selectable geared/belted connection of the mgu to the crankshaft. when conditions are favorable (moderate temperatures and humidity), the engine start may be executed via the belt side connection of the mgu to the crankshaft, without having to resort to the geared operation. since the mgu is several times more powerful than the traditional 12v starter motor, the engine starts resulting from this geared/belted arrangement are considerably faster, smoother, and quieter than conventional engine starts. additional details of the operation of this motor/generator-based starter device may be found in reference [14]. fig. 3 kinematic diagram of a mechatronic device 3. two-speed starter system next, we describe a two-speed starter that succeeds in squeezing more cranking effort out of a conventional starter motor. such motors are typically equipped with a single-speed ratio which is optimized to get the engine turning quickly. however, due to the shape of the motor’s torque-speed characteristics, the cranking torque drops rapidly as engine rpm increases. in the proposed invention, we insert a two-speed gearing between the starter motor and the crankshaft flywheel. cranking begins with a high torque ratio to get the engine turning. we then switch to a lower torque ratio, so that the motor can continue to operate in its optimal torque-speed zone and continue to push the engine past its rated pre-ignition rpm. typically ignition occurs when the engine has reached 300-400 rpm. the currently proposed system is able to spin the engine to 700-800 rpm and this results in a smoother start. there are various possible schemes to execute this two-speed gearset. in our study, we have focused on the use of a ravigneaux gearset due to its potential compactness resulting from the shared pinion between adjacent planetary gearsets. alternatively, layshaft gears and clutches could also be used to execute this speed ratio change. fig. 4 shows the steps entailed in this two-speed engine start. the starter motor begins operation along the line labeled gear ratio 1. the speed ratio change is then executed as shown by the segment labeled ratio change. the starter continues to push the engine, its operation state indicated by the line labeled gear ratio 2. note the engine rpm line with the yellow and red stars. with a conventional single-speed starter, engine ignition would occur at the yellow star, at which time the starter motor would have reached its peak rpm. by virtue of the proposed two-speed arrangement, the engine rpm can reach the red star before ignition, and starter motor rpm would still be within its feasible limits (indicated by the dashed red line at the top of the figure). the conventional starter motor generally reaches a maximum output speed of 18000 rpm.when the engine rpm reaches 400 rpm. this translates to a 5:1 ratio for the starter motor gearing, given that the starter pinion to flywheel gear ratio is approximately 15:135. for our two-speed arrangement, we use the same 5:1 ratio for the first speed and then switch to a 2.5:1 ratio for the second speed. this would allow the engine to reach approximately 800 rpm when the starter motor attains its maximum speed of 18000 rpm. for a generic 2-speed compound planetary ravigneaux gear set, we used the following advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 5 gear teeth numbers: 𝑁𝑆𝑢𝑛1 = 50 , 𝑁𝑅𝑖𝑛𝑔1 = 200 , 𝑁𝑃𝑖𝑛𝑖𝑜𝑛1 = 75, 𝑁𝑆𝑢𝑛2 = 74, 𝑁𝑃𝑖𝑛𝑖𝑜𝑛2 = 30 . in our simulations, we executed the ratio change at 280 rpm engine speed, at approximately the mid-point of the start event. for the purposes of the simulation, one may note that the engine inertia is 0.1 kg-m2 and the starter rotor inertia is 0.000241 kg-m2. the starter motor torque begins with a value of approximately 6 n-m at 0 rpm and drops linearly with speed, down to 0 n-m in the neighborhood of 18000 rpm. fig. 4 engine speed (rpm) with two gear starters fig. 5 shows a comparison between the two-speed starter and the conventional single ratio starter. the two-speed starter is able to crank the engine to approximately 800 rpm while the latter saturates at around 400 rpm. these are unfired simulations, hence the wavy behavior of the engine rpm after ignition speed is reached. the red, green, and blue traces for the novel starter result from different assumed actuation times for the speed ratio change (20, 30, and 40 ms respectively), and thus show the sensitivity to actuator capability. additional details of the operation of this two-speed starter device may be found in reference [15]. fig. 5 engine rpm for conventional vs. two-speed starter 4. application to sailing/coasting and mild hybridization of the two proposed starter systems, the first one enables a considerably faster start, but with the added cost of the alternator being replaced by a motor/generator unit. additionally, a bi-directional tensioner must be added to the front-end accessory drive belt, in order to allow driveline torque boosting operation as well as belted engine starts. in contrast, the second proposed starter enables smooth starts by cranking the engine to a higher rpm prior to ignition. in this case, the added cost is that of the two-speed gearset in place of the single ratio gearset of the conventional starter. the first proposed starter concept may be used for sailing/coasting operation as well as in a mild hybrid vehicle. advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 6 the terms “sailing” and “coasting” are used interchangeably and refer to the mode of operation when the engine is shut off and disconnected to minimize engine drag losses during decelerations. this is popular in europe and china with the high penetration of manual transmissions. when the engine is decoupled from the driveline during coasting, one possible operating strategy is to keep the engine running at idle for quick re-engagement to the driveline when the driver demands acceleration. this idle operation of the engine during coasting continues to use fuel. the proposed first concept in this paper gets around this problem, as it enables ultra-fast re-starts and thus potentially allows one to maximize the true “engine off” time periods during coasting, thus maximizing fuel economy. having a quick re-start capability allows one to re-start and reconnect the engine to the driveline with minimum delay and adequate acceleration response. coasting may be thought of as a vehicle transient state between cruising and braking. the various sailing/coasting modes of operation are shown in fig. 6. fig. 6 sailing/coasting a typical driving maneuver is divided into 6 sections or modes. in mode 1, the vehicle is initially stopped (perhaps at a traffic light) with the engine in auto stop mode. in mode 2, the driver releases the brake pedal and depresses the accelerator pedal. the engine starts and provides torque to accelerate the vehicle as indicated by the linearly increasing speed. once the vehicle reaches the desired cruising speed the driver reduces pressure on the accelerator allowing the vehicle to sail/coast in mode 3. the engine remains on but is disconnected from the driveline. in mode 4, the sailing/coasting operation is continued, but with the engine disconnected and shut off. in mode 5, the driver depresses the brake pedal to slow the vehicle down as needed. in mode 6, the vehicle continues to slow down, but with the motor/generator-based starter ready to make a quick engine re-start in case of a “change of mind” situation, wherein the driver decides to increase speed instead of slowing down (as when a traffic signal turns green). if this change of mind situation does not occur the vehicle comes to a complete stop at the end of mode 6. fig. 7 fuel consumption reduction by using sailing/coasting on a certification driving cycle advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 7 fig. 7 shows how the sailing/coasting mode may be used to save fuel on a certification driving cycle. the black line indicates stipulated vehicle speed on the driving cycle. the blue line indicates how the sailing/coasting mode may be used to approximate the sharp decelerations on the stipulated driving cycle with more gradual coasting maneuvers. this allows one to save fuel as indicated by the differences between the red curve (fuel rate for stipulated vehicle speed) and the green curve (fuel rate for the sailing/coasting approximation). note that the green fuel rate drops to zero during the sailing/coasting portions while the red curve remains non-zero on these portions. conservative estimates suggest that this type of sailing/coasting on the nedc driving cycle could save about 3-6% of the fuel consumed. this does not require a large additional battery, as we are not storing any regenerative braking energy for this mode of operation. we had mentioned earlier the ability of the motor/generator-based starter concept in belted mode to execute super-fast restarts and thus maximize fuel savings while ensuring adequate acceleration response. experimental data backing up this claim are shown in fig. 8, where we see engine rpm plots for a fired engine start using the motor/generator (blue) and the conventional starter (red). the engine rpm ramp rate achieved with the motor/generator unit far exceeds that of the conventional starter, resulting in a 400 ms faster spin up to 550 rpm. moving on from sailing/coasting, we can go one step further in mild hybridization by making the additional investment in a battery for storing regenerative braking energy. this leads to additional fuel economy gains. when the motor/generator unit of the starter is coupled to a 120 wh li-ion battery, such a system, with optimal supervisory powertrain control, can yield 6-8% of fuel economy improvement on the wltp driving cycle [12]. fig. 9 shows simulation plots of cumulative battery regeneration energy (i.e., a summation of energy flow into the battery) during the wltp driving cycle, for a 1350 kg. passenger vehicle equipped with this system. the red curve shows the results of a 12v implementation of such a system and the blue curve shows a 48v implementation. the grey curve is the vehicle speed trace during the wltp cycle. overall, approximately 1000 to 1200 kj of regenerative braking energy is captured in the battery during the driving cycle. this energy, when utilized in the propulsion system to offset 12v electrical loads as well as for driveline torque boosting (i.e., exerting electrical torque on the crankshaft via the motor, in place of mechanical torque from the engine), results in the above-mentioned fuel savings. we have been able to confirm this experimentally on instrumented test vehicles. fig. 8 motor/generator vs. a conventional starter fig. 9 cumulative regenerative braking energy into the battery for wltp 5. conclusion we have described two novel starter concepts. the first one can switch between geared and belted operation. this integrated starter enables a very fast and smooth start in belt mode compared to a conventional 12v starter. the second concept uses a two-speed starting device to crank the engine to a higher rpm prior to ignition. it is comprised of an integrated arrangement of gears and clutches that changes the over-all cranking gear ratio during the course of the start event. the two advances in technology innovation, vol. 5, no. 1, 2020, pp. 01-09 8 designs are very comparable and equally applicable to various types of automobiles. the first starter uses two solenoid actuators and sliding surfaces to move the pinions outwards to execute the belt-to-gear mode changes. the second starter uses an additional plane of gears and brakes/clutches to execute the speed ratio change during the start. both require additional packaging space compared to conventional starters. the first starter is capable of faster starts as the alternator is replaced by a motor/generator unit with more power capability than a traditional starter motor. our experiments have shown that this motor/generator-based starter is about 400 ms faster than a conventional starter. we have investigated the use of this fast start capability for sailing/coasting operation wherein the engine is disconnected and shut off during vehicle deceleration. the fast starter allows quick engine re-start and re-connection to the driveline in response to driver power demand. the use of this sailing/coasting mode of operation could save about 3-6% fuel on the nedc driving cycle. beyond sailing/coasting, one may further increase the level of mild hybridization by adding a battery for regenerative braking energy storage. in such an architecture, the motor/generator-based starter, in belted mode, enables hybrid functions such as torque boosting and regenerative braking to achieve a 6-8% improvement in fuel economy on the wltp driving cycle. conflicts of interest the authors declare no conflict of interest. table of notations apu auxiliary power unit ecu engine control unit ecm epa engine control module environment protection agency ev electric vehicle ghg gdi greenhouse gas gasoline direct injection hwfet highway fuel economy driving schedule mgu motor generator unit nedc new european driving cycle nvh noise, vibration, harshness nycc new york city cycle soc state of charge udds urban dynamometer driving schedule wltp world-harmonized light vehicle test procedure references [1] d. greene and s. plotkin, “reducing greenhouse gas emissions from u.s. transportation,” pew center on global climate change, pp. 1-80, may 2003. 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[12] m. raghavan and a. balhoff, “electrical torque addition mechanism for engines with high levels of egr,” in eucomes 2018: proceedings of the 7th european conference on mechanism science, edited by burkhard corves, philippe wenger, mathias hüsing, 2018, pp. 165-172. [13] m. raghavan, “mild electrification across a spectrum of vehicle types,” in fisita technical paper no. f2018-ehv009, 2018. [14] m. raghavan, n. bucknor, and v. donikian, “the kinematics and dynamics of engine start systems,” in iftomm asian mms conference, bangalore, 2018. [15] m. raghavan, “novel mechanisms to improve the start quality of automotive engines,” in iftomm world congress, krakow, 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 simulation and implementation of a modified anfis mppt technique bachar meryem * , naddami ahmed, fahli ahmed department of electrical engineering, hassan first university, settat, morocco received 19 nobember 2019; received in revised form 06 march 2020; accepted 06 june 2020 doi: https://doi.org/10.46604/aiti.2020.4987 abstract the maximum power point tracking (mppt) algorithms ensure optimal operation of a photovoltaic (pv) system to extract the maximum pv power, regardless of the climatic conditions. this paper exposes the study, design, simulation and implementation of a modified advanced neural fuzzy inference system (anfis) mppt algorithm based on fuzzy data for a pv system. the studied system includes a pv array, a dc/dc buck converter, the anfis controller, a proportional-integral (pi) controller, and a load. the simulation and experimental tests are carried out with the matlab/simulink software and labview, respectively. moreover, the obtained results are compared with previously published results by incremental conductance (ic) and fuzzy logic (fl) algorithms under different climatic conditions of irradiation and temperature. the results show that the proposed anfis algorithm is able to track the maximum power point for varying climatic conditions. furthermore, the comparison analysis reveals that the pv system using anfis algorithm has more efficient and better dynamic response than fl and ic. keywords: pv panel, mppt algorithm, buck converter, anfis 1. introduction nowadays, the demand for energy is constantly rising; however, the availability of fossil energy is rapidly declining. as a result, the cost of energy increasing becomes a hurdle to social development [1-2]. solar energy with multiple benefits [3] is an effective solution to the production of green energy and also an alternative source. one of the most important solar technologies is photovoltaic (pv), which comes from converting sunlight into electricity within semiconductor materials such as silicon under the pv effect [4-5]. the association of the pv cells gives a pv panel that produces direct electrical energy. it can be stored in batteries or injected into the network. hence, pv panels can be used for a stand-alone and grid-connected system [6]. however, pv energy is unstable because of its dependence on the load impedance and climatic conditions such as irradiation and temperature [7-8]. the pv cell characteristic has only one point where the power is maximum called maximum power point (mpp) [9]. as a consequence , researchers are developing approaches to extract as much power as possible from pv panels. maximum power point tracking (mppt) algorithms are used to extract the maximum power and improve the productivity of the pv system regardless of the change in climatic conditions. they are used to adjust the duty cycle (d) to a power conversion system, for example, dc/dc converters act as an impedance matching circuit between the pv array and the load [10-11]. up to today, several mppt algorithms have been used to rise above these problems. they can be classified according to the number of the used sensors, the cost, the complexity, and the efficiency. * corresponding author. e-mail address: meryem.bachar@gmail.com tel.: +2126501753; fax: +212(0)523490354 advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 231 there are two types of mppt techniques. first, the conventional mppt techniques like the perturb and observe (p&o) [12-13], incremental conductance (ic) [14-15], the look-up table [16] second, the intelligent mppt techniques such as fuzzy logic (fl) [17], the fuzzy logic type 2 (flt2) [18], neural network (nn) [19], and advanced neural fuzzy inference system (anfis). nn and fl systems are universal intelligent approximators. nns have an interesting learning ability, while fl systems are built from human knowledge and have a high capacity for description through its use of linguistic values. these advantages have suggested a hybrid solution that combines the two cited approximators: fl and nn algorithm. this hybrid solution can be called a neuro-fuzzy approach or the anfis approach. in general, the used output power of the pv panel in the anfis system is obtained after monitored the behavior of the pv panel in different climatic conditions for a long time. the objective of this paper is to predict the power of the pv panel by the fl algorithm simulations and use the obtained data in the proposed anfis system to make up for the lost time. in this study, the anfis mppt algorithm was used to extract the mpp from the pv array with a pi controller based on the fuzzy data. the authors tested the performance of the proposed algorithm and compared the simulation and experimental results using matlab/simulink environment and laboratory virtual instrument engineering workbench (labview) software. the obtained results will be compared by the fl and ic mppt algorithms results used in the previously published papers. to expose that, this paper is arranged as follows: the second section presents an electrical model of the pv cell that was used in the simulation and the effect of irradiation and temperature on the pv array. the third part gives details about the dc/dc converters, especially dc/dc buck ones. the fourth part shows the anfis mppt algorithm and explains the principle of operation of this proposed technique. the fifth section represents the simulation results with the matlab/simulink environment. the sixth part displays the experimental results with the labview software and compactrio. finally, the last part discusses and compares the results. 2. photovoltaic cell a solar cell is a basic element in the pv system. it converts the incident light into electrical energy. to model a photovoltaic (pv) panel, it is the most important to model a pv cell [20]. generally, the pv cell is presented by four elements: a current generator iph, a diode d, a parallel resistance rsh, and a series resistance rs. iph models the conversion of light radiation into electricity. d represents the pn junction. rsh symbolizes the leakage current and rs models the internal losses due to connections between cells. fig. 1 presents the equivalent circuit of the pv cell. fig. 1 the equivalent circuit of pv cell the current generated by the solar cell is obtained by eqs. (1)-(2): dph shi i i i   (1) 0 s sh v ir rq s ph sh v ir i i i e r              (2) d rs rsh iph i v advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 232 iph, i0, and q are the photodiode current, the inverse saturation current, the charge of the electron, the ideality factor of the pn junction, the boltzmann constant, and the temperature of the pv cell, respectively. the pv cell generates only 0.6v. consequently, the pv cells are connected in series or (and) in parallel to gain the desired voltage to supply the load. figs. 2-3 indicate the i-v and p-v curve of the used pv array at 1000w/m² and 30°c. fig. 2 i-v curve of the studied pv array fig. 3 p-v curve of the studied pv array the characteristic of the pv array is influenced by climatic conditions such as irradiation and temperature. fig. 4 shows the i-v and p-v curves of the used pv array for variant irradiation. fig 5 shows the pv characteristics for variant temperature during 0 and 75 °c. in figs. 4-5, it is seen that the current is produced by the pv panels increases when the irradiation increases. however, the voltage increases when the temperature decreases. (a) i-v curves of the pv array fig. 4 i-v and p-v curve of the pv array for variant irradiation and constant temperature 1 kw/m² 0.8 kw/m² 0.6 kw/m² 0.2 kw/m² 0.4 kw/m² advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 233 (b) p-v curves of the pv array fig. 4 i-v and p-v curve of the pv array for variant irradiation and constant temperature (continued) (a) i-v curves of the pv array (b) p-v curves of the pv array fig. 5 i-v and p-v curve of the pv array for variant temperature and constant irradiation 3. a dc/dc converter fig. 6 the dc/dc buck converter 1 kw/m² 0.8 kw/m² 0.6 kw/m² 0.2 kw/m² 0.4 kw/m² 75°c 50°c 25°c 0°c 75°c 50°c 25°c 0°c c s d ve l o ad l d advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 234 a dc/dc converter is used to transform the dc voltage supplied by the pv panel into a dc voltage suitable for supplying dc voltage receivers. currently, different types of dc/dc converters are used such as the buck converter, the boost converter, the buck-boost converter, and the full-bridge converter [21]. in this study, the buck converter is used to diminish output voltage as shown in fig. 6. the ve is the input voltage, s is a metal-oxide-semiconductor field-effect transistor (mosfet) controlled by the mppt controller, d is a diode, l is inductance, and c is a capacitor. when the switch s is closed, the voltage across the inductor is given by: l e sv v v  (3) the relationship between the input voltage and the output voltage of the buck converter can be found by: s ev dv (4) where d is the duty cycle with 0 <d <1. 4. adaptive neuro-fuzzy inference system mppt maximum power point tracking (mppt) algorithms are needed to extract the maximum power and improve the productivity of the pv system regardless of the change in climatic conditions. several intelligent mppt techniques exist such as nn, fl, and anfis. the advanced neural fuzzy inference system (anfis) approach is a hybrid and intelligent solution that relies on human reasoning. it combines two mppt techniques: nn and fl [22]. the learning mechanism of fl is based on conditional if-then rulescalled fuzzy rules. the main advantage of fl systems is the high capacity to interpret knowledge through its use of linguistic values. nns get inspiration from the biological neurons of brain systems and mathematical learning theories. anfis implemented a fuzzy inference system (fis) of the type takagi sugeno (tsk). it had an architecture composed of five layers as shown in fig. 7. the studied system is characterized by two inputs and one output. it is based on a fuzzy model of the tsk type with the following two rules which are represented by an adaptive network [23]. fig. 7 anfis structure the output is connected to the input by unweighted connections. each node has different functionality and applies a function to the input signals. square nodes are adaptive nodes that contain parameters, while circular nodes are fixed and do not contain parameters. each node i of the layer k (node (i, n)) has an output𝑂𝑖 𝑛 and depends on the signals of the layer n-1 and the parameters of the node (i, n) as presented in: x1 x2 y σ σ n n σ σ a1 a2 b1 b2 w1 w2 v1 v2 v1.f1 v2.f2 advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 235 1 1 1( ... , , , ...)n k k i i nko f o o a b c   (5) where the k-1 layer contains nk-1 node. the a, b, c, etc., are the parameters about this node. to understand how the anfis adaptive network works, it is recommended to understand how each layer works: (1) layer 1: in this layer, each neuron contributed to realize the fuzzy sets used in the antecedents of the rules. the model used in this work was jan's model with gaussian membership functions. the degree of membership 𝑂𝑖 1 is represented by: 1 ( )i aio x (6) where x is the input of the node i, µai is the membership function of the associated linguistic variable ai. (2) layer 2: each node received the outputs of fuzzification nodes to calculate its activation. the product of the equation made it possible to carry out the conjunction of the antecedents. the output wi of this layer can be calculated by: 1 2 , 1, 2( ) ( ) i ai bi iw x x    (7) (3) layer 3: the degree of truth vi of a given fuzzy rule was calculated by the neurons as follows: 1 2 i i w v w w   (8) (4) layer 4: during this layer, each neuron was connected to a normalization neuron and the initial inputs of the network. neurons calculated the weighted consequence 4 io of the rule by eq. (9): 4 1 2 , 1, 2( ) i i i i i ii io v f v a x b x c       (9) where vi is the output of layer 3, and fi is the first-order polynomial. (5) layer 5: a single final neuron calculated the sum of the outputs of the defuzzification neurons to deliver the y anfis output: 5 1 n i i i i o y v f     (10) jan [24] proposed a hybrid learning solution based on a gradient descent algorithm with a least-square estimate. according to the fl data, the temperature and irradiation of the pv array are the inputs for the proposed anfis model which predicts the output pv power. at the same time, the actual power delivered by the pv array was calculated by measuring the voltage and current of the pv array. the actual power and predicted power by the anfis controller represent the input of the pi controller. the error was converted into an operating signal, which was then transformed into a pwm signal using a pwm generator. the pwm signal with a frequency of 25khz controls the mosfet of the dc/dc converter. 5. simulation results the studied system was a pv installation equipped with an anfis controller. it mainly consists of a pv array, the dc/dc converter, an anfis controller, a pi regulator, and a load. the studied system on the matlab/simulink software is shown in fig. 8. advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 236 fig. 8 the global anfis system on matlab/simulink the pv array consists of six tesla solar modules (solar ts 255-p150-60). the pv module specifications given by the constructor are presented in table 1. all date was given for 1000w/m², 25°c, and 1.5 am. table 1 the specifications of the pv panel description value maximum power (w) 255 w maximum power current (a) 8.32 a maximum power voltage (v) 30.6 v short circuit current (a) 8.75 a open circuit voltage (v) 37.6 v shunt resistor (ω) 529.6538 series resistor (ω) 0.29192 module efficiency (%) 15.58 temperature coefficient of current in short circuit (%/°c) 0.0457 temperature coefficient of voltage in open circuit (%/°c) -0.3538 temperature coefficient of max power (%/°c) -0.42 the anfis controller developed in this paper comprises two inputs: irradiation (ir) and temperature (t), as well as a single output power (op), which indicated the optimal power predicted by the controller anfis as shown in fig. 9. in this paper, the authors proposed a model of sugeno inference for the generation of fuzzy rules (9 rules) in this controller. fig. 9 anfis structure with matlab/simulink advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 237 the used data in the anfis regulator was obtained by fl prediction. the fl table contained different values of inputs (ir and t). each couple of inputs corresponds to an op value. the temperature varied from 0°c to 60°c with a step of 5°c, and the irradiation differed from 1 w/m² to 1300 w/m² with a pitch of 100 w/m². the simulation of the two varied factors gives a set of data of about 168 sets that are used to train the anfis controller. each input (ir and t) has three membership functions which give nine fuzzy rules. to produce the maximum op for each input, the rules were derived according to the input and output mapping. fig. 10 shows the op for one case of ir and t level. when the irradiation is 655w/m² and the temperature is 35°c, the op is 929w/m². fig. 10 anfis rules for specific values of ir and t to investigate the performance of the pv system, three scenarios were applied to the anfis mppt system under matlab/simulink. 5.1. constant irradiation and temperature the simulation of the global system with the anfis mppt presented in fig. 11 was done under uniform irradiation (1100w/m²) and fixed temperature (30°c), which are similar to the real climatic conditions in the experimental tests. (a) pv voltage (b) pv current fig. 11 anfis mpptalgorithm (stable climatic conditions) 1 2 3 4 5 6 7 8 9 ir=655 op= 929 t=35 advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 238 (c) pv power fig. 11 anfis mpptalgorithm (stable climatic conditions) (continued) t and ir of the pv array were used as inputs of the anfis controller. fig. 11 shows respectively the voltage, current, and power of the pv system. the voltage obtained by the anfis mppt algorithm is 58.97v. the current is 25,58a, and the power is 1508w. the mpp is reached at t=0.20s. the curves are stable in the steady-state. 5.2. variable irradiation and constant temperature to verify the performance of the global system in different climatic conditions, non-uniform irradiation was applied to the input of the pv array. at the beginning of the simulation, the irradiation took 1100w/m 2 . after one second, it rapidly decreased to 250w/m 2 and returned to 1100w/m². the simulation results show the voltage, current, and power curves generated by the pv array with the anfis mppt algorithm in fig. 12. after the rapid perturbation in irradiation, the anfis controller shows a better performance in terms of response time, stability, and op. the variation of the irradiation influences the output pv current produced by the pv array, while the pv output voltage is slightly perturbed. (a) pv voltage (b) pv current fig. 12 the anfis controller (variable irradiation) advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 239 (c) pv power fig. 12 the anfis controller (variable irradiation) (continued) 5.3. constant irradiation and variable temperature to test the performance of the studied system with the modified anfis mppt algorithm, the simulation of the global system with the anfis mppt was done under constant irradiation (1100w/m²). the temperature was different from 30 to 45°c in one hour. fig. 13 reveals the simulation results in the case of variable temperature. it was observed that the voltage decreases when the temperature of the pv array decreases. while the temperature of the pv array is 30°c, the output voltage is 58.66v. the temperature increases to 45°c, then the output voltage decreases to 56.5v as shown in fig. 13. fig. 13 the output pv voltage with the anfis controller (variable temperature) the current varies from 24.78 to 24.46 a and the op from 1508.4 to 1381.9w as presented in figs. 14-15. from the previous graphs, the simulations results proved that the proposed algorithm reaches mpp in the cases of variable temperature. the previous tests confirmed that the proposed anfis mppt algorithm reaches mpp without any perturbation. it had a good performance not only in the case of stable climatic conditions, but also in the case of variable irradiation and temperature. fig. 14 the output pv current with the anfis controller (variable temperature) advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 240 fig. 15 the output pv power with the anfis controller (variable temperature) 6. experimental test to prove the performance of the proposed mppt technique practically, an experimental setup was installed. the diagram of the pv process is presented in fig. 16. fig. 16 diagram of the pv process in the experimental bench, six pv modules (solar ts255-p150-60) were connected to the dc/dc buck converter and then to the load. the temperature was sensed by the ni 9217 module (0 ω to 400 ω, pt100 rtd c series temperature input module) and the irradiation by using li-cor light sensors with ni wireless sensor networks (wsn). the voltage and the current are measured by ni 9225 (analog input module, 300vrms) and ni 9247 (analog input module, 50 arms), respectively. all collected data is given to the compacrio ni 9025 from national instruments, which controls mosfet of the dc/dc buck converter using ni 9474 (sourcing digital output, 5 to 30 v). fig. 17 experimental setup with the pv array n i 9 2 1 7 l ic o r n i 9 2 2 5 n i 9 2 4 7 n i 9 4 7 4 duty cycle pv array mosfet buck converter load 24 dc power anfis mppt in labview compactrio ni 9025 pi controller t em p er at u re ir ra d ia ti o n v o lt ag e c u rr en t advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 241 fig. 17 exposes the hardware installation of the anfis mppt system. the labview software was used in this work to program and implement the anfis mppt algorithm. it is a graphical software from national instruments, which dedicates to the system design, measurement, and control. the labview software is chosen thanks to its ease and flexibility of programming. (a) i-v curve (b) p-v curve fig. 18 p-v and i-v curves of the pv array the anfis mppt algorithm is verified via the labview environment in the case of stable and variable climatic conditions. the experimental tests were done on august 29, 2019, on a sunny day. fig. 18 presents the p-v and i-v curves of the pv array (6 solar ts255-p150-60) under 1100w/m² and 30°c. the experimental results are indicated in the figures below. 6.1. constant irradiation the experimental test of the pv system with the anfis mppt algorithm was finished under constant irradiation (1100w/m²) and constant temperature (30°c). (a) output pv voltage fig. 19 the experimental results with the anfismppt algorithm in stable climatic conditions advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 242 (b) output pv current (c) pv op fig. 19 the experimental results with the anfismppt algorithm in stable climatic conditions (continued) fig. 19 shows the pv output current, the pv output voltage, pv op, and the buck output voltage. the maximum power obtained by anfis mppt is 1403w at t=0.22s. the maximum output current is 23.93a and the maximum voltage is 58.66v. when the mpp is reached, the power remains stable. 6.2. variable irradiation (a) output pv voltage (b) output pv current fig. 20 the experimental results with the anfis mppt algorithm in variable irradiation (continued) advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 243 (c) pv op fig. 20 the experimental results with the anfis mppt algorithm in variable irradiation (continued) in this part, a variation of the incidence angle of the irradiation was made to experiment the performance of the anfis mppt algorithm in different climatic conditions. at the beginning of the test, the irradiation is equal to 1100w/m². the power increases to 500w/m² at t=3,2s and then returns to the initial value. fig. 20 displays the experimental results. it can be seen that the curves retake easily mpp without falling the track. the power differs from 1403.73w to 580w. 6.3. stable irradiation and variable temperature the experimental results are shown in fig. 21. in the test, the temperature of the pv array is heavily increasing by using a heat exchanger from 30 to 45°c in 1 hour. the output current, voltage ,and power are mainly influenced by the variation of the temperature. the voltage increases to 55.7v, and the current is 22.5a at the end of the test. the power varies from 1403.73 to 1253,25w. the results demonstrate that the proposed anfis mppt shows fast response time and good performance of tracking in the case of variable temperature. (a) output pv voltage (b) output pv current fig. 21 the experimental results with the anfismppt algorithm in variable temperature advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 244 (c) op pv fig. 21 the experimental results with the anfismppt algorithm in variable temperature (continued) 7. discussion the simulation and experimental tests prove that the anfis mppt algorithm can easily track mpp of the pv array. in the case of stable climatic conditions, the curves of the pv power, the pv current, and the pv voltage are very stable. in the variable climatic conditions, the anfis mppt shows a good performance in tracking. the anfis mppt technique combines the high learning ability of the nns and the important capacity for description through the fl systems of linguistic values. these advantages give anfis mppt good performance. the pv voltage, the pv current, the pv power, and the efficiency of the anfis mppt technique, in the case of simulation and experience, are exposed in table 2. table 2 simulation and experimental results of anfis mppt anfis mppt algorithm parameters simulation results experimental results pv voltage (v) 58.97 58.66 pv current (i) 25.58 23.93 pv power (w) 1508.4 1403.73 efficiency (%) 97.58 94.39 the efficiency ηmppt is calculated by: 100 pv mppt mpp p p    (11) where ppv is the measured output power of the pv panels, and pmpp is the maximum expected output pv power in the same conditions of t and ir. the efficiency of the proposed algorithm is 97.58% in the case of simulation, and 94.39% under the real experiment. the difference between the experimental test and simulation is justified by the losses in the conversion chain and the measurement instruments. table 3 comparison of experimental and simulation results efficiency (%) parameters simulation results experimental results anfis 97.58 94.39 fuzzy logic [13] 96.26 94.14 incremental conductance [13] 94.22 90.14 advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 245 table 3 exposes the results of the simulation and experimental test of the pv system in previously published paper [13]. the research studies the ic and the fl mppt algorithms by the same pv system used in this paper. it can be clearly realized that the efficiency of the anfis mppt is better than the ic and fl mppt techniques. 8. conclusions in this research, the design of a new anfis for mppt based on the fl data and pi controller was proposed. the fuzzy data in the anfis mppt algorithm was used to make up the lost time in the collection of the real data in classic anfis tests. the proposed technique was tested under two different climatic conditions: stable and variable t and ir to show its performance. in the simulation tests, matlab/simulink software was used, while the acquisition and the control of the proposed anfis mppt algorithm were made by the labview software and compactrio ni 9032 hardware, respectively. the voltage, current, and power curves show high performance, efficiency and robustness of the proposed anfis mppt algorithm under different cases of climatic conditions. the obtained results were compared to the previously published work with the same pv system. the comparison analysis proved that the pv system using the proposed anfis algorithm was more efficient and robust than fl and ic mppt algorithms in simulation and experimental tests. anfis is the method suggested for the application in physical structures, it presents lower energy losses. in addition, this method does not require the complete modeling of the system, thus it will be a solution for the difficult and complicated systems. in future research, a balance should be observed between the costs of implementing a pv system, its performance, and profit for commercial applications. in addition, the studied mppt algorithms can be tested in the case of a partial shading conditions of pv array and also for a grid-connected system. conflicts of interest the authors declare no conflict of interest. table of abbreviation a ideality factor ai linguistic variable anfis adaptive neuronal fuzzy inference system d duty cycle fi first order polynomial fis fuzzy inference system fl fuzzy logic flt2 fuzzy logic type 2 i node inc incremental conductance iph,id, ish, and i0 photodiode current, current diode, rsh current and inverse saturation current respectively ir irradiation k boltzmann constant k layer mpp maximum power point mppt maximum power point tracking advances in technology innovation, vol. 5, no. 4, 2020, pp. 230-247 246 nn neural networks 𝑂𝑖 𝑛 degree of membership op output power p&o perturb and observe pi proportional integral pv photovoltaic q charge of electron rs series resistance rsh parallel resistance t temperature of cell tks takagi sugeno vi degree of truth vl, ve, and vs inductance voltage, input voltage and output voltage of the buck converter wi output of the layer x input of the node µai and µbi membership functions references [1] p. 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[24] e. h. mamdani and s. assilian, “an experiment in linguistic synthesis with a fuzzy logic controller”, international journal of man-machine studies, vol. 7, pp.1-13, january 1995. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 robust lpv control for attitude stabilization of a quadrotor helicopter under input saturations seif-el-islam hasseni 1,* , latifa abdou 2 1 lmse laboratory, 2 li3cub laboratory, electrical engineering department, university of biskra, algeria received 18 march 2019; received in revised form 29 september 2019; accepted 15 october 2019 doi: https://doi.org/10.46604/aiti.2020.3953 abstract this article investigates the robust stabilization of the rotational subsystem of a quadrotor against external inputs (disturbances, noises, and parametric uncertainties) by the lft-based lpv technique. by establishing the lpv attitude model, the lpv robust controller is designed for the system. the weighting functions are computed by cuckoo search, a meta-heuristic optimization algorithm. besides, the input saturations are also taken into account through the anti-windup compensation technique. simulation results show the robustness of the closed-loop system against disturbances, measurement noises, and the parametric uncertainties. keywords: quadrotor, lpv systems, optimal weighting functions, cuckoo search, input saturations 1. introduction several researchers have focused on quadrotor aircraft because of its advantages such as vertical landing and stationary flight [1]. however, the quadrotor is a nonlinear complex vehicle and very sensible, which motivates the researchers to develop robust controllers. in this article, the development of a robust controller for the quadrotor attitude subsystem is investigated. recently, researchers have been interested in linear-parameter-varying (lpv) theory because of its advantage that allowing them to represent the nonlinear model as the quasi-lpv system. there are several approaches to develop the lpv system from its nonlinear original model. the common ones are the polytopic approach [2] and the linear-fractional-transformation (lft) [3]. in this article, the lft is used because it can exact representative the nonlinear model. on the other hand, one of the efficient robust controllers is the h∞, which is created for the linear-time-invariant systems (lti). in the lpv case, there are no frequency norms. there is a just relative gain in the l2 sense (in the time-domain). in the lti case, the l2 gain and the h∞ norm are equal. hence, the lpv method via the l2 gain concept can be seen as the extension of h∞ synthesis [4]. one of the existed problems on h∞ controller design is weighting functions’ selection. there are many structures such as loop-shaping which is proposed by mcfarlane and glover [5]. loop-shaping is the simplest and the most commonly used method [6]. the other common structure is the mixed sensitivity structure [7]. it is very hard to give a general formula for weighting functions that work in every case [8]. this problem depends on experimental skills [9], but zhou and doyle proposed guidelines to adjust the weighting functions’ parameters for a siso system [10]. in [11], the authors propose to consider each system as a combination of first and second-order sub-systems, which make it easier to find a good weighting function to be used in h∞ control methodology. yet there is no general methodology to adjust the parameters especially when performance specification is difficult to define, plus it gets more complex for mimo systems. * corresponding author. e-mail address: seif.hasseni@univ-biskra.dz advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 99 on the other side, the cuckoo search algorithm is a swarm-based optimization algorithm. it is inspired by a kind of bird (cuckoo) behavior in dumping its eggs into random nests. a cuckoo never builds its own nest but lets other species doing it. the algorithm’s essential operations are the global random walk and the local walk. the global walk is similar to practical swarm optimization (pso) and simulated annealing (sa) with lévy flight transition probability. the local walk is a differential operation with such probability, so it is similar to the differential evolution algorithm (de). therefore, each algorithm (sa, pso, and de) could be considered as a special case of the cs algorithm. conversely, cs is a good and efficient combination of sa, pso, and de in one algorithm [12]. many researchers have used a nature-inspired optimization algorithm to determine weighting functions’ parameters for the lpv system [13-14]. this approach is much more required in the mimo systems. in this article, the mixed sensitivity structure is applied, and then the cuckoo search (cs) algorithm is exploited to find optimal weighting functions’ parameters. the second point investigated in this article is the input saturation. it is a real constraint of the actuators. the actuators can’t provide additional effort although the outputs don’t reach the reference signal. such a technique called anti-windup has been used in [15]. an anti-windup compensator has been designed with the same nature and structure of lft-lpv plant to reject the input saturation effect [16]. the article’s outline is as follows; in section 2, the representation of the quadrotor attitude model as the lpv system and the synthesis controller are recalled [17]. section 3 is about a description of the cs algorithm characteristics. besides that, the optimization of the weighting functions problem for the nominal system (without considering the input saturation) is discussed in section 3.2. in section 4, the anti-windup compensator design is investigated. the simulation results will be shown in section 5, and finally, the conclusion in section 6. 2. lft-lpv controller design in this section, the control of the quadrotor’s attitude by the lpv technique is recalled [17]. 2.1. lft-lpv representation of quadrotor attitude as noticed previously, this work focusses on the rotational subsystem of the quadrotor, the framework of three degrees of freedom system is presented on fig. 1. the angles are the three degrees of freedom; roll (φ), the rotation around the x axis; pitch (θ), the rotation around the y axis; yaw (ψ), the rotation around the z axis. fig. 1 the geometric structure of the quadrotor these motions are achieved by four rotors, ( 1 4)i im  . the nonlinear dynamic model of the rotational subsystem is shown on eqs. (1)-(2). it has six states; roll, pitch, yaw; [ ]   and their derivatives; [ ]   . it has three inputs ][u u u  . advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 100 4 2 3 1 1 2 3 4 ( ) ( ) 1 ( ) y z r r x x x z x r r y y y x y z z i i j l f f i i i i i j l f f i i i i i t t t t i i                                   (1) where 1 2 3 4r         (2) the considered inputs are expressed as: 4 2 3 1 1 2 3 2 2 4 2 2 2 3 1 2 2 2 2 4 1 2 3 4 ( ) ( ) = ( ) u f f u f f u t t t t b b d                               (3) table 1 os4 parameters parameter description value unit l arm length 0.23 m b thrust coefficient 3.13 10 -5 n.s 2 d drag coefficient 7.5 10 -7 n.m.s 2 ix, iy inertia on x and y axis 7.5 10 -3 kg.m 2 iz inertia on z axis 1.3 10 -2 kg.m 2 jr rotor inertia 6 10 -5 kg.m 2 ωi rotor speed [0, 500] rad.s -1 table 1 shows the model’s parameters from the selected project, os4 [18]. by considering the assumption that the selected system is symmetric ( ),x yi i the yaw model can be linearized as: 1 z u i   (4) there are two subsystems i.e., the roll-pitch (φ, θ) subsystem and the linear one, yaw (ψ) subsystem. fig. 2 show the sheme of the quadrotor attitude. after some mathematical operations (for more details see [17]), the lpv model of the nonlinear subsystem (roll-pitch) with lft representation is presented as: 1 1 1 1 11 d p p p pp p p p a b bx x z c d w y c d d u                            (5) and p pw z (6) fig. 2 lft-lpv scheme of the quadrotor attitude zρ u wρ y quadrotor attitude θ advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 101 where the elements of the matrices in eq. (5) can be obtained by: 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 a              (7) 0 0 0 0 0 0 0 0 0 0 0 0 y z r x x p z x r y y i i j i i b i i j i i                        (8) 1 0 0 0 0 0 0 x y l i l b i                     (9) 0 0 0 1 0 0 0 1 0 1 0 0 0 1 0 0 pc              (10) 1 1 0 0 0 0 0 1 0 c        (11) 4 40 xppd  (12) 1 4 20p xd  (13) 1 2 40p xd  (14) 11 2 20 xd  (15) where the state vector t x        , the input vector t u u u     , the outputs  ty   , pz and pw are the inputs and outputs of the parameters block, 1, 2, 1, 2( ).diag p p p p  table 2 presents the parameter range of roll-pitch subsystem. the yaw subsystem is a simple double integrator system with 2 states  t  , and just one input ( ).u table 2 varying-parameters range parameter description range 1p  1[ 2, 2] .rad s 2p r 1[ 500, 500] .rad s 2.2. the controller synthesis in the h∞ controller design, either the lpv subsystem (roll-pitch) or lti subsystem (yaw) needs to interconnect the system with externl inputs (disturbances and noises) and the actuator dynamics. advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 102 the rotor’s dynamic in the selected project, [18] can be expressed as: 0.936 ( ) 0.178 1 i di act s s      (16) where i is the actual rotor speed, di is the desired rotor speed. from eq. (3), it is possible to extract the inputs’ dynamics. the actuators’ dynamic for each input ( , , )u u u   of pitch, roll, and yaw controls can be expressed as: 2( )a du act s u (17) where du is the desired control signal generated by the controller, and au is the actual control signal. fig. 3 lft-lpv representation of closed loop plant-controller as noticed before, both the plant and controller of the roll-pitch subsystem are lpv with lft representation (fig. 3). on the contrary, the yaw subsystem is a simple lti. the augmented plant (p) includes actuators dynamics, external inputs, and weighting functions. the plant’s state space is presented in eqs. (18)-(22), and the controller’s state space is expressed as: 1 2p px ax b w b w b u    (18) 1 2p p pp p p pz c x d w d w d u    (19) 1 1 11 12p pz c x d w d w d u    (20) 2 2 21 22p py c x d w d w d u    (21) p pw z (22) where x is the states vector; u is the input vector; w is the exogenous inputs; disturbances and noises; y is the measured outputs; z is the controlled outputs; pz and pw are inputs and outputs of the block, 1 1 2 2( , ,..., ).r r k rkdiag p i p i p i  1k k k k kp kpx a x b y b w   (23) 1 11 1k k k k p kpu c x d y d w   (24) 1kp kp k kp kpp kpz c x d y d w   (25) kp kpw z (26) where kx is the controller states vector, y is the outputs from the plant, u is the controller outputs, kpz , and kpw are inputs and outputs of the block parameter. zkρ zρ wkρ w u y wρ z p k θ θ advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 103 after getting the lpv model of attitude in section 2.1, establishing an interconnection between the plant and the different inputs is needed. the inputs are reference signals, disturbances, and noises. the actuator dynamic is also added by the block act 2 as shown in eqs. (16)-(17). furthermore, the weighting functions which represent the desired performance are ordered in mixed sensitivity structure by the errors ( , ,e   ) and the input signals ( , ,u   ). in this article, three types of external inputs are considered, i.e., reference signals ( , ,r   ), disturbances ( , ,d   ), and noises ( , ,n   ) as presented in fig. 4. the controller of each subsystem, the lti controller for the yaw subsystem and the lpv controller for the roll-pitch subsystem, will be designed with the same nature as the plant. fig. 4 closed-loop plant-controller of the quadrotor 3. optimal weighting functions 3.1. the cuckoo search algorithm the cuckoo search (cs) algorithm is a swarm-based intelligent algorithm. it was developed by yang and deb in 2009 [19] and inspired by the cuckoo’s behavior in laying its eggs. a cuckoo doesn’t build its own nest but selects another species’ nest to let them brood young cuckoos. in this article, a simple way of application of cs is used; a nest corresponds to a cuckoo and also to an egg. the standard cs procedure strike a balance between a local and a global random walk. the global walk is presented by lévy flight [19] where a cuckoo searches for a new nest. furthermore, there is a probability pa of cases where the host birds discover that the eggs are not theirs, so they abandon the eggs. the cuckoo seeks for a new solution (nest) far from the actual solution; that’s the local random walk. algorithm 1: improved cuckoo search 1 2 3 4 5 6 7 8 9 10 11 initialize solutions randomly; while max_generation not meet do search by fraction (pc); get a cuckoo randomly by lévy flight; evaluate its fitness fi; get a nest randomly (j) if fi is better than fj replace the worse nest(j) by the trial one; end if fraction (pa) of worse nests are abandoned and build new ones; end while p + + + + + ze zu uφ,θ,ψ rφ,θ,ψ φ,θ,ψ eφ,θ,ψ dφ,θ,ψ nφ,θ,ψ zρ wρ zkρ wkρ we act 2 . quadrotor attitude θ θ wu k advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 104 the improved cuckoo search (algorithm 1) was developed by ouaarab et al. [20-21]. its extension to the standard cs is to add a fraction pc of smart cuckoos which seek new solutions in other areas by lévy flight operation, and can be expressed as: 1 ( )t t i ix x l    (27) where l is the lévy flight function [22],  is the scaling factor. after getting a new solution (trial one), it is compared with a random one (j). if the trial solution is better than j (the worse), it should be replaced by the new solution. in addition to the fraction pc, there are other eggs with probability pa witch are abandoned by the host birds. therefore, the cuckoos search for new nests in the local area is: 1 ( )t t t i p q at i t i x s x x if r p x x otherwise         (28) where px and qx are random solutions different from ix , and s is a scaling factor. the parameters’ values are chosen on the base of the recommendation of optimal ranges from experts in the field [20], and are shown in table 3. table 3 parameters setting of improved cs parameter value max_generation 20 population size 50 pc 0.5 α 0.1 λ 1.5 pa 0.25 s 0.2 3.2. the optimal weighting functions the good choice of weighting functions significantly affects the system’s nominal performance. in [17], the selection of the weighting functions is implemented by trial-and-error. in this article, the implementation is done by an optimal algorithm (cuckoo search). the weighting functions are espressed as: 0 0 0 0 0 0 e e e e w w w w               (29) 0 0 0 0 0 0 u u u u w w w w               (30) because the pitch and the roll have the same dynamics, their functions are equal. the weighting function of error is considered as a first-order filter. the weighting function of the control is considered as a scalar gain, i.e., 1 2 1 1 e e e s w w k s         (31) u u uw w k   (32) concerning the yaw subsystem, the weighting function of the error is considered as a first-order filter. the weighting function of the control is considered as a simple gain and expressed as: advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 105 1 2 1 1 e e s w k s       (33) u uw k  (34) the parameters’ selection of the roll-pitch subsystem and yaw subsystem is achieved separately. in the optimization process, the solutions of roll-pitch problem and yaw problem can be obtained by:  1 2e us k k   (35)  1 2e us k k   (36) it should be noticed that the solutions are presented in real-coded. the optimization process of each problem is solved by the presented cs optimization algorithm in section 2. the fitness functions are the integral square of error (ise) is used for the fitness function, that is, 2 2 0 0 ( ) ( ) t t roll pitchf e d e d        (37) 2 0 ( ) t yawf e d    (38) the fitness (ise) evolutions of each criterion, eqs. (37)-(38), are presented in fig. 5 and fig. 6. the efficiency of the cs algorithm is shown by the presented convergences where the fitness of the roll-pitch subsystem (fig. 5) reaches its optimal (minimum) at 10 th generation, and the fitness of the yaw subsystem (fig. 6) reaches its optimal (minimum) at the 8 th generation. the optimal weighting functions parameters are presented in table 4. fig. 5 fitness evolution of the roll-pitch subsystem (iseφ+iseθ) fig. 6 fitness evolution of the yaw subsystem (iseψ) table 4 optimal parameters of we and wu roll-pitch weφ, weθ ke τ1 τ2 12.66 3.112 65.359 wuφ, wuθ ku=0.902 yaw weψ ke τ1 τ2 2.5 0.3388 8.8968 wuψ ku=0.28 fig. 7 presents the inverse sensitivity functions of both subsystems. the presented weights are the error weighting functions ew  and ,ew when the weights in the control criteria ( uw  and uw  ) are just scalar gains. the inverse of advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 106 sensitivity function of the roll-pitch subsystem (1 / ew  ) is a high pass filter, the steady-state error to step input ( 0.078)  , the overshoot magnitude (peak sensitivity, 1.65sm  ), and limit closed-loop bandwidth /0.1937 rad s)( b  . the inverse of the sensitivity function of the yaw subsystem (1 / ew ) is a high pass filter also, the steady-state error to step input ( 0.4)  , the overshoot magnitude (peak sensitivity, 1.55sm  ), and limit closed-loop bandwidth /0.281 rad s)( b  . these results are in line with the recommended guidelines of [10]. fig. 7 desired closed-loop performance let klpv denote the controller of the roll-pitch subsystem, and klti denote the controller of the yaw subsystem, they can be expressed as: 1 1 1 11 1 1 k k kp lpv k k k p kp kp kpp a b b k c d d c d d            (39) 2 2 2 2 k k lti k k a b k c d        (40) the augmented controller k (fig. 4) is obtained by combining the two controllers, and that is: 1 2 0 0 k k k a a a        (41) 1 2 0 0 0 kpk k k bb b b        (42) 1 2 0 0 0 k k k kp c c c c            (43) 111 2 1 0 0 0 0 k pk k k kp kpp dd d d d d            (44) in this stage, the problem of the optimal weighting functions’ parameters is solved, but the problem of the input saturation has not been considered yet. the advantage of this method is that the controller design and the anti-windup compensator synthesis can be carried out independently. the next section is to discuss the anti-windup compensator’s design step. advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 107 4. anti-windup compensator the system is a mini-drone which has actuators, rotors, with low energy consumption. if the input saturation is imposed, the controller design considering the input saturation is needed to stabilize the system. the saturation function is presented in eq. (45): ( ) m m m m m m u if u u sat u u if u u u u if u u           (45) in general nonlinear systems, hyperbolic tangent ( ( ) tanh( ))sat u u is used the approximate function of the saturation e.g., the missile control [23] and ship control [24]. many researchers have focused their attention on the anti-windup problem, hence, a modern anti-windup compensator design is developed for the lti systems called coprime factor [25]. 4.1. theoretical background the main advantage of this approach is that the controller and the anti-windup are designed independently. the anti-windup compensator has the same nature and the same representation of the plant and the controller (lft-lpv). fig. 8 general scheme of the coprime factor anti-windup the anti-windup compensator is shown in the block diagram (fig. 8). the windup’s effect is rejected by adding yd, and the plant can be created as multiplier factors. to design the factors, firstly a matrix ( )f  is created according to some lmi conditions. by putting ( ) ( ) ,m f i   it could be possible to generate the other factor ( )n  ; ( ) ( ) ( ).n g m   so, the plant ( )g  could be presented as multiplier factors; 1 ( ) ( ) ( ).g n m     therefore, the design of the anti-windup compensator is based on determination ( )n  and ( )m  of ( ).g  the key is to find ( )f  that minimize the 2l gain. for more details about computing ( ),f  see [16]. previously, the lpv controller for the nominal system was designed without considering the saturation. as mentioned, the compensator’s design is independent of the controller’s design. what’s next is the proof: by assuming ( ) ( ) ( )n g m   in fig. 8 it yields, ( ) m mom u u u u m u     (46) ( ) ( ) ( ) ( )( ( ) ) ( ) nom d m m nom y y y n u g u n u g u m u g u               (47) where nomu is the nominal input generated by the controller, mu is the actuator input. nomy is the nominal output. y is the actual output, du and dy are the outputs of the anti-windup compensator. advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 108 the anti-windup state-space is presented as: ( ) ( ) ( ) ( ) ( ) u u u u m d y yu y yu a fb b w b u z c fd d w d u aw y m u f u y c fd d w d u w z                                             (48) 4.2. the compensator design fig. 9 implemented anti-windup compensator in the case of the stabilization of the quadrotor attitude, the rejecting of the input saturation’s effect is done by the form of internal model control (imc) [26]. that means ( ) 0f   ; so, ( )m i  and ( )( ) gn   . the only output of the anti-windup compensator is dy (fig. 9). and where the augmented plant, ( )g  , contains the plant ( )p  which is the lft-lpv representation of the quadrotor attitude and the actuators function (act 2 ). from table 2, the rotor’s saturation is 10 500 .i rad s   . by combing it with eq. (3), the saturation values are presented as: (.) (7.825, 7.825, 0.375)sat diag (49) 5. simulation results to show the efficiency of the designed controller, the controller is applied to the nonlinear model itself (eq. (1)). the selected initial angles are 0 0 0 ] ] 3 3 3 [ [ t        rad, where the objective is to stabilize the quadrotor at its origin 0, 0, 0)( . in the next simulation, the nominal performance is taken without considering the disturbances. the application of the controller is done for three modes: the nominal one where no saturation is introduced; the second mode where the input saturation is introduced, and the third mode where the input saturation is introduced by adding the anti-windup compensator. fig. 10 presents the angles’ dynamics of the three modes. fig. 11 and fig. 12 present the inputs and its zoom with the three modes. the benefit of anti-windup compensation is clearly shown. the solid line presents the nominal responses (without saturation). it’s possible to observe a swift response and short settling time with impossible input (reaches 100 n). however, when the saturation is introduced without anti-windup (dotted line), it’s possible to observe a longer settling time and bigger overshoot than the nominal one. by adding the anti-windup compensator (dashed line), the responses are better than the obtained by the saturation without anti-windup compensator, and the responses are almost identical to those in the nominal responses. in fact, this is the objective of the anit-windup compensator. the efficiency of the robustness h∞ controller is shown against the external inputs and the parametric uncertainties with taking the anti-windup compensator. permanent measurement noises of 2 ( 0.034 rad)   are applied on all of the the angles. + g(ρ) ref u + um ũ yd ynom y k(ρ) n(ρ) act 2 p(ρ) advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 109 the input disturbances are introduced as impulses with 0.1 d n   in 6, 6.07][ s, 0.1 d n   in 10, 10.07][ s, and 0.02 .d n m  in 14, 14.1][ s. the simulation results are presented in fig. 13. it is observed that the stability is kept despite the presence of disturbances and noises. fig. 10 the angles responses fig. 11 the plant control inputs fig. 12 the plant control inputs (zoom) by adding 50% of the nominal values of the inertia , , , )( x y z ri i i j after 5 seconds as uncertainties, its simulation is shown in fig. 14. compared with the nominal system, it is clearly noticed that there are no big changes in the responses. in addition to disturbances and noises, the system is robust and also against the parametric uncertainties. advances in technology innovation, vol. 5, no. 2, 2020, pp. 98-111 110 fig. 13 the angles responses with presence of input disturbances and measurement noises fig. 14 the angles responses with presence of the uncertainties 6. conclusions in this article, the robust control of a quadrotor attitude has been carried out by using an lft-lpv h∞ controller. two issues are discussed. first, the weighting functions selection where an optimization meta-heuristic algorithm is exploited, cs, to provide the parameters of these functions to get optimal performances. second, the problem of the input saturation which is imposed by the actuators. this problem has been solved by using an anti-windup compensator. the advantage of this approach is that the lpv controller and the anti-windup compensator could be designed separately without any conflict in the system stability’s analysis. the simulation results showed that the system is robust and against the external inputs as well as the uncertainties. conflicts of interest the authors declare no conflict of interest. references [1] l. carrillo, a. lópez, r. lozano, and c. pégard, quad rotorcraft control. london: springer-verlag, 2013. 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[26] m. c. turner, g. herrmann, and i. postlethwaite, “incorporating robustness requirements into antiwindup design,” ieee transactions on automatic control, vol. 52, no. 10, pp. 1842-1855, 2007. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 impact of flax fiber reinforcement on mechanical properties of solid and foamed geopolymer concrete kinga korniejenko * , michał łach, maria hebdowska-krupa, janusz mikuła institute of material engineering, faculty of material engineering and physics, cracow university of technology, cracow, poland received 18 february 2020; received in revised form 02 june 2020; accepted 25 august 2020 doi: https://doi.org/10.46604/aiti.2021.5294 abstract the main objective of this study is to develop the advanced composites for civil engineering applications as material for the building industry, especially for an insulation purpose. the research processes include several steps. firstly, the prototype elements, such as bricks and elevation elements were performed from eco-friendly composite -flax fiber reinforced geopolymer. the elements were designed to take into consideration for environment. geopolymers are environmentally friendly, sustainable, and resource efficient, including energy demand. next, the wall was built from these elements and exposed during the three months in a relevant environment. the main conclusion of the research is that the kind of fibers is important for the mechanical properties of the composite, including the fact that for those different fibers could be more beneficial for different raw materials, giving higher strength properties. the significant influence on the mechanical properties of the composites has the adhesion between fiber and material used as a matrix. the adhesion depends among others on the previous treatment of the fibers. keywords: geopolymer, mechanical properties, foamed material, flax fiber 1. introduction the background for the article is a pressure for the change of the traditional economy that is based on a linear approach to a so-called circular economy in recent years. the main principle of the circular economy is designing out waste and pollution. the rational management of natural resources and the usage of waste materials are getting more and more important. it is also supported by the growing ecological awareness of society, including the consciousness of sustainable development [1-2]. one of the most promising technologies for a circular economy is the geopolymerization with using waste streams. this technology is dedicated to the construction industry. it has a much lower carbon footprint than the technology of manufacturing traditional construction materials [1, 3]. the geopolymer synthesis also enables one to use waste, such as mining tiles or industrial by-products as a raw material for manufacturing new products in low energy and low emission processes [4-5]. one of the limitations for the wide usage of this technology in construction industry is the brittle fracture behavior of the received materials and their relatively low tensile as well as flexural strength [1, 6]. in order to improve tensile and flexural strength, it is possible to reinforce the geopolymer matrix by fibers [2-3]. from a mechanical point of view, reinforcement by fibers is an efficient method to improve material properties, for instance, fracture toughness. the fibers reduce the general effects of cracking, limit the widths of the occurring cracks, especially the propagation of micro-cracks, suppress all brittle * corresponding author. e-mail address: kinga.korniejenko@pk.edu.pl tel.: +48 609974988 https://context.reverso.net/t%c5%82umaczenie/angielski-polski/need+for+a+change advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 12 behavior, and enhance ductility [1, 3]. the fibers additions also increase the flexural strength of composites. the fibers improve energy absorption and resistance to deformation [3, 7-9]. in particular, the introduction of short fibers due to their easy fiber dispersion and fiber shape factor; it is an effective way to strengthen geopolymer materials [3]. currently, the reinforcements used in geopolymer composites are usually based on inorganic fibers, such as carbon or glass fibers [3, 10] or synthetic fibers [11]. however, the new research direction usage of eco-friendly materials is clearly visible. from the environmental point of view, the addition of natural fibers is particularly beneficial [1, 12]. this solution is an environmentally friendly alternative to inorganic fibers [1, 13]. nevertheless, natural fibers usually have lower mechanical properties. it does not always allow their desired applications. natural fibers have lower dimensional repeatability than artificial fibers, but these fibers have also many advantages [14-15]. the most important features are: reduction of the environmental impact (closing important life cycles, including co2), low cost of production, low density; the fibers are usually renewable in a short time, non-toxic, and easy to process [1, 16]. the research shows natural fibers could replace the conventional ones in many applications; and gives added value, especially reduction of greenhouse gas emissions and negative environmental impacts [1-2]. contemporary, the flax is one of the most popular fibers used as reinforcement to geopolymer matrix [17]. the research was made on the matrix based on dehydroxylated kaolinite-type clay (new zealand halloysite imerys premium grade) [18], low calcium fly ash (from the eraring power station in nsw) [19-20], fly ash with nano-clay particles [21-22]. the flax fibers were added in an amount: 4 10 wt%. the research results pointed out that mechanical properties are improved by fiber addition, especially flexural strength [17, 23]. the other research shows the possibility of using the geopolymers reinforced by short flax fibers in additive manufacturing technology [24-26]. there were several attempts to investigate foamed geopolymers reinforced by fibers. most of the research was dedicated to reinforcement by artificial fibers such as carbon [27-28] or glass [29-30], including waste products [29-30]. some of the investigations have been done on the composites with natural fibers such as hemp [31-32], abaca [33], cellulose [34-35] and jute [36]. the mineral fibers; for example, basalt have been also tested [28, 37]. the hemp (cannabis sativa) fiber is one of the most widely applied cellulosic fibers as reinforcement in different kinds of composites [31]. the two amounts of short hemp fibers were applied 1.13 and 4.53% [32]. the results show good bonding between matrix and reinforcement, good stability to the thermal variation and improvement of mechanical properties [32]. the research conducted with abaca fibers shows its improving properties [33], including increasing compressive strength and flexural ranged from 19.6 mpa to 36.8 mpa and 2.4 mpa to 6.3 mpa, respectively [33]. the addition of jute fibers also positively influenced on mechanical properties, flame, and water resistance [37]. the investigation with cellulose shows the positive influence of this addition on ph and the possibility of applying this material for eco-friendly pots [34-35]. the flax fibers in foamed geopolymers were only investigated as an addition to long fibers [36]. the results show the positive effect of the addition to flax fibers on impact bending and flexural strength [38]. additionally, the flax fibers were compared with basalt fibers (both were added in amount 2.16 wt%). the results show a different pattern of failure mechanisms dependent on applied reinforcement [38]. the main purpose of the provided research is to develop the advanced composites for civil engineering applications, as material for the building industry. this paper shows the possibilities of using waste streams coming from energy industry (fly ashes and agriculture waste) and short flax fibers (residues for linen production), as raw materials to produce high-added value lightweight and low thermal conductivity geopolymer composites, including foamed products. these kinds of materials could be used as the advanced composites for civil engineering applications, as a construction material as well as insulation one and also for rehabilitating deteriorated concrete [39]. the previous study does not include semi-industrial tests for the foamed geopolymers reinforced flax fibers [40-41]. advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 13 2. materials and methods 2.1. materials two kinds of materials have been prepared: solid and foamed. the solid geopolymers based on the fly ash from the chp plant in the city called skawina (lesser poland region, poland) and sand in ratio 1:1. this fly ash has the physical and chemical properties that support the geopolymerization process [42-44]. the second geopolymers according to the metakaolin and sand in ratio 1:1. both kinds of samples were reinforced with 1% by mass of flax fibers. in order to reinforce, the following flax fibers were applied as compositions to solid materials: (1) raw flax fiber shortened (raw straw). (2) long flax fiber after dew retting. (3) cottonized flax fiber. the foamed materials the following flax fibers were applied to: (1) cottonized flax fiber internal layer. (2) shortened flex fiber after water retting external and internal layer. (3) short flax fiber external layer. 2.2. samples preparation samples were prepared using sodium promoter, fly ash or metakaolin, sand, and various flax fibers (each 1%, by mass of the composite). the process of activation has been made by a 10m sodium hydroxide solution combined with the sodium silicate solution (liquid glass at a ratio of 1:2.5). the geopolymers were produced using technical sodium hydroxide flakes and an aqueous sodium silicate solution of r-145 (module 2.5), with a molar density of about 1.45 g/cm 3 . the tap water was used instead of the distilled one. in the case of the foamed plated, the hydrogen peroxide has been used 3.5% for metakaolin and 2% for fly ash based geopolymers. the alkaline solution was prepared by pouring the aqueous solution of sodium silicate over the solid sodium hydroxide. the solution was mixed and allowed to equilibrate until a constant concentration and temperature were achieved. it took nearly 2 hours. the fly ash or metakaolin, sand, alkaline solution, and fibers were mixed for about 15 minutes by using a low-speed mixing machine (to receive the homogeneous paste). on this stage for the foamed materials, a proper amount of hydrogen peroxide was introduced and continuously mixed for approximately 1 min. after the mixing process was complete, the material was poured into a mold and exposed to a temperature of 75 °c for 24 hours. after the heating process, the elements were dismantled and stored under laboratory conditions for a period of 28 days to obtain the full strength. the following kind of samples were prepared (table 1. and table 2.): (1) bricks-solid material  metakaolin with a cottonized flax fibre.  metakaolin with a long flax fibre after dew retting.  metakaolin with a raw flax fibre shortened (raw straw).  fly ash (fa) with a cottonized flax fibre.  fa with a raw flax fibre-shortened (raw straw). the detailed information about composition of prepared samples solid bricks is included in table 1. advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 14 table 1 composition of the solid samples bricks no. sample 1 metakaolin with a cottonized flax fiber 2 metakaolin with a long flax fiber after dew retting 3 metakaolin with a raw flax fiber shortened (raw straw) 4 fly ash (fa) with a cottonized flax fiber 5 fa with a raw flax fiber shortened (raw straw) (2) elevation plates-the internal layer (solid material, ca. 1 cm) and external layer (foamed material, ca. 4 cm) a sketch of the elevation plate are presented in fig. 1:  external layer: metakaolin with the shortened flex fibre after water retting, internal layer: metakaolin with the shortened flex fibre after water retting (metakaolin: sand ratio 0.85:0.15, hydrogen peroxide 3.5%).  external layer: fa with the short flax fibre, internal layer: fa with the cottonized flax fibre (fa: sand ratio 0.75:0.25, hydrogen peroxide 2.0%).  external layer: fa with the shortened flex fibre after water retting, internal layer: fa with a shortened flex fibre after water retting (fa: sand ratio 0.85:0.15, hydrogen peroxide 2.0%). fig. 1 sketch of the elevation plate the detailed information about composition of prepared samples-elevation plates is included in table 2. table 2 composition of the elevation plates no. sample external layer sample internal (foamed) layer h2o2 1 metakaolin with a shortened flex fiber after water retting metakaolin with a shortened flex fiber after water retting (metakaolin: sand ratio 0.85:0.15) 3.5% 2 fa with a short flax fiber fa with a cottonized flax fiber (fa: sand ratio 0.75:0.25) 2.0% 3 fa with a shortened flex fiber after water retting fa with a shortened flex fiber after water retting (fa: sand ratio 0.85:0.15) 2.0% fig. 2 the wall made from bricks and elevation plates – first layer fig. 3 the wall made from bricks and elevation plates build on the university campus the both prototype solutions are presented in fig. 2 bricks (small elements) and elevation plates (large elements). in fig. 2, there were two solid bricks-lower based on metakaolin (white color), upper-based on fly ash (gray color). the brick size was: advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 15 25 cm × 12 cm × 5 cm. the plate’s size was: 40 cm × 24 cm × 5 cm (fig. 1). the gray elevation plates based on the fly ash reinforced by flax fibers and white elevation plates based on metakaolin reinforced by flax fibers are also shown in fig. 2 (right site). eventually, the two products have been used for creating the prototype wall (fig. 3) for testing in a relevant environment. the wall was placed on the campus of the cracow university on technology (jana pawła ii street, cracow) and left on the open-air for 3 months. next, it was demolished and the chosen parts were investigated according to mechanical properties. 2.3. methods compressive strength tests were carried out according to the methodology described in the standard en 12390-3 (‘testing hardened concrete. compressive strength of test specimens’), because of the lack of separate standards for geopolymer materials. the tests involved cubic samples: 50 × 50 × 50 mm. the samples have been cut from large plates previously prepared (wall elements). tests were performed on a concrete press matest 3000kn with speed of 0.5 [mpa/s]. bending tests were carried out according to the methodology described in the standard en 12390-5 (‘testing hardened concrete. flexural strength of test specimens’), because of the lack of separate standards for geopolymer materials. the tests involved prismatic samples: 50 × 50 × 200 mm (space between supporting points 150 mm). the samples have been cut from large plates previously prepared (wall elements). tests were performed on a universal testing machine-matest 3000kn with speed of 0.05 mpa/s. the calculations were based on the following equation: 3 1 2 cf fl f d d  (1) where3 fcf compressive strength, mpa f maximal load, n l space between supporting points, mm (for conducted tests: 140 mm) d1, d2 sample dimensions, mm 3. experimental results and discussion 3.1. compressive strength the results of the compressive strength tests are shown in table 3 and table 4. table 3 results of compressive strength tests: bricks-solid material no. sample mpa 1 metakaolin with a cottonized flax fiber 66.4 2 metakaolin with a long flax fiber after dew retting 67.6 3 metakaolin with a raw flax fiber shortened (raw straw) 42.9 4 fa with a cottonized flax fiber 58.0 5 fa with a raw flax fiber shortened (raw straw) 90.8 the tests were provided on minimum of 6 samples. the compressive strength test results achieved for bricks (solid material) were between 42.9 to 90.8 mpa. the received values for all types of materials are better than for conventional concrete. the best results were achieved for a fly ash based geopolymer with the raw flax fiber 90.8 mpa. the results were drastically different than for the geopolymer concrete based on the metakaolin with the raw flax fiber-shortened (raw straw) advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 16 1% by mass. in the case of the cottonized flax fiber, better results were received for the metakaolin basedmatrix than for fly ash based one. the reverse results were achieved for composites reinforced by raw straw fibers. the better results were for fly ash based geopolymer than metakaolin based material. the investigation was also provided on elevation plates that consist of the foamed material. the plates included elevation part with the solid material and foamed one isolation layer (fig. 4). the grey elements are elevation plates based on the fly ash reinforced by flax fibers in fig. 4. there are visible fibers agglomeration (marked in red arrow). the agglomeration is probably the consequence of not effective mixing process during material manufacturing. it could have an influence on material properties. the white elevation plates based on the metakaolin reinforced by flax fibers are also shown in fig. 4. the layers have been produced with similar materials but based on the metakaolin. the material was also reinforced by flax fibers. the plates did not need additional join between the layers geopolymer binder bounded them. fig. 4 the elevation plates with visible layers and agglomeration of fibers the mechanical properties for foamed samples are presented in table 4. table 4 results of compressive strength tests: elevation plates foamed material no. sample external layer sample internal (foamed) layer h2o2 mpa 1 metakaolin with a shortened flex fiber after water retting metakaolin with a shortened flex fiber after water retting (metakaolin: sand ratio 0.85:0.15) 3.5% 6.8 2 fa with a short flax fiber fa with a cottonized flax fiber (fa: sand ratio 0.75:0.25) 2.0% 6.9 3 fa with a shortened flex fiber after water retting fa with a shortened flex fiber after water retting (fa: sand ratio 0.85:0.15) 2.0% 4.3 the mechanical properties of foamed materials are much lower than solid ones. the same mechanism is presented for all formed materials. the results of compressive strength tests for elevation plates are in range: 4.3 6.9 mpa. the lowest results of compressive strength are for the geopolymer concrete based on fly ash with the shortened flex fiber after water retting 1% by mass. it is almost 38% lower than for other investigated materials based on the metakaolin and fly ash. the pours in foamed layers are open. 3.2. flexural strength the results of the flexural strength tests are shown in table 5 and table 6. the best results were achieved for geopolymer concrete based on the metakaolin with different fibers. this value is definitely better than for traditional cements. as the same as in the case of compressive strength, the foamed materials have much lower properties than solid ones. the flexural strength test results for bricks were between 7.2 and 10.7. the highest value was received for the metakaolin with the cottonized flax fiber 10.7 mpa. the results of flexural strength tests for elevation plates are in the range 0.05 0.86 mpa. however, the results are comparable or even better than other foamed materials accessible on the market, especially foamed organic polymers. the provided research did not show any deterioration process. advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 17 table 5 results of flexural strength tests: bricks solid material no. sample mpa 1 metakaolin with a cottonized flax fiber 10.7 2 metakaolin with a long flax fiber after dew retting 10.6 3 metakaolin with a raw flax fiber shortened (raw straw) 7.2 4 fa with a cottonized flax fiber 7.6 5 fa with a raw flax fiber shortened (raw straw) 9.4 table 6 results of flexural strength tests: elevation plates foamed material no. sample external layer sample internal (foamed) layer h2o2 mpa 1 metakaolin with a shortened flex fiber after water retting metakaolin with a shortened flex fiber after water retting (metakaolin: sand ratio 0.85:0.15) 3.5% 0.86 2 fa with a short flax fiber fa with a cottonized flax fiber (fa: sand ratio 0.75:0.25) 2.0% 0.05 3 fa with a shortened flex fiber after water retting fa with a shortened flex fiber after water retting (fa: sand ratio 0.85:0.15) 2.0% 0.65 3.3. the effect of flax fibers addition the article presents the impact of flax fiber reinforcement on the mechanical properties of solid and foamed geopolymer concrete. the prototype elements such as bricks (made from the solid material) and elevation elements (plates including solid and foamed parts) were manufactured and investigated. the two kinds of raw materials have been tested (fly-ash and metakaolin). the research on the mechanical properties compressive and flexural strength were conducted. the compressive strength results for the new materials (solid) were between 42.9 and 90.8 mpa. these values were achieved for the samples with the raw flax fibers shortened (raw straw). the results depended on used raw materials. the other tendency was observed for the samples reinforced by the cottonized flax fibers. in this case, the material based on the metakaolin had a higher compressive strength 66.4 mpa, compared with the samples where fly ash was applied as a raw material 58.0 mpa. the same tendency was noticed in the results of the flexural strength test. for the samples reinforced by the raw flax fibers-shortened (raw straw), better results were achieved for the material based on fly ash 9.4 mpa than for based on the metakaolin 7.2 mpa. the behavior of the material reinforced by cottonized flax fibers for the flexural strength test was similar to the results of the compressive strength test. the composite based on the metakaolin had higher values for the flexural strength 10.7 mpa than the material based on fly ash 7.6 mpa. it shows that the kind of fiber is important for the mechanical properties of the composite, including the fact that for the different raw materials different fibers could be more advantages. the significant influence in this case has the adhesion between the matrix and reinforcement. the adhesion is depended among others on the previous treatment of the fibers. the significant meaning could have also the reaction between fiber and material used as a matrix. the elevation elements (plates including solid and foamed parts) reinforced by the shortened flex fiber after water retting were also compared. the plates based on the metakaolin have better mechanical properties than based on the fly ash. the values for the plates based on the metakaolin were 6.8 mpa for compressive strength and 0.86 mpa for flexural strength. for the composition based on the fly ash, the relevant values were 4.3 mpa and 0.65 mpa, respectively. the different amount of hydrogen peroxide applied in these compositions was not consider, but a larger amount of hydrogen peroxide was added to the material based on the metakaolin; therefore, this material should potentially have lower mechanical properties. 4. conclusions the research shows the possibility of manufacturing the products for construction industry based on the eco-friendly materials. the composites comprise the waste flax fiber and the reinforced geopolymer concrete. the geopolymers includes advances in technology innovation, vol. 6, no. 1, 2021, pp. 11-20 18 the fly ash as well as the metakaolin. the new products were designed to take into consideration for environment, including the energy efficiency, reduction of carbon footprint, waste reduction, and development of a circular economy. the new composites have comparable properties with the results achieved for traditional foamed and solid building materials. the main conclusion of the research is the kind of fibers is important for the mechanical properties of the composite, including the fact that for that different fibers could be more beneficial for different raw materials, giving higher strength properties. the significant influence on the mechanical properties of the composites has the adhesion between fiber and material used as a matrix. the adhesion depends among others on the previous treatment of the fibers. the contemporary research gives promising results, but further research is required. the practice applications need further tests to optimize the mechanical properties of the composites as well as investigate the other properties such as water absorption and resistance for a different environments, including long-durability issues. the lca analysis of the chosen products will be also desirable. acknowledgement this work has been financed by the national centre for research and development in poland under the grant: low thermal conductivity geopolymer foams produced with industrial wastes as an innovative material for circular economy (lider/31/0168/l-10/18/ncbr/2019) and the eranet-lac 2nd joint call (http://www.eranet-lac.eu) within the framework of the grant: development of eco-friendly composite materials based on 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[44] m. łach, j. mikuła, w. t. lin, p. bazan, b. figiela, k. korniejenko, “development and characterization of thermal insulation geopolymer foams based on fly ash,” proceedings of engineering and technology innovation, vol. 16, pp. 23-29, august 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 6___aiti#8434__66-76 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 cpw-fed penta band monopole antenna for multiservice wireless applications raj kumar 1, 2, * , yedukondalu kamatham 3 , samineni peddakrishna 4 , ajitha gaddam 5 1 department of electronics and communication engineering, shri jagdishprasad jhabarmal tibrewala university, rajasthan, india 2 department of electronics and communication engineering, swami vivekananda institute of technology, secunderabad, india 3 department of electronics and communication engineering, cvr college of engineering, hyderabad, india 4 school of electronics engineering, vit-ap university, amaravati, india 5 department of electronics and communication engineering, institute of aeronautical engineering, hyderabad, india received 06 september 2021; received in revised form 17 october 2021; accepted 18 october 2021 doi: https://doi.org/10.46604/aiti.2021.8434 abstract a compact triple t-shaped stub with meander loaded strip antenna for penta band applications is proposed. the rectangular patch antenna with meandered and open-ended slot cuts is utilized to realize four operating bands at 2.45 ghz, 3.1 ghz, 5.3 ghz, and 6.5 ghz with an impedance bandwidth of 400 mhz (2.15-2.550 ghz), 1000 mhz (2.7-3.7 ghz), 200 mhz (5.4-5.6 ghz), and 200 mhz (6.4-6.6 ghz), respectively. for an additional resonance frequency, the length of the central t-shaped stub is slightly modified which causes the variation in the current distribution. as a result, the resonance frequency of 5.5 ghz is divided into two resonance frequency bands which are operating at 5.25 ghz and 5.85 ghz with an impedance bandwidth of 100 mhz (5.25-5.35 ghz) and 200 mhz (5.75-5.95 ghz), respectively. furthermore, a parametric reflection coefficient and surface current distribution analysis is carried out to understand the strip and slot behavior at resonance frequency bands. finally, a prototype is fabricated and its reflection coefficient, gain, and radiation pattern are measured. the experimental result shows that the proposed antenna is reliable for penta band applications. keywords: microstrip antenna, penta band, wlan, bluetooth, slot, monopole 1. introduction in recent years, multiband and wideband communication techniques have emerged as viable and efficient communication methods over various multiservice wireless applications. especially, the progress in the development of compact antennas is playing an extensive role for numerous wideband and multiband applications [1-3]. for developing such antennas, various techniques were being researched in the literature. among those techniques, multiple slot-based geometry [4] and fractal-shaped geometry [5] have been realized from the conventional patch antenna. however, the fractal-shaped geometry increases its complexity as the number of iterations increases. therefore, a simple slotted patch antenna becomes an important design element because of its low cost, simple fabrication, low profile, and light weight [6-7]. nowadays, the planar version of small antennas based on monopole designs has several attractive features, such as the ease of implementation and the ability to integrate with monolithic microwave integrated circuits. numerous designs have been introduced in the literature for multi-band resonance modes by modifications to the main radiator or in the ground plane element. for instance, the planar double inverted f-antenna [8], printed t monopole [9] with similar resonators, t-shaped monopole having dual l-shaped sleeves on a ground plane [10], and defected ground structure stacked patch [11] antenna for 2.4 ghz and 5.5 ghz wireless local area network (wlan) applications have been suggested. alternatively, for triple band applications such as worldwide interoperability for microwave access (wimax), wlan, and long term evolution (lte) * corresponding author. e-mail address: raj_aga_raj@yahoo.co.in advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 bands, different structures have been introduced in the literature [12-17]. xu et al. [13] have proposed an asymmetrical length fork-shaped antenna for 2.45/3.5/5.5 ghz band applications. pandit and harish [14] have proposed a trapezoid-shaped monopole with two inverted l-shaped and v-shaped slots for the same application bands. also, in other research, it has been proposed an equilateral triangular shape with a pair of symmetrical l-shaped parasitic resonator and open-ended slot [15] and an open complementary split-ring resonator (ocsrr) loading antenna [16]. apart from the above frequency bands, recently it has been proposed a fan-stub-shaped antenna for lte and wlan bands [17-18]. in addition, there is little research work on quad band and penta band applications addressed in the literature [19-22]. however, the designs from the work in [19-22] are greater in scale than the one described in this article. in this manuscript, a compact penta band monopole antenna is considered from the quad band monopole antenna [23] by an additional modification on the open-end rectangular and meandered slots. the design is realized with a coplanar microstrip feeding technique from a basic rectangular monopole patch antenna. due to rectangular and meandered slots on a patch, it forms like a triple t-shaped resonator which generates an additional resonance frequency at 5.5 ghz and 6.5 ghz respectively. also, because of the asymmetry introduced in the middle t-shape resonator, the frequency of 5.5 ghz is divided into two resonance frequencies. hence, the proposed antenna operates on five bands with only 20 × 18 mm 2 overall dimensions. furthermore, another resonance frequency is generated by making the symmetrical stub resonators asymmetrical, and all these stubs operate as a quarter-wave resonator at their resonance frequency. 2. antenna configuration and description fig. 1 illustrates a compact coplanar penta band patch antenna with integrated open-ended and meander slots with resonance characteristics and its equivalent circuit representation. as illustrated in fig. 1(a), two open-ended slots, referred to as rectangular and meandered slots, are cut at different locations on a patch antenna. these perforations are etched to provide three extra resonance frequencies in addition to the initial monopole resonance frequency. furthermore, another resonance is created by making an asymmetry in the middle portion of the extended strip between two slots (rectangular and meandered) in conjunction with quad band resonance. in this process, all the slot widths are considered uniform. the proposed configuration is planned on the fr-4 substrate (loss tangent of 0.02) and a relative permittivity of 4.4. both ground plane and microstrip line are etched on the same side of the dielectric with an overall dimension of 20 × 18 × 1.6 mm 3 . all other design parameters and their constitutive dimensions are shown in fig. 1 as follows: w = 18, l = 20, w1 = 16, w2 = 7.5, w3 = 6.5, w4 = 5, w5 = 1, w6 = 7, w7 = 6, wf = 2, l1 = 7, l2 = 3, and l3 = 5. (all dimensions are in mm.) furthermore, the proposed antenna’s equivalent circuit is represented in fig. 1(b) based on the transmission line theorem, where each metal part acts as an inductance and the gap between two metal parts acts as a capacitance effect. to realize the design evolution process of penta band resonance, a step-by-step design procedure is shown in fig. 2. here, to propose a penta band resonance, a conventional rectangular patch element is chosen as shown in fig. 2(a). this is considered antenna #1 operating with a single resonant frequency. next, to realize another resonance frequency, an open-ended rectangular slot cut on the topmost of the patch is introduced and denoted as antenna #2 (fig. 2(b)). because of the patch’s slot cut, the current distribution is adjusted, resulting in a new resonance. next, antenna #3 is formed by creating a dual t-shaped and meander stub resonator by etching another slot on antenna #2. due to the inclusion of this slot, the effective electrical length of the patch is extended. as a result, another resonance frequency at 2.45 ghz is produced. furthermore, the creation of meander construction affects the antenna impedance at 2.65 ghz, resulting in notch characteristics. after that, antenna #4 (fig. 2(d)) is created by etching a horizontal strip of length w4, which is extended on antenna #3 symmetrically towards the vertical center of the meandering arm. this causes to create another additional resonance in the upper-frequency side. to improve the resonance band even further, the current distribution is controlled on the middle tshaped resonators. this may be achieved by appropriately modifying the length of the central t-shaped stub resonator, as illustrated in fig. 2(e). 67 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 (a) proposed antenna (b) equivalent circuit representation fig. 1 proposed antenna geometry and its equivalent circuit representation (a) antenna #1 (b) antenna #2 (c) antenna #3 (d) antenna #4 (e) antenna #5 fig. 2 step-wise design procedure for achieving multiband 3. results and discussion fig. 3 shows a comparison of the simulated reflection coefficients from antenna #1 to antenna #5. the resonance frequency of antenna #1 is observed at 3.0 ghz with a frequency range from 2.3 ghz to 4.0 ghz and an impedance bandwidth (ibw) of 1700 mhz. the proposed antenna called antenna #5 operates at 2.45 wi-fi/bluetooth band, 3.1 ghz wimax band, 5.25 ghz and 5.85 ghz indoor and outdoor wlan band, and 6.5 ghz mobile/fixed satellite band. the ibws of this antenna is observed as 450 mhz, 1050 mhz, 100 mhz, 200 mhz, and 200 mhz from 2.1-2.55 ghz, 2.75-3.8 ghz, 5.2-5.3 ghz, 5.75-5.95 ghz, and 6.4-6.6 ghz frequency bands respectively. antenna #2, antenna #3, and antenna #4 operates on dual, triple, and quad band resonant frequencies respectively. antenna #2 is operating from 2.3-3.9 ghz and 5.2-5.4 ghz bands with an ibw of 1600 mhz and 200 mhz respectively, whereas antenna #3 is operating with an ibw of 400 mhz, 950 mhz, and 200 mhz from 2.2-2.6 ghz, 2.85-3.8 ghz, and 5.4-5.6 ghz respectively. the quad band resonance antenna (antenna #4) is operating with an ibw of 400 mhz, 1000 mhz, 200 mhz, and 200 mhz from the operating frequency range 2.15-2.55 ghz, 2.7-3.7 ghz, 5.4-5.6 ghz, and 6.4-6.6 ghz, respectively. furthermore, the performance comparison among those antennas in terms of ibw, gain, and antenna response is presented in table 1. to know more about multiband impedance matching, antenna #5 is utilized in a parametric study. parameters w2, w3, and w4 are used to observe antenna #5’s matching behavior. fig. 4 depicts the parametric reflection curves concerning a parameter w2 while keeping another parameters constant. the variation of parameter w2 from 7 to 8 mm attains another resonance frequency with a slight variation in the 5.25 ghz and 6.5 ghz resonance frequencies. as the parameter w2 is at 7.5 mm, the attained resonance frequency has high impedance matching at 5.85 ghz. similarly, while keeping other parameters constant, the variation of w3 is analyzed from 7 to 5 mm. the simulated reflection coefficient curves for various values of the w3 parameter are shown in fig. 5. as can be observed, there is no resonance between 5.5 ghz and 6.5 ghz frequency in the parameter w3 at 7 mm. the value decreases from 7 to 6.5 mm, another resonance frequency appears with a 0.25 ghz deviation from 5.5 ghz resonance. as the value further decreases from 6.5 mm, the resonance frequency at 6.5 ghz is shifting to a higher frequency side and is going to disappear. therefore, 6.5 mm is regarded as the optimal w3 parameter value. 68 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 fig. 3 comparison of simulated reflection coefficient table 1 comparison of ibw, gain, and antenna response for various antenna configurations antenna configuration antenna subtype resonant frequency (fr ghz) / ibw (mhz) realized peak gain (db) antenna response antenna #1 convectional rectangular patch 3.0/1700 -3.0 single band antenna #2 resonator with t-shape patch 2.7/1600 5.3/200 -2.5 1.4 dual band antenna #3 dual t-shaped with meander strip 2.4/400 3.15/950 5.5/200 -2.5 -2.75 1.35 triple band antenna #4 tripple t-shaped with meander strip 2.45/400 3.1/1000 5.5/200 6.5/200 -2.5 -2.8 1.4 1.7 quad band antenna #5 asymmetric t-shaped with meander strip 2.45/450 3.1/1050 5.25/100 5.85/200 6.5/200 -2.5 -2.8 1.05 1.4 1.25 penta band fig. 4 reflection coefficient variation with w2 fig. 5 reflection coefficient variation with w3 in addition to the variations in w2 and w3, there is also a parametric variation in w4 (decreases from 6 to 0 mm) that is performed independently while keeping parameter w2 at 7.5 mm and w3 at 6.5 mm. the simulated reflection coefficient curves for parameter w4 are shown in fig. 6. the results show that when the parameter value decreases, it affects upper resonance frequencies. the variation of the upper resonance frequency is shifted to a higher frequency side with the disappearing of resonance frequency at 5.85 ghz. to explore the functionality of antenna #5, the simulated real and imaginary input impedance characteristics against frequency are shown in fig. 7. the resonance property of the antenna can be seen in enclosed circle areas i, ii, iii, iv, and v, which have about 50 ohm real and 0 ohm imaginary components of input impedance and generate resonant modes at around 2.45, 3.1, 5.25, 5.85, and 6.5 ghz, respectively. 69 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 to further investigate the resonance behavior, the current distribution at various frequencies with various antenna designs of fig. 2 is analyzed in fig. 8. the current distribution of antenna #1 is observed in a forward direction from a feed line and bottom edge of the patch. next, to understand the effect of the open-ended slot on antenna #2, the surface current distribution is analyzed in upper resonance frequency. from this analysis, it is observed that most of the current distribution is concentrated on the upper t-shaped stub resonator. this implies the resonance at 5.3 ghz is caused due to upper t-shaped resonator. for further analysis of resonance bands, the surface current distribution of antenna #3 is analyzed in lower resonance frequency. from antenna #3, the current distribution at 2.4 ghz is observed on the vertical strip in the forward direction. furthermore, it is observed that this resonance is created due to the removal of some frequencies around 2.65 ghz. additionally, the current distribution at 6.5 ghz is analyzed after adding the third horizontal strip on antenna #3 and it is called antenna #4. the observed current is concentrated around the newly added strip. finally, to understand the resonance behavior due to asymmetry, the current distribution of antenna #5 at 5.25 ghz and 5.85 ghz are analyzed. from the current distribution at 5.25 ghz, the current is mostly concentrating on the upper left side of the stub resonator and at 5.85 ghz concentrating mostly on the upper right side of the stub resonator. also, there is a slight current concentration on the middle arm. this is because of the coupling effect between 5.85 ghz and 6.5 ghz frequencies. fig. 6 reflection coefficient variation with w4 . fig. 7 impedance variation against the frequency of antenna #5 (a) antenna #1 at 3 ghz (b) antenna #2 at 5.5 ghz (c) antenna #3 at 2.4 ghz (d) antenna #4 at 6.5 ghz (e) antenna #5 at 5.25 ghz (f) antenna #5 at 5.85 ghz fig. 8 current distribution of antenna #1 to antenna #5 at different resonance frequency 70 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 based on the modified circuit current distribution from a rectangular monopole, the achieved additional resonance frequencies at 2.4 ghz, 5.25 ghz, 5.85ghz, and 6.5 ghz are obtained from eqs. (1)-(4). from eq. (1), the calculated resonance frequency is 2.53 ghz at λ = 72 mm, while the simulated frequency is 2.45 ghz. similarly, from eqs. (2)-(4), the calculated resonance frequencies are 5.37 ghz, 6 ghz, and 7 ghz at 34 mm, 30mm, and 24 mm wavelength, respectively. it is observed from the calculation, the predicted values are close to simulated results, except at 6.5 ghz. this deviation may be due to the presence of additional coupling gap capacitance from the meandering strip. at f = 2.45 ghz, 2 1 18 4 4 = + − − ≈≃ f reff c l w l f λ ε (1) at f = 5.25 ghz, 2 5 8.5 4 4 = + ≈≃ reff c w w a f λ ε (2) at f = 5.85 ghz, 3 5 7.5 4 4 = + ≈≃ reff c w w f λ ε (3) at f = 6.5 ghz, 4 5 6 4 4 = + ≈≃ reff c w w f λ ε (4) where 1 2 + = r reff ε ε (5) to describe the efficient communication between transmitter and receiver made by the proposed antenna, another important parameter called radiation efficiency is plotted in fig. 9. radiation efficiency defines how much power is radiated from the received input power. in the proposed design, the radiation efficiency of antenna #4 and antenna #5 is observed between 97% and 65% in the operating band. also, it is observed in the non-operating band a very low efficiency in the frequency range of interest. fig. 9 radiation efficiency variation against frequency 4. experimental validation to confirm the simulated results, the designed antenna prototypes such as antenna #4 and antenna #5 are fabricated and validated using a vector network analyzer and anechoic chamber setup. fig. 10 shows the photographs of the fabricated prototypes, reflection coefficient, and pattern measurement setup. fig. 11 indicates the reflection coefficient performance of the two antennas. the reflection coefficient is measured using anritsu ms2037c vna after doing the calibration in the 71 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 frequency range setup. with slight variations, a close agreement between the simulated and the measured results are achieved. the observed reflection coefficient of antenna #5 is found at 2.15-2.55 ghz, 2.7-3.6 ghz, 5.2-5.35 ghz, 5.7-6.0 ghz, and 6.4-6.65 ghz resonant bands with an ibw of 400 mhz, 900 mhz, 150 mhz, 300 mhz, and 250 mhz respectively. the deviation between the validated and simulated results below -10 db is observed at their matching bands, which are 50 mhz, 150 mhz, 50 mhz, 100 mhz, and 50 mhz from lower resonance to upper resonance, respectively. furthermore, the achieved bandwidth parameters meet the requirement of bluetooth, wimax, wlan, fixed satellite/mobile communication specifications. as a result, the proposed antenna meets the requirement of multiband applications. (a) antenna #4 prototype (b) antenna #5 prototype (c) antenna #4 s11 measurement setup (d) antenna #5 pattern measurement setup fig. 10 fabricated prototypes and measurement setups for the validation fig. 11 comparison of reflection coefficient for the proposed antenna fig. 12 realized gain comparison of antenna #4 in an anechoic chamber, the gain is measured using the two-antenna method. the measurement is carried out at some discrete frequencies in the matched frequency region. the gain comparison of the proposed antenna is shown in fig. 12. the simulated peak comprehended gain from 2.1-2.6 ghz, 2.7-3.7 ghz, 5.2-5.3 ghz, 5.75-5.95 ghz, and 6.4-6.6 ghz bands are -2.4 dbi, -1.8 dbi, 1.05 dbi, 1.4 dbi, and 1.25 dbi respectively, whereas the measured gain from 2.1-2.7 ghz, 2.8-3.7 ghz, 5.2-5.35 ghz, 5.7-6.0 ghz, and 6.4-6.65 ghz bands are 0-2.05 dbi, -2.45 dbi, 0.65 dbi, 1.6 dbi, and 1.45 dbi respectively. fig. 13 shows the simulated and measured radiation pattern comparison of both coand cross-polarization. measurements are carried out between two antennas, one of which is a high gain horn antenna and the other is a fabricated prototype. to measure the pattern of the proposed antenna, two principle planes in both the elevation plane (e-plane or xoz plane) and azimuth plane (h-plane or yoz plane) are considered. the measurements are taken at various frequencies including 2.45, 3.1, 5.25, 5.85, and 6.5 ghz. in the h-plane, the proposed antenna has almost omnidirectional radiation patterns, while in the e-plane, it exhibits dipole-like radiation patterns. it is also observed that there is a considerable comparison between coand 72 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 cross-polarization in e-plane at higher frequencies. additionally, to show the advantage of the proposed device, a comparison of the reported multi-band antennas in the literature is given in table 2. it can be seen that the proposed antenna is compared in terms of the dimensions, the operating antenna response, and the corresponding bandwidths with various application bands. from the table, it can be easily recognized that the proposed antenna is more compact than the ones in the existing literature with five resonance band frequencies. (a) e-plane (b) h-plane fig. 13 the simulated and measured radiation patterns of the antenna 73 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 table 2 comparison of the penta band antennas in the existing literature ref. size (w × l × h mm3) ground size (mm2) antenna response fr1/r2/r3/r4/r5 (ghz) ibws/bws (ghz) [9] 75 × 75 × 0.8 75 × 50 dual band 2.4/5.2 2.4-2.484 5.15-5.35 [10] 40 × 68 × 0.8 40 × 55 dual band 2.4/5.8 1.76-2.79 5.19-5.51 [11] 22 × 18.5 × 1.6 22 × 18.5 dual band 2.45/5.1 2.31-2.78 4.87-5.74 [12] 25 × 25 × 0.8 25 × 10 dual band 3.5/5.5 3.4-3.6 5.6-5.8 [13] 20 × 37 × 0.508 20 × 10.7 triple band 2.4/5.2/5.8 2.4-2.65 3.3-4.05 5-5.98 [14] 21 × 24 × 0.8 21 × 7.3 triple band 2.4/5.2/5.8 2.35-2.53 3.2-4.56 5.24-6.06 [15] 36 × 40 × 1.52 36 × 14.4 triple band 2.4/3.5/5.8 2.20-2.65 3.47-3.55 5.75-5.83 [16] 30 × 40 × 0.8 9.7 × 17.35 triple band 2.6/3.4/5 2.40-2.70 3.32-4.00 4.76-5.8 [17] 24 × 30 × 0.79 24 × 5 triple band 2.5/3.5/5.5 2.50-2.71 3.37-3.63 5.20-5.85 [19] 28 × 38 × 1.6 28 × 11 quad band 2.47/3.2/5.39/8.87 2.44-2.55 2.89-3.80 5.18-5.66 8.28-9.90 [20] 57.37 × 67.5 × 1.6 67.5 × 30 quad band 1.2/1.65/2.4/3.5 1.15-1.25 1.5-1.9 2.39-2.49 3.5 [21] 24 × 32 × 1.6 24 × 13.5 quad band 2.45/3.5/5.2/5.8 2.31-2.58 3.16-3.57 5.11-5.23 5.72-5.92 [22] 50 × 50 × 1.6 50 × 25 penta band 1.81/2.22/2.51/2.85/3.08 4.97 2.70 5.98 8.42 2.92 this work 20 × 18 × 1.6 18 × 3 penta band 2.45/3.1/5.25/5.85/6.5 2.1-2.55 2.75-3.8 5.2-5.3 5.75-5.95 6.4-6.6 5. conclusions in this article, a simple penta band antenna is designed and validated from the fabricated prototype. by cutting open-ended and meandering slots in a radiator in a systematic way, five resonance bands are generated. because of cutting open-ended and meandering slots, t-shaped stub resonators are formed. parametric studies are performed to show the influence of those stubs on antenna performance. with an acceptable gain and a consistent radiation pattern, the suggested antenna can encompass wi-fi/bluetooth, wimax, wlan, and fixed satellite operating bands. finally, the antenna parameters are measured and validated with the fabricated prototype. in addition, the proposed antenna is compact compared to current penta band antennas with an overall dimension of 20 × 18 × 1.6 mm 3 , which has the benefit of being easier to be included in printed circuit boards (pcbs). hence, this antenna can be used in multiband wireless communications applications such as 5g and beyond. 74 advances in technology innovation, vol. 7, no. 1, 2022, pp. 66-76 conflicts of interest the authors declare no conflict of interest. references [1] j. f. huang, m. t. wu, and j. y. wen, “a compact triple-band antenna design for umts wlan and wimax applications,” microwave and optical technology letters, vol. 51, no. 9, pp. 2207-2212, september 2009. 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[23] r. kumar and y. kamatham, “design of compact quad band monopole antenna using open-ended and meandered slot,” international conference on innovations in electrical and electronics engineering, pp. 627-634, january 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 76 1___aiti#8291__01-18 advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 cost-effective customizable indoor environmental quality monitoring system mohammad ayad al-rawi*, praneel chand, archie van mendoza evangelista centre for engineering and industrial design, waikato institute of technology, hamilton, new zealand received 17 august 2021; received in revised form 10 october 2021; accepted 11 october 2021 doi: https://doi.org/10.46604/aiti.2021.8291 abstract poor indoor environmental quality (ieq) has become a global concern for world health organization (who), and its impact on health and well-being has been exacerbated by the covid-19 pandemic. to monitor and sanitize indoor air, this study develops a cost-effective and customizable ieq monitoring system to detect unhealthy and low-comfort air levels. this system uses thingspeak (matlab), microcontrollers (arduino uno), and various low-cost sensors to measure indoor air quality (iaq) and ieq in terms of gas, particulate matter, temperature, sound level, and ultraviolet (uv) light. the presented system is validated with respect to temperature, relative humidity, and particulate matter by benchmarking against the camfil air image sensor manufactured by camfil ab, stockholm, sweden. the average error of temperature, relative humidity, and pm2.5 are 0.55%, 5.13%, and 3.45%, respectively. keywords: indoor environmental quality (ieq), internet of things (iot), thingspeak, sensors 1. introduction due to the growth of industrial activities and the development of more intensive farming, the volume of carbon monoxide (co), carbon dioxide (co2), and volatile organic compounds (vocs) emitted has risen significantly over the past few decades [1]. most people cannot detect these emissions (due to their odorless, colorless, and tasteless characteristics), nonetheless, they are harmful to health [2]. colclough et al. [3] identified the increase in co2 level at night by using an indicator of the quality of ventilation in home. indoor air can potentially contain a variety of harmful compounds, such as formaldehyde, dust and other allergens, radon gas, organic and inorganic materials, as well as water vapor which increases relative humidity (rh) and contributes to mould growth [4]. poor indoor air quality (iaq) due to the presence of vocs [5] can be the result of the increased intensity of household use [3-4], or overcrowding, as well as the emissions from stoves and other cooking devices, heaters, and unflued fireplaces, such as co, nitrogen oxide (no), and sulphur dioxide (so2) [6]. in general, in developed countries, people spend 90% of their time indoors, with 70% of that time being spent in their own home [7]. the covid-19 pandemic gave rise to an increase in these percentages: governments’ enforced lockdowns resulted in an increase in remote working and schooling, conducted within home [8]. according to the work of nwanaji-enwerem et al. [8], 3.8 million people die from the diseases related to poor indoor air environment. therefore, they advocate that environmental protection agency must develop legislation regarding the integrity of the indoor air environment, to guarantee individuals a minimum level of protection, even in their own residential spaces. any mandate around indoor environmental quality (ieq) would require comprehensive monitoring. however, such monitoring devices must be of low cost to be accessible for small-scale use, such as small business’ offices and residential houses. monitoring devices should have both thermal comfort applications as well as functionality to measure air quality or “safety”. devices should therefore measure particulate matter (pm2.5), vocs, co, co2, and other compounds in the air. the covid-19 pandemic has also increased the demand for detecting pathogens in the air. recent studies [9-11] found a * corresponding author. e-mail address: mohammad.al-rawi@wintec.ac.nz advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 2 correlation between poor iaq and the spread of viruses since 2020 [8]. to achieve a reliable and low-cost iaq monitoring system, there are many different approaches presented in the literature, of the do-it-yourself (diy) variety. zhang et al. [12] used a low-cost raspberry pi-based system for the real-time monitoring of indoor environment parameters in both residential and commercial settings. they studied the correlation among pm2.5, temperature (t), and rh, and noted that effective calibration of sensors required a reasonable length of run time and a comparison across different locations. recent studies indicated that the accuracy of the current low-cost monitoring systems for iaq and ieq is very important [13-17]. therefore, the comparison between a low-cost sensor using a multi-channel monitoring system and calculated concentration is required. additionally, the assessment of thermal comfort parameters (predicted mean vote (pmv) and predicted percentage of dissatisfaction (ppd)) is required in an advanced monitoring system. parkinson et al. [18] investigated three innovative technologies, i.e., internet of things (iot), wireless sensor networks (wsns), and big data, to assess ieq parameters using the samba monitoring system. this system is used for the continuous and real-time data monitoring of ieq categories in a commercial building. these categories are assessed against the ashrae standard 55 for thermal comfort (t, air speed, rh, and radiant temperature), lighting, acoustical quality, and iaq parameters (co, co2, pm2.5, and total vocs). the samba system is configured using zigbee pro mesh networking and uses the ieqanalytics web service. previous studies used iot wherein devices were embedded in a network using microcontroller sensors. these formed a web-based monitoring system which captured real-time data using hypertext transfer protocol (http) [19]. the advantage of using iot is that it is a low-cost and reliable method for constructing a user-friendly iaq monitoring system [5, 12, 20]. this platform is tested with pollution monitoring wsns using ieee 802.15.4 zigbee [5-6, 12, 21-23]. mumtaz et al. [11] employed iot and machine learning to design a predictive iaq system for parameters such as t, rh, pm2.5, co2, co, no2, and ch4. their system achieved an accuracy of 99.37% and precision of 99%. some studies showed how real-time ieq readings and graphs could be presented on readily available smart phones [20, 22-23]. taştan et al. [22] created a diy system using the blynk platform on an android esp32 module. their iaq monitoring system ran using the iot method and presented real-time data to measure t, rh, co2, co, pm10, and no2. marques et al. [20] presented a smartphone and thingspeak interface to capture ieq data. their system “iair” used esp8266 and mics-6814. this enabled users to adjust devices from their smartphones in real time to improve ieq. wall et al. [23] built an ieq monitoring system using the iot architecture. their system measured airborne compounds and other pollutants that impact the respiratory system, t, rh, and vocs, using raspberry pi, epsp32 microcontroller, ieee 802.11 wireless local area network (lan) router, and bosch bme689 sensor [24-25]. previous studies of monitoring systems also examined new approaches to combine deep learning and iot to monitor air conditions in industrial settings and enhance energy conservation. the deep learning approach was based on a recognition algorithm to detect the number of occupants in the interest area, such as commercial or domestic buildings [26-29]. therefore, their proposed approaches are considered industry 4.0 applications, relying on iot and smart sensors to address industrial ieq and noise signals using machine learning algorithms [26-29]. this study aims to create and validate a low-cost air quality monitoring system to detect whether the ieq parameters, such as t, rh, pm1, pm2.5, voc, co, co2, ultraviolet (uv), and sound level, are aligned with national environmental standards for air quality regulations in new zealand [30]. in this work, cost-effective sensors are utilized by choice of low cost device components and cost of the overall system connected through an arduino uno microcontroller as wsns, to monitor air pollutants in a residential dwelling using iot as one of the technological innovations [18]. the measured data is visualized through an android smart device or a pc linked to the sensor which aggregates, displays, and analyses real-time data in the cloud using thingspeak [31] as big data requires a business intelligence and analytics (bia) platform to provide data visualization [18]. the thingspeak service is operated by mathworks and can be obtained at zero-cost for small non-commercial projects. thingspeak includes a web service (rest api) that enables collection and storage of sensor data in the cloud for iot applications. advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 3 2. the system design 2.1. hardware system architecture the architechture of environmental monitoring system using the iot-web based hardware is shown in fig. 1. the proposed system consists of the following. (i) a particulate concentration sensor (pms5003) is used to detect micro suspended particles in the room with the specifications outlined in table 1. pms5003 is supplied by a voltage of 3 v and a rx and tx connection from arduino uno to measure the particles in the air (pm2.5). (ii) an iaq sensor (mq-135) is used to measure vocs, nh3, nox, alcohol, benzene, smoke, and co2 in the room with the specification shown in table 2. mq-135 requires a 5 v supply from arduino uno to transmit the voc and gas readings. (iii) t and rh sensor (dht-11) is used as shown in table 3. the dht-11 requires 3-5 v for sensing the t and rh of the monitored area. (iv) a uv sensor (xc4518) and a sound sensor (xc4438) are used as shown in table 4 and table 5, respectively. xc4518 and xc4438 are connected to a microcontroller (tensilica 32-bit risc cpu xtensa lx106). these sensors are battery powered using the microcontroller (arduino uno and esp2866 wi-fi microchip) communicated as a gateway to thingspeak for capturing real-time data and illustrating them as graphs which could be exported as comma-separated values (.csv) file under mathworks. the captured graphs are used to display the real-time series for each sensor reading stored in the cloud database. values can be displayed every 10 seconds, whereas the time series values are updated every minute showing all data updates on the dashboard. csv is used for the data, meaning the web application can send and retrieve the data from the server asynchronously without interfering with the displayed page. fig. 1 the schematic diagram for the system architecture table 1 specifications for particle concentration sensor (pms5003) parameter index unit range of measurement 0.3-1.0; 1.0-2.5; 2.5-10 �� counting efficiecny 50%@0.3 98% @>=0.5 �� effective range 0-50 ��/�� maximum range (pm2.5 standard) resolution � 1000 1 ��/�� ��/�� maximum consistency error (pm2.5 standard) 10%@100 � 500 10@0 � 100 � 500 ��/�� ��/�� direct current power supply typ: 5.0; min:4.5; max: 5.5 volt (v) physical size 50 × 38 × 21 millimeter (mm) range of measurement 0.3-1.0; 1.0-2.5; 2.5-10 �� advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 4 table 2 specifications for air quality sensor (mq-135) parameter index operating voltage +5 v detect/measure nh3, nox, alcohol, benzene, smoke, co2, etc analog output voltage 0-5 v table 3 specifications for temperature and humidity sensor (dht-11) table 4 specifications for ultraviolet sensor (xc4518) parameter index parameter index printed circuit board (pcb) size 22.0 mm × 20.5 mm × 1.6 mm wavelength response 200-370 nm working voltage 3.3 or 5 v direct current protocol analog: 0-1.2 v direct current operating voltage 3.3 or 5 v direct current output voltage 0-1200 mv measurment range 20-95%rh; 0-50� working temperature -20 to 85� accuracy ±0.5°c; ±2%rh current 0.06-0.1 ma resolution 8-bit (t); 8-bit (rh) supply voltage 3-5 v direct current compatible interfances 2.54 3-pin interface and 4-pin dimensions 43 (l) × 13 (w) × 8(h) table 5 specifications for sound sensor (xc4438) parameter index sensitivity adjustable via trimpot operating voltage 0-5 v direct current (analog) supply voltage 5 v direct current dimensions 43 (l) ×16 (w) × 13 (h) one of the limiting factors in the initial proposed monitoring system is that a “blip” is observed due to the different voltage supply required for each sensor for data transfer. to fix that, a four-channel bi-directional logic level converter (llc) (sparkfun) is used for the variance and to accommodate the variation of the voltage supply to each sensor from the microcontroller. the sparkfun logic device is designed to safely operate on the same channel as it steps up from the 3.3 v signals to 5 v and vice versa. also, it works for future sensors within the range of 2.8 v and 1.8 v. the sparkfun logic device can convert 4 pins on the high side to 4 pins on the low side with two inputs and two outputs provided for each side. in addition to the bi-directional option of the sparkfun llc, the board is easy to use, and is powered from the low voltage 3.3 v to “lv” and grounded from the system to the “gnd” pin. fig. 2 illustrates the final design. fig. 3 shows the final product, and table 6 shows the components of the project for each part connected to the microcontrollers (arduino uno and esp8266) which are the core of the hardware and also the gateway to the iot as well as supplying the required voltage to each of the sensors used in the system. fig. 2 hardware setup illustrating the five sensors pms5003, mq-135, dht-11, xc4518, and xc4438 along with the arduino uno and esp8266 microcontroller unit and the iot connector advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 5 fig. 3 finished prototype of the iot device table 6 the components of current design using iot components specifications arduino uno esp8266 nodemcu v3 wi-fi module arduino uno microcontroller: microchip atmega328p digital i/o pins: 14 (of which 6 can provide pwm output) flash memory: 32 kb operating voltage: 5 volts esp8266 wi-fi module microcontroller: tensilica 32-bit risc cpu xtensa lx106 digital i/o pins: 16 flash memory: 4 mb operating voltage: 3.3 v clock speed: 80 mhz sensors and gateway (iot) pms5003 (table 1) mq-135 (table 2) dht-11 (table 3) xc4518 (table 4) xc4438 (table 5) end user android and ios systems laptop/desktop that can access to the internet 2.2. sensor calibration the pms5003, mq-135, dht-11, xc4518, and xc4438 sensors have their own required supply voltages. that is why the bi-directional llc is needed to change the supply from 3.3 v to 5 v and vice versa on each cycle, and that is also the reason that there is a “blip” on the system reading as mentioned previously. the microcontrollers arduino uno and esp8266 are tested and calibrated as shown in fig. 4. this is to check that the right voltage and re-set/clock time is being supplied from the microcontrollers to the sensors and to ensure that the supply and ground are working in accordance with the required datasheet parameters. fig. 4 testing and calibration of the microcontroller using oscilloscope advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 6 2.3. software system architecture all the sensor data (except for the particulate sensor data) are read and collected by the arduino uno microcontroller as shown in fig. 1. the arduino microcontroller is a slave that relays the collected data to the esp8266 master microcontroller. in turn, esp8266 is responsible for transmitting the acquired data to the web-based iot client. esp8266 also reads the particulate sensor data. microsoft visual studio integrated development environment (ide) with the vmicro extension is used for programming. fig. 5 shows the flowchart for data collection by the arduino uno slave microcontroller. the uv, sound, and air quality are read as 16-bit analogue inputs. t and rh data from the dht11 sensor are 16-bit floating point (8 for t and 8 for rh) and read via serial communication. when the data is requested by the master esp8266, the analogue inputs are converted and inserted into a 14-byte uint8_t data send array. they fill the first six bytes. converting the 32-bit floating t and rh data fills the remaining 8 bytes in the data send array. the 14-byte data send array is then transmitted to the master. the flowchart for data receiving and transmitting by esp8266 is shown in fig. 6. after initializing ports and variables, the sensor data is requested from the arduino uno slave microcontroller. the sensor data is then re-built into their original formats. following this, the particulate sensor data are read from the serial port and the pm2.5 and pm10 data are extracted. finally, when the thingspeak update timer passes, all the sensor data is transmitted to the http uniform resource locator (url) client. fig. 5 the flowchart of data collection by the arduino uno slave microcontroller fig. 6 the flowchart for data receiving and transmitting by esp8266 3. results and discussion a user-friendly and easy-to-assemble sensor can be constructed with interchangeable components enabling a low-cost device and using an open-source platform to capture and analyze the data for further validation and optimization [13]. using the iot technologies enables a wider range of people to be able to access and connect their devices to the sensor via the internet, facilitating the collection and sharing of data. wireless networks are nearly ubiquitous in most countries, benefitting the control and communication of the data. advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 7 the majority of the literature focuses on presenting a low-cost monitoring system, but in this study it is found that their proposed systems are often difficult to modify and lack modularity. furthermore, some studies focus on the hardware, others on the software, but few concentrate on the both. this study demonstrates the implementation of iot low-cost and affordable approach with the use of thingspeak with five low-cost sensors to measure iaq parameters, uv, and sound level. these sensors can be locally purchased in new zealand and do not need sourcing from abroad thus eliminating procurement delays due to covid-19 supply chain and distribution problems. a low-cost iot solution could be significant for the task of monitoring, quantifying, and improving iaq with the correct programming of each sensor. furthermore, these sensors could be used in a smart home environment, where corrective action (e.g., opening a window or turning on an air purifier) could be triggered once the air quality drops below thermal comfort or iaq recommended standards; this could mitigate the risk of illnesses due to poor iaq. the proposed “diy” low-cost monitoring system in this study consists of three main components: the microcontrollers (the arduino uno and the esp8266 microcontroller unit (mcu)) and the bi-directional llc (sparkfun). the current system is easy to assemble and connect, and enables adding and modifying individual sensors in the system as technology advances. in addition, iot is used via thingspeak by application programming interface (api) key under matlab to capture the data which could be analyzed and optimized. to achieve that, the software is scripted using the files datacollector program (appendix a) to communicate to the arduino uno and the datatransmitter program (appendix b) and to the esp8266 mcu and the iot using microsoft visual studio (vmicro extension) by ide based on the architecture layers shown in fig. 7. this allows for both code modification and error detection as it is separated on each mcu. therefore, the key features of the proposed iaq and ieq monitoring system have the following advantages: (1) the device can measure eight different ambient factors presented in the enclosed space: t, rh, co2, mp1, mp2.5, voc, uv, and sound level. (2) due to the iot, the device enables real-time monitoring and the analysis of different ambient impurities. (3) the device does not require any secure digital (sd) memory card for data storage. all the data gathered is stored on the cloud sever and downloadable for future use. (4) the device’s modularity allows for the addition of more sensors, and the used sensors can be switched out for upgraded ones. for the operation of both the datacollector and datatransmitter programs, a video is recorded available as supplementary material. the security of the captured data using wsn requires a username and password to access thingspeak. additionally, the datatransmitter program requires a secure internet by setting and defining the wi-fi parameters wlan_ssid and wlan_pass as shown in fig. 8. fig. 7 the layer architecture with implementation details advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 8 fig. 8 wi-fi parameters for the datatransmitter program the proposed device esp8266 operates as the gateway of the system to the internet and is a more powerful mcu as it can support more sensors; the modularity of the system enables the interchangeability of sensors. this is beneficial for international applications, where some ieq parameters are more concerning than others in different countries or regions due to their specific environmental factors. in this study, the proposed system is also compared with the work of al rasyid et al. [6] and sudarsono et al. [21] in terms of designing a monitoring system through wsn using iot. al rasyid et al. [6] implemented co and co2 sensors on a gas sensor motherboard to monitor environmental gas conditions. they sensed the data using mysql database on meshlium gateway using zigbee wireless to visualize the environment’s condition remotely. sudarsono et al. [21] also used wsn and added extra sensors to measure t, rh, luminosity, noise, co, and co2. they encrypted the sensors’ data and propagated the data through an ieee802.15.4-based communication gateway for temporary storage. one of the advantages of the system is the flexibility to add extra sensors to measure more ieq parameters using the esp8266 mcu. this additional functionality could be programmed using the ide in microsoft visual studio by the data collector and transmitter. in addition, the current system does not require data storage as the free access to thingspeak captures and stores the data. table 7 shows the present proposed design of hardware and software compared against the work of al rasyid et al. [6] and sudarsono et al. [21]. the present proposed design avoids the use of ieee 802.15.4 zigbee, which is a disadvantage of the other systems, so it is easy to carry and access at any time by communication using iot through thingspeak. table 7 comparison of the hardware and software specifications reference [6] reference [21] current study 1. computer as server 1. sensor nodes (node1~node3) 1. arduino uno and esp8266 nodemcu v3 as microcontroller and wi-fi module central processing unit (cpu): 3.20 ghz (intel core i5) memory: 4.0 gb ram microcontroller atmega1281 14 mhz static random access memory (sram) 8 kb electrically erasable programmable read-only memory (eeprom) 4 kb flash 128 kb real-time clock (rtc) 32 khz 802.15.4/zigbee 2.4 ghz arduino uno microcontroller: microchip atmega328p digital i/o pins: 14 (of which 6 can provide pwm output) flash memory: 32 kb operating voltage: 5 volts esp8266 wi-fi module microcontroller: tensilica 32-bit risc cpu xtensa lx106 digital i/o pins: 16 flash memory: 4 mb operating voltage: 3.3 v 2. sensor node and gateway 2. gateway 2. sensors and gateway (iot) waspmote pro 1.2 waspmote gases 2.0 board co sensor (tgs2442) co2 sensor (tgs4161) xbee s1 module meshlium gateway geode integrated amd pcs x86 processor 500 mhz cache memory 128 kb random access memory (ram) 256 mb disk 8 gb linux debian kernel-2.6.30 wi-fi atheros ar5213a 802.11b/g 100 mw 20 dbm xbee pro 802.15.4 2.4 ghz 100 mw ethernet controller via vt6105m (rhine iii) gnu c compiler 4.3 particle concentration sensor (pms5003) air quality sensor co, co2 (mq-135) temperature and humidity sensor (dht-11) ultraviolet sensor (xc4518) sound sensor (xc4438) esp8266 (device used to connect to iot and publish data to the cloud using http protocol) advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 9 table 7 comparison of the hardware and software specifications (continued) reference [6] reference [21] current study 3. data centre server 3. data centre server 3. data centre server ieee 802.15.4 zigbee intel xeon 3.2 ghz ram 4 gb ddr3 linux debian kernel-3.5.0-17 gcc-4.7.2 gmp-5.1.1 pbc-lib-0.5.14 glib-2.34 openssl-1.0.1e java 1.8.060 apache-tomcat-8.0.15 ryzen 5 processor with 8 gb of ram huawei matebook d 14 (ryzen) packs 256 gb of solid-state drive (ssd) storage 4. end user 4. end user 4. end user server computer desktop based web based intel core i3 2.4 ghz ram 2 gb ddr3 wi-fi 802.11b/g/n linux debian kernel-3.5.0-17 gcc-4.7.2 gmp-5.1.1 pbc-lib-0.5.14 glib-2.34 openssl-1.0.1e java 1.8.060 mozilla firefox-40.0.3 any android/ios device that can access/connect to the internet (mozilla firefox and google chrome) laptop/desktop that can access to the internet (mozilla firefox and google chrome) also, the link and resource to obtain each item of equipment and software used in this study are provided, and they are easy to be accessed in new zealand and the pacific region as shown in table 8 (which lists the final total cost as nzd $229.84 (usd $162.58)). table 8 the total cost for each sensor and board used in the proposed system designator equipment price xc-4518 uv sensor $33.90 xc-4438 sound sensor $8.90 pms5003 particulate matter sensor $70.50 mq‐135 air quality and hazardous gas detection alarm module for arduino $5.99 breadboard arduino compatible breadboard with 830 tie points $19.90 jumper breadboard jumper kit $13.90 microcontroller arduino uno $36.05 dht-11 temperature and humidity sensor $10.70 nodemcu esp8266 v.1 $10.00 total cost nzd $209.84 the visualization of the data communicated to the thingspeak for co2, pm1, pm2.5, voc, sound level, and uv live readings accessed at different locations from the sensors are shown in fig. 9. fig. 9 shows how each parameter is captured in the real time data obtained. (a) co2 (b) pm1 fig. 9 the dashboard visualization using thingspeak live data advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 10 (c) pm2.5 (d) voc (e) sound level (f) uv fig. 9 the dashboard visualization using thingspeak live data (continued) furthermore, the dht-11 and pms5003 sensors are validated with an expensive sensor camfil air image sensor ccsg#01324 manufactured by camfil ab, stockholm, sweden costing nzd860 as shown in fig. 10. it weighs 200 g with dimensions: w = 144 × h = 64 × d = 61 mm. it operates with 230 v alternating current > 5 v direct current and consumes 10 w. the accuracy of the camfil sensor for measuring particulate matter (pm2.5) is ±0.1 µg/m³ in the operating range 1 to 2.5 µg/m³, for t it is ±0.5ºc with an operating range -10ºc to +50ºc, and for rh (%rh) it is with an accuracy ±2.5% with an operating range 0 to 100 non-condensing [32]. the validation is for three consecutive days, but a 120 minute period is focused on, as shown in fig. 11 for t, fig. 12 for rh, and fig. 13 for particulate matter. the average temperature measurement error between camfil sensor and the proposed sensor is 0.55% which is within the range of the accuracy of the sensor. the average rh error is 5.13% and the average error for pm2.5 is 3.45%. the testing is conducted in a residential house located in a rural part of waikato, new zealand. fig. 10 the air image sensor (camfil) dashboard advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 11 fig. 11 the dht-11 temperature validation against the air image sensor (camfil) fig. 12 the dht-11 relative humidity validation against the air image sensor (camfil) fig. 13 the pms5003 particulate matter pm2.5 validation against the air image sensor (camfil) 4. conclusions this study presents the steps to assemble and program a low-cost ieq monitoring system using the iot comprising five different sensors to monitor the iaq and ieq parameters. the current design enables real-time monitoring of the risks and hazard levels of gas emissions, vocs, and particulate matter, as well as temperature, sound level, and uv concentration for spaces in a residential dwelling. the vocs, co2, and pm2.5 real-time readings can be of use to people with respiratory illnesses such as asthma, chronic obstructive pulmonary disease, and allergic disorders. the readings and graphs are easy to obtain with open-source software, and the hardware comprises off-the-shelf low-cost components. the system presented is validated for these ieq parameters by benchmarking against the camfil air image sensor manufactured by camfil ab, stockholm, sweden. the average error of t, rh, and pm2.5 are 0.55%, 5.13%, and 3.45%, respectively. advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 12 in future work, this system can be tested in use cases, such as with the subjects with respiratory conditions to validate the effectiveness in assessing and improving the ieq and enhance overall well-being. also, this could be used in a variety of settings to correlate ieq parameters with illness amongst the occupants, e.g., office spaces, childcare facilities, or doctor’s clinics. acknowledgements the authors would like to thank wintec research office and centre for engineering and industrial design for internal funding to support this research. the authors wish to acknowledge the support of jacob bakker, stefan von maltitz, and timothy fargher for helping with the code. conflicts of interest the authors declare no conflict of interest. references [1] p. markowicz and l. larsson, “influence of relative humidity on voc concentrations in indoor air,” environmental science and pollution research, vol. 22, no. 8, pp. 5772-5779, october 2014. 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[32] m. al-rawi, c. a. ikutegbe, a. auckaili, and m. m. farid, “sustainable technologies to improve indoor air quality in a residential house—a case study in waikato, new zealand,” energy and buildings, vol. 250, 111283, july 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). appendix a datacollector program #include <wire.h> #include "lib/dht_sensor_library/dht.h" #include "timer.h" // dht defines #define dhtpin 2 #define dhttype dht11 dht dht(dhtpin, dhttype); #define dhpin 8 byte dat[5]; timer i2ctimer; timer analogreadtimer; timer tempraturetimer; int uvreading = 0; int highestsoundlevel = 0; int airquality = 0; float humidity = 0.0f; float temprature = 0.0f; void setup() { // put your setup code here, to run once: serial.begin(115200); advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 14 delay(100); dht.begin(); // i2c init and listen function wire.begin(20); wire.onrequest(datarequested); i2ctimer.reset(); analogreadtimer.reset(); serial.println("init complete"); pinmode(dhpin, output); } void loop() { // put your main code here, to run repeatedly: // i2cread(); readanalogsignals(); readtempandhumidity(); // delay(700); } // reads in analog signals and stores them in the global variables void readanalogsignals() { if (analogreadtimer.timepassed(100, true)) { // set analog refernce voltage to the internal 1.1v ref analogreference(internal); analogread(a0); delay(2); // store analog reading in the uvreading variable uvreading = analogread(a0); // serial.print("uvreading: "); serial.println(uvreading); // reset to default value (5v ref) analogreference(default); analogread(a0); delay(2); // serial.print("air qual:"); //serial.println(airquality); } // create a tempoary soundin var to store the sound reading. int soundin = analogread(a1); // updates the highestsoundlevel if the soundin reading is higher than the current recorded value if (soundin > highestsoundlevel) { highestsoundlevel = soundin; // serial.print("sound peak: "); serial.println(highestsoundlevel); } airquality = analogread(a2); double testdouble = 23.23; } // sends data back to esp8266 using i2c (wire.h) void datarequested() { serial.println("data req"); uint8_t sendarray[14]; sendarray[0] = highestsoundlevel >> 8; sendarray[1] = highestsoundlevel; sendarray[2] = uvreading >> 8; sendarray[3] = uvreading; sendarray[4] = airquality >> 8; sendarray[5] = airquality; uint8_t temparray[4]; memcpy(temparray, &temprature, 4); sendarray[6] = temparray[0]; sendarray[7] = temparray[1]; sendarray[8] = temparray[2]; sendarray[9] = temparray[3]; advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 15 memcpy(temparray, &humidity, 4); sendarray[10] = temparray[0]; sendarray[11] = temparray[1]; sendarray[12] = temparray[2]; sendarray[13] = temparray[3]; serial.print("data::"); serial.print(temparray[0]); serial.print(temparray[1]); serial.print(temparray[2]); serial.println(temparray[3]); wire.write(sendarray,14); // serial.println(temp[0]); //serial.println(temp[1]); highestsoundlevel = 0; } void readtempandhumidity() { if (tempraturetimer.timepassed(1000, true)) { // reading temperature or humidity takes about 250 milliseconds! // sensor readings may also be up to 2 seconds 'old' (its a very slow sensor) humidity = dht.readhumidity(); // read temperature as celsius (the default) temprature = dht.readtemperature(); // check if any reads failed and exit early (to try again). if (isnan(humidity) || isnan(temprature)) { serial.println(f("failed to read from dht sensor!")); humidity = 0; temprature = 0; return; } // compute heat index in celsius (isfahreheit = false) float temprature = dht.computeheatindex(temprature, humidity, false); serial.print(f("humidity: ")); serial.println(humidity); serial.print("temprature: "); serial.print(temprature); serial.print(f("°c ")); } } appendix b datatransmitter #include <esp8266wifi.h> #include <esp8266httpclient.h> #include <wire.h> #include "timer.h" #include "lib/pmsx003/src/pms.h" #include <softwareserial.h> //softwareserial particlesensor(5, 6); pmsx003 pms(d3, d4); // wifi parameters #define wlan_ssid "alrawi wireless" #define wlan_pass "xyzxyzxyzxyz" // adafruit io /*#define aio_server "https://thingspeak.com/" #define aio_serverport 1883 #define aio_username "mohammad" #define aio_key "fz7y8ql5ibyb0vol" */ // wifi object wificlient client; // http object httpclient http; advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 16 //i2c buffer vars uint8_t incount = 0; uint8_t indata[30]; // retrived data values int rd_soundlevel = 0; int rd_uvlevel = 0; int rd_airquality = 0; float rd_humidity = 0; float rd_temprature = 0; int rd_pm1 = 0; int rd_pm2 = 0; int rd_pm10 = 0; //timers timer fetchdatatimer; timer thingspeakupdatetimer; timer testtimer; void setup() { serial.begin(115200); serial.println(f("adafruit io example")); // connect to wifi access point. serial.println(); serial.println(); delay(10); serial.print(f("connecting to ")); serial.println(wlan_ssid); wifi.begin(wlan_ssid, wlan_pass); wire.begin(); while (wifi.status() != wl_connected) { delay(500); serial.print(f(".")); } serial.println(); serial.println(f("wifi connected")); serial.println(f("ip address: ")); serial.println(wifi.localip()); pms.begin(); pms.waitfordata(pmsx003::wakeuptime); pms.write(pmsx003::cmdmodeactive); fetchdatatimer.reset(); thingspeakupdatetimer.reset(); } void loop() { datarequest(); readparticalsensor(); if (thingspeakupdatetimer.timepassed(20000, true)) { sendhttpdata(); } } auto lastread = millis(); void readparticalsensor() { const auto n = pmsx003::reserved; pmsx003::pmsdata data[n]; pmsx003::pmsstatus status = pms.read(data, n); switch (status) { case pmsx003::ok: { serial.println("_________________"); auto newread = millis(); serial.print("wait time "); advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 17 serial.println(newread lastread); lastread = newread; // for loop starts from 3 // skip the first three data (pm1dot0cf1, pm2dot5cf1, pm10cf1) for (size_t i = pmsx003::pm1dot0; i < n; ++i) { serial.print(data[i]); serial.print("\t"); serial.print(pmsx003::datanames[i]); serial.print(" ["); serial.print(pmsx003::metrics[i]); serial.print("]"); serial.println(); } rd_pm1 = data[4]; rd_pm2 = data[5]; rd_pm10 = data[6]; break; } case pmsx003::nodata: //serial.println("nodata"); break; default: serial.println("_________________"); serial.println(pmsx003::errormsg[status]); }; } void datarequest() { if (fetchdatatimer.timepassed(1000, true)) { serial.println("asking for data"); wire.requestfrom(20, 14); } if (wire.available()) { uint8_t inbyte = wire.read(); serial.println(inbyte); indata[incount] = inbyte; incount++; } if (incount == 14) { serial.println("i2c data updated"); rd_soundlevel = indata[0] << 8; rd_soundlevel += indata[1]; rd_uvlevel = indata[2] << 8; rd_uvlevel += indata[3]; rd_airquality = indata[4] << 8; rd_airquality += indata[5]; //+= (equivalent) = rd_airquality = rd_airquality + indata[5]; // rebuild float data from raw byte data *((uint8_t*)(&rd_temprature) + 3) = indata[9]; *((uint8_t*)(&rd_temprature) + 2) = indata[8]; *((uint8_t*)(&rd_temprature) + 1) = indata[7]; *((uint8_t*)(&rd_temprature) + 0) = indata[6]; serial.print("temp: "); serial.println(rd_temprature); // rebuild float data from raw byte data *((uint8_t*)(&rd_humidity) + 3) = indata[13]; *((uint8_t*)(&rd_humidity) + 2) = indata[12]; *((uint8_t*)(&rd_humidity) + 1) = indata[11]; *((uint8_t*)(&rd_humidity) + 0) = indata[10]; serial.print("humidity: "); serial.println(rd_humidity); serial.print("sound level set to: "); serial.println(rd_soundlevel); incount = 0; } } // packages data and sends to thingspeak rest void sendhttpdata() { advances in technology innovation, vol. 7, no. 1, 2022, pp. 01-18 18 //https://api.thingspeak.com/update?api_key=fz7y8ql5ibyb0vol&field1=0 string httpurl = "http://api.thingspeak.com/update?api_key=fz7y8ql5ibyb0vol"; string datastring = "&field7=" + (string)rd_soundlevel + "&field8=" + (string)rd_uvlevel + "&field3=" + (string)rd_airquality + "&field1=" + (string)rd_temprature + "&field2=" + (string)rd_humidity + "&field4=" + (string)rd_pm1 + "&field5=" + (string)rd_pm2 + "&field6=" + (string)rd_pm10; httpurl += datastring; serial.println(httpurl); string payload = ""; if (http.begin(client, httpurl)); { int httpcode = http.get(); // httpcode will be negative on error if (httpcode > 0) { if (httpcode == http_code_ok) { payload = http.getstring(); serial.println(payload); } } else { serial.print(f("[http] get... failed, error: )")); payload = http.errortostring(httpcode).c_str(); serial.println(payload); } serial.print("http code: "); serial.println(httpcode); http.end(); client.flush(); client.stop(); } //return payload; }  advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 complex independent laboratory tests to signify fuel economy and emissions under real world driving albert boretti 1,* , petros lappas 2 1 independent scientist, bundoora, australia 2 rmit, bundoora, australia received 27 july 2018; received in revised form 21 august 2018; accepted 13 september 2018 abstract we discuss the shortcomings of the current european union emission rules, which are not likely to produce any improvement of fuel economy and emissions during real-world driving vs. the pre-diesel gate rules, because of flaws in the prescribed laboratory and on-the-road tests. the present chassis dynamometer emissions certification test is oversimplified, not representative, and not properly performed. the simple addition of generic on-the-road real-world driving tests does not help, because these tests have poor accuracy and repeatability. therefore, we suggest the use of a more realistic, complicated, suite of driving cycles, to be rigorously performed with chassis dynamometer equipment by independent bodies, rather than the original equipment manufacturers (oems). additionally, we suggest that emission limits be revised, to permit the optimal mix between different engine technologies and different fuels. keywords: internal combustion engine, emissions, fuel consumption, certification 1. introduction in the aftermath of the volkswagen group (vw) emissions scandal of 2015, boretti [1], the move to real driving emissions (rde) tests has been drastically accelerated. the new emission rules will have to be closer to real-world driving and designed to deliver the best global results in terms of environment, economy, and sustainability. certainly, the emission tests will have to be much more complicated and performed by independent bodies. the new emissions tests must be carefully designed to not simply phase out the internal combustion engine (ice) for the sake of electric mobility, which can in many cases have serious environmental and economic disadvantages. for a historical perspective, vw was accused of having programmed their diesel engines to “activate certain emissions controls only during laboratory emissions testing” causing “the vehicles' nox output to meet us standards during regulatory testing but emit up to 40 times more nox in real-world driving”. the accusation was technically flawed, as the emission standards solely required compliance during the prescribed procedure, the ftp, in full laboratory tests. there is no emission standard that requires a vehicle to comply with certain emissions or fuel consumption limits for any other vehicle use or test equipment. the vw cars homologated for the us market were compliant with the ftp. however, these vehicles were then emitting different amounts of pollutant and using different amounts of fuel when operated differently. this was no surprise. there is no reason to expect the same limits to be satisfied over every other possible operation of the vehicle under every possible condition. the measurements collected by the consultants of the icct were performed without any scientific method by using inappropriate schedules vaguely defined “real world driving”. simply, the cars were tested on the road. they discovered what * corresponding author. e-mail address: a.a.boretti@gmail.com advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 60 many automotive engineers already knew: the oems tune their products to perform well on the prescribed certification tests. apart from the specific “defeat device” (en.wikipedia.org/wiki/defeat_device) used to turn-off the nox emissions control when not covering the regulatory cycle (so yielding better fuel economy and engine performance), every oem uses techniques to deliver good performance on the homologation test without penalizing the real-world driving operation. while vw certainly used defeat devices, it is not known if other oems manipulated their controls to identify testing conditions, intentionally turning on and off features during testing and not testing. it is however shared knowledge that a specific calibration is performed for the test cycle of the country of homologation. the calibration is not advanced, nor mature enough, to reduce emissions during off cycle as well as it does during the specific cycle of homologation. until new emission standards are defined, a vehicle remains compliant if the emissions fall below the limits during the prescribed certification tests. compliance is not determined in any other way. as discussed in boretti [1], the united states environmental protection agency (epa) and the united states prosecutes, initiated by the action of the international council on clean transportation (icct) have forced the oem towards a rapid transition to battery based electric mobility. the latest decision of the eu to ban the internal combustion engine (ice) by 2030, which does not leave much opportunity to improve the ice, is a logical consequence of the vw scandal, as predicted in boretti [1]. however, electric mobility is very far from becoming a real substitute, boretti [2]. hence, there is a need to properly improve emission standards. as europe was the driving force behind the rise of the diesel for passenger car applications, it was not a surprise that europe was the first to react to the scandal with different measures, including the definition of new emission standards. the procedure based on the anachronistic new european driving cycle (nedc), a cycle designed by using a ruler, is being replaced by a procedure based on the worldwide harmonized light vehicles test cycle (wltc), with the transition from nedc to wltc occurring over the period 2017-2019. passenger cars must still satisfy pollutant emissions below the euro 6 thresholds and be labelled with their co2 emissions. while there are several wltc test cycles applicable to vehicle categories of different power-to-mass ratio, a given passenger car must perform within the standards only over a single test cycle. a single test cycle was also only required by the nedc. however, in addition, rde supplementary tests have been introduced. the feedback from independent chassis dynamometer and rde tests is still missing, as it is premature to expect such a feedback from new rules not even being completely introduced. however, these two measures – the nedc replaced by the wltc, and the introduction of rde supplements are not expected to ensure that the real-world emissions are really within the agreed euro 6 emission standards. within australia, the current minimum standard for new light vehicles is adr 79/04, based on the euro 5 standards, australian government department of infrastructure, regional development and cities [3]. this rule is still being reviewed to consider whether australia should adopt the euro 6 standards for new light vehicles. it is still unclear if, and for how long, australia will continue to accept vehicles declared compliant by the original equipment manufacturers (oem) with euro 5 and euro 6 standards. it is also unclear whether emissions compliance will be determined over the chassis dynamometer with the nedc or wltc, and/or over laboratory tests, and/or supplemented with rde tests. the requirement in euro 6 regulations to further lower the nox limit of diesel-powered vehicles down to the same limit as gasoline vehicles have significantly raised the cost of the diesel. at the same time, the regulations reduce the competitiveness of the diesel regarding fuel economy. the euro 6 regulations drastically increased the cost of diesel, making them a very difficult commercial proposition for subcompacts and minicars, while still providing advantages for long highway drives in large sedans. the novel emission standards will also have to carefully weigh the minimum amount permitted for all the regulated pollutants, to permit the best mix of different solutions in the different segments, and for different uses, to achieve the best global outcomes. advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 61 fig. 1 presents an example of traffic congestion, in melbourne, victoria, australia. the drivers of passenger cars and light-duty vehicles experience real-world driving conditions that have very little in common with the short, highly stylized, simplified, driving schedule that are used for emission certification. melbourne’s suburban and city roads are struggling to meet the demands of the fast-growing population. peak hour has stretched to six hours a day across melbourne’s congested road network, 6:30am to 9 am and 3 pm to 6:30 pm each day. this translates in longer, more frequent stops, and driving at a small fraction of the speed limit during the lengthened peak-congestion periods. according to www.tomtom.com, in 2016 the increase in the morning peak travel time for melbourne was 55%, while the increase in the evening peak travel time was 58%. the global congestion level was 33% more time if compared to free flow uncongested conditions, or 34 minutes extra travel time per day, for two average rides of 103 minutes per day. therefore, during peak hours, commuters may spend more than one hour and one half for every section of their return trip, experiencing driving conditions that have nothing to do with the new european driving cycle (nedc) or the worldwide harmonized light vehicles test cycle (wltc) used in the certification test. fig. 1 traffic congestion in melbourne, australia the aim of the paper is to discuss the changes needed in the european union emission rules to ensure that the compliant vehicles will then meet the expectations of emissions and fuel economy when driven on the road, while accounting for the use of all the available fuels and different engine technologies (e.g., stoichiometric, lean-burning homogeneous or stratified, premixed or diffusion combustion, spark or compression ignition, see boretti and watson [4], boretti [5], boretti and watson [6], boretti [7], boretti, paudel and tempia [8]). diversification of engine technologies and combustion fuel supply, not only traditional fossil fuels, but also alternative fossil fuels and synthetic fuels and biofuels, see dhinesh et al. [9], annamalai et al. [10], subramani, parthasarathy, balasubramanian, and ramalingam [11], dhinesh and annamalai [12], dhinesh, raj, kalaiselvan and krishna moorthy [13], should also be considered in determining the emission levels. this is because emissions cannot be the same for different fuels and different engine technologies, as every fuel and engine technology has its own emission advantages and disadvantages. the paper first examines the flaws of the current laboratory procedures, then the pitfalls of the current additional on-road tests. a suite-of-cycles laboratory test is then proposed to address the issues of repeatability, representability, and reliability. a discussion and conclusion section then close the paper. http://www.tomtom.com/ advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 62 2. flaws of current laboratory procedures fig. 2 nedc cycle. velocity vs. time fig. 3 nedc cycle. velocity vs. distance fig. 4 wltc cycle. velocity vs. time advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 63 fig. 5 wltc cycle. velocity vs. distance figs. 2-3 and figs. 4-5 present the nedc and wltc schedules, while table 1 and table 2 summarizes the main parameters of the two cycles. all the euro rules, including the latest euro 6 rules, have been based for many years on the unrealistic, simplistic, short, cold-start, new european driving cycle (nedc). the nedc is a stylized driving speed pattern with low accelerations, constant speed cruises, and many idling events. this cycle was designed by using a ruler, with 4 very simplistic city driving sections, followed by 1 extra urban driving section that is concluded with a sharp deceleration from 120 km/h to rest, as shown in fig. 2. the nedc cycle, and the procedure that was using this cycle had many critics, as it is reported in the literature: table 1 nedc parameters phase duration [s] stop duration [s] distance [m] percentage stop vmax [km/h] vave w/o stops [km/h] vave w/ stops [km/h] amin [m/s2] amax [m/s2] ece15-1 195 57 994.1 29.23% 50 25.93 18.35 -0.93 1.042 ece15-2 195 57 994.1 29.23% 50 25.93 18.35 -0.93 1.042 ece15-3 195 57 994.1 29.23% 50 25.93 18.35 -0.93 1.042 ece15-4 195 57 994.1 29.23% 50 25.93 18.35 -0.93 1.042 eudc 400 39 6954.9 9.75% 120 69.36 62.59 -1.39 0.833 total 1180 267 10931.3 table 2 wltc parameters phase duration [s] stop duration [s] distance [m] percentage stop vmax [km/h] vave w/o stops [km/h] vave w/ stops [km/h] amin [m/s2] amax [m/s2] low 3 589 156 3095 26.50% 56.5 25.7 18.9 -1.47 1.47 medium 3-2 433 48 4756 11.10% 76.6 44.5 39.5 -1.49 1.57 high 3-2 455 31 7162 6.80% 97.4 60.8 56.7 -1.49 1.58 extra-high 3 323 7 8254 2.20% 131.3 94 92 -1.21 1.03 total 1800 242 23267 i. the nedc cycle is out-of-date, it does not represent real-world driving conditions (parker [14], mock, german, bandivadekar, and riemersma [15], plotkin [16], kågeson [17], steen [18], shaw [19], peker [20]). ii. the procedure is not accurate (parker [14]). iii. the fixed speeds, gear shift points and accelerations of the nedc offer possibilities for manufacturers to engage in “cycle beating” to optimize engine emission performance to the corresponding operating points of the test cycle, (mock, german, bandivadekar, and riemersma [15]). advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 64 iv. emissions from typical driving conditions would be much higher (mock, german, bandivadekar, and riemersma [15]). v. it is also claimed that the tests can be conducted at 2 km/h below the required speed for better fuel economy (mock, german, bandivadekar, and riemersma [15]). vi. roof-rails and passenger door-mirror can be removed for the test (mock, german, bandivadekar, and riemersma [15]). vii. tire-pressures for the test can be set above the recommended values thus reducing rolling-resistance (mock, german, bandivadekar, and riemersma [15]). viii. the cycle allows large emission differences between test and reality (kågeson [17]). ix. the cycle has numerous loopholes (steen [18], shaw [19], peker [20]). x. the nedc tests are not necessarily repeatable and comparable (steen [18]). xi. the nedc tests can be performed using optional economy settings which will not typically be selected by drivers (steen [8]). xii. the nedc test-cycle is performed with air-conditioning switched off (steen [18]). xiii. no official-body polices the tests (parker [14]). xiv. compliance is declared by the oem without independent verification (parker [14]). xv. the latest sharp deceleration from 120 km/h to zero never occurs in real-world driving (parker [14]). xvi. this deceleration ending the cycle especially rewards hybrid vehicles (parker [14]). xvii. the last high-speed driving section in the nedc reduces the fuel consumption over the cycle (parker [14]). xviii. the cycle does not include traffic congestion (parker [14]). xix. for diesel cars no significant nox reductions have been achieved after 13 years of stricter standards (european federation for transport and environment [21]). xx. similarly, to the nox emissions, even if not claimed so far, it is also questionable whether there has been real improvement in co2 emissions and fuel economy over the last 13 years. about these two latter statements, it is a matter of fact (us environmental protection agency [22]) that the epa has resolved a civil enforcement case against vw alleging violations of the clean air act by approximately 590,000 diesel vehicles sold in the united states. “specifically, the u.s. complaint alleges that each of these vehicles contains, as part of the engine control module, certain computer algorithms and calibrations that cause the emissions control system of those vehicles to perform differently during normal vehicle operation and use than during emissions testing. the u.s. complaint alleges that these computer algorithms and calibrations are prohibited defeat devices under the caa, and that during normal vehicle operation and use, the cars emit levels of nox significantly in excess of the epa compliant levels.” it is a fact admitted by vw in a court-of-law settlement, that the emissions of their diesel cars under real-world driving were largely exceeding the present emission standards in the united states. the actual on-the-road nox emissions of these 590,000 diesel vehicles were well above the thresholds, not only of the latest emission standards, but also on the prior emission standards, franco, sánchez, german, and mock [23], thompson, carder, besch, thiruvengadam, and kappanna [24]. the lack of any improvement of the diesel in real-world driving has been the result of flawed procedures and lack of any independent control on the compliance and co2 performances that are declared by the oem. this is not addressed by simply replacing the nedc cycle of fig. 2 with the wltc of fig. 4 and introducing inaccurate and irreproducible rde supplementary tests. advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 65 despite being longer (1,800 s vs. 1,180 s, or 23,262 m vs. 11,013 m), the wltc is still a single cycle, hence the engine and vehicle control can still be highly optimized to perform well over this cycle, leaving other vehicle operation condition unassessed. the wltc still closes with the unrealistic final deceleration from 130 km/h to rest, that disproportionately rewards hybrids and electric vehicles. the wltc still has a significant highway driving component resulting in much lower fuel consumption than during the real-world driving in congested city traffic. the wltc does not have the many stops of normal city driving. the reasons why the nedc test procedure failed was not only because the driving schedule was simplistic and unrealistic. it was also because the results of the fuel economy and emissions tests were declared by the oem and not measured by independent organizations. this yielded claims of fuel economy and co2 emissions that were inconsistent, parker [14]. this meant that the consumption of one litre of nominally equivalent petrol or diesel fuel produced very different co2 emission results. in addition, real-world driving fuel economy and emissions were largely underrated. a major flaw was that the tests were performed without any detailed specification of the actual fuel properties, and the fuel economy is not directly measured, but rather, it is indirectly computed from inaccurate formulae that use the emitted pollutant levels. in the unece r101, the fuel consumption is calculated from the measured emissions of hydrocarbons, carbon monoxide, and carbon dioxide. the fuel consumption (fc), expressed in liters per 100 km is calculated by means of the following simplistic formula for petrol engines fc = (0.118/ρ) ∙[(0.848·hc) +(0.429·co) +(0.273∙co2)] (1) and the following formula for diesel engines fc=(0.116/ρ) ∙[(0.861∙hc) +(0.429∙co) +(0.273∙co2)] (2) in the previous equations hc, co and co2 are the measured emission of hydrocarbons, carbon monoxide and carbon dioxide in g/km, while ρ is the (specific) density in kg/liter of the test fuel. as explained in parker [14], the above simplistic procedure is significantly inaccurate. pump gasoline and diesel fuels are refined products containing mixtures of many different hydrocarbons. in the case of gasoline, they may also contain a significant amount of oxygenates. the fuel properties, including the density, carbon and energy content strongly vary from one fuel pump to another. the above equations are theoretically valid only for a precise c/h ratio for gasoline or diesel. diesel fuel may have a carbon content that varies from c3 to c25, or a mass percentage of carbon in the range 84-87% with a hydrogen range of 13-16%. the specific density may range from 0.81 to 0.89. the lower heating value may range from 41.87 to 44.19 mj/kg. boiling temperatures, cetane number, and viscosity also vary significantly. a gasoline fuel may vary even more, even before accounting for mixing with methanol ch3oh and ethanol c2h5oh. a gasoline fuel may have a carbon content ranging from c4 to c12, or a percentage of carbon in weight 85-88% and hydrogen 12-15%. the specific density may range from 0.72 to 0.78. the lower heating value may also range from 41.87 to 44.19 mj/kg. boiling temperatures, reid vapor pressure, octane number, and viscosity also vary significantly. the unece r101 procedure simply does not work with real petrol and diesel fuels available at commercial pumps, because of their significantly variable properties. as an additional remark, the concentrations of hc, co, and co2 are difficult to measure with the same accuracy as the mass of fuel consumed, the density of the fuel and the lower heating value of the fuel. it is no surprise that the actual co2 emission and fuel economy figures may differ largely from the certified values. the analysis of the 2014 uk government data for 2,358 types of diesel and 2,103 petrol vehicles of parker [14] showed that same advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 66 volume of pump fuels used during the certification test by the oem, unfortunately, produced very different co2 emissions. very likely, these pump fuels also had very different energy contents in addition to very different carbon contents. the co2 emission per liter of diesel fuel was shown in parker [14] to range from a maximum of 3,049 g for a minimum of 2,125 g, with an average of 2,625 g. the co2 emission per liter of petrol fuel was shown in parker [14] to vary even more, from a maximum of 3,735 g to a minimum of 1,767 g with an average of 2,327 g. the analysis in parker [14] was based on the uk government data (uk vehicle certification agency [25]). because of fuel price (fuel consumption) and taxation (co2 emission) both contribute to the vehicle cost, co2 and fuel economy data were supposed to be consistent. apart from parker [14], the scientific literature does not report any technical discussion of the european certification test regarding the reliability of the co2 and the fuel economy figures declared by the oems. this lack of a healthy, technical discussion is what then generated the vw emissions scandal. fig. 6 relative co2 per litre of theoretically same diesel fuel as accepted by the uk govt. data august 2017 as retrieved from uk vehicle certification agency [25] figs. 6 7 present the latest data collected by the uk government for 2,560 diesels and 2,379 petrol vehicles satisfying euro 6 emission standards that were available for sale in the uk during august 2017. these are the data declared by the manufacturers and not the result of independent tests. fig. 6 shows the carbon dioxide emissions in g co2 per litre of diesel fuel consumed. the average is 2,617 g of co2 per litre. however, apart from outliers which are very likely errors in the transcription, there is a large spreading between different cars of several percentage points that is illogical, as a litre of diesel should produce the same co2 emission, if one assumes that all pump fuels are equivalent for emissions purposes. fig. 7 shows the carbon dioxide emission in g co2 per litre of petrol fuel consumed. the average is 2,310 g of co2 per litre. however, apart from outliers which are very likely errors in the transcription, there is also here a noticeable spreading between different cars of several percentage points that is illogical, as the same litre of petrol should produce the same co2 emission. it stands to reason that one standard liter of diesel produces the same amount of co2, and a similar argument can be made for a standard liter of gasoline, only when the combustion of the fuel and the after treatment of the exhaust gases is complete, converting all the hydrocarbons to co2 and h2o. as evidenced by exhaust measurements, this complete conversion is indeed the case for modern vehicles. in carefully designed experiments where the fuel economy and the carbon dioxide emissions are both measured with accuracy, and the same fuel is used, the spreading as found in the uk data is unlikely to occur. in addition to verifying that vehicles pass newly defined emission limits over a suite of more realistic and complicated schedules, there is also the need to make the measurements more rigorous and to perform these measurements in independent laboratories. advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 67 fig. 7 relative co2 per litre of theoretically same petrol fuel as accepted by the uk govt. data august 2017 as retrieved from uk vehicle certification agency [25] 3. flaws of current real-world-driving tests the controversy over dynamometer vs. real-world driving testing, and the criticisms of emission standards, has increased after the vw emission scandal, costlow [26]. the discussion generated various solutions aimed at closing the gaps, such as the use of portable emissions measurement systems (pems) for real-world mobile emissions testing, birch [27], or birch [28]. on the road measurements with pems are becoming more and more popular. the eu has been the first to adopt rde tests to measure the pollutants emitted on the road, association des constructeurs européens d’automobiles [29], with pems. these rde tests do not replace the chassis dyno full laboratory test, but they complement the standard test. it is very questionable to claim that compliance with the standard flawed procedure, plus compliance of the rde tests, ensure that cars will now deliver low emissions for on-road conditions. every rde test is different from another. there are major factors (e.g., traffic, weather, stops) that are beyond control and the measurements are inaccurate. apart from road and weather conditions, there is also no “standard” pems equipment defined, and equipment manufactured by different suppliers may deliver different results. pems measurements cannot provide the same accuracy as a full laboratory experiments on a chassis dynamometer. rde step 1 (with a nox conformity factor of 2.1) has applied since 1 september 2017 to new car types. it will apply to all types as of september 2019. rde step 2 (with a nox conformity factor of 1.0 plus an error margin of 0.5) will apply in january 2020 for new types and then from january 2021 for all types. as association des constructeurs européens d’automobiles [29] admits, conformity factors are defined to account for errors, as the pems tests are not as accurate as a full laboratory system, so they will not measure to the same level of repeatable accuracy. while association des constructeurs européens d’automobiles [29] states that the oems must set their design objectives well below the legal limit to be certain about complying, it is still unclear which legal limit they are referring to. so far, there is no legislation prescribing threshold pollutant emissions other than the full laboratory cold start nedc. as an example of rde tests on australian roads, abmarc [30] presents a summary of the emissions and fuel consumption test results from seventeen different passenger and light-duty vehicles measured by pems. the number of vehicles powered by petrol, diesel, and lpg were 10, 6 and 1 respectively. each vehicle was tested twice, with one cold and one warm. the testing was conducted on melbourne roads between may 2016 and march 2017, i.e. winter to summer, under strong variable weather conditions. the vehicles tested were 2014-year models or newer taken from the general service fleet and they have driven at least 2,000 km but no more than 85,000 km. the tests were conducted by driving each vehicle around a route consisting of urban, extra-urban and freeway driving, with approximately one-third of the test being driven in each segment. each test is driven in normal traffic conditions. the covered distance is more than seven times the distance covered during the nedc. advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 68 the actual velocity schedule is not provided in the report abmarc [30]. it would have been interesting to compare the nedc velocity schedule with the rde velocity schedule, and possibly compute the energy requirements and the stop timings of both. similarly, relevant, especially for nox, could have been a comparison of the temperature traces of air, metal, and media, also not provided in abmarc [30]. on average, the real-world fuel consumption across all vehicles tested was 25% higher than the official fuel results based on the cold start nedc tests. this is not a surprise. the fuel economy always changes to the driving schedule. the average fuel consumption of vehicles improved when tested with a warm engine. the real-world average fuel consumption for warm engines was 22.9% higher than the official results on the nedc tests. the few percentages penalties due to cold start are also not a surprise. one interesting result was that fuel economy penalties were larger for diesel than petrol vehicles. on average, diesel vehicles have the highest variation between real-world fuel consumption and the laboratory results, with 30.4% higher consumption during the cold test. abmarc [30] suggests that the real-world fuel consumers of diesel vehicles is harder to predict based on the nedc laboratory results. we add those individual drivers may provide different fuel economies covering the same path. regarding the exceedance of specific laboratory pollutant limits during real-world driving, all the nox limit failures were by diesel vehicles. only 1 of the 6 diesel vehicles satisfied the limit when tested on the road. diesel vehicles have been otherwise usually compliant for pm emissions with 1 exception of the cold test only. pm emissions were comfortably met for the cold test, but not during the hot test. two of the 10 petrol vehicles exceeded the co limits both hot and cold. in the summary table of abmarc [30], which only showed data for cold conditions, the 3 diesel euro 4 vehicles exceeded the nedc nox and hc+nox limits, while they complied with the co limit. one of the three failed the pm limit. the 2 petrol (gasoline) euro 4 vehicles passed the nox, co and nhmc tests. the only one euro 5 diesel vehicle failed the nox and hc+nox tests, but passed the co and pm. of the 7 euro 5 petrol vehicles, 2 failed the co test, and 1 the nhmc test while passing all the other tests. finally, of the 2 diesel euro 6 vehicles, 1 failed the nox and hc+nox limits and the only one euro 6 petrol vehicle passed all the tests. the additional vehicle tested was an lpg fueled euro 4 compliantly and passed all the tests. it is not a surprise that the diesel struggled with the nox test. the nox exceedance may be the result of higher temperatures during real-world driving. higher ambient air temperatures, as well as higher temperatures of metal and media in the longer rde, may contribute to the higher nox. these tests only demonstrate that different driving schedules may yield different fuel economies and that the lean burning diesel engines struggle with nox emissions. there is a significant in-cylinder production of nox and an inadequate reduction of it by the after treatment relative to the certification test emission requirements. the co from 2 petrol vehicles and the pm of 1 diesel were probably the result of lack of service. 4. proposed suite-of-cycles laboratory tests fig. 8 and 9 are examples of results from this independent laboratory testing of a diesel 2014 chevrolet cruze diesel, and of a gasoline mazda 3 with ieloop. these data are from the downloadable dynamometer database and were generated at the advanced powertrain research facility (aprf) at argonne national laboratory under the funding and guidance of the united states department of energy (doe), argonne national laboratory [31]. the figures summarize the fuel economy results simplistic and anachronistic driving cycles such as the nedc, but also a single more complex cycle, such as the wltc, must be replaced with a suite of more difficult cycles. an example of the use of a limited suite of cycles, but only for fuel advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 69 economy tests, is from argonne national laboratory [31], which offers in their the downloadable dynamometer database (d3) publicly available testing data regarding advanced technology vehicles including a few conventional vehicles. fig. 8 fuel economy of a 2014 chevrolet cruze diesel. test fuel is type 2007 cert diesel hf0582, fuel density 0.851 kg/litre, fuel net lhv 42.796 mj/kg fig. 9 fuel economy of a 2014 mazda 3 with ieloop. fuel type epa tier ii eee hf0437, fuel density 0.742 kg/litre, fuel net lhv 42.68 mj/kg a solution to the flaws of the current procedures is to perform the tests independently from the manufacturers, by using the same certification fuel of the same properties, starting from the c/h ratio and the lower heating value, and to measure the fuel consumption and the emissions with accuracy. 5. discussion and conclusions even without using defeat devices, the oems have found their way to achieve fuel consumption and emissions results during the cold start nedc that drastically differ from the real-world driving emissions and fuel economy that the customers will then experience in their every-day use of the vehicle, abmarc [30]. the new emission rules will have to address this major pitfall, to make mass mobility more fuel efficient and less polluting. to prevent the sale of vehicles whose real-world driving emissions are far from the current certification levels, it is not acceptable to have uncertain measurements by the oem on a single certification cycle, followed by independent, poorly defined, inaccurate and irreproducible rde tests on the road. the new rules will have to address other major failures of the regulations, such as the one concerning plug-in hybrid vehicles. instead of the current protocol of testing plug-in hybrids over one drive cycle discharging the battery, the revised rules should add a test without the battery connected. the added test would compensate for the unrealistic zero fuel consumption and emissions during the first cycle. similarly, the new rules will have to prevent the recharging of the traction battery of the hybrid electric vehicles during the final sharp braking event 120 km/h (nedc) or 130 km/h (wltc) to rest that is nowhere to be experienced during real-world driving in europe but helps hybrid electric vehicles. also relevant is a different weight of city and highway driving, as hybrids have advantages in stop-and-go traffic, but shortcomings in highway driving, and the length of the travel. advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 70 properly designed new real-world driving emissions tests will completely change the powertrain mix from the present regulations. in addition to lower cost ices that can run on gasoline, diesel and alternative fuels, such as ethanol, methanol, lpg, cng, lng, dme and ammonia, the new emission rules should promote a hybridization of powertrains. a major hurdle to better cars powered by ices is the proposed ban of the ice in favor of electric cars in europe, oltermann [32], castle [33], freedland [34], adepetu and keshav [35]. as the electric vehicle mass mobility is still far from being demonstrated to be superior under the economic and environmental criteria of ice based mobility, this ban will be hopefully revised. otherwise, the car makers will not invest in improving the ice technology. as discussed in boretti [2], it is not feasible in a growing world to completely phase out the ice in favor of electric cars recharged by renewable energy sources. hence, better emission standards for ices powered vehicles are needed more than ever. the use of pems on vehicles tested on the road is not a reliable solution to the present unrealistic certification tests. consistent test conditions cannot be enforced, and the results will be inaccurate. on the road, real-world driving tests cannot produce fair assessments. the only positive aspect of these tests is that they are performed by independent bodies and not the oem, and they use longer and more realistic driving conditions than the nedc. the use of pems on vehicles tested on the road is not a reliable solution to the present unrealistic certification tests. consistent test conditions cannot be enforced, and the results will be inaccurate. on the road, real-world driving tests cannot produce fair assessments. the only positive aspect of these tests is that they are performed by independent bodies and not the oem, and they use longer and more realistic driving conditions than the nedc. there is certainly a need for standardized and repeatable procedures, but still using rigorous chassis dynamometer tests, that are based on more complex and realistic driving conditions. hence, what is needed is a chassis dynamometer full laboratory procedure that comprises multiple driving schedules, this time performed by independent bodies. this novel testing procedure will reduce the ability of the manufacturers to implement “defeat devices”, but also limit the use of emissions reduction technologies that are only effective on a single, test cycle such as the nedc or the wltc. it is proposed that the pollutant thresholds should be dynamically adjusted to permit the best tradeoff. for example, the larger nox emissions of the diesel engine (relative to the gasoline engine) should be compensated by its much larger fuel conversion efficiencies over most of the load and speed map. apart from combined cycle gas turbine (ccgt) power plants and large stationary diesel power generators, most fossil fuel powered electrical generators in the world operate at a fraction of the thermal efficiency of diesel engines for transport. this means that the diesel engine is still needed, and more stringent emission standards can be applied to diesel generators to compensate for possible laxer regulations in transport diesel. we suggest the definition of new emission rules be used as an opportunity to revise current policies that fail to produce balanced societal outcomes for the environment and a sustainable economy. new emission rules should be universally applicable to all alternative vehicles ranging from electric cars to vehicles powered by hydrogen carrier fuels. we have discussed the pitfalls of the current european union emission rules, that will not produce any improvement of fuel economy and emissions during real-world driving vs. the pre-diesel gate condition. this is because of the flaws in the prescribed laboratory and on-the-road tests that have been evidenced in the paper. present laboratory tests are based on a given, simplistic velocity schedule. however, they may be accurate and reproducible, and thus reliable, if performed by independent bodies. on the other hand, real-world driving tests are not very well defined and not repeatable, while emissions and fuel economy measure with poor accuracy. to ensure that emission compliant vehicles will meet expectations in terms of emissions and fuel economy when driven in the real world, it is necessary to introduce accurate, repeatable, representative, complex, laboratory tests independently performed by the certification bodies. advances in technology innovation, vol. 4, no. 2, 2019, pp. 59-72 71 as a further measure, to ensure the optimal mix between different engine technologies (e.g., stoichiometric, lean-burning homogeneous or stratified, premixed or diffusion combustion, spark or compression ignition) and different fuels, such as diesel, gasoline, lpg, cng, lng, ethanol, methanol, dme, ammonia, there is a need to dynamically adjust the pollutant emissions thresholds to compensate fuel economy and carbon dioxide emission. it is to be noted that although lean-burn, compression ignition, diffusion combustion engines may fail to meet extremely stringent emissions of nitrogen oxides, they provide the opportunity to use combustion fuels more efficiently. they also can drastically clean-up the air of extremely polluted areas where some pollutants in the air such as particulate matter, are an order of magnitude more concentrated than at the tail-pipe after the particle trap. this is not only the case for many cities in china, but also the case of some cities in europe, especially during the winter season. hence, policy makers should keep in mind all the issues in designing certification tests if targeting the best outcome for real-world consumers. acknowledgement the authors received no funding and declare no conflict of interests. nomenclature ccgt combined cycle gas turbine epa environmental protection agency (us) icct international council on clean transportation ice internal combustion engines lhv lower heating value nedc new european driving cycle oem original equipment manufacturers pems portable emissions measurement systems rde real driving emissions ftp federal test procedure 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[35] a. adepetu and s. keshav, “the relative importance of price and driving range on electric vehicle adoption: los angeles case study,” transportation, vol. 44, no. 2, pp. 353-373, 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 vibration analysis of two-directional functionally graded sandwich beams using a shear deformable finite element formulation vu nam pham 1, 2 , dinh kien nguyen 2, 3, * , buntara sthenly gan 4 1 thuyloi university, 175 tay son, dong da, hanoi, vietnam 2 graduate university of science and technology, vast, 18 hoang quoc viet, hanoi, vietnam 3 institute of mechanics, vast, 18 hoang quoc viet, hanoi, vietnam 4 department of architecture, college of engineering, nihon university, koriyama, japan received 17 march 2019; received in revised form 10 april 2019; accepted 10 may 2019 abstract free and forced vibration analysis of two-directional functionally graded sandwich (2d-fgsw) beams using a shear deformable finite element formulation is presented. the beams considered in this paper consists of three layers, a homogeneous ceramic core, and two functionally graded skin layers. material properties of the skin layers are supposed to vary in both the thickness and length directions by power gradation laws. based on a refined shear deformation beam theory, in which the transverse displacement is split into bending and shear parts, a novel finite element formulation is derived and employed in the analysis. natural frequencies and dynamic response to a harmonic load of the beams with various boundary conditions are computed, and the influence of the material distribution and the layer thickness ratio on the vibration characteristics of the beams is highlighted. numerical results reveal that the variation of the material properties in the longitudinal direction has a significant influence on the vibration behavior of the beams, and fgsw beams can be designed to achieve desired vibration characteristics by appropriate selection of material grading indexes. keywords: 2d-fgsw beam, refined shear deformation theory, vibration analysis, finite element formulation 1. introduction sandwich structures with high strength-to-weight ratio are widely used to fabricate structural elements in aerospace engineering. in order to improve the mechanical performance of these structures under complex loadings, functionally graded materials (fgms), a new type of composite materials initiated by japanese researchers in 1984 [1], have been incorporated in the sandwich construction in recent years. understanding the mechanical behavior of functionally graded sandwich (fgsw) structures in general, and vibration of fgsw beams, in particular, is crucial for using this new composite material effectively. investigations on the vibration of fgsw beams, the topic discussed in this paper, are briefly discussed below. pradhan and murmu [2] used the modified differential quadrature method to compute natural frequencies of fgsw beams resting on an elastic foundation. the dependence of material properties upon temperature was considered in the work. based on the element free galerkin method, amirani et al. [3] studied free vibration of an fgsw beam with an fgm core. the authors employed two micromechanics models, voigt and mori-tanaka models, to evaluate the effective material properties of the beams, and they showed that the natural frequencies based on mori-tanaka scheme are slightly lower than that using voigt model. adopting a hierarchical displacement field, mashat et al. [4] derived a finite element formulation * corresponding author. e-mail address: ndkien@imech.vast.vn tel.: +84-24-37628006; fax: +84-24-37622039 advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 153 for evaluating natural frequencies of laminated and sandwich beams with material properties varying by a power gradation law. free vibration and buckling of fgsw beams were considered by bennai et al. [5] by using a new refined hyperbolic shear deformation beam theory. in [6, 7], vo et al. presented a refined shear deformation theory and then improved it to form the quasi-3d theory by taking thickness stretching effect into account for studying free vibration and buckling of fgsw beams. recently, su et al. [8] employed the modified fourier series to compute fundamental frequencies of fgsw beams resting on an elastic foundation. in many practical circumstances, the unidirectional fgm in the above-cited papers may not be so appropriate to resist multi-directional variations of mechanical and thermal loadings, and development of fgm with material properties varying in two or three spatial directions is necessary. several investigations on vibration analysis of fgm beams with material gradation in both the thickness and length directions have been reported in recent years [9-12]. investigation on the mechanical behavior of 2d-fgsw beams, however, is still very limited. to the authors’ best knowledge, there is only a study by karamanli in [13], where static bending of fgsw beams with material properties varying in both the thickness and length directions by power gradation laws under uniform distributed load was studied by the symmetric smoothed particle hydrodynamics method. in order to explore the behavior of this new type of structure in some further, a finite beam element is formulated in this paper for studying free and forced vibration of two-directional functionally graded sandwich (2d-fgsw) beams. the beams are considered to be formed from three layers, a homogeneous isotropic ceramic core and two fgm skin layers with material properties varying in both the thickness and length directions by power gradation laws. a refined shear deformation beam theory, in which the transverse displacement is split into bending and shear parts, is adopted to derive the element stiffness and mass matrices of the beam element. thus, in addition to the vibration of the 2d-fgsw beams considered herein for the first time, the refined theory which allows to include the shear and rotary inertia effects by dividing the transverse displacement into bending and shear parts is also a new feature of this paper. the theory with the parabolic distribution of shear deformation in the beam thickness does not require a shear correction factor, and with the mentioned advantages, it has been widely adopted in vibration and buckling analysis of fgsw plates [14-17]. using the derived formulation, natural frequencies and dynamic response of the beams with various boundary conditions to a harmonic load are computed, and the effects of material distribution, the layer thickness ratio and the aspect ratio on the vibration behavior of the beams are examined and highlighted. 2. 2d-fgsw beam model a 2d-fgsw beam with a rectangular cross-section (bxh) as depicted in fig. 1 is considered. the beam is assumed to form from three layers, namely a core of pure ceramic and two skin layers made of ceramic-metal fgm. in the figure, the x-axis is chosen on the mid-plane, and the z-axis is perpendicular to the mid-plane and directs upward. denoting z0, z1, z2, and z3 as the vertical coordinates of the bottom layer, layer interfaces, and the top layer, respectively. layer 1: 2d-fgm layer 3: 2d-fgm layer 2: ceramic b 0z =-h/2 3z =h/2 y z h x z y 2z 1z fig. 1 geometry of 2d-fgsw beam the beam is considered to be made of ceramic and metal whose volume fraction varies in the thickness and length directions by power gradation laws as [13] advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 154       1 0 1 0 1 1 2 2 2 3 3 2 1 for , 2 0 for , 1 for , 2 and 1z x z x n n m n n c m z z x z z z z z l v z z z z z x z z z z z l v v                                 (1) where vc and vm are, respectively, the volume fraction of ceramic and metal; nx and nz are the grading indexes, defining variations of the constituent materials in the xand z-directions, respectively. noting that when nx=0 the beam deduces to the conventional 1d-fgsw beam with the material properties vary in the thickness direction only. the effective property such as young’s modulus and mass density, p(x,z), evaluated by the voigt model is of the forms         1 0 1 0 1 1 2 2 2 3 3 2 ( ) 1 if , 2 , if , ( ) 1 if , 2 z x z x p p m c c c p p m c c z z x p p p z z z z z l p x z p z z z z z x p p p z z z z z l                                      (2) where pm and pc are the properties of the metal and ceramic, respectively. based on the refined third-order shear deformation beam theory [6], the displacements in xand z-directions, u1(x,z,t) and u3(x,z,t), at any point of the beam are respectively given by     3 1 , ,2 3 4 , , ( , ) ( , ) ( , ) 3 , , ( , ) ( , ) b x s x b s z u x z t u x t zw x t w x t h u x z t w x t w x t      (3) where u, wb, ws are the axial displacement, transverse bending and shear displacements of a point on the x-axis, respectively. in eq. (3) and hereafter, a subscript comma is used to denote the derivative with respect to the followed variable, e.g. , /s xw w x   . the strains resulted from eq. (3) are of the forms 3 1, , , ,2 2 1, 3, ,2 4 , 3 4 1 x x x b xx s xx xz z x s x z u u zw w h z u u w h                (4) assuming linearly elastic behavior, the constitutive equations for the beam are of the form 2 , 1 2(1 ) x x xz xz e e           (5) where  is poisson’s ratio, assumed to be unchanged. the strain energy (u) resulted from eqs. (4) and (5) is   2 2 11 , 12 , , 22 . 23 , ,2 0 2 2 44 , , 66 , 11 22 44 ,2 4 2 4 1 1 8 2 2 2 3 8 16 8 16 3 9 [ ] l x x xz xz x x b xx b xx x s xx v b xx s xx s xx s x u dv a u a u w a w a u w h a w w a w b b b w dx h h h h                      (6) where a11, a12 …, a66, b11, b22, b44 are the beam rigidities, defined as advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 155 1 3 2 3 4 6 2 3 4 6 11 12 22 23 44 66 2 2 1 ( , , , , , ) (1, , , , , ) (1, , , , , ) 1 1 i i z ia z e be a a a a a a z z z z z da z z z z z dz           (7) and 1 3 2 4 2 4 11 22 44 1 ( , , ) ( , , ) (1, , ) 2(1 ) 2(1 ) i i z ia z e be b b b z z z da z z dz           (8) in eqs. (6-8), v and a denote the volume and cross-sectional area of the beam, respectively. because the effective young modulus e varies in both the thickness and length directions, the rigidities in eqs. (7) and (8) are functions of x. the kinetic energy (t) of the beam resulted from the displacement field in eq. (3) is as follows 2 2 2 2 234 6644 11 12 , 22 , , , , ,2 2 2 0 8 168 ( 2 ) 2 3 3 9 l b s b s b x b x s x b x s x s x i ii t i u w w w w i uw i w uw w w w dx h h h                (9) in which i11, i12, i22, i34, i44, and i66 are the mass moments, defined as 1 3 2 3 4 6 2 3 4 6 11 12 22 34 44 66 1 ( , , , , , ) ( , )(1, , , , ,z ) ( , )(1, , , , ,z ) i i z ia z i i i i i i x z z z z z da b x z z z z z dz       (10) the above mass moments, as the beam rigidities, also are functions of x. the potential (v) of a harmonic load, f=f0cos(ωt), considered herein has a simple form 0 |cos( )( ) fb s x xv f t w w     (11) in the above equation, the subscript x=xf means that the bending and shear transverse displacements are evaluated at the abscissa of the load f. equations of motion for the beam can be obtained by applying hamilton’s principle to eqs. (6), (9) and (11). however, due to the rigidities and mass moment are functions of longitudinal coordinate x, the coefficients of such equation are dependent on x, and thus a closed-form solution is very difficult to obtain. a finite element formulation is developed below for computing the vibration characteristics of the beam. 3. finite element formulation a two-node beam element with length l is considered in this section. the element contains six degrees of freedom per node, and the vector of nodal displacements is given by { }t u wb wsd d d d (12) where 1 2 1 , 1 2 , 2 1 , 1 2 , 2{ }, { }, { }u wb b b x b b x ws s s x s s xu u w w w w w w w w  d d d (13) are, respectively, the vectors of axial displacements, bending and shear transverse displacements at node 1 and node 2. in eq. (12) and hereafter, a superscript “t” is used to denote the transpose of a vector or a matrix. it should be noted that the order of the nodal displacements is not necessary as in eq. (12), but it is convenient to split the displacements into axial, bending and shear parts. advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 156 the displacements inside the element are interpolated from their nodal values according to 0 0 0 0 0 0 uu b wb wb wss ws u w w                         dn n d n d (14) where nu, nwb and nws are the matrices of shape functions for u, wb and ws, respectively. in the present work, the linear function is used for the axial displacement, while the hermite cubic polynomials are employed for wb and ws. in this regard, we can write 1 2{ }u u u l x x n n l l         n (15) and 1 2 3 4{ }w w w w wn n n nn (16) with 2 3 2 3 2 3 2 3 1 2 3 42 3 2 2 3 2 1 3 2 , 2 , 3 2 ,w w w w x x x x x x x x n n x n n l l l l l l l l            (17) using the above interpolation scheme, one can write the strain energy for the beam in the form       1 1 2 ne t i i i i u    d k d (18) where ne is the total number of elements, and k is the element stiffness matrix, which can be split into the sub-matrices as (10x10) aa ab as t ab bb bs t t as bs ss           k k k k k k k k k k (19) in the above, aak , bbk , ssk , abk , ask , bsk are the stiffness matrices stemming from axial stretching, transverse bending, transverse shear and couplings of these terms. these sub-matrices can be obtained by twice differentiation of the strain energy u with respect the nodal displacements, for example 2 2 2 2 2 , , b b aa ab bb u u w w u u u          k k k d d d d (20) eq. (20) gives the sub-matrices in the following forms , 11 , , 12 , , 34 ,x2 (2x2) (2x4) (2x4)0 0 0 ,x 22 ,x ,x 44 ,x2 (4x4) (4x4)0 0 ,x 66 ,x ,x 11 224 2 (4x4) 4 , , , 3 4 , , 3 16 8 16 9 l l l t t t aa u x u x ab u x w x as u x w x l l t t bb w x w x bs w x w x t t ss w x w x w a dx a dx a dx h a dx a dx h a dx b b h h h                 k n n k n n k n n k n n k n n k n n n 44 ,x4 0 0 l l wb dx         n (21) similarly, the kinetic energy of the beam can also be written in the form advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 157       1 1 2 ne t ii i i t    d m d (22) where / t  d d is the element nodal velocity, and m is the element mass matrix which can be written in sub-matrices as (10x10) b s b b b b s s b s s s uu uw uw t uw w w w w t t uw w w w w            m m m m m m m m m m (23) the mass sub-matrices in the above equation are obtained by twice differentiation of the kinetic energy with respect to the associated nodal velocities and they have the following forms   11 12 , 11 , 34 ,x2 (2x2) (2x4) (2x4)0 0 0 11 ,x 22 ,x 11 ,x 44 ,x2 (4x4)(4x4) 0 0 11 (4x4) 4 , , , 3 4 , , 3 1 b s b b l l l t t t t uu u u uw u w x uw w w u x w l l t t t t m m w w w w bs w w w w t ss w w i dx i dx i i dx h i i dx i i dx h i                           m n n m n n m n n n n m n n n n m n n n n m n n ,x 66 ,4 0 6 9 l t w w xi dx h        n n (24) due to the rigidities and mass moments are functions of x, the integrals in eqs. (21) and (24) are hardly computed explicitly. gauss quadrature is employed herein to compute the stiffness and mass matrices. with the introduced interpolations, the vector of nodal external load given by eq. (11) can be written in the form 0 element under loading cos( ) 0 0 0..... 0 0 0 0...0 0 0 t ex w wf t              f n n (25) the matrix of the shape functions in the above equation is evaluated at x=xf, the abscissa measured from the load to the left end of the element. the equations of motion for the beam in term of finite element analysis can be written in the form [18] ex  md cd kd f (26) where d, d , d are, respectively, the structural vectors of nodal displacements, velocities and accelerations; k, m, and c are structural stiffness, mass and damping matrices, respectively. rayleigh damping, in which the damping matrix c is proportional to a linear combination of mass and stiffness, is employed herein   c k m (27) where α and β are, respectively, the mass and stiffness proportional rayleigh damping coefficient, which are calculated from the critical damping ratio and the natural frequencies as 1 2 1 2 1 2 2 2 ,              (28) in the above,  is the damping ratio, taken by 5% for all numerical computation below. advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 158 4. results and discussion using the derived finite element formulation, natural frequencies and dynamic response of the 2d-fgsw beam are computed, and numerical results are reported in this section. to this end, an fgsw beam formed from alumina (ceramic) and aluminum (metal) is considered. the material properties of the constituents are as follows [7]: (1) ec=380 mpa, ρc=3800 kg/m 3 , 0.3c  for alumina (2) em=70 mpa, ρm=2702 kg/m 3 , 0.3m  for aluminum for the convenience of discussion, the three numbers as proposed in [6] are used to indicate the layer thickness ratio, for example (2-1-2) means the thickness ratio of the bottom, core, and top layers is 2:1:2. fig. 2 shows the variation of the effective young’s modulus and mass density in the thickness and length directions for (1-1-1) beam made of alumina and aluminum with nx=nz=0.5 according to eq. (2). it can be seen that young’s modulus and mass density continuously vary in both the thickness and length directions of the beam. (a) young’s modulus (b) mass density fig. 2 variation of young’s modulus and mass density for (1-1-1) beam with nx=nz=0.5 4.1. formulation verification before computing vibration characteristics of the beam, the derived formulation is necessary to confirm. since there is no data on the vibration of the 2d-fgsw beam considered herein available in the literature, the comparison is carried out for the static bending of the beam as reported in [13]. table 1 compares the maximum dimensionless deflection of the simply supported beam (ss beam) under uniform distributed load q0 obtained by the present finite element formulation with that of karamanli [13] using the symmetric smoothed particle hydrodynamics method. regardless of the grading indexes, the layer thickness ratio and the aspect ratio, the maximum deflection of the beam obtained in the present paper is in good agreement with that of ref. [13]. the dimensionless deflection in table 1 is defined as follows [13]   3 * 4 0 100 max ( )me bh w w x q l  (29) where em is young’s modulus of metal. advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 159 table 1 comparison of maximum dimensionless deflection ( *w ) of ss beam under static uniform load nx nz source l/h = 5 l/h=20 1-1-1 1-8-1 2-2-1 1-1-1 1-8-1 2-2-1 0.1 0.1 ref. [13] 10.7054 4.7401 10.9470 10.3994 4.4818 9.1047 present 10.8634 4.8064 9.4128 10.4116 4.4848 9.1096 0.5 ref. [13] 7.5039 4.2112 9.5412 7.2199 3.9561 6.5597 present 7.6124 4.2698 6.8473 7.2273 3.9586 6.5680 1 ref. [13] 6.0343 3.9030 6.9428 5.7613 3.6501 5.3608 present 6.1185 3.9570 5.6327 5.7667 3.6525 5.3658 2 ref. [13] 4.8871 3.6275 4.6673 4.6274 3.3772 4.4070 present 4.9572 3.6775 4.7321 4.6313 3.3793 4.4101 0.5 0.1 ref. [13] 8.4793 4.4862 5.7112 8.1706 4.4143 7.3680 present 8.6148 4.5492 7.6764 8.1964 4.2298 7.3839 0.5 ref. [13] 6.5069 4.0580 7.7882 6.2253 4.2331 5.7569 present 6.6011 4.1143 6.0408 6.2338 3.8040 5.7660 1 ref. [13] 5.4735 3.8004 6.1257 5.2055 3.8068 4.9004 present 5.5523 3.8534 5.1692 5.2114 3.5490 4.9064 2 ref. [13] 4.6040 3.5666 4.4251 4.3451 3.3169 4.1669 present 4.6689 3.6155 4.4873 4.3491 3.3190 4.1706 1 0.1 ref. [13] 6.9827 4.2462 6.4602 6.6753 3.5515 6.1562 present 7.0975 4.3050 6.5600 6.7054 3.9922 6.1781 0.5 ref. [13] 5.7178 3.9088 5.3861 5.4388 3.9943 5.1050 present 5.8019 3.9608 5.4616 5.4499 3.6551 5.1153 1 ref. [13] 4.9904 3.6976 4.7624 4.7252 3.6570 4.4948 present 5.0598 3.7487 4.8272 4.7288 3.4477 4.5000 2 ref. [13] 4.3387 3.5031 4.1978 4.0816 3.2549 3.9396 present 4.3982 3.5514 4.2549 4.0843 3.2566 3.9434 4.2. free vibration the fundamental frequency parameters of the ss beam are listed in tables 2 and 3 for various values of the grading indexes and the layer thickness ratio and two value of the aspect ratio, l/h=5 and l/h=20, respectively. the frequency parameters in the tables (and below) are defined as follows 2 i m i m l h e     (30) where ωi is the i th natural frequency of the beam. table 2 fundamental frequency parameter (μ1) of ss beam with l/h = 5 nx nz 1-0-1 2-1-2 1-1-1 1-2-1 1-8-1 2-2-1 0 0.5 3.2500 3.3728 3.5186 3.7904 4.5227 3.7057 1 3.5735 3.7297 3.8755 4.1105 4.6795 4.0189 5 4.4615 4.5756 4.6582 4.7690 4.9899 4.7106 0.5 0.5 3.6300 3.7134 3.8194 4.0263 4.6176 3.9640 1 3.8648 3.9816 4.0942 4.2804 4.7489 4.2086 5 4.5673 4.6620 4.7311 4.8245 5.0125 4.7753 1 0.5 3.8922 3.9549 4.0378 4.2037 4.6942 4.1548 1 4.0761 4.1687 4.2596 4.4123 4.8056 4.3538 5 4.6520 4.7319 4.7906 4.8701 5.0315 4.8282 2 0.5 4.2427 4.2840 4.3402 4.4556 4.8093 4.4223 1 4.3679 4.4318 4.4956 4.6043 4.8918 4.5629 5 4.7785 4.8373 4.8807 4.9398 5.0609 4.9087 5 0.5 4.2427 4.2840 4.3402 4.4556 4.8093 4.4223 1 4.3679 4.4318 4.4956 4.6043 4.8918 4.5629 5 4.7785 4.8373 4.8807 4.9398 5.0609 4.9087 the effects of the grading indexes and the layer thickness ratio on the frequency of the beam are clearly seen from tables 2 and 3. for a given value of the layer thickness ratio, the frequency parameter of the beam increases by the increase of the advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 160 material grading indexes, regardless of the aspect ratio. this can be explained by the fact that the volume fraction of the metal, as seen from eq. (1), is lower, and thus the ceramic percentage is larger for the beam associated with higher indexes nx and nz. since young’s modulus of the ceramic is much higher than that of the metal, the rigidities of the beam with higher ceramic content are higher. the mass density of the beam with a higher ceramic content also larger, but for the constituent materials considered in this paper, the increase of the rigidities by increasing nx and nz is much faster than that of the mass moments. this explains the increase of the frequency when increasing the grading indexes. the layer thickness ratio, as seen from table 2 and 3, also influences the increase of the frequency. for example, for the ss beam with l/h=20 and a length index nx=0.5, the frequency parameter μ1 of the (1-0-1) beam increases 21.02% when increasing nz from 0.5 to 5, but the corresponding value is 20.24%, 7.51%, and 8.44% for the (1-1-1), (1-2-1), and (1-8-1) beams, respectively. a careful examination of table 2 and 3 shows that the increase of the frequency by increasing nz depends upon the value of nx also. for example, as seen from table 2, the frequency parameter increases 20.35% when increasing nz from 0.5 to 5 for (1-1-1) beam with nx=0.5, but the corresponding value for the (1-1-1) beam with nx=5 is just 11.44%. in other words, the increase of the fundamental frequency by increasing the thickness index is smaller for the beam associated with a higher length index. table 3 fundamental frequency parameter (μ1) of ss beam with l/h = 20 nx nz 1-0-1 2-1-2 1-1-1 1-2-1 1-8-1 2-2-1 0 0.5 3.3781 3.4953 3.6472 3.9387 4.7473 3.8512 1 3.7147 3.8768 4.0328 4.2889 4.9233 4.1906 5 4.6783 4.8058 4.8987 5.0239 5.2748 4.9578 0.5 0.5 3.7880 3.8629 3.9727 4.1958 4.8533 4.1320 1 4.0307 4.1510 4.2717 4.4760 5.0012 4.3988 5 4.7962 4.9026 4.9806 5.0864 5.3005 5.0306 1 0.5 4.0732 4.1260 4.2112 4.3907 4.9391 4.3413 1 4.2617 4.3563 4.4539 4.6222 5.0651 4.5594 5 4.8911 4.9812 5.0476 5.1380 5.3220 5.0903 2 0.5 4.4581 4.4884 4.5450 4.6700 5.0686 4.6374 1 4.5838 4.6477 4.7160 4.8365 5.1623 4.7923 5 5.0334 5.1000 5.1494 5.2169 5.3554 5.1813 5 0.5 5.0070 5.0168 5.0398 5.0940 5.2756 5.0808 1 5.0587 5.0853 5.1151 5.1690 5.3194 5.1496 5 5.2595 5.2904 5.3134 5.3450 5.4104 5.3284 (a) the first parameter μ1 (b) the second parameter μ2 (c) the third parameter μ3 (d) the fourth parameter μ4 fig. 3 variation of the first four frequency parameters with grading indexes of (1-1-1) ss beam with l/h = 20 advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 161 the aspect ratio l/h also slightly influences the change of the frequency parameter and the change in the frequency parameter is not significant for the beam with a lower aspect ratio l/h. for example, the fundamental frequency parameter increases 17.17% for the (2-1-2) beam with nx=1 having l/h=20 when increasing nz from 0.5 to 5, but this increase reduces to 16.42% for the beam with l/h=5. thus, the material gradation, the layer thickness ratio, and the aspect ratio are all important parameters which should be considered in designing the 2d-fgsw beam depends in order to achieve a beam with desired natural frequencies. the effect of the grading indexes on the higher frequency parameters is illustrated in fig. 3-5, where the variation of the first four natural frequency parameters with the grading indexes nx and nx is depicted for the ss, clamped (cc) and cantilever (cf) beams with a layer thickness ratio of (1-1-1) and an aspect ratio l/h=20, respectively. similar to the fundamental frequency, the higher frequencies also increase by increasing the grading indexes nx and nz, regardless of the boundary conditions. the boundary conditions may affect the amplitude of the natural frequencies, but it hardly influences the dependence of the frequency parameters upon the material grading indexes. (a) the first parameter μ1 (b) the second parameter μ2 (c) the third parameter μ3 (d) the fourth parameter μ4 fig. 4 variation of the first four frequency parameters with grading indexes of (1-1-1) cc beam with l/h = 20 (a) the first parameter μ1 (b) the second parameter μ2 (c) the third parameter μ3 (d) the fourth parameter μ4 fig. 5 variation of the first four frequency parameters with grading indexes of (1-1-1) cf beam with l/h = 20 advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 162 4.3. dynamic response the dynamic response of the 2d-fgsw beam to a harmonic load p=p0cos(ωt) is investigated in this sub-section. in order to calculate the response of the beam, the average acceleration newmark method is employed to solve eq. (26). the beam with two types of boundary conditions, namely ss and cf beams, with a harmonic load acting at the mid-span and free and, respectively are considered herein. the variation of the dimensionless deflections with the time at the loaded points of the ss and cf beams with an aspect ratio l/h=20 and a layer thickness ratio of (2-1-2) is illustrated in fig. 6 and 7 for an excitation frequency ω=10 rad/s, respectively. the deflections w* in the figures are normalized by the static bending transverse displacements of the ceramic beam, that are 3 48 * ( / 2) for ss beamc b e i w w l pl  (31) 3 3 * ( ) for cf beamc b e i w w l pl  (32) (a) nx=1, nz is variable (b) nz=1, nx is variable fig. 6 variation of mid-span dimensionless deflection with the time of ss (2-1-2) beam under harmonic load with ω=10 rad/s acting at mid-span (a) nx=1, nz is variable (b) nz=1, nx is variable fig. 7 variation of dimensionless deflection at the free end with a time of cf (2-1-2) beam under harmonic load with ω=10 rad/s acting at the free end the effect of the grading indexes on the harmonic response of the beams can be seen from the figures, where the dynamic deflections are clearly decreased by increasing the material grading indexes nx and nz , regardless of the boundary conditions. advances in technology innovation, vol. 4, no. 3, 2019, pp. 152-164 163 this effect can also be explained by the increase of ceramic content for the beam associated with the higher indexes, and this leads to higher rigidities for the beam associated with higher grading indexes, as explained above. as a result, the dynamic deflection of the beam is decreased by increasing the material grading indexes. 5. conclusions in this paper, a finite element formulation was developed for analyzing the free and forced vibration of 2d-fgsw beams. the beams were considered to be formed from three layers, a homogeneous ceramic core and two functionally graded skin layers with material properties varying in both the thickness and length directions by power gradation laws. based on the refined third-order shear deformation theory, in which the transverse displacement is split into bending and shear parts, expressions for stiffness and mass matrices of a two-node beam element were derived and employed in computing natural frequencies and dynamic response of the beams. numerical results obtained by using the formulation was compared with the published data to confirm the accuracy of the proposed formulation. a parametric study has been carried to highlight the effects of the material distribution, the layer thickness ratio and the aspect ratio on the vibration characteristics of the beams. the obtained results reveal that the material distribution and the layer thickness ratio of the beams play an important role on the vibration response of the 2d-fgsw beams. the numerical results of the present paper guide to design 2d-fdsw beams to achieve desired vibration characteristics. though the paper examined only harmonic response of the beam, the finite element formulation developed herein can be employed to compute dynamic response of 2d-fgsw beams subjected to other types of dynamic loads as well. conflicts of interest the authors declare no conflict of interest. acknowledgement this work was supported by vietnam national foundation for science and technology development (nafosted) under grant no. 107.02-2018.23. references [1] m. koizumin, “fgm activities in japan,” composites: part b, vol. 28, pp. 1-4, 1997. 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[18] m. géradin and r. rixen, mechanical vibrations, theory and application to structural dynamics, 2nd edition. england; chichester, john wiley and sons, 1997. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://journals.sagepub.com/doi/abs/10.1177/1099636214526852?journalcode=jsma https://journals.sagepub.com/doi/abs/10.1177/1099636214526852?journalcode=jsma https://journals.sagepub.com/doi/abs/10.1177/1099636214526852?journalcode=jsma callto:16(3),%20293-318 https://www.tandfonline.com/author/bennoun%2c+mohammed https://www.tandfonline.com/author/houari%2c+mohammed+sid+ahmed https://www.tandfonline.com/author/tounsi%2c+abdelouahed https://www.researchgate.net/journal/1225-4568_structural_engineering_mechanics advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 outdoor thermal comfort improvement of campus public space damrongsak rinchumphu 1,2,* , non phichetkunbodee 1,2 , nakarin pomsurin 1,2 , chawanat sundaranaga 2 , sarote tepweerakun 2 , chatchawan chaichana 3 1 department of civil engineering, faculty of engineering, chiang mai university, chiang mai, thailand 2 civil innovation and city engineering laboratory, chiang mai, thailand 3 department of mechanical engineering, faculty of engineering, chiang mai university, chiang mai, thailand received 20 september 2020; received in revised form 31 january 2021; accepted 01 february 2021 doi: https://doi.org/10.46604/aiti.2021.6453 abstract this study focuses on the design of a campus public space, located within the faculty of engineering, chiang mai university, thailand. this area faces extreme temperatures, creating uncomfortable outdoor thermal conditions and hindering activities that are expected to support the learning and social cohesion needs of students. to create the best conditions in this space, three design alternatives such as adding a pond, large trees, or shrubs were considered, and the physiologically equivalent temperature (pet) was used to calculate the outdoor thermal comfort index for each alternative. the alternatives were then compared to the base case. the pet can be calculated using the envi-met simulation software following the appropriate field data collection and calibration process. the results showed that adding large trees in the south-west area is the best design alternative. the pet for this alternative was 3.17 % lower than the base case. in addition, this design workflow is an effective working model for further outdoor public space designs to meet the constraints of effective sustainable development in any tropical campus area. keywords: outdoor public space, thermal comfort, physical equivalent temperature, design alternative 1. introduction the development of a university's outdoor activity area is often in response to the learning and social needs of students, and its building is an important policy of chiang mai university, as it has a focus on creating an environment that is attractive and suitable to be used appropriately [1]. outdoor public space development should be based on indicators that reflect the conditions for the actual use. weather conditions that are not too hot or too cold will have a positive effect on the students who use the outdoor public space for studying as the conditions outside the building are comfortable [2-4]. suitable outdoor thermal conditions for comfort are related to air temperature, relative humidity and wind speed that make the human body feel comfortable [5]. from several research studies, there are a number of outdoor thermal comfort indicators. a commonly used indicator is the physiologically equivalent temperature (pet) [6-8]. the pet is based on modeling the heat balance of the human body. the numerical values are based on the evaporation of moisture related to the heat and air mass, and it is the heat that can maintain the heat balance in humans. pet is also an indicator that can explain the thermal exchange between the body and the environment, and it is used for outdoor comfort analysis. the measured variables are air temperature, relative humidity, wind speed, average heat radiation value and the variables of the human natural state that tries to present them, so they are comparable to human feelings [6, 9]. * corresponding author. e-mail address: damrongsak.r@cmu.ac.th tel.: +66-95-9959519; fax: +66-53-892376 advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 129 to develop an outdoor public space that it is more sustainable, this study focuses on outdoor thermal comfort improvement, as represented by the pet around the area within the boundary of the lan witsawa ruamjai, which is the space for outdoor activities on the campus. the result is expected to identify the best alternative design for outdoor public space. the workflow from this study could be used as a framework for improving other campus outdoor public spaces to meet smart campus policy of universities in the future. the paper is structured in five sections: (1) introduction, (2) physiologically equivalent temperature (pet), (3) research methodology, (4) results and discussion and (5) conclusions. 2. physiologically equivalent temperature (pet) there are several indices used to measure the outdoor thermal comfort level [7, 10], for example, predicted mean vote (pmv), effective temperature (et), perceived temperature (pt), physiological equivalent temperature (pet) and universal thermal climate index (utci). according to the research conducted by johansson [11] and klaylee [12], pet is the most suitable indicator for assessing the outdoor thermal comfort. pet can be calculated by a computer program, which represents a realistic state from an airflow simulation program. the most effective simulation software is envi-met v 4.4 [9]. pet is affected by four environmental factors as follows: 2.1. air temperature air temperature is a fundamental factor in climate studies, which always changes over time and varies by season. the comfortable temperature for humans outside a building in greece, according to a study by matzarakis et al. [13], was found to be between 18-23 ºc, with relative humidity and air velocity at optimal conditions. however, srivanit & auttarat [14] conducted a study in chiang mai province, and concluded that the average outdoor comfortable condition was 23.0 – 31.0 o c, which is related to the local conditions of the area in this study. 2.2. relative humidity relative humidity is the ratio of the amount of water vapor in the air at that time compared to the amount of water vapor that the air can accept. the relative humidity in thailand, which is located in the tropical climate zone, during the summer is up to 90%, while in the winter it may drop below 40%, which is approximately 60-70% on average. however, if the relative humidity level is too high, it can make human sweat more result in difficult evaporation, and causes them to feel hot and uncomfortable. while a too low relative humidity will irritate the skin [12]. 2.3. air velocity air velocity is a factor that affects the heat transfer of the body. an uncomfortable situation may be caused by convection when the wind speed increases, and humans will feel colder than the actual temperature. due to the higher cooling rate from the body surface, humans feel 0.4 o c cooler than the actual air temperature when the wind speed increases by 1 km/hr. humans may feel especially cold if the wind speed is too high and the temperature is too low. on the other hand, if the weather is hot and the air velocity is low, the air will not take the heat out of the body, and this causes humans to feel hot and uncomfortable. the wind speed will vary depending on the physical environment and location [9]. it was found that humans feel comfortable with an air velocity of 0.25-0.50 m/s [15]. 2.4. solar radiation solar radiation is the electromagnetic waves emitted from the sun. people often call it sunlight, but the electromagnetic waves are not the only light as there are also other rays [16]. however, the radiation from the sun varies by specific place. advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 130 international studies often use a specific city or country to measure the solar radiation when calculating the outdoor thermal comfort. a survey was conducted, and it showed that the average solar radiation value for thailand was 219.9 w/m 2 [17]. furthermore, this study has found 4 factors that are not direct design elements but are consequences of the design and selection of open space. for example, increasing the number of trees or buildings can reduce the temperature of the area. in addition, from the literature review [18-19], there are experiments on modifying the area by changing the surface and green components, such as replacing the land surface with a waterscape. this will increase the water surface area, which affects the temperature and humidity of the surrounding area [19]. increasing the number of trees of various sizes can also decrease the temperature. a tree of any shape and size will affect the shading, wind speed, and solar radiation, resulting in a lower pet value and increasing outdoor thermal comfort in the area, especially in tropical areas such as chiang mai, thailand [20]. these factors can be used when planning and creating outdoor public space design alternatives as well as for determining pet, as per the purpose of this research [21]. 3. research methodology the research methodology includes two parts: the first part is selecting a study area and defining the base case and setting the alternative cases model. the second part is the process of the model simulation and analysis. 3.1. selecting study area and models setting the study area is named lan witsawa ruamjai, an open public space, located in the faculty of engineering, chiang mai university, chiang mai, thailand. it is a space that students can use for relaxation or activities in the university. this research defines the boundary of the study area using aerial images from google earth at the latitude and longitude of 18.7942153, 98.9512263, respectively (fig. 1). fig. 1 aerial view of lan witsawa ruamjai, chiang mai university fig. 2 2d model of study area presented in envi-met version 4.4 advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 131 the total area of the space is 3,023.0 m², including 1,114.4 m 2 of hardscape and 1,908.6 m² of softscape, which consists of shrubs and trees. in a radius of 50 m, the area is surrounded by buildings with 16 floors, asphalt concrete road, ditch, green spaces and big trees as shown in fig. 2. according to the design guideline in the trees-nc standard in section 2: site and landscape, the pet value depends on the land surface type, number, and location of trees and shrubs [22]. after determining the existing physical characteristics of the base case, the design alternatives will be developed following the trees – nc standard with three options of adding a pond as a water surface area and adding large trees and shrubs, specifically in the south-west of the study area. the details of the three alternative designs are shown in table 1 and presented as follows: alternative 1: replacing the surface of the space with a 2 m deep pond. the pond would be semi-natural, with a small water treatment system. the pond would increase the relative humidity and also absorbs solar radiation to reduce the pet. alternative 2: plant cork trees, shading, broad and dense foliage over an area of 10 m with perennial trees in the south-west of the study area. these trees will provide shade during daytime, especially in the afternoon when the temperature is at its peak. the large trees will also be able to block radiation from the sun. alternative 3: medium sized shrubs planted around the study area in the south-west. it may add a little shade to the study area and can provide some degree of protection against solar radiation. table 1 details of design alternatives design alternative design type details base case concrete pavement light gray color alternative 1 pond 2 m depth alternative 2 large trees diameter of shading area >10 m two large trees of native plant (cork tree) south – west* alternative 3 shrubs diameter of shading area <5 m medium sized shrubs (banyan tree) south – west* * according to the srivanit & hokao [20] explained that chiang mai, thailand is located at longitude 18.7942153 on, therefore the sun direction will lay on the south side of the area for most of the year, and the sun will raise the air temperature during the afternoon time on the west direction for the whole year, then the most efficient thermal protection concerned must be focused on the south-west direction for this study area. 3.2. model simulation processes the measured meteorological data includes the air temperature, relative humidity, wind speed and solar radiation, as these are the main factors that are directly related to the daily climate. this research was to determine the average daily temperature over the five years 2015-2019 to identify the days with the highest average temperature during the year. the data is from a weather monitoring station of the meteorological department, the northern meteorological center. the monitoring station, located in suthep subdistrict, mueang chiang mai district, chiang mai, is the closest weather monitoring station to the study area, approximately 2.35 kilometers from the site. the highest average five-year (2015-2019) temperature was on april 13, this day will be used in this study. the field data was obtained from a lutron wbgt-2010sd instrument to measure the air temperature, relative humidity, mean radiant temperature, and were calculated using a diameter globe thermometer at 75 mm. the wind velocity was measured using a hot-wire anemometer that was recorded in the testo 435-2 data logger and used to calculate the mean radiant temperature (tmrt) according to eq. (1). advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 132 18 0.71 4 4 0.4 1.335 10 [( 273.15) ( )]a mrt g g a v t t t t d       (1) where tg is the globe temperature (°c), va is the wind speed (m/s), ta is the air temperature (°c), d is the globe thermometer diameter (m) and ε is the globe emissivity (ε = 0.95). the air temperature, relative humidity and wind speed were collected from 07:00-18:00. on april 13 th , 2020, by the lutron wbgt-2010sd for the data calibration process. after collecting the weather data, the model calibration process was started by comparing the tmrt between the computer simulation and the field results. the envi-met simulation program was used for calibration, and the results of the field calibration and the five-year average dataset of the meteorological department were compared. by comparing the similarity of the data set with the root mean square error (rmse) and willmott's index of agreement (d), the rmse and d result must be within the acceptable range of 0.66-7.98 and 0.53-0.95, respectively [23]. if they are not in the range, a trial-and-error process must be applied until the rmse and d values are within the acceptable range. after three rounds of calibration, rmse = 1.94 and d = 0.75 were within the acceptable range. the four models in this study, base case and three alternative cases, are presented in fig. 3. the pet simulation results of each model will be presented in the next section. (a) base case (b) alternative 1 (c) alternative 2 (d) alternative 3 fig. 3 models showing approach for outdoor area design by envi-met version 4.4 program 4. results and discussion table 2 average pet during period 07:00-18:00 of base case and different design options. time base case alternative 1 alternative 2 alternative 3 ( o c) (%) ( o c) (%) ( o c) (%) 07:00 23.96 23.95 -0.05 23.95 -0.05 23.95 -0.05 08:00 28.85 28.79 -0.21 28.74 -0.38 28.82 -0.10 09:00 37.42 37.26 -0.43 37.12 -0.82 37.38 -0.10 10:00 43.29 43.06 -0.53 42.86 -0.99 43.23 -0.14 11:00 45.58 45.29 -0.63 45.06 -1.12 45.51 -0.15 12:00 46.46 46.13 -0.71 45.76 -1.51 46.36 -0.21 13:00 48.36 48.26 -0.20 47.80 -1.15 48.32 -0.08 14:00 49.13 49.08 -0.10 48.37 -1.54 49.10 -0.06 15:00 49.45 49.41 -0.08 48.12 -2.68 49.43 -0.04 16:00 49.31 49.27 -0.08 45.82 -7.62 49.30 -0.03 17:00 48.33 48.27 -0.12 40.91 -18.13 48.32 -0.02 18:00 36.91 36.79 -0.32 36.45 -1.25 36.74 -0.47 average 42.25 42.13 -0.29 40.91 -3.17 42.21 -0.12 advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 133 the results of the climate data, temperature, and pet from the simulation in the envi-met version 4.4 program on the hottest day in thailand, april 13 during the period 07:00-18:00, measured at 1.40 meters above the ground, are present in table 2. in table 2, the highest pet value predicted on the site was under alternative 3 as the wind was blocked by a long line of trees. the most effective option that gives the lowest pet value is alternative 2, as the trees do not block the wind and give significant shade that blocks the radiation from the sun. the simulation results during the afternoon peak temperature period 13:00-16:00 are shown in figs. 4-8. fig. 4 air temperature at 1.4 m during 13:00-16:00, april 13, 2020 fig. 5 specific humidity at 1.4 m during 13:00-16:00, april 13, 2020 it can be concluded that the hour with the highest pet value for all alternative cases is between 14:00-15:00. according to srivanit & auttarat [14], during this period, the heat accumulated from radiation throughout the day and the rays from the sun causes a high temperature. in addition, the researchers compared the pet values with the base case and the average values obtained in each alternative, and it was found that the difference in the pet during the day compared to the base case advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 134 for alternative 2 had the greatest difference from the base case at 1.33 o c and the least difference from the base case of 0.05 degrees as shown in table 2, especially during the period 16:00-17:00. the average value of the pet for all periods of the base case and alternatives 1-3 are shown in table 3. fig. 6 wind speed at 1.4 m during 13:00-16:00, april 13, 2020 fig. 7 mean radian temperature at 1.4 m during 13:00-16:00, april 13, 2020 from table 3, it can be concluded that alternative 2 is the best alternative to improve the outdoor thermal comfort for this area, as adding larger trees to the model has a large effect on the pet value. this is consistent with the studies of gatto et al. [24] and cheung and jim [25], which clearly show the benefits of large trees compared to other cases. table 3 average pet values during day time 6.00-18.00 base case alternative 1 alternative 2 alternative 3 average pet 42.25 42.13 40.91 42.21 different pet from base case ( o c) -0.12 -1.33 -0.04 different pet from base case (%) -0.29 -3.17 -0.09 advances in technology innovation, vol. 6, no. 2, 2021, pp. 128-136 135 fig. 8 pet at 1.4 m during 13:00-16:00, april 13, 2020 5. conclusions this study aims to present an appropriate alternative for improving outdoor public spaces in universities. the study area, named lan witsawa ruamjai, was an open public space, located in the faculty of engineering, chiang mai university, chiang mai, thailand. it is a space where students can relax or perform activities in the university area. to measure the effects of the design alternatives, pet was the index used to choose the best outdoor thermal comfort design. from the results of the three alternative cases, it was found that the option that uses large trees in the south-west locations of the area had the highest pet reduction, compared with the other cases. the results of the study further support the idea of the benefits of large trees for human habitation in urban areas. this is consistent with previous research. in addition, to select the most suitable option by using the simulation process in a quantitative technique. this can give a clear understanding to compare and reduce conflicts when choosing a complicated design alternative. it can be used as an example of a design process for new construction and renovation work in other types of construction project to find a balance for sustainable development that can be effective in the future. acknowledgement this research work was partially supported by the cmu junior research fellowship program. conflicts of interest the authors declare no conflict of interest. references [1] “cmu smart city information,” https://enis.cmu.ac.th/audit_analytic/dashboard.php, may 28, 2019. 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[23] f. salata, i. golasi, r. de lieto vollaro, and a. de lieto vollaro, “urban microclimate and outdoor thermal comfort: a proper procedure to fit envi-met simulation outputs to experimental data,” sustainable cities and society, vol. 26, pp. 318-343, october 2016. [24] e. gatto, r. buccolieri, e. aarrevaara, f. ippolito, r. emmanuel, l. perronace, and j. l. santiago, “impact of urban vegetation on outdoor thermal comfort: comparison between a mediterranean city (lecce, italy) and a northern european city (lahti, finland),” forests, vol. 11, no. 2, pp. 1-22, february 2020. [25] p. k. cheung and c. y. jim, “comparing the cooling effects of a tree and a concrete shelter using pet and utci,” building and environment, vol. 130, pp. 49-61, december 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 2__aiti#6666__146-156 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 dockless shared bicycle flow control by using kernel density estimation based clustering shang-yuan chen * , tzu-tien chen school of architecture, feng chia university, taichung, taiwan received 31 october 2020; received in revised form 29 january 2021; accepted 03 february 2021 doi: https://doi.org/10.46604/aiti.2021.6666 abstract since dockless sharing bicycles have become an indispensable means of everyday life for urban residents, how to effectively control the supply and demand balance of bikes has become an important issue. this study aims to apply kernel density estimation based (kde-based) clustering analysis and a threshold-based reverse flow incentive mechanism to encourage the users of bicycles to adjust the supply and demand actively. and it takes shanghai jing’an temple and its surroundings as the research area. its practical steps include: (1) compilation and processing of the needed data, (2) application of kde-based clustering, partitioning, and grading, and (3) incentives calculation based on dockless shared bicycle flow control system. the study finds that the generalization function of kde-based clustering can be used to estimate the density value at any point in the study area to support the calculation of the incentive mechanism for bicycle reverse flow. keywords: classification, clustering, unsupervised neural networks learning, r language, choropleth map 1. introduction the promotion of shared bicycles seeks to resolve the problem of short-distance urban transportation, and shared bicycles are an important means of contemporary green transportation [1]. the docking shared bicycles found throughout taiwan are chiefly aimed at tourists. however, unlike dockless shared bicycles, docking shared bicycles do not allow users to obtain and return the bikes at any location, thus docking shared bicycles cannot easily become important means of everyday transportation for urban residents. in addition, although dockless v-bikes made a short-lived appearance in taiwan during 2017, little data concerning v-bikes is available. as a consequence, this study relies on observations and analysis of dockless shared bicycles in shanghai, china to gain a better understanding of dockless shared bicycles and methods of improving their effectiveness, as well as specific methods of making them more acceptable to city residents and a more important means of transportation. after the shared bicycles are introduced on a large scale in a city, the supply and demand problems of bicycles involving different areas often emerge. for instance, at certain important transportation nodes, the use of bicycles frequently increases during peak times, and may cause bicycle shortages. therefore, it is necessary to dispatch bicycles in order to resolve the supply and demand problems. however, the current dispatching aprroach is often too inefficient to be of much use. furthermore, it also imposes logistics costs on bicycle companies because manpower and trucks are required to move bicycles from oversupplied areas to shortage areas. besides, since bicycles cannot be used while they are being transported, the capacity of urban transportation is reduced. as a consequence, how to dispatch shared bicycles in real-time, or in advance, is an especially important issue. * corresponding author. e-mail address: shangyuanc@gmail.com tel.: +886-4-24517250 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 in this study, we apply cluster analysis with unsupervised learning to shared bicycle flow control and dispatching, and employ artificial intelligence to extract the real and full-scale transportation rules from open data. this study’s analysis of the times and locations at which the oversupply or shortage of shared bicycles may occur in shanghai will help bicycle companies to perform dispatching ahead of time. furthermore, clustering results can be used in conjunction with incentive mechanisms employing threshold values to encourage bicycle users to actively perform bicycle dispersal and dispatching, which will boost the carrying capacity of urban transportation systems, and reduce the risk and cost of ineffective dispatching. 2. literature review the scope of this study includes shared bicycles and cluster analysis; the following is a review of the literature: 2.1. shared bicycles shared bicycle systems include docking and dockless models. the world’s first intelligent public bicycle system was the vélo’v docking public bicycle system, which was established in lyon, france, in 2005 [2]. nevertheless, docking shared bicycles have never caught on in china. since the residents of china consider bicycles to be everyday means of transportation, many dockless shared bikes began appearing in china during the second half of 2016. they are not dependent on the fixed and managed parking areas, and can be left in any vacant space along roads. consumers only need to use wechat pay, alipay, or some other apps to pay a specified deposit before using the bikes. the following explains the clustering principles of the docking and dockless shared bicycles, and the differences between the two. (1) docking shared bicycles and their clustering principles: it is much easier and more clear-cut to calculate the number of docking bikes that are taken or returned than dockless bikes. to predict the number of bikes at each group of docks in a city as a whole and after clustering, it is first necessary to perform the grouping of the docking points. in the case of docking shared bikes, because the locations at which bicycles can be obtained or returned are limited to places where docks are present, it is only necessary to perform clustering of the fixed docks, instead of the bikes themselves. if within a specific geographical scope, we divide n docks into m groups (n>m), calculate the probability of bikes moving among the m groups, and analyze their historical data (including time, climate, notable events, and other influencing factors), we can then predict future movement trends [3]. (2) dockless shared bikes and their clustering principles: unlike the case of shared bicycles with fixed docks, the clustering of dockless shared bicycles changes with time, and it is challenging to calculate check-out and check-in probabilities. one feasible approach that can be employed to cluster dockless shared bicycles is to perform clustering of the coordinates of the bicycles’ check-out and check-in locations. however, it is still hard to perform direct clustering due to the fact that check-out points and check-in points have an irregular and macro distribution. moreover, the clustering of dockless shared bicycles must also reflect the precondition that users within each cluster can easily find out usable shared bicycles within a comfortable walking distance. besides, the most suitable walking distance is affected by climatic conditions, vertical distance, and a city’s state of economic development [4]. in the case of shanghai community residents, taking a walking distance of 787m as a dividing point, residents would choose to walk when the distance is shorter than 787m, but would very seldom choose to walk when the distance is longer than 787m [5]. this study, therefore, adopts the round figure of 787m as the scope of the most suitable walking distance; 787m is established as the baseline scope of clusters in the remainder of this paper. since 787m is roughly equivalent to the distance that can be walked in 10 minutes, it is a representative figure of daily walking distance. as shown in fig. 1, in a zone, the distance for users to find a bicycle should not exceed the “optimum walking distance”. the minimum diagonal of the equilateral rectangle is 787m, which corresponds approximately to the cell grid with a side length of 550m, reflecting the unit distance of the longitude and latitude grid in the shanghai area. 147 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 fig. 1 the hypothesis for the cell grid 2.2. cluster analysis as described above, the methods and algorithms used to cluster shared bikes affect the shared bicycle flow prediction and dispatching ability. in machine learning, the use of clustering methods and the derivation of clustering algorithms are referred to as “cluster analysis”. cluster analysis is defined as the division of different objects into homogeneous subgroups [6]. data clustering is ordinarily classified as unsupervised learning. while clustering and classification are easily confused, particularly in data mining, the difference between clustering and classification lies in the fact that clustering is a process of grouping to form samples, where the examples are adjacent in space. in contrast, classification involves attaching labels to samples, where the labels are derived from supervised external standards. in other words, clustering constitutes an unsupervised grouping process, where groups are formed after data has been input naturally [7], but the classification is supervised and involves other external information. unsupervised neural networks can uncover essential characteristics, or that may be overlooked, from data on their own, without any preconceived expectation of the output values, and can, therefore, perform clustering of data [8-9]. different clustering methods of unsupervised learning use mathematical formulas as their algorithms. although cluster analysis has been used to develop various types of algorithms [10-16], those algorithms lack a uniform classification. in terms of classification, this study synthesizes the views of gan et al. (2007) [11] and saxena et al. (2017) [14]. gan created the parsing tree based on the characteristics of clustering algorithms. from the top, this tree lists hard clustering and fuzzy clustering. hard clustering includes partitional and hierarchical approaches. hierarchical approaches may consist of either divisive or agglomerative methods [11]. also, saxena et al. suggested the following three additional categories for applying clustering techniques: distance-based methods, model-based methods, and density-based methods (fig. 2) [14]. according to the nature of the dockless shared bicycle problem, they are often distributed in arbitrary shape in a city. therefore, this study proposes to employ density-based clustering algorithms. most partitioning methods are based on the distance between objects. such methods can find only spherical-shaped clusters and encounter difficulty in discovering clusters of arbitrary shapes. however, the density-based method can be used to filter out the noise or outliers and identify the clusters of arbitrary shapes. there are two types of density-based approaches. one is density function, which is a total mathematical function, e.g. kernel density estimation based (kde-based) clustering, and the other is density-based connectivity, e.g. density-based spatial clustering of applications with noise (dbscan) [17]. 148 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 fig. 2 the clustering method parsing tree comparing the kde-based clustering with dbscan methods, the former offers the advantage of the setting of generalization function, which is convenient to partition and grading and is capable of being the basis for incentive mechanism. however, the latter can only be used to mark those clusters that meet a pre-set density requirement by the control radius ε and minpts quantity. kde-based clustering has long been used for detecting traffic accident hot spots and has proven to be useful in traffic accident analysis [18]. in particular, the ordering capabilities of kde-based clustering help compare the spatial structure to determine or assign the importance of mitigation measures [19-20]. as a consequence, the following research will discuss the introduction of kde-based clustering applied to the dockless shared bicycle flow control system. 3. theory and method as mentioned above, this study proposes a “dockless shared bicycle flow control system” that is an incentive mechanism to encourage the reverse flow of bikes in which kde-based clustering is introduced to partition and grading as the basis of threshold control. the activity of the dynamic bicycle control system is not evenly distributed but varied in intensity and scope following people’s everyday activities. because the system’s most important function is to maintain a balance between supply and demand in clusters with different densities, the incentive mechanism is used to reverse supply and demand imbalances during earlier periods. this solution brings up the question of how to perform partitioning and grading of bicycle check-out points and check-in points. when check-outs and check-ins span different clusters, how should incentives be provided to reverse bicycle movement trends? the following explains kde-based clustering partition and grading and dockless shared bicycle flow control system. 3.1. kde-based clustering partition and grading kde-based clustering analysis over a density surface is based on the technologies of spatial smoothing and spatial interpolation [21-22]. the kernel function analyzes and converts the point distribution of the plane in the area, and infers the spatial density distribution in the area. the spatial density is the property that describes the spatial distribution in an intensive or sparse pattern in quantity. therefore, the point data is mapped from the inseparable 2-dimensional space to the separable 3-dimensional space. since a density value is calculated as an attribute of each grid cell in the sub-region, it is, therefore, possible to represent the spatial distribution employing homogenous and easily comparable areas with choropleth map visualization. this estimated density is used to cover the top of the research domain with a grid cell, and the estimation of density is performed based on each grid cell’s center point (fig. 3). based on defined kernel function and bandwidth, kde provides an estimate of the intensity in each position of the grid cell by moving three-dimensional functions. the defined kernel function weights events within its sphere of influence according to their distance from the point at which the intensity is estimated (fig. 4) [23]. in other words, the nature of the optimization and generalization function is a significant characteristic of this density estimation method, which can perform fitting and generalization of large bodies of complex data following the approximation function and bandwidth, and can possess estimation ability. 149 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 commonly used density functions include uniform, epanechnikov curve, quartic curve, and gaussian curve, etc. (fig. 5). among them, quartic and gaussian are more suitable radial basis function kernels but the quadratic kernel is less computationally intensive than the gaussian kernel and can be used as an alternative when using the gaussian becomes too time-consuming and tedious [20]. after optimization, the system can estimate the density value of any position in the study area. since a density value is calculated as an attribute of each quadrat sub-region, it is, therefore, possible to represent the spatial distribution employing homogenous and easily comparable areas with choropleth map visualization [20]. the general form of a kernel density estimator is expressed as: 21 ( , )1 ( ) n i i d s c f s k h h = =      ∑ (1) where f(s) is the density measured at location s, h is the search radius (bandwidth) of the kde [only events within h are used to estimate f(s)], ci is the observed event point, k[ ] is the weight of event ci at distance d(s, ci) to location s. the kde usually models the so-called kernel function, k, as a function of the ratio between d(s, ci) and h so that the “distance decay effect” can be taken into account in density estimation. the evaluation of kde requires two parameters: the bandwidth h and the kernel function k, which determine the weighting of the points. in this study, we use the quartic kernel function, which is one of the most commonly used features: [ ]2 2 ( , )( , ) 3 1 4 d s cd s c k h h = −          (2) fig. 3 performing density estimation based on the center point of each grid cell [24] fig. 4 weighting (ωi) based on a specific kernel function and bandwidth [25] 150 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 fig. 5 kernel functions in a standard coordinate system [26] 3.2. dockless shared bicycle flow control system it is crucial that shared bicycle companies possess real-time or ahead of time dispatching and management ability. this study proposes a dockless shared bicycle flow control system model and an incentive mechanism for the reverse flow of bikes based on threshold values. the clustering results can be used in conjunction with incentive mechanisms employing threshold values to encourage bicycle users to perform bicycle dispersal and dispatching actively. it boosts the carrying capacity of urban transportation systems, and reduces the risk and cost of ineffective dispatching. as shown in fig. 6, this system considers the number of check-outs within a unit time and a unit area to be the bicycle demand of that area, and the number of check-ins within a unit time and a unit area to be the bicycle supply of that area. it is necessary to use incentives or compulsory rules to control the rate of check-outs and check-ins to ensure that each region has a proper amount of bicycle stock. when the stock is excessively high—higher than the upper threshold—the system triggers the check-out incentive mechanism. when the stock is too low—below the lower limit—the system activates the check-in incentive mechanism. these incentive mechanisms controlling reverse flow based on threshold values can be expected to ensure that the stock can be in a better state than when not using the incentive mechanisms. apart from this, when the system detects that the bicycle density reaches the level of oversupply or shortage, the shared bicycle company have to dispatch trucks to perform transport and force the system back within the normal range [27]. fig. 6 dockless shared bicycle control system model 151 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 for every partition, the most important aspect is maintaining a balance between supply and demand within each cluster in this dynamic system, and incentives must seek to reverse imbalances in supply and demand during the previous period. in this study, we consequently design a check-out incentive formula (referring to eq. (3)) and a check-in incentive formula (referring to eq. (4)), in which x is the check-out rate, y is the check-in rate, �� is the time, and n is an integer. if ����� ≤ ���� at the time ��, then the check-out incentive amount is expressed as: 1 1 2 i n nt ty x − − − (3) where � is a whole number and is the check-out sequence at a time ��. by eq. (3), at the time ��, the incentive for check-out of the first bicycle is maximum, and the impetus for the check-out of each subsequent bike decreases progressively with the increasing root of 1/2 with the increase in the number of bikes checked out: 1/2 1 , 1/2 2 , 1/2 3 , and so on. the incentive for the final bicycle checked-out approaches 0 without limit, but never reaches 0. if ����� ≤ ���� at the time � , then the check-in incentive amount is expressed as: 1 1 2 j m mt tx y − − − (4) where j is a whole number and is the check-in sequence at a time � . by eq. (4), at time � , the incentive for check-in of the first bicycle is maximum, and the impetus for the check-in of each subsequent bike decreases progressively with the increasing root of 1/2: 1/2 1 , 1/2 2 , 1/2 3 , and so on. the incentive for the final bicycle checked-in approaches 0 without limit, but never reaches 0. as described above, if a bicycle is checked out from area p at time �� and checked in area q at � , the incentive amount is the sum of the check-in incentive in area p during at time tout and the check-out incentive in area q during at time ���. the total incentive amount can be represented as: 1 1 1 1 2 2 i j n n m mt t t ty x x y sum − − − − − − = + (5) 4. realization and verification this section realizes and tests a dockless shared bicycle flow control system following the preceding theory and method. we employ 101,843 data items issued in august 2016 for the shanghai open data innovative application competition to perform modeling and verification [28]. these data items include order numbers, bicycle serial numbers, user serial numbers, check-out times, check-out longitudes, check-out latitudes, check-out times, check-in longitudes, check-in latitudes, and routes. we use this data to find the optimal clustering methods for shared bikes in shanghai by examining relatively small areas (the area around shanghai’s jing’an temple) and relatively large areas (the part of shanghai within the fourth ring roads—121.75°e-121.125°e, 30.95°n-31.45°n) and also establish the models corresponding to the state of clustering. this control system applies the kde-based clustering analysis to propose an incentive mechanism for the reverse flow of bikes based on partition and threshold to encouraging bicycle users to evacuate and dispatch actively. we employ the following three steps in this process: (1) compilation and processing of the needed data, (2) application of kde-based clustering, partitioning, and grading, and (3) incentives calculation based on dockless shared bicycle flow control system. in the development of the application, the rstudio software is used as an integrated development environment for writing r language programs [29]. 152 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 4.1. stage 1: compilation and processing of data as of august 2016, 223,000 mobike bikes are in use in shanghai [28]. since each mobike bike in china is ridden by 5.4 persons per day [30], we can roughly estimate that there are approximately 36,000,000 use records each month for mobike bikes in shanghai during august 2016. based on the shanghai area’s latitude and longitude, as well as a maximum suitable walking distance of 787m, which corresponds approximately to the cell grid with a side length of 550m, we can estimate that there is an average of approximately 2,857 bikes in each 550m×550m grid square at that latitude and longitude (discarded, damaged, and under-repair bikes were not subtracted). assuming that 50% of bikes in the urban area of shanghai can still be found, we can estimate that there are approximately 1,428 bikes in each grid square. the following modeling, therefore, employs a common stock of 1,428 bikes in each 550m×550m grid square as the reference bicycle stock value for shanghai during august 2016. 550m×550m squares are designated as grid cells for kde-based clustering calculations. 4.2. stage 2: application of kde-based clustering, partitioning, and grading as described above, the activity of the dynamic bicycle control system is not evenly distributed but varied in intensity and scope following people’s everyday activities. because the system’s most important function is to maintain a balance between supply and demand in clusters with different densities, the incentive mechanism is used to reverse supply and demand imbalances during earlier periods. the following is an explanation of how this is done: following the analysis in section 3.2, the kernel density spatial clustering method is used to perform partitioning and grading of check-out and check-in density in the study area around shanghai’s jing’an temple on 8/1/2016. in this study, we set 787m as bandwidth and choose the quartic kernel function to execute kde-based clustering. (1) check-out density partitioning and grading: as shown in table 1, according to the results of calculations, the level 1 area around jing’an temple has a check-out density of approximately 3,600, while the adjacent peripheral area has a check-in density of roughly 900. this number shows that the density difference between the central region and the adjacent outer space is around 3,600�900=2,700. following the depth of the purple color in fig. 7, the system recommends that there be 12 clusters; when 2,700 points are divided among levels 1 to 12, we obtain the clustering thresholds for each level shown in table 1. table 1 check-out clustering thresholds for each level areas with different check-out clustering levels level 1 level 2 level 3 level 4 level 5 level 6 level 7 level 8 level 9 level 10 level 11 level 12 upper threshold ≥3600 3375 3150 2925 2700 2475 2250 2025 1800 1575 1350 1125 lower threshold 3375 3150 2925 2700 2475 2250 2025 1800 1575 1350 1125 ≤900 fig. 7 partitioning of check-out density in the area around shanghai’s jing’an temple on 8/1/2016 fig. 8 partitioning of check-in density in the area around shanghai’s jing’an temple on 8/1/2016 153 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 (2) check-in density partitioning and grading: as shown in table 2, according to the results of calculations, the level 1 area around jing’an temple has a check-in density of approximately 3,100. in contrast, the adjacent peripheral area has a check-in density of roughly 800. this number shows that the density difference between the central region and the adjacent outer space is around 3,100�800=2,300. following the depth of the orange color in fig. 8, the system recommends that there be 11 clusters; when 2,300 points are divided among levels 1 to 11, we obtain the clustering thresholds for each level shown in table 2. table 2 check-in clustering thresholds for each level areas with different check-in clustering levels level 1 level 2 level 3 level 4 level 5 level 6 level 7 level 8 level 9 level 10 level 11 upper threshold ≥3100 2891 2681 2472 2263 2055 1845 1636 1427 1218 1009 lower threshold 2891 2681 2472 2263 2055 1845 1636 1427 1218 1009 ≤800 4.3. stage 3: incentives calculation based on dockless shared bicycle flow control system as shown in figs. 7-8, during the period from 12:00 to 18:00 on 8/1/2016 (i.e., the period following 06:00 to 12:00 on 8/1/2016), the first bicycle is checked-out from the check-out point and returned at the check-in point half an hour later, which is during the same period. the calculations of the check-outs and check-ins are presented as follows. (1) as for the check-outs, the estimated check-out rate x at the check-out point is 1600, and this area is in a level 7 check-in cluster (threshold: 1,845-1,636); since 1600 < 1636 (implying that the check-out rate x is slower than the minimum estimated check-in rate), consequently when x��� ≤ x���� ≤ x���, and x���� < y���. the check-out incentive system should be activated. according to eq. (3), y���� is entered as y���, 1 1636 1600 18 2 − = (6) (2) as for the check-ins, the estimated check-in density y of the check-in point is 2,800; and this area is in a level 2 check-out cluster (threshold: 3,375~3,150); since 2750 < 3150 (implying that the check-in rate y is slower than the minimum estimated check-out rate), when y��� ≤ y�&�� ≤ y���, x��� ≥ y�&�� . the check-in incentive system should be activated. according to eq. (4), when x�&�� is entered as x���, 1 3150 2750 200 2 − = (7) (3) the total incentive is the sum of the two amounts. according to eq. (5), a total incentive amount of 218 units is obtained. 18 200 218sum = + = (8) the preceding is a discussion of partitioning and grading and the use of an incentive mechanism relying on threshold values to reverse the flow of bikes. the data for the period from 12:00 to 18:00 on 8/1/2016 obtained from on-site observations is very consistent with the results of our model. because 8/1/2016, monday, is the first working day of the week, it is easy to find shared bikes in the outer marginal area of jing’an temple. but in contrast, the jing’an temple center is located in a dense commercial and office area, so it is often difficult to find bikes that can be borrowed. 154 advances in technology innovation, vol. 6, no. 3, 2021, pp. 146-156 5. conclusions with kde-based clustering, this study can use the choropleth map visualization to represent spatial distribution to achieve partitioning and grading. it can support the calculation of the threshold-based incentive mechanism for bicycle reverse flow. the analysis of the implementation results is as follows: (1) if an area is in a peak usage period, the flow rate is fast (i.e., the pick-up rate is fast, and the return speed is also fast). alternatively vice versa, if the relative time is in the off-peak period. when the absolute value of the difference between the check-out rate and the check-in rate is in a range, the number of bikes in the area is considered to be in a state in which regular operation can be maintained. (2) however, if a domain is in a fast check-out speed for a long time, and the check-in speed is very slow or almost stationary, it means that the number of bikes in the area has been slower than the shortage threshold. conversely, if the check-in rate is rapid for a prolonged period within a specific area, but the check-out rate is almost 0, this indicates that the number of bikes in that area quickly rises above the oversupply threshold. when states of oversupply or shortage occur, trucks should be dispatched to move and redistribute the bikes in order to ensure that the system returns to a healthy state. kde-based clustering has its constraints to establish dispersal and dispatching strategies. as analyzed above, although the incentive mechanism can alleviate the situation of imbalance between supply and demand, the oversupply or shortage of bicycles still cannot be completely ruled out. the dbscan clustering method, is better than kde-based clustering obviously in this situation. therefore, how to use the dbscan cluster analysis to find out the oversupply or shortage of distribution of bikes in the study area to establish dispersal and dispatching strategies will be the core issue of the next research. acknowledgments this work was supported by project: cluster analysis of unsupervised learning applied to dockless shared bicycle traffic prediction and scheduling, most 108-2221-e-035-005. conflicts of interest the authors declare no conflict of interest. references [1] s. k. chang, h. w. chang, and y. w. chen, green transportation, slow, friendly, and sustainable: people-oriented transportation environment makes the city smoother and life better, taipei: neonaturalism, 2013. 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(in chinese) copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 156  advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 new ventures, internationalization, and asymmetric grin curve: analysis of taiwan’s big data jwu-rong lin 1 , chen-jui huang 2,* , ching-yu chen 1 , huey-ling shiau 2 , yan-chen yeh 1 1 department of international business, tunghai university, taichung, taiwan, roc 2 department of finance, tunghai university, taichung, taiwan, roc received 02 march 2018; received in revised form 18 july 2018; accepted 04 september 2018 abstract under globalization, small and medium enterprises (smes) that predominate taiwan’s economy have been primarily original equipment manufacturers (oems) continuing to adjust operating strategies in order to extend supply chains and enhance competitiveness. this paper adopts the big data composed of 104,377 taiwanese manufacturers from the 2011 industry, commerce, and service census to assess impact of the business life cycle, brand revenue, r&d spending, and internationalization on value creation. major findings are as follows. first, the link of the firm’s operating years with value creation is characterized by a quadratic u-shaped curve where the minimum point corresponds to 15 years of operation, suggesting a cost of lower value added for new ventures at the early stage of development. second, a reversed u-shaped curve of value creation is found as regards brand revenue and r&d spending, with the greater impact of the latter. third, the impact of overseas investment and export expansion is also captured by a reversed u-shaped curve, with greater impact for the former. fourth, an asymmetric grin curve rather than a smile curve is found in taiwan’s manufacturers, whose value creation can be strengthened by strategies that focus on the learning curve, internationalization, internet, operating scale, and capital intensity. keywords: new venture, internationalization, grin curve, value creation 1. introduction the emergence of the regional comprehensive economic partnership (rcep), which enlarges the trade link of the ten asean members and six asian countries, marks a new challenge as regards the cost advantage that most original equipment manufacturers (oems) in taiwan have benefited over past decades. these firms are now forced to develop strategies that transform the current cost-based industry into the one with high value added through new ventures, brand benefit, r&d spending, and internationalization. however, the 2011 industry, commerce, and service census conducted by taiwan’s directorate-general of budget, accounting, and statistics shows that the business operating years ranges from 1 to 100 and averages at 18 among the 104,377 firms surveyed. this seems to imply significant discrepancy in terms of the business life cycle. in addition, the number of firms that have been engaged in brand, r&d, overseas investment, and export activities are only 12,440, 10,062, 14,326, and 17,206, respectively accounting for 11.92%, 9.64%, 13.73%, and 16.49% of the total sample and leaving the ratio of the value added to total revenue at 36% only. this paper intends to deepen the issue on insufficient value creation observed in most small and medium enterprises (smes) that dominate taiwan’s manufacturing sectors and discuss relevant strategies for transformation in the business model. * corresponding author. e-mail address: cjhuang@thu.edu.tw. advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 45 the remainder of this paper is structured as follows. section 2 succinctly reviews theoretic foundations and relevant empirical evidence. section 3 proposes the empirical model and hypotheses to be tested. section 4 analyzes primary regression results and checks robustness of the empirical model. section 5 concludes with discussion on research limitations and suggestion for future studies. 2. theoretic foundations and literature review the smile curve characterizes the relation between value creation and supply chains. the value added is expressed on the vertical axis, whereas the supply chains from the upstream to the downstream are expressed from the left to the right on the horizontal axis. over the supply chains, upstream, midstream, and downstream firms respectively play the role of original design manufacturers (odms), original equipment manufacturers (oems), and own branding manufacturers (obms). in less developing countries (ldcs), the smile curve appears reversed, called the forced smile curve. in between, the grin curve raises the two ends of the smile curve and appears flatter to reflect the evolution in industry competition. the typical smile curve, forced smile curve, and grin curve are illustrated in fig. 1. fig. 1 smile curve, forced smile curve, and grin curve new ventures have grown rapidly over the past decades. lussier [1] defines the new ventures as businesses established within 10 years. in taiwan, the start-up and incubation center of the small and medium enterprise administration of the ministry of economic affairs adopts instead a definition of 5 years, also applied to associated start-up loans open to the youth. but its business start-up award targets businesses of an age of not more than 3 years. across relevant studies, businesses established within 3 to 14 years exhibit essential characteristics of new ventures. as this research employs data from the industry, commerce, and service census conducted every 5 years by taiwan’s directorate-general of budget, accounting, and statistics, subsequent analysis will define new ventures by an age of not more than five years. businesses that have continuously operated over more than 5 years are regarded as survivors. marco et al. [2] examine a sample of italian companies between 1982 and 1992. firm characteristics before and after the public initial offerings (ipo) are compared in order to find determinants for listing on exchanges. the authors adopt the competitive theory to distinguish cost-side and benefit-side determinants and classify new ventures and survivors by firm age. the empirical evidence indicates lower capital demand reflected by a lower debt ratio for new ventures as these businesses have shorter operations and/or funds provided by establishing shareholders are able to meet the demand. erel et al. [3] turn to a larger sample of european companies involved with mergers and acquisitions from 2001 to 2008 and investigate the sensitivity of cash holdings and investment to cash flows. they find that it is the survivor rather than the new venture which significantly increase cash holdings one year after the ipo. in addition, positive sensitivity of investment to cash flows is found among new ventures, which implies that investment by financially constrained firms mainly relies on own funds as post-ipo firm characteristics cannot not be changed immediately. odm oem obm smile curve value added grin curve forced smile curve advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 46 relevant studies such as maine et al. [4] discuss value creation by startupand science-based businesses such as biotechnology firms and deepen the specifics inherent in value creation by companies producing high-end materials. the authors apply hierarchical clustering to differentiate various types of material technology and observe differences in value creation driven by decision incorporating uncertainty, commercialization of products, target-market-tailored r&d, and value chain integration across the sample firms. chemmanur et al. [5] advance by connecting the venture capital firm with corporate innovation. the authors substantiate a higher degree of innovation in venture capital firms established and supported by parent firms than in those which operate independently, suggesting the key role played by industrial knowledge and greater room for failure in value creation achieved by external venture capital. yang et al. [6] continue the studies in corporate growth and find a u-shaped relation between diversification by venture capital businesses and value creation of new ventures. quentier [7] deepens with analysis of self-employment by the unemployed through creation of new ventures and find that government subsidies in the form of loans better increase quality and selection of new ventures than direct subsidies. the loans also serve to solve financial constraint faced by these new ventures. fig. 2 synthesizes the theoretical foundations inherent in the technology gap theory suggested by posner [8] with illustration of strategies by the oem, odm, and obm. the firm is not established over the period of t0~t1 for lack of competitiveness and starts to imitate other firms by operation in the form of oem regarding conditions such as the economies of scale, production standardization, and initial capacity over the period of t1~t2. then the firm gradually raises operation performance (op) along the path of t1a under the imitation lag. however, the firm which keeps the oem strategy may face stagnant or decreasing op and enjoy the marginal profit only under the agency problem caused by high concentration of buyers or an increase in competitors as suggested by the transaction cost theory. to avoid such a strategic problem for oem, the firm should adopt the odm strategy by an increase in spending on research and development to gain patents at the initial expense of the design lag and failure in the early state of innovation, making op fall along the path of ab over the period of t2~t3. beyond t3, the firm’s op gradually rises along the path of bc with advantages from technological improvement and creation of new product. if other oems also experience imitation and design lags to catch the firm’s odm strategy, the firm’s op may become stagnant or declining beyond t4 under the love for varieties by consumers. as suggested in the product differentiation theory by krugman [9] and attribute differential theory by lancaster [10], the odm’s gross margin will decrease with mass customization. to increase op, the obm strategy should be adopted, but the firm has to experience the demand lag and substantial branding investment over the period t4~t5 where op falls along the path of cd. only as the capability for product differentiation, operational digitalization, investment in intangible assets, and internationalization reach a stable level, the firm’s op grows along the path of de. fig. 2 strategies by oem, odm, and obm fig. 3 business life cycle, internationalization, and value creation in literature, dunning [11], wagner [12], bhide [13], zahra et al. [14], kuo and li [15], head and ries [16], and hmieleski and baron [17] discuss from various dimensions the strategies for business evolution and expansion in the context of international competition. kumar and siddharthan [18] place focus on the indian enterprises, whereas chen [19], lundquist [20], lin [21], and lin et al. [22] examine businesses in taiwan. this paper attempts to evaluate whether the firm’s operating advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 47 years (business life cycle) and internationalization (overseas investment and export) shift the smile curve up to strengthen value creation, illustrated by fig. 3. subsequent analysis is to construct a regression model of value creation and assess the impact of the operating years, brand, r&d, internationalization, and other control variables of management on the value added for taiwan’s manufacturers in addition to proposing appropriate strategies. 3. empirical model and hypotheses 3.1. data the empirical analysis adopts the 2011 industry, commerce, and service census conducted by taiwan’s directorate-general of budget, accounting, and statistics. the original sample covers 167,840 firms. with the deletion of firms whose variable values are erroneous or omitted, the final sample contains 104,377 firms regrouped into ten classes. table 1 recapitulates variable definitions. table 1 variable definitions variable definition remark panel a: value creation lva value added in logarithm panel b: business life cycle age operating years age 2 squared age panel c: asymmetric grin curve br brand revenue to total revenue in percentage rd r&d spending to total spending in percentage fi overseas investment to net fixed assets in percentage ex export revenue to total revenue in percentage panel d: operation digitalization ec1 information disclosure on internet dummy ec21 purchases on internet dummy ec22 internet purchases to total spending in percentage ec31 sales on internet dummy ec32 internet sales to total revenue in percentage panel e: control variable opr manufacturing as main business dummy lsize net assets in logarithm klr net fixed assets to number of employees capital-labor ratio panel f: industry class inda food and drink dummy indb textile, clothing, and leather dummy indc paper and printing dummy indd oil, coal, and chemistry dummy inde rubber and plastics dummy indf metal dummy indg electronics and computer dummy indh machinery dummy indi car and other vehicle dummy indj furniture dummy 3.2. model and hypotheses to measure the impact of innovation, brand revenue, r&d spending, and internationalization on value creation for taiwan’s manufacturers, the model of eq. (1) is constructed by the following regression equation. advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 48 lva = a0 + a1age + a2age 2 + a3br + a4br 2 + a5rd + a6rd 2 + a7fi + a8fi 2 + a9ex + a10ex 2 + a11ec1 + a12ec21+ a13ec22+ a14ec31+ a15ec32 + a16opr + a17lsize + a18klr + a19klr 2 + a20indb + a21indc + a22indd + a23inde + a24indf + a25indg+ a26indh + a27indi + a28indj + e (1) lva is taken in logarithm and measure value creation. the parameters a1 and a2 serve to assess the role played by the business life cycle in the firm’s value added, whereas the parameters from a3 to a6 respectively focus on the impact of obms (a3 and a4) and odms (a5 and a6). the parameters from a7 to a10 serve to assess the role played by internationalization in terms of overseas investment (a7 and a8) and export (a9 and a10). the parameters from a11 to a15 serve to evaluate the contribution of operation digitalization through internet to value creation. finally, the influence of the control variables and industry class dummies are captured by the parameters from a16 and a28. the last term e represents the error term. the model of eq. (1) is preliminarily estimated by the ordinary least squares method. the white test suggests significant heteroscedasticity in residuals, with a chi-squared value of 58,305. hence, subsequent analysis substitutes the robust standard errors for standard errors estimated by the ordinary least squares method. besides, results from parameter estimation of the model of eq. (1) are used as foundations for testing the seven core hypotheses summarized from eqs. on (2) to (8). h1: value creation is a u-shaped quadratic function of business life cycle, implying increasing marginal benefit, or a1 < 0 and a2 > 0. (2) h2: value creation is a reversed u-shaped quadratic function of brand revenue, implying decreasing marginal benefit, or a3 > 0 and a4 < 0. (3) h3: value creation is a reversed u-shaped quadratic function of r&d spending, implying decreasing marginal benefit, or a5 > 0 and a6 < 0. (4) h4: the impact of brand revenue and r&d spending on value creation is asymmetric, or a3 + 2a4br  a5 + 2a6rd. (5) h5: value creation is a reversed u-shaped quadratic function of overseas investment, implying decreasing marginal benefit, or a7 > 0 and a8 < 0. (6) h6: value creation is a reversed u-shaped quadratic function of export, implying decreasing marginal benefit, or a9 < 0 and a10 < 0. (7) h7: the impact of overseas investment and export on value creation is asymmetric, or a7 + 2a8fi  a9 + 2a10ex. (8) 4. empirical results 4.1. descriptive statistics table 2 summarizes descriptive statistics for the value creation, business life cycle, brand, r&d, internationalization, operation digitalization, and other control variables of management across 104,377 manufacturers in taiwan in 2011. for value creation (va), the mean for the original values is at $39,043 thousand new taiwan dollars across surveyed manufactures in taiwan. the gap between the maximum value and the minimum value appears substantial, confirmed by a high level of its standard deviation. a similar pattern is observed in the business life cycle (age) ranging from new ventures (1 year) to sustainable operating firms (100 years). the average of age is close to 18 years. advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 49 the ratios of brand revenue to total revenue (br), r&d spending to total spending (rd), overseas investment to net fixed asset (fi), and export to total revenue (ex) are respectively 8.8812%, 0.3251%, 0.0511%, and 8.3778%, showing strong bias to oems and insufficient internationalization for most manufacturers in taiwan. as regards operation digitalization, the ratios of internet purchases to total spending (ec22) and internet sales to total revenue (ec32) are 1.3210% and 1.3337% only, suggesting that purchases and sales through internet remain at its early stage of development in taiwan’s manufacturing industry. in terms of control variables, the dispersion for the value of net assets (lsize) that reflects the firm’s operating scale remains significant in logarithm. the capital-to-labor ratio (klr) measured by net fixed assets over the number of employees is averaged at 1.5335. table 2 descriptive statistics variable mean maximum minimum std. dev. panel a: value creation lva 8.5416 19.4878 5.0626 1.3276 panel b: business life cycle age 17.5632 100 1 0.2784 panel c: asymmetric grin curve br 8.8812 100 0 25.6504 rd 0.3251 74.5755 0 2253.051 fi 0.0511 224.4135 0 2.0569 ex 8.3778 100 0 80.3330 panel d: operation digitalization ec1 0.6122 1 0 1.3542 ec21 0.1136 1 0 227.8531 ec22 1.3209 99.5421 0 22.1068 ec31 0.0847 1 0 1774.022 ec32 1.3337 99.9995 0 0.4872 panel e: control variable opr 0.8308 1 0 0.3173 size 248,994 1.53e+09 169 6.4962 klr 1.5335 63.8248 0.0016 0.3749 panel f: industry class inda 0.0382 1 0 0.1917 indb 0.0681 1 0 0.2519 indc 0.0964 1 0 0.2951 indd 0.0338 1 0 0.1806 inde 0.0882 1 0 0.2836 indf 0.2933 1 0 0.4553 indg 0.0755 1 0 0.2642 indh 0.2135 1 0 0.4098 indi 0.0464 1 0 0.2103 indj 0.0466 1 0 0.2107 4.2. estimation results table 3 below summarizes major results from estimation of equation (1) with adjustment in heteroscedasticity. with additional regression for independent variables, the variance inflation factor (vif) appears low except for age, age2, br, br2, ex, and ex2 whose vif exceeds 10. therefore, there is, overall, no serious problem of collinearity. the adjusted r2 is around 0.6533, substantiating sufficient explanatory power of the model specified. the chi-squared value for the white test is at 58,305, implying significant heteroscedasticity in residuals. therefore, the t-values reported in table 3 are adjusted by robust standard errors. advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 50 table 3 estimation results variable lva t-value vif constant 3.2936*** 104.3353 na age -0.0029*** -3.4095 11.8816 age 2 1.01e-0.4*** 4.7657 11.7598 br 0.0041*** 6.0753 40.9094 br 2 -3.08e-05*** -4.0718 39.8211 rd 0.0805*** 22.0287 3.8738 rd 2 -0.0016*** -12.6025 3.4283 fi 0.0255*** 3.5577 4.3578 fi 2 -1.28e-04*** -3.4249 4.2128 ex 0.0119*** 26.6641 13.6124 ex 2 -9.36e-05*** -17.0069 12.4328 ec1 0.0393*** 7.5535 1.1698 ec21 0.1310*** 10.1139 2.6106 ec22 -4.72e-05 -0.0358 10.4591 ec222 -3.83e-05* -1.8291 7.8524 ec31 0.0175 1.1186 2.8294 ec32 -7.47e-04 -0.6356 11.0646 ec322 8.26e-06 0.5897 7.9876 opr -0.0441*** -6.4857 1.0724 klr -0.0942*** -16.0990 4.8555 klr 2 1.72e-04*** 5.5128 1.4425 lsize 0.5627*** 139.6625 5.6422 indb 0.0771*** 4.4743 3.0369 indc 0.1214*** 7.5717 4.5435 indd 0.1636*** 7.5286 1.7445 inde 0.1141*** 6.9995 3.9985 indf 0.1983*** 13.2852 8.7908 indg 0.1771*** 9.7818 2.8244 indh 0.0903*** 5.9271 6.8611 indi 0.2896*** 15.6108 2.5161 indj -0.0217 -1.2003 2.5268 adjusted r 2 0.6533 white test 58,394*** note: ***, **, * for significance at the 1%, 5%, 10% level. fig. 4 marginal impact of business life cycle fig. 5 marginal impact of brand revenue advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 51 next, the seven hypotheses summarized from (2.1) to (2.7) are each examined. for h1, the estimated coefficient for age is significantly lower than zero and that for age2 is significantly greater than zero. this confirms that the relation between value creation (lva) and the business life cycle can be portrayed by a u-shaped curve which decreases first before increasing. this link can be illustrated by fig. 4. in fig. 4, the minimum point of the lva curve corresponds to around 15 years of the business life cycle. hence, new ventures have to pay a cost of lower value creation at the early stage of corporate development, supporting h1 (2.1). for h2, the marginal impact of br on lva is observed from a reversed u-shaped curve that rises first before falling, illustrated by fig. 5. the maximum point of the lva curve is at 66.5584%, far above the sample mean (8.8812%). therefore, the role of branding in value creation is captured by a grin curve and there seems great room for improvement in taiwan’s current obms, supporting h2 (2.2). as regards h3, the coefficient for rd is positive whereas that for rd2 is negative. this can be illustrated by fig. 6, where the relation between r&d spending and value creation is presented by a reversed u-shaped curve. the maximum point of the lva curve is at 25.1563%, far above the mean for rd (0.3251%). hence, on the left side of supply chains, the strategies for odms are subject to a rising-then-falling grin curve, supporting h3 (2.3). comparing the marginal impact of brand (fig. 5) and the marginal impact of r&d (fig. 6), it is observed that the former impact is smaller than the latter impact. in other words, we observe an asymmetric grin curve whose left-side peak is higher than the right-side peak, supporting h4 (2.4). with respect to h5, the estimated coefficients for fi and fi2 also supports h5 (2.5), which implies a reversed u-shaped lva curve illustrated by fig. 7. the maximum point of this curve corresponds to a ratio of overseas investment to net fixed assets at 99.6094%, far above the industry mean (0.0511%), suggesting current underinvestment overseas by most smes in taiwan’s manufacturing industry. the finding for h6 is analogous to that for h5. as illustrated by fig. 8, the optimal export ratio is at 63.5684% and also far above the industry mean (8.3788%). hence, taiwan’s manufacturers which aim to strengthen the value creation need to substantially raise the weight of export in total revenue. comparing fig. 7 and fig. 8, the marginal impact of overseas investment is also higher than that of the export, implying an asymmetric grin curve and substantiating h7 (2.7). fig. 6 marginal impact of r&d spending fig. 7 marginal impact of overseas investment fig. 8 marginal impact of export advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 52 in terms of operation digitalization, the positive coefficients for the two dummies, ec1 and ec21, suggest that information disclosure and purchases on the internet serve to improve value creation by significant cost cut. however, the coefficients for ec22 significant negative and the coefficient for ec 31 and ec 32 are found insignificant. therefore, at least at the current stage, internet activities may not effectively contribute to value creation in taiwan’s businesses in the manufacturing sector. finally, the empirical findings with respect to control variables can be analyzed from five aspects. first, the coefficient for opr is significantly negative, implying that whether the firm’s main activity involves manufacturing or not cannot effectively increase the level of value creation. second, the positive sign for the firm’s size (lsize) confirms that value creation rises with corporate expansion. third, the capital-to-labor ratio (klr) exerts a u-shaped impact on value creation. capital intensity hence plays an important role in the firm’s value added. four, as regards the dummies for the various classes in taiwan’s manufacturing industry, the value added appears higher among indb～indi as we adopt food and drink (inda) as the benchmark industry class for comparison. fig. 9 integrates previous findings and analysis illustrated by fig. 5 to fig. 8 and presents an overall grin curve for taiwan’s manufacturing industry. figure 9 suggests that the grin curve shifts down as the firm’s operating years are less than 15 years. only as the firm’s life cycle exceeds 15 years will value creation be raised. fig. 9 asymmetric grin curve moreover, the marginal impact of r&d on value creation is higher than that of the brand, leading to an asymmetric grin curve where the left-side peak is higher than the right-side peak. the marginal impact of overseas investment is greater than that of exports, too. overall, the seven hypotheses stated in (2.1) to (2.7) are in line with fig. 9, which highlights graphic asymmetry in the grin curve for taiwan’s manufacturers. 4.3. robustness check to check the robustness of the previous analysis, we conduct three additional tests. table 4 summarizes results of testing the differences in means for major variables between new venture and survivors on the basis of two definitions for new ventures: defined by 12 years against definition by 15 years. overall, all variables except for ec31, ec32, indf, and indi exhibit significant differences between new ventures and survivors regardless of the definition for new ventures adopted, substantiating robustness of our analysis framework and results. table 5 compares coefficients respectively estimated with linear, quadratic, and cubic forms for selected variables for regression of lva. the estimation results appear consistent across the three regression models, further confirming the advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 53 robustness of our model specification. more specifically, the adjusted r2 remains around a similar level across the three models, implying that the respectively effect of key variables included in table 3 on value creation (lva) all holds regardless of the functional form adopted. for variables such as age, br, rd, fi, and ex, the impact on lva is consistently significant. in contract, the role for dummies such as e31 and e32 keeps absent. table 4 differences in means between new ventures and survivors new venture defined by 12 years new venture defined by 15 years variable age≤12 age≥12 age≤15 age≥15 lva 8.3191 8.6497 8.3599 8.6698 (1443.683***) (1397.573***) age 6.3419 23.0156 7.7371 24.5002 (134293.5***) (175364***) br 7.2344 9.6813 23.6322 26.9382 (209.4597***) (233.1375***) rd 0.3677 0.3045 0.3831 0.28426 (21.6962***) (58.4488***) fi 0.0210 0.0657 0.0244 0.0700 (25.0707***) (28.7915***) ex 6.4475 9.3157 6.7972 9.4936 (388.1113***) (378.0316***) opr 0.7816 0.8547 0.7869 0.8619 (880.1822***) (1022.868***) lsize 8.8140 9.3984 8.8743 9.4423 (2377.543***) (2477.660***) klr 1.4360 1.5809 1.4419 1.5982 (32.2502***) (41.4143***) ec1 0.5523 0.6414 0.5705 0.6417 (773.5952***) (543.8418***) ec21 0.1175 0.1117 0.1191 0.1097 (7.5348***) (22.3491***) ec22 1.3690 1.2976 1.3943 1.2691 (2.7802*) (9.3998***) ec31 0.0853 0.0843 0.0864 0.0834 (0.2861) (2.8233*) ec32 7.6027 7.4995 0.0864 1.3224 (0.1274) (0.1645) inda 0.2150 0.1791 0.0459 0.0328 (148.7985***) (119.8543***) indb 0.0588 0.0726 0.0609 0.0732 (68.5690***) (60.6506***) indc 0.0882 0.1003 0.0898 0.1010 (38.5585***) (36.6144***) indd 0.0319 0.0344 0.0305 0.0361 (5.5848**) (23.6399***) inde 0.0712 0.0965 0.0725 0.0993 (183.2514***) (227.4697***) indf 0.4542 0.4558 0.2954 0.2918 (1.3431) (1.5731) indg 0.0942 0.0664 0.0936 0.0627 (254.5745***) (347.7844***) indh 0.2275 0.2067 0.2228 0.2070 (58.7679***) (37.4631***) indi 0.0465 0.0463 0.0463 0.0465 (0.0275) (0.0216) indj 0.0420 0.0487 0.0423 0.0496 (23.2437***) (30.7220***) observations 34,132 70,245 43,194 61,183 note: ***, **, * for significance of the f-value at the 1%, 5%, 10% level. advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 54 table 5 robustness test by function form linear quadratic cubic variable lva lva lva constant 3.3533*** (53.0204) 3.2936*** (104.3353) 3.1809*** (108.8993) age 0.0014*** (5.0475) -0.0029*** (-3.4095) 0.0019 (1.3231) age 2 na 0.0001*** (4.7657) -0.0001** (-1.9651) age 3 na na 2.48e-06*** (3.0442) br 0.0019*** (14.3199) 0.0041*** (6.0753) 2.00e-05 (0.0090) br 2 na -3.08e-05*** (-4.0718) 5.57e-05 (0.9852) br 3 na na -4.84e-07 (-1.3533) rd 0.0296*** (10.5057) 0.0805*** (22.0287) 0.1573*** (33.8342) rd 2 na -0.0016*** (-12.6025) -0.0077*** (-23.9350) rd 3 na na 7.84e-05*** (18.7086) fi 0.0081** (2.3060) 0.0255*** (3.5577) 0.0594*** (6.1528) fi 2 na -0.0001*** (-3.4249) -0.0012*** (-5.3520) fi 3 na na 4.38e-06*** (5.0506) ex 0.0052*** (29.7733) 0.0119*** (26.6641) 0.0159*** (13.3506) ex 2 na -9.36e-05*** (-17.0069) -0.0003*** (-6.9366) ex 3 na na 1.17e-06*** (4.5717) ec1 0.0496*** (8.6773) 0.0393*** (7.5535) 0.0306*** (6.0460) ec21 0.1578*** (13.3077) 0.1310*** (10.1139) 0.1059*** (7.3308) ec22 -0.0024*** (-3.9812) -4.72e-05 (-0.0358) 0.0064*** (2.7088) ec22 2 na -3.83e-05* (-1.8291) -0.0003*** (-3.7794) ec22 3 na na 2.29e-06*** (3.5345) ec31 0.0137 (0.9719) 0.0175 (1.1186) 0.0178 (1.0281) ec32 0.0005 (0.9216) -0.0007 (-0.6356) -0.0003 (-0.1436) ec32 2 na 8.26e-06 (7.9876) -1.58e-05 (-0.2124) ec32 3 na na 2.38e-07 (0.4314) opr -0.0362*** (-0.0588) -0.0441*** (1.0724) -0.0438*** (-6.5869) klr -0.0497*** (-3.4393) -0.0942*** (4.8555) -0.1414*** (-21.8759) klr 2 na 0.0002*** (1.4425) 0.0009*** (6.3332) klr 3 na na -1.13e-06*** (-5.2410) lsize 0.5423*** (52.5408) 0.5627*** (5.6422) 0.5823*** (161.4039) advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 55 table 5 robustness test by function form (continued) linear quadratic cubic variable lva lva lva indb 0.0965*** (4.9269) 0.0771*** (3.0369) 0.0556*** (3.2904) indc 0.1321*** (7.7247) 0.1214*** (4.5435) 0.1075*** (6.8314) indd 0.1857*** (8.6562) 0.1636*** (1.7445) 0.1520*** (7.0760) inde 0.1360*** (7.6700) 0.1141*** (3.9985) 0.0943*** (5.9018) indf 0.2177*** (13.2065) 0.1983*** (8.7908) 0.1779*** (12.1368) indg 0.2373*** (11.3780) 0.1771*** (2.8244) 0.1301*** (7.3822) indh 0.1175*** (6.9732) 0.0903*** (6.8611) 0.0637*** (4.2661) indi 0.3201*** (15.6212) 0.2896*** (2.5161) 0.2529*** (13.9078) indj -0.0113*** (-0.5899) -0.0217 (2.5268) -0.0414** (-2.3481) adj. r 2 0.6332 0.6533 0.6696 white test 90341.73*** 58,394*** 34,574*** note: ***, **, * for significance at the 1%, 5%, 10% level. 5. conclusions this paper empirically adopts the big data obtained from the 2011 industry, commerce, and service census conducted by taiwan’s directorate-general of budget, accounting, and statistics and examines the link between the business life cycle, brand, r&d, internationalization, and value creation for taiwan’s manufacturers. regression results based on 104,377 observations in the prescreened sample can be recapitulated in seven points. (1) a relatively low level of the value added, brand revenue, r&d spending, and internationalization suggests that taiwan’s manufacturing industry is currently subject to a business environment dominated by oems mainly oriented to the local market. (2) new ventures whose business life is less than 15 years have to face a low level of value creation. only beyond 15 years will value creation be strengthened by greater efficiency in operation. (3) the marginal impact of brand revenue and r&d spending on value creation is captured by a reversed u-shaped curve. the decreasing marginal effect is higher for r&d than for brand revenue. (4) the marginal impact of the two gauges for internationalization (overseas investment and export) on value creation is captured by a reversed u-shaped curve, too. the decreasing marginal effect is higher for overseas investment than for export. (5) operation digitalization remains at a low level for taiwan’s manufacturers and its impact on value creation appears insignificant as of 2011. (6) the average business life cycle is around 18 years in the sample. under intensifying competition from globalization and e-business, the business life cycle is anticipated to be further shortened, creating more challenges to taiwan’s manufacturing industry. advances in technology innovation, vol. 4, no. 1, 2019, pp. 44 57 56 (7) businesses in the manufacturing industry in taiwan face an asymmetric grin curve rather than a smile curve. therefore, value creation can be strengthened through enhancement in the business life cycle, internationalization, internet activity, operating scale, and capital intensity. this study is conditioned on a few limitations, though. the big data obtained from the government census are based on five-year surveys. the problem associated with potentially lagged information appears unavoidable. besides, discontinuity in our data makes it difficult to analyze the stock value and lagged effect for activities associated with the brand, r&d, and overseas investment. availability of a more complete dataset will benefit future research, which can also extend analysis to issues such as income distribution and equality under intensified globalization. acknowledgement the authors would like to acknowledge a research grant (most 103-2632-h-029-002-my2) from the ministry science and technology in taiwan, roc. references [1] r. n. lussier, “a nonfinancial business success versus failure prediction model for young firms,” journal of small business management, vol. 33, no. 1, pp. 8-20, 1995. 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[22] j. r. lin, c. j. huang, and c. h. hsieh, “internationalization, domestic employment, and overstatement of export contribution,” taipei economic inquiry, vol. 51, no. 1, pp. 135-169, 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 improved whale optimization algorithm based on inertia weights for solving global optimization problems i-ming chao 1 , shou-cheng hsiung 1,* , jenn-long liu 2 1 department of industrial management, i-shou university, kaohsiung, taiwan 2 department of information management, i-shou university, kaohsiung, taiwan received 08 september 2019; received in revised form 09 december 2019; accepted 20 february 2020 doi: https://doi.org/10.46604/aiti.2020.4167 abstract whale optimization algorithm (woa) is a new kind of swarm-based optimization algorithm that mimics the foraging behavior of humpback whales. woa models the particular hunting behavior with three stages: encircling prey, bubble-net attacking, and search for prey. in this work, we proposed a new linear decreasing inertia weight with a random exploration ability (ldiwr) strategy. it also compared with the other three inertia weight woa (iwwoa) methods: constant inertia weight (ciw), linear decreasing inertia weight (ldiw), and linear increasing inertia weight (liiw) by adding fixed or linear inertia weights to the position vector of the reference whale. the four iwwoas are tested with 23 mathematical and theoretical optimization benchmark functions. experimental results show that most of iwwoas outperform the original woa in terms of solution accuracy and convergence rate when solving global optimization problems. accordingly, the ldiwr strategy produces a better balance between exploration and exploitation capabilities for multimodal functions. keywords: whale optimization algorithm, bubble-net feeding method, inertia weights, exploration and exploitation capabilities 1. introduction optimization plays essential roles in scientific research, management, and industry because numerous real-world problems can mostly model as optimization tasks [1]. in recent years, many meta-heuristic algorithms have been widely applied as powerful tools to solve optimization problems. due to the following reasons: (i) have fewer parameters; (ii) do not require gradient information; (iii) can bypass local optima; (iv) can be utilized to solve the practical problems [2]. there are many popular population-based meta-heuristic optimization algorithms, such as particle swarm optimization (pso) [3], ant colony system (acs) [4], artificial bee colony (abc) [5], cuckoo search (cs) [6], fruit fly optimization algorithm [7], and whale optimization algorithm (woa) [8]. among them, woa, proposed by mirjalili and lewis [8], is competitive. due to the simplicity of woa in implementation and only two main parameters adjusted, the algorithm has shown superior compared to the state-of-art meta-heuristic algorithms from the testing results of different benchmark functions and engineering design problems [8-9]. basically, the algorithm is inspired by the foraging behavior of humpback whales. humpback whales in a group hunt school of krill or small fishes by shrinking and encircling around them to herd them to close to the sea surface and generating bubbles along a helix-shaped or ‘9’-shaped path to perform a bubble-net attack [8-9]. population-based meta-heuristic optimization algorithms have a common feature regardless of their nature — the search process dividing into two phases: exploration and exploitation [8, 10]. the mechanisms of shrinking encircling and spiral * corresponding author. e-mail address: melvinisstrong@gmail.com advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 148 updating represent the exploitation phase, and the method of a random search for prey represents the exploration phase. finding a proper balance between exploration and exploitation is the most challenging task in the development of any metaheuristic algorithm due to the stochastic nature of the optimization process. the main problems faced by woa are slow and premature convergence, similar to other meta-heuristic algorithms. therefore, many variants of woa were proposed in the literature. to enhance the convergence speed and exploitation mechanism, mafarja and mirjalili proposed a memetic algorithm by hybrid woa with simulated annealing (sa) by searching the most promising regions located by the woa algorithm to improve the exploitation [9]. because the updated solution is mainly depending on the current best solution got so far. hu et al. [2] proposed the original woa with inertia weights, which is similar to the modified pso algorithm [11], to get an improved woa. in 2018, kaur and arora proposed a chaotic whale optimization algorithm (cwoa) to replace the critical parameter ‘p’ of woa instead of 0.5 probability that whale either chose the encircling or spiral path to update the position during optimization in the original woa [12]. to conclude the literature review; different inertia weight strategies may get various incremental changes in a better solution. in this paper, a new idea was proposed by adding linear decreasing inertia weight to the position vector of the reference whale and remaining the exploration ability of the original woa. to compare with the two best inertia weight methods, obtained from the study of hu et al. [2], the efficiency of the opposite strategy is also observed for linear decreasing inertia weight method. the rest of this paper is organized as follows. section 2 presents the basis of the original woa algorithm. improving woa by four inertia weightings was performed in section 3. in section 4, the experimental results presented and result analyzed. finally, in section 5, conclusions are given. 2. whale optimization algorithm woa is inspired by the individual foraging behavior of humpback whales. fig. 1 [9] shows the special hunting method of humpback whales. woa models the behavior as two phases. the first one is the exploitation phase, including encircling prey and spiral bubble-net attacking method. the second one is the exploration phase when searching randomly for prey. fig. 1 bubble-net feeding behavior of humpback whales [9] 2.1. exploitation phase (encircling prey and spiral bubble-net attacking method) humpback whales hunt prey with two steps: encircling around them and creating bubbles-nets. first, they recognize the locations of the prey and then encircle around them. woa algorithm assumes that the solution of the current best candidate (leader whale) is targeting prey or closing to the optimum. when encircling the prey, the other whales update their positions towards the best whale obtained so far. therefore, encircling prey can be represented by the following equations [8]: ( 1) ( )   j k i p jx t x t a d (1) ( ) ( )  j j j p id c x t x t (2) advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 149 the number of population and variables (dimensions) is assumed as m, and n. 𝑋𝑖 𝑗 is a position matrix, 𝑖 = 1, 2,⋯ ,𝑀, 𝑗 = 1, 2,⋯ ,𝑁 represents the position of the i th whale on the j th dimension. 𝑋𝑝 𝑗 represents the position of prey (the leader whale p) on the j th dimension. where t indicates the current iteration, 𝑋𝑝 𝑗 (𝑡) represents the current position on the j th dimension of the leader whale p, and 𝑋𝑖 𝑗 (𝑡) represents the current position of the i th whale on j th dimension; | |denotes the absolute value. xp should be updated every iteration if there is a better solution appearing. a and c are coefficient numbers that are calculated based on random functions as follows: 12  a a rand a (3) 22 c a rand (4) 2 2 a t maxiter (5) where maxiter is the maximum number of iterations, α is linearly decreasing from 2 to 0 from the start to the end of iterations (in both exploration and exploitation phases). since rand1 and rand2 are random numbers in the intervals [0, 1], then the ranges of a and c are in the intervals [−α, α] and [0, 2], respectively. in the exploitation phase, whales swim around the prey within the shrinking circle as well as move along a spiral-shaped path at the same time to form distinctive bubbles along a 9-shaped path to perform the bubble-net attacking [8]. in other words, there are two types of behavior in the bubble-net attacking that include a shrinking encircling mechanism or spiral updating position. as mentioned before, the value of a is linearly decreased from 2 to 0. since the range of a being in the intervals[−α, α], the absolute value of a decreases for iterations. therefore, the shrinking encircling mechanism can be achieved by using eq. (1) the spiral-shaped path between a whale 𝑋𝑖 𝑗 (𝑡) and the prey 𝑋𝑝 𝑗 (𝑡) can be expressed by eq. (6) [9]. ( 1) cos(2 ) ( )   j bl j i j px t d e l x t (6) where 𝐷𝑗 ′ = |𝑋𝑝 𝑗(𝑡) − 𝑋𝑖 𝑗(𝑡)| represents the distance between the i th whale and the prey (the best solution obtained so far) on the j th dimension, b is a constant for defining the logarithmic spiral shape, and l is a random number in [-1, 1]. to model the two mechanisms in the bubble-net attacking, shrinking encircling, and the spiral-shaped path. mirjalili and lewis assumed that there is a probability of 0.5 to choose between them throughout iterations as in eq. (7) [8, 9]. ( ) 0.5 ( 1) cos(2 ) ( ) 0.5            j p j j i bl j j p x t a d if p x t d e l x t if p (7) 2.2. exploration phase (search for prey) to enhance the exploration mechanism in woa, instead of updating the positions by the location of the best solution found so far. a random whale is selected to guide the search. when |𝐴| ≻ 1, a whale forced to move far away from the best-known whale to execute the global search for prey (exploration). however, when |𝐴| ≺ 1, a whale will perform a local search according to the best solution found so far (exploitation). this mechanism can model as follows [8, 9]: ( ) ( )  j j j rand id c x t x t (8) ( 1) ( )   j j i rand jx t x t a d (9) where 𝑋𝑟𝑎𝑛𝑑 𝑗 (𝑡) represents the position on j th dimension of a random whale from the population selected by |𝐴| ≻ 1. advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 150 3. inertia weight woa as seen in the previous section 2, the original woa updated solution mostly depends on the current best candidate solution. from the literature review, different inertia weight strategies are known to get different changes in solution [2, 11]. inertia weights are introduced ω & ωr ∈ [0, 1] into woa to get the improved whale optimization algorithm (inertia weight whale optimization algorithm, iwwoa) by adding fixed or linear inertia weights to the position of the reference whale. in the exploitation phase (|𝐴| ≺ 1), the updated method is represented by the following equations: ( ) ( )   j j j p id c x t x t (10) ( ) 0.5 ( 1) cos(2 ) ( ) 0.5                 j p j j i bl j j p x t a d if p x t d e l x t if p (11) in the exploration phase (|𝐴| ≻ 1), the updated mathematical model is as follows: ( ) ( )   j j j rand id r c x t x t (12) ( 1) ( )    j j i rand jx t r x t a d (13) hu et al. [2] had proved to add inertia weights into woa are competitive with other meta-heuristic algorithms: woa, foa, abc, and pso can enhance the ability of exploitation. hu et al. [2] applied four strategies, the ldiw strategy introduced by shi and eberhart [11] in 1998, sugeno function as an inertia weight (sfiw) introduced by lei et al. [13] in 2006, exponential decreasing inertia weight (ediw) strategy and ciw introduced by lu et al. [14] in 2014. iwwoa1 is the best result of the study [2] by adding smaller fixed inertia weights to the position vector of the reference whale. iwwoa2 uses the better region refer to the paper [11] by adding linear inertia weights to the reference whale to strengthen the local search ability of the original woa. iwwoa3 is the opposite way of iwwoa2. the iwwoa4 represents the new idea by adding linear decreasing inertia weight to the position vector of the reference whale and remaining the exploration ability of the original woa in the meantime. those ways are in the following: (1) iwwoa1: ω = ωr = 0.1 (ciw-the best); (2) iwwoa2: ω = ωr; ω_initial=0.9; ω_final=0.4; ω=ω_initial-(t/max_iter)×( ω_initial-ω_final) (ldiw-revised); (3) iwwoa3: ω = ωr; ω_initial=0.4; ω_final=0.9; ω=ω_initial-(t/max_iter)×( ω_initial-ω_final) (liiw-revised); (4) iwwoa4: ωr=1; ω_initial=0.9; ω_final=0.4; ω=ω_initial-(t/max_iter)×( ω_initial-ω_final) (ldiwr-proposed) where ω and ωr represent the inertia weight in the exploitation and exploration phase, respectively. when ω = ωr = 1, iwwoas become the original woa. ω = ωr = 0.1 have already been known can obtain a better solution in the ciw strategy for woa [2]. inertia weight linearly was learned to decrease from ω_initial=0.9 to ω_final=0.4 can obtain a better solution in the ldiw strategy for pso [11]. the effect of the liiw strategy on woa wants to be realized (from ω_initial=0.4 to ω_final=0.9), and the effect of the ldiwr strategy on woa. 4. results and discussion 4.1. experiments of benchmark functions to test the performance of the original woa [8] and the ldiwr strategy, the former methods proposed by hu et al. [2], the same 23 benchmark functions used in the literature [8] are taken, which consist of 7 (f1-f7) unimodal, 6 (f8-f13) advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 151 multimodal and 10 (f14-f23) fixeddimension multimodal functions. those functions are quite different from the test functions of hu et al. [2] in 2017 when consisting of 18 unimodal functions and only 9 multimodal functions. fig. 2 shows the typical 2d plot examples of the test benchmark functions considered in this work. f3 f8 f14 f6 f12 f16 (a) unimodal (b) multimodal (c) fixeddimension multimodal fig. 2 typical 2d plots of benchmark functions for all iwwoas & woa algorithms, the population size and maximum iteration are equal to 30 and 500, respectively. for each benchmark function, iwwoas & woa algorithms were executed independently run 30 times. table 1 and table 2 compares the best, the best mean (mean) and standard deviation (std) of solutions obtained by using the original woa & iwwoas for the benchmark functions (f1-f23). 4.2. evaluation of exploitation capability (functions f1–f7) f1-f7 are unimodal functions because there is only one global optimum solution. these functions usually utilized to evaluate the exploitation ability of meta-heuristic algorithms [8]. as seen from table 1 and table 2, the smaller ciw strategy got 5 in 7 of the best means, and the ldiw and ldiwr strategy got the others. the iwwoas are highly competitive with the original woa algorithm. most of the iwwoas is better than the original woa on the mean and standard deviation of 30 independent runs. furthermore, comparing the ldiw and liiw methods, the performance of those approaches follows this order: ldiw > liiw. because the ldiw strategy (ω = ωr from 0.9 to 0.4) leads the smaller and smaller stride, so it can provide better exploitation ability than liiw (ω = ωr from 0.4 to 0.9), especially in the final stage to find the globally optimal solution of unimodal functions. it is worth mentioning that the iwwoa1 (ciw ω = ωr = 0.1) is the best method on f1, f2, f3, f4, and f7. thus, iwwoas provide excellent exploitation capability, and the smaller ciw strategy is the better choice for unimodal functions. table 1 comparison of the best, mean and std values of the objective functions obtained using the woa and iwwoa1-iwwoa2 (continued) fun original woa iwwoa1(0.1) ciw iwwoa2(0.9->0.4) ldiw f1 1.60450e-73 6.09550e-73 0.00000e+00 0.00000e+00 1.54950e-271 0.00000e+00 f2 3.90430e-49 2.01600e-48 4.50300e-220 0.00000e+00 6.22180e-144 1.63220e-143 f3 4.46769e+04 1.42133e+04 0.00000e+00 0.00000e+00 7.35480e-182 0.00000e+00 f4 5.46388e+01 2.87173e+01 1.43180e-218 0.00000e+00 3.12300e-120 1.61210e-119 advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 152 table 1 comparison of the best, mean and std values of the objective functions obtained using the woa and iwwoa1-iwwoa2 fun original woa iwwoa1(0.1) ciw iwwoa2(0.9->0.4) ldiw f5 2.79790e+01 3.73070e-01 2.87286e+01 3.23700e-02 2.79719e+01 2.92100e-01 f6 4.19590e-01 2.67260e-01 6.09030e-01 3.07770e-01 2.81010e-01 1.25790e-01 f7 4.48670e-03 5.20030e-03 6.78090e-05 6.12410e-05 8.85760e-05 7.35660e-05 sum 5 / 0 6 / 0 2 / 5 1 / 6 0 / 1 0 / 2 f8 -9.95404e+03 1.56063e+03 -7.60267e+03 2.17479e+03 -1.10905e+04 1.63330e+03 f9 1.89480e-15 1.02040e-14 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 f10 4.79620e-15 2.31150e-15 8.88180e-16 0.00000e+00 2.42770e-15 1.76050e-15 f11 6.73470e-03 3.62670e-02 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 f12 4.06280e-02 7.38760e-02 3.70340e-02 2.43910e-02 1.24130e-02 5.75200e-03 f13 5.60110e-01 2.38900e-01 4.01050e-01 2.49290e-01 2.35320e-01 8.37050e-02 f14 3.12180e+00 3.50270e+00 6.09460e+00 3.61850e+00 2.60110e+00 3.01320e+00 f15 6.61020e-04 3.82440e-04 8.33010e-04 6.12800e-04 7.54130e-04 5.87520e-04 f16 -1.03160e+00 1.32260e-09 -9.83610e-01 1.86660e-02 -1.02900e+00 2.95320e-03 f17 3.97900e-01 1.16820e-05 5.99420e-01 1.64920e-01 3.98180e-01 4.20450e-04 f18 3.00010e+00 1.57690e-04 1.02615e+01 9.21590e+00 3.01600e+00 2.36150e-02 f19 -3.85460e+00 1.00220e-02 -3.26660e+00 4.38600e-01 -3.83800e+00 2.26320e-02 f20 -3.21410e+00 1.13040e-01 -1.80080e+00 4.58620e-01 -3.24200e+00 9.04730e-02 f21 -8.17300e+00 2.58430e+00 -2.65770e+00 1.11060e+00 -7.31410e+00 2.77040e+00 f22 -7.58410e+00 3.06820e+00 -2.56330e+00 9.32650e-01 -7.09060e+00 2.74490e+00 f23 -6.83310e+00 3.32870e+00 -2.90990e+00 1.65360e+00 -6.44140e+00 2.50680e+00 sum 5 / 5 6 / 4 11 / 3 9 / 3 0 / 3 1 / 3 remarks: 1. data with bold black font indicates the worst among the original woa and the other iwwoas 2. data with bold red font indicates the best among the original woa and the other iwwoas 3. the rows of sum indicate the accumulated number of the worst and the best in unimodal and multimodal functions 4.3. evaluation of exploration capability (functions f8–f23) multimodal functions are more complex than unimodal functions. the former functions include many local optima whose complexity increases exponentially with the number of design variables. consequently, this kind of test problems turns very popular to evaluate the exploration ability of the optimizer [8]. the results reported in table 1 and table 2 for functions f8-f23 show that the ldiwr strategy has an outstanding exploration capability. comparing the performance of the original woa with the inertia weighting methods in this work follows the order: ldiwr > original woa > liiw > ldiw > smaller ciw. the novel ldiwr method obtained 7 best mean solutions on f8-f9, f11-f14, and f23 in the 16 multimodal functions. notably, there is no worst solution obtained 8 best mean solutions on f8-f9, f11-f14, and f22-f23 in the 16 multimodal functions. notably, there is no worst solution obtained by the ldiwr strategy. previously mentioned ldiwr integrated the exploration mechanism of the original woa algorithm (ωr=1), and the better exploitation mechanism of the ldiw strategy on woa, as mentioned before. however, there are 11 worst mean solutions obtained by the ciw approach. it might be decreasing the exploration capability of iwwoa1 by using the smaller ciw strategy (ω = ωr = 0.1). it is worth mentioning that the liiw strategy is better than the ldiw for multimodal functions. because the liiw (ω = ωr from 0.4 to 0.9) leads the larger and larger stride; it could provide better exploration ability than the ldiw (ω = ωr from 0.9 to 0.4), especially in the final stage to find the globally optimal solution of multimodal functions. hence, the ldiwr is more robust than the other iwwoas and the original woa. advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 153 table 2 comparison of the best, mean and std values of the objective functions obtained using the iwwoa3 and iwwoa4 fun iwwoa3(0.4->0.9) liiw iwwoa4(0.9->0.4) with random ability-ldiwr mean std mean std f1 1.19800e-190 0.00000e+00 1.86600e-261 0.00000e+00 f2 4.25480e-105 1.38300e-104 1.71000e-141 5.32650e-141 f3 6.60840e-120 2.78580e-119 6.52640e-178 0.00000e+00 f4 1.09580e-75 3.82330e-75 2.99650e-116 1.56740e-115 f5 2.81399e+01 2.80560e-01 2.78947e+01 2.43210e-01 f6 4.88890e-01 1.75960e-01 2.95130e-01 9.86380e-02 f7 8.46060e-05 8.72020e-05 1.49770e-04 1.20400e-04 sum 0 / 0 0 / 1 0 / 1 0 / 3 f8 -1.10724e+04 1.68468e+03 -1.14430e+04 1.51963e+03 f9 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 f10 1.48030e-15 1.32400e-15 2.78300e-15 1.77240e-15 f11 0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00 f12 2.33280e-02 8.77710e-03 1.20190e-02 4.66670e-03 f13 2.70880e-01 8.10020e-02 2.19660e-01 7.98360e-02 f14 3.48570e+00 3.34880e+00 1.98310e+00 2.10240e+00 f15 3.63690e-04 8.53780e-05 6.74530e-04 5.41630e-04 f16 -1.00900e+00 1.12530e-02 -1.02780e+00 5.95660e-03 f17 3.99250e-01 1.95610e-03 3.98160e-01 3.54870e-04 f18 3.01550e+00 2.42980e-02 3.01610e+00 2.44000e-02 f19 -3.83410e+00 2.84740e-02 -3.83910e+00 2.49720e-02 f20 -3.15340e+00 1.28960e-01 -3.23220e+00 9.90000e-02 f21 -4.99030e+00 6.67050e-02 -7.29060e+00 2.40980e+00 f22 -5.22030e+00 8.95650e-01 -7.66510e+00 2.64640e+00 f23 -5.17970e+00 9.96500e-01 -8.17640e+00 2.53490e+00 sum 0 / 3 0 / 6 0 / 8 0 / 6 remarks: 1. data with bold black font indicates the worst among the original woa and the other iwwoas 2. data with bold red font indicates the best among the original woa and the other iwwoas 3. the rows of sum indicate the accumulated number of the worst and the best in unimodal and multimodal 4.4. analysis of convergence behavior as learned that the quality of the solution and the convergence speed of an algorithm of the global optimal solution enormously depends on the parameter and search strategy of the optimizer [1]. therefore; analyzing the convergence behavior after different inertia weighting was added to the position vector of the reference whale in necessary. convergence curves of the original woa, ciw, ldiw, liiw, and ldiwr were compared in fig. 3 for 23 benchmark functions. iwwoas are competitive enough with the original woa on the mean best fitness in each iteration over 30 runs. the slow convergence and premature convergence problems of woa on unimodal and multimodal functions (f1 to f13) can be seen. as shown in fig. 3, the iwwoas shows three different convergence behaviors when optimizing 23 benchmark functions. firstly, the convergence of the iwwoas tends to be accelerated as iteration increases except the liiw on f1 through f4. secondly, iwwoas trend of convergence within fewer iterations. the adding inertia weight strategy proposed for ciw, ldiw, and liiw restrict the exploration capability to assist them in looking for the promising regions of unimodal and multimodal functions in the initial steps of iteration. they also cause a more rapid converge towards the optimum almost before half of the iterations. this behavior is evident in f5 through f13. thirdly, the original woa and ldiwr are almost faster than the others on the fixed-dimension multimodal functions. their excellent performance is due to their full exploration ability of woa on multimodal functions. advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 154 f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f11 f12 f13 f14 f15 f16 f17 f18 f19 f20 f21 f22 f23 fig. 3 comparison of convergence curves obtained using the original woa and proposed four iwwoas for solving 23 benchmark functions advances in technology innovation, vol. 5, no. 3, 2020, pp. 147-155 155 5. conclusions this work introduced four inertia weighting to the position vector of the reference whale to strengthen the local search ability of the woa. the proposed iwwoas on 23 mathematics benchmark functions were conducted to analyze the exploitation, exploration, and convergence behavior by comparison with the original woa, iwwoa1 (ciw ω = ωr = 0.1), iwwoa2 (ldiw ω = ωr = 0.9 to 0.4), iwwoa3 (liiw ω = ωr = 0.4 to 0.9), and iwwoa4 (ldiwr ω =0.9 to 0.4, ωr =1). iwwoas were found to be competitive enough. according to our analysis, the smaller constant inertia weight strategy (ciw ω = ωr = 0.1) was the better choice for unimodal functions. furthermore, the linear decreasing inertia weight with random exploration ability strategy (ldiwr ω =0.9 to 0.4, ωr =1) preserved the full exploration capability of woa. it possesses the benefit of the inertia weight method, which is also more robust than the other iwwoas and the original woa on multimodal functions. hence, the ldiwr strategy can produce a better balance between exploration and exploitation capabilities for searching solutions and result in an improvement in the convergence speed and optimal solution of the original woa. conflicts of interest the authors declare no conflict of interest. references [1] g. wu, r. mallipeddi, and p. n. suganthan, “ensemble strategies for population-based optimization algorithmsa survey,” swarm and evolutionary computation, vol. 44, pp. 695-711, february 2019. 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[7] w. t. pan, “a new fruit fly optimization algorithm: taking the financial distress model as an example,” knowledge-based systems, vol. 26, pp. 69-74, february 2012. [8] s. mirjalili and a. lewis, “the whale optimization algorithm,” advances in engineering software, vol. 95, pp. 51-67, may 2016. [9] m. m. mafarja and s. mirjalili, “hybrid whale optimization algorithm with simulated annealing for feature selection,” neurocomputing, vol. 260, pp. 302-312, october 2017. [10] m. črepinšek, s. h. liu, and m. mernik, “exploration and exploitation in evolutionary algorithms: a survey,” acm computing surveys (csur), vol. 45, no. 3, pp. 1-33, june 2013. [11] y. shi and r. c. eberhart, “parameter selection in particle swarm optimization,” proc. international conference on evolutionary programming, march 1998, pp. 591-600. [12] g. kaur and s. arora, “chaotic whale optimization algorithm,” journal of computational design and engineering, vol. 5, no. 3, pp. 275-284, january 2018. [13] k. lei, y. qiu, and y. he, “a new adaptive well-chosen inertia weight strategy to automatically harmonize global and local search ability in particle swarm optimization,” proc. ieee symp. 2006 1st international symposium on systems and control in aerospace and astronautics (isscaa), january 2006, pp. 977-980. [14] j. lu, h. hu, and y. bai, “radial basis function neural network based on an improved exponential decreasing inertia weight-particle swarm optimization algorithm for aqi prediction,” abstract and applied analysis, vol. 2014, pp. 1-9, july 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 3___aiti#9227___258-269 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 effects of data standardization on hyperparameter optimization with the grid search algorithm based on deep learning: a case study of electric load forecasting tran thanh ngoc, le van dai * , lam binh minh faculty of electrical engineering technology, industrial university of ho chi minh city, ho chi minh city, vietnam received 04 january 2022; received in revised form 24 march 2022; accepted 25 march 2022 doi: https://doi.org/10.46604/aiti.2022.9227 abstract this study investigates data standardization methods based on the grid search (gs) algorithm for energy load forecasting, including zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust, to determine the hyperparameters of deep learning (dl) models. the considered dl models are the convolutional neural network (cnn) and long short-term memory network (lstmn). the procedure is made over (i) setting the configuration for cnn and lstmn, (ii) establishing the hyperparameter values of cnn and lstmn models based on epoch, batch, optimizer, dropout, filters, and kernel, (iii) using eight data standardization methods to standardize the input data, and (iv) using the gs algorithm to search the optimal hyperparameters based on the mean absolute error (mae) and mean absolute percent error (mape) indexes. the effectiveness of the proposed method is verified on the power load data of the australian state of queensland and vietnamese ho chi minh city. the simulation results show that the proposed data standardization methods are appropriate, except for the zero-mean and min-max methods. keywords: deep learning, grid search, data standardization method, hyperparameter, electric load forecasting 1. introduction according to the united states energy information administration (us-eia), worldwide energy demand is expected to rise by 50%, with rising countries in asia leading the way. this rising demand would place considerable strain on the current energy infrastructure and jeopardize global environmental health by increasing greenhouse gas emissions from conventional power sources [1]. in the united states and europe, an estimated 40% of electricity consumption and 38% of co2 emissions come from the construction industry [2]. currently, the construction industry tends to use sustainable energy sources to replace limited energy sources. as a result, the use of renewable energy sources has been increasing, the design of buildings must be improved, and the building energy demand needs to be forecasted. therefore, it is necessary to apply the energy load forecasting method because it has both economic and infrastructure advantages. this method can predict future electricity consumption and help power companies make economically viable plans and decisions [3]. short-term load forecasting plays an important role in the power industry, including power system planning, power generation planning, and the power supply-demand balance [4-5]. if load forecasting is accurate, significant cost reductions in control operations and decision-making, such as dispatch, unit commitment, fuel allocation, power system security assessment, and off-line analysis, would be realized. on the contrary, if there is an error in the forecast of electricity demand, there will be an increase in operating costs. * corresponding author. e-mail address: levandai@iuh.edu.vn advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 in the past decade, many methodologies and techniques have been proposed to solve the problem of short-term power load forecasting. they can be classified into two groups of methods. the first group relates to using statistical methods, such as multiple regression, exponential smoothing, and autoregressive integrated moving average (arima) [6-7]. the second group employs artificial intelligence techniques, such as support vector machines (svm) and artificial neural networks (anns) [8-9]. recent development based on anns and deep learning (dl) networks is one of the methods applied to solve the problem of load forecasting. the dl architecture includes different models, such as long short-term memory networks (lstmn), convolutional neural networks (cnn), deep belief networks, and deep boltzmann machine networks. among them, lstmn and cnn are popular in the problem of power load forecasting [10-11]. the main feature of the dl model is that the accuracy of the load-forecasted results highly depends on its hyperparameters. therefore, determining these hyperparameters for dl models is important [12-13]. recently, some algorithms, such as grid search (gs), random search (rs), and genetic algorithm (ga), have been applied to determine the hyperparameters of the dl model, among which the gs algorithm was widely applied [14-15]. in addition, the characteristics of the input data are also important factors affecting the accuracy of the dl model. moolayil [16] introduced some data standardization methods to solve this problem. however, raschka et al. [17] and yang et al. [18] did not show any interest in employing data normalization on the gs algorithm. as a result, this may be a leading disadvantage for these studies. to overcome this disadvantage, this study proposes an input data standardization method on the gs algorithm to determine the hyperparameters of the dl model, including cnn and lstmn, for energy load forecasting. for this proposed method, the model data are split into training and testing sets. for the training step, the gs algorithm is performed to determine the hyperparameters of the dl model corresponding to each data normalization method. for the testing step, the predicted errors of these optimal models are compared, and thereby the proposed methodology can evaluate the impact of the data normalization methods on the gs algorithm to the dl model. the error value in the dl model is usually determined based on the error evaluation indexes of the actual value and predicted value of the model, such as the mean absolute error (mae) and the mean absolute percent error (mape). the forecasting results of the dl model are significantly affected by the scale and size of the data. therefore, it is necessary to standardize the data during training and forecasting for the dl model. in this study, the methods, such as zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust, are proposed to standardize the input data of the dl model, and the hyperparameter values of cnn and lstmn models are established based on epoch, batch, optimizer, dropout, filters, and kernel. the novelty and contributions of this study include the following aspects: (i) introduce a data standardization method on the gs algorithm to determine the optimal hyperparameters of the dl model, including cnn and lstmn for the energy load forecasting; (ii) consider the error evaluation indexes of mae and mape of actual and predicted values for determining the optimal hyperparameters of the dl model through the epoch, batch, optimizer, dropout, filters, and kernel; (iii) conclude that the zero-mean and min-max are two of the data standardization methods and not the best methods on the gs algorithm for determining the optimal hyperparameters of the dl model. this study consists of five sections. section 1 presents the urgency, settlement, and unresolved issues of the load forecasting problem. section 2 describes the principle, hyperparameters, gs algorithm, and data normalization method for the dl model. the experimental procedures and settings are presented in section 3. section 4 presents the results and discussion. finally, the conclusions and future research aspects are presented in section 5. 2. methodology 2.1. deep learning structures artificial intelligence is the ability of a machine to imitate intelligent human behavior. machine learning (ml) is part of artificial intelligence that allows a system to learn and automatically improve from experience. dl is an application of ml that 259 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 uses complex algorithms and deep neural nets to train a model. dl models are built using several algorithms, such as cnns, lstmns, recurrent neural networks (rnns), generative adversarial networks (gans), radial basis function networks (rbfns), and so on [19]. in this study, two widespread dl networks, lstmn and cnn, are used to resolve the problem. the procedure is performed as follows. 2.1.1. lstmn network the difference between the rnn and feed-forward neural network (ffnn) is that the rnn is a model that can create a correlation between the previous information and the current state. a simple rnn structure is shown in fig. 1, in which the output signal is determined based on a linear transformation and nonlinear activation. the output signal can be calculated under the tangent function as follows [20]: 1tanh( ( , ) ) t t t h w h x b−= + (1) where ht-1 denotes the (t-1)th output signal, xt denotes the t th input signal, and b denotes the bias. the lstmn is a modified rnn model developed by song et al. [21]. the difference between the lstmn and the rnn is that the lstmn can process long-term dependencies. fig. 2 describes the lstmn structure. each block has two parallel lines going in and out, representing the cell state and hidden state information. the general structure of lstmn has four layers of neural networks composed of three inputs (i.e., ct-1, ht-1, and xt) and two outputs (i.e., ct and ht). therefore, this lstmn structure can be described by the following equations [21]: the authors identify the information from the previous cell state ct-1 that should be removed by the following forget gate ft. 1( ))( , t f t t f f w h x b−= × +σ (2) the authors identify the input signal xt that should be stored in the cell state ct in the input gate, in which the input information and the candidacy cell state ��� should be updated by: 1 ( ( , ) ) t i t t i i w h x b−= × +σ (3) 1tanh( ( , ) ) t c t t c c w h x b−= × +ɶ (4) the previous cell state ct is updated by combining ct-1 and ���: 1t t t t t c f c i c−= × + × ɶ (5) the outcome ht in the output gate is confirmed based on the output information ot and ct: 1 ( ))( , t o t t o o w h x b−= × +σ (6) tanh( ) t t t h o c= × (7) in which w is the input weight and f, i, and o represent the forget, input, and output gates, respectively. a a ht-1 ht ht+1 xt-1 xt xt+1 tanh fig. 1 simple rnn architecture 260 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 ht ct-1 ht-1 xt σ tanh ct ht ft it ot tcɶ σ σ tanh fig. 2 lstmn architecture 2.1.2. cnn network cnn is a feedforward neural network with a structure similar to that of human neurons. fig. 3 depicts the cnn structure developed based on the convolutional cnn structure introduced in the work of bon et al. [22], which includes convolution, pooling, and fully linked layers. the input data are convolved using many filters for the convolution layer, and a feature map is formed when a bias term is added. then, a nonlinear function is applied. the pooling layer’s primary goal is to lower the resolution of the feature maps to aggregate the input data. there are several sorts of pooling procedures, the most prevalent of which is the max-pooling strategy. finally, fully connected layers process the convolutional layers’ outputs [21]. ... ... input convolution layer pooling layer fully connected layer output fig. 3 the architecture of the cnn model 2.2. hyperparameters in general, the accuracy of a dl model depends on its hyperparameters. therefore, determining the hyperparameters for dl plays an extremely important role. a hyperparameter is a configuration that is external to the model, whose value cannot be estimated from data and all values are set before the started network training. in this study, the hyperparameter values of lstm and cnn are established, as listed in table 1. epoch refers to the number of times to expose the model to the whole training dataset; batch refers to the number of samples within an epoch after which the weights are updated; dropout refers to the process of randomly omitting a fraction of the hidden neurons. for each training case, each hidden neuron is randomly omitted from the network with a fixed probability p, where p can be chosen in the range [0,1]. optimizer refers to the optimization algorithm which plays an important role in improving the accuracy of the dl network. the optimizer is a mathematical algorithm that uses derivatives, partial derivatives, and the chain rule in calculus to understand how much change the network will see in the loss function by making a small change in the weight of the neurons. filter is one of the most important cnn hyperparameters, which is the number of filters that will be learned by the convolutional layer. in a cnn, a convolution filter iterates over all of the input components, executing convolution operations to extract input characteristics; 32, 64, 128, and so on are the most frequent number of filters. the convolution window width and height are determined by kernel size. the kernel size might be an odd integer, such as (3, 3), (5, 5), (7, 7), and so on. there have been many proposed methods to determine the dl hyperparameters in recent years, such as the gs, rs, gradient-based optimization, bayesian optimization (bo), ga, and particle swarm optimization (pso). of these methods, gs is widely employed due to its simplicity and efficiency. therefore, gs is the choice to determine the dl hyperparameters in this study. 261 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 table 1 graph representations lstmn model cnn model epoch epoch batch batch optimizer optimizer dropout filter kernel 2.3. grid search method the gs is a comprehensive search process through the predefined subclass of the value’s combinatory of the model’s hyperparameters. the operation principle of gs is illustrated in fig. 4. it is composed of two hyperparameters, x and y [23-24]. the x is established by three values {x1, x2, x3}, and the y is established by three values {y1, y2, y3}. as a result, their combination is nine value pairs. the gs will perform a search for the optimal model based on these values, and the optimal hyperparameter corresponds to the dl model with the smallest error. x y 3 y 2 y 1 y 2 x 1 x 3 x fig. 4 the operation principle of the gs method the error value in the dl model is usually determined based on the error evaluation indexes of the actual and predicted values of the model, such as mean square error (mse), mae, and mape. these evaluation indexes can be described as follows [25]: 2 1 1 ˆmse n i i i y y n = = −∑ (8) 1 1 ˆmae n i i i y y n = = −∑ (9) 1 ˆ1 mape 100 n i i i i y y n y= − = ×∑ (10) where �� is the actual value i th , and ˆ i y is the predicted value i th . 2.4. data normalization many studies have shown that the forecasting results of the dl model are significantly affected by the scale and size of the data [26]. thus, it is necessary to standardize the data during training and forecasting for the dl model. in this study, the methods zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust are proposed to standardize the input data of the dl model. the mathematical models of these methods can be described as follows [16]: mean std zero-mean normalization : x x x x ′ − = (11) min max min min-max normalization: x x x x x − = − ′ (12) 262 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 max max normalization: x x x =′ (13) decimal normalization: 10 j x x′ = (14) min1 sigmoid normalization: , 1 a std x x x a xe − ′ − = = + ∀ (15) min1 softmax normalization: , 1 a a std x xe x a xe − − −−= =′ + ∀ (16) med median normalization: x x x =′ (17) med 75 25robust normalization: , x x x iqr x x iqr − = = −′ ∀ (18) where � and �� are the original and standardized date value, respectively; xmean, xstd, xmin, xmax, and xmed are the mean, standard deviation, min, max, and median values of x, respectively; x25 and x75 are the 25 th quantile and the 75 th quantile values of x, respectively; j is the smallest integer that satisfies the condition of max|��| ≤ 1. 2.5. grid search method based on data normalization based on the theoretical base of the dl structure, hyperparameter, and the date standardization method, as presented in sections 2.1, 2.2, and 2.4, the proposed gs algorithm applied to standardize the data for the dl model is shown in fig. 5. the procedure is done in the six steps below. the procedure is applied to each data standardization method, as introduced in section 2.4, to determine the error value. this error value is then compared to evaluate the effect of these methods on the gs algorithm for the dl network. step 1: the original data is processed and the input-target pairs of (��� �� , ��� �� ) and (����� , ����� ) are determined corresponding to the training and test processes, respectively. step 2: the training and test data are standardized by using the methods described in section 2.4 to determine (��� �� � , ��� �� � ) and (����� � , ����� � ). the next step is the training process. step 3: the gs algorithm is applied to determine the optimal hyperparameters of the dl model from the variable value combination of each hyperparameter cfg = {cfgi}, i= 1: n, in which n is the total number of combinations. the vector cfgi depends on the dl model. for the lstmn model, cfgi = {ei, bi, oi, di} is used, whereas cfgi ={ei, bi, oi, fi, ki} is used for the cnn model, in which e, b, o, d, f, and k notate the hyperparameters of epoch, batch, optimizer, dropout, filters, and kernel, respectively. for this step, to overcome overfitting during training, the cross-validation (cv) technique is applied, and the dl model is run repeatedly at the same time. then, the average value of the model is used to increase its reliability. the next steps are the test processes: step 4: the dl is used with the obtained hyperparameters in step 3 to predict the �������� � . step 5: �������� is calculated by using the value �������� � . step 6: the error value of the dl is determined based on the difference between �������� and ����� by using eqs. (8)-(10). 263 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 process data scaling data data trainx trainy testx testy mse ' trainx ' train y using cnn and lstmn models (testing process) un-scaling data ' testx ' testy' predict y evaluate by using eqs. (8)-(10) predicty testy mae mape using cnn and lstmn models (training process) cfgopt cfg fig. 5 the gs methodology based on data normalization 3. simulation data setup 3.1. data the half-hourly load demand data of queensland state, australia, and the hourly load demand data of ho chi minh city, vietnam, are used to verify the effectiveness of the proposed method. the selected data are divided into two different cases, corresponding to the lstmn and the cnn. these datasets have different periods, and their statistical properties are shown in table 2. fig. 6 shows the ytrain value waveform in case 1 according to the data normalization methods. 6000 5000 (1)-none 1.0 -1.0 0.0 (2)-zero-mean 0.75 0.25 0.50 (3)-min-max 0.9 0.7 0.8 (4)-max 0.6 0.5 (5)-decimal 0.75 0.25 0.50 (6)-sigmoid 0.5 -0.5 0.0 (7)-softmax 1.0 0.8 (8)-median 0.0 -1.0 (9)-robust m w p u p u p u p u p u p u p u p u 0 100 200 300 time (half hour) (2)-zero-mean (7)-softmax time (half hour) 3000 2000 (1)-none m w -1.0 0.25 0.50 (3)-min-max p u 0.6 0.8 (4)-max p u 0.3 0.2 (5)-decimal p u 0.75 0.25 0.50 (6)-sigmoid p u 1.00 0.75 (8)-median p u 0.0 -0.5 (9)-robust p u 0 50 100 150 0.5 1.0 0.0p u 0.5 -0.5 0.0p u (a) queensland state (b) ho chi minh city fig. 6 the ytrain test value waveform in case 1 according to the data normalization methods 264 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 table 2 data characteristics description case 1: lstm model case 2: cnn model queensland state ho chi minh city queensland state ho chi minh city xtrain xtest xtrain xtest xtrain xtest xtrain xtest time (day) 05/10/14 05/23/14 05/24/14 05/30/14 25/11/18 22/12/18 12/23/18 12/29/18 03/29/14 05/23/14 05/24/14 05/30/14 10/28/14 12/22/14 12/23/18 12/29/18 size (672,48) (336, 48) (672, 24) (168, 24) (2688, 48) (336, 48) (1344, 24) (168, 24) min (mw) 4,304.46 4,404.48 1,347.70 1,873.90 4,279.21 4,404.48 1,347.70 1,873.90 mean (mw) 5,535.20 5,591.45 2,917.94 2,844.65 5,589.60 5,591.45 2,951.42 2,844.65 max (mw) 6,917.66 6,824.76 3,945.90 3,695.20 6,984.78 6,824.76 3,945.9 3,695.20 std (mw) 6,38.78 6,54.69 6,02.94 553.73 679.70 654.69 589.33 553.73 3.2. simulation value setup the values of the optimal hyperparameters for the dl model are listed in table 3. for the lstm model, the total number of the hyperparameter combinations, represented by cfgi = {ei, bi, oi, di}, is 81. the set value for the cv cycle is 2 (i.e., the training dataset is divided into two subsets corresponding to two times of training and testing). for the cnn model, the total number of the hyperparameter combinations, written as cfgi = {ei, bi, oi, fi, ki}, is 243. the set value for the cv cycle is equal to 3 (i.e., the training dataset is divided into three subsets corresponding to three times of training and testing). the set value for the number of repetitions is two times for both lstm and cnn (i.e., each model is trained twice). the error measurement of the gs algorithm used in the training process is mae. table 3 the values of the optimal hyperparameters for the dl model hyperparameter lstm model cnn model epoch (e) 100, 300, 500 300, 500, 700 batch (b) 10, 30, 50 30, 50, 70 optimizer (o) adadelta, adam, adamax adagrad, adam, sgd dropout rate (d) 0.1, 0.3, 0.5 filter (f) 48, 80, 112 kernel (k) 3, 5, 7 number of combinations (cfg) 81 243 4. experimental results and analyses tables 4 and 5 show the experimental results produced while using lstm and cnn based on the gs algorithm during training for the data normalization scenarios, respectively. these tables illustrate that the dl model’s ideal hyperparameters have distinct values for each data normalization approach and for various queensland and ho chi minh city datasets. in addition, it shows the same values of the optimal hyperparameter set in some cases. for example, in the instance of queensland state data where the lstmn is applied, the max and median approaches yield the same values of the ideal hyperparameters as the normal method (original data). table 4 the obtained results of optimal hyperparameters when using lstmn method queensland state ho chi minh city epoch batch dropout optimizer epoch batch dropout optimizer normal 500 10 0.1 adam 500 10 0.3 adam zero-mean 500 10 0.1 adamax 500 30 0.1 adam min-max 500 10 0.1 adamax 500 10 0.1 adam max 500 10 0.1 adam 300 10 0.1 adam decimal 500 10 0.3 adam 500 10 0.3 adam sigmoid 500 10 0.1 adamax 500 10 0.1 adam softmax 500 10 0.1 adamax 500 10 0.1 adam median 500 10 0.1 adam 300 10 0.1 adam robust 500 50 0.1 adam 500 10 0.1 adam 265 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 table 5 the obtained results of optimal hyperparameters when using cnn method queensland state ho chi minh city epoch batch optimizer filter kernel epoch batch optimizer filter kernel normal 700 50 adam 112 7 700 30 adam 80 5 zero-mean 700 70 adam 112 3 500 50 adam 112 7 min-max 500 50 adam 112 3 700 50 adam 112 7 max 700 30 adam 112 3 700 30 adam 112 5 decimal 700 50 adam 112 7 700 70 adam 112 7 sigmoid 700 50 adam 80 7 700 30 adam 80 7 softmax 300 70 adam 80 7 700 50 adam 80 7 median 700 50 adam 80 5 700 30 adam 80 7 robust 500 70 adam 112 7 700 50 adam 80 5 table 6 the mae when using the lstmn method mae (mw) mape (%) training test training queensland ho chi minh city queensland ho chi minh city queensland ho chi minh city normal 546.17 534.95 567.59 504.53 10.68 20.07 standard 33.31 26.68 39.94 48.58 0.73 1.73 min-max 40.21 35.37 39.14 46.81 0.70 1.76 max 44.04 50.82 44.18 50.09 0.81 1.85 decimal 45.63 47.32 43.74 53.42 0.80 2.00 sigmoid 40.19 56.87 40.96 68.12 0.73 2.43 softmax 34.43 30.88 36.64 43.95 0.66 1.61 median 41.98 65.02 42.44 60.23 0.77 2.24 robust 34.16 28.62 37.24 39.31 0.67 1.42 table 7 the mae when using cnn method mae (mw) mape (%) training test training queensland ho chi minh city queensland ho chi minh city queensland ho chi minh city normal 52.66 38.95 52.94 46.97 0.94 1.71 standard 32.98 25.60 37.03 38.72 0.67 1.41 min-max 35.98 26.02 37.18 38.65 0.66 1.42 max 44.57 34.58 41.64 38.62 0.74 1.42 decimal 40.76 37.25 39.38 43.80 0.71 1.61 sigmoid 35.79 30.40 38.01 42.89 0.68 1.56 softmax 33.17 24.48 35.51 36.19 0.64 1.37 median 40.78 34.01 39.48 39.25 0.70 1.45 robust 26.21 23.63 33.56 36.03 0.60 1.32 table 6 presents the mae and the mape error of the training and test stages of the lstmn model. fig. 7 shows the boxplot chart of these maes and mapes corresponding to table 6. the obtained results show the effectiveness of the data normalization method for the gs algorithm in the lstm model. specifically, the mae is significantly reduced when a data normalization method is applied. for queensland data, the mae of the test process is 567.59 mw and the mape is 10.68% without using any data normalization technique, while they decrease to 44.18 mw and 0.81% at max, respectively, when the proposed data normalization methods are applied. similarly, table 7 and fig. 8 show the mae, the mape, and their boxplots of the training and test stages for the cnn model. again, the observed results show that applying data normalization methods significantly reduces both the mae and mpae. in other words, the performance of the gs algorithm is greatly improved with data normalization. moreover, the effectiveness of applying data normalization techniques can be divided into three groups. the first group of applying the softmax and robust methods yields small maes. the second group, which presents medium maes, includes the zero-mean and the min-max. the third group that provides medium maes consists of the max, decimal, sigmoid, and median methods. 266 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 queensland ho chi minh normalization m a e ( m w ) (a) mae of the training process 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 queensland ho chi minh normalization m a e ( m w ) 17.5 12.5 10.0 7.5 2.5 0 1 2 3 4 5 6 7 8 9 queensland ho chi minh normalization m a p e ( % ) 5.0 15.0 20.0 (b) mae of the test process (c) mape of the test process fig. 7 the boxplot of the maes and mapes when using lstmn 50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 queensland ho chi minh normalization m a e ( m w ) (a) mae of the training process 50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 queensland ho chi minh normalization m a e ( m w ) 1.6 1.2 1.0 0.6 0.2 0 1 2 3 4 5 6 7 8 9 queensland ho chi minh normalization m a p e ( % ) 0.4 0.8 1.4 (b) mae of the testing process (c) mape of the test process fig. 8 the boxplot of the maes and mapes when using cnn 267 advances in technology innovation, vol. 7, no. 4, 2022, pp. 258-269 5. conclusions this study presents an approach to examine the effect of data normalization methods on the gs algorithm for determining the optimal hyperparameters of the dl model, including the lstmn and cnn, for energy load forecasting. the power load data of the australian state of queensland and the vietnamese city of ho chi minh were used to verify the reliability of the proposed method. the error evaluation indexes of mae and mape of the actual and predicted values are established based on the epoch, batch, optimizer, dropout, filters, and kernel to determine the optimal hyperparameters of the dl model. the effectiveness of applying data normalization techniques can be divided into three groups. the first group of the applications of the softmax and robust methods yielded small maes. the second group, which presented medium maes, included the zero-mean and the min-max. the third group that provided medium maes consisted of the max, decimal, sigmoid, and median methods. the results showed that both mae and mape were much smaller when applying data normalization. in addition, out of the eight proposed data normalization methods, zero-mean or min-max was not the best method for the gs algorithm for determining the optimal hyperparameters of the dl model. conflicts of interest the authors declare no conflicts of interest. references [1] 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[26] a. s. girsang, et al., “stock price prediction using lstm and search economics optimization,” iaeng international journal of computer science, vol. 47, no. 4, pp. 758-764, november 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 269  advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 free vibration frequency of thick fgm circular cylindrical shells with simply homogeneous equation by using tsdt chih-chiang hong * department of mechanical engineering, hsiuping university of science and technology, taichung, taiwan received 04 june 2019; received in revised form 20 july 2019; accepted 17 september 2019 doi: https://doi.org/10.46604/aiti.2020.4380 abstract the objective of this study is to provide the frequency solutions of free vibration in thick fgm circular cylindrical shells by mainly considering both shear correction coefficient and nonlinear coefficient term. this paper investigates the effects of third-order shear deformation theory (tsdt) and the varied shear correction coefficient on the free vibration of thick functionally graded material (fgm), the circular cylindrical shells with simply homogeneous equation under thermal environment. the approach of derivations are given as follows, the varied value of shear correction coefficient is included in the simple homogeneous equation. the nonlinear term of displacement field of tsdt is also included to derive the simply homogeneous equation, some reasonable simplifications in the elements of homogeneous matrix under free vibration of thick fgm circular cylindrical shells are assumed, thus, the natural frequency can be found. three parameters effect on the frequency of thick fgm circular cylindrical shells are computed and investigated, they are nonlinear coefficient c1 term, environment temperature and power law index. there are some main conclusions obtained, generally the natural frequency results are in decreasing value with the mode shape numbers for the thicker circular cylindrical shells. the values of natural frequencies are also affected by the nonlinear coefficient term. keywords: third-order shear deformation theory, tsdt, fgm, shells, vibration, frequency 1. introduction there are some free vibration frequency investigations with shear deformation effect and experimental studies in the functionally graded material (fgm) circular cylindrical shells. in 2019, shahbaztabar et al. [1] presented the free vibration of fgm circular cylindrical shells, including the pasternak foundation and stationary fluid by using the first order shear deformation theory (fsdt). some effects on the result of the natural frequencies are investigated e.g. fluid depth ratio, elastic foundation, volume fraction exponent, geometrical parameters and boundary conditions. in 2019, zippo et al. [2] used the experimental method and the model of finite element method (fem) to study the linear and dynamic behavior of vibrations in the polymeric circular cylindrical shell with fgm equivalent thermal temperature properties. in 2018, baltacıoğlu and civalek [3] used the love’s shell theory and fsdt of the displacements to obtain the numerical results for the circular cylindrical fgm with carbon nanotube reinforced (cntr) panels. for the thick fgm shells, it is necessary to consider the nonlinear terms of displacement theories to obtain more accurate results of analyses, e.g. third-order shear deformation theory (tsdt), higher-order shear deformation theory and triangular function shear deformation theory. in 2018, torabi and ansari [4] presented a formulation of higher-order isoparametric supplement to study the free vibration of fgm shells, considering the structural effects of circular cylindrical, conical, spherical and toroid shells. in 2017, baltacıoğlu and civalek [5] used the extended fem to obtain the frequency of the vibration of cracked fgm shells considering the structural effects of cylindrical * corresponding author. e-mail address: cchong@mail.hust.edu.tw advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 85 shell, conical shell and spherical on the vibrations. in 2017, wang and wu [6] presented the free vibration analysis of porous fgm cylindrical shells based on a sinusoidal shear deformation theory (ssdt). in 2014, fazzolari and carrera [7] presented the hierarchical trigonometric ritz formulation (htrf) and used in the free vibration analyses for the doubly curved fgm shells and sandwich shells with fgm core. in 2016, fantuzzi et al. [8] presented free vibration analyses of cylindrical and spherical shells by using the fem and the generalized differential quadrature (gdq) methods. there are some new and improved tsdt used in the investigations of fgms. in 2016, bui et al. [9] presented the numerical results of deflection and frequency by using the tsdt and fem for the static bending behaviors of fgm plates. a similar new tsdt in terms of five un-known variables was used in the eigenvalue equation to calculate the natural frequency. in 2017, do et al. [10] presented the numerical results of deflection and stress by using the tsdt and fem for the static buckling and bending behaviors of fgm plates. the same new tsdt in terms of five un-known variables was used in the bending equation and pre-buckling equation respectively to calculate the numerical solutions without considering the effect of shear correction factors. in 2018, vu et al. [11] presented the numerical results of deflection and frequency by using the tsdt and meshfree method for the static bending, free vibration and buckling behaviors of fgm plates. a similar refined tsdt in terms of four un-known variables was used in the equations to calculate the numerical solutions. fig. 1 two-material thick fgm circular cylindrical shells there are some importance and relevance of studied topics in the dynamics of cylindrical shells composed of fgms. in 2012, zhang et al. [12] presented the nonlinear dynamics of clamped-clamped fgm circular cylindrical shells under an external excitation and uniform temperature change. the similar equations were used and based on the fsdt and von-karman nonlinear strains-displacement relation to obtain the numerical response of displacements. in 2016, dai et al. [13] presented the reviews of coupled mechanics on the fgm cylindrical structures during years 2000-2015. some of the existing mechanical theories and hypotheses were assumed and would be improved in the future for obtaining the more accuracy of the results. in 2008, ansari and darvizeh [14] presented a general analytical approach in arbitrary boundary conditions of fgm circular cylindrical shells. the fsdt of displacements was used to derive the homogeneous linear system and obtained the natural frequency under different boundary conditions. the author has some gdq computational experiences in the composited fgm circular cylindrical shells. in 2017, hong [15] used the approach of fsdt model and the varied shear correction factor to present the numerical gdq results of thermal vibration and flutter of a supersonic air flowed over thick fgm circular cylindrical shells. in 2017, hong [16] used the approach of love’s theory for thin multilayered shells to present the numerical gdq results of displacement and stresses of thin fgm laminated magnetostrictive shells with the value effects of velocity feedback and control gain subjected to thermal vibration. it is interesting to investigate the natural frequency in the tsdt approach of thick fgm circular cylindrical shells under free vibration with simply homogeneous equation and four edges in simply supported boundary conditions. the value effects of three parametric: nonlinear coefficient 1c term, environment temperature and power law index on the natural frequency of thick fgm circular cylindrical shells are investigated. the main contribution and novelty of paper is to provide and investigate the analytic solutions of natural frequencies in the free vibration ,  x,u z,w r t z r * h l x fgm material 1 fgm material 2 1h 2h advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 86 of thick fgm circular cylindrical shells by considering the varied effects of shear correction coefficient and nonlinear terms of tsdt. the motivation of the paper is listed as follows. to obtain the natural frequency values of fgm shells considering the nonlinear coefficient terms of tsdt within the simply homogeneous matrix equation. also by considering the calculated values of shear correction coefficient usually varied with thickness, power law index and environment temperature. 2. formulation for a two-material thick fgm circular cylindrical shells in thermal environment with thickness 1h of fgm material 1 and thickness 2h of fgm material 2. fig. 1 shows a colorful figure that can illustrate the fgm material for the approach of the study. the material properties of power-law function of fgm circular cylindrical shells are considered with a young’s modulus fgme of fgm in the standard variation form of power law index nr , the others are assumed in the simple average form [17]. the properties ip of individual constituent material of fgms are functions of environment temperature t in the following form [18], 1 2 3 0 1 1 2 3( 1 )ip p p t pt p t pt       (1) where 0 1 1 2, , ,p p p p and 3p are the temperature coefficients. the time dependent of nonlinear displacements u , v and w of thick fgm circular cylindrical shells are assumed in the nonlinear coefficient 1c term of tsdt equations [19] as follows, 3 0 1 3 0 1 ( , , ) ( , , ) ( ) ( , , ) ( , , ) ( ) ( , , ) x x w u u x t z x t c z x w v v x t z x t c z r w w x t                          (2) where 0u and 0v are tangential displacements in the in-surface coordinates x and  axes direction, respectively, w is transverse displacement in the out of surface coordinates z axis direction of the middle-plane of circular cylindrical shells, x and  are the shear rotations, r is the middle-surface radius of fgm shell, t is time. coefficient for *2 1 4 / (3 )c h is given as in tsdt approach, in which *h is the total thickness of circular cylindrical shells. the linear time dependent of displacements also can be obtained by letting 1 0c  in the equations. the nonlinear coefficient 1c term of displacement fields of tsdt [19] is used in the thick fgm circular cylindrical shells to investigate the nonlinear value effect on the natural frequency results. for the normal stresses ( x and  ) and the shear stresses ( ,x z   and xz ) in the thick fgm circular cylindrical shells under temperature difference t for the 𝑘 th layer are in the following equations [20-21], 11 12 16 12 22 26 ( ) ( )16 26 66 ( ) 44 45 ( ) ( )45 55 ( )   , , x x x x x xk k k z z xz xzk kk q q q t q q q t tq q q q q q q                                                                                 (3) where x and  are the coefficients of thermal expansion, x is the coefficient of thermal shear, ijq is the stiffness of fgm circular cylindrical shells. x ,  and x are in-plane strains, not negligible z and xz are shear strains. advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 87 the dynamic equations of motion with tsdt for a thick fgm circular cylindrical shells are given as follows [22], 2 2 2 0 0 1 1 32 2 2 2 2 2 0 0 1 1 32 2 2 2 2 2 1 2 2 2 2 2 2 2 2 0 1 6 1 32 2 2 2 2 1 + ( ) 1 + ( ) 1 2 1 + ( ) 1 ( ) [ xx x x x x xx x n n u w i j c i x r xt t t n n v w i j c i x r rt t t q q p p p c q x r r xx r w w w i c i c i t t x r                                                                        2 2 0 0 42 2 2 1 0 2 1 42 2 1 0 2 1 42 1 1 ( ) ( )] 1 + ( ) 1 1 + ( ) x xx x xx x u v j x r x rt t m m w q j u k c j x r xt m m w q j v k c j x r rt                                                 (4) where * * * * * * 1 1 2 2 2 2 32 2 , ( , , ) hxx x h x x hxx x h x x hxx x h x x z x xz m m c p q q c p x n n dz n m m zdz m p p z dz p q q                                                                                                                  * * * 2 2 1 ( ) 1 , ( 0,1, 2,...,6) h h n k k i i k k dz i z dz i           (5) where *n is the total number of layers,  k  is the density of k th ply.   i i 1 i 2j i c i , i 1,4   , 2 2 2 1 4 1 6k i 2c i c i   there are some assumptions for the terms in the strains, e.g. the higher order terms 2( / )w x  , 2[ / ( )]w r   and ( / )[ / ( )]w x w r     can’t be neglected. the von karman type of strain-displacement relations with 0 0/ /v z v r    , 0 0/ /u z u r    and / / / 0xw z z z          are used as eq. (6), by substituting equations (3) and (6) into equation (4), the dynamic equilibrium differential equations with tsdt of thick fgm circular cylindrical shells in terms of partial derivatives of displacements and shear rotations subjected to the expressions terms ( 1 5, ...,f f ) in partial derivatives of thermal loads ( , ,n m p ), mechanical loads ( 1 2, ,p p q ) and inertia terms can be derived and expressed in matrix forms. by assuming that mid-plane strain terms    2 1 / 2 w / x  ,    w / x 1 / r w /     and      2 1 / 2 1 / r w /    are in constant values, the 1 5, ...,f f can be expressed in the derivative terms as eq. (7)-(8), advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 88 2 22 30 x x x 1 2 2 22 30 1 2 2 2 zz x u 1 w u w 1 w z c z x 2 x x x x x 2 x 1 v 1 1 w 1 v 1 1 1 w 1 1 w z c z r 2 r r r r r 2 r 0 1 u v w 1 w r x x r                                                                                                          2 2 3 30 x x 0 1 1 20 z 1 20 xz x 1 x 1 u w v 1 w w 1 w z c z z c z r x x x x r x x r v 1 w v 1 w 1 w 3c z z r r r r u w u w 3c z z x r x                                                                                                              　　 w x    (6) 1 1 2 2 2 2 2 3 1 2 2 2 4 1 5 1 1 + 1 + 2 1 ( ) 1 1 + ( ) 1 1 + ( ) xx x x xx x xx x xx x x x n n f p x r n n f p x r p p p f q c r xx r m m p p f c x r x r m m p p f c x r x r                                                                 (7) and * * * * * * 32 11 12 16 2 32 12 22 26 2 32 16 26 66 2 ( , , ) ( ) (1, , ) ( , , ) ( ) (1, , ) ( , , ) ( ) (1, , ) ( , , , , , )s s s s s s s s s s s s h xx xxxx x xh h x xh h x xx x xh i j i j i j i j i j i j n m p q q q t z z dz n m p q q q t z z dz n m p q q q t z z dz a b d e f h                                       * * * * ** * * * * * * * * * * * * 2 3 4 62 2 2 3 4 5 * *2 2 (1, , , , , ) , ( , 1,2,6) ( , , , , , ) (1, , , , , ) , ( , 4,5) s s h s s i jh h i ji j i j i j i j i j i j h q z z z z z dz i j a b d e f h k q z z z z z dz i j        (8) where 1 p and 2 p are external in-plane distributed forces in x and  direction respectively. q is external pressure load. k is the shear correction coefficient. *h is the total thickness of fgms circular cylindrical shells. the computed and varied values of k are usually functions of total thickness of circular cylindrical shells, fgm power law index and environment temperature [23]. the s si j q and * *i j q for thick fgm circular cylindrical shells with /z r terms cannot be neglected are used in the following simple forms in 2014 by hong [23], in 2010 by sepiani et al. [24], advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 89 2 11 22 2 12 21 44 55 66 16 26 45 / (1 ) ( ) / [(1 / )(1 )] / [2(1 )] / [2(1 / )(1 )] 0 fgm fgm fgm fgm fgm fgm fgm fgm fgm q q e q q e z r q e q q e z r q q q                      (9) where 1 2=( ) / 2fgm   is the poisson’s ratios of the fgm circular cylindrical shells, * * 2 1 1( )[( ) / ] nr fgme e e z h h e    is the young’s modulus of the fgm circular cylindrical shells, nr is the power-law exponent parameter, 1e and 2e are the young’s modulus, 1 and 2 are the poisson’s ratios of the fgm constituent material 1 and 2, respectively. the simpler stiffness forms of s si j q and * *i j q are used to calculate the stresses, , , , , ,s s s s s s s s s s s si j i j i j i j i j i j a b d e f h and * * * * * * * * * * * *, , , , , i j i j i j i j i j i j a b d e f h . for example, by using change of variable in integration calculation, the 11a , 11e , 11f , 11h and 44h of thick fgm circular cylindrical shells are given as follows, * 1 2 11 21 2 * 4 2 1 11 21 2 * 5 1 11 2 1 21 2 * 7 11 2 1 21 2 ( ) 1 1 ( ) 2 ( ) ( ) 1 3 3 1 [ ] 4 2( 3) 4( 2) 8( 1) 1 ( ) 2 ( ) 1 2 1 1 1 {( )[ ] } 5 4 3 2( 2) 16( 1) 80 1 ( ) 2 ( ) 1 3 {( )[ 7 1 ( ) 2 n n n n n n n n n n n n r e eh a r h e e e r r r r h e f e e r r r r r h h e e r r                                             1 * 6 2 1 44 1 2 13 2 13 6 4( 5) 4 16( 3) 3 1 ] } 16( 2) 64( 1) 448 ( ) ( ) 1 5 2 1 5 1 [ ] 6 2( 5) 4 3 64( 2) 32( 1) 2(1 ) 2 n n n n n n n n n n n n r r r e r r k h e e h r r r r r r                               (10) 3. vibration frequency the thick fgm circular cylindrical shells with layers in the stacking sequence (0 / 0 )  are used to study the free vibration frequency results with the effects of environment temperature and varied shear correction coefficient calculations, under four sides simply supported boundary condition, no thermal loads ( t 0  ), no in-plane distributed forces ( 1 p = 2 p =0) and no external pressure load ( q =0) . the free vibration frequency mn with mode shape numbers 𝑚 and 𝑛 for four sides simply supported boundary condition can be derived by simply assuming that 31 1 0i i j   , 0ij ijb e  , 16 26 0a a  , 16 26 0d d  and 45 45 45 0a d f   under the following time sinusoidal displacement and shear rotations forms with amplitudes mna , mnb , mnc , mnd and mne . 0 0 cos( / )sin( / )sin( ) sin( / )cos( / )sin( ) sin( / )sin( / )sin( ) cos( / )sin( / )sin( ) sin( / )cos( / )sin( ) mn mn mn mn mn mn x mn mn mn mn u a m x l n r t v b m x l n r t w c m x l n r t d m x l n r t e m x l n r t                       (11) advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 90 where m is the number of axial half-waves, n is the number of circumferential waves. by substituting equations (11) into dynamic equilibrium differential equations under free vibration  1 2 5... 0f f f    with the assumed reasonable simplifications of 13 14 15 23 24 25 0fh fh fh fh fh fh      and 3 61 4 0i ij j   in the elements of homogeneous matrix, thus the simply homogeneous equation can be obtained as follows. 11 12 12 22 33 34 35 2 34 44 45 0 2 35 45 55 0 0 0 0 00 0 0 00 0 ,0 0 0 0 0 0 0 mn mnmn mnmn mn mn mn mn mn fh fh afh fh bfh fh fh ck fh fh fh i d ek fh fh fh i                                                       (12) where 2 0 2 2 11 11 66 12 12 66 2 2 22 66 22 2 2 2 4 2 2 2 2 33 55 44 1 11 1 12 1 66 2 4 1 22 1 55 1 55 ( / ) ( / ) ( )( / )( / ) ( / ) ( / ) ( / ) ( / ) ( / ) (2 +4 )( / ) ( / ) ( / ) 3 (2 -3 )( mn mni fh a m l a n r fh a a m l n r fh a m l a n r fh a m l a n r c h m l c h c h m l n r c h n r c d c f                            2 2 1 44 1 44/ ) 3 (2 -3 )( / )m l c d c f n r  (13) and 2 3 2 2 2 34 55 1 11 1 11 1 66 1 66 1 12 1 12 2 1 55 1 55 2 3 2 2 2 35 44 1 22 1 22 1 66 1 66 1 12 1 12 2 1 44 1 44 ( / ) ( )( / ) (2 -3 + )( / )( / ) (6 -9 )( / ) ( / ) ( )( / ) (2 -3 + )( / ) ( / ) (6 -9 )( fh a m l c f c h m l c f c h c f c h m l n r c d c f m l fh a n r c f c h n r c f c h c f c h m l n r c d c f n                  2 3 2 2 2 2 44 11 1 11 1 11 66 1 66 1 66 55 1 55 1 55 2 2 45 12 66 1 12 1 12 1 66 1 66 2 2 2 2 55 66 1 66 1 66 22 1 22 1 22 44 / ) ( -2 + )( / ) ( -2 + )( / ) 6 9 ( + -2 + -2 + )( / )( / ) ( -2 + )( / ) ( -2 + )( / ) 6 r fh d c f c h m l d c f c h n r a c d c f fh d d c f c h c f c h m l n r fh d c f c h m l d c f c h n r a                  2 1 44 1 449c d c f (14) the determinant of the coefficient matrix in equation (12) vanishes for obtaining non-trivial solution of amplitudes can be represented in the simply five degree polynomial equation as follows, thus the mn can be found. 5 4 3 2(1) (2) (3) (4) (5) (6) 0mn mn mn mn mna a a a a a          (15) where 11 12 11 22 12 12 11 12 11 22 12 12 11 22 11 22 12 12 11 22 11 22 12 12 (1) (2) ( ) (3) [( ) ( ) ] (4) ( ) ( ) (5) [( ) ( ) ] (6) ( ) a sd a fh fh sd sc a fh fh fh fh sd fh fh sc sb a fh fh fh fh sc fh fh sb sa a fh fh fh fh sb fh fh sa a fh fh fh fh sa                        (16) advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 91 in which 2 2 0 33 44 2 0 33 55 44 55 33 44 35 35 34 34 2 0 45 45 33 44 55 44 34 35 35 34 45 35 35 44 34 34 55 45 45 33 ( / ) / ( ) / sd k i sc fh sd fh k i sb fh fh fh fh fh fh fh fh fh fh k i fh fh sa fh fh fh fh fh fh fh fh fh fh fh fh fh fh fh fh fh fh                (17) 4. results and discussion table 1 *f for sus304/si3n4 */l h nr 1c (1/ mm2) *f present solution, * 1.2h  mm, varied k 1t k 100t k 300t k 600t k 1000t k 5 0.5 0.925925 0 3.178485 8.567362 3.434401 9.391482 3.873990 10.984527 4.111627 12.617598 3.662770 13.538765 1 0.925925 0 3.318237 7.958229 3.570262 8.647485 4.005848 9.985663 4.253132 11.39358 3.862303 12.597763 2 0.925925 0 3.477849 7.132526 3.723252 7.690617 4.151720 8.763615 4.409905 9.831241 4.098108 10.888006 10 0.925925 0 3.756482 6.452526 3.984509 6.885567 4.394140 7.695008 4.670961 8.305713 4.532945 8.563466 8 0.5 0.925925 0 2.238668 6.204801 2.419486 6.788758 2.730914 7.907682 2.897884 9.025515 2.576800 9.594029 1 0.925925 0 2.336488 5.856612 2.514541 6.350593 2.823131 7.296222 2.996852 8.251528 2.716518 8.981841 2 0.925925 0 2.448283 5.856612 2.621661 6.350593 2.925246 6.587167 3.106589 7.313977 2.881696 7.905719 10 0.925925 0 2.643672 5.107512 2.804862 5.428395 3.095301 6.021389 3.289678 6.482052 3.186499 6.638852 10 0.5 0.925925 0 1.926014 5.478031 2.081703 5.986835 2.349735 6.954710 2.830540 7.897100 2.217255 8.325227 1 0.925925 0 2.010152 5.224647 2.163467 5.659943 2.429062 6.485115 2.578504 7.288469 2.337450 7.833433 2 0.925925 0 2.106326 4.906995 2.255628 5.272914 2.663339 5.956491 2.672919 6.573925 2.479556 6.987514 10 0.925925 0 2.274471 4.730258 2.413313 5.024359 2.663339 5.565807 2.830540 5.980343 2.741827 6.078461 the composited thick fgm sus304/si3n4 material is used to implement the numerical computation of vibration under environment temperature t (free stress assumed). the fgm material 1 at inner position of circular cylindrical shells is sus304 (stainless steel), the fgm material 2 at outer position of circular cylindrical shells is si3n4 (silicon nitride) used for the free vibration frequency computations with simply homogeneous equation. for the preliminary fgm circular cylindrical shells study, it did not considered the effect of nonlinear coefficient term on the calculation of varied shear correction coefficient. the varied values of k are usually functions of *h , nr and t in the thick fgm circular cylindrical shells ( 0ijb  ). for l/r=1, 1 2h h , * 1.2h  mm, calculated values of k are increasing with nr (from 0.1 to 10). thus values of k are used for frequency calculations of the free vibration (no thermal loads under no temperature difference ( t =0) including the effects of nonlinear coefficient 1c term. firstly, for the frequency parameter * 11 2 114 /f r i a values under the effects of 1c = 0.925925/mm 2 and 1c = 0/mm 2 for */l h = 5, 8 and 10 are shown in table 1, where 11 is the fundamental first natural frequency (m = n = 1). for sus304/si3n4 thick circular cylindrical shells under free vibration with * 1.2h  mm, the *f values under 1t k , 100k, 300k, 600k and 1000k with varied k and 1c effects are in the values not greater than 13.538765. advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 92 the frequency parameter 2 * 11 1 1( / ) /l h e   values under the effects of 1c = 0.925925/mm 2 and 1c = 0/mm 2 for */l h = 5, 8 and 10 are shown in table 2, 1 is the density of fgm material 1, for sus304/si3n4 thick circular cylindrical shells under free vibration with * 1.2h  mm, the ω values under 1t k , 100k, 300k, 600k and 1000k with varied k and 1c effects are in the values not greater than 32.380783. it is easy to judge the machining abnormality by the external sensor signal in this experiment. at this time, the internal condition data could be combined to determine the type of abnormality as chatter. the accuracy of the monitoring is improved. there are a variety of visualization methods in this monitoring system, which could help to quickly locate abnormal positions. in addition, it helped to grasp the information of cnc machine tool conditions at all times, which reduced the difficulty of subsequent fault analysis and diagnosis. table 2  for sus304/si3n4 */l h nr 1c (1/ mm2)  present solution, * 1.2h  mm , varied k 1t k 100t k 300t k 600t k 1000t k 5 0.5 0.925925 0 5.781036 15.582337 6.101545 16.684873 6.693336 18.978658 7.132169 21.886919 7.123131 26.329359 1 0.925925 0 5.782522 13.868399 6.103089 14.782213 6.694982 16.689058 7.133930 19.110862 7.124928 23.239543 2 0.925925 0 5.783707 11.861481 6.104272 12.608768 6.696166 14.134532 7.135265 15.907033 7.126575 18.934150 10 0.925925 0 5.784393 9.935876 6.104699 10.549432 6.696107 11.726208 7.135397 12.687871 7.128233 13.466383 */l h nr 1c (1/ mm2)  present solution, * 1.2h  mm , varied k 1t k 100t k 300t k 600t k 1000t k 8 0.5 0.925925 0 6.514712 18.056488 6.877522 19.297414 7.549395 21.860160 8.042832 25.049551 8.017926 29.852609 1 0.925925 0 6.514685 16.329633 6.877464 17.369365 7.549288 19.510704 8.042762 22.144931 8.018013 26.510597 2 0.925925 0 6.514442 16.329633 6.877144 17.369365 7.548845 16.998745 8.042382 18.934526 8.017992 21.996770 10 0.925925 0 6.513346 12.583626 6.875763 13.307022 7.546949 14.681323 8.040542 15.843253 8.017431 16.703767 10 0.5 0.925925 0 7.006078 19.926910 7.396695 21.272380 8.119573 24.032178 8.647910 27.397165 8.623964 32.380783 1 0.925925 0 7.005980 18.209449 7.396562 19.350477 8.119391 21.677169 8.650032 24.450416 8.623955 28.901228 2 0.925925 0 7.005695 16.320789 7.396207 17.289890 8.117177 19.214038 8.649613 21.273336 8.623854 24.302459 10 0.925925 0 7.004657 14.567711 7.394913 15.395722 8.117177 16.963157 8.647910 18.271238 8.623262 19.117235 it is interesting to compare the present vibration values of frequency with some authors' work as shown in the tables (3)-(4). the values of *f vs. *h for sus304/si3n4 under */l h =10 and 300t k with varied k and 1c effects are shown in table 3. the compared value *f = 8.426538 at *h = 2mm, nr = 0.5 is greater than *f = 8.0 at n= 13 with silicon nitride-nickel under classical shell theory (cst), no external pressure ( 0ek  ) by sepiani et al. in 2010 [24]. the values of  vs. *h for sus304/si3n4 under */l h =10 and t=700k with varied k and 1c effects are shown in table 4. the compared value  = 2.459972 at 1c = 0.925925/mm 2 , * 1.2h  mm, nr = 0.5 is greater than  = 1.71137 with the material variation type a, three layers thickness ratio 1-8-1, the l directional radius of curvature is ∞, */l h =10, nr = 0.5 for the fgm sandwich shell presented by chen et al. in 2017 [25]. advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 93 table 3 comparison of frequency *f for sus304/si3n4 and silicon nitride-nickel 1c (1/mm2) *h (mm) *f present method , * 1/ = 0l h , 300t k , varied k , for 3 4sus304 / si n sepiani et al. 2010, for silicon nitride-nickel, n 13 0.5nr  1nr  2nr  0.925925 1.2 2.349735 2.429062 2.516924 0.333333 2 8.426538 8.711254 9.026930 8.0 0.000033 200 842669.2 871142.9 902712.1 0.000014 300 253980.0 262560.1 272073.1 0.000003 600 18903.19 19542.01 20250.14 0.000001 900 43930.59 45414.97 47060.53 table 4 comparison of frequency  for sus304/si3n4 1c (1/mm2) *h (mm)  present method, * 0/ 1l h  , 700t k , varied k chen et al. 2017, type a, 1-8-1, 0.5nr  0.5nr  1nr  2nr  0.925925 1.2 2.459972 2.550420 2.651571 1.71137 0.333333 2 8.821661 9.146189 9.509387 0.000033 200 882174.8 914629.0 950949.6 0.000014 300 267903.0 277757.0 288785.0 0.000003 600 19897.76 20629.82 21448.99 0.000001 900 46307.33 48010.84 49917.17 table 5 fundamental natural frequency 11 for * 1.2 h mm */l h nr 1c (1/ mm2) 11 1t k 100t k 300t k 600t k 1000t k 5 0.5 0.925925 0 0.001620 0.004366 0.001730 0.004731 0.001906 0.005406 0.001947 0.005975 0.001614 0.005968 1 0.925925 0 0.001620 0.003886 0.001730 0.004191 0.001907 0.004753 0.001947 0.005217 0.001615 0.005267 2 0.925925 0 0.001620 0.003324 0.001730 0.003575 0.001907 0.004026 0.001948 0.004343 0.001615 0.004291 10 0.925925 0 0.001620 0.002784 0.001731 0.002991 0.001907 0.003340 0.001948 0.003464 0.001615 0.003052 8 0.5 0.925925 0 0.000713 0.001976 0.000761 0.002137 0.000840 0.002432 0.000857 0.002671 0.000709 0.002643 1 0.925925 0 0.000713 0.001787 0.000761 0.001924 0.000840 0.002170 0.000857 0.002361 0.000709 0.002347 2 0.925925 0 0.000713 0.001787 0.000761 0.001924 0.000839 0.001891 0.000857 0.002019 0.000709 0.001947 10 0.925925 0 0.000712 0.001377 0.000761 0.001474 0.000839 0.001633 0.000857 0.001689 0.000709 0.001479 10 0.5 0.925925 0 0.000490 0.001396 0.000524 0.001508 0.000578 0.001711 0.000590 0.001870 0.000488 0.001835 1 0.925925 0 0.000490 0.001275 0.000524 0.001371 0.000578 0.001543 0.000590 0.001668 0.000488 0.001637 2 0.925925 0 0.000490 0.001143 0.000524 0.001225 0.000578 0.001368 0.000590 0.001452 0.000488 0.001377 10 0.925925 0 0.000490 0.001020 0.000524 0.001091 0.000578 0.001208 0.000590 0.001247 0.000488 0.001083 secondly, the natural frequency mn values (unit 1/s) of free vibration ( t 0  ) according to mode shape numbers m and n for the sus304/si3n4 fgm thick circular cylindrical shells are calculated. for the values of fundamental first (m=n=1) natural frequency 11 vs. nr with * 1.2h  mm, varied k and the effects of 1c = 0.925925/mm 2 and 1c = 0/mm 2 for */l h = 5, 8 and 10 are under 1t k , 100k, 300k, 600k and 1000k are shown in table 5. for the values of natural frequency mn vs. m,n=1,2,…,9 with nr = 0.5, 300t k , * 1.2h  mm under varied k and the effects of 1c = 0.925925/mm 2 and 1c = 0/mm 2 for */l h = 5 and 10 are shown in table 6. advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 94 table 6 natural frequency mn vs. m and n under varied k , 1c , 0.5nr  and 300t k 1c (1/ mm 2 ) */l h 1n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.001906 0.000578 0.001347 0.000409 0.001098 0.000334 0.000949 0.000289 0.000847 0.000258 0.000772 0.000236 0.000713 0.000218 0.000666 0.000204 0.000627 0.000193 0 5 10 0.005406 0.001711 0.005285 0.001621 0.005244 0.001602 0.005209 0.001595 0.005170 0.001592 0.005126 0.001590 0.005077 0.001588 0.005022 0.001587 0.004963 0.001586 1c (1/ mm 2 ) */l h 2n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.001347 0.000409 0.000953 0.000289 0.000778 0.000236 0.000673 0.000204 0.000602 0.000183 0.000549 0.000167 0.000508 0.000154 0.000474 0.000144 0.000447 0.000136 0 5 10 0.002712 0.000861 0.002647 0.000811 0.002633 0.000801 0.002626 0.000797 0.002620 0.000796 0.002613 0.000795 0.002606 0.000794 0.002606 0.000794 0.002590 0.000794 1c (1/ mm 2 ) */l h 3n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.001098 0.000334 0.000778 0.000236 0.000635 0.000192 0.000550 0.000167 0.000492 0.000149 0.000449 0.000136 0.000415 0.000126 0.000388 0.000118 0.000366 0.000111 0 5 10 0.001817 0.000578 0.001766 0.000541 0.001757 0.000534 0.001753 0.000532 0.001751 0.000531 0.001748 0.000530 0.001746 0.000530 0.001744 0.000529 0.001741 0.000529 1c (1/ mm 2 ) */l h 4n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.000949 0.000289 0.000673 0.000204 0.000550 0.000167 0.000476 0.000144 0.000426 0.000129 0.000389 0.000118 0.000360 0.000109 0.000337 0.000102 0.000317 0.000096 0 5 10 0.001373 0.000438 0.001326 0.000407 0.001318 0.000401 0.001316 0.000399 0.001314 0.000398 0.001313 0.000397 0.001312 0.000397 0.001311 0.000397 0.001309 0.000397 1c (1/ mm 2 ) */l h 5n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.000847 0.000258 0.000602 0.000183 0.000492 0.000149 0.000426 0.000129 0.000381 0.000115 0.000348 0.000105 0.000322 0.000098 0.000301 0.000091 0.000284 0.000087 0 5 10 0.001111 0.000355 0.001062 0.000326 0.001055 0.000321 0.001053 0.000319 0.001052 0.000318 0.001051 0.000318 0.001050 0.000318 0.001050 0.000317 0.001049 0.000317 1c (1/ mm 2 ) */l h 6n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.000772 0.000215 0.000549 0.000167 0.000449 0.000136 0.000389 0.000118 0.000348 0.000105 0.000317 0.000096 0.000294 0.000089 0.000275 0.000083 0.000259 0.000079 0 5 10 0.000941 0.000300 0.000886 0.000272 0.000880 0.000267 0.000878 0.000266 0.000877 0.000265 0.000876 0.000265 0.000876 0.000265 0.000875 0.000265 0.000875 0.000265 1c (1/ mm 2 ) */l h 7n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.000713 0.000218 0.000508 0.000154 0.000415 0.000126 0.000360 0.000109 0.000322 0.000098 0.000294 0.000089 0.000272 0.000082 0.000254 0.000846 0.000240 0.000073 0 5 10 0.000826 0.000263 0.000761 0.000234 0.000754 0.000229 0.000752 0.000228 0.000751 0.000227 0.000751 0.000227 0.000751 0.000227 0.000750 0.000227 0.000750 0.000227 1c (1/ mm 2 ) */l h 8n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.000666 0.000204 0.000474 0.000144 0.000388 0.000118 0.000337 0.000102 0.000301 0.000091 0.000275 0.000083 0.000254 0.000078 0.000238 0.000072 0.000224 0.000069 0 5 10 0.000744 0.000236 0.000668 0.000205 0.000661 0.000201 0.000658 0.000199 0.000658 0.000199 0.000657 0.000199 0.000657 0.000198 0.000657 0.000198 0.000656 0.000198 1c (1/ mm 2 ) */l h 9n 1n 2n 3n 4n 5n 6n 7n 8n 9n 0.925925 5 10 0.000627 0.000193 0.000447 0.000136 0.000366 0.000111 0.000317 0.000096 0.000284 0.000087 0.000259 0.000079 0.000240 0.000073 0.000224 0.000069 0.000212 0.000064 0 5 10 0.000684 0.000215 0.000596 0.000183 0.000588 0.000179 0.000586 0.000177 0.000585 0.000177 0.000584 0.000176 0.000584 0.000176 0.000584 0.000176 0.000584 0.000176 advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 95 fig. 2 1n vs. nr for *=/ 5l h fig. 3 1n vs. nr for * 1/ = 0l h fig. 4 1n vs. t for *=/ 5l h fig. 5 1n vs. nr for * 1/ = 0l h finally, the natural frequency mn values (unit 1/s) vs. nr and t of free vibration ( t =0) according to mode shape numbers m=1 and n (from 1 to 9) for the sus304/si3n4 fgm thick circular cylindrical shells are calculated. figs. (2)-(3) show the values of 1n vs. nr in fgm circular cylindrical shells for thick */l h = 5, 10 respectively, with the effects of varied k and 1c = 0.925925/mm 2 under 300t k . generally the values of 1n are decreasing with values of n (from 1 to 9) for */l h = 5, nr = 0.5, 1 and 10. the greatest value of 11 = 0.00191 (unit 1/s) is found for */l h = 5. the values of 1n are also decreasing with values of n (from 1 to 9) for */l h = 10, nr = 0.5, 1 and 10. figs. 4-5 show the values of 1n vs. t in fgm circular cylindrical shells for thick */l h =5, 10 respectively, under the effects of varied k , 1c = 0.925925/mm 2 and nr = 0.5. generally the values of 1n are decreasing with values of n (from 1 to 9) for */l h = 5, 300t k , 600k and 1000k, the values of 1n are almost in the same for 300t k and 600k, but in greater values than that in the 1000t k . the greatest value of 11 = 0.00191 (unit 1/s) is found for */l h = 5, 600t k . the values of 1n can stand for higher temperature 1000t k at */l h = 5. the values of 1n are decreasing with values of n (from 1 to 9) for */l h = 10, 300t k , 600k and 1000k , the values of 1n are almost in the same for 300t k and 600k, but in greater values than that in the 1000t k . the greatest value of 11 = 0.00059 (unit 1/s) is found for */l h = 10, 600t k . the values of 1n can stand for higher temperature 1000t k at */l h = 10. the values of 1n at */l h = 5 are also found in the greater values than that at */l h = 10. 5. conclusions the values of natural frequency and frequency parameters are calculated and obtained by using the simply homogeneous equation with the polynomial equation in fifth-order of mn in the free vibration of thick fgm circular cylindrical shells. the advances in technology innovation, vol. 5, no. 2, 2020, pp. 84-97 96 three items of value effects are considered in nonlinear coefficient term 1c , shear correction coefficient and environment temperature. some of the important results are found as follows. 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[25] h. chen, a. wang, y. hao, and w. zhang, “free vibration of fgm sandwich doubly-curved shallow shell based on a new shear deformation theory with stretching effects,” composite structures, vol.179, pp. 50-60, 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 efficient rsu selection approaches for load balancing in vehicular ad hoc networks chi-fu huang * , jyun-hao jhang department of computer science and information engineering, national chung-cheng university, chiayi, taiwan received 12 april 2019; received in revised form 23 april 2019; accepted 04 august 2019 doi: https://doi.org/10.46604/aiti.2020.4080 abstract due to advances in wireless communication technologies, wireless transmissions gradually replace traditional wired data transmissions. in recent years, vehicles on the move can also enjoy the convenience of wireless communication technologies by assisting each other in message exchange and form an interconnecting network, namely vehicular ad hoc networks (vanets). in a vanet, each vehicle is capable of communicating with nearby vehicles and accessing information provided by the network. there are two basic communication models in vanets, v2v and v2i. vehicles equipped with wireless transceiver can communicate with other vehicles (v2v) or roadside units (rsus) (v2i). rsus acting as gateways are entry points to the internet for vehicles. naturally, vehicles tend to choose nearby rsus as serving gateways. however, due to uneven density distribution and high mobility nature of vehicles, load imbalance of rsus can happen. in this paper, we study the rsu load-balancing problem and propose two solutions. in the first solution, the whole network is divided into sub-regions based on rsus’ locations. a rsu provides internet access for vehicles in its sub-region and the boundaries between sub-regions change dynamically to adopt to load migration. in the second solution, vehicles choose their serving rsus distributedly by taking their future trajectories and rsus’ loading information into considerations. from simulation results, the proposed methods can improve packet delivery ratio, packet delay, and load balance among rsus. keywords: vanet, rsu, load balance, routing 1. introduction vehicular ad hoc networks (vanets) [1-2] attract a lot of attention in recent years due to lots of potential applications [3-5]. a vanet consists of many highly mobile vehicles. each vehicle is able to communicate with nearby vehicles and share information through the network. vanets can be regards as a particular type of traditional mobile ad-hoc networks (manets). many technologies of vanets inherit from manets, such as multi-hop relays and routing protocols. however, vanets have some different characteristics. the moving paths and speeds are constrained by the pre-existing road map. taking vehicles’ speeds and moving directions into considerations can predict the future positions of vehicles. besides, we usually assume vehicles have no energy constraint. there are two basic communication models in vanets [6], vehicle-to-infrastructure (v2i), and vehicle-to-vehicle (v2v), as shown in fig 1. v2i communication relies on fixed infrastructures, such as roadside units (rsus), to communicate vehicles. rsus connect to each other through a wired network and form a backbone network. rsus also act as gateways, which are entry points to the internet for vehicles. because of huge deployment and maintenance cost, it is nearly impossible to * corresponding author. e-mail address: cfhuang@cs.ccu.edu.tw tel.: +886-5-2720411; fax: +886-5-2720859 advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 57 deploy a large amount of rsus such that each vehicle can directly connect to a rsu. to extend the service ranges of rsus, vehicles utilize v2v communication to connect to rsus. in v2v communication, vehicles form a self-organized network without any centralized system. vehicles communicate with each other directly and achieve long-distance communications through multi-hop relays to connect to rsus. with rsus sparsely deployed, a critical issue is how vehicles establish routing paths to delivery their packets to/from rsus [7]. traditional routing protocols of manets are not suitable for vanets due to high mobility of vehicles and consequent control overhead. geographic routing [8] is suitable for vanets due to its low control overhead. the main idea of geographic routing is to choose the vehicle geographically closest to the destination as the next hop to relay packets. naumove et al. [9] proposed the advanced greedy forwarding (agf) algorithm and preferred group broadcasting algorithm (pgb) to improve gpsr performance in vanet. context-aware routing (car) [10] based on agf and pgb could find a route that maximizes the chance of successful delivery. in gytar [11], data packets are forwarded through the selected intersections by a greedy carry-and-forward scheme.. fig. 1 basic communication models in vanets vehicles tend to choose nearby rsus as their entry points to internet. the distance between a vehicle and its servicing gateway affects network performance significantly. the longer distance can result in a higher end-to-end delay and a lower packet delivery ratio. how to deploy rsus becomes a critical issue [12]. intersections are good places to deploy rsus. because when approaching an intersection, vehicles decelerate, which increases the connection time between vehicles and rsus. other criterions to deploy rsus include the area with high vehicular density is preferred, and the distances between any two rsus should be large enough. however, the vehicular density varies from time to time due to the high mobility nature of vehicles. if each vehicle connect to its closet rsu, it is possible that some rsus are overloaded but some are idle. such load imbalance among rsus can prevent the network from fully utilizing rsus’ bandwidths [13-15]. in this paper, we study how to balance the loads of rsus providing internet access for vehicles in an urban environment. there are serval criteria in our design. first, current and future loads of rsus are primary concerns when choosing a serving rsu. second, we should not ask a vehicle to choose a faraway rsu as its serving gateway, even if the rsu is with a very light load. third, the length of routing path between a vehicle and its serving rsu changes as the vehicle moves. therefore, a vehicle should consider its future trajectory when choosing a serving rsu. in this paper, we first propose a rsu-based method, which divides the whole map into several sub-regions. there is only one rsu residences in each sub-region to provide internet access service for all vehicles in its sub-region. the boundaries between sub-regions change dynamically to react to load migrations of rsus. this centralized method is inspired by the cell breathing for wlan [16], which adjusts the beacon transmission range of access points (aps) to balance the loads of aps. to be more scalable, we proposed a distributed vehicle-based method, which allows vehicles choose their serving rsu distributedly. we design a criterion for vehicles to advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 58 choose their service rsus based on their future locations, which can prevent vehicles from changing their serving rsus frequently. the main contributions of this paper are listed as follows. 1. we design two methods to balance the loads among rsus for different scenarios. the simulation results shows that both our methods can balance the loads among rsus. 2. with simulation verifications, both of our rsu-based and vehicle-based methods can improve the packet delivery ratio and the end-to-end delay. it is because an overloaded rsu increases the average queuing delay. in the worst case, the rsu may need to drop packets from its queue. 3. the proposed vehicle-based method considers both the driving directions and the future locations of vehicles, which can prevent vehicles from changing their serving rsus frequently. 4. we assist vehicles to choose a suitable rsu with vehicular density, load conditions of rsus, and routing length to improve the overall network performance. the rest of this paper is organized as follows. section 2 presents the system model and define the load-balancing rsu selection problem. in section 3, we describes the proposed methods. section 4 demonstrates the efficiency of the proposed methods through simulations. section 5 discusses the future works and concludes this paper. 2. system model and problem definition in an urban environment, there are n intersections and p road segments. we assume there are total m rsus deployed at a portion of n intersections to provide internet access for vehicles, where n m . to formulate the problem, we translate the city map into a graph g (v, e) as shown in fig. 2, where v is the set of intersections, v’ is the set of intersections with rsu deployed, and e is the set of road segments. for each edge e in e, there is a weight representing its traffic density. except the distance, there are several concerns need to be address when choosing a serving rsu. first, the queuing delay of packets increases as the load of a rsu increases. therefore, the load index ( il ) of rsu i is an important factor to be considered, where li is the ratio of the remaining bandwidth to the total bandwidth of rsu i. second, due to the finite queue length of a rsu, an overloading rsu increases the packet dropping rate. third, a vehicle should take its driving direction and future position into consideration in addition to its current position. otherwise, a vehicle will change its serving rsu frequently. fig. 2 the city map translates into a graph g (v, e) balancing the loads among rsus is important. it can improve not only the packet queuing delay but also the packet delivery ratio for vehicles. we call the problem of how to assign each vehicle to a suitable serving rsu as the load-balancing advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 59 rsu selection (lbrs) problem. to evaluate how balance we can achieve, a load-balance index (lbi) of the whole network is defined as {li {li} l 1 m {li} max min bi ,where i . max     (1) the value of lbi is between 0 and 1. a lower lbi implies a more balanced condition. note that, even if a method can minimize lbi value but assign vehicles to distancing rsus, it cannot be a good solution. it would increase the end-to-end delay and decrease delivery ratio. therefore, our goal is to assign each vehicle to a serving rsu such that the lbi of the whole network as small as possible without violating the principle of distance criteria. 3. the proposed rsu-based and vehicle-based schemes in this section, two types of schemes, called rsu-based and vehicle-based schemes, are presented to solve the lbrs problem. the rsu-based schemes divides the urban environment into m non-overlapped cells according to the number of rsus. only one rsu residences in a cell to provide internet access service for vehicles in this cell. boundaries between cells define the service ranges of rsus and change dynamically to balance the loads among rsus. in vehicle-based scheme, vehicles choose their serving rsu according to the load index, trajectories, and path lengths to rsus, independently and distributedly. 3.1. rsu-based mechanism in a vanet, due to high mobility of vehicles and the rapidly changing topology, a long delivery path based on multi-hop relays from a vehicle to a rsu may disconnect frequently. to choose a near gateway, we utilize voronoi diagram [16] to partition the network and define the serving ranges of rsus. given a plane and a set a of sits on the plane, the voronoi diagram partitions the plane into numerous cells such that each cell contains exactly one site, denoted as s , in a. the cell contains all points that are closer to s than to any other site in a. in this paper, sites in a are rsus and points are vehicles driving on the roads. we utilize the voronoi diagram to partition the city map into m cells, and each cell contains exactly one rsu. besides, vehicles driving on the roads assist each other in packet forwarding from vehicles to rsus. the distribution of road segments and their lengths are the factors to be concerned, rather than a plane and the euclidian distance. fig. 3 an example of the map-based voronoi diagram resulted from fig. 2 a map-based voronoi diagram considering a city map rather than a plane works as follows. we modify the partition algorithm of the voronoi diagram. instead of the perpendicular bisectors, we find the midpoints of the shortest paths between each pair of rsus. the network is then partitioned by connecting those midpoints. an example is shown in fig. 3. a vehicle in a cell will chooses the rsu in the same cell as its serving gateway, and change to another rsu when driving into another cell. notice that vehicles will not change their serving rsu before their session ends. advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 60 next, we further take the load indexes of rsus and vehicular densities of road segments into consideration. the boundaries between rsus adjust dynamically to adapt to loads and densities changes. to distinguish from the above method, we call this method as the weighted map-based voronoi diagram. we make the following modifications. first, we consider the weighted road lengths by the vehicular density of a load segment, instead of the actual lengths. next, when calculating a midpoint, we select the point where the weighted path lengths from the point to two rsus are inversely proportional to their load indexes. rsus calculates the boundaries periodically to maintain the load balance among rsus. the last boundary information is disseminated to vehicles by geocast. once a vehicle receives an updated boundaries information, it selects its serving rsu accordingly. 3.2. vehicle -based mechanism in this type of solution, vehicles utilize their future trajectories and the last load indexes of rsus to choose their serving gateways distributedly. we call this scheme as the trajectory-based scheme since trajectories of vehicles play a major role in the design. compared to the previous methods, there are no clear boundaries defining the serving ranges of rsus. moreover, this solution does not need the density information of road segments, since each vehicle select its rsu individually. fig. 4 a vehicle samples its future trajectory with intersections to calculate a favor value of each rsu in this scheme, vehicles obtain the load index information from rsus by geocast periodically. vehicles are aware of their future trajectories, which can be acquired from the gps navigation system. intersections on a vehicle’s trajectory are selected as representative points, as shown in fig. 4. the path lengths from each representative point i to a nearby rsu j are estimated and denoted as  d i, j . an exponential decay function  h i is used to decay the influences of distancing intersections. then, the vehicle calculates a favor value jf for each rsu j as,     0 1 d l j n ii f h i i, j       (2) where 0 , 1   . a vehicle selects the rsu with the largest favor value as its serving rsu. when a vehicle receives new load indexes of rsus or arrives at a new intersection, the vehicle calculate the favor values of all rsus to decide the best serving rsu. as mention above, vehicle will not change its serving rsu before its current session ends. moreover, we use a predefined threshold to prevent a vehicle from changing its’ serving rsu frequently to avoid the ping-pong effect. 4. simulation results we develope simulations to compare the network performance of the proposed schemes. the simulations adopte a 6 * 6 grid network in a 6 km * 6 km area where the length of each segment is 1 km. there are 6 rsus randomly deployed on different intersections. we generate 300 vehicles and the trajectory of each vehicle is the shortest path between a random advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 61 source and destination intersections. communication ranges of vehicles and rsus are the same, which is 350 m. to test heterogeneity and homogeneity of rsus, we set rsus with different bandwidths to the internet, randomly between 5 ~ 20 mbps in case 1 and equally 10 mbps in case 2. fig. 5 packet delivery ratio with different request rates fig. 6 end to end delay with different request rates we first compare the performance of the delivery ratio among voronoi diagram, map-based voronoi diagram, weighted map-based voronoi diagram, and the distributed trajectory-based method. the results are shown in fig. 5. it illustrates the average successful packet delivery ratio among different request rates from source vehicles to a destination rsus. at a low bit rate, the weighted map-based voronoi diagram and the trajectory-based method have a lower delivery ratio due to the longer routing length. however, when the request bit rate increases, the delivery ratio of voronoi diagram and map-based voronoi diagram decrease fast because some rsus are over-loaded and dropping packets from their queues. our proposed methods can relieve the problem of packet dropping and achieve better load balance. as shown in fig 6, we compare the end-to-end delay of packets. in a low traffic condition, both of weighted map-based voronoi diagram and the trajectory-based methods have a longer transmission delay resulted from choosing a farer serving rsu. however, when the request rate increases, both methods can benefit from the shorter queuing delay and reduce the overall end-to-end delay. in the following experiments, we evaluate the load balance effects of the proposed methods in homogeneous and heterogeneous rsu bandwidth settings. as shown in fig. 7, both of weighted map-based voronoi diagram and the trajectory-based methods can relieve the load unbalance problem among rsus. the weighted map-based voronoi diagram method needs to monitor the load information of all rsus and make the decisions of serving range of each rsu in a central server. therefore, it is reasonable that it can achieve a better load-balanced status than trajectory-based method. from fig. 8, we find that some rsus are overloaded when the request bit rate increases; however, our weighted map-based voronoi diagram and the trajectory-based methods can eliminate this problem. (a) heterogeneous bandwidths (case 1) (b) homogeneous bandwidths (case 2) fig. 7 the load balance index with different bandwidth settings of rsus advances in technology innovation, vol. 5, no. 1, 2020, pp. 56-63 62 (a) heterogeneous bandwidths (case 1) (b) homogeneous bandwidths (case 2) fig. 8 the maximum load index among rsus with different bandwidth settings of rsus 5. conclusions and future works in this paper, we discuss the load unbalancing problem among rsus in vanets resulted from the uneven distribution of vehicles and heterogeneity of rsus. then, we proposed two schemes to solve the problem from different aspects. the first one is a centralized rsu-based method, and the second one is a distributed vehicle-based method. both of the proposed methods can balance the loads among rsus and improve the overall packet delivery ratio and latency. in the weighted map-based voronoi diagram, we divides the map into several cells and take the routing length, vehicular density, load indexes of rsus into considerations. this centralized solution can balance the loads among rsus better than the distributed method. however, it needs the vehicular density information and vehicles may change their serving rsu more frequently. therefore, we propose a scalable distributed solution, called trajectory-based method, without the demand of the vehicular density information. moreover, it considers the future locations of vehicles when choosing serving rsu. as a result, it can prevent vehicles from changing their serving rsu frequently. in the future, we tend to use the historical records of vehicular density in a day to analysis the expected delivery ratio and delay to replace the routing length in the current design. in addition, we want to design a reservation mechanism. we will utilize the future trajectory of vehicles to calculate the suitable future serving rsu and reserve bandwidth. this may be able to achieve a better quality of service of vehicles and meanwhile maintain load balancing among rsus. acknowledgement the study is sponsored by minister of science and technology, taiwan under grant no. most 107-2221-e-194-015. references [1] f. cunha, l. villas, a. boukerche, g. maia, a. viana, r. a. f. mini, and a. a. f. loureiro, “data communication in vanets: protocols, applications and challenges,” ad hoc networks, vol. 44, pp. 90-103, july 2016. 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[17] f. aurenhammer, “voronoi diagrams: a survey of a fundamental geometric data structure,” acm computing survey, vol. 23, no. 3, pp. 345-405, september 1991. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 4___aiti#7988_in press_20211213 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 determination of natural frequency and critical velocity of inclined pipe conveying fluid under thermal effect by using integral transform technique jabbar hussein mohmmed * , mauwafak ali tawfik, qasim abbas atiyah department of mechanical engineering, university of technology, baghdad, iraq received 28 june 2021; received in revised form 02 september 2021; accepted 03 september 2021 doi: https://doi.org/10.46604/aiti.2021.7988 abstract this study proposes an analytical solution of natural frequencies for an inclined fixed supported euler-bernoulli pipe containing the flowing fluid subjected to thermal loads. the integral transform technique is employed to obtain the spatial displacement-time domain response of the pipe-fluid system. then, a closed-form analytical expression is presented. the effects of various geometric and system parameters on the vibration characteristics of pipe-fluid system with different flow velocities are discussed. the results illustrate that the proposed analytical solution agrees with the solutions achieved in previous works. the proposed model predicts that the pipe loses the stability by divergence with the increasing flow velocity. it is evident that the influences of inclination angle and temperature variation are dramatically increased at a higher aspect ratio. additionally, it is demonstrated that the temperature variation becomes a more harmful effect than the internal fluid velocity on the stability of the pipe at elevated temperature. keywords: pipe conveying fluid, natural frequency, critical flow velocity, finite fourier sine transform, laplace transform 1. introduction fluid-conveying pipes are very important parts in many engineering structures and have many potential applications in industry. practical applications include chemical plants, nuclear reactors, oil and gas industries, heat exchangers, fuel lines of transportations, monitoring and controlling tubes, marine risers, and so on. other applications in engineering devices involve jet pumps, some kinds of valves and parts of hydraulic machinery, and submarine systems, etc. hemodynamics and the pulmonary and urinary systems also may be including some applications of the pipes conveying fluid [1-2]. the function of these pipes is very important and can be considered the blood circulation of human body. the fluid flowing inside these pipes influences the dynamic behaviors of the piping systems, which play a significant role in the stability and the performance of the systems. the influences of the fluid and structure interaction usually lead to the vibration of the pipe and even the rupture of the pipe. thus, a convenient knowledge of the dynamic behavior of these types of systems is essential and has motivated many scholars over the last six decades. extensive investigations have been executed on the vibration analysis of the fluid-conveying pipes subjected to various end and loading conditions. the first correct motion equation of the structure-fluid coupling vibration for a pipe containing flowing fluid was proposed by housner [3]. thereafter, the vibration characteristics of pipe-fluid system have been increasingly studied by several other scholars. stein and tobriner [4] discovered that the internal pressure of flowing fluid has inverse effect on the natural frequency of the system. païdoussis [5] further investigated the dynamic behavior of conservative system, predicting that the system may be undergoing the flexural oscillatory instability by divergence at a certain high flow speed, and that at higher flow speed the system can be subjected to coupled-mode flutter. plaut and huseyin [6], hatfield et al. [7], and lesmez et al. [8] further analyzed the plain and u-bend piping systems. * corresponding author. e-mail address:10493@uotechnology.edu.iq tel.: +9647805886894 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 nowadays, with the existence of larger pipeline systems, the demand for inclined pipes have been grown due to their special conditions, and it is therefore worthy being concerned about. moreover, these pipes can be possessed various aspect ratios of length to external diameter. a better understanding of the influence of the aspect ratio and inclination angle on the dynamic behavior of a pipe is very essential to design thin components in different industries. additionally, when the pipes are designed and analyzed, it is very important to take account of the working conditions which can affect the dynamic behavior and integrity of such components. one of the important examples of such operating conditions is the temperature variation, which is undergone during the conveyance of fluid in pipes. the pipes in such cases suffer the compressive stresses resulting from the thermal effect in addition to those generated by the fluid flowing through the pipe. such pipes can experience buckling and show the complicated dynamical behavior related to their divergence even at a very low internal flow velocity of fluid [9]. consequently, temperature is one of the main concerns among other factors and operating conditions in designing slender structures like the pipeline systems containing flowing fluid. recently, qian et al. [9] studied the effects of both linear and non-linear stress-temperature cases on the stability of pipe containing flowing fluid. zhao et al. [10] investigated the stability of the simply supported pipes induced by pulsating fluid velocity and thermal loading. kukla [11] studied the temperature distribution and lateral vibration of beam induced by external heating source. blandino and thornton [12] performed a study about the vibration characteristic of an internally heated beam. alfosail et al. [13] numerically evaluated the dynamic behavior of inclined risers. gan et al. [14] investigated the stability of an inclined cantilevered pipe containing flowing fluid. yang and wang [15] analyzed the dynamic behavior of an inclined beam induced by moving loads. from the literature review, it is observed that no previous works have been reported on the response of pipes due to a combination effect of internal fluid, inclination angle, aspect ratio, and thermal loads. furthermore, it is noted that most of the above-mentioned analyses have been based on numerical or approximate approaches in tackling linear and non-linear dynamics issues of these slender structures. this approximation is valid only for small values of the applied loads and self-weight. it has been found that there are quite a few articles that use analytical approaches to analyze the dynamic problems of the pipes conveying fluid. an analytical solution is very important for the improvements and verifications of effective applied numerical simulation tools. to address the lack of research in this aspect, the analytic solution based on integral transform technique (itt) approach (via the combination of finite fourier sine and laplace transforms) is adopted in this work to analyze the dynamic behavior of an inclined and doubly fixed supported pipe subjected to the thermal loads. firstly, the frequency-domain response of the pipe conveying fluid is obtained. then, the corresponding inverse transforms on the displacement frequency-domain responses of the pipe are conducted to obtain the spatial displacement time-domain responses. moreover, the effects of changing the aspect ratio, inclination angle, and temperature variation on the natural frequencies, as well as the critical velocities of the pipes conveying fluid under different fluid speeds are evaluated. this work is structured as follows. section 1 introduces the problem under study. section 2 presents the methods used to solve motion equations. section 3 provides the model description and solution procedure of governing equations. in section 4, results are analyzed and discussed. finally, the paper ends in section 5 with the summary and conclusions of the current work. 2. methods 2.1. laplace transform laplace transform is a linear transform that is widely applied in the dynamic problems of structure. it provides easy and powerful means to transform partial differential equations into ordinary differential equations, or transform ordinary differential equations into integral form equations, which make them much easier to be solved. laplace transform directly obtains the solution of differential equations with certain boundary values without determining the general solution first 42 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 [16-17]. many successful applications of laplace transform were done to study the dynamic behavior of the components with and without external forces [18-19]. assume that �(�) is a real function of time t, which is defined in the real domain [0, +∞), the laplace transform and its inversion are defined by: ( ) ( ) ( )0 [ ] st s t tl f f e dtψ ∞ −= = ∫ (1) 1 ( ) ( ) ( ) 1 [ ] 2 i st t s si f l e ds i ε ε ψ ψ π + ∞− − ∞ = = ∫ (2) where l is laplace transform, l −1 is the inverse laplace transform, s represents a complex number in the laplace domain, and si (i = 1, 2, 3, …) are the singularities of �(�). 2.2. finite fourier sine transform the fourier transform method was utilized into the field of structural dynamics by many researchers [20-21]. fourier transform is helpful in solving the differential and partial differential equations of non-periodic functions. it can be applied to solve some boundary-value and initial-value problems for partial differential equations. fourier transform is usually used in order to reduce the order of differential equations. it can be employed to convert the infinite degree of freedom systems into a superimposed double or single degree of freedom system. the finite sine fourier transform for a function of �(�), which is a real function of coordinate x in space (0 ≤ x ≤ l), can be represented as follows [22]. 1 ( ) ( ) ( )0 [ ] sins x x nf f f n xdx fπ= =∫ (3) ( ) ( ) 1 ( ) 1 [ ] 2 sin n xs n n f f f n x fπ∞− == =∑ (4) where �� is fourier transform, �� is the inverse fourier transform, and n is an integer. 3. model description 3.1. governing equation the system considered in the present investigation comprises a linear elastic, clamped ends, and the inclined pipes made of polypropylene-random (pp-r) material with total length (l), inner and outer diameter (di and do), thickness (t), cross-sectional area (ap), mass per unit length (mp), young’s modulus (e), and moment of inertia (i). the fluid passing through the pipe has a mass per unit length mf with an axial internal fluid flowing velocity υ. a represents the cross-sectional area of the flow and is assumed to be a constant. the fluid has no compression properties and has no viscosity. unlike the discrete systems (simple or torsional), the continuous systems, like pipe or beam, possess an infinite number of degrees of freedom that make them more difficult to be treated. hence, many assumptions were made to simplify the working process with these systems [23-24]. figs. 1 and 2 present the geometry and cartesian coordinate system, assuming that the origin of the (x, y, z) framework is placed in the space at the left end of the pipe. the properties of pipe and fluid and the numeric parameters considered in this study are presented in table 1. the current study focuses on finding the natural frequencies and critical velocities of axial flow fluid-carrying pipes under different conditions. since the non-planar motion (three-dimensional motion) does not affect the values of the natural frequencies or critical velocities, it is neglected and the planar motion (two-dimensional motion) of the pipes is adopted. fig. 3 illustrates the fluid and pipe elements, and shows all the forces acting on the system. 43 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 table 1 numeric values of used parameters specification value material pp-r fluid water outer diameter do (m) 0.025 inner diameter di (m) 0.018 thickness t (m) 0.0035 length l (m) 0.5-1.25 aspect ratio (length to outer diameter) l/do (20-50) do modulus of elasticity e (gpa) 0.8 at 25°c 0.38 at 50°c 0.23 at 70°c density of pipe ρp (kg/m 3 ) 909 density of fluid ρf (kg/m 3 ) 1000 coefficient of expansion α (1/k) 0.3 × 10 -4 fig. 1 three-dimension geometry of the clamped-end pipeline fig. 2 schematic of the clamped-end inclined pipe (a) fluid element (b) pipe element fig. 3 free-body diagram of the fluid and pipe element to simplify the derivation process, some assumptions are adopted: considering the vertical motion (y-axis) of the pipe; ignoring internal damping (viscoelastic effect), dissipation, external tension, and internal pressurization; assuming a small deformation; treating the pipe as an euler-bernoulli beam model. then, using the newtonian method by balancing forces on 44 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 the fluid and pipe elements in the transverse and longitudinal directions, and after some substitutions processes and mathematical calculations, the following motion equation of the heated and inclined pipe can be derived (more details about the assumptions and derivation process can be found in the work of mohmmed et al. [25]): ( )( ) ( ) ( ) ( ) 4 2 2 2 2 4 2 2 2 2 2 2 sin sin cos 2 0 f p f f p f p f f p y y y y y ei m m l x g m v n m m g m m g x x x x x y y m v m m x t t θ θ θ∂ ∂ ∂ ∂ ∂− + − + + + + + + ∂ ∂ ∂ ∂ ∂ ∂ ∂+ + + = ∂ ∂ ∂ (5) where ei is the flexural rigidity of the pipe; g is gravitational constant; θ is the inclination angle of the pipe with horizontal axis; qs represents internal shear stress; p is internal fluid pressure; s is the internal perimeter (internal section circumference) of the pipe; f is the transverse force between pipe wall and fluid (per unit length); t represents longitudinal tension. m is bending moment; q represents the transverse shear force in the pipe; y(x, t) is the lateral displacement of the pipe; x and t are the axial coordinate and time, respectively. n represents the thermal load in the pipe due to temperature variation and can be calculated as: n = αeap∆t, where α is thermal expansion coefficient (1/°c) and l is pipe length (m). ∆t = (tpt)x − ti is the temperature change (°c). ti is the initial temperature of the pipe (°c). (tpt)x is the instantaneous temperature of the pipe after the time (°c). the terms of eq. (5) can be described as follows: the first component represents the acceleration resulting from the restoring force, and the second and third components represent the accelerations due to the gravity force and the centrifugal force respectively. after that, the forth component associates with the acceleration due to the thermal force caused by the temperatures variation, then the fifth and sixth components illustrate the static force because of the gravity effect. the seventh component stands for the acceleration due to the coriolis forces, following the acceleration because of the system’s inertia force. rearranging eq. (5) gives: ( )( ) ( ) ( ) ( ) 4 2 2 2 4 2 2 2 sin sin cos 2 0 p p pf f f f f pf y y y y ei m m l x g n m v m m g m m g m v x x tx x y m m t θ θ θ    ∂ ∂ ∂ ∂− + − − − + + + + + ∂ ∂ ∂∂ ∂ ∂+ + = ∂ (6) eq. (6) can be rewritten in non-dimensional form as follows: ( ) 4 2 2 2 2 1 2 4 2 2 1 sin sin cos 2 0g n u g g u t t φ φ φ φ φ ζ θ θ θ β ζ ζ ζ ζ ∂ ∂ ∂ ∂ ∂ − − − − + + + + = ∂ ∂ ∂ ∂ ∂ ∂    (7) where y l φ = (8) x l ζ = (9) f f p m m m β = + (10) ( ) 3 m m gl g ei + = (11) 1 2 f m u vl ei =       (12) 45 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 1 2 2 1 f p ei t l m m = +       (13) 2 nl n ei = (14) ( ) 2 1/ 2 1 sin sin 2 cosg n u g u gφ ζ θ φ θφ β φ φ θ′′′′ ′′ ′ ′− − − − + + + = −   ɺ ɺɺ (15) 3.2. solution procedure in order to discrete eq. (15) and transform it to an ordinary differential equation, the term η(ζ, τ) is used to decompose the equation into space and time as follows: ( ) ( ) ( ), t tφ ζ ζ= γ λ (16) where λ(�̅) the generalized coordinate of the system and γ(ζ) is a trial/comparison function satisfying both the geometrical and natural boundary conditions. the pipe end boundary conditions considered in the current study is clamped-clamped support, which can be symbolized as c-c. the boundary conditions at the edges can be expressed as: clamped (ζ = 0) clamped (ζ = 1), c-c at ζ = 0, γ = 0, and �γ/�ζ = 0; at ζ = 1, γ = 0, and �γ/�ζ = 0. substituting eq. (16) into eq. (15) gives: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )2 1 21 sin sin 2 cos t g n u t g t u t t g ζ ζ θ ζ θ ζ β ζ ζ θ  ′′′′ ′′ ′ ′γ λ − − − − γ λ + γ λ + γ λ + γ λ  = − ɺ ɺɺ (17) to solve eq. (17), itts are used in this work. first, based on eq. (1), by assuming zero initial conditions case, laplace transform is introduced to suppress the time dependency. ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )2 1 2 2 1 sin sin 2 cos s g n u s g us s s s g s ζ ζ θ ζ θ ζ β ζ ζ θ ′′′′ ′′ ′ ′γ λ − − − − γ λ + γ + γ λ + γ λ = −    (18) next, for reducing the difficulty of solving eq. (18), a finite fourier sine transform is introduced to convert the infinite degree of freedom pipe-fluid system into a superimposed double degrees of freedom system. thus, by using eq. (3), finite fourier sine transform with regard to spatial (space) coordinate γ is conducted on eq. (18), and the following equation can be obtained: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 1 1 1 2 0 0 0 1 1 1 1 2 2 0 0 0 1 0 sin sin sin sin sin sin sin 2 sin sin cos 1 sin s n d g n u s n d g s n d g s n d us s n d s s n d g n d s ζ πζ ζ θ ζ πζ ζ θ ζ ζ πζ ζ θ ζ πζ ζ β ζ πζ ζ ζ πζ ζ θ πζ ζ ′′′′ ′′ ′′λ γ − − − λ γ + λ ⋅ γ ′ ′+ λ γ + λ γ + λ γ = − ∫ ∫ ∫ ∫ ∫ ∫ ∫ (19) γ(ζ) is beam eigen function and varies according to boundary condition for the clamped supported case: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )cosh l cos l cosh cos [ sinh sin ] sinh l sin l r r r r r r r r λ λ ζ λ ζ λ ζ λ ζ λ ζ λ λ − γ = − − − −       (20) 46 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )sinh l sin l cosh cos [ sinh sin ] cosh l cos l r r r r r r r r λ λ ζ λ ζ λ ζ λ ζ λ ζ λ λ + γ = − − − −       (21) where ��is the root of the equation cosh(��l) cos(��l). the using of terms included in eq. (20) or (21) for fixed support may contain some difficulty and complexity in determining the integral transformation for each term in eq. (19). thus, for simplification, a polynomial function can be applied for this type of support system: ( ) 2 3 4 0 1 2 3 4 a a a a aζ ζ ζ ζ ζγ = + + + + (22) applying the boundary conditions of c-c gives: ( ) ( )4 3 2 4 2 aζ ζ ζ ζγ = − + (23) using orthogonal functions gives: ( )4 5 4 3 2 1 3 70 70 315 540 420 126 a a a a a a− + − + =       (24) by substituting � = 1 in eq. (21), �� = 25.20 can be obtained for the first mode. by substituting eq. (23) in eq. (19), performing the integral transformation, and reorganizing and combining similar terms, the following equation is yielded: ( ) ( ) ( ){ }{ } ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 1 5 5 12 1 2 2 3 3 1 3 3 1 11 3 3 3 3 1 1 3 3 3 3 24 [1 1 ] 12 24 2 [1 1 ] [1 1 ] 1 [1 1 ] 2 24 242 [1 1 ] [1 1 ][1 1 ] sin 24 2 1 12 [1 1 ] [1 2 1 ] [1 1 ] n n n n n nn n n n n n s s u n u n n n n n nn g n n n π β π π π π π ππ θ π π π + + + + ++ + + + − − + + − + + − − + + − + − − + − ++ − − + −+ − + − + + + −                         ( ) ( ) 4 1 cos .1 s g f a s θ λ = −                              (25) where ( ) ( ) ( ) 1 1 0 [1 1 ] 1 sin 1 n n d f n πζ ζ π ++ − = =∫ (26) eq. (25) can be simplified by assuming: ( )( )1 2 1 3 3 12 2 1 1 n f z u n β π = + −     (27) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 1 11 3 3 3 3 1 2 2 1 1 3 3 3 3 2 24 242 [1 1 ] [1 1 ][1 1 ] 24 [1 1 ] sin 24 2 1 12 [1 1 ] [1 2 1 ] [1 1 ] n nn n f n n n n n n nn z n u g n n n n π π ππ θ π π π π + ++ + + + + − − + − ++ − − = + − − + + −+ − + − + + + −                         (28) 47 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 ( ) ( ){ }{ } ( ) ( )1 12 1 25 5 3 3 4 24 1 1 [1 1 ] [1 1 ] cos .1 n n f f g s z s z s f n n a s θ π π + +∴ + − − + − + + λ = − (29) additionally, the following equations can be assumed: ( ) ( ) 1 1 1 1 5 5 3 3 24 1 [1 1 ] [1 1 ] f f n n z n n ϕ π π + + = + − − + − (30) ( ) ( ) 22 1 1 5 5 3 3 24 1 [1 1 ] [1 1 ] f f n n z n n ϕ π π + + = + − − + − (31) ( ) ( ) ( ) ( ) 4 1 1 5 5 3 3 2 2 1 1 cos .1 24 1 [1 1 ] [1 1 ] n n f f g f a s n n s s s θ π π ϕ ϕ + + − + − − + − ∴ λ = + + (32) by applying the fourier-laplace inversion, the spatial displacement time-domain response (dynamic response !) for the inclined fixed supported pipe conveying fluid can be given: ( ) ( ) ( ) 4 4 4 2 2 cos .f , 24 2 f g t t a n n θ φ ζ ζ π π − = γ −      (33) ( ) ( ) ( )2 1 1 2 1 2 1 2 2 1 1 1 f f f f f f f f f f f f t t t e e α αα α α α α α α α − − = + − −       (34) 2 1 12 1 2 4 f f f f i ϕ ϕ α ϕ= + − (35) 2 1 12 2 2 4 f f f f i ϕ ϕ α ϕ= − − (36) by isolating characteristic equations, the dimensionless fundamental natural frequency (ωn) and its complimentary value (ωm) are: 2 2 2 1 1 12 2 2 2 4 4 f f f n f n f ϕ ϕ ϕ ω ϕ ω ϕ= − ⇒ = −           ∓ (37) 2 m f ω ϕ= − (38) the fundamental natural frequency ωn is adopted in this work. the aforementioned equations are solved for each value of variables by using matlab 2019b software program to determine the fundamental natural frequency of the system. the simplified flow chart is illustrated in fig. 4. 48 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 fig. 4 the flowchart for matlab code 4. results and discussion 4.1. validation of analytical model to validate the analytical calculation method proposed in this work, the fundamental natural frequency is calculated at stationary fluid case (u = 0) and at fluid velocities u = 0.5, u = 1, and u = 1.5, respectively, and compared with those in the work of ni et al. [26] and liang et al. [27]. table 2 presents the geometry and material properties used in this comparison, and lists the obtained results. it is clear from table 3 that the relative errors between the results in current study and those in refs. [26-27] are less than 2.46%. these little differences may be attributed to the using of different models in the two references. in refs. [26-27], the pipe is modeled according to timoshenko theory; in the current work the euler-bernoulli beam is adopted. it can be concluded from this comparison that the applied integral transform method (via the combination of the finite fourier sine transform and laplace transform) gives quite reliable results provided that the fluid flow velocity is moderate. table 2 parameters of pipe and fluid young’s modulus pipe size pipe length pipe density fluid density 210 gpa do = 324 mm 32 m 8200 kg/m 3 908.2 kg/m 3 di = 292 mm table 3 comparison of dimensionless natural frequency of the fixed supported pipe with different fluid velocities frequency fluid velocity current value ref. [26] relative error % ref. [27] relative error % ωn ωn ωn u = 0 22.3087 22.2597 0.22 22.42 0.49 u = 0.5 22.2534 22.0910 0.73 22.27 0.07 u = 1 22.0864 21.9224 0.74 22.11 0.10 u = 1.5 21.8053 21.4165 1.81 21.28 2.46 4.2. natural frequency in the current study, the natural frequency and stability of an elastic, inclined, and doubly fixed supported pipe conveying a newtonian and incompressible fluid at different temperature are investigated. the natural frequencies of the pipe are analytically calculated based on eq. (37). the values of the system parameters used to obtain the results are listed in table 1. to connect the subcritical, critical, and post-critical vibratory behaviors, the continuity profile of the real and imaginary components of pipe-fluid system’s natural frequencies (instead of separated profile as widely observed in the literature) is adopted in this study by plotting the natural frequencies in absolute values against the internal flow velocity. start input constants g, ρf, ρp, di, do, ti, and α define variables v, l/do, θ, (tpt)x, and t calculate the parameters a, ap, mf, mp, and i define the parameters e, n, a4, and n calculate the dimensionless parameters β, g, "#, and �̅ set the interval of ζ find the terms $% , $%&, !% , and !% & find the natural frequency '( plot the results print output end 49 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 the natural frequency of the pipe-fluid system is demonstrated in figs. 5-9. two zones are identified by observing the profile of fundamental natural frequency with respect to the influence of flow speed in figs. 5 and 8; where the two zones illustrate the divergence case when the flow is lower and higher than the critical points of flow. in general, the results show that the fundamental natural frequency of the system is affected by factors such as fluid velocity, and tends to reduce as the velocity of fluid flowing within the pipe increases. with the increasing fluid velocity, the fundamental natural frequency of the pipe vanishes, and then the divergence instability happens. the corresponding fluid velocity, at which the fundamental natural frequency vanishes, is named critical velocity. this is because the increase of the velocity of fluid flowing inside the pipe leads to the weakness of the pipe stiffness. almost similar conclusions in the subcritical fluid velocity range (1st zone) were observed in the work of ni et al. [26] and in the supercritical regime (2nd zone) in the work of adelaja [28] and olunloyo et al. [29], while for the whole spectrum results the same trend was found in the work of plaut [30]. fig. 5 presents the effect of different aspect ratio (length to diameter ratio) on the natural frequency. it is clear that the natural frequencies of the fluid-conveying pipe decrease with the increase of length to diameter ratio. similarly, the critical fluid velocity decreases with the increase of the aspect ratio. this suggests that the pipe-fluid system will hastily reach divergence instability situation with higher aspect ratio. the reason is that the higher length to diameter ratio leads to the increase of the pipe weight resulting in the weakness of its stuffiness. the same trend was observed in the work of liang [27] and olunloyo et al. [31] with the increase of the pipe length. meanwhile, by observing fig. 5, it is evident that the level of reduction in the magnitude of natural frequencies and critical velocity for the same aspect ratio reduces with the increase of the support angle. at the same time, by observing fig. 5, it is clear that the level of reduction in the value of the natural frequency and critical velocity decreases for the same aspect ratio with the increase of the inclination angle. (a) ) = 0° (b) ) = 15° (c) ) = 30° fig. 5 the natural frequency value versus fluid velocity with different aspect ratios for the case of t = 25°c and n = 1 50 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 the effect of the pipe’s inclination angle and aspect ratio on the fundamental natural frequency of the structure is studied further in figs. 6 and 7 respectively. in general, the results indicate the increase of natural frequencies with the increase of the inclination angle. in addition, it can be observed that the enhancement in the natural frequency values is larger at higher aspect ratio. for example, the natural frequency value increases approximately by 0.18% (from 23.104 for θ = 0° to 23.146 for θ = 60°) at aspect ratio = 20 while its value increases by 5.2% (from 22.223 for θ = 0° to 23.380 for θ = 60°) at aspect ratio = 50. additionally, the results in fig. 7 show an interesting phenomenon. when the aspect ratio equals 50 and the inclination angle is in the range of 40-90, the influence of the inclination angle on the fundamental natural frequencies becomes higher than the influence of the aspect ratio on the fundamental natural frequencies, i.e., the increase of inclination angle compensates the loss in natural frequency value due to the increase of aspect ratio. also, it can be observed from fig. 7 that the natural frequency of the pipe has an increasing trend up to the inclination angle of θ = 90° and a reverse trend afterward, i.e., beyond the angle 90° the behavior is reflected. this can be explained as follows: for an inclined pipe, the gravitational force generated by the weight of the pipe and the fluid is divided into two components, the lateral component and the axial component relative to the pipe axes. when the angle of inclination of the pipe is * 90,, the axial component exerts a tensile force on the pipe, which increases with the increase of the inclination angle of the pipe and the aspect ratio. this in turn reduces the impact of the lateral component, responsible for the occurrence of the lateral displacement of the pipe, and thus increases natural frequencies of the inclined pipe. on the contrary, as the pipe’s inclination angle ) 90, , the axial component gradually decreases and the lateral component becomes larger with the increase of the inclination angle which causes the natural frequency become lower and eventually same as the horizontal case. (a) l/d = 20 (b) l/d = 30 (c) l/d = 50 fig. 6 the natural frequency value versus internal fluid velocity with different inclination angles and aspect ratios for the case of t = 25°c and n = 1 51 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 fig. 7 the natural frequency value versus inclination angle with different aspect ratios for the case of t = 25°c, u = 1, and n = 1 fig. 8 describes the effect of the temperature variation on the fundamental natural frequency and the critical velocity of the pipe conveying fluid for different aspect ratios. the results reveal that the temperature variation has a great influence on the fundamental natural frequencies and the critical velocity. here, as temperature increases, a significant reduction in fundamental natural frequency and critical velocity is observed. thus, the temperature variations have a softening effect on the pipe stiffness, which is consistent with the work of ashley et al. [32] where the natural frequency was found to be inversely proportional to the temperature and with the work of orolu et al. [33] where the critical velocity reduces with the increase of temperature. also, it is noted that the temperature effect on the fundamental natural frequency and the critical velocity of the pipe conveying fluid is considerably growing at higher aspect ratio. for example, the natural frequency and critical velocity reduce from “23.23 and 7.46” to “22.89 and 7.35” respectively at l/d = 20, while the lowering is from “23.2 and 7.38” to “4.55 and 0.09” respectively at l/d = 50. it can be inferred from these results that the pipe may be losing their stability even with zero fluid velocity with the increasing temperature. this suggests that the temperature effect becomes more essential parameter, for engineers and designers, than the velocity of fluid flowing inside the pipe at higher aspect ratio as designing the pipelines systems. the temperature effect on natural frequencies is further examined by plotting in fig. 9 the variation of the fundamental natural frequencies with the pipe’s inclination angle for different temperatures. the curves in fig. 9 manifest that when the variation in the pipe temperature is slight, the change of the inclination angle has very little effect on the fundamental natural frequency. however, as the pipe temperature increases, the influence of inclination angle becomes more noticeable. (a) l/d = 20 fig. 8 the natural frequency value versus fluid velocity with different temperatures and aspect ratios for the case of θ = 0° and n = 1 52 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 (b) l/d = 30 (c) l/d = 50 fig. 8 the natural frequency value versus fluid velocity with different temperatures and aspect ratios for the case of θ = 0° and n = 1 (continued) fig. 9 the natural frequency value versus pipe’s inclination angle with different temperatures for the case of u = 1, n = 1, and l/d = 50 5. summary and conclusions the itt for natural frequency and dynamic response computation of pp-r pipe containing incompressible flowing fluid is proposed in this article. the euler-bernoulli beam model is applied to obtain the transverse vibration of the pipe containing flowing fluid. the closed-form analytical expression used to calculate both natural frequency and overall dynamic of the fixed supported pipe containing flowing fluid is derived based on the combination of finite fourier sine and laplace transforms and their inverse transform. the effect of various parameters (internal flow velocity, aspect ratio, inclination angle, and temperature variation) on the vibration characteristic of the pipe conveying fluid is presented. the comparison of the numerical results of natural frequency at different internal fluid velocity with the results in published references is conducted and shows a good agreement. the results reveal that the fundamental natural frequency of the pipe containing flowing fluid reduces as the internal flow velocity increases. once the fundamental natural frequency reduces to zero, the divergence instability happens. the findings of the current study can be summarized as follows: (1) the proposed analytical method has a clear concept, suitable for hand computation, and gives a theoretical basis for more engineering applications of the inclined fixed supported pipe conveying fluid under thermal loads. (2) the aspect ratio, temperature variation, and inclination angle strongly affect both the natural frequency and critical velocity of the system. 53 advances in technology innovation, vol. 7, no. 1, 2022, pp. 41-55 (3) there is a strong coupling between the aspect ratio of pipe length to its outside diameter with temperature variation and inclination angle. (4) the temperature variation is a major concern rather than the internal fluid velocity in the design of the pipe containing flowing fluid at higher aspect ratio. (5) the inclination angle has larger impact on vibration characteristics at higher aspect ratio, which should be paid attention in engineering. (6) the natural frequency and critical velocity of the pipe-fluid system decrease while its dynamic deflection increases with the increase of temperature. the divergence can occur even when the fluid velocity equals zero with the increasing temperature of the pipe. 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[33] k. o. orolu, t. a. fashanu, and a. a. oyediran, “cusp bifurcation of slightly curved tensioned pipe conveying hot pressurized fluid,” journal of vibration and control, vol. 25, no. 5, pp. 1109-1121, march 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 55 6___aiti#8504___143-154 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 low access latency and high throughput for full-duplex cognitive radio using mobility caching placement strategy madhunala srilatha 1,*, anantha bharathi 2 1 department of electronics and communication engineering, vardhaman college of engineering, hyderabad, india 2 department of electronics and communication engineering, university college of engineering, osmania university, hyderabad, india received 18 september 2021; received in revised form 11 november 2021; accepted 12 november 2021 doi: https://doi.org/10.46604/2022.8504 abstract in a remote framework, the densely allotted radio range is not effectively utilized by an authorized primary user, which limits a secondary user to avoid disturbance to a primary user while utilizing a channel. to solve the shortage problem of accessible range, this study proposes a mobility caching placement strategy (mcps) based sliding window scheme to optimize the latency and throughput of cognitive radio system. the performance parameters of the proposed system are analyzed using energy detection metrics by considering full-duplex communication. by the matlab analysis and the evaluation with and without self-interference suppression, the results demonstrate that the entrance inactivity of the mcps based sliding window is diminished by a factor of 1.9 as contrasted with the existing full-duplex systems. with the improved latency and throughput, the proposed method can avoid the ruinous impacts of drawn-out self-residual suppression more effectively compared to the existing approaches. keywords: full-duplex cognitive radio, latency, mobility caching placement strategy, self-residual suppression 1. introduction one of the biggest difficulties in remote framework today is the shortage of accessible range, which can be resolved by using one of the best multiple access schemes, i.e., non-orthogonal multiple access (noma) [1]. nonetheless, ongoing investigations have demonstrated that while the radio range is thickly allotted, it is frequently not intensely involved or utilized by an authorized primary user (pu) [2]. a recurrence coordinated cognitive radio (cr) system is proposed to exploit this circumstance while permitting an unlicensed secondary user (su) to entrepreneurially reuse authorized recurrence groups without creating interference to the authorized user. one of the major necessities of such a framework is that su ought not to produce destructive obstruction to pu [3-4]. therefore, su’s handset must be equipped for detecting the radio channel to decide whether pu is available or not by checking various performance parameters [5]. for range re-utilization, it requires low-inertness medium access for high-need users or high-need transmission. in this framework, a low latency-sensitive continuous transmission requires to be on hold for a split second as pu powerfully gets to the channel for getting its pressing message over. such situations are of specific significance for the ongoing administration, for example, virtual/increased reality and independent vehicles. therefore, it is required to get a latency of less than 1 msec to meet the forthcoming 5g systems [6]. javed et al. [7] have given various methods to sense the pu spectrum with its pros and cons. framework models that intermittently stop the su transmission to detect the channel have been broadly proposed to recognize the beginning of the pu transmission and given various performance parameters’ comparison. these methodologies present visually impaired interims, where the su framework is transmitting and becomes incapable of recognizing the beginning of the pu * corresponding author. e-mail address: ma_srilatha2@yahoo.co.in tel.: +91-9290885384 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 transmission. diminishing the interim between progressive detecting spaces will decrease the proficiency and throughput of the su framework; however, this will enhance its range detecting abilities. to solve this problem, khalid et al. [8] and singh et al. [9] described the use of a full-duplex scheme that senses the spectrum and transmits the data simultaneously, and alves et al. [10] provides protection to the user’s spectrum. irio et al. [11] and gaspard et al. [12] developed a method to expand the throughput of remote correspondence framework, where the remote terminal is permitted to transmit and sense at the same time in the same recurrence band. the throughput can also be increased by increasing the detection probability [13]. tiwari et al. [14] proposed a cooperative medium access control (mac) protocol called mlcp, which improves the throughput even more by enabling simultaneous transmission of pu and su. kumar et al. [15] proposed a clustering algorithm along with an energy efficient power allocation scheme due to which huge improvement in throughput is achieved. however, sustaining the improvement under imperfect self-interference cancellation is not addressed. mokhtarzadeh et al. [16] proposed a method to increase throughput for a full-duplex cr system. previous research has analyzed the exchange of detection which requires further improvement to detect proficiency. the best way to enhance the identification of pu is by utilizing full-duplex cr under self-residual suppression (srs), which senses the channel for every �� test. this makes high access inertness as pu may begin the transmission whenever possible and can identify the nearness of pu more rapidly. ayesha et al. [17] and ayesha et al. [18] have described the alternative approaches of simultaneously sensing and transmission, using srs for improving the trade-off between sensing the spectrum and su throughput. however, the faultless srs cannot be achieved below the noise floor. in the existing work, the performance analysis of spectrum sensing is done by using various schemes and protocols, e.g., multi-objective modified grey wolf optimization algorithm [19], noma network under power splitting based simultaneous wireless information and power transfer (swipt) [20], noma based mobile edge computing with imperfect channel state information (csi) [21], decode-and-forward (df) and amplify-and-forward (af) techniques in noma based cognitive radio network (crn) [22], signal segmentation [23], neural network based multilayer perception model [24], and the channel allocation scheme based on greedy algorithm [25]. cache technology is used to even improve the performance of parameters of spectrum sensing which includes various strategies: cache capacity allocation, cache replacement, cache utilization, and cache placement [26]. in the work of zheng et al. [27] and xia et al. [28], the performance improvement of parameters is analyzed including energy consumption optimization, system transmission performance, and latency. in this study, a mobility caching placement strategy (mcps) based sliding window scheme is proposed. this method significantly reduces access latency for the full-duplex system under srs to protect pu. additionally, it improves the su throughput which maximizes the data transmission. this study emphasizes the issue of compromising the performance parameters of spectrum sensing (such as throughput and access latency) in the full-duplex cr under srs. with different schemes, e.g., half-duplex, full-duplex using slotted window, and full-duplex using sliding window, the performance of parameters is evaluated with and without srs. to optimize the sensing parameters, a mcps based sliding window is proposed. compared to the existing methods, the proposed method will exchange more information bits by taking decisions based on each sample, resulting in a quick detection of pu, in turn lowering the latency, and improving the su throughput. the study is organized as follows. the system model and frame structure of the existing methods and the proposed method is described in section 2. in section 3, the mcps based sliding window scheme is discussed. the performance analysis of latency and throughput is analyzed in section 4. analytical and simulation results are presented in section 5. finally, section 6 concludes the study. 2. system model while su is using the spectrum of pu, no interference in the pu network should occur. to ensure this, su needs to accurately identify the white spaces for the transmission and should vacate and opt for the subsequent band when pu appears. the 144 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 first scenario is considered hypothesis h1. when pu is using the spectrum, the signal received at su is expressed in eq. (1). the second scenario is considered hypothesis h0. while pu is not using the spectrum, the received signal can be expressed in eq. (2). ( ) ( ) ( )s n x n u n= + (1) ( ) ( )s n u n= (2) in the above equation, ���� is the signal which needs to be identified, ���� is the gaussian noise which is additive white in nature, and n is the sample index. the parameters of performance using detection algorithm will be analyzed based on two probabilities: the detection probability (pd) with hypothesis h1 for identifying the presence of licensed user activity and the false alarm probability (pf) with hypothesis h0 for detecting the licensed user when the licensed user is actually not present. pu is effectively protected when the probability of detection is high. in another scenario, su can use the frequency band recurrently when the false alarm probability is low and is available. to guarantee better performance of the system, the detection probability shall be as much as possible, and the false alarm probability shall be as minimum as possible. cr system schemes are half-duplex and full-duplex, which are addressed in this section. the presence of detection of pu is done by using a metric m, which is compared with a given threshold � for both schemes. pu is present if �, otherwise pu is absent and su can use the channel. energy detection is the frequently used metric for sensing the spectrum [29]. ( ) 2 1 1 sn ns m s n n = = ∑ (3) where ���� is the su received signal. if the pu information is known prior, other detection methods can be used. using decision metric, the detection probability pd and the false alarm probability pf can be evaluated with the help of a hypothesis test [7]. ( )0/rf p p m h= > γ (4) ( )1/rd p p m h= < γ (5) the cr system frame structure is shown in fig. 1. initially, the cr system has to sense the spectrum and determine the status of pu. if the frequency band of pu is detected as idle, then the su transmitter will make use of the band to transmit information to the su receiver for the frame duration. if pu starts transmission, then su has to cease its transmission, to avoid interference to pu. again, in the next frame, su will access the frequency band and the process repeats. fig. 1 frame structure of cr system under srs 145 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 2.1. half-duplex cr system in this scheme, spectrum sensing has to be scheduled sequentially with transmission, as shown in fig. 2. the frame contains two parts: � �� sample window for transmission and �� sample window for sensing the frequency band. �� samples are used to know the status of pu using eq. (1) and thus decisions will be made for every � sample. it is clear that under the half-duplex scheme, su has to cease the transmission each time the spectrum sensing is established, which leads to the higher access latency of pu and the reduction of su throughput by a factor of ���� � . fig. 2 frame structure of half-duplex cr system 2.2. simultaneous detection and transmission with slotted window scheme the frame structure of simultaneous detection and transmission with a slotted window using srs is shown in fig. 3 [16]. it contains a single frame, in which both the sensing and transmission will be performed simultaneously to lead to the improvement in detection probability and the decisions made for every ��. in this scheme, as there is no separate sensing slot, the su throughput will not reduce, and su can detect the status of pu immediately which leads to a reduction of latency. fig. 3 frame structure of slotted window full-duplex cr system 2.3. sliding window scheme for simultaneous detection and transmission the frame structure of simultaneous detection and transmission with a sliding window using srs is shown in fig. 4, where the decisions will be made for every sample compared to the slotted window (for every ��). this scheme can be actualized effortlessly in computerized equipment employing a first-in first-out (fifo) cushion. it is imperative to take a note that progressive choice measurements are not free as just a single new sample is included (and one is expelled). fig. 4 frame structure of sliding window full-duplex cr system 2.4. quadrature phase shift keying the major advantages of digital modulation techniques are the improved capacity to transmit huge data with high immunity and the easy detection of its distinct transmission state at the receiver in a noisy medium. while converting analogue signals to digital signals, a trade-off is always made due to the loss of some information in the quantization process. proper selection of the digital modulation technique is crucial especially when the bandwidth and time slots are limited in 146 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 uplink-downlink transmission. the efficacy of a modulation technique is restrained in terms of its bandwidth and power efficiency. the capability of a modulation technique in accommodating data within a limited bandwidth is regarded as bandwidth efficiency whereas the ability to preserve the bit error probability of the digital message at low power levels is treated as the power efficiency of a modulation technique. with regards to the digital modulation schemes, for the same number of bits transmitted and received, binary phase shift keying (bpsk) modulation has less bit error rate and bandwidth for different values of signal-to-noise ratio (snr), as compared to binary amplitude shift keying (bask) and binary frequency shift keying (bfsk) modulation. to detect the message at the output, minimum snr and low bit error rate with higher performance is required. with low power consumption, bpsk modulation technique provides the best performance even for less snr. bandwidth can be saved even more in m-ary phase shift keying (m-psk) modulation schemes by maintaining symbol rate constantly and increasing the number of bits per symbol. for example, in quadrature phase shift keying (qpsk), one of the 4 possible phase shifts per symbol can be transmitted rather than transmitting only 2 possible phase shifts so that 2 bits per symbol (i.e., for the same bandwidth with twice the information) can be transmitted [30]. also, with the same energy efficiency, one can achieve double spectral efficiency. higher compound m-psk modulation schemes can also be possible (8-psk, 32psk, 64psk, etc.) to transmit more bits per symbol and in turn achieve higher bit rate. however, this employs higher vulnerability to noise as the symbols together get the closer and increased bit errors. in order to make a trade-off between bit rate and probability of error, qpsk is opted in the proposed system. 3. mcps based sliding window scheme caching techniques are attracted expressively since they can decrease backhaul traffic and also improve performance metrics. caching placement strategies can be of uncoded or coded type. both are used for optimizing the performance of parameters. the mcps scheme allows decisions to be taken on a multiple sample transfer at a time and increases the concurrent transmission and sensing using intra interference suppression, which checks the presence of pu continuously in a spectrum band and gives a perfect position. the operation of mcps is shown in fig. 5 and the flowchart is shown in fig. 6. the number of input samples and coding rate is calculated by considering snr, number of symbols present at the transmitter, and threshold value using eqs. (6) and (7). ( ) ( )1 ..... 2 x bs bsn r snr n snr n= × × + + (6) / ( 10 )txsnr n i r h thr n= × + × (7) where n represents the number of samples, h is the analysis of h equation, snr represents the signal-to-noise ratio, rx is the receiver, thr represents the threshold value, ri represents the coding rate, and ntx represents the number of symbols at the transmitter. a signal is passed through the qpsk modulator, then the modulated data is analyzed, processed using eqs. (8)-(10), and then transmitted through the channel. ( ) ( ) ( ) ( )1 i bs bs i ipq r w l n k w l n r k = × − × × × − ×φ φ (8) ( ) ( ) bs tx w l ipq w l n r = × × (9) 147 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 ( ) ( )ipq w s w l ifft= × (10) where ���� represents the phase of the signal, ���� is the line width, ipq represents the quadrature input, rtx represents the random information at transmitter, and ��s� is the sample width. parameter optimization is done by using eqs. (11)-(17). ( ) ( ) ( ) ( ) 2 s i tx txt bs bs w l qp np c r n n j w l r w l n= × × × − × × × × (11) ( ) ( ) ( ) ( )itt r w s qp ifft qp r w l = × × (12) ( ) ( ) tx t tsqp r m qp conj qp w s = × ×  ∑ (13) ( ) ( )( )v p txt r t r p q max qp conj qp r = × −   (14) ( )( ) ( ) ( ) tx tsrn t r r m qp conj qp w s = × −∑ (15) sqp srn m m gain = (16) ( )1010 logmse gain= × (17) fig. 5 operation of mcps fig. 6 flowchart of mcps 148 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 4. performance analysis 4.1. analysis of latency and throughput in mcps based sliding window the impact of detecting time on the throughput is examined in this section. in each edge of the frame structure span tf, su starts sensing the channel for a period of sensing time (��), and if the channel is free (which indicates pu is not using the channel), then su utilizes the channel (spectrum) for information transmission. on the other hand, if pu wants to use the channel, then su has to evacuate the channel and use another channel that is free for transmission without creating interference to pu. if the length of the corresponding edge of pu is tprf, then the throughput of su that could be transmitted when pu is not utilizing the spectrum is tprf + tf. the throughput (th) of su is given by: ( )1sf cf f t t th p p t −= − (18) at the point, when pu has an exponential on-off movement display, with the mean spans of “on” period signified by β, then pc is given by: exp prf f c t t p       += − β (19) expecting that the casing of span tprf, tf, and false caution likelihood has been settled, then the standardized throughput of su is: ( )1 expsf prf f f f t t t t th p t       − += − − β (20) for the case of h0 (i.e., pu is available but wrongly detected), the probability density function (pdf) of the su received signal (s) is p0(x), and the probability of false alarms pf is: ( ) ( )0 0/fp p s h p x dx ∞ = > = ∫ ε ε (21) the detection threshold ɛ is calculated as: ( )2 1 1u f sq p f − ε = σ τ +  (22) on the other hand, when pu is using the channel (for the case of h1), the pdf of the su received signal (s) is p1(x), and the detection probability pd is: ( ) ( )1 1/dp s h p x dx ∞ = > = ∫ ε ε (23) the latency (l) of the system is calculated as: ( )         ∩∩ ++       ∩ +       += − c i cc i iccc ddd d pn dd d pn d d pndpnl 12121 3 3 1 2 211 ... ..... (24) where ni is the number of samples when pu begins with i th decision point, di denotes the event when pu is detected at i th decision once transmission starts, and ��� represents the complementary event when pu is not detected during i th decision. 149 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 4.2. algorithm the algorithm of mcps based on latency and throughput optimization is described in table 1, where the input parameters need to be specified first and then the eqs. (8)-(10) are analyzed. furthermore, the optimization of latency and throughput are calculated based on the analytical values. table 1 algorithm of mcps input: ��, ���, ���, ��, ��, � !, �!# output: return the estimated data in the qpsk domain [var] begin for i = 1 to $!�% &' &( j = 1 to $!�% &' &( )*ℎ,� , �. = ���0!,1!, ��, ��� for k = 1…………. $!�% &' using 8-10 in var �� parameter optimization learn (latency variance) δ3� update (var name) 43� using � → �� + 1� or �� 1� throughput = ∑ �9:�;:���3;:�� <=> �? = @(ab%ccd� ��efghi end 5. analytical and simulation results this section explains the analytical and simulation results of the proposed mcps technique under perfect srs and imperfect srs, as compared with the existing methods. simulation results show the improvement in performance parameters by using the proposed technique. simulation parameters of the mcps scheme are shown in table 2. table 2 simulation parameters parameter value channel length 128 number of bits 10 5 number of sub-carriers 128 number of transmitters 2 number of receivers 2 fast fourier transform size 64 sensing window size 16 5.1. perfect self-interference suppression fig. 7 depicts the substantial improvement of latency and throughput with the mcps based sliding full-duplex method compared to the existing methods under perfect srs. since half-duplex allows either sensing or transmission at a time and cannot perform both tasks at a time, the latency of this method is almost half of a su frame length and throughput is also very less. unlike half-duplex, the slotted full-duplex method allows both sensing and transmission at a time, and the latency of this method has been improved for a duration of ��/2 compared to half-duplex since, for each �� duration, there is a provision of taking decisions. as the decisions are taken for every sample, the sliding full-duplex method can detect the usage of the channel by pu quickly. furthermore, compared to the sliding full-duplex, the latency of mcps is improved by a factor of 0.98; compared to the slotted full-duplex, the mcps latency is improved by a factor of 3.7; compared to half-duplex, the mcps latency is improved by a factor of 20. fig. 8 illustrates the different quantiles of optimization parameter trade-off for the proposed mcps technique and the existing sliding and slotted techniques. the performance of parameters depends on self-residual, noise, and signal realizations. the results show the improvement of the proposed technique compared to the existing techniques. 150 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 fig. 7 latency versus throughput comparison for all the 4 methods under perfect srs fig. 8 quantiles of optimization parameter trade-off under perfect srs 5.2. imperfect self-interference suppression fig. 9 depicts latency improvement for mcps with an increase in srs, measured with respect to the noise floor which is calculated by considering throughput to 0.9. when compared with the existing methods, the slotted full-duplex method has higher latency for all values of self-interference, but the proposed method can withstand the improvement of self-interference by a 3.2 factor. fig. 10 depicts the throughput improvement for mcps with increasing srs. the mcps method has improved the throughput under the pu protection. table 3 shows the comparison of the parameters of the sliding full-duplex and mcps methods. fig. 9 latency versus srs fig. 10 throughput with increasing srs for the latency of 16 samples table 3 comparison of parameters parameters sliding window full-duplex mcps no. of transmitters (tx) 2 2 no. of receivers (rx) 2 2 channel length 64 up to 128 number of bits 10 4 10 5 channel size 52 52 max latency 0.90 0.79 throughput 0.78 0.89 error rate 0.44 0.42 snr 0.97 0.99 151 advances in technology innovation, vol. 7, no. 2, 2022, pp. 143-154 6. conclusions and future scope this study investigated cr from the point of view of ensuring the essential and high priority users under perfect srs and imperfect srs by diminishing the latency of the framework. by inferring systematic recipes for latency and throughput of the existing methods, the proposed method is beneficial in terms of its capacity to make choices at each sample. additionally, the results of simulation show that the proposed sensing framework can achieve a huge improvement in latency and throughput under srs, which is diminished by a factor of 1.9 contrasted with the current full-duplex system. the performance parameters can be further extended by using vehicular ad-hoc networks, which provide cooperation in cr and share the channel status while switching between the channels when pu exists. furthermore, the parameters can be extended by using a testbed that tests the performance and practicability of cr framework. list of acronyms noma non-orthogonal multiple access snr signal-to-noise ratio pu primary user bask binary amplitude shift keying su secondary user bfsk binary frequency shift keying cr cognitive radio m-psk m-ary phase shift keying mac medium access control rx receiver srs self-residual suppression ntx number of symbols at transmitter swipt simultaneous wireless information and power transfer qpsk quadrature phase shift keying csi channel state information ���� the phase of the signal df decode-and-forward ���� line width af amplify-and-forward ipq quadrature input crn cognitive radio network rtx random information at transmitter mcps mobility caching placement strategy ��s� sample width pd probability of detection mse mean square error pf probability of false alarm tf frame structure span fifo first-in first-out ɛ detection threshold bpsk binary phase shift keying th throughput of su �� sensing time β mean span of “on” period �� transmission time tprf length of the corresponding edge of pu ���� detected signal pdf probability density function ���� additive white gaussian noise l latency m decision metric ni number of samples at i th decision point � threshold di event when pu detected at i th decision ���� received signal ��� complimentary event when pu is not detected during i th decision n number of input samples conflicts of interest the authors declare no conflict of interest. references [1] a. kumar and k. kumar, “multiple access schemes for cognitive radio networks: a survey,” physical communication, vol. 38, 100953, february 2020. 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[30] n. fatima, s. a. siddiqui, and a. ahmad, “comparative performance analysis of digital modulation schemes with digital audio transmission through awgn channel,” international conference on power electronics, control, and automation, pp. 1-3, november 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 154  advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 an overview of own tracking wireless sensors with gsm-gps features hamed yassin-kassab, marius-corneliu rosu * applied electronics and information engineering, politehnica university of bucharest, romania received 27 september 2019; received in revised form 28 december 2019; accepted 20 january 2020 doi: https://doi.org/10.46604/aiti.2021.4793 abstract wireless sensors (ws) mobility and pause time have a major impact directly influencing the energy consumption. lifetime of a ws network (wsn) depends directly on the energy consumption, thus, the hardware and software components must be optimized for energy management. this study aims to combine a compact hardware architecture with a smart energy management efficiency in order to increase ratio lifetime/energy consumption, to improve the operating time on a portable tracking system with gps/gsm/gprs features and own power. in this paper we present the evolution of own ws tracking architecture with gps/gsm/gprs features, basic criterion being the lifetime combined with low power consumption. concern was focused on hardware and software areas: large number of physical components led to reconsideration of hardware architecture, while for software, we focused on algorithms able to reduce the number of bits in transmitted data packets, which help to reduce energy consumption. the results and conclusions show that the goal was achieved. keywords: ws, gps/gsm/gprs features, portable devices, operating lifetime/energy consumption 1. introduction a typical embedded system involves the following main features: sense, process and store, transmit, and power management as shown in fig. 1, while the first order radio energy consumption model is shown in fig. 2 [1-2]. since computers and software have made their presence in every component and as part of communication and automation, the structure described above has changed, and concern has materialized in both hardware and software direction. as electronic components manufacturing technology has evolved, specialized companies appeared in achieving their specific features dedicated to the purpose of use; thus, at least hardware designers can choose components with low noise and minimal power consumption. in the software part, the remote data transmission algorithm has focused on minimizing the number of usable bits for data packets, the next packet following will be transmitted or not, depending on the decision taken locally in the ws, so that the active transmission time would be shorter, which reduces the energy effort in the sensor. ideally, we want a network to have a long life and to operate unattended, but there are factors that limit the capacity of the power source. the issue of energy consumption has been divided into two different directions: first, a large number of efficient energy communication protocols have emerged, including mac protocols, routing and self-organizing, which take into account the particularities of wireless sensor networks (wsn). secondly, local dynamic power management (dpm) strategies are developed to detect and minimize the impact of inefficient activities on an individual node. 1.1. energy model description as already mentioned in the introduction, the model used for radio energy dissipation is shown in fig. 2 and, according with literature, it is a first order radio model [3-4]; the definitions used parameters are shown in table 1 [3]. * corresponding author. e-mail address: marius-corneliu.rosu@sdettib.pub.ro tel.: +4-0768-957-856 advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 48 fig. 1 typical embedded system fig. 2 energy dissipation model in radio transmission table 1 graph representations parameter definition unit eelec energy dissipated during transmission / reception 50 nj/bit εfs free transmitter amplifier model 10pj/bit/m 2 εmp multi-path model of the transmitter 0.0013pj/bit/m 4 k data length 2,000 bits d0 threshold for distance √𝜀𝑓𝑠/𝜀𝑚𝑝 m when k-bits message is transmitted over a distance a d, it will consume an amount of etx energy according with eq. (1) [5]: 0 4 0 , ( ) , s fs f 2 elec tx elec k e + k ε d if d < d e k,d = k e + k ε d if d d (1) and the erx energy needed to receive the transmitted message is given by relation eq. (2) [3] ( )rx elece k = k e (2) to forward this message, the amount of efx energy needed is given by expression eq. (3) [3], where d0 it is defined in table 1 and expresses the threshold for changing the amplification patterns. 0 4 0 , ( , ) ( , ) ( ) , fs fs 2 elec tx rxfx elec 2k e + k ε d if d < d e k d = e k d + e k = 2k e + k ε d if d d (3) 2. background and related work 2.1. background in this section we will briefly review the theories and technologies relevant to the subject of this paper. as autonomous devices, available energy and other resources are limited in size and cost, being directly dependent on the range of available energy (e.g. battery energy density or external energy capture devices); computational resources, storage and communication, all of these vary from one system to another. the design challenges for such ws devices and are illustrated in table 2. table 2 design challenge issues design issues determined factors dynamics of the network mobility of ws, target and sink for ws node location deterministic or ad-hoc inter-node communication direct or multi-hop communication data transfer models continue, event-triggered, on demand, hybrid data aggregation internal network (partial total) or network external tracking systems are a way to monitor, detect, and then notify users of certain activities. such systems use different types of technologies that are covered by the internet of things (iot). to determine the most accurate location of an object, the global positioning system (gps) represents the main technology for such purpose. advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 49 a gps tracking system involves three layers [6]: (1) space layer, composed of at least 24 geostationary satellites orbiting twice a day; (2) control layer, consisting of 5 stations across the globe, monitors and manages satellites by updating orbital data and clock correction. (3) user layer, consisting of all kinds of gps receivers; they have the ability to receive data from satellites. once the receiver sets its position with the gps satellites, the information is usually delivered in one of the following formats: 1. latitude and longitude and 2. universal transverse mercator (utm); gps receiver provides location and time information about any object anywhere, anytime, as long as the communication path is not obstructed by any obstacle. when ws is in contact with at least three satellites, two-dimensional position (latitude and longitude) is determined by triangulation method [7]; we must remember that the satellite emits a signal with a certain frequency. if four or more satellites are detected by our ws, then it is able to calculate the position in three dimensions: latitude, longitude and altitude; after that it is possible to calculate vehicle’s average speed and moving direction. gps technology has the following drawbacks [6-7]: (1) they consume large amounts of energy; (2) it is not efficient for indoor locations; (3) it needs a free line of sight for at least three satellites; (4) detects position approximately; (5) yield is weaker in crowded areas. however, simultaneously it is also necessary the access by mobile communication network gsm/gprs who made possible online tracking of the system; we make it clear that gps tracking uses the global satellite network, while gsm/gprs is the mobile communications terrestrial network. a clarification in this respect can be found by the reader in table 3 [8]. similar systems have been designed and built by researchers, tailored to the specific requirements and purpose pursued (e.g. in the health field). there are five major classes, generally accepted techniques for energy efficiency in ws, summarized in tables 4-5 and shows how each technique addresses energy-consuming processes. use of energy must be tightly controlled; energy efficiency means adapting the power cycle to the node's operating mode. table 3 comparation gps–gsm/gprs terms of comparison gps gprs semantics global positioning system general packet radio service scope it provides positioning services offers voice&data services for mobile telephony applications navigation, surveillance, mapping, gis, and others access on e-mail, multimedia messages, video calls, etc. operating communicates with a collection of satellites orbiting the earth. communicates with a terrestrial tower. minimum number of stations 3 1 use gps is used anywhere: sky, earth, water, etc. gprs limited range and available only on land. costs expensive economic advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 50 table 4 design challenge issues techniques description data reduction reducing the amount of produced, processed and transmitted data. examples: data compression and aggregation. reducing the protocols size (rps) goal: increase protocol efficiency by reducing overall costs. transmission periods, adapted to network stability or distance to the transmission source. examples: stratification approach or avalanche optimization of transmitted data. efficiency routing routing protocols must be developed so that the network life will grow by reducing energy transmission and avoid nodes with low residual energy. examples: opportunistic protocols taking advantage of node mobility; protocols using geographic coordinates of nodes; protocols that hierarchize nodes to simplify routing; protocols that send data only to nodes interested in avoiding unnecessary transmissions. cycle of service express the fraction of times when the nodes are active; active / inactive periods must be tailored to the application-specific requirements, which can be further subdivided. they are related to the medium access protocol. examples: 1. techniques centered on selecting active nodes in wsn; 2. techniques that perform the on / off mode of active node radios when communication involves the node. topology control adjusts transmission power, maintaining network connectivity; a low topology is created based on local information. table 5 techniques influence on wsn processes stage techniques sensing processing communication collision over-listening package control passive listening interference data reduction: major major secondary secondary secondary rps major secondary secondary major secondary efficiency routing major secondary major secondary major cycle of service major major major major secondary major major topology control major major major major 2.2. related work ws development has facilitated the emergence of increasingly diverse applications. however, the issue of energy and how to maximize the life of the network in a very limited budget of energy, are still the design priorities. as we have shown in table 4, five main classes are considered energy-consuming. next, there are mentioned the techniques that address the energy efficiency challenge in the literature, divided into the five classes corresponding to table 4; a brief reference will also be mentioned. a. regarding data reduction – literature proposals are divided into 3 main categories depending on the data processing stage: acquisition, processing, and communication. b. regarding protocols size – schemes to reduce the size of protocols and implicitly their costs, lead ultimately on saving the limited energy resources. c. regarding efficiency routing – raises problems with the design of routing protocols for a network; they seek load balancing, minimizing energy consumption for end-to-end transmission of a packet, avoiding low-energy nodes. d. regarding cycle of service – are techniques for planning activity alternating the active and inactive periods to turn off the radio subsystem whenever possible, and providing an operational network for application. e. regarding topology control algorithms – refers to building and maintaining a low topology that preserves energy while maintaining network connectivity and coverage as shown in [9]. there is an optimum distance transmission that minimizes energy dissipation while keeping a connected topology, as shown in [10]; methods presented in [11] are listed. in table 6 we made a brief review of data reduction solutions for earlier mentioned classes, as we have found in papers. advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 51 table 6 state of the art in energy consumption reduction main classes processing steps techniques achievements a data reduction data acquisition 1. based on sampling [12-15] 2. based on prediction in [16] centralized prediction; in [17] prediction is done by grouping sensors; in [18] describes the communication protocol with neighbors. data processing 1. data compression several techniques: command encoding; pipe-line or dis31bution compression, in [19]. 2. data aggregation categories: structure cluster cu protocols leach in [20-21], pegasis in [22]; structure tree with the algorithm appointed dctc in [23-24]; in [25] low cost tree; in [26] and in [27], based smt and mst. without structure, in [28] for dynamic events, or tod in [29], a scalable technique. data transmission they are related to data acquisition and processing techniques. main classes reduction method techniques achievements b protocols size through regular adaptive transmission 1. based on adaptation to network changes in [30], it is suggested to adapt the message period to network stability. in [31] trickle algorithm presents a more complex approach. 2. based on distance adaptation to the information source. in [32] basic idea is the concept fish eye and the period of transmission increases with distance from the source. by stratified optimization 1. top-down approach all techniques listed for sensors with limited resources were given in [33]. 2. the bottom-up approach 3. apps-centered approach 4. mac-centered approach 5. integrated approach by optimizing floods 1. based on multiple relocations it has been found to be more difficult to find for most graphs a set of minimally connected nodes [34]. 2. based on dominant domains (dd) in [35-37] a heuristic distribution is used, where a dominant set is originally built and then redundant nodes are removed. other authors, [38-39], use a leading node to assign a rank to each node. 3. based on neighborhood negotiations in [40], any data is described by a descriptor called metadata, which is unique and shorter than actual data. main classes reduction method techniques achievements c efficiency routing by data-driven protocols technology spin [40] directed diffusion technique (did) [22] technology cadr, cougar. [22] by hierarchical protocols technology leach [22] technology pegasis [22] technology teen [22] technology apteen [22] advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 52 table 6 state of the art in energy consumption reduction (continued) main classes reduction method techniques achievements c efficiency routing by geographic protocols technology gear [22] technology gaf [22] technology speed [20] by opportunistic protocols based on spatial and natural diversity. [41] based on mobility. variants based on router node mobility protocols are proposed in [42-45]. protocols based on mobile relays are in [46-48]. main classes reduction method techniques achievements d cycle of service high level granularity linear programming technique. [49-50] gaf technique [22] span technique [51-54] low level granularity based on “time division multiple access” (tdma) proposed in: [55]–trama; [56]-flama; [57]-flexitp; [58]-asap. based on “sensor media access control” (smac) variants: [59]-sync messages; [60]-smac; [61]-dmac; [62]-bmac. hybrid between tdma and “carrier sense multiple access” (csma) variants: [63]zmac; [64] protocol tdma/ca based on colors nodes provided by serena main classes reduction method techniques achievements e topology control algorithms directed lmst (dlmst) dlmst [11] directed rng (drng) drng [11] residual energy aware dynamic (read) read [11] on the other hand, researchers have developed systems with different design hardware, performing the same task. we focused on real-time detection for location and speed, and in addition, the vehicle temperature and to require the imposition of new features and constraints on the measured parameters. industry has developed around an ever-changing technology with a wide range of applications aimed at the environment, health systems, military and robotics, as we have shown in table 6. typically, such applications use a large number of nodes in a self-organizing multi-hop wsn, running on batteries and equipped with one or more sensors, as well as low power processors and transceivers. in this section we analyzed the main factors who contributes on reduction of wsn's autonomous operation time, the factors that influence the architecture of the networks, the energy problems that may occur and the state-of-the-art achievements in the field; we have also developed a classification of energy efficiency techniques by describing the algorithms that lead to the reduction of energy consumption which were synthesized in table 6. in addition, for a complete analysis of real-time tracking devices, we recommend to the interested readers to consult chapter3 from reference [65]. instead of conclusions: it is obvious that the domain is still open to researchers, the subject of consumption and limited resources over time being more present than ever. 3. hardware development a node consumes energy and most of it, with values between 60% and 80% [66-67], during communication. at the same time improving energy storage has an annual average growth rate of 6%, as stated in [68]. due to many constraints, the advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 53 complexity of nodes development is limited. depending on applications, nodes can be designed with enhanced local decision capacity or not. as we pointed out in the introduction, the paper presents the evolution of our own ws, with gps gsm/gprs features; the design and improvement criterion were the stand-alone operating time by reducing energy consumption. our focus is on both hardware and software sides, and figs. 3-5 show the evolution on the hardware enhancement component. as can be seen, the large number of physical components in fig. 3 led to a reconsideration in the design concept (see figs. 4 and 5). (a) gps side view (b) gsm/gprs side view fig. 3 first hardware solution the demand for choosing the electronic components in the following modules was reported in the energy consumption balance of the active components (see appendix 2 with datasheet reference). overall the entire hardware system, besides module from this work, includes the following units: (1) the mobile units specialized in “machine to machine’’ tracking; (2) the alarm station; (3) hardware systems to optimize energy consumption and battery charge that ensures autonomy of ws; (4) hardware analysis and filtering systems for analogue and/or digital signals. the module is based on the dual gps-gsm/gprs connection, and performs remote positioning and target monitoring via sms or internet; it has statistical features for mileage, detection and alarm when power is interrupted, as well as other customizable features. external interfaces make it possible to connect a radio frequency identifier (rfid), to a serial port, a fuel sensor, an led display, etc. the modules in this paper have been modified for improved performance particularly energy consumption and thus increase autonomy in operation. however, they need to be explained as follows: fig. 3 shows the first prototype, made on double front wiring, one dedicated to gps communications (fig. 3(a)), the other side to gsm communications (fig. 3(b)). as a result of increasing number of simultaneous surveillance and different manufacturers for gps and gsm modems (gps-u-blox, gsm-huawei, cpu-philips), rewriting of the programs in modules according to the adaptations needed for the transmission and reception was not fully compatible and satisfactorily, optimization and technical compatibility not being 100% possible at that time. in addition to this variant we didn’t take into account the optimization of the data transmission, the main requirement being the stability of the transmission and its non-stop maintenance. in an analysis of the total energy consumption, we found that it exceeded 250ma / h, which, subject to the requirement of autonomy, was limited to a maximum of 24 hours. fig. 4 it is the intermediate step of improving the first module, in the sense of redesigning the double-sided wiring, the use of the same manufacturer for gps and gsm modems and an advanced risc machine (arm) microprocessor (μp). advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 54 fig. 4 the second hardware solution fig. 5 the third hardware solution however, there were several drawbacks related to energy consumption (80ma max gsm modem / h, max 30ma gps / h and μp max 15ma / h relative to a supply voltage of 3.3v), but also in local limitation at μp level of data processing before the transmission, and with this version we have succeeded, within 30 days, to deliver without loss of quality and accuracy, only 5mb of data, thanks to software development supported by μp. full description can be found in [5]. since energy efficiency remains the main theme, we continued to improve the module at hardware point of view. fig. 5 represents the new hardware concept that improves the life of its own power supply (if it is used to continuously track container shipping). also, through a physical interface, it can be linked to a hardware and software management interface for data and alarms transmission and reception, thus becoming a coordinating node in a network topology. the design concept is also a double face circuit, the two components responsible for the gps-gsm/gprs communication are from u-blox with a consumption of 5ma/h in stand-by; entire assembly consumes 75ma/h in transmission-reception mode, which satisfies one of the objectives stated in paper. equipped with a μp from microchip (pic32mx775) with a core 80mhz/32-bit mips 105dmips m4k ® [69], we were able to write a program to detect all events that required a "wake-up" decision from sleep mode, to perform all instructions for data transmission or reception, consumption in sleep mode being determined insignificant (5ma). another aspect of hardware design, as we have already noted, is the quality of the active components used; so, using the processor at a minimum computing power and working frequency, the results are reflected in improving the overall energy balance because, as we said, energy consumption increase with increasing work frequency and computing power. 4. the software application table 7 loop code distribution [5] original code modified code int a[n], b[n], c[n], i; for( i = 5; i < 3500; i += 50 ) c[i] = val; for( i = 5; i < 2000; i += 100 ) b[i] = val; for( i = 5; i < 1000; i += 100 ) a[i] = val; for( i = 0; i < n; i++ ) { for( j = 0; j < n; j++ ) { a[j] = a[j] + c[i]; b[j] = b[j] + c[i]; } } int c[n], a[n], b[n], i; for( i = 5; i < 3500; i += 50 ) c[i] = val; for( i = 5; i < 2000; i += 100 ) b[i] = val; for( i = 5; i < 1000; i += 100 ) a[i] = val; for( i = 0; i < n; i++ ) { for( j = 0; j < n; j++ ) { a[j] = a[j] + c[i]; } } for( i = 0; i < n; i++ ) { for( j = 0; j < n; j++ ) { b[j] = b[j] + c[i]; } } advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 55 allows mobile units to be viewed by using maps; the resident program in mobile units gps/gsm/gprs or gsm/gprs is written in the programming language c/c++/java, while for the communications server we only used the java programming language. both programs, from mobile units and communication server, perform specific functions. simultaneously, for the remote data transfer algorithm we focused on minimizing the number of usable bits in data packets; next data packet is transmitted or not, depending on the decision taken locally in ws, the decision being in fact only on the data difference calculated by the sensor between the transmitted and the current packet. such transmission duty cycle is shortened, leading to a decrease in the sensor energy effort. a very useful method to decrease energy consumption is also optimizing the code. as we shown in [5], there are many optimization techniques; of all of them, we expose to the reader a modified programing code solution so that it will require a minimum cpu usage (see table 7) [5]. the costumed software solutions call a few tricks and even though at first glance it gives the impression that it is laborious; in its decipherment it can be seen that by intelligent use of structured programming blocks that accelerates work instructions specific to the programming language (interrupts, semaphores, timers, reducing execution time, loops technique by vector addition and distribution loops, reducing the instantaneous power, cache memory usage, storage 0 instead of 1), simultaneously with tailored software solutions that minimize transmission time (special protocols, data compression, eliminate transmission errors, choosing optimal level of security), the use of cpu is directed to the minimum calculations required. 5. gps tracking system real-time tracking with one of the modules described in section 3, are made according to the diagram in fig. 6: internet access to the system is via web/ftp servers that are loaded with a series of html pages containing “server-side” scripts and “client-side” scripts, which are actually files such as xml, css, swf, etc. fig. 6 real-time gps tracking system note: alarms generated by mobile units or fixed gprs communicators are transmitted by dual gprs / gsm; so we have the guarantee that the alarms will be dispatched regardless of the provider's gsm / gprs network; in this way the success rate can be up to 100%. we remind that gps tracking uses the global satellite network, while gsm / gprs mobile terrestrial network. these servers are designed and configured so that they can perform certain functions: (1) to communicate bidirectionally with java servers through: commands, messages, events, gps positions, data base (db) information etc., with the purpose of mediating customer-car links. advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 56 (2) communicate with db to get mobile unit reports, db personalization by customers, viewing routes, positions, on-line journeys, points of interest, areas of interest, events, etc. (3) communicate with other users (customers, operators, administrators, etc.) through programs that are localized to the administrator or clients, for mobile unit management, back-ups, log management, etc. (4) to configure, display and maintain the maps functionality. (5) to execute the download over the air (dota) operation through ftp protocols. (6) ensure the possibility of on-line uploading, directly by clients, of back-up files. 5.1. the software system enables mobile units to be viewed using maps, which have the following features: (1) vectorized format, which makes their size to be very small (under 100kb each). (2) they are always on the client's computer, so they "move very fast" to any mouse action (zoom, left / right, up / down). (3) objects displayed on the map are disjoint, so size map remains the same no matter how many items are displayed on this. (4) both the server and client computer information, can be displayed on a map, at the same time. (5) at any change of displayed information, the map remains the same, the refresh sensation being insensible. (6) regardless of users’ number accessing the same map, it will "move" as fast as it would on the client's computer. (7) the map can display simultaneously in real time, approx. 1000 (one thousand) cars. (8) maps can be displayed on any pc, laptop, pda or smart phone. (9) any change in the field will be done very quickly on the appropriate maps, because the software required for editing and georeferencing is proprietary. (10) it can compile a map in its own format for any city in the world in a few days. (11) each map has an associated chart network (corresponding to the access paths) through which may represent routes or find optimal paths between points; the software needed to create this network as proprietary code. (12) georeferencing of maps is also done using proprietary software code. (13) access to information is the rule type user / password / rights. (14) optional, it can be implemented and viewed on google maps; on request, any public maps, for which the client provides user ids (yahoo, open street, garmin, google etc.), can be used. as practical implementation at national level, we scaled romania map at 1: 25,000, being able to realize various views (e.g. view by time and geographic area). 5.2. fleet/machine to machine monitoring typically, the tracking unit program algorithm passes through three steps: measuring, recording and transmitting data over the gsm network; maximum power consumption is recorded in the last round when data is transmitted via gsm network. to reduce energy consumption, the workflow implemented on the tracking unit goes through five stages. to the three steps mentioned we introduced two more sequences, memorize and compare, designed to reduce data transmission stage. advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 57 how it works? in the step memorizes, μp stores the output of the sensors as variables in its memory; then in compare step, the new values of the acquired data are compared with those in the previous step. ex.: for geographical azimuth (latitude and longitude) the new values measured are compared with those already previously stored; if they are identical, then compare other physical values (temperature): if the difference between two consecutive measurements does not exceed a default threshold, then the data is not transmitted, otherwise the data is transmitted. monitoring is done in real time, data transmission from the mobile unit to the servers being made by gps / gsm / gprs continuously 24h / 7 days. pseudocode algorithm that guide in 5 steps shows as follows: measures temperature, position and speed; if position is identical to the previous position; if temperature is identical to the previous temperature; if the difference between the previous temperature and the current temperature is within the threshold; do not transmit data; else transmit data; else transmit data; for more detailed analyzes, besides the website, there is a special monitoring software with capabilities in car behavior analysis. alarms generated by mobile units or fixed gprs communicators are transmitted dual gsm / gprs.; success rate of alarms as they reach dispatch center, regardless of mobile communication network gsm / gprs, is approaching by 100%. the application runs on any computer with internet connection and windows. a large number of monitors can be installed and this does not affect system load, or limit real-time access to monitored vehicles or fixed targets; a remote tracking application we also described in [70] the main interface of the screen control, is divided into two divisions: self-monitoring track division and the alarms monitoring division from either monitored vehicles or fixed targets viewing mobile units is done using maps that provide information about mobile unit positions in several variants: routes, current positions, all in real time, for groups or subgroups of cars, or individual cars in any of the above-mentioned variants. note: all programs that use maps are proprietary code and maps are loaded in vector format from google maps! 5.3. system maintenance for system maintenance, a series of dedicated programs are used, that perform database management functions, traffic analysis, information stored in the system, georeferencing, associated network drawing maps, server monitoring and backup. these are able to perform both functions of management activities, as well as analysis and providing reports; figs. 7 and 8 are such examples for database management functions. these mean the following: fig. 7 is a report generated for a car for 24 hours. the upper part is a complete report, while the two-column table is the synthesis of the day. fig. 8 is a 24 hours summary for a client who owns a fleet of 27 cars; green means stationary, blue stops, and movement ocher. in addition, fig. 8 has a “blind zone” column, which means that the vehicle could not be located by gps. the other data are easy to understand. advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 58 fig. 7 real-time gps detailed report for one car fig. 8 real-time gps detailed cars report 6. experiments and results we have already mentioned in the previous section, that in tracking algorithm we introduced two more intermediate sequences aimed at reducing energy consumption for the device. the determinations were made on two levels: hardware and software. in this section we have summarized the main results. 6.1. the hardware development the experiment was designed to measure the energy consumption of the tracking device. for this purpose, we used the monsoon power monitor (mpm) hardware to determine energy consumption [71], the second and third hardware solution (figs. 4 and 5), and the appropriate mpm graphic user interface (gui) available at [72], installed on a laptop with an intel advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 59 centrino 2 duo processor, 8gb of ram, and windows 10 pro os.; the description of gui software for these measurements is provided also in [71]. the graph gui scale was set as follows: (1) time (bottom) was shown every 100ms, with 10 units gap. (2) on left side power, with a scale gap of 500mw. (3) on right side current, with a scale gap of 500ma. and the measurements results are shows in fig. 9. the battery size was 550mah, which is for a 9v battery, on display is show the number of samples, the total consumed energy, average power and the average tension for the entire duration of the measurement. fig. 9 power measurements results 6.2. the software development in this section we have summarized the main results for the software applications. the following figures highlight comments made in sections 4 and 5 of this paper; fig. 10 is a custom gui for logging into the gps tracking system, written as we said in java. fig. 10 gui logging interface in section 5 we said that real-time tracking is done by gps and communication of positions through gsm/gprs; here too we mentioned that through the proprietary software we were able to build our own tracking maps, with different levels of resolution and accuracy. in figs. 11-13 maps are carried on 3 levels of accuracy, from general to detail on the area of interest (fig. 13 is the city of bucharest). in fig. 14 we gave a detail plan; is from faculty of electronics (we noted). advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 60 fig. 11 level 1 accuracy of own tracking maps fig. 12 level 2 accuracy of own tracking maps fig. 13 level 3 accuracy of own tracking maps fig. 14 detail of level 3 accuracy of same map fig. 15 geofencing results fig. 16 real-time position repot fig. 17 real-time travel routes advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 61 regarding real time mobile units viewing and tracking, we have implemented our own program that allows us to restrict the area of traffic by drawing the displaced area of movement (general called geofencing), being physically visible on the map. fig. 15 illustrates such a restriction points that is actually the fence limiting movement; if the border is passed, the system sends sms alert to administrator, so permanent surveillance on pc monitor is not necessary. the particularity towards other similar achievements is the use of our own maps rather than google's. the second is the possibility to choose how to delimit the allowed area: in fig. 15 we showed only the punctuation of boundaries, which are linked to each other, and also through physical marking an area of travel which can be adjusted by simply dragging whit mouse. our programs are also written to generate a series of reports (of which two have already been mentioned in figs. 7 and 8). another thought-based and implemented feature is the tracking of real-time positioning of the device being tracked; by the colors allocated for various situations, the administrator, after a certain time of use, can realize the deviations from the imposed rules. fig. 16 illustrates such a report, and in fig. 17 we have illustrated another type of query that shows the movement of a fleet on a certain day and pre-set hourly. 7. conclusions this paper presents detailed aspects related to progress of our own wn tracking device, with gsm / gps / gprs features. thus the concern of improvement and optimization of energy consumption had aimed on both hardware and software component. developed hardware modules are those of section 3, figs. 3-5, specifying that they work in real time, and the side of software applications is done in section 4. we show that hardware solution from fig. 5 represents the new concept that improves the life of its own power supply and provides the ability to bind to a hardware and software management dispatch system, for data and alarm transmission and reception, thus becoming a coordinating node in a network topology. as far as software design is concerned, we have looked for the management and handling programs to be as easy and simple to use as possible, that's why the programs needed for the mobile units were written in combined language c / c ++ / java, and for servers only java programming language. we adopted the differential transmission strategy for significant data packets, the difference measurements are calculated in mobile units and only data that is perceived by the software as alerts are transmitted; the user is responsible for choosing the communication interface and defining all related metrics. we introduced two other intermediate software stages in the data transmission, described by the pseudocode on subsection 5.2 thus managing to improve the balance of energy consumption; system maintenance is done by dedicated programs that perform tasks and database management. section 6 describes the results obtained for both hardware and software solutions. in subsection 6.1 we made a brief description of the experiment, results and methods used in the hardware area, while subsection 6.2 is allocated to software results, in fact much more spectacular in our opinion. the programs for which we presented the results of subsection 6.2 are proprietary code, runs on any computer with an internet connection and windows system and not limit real-time access to monitored vehicles or fixed targets. particularities with respect to other similar achievements in the field: 1. the use of own maps adapted after google; 2. the possibility to choose the delimitation mode for the allowed area. however, we consider the following achievements for further development: (1) an architecture for a new device that includes a wifi module, bluetooth and internal battery; (2) wireless charging of electric cars; advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 62 (3) capturing energy from surrounding electromagnetic sources that deliberately transfers energy from: radio frequency, solar and wind energy, thermal energy; (4) application in the existing intelligent buildings without additional wiring, a wireless monitoring system based on passive infrared sensors (pir); (5) using thermal energy dissipated by wireless devices for generating electricity. 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[71] https://msoon.github.io/powermonitor/powertool/doc/power%20monitor%20manual.pdf [72] https://en.freedownloadmanager.org/windows-pc/monsoon-powertool-free.html appendix 1 – abbreviations from table 6 apteen adaptive periodic teen asap accelerated sap bmac berkeley mac cadr constrained anisotropic diffusion routing cougar data-centric cadr protocol csma carrier sense multiple access dctc direct connect text client protocol did directed diffusion technique dlmst directed lmst dmac directional mac drng directed rng flama flow-aware medium access flexitp flexible based tdma protocol gaf geographic adaptive fidelity gear geographical and energy aware routing leach low-energy adaptive clustering hierarchy protocol lmst local minimum spanning tree mac medium access control mst multiple shared tree pegasis power-efficient gathering in sensor information systems read residual energy aware dynamic rng random number generator serena scheduling router nodes activity smac sensor media access control smt steiner minimum tree span switch port analyzer speed routing protocol with qos spin sensor protocols for information via negotiation sync data synchronization tdma time division multiple access tdma/ca time division multiple access/ control access teen threshold-sensitive energy efficient sensor network protocol tod tree on directed acyclic graph trama traffic-adaptive medium access protocol zmac zebra mac appendix 2 – datasheets links 1. huawei gtm900 gsm/gprs wireless module; available: https://www.digchip.com/datasheets/download_datasheet.php?id=4375635&part-number=gsm900 2. ublox neo-6m gps modul; available: https://www.waveshare.com/w/upload/2/2c/neo-6-datasheet.pdf. 3. nxp semiconductors lpc2361/62 µc; available: https://www.nxp.com/docs/en/data-sheet/lpc2361_62.pdf. advances in technology innovation, vol. 6, no. 1, 2021, pp. 47-66 66 4. ublox leon-g1 series gsm/gprs module; available: https://www.u-blox.com/sites/default/files/products/documents/ leon-g1_datasheet_%28ubx-13004887%29.pdf. 5. u-blox max-6q-0-000 gps modul; available: https://www.iot-lab.info/wp-content/uploads/2013/10/gps_max6.pdf. 6. sim900 gsm/gprs modul; available: https://datasheet.octopart.com/sim900-simcom-datasheet-17594122.pdf. 7. stm32f103rb microcontroller (µc); available: https://www.st.com/content/st_com/en/products/microcontrollers-micro processors/stm32-32-bit-arm-cortex-mcus/stm32-mainstream-mcus/stm32f1series/stm32f103/stm32f103rb.html. 8. microchip-pic32 µc; available: https://ro.mouser.com/datasheet/2/268/60001156j-1315355.pdf. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 real time scanning-modeling system for architecture design and construction ye zhang * , kun zhang, kaidi chen, zhen xu department of architecture, tianjin university, tianjin, china received 12 march 2020; received in revised form 05 june 2020; accepted 02 july 2020 doi: https://doi.org/10.46604/aiti.2020.5385 abstract the disconnection between architectural form and materiality has become an important issue in recent years. architectural form is mainly decided by the designer, while material data is often treated as an afterthought which doesn’t factor in decision-making directly. this study proposes a new, real-time scanning-modeling system for computational design and autonomous robotic construction. by using cameras to scan the raw materials, this system would get related data and build 3d models in real time. these data would be used by a computer to calculate rational outcomes and help a robot make decisions about its construction paths and methods. the result of an application pavilion shows that data of raw materials, architectural design, and robotic construction can be integrated into a digital chain. the method and gain of the material-oriented design approach are discussed and future research on using different source materials is laid out. keywords: scanning-modeling system, material data, computational design, robotic construction 1. introduction the disconnection between form and material in the architecture field has become a serious problem. with the popularity of 3d modeling software such as sketchup, rhino, and grasshopper, architects are prone to first develop form on a computer screen and only afterwards associate material designations to the predefined geometry model [1]. in improper citing, the digital form is freely rendered with any material bitmap or texture without regard to a material’s rational use or practicality [2], and risking that material information cannot be timely and effectively fed back to the design and construction stages. the separation of material and form or the linear progression from the design intention to materialization has caused some problems in recent decades. firstly, the process of fabricating source material into a variety of sizes and shapes consumes significant time, while a large quantity of material waste is produced. secondly, human-designed rules and solutions are prone to be limited by empirical knowledge [3], especially in projects with irregular surfaces and complex geometries. ignoring source material’s properties makes the design and fabrication process more passive, inefficient, imprecise, and expensive. finally, it hinders expressing building’s regional and cultural characteristics as architectural materials with different personalities in different regions are mass produced through the same processing method. advances in contemporary digital scanning and bespoke robotic technologies [4] enable material information to be simulated, calculated, and well organized. as a result, it is an alternative approach for architecture. in this study, a new, real-time scanning-modeling system for obtaining material information and incorporating the data into a continuous digital chain of computational design and robotic construction are introduced. as fig. 1 shows, traditional designs are determined subjectively by the architects; while a new chain with the scanning-modeling system enables an alternative design approach derived objectively by the data of source material. * corresponding author. e-mail address: yaapp2012@gmail.com tel.: +86-15900241936 advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 249 fig. 1 comparison of two modes the scanning-modeling system is regarded as the sensing end of this digital chain. it reads data of raw materials including their sizes and shapes without cumbersome supporting equipment and builds a visual model in real-time. after collecting and visualizing the data, the calculation end of the chain would generate architectural geometry based on material data, site conditions and structural performance. finally, at the action end of the chain, a robot arm would be used to fabricate the design. according to the data obtained during the previous stages, the robot would find an assembly location autonomously without having to be programmed in advance. in sum, this study creates a convenient and rapid material information acquisition system that benefits architectural design and digital construction. 2. literature review and innovation points this study provides a new scanning-modeling system and examines its application in architectural programs. the research contents include autonomous perception, computational generation, and robotic actuation. despite a great deal of research on these three topics over the past several decades, there has been very little research intended to integrate them into the field of architecture. previous studies and new development in measuring and modeling, computational design, and robotic construction are described as follows. 2.1. measuring and modeling table 1 measuring and modeling methods name principle speed accuracy cost stability limitation active method moiré fringes diffraction and interference of light ++ +++ + + only available for objects with regular texture time-of-flight (tof) time taken for the wave to bounce back to the emitter ++ -- low resolution and easy to be disturbed structured lighting encoding and decoding of light + ++ + ++ projection equipment required triangulation solve trigonometric equation + + + data sparseness passive method shape from texture (sft) perspective distortion calculation + + + surface texture information required shape from shading (sfs) ray calculation + light parameters required multi-view stereo (mvs） parallax principle --+ + image error is big silhouette visible shell approximation +++ -++ ++ visible shell only existing 3d reconstruction methods can be divided into two categories: active and passive. the active methods mainly include moire fringe, time-of-flight (tof), and structured lighting and triangulation; while the passive methods mainly include shape from texture (sft), shape from shading (sfs), multi-view stereo (mvs), and silhouette. these methods use mathematical and physical knowledge to rebuild objects. among them, moire fringe used the interference of wave to digital construction construction subjective decision objective decision advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 250 deduce the shape; sft, sfs and structured lighting mainly use perspective principle; triangulation, mvs and silhouette use the methods of deformations of triangle positioning. the characteristics of each method are presented in table 1 [5-9]. “+” means the performance is strong while “-” means it is weak. in the field of architecture, the precision of measuring and modeling required is not as strict as other fields. the demands of speed, cost, and stability are higher. therefore, this study is established on the basis of the silhouette method, which develops to improve the speed and efficiency of getting information on material size, and to make it easier to operate as the computing moreover, the information communication mechanism are in a visual interface. 2.2. computational design different from design precedents which rely on intuition and experience to solve design problems, computational design encodes design decisions using a computer language; consequently, the design expression is changed from geometry to logic [10]. the computational design is excellent in dealing with complexity, coming up with many options in a short time, and optimizing the solution. although the computational design is still a relatively young and evolving field [11], some research institutions and researchers have made progress in theoretical development, methodologies, and strategies [12-14]. based on the methodologies and strategies of computational design, this study presents a pavilion which is generated from material information. the major dimensions of computational design in this study include: (1) information transformation: this pavilion makes use of natural branches containing three forks. the length of each fork and the angles between the forks are read by a scanning system and the information is transformed into grasshopper in real time by a plug-in developed by this research. (2) parameter setting: considering the site conditions and the pavilion’s functional uses, the parameters are the location of the anchor points, the camber of the surface, the fractal geometry, and the number of forks at a node. (3) 3d modeling and visualization: the computation of the design and fabrication is conducted in rhino3d which allows designers to test and simulate in a visual environment. (4) processing with data and algorithms: the rules and standards to inform the design direction comprising waste less material, similarity to the target surface, and structural performance. 2.3. robotic construction the use of robots in architectural construction can be traced back to the 1980s [15]. at that time, robotic systems were mainly used in japan, but the efficiency didn’t prove satisfactory and hence received fading research attention. however, with the development of digital tools and manufacturing technologies, robotics in architecture has been a burgeoning research topic since 2010. prior studies have sought to explore and expand the possibilities of robotic fabrication, robotic assembly, and even human-robot interactions on site. however, an important limitation of past research is the material sensing and real-time feedback. this study seeks to fill that gap by emphasizing robotic eye-hand coordination and to break with the typical robot movement pattern which is controlled by humans and not by the robot itself. 3. real time scanning-modelling system 3.1. motivation and framework the primary purpose of the scanning-modeling system is measuring architectural materials on-site automatically and gets their three-dimensional models in real time. the procedure is shown as fig. 2. for each material component, the images from advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 251 different perspectives will be scanned by a camera group. an independent program specially written by this study will capture the effective information of the material image and calculate feature points using an open source computer vision library. in order to ensure the efficiency of operational and data transmission, the program is simplified to transmit data of the quantity of controllable feature points with high information concentration. then, a pre-programmed plug-in in rhino/grasshopper will receive data from the scanning program by memory mapping and analyzing outlines from different perspectives. finally, a three-dimensional model of the corresponding material component will be generated within 1 second for subsequent design development. fig. 2 scanning-modelling system 3.2. method this research takes natural branches as an example material to explain how the scanning-modeling system works. the system extracts the contours of the physical branch and reconstructs it digitally. it has two working paths: a software workflow and a hardware workflow. the software workflow is virtual and programmable, while hardware workflow is realistic and transitive. the data circulate and transmit in the software workflow, participating in complex interactions and transformation operations, before finally outputting a concise digital model of the branch. the hardware workflow is very simple, consisting only of material components, sensors (cameras) and a computer. six cameras can complete all of the image acquisition work while the computer can realize image recognition, data processing and 3d model reconstruction. 3.3. hardware workflow the branches (source material), camera group, and computer constitute the hardware workflow of the system. in the laboratory, a 6m-long custom frame to fix the cameras is built, and the background with black curtains to extract information effectively is covered. the conditions and settings for each hardware element are as follows: (1) branches to be tested: this study used natural branches which had minor branches, leaves and twigs pruned away. their lengths range from 75 cm to 245 cm and their radius range from 2cm to 10cm. (2) number and location of cameras: the branch’s radius is set as r, the length of the frame holding the cameras as l and the camera angle as α. an equation can be calculated as: l=2r/sin(α/2) (1) the number of pixels in the corresponding direction of the camera is set as n, the resolution value of the reconstructed model is γ. the calculation is based on the 1st formula: γ=2rcos(α/2)/n=lsinα/2n (2) advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 252 the inherent error of this system is not uniform. it is affected by two factors as shown in fig. 3: one is the angle between the object and the camera, and the other is the normal vector of the surface point with respect to the plane of the camera group. to establish this error, this study sets the angle between two adjacent cameras as δ and the inherent error as e. an equation can be computed as: e=r[csc(δ/2)-1] (3) fig. 3 calculations in order for γ> e and considering feasibility, convenience, and accuracy, this research finally takes l = 600cm, α = 0.3π, δ = 0.667π, which means 6 cameras are fixed to a 600 cm-long frame to catch images of the branch. 3.4. software workflow the software workflow is the core of this system. it includes three steps, as shown in fig. 4: (1) generating a description file of calibration cameras. (2) an external program which extracts the image of the branch and calculates related data for visual presentation. (3) a pre-programmed module in rhino receives the data and converts it into a digital branch model in real time. the following sections explain the three steps in more detail. fig. 4 software workflow the first step is to develop a camera calibration file “cameracorrect.py”. the purpose of this step is to determine the mapping relationship between contour pixels and spatial points in the modeling software. the calibration is based on the perspective principle, it does not require a complete camera internal parameter matrix, only a scaling parameter and rotation parameter are taken. because of the usb broadband limitation, an additional module was added in the python script in order to read information from multiple cameras simultaneously. there are five commands “z”, “x”, “f”, “s” and “q” in the script: “z” and “x” to change the camera, “f” to refresh, “s” to display the recorded data, “q” to save the data and exit. after the relevant parameters of the calibration tool are entered, an auxiliary script automatically calculates the final calibration parameters and generates this calibration file. this step only runs once in the whole workflow and is not repeated when a branch is scanned. advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 253 the second step is to analyze the branch images and generate both a “points.py” file which contains image information and a “getgeo.gh” file which is used in the modeling software. first, through the gauss filter process and the binary image process, it is able to extract smooth contours of a branch from different perspectives. then, the number of pixels selected in the contour is adjusted by a tolerance parameter and the three-dimensional coordinates of all the selected points are calculated. finally, the three-dimensional array is transferred into grasshopper through shared memory and the spatial position of the points is inversely mapped in rhino according to the former calibration file. the third step in the software workflow is to generate a visual model which runs simultaneously with the second step. a preset program receives array data and reorganizes them into projections from different views in order. by the algorithm of the boolean intersection, all the information work together to generate a digital branch model representative of the scanned physical branch. 3.5. results and discussions the system is characterized by flexibility, reliability, and processing speed. because of the modular organization of the workflow, the perception of material information is expandable. the researchers can increase the number of cameras to improve the accuracy of the system; in addition, expand the type of sensors to capture and analyze other qualities of the source material. flexibility is also reflected in the diversity of operating environments and source materials. although the former branch experiment is carried out in a laboratory, it can be performed in other places including outdoor environments by simply changing the fixing points and corresponding values in the equations. similarly, the system can scan other building materials (source materials). additionally, the system has a high tolerance for faults, built-in redundancy; therefore, it is very reliable. even if some of the sensors are broken, other sensors can still work as usual, so the program can run normally despite the reduced accuracy. last but not the least, this system runs very fast. usually, image processing is extremely cpu intensive, but this system basically eliminates this problem with appropriate abstraction and sufficient optimization. taking the branch project as an example, even in ordinary notebook configuration, a refresh rate of 1 second per time can be achieved. this efficiency not only saves time, but also makes the system more practical to use. 4. application example using the above-mentioned real time scanning-modelling system, a pavilion is built and the application of the system in new architecture model is shown. this pavilion uses abandoned "y" shaped branches as source materials. by the algorithms, the computer can make independent decisions and generate a design based on the quantity and characteristics of the existing materials [16]. then, a robotic arm is used to complete the construction process. 4.1. design of the pavilion 4.1.1. selection and organization of the branches fig. 5 information abstraction advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 254 with the scanning-modelling system, the researchers develop digital models of all wooden branches that can be used for the pavilion. next, the researchers distill the information which is useful to design and discard data that does not affect the design such as slight unevenness on the branch surface and the bending amplitude of each fork, etc. the useful parameters are three-dimensional coordinates of the four points p0, p1, p2 and p3 on the branch. the length between every two points and the length and thickness of each fork are shown in fig. 5. because all tree branches are from the same species of the ash tree, their density is considered the same. fig. 6 computational generation process according to the environmental conditions and functional requirements, the approximate dimensions of the pavilion are established. the location of the ground points and the geometry logic are seen as a preliminary step, in addition to stipulating that each vertex must have three forks jointing together, as shown in fig. 6. in the procedure of component selection and organization, the logic is set as follows: (1) all branches are sorted by volume and the three largest load-bearing branches are selected. (2) for any two branches b and c which are connected to the same branch a, if they can intersect, their trajectory of intersection is an ellipse and takes the position with the minimum distance from the central axis of branch a to ensure the overall stability. (3) if branch b and branch c cannot intersect, they are cut shorter to make the intersection possible. according to the information list of all the branches, the computer can quickly calculate the cutting lengths of different options and the branches spatial positions under all possibilities. corresponding pavilion forms are also simulated and all possibilities are sorted by how much material is wasted. (4) the top five options are chosen, then "millipedes" and other analysis tools are used to test and optimize their structural performance. combining the amount of material waste factor, structural properties, and formal aesthetics, the final pavilion design option is selected, as shown in fig. 7. fig. 7 structure performance analysis 4.1.2. detailed design after the design program is generated and optimized, its details are refined. the first is the node. every node in this pavilion is different and because all branches have their own angles, the nodes are customized rather than standardized. traditional rope-wood nodes can adjust the angle and are easy to make; however, they are not strong enough. cnc-customized advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 255 tenon-and-mortise nodes are stable, but their fault tolerance ability is weak and the manufacturing takes detailed time. ultimately, a new type of node with universal joints, three-way pipes and jackscrews are designed. the new node is strong, cheap and easy to make, as shown in fig. 8. fig. 8 joints for the base, a cast-in-place concrete foundation and embedded bolt method are tried, but this was eliminated due to their insufficient strength and site environmental limitations. instead, the project uses metal bearing plate and ground pins to establish the base, as shown in fig. 9. fig. 9 base 4.2. robotic construction in the robotic construction stage, the motion of the robot arm and the design of the tool end should be carefully considered. by writing the relevant code in grasshopper and kukaprc, the robotic arm can automatically control its grabbing position and motion movement path according to the generated design. the robotic arm determines the final position of each branch quickly and accurately and then fixes the joint by cooperating with human workers or another robot. if there is any problem during the construction process, the data will be fed back into the digital model for real-time adjustment. in terms of the tool end of the robotic arm, it has to be strong enough to grasp the branch and ensure that it doesn’t twist. an electronically controlled claw is first applied. with the afmotor library in arduino, the opening and closing state, running speed and rotation direction of the gripper can be controlled in real time. however, claws have limitations: its opening and closing range is only 0-90mm and its maximum clamping force is only 16 newton. thus, it is only suitable for grabbing light and small branches. in order to improve the ability to grab, the pneumatic parallel open and close claw are selected and modified. the size between the parallel plates could be adjusted to match the diameter of the branch. the contact surface of the plates is coated with a special rubber material to increase the coefficient of friction; consequently, the branch wouldn’t twist. features of this pneumatic claw are: advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 256 (1) wide opening and closing range. (2) greater grabbling ability. (3) suitable for branches with different sizes and weights. (4) it can be deployed in grasshopper, so the robot arm can perform the entire step independently (fig. 10). fig. 10 robotic construction 5. conclusion and future work this research succeeds in developing a real time scanning-modelling system to perceive and analyze material information for guiding the architectural design and robotic construction (figs. 11-12). the material oriented “eye-brain-hand collaboration” chain saves construction materials, greatly reduces the cost of component fabrication, gives unprecedented flexibility to geometry, optimizes structural performance and improves construction work. fig. 11 pavilion in this study, there is still some room for improvement. first of all, the environment perception aspect can be enriched. more types of sensors can be installed and the analysis of algorithms can be optimized; therefore, the system can perceive and utilize other kinds of information such as material strength and toughness. secondly, the computational design part can be further optimized and treated as agent-based simulation and generation. the researchers can develop algorithms that let the agent system provide better outcomes. user interfaces can also be developed. finally, the experimental pavilion relies exclusively on a kuka robotic arm. bespoke robotic arms can be modified and the interoperability of different robotic arms can be developed. advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 257 fig. 12 pavilion in future research, the theory and method of this study are expected to be used for other materials in real scale architecture projects. the scripts and scanning-modeling methods can be partially replaced and used for materials with various shapes. for larger scale construction, the locations of sensors could be recalculated using the formula put forward in this paper. the researchers envision that success in digital manufacturing with globally abundant and locally available materials may impact the design approach by considering materials’ personalities. acknowledgement this study was funded by tianjin science foundation (agreement no.: 19jcqnjc07300). conflicts of interest the authors declare no conflict of interest. references [1] k. wu and a. kilian, “design natural wood log structures with stochastic assembly and deep learning,” robotic fabrication in architecture, art and design, springer press, august 2018, pp. 16-30. 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[7] j. schlarp, e. csencsics, and g. schitter, “scanning laser triangulation sensor geometry maintaining imaging condition,” ifac-papers online, vol. 52, no. 15, pp. 301-306, december 2019. [8] m. slembrouck, p. veelaert, d. hamme, d. van cauwelaert, and w.philips, “cell-based approach for 3d reconstruction from incomplete silhouettes,” international conference on advanced concepts for intelligent vision systems, springer press, september 2017, pp. 530-541. [9] j. s. franco and e. boyeb, “efficient polyhedral modeling from silhouettes,” ieee transactions on pattern analysis and machine intelligence, april 2009, pp. 414-427. advances in technology innovation, vol. 5, no. 4, 2020, pp. 248-258 258 [10] h. hua, “a bi-directional procedural model for architectural design,” computer graphics forum, vol. 36, no. 8, pp. 219-231, december 2017. [11] g. brugnaro, e. baharlou, l. vasey, and a. menges, “robotic softness-an adaptive robotic fabrication process for woven structures,” proc. 36th annual conference of the association for computer aided design in architecture, october 2016, pp. 154-163. [12] p. eversmann, f. gramazio, and m. kohler, “robotic prefabrication of timber structures: towards automated large-scale spatial assembly,” construction robotics, vol. 1, no. 1-4, pp. 49-60, august 2017. [13] m. maasoumy and a. sangiovanni-vincentelli, “smart connected buildings design automation: foundations and trends,” foundation and trends in electronic design automation, vol. 10, no. 1-2, pp. 1-143, march 2016. [14] r. snooks and g. jahn, “closeness: on the relationship of multi-agent algorithms and robotic fabrication,” robotic fabrication in architecture, art and design, springer press, february 2016, pp. 218-229. [15] j. p. sousa, c. g. palop, e. moreira, a. m. pinto, j. lima, p. costa, et al. “the spiderobot: a cable-robot system for on-site construction in architecture,” robotic fabrication in architecture, art and design, springer press, february 2016, pp. 230-239. [16] r. rust, d. jenny, f. gramazio, and m. kohler, “spatial wire cutting: cooperative robotic cutting of non-ruled surface geometries for bespoke building components,” proc. 21st international conference on computer-aided architectural design research in asia, southeastern university press, march-april 2016, pp. 529-538. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 a biogas desulphurization system with water scrubbing cheng-chang lien * , wei-cheng lin department of biomechatronic engineering, national chiayi university, chiayi, taiwan received 04 april 2019; received in revised form 21 april 2019; accepted 04 june 2019 abstract the biogas is renewable energy with very good potential. it is a gas produced by the bacteria transformation of the organic substance under the anaerobic condition. it is a flammable gas because it contains the hydrogen sulfide (h2s) in its composition. it will cause damage to metal equipment and the corrosion of the pipe. so before using the biogas, the desulphurization process should be carried on. the purpose of this study was to design a water scrubbing system for biogas and carry on the performance test of the desulphurization process in the hog farm. in the field test, the biogas flow rate is changed in the water scrubbing cylinder and under different external circulation water flow rate. the h2s concentration in the biogas is detected before and after water scrubbing, and the desulphurization efficiency of biogas was discussed, furthermore, the ph value of water in the water storage tank was measured. when the h2s adsorbed by water was at steady state, whether the ph value of external circulation water can meet the effluent standard was discussed. from the test results, it showed that the removal efficiency of h2s was 47.7% in 30 minutes of water scrubbing time under 120 ℓ of total water amount, 80 cm of water level in the water scrubbing cylinder, 20 ℓ/min of internal circulation water flow rate and 10 ℓ/min of external circulation water flow rate, and 25 ℓ/min of biogas flow rate. the ph value of water in the water storage tank was 6.22, which met the effluent standard of regulation for discharging directly. this system can reduce the h2s content in the biogas, and purify the quality of the biogas. the operation of this system is convenient and the fabrication cost is low, which is suitable for the small-scale hog farm to purify the biogas. keywords: biogas, water scrubbing, hydrogen sulfide, ph, desulphurization 1. introduction the biogas is considered as renewable energy with very good potential. it is a gas produced by the bacteria transformation of the organic substance under the anaerobic condition. it is a flammable gas, which contains 50-75% of methane (ch4), 25-45% of carbon dioxide (co2), 0-20,000ppm of hydrogen sulfide (h2s), and small amount of gases such as nitrogen (n2), oxygen (o2), hydrogen (h2), and ammonia (nh3) [1]. the production sources of biogas are much extensive, including animal droppings, wastewater, and rubbish landfill, etc. [2]. it can be applied in house fuel, warm-keeping light, generator, electric car, and warm-keeping facilities in the pigsty of hog farm, etc. [3]. the h2s in the biogas is a gas having stink odor and toxicity. it has a very strong corrosive property to some metals. it will cause damage to machinery equipment. therefore, the use of biogas as the fuel will be limited. before using the biogas as the fuel, the h2s must be removed [4]. the h2s in the biogas can be removed through the physical, chemical and biological methods, such as the absorption, adsorption, and bio-reaction. the h2s and co2 in the biogas are the acidic gases. they will be acidified after h2s and co2 are adsorbed in the water [5-7]. the water scrubbing of biogas is a physical purification method. the solubility in water for various gases in the biogas is different. the methane gas is much more difficult to be dissolved in the * corresponding author. e-mail address: lanjc@mail.ncyu.edu.tw tel.: +886-5-2717972; fax: +886-5-2750728 advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 270 water. this property is used to remove h2s and co2 by water scrubbing, in order to increase the methane purity in the biogas [8-9]. when selecting the scrubbing column as water scrubbing purification equipment, the desulfurization performance would depend on the scrubber size and design, gas pressure, composition of raw biogas, water flow velocity and water purity. water scrubbing as adsorbent mainly had the low cost and the easy operation, as well as easily increased the contact area and time of gas and liquid to accomplish the continuous purification [10]. the purpose of this study was to design a water scrubbing system for biogas and carry on the performance test of the desulphurization process in the hog farm. the test was carried under different biogas flow rate in the water scrubbing cylinder and external circulation water flow rate, the h2s concentration in the biogas was detected before and after water scrubbing, and the desulphurization efficiency of biogas using water scrubbing was discussed, furthermore the ph value of water in the water storage tank was measured. when the h2s adsorbed by water was at steady state, whether the ph value of external circulation water can meet the effluent standard was discussed. this system can reduce the h2s content in the biogas, and purify the quality of the biogas. 2. materials and method 2.1. design of water scrubbing and desulphurization system fig. 1 illustration of water scrubbing and desulphurization system for biogas the water scrubbing and desulphurization system for biogas is illustrated in fig. 1. the water scrubbing cylinder with 0.003 m thickness made by transparent acrylic is 0.25 m in diameter and 1.20 m in height. it is the main body of water scrubbing and desulphurization system, which is used to observe the internal biogas bubbles and the reaction situation in the water scrubbing cylinder. there are an internal circulation water inlet and an outlet for measurement of h2s in biogas after water scrubbing and desulphurization at the top of the water scrubbing cylinder. there are water outlet and aeration disc at the bottom of water scrubbing cylinder. the aeration disc with 0.23 m in diameter is placed at the bottom of water scrubbing cylinder. there is a biogas inlet under aeration disc. a biogas pump is used to pressurize the biogas. a pressure gauge is used to measure the pressure of biogas flowing into the water scrubbing cylinder. the biogas flow rate is measured by a float type gas flowmeter (f20-100nlpm, lorric ® , taiwan). the biogas enters the water scrubbing cylinder through the bottom of the aeration disc. because there are a lot of holes on the surface of aeration disc, the biogas will enter into the water scrubbing cylinder in a way of many small bubbles, so that the biogas bubbles will contact with water sufficiently for reacting. advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 271 the internal circulation water and external circulation water are used for the field test. at the internal water circulation, the water pump is used to pump the circulation water into the water scrubbing cylinder from the top of water scrubbing cylinder, so that the biogas bubbles will contact with water sufficiently for reacting that increase solubility in water, in order to remove the h2s in biogas, and flow back to the water storage tank from the water outlet at the bottom of water scrubbing cylinder. at water external circulation, the external circulation water without adsorbing h2s flows into the water storage tank to upgrade the inner circulation water. the water absorbing h2s is discharged from the water storage tank. the biogas after water scrubbing and desulphurization is discharged from the outlet at the top of the water scrubbing cylinder. the h2s detecting device (120-sm, kitagawa, japan) is used to measure the h2s concentration versus water scrubbing time, in order to calculate the removal h2s efficiency of water scrubbing and desulphurization. at the same time, the ph meter (ts100, suntex, taiwan) is used to measure and record the variation of ph value for the water in the water storage tank during water scrubbing and desulphurization process. 2.2. performance test of water scrubbing and desulphurization system fig. 2 the test flow diagram of water scrubbing and desulphurization system for biogas after the assembly of this water scrubbing and desulphurization system is finished, it is moved to the hog farm to carry on the field test. the biogas used for the test is the swine wastewater treated through the three-step system and produced from the anaerobic fermentation process. before the field test, the total water amount is 120 ℓ in the water storage tank and the acrylic water scrubbing cylinder, the height of water level in the water scrubbing cylinder is 80 cm, and the flow rate of internal circulation water is 20 ℓ/min. the biogas flow rate is changed to 25, 50, and 75 ℓ/min and the external circulation water flow rate is changed to 0 and 10 ℓ/min for carrying on the field test. before the field test, the two-point standard buffer ph 4 and ph 7 were used to calibrate the slope of the electrode for ph meter, and the set time interval was recorded once per minute for ph value. every test time for water scrubbing is 30 minutes. advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 272 before starting the field test, the detecting device is used to measure the h2s concentration in biogas without water scrubbing and desulphurization. measure and record the h2s concentration in biogas and the variation of ph value for the water in the water storage tank during water scrubbing and desulphurization process. fig. 2 shows the test flow diagram of water scrubbing and desulphurization system for biogas. the removal efficiency of h2s in the biogas is shown in eq. (1).   ( )% / 100[ ]the removal efficiency a b a  　 (1) where a is the h2s concentration (ppm) before water scrubbing of biogas and b is the h2s concentration (ppm) after water scrubbing of biogas. 3. result and discussion 3.1. variation of removal h2s efficiency fig. 3 the removal of h2s efficiency versus water scrubbing time for different biogas flow rate under 0 ℓ/min of external circulation water flow rate fig. 4 the removal h2s efficiency versus water scrubbing time for 0 and 10 ℓ/min of external circulation water flow rate under 25 ℓ/min of biogas flow rate during the performance test of this system, the total water amount is 120 ℓ, the height of water level in the water scrubbing cylinder is 80 cm, and the flow rate of internal circulation water is 20 ℓ/min. under the external circulation water flow rate is 0 ℓ/min, and the removal of h2s efficiency versus water scrubbing time for the different biogas flow rate is measured and recorded, as shown in fig. 3. from the figure, it is shown that the removal of h2s efficiency is decreased with the increase of water scrubbing time. under 50 and 75 l/min of biogas flow rate, at 12 minutes of water scrubbing time, the removal h2s efficiency is dropped to 4.9% rapidly. after 12 minutes of water scrubbing time, the h2s adsorbed by water has already been closed to the saturated condition, and there is almost no removal h2s efficiency. under 25 l/min of biogas flow rate, at 12 minutes of water scrubbing time, the removal h2s efficiency is dropped to about 24.9%. at 30 minutes of water scrubbing time, the removal of h2s efficiency is dropped to below 7.0%. the water in the water scrubbing cylinder and water storage tank is not discharged by the external circulation water flow. the h2s content in water is increased with the increase of water scrubbing time and reached to the saturated condition finally. under 25 ℓ/min of biogas flow rate, the removal h2s 0 20 40 60 80 100 0 5 10 15 20 25 30 biogas flow rate : 25 ℓ/min biogas flow rate : 50 ℓ/min biogas flow rate : 75 ℓ/min water scrubbing time (min) r em o v al h 2 s e ff ic ie n cy ( % ) 0 20 40 60 80 100 0 5 10 15 20 25 30 outside cycle 0 ℓ/min of water flow water scrubbing time (min) r em o v al h 2 s e ff ic ie n cy ( % ) advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 273 efficiency versus water scrubbing time for 0 and 10 ℓ/min of external circulation water flow rate is shown in fig. 4. when the external circulation water flow rate is 10 ℓ/min, the h2s adsorbed in water will not reach the saturated condition after 12 minutes. the removal of h2s efficiency is kept at a steady value. the external circulation water without adsorbed h2s is added to replace the old water adsorbed h2s can increase the desulphurization effect. fig. 5 illustrates the removal of h2s efficiency versus water scrubbing time for different biogas flow rate under 10 ℓ/min of external circulation water flow rate. 10 minutes before water scrubbing time, the removal of h2s efficiency is decreased with the increase of water scrubbing time under 25, 50, and 75 ℓ/min of biogas flow rate. 10 minutes after water scrubbing time, the variation of removal h2s efficiency is not large. when the water scrubbing time is 30 minutes, the removal h2s efficiency is kept at a constant value respectively under 25, 50, and 75 ℓ/min of biogas flow rate. the removal of h2s efficiency is decreased with the increase of biogas flow rate. from the test results, it is known that when the external circulation water flow rate is increased to 10 ℓ/min, the h2s concentration in water will not reach the saturated condition, and the desulphurization rate will be kept at a certain level steadily. fig. 5 the removal h2s efficiency versus water scrubbing time for different biogas flow rate under 10 ℓ/min of external circulation water flow rate table 1 shows the removal of h2s efficiency versus water scrubbing time for different biogas flow rate under 0 and 10 ℓ/min of external circulation water flow rate and 30 min of water scrubbing time. under 0 ℓ/min of external circulation water flow rate and 30 min of water scrubbing time, the removal h2s efficiency at 25, 50, and 75 ℓ/min of biogas flow rate is 7.0%, 2.1%, and 2.0% respectively, nearly reach the saturated condition. under 10 ℓ/min of external circulation water flow rate and 30 min of water scrubbing time, the removal h2s efficiency at 25, 50, and 75 ℓ/min of biogas flow rate is 47.7%, 33.4%, and 20.7% respectively. it can be seen the removal h2s efficiency in biogas upgrades as the external circulation water flow increases, and steadily remain in a certain one without saturation; this is because the water in the water storage tank is continuously changed so that the removal h2s efficiency can steadily remain after certain water scrubbing time. it is also known that the removal of h2s efficiency is decreased with the increase of biogas flow rate. table 1 the removal h2s efficiency for different biogas flow rate under 0 and 10 ℓ/min of external circulation water flow rate and 30 min of water scrubbing time external circulation water flow (ℓ/min) 10 0 biogas flow (ℓ/min) 25 50 75 25 50 75 trial 1 3 3 3 3 3 3 concentration of h2s (ppm) 5230 7990 9950 11770 12170 12120 the removal efficiency (%) 47.7±0.3 33.4±0.1 20.7±0.9 7.0±0.7 2.1±0.6 2.0±0.1 1 the total water amount is 120 ℓ of, the height of water level in the water scrubbing cylinder is 80 cm and the internal circulation water flow rate is 20 ℓ/min 3.2. variation of ph value in the water storage tank fig. 6 show that the ph value in water storage tank versus water scrubbing time for 0 ℓ/min and 10 ℓ/min external circulation water flow rate under 25 ℓ/min of biogas flow rate. the ph value in the water storage tank decreases with the 0 20 40 60 80 100 0 5 10 15 20 25 30 biogas inflow rate : 25 l/min biogas inflow rate : 50 l/min biogas inflow rate : 75 l/min water scrubbing time (min) r em o v al h 2 s e ff ic ie n cy ( % ) advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 274 increase of the washing time before 10 minutes of the water scrubbing time. the ph value in the water storage tank tends to be saturated after 10 minutes of the water scrubbing time, it can be seen that the ph value in water storage tank of the external circulating water flow 0 ℓ/min after 10 min of water scrubbing time is lower than the ph value in water storage tank of the external circulating water flow 10 ℓ/min. fig. 7 illustrates the ph value in water storage tank versus water scrubbing time for different biogas flow rate under 10 ℓ/min of external circulation water flow rate. the ph value in water storage tank for the different biogas flow rate is decreased with the increase of water scrubbing time. 10 minutes before water scrubbing time, the ph value in the water storage tank is decreased with the increase of water scrubbing time under 25, 50, and 75 ℓ/min of biogas flow rate. 10 minutes after water scrubbing time, the variation of ph value in water storage tank saturates to a certain value, which is also similar to the variation of removal h2s efficiency versus water scrubbing time. table 2 shows the ph value in the water storage tank versus water scrubbing time under 10 ℓ/min of external circulation water flow rate and 30 min of water scrubbing time. under 30 minutes of water scrubbing time, the ph value in water storage tank for 25, 50, and 75 ℓ/min of biogas flow rate is dropped to 6.22, 6.22, and 6.24 respectively. according to the effluent standard of wastewater specified in government regulation for taiwan, the ph value of the effluent standard is 6.00-9.00. the ph value of field test result does not exceed the effluent standard, and the water can be discharged directly without special wastewater treatment [11]. table 2 the ph value in the water storage tank at different biogas flow rate under 10 ℓ/min of external circulation water flow rate and 30 min of water scrubbing time biogas inflow (l/min) 25 50 75 trial 1 3 3 3 ph in 0 min 7.15 7.19 7.15 ph in 30 min 6.22±0.01 6.22±0.03 6.24±0.01 1 the total water amount is 120 ℓ of, the height of water level in the water scrubbing cylinder is 80 cm and the internal circulation water flow rate is 20 ℓ/min fig. 6 the ph value in water storage tank versus water scrubbing time for 0 ℓ/min and 10 ℓ/min external circulation water flow rate under 25 ℓ/min of biogas flow rate fig. 7 the ph value in water storage tank versus water scrubbing time for different biogas flow rate under 10 ℓ/min of external circulation water flow rate 5.50 5.75 6.00 6.25 6.50 6.75 7.00 7.25 0 5 10 15 20 25 30 outside cycle 0 ℓ/min of water flow water scrubbing time (min) w at er p h i n w at er s to ra g e 5.5 5.75 6 6.25 6.5 6.75 7 7.25 0 5 10 15 20 25 30 biogas inflow rate : 25 ℓ/min biogas inflow rate : 50 ℓ/min biogas inflow rate : 75 ℓ/min water scrubbing time (min) w at er p h i n w at er s to ra g e advances in technology innovation, vol. 4, no. 4, 2019, pp. 269-275 275 4. result and discussion a water scrubbing and desulphurization system were designed and the performance test of the desulphurization process was carried on in the hog farm. 10 minutes before water scrubbing time, the removal of h2s efficiency is decreased with the increase of water scrubbing time under 25, 50, and 75 ℓ/min of biogas flow rate at 120 ℓ of total water amount, 80 cm of water level, 20 ℓ/min of internal circulation water flow rate and 10 ℓ/min of external circulation water flow rate. 10 minutes after water scrubbing time, the removal h2s efficiency was kept at a constant value under three different biogas flow rates. under 25 ℓ/min of biogas flow rate, the removal h2s efficiency was 47.7% in 30 minutes of water scrubbing time, and the ph value in the water storage tank was 6.22 in 30 minutes of water scrubbing time, which met the effluent standard of regulation and can be discharged directly. as for this water scrubbing and desulphurization system, was often used as a pre-treatment equipment for heating water of biogas combustion, the operation is convenient and the fabrication cost is low, which is suitable for the small-scale hog farm to purify the biogas. conflicts of interest the authors declare no conflict of interest. references [1] m. kaltschmitt and w. streicher, “energie aus biomasse,” regenerative energien in ö sterreich, pp. 339-532, 2009. [2] s. pipatmanomai, s. kaewluan, and t. vitidsant, “economic assessment of biogas-to-electricity generation system with h2s removal by activated carbon in small pig farm,” applied energy, vol. 86, no. 5, pp. 669-674, may 2009. [3] c. c. lien, c. h. ting, and j. h. mei. “piglets comfort with hot water by biogas combustion under controllable ventilation,” advances in technology innovation, vol. 3, no. 2, pp. 86-93, april 2018. [4] j. nägele, h. j. steinbrenner, g. hermanns, v. holstein, n. l. haag, and h. oechsner, “innovative additives for chemical desulphurization in biogas processes: a comparative study on iron compound products,” biochemical engineering journal, vol. 121, pp. 181-187, may 2017. [5] a. l. kohl and r. nielsen, gas purification, 5th ed. houston: gulf publishing company, 1997. [6] g. lastella, c. testa, g. cornacchia, m. notornicola, f. voltasio, and v. k. sharma, “anaerobic digestion of semi-solid organic waste: biogas production and its purification,” energy conversion and management, vol. 43, no. 1, pp. 63-75, january 2002. [7] s. a. marzouk, m. h. al-marzouqi, m. teramoto, n. abdullatif, and z. m. ismail, “simultaneous removal of co2 and h2s from pressurized co2-h2s-ch4 gas mixture using hollow fiber membrane contactors,” separation and purification technology, vol. 86, pp. 88-97, february 2012. [8] s. rasi, j. läntelä, a. veijanen, and j. rintala, “landfill gas upgrading with countercurrent water wash,” waste management, vol. 28, no. 9, pp. 1528-1534, 2008. [9] m. islamiyaha, t. soehartantoa, r. hantoroa, and a. abdurrahman, “water scrubbing for removal of co2 (carbon dioxide) and h2s (hydrogen sulfide) in biogas from manure,” issn 2413-5453, 2: 126-131, 2015. doi: http://dx.doi.org/10.18502/ken.v2i2.367. [10] r. kapoor, p. m. v. subbarao, shah, v. k. vijay, g. shah, s. sahota, and d. singh “factors affecting methane loss from a water scrubbing based biogas upgrading system,” applied energy, vol. 208, pp. 1379-1388, december 2017. [11] water quality protection division, environmental protection administration, executive yuan, taiwan, roc. 2017, “the emission standard for chemical industry stipulated by the environmental protection administration,” article 2, article 5, amended article 2-1, no. 1060101625 order of environmental protection administration, dated on december 25, 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-aiti#6047 90-105.docx advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 design and implementation of adaptive pid and adaptive fuzzy controllers for a level process station aparna venkataraman* department of electronics & instrumentation engineering, b. s. abdur rahman crescent institute of science & technology, chennai, india received 11 july 2020; received in revised form 31 october 2020; accepted 20 january 2021 doi: https://doi.org/10.46604/aiti.2021.6047 abstract this proposed work proposes the design and real-time implementation of an adaptive fuzzy logic controller (flc) and a proportional-integral-derivative (pid) controller for adaptive gain scheduling that can be configured for any complex industrial nonlinear application. initially, the open-loop test of the single-input single-output (siso) system, with nonlinearities and disturbances, is conducted to represent the mathematical model of the process around a set of equilibrium points. the adaptive controllers are then developed and deployed by using the national instruments reconfigurable input/output data acquisition device (ni rio), ni myrio-1900, and the control parameters are adapted in real-time corresponding to the changes in the process variable. the resulting servo and regulatory performance of the controllers are compared in matlab® software. the adaptive fuzzy controller is deduced to be the better controller as it can generate the desired output with quicker settling times, fewer oscillations, and negligible overshoot. keywords: adaptive pid, adaptive fuzzy, nonlinear system, level control, data acquisition 1. introduction the fluid level control is a severe problem in industries as an ineffective control action will cause critical complexities in process operation, which may disagree with the equilibrium of the process reaction. real-time level control is also a challenging problem because of inherent nonlinear characteristics, such as interaction effects, parametric uncertainties, and input dead time and measurement delays; these nonlinear features significantly affect the accuracy of industrial processes. most industrial processes deploy a conventional proportional-integral-derivative (pid) controller for its simple setup. the structure of the pid controller is widespread, and several thumb rules are available to tune its parameters [1-5]. however, in a nonlinear system, a controller built for a specific equilibrium point will not work satisfactorily at other equilibrium points because of system uncertainties resulting from the scaling of the process components. therefore, a precise control action cannot be achieved with such open-loop pid tuning schemes. in order to overcome the limitation of the pid controller in a nonlinear plant, gain scheduling is proposed. the scheduling of pid gains is a significant enhancement in the pid structure [1, 6] and is usually carried out to reduce the slow convergence of traditional pid controllers. the typical implementation of a pid controller with gain scheduling requires the development of mathematical process models around several equilibrium points and the estimation of corresponding pid gains. then, the controllers of each operating region would be combined into a single controller for the entire operation region of the plant [7]. * corresponding author. e-mail address: vaparna06@gmail.com advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 91 however, no algorithms can ascertain the different thumb rules, such as the optimal number of operating points and the appropriate process variable dynamics, to design a gain scheduling pid controller. there is also no practical technique to test the reliability and efficacy of a gain scheduled control system [8-11]. furthermore, one significant limitation of gain scheduling is its inability to achieve a high precision of stability by minimizing the effects of the external disturbances in the system [12]. gain scheduled pid is also a model-based design method, and any uncertainty in the process model might have a significant impact on the controller's performance. hence, it is necessary to use an algorithm with a simple structure that would not require knowledge about the process's mathematical model. therefore, this continues to be a research interest for various researchers to determine the most accurate and stable control method, which can also reject multiple disturbances. even though the gain scheduling pid control produces highly stable and precise control action, its dynamic response is usually inadequate, which leads to overshoot and substantial settling time. relatively, the fuzzy control logic is capable of excellent dynamic response in nonlinear and time-varying systems by generating outputs with lesser overshoot and response times. fuzzy logic control (flc) has rapidly evolved into one of the most successful theories for complex control systems. from control systems to artificial intelligence, fuzzy logic has been applied in many fields. fuzzy logic is a suitable alternative to pid structures for nonlinear and time-varying systems [13]. it reduces the oscillations of the manipulated variable around the setpoint, which leads to a quick convergence of the process variable. the most crucial advantage of fuzzy logic is that it does not require knowledge of the mathematical model. thus, it can effectively handle the parametric uncertainty, which makes it more robust than pid controllers [13-16]. however, for large time-delay systems, a fuzzy logic control scheme might not be considered suitable. it should also be noted that the complex structure of a fuzzy logic controller must be simplified before real-time implementation by combining the proportional error component and its derivative linearly [17-19]. in order to ensure a robust and stable control action, the fuzzy rule base should possess a linear dependence on the summed fuzzy inputs [20]. since every real-time industrial process is laden with intrinsic nonlinearities, disturbances, process variable saturation, hysteresis, and nonlinear flow dynamics, it is necessary to implement an adaptive controller with high disturbance rejection capability to achieve adequate control against these nonlinearities and time-varying disturbances [21]. in this proposed work, the advantages of both adaptive control and fuzzy logic control were incorporated by implementing an adaptive fuzzy controller, and its efficiency was compared to that of a gain scheduling pid controller. the various topics of this paper are arranged in the following manner: section 2 presents a brief description of the various adaptive pid and adaptive fuzzy control techniques employed in complex nonlinear industrial systems. section 3 details the hardware of the level process station. the mathematical modeling of the process is described in section 4. the controller design steps and the simulation results are explained in parts 5 and 6. the real-time implementation of the controllers and their corresponding results are presented in section 7. section 8 discusses the adaptive controllers' performance, and the concluding explanations about the suitable controller for the proposed system are provided in section 9. 2. study on adaptive pid and adaptive fuzzy control techniques several techniques are proposed in the literature to improve upon the limitations of traditional pid control scheme, namely, adaptive gain scheduling technique, adaptive pid design using the asynchronous advantage actor-critic (a3c) algorithm, pid control using model reference adaptive control (mrac) scheme, pid controller tuned with characteristics ratio assignment (cra) technique, and pid controller with decoupler and inverting decoupler. the gain scheduling strategy proposed in this work has been successfully implemented in several systems; sain and peczkowski [22-24] have implemented gain scheduling pid controllers for engine speed control for several nonlinear turbojet engines. aparna et al. [25] have successfully designed a gain scheduled multi-loop proportional-integral (pi) level controller advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 92 for a nonlinear interacting multiple-input multiple-output (mimo) conical tank system. åstrom [1] has implemented gain scheduling pid control in several systems such as car air-fuel ratio systems, ship steering systems, and effluent systems. many articles also elaborate on the implementation of fuzzy logic in industrial applications. zhou et al. [26] implemented an adaptive fuzzy-based pid control scheme to improve the controller's disturbance rejection capability in an inertially stabilized platform (isp). cheng et al. [27] developed an flc scheme to stabilize a double inverted pendulum system. mahapatro, subudhi, and ghosh proposed the design and implementation of an adaptive fuzzy pi controller [28] and adaptive fuzzy sliding mode controller (smc) [29] to reduce the chattering and to improve robustness in the liquid level control of a coupled tank system. tamilselvan and aarthy [30] proposed an flc using the kalman algorithm to control the fluid level in a conical tank system. sakthivel, anandhi, and natarajan [31] designed and implemented a fuzzy logic liquid level controller for a nonlinear spherical tank system with three operating regions. 3. process setup hardware in the level process station, the process tank level is controlled by regulating the fluid's inlet flow rate. a wheel flow meter and an orifice plate with a differential pressure transmitter (dpt) are used to measure the liquid's flow rate in the pipeline. a radio frequency (rf) capacitance level transmitter is used to measure the process tank level. initially, a pump with a discharge capacity of 1200 lph is used to fetch the water from the reservoir tank and discharge it to an equal percentage control valve. during the fluid flow through the orifice plate, a differential pressure is developed across it. the dpt, whose corresponding output range is between 4-20 ma, senses the differential pressure. this analog output is converted and scaled to 0-5 v and fed to the 12-bit analog-to-digital converter (adc) in national instruments reconfigurable input/output data acquisition device (ni rio), ni myrio-1900. (a) the level process station (b) the schematic diagram of the system fig. 1 the level process station and its schematic representation the adaptive pid or adaptive fuzzy control algorithm infers the corresponding digital output, which is later converted to an analog value of 0-5 v by a 12-bit digital-to-analog converter (dac). the dac output is fed to an electro-pneumatic (e/p) converter to generate a 3-15 psi output. the e/p converter's output manipulates the control valve's stem position to regulate the inlet flow rate, which eventually maintains the fluid level at the desired value. fig. 1 shows the level process station and its schematic diagram on which the adaptive pid and adaptive fuzzy controllers are implemented. advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 93 4. mathematical modeling the plant's open-loop response is recorded for different percentages of control valve opening, and the input/output (i/o) characteristics of the process are plotted. the piecewise linearization of the nonlinear process characteristics yields four operational areas depending on the change in the trajectory's gain. the operating regions' equilibrium points are chosen such that a noticeable difference in the process gain is visualized at each equilibrium point. the open-loop characteristics are linearized into four operational areas, as depicted in fig. 2. for each region, the transfer function is derived. the parameters of the transfer function for a first-order system with transportation lag, time constant (τ), delay time (td), and process gain (k) are found by using the cohen-coon two-point method [32], as shown in table 1. the system's gain is computed from the slope of the nonlinear regions, and the product between the operating area and the gain yields the time constant. an arbitrary value derived from the test results is chosen as the time delay in the transfer function. fig. 2 linearized i/o response for the level process table 1 transfer function for the various operating regions region level (cm) transfer function 1 0–2.4 1.377 4.5� � 1 �� 1.5�� 2 2.5–10.8 1.03 33� � 1 �� 2�� 3 10.9–13.6 0.98 12.75� � 1 �� 2.75�� 4 13.7–24.4 1 5.25� � 1 �� 0.95�� 5. controller design the design procedure and implementation of the adaptive gain scheduling pid controller and the adaptive fuzzy controller are explained in the following subsections. 5.1. design of adaptive gain scheduling pid controller famous and sophisticated cohen & coon tuning rules, (1) to (3), based on the process reaction curve method [32], was used in computing the gains of the adaptive pid controller (kc, ki, and kd) in each operating zone. the cohen-coon tuning method was chosen as it is a reliable and effective technique to generate a quick dynamic response in the proposed self-regulating level process. table 2 shows the gains computed for the adaptive pid in the various operating regions. 1 4 1 3 4 d c d t k k t τ τ     = +        (1) advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 94 32 6 1 *60; 13 8 d i d i d i t t t k t t τ τ    +      = =    +      (2) 4 2 *60; 11 d d d d d t t t k t τ    = + =      (3) where kc is the proportional gain, ti is the integral time (s), ki is the integral gain, td is the derivative time (s), and kd is the derivative gain. table 2 cohen-coon pid gains for all the operating regions region kc ki kd 1 1.079 9.091 0.003 2 5.179 6.370 0.003 3 4.160 3.448 0.002 4 2.377 4.167 0.004 once the pid controllers were designed for each operating region, the gain scheduling pid controller switched pid gains whenever a setpoint in a particular operating region was provided. this adaptive pid controller adopts online gain change depending on the process operating point and hence possesses better adaptability. 5.2. design of adaptive fuzzy controller the fuzzy logic control scheme is implemented by using natural language rules and is closer to human thinking than other control logic. fuzzy logic control can be implemented effectively in five significant steps [33-34]: (1) selection of fuzzy inference engine (2) design of the fuzzy inference system (3) formulation of the fuzzy rule base (4) fuzzification (5) defuzzification in the adaptive fuzzy controller design, mamdani fuzzy inference engine is chosen. a linear combination of error and derivative of the error is given as input to the fuzzy logic controller, and the fluid level is generated as output from the controller. a value of 0 to 100% is considered for the error and change in error inputs. the minimum and maximum permissible scale of the process variable, ranging from 0 to 25, is defined for the output. five membership functions are considered for all the variables, very low value (nb), low value (ns), median value (me), high value (ps), and very high value (pb). fig. 3 range of input membership function in the various operating regions fig. 4 range of output membership function in operating region 1 advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 95 the following fig. 3 depicts the input membership functions adopted in all the operating regions, and fig. 4 illustrates the output membership functions adopted in operating region 1. a combination of several fuzzy membership functions of various shapes and intervals is chosen to narrow down the optimal combination with the lowest mean average percentage error (mape). a 5x5 rule base, as given in table 3, is applied to tune the fuzzy logic controller in each operating region. minimum implication and centroid defuzzification methods are adopted to generate the crisp output. table 3 fuzzy rule base for the adaptive flc in operating region 1 error error� nb ns me ps pb nb ps ns me ps nb ns me ps ns ns ps me pb pb pb pb pb ps pb pb pb pb nb pb pb nb nb pb nb after membership functions and fuzzy rules are defined for each operating region, the adaptive fuzzy controller switches the fuzzy controller's rules and membership functions whenever a setpoint in a particular operating region is provided, as illustrated in fig. 5. fig. 5 the schematic diagram of an adaptive gain scheduling pid controller/adaptive flc 6. simulation results adaptive pid and adaptive fuzzy controllers are designed and tested with input disturbance and different setpoints in various operating regions. the better controller is realized by analyzing the setpoint tracking and input disturbance rejection capability. the following setpoints are considered that enclosed the entire operating zone of the plant, setpoint in operating region 1 level in tank = 2 cm setpoint in operating region 2 level in tank = 8 cm setpoint in operating region 3 level in tank = 12 cm setpoint in operating region 4 level in tank = 18 cm the controllers' response to the simulation tests is described in the following subsections. 6.1. servo response the setpoint tracking capability of both the adaptive gain scheduling pid controller and the adaptive fuzzy controller is compared for different setpoints in various operating regions. fig. 6 demonstrates the setpoint tracking capability of the advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 96 adaptive pid controller in the four operating zones. similarly, fig. 7 represents the adaptive flc's servo response in the operating regions 3 and 4. from the step-response characteristics of the controllers' servo response presented in table 4, it can be inferred that the controllers quickly track their setpoints. the servo control action of gain scheduling pid is faster than its counterpart, but it leads to overshoot and oscillations in the response, which is undesirable. with adaptive flc, its output response reaches a steady state quickly but with a minor steady-state error. fig. 6 the servo response of the adaptive pid controller in simulation (a) the simulated servo response in region 3 (b) the simulated servo response in region 4 fig. 7 the servo response of the adaptive flc in the operating regions 3 & 4 in simulation table 4 time-domain specifications of the servo response of the controllers in simulation region controller rise time (s) settling time (s) overshoot offset 1 adaptive gain scheduled pid 0.508 8.105 0.444 adaptive flc 4.089 7.632 0.061 2 adaptive gain scheduled pid 0.994 9.905 0.340 adaptive flc 3.895 7.073 0.075 3 adaptive gain scheduled pid 1.258 8.627 0.133 adaptive flc 3.875 7.009 0.010 4 adaptive gain scheduled pid 1.509 9.306 0.151 adaptive flc 1.975 6.942 0.031 6.2. servo & regulatory response a disturbance of +10% of the setpoint values is applied at 20 s, 60 s, 100 s, and 120 s to simulate input disturbance in each operating region so that the servo and regulatory action of the gain scheduling pid controller to a step input and a disturbance can be analyzed simultaneously. fig. 8 illustrates the servo and regulatory responses of the gain scheduling pid controller subjected to varying setpoints and input disturbance in each operating region. the response within the encircled area in fig. 8 depicts the regulatory action of the adaptive pid controller. advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 97 fig. 8 the servo and regulatory responses of the adaptive pid controller in simulation (a) the simulated servo & regulatory responses in region 3 (b) the simulated servo & regulatory responses in region 4 fig. 9 the servo and regulatory responses of the adaptive flc in the operating regions 3 & 4 in simulation similarly, the setpoint tracking capability and the disturbance rejection capability of the adaptive fuzzy controller are tested by applying varying setpoints and a step input change of '1' at 20 s in each operating region. the corresponding result in fig. 9 shows the servo and regulatory control action of the adaptive fuzzy controller in the operating regions 3 and 4. it can be seen from figs. 8, figs. 9, and the time-domain specifications of the servo and regulatory responses described in table 5 that the controllers exhibit similar behavior as with their servo control loop. the adaptive pid is capable of quicker control action with overshoot, and the adaptive flc is the fastest to reject the disturbance and track the setpoint with a small offset. table 5 the time-domain specifications of the servo and regulatory responses of the controllers in simulation region controller rise time (s) settling time (s) overshoot offset 1 adaptive gain scheduled pid 0.508 7.125 0.444 adaptive flc 4.089 1.431 0.061 2 adaptive gain scheduled pid 0.994 6.179 0.340 adaptive flc 3.895 0.869 0.075 3 adaptive gain scheduled pid 1.258 5.985 0.133 adaptive flc 3.875 0.234 0.009 4 adaptive gain scheduled pid 1.509 6.805 0.151 adaptive flc 1.975 1.717 0.031 7. real-time implementation & results the adaptive pid and adaptive fuzzy controller designed in the simulation are implemented in real-time using ni myrio-1900 reconfigurable i/o data acquisition device that comprises xilinx processor and supports real-time programming to generate quicker response times in applications. fig. 10 depicts the schematic diagram for the real-time implementation of the adaptive control loop. fig. 11 illustrates the wiring diagram to connect the ni myrio-1900 with the level process station. advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 98 in the proposed system, the dpt's output is converted and scaled to 0-5 v and fed to the differential analog inputs (ai+ and ai-) of the 12-bit adc in ni myrio-1900. the data from ni myrio are scaled to the operating range of fluid level and fed to the adaptive pid and adaptive fuzzy control loop developed in labview software, as shown in figs. 12 and 13, respectively. the configurations of the offline controllers are assumed for the real-time implementation, and the adaptive controllers are configured in the front panel and block diagram of the labview software. fig. 10 the schematic diagram for the real-time implementation of the adaptive control loop in the plant fig. 11 the wiring diagram to connect the ni myrio-1900 with the level process station fig. 12 the block diagram of the adaptive gain scheduling pid control loop in labview when the desired setpoint is provided, the controller configurations are switched to the specific operating conditions, and the corresponding level output is obtained. this level output is then scaled to an analog value of 0-5 v by a 12-bit dac before it is fed to the analog output channel (ao) of ni myrio-1900. the output voltage is provided to an e/p converter whose output regulated the control valve's stem position to maintain the fluid level of the process tank at the desired value. advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 99 fig. 13 the block diagram of the adaptive flc loop in labview the experiments are conducted with similar setpoints in the simulation to study the efficacy of adaptive pid and adaptive fuzzy controller in the process plant. the servo and regulatory capability of the adaptive controllers in the real-time plant are discussed in the following subsections. 7.1. setpoint tracking capability the servo capability of the controllers is tested by providing setpoints in different operating regions. a different setpoint value is provided for every 150 s to analyze the servo behavior of the adaptive gain scheduling pid controller. similarly, the adaptive flc's servo control capability is tested by providing different setpoints for every 300 s. fig. 14 depicts the resulting servo response of the adaptive pid controller in the four operating regions, and fig. 15 portrays the servo response of adaptive flc in operating regions 3 and 4. fig. 14 the servo response of the adaptive pid controller using ni myrio-1900 (a) the real-time servo response in region 3 (b) the real-time servo response in region 4 fig. 15 the servo response of the adaptive flc in the operating regions 3 & 4 using ni myrio-1900 advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 100 the servo response of the controllers can be inferred from the step-response characteristics given in table 6. the adaptive pid can generate a quicker response with significant overshoot, oscillations, and offset. in contrast, the adaptive flc can quickly attain a steady state with no overshoot but with a significant steady-state error. table 6 the time-domain specifications of the servo response of the controllers in real-time plant region controller rise time (s) (approx.) settling time (s) (approx.) overshoot (approx.) offset (approx.) 1 adaptive gain scheduled pid 4.145 25.746 1.648 1.769 adaptive flc 18.963 22.011 1.998 2 adaptive gain scheduled pid 6.470 39.614 1.010 1.572 adaptive flc 27.322 34.785 1.627 3 adaptive gain scheduled pid 9.196 63.416 0.068 1.477 adaptive flc 43.198 55.303 1.817 4 adaptive gain scheduled pid 12.649 106.794 0.022 0.600 adaptive flc 69.027 91.976 0.973 7.2. setpoint tracking & input disturbance rejection capabilities the adaptive controllers' servo and regulatory responses are tested by changing the setpoint and the inlet hand valve position for 20 s. besides the inherent disturbances in a real-time plant, this change in the inlet hand valve's position for a specific period mimics input disturbance as the intrinsic characteristics of an equal percentage control valve are not matched to the process's flow conditions in an industrial setup. therefore, the steady-state flow rate corresponding to the controller output is not linear, and this behavior is used in the analysis of the servo and regulatory responses of the controllers. fig. 16 the servo and regulatory responses of the adaptive pid controller using ni myrio-1900 (a) the real-time servo & regulatory responses in region 3 (b) the real-time servo & regulatory responses in region 4 fig. 17 servo and regulatory responses of the adaptive flc in the operating regions 3 & 4 using ni myrio-1900 advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 101 fig. 16 illustrates the servo and regulatory responses of the adaptive pid controller to varying setpoints and input disturbance in the four operating regions. fig. 17 presents the servo and regulatory responses of the adaptive fuzzy controller in operating regions 3 and 4, and the response within the encircled area in figs. 16 and 17 depicts the controllers' regulatory action. from the responses depicted in figs. 16, figs. 17, and the time-domain specifications of the servo and regulatory responses stated in table 7; it can be inferred that the controllers are capable of effective disturbance rejection and setpoint tracking. although the adaptive pid controller exhibits quicker control action, it generates significant overshoot, oscillations, and offset in the response. in contrast, the adaptive flc displays better regulatory capabilities than its counterpart by generating steady-state output quickly with no overshoot but with a significant offset. table 7 time-domain specifications of the servo and regulatory responses of the controllers in real-time plant region controller rise time (s) (approx.) settling time (s) (approx.) overshoot (approx.) offset (approx.) 1 adaptive gain scheduled pid 4.145 29.211 1.648 1.769 adaptive flc 18.963 19.030 1.997 2 adaptive gain scheduled pid 6.470 24.233 1.010 1.572 adaptive flc 27.322 12.561 1.627 3 adaptive gain scheduled pid 9.196 29.970 0.068 1.478 adaptive flc 43.198 13.154 1.817 4 adaptive gain scheduled pid 12.649 26.983 0.022 0.598 adaptive flc 69.027 18.431 0.972 8. discussions the setpoint tracking and the disturbance rejection capability of the simulated controllers and the real-time controllers are compared and depicted in figs. 18 to 21. the servo response of the controllers in the simulation in the operating regions 3 and 4 is compared in fig. 18. similarly, the servo and regulatory responses of the controllers in the simulation in the operating regions 3 and 4 are compared and depicted in fig. 19, wherein the response within the encircled area illustrates the adaptive controllers' regulatory action. (a) the simulated servo responses in region 3 (b) the simulated servo responses in region 4 fig. 18 the comparison of servo response of the controllers in the operating regions 3 & 4 in simulation although the adaptive pid controller responds quickly to variations in the process variable, the response is rather abrupt, leading to overshoots and sharp oscillations. meanwhile, the response of the adaptive fuzzy controller is smooth without fluctuations. further, fig. 20 demonstrates the servo behavior of the proposed controllers in the operating regions 3 & 4 in the process plant. fig. 21 shows the servo and regulatory behavior of the adaptive controllers in real-time in the operating regions 3 & 4, wherein the response within the encircled area depicts the controllers' regulatory action. advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 102 (a) the simulated servo & regulatory responses in region 3 (b) the simulated servo & regulatory responses in region 4 fig. 19 the comparison of servo and regulatory responses of the controllers in the operating regions 3 & 4 in simulation from the responses illustrated in fig. 20, fig. 21, and the time-domain specifications stated in table 8, it can be visualized that a large offset is generated by both the controllers in the real-time plant, even if the adaptive pid controller generates virtually no offset in simulation. hence, even though the adaptive pid exhibits excellent steady-state behavior in the simulation, both the controllers generate a residual steady-state error, which leads to poor steady-state behavior in the real-time plant. (a) the real-time servo responses in region 3 (b) the real-time servo responses in region 4 fig. 20 the comparison of servo response of the controllers in the operating regions 3 & 4 using ni myrio-1900 (a) the real-time servo & regulatory responses in region 3 (b) the real-time servo & regulatory responses in region 4 fig. 21 the comparison of servo and regulatory responses of the controllers in the operating regions 3 & 4 using ni myrio-1900 the adaptive pid controller's dynamic property is also weak, even if the control action is highly stable in the process plant. meanwhile, the adaptive fuzzy controller exhibits excellent dynamic control capability with reduced settling times, overshoot, and oscillations in the presence of disturbances. however, one major disadvantage of the adaptive fuzzy controller is that expert knowledge is necessary to configure the controller for variations of process variables, unlike in adaptive pid, where changes require no estimation or computation as the controller is tuned for each change beforehand. advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 103 nonetheless, the adaptive fuzzy controller is preferable in the proposed real-time plant than its counterpart as the fuzzy logic algorithm does not rely on the mathematical model but the dynamics of the process. thus, the adaptive flc designed with adequate knowledge of the process dynamics helps generate the desired output response with less overshoot and oscillations despite inherent model uncertainties, disturbances, and nonlinearities. table 8 the comparison of the response of the controllers in simulation and real-time plant servo & regulatory response simulation real-time plant adaptive gain scheduled pid controller adaptive flc adaptive gain scheduled pid controller adaptive flc rise time quick slow quick slow settling time slow quick slow quick overshoot more no slightly more no offset no negligible significant significant 9. conclusions in this proposed work, a single-input single-output (siso) system was modeled around a set of operating points because of system nonlinearities resulting from the inherent hysteresis of components, model uncertainties, and other disturbances. an adaptive gain scheduling pid controller and an adaptive fuzzy controller were then designed and simulated for the modeled system. the configurations and tuning parameters of the simulated controllers were used to implement the controllers in real-time using the ni myrio-1900 data acquisition device. the efficacy of the controllers in real-time experiments was studied by analyzing their servo and regulatory responses. both the adaptive controllers showed poor steady-state behavior in the face of uncertainties and disturbances. meanwhile, the adaptive fuzzy controller's dynamic control behavior was marginally superior to its counterpart with reduced settling times and overshoot. therefore, it was concluded from the adaptive controllers' response that the adaptive flc is better suited to generate the desired output from the proposed real-time plant with quicker settling times and negligible overshoot than the adaptive pid controller despite the adaptive flc's insufficient steady-state control action. the author aims to reduce the residual steady-state error of the controllers in future works by adopting advanced meta-heuristic optimization algorithms and robust algorithms to tune the gain scheduling pid controller. similarly, incorporating a self-tuning logic in the adaptive fuzzy controller would drastically improve the steady-state control action in future research works, owing to the automatic generation of rules based on the initial pre-defined conditions, process trends, and the adaptation law. acknowledgement the author is very grateful to dr. u. sabura banu, professor at b. s. abdur rahman crescent institute of science and technology, for her insightful ideas. abbreviations a3c asynchronous advantage actor-critic adc analog-to-digital converter ai analog input ao analog output cra characteristics ratio assignment dpt differential pressure transmitter dac digital-to-analog converter e/p electro-pneumatic advances in technology innovation, vol. 6, no. 2, 2021, pp. 90-105 104 flc fuzzy logic control i/o input/output isp inertially stabilized platform mape mean average percentage error mimo multiple-input multiple-output mrac model reference adaptive control ni rio national instruments reconfigurable input/output pi proportional-integral pid proportional-integral-derivative rf radio frequency siso single-input single-output smc sliding mode controller conflicts of interest the authors declare no conflict of interest. references [1] k. j. åström, adaptive control, dover books on electrical engineering, 2nd ed. berlin: heidelberg, 1991. 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[34] l. a. zadeh, “fuzzy logic,” computer, vol. 21, no. 4, pp. 83-93, april 1988. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). aiti#7109_in press__20210618 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 driving assistance system with lane change detection jia-shing sheu 1,* , chun-kang tsai 1 , po-tong wang 2 1 department of computer science, national taipei university of education, taipei, taiwan 2 department of mechanical engineering, minghsin university of science and technology, hsinchu, taiwan received 04 february 2021; received in revised form 10 march 2021; accepted 12 march 2021 doi: https://doi.org/10.46604/aiti.2021.7109 abstract in this study, a simple technology for a self-driving system called “driver assistance system” is developed based on embedded image identification. the system consists of a camera, a raspberry pi board, and opencv. the camera is used to capture lane images, and the image noise is overcome through color space conversion, grayscale, otsu thresholding, binarization, erosion, and dilation. subsequently, two horizontal lines parallel to the x-axis with a fixed range and interval are used to detect left and right lane lines. the intersection points between the left and right lane lines and the two horizontal lines can be obtained, and can be used to calculate the slopes of the left and right lanes. finally, the slope change of the left and right lanes and the offset of the lane intersection are determined to detect the deviation. when the angle of lanes changes drastically, the driver receives a deviation warning. the results of this study suggest that the proposed algorithm is 1.96 times faster than the conventional algorithm. keywords: computer vision, embedded system, lane-shift detection, driver assistance system 1. introduction with the increasing use of vehicles, frequent traffic accidents occurs worldwide. to reduce the casualties caused by traffic accidents, this study proposes a lane-shift detection system that combines an embedded device and image identification. in this system, the embedded device and a camera module are used to capture lane images. the captured images are processed through grayscale, binarization, erosion, and dilation in order to filter image noise and achieve lane-line labeling. when an irregular deviation from a lane line is identified, the driver is automatically warned of the deviation. real-time lane detection using embedded devices is often impossible because of the high-performance hardware required by current lane detection algorithms. in the proposed algorithm, a substantial reduction in performance is required for lane detection to maintain the lane line detection in conventional algorithms. in addition, traditional algorithms depend on the use of masks or perspective transformation [1] to obtain a region of interest [2], but these prior manual adjustments and lane slope restrictions are not applicable to any road. to overcome the shortcomings of traditional algorithms, this study proposes a lane detection algorithm that can greatly reduce lane-image-processing time and does not depend on masks and perspective transformation. the proposed intersection detection algorithm can not only run smoothly on embedded devices, but can also be adapted to lane lines of different shapes. because the intersection detection algorithm does not use the region of interest algorithm, it can avoid mismatches between the region of interest and the lane area. * corresponding author. e-mail address: jiashing@tea.ntue.edu.tw tel.: +886-9-38397255; fax: +886-2-27375457 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 2. literature review and methodology a lane departure detection system is an alarm system that helps drivers avoid unintentionally switching lanes. driver assistance systems, which debuted in 2000, reduce the number of vehicle crashes by helping drivers preemptively avoid accidents [3]. many new vehicles are equipped with such a system. fig. 1 traditional lane detection algorithm fig. 1 presents the steps involved in the most current lane detection algorithms [4-7]. in this study, a new lane detection algorithm is proposed to improve the execution efficiency of traditional lane detection algorithms. image processing in traditional algorithms can be roughly divided into five steps: perspective transformation, region of interest extraction, grayscale conversion [8], canny edge detection [9], and hough transformation [10]. in the proposed method, grayscale is retained; perspective transformation, region of interest extraction, canny edge detection, and hough transformation are removed. in addition, image binarization, image morphological erosion, expansion operation, and the algorithm for horizontal line intersection detection are added to the method of detecting lane lines. this method is not limited by the region of interest of the traditional algorithm. the new algorithm can be used to retain a large amount of the lane image information, adapt to different lane images, and provide rapid lane detection real-time data to determine whether the vehicle is deviating. the first step of image processing is grayscale conversion. an original image captured from a camera module [11] is in the rgb color space, and such colored images lead to poor performance of direct calculations and consequent faulty lane line determinations. the grayscale equation (eq. (1)) can be used to transform an rgb color space into a ycbcr [12] color space. as a result, the computational amount is reduced from 24 bits per pixel to 8 bits per pixel. this step is employed to improve the calculation efficiency and accuracy of lane detection. then, the y brightness obtained in the ycbcr color space can be considered the grayscale result. 0.299 0.578 0.114y r g b= + + (1) the second step is canny edge detection, a compound edge detection algorithm that integrates a gaussian filter [13], which is used to determine the intensity gradient of images, nonmaximum suppression [14], double threshold, and edge tracking through hysteresis for practicing edge detection. gaussian filtering can be effectively used to reduce the noise generated by grayscale images, and its formula is as follows: 2 2 22 2 1 ( , ) 2 x y g x y e σ πσ + = (2) where sigma (�) of approximately 0.68-0.95 is suitable (normal distribution) and is user-defined. the commonly used 3 × 3 gaussian filter matrix is as follows: 1 2 1 1 2 4 2 16 1 2 1 k    =      (3) the next step is to find the intensity gradient of images. lane lines can be accurately detected by using canny edge detection to select the sobel [15] operator as a kernel for calculating the intensity gradient of images, given by the following equation: 138 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 2 2 -1 1 0 1 1 2 1 2 0 2 , 0 0 0 , = , =tan ( ) 1 0 1 1 2 1 x x y x y y g g g g g g g −       = − = +       − − − −    θ (4) non-maximum suppression is divided into three angles, � = 0°, 45°, and 135°. the algorithm is employed to determine a point with the highest gradient change in each angle and remaining the points in the same direction. figs. 2 and 3 present the example of nonmaximum suppression. fig. 2 nonmaximum suppression fig. 3 matrix with nonmaximum suppression to suppress the noise and color changes of images, most algorithms use double thresholds for filtering, which can be achieved with high and low thresholds. the nonmaximum suppression algorithm is as follows: first, let x be the gradient intensity value of an edge pixel. (a) when x is higher than the high threshold value, x is marked as a strong edge pixel. (b) when x is less than the high threshold and greater than the low threshold, x is marked as a weak edge pixel. (c) when x is lower than the low threshold value, x is suppressed. the last step of canny edge detection is edge tracking using hysteresis. however, weak edge pixels are controversial because they can be extracted from real edges and noise/color changes. to determine whether weak edge pixels should be judged in the real edge, we use eight adjacent pixels around the weak edge. according to the judgment method, if the gradient intensity value of an adjacent pixel is higher than that of the strong edge pixel, the weak edge pixel is considered the real edge. otherwise, it is suppressed. traditional image processing uses the hough transform to detect lines. hough transform is an algorithm used for finding straight lines in images. the algorithm uses a point-slope formula to convert the original pixel points of a cartesian coordinate system into the polar-coordinate system and a voting mechanism to find the required (γ, �). fig. 4 hough transform in fig. 4, γ is the shortest straight-line distance between the origin and line, and � is the angle between the shortest line and the x-axis. the hough transform is an algorithm used to determine the γ and � coordinates, and after the determination of these two values, it can be used to create a straight line on the image. the normal representation of a line given by the following equation is used in this study: 139 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 cos sinx yγ θ θ= + (5) where � is the angle between the normal straight line, and the x-axis and γ is the normal form of the length. this method of computation can solve an infinite number of problems by using the characteristics of a triangle function despite being limited to a certain range of angles. 3. system structure this study employs image processing technology to realize a lane deviation warning system. continuous images captured by the embedded camera are used as input. after image processing, it is possible to judge whether the lane is offset by the change of lane line angle. in the case of deviation, the system warns drivers. fig. 5 illustrates the system architecture obtained by using icam definition method 0 (idef0) [16]. idef0 is a part of the idef family of modeling languages used in software engineering, and is built on the functional modeling language of structured analysis and design technique (sadt). this study is divided into three parts, namely image processing (fig. 6), deviation judgment (fig. 7), and notification to drivers. fig. 5 system structure fig. 6 image processing fig. 7 offset judgment 140 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 3.1. part 1: image processing (1) grayscale: the rgb color space of the lane image captured by the camera is converted to a ycbcr color space by using eq. (1). (2) otsu thresholding [17]: otsu is used to perform automatic image thresholding. the purpose of this algorithm is to return a threshold that separates pixels into two classes, the foreground and the background. this threshold is determined by minimizing intraclass intensity variance or by maximizing interclass variance. in this study’s proposed system, otsu thresholding is used to separate the lane line from the background. (3) erode [18]: by using an erosion morphology algorithm, the majority of the noise in binary black-and-white lane maps can be filtered out, and the main lane lines can be retained. in this part, we use a 5×5 rectangle matrix to erode the lane map. (4) dilate [19]: lane lines narrowed using erosion are expanded back to their original width to facilitate the next step in lane detection. in this step, we use the 5×5 rectangle matrix to dilate the lane map. by using dilate (and gate) characteristics, the operation time is reduced by half. (5) intersection point detection: two horizontal lines parallel to the x-axis with a fixed range and interval are used for intersection detection. these two horizontal lines are used to determine four intersection coordinates between the lane line and two horizontal lines. this study simplifies the intersection detection method. given a preset range between y1 and y2, as the basic y-coordinate of the two horizontal lines, the overlapping parts of the two horizontal lines and the lane line are used to perform a grouping calculation, and the four possible coordinates (ly1, y1), (ry1, y1), (ly2, y2), and (ry2, y2) can be obtained. the four coordinates are used to extend the lane line, find the intersection of the lanes, and present the slope of the left and right lanes, as shown in fig. 8. fig. 8 intersection point detection 3.2. part 2: offset judgment (1) calculation of the slope and two lane line intersection coordinates: the coordinates of the four intersection points obtained from part 1 are used to calculate the slope of the left and right lane lines the intersection points of the extended lane lines and the left and right lane lines are marked [20]. (2) comparison with a previous frame: the slope of the left and right lane lines and the intersection coordinates of the extended left and right lane lines can be compared with the data in previous frames to determine whether the vehicle has positional offset. (3) deviation determination: to prevent obtaining unclear lane lines or noise interference, the offset data of the previous 15 frames are stored in buffer and subsequently compared with the current data to increase the judgment accuracy. 3.3. part 3: notify the driver (1) when abnormal deviations in slope and intersection coordinates occur, a warning is sent to alert the driver. 141 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 4. experiment results the experimental equipment consists of a raspberry pi board and a camera for still image processors, as listed in table 1. the experimental system is also shown in fig. 9. table 1 experimental equipment components specification operating system raspbian central processing unit arm cortex-a72 random access memory 4 gb (lpddr4) camera 8mp raspberry pi camera module (v2) fig. 9 raspberry pi combined with the camera module and a 7-inch touch display raspberry pi is a popular embedded system developed by raspberry pi foundation in the united kingdom. the processor used in the experiment is a broadcom bcm2711 soc with a 1.5-ghz 64-bit quad-core arm cortex-a72 processor. raspberry pi has a 40-pin general purpose input-output (gpio) connector that enables users to connect peripherals such as lcd1602 modules and sensors through inter-integrated circuit (i²c), universal asynchronous receiver-transmitter (uart), and serial peripheral interface (spi). to reduce operation time and maintain accuracy, the 8-mp raspberry pi camera module (v2) is used to continuously capture images [21-22] with 640 × 480 pixel resolution (fig. 10), and the rgb image is returned to the raspberry pi by using eq. (1) for grayscale pretreatment. matrix data are obtained from opencv to store the grayscale images (fig. 11) in the memory. fig. 10 rgb image fig. 11 grayscale image after the grayscale conversion, image binarization is performed to accurately separate the lane lines from the asphalt. in this step, the otsu algorithm is used to determine an adaptive threshold, and the threshold is used as a boundary, as shown in fig. 12. the pixel values which are lower and higher than this threshold value are classified as black (lightness y = 0) and white 142 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 (lightness y = 255), respectively. after binarization, black and white images are subjected to the erosion morphology for filtering white impurities remaining in the binarization image and increasing the accuracy of lane line detection. in the erosion, 5×5 rectangular erosion elements are used, and fig. 13 presents the erosion results. fig. 12 otsu thresholding image fig. 13 erosion image after erosion calculation, the lane line shape is no longer true. therefore, using an expansion operation in typology is necessary to restore the eroded lane line to obtain an appearance consistent with the actual situation. moreover, in the expansion operation, 5×5 rectangular elements are used. fig. 14 presents the results. in intersection detection, two horizontal lines parallel to the x-axis are used to determine the intersection with the lane line. the method involves scanning for specific y coordinates in the image, recording the x coordinates of white points, and dividing the points into “left” and “right” groups based on their x coordinates. in this manner, two specific y coordinates are selected for scanning simultaneously, and the intersection of horizontal lines 1 and 2 with the left and right lane lines is obtained, which leads to four intersection points. in this step, the vehicle movement causes the y coordinates of lane line to not exhibit a fixed relationship. approximately 10 groups of horizontal lines with different y coordinates are detected simultaneously during calculation to improve the detection accuracy of intersection points. fig. 15 illustrates the detection of intersection points by using two red horizontal lines, and the blue circle represents the coordinates of four intersection points. fig. 14 dilation image fig. 15 intersection point detection the first step of the migration judgment is performed to calculate the point of intersection of the slope and the two lines, as shown in fig. 16. by connecting the intersection points of left and right groups and extending them, the intersection coordinates of the slope of left and right lane lines and the lane lines of both sides are obtained. the intersection coordinates of left and right lane lines and the lane slope are stored in buffer, and the next frame of the image is captured using the camera. in the practical method of deviation judgment, the intersection coordinates of left and right lane lines and the lane slope of this frame with the historical data of the previous 15 frames stored in buffer are compared. when abnormal deviations in slope and intersection coordinates occur, a warning is sent to alert the driver of lane deviation. 143 advances in technology innovation, vol. 6, no. 3, 2021, pp. 137-145 fig. 16. intersection point of slope and two lines table 2 compares the conventional algorithm [23] with the intersection detection algorithm proposed in this paper. the terms of comparison include the time spent on each step of image processing for each frame and accuracy. table 2 experimental results procedure / algorithm traditional lane detection intersection point detection grayscale 0.005 sec 0.005 sec canny edge detection 0.018 sec hough transform 0.023 sec otsu thresholding 0.005 sec erode 0.007 sec dilate 0.004 sec intersection point detection 0.001 sec 0.003 sec sum (sec)/frame 0.047 sec/frame 0.024 sec/frame accuracy 0.981 0.924 *accuracy = (number of detected/actual number of lanes) 5. conclusions the intersection detection algorithms proposed in this study achieved a higher testing efficiency than the traditional lane detection algorithms did, and can be used to determine whether a vehicle is in the middle of a lane. the test results revealed that the proposed algorithm was 1.96 times faster than the conventional algorithm at a speed of 90 km/h on a highway. moreover, the system can determine whether a vehicle is turning, as well as detect if the external environment causes the slope of the lane to have an irregularly large change in angle and send a warning to the driver. however, because lane detection depends on white pixels for group judgment after binarization, judgment errors can occur when white road signs are located on the lanes or when white vehicles are under strong light. these situations may require additional lane clustering to reduce the likelihood of judgment errors. conflicts of 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[23] j. h. yoo, s. w. lee, s. k. park, and d. h. kim, “a robust lane detection method based on vanishing point estimation using the relevance of line segments,” ieee transactions on intelligent transportation systems, vol. 18, no. 12, pp. 3254-3266, december 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 145 template encit2010 advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 combining cloud computing and artificial intelligence scene recognition in real-time environment image planning walkable area jia-shing sheu * , chen-yin han department of computer science, national taipei university of education, taipei, taiwan received 18 may 2019; received in revised form 11 june 2019; accepted 20 august 2019 doi: https://doi.org/10.46604/aiti.2020.4284 abstract this study developed scene recognition and cloud computing technology for real-time environmental imagebased regional planning using artificial intelligence. tensorflow object detection functions were used for artificial intelligence technology. first, an image from the environment is transmitted to a cloud server for cloud computing, and all objects in the image are marked using a bounding box method. obstacle detection is performed using object detection, and the associated technique algorithm is used to mark walkable areas and relative coordinates. the results of this study provide a machine vision application combined with cloud computing and artificial intelligence scene recognition that can be used to complete walking space activities planned by a cleaning robot or unmanned vehicle through real-time utilization of images from the environment. keywords: tensorflow, computer vision, neural network, scene recognition, cloud computing 1. introduction with the rapid development of technology, high-quality digital cameras have become commonly used for acquiring images. these cameras are used in mobile phones, personal digital assistants, robots, medical systems, and surveillance and home security systems. with machine learning and neural operations, the image in the cloud can be easily identified. this study primarily used cloud resources currently available to upload real-time images from the environment obtained using a digital camera to the cloud and cooperate with cloud machine learning and image recognition for identifying different objects in the real-time image. when objects in a live image can be successfully identified, the environmental conditions observed in the live image can be further distinguished. this study used these resources to map real-time images from the environment to walkable areas by combining images obtained using digital cameras, which can be used with eye-like cameras when combined with cloud machine learning and neural recognition. in the study, section 2 provides a review of the literature and methodology. the structure of the system is discussed in section 3. design and experiments are provided in section 4. finally, conclusions are provided in section 5. 2. literature review and methodology an artificial neural network is a mathematical model based on a neural network system that mimics humans. the neural network aims to establish a neural network model that mimics biological perception in a computer and uses this mathematical statistical model to optimize data learning. in the cognitive system of artificial intelligence, the use of neural network-like algorithms is more advantageous than formal logic inference algorithms. because the neural network has nonfixed, nonconvex, nonlinear, and nonlimiting characteristics, different structures, functions, and learning algorithms can be used [1-3]. neural networks can be classified into various types, such as perceptual neural networks, linear neural * corresponding author. e-mail address: jiashing@tea.ntue.edu.tw tel.: +886-2-27321104 ext. 55425; fax: +886-2-27375457 advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 11 networks, inverted-transitive neural networks, and enhanced neural networks. because an inverse-transfer-like neural network can approximate any function with arbitrary precision under appropriate parameter settings, it can effectively predict the problem and provide functions such as environment perception, pattern recognition, and prediction. neural networks have been applied in many fields, including emotion perception, handwriting recognition, image recognition, and language translation [4-7]. a neural network generally has several levels, and each level can provide a sufficient number of neurons. each neuron adds up the input of the previous layer of neurons and enters the conversion of an activation function. each neuron has a distinct connection with the neurons of the subsequent layer, and thus, the output value of the upper layer of neurons is weighted and passed to the neurons of the subsequent layer. the neurons in the same layer are not connected and are distinct [8-9]. fig. 1 neural network-like simulation of how a single neuron operates the neural network is represented by numerous single neurons as shown in fig. 1, and comprises the following components: (1) inputs: receive signals from external or upper neurons. (2) weights: the memory of the neural network. the number of weights corresponds to the number of inputs in the input layer; that is, one weight corresponds to one input, which is multiplied by a conversion function and then added to the other values. (3) transfer function: the transfer function accumulates the product of all input values and weight values and then enters the activation function. (4) threshold: each neuron has a threshold. when the product value is accumulated by the conversion function, the offset value is added. the excitation function is provided to determine whether the signal needs to be output downward. that is, partial migration is used to control the continuation of the value. (5) activation function: an excitation function of the neural network introduces the characteristics of the nonlinear output, and thus, the neural network can perform mapping to learn complex functions (6) outputs/activation: the output values mapped using the excitation function can be used as inputs to the subsequent layer of neurons. advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 12 the architecture of the neural network connects the aforementioned single neurons to form a model. some commonly used neural network architectures are inverted neural networks, convolutional neural networks, and recurrent neural networks. 3. system structure the study is primarily based on a neural network-based regional identification system, its focus being on detecting walkable areas. by inputting images to a pre-trained neural network, the objects in the images can be identified. the empty areas between objects indicate walkable areas. fig. 2 presents the architecture of the system obtained from using ief0 [10]. to achieve to mark walkable areas and relative coordinates, this study is divided into three parts: (1) the first part constitutes neural network object identification. when the image enters the neural network, the trained model is used to load the images into the personal computer, identify the object position, and predict the score and object name. (2) the second part involves finding the path. by using the object position and coordinates obtained using the neural network, the distance between the objects is calculated, and the shortest distance between objects is identified to determine the position of the empty area as shown in fig. 3. (3) the third part includes path marking. the two points with the shortest path are connected. the enclosed space inside the line is the walkable area primarily discussed in this paper as shown in fig. 4. fig. 2 the architecture of the whole system fig. 3 the architecture of object detection advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 13 fig. 4 the architecture of walkable area marked this experiment used tensorflow as the core machine learning framework and an open source project tensorflow object detection application programming interface [11] as the core of object recognition, where the source code allows the use of trained models that meet their requirements. the pretraining model compiled using the tensorflow detection model zoo was used in this study. the models used for object recognition were faster_rcnn_inception_v2_atrous_coco, ssd_mobilenet_v1_coco, and ssd_mobilenet_v1_fpn_coco. with the bounding box coordinates of the object, the distance between all bounding boxes can be calculated. the algorithm uses the distance between each point to select the shortest path, which is considered a part of the walkable area and is connected into a large block through the plurality of lines. according to an axiom in the euclidean geometry system, “there are two points and only one line,” and each bounding box has four points. thus, for n bounding boxes, the following general formula can be used in eq. (1): 4 2 2 4n n n            (1) in any two bounding boxes, distance d between any two points is measured, which can be recorded as 𝑷𝟏(𝒙𝟏, 𝒚𝟏) and 𝑷𝟐(𝒙𝟐, 𝒚𝟐). the distance between all points is calculated using eq. (2). for each length comparison, the two shortest distance between all bounding boxes is selected, and starting and ending point coordinates are recorded. 2 2 2 1 2 1 ( ) ( )d x x y y    (2) the start and end point coordinates are obtained using the aforementioned method, and the line connecting the points can form a closed area, which is the walkable area discussed by the research institute. 4. experimental results table 1 graph representations components specification operating system debian 9 central processing unit amd ryzen 7 2700x random access memory ddr4-3200 16gb graphics processing unit nvidia gtx1080ti a car combined the raspberry pi and cmos camera is used to capture the environmental image as shown in fig. 5. the raspberry pi is a popular embedded system, which is developed by the raspberry pi foundation in the united kingdom. the processor is boardcom bcm2837 soc with a 1.2ghz 64-bit quad-core arm cortex-a53 processor. raspberry pi provides 40-pin general purpose input-output (gpio) connector, that allows user connect peripherals such as lcd1602 advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 14 module, sensors, etc. via inter-integrated circuit (i²c), universal asynchronous receiver-transmitter (uart) and serial peripheral interface (spi). raspberry pi also provides the accessories, such as touch panel and camera, the camera which is this experiment used, the camera can get 1024 × 768 images by 5 million pixels, it connects raspberry pi by camera serial interface (csi) with a flexible flat cable. raspberry pi’s power rating is 5v/1.34a (1.5w), we use a mobile power as a power source by microusb, providing maximum 5v/2.4a (12w) output. in this experiment, we use wireless local area network (wlan) and local area network (lan) connect raspberry pi and server. raspbian was chosen for the operating system, it is a debian-based for raspberry pi, officially provided by raspberry pi foundation. raspbian is highly optimized for the raspberry pi line’s low-performance arm cpus, also provide a desktop environment for beginners. in the beginning, raspberry pi boots into the system, then startup streaming service, the protocol is using real time streaming protocol (rtsp). at the server side, the server captures the image from raspberry pi, tensorflow object detection program will detect the object from the image, in this experiment, we use “faster_rcnn_inception_ resnet_v2_atrous_coco” as frozen model to detect object, the reason we chose this model, it can recognize object more than the other two frozen model, but disadvantage of this model is using more time. after detected, the program will generate object coordinate, name and detected score, to validate our theory, we need coordinate data to calculate the walkable area, then, the program will send object coordinate data and source imaged to the walkable area program, name and score data are optional data, but in this experiment, we didn’t use them, those data contain the object name and detected score. the walkable area program was used in python 3 as programming language, in this program, coordinate data from tensorflow object detection is playing an important part in this experiment, first step, we use the coordinate data to mark the bounding box, second step, using the algorithm to find the walkable area of this image, then, the program will generate the marked image. (a) the raspberry pi (b) cmos camera fig. 5 a car combined the raspberry pi and cmos camera figs. (6-7) present the original input, result detected using tensorflow object detection, and walkable area determined using the program, respectively. the program was developed according to the aforementioned theory. fig. 7 shows the result of the system output, bounding box in green represent the object, the two red lines represent the two shortest distance between two bounding boxes, two lines means we have four coordinates. to show the walkable area, creating an empty layer, same width and height as origin image, using these coordinates to create a polygon on it, filling in blue color in a closed area, after creating the layer, it will overlay on the origin image. the marked area is the walkable area that the system determined. advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 15 fig. 6 the environmental image captured by the cmos camera fig. 7 the walkable area determined using the system marked by blue color in fig. 8, this environment is a walking area in the laboratory, in human thinking, we can pass through by the box’s lefthand side, but there was a wheel of the chair in the left, so we pass through between these two objects. the program will detect the objects using fig. 8, then the program used an algorithm to calculate the walkable area between these two objects, shown in fig. 9. you can see that the program marks the walkable area by blue color, so does human thinking. but in fig. 9, some object is not marked, for example, the cabinet in the middle of fig. 9, algorithm skip that object, the blue area is overlapped on it. fig. 8 the environmental image captured by the cmos camera fig. 9 the walkable area determined using the system, marked by blue color fig. 10 the environmental image captured by the cmos camera fig. 11 the walkable area determined using the system, marked by blue color table 2 presents the detail of the detection, we chosen google’s tensorflow object detection api “faster_rcnn_ inception_resnet_v2_atrous_coco” frozen model as object detection model, “ssd_mobilenet_v1_coco,” and “ssd_mobilenet advances in technology innovation, vol. 5, no. 1, 2020, pp. 10-17 16 _v1_ fpn_coco” are not used here, two of them can’t recognize more than two objects, by this reason, the algorithm needs two or more objects input, which is the area that we want to find. table 2 detection details for figs. (7, 9, 11) number of detections detection classes time (sec.) fig. 7 4 toilet, microwave, oven, chair 0.0157 fig. 9 4 refrigerator, chair, bowl 0.0161 fig. 11 2 chair 0.0191 by experiment results, this algorithm needs more object data, accuracy will be increased. choosing a model is a subject in this study, we can train the model base on the existing model, so we should prepare the object that appears indoor frequently, such as sofa, chairs, cabinet, fans, computers, etc. another problem is, vision is limited, the camera cannot capture whole object, only a part of an object, chair foot is an obvious case, sometimes object detection cannot detect what the object is, or it is an object, cause the program cannot find the walkable area. the problem as descript above mentioned, this problem is future work that we need to solve them. 5. conclusions this study proposed the use of recent paths between all objects to determine the walkable area, the experiment showed the result, it proofs the algorithm can find the walkable area by tensorflow object detection. enhanced this algorithm is the most important job in the future, low latency is the goal of this algorithm, the real-time system does not allow high latency. for example, the cleaning robot needs to know which area cannot entry, low latency can speed up the efficiency of the cleaning work. with the popularity of high-bandwidth networks, cloud computing was used to obtain the desired results. with technological developments, the tensor calculation of embedded systems can considerably improve computing efficiency. in the near future, this algorithm can be installed in embedded systems, which will be a significant development for robot vision. conflicts of interest the authors declare no conflict of interest. references [1] s. ren, k. he, r. girshick, and j. sun, “faster r-cnn: towards real-time object detection with region proposal networks,” ieee transactions on pattern analysis and machine intelligence, vol. 39, no. 6, pp. 1137-1149, 2017. [2] t. y. lin, m. maire, s. belongie, l. bourdev, r. girshick, j. hays, p. perona, d. ramanan, c. l. zitnick, and p. dollár, “microsoft coco: common objects in context,” arxiv:1405.0312v3 [cs. cv], february 2015. [3] a. g. howard, m. zhu, b. chen, d. kalenichenko, w. wang, t. weyand, m. andreetto, and h. adam, “mobilenets: efficient convolutional neural networks for mobile vision applications,” arxiv:1704.04861 [cs. cv], 2017. [4] r. girshick, j. donahue, t. darrell, and j. malik, “rich feature hierarchies for accurate object detection and semantic segmentation,” proc. the ieee conference on computer vision and pattern recognition (cvpr), ieee press, june 2014, pp. 580-587. [5] w. liu, d. anguelov, d. erhan, c. szegedy, s. reed, c. y. fu, and a. c. berg, “ssd: single shot multibox detector,” proc. part i: eccv 2016-the 14th european conference, amsterdam, netherlands, october 2016, pp. 21-37. 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[11] m. abadi, p. barham, j. chen, z. chen, a. davis, j. dean, m. devin, s. ghemawat, g. irving, m. isard, m. kudlur, j. levenberg, r. monga, s. moore, d. g. murray, b. steiner, p. tucker, v. vasudevan, p. warden, m. wicke, y. yu, and x. zheng, “tensorflow: a system for large-scale machine learning,” arxiv:1605.08695 [cs.cv], 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 3___aiti#7330_in press advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 experimental and theoretical analysis of cracking moment of concrete beams reinforced with hybrid fiber reinforced polymer and steel rebars hiep dang vu1, duy nguyen phan2,* 1civil engineering faculty, hanoi architectural university, vietnam 2faculty of civil engineering, mientrung university of civil engineering, vietnam received 18 march 2021; received in revised form 11 may 2021; accepted 12 may 2021 doi: https://doi.org/10.46604/aiti.2021.7330 abstract this study aims at experimentally and theoretically investigating the cracking moment (mcrc) of hybrid fiber reinforced polymer (frp)/steel reinforced concrete (rc) beams. six hybrid glass frp (gfrp)/steel and three gfrp rc beams with various gfrp and steel reinforcement ratios are tested in four-point bending scheme. experimental results indicate that both gfrp and steel rebars affect mcrc, but the effect of steel reinforcement is more significant. when the steel reinforcement ratio increases to 1.17%, mcrc goes up to 15.9%, while the same value for gfrp is only 9.7%. an analytical method is proposed based on the plain section assumption and nonlinear behavior of materials for estimating mcrc. the proposed model shows a good agreement with the experimental data conducted in this study and collected from the literature. the results of the parametric study give evidence of the positive effects of hybrid reinforcement ratios and elastic modulus of frp on mcrc of hybrid rc beams. keywords: concrete beam, fiber reinforced polymer (frp), hybrid reinforcement, cracking moment, flexural behavior 1. introduction due to some special characteristics, such as superior corrosion resistance, low strength/weight ratio, non-conductive, non-magnetic, fiber reinforced polymer (frp) rebars, are widely used as an alternative to steel rebar for concrete structures [1-2]. it is well known that there are four common types of frp rebars used to reinforce concrete components: aramid frp (afrp), basalt frp (bfrp), carbon frp (cfrp), and glass frp (gfrp). only the elastic modulus of cfrp is equivalent or higher than that of steel bar. the elastic modulus of other frp types is much lower than that of steel bar, which causes large deflection and crack width of frp reinforced concrete (rc) bending elements [3-6]. to overcome this drawback of frp rc beams, many researchers proposed combining traditional steel bars to frp bars in the tension zone of the concrete beam. as a result, hybrid frp/steel rc beams are formed [7-9]. in practice, the hybrid frp/steel rc beams were also met in a type of rc beams strengthened with frp sheets. although the flexural behavior of frp/steel rc beams has been extensively investigated, the data on cracking behavior is still limited. this study presents experimentally and theoretically the investigation on the cracking behavior of hybrid frp/steel rc beams, and introduces an analytical method for predicting the cracking moment of frp/steel rc beams. first, three groups of beams, which contain six hybrid gfrp/steel and three gfrp rc beams, are cast and tested in the four-point pending scheme to clarify the cracking behavior. second, an analytical method based on the plane section assumption and strain compatibility is * corresponding author. e-mail address: nguyenphanduy@muce.edu.vn tel.: +84-917688903 advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 proposed for estimating the cracking moment. this method considers the nonlinear behavior of concrete and the contribution of reinforcements. finally, a parametric study on the effect of longitudinal reinforcement ratios and elastic modulus of frp on the cracking moment is done by using the proposed analytical method. 2. literature review previous studies of frp/steel rc beams mainly focused on the flexural behavior, evaluating the cracking moment, failure modes and load-bearing capacity, short-term and long-term deflections, crack width, crack spacing, stiffness, and ductility. the results of the previous studies revealed the positive effect of steel reinforcement in improving the flexural behavior of frp/steel rc beams [4-16]. for the design purposes of hybrid frp/steel rc beams, many researchers proposed analytical methods to estimate load-carrying capacity [10, 12-13, 17-19] and limits of reinforcement ratios [20], to determine failure modes [10-16], and to estimate crack width, crack spacing, and midspan deflection [21-22]. some researchers tried to use the existing design codes with some modifications for the calculation of hybrid frp/steel rc beams [4, 18, 23-24]. regarding the cracking moment of frp/steel rc beams, very few researchers focused on the cracking behavior and proposed the formulas to calculate the cracking moment of frp/steel rc beams. by using the existing design codes with the modulus of rupture and transformed uncracked sections, mohamed [25] compared the theoretical and experimental cracking moments of frp/steel rc beams, and reported that the theoretical cracking loads were significantly smaller than the experimental values. kartal and kalkan [26] developed two cracking moment estimates of frp/steel rc beams, one for the gross moment of inertia and the other for the uncracked transformed moment of inertia. in each method, three different tensile strengths of concrete, i.e., the experimental value calculated from the prismatic beam tests and the second and third values obtained from empirical flexural tensile strength of eurocode 2 and aci 318m, were applied. the results showed that the uncracked transformed moment of inertia method with a modulus of rupture expression according to the aci 318 m gave the best agreement between theoretical and experimental results. besides, the authors reported that ignoring the contribution of the longitudinal reinforcements in the calculation may lead to underestimation of the cracking moment. maleki and kheyroddin [18] used the recommendations of aci440.1r-15 and csa-s806-12 to estimate the first cracking moment of gfrp/steel rc beams. the results showed that these design codes underestimated the cracking moment of tested beams. valivonis and skuturna [27] experimentally investigated the cracking moment of rc beams strengthened by cfrp laminates. they reported that cfrp laminates significantly increased the critical tension strains of the concrete and cracking moment (from 56% to 106%), and that cfrp laminates also influence the expansion of cracks and restrict the development of the crack. these authors proposed an analytical equation for estimating the cracking moment by using curvilinear diagrams to describe the compressed concrete and the concrete in tension. however, the comparison results showed a large deviation between theoretical and experimental values. gao et al. [28] carried out an experimental study on the flexural behavior of one-way slab strengthened by frp sheets, and pointed out the influence of the amount of strengthening cfrp and gfrp sheets on cracking moment of rc one-way slab. in particular, the cfrp sheet with a high elastic modulus has a stronger effect on the cracking moment in comparison with a gfrp sheet. due to the complication of a method for estimating the cracking moment based on the plane cross-section assumption and equilibrium condition, these authors proposed an equivalent-conversion method for determining the cracking moment of rc slabs strengthened with frp, in which the formula of elastic materials is used with a plasticity coefficient. the proposed method revealed good agreement between experimental and theoretical values. a lot of experimental research on the flexural behavior of hybrid frp/steel rc beams has been reported along with many proposals for prediction models of cracking moments. however, the majority of these proposals are based on the existing design codes (aci and eurocode), which neglected the contribution of reinforcements. this fact led to the underestimation of the cracking moment of frp/steel rc beams. 223 advances in technology innovation, vol. 6, no. 4, 2021, pp. 223-234 3. experimental investigation six hybrid gfrp/steel rc and three gfrp rc beams with dimensions of 150 × 250 × 2700 mm (width × height × long) and different gfrp and steel reinforcement ratios are cast and loaded in a four-point bending scheme. all nine testing beams are divided into three groups to evaluate the influence of gfrp/steel reinforcement on the cracking load. in each group, the gfrp reinforcement area (af) is fixed, and the steel reinforcement area (as) varies (fig. 1 and table 1). specifically, the group of beams #1 (beams b1, b2, and b3) is reinforced with 2g10 (two gfrp bars with a diameter of 10 mm, af = 1.225 cm2), the group of beams #2 (beams b4, b5, and b6) is reinforced with 2g14 (af = 2.65 cm2), and the group of beams #3 (beams b7, b8, and b9) is reinforced with 3g14 (af = 3.97 cm2). in addition, during the analysis of the test results, the groups of beams with fixed longitudinal steel reinforcement and varied gfrp reinforcement are also created. the group of beams with fixed 2s10 (two steel bars with the diameter of 10 mm) contains beams b2, b5 and b8, and the group of beams with fixed 2s14 (two steel bars with the diameter of 14 mm) contains beams b3, b6, and b9. the loading span is 2400 mm, of which the length of the pure bending zone is 400 mm (fig. 2(a)). as shown in fig. 1, the gfrp and steel rebars are arranged in two layers, wherein the gfrp rebars are placed in the undermost layer with a concrete cover thickness (cf) of 25 mm, while the steel rebars are arranged in the inner layer (second layer) with a concrete cover thickness (cs) of 50 mm. all the actual dimensions of the testing beams are re-measured after casting, as shown in table 1. the shear reinforcements from plain round steel bars with the diameter of 6 mm and the spacing of 100 mm are put in the shear spans to prevent shear failure. in the middle span, the spacing of stirrups is 200 mm to form a reinforcement cage and reduce the influence of stirrups on flexural behavior. two 6 mm diameter steel rebars are used as compressive reinforcements. the beam specimens are designed with references to aci 440.1r-15 [29] and recommendations by previous researchers [12, 20]. accordingly, the gfrp reinforcement ratio (��) varies from 0.35% to 1.18%, and the steel reinforcement ratio (��) ranges from 0.52% to 1.13%. details of geometries and reinforcements of specimens are presented in table 1. (a) gfrp rc beams (b) hybrid gfrp/steel rc beams (c) reinforcement cage fig. 1 beam’s reinforcement (unit: mm) table 1 details of beam specimens group of beams beam id b, mm h, mm ��, mm ��, mm h0f, mm h0s, mm af, cm 2 as, cm 2 ��, % ��, % rm, mpa #1 b1.2g10 150 253 21 232 1.23 0.35 37.2 b2.2g10-2s10 152 254 30 54 224 200 1.23 1.57 0.36 0.52 41.6 b3.2g10-2s14 151 252 27 72 225 180 1.23 3.08 0.36 1.13 39.5 #2 b4.2g14 148 252 31 221 2.65 0.81 42.6 b5.2g14-2s10 151 251 31 52 220 199 2.65 1.57 0.80 0.52 41.0 b6.2g14-2s14 152 254 33 62 221 192 2.65 3.08 0.79 1.06 40.5 #3 b7.3g14 148 255 26 229 3.97 1.17 45.5 b8.3g14-2s10 153 254 33 59 221 195 3.97 1.57 1.18 0.53 42.8 b9.3g14-2s14 155 255 23 58 232 197 3.97 3.08 1.11 1.01 42.9 *note: b, h, ��, ��, h0f, and h0s are the geometric dimensions of cross section as shown in fig. 1. �� = as /(bh0s) and ��= af /(bh0f) are the steel and gfrp reinforcement ratios, respectively. the beam id is formed from 3 parts: the first part (e.g., b1) is the order number of the beams, the second part (2g10, 2g14, and 3g14) refers to the number and the diameter of gfrp bars, and the last part (2s10 and 2s14) indicates the number and the diameter of steel bars. b refers to beam, g refers to gfrp, and s refers to steel. 200 ø6 af h 0 f 2 5 0 a f c f 2ø6 ( )asca sc c sc a c f c s h 0 f h 0s ø6 a s a f f a s 2ø6 ( )asc c sc 224 advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 (a) schematic diagram (b) test setup fig. 2 flexural test the concrete with the desired compressive strength of 40 mpa and the water-to-cement ratio of 0.55 is produced from ordinary portland cement. the actual average compressive strength (rm) is evaluated from compressive tests on 150 × 150 × 150 mm cubic specimens after 28 days of curing, as shown in table 2. the ribbed gfrp rebars with nominal diameters of 10 mm and 14 mm are used in this study and are manufactured by vietnam frp trading and production joint stock company. the gfrp bars are produced from continuous high-strength e-glass fiber and vinyl ester resin. the hot-rolled plain steel bar with a diameter of 6 mm is used for stirrups and compressive reinforcement, and the hot-rolled ribbed steel bars with diameters of 10 mm and 14 mm are used as longitudinal rebars. the mechanical properties of gfrp, round plain steel, and ribbed rebars according to tensile tests are shown in table 2. table 2 mechanical properties of reinforcements rebars yield strength, mpa tensile strength, mpa young’s modulus, gpa gfrp rf = 997 ef = 44.3 the 6 mm plain round steel σsy = 309 rs = 358 es = 200 the ribbed steel (diameter ≥ 10 mm) σsy = 412 rs = 577 es = 200 the beams are loaded after a 28-day curing period in a four-point bending scheme until failure (fig. 2). three 100 mm strain gauges (s1, s2, and s5) are placed at the top, side, and bottom surfaces at the midspan of the test beams to record the compressive and tensile strains in concrete. two 5 mm strain gauges (s3 and s4) are attached on the surface of tensile steel and gfrp rebars at midspan before casting and are protected by silicon to measure the strains in rebars during the test. a linear variable differential transformer (lvdt) is fixed at midspan to measure the deflection, and two digital indicators i1 and i2 are placed at supports to eliminate the displacements of holders. during the test, the loads on the beam are applied in a step-by-step procedure, and the values of load from loadcell, the data from lvdt, and strain gauges are automatically collected by the datalogger sts-wifi system. 4. experimental results and discussion the first cracking moment of tested beams is obtained from the load versus strain curve of the concrete and reinforcements. this value can also be determined from the load versus midspan deflection curve. fig. 3 and fig. 4 illustrate the load-strain and load-midspan deflection curves for a typical tested beam b2.2g10-2s10. it is worth to note that until the yield of steel (after the concrete cracks), the trends of the load versus strain curves of the concrete and reinforcements and the load versus midspan deflection curves of the remained tested beams are similar to those of the beam b2.2g10-2s10. as shown in fig. 3, there are leaps on the load-strain curves as the first crack appears. the leap is also noticed on the load-midspan curve at the moment when the first crack appears (fig. 4). the experimental cracking moments of tested beams (mcrc,e) are presented in table 3. the load-carrying capacities (mu,e) and failure modes of tested beams are also recorded and presented in table 3 to evaluate the ratio between cracking moment and load-carrying capacity. the relationship between the cracking moments and distribute beam loadcell hydraulic jack 150 1000 400 1000 150 2700 ø6@200 ø6@100 gfrp bars steel bars s1 s3 s4 s5 2 5 0 s2 i2i1 lvdt 225 advances in technology innovation, vol. 6, no. 4, 2021, pp. 223-234 the steel reinforcement ratios of the groups of beams with fixed gfrp reinforcement ratios are illustrated in fig. 5. the relationship between the cracking moments and the gfrp reinforcement ratios of the groups of beams with fixed steel reinforcement ratios are also presented in fig. 6. fig. 3 load versus strain curve of the concrete and reinforcements (beam b2.2g10-2s10) fig. 4 load versus midspan deflection curve (beam b2.2g10-2s10) table 3 the cracking moment of tested hybrid gfrp/steel rc beams beam id experimental theoretical εs,e ×104 εf,e ×104 εbt,e ×104 σs,e, kn σf,e, kn σs,e /σf,e σs,e /σsy, % σf,e /ffu, % mcrc,e, knm mu,e, knm mcrc,e / mu,e failure mode εs,t ×104 εf,t ×104 εbt,t ×104 mcrc,t, knm mcrc,t / mcrc,e b1.2g10 1.65 1.72 7.3 0.73 5.35 24.1 0.22 rg 1.23 1.67 5.73 1.07 b2.2g10-2s10 0.86 1.29 1.73 17.2 5.7 3.02 4.17 0.57 6.20 34.4 0.18 sy-rg 0.82 1.12 1.70 6.60 1.06 b3.2g10-2s14 0.83 1.12 1.40 16.6 5.0 3.32 4.03 0.5 6.20 38.1 0.16 sy-cc 0.57 1.15 1.74 6.30 1.02 b4.2g14 1.31 1.47 5.8 0.58 6.20 41.4 0.15 cc 1.11 1.65 6.30 1.02 b5.2g14-2s10 1.00 1.14 1.76 20 5.1 3.92 4.85 0.51 6.40 48.4 0.13 sy-cc 0.83 1.10 1.72 6.47 1.01 b6.2g14-2s14 0.75 0.99 1.62 15 4.4 3.41 3.64 0.44 6.50 56.5 0.12 sy-cc 0.70 1.08 1.76 6.76 1.04 b7.3g14 1.30 1.64 5.8 0.58 6.65 52.4 0.13 cc 1.18 1.65 6.85 1.03 b8.3g14-2s10 0.73 1.03 1.51 14.6 4.6 3.17 3.54 0.46 6.40 50.0 0.13 sy-cc 0.75 1.08 1.72 6.94 1.08 b9.3g14-2s14 0.93 1.39 1.86 18.6 6.2 3.00 4.51 0.62 6.80 56.7 0.12 sy-cc 0.76 1.21 1.77 7.40 1.09 *note: rg refers to the rupture of gfrp, sy refers to steel yielding, and cc refers to concrete crushing. fig. 5 cracking moment versus steel reinforcement ratio curves of the groups of beams with fixed gfrp reinforcement ratios fig. 6 cracking moment versus gfrp reinforcement ratio curves of the groups of beams with fixed steel reinforcement ratios -3 0 3 6 9 12 15 s1 s2 s3 s5 0 20 40 60 80 strain ε×103 l o a d , k n first crack s4 5.0 5.5 6.0 6.5 7.0 0 0.4 0.8 1.2 c ra ck in g m o m en t, k n m steel reinforcement ratio µs , % group of beams #1 (b1, b2, b3) group of beams #2 (b4, b5, b6) group of beams #3 (b7, b8, b9) 6.00 6.25 6.50 6.75 7.00 0.3 0.6 0.9 1.2 c ra ck in g o m en t m , kn m gfrp reinforcement ratio µ f , % grou s 2 5 8p of beams with fixed 2 10 (b , b , b ) beams with fixed 2 1 (b , b , b )group of s 4 3 6 9 226 advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 it is well known that the cracking moment depends on beam dimensions, properties of materials, and reinforcement ratios [28, 30]. it can be seen in figs. 5-6 that the reinforcements significantly affect the cracking moment of hybrid gfrp/steel rc beams. as gfrp or steel reinforcement ratios increase, the cracking moment of tested beams linearly increases. as can be seen in fig. 5, in the groups of hybrid beams with fixed gfrp reinforcement ratio, the effect of steel reinforcement on cracking moment decreases with the increase of the gfrp reinforcement ratio. in the group of beams #1 (�� = 0.36%), when the steel reinforcement ratio increases from 0 to 1.13%, the cracking moment of hybrid gfrp/steel beams increases to 15.9%, while in the group of beams #2 (�� = 0.8%) and #3 (�� = 1.17%) the corresponding values are 4.8% and 2.3% respectively. when the steel reinforcement ratios are fixed, the cracking moment of hybrid gfrp/steel rc beams also increases with the increase of the gfrp reinforcement ratio. however, the effect of gfrp reinforcement on the cracking moment of the hybrid beam is less than that of steel rebars. in the groups of beams with fixed steel reinforcement (groups 2s10 and 2s14 in fig. 6), the cracking moments of hybrid beams increase to 8.8% and 9.7% respectively. for the tested beams, the experimental cracking moment to load-carrying capacity ratio (mcrc,e /mu,e) varies from 0.12 to 0.22 (table 3), and this ratio decrease with the increase of the gfrp or steel reinforcement ratio. (a) beams b1.2g10 (b) beams b2.2g10-2s10 (c) beams b3.2g10-2s14 (d) beams b4.2g14 (e) beams b5.2g14-2s10 (f) beams b6.2g14-2s14 (g) beams b7.3g14 (h) beams b8.3g14-2s10 (i) beams b9.3g14-2s14 fig. 7 distribution of strains on the cross-section at the fist cracking moment fig. 7 presents the distribution of strain on the cross-section of tested beams at the moment when the first crack appears. as can be seen, the plane cross-section assumption is satisfied for hybrid frp/steel rc beams. to clarify the contribution of each type of longitudinal reinforcements to the cracking moment, the maximum experimental tensile strains and stresses of gfrp (��,� and ��,�) and steel rebars (��,� and ��,�) before the appearance of the first crack are reported in table 3. the 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 0-0.5-1.0-1.5 0.5 1.0 1.5 2.0 0 50 100 150 200 250 h e ig h t, m m strain × 104 227 advances in technology innovation, vol. 6, no. 4, 2021, pp. 223-234 maximum tensile strain in concrete (� ,� ) at this moment is also presented in table 3. due to the elastic behavior of reinforcements in this stage, the values of the tensile stresses in gfrp and steel rebars are determined by multiplying the measured tensile strains by the corresponding young’s moduli (44.3 gpa and 200 gpa, table 2). as can be seen in table 3, due to the high young’s modulus of steel rebars, at the first cracking moment, the stress in steel bars is about 3.02 to 3.92 times higher than that in gfrp rebars, and is about 3.00% to 4.85% of the yield strength. that fact has proven that both gfrp and steel reinforcement affects the cracking moment of hybrid gfrp/steel rc beams, but the contribution of gfrp reinforcement in this stage is negligible as compared to steel, and the stress in gfrp is about 0.44% to 0.73% of ultimate tensile strength. these results are consistent with the findings reported by most other researchers [27-28, 31] and are contrary to the results presented in [32]. in addition, experimental research results show that, as the first crack appears, the maximum tensile strain in the outermost concrete fiber (� ,�) reaches the value of 1.47×10-4 to 1.86×10-4, which meets the recommended ultimate tensile strain of concrete � � = 1.5×10-4 in sp 63.13330:2018 [33]. in addition, the recorded maximum compressive strains in the outermost concrete fiber (� ,�) before the appearance of the first crack vary from 0.91×10-4 to 1.67×10-4, which are much less than the ultimate compressive strain of concrete. 5. an analytical method for calculating the cracking moment of hybrid frp/steel rc beam as reported in the introduction and as indicated from the experimental results, the hybrid gfrp/steel reinforcement significantly affects the cracking moment. therefore, using the recommendations of the existing design codes which neglect the contribution of reinforcements leads to the underestimation of the cracking moment. this section introduces an analytical method for calculating the cracking moment of frp/steel rc beams based on the plane cross-section assumption and equations of equilibrium. the bilinear stress-strain relationship of concrete introduced in sp 63.13330:2018 [33] is used in the calculation (fig. 8). at the first cracking moment, the maximum strain in the outermost tensile concrete fiber reaches the ultimate value � � = 1.5×10-5 according to the stress-strain relationship in fig. 8. before the concrete cracks, assuming that the concrete in compression behaves elastically, the stress distributes in triangular form. in the tension zone, the stress distributes in trapezoid form with the maximum stress equal to the tensile strength rbt according to the stress-strain relationship in fig. 8. the distributions of strain and stress on the cross-section are presented in fig. 9. fig. 8 bilinear stress-strain relationship of concrete [33] (a) cross-section (b) distribution of strains (c) distribution of stress fig. 9 stress and strain distributions for calculating the cracking moment σ r σ 8×10 -5 15×10 -5 0.0015 arctge ε b2 ε b ε b1,red εbt1,redεbt2 εbt rb b bt bt b,red h hh b a a f s 0 f 0s a a s f asc a sc εb εs ε f ε = 15×10bt2 εsc -5 ε = 8 × 10 bt 1 ,r ed -5 h hh 0 f 0 s a a s f a sc σb σsc σs σf rbt x h -x ( ) h -x 7 1 5 ( ) h -x 8 1 5 228 advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 the maximum strains in the outermost compressive concrete fiber � , in the compressive steel rebars �� , in the tensile steel rebars ��, and in the tensile gfrp rebars �� are determined according to � � by using the plane cross-section assumption, i.e., according to the strain distribution shown in fig. 9(b). the stress in concrete and reinforcements can be found by using the obtained strains in materials. before the first crack appears, the stress in the outermost compressive fiber of concrete � is determined by eq. (1): 2 1, 10 bt b b b b bred b red x r rx e h x h x ε σ ε ε = = = − − (1) where rb is the prismatic strength of concrete; x is the compression zone height; � is the maximum strain in the outermost compressive concrete fiber, which can be determined according to the eq. (2) based on the plain cross section in fig. 9(b); ebred is the reduced modulus of concrete, which is determined by eq. (3) according to sp 63.13330 : 2018 [33]. ( )2 / b bt h xxε ε −= (2) 1,/ bred b b red e r ε= (3) the stress in compressive reinforcement rebars is as follows: ( )2bt sc s sc sc s x a e e h x ε σ ε − = = − (4) where es is the modulus of elasticity of steel; �� is the strain in compressive steel rebars and is calculated according to fig. 9(b) by the following equation. ( ) ( )2 / sc bt sc x a h xε ε= − − (5) the stress in tensile steel rebars is as follows: ( )2bt s s s s s h x a e e h x ε σ ε − − = = − (6) where �� is the strain in tensile steel reinforcement obtained from fig. 9(b) as follows: ( ) ( )2 / s bt s h x a h xε ε= − − − (7) the stress in tensile frp rebars is as follows: ( )2bt f f f f f h x a e e h x ε σ ε − − = = − (8) where �� is the strain in gfrp rebars and determined according to fig. 9(b) as follows: ( ) ( )2 / f bt f h x a h xε ε= − − − (9) the resultant forces of the compression zone of concrete (nb), of the compressive reinforcement (nsc), of the tensile steel (ns) and gfrp (nf) rebars, and in the tension zone of concrete (nbt) are calculated using the following equations: 229 advances in technology innovation, vol. 6, no. 4, 2021, pp. 223-234 2 2 20 b b b bx brx n h x σ = = − (10) ( )2bt s sc sc sc sc sc e x a a n a h x ε σ − = = − (11) ( )2bt s s s s s s e h x a a n a h x ε σ − − = = − (12) ( )2bt f f f f f f h x a e a n a h x ε σ − − = = − (13) ( ) ( ) 1 2 7 4 15 15 bt bt bt bt bt h x r b h x r b n n n − − = + = + (14) the equation of horizontal force equilibrium is as follows: ( ) ( ) ( ) ( )2 22 2 11 20 15 bt f f fbt s sc sc bt s s s btb h x a e ae x a a h x a e a h x r bbrx h x h x h x h x εε ε − −− − − − + = + + − − − − (15) by expanding eq. (15) and setting the constants a (16), b (17), and c (18), eq. (15) is re-written as eq. (19): 11 20 15 b bt r b r b a = − (16) ( )2 22 15 bt bt s s s sc f f r bh b e a e a e aε= + + + (17) ( ) 2 2 11 15 bt bt s s s s sc sc f f f s s f f r bh c e a a e a a e a a e a h e a hε= − + − − − (18) 2 0ax bx c+ + = (19) by solving eq. (19) and choosing the compatible root meeting the condition 0 < x < h, the equations for calculating the compression zone height is expressed as follows: 2 4 2 b ac b x a − − = (20) by using the compression zone height x (eq. (20)) and defining the resultant forces in materials (nb, nsc, ns, nf, and nbt) according to eq. (10) to eq. (14), the first cracking moment mcrc can be determined by taking the moment about the axis passing through the neutral axis (eq. (21)). the comparison results between the experimental cracking moments and the theoretical values (mcrc,t) of the tested beams obtained by eq. (21) in table 3 show good agreement. the deviation between the experimental and theoretical cracking moment is less than 9%. in addition, the theoretical strains in the outermost compressive concrete fiber, in the steel tensile reinforcement, and in the tensile gfrp reinforcement obtained by eq. (2), eq. (7), and eq. (9) respectively are also in good agreement with the experimental values (table 3). ( ) ( ) ( ) ( ) ( )1 223 162 3 30 45 bt btb crc sc sc s s f f n h x n h xxn m n x a n h x a n h x a − − = + − + − − + − − + + (21) 230 advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 to verify the applicability of the proposed theory for determining the cracking moment of concrete beams reinforced with a combination of steel bars and different types of frp bars, the experimental data of 24 tested hybrid frp/steel rc beams in the literature are collected and compared as shown in table 4. the comparison results prove the accuracy in estimating the cracking moment of concrete beams reinforced with hybrid frp/steel rebars. the average value is 1.006, the standard deviation is 0.076, and the mean value is 0.995. table 4 the comparison between experimental and theoretical cracking moments of concrete beams reinforced with a combination of different types of frp and steel bars ref. beam id b, mm h, mm af, mm as, mm af, mm 2 as, mm 2 asc, mm 2 asc, mm es, gpa type of frp ef, gpa rm, mpa mcrc,e, knm mcrc,t, knm mcrc,t / mcrc,e [25] b10/8s 100 200 22 64 100.6 157 0 0 200 gfrp 39 30 2.5 2.39 0.96 b10/6 100 200 21 64 56.6 157 0 0 200 gfrp 41 30 2.5 2.37 0.95 b12/8 100 200 22 65 100.6 226 0 0 200 gfrp 39 30 2.7 2.42 0.90 b12/6s 100 200 21 65 56.6 226 0 0 200 gfrp 41 30 2.3 2.4 1.04 [23] gfrp-40s 150 250 42 98 253.4 142.6 142.6 210 200 gfrp 48 32.7 5.4 5.4 1.00 cfrp-40s 150 250 40 95 142.6 142.6 142.6 210 200 cfrp 103 32.7 5.7 5.4 0.95 gfrp-60s 150 250 42 98 253.4 142.6 142.6 210 200 gfrp 48 49.3 7.43 7.11 0.96 cfrp-60s 150 250 40 95 142.6 142.6 142.6 210 200 cfrp 103 49.3 6.3 7.11 1.13 [26] b2s3 200 300 30 30 118.3 339.3 1.57 270 200 bfrp 43 25 13.2 11.85 0.90 b3s2 200 300 30 30 177.5 226.2 1.57 270 200 bfrp 43 25 11.6 11.5 0.99 b4s1 200 300 30 30 236.7 113.1 1.57 270 200 bfrp 43 25 10.4 11.1 1.07 g2s3 200 300 30 30 259.8 339.3 1.57 270 200 gfrp 35 25 11.5 11.9 1.03 g3s2 200 300 30 30 389.7 226.2 1.57 270 200 gfrp 35 25 10.1 11.6 1.15 g4s1 200 300 30 30 519.6 113.1 1.57 270 200 gfrp 35 25 10.5 11.2 1.07 g1s5 200.8 301.9 30 30 117.5 565.5 0 0 200 gfrp 46 24.4 13.3 12.7 0.95 g2s4 199.8 301.1 30 30 234.9 452.4 0 0 200 gfrp 46 24.4 12.7 12.3 0.97 g3s3 200.6 304.4 30 30 352.4 339.3 0 0 200 gfrp 46 24.4 10.9 12.2 1.12 g4s2 198.6 304.6 30 30 469.9 226.2 0 0 200 gfrp 46 24.4 11 11.8 1.07 b1s2 199.8 308 30 30 59.2 226.2 0 0 200 bfrp 43 24.4 11.8 11.7 0.99 b1s4 200 300 30 30 59.2 452.4 1.57 270 200 bfrp 43 25 14 12.2 0.87 g1s4 200 300 30 30 129.9 452.4 1.57 270 200 gfrp 35 25 13.2 12.3 0.93 b2s1 199.2 301.7 30 30 118.3 113.1 0 0 200 bfrp 43 24.4 10.8 10.9 1.01 g1s2 198.6 304.9 30 30 117.5 226.2 0 0 200 gfrp 46 24.4 11.4 11.5 1.01 g2s1 202 301.6 30 30 234.9 113.1 0 0 200 gfrp 46 24.4 9.9 11.1 1.12 average standard deviation mean 1.006 0.076 0.995 6. parametric study as mentioned above, besides the section geometry and mechanical properties of concrete, the longitudinal reinforcements also significantly affect the cracking moment of hybrid frp/steel rc beams. in this section, a parametric study of the effects of the longitudinal frp and steel reinforcement ratios and young’s modulus of frp rebars on the cracking moment of hybrid frp/steel rc beams is carried out using the proposed formula (eq. (21)). first, the influence of hybrid frp/steel reinforcement ratios on the cracking moment are performed with the following input data: b×h = 300×600 mm; rb = 30 mpa; rbt = 2.5 mpa; eb = 32 gpa; es = 200 gpa; σsy = 400 mpa; ef = 50 gpa; rf = 1000 mpa. the distances from the centroid of the steel rebars and frp rebars to the outermost tensile concrete fiber are chosen equally: af = as = 40 mm. by considering the recommendations in [20], the steel and frp reinforcement ratios are selected to vary from 0% to a maximum 4% (i.e, the area of each type of reinforcements varies from 0 cm2 to 67.2 cm2). by conducting nonlinear regression analysis, the relationship between cracking moment calculated by eq. (21) and hybrid steel/frp reinforcement ratios is expressed by eq. (22). it should be noticed that, the adjusted coefficient of multiple determination (r2) of regression model in eq. (21) is higher than 0.9999. 231 advances in technology innovation, vol. 6, no. 4, 2021, pp. 223-234 2 2 , 3.597 15.077 5.49 0.1567crc crc b f s f sm m µ µ µ µ= + + + − (22) where mcrc,b is the cracking moment of plain concrete beam; µf and µs are in percent (%). the response surface which expresses the relationship among cracking moment, frp, and steel reinforcement ratios according to eq. (22) is shown in fig. 10. the results of the parametric study on the current section and properties of beam show that the cracking moment increases to 93.7% when the steel reinforcement ratios increase from 0% to 4%. meanwhile, the corresponding value for the case of the increasing frp reinforcement is only 24.3%. this outcome affirms the above conclusion of the lower contribution of frp reinforcement on the cracking moment of hybrid frp/steel rc beam in comparison with the steel reinforcement. in addition, as reported in previous studies, the ratio af /as significantly affects the flexural behavior of frp/steel rc beams. as found from the parametric study, this ratio also significantly affects the cracking moment of frp/steel rc beams. namely, with a constant total area of hybrid frp/steel reinforcement, the cracking moment decreases with an increase in the af /as ratio. the effect of young’s modulus of frp on the cracking moment is also investigated on the above-mentioned cross section and properties of materials. the cross section is reinforced with three groups of steel and frp reinforcement: the first group — as = 4 cm2 and af = 4 cm2 (minimum hybrid frp/steel reinforcement ratio [20]), the second group — as = 25 cm2 and af = 25 cm2 (compatible hybrid frp/steel reinforcement ratio [20]), and the third group — as = 50 cm2 and af = 50 cm2 (maximum hybrid frp/steel reinforcement ratio [20]). the modulus of elasticity of frp reinforcement varies from 50 gpa to 200 gpa. it can be seen in fig. 11 that the cracking moment of hybrid frp/steel rc beams is linearly proportional to young’s modulus of frp reinforcement. besides, the effect of young’s modulus of frp reinforcement on cracking moment increases with the increase of the frp reinforcement ratio. fig. 10 the response surface among cracking moment, frp, and steel reinforcement ratios fig. 11 the relationship between young’s modulus of frp reinforcement and cracking moment 7. conclusions in this study, the cracking moment of hybrid frp/steel rc beams was experimentally and theoretically investigated. based on the study results, the following conclusions may be drawn: µ , % µ , % 4.0 3.0 2.0 1.0 0.0 1.0 2.0 3.0 60.0 80.0 100.0 120.0 140.0 f m ,k n m cr c 0.0 s 60 85 110 135 160 50 100 150 200 e , gpa m , kn m c rc f a a = = 4 cms f 2 a = a = 25 cm s f 2 a = a = 50 cm s f 2 232 advances in technology innovation, vol. 6, no. 4, 2021, pp. 222-234 (1) the cracking moment of hybrid frp/steel rc beams is linearly proportional with the steel and frp reinforcement ratios. (2) in the scope of the experimental study, the cracking moment to load-carrying capacity ratio of hybrid gfrp/steel rc beams varies from 12% to 22%, and this ratio reduces with increasing total hybrid reinforcement ratio. (3) both steel and frp rebars affect the cracking moment of hybrid frp/steel rc beams. however, due to higher modulus of elasticity of steel in comparison with the frp reinforcement, the contribution of steel rebars on the cracking moment of hybrid frp/steel rc beams are more significant in comparison with frp reinforcement. (4) the proposed analytical method, which is based on the nonlinear stress-strain relationship of concrete and considered the contribution of hybrid reinforcements, accurately estimates the cracking moment of hybrid frp/steel rc beams. 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[33] concrete and reinforced concrete structures, russian technical standard sp 63.13330, 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 234 microsoft word 5-aiti#6922 117-127.docx advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 defining effective gain for evaluation of orbital angular momentum links elaheh shamoushaki*, hadi aliakbarian department of electrical engineering, k. n. toosi university of technology, tehran, iran received 26 december 2020; received in revised form 14 february 2021; accepted 21 february 2021 doi: https://doi.org/10.46604/aiti.2021.6922 abstract in this paper, a communication link based on circular phased array antennas generating orbital angular momentum (oam) beams at radio frequency is investigated. the presence of a null in the radiation pattern of oam antennas is the main drawback of them. this problem makes it difficult to establish a telecommunication link using oam systems and calculate the link budget for such a system. to solve this problem, we have defined two new gain parameters by using friis transmission equation. the new formulas can help to calculate the effective gain of oam antennas. also, we have defined the effective oam gain in detail for the first time in order to evaluate the performance of the oam links. by using the proposed formulas, a capable and secure link based on the orthogonality of oam beams can be designed. keywords: circular array antenna, effective oam gain, helical phase front, orbital angular momentum, oam link 1. introduction due to the significant progression of communication systems in recent centuries, the efficiency and security of such systems have been considered as essential issues [1]. orthogonality of electromagnetic waves is a property of them that can be used to transmit different information on the same frequency in a communication system. this property causes the channel capacity to increase and also makes the channel more secure [2-5]. orbital angular momentum (oam) is a way that has been introduced to realize this property of electromagnetic waves. during the last two decades, oam of light has been studied in optics with laguerre-gaussian beams [6]. recent reports have shown that oam can be used in the radio frequency both theoretically [7-8], and experimentally [3]. researchers have presented different techniques to generate oam carrying beams at optical frequency ranges or rf ranges. at optical frequency, these techniques contain plasmonic meta-surfaces [9], holograms [10], liquid crystal-based spatial light modulators [11] and spiral phase plates [7]. at rf frequency the presented techniques are circular array antennas [4, 8, 12], spiral phase plates (spp) [1], twisted parabolic reflectors [3] and transmit arrays [13]. the first simulation of oam in radio frequency was performed in 2007 [14]. spiral phase plate has a simple structure, but when multiple spps are used in an oam carrying beam, multiplexing and de-multiplexing cannot be implemented easily [14]. circular array antenna is the typical structure to radiate different oam beams simultaneously. one of the key problems of oam systems is the presence of a null in the middle of their radiation pattern. this problem is discussed in the present paper. as a result, not only it is difficult to establish a telecommunication link using oam systems, but also, we are not really sure about how to calculate the link budget for such a system as theoretically the antenna’s gain is zero in its main direction. therefore, the main problem which is considered here is to define a value in which one can use in its calculations, called effective oam gain. * corresponding author. e-mail address: elaheshamushaki@email.kntu.ac.ir advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 118 the structure that was used in this paper, similar to [4, 8], is a phased circular array with each element having progressive 2πl/n phase difference, which leads to different orbital angular momentum (oam) mode numbers (l). the proposed structure is designed, simulated, and then used in a communication link to analyze the rate of receiving information in such systems by varying the distance between the transmitter and the receiver. it should be emphasized that for generating electromagnetic waves carrying oam beams, it is not necessary to use circular phased array antennas, but it is sufficient [8]. also, an effective gain is defined and introduced in order to evaluate oam links. 2. theoretical background when a wave beam has an amplitude distribution of ���, �, �� = � ��, ��� � � in the transverse plane, it carries angular momentum over the beam axis over a free space volume v, which is defined as follows. { }0 rej r e b dvε ∗= × ×∫ (1) where � is the free space permittivity and ∗ denotes a complex conjugate. this angular momentum is decomposed into spin angular momentum (sam) and orbital angular momentum (oam). spin angular momentum is related to the circular polarization of the wave beam, where orbital angular momentum is not related to the polarization of the light beam, and it is an extrinsic rotation of the electromagnetic wave. in fact, oam is related to the spatial structure of the wave-front [15]. decomposition of angular momentum into sam and oam is known as humblet decomposition, i.e., j l s= + (2) where ( ){ }0 re .l ie l a dvε ∗= ∫ ⌢ (3) { }0 res e a dvε ∗= ×∫ (4) the oam operator is occurred as �� = −��� × ∇� in (3) [4, 8, 16]. oam modes with unlimited eigenstates can improve the capacity of the communication system, comparing with sam with only two orthogonal states. the most usual antenna structure to generate oam beams is uniform circular (ring) array, similar to the structure of fig. 1(a). in general, when the goal is directivity, the whole circular plane is filled with antenna elements, which is called circular array in contrast with ring array in oam having elements only on its circumference. the fundamental theory of circular ring arrays has been studied in [17]. such a structure of fig. 1(a) is normally used for end-fire radiation pattern in the horizontal plane with elements pointing in different directions. in contrast, in oam applications, the radiation is desired in the broadside direction with the element pointing in the same direction, namely broadside. for such an array, one can formulate the radiation pattern of the array as the product of the element factor and the array factor, in which the array factor is given by the following equation: 1 2 exp sin cos n i af jka i n π θ φ =    = −      ∑ (5) where n is the number of elements in the array, � = 2π/λ and a is the radius of the ring. this radiation pattern is very similar to the 0th order of bessel function of the first kind (� ), when the number of elements approaches infinity [18]. advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 119 3. null of a circular array antenna using a circular phased array antenna is a way to generate electromagnetic waves carrying oam beams. such antennas can generate several oam modes just by tuning the feeding network or even having multiple beams feeding network to excite several oam modes simultaneously. assigning different information to each of these oam modes can increase the capacity of a communication channel. in this section, a circular phased array antenna that generates electromagnetic wave carrying oam is simulated and later used for our study. in the proposed antenna, � array elements are distributed equidistantly along a circle's perimeter. the radiating elements have identical amplitudes and they all point in the same direction. two adjacent elements have the phase difference 2��/�, and the !" element has the phase #$ = ��$ where � determines the oam mode number. possible values of oam modes are limited due to the number of array elements, where oam mode numbers greater than � = �/2 will not generate a pure rotating phase front [8]. the characteristic of an oam beam is its helical phase front. the magnitude and the sign of � defines the number of intertwined helices and the handedness, respectively [6]. in the proposed structure,12 dipole elements with the length of %/2 are placed in x − y plane, in y direction, operating at the frequency of 2.4*+,. the elements are phased such that two adjacent elements have the phase difference 2��/�. (a) structure of a circular array antenna and a monitoring screen (b) � = 0 (c) � = 1 (d) � = 2 (e) � = 3 fig. 1 different oam mode numbers of a circular array antenna fig. 1(a) shows the schematic of a circular array antenna with 12 dipole elements along the perimeter of a circle with the array diameter of 4% operating at the frequency of 0 = 2.4*+, and a monitoring screen away from it at the distance of 25% to show the electric field of different oam mode numbers. the amplitude (left) and the phase (right) of the electric fields for advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 120 different oam mode numbers at 2 = 25% meters distance from the antenna are simulated using matlab, as shown in fig. 1(b)-(e). according to diffraction theory, when oam beams propagate in free space, they diverge. by increasing the mode number of oam beams, they diverge faster, and consequently, the width and the depth of the null increases, as is shown in fig. 1(b)-(e). the schematic of the proposed circular array antenna simulated using cst is depicted in fig. 2, which has 12 dipole elements located on a circle’s perimeter and operating at the frequency of 0 = 2.4*+,. the diameter of the array is 2%. the length and the radius of the dipoles are 0.5% and 0.001%, respectively. fig. 2 schematic of the circular array antenna the reflection magnitude vs frequency plot for the proposed phased array antenna generating oam mode number of � = 0 is presented in fig. 3. fig. 3 diagram of the reflection magnitude (a) 3d radiation pattern (b) phase front fig. 4 simulated results of the circular array antenna with oam mode number of � = 0 advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 121 for an antenna carrying oam mode number of � = 0, the phase difference between adjacent elements is 0°, thus the wave front is like a plane wave. the 3d radiation pattern and the phase front of the circular array antenna carrying oam mode number of � = 0 is shown in fig. 4. as shown in fig. 4(a), the beam maximum is in the direction along the axis of the array and there is no null in this direction of the pattern. in the proposed antenna with oam mode number of � = 1, the phase difference between two adjacent elements is 2��/� = 30°. for this purpose, a controlled phase shift feeding network has been used. using this phase difference, causes the circular array antenna to generate beams carrying oam mode number of � = 1. the reflection magnitude versus frequency plot for the proposed antenna is presented in fig. 3. the 3d radiation pattern and the phase front of such antenna are shown in fig. 5. as shown in fig. 5(a), a null is created along the axis of the array, and the main lobe magnitude is weaker in comparison to fig. 4(a). in such an antenna, as shown in fig. 5(b), the phase front is helical. (a) 3d radiation pattern (b) phase front fig. 5 simulated results of the circular array antenna with oam mode number of 1l = 4. null performance in an oam link for an aperture antenna, the far field is proportional to the fourier transform of the aperture field [19]. to understand the far field behaviour of an oam antenna, a communication link is proposed by using a transmitter located on the left side and a receiver located on its right side, in the broadside direction of the transmitting antenna. the transmitter and receiver are circular array antennas with 12 dipole elements along the perimeter of a circle with the array diameter of 2%, as shown in fig. 6(a). in the proposed structure, 45 and #5 denote the radial and angular variables, the aperture field which is denoted by 0 and �5 shows the radial coordinate in the spectral domain, therefore, according to [20], the far field power pattern of the source is given by the following equation in (6), ( ) ( ) ( ) ( ){ } 0 l l l l l f k f j k d h fρ ρ ρ ρ ρ ∞ ′ ′ ′ ′ ′ ′ ′= =∫ (6) which is the hankel transform of order � of the function 0 �4 5� and � is the �67 order bessel function of the first kind. according to (6), for � 8 0 the value of � �0� is zero, which means the presence of a null in the boresight direction of the source. due to the characteristics of bessel function, increasing the number of � causes the size and the depth of the null to increase. therefore, when a receiver is located in the broadside direction of the source, increasing the number of � makes the receiving signal even weaker. this causes the transmitted signal to be wasted. also, increasing the distance of the receiving antenna from the transmitter causes an increase in the depth and the size of the null. advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 122 in this section, oam antennas are used in a communication link in order to improve the capacity and the security of the channel. therefore, the null performance and the rate of receiving the information have been analyzed as well. for this purpose, receiving and transmitting information in a communication link, and using two circular array antennas with 12 dipole elements along the perimeter of a circle with array diameter of 2% is considered, operating at the frequency of 2.4*+,. the simulated structure using cst is shown in fig. 6(b). in the following, three different feeding networks of the circular array antennas providing � = 0 and � = 1 oam modes and their effects on a communication link are considered using cst. (a) schematic of the communication link (b) the simulated communication link using cst fig. 6 communication link 4.1. transmitter and receiver carrying oam mode number of � = 0 in this part, elements of the receiver and the transmitter in the communication link in the same phase of � = 0, which are providing oam mode number of � = 0. in fig. 7, schematic of a two-port network has been presented. elements 1 to 12 constitute the elements of the transmitter and elements 13 to 24 constitute the elements of the receiver. each element has a controlled phase shifting feeding network. for such two-port network, s21 parameter is defined as follows. 2 21 1 10log p s p = (7) fig. 7 schematic of the two-port network in the proposed communication link, the receiver is located at the distances of 1000�8%�::, 2000�16%�:: and 5000�40%�:: away from the transmitter. the diagram of the insertion loss between the ports of the transmitter and the receiver, calculated as s21 parameter for different distances is presented in fig. 8. the obtained values of s21 are -16.92=, -21.62= and -31.42= for the distances of 1000::, 2000:: and 5000::, respectively. advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 123 according to fig. 8, as expected, increasing the distance of the receiver from the transmitter causes a decrease in the level of the receiving signal from the aperture of the receiver. fig. 8 diagram of the insertion loss 4.2. transmitter carrying oam mode number of � = 1 and receiver carrying oam mode number of � = 0 in this part, a circular phased array antenna with a feeding network generating oam mode number of � = 1 is designed as a transmitter, while the elements of the receiving antenna have the same phase, supporting oam mode number of � = 0. the diagram of the insertion loss between the ports of the receiver and the transmitter calculated as s21 parameter for different distances is presented in fig. 9. fig. 9 diagram of the insertion loss the obtained values of s21 are -58.82=, -64.72= and -70.62= for the distances of, 1000::, 2000::, and 5000::, respectively. comparison of fig. 8 with fig. 9 shows that when oam mode numbers in the receiver and the transmitter are different, the insertion loss in the proposed link is increased significantly. this shows low interference between the end ports of the transmitter and the receiver. fig. 9 also shows that increasing the distance between the receiver and the transmitter causes the drop of receiving signal level, as expected. 4.3. transmitter and receiver carrying oam mode number of � = 1 in this part, the transmitter and the receiver are circular array antennas carrying oam mode number of � = 1. the diagram of the insertion loss between the ports of the receiver and the transmitter calculated as s21 parameter for different distances is presented in fig. 10. fig. 10 diagram of the insertion loss the obtained values of s21 are -35.82=, -37.42=, -44.12=, -42.12= and -42.42= for the distances of 1000::, 2000::, 5000::, 7000::, and 10000::, respectively. advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 124 by comparing fig. 8 and fig. 10 with fig. 9, it is observed that when the transmitter and the receiver have the same oam mode numbers, the received signal level is relatively higher than when the modes are different. therefore, the full wave simulation shows that the receiver in an oam link receives the same mode number from the transmitter rather than other mode numbers demonstrating the orthogonality between them. this also indicates low interference between different oam modes. by comparing fig. 8 with fig. 10, it can be observed that increasing the mode number of oam antennas decreases the level of the receiving signal as expected due to the presence of a null at their boresight direction. 5. definition of effective oam gain 5.1. defining a reference gain assume that we have an oam link with two circular array antennas in front of each other. due to the presence of the boresight null in the radiation pattern of oam antennas, the observed gain on the axis of the link where the null is observed is negligible, theoretically zero. therefore, assuming ? = 0 to define the effective gain in an oam link will result in a very low effective gain, which is of course an undesired point for oam links. to resolve such a problem, one can assume that two oam antennas in a communication link are visible by each other in angles up to ? = tancd�e/2� above and less than ? = 0, according to fig. 6(a). by assuming angle ? as the higher angle from which the other antenna can be observed, we can define non-zero oam gain in the direction of the other antenna as a reference gain, which can be later used. it is clear that we don’t expect this value can be used in friis transmission formula. 5.2. using friis formula when there is an antenna link, we are able to calculate the effective gain of each antenna by using friis transmission equation. in [21-22], friis transmission formula for an oam link with two circular phased array antennas was used and discussed to evaluate the gain of the link. it is shown by them that the friis formula should be manipulated in order to fit oam links by introducing a new formulation which depends on 1/2�fgf| |� instead of 1/2f. the obtained result was dependent on variables such as the number of the elements of the circular arrays, the radius of the arrays, oam mode number of the antennas and also the distance of the receiver from the transmitter. however, having the well-known friis transmission formula as a basic equation to calculate the link budget, we use the same simple formula to demonstrate the superiority of oam links over none-oam cases. assume that a receiver and a transmitter with the gain of gr and gt, and the power of pr and pt, respectively, are placed in a communication link, separated by a distance of d and operating at the frequency of 0, if pt watts of total power from the source are delivered to the transmitter, the received power in the receiver, can be written as follows [4]. ( ) ( ) ( ) ( ) 2 2 2 2 2 , , 4 4 t t r t eff r p g g p g p d d θ ϕ θ ϕ λ λ π π = = (8) eq. (8) relates the free space path loss, antenna gains and wavelength, with the power of the receiver and the transmitter antennas. when the receiving and the transmitting antennas are exactly the same, the relation becomes simpler by having only one gain parameter. by having full wave results of a link simulation from the previous section and also using (7), we are able to calculate antenna’s effective gain geff from the s21 results of the link in a simpler form as shown in (9). ( ) 2 2 2 21 2 4 eff g s d λ π = (9) advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 125 friis transmission equation is valid when the antennas are in each other’s far field region. therefore, the far field of the proposed circular array antenna is calculated as �2if�/% = 1000::. thus, when the receiver is placed farther than the distance of 1000d mm= from the transmitter, friis transmission equation can be applied with acceptable accuracy. to calculate the effective gain of an antenna in an oam link with antennas carrying oam mode number of � = 0, friis transmission equation has been considered for different distances of the receiver from the transmitter which are in the far field of the transmitting antenna. according to (9), for � = 0, the effective gain is calculated by using fig. 8 and is presented in table 1. table 1 results of the communication link in fig. 8 d (mm) s21 (db) geff (db) 2000 -22 12.03 5000 -31 11.5 the obtained values of the effective gain are 12.032= and 11.52= for the distances of 2000:: and 5000:: respectively, which are equal to the simulation results of the radiation pattern in fig. 4. this validates the results of this method with the accuracy of around 12=. 5.3. defining oam gain then, proceeding to oam mode number of � = 1, the effective gain in the communication link with antennas carrying oam mode number of � = 1 is calculated according to the obtained values of s21 in fig. 10 and presented in table 2. the obtained results are 4.32=, 5.012=, 7.42= and 8.82= for the distances of 2000::, 5000::, 7000:: and 10000::, respectively. in order to have a fair comparison, the calculated effective gain is compared with the observed gain by one of the antennas view angles from the other one, namely as shown in fig. 1. the 2d radiation pattern of the antenna carrying oam mode number of � = 1 has presented in fig. 11. the view angle of each antenna by the other one for different distances has been calculated using (10). 1tan ( ) r d θ −= (10) fig. 11 2d radiation pattern of the circular array antenna as shown in fig. 11, the obtained values of *j are -0.922=, -9.452=, -11.742= and -12.82= for the distances of 2000::, 5000::, 7000::, and 10000::, respectively. thus, we are able to define a useful parameter called oam gain as the difference between the two as follows. gain eff oam db g db g dbθ= − (11) this parameter indicates that how much an oam system improves the obtained signal level at the receiver side compared to the maximum gain value, which is obtained from its radiation pattern in the broadside direction of the other antenna. the advances in technology innovation, vol. 6, no. 2, 2021, pp. 117-127 126 parameter can simplify the calculation of the link budget in such cases. table 2 shows the results of the s21 parameter, the calculated effective gain (geff), the effective area of the aperture (aeff), the view angle of each antenna by the other one (?) and its related gain (*j), and the oam gain (oamgain) of the communication link presented in fig. 10 for different distances. the view angle of each antenna by the other one is determined in fig. 6(a), and the effective area of the aperture is calculated using the following equation 2 4 eff eff a g λ π = (12) table 2 results of the communication link in fig. 10 d (mm) s21 (db) geff (db) aeff (m 2) θ (˚) gθ (db) oamgain (db) 2000 -37.4 4.3 0.0028 3.6 -0.92 5.22 5000 -44.1 5.01 0.0031 1.4 -9.45 14.46 7000 -42.1 7.4 0.0055 1.02 -11.74 19.14 10000 -42.4 8.8 0.0079 0.7 -12.8 21.6 in order to show the advantage of oam link, two simulations by using a communication link with a transmitter carrying oam mode number of � = 1 to a receiver carrying oam mode number of � = 0 are performed. the effective gain for the two other combinations has been calculated using fig. 9 and have been presented in table 3. the obtained values are -9.52= and -8.52= for the distances of 2000:: and 5000::, respectively. this makes us claim that an antenna with oam mode number of � receives the information of a transmitter with the same oam mode number, which makes the communication link secure. table 3 results of the communication link in fig. 9 d (mm) s21 (db) geff (db) 2000 -65 -9.5 5000 -71 -8.5 6. conclusion with reference to the nature of electromagnetic waves, orthogonality of different modes makes it possible to transmit several categories of information simultaneously at a single frequency. in the presented paper, this property of electromagnetic waves has been analyzed using orbital angular momentum (oam). for this purpose, we have simulated a circular phased array antenna generating beams carrying oam and then used them as a transmitter and a receiver in a communication link. for non-zero oam links, the gain parameter cannot be calculated as usual because of the presence of a null in the beam axis of the radiation pattern of such antennas. by using two new gain parameters, we defined the concept of oam gain for the first time in 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[22] d. k. nguyen, o. pascal, j. sokoloff, a. chabory, b. palacin, and n. capet, “antenna gain and link budget for waves carrying orbital angular momentum,” radio science, vol. 50, no. 11, pp. 1165-1175, november 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-aiti#6494 74-89.docx advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 development of a small intelligent weather station for agricultural applications yi-hua chung 1 , jun-fu huang 2 , yuan-chen hu 2 , chen-kang huang 2,* 1 department of chemistry, national taiwan university, taipei, taiwan 2 department of biomechatronics engineering, national taiwan university, taipei, taiwan received 29 september 2020; received in revised form 08 december 2020; accepted 01 february 2021 doi: https://doi.org/10.46604/aiti.2021.6494 abstract it is known that climate change causes a decrease in the profit gained from agricultural production. this work designs and establishes weather boxes equipped with functions of rainfall prediction, frosting forecast, and lightning detection. with the wireless connection and the build-in decision mode, weather boxes can deliver early-warning by sending texting messages to the users and actuating the corresponding action to response the extreme climate. to implement rainfall and frosting prognostication, two different datasets are analyzed by the technology of data mining. one of the datasets is acquired from the central weather bureau, and the other is from the proposed weather box monitoring the agricultural environment. from the experimental results, the prediction model constructed from the data which is collected by the proposed weather box exhibits a higher accuracy in rainfall forecasting than those based on the central weather bureau. keywords: weather box, rainfall, frosting, lightning, early warning 1. introduction climate change and agriculture gain have a reciprocal relationship. climate change may cause a decrease in the profit gained from agricultural production. therefore, accurate weather forecasting becomes an important but challenging task to researchers for a long time. in addition, numerous people are aware of climate-changing. for example, orchardists pay attention to the amount of rainfall, which affects the fruit quality. the frosting, which will impact the flavor and aromatics of the tea, is concerned by tea growers. lightning is responsible for plantation fires and the death of the crops [1-3]. recently, the continuous advances in sensors, sensing systems, and the internet of things (iot) [4-5] technology significantly impact several fields. for instance, in the agriculture fields, to accomplish the task of the remote environment monitoring for the farmland, developers can utilize single-board microcontrollers or computers to connect with various sensors to collect and accumulate a large amount of local environmental data at first. the data can be analyzed to get a more undiscovered relationship between the data via the technology of data mining [6-12]. after all, those relations can be used to achieve the goal of future predicting. currently, some companies and organizations, such as airports and agriculture agencies, collect and accumulate the weather data by their own weather stations to fulfill some of their particular needs. the data, which is for weather monitoring or predictions, become more precise when a greater amount of data are collected and analyzed. * corresponding author. e-mail address: ckhuang94530@ntu.edu.tw tel.: +886-2-3366-5351 advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 75 official weather stations collecting professional data are precious. however, these weather stations are mostly found in the research institutions located in urban area far from the remote agricultural locations, which may cause the grabbed data to have some potentially hidden problems. fortunately, the concepts, such as free software and free hardware can significantly reduce the cost of a station. to construct a low-cost weather station, the developers can modify the existing version to reduce or increase the functions and costs based on the needs. sensors are elements that translate a usually non-electrical value to an electrical value, which can be measured, amplified, or even modified. to manage and control these sensors and share the collected data, some new low-cost single board computers may be used, for example, arduino and raspberry pi. it is commonly known that the central weather bureau (cwb) has already set up numerous weather stations nowadays. nevertheless, most of the weather stations are built in the megalopolis instead of some distant regions. furthermore, most of the commercially available weather stations are too expensive to be afforded. low cost weather stations are required to set up in remote agricultural area. the functions of the weather boxes constructed in this work are shown in fig. 1. this paper is purposed to construct a weather box with the ability to perform rainfall, frosting prediction, and lightning detection. for the first aim, rainfall prognostication, a weather box is constructed with the wemosd1 choosing to be the microcontroller. three sensors, bme280, fc-37, and gy-49 are used to sense the humidity, temperature, pressure, rain, and solar radiation as the local weather parameters to accumulate the amounts of the local weather data in three experimental fields, including taipei city, taoyuan city, and yilan city. after stockpiling the local weather data, data sets from (1) weather box or (2) the historical dataset released by the cwb, which consists of several atmospheric attributes, are analyzed by the techniques of data mining to extract the hidden relationships among weather parameters. above all, as the weather box releases a heavy rain alerting by the prediction of the weather forecasting model, it can also send out the alarming message to the users by the communication application. fig. 1 different weather boxes with various functions constructed in this work second, the frosting module is added into the system with both of the frosting point exploring and recording functions. when in the exploring mode, the testing surface is lowered by the thermoelectric cooler controlled by raspberry pi. during the surface temperature drop, photos are taken and analyzed thereafter. when the frost is first observed, the surface temperature is considered as the frosting point for the corresponding environment temperature, pressure, and relative humidity. when in the recording mode, a webcam is set to take photos at the testing surface regularly. the series of photos are analyzed to find out the frosting occurrence and its corresponding surface temperature. lastly, regarding the lightning detection, the weather box attained the greatest performance with precision = 66.7% and recall = 22.2% on may 27, 2020, in taipei, and precision = 71.1% and recall = 45.8% on july 16, 2020, in yilan. obviously, the presentation of the detecting results in yilan is better than those in taipei as the section of result and discussion shown. the main causation for the poor performance of the recall is because of the small bandwidth for the detecting frequency of the lightning events. unfortunately, the data released by the cwb is constructed by the cg flash and ic flash events. however, the as3935 sensor can only detect some of the cg flash events, and all of the ic flash events can not be sensed by the as3935 due to the narrow bandwidth of it. the principal reason for the subpar precision is on account of the detection method we chose, radio detection. though we put effort into finding the experimental fields without noises, the system is still easy to be affected by the disturbers in the environment. advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 76 2. literature review low-cost weather stations were developed in previous literature [13]. to establish the weather station, r. c. brito’s team firstly proposed an architecture structured in layers, which considered the scalability of the system and allowed the connection of new sensors to support the needs of monitoring new data. each feature in this structure was equipped with specific hardware, and the sensors would send the measured data back to the arduino through different means, such as cable, analogically, or digitally. the arduino used i 2 c communication protocol to exchange information with the raspberry pi. the raspberry pi was connected to the internet through rj-45 cable, which sent the data to a web server, the database. it also shared the data in rest format, which could be read by web pages, desktop applications, and mobile devices. the connection to the internet was done through a wifi or cellular (gsm, 3g, 4g) network. proprietary resources weren't used in the creation of this weather station. all the elements, such as hardware, software, and communication protocols were free to use and low-cost to construct. in the literature and this work, the classification in matlab toolbox, including decision tree [14], support vector machine [15-17], k nearest neighbor [18], and bagged tree [19-20], was used to find the best classification to construct the rainfall prediction model of rainfall. the last case is lightning detection. discharge activity is a weather phenomenon, including two types. lightning of cloud to cloud is called ic flash, and lightning cloud to ground is called cg flash. besides, the cg lightning has a more harmful destructive power to the targets on the ground, including human beings, forest creatures, and so on. commonly, there are three ways to detect the lightning event, inclusive of radio detection, radar detection, and optical lightning detection [21]. in [22], an intelligent lightning detection system was constructed. the system was built on a lightning signal collection module, central control module, display module, memory module, time module, and host computer module, which is established to cope with the problems of the high cost and the lacking the weather stations for detecting lightning. the 32-bit arm stm32f103 was used to act as the core, microcontroller, of the system. as the lightning occurrs, the lightning signal acquisition module will output a signal pulse which implies the fast sampling intensity of the lightning in real-time, and the sampled data is transited to the arm stm32f103. after receiving the data, the microcontroller will count the number of lightning and the strength through tft color screen display, automatically record the time of lightning occurs, and store these data in the sd card. meanwhile, via rs485 bus, the arm stm32f103 will transmit processed data to the pc. monitoring software in the pc which allows the users to get monitoring instantaneously about the number of lightning occurring and the lightning intensity. moreover, the data can be stored on a computer hard drive, with retrospective queries functions. after owning the ability to detect whenever lightning occurs, another task that needs to be solved is lightning positioning development. as the previous paragraph mentioned, the method of radar to detect lightning is mainly used for thunderstorm activity detection, and it is impossible to detect single lightning and its intensity parameters. therefore, in order to judge the real placement that the lightning happens, the tome-of-arrival (toa) method and the magnetic direction method (mdf) are used in combination. referring to the main purpose of distant regions’ remote environmental monitoring, the way of radio detection is chosen to be used to sense the lightning events, and the events of cg flash are mainly focused on. to complete lightning detection, the as3935 [23] sensor is used to support our decision model to make the arbitration and the raspberry pi acts as the core. two experimental fields, including national taiwan university in taipei city and the national yilan university in yilan city, are set. when the microcontroller is connected to the internet, the collected local lightning events data will be uploaded to the intelligent biosensing platform, an online website. otherwise, the data is accumulated in the micro sd card slotted on the microcontroller. after piling up the data, the data collected by the weather box is compared with the lightning events data released by the cwb, which is open access, as the benchmark to ensure the precision and the accuracy of the data collected by the weather box. advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 77 the results of rainfall prognostication show that the best prediction model that covered the data collected by the weather box is knn (k=3). as for the data released by the cwb, bagged tree is the best. besides, the matthews correlation coefficient (mcc) [24] is used as the index to measure the qualities of the classifications used in the experiments. as the experimental result showed in the results section, the best mcc number of the models to predict rainfall before raining for 2-hr of the data collected by the weather box is 0.925 (knn), which is better than 0.596 (bagged tree), the outstanding mcc of the data released by the cwb. compared to the cwb data, the reasons why the data collected by the weather box, lead to more precise and instantaneous prediction models are on account of the higher location congestion of the weather stations and the more frequent interval of the detecting time. for the frosting prediction, the alarming would take the corresponding actions when the temperature < 5°c, less cloud cover, and the relative humidity greater than 60% were occurred simultaneously. 3. material and methods 3.1. rainfall forecast (1) weather box construction fig. 2 the rainfall weather box designing flow chart fig. 3 the rainfall weather box experimental set-up diagram to reach the goal of rainfall forecast, a weather box is constructed to collect the data, which has a coverage of a small area, in order to provide an instantaneous and short-range weather prediction that reflects the real local weather accurately. considering the problem of accessing internet [20] in the remote region and the cost of the weather box, wemosd1 is chosen advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 78 to be the core of the weather box for its’ low-cost and self-contained wi-fi networking capabilities. the weather box of rainfall prediction was equipped with three different detecting sensors, including bme280, fc-37 and gy-49. they are used to sense the humidity, temperature, pressure, rain and radiation and used four li ion 186500 batteries in parallel as its’ power supply. the weather box designing flow chart is shown in fig. 2 and fig. 3. besides, the voltage given by the 3.7v batteries does not meet with the specification of the wemmosd1. we cope with the dilemma by assembling a step-up transformer, which is constructed with a boost convertor, lm-2577, and a protection circuit module, xd-58a, which can increase the voltage to the scope of application. furthermore, ssd1306-oled is selected as the display module to be the monitor for our climate box. there are five layers for the module to set out distinct information. the first layer shows the time and date instantly. the second and third layers illustrate two kinds of datasets that are both grabbed from the openweathermap api, a website provided by the cwb open information. primarily, the second layer, which presents the instantaneous rainfall prediction, indicates some messages, including the character to judge the weather today, t symboling the temperature, h representing the humidity, p designating as the pressure, and w stood for the wind speed. then, the third layer denotes weather forecasting with three days in succession, which helps us to predict the climate during the upcoming three days. the forth layer, which demonstrates the dataset supervised by our sensors straight away. additionally, the data of the instantaneous rainfall prediction provided by the cwb open information is used to compare with the dataset supervised by our sensors. after gripping the data, there are two different ways for data storage. ultimately, the fifth layer acting as the recording layer aims to determine which way is used to store the data and checked whether the sd card works correctly. cooperating with the internet accessibility, if the internet is connected, the data sensed will be sent to the cloud, thingspeak, or the data will only be stored in the sd card module. notably, when the reading of the fc-37, the rain sensor exceeds the setting threshold. a text message will automatically be sent to the users for the heavy rain advisory by using ifttt, a freeware web-based service that creates chains of simple conditional statements [25], or a communication application. (2) data gathering from weather box as completing to manufacture the weather box, the experimental fields are set in the national taiwan university in taipei, taoyuan city, and pear orchard located at yilan city. since the bme280 sensor needs to be situated in the outside of the weather box to get a precise record. therefore, all of the weather boxes for experimental fields are located at the places that sheltered from the storm to satisfy the needing and prolong the service life of the sensor at the same time, as shown in fig. 4. nevertheless the rain sensor, the fc-37, demands to be exposed under the rain to catch the information of the instant raindrop so that the fc-37 sensor are extended out of the shelter. fig. 4 the rainfall prediction weather box the first experimental field is national taiwan university. it is worth mentioning that the rain detector is leaned in a slanted position to let the water roll down through the edge to avoid having puddles on the sensor, as shown in fig. 5. in addition, the second experimental field is set up in taoyuan city to be a comparison to the first field to find out whether the advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 79 experimental location will impact our rainfall weather box or not shown in fig. 6. the last field is located in the pear orchard in yilan city. apart from the other two fields, this field grabs another two specific weather parameters, inclusive of soil humidity and soil electrical conductivity. the method of supervised learning is used and corresponding class labels are given as either sunny or rainy to construct a new rainfall prediction model, which is distinguishing from the previous weather boxes. fig. 5 the rain detector was leaned in a slanted position (taipei) fig. 6 the rain detector was leaned in a slanted position (taoyuan) (3) data pre-processing after accessing two datasets (the daily meteorological report provided by the cwband the data accumulated by our rainfall weather box) the data must have been rectified by data cleaning for the following three different cases. firstly, for the data collected by our weather box every ten minutes, the anomalous data caused by the problems of instrument and data transfer should be disposed of. the reason why those data can be abandoned is that it will not have a significant change of weather status in ten minutes (the time interval that we collected one piece of data). for the data provided by the cwb, there are two parameters that needs to be processed. that is, if the symbol of “v” is presented in wind direction, the current value of the wind direction will be replaced by taking the average of the previous data and the next one. likewise, if the symbol of precipitation is “t”, which implies the data is less than 0.1mm, the precipitation value will be altered by replacing it with 0.1mm. in order to design a rainfall-forecast model which could give out the alarm two hours earlier, the method of supervised learning is used. a rainfall label is constructed for the labeling schema, which is defined as follows: 1, if rain or two hours before rain 0, otherwise label  =   (1) the methods used for feature scaling are min-max normalization and standardization (z-score normalization) in this paper. although there are 17 weather parameters, some of them are lost. thus, only eight of them are chosen to be the training features, including temperature, dew point, relative humidity, atmospheric pressure for weather station and sea level, wind advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 80 speed, wind direction, and solar radiation. after that, the 10-fold cross validation measurement is used to test and improve those constructed models. all of the machine learning model is developed in matlab. 3.2. frosting prediction the raspberry pi controls two sensors, including the bme280 and ds18b20. the bme280 detects temperature, humidity, and pressure in the air; the ds18b20 measures the temperature of the surface. in the hoarfrost point finding mode with the temperature controller and the thermoelectric cooler module the hoarfrost point is measured in any environment by gradually decreasing the surface temperature. in normal mode, the thermoelectric cooler module only have the function of heat dissipation by running fans. by the heat pipe in the thermoelectric cooler module, the surface temperature is close to the atmospheric temperature to simulate the leaf in the outdoor environment for a long time. the picture of the frosting prediction weather box is shown in the fig. 7. the experimental field is set in the tea plantation in fushoushan farm in taichung. fig. 7 the frosting prediction weather box 3.3. lightning detection for lightning detection, a lightning detecting weather box is constructed with raspberry pi acting as the microcontroller. the raspberry pi is connected to two sensors, as3935 and bmp180. the weather box is illustrated in fig. 8. following ensuring the connection of the hardware, the first case is tuning the loop antenna. the loop antenna is designed to have a resonance frequency at 500khz, which is the same as the lightning frequency of most lightning events of cg flashes, by adding or removing the tuning capacitors from 0pf to 120 pf in the step of 8pf to optimize the performance of the signal validation and distance estimation. the embedded algorithm will check the incoming signal pattern to reject the potential man-made disturbers [26]. fig. 8 the lightning detection system in a thermometer shelter in yilan advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 81 in this paper, the sensor interacts with the raspberry pi via spi protocol, and python2 is chosen as the developing language with package “spidev” (a python module for interfacing with spi devices from user space via the spidev linux kernel driver). there are four focused programmable settings in this paper. the first one is analog-front-end (afe), which is a setting that can amplify and demodulate the ac-signal picked up by the antenna. the second one is mask disturber (mask_dist), which can shield the man-made disturber from the as3935. the third one is spike rejection (srej), which is used to increase the robustness against false alarms from such disturbers with its range between 0 and 15. the last one is noise floor level threshold (nf_lev). the output signal of afe is also used to measure the noise floor level, which is continuously compared to the noise threshold. whenever the noise floor level exceeds the noise threshold, as3935 issues an interrupt, int_nh, to inform the raspberry pi that it cannot operate properly due to the high input noise received by the antenna in this work. after the pre-work of the system is finished, whenever an event happened, the int pin will go high, which implies that an event had happened. if the event is judged as a lightning event, the estimated distance of the lightning will be recorded in the register and stored in the micro sd card, as the algorithm flow chart shown in fig. 9. the collected data will be sent to the intelligent biosensing platform within 6 hours, and the lightning detection system status can be monitored remotely with the weather boxes working automatically. fig. 9 the algorithm works flow chart of lightning detection system 4. results and discussion 4.1. rainfall forecast (1) taipei, data collected by weather box the instantaneous rainfall prediction model uses four parameters as inputs, including temperature, humidity, pressure, and solar radiation at that time to determine whether it is raining or not. as table 1 shows, all of the models used in this advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 82 research reaches an accuracy of over 90%, and the model using knn is the best. for constructing a model to predict raining before 2 hours, the extra models are built in two cases, inclusive of “before raining for 1-hr prediction model” and “before raining for 2-hr prediction model”. as the results portrayed in table 2 and table 3, both of the outstanding models for the two cases are the models utilizing knn classifiers. table 1 the result of instantaneous rainfall prediction model (taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 94.3% 94.9% 93.9% 97.2% 89.0% 95.9% 91.3% 0.867 bagged tree 96.9% 97.0% 97.7% 99.0% 93.8% 97.9% 95.7% 0.928 knn(k=3) 97.4% 98.3% 96.4% 98.7% 96.0% 98.5% 96.1% 0.941 svm 90.8% 92.1% 88.3% 95.1% 83.1% 93.4% 85.6% 0.786 table 2 the result of before raining for 1-hr prediction model (taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 94.0% 93.8% 93.7% 96.9% 87.7% 95.4% 90.9% 0.863 bagged tree 96.7% 96.7% 97.5% 98.4% 93.5% 97.4% 95.4% 0.925 knn(k=3) 97.1% 98.1% 96.1% 98.5% 95.7% 98.3% 95.9% 0.934 svm 90.4% 91.0% 88.0% 94.5% 82.3% 92.7% 84.9% 0.782 table 3 the result of before raining for 2-hr prediction model (taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 91.7% 91.5% 92.2% 96.3% 84.1% 93.8% 87.8% 0.821 bagged tree 96.4% 96.1% 97.3% 98.2% 93.4% 97.1% 94.9% 0.922 knn(k=3) 96.6% 97.8% 96.0% 98.3% 94.5% 98.0% 95.2% 0.925 svm 88.6% 89.9% 88.1% 94.1% 80.5% 91.9% 83.8% 0.750 (2) taoyuan, the data collected by weather box similar to the method used to predict rainfall in taipei, there are also three models constructed in this part, inclusive of the “instantaneous rainfall prediction model”, the “before raining for 1-hr prediction model”, and the “before raining for 2-hr prediction model”. as the results showed in table 4, table 5, and table 6, the models using knn as a classifier have an exceptional outcome. it is worth mentioning that the models using bagged tree as their classifier in taoyuan are better than those in taipei. table 4 the result of instantaneous rainfall prediction model (taoyuan) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 94.3% 96.2% 86.1% 97.0% 82.5% 96.4% 83.9% 0.804 bagged tree 96.8% 97.2% 94.3% 99.0% 88.1% 97.9% 90.9% 0.891 knn(k=3) 97.1% 97.4% 94.4% 99.1% 88.9% 98.1% 91.6% 0.899 svm 89.9% 92.9% 73.5% 94.2% 70.0% 93.4% 71.7% 0.651 table 5 the result of before raining for 1-hr prediction model (taoyuan) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 93.2% 95.1% 86.0% 97.0% 80.1% 95.9% 82.8% 0.783 bagged tree 96.2% 97.0% 92.1% 99.0% 87.3% 97.9% 89.6% 0.877 knn(k=3) 96.4% 97.2% 93.1% 98.1% 88.2% 97.4% 90.5% 0.884 svm 88.8% 91.5% 72.4% 94.1% 68.1% 92.9% 71.0% 0.639 advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 83 table 6 the result of before raining for 2-hr prediction model (taoyuan) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 93.2% 92.9% 85.0% 96.1% 76.1% 94.4% 80.2% 0.753 bagged tree 96.0% 96.8% 92.1% 98.2% 88.1% 97.4% 90.1% 0.881 knn(k=3) 96.0% 96.9% 92.0% 98.2% 88.0% 97.5% 90.0% 0.882 svm 87.7% 91.0% 74.6% 93.8% 65.6% 92.4% 70.0% 0.629 (3) yilan, the data collected by weather box apart from the models used in the previous fields, models in this part are constructed differently for comparison to the previous ones. the models constructed in this part use six parameters as inputs, including temperature, humidity, soil humidity, soil electrical conductivity, wind speed, and solar radiation. as the results illustrated in table 7, the performance in yilan is not as good as those in other experimental fields. besides, the model using svm as a classifier have a recall of zero to predict rainfall. table 7 the result of instantaneous rainfall prediction model (yilan) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 87.9% 93.1% 71.1% 91.8% 73.2% 92.4% 72.1% 0.646 bagged tree 91.3% 90.2% 86.3% 96.7% 72.9% 93.3% 79.0% 0.736 knn(k=3) 87.3% 90.8% 72.0% 92.1% 69.3% 91.4% 70.6% 0.626 svm 77.9% 78.0% 22.0% 100% 0% 87.6% 0% 0 (4) taipei, the data provided by central weather bureau as shown in tables 8 to 10, it can be found that models trained by the data collected by the weather boxes in taipei have lower accuracies. the models using bagged tree as their classifier perform best in this part. moreover, the accuracy and recall of predicting rainfall decrease for longer predictions. table 8 the result of instantaneous rainfall prediction model (cwb_taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 86.7% 90.8% 69.2% 94.1% 55.3% 92.4% 61.4% 0.537 bagged tree 87.8% 90.2% 74.4% 95.7% 56.3% 92.8% 64.0% 0.574 knn(k=5) 84.8% 90.5% 61.1% 90.3% 60.4% 90.3% 60.0% 0.508 svm 85.7% 88.2% 69.3% 95.4% 46.6% 91.6% 55.7% 0.481 table 9 the result of before raining for 1-hr prediction model (cwb_ taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 84.6% 90.7% 69.8% 94.1% 54.1% 91.9% 60.9% 0.523 bagged tree 86.3% 90.0% 74.3% 95.4% 56.4% 92.4% 64.1% 0.575 knn(k=5) 83.3% 90.2% 61.4% 91.3% 58.2% 90.7% 60.0% 0.501 svm 83.8% 88.3% 69.5% 95.2% 46.3% 91.6% 55.5% 0.487 table 10 the result of before raining for 2-hr prediction model (cwb_ taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 83.3% 86.1% 72.3% 93.5% 54.1% 89.3% 61.8% 0.523 bagged tree 85.7% 88.1% 78.3% 94.0% 60.4% 90.9% 68.1% 0.596 knn(k=5) 82.4% 86.7% 63.4% 88.7% 60.2% 87.4% 61.7% 0.495 svm 82.3% 84.8% 72.1% 94.6% 49.1% 89.2% 58.4% 0.487 advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 84 three types of models use four classifiers to find out the best classifier to fulfill the task of rainfall forecast. as the results shown in table 1 to table 3, for the three types of the models, it is obvious to recognize that the all of the models using the knn as a classifier have the best performance, and those who used svm have the worst. as for the models utilize the data provided by the cwb in taipei used eight training features, inclusive of temperature, dew point, relative humidity, atmospheric pressure (weather station and sea level), wind speed, wind direction, and solar radiation. the training results of these models indicate that the models using bagged tree as their classifier have the top achievement, and those using svm as their classifier look wretched as the results shown in table 8 to table 10. by the comparison of the models between the two different datasets, the prediction results suggest that the models which use the data collected by the weather box rather than the cwb lead to the increase of the predicting accuracies. additionally, it is clear to find that the accuracies decrease continuously from the “instantaneous rainfall prediction model” to the “before raining for 1-hr prediction model” until the “before raining for 2-hr prediction model”. it is thought to because of the wrong prediction of the rainfall. as the high density of the orange dots that denote raining between the humidity of 70% and80% in the humiditypressure graph in fig. 10, this situation implies that the prediction models might have had the wrong prediction in this zone caused by the high density. this might also be the reason why the rainfall prediction results at the yilan experimental field are worse than those at the taipei. because the weather in yilan is more prone to rain, and the detected humidity maintains at a high level which might cause the misjudgments. fig. 10 the humiditypressure graph provided by the cwb in order to have a higher accuracy of the rainfall prediction before raining for two hours earlier, the construction of the data is modified to build more accurate prediction models. more data are being labeled as “raining” in the new and “before raining for 2-hr prediction model” in the following extra experiments by adjusting the ratio of the raining data to no-raining data to find out the best constitution of the training datasets for the four classifiers as presented in table 11, though this action might have led to the ability to forecast no-rain decrease. for the following experimental results, these models of cwb and of our weather box are tested during other raining days. the experimental results are demonstrated in table 12 and table 13. it is suggested that because the shorter data collecting period(ten minutes) which is more frequent than an hour, the period time of cwb grabbing data, causes a higher accuracy as the reason in the previous part. additionally, the models built by the data collected by the weather box are overfitted, which leads to the poor performance as presented in table 12 and comparing to the results in table 11. for the results in the experimental field in taoyuan, the best recall of the models built to forecast the rainfall in taoyuan is 88%, which is lower than the best recall among all models in taipei, 94.5%. this is caused by the different locations where the weather boxes are placed. the weather boxes in the taoyuan experimental field are placed indoors. even though we try to extend the weather boxes to the outdoors, they are still placed directly indoors. nonetheless, the weather boxes in taipei advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 85 experimental fields are placed in the outdoors, which receive the weather parameters directly. another possible reason is the terrain, since the topography of taoyuan city is tableland, dissimilar to basin, the terrain of taipei. for the models in yilan, though they use more weather parameters than those in taipei, they perform poorly. for example, as the table 7 showed, the model using svm as classifier has no ability to predict rainfall. the reason is because of the lack of the label of the state of weather. to fix up this problem, the corresponding method is taken at the time using the relative humidity to substitute the label of the state of weather. the fixing approach is applicable because it is obvious that as soon as the fc-37 sensor of the weather box detectes the raindrop, the reading of the humidity will increase instantly as response. the results reveal that this solution is not a proper way to take. therefore, there are some recommended improving ways to implement these models. for example, adding some extra indicators such as rain gauge and raindrop sensor for the experimental modules might help predicting the rainfall. otherwise, the collected data should be analyzed through the differential method to find the trend of the rain point. table 11 the result of before raining for 2-hr best-ratio prediction model (weather box_ taipei) classifier accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 93.7% 94.2% 92.2% 95.8% 90.1% 94.9% 91.1% 0.862 bagged tree 93.5% 94.1% 92.3% 96.1% 89.8% 95.0% 91.0% 0.858 knn(k=3) 93.9% 92.4% 96.0% 98.5% 86.9% 95.3% 91.2% 0.868 svm 92.0% 91.1% 93.8% 96.5% 83.5% 93.7% 88.3% 0.825 table 12 result of before raining for 2-hr best-ratio prediction model (1) (cwb_ taipei) classifier ratio accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 75:25 83.7% 88.3% 64.5% 91.1% 57.7% 89.6% 60.9% 0.506 bagged tree 50:50 79.7% 92.7% 52.7% 80.3% 77.8% 86.0% 62.8% 0.513 knn(k=5) 50:50 79.0% 91.7% 51.8% 80.4% 74.2% 85.7% 61.0% 0.487 svm 50:50 81.1% 92.0% 55.3% 83.0% 74.4% 87.3% 63.4% 0.520 table 13 the result of before raining for 2-hr best-ratio prediction model (2) (cwb_ taipei) classifier ratio accuracy precision recall f1 measure mcc no rain rain no rain rain no rain rain decision tree 75:25 72.6% 91.0% 47.1% 70.4% 79.2% 79.4% 59.1% 0.434 bagged tree 50:50 77.4% 92.2% 53.2% 76.4% 80.6% 83.6% 64.1% 0.508 knn(k=5) 50:50 77.1% 87.1% 53.5% 81.5% 63.9% 84.2% 58.2% 0.429 svm 50:50 69.8% 92.7% 44.5% 64.8% 84.7% 76.2% 58.3% 0.430 4.2. frosting prediction via some tentative, there are three situations found to be the conditions of frosting, involving “as the temperature is lower than 5°c”, “the cloud cover is less”, and “the relative humidity is higher than 60%”. under these situations, the weather box will send out a warning message to alarm the users to take some protection procedures, such as spraying water when the phenomenon of frosting is occurring or applying irrigation before the crops are frosted at nights soon. 4.3. lightning detection after constructing the lightning-detecting weather box, we start to collect the lightning data and optimize the related settings based on the feedback of the collected data during the plum rain season in taiwan. besides, we use the lightning data received by the central weather bureau as the standard to evaluate the recall and precision of the data we receive. moreover, five minutes is set as a time-interval. that is, if the central weather bureau and the weather box we constructed both receive lightning events in the same time-interval, we consider that the data detected from both resources are the same flash event. some parameters are defined as the followings, the units of them are the number of time-intervals. advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 86 : true positive if both resources received data (2) : false positive if both weather box received data (3) : false negative if only cwb received data (4) + true positive recell true positive false negative = (5) + true positive precision true positive false positive = (6) the reason why we use time-interval to calculate the recall is because the as3935 sensor will only record the most recent data among all the detected lightning events during one time-interval. the estimated distance does not represent the distance to a single lightning event but the estimated distance to the leading edge of the storm. for instance, if there exist three lightning events which estimated distances are 1-km, 3-km, and 5-km at the same time-interval, the as3935 will only record the lightning event of the 1-km one during this time-interval. as the results shown in table 14, both of the recall and the precision outcome are not good enough, especially the performance of the recall. besides, compared to the results in the field of taipei in table 14, the results, no matter the recall or the precision, in yilan in table 15 present better. the reasons of the poor performance of the lightning detection system are discussed in the following. table 14 the part of lightning events result in the field of taipei data received during 2020/05/26 parameter true positive false positive false negative recall precision counts 2 3 6 25.0% 40.0% data received during 2020/05/27 parameter true positive false positive false negative recall precision counts 2 1 7 22.2% 66.7% data received during 2020/05/28 parameter true positive false positive false negative recall precision counts 1 1 9 10.0% 50% table 15 part of lightning events result in the field of yilan data received during 2020/07/01 parameter true positive false positive false negative recall precision counts 35 17 78 31.0% 67.3% data received during 2020/07/10 parameter true positive false positive false negative recall precision counts 17 8 42 28.8% 68.0% data received during 2020/07/16 parameter true positive false positive false negative recall precision counts 27 11 32 45.8% 71.1% at the beginning of the experiment, it is found out that the constructed lightning detection system is vulnerable to be interference with external disturbance. the data collected in march fills with a distance of 1 km. there are some possible reasons to discuss. the first one is because of the noise generating by the raspberry pi itself. another is that the ntu's internet base station formed an interference source that is 1-km away from the place where we collect the data. the fixing-up solution we adopt is extending the wires to make the microcontroller become farther away from the as3935. this demand is due to the detection way of as3935, radio detection, which is known to be sensitive to any other nearby interference [21]. advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 87 so during april, we put the effort into finding the proper places with fewer disturbers to collect the lightning data, and the experimental field is finally set on the top floor of the department of bio-mechatronics engineering of ntu for less man-made interference. the power supply used at that time is solar power, and the weather box is placed under the solar panels to shield from the rainfall. however, after several times failing to receive data, we ultimately find out that the solar panel will block the reception of electromagnetic waves. the lightning detection system is finally placed in a thermometer shelter to avoid the rain from destroying the system. besides, the system is connected to the power wire of raspberry pi to the socket as the power supply. additionally, the pieces of lightning events collected by the weather box are far less than those provided by the cwb during one storm in the experimental field of taipei. it is supposed that the number of weather stations of the weather box in taipei is far less than the number of weather stations of cwb in taipei. furthermore, it is easy to reveal that the recall and the precision of the system perform worse than expected. the first reason causing the poor recall is due to the narrow bandwidth of the as3935 to collect the lightning events. it is known that the frequency bandwidth of cg flash is 3-3000khz, and the frequency bandwidth of ic flash is 30,000-300,000khz. however, according to the datasheet of as3935, the as3935 only receive lightning events with frequency in the range of (500 ± 33) khz. there are large amounts of the lightning events that are not able to be received by the as3935, which have caused the number of false negatives soaredand poor performance of recall. for the precision, though the precision is better than the recall in the taipei field, it still does not meet with the expected result. the main reason to be discussed is the disturbance. raspberry pi 4 and raspberry 3b+ are used as the microcontroller at the beginning. however, the experimental data points out that the noises generated by raspberry pi 4 will misjudge as the lightning events, which give rise to the number of the true positive and decreased the precision of the detection system. moreover, as mentioned in the first paragraph of this section, though the chosen experimental field in taipei is as possible as interference-free, the unexpected man-made disturbance can not be avoided completely, which increases the true positive and the decreased the precision. additionally, it is worth mentioning that even if the datasheet of as3935 claims that as3935 is subjected to lightning events with a radius of 40 kilometers, according to the actual use, the range of lightning events that can be detected as completely as possible is 20 kilometers. besides, compared to the results of taipei experimental field, the results in yilan perform noticeably. two main differences are responsible for it. firstly, the disturbance with a radius of 40 kilometers of the yilan field are lesser than the taipei field. secondly, the lightning detection system in yilan had an automatic scheduling function, and the system will retune the antenna every minute to ensure the accuracy of every moment. additionally, this system can also be connected remotely to observe and monitor the working status of the entire system at any time. into the bargain, from the lightning observation document of the cwb, an experiment is done to count the lightning events collected by different lightning-detecting systems during a storm in [26]. the plotting-results reveal the number of lightning events collected by different systems. for instance, the lightning events collected by the cwb system are 76, which is larger than the number of events detected by the jma system, 0, at 15:00. however, at 15:22, the lightning events collected by the jma system are 1137, which is far larger than the number of events detected by the cwb system, which is 76. it is shown from the results that the number of the collected lightning events has a significant relationship with the bandwidth that the system can collect lightning and the mainly-focused detecting frequency, which is 500khz for as3935. also, using the number of lightning events provided by the cwb as the benchmark may not have been a suitable method to examine the performance of the system. 5. conclusion a small intelligent weather station was developed, designed and established. it detected and collected rainfall, frosting, and lightning. the microprocessor could send out data via internet or store data locally. results showed that prediction model advances in technology innovation, vol. 6, no. 2, 2021, pp. 74-89 88 based on the locally collected data was more accurate than using data from weather bureau. frosting could be observed and recorded by an interval-shooting webcam. the lightning prediction was limited due to the frequency restriction of currently available sensors. for future work, we hope to increase the amount of lightning data by trying to use multiple weather boxes to collect data in the same area at the same time. besides, we also aim to find other lightning sensors that detect different bandwidths of the lightning events to complete our lightning detection function. conflicts of interest the authors declare no conflict of interest. references [1] m. a. cooper and r. l. holle, current global estimates of lightning fatalities and injuries, reducing lightning injuries worldwide, springer, 2019. 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[25] welcome to collective.ifttt! https://collectiveifttt.readthedocs.io/en/latest/ [26] y. shibai, l. f. tsai, and y. q. lee, “analysis of the characteristics of each lightning detection system in taiwan,” 2018, http://photino.cwb.gov.tw/conf/history/108/a3/a3_10_l_%e7%99%bd%e6%84%8f%e8%a9%a9_%e5%90%84% e9%96%83%e9%9b%bb%e5%81%b5%e6%b8%ac.pdf (chinese) copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). template encit2010 advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 synthesis of formation control systems for multi-agent systems under control gain perturbations kazuki miyakoshi 1,* , shun ito 1 , hidetoshi oya 1 , yoshikatsu hoshi 1 , shunya nagai 2 1 graduate school of integrative science and engineering, tokyo city university, tokyo, japan 2 department of information systems creation, kanagawa university, kanagawa, japan received 25 april 2019; received in revised form 28 july 2019; accepted 26 november 2019 doi: https://doi.org/10.46604/aiti.2020.4136 abstract this paper proposed a linear matrix inequality (lmi)-based design method of non-fragile guaranteed cost controllers for multi-agent systems (mass) with leader-follower structures. in the guaranteed cost control approach, the resultant controller guarantees an upper bound on the given cost function together with asymptotical stability for the closed-loop system. the proposed non-fragile guaranteed cost control system can achieve consensus for mass despite control gain perturbations. the goal is to develop an lmi-based sufficient condition for the existence of the proposed non-fragile guaranteed cost controller. moreover, a design problem of an optimal non-fragile guaranteed cost controller showe that minimizing an upper bound on the given quadratic cost function can be reduced to constrain a convex optimization problem. finally, numerical examples were given to illustrate the effectiveness of the proposed non-fragile controller for mass. keywords: multi-agent systems (mass), consensus, control gain perturbations, guaranteed cost control, lmis 1. introduction the robustness of control systems is an important property, and thus “robust stability analysis” and “robust stabilization problems” have been well studied for a long time [1-2]. especially, quadratic stabilizing controllers and control are typical robust control strategies [3-5]. furthermore, for practical situations, it is desirable to design control systems that achieve not only asymptotical stability but also an adequate level of control performance. one approach to this problem is “the guaranteed cost control”, and was introduced by chang and peng [6]. in the guaranteed cost control approach, a cost function corresponding to control performance introduced, and the resultant controller has the advantage of providing an upper bound on the given cost function. namely, the system performance degradation incurred by the uncertainties is guaranteed to be less than this bound. based on this idea, many significant results have been presented [7-9]. in the work of petersen and mcfarlane [7], the parameter-dependent riccati equation approach adopted, and yu and chu have proposed a guaranteed cost controller design method based on linear matrix inequalities (lmis) [8-9]. on the other hand, it is generally known that feedback systems designed for robustness concerning parameters in the controlled system may require very accurate controllers. however, uncertainties in controllers may appear for imprecision inherent in conversion and roundoff errors in numerical computations. furthermore, it has pointed out that any useful design strategy should generate a controller which also has a sufficient margin for the readjustment of its coefficients [10-11]. in particular, keel and bhattacharyya [10] showed some examples that optimum and robust controllers can produce extremely fragile controllers, concerning vanishingly small perturbations for parameters of the designed controller. namely, any useful design procedure should generate a controller which also has sufficient room for the readjustment of its coefficients because * corresponding author. e-mail address: g1881842@tcu.ac.jp advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 113 controller implementation is subject to imprecision inherent in analog-digital and digital-analog conversion. finite word length and finite resolution measuring instruments and roundoff errors in numerical computations. from this viewpoint, there are some efforts to tackle the design problem of robust non-fragile controllers [12-14]. famularo et al. had shown a design method of a robust non-fragile lq controller for linear systems with structured uncertainties in the system matrix [12]. additionally, an lmi-based design method of the decentralized guaranteed cost controller for uncertain large-scale interconnected systems has been presented [13]. in the work of oya et al. [14], for linear continuous-time systems with structured uncertainties included in the system matrix and the input under multiplicative or additive control gain variations, an lmi-based design method of a robust non-fragile stabilizing controller has been proposed. by the way, with rapid technological development, controlled systems become large-scale and complex. one can see that systems are referred to as “large-scale interconnected systems”. for large-scale interconnected systems, “centralized control strategies” might be unrealistic for physical, technical, and societal reasons. also, one can see that “decentralized control strategies” are useful. many researchers have studied decentralized control for large-scale interconnected systems (see [15] and references therein). for large-scale interconnected systems, some design methods for the decentralized robust control had been suggested [16-18]. nagai et al. [17] proposed a decentralized variable to gain robust controller for a class of uncertain large-scale interconnected systems, and guaranteed cost control for large-scale interconnected systems with control gain perturbations has also been studied in [18]. additionally, formation control for multi-agent systems (mass) is known as one of the decentralized control problems and has recently attracted much attention. in general, a multi-agent system is a loosely coupled network of multiple interacting agents, and it is well-known that mass can achieve various tasks efficiently. although there are various topics in the formation control problem for mass, the consensus problem has been well focused. the consensus problem can be applied to various fields such as sensor networks, vehicle formations, mobile robots, unmanned aerial vehicles, and so on. additionally, consensus means that states of all agents are driven to a common state by implementing distributed protocols. therefore, the consensus problems are one of the most important and fundamental in the formation, and lots of existing results for consensus problems have been shown (e.g. [19-22]). the consensus problem for a network of first-order integrators with directed in the formation flow and fixed/switching topology has been studied in [19]. xie and wang have studied convergence analysis of a consensus protocol for a class of networks of dynamic agents with fixed topology. furthermore, zhai et al. proposed the matrix inequality-based stabilization condition and consensus algorithm for mass had been presented [22]. ito et al. [23] proposed an adaptive gain controller design method considering relative distances for mass. although the existing result [23] had dealt with consensus problems for multi-agent systems with a leader-follower structure, control gain perturbations have not been considered. about these results of the consensus problem for mass, uncertainties in controllers were not considered, and the lmi-based design method of non-fragile guaranteed cost controllers for mass with control gain perturbations has little been considered as far as known. from this viewpoint, a consensus problem for mass with leader-follower structures was discussed, and an lmi-based design method of a non-fragile guaranteed cost controller which was presented guarantees a consensus for mass. in this paper, additive control gain perturbations are dealt with and showed that sufficient conditions for the existence of the proposed non-fragile guaranteed cost controller given in terms of linear matrix inequalities (lmis). additionally, a design method of quadratic guaranteed cost control-based consensus strategy which guarantees the upper bound of a given quadratic cost function is considered. moreover, the optimal guaranteed cost control approach which minimizes the upper bound of the quadratic cost function is discussed. the crucial differences between the proposed controller synthesis and the existing results [19-23] are that the proposed controller perturbations and optimal guaranteed cost control–based consensus strategy can be achieved. besides, the proposed non-fragile controller can easily be obtained by solving the constrained convex optimization problem, i.e. the proposed non-fragile guaranteed cost control for a consensus is useful. finally, a numerical example is presented to illustrate the effectiveness of the proposed guaranteed cost controller for formation control systems. advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 114 this paper is organized as follows. in section 2, notation and two useful lemmas which were used in this paper are shown. in section 3, the main results presented. namely, an lmi-based design method of a guaranteed cost controller for mass under control gain perturbations. additionally, the optimal guaranteed cost controller which was discussed minimizes the upper bound on a given quadratic cost function. finally, simple illustrative examples were displayed to show the effectiveness of the non-fragile guaranteed cost controller developed in this paper. 2. notations and lemmas the following notations were used in this paper. for a matrix a , the inverse matrix a and its transpose are denoted by 1a and ta , respectively. also,  he a means ta a and ni represent n -dimensional identity matrix, and a block diagonal matrix is composed of matrices ia for 1,2, ,i m are described as  1 2diag , , , ma a a . moreover, real symmetric matrix , 0a a  (resp. 0a  ) means that a is positive (resp. nonnegative) definite matrix. for a vector a , a is euclidian norm, and a represents its included norm for a matrix a . the symbols “*” and “ ” mean symmetric blocks in matrix inequalities and equality by definition, respectively. moreover, the kronecker product of matrices m na  and p qb  is defined as 11 1 1 n m mn a b a b a b a b a b             (1) furthermore, the following two useful lemmas were used in this paper: lemma 1 (schur complement formula [24]): for a given constant real symmetric matrix  , the following items are equivalent: (i) 11 12 22 0 *            , (ii) 11 0  and 1 22 12 11 12 0t     , (iii) 22 0  and 1 11 12 22 12 0t     . lemma 2 [14]: for matrices p and h , which have appropriate dimensions and a positive scalar  , the following relation holds: 1t t t tph h p pp h h     (2) 3. problem formulation the multi-agent system which is considered is composed of 3 agents where an agent indexed by 1 acts as the leader and the other agents indexed by 2, 3, respectively, act as the followers described as the following state equation: ( ) ( ) ( )i i i d x t ax t bu t dt   (3) where  (1) (2) (3) (4)( ) ( ), ( ), ( ), ( )t i i i i ix t x t x t x t x t is the state of i -th agent and elements, (1) ( )ix t and (2) ( )ix t (resp. (3) ( )ix t and (4) ( )ix t ) mean the position and velocity on x axis (resp. y axis), 4 4a  and 4 2b  are given by advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 115 0 1 0 0 0 0 0 0 0 0 1 0 , 0 0 0 1 0 0 0 0 0 0 0 1 a b                          　 (4) one can see that the overall system can be written as ( ) ( ) ( )t t d x t a x t b u t dt   (5) where  diag , ,ta a a a and  diag , ,tb b b b . moreover,  2 3( ) ( ) ( ) ( ) t t t t lx t x t x t x t and  2 3( ) ( ) ( ) ( ) t t t t lu t u t u t u t in eq. (5) are the vectors of the state and the control input for the overall system, respectively. it is well-known that the information path between agents based on graph theory, and the topology connection which is considered is shown in fig. 1. fig. 1 the topology connection of agents since the topology connection can also be expressed by graph laplacian l defined by the adjacency matrix a and the degree matrix d. in the topology connection, the adjacency matrix a and the degree matrix d are given by 0 0 0 0 0 0 1 0 1 , 0 2 0 1 1 0 0 0 2 a d                      　 (6) thus, the corresponding graph laplacian l can be described as 0 0 0 1 2 1 1 1 2 l d a              (7) now, to consider the control gain perturbations for the i -th agent of eq. (3), there are the following control input:   , ,( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) i i k i f i i i j j n u t u t u t k t x t f t x t x t      (8) where in is the set of neighbors for the i -th agent. 2 4( )k t  is the state feedback gain matrix and 2 4( )f t  is the consensus gain matrix. these gain matrices are defined as ( ) ( )k t k k t (9) ( ) ( )f t f f t (10) note that 2 4k  and 2 4f  are the nominal control gain matrices, and the matrices 2 4( )k t   and 2 4( )f t   are unknown time-varying parameters which satisfy the relations ( ) kk t   and ( ) ff t   . one can see that additive control gain perturbations were considered in this paper. additionally, 1 k  and 1 f  mean upper bounds of the advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 116 control gain perturbations and are known positive scalars. namely, for the overall system of eq. (5) the actual control input implemented is assumed to be ( ) ( ) ( ) ( ) ( ) ( ) ( ) k f t t u t u t u t k t x t f t x t    (11) where  2 3( ) ( ) ( ) ( ) ( , ) t t t t p pl p pu t u t u t u t p k f  . in eq. (11), 6( )ku t  can be described as  3( ) ( ) ( ) ( ) ( )k tu t i k t x t k t x t  (12) and 6( )fu t  is the consensus protocol given by   2 3 0 0 0 ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) ( ) ( ) l f t x t u t f t f t f t x t f t f t f t x t l f t x t f t x t                     (13) therefore, the actual control input of eq. (11) can be rewritten as ( ) 0 0 ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) ( ) ( ) 2 ( ) k t u t f t k t f t f t x t f t f t k t f t               (14) moreover, the closed-loop system found is described as   2 3 ( ) ( ) ( ) ( ) ( ) ( ) 0 0 0 0 ( ) 0 0 ( ) * 0 * 0 ( ) ( ) 2 ( ) ( ) ( ) * * * * ( ) ( ) ( ) 2 ( ) ( ) 0 0 t t t t l k f f d x t a x t b k t x t f t x t dt a b k t x t a b f t k t f t f t x t a b f t f t k t f t x t a bf a bf b bf bf a                                                                2 3 ( ) ( ) ( ) ( ) ( ) l t t t x t k t f t x t x t                  (15) where 4 4 ka  and 4 4 fa  are given by ka a bk  and 2fa a bk bf   , respectively. also, ( )tk t and ( )tf t are unknown matrices which can be written as ( ) 0 0 0 0 0 ( ) * ( ) 0 , ( ) ( ) 2 ( ) ( ) * * ( ) ( ) ( ) 2 ( ) t t k t k t k t f t f t f t f t k t f t f t f t                              　 (16) now, the following quadratic cost function introduced:   0 ( ) ( ) ( ) ( ) ( ) ( ) t t t t t t k k k f f fj x t q x t u t r u t u t r u t dt     (17) where 12 12 6 6, tt kq r   , and 6 6 tfr  are given positive-definite symmetric matrices that are selected by designers. from the above discussion, the control objective in this paper is to design a guaranteed cost controller which minimizes the upper bound on the quadratic cost function of eq. (17). that is to derive gain matrices 2 4k  and 2 4f  minimizing the upper bound on the quadratic cost function of eq. (17). advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 117 4. main results in this section, a design method of the non-fragile controller showed based on the linear matrix inequality (lmi) framework. firstly, the following theorem is given for the non-fragile controller under additive control to gain perturbations of eq. (11). theorem 1: for the overall system of eq. (15) with the control input of eq. (11) and the quadratic cost function of eq. (17), if there are symmetric positive definite matrix 0s  , matrices kw and fw , and scalars 0, 0, 0     and 0  satisfying the following lmi condition:   122 122 1 1 2 6 1 2 6 12 12 , , , , 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 t t t t t t t t k f t t t k f t t t k t f t t k k k f f f t t s w w s s s w w s s s i s i s q w r i w r i s i s i                                                 (18)               11 12 13 22 23 33 , , , , , * , , , , * * , , , , k f f k f k f f k f s w w w s w w s w w w s w w                    (19)            11 12 13 23, , ,t t k k f f f f fs w he as bw w w w b w he bw           (20)        22 33, , , , , , , , 2 t k f k f k fs w w s w w he as bw bw bb             (21) then the upper bound on the quadratic cost function of eq. (17) is guaranteed and the closed-loop system of eq. (15) with gain matrices 1 kk w s  and 1 ff w s  are asymptotically stable. moreover, the upper bound on the quadratic cost function of eq. (17) is given by  * (0) (0) (0)tj x x px . proof: using a symmetric positive definite matrix 4 4p  , the following quadratic function introduced as a lyapunov function candidate:    3, ( ) ( )tv x t x t i p x t  (22) from eqs. (5), (11), and (15), the time derivative of the quadratic function ( , )v x t which is along the trajectory of the closed-loop system of eq. (15) can be computed as          3 3 3 ( , ) ( ) ( ) ( ) ( ) ( ) ( , ) ( ) ( ) ( ) t t t t t t d d d v x t x t i p x t x t i p x t dt dt dt x t he i p k f b k t f t x t                        (23) where 12 12( , )k f   is the matrix described as 0 0 ( , ) k f f a k f bf a bf bf bf a             (24) advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 118 therefore, if there exists the state feedback gain matrix 2 4k  , consensus gain matrix 2 4f  and the symmetric positive definite matrix 4 4p  which satisfy the inequality condition     3 ( , ) ( ) ( ) 0t t the i p k f b k t f t        (25) then the quadratic function ( , )v x t satisfies the following inequality: ( , ) 0, ( ) 0 d v x t x t dt    (26) i.e. the quadratic function ( , )v x t becomes a lyapunov function for the closed-loop system eq. (15). by considering the quadratic cost function of eq. (17), there is an inequality condition:   ( , ) ( ) ( ) ( ) ( ) ( ) ( ) 0 t t t t t t t t t t k t t f tk f he pb k t f t q k t r k t f t r f t        (27) instead of the matrix inequality of eq. (25). the matrix 1s p introduced, and the change of variables kw ks and fw fs considered. then preand post-multiplying eq. (25) by 4 4s  and using lemma 2, there is         2 25 ( , , ) ( ) ( ) ( ) ( ) ( ) 0 t t t t t t t k f k f t t t t t t t t t t t k t k k t f t f f t s w w b b s s s s s q s w k t s r w k t s w f t s r w f t s                        (28) where 12 12( , , )k fs w w   is given by 11 12 13 3 3 22 23 33 ( , ) ( ) ( ) ( , , ) ( ) ( , , )( ) * ( , , ) ( ) * * ( , , ) k f f k f k f f k f s w w w s w w i s p k f i s s w w w s w w                         (29)            11 12 13 23, , ,t t k k f f f f fs w he as bw w w w b w he bw          (30)      22 33, , , , 2k f k f k fs w w s w w he as bw bw     (31) one can see that 12 12( , , , , )k fs w w     can be expressed as ( , , , , ) ( , , ) ( ) t t tk f k fs w w s w w b b       (32) therefore, applying lemma 1 to the inequality eq. (28) and simple algebraic gives   122 122 1 1 1 , , , , 0 0 0 0 0 0 0 0 ( , ) 0 5 0 0 0 0 0 0 0 0 0 0 0 0 t t t t t t t t t t tk f k f t k t f t t k k f f s w w s s s w w s i s i k f s q w r w r                                                     (33) where 12 12( , )k f     is given by advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 119 00 0 00 0 0 0 0 0 00 0 0 0 0 0 ( , ) 00 0 0 0 0 0 0( ) 0 0 ( ) 0 0 ( )0 0 0 0 0 0 t t t t t t t t t t t t t s s s s k f k t k t f t                                                                                                0 0 0 0 0 ( ) t t tf t                            (34) thus, one can see from lemma 2 that the following inequality can be obtained:   1 1 122 122 1 1 2 6 1 2 6 , , , , ( ) 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 6 t t t t t t t t k f t t t t t k f t k t f t t k k k f f f s w w s s s s s w w s i s i s q w r i w r i                                              (35) furthermore, by applying lemma 1 to the inequality of eq. (35), the inequality of eq. (35) which was found is equivalent to the lmi of eq. (18). it follows that the result of the theorem is true. therefore, the proof of theorem 1 is completed. (q.e.d) theorem 1 provides a sufficient condition to gain perturbations of the form of eq. (15) for the existence of the guaranteed cost controller which is under control. next, the theorem for the optimal guaranteed cost controller is showed. the lmi of eq. (18) defines a convex solution set, and thus various efficient convex optimization algorithms can be adapted to test whether the lmis are solvable and whether they generate particular solutions. moreover, the parametrized representation exploited to design the guaranteed cost controller with some additional requirements, its solutions parametrize the set of guaranteed cost controllers. in particular, the optimal guaranteed cost controller which minimizes the upper bound on the quadratic cost function of eq. (17) can be obtained by solving a certain optimization problem. the upper bound on the quadratic cost function of eq. (17) depends on the initial value of the overall system. thus, the complementary variable  which was introduced satisfies the following lmi: (0) 0 (0) tx x s       (36) one can easily see that the minimization of  is equivalent to the minimization of the upper bound on the quadratic cost function of eq. (17). consequently, the following theorem developed: theorem 2: consider the overall system of eq. (5) with control gain perturbations, the quadratic cost function of eq. (17) and the control input of eq. (11). if there exists solutions of the following constrained convex optimization problem: 0, , , 0, 0, 0, 0, 0 minimize [ ] subject to eqs.(18) and (34)      k fs w w       (37) then the control input of eq. (11) is an optimal guaranteed cost control which minimizes the upper bound on the quadratic cost function of eq. (17). proof: since the minimization of  is equivalent to the minimization of the upper bound on the quadratic cost function of eq. (17), the result of theorem 2 is obtained by adopting a similar way to the proof of theorem 1 and the existing results (e.g. [13-14, 25]). advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 120 remark 1: in this paper, a design problem of non-fragile guaranteed cost controllers which achieve consensus for multiagent systems (mass) with leader-follower structures was studied, and for simplicity mass composed of 3 agents had been considered. additionally, lmi-based design for optimal non-fragile guaranteed cost control had also been discussed. one can easily see that the proposed controller design approach applies to mass without leaders, and the proposed non-fragile controller can be extended to mass composed of more than 3 agents. 5. numerical examples to demonstrate the efficiency of the proposed non-fragile stabilizing controller, a simple example had been run. in this example, the non-fragile controller under the control gain perturbations is considered. also, the simulation results are shown for the proposed robust stabilizing controller designed without thinking of control gain perturbations. the control problem considered here is not necessarily practical. however, the simulation results stated below illustrate the distinct feature of the proposed non-fragile controller, i.e. the proposed non-fragile controller was compared with the conventional consensus controller which was designed by ignoring controller gain perturbations. consider the multi-agent system of eq. (5). in this example, 13.5 10k   and 13.5 10f   is assumed, respectively. the initial state for agent (0)ix and target value * ix were chosen to be 2 3 4 0 3 3 3 6 (0) , (0) , (0) 3 3 1 2 2 1 lx x x                                       　 　 (38) * * * 2 3 0 1 1 0 0 0 , , 0 1 1 0 0 0 lx x x                                        　 　 (39) as shown in the image in fig. 2. additionally, the weighting parameters q , kr , fr were set as 1.0q  , 12.0 10kr   , and 12.0 10fr   . here, unknown parameter ( )k t and ( )f t is given as  1 1 1 1 1 8.0 10 1.0 exp( 0.1 ) cos(10.0 ) 1 1 1 1 kk t t               (40)  1 1 1 1 1 8.0 10 1.0 exp( 0.1 ) cos(10.0 ) 1 1 1 1 kf t t               (41) fig. 2 trajectories for each agent in the state space advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 121 by applying theorem 2 and solving the constrained convex optimization problem eq. (36), there are the following values for the lmi solution: 1 1 3 2 1 2 2 1 1 1 2.6795 10 1.0585 10 2.7372 10 2.9836 10 * 4.4751 10 2.3603 10 1.1958 10 * * 3.5287 10 1.5169 10 * * * 3.4045 10 s                                 (42) 1 3 2 4 3 3 2.3088 10 4.5315 2.9135 10 1.2169 10 8.8730 10 8.2894 10 2.3342 10 4.4138 kw                     (43) 9 9 10 9 10 9 10 8 1.1693 10 6.4972 10 4.4497 10 7.0950 10 2.3135 10 5.8497 10 6.6781 10 6.1563 10 fw                           (44) 1 26.1981 10 , 1.3859, 5.0597, 6.8027, 3.5265 10           (45) therefore, the feedback gain matrix and the consensus can be calculated as 1 1 1 1 1 1 4.2765 1.1199 10 9.2459 10 4.6627 10 1.7296 10 3.7704 10 7.0206 1.6257 10 k                     (46) 9 8 9 8 8 8 7 7 4.1277 10 1.4406 10 8.2922 10 2.4390 10 2.9470 10 1.9930 10 1.0160 10 2.2850 10 f                         (47) on the other hand, the gain matrices for the conventional consensus controller can be obtained as 1 5 6 5 6 1 1.2613 7.7305 10 1.1617 10 6.6800 10 1.6130 10 4.7165 10 1.2615 7.7315 10 k                      (48) 4 6 6 6 5 6 6 6 2.0593 10 7.9111 10 4.2830 10 9.4814 10 4.7420 10 1.7697 10 2.3861 10 1.5674 10 f                        (49) note that the gain matrices of eq. (47) and (48) in the conventional controller can be designed by solving lmi of eq. (a.1) in appendix and theorem a.1, and it shows an lmi-based design method of the conventional consensus controller. the conventional controller is designed by considering the stabilization of the closed-loop system of eq. (a.2). fig. 3 time histories of the x-position fig. 4 time histories of the control input for x-direction the results of the simulation of this example were depicted in figs. (3)-(10). fig. 3 (resp. fig. 5) shows the time histories of the x-position (resp. y-position), and fig. 4 (resp. fig. 6) presents those of the control input for x-direction(resp. y-position). in these figures, the transient time-response, the manipulated control input, and the actual control input generated advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 122 by the proposed consensus controller, i.e. figs. (3)-(6) are the results for the proposed consensus controller which is based on a guaranteed cost control strategy. additionally, the figures (figs. (7)-(10) show time histories of the state and the control input which were generated by the conventional consensus controller. fig. 7 and fig. 8 (resp. fig. 9 and fig. 10) represent the time histories of the x-position and one of the control input for x-direction (resp. the time histories of the y-position and one of the control input for y-direction), respectively. fig. 5 time histories of the y-position fig. 6 time histories of the control input for y-direction fig. 7 transient time-response of the x-position fig. 8 time histories of the control input x-direction fig. 9 transient time-response of the y-position fig. 10 time histories of the control input y-direction advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 123 from figs. (2)-(10), the proposed non-fragile controller which was found stabilizes the uncertain linear system eq. (5) under the control gain perturbation eq. (41). furthermore, the proposed non-fragile control strategy can achieve the consensus for multi-agent systems despite control gain perturbations. on the other hand, the conventional controller was found cannot achieve consensus because of the controller gain perturbations are ignored in the controller design stage. therefore, the effectiveness of the proposed non-fragile stabilizing controller is shown. 6. conclusions this study had dealt with a design problem of a non-fragile guaranteed cost controller achieving consensus for mass with leader-follower structures. sufficient conditions had been shown for the existence of the proposed non-fragile guaranteed controller can be reduced to the solvability of lmis. furthermore, the optimal non-fragile guaranteed cost controller, which minimizes the upper bound on a given quadratic cost function had been presented. finally, simple numerical examples were given to illustrate the effectiveness of the proposed formation control system. the simulation result had shown that the closed-loop system was well stabilized despite control gain variations. besides, the consensus for mass can be achieved by the proposed non-fragile controller. additionally, the proposed optimal guaranteed cost controller which had been shown can be designed by solving the constrained convex optimization problem. namely, the proposed nonfragile controller can easily be obtained by using software such as matlab’s lmi control toolbox and scilab’s lmitool. it is worth pointing out that this paper didn’t take into account the time delay that occurred when control was performed via a network. therefore, there is room for expansion to the control system for systems with delays. furthermore, future research subjects include some extensions of the proposed design approach to a broad class of systems such as discrete-time systems and output feedback systems. additionally, the proposed controller synthesis will be extented to formation control for mass consisting of more general agent’s dynamics. conflicts of interest the authors declare no conflict of interest. appendix in this appendix, an lmi-based design method of the conventional consensus controller which is showed was obtained by ignoring control gain perturbations. namely, for i -th agent of eq. (3), the following control input is considered:   , ,( ) ( ) ( ) ( ) ( ) ( ) i i k i f i i i j j n u t u t u t kx t f x t x t      (a.1) thus, the closed-loop system can be described as   2 3 2 3 ( ) ( ) ( ) ( ) 0 0 0 0 0 0 ( ) * 0 * 0 2 ( ) * * * * 2 ( ) 0 0 ( ) ( ) ( )                                                                  t t t t l k l f f d x t a x t b k x t f x t dt a b k x t a b f k f f x t a b f f k f x t a x t bf a bf x t bf bf a x t (a.2) and the following lmi-based design method of the conventional consensus controller can be developed: advances in technology innovation, vol. 5, no. 2, 2020, pp. 112-125 124 theorem a-1: consider the overall system of eq. (5) and the control input of eq. (a.1). if there exists a symmetric positive definite matrix 0s  , matrices kw and fw will satisfy the following lmi condition:             * 2 0 * * 2 t t k f f k f f k f he as bw bw bw he as bw bw he bw he as bw bw                 (a.3) then the closed-loop system of eq. (a.2) with gain matrices 1 kk w s and 1 ff w s  are asymptotically stable. proof: the result of theorem a.1 can easily be obtained by using a similar way to the proof of theorem 1. references [1] k. zhou, j. c. doyle, and k. glover, robust and optimal control, prentice hall, 1996. [2] k. zhou, essentials of robust control, prentice hall, 1998. [3] b. r. barmish, “stabilization of uncertain systems via linear control,” ieee transaction on automat control, vol. 28, no. 8, pp. 848-850, 1983. [4] i. r. petersen and c. v. hollot, “a riccati equation approach to the stabilization of uncertain linear systems,” automatica, vol. 22, no. 4, pp. 397-411, 1986. 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[25] h. oya, k. hagino and h. mukaidani, “guaranteed. cost control for uncertain. linear continuous-time. systems. under conrtol gain perturbations,” (in japanese) trans. of jsme(c), vol. 72, no. 713, pp. 92-101, 2006. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 the strategy of energy saving for smart shipping heiu-jou shaw1, fu-ming tzu2,* 1 department of system and naval mechatronic engineering, national cheng kung university, tainan, taiwan 2 department of marine engineering, national kaohsiung university of science and technology, kaohsiung, taiwan received 13 march 2019; received in revised form 22 april 2019; accepted 25 may 2019 abstract this paper presents a real record and analysis to reduce carbon dioxide (co2) emission and fuel consumption using the energy efficiency operational index (eeoi) for practical ships. with giant commercial tankers constantly launching into the sea, emission increase with the tonnage is unavoidable. more weight means more pollution. in the experiment, big data of internet of things (iot) were collected to analyze the sailing conditions for over six months through global satellite communications while the ship sailed across the ocean. the results showed that deep draft results in a better performance than shallow draft; that is, the ship carries more cargo but consumes less fuel oil, as opposed to the traditional concept. among the parameters, the draft and cargo mass interacts with the index to identify the fuel consumption at a constant speed; a draft between 11.5 m and 12 m was found to be optimum for this type of container ship. the eeoi is a metric tool to illustrate the variation of fuel consumption and an effective management strategy to reduce the co2 emission quantity. moreover, a constructive model using iot technology and an energy efficiency management strategy presents an accurate big data basis to guide decision making on the vessel. keywords: cargo loading, speed over ground, average draft, fuel consumption, energy efficiency operational index (eeoi) 1. introduction following the booming shipping market, giant container ships now constantly launch into the sea; thus, greenhouse gas pollution is getting more severe due to the increasing carbon dioxide (co2) emission [1, 2]. therefore, an effective method to evaluate the emission [3-5] is urgently needed. the energy efficiency operational index (eeoi) [6, 7] is a metric unit that measures the co2 emission of a ship and also predicts the consumption of the fuel oil in the vessel. presently, energy saving is an extremely necessary task on board since the container ship is always on missions across the oceans so that schedules to improve energy saving are hardly made. furthermore, the international convention for the prevention of pollution from ships, adopted by the international maritime organization (imo), is the standard guiding the energy efficiency of ships [8]. moreover, the measurement of the performance indicator refers to iso19030, which describes the measurement of changes in the hull and propeller parameter for energy efficiency [8]. recently, big data analysis has become a mainstream statistical method for maritime management for global shipping [9]. various shipping companies utilize smart shipping to analyze the navigational attitude, loading, nacelle, and sea weather information, and this improves the energy efficiency to enhance sailing safety. in the globalization era, the shipping industry has become a key factor of the economy in a world where over 90% of global trade is seaborne [10]. moreover, the weight scale of container ships is in megatonnage; thus, in this study, we use current data recorded in a ship to measure the emission * corresponding author. e-mail address: fuming88@nkust.edu.tw tel.: +886-7-8100888#25245; fax: +886-7-5716043 advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 166 pollution. if the shipping industry were a country, its co2 emission would be higher than that of germany [2]. the industry accounts for 3% of the world’s co2 emission, ranking as the seventh-largest seventh emitter among countries. in 2013, the imo, aiming at energy saving in ships, enforced regulation for emission control that mandates every shipping company to build a self-project based on the ship energy efficiency management plan (seemp). however, the seemp cannot reflect the real consumption of fuel oil without the eeoi. the eeoi is voluntary behavior to take the measured by own shipping. when a ship sails across the ocean from country to country, especially to an emission control area [11, 12], it follows rather strict regulations; the regulation can help control the pollution and carbon emission quantity. the paper contributes two aspects to reduce co2 emission and save fuel consumption. first, the relationships between power efficiency and speed as well as power efficiency and trim at various drafts are analyzed. second, an eeoi-based strategy for ship energy management is presented. the measured parameters include engine power, trim, draft, fuel consumption, cargo mass, and weather condition. 2. systematic architecture this work is focused on the evaluation of energy saving for ships using the eeoi metric. we selected a practical container ship to install a digital device that functions based on the internet of things (iot) technology. the device collects the sailing information and creates a whole communication system between the headquarter (hq) and ship for energy efficiency by big data analysis (fig. 1). an eeoi-based energy efficiency strategy can then be suggested for improving efficiency and thus saving energy. the installed device consists of a vessel data recorder and an alarm monitoring system (ams). the data are transferred to the hq by amos software (spec tec group holding ltd, italy) using satellite communication and fed back to the ship [13], using the glocalme wifi all-day network service. the devices are installed in the engine room and bridge, and the sub-server is installed inside the electrical room where the big data of a particular parameter are transferred to the main server. this is a novel forward-looking method to manage energy efficiency through big data analysis, whereby the data model is constructed using eeoi, and valuable information is provided to decision makers for smart shipping. fig. 1 communication involving big data using satellite on a practical ship the ship’s big data architecture is divided into three layers. the first layer collects the hardware information of the ship. at this stage, the sensing layer, that is, the installed active sensor, collects information on time from the host (auxiliary machines, and power centers); such information includes navigational information, such as draft, speed, load, and climate condition, and actual operational information. in addition, the fiber optic sensor detects the main shaft speed, and the mass flow meter collects the fuel state. the second layer is the network layer. the information detected by each sensor is collected into the gateway and then enters the router. a wired or wireless network connection is used. when the information packet enters the server, the statistical program automatically begins to connect the satellite communication. the shore-based hq of the traffic control center and the land data center complete the networking function, and the data are scheduled to be sent to the designated advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 167 address. the third layer is the application layer. the big data collection is not only used by a single ship; the statistical program structure data are analyzed by the host computer and the server to connect the data to the same type of ship, allowing the fleet to use the data simultaneously. the construction of this system can maximize the application of energy efficiency of the entire ship, which enhances convenient pipeline operations in maritime science for exploration, supporting the practitioners, and reducing marine accidents. the evaluation is based on the eeoi metric unit to examine the fuel oil consumption and co2 emission per distance (nautical mile) for a period of over six months, from feb. 8 to aug. 3, 2018. the evaluated parameters in the experiment include eeoi, cargo mass, fuel consumption, distance, avg. draft, and trim by the fore and stern of a practical ship. 3. data acquisition the data were acquired at a steady rate to measure the hull and propeller parameters [14]; the digital device of big data analysis was used in the experiment to acquire information. the digital data were selected to measure the loading of the container ship every five minutes. the data were collected on board for a voyage of six months: 166 days in the sea and 14 days is in the port; that is, for roughly 92% of the operation time, the ship was in activity. data were still collected when the ship was at the harbor. the steering angle frequently varied due to ship operations, such as entering or departing the harbor, and special conditions. moreover, to fulfill the safety requirements, the speed of the ship was adjusted by the captain, who manipulated the ship to avoid collision during the course. the engine order and rudder order in the interaction often varied for safe navigation. normally, the “ahead” orders of the ship consist of stop, standby, dead slow ahead, slow ahead, half ahead, full ahead. if the ship needs an astern, then the orders include dead slow astern, slow astern, half astern, and full astern. the sensor device installed in the ship is very challenging in the task which the marine equipment must maintain at safety operation, and the installed device cannot affect operation. the acquired parameters, which include fuel consumption, loading change, draft, and trim profile, were analyzed through big data analysis. in addition, due to various weather conditions, the sea wave significantly affected speed. the speed over ground (sog) is the same as the speed displayed on the global position system (gps). furthermore, the ship was manipulated by autopilot while sailing in the wide ocean. however, for safety, the steering gear can be released by hand pilot to avoid an accident. the eeoi is a metric unit to quantify co2 emission and a method to evaluate fuel consumption [6, 7]. according to the imo, the eeoi can be expressed as the product of the co2 factor of transfer coefficient and fuel consumption divided by the product of carrier cargo and sailing distance: average eeoi= ∑ co2factor×foc (tonne) cargo mass (tonne)×sailed distance (nautical mile) n 1 (1) here, n is the total number of voyage segments over the period. a co2 factor of 3.114 (t-co2/t-fuel) was assumed in our experiment, based on the heavy fuel oil at the type of main engine [15]. the foc means fuel consumption during the voyage every five minutes for over six months. hence, the numerator represents the co2 emission of fuel consumption. typically, the large two-stroke cycle of marine engine uses the heavy fuel oil to supply the main power. on the other hand, the denominator represents the cargo mass carried during the voyage. a large denominator, i.e., small eeoi, is based on a certain consumption of fuel oil, and it means higher efficiency of the ship. in this study, the eeoi at the ship varied from 1~3 × 10 −5 , depending on the parameters. thus, we anticipate the measurement method will save fuel oil consumption and reduce the co2 emission to support the marine industry. the main engine (manufactured by man b&w), which is a typical diesel engine of the large two-stroke cycle using heavy fuel oil, was installed in the ship. the technical specifications are presented in table 1. advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 168 table 1 the technical data of the ship in the experiment item description unit launch date 2012 main engine type man b&w 12k98mc main engine power 68,640 kw container capacity 8200 teu length over all 333.2 meter depth (molded) 24.2 meter breath (molded) 42.8 meter scantling draft (molded)/summer draft 14.5 meter gross tonnage 90,532 net tonnage 41,396 ton deadweight tonnage/d.w.t 103,235 ton main engine revolution per minute 94 rpm service speed 25 knot 4. result and discussion the experiment was carried out using a practical ship that sailed across the pacific ocean to the atlantic ocean. first, through satellite communication, the digital device installed on the board timely transferred information to the hq, and a big data analysis was performed in the ship. the ship’s route (fig. 2) was from taiwan, hong kong, china to the east coast of the usa throughout panama canal, back and forth. the ship traveled a total distance of 55,000 nautical miles with four voyages during the period. however, temporary disconnection of satellite communication on the vessel was sometimes unavoidable due to unpredictable bad weather or poor transmission at sea. there was a small broken route during the period, as shown in fig. 2, to express bad communication in the vessel. however, the temporary disconnection will not affect the experiment since the data can be saved and transferred to the hq after the communication is restored. fig. 2 electronic chart of 2d route illustrating the trace of the ship a combined statistical distribution of the relative wind speed and direction is presented in fig. 3. the upper fig. 3(a) illustrates the frequency statistics of the relative wind speed at each section; the occurrences from 0 to 60 knots is about 3,000 times at 0 knots, 1,500 times at 10 knots, and 1,000 times at 20 knots, descending sequentially. the lower fig. 3(a) displays the frequency statistics of the wind direction angle, from −180 degrees to +180 degrees. the wind direction angle is 0 degree at the bow, 0 to +180 degrees on the starboard side, and 0 to −180 degrees on the port side. compared with the occurrences of wind speed, the wind direction angle appears denser. except for 180 degrees at 1200 times, the average angle is about 200 times. therefore, the wind direction angle is denser than the relative wind speed. the fig. 3(b) shows the combined distribution of the upper and lower fig. 3(a) diagrams, where blue represents the relative wind direction and red represents the relative wind speed. fig. 4 is a distribution of the relative wind direction and relative wind speed for fuel consumption during the ship navigation. the lateral coordinate presents relative wind speeds, and the longitudinal coordinate displays a relative wind direction. when the ship was heading at the 0-degree course, the positive wind direction came from the bow, whereby the bow advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 169 is represented by a 0-degree angle. when the ship hull area was larger, the resistance was greater, which was caused by the positive wind direction. in addition, the color bar on the right of fig. 4 indicates the amount of fuel consumption. the red color indicates large fuel consumption, which sequentially decreases in the downward direction. the blue area presents a small fuel consumption. the wind direction was large, and the relative wind speed was fast; thus, the fuel consumption was relatively high, as indicated by the increase in the red indicator. due to the large area of the hull, the sway was increased during the voyage. once the voyage was increased, the resistance was also large and high fuel consumption was possible. (a) statistics of wind speed and wind direction (b) frequency between wind direction and wind speed fig. 3 distribution of statistics and frequency for wind speed vs. wind direction, respectively fig. 4 comparison of relative wind direction (degree) and speed vs. main engine fuel consumption fig. 5 illustrates the relationships between the speed through water (stw) as well as the sog and the main engine (me) power, main shaft speed, and the relative wind speed. the upper left (a) and upper right (b) figures show the relationships between sog and me power and main shaft speed, respectively. the lower left (c) and right diagrams (d) show the relationships between the stw and the me power and main shaft speed, respectively. the color bar on the right of the figure indicates the relative wind speed. the stronger the red, the weaker the blue. as a result, the ship’s speed and wind speed increase and vice versa. fig. 6 presents cross views of a combined statistical distribution of the me power and stw frequencies. the frequency statistics of the me power at 0~38,000 kw is shown in the upper fig. 6(a). the frequency of the me was up to 46,000 kw, which is used for low-speed operations, and the captain relied on the power; the other different power times were between 1 and 30; this range cannot be clearly displayed due to the limitation of the unit scale in the chart. in the lower fig. 6(a), the occurrences of the stw is shown. the figure shows that the ship’s speed had the second-highest frequency when it was at 0 knots, but the highest frequency was around 18 knots, which also means that the ship’s speed was economical. at the fig. 6(b), the me power is integrated with the stw. as a result, the blue color indicates the stw and the red indicates the me power. on the other hand, the sog depends on the ocean currents and weather at sea and indirectly affects the me output power. advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 170 (a) statistics of me power and stw (b) frequency between stw and me power fig. 6 distribution of statistics and frequency for me power vs. stw, respectively fig. 7 shows an exponential function or a polynomial distribution for the relationship between the stw and me power, where the right color bar is red at maximum fuel consumption and blue at minimum fuel consumption. when the stw on the abscissa is higher than 20 knots, the fuel consumption increases in the red or even gray area. both the horizontal and vertical coordinates are exponential functions. among them, the horizontal stripe appearing on the surface indicates that the navigation at this stage was affected by ocean currents. in addition, radio noise sometimes interfered with the data collection on the ship. because the big data hardware was installed in the electrical room, it might have been affected by a heat wave, humidity, and temperature; however, these data can be ignored. fig. 8 illustrates the relationship between the stw and me power. the bar on the right shows the sog. the red indicates the ahead speed of the ship. the higher the speed, the faster the ship. the sog is the actual sailing distance, which is affected by the influence of tidal current, wave, and climate on the water speed. sometimes, the sog was higher than the stw, but the ship’s speed was reduced when it was affected by the resistance of the current. for example, when the sog was in the 17~24 knots, the stw was about 20 knots, which means that the forward or reverse flow or the wind resistance affected the speed of the ship. (a) the relationship between sog and me power (b) the relationship between sog and rpm (c) the relationship between stw and me power (d) the relationship between stw and rpm fig. 5 distribution of speed, power profile and wind speed advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 171 fig. 7 a profile illustration involving stw, me power, and fuel consumption fig. 8 a distribution of stw and me power vs. sog fig. 9 illustrates the relationship between the engine speed, me power, and fuel consumption. the right side is a color bar indicating fuel consumption, where red is the highest fuel quantity, which is decremented in turn, and blue is the minimum fuel quantity; the faster the shaft speed, the more the fuel consumption. the figure shows that fuel consumption conditions were normal when the main shaft speed was about 40~60 revolutions per minute (rpm). once the speed exceeded 80 rpm, the fuel consumption was very high, and it falls in the red area or even the gray stage in the figure. from the experiment, it can be concluded that the ship operation was usually under 75% me power and energy was saved. in addition, the maneuvering system was controlled by a governor, which could stabilize the speed of the main shaft. when the ship navigation was affected by the external climate and ocean current, the system sent a feedback signal to adjust the fuel injection to maintain a stable speed of the main shaft. at this moment, the me power will change accordingly. therefore, the profile of me power in fig. 9 is a fluctuation against environmental variation. fig. 10 illustrates the analysis of stw and me power versus the speed of the main shaft, where stw is dependent on the power level of the me. the color pattern on the right represents the main shaft speed. when the stw was high, the me ran at high power, and the fuel consumption increased accordingly. fig. 9 distribution of engine speed and me power vs. foc fig. 10 profile of stw, me power, and shaft speed (rpm) fig. 11 presents the cross views of a combined statistical distribution of the engine speed and me power frequencies. the upper fig. 11(a) depicts the frequency statistics of the engine speed, of which 40 rpm had the highest frequency, about 4,000 times for this ship, due to the needs for special sea detail and along the coastline. moreover, the engine speed can reduce the emission pollution which is used the speed of the same type of ship. second, the speeds were 55, 65, 70, and 75 rpm. furthermore, the lower fig. 11(a) shows the peak frequency, which also conforms to a power of 40 rpm. the fig. 11(b) indicates the frequency statistics of the two parameters, in which the blue color represents the me power and the red color represents the main shaft speed (rpm). both frequencies are integrated into the vertical axis, and the highest peak can be observed as 40 rpm. advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 172 (a) statistics of engine speed (rpm) and me power (b) frequency between me power and engine speed (rpm) fig. 11 distribution of statistics and frequency for engine speed vs. me power, respectively fig. 12 presents the relationship between the average draft, trim, and fuel consumption. the right color bar indicates the fuel consumption measured in metric tons. it can be seen that the draft was below 10.5 m. the fuel consumption was still high even if the trim by the stern was between 0 and 0.5 m. the average draft and the load are significant parameters that affect fuel consumption. in addition, improper control of the trim will also increase the ship’s resistance. the trim by the stern indicates that the bow is lifted, and the trim by the head indicates that the bow is sinking. the data show that the bow was always sinking in the containership. from the experiment results, it is recommended that the ship should utilize the ballast water to deliver to the stern section that increases the draft of the aft. fig. 13 illustrates the relationship between the average draft, stw, and me power. the coordinate is the stw and the ordinate is the me power. the right color bar represents the draft; red indicates the draft at deep depth, while blue indicates the draft at shallow depth. the results show that the stw is related to the me power, and the relationship features a curve phenomenon. by statistics, the 12-meter draft was at a speed of over 18 knots. fig. 12 profile of average draft and trim with respect to me fuel consumption fig. 13 profile of stw and me power with respect to average draft fig. 14 presents the cross views of a combined statistical distribution of the average draft and trim frequencies. the frequency statistics of the average draft is depicted in the upper fig. 14(a). the plot shows that the draft depth of 12 m was the most used in the navigation, followed by the adjacency of 11.8 m, and then the depth of about 10 m. the lower fig. 14 (a) graph shows the statistical result of the trim. when the trim is 0 m, the frequency is about 8000 times, and the sequence order is −0.3, −1, and −1.2 m, which can show the tendency at the trim of the ship. as a result, the trim by the head occurred more times than the trim by the stern. the fig. 14(b) shows the distribution of the average draft and trim; blue represents trim and yellow represents the average draft. fig. 15 displays the relationships between the trim and the stw and me power. the result is similar to the previous figure and features an exponential function relationship. the right of the figure shows the height of the trim; where the red color represents the trim by the stern, and the blue represents the trim by the head. as a result, the statistics show that the trim fell to advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 173 near 0 m and the frequency of trim by the head was much more than trim by the stern. in addition, fig. 16 shows the distribution of the calculated eeoi statistic. (a) statistics of average draft and trim (b) frequency between average draft and trim fig. 14 distribution of statistics and frequency for average draft vs. trim, respectively fig. 15 profile of stw and me power with respect to trim fig. 16 shows the relationship between the trim, avg. draft, foc, sailing distance, cargo mass, and eeoi. the figure is divided into five operational windows: a, b, c, d, and e. the trim is the difference between the aft draft and the fore draft, and the avg. the draft is an average of the aft draft and fore draft. foc means fuel consumption. the sailing distance is the distance traveled in nautical miles. moreover, sog is the real speed displayed on the gps, which is the vessel speed relative to the earth surface. cargo mass expresses the carrier capability of the ship. the eeoi represents a metric unit of co2 per nautical mile and cargo mass, and it is an indication of co2 emission quantity. as a result, the trim is dependent on the height difference between the fore draft and aft draft, which is one of the major factors that affect the energy-saving strategy. the trim was approximately at 0 m to 0.8 m, an acceptable range considering the various sailing conditions. despite the minor effect of the trim on the eeoi in the experiment, the avg. the draft was a major factor that affected the eeoi. consequently, the operational window of a indicates low draft around 10 m but high emission (eeoi). however, the average drafts around 12 m shown in windows b, c, d, and e correspond to a lower co2 emission than that of window a. thus, the energy saving phenomenon illustrates a quite remarkable and more saving of fuel oil at an average draft of 12 m. on the other hand, cargo mass is a function of draft, and both parameters interact with each other. furthermore, the ballast water is an alternative method to adjust the suitable draft depth. window a indicates light cargo mass, but fuel consumption is worsened and the eeoi increases. windows b, c, d, and e illustrate a heavy cargo mass, but low fuel consumption and low eeoi, which is in the range of 1~3 × 10 −5 . consequently, the cargo mass significantly affected energy efficiency. the eeoi variation for over six months was successfully investigated by statistical analysis of the sailing condition. advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 174 fig. 16 eeoi calculation for various cargo masses, distances, focs, avg. drafts, and trims table 2 presents the quantitative intensity of emission index for each window of fig. 16 in the order of the eeoi. window b corresponds to the strategy with the least eeoi. window d also features a low eeoi but has the highest cargo mass than that of the condition if the captain chooses the option. window a corresponds to the worst energy-saving strategy; thus, the captain must avoid this operational condition. table 2 quantitative index for each window according to the eeoi window date duration eeoi × 10 −5 mass (ton) distance (nm) foc (mt) avg. draft (m) trim (m) b 4/3~4/22 1.50 50,803 1.19 0.19 11.86 −0.15 d 5/21~6/4 2.46 54,980 1.43 0.27 11.95 −0.79 e 6/9~7/8 2.17 47,239 1.21 0.22 11.65 −0.29 c 5/3~5/15 2.72 45,337 1.21 0.25 12.01 −0.23 a 2/28~3/18 5.01 27,254 1.38 0.28 10.06 −0.43 table 3 a quantitative result showing the differences and values from max. to min windows eeoi mass distance foc b 10.8% 22.5% 18.6% 15.8% d 17.7% 24.4% 22.2% 22.6% e 15.7% 20.9% 18.9% 18.2% c 19.6% 20.1% 18.9% 20.3% a 36.1% 12.1% 21.4% 23.1% differ 25.3% 12.3% 3.6% 7.3% value 3.51*10 -5 (t-co2/t-nm) 27,726 (ton) 0.23 (nm) 0.09 (ton) table 3 summarizes the analysis results of the percentage difference between the maximum and minimum energy efficiency parameters during different voyages. statistics for interval windows a, b, c, d, and e are presented. the eeoi difference is the amount of co2 emissions, and the eeoi value of each interval is divided by the amount of each interval; for example, for the b interval, the formula is (eeoi value of b)/(eeoi value of a + b + c + d + e). the value for each interval is taken, and then the maximum value is subtracted from the minimum value to obtain the difference in amount. the results show that eeoi could be reduced to 25.3%, which corresponds to a co2 emission reduction of 3.5 × 10 −5 . in the same way, the load capacity was increased by 12.3% or 27,726 tons; the travel distance was increased by 3.6% or 0.23 nautical miles, and fuel consumption was saved by 7.3% or 0.09 tons. therefore, adjusting the load and draft can reduce the co2 emissions and fuel consumption of the ship and provide positive guidance to ship decision makers. advances in technology innovation, vol. 4, no. 3, 2019, pp. 165-176 175 a forward-looking energy efficiency strategy for smart shipping through a big data analysis device is developing in this work. for various conditions of the vessel, the sailing mode can be selected based on an evaluation of energy saving and emission control. the variation of eeoi with the trim, avg. draft, foc, distance, cargo mass indicates a clear relationship. for this type of container ship, a draft between 11.5 m and 12 m is suitably deep to reduce fuel consumption. this energy-saving strategy can significantly save fuel oil and reduce the co2 emission quantity, as opposed to the traditional concept in the shipping industry. furthermore, both cargo mass and ballast technique always interact with the draft depth of the ship. a constructive model using iot technology and an energy efficiency management strategy presents an accurate big data basis to guide decision making on the vessel. the results showed that the eeoi (the co2 emission) was reduced by 25.3%, the ship could carry an additional cargo mass of 12.3%, the travel distance (nautical mile) was increased by 3.6%, and then fuel oil was saved by 7.3%. thus, the maritime industry can improve the energy saving and engine efficiency of ships using the eeoi-based model. acknowledgement this project is financially supported by the program “data analytics for smart shipping and marine energy management” of the ministry of science and technology, taiwan, r.o.c. under grant no. most 107-2218-e-006 -042. moreover, the authors thank enago (www.enago.tw) for providing professional english review services. conflicts of interest the authors declare no conflict of interest. references [1] m. d. a. al-falahi, k. s. nimma, s. d. g. jayasinghe, h. enshaei, and j. m. guerrero, “power management optimization of hybrid power systems in electric ferries,” energy conversion and management, vol. 172, pp. 50-66, september 2018. 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[15] “imo train the trainer (ttt) course on energy efficient ship operation, module 2–ship energy efficiency regulations and related guidelines,” printed and published by the international maritime organization, vol. 2, p. 42, 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-aiti#5290 270-291.docx advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 study of primary and internal resonance on 3d free-free double-section beam yi-ren wang*, yun-shuo chang department of aerospace engineering, tamkang university, new taipei city, taiwan received 17 february 2020; received in revised form 25 april 2020; accepted 23 june 2020 doi: https://doi.org/10.46604/aiti.2020.5290 abstract this work investigates the primary resonance and internal resonance of a double-section beam with cubic nonlinearities. this model can be applied in a wide range of engineering problems, such as rocket and missile structures. even space technology has been developed for decades; several nonlinear properties deserve further study, especially, for the internal resonance. the method of multiple scales (a perturbation technique) is employed to analyze this nonlinear problem. this study focuses on finding the forcing conditions of this 3d double-section beam to trigger the often-ignored internal resonance or prime resonance in rocket structures. a primary resonance is found on a uniform free-free beam at certain flight speed. the three-to-one internal resonance of the double-section beam occurs within the first and the second modes in the diameter ratio of 1/0.75 with the length ratio of 0.33 or 0.51. the semi-analytical results are verified by the time marching numerical method. keywords: nonlinear vibration, internal resonance, method of multiple scales 1. introduction studies of vibration have always been a concern for researchers and engineers because it may cause the structural fatigue or failure. beams are widely applied in engineering, such as wings in aerospace, bridges in civil engineering, and train rails in mechanical engineering. many studies on beam vibrations have been performed previously. özkaya [1] researched on a beam-mass system under simply supported end conditions, and the effect of positions, magnitudes, and the number of the masses was investigated. mundrey [2] considered the 2d bernoulli-euler beam resting on an elastic foundation to simulate the railway track and a moving load on the 2d beam was studied. phuoc nguyen et al. [3] considered the dynamic response of the euler-bernoulli beam subjected to moving oscillators. chang [4] used a variational method to study nonlinear vibrations in carbon nanobeams under the magnetic field. zhang et al. [5] provided a controllable active torque actuator model for wind-turbine tower vibrations and demonstrated that the proposed module can effectively mitigate the vibrations in wind turbines during operation. these studies demonstrated a wide application of nonlinear models; yet, a 3d nonlinear model and some unique nonlinear properties should be discussed further. in most nonlinear beam problems, an internal resonance is a major point of discussion. the internal resonance is unique to nonlinear systems in which integer relationships exist among the natural frequencies with various modes. due to nonlinearity, the internal resonance generally occurs in modes that are not being directly excited by external forces. exciting the higher modes can lead to high amplitude vibrations in lower modes [6]. large vibration amplitude of the unexcited mode of nonlinear beams could be triggered due to internal resonance. therefore, the lower modes should not be overlooked. however, it is interesting that in common 3d beams with symmetrical cross sections; one-to-one internal resonance is the most likely to take * corresponding author. e-mail address: 090730@mail.tku.edu.tw tel.: +886-2-26215656; fax: +886-2-26209746 advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 271 place among the various degrees of freedom. as its resonant frequency is the same as each other, it is also called primary resonance. for instance, pai [7] analyzed the primary resonance in a 3d nonlinear composite rotating beam. stoykov and ribeiro [8] examined the stability of a 3d nonlinear rotating beam based on timoshenko’s theory and took into account the deformation caused by twists and warps. research has also been conducted on the internal resonance of beams caused by external forces or additional structures, such as those associated with the suspension or support. for instance, van horssen et al. [9-10] considered the use of nonlinear aerodynamics to create three-to-one internal resonance in systems with elastic foundations or suspension springs. wang et al. [11] analyzed a hinged-hinged nonlinear bernoulli-euler beam with linear and nonlinear tuned dampers. the internal resonance was investigated for the system. the nonlinear properties of the nonlinear beam and the nonlinear damper were studied in-depth. wang and hsiao [12] studied the 3d nonlinear multi-loaded slender beam. the nonlinear primary resonance was first found in the wind turbine tower. tekin et al. [13] considered the three-to-one internal resonance in the multiple stepped beam systems. these previous researches investigated the nonlinear properties of internal resonance and primary resonance. however, the internal and primary resonance conditions might happen simultaneously for a 3d beam. they should be taken into consideration at the same time. in addressing general analytical methods to nonlinear vibrations, nayfeh and pai [14] investigated vibrations in nonlinear euler-bernoulli beams. they formulated a number of useful nonlinear beams equations in accordance with newton's laws, euler angles transformation, and the karman-type strain-displacement relationship. nayfeh and mook [6] also proposed a number of perturbation methods by which to solve nonlinear systems, including the lindstedt-poincaré method, the method of averaging, and the method of multiple scales (moms). perturbation methods allow the researchers to get good approximations for systems that the exact solutions are not all easy to be solved. ji and zu [15] studied the rotating shaft system of a timoshenko beam, using moms to analyze the natural frequency responses of nonlinear systems. nayfeh and nayfeh [16] employed moms to identify nonlinear modes and nonlinear frequencies, whereupon they applied the galerkin method to the analysis of dynamic responses in a nonlinear beam. mao [17] used the adm method to analyze the vibration of beams consisting of an arbitrary number of steps through a recursive method. he showed that the adm offers an accurate and effective method of free vibration analysis of multiple-stepped beams with arbitrary boundary conditions. the 3d free-free beam model can be used to simulate space rocket vibration in high-speed motion. the double-section 3d beam model can also be utilized to model a high-speed double-stage rocket motion. the most concerns on the multi-stage rocket motion are the stage separation dynamic control [18] or the high speed flows over the joint of the space rocket stages [19]. according to the references aforementioned with 3d beams or rocket motions, the nonlinear properties of both primary resonance and internal resonance are less discussed simultaneously in the 3d beams or rocket structures. the present study considers a nonlinear double section free-free beam subjected to the distributed load with the wind force and its associated unsteady aerodynamic force. since the primary resonance or internal resonance is unique in nonlinear problems, the unexcited modes usually have larger amplitudes than the excited modes. however, these conditions cannot be predicted by using linear theories. it is worth having a deep study on this model. the present work focuses on finding the forcing conditions of this 3d double-section beam to trigger the often-ignored internal resonance or prime resonance in rocket structures. this research uses newton’s second law to derive the nonlinear equation of motion. the method of multiple scales (moms) is used to obtain the steady state frequency response (fixed point). a primary resonance is found for a uniform free-free beam at certain flight speed. the three-to-one internal resonance is also triggered within the first and the second modes in certain combinations of beam length and diameter ratios of a double-section beam. the fixed points plot is used to observe the nonlinear phenomenon in the system. the fourth-order runge-kutta method is also performed to verify the results of frequency response and the internal resonance. advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 272 2. theoretical model 2.1. equations of motion for uniform free-free beam this study analyzes the vibrations in a straight 3d free-free nonlinear beam, which could be used to simulate the high speed aircrafts such as rocket, missiles, etc. the schematic of the space rocket, the coordinate definitions of the simulated beam, and the relationships between the various external forces are demonstrated in fig. 1. fig. 1(a) shows the space rocket model similar to the satellite and rocket propulsion lab. at ncku. it is true that the proposed beam model can be applied to simulate a missile or a rocket vibration motion. even though the rocket model is hollow, the bulkheads, formers, longerons, stringers and struts strengthen the fuselage structure of the rocket. the beam model is used to simulate the rocket motion for a preliminary study. in this research, the internal resonance and the primary resonance of the rocket nonlinear properties are studied. fig. 1(b) represents the schematic of the coordinate definitions and the multiple forces applied to a uniform free-free beam. the initial status of the beam is considered straight under the assumption that each cross-section is a plane. the deformation of the beam also follows the stress-strain laws. three consecutive euler angles are used to relate the deformed and unreformed states. the equations contain structural coupling terms, quadratic, and cubic nonlinearities due to curvature and inertia. based on newton’s 2nd law, euler angle transformation, and taylor series expansion, the equations of motion of the nonlinear beam can be expressed as follows [14]: y y y mv c v g f′+ = +ɺɺ ɺ (1) z z zmw c w g f′+ = +ɺɺ ɺ (2) x x x xj c g mγ γ+ = +ɺɺ ɺ (3) (a) schematic of ncku htpb/n2o hybrid rocket model (b) schematic of multiple forces applied to a uniform free-free beam fig. 1 the rocket model and a uniform free-free beam approximated model where m is the beam mass per unit length, ��̅ is the mass moment of inertia in the x-direction, ��̅ , ��̅, and ��̅ represent the damping coefficient of the beam in the y-, z-, and x-axis, respectively. the � � , � � , and �� represent the unsteady harmonic wind force and aerodynamic moment in the y-, z-, and x-directions, respectively. the v, w, and � represent the beam displacement (or twist angle) in the y-, zand x-directions, respectively. ⋅� denotes �/��̅ , and �� denotes �/��̅ . furthermore, gy, gz, and gx are defined below for a uniform and isotropic beam [14]: 2 0 2 2 0 ( ) ( ) ( ) ( )[( ) ] (1/ 2) [ ( ) ] x y zz xx zz yy zz x x l g d v d w d v v v w w d d w v w v w dx v m v w dx dx γ γ γ′′ ′ ′ ′′ ′ ′ ′′ ′ ′′ ′ ′′ ′′ ′ ′′′ ′′ ′= − − − + + − − − ′ ′ ′− + ∫ ∫ ∫ ɺɺ (4) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 273 2 0 2 2 0 ( ) ( ) ( ) ( )[( ) ] (1/ 2) [ ( ) ] x z yy xx yy yy zz x x l g d w d v d w v v w w d d v w v w v dx w m v w dx dx γ γ γ′′ ′ ′ ′′ ′ ′ ′′ ′ ′′ ′ ′′ ′′ ′ ′′′ ′′ ′= − + − + + − + + ′ ′ ′− + ∫ ∫ ∫ ɺɺ (5) 2 2 2 2 0 ( ) ( )[( ) ] [( ) ( ) ] ( )[( ) ] x x xx zz yy x y z g d d d v w v w j v w dx v w j j v w w vγ γ γ′ ′ ′′ ′′ ′′ ′′ ′′ ′ ′ ′ ′ ′ ′ ′= + − − − + − + − − −∫ ɺɺ ɺ ɺ ɺ ɺ ɺ ɺ (6) where �̅ is the position coordinate along the beam in the axial direction, � ̅ is the beam length, ��� = ���̅ , ��� = ���̅ , ��� = ���̅, and g is the elastic shear modulus and e is young’s modulus. the ��̅,�,� represent the area moment of inertia in the x-, y-, and z-directions, respectively. the dimensionless coefficients are defined as follows: 4 2 2 2 2 2 xy zy / 1, / , / , / / , / , / / , / , / , / yy y y yy z z yy x x yy x x x y y z z xx yy zz yy l l l x x l t t d ml c c l md c c l md c c md j j j ml j j ml j j ml d d d dµ µ  = = = = =   = = =  = = = = (7) to simplify the notation, the symbols for the dimensionless displacement of the beam were used as the same as the three axes. in other words, y and z are respectively used to represent the transverse (transverse dir., � = �/�)̅ and lateral (side dir., � = �/�)̅ dimensionless displacement functions to avoid influencing the derivation of the theoretical model and to maintain consistency in the overall equations of motion. therefore, the 3d flexural-flexural-torsional vibration of uniform isotropic beam equation can be written as: 2 0 2 2 1 0 ( ) [ ( ) ] (1 )[( ) ] 1 { [ ( ) ] } 2 x iv zy y xy zy zy x x y y y c y z y y y z z y z z y z dx y y z dx dx f µ µ γ µ µ γ γ′ ′′ ′ ′ ′ ′′ ′ ′′ ′ ′ ′′ ′′ ′ ′′′ ′′ ′ ′+ = − − − + − − − + ′ ′ ′ ′− + + ∫ ∫ ∫ ɺɺ ɺ ɺɺ (8) 2 0 2 2 1 0 ( ) [ ( ) ] (1 )[( ) ] 1 { [ ( ) ] } 2 x iv z xy zy x x z z z c z y z y y z z y z y y z dx z y z dx dx f µ γ µ γ γ′ ′′ ′ ′ ′ ′′ ′ ′′ ′ ′ ′′ ′′ ′ ′′′ ′ ′′ ′+ = − + − + + − + + ′ ′ ′ ′− + + ∫ ∫ ∫ ɺɺ ɺ ɺɺ (9) 2 2 2 2 0 1 ( ) ( ) ( ) ( ) xxy zy y z x x x x x j j c y z y z y z dx y z y z y z m j j j µ µ γ γ γ γ γ γ γ − − ′′ ′′ ′′ ′′ ′′ ′′ ′ ′ ′ ′ ′ ′ ′− = − + − − + − + − − +∫ɺɺ ɺ ɺɺ ɺ ɺ ɺ ɺɺ ɺ (10) in addition, the cross-section of the beam in this study is a circle, and the ratio of the lateral area moments of inertia is equal to 1, which means that �� = 1. the structural damping coefficients are also the same, which means that cy= cz. it is noted that the structural damping is always used to simulate a solid material when it flexes. as for the simulation of beam vibrations, the damping coefficient is rather small, and cy is taken as 0.1 in this study. assuming the beam is subjected to a distributed load with the harmonic wind force " �,�# $%�&,'(̅. its associate unsteady aerodynamic force � ),*, that is, � �,� can be expressed as � �,� = " �,�# $%�&,'(̅ + � ),*. the wind force can be normalized as: , , 2 4 , , / / y z y z yy y z y z yy q q d l l d ml = ω = ω (11) the windward aerodynamic forces in the y-direction of the beam are given as follows (please refer the research from van horssen [20]), advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 274 2 2 3 1 2 3 0 2 3 2 2 3 1 2 3 0 2 3 ( , ) ( , ) ( , ) ... 2 ( , ) ( , ) ( , ) ... 2 a y d u d u d u d d u y y y a z a u a u a u a a u z z z u d a a ay x t y x t y x t f a u t t tu u u d a a az x t z x t z x t f a u t t tu u ρ ρ   ∂ ∂ ∂ = + + + +   ∂ ∂ ∂     ∂ ∂ ∂ = + + + +  ∂ ∂ ∂  (12) normalizing eq. (12) yields: 2 3 0 1 2 3 2 3 0 1 2 3 ˆ ˆ ˆ ˆ ..., ˆ ˆ ˆ ˆ ..., d d u d u d u d u a a u a u a u a u f a a y a y a y f a a z a z a z  = + + + +  = + + + + ɺ ɺ ɺ ɺ ɺ ɺ (13) where ,-)./ is the lifting coefficients and ,-)0/ is the first-order derivative modified term. both of them are defined as: 2 0 0 2 ˆ 2 a y d u d u u da a m ρ ω = (14) 1 1 2 ˆ 2 a y d u d u u da a m ρ ω = (15) 2 2 2 ˆ 2 a d u d u da a m ρ ω = (16) 2 3 2 ˆ 2 a d u d u y da a m u ρ ω = (17) 2 0 0 2 ˆ 2 a z a u a u u da a m ρ ω = (18) 1 1 2 ˆ 2 a z a u a u u da a m ρ ω = (19) 2 2 2 ˆ 2 a a u a u da a m ρ ω = (20) 3 3 2 ˆ 2 a a u a u z da a m u ρ ω = (21) the aerodynamic coefficients of the y and z directions, and 1��,� denotes the wind speed in the y and z directions. if 1��,� is also in unsteady form, then 2 0 0ˆ i t d u d ua a e ω= ɶ (22) 1 1ˆ i t d u d ua a e ω= ɶ (23) 2 0 0ˆ i t a u a ua a e ω= ɶ (24) 1 1ˆ i t a u a ua a e ω= ɶ (25) it is also noted that ,-)./ is zero for non-rotating body, and ,-)0/ is 22. this study investigates the internal resonance of a 3d nonlinear free-free beam. the main goal is focusing on the structural vibration analysis due to unsteady loads. the fluid-solid interaction aeroelastic problem is not considered in this advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 275 research. the boundary conditions for the free-free beam are simply the structural dynamic model. the dimensionless boundary conditions of the beam are: (0, ) (0, ) (1, ) (1, ) 0 (0, ) (0, ) (1, ) (1, ) 0 (0, ) (1, ) 0 y t y t y t y t z t z t z t z t t tγ γ ′′ ′′′ ′′ ′′′= = = =  ′′ ′′′ ′′ ′′′= = = =  ′ ′= = (26) 2.2. double section beam model the equations of motion of a double section free-free beam (fig. 2) can be re-written by using eqs. (1)-(6) as follows: fig. 2 schematic model of double section uniform free-free beam 1 1 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 2 ( ) ( ) ( ) ( ) ( ) [ ( ) ] ( )[( ) ] 1 { [ ( ) ] 2 i i i i i i i i i i i y i yy i xx i i zz i i i i i x yy zz i i i i i i i i l x i i i i i l m v c v d v d w d v v v w w d d w v w v w dx v m v w dx γ γ γ − − ′′ ′′ ′ ′′ ′ ′ ′ ′′ ′ ′′ ′ ′+ = − + − + ′′ ′′ ′ ′′′ ′′ ′ ′+ − − − ′ ′ ′− + ∫ ∫ ɺɺ ɺ ɺɺ } i i x i y l dx f′ +∫ (27) 1 1 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 2 ( ) ( ) ( ) ( ) ( ) [ ( ) ] ( )[( ) ] 1 { [ ( ) ] 2 i i i i i i i i i i i z i yy i xx i i yy i i i i i x yy zz i i i i i i i i l x i i i i i l m w c w d w d v d w v v w w d d v w v w v dx w m v w dx γ γ γ − − ′′ ′′ ′ ′′ ′ ′ ′ ′′ ′ ′′ ′ ′+ = − + − + ′′ ′′ ′ ′′′ ′′ ′ ′+ − + + ′ ′ ′− + ∫ ∫ ɺɺ ɺ ɺɺ } i i x i z l dx f′ +∫ (28) 1 2 2 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 2 ( ) ( ) ( ) ( ) ( ) ( ) ( )[( ) ] [( ) ( ) ] ( )[( ) ] i i i i i i i i i x i x i xx i zz yy i i i i i x x i i i i i l y z i i i i i x j c d d d v w v w j v w dx v w j j v w w v m γ γ γ γ γ − ′ ′ ′′ ′′ ′′ ′′+ = + − − − ′′ ′ ′ ′+ − ′ ′ ′ ′+ − − − + ∫ ɺɺ ɺ ɺɺ ɺ ɺ ɺ ɺ ɺ ɺ (29) the index i =1, 2 and represents the section number for this beam. for a circular cross-section beam, the moment of inertia 3�4 = 3�4 , and the side moment of inertia ratio equals 1 ( ��4 = 1), the structural dampings in the yand z-dir are the same, cy= cz, the two sections of the beam are using the same material e1= e2. the wind force applied on the double-section beam is uniform and expressed as " �,�# $%�&,'(̅ and is the same as in the case of uniform beam (fig.1). this beam is subjected to unsteady aerodynamic forces in the y and z-dir. these forces are expressed as � ),*, where , , 1 2 4 , , 1 / / y z y z yy y z y z yy q q d l l d m l = ω = ω (30) 2 2 3 1 ( ) ( ) ( )1 2 3 0 2 3 2 32 ( ) ( ) ( )1 1 2 3 0 2 3 ( , ) ( , ) ( , ) ... 2 ( , ) ( , ) ( , ) ... 2 a y i i id u d u d u d d u y y y i i ia z a u a u a u a a u z z z u d y x t y x t y x ta a a f a u t t tu u z x t z x t z x tu d a a a f a u t t tu u ρ ρ   ∂ ∂ ∂ = + + + +   ∂ ∂ ∂     ∂ ∂ ∂ = + + + +   ∂ ∂ ∂  (31) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 276 the dimensionless forms are: 2 3 0 1 2 3 2 3 0 1 2 3 ˆ ˆ ˆ ˆ ..., ˆ ˆ ˆ ˆ ..., d d u d u d u d u a a u a u a u a u f a a y a y a y f a a z a z a z  = + + + +  = + + + + ɺ ɺ ɺ ɺ ɺ ɺ (32) where 2 1 0 0 2 1 ˆ 2 a y d u d u u d a a m ρ ω = (33) 1 1 1 2 1 ˆ 2 a y d u d u u d a a m ρ ω = (34) 1 2 2 2 1 ˆ 2 a d u d u d a a m ρ ω = (35) 1 3 3 2 1 ˆ 2 a d u d u y d a a m u ρ ω = (36) 2 1 0 0 2 1 ˆ 2 a z a u a u u d a a m ρ ω = (37) 1 1 1 2 1 ˆ 2 a z a u a u u d a a m ρ ω = (38) 1 2 2 2 1 ˆ 2 a a u a u d a a m ρ ω = (39) 1 3 3 2 1 ˆ 2 a a u a u z d a a m u ρ ω = (40) it is noted that eqs. (30)-(32) are used for the two-stage beam. instead of using “m” and “d ” in eqs. (11)-(21), eqs. (30)-(32) use the dimensions of the first stage beam’s mass “m1” and the characteristic length “�̅0” to express the aerodynamic forces. in order to make dimensionless beam equations, the following definitions are introduced. 1 1 1 1 4 1 2 2 1 1 1 1 2 2 2 1 1 1 / , / , / , / , / / , / , / / , / , / / , / i i i i i i i i i i i i i i i i i i i i yy y y yy z z yy x x yy x x x y y z z xy xx yy zy zz yy x x l l l l y v l z w l t t d m l c c l m d c c l m d c c m d j j j m l j j m l j j m l d d d dµ µ  = = = = =   = = =   = = =  = = (41) the dimensionless equations of motion of this double section beam can be obtained as: ( ) 1 ( ) ( ) 1 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 2 ( ) ( ) ( ) 0 ˆ( ) ( ) [ ( ) ] 1 ˆ{ [ ( ) ] , 1, 2} 2 i i i y i i iv i i y d u i xy i i i i i i i x x i t i i i i i y d u l l y y c a y z y y y z z y y z dx dx q e a i µ γ − ω ′ ′′ ′ ′ ′ ′′ ′ ′′ ′ ′+ = − − − − + ′ ′ ′ ′ =− + + +∫ ∫ ɺɺ ɺ ɺɺ 　 (42) ( ) 1 ( ) ( ) 0 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 2 ( ) ( ) ( ) 0 ˆ( ) ( ) [ ( ) ] 1 ˆ{ [ ( ) ] , 1, 2} 2 i i i z i i iv i i z a u i xy i i i i i i i x x i t i i i i i z a u l l z z c a z y z y y z z z y z dx dx q e a i µ γ − ω ′ ′′ ′ ′ ′ ′′ ′ ′′ ′ ′+ = − − + − + ′ ′ ′ ′ =− + + +∫ ∫ ɺɺ ɺ ɺɺ 　 (43) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 277 ( ) 1 ( ) ( ) ( ) ( ) ( ) ( ) ( )( ) , ( 1 2) + , i i i i xxy i i x i i i i i x l x c y z dx y z m j i µ γ γ γ − ′′ ′′ ′ ′ ′− = − + − =∫ɺɺ ɺ ɺɺ ɺ ɺ 　 (44) the boundary conditions (eq. (45)) and the compatibility equations (eq. (46)) at the joint of the two beam sections are: (1) (1) (2) (2) (1) (1) (2) (2) (1) (2) (0, ) (0, ) (1, ) (1, ) 0 (0, ) (0, ) (1, ) (1, ) 0 (0, ) (1, ) 0 y t y t y t y t z t z t z t z t t tγ γ ′′ ′′′ ′′ ′′′ = = = =  ′′ ′′′ ′′ ′′′= = = =  ′ ′= = (45) (1) (2) (1) (2) (1) (2) (1) (2) (1) (2) ( , ) (0, ), ( , ) (0, ) ( , ) (0, ), ( , ) (0, ) ( , ) (0, ) y t y t y t y t z t z t z t z t t t η η η η γ η γ ′ ′ = =  ′ ′= =  = (46) where 5 = �0/ �0 + �6�. 2.3. preturbation analysis perturbation methods allow the researchers to get good approximations for systems where the exact solutions are not all easy to be solved. this study adopted the method of multiple scales (moms) to analyze the frequency response and make the fixed point plots of this nonlinear system. the time scale was divided into fast and slow time scales. suppose that 7. = � is the fast-time term, 70 = 86� is the slow-time terms, and the expansions of each direction are: 1 3 ( ) ( )0 0 1 ( )1 0 1 1 3 ( ) ( )0 0 1 ( )1 0 1 1 3 ( ) ( )0 0 1 ( )1 0 1 ( , ; ) ( , , ) ( , , ) ..., ( , ; ) ( , , ) ( , , ) ..., ( , ; ) ( , , ) ( , , ) ..., i i i i i i i i i y x t y x t t y x t t z x t z x t t z x t t x t x t t x t t ε ε ε ε ε ε γ ε ε γ ε γ  = + +  = + +  = + + (47) where 8 is the time scale of small disturbances and is a minimum value. for the sake of simplicity, the influence of high-order terms such as 89, 8:... are neglected in the system. two time scales (t0 and t1) are considered in this study. under the assumption of nonlinear vibrations, the damping coefficient c is scaled as 86�, the forcing term q is scaled as 8;", respectively. to facilitate this analysis, only the first two terms of the unsteady aerodynamic force are extracted for the external force. the orders of ,-)./ and ,-)0/ in the �) equation are chosen as 8; and 86. similarly, the orders of ,-*./ and ,-*0/ in the �* equation are set as 8; and 86. these principles are substituted into eqs. (42)-(44) and obtain the expansion of the equation of the 80 order in the y-direction. ( )2 0 ( )0 ( )0 0, 1, 2iv i i d y y i =+ = 　 (48) the equation of order 8; is: ( ) 1 2 0 ( )1 ( )1 0 1 ( )0 1 0 ( )0 ( )0 ( )0 ( )0 ( )0 ( )0 2 2 ( )0 ( )0 ( )0 0 ˆ2 ( ) [ ( ) ] 1 ˆ{ [ ( ) ] , } 2 1, 2 i i y i i iv i i i y d u i i i i i i x x i t i i i i i y d u l l d y y d d y c a d y y y y z z y y z dx dx q e a i − ω ′ ′ ′′ ′ ′′ ′ ′+ = − − − − + ′ ′ =′ ′− + + +∫ ∫ ɺɺ 　 (49) the equation of the 80 order in the z direction is: ( )2 0 ( )0 ( )0 0, 1, 2iv i i d z z i =+ = 　 (50) the equation of order 8; is: advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 278 ( ) 1 2 0 ( )1 ( )1 0 1 ( )0 1 0 ( )0 ( )0 ( )0 ( )0 ( )0 ( )0 2 2 ( )0 ( )0 ( )0 0 ˆ2 ( ) [ ( ) ] 1 ˆ{ [ ( ) ] , } 2 1, 2 i i z i i iv i i i z a u i i i i i i x x i t i i i i i z a u l l d z z d d z c a d z z y y z z z y z dx dx q e a i − ω ′ ′ ′′ ′ ′′ ′ ′+ = − − − − + ′ ′ =′ ′− + + +∫ ∫ ɺɺ 　 (51) the equation of the 80 order in the γ direction is: ( )2 0 ( )0 ( )0 , 1, 20i i xy i i x id j µ γ γ ′′ =− = 　 (52) the equation of order 8; is: ( )2 0 ( )1 ( )1 0 1 ( )0 0 ( )0 , 1 22 ,i i xy i i i x i x x d d d c d m i j µ γ γ γ γ =′′− = − − + 　 (53) the boundary conditions and the compatibility equations at the joint of the two beam sections are = 80�: (1)0 (1)0 (2)0 (2)0 (1)0 (1)0 (2)0 (2)0 (1)0 (2)0 (0, ) (0, ) (1, ) (1, ) 0, (0, ) (0, ) (1, ) (1, ) 0, (0, ) (1, ) 0. y t y t y t y t z t z t z t z t t tγ γ ′′ ′′′ ′′ ′′′ = = = =  ′′ ′′′ ′′ ′′′= = = =  ′ ′= = (54) (1)0 (2)0 (1)0 (2)0 (1)0 (2)0 (1)0 (2)0 (1)0 (2)0 ( , ) (0, ), ( , ) (0, ), ( , ) (0, ), ( , ) (0, ), ( , ) (0, ). y t y t y t y t z t z t z t z t t t η η η η γ η γ ′ ′ = =  ′ ′= =  = (55) the equation of order 8; is: (1)1 (1)1 (2)1 (2)1 (1)1 (1)1 (2)1 (2)1 (1)0 (2)0 (0, ) (0, ) (1, ) (1, ) 0, (0, ) (0, ) (1, ) (1, ) 0, (0, ) (1, ) 0. y t y t y t y t z t z t z t z t t tγ γ ′′ ′′′ ′′ ′′′ = = = =  ′′ ′′′ ′′ ′′′= = = =  ′ ′= = (56) (1)1 (2)1 (1)1 (2)1 (1)1 (2)1 (1)1 (2)1 (1)1 (2)1 ( , ) (0, ), ( , ) (0, ), ( , ) (0, ), ( , ) (0, ), ( , ) (0, ). y t y t y t y t z t z t z t z t t t η η η η γ η γ ′ ′ = =  ′ ′= =  = (57) 2.4. 3d free-free beam free vibration analysis the purpose of this section is to find the mode shapes of this vibration beam by the free vibration analysis. by using the moms (section 2.3), the 80 order in the y direction is expressed in eq. (48). the � $�. is divided into time and space by using the separation of variables, defined as � $�. = > ��7 ��, and substituted in eq. (48) to obtain: 2 40 ( )( ) ( ) ( ) iv d t tx x x x t t α= − = (58) where ? is the eigenvalue of the system. the general solution of > �� is assumed as: 1 2 3 4( ) (sin sinh ) (sin sinh ) (cos cosh ) (cos cosh )x x e x x e x x e x x e x xα α α α α α α α= + + − + + + − (59) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 279 and substituted into the boundary conditions, which reveals that e1 = e3 = 0 and that the characteristic equation is cos cosh 1α α = (60) then the mode shape of the i th mode can be expressed as the following: )cosh(cos coscosh sinhsin )(sinhsin)()( xxxxx ii ii ii iii αα αα αα ααϕ + − − ++= (61) 3. frequency response 3.1. conditions for internal resonance the natural frequency will be changed if the diameter and length of the beam are altered. the diameter ratios and the sectional length ratios of the compound beam are the main properties to trigger internal resonance. references [21 and 22] showed that the diameter ratio range is from 1/0.6 to 1/0.9 for the space rockets. the case of �̅0/�̅6 = 1/0.75 is chosen as the test case. the transfer matrix method [17, 23] is used to find the relationship between modal frequency and the sectional length ratio (5) for the beam. the conditions for internal resonance can be obtained by a certain combination of 5. taking an example of the y-direction motion and using the separation of variables, the following expression for y(i)0 can be obtained by: ( ) 0( )0 ( ) ( ) , 1,) 2(i i yy x itϕ ξ == 　 (62) substituting eq. (62) into eq. (48) and dividing by d $� ��e�. ��, it yields: ( )0 0 2 0( ) 4 ( ) ( )( ) , ) 1, ( ( 2 ) iv yi i i y tx t i d x ξϕ λ ϕ ξ = == − 　 (63) where d $� �� can be expressed as: (1) 1 1 1 1 1 1 1( ) cosh( ) sinh( ) cos( ) sin( ) i x a x b x c x d xϕ λ λ λ λ= + + + (64) (2) 2 2 2 2 2 2 2 2( ) cosh( ( )) sinh( ( )) cos( ( )) cos( ( ))x a x b x c x d xϕ η λ η λ η λ η λ η− = − + − + − + − (65) where f0 is the eigen value. from [23], f0 and f6 satisfy the relationship f6 = g6�0̅/g0�6̅� 0/hf0, where a is the area of beam’s cross-section and i is the moment of inertia. since circular cross-sections are considered, f6 = �̅0/�̅6� 0/6f0 = 1.1547f0. the mode shape is expressed as: ( )(1) (2) (1)( ) ( ) ( ) ( )x x x x h xϕ ϕ ϕ η ϕ η = + − − −  (66) where j � is the heaviside function. the researchers define matrix k 0� and l 0� as 1 1(1) 2 2 1 1 3 3 1 1 1 0 1 0 0 1.1547 0 1.1547 0.4219 0 0.4219 0 0 0.4871 0 0.4871 λ λ λ λ λ λ      =  −   −  p (67) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 280 1 1 1 1 1 1 1 1 1 1 1 1(1) 2 2 2 2 1 1 1 1 1 1 1 1 3 3 3 3 1 1 1 1 1 1 1 1 cosh( ) sinh( ) cos( ) sin( ) sinh( ) cosh( ) sin( ) cos( ) cosh( ) sinh( ) cos( ) sin( ) sinh( ) cosh( ) sin( ) cos( ) ηλ ηλ ηλ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ λ ηλ    − =  − −   −  q (68) k 0� represents the moment of inertia of the 2nd section to the 1st section of the beam. l 0� represents the displacement, slope, bending moment, and shear force shape function. the transfer matrix is expressed as: 1(1) (1) (1)−  =  t p q (69) and also satisfies the following condition, { } { }(1) 2 2 2 2 1 1 1 1 t t a b c d a b c d= t (70) from the boundary condition d 0� �� 0� = d 0� ��� 0�, it can be obtained by: 1 1 1 1 1 0 1 0 0 0 1 0 1 0 a b c d    −     =    −        (71) the external boundary conditions are: cosh sinh cos sin sinh cosh sin cosl s s s s s s s s − −  =  −  b (72) where m = 1.1547 1 − 5�f0 and { }2 2 2 2 0 0 t l a b c d   =     b (73) substituting eq. (70) into eq. (73), it yields: { } { }(1) 1 1 1 1 1 1 1 1 0 0 t t l a b c d a b c d   = =     h b t (74) where o = pq ̅r 0� 11 12 13 14 21 22 23 24 h h h h h h h h   =     h (75) and is the total transfer matrix. eqs. (71) and (74) can be solved simultaneously, 1 1 11 12 13 14 1 21 22 23 24 1 1 0 1 0 0 0 1 0 1 0 0 0 a b h h h h c h h h h d −           −      =                 (76) the characteristic equation for the eigen values is: advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 281 11 12 13 14 21 22 23 24 1 0 1 0 0 1 0 1 det( ) 0 h h h h h h h h −   −  =       (77) let 00 1 ( , ) ( ) ( )y n n n y x t t xξ ϕ ∞ = =∑ (78) 11 1 ( , ) ( ) ( )y n n n y x t t xξ ϕ ∞ = =∑ (79) substituting into eqs. (78) and (79) into eqs. (48) and (49) and using orthogonal properties, the following dynamic equations can be obtained, = 80�: 0 0 2 4 0 1 0y m m y md ξ λ ξ+ = (80) = 8;�: 1 1 0 0 0 0 0 0 0 0 2 4 0 1 0 1 1 0 1 1 1 1 0 0 0 0 , , 1 1 0 ˆ2 ( ) ( 3 ) ( 3 y m m y m y m y d u y m iv m y i y j y k m i j k m i j k m i j k m i j k i j k m y i z j z k m i j k m i j d d d c a d g dx dx dx dx g dx ξ λ ξ ξ ξ ξ ξ ξ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ξ ξ ξ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ∞ = + = − − − ′′ ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′− + + + ′′ ′′ ′′ ′ ′′ ′′′− + ∑ ∫ ∫ ∫ ∫ ∫ ɶ ɶ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 , , 1 , , 1 ) 1 ( 2 2 ) 2 ( i i i i i i i iv k m i j k m i j k i j k m y i y j y k y j y k y j y k z j z k z j z k z j z k i j k x x x x m i j k i i i j k i i l l l l dx dx dx g dx dx dx dx ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ϕ ϕ ϕ ϕ ϕ ϕ ϕ − − ∞ = ∞ = ′′ ′ ′′′ ′ ′+ + − + + + + + ′′ ′ ′ ′ ′ ′⋅ + ∑ ∫ ∫ ∫ ∑ ∫ ∫ ∫ ɶ ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ ɺɺ 21 1 00 0 1 ˆ) i yi t ym m d u m i dx q e g a dxϕ ω =   ′ + +     ∑∫ ∫ ∫ɶɶ (81) the frequency as st = f0t 6 , m=1, 2, 3…can be obtained from eq. (80). the relationship between different frequency ratios and the beam sectional length ratios (5) is shown in fig. 3. the integer multiple of frequency ratios has the potential to trigger the internal resonance (i.r.). it is noted that higher orders of structural modes do not exist in linear cases. the energy transferring between lower and higher modes does not happen in the linear structural models. since there are so many combinations of frequency ratios in this nonlinear system, the fixed point’s plots are used to examine if the internal resonance really happens in these cases. besides, for the cases with many combinations of the ratios between higher and lower modes frequencies, the energy may not be possible to transfer between these modes. the possibility of higher modes frequency ratios to trigger i.r. is much less than the cases of small frequency ratios. this study also reveals that when 5 = 0.33 & 0.51, s0: s6 = 1: 3, 5 = 0.68 & 0.86, s0: s6 = 1: 5 and 5 = 0.25 & 0.42, s0: s6 = 1: 6 are possible to trigger i.r. according to eq. (53), only cubic order of e exists in this system, which means only 1:3 i.r. exists in the 1st and 2nd modes. therefore, only the case of 1:3 i.r. in the 1st and 2nd modes will be investigated in this study. 5 = 0.33 is chosen and substituted into eqs. (68), (72). by using eqs. (67)-(76), this study can obtain transfer matrix r 0� and find the first three eigenvalues: 4.03, 6.98, 10.04. the 1st section beam mode shape coefficients can be obtained by eq. (76). the 2nd section beam mode shape coefficients can be obtained by eq. (70). the mode shape functions of the 1st and 2nd beam sections can be obtained by eqs. (65)-(66). similarly, this study can gain other mode shapes for different 5. advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 282 fig. 3 frequency ratios for different beam sectional length ratios 3.2. frequency analysis since 1:3 i.r. happens in the 1st and 2nd modes, the 1st and 2nd modes will be discussed in the following analysis. the solutions to the generalized coordinate are introduced: 0 0 1( ) m mi i t m mb t e e cc ς ωξ −= + (82) 0 0 00 1( ) m mi i t m m m md i b t e e cc ς ωξ ξ ω −= = +ɺ (83) 0 0 00 1 1 1( ( ) ) ( ( ) )m m m mi i t i i t m m m m m md d i b t e e cc b t e e cc ς ω ς ωξ ω ω ς− −′ ′= + + + (84) where �� ≡ �0 � and cc represents complex conjugate. in eq. (81), the distributed load is assumed as "t# $%\ = "t# $ ]^_`ab�cd = "t# $`abcd#$]^cd = "t# $bce#$]^cd . if the solving procedure continues, terms containing the factors of the system frequencies (or harmonics) appear on the right-hand of eq. (81). terms such as these are called secular terms. because of the secular terms, the solution of eq. (81) increases without bound as t increases. the time scale of e0 does not provide a small correction to time scale of e.. the secular terms for s0, s6 − 2s0 harmonics of the y-dir. 1st mode (m = 1) can be selected. likewise, the secular terms due to harmonic numbers of s6, 3s0for the y-dir 2nd mode, due to harmonic numbers of s0, s6 − 2s0 for the z-dir 1st mode, and due to harmonic numbers of s6, 3s0 for the z-dir 2nd mode can be obtained, respectively. refer to appendix for the secular terms. next is to let the secular terms as 0 to get the solvability conditions for solving the mode amplitudes in the frequency domain. the fixed point’s plots can be obtained to analyze the frequency response for the 1st and 2nd modes of the yand z-dir. fig. 4 fixed point plot of diameter ratio = 1/0.75, 5 = 0.33, exciting the y-dir., 1st mode fig. 5 fixed point plot of diameter ratio = 1/0.75, 5 = 0.33, exciting the y-dir., 2nd mode advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 283 figs. 4-5 are the fixed point plot of the y-dir., 5 = 0.33 and for the 1st and 2nd mode, individually. even though the 2nd mode is excited, the 1st mode amplitude is larger than the 2nd mode (the excited mode), and thus an i.r. happens in the 1st and 2nd modes. the same thing happens in the case of 5 = 0.51. the fixed point’s plots are shown in figs. 6-7 for the 1st and 2nd mode are excited. fig. 6 fixed point plot of diameter ratio = 1/0.75, 5 = 0.51, exciting the y-dir., 1st mode fig. 7 fixed point plot of diameter ratio = 1/0.75, 5 = 0.51, exciting the y-dir., 2nd mode to verify the frequency domain results, the fourth order runge-kutta method (rk-4) is used to get the numerical results. the fourth order runge–kutta method is a family of implicit and explicit iterative methods in numerical analysis. it is used in temporal discretization for the approximate solutions of linear or nonlinear differential equations. in order to get the dynamic equations for the rk-4 method, the following expressions for y and z are chosen: 1 yn n n y ξ ϕ ∞ = =∑ (85) 1 zn n n z ξ ϕ ∞ = =∑ (86) substituting eqs. (85) and (86) into eqs. (42) and (43) and by using the orthogonal property, the following dynamic equations can be obtained: 2 3 2 2 2 2 1 1 1 1 1 1 1 1 1 1 2 1 1 2 4 1 2 2 1 5 2 2 2 3 2 2 2 1 2 1 2 6 1 2 2 1 2 7 2 2 2 13 1 1 1 1 1 1 1 16 1 ˆ( ) ( ) ( ) ( ) ( ) ( ) ( ) [ ( )] [ ( y y d u y y y y z y y y z z y y y z y y y z y y y z z y y z y y y y z z z y c a c c c c c c c ξ ξ ω ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + − + + + + + + + + + + + + + + + + + + ɺɺ ɺ ɶ ɶ ɶ ɶ ɶ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺ 2 2 1 2 1 2 1 2 1 2 1 2 1 2 17 2 1 1 1 1 1 1 15 2 2 1 2 2 2 2 2 2 25 2 1 2 1 2 1 2 1 2 1 2 1 2 2 )] [ ( )] [ ( )] [ ( 2 2 y y y y y y z z z z z z y y y y z z z y y y y z z z y y y y y y y z z z z z c c c ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + + + + + + + + + + + + + + + + + + + ɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ ɺɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ ɺɺ 2 19 2 2 2 2 2 2 2 2 2 25 1 1 1 0 10 )] [ ( )] ˆy z y y y y z z z i t y d u c c q e g a dx ξ ξ ξ ξ ξ ξ ξ ξ ϕ ω + + + + = + ∫ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɶɶ (87) 2 3 2 2 2 2 2 1 2 2 2 1 1 1 8 1 2 1 1 2 11 1 2 2 1 12 2 2 2 3 2 2 2 1 2 1 2 14 1 2 2 1 2 15 2 2 2 10 1 1 1 1 1 1 1 21 ˆ( ) ( ) ( ) ( ) ( ) ( ) ( ) [ ( )] [ y y d u y y y y z y y y z z y y y z y y y z y y y z z y y z y y y y z z z c a c c c c c c c ξ ξ ω ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + − + + + + + + + + + + + + + + + + + + ɺɺ ɺ ɶ ɶ ɶ ɶ ɶ ɶ ɺɺ ɺ ɺɺ ɺ ɶ 2 2 1 1 2 1 2 1 2 1 2 1 2 1 2 22 2 1 1 1 1 1 1 23 2 2 1 2 2 2 2 2 2 24 2 1 2 1 2 1 2 1 2 1 2 ( 2 2 )] [ ( )] [ ( )] [ ( 2 2 y y y y y y y z z z z z z y y y y z z z y y y y z z z y y y y y y y z z z z c c c ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + + + + + + + + + + + + + + + + + + + ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ ɺɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ 1 2 26 2 2 2 2 2 2 2 2 2 24 1 2 2 0 20 )] [ ( )] ˆy z z y y y y z z z i t y d u c c q e g a dx ξ ξ ξ ξ ξ ξ ξ ξ ϕ ω + + + + = + ∫ ɺɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɶɶ (88) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 284 2 3 2 2 2 2 1 1 1 1 1 1 1 1 1 1 2 1 1 2 4 1 2 2 1 5 2 2 2 3 2 2 2 1 2 1 2 6 1 2 2 1 2 7 2 2 2 13 1 1 1 1 1 1 1 16 1 ˆ( ) ( ) ( ) ( ) ( ) ( ) ( ) [ ( )] [ ( z z a u z z z z y z z z y y z z z y z z z y z z z y y z z y z z z z y y y z c a c c c c c c c ξ ξ ω ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + − + + + + + + + + + + + + + + + + + + ɺɺ ɺ ɶ ɶ ɶ ɶ ɶ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺ 2 2 1 2 1 2 1 2 1 2 1 2 1 2 17 1 2 1 1 1 1 1 1 15 2 2 1 2 2 2 2 2 2 25 2 1 2 1 2 1 2 1 2 1 2 2 2 )] [ ( )] [ ( )] [ ( 2 2 z z z z z z y y y z z z z z z z y y y z z z z y y y z z z z z z z y y y y y c g c c ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + + + + + + + + + + + + + + + + + + + ɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ ɺɺ ɶ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ 1 2 19 2 2 2 2 2 2 2 2 2 25 1 1 1 0 10 )] [ ( )] ˆz y z z z z y y y i t z a u c c q e g a dx ξ ξ ξ ξ ξ ξ ξ ξ ϕω + + + + = + ∫ ɺɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɶɶ (89) 2 3 2 2 2 2 2 1 2 2 2 1 1 1 8 1 2 1 1 2 11 1 2 2 1 12 2 2 2 3 2 2 2 1 2 1 2 14 1 2 2 1 2 15 2 2 2 10 1 1 1 1 1 1 1 21 ˆ( ) ( ) ( ) ( ) ( ) ( ) ( ) [ ( )] [ z z a u z z z z y z z z y y z z z y z z z y z z z y y z z y z z z z y y y c a c c c c c c c ξ ξ ω ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + − + + + + + + + + + + + + + + + + + + ɺɺ ɺ ɶ ɶ ɶ ɶ ɶ ɶ ɺɺ ɺ ɺɺ ɺ ɶ 2 2 1 1 2 1 2 1 2 1 2 1 2 1 2 22 2 1 1 1 1 1 1 23 2 2 1 2 2 2 2 2 2 24 2 1 2 1 2 1 2 1 2 1 2 ( 2 2 )] [ ( )] [ ( )] [ ( 2 2 z z z z z z z y y y y y y z z z z y y y z z z z y y y z z z z z z z y y y y c c c ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ ξ + + + + + + + + + + + + + + + + + + + ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ ɺɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɺɺ ɺ ɺ ɺɺ ɺɺ ɺ ɺ 1 2 26 2 2 2 2 2 2 2 2 2 24 1 2 2 0 20 )] [ ( )] ˆz y y z z z z y y y i t z a u c c q e g a dx ξ ξ ξ ξ ξ ξ ξ ξ ϕω + + + + = + ∫ ɺɺ ɶ ɺɺ ɺ ɺɺ ɺ ɶ ɶɶ (90) where the fgh are the mode shape integrations and are shown in the appendix. eqs. (87)-(90) can be solved simultaneously by using rk-4. (a) y-dir., 1st mode (e�0 and ei�0) (b) y-dir., 2nd mode (e�6 and ei�6) fig. 8 phase plot of diameter ratio = 1/0.75, j = k. ll, exciting the y-dir., 1st mode (a) y-dir., 1st mode (e�0 and ei�0) (b) y-dir., 2nd mode (e�6 and ei�6) fig. 9 phase plot of diameter ratio = 1/0.75, j = k. mn, exciting the y-dir., 1st mode the phase plots are shown in figs. 8-11. it is recorded that figs. 8-9 are the cases for the 1st mode excited (the excitation frequency is the 1st mode’s natural frequency). figs. 10-11 are the cases for the 2nd mode excited (the excitation frequency is the 1st mode’s natural frequency). the displ. and vel. represent the e�0,�6,�0 and ei�0,�6,�0 , respectively. the converged displacements in time domain in figs. 8-11 agree with the amplitudes form fixed point plots and show the i.r. happens in these cases. advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 285 (a) y-dir., 1st mode (e�0 and ei�0) (b) y-dir., 2nd mode (e�6 and ei�6) (c) z-dir., 1st mode (e�0 and ei�0) fig. 10 phase plot of diameter ratio = 1/0.75, j = k. ll, y-dir., exciting the 2nd mode it is noted that the frequency analysis of the uniform beam can also be done by using eqs. (8)-(10) and apply moms, select the secular terms for different harmonics of different modes and solve the solvability conditions to make the fixed point plots, since the procedure is similar to the case of double-section beam, and will not detail here. (a) y-dir., 1st mode (e�0 and ei�0) (b) y-dir., 2nd mode (e�6 and ei�6) (c) z-dir., 1st mode (e�0 and ei�0) fig. 11 phase plot of diameter ratio = 1/0.75, j = k. mn, y-dir., exciting the 2nd mode 4. wind pressure effects 4.1. diameter ratio and length ratio section 3.2 showed that when the diameter ratio �̅0/�̅6 = 1/0.75 and the length ratio 5 = 0.33&0.51, the 1:3 i.r. internal resonance occurs in the 1st and 2nd modes. various diameter ratios from 1/0.6 to 1/0.9 will be discussed in this section. fig. 12 shows that when the diameter ratios are less than 1/0.78, there will be no i.r. when the diameter ratios are greater than 1/0.78, there will be two possible combinations for the length ratios to trigger i.r. since there is no integer multiple of the frequency ratio for the first 3 modes in the uniform beam, the i.r. will not occur. however, the primary resonance will be examined for the uniform beam in the following section. 4.2. wind pressure and the beam amplitude section 4.1 finds that the i.r. could be triggered in some certain combinations of diameter ratios and beam sectional length ratios. the i.r. cannot happen in the uniform beam, because there is no integer multiple of frequency ratios. next step is to study the effect of the dimensionless wind pressure "ot (refer to appendix for the definition) on this beam amplitude. for the case of a uniform beam, the value of the dimensionless wind pressure "o�0 varies from 1-10. the responding amplitudes in both yand z-d.o.f. can be found from eqs. (8)-(10) by using moms method. the aerodynamic force is treated as the external load in this study. instead of reynolds number, the dimensionless wind pressure "o�0 is considered in figs. 13-17. advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 286 fig. 13 demonstrates the primary resonance phenomenon in an isotropic uniform beam when the 1st mode’s natural frequency in the y-dir. is excited. fig. 13 presents that the amplitudes in the y-dir. increases linearly when "o�0 increases when "o�0 p 7. the amplitudes in the z-dir. seem to be unexcited. however, in the cases of "o�0 q 7, the amplitudes in the z-dir. increase notably. this implies that the energy is transferring from one d.o.f. to another d.o.f. under these conditions. when "o�0 = 10, the amplitude in the z-dir. is larger than the y-dir. this is a typical primary resonance. the result shows the primary resonance can happen under such conditions. fig. 12 frequency ratio plot of a double section beam, exciting the y-dir. 1st mode fig. 13 beam amplitude-wind pressure plot of the uniform isotropic beam, exciting the y-dir. 1st mode’s natural frequency fig. 14 indicates the beam amplitude-wind pressure plot of the double section beam �̅0/�̅6 = 1/0.75, 5 = 0.33, when the y-dir. 1st mode is excited. fig. 15 reveals the beam amplitude-wind pressure plot of the double section beam�̅0/�̅6 = 1/0.75, 5 = 0.51, when the y-dir. 1st mode is excited. the amplitude of by1 is always larger than the other cases and increases linearly as the wind pressure increases. the case of 5 = 0.33 represents a more flexible beam than the case of 5 = 0.51. this is the reason that by1 has the largest amplitude than the other cases. fig. 14 beam amplitude-wind pressure plot of the double section beam �̅0/�̅6 = 1/0.75, 5 = 0.33, exciting the y-dir. 1st mode fig. 15 beam amplitude-wind pressure plot of the double section beam �̅0/�̅6 = 1/0.75, 5 = 0.51, exciting the y-dir. 1st mode figs. 16-17 are the beam amplitude-wind pressure plots of the double section beam �̅0/�̅6 = 1/0.75 when the y-dir. 2nd mode is excited and when 5 = 0.33 and 5 = 0.51, respectively. even if the 2nd mode is excited and by2 increases as the wind pressure increases, the unexcited d.o.f. amplitude by1 is still larger than that of the excited d.o.f. this implies the energy is transferring in between these two modes. the internal resonance is triggered. in comparing with the primary resonance, the 3:1 i.r. happens earlier (less wind pressure) than the primary resonance (evidenced by the growth of bz1). the internal resonance has greater effects than the primary resonance and should be noticed under this forcing condition. advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 287 fig. 16 beam amplitude-wind pressure plot of the double section beam �̅0/�̅6 = 1/0.75, 5 = 0.33, exciting the y-dir. 2nd mode fig. 17 beam amplitude-wind pressure plot of the double section beam �̅0/�̅6 = 1/0.75, 5 = 0.51, exciting the y-dir. 2nd mode 5. conclusions this study investigates the internal resonance of a double-section beam with cubic nonlinearities. this model can be applied in a wide range of engineering problems, such as rocket and missile structures. different ratios of beam section lengths and diameters in a variety of external loads (aerodynamic forces or flight speeds of the rockets or missiles) are studied. a primary resonance occurs on a uniform free-free beam at certain flight speed. the three-to-one internal resonance is also triggered within the 1st and the 2nd modes in certain combinations of beam length and diameter ratios. the phase plots and the time marching numerical method are used to verify the semi-analytical results. the findings are concluded as follows: (1) for a uniform beam, and when wind pressure " �0 r 10, primary resonance occurs. (2) the internal resonance does not happen in the uniform beam case, because the frequency ratios of different modes in the uniform beam are not equal to integer multiples. (3) for the double sectional beam and the diameter ratio �̅0/�̅6 = 1/0.75, the length ratio 5 = 0.33&0.51, the 1:3 internal resonance in the 1st and 2nd modes occurs. (4) when the diameter ratios are less than 1/0.78, there will be no i.r. while the diameter ratios are greater than 1/0.78, there will be two possible combinations for the length ratios to trigger i.r. (5) for the case of the double section beam, the internal resonance has greater effects than the primary resonance and should be noticed in this forcing condition. this study reveals the fight conditions to trigger primary resonance or internal resonance. however, the vibration of the beam structure still exists. the investigations of vibration reduction on the 3d beam or rocket model deserve an extension study on this research. the tuned mass damper (tmd) or the damping ring may be added to see the damping effects on the vibration beam. since the nonlinear phenomenon is difficult to be observed experimentally, the experimental setup for verification of the present predictions is suggested in future research. acknowledgement this research was supported by the ministry of science and technology of taiwan, republic of china (grant number: most 108-2218-e-006-021). conflicts of interest the authors declare no conflict of interest advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 288 appendix the secular terms for s0, s6 − 2s0 harmonics of the y-dir. 1st mode (m = 1) are: 1 1 1 1 1 2 1 1 1 1 1 1 2 ( 2 )2 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 ( 2 ) ( )2 1 2 2 3 1 1 1 1 1 1 1 1 2 4 2 2 1 ˆ2( ) ( ) 3 2 (2 ) y y y y y y y y y z y z z i i i i i y y y y d u y y y y y i i y y y y z z y z y z z y z i b e b e c a i b e b b e c b b e c b b b e c b b b e b b e c b b b e c b b e ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω ς ω − − − − − − + − − − − + − − − + ′ ′− + − − − − − − + − − ɶ ɶ ɶ ɶ ɶ 2 1 1 2 1 2 2 1 2 1 1 2 1 1 2 ( 2 ) ( ) ( ) 5 1 2 2 6 2 1 2 2 1 2 7 ( 2 ) ( 2 )2 2 2 2 2 1 1 1 16 1 2 17 18 1 2 2 19 2 1 2 17 2 ( ) [3 ( ) 2 ] [ y z y y z z y z z y y y y y y i i i y z z y z z y z z i i i i y y y y y y y y y c b b b e c b b b e b b b e c b b e c b b e c c b b b e c b b e c ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω − − − − + − − − + + − − − + − − − + − − + + + + + + ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ 1 1 1 2 1 2 1 1 1 1 1 ( 2 ) ( 2 )2 2 2 2 2 1 2 2 20 19 1 1 1 16 1 2 1 2 17 1 1 2 18 ( 2 ) (2 2 2 2 1 2 2 20 1 1 1 1 1 1 16 1 1 2 2 ( )] 2 2 [(2 ) y y y y y y y y y z y i i i i y y y y y y y y y i i y y y y z z y z y z z b b b e c c b b e c b b e c b b e c b b b e c b b b e b b e c b b b e ς ς ς ς ς ς ς ς ς ς ς ω ω ω ω ω ω − − − − + − − + − − − − + − − − + + − − + − + + + ɶ ɶ ɶ ɶ ɶ ɶ ɶ 1 2 2 1 2 1 2 2 1 2 1 1 2 1 2 1 2 2 1 ) 17 ( 2 ) ( ) ( ) ( )2 2 2 1 18 2 1 2 2 1 2 19 2 1 1 2 17 ( ) ( 1 2 2 20 2 1 2 2 1 2 ( ) ] [ 2 ( z z y z y z z y z z y z z y y z z y z i i y z y z z y z z y z z i i i y z z y z z y z z c b b e c b b b e b b b e c b b b e c b b b e c b b b e b b b e ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω + − − − + − − − + + − − − + − − + − − − + + + + + + + + ɶ ɶ ɶ ɶ ɶ 2 1 1 1 1 1 1 2 2 1 2 1 2 2 1 ) 2 19 1 1 1 1 ( 2 ) ( ) ( 2 )2 2 2 2 1 1 16 2 1 2 2 20 1 2 1 1 2 17 1 2 1 18 ( ) ( 1 2 2 1 2 2 1 2 ) ] ( 2 ) 2 2 2 ( z y y z y y z z y z y z z y z i y z z i y z y z z y z z y z i i y z z y z z c b b b e b b e c b b b e c b b b e c b b e c b b b e b b b e ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω ω ω ω ω ω + − − − + − − − − + − − − + − − − + + − + − − + − − + ɶ ɶ ɶ ɶ ɶ 2 1 ) 19 1)z i t y c q e ς σ+ +ɶ ɶ the secular terms for s6, 3s0 harmonics of the y-dir. 2nd mode are: 2 2 2 1 2 2 1 1 1 1 2 1 1 2 33 2 2 2 2 2 2 1 2 2 1 8 1 1 2 9 2 2 10 ( 2 ) ( ) ( )2 1 1 8 1 1 2 1 1 2 11 2 ˆ2( ) ( ) 2 3 ( ) 2 y y y y y y y z y z z y z z i i i i i i y y y y d u y y y y y y y i i i y z y z z y z z y z i b e b e c a i b e b e c b b b e c b b e c b b e c b b b e b b b e c b b ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω ς ω − − − − − − − + − − + − − + + ′ ′− + − − − − − − − + − ɶ ɶ ɶ ɶ ɶ 2 2 2 2 1 2 2 2 1 2 1 1 12 ( 2 ) 32 2 3 2 2 2 2 2 10 1 1 21 1 1 2 22 23 32 2 2 3 2 2 1 1 2 22 2 2 24 2 1 1 21 1 1 1 2 23 (2 ) [ 2 ( )] [2 3 ] 2 y y y z y y y y y y i z i i i i y z z y z y y y y i i i i y y y y y y y y y b e c b b b e b b e c b e c b b b e c c b b b e c b b e c g b e c b b b e c ς ς ς ς ς ς ς ς ς ς ω ω ω ω − − − − + − − − − − − − + + + + + + + − − ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ 2 1 1 1 1 2 1 1 2 2 2 1 1 2 2 2 1 2 2 24 ( 2 ) ( ) ( )2 2 1 1 1 21 1 1 2 1 1 2 22 2 1 1 23 ( ) (2 2 1 2 1 1 23 2 1 1 2 1 1 2 [ ( ) 2 ] 2 [( y y z y z z y z z y y y z z i y y i i i i y z y z z y z z y z z i i i y z z y z z y z z b b e c b b e c b b b e b b b e c b b b e c b b b e c b b b e b b b e ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω ω ω − − + − − + − − + + − − − − + − − + + + + − + + ɶ ɶ ɶ ɶ ɶ ( ) 1 1 2 1 12 2 2 1 1 2 1 1 2 2 2 2 ) 22 2( 2 )2 2 2 2 2 2 2 2 24 1 1 1 21 ( ) ( ) 1 2 1 1 2 1 1 2 22 ( 2 )2 2 2 2 2 2 2 2 ) (2 ) ] 2 ( ) ( 2 ) y z z y zy y z y z z y z z y y z ii i y z z y z y z i i y z z y z z i i y z z y z c b b b e b b e c b b e c b b b e b b b e c b b b e b b e ς ς ς ς ςς ς ς ς ς ς ς ς ς ς ς ς ω ω ω ω + + − +− − − + − − + − − + + − − − + + + + + − + + − + ɶ ɶ ɶ ɶ ɶ 1 24 2 i t yc q e σ+ ɶ the secular terms for s0, s6 − 2s0 harmonics of the z-dir and 1st mode are: 1 1 1 1 1 2 1 1 1 1 1 21 ( 2 )2 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 2 2 3 ( 2 ) ( )2 2 1 1 1 1 1 1 1 1 2 4 2 1 ˆ2( ) ( ) 3 2 (2 ) z z z z z z z z y z y yz i i i i i i z z z z a u z z z z z z z z i z y y z y z y y z y i b e b e c a i b e b b e c b b e c b b b e c b b b e b b e c b b b e c b b e ς ς ς ς ς ς ς ς ς ς ς ςς ω ω ς ω− − − − − − + − − − + − − − +− ′ ′− + − − − − − − + − − ɶ ɶ ɶ ɶ ɶ 2 1 1 2 1 2 2 1 2 1 1 2 1 1 2 ( 2 ) 5 1 2 2 6 ( ) ( ) ( 2 )2 2 2 2 1 2 2 1 2 7 1 1 1 16 1 2 17 18 ( 2 )2 2 1 2 2 19 2 1 2 17 2 ( ) [3 ( ) 2 ] [ z y z z y y z y y z z z z z z i z y y i i i i z y y z y y z z z z i i z z z z z c b b b e c b b b e b b b e c b b e c b b e c c b b b e c b b e c ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω − − − − + − − − + + − − − + − − − + − − + + + + + + ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ 1 1 1 2 1 2 1 1 1 11 2 2 1 2 2 20 19 1 1 1 16 ( 2 ) ( 2 )2 2 2 2 1 2 1 2 17 1 1 2 18 2 1 2 2 20 ( 2 ) (2 2 1 1 1 1 1 1 16 1 1 2 2 ( )] 2 2 [(2 ) z z z z z z z z y zz i i z z z z z i i i z z z z z z z i z y y z y z y y b b b e c c b b e c b b e c b b e c b b b e c b b b e b b e c b b b e ς ς ς ς ς ς ς ς ς ςς ω ω ω ω ω ω − − − − + − − + − − − + − − −− + + − − + − + + + ɶ ɶ ɶ ɶ ɶ ɶ ɶ 1 2 2 1 2 1 2 2 1 2 1 1 2 1 2 1 2 2 1 ) ( 2 )2 17 2 1 18 ( ) ( ) ( )2 2 1 2 2 1 2 19 2 1 1 2 17 1 2 2 20 ( ) ( 2 1 2 2 1 2 ( ) ] [ 2 ( y y z y z y y z y y z y y z z y y z y z y i i i z y y z y y z y y z y y i i z y y z y y c b b e c b b b e b b b e c b b b e c b b b e c b b b e b b b e ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω + − − − + − − − + + − − − + − − + − − − + + + + + + + + ɶ ɶ ɶ ɶ ɶ 2 1 11 1 1 2 2 11 2 1 2 2 ) ( 2 )2 2 19 1 1 1 1 1 1 16 ( ) ( 2 )2 2 2 1 2 1 2 2 20 1 2 1 1 2 17 1 2 1 18 ( ) ( 1 2 2 1 2 2 1 2 ) ] ( 2 ) 2 2 2 ( y z yz z y y z yz z y y z i z y y z y i z y y z y y z y i i z y y z y y c b b b e b b e c g b b b e c b b b e c b b e c b b b e b b b e ς ς ςς ς ς ς ς ςς ς ς ς ς ω ω ω ω ω ω ω + − − +− − − − + − −− − + − − − + + − + − − + − − + ɶ ɶ ɶ ɶ ɶ ɶ 1 2 1 ) 19 1)y y i t z c q e ς ς σ+ +ɶ ɶ the secular terms for s6, 3s0 harmonics of the z-dir and 2nd mode are: advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 289 2 2 2 1 2 2 1 1 1 1 2 1 1 2 33 2 2 2 2 2 2 1 2 2 1 8 1 1 2 9 2 2 10 ( 2 ) ( ) ( )2 1 1 8 1 1 2 1 1 2 11 2 ˆ2( ) ( ) 2 3 ( ) 2 z z z z z z z y z y y z y y i i i i i i z z z z a u z z z z z z z i i i z y z y y z y y z y i b e b e c a i b e b e c b b b e c b b e c b b e c b b b e b b b e c b b − − − − − − − + − − + − − + + ′ ′− + − − − − − − − + − ɶ ɶ ɶ ɶ ɶ ς ς ς ς ς ς ς ς ς ς ς ς ς ς ω ω ς ω 2 2 22 1 2 2 2 1 2 1 1 12 ( 2 ) 32 2 3 2 2 2 2 2 10 1 1 21 1 1 2 22 23 32 2 2 3 2 2 2 1 1 2 22 2 2 24 1 1 21 1 1 1 2 23 1 (2 ) [ 2 ( )] [2 3 ] 2 z z yz z z z z z z i y ii i i z y y z y z z z z i i i i z z z z z z z z z b e c b b b e b b e c b e c b b b e c c b b b e c b b e c b e c b b b e c − − − +− − − − − − − − + + + + + + + − − ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ ɶ ς ς ςς ς ς ς ς ς ς ω ω ω ω ω 2 1 1 1 1 2 1 1 2 2 1 1 2 12 2 2 2 24 ( 2 ) ( ) ( )2 2 1 1 1 21 1 1 2 1 1 2 22 2 1 1 23 ( ) (2 2 1 2 1 1 23 2 1 1 2 1 1 2 [ ( ) 2 ] 2 [( z z y z y y z y y z z y y zz i z z i i i i z y z y y z y y z y y i ii z y y z y y z y y b b e c b b e c b b b e b b b e c b b b e c b b b e c b b b e b b b e − − + − − + − − + + − − − + − −− + + + + − + + ɶ ɶ ɶ ɶ ɶ ς ς ς ς ς ς ς ς ς ς ς ς ς ςς ω ω ω 1 2 2 2 1 12 1 1 2 1 1 2 2 22 ) 22 ( 2 ) ( 2 )2 2 2 2 2 2 2 2 24 1 1 1 21 ( ) ( ) 1 2 1 1 2 1 1 2 22 ( 2 )2 2 2 2 2 2 2 2 ) (2 ) ] 2 ( ) ( 2 ) y y z y z yz z y y z y y z yz i ii z y y z y z y i i z y y z y y ii z y y z y c b b b e b b e c b b e c b b b e b b b e c b b b e b b e c + + − − + − +− − − + − − + + − − +− + + + + − + + − + ɶ ɶ ɶ ɶ ɶ ς ς ς ς ς ςς ς ς ς ς ς ς ς ςς ω ω ω ω 1 24 2 i t zq e+ ɶ σ where ( )1 2 0 2 1 , 1,m m g dx m ϕ = = ∫ ɶ 　 (a1) ( ) 1 0 1 2 0 , 1, 2 m m m m q dx q dx m ϕ ϕ == ∫ ∫ ɶ 　 (a2) 1 3 2 1 1 1 1 1 1 1 1 10 ( 4 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′ ′′ ′′′ ′= + +∫ɶ ɶ (a3) 1 2 2 2 1 1 1 2 1 1 2 1 2 1 2 1 1 1 2 1 2 10 (3 4 4 4 2 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′ ′′ ′′′ ′ ′′ ′′′ ′ ′ ′= + + + + +∫ɶ ɶ (a4) 1 2 2 3 1 1 1 2 1 2 2 2 1 2 2 2 1 1 2 2 2 10 (3 4 4 4 2 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′ ′′ ′′′ ′ ′′ ′′′ ′ ′ ′= + + + + +∫ɶ ɶ (a5) 1 2 2 4 1 1 1 2 1 1 2 1 2 1 2 1 1 2 1 1 2 10 (2 4 3 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′= + + + + +∫ɶ ɶ (a6) 1 2 5 1 1 1 2 2 1 1 2 1 1 1 2 10 ( 3 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′= + + +∫ɶ ɶ (a7) 1 2 6 1 1 1 2 1 2 2 1 2 2 1 2 20 ( 3 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′= + + +∫ɶ ɶ (a8) 1 2 2 7 1 1 1 2 2 1 2 2 1 2 1 2 2 2 2 1 2 10 (2 3 4 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′ ′ ′′ ′′′ ′= + + + + +∫ɶ ɶ (a9) 1 3 2 8 2 2 1 1 1 1 1 10 ( 4 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′ ′′ ′′′ ′= + +∫ɶ ɶ (a10) 1 2 2 9 2 2 1 2 1 1 2 1 2 1 2 1 1 1 2 1 2 10 (3 4 4 4 2 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′ ′′ ′′′ ′ ′′ ′′′ ′ ′ ′= + + + + +∫ɶ ɶ (a11) 1 3 2 10 2 2 2 2 2 2 2 20 ( 4 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′ ′′ ′′′ ′= + +∫ɶ ɶ (a12) 1 2 2 11 2 2 1 2 1 1 2 1 2 1 2 1 1 2 1 1 2 10 (2 4 3 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′= + + + + +∫ɶ ɶ (a13) 1 2 12 2 2 1 2 2 1 1 2 1 1 1 2 10 ( 3 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′= + + +∫ɶ ɶ (a14) advances in technology innovation, vol. 5, no. 4, 2020, pp. 270-291 290 1 3 2 13 1 1 2 2 2 2 2 20 ( 4 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′ ′′ ′′′ ′= + +∫ɶ ɶ (a15) 1 2 14 2 2 1 2 1 2 2 1 2 2 1 2 20 ( 3 )iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′= + + +∫ɶ ɶ (a16) 1 2 2 15 2 2 1 2 2 1 2 2 1 2 2 2 1 1 2 2 2 10 ( 3 4 )iv iv c g dxϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ ϕ′′ ′′ ′ ′′ ′′′ ′′ ′ ′′′ ′ ′′ ′′′ ′ ′ ′= + + + + +∫ɶ ɶ (a17) 1 1 21 2 2 16 1 1 1 1 1 10 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a18) 1 1 21 17 1 1 1 1 2 1 1 20 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a19) 1 1 21 2 2 18 1 1 2 1 2 10 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a20) 1 1 21 19 1 1 2 1 2 2 1 20 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a21) 1 1 21 2 2 20 1 1 1 2 1 20 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a22) 1 1 21 2 2 21 2 2 1 1 1 10 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a23) 1 1 21 22 2 2 1 1 2 1 1 20 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a24) 1 1 21 2 2 23 2 2 2 1 2 10 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a25) 1 1 21 2 2 24 2 2 2 2 2 20 1 ( ) i i i i i i i i x x x x i i i i l l l l i c g dx dx dx dx dxϕ ϕ ϕ ϕ ϕ − −=  ′′ ′ ′ ′ ′= +   ∑∫ ∫ ∫ ∫ ∫ɶ ɶ (a26) 1 1 21 2 2 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[23] k. torabi, h. afshari, and h. najafi, “vibration analysis of multi-step bernoulli-euler and timoshenko beams carrying concentrated masses,” journal of solid mechanics, vol. 5, no. 4, pp. 336-349, 2013. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 4__aiti#6517__169-178 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 fuzzy study on the winning rate of football game betting woo-joo lee1, hyo-jin jhan2, seung-hoe choi3,* 1department of mathematics, yonsei university, seoul, korea 2school of aerospace and mechanical engineering, korea aerospace university, goyang, korea 3school of liberal arts and science, korea aerospace university, goyang, korea received 03 october 2020; received in revised form 14 april 2021; accepted 15 april 2021 doi: https://doi.org/10.46604/aiti.2021.6517 abstract this study aims to find variables that affect the winning rate of the football team before a match. qualitative variables such as venue, match importance, performance, and atmosphere of both teams are suggested to predict the outcome. regression analysis is used to select proper variables. in this study, the performance of the football team is based on the opinions of experts, and the team atmosphere can be calculated with the results of the previous five games. elo rating represents the state of the opponent. also, the selected qualitative variables are expressed in fuzzy numbers using fuzzy partitions. a fuzzy regression model for the winning rate of the football team can be estimated by using the least squares method and the least absolute method. it is concluded that the stadium environment, elo rating, team performance, and importance of the match have effects on the winning rate of korean national football (knf) team from the data on 118 matches. keywords: winning rate prediction, elo rating, fuzzy number, fuzzy partition, regression model 1. introduction for the member countries of international federation of association football (fifa), their primary interest is the athletic performance in the world cup qualifiers and the finals [1]. predicting the results of football matches as well as other popular sport matches is also important for fans [2]. thus, the methods for forecasting football results have been studied in various ways [3-10]. researchers can take advantages of the long history of football because the football results have been continuously recorded. since modern football has been first introduced to korea, knf team has played a total of 941 games, with a winning percentage of 54.3% [11]. presently, the primary methods for predicting a football game are sorted into two types: 1) quantitative methods and 2) qualitative methods. the quantitative approach is used to predict the outcome of a match by analyzing the previous datasets of both teams competing in the match [12-16]. on the other hand, the qualitative approach is used to predict the outcome of a match by expressing the characteristics that cannot be expressed numerically. these might include the athletic performance of the teams, the match location, and the physical condition of the players [17]. in addition, there is also a combination of two approaches. however, while the research on quantitative methods of predicting the outcome of sport events is more prominent, the research on qualitative and combined methods seems to be scarce [18-19]. furthermore, the variables that affect the performance of each team before the match include the condition of the players’ participation, the condition of teamwork, and the starting squads. it can be quite exciting for football fans to predict the outcome of matches using variables that can be inferred before the match [3]. * corresponding author. e-mail address: shchoi@kau.ac.kr tel.: +82-2-300-0073; fax: +82-2-300-0492 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 the objective of this study is to propose the quantitative and qualitative variables affecting the winning rate of the football team before the match, and to present a statistical model of the winning rate of the team using the selected variables. accordingly, we express qualitative variables in fuzzy numbers and use the selected quantitative and qualitative variables to infer a fuzzy regression model of the football team’s winning rate. for this purpose, we analyze 118 games of korean national football (knf) team. the overall workflow can be sorted into three steps: (1) collecting raw data: public football in-game data have long been recorded and published online. the quantitative data provided by the korea football association (kfa) on 118 matches from september 2, 2011 to november 14, 2019 are collected. also, the qualitative data are primarily extracted from reviews of football experts. (2) pre-processing and transformation: numerically derived variables such as the winning rate, difference in elo rating, and atmosphere are added, and the details of those are described by eqs. (7)-(12). also, the qualitative variables such as the performance of the team and the importance of a match are transformed into fuzzy numbers. (3) fitting the data into the fuzzy regression model and estimate the coefficients: section 2 presents fuzzy regression model for the winning rate of the football game betting. section 3 gives the numerical results of knf team using the absolute deviation method. section 4 concludes the study. 2. fuzzy regression model for the winning rate of the football game betting this section introduces a fuzzy regression model for the winning rate using triangular fuzzy numbers and fuzzy partitions. regression model (eq. (1)) is presented to analyze the impact of match location (��), elo rating difference (��), atmosphere of the national football team (��), performance (��), and importance (��) of the match on the winning rate ( ) of the football team. ( ), , , ,w g e a a gp f p d t a i= (1) to estimate a given regression model in the classical statistical method, the residuals, which are the differences between observations and estimated values, must meet gauss-markov conditions. in other words, the residuals must satisfy the independence, the normality, and the heteroscedasticity [20-21]. if there is a correlation between independent variables, such as atmosphere, athletic performance and match importance, the use of traditional regression will result in multicollinearity problems. in addition, all variables used in the regression model can be expressed as quantitative variables, but sometimes the independent or dependent variables can be expressed as qualitative or categorical. although qualitative data can be quantitatively expressed using probability variables to estimate regression models, this can represent a reduction or omission of the information contained in the qualitative data. thus, it may be more efficient to use qualitative or linguistic data for the regression analysis. the proposed statistical analysis method to account for the causal relationship of such linguistic or qualitative data is the fuzzy regression model. in 1980, professor tanaka introduced the first fuzzy regression model, which applied fuzzy numbers to the regression model introduced by professor zadeh in 1965 [22-23]. since then, fuzzy regression models have been used in many areas [24-26]. data used for fuzzy regression can be expressed in triangular fuzzy numbers. the triangular fuzzy number, denoted by numbers a = (�� , �, ��)�, consists of the mode (�), left endpoint (��), and right endpoint (��) [26]. the membership functions of the right and left sides of the triangular fuzzy number are shown in fig. 1. 170 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 ( ) ( ) , 0, . 1 a a aa x l l x o w a a ll x − ≤ ≤ −=      (2) and ( ) ( ) 0, , . 1 a a aa x r a x r a rr o x w − ≤ ≤ −=      (3) fig. 1 fuzzy number in this study, we apply a fuzzy partition to represent the winning rate, performance, and importance of the football team in triangular fuzzy numbers. if ��� ∶ ��(0) ⊆ �, � = 1, … , � � 1 is set as a fuzzy partition of the universal set �, it satisfies for each i and any ! ∈ �: ( )0 i a φ≠ (4) ( )1 1 0n i i u a x + = = (5) ( )1 1 1 n ii a x + = =∑ (6) where ��(0) is a 0-level set of a fuzzy set �� [27]. fig. 2 implies that the sum of the membership value at one point is 1. fig. 2 shows a fuzzy segmentation consisting of five points: #$, #%, #&, #', and #(. we use the least absolute deviation method suggested by choi and buckley [24] to estimate the regression coefficients of the fuzzy regression model (eq. (1)). they first transformed the fuzzy number into crisp number to estimate the regression model for the center [24]. fig. 2 fuzzy partition 171 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 3. regression analysis for the winning rate of knf team this section examines the variables that affect the winning rate of knf team in the betting, and estimates the fuzzy regression model for knf team. this study uses the data provided by kfa on 118 matches from september 2, 2011 to november 14, 2019, along with the columns written by the experts who analyzed knf team’s performance [2]. this section explains various quantitative and qualitative variables that have influenced the winning rate of knf team, and it subsequently produces a fuzzy regression model for the winning rate of knf team using the selected variables. 3.1. quantitative data for the model we study 118 sets of knf team’s data to forecast the result of the football matches. the anova results show that knf team’s winning rates not only vary with match types such as friendly matches, world cup qualifiers, east asian cup finals, and world cup matches, but also vary with the region in which the matches take place (� − *#�+, < 0.05) [28]. knf team has its lowest winning rate in the world cup matches and the highest winning rate in the world cup qualifiers. also, the winning rate is higher at home games than at neutral games and away games (table 1). table 1 results according to the match type and region match type number of matches winning rate location number of matches winning rate friendly 60 0.42 home 50 0.56 world cup qualifier 35 0.63 neutral 40 0.43 east asian cup 6 0.48 away 28 0.45 asian cup 11 0.57 world cup 6 0.23 total 118 mean: 0.49 the quantitative data on the football team can be classified into two categories: before the match and after the match. the quantitative data that are available before the match are the team’s fifa ranking, elo rating, and the dividend rate for the football team announced by the betting company. the fifa / coca-cola world ranking, which was released for the first time in august 1993, can be obtained from the website of the international football confederation [29-30]. the elo rating, which was developed by arpad elo in 1997, can be found online [31-32]. the sample correlation (0�1) between the fifa and elo rankings for knf team is positive (0�1 = 0.48, � − *#�+, < 0.000). since elo rating is instantly published after every match and fifa ranking is updated every month, it may be more efficient to predict knf team’s winning rate by using elo rating than fifa ranking. kfa releases the results of every match through the knf team website. there are 17 types of data on game scoreboards published by kfa, including goals for (gf), goals against (ga), shots (!�&), shots on target (!�'), fouls (!�(), yellow cards, red cards, offsides, corner kicks (!�4), saves, clears, interceptions, aerial ball winning rates, pass success rates (!�$'), ground ball winning rates (!�$(), pass blocks, and ball possession. in order to estimate the regression model proposed in this section, we use the least squares method. this study is conducted based on records provided by kfa from 2011 to 2019. kfa has announced that the online update of 2017-2019 season data is in progress. with the variable selection method commonly used in regression analysis [28], our variables that influence the goal difference (��(�)) of knf team are derived as shown in the following equation (� − *#�+, < 0.000, #�56% = 0.61): ( ) * 3 6 152.613 0.507 0.115 0.248 0.016 i g e i i i d i d x x x= − + + + + (7) 172 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 where ��8 ∗ is the difference in the elo rating. the above regression equation shows that the variations in knf team’s score difference are statistically significant with shots (!�&), ground ball winning rates (!�$(), and elo ratings (��8 ∗). in addition, the positive results for the estimated coefficients of shots, ground ball winning rates, and elo ratings indicate that as the ranking of the opposing team decreases and the team’s performance increases, the score increases in relation to the knf team’s losses. moreover, the estimated regression equation shows that as the aggressiveness of knf team’s defense increases, the number of losses decreases. the variables used in this study are not standardized because they have different characteristics. as a result, the estimated regression model (eqs. (7) and (8)) show the intercept values. as shown in table 1, knf team’s performance can vary according to match importance such as world cup matches, world cup qualifiers, asian cup finals, and friendly matches. therefore, in this study, we choose to analyze the data on knf team’s world cup qualifier matches, which are held regularly (� − *#�+, < 0.000, #�56% = 0.877). ( ) 5 9 14 159.47 0.644 0.133 0.269 0.095 0.03 ig p i i i i d i g x x x x= − + − − + + (8) the estimated regression equation shows that the location of the match (;<8 ), pass success rates (!�$'), and ground ball winning rates (!�$() are important variables for knf team’s performance. in addition, the estimated regression equation indicates that a high number of fouls (!�() in a match negatively affect the team’s chances of victory because the korean team is one of the top teams in asia. this is the same for the number of corner kicks (!�4). 3.2. qualitative data for the model before a football match, the media and fans are interested in predicting the outcome. although football results do not seem easy to predict, prediction methods can be implemented by using variables that can affect the outcome of a match, including the ranking of the two teams, the match location, the atmosphere and teamwork of each team, the physical condition of players, athletic performance, and the importance of the match. the media provides important information about the game through a preview with football experts, and then a betting company sets a dividend on the victory, draw, and defeat of the match according to the customer’s bet. the winning rate of the football team can be predicted before the match based on the opinions of football experts and the information announced by the betting company [33-34]. in this study, we use expert columns and dividend rates published by the betting company, which both provide predictions and analyses of various sports in addition to football to predict the winning rate of knf team. the dividend rate for a match announced by a betting company cannot be unrelated to the outcome of the match [35-36]. the winning rate calculated by the dividends of winning (� ), drawing (�=), and losing (�>) for a team in a particular match are equal to: d l w d l w l w d d d p d d d d d d = + + (9) the above expression is given by odds-makers, who estimate the odds in betting or competing [37-38]. the sample correlation (0wg) between the winning rate of knf team and the difference between the scored and lost goal of knf team is: ( )0.616 0.000 wg p valueρ = − < (10) the regression equation for the winning rate of knf team (pw) based on knf team’s goal difference (gd) is as follows (#�56% = 0.374, � − *#�+, < 0.000): 0.436 0.06 w d p g= + (11) 173 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 this shows that the winning rate based on the dividends is related to the outcome of knf team. other important variables that can determine the outcomes of matches are the performances in previous matches, the current teamwork, the current athletic performance, the physical condition of the players competing in the game, and the importance of the game. the current atmosphere of the football team can change depending on the outcome of previous game results. when a team goes on a losing streak, the atmosphere of the team will deteriorate, and negative public opinions can cause significant changes, including the replacement of the coach. therefore, the outcome of the national team’s recent matches is an important factor in predicting the national team’s winning rate. based on the recent five matches, the current atmosphere of the national team is defined as: ( ) ( ) ( ) ( ) ( )1 2 3 4 50.3 0.3 0.2 0.1 0.1 i s s s s s a i i i i i t e e e e e− − − − −= + + + + (12) where ,$@a b stands for the elo rating the knf team acquired at t matches before the current match. the importance of the match can affect its outcome. as with other team sports, the importance of the match determines the starting players in the match. while the rookie players are usually assigned in a squad of friendly matches, the best players are assigned for important matches that determine whether the team is qualified for a tournament. in this study, the importance of matches is classified into “very important”, “important”, “normal”, “ordinary”, and “very ordinary”. knf team’s athletic performance is another variable that can affect the outcome of a match. a team’s athletic performance can be evaluated by its ability to score, the ability to defend, and the organizational ability that expresses the organic movement of the defense, offense, and midfield. in addition, the physical strength and condition of the teams participating in the match are also the factors of the team’s performance. this study utilizes the columns of three experts who regularly analyze knf team’s performance and publish their opinions on team organization prior to knf matches. these columns enable us to tally all of the expert-derived positive and negative remarks regarding knf team’s offensive, defensive, and organizational abilities, as well as the strength and physical conditioning of knf team. team performance is expressed as one of the five categories: “very good”, “good”, “normal”, “bad”, or “very bad”. 3.3. fuzzy regression model for the winning rate of knf team in this study, the following fuzzy partitions are used to represent the winning rate of the football team as fuzzy numbers. (1) $: defeat with large margin, denoted by $ = (0, 0, 0.25) (2) %: defeat with small margin, denoted by % = (0, 0.25, 0.5) (3) &: draw, denoted by & = (0.25, 0.5, 0.75) (4) ': win with small margin, denoted by ' = (0.5, 0.75, 1) (5) (: win with large margin, denoted by ( = (0.75, 1, 1)� similar to the winning rate, we apply the following fuzzy partitions for the importance of the match. (1) �� $: very ordinary, denoted by �� $ = (0, 0, 0.25)� (2) �� %: ordinary, denoted by �� % = (0, 0.25, 0.5)� (3) �� &: normal, denoted by �� & = (0.25, 0.5, 0.75)� (4) �� ': important, denoted by �� ' = (0.5, 0.75, 1)� (5) �� (: very important, denoted by �� ( = (0.75, 1, 1)� 174 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 in this study, we also express knf team’s performance along with the winning rate and importance as fuzzy numbers. we present the national team’s performance in a combination of offensive ability, defensive ability, organizational ability, and physical conditioning evaluated by football experts. the overall competition performance of the four categories is equal to 2. thus, the universal set of the knf team’s ability to apply all four categories is equal to � = �0.5, 1.5 . fig. 3 shows the fuzzy division of a football team into five stages, including “very bad”, “bad”, “normal”, “good”, and “very good”. fig. 3 fuzzy partition for the national team’s performance we describe the national team’s performance as fuzzy numbers using the following divisions: (1) �d $: very bad, denoted by �d $ = (0.5, 0.5, 0.75)� (2) �d %: bad, denoted by �d % = (0.5, 0.75, 1)� (3) �d &: normal, denoted by �d & = (0.75, 1, 1.25)� (4) �d ': good, denoted by �d ' = (1, 1.25, 1.5)� (5) �d (: very good, denoted by �d ( = (1.25, 1.5, 1.5)� the football experts’ opinions are combined with the national team’s athletic ability and match importance. the betting company publishes the opinions of three or four experts on its website before national team [2, 34]. table 2 data of knf team number opponent location (��) goal difference (��) elo rating difference (,e) atmosphere (�d) athletic performance (�d) match importance (��) winning rate ( ) 1 lebanon home 6 627 0.6 �d ' �� ' ' 2 kuwait away 0 195 -0.5 �d & �� ' & ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ 26 croatia home -1 -166 -3.3 �d ' �� & & ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ 76 china away -1 271 -0.2 �d & �� ' & ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ 117 lebanon away 0 371 -4.3 �d ( �� ' ( 118 brazil neutral -3 -320 -8.3 �d ' �� & $ the following is a summary of the expert opinions on a match against croatia in 2013: “south korea’s recent a-match performance has been bad. however, all of the players in good condition are going to be in the match, and we are expecting much from the europa league players in particular. this friendly match is an important test match ahead of the final qualifying round.” in addition, the expert opinions on the world cup asian qualifying rounds against china in 2017 are as follows: “the 175 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 korean team is currently ranked second in its group for the world cup asia qualifying round. while winning points in away matches in china is important, key players from the europa league are absent due to warnings and injuries. the opposing team, china, will put forth a strong effort because the new coach has yet to win his first victory.” we have compiled the national team’s data based on the expert opinions above. table 2 shows the quantitative data and the fuzzy data of knf team since september 2011. in table 2, the performance, the game importance, and the winning percentage are expressed in the triangle fuzzy numbers. the aim of this study is to infer the regression equation for the winning rate for the national team using the data given in table 2. the most common method is to estimate the fuzzy regression model using the least squares method. however, it may be more efficient to use the least absolute deviation method instead of the least squares method, which is sensitive to outliers. in this study, the three levels of least absolute deviation method proposed by choi and buckley [24] are used to estimate the fuzzy linear regression model for the winning rate of knf team given in table 2. * 1 2 3 4 5j j j j j jw g e a a gp c p c d c t c a c i= + + + + (13) step 1: consider the centroids of the fuzzy number. to find the center of support for the winning rate, the performance and match importance are expressed in the triangular fuzzy number. the triangular fuzzy number used in this study is symmetrical, so each fuzzy number mode becomes a centroid. step 2: estimate the regression coefficient based on the centroid data. the pseudo-estimate is estimated based on the centroid data [(�gh , ��h , �ih , �dh , ��h , ��h ): 5 = 1, … , 118 given in table 2 and the least absolute deviation method, which minimizes the following equations. * 1 2 3 4 5ˆ ˆ ˆ ˆ ˆ j j j j j jw g e a a gp c p c d c t c a c i= + + + + (14) 118 * 1 2 3 4 5 1 j j j j j jw g e a a g j p c p c d c t c a c i = − − − − −∑ (15) step 3: estimate the spread of the fuzzy number. using the pseudo-estimate k obtained in the second step, the estimate of the winning rate for the knf team l k is as follows. * 1 2 3 4 5 ˆˆ ˆ ˆ ˆ ˆ ˆ ˆ( ,0, ) j j j j j jw g e a a g tp c p c d c t c a c i l r= + + + + + − (16) where �m and �̂ are, respectively, the values minimizing the following subject to � > 0 and � > 0: 118 * 1 2 3 4 5 1 ˆ ˆ ˆ ˆ ˆ w j j j a gj j j p g e a a i j l c p c d c t c l c l l = − − − − − +∑ (17) 118 * 1 2 3 4 5 j 1 ˆ ˆ ˆ ˆ ˆ w j j j a gj j j p g e a a ir c p c d c t c r c r r = − − − − − −∑ (18) the fuzzy regression model for the winning rate of knf team using the data given in table 2 and the three-stage absolute deviation method is: *0.078 0.066 0.039 0.288 0.239, 0.251ˆ ( ) j j j j jw g e c g tp p d a i= + + + + − (19) 176 advances in technology innovation, vol. 6, no. 3, 2021, pp. 169-178 the estimated model indicates that the match location (��), elo rating (,e), athletic performance (��), and match importance (��) affect the national team’s winning rate. the results are in line with the thoughts of both experts and fans. in other words, knf team has a high chance of winning in matches when its performance is good, the importance of match is high, and its elo rating is high. however, the atmosphere of knf team does not seem to have a significant impact on the knf team’s winning rate. we think this result requires further study. 4. conclusions in this study, we suggested the fuzzy regression model for the winning rate of the football team betting, and estimated the regression model of knf team using the data of 118 matches of knf team from 2011 to 2019. before the football match, the qualitative data on the basis of football experts’ reviews were collected to express knf team’s offensive, defensive, and organizational abilities, as well as the match importance, as a fuzzy number. we subsequently examined the impact of the fuzzy numbers defined by using the fuzzy partition and elo rating on the football team’s winning rate. it was found that the winning rate for knf team was influenced by the match location, elo rating, team performance, and match importance. consequently, as all of the coefficients are positive, it turned out that home court advantage increases the possibility of winning. the better the knf team’s performance reviewed in previous games is and the more important the upcoming match is, the higher the winning rate of knf team is expected. however, the atmosphere of knf team was not found to influence the match results. the results of 118 matches of knf team were analyzed with a limited amount of information in this study. however, in the future, it would be useful to extend this research to include more games and extrapolate a model of the winning rate depending on the match type, e.g., world cup matches, regional qualifiers, and friendly matches. acknowledgements the authors thank visual sports and wise toto for offering their data for this study. this work was supported by a national research foundation of korea (nrf) grant funded by the korean government (msit) (no. 2017r1d1a1b03029559). conflicts of interest the authors declare no conflicts of interest. references [1] “fifa,” http://www.fifa.com/index.html, july 05, 2019. 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[38] m. j. dixon and p. f. pope, “the value of statistical forecasts in the uk association football betting market,” international journal of forecasting, vol. 20, no. 4, pp. 697-711, october-december 2004. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 178 2___aiti#7192_in press advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 vehicle path planning with multicloud computation services po-tong wang 1 , shao-yu lin 2 , jia-shing sheu 2,* 1 department of electrical engineering, lunghwa university of science and technology, taoyuan, taiwan 2 department of computer science, national taipei university of education, taipei, taiwan received 21 february 2021; received in revised form 09 august 2021; accepted 10 august 2021 doi: https://doi.org/10.46604/aiti.2021.7192 abstract with the development of artificial intelligence, public cloud service platforms have begun to provide common pretrained object recognition models for public use. in this study, a dynamic vehicle path-planning system is developed, which uses several general pretrained cloud models to detect obstacles and calculate the navigation area. the euclidean distance and the inequality based on the detected marker box data are used for vehicle path planning. experimental results show that the proposed method can effectively identify the driving area and plan a safe route. the proposed method integrates the bounding box information provided by multiple cloud object detection services to detect navigable areas and plan routes. the time required for cloud-based obstacle identification is 2 s per frame, and the time required for feasible area detection and action planning is 0.001 s per frame. in the experiments, the robot that uses the proposed navigation method can plan routes successfully. keywords: computer vision, scene recognition, cloud computing, object detection 1. introduction although humans can walk small distances, walking long distances is exhausting and time-consuming. therefore, bicycles, motorcycles, and cars were invented over time, and their continued evolution has made movement convenient and safe. the focus of vehicle development has now shifted to the production of low-pollution electric vehicles, such as electric bicycles, balance bikes, and skateboards. autonomous driving can decrease the burden on human drivers, reduce road congestion, and improve transportation safety [1]. planning a safe pathway is the focus of autonomous driving. the information regarding the surrounding environment is collected to plan the next action. to prevent collisions, the environment and moving objects are monitored in real time for determining appropriate responses. however, the implementation of autonomous driving technologies is difficult. current autonomous vehicles use multiple ultrasonic or optical radars for detecting surrounding objects to create high-quality three-dimensional (3d) models at night and during the day; however, these sensors are expensive. furthermore, inclement weather severely affects the performance of the aforementioned sensors. machine vision technology is used in daily life applications, such as the smart face unlock feature in smartphones, instant text translation, and automatic checkout in stores. the capabilities of hardware equipment, such as high-image-quality cameras, vision processors, and 5g networks, are continually improving. commercially available visual models can accurately perform face, object, and text recognition. this study realizes the recognition of different objects in real-time images by using application programming interfaces (apis), i.e., google cloud vision, amazon rekognition, and azure computer vision. the obtained object information is regarded as the current environmental conditions when determining the walking area. this study uses available resources and machine vision to develop a low-cost and fast method for dynamic path discrimination. * corresponding author. e-mail address: jiashing@tea.ntue.edu.tw tel.: +886-9-38397255; fax: +886-2-27375457 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 the remainder of this study is organized as follows. section 2 describes the relevant literature. section 3 describes the system architecture. section 4 presents a description of the experiments and the experiment results, and section 5 provides the conclusions of this study. 2. literature review and methodology object detection is a technique for classifying objects in an image, and object detection technology has evolved considerably. lecun et al. [2] proposed the lenet image recognition network, which was subsequently modified by krizhevsky et al. [3] into alexnet. the addition of the rectified linear unit and dropout nonlinear activation functions to lenet considerably improved its image recognition rate. thus, machine vision has evolved rapidly. he et al. [4] proposed residual network architecture to solve the problem of overfitting. huang et al. [5] and wang et al. [6] made subtle changes and proposed densenet and cspnet, respectively. similar concepts of cspnet were used to design novel architectures that effectively enhance network identification capabilities [5-6]. howard et al. [7] proposed lightweight network architecture to increase the processor calculation speed and solve the problem of slow network operations in mobile devices and embedded learning. the aforementioned network architectures can be implemented to obtain a backbone network for the rapid learning of image features. many object recognition networks use such backbone networks for image feature extraction. various calculation methods are then incorporated into the network to learn the category and location of images [8]. ren et al. [9] developed a two-stage object recognition, i.e., faster region based convolutional neural networks (faster rcnn), with a high recognition rate by using visual geometry group (vgg) as the backbone network and the region proposal network. the aforementioned architecture was also used in an object recognition network [10]; however, in contrast to faster rcnn, the single-shot detector (ssd) object recognition network performs one-stage identification in real time. numerous sophisticated, fast, and automated object detection networks have been proposed. the initially proposed object detection networks such as “you only look once (yolo)” do not use artificial anchor frames [11]. law et al. [12] proposed cornernet, which is a novel anchorless frame network, for self-learning object detection. duan et al. [13] and tian et al. [14] subsequently improved cornernet and achieved the same results as law et al. [12] without relying on anchor frames. tan et al. [15] developed efficientdet and achieved up to 53.7 average precision (ap) with current one-stage object detectors. achieving simultaneous localization and mapping is critical for developing automated machinery. light detection and ranging technology can be used to sense the surrounding environment and dynamically avoid moving objects, such as crowds and vehicles on the road [16-17]. furthermore, rgbd-based visual sensors were used to establish real-time environmental images and motion paths for augmented reality (ar), virtual reality (vr), and unmanned aerial vehicle (uav) positioning [18]. a vision-based deep learning network can be used to detect the environment for conducting motion detection, walkable area detection, and motion planning [19]. obstacle detection can also performed by object detection, and the technique algorithm will be used to mark walkable areas and relative coordinates [20-21]. avoiding obstacles is a crucial ability for autonomous mobile robots, which must plan suitable movement routes. when moving from the current location to a target location, the most efficient movement route is the shortest path without any restrictions. dijkstra’s algorithm and the a* algorithm are common methods for determining the shortest path. dijkstra’s algorithm is similar to the breadth-first search method; it searches for the shortest distance node outward from the current coordinate point and continues the search until the target point is found. the a* algorithm combines the speed priority and dijkstra methods. the costs from the starting point to the node and from the node to the target point are added and used as the node’s search cost, and the path with the lowest cost is searched for outward from the starting point. using the method, the a* algorithm can plan the optimal path while avoiding obstacles. the obstacle avoidance problem is also called the velocity obstacle (vo) problem. if a robot collides with another robot when maintaining its current speed, the set of all collision events comprises the vo [22]. 214 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 3. system structure this study proposes a real-time path-planning system based on neural networks for unmanned vehicles. the image obtained by an embedded camera is used as the input, and multiple public pretrained neural networks are used to increase the amount of information available on obstacle positions. the drivable area is determined from the blank areas between multiple objects, and safe paths are planned in drivable areas. fig. 1 displays the architecture of the proposed system. three steps are used in this study to plan the path of a self-propelled vehicle: object detection (fig. 2), path planning (fig. 3), and movement control. fig. 1 architecture of the proposed system fig. 2 framework of cloud object detection fig. 3 framework of path planning 3.1. cloud object detection the purpose of object detection is to detect the locations of obstacles and avoid them. an object detector is composed of a backbone, neck, and head. the backbone is a network for obtaining image features, the neck fuses the feature maps from various layers, and the head is used for classification and localization. the model architecture of an object detector is displayed in fig. 4. 215 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 fig. 4 model architecture of an object detector the pretrained networks provided by google cloud platform (gcp), microsoft azure, and amazon web service (aws) are used to detect objects in real-time images and store the data from each platform in the following order: object class name, confidence score, bounding box top boundary value, bounding box bottom boundary value, bounding box left boundary value, and bounding box right boundary value. 3.2. path planning for a vehicle 3.2.1. deletion of the overlapped box first, the coordinates of the object bounding box are determined. next, whether two object bounding boxes overlap is determined. if an overlap is discovered, the bounding box with the higher bottom boundary value is removed. the left and right boundary values of objects a and b are set as (al, ar) and (bl, br), respectively. if the bounding boxes of a and b do not overlap, they must satisfy the following eqs. (1) and (2). l r l rb b a a< < < (1) l r l ra a b b< < < (2) 3.2.2. drivable area detection after removing the overlapping bounding box, the blank area between any two nonoverlapping objects is considered the movement area. the distance between all objects can be calculated from their bounding box coordinates. according to an axiom in the euclidean geometry system, the distance d between any two points p1(x1, y1) and p2(x2, y2) can be calculated using eq. (3). the shortest distance between the bottom endpoints of two bounding boxes, that is, the bottom line of the drivable area, is calculated as follows: 2 2 1 2 1 2 ( ) ( )d x x y y= − + − (3) 3.2.3. set destination the drivable area should be clear and not blocked by intermediate objects. a and b are set as nonadjacent objects, and a is to the left of b. the four endpoint coordinates of the bottom boundaries of the two objects are denoted as al(x1, y1), ar(x2, y2), bl(x1, y1), and br(x2, y2). when n objects exist between a and b, the bottom boundary endpoint coordinates of any object can be denoted as ol(x1, y1) or or(x2, y2). if the area is not blocked, eqs. (4) and (5) are satisfied. when the denominator in eqs. (4) and (5) is 0, the bounding boxes of the two objects overlap. this overlap is eliminated using eq. (1) or (2). 2 1 2 1 2 1 2 1 ax bx ax ox ay by ay oy − − < − − (4) 2 1 2 2 2 1 2 2 ax bx ax ox ay by ay oy − − < − − (5) 216 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 the center point of a robotic car is set as the midpoint of the bottom boundary of the image. the center point of each drivable area can be calculated from the endpoint coordinates of the bottom line of the drivable area. assuming that the two endpoints at the bottom of the drivable area are p1(x1, y1) and p2(x2, y2), the midpoint coordinates of the drivable area, namely pm(xm, ym), can be calculated using eq. (6). eq. (3) is used to calculate the distance between the midpoint of all drivable areas and the center point of the robotic car. the midpoint with the shortest distance to the center point is set as the waypoint, and the straight line from the center point to the waypoint represents the planned route. 1 2 1 2 ( , ) ( , ) 2 2 m m m x x y y p x y − − = (6) 3.3. movement control the coordinates of the center point of the robotic car and the waypoint can be used to calculate the offset angle between the travel direction of the robotic car and the waypoint. first, eq. (3) is used to calculate the distance between the car and waypoint. then, the cosine value of the angle between the planned path and the vertical line is calculated. the angle converted by the cosine value is the offset angle. if the offset angle does not exceed the preset threshold, a forward command is issued to allow the car to move forward. however, if the offset angle exceeds the preset threshold, a turn-left or turn-right command is issued for appropriately controlling the direction of car movement. 4. experimental results table 1 lists the experimental equipment used in this study. the raspberry pi is a single-chip computer developed by the raspberry pi foundation for improving students’ understanding of computing science. the experiment uses docker to construct an image file with the official raspberry pi operating system and the python 3 language for research. table 1 experimental equipment used in this study components specification operating system raspbian central processing unit arm cortex-a72 random access memory 4 gb (lpddr4) camera logitech c310 fig. 5 displays a self-propelled vehicle equipped with a raspberry pi 4 computer and complementary metal oxide semiconductor (cmos) lens assembly for capturing environmental images. the raspberry pi 4 has a 40-pin universal input and output that can be used for external screens and sensors. the raspberry pi 4 is connected to a power source motor for controlling the movement of a robotic car. a logitech c310 fixed-focus lens is used to obtain a 5-million-pixel image with a size of 1280 × 960. this lens is connected to the raspberry pi 4 through a universal serial bus (usb) interface. raspberry pi 4 has a rated power of 5 v/3 a. a mobile power bank is used as a power source through usb-c to provide a maximum output of 5 v/2.1 a to the raspberry pi 4. (a) front view of the vehicle (b) top view of the vehicle fig. 5 the robotic car equipped with raspberry pi 4 and cmos camera 217 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 4.1. drivable area detection the raspberry pi 4 and a streaming service are started. the streaming service is based on real time streaming protocol (rtsp). streaming images are sent to the cloud through cloud platforms, and apis are used for object identification. the object detection services used in this study are provided by google cloud vision, amazon rekognition, and azure computer vision cloud platforms to obtain the position coordinates, category names, and confidence scores for the objects in an image. obstacles are identified by using multiple clouds to increase the amount of information because insufficient information would have negatively affected the suitability of the planned path. moreover, accurate object class names and confidence scores are not required because the aim is to obtain information on surrounding obstacles. fig. 6 displays the results of object marking when using multiple cloud platforms, and the marked boxes of the same color represent the detection results obtained from the same platform. here, the gcp vision is presented by red color and the azure vision is presented by blue color. the program for drivable area detection is written in the python 3 language. first, the overlapping object bounding boxes are removed. then, the drivable area is detected and the waypoint is set. fig. 7 displays the result obtained after subjecting fig. 6 to drivable area detection. the green lines represent the bottom lines of multiple drivable areas. fig. 6 results of the comprehensive mark bounding box of cloud object detection fig. 7 schematic of drivable area detection 4.2. results and analysis fig. 8 depicts the two areas used in the experiment. fig. 8(a) displays a narrow walking passage in a laboratory. this image indicates that the exit of the aisle is on the left; therefore, the robotic car should turn to the left at the end of this aisle to avoid collision with the stacked boxes. fig. 8(b) displays a wide laboratory area with two exits. fig. 9 displays the legend for the different bounding box colors in figs. 10 and 11, which depict the continuous images obtained when the robot car moves according to the system instructions in the narrow and wide laboratory areas, respectively. in these images, different colors are used to represent the obstacles identified using different platforms. the yellow lines in figs. 10 and 11 indicate the real-time planned path for each image. the images in the aforementioned figures prove that visual recognition could be used to obtain a bounding box for path planning. thus, cloud computing facilitates real-time dynamic path planning. (a) narrow area (b) wide area fig. 8 panoramic images of the experimental areas 218 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 fig. 9 legend of the bounding box colors the third perspective the third perspective the third perspective the third perspective the vehicle view the vehicle view the vehicle view the vehicle view (a) at 5 s (b) at 15 s (c) at 25 s (d) at 35 s fig. 10 real-time images of the path planning and movement of the robotic car in the narrow laboratory area the third perspective the third perspective the third perspective the third perspective the vehicle view the vehicle view the vehicle view the vehicle view (a) at 5 s (b) at 15 s (c) at 25 s (d) at 35 s fig. 11 real-time images of the path planning and movement of the robotic car in the wide laboratory area all the obstacles on the ground are marked with white bounding boxes because the correct labeling of the object category is not crucial. moreover, the threshold to limit the object discrimination rate is obtained. multiple travel zones are detected by using a self-developed algorithm, and path planning is completed rapidly by using the obtained obstacle information. detailed experimental data are listed in tables 2 and 3. legend google amazon microsoft obstacles 219 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 table 2 detailed experimental results for cloud object detection figure path planning time (s) cloud platform class name detection confidence score left boundary value right boundary value top boundary value bottom boundary value 10(a) 0.001 gcp packaged goods 0.76 60 259 0 109 aws box 0.95 66 345 139 444 gcp packaged goods 0.69 67 261 64 171 gcp shipping box 0.61 79 340 150 432 azure wall 0.35 656 878 0 391 10(b) 0.02 gcp shipping box 0.76 0 230 85 511 aws box 0.56 0 232 103 500 10(c) 0.001 azure box 0.68 0 238 0 549 gcp shipping box 0.71 2 221 0 489 azure wall 0.56 896 1280 10 503 10(d) 0.001 gcp shoe 0.62 765 1004 285 344 azure cabinet 0.36 1118 1272 0 468 11(a) 0.001 gcp furniture 0.59 3 538 0 386 azure chair 0.38 628 1073 0 249 11(b) 0.001 gcp person 0.73 2 243 2 427 aws high heel 0.55 5 240 133 418 gcp person 0.71 10 254 1 434 azure chair 0.51 829 1253 74 292 azure wall 0.36 862 1216 20 216 11(c) 0.001 azure chair 0.45 2 94 274 481 azure chair 0.44 916 1280 78 267 11(d) 0.001 azure chair 0.38 124 323 0 387 aws airplane 0.82 497 1248 0 288 gcp person 0.69 787 1105 0 264 gcp home appliance 0.54 791 1121 0 266 table 3 average time required for cloud service object identification google cloud vision api 0.356 (s) microsoft azure computer vision api 1.042 (s) amazon web services rekognition api 2.098 (s) 5. conclusions this study developed a method in which the bounding box information returned by multiple cloud object detection services is integrated to detect the drivable area and plan a movement route. the experimental results reveal that robotic cars can perform appropriate path planning by using the developed method. the obtained images indicate that the planned route using the developed method is safe. the goals of this research were to reduce the cost of developing a collision-avoidance system, the cost of computing, and the dependence on an object sensor. cloud vision models are used to reduce the amount of computing in the designed system. the designed system is simple, has low cost, and contains only one lens. routes are planned through simple mathematical operations that do not burden the developed real-time path-planning system. latency is a critical real-time problem that should be considered when using cloud computing local area network signals because it affects system operation. the delay problem can be solved using next-generation high-speed networks that provide high transmission speeds with novel visual recognition models. conflicts of interest the authors declare no conflict of interest. 220 advances in technology innovation, vol. 6, no. 4, 2021, pp. 213-221 references [1] p. h. lin, c. y. lin, c. t. hung, j. j. chen, and j. m. liang, “the autonomous shopping-guide robot in cashier-less convenience stores,” proceedings of engineering and technology innovation, vol. 14, pp. 9-15, january 2020. 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[22] t. xu, s. zhang, z. jiang, z. liu, and h. cheng, “collision avoidance of high-speed obstacles for mobile robots via maximum-speed aware velocity obstacle method,” ieee access, vol. 8, pp.138493-138507, 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 221 microsoft word 1-v8n1(2023)-aiti#10658(01-11).docx advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 optimization of weld parameters in wire and arc-based directed energy deposition of high strength low alloy steels van thao le1,*, dinh si mai1, van thuc dang1, duc manh dinh1, thi hong cao2, van anh nguyen3 1advanced technology center, le quy don technical university, hanoi, vietnam 2institute for tropical technology, vietnam academy of science and technology, hanoi, vietnam 3welding engineering and laser processing centre, cranfield university, bedford, uk received 10 august 2022; received in revised form 27 september 2022; accepted 30 september 2022 doi: https://doi.org/10.46604/aiti.2023.10658 abstract this paper aims to investigate the fabrication of high strength low alloy (hsla) steels by wire and arc-based directed energy deposition (waded). firstly, the relationship between the process variables (including the travel speed-v, the current-c, and the voltage-u) and the geometrical characteristics of weld beads (including the bead height (bh), bead width (bw), and melting pool length (mpl)) was investigated. secondly, the optimal process variables were identified using the desirability approach. the results indicate that voltage-u has the highest impact on bw and mpl, meanwhile the travel speed-v is the most impacting factor on bh. the optimal variables for the waded process of hsal steels are v = 0.3 m/min, c = 160 a, and u = 19 v. the component fabricated with the optimal variables is fully dense without spatters and defects, confirming the efficiency of the waded process for hsla steels. keywords: waded, hsla steel, weld bead, optimal variables 1. introduction emerged since the 1980s, additive manufacturing (am) technologies, especially metallic am, are strongly developed, and they are becoming the key technology in the industry 4.0 era [1]. because of the layer-by-layer manufacturing principle, am technologies can fabricate very complex structures from various materials, including metallic alloys that are very difficult to machine by conventional processes such as milling and turning [2]. the metallic am technologies can be categorized based on the energy source and feedstock form or the fabrication methods. according to the feedstock form and the fabrication methods, there are two main groups of metallic am, i.e., powder bed fusion (pbf) and directed energy deposition (ded) [3]. compared to pbf-am processes, ded-am can produce metallic components with larger dimensions and can be applied effectively for repairing and remanufacturing applications [4-7]. the ded-am processes include two technologies: (i) laser and powder-based ded (lpded) using a laser source to melt metal powder (fig. 1(a)), and (ii) wire and arc-based ded (waded) utilizing an arc source to melt the metal wire (fig. 1(b)). the nozzle in the waded is a welding torch, and the wire feeding method depends on the used welding source, for example, gas tungsten arc welding (gtaw), plasma arc welding (paw), and gas metal arc welding (gmaw) [8]. compared to other metal am technologies, waded has a superior rate of material deposition (from 3 to 8 kg/h), high efficiency of material utilization, low costs of investing systems and devices, and easy implementation [9]. * corresponding author. e-mail address: vtle@lqdtu.edu.vn advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 2 the metal wire available in the welding market can be used for waded processes. they are also much cheaper than metal powder used in pbf-am and lpded. therefore, waded is becoming a potential solution for manufacturing components with large and wide dimensions [10]. (a) the lpded process [11] (b) the waded process fig. 1 schemas of lpded and waded processes among metals used in waded, including steels, aluminum, titanium, and nickel-based alloys, steels are the most investigated materials because of their relatively low costs, wide applications, and availability in the welding market. in the literature, many steel grades have been investigated and fabricated with the waded processes, for example, low-carbon steels (e.g., er70s-6) [12-14], austenite stainless steels (e.g., 304, 308l, 308lsi, 309l, and 316l) [15], and highstrength low alloy (hsla) steels (e.g., er110s-g and er120s-g) [16-18]. the hsla steels are largely utilized for manufacturing lightweight structures and high strength components in many sectors, for example, automotive, shipbuilding, tools and die industries. these steel grades have high strength, toughness, weldability, and low costs [19]. recently, many researchers have investigated and fabricated components from hsla steels by the waded processes. sun et al. [20] produced thin-wall hsla steel components by waded and examined the anisotropy in mechanical characteristics. they stated that the strengths of the as-fabricated component in the horizontal direction were lower than those in the vertical direction. rodrigues et al. [16] studied the impact of the heat input on the microstructures and mechanical properties of the wadeded thin-wall hsla steel part. they observed that there were no significant differences in microstructure between the specimens fabricated with low and high levels of heat input. dirisu et al. [19] analyzed the toughness properties of hsla steels produced by waded. they found that the refinement in grains and the increase in density of grain boundaries resulted in high resistance to failure of the samples in the vertical direction. fang et al. [21] also fabricated hsla steel parts by waded. the researcher observed that the part had a superior balance in strength and ductility. the variation in microhardness was due to the difference of thermal histories in different regions of the component. although certain authors have investigated hsla steels fabricated by the waded processes, as mentioned above, they mainly analyzed microstructures and mechanical characterization of the as-built material, as well as the influence of process variables on the quality of the part. until now, the studies on predicting and optimizing process variables in waded of hsla steel to obtain the expected geometrical properties of weld beads are still limited. most of the previously mentioned studies have selected the process variables (e.g., the arc voltage, welding current, and wire-feed speed) based on the suggestion of the wire manufacturers for conventional welding or based on several tests, while the waded process is very different from welding. in waded processes, the quality and geometry of weld beads (e.g., stable and smooth shape and less spatter) notably affect the process stability and the appearance of as-fabricated components [22-25]. therefore, this study aims to explore the relationship between the process variables {c, u, and v} and the geometrical characteristics of weld beads {bw, bh, and mpl} and identify optimal process parameters that produce weld beads with expected geometrical properties. advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 3 2. materials and methods 2.1. materials and the waded system in this investigation, the hsla steel wire (sm-110) with a 1.2-mm diameter supplied by hyundai welding and the low-carbon steel substrates with a size of 200 × 200 × 10 mm had been utilized. the chemical elements of the wire are 1.95%ni, 1.90%mo, 0.34%cr, 0.58%mo, 0.80%si, 0.089%c, 0.010%p, 0.004%s, and %fe in balance (wt.%). a waded system (fig. 2(a)) consists of a gmaw source, a welding torch, a welding wire feeder, a 6-axis robot, and a shielding gas feeder was used to fabricate the samples (e.g., single weld tracks, fig. 2(b) and fig. 2(c)). the relationships between the wire feed speed and welding current in this gmaw-am system is approximately increasing linearly. a mixed gas of argon (80%) and co2 (20%) with 16 l/min in flow speed was applied during the waded process. (a) the welding robot (b) weld bead samples (c) wb’s characteristics fig. 2 the waded system, the wb samples with the measurement area, and the response description 2.2. experimental procedure to achieve the goal of the study, the research procedure shown in fig. 3 was performed. the research procedure includes the following steps: (i) identification of the process variables and their ranges, (ii) design of experiment, (iii) fabrication of single weld beads by the waded process, (iv) measurement of the responses (i.e., bh, bw, and mpl), development of regression models for the responses and determining the impact of process variables on the responses through the analysis of variance (anova), and (v) the optimization of process variables. to observe the relationship between the process variables and the responses, the taguchi l9 orthogonal array was adopted to design the experimental plan. three input variables, including the current-c, the travel speed of the weld torch-v, and the voltage-u were selected for the investigation because they directly influence the shape and dimensions of the weld beads. three levels for each variable were used (table 1). as a result, there were nine experiment runs. table 1 input variables and their levels for the doe item levels voltage-u (v) 18 20 22 current-c (a) 120 140 160 travel speed-v (m/min) 0.3 0.4 0.5 advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 4 fig. 3 the study flowchart after the fabrication of weld bead samples, the responses of weld beads, including bh, bw, and mpl were measured. these characteristics of weld beads play important roles in the waded process. bh and bw are related to the layer width and height, whereas the mpl is related to the planning of deposition paths. the measurements were executed in the stable regions of welding beads (fig. 2(b)) utilizing a digital mitutoyo caliper with 0.01 mm in resolution and ± 0.02 mm in accuracy. the bw and bh were measured five times at five locations in the middle zone of weld beads (fig. 2(b)). finally, the average value of the five measurements of bw and bh was taken for analysis. on the other hand, the measurement of mpl was repeated three times to ensure the reliability of the measurement results. the experiment runs and measured results were presented in table 2. table 2 experiment runs and the response measurement experiment run input variables responses current-c (a) voltage-u (v) travel speed-v (m/min) bw (mm) bh (mm) mpl (mm) 1 120 18 0.3 5.39 3.09 11.26 2 120 20 0.4 5.86 2.54 11.64 3 120 22 0.5 5.82 1.82 12.39 4 140 18 0.4 4.58 2.92 10.49 5 140 20 0.5 5.41 2.33 11.34 6 140 22 0.3 7.51 2.81 13.52 7 160 18 0.5 4.18 2.77 9.79 8 160 20 0.3 6.87 3.00 11.95 9 160 22 0.4 7.82 2.37 13.24 2.3. analysis and optimization methods to evaluate the impact of input variables on the responses and identify the impact contribution of each input, the anova and the minitab software was adopted. the anova was executed with a 5% significance level and a 95% confidence level. in the waded, bh, and bw are expected to be maximal while the mpl is minimal to enhance productivity. as a result, the optimization problem was formulated as eq. (1). { } { } { } { } , , , 120 160 , 18 22 , 0.3 0.5 / find c u v to maximize bh bw and minimize mpl subject to c a u v v m min≤ ≤ ≤ ≤ ≤ ≤      (1) advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 5 the optimal input variables were estimated by the desirability function (df) method [26]. moreover, the weight for each response (i.e., bw, bh, and mpl) was identified by the critic method [27]. the steps of the critic method are described as follows: step 1: construct the decision matrix (dm) of k experimental runs and p evaluation attributes: dm = [���] ×� . step 2: normalize the dm using eq. (2): ˆ worst ij j ij best worst j j m m m m m − = − (2) where �� �� is the normalized value of the �� alternative for ��� attribute, �� ���� and �� ����� are the best and worst values of ��� attribute. step 3: calculate the standard deviation of each normalized attribute using eq. (3): 2 1 ˆ( ) k ij j i j m m k σ = − =  (3) where k is the number of experimental runs and ��� is the average value of ��� normalized attribute. step 4: construct the symmetric matrix [����] × with the linear-correlation coefficient ���� between the attributes. ���� is calculated by eq. (4): 1 2 2 1 1 ˆ ˆ( )( ) ˆ ˆ( ) ( ) k li i lj j l ij k k li i lj j l l m m m m cc m m m m = = = − − = − −    (4) step 5: calculate the attribute information ��� by eq. (5): 1 (1 ) k j j jl l ai ccσ = = − (5) step 6: calculate the weight �� for each attribute (i.e., response): 1 j j p j j ai w ai = =  (6) 3. results and discussion 3.1. regression models the regressive models of the responses bw, bh, and mpl are shown in tables 3, 4, and 5, respectively. they were developed with the help of minitab software. in the case of bw, the p-values of u and v in table 3, are smaller than 0.05, while the p-value of c is bigger than 0.05, meaning that u and v are the significant terms of the bw model. the values of r-sq, r-sq(adj), and r-sq(pred) are 95.67%, 93.07%, and 83.83%, respectively. it indicates that the bw model has acceptable accuracy and can terms be used to predict the response in the entire design space. for the bh model, all the p-values of c, u, and v in table 4 are smaller than 0.05. therefore, all the model terms c, u, and v are significant. the values of the determination coefficients r-sq, r-sq(adj), and r-sq(pred) are 96.51%, 94.72%, and advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 6 86.18%, respectively, indicating a reasonable accuracy of the bh model. this model can also be used to predict the response in the entire design space. for the developed model of mpl, the p-values of u and v in table 5 are smaller than 0.05, while the p-value of c is bigger than 0.05, indicating that u and v are the significant term of the mpl model. the values of r-sq, r-sq(adj), and r-sq(pred) are 97.73%, 96.36%, and 91.15%, respectively. therefore, the mpl model has an acceptable accuracy, and it can be used to predict the responses (i.e., bw, bh, and mpl) in the whole design space. table 3 anova of bw source df seq ss contribution adj ss adj ms f-value p-value regression 3 11.8791 95.67% 11.8791 3.9597 36.81 0.001 c 1 0.5424 4.37% 0.5424 0.5424 5.04 0.075 u 1 8.1713 65.81% 8.1713 8.1713 75.97 0.000 v 1 3.1654 25.49% 3.1654 3.1654 29.43 0.003 error 5 0.5378 4.33% 0.5378 0.1076 total 8 12.4169 100.00% regressive model �� = �4.93 # 0.01503 × ' # 0.5835 × ) � 7.26 × r-sq = 95.67% r-sq(adj) = 93.07% r-sq(pred) = 83.83% table 4 anova of bh source df seq ss contribution adj ss adj ms f-value p-value regression 3 1.26082 96.51% 1.26082 0.420272 46.14 0.000 c 1 0.07935 6.07% 0.07935 0.079350 8.71 0.032 u 1 0.52807 40.42% 0.52807 0.528067 57.98 0.001 v 1 0.65340 50.02% 0.65340 0.653400 71.74 0.000 error 5 0.04554 3.49% 0.04554 0.009108 total 8 1.30636 100.00% regressive model �. = 6.109 # 0.00575 × ' � 0.1483 × ) � 3.300 × r-sq = 96.51% r-sq(adj) = 94.42% r-sq(pred) = 86.18% table 5 anova of mpl source df seq ss contribution adj ss adj ms f-value p-value regression 3 11.3854 97.73% 11.3854 3.79513 71.65 0.000 c 1 0.0160 0.14% 0.0160 0.01602 0.30 0.606 u 1 9.6520 82.85% 9.6520 9.65202 182.22 0.000 v 1 1.7173 14.74% 1.7173 1.71735 32.42 0.002 error 5 0.2648 2.27% 0.2648 0.05297 total 8 11.6502 100.00% regressive model /01 = 1.55 � 0.00258 × ' # 0.6342 × ) � 5.350 × r-sq = 97.73% r-sq(adj) = 96.36% r-sq(pred) = 91.15% 3.2. relationship between the input variables and the responses as shown in fig. 4(a), it is indicated that the bw increases when u and c increment. meanwhile, v shows an opposite impact tendency. the bw decreases with the augmentation in v. based on the anova results (table 3), the voltage-u has the most impact contribution to the bw with 65.81%, followed by the travel speed (25.49%), and the current (4.37%), respectively. the influence of the input variables on the bw can be explained as follows. an increase in voltage also makes an increase in the length and spreading of the arc. therefore, bw becomes larger with a higher level of voltage [28]. an increase in welding current leads to an increase in wire feed speed and material deposition, resulting in an augmentation in melting pool size and in advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 7 the width of weld beads (bw) [23]. oppositely, an increase in travel speed causes a reduction in material deposition quantity per length unit. therefore, the bw becomes narrow as the travel speed increases [28]. the influence of the input variables on the bh is shown in fig. 4(b). it is shown that the increase in both the voltage-u and the travel speed-v causes a decrease in the bh. on the other hand, the bh increases when the current-c increase. however, the bh sightly increases when c increases from 140 a to 160 a. in this case, the travel speed-v reveals the highest impact on the bh with a contribution of 50.02%, followed by the voltage-u (40.42%), and the current-c (6.02%), respectively (table 4). indeed, when increasing the travel speed, the quantity of deposited materials per length unit is reduced. hence, bh is reduced [28-29]. the spreading area of the arc is larger when the voltage increases, leading to flatter weld beads [30]. as a result, bh reveals a reducing trend with an increment in voltage. as c increases, the wire feeding speed augments. hence, the volume of materials deposited increases, leading to an increase in bh [28]. for the mpl, as depicted in fig. 4(c), it strongly increases when the voltage increases, meanwhile the mpl slightly increases with the increase in the current-c. the mpl, on the other hand, increases as v augments from 0.3 m/min to 0.4 m/min, after that it decreases. these findings can be explained by the anova results (table 5). it is shown that the voltage-c has the most influential contribution of 82.85% to mpl, while the current has the lowest impact contribution of 0.14% to mpl. (a) effects of process variables on bw (b) effects of process variables on bh (c) effects of process variables on mpl fig. 4 influences of the input variables on the responses 3.3. optimization results as mentioned previously, the weights for the responses were calculated by the critic method. the weight values of bw, bh, and mpl were 0.42, 0.23, and 0.34, respectively. the solution of the multi-attribute optimization problem (eq. (1)) was shown in fig. 5. it indicated that the optimal input variables are {c = 160 a, v = 0.3 m/min, and u = 19 v}. this set of input parameters is corresponding to the df value of 0.8651 and the predicted responses bw = 6.39 mm, bh = 3.22 mm, and mpl = 11.59 mm. compared to the worst case, where the bh was the smallest (the experiment run #3), the optimal input parameters allow enhancing the bh and bw by 77% and 10%, respectively, while reducing the mpl by 6%. advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 8 fig. 5 optimization solution to confirm the efficiency of the optimal input parameters, they were tested to fabricate a three-bead multi-layer-cylindric wall (fig. 6). it is shown that the optimal parameters enable the production of smooth weld beads without spatters and major defects. there is only a minor defect in shape on the top surface at the stopping point of the weld path. in this investigation, as the starting point and the ending point of the weld path were not identical, there was an overlap between the arc-striking and the arc-extinguishing regions of the arc (fig. 7(a)). therefore, the difference in height between the arc-striking and the arc-extinguishing regions was compensated. on the other hand, when the starting and the ending points are identical, there is a space in the circle weld bead between the starting and the ending points (fig. 7(b). as the number of layers increases, the gap depth increases, resulting in major defects in the shape of the part. fig. 6 multi-bead multi-layer cylindric part (a) not identical (b) identical fig. 7 programming of a circle weld path: the starting point and the ending point advances in technology innovation, vol. 8, no. 1, 2023, pp. 01-11 9 moreover, the as-built material is fully dense without defects such as pores, cracks, and lack of fusion. the microstructure mainly consists of α-ferrite phases in acicular and granular morphologies (fig. 8(a)). the edx analysis results also indicate that the as-built material has similar chemical elements as the wire material (fig. 8(b)). the melted metal was perfectly protected by the shielding gas during the waded process. (a) microstructure (b) chemical elements fig. 8 microstructure and chemical elements of the as-built material 4. conclusions in this study, hsla steel was utilized as the raw material in the waded process. the study aims to predict the connection between the main process variables {c, u, and v} and the geometrical characteristics of weld beads {bw, bh, and mpl}. furthermore, finding the optimal process variables is also the study’s aim. the main findings of this investigation are highlighted as follows. (1) the voltage-u has the highest impact on bw and mpl, meanwhile the travel speed-v is the most impacting factor on bh. an increase in u leads to an increase in bw and mpl and a decrease in bh. on the other hand, an increase in v causes a decrease in both bw and bh. (2) all the predictive models of bw, bh, and mpl have an acceptable accuracy with the determination values r-sq = 95.67%, 96.51%, and 97.73%, respectively. they can be applied to predict the responses in the entire design space. (3) the optimal process variables for the waded process of sm-110 hsla steel are v = 0.3 m/min, c = 160 a, and u = 19 v. the component fabricated with the optimal variables has a smooth top surface. moreover, spatters and defects don’t present in the fabrication. the as-built material is fully dense without defects such as pores, cracks, and lack of fusion. 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[30] s. jindal, r. chhibber, and n. p. mehta, “effect of welding parameters on bead profile, microhardness and h2 content in submerged arc welding of high-strength low-alloy steel,” proceedings of the institution of mechanical engineers, part b: journal of engineering manufacture, vol. 228, no. 1, pp. 82-94, january 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 numerical analysis of an industrial-scale steam methane reformer chun-lang yeh * department of marine engineering, national taiwan ocean university, keelung, taiwan received 02 march 2018; received in revised form 24 june 2018; accepted 29 july 2018 abstract a steam reformer of a hydrogen plant is a device that supplies heat to convert the natural gas or liquid petroleum gas into hydrogen via catalysis. it has been often used in the petrochemical industry to produce hydrogen. control of the catalyst tube temperature is a fundamental demand of the reformer design because the tube temperature must be maintained within a range that the tube has minor damage and the catalysts have a high activity to convert the natural gas or liquid petroleum gas into hydrogen. in this research, the effect of the burner on/off manners on the catalyst tube temperature and the hydrogen yield of an industrial-scale side-fired steam methane reformer is investigated. the aim is to seek a feasible burner on/off manner that has acceptable catalyst tube temperature and hydrogen yield, so as to improve the performance and service life of a steam methane reformer. it is found that when one group of burners is turned off, the outer surface temperatures of the tubes are decreased by about 94°c in average, the inner surface temperatures are decreased by about 54°c in average, and the hydrogen yields are decreased by about 4%. when two groups of burners are turned off, the outer surface temperatures of the tubes are decreased by about 175°c in average, the inner surface temperatures are decreased by about 106°c in average, and the hydrogen yields are decreased by about 7.9%. when three groups of burners are turned off, the outer surface temperatures of the tubes are decreased by about 251°c in average, the inner surface temperatures are decreased by about 151°c in average, and the hydrogen yields are decreased by about 11.4%. the catalyst tube temperatures and the hydrogen yields reduce to a greater extent in regions where burners are turned off. when the central groups of burners are turned off, the tube temperatures and the hydrogen yields have greater reductions. on the other hand, when the rear groups of burners are turned off, the tube temperatures and the hydrogen yields have lower reductions. keywords: hydrogen, steam methane reformer, catalyst tube, burner operation 1. introduction a steam reformer of a hydrogen plant is a device that supplies heat to convert the natural gas or liquid petroleum gas into hydrogen via catalysts. hydrogen is an important material for petroleum refineries. it converts crude oil into products with high economic value, e.g., gasoline, jet fuel, and diesel. hydrogen can be produced by a number of ways, e.g., electrolysis, steam methane reforming (smr), partial oxidation reforming, nuclear energy, etc. [1,2] among these ways, smr is the most common commercial method of industrial hydrogen production. smr reaction mainly includes the following three chemical equations: 4 2 2 ch h o co 3h  (1) 2 2 2 co h o co h  (2) 4 2 2 2 ch 2h o co 4h  (3) * corresponding author. e-mail address: clyeh@nfu.edu.tw advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 141 the first (smr) and the third reactions are endothermic, the second reaction (water-gas shift (wgs)) is exothermic, and the overall reaction is endothermic. the combustion process in a reformer provides heat to maintain the reforming reaction in a catalyst tube. control of the catalyst tube temperature is a fundamental demand of the reformer design because the tube temperature must be maintained within a range that the tube has minor damage and the catalysts have a high activity to convert the natural gas or liquid petroleum gas into hydrogen. when a steam reformer is operating, the catalyst tubes are subjected to stresses close to the ultimate stress of the tube material. this leads to an acceleration of the creep damage. safety, reliability, and efficiency are the basic requirements of the reformer operation. the catalyst tube should have uniform heat distribution to extend the tube service life. however, the heat distribution in a reformer is practically non-uniform. in addition, maldistribution of the flue gas and fuel gas may result in flame impingement on the catalyst tubes and lead to localized hot spots and high tube wall temperature. these factors may shorten tube life. owing to the rapid development in computer science and technology, as well as the improvements in physical models and numerical methods, computational fluid dynamics (cfd) is widely used in analyzing systems involving heat transfer, fluid flow, and chemical reactions. cfd is also used to simulate systems that cannot be measured easily or simulated experimentally. in recent years, there have been a lot of smr researches using cfd. tran et al. [3] developed a cfd model of an industrial-scale steam methane reformer. the authors pointed out that the reformer cfd model can be considered an adequate representation of the on-line reformer and can be used to determine the risk of operating the online reformer at unexplored and potentially more beneficial operating conditions. di carlo et al. [4] investigated numerically a pilot scale bubbling fluidized bed se-smr (sorption enhanced steam methane reforming) reactor by means of a two-dimensional cfd approach. the numerical results show quantitatively the positive influence of carbon dioxide sorption on the reforming process at different operating conditions, specifically the enhancement of hydrogen yield and reduction of methane residual concentration in the reactor outlet stream. lao et al. [5] developed a cfd model of an industrial-scale reforming tube using ansys fluent with realistic geometry characteristics to simulate the transport and chemical reaction phenomena with the approximate representation of the catalyst packing. the authors analyzed the real-time regulation of the hydrogen production by choosing the outer wall temperature profile of the reforming tube and the hydrogen concentration at the outlet as the manipulated input and controlled output, respectively. mokheimer et al. [6] presented modeling and simulations of the smr process. the model was applied to study the effect of different operating parameters on the steam and methane conversion. the results showed that increasing the conversion thermodynamic limits with the decrease of the pressure results in a need for long reformers so as to achieve the associated fuel reforming thermodynamics limit. it is also shown that not only increasing the steam to methane molar ratio is favorable for higher methane conversion but the way the ratio is changed also matters to a considerable extent. ni [7] developed a 2d heat and mass transfer model to investigate the fundamental transport phenomenon and chemical reaction kinetics in a compact reformer for hydrogen production by smr. parametric simulations were performed to examine the effects of permeability, gas velocity, temperature, and rate of heat supply on the reformer performance. it was found that the reaction rates of smr and wgs are the highest at the inlet but decrease significantly along with the reformer. increasing the operating temperature raises the reaction rates at the inlet but shows very small influence downstream. ebrahimi et al. [8] applied a three-dimensional zone method to an industrial fired heater of the smr reactor. the effect of emissivity, extinction coefficient, heat release pattern and flame angle on the performance of the fired heater are presented. it was found that decreasing the extinction coefficients of combustion gases by 25% caused a 2.6% rise in the temperature of heat sink surfaces. seo et al. [9] investigated numerically a compact smr system integrated with a wgs reactor. heat transfer to the catalyst beds and the catalytic reactions in the smr and wgs catalyst beds were investigated. the effects of the cooling heat flux at the outside wall of the system and steam-to-carbon ratio were also examined. it was found that as the cooling heat flux increases, both the methane conversion and carbon monoxide content are reduced in the smr bed and the carbon monoxide conversion is advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 142 improved in the wgs bed. in addition, both methane conversion and carbon dioxide reduction increase with increasing steam-to-carbon ratio. in this paper, the transport and chemical reaction in an industrial-scale steam methane reformer is simulated using cfd. the influence of burner on/off manners on the catalyst tube temperature and the hydrogen yield of an industrial-scale side-fired steam methane reformer is investigated. the aim is to seek a feasible burner on/off manner that has acceptable catalyst tube temperature and hydrogen yield, so as to improve the performance and service life of a steam methane reformer. 2. numerical methods and physical models in this study, the ansys fluent v.17 commercial code [10] is employed to simulate the reacting and fluid flow in a steam methane reformer. the simple algorithm by patankar [11] is used to solve the governing equations. the discretizations of convection terms and diffusion terms are carried out by the second-order upwind scheme and the central difference scheme, respectively. in respect to physical models, by considering the accuracy and stability of the models and by referring to the other cfd researches [3-5] of steam methane reformers, the standard k-ε model [12], discrete ordinate (do) radiation model [13] and finite rate/eddy dissipation (fred) model [14] are adopted for turbulence, radiation and chemical reaction simulations, respectively. the standard wall functions [15] are used to resolve the flow quantities (velocity, temperature, and turbulence quantities) at the near-wall regions. for the steady-state three-dimensional flow field with chemical reaction in this study, the governing equations include the continuity equation, momentum equation, turbulence model equation (k-ε model), energy equation, radiation model equation (discrete ordinates radiation model), and chemical reaction model equation (fred model). among these models, only the fred chemical reaction model is described below while the others and the convergence criterion are not described because they have been introduced in the author’s previous study [16]. consider the general form of the r th chemical reaction as follows: f ,r b ,r k n n i,r i i,r ii 1 i 1 k         (4) where n = number of chemical species in the system 𝜈𝑖,𝑟 ′ = stoichiometric coefficient for reactant i in reaction r 𝜈𝑖,𝑟 ′′ = stoichiometric coefficient for product i in reaction r μi = species i 𝑘𝑓,𝑟 = forward rate constant for reaction r 𝑘𝑏,𝑟 = backward rate constant for reaction r eq. (4) is valid for both reversible and non-reversible reactions. for non-reversible reactions, the backward rate constant, kb,r, is omitted. the species transport equation of a chemical reaction system can be written as   t i i,m i i i t y d y r s sc              (5) where yi, di,m, sct, ri, and si are the mass fraction, diffusion coefficient, turbulent schmidt number, net generation rate, and extra source term of species i, respectively. the net source of chemical species i due to reaction is computed as the sum of the arrhenius reaction sources over the nr reactions that the species participate in �̂� advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 143 rn i w,i r 1 i,r ˆr m r    (6) where mw, i is the molecular weight of species i and �̂�𝑖.𝑟 is the arrhenius molar rate of creation/destruction of species i in reaction r. for a non-reversible reaction, the molar rate of creation/destruction of species i in reaction r is given by     j,r j,rn i,r i,r i,r f ,r j 1 j,rr̂ k c               (7) for a reversible reaction,   j,r j,rn n i,r i,r i,r f ,r j 1 j,r b,r j 1 j,rr̂ k c k c                     (8) where 𝐶𝑗,𝑟 = molar concentration of species j in reaction r (kgmol/m 3 ) 𝜂𝑗,𝑟 ′ = rate exponent for reactant species j in reaction r 𝜂𝑗,𝑟 ′′ = rate exponent for product species j in reaction r γ = net effect of third bodies on the reaction rate the forward and backward rate constants for reaction r, kf,r and kb,r, are computed using the arrhenius expression: r er/rt f ,r rk t e   (9) f ,r b,r r k k k  (10) where ar = pre-exponential factor (consistent units) βr = temperature exponent (dimensionless) er = activation energy for the reaction (j/kgmol) r = universal gas constant (j/kgmol-k) kr is the equilibrium constant for the r th reaction and is computed from   n i,r i,ri 1o o atmr r r s h k exp r rt rt                  (11) where patm denotes atmospheric pressure (101, 325 pa). the term within the exponential function represents the change in gibbs free energy, and its components are computed as follows:   o o n r i i,r i,ri 1 s s r r      (12)   o o nr i i,r i,ri 1 h h rt rt      (13) where si o and hi o are the standard-state entropy and standard-state enthalpy (heat of formation). in this study, the kinetic and thermodynamic constants for reactions (1-3) used in chibane and djellouli’s work [17] are adopted. in general, a reformer operates at high temperatures. for a non-premixed reaction, turbulence mixes the reactants and then advects the mixture to the reaction zone for quick reaction. for a premixed reaction, turbulence mixes the lower-temperature reactants and the higher-temperature products and then advects the mixture to the reaction zone for a quick reaction. therefore, advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 144 the chemical reaction is generally mixing (diffusion) controlled. however, the flue gas, fuel gas, and air are generally premixed before injecting into the reformer. although the chemical reaction in most regions in a reformer is mixing controlled, in some regions, e.g., the neighborhood of the feed inlet, the chemical reaction is kinetically controlled. in existing chemical reaction models, the eddy dissipation model (edm) [18] can consider simultaneously the diffusion controlled and the kinetically controlled reaction rates. in edm, the net generation rate of species i in the r th chemical reaction is found from the smaller value of the following two reaction rates: r i,r i,r w,i r r,r w,r y r m min k m          (14) p p i,r i,r w,i n j,r w, jj y r m k m        (15) where yp is the mass fraction of any product, p yr is the mass fraction of a particular reactant, r a is an empirical constant equal to 4.0 b is an empirical constant equal to 0.5 in general, the edm works well for a non-premixed reaction. however, for a premixed reaction, the reaction may start immediately when injecting into a reformer. this is unrealistic in practical situations. to overcome this unreasonable phenomenon, ansys fluent provides another model, the finite-rate/eddy-dissipation (fred) model, which combines the finite-rate model and the edm. in this model, the net generation rate of a species is taken as the smaller value of the arrhenius reaction rate and the value determined by edm. the arrhenius reaction rate plays the role of a switch to avoid the unreasonable situation that the reaction starts immediately when injecting into a reformer. once the reaction is activated, the eddy-dissipation rate is generally lower than the arrhenius reaction rate, and the reaction rate is then determined by the edm. 3. results and discussion to validate the numerical methods and physical models used in this study, an industrial-scale steam methane reformer is simulated. the configuration and dimension of the reformer investigated are shown in fig. 1. note that only one half of the reformer is simulated due to its symmetry, as shown in figure 1b,c. the reformer contains 138 reforming tubes and 216 burners on one side (totally 276 tubes and 432 burners). the outer diameter and thickness of a reforming tube are 136mm and 13.4 mm, respectively, while the diameter of a burner is 197 mm. the boundary conditions for the numerical model of the steam methane reformer are described below. these conditions are practical operating conditions that are used by a petrochemical corporation in taiwan. (1) symmetry plane: symmetric boundary condition (2) wall: standard wall function (3) reforming tube inlet: v = 5.4 m/s (in axial direction) t = 912.75 k pgauge = 2.1658 × 10 6 n/m 2 advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 145 species mole fraction: ch4 = 0.2029 h2o = 0.6 h2 = 0.12855 co2 = 0.06565 co = 0.00145 n2 = 0.00145 (a) a typical steam methane reformer (b) a numerical model of the steam methane reformer (c) the dimension of the steam methane reformer (d) illustration of the burner positions (e) illustration of the reforming tube positions fig. 1 configuration and dimension of the steam methane reformer investigated (4) reforming tube exit the diffusion flux for all flow variables in the outflow direction are zero. in addition, the mass conservation is obeyed at the exit. advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 146 (5) fuel and flue gas inlet (burner inlet): v = 2.404 m/s (in radial direction) t = 673.15 k pgauge = 1.04544 × 10 4 n/m 2 species mole fraction: h2 = 0.0816 ch4 = 0.0474 n2 = 0.49057 o2 = 0.12818 co2 = 0.25225 (6) fuel and flue gas exit: the diffusion flux for all flow variables in the outflow direction are zero. in addition, the mass conservation is obeyed at the exit. the turbulence kinetic energy is 10% of the inlet mean flow kinetic energy and the turbulence dissipation rate is computed using eq. (16). l k c 2/3 4/3   (16) where l = 0.07 l and l is the hydraulic diameter. 3.1. comparison of numerical results with experimental data the simulation results are compared with the experimental data from a petrochemical refinery in taiwan to evaluate the numerical methods and physical models adopted in this study. the temperature of the reformer is detected by an infrared thermographer with radiation emissivity of 0.92, the field of view (fov) 24mm and object distance of 5m. as mentioned above, the real reformer contains 138 reforming tubes and 216 burners on one side (totally 276 tubes and 432 burners). to save simulation time, a simplified model is also calculated and compared. the simplified model contains 6 tubes and 12 burners on one side of the reformer. the arrangement of reforming tubes and burners as well as their dimensions for the simplified model is shown in fig. 2. the flow rates in the reforming tubes and burners for the simplified model are the same as those in the real reformer. therefore, the reforming tubes and burners for the simplified model have larger diameters. fig. 2 the arrangement of reforming tubes and burners as well as their dimensions for the simplified model advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 147 the computer used in this study is an asus esc-500-g4 work station of 8 cores with intel core i7-6700 cpu and 64 gb ram. the numbers of cfd cells for the real reformer model and the simplified model are around 4 million and 1.5 million, respectively. the grid mesh is generated by the software gambit and is unstructured. the dimensionless distance from the wall, y*, in the wall function method has been examined after a converged solution is obtained. it was found that the values of y* for the nodes at the wall to their nearest interior nodes vary between 20.0 and 60.0, and lie in the logarithmic layer of the wall function method. this implies that the wall-adjacent cells of the grid mesh in this study are suitable for the use of wall function. the solution of the cfd model for the real reformer is obtained after approximately 30 full days while that for the simplified reformer is approximately 10 full days. fig. 3 compares the average temperatures at the outer surfaces of the reforming tubes. it can be seen that the simulation result agrees well with the experimental data. the deviations from the experimental data using the real reformer model and the simplified model are 2.88% and 3.18%, respectively, which are both acceptable from a viewpoint of engineering applications. the result calculated from the real reformer model agrees better with the experimental data than that from the simplified model, although the latter also gives an acceptable result. fig. 4 shows the simulated hydrogen yield at the reforming tube outlets using a simplified model. the experimental value of the hydrogen yield is 0.698. the simulated value is 0.708. the deviation of the cfd simulation is 1.43%. in the subsequent discussion, the simplified model is used for the parametric study to save simulation time. fig. 3 comparison of the average temperatures at the outer surfaces of the reforming tubes fig. 4 the simulated average mole fraction of hydrogen at the reforming tube outlets 3.2. effect of the burner on/off manner to explore the effect of the burner on/off manner on the thermal field and hydrogen yield, the burners are divided into six groups. the first group ranges from x=0 to x=6.5m, the second group ranges from x=6.5m to x=12.67m, the third group ranges from x=12.67m to x=18.84m, the fourth group ranges from x=18.84m to x=25.01m, the fifth group ranges from x=25.01m to x=31.18m, and the sixth group ranges from x=31.18m to x=37.68m. each group of burners can be controlled on or off. in the following discussion, 12 different manners of the burner on/off are discussed. x (m) t ( c ) 0 5 10 15 20 25 30 35 0 200 400 600 800 1000 experimental data (for tube outer surface) o real reformer model simplified model x (m) 5 10 15 20 25 30 0 0.2 0.4 0.6 0.8 1 y h2 advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 148 fig. 5 and 6 compare the average temperatures at the inner and outer surfaces, respectively, of the reforming tubes using different manners of the burner on/off. from the simulation results, it is seen that temperature profiles are obviously influenced by the manners of the burner on/off. when one group of burners is turned off, the outer surface temperatures of the tubes are decreased by about 94°c on average, and the inner surface temperatures are decreased by about 54°c on average. when two groups of burners are turned off, the outer surface temperatures of the tubes are decreased by about 175°c on average, and the inner surface temperatures are decreased by about 106°c on average. when three groups of burners are turned off, the outer surface temperatures of the tubes are decreased by about 251°c on average, and the inner surface temperatures are decreased by about 151°c on average. the tube temperatures reduce in regions where burners are turned off. when the central groups of burners are turned off, the tube temperatures have greater reductions. on the other hand, when the rear groups of burners are turned off, the tube temperatures have lower reductions. the results can also be observed in table 1. (a) group 1 turned off (b) group 2 turned off (c) group 3 turned off (d) group 4 turned off (e) group 5 turned off (f) group 6 turned off (g) groups 1 and 2 turned off (h) groups 3 and4 turned off (i) groups 5 and 6 turned off (j) groups 1, 2 and 3 turned off (k) groups 4, 5 and 6 turned off fig. 5 comparison of the average temperatures at the outer surfaces of the reforming tubes x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 1 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 2 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 3 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 4 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 5 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 6 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 1&2 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 3&4 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 5&6 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 1,2&3 closed x (m) t ( c ) 5 10 15 20 25 30 35 0 200 400 600 800 1000 o fully opened group 4,5&6 closed advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 149 for a reformer operating at a high temperature, the heat transfer to the catalyst tubes comes primarily from the radiation of the fired walls and the combustion gas, and secondarily from the convection of the combustion gas. in terms of radiation, the radiation intensity from the middle groups of burners is higher than that from the side groups of burners. this is because the view factors among the middle groups of burners and the reformer tubes are larger than those among the side groups of burners and the reformer tubes. in terms of convection, turning off the upstream groups of burners can alleviate convection to the downstream region and hence can reduce the tube temperature to a higher extent. on the contrary, turning off the downstream groups of burners has little influence on the convection to the upstream region and hence can reduce the tube temperature only to a lower extent. table 1 comparison of the average temperatures at the reforming tube surface operating manner of the burners the average temperature of tube outer surfaces ( o c) the average temperature of tube inner surfaces ( o c) fully opened 866 761 group 1 turned off 770 706 group 2 turned off 769 704 group 3 turned off 767 697 group 4 turned off 768 701 group 5 turned off 776 710 group 6 turned off 780 727 group 1&2 turned off 690 654 group 3&4 turned off 684 649 group 5&6 turned off 699 661 group 1,2&3 turned off 609 605 group 4,5&6 turned off 621 616 the above result can also be observed from fig. 7 which compares the average mole fractions of hydrogen at the reforming tube outlets using different manners of the burner on/off. it can be found from fig. 7 that the simulated hydrogen yield is 0.708 for the case of burners fully opened. the real value of the hydrogen yield is 0.698. the deviation of the cfd simulation is 1.43%. it is also observed that the hydrogen yields reduce in regions where burners are turned off. the more the burners are turned off, the greater the reduction in hydrogen yields will be. table 2 shows the comparison of the average mole fractions of hydrogen at the reforming tube outlets using different manners of the burner on/off. it is observed that when one group of burners is turned off, the hydrogen yields are decreased by about 4%. when two groups of burners are turned off, the hydrogen yields are decreased by about 7.9%. when three groups of burners are turned off, the hydrogen yields are decreased by about 11.4%. when the central groups of burners are turned off, the hydrogen yields have greater reductions. on the other hand, when the rear groups of burners are turned off, the hydrogen yields have lower reductions. fig. 6 comparison of the average mole fractions of hydrogen at the reforming tube outlets x (m) 5 10 15 20 25 30 35 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1yh2 fully opened group 2 closed group 1 closed group 4,5&6 closed group 1,2&3 closed group 5&6 closed group 3&4 closed group 1&2 closed group 6 closed group 5 closed group 4 closed group 3 closed advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 150 table 2 comparison of the average mole fractions of hydrogen at the reforming tube outlets operating manner average mole fractions of hydrogen at the reforming tube outlets fully opened 0.708 group 1 turned off 0.681 group 2 turned off 0.678 group 3 turned off 0.676 group 4 turned off 0.675 group 5 turned off 0.681 group 6 turned off 0.686 group 1&2 turned off 0.655 group 3&4 turned off 0.647 group 5&6 turned off 0.653 group 1,2&3 turned off 0.625 group 4,5&6 turned off 0.629 4. conclusions in this research, the effect of the burner on/off manners on an industrial-scale side-fired steam methane reformer is investigated to seek a feasible burner on/off manner that has acceptable catalyst tube temperature and hydrogen yield, so as to improve the performance and service life of a steam methane reformer. it is found that when one group of burners is turned off, the outer surface temperatures of the tubes are decreased by about 94°c in average, the inner surface temperatures are decreased by about 54°c in average, and the hydrogen yields are decreased by about 4%. when two groups of burners are turned off, the outer surface temperatures of the tubes are decreased by about 175°c in average, the inner surface temperatures are decreased by about 106°c in average, and the hydrogen yields are decreased by about 7.9%. when three groups of burners are turned off, the outer surface temperatures of the tubes are decreased by about 251°c in average, the inner surface temperatures are decreased by about 151°c in average, and the hydrogen yields are decreased by about 11.4%. the tube temperatures and the hydrogen yields reduce to a greater extent in regions where burners are turned off. when the central groups of burners are turned off, the tube temperatures and the hydrogen yields have greater reductions. on the other hand, when the rear groups of burners are turned off, the tube temperatures and the hydrogen yields have lower reductions. the result of this paper is helpful in improving the performance and service life of a steam methane reformer. funfing this research and the apc were funded by the ministry of science and technology, taiwan, under the contract most107-2221-e-150-061. acknowledgement the author is grateful to the formosa petrochemical corporation in taiwan for providing valuable data and constructive suggestions to this research during the execution of the industry-university cooperative research project under the contract 104af-86. conflicts of interest the author declares no conflict of interest. abbreviations the following abbreviations are used in this manuscript: cμ turbulence model constant (=0.09) k turbulence kinetic energy (m 2 /s 2 ) advances in technology innovation, vol. 4, no. 3, 2019, pp. 140-151 151 p pressure (n/m 2 ) t temperature (k) v velocity (m/s) xyz cartesian coordinates with origin at the centroid of the burner inlet (m) y mole fraction (%) greek symbols ε turbulence dissipation rate (m 2 /s 3 ) μ viscosity (kg/(m s)) ρ density (kg/m 3 ) τ shear stress (n/m 2 ) references [1] a. s. kimmel, “heat and mass transfer correlations for steam methane reforming in non-adiabatic, process-intensified catalytic reactors,” master thesis, marquette university, milwaukee, wi, usa, 2011. 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[18] b. f. magnussen and b. h. hjertager, “on mathematical models of turbulent combustion with special emphasis on soot formation and combustion,” proc. symp. (international) on combustion, the combustion institute, 1976. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 4___aiti#7853_in press advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 a recursive least-squares approach with memorizing factor for deriving dynamic equivalents of power systems ali karami * faculty of engineering, university of guilan, rasht, iran received 06 june 2021; received in revised form 01 august 2021; accepted 02 august 2021 doi: https://doi.org/10.46604/aiti.2021.7853 abstract in this research, a two-stage identification-based approach is proposed to obtain a two-machine equivalent (tme) system of an interconnected power system for transient stability studies. to estimate the parameters of the equivalent system, a three-phase fault is applied near and/or at the bus of a local machine in the original multimachine system. the electrical parameters of the equivalent system are calculated in the first stage by equating the active and reactive powers of the local machine in both the original and the predefined equivalent systems. the mechanical parameters are estimated in the second stage by using a recursive least-squares estimation (rlse) technique with a factor called “memorizing factor”. the approach is demonstrated on new england 10-machine 39-bus system, and its accuracy and efficiency are verified by computer simulation in matlab software. the results obtained from the tme system agree well with those obtained from the original multimachine system. keywords: network reduction, transient stability, critical clearing time, system identification 1. introduction in modern power systems, for economic and security reasons, individual power companies are connected together with tie lines to form an interconnected system. sophisticated computer programs are usually used for analysis and control of large power systems. however, it is not necessary to model the whole power network when the aim is to investigate a specific phenomenon in a small part of the system. in addition, sometimes it is very difficult to model the entire system in detail due to the lack of complete system data and/or inaccuracies in the system data [1]. to reduce the computational requirement, it is highly desirable to model only a small part of the system called “internal system” with enough accuracy, and represent the rest part of the system known as “external system”, by an equivalent model. power system equivalencing (or reduction) is generally divided into two main groups, namely static equivalencing and dynamic equivalencing. the static equivalents are employed in investigating the steady-state problems of power systems such as power flow and system planning studies. the dynamic equivalents are used in dynamical studies of power systems, including large and/or small disturbance stability problems as well as dynamic security assessment. this study is concerned with dynamic equivalencing of power systems for transient stability studies [2-3]. to reduce the computational burden of transient stability analysis, a dynamic equivalent is sometimes used for multimachine power systems [4]. however, a single-machine-infinite-bus (smib) system is usually employed for this purpose. an infinite bus is used to approximately model a large area in a power system [1]. an equivalent synchronous machine rather than an infinite bus was considered in the work of li et al. [5] to include the external system effect on the internal system. this early work was the main motivation for the present study. however, the method proposed in this study differs significantly from the method of this early work. * corresponding author. e-mail address: karami_s@guilan.ac.ir tel.: +98-13-33690274; fax: +98-13-33690271 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 the main objective of this study is to derive a two-machine equivalent (tme) system of a multimachine power system, by looking into the system from the bus of a local machine. the desired parameters of the defined equivalent system can be separated into two groups. the first group consists of the electrical parameters and the second group consists of the mechanical parameters of the tme system. to estimate the parameters of the equivalent system, a systematic two-stage identification-based approach is proposed. the electrical parameters of the equivalent system are calculated in the first stage of the approach by using an innovative and simple method. the mechanical parameters of the equivalent system are estimated in the second stage of the approach by employing a recursive least-squares estimation (rlse) technique with a factor called here “memorizing factor”. one advantage of the proposed methodology is that it is simple to understand. in addition, it is relatively easy to implement in a computer program. the effectiveness of the proposed methodology is demonstrated on the new england 10-machine 39-bus test system. the simulation results obtained are thoroughly described and discussed. the rest of the study is organized as follows. section 2 presents the literature review. section 3 represents a brief description of the rlse algorithm. the multimachine power system model and problem statement are described in section 4. section 5 presents the first stage of the proposed approach. the second stage of the proposed approach is described in section 6. the simulation results are presented in section 7. section 8 discusses the performance of the approach, and finally section 9 is devoted to the concluding remarks. 2. literature review research in power system reduction dates back to several decades ago; however, only a few references are mentioned here due to space limitation. the most well-known methods of static equivalencing are ward equivalent [6] and radial equivalent independent (rei) equivalent [7]. the ward equivalent is based on gaussian elimination technique, and the rei equivalent is indeed an extension of the ward equivalent. these methods separate a power system into three parts: internal, boundary, and external systems. the size of power system model is decreased by replacing the external system with small equivalents, whereas the internal system remains unchanged [1]. an extended ward equivalent method has been used for power system contingency analysis and static security assessment in the work of srivani et al. [8]. fu et al. [9] have proposed a hybrid method based on artificial neural network (ann) and ward-type equivalency for fast and online voltage security assessment of power systems. the proposed approach possesses good properties of ward equivalent method, and can update the parameters of the equivalent model for representing real-time topology change of the external system. lee et al. [10] have presented a static network equivalent model for korean power systems. the proposed equivalent model preserves the overall transmission network characteristics focusing on power flows among the areas in korean power systems. the already existing methods of dynamic equivalencing are modal methods, coherency methods, and measurement or simulation-based methods [11]. modal methods are based on the linearized state-space model of power systems. in the modal methods, the system equations are first linearized. then, the eigenvalues, eigenvectors, and participation factors of the linearized equations are employed to eliminate the less relevant part of the system [12]. paternina et al. [13] have proposed a strategy for developing dynamic equivalents in large-scale power system by mode preservation. using the state-space representation of power systems, other reduction techniques have also been investigated in the literature. rergis et al. [14] have proposed a general approach for constructing reduced-order models of power systems, which is based on a truncated balanced realization (tbr) linear reduction procedure. chaniotis et al. [15] have described the use of krylov subspace methods in the model reduction of power systems. zhu et al. [16] have proposed a method for large-scale power system model reduction based on the extended krylov subspace technique. ritschel et al. [17] have reported a balanced truncation model reduction approach for reducing two commonly used nonlinear and dynamical models of power grids. 236 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 in coherency methods, coherent groups of generators are first identified by using a suitable technique. then, the generators in coherent groups are represented by an equivalent generator [18]. unlike the modal methods, the coherency methods retain the physical models of the generators in an equivalent form [1, 11]. ayon et al. [19] have presented a methodology to identify coherent areas based on sliding power spectral density algorithm. miah [20] has proposed a coherency-based dynamic equivalent of a power system external area for transient stability assessment. based on the use of coherency aggregation techniques and nonlinear black-box optimization, matar [21] has developed a dynamic model reduction methodology. chittora et al. [22] have proposed a coherency based dynamic reduction technique for reducing the size of the power system network, and have tested it on a network having high voltage direct current (hvdc) transmission line. in measurement or simulation-based methods, the external system response is either measured or simulated, and system identification or curve-fitting techniques are used to determine the model parameters [11]. in the system identification based methods, a structure is first defined for the equivalent system. the measured data are then utilized to estimate the parameters of the predefined equivalent system. these methods require no knowledge of the parameters and topology (structure) of the external system. stankovic et al. [23] have proposed an ann-based strategy for the identification of the reduced-order dynamic equivalents, which uses only measurements at points where the internal and external systems are interfaced. chakrabortty et al. [24] have described an algorithm for constructing simplified interarea models of large power networks, using dynamic measurements available from phasor measurement units (pmus). ramirez et al. [25] have proposed a robust dynamic reduction approach to reduce the computational burden and time of transient stability studies. rueda et al. [26] have introduced an identification approach of the dynamic equivalent parameters, from measured operational dynamic responses associated to different disturbances. in order to increase both model accuracy and simulation speed, zhang et al. [27] have proposed a measurement-based dynamic equivalent. tong et al. [28] have proposed an artificial neuro-fuzzy inference system (anfis)-based dynamic reduction approach, in which the wide-area measurements obtained by pmus at the boundaries between the reduced system and the study system have been used to represent the external area. jiang et al. [29] have proposed a measurement-based reduction approach using system identification techniques, in which instead of a single event, multiple grid events with different patterns have been considered for estimating the parameters of the equivalent loads. almeida et al. [30] have reported the development of three software tools for the computation of dynamic equivalent models of power systems. the available techniques for power system dynamic reduction suffer from two major drawbacks: (1) they are usually time-consuming; (2) they are difficult to implement in a conventional transient stability program. for instance, as noted in the work of ayon et al. [19], the eigenvalues and eigen-matrix of the linearized system equations are usually difficult and also time-consuming to compute in the modal based methods. 3. rlse algorithm with memorizing factor assume that a dependent variable y can be evaluated by a linear function of k independent variables denoted by a row vector x = (x1, x2, …, xk) [31], then eq. (1) can be obtained: 1 1 2 2( x ) ... xφk ky f x x xφ φ φ= = + + + = (1) where φ = ���, ��, … , � � shows an unknown column vector of parameters to be estimated, and t denotes transpose. assume further that s samples of measurements y(t) and x1(t), x2(t), …, xk(t) are available at time t = 1, 2, …, s. in the least-squares (ls) technique, the aim is to fit the s samples by the linear function of eq. (1). by filling the samples into eq. (1), a set of linear equations is obtained and can be written in matrix form as: y xφ= (2) 237 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 where y denotes an s × 1 vector and x shows an s k× matrix. note that if s > k, that is for the case in which the number of samples is greater than the number of unknown parameters (i.e., overdetermined system of equations), there exists no exact solution for the k unknown parameters φ. notice that sometimes a time-varying process is encountered and it is required that the estimated parameters are updated when new observations (samples) are available. to improve the computational efficiency, rlse technique can be employed in such cases. in rlse algorithm, the previously estimated parameters are utilized to obtain new estimations for the unknown parameters. to reduce the effect of past data points on the current estimate, a forgetting factor (� ) is used in the ls criterion. the forgetting factor � is a number less than 1 (e.g., � = 0.99) and causes the recent measured data to affect the estimation more, i.e., past samples are discounted. the rlse updating procedure with a forgetting factor � can be summarized as follows [31]: p ( )x ( 1) g ( 1) [ x ( 1)p ( )x ( 1)] t t f t t t t t tλ ++ = + + + (3) φ( 1) φ( ) g( 1)[ ( 1) x( 1)φ( )]t t t y t t t+ = + + + − + (4) p( 1) [p( ) g ( 1)x ( 1)p( )] / ft t t t t λ+ = − + + (5) where g(t+1) denotes an k × 1 vector and p(t) is an k × k matrix. the matrix p is usually initialized to a very large identity matrix since no information is available in the beginning of rlse algorithm. the initial values of unknown parameters, that is φ(0), can be obtained by ls method or can be simply assumed as a vector of zeroes. in some cases, however, a time-varying process may be encountered, in which the older samples convey more information about the “true” parameter vector φ than the newly available data points. in such cases, more weights are to be given to the older samples so that the parameter values are weighted more by the older samples. to fix this problem, a factor called “memorizing factor” (��) is introduced in this study. the idea of a memorizing factor is very simple. it can be shown that if a number of more than 1 is set to the forgetting factor � used in eqs. (3)-(5), then rather than the older data points, less weight is given to the newly available samples. in other words, if the forgetting factor � is set to a value just more than 1, then compared with the older samples, the recent samples are discounted. this forgetting factor of more than 1 is called here the memorizing factor ��. notice that the greater the memorizing factor is, the less the influence of the recent data points on the estimation algorithm is. it is to be noted that the equations for rlse method with a memorizing factor �� are almost same as eqs. (3)-(5). the only difference is that the forgetting factor � is replaced by the memorizing factor �� in those equations. as will be seen later on in this study in section 7.1., the parameters of the tme system are estimated with much more accuracy if a memorizing factor (e.g., �� = 1.002) is used in the estimation algorithm. 4. power system model and problem statement consider that there is a power system consisting of n generators. in the classical model, the ith generator is represented with internal electromotive forces (emf) ��� = ��∠�� behind direct-axis transient reactance ��� � as shown in fig. 1. in fig. 1, it is assumed that a local machine i is connected to the rest of the power system. the aim is to derive a tme system for the entire power system, by looking into the system from the bus of this local machine. the loads are assumed to be represented as constant shunt admittances in the classical model of power system. the reduced (internal) admittance matrix yred (or yint) of the system is then obtained [32]. 238 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 i i e δ∠ dixj ′ip iq fig. 1 the connection of a local machine to a multimachine system letting ��� ≅ �� − �� and denoting the elements of matrix ���� as ��� = ��� + � ��, the active power and reactive power of the ith machine can be expressed as follows [32]: 2 1 ( cos sin ) n j i i i ii i j ij ij i j ij ijp e g e e g e e bδ δ = ≠ = + +∑ (6) 2 1 ( sin cos ) n j i i i ii i j ij ij i j ij ijq e b e e g e e bδ δ = ≠ = − + −∑ (7) the dynamics of the synchronous machine in classical model are governed by the following differential equations [32]: ; with 1, 2, ...,i i s d i n dt δ ω ω= − = (8) 1 [ ( )] ; with 1, 2, ...,i mi i i i s i d p p d i n dt m ω ω ω= − − − = (9) where !�� is the input mechanical power (assumed constant), "� is the rotor inertia constant, and #� is the natural damping coefficient of the ith machine. also, %& is the electrical synchronous speed. to simulate the behaviour of the actual system in the event of a large disturbance, it is necessary to numerically solve eqs. (8) and (9) in both faulted period and post fault period. having obtained the time variation of the rotor angles, the time variation of the ith machine’s active power (!�) and reactive power ('�) can be easily obtained by using eqs. (6) and (7), respectively. as can be seen in eqs. (6) and (7), both the angle of ith machine itself and the angle of remaining system machines are used in calculating !� and '� . it is also required to use the elements of the reduced matrix ���� . it is important to mention here that the information of the whole system is implicitly included in the expressions for !� and '� . in other words, !� and '� are indeed global system variables, in which the effects of both the machine itself and the rest of the network are included. suppose that a large disturbance occurs near and/or at the bus of local machine i. furthermore, assume that it is only required to approximately evaluate the transient stability of this machine with respect to the rest of the system. a dynamic equivalent model of a multimachine system, viewed from the bus of this local machine, is derived for this purpose. here, machine i represents the internal system (of interest), and the rest of the system represents the external system (to be reduced). instead of an infinite bus, the aim is to replace the external system by an equivalent machine e in series with a lossless transmission line of reactance ��, as depicted in fig. 2. fig. 2 shows the defined tme system. the equivalent machine e shown in fig. 2 is represented as a classical machine with an internal emf ��� = ��∠��, a rotor inertia constant "�, and a natural damping coefficient #� . direct-axis transient reactance of the equivalent machine e is included in the reactance of transmission line �� for the sake of simplicity. 239 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 , im id ip iq dixj ′ ejx , em ed i ie δ∠ e e e δ∠ fig. 2 the tme system of a power system to determine the parameters of the tme system, the original multimachine system is initially excited to obtain the time variations of several system variables. a three-phase fault of short duration (e.g., 50 ms) is considered at the terminal of the local machine for this purpose. the obtained time solution for the system variables is then saved. notice that the two-stage approach is performed only in post fault period. for practical application of the proposed approach, the required time variations of the system variables can be obtained from real system events. the desired parameters of the tme system can be separated into two groups. the first group consists of three electrical parameters (i.e., ��, ��, and ��); whereas the second group includes "� and #� , representing the mechanical parameters of the equivalent machine e. it is to be noted that all parameters of the local machine i are assumed to be known. 5. the first stage of the proposed approach to estimate the parameters of the tme system, a three-phase short circuit is applied near the terminal of machine i in the original multimachine system. in other words, a time-domain simulation is carried out in the original test system. from the simulation, the active and reactive powers of machine i (i.e., !� and '�), are obtained at each time-step in post fault period. the time variation of local machine angle (i.e., ��), is also obtained from the time-domain simulation. the electrical parameters of the tme system are then estimated as follows. the active and reactive powers of machine i in fig. 2 can be calculated by using the following equations [1]: sin( )i e i i e edi e e p x x δ δ= − ′ + (10) [ cos( )]i i i e i e edi e q e e x x δ δ= − − ′ + (11) the electrical parameters �� , �� , and �� can be estimated by equating the active and reactive powers of machine i, obtained from the original system, with the corresponding powers calculated from eqs. (10) and (11). in other words, those electrical parameters are calculated in such a way that if they are substituted into eqs. (10) and (11), the active and reactive powers of machine i from the tme system become equal to their corresponding powers from the original system. there are only two known variables (i.e., !� and '�) here, but three unknown parameters (i.e., ��, ��, and ��) need to be estimated. therefore, many solutions can be found for the unknown parameters. to obtain suitable solutions, the rotor angle �� of machine e is assumed to be equal to the inertia weighted average (iwa) angle of all machines in the external system. the angle ��() is defined as: 1 1 n iwa j j j it m m δ δ = ≠ = ∑ (12) where "* = ∑ "� , �-�.� , and n is the number of generators. replacing the assumed value for �� from eq. (12) into eqs. (10) and (11), one can find �� and �� by the following equations (after a little algebra): 240 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 [ cos( ) sin( )] i i e i i e i i e e p e p qδ δ δ δ = − + − (13) sin( )i e e i e di i e e x x p δ δ ′= − − (14) it should be emphasized that, at each time-step of integration, it is required to re-calculate the parameters ��, ��, and �� by repeatedly solving eqs. (12)-(14). then, the time solutions of ��, ��, and �� are saved. the values obtained for these parameters at the end of the first stage are considered their final estimated values. 6. the second stage of the proposed approach to estimate the values of "� and #� , it is assumed that the time variation of �� obtained from the first stage of the approach fits the following second-order swing equation: 2 2 e e e e me e d d m d p p dtdt δ δ+ = − (15) where !�� represents the input mechanical power and !� denotes the electrical output power of machine e. note that the defined tme system shown in fig. 2 is purely reactive; therefore, the electrical output power of machine i is completely absorbed by the equivalent machine e. the equivalent machine e acts here as a synchronous motor, and this leads to the following equations: e ip p= − (16) me mip p= − (17) substituting eqs. (16) and (17) into eq. (15), it yields: 2 2 e e e e i mi d d m d p p dtdt δ δ+ = − (18) to estimate the values of "� and #� , the following approach is used. since time variation of �� is known, time variations of the first and second time-derivatives of �� (i.e., �/� = 0��/02 and �3� = 0���/02 �) can be calculated by using suitable numerical differentiation techniques. the first and second time derivatives of eδ for the lth step in post fault period are denoted by �/��4 and �3��4 , respectively. substituting �/��4 and �3��4 into eq. (18) gives: miieeee plpldlm −=+ )()()( ... δδ (19) where !��4 shows the electrical output power of machine i, for the lth step in post fault period. notice that eq. (19) represents a discrete and algebraic equation, which is also linear with respect to "� and #� . also, eq. (19) needs to be satisfied at each time-step in post fault. therefore, at the end of the post fault, there will be a set of algebraic equations from which only two unknown parameters are to be estimated. a set of overdetermined linear algebraic equations needs to be solved here. in this study, the rlse algorithm with a memorizing factor is employed to estimate the values of "� and #� (referring to section 3). based on what mentioned so far, the main steps of the proposed method are summarized in the flowchart illustrated in fig. 3. in fig. 3, dt denotes the time-step used in the numerical integration, and t represents the total simulation time. 241 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 start perform time-domain simulation to solve swing equations f irst stag e o f th e ap p ro ach is t > t ? no yes no yes end s eco n d stag e o f th e ap p ro ach define a fault scenario in the power system set t = t0 , where t0 is a few time after the fault clearing time calculate by using eq. (12), and then setiwaδ iwae δδ = e x cite th e sy stem b y ap p ly in g a fau lt obtain and by solving eqs. (13) and (14)ee ex set t = t + dt save final estimated values of , , and ee eδ ex obtain and for the post-fault period using numerical differentiation techniques eδɺ eδɺɺ set t = t0 , where t0 is a few time after the fault clearing time obtain and by employing an rlse algorithmem ed set t = t + dt is t > t ? save final estimated values of and em ed read power system data and perform power flow analysis fig. 3 the proposed two-stage equivalencing approach 7. simulation results the proposed two-stage approach is applied to the new england 10-machine 39-bus (or the ieee 39-bus) test system. a single-line diagram of this system is shown in fig. 4. the bus and line data of this system can be found in the work of pai et al. [32]. the new england test system is called “the test system” hereafter, for the sake of simplicity. the time-domain simulations are carried out by using a computer program written by the author in matlab software. this program solves system differential equations by utilizing the fourth-order runge-kutta integration technique. however, power flow solutions for the test system are obtained by using the matpower package [33]. a time-step of 0.001 s is used in all calculations. the classical model is used and a uniform damping (i.e., 567806 = #�/"�; with i = 1, 2, …, n) of 1.0 is assumed for all machines of the test system. fig. 4 single-line diagram of the new england 39-bus test system 242 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 7.1. main results of simulation to excite the test system, a three-phase self-clearing type fault of 0.05 s duration is considered at bus 35. the simulation is carried out for 10 s in order to capture full dynamic behaviour of the test system. the location of the fault is very close to generator 2, as shown in fig. 4. for this fault, the internal system consists of generator 2 and the rest of the system represents the external system. generator 2 is the local machine here (i.e., i = 2), and the aim is to obtain a tme system from the bus of this local machine. it is to be noted that the proposed approach is performed only for post fault period. the time variation of the local machine angle (rotor angle of generator 2), obtained from the time-domain simulation in the original test system, is plotted in fig. 5 (blue curve). the time variation of the equivalent machine angle ��, obtained from the first-stage of the approach, is also illustrated in fig. 5 (red curve). the variation of the local machine active power is plotted in fig. 6. the variations of �� and �� are also illustrated in figs. 7 and 8, respectively. figs. 5, 7, and 8 clearly show that the values of ��, �� , and �� progressively settle at certain values as the time increases. the final estimates of several system variables including the rotor angle of both the local machine and the equivalent machine, along with some other system variables such as the inertia constant and damping coefficient of the local machine, are listed in table 1. the values of "� and #� are estimated in the second stage of the approach. before presenting the simulation results for "� and #� , it is worthwhile to investigate the effect of the inertia constant and damping coefficient of a machine on its dynamic behaviour (or on its rotor angle oscillations). for this purpose, consider the swing equations of a synchronous machine, e.g. eq. (18). as can be seen in eq. (18), only for the case in which the machine angle varies with time, its dynamic behaviour will be affected by its inertia constant and damping coefficient. this is due to the fact that when the machine angle remains constant, the first and second time derivatives of its angle will be equal to zero. for such a case, the machine inertia constant and damping coefficient are indeed omitted in the machine swing equations. consequently, the machine inertia constant and damping coefficient will have no effect on the rotor angle oscillations. instead, if the machine angle quickly varies with time, the machine dynamic behaviour is greatly affected by its inertia constant and damping coefficient. table 1 final estimated values for parameters of the tme system �� (rad) �� (p.u.) �� (p.u.) �� (rad) �� (p.u.) !�� (p.u.) "� (p.u.) #� (p.u.) "� (p.u.) #� (p.u.) 0.7597 0.9709 0.0051 1.1694 1.2255 6.3339 0.1607 0.1607 2.2152 0.9447 from the above discussion, it is concluded that in the beginning of post fault period, rotor angle of a synchronous machine conveys much information regarding its inertia constant and damping coefficient. therefore, instead of a forgetting factor, a memorizing factor can be used in the rlse algorithm of the second stage. as mentioned in section 3, a forgetting factor is a number less than 1; whereas a memorizing factor is a number more than 1. if a memorizing factor is used in the rlse algorithm, then compared with the recent measurements, more weights are given to the older data points. fig. 5 variations of the local and equivalent machines angles fig. 6 active power variations of the local machine after an 0.05 s fault on the original system 243 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 fig. 7 voltage magnitude variations of the equivalent machine fig. 8 variations of the transmission line reactance the time variations of "� and #� obtained by utilizing a fixed memorizing factor of 1.002 are illustrated (green curves) in figs. 9 and 10, respectively. it can be easily seen in figs. 9 and 10 that, except for the first few seconds, the values of "� and #� remain almost constant in post fault period. the time plots in figs. 9 and 10 are consistent with the time variations of the local machine and equivalent machine angles shown in fig. 5. as can be seen in fig. 5, those angles progressively settle at certain values in post fault period. however, for the first few seconds in post fault period, considerable time variations in both rotor angles can be observed. the final estimated values of "� and #� are also given in table 1. to show the advantage of memorizing factor, a fixed forgetting factor of 0.99 is also used in the second stage of the proposed approach, and then the time variations of "� and #� are obtained. the time variations obtained for "� and #� are plotted (red curves) in figs. 11 and 12, respectively. as can be seen, now there exist big fluctuations in the values of "� and #� . as a matter of fact, it is very difficult or even impossible to estimate the values of "� and #� , in this case. this proves the superiority of the memorizing factor to the forgetting factor. the time variations of "� and #� obtained by considering three different values for the memorizing factor are also obtained and plotted in figs. 9 and 10, respectively. the values chosen for the memorizing factor are 1.004, 1.01, and 1.05. in addition, the time variations of "� and #� obtained by employing ls technique are illustrated in figs. 9 and 10, respectively. for the case of ls technique, the memorizing factor is assumed to be one (i.e., ��= 1.00). as can be seen in figs. 9 and 10, depending on the value of the memorizing factor, both "� and #� vary differently over time. furthermore, for each value of the memorizing factor, both "� and #� progressively settle at some different values in the post-fault period. the final estimated values of "� and #� , for various values of the memorizing factor, are listed in table 2. fig. 9 inertia constant variations of the equivalent machine by using memorizing factor 244 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 fig. 10 damping coefficient variations of the equivalent machine by using memorizing factor fig. 11 inertia constant variations of the equivalent machine by using forgetting factor fig. 12 damping coefficient variations of the equivalent machine by using forgetting factor table 2 comparison of parameters of the tme system �� "� (p.u) #� (p.u.) cct (sec) 1.00 1.6071 1.0257 0.251 1.002 2.2152 0.9447 0.254 1.004 2.4208 0.9575 0.255 1.01 1.6417 2.0033 0.253 1.05 1.7766 2.2474 0.254 in an rlse based estimation method, a system of overdetermined equations needs to be solved (referring to section 3). for a system of overdetermined equations, there exists no solution that satisfies all the equations exactly. therefore, rlse algorithm is used to estimate the unknown parameters in an optimal sense. in ls algorithm, to obtain solutions for the unknown 245 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 parameters, each equation is weighted equally. however, in rlse algorithm, based on the value chosen for the memorizing factor (or the forgetting factor), each equation is weighted differently. therefore, for each value chosen for ��, the parameters "� and #� vary differently over time. the system of overdetermined equations obtained from eq. (19) is solved in the second stage of the proposed approach. as can be seen in eq. (19), when the first and second time derivatives of the local machine angle become zero, and at the same time, the right hand side of eq. (19) becomes zero, then no new equation is added to the set of aforementioned overdetermined system of equations. as shown in fig. 5, after a few seconds in the post-fault period, rotor angle of the equivalent machine remains unchanged. therefore, after a few seconds, the first and second time derivatives of the equivalent machine angle become zero. in addition, as shown in fig. 6, the active power of the local machine remains unchanged and reaches to its input mechanical power after a few seconds. consequently, the right hand side of eq. (19) becomes zero. in fact, the right hand side of eq. (19) represents the dependent variable y used in eq. (4). moreover, the first and second time derivatives of the equivalent machine angle are indeed the independent variables denoted by the vector x in eq. (4). referring to eq. (4), it can be concluded that when both y and x are equal to zero, the unknown vector of parameters φ is no longer updated by rlse algorithm. the vector φ consists of the mechanical parameters "� and #� of the equivalent machine e. as mentioned in section 3, the greater the memorizing factor is, the less the influence of the recent data points (or equations) on the estimation algorithm is. however, if the memorizing factor is a value very greater than 1, then almost all equations in a system of overdetermined equations are greatly discounted. this means that even those past equations that are very important for estimating the unknowns are neglected. for such a case, the parameters cannot be estimated by rlse algorithm. the curves shown in figs. 9 and 10 confirm this fact. as seen, for a memorizing factor of greater than 1.05, rlse algorithm may fail to correctly estimate the parameters "� and #� . the memorizing factor leading to the best (or optimal) estimation for the unknown parameters will depend on the system of overdetermined equations being considered. as stated before, the values of "� and #� cannot be estimated by using rlse algorithm with a forgetting factor. for the case of forgetting factor, past samples (equations) are discounted. the less the forgetting factor is, the less the influence of past equations on the estimation algorithm is. the variations of "� and #� obtained by using a fixed forgetting factor of 0.986 are also illustrated (blue curves) in figs. 10 and 11, respectively. as shown, compared with the case of a fixed forgetting factor of 0.99, there exist higher fluctuations in the values of "� and #� in this case. this is due to the fact that the less the forgetting factor, the less the effect of past equations in estimating the parameters "� and #� . it should be noted that only the values of "� and #� estimated in the second stage of the approach are dependent on the value of the memorizing factor. the parameters �� , ��, and �� are estimated in the first stage of the approach and their values do not depend on the value chosen for the memorizing factor. therefore, for all cases considered in this sub-section, the values of ��, ��, and �� are the same as those given in table 1. 7.2. results for the derived tme system in this sub-section, the derived tme system is used to replicate the behaviour of the original unreduced system by considering a three-phase fault on both systems. a three-phase self-clearing type fault of 0.1 s duration is considered at bus 2 in the original test system. the same fault is also considered at bus 2 in the derived tme system. as it is well known, relative rotor angles rather than absolute rotor angles need to be used in evaluating the stability of a power system. to obtain the relative rotor angles, it is required to take a reference rotor angle. the relative rotor angle in the tme system is easily obtained as: ��� − �� , where �� and �� are the angles of local machine 2 and equivalent machine e, respectively. for the original test system, the inertia weighted average angle (��()) of machines in the external system is used as an approximate reference rotor angle for local machine 2. the angle ��() is defined earlier in eq. (12). this relative rotor angle is denoted as: ��� − ��() . 246 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 the time variation of the relative angle ��� − ��() is shown in fig. 13 (solid blue curve). the time variation of the relative angle ��� − �� is also illustrated in fig. 13 (dotted red color). as can be seen in fig. 13, the relative rotor angle ��� − �� of the tme system closely approximates the relative rotor angle ��� − ��() of the original system. the time variations of the active and reactive powers of local machine 2 on both systems are shown in figs. 14 and 15, respectively. it can again be observed in figs. 14 and 15 that the active and reactive powers of the local machine in the tme system closely approximate the corresponding powers in the original system. to further investigate the effectiveness of the proposed method, a three-phase self-clearing type fault is considered at bus 2 on both the tme system and the original test system. the critical clearing time (cct) corresponding to this fault on both systems is then obtained. note that cct is used as an index for transient stability analysis of power systems [34]. the cct is found to be 0.254 s for the tme system, whereas the cct of 0.228 s is obtained for the original system. the values of cct on both systems are obtained via a trial-and-error approach and performing several time-domain simulations. it is obvious that the cct obtained from the tme system is near to its value in the original system, and this confirms the correctness of the proposed approach. fig. 13 relative rotor angles of local machine after an 0.1 s fault on the original and tme systems fig. 14 active power output of local machine after an 0.1 s fault on the original and tme systems fig. 15 reactive power output of local machine after an 0.1 s fault on the original and tme systems the ccts for other values of "� and #� mentioned in table 2 are also obtained in the tme system. the obtained ccts are listed in table 2. as seen in this table, the ccts obtained by using different values for the memorizing factor are almost equal to each other. this can be justified as follows. on the one hand, it is to be noted that the differences between the values of "� and #� are rather small, for various values of the memorizing factor. on the other hand, it can be noticed that the assumed fault is a severe three-phase short circuit at the terminal of the local machine. for this fault, the rest of the system, which is modelled here by an equivalent machine, has a little effect on the dynamic performance of the local machine. therefore, the values of "� and #� will only have a little impact on the cct value as well. 247 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 8. discussion the simulation results presented in section 7 shows that there exist some differences between the behaviour of the original system and that of the derived tme system. these differences may be associated with the model defined for the tme system. as shown in fig. 2, the equivalent machine e is assumed to be connected to the local machine i through a lossless transmission line. as a modification, a resistance can be included in series with the transmission line in the defined tme system. it is expected that by this modification, the tme system can approximate the behaviour of the original system with more accuracy. in this case, however, all the necessary equations mentioned in sections 5 and 6 are to be changed appropriately. in this study, the parameters of the equivalent system are obtained by using simulation data from a single fault scenario. in addition, just one system operating condition is considered. in order to improve the performance of the reduced (equivalent) model, multiple faults at different locations with different system operating conditions can be considered for estimating the parameters of the equivalent model. furthermore, the approach proposed in this study can be used in combination with a heuristic optimization-based method such as particle swarm optimization (pso) algorithm [35], to enhance the estimation accuracy of the tme system parameters. the time variations of the required system variables are obtained by considering a three-phase fault on the original test system in this study. it is important to point out that the required time variations of system variables can be acquired from an actual system disturbance event or an actual field measurement on a multimachine power system. the first three steps of the proposed approach, shown by the dotted red color in fig. 3, can be avoided if the measured (recorded) data are utilized in estimating the parameters of the tme system. furthermore, if some of the required system data are unavailable, they can be estimated by employing a suitable state estimation technique. the use of local measurements available from pmus is also an alternative way for estimating the required data [24]. nevertheless, these issues have not been addressed in the present study. the tme system is derived for the classical model of power system; however, it can be used for more accurate transient stability analysis of the local machine as well. to this end, the detailed generator model with excitation system and other control systems can be applied to the local machine in the derived tme system. the tme system can then be employed for more accurate design of power system stabilizer (pss) [1] or other controllers for the local machine. as described in section 7.1., the idea of memorizing factor is inspired by analyzing the behaviour of synchronous generators, following a three-phase fault on a multimachine power system. however, the memorizing factor based rlse algorithm can, in general, be used for solving any set of over-determined algebraic equations in which the older equations are more important than the recent ones. as a matter of fact, the dynamic equivalencing approach proposed in this study can be considered one of the applications of the memorizing factor concept. as stated in section 7.1., for a given system of overdetermined equations, there exists an optimal value for the memorizing factor that leads to the best estimation of the unknown parameters. future research can be focused on finding such an optimal value for the memorizing factor. 9. conclusions in this study, a systematic two-stage identification-based approach was presented to tackle the challenging problem of multimachine power systems dynamic equivalencing. in particular, a tme system was derived for a multimachine power system, by looking into the system from the bus of a local system machine. first, the tme system was defined, and then the desired parameters of the predefined equivalent system were estimated by using a two-stage approach. the electrical parameters of the equivalent system were obtained by utilizing a simple technique in the first stage of the approach. the mechanical parameters of the equivalent system were obtained in the second stage of the approach by employing an innovative rlse technique with a “memorizing factor”. the effectiveness of the proposed methodology was validated by using the new england 39-bus test system. 248 advances in technology innovation, vol. 6, no. 4, 2021, pp. 235-250 many simulation results were presented to show the correctness of the proposed approach. the advantages of using a memorizing factor rather than a forgetting factor were justified and also verified by many simulation results. instead of the traditional smib system, the derived tme system can be employed for transient stability analysis as well as other dynamical studies in multimachine power systems. it can also be used for more accurate design of pss or other controllers for the local machine. the memorizing factor based rlse algorithm introduced in this study is completely new, and can be applied in any system identification-based problem in which the older samples are more 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[35] a. slowik, swarm intelligence algorithms: a tutorial, boca raton: crc press, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 250 3___aiti#8492_in press_20211213 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 clustering analysis with embedding vectors: an application to real estate market delineation changro lee * department of real estate, kangwon national university, chuncheon, south korea received 16 september 2021; received in revised form 15 november 2021; accepted 16 november 2021 doi: https://doi.org/10.46604/aiti.2021.8492 abstract although clustering analysis is a popular tool in unsupervised learning, it is inefficient for the datasets dominated by categorical variables, e.g., real estate datasets. to apply clustering analysis to real estate datasets, this study proposes an entity embedding approach that transforms categorical variables into vector representations. three variants of a clustering algorithm, i.e., the clustering based on the traditional euclidean distance, the gower distance, and the embedding vectors, are applied to the land sales records to delineate the real estate market in gwacheon-si, gyeonggi province, south korea. then, the relevance of the resultant submarkets is evaluated using the root mean squared errors (rmse) obtained from a hedonic pricing model. the results show that the rmse in the embedding vector-based algorithm decreases substantially from 0.076-0.077 to 0.069. this study shows that the clustering algorithm empowered by embedding vectors outperforms the conventional algorithms, thereby enhancing the relevance of the delineated submarkets. keywords: clustering, categorical data, high-cardinality, entity embedding, market delineation 1. introduction machine learning is rapidly expanding to various applications; particularly, it has been used with great success in several applications such as computer vision, natural language processing, speech recognition, and time-series forecasting [1-4]. there are two main types of tasks within the field of machine learning: supervised and unsupervised learning. in a supervised learning framework, the algorithm learns on a labeled dataset. however, an unsupervised learning framework provides unlabeled data that the algorithm attempts to learn by extracting meaningful features without any guidance from the labels. clustering is a de facto standard tool employed in unsupervised learning and is extensively used as a technique for discovering hidden patterns in data, such as consumer groups based on demographic profiles, or real estate submarkets based on property characteristics [5]. although clustering analysis is a popular tool in unsupervised learning, it experiences difficulty when categorical variables are dominant in the dataset. clustering is the process of grouping similar data points. the similarity between data points is calculated by a distance measure, which is essentially based on the geometry and distance in the euclidean space. this concept of physical distance is well-suited to continuous data, but it is not directly applicable to categorical data. for instance, categorical data such as the color of products with each element being black, blue, and red cannot be clustered based on the distance between the three colors. several methods, such as one-hot encoding approaches and specialized distance metrics for categorical data, have been proposed in the literature to solve this problem; however, these methods have not performed satisfactorily. this study attempts to overcome this limitation by using an entity embedding approach. the entity embedding maps categorical data into metric spaces, such as the euclidean space, and thus can alleviate the discrete properties inherent in categorical data. * corresponding author. e-mail address: spatialstat@naver.com tel.: +82-33-250-6833 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 this study offers a way to enhance the clustering performance via an entity embedding approach, which has been actively used in the field of machine learning, particularly in natural language processing tasks. first, a study area is chosen to delineate the real estate market. because the real estate market is always localized, it is routine to segment the market before performing the main tasks, such as property price estimation for tax assessment [6]. second, to construct appropriate submarkets within the study area, the sales records of lots sold from 2016 to 2018 are analyzed and grouped by using several variants of a k-means clustering algorithm, respectively. an entity embedding approach is applied to handle high-cardinality variables when performing clustering analysis. finally, the predictive accuracy of different sets of submarkets created earlier is compared in the context of property valuation. the contribution of this study can be summarized as follows: (1) by adopting the framework proposed in this study, clustering algorithms can be utilized in a more efficient manner when applied to the tasks in which high-cardinality categorical data are dominant. (2) this study shows that the entity embedding approach can be used effectively in processing structured data, i.e., traditional tabular format data with rows and columns, beyond the field of unstructured data, such as images and free-form texts. (3) to the best of the authors’ knowledge, real estate markets have not been delineated with the aid of entity embedding. this study attempts to construct real estate submarkets by exploiting the entity embedding approach. the remainder of this study is organized as follows. section 2 presents the background information on clustering analysis and real estate market delineation. section 3 describes the dataset, embedding vectors, and silhouette score used to determine the optimal number of clusters. the results and interpretations are provided in section 4. a summary of this study and conclusions are presented in section 5. 2. literature review 2.1. clustering analysis and entity embedding for a clustering algorithm to group observations together, the notion of (dis)similarity among observations must be defined first. a popular dissimilarity metric, i.e., a distance metric for clustering, is the euclidean distance. however, the euclidean distance is only applicable to continuous variables and not categorical variables. when categorical variables must be used for clustering, the simplest technique to calculate the euclidean distance is to convert each element in a categorical variable to a separate binary dummy variable, and this is often called the one-hot encoding approach. although this approach is applicable to a clustering algorithm, it becomes cumbersome and inefficient for processing data when categorical variables are dominant in the dataset. alternatively, a special distance metric that can handle both continuous and categorical data types may be utilized, and a well-known such metric is the gower distance [7]. to calculate the gower distance, an appropriate distance metric for each variable type is selected and scaled to fall between 0 and 1; the euclidean distance is chosen for continuous variables, and the dice coefficient is chosen for categorical variables [8]. the dice coefficient is a well-known similarity measure for categorical data [9]. subsequently, the average value of all variables is calculated to create the final gower distance. the dice coefficient is a measure that replaces the euclidean distance metric with a matching similarity measure, which is easily applicable to categorical data. many clustering algorithms proposed for grouping categorical variables are implemented based on the modified concept of (dis)similarity, such as the dice coefficient; k-modes is one such well-known algorithm [10]. k-modes is a clustering algorithm that is specialized in classifying categorical data. in addition, useful modifications to the k-modes have been proposed recently to achieve better performance [11-12]. 31 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 however, the above approaches become very inefficient when a categorical variable is highly cardinal; that is, the number of unique values in a categorical variable is very large. to solve this problem, this study utilizes an entity embedding approach for high-cardinality categorical variables. an entity embedding technique is used for mapping categorical values to a multidimensional space with fewer dimensions than the original number of levels, where the values with similar function outputs are close to each other [13-14]. an entity embedding is usually created via neural network training in the form of embedding vectors. the entity embedding technique is widely used in the field of natural language processing because words can be viewed as the agglomeration of high-cardinality categorical variables [15-18]. according to the work of guo et al. [13], the traditional one-hot encoding of a categorical variable can be expressed as: ii x a x → δ (1) where ���� denotes the kronecker delta, and the possible values for � are the same as ��. the element is nonzero only when � � ��. based on the work of guo et al. [13], the entity embedding of �� can be expressed as: i ii a a x a x x w w→∑ =δ (2) where � represents the weight connecting the one-hot encoding layer to the embedding layer in a neural network. thus, the mapped embedding is the weight of the embedding layer and can be learned in the same way as the parameters of other neural network layers. in short, entity embedding is an approach of converting a categorical variable into a vector representation. the entity can be a word in natural language processing or a level in a categorical variable. synonyms in natural language or similar levels in a categorical variable come to have similar vector values after neural network training. fig. 1 illustrates the vector representation of entity embedding for the categorical variable “pet breeds”. a few studies utilizing entity embedding for clustering have been reported in the literature [19-20]. however, they attempted to apply the entity embedding technique to unstructured data such as imagery data, more specifically, the modified national institute of standards and technology (mnist) database. this image dataset is already pre-processed public data. this study differs from them in that the entity embedding is applied to structured data, that is, tabular format data with rows and columns, and the real estate dataset used in the study is collected from scratch and cleaned thoroughly. by adopting the entity embedding approach, especially for the data with high-cardinality categorical variables, several problems can be mitigated. first, an unrealistic amount of computational resource consumption can be avoided owing to the traditional one-hot encoding of high-cardinality variables. second, different values of categorical variables can be treated in a meaningful manner, instead of processing them completely independently from each other. third, the feature engineering step is avoided because the embeddings, by nature, can intrinsically group similar values together, thereby removing the need for domain experts to learn the relationships between values in the same categorical variable. finally, the learned embedding vectors can be visualized using a dimensionality reduction technique, providing additional insights to business practitioners. fig. 1 vector representation of entity embedding in the case of “pet breeds” 32 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 in this study, the embedding vectors are created by neural network training for high-cardinality variables and added to the existing dataset that comprises continuous variables. subsequently, to overcome the inefficiency observed in the one-hot encoding and gower distance approaches, the euclidean distance is calculated for this combined dataset. 2.2. application to real estate market delineation because buyers and sellers require different types of properties for different reasons, the real estate market is almost always divided into submarkets within those property types and sales motivations. because real estate is best characterized by its fixed location, its market delineation usually involves defining geographical boundaries [21-22]. it is routine that licensed appraisers and automated valuation models first identify the relevant submarket boundaries and then analyze the supply and demand of the proposed properties within a specific submarket. a submarket is generally associated with a group of similar properties in terms of price level and geographical location. various methods have been proposed to delineate the real estate market; examples of these methods range from well-established approaches, such as automatic zoning procedure [23-24] and spatial ‘k’luster analysis by tree edge removal algorithm [25-26], to more recently suggested methods, such as adaptive density-based spatial clustering [27-28]. most of these methods are based on a range of data-driven algorithms. the most popular algorithm for market delineation is a clustering algorithm. conversely, a clustering procedure is performed using relevant variables such as price and geographical location, following which the clustering results are evaluated considering both internal and external validity measures [29-30]. representative indices for internal validity measures include inertia and silhouette score; however, the criteria for external validity measures can vary depending on the dataset and research purpose [31-34]. this study adopts a k-means clustering algorithm to group similar observations (sales records of land in this study) into several distinct clusters, which serve as real estate submarkets for the purpose of price estimation. several studies utilized price estimation results to test market segmentation, and they proved that market delineations improved the accuracy of price estimation [35-37]. 3. embedding vectors and silhouette score 3.1. dataset this study estimates the land prices in gwacheon-si, gyeonggi province, south korea. with a population of over 13 million, gyeonggi province is the most populous province in south korea [38]. the gwacheon-si government is one of the 45 local governments in gyeonggi province, and gwacheon-si comprises both urban and rural areas. this mixed landscape is the main reason behind choosing gwacheon-si for the analysis because the heterogeneity strongly indicates the need for market segmentation. the dataset is periodically provided in a comma-separated value file format by the ministry of land, infrastructure and transport (molit) website, and have been released by the government since 2006, when the act on report on real estate transactions was enforced. these land sales records are used in a range of government administrations, such as monitoring the real estate market and tax assessment for traded properties. the records are also used in private sectors, such as for the valuation of collaterals for loan approval. the dataset comprises the lots sold in gwacheon-si from 2016 to 2018, and includes the attributes of 1,111 samples. these attributes include sales price, zone improvement plan (zip) code, lot shape, and bearing. the following variables are used for the clustering analysis: sales price, longitude and latitude (hereafter denoted as x-coordinate and y-coordinate, respectively), zip code, and zone. by employing these five variables, the lots close to each other in terms of sales price, 33 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 geographical location, and zoning are expected to group together to form a submarket. although more variables, such as lot shape (regular or irregular) and bearing, are available as inputs, they reflect the physical characteristics of individual lots, rather than neighborhood/submarket characteristics; thus, these other variables are not employed for market delineation. table 1 presents the descriptive statistics of sales samples. table 1 descriptive statistics of the 1,111 lots sold from 2016 to 2018 variable min. mean median max. sales price (krw/m 2 ) 6,938 1,539,433 379,753 22,783,807 zip code (25 levels) #13820: 245 (22.1%) #13840: 164 (14.8%) #13814: 101 (9.1%) #13813: 81 (7.3%) #13801: 75 (6.8%) #13824: 73 (6.6%) zone (7 levels) green belt: 951 (85.6%) residence 3: 103 (9.3%) residence 5: 40 (3.6%) natural & green area: 8 (0.7%) residence 2: 6 (0.5%) residence 4: 2 (0.2%) residence 1: 1 (0.1%) *note: only primary levels are presented in the zip code for readability. the median sales price of lots in gwacheon-si is 379,753 krw/m 2 , and most area is zoned for the green belt (85.6%). as shown in the table, zip code and zone are categorical variables. particularly, the zip code is highly cardinal with 25 levels. all continuous variables (sales price, x-coordinate, and y-coordinate) are scaled to have a mean of zero and a standard deviation of one before being fed into the clustering algorithm. a portion of the dataset (222 samples, 20%) is reserved to evaluate the performance of clustering algorithms. the land sales records are collected by local governments and released to the public on a monthly basis. the records can be utilized to detect overheating spots in real estate submarkets and diagnose the sustainability of the overall market. in the future, local governments need to collect and agglomerate the land sales data in a more frequent cycle, for example, on a weekly or daily basis, to adapt to a rapidly changing real estate market. in addition to optimizing the data accumulation process, data-driven algorithms based on machine learning must be developed and deployed in administration tasks ranging from disclosing the real estate market in a transparent manner to detecting fraudulent land transactions. 3.2. creating embedding vectors in the case of a high-cardinality categorical variable, such as the zip code, a one-hot encoding technique cannot be efficient in handling a large number of elements in a variable; thus, the high-cardinality categorical variable should be represented in the form of embedding vectors. the embedding vectors utilized in this study are obtained from the training results of a neural network. the aforementioned network is a fully connected layer network with the following architecture: four input variables are employed, and then two embedding layers corresponding to the categorical variables are additionally specified and added to the network. an appropriate number of dimensions has to be determined for each embedding layer, and the prediction performance for various dimension sizes is reviewed through the usual cross-validation process. the number of dimensions assigned to each categorical variable through this cross-validation process is 10 and 3 for the zip code and zone, respectively. the number of dimensions in fig. 2 is selected based on the results of the heuristic grid search. the grid search uses five-fold cross-validation to evaluate the possible combinations of values (the number of dimensions for the zip code and zone in this study), and the mean squared error (mse) between the observed land prices and the predicted prices is used as a criterion for 34 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 the evaluation. as a rule of thumb, half the number of original levels is often used as a reference number for dimensions [39]. the zip code comprises 25 levels, and the zone consists of 7 levels, as shown in fig. 2. thus, according to this rule of thumb, good candidate numbers of dimensions for the zip code and zone are 12-13 and 3-4, respectively. hence, the number of dimensions for the zip code is chosen as 10, and that for the zone is chosen as three, considering the results of the heuristic grid search and the rule of thumb together. finally, to include more parameters to capture minor data nuances, three hidden layers are added to the end of the architecture. the output layer with one neuron corresponds to the land price estimated by the neural network. the final architecture of the neural network used to obtain the embedding vectors is presented in fig. 2. the resultant embedding vectors assume the following form: a 25 × 10 matrix for the zip code and a 7 × 3 matrix for the zone. table 2 presents the embedding vectors of the zone. interpreting the learned embedding vectors always involves subjective judgments, and this study does not attempt to interpret their meanings because the primary goal is to reuse them in a subsequent clustering algorithm and achieve a performance better than those of the baseline algorithms. fig. 2 architecture of the neural network used to obtain embedding vectors table 2 embedding vectors (7 × 3 matrix) of the zone learned from neural network training zone vector 1 vector 2 vector 3 residence 1 0.21375 0.20492 0.24875 residence 2 -0.13061 -0.18887 -0.21148 residence 3 0.01262 0.01311 0.01660 residence 4 0.04791 0.04156 -0.00550 residence 5 -0.02817 -0.02647 -0.02822 natural & green area 0.00644 -0.03270 0.01594 green belt 0.01215 -0.02023 -0.00067 3.3. silhouette score when fitting a clustering algorithm such as k-means to a dataset, it is always subject to the judgment of a researcher to determine the optimal number of clusters, making the results vulnerable to criticism of subjectivity. two popular methods are used to overcome this criticism: inertia and silhouette score analysis [40-41]. the former is defined as the mean squared distance between each observation and its closest centroid. the lower the inertia is, the better the algorithm is. however, this approach suffers from a limitation: as the number of clusters increases, the inertia always becomes lower. the silhouette score is a better measure to determine the number of clusters. it measures the extent of closeness between each observation in a cluster and the observations in the neighboring clusters, providing a way to assess the number of clusters. it varies between -1 and 1. a score close to 1 indicates that the observation is far from the neighboring clusters. a score close to 0 denotes that the observation is very close to the decision boundary between two neighboring clusters, and a negative score indicates that those observations might have been assigned to a wrong cluster. this study uses the silhouette score for the analysis. 35 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 a k-means clustering algorithm is used to delineate the real estate market, and three distance metrics are utilized. first, the euclidean distance is applied for the five input variables, and categorical variables are converted to binary variables using the one-hot encoding approach. second, the gower distance, which is capable of dealing with both continuous and categorical variables, is used. third, the euclidean distance is applied again, although this time the categorical variables are converted to the continuous ones using entity embedding vectors. the continuous input variables (xand ycoordinates) are standardized before calculating the distance metrics. the k-means algorithm is implemented primarily following the clustering algorithm described in the work of kaufman et al. [41]. fig. 3 shows the respective silhouette score for k-means clustering based on the following three distance metrics: the euclidean distance, the gower distance, and the euclidean distance empowered by embedding vectors (hereafter denoted as euclidean distance 1, gower distance, and euclidean distance 2, respectively). for the categorical variables, the one-hot encoding approach is used in euclidean distance 1, and the entity embedding approach is employed in euclidean distance 2. after reviewing the visual depictions in the figure, three, four, and three clusters are chosen for each algorithm. as shown in panels (a) and (b) of fig. 3, there are points with higher scores than those of the chosen points; however, the model sparsity is also considered when choosing the optimal number of clusters. (a) euclidean distance 1 (b) gower distance (c) euclidean distance 2 fig. 3 silhouette score for each clustering algorithm 4. results 4.1. results and evaluation fig. 4 shows the market delineation results from the three k-means algorithms based on the euclidean distance 1, gower distance, and euclidean distance 2, respectively. each k-means algorithm produces three, four, and three submarkets, respectively, as shown in the panels (a), (b), and (c) in the figure. the three submarkets delineated by the k-means algorithm based on euclidean distances 1 and 2 appear to correspond approximately to northern, southern, and eastern parts of the study area. the four submarkets identified by the k-means algorithm utilizing gower distance correspond approximately to northern, middle, southern, and eastern parts of the study area. (a) euclidean distance 1 (b) gower distance (c) euclidean distance 2 fig. 4 market delineation results 36 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 the clustering results generally need to be checked using external validity measures, which can vary depending on the dataset and application areas, as explained earlier. this study uses the predictive accuracy of price estimation for the external validity measure. conversely, the delineation results are evaluated on the basis of the accuracy of the predicted price for each submarket. this approach is often used to compare the resultant submarkets delineated by clustering algorithms [42]. the price is estimated using the well-established hedonic pricing model, as follows [43-45]: i i i i i i i price zip zone year shape bearing area= + + + + + (3) where pricei denotes the sales price per square meter of lot i, zipi and zonei denote the areas to which lot i belongs, and yeari denotes the year in which lot i is sold. shapei of lot i has two levels: regular and irregular shape. bearingi of lot i comprises four levels: east, west, south, and north. finally, areai represents the size of lot i measured in square meters. then, the root-mean-square error (rmse) criterion is used for comparing the predictive accuracy, as follows [46]: ( )2 1 1 ˆ n i rmse y y n = = −∑ (4) where � denotes the price predicted by the pricing model, and y denotes the observed price. table 3 presents the predictive accuracy (rmse) for each submarket. prices in which rmse is measured are standardized to have a mean of zero and a standard deviation of one. although the marginal difference in average rmse exists between euclidean distance 1 and gower distance, the average rmse for the submarkets created by euclidean distance 2 is significantly reduced compared with the former two results. the average rmse in euclidean distance 2 is reduced by 10% approximately, from 0.076-0.077 (euclidean distance 1 and gower distance) to 0.069. this decrease could be attributed to the capability of embedding vectors used in euclidean distance 2 to extract the intrinsic relationships between levels in a categorical variable. conversely, by identifying the meaningful patterns inherent in categorical data and representing the patterns in the form of numerical vectors, the entity embedding approach can enhance the relevance of delineated submarkets. table 3 predictive accuracy for each submarket constructed by euclidean distance 1, gower distance, and euclidean distance 2, respectively rmse euclidean distance 1 gower distance euclidean distance 2 submarket 1 0.075 0.074 0.071 submarket 2 0.104 0.088 0.090 submarket 3 0.049 0.097 0.047 submarket 4 0.048 average 0.076 0.077 0.069 4.2. interpreting the resultant submarkets the average rmse for the submarkets constructed by euclidean distance 2 is the lowest. the submarkets are illustrated in fig. 5, which shows the subway line and arterial road. the clustering algorithm agglomerated the individual sales lots in gwacheon-si into three submarkets: northern, southern, and eastern submarkets. the northern submarket, which has old single-family houses, is a typical residential area with a well-established urban infrastructure. the southern submarket can be characterized by the landscapes mixed with public facilities and apartments; the public facilities include gwacheon city hall and the old central government complex. the eastern submarket mainly comprises low hills, small mountains, and sparsely located houses. in fig. 5, the area indicated by the dotted circle is classified as belonging to the southern submarket by euclidean distance 1, but is reclassified as belonging to the northern submarket when euclidean distance 2 is applied. it is the area located close to the subway line and appears to be difficult to delineate in a confident manner. consultations from the local experts, such as real 37 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 estate brokers and property appraisers, also confirm the ambiguity of the submarket membership of this area. some experts classify the dotted area as belonging to the northern submarket in gwacheon-si, while others consider that the area should belong to the southern submarket. although the topic of the submarket membership of the area is controversial even among domain experts, the data-driven clustering by euclidean distance 2 labels the area as belonging to the northern submarket in gwacheon-si, and the validity is proved by the lowest rmse obtained from a hedonic pricing model. fig. 5 submarkets constructed by euclidean distance 2 5. conclusions a clustering algorithm becomes inefficient or unstable when categorical variables are dominant in the input dataset, and the situation worsens in the case of high-cardinality categorical variables. this study attempted to enhance the performance of a clustering algorithm by employing an entity embedding approach to high-cardinality variables. gwacheon-si was chosen for the analysis, and a clustering algorithm was applied to the sales records of lots to delineate the real estate market. embedding vectors for the zip code and zone were learned from neural network training and subsequently applied to the clustering algorithm. the results showed that the submarket delineation created by the euclidean distance-based clustering algorithm equipped with embedding vectors outperformed the ones achieved by baseline models, such as the ordinary euclidean distance-based algorithm and the gower distance-based algorithm. this study offered an efficient alternative to handle these categorical variables when applying clustering algorithms: the clustering analysis results can be improved by using embedding vectors learned from neural network training, which has been utilized universally in machine learning applications that handle unstructured data. this study might promote the rapid adoption of machine-learning tools in the field of structured data. the dataset used in the study comprised 1,111 lots, but the data size may be insufficient to draw a generalizable conclusion. different results would possibly be observed if the proposed approach was applied to different datasets or different local areas. empirical experiments at a more extensive scale need to be attempted in future studies. conflicts of interest the author declares no conflict of interest. references [1] v. goyal, g. singh, o. tiwari, s. punia, and m. kumar, “intelligent skin cancer detection mobile application using convolution neural network,” journal of advanced research in dynamical and control systems, vol. 11, no. 7, pp. 253-259, 2019. 38 advances in technology innovation, vol. 7, no. 1, 2022, pp. 30-40 [2] a. aggarwal, m. alshehri, m. kumar, p. sharma, o. alfarraj, and v. deep, “principal component analysis, hidden markov model, and artificial neural network inspired techniques to recognize faces,” concurrency and computation: practice and experience, vol. 33, no. 9, e6157, may 2021. 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[46] d. wackerly, w. mendenhall, and r. l. scheaffer, mathematical statistics with applications, belmont: cengage learning, 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 40  advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 english language proofreader: si-yu lin flow separation characteristics of tandem minibus model configuration melkiyanto, nasaruddin salam*, rustan tarakka department of mechanical engineering, faculty of engineering, hasanuddin university, gowa, indonesia received 29 june 2024; received in revised form 21 november 2024; accepted 26 november 2024 doi: https://doi.org/10.46604/aiti.2024.13942 abstract this study aims to determine the characteristics of the pressure coefficient and fluid flow separation in a tandem minibus model using the fluent 6.3.26 computational method and experimental testing in a wind tunnel. pressure measurements are taken by installing 14 pressure taps connected to a manometer on a 1:40-scale minibus model. tests were conducted at five different distances between minibuses in a series configuration at seven-speed levels. the results showed that at the highest speed tested, minimal flow separation occurred at a distance ratio of l/d = 0.455, with values of cp = -0.083 in the first minibus and cp = -0.250 in the second minibus. this configuration is identified as the optimal spacing to reduce aerodynamic disturbance in the tandem minibus system. keywords: pressure coefficient, flow separation, tandem minibus configuration, computational fluid dynamics (cfd), fluent software 1. introduction in the design field, especially for vehicles and infrastructure, such as buildings and utilities, understanding the characteristics of aerodynamic flow is crucial for achieving optimal form and adequate strength, particularly when facing wind loads. wind strength becomes a crucial factor that must be considered to ensure effective and efficient object functionality. in reducing energy losses and delaying the occurrence of flow separation when fluid passes through an object, it must be a primary factor in designing both the shape and structure to generate a uniform flow that provides significant advantages to the overall performance of the object [1-2]. speed greatly affects the drag force. as the speed increases, the drag force value will increase, and the drag coefficient will decrease. the addition of deflectors can reduce fuel consumption on trucks at a speed of 100 km/h, producing a drag force of 394,768 n with a value of cd = 0.743 [2]. positioning models in tandem affect flow field characteristics and delay flow separation [3–5]. for two tandem objects with varying diameters, at re = 3900 and l/d = 1.00–1.50, the flow shows small-scale periodic reattachment [6]. tandem body configurations have been widely studied experimentally and computationally [7]. research on tandem circular cylinders reveals that at a relative roughness height of ε/d = 0.001, the strouhal number decreases by 6.25%, and drag on the upstream cylinder is reduced by 16.42% [8]. two tandem cylinders with varying reynolds numbers and spacing (l/d) were studied experimentally in a low-speed wind tunnel. at l/d = 1.8, stable shear layer reattachment was observed, enhancing the understanding of airflow around tandem cylinders [9]. for triangular and square cylinders, increasing l/d shifts the vortex toward the triangular cylinder, * corresponding author. e-mail address: nassalam.unhas@yahoo.co.id 119 advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 raising drag coefficients [10]. square cylinders of equal size, tested at reynolds numbers (re) from 1 to 200 with g = 5 (where g is the gap or spacing between the two cylinders), showed steady flow at re ≤ 35 and unsteady flow at re ≥ 40 [11]. the geometry and spacing of test objects in tandem influence fluid flow behavior [12–13]. for a rectangular cylinder, increasing aspect ratios (ar) reduces drag force by 65% upstream, with a gap spacing of (g = 4) for ar = 1 [14]. large eddy simulations of square cylinders under extreme wind pressure reveal that gap and wall vortices significantly impact extreme pressure, while corner vortices drive negative pressure near the upstream cylinder's front corner and the rear corners of both cylinders [15]. the spacing between three tandem cars significantly reduces drag and lift coefficients, with the lowest drag values corresponding to reduced lift coefficients [16]. for tandem square cylinders, vibration phenomena occur at low reynolds numbers, but a vibration control device suppresses vibrations by 98% and 97% at re = 100 [17]. using splitter plates on tandem square cylinders with g/d variations reduces resistance by 1.61% for the upstream and 7.26% for the downstream cylinder at g/d = 4 [18]. spacing and diameter of tandem airfoils greatly influence fluid flow, with experimental results showing flow separation near the trailing edge can be eliminated at 8°–10° and delayed at angles >10° [19, 20]. for tandem minibus models in four configurations, increasing speed and decreasing distance minimize drag, with the lowest drag coefficient (0.78) observed in configuration iii [12]. by varying specimen spacing and adding a disturbance body, experimental and computational analysis shows the lowest drag coefficient (1.67) and pressure coefficient (0.87) at l/d = 0.43 and d/d = 0.14 (where d/d represents the ratio of the disturbance body inlet cylinder diameter to the square cylinder diameter), with reductions of 21.6% and 14.7%, respectively [21]. cfd simulations of three tandem minibuses arranged in four configurations at 20 m/s reveal that configuration iii achieves the best pressure coefficient at l/d = 2.75 and m/d = 0.57 (where m/d represents the ratio of the distance in the y direction (m) to the diameter of the minibus model) [1]. the spacing ratio in the configuration of three cylinders arranged in tandem, with a range of l/d = 2 to 6 at 𝑅𝑒 = 150, has a significant effect on the aerodynamic drag of the test model. this study shows that the distance between cylinders in a tandem configuration greatly affects the aerodynamic characteristics, where the secondary vortices in the wake area exhibit higher energy, and the center cylinder experiences negative drag at a small distance. based on the results, the best spacing for this configuration is l/d = 2, which is the most optimal spacing compared to other l/d variations [22]. a 2d simulation studied flow past twin tandem rectangular cylinders at re = 150, varying gap ratios (l* = cylinder spacing normalized by length, 1.0–8.0) and aspect ratios (b* = width-to-height ratio, 0.3–4.0). fluid force trends categorized gaps as narrow (l* = 1.0–2.0), medium (l* = 3.0–4.0), and wide (l* = 6.0–8.0). higher b* reduced downstream cylinder (dc) force fluctuations for narrow gaps but amplified them for wide gaps. wake flow showed a 2s vortex pattern (two single vortices) for narrow gaps and shifted from synchronized c(2s) to 2s for medium and wide gaps as b* increased. proper orthogonal decomposition revealed the mechanisms behind these fluid force and vortex changes [23]. the drag coefficient, which measures the aerodynamic resistance experienced by a minibus, has been determined at 0.4 through rigorous testing and analysis, indicating the vehicle's capability to navigate the airflow with relative ease and efficiency. however, to achieve the optimal coefficient of pressure (cp) value and delay flow separation, the minibusses are arranged into a tandem formation by varying the distance between them [1, 24]. based on the theory and research results that have been presented, the distance between tandem objects in a series configuration significantly influences the pressure distribution and aerodynamic resistance experienced by each model. therefore, this study aims to determine the distance between the minibus that yields the optimal coefficient of pressure (cp). in addition, this study also seeks to characterize the flow separation on the surface of the minibus arranged in tandem series both experimentally and computationally using fluent 6.3.26 software. to answer these problems, the following sections present the results of research and analysis of the characteristics of these variables. advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 120 2. methodology the minibus as the specimen of this research employs two methods: the first method is experimental, conducted in a subsonic wind tunnel, and the second method is computational fluid dynamics (cfd) applied using the fluent 6.3.26 software to simulate the series tandem minibus model. meanwhile, the dimensions of the test object use two minibus vehicle models with the following specifications: they are made of iron with a thickness of 1 mm and a length of 121 mm. the width of the minibus is 45 mm, the height is 43 mm, and the hydraulic diameter (d) has a value of 44 mm, with an actual scale ratio of 1: 40. the two minibuses are arranged in a tandem series configuration with five levels of distance variation (l) of 10, 20, 30, 40, and 50 mm. seven levels of variation in the same upstream speed starting from (u) = 8, 10, 12, 14, 16, 18, and 20 m/s. for this reason, in this study, where fig. 1 describes the position of the first and second minibus arranged in a series tandem configuration, which is given a treatment of variation in the ratio of distance and diameter (l/d) of five levels of variation, namely at l/d = 0.227, 0.455, 0.682, 0.909, and 1.136. fig. 1 the positions of the first minibus and the second minibus in a series tandem model furthermore, fig. 2 illustrates the position of each pressure tap installed around the body of the first minibus and the second minibus arranged in a tandem series configuration. each minibus is fitted with 14 pressure taps: 3 pressure taps at the front, 3 at the rear, 4 on the left side, and 4 on the right side of the minibus body. these taps are useful for measuring the pressure distribution around the test model body connected directly to the manometer. fig. 2 position of each pressure tap for the series configuration the reynolds number equation provided is used to analyze and determine the flow characteristics passing through the tandem minibus configuration and is expressed as u d re   = (1) in eq. (1), the variables and parameters involved include the upstream velocity (u), minibus model hydraulic diameter (d), and fluid kinematic viscosity (υ). to calculate the diameter of the minibus, the following equation can be used: 4 a d p  = (2) the variables and parameters presented in eq. (2) include frontal cross-sectional area (a) and frontal perimeter (p). 121 advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 table 1 outlines the boundary conditions applied in the computational method using the fluent 6.3.26 application for the aerodynamic analysis of the tandem minibus. the working fluid in this simulation is air with a density of 1.164 kg/m³ and a viscosity of 0.00001872 kg/m.s. the boundary conditions include a velocity inlet to regulate the flow velocity at the inlet, a pressure outlet at the exit as a pressure limit, and the surface of the minibus and the simulation domain configured as a wall. simulations were conducted with airflow velocity variations of 8, 10, 12, 14, 16, 18, and 20 m/s to evaluate the effect of velocity changes on the flow characteristics around the tandem minibus. table 1 boundary conditions for computational methods on tandem-aisled minibus fluid (air) properties density 1.164 kg/m3 viscosity 0.00001872 kg/m.s tandem minibus boundary conditions tandem minibus wall inlet velocity inlet outlet pressure outlet wall wall upstream velocity 8, 10, 12, 14, 16, 18, and 20 m/s the pressure coefficient (cp) and can be obtained by sm p sm tm h h c h h − = − (3) eq. (3) involves variables and parameters such as the fluid flow (air) head at the test point on the object's surface (h), the static fluid flow (air) head in the manometer (hsm), and the stagnation fluid flow (air) head in the manometer (htm). meanwhile, the pressure conditions at room temperature in the research setting become the determining factor of the kinematic viscosity value of the fluid (air). 3. result and discussion from this research, the results are obtained through both the experimental approach and the computational approach using the cfd program the applied fluid flow velocity was 8, 10, 12, 14, 16, 18, and 20 m/s for each distance to diameter ratio (l/d) of 0.227, 0.455, 0.682, 0.909, and 1.136. the data of this research is presented in the form of graph contours, including pressure contours, velocity contours, and vorticity contours. the attached graphs exhibit the relationship of the pressure coefficient (cp) with each position of the pressure tap (tp) around the minibus for each level of variation of the ratio l/d = 0.227, 0.455, 0.682, 0.909, and 1.136 are presented in fig. 3. for figs. 4-8, the attached graphs display the relationship of cp with each position of tp around the minibus at seven levels of reynolds number variations (21891, 27363, 32836, 38308, 43781, 49254, and 54726). meanwhile, the results of computational data using fluent 6.3.26 include pressure contours, velocity contours, and vorticity contours at l/d = 0.227, 0.455, 0.682, 0.909, and 1.136 for a speed of 20 m/s (re = 54726) are shown in figs. 9-13. the variation of speed and l/d ratio applied to the tandem minibus can affect the change of pressure coefficient at each point around the tandem minibus. this can delay the occurrence of airflow separation on the rear side of the minibus or prevent early flow separation on the tandem minibus surface. when the tandem minibus is at the closest l/d ratio (0.227), the cp value increases, but when the l/d ratio is increased to 0.455, the cp value stabilizes for both minibuses. further increasing the l/d ratio variation from 0.682 to 1.136 allows the rear-positioned minibus to experience free airflow, reducing the pressure influence of minibus 1. advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 122 fig. 3 pressure coefficient (cp) against pressure tap (tp) for minibus 1 and 2 at condition re = 54726 fig. 3 demonstrates the results of cp against each tp position around the minibus at five levels of variation l/d = 0.227, 0.455, 0.682, 0.909, and 1.136 for re = 54726, showing a high-intensity cp increase occurs at tp 0, which is at the front position of minibus 1 and tp 14, at the front position of minibus 2. then, there is a drastic decrease in cp at tp 2 tp 12 minibus 1 and tp 16 tp 26 minibus 2 at all levels of l/d variation. this indicates that the l/d variation affects the cp value at each point on the minibus wall surface, but at a ratio of l/d = 0.227, the flow separation in tandemly arranged minibus is more effectively delayed. fig. 4 pressure coefficient (cp) against pressure tap (tp) for minibus 1 and 2 at condition l/d = 0.227 fig. 4 presents the cp results at each tp position around the tandem minibus at seven reynolds number variations (21891, 27363, 32836, 38308, 43781, 49254, and 54726) for l/d = 0.227. in this graph, it can be observed that a significant cp increase at tp 0 (front of minibus 1) and tp 14 (front of minibus 2). after that, there is a drastic decrease in cp values in the range of tp 2 to 12 in minibus 1, as well as at tp 16 to 26 in minibus 2 across all reynolds numbers. this denotes that reynolds affects cp, especially in the front and rear areas of the vehicle. however, at higher reynolds numbers, the changes in pressure distribution tend to be smaller. fig. 5 illustrates the cp results at each tp position around the tandem minibus at seven levels of reynolds number variation (21891, 27363, 32836, 38308, 43781, 49254, and 54726) for a ratio of l/d = 0.455. in this graph, it can be seen that a significant increase in cp occurs at tp 0, and tp 14. following this, there is a drastic decrease in the cp value from tp 2 to tp 12 in the first minibus, as well as at tp 16 to tp 26 in the second minibus, for all variations of reynolds number. this demonstrates that 123 advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 the reynolds number influences cp, particularly in the front and rear areas of the vehicle, but at higher reynolds numbers, the changes in pressure distribution tend to lessen. fig. 5 pressure coefficient (cp) against pressure tap (tp) for minibus 1 and 2 at condition l/d = 0.455 fig. 6 pressure coefficient (cp) against pressure tap (tp) for minibus 1 and 2 at condition l/d = 0.682 fig. 6 shows the cp distribution at each tp position around the tandem minibus for seven variations of reynolds number (21891, 27363, 32836, 38308, 43781, 49254, and 54726) with a ratio of l/d = 0.455. this graph shows a significant increase in cp occurs at tp 0, and tp 14. thereafter, the cp values decrease significantly in the range of tp 2 to tp 12 for the first minibus, as well as in the range of tp 16 to tp 26 for the second minibus, applicable to all levels of reynolds number variation. this indicates that the reynolds number affects the cp distribution, especially in the front and rear areas of the vehicle, but at higher reynolds numbers, the change in pressure distribution is relatively smaller. fig. 7 displays the cp distribution at each tp position around the tandemly arranged minibus at seven different reynolds number levels (21891, 27363, 32836, 38308, 43781, 49254, and 54726) for a ratio of l/d = 0.455. in this graph, it can be seen that a significant increase in cp occurs at tp 0, and tp 14. after that, the cp value decreases sharply from tp 2 to tp 12 for the first minibus, and from tp 16 to tp 26 for the second minibus, for all levels of reynolds number variation. this shows that the reynolds number affects the cp distribution, especially in the front and rear areas of the vehicle, whereas the changes in pressure distribution tend to be smaller at higher reynolds numbers. advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 124 fig. 7 pressure coefficient (cp) against pressure tap (tp) for minibus 1 and 2 at condition l/d = 0.909 fig. 8 pressure coefficient (cp) against pressure tap (tp) for minibus 1 and 2 at condition l/d = 1.136 meanwhile, fig. 8 presents the cp distribution at each tp point of the tandemly arranged minibus at seven variations of reynolds numbers (21891, 27363, 32836, 38308, 43781, 49254, and 54726) with a ratio of l/d = 0.455. from this graph, it can be seen that a significant increase in cp occurs at tp 0, and tp 14. thereafter, the cp value drops dramatically between tp 2 and tp 12 for the first minibus, and between tp 16 and tp 26 for the second minibus, with this pattern prevailing for all levels of reynolds number variation. these findings indicate that the reynolds number affects the coefficient of pressure (cp) on all sides of the minibus, but at higher reynolds values, the changes in pressure distribution tend to lessen. table 2 presents the minimum pressure coefficient (cp) values at tp 7 for minibus 1 and tp 21 for minibus 2 with l/d = 0.227, 0.455, 0.682, 0.909, and 1.136, respectively. the results from table 1 display that the minimum pressure coefficient that occurs in the tandem minibus series configuration is at l/d = 0.455, with a value of cp = -0.083 for minibus 1 and cp = -0.250 for minibus 2. these minimum pressure coefficients are observed at tp 7 for minibus 1 and tp 21 for minibus 2 when the flow velocity is u = 20 m/s (re = 54726). based on the attached figs. 3-8, in general, the same characteristic pattern is produced in each variation of l/d ratio and reynolds number (re) namely, flow separation consistently occurs between tp 2 and tp 13 for minibus 1 and between tp 16 and tp 26 for minibus 2. however, more delayed flow separation occurs in tandemly arranged minibuses at a variation ratio of l/d = 0.227. this indicates that at this ratio, the fluid flow conditions are more stable and controlled. 125 advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 table 2 minimum pressure coefficient for tandem minibus at tp 7 and tp 21 l/d minibus 1 (m1) minibus 2 (m2) 0.227 -0.120 -0.260 0.455 -0.083 -0.250 0.682 -0.127 -0.265 0.909 -0.133 -0.267 1.136 -0.127 -0.270 figs. 9-13 display the simulation results from the top perspective of the tandem minibus model, with five levels of variation (l/d = 0.227, 0.455, 0.692, 0.909, and 1.136) at a constant flow velocity of 20 m/s (re = 54726) for each contour. fig. 9 displays the results for the (a) pressure contours, (b) velocity magnitude contours, and (c) vorticity contours. these results were obtained using the computational method with the fluent 6.3.26 application. these computational simulation results were validated with the experimental data listed in fig. 3, which illustrates the occurrence of the flow separation phenomenon in the tandem minibus model. (a) pressure contour (b) velocity contour (c) vorticity contour fig. 9 the cfd simulation results at a flow rate of u = 20 m/s (re = 54726), with l/d = 0.277 arranged in tandem advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 126 fig. 9(a) presents a tandem minibus model with increasing pressure at the front of minibus 1, which then experiences a significant decrease in the left, right, and rear sides of minibus 1. for minibus 2, the pressure at the front remains balanced without significant fluctuations, indicating stability in these conditions. a decrease in pressure is also observed at the left, right, and rear sides of minibus 2. fig. 9(b) shows that there is a slight flow separation phenomenon that can be observed between the positions of minibus 1 and 2. fig. 9(c) also indicates the presence of small eddies or vortices in the rear area of both minibuses. (a) pressure contour (b) velocity contour (c) vorticity contour fig. 10 the cfd simulation results at a flow rate of u = 20 m/s (re = 54726), with l/d = 0.455 arranged in tandem fig. 10(a) displays conditions for increased pressure in the front of minibus 1, after which it experiences a significant decrease in the left, right, and rear sections of minibus 1. at the same time, for minibus 2, the pressure at the front displays the balance results. there is no significant fluctuation since the front is stable. subsequently, the left, right, and rear sections of minibus 2 also experienced a significant decrease in pressure. meanwhile, fig. 10 (b) shows the phenomenon of small flow separation in both minibuses. in the case of fig. 10(c) indicates the presence of a relatively small vorticity located right at the rear of both minibuses. 127 advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 furthermore, in fig. 11(a), there is a significant increase in pressure at the front of minibus 1, followed by a significant decrease in pressure in the left, right, and rear areas of the minibus. meanwhile, for minibus 2, the front exhibits stability or no significant fluctuations, but there is a considerable decrease in pressure in the left, right, and rear areas of minibus 2. fig. 11(b) depicts a small-scale phenomenon of flow separation between the two minibuses. additionally, in fig. 11(c), this also leads to a significant vorticity phenomenon at the rear of both minibuses when compared to the phenomenon observed in fig. 10(c). (a) pressure contour (b) velocity contour (c) vorticity contour fig. 11 the cfd simulation results at a flow rate of u = 20 m/s (re = 54726), with l/d = 0.682 arranged in tandem fig. 12(a) illustrates an increase in pressure at the front of minibus 1 followed by a significant decrease in pressure at its left, right, and rear sides, while on the other hand, minibus 2 depicts stability at its front with minimal significant fluctuations, while its left, right, and rear sides experience a considerable decrease in pressure. on the other hand, fig. 12(b) illustrates a phenomenon where small-scale separated flow occurs between the two minibusses. in the context of fig. 12(c), it can be observed that there is a significant vorticity phenomenon at the rear of both minibuses, indicating a substantial disturbance at the rear of both test objects. advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 128 (a) pressure contour (b) velocity contour (c) vorticity contour fig. 12 the cfd simulation results at a flow rate of u = 20 m/s (re = 54726), with l/d = 0.909 arranged in tandem (a) pressure contour fig. 13 the cfd simulation results at a flow rate of u = 20 m/s (re = 54726), with l/d = 1.136 arranged in tandem 129 advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 (b) velocity contour (c) vorticity contour fig. 13 the cfd simulation results at a flow rate of u = 20 m/s (re = 54726), with l/d = 1.136 arranged in tandem(continued) next, fig. 13(a) describes that there is an increase in pressure on the front of minibus 1, while the front of minibus 2 appears to be stable with no significant fluctuation. this is followed by a fairly intense pressure drop fluctuation caused by both the left and right minibus, accompanied by the ensuing high-pressure drop at the rear. meanwhile, fig. 13(b) illustrates a phenomenon where separate flows occur on a small scale between the two test objects. fig. 13(c) displays the phenomenon of significant vorticity occurring at the rear of both minibuses. 4. conclusions this study analyzes the aerodynamic characteristics of two minibuses arranged in a tandem configuration using experimental and computational methods. the tests were conducted in a subsonic wind tunnel with a 1:40-scale minibus model equipped with 14 pressure taps. experimental data were compared with numerical simulation results using fluent 6.3.26 software to obtain pressure, velocity, and vorticity distributions. the main focus of the study was to identify the effects of varying the spacing between minibus on flow separation and pressure distribution. (1) the optimum spacing in a tandem configuration was found at l/d = 0.455, where smaller flow separation occurs, resulting in a more stable pressure distribution around the minibus. this suggests that choosing the right spacing can minimize aerodynamic drag, ultimately improving the airflow efficiency around the minibus. (2) better aerodynamic efficiency improves minibus performance, especially in terms of stability and potential reductions in energy consumption. this configuration can reduce drag and improve minibus fuel efficiency under real conditions by suppressing flow separation and dominant negative cp values. this study also shows the importance of exploring other parameters, such as minibus shape, model scale, and crosswind effects, to better understand aerodynamic performance in real-world applications. advances in technology innovation, vol. 10, no. 2, 2025, pp. 118-131 130 nomenclature a frontal cross-sectional area cp pressure coefficient d hydraulic diameter h head of airflow in the manometer hsm head of static airflow in the manometer htm head of a stagnation airflow in the manometer l tandem minibus distance p frontal perimeter re reynolds number u inlet airspeed to the wind tunnel ρ air density υ the kinematic velocity of air conflicts of interest the authors declare no conflict of interest. references [1] n. salam, r. tarakka, jalaluddin, m. a. jimran, and m. ihsan, “flow separation in four configurations of three tandem minibus models,” international journal of mechanical engineering and robotics research, vol. 10. no. 5, pp. 236-247, 2021. 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[24] y. a. cengel and j. m. cimbala, fluid mechanics fundamentals and applications, 3rd ed., new york: mcgraw-hill companies, 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 1___aiti#9592___229-241 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 measurement accuracy of ultrasound viscoelastic creep imaging in measuring the viscoelastic properties of heterogeneous materials che-yu lin * , yi-cheng chen, chin pok pang, tung-han yang institute of applied mechanics, college of engineering, national taiwan university, taipei, taiwan received 28 february 2022; received in revised form 06 may 2022; accepted 07 may 2022 doi: https://doi.org/10.46604/aiti.2022.9592 abstract ultrasound viscoelastic creep imaging (uvci) is a newly developed technology aiming to measure the viscoelastic properties of materials. the purpose of this study is to investigate the accuracy of uvci in measuring the viscoelastic properties of heterogeneous materials that mimic pathological lesions and normal tissues. the finite element simulation is used to investigate the measurement accuracy of uvci on three material models, including a homogeneous material, a single-inclusion phantom, and a three-layer structure. the measurement accuracy for a viscoelastic property is determined by the difference between the simulated measurement result of that viscoelastic property and its true value defined during the simulation process. the results show that uvci in general cannot accurately measure the true values of the viscoelastic properties of a heterogeneous material, demonstrating the need to further improve the theories and technologies relevant to uvci to improve its measurement accuracy on tissue-like heterogeneous materials. keywords: elastography, elasticity, stiffness, stress relaxation, viscoelasticity 1. introduction ultrasound elastography, or called ultrasound elasticity imaging, is an advanced ultrasound-imaging-based technology that aims to noninvasively measure the mechanical properties of tissues [1-3]. the initial description of ultrasound elastography appeared in the early 1990s [4]. subsequently, the development of its relevant technologies and the feasibility studies for investigating its application potential has become one of the most popular research topics [5]. soon, ultrasound elastography has developed into a real-time clinical tool capable of diagnosing pathologies of tissues based on serving the parameters relevant to the stiffness of tissues as biomarkers [6-10]. this rationale for diagnosis is based on the fact that pathological processes may cause changes in the stiffness of tissues [9, 11-13]. despite the fact that ultrasound elastography has been widely applied in research to measure the stiffness of various tissues such as breast, liver, and musculoskeletal tissues, its clinical usefulness has not been assured. it is because, in part, the stiffness alone (the single metric that ultrasound elastography measures) could not be sufficient to completely describe the mechanical condition of tissues [14-15]. the stiffness is just a single parameter that describes the combined effect of mechanical properties. however, biological tissues are all viscoelastic, meaning that tissues possess both fluid-like and solid-like properties [16-18]. changes in the status of tissues due to pathologies lead to changes in both fluid-like and solid-like properties, resulting in changes in viscoelastic properties of tissues [15, 19-20]. in order to more completely evaluate the health status of tissues in terms of their mechanical properties, it is important to measure the viscoelastic properties rather than just the stiffness alone. * corresponding author. e-mail address: cheyu@ntu.edu.tw tel.: +886-2-33665653; fax: +886-2-23639290 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 fig. 1 illustration of the ultrasound viscoelastic creep imaging system in recent years, a research group [21-24] has proposed a novel ultrasound imaging technology called ultrasound viscoelastic creep imaging (uvci) aiming to noninvasively measure the viscoelastic properties of tissues, as illustrated in fig. 1. compared to ultrasound elastography that can only measure the stiffness, uvci can measure several parameters relevant to the viscoelastic properties of tissues, and therefore may have a greater potential to be a useful clinical tool to provide a more thorough evaluation of the mechanical condition and health statue of tissues. compared to traditional mechanical testing methods such as uniaxial tensile and compressive testings, multiaxial testing, and shear rheometer testing that can only measure the bulk properties of materials, uvci can quantitatively measure the internal spatial distribution of the viscoelastic properties of materials. in addition, compared to traditional mechanical testing systems, an ultrasound-imaging-based technology such as uvci should be portable, lighter, and easier to apply for in vivo studies on human tissues. in order to further understand how useful uvci can be applied in the field of clinical diagnosis, this study intends to quantitatively investigate the accuracy of uvci in measuring the viscoelastic properties of tissue-like heterogeneous materials. the main study question is: can uvci accurately measure the true viscoelastic properties of each portion in a heterogeneous material? for this study purpose, finite element simulation is utilized in the present study, and it is believed that computer simulation is the most appropriate methodology that can fulfill this study purpose because the theoretical parameters defined during the simulation process can be served as the golden standard to be compared with the results obtained from the simulation for verifying the measurement accuracy of uvci. 2. literature review in literature, uvci has been used to measure the viscoelastic properties of homogeneous and heterogeneous tissue-like phantoms, as well as benign and malignant human breast lesions in vivo [21-24]. these studies have consistently concluded that uvci can provide accurate measurements of the viscoelastic properties of these samples. however, by observing some of the color images illustrated in these studies that display the spatial distribution of the viscoelastic properties (for example, fig. 6 in [22], figs. 2 and 3 in [24]), it can be observed that the contrast of the image is not high. it means that, the color of an area in the image suspected as where the lesion locates is similar to the color of many other areas; therefore, the lesion cannot be clearly identified in the image and cannot be specifically distinguished from many other areas in the image. fig. 2 shows an example. the problem mentioned above could be due to the imperfect function of uvci, or due to the heterogeneous nature of in vivo tissues. however it may be, the lack of high contrast in the image may decrease the success rate of clearly identifying pathological lesions, and decrease the accuracy to measure the true viscoelastic properties of tissues. consequently, the esteem of uvci for clinical and biomedical applications could be hampered. hence, even though some exciting preliminary results have been reported in literature [21-24], it is still unclear whether or not uvci can be successfully applied to heterogeneous materials and structures such as pathological lesions and tumors in a tissue. this issue raises the motivation of the present study to investigate the accuracy of uvci in measuring the viscoelastic properties of tissue-like heterogeneous materials, in order to understand the potential of uvci as a tool to be applied in the field of clinical diagnosis. 230 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 (a) b-mode ultrasound image (b) spatial distribution map of mechanical properties fig. 2 an example showing a spatial distribution map of the viscoelastic properties with low contrast 3. materials and methods 3.1. introduction to ultrasound viscoelastic creep imaging the principle of uvci is similar to that of mechanical creep testing, in which a constant load is applied to the sample for a period of time to induce the viscoelastic creep behavior. by recording the creep data using ultrasound imaging and then analyzing (i.e., curvefitting) the creep data using a viscoelastic mathematical model, the viscoelastic properties of the sample can be quantitatively evaluated. in uvci, the ultrasound transducer is used to exert a uniform compression force on the sample’s top surface. the automatic motion control of the transducer is achieved using a linear motor. the magnitude of compression force, measured using the load cells embedded between the two plates attached to the transducer, is instantly monitored and controlled by a feedback controller. the axial strain of each material point within the sample is measured using ultrasound imaging. for the measurement, the transducer is continuously moved downward by a consistent loading rate to compress the sample, until the magnitude of compression force attains a prescribed maximal value. the load is applied using an extremely rapid loading rate (the duration from the beginning to maximal compression force is 1/6 s), such that the load can be approximated as a step load. once the prescribed maximal compression force is attained, the compression force is thereupon kept constant for a time period. since the compression force on the sample’s top surface is constant, the axial stress of each material point within the sample should also be constant. hence, according to the principle of viscoelasticity, during the time period when the stress of each material point within the sample is constant, all material points within the sample exhibit creep (fig. 3). the strain-time relationship during creep (i.e., the creep curve) of each material point can be described by the following equation derived using the standard linear solid model maxwell form (fig. 3) based on the assumption that the load is a step load [18]: 0 ( ) (1 )c t t e g e − = − ⋅ τσ ε (1) where ���� is the axial strain as a function of time. � is the modulus of elasticity. � is a parameter relevant to the viscoelastic properties [18]. �� is equal to � /�1 � ��, where �� is the retardation time constant while � is the relaxation time constant, and these two parameters are relevant to the viscoelastic properties. � is the axial stress at the beginning of creep (i.e., the axial stress at � � 0) as well as the constant axial stress during creep. in the present study, � is set as the magnitude of compression force on the sample’s top surface. the viscoelastic properties of each material point are quantitatively evaluated through curvefitting the creep curve of each material point by eq. (1). the viscoelastic properties of all material points are then used to construct the 2d spatial distribution maps of the viscoelastic properties of the entire sample. 231 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 fig. 3 evaluation of the viscoelastic properties using the standard linear solid model to curvefit the creep curve 3.2. finite element simulation and data analysis in the present study, the accuracy of uvci in measuring the viscoelastic properties of heterogeneous materials is studied by finite element simulation. the package abaqus/cae 2021 (dassault systems simulia corp., johnson, ri, usa) is used to perform the finite element simulation. the finite element models used in the present study are all 3d axisymmetric cylindrical models. there are three material models investigated in the present study, and their dimensions are described as follows: (1) homogeneous material (fig. 4): the thickness and radius of the model are 50 and 25 mm, respectively. the model meshes with quadrilateral elements of dimensions 0.5 � 0.5 mm. the element number and the node number in the model are 5000 and 5284 nodes respectively. (2) single-inclusion phantom (fig. 4): the thickness of the entire model is 50 mm while its radius is 25 mm. the thickness of the inclusion is 15 mm while its radius is 7.5 mm. the model meshes with quadrilateral elements of dimensions 0.5 � 0.5 mm. the element number and the node number in the model are 5000 and 5284 nodes respectively. (3) three-layer structure (fig. 4): the thickness of the entire model is 30 mm while its radius is 25 mm. the model has three layers with consistent dimensions. the thickness of each layer is 10 mm while its radius is 25 mm. the model meshes with quadrilateral elements of dimensions 0.5 � 0.5 mm. the element number and the node number in the model are 3000 and 3213 nodes respectively. (a) homogeneous material (b) single-inclusion phantom (c) three-layer structure fig. 4 illustration of three material models investigated in the present study inclusion background material top layer middle layer bottom layer 232 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 the settings of the boundary conditions and mechanical properties for all three material models are the same, described as follows. the boundary conditions are that, the model’s bottom is constrained along the axial direction, and its top and sides are not constrained. the material that constructs the model is assumed to be linearly viscoelastic, isotropic, and incompressible. the mechanical properties of the material are defined by four parameters: the modulus of elasticity (�), the poisson’s ratio, � and �. � and � are two parameters relevant to the viscoelastic properties, defined using the one-branch prony series of the dimensionless relaxation modulus. ( ) 1 (1 )r t r g t g e − = − − τ (2) where � and � are the same parameters in eq. (1); that is, � is the relaxation time constant while � is a parameter relevant to the viscoelastic properties [18]. � is set as a constant of 0.8 in the present study. since the material is assumed to be incompressible, the poisson’s ratio is set as 0.495 (the maximal poisson’s ratio that can be set in abaqus). in the simulation, a uniform and constant compression pressure (1000 pa) is applied on the model’s top surface. the load is applied using an extremely rapid loading rate (the duration from the beginning to maximal compression force is 1/6 s). once the prescribed maximal compression pressure is attained, the compression pressure is thereupon kept constant for a time period (set as 1000 s in the present study), during which the creep behavior occurrs. that is, the strain of each element of the model increases with time until a constant strain is attained. the strain-time data (i.e., the creep curve) of each element is recorded for further analysis. then, a matlab-based b-mode ultrasound imaging simulation tool [25-27] is used to convert each element’s raw strain-time data to the simulated strain-time data obtained from b-mode ultrasound imaging system with the characteristics of pulse-echo ultrasound signals. fig. 5 is an example that shows the comparison between an original spatial distribution map of a viscoelastic property of the homogeneous material (fig. 5(a)) and the corresponding map with simulated pulse-echo ultrasound signals of b-mode ultrasound imaging (fig. 5(b)). the randomly scattered dots that can be observed in fig. 5(b) reflect the simulated pulse-echo ultrasound signals of b-mode ultrasound imaging. the creep curve of each element is curvefitted using eq. (1) for obtaining the two parameters relevant to the viscoelastic properties (� and � ) of each element. please note that, according to eq. (1), there are actually three viscoelastic parameters, i.e., �, � , and �, but only � and � are considered in the data analysis since � is set as a constant in the simulation. the curve fitting is performed using matlab (r2022a; mathworks, natick ma) [30]. the values of � and � of each element yielded by the curve fitting are regarded as the viscoelastic properties of each element measured by uvci obtained from the simulation. once the viscoelastic properties of all elements are obtained, the 2d spatial distribution map for each viscoelastic property (� and � ) of the material model can be developed. however, because of the axisymmetric nature of the finite element model, the currently-obtained map is just half of that obtained from uvci in reality. hence, the current map is combined with its reflection to obtain the full map that should be obtained in a real uvci measurement. (a) original map (b) map with simulated ultrasound signals fig. 5 comparison between the original map and the corresponding map with simulated ultrasound signals 233 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 the settings of the theoretical viscoelastic properties during the simulation in abaqus for each material model are described as follows: (1) homogeneous material: � is set as 10000 pa, while � is set as 1 s. (2) single-inclusion phantom: � of the background material is fixed as 10000 pa, while � of the background material is fixed as 1 s. � of the inclusion is 1000, 5000, 10000, and 20000 pa respectively, while � of the inclusion is 0.5, 1, and 2 s respectively. hence, eleven simulation tests in total will be conducted, excluding the case in which the material is homogeneous with e and � of the inclusion are 10000 pa and 1 s respectively. (3) three-layer structure: � of the top and bottom layers is fixed as 10000 pa, while � of the top and bottom layers is fixed as 1 s. � of the middle layer is 1000, 5000, 10000, and 20000 pa respectively, while � of the middle layer is 0.5, 1, and 2 s respectively. hence, eleven simulation tests in total will be conducted, excluding the case in which the material is homogeneous with � and � of the middle layer are 10000 pa and 1 s respectively. the measurement accuracy of uvci for a viscoelastic property (� or � ) is determined by the difference between the simulation value (i.e., the value of that viscoelastic property obtained from the simulation) and the theoretical value (i.e., the value of that viscoelastic property defined in abaqus). the smaller the difference between them, the higher the measurement accuracy. this difference is quantified using the following equation: simulation value theoretical value error (%) theoretical value − = (3) if the error is smaller than 5%, the simulation and theoretical values are close enough to each other and the measurement is regarded as accurate. the simulation value of a viscoelastic property of a portion (i.e., the background material and inclusion of the single-inclusion phantom, and the top, middle, and bottom layers of the three-layer structure) in the model is defined as the average value of that property of all elements in that portion obtained from the simulation. 4. results fig. 6 shows a set of examples of the spatial distribution maps of the viscoelastic properties (� and � ) for each material model. some observations from fig. 6 can be highlighted: (1) homogeneous material: the maps of both properties are homogeneous, as expected. (2) heterogeneous materials, including the single-inclusion phantom and the three-layer structure: the map of a property (i.e., (� or � ) of a portion (i.e., the background material and inclusion of the single-inclusion phantom, as well as the top, middle, and bottom layers of the three-layer structure) is not homogeneous, although in theory it should be homogeneous (since the theoretical value of a property of a portion is set as a single value during the simulation). in addition, there are larger errors and stronger inhomogeneities near the boundaries of a portion. (a) homogeneous material fig. 6 examples of the spatial distribution maps of the viscoelastic properties for each material model 234 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 (b) single-inclusion phantom (c) three-layer structure fig. 6 examples of the spatial distribution maps of the viscoelastic properties for each material model (continued) table 1 simulation results for the homogeneous material theoretical properties of the homogeneous material simulation properties of the homogeneous material error (%) � (pa) � (s) � (pa) � (s) � � 10000 1 10000 1.016 0.00 * 0.02 * note: the error value of the case, in which the error is lower than 5% and the measurement is accurate, is marked with an asterisk and underline. table 2 simulation results for the background material of the single-inclusion phantom theoretical properties of the inclusion simulation properties of the background material error (%) � (pa) � (s) � (pa) � (s) � � 1000 0.5 10231 1.009 2.31 * 0.94 * 1000 1 10233 1.008 2.33 * 0.83 * 1000 2 10226 1.004 2.26 * 0.36 * 5000 0.5 10042 1.016 0.42 * 1.60 * 5000 1 10046 1.013 0.46 * 1.31 * 5000 2 10038 1.012 0.38 * 1.18 * 10000 0.5 9996 1.015 0.04 * 1.51 * 10000 2 9999 1.017 0.01 * 1.67 * 20000 0.5 10021 1.014 0.21 * 1.41 * 20000 1 10025 1.017 0.25 * 1.74 * 20000 2 10025 1.026 0.25 * 2.59 * note: the error value of the case, in which the error is lower than 5% and the measurement is accurate, is marked with an asterisk and underline. table 3 simulation results for the inclusion of the single-inclusion phantom theoretical properties of the inclusion simulation properties of the inclusion error (%) � (pa) � (s) � (pa) � (s) � � 1000 0.5 6206 1.036 520.58 107.27 1000 1 6199 1.071 519.86 7.15 1000 2 6211 1.146 521.14 42.69 5000 0.5 7948 0.911 58.95 82.11 5000 1 7953 1.026 59.05 2.56 * 5000 2 7948 1.319 58.95 34.05 10000 0.5 10012 0.825 0.12 * 64.99 10000 2 10030 1.457 0.30 * 27.17 20000 0.5 14108 0.735 29.46 46.95 20000 1 14098 1.003 29.51 0.33 * 20000 2 14128 1.611 29.36 19.43 note: the error value of the case, in which the error is lower than 5% and the measurement is accurate, is marked with an asterisk and underline. 235 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 table 4 simulation results for the top layer of the three-layer structure theoretical properties of the middle layer simulation properties of the top layer error (%) � (pa) � (s) � (pa) � (s) � � 1000 0.5 7494 0.951 25.06 4.88 * 1000 1 7481 0.979 25.19 2.15 * 1000 2 7489 1.056 25.11 5.60 5000 0.5 8823 0.928 11.77 7.22 5000 1 8813 1.003 11.87 0.27 * 5000 2 8830 1.180 11.70 17.96 10000 0.5 10018 0.915 0.18 * 8.54 10000 2 10026 1.228 0.26 * 22.76 20000 0.5 11739 0.914 17.39 8.59 20000 1 11706 1.029 17.06 2.85 * 20000 2 11758 1.265 17.58 26.48 note: the error value of the case, in which the error is lower than 5% and the measurement is accurate, is marked with an asterisk and underline. table 5 simulation results for the middle layer of the three-layer structure theoretical properties of the middle layer simulation properties of the middle layer error (%) � (pa) � (s) � (pa) � (s) � � 1000 0.5 2712 0.826 171.24 65.10 1000 1 2692 1.232 169.25 23.17 1000 2 2703 2.004 170.30 0.21 * 5000 0.5 6760 0.776 35.20 55.22 5000 1 6726 1.058 34.53 5.81 5000 2 6746 1.629 34.92 18.57 10000 0.5 10021 0.722 0.21 * 44.49 10000 2 10025 1.651 0.25 * 17.46 20000 0.5 15860 0.649 20.7 29.86 20000 1 15834 0.989 20.83 1.06 * 20000 2 15861 1.713 20.69 14.33 note: the error value of the case, in which the error is lower than 5% and the measurement is accurate, is marked with an asterisk and underline. table 6 simulation results for the bottom layer of the three-layer structure theoretical properties of the middle layer simulation properties of the bottom layer error (%) � (pa) � (s) � (pa) � (s) � � 1000 0.5 7342 0.957 26.58 4.27 * 1000 1 7349 0.979 26.51 2.12 * 1000 2 7345 1.054 26.55 5.41 5000 0.5 8690 0.920 13.10 7.99 5000 1 8682 1.000 13.18 0.03 * 5000 2 8700 1.190 13.00 19.00 10000 0.5 10024 0.897 0.24 * 10.28 10000 2 10033 1.262 0.33 * 26.20 20000 0.5 11964 0.904 19.64 9.60 20000 1 11943 1.036 19.43 3.63 * 20000 2 11991 1.301 19.91 30.13 note: the error value of the case, in which the error is lower than 5% and the measurement is accurate, is marked with an asterisk and underline. table 1 shows the simulation results for the homogeneous material, showing the comparison between the simulation and theoretical properties. tables 2 and 3 show the simulation results for the background material and inclusion of the single-inclusion phantom respectively, showing how the simulation properties of the background material and inclusion change with the theoretical properties of the inclusion. tables 4, 5, and 6 show the simulation results for the top, middle, and bottom layers of the three-layer structure respectively, showing how the simulation properties of the top, middle, and bottom 236 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 layers change with the theoretical properties of the middle layer. the simulation results shown in these tables demonstrate the measurement accuracy of uvci. some observations from tables 1 to 6 can be highlighted: (1) homogeneous material: the simulation property is almost equal to the theoretical property, showing that uvci can accurately measure the viscoelastic properties of the homogeneous material. (2) single-inclusion phantom: the measurement of � or � of the background material is accurate in each case. however, for the inclusion, the measurements of both properties are inaccurate in most cases, showing that uvci in general cannot accurately measure the viscoelastic properties of the inclusion of the single-inclusion phantom. the measurement of a property of the inclusion can be accurate if and only if when the background material and inclusion have the same value of that property. (3) three-layer structure: for all three layers, the measurements of both properties are inaccurate in most cases, showing that uvci in general cannot accurately measure the viscoelastic properties of the three respective layers of the three-layer structure. the measurement of a property of a layer can be accurate if and only if when all three layers have the same value of that property. 5. discussion the idea of developing uvci technology is to provide a clinical diagnostic tool for quantifying the severity of pathologies based on serving the viscoelastic properties of tissues as biomarkers. this idea is based on the fact that pathological processes could result in changes of the viscoelastic properties of tissues, and therefore there could be a correlation between the viscoelastic properties of tissues and the severity of pathologies. however, the findings of the present study demonstrate that uvci cannot accurately measure the viscoelastic properties of the inclusion of the single-inclusion phantom and those of the three respective layers of the three-layer structure, although it can accurately measure the viscoelastic properties of the homogeneous material and those of the background material of the single-inclusion phantom. these findings suggest that uvci in general cannot accurately measure the true values of the viscoelastic properties of a single material point as well as a portion of a heterogeneous material. the clinical implication of the findings of the present study is that, it could be difficult to apply uvci as a clinical tool to accurately and quantitatively diagnose the severity of pathologies or the health status of tissues based on serving the true values of the viscoelastic properties of tissues as biomarkers. fortunately, at least, uvci can accurately measure the viscoelastic properties of homogeneous materials; therefore, it still has the potential to be a useful clinical tool to quantify the severity of pathologies and the health status of tissues that can be reasonably regarded as homogeneous, such as liver tissues. the innovation of the present study is that, it is the first study to quantitatively and thoroughly investigate the accuracy of uvci in measuring the viscoelastic properties of various kinds of heterogeneous materials by using finite element simulation, and the findings can help explain the experimental results in previous studies. computer simulation is the necessary methodology for this study purpose. it is because, the theoretical parameters defined during the simulation process can be served as the golden standard to be compared with the simulation results for verifying the measurement accuracy of uvci. it is one of the invaluable benefits of computer simulation. on the other hand, although direct experimental measurements on in vivo tissues can provide real measurement data, they actually cannot verify the measurement accuracy of uvci since the viscoelastic properties of in vivo tissues are unknown (and to be determined) and therefore there is no golden standard to verify the experimental results. by visually inspecting the spatial distribution maps of the viscoelastic properties obtained from uvci (i.e., fig. 6), different portions with different viscoelastic properties of a heterogeneous material could be clearly distinguished. for example, by visually inspecting fig. 6, the inclusion can be distinguished from the background material of the single-inclusion 237 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 phantom, while the middle layer can be distinguished from the top and bottom layers of the three-layer structure. hence, although uvci cannot measure the true values of the viscoelastic properties of a portion of a heterogeneous material, it still could measure the relative values and could be useful to tell different portions of a heterogeneous material apart. based on this feature, uvci still could be a useful clinical tool for diagnosing the all-or-none presence or absence of pathology, although it could not be used to accurately quantify the severity of pathology. in the future, in order to maximize uvci’s clinical and biomedical application values, there is an essential need to improve the measurement accuracy of uvci on heterogeneous materials and structures by further improving the theories and technologies relevant to uvci. it is because, after all, most biological tissues and biomaterials that uvci aims to measure in real applications are heterogeneous. three directions for improving the performance of uvci are proposed as follows: (1) in current uvci technology, only the axial strain component of the sample is measured by ultrasound imaging. in addition, the constitutive equation applied to curvefit the creep curve for quantifying the associated viscoelastic properties, i.e. eq. (1), is a one-dimensional mathematical model only considering axial strain and stress components. however, during the measurement using uvci, the sample should undergo not only axial but also lateral stress and strain components under the compression of the ultrasound transducer, meaning that the mechanical behaviors (i.e., the states of stress and strain) of the sample should be two-dimensional in this situation. hence, a one-dimensional constitutive equation could not be sufficient to completely describe and analyze the mechanical behehavior of the sample for accurately quantifying its viscoelastic properties. in the future, it is promising that the measurement accuracy of uvci on heterogeneous materials and structures could be significantly improved, if both axial and lateral strain components can be measured by ultrasound imaging and a two-dimensional constitutive equation can be applied to analyze the measured data. (2) in the future, a more detailed simulation analysis can be conducted to collect a large amount of data, and then a deep machine learning approach can be applied to construct a model that describes the relationship between the measured and theoretical (i.e., true) viscoelastic properties for each specific type of material. by serving the measured viscoelastic properties as the input of the established deep machine learning model, this model can be applied to reconstruct the true viscoelastic properties of the sample for obtaining accurate measurement results. (3) two published studies have proposed correction methods for improving the measurement accuracy of quantitative ultrasound imaging technologies [28-29]. it is suggested that these correction methods could be modified for use in improving the measurement accuracy of uvci. although the structures of the heterogeneous material models (single-inclusion phantom and three-layer structure) used in the present simulation study are relatively simple compared to those of real tissues, they can appropriately mimic the main structural characteristics of some types of tissues. the structure of the single-inclusion phantom is similar to the nature of soft tissue tumors; therefore, the single-inclusion phantom is often chosen to model soft tissue tumors in both experimental and computational studies in literature. on the other hand, the three-layer structure is a natural configuration that can be often seen in some biological tissues and various kinds of biomaterials. in addition to their tissue-mimicking nature, single-inclusion phantom and three-layer structure are favorable for modeling tissues in research because they are easy to model and analyze due to their relatively simple geometries. hence, it is believed that the single-inclusion phantom and three-layer structure are appropriate models for investigating the mechanical behaviors of normal and pathological tissues. nevertheless, in the future, more realistic models are still needed to account for the complexity of real tissues in order to more accurately understand the actual mechanical behaviors of real tissues. the uvci technology investigated in the present study is also named compressional viscoelastography, a type of uvci systems using mechanical compression (via the ultrasound transducer) as the source of the force excitation for inducing the stress field and creep behavior within the sample. in literature, several types of uvci systems have been reported by different 238 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 research groups. these different uvci systems are similar in fundamental principles, but there are still some key differences between them: (1) the means of these uvci systems to exert the force excitation are different and can be classified into two types, i.e., mechanical compression or acoustic radiation force. (2) the acoustic-radiation-force based uvci can only take the measurement at the focus of the acoustic radiation force, since only the magnitude of the acoustic radiation force at the focus is strong enough to induce significant deformation to be detected by ultrasound imaging. in other words, the acoustic-radiation-force based uvci can only take the measurement at one single point at a time. on the other hand, the magnitude of the stress field induced by the mechanical-compression based uvci is strong and uniformly distributed within the sample; therefore, the mechanical-compression based uvci can take the measurement at each material point of a full cross-section of the sample and produce the 2d spatial distribution maps of viscoelastic properties. (3) the magnitude of the acoustic radiation force at the focus is unknown in vivo, and therefore the acoustic-radiation-force based uvci cannot obtain the true viscoelastic properties of in vivo tissues. it is because, two parameters, the absorption coefficient and the compressional sound speed of the sample, are needed to calculate the magnitude of the acoustic radiation force, but these two parameters are generally unknown for in vivo tissues. similarly, for the mechanical-compression based uvci, although the magnitude of the induced stress field is unknown in vivo, it is close to the known magnitude of the compressional pressure applied on the sample’s top surface and could potentially be approximated using the principles of mechanics. therefore, although the current mechanical-compression based uvci cannot obtain the true viscoelastic properties of in vivo tissues either, it is believed that it could have a high potential for achieving that ultimate goal. the present study has several limitations that should be carefully considered in future research: (1) the material that constructs the computational models is assumed to be linearly viscoelastic, isotropic, and incompressible. in addition, the poisson’s ratio of the material is assumed to be a constant. however, a real tissue could be nonlinearly viscoelastic, anisotropic, and compressible, and its poisson’s ratio could be strainand time-dependent. therefore, due to these assumptions, the simulation results in the present study are just relative trends and should not be regarded as absolute relationships. however, this limitation does not violate the purpose of the present study that aims to provide relative trends for application guidelines. (2) the dimensions of the models are not designed according to physical measures or a systematic methodology. in the future, it is essential to design the dimensions of the models according to those of real biological tissues and biomaterials, such that the simulation results could be more realistic. it is suggested that realistic tumor or tissue models can be constructed by real ultrasound images, such that the simulation and experimental results could be compared to each other. (3) in this finite element simulation study, the settings of the factors that may affect the measurement accuracy (such as the loading and boundary conditions, dimensions and mechanical properties of materials, and so on) are specific. therefore, the simulation results cannot be generalized to any situation. in the future, it is essential to explore the effects of different settings of these factors on the simulation results and conclusions. 6. conclusions in conclusion, the findings of the present finite element simulation study demonstrate that uvci cannot accurately measure the viscoelastic properties of the inclusion of the single-inclusion phantom and those of the three respective layers of the three-layer structure. these findings suggest that uvci in general cannot accurately measure the true values of the 239 advances in technology innovation, vol. 7, no. 4, 2022, pp. 229-241 viscoelastic properties of heterogeneous materials. the clinical implication of these findings is that, it could be difficult to apply uvci as a clinical tool to accurately diagnose the severity of pathologies or the health status of tissues based on serving the viscoelastic properties of tissues as biomarkers, since most tissues are heterogeneous. however, at least, uvci can accurately measure the viscoelastic properties of homogeneous materials. therefore, it still has the potential to be a useful clinical tool to quantify the severity of pathologies and the health status of tissues that can be reasonably regarded as homogeneous, such as liver tissues. in addition, although uvci cannot measure the true values of the viscoelastic properties of heterogeneous materials, it still could measure the relative values and could be useful to tell different portions of a heterogeneous material apart by visually inspecting the spatial distribution maps of the viscoelastic properties. based on this feature, uvci still could be a useful clinical tool for diagnosing the all-or-none presence or absence of pathology. conflicts of interest the authors declare no conflicts of interest. acknowledgments the authors sincerely thank the research funding supported by the ministry of science and technology of taiwan (grant number: most 108-2218-e-002-046-my3). references [1] j. bamber, et al., “efsumb guidelines and recommendations on the clinical use of ultrasound elastography. part 1: basic principles and technology,” ultraschall in der medizin-european journal of ultrasound, vol. 34, no. 2, pp. 169-184, april 2013. 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[30] m. toğaçar, et al., “tumor type detection in brain mr images of the deep model developed using hypercolumn technique, attention modules, and residual blocks,” medical and biological engineering and computing, vol. 59, no. 1, pp. 57-70, november 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 241 microsoft word 3-v9n2(2024)-aiti#13175(116-128).docx advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 english language proofreader: chih-wei chang smart streetlight energy saving system based on mmwave radar yu-kai lin, jhih-ci li, kai-li wang, yu-ping liao* department of electrical engineering, chung yuan christian university, taoyuan, taiwan, roc received 07 december 2023; received in revised form 12 february 2024; accepted 13 february 2024 doi: https://doi.org/10.46604/aiti.2024.13175 abstract streetlights serve as fundamental infrastructure to meet the lighting needs of people on every road. however, their extensive deployment often results in unnecessary energy waste, with many streetlights maintaining high brightness despite minimal usage during the night. this study aims to develop a smart energy-efficient streetlight system that automatically adjusts lighting levels based on the absence of vehicles and pedestrians, detected after a 3-minute countdown. specifically, the study utilizes mmwave radar to collect point cloud data, which undergoes denoising through doppler, dbscan, and xyz techniques. additionally, the mmwave radar assists in training an lstm model to identify pedestrian pathways. the implementation of the proposed system significantly reduces energy consumption and annual costs by automatically dimming or turning off streetlights in areas with minimal pedestrian activity during nighttime. keywords: deep learning, lstm, mmwave radar, point cloud data, dbscan 1. introduction given the need to reduce energy consumption and operating costs, the installation of smart systems has been globally implemented. specifically, advanced smart operation technology is required to effectively control, manage, and communicate street lighting to minimize energy consumption. hence, to expound on the technology, the following introduction will be divided into three parts, i.e., background, motivation, and finally, goal. 1.1. background fig. 1 the proportion and resource consumption of street light types across taiwan streetlights are the most widely installed infrastructure and are essential equipment to assure public safety. due to their pervasive distribution and strict requirements for lighting direction and brightness, the power and specifications of streetlights are rigorously regulated. according to [1-2], as shown in fig. 1, statistically, about 1.6 million streetlights are installed in * corresponding author. e-mail address: lyp@cycu.edu.tw advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 117 taiwan, of which mercury streetlights account for 51.8%, high-pressure sodium lamps standing at 35.2%, metal halide lamps for 2.9%, fluorescent lamps for 9.3%, and led street lights for 0.8%, respectively. assuming all street lights are 200w traditional lights (non-led) and are illuminated for 12 hours per day annually, they consume approximately 1,401,600,000 kwh (1,401,600 mwh) of electricity per year, with an annual cost of more than nt$2.3 billion (nt$1454 per light × 1.6 million lights). despite the truth lying in the satisfaction of people’s need for lighting, the government confronts a huge financial burden, and reports have profusely emanated and discussed the inability of local governments to undertake the cost of streetlights. in addition, in recent years, the conflicts among energy supply, economy, environmental protection, and people’s livelihoods have continued to emerge. despite the ostensible insignificance, the economic and energy pressures incurred by streetlights have osmotically impacted daily life. 1.2. motivation currently, despite the presence of research concerning mmwave radar [3-4], still, related products, research, and applications concerning energy-saving streetlights are insufficient. the recent practice is “ai island” in songdo, south korea. however, artificial intelligence (ai) is widely applied to various products and services, and many electronic products increasingly seek to incorporate the internet of things (iot). given this trend, such a phenomenon is inevitable to develop a small device that can intelligently recognize and operate at the edge. furthermore, in comparison, the most suitable sensor for detecting objects at night is the millimeter wave radar. millimeter wave radar technology is gradually maturing and is equipped with a certain level of software and hardware knowledge. millimeter wave radar remains flexible functions for college students to use various data processing techniques for object detection in varied circumstances, accurately recognize target objects, and ultimately achieve the desired purpose through controlled hardware and components. 1.3. goal to address the issue of energy consumption of street lights in a state of being sustainably idle and illuminating at full brightness, this study proposes a method wherein the lights turn off after a 3-minute countdown in the absence of passing vehicles and pedestrians. millimeter-wave radar will be deployed to detect specific targets, as illustrated in fig. 2, and activate the lights to ensure driving safety. as a result, the project aims to achieve energy saving, carbon reduction, and cost reduction. (a) system schematic diagram (b) system schematic flowchart fig. 2 smart streetlight energy saving system schematic diagram 118 advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 2. research methods the implementation of smart street lighting systems is pervasive in large cities. meanwhile, the millimeter-wave radar is perceived to be the most suitable sensor for nocturnal detection because of its long detection range and ability to identify objects under any nocturnal and meteorological conditions. in this section, the project approach will be further explored as follows. 2.1. research methods the project is mainly divided into four parts: (1) collecting and building a millimeter wave radar database on the windows 10 operating system. (2) building and training a long short-term memory (lstm) neural network model using pytorch on the windows 10 operating system. (3) developing a control program for ht32f52352 streetlights on the windows 10 operating system. (4) integrating the millimeter wave program in the ubuntu system of nvidia jetson nano and communicating with ht32f52352 to control streetlights. in this project, the ti iwr6843 single-chip mmwave sensor millimeter wave radar, which is mounted on the batman bm501 mmwave evm kit [5], is used to collect multiple sets of 50-frame millimeter wave data on the windows 10 operating system. three noise reduction methods including doppler, dbscan, and averaging over thousands of data points in each frame, are used to remove a large amount of background noise. next, an lstm neural network model is built using pytorch, and the pre-processed multiple datasets are sent to the lstm neural network for training in a concatenated matrix form. after adjusting the parameters appropriately, the trained module can be exported for real-time recognition on the nvidia jetson nano later. the streetlight control program runs on the ht32f52352 based on the arm architecture and is developed using keil v5. the main function is to use an interrupt function to calculate the time the light is on and control the brightness of the led light board through pulse-width modulation (pwm). the final step involves integrating the pytorch-trained lstm model with the millimeter wave radar on the nvidia jetson nano hardware. this integration allows the pre-processed millimeter wave data to be analyzed in real-time by the trained model to identify the direction of the target’s movement. the resulting output is then sent to the gpio on the nvidia jetson nano and forwarded to the ht32f52352 to activate the streetlights along the path. in cases where no target is detected, the lights are dimmed or turned off sequentially to conserve energy. 2.2. system architecture the steps of the system process are enumerated as follows: (1) the millimeter-wave radar on nvidia jetson nano receives detection data. (2) the data is organized and denoised on nvidia jetson nano, and the trained lstm model is used to perform calculations. (3) the result is transmitted to ht32f52352 via gpio. (4) ht32f52352 controls the led lights based on the recognition result. the system architecture diagram is depicted in fig. 3. the nvidia jetson nano is connected to the batman bm501pcr mmwave sensor through a usb port to collect point cloud data and perform recognition using the ai model, and the recognition results are then transmitted to the ht32f52352 via gpio, while the ht32f52352 utilizes pwm to control the brightness of street lights. advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 119 fig. 3 system architecture diagram 2.3. ti iwr6843 single-chip mmwave sensor the cnn image recognition has been employed for pedestrian and vehicle detection in some studies [6-8]. however, given that street lights are only turned on at night, using traditional cameras under low light conditions will result in lower recognition rates, as shown in table 1. even with infrared and thermal cameras, the effective range is limited to a maximum of 50 meters. therefore, the decision is made to utilize a millimeter-wave radar capable of effectively detecting objects in any situation, with a working range of up to 250 meters. table 1 comparison chart of common sensors [9] radar lidar ultrasonic camera laser infrared range long medium short short short short range accuracy high high high medium high poor angle accuracy medium high none high high poor speed measurements yes no no no no no dust/fog/smoke robustness high medium poor poor poor poor dark/light robustness high high high medium poor medium efforts to integrate into machines small high small medium medium small cost factor small to medium extremely high small medium to high high small stepwisely, the process can be divided into three steps. first, the millimeter-wave radar emits radio waves and receives the reflected signals from the target. second, the relative distance, velocity, angle, and motion direction of the target are calculated. third, the aforementioned data is returned to the computer for processing and decision-making. currently, mediumrange radar (mrr), operating at 24 ghz, and long-range radar (lrr), operating at 77 ghz, are the main types of millimeterwave radar used ubiquitously, as shown in table 2. table 2 advantages and disadvantages of millimeter-wave radars in different frequency bands advantages disadvantages 40 ghz wide detection angle and cheap price. the maximum detection range is approximately 50 meters. 60 ghz the radar with a detection range of about 100 to 150 meters, with a medium price and a wider detection angle than 77ghz. the detection distance is not farther than that of a 77ghz radar. 77 ghz the radar with the farthest detection distance is up to 250 meters. the radar with a narrow detection angle and is expensively priced. the 24 ghz millimeter-wave radar used in autonomous driving, automatic parking, and other applications can only detect distances of approximately 50 meters. in the case of employing the 24 ghz millimeter-wave radar for the streetlights, a false activation after the passage of vehicles may incur. although the 77 ghz millimeter-wave radar can detect longer distances and higher speeds, it demands a relatively high price. therefore, the decision is made to utilize the iwr6843aop single-chip 60 120 advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 to 64-ghz mmwave sensor-batman bm501, which has a detection range of approximately 100 to 150 meters, a lower price than purchasing only a 77 ghz radar, and a wider detection angle than 77 ghz. relevant specifications are shown in fig. 4 and table 3 [5, 10]. fig. 4 bm501 module on carrier board [5, 10] table 3 configuration parameters [5, 10] parameter configuration 1 start frequency 60 ghz 2 stop frequency 64 ghz 3 bandwidth 4 ghz continuous bandwidth 4 tx power 15 dbm 5 rx noise figure 14 db 6 phase noise at 1 mhz -92 dbc/hz 7 number of transmitters 3 8 number of receivers 4 9 azimuth field of view 120° 10 elevation field of view 120° 11 the heights of 3 subjects 171, 180 and 182 cm the output of the millimeter-wave module is segmented into key data and raw data. key data has less data and uses a baud rate of 115200/8/n/1, while raw data has more data and uses a baud rate of 921600/8/n/1. this project uses raw data and opens the jetson nano’s usb-uart to read data, enabling dial-out permission. the bm501-pcr will transmit three packets: v6, v7, and v8, which correspond to the point cloud, target object, and target index, respectively. concerning the classification and processing, the raw v6 (point cloud) data is deployed. the v6 packet contains seven pieces of information: frame number, type, elevation, azimuth, doppler, range, and snr. in other words, the information represents frame number, data type, elevation angle, azimuth angle, velocity, distance to the radar, and signal-to-noise ratio of each point in the point cloud, respectively. by using the point cloud’s elevation (ψ), azimuth (θ), and range (r), the x, y, and z positions of each point can be calculated. elevation, azimuth, and range are in spherical coordinates, which are nuanced from the commonly used x, y, and z coordinates, but they can be transformed into point cloud’s x, y, and z coordinates using a mathematical formula. a 60 ghz millimeter-wave radar is employed, commencing with the detection of individuals within a 6-meter and 120degree range. the team will repeatedly walk past in front of the millimeter-wave radar at the same distance and height. the 60 ghz radar transmitter generates radio frequency signals, which are then converted to low-frequency signals by the receiver. the signal is subsequently transmitted to the signal processor, which extracts information such as distance, velocity, and angle, and eventually is returned to the jetson nano for processing. 2.4. millimeter-wave radar data collection the output data of the bm501-pcr mmwave sensor can be processed into some data structures using the mmwave python sdk. the v6 point cloud data is utilized to process and classify data. the data structure of v6 point cloud data is depicted in fig. 5 [11]. the v6 point cloud data structure contains ten data items, from which the values of sx, sy, sz, and doppler can be used as input features for training the deep learning lstm model to recognize object movement. advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 121 fig. 5 data structure of v6 point cloud [11] considering the position of the radar on the road, the range of data collection, and the ease of collecting data on the target for students, data collection on pedestrians is conducted, as shown in fig. 6. the radar is installed at a height of 1.5 meters above the ground, and the range presents rectangularly with a length of 3 meters and a width of 2 meters centered on the radar. the pedestrian will walk straight 1 meter away from the radar at a speed of 2 m/5s, and the direction of the movement is either left or right. fig. 6 schematic of data collection range (a) an originally single frame (b) superimposed frames fig. 7 data before and after superimposing 122 advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 it is noteworthy that partially observing point cloud data in each frame will incur the inability to target the location of the detected object and the inability to identify the object concerning the attributes, moving state, and additional information. therefore, by superimposing multiple frames of point cloud data, as shown in fig. 7, there will be considerable dense point cloud data in the detected place, which is helpful for position identification data processing and object classification. 2.5. denoising the collected point cloud data is initially noisy, with over 10,000 point clouds containing noise and all information about the target objects within the detection time and range of 50 frames. thus, to filter out all irrelevant noise and extract detailed data of each target object in each frame, three denoising methods are used sequentially: (1) doppler filtering [12] the point cloud data type provides doppler data for each point, and doppler is exactly defined as the speed of a certain point. by using doppler, many static background noises are easily filterable, and only the point cloud data of the “walking person” that is desired to be retained is preserved. the condition is “if |doppler| < 0.1” which is shown in fig. 8, the data of that point is eliminated. (a) an original data (b) a doppler filtered data fig. 8 data before and after doppler filtering (2) dbscan fig. 9 a data after dbscan despite the addition of the doppler filter, millimeter-wave radar is somewhat susceptible to misidentifying stationary noise as moving. such misidentification is environmentally caused by diffraction and interference and subsequently generates an incorrect doppler value. however, most of the remaining point cloud data is located on the target and has a high density. advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 123 as a solution, numerous clustering algorithms based on cluster density can be employed to further filter out noise. in this context, the algorithm utilized is dbscan (density-based spatial clustering of applications with noise) proposed in 1996 [13]. technically, dbscan is a density-based algorithm [14] that defines the user’s literal definition of “high density” by inputting two parameters: eps (the radius at which a data point looks for other points) and min_samples (the minimum number of points in eps to be considered non-noise). as shown in fig. 9, the parameters are set to eps = 0.25 and min_samples = 12. (3) mean filtering in x, y, z direction notwithstanding undergoing two antecedent steps and the filtration of the majority of background noise, the point cloud data intersperses residual noise. being cognizant of the majority of remaining points from pedestrians, their characteristic motion applies to further filter out noise. specifically, a mean filter is applied in the x, y, and z directions to each frame of point cloud data. the result is shown in fig. 10. this averaging process helps to highlight the distinctive features of pedestrians in motion. 1 1 1( , , ) ( , , )= = = =    n n n i i ii i i mean mean mean x y z x y z n n n (1) remark: n is the rest point cloud data counts of a single frame of 50 superimposed frames. fig. 10 a mean filtered data by averaging all the points in this frame, the previously chaotic and noisy data will be converted into a point, which represents the position of the person in that frame. this also signifies the sequence information will be used later in lstm deep learning. to better understand its temporal variation, fig. 11 shows the position line chart having been averaged, and fig. 12 shows the averaged variation of each frame. fig. 11 line chart of mean position fig. 12 line chart of variation of the mean position 124 advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 2.6. lstm deep learning after preprocessing the millimeter-wave radar v6 point cloud data through doppler filtering, dbscan, and mean filtering in x, y, and z directions to filter out all irrelevant noise and extract detailed data of each target object in each frame, the data is fed into an ai model. since the point cloud data is sequential, an lstm model is chosen for recognition. after multiple rounds of testing, the following neural network architecture is adopted. (1) model as illustrated in table 4, the first layer is constructed as lstm, the third and fourth layers as linear layers, and the second layer in the middle with relu (linear rectification function) to prevent gradient disappearance and gradient explosion. the input size of the lstm input shape in the first layer is 4, which are the 4 feature values (x pos, y pos, z pos, doppler) of the millimeter wave radar detection [14]. the fifth layer is softmax, which induces the sum of the two numbers in the matrix as 1, and the output is 2 for (1, 0) and (0, 1) respectively. if the matrix is close to (1, 0) for people walking to the right, the street light will turn on from left to right. if the result is close to (0, 1) for people walking to the left, the streetlights will turn on from right to left. if neither, the street light will not make any response. table 4 layers of lstm neural network layer i/o configuration lstm input (none, 50, 4) output (none, 50, 16) relu input (none, 16) output (none, 16) linear input (none, 16) output (none, 20) linear input (none, 20) output (none, 2) softmax input (none, 2) output (none, 2) (2) training fig. 13 lstm training and validation loss in this section, three people would pass 1.5 m-3 m in front of the millimeter wave radar for testing. each person passed from left to right and right to left 110 times, with inconstant speed each time. a total of 660 records were collected. the learning rate is 0.001 and is inversely proportional to the change speed of the loss function. according to [15-16], 20% of the training data is used as validation data, and the data use “optimizer.zero_grad” to set the gradient to zero, i.e., changing the derivative of loss concerning weights to 0 before backpropagation. then, “loss.backward” is called to start backpropagation, and, finally, “optimizer.step” is used to update the weights. a total of 100 epochs are performed, and the batch size is 20. the results are shown in fig. 13 and table 5. advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 125 table 5 confusion matrix of the proposed work class walk from left to right walk from right to left else total walk from left to right 324 1 5 330 walk from right to left 0 327 3 330 else 3 2 325 330 2.7. streetlight controlling program fig. 14 is a flowchart for streetlight control. this chart purposively visualizes the steps of streetlight control to proffer the reader a comprehensive insight into the overall program. initially, the system waits for a signal from the jetson nano, and if the signal is absent, no action will be taken. then, the jetson nano transmits a signal indicating the correct direction of the illumination, which triggers the key process (interrupt function) and the sleep function. when the system receives a signal from the jetson nano, the countdown variable is incremented by five, and when it reaches zero, the system continues to wait for the subsequent signal. fig. 14 the flowchart of the streetlight control program the key process function is the interrupt function area, primarily used to send signals from the jetson nano to the ht32f52352 and determine the direction of the signal source. the sleep function is mainly used to turn on the led light. table 6 shows the pwm duty cycle variations that control the brightness of the streetlight, for readers to refer to. table 6 the duty cycle variation of pwm the duty cycle when pwm is turned on and fully bright 100% the variation in duty cycle during the pwm off period 75% => 50% => 25% => 0% 3. result and analysis the model is first trained on the windows 10 operating system using lstm, and the ensuing trained model is deployed onto the nvidia jetson nano. the millimeter-wave radar is connected to perform object recognition, and the results are then transmitted to the ht32f52352 to control the streetlight switch. assuming that the streetlights can halve their operating time every night, the analysis of power consumption and running costs of the proposed system signifies the importance of a smart lighting system. the results and analysis of the proposed system are demonstrated in the following sections. 126 advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 3.1. result the results are shown in figs. 15, 16, and 17. the trained lstm model was saved using the torch.save and transferred as a path file to the jetson nano for loading. the weights in the file were used to compare with the data measured by the millimeter wave radar for recognition. the output after weight calculation is also a 1 × 2 matrix, where both values are between 0 and 1, and the sum of the two values is 1 (due to the softmax layer). the values between 0 and 1 represent probabilities, where 0 represents 0% and 1 represents 100%. therefore, the 1 × 2 matrix represents the probabilities of two possibilities. if the left value is larger, such as [0.8, 0.2], the system determines that there is an 80% probability of moving to the right and a 20% probability of moving to the left. thus, torch.max is used to select the higher value (higher probability) as the output. however, if both values do not exceed 0.6 (60%), such as [0.56, 0.44], the system will determine that there is no passing pedestrian, and the street light will not respond. fig. 15 the smart streetlight energy-saving system fig. 16 the person passing by and the light turns on fig. 17 the light turns off after the person has gone for a while 3.2. analysis through the use of millimeter-wave radar recognition, the system has achieved excellent results in recognizing people, walking direction, and identifying the target objects. this project is planned to install one system approximately every 500 meters. streetlights are spaced at a distance of about 35 to 50 meters, i.e., at least 10 streetlights will be situated if this system is installed. the cost of this device is approximately 28,000 twd. each device can provide power for around 10 streetlights, which means the average cost per streetlight is 2,800 twd. table 7 presents the “device cost” of the “smart streetlight energy saving system” and common types of streetlights in taiwan, along with their annual “energy consumption” and “electricity cost”. advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 127 table 7 the device cost and the annual energy consumption and electricity cost [17] name device cost power consumption energy consumption (11 hours / day × 1 year ) electricity cost (1 year) (3.5 twd / kwh) smart streetlight energy-saving system 28,000 twd 10w 11 hours × 0.01 kw × 365 days × 10 units = 40 kwh 40 kwh × 3.5 = 140 twd led 20,000 twd × 10 units = 200,000 twd 120w 11 hours × 0.12 kw × 365 days × 10 units = 4,818 kwh 4,818 kwh × 3.5 = 16,863 twd sodium-vapor lamp 10,000 twd × 10 units = 100,000 twd 250w 11 hours × 0.25kw × 365 days × 10 units = 10,038 kwh 10,038 kwh × 3.5 = 35,133 twd mercury-vapor lamp 5,000 twd × 10 units = 500,000 twd 400w 11 hours × 0.4kw × 365 days × 10 units = 16,060 kwh 16,060 kwh × 3.5 = 56,210 twd due to the energy-saving effect of the “smart streetlight energy saving system”, the operating time of the streetlights is reduced from 11 hours to 5 hours per day, as shown in table 8. if the most power-consuming mercury-vapor lamp is considered, the “smart streetlight energy saving system” can save approximately 8,760 kwh annually. even if the most energy-saving led is used, based on the equipment cost of the proposed system, 2,628 kwh of electricity can be saved annually, which is equivalent to saving at least 9,058 twd per year. the calculated investment payback period is 28,000 / 9,058 ≈ 3.09, and it will take approximately three years to recoup the equipment cost. taiwan currently has about 1.6 million streetlights. even if all streetlights in taiwan were converted to led, each group of 10 lights could save 2,628 kwh of electricity per year, and the total annual electricity savings for the entire country would be 2,628 kwh × 160,000 = 420,480 mwh. table 8 the energy-saving benefits and total savings after using the “smart streetlight energy saving system” [17] name the system is in use or not energy consumption energy-saving benefits (1 years) electricity cost (3.5 twd / kwh) # 140 twd is the annual electricity cost for this system. total savings led no 11 hours × 0.12 kw × 365 days × 10 units = 4,818 kwh 4,818 kwh 2,190kwh = 2,628 kwh 4,818 kwh × 3.5 = 16,863 twd 16,863 7,805 = 9,058 twd yes 5 hours × 0.12 kw × 365 days × 10 units = 2,190 kwh 2,190 kwh × 3.5 + 140 twd = 7,805 twd sodiumvapor lamp no 11 hours × 0.25 kw × 365 days × 10 units = 10,038 kwh 10,038 kwh 4,563kwh = 5475 kwh 10,038 kwh × 3.5 = 35,133 twd 35,133 16,109 = 19,024 twd yes 5 hours × 0.25 kw × 365 days × 10 units = 4,563 kwh 4,563 kwh × 3.5 + 140 twd = 16109 twd mercuryvapor lamp no 11 hours × 0.4 kw × 365 days × 10 units = 16,060 kwh 16,060 kwh 7,300kwh = 8760 kwh 16,060 kwh × 3.5 = 56,210 twd 56,210 25,690 = 30,520 twd yes 5 hours × 0.4 kw × 365 days × 10 units = 7,300kwh 7,300 kwh × 3.5 + 140 twd = 25690 twd 4. conclusion this paper proposed a method that utilizes millimeter-wave radar combined with deep learning lstm to identify targets for controlling the brightness of streetlights. the noticeable difference from conventional motion sensor lights lies in the proposed system approach of recognition rather than mere sensing. therefore, the prerequisite of streetlight activation is the objects which are identified as pedestrians and vehicles. such a function could conduce to the avoidability of frequent illumination of the streetlights, thereby achieving energy-saving benefits. while the system consumes power, the current architecture only consumes a maximum of 10w. the system is supposed to control traditional streetlights with approximately 10,200w, which is regarded as a mere 0.5% increase in total consumption. therefore, ideally, the energy consumption caused 128 advances in technology innovation, vol. 9, no. 2, 2024, pp. 116-128 by the system can be considered negligible. given the aforementioned findings and the pervasive installation of streetlights, the system has the potential to save approximately 420,480 mwh annually, which is equivalent to around 1.5 billion new taiwan dollars. acknowledgments this project is sponsored by the national science and technology council, taiwan with project number 111-2813-c033-079-e. conflicts of interest the authors declare no conflict of interest. references [1] g. allen, “the private finance initiative (pfi),” economic policy and statistics section, house of commons library, research paper 03/79, october 21, 2003. 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(in chinese) copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v8n3(2023)-aiti#11568(192-209).docx advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 english language proofreader: chih-wen teng an improved mobilenet for disease detection on tomato leaves hai thanh nguyen1,*, huong hoang luong2, long bao huynh2, bao quoc hoang le2, nhan hieu doan2, duc thien dao le2 1college of information and communication technology, can tho university, can tho, vietnam 2information technology department, fpt university, can tho, vietnam received 15 february 2023; received in revised form 02 april 2023; accepted 04 april 2023 doi: https://doi.org/10.46604/aiti.2023.11568 abstract tomatoes are widely grown vegetables, and farmers face challenges in caring for them, particularly regarding plant diseases. the mobilenet architecture is renowned for its simplicity and compatibility with mobile devices. this study introduces mobilenet as a deep learning model to enhance disease detection efficiency in tomato plants. the model is evaluated on a dataset of 2,064 tomato leaf images, encompassing early blight, leaf spot, yellow curl, and healthy leaves. results demonstrate promising accuracy, exceeding 0.980 for disease classification and 0.975 for distinguishing between diseases and healthy cases. moreover, the proposed model outperforms existing approaches in terms of accuracy and training time for plant leaf disease detection. keywords: plant diseases, transfer learning, fine-tuning, mobilenet, mobile devices 1. introduction nowadays, the research and application of automatic identification of plant diseases using leaves are fundamental to agricultural needs. moreover, hassan et al. [1] reported that early and accurate identification of crop diseases helps farmers to reduce some difficulties and risks and improve the productivity and quality of agricultural products. the tomato plant, one of the easiest fruits to grow, is suitable for many soil types. additionally, tomatoes bring very high nutritional and economic value to human lives. tomato contains many antioxidants and vitamins, essential for people's overall health. however, sometimes farmers also need help checking and determining if the tomato fruit quality is up to the standard or if the tomato plant is healthy or not because sometimes diseases of tomato plants usually manifest mainly on their leaves [2]. moreover, insects and pests that attack tomato plants and produce numerous illnesses can stymie the production of this well-known crop. therefore, farmers must first understand the illness to treat diseases on tomato leaves manually. they face many problems yearly as they try to raise their healthy harvests to keep the profits from farming and raising livestock. bhagwat and dandawate [3] mentioned some countries have a gross domestic product (gdp) of up to 25%. insects and other harmful viruses damage production lines and slow them down to the point where they can no longer produce as much as they can. this is a big problem for the industry, especially farmers. even though farmers use a variety of pesticides and insecticides to protect their tomato plants from disease, they frequently need to gain knowledge of the disease and how to prevent it. excessive pesticide and insecticide usage endangers human health and life. crop damage can result from incorrect disease diagnosis and applying too many or too few pesticides. in addition, the improper use of pesticides also seriously affects the surrounding soil and water environment and so on. * corresponding author. e-mail address: nthai.cit@ctu.edu.vn advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 193 diagnosing tomato plant diseases is very important to achieve maximum yields. on the other hand, manually detecting disease by carefully examining the crop is time-consuming and complicated. farmers often find it challenging to contact specialists in remote areas and take steps to prevent unusual diseases. it is easier to detect with helpful information. that is why images can be considered self-contained information helping the system detect diseases. visual studies of plants without prior information can lead to inaccurate disease diagnoses. as a result, preventive measures are used. using machines can help locate damaged tomato plants, determine what diseases affect them, and use that knowledge to help the rest of the crop grow more efficiently and with less loss. mobilenet is one of the great models the authors proposed because of its low-latency, lowpower models that can be parameterized to meet the resource constraints of a wide range of use cases. it can be used to build classification and detection systems. this study examines the leading convolutional neural network (cnn) mobilenet architecture. they applied transfer learning and refinement to pre-trained data: tomato leaves ranging from healthy to diseases. the goal is to maximize model accuracy and quickly set up “data augmentation” factors to help in disease categorization and detection on tomato leaves. the following are the key contributions: (1) this study devised the first transfer learning technique and development stage to detect diseases in tomato leaves. the final stage is to fine-tune the parameters accordingly. (2) some machine learning-based architectures were leveraged during the implementation and compared the findings to the cnn models. vgg16, vgg19, mobilenet, densenet201, and xception are other examples. (3) three main scenarios were assessed with various metrics to present the predictions for detecting and distinguishing foliar diseases. first, they demonstrated empirically that the author’s suggested strategy outperforms alternative cnn and transformer-based architectures and earlier illness detection and classification models on tomato leaves. (4) the work obtained promising results using the multilayer classification of the cnn architecture given above, and mobilenet delivered the best results. the rest of the article is divided into five following sections. section 1 begins with an introduction and explanation of the problem. section 2 will then present similar works. section 3 will next demonstrate the implementation process. the outcomes of the experiments are shown in section 4. finally, section 5 is followed by the conclusion. 2. related work to build automated decontamination procedures on plant detection systems, some researchers have used advanced technology such as machine learning and neural network design including googlenet, alexnet, inceptionv3, vgg16, and squeezenet, etc. to perform research and classification of crops based on machine learning. as a result, they use exact methods to detect plant diseases in tomato leaves. furthermore, researchers have developed various deep learning-based disease detection and classification methods. bhagwat and dandawate [3] presented some ways to detect plant disease for machine learning. the authors provided the traditional machine learning method using various evaluation metrics or the new machine learning on rgb images, which best reported the accuracy at 91.5%. fazari et al. [4] proposed a method to detect anthracnose disease on olives using the resnet101 model. the proposed method was successfully tested, which resulted in an accuracy of 91.8%. this method promises to be one of the proposals to ensure the quality of olives and olive oil is improved and meets the required standards. about the dataset, images were shot on several days and with different lighting to create a dataset with distinct phases of error growth, the data set must satisfy the condition that there must be enough light, and the leaves must see the characteristic manifestations of that disease and the image must not be blurred. on the ground, each image includes a particular leaf object. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 194 lu et al. [5] introduced and clarified the use of the deep learning (dl) method and suggested that the image set needs to go through the preprocessing stage (increasing contrast, slightly blurring, reducing brightness, etc.) for picture categorization, the majority of these approaches employ ordinary neural networks. for example, using the plantvillage dataset, brahimi et al. [6] employed googlenet and alexnet to pinpoint disease zones in the tomato plant. as a result, they classified nine illnesses with 99.18% accuracy. however, because their model was one of the first proposed, it is gradually becoming obsolete due to processing speed and model size, resulting in a limitation that the research team mentioned that the model could not be applied on mobile devices. alruwaili et al. [7] proposed a new method, known as the real-time faster region convolutional neural network (rtfrcnn) model, for trained & tested with other models using each different parameters such as precision, accuracy, and recall. the final result was 97.42% accuracy. with new technology and support for real-time disease detection, the proposed model outperforms other models and holds great promise for the future. however, learning and acclimating to it can be challenging. durmus et al. [8] employed and compared alexnet and squeezenet to classify diseases in real-time. using the plantvillage dataset, the authors categorized ten illnesses and a healthy leaf with 95.65% accuracy for alexnet and 94.3% for squeezenet. the squeezenet model has shown its strengths due to the alexnet model in approximate prediction results. however, it is very light and convenient, promising applications with mobile electronic devices. saeed et al. [9] and adhikari et al. [10] presented a pre-trained network model for detecting and categorizing tomato illness has been presented. the authors used resnetv2 model and increased the dropout coefficient from 5% to 10% to 50%. each batch of changes demonstrates that these parameters contributed to better model training and fewer errors. zhang et al. [11] discussed using a dl cnn to identify tomato leaf disease. with an accuracy of 97.19%, the paper used many pre-trained networks such as alexnet, googlenet, and resnet. ishak et al. [12] discussed a method for analyzing plant leaf quality, beginning with image acquisition, image processing, and classification. the images were collected using an 8-megapixel intelligent phone era, and the samples were divided into fifty for healthy and fifty for unhealthy. the image processing method is divided into three steps: contrast enhancement, segmentation, and feature extraction. the classification method was performed using an artificial neural network, which employs a multi-layer feed-forward neural network, followed by a comparison of two network structures, multilayer perceptron (mlp) and radial basis function (rbf). the rbf network outperformed the mlp network in terms of performance. however, the search only distinguishes between healthy and unhealthy plant leaf images. it cannot determine the type of disease. a basic cnn model with eight hidden layers was used to identify a tomato plant's circumstances. compared to other classical models [13-17], the proposed strategies produce the best results. dl approaches are used in the image processing methodology to identify and categorize tomato plant illnesses [13]. the author constructed a comprehensive system using the segmentation technique and cnn. a variant in the cnn model was adopted and used to improve accuracy. in research about the application of disease identification on tomato leaves, the author introduced and used a cnn model developed by tm et al. [14] called lenet. this process follows three steps: data collection, preprocessing, and classification. with outstanding and promising results with an accuracy of 94-95%. trivedi et al. [15] presented this article discussing standard profound learning models and variants. this article discussed biotic diseases caused by fungal and bacterial pathogens, specifically tomato leaf blight, blast, and browning. the proposed model detection rate was 98.49% correct. the proposed model was compared to vgg and resnet versions using the same dataset. in another work, suryanarayana et al. [16] reviewed all cnn variants for plant disease classification. the authors also briefed all dl principles employed for leaf disease diagnosis and classification. the authors concentrated on the most recent cnn models and evaluated their performance. in this paper, the authors summarize several cnn versions, such as vgg16, vgg19, and resnet, while also examining their benefits, drawbacks, and prospects for use in various applications. bhagwat advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 195 and dandawate [17] conducted a study on disease identification on crops, the authors applied hand-crafter features (hcf) together with cnn in the form of fusion. the author also mentioned fine-tuning the central coefficient. as a result, the accuracy for the entire leaf dataset is 99.93%, which is impressive. this result is auspicious, demonstrating improved results based on the prominence of feature fusion in crop disease detection. coulibaly et al. [18] used cnn vgg16 to perform state classification detection of millet crop. the machine learning process is fast, with promising results such as an accuracy of 95.00%, precision of 90.50%, recall of 94.50%, and an f1-score of 91.75%. ashwinkumar et al. [19] proposed using mobilenet as a base cnn model and built a new automated model for detecting and classifying plant leaf diseases based on an optimal mobile network-based convolutional neural network (omncnn). the proposed omncnn model goes through several stages, including preprocessing, segmentation, feature extraction, and classification. with a higher accuracy of 98.7%, the proposed omncnn methodology achieved maximum performance. as a result, the cnn model is an effective real-time tool for detecting and classifying plant leaf diseases. kaya and gursoy [20] proposed a novel approach based on dl for plant disease detection. the authors fused rgb images with segmentation images, then considered them with a multi-headed densenet-based architecture that the authors developed. the accuracy result was 98.17%, which is also promising because the authors mentioned that we could apply this model to the early prediction of diseases on the leaves of plants and reduce costs and losses, which affect the quality of agricultural products. thakur et al. [21] introduced a lightweight cnn model called “vgg-icnn”. vgg-icnn has approximately 6 million parameters, much fewer than most high-performing dl models. the model’s performance is evaluated using five public datasets, including various crop kinds. this model produces compelling results with up to 99.16% accuracy. however, because this is the model used to classify crop diversity, it can be inappropriate to compare it with the proposed model. 3. method convolutional neural networks (cnns) with fine-tuning have shown great promise in the classification of plant diseases. cnn models can efficiently analyze and classify various types of plant diseases, assisting in early detection and efficient management. this is made possible by utilizing the strength of deep learning and transfer learning techniques. first, data collection is important because it ensures clear, bright, and visible images, which leads to better training results. next, the reference and selection of suitable cnn models are equally important, depending on the degree of accuracy that the model performs, along with the amount of storage that the model occupies in the system. then comes the stage of decomposing and fine-tuning the hyperparameters. finally, apply comparison, evaluation, and validation. remember to periodically update and retrain the model as new data becomes available to ensure its continued accuracy and relevance in classifying tomato leaf diseases. 3.1. overall workflow fig. 1 shows the process of performing machine learning and leaf classification in tomato plants in 8 steps. the following steps will be shown in the order of arrows from the “start” button to the sequential steps from 1 to 8, and finally the end of the flow. the machine learning model uses a data file containing four picture files of tomato leaves categorized by name to prepare and perform training. 1. the first stage in this process is to gather data. this information was gathered from the plantvillage dataset † file submitted by the author charu, who is a user of the kaggle application. this data set was gathered from a group of tomato plants cultivated together. the data set contains 14,529 jpg photos with a pixel size of 256 px. the authors collected three disease samples and one healthy sample for 2,064 pictures split into four categories: early blight, septoria, yellow curl, and healthy. † plantvillage tomato leaf dataset: https://www.kaggle.com/datasets/charuchaudhry/plantvillage-tomato-leaf-dataset advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 196 2. researchers started to perform image discrimination of tomato leaves, in which there can be three diseases and one healthy type. one of the members used five well-known cnn architectures (mobilenet, densenet, vgg16, vgg19, and xception) to analyze and compare training and testing outcomes for four types of image recognition, as described above. the authors involve partitioning the data set. the obtained data is separated into training, validation, and testing. specifically, this division is done in the ratio of 60% of the photos used for training, 20% for evaluating, and 20% to test the model’s correctness. 3. in the following stage, the authors use several mobilenet models and other cnns to detect and classify each tomato plant leaf illness as transfer learning models. 4. the authors improve the hyperparameters (including epoch, learning rate, batch size, patch size, weight decay, etc.), volume, project opacity, numeric header, and transform layers and add specific layers to optimize for dl models and get the best prediction results. 5. the authors retrain using the proposed mobilenet and cnn samples from the previous stage’s refinement. following retraining, the next stage is to compute and assess the model’s accuracy against the test set. 6. validation and metric computation: they count how many images were correctly classified and compute metrics to compare the proposed model to other cnn architectures, most notably test accuracy and f1-score results. 7. the authors need to compare the outcomes of the cnn models with the suggested model. therefore, after training, validating, and testing the proposed model, they compared the results to original cnn architectures like vgg16 [22], vgg19, densenet, xception, and mobilenet [23]. 8. the final step is showing the result. after the data has been compared, tables and graphs will be displayed for comparison. fig. 1 implementation process flow table 1 shows cnn models which are used to prepare for the training. there are many cnn models provided, but the models are selected because of the high results in the training process. the table reveals the pros and cons of each model. in addition, the parameter part shows the popularity and usage of that model based on keras’s statistics. table 1 list of deep learning models deep learning model #parameters key features with pros and cons vgg16 138.4 m popular, lightweight, and easy to use with high accuracy. vgg19 143.7 m similarity to vgg16 but with 19 layers deep. high accuracy and great understanding of shape, color, and structure. mobilenet 4.3 m consider the depth-wise separable convolution concept. reduced parameters significantly. xception 22.9 m a depth-wise separable convolution approach. densenet201 20.2 m dense connections between the layers. reduced number of parameters with better accuracy. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 197 3.2. dataset the tomato leaf disease dataset is collected from the open source kaggle platform, the folder named plantvillage, including 2,064 images taken corresponding to 3 diseases and one healthy, including (early blight, yellow curl, septoria, and healthy). the data set is divided into three sets with a ratio of 60-20-20 corresponding to the training set-validation set-test set. the dataset has an individual image size of 256 × 256 pixels, as mobilenet takes the form of static square images [21]. a list of image numbers is described in table 2, and the illustration of the leaf image stands for the leaf status in fig. 2. (a) healthy (b) early blight (c) septoria (d) yellow curl fig. 2 some samples of each status of the tomato leaf before implementing section training, the authors pre-processed the image by visualizing, dividing the image size by 255, and then applying the data augmentation method to generate more new images. data augmentation has seven techniques applied to generate new images, including rotation, zoom, shear, width shift, height shift, horizontal flip, and vertical flip. after generating images, the datasets increase significantly, twice as much as the original dataset, and the difference between datasets is low. eligible to apply to model and fine-tuning. table 2 classes of tomato’s leaf image and its usage in learning class category number of images images after data augmentation images used for the training set (60%) images used for validating set (20%) images used for the testing set (20%) early blight 504 1008 605 201 202 septoria 528 1056 633 212 211 yellow curl 507 1014 608 202 204 healthy 525 1050 630 210 210 total 2064 4128 2476 825 827 3.3. the proposed mobilenet this study used mobilenet transfer learning techniques and fine-tuning methodologies to categorize color photos under ideal lighting circumstances, including early blight, septoria, yellow curl, and healthy leaves. as revealed in fig. 3, the mobilenet employs depthwise separable convolution (dsc) to reduce the number of computations, the number of parameters, and the ability to perform feature extraction on different channels independently. five popular dl models, namely vgg16 [22], vgg19, densenet, mobilenet [23], and xception, were used to build an accurate automated model for general purpose and trained on a diverse set of examples, such as imagenet with 1000 classes. in addition, in some studies, for example, coulibaly et al. [18] proposed to use vgg16 to classify and identify many individual plants together on a dataset, plantvillage dataset for these dilated cnn networks to improve accuracy. therefore, those models are expected to provide promising performance in disease detection on tomato leaves. the dilated convolution expands the kernel’s field of view while maintaining the same computational complexities by inserting “holes” or zeros between the kernels of each convolutional layer. as a result, it can be used for applications that require a wide field of vision but cannot support larger kernels or many convolutions. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 198 fig. 3 transfer learning model to classify diseases when working with sparse data, dilated convolution can be advantageous because it allows for more expansive receptive fields without introducing extra parameters. in addition, dilated convolution can reduce overfitting in a neural network by reducing the number of parameters that need to be learned. however, dilated convolution can be slower to train than traditional convolution because it requires more computation. furthermore, dilated convolution may be less effective for small kernel sizes because it decreases the number of parameters learned in a given layer. the scenario of dilated convolution in the 1d field is as: [ ] [ ] [ ] 1 . h h m i x i r h w h = = + (1) for explanation, in every location, the output is �. moreover, ���� is the input signal where x is also referred to as a feature map. besides, ��ℎ� spatial dimensions were filtered with the length ℎ, � corresponding to the dilation rate with which the authors sample the input signal ����. in the standard convolution, � 1. the dilated convolution rate is always bigger than 1. an intuitive and straightforward method to comprehend dilated convolution is that push �� � 1 zeros between every two consecutive filters in the standard convolution. in a standard convolution, the kernel or filter size is � � �, then in the resulting dilated convolution, the filter or kernel size is �� � �� where the value can be found by empirical estimation �� � � �� � 1 � �� � 1 . one of the main reasons to use this method is that 1-dilated convolutions allow for exponentially expanding receptive fields without sacrificing coverage or resolution. dilated convolutions can be used to adjust the effective receptive field of a convolutional layer without changing the kernel size. on the other hand, modify the spacing between the filter’s sampling positions within the input. by introducing gaps or skips between the filter elements, dilated convolutions increase the effective receptive field without changing the kernel size. fig. 4 depicts the architecture, the first of the pre-trained mobilenet model in a workflow for disease recognition on the tomato tree. mobilenet was designed to provide a small, low-latency, computationally sound model for embedded mobile vision applications. convolutional operations in mobilenet are classified into three types: standard convolution, pointwise advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 199 convolution, and depthwise convolution. to implement the dilated convolution. the authors use five depthwise layers, each with its stride rate (2,2). the first two depthwise layers have a dilation rate of (1,1); however, the third and fourth layers have a dilation rate of (2,1) or (2,2). furthermore, the authors concatenate three parallel depthwise 2d convolution layers with dilation rates of 4, 8, and 16 for the final depthwise layer. the process continues concatenating these three depthwise convolutional 2d layers to create the fifth depthwise convolutional 2d layer. initially, every depthwise layer of mobilenet had a dilation rate = 1, but implementing different dilation rates in distinct depthwise layers of mobilenet architecture is novel. now it is time to start proposing this approach. fig. 4 an illustration of mobilenet architecture to identify and classify diseases transformational learning applies past model knowledge to the current situation. the authors apply transformational learning when the provided dataset does not contain enough data to train a full-scale model from the start. instead, previously trained mobilenet model parameters are utilized in the training procedure. as a result, transfer learning uses the model’s existing classes rather than retraining it from the start, boosting its accuracy. the mobilenet model is now enhanced with a new fully connected layer and an output layer with a softmax classification function for diseases in tomato leaf classification. fine-tuning: the process continues to refine after using transfer learning, and the results will improve. fine-tuning uses a trained network model to perform a comparable task for a specific task. usually, the model’s initial layers are frozen (i.e., default and unchanged). the weights of these classes are not changed during training. these layers can perform low-level information extraction; this skill is acquired through prior training. the solution is to continue to tweak the hyperparameters during the fine-tuning phase to help the model achieve the highest accuracy while avoiding overfitting or underfitting. in this fine-tuning section, the authors have fine-tuned the following hyperparameters: (i) dropout: dropout is a regularization technique used in dl to prevent a model from overfitting. during training, a specific percentage of the nodes in a neural network are randomly dropped out (recommend from 0.2 to 0.5). (ii) learning rate: the learning rate is a hyperparameter that controls how quickly the model’s parameters are updated during training iterations. it is an essential hyperparameter since it considerably impacts model performance (should be from 0.00001 to 0.0001). (iii) hidden layer: a hidden neural network layer is neurons not directly connected to the input or output layers. because its values are not directly visible in the input or output data, it is referred to as a “hidden” layer. (the study evaluates the number of units in the hidden layer from 1024 down to 512, 256, 128, etc.) advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 200 (iv) batch size: the batch size is the number of samples used to update the model’s parameters during each round of training. it is a crucial hyperparameter that can affect the training speed and the model’s performance. (it should be 8, 16, 32, or 64). (v) epoch: an epoch is a complete pass of the entire training dataset during the training process. it is a critical hyperparameter that can affect model correctness and training time. (epochs can be 10 times or 20, or 30 times depending on how long the training is). the following hyperparameters are used during tuning: first, the number of training intervals is evaluated with a value of 20-25-30 to determine the appropriate time threshold. next, the batch number size is tested with values ranging from 1632-64, with the default batch number being 32. finally, the hidden layer is tested with [1024, 512, 256], [512, 128], and the learning rate is tested with [0.001], [0.0001], and [0.00001]. each model training implementation will only change one of the hyperparameters described above to avoid overfitting and make them easy to manipulate. members of the group are working to refine those hyperparameters further. adjusting the batch size is to use how much data each time has been calculated and update the coefficient. the larger the batch size, the more vectorization the application can be calculated. when fine-tuning the number of epochs, it only performs more or less traversal in a single train. in case the result is underfitting, which leads to the need to increase the complexity of the model (increase the number of hidden layers and the number of nodes of that layer) along with increasing the number of epochs. if the result is overfitting, the solution is to insert more datasets, perform data augmentation, and refine the dropout coefficient to remove a few percent. 4. experiments 4.1. environmental settings the experiments were implemented on google colab with 12 gb of ram and an nvidia k80 gpu with 12 gb of gddr5 vram. the proposed model was trained using 30 epochs and a batch size of 32. the specifications of the google colab are shown in table 3. table 3 google colab proposed specification parameters google colab cpu model name intel(r) xeon(r) cpu frequency 2.30 ghz no. cpu cores 2 cpu family haswell available ram 12 gb disk space 25 gb 4.2. overall evaluation this study divided the data set into three sets for model evaluation, using a ratio of 60-20-20 for training, validation, and testing, respectively, with accuracy, loss, and f1-score metrics. the authors show that the validation set aims to select the best model to apply to the test set. first, the authors compare the proposed model mobilenet, with well-known cnns to compare the results with mobilenet, vgg16, vgg19, densenet, and xception. the research conducted three experiments in this study. scenario 1 used data from two categories: 1 of tomato leaf diseases (examples below are an early blight, yellow curl, or septoria with healthy leaves). the proposed model was then trained, evaluated, and tested. next, compare the results of the proposed model with the results of other mobilenet and cnn models. then, continue to alternately compare healthy leaves with each other disease, including yellow curl and septoria. scenario 2 was performed similarly but with three data types: early blight, septoria, and yellow curl, and the last thing is to compare the proposed model with the most advanced methods. finally, the data set is trained using the mobilenet model in two stages: transfer learning and fine-tuning. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 201 scenario 1 includes the following sequences: first, the study collects data from a pair of types present in the dataset, early blight/septoria/yellow curl and healthy leaves. then, the training is performed, analyzed, and tested with the provided model. finally, the study compares the results of the proposed model to those of different cnn designs. the goal of presenting scenario 1 aims to evaluate how the proposed model differentiates between healthy leaves and those displaying indications of early blight, septoria, or yellow curl. the accuracy, f1-score, and confusion matrix metrics are used to evaluate the test results. scenario 2 includes the following sequences: the scenario collects four disease types of early blight, septoria, yellow curl, and healthy leaf classes for multi-class classification tasks. first, the proposed model is modified with the number of outputs to be trained, evaluated, and tested on multi-class classification tasks. then, the proposed model's results are compared to other cnn designs. the aim of performing this scenario is to predict and classify classes against each other accurately. therefore, the authors want to test the classification capacity of the proposed model between early blight, septoria, yellow curl, and healthy leaf. 4.3. scenario 1 – discriminate each disease with healthy (1) discriminate early blight and healthy leaves in this experiment, the study used the same hyperparameters used for all models, including an epoch value of 30, a learning rate value of 0.0001, a batch size of 32, and a weight decay of 0.01. the hidden layer includes 1024 neurons. in addition, four layers, including platten, batch normalization, dense classes with activation gaussian error linear unit (gelu), and softmax are added. scenario 1, including training and testing results, is shown in table 4. table 4 the classification results of early blight and healthy leaves training set validation set test set model accuracy loss accuracy loss accuracy f1-score proposed model 0.9951 0.0434 1.0000 0.0097 0.9868 0.9873 densenet 0.9570 0.0945 0.9516 0.3832 0.9517 0.9516 vgg16 0.9282 0.0227 0.9234 0.1175 0.9287 0.9282 vgg19 0.9145 0.0684 0.9154 0.1542 0.9133 0.9182 xception 0.8661 0.0807 0.8934 0.1023 0.8662 0.8660 mobilenet 0.7885 0.0354 0.8124 0.0416 0.8647 0.8434 the training and validation curves for accuracy and loss are shown in fig. 5. transfer-learning machine-learning techniques provide training accuracy of up to 95 percent, compared to 98 percent for fine-tuning techniques. following training, it is evaluated with the previously indicated split test set, yielding the confusion matrix model shown in fig. 6. (a) the pre-trained mobilenet without fine-tuning accuracy (b) the improved mobilenet accuracy fig. 5 the classification results of early blight and healthy leaves: training and validation performance in accuracy and loss during epochs advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 202 (c) the pre-trained mobilenet without fine-tuning loss (d) the improved mobilenet loss fig. 5 the classification results of early blight and healthy leaves: training and validation performance in accuracy and loss during epochs (continued) from the illustration of figures and confusion matrix in scenario 1 (discriminate early blight), the result showed that the training process of the proposed model achieves a promising result. moreover, the predictive results of the two types in the test kit achieved an accuracy of 98.57% for early blight and an accuracy of 99.5% for healthy leaves. these results prove that the proposed model can classify early blight and healthy leaves. both results achieved more than 90% accuracy. fig. 6 confusion matrix of scenario 1 (discriminate early blight) (2) discriminate yellow curl and healthy leaves in this experiment, the authors used the same hyperparameters used for all models in it, including epoch’s value is 30, learning rates value is [0.0001], batch sizes were also tested at [32], weight decay within the at [0.01] and hidden layers tested value which are [1024]. in addition, four additional layers are included, including platten, batch normalization, dense classes with activation gelu, and software. the training and testing results are shown in table 5. table 5 the classification results of yellow curl and healthy leaves training set validation set test set model accuracy loss accuracy loss accuracy f1-score proposed model 0.9857 0.0024 0.9905 0.0010 0.9857 0.9905 densenet 0.9570 0.0945 0.9516 0.0383 0.9517 0.9516 vgg16 0.9282 0.0227 0.9234 0.1175 0.9287 0.9282 vgg19 0.9145 0.0684 0.9154 0.1542 0.9133 0.9182 xception 0.8661 0.0807 0.8934 0.1023 0.8662 0.8660 mobilenet 1.0000 0.0101 0.7885 0.0416 0.8347 0.8654 the training and validation curves for accuracy and loss are shown in fig. 7. transfer-learning machine-learning techniques provide training accuracy of up to 98 percent, compared to 99 percent for fine-tuning techniques. following training, it is evaluated with the previously indicated split test set, yielding the confusion matrix model shown in fig. 8. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 203 (a) the pre-trained mobilenet without fine-tuning accuracy (b) the improved fine-tuned mobilenet accuracy (c) the pre-trained mobilenet without fine-tuning loss (d) the improved mobilenet loss fig. 7 the classification results of yellow curl and healthy leaves in accuracy and loss during epochs from the illustration of graphs and confusion matrix in scenario 1 (discriminate yellow curl virus), the training process of the proposed model achieves a promising result. furthermore, the predictive results of the two types in the test set achieved an accuracy of 99.52% for the yellow curl virus and an accuracy of 99.05% for healthy leaves. these results prove that the proposed model can classify early blight and healthy leaves. both results achieved more than 90% accuracy. fig. 8 confusion matrix of scenario 1 (discriminate yellow curl virus) (3) discriminate septoria and healthy leaves in this experiment, the authors used the same hyperparameters used for all models in it, including epoch’s value is 30, learning rates value is [0.0001], batch sizes were also tested at [32], weight decay within the at [0.01] and hidden layers tested value which are [1024]. in addition, four additional layers are included, including platten, batch normalization, dense classes with activation gelu, and software. the training and testing results are shown in table 6. the training and validation curves for accuracy and loss are shown in fig. 9. transfer-learning machine-learning techniques provide training accuracy of up to 95 percent, compared to 97 percent for fine-tuning techniques. following training, it is evaluated with the previously indicated split test set, yielding the confusion matrix model shown in fig. 10. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 204 table 6 the classification results of septoria and healthy leaves training set validation set test set model accuracy loss accuracy loss accuracy f1-score proposed model 0.9422 0.0363 0.9443 0.0148 0.9818 0.9905 densenet 0.9372 0.0945 0.9383 0.3632 0.9335 0.9316 vgg16 0.9032 0.0227 0.9021 0.5175 0.9076 0.9057 vgg19 0.9279 0.0323 0.9164 0.4789 0.9265 0.9188 xception 0.8366 0.0607 0.8934 0.1223 0.8536 0.8343 mobilenet 0.9452 0.011 0.9023 0.1024 0.9507 0.9576 (a) the pre-trained mobilenet without fine-tuning accuracy (b) the improved mobilenet accuracy (c) the pre-trained mobilenet without fine-tuning loss (d) the improved mobilenet loss fig. 9 the classification results of septoria and healthy leaves in accuracy and loss during epochs from the illustration of graphs and confusion matrix in scenario 1 (discriminate septoria), the training process of the proposed model achieves a promising result that archived more than 90% accuracy. in detail, the predictive results of the two types in the test set achieved an accuracy of 99.01% for the yellow curl virus and an accuracy of 99.54% on healthy leaves. these results prove that the proposed model can classify early blight and healthy leaves. furthermore, both results achieved more than 90% accuracy. fig. 10 confusion matrix of scenario 1 (discriminate septoria) advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 205 4.4. scenario 2 – classification of 4 classes: early blight, septoria, yellow curl, and healthy this scenario retains the same hyperparameters as in scenario 1, including adding and deleting dense layers and performing mass normalization. the study trained the model in transfer learning and fine-tuning to compare the mobilenet results to those of other cnn models. the hyperparameters utilized in the models are the same for both stages and models from the same group. the outcomes of this scenario are presented in table 7, fig. 11 and fig. 12. the results show that the mobilenet model with the proposed architecture beat the other cnn architectures by around 95%. the accuracy and loss during training in scenario 2 are displayed in fig. 11. fig. 12 reveals the confusion matrix for the third case. table 7 classification results of 4 classes: early blight, septoria, yellow curl, and healthy training set validation set test set model accuracy loss accuracy loss accuracy f1-score proposed model 0.9348 0.0363 0.9443 0.0148 0.9717 0.9442 densenet 0.9353 0.0945 0.9383 0.3632 0.9335 0.9316 vgg16 0.9038 0.0227 0.9021 0.5175 0.9076 0.9057 vgg19 0.9279 0.0323 0.9164 0.4789 0.9265 0.9188 xception 0.8376 0.0607 0.8934 0.1223 0.8536 0.8343 mobilenet 0.9464 0.011 0.9023 0.4404 0.7907 0.7176 (a) the pre-trained mobilenet without fine-tuning accuracy (b) the improved mobilenet accuracy (c) the pre-trained mobilenet without fine-tuning loss (d) the improved mobilenet loss fig. 11 performance of accuracy and loss training in scenario 2 in detail, the predictive results of the four types in the test set achieved an accuracy of 95.19% for early blight, 96.78% for yellow curl virus, 97.41% for septoria, and the accuracy of 97.5% for healthy leaves. these results prove that the proposed model can classify early blight and healthy leaves. both results achieved more than 90% accuracy. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 206 fig. 12 confusion matrix of the proposed method in scenario 2 4.5. discussion through the two scenarios that were run, the results revealed that every prediction case had more accurate results than 90%; this was the level of accuracy that the author desired and was surpassed by the actual outcomes. in scenario 1, the results of discriminating between early blight and healthy cases are close to 100%. there is almost no confusion in the machine learning process. furthermore, the classification between yellow curl virus and healthy cases and the tasks of discriminating between septoria and healthy samples also exhibits similar performance. because two diseases, including septoria and yellow curl virus, are more challenging to recognize than early blight, the results are somewhat not as high as early blight. fig. 13 transfer learning model results on different scenario experiments with various metrics in scenario 2, the implementation of training three diseases and healthy cases can be more complicated, and the implementation time might also be longer. this is the promising result of the proposed model in distinguishing some specific diseases on tomato leaves. all the accuracy, validation accuracy, test accuracy, and f1-score calculated of the proposed model in two scenarios are summarized in fig. 13. the experimental results show promising results when training, testing, and evaluating the proposed model in two scenarios suitable for plant disease detection. as observed in scenario 2, the proposed model achieves 97.17% accuracy when predicting three classifications, and the f1-score accuracy is 0.9442 on the testing set. in addition, the accuracy score achieves higher when there is sufficient accuracy in one classification, with more than 99.68% accuracy in the first scenario (early blight), more than 98.57% in the first (yellow curl), and more than 98.18% in the first scenario (septoria). advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 207 the cumulative match curve (cmc) is also used to illustrate the comparison of the proposed model with other architectures in another view with the x−axis to a constant value of rank and the y−axis for the recognition rate. the curve getting up and then moving to the top of the right side is the best system. the cmc curve plays an essential part in evaluating. it judges the ranking capabilities of an identification system. the results shown in fig. 14 show that the proposed method gives the best and most stable prediction results. fig. 14 the cmc in the architecture’s comparison on the test set based on the experimental findings above, the proposed model is appropriate for diagnosing various illnesses on tomato leaves using color images compared to the previous study as presented in table 8. the results show that the proposed model (improved mobilenet) outperforms most recently published efforts on identifying disease signals in tomato plants. furthermore, based on the test results, the machine learning process on the cnn mobilenet model gives a positive and promising result. table 8 comparative analysis of the proposed mobilenet model with state-of-the-art methods references dataset model result accuracy result bhagwat et al. [3] plantvillage dataset support vector machine 91.5% durmus et al. [8] plantvillage dataset fine-tuned squeezenet 94.30% fine-tuned alexnet 95.65% adhikari et al. [10] imagenet (colored images) insprired by alexnet and yolo 92.61% tm et al. [14] plantvillage dataset fine-tuned lenet 94-95% coulibaly et al. [18] imagenet (rgb) fine-tuned vgg16 95.00% ashwinkumar et al. [19] plantvillage dataset fine-tuned mobilenet based with omncnn improved 98.7% kaya and gursoy [20] plantvillage dataset fine-tuned densenet 98.17% proposed model plantvillage dataset fine-tuned mobilenet 97.17% 5. conclusion this study fine-tuned mobilenet to classify several common tomato leaf diseases. there are a few of the significant repercussions of the influence of bacteria, viruses, fungi, etc., that can damage the quality and productivity of tomato plants during the season. the results of the training model have significantly improved in comparison to previous studies. in addition, the authors may determine which combination strategy provides the highest potential performance for the situation. positive results were obtained with the revised model mobilenet, achieving a result of 98%. the proposed model performs better in both circumstances than the other models. advances in technology innovation, vol. 8, no. 3, 2023, pp. 192-209 208 in future research, the work is expected to adapt and apply different data preparation strategies to improve the prediction model outputs further. furthermore, research is being conducted to evaluate various preprocessing approaches to tomato leaf pictures. by enhancing the data, the data-enhancement strategy not only improves the model’s performance but also expands the range of diseases that the model can predict. the authors realize that this study still has shortcomings, and at the same time, some points have yet to be exploited, in particular, the limitation is in the diversity of tomato leaves diseases dataset because the environment provided is not enough to perform training on many types of tomato. in the future, the research plan will continue to be carried out. this model can be applied in real-time and used on mobile devices. conflicts of interest the authors declare no conflict of interest. references [1] s. m. hassan, a. k. maji, m. jasiński, z. leonowicz, and e. jasińska, “identification of plant-leaf diseases using cnn and transfer-learning approach,” electronics, vol. 10, no. 12, article no. 1388, june 2021. 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[23] a. g. howard, m. zhu, b. chen, d. kalenichenko, w. wang, t. weyand, et al., “mobilenets: efficient convolutional neural networks for mobile vision applications,” https://doi.org/10.48550/arxiv.1704.04861, april 17, 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 5___aiti#8971___206-215 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 quantitative and qualitative characterization of coatings added to low voltage switches leila troudi*, khaled jelassi université de tunis el manar, ecole nationale d'ingénieurs de tunis, lr11es15 laboratoire des systèmes électriques, tunisia received 23 november 2021; received in revised form 13 march 2022; accepted 14 march 2022 doi: https://doi.org/10.46604/aiti.2022.8971 abstract electroplating is one of the most important processes in the manufacturing of switches. coating the conductive parts of switches improves their appearance and increases their durability, even in severe environments. this study proposes a non-destructive testing method to qualitatively and quantitatively characterize coatings added to the conductive parts of low voltage switches (contacts and terminals). the method is based on the injection of a high-frequency signal into a switch using the vector network analyzer (vna). an in-depth analysis of the reflected signal is conducted to characterize the coatings. for the quantitative characterization, a comparison is made between switches that are plated with different coating thicknesses. as for the qualitative characterization, a comparison is made between switches that are manufactured with different types of metals. the results show that each switch type has an electromagnetic signature that varies according to the conductivity and the thickness of the metals used for coating. keywords: electroplating, switches, scattering parameters, vector network analyzer, coatings 1. introduction electroplating is the process of adding a metal coating to a metal [1]. the added coating can improve the metal’s final characteristics, such as its corrosion resistance, surface hardness, friction resistance, surface texture, electrical characteristics, durability, etc. [2-3]. for example, nickel is used for corrosion protection and to enhance wear resistance [4]. it is generally used as an undercoat between the base metal and the added layer of coating to prevent the migration of the base metal to silver and gold coatings [5-6]. silver is used because of its high electrical conductivity and its resistance to corrosion and oxidation [7]. in addition, it can reduce skin effect losses at high frequencies [8]. copper is used because of its high conductivity and its ability to make the surface of the base metal smoother and ready for other coatings [9]. gold is used to increase the lifetime and the stability of electrical performance because it is characterized by excellent resistance to corrosion, even in polluted environments [10]. when it comes to the application of electroplating, manufacturers face many challenges. first, it is difficult to guarantee the final result of electroplating, such as the nature, thickness, and proper application of coatings to the conductive parts of a switch, especially when using noble metals, which increases the manufacturing cost. if the different parts of a switch are assembled and a defect is found, it is difficult, if not impossible, to detect the flaw. another industrial problem is the existence of components in the same production location that have the same exterior appearance but are manufactured with different types of coatings, such as gold-plated copper contacts and gold-plated silver contacts, or with different coating thicknesses, such as a plated component with a 0.6 µm thick gold layer and a plated component with a 1.3 µm thick gold layer. * corresponding author. e-mail address: leila.troudi@enit.utm.tn advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 to overcome these problems, there are many non-destructive testing methods to qualitatively and quantitatively characterize metallic coatings. the most commonly used non-destructive testing methods are magnetic induction, eddy current, and radiometric methods (x-ray fluorescence and backscatter β), which are very expensive [11]. x-ray fluorescence allows the coating thickness to be measured with high precision, but it is very expensive [12]. this method is applied to coatings whose atomic number is greater than or equal to 11 [13]. backscatter β is applied when the difference between the atomic number of the coating and that of the substrate is greater than 20% [14]. this is the case for copper (z = 29), gold (z = 79), and silver (z = 47), but the measurements become complicated when nickel (z = 28) is used as an undercoat. magnetic induction is used to measure non-magnetic coatings on ferrous substrates and magnetic coatings on non-magnetic substrates [15]. it is applied to measure thicknesses between 0.001 mm and 1 mm [16]. eddy current methods are applied to measure the thickness of non-conductive coatings on non-magnetic metallic substrates [17]. there are also destructive testing methods, such as microscopic analysis (optical microscopy or electron microscopy). these require the implementation of transverse cuts at the level of the conductor to be diagnosed. then, the sections are analyzed using an optical system (optical microscope or scanning electron microscope) to obtain the appropriate magnification to determine the nature and thickness of coatings [18]. all the methods mentioned above for the characterization of coatings are only applied off the production line and make the final product unusable. this study presents a non-destructive testing method to characterize coatings added to the conductive parts of switches. to apply this method, a very high-frequency signal is injected into the switch to be tested. to ensure the transfer of the high-frequency signal without loss and distortion, the switch is mounted on a printed circuit board that is directly connected to the vector network analyzer (vna). then, the obtained signals (transmitted/reflected) are analyzed for the quantitative and qualitative characterization of coatings added to low voltage switches. 2. description of the proposed solution the proposed method to characterize coatings added to the conductive parts of switches (terminals and contacts) is based on the injection of a high-frequency signal into the device being tested to detect defects. the proposed prototype to carry out the different experimental tests is presented in fig. 1(a). all parts of this prototype are detailed in fig. 1(b). a toggle switch is composed of two terminals, a central support, a movable contact that ensures the opening and closing of an electrical circuit, and a non-conductive housing. all the switches that were used during the experimental tests are shown in table 1. a printed circuit board is formed by three transmission lines that are separated by a well-determined distance, which is equal to the distance between the central support and the terminals to connect the switch to the transmission lines. a subminiature version a (sma) connector is put at the end of each transmission line to connect the board to the vna. during the experimental tests, only two sma connectors were used to make the connection between the printed circuit board and the vna. the third connector is used if one of the sma connectors is damaged. (a) the experimental prototype (b) different parts of the experimental prototype fig. 1 the proposed prototype 207 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 table 1 tested switches bipolar switches unipolar switches number 10 10 10 5 5 9 7 metal used silver (s) gold plated silver (gs) gold plated copper (gc) gc with silver contact (gs silver contact) gs with silver contact (gs silver contact) gc with 1.3 µm gold coating thickness (gc, 1.3 µm) gc with 0.6 µm gold coating thickness (gc, 0.6 µm) the vna is connected to the two transmission lines to inject the high-frequency signal into the switch. it generates a high-frequency signal that is injected into the device undergoing testing, and then detects the reflected and transmitted waves to calculate the s parameters [19]. the s parameters, also called scattering or dispersion parameters, address the main problem of experimental characterization of a two-port network at high frequencies. the determination of classical parameters, such as impedance z, admittance y, and abcd parameters requires short, open circuits, which are very difficult to achieve at high frequencies [20-21]. for a two-port network, four parameters are calculated: s11 (reflection coefficient at port 1), s12 (transmission coefficient from port 2 to port 1), s21 (transmission coefficient from port 1 to port 2), and s22 (reflection coefficient at port 2). the measured s11 parameters are analyzed using an awr design environment that generates and reads touchstone files and plots the obtained results to distinguish between switches manufactured with different types of metals (silver, gold-plated silver (gs), and gold-plated copper (gc)). then, to quantitatively and qualitatively characterize the coatings, the return losses of each switch type are calculated and presented in the form of a boxplot diagram, using matlab. the experimental tests are carried out in a frequency band that varies between 0.01 ghz and 10 ghz. the return losses (rl), given by eqs. (1) and (2) and expressed in decibels (db), describe the power reflected from the incident power by the device being tested [22]. when the reflected power increases, the return losses (db) decrease, and when the reflected power decreases, the return losses (db) increase [23]. if the return losses (db) → ∞, the signal transmission is considered ideal; that is, there is no reflection. the return losses are defined by the following equation: ( ) 10log( )incident reflected p rl db p = (1) the calculation of the return losses using the s11 parameter is expressed as: 10 11 11( ) 20log | | ( )rl db s s db= − −= (2) 3. experimental results: observations and analysis 3.1. comparison between the s11 parameters of the switches the s11 parameters of the silver, gs, and gc switches are compared to qualitatively characterize the switches. fig. 2 and fig. 3 show that the s11 parameters of switches made with the same type of metal have the same curve shape. the curves are relatively similar, particularly the blue curves of the gs switches and the silver switches. each type of switch is characterized by its specific s11 parameters. fig. 2 presents a comparison between the s11 parameters of silver switches and gc switches. in this case, the switches could be distinguished by the silver and gold colors. the measurements of the s11 parameters confirm this distinction through the differences between the s11 parameters of silver switches and those of gc switches at frequencies between 2 ghz and 4 ghz. 208 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 fig. 2 s11 parameters of the silver switches and the gc switches fig. 3 shows a comparison between the s11 parameters of gs switches and gc switches. these switches have the same external appearance and therefore their characterization is very difficult. both types of switches are gold-plated, but their difference can be observed when comparing the s11 parameters, which enables qualitative characterization of the switches without opening or disassembling them. the differences between the s11 parameters are due to the proportional relationship between the reflection losses (s11) and the conductivity of the metals. the conductivity of silver is higher than that of copper, so the reflection losses of silver are greater than those of copper [24]. the curves of the s11 parameters are relatively similar for the gs switches and the silver switches due to the presence of silver in both switches, as shown in fig. 4. the terminals and contacts of the switches are generally made of the same type of metal; that is, both are made of either silver, gs, or gc. in this part, two different types of metals are used in the same switch to determine the influence of this change on the performance of the switches. fig. 5 and fig. 6 show the s11 differences between the gs switches and the gs switches with silver contacts, as well as the s11 differences between the gc switches and the gc switches with silver contacts, respectively. these differences are due to the use of different metals in the same switch. fig. 3 s11 parameters of the gs switches and the gc switches fig. 4 s11 parameters of the silver switches and the gs switches 209 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 fig. 5 s11 parameters of the gs switches and the gs switches with silver contacts fig. 6 s11 parameters of the gc switches and the gc switches with silver contacts fig. 7 s11 parameters of the gc switches with 0.6 µm and 1.3 µm coating thickness fig. 7 shows differences between the s11 parameters of gc switches with a coating thickness of 0.6 µm and gc switches with a coating thickness of 1.3 µm, particularly at frequencies between 8 ghz and 10 ghz. this result indicates that the thickness of the gold layer influences the electromagnetic signature of the switches. 3.2. comparison between the return losses of the switches to identify the causes of the differences between the s11 parameters of the different switches, the return losses of each switch group are calculated using eq. (2). the obtained results are presented in the form of a boxplot diagram, which is a graphical representation of a statistical series and offers a quick and useful way to visualize the data distribution [25]. this graphical representation also allows the identification of measurement errors by symbols. the shapes of the curves are relatively similar, so the obtained signals are divided into several bands to plot the boxplot diagrams and to simplify the calculations. in figs. 8-10, differences in the return losses between switches appear in band 1 (frequency range: 0.01-1.8082 ghz), band 2 (frequency range: 1.8581-2.8072 ghz), band 3 (frequency range: 2.8571-3.5564 ghz), and band 4 (frequency range: 3.6064-4.5554 ghz). the current flows through gold and a small portion of copper or silver because, at high frequency, the current flows through the layer closest to the surface of the conductor. this is the case for the gc switches and gs switches. 210 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 through a simulation using comsol multiphysics, the current distribution is studied for a gc wire. the thickness of the gold layer is 1.3 µm and its boundaries are represented by white lines in fig. 11. at 0.01 ghz and 1 ghz, the simulation results show that the current flows in the gold layer and a small portion of the copper layer, but at 10 ghz the current flows through the gold layer only [26]. this accounts for the differences between bands 1, 2, 3, and 4. in figs. 8-9, the return losses of the gc switches are greater than those of the gs switches and silver switches. at high frequencies, when the conductivity of metal increases, the reflection increases, and the return losses decrease [27-28]. for silver and gs switches, the difference is not very important because the current flows through the silver in the first four bands for both switches, as shown in fig. 10. fig. 8 comparison between the return losses of the gs switches and the gc switches fig. 9 comparison between the return losses of silver switches and the gc switches fig. 10 comparison between the return losses of silver switches and the gs switches 211 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 fig. 11 simulation on comsol multiphysics to study the current distribution in a gc wire from band 5 to band 10, the boxplots of the different switch types overlap. for the qualitative characterization of switches that have the same external appearance, such as gs switches and gc switches, it is sufficient to calculate the return losses in the first four bands, where the frequency varies between 0.01 ghz and 4.55545 ghz. the connection between the movable contact and the terminal ensures the flow of the current through the switch, as shown in fig. 1(b). when a silver contact is used instead of a gc contact for the gc switches, or instead of a gs contact for the gs switches, the return losses show large variation throughout the signal, as shown in fig. 12 and fig. 13. in this case, two different metals (gold and silver) are in contact. these results demonstrate that this contact between two different metals creates significant differences in the return losses of the switches. galvanic corrosion can result from the contact between two dissimilar metals. each metal has a standard electrode potential. to avoid corrosion, the absolute value of the difference between the electrode potentials of two metals in contact should be very small [29]. fig. 12 comparison between the return losses of the gs switches and the gs switches with silver contacts (gs silver contact) fig. 13 comparison between the return losses of the gc switches and the gc switches with silver contacts (gc silver contact) 212 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 fig. 14 comparison between the return losses of the gc switches with 1.3 µm and 0.6 µm coating thickness for example, the standard electrode potentials of copper, silver, and gold are equal to 0.16 v, 0.8 v, and 1.52 v, respectively. the difference between the potentials of silver and gold is 0.7 v and the difference between the potentials of gold and gold is 0.0 v. therefore, the contact between gold and silver affects the electromagnetic signature of the gs switches with silver contacts (gs silver contact) and the gc switches with silver contacts (gc silver contact). moreover, the obtained results could be used to identify the contact type in the assembled switches, especially over bands 2 and 3. in fig. 14, the boxplots of copper switches plated with a 0.6 µm thick gold layer (gc, 0.6 m) and copper switches plated with a 1.3 µm thick gold layer (gc, 1.3 m) are superimposed for frequencies between 0.01 ghz and 8.2018 ghz (from band 1 to band 8). at very high frequencies, because the current only flows through the gold layer, differences appear between the boxplots of the gc switches with 0.6 and 1.3 µm coating thickness in band 9 (frequency range: 8.2517-9.1009 ghz) and band 10 (frequency range: 9.1508-10 ghz). at high frequencies, the thickness of the upper layer of gold must be greater than the skin depth of the metal to avoid losses caused by the skin effect [30]. therefore, the return losses of the gc switches with 1.3 µm coating thickness are greater than those of the gc switches with 0.6 µm coating thickness in bands 9 and 10, where the frequency varies between 8 ghz and 10 ghz. the skin depth is calculated using the following equation: 1 f =δ π σµ (3) where µ is the permeability, σ is the conductivity, and f is the frequency. in bands 9 and 10, the skin depth of gold which is calculated using eq. (3) varies between 0.7 µm and 0.8 µm, and the current flows through the gold layer only. therefore, when the gold coating thickness increases, the reflection decreases, and the return losses increase. 4. summary and conclusions this study presents an industrial non-destructive testing method for the qualitative and quantitative characterization of coatings added to low voltage switches. according to the proposed solution, which is based on the injection of a high-frequency signal into the switch to be tested, the types and thicknesses of coatings influence the electromagnetic signatures of switches. when the conductivity of a metal increases, the reflection increases, and therefore the return losses decrease, which allows the qualitative characterization of switches. at high frequencies, the return losses of switches plated with a 1.3 µm thick gold layer are greater than those of switches plated with a 0.6 µm thick gold layer. the gold coating thickness must be greater than the skin depth of gold, which allows the quantitative characterization of switches. when the coating thickness is less than 0.6 µm, the accuracy of the proposed testing method decreases and the quantitative characterization of switches becomes difficult. 213 advances in technology innovation, vol. 7, no. 3, 2022, pp. 206-215 to summarize, the proposed testing method can be used to characterize coatings added to assembled, new, and used switches. it allows the characterization of coatings added to low voltage switches by the analysis of their reflected signals. to qualitatively characterize switches, the tests are carried out in a frequency range between 2 ghz and 4 ghz. for quantitative characterization, the tests are carried out in a frequency range between 8 ghz and 10 ghz. conflicts of interest the authors declare no conflicts of interest. references [1] a. mahapatro, et al., “modeling and simulation of electrodeposition: effect of electrolyte current density and conductivity on electroplating thickness,” advanced materials science, vol. 3, no. 2, pp. 1-9, august 2018. [2] b. fotovvati, et al., “on coating techniques for surface protection: a review,” journal of manufacturing and materials processing, vol. 3, no. 1, article no. 28, march 2019. [3] m. tyagi, et al., optimization methods in engineering: select proceedings of cpie 2019, singapore: springer, 2020. [4] w. sha, et al., electroless copper and nickel-phosphorus plating: processing, characterization, and modeling, amsterdam: elsevier science, 2016. [5] s. kyeong, et al., electrical connectors: design, manufacture, test, and selection, united states: john wiley and sons, 2021. [6] s. roy, et al., advanced surface coating techniques for modern industrial applications, united states: igi global, 2020. [7] d. lu, et al., materials for advanced packaging, 2nd ed., united states: springer, 2017. [8] j. moreira and h. werkmann, an engineer’s guide to automated testing of high-speed interfaces, 2nd ed., united states: artech house, 2016. 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[26] l. troudi, et al., “the influence of the coating thickness on transmission in electronic devices,” 10th international renewable energy congress, pp. 1-5, march 2019. [27] s. varnaitė-žuravliova, the types, properties, and applications of conductive textiles, united kingdom: cambridge scholars publishing, 2019. [28] a. m. chrysler, et al., “effect of material properties on a subdermal uhf rfid antenna,” ieee journal of radio frequency identification, vol. 1, no. 4, pp. 260-266, december 2017. [29] b. a. omran, et al., a new era for microbial corrosion mitigation using nanotechnology: biocorrosion and nanotechnology, switzerland: springer nature, 2020 [30] h. liu, et al., high-temperature superconducting microwave circuits and applications, singapore: springer, 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 215  advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 side resistance of drilled shafts socketed into rocks for serviceability and ultimate limit states yit-jin chen * , cheng-chieh hsiao, anjerick topacio department of civil engineering, chung yuan christian university, taoyuan, taiwan received 26 april 2019; received in revised form 08 august 2019; accepted 04 october 2019 doi: https://doi.org/10.46604/aiti.2020.4155 abstract this study evaluates the analysis models of side resistance in rock sections by utilizing a wide variety of load test data. available analytical models including the empirical adhesion factor versus the rock’s uniaxial compressive strength and its root are analyzed and compared statistically to determine the optimum relationships. the interpretation criteria for the l1 and l2 methods are used to analyze the load test results for serviceability and ultimate limit states, respectively. the analysis results show that the relationship model with the empirical adhesion factor versus the root of the rock’s uniaxial compressive strength exhibits better correlation than the one with the rock’s uniaxial compressive strength. moreover, the general coordinate axes regression equation demonstrates better reliability than the semi-logarithmic and full logarithmic axes equations for both limit states. based on these analyses, specific design recommendations for the side resistance of drilled shafts socketed into rocks are developed and provided with the appropriate statistics to verify their reliability. keywords: drilled shaft, socketed into rock, side resistance, statistical analysis 1. introduction limited land for building structures frequently lead to the construction of high buildings to save land occupancy. the structures of such buildings are heavy. to stabilize these structures, a deep foundation is often used to transfer the load of the superstructure to the underlying bearing layer. occasionally, a certain length of the pile foundation is embedded into the rock layer to increase the effects of stabilizing the superstructure. among pile foundations, drilled shafts (also called cast-in-place piles, drilled piers, or bored piles) are frequently used as deep foundation because they produce less noise and vibration during construction and meet the required pile diameter and depth. in addition, drilled shafts can provide sufficient lateral support to resist the force of the superstructure from earthquakes and wind loads. when a pile is subjected to an axial load, the load is transmitted along the length of the pile toward the hard soil or rock layer, as shown in fig. 1. pile capacity includes side and tip resistances for resisting axial load. side resistance plays an important role when a pile is socketed into rocks. in the analysis of side resistance, the analysis concept of the shaft in cohesive soil and rocks is the same. in cohesive soil, the total stress analysis method is frequently used to evaluate unit side resistance (fs). the fs value can be computed on the basis of an empirical coefficient (a), which is the adhesion factor between the soil and the shaft, and the average soil undrained shear * corresponding author. e-mail address: yjc@cycu.edu.tw tel.: +886-3-2654227; fax: +886-3-2654299 advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 157 strength (su) over the shaft length. moreover, the α value is related to su, and the initial asu relationship of the drilled shafts was developed by stas and kulhawy [1], as shown in fig. 2. however, the su values in their analysis were obtained from random test types. the su value can be determined from various test types, but the results present an evident difference. therefore, chen and kulhawy [2, 3] later adopted a unique test type for su from the consolidated isotropically undrained triaxial compression (ciuc) test, which is denoted as su(ciuc), the reference plane for a consistent test. the improved aciuc-su(ciuc) relation is illustrated in fig. 3. the data distribution of the improved aciuc-su(ciuc) correlation is superior to that of the previous result shown in fig. 2. these concepts have been expanded to the analysis of side resistance for driven precast concrete piles [4, 5]. fig. 1 axial load resisted by a pile foundation fig. 2 early a-su relation [1] fig. 3 improved aciuc-su(ciuc) relation [2,3] the analysis model of side resistance for drilled shafts socketed into rocks is similar to the conventional total stress analysis in cohesive soil. however, the uniaxial compressive strength (qu) is adopted in rocks instead of the su in cohesive soil. the fs value expressed by using qu or its rootz ( uq ) can be expressed as: su(ciuc)/pa advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 158  s uf q (1)  s uf q (2) accordingly, numerous studies have been conducted and have resulted in various relationships in determining the side resistance value of drilled shafts. kulhawy and goodman [6] recommended an  value of 0.15 and found that the value of qu should be less than 5 mpa. they used eq. (1) to determine side resistance. moreover, several researchers have utilized eq. (2) to determine side resistance during analyses. hooley and brooks [7] studied the friction force of piles in overcompacted clay, soft rock, and weathered rock. they recommended a qu value between 0.25 and 3.0 mpa and an α value of 0.15. the american association of state highway and transportation officials [8] suggested that the qu value should be less than 40 mpa and the α value should be between 0.03 and 0.04. horvath et al. [9] suggested that the qu value should be less than 40 mpa, and the α value should be between 0.2 and 0.3. ku et al. [10] conducted related research on the western soft rock of taiwan and recommended an α value of 0.16-0.21 but did not recommend any value for qu. lastly, yang et al. [11] found that the α value of piles socketed into rocks in northern taiwan is between 0.1 and 0.5, and the relation α versus uq is shown in fig. 4. fig. 4 αuq relationship based on northern taiwan's load tests [11] the aforementioned descriptions indicate that the current relations are based on a few load test data, and the range of the values of α is extremely broad and scattered. thus, the current study was conducted to reassess side resistance for the serviceability limit state (sls) and ultimate limit state (uls) of drilled shafts socketed into rocks. moreover, the various influencing factors were analyzed to provide a reliable design recommendation. 2. database for analysis to evaluate the side resistance behavior of drilled shaft foundations socketed into rock sections, this study collected data from taiwan, turkey, the usa, italy, and singapore [12]. a total of 44 load tests embedded into rocks were obtained, including 28 sandstones, 3 mudstones, 3 limes, 3 soft sandstones, 3 hard shales, 2 tuffs, and 3 amphibolite. in addition, 81 sets of pile load data instruments were used from these load tests. therefore, one load test may consist of several instruments for different rock sections. the average a and qu values were adopted for the analysis of each load test. the collected pile information was accompanied by soil/rock layer information, pile foundation information, load–displacement curve, and load distribution curve along the pile length. table 1 provides the details for the geometries, geotechnical parameters, and interpreted results of these load test data. table 2 lists the statistical summary of these data [12]. u aq , mp advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 159 table 1 geometries, geotechnical parameters, and interpreted results of load test data shaft no. depth, d diameter, b test depth from gl qu fs(l1) 1 fs(l2) 2 (m) (m) (m) (mpa) (mpa) (mpa) tp1 37.6 0.95 28.0~36.0 12.77 0.268 0.63 tp2 42.6 0.95 34.2~41.0 10.01 0.176 0.53 tp3 20.0 1.2 4.0~19.0 0.60 0.063 0.16 tp4 66.0 1.5 61.5~66.0 4.17 0.160 0.59 tp5 25.5 1.5 21.5~25.5 0.20 0.088 0.24 tp6 48.0 1.5 40.0~48.0 1.21 0.095 0.31 tp7 48.0 1.5 40.0~48.0 0.80 0.080 0.25 tp8 53.0 1.5 49.5~53.0 1.03 0.110 0.52 tp9 30.0 1.2 26.4~30.0 2.26 0.070 0.24 tp10 53.5 2.0 37.2~53.3 2.46 0.060 0.22 tp11 54.5 2.0 38.2~54.5 0.34 0.069 0.17 tp12 24.0 0.8 16.7~24.0 0.70 0.018 0.11 tp13 48.0 1.5 47.7~52.0 0.65 0.090 0.13 tp14 47.7 1.2 41.7~47.7 0.16 0.115 0.14 tp15 59.0 1.2 55.8~59.0 3.00 0.110 0.29 tp16 29.0 1.2 24.9~29.0 0.13 0.060 0.16 tp17 45.0 1.2 35.0~42.5 3.47 0.062 0.20 tp18 38.0 1.0 35.0~37.4 13.00 0.150 0.37 tp19 60.4 1.5 58.4~59.8 13.70 0.300 0.58 tp20 48.0 1.5 44.5~48.0 13.64 0.277 1.15 tp21 46.0 0.41 43.4~45.3 2.54 0.160 0.53 tp22 10.0 1.2 2.5~10.0 1.30 0.053 0.21 tp23 9.1 1.2 3.5~9.1 1.60 0.050 0.22 tp24 8.0 1.2 4.5~8.0 1.00 0.050 0.20 tp25 25.0 1.0 15.5~25.5 4.26 0.135 0.53 tp26 17.0 1.8 3.0~16.4 1.70 0.064 0.24 tp27 36.0 1.0 32.9~35.4 1.03 0.092 0.18 tp28 27.5 1.2 25.5~27.0 1.51 0.075 0.47 tp29 22.8 0.8 12.3~22.2 0.52 0.110 0.35 tp30 20.4 0.8 15.5~19.8 1.86 0.111 0.30 tp31 26.4 1.0 16.8~26.8 0.32 0.082 0.23 tp32 8.7 0.7 5.6~8.8 5.00 0.227 0.50 tp33 11.0 0.7 5.6~11.0 5.00 0.40 tp34 18.5 1.2 11.0~18.5 0.90 0.100 0.15 tp35 39.0 1.2 26.0~37.0 3.00 0.046 0.20 tp36 13.5 1.2 11.0~13.5 6.00 0.148 0.42 tp37 7.3 0.7 2.1~7.3 6.82 0.133 0.46 tp38 13.5 1.35 4 .0~10.0 7.00 0.080 0.34 tp39 11.5 1.5 3.5~9.6 7.77 0.088 0.40 tp40 59.0 1.2 54.6~58 0.26 0.050 0.26 tp41 73.0 1.5 67.0~73.0 0.30 0.053 0.15 tp42 76.0 1.3 71.0~76.0 0.45 0.012 0.22 tp43 40.7 2.2 28.5~39.5 0.37 0.026 0.04 tp44 15.0 1.2 2.0~14.5 0.93 0.053 0.14 1 fs(l1) is the unit friction interpreted from l1 method 2 fs(l2) is the unit friction interpreted from l2 method 3. analysis method two methods were used in this study to obtain the side resistance of the drilled shaft foundation. first, the value was directly obtained from the t-z curve, which defines the shear stress–vertical displacement response of the soil at each particular depth. second, the load–displacement curve and the load distribution curve throughout the pile length were utilized. by considering these test results, the interpretation of kulhawy and hirany (called the l1-l2 interpretation) [13] was adopted to construe unit side resistance under various limit states. advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 160 table 2 statistics of load test data for analysis interpretation method n statistical analysis pile geometry qu (mpa)  fs (mpa) pile length d (m) pile diameter b (m) d/b l1 44 range 7.3-76.0 0.41-2.2 6.7-112.2 0.13-13.7 0.011-0.719 0.012-0.50 mean 33.10 1.2 28.13 3.372 0.098 0.104 sd 17.53 0.39 18.35 3.92 0.14 0.078 cov 0.53 0.33 0.65 1.16 1.42 0.75 l2 44 range 7.3-76.0 0.41-2.2 6.7-112.2 0.13-13.7 0.03-1.23 0.04-1.19 mean 33.10 1.2 28.13 3.372 0.277 0.33 sd 17.53 0.39 18.35 3.92 0.31 0.21 cov 0.53 0.33 0.53 1.16 1.12 0.64 this l1-l2 interpretation is a graphical method that utilizes the load–displacement curve. l1 is defined as the endpoint of the initial linear segment. as illustrated in fig. 5, the load and displacement are represented by ql1 and 1l respectively. l2 is the starting point of the final line segment. the load and displacement are represented by 2lq and 2l respectively. an interpretation example based on one of the pile report data is shown in fig. 6. chen and fang [14] studied the l1 and l2 interpretation by using many load test data and established the interrelationships among l1, l2, and several typical interpretation criteria. their analysis showed that l1 = 0.5l2, on average. this finding indicates a factor of safety of 2 if l1 is used for the design. moreover, l1 should be used in sls and l2 should be used in uls. tang et al. [15] recently conducted statistical analyses to evaluate model factors in a reliability-based design for drilled shafts under axial loading with sls and uls. fig. 5 regions of load–displacement curve fig. 6 l1-l2 interpretation of the t-z curve example [12] 4. analysis results 4.1. correlation of α versus qu eq. (1) was used to evaluate the pile load test data for α, and the results of the l1 and l2 interpretations are presented in figs. 7 and 8, respectively, including the average results of the data obtained from 44 single pile reports. unit side resistance was determined using the load–displacement curve or the t–z curve. the data in figs. 7 and 8 were then plotted into three coordinate axes, namely (a) general coordinate, (b) semi-logarithmic, and (c) full logarithmic axes, to determine the optimum trend for each interpretation. the statistical analysis is provided in table 3 to compare the three equations. the statistical results of the coefficient of determination (r 2 ), standard deviation (sd), and coefficient of variation (cov) are also listed in the figures and tables. fsl2 fsl1 displacement, (mm) s o c k e t f ri c ti o n , fs ( k p a ) final linear region transition region initial linar region displacement l o a d advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 161 (a) general coordinate (b) semi-logarithmic coordinate (c) full-logarithmic coordinate fig. 7 a-qu relationships for l1 interpretation (a) general coordinate (b) semi-logarithmic coordinate (c) full-logarithmic coordinate fig. 8 a-qu relationships for l2 interpretation advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 162 table 3 statistical results for a-qu relationships interpretation method coordinate form regression equation n r 2 sd cov l1 general coordinate 0.01 0.07 /  uq 44 0.82 0.06 0.59 semi-logarithmic 0.13 0.08 log( )   uq 0.50 0.10 1.00 full logarithmic log( ) 2.60 0.70 log( )    uq 0.75 0.09 0.87 l2 general coordinate 0.07 0.16 /  uq 44 0.81 0.13 0.45 semi-logarithmic 0.36 0.19 log( )   uq 0.60 0.19 0.66 full logarithmic log( ) 1.43 0.68 log( )    uq 0.79 0.15 0.51 the results of the statistical analyses indicated that the three coordinate axes used in the study caused differences in terms of reliability with each interpretation used. as shown by the results, the general coordinate regression equation has the lowest cov for the l1 and l2 interpretations. therefore, the general coordinate regression equation exhibits higher reliability than the other equations. 4.2. correlation of α versus uq (a) general coordinate (b) semi-logarithmic coordinate (c) full-logarithmic coordinate fig. 9  uq relationships for l1 interpretation the analysis presented in this section is commonly used in determining the side resistance of drilled shafts socketed into rock sections. the difference is that the uniaxial compressive strength was analyzed through its root. the results showed that several discrete data points are scattered, resulted in an inconsistent plot. these data were obtained from piles socketed into mudstone (n = 3) because foundations embedded into mudstone tend to have a greater tip capacity than friction. thus, these data were omitted in this section to obtain reasonable results. the new data were then plotted into (a) general coordinate, (b) semi-logarithmic, and (c) full logarithmic axes, as shown in figs. 9 and 10 for the l1 and l2 interpretations respectively. the advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 163 data were plotted in the three coordinate axes in order to determine the optimum trend for each interpretation. statistical analysis is provided in table 4 to compare the two interpretations used in the study. (a) general coordinate (b) semi-logarithmic coordinate (c) full-logarithmic coordinate fig. 10  uq relationships for l2 interpretation table 4 statistical results for  uq relationships interpretation method coordinate form regression equation n r 2 sd cov l1 general coordinate 0.03 0.06 /  uq 41 0.56 0.03 0.41 semi-logarithmic 0.10 0.05 log( )   uq 0.40 0.04 0.48 full logarithmic log( ) 2.53 0.48 log( )    uq 0.30 0.04 0.48 l2 general coordinate 0.14 0.12 /  uq 41 0.40 0.09 0.36 semi-logarithmic 0.29 0.12 log( )   uq 0.38 0.10 0.37 full logarithmic log( ) 1.34 0.45 log( )    uq 0.39 0.10 0.37 similarly, the general coordinate regression equation has the lowest cov for the l1 and l2 interpretations. therefore, the general coordinate regression equation exhibits higher reliability than those of the semi-logarithmic and full logarithmic coordinates. 4 .3. comparison of  versus qu and uq from the preceding analysis results, the regression equation developed in the general coordinate axes should be used when analyzing drilled shafts socketed into rocks. moreover, in accordance with the cov values computed in the study, the advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 164  uq relationship yielded better correlation than that of α – qu. table 5 provides the comparison of the cov values of the l1 and l2 interpretations of theα – qu and  uq relationships. the  uq relationship resulted in a lower cov than that of the α–qu relationship, providing accurate results for sls and uls. fig. 4 indicates that the current proposed relation between a and uq , and the range of α values is extremely broad and scattered. with the completion of the study, data correlation through analysis was improved, which increased the reliability of its application to sls and uls. table 5 statistical results for αuq relationships interpretation method relationship regression equation n r 2 sd cov l1  uq 0.01 0.07 /  uq 44 0.82 0.06 0.59  uq 0.03 0.06 /  uq 41 0.56 0.03 0.41 l2  uq 0.07 0.16 /  uq 44 0.81 0.13 0.45  uq u0.14 0 q.12 /   41 0.40 0.09 0.36 5. conclusions this study utilized numerous load test data to evaluate the side resistance of drilled shafts socketed into rocks. upon analysis of the test results, the following conclusions were drawn. 1. this study developed α–qu and  uq relationships plotted into three coordinate axes. the three coordinate axes were then compared, and the analysis results showed that the general coordinate axes regression equation exhibited better reliability than the semi-logarithmic and full logarithmic axes equations. 2. the study proved that using the  uq relationship is reliable in the analysis of drilled shafts socketed into rocks for the l1 and l2 interpretations because of its lower cov value than that of the α–qu relationship. the relations recommended in this study also yielded higher reliability than previous ones. 3. to determine sls, the l1 interpretation of the  uq relationship developed in the study using the regression equation, 0.03 0.06 /  uq , is recommended for the developed equation, r 2 = 0.56, sd = 0.03, and cov = 0.41. 4. to determine uls, the l2 interpretation of the  uq relationship developed in the study using the regression equation, u0.14 0 q.12 /   , is recommended for the developed equation, r 2 = 0.40, sd = 0.09, and cov = 0.36. acknowledgments this research work was supported by the ministry of science and technology (most), taiwan, under grant 107-2221-e-033-014. conflicts of interest the authors declare no conflict of interest. references [1] c. v. stas and f. h. kulhawy, “some observations on undrained side resistance of drilled shafts,” foundation engineering, current principles and practices, asce, pp. 1011-1025, 1984. advances in technology innovation, vol. 5, no. 3, 2020, pp. 156-165 165 [2] y. j. chen and f. h. kulhawy, “case history evaluation of drilled shafts behavior,” electric power research institute, palo alto, report tr-104601, p. 356, 1994. [3] y. j. chen and f. h. kulhawy, “evaluation of undrained side and tip resistances for drilled shafts,” proc. soil and rock america, vol. 2, pp. 1963-1968, 2003. [4] m. c. marcos and y. j. chen, “evaluation of side resistance of driven precast concrete piles,” materials science and engineering, iop, vol. 658, no. 1, 012005, 2019. [5] m. c. marcos, and y. j. chen, “applicability of various load test interpretation criteria in measuring driven precast concrete pile uplift capacity,” international journal of engineering and technology innovation, vol. 8, no. 2, pp. 118-132, 2018. [6] f. h. kulhawy and r. e. goodman, foundation in rock, ground engineers reference book, butterworth and co. ltd., 2005. [7] p. hooley and s. r. l. brooks, “the ultimate shaft frictional resistance mobilized by bored piles in overconsolidated clays and socked into weak and weathered rock,” the engineering geology of weak rock, balkema, pp. 447-455, 1993. [8] american association of state highway and transportation official (aashto), standard specifications for highway bridges, 1992. [9] r. g. horvath, t. c. kenney, and p. kozicki, “methods of improving the performance of drilled piers in weak rock,” canadian geotechnical journal, vol. 20, no. 4, pp. 758-772, 1983. [10] c. s. ku, j. weng, x. liu, and x. lin, “study on side resistance of soft rock foundations,” proc. rock engineering symposium, tamsui, pp. 224-231, 2007. [11] z. y. yang, j. q. shiau, j. ching, y. s. lee, and c. j. chen, “side resistance of pile socketed into rock in taiwan area,” proc. rock engineering symposium, kaohsiung, pp. 75-83, 2010. [12] c. c. hsiao, “evaluation of side resistance for drilled shafts socketed into rocks,” master thesis, department of civil engineering, chung yuan christian university, 2018. [13] a. hirany and f. h. kulhawy, “interpretation of load tests on drilled shafts: axial compression,” foundation engineering: current principles & practices (gsp22), asce, new york, pp.1150-1159, 1989. [14] y. j. chen and y. c. fang, “critical evaluation of compression interpretation criteria for drilled shafts,” journal of geotechnical and geoenvironmental engineering, asce, vol. 135, no. 8, pp. 1056-1069, 2009. [15] c. tang, k. k. phoon, and y. j. chen, “statistical analyses of model factors in reliability-based limit state design of drilled shafts under axial loading,” journal of geotechnical and geoenvironmental engineering, asce, vol. 145, no. 9, pp. 04019042-1-19, 2019. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 5-v9n3(2024)-aiti#13689(210-223).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 english language proofreader: chih-wei chang synergistic application of particle swarm optimization and gravitational search algorithm for solar pv performance improvement aditya sharma*, dheeraj kumar palwalia department of electrical engineering, rajasthan technical university, kota, india received 06 may 2024; received in revised form 29 june 2024; accepted 01 july 2024 doi: https://doi.org/10.46604/aiti.2024.13689 abstract this study aims to optimize photovoltaic systems by developing a novel hybrid metaheuristic approach for maximum power point tracking (mppt). the proposed method eclectically combines particle swarm optimization (pso) and gravitational search algorithm (gsa) to overcome individual limitations and leverage complementary strengths. pso, while surpassing in exploration, may suffer from premature convergence. gsa demonstrates strong exploitation capabilities but can struggle with slow convergence. a simulation model is developed to evaluate the hybrid algorithm’s performance in optimizing pv systems’ duty cycle. the approach utilizes the exploitation capabilities of pso and gsa to navigate the search space effectively. results demonstrate that the hybrid algorithm outperforms traditional techniques and standalone metaheuristics, achieving improved convergence time, faster settling time, and enhanced mppt tracking efficiency. under varying irradiance conditions, the proposed method consistently delivers higher power generation and improved overall pv system efficiency, offering a promising solution for optimizing pv systems and maximizing energy generation. keywords: gravitational search algorithm (gsa), particle swarm optimization algorithm (pso), maximum power point tracking (mppt), photovoltaic (pv) system 1. introduction in the face of escalating energy demands and growing concerns over environmental sustainability, harnessing renewable energy sources has become a global imperative. solar photovoltaic (pv) systems, which transform sunlight into electrical energy, have been necessitated [1]. pv systems offer a clean, renewable, and sustainable source of energy, embodying their inherent importance in the transition towards a greener and environmentally-friendly future. pv systems rely on solar panels, which are composed of interconnected pv cells that absorb sunlight and generate electrical current [2]. however, the effectiveness of these schemes is influenced by various environmental factors, such as solar irradiance, temperature, and shading conditions. to maximize the power output from solar pv systems, advanced maximum power point tracking (mppt) techniques underscore functional indispensability [3-4]. mppt algorithms continuously adjust the operating point of the pv system to ensure the system operates at the maximum power point (mpp), thereby extracting the highest possible power from the solar panels under varying conditions [5]. several mppt methods are widely deployed, such as perturb and observe (p&o) and incremental conductance (ic), while effective in certain scenarios, often struggle to cope with rapidly changing environmental conditions or complex system dynamics [6]. to address these limitations, researchers have explored the application of metaheuristic optimization * corresponding author. e-mail address: asharma.phd17@rtu.ac.in advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 211 algorithms for mppt in pv systems [7]. these algorithms, inspired by natural phenomena or biological processes, offer robust and effective solutions for complex optimization problems [8]. two prominent algorithms, the have attracted attention in the field of mppt, are the particle swarm optimization (pso) and the gravitational search algorithm (gsa). the pso algorithm is a population-based optimization technique that emulates the collective behavior observed in bird flocking or fish schooling. technically the pso commences by initializing a swarm of particles, where each particle represents a potential solution to the problem [9-10]. the pso iteratively updates the positions and velocities of the particles based on their respective best solutions and the globally optimal solution found by the entire swarm. this approach has demonstrated effective exploration capabilities, enabling the pso to efficiently navigate the search space and identify promising regions of interest. on the other hand, the gsa draws inspiration from the principles of newtonian gravity and mass interactions [11]. the gsa initializes a population of agents, conceptualized as masses, and iteratively adjusts their positions based on the gravitational forces exerted by other agents within the population. the gsa has attested to its potency of optimization, offering robust exploitation capabilities and the ability to converge towards optimal solutions efficiently by capitalizing on the attractive forces between agents. both pso and gsa have shown promising results in mppt applications, each algorithm has its strengths and limitations. the pso excels in exploration but may struggle with premature convergence or stagnation in complex search spaces [12]. despite the effectiveness of pso in mppt, the algorithm can incur steady-state oscillations, thereby impacting system stability [13]. traditional pso algorithms might fail under partial shading conditions without significant modifications to improve accuracy and convergence speed [14]. conventional pso methods exhibit steady-state oscillations and slow tracking under fickle environmental conditions [15]. classical pso techniques have high oscillations around the mpp and slower convergence times under dynamic weather conditions [16]. the traditional pso approach suffers from lower accuracy and speed, particularly under partial shading scenarios [17]. conversely, gsa demonstrates strong exploitation capabilities but may suffer from slow convergence or lack of diversity in certain scenarios [18]. while implementing gsa, potential issues with convergence speed and accuracy in certain shading conditions should be considered [19]. despite its effectiveness, the combination of gsa with other algorithms, such as the traditional p&o method, introduces complexity and potential inefficiencies in certain conditions [20]. additionally, the integration of gsa with pso may hinder the practicability with increased computational complexity [2122]. to overcome these drawbacks and leverage the complementary strengths of both algorithms, a proposed hybrid metaheuristic approach that combines pso and gsa is introduced. by integrating the exploration capabilities of pso with the exploitation strengths of gsa, these hybrid algorithms aim to strike a balance between global search and local refinement, potentially facilitating improved performance and faster convergence toward optimal solutions. the proposed hybrid particle swarm optimization and gravitational search algorithm (hpso-gsa) algorithm, which is presented in this research, integrates the principles of pso and gsa to optimize the duty cycle solutions for pv systems. in this hybrid method, a swarm of particles is initialized to represent potential solutions. the pso component directs the particles towards promising areas, while the gsa component calculates gravitational forces and masses to enhance the exploitation of optimal solutions. the algorithm updates the velocities and positions of particles by combining pso and gsa equations, attaining a balanced approach between exploration and exploitation. by leveraging the strengths of both pso and gsa, the hpso-gsa algorithm aims to surpass the limitations of individual algorithms, furnishing a more robust and efficient optimization framework for mppt in pv systems. this hybrid approach is expected to outperform traditional optimization techniques and single metaheuristic algorithms, resulting in higher power generation and improved efficiency under various operating conditions. 212 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 this paper is structured to commence with an exploration of mppt in section 2. section 3 discusses pso, while section 4 covers the gsa. a novel hpso-gsa method is introduced in section 5, aiming to enhance optimization efficiency. empirical results and discussions of this method are presented in section 6, demonstrating its comparative advantages with conclusions in section 7 with a summary of findings. 2. maximum power point tracking mppt is an essential technique used in solar pv systems to optimize power output and enhance system efficiency. mppt algorithms continuously adjust the operating point of the pv system to the mpp, ensuring maximum power extraction from the solar panels under varying conditions [23]. a solar power system, as illustrated in fig. 1, employs a hybrid mppt strategy using the gsa and pso. the system’s core comprises a pv array that converts solar energy into electrical power, which is characterized by its voltage (vpv) and current (ipv). this power is subsequently fed into a dc-dc boost converter, which increases the pv array’s voltage to a suitable level for the load [24]. the boost converter consists of an inductor (l) for energy storage, a diode (d) to prevent current backflow, and a capacitor (c) to smooth the output to the load. a transistor acts as a switch, toggling on and off rapidly, controlled by a pulse width modulation (pwm) signal. this pwm signal, which is modulated by the mppt algorithm, is crucial for the boost converter’s operation. fig. 1 block diagram of pv system with mppt the duty cycle (d) of the boost converter is the ratio of the time the switch is closed (��n) to the total switching cycle time (t), as shown in: = ont d t (1) the output voltage (����) and input voltage (���) are defined in: 1 = − in out v v d (2) to find the duty cycle, the above equation is rearranged: 1= − in out v d v (3) the system is designed to ensure that the maximum possible power is extracted from the pv array and delivered to the load efficiently, notwithstanding changes in sunlight intensity or temperature. this dynamic adjustment is key to maintaining system efficiency and is the primary function of the mppt algorithm informed by the intelligent combination of gsa and pso methodologies. the parameters used for this mppt design are shown in table 1. advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 213 table 1 pv array system parameters parameters values max. power 55 w open circuit voltage voc (v) 21.7 v short circuit current isc (a) 4.8 a voltage at maximum power point vmp (v) 15 v current at maximum power point imp (a) 3.7 a input capacitor ( ��) 470e-6 inductor (l) 1.2e-3 capacitor (c) 47e-6 load resistance (r) 100 ω fig. 2 delineates two graphs that depict the performance of a solar pv system under different levels of irradiance. the top graph is the i-v (current-voltage) curve, and the bottom graph is the p-v (power-voltage) curve. these graphs illustrate how the current and power output from a solar pv system change with voltage across various irradiance levels, ranging from 400 w/m2 to 1000 w/m2. as irradiance increases, both the current and voltage, at which the panel operates, also increase, facilitating higher current for a given voltage due to profuse solar energy. similarly, higher irradiance leads to greater maximum power output, with the peak of each p-v curve representing the mpp. the mpps, marked with circles on the p-v curves, indicate where the solar panel operates most efficiently. mppt controllers aim to keep the panel operating at these points to maximize power extraction. fig. 2 pv and iv curve for solar module 3. particle swarm optimization the pso algorithm is a robust computational method designed to optimize complex problems by simulating social behaviors observed in nature [17, 25]. the following paragraph outlines the stepwise execution of the pso algorithm within a pv system to achieve mppt efficiently. 214 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 (1) initialization: the pso algorithm commences by initializing a swarm of particles with variables for each particle’s bestknown position (`localbest`), the best-known position among all particles (`globalbest`), a counter (`k`), an array for best power output (`p`), an array for duty cycles (`dc`), the best power output (`pbest`), the previous power output (`pprev`), the current duty cycle (`dcurrent`), an index (`u`), velocity of each particle (` `), and a conditional flag (`temp`). duty cycles are randomly assigned to ensure a wide range of starting points, with `dcurrent` beginning at an assumed optimal of 0.5. (2) iterative loop: within the main loop, the current duty cycle (`dcurrent`) is assigned to d, and the algorithm proceeds with sequential evaluations. if the conditional flag `temp` is negative, `temp` will be incremented for delay purposes, and the loop may exit early. assuming the current power `p` exceeds `pbest`, `pbest` is updated to reflect this new maximum. hypothesizing the iteration count (`k`) hasn’t reached its threshold, the loop will continue for additional iterations. postulating the change in power is minimal, indicating a potential plateau, the algorithm will reshuffle the duty cycles to stimulate new explorations. (3) particle update: the function iterates through each particle, updating personal best positions (`localbest`) based on improved power outputs (`p`). once all particles are cycled through (`u` equals 4), the `globalbest` is updated. particle velocities are recalculated considering the current velocity, proximate to personal and global bests, with new duty cycles computed accordingly. particle position is updated in the following equation. ( 1) ( ) ( 1) , , , + += +t t t i d i d i dx x v (4) where, ��, (���) is the newly updated position of particle � at iteration � + 1. (4) velocity update: each particle’s velocity is recalculated using the `updatevelocity` function, which incorporates a fraction of the particle’s current velocity (inertia) and attractive forces towards personal and global bests (cognitive and social components). stochastic elements (`c1` and `c2`) are introduced for robust search behaviors. velocity update is governed by the following equations. ( ) ( )( 1) ( ) ( ) ( ) 1 1 1 2 2. . .χ χ+ = + − + − t t tt i i i iu w u c pbest x c gbest x (5) where, � (���) is the velocity of particle � at iteration � + 1. (5) duty update: the duty cycle for each particle is updated through the `updateduty` function using the newly computed velocity. this function ensures the duty cycle remains between 0 and 1. if the updated duty cycle deviates outside this range, it will be corrected to maintain the system’s stability and efficiency. the duty cycle, corresponding to the best solution (`d`), is subsequently used to adjust the pv system’s converter settings in search of the mpp. algorithm-1: pseudo code of pso for mppt step-1 start step-2 initialize pso parameters and persistent variables: define learning factors c1 and c2. compute power (p) from ipv and vpv. initialize pso variables such as globalbest, k, dc, and pbest. set starting points for dcurrent and dc if this is the first run. step-3 set d to the current duty cycle (dcurrent) step-4 increment temp if less than 0 and exit early step-5 update pbest if the current power p is greater than pbest step-6 increment iteration counter k if it is less than a threshold (3000) step-7 if a change in power is negligible, randomize duty cycles dc to escape local optima advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 215 step-8 update each particle: update personal best if current power is higher. update globalbest if a cycle through particles is complete. calculate the new velocity for each particle. update each particle’s duty cycle within a valid range (0 to 1) step-9 repeat steps 3 to 8 for each function call, refining the search for optimal duty cycle step-10 end when maximum iterations are reached or the algorithm converges step-11 output the optimal duty cycle d from the best nest 4. gravitational search algorithm the gsa is a metaheuristic optimization approach that draws inspiration from the laws of newtonian gravity and the interactions between masses. the gsa mimics the movement of objects influenced by gravitational forces, where each object represents a potential solution to the optimization problem at hand. the gsa commences by initializing a set of agents (masses) and iteratively updates their positions based on the gravitational pull exerted by other agents within the population. the gravitational force acting upon an agent is directly proportional to the product of the masses of the interacting agents and inversely pertinent to the distance separating them. this force determines the movement and positioning of agents within the search space as the algorithm progresses. agents with better fitness values (solutions) are assigned higher masses, enabling them to exert stronger gravitational forces and attract other agents towards their positions. this exploitation mechanism enables gsa to efficiently refine solutions and converge towards optimal regions of the search space. applied to mppt in solar pv systems, the gsa leverages the metaphorical gravitational pull among candidate solutions to steer the search towards the mpp with smart precision [26-27]. below is the systematic process of gsa, where each solution is weighted by its fitness, orchestrating a delicate balance between attraction towards the best solution and repulsion from the least efficient, thereby ensuring a continuous evolution towards the system’s optimal performance. (1) initialization: the gsa commences by setting up agents randomly within the solution space, laying a foundation for a comprehensive search across potential solutions. (2) iterative loop: during each iteration, the algorithm assesses the power output of each agent, comparing it to their respective bests and updating records for continual performance enhancement. (3) mass calculation: the algorithm calculates the mass of each agent based on their fitness, using the relative mass strength variable q, to translate fitness into gravitational mass. ( ) ( ) ( ) ( ) ( ) − = − t t t i t t fitness worst m best worst (6) where, �� (�) is the mass of agent � and � at time �. meanwhile, �������(�) is the fitness value of agent � and � at time � . ����(�) and �����(�) are the best and worst fitness values among all agents at time �. (4) force calculation: forces between agents are computed considering an exponentially decaying gravitational constant g and a stochastic element, which enables the algorithm to avoid local optima and navigate the search space effectively. ( ) ( ) ( ) ( ) ( ) .= + t t i jt ij ijt ij m m f g t rand r e (7) where, ��� (�) is the gravitational force between agent � and � at time �. (�) is the gravitational constant at time �. �� (�) �� (�) are the masses of agents � and � at time �. "�� (�) is the euclidean distance between agent � and � at time �. �#�$�� is a random number between 0 and 1. 216 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 (5) position update: the positions of agents, which are conceptualized as duty cycles, are updated and influenced by both the calculated gravitational forces and an element of randomness that includes a portion of their previous velocity. ( 1) ( ) ( 1)+ + = + t t t ij i ix x v (8) where %� (���) and �� (���) is the new position and velocity agent � at time �. (6) distance function: the function, which is essential for the movement dynamics of the algorithm, calculates the euclidean distance between two agents, influencing the gravitational force calculations. (7) velocity update: the velocities of agents are updated by introducing variability through a random multiplier, combined with the new acceleration from the gravitational force, resulting in the final velocity. ( 1) ( ) ( ) ( ) ( ) . . + = + − t t t t t ij ij ij ij j iv v f rand x x (9) where ��� (���) is the velocity of agent � towards agent � at time � + 1. ��� (�) is the current velocity of agent � at time �. %� (�) and %� (�) are the positions of agent � and � at time �. (8) duty update: finally, the algorithm ensures that the updated positions (duty cycles) of agents remain within the operational bounds of the system, thereby maintaining the physical feasibility of the pv system. algorithm-2: pseudo code of gsa for mppt step-1 start step-2 initialize gsa variables, including dcurrent, pbest, force, acceleration, mass, q, p, p_current, p_min, worse, dc, v, and gbest. set dcurrent and gbest to 0.5, and initialize dc randomly if it’s the start of the gsa process. step-3 if the counter is within operational limits (less than 3000), proceed with the current duty cycle step-4 for each particle (u = 1 to 3), update p_current, improve p and pbest if possible, and adjust p_min and worse if necessary. step-5 increment the particle index (u), resetting after cycling through all particles step-6 if within the iteration limit, refine d for ongoing exploration or finalize it. step-7 calculate each particle’s mass (q) based on their performance relative to the group’s best and worst, affecting their gravitational pull step-8 determine the total strength of mass and individual masses, informing the force calculation step-9 adjust the gravitational constant over iterations to ensure convergence, calculate forces incorporating stochastic elements for robust search behavior step-10 update acceleration based on calculated forces proportionate to the mass step-11 for each particle, update velocity and subsequently, the duty cycle (dc) ensuring exploration guided by gravitational forces step-12 if the final iteration is reached, solidify the duty cycle (d) to prevent further adjustments step-13 conclude the process once the maximum iterations are reached or the algorithm converges on a solution, outputting the optimal duty cycle (d) step-14 end 5. hpso-gsa algorithm the hpso-gsa algorithm is a novel approach that synergistically combines the principles of pso and gsa for optimizing the duty cycle of solar pv systems. this hybrid metaheuristic technique aims to leverage the complementary strengths of both algorithms, balancing the exploration capabilities of pso with the exploitation strengths of gsa, to efficiently navigate the search space and converge towards optimal duty cycle values that maximize the power output of the pv system. advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 217 the objective function for an optimization algorithm in pv systems aims to maximize the power output or, equivalently, to minimize the negative power output. for the given hpso-gsa approach, an appropriate objective function would be: → = × pv pv maximize p v i (10) where p is the power output of the pv system, vpv is the voltage, and ipv is the current. the algorithm seeks to adjust the duty cycle (d) to find the mpp. upon initiating the hpso-gsa function, the algorithm checks for the existence of ‘globalbest’ as a marker indicating whether the algorithm has run before. if absent, the algorithm initializes the parameters for pso, such as the particles’ duty cycles ‘dc’, personal bests ‘localbest’, velocities ‘v’, and the global best condition ‘globalbest’. duty cycles, which determine the operating state of the power converter in the pv system, are initialized with random values within specified ranges. this randomness is essential for the broad search capabilities of the algorithm. the core of the algorithm revolves around two key equations. first, in the pso component, the velocity of each particle is updated using the formula: ( ) ( )1 2. . (). . ().= + − + −finalv w v c rand pbest d c rand gbest d (11) where, w is the inertia weight, c1 and c2 are the cognitive and social coefficients, respectively, �#�$() is a random number between 0 and 1, pbest is the personal best position, gbest is the global best position, and d is the current position. this equation ensures each particle is influenced by its own best position and that of the swarm. second, the gsa part calculates the force exerted on each mass (particle), simulating a gravitational attraction. the force is given by: . . . ()= + i j m m f g rand distance e (12) where g is the gravitational constant, &� and &� are the active and passive masses, distance is the euclidean distance between two particles, e is a small constant to prevent division by zero, and �#�$() introduces a stochastic element. subsequently, the force determines the acceleration and, ultimately, the updated velocity of the particle. by alternating between these two mechanisms, the algorithm adeptly balances exploration and exploitation. furthermore, the algorithm continuously updates the positions of particles, i.e., the different duty cycle values, and converges on the mpp. the optimal duty cycle d, which is found when the algorithm satisfies its convergence criteria, is subsequently applied to the pv system to effectuate its very efficient point, despite the variability of solar irradiance and environmental factors. the pseudo-code for this hybrid approach is given as follows in table 2. table 2 parameters values for the hpso-gsa algorithm parameter description value ‘c1’ the cognitive coefficient for pso 2 ‘c2’ the social coefficient for pso 2 ‘max_iter’ maximum number of iterations 3000 ‘dcurrent’ (initial) initial guess for the duty cycle 0.5 ‘dc range’ the range for initializing duty cycle positions 0.005 to 0.995 ‘iteration’ iteration counter initialized to 1, increments ‘alpha’ coefficient for gravitational constant decay in gsa 200 ‘g0’ initial gravitational constant in gsa 1 ‘e’ small constant to prevent division by zero in gsa 2.2204 × 10-16 this table indicates an overview of key parameters utilized in a hybrid optimization algorithm combining pso and gsa. a direct impact lying in each parameter reflects on the performance and convergence of the hpso-gsa function. notably, the values for the dc range are extrapolated from the ‘randi’ function with the division by 1000 in the code and reflect the initial setup. actual values of ‘dc’ during algorithm execution will vary as they are updated by the pso and gsa procedures. 218 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 algorithm-3: pseudo code of hpso-gsa for mppt step-1 start step-2 initialize parameters: initialize persistent variables for pso and gsa parameters. set pso coefficients (c1, c2) and maximum iterations (max_iter). step-3 check initialization if globalbest is empty, initialize pso and gsa parameters. step-4 calculate the power (p) using the given voltage (vpv) and current (ipv). step-5 update personal and global best (pso) update the personal best (pbest) if the current power is better. check if the maximum iterations are reached and reset the iteration counter (k) if necessary. if the power change is small and far from the best, reinitialize pso parameters. step-6 update local best and worst (gsa) update the personal best (localbest) and worst (worse) solutions for each particle. step-7 hpso-gsa update if all particles have been updated (u == 4): find the index of the maximum personal best and update the global best (globalbest). calculate the strength of mass (q), mass, and force (gsa). update acceleration (gsa). -for each dimension: update velocity using a hybrid of pso and gsa equations. update position (duty cycle) using the updated velocity. increment the iteration counter. -update the previous power (pprev). otherwise, update the duty cycle (d) and current duty cycle (dcurrent) with the current particle’s values. step-8 return result. return the optimized duty cycle (d) step-9 end several complexity challenges emerge as the proposed hpso-gsa algorithm is primarily driven by the initialization and iterative update processes. during initialization, parameters for both pso and gsa are set up, entailing a linear time complexity pertinent to the number of particles. each iteration, which can reach a maximum number of iterations, involves evaluating the fitness of each particle, updating personal and global bests, and computing new velocities and positions using both pso and gsa equations. these steps collectively contribute to a linear time complexity per iteration, resulting in an overall complexity that scales linearly with the number of particles and iterations. regarding scalability, the hpso-gsa algorithm is designed to handle larger datasets and more extensive pv systems effectively. both exploration and exploitation are maintained in an equilibrium, thereby adapting efficiently to various problem sizes. the performance of the algorithm, demonstrated in the results section, exhibits superior efficiency and effectiveness, compared to traditional optimization techniques, highlighting its robustness and suitability for large-scale applications. 6. results and discussions in a matlab simulink simulation environment, the models depicted in fig. 1 were utilized to evaluate the efficiency of mppt algorithms at a uniform temperature of 25 ℃ and irradiance of 1000 w/m2. fig. 3 captures the performance of the pso algorithm, which demonstrated initial power oscillations before stabilizing at a power output of 54.32 w and a load voltage of 15.29 v. fig. 4 exhibits the results for the gsa algorithm, yielding a more consistent power output of 55.1 w and a load voltage of 56.39 v, thereby indicating its robust capacity. the hpso-gsa approach is represented in fig. 5, where it outstripped the standalone algorithms by achieving the highest power output of 55.4 w and load voltage of 56.41 v. hence, the hpso-gsa effectively and rapidly secures the mpp. these representations in figs. 3, 4, and 5 provide a clear comparative insight into the progressive optimization capabilities of the algorithms in enhancing solar pv system performance. advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 219 fig. 3 mppt output with pso algorithm for 1000 w/m2 fig. 4 mppt output with gsa algorithm for 1000 w/m2 fig. 5 mppt output with hpso-gsa algorithm for 1000 w/m2 220 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 fig. 5 mppt output with hpso-gsa algorithm for 1000 w/m2 (continued) fig. 6 to fig. 8 compares the performance of the pso, gsa, and hpso-gsa algorithms in maintaining power output over time under specific testing conditions, as mentioned in table 1, at different irradiance levels of 1000 w/m2, 800 w/m2, and 600 w/m2. specifically, comparative results concern tracking efficiency, settling time, convergence time, and oscillations. moreover, these results highlight that the hpso-gsa algorithm outperforms both pso and gsa, thereby attesting to its effectiveness in achieving and maintaining a stable power output under varying irradiance levels. (a) hpso-gsa (b) gsa (c) pso fig. 6 power comparison of all at 1000 w/m2 (a) hpso-gsa (b) gsa fig. 7 power comparison of all at 800 w/m2 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 221 (c) pso fig. 7 power comparison of all at 800 w/m2 (continued) (a) hpso-gsa (b) gsa (c) pso fig. 8 power comparison of all at 600 w/m2 from fig. 6 to fig. 8, as listed above, a performance comparison of pso, gsa, and hpso-gsa approach for mppt at 1000 w/m2, 800 w/m2, and 600 w/m2, respectively, is demonstrated. the pso line seemingly exhibits more fluctuations initially before stabilizing, while the gsa line also displays variability in power output, with less intensity than pso. the hpso-gsa line, in contrast, expeditiously reaches a stable power output and maintains this stability over time, indicating quicker convergence and less oscillatory behavior. table 3 below summarizes and shows quantified data for the above results. table 3 performance analysis of pso and gsa and hpso-gsa algorithm irradiance (w/m2) pso gsa hpso-gsa power (w) 1000 54.32 w 55.1 w 55.4 w 800 45.7 w 46.1 w 46.4 w 600 35.2 35.8 w 36.2 w efficiency 1000 97.87% 99.27% 99.81% 800 98.2% 99.13% 99.78% 600 96.96% 98.62% 99.72% settling time 1000 0.21 sec 0.15 sec 0.11 sec 800 0.16 sec 0.12 sec 0.09 sec 600 0.19 sec 0.13 sec 0.10 sec convergence time 1000 0.21 sec 0.17 sec 0.06 sec 800 0.14 sec 0.09 sec 0.05 sec 600 0.19 sec 0.10 sec 0.04 sec oscillations 1000-600 more less least conversion 1000-600 slower faster fastest 222 advances in technology innovation, vol. 9, no. 3, 2024, pp. 210-223 table 3 summarizes the performance of the pso, gsa, and hpso-gsa approaches for mppt in pv systems across varying irradiance levels. the hybrid approach outperforms the individual pso and gsa in several metrics, including power output, efficiency, convergence time, and settling time. notably, concerning convergence time across irradiance levels of 1000, 800, and 600 w/m2, the hybrid algorithm is on average 56.38%, which is better than gsa and 71.55% better than pso. apropos settling time, the hybrid method shows an average improvement of 24.91% over gsa and 46.24% over pso, underscoring its ability to rapidly stabilize at the optimal operating point. the hybrid algorithm excels in tracking the mppt power with efficiency ratings peaking at 99.81%, 99.78%, and 99.72% for all irradiance levels. overall, the hpso-gsa algorithm accentuates its rapid response and high efficiency, marking it as a significant enhancement in the optimization of solar pv systems. 7. conclusions the study presents a novel hybrid metaheuristic approach, i.e., hpso-gsa, combining pso and gsa for optimizing solar pv systems. based on simulations under various solar irradiance conditions, the following conclusions can be drawn: (1) the proposed hpso-gsa algorithm demonstrates potential as an intelligent and robust solution for maximizing power generation in solar pv systems, contributing to enhanced efficiency and reliability in renewable energy systems. (2) the hpso-gsa consistently outperforms individual pso and gsa algorithms across all measured metrics, including power output, convergence speed, settling time, and overall efficiency. (3) the hybrid approach demonstrates significant enhancements in convergence time, with an average improvement of 56.38% over gsa and 71.55% over pso across irradiance levels of 1000, 800, and 600 w/m2. (4) the hpso-gsa exhibits an average improvement of 24.91% over gsa and 46.24% over pso in settling time, indicating a superior ability to quickly stabilize at the optimal operating point. (5) the hybrid algorithm excels in tracking the mpp with efficiency ratings peaking at 99.81%, 99.78%, and 99.72% for all tested irradiance levels. (6) by integrating the exploration capabilities of pso with gsa’s exploitation strengths, hpso-gsa effectively explores the search space and converges towards optimal duty cycle values, maximizing power generation from pv systems. 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[26] n. priyadarshi, m. s. bhaskar, m. g. hussien, b. khan, and a. e. w. hassan, “an experimental realization of improved grid integrated multilevel inverter based pv systems with mppt,” iet renewable power generation, in press. https://doi.org/10.1049/rpg2.12652 [27] k. aygül, m. cikan, t. demirdelen, and m. tumay, “butterfly optimization algorithm based maximum power point tracking of photovoltaic systems under partial shading condition,” energy sources, part a: recovery, utilization, and environmental effects, vol. 45, no. 3, pp. 8337-8355, 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 circularly polarized antennas using characteristic mode analysis: a review vamshi kollipara, samineni peddakrishna * school of electronics engineering, vit-ap university, amaravati, india received 19 october 2021; received in revised form 20 december 2021; accepted 21 december 2021 doi: https://doi.org/10.46604/aiti.2022.8739 abstract characteristic mode analysis (cma) can be used in antenna designs to solve radiation problems. this review focuses on the existing development methodologies for circularly polarized (cp) antennas and their axial ratio bandwidth (arbw) improvement using cma. to discuss the physical insights related to cp radiation, this study systematically examines different antenna design structures used in previous research. it investigates the impact of modal parameters such as the eigenvalue, modal significance (ms), characteristic angle (ca), surface current, far-field radiation behavior on cp radiation, and arbw for various antenna designs. in addition, it discusses the comparative analysis of various antenna design approaches in terms of antenna performance parameters such as the operating frequency band, arbw, and gain. the results show that cma provides more valuable information for the selection of feed position in antenna designs than the conventional full-wave simulation approach. keywords: characteristic mode analysis (cma), eigenvalues, modal significance, characteristic angle 1. introduction today’s advanced wireless communication technology development is being driven by different integrated challenges. the antenna design methodology is one of the interesting challenges with desired radiation behavior [1-3]. an independent antenna design approach contributes to the optimization of a communication system [4-5]. sometimes, in such a communication system, unnecessary power losses may occur if the polarization of the receiving and transmitting antennas is not matched. by using circularly polarized (cp) antennas, power losses due to polarization mismatch can be avoided. cp antennas are essential in various applications due to their ability to combat multi-path interference and mitigate linear polarization (lp) problems such as faraday rotation [6]. cp radiation can be achieved by combining two orthogonal lp radiations with equal magnitude and quadrature-phase excitations. additionally, various techniques have been used, such as adjusting patch shapes with single or multiple feed networks through parameter sweeping [7] and using automated optimization methods [8]. most of the antenna designs typically follow a cut-and-try approach, based on the engineering experience by full-wave simulation without understanding the natural resonance characteristics of structures. this procedure becomes somewhat trivial and lacks physical insights. because of this, the final simulation characteristics such as the radiation efficiency, input impedance, and radiation patterns of antennas are dependent on the resonance properties themselves from the exciting external feed. hence, the antenna resultant current distribution does not reflect the natural resonance characteristics with the improper feed. thus, to understand and analyze the resultant current distribution that does reflect the natural resonant behavior, the theory of characteristic mode analysis (cma) is one of the fundamental approaches of recent days in the antenna domain. cma analyzes the resonant behavior of an antenna structure using a source-free method and it decomposes the full-wave current into an individual mode [9-10]. this will help understand the physical insights and optimal feed arrangements, and excite the desired modes by suppressing undesired modes [11]. the optimization can thus be done on the designs to the desired radiation performance. * corresponding author. e-mail address: krishna.samineni@gmail.com advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 cma was originally addressed by garbacz [12] and formulated with turpin [13]. they demonstrated a specific set of characteristic modes (cms) for an arbitrary perfect electric conductor (pec) obstacle that is independent of any specific source. there is only the assumption that cms have been given instead of an explicit definition. therefore, harington and mautz [14] refined the cm theory for pec objects by relating the surface current to the tangential electric field and defined that an infinite number of independent current modes can naturally exist in an arbitrary structure. later, it has been extended to different structures [15-16]. however, the appropriateness of their formulations has not been exhibited properly in solving practical problems. in recent years, numerous investigations into these earlier formulations have been addressed [17-19]. the most important applications of these findings include mobile handset antenna designs [20], radio-frequency identification (rfid) tag antennas [21], universal serial bus (usb) dongle antennas [22], aircrafts [23], unmanned aerial vehicles (uav) [24-25], ships [26], and land vehicles [27-29]. recently, the study has been extended to a dual-port fractal ultrawideband (uwb) multiple-input multiple-output (mimo) antenna for portable handheld wireless devices [30] and a 4-port mimo antenna for 5.8 ghz wlan applications [31]. very recently, some 5g antennas have also been proposed using mimo technology [32-36]. the cm theory has become a standard approach in these developments. in this article, the authors explore the cm-based methodological advancement for a variety of critical cp antenna designs. this article intends to assemble and organize the advanced research achievement made in the area of cm studies, especially for the cp achievement with wide axial ratio bandwidth (arbw). it gives preliminary knowledge about the cm parameters and helps readers get a deeper understanding of various practical antenna developments using cm-based methodologies. the organization of the article is in the following manner. section 2 explains the basic cm parameters that are required for understanding the natural resonance behavior of an antenna. section 3 describes the comprehensive methodologies in the literature for the cp achievement and arbw enhancement using cma. section 4 concludes the discussion followed by a list of references. 2. cm parameters this section discusses the formulation of cms and their parameters that are useful in antenna designs. the initial phase of any antenna design using cma involves the modal analysis. this will help understand the modal behavior of geometry. mathematically, it can be thought of as eigenvalue analysis [37]. typically, cma begins by extracting the resonance information from cm parameters. these cm parameters are obtained by solving an eigenvalue equation that is derived from the method of moment impedance matrix as shown in eq. (1) [13]. [ ] [ ] [ ]z r j x  (1) from this, an eigenvalue equation is formulated as eq. (2): [ ][ ] [ ][ ]n n nx i r i  (2) here, x and r are the imaginary and real parts of the generalized impedance matrix [z], respectively. vector in is the eigen or characteristic current, where n represents the index of each mode. λn is the real eigenvalue. this represents the possible modes that are naturally supported by the structure. by observing the real eigenvalue λn, the physical insight corresponding to the natural resonance information is obtained. 2.1. eigenvalue (λn) an eigenvalue (λn) provides useful information about the natural resonant frequency of an intended antenna design, especially as a function of frequency. the eigenvalue is useful to identify the mode information because its magnitude is proportional to the total stored field energy within a radiating antenna. based on the stored electric and magnetic energy, the associated mode information can be classified as resonant mode, inductive mode, and capacitive mode. 243 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 in particular, if it shows λn = 0, i.e., the stored magnetic energy is the same as the stored electric energy as represented by eq. (3), the associated modes are said to be resonant. * * . . n n m n v v h h dv e e dv    (3) if it shows λn > 0, i.e., the stored magnetic energy is more than the stored electric energy as represented by eq. (4), the associated modes are said to be inductive. * * . . n n m n v v h h dv e e dv    (4) if it shows λn < 0, i.e., the stored magnetic energy is less than the stored electric energy as represented by eq. (5), the associated modes are said to be capacitive [6]. * * . . n n m n v v h h dv e e dv    (5) to understand the behavior of eigenvalues for various modes supported by the structure, a typical rectangular patch with 25 × 160 mm is considered to represent the eigenvalues for various modes [38]. as can be seen from fig. 1, the eigenvalues of mode 1 and mode 4 are approaching zero, and these modes are identified as resonance frequencies across the frequency band. in addition, it shows the sign of the eigenvalue of mode 3 indicating the ability to store electrical energy (λn < 0) and mode 2 indicating the ability to store magnetic energy (λn > 0). however, if higher frequencies are considered with higher-order modes, more than one mode turns into the resonance conditions. hence, for good polarization purity, it is not easy to excite a single mode. also, extracting the modal resonance properties for higher frequencies becomes quite difficult because they are tightly grouped and cannot be differentiated from each other. therefore, to visualize those resonating characteristics, additional parameters such as modal significance (ms) and characteristic angle (ca) are defined along with eigenvalues. fig. 1 variation of eigenvalues for different modes [38] 2.2. modal significance (ms) ms is another way of extracting the resonance characteristics by using eigenvalues, and it measures the potential contribution of each mode. ms is the intrinsic property of each mode and is defined in eq. (6): 1 | 1 | n ms j    (6) 244 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 from eq. (6), it can be observed that the eigenvalue λn tends to be zero, and the ms becomes one and the mode starts resonating. the ms range transforms to [[0, 1]] from the much higher eigenvalue range [−∞, +∞]. therefore, in many cases, to investigate the resonant behavior, it is more convenient to use ms than eigenvalues, especially over wide frequency band applications. additionally, ms is also used to determine how many significant modes will be considered in the antenna design from the contribution of eigenvalues. to distinguish the significant modes and non-significant modes, the half-power ms is defined. from this, if ms ≥ 0.707, the associated modes are significant. if ms < 0.707, the associated modes are non-significant. further, the half-power ms also reinforces the definition of each cm bandwidth, especially in the case when the feed structure is not available in the initial stage of the design. the half-power bandwidth of each cm is defined in eq. (7). h l res f f bw f   (7) where fres, fh, and fl are the resonant frequency, upper half frequency, and lower half frequency, respectively. they are determined from eq. (6) in the following manner. if λn = 0 and ms = 1, then the associated mode is a resonant mode (fres). if λn = ±1 and ms = 0.707, then the associated mode is the lower and upper half power frequency band mode (fl and fh), as shown in eq. (8): 1 1 ( ) ( ) 0.707 1 2 l h n ms f ms f j       (8) as a further extension, fig. 2 shows the associated ms behavior of each mode supported by the same structure across the frequency for four different modes [38]. as observed from the figure, ms approaches unity for mode 1 and mode 4 and is considered to contribute to the radiation. mode 2 and mode 3 are considered non-significant modes. fig. 2 variation of ms for different modes [38] 2.3. characteristic angle (ca) ca is another way to show the mode behavior near resonance. it is the phase lag between the real characteristic current on the surface and the tangential electric field. this can be extracted from the eigenvalue using eq. (9). 1 180 tan ( ) n n     (9) from eq. (9), if λn = 0, the phase lag between the electric field and real current on the surface is 180° out of phase, and the mode is said to be the most effective radiating mode of the radiating element. on the opposite, if λn = ±∞, the attained phase lag is 90° or 270°, and the mode is said to be non-radiating or cavity resonance mode [9]. in this case, the modal current generates a null field in the exterior region. additionally, if the phase angle varies between [90°, 180°] and [180°, 270°], the modes are said to be inductive modes and capacitive modes, respectively. 245 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 to further understand the associated modal behavior of each mode supported by a structure, the variation of ca across the frequency for four different modes is shown in fig. 3 [38]. from the figure, it can be easily understood that the variation of ca for mode 1 and mode 2 attains 180° phase lag at a certain frequency and these are considered resonant modes. mode 3 and mode 4 are varying between [90°, 180°] and [180°, 270°] over a given frequency range, so they are said to be inductive modes and capacitive modes, respectively. fig. 3 variation of ca for different modes [38] 2.4. eigen current or field in addition to the characteristic parameters, the real eigen currents are important to illustrate various possible currents or fields that are naturally supported by the structure. thorough investigations into modal currents and modal fields can yield useful information on how to feed the structure for certain desirable radiation patterns. to excite the desired mode, a source needs to be positioned at a location with high characteristic currents. to understand how to place the source to excite all of the desired cms from the characteristic currents, the modal currents of the first three normalized modes are illustrated in fig. 4 [39]. as from the current distribution, the maxima and minima of the individual cms j1, j2, and j3 are primarily observed at the edges of the major and minor axis and can be characterized by a sinusoidal behavior. as regards this current behavior, two feeding methods have been proposed: the capacitive coupling element (cce) and inductive coupling element (ice) methods. for efficient mode excitation, cce and ice have to be placed at the location with the minimum and maximum characteristic current, respectively. (a) surface current and field (b) sinusoidal behavior of current fig. 4 modal current and field pattern variation [39] however, practical radiating antennas typically consider the effect of source excitation. from the source excitation point of view, modal decompositions can tell how well each of the designs is excited in the desired modes. this can be done by calculating the quantities called modal excitation coefficient (mec), modal weighting coefficient (mwc), and modal input power from eqs. (10)-(14). the total current on the structure is assumed to be linear superposition of the orthogonal set of mode currents [14, 37]. this can be extracted from eq. (10). . n ntot nj jc   (10) where cn is the mwc and jn is the characteristic current of the mode n. 246 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 mwc is an important guiding parameter for an antenna design to determine the appropriate feed point and feed structure telling which mode carries the maximum current. 1 | | . | . | |1 | n n i n c j e ds j     (11) | | . | | n n msc v (12) where vn is the mec which describes an easy way to excite the mode from its excitation. | | . n n i v j e ds  (13) from eq. (12), it can be understood that a large ms and mec are necessary to excite the desired operating modes. another important parameter is the modal input power, which is described as the power in each mode and used to find which mode is exited for radiation behavior problems. the modal input power pin is determined by the mwc cn, as shown in eq. (14). 21 | | 2 in n n p c  (14) the above quantities explain how a design can succeed in the excitation of the desired modes. finally, this section summarizes the standard values for the measure of a resonant mode from the above parameters, i.e., eigenvalue (λn) = 0, ms = 1, and ca = 180°. they are essentially expressing the same thing differently, and which parameter is used depends on the personal design requirement. if the design requirement is only on the primary resonant mode or to identify a few lower-order resonant modes, the parameter extraction of the eigenvalue (λn) is sufficient. to extract the behavior of higher-order modes or over a wide frequency band of operation, ms is an important parameter. when multiple modes need to be excited for certain radiation performance (i.e., circular polarization), the ca and current or field distribution are of great importance in the antenna design. 3. cp antennas using cma cma and its applications in antenna designs for enhancing various radiation parameters are described by various research groups in the literature. however, this section has limited the review to a parameter called circular polarization. the underlying mechanism of this parameter is readily available to be read through many electronic databases individually. this review process is highlighted, with all those approaches together, by classifying various groups based on the feed networks and the type of geometry. this will help further understand the insight into the design of the cp antenna and its arbw enhancement using cma. antenna polarization is usually defined as the orientation of an electric field as a function of time, at a fixed position in space. the polarization type of an antenna can be identified from the axial ratio (ar) [40-41]. if ar is zero or infinity, it is lp. for unity ar, it is circular polarization. if ar is between zero to one, it is elliptical polarization. however, for practical applications, the most acceptable ar is 1.414 = 3 db for circular polarization. to generate circular polarization in antennas, a well-known fact is to excite two orthogonal modes with equal amplitude and quadrature (90°) phase difference. various techniques have been described in the literature using singleor dual-feeding techniques [42-43]. in a single-feeding method, a small perturbation is required for the orthogonal mode and a quadrature phase shift at the feed point. the perturbation segment is in the form of a slit, a slot, a truncated segment, or an added stub [44-46]. however, the single-feed antennas are structurally simple but suffer from narrow arbw. to overcome this, a 247 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 dual-feed network is one of the solutions. however, dual-feed cp antennas require an additional power divider to split the input signal with equal amplitude and an additional quadrature wavelength transmission line to generate 90° phase shifts. this enhances the design complexity. to compensate for the two issues, another type of cp antennas called slot and stub antennas has been proposed [47-49]. however, most of these antennas are usually accomplished by tuning the patch shapes and feed positions through full-wave simulation. those designs have not been verified for the similarity between the natural resonance characteristics and the physical insight of the feed location. to address the above two characteristics and further optimization of the structure, cma has been identified by many research groups. using cma and its parameter extraction, one can easily identify the circular polarization of the design from the following three conditions: (1) the first condition to satisfy circular polarization is to identify adjacent orthogonal modes and this can be easily verified from the modal current distribution analysis for various modes. (2) the next condition is that both orthogonal fields are with uniform magnitude and it can be verified from the ms between two orthogonal modes. if the ms is the same for two orthogonal modes at a certain frequency means, it satisfies the required condition. (3) finally, the last condition for circular polarization is a quadrature-phase difference between the modes and it can be verified from ca. if the ca difference between the orthogonal modes is 90° means, it satisfies the required condition. with the use of the above three conditions, various cp antennas have been designed in the literature. these antennas mainly differ in the way by which the lp modes are excited properly with the help of cma. to review those proposed structures, they are divided into two parts. the first part of the cp antennas is considered without metasurface (mts) and the second part is with mts. 3.1. cp antennas without mts to demonstrate how cma is useful to achieve circular polarization, a simple rectangular asymmetrical u-shaped slot antenna as shown in fig. 5 is considered [50]. cma has been carried out without considering the feed structure. fig. 6 shows the first two modes of ms and ca across the frequency band from 2.0-2.7 ghz. it is found that the two modes have the same large ms and a 90° phase difference at 2.3 ghz, which satisfies the above three conditions. as a result, for cp operations, these two modes operate together at the center frequency. next, to find the optimal feed position, the characteristic currents as shown in figs. 7(a) and (b) have been characterized in the horizontal mode and vertical mode with respect to the modes j1 and j2. then, to excite two modes properly, the vertical mode is subtracted from the horizontal mode, i.e., performed j1 − j2 between the two modes. as a result, the minimum current has been obtained at the inner edge of the u-slot’s long arm, as shown in fig. 7(c). this location specifies that the two orthogonal modes represent a similar current amplitude. the two orthogonal modes that have comparable current density location points (indicated with the black dot in fig. 5) will generate far-field cp radiation upon excitation. to generate the circular polarization, an equal current magnitude and 90° ca phase difference has been generated from an equal crossed dipole to an unequal crossed dipole [51]. it has been observed that a square contour parallel dipole has shown a 90° phase difference for degenerating modes such as mode 2 and mode 3 by analyzing individual orthogonal current modes [52]. the designs discussed above have a low profile and can be fabricated easily [53-59]. however, some of those structures exhibit a narrow arbw because the orthogonality and phase difference is achieved at a single frequency. to enhance the arbw with a single-feed mechanism from cma, tran et al. [53.] coupled a higher band c-shaped monopole cp antenna with a lower band square patch with a c-shaped slot aperture, as shown in fig. 8. to understand the arbw enhancement, the ms, ca, current distribution, and far-field radiation of a c-shaped monopole and c-shaped slotted patch are presented in fig. 9 and fig. 10, respectively. as observed from fig. 9, the first two modes are exactly the same, with a 90° phase difference at around 5.5 ghz radiating in a broadside direction. from fig. 10, a similar phenomenon is observed for the first two 248 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 fundamental modes at around 2.1 ghz with broadside radiation. in addition, it is noticed that the same ms is quite close to 90° phase difference between the modes j2 and j4 as well as the modes j2 and j5 at 3.2 and 3.5 ghz, respectively. however, the current directions of the modes j2 and j4 are observed on the opposite side instead of having quadrature-phase differences. hence, it has been considered that the c-shaped slotted patch is proposed to radiate cp waves at 2.1 and 3.5 ghz. fig. 5 asymmetric u-slot antenna for circular polarization [50] (a) ms (b) ca fig. 6 cm parameters of the asymmetric u-slot antenna [50] (a) mode j1 (b) mode j2 (c) j1 − j2 fig. 7 current distribution of the u-slot antenna at 2.3 ghz [50] (a) top layer (b) bottom layer fig. 8 geometry of the cp c-shaped monopole antenna [53] (a) ms fig. 9 modal characteristics of the c-shaped monopole patch [53] 249 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 (b) ca (c) current distribution and far-field radiation fig. 9 modal characteristics of the c-shaped monopole patch [53] (continued) (a) ms (b) ca (c) far-field radiation fig. 10 modal characteristics of the c-shaped slotted patch [53] (a) s11 parameters (b) ar fig. 11 parameters of the c-shaped monopole and c-shaped slotted patch antenna [53] once the desired modes have been selected for wide cp radiation from the above two shapes, the feed point from the c-shaped monopole patch is subsequently identified from the current distribution. it is identified as the feed point at the corner by subtracting the current mode j2 from the mode j1 of the c-shaped patch. then, the patch is excited with a monopole arrangement and the arbw is obtained ranging from 4.6 to 6.1 ghz. next, to enhance the arbw, the slotted c-shaped patch aperture is excited through a coupling mechanism with the directly fed c-shaped patch monopole. the final geometry of the cp antenna top and bottom layer design is shown in fig. 10. here, the cp radiation at 2.1 ghz and 3.5 ghz is predicted based on the desired 250 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 modes (j1, j2, and j5) of the current distribution of the c-shaped slotted patch. therefore, the position of the c-shaped patch monopole plays an extensive role in the performance of the c-slotted patch. to obtain the optimum coupling position, the design is fine-tuned using numerical simulation. the simulated s11 and arbw results of an individual and optimized patch antenna are shown in fig. 11. the results show that a very wide arbw of 96.1% can be achieved in this configuration. using similar kinds of techniques, a cpw-fed rectangular slot antenna has been designed for wider arbw [54-57]. the cp conditions are attained using an asymmetric slot [54] and asymmetric stubs [55] on the ground plane by altering the current distribution. additionally, the arbw has been improved by employing two symmetric inverted l-stubs with vertical strips parallel to an antenna and a pair of asymmetric inverted l-strips with spiral slots, respectively. in another design, a circular ring cpw-fed antenna has been proposed with two orthogonal clock angle microstrip lines on opposite sides of the substrate [56]. to attain a quadrature-phase difference ca, the angle between the microstrip lines is optimized to achieve circular polarization. recently, a cp loop antenna has been designed with a broad arbw and impedance bandwidth with a single-feeding technique [57]. here, a 90° phase difference is attained by loading the lumped inductors. a pair of degenerated mode resonance points is split by properly positioning the feeds and loading the inductors with the aid of cma. using this method, an 8.3% arbw and a 47% impedance bandwidth are achieved at 2.4 ghz wlan band. in summary, this subsection has reviewed the cma of optimal antenna designs without mts for cp radiation and improvement in ar. the optimal designs discussed above [55-57] demonstrate that cma provides important information for cp performance and arbw enhancement from cm parameters and current or field distribution. on the other hand, the designs described above illustrate how to optimize the feed position to provide cp radiation and improvement in arbw from the modal current distribution. 3.2. cp antennas with mts this subsection investigates how cma can be used to tailor the mts for the purpose of designing cp antennas. various mtss are exploited in the cp radiation and arbw improvement [58]. to demonstrate the usefulness of cma with respect to mts, the geometry of the mts antenna is shown in fig. 12. it comprises two dielectric layers and three metallic layers. the three metallic layers (i.e., the mts, cross-shaped slot, and feed structure) are placed on the top, middle, and bottom of two substrates. to analyze the cp behavior, cma is first performed on the top mts, and ms is demonstrated for the first four modes across the frequency band, as shown in fig. 13(a). then, the current distribution and far-field patterns of these modes at the respective resonance frequencies, such as 6 ghz (for the modes j1 and j2) and 6.5 ghz (for the modes j3 and j4), are observed as shown in figs. 13(b) and (c). as observed from the modal currents, the modes j1 and j2 have an identical current distribution except for the 90° phase difference. however, they are a pair of degenerate modes and cannot provide 90° ca. the modes j3 and j4 are self-symmetrical modes with out-of-phase current distribution and appear null in the broadside direction. hence, only mode 1 and mode 2 have been considered for cp radiation with simultaneous excitation with a 90° phase difference from the feed structure. (a) top view of mts (b) cross slot (c) back view of the microstrip line (d) side view of the antenna fig. 12 configuration of the mts-based antenna [58] 251 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 (a) ms (b) current distribution (c) far-field patterns fig. 13 mts cm parameters [58] to excite only the first two modes with a 90° phase difference and suppress higher-order modes, an adaptive feed network has been employed with a combination of a cross-slot and a microstrip meander-line (figs. 13(b) and (c)). as a result, cp radiation is formed. to investigate the cp performance, the s parameter and ar performance are compared in fig. 14. further, various mts antennas have been proposed in the literature based on the orthogonality principle of surface current distribution and identical ms between adjacent or lower-order modes and higher-order modes [59-62]. a perforated h-shaped mts [59] and a corner-truncated patch mts with capacitive loading strips [60] have been proposed by exciting adjacent higher-order modes and lower-order modes, respectively. recently, another non-uniform chebyshev distribution mts has been exploited as a superstrate by exciting two alternative modes such as mode 1 and mode 3 with an equal electric field and relative phase difference close to 90° [61]. apart from the arbw enhancement, the cp mts antenna has been proposed for radar cross-section (rcs) reduction [62]. here, by using cma, a linearly polarized slot antenna is converted to a cp antenna with the help of polarization-dependent mts and is additionally used for rcs reduction. in another design, a dual cp mts antenna has been proposed [63]. (a) s11 (b) ar fig. 14 mts antenna parameters [58] 252 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 in this design, the desired modes are chosen and excited by a modified slot antenna with two orthogonal feeds. the modified cross slots, called two diagonal linear slot arms and a circular ring slot, introduce another resonance for wide arbw. apart from the arbw enhancement, the mts is also used for polarization conversion [64]. here, various etching mechanisms, like diagonal slot, cross slot, and corner truncation, have been used on a linearly polarized rectangular mts. to achieve circular polarization, this has been done with the exciting slot antenna. modal analysis is used to verify cp conditions and optimize them. recently, an artificial magnetic conductor (amc)-based reflector cp antenna using a cpw-fed structure has been proposed for 5g sub-6 ghz communications with unidirectional radiation [65]. the periodic metallic square patches amc improve arbw from 27.27% to 51.67% and gain increases from 3.3 dbic to 8.7 dbic than the conventional pec. from the above discussion, it can be summarized that orthogonality is verified before the selection of a specific feed design. if any of the cp conditions are not satisfied for a simultaneous 90° phase difference for excitation, it has been optimized from the feed network and further analyzed. in some designs, the quadrature phase shift has not been attained from the cma and has been compensated by properly designing the feed network. moreover, the largest ms of different modes at the same frequency and different frequencies together with the 90° phase differences can generate narrowband and wideband arbw, respectively. studies have also indicated how to optimize cp antenna designs for two linear modes using mts. after identifying the cp waves in a particular frequency band with the cma, antenna designers concentrate their effort on the feed structure. moreover, in the literature, most of the cma has been carried out for isolated patches by neglecting the ground plane and dielectric material. the accuracy of the resonant frequencies will be affected by such kind of simplification. this is because the characteristic fields and currents are dependent on the size and shape of the patch as well as the dielectric substrate. hence, while considering cma, the dielectric substrate and ground plane cannot be ignored when seeking resonant frequencies of microstrip antennas. moreover, fig. 15 represents a potential mts utilized for circular polarization and arbw enhancement using cma. additionally, the design approaches discussed above are consolidated in fig. 16 based on the utilized feed network. moreover, the analysis of these parameters is performed before the selection of source excitation. thus, there is a degree of freedom in the feed network selection and feed location in the final antenna design. therefore, the techniques for the selection of feed networks and their final optimization with the help of cma are reviewed in the above section from the mentioned literature [50-65]. fig. 17 shows the antenna designs for various feeding methods. additionally, the important observations of all these antenna designs are summarized with their achieved operating band and arbw as shown in table 1. fig. 15 typical mts geometry utilized for circular polarization using cma fig. 16 cp antennas designed using cma with different feeding techniques 253 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 fig 17 typical cp geometry using cma with various feeding methods table 1 summary on various antenna design approaches for circular polarization ref. antenna design approach ar band (ghz) arbw (% and ghz) gain (dbi) observation [50] (a) an asymmetric u-slot antenna (b) a redundant e-slot antenna (a) 2.28-2.37 (b) 2.2-2.55 (a) 3.8 and 0.09 (b) 3.7 and 0.35 (a) 5.86 (b) 8.87 (a) an offset probe feed provides better ar performance than a center feed. (b) an insignificant mode is suppressed to get a redundant e-shaped slot antenna. [51] two crossed-dipole antennas 0.282-0.295.5 4.65 and 13.5 the length of one dipole is increased slightly to get a 90° phase shift. [54] a small semicircular slot rectangular antenna 2.25-4.4 64.6 and 2.15 the inverted-l stubs are used for desired phase difference and diagonal corner truncation for orthogonal modes. [55] an i-shaped radiating patch 6.6-11.8 56.5 and 5.2 5.5 the simultaneous excitation of even and odd modes from a rectangular stub, inverted-l stub, and spiral slot provides the wideband radiation behavior. [56] a clock-shaped antenna from a metallic ring antenna 2.38-5.8 84.6 and 3.42 3.9 a 90° phase difference is introduced by the two opposite microstrip lines in the x and y directions. [59] a crossed shape aperture with h-shaped unit cell mts 5.2-6 14.3 and 0.8 9.4 the additional required phase for circular polarization is compensated via a cross-shaped strip with an aperture. [60] a corner-truncated patch along with a pair of inserted capacitive loading strips 3.3-3.6 8.5 and 0.3 6.57 from cma, the pair of inserted diagonal capacitive loading strips of a corner-truncated patch is optimized for attaining quadrature phase difference and arbw improvement. [61] a non-uniform mts superstrate layer excited by a stripline through a rectangular slot 1.99-2.37 17.4 and 0.265 7.1-8 the phase difference between the orthogonal modes is observed only 60° and exploited as an inductive exciter for an additional 30° phase shift. [62] a rectangular patch as a polarization-dependent mts 5.83-6.32 9.05 and 0.49 6.4 the degenerated modes are achieved using polarization-dependent mts with 74° phase difference and excited with a linearly polarized slot antenna to achieve cp radiation. [63] an mts excited with a hybrid feed system consisting of a cross slot and a microstrip line 2.15-2.95 31.3 and 0.8 7.01 due to a cross-slot on the ground plane, 90° phase difference is presented via microstrip meander line excitation. [64] a square patch with a diagonal slot, crossed slot, and corner-truncated mts 2.32-2.46 2.55-2.58 2.52-2.54 5.8 and 0.14 1.1 and 0.03 0.7 and 0.02 5 3.5 3.5 due to asymmetry on the square patch, a phase difference is created for circular polarization. 4. conclusions this article concentrated on modal parameters that are required to analyze the natural mode resonance and radiating behavior, followed by a novel approach for designing an antenna using cma to improve arbw. the cm parameters together with characteristic currents explicitly gave useful information for analysis of the antenna before excitation. in particular, this review 254 advances in technology innovation, vol. 7, no. 4, 2022, pp. 242-257 presented how the arbw is enhanced in various developed structures from the theoretical formation analysis of the cm theory. the information provided by these developed structures helps understand valuable insights for the selection of feed position to maximize the antenna performance. moreover, the authors’ abundant contributions to the study of the cm theory were summarized based on the feed structures, utilizing mts with concluding remarks. fully exploiting and making use of cma in antenna designs could significantly enhance 5g and mm-wave applications from the dual-polarized cp antenna perspective. from a future perspective, if cp antennas can fulfill the needs of long-distance communication as done by high gain linearly polarized antennas, the cm-based approach becomes attractive in antenna designs. numerical models, physical interpretation insights, and cma would be available for a more detailed analysis of cp antennas with and without mts. this approach is also helpful to demonstrate that simultaneous mimo operations increase channel capacity and throughput. for efficient mimo performance, the radiation diversity is also explored for its low correlation coefficient. additionally, further research is going on to improve other important parameters, such as gain, efficiency, compactness, and polarization purity. finally, these challenges require the cma method to become more efficient for designing cp antennas. conflicts of interest the authors declare no conflict of interest. references [1] r. s. uqaili, j. a. uqaili, s. zahra, f. b. soomro, and a. akbar, “a study on dual-band microstrip rectangular patch antenna for wi-fi,” proceedings of engineering and technology innovation, vol. 16, pp. 1-12, august 2020. 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[65] h. askari, n. hussain, d. choi, m. a. sufian, a. abbas, and n. kim, “an amc-based circularly polarized antenna for 5g sub-6 ghz communications,” computers, materials, and continua, vol. 69, no. 3, pp. 2997-3013, august 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 257 2___aiti#8904___169-180 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 developing and implementing an ai-based leak detection system in a long-distance gas pipeline te-kwei wang 1 , yu-hsun lin 2,* , jian-yuan shen 1 1 department of electrical engineering, ming chi university of technology, new taipei city, taiwan 2 department of business and management, ming chi university of technology, new taipei city, taiwan received 12 november 2021; received in revised form 13 april 2022; accepted 14 april 2022 doi: https://doi.org/10.46604/aiti.2022.8904 abstract this research proposes an artificial intelligence (ai) detection model using convolutional neural networks (cnn) to automatically detect gas leaks in a long-distance pipeline. the change of gap pressure is collected when leakage occurs in the pipeline, and thereby the feature of gas leakage is extracted for building the cnn model. the gas leak patterns in the long-distance pipeline are analyzed. a pipeline detection model based on ai technology for automatically monitoring the leaks is proposed by extracting the feature of gas leakage. this model is tested by collecting gas pressure data from an existing natural gas pipeline system starting from mailiao to taoyuan in taiwan. the testing result shows that the reduced model of leak detection can be used to detect the leaks from the upstream and downstream pipelines, and the ai-based pipeline leak detection system can obtain a satisfactory result. keywords: artificial intelligence, convolutional neural network, pipeline leak, leak detection 1. introduction pipeline transportation systems are generally used to transport oil, natural gas, domestic water, etc. the long-distance transportation system may encounter leak problems due to old pipelines. also, thieves may destroy pipelines and steal the resources from the pipelines. thus, leak detection is a critical issue for effective pipeline management. leak detection techniques based on acoustics and infrared (ir) are the most widely used techniques for the detection of liquid and gas leaks, respectively. however, these two techniques do not work sometimes [1]. for instance, ir approaches cannot accurately detect leaks in wet weather, while acoustic sensors may not accurately detect gas leaks in the target area because of noise [1]. due to the need to purchase and install new sensors, the additional cost of buying hardware equipment may be incurred. in recent years, many methods have been proposed based on artificial intelligence (ai) techniques for developing leak detection systems [2-3]. for example, yang and zhao [2] used an optimally pruned extreme learning machine (opelm) to improve the accuracy of the pressure point analysis (ppa), and used bidirectional long-short term memory (bilstm) to construct a leak detection system [2]. zhou et al. [3] used improved spline-local mean decomposition (islmd) to analyze the internal pressure value of pipelines. they converted the data into an image, employed alexnet to build a model to determine the occurrence of leakage, and used a cross-correlation function to calculate the time difference between upstream and downstream sensor values to find the location of the leakage point [3]. a growing number of ai techniques for developing leak detection systems are based on convolutional neural networks (cnns) [3-5]. cnns are based on neurons arranged in layers and can therefore learn hierarchical representations; moreover, weights and biases link neurons from one layer to the next [6]. the first layer acts as the input layer for receiving the * corresponding author. e-mail address: yslin@mail.mcut.edu.tw tel.: +886-2-29089899#3168; fax: +886-2-29084533 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 transformed vector from image-based data, e.g., remote leak data. the last layer is the output, e.g., predicting whether a pipeline leaks or not. the feature derived from the previous layer serves as an input for the following layer. the final layer predicts an outcome according to the detected features. layers between the first and the last layer are hidden layers that transform the feature values from the input to the output. traditionally, cnns consist of at least one convolutional layer as a hidden layer for exploiting spatial patterns [6]. melo [4] used gradient-weighted class activation mapping algorithm (grad-cam) and cnn models to judge whether the images recorded by closed-circuit television (cctv) have a leak response; the experimental results reached an accuracy of 99.78%. li et al. [5] proposed a method for small-scale natural gas pipeline leak detection. the model converts the value of the acoustic sensor into the frequency domain and then uses a one-dimensional cnn to train the model. the final trained model has higher accuracy than the leakage detection performance of the traditional two-dimensional cnn model [5]. kang et al. [7] used ensemble cnn-svm for leak detection in a water distribution system, and used a graph-based algorithm to determine the leak location according to the time difference of sensor value changes. the experimental results can reach 99.3% of the leak detection accuracy rate and control the leakage point position error within 3 meters [7]. as shown by the literature review above, employing ai techniques to develop leak detection has received growing attention. however, few studies have investigated ai-based leak detection systems based on cnn for automatically monitoring the leaks in a real context. to fill the gap, the present study aims to develop an ai-based model to detect the leaks of a long-distance pipeline and test the model’s accuracy in a real context. in this research, pressure sensors (the inherent hardware equipment of a pipeline) are used to read the gas pressure in the pipeline, and the collected gas pressure data are used for feature extraction and model training. additionally, the present study employs the pipeline detection data from supervisory control and data acquisition (scada) as the training data for deep learning. by doing so, the smart detection of pipeline leaks can be realized, and the hardware cost of the sensor can be saved. specifically, this research uses the pressure sensor data recorded in scada to analyze and extract suitable data features, and then labels the data features separately and conducts model training through cnn. the model trained in this study can realize a rapid and accurate function of leak detection. the developed system is beneficial for managers to detect leaks in the long-distance pipeline. 2. system structure this research obtains the dataset from the pressure sensors in the scada system provided by a petrochemical manufacturer in taiwan. fig. 1 depicts the schematic diagram of this study by showing the pipeline transportation system. pt is a pressure gauge. the pipeline transportation starts from plant a to plant c via plant b. plant c is the end of the entire pipeline transportation system. the distance between plant a and plant b is about 63 kilometers. the distance between plant b and plant c is about 136 kilometers. the pipeline in plant b will be pressurized by pumps before sending resources to plant c. in this study, the pressure sensor, pt-m621, in plant b is used to collect data for subsequent data analysis and model training, and the pressure sensor, pt-m622, is used to test and validate the model. fig. 1 schematic diagram of this study 170 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 fig. 2 system architecture fig. 3 data from the real pipeline leak test the research system architecture is shown in fig. 2. first, the data received from the scada system is classified into the normal data group and the leak data group. next, the characteristics of the two data groups are extracted through feature engineering. therefore, the two groups’ data are merged and divided into the training data set and the test data set for model training. finally, this study tests whether the model can distinguish the leak data. overall, this study employs the cnn architecture to construct the model. if the model cannot accurately classify the two types of data, the feature engineering needs to be adjusted until the model can effectively classify the two kinds of data. fig. 3 shows the full-day data on the day of the actual leak test. the time points of the three leak tests for data analysis and feature engineering are marked in fig. 3. the x-axis presents the time point of measuring the pressure. the time interval between pieces is one second. 2.1. data analysis and feature extraction fig. 4 illustrates the data sampling for the leak test. for observing the data variance in detail, the data for analysis is captured after the start of the leak test. in fig. 4, the positions pointed to by the red arrow are the data points during the leak test; through data visualization, there are obvious pressure fluctuations when leakage occurs. this study uses these three leakage points as reference points to find more suitable data for feature engineering. although the leakage appears at these points, the data of the leak pattern for extracting the feature cannot be reflected by these points. therefore, according to the rule of thumb for capturing the leak feature found in this study, 1000 pieces of data are taken before and after the leakage points to capture the graphical pattern of leak occurrence, as illustrated in fig. 4. the time interval for the pressure data sampling between pieces is one second. in doing so, this study does observe and find the data suitable for presenting the characteristics of the leakage data. in practice, the operators test the functionality of the pressure sensor by opening and then closing the valve after 30 seconds and four minutes to simulate the gas leaks. fig. 5(a) and fig. 6(a) show the data collected from the interval between opening the leak valve instantly and waiting for 30 seconds to close the leak valve instantly, respectively. the curves marked 171 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 with red squares in the two figures are the pressure fluctuations during the leak test. as shown in fig. 5(a) and fig. 6(a), the width of the red region is the period for the opening and closing of the valve and is enlarged in fig. 5(b) and fig. 6(b). the pressure variance of the first leak test and the second leak test are shown in fig. 5(b) and fig. 6(b), respectively. as depicted in fig. 6(a), the internal pressure of the pipeline does not return to a stable state during the second leak test. therefore, the level of pressure fluctuation in the second test is smaller than in the first test. fig. 7(a) shows the data collected from the pressure sensor during the third leak test. in the third leak test, the data collection process begins when the leaking valve is opened at a slower speed and ends when the valve is fully opened. the time interval for the opening and closing of the valve is four minutes. after four minutes, the leakage valve is closed at a slow speed. the width of the red region in fig. 7(a) is the period for the opening and closing of the valve and is enlarged in fig. 7(b). thus, the pressure variance of the third leak test can be clearly seen in fig. 7(b). fig. 4 illustration of the pressure data for detecting real pipeline leaks (a) result of the first leak test showing leak point 1 (b) close-up view of the red region in fig. 5(a) (showing the test interval) fig. 5 the first leak test (a) result of the second leak test showing leak point 2 fig. 6 the second leak test 172 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 (b) close-up view of the red region in fig. 6(a) (showing the test interval) fig. 6 the second leak test (continued) (a) result of the third leak test showing leak point 3 (b) close-up view of the red region in fig. 7(a) (showing the test interval) fig. 7 the third leak test fig. 8 fod processing result for the data of real pipeline leaks after training the model many times, even if the number of the convolutional layers, the number of the filters, and the size of the convolution kernel are increased, the resisting noise interference does not reach the requirement. the result presents that a single feature is less effective in resisting noise interference. thus, the data is processed by the first-order differential (fod) processing and its characteristics are analyzed. as shown in fig. 8, the red arrows point to the data points of the real leak test. when observing the curve of the data analysis after the fod processing, it can be understood that relatively large pressure fluctuations will be generated in the interval of the leak test. thus, these features are adopted as the second feature of model training. as shown in fig. 9, fig. 10, and fig 11, 1000 points of data extracted from the interval of the first, second, and third leak tests are used to analyze the features. fig. 9(a), fig. 10(a), and fig. 11(a) are the fod data from the first leak test, the second leak test, and the third leak test, respectively. the width of the red region in fig. 9(a), fig. 10(a), and fig 11(a) is the period for 173 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 the opening and closing of the valve and is enlarged in fig. 9(b), fig. 10(b), and fig 11(b), respectively. taken together, after the data is transformed by the fod processing, the pressure fluctuation produced by the first leak test is more obvious than the other two. therefore, the fod data of the first leak test is selected as the second feature of the training model of this research. (a) fod processing result of the first leak test showing leak point 1 (b) close-up view of the red region in fig. 9(a) (showing the test interval) fig. 9 first-order data differentiation for the first leak test (a) fod processing result of the second leak test data showing leak point 2 (b) close-up view of the red region in fig. 10(a) (showing the test interval) fig. 10 first-order data differentiation for the second leak test (a) fod processing result of the third leak test data showing leak point 3 fig. 11 first-order data differentiation for the third leak test 174 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 (b) close-up view of the red region in fig. 11(a) (showing the test interval) fig. 11 first-order data differentiation for the third leak test (continued) 2.2. model training data set and testing data set according to the analysis result, a suitable data interval for identifying the features of the model training is found. the normal data and the leak data are given corresponding labels. as presented in figs. 12(a) and 13(a), the data obtained from the pressure sensors are normalized to make the value with the range from 0 to 1, so the data in the two figures are not marked with the x-axis unit. because the feature amount of the leak data is less than the feature amount of the normal data, data expansion is needed to achieve better training performance. in order to avoid the model from only learning the characteristics of a single data and causing identification failure, the data set is balanced. finally, 70% of the normal data and the leak data are used as the training data. the rest of the data is used as the test data set. the result of experimental tests shows that if the data set is randomly arranged, it will reduce the accuracy of the overall model classification. thus, this study orders the data according to the same characteristics and by the arrangement method. as shown in fig. 12(a) and fig. 12(b), the first half of the training data set is normal data, and the second half is leak data. fig. 13(a) and fig. 13(b) are the testing data sets, which are used to evaluate the effect of the training model during model training. (a) original training data set (b) fod training data set fig. 12 training data set 175 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 (a) original testing data set (b) fod testing data set fig. 13 testing data set 2.3. model building this study uses keras to construct a cnn model. the values collected from the pressure sensor are time series and belong to a one-dimensional data type. therefore, a one-dimensional convolutional layer is used to build the model, and relu is selected as the activation function. to avoid the over-fitting of the model on the training data and reduce the generalization of the model, this study adds a dropout layer after the convolutional layer. furthermore, through adding the pooling layer, the dimensions of the model features are reduced and output to the full connection layer. in the full connection layer, softmax is used as the activation function. the loss function for the evaluation model is categorical cross-entropy, and the function for the optimizer is the adam function. fig. 14 depicts the flowchart of model building in this study. fig. 14 model building 3. system implementation after confirming that the training model can identify the leak data, the training model is used to perform a leak test in the data interval, thus verifying whether the model can correctly determine the occurrence of leaks and effectively resist noise 176 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 interference. as shown in fig. 15, if the result of the model test is different from the expected result, then the hyperparameters of the model are re-adjusted to meet the condition where the time interval of the leak occurrence is consistent with the time interval of the real leak test. fig. 15 system implementation 3.1. model architecture fig. 16 shows the model architecture, in which the three layers of the one-dimensional convolutional layer are stacked, and the dropout layer is added to prevent the model from overly relying on the training data set. after repeated testing is conducted, the classification effect of using the average pooling layer is found to be better than the effect of the max pooling layer. thus, the average pooling layer is used here. fig. 16 model architecture 3.2. result of leak point identification after completing the model training, the data of two different pressure sensors are employed to test whether the testing model can correctly distinguish and predict the point of pipeline leak where the leak actually occurs. the pressure sensor data shown in fig. 16 is the data of the training model (pt-m621). in fig. 16, if the model finds leakage, the leak point is one, and the normal data is zero. moreover, in order to avoid the excessive dependence of the model on the training data set, the data from the differential pressure sensor (pt-m622) is used to verify the generalization of the model. the model architecture used in figs. 17-18 is the same as the one shown in fig. 16. in these figures, the red line represents the zero value of the pressure. in the pooling layer, this study chooses the max pooling instead of the average pooling as the mean to gain the results of the model training. fig. 17 and fig. 18 use pt-m621 and pt-m622 as the data sources of the model verification, respectively. fig. 18 shows that model 1 can accurately detect the occurrence of leakage, while fig. 17 can only 177 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 detect the signal of the leakage generated during the first leak test. fig. 19 and fig. 20 use pt-m621 and pt-m622 as the data sources of the test model, respectively. the architecture of this test model uses the average pooling instead of the max pooling in designing the pooling layer, and the size of the convolution kernel is 3. as shown in fig. 19, model 2 only identifies the first and third leak occurrences but does not identify the second leak test. fig. 20 shows that this model can accurately detect leakage in the interval where the leakage occurs. fig. 21 and fig. 22 use pt-m621 and pt-m622 as the data sources of the test model, respectively. the structure of the test model is shown in fig. 16. the size of the convolution kernel is adjusted to 5, and the test results are shown in fig. 21 and fig. 22. as shown in fig. 21 and fig. 22, this model architecture can accurately detect leaks in the time interval of the leak test on two different data sets, which confirms that the model is with good generalization and can be applied to different data sets. table 1 lists the result of testing leak data after adjusting the hyperparameters of the above models. finally, the model developed by this study is employed to test the data set from different sensors. the result indicates that this model can still play a role in leak detection when a real leak occurs, thus confirming that this model can well function, receive the accurate leak detection function, and achieve the level of generalization. the model developed by this study is implemented with simple architecture. the time interval for the pressure sensor to record data is one second. thus, the data volume is also equal to the sampling time of the data volume. if the real-time leak detection function is to be achieved, the time for calculating the data of the model must be controlled within one second. the calculating time on different data volumes in the model is shown in table 2. the experimental results show that if the data recorded every hour, 3600 cases, is used for leak detection, the calculating time for the model to predict the leakage can be below one second, thus being able to satisfy the requirement of real-time leak detection. table 1 results of testing the pipeline leakage with different hyperparameters model parameters pt-m621 pt-m622 model 1 max pooling kernel size = 3 fail success model 2 average pooling kernel size = 3 fail success model 3 average pooling kernel size = 5 success success table 2 calculating time of the model for different data volume data volume (cases) calculating time (second) 86400 3.339572191238403 43940 1.904508652279663 3600 0.636376142501831 600 0.476074934005737 fig. 17 results of leak identification for model 1 (using the pt-m621 pressure sensor) fig. 18 results of leak identification for model 1 (using the pt-m622 pressure sensor) 178 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 fig. 19 results of leak identification for model 2 (using the pt-m621 pressure sensor) fig. 20 results of leak identification for model 2 (using the pt-m622 pressure sensor) fig. 21 results of leak identification for model 3 (using the pt-m621 pressure sensor) fig. 22 results of leak identification for model 3 (using the pt-m622 pressure sensor) the result can be summarized as follows. first, based on the physical features of the pipeline, the ai model of pipeline transportation is derived. second, based on the ai model, the pipeline leak patterns are analyzed. it is found that the reduced model of detecting the pipeline leakage can be used to detect the leakage from the upstream and downstream pipelines. finally, the model is tested in an existing natural gas pipeline system starting from mailiao to taoyuan in taiwan. the results show that in the proposed ai-based leak detection system, the correctness concerning the detection function is not affected by various operational conditions of the pipelines. 4. conclusions and directions for future research the present study contributes to the research and practice of pipeline leak detection in the following ways: (1) the model developed by this study can effectively detect the leakage in the real long-distance transmission pipeline system. it can achieve the same performance as the traditional leak detection system. (2) the training data used in this study is collected from the sensor of the original pipeline system. thus, no additional hardware equipment is required, which can save the cost of hardware equipment. (3) it can run smoothly without adding the extra graphics card. the operator can easily load the trained model when performing leak detection. nevertheless, some limitations remain and need to be resolved in further research: (1) this study uses the pressure sensor data collected from a single site to train the model. however, the data recorded by the pressure sensor at different sites may be different. it will be better to collect the training data from different sites in the pipeline system in future research. 179 advances in technology innovation, vol. 7, no. 3, 2022, pp. 169-180 (2) the present study only uses the basic cnn architecture for model training and collects the data from one site in the pipeline. future research can collect sensor values from other sites and employ rnn or lstm algorithms for processing the time-series data. (3) only a few pressure data for pipeline leakage can be collected due to the expensive testing cost of the existing detection system. thus, the issue of overfitting and false negatives may occur in the proposed model. more pressure data should be collected in further research. conflicts of interest the authors declare no conflicts of interest. references [1] m. meribout, et al., “leak detection systems in oil and gas fields: present trends and future prospects,” flow measurement and instrumentation, vol. 75, article no. 101772, october 2020. [2] l. yang, et al., “a novel ppa method for fluid pipeline leak detection based on opelm and bidirectional lstm,” ieee access, vol. 8, pp. 107185-107199, 2020. [3] m. zhou, et al., “leak detection and location based on islmd and cnn in a pipeline,” ieee access, vol. 7, pp. 30457-30464, 2019. [4] r. o. melo, et al., “applying convolutional neural networks to detect natural gas leaks in wellhead images,” ieee access, vol. 8, pp. 191775-191784, 2020. [5] j. li, et al., “a small leakage detection approach for gas pipelines based on cnn,” 2019 caa symposium on fault detection, supervision, and safety for technical processes, pp. 390-394, july 2019. [6] t. kattenborn, et al., “review on convolutional neural networks (cnn) in vegetation remote sensing,” isprs journal of photogrammetry and remote sensing, vol. 173, pp. 24-49, march 2021. [7] j. kang, et al., “novel leakage detection by ensemble cnn-svm and graph-based localization in water distribution systems,” ieee transactions on industrial electronics, vol. 65, no. 5, pp. 4279-4289, may 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 180  advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 evaluation of pan-sharpening techniques using lagrange optimization mutum bidyarani devi 1,* , rajagopalan devanathan 2 1 department of electronics and communication engineering, 2 department of electrical and electronics engineering, hindustan institute of technology and science, chennai, india received 19 may 2019; received in revised form 07 december 2019; accepted 04 march 2020 doi: https://doi.org/10.46604/aiti.2020.4288 abstract earth’s observation satellites, such as ikonos, provide simultaneously multispectral and panchromatic images. a multispectral image comes with a lower spatial and higher spectral resolution in contrast to a panchromatic image which usually has a high spatial and a low spectral resolution. pan-sharpening represents a fusion of these two complementary images to provide an output image that has both spatial and spectral high resolutions. the objective of this paper is to propose a new method of pan-sharpening based on pixel-level image manipulation and to compare it with several state-of-art pansharpening methods using different evaluation criteria. the paper presents an image fusion method based on pixel-level optimization using the lagrange multiplier. two cases are discussed: (a) the maximization of spectral consistency and (b) the minimization of the variance difference between the original data and the computed data. the paper compares the results of the proposed method with several state-of-the-art pan-sharpening methods. the performance of the pan-sharpening methods is evaluated qualitatively and quantitatively using evaluation criteria, such as the chi-square test, rmse, snr, sd, ergas, and rase. overall, the proposed method is shown to outperform all the existing methods. keywords: image fusion, pan-sharpening, optimization, spectral consistency 1. introduction with the fast-growing number of earth’s observation satellites, satellite data providing information about the surface of the earth is increasing. this information has been applied in different fields for various end-users’ applications, such as urban planning, agriculture, forestry, and mining. depending on sensors onboard the satellite, different types of images of the earth’s surface received. some sensors provide single-channel data while other sensors provide both single and multichannel data. single-channel data or monochrome images, such as the panchromatic (pan) image, usually comes with a high spatial resolution associated with a low spectral resolution. on the other hand, the multispectral (xs) image comes with a low spatial resolution and a high spectral resolution. for example, the commercial-launched satellite sensor, such as ikonos, provides 1 m pan and 4 m xs (r, g, b, and near-infrared bands) images. the analysis and the usage of the remotely sensed data are user-dependent. sometimes the processing of high-quality images is needed for certain applications such as classification and target detection. since satellite data are available in different resolutions spatially and spectrally as well as at different scales and times, data fusion has been applied successfully to obtain both high resolution spatial and spectral image. data fusion can be defined as the process of combining two or more incoming signals which complement each other and produce an output signal which has more information content than the incoming inputs. more formally, data fusion is a formal framework that expresses means and tools for the alliance of data of the same scene originating from different sources. it aims * corresponding author. e-mail address: bidyarani.mutum@gmail.com advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 167 at obtaining information of greater quality; the exact definition of greater quality will depend on the application” [1]. image fusion plays an important role in the remote sensing field where satellite images come with complementary resolutions that are being made available in the public domain. image fusion, in particular, is defined as the “combination of two or more different images (of the same scene) to form a new image by using a certain algorithm” [2]. one important application of image fusion has been increasing the resolution of an xs imagery by using higher-resolution pan data. the output consists of an xs image whose resolution is both spatially and spectrally high. such an image fusion process usually termed as pan-sharpening. pan-sharpening involves the integration of a panchromatic band and a multispectral band of different resolutions. generally, a panchromatic band comes with a high spatial resolution and a low spectral resolution, while a multispectral band comes with a lower spatial resolution and a high spectral resolution. sometimes, the integration of these images is required when a very high-quality image is needed. a panchromatic image provides details of the scene observed while lacking in color properties. nevertheless, a multispectral image can be useful in detecting objects with a similar spectral signature but belonging to different classes. in the pan-sharpening process, the properties of these complementary images are combined to get an output image that has a high resolution spatially and spectrally. however, one primary challenge in pan-sharpening is to preserve the spectral properties of the multispectral band in the output image. the assessment of the fused image can be performed using various evaluation parameters. the most commonly used fusion methods include intensity-hue-saturation (his) transform, brovey transform, principal component analysis (pca), smoothing filter-based intensity modulation (sfim), high pass filter (hpf), and multiplicative transform. in the his [3-6] pan-sharpening method, the rgb color space is transformed into ihs color space. the transformation can be performed by using three bands only at a time. the step consists firstly of resampling the xs images to the same spatial resolution of pan. secondly, the transformation of resampled rgb to ihs color space is carried out. thirdly, the intensity component is a histogram matched with panchromatic band data. fourthly, the intensity component is replaced by the histogram matched with panchromatic band data. finally, the reverse transformation is applied to get the new r, g, and b fused images. the brovey method [7], on the other hand, is a combination of pan and xs images. the method involves multiplication and division operations. the brovey method is limited to only three bands of the xs channels. each xs band is divided by the sum of all the three bands and multiplied by pan. smoothing filter-based intensity modulation (sfim) is a smoothing algorithm [8] where a low pass filter is applied to a high-resolution pan channel. the low resolution multispectral is multiplied with the high-resolution pan band, which is divided by the low pass filtered pan band. this is done for every band of the multispectral channel. the high pass filter (hpf) [8] method involves high pass filtering of pan band with a window size of a 3×3 filter. in this case, the multispectral band is multiplied with the high pass filtered pan band divided by 2. principal component analysis (pca) [9, 10] is another commonly used method applied to image fusion. first, the principal components (pc) are computed for each multispectral band, then the first pc is replaced by the pan band, and an inverse transformation is applied to get the fused output. lastly, multiplication transform [8] is another popular algorithm used for image fusion. this method is very simple to implement. each of the low-resolution multispectral bands is multiplied with the high-resolution pan band with a corresponding weight. a square root is taken on the final output to avoid excessive brightness values. earlier work of the authors [11] proposed a solution to the problem of pan-sharpening, which aims in maintaining the spectral consistency of the xs channels in the fused image. the primary objective of the current work is to compare the proposed pan-sharpening technique [11] to the existing fusion methods of his, brovey, and other standard methods (namely, sfim, hpf, pca, and multiplication methods) based on several evaluation criteria such as chi-square test, rmse, snr, sd, ergas, and rase. the main contribution of the paper stated as (a) restatement of the authors’ earlier proposal for pan-sharpening based on linear regression and lagrange optimization, (b) application of the proposed algorithm of pan-sharpening to ikonos data, (c) validation of the results of the proposed pan-sharpening method, (d) complexity analysis of the proposed pan-sharpening algorithm, and, (e) finally, a comparison of the performance of the proposed pan-sharpening advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 168 method to the other fusion methods viz. his, brovey, sfim, hpf, pca, and multiplication methods based on several evaluation indices, namely, chi-square test, rmse, snr, sd, ergas, and rase. the organization of the rest of the paper is as follows: section 2 gives an overview of the existing work related to the pan-sharpening comprising of state-of-the-art methods including model-based methods. section 3 deals with a brief description of the proposed fusion method formulated as an optimization problem with an objective function and the lagrange multiplier-based solution. the proposed method is applied to ikonos data as described in section 4. simulation results of the proposed method and comparison with other fusion methods based on several evaluation criteria are discussed in section 5. finally, section 6 presents the main discussions of the experimental results followed by the conclusion. 2. related work the state-of-art methods include the intensity-hue-saturation transformation (ihs) [3-6], the brovey method [7], and principal component analysis (pca) [12]. many researchers have reported that though these conventional methods produce a spatially high-resolution fused image, images are spectrally distorted. hong [13] proposed a method that involves the integration of “ihs and wavelet” to preserve the spatial details. zhang and hong [14] also proposed a method of integrating ihs and wavelet to solve the spectral distortion problem. a method combining pca and nonsubsampled contourlet transform was reported by [15] to overcome the drawback of spectral distortion. andreja [16] proposed a method integrating ihs and brovey methods with a multiplicative (multi) method for maintaining the spatial and spectral details. yang [17] proposed an ihs based on pan-sharpening technique using ripplet transform and compressed sensing for improved spectral properties. the pan-sharpening method based on bayesian theory was proposed by [18]. a comparison between different popular image fusion techniques was reported in the works of [19-20]. performance evaluation of fusion algorithms can also be seen from [20-22]. an assumption that the downsampled fused image should be similar to the original xs image was proposed by [23]. meng [24] proposed a pan-sharpening technique which uses an edge-preserving guided filter based on a three-layer decomposition. to strengthen pan-sharpening methods, [25] proposed a method involving the prior modification of the panchromatic image. this method preserves simultaneously spatial and spectral quality. there also exist a few variational models reported by researchers. ballester [26] proposed the first variational model called p+xs. fang [27] also proposed a model to fuse pan and xs based on certain assumptions. moller [28] proposed a model called variational wavelet for pan-sharpening (vwp). deng [29] also proposed a variational model based on kernel hilbert space and heaviside function. super resolution-based pan-sharpening can be found in the works of [30-32]. the fusion of satellite images has been done on data obtained from various sensors. it can be done on the data coming from the same sensor or different sensors onboard. examples of single-source sensors include ikonos, quickbird, landsat, spot, etc. ikonos data fusion has been reported in the works of [6, 23, 33-34]. fusion using spot data has been reported in the works of [3, 35]. several works have been reported integrating ikonos with landsat data as well as spot data with landsat data [4-5]. a review of different pan-sharpening techniques can be seen in the works of [2, 36-39]. 3. proposed fusion method 3.1. linear regression the first step in our fusion method was to build a linear regression model based on the assumption that a strong correlation exists between the panchromatic and the multispectral bands. the regression model can be defined as follows ar bg cb p   (1) advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 169 where r, g, and b represent the deviations from the respective sample mean of red, green, and blue spectral band intensity data. a, b, and c are the regression coefficients. eq. (1) can also be written as xu p (2) where x = [r g b] is an n × 3 matrix containing columns of n samples of red, green, and blue color data. besides, u= [a b c] t represents the vector of regression coefficients determined. the superscript t stands for matrix transpose. the regression coefficients can be calculated as   1 t tu x x x p   (3) it is assumed that ( x t x ) -1 exists. 3.2. lagrange optimization using (1) as a constraint, an objective function for minimization is formulated to achieve spectral consistency and variance matching of the xs bands as follows.       2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1                                                                                       r jk r jk jk r g jk j j j j g jk jk g b jk j j j b jk jk b jk jk j j j r r r g n n n n g g b n n n b b ar n n n i bg m                               k jk jk j cb p (4) where rjk, gjk, and bjk are deviations from the respective sample mean for the red, green, and blue band, respectively at pixel location (j, k) of the n×n image. besides, r , g , and b are the parameters for red (r), green (g), and blue (b) band, respectively forming a convex combination of spectral consistency and variance matching. 2 r , 2 g and 2 b are the variances of the original red (r), green (g), and blue (b) band data, respectively, and jk is the lagrange multiplier to enforce the constraint (1). the solution to the above-mentioned minimization problem had been reported in an earlier work of the authors [11] and is briefly described in the following section. two independent cases can be derived from eq. (4). case 1: with 1, , ,j j r g b   , for red, green, and blue respectively. case 2: when 0, , ,j j r g b   , for red, green, and blue respectively. the first case deals with minimizing the spectral inconsistency between the actual multispectral data and the computed data. the second case compares the variances between the actual multispectral data and the computed data assuming a gaussian distribution of the intensity data. proposition 1: 1, , ,j j r g b   for red, green, and blue, respectively. eq. (4) can be written as   2 2 2 2 2 2 2 2 2 1 1 1                                jk jk jk jk jk jk jk jk j j j j r g b ar bg cb n n m p n in (5) without loss of generality, the three bands, namely red, green, and blue can be considered independently. differentiating eq. (5) concerning rjk, the solution to eq. (4) is given as advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 170 2 2 2 ,    jk jk fo a r the red p r a b c band (6) the pan-sharpened output for the red band is obtained as (1) ,  new jk jk meanr r r (7) where (1) , new jkr is the pan-sharpened high-resolution output at the location (j,k), and rmean is the sample mean of the red band. superscript (1) stands for case 1. similarly, if we differentiate (4) concerning gjk and bjk respectively, the solution to eq. (4) is given as 2 2 2 ,    jk jk for the green bp g a b c band (8) the pan-sharpened output for the green band is obtained as (1) ,  new jk jk meang g g (9) where (1) , new jkg is the pan-sharpened high-resolution output at the location (j, k), gmean is the sample mean of the green band, and 2 2 2 ,    jk jk for the blue cp b a b c band (10) the pan-sharpened output for the blue band is obtained as (1) ,  new jk jk meanb b b (11) where (1) , new jkb is the pan-sharpened high-resolution output at the location (j,k), and bmean is the sample mean of the blue band. proposition 2: 0, , ,j j r g b   for red, green, and blue band, respectively. eq. (4) can be written as   2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1                                                                      jk jk r jk jk g j j j j jk jk b jk jk jk jk jk j j j r r g g n n n n b b ar bg cb p n in n m (12) without loss of generality, the three bands, namely red, green, and blue can be considered independently. differentiating eq. (9) concerning rjk, gjk, and bjk respectively, the solution to eq. (4) is given as 2 2 2 ,    jk jk r r g b ap r e e a b c e for the red e band (13) 2 2 2 ,    jk jk g g r b bp g e e a b c e e for the green band (14) and 2 2 2 ,    jk jk b b r g for the b cp lub e e a b c e e e band (15) advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 171 respectively, the pan-sharpened output for the red, green, and blue band is respectively obtained as (2) , (2) , (2) ,       new jk jk mean new jk jk mean new jk jk mean r r r g g g b b b (16) where (2) (2) (2) , , , , , new jk new jk new jkr g b is the pan-sharpened high-resolution output and rmean, gmean, bmean are the respective sample means of the red, green, and blue band respectively. superscript (2) stands for case 2. remark 1: er, eg, and eb are the errors associated with the multispectral red, green, and blue band which represents the variance difference between the actual and the computed data. eqs. (13)-(15) are circuitous involving error ratios that are dependent on the solution of rjk, gjk, and bjk, respectively. for example, the ratios /g re e and /g be e in eq. (14) for gjk depend on rjk, gjk, and bjk. similarly, for the error ratios involved in eqs. (13) and (15). the circuitous relation is resolved [11] by showing that the error ratios, in the optimal case, can be considered as the ratio of the variances of the respective spectral band. for example, the error ratios in eq. (14) is in the form 2 2/ / g r g re e and 2 2/ / g b g be e . similar results apply for the error ratios in eqs. (13) and (15). the solution of case 1 and case 2 as given in eqs. (6), (8) and (10) as well as eqs. (13)-(15), respectively represent high-resolution deviation (from the respective mean) in the multispectral band for each channel. remark 2: the fusion process can be performed simultaneously for all the three bands considered. (1) (1) (1) , , , , , new jk new jk new jkr g b (when added to respective mean) represent the projected high-resolution multispectral band based on case 1 while (2) (2) (2) , , , , , new jk new jk new jkr g b (when added to respective mean) represent the high-resolution multispectral band based on case 2. remark 3: since the eqs. (6)-(11) and (13)-(16) are in closed form, the computation of (1) (1) (1) , , , , , new jk new jk new jkr g b and (2) (2) (2) , , , , , new jk new jk new jkr g b for each location (j, k) is done in a single operation. hence, the complexity of pan-sharpening computation is o(n) where n is the number of data points. 3.3. proposed fusion method fig. 1 flowchart of the proposed fusion method advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 172 fig. 1 shows the methodology of the proposed fusion method indicating the sequence of steps involved as 1, 2, etc as shown. first, a panchromatic band and multispectral band images were taken. second, down-sampling the panchromatic data to the lower resolution of multispectral data since the resolution differs in the ratio of 4:1. for example, down-sampling of 8×8 pixels pan data gives 2×2 pixels points. thirdly, the deviation from the respective sample means was calculated for both the pan and xs data. fourthly, the regression coefficients were calculated using eq. (3), and the fifth step consists of applying the proposed two cases of fusion methods to the dataset with the respective means of the band added to the deviations (eqs. (6)-(16)). finally, the projected high-resolution multispectral data was down-sampled for comparison with the original low-resolution multispectral data. 4. evaluation criteria the proposed method is applied to ikonos data, the results of which are presented in the following section. the results of the proposed method of pan-sharpening are also compared with that of other state-of-the-art methods on the same data in that section. to compare the various results, using a common set of evaluation criteria which are described in this section. 4.1. chi-square test the chi-square test [40] is computed as   2 2 i i i i o e e     (17) where ie and io are the expected and the observed data points, respectively, and i=1, 2…n. a small p-value indicates a good fit. the lower the p-value is, the more significant the result is. a low p-value indicates the probability of getting a better fit than the one evaluated is low. 4.2. root mean square error (rmse) root mean square error (rmse) [41] is defined as 2 1 ˆ( )     n i i i x x rmse n (18) where ix is the original value, while ˆ ix is the computed value. a lower rmse value indicates good spatial and spectral properties. 4.3. signal to noise ratio (snr) the signal to noise ratio (snr) [42] can be calculated as follows 2 1 2 1 ˆ( ) ˆ( )       n i i n i i i x snr x x (19) where ix and ˆ ix are the original and computed data, respectively. a higher snr value indicates a good result. 4.4. spectral discrepancy (sd) spectral discrepancy (sd) [41] is usually done to check the spectral quality of the fusion result and is computed as follows advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 173 1 1 ˆ      n i i i sd x x n (20) a lower sd value indicates a good spectral quality of the fusion result. 4.5. erreur relative globale adimensionelle de synthese (ergas) “erreur relative globale adimensionelle de synthese (ergas)”, an error-index proposed by [43] which specifies the global picture quality of the fusion output and is given as 2 1 1 ( ) 100 ( ) q q h rmse q ergas l q q         (21) where (h/l) is the ratio of the pixel sizes between the pan and xs; ( )q and q represents the mean of the q th channel and the index of the band respectively. as proposed by [43], a lower value of ergas indicates a good quality or better fusion output, or the results are considered to be of low quality. 4.6. relative average spectral error (rase) rase index is represented as a percentage to predict the spectral quality of the fusion output [44]. 2 1 100 1 ( ) k i i rase rmse k m k    (22) where m is the average pixel value in the spectral band considered, k indicates the number of bands, and rmse is the root mean square error of the k th channel. like the ergas, the result can be interpreted similarly. a lower value of the rase index indicates a good spectral quality of the fusion output. 5. experimental results and analysis ikonos satellite image was used for the fusion process. ikonos satellite image has been used by many researchers for various applications. in this work, an illustration of the proposed methods and other fusion methods were performed on a real ikonos image consisting of a 32×32 pixels panchromatic band and corresponding 8 ×8 pixels multispectral band (shown in figs. 2 and 3, respectively). the dataset consists of smaller areas selected from a larger ikonos satellite image that is freely available for use. the ikonos satellite image provides two types of images (a) a panchromatic image (1 m spatial resolution) and (b) a multispectral image (4 m spatial resolution) comprising of 4 bands namely, red, green, blue, and nir. in this study, only the first three bands were considered. fig. 2 32×32 panchromatic band fig. 4 shows the fusion result based on the proposed method and fig. 5(a) through (f) shows the fusion results based on his, brovey, sfim, hpf, pca, and multiplicative methods, respectively. in this work, the fusion result was obtained only for advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 174 the three bands, namely, red, green, and blue of the multispectral channels. all the figures are presented in grayscale since each band can be represented as a single color. therefore, the grayscale image will be equally effective. fig. 3 8 ×8 multispectral band (a) case 1 (b) case 2 fig. 4 fusion result based on proposed fusion method advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 175 for the assessment of the spectral and spatial quality of the fusion result, the projected high-resolution xs images are down-sampled so that they are in the same dimension as the original xs. spectral consistency means that the down-sampled data from the high-resolution xs should be close to the original xs data [45]. (a) ihs method (b) brovey method (c) sfim (d) high pass filter fig. 5 fusion results advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 176 (e) pca (f) multiplicative methods respectively fig. 5 fusion results (continued) table 1 performance evaluation of the proposed fusion method (case 1 and case 2) evaluation criteria multispectral band case 1 case 2 chi square test (p value) red 0.01 0.0002 green 1.4×10 -6 1.4×10 -6 blue 3.9×10 -4 0.48 rmse red 4.75 4.43 green 4.21 4.21 blue 4.45 5.86 snr red 7.04 7.53 green 11.39 11.4 blue 10.13 7.70 spectral discrepancy red 3.72 3.46 green 2.54 2.53 blue 2.22 3.35 ergas 2.82 2.98 rase 10.63 11.61 variance red (21.17) 31.83 25.882 green (17.81) 0.002 0.002 blue (10) 3.5 12.5 in this study, the following evaluation factors were used for the qualitative and quantitative analysis of the discussed methods; chi-square test, rmse, snr, sd, ergas, and relative average spectral error (rase) for assessing the fusion results. table 1 shows the fusion result based on case 1 and case 2 of the proposed fusion method. in table 1, columns correspond to the evaluation criteria discussed in section 4, the multispectral band considered and the results of case 1 and case 2 of the proposed method. the rows of table 1 correspond to the evaluation criteria, viz. chi-square test, rmse, snr, sd, ergas, relative average spectral error (rase) as well as the red, green, and blue band data for each criterion used. table advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 177 2 shows the performance of the existing fusion methods, viz. his, brovey, sfim, hps, pca, and multiplicative methods under the evaluation criteria mentioned in the previous section. the columns of table 2 correspond to the existing fusion methods listed above, and the rows of table 2 correspond to the different evaluation criteria, viz. chi-square test, rmse, snr, sd, ergas, and relative average spectral error (rase) as explained in section 4. the comparisons made from table 1 and table 2 for the dataset used in this work can be summarized as follows. table 2 performance evaluation of his, brovey, sfim, hpf, pca and multiplication methods evaluation criteria multispectral band ihs brovey sfim hpf pca multiplication chi square test (p value) red 0.92 1 0.56 1 1 0 green 0.09 1 0.99 1 1 0.1 blue 0.15 1 0.97 1 1 7x10 -4 rmse red 5.38 23.5 7.19 16.02 26.27 3.15 green 5.39 33.38 10.12 23.09 32.88 5.65 blue 5.46 31.71 9.56 21.89 43.88 4.51 snr red 5.72 0.43 5.31 1.12 2.28 11.40 green 8.28 0.44 5.36 1.07 2.45 7.58 blue 7.74 0.44 4.85 1.08 2.04 9.24 spectral discrepancy red 4.62 23.24 4.33 15.85 26.05 2.42 green 4.62 33.19 6.08 22.99 32.84 5.19 blue 4.63 31.57 5.77 21.83 43.87 4.02 rase 14.04 233.21 6 31 15 4 variance red (21.17) 58.4 3.05 37.19 17.52 52.49 35.67 green (17.81) 52.31 4.13 53.07 24.68 17.55 42.63 blue (10) 38.04 3.23 50.45 23.51 10.05 41.58 table 1 shows the performance evaluation of the proposed method (two cases) based on the evaluation parameters used. table 2 gives the performance evaluation of the state-of-art methods, namely his, brovey, sfim, hpf, pca, and multiplication methods using the evaluation indices discussed. the evaluation indices discussed in section 4 have been applied to our proposed method and each of the existing method mentioned in the previous section. the evaluation of each methods is done using the same dataset so that a comparative analysis can be made from the results shown in table 1 and table 2. a numerical analysis between the proposed method and the state-of-art methods based on the evaluation criteria mentioned above is as follows. 5.1. chi-square test from table 1 and table 2, it can be seen that case 1 and case 2 of the proposed method give the smallest p-value for all the xs bands. except for the blue band, the multiplication method gives the least p-value of 0.0007. the p-value indicates the probability of getting a better fit. smaller the p-value better the goodness of fit. therefore, there is a small chance that other methods will provide a better fit than the proposed method. on the other hand, brovey, hpf, and pca methods correspond to a maximum p-value of 1 for all the xs bands. therefore, the fit is poorer in those cases compared to the proposed cases. 5.2. root mean square error (rmse) the rmse value indicates the error between the computed and the observed data. it shows how far the computed data deviate from the observed data. larger the value of rmse, greater the error between the dataset points. the rmse for case 1 was found to be 4.75, 4.21, and 4.45, respectively for the red, green, and blue band while case 2 gives corresponding values of 4.43, 4.21, and 5.86. the rmse of the proposed method was found to be similar compared to that of the multiplicative method which gives a value of 3.15, 5.65, and 4.51, respectively for the red, green, and blue band. but the proposed two cases give a lower value compared to the remaining methods. the brovey and pca methods result in the largest rmse value amongst all the methods indicating that the difference between the original xs and the computed xs is very large. for example, the brovey method gives an rmse value of 23.5, 33.38, and 31.71, respectively for the red, green and blue band. advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 178 5.3. signal to noise ratio (snr) the snr value gives the amount of information contained in the fused output. the snr is the highest for the proposed two cases with a value of 7.04, 11.39, and 10.13 for case 1; 7.53, 11.4 and 7.70 for case 2 for the three bands respectively. the multiplication method also results in similar values of 11.40, 7.58, and 9.24, respectively for the three bands. brovey, hpf, and pca result in the least snr value. for example, the hpf method results with a lower snr value of 2.28, 2.45, and 2.04 for the red, green, and blue band, respectively. 5.4. spectral discrepancy (sd) a low value of sd indicates a good spectral quality. sd is the lowest for the proposed method followed by the multiplication method, while brovey and pca methods give the highest discrepancies. two proposed cases result in the values of 3.72, 2.54, and 2.22 for case 1; 3.46, 2.53, and 3.35 for case 2 for the red, green, and blue band, respectively. on the other hand, the existing methods give a higher value than the proposed methods. for example, a pca based method gives a value of 26.05, 32.84, and 43.87, respectively for the red, green and blue band. as mentioned above, sd indicates the level of spectral quality of the results. higher the value, lower the spectral information. 5.5. erreur relative globale adimensionelle de synthese (ergas) the ergas values of the proposed two cases compare quite well with a value of 2.82 for case 1, and 2.98 for case 2 with the multiplication method value of 3. the remaining methods give a higher ergas value, for instance, hpf and pca give a value of 23 and 22, respectively. a low ergas value indicates a good fusion output. brovey, hpf, and pca methods result in a maximum ergas value and hence indicate a poor output. 5.6. relative average spectral error (rase) the sfim and multiplication methods give a lower rase value of 6 and 4, respectively against the proposed two cases (case 1 and case 2) with a value of 10.63 and 11.61. the brovey method results in the maximum rase value of 233.31. similar to ergas, a low rase value indicates a good result of the output. in terms of variance matching, for both the two cases of the proposed fusion method, the variance of green bands is almost constant with a very small value of 0.002 against the actual variance of 17.81. however, compared to the other methods, case 2 gives the best approximation for red and blue bands of 25.88 and 12.5 against the original variance values of 21.17 and 10, respectively. ihs gives a larger value than the original multispectral variance. and, brovey method results in the lower variance value compared to the actual multispectral variance. though pca seems to result in a closer approximation to the actual variance for green and blue bands, the result is not significant since other evaluation parameters of pca such as the p-value, rmse, sd, ergas, and rase values do not relate well with its variance data. case 2 of the proposed method gives a better approximation to the actual variance for red and blue bands. there are certain specific cases where the existing fusion methods seem to indicate a better result than that of the proposed method. for example, the p-value for the blue band obtained by the ihs method and multiplication method is smaller than the p-value of the proposed method of case 2. the critical value (cv) obtained through his and multiplication methods are small, so the p-value results are small. the rmse value provided by the multiplication method for the red band is also smaller than that provided by the proposed method. the multiplication transform method also gives a higher snr value for the red band. because the rmse value of the multiplication method is smaller and according to snr definition, smaller rmse results in large snr. lastly, the sfim and multiplication transform methods give a lower rase value compared to the proposed method. however, in summary, it is clear that overall the proposed cases of 1 and 2 outperform all the existing methods. advances in technology innovation, vol. 5, no. 3, 2020, pp. 166-181 179 6. conclusion in this paper, a new pixel value-based image fusion method of a high-resolution panchromatic band and a low-resolution multispectral band were proposed. a linear regression relationship between the panchromatic and multispectral band was formulated. a lagrange multiplier based objective function which seeks to maximize spectral consistency and tracks variance of the given data independently was formed. the results of the proposed pan-sharpening method were compared with a few existing image fusion methods such as his, brovey, sfim, hpf, pca, and multiplication methods on a common set of ikonos satellite data. the comparison was made based on seven evaluation criteria. considering overall performance, the proposed method came out favorably when compared with all other existing methods because the majority of the evaluation indices gave a better result for the proposed method. however, there were a few cases of isolated improved data for the existing methods on certain criteria compared to the proposed method as pointed out under the discussion section. nevertheless, improved results of the existing methods seemed to be sporadic and not supported all criteria, so the performance of the existing methods put into question. hence, it can be concluded that the proposed method outperforms the existing methods based on common data and independent criteria. as future work, it is necessary to study how far the improved performance of the proposed method is robust in the sense 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[45] a. vesteinsson, j. r. sveinsson, j. a. benediktsson, and h. aanaes, “spectral consistent satellite image fusion: using a high resolution panchromatic and low resolution multi-spectral images,” proc. 2005 ieee international geoscience and remote sensing symposium, vol. 4, pp. 2834-2837, july 2005. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 an experimental study of plastic waste as fine aggregate substitute for environmentally friendly concrete anita intan nura diana 1,* , subaidillah fansuri 1 , akhmad feri fatoni 2 1department of civil engineering, wiraraja university, sumenep, indonesia 2department of nursing, wiraraja university, sumenep, indonesia received 29 december 2020; received in revised form 06 april 2021; accepted 07 april 2021 doi: https://doi.org/10.46604/aiti.2021.6930 abstract decomposing plastics, including plastic bottles, is a very difficult process because it takes 50-100 years. every year, the use of plastic bottles is increasing, but only few people are willing to treat plastic bottle waste. in this study, plastic bottle waste is used as a substitute of fine aggregate and shaped in such a way to have a sand-like gradation. the variations of graded plastic bottle waste are 0%, 5%, 10%, and 12%. the test objects for each variation consist of three specimens. data are analyzed by using regression and classical assumption test with spss program. the results of the data analysis show that there is a simultaneous effect on the compressive strength with variations in plastic waste substitution. the compressive strength decreases with the increase in the percentage of plastic added. maximum compressive strength is at the variations of 0% and 5% with19.192 mpa and 16.414 mpa, respectively. keywords: environmentally friendly concrete, plastic waste, compressive strength 1. introduction plastic bottle waste is one of the most common environmental problems in this era. plastic is a material that is difficult to decompose, taking up to 50-100 years. every year, the amount of plastic bottle waste is increasing because people use plastic-based packaging almost every day. nonetheless, people are less aware that behind the use of plastic materials, the recycling process of plastic bottle waste is not optimal. some people recycle plastic bottle waste by converting them into vases, bags, and furniture so that it can be reused. however, the results of the survey conducted in sumenep area regarding the recycling process of plastic bottle waste are still limited. in the field of structure and materials, there have been many studies using plastic bottle waste as a research subject. using plastic bottle waste as construction materials can reduce environmental damages caused by plastic waste pollution. in this study, plastic bottle waste is used as a substitute of fine aggregate and shaped in such a way so that its gradation is similar to the common fine aggregate, i.e. the sand. sand is the main ingredient for making concrete. the sand used in the concrete mixture is black sand, which is more suitable than other types of sand for building construction. the black sand content has a good binder with other concrete mixture materials. behind the excellent use of black sand in building construction, a very serious problem arises. land damage has often occurred due to uncontrolled mining of black sand (illegal mining) around the sand mining area. in the last few years, there have been conflicts that claimed the lives of environmentalists in the mining areas, including lumajang area. every day, black sand mining is carried out in the lumajang area to meet consumer demand without any restrictions on black sand mining which will have a negative impact on the surrounding environment. * corresponding author. e-mail address: anita@wiraraja.ac.id tel.: +62-81332299841 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 sumenep does not have black sand materials for infrastructure purposes. the black sand in sumenep regency is imported from outside the city. therefore, it is not surprising that the price of black sand in sumenep regency is quite high since the demand is high. as a result, people in sumenep regency have started many private companies and agencies that prioritize in building materials for fine aggregate using black sand. various studies have been carried out on utilizing plastic waste as a substitute of fine aggregate [1-11]. guendouz et al. [1] investigated the use of two types of plastic scrap with the pet and ldpe logos used for the manufacture of fine aggregate in the form of powder in concrete z. diana and depriyanto [2] examined the effect of adding plastic fibers to paving blocks on compressive strength, shock resistance, and water absorption. karimah [3] studied the compressive strength of normal strength concrete by adding 15%, 30%, and 45% ldpe plastic waste. alvine [4] investigated the compressive strength of concrete by adding 20%, 40%, and 60% abs plastic waste. previous research combined plastic waste with other materials as a substitute for concrete mixtures. among these materials are electronic plastic waste and marble dust on hardened properties of high-strength concrete [9] and plastic/rubber waste as environmentally friendly aggregates for concrete mixtures [10]. adela, behanu, and gobena [11] utilized plastic waste as an alternative material for coarse aggregates. several studies have shown that adding a number of plastic waste to the concrete mixture can reduce the quality of the concrete production [9-11]. based on the previous research, further research on the use of plastic waste for concrete mixture is needed. research can be in the form of variations in processing plastic waste and the addition of additives. table 1 literature review ref. plastic type shape replacement level aggregate replacement type application [1] pet + ldpe fibers and powder powder: 10%, 20%, 30%, and 40% fibers: 0.5%, 1%, 1.5%, and 2% fine concrete [2] pet fibers 0%, 0.25%, 0.50%, 0.75%, and 1% coarse paving block [3] ldpe flakes 15%, 30%, and 45% coarse concrete [4] abs flakes and powder 20%, 40%, and 60% coarse and fine concrete [5] e-plastic waste flakes 0%, 5.5%, 11%, and 16.5% coarse concrete [6] ldpe powder particles below 75 μm fine [7] ldpe shredded 5%, 10%, 15%, 20%, and 25% fine concrete [8] ldpe powder 15% and 30% fine concrete [9] e-plastic waste irregular flakes 0%, 10%, 20%, 30%, and 40% coarse and fine concrete [11] plastic bags and plastic bottles irregular 0%, 25%, 35%, and 50% coarse concrete table 1 shows several types and shape of plastic waste that have been used in previous studies. based on the background discussion above, only few researchers in sumenep district utilized plastic waste as substitute of fine aggregate in concrete mixture.this study focuses on the use of graded plastic bottle waste (the plastic type is pet) as a substitute of fine aggregate, and uses the local coarse aggregates originating from duko village, rubaru district, and sumenep regency based on the results of research conducted by fansuri et.al [12]. the use of local materials is intended as a form of sustainability of construction materials by local construction actors in sumenep regency. 2. research methodology 2.1. flow chart of the study fig. 1 shows the flow chart of the approach for this study. the process consists of five steps: problem statement, data collection, analysis data, result and discussion, and conclusions.the five steps are described as follows: 180 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 step 1: problem statement the most important background is the plastic bottle waste problem that we face in this era. plastic is a material that is difficult to decompose, which takes 50-100 years to decompose. every year the amount of plastic bottle waste is increasing because almost every day people use plastic-based packaging. it takes innovation to turn plastic waste into construction materials (see introductory section for detailed explanations). step 2: data collection data are divided into primary data and secondary data. primary data are collected through experiments in the civil engineering laboratory by testing the aggregate materials for their density, water content, and sieve analysis, by making fresh concrete started with the calculation of mix design, manufacture of test object, slump test, concrete molding, and concrete curing, and by testing the compressive strength of fresh concrete. secondary data are obtained by reviewing similar previous research and by testing the standards used in the study. the standards include the specific gravity test, water absorption of fine and coarse aggregates, fine aggregate and coarse aggregate sieve analysis testing, concrete manufacturing procedures, and concrete compressive strength testing. step 3: data analysis primary data are especially analyzed by using classical assumption tests (linearity test, normality test, and heteroscedasticity test) and linier regression. all the analyses in the study are executed by using spss software. step 4: result and discussion at this stage, all the experimental and analytical results will be displayed in the form of tables, figures, and detailed calculations. then, the obtained experimental results and analysis are compared with the previous literature. step 5: conclusion at this stage, conclusions and recommendations will be obtained from the results of the experiments and analyses that have been carried out. fig. 1 research methodology 2.2. model the model used in this study is fresh concrete with a mixture of plastic bottle waste. plastic bottles are cut into small pieces to resemble grading sand. furthermore, the small pieces of plastic waste used as a substitute for sand for the concrete mixture are divided into several variations. there are three concrete specimens as samples for each variation. the concrete compressive strength test is carried out for 14 days. table 2 presents the test objects for each substitute variation. problem statement data collection primary data secondary data analysis data results and discussion conclusions 181 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 table 2 plastic gradient variation for each specimen plastic gradient variations specimen for each variation 0% 3 5% 3 10% 3 12% 3 total samples 12 2.3. data analysis the data to be analyzed are obtained from the results of testing in the laboratory. data from the laboratory are presented in tables and graphs. data are analyzed using linear regression with classical assumption tests (linearity test, normality test, and heteroscedasticity test). all the analyses use spss program which are presented in the form of tables, pictures, and descriptions. 3. results and discussion the results of this study consist of several test results for concrete mixtures (fine and coarse aggregate). after concrete compressive strength tests are carried out at the civil engineering laboratory, compressive strength test data are analyzed using spss software. the results of the study are described below. 3.1. fine aggregate experiments there are several experiments carried out in the laboratory to determine the quality of fine aggregate, including water content experiment, specific gravity experiment [13], and sieve analysis experiment [14]. the following is the result of the water experiments in the laboratory. table 3 data testing and calculation of fine aggregate water content experiment 1 2 3 weight of original fine aggregate (w1) 500 gr 500 gr 500 gr weight of oven-dry fine aggregate (w2) 485 gr 487 gr 486 gr water content of fine aggregate (w1 − w2) / w2 × 100% 3.52% 2.67% 2.88% average of water content 3.023% from the test shown in table 3, it can be seen that the average value of fine aggregate water content is 3.023%. the greater the difference between the original weight of the fine aggregate and the weight of the fine aggregate after being heated, the more water the aggregate will contain. from the test shown in table 4, it can be seen that dry specific gravity is 2.56, saturated surface dry (ssd) is 2.62, apparent specific gravity is 2.71, and absorption is 2%. detailed calculations can be seen in table 4. table 4 data testing and calculation of fine aggregate density experiment 1 2 3 average weight of pycno + ssd fine aggregate + water (w1) 1005 1019 1017 weight of ssd fine aggregate (500 gr) 500 500 500 weight of pycno + water (w2) 705 705 705 weight of oven-dry fine aggregate (w3) 490 490 490 dry specific gravity = w3 / (w2 + 500 − w1) 2.45 2.63 2.60 2.56 ssd specific gravity = 500 / (w2 + 500 − w1) 2.50 2.69 2.66 2.62 apparent specific gravity = w3 / (w2 + w3 − w1) 2.58 2.78 2.75 2.71 absorption = [(500 − w3) / 500] × 100% 2% 2% 2% 2% 182 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 figs. 2-5 illustrate the fine aggregate grading zone graphs. the value to illustrate the graph of the fine aggregate zone is obtained from table 5. from the fine aggregate gradation graphs, it can be seen that the fine aggregate used is at the gradation limit no. 3. furthermore, the amount of sand replaced by plastic bottle waste adjusts the selected gradation. it is done so that the plastic grading is similar to the sand grading used. the materials used in this study are shown in fig. 6. table 5 data testing and calculation of fine aggregate sieve analysis filter size restrained weight (gr) cumulative restrained weight (gr) cumulative restrained (%) cumulative passes (%) mm inch 4.8 3/8 30 30 3 96.95 2.36 8 46 76 7.72 92.28 1.70 12 60 136 13.81 86.19 1.18 16 73 209 21.22 78.78 0.60 30 210 419 42.54 57.46 0.425 40 160 579 58.78 41.22 0.30 50 42 621 63.05 36.95 0.15 100 301 922 93.60 6.40 0.075 200 48 970 98.48 1.52 pan 15 985 100 0 total 985 0 20 40 60 80 100 0.01 0.1 1 10 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 2 fine aggregate gradation limit no. 1 0 20 40 60 80 100 0.01 0.1 1 10 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 3 fine aggregate gradation limit no. 2 0 20 40 60 80 100 0.01 0.1 1 10 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 4 fine aggregate gradation limit no. 3 183 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 0 20 40 60 80 100 0.01 0.1 1 10 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 5 fine aggregate gradation limit no. 4 (a) sand (b) plastic bottle waste (c) graded plastic fig. 6 materials used in this study 3.2. coarse aggregate experiment there are several experiments conducted in the laboratory to determine the quality of the local coarse aggregate in duko village, rubaru district [12]. the experiments include sieve analysis experiment [14] and water content experiment, specific gravity experiment [15]. the followings are the results of the experiments. table 6 data testing and calculation of coarse aggregate water content experiment 1 2 3 weight of original coarse aggregate (w1) 500 gr 500 gr 500 gr weight of oven-dry coarse aggregate (w2) 401 gr 401 gr 401 gr water content of coarse aggregate (w1 − w2) / w2 × 100% 24.7% 24.7% 24.7% average of water content 24.7% from the test shown in table 6, it can be seen that the average of coarse aggregate water content value is 24.7%. the greater the difference between the original weight of the fine aggregate and the weight of the fine aggregate after being heated, the more water the aggregate will contain. from the test shown in table 7 below, it can be seen that the dry specific gravity is 2.02, ssd specific gravity is 2.52, apparent specific gravity is 4.03, and absorption is 24.69%. table 7 data testing and calculation of coarse aggregate density experiment 1 2 3 average weight of the test specimen in saturated surface dry condition (w1) 500 500 500 bucket weight in water (w2) 631 631 631 bucket weight + specimen in water (w3) 930 935 932 weight of oven-dry coarse aggregate (w4) 401 401 401 dry specific gravity = w4 / (w2 + w1 − w3) 2.00 2.05 2.02 2.02 ssd specific gravity = w1 / (w2 + w1 − w3) 2.49 2.55 2.51 2.52 apparent specific gravity= w4 / (w2 + w4 − w3) 3.93 4.13 4.01 4.03 absorption = [(w1 − w4) / w4] × 100% 24.69% 24.69% 24.69% 24.69% 184 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 figs. 7-9 illustrate the coarse aggregate grading zone graphs. the value to illustrate the graph of the coarse aggregate zone is obtained from table 8. based on the experimental results and gradation limit of coarse aggregate sieve analysis, it is obtained that the coarse aggregate gradation is in the coarse aggregate gradation with a maximum size of 40 mm. table 8 data testing and calculation of coarse aggregate sieve analysis filter size restrained weight (gr) cumulative restrained weight (gr) cumulative restrained (%) cumulative passes (%) mm inch 76.20 3 0 0 0 100 50.8 2 0 0 0 100 38.1 1.5 0 0 0 100 25.40 1 318 318 35.14 64.86 19 3/4 235 553 61.10 38.90 13.20 1/2 70 623 68.84 31.16 8.5 3/8 110 733 80.99 19.01 4.75 #4 160 893 98.67 1.33 2.36 #8 12 905 100 0 0.15 100 0 905 100 0 pan 0 905 100 0 total 1000 0 20 40 60 80 100 1 10 100 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 7 coarse aggregate gradation limit (10 mm) 0 20 40 60 80 100 1 10 100 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 8 coarse aggregate gradation limit (20 mm) 0 20 40 60 80 100 1 10 100 % c um m u la ti ve filter size lower limit upper limit % cummulative passes fig. 9 coarse aggregate gradation limit (40 mm) 185 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 3.3. concrete mix design planning mix design planning is an important stage in concrete planning. based on the mix design planning, the composition of coarse aggregate, fine aggregate, cement, and water can be obtained. in this study, mix design planning uses the indonesian national standard (sni) 03-2834 [16]. data of concrete mixture material are used to create three specimens for each variation, providing the required compressive strength in 23 mpa equivalents to k270. concrete mixture data for each variation is shown in table 9. table 9 data of concrete mixture material concrete mixture material variation 0% (kg) variation 5% (kg) variation 10% (kg) variation 12% (kg) total (kg) cement 3.43 3.43 3.43 3.43 13.72 water 2.035 2.035 2.035 2.035 8.14 coarse aggregate 12.571 12.571 12.571 12.571 50.284 fine aggregate 8.109 7.704 7.298 7.136 30.247 plastic bottle waste 0.405 0.811 0.973 2.189 3.4. concrete slump testing in this study, the stages and calculations of concrete slump testing use the procedure listed in the indonesian national standard (sni) 1972 [17]. fig. 10 shows the tool used in the slum test, namely the abram cone. the test tool must be a mold made of a metal material that is not sticky and does not react with cement paste. the thickness of the metal shall not be less than 1.5 mm, and when it is formed by a spinning process, there shall be no dots in the mold and its thickness is smaller than 1.15 mm. the mold must be cone-shaped with a base diameter of 203 mm, top diameter of 102 mm, and height of 305 mm. the base and top faces of the cone must be open and parallel to each other and perpendicular to the axis of the cone. the mold must be equipped with a treadle section and a handle as shown in fig. 10. fig. 10 mold for slump test (abram cone) table 10 data testing and calculation of slump value plastic waste variation mold of slump test height (cm) height of each specimen (cm) slump value for each specimen (cm) average (cm) 1 2 1 2 0% 30 19 21 11 9 10 5% 30 21 21 9 9 9 10% 30 20 22 10 8 9 12% 30 22 21 8 9 8.5 based on table 10, which shows the slump plan set in 60-180 mm, the results of the laboratory experiments meet the requirements. the lowest average value of the slump test is 85 mm and the highest value is 100 mm. this value is within the planned slump value. 186 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 3.5. concrete compressive strength this concrete compressive strength test is carried out according to the procedure in the indonesian national standard (sni) 1974 [18]. the detailed results of the concrete compressive strength test can be seen in tables 11-14. table 11 data testing and calculation of concrete compressive strength value in 0% variation sample date weight (kg) p (n) a (mm2) age conversion (14 days) compressive strength (f’c) mpa characteristic concrete (k) kg/cm2 create test 1 06/05/2020 20/05/2020 8.143 340000 22500 0.88 17.172 206.888 2 06/05/2020 20/05/2020 8.064 395000 22500 0.88 19.949 240.355 3 06/05/2020 20/05/2020 8.083 405000 22500 0.88 20.455 246.440 average of variation: 0% 19.192 231.228 table 12 data testing and calculation of concrete compressive strength value in 5% variation sample date weight (kg) p (n) a (mm2) age conversion (14 days) compressive strength (f’c) mpa characteristic concrete (k) kg/cm2 create test 1 12/05/2020 26/05/2020 7.926 410000 22500 0.88 20.707 249.483 2 12/05/2020 26/05/2020 7.615 360000 22500 0.88 18.182 219.058 3 12/05/2020 26/05/2020 8.058 205000 22500 0.88 10.354 124.741 average of variation: 5% 16.414 197.761 table 13 data testing and calculation of concrete compressive strength value in 10% variation sample date weight (kg) p (n) a (mm2) age conversion (14 days) compressive strength (f’c) mpa characteristic concrete (k) kg/cm2 create test 1 18/05/2020 01/06/2020 7.240 240000 22500 0.88 12.121 146.039 2 18/05/2020 01/06/2020 7.200 185000 22500 0.88 9.343 112.571 3 18/05/2020 01/06/2020 7.160 200000 22500 0.88 10.101 121.699 average of variation: 10% 10.522 126.770 table 14 data testing and calculation of concrete compressive strength value in 12% variation sample date weight (kg) p (n) a (mm2) age conversion (14 days) compressive strength (f’c) mpa characteristic concrete (k) kg/cm2 create test 1 18/05/2020 01/06/2020 7.284 215000 22500 0.88 10.859 130.826 2 18/05/2020 01/06/2020 7.140 210000 22500 0.88 10.606 127.784 3 18/05/2020 01/06/2020 7.247 200000 22500 0.88 10.101 121.699 average of variation: 12% 10.522 126.770 fig. 11 shows the relationship between the variations of plastic waste substitution in the fine aggregate of concrete mixture and the result of compressive strength value. the highest compressive strength is shown by concrete without plastic waste substitution in the concrete mixture (19.19 mpa in 0% variation). there is a decrease in compressive strength that is in line with the increase in the amount of plastic waste added to the concrete mixture. all the results of the compressive strength of the concrete, none of them meets the compressive strength requirements in 23 mpa. there are several factors that cause failure to pass in this experiment. first, the coarse aggregate material used do not meet the overall sni requirements. the aggregate material in this study uses the local aggregate in sumenep area. in a study conducted by fansuri et al. [12] in five local coarse aggregate mining locations, namely batuan village, batu putih village, dasuk village, duko village, and ellak daya village, it can be seen that the aggregate in duko village met the parameters of coarse aggregate as a concrete material, where the water absorption was 1.83% (maximum value is 3%), specific gravity was 187 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 2.57 (minimum value is 1.8), test value wear and tear using los angeles was 24.8% (maximum value is 40%), and volume weight was 2075.5 kg/m3 (minimum value is 2200 kg/m3). second, several studies that have been done previously explained that the use of additives in the form of additives (chemical compounds) is needed as the liquid can add strength to concrete with variations of plastic waste. meanwhile, the experiments conducted in this study do not use added materials in the form of additives (chemical compounds). 0 5 10 15 20 25 0% 5% 10% 15% c o m p re s s iv e s tr e n g th v a lu e ( m p a ) variation of plastic waste fig. 11 compressive strength relationship and plastic waste variations 3.6. normality test of concrete normality test in this study uses the spss for windows program. the normality test is used to determine whether the obtained research data has a normal distribution or not. from table 15, it can be seen that the spread of unstandardized residual value is normal because the significant value is 0.200 > 0.05 (normally distributed). therefore, this analysis can be processed to regression analysis because the conditions in the classical assumption test, in this case the residual value, have been stated as normally distributed. table 15 normality test result of unstandardized residual using one-sample kolmogorov-smirnov test n 12 normal parametersa,b mean 0.0000000 std. deviation 31.61054075 most extreme differences absolute 0.194 positive 0.194 negative -0.183 test statistic 0.194 asymp. sig. (2-tailed) 0.200c,d a. normal test distribution b. calculated from data c. lilliefors significance correction d. lower bound of the true significance 3.7. heteroscedasticity test of concrete this test is used to determine deviation of the classic assumptions of heteroscedasticity because there is an inequality of variance from one residual observation to another, while in the regression model, it is actually expected to be constant. in this test, the researchers use the spss 25 for windows program and the glejtser method. the symptom of heteroscedasticity is shown by the regression coefficient of the independent variable on the absolute value of the residual. in decision making, there is no symptom of heteroscedasticity if the probability value is greater than the alpha value (0.05). from table 16, it can be concluded that heteroscedasticity do not occur in the regression model because the sig. variation of plastic waste to the absolute residual is 0.386 > 0.05. 0% 5% 10% 15% variation of plastic waste 188 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 table 16 result of heteroscedasticity test of concrete model unstandardized coefficient standardized coefficient t sig. b std. error beta 1 constant 30.647 10.761 2.848 0.017 plastic waste variation -1.189 1.312 -0.275 -0.906 0.386 a. dependent variable: re3 3.8. hypotheses test and regression equations there are two variables in this study, namely independent variable (x) and dependent variable (y). variable x is variation of plastic waste, and variable y is concrete compressive strength. the hypotheses in this study are as follows. (1) ho: there is no simultaneous effect between variable x on variable y. (2) ha: there is a simultaneous effect between variable x on variable y. table 17 anova test result anovaa model sum of squares df mean square f sig. 1 regression 23784.941 1 23784.941 21.639 0.001b residual 10991.489 10 1099.149 total 34776.430 11 a. dependent variable: compressive strength b. predictors: constant, plastic waste variation hypotheses test can be done using the f test and significance test (probability). the test rule is to use the f test under several conditions: if f value ≤ f table, ho is accepted; if f value > f table, ho is rejected. based on the calculation, the f value of the anova table is 21.639 and the f table value is 4.96. thus, it can be concluded that f value > f table. it means ho is rejected, or in other words, ha is accepted (there is simultaneous effect between variable x on variable y). the significance test (probability) is conducted under several conditions: if probability (sig.) > α, ho is accepted; if probability (sig.) < α, ho is rejected. based on table 17, the probability value (sig.) = 0.001 and the significant level value α = 0.05. therefore, it can be concluded that the probability value (sig.) < α. it means ho is rejected, or in other words, ha is accepted (there is a simultaneous effect between variable x on variable y). table 18 coefficient results of compressive strength regression analysis coefficienta model unstandardized coefficients standardized coefficients t sig. 95% confidence interval for b b std. error beta lower bound upper bound 1 constant 235.162 16.853 13.954 0.000 197.611 272.713 plastic waste variation -9.560 2.055 -0.827 -4.652 0.001 -14.139 -4.981 a. dependent variable: compressive strength based on table 18, it can be analyzed that the regression equation model for the simultaneous effect on compressive strength with plastic waste variation is y = 235.162 – 9.560 x, compressive strength without the addition of variation of plastic bottle waste is x = 0, and the value of compressive strength is (y) = 235.162 kg/cm2 (19.518 mpa). if the addition of variation of plastic bottle waste is x = 1%, it is estimated that the value of compressive strength (y) = 235.162 – 9.560 (1) = 225.602 kg/cm2 (18.725mpa) is added. every 1% addition of plastic bottle waste will decrease the compressive strength of the concrete by 9.560 kg/cm2 (0.793 mpa). 189 advancesin technology innovation, vol. 6, no. 3, 2021, pp. 179-190 4. conclusions based on the results of the analysis and discussion in the previous section, the following conclusions are obtained. (1) the linear regression equation for the variation of plastic waste on the compressive strength of concrete is y=235.162– 9.560x, meaning that there is a significant influence between the variation of plastic waste on the compressive strength of concrete. (2) the more plastic waste added into the variation, the lower the concrete compressive strength, where the maximum compressive strength is at the variations of 0% and 5%, namely 19.192 mpa for the variation of 0% and 16.414mpa for the variation of 5%. in general, the concrete which contains more plastic has poorer durability performance. conflicts of interest the authors declare no conflict of interest. references [1] m. guendouz, f. debieb, o. boukendakdji, e. h. kadri, m. bentchikou, and h. soualhi, “use of plastic waste in sand concrete,” journal of materials and environmental science, vol. 7, no. 2, pp. 382-389, october 2016. [2] a. i. n. diana and h. depriyanto, “the effect of using economic plastic fiber (eco plafie) paving block on compressive strength, shock resistance, and water absorption as environmentally friendly products,” national conference on mathematics, science and education, madura islamic university press, october 2018, pp. 19-26. [3] h. karimah, “experimental study of the effect of ldpe cast plastic content on the compressive strength of normal strength concrete,” thesis, department civil engineering, parahyangan catholic university, bandung, jawa barat, 2018. [4] alvine, “experimental study of the effect of abs plastic waste as a partial substitution of concrete aggregates with a design compressive strength of f’c = 35 mpa,” thesis, department civil engineering, parahyangan catholic university, bandung, jawa barat, 2019. [5] s. suleman and s. needhidasan, “utilization of manufactured sand as fine aggregates in electronic plastic waste concrete of m30 mix,” materials today, vol. 33, no. 1, pp. 1192-1197, september 2020. [6] b. v. bahoria, d. k. parbat, and p. b. nagarnaik, “xrd analysis of natural sand, quarry dust, waste plastic (ldpe) to be used as a fine aggregate in concrete,” materials today, vol. 5, no.1, pp. 1432-1438, february 2018. [7] s. s. mathi, v. johnpaul, r. sindhu, p. r. riyas, and n. chidambaram, “mechanical properties of concrete with plastic as partial replacement of fine aggregate,” materials today: proceedings, in press. [8] z. c. steyn, a. j. babafemi, h. fataar, and r. combrinck, “concrete containing waste recycled glass, plastic, and rubber as sand replacement,” construction and building materials, vol. 269, 121242, february 2021. [9] a. evram, t. akçaoğlu, k. ramyar, and b. çubukçuoğlu, “effects of waste electronic plastic and marble dust on hardened properties of high strength concrete,” construction and building materials, vol. 263, no. 1, pp. 1-10, september 2020. [10] x. li, t. c. ling, and k. h. mo, “functions and impacts of plastic/rubber wastes as eco-friendly aggregate in concrete—a review,” construction and building materials, vol. 240, no. 1, pp. 1-13, december 2019. [11] y. adela, m. behanu, and b. gobena, “plastic wastes as a raw material in the concrete mix: an alternative approach to manage plastic wastes in developing countries,” international journal of waste resources, vol. 10, no. 382, pp. 1-7, june 2020. [12] s. fansuri and a. i. n. diana, “characteristics of coarse aggregate and fine aggregate for building materials in sumenep regency,” national conference on mathematics, science, and education, madura islamic university press, october 2018, pp. 9-18. [13] method of test for specific gravity and water absorption of fine aggregate, indonesian national standard 1970, 2008. [14] test method for fine aggregate and coarse aggregate sieve analysis, indonesian national standard astm c136, 2012. [15] method of test for specific gravity and water absorption of coarse aggregate, indonesian national standard 1969, 2008. [16] procedure for making a normal concrete mix plan, indonesian national standard 03-2834, 2000. [17] how to test a concrete slump, indonesian national standard 1972, 2008. [18] how to test concrete compressive strength with cylindrical test objects, indonesian national standard 1974, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 190 2___aiti#8933_in press advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 behavior of built-up cold-formed steel stub columns infilled with washed bottom ash concrete mohd syahrul hisyam mohd sani 1,* , fadhluhartini muftah 1 , nor maslina mohsan 1 , bishir kado 2 1 school of civil engineering, college of engineering, universiti teknologi mara (uitm) cawangan pahang, bandar jengka, malaysia 2 department of civil engineering, faculty of engineering, bayero university, kano, nigeria received 18 november 2021; received in revised form 25 january 2022; accepted 26 january 2022 doi: https://doi.org/10.46604/aiti.2022.8933 abstract the main objective of the study is to determine the behavior of built-up cold-formed steel (cfs) stub columns infilled with washed bottom ash (wba) concrete and also their failure mode. five proportions of wba as sand replacement in concrete and five specimens of built-up cfs stub columns infilled with wba are produced in this study. there are four parts of the testing conducted: material properties of cfs, material properties of wba concrete, mechanical properties of the connection, and mechanical behavior of built-up cfs stub columns. the result shows that the specimen with 25% wba is reported to have the highest value of compressive strength in the material properties of wba concrete and the mechanical behavior of built-up cfs stub column. the percentage difference of the ultimate load of the built-up cfs column filled with normal concrete and filled with wba concrete is noted to have a range of 3% to 25%. keywords: built-up section, cold-formed steel, stub column, washed bottom ash concrete, buckling 1. introduction cold-formed steel (cfs), sometimes identified as a thin-walled structure, is generally used as construction material either structural or non-structural element. cfs is produced by using steel sheets through a rolling process in ambient temperature, and is different from the hot-rolled steel produced by using high technology and huge machine in high temperature with an energy-consuming process. cfs is with many advantages such as being lightweight, ease of transportation, quick installation and erection, corrosion resistance, high strength to weight ratio, etc., and is normally utilized as a wall frame or panel, roof truss structure, and storage rack. cfs is formed in a variety of shapes, thicknesses, and cross-section areas, with the channel, hat, angle, and zee section normally found in the construction market. this section is becoming popular due to its ability for minimizing the total production or material cost. this popular section is classified as an open section which is common in the unsymmetrical section and exposed to structural integrity issues and failure. the development of cfs is constantly changing in line with technological changes such as the production of complex shapes and cross-sections, enhancing the quality of steel material, producing corrosion resistance methods, and improvising methods of forming [1]. in overcoming the issue of structural integrity, this section is established by using a combination of two or more sections to produce the symmetrical section and sometimes it becomes a closed section. selvaraj and madhavan [2] mentioned about the cfs section with an unsymmetrical or single symmetrical or open section that failed due to the instability effect. also, they mentioned that cfs is designed to transform to the built-up section which is classified as a close section or * corresponding author. e-mail address: msyahrul210@uitm.edu.my tel.: +60123267055 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 double symmetrical section. the new section which is recognized as the built-up section has existed in a variety of shapes, cross-section areas, and dimensions. the basic of the built-up section by using channel section is a back-to-back configuration or known as the i-section and face-to-face configuration or also as box-up or a hollow section. fig. 1 illustrates the example of a built-up face-to-face and back-to-back cfs section by using a variety of sections. muftah et al. [3] reported the result of the behavior of built-up face-to-face cfs section with difference channel section which is fastened by using bolt and nut and known as outstand and extended stiffener under bending load. by producing the built-up section, the production cost of the section can be reduced and the cost of using an expert and high technology machine can be reduced. the build-up section is formed by using a variety of fasteners or connectors, for instance, bolt and nut, full welding, spot welding, self-tapping screw, self-drilling screw, rivet, and innovation fastener. li et al. [4] have stated that the compression capacity in the axial condition of the built-up column section is allowed twice and more than twice of the basic section in producing the closed or symmetrical section. nie et al. [5] mentioned that there are a lot of researchers who studied screw spacing and thickness effect on the strength of built-up back-to-back cfs columns that are broadly utilized in engineering activity due to quick assembly and installation. meza et al. [6] stated that the performance and fundamental knowledge of built-up cfs columns are still limited. the main objective of the study is to determine the mechanical behavior of the built-up cfs columns under compression load and observe the failure mode of the columns. furthermore, the study is also to determine the suitable proportion which would provide the optimum mechanical behavior of built-up cfs columns with different proportions of the washed bottom ash (wba) as sand replacement in concrete for solving the structural integrity issues and failures. (a) face-to-face and back-to-back [8] (b) back-to-back [9] fig. 1 the example of the built-up cfs section 2. built-up cold-formed steel column the built-up cfs column is normally provided of the mechanical behavior, especially the ultimate load value with twice or more than twice of the individual section under axial compression [4]. roy and lim [7] have reported the built-up face-to-face 93 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 channel column which is classified as a hollow section with twice the strength of the individual section, and have promoted that the stability of the section is suitable to use in frames. in american iron and steel institute (aisi s100-16) and australia and new zealand (as/nz) specification, the built-up cfs section is designed by modifying the slenderness ratio (kl/r)m: 22 m o i kl kl a r r r = +                  (1) where (kl/r)o is the overall slenderness ratio, a is the length of the intermediate fastener, and ri is the radius of gyration (minimum). cfs with a thin and slender section as compression or flexural member tends to have the buckling failure, such as local, distortional, global and lateral buckling, web crippling, and torsion when subjected to load. the local, distortional, global, and lateral buckling of the cfs section is illustrated in fig. 2. several factors involved in the buckling failure of the cfs section are the cross-section, shape, imperfection, slenderness ratio, and height. normally, the column is divided by referring to the slenderness ratio into three categories: short, intermediate, and slender columns; the short column fails due to yielding, while the slender column fails due to buckling [10]. rokilan and mahendran [11] stated that the local buckling affected the cfs section to fail because the cfs section has a larger width-to-thickness ratio and is not similar to the hot-rolled steel section. selvaraj and madhavan [2] described that the individual cfs section, which is classified as an open or slender section, has failed in several ways such as local, distortional, and global buckling when the structural section is exposed to the instability conditions. nie et al. [5] reported that local buckling and local-flexural buckling happened for the cfs closed section, and the built-up closed section with two channel sections could avoid the distortional buckling when subjected to compressive load. li et al. [4] reported that the study on the mechanical behavior of the built-up cfs, especially the effect of the distortional buckling, is still limited, and no research has been discussed due to the complexity of the cross-section. (a) local (b) distortional (c) global (d) lateral fig. 2 the buckling failure of the cfs section 3. built-up cold-formed steel column with concrete the built-up cfs incorporated with concrete and mortar as the column structure is increased due to an increase in the demand for the tall building construction. the composite structure is produced to be excellent in strength, buckling resistance, seismic resistance, and fire resistance, and is also capable to reduce the production cost and material cost. ibanez et al. [12] reported that the combination of steel and concrete is broadly used in huge infrastructure and tall buildings because of its economic aspects, good structural behavior and bearing capacities, and better ductility. the built-up cfs column with concrete can delay the deformation and crack of the concrete when subjected to axial compression, and acts as a permanent formwork that replaces the timber formwork. zhu et al. [13] reported that the normal and self-consolidating concrete with a design strength of 30 mpa is utilized and filled into cfs tubes with 200 mm × 200 mm, square hollow section. mohd sani et al. [14] analyzed the resistance of the built-up face-to-face cfs column, which is fastened by bolt and nut and filled with normal concrete for the height of the column of 900 mm. qu et al. [15] studied the axial 94 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 compression behavior of the rectangular cfs tubes filled with concrete under two different loading methods. in design standard eurocode 4, the plastic resistance to compression (npl,rd) of the composite column based on the ultimate limit states is determined by the equation: , 0.85a y ck s sk pl rd c ma c s a f f a f n a= + +      γ γ γ (2) where aa is the cross-section areas of structural steel; ac is the cross-section areas of concrete; as is the cross-section of reinforcement; fy is the yield stress of steel; fck is the strength of concrete; fsk is the yield stress of steel reinforcement; ɣma, ɣc, and ɣs are the partial safety factors at the ultimate limit states. in general, the stub column or known as the short column is tested to obtain the structural behavior information as comprehensive and inclusive parametric studies to further assess the failure mode for considering varieties of the steel slenderness value and grades. besides, when the length of the beam or slab is extended for any reason, the stub column is utilized as a structure and specifically acts as a concentrated point load which is designed and built above the beam. the stub column is sometimes planned as an interior aspect and utilized to improve the stability of the building. the testing of the stub column is conducted to evaluate the effect of the width-thickness ratio (b/t) on buckling behavior and bearing capacity. bottom ash (ba) is the waste product from coal-fired electric power plants which physically is lightweight and has a granular, porous, and coarsen surface. ba is collected from the furnace or boiler kiln at the bottom side, and another waste product, which is normally recognized as fly ash, is collected from the precipitator process. normally, the total percentage of waste product of ba is more than the fly ash, and sometimes the ba is dumped at the nearest area for storing or recycling. if the ba is not properly stored, there will be environmental effects (such as air pollution, water pollution, and groundwater contamination) and human health effects (such as respiratory diseases and cancer risk) occurred imminently. thus, ba is proposed for the 3r (reduce, reuse, and recycle) process which is utilized as structural fill material, concrete ingredient material, and road base. ba with similar size of the sand is becoming popular to replace sand in concrete and lastly promoting the lightweight concrete. there is no information from previous studies on the utilization of ba filled in built-up cfs section as column or beam. nowadays, the normal concrete is shifted from traditional material to waste material which is parallel to the sustainable development program. the traditional material in normal concrete is replaced or substituted with waste material to solve the environmental problem which occurred from the beginning of the quarry activity. mainly, the co2 emission from aggregate occurred from the excavation, blasting, and transportation activities using electricity. fayaz et al. [16] have noted that sand is scarce due to the indian government imposing harsh restrictions on the sand quarrying at the river, which causes construction activities to be affected. the sand quarrying activities at the river normally produced environmental damage and river erosion [16]. besides, sand mining activities have also created a lot of problems such as riverbeds becoming deeper, riverbank collapsed, vegetation losses on a riverbank and, aquatic life and agriculture sector interrupted [17]. they have also separated the aggregate into three categories, i.e., recycled coarse aggregate, normal coarse aggregate, and fine aggregate that are being used in concrete manufacturing which contributed to co2 emission of 39%, 42%, and 19%, respectively. from the observation and analysis, the information of the built-up cfs created with spot weld is still limited rather than other fasteners to form a symmetrical and closed section. besides, the built-up cfs stub column infilled with normal concrete is considered a common of the study, but nowadays they are combined with special concrete for increasing the strength and improving the stability of the structure. the combination of built-up cfs with special concrete is recognized as new research activity and there is no code of practice that fully describes it. the arrangement and complete experimental setup for the built-up cfs stub column subjected to axial compression are not explained well in previous studies, especially the support condition and the imperfection analysis. 95 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 previous studies have not enlightened the utilization of special concrete in the built-up cfs stub column as a structural component to reduce the overall weight and production cost of the structure, such as the optimum percentage of waste material for replacing the traditional material. roy et al. [18] have reported that the information and design guidelines of the cfs stub column in the australia-new zealand code of practice (as/nzs 4600) are classified as conservative when compared with a slender column. roy et al. [19] stated that there are limited information and study on the determination of the strength due to axial compression for built-up face-to-face cfs and the effect of the spacing of the fastener. ferhoune and zeghiche [20] reported that very few studies by experiments have been conducted on the built-up cfs stub column which is with welding fastener and filled with normal concrete or special concrete. 4. specimen preparation and experimental setup the cfs channel section with double intermediate web stiffeners and with a dimension of web element of 75 mm, flange elements of 34 mm, lipped element of 8 mm, the thickness of 1 mm, and steel grade of 550 mpa is selected as shown in fig. 3. the section properties of the cfs channel section are tabulated in table 1. cfs channel section is clean and clear before starting by checking the material properties of the section using a coupon tensile test specimen. cfs is cut on the web and flange elements which are situated vertically as similar as the column condition by referring to bs en 10002-1:2001 [21]. then, two cfs channel sections are located face to face to produce the built-up cfs section as same as the square hollow section by using spot weld on three locations as shown in fig. 4. the spot weld with the width of 5 mm and with three numbers is located at the top, middle, and bottom of the built-up section in two parts (left and right) by referring to the study of roy et al. [19]. the height of the specimens is constant at 250 mm. the ba collected from the furnace or boiler kiln is prepared for the cleaning and washing process to form the wba with appropriate sizes. for material properties of the wba concrete, the concrete with grade 20 is designed by using material density and cast in 5 times accordingly to the proportion of sand replacement, 0%, 25%, 50%, 75%, and 100%. the total specimen of the concrete for material properties is 30 cubes, and the mix of all specimens is without using a superplasticizer. the concrete is cured in the water-curing tank for 7 days and 28 days of compressive strength. the built-up cfs section, as shown in fig. 4(a), is filled with normal concrete as a control specimen and wba concrete with 25%, 50%, 75%, and 100% to form a column. the total specimen of the built-up cfs column with wba concrete is 12 specimens and 3 specimens with normal concrete. the built-up cfs with normal and wba concrete is cured for 28 days before testing. the imperfection and residual stress of the cfs section are ignored in the study. in the experimental activity, there are four parts which include material properties of cfs, material properties of wba concrete, mechanical properties of the connection, and mechanical behavior of built-up cfs stub column. the universal testing machine (utm) with a capacity of 30 kn is used for determining the material properties of the cfs test. the mechanical properties of connection are divided into two parts: shear connection and pull-out connection test. from the material properties of cfs, the ultimate strength, yield strength, elastic modulus, and deformation at ultimate load are observed. furthermore, there are four specimens for the shear connection test and three specimens for the pull-out connection test proposed for checking the mechanical properties of the connection. the utm with a capacity of 100 kn is utilized. the ultimate load of all connection test specimens is determined and the failure mode is observed. next, the material properties of the normal and wba concrete, especially the ultimate load and compressive strength, are determined by using an auto compression machine with a capacity of 3000 kn. the failure mode of the concrete under compressive strength is observed. lastly, for the mechanical behavior of the built-up cfs stub column, the ultimate load of the column is evaluated and the failure mode of the column for all proportions of wba concrete is observed. the built-up cfs column without concrete is also determined for the comparison study. the experimental setup of the mechanical behavior of the built-up cfs stub column has followed the study of mohd sani and muftah [22] as shown in fig. 5. 96 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 fig. 3 the cross-section and dimension of the cfs channel section table 1 the section properties and dimensions of the cfs channel section parameter value and unit web (d) 75 mm lipped (l) 8 mm area (a) 148 mm 2 second moment of area (ixx) 0.135 × 10 6 mm 4 section modulus (zxx) 3.605 × 10 3 mm 3 radius of gyration (rx) 30.22 mm flange (f) 34 mm thickness (t) 1 mm yield strength (fy) 550 mpa second moment of area (iyy) 0.025 × 10 6 mm 4 section modulus (zyy) 2.240 × 10 3 mm 3 radius of gyration (ry) 12.94 mm (a) top (b) front fig. 5 experimental setup for testing the mechanical behavior of the built-up cfs stub column fig. 4 the view of the built-up cfs column 5. results and discussion the results and discussion for the four parts of the experiment are analyzed here for achieving the objective of the study. the results and discussion are started with the material properties of cfs, continued with the material properties of wba concrete and mechanical properties of the connection test, ending with the mechanical behavior of the built-up cfs stub column. 5.1. material properties of cold-formed steel (cfs) the result of the material properties of cfs is tabulated in table 2. from the table, the highest value of the ultimate load is the flange element, and the lowest value of the ultimate load is recorded at the web element. the percentage difference of 5.89% for ultimate load, 5.88% for ultimate strength, 6.43% for yield stress, 2.44% for elastic modulus, and 4.06% for deformation at ultimate load are recorded between web and flange elements. the ultimate load and strength of the flange element are more than the web element because of the process of bending the flat element into a new element. the ultimate and yield strength is vividly increased from web to flange element due to strain hardening and cold-rolling process in the ambient temperature. 97 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 besides, the increment is also due to cold-forming, which produces new strength, is added with existing strength, and decreases the ductility. therefore, the ultimate load and strength of the element are dependent on the bending process. if the element is without a bending process, the ultimate load and strength would show the lowest value. the cfs which was bought from the malaysia construction market has met the quality and is suitable for further work. dinis et al. [23] reported that the elastic modulus of the web element is higher than the flange element when testing by using a coupon tensile specimen. fig. 6 illustrates the example of the coupon specimen after failing, and fig. 7 shows the stress-strain graph of the cfs. table 2 the result of the material properties of cfs element ultimate load (kn) ultimate strength (mpa) yield strength (mpa) elastic modulus (gpa) deformation at ultimate load (mm) web 6.71 536.6 524 205 4.43 flange 7.13 570.1 560 200 4.25 fig. 6 the coupon specimen after testing 5.2. material properties of washed bottom ash (wba) concrete the material properties of wba concrete, especially the ultimate load and compressive strength, are tabulated in table 3. from the observation, the color of the specimen without wba is brighter if compared with the specimen with wba which shows dark grey. fig. 8 and fig. 9 illustrate the relationship between the compressive strength and the age of curing and the relationship between the compressive strength and the proportion of wba, respectively. the highest and lowest value of compressive strength is 25% and 100% respectively of the wba concrete specimen. the ultimate load and compressive strength of the wba concrete are increased by increasing 25% wba and decreased by increasing more than 25% wba. this is because the wba concrete with a high percentage of wba has the fresh mix very dry and the hardened concrete too brittle. the compressive strength of all specimens is increased from 7 days to 28 days as calculated approximately 24.26% of 0%, 26.15% of 25%, 25% of 50%, 21.05% of 75%, and 24% of 100%. the percentage achieved from the calculation is noted as significant and acceptable. the result of ultimate load and compressive strength with 25% wba which is more than the control mix is similar to the study by kim et al. [24]. kim et al. [24] reported that the specimens with 25%, 50%, and 75% fine ba aggregate have shown more value of compressive strength compared with the control mix. the percentage difference of the 0.00e+00 1.00e+02 2.00e+02 3.00e+02 4.00e+02 5.00e+02 6.00e+02 0 0.02 0.04 0.06 0.08 0.1 0.12 s tr es s (m p a) strain (mm/mm) web flange fig. 7 the stress-strain graph of the material properties of cfs 98 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 compressive strength between all specimens with control is 7.34% of 25%, 18.81% of 50%, 71.78% of 75%, and 87.62% of 100% wba concrete specimen. the failure mode of the 0% (control mix), 25%, 50%, and 75% are shown in fig. 10. 100% wba concrete specimen is classified as brittle concrete as shown in fig. 11 with the overall side, and the corner of the cube is broken. table 3 the ultimate load and compressive strength of the wba concrete specimen specimen 7 days 28 days ultimate load (kn) compressive strength (mpa) ultimate load (kn) compressive strength (mpa) 0% (control) 153.5 15.3 202.2 20.2 25% 160.7 16.1 218.7 21.8 50% 123.0 12.3 164.0 16.4 75% 44.9 4.5 57.56 5.7 100% 19.5 1.9 24.66 2.5 fig. 10 the failure mode of specimen fig. 11 the failure mode of 100% wba specimen after compressive strength test 0 2 4 6 8 10 12 14 16 18 20 22 7 days 28 days c o m p re ss iv e s tr en g th (m p a) age of curing 0% (control) 25% 50% 75% 100% 0 5 10 15 20 25 0% (control) 25% 50% 75% 100% c o m p re ss iv e s tr en g th (m p a) specimen 7 days 28 days 0% (control mix) 25% 50% 75% fig. 8 the relationship of the compressive strength and the age of curing fig. 9 the relationship of the compressive strength and different specimens 99 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 5.3. mechanical properties of the connection test the shear connection test is conducted and the result is shown in table 4. the percentage difference between the full weld and spot weld is determined and noted to have 77.49% for 1sw, 73.60% for 2sw, and 27.67% for 3sw. 68.87% and 63.50% are reported when the 3sw specimen is compared with 1sw and 2sw, respectively. 3sw is classified as an appropriate connection method for the built-up cfs section that gives the optimum value and shows the highest value of ultimate load with less energy consumption and less cost compared with the full weld method. the failure mode of all specimens is observed to have the break at the location of the weld. fig. 12 illustrates the ultimate load between the methods of connection for shear testing. the graph illustrates that the ultimate load is increased by increasing the number of the spot weld. the result of the pull-out connection test is tabulated in table 5. three specimens are tested and two-surface full weld (2sfw) specimens obtain the highest ultimate load value of 37.03 kn. the percentage differences between the three-number spot weld (3sw) specimen with 1sfw and 2sfw are 27.10% and 55.04%, respectively. the deformation at ultimate load between 3sw and 1sfw is illustrated similarly and the value is not too far between them, around 9.37%. the deformation at ultimate load for 2sfw is 10.64 mm and demonstrates that the connection with full weld at two surfaces is the most practical method to the joint between two sections. with the less deformation at ultimate load among the specimen, 2sfw is considered an appropriate connection method but the specimen is categorized as more costly and has high energy consumption when using full weld and compared with other connection methods. 3sw specimen is classified as a suitable connection method that provides a significant ultimate load for joining between two specimens without high cost and energy consumption. all specimens fail due to breaking at the weld. table 4 the shear connection test result specimen symbol ultimate load (kn) failure mode full weld fw 13.37 break at the weld one-number of spot weld 1sw 3.01 break at the weld two-number of spot weld 2sw 3.53 break at the weld three-number of spot weld 3sw 9.67 break at the weld table 5 the pull-out connection test result specimen symbol ultimate load (kn) deformation at ultimate load (mm) three-number spot weld 3sw 16.65 25.14 one-surface full weld 1sfw 22.84 27.74 two-surface full weld 2sfw 37.03 10.64 5.4. mechanical behavior of built-up cold-formed steel (cfs) stub column the mechanical behavior of the built-up cfs stub column is tabulated in table 6 and fig. 13. the highest value of the ultimate load and compressive strength is 25% wba specimen, and the lowest value of the ultimate load and compressive 0 2 4 6 8 10 12 14 1sw 2sw 3sw fw u lt im at e l o ad ( k n ) specimen fig. 12 the graph of the ultimate load according to the specimen or method of connection 100 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 strength is 100% wba specimen. the ultimate load of the built-up cfs stub column without concrete is reported to have 73.5 kn. when the built-up cfs column is filled with normal concrete, the ultimate load is increased by around 55.86%. although when the built-up cfs column is filled with wba concrete with a different proportion, the ultimate load is improved approximately 66.53% of 25%, 54.148% of 50%, 48.24% of 75%, and 46.55% of 100% wba specimen. the percentage difference of the ultimate load between the control specimens with wba concrete is noted as having 24.18% for 25% wba specimen, 3.72% for 50% wba specimen, 14.72% for 75% wba specimen, and 17.42% for 100% wba specimen. the failure mode of the specimen is also tabulated in the table and illustrated in fig. 14. all specimens are observed to have local buckling and distortional buckling. nie et al. [5] mentioned about the local buckling existing for the short column at web and flange elements when subjected to axial compression. the web and flange elements are deformed and moved out from the original as shown in the red circle in fig. 15. the specimens do not fail at the connection area between one cfs channel with another cfs channel. the cfs section shows significant failure in buckling rather than concrete either normal or wba concrete which does not illustrate the crack or failure as illustrated in fig. 16. from the experimental activity, the built-up cfs with wba concrete of 25% is shown as the specimen with optimum value, and the built-up cfs with wba concrete of 50% is represented quite similar with control specimen. besides, the 75% wba and 100% wba specimens are observed to fail on the surface of the column due to the brittleness of the wba when fully replaced with sand. the pattern of the failure mode of all specimens is observed having the same condition and proven by previous studies, nie et al. [5] and nie et al. [25]. table 6 the result of the mechanical behavior of the built-up cfs stub column specimen ultimate load (kn) compressive strength (mpa) failure mode 0% (control) 166.5 31.71 local and distortional buckling 25% 219.6 41.83 local and distortional buckling 50% 160.3 30.53 local and distortional buckling 75% 142.0 27.05 local and distortional buckling 100% 137.5 26.19 local and distortional buckling fig. 13 the ultimate load of the built-up cfs column with different proportions of wba concrete fig. 14 the failure mode of the built-up cfs specimen from the front view 0 50 100 150 200 250 0% (control) 25% 50% 75% 100% u lt im at e l o ad ( k n ) specimen without concrete 0% wba 25% wba 50% wba 75% wba 100% wba 101 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 fig. 15 the failure mode of the built-up cfs specimen at the connection area fig. 16 the failure mode of the built-up cfs specimen from the top view 6. conclusions and recommendations from the result and observation of the complete experimental activity, several conclusions and recommendations are drawn as shown here. (1) the compressive strength of the wba concrete with 25% of wba is increased approximately 7.34% when compared with the control specimen. the result of compressive strength is increased between 21% and 26% when the concrete is fully submerged in water in early strength age with mature strength. the wba concrete with more than 25% of wba is shown to decrease and recorded to have 19% to 88% compared with the control mix. from the observation of the failure mode, the wba concrete is noted to have brittle conditions when achieving more than 50% or until 100% of wba. (2) the built-up cfs stub column with 25% wba concrete is shown to have the highest value of ultimate load and compressive strength with 219.6 kn and 41.83 mpa respectively and recorded to have 24.19% compared with the control specimen. the ultimate load and compressive strength of the built-up cfs column are increased when the wba concrete is less than 25% and decreased when the wba concrete is more than 25%. (3) all specimens failed the local and distortional buckling on the steel surface, but there are no cracks or failure on the concrete surface detected. thus, the utilization of 25% wba as sand replacement can reduce the production cost and environmental problems produced from the site of the sand quarry. for further study, the casting and mixing process of the fresh concrete must be added with the superplasticizer for controlling the strength and workability of the specimen. the built-up cfs intermediate and slender column should be designed and established to determine the relationship between the slenderness ratio and strength of the column. lastly, the built-up cfs column with a variety of the fastener should be designed, produced, and discussed, and the imperfection aspect should be added in numerical analysis to evaluate the mechanical behavior. acknowledgements the authors kindly thank the malaysia ministry of higher education under the fundamental research grant scheme (frgs/1/2018/tk01/uitm/02/2) for the financial support and universiti teknologi mara (uitm) cawangan pahang for the facility support, especially laboratory machines and equipment. sincerest gratitude is extended to the college of engineering, uitm cawangan pahang members and staff for providing technical assistance and advice. without concrete 0% wba 25% wba 50% wba 75% wba 100% wba without concrete 0% wba 25% wba 50% wba 75% wba 100% wba 102 advances in technology innovation, vol. 7, no. 2, 2022, pp. 92-104 conflicts of interest the authors declare no conflict of interest. references [1] h. d. craveiro, j. p. c. rodrigues, and l. laím, “buckling resistance of axially loaded cold-formed steel columns,” thin-walled structures, vol. 106, pp. 358-375, september 2016. 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[25] s. nie, t. zhou, m. r. eatherton, j. li, and y. zhang, “compressive behaviour of built-up double-box columns consisting of four cold-formed steel channels,” engineering structures, vol. 222, article no. 111133, november 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 104  advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 maintenance initiation prediction incorporating vibrations and system availability lasithan lasyam gopikuttan 1,*, shouri puthan veettil 2 , rajesh vazhayil govindan 2 1apj abdul kalam technological university, kerala, india 2department of mechanical engineering, model engineering college, kerala, india received 04 october 2021; received in revised form 25 december 2021; accepted 26 december 2021 doi: https://doi.org/10.46604/aiti.2022.8618 abstract as per iso-10816, electric motors up to 15 kw are classified as class i machines, and the major reason for their failure is that the vibrations in them are above the alert limit. this study presents a new model for predicting the condition-based maintenance (cbm) initiation points through vibration measurement in a system of class i machines. the proposed model follows the accelerated life testing (alt) procedure. alt includes the formation of an artificial wear environment in bearings to analyze the resultant system vibrations on system availability. the artificial wear environment created is close to the real industrial situation. the results show that the prediction of the cbm initiation points is based on the established relation between the system availability and vibrations. furthermore, a relation between the available time for maintenance initiation and different vibration velocities is demonstrated. keywords: availability, condition-based maintenance, alert limit, alarm limit, acceleration factor 1. introduction reliability and availability management plays a prime role in the success of a company. for the economic performance of an industrial plant, maintaining high availability, reliability, and maintainability for the plant machines and their subsystems is crucial [1-3]. the machines in an industrial process plant can fail because of a wide range of reasons. the major reason behind machine failure is the unchecked magnitude of vibrations above the alert limit. the availability of a system or machine is affected badly when the machine failure occurs. the direct impact of the vibration levels on the system availability and the usability of that influence in condition-based maintenance (cbm) programs are not reported in the literature so far [4-5]. over the years, maintenance has advanced to adopt the aspect of reliability. reliability is a design attribute that shows the expected acceptable performance of an item. reliability-centered maintenance (rcm) is used to decide the maintenance requirements of any physical asset to ensure its satisfactory operation. cbm is a subclass of rcm [3]. typically, the objective of a cbm program is to devise a maintenance policy that optimizes the system performance according to the criteria such as cost, availability, and reliability [3]. early failure detection is the responsibility of most cbm programs [4]. for the cbm application, a potential failure-functional failure (p-f) curve can be plotted between the failure resistance or health condition of a machinery system and the time period of its failure [3]. it can be inferred from this curve that as time increases, failure resistance decreases to complete the system failure. this curve can be used to explain various stages of system failure, i.e., failure initiation (i), potential failure (p), and functional failure (f). along this curve, a point “p” can be identified, where there is a potential to fail, * corresponding author. e-mail address: lasithanlg@gmail.com tel.: +91-9744000988 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 and a point “f” beyond “p” can be detected, where the system will not perform as expected. after the point “p,” the health condition decreases rapidly. there is no hard data to define p-f intervals [3]. therefore, the best strategy is to employ methods that could effectively ascertain the machine condition before the potential failure occurs, and this should permit scheduling the repair activity before the p-f interval. shin et al. [5] examined the cbm strategy from various perspectives and addressed the data, procedure, and techniques for implementing the cbm approach. li et al. [4] proposed a cbm model for assuring average system availability and plant safety. electrical motors are integral parts of the majority of the machines installed in an industrial plant [3, 6]. the failure of any one of these motors degrades the machine performance, which, in turn, influences the overall plant availability. manjare et al. [6] reviewed machine learning (ml)-based fault detection techniques and predictive maintenance (pdm)/cbm strategies for electrical motors used in industrial plants. furthermore, the vibration data acquired from accelerometer sensors are extensively used for data analysis. kumar et al. [7] presented a comprehensive review of various faults in electric motors, failure causes, and advanced condition monitoring and diagnostic techniques. however, the availability aspects associated with the failure of electric motors and maintenance initiation points are not considered in these studies. in this experimental study, the deterioration in a system of electric motors with five hp-rated power class i machines is simulated by deliberately creating the vibrations above the alert limit. an analysis is performed for the values of the alert and alarm limits of vibration velocity (root mean square (rms)). the alert limit corresponds to the failure initiation, and the alarm limit corresponds to the potential failure for the system [3]. the maintenance initiation points for cbm are defined only in accordance with the shrinkage pattern of system availability with the vibration velocity for a particular system load. the maintenance initiation points of cbm for different system loads are predicted according to this relation. the proposed approach can be applied to accurately predict the value of vibration velocity (rms) for the maintenance initiation points of class i machines. the frequent failure of certain class i machines in an industrial process plant is mainly due to bearing wear, which gives rise to vibrations in the machines. as the wear increases, the system vibration level increases. in this study, the system failure is simulated by artificially wearing the bearings. the resultant vibration velocity is measured as a time series. the time recorded during the experiment is changed by suitable transformation to the corresponding useful life under normal operating conditions of the machines. this study establishes a relation between the vibration velocity and the projected useful life period of the bearings in the system for different possible system loads. from the value of a maintenance initiation point of vibration velocity for a possible system load, the corresponding life of the bearings in the system can be calculated. by considering possible system loads, this study establishes a general expression between the available maintenance initiation time for cbm and the vibration velocity for the system under consideration. in the expression, the vibration velocity considered is less than the defined value of maintenance initiation vibration velocity. the remainder of this study is organized as follows. section 2 provides a detailed review of the extant literature. section 3 explains the experimental setup of a class i machine and the loading arrangement for the same. the experimental procedure of the accelerated life testing (alt) and vibration measurement is also explained in this section. section 4 details the experimental data and failure analysis; also, the system availability is modeled in terms of vibration velocity (between alert and alarm limits), and the resulting curves are plotted. the equations for the available maintenance initiation time and the value of maintenance initiation points of the system are established in this section. finally, section 5 concludes this study by summarizing the findings. 2. literature review and background study the term “reliability” can be defined as the probability that under the stated operating conditions, a system or equipment will perform its intended function satisfactorily for a specified interval [2]. the general expression for reliability with time period t and failure rate λ [2] is given by: 182 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 ( ) t r t e    (1) where λ = 1/mtbf. mtbf refers to the mean time between failures. from eq. (1), it can be inferred that as system failure resistance decreases, its reliability decreases. the term “availability” is used to indicate the probability of a system or equipment being in operating condition at any time t, given that it is in operating condition at t = 0 [2]. to make a system in operating condition at time period t, it must be functional. in other words, it must not fail, and if there is a failure at t, it must be repaired. thus, availability involves the characteristics of both reliability and maintainability. the latter is defined as the probability of repairing a failed system or component in a specified period [2]. availability features allow the system to stay operational even when faults occur, whereas reliability means it is likely to perform perfectly, and maintainability implies that even if something does go wrong, it can be rectified effortlessly [2-3]. the general expression for the system availability a is given as eq. (2) [2]: 1 1 mtbf a mtbf mttr mttr      (2) where mttr refers to the mean time to repair. vibration monitoring might be considered the grandfather of cbm/pdm and provides the foundation for the cbm programs of most facilities [3, 8-9]. bianchini et al. [10] conducted an experimental study for cbm through vibration monitoring on submersible well pumps following vibration severity standards such as iso 10816-7 (2009). however, in their study, the availability of pumps corresponding to the vibration level was not set. sulaiman et al. [11] investigated the effect of high vibration (above acceptable limit) in gas turbines installed in al ghubra power & desalination company and suggested using online condition monitoring methods to determine the running condition of gas turbines in advance to plan maintenance activities to avoid sudden failure of the turbine. in industrial situations, the process plants often operate with certain machines, which can be classified as class i, ii, iii, and iv on the basis of vibration severity standards iso 10816 and whose failure is mainly due to severe vibrations. the standard provides a reference for evaluating vibration severity in machines operating over the range of 600 to 12,000 rpm [8-9]. these machines are often subjected to more than the acceptable limits of vibration, which invariably leads to an increase in their failure rate, especially in the case of components with rotating parts. rotating machinery is extensively used in today’s industries, and some of these are extremely critical for the successful operation of the plant. the machine collapse may result in costly downtime of the plant. the faults in rotating machinery, such as machine being out of balance or alignment, gear fault, resonance, bent shafts, bearing failures, mechanical looseness, can be identified by measuring and analyzing the vibration generated by the machine [8-9]. the rolling element bearings in rotating machinery allow a relative movement and bear shaft load [12]. the life of a bearing depends on its use, and its expected life is solely based on experience [13]. the main cause of failure of industrial bearing is rolling contact fatigue (rcf). the rcf wear mechanism involves false brinelling, characterized by plastically formed indentations, which are generally caused by vibration due to overload. the cause of the wear is that lubricant is squeezed out between the contact area of rolling elements and raceways, resulting in direct metal-to-metal contact. vibration causes wear of the surfaces in contact, and fine abrasive particles are rapidly produced, which results in a characteristic groove with the oxide acting as an abrasive [14]. failure analysis of the bearing can be investigated by making artificial defects on various elements of the bearing and analyzing it with a vibration signature tool for monitoring its condition [15]. usually, life testing under normal operating conditions of mechanical parts with high reliability is expensive in terms of both capital and time. hence, it is desirable to accelerate the testing procedure for gathering the failure data. the chief objective of accelerated testing procedures is to reduce the time required for life testing by strategies such as intensified stress levels. 183 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 physical acceleration or true acceleration means that operating a unit at high stress produces the same failures that would occur at typical use stresses, except that they happen much quicker. then, by extrapolating the results suitably to the “normal use” conditions, a reasonably accurate estimate of the life of the component under the “normal use” conditions can be obtained [2, 16]. however, the issue of prediction accuracy associated with extrapolating data outside the range of testing has not yet been addressed comprehensively [16]. acceleration factors show how the time-to-fail at a particular operating stress level (for one failure mode or mechanism) can be used to predict the equivalent time-to-fail at a different operating stress level [17-18]. thus, an efficient diagnosis system is needed to predict the condition and consistent lead time of the machine. vibration analysis is a method used for monitoring the condition of the machine. effective vibration signal extracting techniques, therefore, have a critical part in diagnosing a rotating machine. in detecting early fault generation, frequency domain features in the vibration signals are generally more effective as compared to the time domain features [19]. tools such as neural networks, hybrid systems, and fuzzy logic are being employed for increasing the effectiveness of fault diagnosis [20]. it is normally accepted that the vibration velocity recorded over the range of 10 hz (600 rpm) to 1000 hz (60,000 rpm) provides the finest indication of a vibration’s severity on rotating machines [8-9, 11]. as most of the rotating machines operate between 600 rpm and 60,000 rpm, the vibration velocity is the best candidate for vibration measurement and analysis [8, 11], whereas above 60,000 rpm vibration acceleration is only the fine indicator [8, 11]. the rms value is directly related to the energy content of the vibration and thus its destructive capability [8-9]. the indicators used for the initiation of cbm involve vibration signatures, temperature changes, and process parameters of machining such as spindle speed, depth of cut, and feed rate. by the analysis of these indicators, the failure of the machine can be predicted, and the corrective measures must be performed [21]. the process parameter used in the proposed model is vibration velocity (rms), and its influence on system availability was analyzed. the remaining useful life (rul) is the life period left on any system of machines at a particular time of operation [3]. from a specific time of operation of the system, the rul is the time period up to its functional failure. by taking rul into account, a plant engineer can schedule system maintenance, which can avoid unexpected system downtime. because of this, the prediction of rul has the highest priority in cbm programs. the method used to calculate rul depends on the kind of data available [3]. coppe et al. [22] proposed the use of a simple crack growth model is proposed t o predict the system rul influenced by the fatigue failure mechanism. kang et al. [23] implemented an ml-based approach for automating the prediction of rul of equipment in continuous production lines. han et al. [24] developed a method for rul prediction for manufacturing systems using a mission reliability-oriented approach based on the functional dependence of components. in this study, the alert limit of vibration, alarm limit of vibration, and the system availability are considered for defining the maintenance initiation points of cbm for class i machines of specific power rating. a relation is established between the system availability and the process parameter vibration velocity (rms). it is observed that the system availability starts to decline at a point much before the alarm limit of vibration (potential failure), and the maintenance is initiated at this point for the proposed model. from this point onward, the reliability begins to drop rapidly. the time available for maintenance initiation can be predicted from a given level of vibration, which is less than the defined value of maintenance initiation vibration level. the functional failure occurs beyond the potential failure and is not considered in this study [3]. it is evident that even though the relation between vibration velocity and system availability can be deduced, no study has predicted the time available to initiate the cbm from a given level of vibration of the machine [4, 25]. in this study, an attempt is made to ascertain the time available for initiating the cbm by having a measure of the vibration level. 184 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 3. experimental setup and design of alt according to the vibration severity standards table for iso 10816 [8-9], class i industrial machines are individual parts of engines and machines, integrally connected with the complete machine in its normal operating condition (electrical motors of up to 20 hp are typical examples of machines in this category). according to iso 10816, the speed of rotation of class i machines lies in the range of 600 to 12,000 rpm. on the one hand, the upper limit of vibration for a good operating condition, defined as the good operating limit, is 0.71 mm/sec, and for a satisfactory condition, defined as an acceptable or alert limit (failure initiation), is 1.8 mm/sec (table 1). on the other hand, the corresponding value for the unsatisfactory condition of vibration level, defined as the alarm limit (potential failure), is 4.5 mm/sec. above the alarm limit, potential failure leads to a functional failure, and some functions of the asset stop working [3]. therefore, the failure probability of machine components subjected to vibration can be defined such that the failure probability is zero for vibration levels below the alert limit and 100% as it reaches the alarm limit. three-phase squirrel-cage induction motors are widely used as industrial drives because they are self-starting, reliable, and economical [8]. around 70% of the failures that occur in electric motors are mechanical in nature [26]. the bearing failure is the leading cause (~51%) of most mechanical failures [27]. the causes of bearing failure include excessive loads, overheating, true and false brinelling, spalling, contamination, lubricant failure, loose and tight fits, corrosion, and misalignment [9]. the contamination is caused by foreign substances getting into bearing lubricants or cleaning solutions. examples of such foreign substances include dirt, abrasive grit, dust, and steel chips from contaminated work areas. solid particle contamination is a serious problem in all industrial sectors, which causes wear in contact surfaces [28]. the wear happens in the inner and outer races of the bearing, and when the ball passes over these races, the phenomenon called “ringing” occurs, which is similar to the vibrations in a car moving on an irregular road. as wear increases, vibration increases. the vibration standards iso 10816 can be used as a reference for evaluating the severity of vibrations. the proposed model creates the wear in the raceways of the bearing of a class i machine intentionally, and the resultant vibrations above the alert limit can be measured and recorded using vibration measurement systems. figs. 1(a)-(b) indicate the line diagram and the photograph of the practical setup used for experimentation. it consists of a delta-connected three-phase induction motor, a long shaft with necessary detachable couplings at the ends, bearings and brackets, and a mechanical loading mechanism with cooling accessories. the rated voltage, current, power, rpm, and frequency of the motor used are 415 v, 7.1 a, 5 hp, 1440 rpm, and 50 hz, respectively. similarly, the shaft material used is en32 grade steel with a diameter of 18 mm and a total length of 75 mm. the shaft is connected to the motor using a flexible element jaw coupling, and a spider rubber bush is placed on the inside of this coupling. the shaft is simply supported at the two bearings, which are placed inside two bearing brackets. the distance between the bearing ends is 65 cm. a brake drum is mounted on the shaft at a distance of 56 cm from the bearing bracket 1. the bearings used are deep groove ball bearing skf 6202 z. the inside diameter of the bearing is 15 mm, and accordingly, the diameter of the shaft when it passes through the bearing portion is reduced to suit this value. as per the data sheet of skf 6202 z bearing, the fatigue load limit (maximum radial load) is 0.16 kn. for analysis purposes, the bearings fitted inside the bearing brackets 1 and 2 are referred to as bearing 1 and bearing 2, respectively. during experiments, the failure of bearing 2 is created by developing the wear in it by adding c10 coarse (10-micron grain size) silicon carbide paste between its inner and outer races. table 1 iso 10816 vibration severity levels for class i machines operating condition of class i machines vibration velocity in mm/sec (rms value) good 0.28 to 0.71 satisfactory (acceptable) 1.12 to 1.80 unsatisfactory (monitored closely) 2.80 to 4.50 unacceptable 7.10 to 45.90 185 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 (a) line diagram of the experimental setup (b) practical setup fig. 1 experimental setup for vibration measurement in class i machines the shaft design is based on the combined torque and bending moment (static analysis). on the basis of the design, the appropriate shaft diameter is calculated as 18 mm. a modal analysis of the combined system involving the shaft and the brake drum is performed using ansys software. the analysis revealed “n” modes of vibration and corresponding natural frequencies. the natural frequencies of the system obtained for the first and second modes are 166 hz (9,960 rpm) and 332 hz (19,920 rpm), respectively. the natural frequencies are observed to have an increasing trend for further modes of vibration. in this study, a variable frequency drive (vfd) is used between the motor and input three-phase supply to fix the motor speed at 1,465 rpm. also, the ratio of the motor’s applied voltage and applied frequency is set as 8.3 v/hz. as the natural frequency values obtained for all the modes of vibration for the designed system are noted to be much higher than 1,465 rpm, the resonance condition is avoided to make the design safe. the loading arrangement used is illustrated in fig. 2 and consists of a brake drum, brake shoe, and loading wheel. the material of the brake shoe is compressed asbestos, and that of the brake drum is en8 grade steel. the brake drum is connected to the shaft at a distance of 56 cm from the bearing bracket 1. the brake drum has a diameter of 150 mm and a thickness of 40 mm. the loading of the motor is achieved by turning the loading wheel, which makes the brake shoe inside the brake shoe bracket to press against or pull away from the rotating hollow brake drum. the system load applied is noted from the load indicator dial. the hinge, brake shoe bracket, and bearing bracket are made of mild steel. the electric motor, bearing brackets, brake shoe bracket, load indicator, hinge, and cooling water arrangement of the brake drum are mounted on a frame made using a light gauge rectangular hollow cross section galvanized iron tube (is1239). rubber bush dampers are used for vibration isolation from the floor. during loading, because of the friction between brake drum and brake shoe, heat is generated inside the hollow brake drum. it is removed by constantly circulating cooling water through the hollow brake drum. the water flow is controlled by a ball valve. the temperature of water at the inlet and exit are measured using k-type thermocouples, and the steady readings obtained are 27°c and 63°c, respectively. fig. 2 line diagram for loading arrangements 186 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 the alt conducted in this experiment follows the procedure detailed in regattieri's work [29]. the experimental setup is designed such that the failure of bearing 2 is the reason for the failure of the system. experimental trials are conducted by continuous measurement of the rms vibration values of the system from the moment the silicon carbide paste is added to the final failure state of the system. during each trial, under a constant radial load, the failure of the system is created by developing the wear in bearing 2. the failure so created is assessed in terms of the induced vibrations of the order of the magnitude above alarm limit vibrations (glut vibrations) in the system by comparing with the vibration severity standards (iso 10816). the trials are repeated by changing the radial load on bearing 2 from 14 kg to 18 kg in steps of 1 kg. eight sets of experiments are conducted under each trial to ensure repeatability. these radial loads are selected such that the fatigue limit of the bearing is never exceeded. the loads on bearing 2 are calculated considering equilibrium conditions of the shaft and assuming a simply supported configuration at bearings 1 and 2. during the experiments, after the motor starts, the system steadies itself in a few seconds and begins to operate in a stable condition. the vibration level is measured to ensure that there is no vibration interference, such as the vibration of the mounting of the load indicator in the system. thereafter, 10 g silicon carbide paste is added in bearing 2 between its inner and outer races from the outside to develop the wear in it. the paste is added thrice at the intervals of 5 minutes for every set of the experiment. this results in the failure of the system as observed from the recorded rms vibration values (table 1) when the alarm limit is reached. the system used in the measurement, preprocessing, storage, and postprocessing of the vibration signals consists of an accelerometer sensor, compactdaq, a personal computer (pc), and the labview software (version 2017). compactdaq, a data acquisition platform built by national instruments, includes a broad set of compatible hardware and software; it is a usb-powered plug-and-play type and requires no data card. compactdaq integrates hardware for data i/o with labview software to enable engineers to collect, process, and analyze the sensor vibration data. the accelerometer sensor used is a uniaxial integrated electronic piezoelectric (iepe; made by pcb piezotronics). the setup, used to sense the vibrations in a radial direction perpendicular to the axis of the rotating shaft, is mounted magnetically above the bearing bracket 2, where the maximum level of the vibration is obtained. the sensor has the sensitivity of 100 mv/g, measurement range ±50g, resonant frequency 25 khz, and frequency range 0.5 hz to 10 khz. compactdaq is used to acquire and process the analog signal coming from the uniaxial accelerometer sensor. the signal conditioner, which is inbuilt in the data acquisition (daq) module, removes noise from the signal and supplies a constant current excitation of 2.1 ma to the accelerometer sensor. compactdaq connects to the accelerometer sensor via a wired i/o daq module. a shielded twisted pair (stp) cable is used to carry the analog signal from the accelerometer sensor to the daq module connected to the daq chassis, which, in turn, connects a pc where labview software is installed (fig. 3). the function of the daq chassis includes the synchronization and transfer of digital signals from the daq module into the computer. the synchronization involves determining or enforcing and ordering events on signals. the digital signals from the daq chassis can be stored as binary values in the computer. a military standard connector is used to connect the accelerometer sensor to the stp cable. the signals from the daq chassis are transmitted through a shielded usb cable to the computer. in this experiment, the labview software band-pass filter passes the frequencies of vibration data in the range of 200 hz to 25 khz. this software is used to convert the measured value of instantaneous vibration accelerations into instantaneous vibration velocities by integration, and from these instantaneous values, rms values of vibration velocities are calculated. the rms value of 51.2k samples of vibration velocity is calculated at each second. fig. 3 block diagram for vibration measurement setup in the proposed system 187 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 the daq module used in this experiment is ni 9234 with ni 9171. ni 9171 is the usb interface for powering ni 9234. the daq module ni 9234 has the maximum sampling rate of 51.2 kilo samples/sec(fs) with an inbuilt hardware-based anti-aliasing filter (low pass) with a cut-off frequency of 0.45 × fs (= 23.04 kilo samples/sec). the specifications of the daq module are enumerated as follows: (1) four analog input channels (2) ±5v input range (from accelerometer sensor to daq module) (3) simultaneous sampling (4) ac/dc coupling (5) operating temperature: -40°c to 70°c (6) maximum allowed vibration and shock are 5 g and 50 g, respectively. (7) analog-to-digital converter (adc) amplitude resolution: 24-bit 4. failure analysis, discussion, and results the following assumption is made during failure analysis: (1) failure and repair rates for each subsystem are constant and statistically independent [1]. (2) failure of machines with moving parts is caused by vibrations alone and occurs when the vibration velocity is above the acceptable or alert limit of vibration. while loading, a lot of heat is created inside the hollow brake drum because of the friction between brake drum and brake shoe. this heat is removed using a cooling water arrangement. the cooling water from the tank enters inside the hollow brake drum through a pvc pipe, and its flow is controlled by a ball valve. the centripetal force produced by the rotation of the brake drum pushes the hot water inside the drum to exit through a copper tube. the temperature of hot water coming from the copper tube is measured as 63°c. (3) the parameter for measuring mechanical vibration is taken as a velocity of vibration. the velocity is the best representation of true energy generated by a machine when the relative or bearing cap data are used [9]. (4) availability under consideration is inherent availability or steady-state availability. the steady-state availability represents the long-term availability after the system settles. at the early stages of operation or before the system settles, it may be wobbly because of the issues in (i) employee training, (ii) determining a genuine/good spare part keeping policy, (iii) determining the number of maintenance personnel, and (iv) optimizing the effectiveness/efficiency of maintenance. (5) the life of the bearing is assumed to be 12,000 hours and is taken as the reference life in the analysis [13]. this reference life corresponds to the maximum radial load acting on the bearings used in the experiment. (6) the transformations used are linear, i.e., the time-to-fail at high stress is multiplied by a constant (the acceleration factor) to obtain the equivalent time-to-fail at use stress [17-18]. (7) the bearing failure (potential) probability is 0% below the alert limit of vibration, and it is 100% at and above the alarm limit. according to vibration severity standards iso 10816 shown in table 1, the satisfactory/acceptable vibration level in class i machines is in the range 1.12 to 1.80 mm/sec (rms). the unsatisfactory level (monitor closely) of vibration is in the range 2.80 to 4.5 mm/sec (rms). the vibration level 1.80 mm/sec (rms) can be defined as alert limit or failure initiation stage as per 188 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 p-f curve for class i machines [3]. the vibration level 4.5 mm/sec (rms) can be defined as alarm limit or potential failure stage as per p-f curve. therefore, the system failure probability is zero below the alert limit, and 100% potential failure happens at and above the alarm limit. in this study, bearing 2 is subjected to alt by causing the wear in it by adding some silicon carbide paste. the bearing fails because of the excessive wear so created. as the wear in the bearing increases, the vibration in the system also increases. during the experiment, the rms value of the vibration velocity for a particular system load is recorded after the silicon carbide paste is added. the measurement of rms vibration velocity continues until the alarm limit of vibration is reached. the availability and reliability of the system are calculated by extrapolating the time corresponding to this recorded rms value of the vibration velocity to normal-use conditions. the rated life of a ball bearing in working hours can be expressed as [13-14]: 3 6 10 10 60 h c l p n          (3) where l10h = rated bearing life in hr; c = dynamic load capacity (n; constant for identical bearings); p = load applied on the system (n); n = speed of rotation of the motor (rpm). in the industrial application of bearings, the speed of rotation is relatively constant, and the desired life is expressed in terms of hours of service. in this study, the bearing speed is kept constant at 1,465 rpm. the expected life for bearings in industrial applications is in the range of 12,000 to 20,000 hr [13]. if two groups of identical ball bearings are tested under loads p1 and p2 for respective lives l1 and l2, then 3 1 2 2 1 l p l p        (4) the data sheet for the skf 6202 z bearing (bearing 2) mentions that the maximum radial load that can be applied on it is 160 n. in the experimental setup, the shaft is simply supported at the two bearing ends. when the radial load applied on the system is 18 kg (176.58 n), by using equilibrium equations for the shaft configuration, the load acting on bearing 2 is found to be 15.51 kg (152 n). when l1 = 12,000 hr and p1 = 160 n, the life corresponding to the load of p2 = 15.51 kg (152 n) on bearing 2 is calculated as l2 = 13996.21 hr. similarly, the life of the ball bearing for different system radial loads (m kg) can be calculated and is encapsulated in table 2. table 2 life of bearing calculated for different system loads radial load applied on the system (m kg) radial load on bearing 2, whose failure due to excess vibration is considered (kg) life of bearing 2 based on the reference life of 12,000 hr (hr) 14 12.06 29,771.38 15 12.92 24,212.20 16 13.78 19,959.70 17 14.65 16,609.25 18 15.51 13,996.21 4.1. experimental data and failure analysis eight trials of the experiment are performed for a particular system load to ensure repeatability. each trial involved the time series vibration level measurement up to the alarm limit. thus, a total of 40 trials are conducted for the system loads varying from 14 to 18 kg. by performing the error analysis for the data collected, inappropriate trial measurement is removed. 189 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 furthermore, a total of 40 bearings fail during the experiment. the silicon carbide paste is added between the inner and outer races of the bearing to create the wear. the common bearing defect is the indentations in the raceways, and when the ball passes over the raceways, mechanical vibration is induced. table 3 summarizes the measured failure data of vibration velocity (between alert to alarm limits), the time between failures, and the projected useful life period for bearing 2 under the 14 kg system load obtained for each of the six different trials. the estimated projected time for the bearing for its useful life period is calculated following assumption 6 for the analysis. for an applied system load of m kg, the useful life period of the bearing in the system l hr (during its normal operating conditions) can be calculated from the observed failure time of t s (during experimentation) as given by eq. (5) [17-18]: 3600 m af t l   (5) where afm (the acceleration factor for system load m kg) is the proportionality constant. for a system load of 14 kg, the value of the acceleration factor used in the analysis is af14 = 34,786.423. the experiment is repeated for the system loads of 15 kg, 16 kg, 17 kg, and 18 kg in a similar way, and the values are calculated. using curve-fitting techniques, the relation between the vibration velocity and the projected time for the system loads from 14 kg to 18 kg is found to be parabolic in nature with goodness of fit, r2 ≥ 0.95. the relationship can be written as: 2 p p v at b t c    (6) where v represents the vibration velocity recorded in mm/hr between alert to alarm limits for the system load (m kg); tp represents the projected time calculated in hrs using the acceleration factor (af m) corresponding to the vibration velocity (v). the system load (m kg), coefficients (a, b, and c) in eq. (6), goodness of fit (r2 value) for eq. (6), and acceleration factor (afm) obtained from this study are summarized in table 4. using curve-fitting techniques, the relation between the vibration velocity v (mm/hr) and the average value of projected time for system loads from 14 kg to 18 kg, tpa (hr), is found to be parabolic in nature with the r2 value 0.9986. the relationship can be expressed as: 2 0.00003 0.0583 2169.7, 6480 16200 pa pa v t t for mm hr v mm hr       (7) for any given vibration velocity, the corresponding projected time can be obtained by solving eq. (7). the values of vibration velocity in mm/hr and the corresponding values of mtbf and failure rate for the 14 kg system load are encapsulated in table 5. the mtbf (12,998.2 hr) corresponding to vibration velocity 6,480 mm/hr (1.8 mm/sec) is obtained by deducting the value of average useful life period of the bearing, 16,773.18 hr (corresponding to 6,480 mm/hr) from the useful average life 29,771.38 (corresponding to 16,200 mm/hr). similarly, the mtbf (11,492.4 hr) corresponding to vibration velocity 7,200 mm/hr is obtained by deducting the value of average useful life period of the bearing, 18,278.98 hr (corresponding to 7,200 mm/hr) from the useful average life 29,771.38 (corresponding to 16,200 mm/hr). likewise, other values from 10,255.55 hr to 0.00 hr are obtained. in accordance with table 5, the variation of failure rate (per hr) of the experimental setup of class i machine with vibration velocity (mm/hr) for the system load of 14 kg, can be drawn as shown in fig. 4. the system availability can be calculated using the eq. (2). the repair corresponding to bearing failure involves (a) changing the bearing and (b) (occasionally) changing the shaft. the mttr is calculated as 47 min (0.783 hr). 190 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 table 3 the measured failure data and the projected useful life period for bearing 2 under the 14 kg system load vibration velocity (mm/hr) time (s) projected time for bearing for its useful life period (hr) trial 1 trial 2 trial 3 trial 4 trial 5 trial 6 average value 6,480 1,902 1,734 1,700 1,692 1,694 1,693 1,735.83 16,773.18 7,200 1,988 1,914 1,870 1,858 1,860 1,860 1,891.67 18,278.98 7,920 2,074 2,026 2,008 2,002 2,004 2,004 2,019.67 19,515.83 8,640 2,200 2,176 2,164 2,162 2,162 2,162 2,171.00 20,978.15 9,360 2,268 2,270 2,270 2,270 2,269 2,270 2,269.50 21,929.94 10,080 2,374 2,374 2,374 2,374 2,374 2,373 2,373.83 22,938.10 10,800 2,438 2,448 2,454 2,454 2454 2,454 2,450.33 23,677.31 11,520 2,496 2,520 2,526 2,528 2,528 2,528 2,521.00 24,360.16 12,240 2,570 2,614 2,622 2,624 2,623 2,622 2,612.50 25,244.31 12,960 2,714 2,733 2,738 2,740 2,739 2,738 2,733.67 26,415.13 13,680 2,806 2,838 2,846 2,848 2,848 2,847 2,838.83 27,431.35 14,400 2,896 2,934 2,944 2,946 2,946 2,945 2,935.17 28,362.21 14,760 2,936 2,969 2,980 2,982 2,982 2,982 2,971.83 28,716.51 15,120 2,968 3,004 3,014 3,016 3,015 3,016 3,005.50 29,041.83 15,480 2,998 3,034 3,042 3,044 3,043 3,044 3,034.17 29,318.83 15,840 3,028 3,060 3,068 3,069 3,068 3,069 3,060.33 29,571.68 16,200 3,060 3,086 3,091 3,075 3,090 3,084 3,081.00 29,771.38 table 4 the system load, coefficients, goodness of fit, and acceleration factor obtained from this study system load (m kg) coefficients goodness of fit (r2 value) acceleration factor (afm) a b c 14 +1.7491 × 10−5 −0.0803 +2828.30 0.997 34,786.423 15 +2.2053 × 10−5 −0.0313 +3975.10 0.999 32,723.243 16 −1.4072 × 10−5 +1.4825 −7885.70 0.987 32,694.021 17 +2.2995 × 10−5 +0.5762 −294.48 0.989 33,196.922 18 +2.4260 × 10−4 −3.7696 +21356.00 0.997 37,301.122 table 5 the vibration velocity, mtbf, and failure rate of the system for the 14 kg system load vibration velocity (mm/hr) mtbf (hr) failure rate (per hr) 6,480 12,998.20 0.000076934 7,200 11,492.40 0.000087014 7,920 10,255.55 0.000097508 8,640 8,793.23 0.000113724 9,360 7,841.44 0.000127528 10,080 6,833.28 0.000146343 10,800 6,094.07 0.000164094 11,520 5,411.22 0.000184801 12,240 4,527.07 0.000220894 12,960 3,356.25 0.000297952 13,680 2,340.03 0.000427345 14,400 1,409.17 0.000709637 14,760 1,054.87 0.000947988 15,120 729.55 0.001370711 15,480 452.55 0.002209724 15,840 199.70 0.005007524 16,200 0.00 ∞ 191 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 fig. 4 variation of failure rate (per hr) with vibration velocity (mm/hr) for the 14 kg system load fig. 5 variation of system availability with vibration velocity for different system loads fig. 5 shows the variation of system availability with vibration velocity (mm/hr) for different system loads from 14 kg to 18 kg. it is found that there is a slight decrease in availability between alert and alarm limit of vibration, and at the latter, there is a sudden decrease in availability to a value of zero for all system loads. it can be noted that at the maintenance initiation point, the system availability begins to decline. this is because, from this point onward, the reliability starts to decrease rapidly. the value of the maintenance initiation point for possible system loads is obtained as 12,176 mm/hr (3.4 mm/s). the value 3.4 mm/s is considered to be the maintenance initiation point for a system of class i machines. by considering all the possible system loads, the relation between the time available for maintenance initiation ta (hr) and the vibration velocity v (mm/hr) is given by: 2 0.00008 2.5944 20196 , 6480 12176  a t v v for mm h m hrr mv     (8) 4.2. error analysis keeping the system configuration and applied load unaltered, eight trials of the experiment are conducted, and the rms vibration velocity values and the corresponding times are recorded. using grubbs’ test at a significance level (α) = 0.02, the trials which involve outliers are detected and removed for a particular system load. the trials that are removed are two trials for the system loads of 14 kg, 15 kg, and 17 kg, and three trials for the system loads of 16 kg and 18 kg. the remaining trials of time (corresponding to the vibration velocity between alert and alarm limits) for the system loads of 14 kg, 15 kg, 16 kg, 17 kg, and 18 kg are subjected to error analysis to find the margin of error at 95% confidence interval. the maximum value of percentage margin of error (at 95% confidence interval) in the average time is calculated as 3.5%, which corresponds to the average time of 1735.83 s (corresponding to the vibration velocity 1.8 mm/s) for the system load of 14 kg. the minimum value of the percentage margin of error in the average time is 0.013%, which corresponds to the average time of 2373.83 sec (corresponding to the vibration velocity 2.8 mm/sec) for the system load of 14 kg. 0 0.001 0.002 0.003 0.004 0.005 0.006 6480 8480 10480 12480 14480 16480 f a ilu re r a te ( p e r h r) vibration velocity (mm/hr) 192 advances in technology innovation, vol. 7, no. 3, 2022, pp. 181-194 fig. 6 vibration velocity vs the average time corresponding to system loads (14 kg to18 kg) with error bars fig. 6 depicts the variation of vibration velocity between the alert and alarm limits against the average time of different trials (recorded in alt of bearing) for system loads from 14 kg to 18 kg. error bars (corresponding to the margin of error) in the average time are also shown in this figure. 5. conclusions in this experimental study, the failure of the machine was assessed by considering vibrations above the alert limit. accelerated life tests were conducted by creating a severe environment of high stress in the bearing of a class i machine system for experimentation. by a suitable external mechanism, the wear rate in the bearing was increased rapidly until failure occurred. the resulting vibration data were captured as a time series for analysis. the vibration was recorded as vibration velocity (rms). using a linear transformation, the time recorded was converted to the corresponding value in its normal use. a suitable loading mechanism was designed to apply possible magnitudes of system load. the major contributions of the proposed experimental study are summarized below. (1) it is demonstrated that the cbm initiation point of vibration velocity can be accurately predicted by the analysis of the pattern of system availability with vibrations to ensure the long life of the process plant machines and to enhance the overall performance of the plant. (2) the proposed model established a relationship between the vibration velocity and the projected useful life period of the bearing for the system of the electric motor with rated power 5 hp (class i machine) applied with different possible system loads. for a given value of maintenance initiation point of vibration velocity and a possible system load, the corresponding life of the bearing in the system can be computed using the proposed relation to conduct the systematic maintenance of the machines effectively. (3) in the proposed model, a general equation is developed between the time available for maintenance initiation and vibration velocity for the given system by considering different possible system loads. (4) the experimental study revealed that in cbm, the vibration parameter can be used as a reliable characteristic to predict the maintenance initiation point. conflicts of interest the authors declare no conflict of interest. references [1] h. d. goel, j. grievink, p. m. herder, and m. p. weijnen, “integrating reliability optimization into chemical process synthesis,” reliability engineering and system safety, vol. 78, no. 3, pp. 247-258, december 2002. [2] s. s. rao, reliability-based design, 1st ed., new york: mcgraw-hill inc., 1992. 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[29] a. regattieri, f. piana, m. gamberi, f. g. galizia, and a. casto, “reliability assessment of a packaging automatic machine by accelerated life testing approach,” procedia manufacturing, vol. 11, pp. 2178-2186, january 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 194 microsoft word 5-v9n2(2024)-aiti#13533(143-155).docx advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 english language proofreader: chih-wei chang influence of surface roughness on durability of new-old concrete interface nurdeen mohamed altwair*, younis omran yacoub, abdualhamid mohamed alsharif, lamen saleh sryh department of civil engineering, el-mergib university, al-khums, libya received 01 april 2024; received in revised form 29 april 2024; accepted 30 april 2024 doi: https://doi.org/10.46604/aiti.2024.13533 abstract the bond zone between old and new concrete is greatly affected by environmental factors. this study investigates the impact of surface roughness on durability using as-cast surface (cs), drilled holes surface (ds), and grooved surface (gs). after a 28-day water-curing, specimens undergo a 5% nacl solution immersion for 30 and 60 days; exposure to temperatures of 200 ℃ and 500 ℃; and a water permeability test. slant shear and splitting tensile tests assess durability. results show that cs exhibits the greatest decrease in resistance to sodium chloride solution and temperature, while ds and gs show less pronounced effects. at 500 ℃, cs and ds specimens fail, whereas gs retains 50% and 75% of its shear and tensile strengths, respectively. gs has the lowest water permeability (7 × 10-11 m/s), followed by ds (1.2 × 10-10) and cs (1.5 × 10-10). overall, surface roughness enhances durability and mitigates environmental effects. keywords: bonding strength, temperature, nacl solution, permeability 1. introduction repairing and strengthening structures often involves adding new concrete to an existing concrete substrate. typically, before applying the concrete, the surface of the substrate is intentionally made rough. numerous methods are evidenced to enhance surface roughness, with one of them being the mechanical approach. tools like scarifiers, grinders, or shot blasting machines are frequently adopted to create a surface by removing the layer of the existing substrate and exposing the aggregate [1]. this rough texture promotes bonding between the old concrete, enabling mechanical methods to be highly effective in enhancing bonding. the roughness of the existing substrate is particularly crucial in strengthening the bond between the new concrete [2]. a rough surface provides a contact area for the concrete to adhere to, resulting in improved bond strength. additionally, it enables interlocking between both layers of concrete, further enhancing their bond strength. in other words, enhancing the roughness of the concrete substrate surface leads to improved interfacial bond strength, primarily attributed to increased interfacial shear friction and mechanical interlocking between the layers of concrete [3]. previous research has examined techniques for creating surface roughness on concrete and improving bonding with newly applied concrete. the aforementioned methods were employed to roughen surfaces in real-world applications including utilizing a steel brush to prepare the surface, partially chipping the surface through holes, sandblasting the surface, and creating a textured surface [3-4]. the identification and characterization of bond qualities between old and new concrete have elicited considerable advances in structural engineering research in recent years. nevertheless, the strength of the connection often serves as a critical area in repaired structures. despite the progress herein, several ongoing concerns about the durability of bonding * corresponding author. e-mail address: nmaltwair@elmergib.edu.ly 144 advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 systems emerge subsequently [4]. one particular concern is the insufficient understanding and investigation concerning bond deterioration in harsh environments [5]. structural engineers delve into the durability of the bond zone between newly applied and existing concrete surfaces [6]. however, this zone is highly vulnerable to aggressive environmental conditions, especially after undergoing a rehabilitation period. the presence of chloride salts, acids, carbonation, significant variation in temperature and humidity, and the recurrence of freezing and thawing, can all contribute to the development of cracks that spread into undamaged regions [7], which ultimately compromises the overall durability of the concrete structure and may lead to structural failure. various environmental factors are evidenced, which can impact the durability of the bonding between existing and new concrete. among these factors, elevated temperatures, chloride exposure, and water permeability are known to significantly affect the integrity of the interface [8]. the surface roughness of the old concrete substrate has been identified as an important parameter influencing the properties. the temperature resistance of the interface is a critical factor. the thermal stresses experienced by the interface between new and old concrete can induce detrimental effects, subsequently leading to cracking and, ultimately, failure [9-10]. another significant concern regarding the new and old concrete interfaces is chloride resistance [11]. coastal regions and construction sites that are exposed to deicing salts are more susceptible to the penetration of chloride. the penetration of chlorides into the concrete may exacerbate and expedite the corrosion of reinforcement, presenting a significant hazard to the structural durability of the whole system [7, 11]. furthermore, the water permeability of the interface directly impacts the overall durability of the concrete structure [12]. the ingress of moisture through the interface can lead to various forms of damage, including freeze-thaw cycles and chemical degradation [13]. previous studies have investigated the impact of various environmental factors on the bond strength between old concrete and repaired concrete. the studies conducted by ding et al. [12] and mallat and alliche [14] expound on the importance of substrate roughness in enhancing the water impermeability and bond strength of concrete-based composites. while ding et al. [12] observed marginally higher permeability coefficients in bonded self-healing concrete (shc) with normal concrete (nc) compared to monotonic strain-hardening cementitious composite (shcc), the overall improvement in splitting tensile strength indicated that the roughened surfaces and epoxy bonding effectively strengthened the interfacial bond between the two shc and nc. similarly, tayeh et al. [2] explained the improved performance of ultra-high-performance concrete (uhpc)-nc composites, emphasizing mechanical interlock due to substrate roughening and the growth of hydration products as key factors contributing to the formation of a mechano-chemical bond. this bond, in turn, reduces the permeability of the composite to water, gas, and chloride ions. on the other hand, sabah et al. [15] conducted a retrospective study to investigate the composite action between uhpc and nc under fire exposure. the study employed various tests, including pull-off, flexure, splitting cylinder, and slant shear tests, to assess the bond strength between the two materials. the findings indicated an overall decrease in bond strength values across all test types. however, samples with roughened surfaces exhibited better performance and retained relatively higher strengths, particularly in tests involving tensile stresses. in a more recent investigation by gao et al. [10], the bond strength between engineered cementitious composites (ecc) and high-strength (hs) overlays was studied under temperatures ranging up to 800 ℃. interestingly, the researchers reported an anomalous result at 200 ℃, where an increase in bond strength was observed. such phenomenon can be attributed to the availability of free water at the interface, which facilitates the hydration of unreacted cement grains. however, at temperatures beyond 600 ℃, the hs overlay experienced severe cracking, rendering it unendurable to any loads. in contrast, the ecc overlay still displayed small bond strength values, highlighting the remarkable ability of ecc to maintain its integral bond and cohesiveness with another concrete surface even after exposure to extremely high temperatures. advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 145 regarding concrete bonding, significant progress has been achieved in understanding the quality of the bond between old and new concrete. nonetheless, the paucity of comprehensive research on the durability of the bonding zone has not been resolved as yet. existing studies have mainly focused on techniques to enhance the bonding, such as creating surface roughness, whereas scarce studies have addressed the influence of environmental factors on the bond. this research gap is particularly evident when considering the effects of temperature, direct exposure to chloride salt solutions, and water penetration on the contact area between the old and new concrete. these environmental factors can incur cracks and deterioration in the interface, compromising the overall durability of the repaired structure. to address this gap, further rigorous academic research is required to comprehensively understand the impact of these environmental conditions on the contact area and bond strength, especially in scenarios where the surface roughness of the old concrete changes, and the repaired concrete has normal compressive strength. the primary objective of this study is to determine the optimal methods of surface roughness preparation, e.g., as-cast surface (cs), drilled holes surface (ds), and grooved surface (gs), that promote optimal bonding between existing and new concrete. furthermore, the research aims to evaluate how this specific roughness influences permeability, ensures resistance against chloride salt attacks and enhances resistance against debonding when exposed to non-conventional temperature variations. to achieve these goals, the study will address the following tasks: (1) examine the effect of chloride salt solution and varying temperatures on the bond strength between existing and new concrete through slant shear and splitting tensile tests (2) assess the failure modes resulting from slant shear and splitting tensile tests when joint surfaces with different surface roughness between existing and new concrete are exposed to a sodium chloride salt solution and temperature (3) explore the influence of the concrete substrate surface with different surface roughness on reducing water penetration and improving the impermeability of the bond interface 2. materials and methods concrete was comprised of portland cement, natural sand from the zlitan region, and crushed gravel as coarse aggregate. the sand had a fineness modulus of 2.7, a specific gravity of 2.66, and a water absorption ratio of 0.85%. crushed gravel was deployed as coarse aggregate with a maximum grain size of 19 mm, a density of 2.67 g/cm3, and a water absorption of 2.8%. the process involved using ordinary tap water for curing and mixing fresh concrete, which exhibited qualities including freshness, potability, absence of color, taste, and biological materials. the composite specimens are composed of the concrete substrate and a newly designed concrete mixture intended to achieve normal-strength characteristics. specifically, the nc was targeted to have a grade of 30 mpa. the specimens were prepared with a mix containing 396 kg/m3 of cement, 185 kg/m3 of water, 425 kg/m3 of fine aggregate, and 1344 kg/m3 of coarse aggregate. this study focuses on preparing concrete surfaces before applying overlay concrete. the test specimens consist of two identical layers of concrete: the existing plain concrete substrate (old concrete) and the new concrete overlay. the plain concrete substrate specimens are placed within a lubricated mold and allowed to remain in their molds at room temperature for 24 hours. after a 24 hours period, the plain concrete substrate specimens are thoroughly cleaned and subjected to a 28-day curing process in a water curing tank. after 28 days of being cast and cured in water, the specimens were removed from the water tank for surface preparation. three methods of preparing the concrete substrate surface were used: cs (without surface preparation), gs, and ds, as shown in fig. 1. before applying the new concrete overlay, the old concrete specimens were fully immersed in water for one day and subjected to a drying period of 25 minutes. subsequently, the specimens were placed into their respective molds, and then the new concrete overlay was poured and allowed to cure at room temperature for 24 hours. after 24 hours, the specimens were removed from the molds and subjected to water curing for 28 days. 146 advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 (a) as-cast surface (b) drilled holes surface (c) grooves fig. 1 surface preparation after curing for 28 days, the specimens were removed from the water curing tank immersed in nacl solutions with mass concentrations of 5% for 30 and 60 days, and subjected to slant shear and splitting tensile tests. the slant shear specimens were designed with a prism shape measuring 15 cm × 15 cm × 30 cm (fig. 2(a)). the specimens were tested under compression using the standard approach for assessing the compressive strength of cubes, as outlined in the astm c882 standard [16]. the splitting tensile test was based on the guidelines specified in bs en 12390-6 [17]. as illustrated in fig. 2(b), the specimens were modified from their original cylindrical shape to cubic specimens measuring 15 cm × 15 cm × 15 cm. in the particular experimental setup, using cubic specimens elicits the feasibility and efficiency to conduct a larger number of tests within the given time and resource constraints. notably, both the cylinder-splitting test and the cube-splitting test yielded almost the same accuracy. (a) slant shear test (b) splitting tensile test fig. 2 test setup an automatic electric furnace was used for the heating of specimens with a constant heating rate of about 15 ℃/min to reach the prescribed 200 ℃ and 500 ℃ temperature levels (fig. 3). the temperature inside the furnace was maintained constant for three hours to achieve the thermal steady state condition after the target temperature was reached. after heating, the specimens were left at room temperature for one day before slant shear and splitting tensile tests. fig. 3 an automatic electric furnace contains specimens fig. 4 schematic view of permeability test advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 147 a water permeability test was conducted using cubic specimens with dimensions of 15 cm × 15 cm × 15cm, following bs en 12390-8 [18]. the permeability testing procedure is schematically shown in fig. 4. the test specimens were first placed inside the permeability cells, and then water was introduced on the lower face of the specimen. meanwhile, a pressure head of 5.5 bars was applied in a direction parallel to the contact surface between the old and new concrete for 72 hours. subsequently, the specimen was split in half perpendicular to the water pressure applied to the face. the maximum depth of penetration under the test area was recorded and measured to the nearest millimeter. the coefficient of water permeability, ��, was calculated using [19]: 2 2 =w d v k ht (1) where �� is the coefficient of water permeability (in m/s); � is the depth of penetration of concrete in meters; ℎ is the hydraulic head in meters; � is the time under pressure in seconds; and � is the porosity of concrete, which was determined following [2]. ρ = m v ad (2) where � is the gain in mass (in kg); � is the cross-sectional area of the specimen (in m2); is the density of water. 3. results and discussion this section presents and discusses the results of the accelerated environmental exposure tests conducted. the analysis and discussion of the tests carried out in this part are organized as follows: firstly, a comprehensive examination of the test results was performed, with a particular focus on the effect of subjecting the specimens to a sodium chloride solution. this part encompasses evaluations such as slant shear and splitting tensile tests. subsequently, the analysis and discussion of the results obtained from exposing the samples to different temperatures are addressed using the same set of evaluations. lastly, the analysis proceeds to discuss the results derived from the permeability test. 3.1. effect of nacl solution fig. 5 the relationship between shear strength and surface roughness after 15 and 30 days of nacl solution exposure the slant shear test is a widely recognized method for measuring bond strength under combined compression and shear loads. given its frequent deployment, moreover, it has been formally acknowledged by numerous international standards. fig. 5 displays the experimental slant shear strength test results. it can be noted that the bond strength of specimens without a 148 advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 roughening cs was found to decrease by 51% and 75% after 30 and 60 days when immersed in nacl solution. meanwhile, the ds specimens experienced a reduction of around 30% and 35% after 15 and 30 days, respectively. the gs specimens experienced a drop of around 8.6% and 15%. the gs yielded a lower decrease in shear strength compared to other surface roughness methods. the gs exhibited an 81% and 90% increase in shear strength compared to the cs after 30 and 60 days of immersion in nacl solution, respectively. the improvement also embodied a growth of around 49% to 48% compared to the ds at the corresponding ages. the aci 546r-96 [20] specifies a minimum permissible slant bond strength ranging from 6.9 to 12 mpa. ds and gs indicated shear strengths within acceptable limits before being placed in nacl solution. furthermore, it was reported that the gs specimens, while being submerged in a nacl solution for 60 days, exhibited shear strengths that fell within acceptable limits. these findings demonstrate that surfaces with varying types of roughness, such as ds and gs, significantly enhance the slant bond strength of the specimens in comparison to the control specimens. the splitting tensile test is a method used to assess bond strength at composite interfaces and measure the indirect tensile strength of the composite interface. the splitting tensile test results are shown in fig. 6 and are eminently consistent with those of the slant shear test. furthermore, the results reflect that substrate surfaces significantly increased the indirect tensile capacity before submerging the specimens in nacl solution. however, the ds and gs specimens demonstrated durability to the effects of the nacl solution, particularly the grooved specimens, which provided the highest value of tensile strength after being submerged in a nacl solution for 30 and 60 days. the groove method of surface preparation is the optimally efficient technique, as it yields the greatest capacity for indirect tensile strength compared to other methods. quantitative bond quality can be classified into five categories based on bond strength as follows: excellent (> 2.1 mpa), very good (1.7-2.1), good (1.4-1.7), fair (0.7-1.4), and poor (0-0.7). fig. 6 the relationship between the splitting tensile strength and surface roughness after 15 and 30 days of nacl solution exposure both ds and gs may be categorized as possessing exceptional bond strength since the bond strengths were more than 2.1 mpa. furthermore, the findings concerning the impact of surface roughness were discovered to be highly consistent with those of tayeh et al. [2], where the authors investigated various surface preparation methods for bonding ultra-high-performance fiber concrete to nc substrates to create repair composites. the researchers conducted a rapid chloride permeability test to evaluate the chloride resistance of the composites. five different surface textures were employed for surface roughening, including no roughness, sandblasting, wire brushing, drilling holes, and creating grooves. the results highlight the significance of surface preparation in achieving a strong mechanical bond between the composites and the substrate. the composites that underwent surface treatment exhibited the highest mechanical bond strength, yielding an enhanced resistance against chloride penetration. advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 149 the application of sodium chloride to concrete induces a sequence of reactions and interactions. given that sodium chloride would readily dissolve in water, the formation of sodium ions (na+) and chloride ions (cl-) can naturally react. upon the dissociation of chloride ions from sodium ions, they gain mobility within the aqueous solution, enabling them to permeate the concrete matrix through capillary action and diffusion. they can migrate through voids, pores, and weak areas, such as the surface between old and new concrete. high concentrations of chloride ions can interfere with the hydration process of cement, disrupting the formation of the cementitious gel, and resulting in reduced strength and increased permeability [21]. furthermore, grooves on the surface of old concrete (gs substrate) improve the bond strength with new concrete due to several factors. they provide interlocking mechanisms that enhance the mechanical connection between the layers, prevent slippage, increase the surface area available for bonding, facilitate chemical adhesion and mechanical interlocking, create a keying effect, distribute stresses between the old and new concrete, and help in load transfer by distributing stresses more uniformly [22]. the unique resistance of rough surfaces, especially those with gs, to the effects of nacl solution, may be due to the presence of grooves creating a more complex and interlocking surface profile. this mechanical interlocking provides additional resistance against separation and increases the overall surface area available for bonding. 3.2. effect of elevated temperature the effect of temperature on the slant shear bond is shown in fig. 7. the slant shear strength level was found to be susceptible to temperature changes. as shown in the figure, surface roughness is of evident importance in resisting the effects of temperature. by comparing the methods used in surface treatment, gs, yielded the highest slant shear strength, whether at a temperature of 200 ℃ or 500 ℃. the resistance of all the examined specimens to the effects of elevated temperature was observed at 200 ℃. the cs and ds specimens, however, failed at 500 ℃, whereas the gs specimen remained resistant. additionally, it is observed that the bonding strength of cs and ds decreased as the temperature increased due to the expansion emerging between the two layers of concrete and the development of thermal cracks on the composite surface, which also begot spelling at 500 ℃. the results of the slant shear strength of cs, ds, and gs were 0.87, 3.67, and 6.73 mpa at 200 ℃, respectively, while the slant shear strength of gs was 4.63 mpa at 500 ℃. fig. 7 the relationship between shear strength and surface roughness of specimens at 200 °c and 500 °c after 28 days of water curing failure patterns emerging during a slant shear strength test can be classified into four categories: pure interfacial failure (type a), concrete substrate cracking (type b), interfacial failure in conjunction with substrate fracture (type c), and substratum failure with a good interface (type d) [15]. encapsulate from the slant shear test results of this study, at 200 ℃, all specimens with both cs and ds surface treatments were successfully categorized as failure mode type a, while the failure 150 advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 mode in the gs, whether at 200 ℃ or 500 ℃, was type b (fig. 8). furthermore, despite being subjected to temperatures significantly exceeding the average room temperature, the gs specimens exhibited satisfactory strength, as specified in the aci 546r-96 [20]. (a) cs exhibited type a (b) ds exhibited type a (c) gs exhibited type b fig. 8 failure modes of specimens subjected to a slant shear test after exposure to temperature fig. 9 depicts the splitting tensile strength of specimens with varying roughness after exposure to temperatures of 200 and 500 ℃. the results of this test are consummately consistent with the scenarios concerning the slant shear test results. observably, the percentage reduction in splitting tensile strength for cs, ds, and gs at 200 ℃ was 50%, 47%, and 14%, respectively. fig. 9 the relationship between splitting tensile strength and surface roughness of specimens at 200 ℃ and 500 ℃ after 28 days of water curing however, both cs and ds failed before the specified duration of the test when exposed to a temperature of 500 ℃, which is due to the development of thermal cracks on the composite surface and the decomposition of the concrete structure after exposure to high temperatures, physically and chemically, which begot spelling [15]. the splitting tensile strength of gs specimens experienced a decline of approximately 75%, which is deemed acceptable for withstanding the impact of such temperatures. the tensile bond strengths of specimens treated with gs at 500 ℃ ranged from 0.7 to 1.4 mpa (i.e., 1.12 mpa), indicating that the quality of bonding was satisfactory [2]. indeed, the findings of this study correspond to the results reported by behforouz et al. [23] in the related study. the study investigated the effects of fly ash content and surface preparation methods on the bond strength of repaired concrete subjected to high temperatures. to evaluate the effects, four surface preparation methods were employed: cs, wire brushed, grooved, and grooved-wire brushed. the findings revealed that surface preparation yielded the most significant influence on bond advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 151 strength, gradually improving the bond strength. in the case of overlay concretes without fly ash, the bond strength reached zero for the cs and wire-brushed surface preparation methods at temperatures of 400 ℃ and 600 ℃, respectively. conversely, for the grooved and grooved-wire brushed methods, a 63% reduction was found in bond strength. based on fig. 10, the failure mode of the studied specimens in the splitting tensile test is similar to the failure in the slant shear test. in other words, at 200 ◦c, the cs and ds specimens had interface fractures, and no damage was observed either from the substrate (old concrete) or the overlay concrete (new concrete). total specimen failure occurred when the crack in the specimens subjected to tensile stresses emerged from the middle of the interface, propagated on both sides and reached the top and bottom of the specimens. (a) cs exhibited type a (b) ds exhibited type a (c) gs exhibited type b fig. 10 failure modes of specimens subjected to a splitting tensile test after exposure to temperature fig. 10(a) depicts the cs specimen subjected to the splitting tensile test. it can be observed that the concrete surface remained undamaged, and no additional damage was found on the surfaces (exhibiting type a failure). fig. 10(b) illustrates ds specimens that underwent the splitting tensile test. during the test, a small portion of concrete was penetrated the cavities formed by the drilling process. the interface failure mode occurred between the surfaces, similar to cs specimens, which exhibited type a failure. fig. 10(c) demonstrates the failure mode of the gs specimen under splitting tensile stress. the specimens had mixed-mode failure, which means minor substrate failure and interface failure occurred in specimens that exhibited type b failure. fig. 10(c) also reveals that the grooves provided significantly stronger bond strength compared to the substrate. it is palpable that the failure occurred partially within the substrate without complete separation or debonding between the substrate and the overlay concrete. the failure within the concrete substrate indicates robust bond proficiency, signifying that the strength of the interfacial bond is more significant than the strength of the concrete substrate. as stated by hager [24], specimens exposed to a temperature of 500 ℃ consistently exhibit a gradual decrease in their bonding strength. this decrease is attributed to the rapid decline in the content of portlandite as it undergoes decomposition. castellote et al. [25] further support this observation, reporting that the increase in cao content in cement paste at 500 ℃ can be explained by the decomposition reaction of portlandite. 3.3. water permeability evaluation fig. 11 depicts the water permeability of specimens with different surface treatments after 28 days of water curing. from this figure, it is evident that the surface roughness of the concrete substrate after treatment is the main factor affecting the permeability of the interface. as presented in fig. 11, it portrays that gs specimens exhibit a low value of water permeability, followed by ds specimens. it was found that the permeability coefficient was 1.5 × 10-10, 1.2 × 10-10, and 7 × 10-11 m/s for cs, ds, and gs, respectively. the percentage reduction in permeability coefficient values was approximately 20% for ds and 53% for gs compared to the permeability of cs. the grooved interface gs exhibits optimal impermeability due to its high interfacial 152 advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 bonding strength, which effectively reduces water permeability. the gs specimens effectuate a high roughness of the interface, which can effectively improve the mechanical interlocking and chemical force of the interface [26]. however, the permeability coefficient values for gs specimens still fall within the range of water permeability coefficients typically observed in concrete with average quality (10-11 10-12 m/s) [27]. fig. 11 water permeability of specimens with varying roughness after 28 days of water curing fig. 12 demonstrates that the permeability of the bond interface between old and new concrete is influenced by the treatments applied to the interface. the black line in the figures represents the water penetration depth of the specimen’s cross-section. when the interface is adequately treated and results in a well-bonded surface combination, the impermeability is significantly improved, effectively preventing water penetration. additionally, fig. 12 illustrates that specimens with different roughness, particularly gs specimens, demonstrated resistance to water penetration in comparison to specimens without roughness. the depth of water penetration was lowest in gs specimens, then ds specimens, and finally cs specimens. as previously mentioned, the reason for the prevention of water penetration on rough surfaces, particularly in gs specimens, can be attributed to the presence of grooves that create a more intricate and interlocking surface profile. when water comes into contact with the bonding zone, the grooves enhance the mechanical interlocking between the layers. these grooves introduce irregularities that amplify frictional forces, producing more bonding strength. this mechanical interlocking significantly contributes to additional resistance against water penetration. (a) as-cast surface (b) drilled holes surface (c) grooves fig. 12 water penetration depth front marked after the test moreover, the grooves generate additional contact points and increase the surface area, facilitating a larger bonding interface. this increased surface area enhances bond strength and fortifies the resistance to water penetration [22]. this finding is in agreement with the explanation given by ding et al. [12], who investigated the effects of interface treatment on the bonding surface permeabilities of shcc and nc. three surface treatments were used: no surface treatment, brushed interface, advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 153 and corrugated interface. the study found that the substrate material’s influence on interface permeability depends on surface roughness. the bonding behavior between shcc and nc is affected by factors such as existing concrete strength and surface roughness. the average permeability coefficient for the bonding surface treated by brushing was the lowest at 1.69 × 10-12 m/s, followed by the corrugated interface at 3.98 × 10-12 m/s. the bonding surface without treatment effectuated the highest average permeability coefficient at 7.81 × 10-12 m/s. these findings suggest that surface roughness is rather crucial in interfacial bonding strength and permeability. 4. conclusions based on the results obtained from the conducted experiments, the following conclusions can be drawn: (1) cs specimens exhibited a significant decrease in bond strength (51% and 75% after 30 and 60 days, respectively) when exposed to nacl solution. ds showed better resistance, with a smaller reduction (30% and 35% after 15 and 30 days, respectively). gs showed the highest increase in shear strength (81% and 90% after 30 and 60 days, respectively), surpassing cs and ds. the splitting tensile test results supported these findings, with ds and gs significantly enhancing indirect tensile capacity. gs specimens displayed the highest tensile strength, indicating their durability against nacl solution effects. (2) at 200 ℃, the slant shear strength results were 0.87 mpa for cs, 3.67 mpa for ds, and 6.73 mpa for gs. splitting tensile strength reductions were 50% for cs, 47% for ds, and 14% for gs. cs and ds specimens displayed interface fractures, while gs specimens exhibited mixed-mode failure. at 500 °c, cs and ds specimens failed, while gs specimens showed a decline in bonding shear strength. gs specimens demonstrated a significant reduction in splitting tensile strength, indicating a robust interfacial bond within the concrete substrate. (3) gs specimens demonstrated the lowest water permeability, with a coefficient of 7 × 10-11 m/s, followed by ds specimens with a coefficient of 1.2 × 10-10 m/s. cs specimens showed the highest permeability at 1.5 × 10-10 m/s. the permeability coefficient values for gs specimens fell within the typical range for average-quality concrete. depth of water penetration results supported these findings. the study focused on three surface preparation methods (cs, ds, and gs) to assess interfacial bond strength and durability. however, excluding environmental factors, such as carbonation and freeze-thaw cycles, limits further discussions. the evaluation was limited to specific exposure periods, hindering long-term insights. field studies and techniques like sem and xrd could enhance the investigation. the study did not consider the influence of concrete mix designs or properties. future research should explore the impact of different compositions, including aggregates and admixtures, on interfacial zone performance. abbreviations and symbols cs as-cast surface (without surface preparation) hs high-strength ds drilled holes surface na+ sodium ions gs grooved surface clchloride ions nacl sodium chloride sem scanning electron microscopy shc self-healing concrete xrd x-ray diffraction nc normal concrete astm american society for testing and materials shcc strain-hardening cementitious composite bsi british standards institution uhpc ultra-high-performance concrete kw coefficient of water permeability ecc engineered cementitious composites porosity of concrete conflicts of interest the authors declare no conflict of interest. 154 advances in technology innovation, vol. 9, no. 2, 2024, pp. 143-155 references [1] b. zhang, j. yu, w. chen, h. liu, h. li, and h. guo, “experimental study on bond performance of nc-uhpc interfaces with different roughness and substrate strength,” materials, vol. 16, no. 7, article no. 2708, april 2023. 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[27] f. rendell, r. jauberthie, and m. grantham, deteriorated concrete: inspection and physicochemical analysis, london: thomas telford, 2002. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v9n4(2024)-aiti#14048(273-286).docx advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 english language proofreader: yen-chun hsieh enhanced design of on-chip monopole antenna inspired by partially reflective surface at 5.8 ghz ahmadu girgiri1, mohd fadzil ain1,*, mohd zamir bin pakhuruddin2, bello abdullahi muhammad1, abdullahi sarkin bauchi mohammed1 1school of electrical and electronic engineering, university sains malaysia, nibong tebal, malaysia 2school of physic, university sains malaysia, penang, malaysia received 24 april 2024; received in revised form 24 july 2024; accepted 25 july 2024 doi: https://doi.org/10.46604/aiti.2024.14048 abstract the increasing popularity of compact, chip-based devices has spurred interest in developing on-chip antennas (ocas). however, ocas suffer from low gain and poor radiation efficiency due to the silicon substrate’s low resistivity and high permittivity, influencing antenna performance. to avert these challenges, this study aims to enhance an oca’s gain and radiation efficiency by incorporating a partially reflective surface (prs) into the antenna structure. the antenna is simulated using 3d cst software, and its performance is evaluated. to validate the simulation, an antenna prototype is fabricated using sputtering and chemical vapor deposition (cvd) technologies. the prototype demonstrates a peak gain of 2.14 db and radiation efficiency of 72.2%, showing a 24.3% gain increase and a 16.25% efficiency increase compared to the design without prs. additionally, it achieves an impedance bandwidth of 0.63 ghz, making it suitable for wimax, rfic, and wi-fi 6 applications. keywords: on-chip antenna, gain, partially reflective surface, radiation efficiency, silicon substrate 1. introduction in recent years, the demand for compact and integrated devices has risen due to the emergence of new applications. this increased demand has necessitated the development of integrated antennas, specifically on-chip antenna (oca) technology. oca is a noteworthy chip-based antenna that can be integrated into a silicon chip alongside other proximity radio frequency (rf) front-end components [1]. it is potentially integrated into internet-of-things (iot) based devices, energy harvesting, emerging wireless systems, and similar devices. its applications span various devices such as mobile phones, transceivers, and iot devices [2]; as a result, the need for communication channels that are low-power, secured, and high-speed has become essential. this facilitates the seamless integration of ocas into compact transceivers in lower and higher applications [3-6]. numerous studies highlight the potential and significance of integrated antennas in expansive settings. the prevalent approach involves either single-chip modules (scm) or multi-chip modules (mcm) [7-9]. however, silicon as a substrate poses significant challenges due to its low resistivity and high permittivity [10-11]. these drawbacks adversely impact the antenna performance and distort its radiation and signal integrity [12-13]. to overcome these limitations, alternative approaches incorporating the use of an artificial magnetic conductor (amc), substrate thinning technology, low back-etching (lbe), dielectric resonator antenna (dra), inductor-capacitor loading, ion implantation, artificial dielectric layer (adl), partial shield layers (psl) and similar techniques have been demonstrated in the literature. the most adopted techniques are amc, inductor-capacitor loading, psl, and partially reflective surface (prs) due to their cost-effectiveness and simple design configuration compared to the few mentioned. * corresponding author. e-mail address: eemfadzil@usm.my 274 advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 bean and venkataraman [13] employed, an amc to improve a gain of 60 ghz yagi-uda integrated oca designed for short-range inter-chip communication. in the design, units of jerusalem cross amc were configured to achieve an increased gain of 11% and radiation efficiency of 12%. a study progressively demonstrated this technique, where amc techniques have increased wideband, circular ring monopole integrated oca performance [14]. the design considerably increased the operational gain, impedance bandwidth, and radiation efficiency. similarly, the study employing amc changes the performance of folded-dipole oca by improving the antenna gain by 8 db compared to the antenna without amc [15]. furthermore, inductance-capacitance loading [16] and psl [17] represent another potential technique for enhancing oca performance. these layers share similar characteristics with an amc and prs, and they equally aid in antenna miniaturization. for instance, a psl was embedded within sio2 of 11 ghz meandered loop oca, which yielded an increased gain of 4 db, which is considered remarkable in oca design [17]. however, an alternative technique for enhancing gain and radiation characteristics involves dra loading, wherein a highresistivity substrate would be added to the antenna, thereby mitigating losses associated with the lossy substrate. this method reduces surface wave generation and radiation loss by directing electromagnetic (em) through a dielectric resonator before releasing them into the surrounding medium. several studies have suggested using a dra as an alternative approach. for example, kong et al. [18] proposed a high gain, wide impedance bandwidth by incorporating a dra into a low-profile oca. the constructed prototype was tested, resulting in a radiation efficiency of 44% and an absolute gain of 8.6 db. this method significantly performs as it reduces surface waves and loss attributed to metallization; besides, it faces integration challenges and incompatibility with modern complementary metal-oxide-semiconductor (cmos) processes. this study employs a prs to enhance oca performance, particularly the gain and radiation characteristics. prs similarly behaves like amc as it exhibits high impedance characteristics, where the magnitude of the surface impedance is based on the number of unit cells and the reactance parameters of the periodic structure [19]. the fundamental concept of artificially created surface or material is to achieve a high impedance surface (his) that acts as a whole or partial shield to the striking incidence wave on their surface, where both the prs and amc have such characteristics and consist of an array of unit cell or patch arranged periodically. they exhibit high-impedance properties and are engineered to reflect incoming waves with zerophase shifts. however, while the prs partially reflects incoming waves, directing them toward the lossy substrate, the amc achieves high reflection. its inclusion significantly improves the antenna gain and radiation efficiency over non-prs-inspired designs. prs enables partial reflection of incidence wave from confining into the lossy si-substrate [20]. however, complete restriction of em is not achievable as the cmos metallization rule process limits the metal density usage to around 20-80% in both layers [3]. as oca integration can be achieved by standard cmos, bi-cmos process with metal-insulator-metal (mim) configuration, or using sio2 on si-wafer commonly using 250 µm, 500 µm, or 525µm based on metal-insulator-semiconductor (mis) using cmos design procedures. in this design, an mis structure was used instead of standard cmos process 0.18 µm or 0.13 µm technology due to the notable antenna performance, despite the significant feature of cmos process 0.18 µm in chip design. to justify the importance of the adopted technology, the following reasons are enlisted based on the following parameters; (1) technology: in cmos 0.18 µm technology, multiple layers of mim are utilized to create an oca, contrasting with just five layers of mis used previously. this approach significantly enhances antenna performance compared to existing literature on 0.18 µm technology. (2) performance: increasing the number of mim layers in the configuration causes mutual coupling within the chip, which creates parasitic capacitance across the structure. this capacitance impacts the antenna’s radiation resistance, pattern, and gain. advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 275 (3) optimization: the cmos technology fabricated using the standard 0.18 µm process is inherently inflexible compared to those built on 525 µm si-wafers, which provide greater design flexibility and are easier to optimize at a lower fabrication cost, independent of manufacturer specifications. (4) cost: the 0.18 µm standard technology incorporates numerous reactive components and multiple metal layers, some dedicated to antenna design and others to different integration purposes. however, several layers remain unused, adding to power consumption and costs. prs offers distinct advantages over other mentioned techniques. for example, substrate loading and dra incur additional integration costs and are incompatible with silicon substrates, while amc increases metal density, leading to larger chip sizes and greater design complexity. on the other hand, substrate thinning and lbe require post-processing, resulting in high fabrication costs. prs stands out with benefits such as low integration costs, the ability to enable multiple layer configurations within a small area, and a compact oca design compared to other methods. however, prs also has drawbacks, including partial reflection characteristics and susceptibility to significant changes in reflection and transmission coefficients, especially in high-frequency designs. this paper is arranged as follows: the design and configuration of the proposed antenna, the periodic structure prs design, and its characteristics are discussed in section 2. in section 3, the results and analysis of the simulated and corresponding measured parameters were discussed and presented. thus, the results summary is concluded in section 4. 2. antenna design and analysis this section covers the design and analysis of the proposed antenna and its configurations, including the geometric dimensions, materials, and tools used in the design process. generally, the antenna features a multi-layered stacked structure with top metal as a radiator. the following section will provide a detailed presentation of the antenna parameters. 2.1. antenna geometry and configuration the proposed antenna geometrically follows the typical principles of cmos design, wherein a six-layer mis consists of sio2 layers, a ground conductor, prs, a radiating element, and a silicon substrate [21-22]. the host material used was a processed silicon wafer of dielectric constant (εr) of 11.7-11.9 [6], a resistivity of 1-20 ω-cm, and a thickness of 525 μm [6] coplanar waveguide (cpw) port is used as a feeding port due to its low profile, low dispersion, and integration simplicity [23], which is coupled to the monopole antenna (m1) on the top metal layer of the chip as depicted in fig. 1. (a) top view (b) layered view fig. 1 geometry of the proposed antenna the design incorporates a prs as a high-impedance surface (his). the radiator optimized to a dimension of 0.26 λ × 0.34 λ mm2 fitted to be integrated as the oca. fig. 2(a) illustrates the stacked antenna structure showing two sio2 layers of 2.5 µm each, a thin film of silver material, and m1 of 1.7 µm were configured as insulators and the radiating conductor. the 276 advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 second metallization (m2) is used as the prs and embedded within the layers of sio2 as a reflective surface, which acts as a shield to the confining em wave migrating from the radiating element into the lossy si-substrate. the third metallization (m3) is the ground plane of the chip. an optimized dimension of the radiating element is shown in table 1. table 1 optimized parameters of the proposed antenna parameter value (mm) parameter value (mm) le 1.0 wf 2.0 ws 5.45 lp 17.62 lx 5.62 la 4.12 wq 5.45 lr 5.7 wp 13.91 lf 15.4 tm 0.001 hs 0.002 hsi 0.525 g 0.505 2.2. design of partially reflective surface (a) isometric stacked-up view (b) periodic prs structure fig. 2 staked up layers of the proposed design advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 277 prs is the arrangement of regular metal film designed to be his embedded between the layers of sio2. it has working features similar to an amc. prs acts to obstruct migrated incidence power from the radiating element to the lossy si-substrate. it can be designed to plump the magnitude of the reflected signal and control the antenna’s resonance [19]. for example, in cmos process design, embedding a high impedance periodic structure within the layers of sio2 restricts a reflected incidence wave emanating from the radiator toward the si-substrate [24], thereby minimizing the power losses of the oca. in this design, a periodic aperture of 4 × 4 unit cells of metal thickness, tm = 1 μm, a length and width of a = 2 mm each configured as an aperture of his. the structure is embedded into the thin sio2 layers shown in fig. 2(b). 2.3. characteristics of prs structure a single unit of the prs was configured and positioned within the waveguide ports with boundary conditions set at the x-plane and y-plane and simulated using a frequency domain solver. consequently, in fig. 3(a), the reflection and transmission coefficients of the structure are depicted, while fig. 3(b) showcases the reflection phase at 5.804 ghz. the characteristic response of fig. 3(a) indicates that the peak reflection coefficient occurred below -0.19 db and the reflection coefficient at 24.1 db across a bandwidth of 5.68-5.92 ghz. similarly, fig. 3(b) illustrates a zero-degree reflection phase at 5.88 ghz with a slight shift in the center frequency of 5.8 ghz. this indicates that the incident wave was hindered due to the high impedance generated by the prs. moreover, it resulted in an insertion loss of about 3 db at the transmission phase from 5.62 ghz at the lower side frequency and 6.16 ghz at the upper side frequency with 5.804 ghz as the center frequency. 2.4. effect of prs patch separation distance on the reflection phase the characteristics of the prs indicate that the reflection phase magnitude is influenced by the number of unit cells or patches, the spacing between the patches, and their thickness. this section examined the prs’s effectiveness based on the separation gap, s, between adjacent patches, which indirectly reduces the length and width of the patch. the optimized prs patch size and gap are 2 mm and 0.2 mm, respectively. consequently, a parametric analysis of the separation, s, was conducted from 1.5 mm to 3 mm in 0.5 mm intervals. fig. 3(c) illustrates the impact of the gap between prs patches on the reflection phase magnitude. the plots reveal that the magnitude of the reflection phase decreases as the separation gap increases. this is due to the additional change in capacitance between adjacent patches, as the capacitance between two adjoining patches is inversely proportional to the separation distance. this change in capacitance significantly affects the reflection phase antenna’s performance. (a) reflection and transmission fig. 3 the simulated coefficients and the reflection phase of prs at 5.8 ghz 278 advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 (b) reflection phase (c) effect of sio2 thickness on the antenna gain fig. 3 the simulated coefficients and the reflection phase of prs at 5.8 ghz (continued) 3. measured results and analysis measurement is a crucial phase for evaluating the simulation results. it outlines the comprehensive analysis of the results obtained, as well as the procedures and graphical presentation of the results. in this design, detailed measurements of the fabrication process, measurement procedures, and equipment are included. the primary measured parameters include the return loss, gain, radiation efficiency, radiation pattern, and antenna impedance bandwidth. 3.1. antenna fabrication process prototype development of the design was realized based on the cmos compatibility procedure, where direct current (dc) sputtering and chemical vapor deposition (cvd) technologies were employed. a processed standard si-substrate, p-type, 100 orientations, 525 μm thick, and resistivity of 1-20 ω-cm was selected to accomplish the process. the stacked structure consists of thin layers of sio2, top metal (m1), prs (m2), and ground conductor (m3), all stacked on the substrate to form a single structure. step 1, a thin layer of 1 μm of silver (ag) material was deposited at the bottom of the si-substrate, which acts as a ground conductor. step 2, a cvd process was used to deposit a 2.5 µm sio2 layer on top of the si-substrate as an insulation segment. the step 1 was repeated for depositing prs (m2) of 1 μm thickness. similarly, the second sio2 layer was deposited on top of the prs layer utilizing the same process as step 2. advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 279 finally, the monopole planar radiator (m1) of 1 µm was deposited on the top metal layer on the upper layer. fig. 4(a) and 4(b) show the fabrication process and final fabricated prototype, while fig. 4(c) depicts the measurement set-up. (a) fabrication process (b) fabricated prototype (c) measurement set-up fig. 4 fabrication and measurement set-up of the proposed antenna 3.2. impedance, radiation characteristics, gain and efficiency (a) simulated and measured return loss (b) gain and efficiency fig. 5 simulated and measured parameters of the proposed at 5.8 ghz 280 advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 following the fabrication process, this section presents the measured performance of the proposed antenna, introducing the reflective surface, prs, which significantly enhanced the antenna’s gain and radiation efficiency. specifically, compared to the antenna without prs, the antenna achieved a notable increase in gain of 24.3% and efficiency of 16.25%. notably, a significant agreement is observed between the simulated and measured parameters. the fabricated prototype was measured and realized a maximum gain of 2.14 db with a radiation efficiency of 72.2%, as shown in fig. 5. although minor discrepancies in antenna parameters were noted, likely due to mismatches and fabrication tolerances. (a) magnitude of s11 (db) (b) gain (db) (c) efficiency (%) fig. 6 the comparison s11, gain and efficiency of an antenna with and without prs moreover, efficiency is measured based on the gain and directivity derived from characteristic measurements. initially, these values were determined by setting an agilent signal generator 83640b to 0 dbm and an operating frequency of 5.8 ghz. the output power was recorded using a network signal analyzer n9030a, which was connected to a receiver antenna positioned at a distance s from the transmitter antenna, as illustrated in fig. 6. a broadband horn antenna (lb-20200-sf) with a gain of 20 db and a frequency range of 2-20 ghz served as the transmitter antenna. measurements were repeated at various values of s until the maximum gain was identified. a link budget based on friis’s transmission formula below was employed to calculate the maximum gain in db. consequently, peak gains of 1.587 db and 2.138 db were achieved for the antenna under test (aut) with and without prs, respectively. = + + + −r t t r p clp p g g l p (1) 2 (mw) π λ = r t pd g p (2) advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 281 10 2 10 log (db) π λ   =      r t pd g p (3) where, �� and �� are the transmitted power by the transmitter and received power by the receiver (dbm), �� and �� are the gain of the transmitter antenna, and the receiver antenna’s gain (db). ��� and �� are cable loss (dbm) and the loss due to free space. hence, �� can be determined as: 34.21 20log 20log= + +pl s f (4) 22 λ ≥ d s (5) the performance of the antenna with and without the prs was compared in terms of s11, gain, and efficiency, as illustrated in fig. 6. the 2d radiation characteristic of the model in the e-plane and h-plane were plotted as shown in fig. 7, where s is the distance between the transmitter and receiver antenna, d is the diameter of the horn antenna, λ is the wavelength, and f is the operating frequency in (mhz). (a) e-plane (b) h-plane fig. 7 simulated and measured 2d radiation pattern at 5.8 ghz in a similar procedure, the directivity of the aut was assessed based on the measured radiation pattern, where the gain and the corresponding theta (degree) for the e-plane and h-plane were plotted on a polar graph, and the equivalent half-power beam width (hpbw) angle denoted as and � were measured. the directivity was then determined as: 32400 θ θ = ×e h d (6) η = + l r r p p p (7) η = g d (8) subsequently, eqs. (7) and (8) were used to measure the radiation efficiency of the antenna. however, the result for eq. (8) was finally chosen for accuracy, considering the relationship between gain, directivity, and losses incurred by antenna components such as dielectric and conductor tied to antenna design material. this equation also aligns with ieee standards for calculating radiation efficiency. to assess the notable impact of the similarity in pattern between the simulated and measured characteristics. however, some variation exists ascribed to unavoidable path loss, conductor loss, interference, and stacking tolerance due to the metallic layers. this positive implementation underscores the efficacy of the design modifications in improving antenna performance. 282 advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 however, the impact of the prs on the reflection coefficient was noted by positioning it at various separation distances (d) from the upper antenna element. this led to a frequency shift caused by induced mutual coupling and parasitic capacitance across the region, as depicted in fig. 8. equally, significant values for the gain, radiation efficiency, and bandwidth below a return loss below -10 db were achieved. the simulation outcomes indicated an impedance bandwidth of 0.72 ghz, which is 5.56% greater than the measured bandwidth of 0.68 ghz. consequently, this bandwidth aligns well with the requirements of wi-fi, wimax, and rfic applications at 5.8 ghz [25]. (a) surface current distribution (b) e-field fig. 8 simulated surface and e-field at 5.8 ghz 3.3. surface current distribution and e-field vector due to the varied characteristics of the antenna radiation pattern, the antenna’s surface current distribution and electric field (e-field) were also analyzed. figs. 8(a) and 8(b) illustrate the e-field strength and surface current distribution at 5.8 ghz. as shown in fig. 8(a), the e-field concentration is highest at the excitation port and along the entire signal conductor, while it is lower at the antenna’s curvature. similarly, the surface current distribution is most significant around the excitation point and along the center conductor, with less distribution observed in other parts of the antenna. the increased surface current distribution along the metallic path enhances the antenna’s radiation characteristics, indicating that the strength of the current distribution effectively transforms the transverse electromagnetic (tem) mode near the port into a parallel plate mode. 3.4. effect of prs separation distance on the reflection coefficient (a) frequency vs. reflection coefficient (b) antenna-prs model fig. 9 effect of prs separation on the reflection coefficient advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 283 this section investigated the effect of the separation distance between the prs and the top antenna element. the antenna is positioned above the prs structure, and the impact of the separation distance between the antenna and prs, denoted as d, is investigated. distances d from 1 µm to 3 μm at 0.5 µm intervals are considered. a sio2 with a permittivity of 3.8 is utilized between the prs and the antenna. fig. 9 shows the simulation outcomes, revealing a noticeable shift in resonance frequency as the separation distance increases, where d equals 2.5 μm and 3 μm corresponds to the target frequency of 5.8 ghz. this shift is attributed to the mutual coupling between the prs and the top radiating element, leading to the induction of parasitic capacitance across the separation. thus, it is evident that altering the capacitance values, whether increasing or decreasing them, significantly affects the resonance frequency as it is inversely proportional to the equivalent capacitance. which can be expressed as; 1 α r eq f c (9) where �� is an equivalent capacitance between the separation, and the fr is the antenna’s resonant frequency. however, to achieve prs’s height optimization, the following factors should be considered: ensuring that the reflected phase is within -90° to +90°. this means that the prs’s operating frequency should equal the desired frequency. = −c mdevf f f (10) = −max minbandf f f (11) secondly, the bandwidth of the structure is as wide as possible in such a deviation in frequency, fdev is minimized, and band frequency, fband is maximized as expressed in: ( ) ( ), =  band devf maximize f minimize f (12) secondly, when optimizing the prs height, it’s crucial to account for the distance between the prs and the radiating conductor to prevent the incidence and reflected waves from overlapping in time, as given in: ( ) ( ) ( ) 4π ϕ ϕ ϕ= − +prs r inc fd f f f v (13) where f is the frequency (hz), ������� is the prs shift in the reflection phase, ����� is the reflected wave phase, ������� is the incidence wave phase, d denotes the distance between the prs and the top antenna, and v is the speed of the medium. however, �� is the center frequency at 0° reflection phase, �� is the medium frequency obtained at 0° reflection phase, and ���� and ���� are bandwidth minimum and maximum frequency. fig. 10 parametric studies on the effect of sio2 on the antenna gain 284 advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 3.5. a parametric analysis of the effect of prs geometry on the reflection phase in the oca structure, comprising sio2, metal layers, and a lossy si-substrate, previous studies and this research highlight the critical role of the insulation layer, sio2, in shaping antenna performance. minor changes in sio2 thickness significantly impact both gain and radiation resistance by providing insulation between the metallization layers and the si-substrate. the parametric analysis shows that increasing sio2 thickness widens the separation between the prs and the si-substrate and between the prs and the top antenna element. this results in a notable gain enhancement. fig. 10 illustrates the effect of varying sio2 on antenna gain. 3.6. comparative analysis of the proposed antenna and the performance of published work table 2 compares the proposed design’s performance and other ocas, focusing on gain, radiation efficiency, bandwidth, and technology. this work utilized mis components following the metallization rule of the cmos process, employing only three metal layers to reduce the fabrication and material cost. despite the few metal layers, the proposed antenna achieved a gain of 2.14 db and a radiation efficiency of 72.2%. this improvement is attributed to the reduced dielectric losses and magnetic coupling across the layers. in contrast, previous work utilized standard cmos technology 0.18 μm and 0.13 μm. although oca design using these technologies is notably compact, facilitating integration into smaller chip sizes. however, this results in a low gain and radiation efficiency, significantly reducing the antenna’s performance. the proposed oca facilitates a physical connection to the coaxial port of 50 ω and simplifies real-time measurement as no micrograph technology is required. thus, integration into the transceiver is achievable by replacing the port and utilizing the cpw pad to enable connection to the front-end circuit. table 2 comparison of the proposed antenna with previous literature ref antenna type freq (ghz) size (��) max gain (db) rad. eff (%) return loss (db) technology [17] monopole meandered 9.45 0.063 × 0.066 -29.2 21.07 13.2 0.18 μm cmos [22] meander loop 5.8 0.12 × 0.01 -40 25 nm 0.13 μm cmos [25] loop 5.8 0.027 × 0.027 -48.93 nm 48.09 0.18 μm cmos [26] meander dipole 2.4 0.032 × 0.032 -23.8 (in air) -25.9 (in skin) 60 <-10 0.18 μm cmos [27] loop 5.8 0.020 × 0.016 -23.7 nm 0.18 µm cmos [28] folded dipole 5.8 0.079 × 0.77 2.1 68.7 -23 mis-si-wafer [29] folded loop 2.4 0.012 × 0.012 -20.8 31.2 nm umc 0.18 µm this work monopole planar 5.8 0.26 × 0.34 2.14 72.2 14.99 0.525μm si wafer + sio2 4. conclusion this article introduces a monopole planar oca with improved gain and radiation performance. a six-layer mis stacked structure was configured as the oca. the design incorporates a prs aperture as the gain and radiation enhancement technique. a dc magnetron sputtering and cvd technologies were employed for the prototype development. the prototype was measured and obtained an increased gain of 24.3%, elevating it from 1.59 db to 2.14 db, yielding a peak radiation efficiency of 72.2%. this broadened the measured impedance bandwidth of the antenna to 0.63 ghz, covering the range from 5.56 ghz to 6.24 ghz. the radiation characteristics of the prototype were assessed, revealing a similar radiation pattern in both absolute measured and simulated plots. this indicates a consistent alignment between the simulated and measured patterns. however, minor discrepancies and irregularities were noted in the measured radiation patterns, attributed to fabrication tolerances and advances in technology innovation, vol. 9, no. 4, 2024, pp. 273-286 285 reactance generated across layers due to utilizing multiple components with varying dielectric properties. despite these variations, the prototype exhibited desirable bandwidth, gain, and efficiency, enabling its integration with rf front-end circuitry, rfic, and wimax at 5.8 ghz despite the larger wavelength at a lower frequency. acknowledgment this work was supported by the ministry of higher education malaysia through the fundamental research grant scheme under frgs/1/2023/tko7/usm/01/1. 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[28] a. girgiri, m. f. ain, b. a. muhammad, and a. s. mohammed, “design of miniaturized folded dipole integrated onchip antenna for 5.8ghz application,” ieee international symposium on antennas and propagation, pp. 1-2, october-november 2023. [29] s. archana and m. bhaskar, “an integrated 2.4 ghz inductorless power amplifier and on-chip two turn folded loop antenna for biotelemetry applications,” 14th international conference on computing communication and networking technologies, pp. 1-6, july 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 6___aiti#7592_in press advances in technology innovation, vol. 6, no. 4, 2021, pp. 262-281 new electronically tunable third order filters and dual mode sinusoidal oscillator using vdtas and grounded capacitors tapas kumar paul, radha raman pal* department of physics, vidyasagar university, midnapore, west bengal, india received 03 may 2021; received in revised form 13 august 2021; accepted 14 august 2021 doi: https://doi.org/10.46604/aiti.2021.7592 abstract this study introduces a third order filter and a third order oscillator configuration. both the circuits use two voltage difference transconductance amplifiers (vdtas) and three grounded capacitors. by selecting the input and output terminals properly, current mode and transimpedance mode low-pass and band-pass filters can be obtained without component matching conditions. the natural frequency (ω0) can be tuned electronically. the oscillator circuit provides voltage and current outputs explicitly. the condition of oscillation (co) and the frequency of oscillation (fo) can be adjusted orthogonally and electronically. the workability of the configurations is judged using tsmc cmos 0.18 µm technology parameter as well as commercially available lm13700 integrated circuits (ics). the simulation results show that: for ±0.9v power supply, the power consumption is 1.08 mw for both the configurations, while total harmonic distortions (thds) are less than 2.06% and 2.17% for the filter and oscillator configurations, respectively. keywords: dual mode third order oscillator, third order filter, total harmonic distortion (thd), voltage difference transconductance amplifier (vdta) 1. introduction although there has been a great development in the field of digital signal processing, the devices which are entirely capable of processing analog signals have not lost their popularity because all the natural signals are analog in nature. analog signal processing (asp), in which natural/analog signals are handled according to the specifications, has advantages such as higher bandwidth, faster operation speed, etc. filter and sinusoidal oscillators are two widely used applications in the field of asp [1]. filters are very useful for signal processing circuits in instrumentation, control engineering, and various communication systems. filters are also useful in phase shifting, frequency doubling, and interfacing with other circuits. current mode filters offer some advantages, e.g., low power consumption, wide bandwidth, wider dynamic range, and high slew rate [1]. third order filters have a sharper cut-off than biquadratic filters, which is a great advantage in various communication applications. recently, there has been an increasing interest in designing a filter employing various active building blocks (abbs) such as four terminal floating nullor (ftfn) [2], voltage differencing buffered amplifier (vdba) [3], differential difference current conveyor (ddcc) [4], current differencing buffered amplifier (cdba) [5], differential voltage current conveyor (dvcc) [6], voltage differencing current conveyor (vdcc) [7], voltage differencing transconductance amplifier (vdta) [8], etc. most of the reported circuits are second-order filters [1-8]. however, some research also deal with third order and higher order filters [9-25]. these filters suffer from one or more of the following drawbacks: *corresponding author. e-mail address: rrpal@mail.vidyasagar.ac.in advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 (1) more than two abbs are used [4, 10-11, 16-21, 23, 25]. (2) comparatively large supply voltage is required [2-3, 8, 10-14, 18, 23-25]. (3) circuits are not resistorless [1-2, 4-6, 7, 9, 12-16, 22-24]. (4) all the used capacitors are not grounded [2-3, 5-6, 12-15, 24-25]. (5) double/inverted input signals are required for response realization [2-3, 5-6, 25]. (6) matching conditions are required to realize various filter responses [6, 9, 11, 13, 15, 24]. (7) the natural frequency is not electronically tunable [2, 4-6, 9-10, 12-17, 21-24]. sinusoidal oscillators play a vital role in power electronics, measurement, standard tests, communication systems, and instrumentation. the third order sinusoidal oscillators offer better frequency response and low harmonic distortion than second order oscillators [26]. recently, a number of oscillators using vdta as an active block have already been published [26-29], but all the reported circuits have one or more limitations: (1) the oscillators require additional terminals for vdta blocks [26-29]. (2) matching condition is required [26]. a universal current mode biquad filter is proposed in the work of satansup et al. [8]. the topology of their work has become our topic of contemplation. we have considered carefully appending a vdta block and a capacitor to realize third order low-pass (lp) and band-pass (bp) filters. by making slight changes to the filter configuration, a third order sinusoidal oscillator can also be realized. thus, the aim of this work is to propose a third order filter and a dual mode third order oscillator configuration employing two vdtas and three grounded capacitors without the use of any resistors. the features of the proposed filters are that: (i) the configuration uses two active components and three grounded capacitors; (ii) the natural frequency can be tuned electronically; (iii) double/inverted input signals are not required for response realizations; (iv) the proposed filters use only grounded capacitors; (v) matching conditions are not required to realize various filter responses; (vi) the proposed filters have low active and passive sensitivities. the proposed third-order quadrature oscillator has the following advantages simultaneously: (i) like third order filter, it contains only two active components and three grounded capacitors; (ii) it provides explicit current output; (iii) it has a voltage mode and a current mode sinusoidal output; (iv) it has orthogonally and electronically tunable characteristics for the condition of oscillation (co) and the frequency of oscillation (fo); (v) it uses only grounded capacitors; (vi) it has low active and passive sensitivity. the workability of the proposed configurations is verified using the tsmc cmos 0.18 µm technology parameter as well as commercially available lm13700 integrated circuits (ics). both the theoretical and personal simulation program with integrated circuit emphasis (pspice) simulated results are depicted in the frequency response graph. the manuscript is divided into nine sections, including this one. the basic concept of the vdta block is described in section 2. section 3 presents the proposed configurations. in section 4, the non-ideality effects of vdta is described, followed by section 5 where the sensitivity analysis is described. the simulation and experimental results are thoroughly explained in section 6 and section 7, respectively. furthermore, in section 8, the comparison of the proposed work with the available literature is discussed. the manuscript is concluded in section 9. 2. basic concept of vdta vdta is a current mode abb. the circuit symbol and inner block diagram of vdta are shown in fig. 1, where p and n are the input ports and z, x+, and x− are the output ports. all ports show high impedance values [26]. in vdta, the difference between two input voltages is transferred to current at the z port by first transconductance gain (gmf). the voltage drop at the z port is transferred to current at the x port by second transconductance gain (gms). both transconductances can be controlled electronically by external bias currents. the port relations of an ideal vdta can be expressed as [8]: 263 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 00 0 00 0 0 00 0 0 0 0 p p n n z xmf mf msx z i v i v i vg g gi v = −                               (1) the complementary metal oxide semiconductor (cmos) implementation of vdta, which consists of two arbel-goldminz transconductances, is depicted in fig. 2 [30]. the two electronically tunable transconductances gmf and gms of vdta can be expressed as: 1 5( ) 2 m m mf g g g + = or 2 6( ) 2 m m mf g g g + = (2) 3 7( ) 2 m m ms g g g + = or 4 8( ) 2 m m ms g g g + = (3) the value of transconductance can be expressed as: ( ) mi bi ox i i w g i c l = µ (4) where ibi is the bias current of i-th transistor, cox is the gate-oxide capacitance per unit area, µ i is the carrier mobility for p-channel metal oxide semiconductor (pmos) or n-channel metal oxide semiconductor (nmos) transistors, w is the effective channel width, and l is the length of the i-th transistor (i = 1, 2,…, 8), respectively. fig. 2 the cmos based internal circuit construction of vdta [30] (a) symbolic representation (b) inner block diagram fig. 1 vdta [8] 3. the proposed configurations 3.1. the proposed third order filter circuit fig. 3 the proposed resistorless and electronically tunable third order filter 264 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 the proposed third order current mode and transimpedance mode filter configuration consisting of two vdta blocks and three grounded capacitors is shown in fig. 3. the routine analysis of this filter circuit yields the output currents and voltage as: 2 2 1 2 2 1 2 1 3 1 2 3 1 2 ( ) mf ms mf mf ms o o g g g g g s i i c c c c c i i d s + = − = (5) 2 1 2 1 2 1 3 1 2 3 ( ) mf mf mf o g g g s i i c c c c c v d s + = (6) where gmf1 is the first transconductance gain of vdta1, gms1 is the second transconductance gain of vdta1, gmf2 is the first transconductance gain of vdta2, gms2 is the second transconductance gain of vdta2, and d(s) can be expressed as: ( ) 3 2 1 2 1 2 1 1 2 1 1 3 1 3 2 1 2 3 mf mf mf mf ms mf mf ms g g g g g g g g d s s s s c c c c c c c c = + + + + +             (7) thus, the reported filter configuration can realize current mode (inverting and non-inverting) and transimpedance mode (non-inverting) lp and bp third order filters. eqs. (5)-(6) have two input sections that allow the designer to select the appropriate inputs for achieving filter responses. the selection of input and output terminals for realizing the current mode and transimpedance mode filter responses is shown in table 1. the performance parameters of the filters, namely, natural frequency (ω0) and quality factor (q) can be calculated according to the akerberg-mossberg approximation [25] by putting s3 = – sω2 in d(s). the calculated natural frequency and quality factor can be written as: 1 2 1 0 2 3 1 1 2 ( ) mf mf ms mf mf g g g c c g c g ω = + (8) ( ) 3 1 2 1 2 3 1 1 2 2 1 3 1 2 2 3 s1 1 2 2 ( ) [ ] mf mf ms mf mf mf mf mf m mf g g g c c g c g q g c g c g c g c c g + = + + (9) if c1 = c2 = c3 = c and gmf1 = gmf2 = gms1 = gms2 = gm, then q = 0.942 and the expression of ω0 becomes: 0 2 m g c ω = (10) table 1 selection of input and output terminals for realizing different filter functions filter responses input output (io1 or io2 or vo) i1 i2 lp1 (non-inverting current mode) 0 iin io1 lp2 (inverting current mode) 0 iin io2 lp3 (non-inverting transimpedance mode) 0 iin vo bp1 (non-inverting current mode) iin 0 io1 bp2 (inverting current mode) iin 0 io2 bp3 (non-inverting transimpedance mode) iin 0 vo 3.2. the proposed third order dual mode sinusoidal oscillator circuit by making minor modifications to the proposed third order filter configuration, a dual mode third order sinusoidal oscillator circuit which is depicted in fig. 4 can be realized. the reported oscillator circuit provides explicit current and voltage 265 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 outputs. the theoretical analysis of the oscillator circuit yields the characteristic equation as shown in eq. (11). based on eq. (11), the reported third order oscillator can generate oscillation in the case that the oscillation condition shown in eq. (12) is fulfilled. the oscillation frequency is expressed in eq. (13). fig. 4 the proposed resistorless and electronically tunable third order oscillator 3 2 1 1 1 1 2 1 1 1 2 1 2 3 0mf mf ms mf mf ms g g g g g g s s s c c c c c c + + + = (11) co: 3 1 1 2mf mf c g c g= (12) fo: 2 1 0 2 3 mf ms g g c c ω = (13) eqs. (12)-(13) confirm that co and fo can be adjusted orthogonally. for example, co can be adjusted by gmf1 without disturbing fo, and fo can be adjusted by gms1 without hampering co. both the transconductance gains, gmf1 and gms1 of the vdta, can be tuned electronically by the two bias currents ibf1 and ibs1 respectively. ibfk and ibsk are the bias currents, ibf and ibs of the k-th vdta (k = 1, 2). thus, the co and fo of the derived third order sinusoidal oscillator can be adjusted orthogonally by two bias currents ibf1 and ibs1 respectively. 4. non-ideality effects of vdta the non-ideality effects of vdta have been discussed in this section. in practice, these non-idealities are classified as tracking errors and parasitics. the non-ideality arises due to an error in the transconductance transfer function from p and n terminals to z terminals and z terminals to x terminals. the terminal relationships of vdta including tracking errors of the vdta can be rewritten as: iz = βfigmfi(vp–vn) and ix = βsigmsivz.. βfi and βsi are the tracking errors of i-th vdta [8]. in addition, like any other active device, a practical vdta shows various terminals parasitics. at all terminals, vdta has a high parasitic resistance in parallel with low valued parasitic capacitance. the parasites in the form of shunt output impedances (rp//cp), (rn//cn), (rz//cz), (rx+//cx+), and (rx–//cx–) appear at p, n, z, x+, and x− ports respectively. the non-ideal model of vdta is shown in fig. 5. fig. 5 non-ideal vdta showing its parasitic impedances [8] 266 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 4.1. non-ideal analysis of the proposed third order filter considering these parasitics in the proposed filter, fig. 3 is modified to fig. 6. the components including the influence of parasites are simplified as follows: 1 1 1 1 2e z n p c c c c c= + + + (14) 2 2 1 1e p x c c c c −= + + (15) 3 3 2 2e z n c c c c= + + (16) 1 2 1 1 || || e p n z r r r r= (17) 2 1 1 || e p x r r r −= (18) 3 2 2 || e n z r r r= (19) fig. 6 the proposed resistorless and electronically tunable third order filter with device parasitics considering the above non-ideality and parasitics, the natural frequency and quality factor are given by eq. (20) and eq. (21), respectively. ' 0 d b ω = (20) 3 ' b d q bc ad = − (21) where 1 2 3e e e a c c c= (22) ( ) 2 3 1 3 1 2 2 1 3 1 2 1 2 1 2 3 e e e e e e e f e mf f e mf e e e c c c c c c b c c g c g r r r β β= + + + +       (23) 2 2 2 1 2 1 2 1 2 1 2 1 2 3 2 3 1 3 1 1 2 2 2 1 3 1 3 1 1 3 1 1 1 2 1 2 3 ( ) f e mf f e mf f e mf e e e e e e e e e f mf f e mf s e ms e f s e mf ms e e e e e c g c g c g c c r r r r r r r c g c g c g c c g g r r r r r β β β β β β β β              = + + + + + + + + (24) 1 2 1 2 1 1 1 1 1 1 2 2 1 2 1 1 2 1 2 3 2 3 1 2 1 2 3 1 f f mf mf f s mf ms f mf f mf f f s mf mf ms e e e e e e e e e g g g g g g d g g g r r r r r r r r r β β β β β β β β β= + + + + +       (25) 267 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 it is seen from eqs. (20)-(21) that the natural frequency and quality factor have been slightly changed due to the non-ideality errors of vdta. in reality, the effect can be observed in the simulation curves where a small deviation will appear when compared to theoretical graphs. from the above expressions, it is also observed that ω0 and q are affected due to the parasitic of vdta, but it is not adverse as the values of parasitic resistances are very high in comparison to transconductance gains. furthermore, the values of parasitic capacitances are very low compared to external capacitors. as a result, ce1 = c1, ce2 = c2, and ce3 = c3. by assuming these values of capacitors and neglecting the terms which are associated with parasitic resistances, eq. (20) and eq. (21) can be approximated to the ideal value of ω0 and q. therefore, it may be concluded that, by choosing external capacitances much higher than parasitic capacitances, the output frequency response of the reported circuit would not be affected. adding some sample values of parasitic capacitors (cp1 = cp2 = cn1 = cn2 = cz1 = cz2 = cx1+ = cx2+ = cx1= cx2= cpara) and resistors (rp1 = rp2 = rn1 = rn2 = rz1 = rz2 = rx1+ = rx2+ = rx1= rx2= rpara) at all the terminals of vdta, the parasitic influence on the current mode bp filter (bp1) is shown in fig. 7. fig. 7(a) indicates that the proposed filter circuit would not be affected by up to 0.03 pf parasitic capacitances. at 10 mω parasitic resistance, a small deviation is noticeable in fig. 7(b). therefore, the performance of the proposed filter cannot be affected above the 10 mω parasitic resistance. (a) for parasitic capacitors (b) for parasitic resistors fig. 7 parasitic influence on the performance of the proposed bp1 filter 4.2. non-ideal analysis of the proposed third order sinusoidal oscillator considering the parasitics in the proposed sinusoidal oscillator, fig. 4 is modified to fig. 8. the components are simplified as follows: 1 1 1 1e z n c c c c= + + (26) 2 2 1 1 2e p x z c c c c c−= + + + (27) 3 3 1 2e x n c c c c+= + + (28) 1 1 1 || e z n r r r= (29) 2 1 1 2 || || e p x z r r r r−= (30) 3 1 2 || e x n r r r+= (31) 268 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 fig. 8 the proposed resistorless and electronically tunable third order oscillator with device parasitics using non-ideality errors and parasitic model of vdta, the characteristic equation changes to: 3 2 0s s x sy z+ + + = (32) where 1 1 1 1 1 2 2 3 3 1 1 1 f mf e e e e e e e g x c c r c r c r β = + + +       (33) 1 1 1 1 1 1 1 2 1 1 3 1 3 1 2 1 2 2 3 2 33 3 2 2 1 1 11 1 f s mf ms f mf e e e e e e e e e e e e e e ee e e e g g g y c c c c c r r c c r r c c r rc r c r β β β = + + + ++           (34) 1 2 1 1 2 1 1 1 1 1 1 1 1 2 3 1 2 3 3 2 3 1 2 3 1 1 f f s mf mf ms f s mf ms f mf e e e e e e e e e e e e g g g g g g z c c c c c c r r r r r r β β β β β β = + + +       (35) the modified co and fo are given by: co: xy z= (36) fo: ' 0 z x ω = (37) eqs. (36)-(37) show that co and fo are slightly deviated due to non-ideality errors, but as the values of non-ideality errors are very near to unity, the deviations are minute. hence, even when non-ideality errors are considered, the oscillator’s performance is close to that of the ideal. eqs. (36)-(37) also show that co and fo are affected due to the parasitics of vdta. the parasitic effect is not noticeable if the values of c1, c2, and c3 are chosen to be large compared to the parasitic capacitors. (a) for parasitic capacitors (b) for parasitic resistors fig. 9 variation of frequency considering parasitics at different terminals 269 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 the parasitic influences on the oscillator are investigated. considering some sample values of parasitic capacitors and resistors, at all the terminals of the vdta, the variation in oscillation frequency with regard to bias current is shown in fig. 9. fig. 9(a) indicates that the proposed oscillator circuit would not be affected by up to 0.01 pf parasitic capacitances. at 15 mω parasitic resistance, a small deviation is noticeable in fig. 9(b). therefore, the performance of the proposed oscillator cannot be affected above the 15 mω parasitic resistance. thus, the limitation is that the values of external capacitors should be chosen much higher than cp1, cp2, cn1, cn2, cz1, cz2, cx1+, cx2+, cx1-, and cx2to ignore the parasitic effects easily. to satisfy these conditions, the circuits may be realized using external capacitors instead of using on chip capacitors. 5. sensitivity analysis the practical solution is to design a network that has low sensitivity to element changes. thus, sensitivity must be less than the limit, i.e., unity. the lower the sensitivity of the circuit is, the less its performance deviate will be because of element changes [19]. the sensitivity of frequency (ω0) regarding circuit parameter x (say) is expressed as [31]: 0 0 0 x x s x ω ω ω ∂ = ∂ (38) 5.1. sensitivity analysis of the proposed filter using the above definition, the sensitivities of ω0 for the filter circuit with regard to active and passive components are obtained as: 0 0 0 0 0 0 0 1 2 1 1 3 1 1 2 3 1 2 3 3 1 1 2 1 2 2 2( ) 2( ) 1 2 0 mf mf mf mf mf mf mf mf ms ms g c g c g c g c g c g c g c g c g c g s s s s s s s ω ω ω ω ω ω ω + + = − = = − = = − = =            (39) it is seen from eq. (39) that all of the passive sensitivities are not more than 1/2 in magnitude. thus, it confirms that the sensitivity performance is satisfactory. 5.2. sensitivity analysis of the proposed oscillator from eq. (12), the value of gmf2 can be expressed as: 3 1 2 1 mf mf c g g c = (40) putting this value of gmf2 in eq. (13), the value of ω0 can be expressed as: 1 0 21 1mf ms g g c c ω = (41) 270 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 the sensitivities of ω0 with regard to active and passive components are derived as: 0 0 0 2 2 3 0 0 0 0 1 1 1 2 0 1 2 ms mf mf ms g g c g g c c s s s s s s s ω ω ω ω ω ω ω =   = = ==− − = =   (42) therefore, from the above equation, it can be ensured that all the sensitivities for the oscillator circuits are low and do not exceed half in magnitude, which implies attractive sensitivity performances. 6. simulation results pspice simulations are carried out to demonstrate the workability of the proposed circuits. the cmos based vdta block (shown in fig. 2) is simulated with tsmc cmos 0.18 µm technology parameter and a dc supply voltage of ±0.9 v. the aspect ratios of the transistors are taken as 3.6/0.36 for m1-m4 and 16.64/0.36 for m5-m8. 6.1. simulation results of filter for pspice simulation of the filter, the bias currents are selected as ibf1 = ibf2 = ibs1 = ibs2 = 150 µa (gmf1 = gmf2 = gms1 = gms2 = 0.623 ma/v), and the values of capacitors are selected as c1 = c2 = c3 = 10 pf. the total power consumption is about 1.08 mw. fig. 10 shows the theoretical and simulated frequency response of the current mode and the transimpedace mode filters with the appropriate selection of inputs and outputs according to table 1. figs. 10(a)-(d) depict the frequency response of current mode lp, transimpedance mode lp, current mode bp and transimpedance mode bp filters. the theoretical and simulated phase responses of these filters are shown in figs. 11(a)-(d) respectively. to illustrate the tuning property, bp1 and bp3 are chosen. by changing the bias current of vdta, the values of f0 are tuned to a particular q value (q = 0.942). for controllability of f0 value, all the transconductance gains of the vdta are set to be equal (gm = gmf1 = gmf2 = gms1 = gms2 or ib = ibf1 = ibf2 = ibs1 = ibs2) and varied to the values of 343 µa/v (ib = 50 µa), 512 µa/v (ib = 100 µa), 623 µa/v (ib = 150 µa), 704 µa/v (ib = 200 µa), 768 µa/v (ib = 250 µa), and 824 µa/v (ib = 300 µa). the graphs for bp1 and bp3 filters are shown in fig. 12(a) and fig. 12(b) respectively. (a) for current mode lp filter (b) for transimpedance mode lp filter (c) for current mode bp filter (d) for transimpedance mode bp filter fig. 10 ideal and simulated frequency responses 271 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 (a) for current mode lp filter (b) for transimpedance mode lp filter (c) for current mode bp filter (d) for transimpedance mode bp filter fig. 11 ideal and simulated phase responses (a) for bp1 filter (b) for bp3 filter fig. 12 simulated responses using different bias current the total harmonic distortion (thd) analysis is done for the bp1 filter to determine the quality of the output. the simulated thd values for the reported third order filter configuration are depicted in fig. 13. it is concluded that the output distortion is within 2.06% for sinusoidal input currents up to 60 µa (peak). the intermodulation distortion (imd) of the bp1 filter is investigated. fig. 14 depicts the dependence of the 3rd imd of bp1 response employing two nearly spaced tones f1 = 8.71 mhz and f2 = 9.11 mhz (0.2 mhz higher and lower frequencies than the center frequency of the bp filter) with the same input signal amplitude. it is observed that the 3rd imd is 6.7% for input signals of 35 µa (peak). hence, the output is of good quality and the dynamic range is large. a final point deals with the impact of the active and passive discrepancies between the filter’s frequency responses. monte-carlo analysis is conducted to collect statistical data. the bp1 filter is simulated by setting 5% tolerance for all the capacitors and also 5% variation for the dimension of the metal oxide semiconductor (mos) transistors channel length. after one hundred simulation runs, the obtained statistical histogram is shown in fig. 15. according to the simulation, f0 value of the filters is affected in the range of –5.8% to +5.4% with a mean value of 8.90689 mhz and a standard deviation of 208.175 khz. thus, it is evident from the analysis results that the proposed third order filter topology has excellent sensitivity performance. 272 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 fig. 13 variation of thd against amplitude of input current fig. 14 dependence of the third-order imd of the bp1 filter on input current fig. 15 monte-carlo analysis for the bp1 filter 6.2. simulation results of oscillator a sinusoidal third order oscillator circuit is derived by making minor modifications to the reported filter configuration. this circuit is capable of producing outputs in both voltage and current modes. the biasing currents are selected as ibf1 = ibf2 = ibs1 = ibs2 = 150 µa and the values of all capacitors are chosen at 20 pf. to get the current output, a 330 ω resistor is used at the output current node. the power dissipation is found to be 1.08 mw. fig. 16 depicts the transient analysis of voltage and current outputs. these show the rise of oscillations and later attain a stable output. the corresponding steady state outputs are shown in fig. 17. simulation results show that the oscillation frequency is 4.77 mhz, which is close to the theoretical frequency of 4.96 mhz. the deviation is 3.83%. the voltage and current output spectrums are shown in fig. 18. the thds for voltage (vo) and current output (io) are 1.51% and 1.72% respectively. fig. 19 shows the variations of thd against the amplitude of the biasing current. it is found that, for the entire current range, the thd value of the vo varies from 1.12% to 1.98%, whereas it varies from 1.34% to 2.17% for the io. fig. 20 shows the simulated dependence of the voltage and current output amplitude on bias current ibs1. fig. 20 confirms that the output voltage is almost constant for a bias current between 100 µa and 250 µa, whereas the output current is almost constant for a bias current between 50 µa and 250 µa. from eq. (13) it is seen that the frequency of oscillation can be tuned with the help of a bias current (ibs1) and a capacitor (c2) without affecting co. the variation in oscillation frequency with regard to bias current (ibs1) and capacitor (c2) are shown in fig. 21. in fig. 21(a), capacitor values are set at 20 pf and the bias current (ibs1) is varied from 10 µa to 300 µa. the variation in frequency with the capacitor c2 is obtained by changing the values of the capacitor c2 from 1 pf to 10 nf and fixing the bias currents at 150 µa. for better clarity of the graph, the variation of frequency with the value of c2 up to 100 pf is shown in fig. 21(b). the measured highest and lowest frequencies are 20.554 mhz and 219.191 khz respectively. 273 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 the robustness of the reported oscillator is checked through monte-carlo analysis with ±5% gaussian deviation on capacitors. the histogram for 100 runs is depicted in fig. 22. according to the obtained results, with a variation of fo between 3.93 mhz and 5.13 mhz, the f0 value of the oscillator are affected in the range of –10% to +17%. it illustrates that the proposed oscillator exhibits reasonable sensitivity performance. (a) for voltage (vo) (b) for current (io) fig. 16 transient response (a) for voltage (vo) (b) for current (io) fig. 17 simulated waveforms in the steady state (a) for voltage (vo) (b) for current (io) fig. 18 the simulated frequency spectrum of the output waveforms fig. 19 variation of thd (%) with ibs1 fig. 20 output amplitude versus ibs1 274 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 (a) with bias current ibs1 (b) with capacitor c2 fig. 21 frequency tuning fig. 22 histogram of the reported oscillator after monte carlo simulation 7. experimental results the simulation and experimental (using lm13700 ic) verification results for the third order filters and oscillator are studied next. though the vdta is not an off-the-shelf component, it can be implemented using commercially available ics, i.e., lm13700. the practical implementation of vdta using lm13700 ic is shown in the schematic of fig. 23. supply voltages of ±15 v and bias current 0.5 ma (gm = 9.229 ma/v) are selected for both the simulation and experimental verification. the similarity is kept to appreciate comparison between simulation and hardware results. fig. 23 vdta realization using lm13700 7.1. experimental results for third order filter for hardware implementation, metravi multiple power supply (rps3002-2), rigol function generator (dg1022), and agilent oscilloscope (350 mhz, 54641a) are used. to verify the proposed filters experimentally, the value of capacitors are selected as c1 = c2 = c3 = 10 nf. fig. 24(a) shows the schematic diagram of the realization of the proposed filter configuration of fig. 3 using discrete components, and the actual hardware arrangement is depicted in fig. 24(b). the 275 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 theoretical, simulation, and experimental (using lm13700 ic) results for the filters are shown in fig. 25. it is concluded from the figures that though small deviations are observed in the experimental result, the simulation results are close to the theoretical results. for controllability of the f0 value, all the transconductance gains of vdta are set to be equal (gm = gmf1 = gmf2 = gms1 = gms2 or ib = ibf1 = ibf2 = ibs1 = ibs2) and varied to the values of 9.229 ma/v (ib = 0.5 ma), 10.893 ma/v (ib = 0.6 ma), and 12.575 ma/v (ib = 0.7 ma). the corresponding graph for bp1 filter is depicted in fig. 26. (a) schematic diagram (b) experimental setup fig. 24 experimental arrangement for the recommended third order filters (a) for non-inverting current mode filter (b) for inverting current mode filter (c) for transimpedance mode lp/bp filter fig. 25 ideal, simulated, and experimental frequency responses fig. 26 simulated and experimental responses using different bias currents for bp1 filter 276 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 7.2. experimental results for third order oscillator for experimental verification of the proposed third order oscillator, the value of capacitors are selected as c1 = c2 = c3 = 1 nf. this choice leads to an oscillation frequency of 1.469 mhz. with these values, the condition of oscillation is satisfied. the circuits are supplied with metravi multiple power supply (rps3002-2). agilent oscilloscope (350 mhz, 54641a) is used to observe the oscillations. the schematic diagram and the experimental arrangement on veroboard for evaluating the behavior of the recommended oscillator configuration are demonstrated in fig. 27. the simulation results (using lm13700 ic) for the proposed oscillator are demonstrated in fig. 28. the 330 ω resistor load is used to convert the output current into voltage at the output current node. it is justified from fig. 28 that as claimed earlier, the proposed configuration is capable of generating voltage (vo) and current (io) waveforms. the measured oscillation frequency in fig. 28 is 1.432 mhz, which is close to the theoretical value, and the error rate is 2.5%. the experimental (using lm13700 ic) voltage and current outputs are shown in fig. 29(a) and fig. 29(b), respectively. the figure depicts that the yield frequency is 1.356 mhz, which is an error of 7.7%. in order to focus on comparative study among theoretical, simulation, and experiment values, a curve between varying values of bias current (ibs1) and frequency of oscillation is drawn and presented in fig. 30. this graph shows the deviation between frequency values obtained in all three cases for a fixed value of ibs1. (a) schematic diagram (b) experimental setup fig. 27 experimental setup for the recommended third order oscillator (a) for voltage (vo) (b) for current (io) fig. 28 simulated waveforms in the steady state using lm13700 (a) for voltage (vo) (b) for current (io) fig. 29 experimental waveforms in the steady state using lm13700 277 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 fig. 30 variations in frequency of oscillation with respect to ibs1 8. comparison with existing structures the proposed vdta based filters are compared with different third order filters and presented in table 2. third order analog filters using various types of active elements are well known to be of greater interest than second order filter, as they can be used where a sharp cut off is desired and also being useful to implement digital filters. though only the lp and bp filter responses can be realized in this configuration, the proposed filter circuit has various advantages over the previously reported third order filters. a summary of this comparison is shown below: (1) the proposed filter circuit uses two vdta blocks in contrast to the work of [10-11, 16-21, 23, 25] which require more than two active blocks. (2) in the work of [9-10, 12-16, 20, 22-24], numerous passive elements are required in contrast to the reported circuit which requires only three capacitors. (3) the proposed filter circuit realizes current mode and transimpedance mode lp and bp filters without any matching conditions in comparison to the work of [9, 11, 13, 15, 24]. (4) the proposed filter circuit requires a low supply voltage in comparison with the work of [10-14, 18, 23-25] which need a comparatively large supply voltage. (5) moreover, all the capacitors employed in the reported circuit are grounded in comparison to the work of [12-15, 24-25]. (6) additionally, the reported circuit has a tuning capability whereas the circuits in the work of [9-10, 12-17, 21-24] cannot be tuned electronically. in comparison to the above-mentioned work, the designed third order filter uses only two active devices along with all the grounded capacitors. it can be tuned electronically through the bias currents of vdta. moreover, there is no requirement for matching conditions to obtain filter responses. it is evident that all the above advantages cannot be simultaneously achieved in any of the work reported in table 2, thus justifying our design proposal. the proposed oscillator is compared with previously reported vdta based third order oscillators and presented in table 3. the third order sinusoidal oscillators offer better frequency response and low harmonic distortion than second order oscillators. a summary of this comparison is listed below: (1) the proposed oscillator does not require multiple output terminals of abbs compared to all the above vdta based reported circuits [26-29]. (2) comparatively large supply voltages are needed for the oscillator reported in the work of [26-27] compared to the proposed oscillator. (3) moreover, the proposed third order oscillator can be realized without any matching condition in comparison to the work of [26]. 278 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 table 2 comparison of the proposed filter with the previously developed third order filters ref. analog blocks used external capacitors and resistors required availability of inbuilt tuning power consumption (mw) types of responses available sensitivity/ thd technology supply voltage (v) mode of operation matching condition noise analysis experimental results [9] fig. 1 1 dbta, 1 ad844 3 (g) + 5 (3 g, 2 f) no not reported lp not reported ad844 ±12 voltage yes not reported yes [10] fig. 4(a) 8 cfta 4 (g) + 0 no not reported lp not reported 0.35 µm ±1.65 voltage no not reported yes [11] fig. 3 3 cccii 3 (g) + 0 yes 25.6 [25] bp ─/3.43% [25] 0.35 µm ±2.5 voltage yes total output noise voltage at center frequency 11.482 mhz is 5.845 nv/√hz, equivalent input noise voltage 14.782 nv/√hz. no [12] fig. 3 2 cdba 5 (1 g, 4 f) + 5(1 g, 4 f) no not reported ap ≤1/─ level-3 ±5 current no not reported no [13] fig. 9 1 cdba fig. 10 1cdba 3 (1 g, 2 f) + 4 (1 g, 3 f) 3 (1 g, 2 f) + 3 (1 g, 2 f) no not reported lp and bp − � � /─ 0.25 µm ±1.25 voltage yes no not reported no [14] fig. 4 1 cdba 4 (1 g, 3 f) + 5 (1 g, 4 f) no not reported lp ≤− � � /─ 3 µm ±5 voltage no not reported no [15] fig. 1 1 cdba, 1 cfa 3 (2 g, 1 f) + 7 (4 g, 3 f) no not reported lp ≤1/─ ad844 ±12 voltage yes not reported yes [16] fig. 4 5 cdba 3 (g) + 12 (2 g, 10 f) no 1590 [29] ap ─/0.273 [25] ad844 ±12 current no total output noise voltage at 15.9 khz frequency is 480 nv/√hz and equivalent input noise is 49.17 pa/√hz [25]. yes [17] fig. 3 3 ota 3 (g) + 0 no 0.006 lp not reported 0.18 µm ±0.5 current no not reported no [18] fig. 3 4 do-ota fig. 4 6 do-ota 3 (g) + 0 yes not reported bp ≤1/─ 0.5 µm ±2 current no not reported no [19] fig. 1 4 ota, 3 oa 0 + 0 yes not reported hp and lp ≤1/─ not reported ±10 current no not reported no [20] fig. 1 3 oa 0 + 10 (4 g, 6 f) yes not reported hp ≤1/─ lf 356n ±18 current no not reported no [21] fig. 1 3 op-ampa, 8 mosfet 3 (g) + 0 no not reported hp, lp, and bp ≤ � � /─ µa741 ±22 voltage no not reported no [22] fig. 1 2 cfa 3 (g) + 6 (5 g, 1 f) no not reported lp ≤ � �� /─ ad844 ±12 voltage no not reported yes [23] fig. 5 4 moccii 3 (g) + 4 (3 g, 1 f) no 7.54 [25] hp, lp, bp, br, and ap ≤1/1.54 [29] 0.18 µm ±1.25 current and transimpedance no total output noise voltage at 3 khz frequency is 28 nv/√hz and equivalent input noise is 14 pa/√hz [25]. no [24] fig. 4 1 otra 6 (f) + 5 (f) no 1.73 [25] hp, lp, bp, br, and ap − � � /4.5% 0.5 µm ±1.5 voltage yes total output noise voltage is 0.13 nv/√hz and equivalent input noise is 0.1253 na/√hz at 200 khz frequency [25]. no [25] fig. 3 3 cccii 3 (f) + 0 yes 56.9 hp, lp, bp, br, and ap ≤0.4/3.25 0.35 µm ±2.5 voltage no total output noise voltage at 1 mhz frequency is 3.856 nv/√hz and equivalent input noise is 4.092 nv/√hz. no this work fig. 3 2 vdta 3 (g) + 0 yes 1.08 lp and bp ≤0.5/2.06 0.18 µm ±0.9 current and transimpedance no total output noise voltage at 10 mhz frequency is 4.81 nv/√hz and equivalent input noise is 5.926 pa/√hz. yes note: g = grounded; f = floating; hp = high-pass; br = band-rejection; ap = all-pass; dbta = differential buffered and transconductance amplifier; cfta = current follower transconductance amplifier; cccii = current-controlled current conveyor; cfa = current feedback amplifier; do-ota = dual-output operational transconductance amplifier; oa = operational amplifiers; moccii = multiple output second-generation current conveyor; otra = operational transresistance amplifier. table 3 comparison of the proposed oscillator with available vdta based third order oscillators ref. number of vdta used number of resistor used number of capacitor used need of abb with multiple output terminals electronic tuning fo without disturbing co need of matching condition use of grounded capacitor technology thd/ sensitivity supply voltage (v) power consumption (mw) output type experimental results [26] 2 0 3 yes yes yes yes 0.35 µm ≤1.8/0.5 ±2 not reported both no [27] 2 0 3 yes yes no yes 0.25 µm ≤2.98%/– ±1 not reported both no [28] 2 0 3 yes yes no yes 0.18 µm ≤3.29%/– ±0.9 0.457 both yes [29] 2 0 3 yes yes no yes 0.18 µm ≤4.5%/0.5 ±0.9 not reported both yes the proposed oscillator 2 0 3 no yes no yes 0.18 µm ≤2.17%/0.5 ±0.9 1.08 both yes table 3 presents the various features of the previously reported vdta based oscillator. however, none of them can be realized without the use of additional copy terminals of vdta. the proposed oscillator is composed of two vdtas and three grounded capacitors, without requiring resistors. although the quadrature outputs are not available in the oscillator, it has a voltage mode and a current mode sinusoidal output. the co and fo of the oscillator can be tuned electronically. furthermore, no matching conditions are required. hence, the proposed circuit is strikingly superior to others compared here. 279 advancesin technology innovation, vol. 6, no. 4, 2021, pp. 262-281 9. conclusions a third order resistorless filter circuit that provides current mode and transimpedance mode lp and bp filters without any matching condition is presented in this work. by selecting the input and output terminals properly, the filter responses can be obtained without changing the circuit topology. by making minor modifications to the third order filter configuration, sinusoidal oscillator configuration can be easily realized as it has supporting advantageous features, e.g., resistorless approach, use of grounded capacitors, availability of voltage and current outputs explicitly, orthogonally and electronically tunable condition of oscillation and frequency of oscillation, etc. the pspice simulation results using 0.18 µm cmos technology and experimental results confirm the desired performance of the proposed filters and oscillator. additionally, non-ideal and sensitivity analysis is also included. the simulation results confirm that the power dissipation is 1.08 mw for both circuits, whereas thds are less than 2.06% up to 60 µa and 2.17% up to 300 µa for the filter and oscillator circuits, respectively. for the filter, the imd is less than 6.7% up to 35 µa input signals. for the oscillator, the output voltage is almost constant for a bias current between 100 µa and 250 µa, whereas the output current is almost constant for a bias current between 50 µa and 250 µa. therefore, the proposed third order filters and oscillator may bring an effective alternative to the arena of third order filter and oscillator design for researchers. acknowledgments the authors would like to express their gratitude to the fist-department of science and technology, sap-university grants commission, india for their unswerving financial support to pursue and complete this research work. conflicts of interest the authors declare no conflict of interest. references [1] m. gupta, p. dogra, and t. s. arora, “novel current mode universal filter and dual-mode quadrature oscillator using vdcc and all grounded passive elements,” australian journal of electrical and electronics engineering, vol. 16, no. 4, pp. 220-236, july 2019. 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[31] g. komanapalli, n. pandey, and r. pandey, “new realization of third order sinusoidal oscillator using single otra,” aeü—international journal of electronics and communications, vol. 93, pp. 182-190, september 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 281 microsoft word 5-v9n1(2024)-aiti#12683(50-64).docx advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 english language proofreader: chih-wei chang estimating macronutrient content of paddy soil based on near-infrared spectroscopy technology using multiple linear regression jonni firdaus1,2,*, usman ahmad3, i wayan budiastra3, i dewa made subrata3 1agricultural engineering science study program, ipb university, bogor, indonesia 2national research and innovation agency republic of indonesia, jakarta, indonesia 3department of mechanical and biosystem engineering, ipb university, bogor, indonesia received 04 august 2023; received in revised form 10 november 2023; accepted 11 november 2023 doi: https://doi.org/10.46604/aiti.2023.12683 abstract this study investigates the feasibility of employing near-infrared (nir) spectroscopy with multiple linear regression (mlr) to estimate macronutrients in paddy soil compared with partial least squares (pls) and principal component regression (pcr). seventy-nine soil samples from west java province, indonesia, are subject to conventional nutrient analysis and nir spectroscopy (1000-2500 nm). the reflectance data undergoes various pretreatment techniques, and mlr models are calibrated using the forward method to achieve correlations exceeding 0.90. the best model calibrations are selected based on high correlation coefficients, determination coefficients, rpd, and low rmse values. meanwhile, the comparison of performance mlr is made with the pls and pcr models. results indicate that simple mlr models perform less than pls for all nutrients, better than pcr for nitrogen, and below pcr for phosphorus and potassium. however, mlr reliably estimates soil nitrogen, phosphorus, and potassium content with ratio of performance to deviation (rpd) exceeding 2.0. this study demonstrates the potential of mlr for precise macronutrient estimation in paddy soil. keywords: fertility, near-infrared spectroscopy, nitrogen, phosphorus, potassium 1. introduction soil plays a crucial role in agriculture by providing the necessary nutrients for plants to grow and ultimately supporting human food availability. due to the diverse soil conditions, the practices of agricultural land management must be adapted accordingly. maintaining a consistent nutrient supply during the crop-growing phase maximizes crop productivity [1]. hence, soil health is the continuation of the soil’s capacity to function as a vital living ecosystem that supports plants and ensures all essential soil functions. one of the critical aspects of soil health is soil fertility. soil fertility is primarily determined by the presence of macronutrients such as nitrogen (n), phosphorus (p), and potassium (k), which are required in large quantities. furthermore, soil fertility parameters reflect the soil’s ability to supply plant nutrients. regular monitoring of soil nutrient levels is crucial to ensure optimal soil nutrient availability. traditional laboratory methods of soil analysis are time-consuming, costly, and risky. it often requires heedful operation for hazardous chemicals harmful to the environment, resulting in impracticability for farmers. therefore, developing accurate, environmentally friendly, time-efficient, and cost-effective soil analysis methods is imperative [2]. however, it is essential to identify various nearinfrared (nir) wavelengths that impact nutrients through straightforward multivariate models such as multiple linear regression (mlr) equations in the initial phase of creating a device that is lightweight, portable, and user-friendly. * corresponding author. e-mail address: jonni_firdaus@yahoo.com advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 51 west java is one of indonesia’s provinces with the most extensive rice fields, requiring fast soil fertility monitoring to ensure practical support for plant growth. earlier research has indicated significant variations in the accuracy of soil nutrient prediction models across different regions and soil types. consequently, studying and exploring precision and practical application effects are continuously needed, particularly concerning diverse origins and types of croplands [3]. nir spectroscopy is a promising alternative to traditional soil analysis methods. specifically, nir spectroscopy is a nondestructive chemical content detection technology that is fast and simple in sample preparation, while chemicals are not needed, conducing to an environmentally friendly solution. numerous studies have demonstrated the efficacy of nir spectroscopy in soil analysis, with its ability to rapidly and accurately predict soil nutrient contents and other soil properties. therefore, adopting nir spectroscopy as a soil analysis tool can significantly benefit farmers and facilitate sustainable agriculture practices. many studies have been conducted on nir to determine property characteristics and soil fertility [4-8]. the accuracy of deploying nir to estimate soil nitrogen was relatively high, with an r2 value of 0.75-0.95 [9-15]. research on phosphorus estimation showed a low r2 value [16], but several other studies obtained high r2 values of 0.63-0.91 [17]. meanwhile, potassium prediction obtained 0.47-0.59 for r2 value [2], and other researchers got higher r2 values standing at 0.92-0.99 [3, 18]. nitrogen prediction has been studied using foss nirsystems 5000 (foss nirsystems, inc, laurel, usa) (1100-2498 nm) and partial least squares (pls) with reflectance (r) and first derivative (d1) pretreatment in 360 samples, resulting in an r2 value of 0.77 and ratio of performance to deviation (rpd) of 2.10 [9]. the study used a fieldspec® pro sensor (analytical spectral devices inc., colorado, usa), visible-near infrared (vis-nir) range (350-2500 nm), and support vector machine (svm) with absorbance pretreatment in a total of 210 samples, resulting in an r2 value of 0.75 [11]. munawar et al. [12] employed the benchtop nir instrument thermo nicolet antaris ii (thermo fisher scientific inc, waltham, usa) range (10002500 nm), principal component regression (pcr), and pls in 40 samples, resulting in r2 values of 0.85 and 0.87, respectively. regarding rpd values, they stood at 2.00 and 3.50, respectively. pudełko and chodak [13] used the antaris ii ft-nir analyzer (thermo fisher scientific inc, waltham, usa) range (1000-2500 nm) and pcr, pls, artificial neural network (ann), principal component analysis-artificial neural network (pca-ann), pls-ann with absorbance, baseline offset (bo), d1, and d1+bo pretreatments in 90 samples, resulting in r2 values of 0.90, 0.89, 0.91, 0.93, and 0.91, respectively. reda et al. [14] used the nir portable spectrometer (1100-2500 nm) and pls with absorbance pretreatment in 400 samples, resulting in an r2 value of 0.80 and rpd of 2.77. they also employed back propagation neural network (bpnn), backward variable elimination-back propagation neural network (bve-bpnn), and ensemble learning modeling (elm) with multi scatter correction (msc) pretreatment, resulting in r2 values of 0.93, 0.90, and 0.94, while rpd values are 3.84, 3.03, and 4.91, respectively. ng et al. [16] used the neospectra module sws62221 (si-ware systems, cairo, egypt) range (1300-2600 nm) and cubist model with savitzky-golay (sg) second order polynomial and standard normal variate (snv) pretreatments in 1601 samples, resulting in r2 values of 0.52. several studies have successfully predicted soil nitrogen content using different types of nir equipment and multivariate methods, achieving r2 values ranging from 0.75 to 0.94. munawar et al. [12] used a benchtop nir instrument thermo nicolet antaris ii (thermo fisher scientific inc, waltham, usa) for phosphorus and applied pcr and pls, achieving r2 values of 0.93 and 0.99, respectively, with rpd values of 3.86 and 5.41. the neospectra module sws62221 (si-ware systems, cairo, egypt) was used with a cubist model, sg and second order polynomial, and snv pretreatment, but the r2 value was merely 0.47. it is noteworthy that phosphorus is considered one of the most challenging nutrients to predict using nir spectroscopy, as it presents in soil at low concentrations and is highly reactive with other soil minerals. thus, more research is needed to improve the accuracy of phosphorus estimation using nir spectroscopy [16]. advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 52 for potassium, munawar et al. [12] also used a benchtop nir instrument thermo nicolet antaris ii (thermo fisher scientific inc, waltham, usa) with pcr and pls multivariate methods to achieve r2 values of 0.88 and 0.90, respectively, with rpd values of 2.04 and 2.68. tang et al. [19] employed the asd agrispec spectrometer (malvern panalytical inc. boulder, colorado, usa) range (350-2500 nm) with a cubist model, sg, and second-order polynomial with 392 samples, but the r2 value merely reached 0.36. tang et al. [19] also tried using other spectrometers, such as the malvern panalytical inc. boulder (spectral evolution inc. lawrence, ma, usa) range (350-3500 nm), the neospectra module sws62221 (si-ware systems, cairo) range (1250-2500 nm), and the nirvascan asp-nir-350m-reflect (allied scientific pro., quebec, canada) range (900-1700 nm), but the r2 values were all lower than 0.40. most of these studies use various mathematical models such as pls, artificial neural networks, and machine learning, where the wavelengths used have a wide range between 400 to 2498 nm [20], 900-1700 nm [21], 350-2500 nm [22], and 3502500 nm [23], for instance. mlr is rarely used in nir spectroscopic prediction models, whereas mlr has some virtues. one of the typical virtues is providing simple interpretation where regression coefficients in mlr models represent the relative contribution of each independent variable to the dependent variable [24]. mlr is a relatively computationally simple model compared to more complex models like neural networks or deep learning, enhancing the efficiency to implement in limited computational resources. therefore, in this research, the mlr method was assessed to estimate macronutrients based on nir spectroscopy and compared with commonly used models such as pls and pcr. 2. methodology the implementation of the research commences with soil sampling, followed by the collection of nir data in the form of reflectance spectra and conventional macro-nutrient soil data. subsequently, data pretreatment was conducted on the reflectance spectra. the following steps involve the development of mlr, pls, and pcr models through calibration between nir spectra and conventional soil macro-nutrient data. once the models were constructed, performance testing was carried out to verify the effectiveness and reliability of the developed models in soil analysis. 2.1. soil sample collection table 1 soil type and parent material at the sampling location in west java province districts sub-districts number of samples dominant soil type parent material bogor jasinga 7 gleisol district, cambisol gleik clay deposits ciampea 6 regosol district, latosol haplik andesit, basalt leuwiliang 7 gleisol distrik, cambisol distrik clay deposits tenjolaya 4 district regosol, latosol haplik andesite, basalt cihoe 6 latosol haplik, podsolik haplik clay deposits ciseeng 7 gleisol district, cambisol district clay deposits rumpin 7 latosol haplik, podsolik haplik clay deposits sukabumi cikembar 7 cambisol district, andosol district andesit warungkiara 7 latosol haplik, district andosol andesit, basalt indramayu patrol 7 gleisol eutrik clay deposits anjatan 7 gleisol eutrik, gleisol vertik clay deposits subang pamanukan 7 gleisol eutrik, gleisol fluvik clay deposits source: soil type based on the national soil classification of indonesia [25-28]. a total of 79 samples of paddy soil (500 g each) at a depth of 0-20 cm were employed in this study. the samples in this study came from 4 districts in west java province, indonesia. when the soil samples were adopted, the weather varied between sunny and cloudy. soil sampling was accomplished by randomized purposive sampling based on p and k’s soil nutrient availability map [25-28]. the soil sample was situated in a sealed plastic bag and brought to the laboratory. the type of soil advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 53 and soil parent material at the sampling locations are presented in table 1. the sampling locations have dominant soil types and parent material. in general, the dominant soil types at the sampling location were gleisol, cambisol, regosol, latosol, podzolic, and andosol (based on the national soil classification of indonesia), and the main material types consisted of clay, andesite, and basalt deposits. 2.2. retrieval and pretreatment of nir spectra data the samples were dried (average moisture content 8.31%, standard deviation 1.14), cleaned of foreign material, and then sieved with a size of 0.75 mm. after sieving, the soil sample was placed in a plastic bag, and then it was mixed and shaken for 30 seconds to uniform the nutrient distribution in the soil sample. subsequently, the soil sample was inserted into the petri dish 9 cm in diameter and a height of 2 cm. before collecting the nir spectra, the soil in the petri dish was compacted by tapping until the soil surface level did not decrease any further to ensure the soil density in each petri dish was the same. next, the soil was leveled using a glass spatula to level the soil surface in a petri dish. eventually, the reflectance data was taken using the nir spectrometer nirflex n500 buchi in the 1000-2500 nm wavelength range with 1501 wavelength data. reflectance data collection for each sample was carried out in 3 replications by rotating the petri dish position by 1/3 turn to obtain 237 reflectance data. the reflectance data were transformed into absorbance (a = log (1/r)). moreover, the data were pretreated in the form of the d1, second derivative (d2), normalized, and snv using nircal software with the following formula: d1 by savitzky-golay (dg1) 4 3 2 1 1 2 4 486 ( ) 142 ( )+193 ( )+126 ( ) 126 ( ) 193 ( ) 142 ( ) 86 ( ) ( ) 188 + + + + − − − − − + − − − + ′ = i i i i i i i i i f x f x f x f x f x f x f x f x f x (1) d2 by savitzky-golay (dg2) 4 3 2 1 1 1 2 3 428 ( ) 7 ( ) 8 ( ) 17 ( ) 20 ( ) 17 ( ) 8 ( ) 7 ( ) 28 ( ) ( ) 462 + + + + − − − − + − − − − − + + ′′ = i i i i i i i i i f x f x f x f x f x f x f x f x f x f x (2) standard normal variate (snv) ( ) . ( ) − = snv x mean x x st dev x (3) normalization 0-1 (norm) min( ) max( ) min( ) − = − i norm x x x x x (4) 2.3. conventional soil nutrient data collection soil samples, for which spectral data had been collected, were analyzed for their macronutrient content using conventional methods. total nitrogen was determined using the kjeldahl method, where nitrogen compounds were oxidized in a concentrated sulfuric acid environment with a selenium mixture catalyst, forming (nh4)2so4. the subsequent ammonium content in the extract was determined using spectrophotometry with the indophenol blue color generator. total phosphorus and potassium in the soil were extracted using a wet digestion method with a mixture of concentrated hno3 and hclo4. the total phosphorus in the extract was measured using a spectrophotometer, while the total potassium in the extract was measured using atomic absorption spectrophotometry. the water content was determined by the gravimetric method. 2.4. data calibration data calibration aims to adjust the nir spectrum response to the values of macronutrient measurements, such as total nitrogen, total phosphorus, and total potassium, to provide accurate measurement results. this process involves measuring the advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 54 nir spectrum response from samples with varying concentrations of macronutrients, and this data is evaluated to create mathematical models such as mlr, pls, and pcr, (1) multiple linear regression (mlr) nir spectral data was calibrated with conventional nitrogen, phosphorus, and potassium (npk) value reading data and used the mlr model with the step-forward method in ibm spss statistics software. 150 spectra data were used as calibration data, and 87 spectra were used as validation data. in the step-forward method, the variable wavelength selection was carried out in stages where the wavelengths were entered sequentially into the model. the first wavelength variable in the equation contains the most significant partial correlation to the n, p, and k nutrient content variables. the following wavelength variable is re-selected, which gives the most significant total correlation to the npk nutrient content to be included in the equation model. the selection and addition of the wavelength variable will be stopped once the total correlation of the mlr equation model has reached > 0.90. 1 1 ( ) ( )= + + k k y a b x b x (5) where y is the estimated value of total nutrients (nitrogen, phosphorus, and potassium), a is the constant, b1 is the first wavelength variable coefficient, bk is the variable coefficient of the nth wavelength, x1 is the 1st wavelength nir spectral intensity value, and xk is the nth wavelength nir spectral intensity value. in the calibration process, the pretreatment of spectral data was considered as input data (x) for constructing an mlr model using the following models: a. input data is raw data as r b. input data is the d1 of the reflectance spectra (rdg1) c. input data is the d2 of the reflectance spectra (rdg2) d. input data is snv of reflectance spectra (rsnv) e. input data is a normalization of reflectance spectra (rnorm) f. input data is absorbance (a), which is the transformation of log (1/reflectance) g. input data d1 of the absorbance spectra (adg1) h. input data is the d2 of the absorbance spectra (adg2) i. input data is snv of absorbance spectra (asnv) j. input data was normalized from absorbance spectra (anorm) (2) partial least squares (pls) and principal component regression (pcr) the performance of mlr in predicting soil nutrients will be compared with other commonly used methods in nir spectroscopy, i.e., pls and pcr. besides, pls and pcr are multivariate calibration techniques. this algorithm uses both spectral data and reference matrices in multivariate regression. it is achieved by projecting spectral data into a reduceddimensional space. they were initially designed for high-dimensional and collinear multivariate scenarios. cross-validation was employed in both pls and pcr to determine the best number of terms latent variables (lv) for pls and principal component (pc) for pcr in the calibration model to prevent overfitting [13]. cross-validation method using 237 random samples with 20 segments. calibration process using the unscrambler software. (3) model performance assessment the best model calibrations were selected based on high correlation coefficients r, determination coefficients r2, and the ratio of performance deviation (rpd) values while minimizing root mean square error (rmse) values. the stability of the model was determined by the rpd advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 55 . = st dev rpd rmse (6) st.dev is the standard deviation of reference, and rmse is the root mean square error between prediction and measurement. rpd > 2.0 indicates accurate predictions, rpd 1.4-2.0 indicates less accurate predictions and rpd < 1.4 indicates unreliable predictions, and the model cannot be used to predict soil properties [29]. 3. results and discussion observations exhibit high variation coefficients in the diversity of macronutrient content in the soil. this variability ensures that the model built in the calibration process can represent nutrient content over a wide range to generate a high generalization value for the model. specifically, observations of soil content at sampling locations and calibration models to predict macronutrient content using nir waves are explicated further. 3.1. soil conditions at the soil sampling location the heterogeneity is desperately needed in developing soil nutrient estimation models to elicit the obtained equations having a wide and varied range of uses for soil types, parent material, and soil nutrient status as found at the sampling locations. the total nitrogen, phosphorus, and potassium of the soil samples are described in table 2. table 2 descriptive statistics of soil nutrient content in 79 samples soil nutrient content mean (g/100 g) minimum (g/100 g) maximum (g/100 g) sd (g/100 g) cv (%) total nitrogen 0.16 0.09 0.24 0.04 22.93 total phosphorus 0.07 0.01 0.36 0.07 96.34 total potassium 0.11 0.01 0.39 0.12 112.41 sd is the standard deviation, and cv is the coefficient variation. table 2 is drawn regarding the soil nutrient content in 79 samples. first, total nitrogen exhibits a relatively low variation, with a cv of 22.93%. the range between maximum and minimum is about 0.15 g/100 g. second, conversely, total phosphorus evinces a larger variation with a cv of 96.34%, signifying significant differences in phosphorus content among the soil samples with a range between maximum and minimum of about 0.35 g/100 g. eventually, the total potassium content demonstrates a high level of variation, reflected in a cv of 112.41%, with a range between a maximum and a minimum of about 0.38 g/100 g. heterogeneity in soil nutrient content values with a wide range of values is needed in building a soil nutrient estimation model using nir waves so that the resulting model can be used in a wide range of soil nutrients according to calibration data. 3.2. data calibration and validation the calibration and validation process aims to construct a model for estimating the total content of soil macronutrients based on the nir wavelength spectrum. the results of the calibration models mlr, pls, and pcr for estimating total nitrogen, total phosphorus, and total potassium using nir wavelengths will be further elaborated. (1) total nitrogen the selected mlr models for estimating total nitrogen are presented in table 3. table 3 illustrates that applying data pretreatments such as snv, normalization, d1, and snv of log(1/r) can enhance the performance of total nitrogen estimation in the soil compared to using only raw reflectance data. based on the calibration results, the best performance is observed in model 5, which employs normalization of the reflectance data, indicated by the highest values of r, r2, and rpd, followed by the smallest rmse values of 0.93, 0.86, 2.6, and 0.014 g/100 g, respectively. normalization helps eliminate scale differences among spectra affecting the mlr model. with normalization, each spectrum was transformed to have a similar standard advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 56 deviation, helping to overcome the non-linearity effects caused by large-scale variations among spectra. additionally, normalization can improve the consistency and stability of the spectrum in mlr analysis, thereby enhancing the model’s ability to capture the linear relationship between spectral data and total nitrogen. table 3 mlr model calibration and validation result for estimating total nitrogen with several pretreatment spectra data model spectra pretreatment data number of wavelengths calibration validation r r2 rmse (g/100 g) rpd rmse (g/100 g) rpd 1 r (raw data) 9 0.91 0.82 0.015 2.4 0.019 2.0 2 rdg1 5 0.90 0.81 0.016 2.3 0.019 1.9 3 rdg2 5 0.90 0.81 0.016 2.3 0.021 1.8 4 rsnv 7 0.92 0.84 0.014 2.5 0.017 2.1 5 rnorm 6 0.93 0.86 0.014 2.6 0.018 2.1 6 a 12 0.89 0.79 0.017 2.2 0.021 1.7 7 adg1 7 0.91 0.83 0.015 2.4 0.019 2.0 8 adg2 5 0.91 0.82 0.015 2.4 0.026 1.4 9 asnv 5 0.91 0.83 0.015 2.5 0.018 2.1 10 anorm 7 0.91 0.82 0.015 2.4 0.022 2.1 the best model is marked in bold, r: coefficient correlation, r2: coefficient determination, rmse: root mean square error, rpd: ratio of performance deviation. a comparison of the mlr model with pls and pcr models in estimating total nitrogen is presented in table 4. mlr demonstrates good performance on the training data with an r2 of around 0.86 but experiences a decline in performance on the validation data with an r2 of around 0.77. this decline may indicate overfitting or the absence of the model’s generalization ability. pls consistently performs well on calibration and validation data sets, with r2 values above 0.80. hence, pls might be a favorable choice, with a note to consider the optimality of the number of lv. on the other hand, pcr exhibits the lowest performance, with rdg1 providing an r-value of 0.87, r2 of 0.76, and rmse of 0.018. pcr in the validation stage shows consistent performance with r, r2, and rmse values relatively similar to those in the calibration stage. the analysis results specify that pls with rsnv outperforms the other two models with r of 0.93, r2 of 0.87, and rmse of 0.013 g/100 g. although mlr with rnorm performs well with r of 0.93 and r2 of 0.86, pls is significantly better in more accurate predictions. pcr with rdg1 shows moderate performance with r of 0.87, r2 of 0.76, and rmse of 0.018 g/100 g. table 4 comparison of mlr model with pls and pcr in predicting total nitrogen model pretreatment data calibration validation r r2 rmse (g/100 g) rpd r r2 rmse (g/100 g) rpd mlr rnorm wl 6 0.93 0.86 0.014 2.6 0.87 0.77 0.018 2.1 pls rsnv lv 11 0.93 0.87 0.013 2.8 0.92 0.84 0.014 2.5 pcr rdg1 pc 8 0.87 0.76 0.018 2.0 0.85 0.73 0.019 1.9 wl: number of wavelengths, lv: number of latent variables, pc: number of principal components, r: coefficient correlation, r2: coefficient determination, rmse: root mean square error, rpd: ratio of performance deviation. rpd is an indicator to understand the reliability of the model in predicting total nitrogen content. pls with rsnv manifests the highest rpd values, namely 2.8 in the calibration stage and 2.5 in the validation stage. a relatively high rpd indicates that the pls model’s predictions are accurate and can provide significant predictive value compared to the natural variation in the data. specifically, the high rpd in pls may be due to its ability to extract relevant information from independent variables, thus improving prediction accuracy. mlr with rnorm also shows reasonably good rpd, with values of 2.6 in the calibration and 2.1 in the validation. although not as optimal as pls, mlr still provides good prediction accuracy, especially considering its simplicity in interpretation. pcr with rdg1, while having a decent rpd value, shows lower performance compared to pls and mlr, with values of 2.0 in the calibration and 1.9 in the validation. this lower performance denotes that pcr may not be able to provide prediction accuracy as good as pls and mlr. advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 57 the research conducted by munawar et al. [12] deployed the benchtop nir instrument thermo nicolet antaris ii (thermo fisher scientific inc, waltham, usa) at 1000-2500 nm and used pcr and pls in 40 samples, resulting in r2 values of 0.85 and 0.87, respectively exhibited relatively similar performance to this study, achieving an r2 value of 0.86 in the mlr and 0.85 in pcr models, but lower than the pls model from this study. pls, through the partial component formation approach, can capture complex patterns in data and improve prediction accuracy. given such results, pls may be the primary choice for accurate predictions, while mlr remains relevant for simple model interpretation. moreover, pcr may be an alternative in significant multicollinearity issues despite the disposition of lower performance. the pls and pcr models are obtained by projecting spectral data into smaller dimensions, i.e., lv for pls and pc for pcr. however, in practical terms, it is challenging to implement this for building portable measuring devices. on the other hand, the mlr model enables the direct use of spectral data as input for the portable model to be constructed. the specified wavelengths in model 5 correlating highly with total nitrogen, are 1871, 2059, 1873, 1929, 2013, and 2082 nm (fig. 1), with a correlation coefficient of 0.93 (table 3). fig. 1 shows the normalized reflectance spectra from all soil samples in 1800-2100 nm and the contribution of each wavelength to the correlation coefficient that has been achieved. the wavelength of 1871 nm provides the highest contribution to the correlation coefficient of the mlr model (model 5), amounting to 78.2%, following 8.6% in 1929 nm. fig. 2 illustrates the calibration and validation results between actual total nitrogen and predicted total nitrogen, yielding calibration determination coefficients (r2) of 0.86, validation root mean square error (rmsev) of 0.018 g/100 g, and validation ratio of performance to deviation (rpdv) of 2.1. fig. 1 wavelength contribution to mlr model (model 5) for total nitrogen prediction fig. 2 mlr model (model 5) calibration and validation for predicted total nitrogen advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 58 (2) total phosphorus the selected mlr model for estimating total phosphorus is presented in table 5. all data pretreatment can improve the performance of phosphorus estimation compared to employing only raw reflectance data. based on the calibration results, the best performance is attained by model 5 with data pretreatment of normalization of reflectance, indicated by the highest values of r, r2, and rpd, followed by the smallest rmse values of 0.92, 0.85, 2.6, and 0.028 g/100 g, respectively in the calibration data set. similar to total nitrogen estimation, normalization in phosphorus estimation can also assist in addressing the nonlinearity effects caused by large-scale spectra variations. normalization can improve the consistency and stability of the spectrum in mlr analysis, thereby enhancing the model’s ability to capture the linear relationship between spectral data and total phosphorus. table 5 mlr model calibration and validation result for estimating total phosphorus with several pretreatment spectra data model spectra pretreatment data number of wavelengths calibration validation r r2 rmse (g/100 g) rpd rmse (g/100 g) rpd 1 r (raw data) 7 0.78 0.60 0.045 1.6 0.056 1.2 2 rdg1 13 0.91 0.82 0.030 2.3 0.056 1.2 3 rdg2 10 0.90 0.81 0.031 2.3 0.043 1.5 4 rsnv 10 0.90 0.81 0.031 2.3 0.039 1.7 5 rnorm 13 0.92 0.85 0.028 2.6 0.036 1.9 6 a 7 0.79 0.63 0.043 1.6 0.050 1.3 7 adg1 12 0.90 0.82 0.030 2.3 0.052 1.3 8 adg2 11 0.91 0.82 0.030 2.4 0.055 1.2 9 asnv 12 0.91 0.82 0.030 2.3 0.036 1.8 10 anorm 10 0.91 0.83 0.030 2.4 0.034 1.9 the best model is marked in bold, r: coefficient correlation, r2: coefficient determination, rmse: root mean square error, rpd: ratio of performance deviation. a comparison of the mlr model with pls and pcr models in estimating total phosphorus is presented in table 6. mlr used normalized data (rnorm) as a preprocessing method, resulting in a strong correlation between prediction and observation in the calibration (r = 0.92). however, in the validation, this model exhibited a significant decrease in r2 and rpd, reflecting the potential for overfitting or the absence of generalization to new data. meanwhile, pls demonstrated consistent performance improvement using the same pretreatment data as rnorm in mlr. with a higher calibration correlation (r = 0.93) and an increased r2 of 0.86, pls remained consistent and even enhanced predictions in the validation phase with a high r2 (0.83) and a relatively high rpd (2.5). these results indicate the ability of pls to provide stable and accurate predictions. employing normalization pretreatment data (anorm), pcr showed calibration results similar to mlr. however, this model experienced a slight performance decrease in the validation with an rpd of 2.4. consequently, the use of principal components as predictors may be less optimal in terms of generalization to new data. table 6 comparison mlr model with pls and pcr in predicting total phosphorus model pretreatment data calibration validation r r2 rmse (g/100 g) rpd r r2 rmse (g/100 g) rpd mlr rnorm wl 13 0.92 0.85 0.028 2.6 0.85 0.72 0.036 1.9 pls rnorm lv 11 0.93 0.86 0.026 2.6 0.91 0.83 0.028 2.5 pcr anorm pc 12 0.92 0.85 0.027 2.6 0.91 0.82 0.029 2.4 wl: number of wavelengths, lv: number of latent variables, pc: number of principal components, r: coefficient correlation, r2: coefficient determination, rmse: root mean square error, rpd: ratio of performance deviation. pls is the most effective model in predicting total phosphorus content, especially in the calibration due to the production of the highest r value (0.93), high r2 (0.86), and low rmse (0.026 g/100 g). additionally, the high rpd (2.6) indicates the superiority of pls in providing accurate and consistent predictions. despite the decent results mlr and pcr yielded, pls remains superior in most evaluation parameters. mlr and pcr perform similarly in the calibration, with r values of 0.92 and advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 59 r2 of 0.85. pls maintains higher performance in the validation, while mlr and pcr experience a decline. these results indicate that pls is a better choice for addressing the challenges of predicting total phosphorus content, especially in dealing with the complexity of relationships between variables. pls’s ability to handle multicollinearity and produce more stable predictions signifies the superiority of mlr and pcr models in the context of this research. despite the evident superiority of pls in predicting total phosphorus content, particularly during the calibration, it is noteworthy that mlr still yields commendable accuracy. both mlr and pcr demonstrate comparable performance in the calibration, with r values of 0.92 and r2 of 0.85. these metrics indicate that mlr is still a viable option concerning accuracy. moreover, it is crucial to acknowledge the practicality of mlr, especially its simplicity of use. mlr’s simplicity enables users to implement straightforwardly, being regarded as a convenient choice for applications where simplicity and quick application are prioritized. the ability to easily select specific wavelengths enhances the adaptability of mlr to portable devices, which is a factor that might be crucial in specific practical scenarios. while pls excels in addressing the complexity of relationships between variables and handling multicollinearity, mlr’s accuracy and simplicity rationalize itself in situations where computational simplicity and interpretability are paramount. fig. 3 wavelength contribution to mlr model (model 5) for total phosphorus prediction fig. 4 mlr model (model 5) calibration and validation for predicted total phosphorus the selected wavelengths in model 5, which have a high correlation with total phosphorus, are 1837, 1897, 1972, 1833, 1904, 1862, 2220, 2189, 2498, 1276, 1774, 2203, and 2144 nm (fig 3), with a correlation coefficient of 0.92 (table 5). fig. 3 shows the normalized reflectance from all soil samples in 1200–2200 nm and the contribution of each wavelength to the advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 60 correlation coefficient having been achieved. the wavelength of 1837 nm provides the highest contribution to the correlation coefficient of the mlr model (model 5), amounting to 32.6%, following 22.1% in 1972 nm and 16.7% in 1897 nm. fig. 4 illustrates the calibration and validation results between actual total phosphorus and predicted total phosphorus, yielding calibration determination coefficients (r2) of 0.85, rmsev of 0.036 g/100 g, and rpdv of 1.9. (3) total potassium the selected mlr model for estimating total potassium is depicted in table 7. all pretreatment methods applied can improve the performance of mlr in predicting total potassium compared to using raw data (reflectance) alone. based on calibration results, the d1 treatment applied to the raw data (reflectance) yielded the highest model performance regarding r, r2, and rpd, with values of 0.97, 0.94, and 4.2 g/100 g, respectively. nir spectra often contain nonlinear variations that can affect the relationship between input and output variables. the d1 can help “flatten” nonlinear changes in the spectrum, thus creating a more linear relationship between nir spectra and total potassium. the d1 in potassium estimation using mlr can enhance the model’s ability to capture linear patterns in the nir spectrum. the effect of d2 is also similar to that of d1 in reducing nonlinear effects. however, in this study, the performance of the d2 is lower than it is in the d1. this lower performance could be attributed to second-order derivatives being more sensitive to noise in the data. furthermore, noise can be accentuated during the calculation of the d2, potentially leading to overfitting, especially if the model captures noise in the training data rather than the true underlying patterns. additionally, the model may struggle to generalize to new data. second-order derivatives, while capable of highlighting peaks and valleys, might also result in the loss of certain information in the original spectra. table 7 mlr model calibration and validation result for estimating total potassium with several pretreatment spectra data model spectra pretreatment data number of wavelengths calibration validation r r2 rmse (g/100 g) rpd rmse (g/100 g) rpd 1 r (raw data) 6 0.90 0.81 0.051 2.3 0.057 2.2 2 rdg1 4 0.97 0.94 0.029 4.2 0.036 3.6 3 rdg2 4 0.97 0.93 0.031 3.8 0.037 3.4 4 rsnv 4 0.95 0.91 0.037 3.2 0.034 3.7 5 rnorm 4 0.94 0.88 0.042 2.9 0.055 2.3 6 a 4 0.90 0.82 0.051 2.3 0.055 2.3 7 adg1 4 0.96 0.93 0.032 3.7 0.035 3.8 8 adg2 4 0.96 0.92 0.034 3.5 0.050 2.6 9 asnv 4 0.95 0.91 0.036 3.3 0.034 3.6 10 anorm 4 0.93 0.87 0.044 2.7 0.063 2.0 the best model is written in bold, r: coefficient correlation, r2: coefficient determination, rmse: root mean square error, rpd: ratio of performance deviation. a comparison of the mlr model with pls and pcr models in estimating total phosphorus is depicted in table 8. the mlr model, with the d1, demonstrates excellent performance in the calibration with an r2 value of 0.94 and a r of 0.97. besides, the rmse value of 0.029 g/100 g and rpd value of 4.2 indicate significant prediction accuracy. however, in the validation, this model experiences a slight decrease in performance with r² at 0.92 and r at 0.96. meanwhile, with absorbance (log 1/r), the pls model exhibits higher performance in calibration and validation. this model achieves high accuracy with r² values of 0.95 and 0.97 and r at 0.98 in the calibration. the low rmse value (0.026 g/100 g) and high rpd (4.7) affirm the reliability of the pls model’s predictions. on the other hand, the pcr model, with the normalization of absorbance, demonstrates performance comparable to mlr. with r² at 0.94 in the calibration and 0.93 in the validation, this model provides good predictions. although slightly lower than pls, pcr yields a low rmse value (0.029 g/100 g) and a sufficiently high rpd (3.9). advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 61 table 8 comparison mlr model with pls and pcr in predicting total potassium model pretreatment data calibration validation r r2 rmse (g/100 g) rpd r r2 rmse (g/100 g) rpd mlr rdg1 wl 0.97 0.94 0.029 4.2 0.96 0.92 0.036 3.6 1.9 pls a lv 0.98 0.95 0.026 4.7 0.97 0.95 0.028 4.3 2.5 pcr anorm pc 0.97 0.94 0.029 4.1 0.97 0.93 0.031 3.9 2.4 wl: number of wavelengths, lv: number of latent variables, pc: number of principal components, r: coefficient correlation, r2: coefficient determination, rmse: root mean square error, rpd: ratio of performance deviation. in the calibration, the pls model r value of 0.98 is higher than mlr (0.97) and pcr (0.97). this result denotes that pls can better elaborate the training data’s relationship between input variables and total potassium. regarding the r2 calibration, pls also excels with a score of 0.95, while mlr and pcr have values of 0.94 and 0.941, respectively. therefore, pls can better capture the variation in the calibration data. furthermore, the root mean square error (rmse) during calibration, pls, has the lowest rmse value (0.026 g/100 g), and therein lies the lower prediction error of this model compared to mlr (0.029 g/100 g) and pcr (0.029 g/100 g). in the validation stage, the results are also noteworthy. pls maintains good performance with an r2 value of 0.95, whereas mlr and pcr show a slight decrease in performance with values of 0.92 and 0.933, respectively. regarding the rpd values in validation, both pls (4.3) and mlr (3.6) experience a decline from the calibration rpd values, but pls remains superior. overall, the pls model stands out in its predictive ability, both in the calibration and validation, with high correlation, good r2, and low prediction error. while mlr and pcr also provide good results, pls might be more optimal for predicting total potassium thereon. fig. 5 wavelength contribution to mlr model (model 2) for total potassium prediction from d1 reflectance spectra fig. 6 mlr model (model 2) calibration and validation for predicted total potassium advances in technology innovation, vol. 9, no. 1, 2024, pp. 50-64 62 the selected wavelengths in model 2, which correlate highly with total potassium, are 1413, 1919, 2352, and 2172 nm (fig. 5), with a correlation coefficient of 0.97 (table 7). fig. 5 describes the d1 of reflectance from all soil samples in 1400– 2400 nm and the contribution of each wavelength to the correlation coefficient that has been achieved. the wavelength of 1413 nm provides the highest contribution to the correlation coefficient of the mlr model (model 5), amounting to 88.0%. fig. 6 illustrates the calibration and validation results between actual total potassium and predicted total potassium, yielding calibration r2 of 0.94, rmsev of 0.036 g/100 g, and rpdv of 3.6. 4. conclusion estimating nitrogen, phosphorus, and potassium content in paddy soil using nir at 1000-2500 nm and the mlr model evinced lower performance than pls for all nutrients but better than pcr for nitrogen, and it was below pcr for phosphorus and potassium. however, mlr is well-performed owing to achieving a high rpd > 2.0 in the best model for each nutrient. the study using simple mlr induces different pretreatment data and the number of wavelengths in soil nitrogen, phosphorus, and potassium. (1) nitrogen: the highest performance was achieved by normalization of reflectance in pretreatment data with six wavelengths as variables, giving results with r, r2, rmse, and rpd values of 0.93, 0.86, 0.014 g/100 g, and 2.6, respectively. (2) phosphorus: the highest performance was achieved by normalization of reflectance in pretreatment data with thirteen wavelengths as variables, giving results with r, r2, rmse, and rpd values of about 0.92, 0.85, 0.028 g/100 g, and 2.6, respectively. (3) potassium: the highest performance achieved by the d1 of reflectance in pretreatment data with four wavelengths as a variable, giving results with r, r2, rmse, and rpd values is about 0.97, 0.94, 0.029 g/100 g, and 4.6, respectively. this research shows that all selected models provide statistically excellent correlation values (r > 0.80) for all soil nutrients. likewise, the selected model provides an accurate level of prediction (rpd ≥ 2.0) for all soil nutrient estimation models using nir spectra, except the validation of the pcr model for nitrogen estimation and the mlr model for phosphorus estimation indicating less accurate prediction (rpd < 2.0). acknowledgments this research was funded by the ministry of education and culture of the republic of indonesia through a doctoral dissertation research program (contract no. 082/e5/pg.02.00.pt/2022, year 2022). conflicts of interest the authors declare no conflict of interest. references [1] m. a. munnaf and a. m. mouazen, “development of a soil fertility index using on-line vis-nir spectroscopy,” computers and electronics in agriculture, vol. 188, article no. 106341, september 2021. 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[29] b. miloš, a. bensa, and b. japundžić-palenkić, “evaluation of vis-nir preprocessing combined with pls regression for estimation soil organic carbon, cation exchange capacity and clay from eastern croatia,” geoderma regional, vol. 30, article no. e00558, september 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 1___aiti#9396___77-91 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 a novel ultrasonic method for measuring the position and velocity of moving objects in 3d space natee thong-un, wongsakorn wongsaroj* department of instrumentation and electronics engineering, king mongkut’s university of technology north bangkok, bangkok, thailand received 05 january 2022; received in revised form 27 january 2022; accepted 05 february 2022 doi: https://doi.org/10.46604/aiti.2022.9396 abstract this study proposes a method for concurrently determining the position and velocity of a moving object in three-dimensional (3d) space using echolocation. a spherical object, i.e., a flying ball, is used to demonstrate the ability of the proposed method. the position of the object is calculated using a time-of-flight (tof) technique based on a cross-correlation function, which requires less computational time when using one-bit signal technology. the velocity of the object is subsequently computed from the length of chirp signals and the velocity vector measurements between the position of the object and the position of acoustical receivers. the coordinate of the object location is identified by the distance from the sound source to the object, the elevation angle, and the azimuth angle. the validity and repeatability of the experimental results are evaluated by statistical methods, showing ±1% of accuracy. it is concluded that the proposed method can identify the position and velocity of a rigid body in 3d space. keywords: chirp signal, echolocation, one-bit signal, position, velocity 1. introduction bats and dolphins have a remarkable ability to generate an image of the world from acoustic data or called ultrasound, while almost all other animals produce the image from visual information. they can transmit sound pulse trains and identify targets by using echolocation [1]. in engineering measurement, there are many applications of the ultrasonic technique applied such as fluid engineering [2], non-destructive testing [3], and so on. to determine the distance, time-of-flight (tof) methods are proposed to provide the time interval between the emitted sound and received echo. tof methods can be used in a variety of applications [4-7]. there are many studies on acoustic systems for position measurement [8-13]. the target position is identified by the tof computation between the transmitter and the receiver of sound. however, this determination of position does not consider the effects of velocity. presently, the most advanced devices for robots use a laser rangefinder and a vision finder. however, these devices still have disadvantages when compared with ultrasonic airborne systems [14]. for instance, the vision system’s main disadvantage is the time-consuming computational methods and the high expense of the system [15]. the localization techniques using ultrasonic methods are inexpensive alternatives as suitable ultrasonic transducers can be produced for as little as usd 10 [9]. moreover, ultrasonic ranging systems can be applied in electromagnetically shielded environments where gpss cannot be used. * corresponding author. e-mail address: wongsakorn.w@eng.kmutnb.ac.th tel.: +66-2-5552000; fax: +668-4-2356417 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 pulse compression signals for ultrasonic methods are an ingenious solution for dealing with the practical problem in ultrasonic tof measurement because they provide a high level of accuracy [16-17]. in general, a linear-frequency-modulated (lfm) signal can be utilized for tof computation by using the maximum peak time in the cross-correlation function of the received signal as the reference signal. however, if the lfm signal is heavily modulated by the doppler effect, it is unsuitable for measuring moving objects. the problem is that cross-correlation cannot completely be achieved between the transmitted signal and the received signal. to overcome this problem, a linear-period-modulated (lpm) signal, which is a pulse compression signal, has been presented [18-19]. although these methods can satisfy the doppler effect, they require a lengthy period of computational time because of the use of the envelop-signal calculation. accordingly, a low-computation-cost method for ultrasonic distance measurement has been proposed by applying two cycles of pulse compression to lpm signals and compensating for the doppler-shifted [20-21]. signal processing-based one-bit stream is the powerful technique of digital decoder for super audio cd (sacd) with direct stream digital (dsd) technology. this processing allows an sacd to achieve its unprecedented audio quality, thus allowing it to reproduce audio better than several digital or analog technologies [22]. in addition, the cross-correlation process of pulse compression signals for tof computation relies on one-bit signal processing technology [23]. this process is proposed for the accuracy and the resolution of ultrasonic distance measurement as well as hugely reducing the number of multiplications and accumulations of the one-bit signal. two-dimensional (2d) and three-dimensional (3d) airborne ultrasonic systems using one-bit signal processing have been developed [24, 9], respectively. unfortunately, the 3d airborne ultrasonic system for one-bit signal processing has a limitation in that it supports only mobile robots with a 90° scanning area and does not include the velocity measurements [25-26]. in a recent development, for instance, lazarov et al. [27] proposed the design and implementation of the ultrasonic positioning system based on new multifunctional hardware components to visualize the 3d distance of moving objects. however, the measurement technique cannot obtain the object’s velocity. to address these critical issues, a direction-of-arrival (doa) technique is interesting because it essentially concerns the direction of the signal source in 3d positioning, either in the form of an electromagnetic or acoustic wave, when impinging on the sensor array [28]. also, the object velocity can be estimated by utilizing the technique. accordingly, the determination of the direction of the echo from an object position using a doa technique is not complicated, and it can cover a range of ±180° in both the elevation and azimuth angles. this study proposes a 3d ultrasonic airborne system for concurrently measuring a moving object’s position and velocity. the proposed system can compute the position with the accuracy of a doa technique. the velocity measurement relies on the projection of 3d vector measurements. this system operates using a one-bit signal processing technique with a low computation cost [29] of a field-programmable gate arrow (fpga). the repeatability of measurements is measured by the average and the standard deviation from 50 experiments. in the study, the principle of cross-correlation and doppler compensation via one-bit signal processing is explained in section 2. the model of 3d position and velocity measurements is represented in section 3. then, in section 4, the measurement results of the proposed system are illustrated and evaluated. lastly, the conclusion is summarized in section 5. 2. cross-correlation and doppler compensation via one-bit signal processing 2.1. cross-correlation using one-bit signal processing in the proposed system, the cross-correlation function, which uses one-bit signal processing, consists of the recursive cross-correlation with one-bit signals and the smoothing operation with a finite impulse response (fir) low-pass filter, as illustrated in fig. 1. a pair of lpm signals is driven by the sound source. the echo sensed in each microphone is changed into a one-bit stream x(m) with a delta-sigma modulation. a reference lpm signal is converted into a reference lpm one-bit signal s(k) by a digital comparator. the cross-correlation function c(m) is defined as [29]: 78 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 1 1 ( ) ( ) ( ) m k c m s m k x m k − − = − ⋅ −∑ (1) the cross-correlation operation of eq. (1) requires a huge number, m, of multiplication and summation of one-bit signals. then, the difference in the cross-correlation operation, c(m) – c(m–1), is described as [29]: 1 1 ( ) ( 1) ( ) ( ) (1) ( ) [ ( ) ( 1)] ( ) m k c m c m s m x m s x m m s m k s m k x m k − − − − ⋅ − ⋅ − + − − − + ⋅ −= ∑ (2) the s(1) and s(m) have values 1 and -1, respectively, owing to s(k) being the lpm signal transformed to be a one-bit signal. in addition, s(k) has hundreds of zero cross points zk. there is the same difference in values, either 1 or -1, between any two consecutive zero-cross points zk and zk+1 in s(k). hence, the values of s(m – k) – s(m – k + 1) can be expressed as [29]: k l l zkm zkm zkm kmskms ≠−⋅⋅⋅ =−⋅⋅⋅− =−⋅⋅⋅ =+−−− − ,0 ,2 ,2 )1()( 2 12 (3) where l is a natural number. the computation of the recursive cross-correlation operation, which is performed by summating the difference in the cross-correlation operation, is expressed as [29]: 1 2 3( ) ( 1) ( ) 2 ( ) 2 ( ) 2 ( ) ( )c m c m x m m x m m z x m m z x m m z x m= − − − + ⋅ − + − ⋅ − + + ⋅ − + − ⋅ ⋅ ⋅ − (4) the computation cost of the recursive cross-correlation operation arises from the integration and summation of the one-bit samples. the number of summation zk+2 depends on the number of zero-cross points in the lpm signal. therefore, the computational costs are constant and independent from the altering of sampling frequency. thus, the recursive cross-correlation operation of one-bit signals can reduce the computational costs of cross-correlation. moreover, to improve the signal-to-noise ratio (snr) of c(m), the moving average filter performed in the smoothing operation is required to minimize the high-frequency noise in c(m). finally, the tof can be expressed in terms of the peaks of the cross-correlation. fig. 1 proposed three-dimensional position and velocity measurement by one-bit signal processing [29] 2.2. doppler-shift compensation of time-of-flight (tof) the tof of a pair of lpm signals is usually estimated from the time point of the maximum peak in c(m). however, considering the case of a moving object, the doppler effect on the waveform of the modulated cross-correlation function is caused by the phase shift of the received lpm signal, as illustrated in fig. 2. the maximum peak value in the modulated cross-correlation function does not show the tof of the received lpm signal. therefore, the peak time in the envelope of the cross-correlation function te is obtained to estimate the tof of the received lpm signal. 79 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 fig. 2 modulated cross-correlation envelope of the lpm signal to identify the tof due to the cross-correlation, the peak time in the envelope of the cross-correlation function can still be compensated by the maximum peak pmax and the minimum peak pmin, the time at the maximum tmax and minimum tmin, and the doppler velocity measurements. the doppler velocity measurements are required to adjust the length of the modulated lpm signal to account for doppler effects. the cross-correlation function between the pair of doppler-shift lpm signals and the single reference lpm signal in fig. 1 has two peaks. thus, the interval containing the first maximum peak and the one containing the second maximum peak in the modulated cross-correlation function displays the doppler-shift length of the single lpm signal. the doppler-shift length of the reference lpm signal is expressed as [20]: 0l vv vv l d d d ⋅ + −= (5) where ld represents the doppler-shift length of the received lpm signal, l0 is the reference lpm signal length, vd stands for the doppler velocity, and v is the propagation velocity of a sound wave in the air. the original lpm signal f(t) is defined as [20]: 0 0 0 0( ) sin 2 ln 2 lns s b b b b l p l l p l f t t p p p p                   ⋅ ⋅= π ⋅ + − π ⋅ (6) where pb is the period of the lpm signal and ps is the starting time of the sweeping period. in the work of hirata et al. [20], the compensated peak time can be estimated from the maximum and minimum peak times and the doppler velocity coefficient ξ. for the doppler velocity in eq. (7), the compensated peak time is expressed as eq. (8) [20]: 0 0 1 ( 1) ( 1) b bp p l l l l dv e v v e ⋅ ⋅ + − < < − (7) 02 ln (2 1)d b d v vl l p v v         −ξ = − ⋅ − + + (8) max minξ (1 ξ)et t t= ⋅ + − ⋅ (9) where te is the compensated peak time and l is an integer. the tof of the received lpm signal is estimated as [20]: 0tof sd e d b v p l t v v p ⋅= − ⋅ + (10) 2.3. direction-of-arrival (doa) doa has been an active method of finding direction for a long time. typically, the doa techniques have been found in the application of radar, sonar, and surveillance. they are available for air traffic control and target searching involving the 80 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 air-plane industry for converting the location of the transmitter and signal interception. more recently, doa has played a vital role in mobile radio communications in identifying the multipath of radio channels. doa is the method based on beamforming in determining the origin of the signal moving to receivers. there are various doa estimation algorithms such as the algorithms of multiple signal classification (music) and estimation of signal parameters via rotation invariance technique (esprit). fig. 3 pictures a pattern of an array with m elements placed in space. the plane wavefront has a frequency and arrives at an angle ɵ and φ with respect to the z-axis and x-axis, respectively. doa provides a peak of spectra to match the angle direction come from an original of plane wavefront [28]. this study uses doa to locate an obstacle. fig. 3 basic concept of doa 3. proposed model for three-dimensional position and velocity measurements 3.1. three-dimensional position measurements in fig. 4(a), the proposed system can detect the object using ranging measurements in an area from –x to +x and from –z to +z. the object is presented in the face of the loudspeaker in +y direction. four acoustical sensors or microphones are located on both the x and the z axes, and their own positions are (+m, 0, 0), (–m, 0, 0), (0, 0, +n), and (0, 0, –n). the object is supposed to have an unknown position as represented by the point (x, y, z). (a) positioning in z-axis (b) positioning in x-y plane fig. 4 three-dimensional positioning method firstly, fig. 4(a) illustrates the object position which is represented in terms of the x-y plane and z-axis, where d is the distance from the loudspeaker to the object, θ is the elevation angle on the x-y plane, and 2n represents the distance between microphones 3 and 4. the object is decided to be whether in +z or –z direction by evaluating tof3 and tof4, which are the tof as determined by microphones 3 and 4, respectively. if tof4 is more than tof3, the object is in the +z direction; otherwise, the object is in the –z direction. it is supposed that d is much longer than 2n (i.e., d >> 2n), which can be deduced from the first triangle secant [30] into the curve in fig. 4(a). the triangle secant consists of two known sides: the length 2n and the length equal to the difference of the tof between the microphones 3 and 4 multiplied by the speed of the sound propagation v. with the definition of doa, the elevation angle (θ) can be calculated as [31]: 81 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 1 4 3(tof tof ) sin 2 v n − −θ = (11) secondly, d is computed by looking back to fig. 3(a) again. an obtuse triangle with vertex points is created at mic.4, the speaker, and the target object. thus, d4 can be computed as: 2 2 2 4 2 cos(90 )d d n nd °= + − +θ (12) when d4 = v·tof4 – d, it is substituted back into eq. (12). d can be obtained. 2 2 4 4 ( tof ) 2 tof 2 cos(90 ) v n d v n − − ° = + θ (13) conversely, if tof4 is less than tof3, the object occurs in the –z direction. θ is computed in eq. (11), but d is different from that expressed in eqs. (12) and (13). it can instead be expressed as: 2 2 2 3 2 cos(90 )d d n nd+ − °= + θ (14) 2 2 3 3 ( tof ) 2 tof 2 cos(90 ) v n d v n − − ° = + θ (15) now, the parameters z from d and θ are determined, that is, z = dsinθ. next, the unknown parameters x and y in fig. 4(b) are considered. the total distance is between the sound source and the object, then to microphone 1, equals d + d1 = v·tof1. the parameters x, y, and z can be related as: 2 2 2 2 2 1 12 ( tof) 2 tofy x z mx v vd d= − − − − + (16) consider microphone 2, where d + d2 = v·tof2, eq. (17) is obtained similarly to eq. (16): 2 2 2 2 2 2 22 ( tof ) 2 tofy x z mx v vd d= − − − − + (17) using eqs. (16) and (17), the x and y parameters can be solved. lastly, a transform from the cartesian coordinate system to the spherical coordinate system is utilized to obtain the angle of azimuth (ϕ). 2 2 2 1 1 2 2 12 (tof tof ) (tof tof ) cos 4 sin vd v dm − − + +ϕ = α (18) 3.2. three-dimensional velocity vector measurements the velocity of the moving object can be measured from the signal length of the echo, which is reflected from the target. the signal length difference is proportional to the velocity of the object. the length of the received lpm signal is linearly decreased or increased due to the doppler effect. the doppler velocity at each microphone, which is a relative velocity measurement, can be expressed in eq. (5). it is assumed that the microphone vectors are the directions in which the microphones measure the relative velocity from the moving object, as illustrated in fig. 3. these vectors can be computed with the coordinates of the instantaneous object position and the microphone position. if the unknown velocity vector of the moving object u = [ux, uy, uz] t is projected onto the microphone vectors, the result of the projection is the relative velocity measured by the microphones. thus, the velocity of the moving object can be estimated using the measurements from the relative velocity of each microphone, the instantaneous object position of the moving object, and the microphone positions. the relative-doppler velocity measurements vd = [vd1, vd2, vd3, vd4] t of microphones 1, 2, 3 and 4 are used, respectively. the projection of the unknown vector u on a microphone vector is: 82 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 t d v u q= ⋅ (19) where 1 2 3 4 1 2 3 4 t p p p p p p p p q          = (20) it is assumed that a point (x, y, z) is the instantaneous position of the moving object when the wave is incident on the surface of the object. the microphone vectors p1 = –[x – n, y, z]t , p2 = –[x + n, y, z]t, p3 = –[x, y, z – m]t, and p4 = –[x, y, z + m]t have a magnitude of the form ‖�‖ = ����. now, the proposed system has four equations and only three unknown variables. in general, v can be projected onto the column space of a four-by-three matrix. therefore, u can be estimated by the linear-least-squares approach [32]. 1( )t t d u h h h wv−= (21) where ( )x n y z p p p yx n z p p p yx z m p p p yx z m p p p h                                 + + = 1 1 1 2 2 2 3 3 3 4 4 4 (22) and 1 1 1 1 1 1 1 11 4 1 1 1 1 1 1 1 1 w              = (23) h is an observation matrix, and w is a weighted averaging matrix. 4. evaluation and results for proposed system 4.1. experimental setup the experimental setup for the 3d position and velocity measurements is pictured in fig. 5. in this experiment, the frequency of the transmitted lpm signal sweeps from 50 khz to 20 khz. the length of the transmitted lpm signal is 3.274 ms. a pair of lpm signals are generated from a function generator at 4 vp-p and enlarged by an amplifier with a factor of 10. a loudspeaker emits the lpm signal to the spherical object with a 10 cm diameter. the echoed signals are derived by the four acoustical receivers made from silicon mems. this model can sense sound pressure or particle velocity in all directions (i.e., it is omnidirectional) [9, 33-34]. the allowed frequencies range from 10 khz to 100 khz. as such, the sensor is embedded into a signal processing board with a low-pass frequency circuit with a 60 khz frequency cutoff and a preamplifier of 20 db. the minimum sensitivity level of the sensor is -47 db when the humidity does not exceed 70 r.h. the distance between the pioneer pt-r4 loudspeaker and the microphones is 10 cm on the x-axis. on the other hand, the distance to the microphones on the z-axis is 11 cm. 83 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 fig. 5 experimental setup for three-dimensional ultrasonic position and velocity measurements the velocity of the ultrasonic wave propagated in the air is approximately 345 m/s in the temperature range between 20 and 25°c and a humidity of 50 r.h. the signals derived by the acoustical receivers are transformed into one-bit signals by an ad7720 delta-sigma modulator. the sampling frequency of the delta-sigma modulator is 12.5 mhz. the length of the weighted moving average filter for smoothing the cross-correlation function is 141 taps. the cross-correlation function for one-bit signal processing is programmed into a cyclone v 5cgxfc5c6f27c7 fpga board. the specifications of logic utilization for the one-bit cross-correlation function programmed into the fpga board are 2602 logic elements, 5777 total registers, 175,948 bits of total block memory, and 10 total pins. the moving object is driven by a sigma koki sgma46-300 motorized stage, which can drive a moving object in only the +y and –y direction with maximum and minimum velocities within ±0.4 m/s; the velocities could be adjusted in ±0.1 m/s per step. the resolution of the proposed system is approximately 14 µm when a sampling rate is set at 12.5 mhz, with the speed of sound supposed to be 345 m/s. 4.2. experimental results the distance to the object is repeated continuously in 50 experiments. the probability distributions of the estimated position at the various velocities are illustrated in figs. 6-9. the first position is located using sound beam radiation of the speaker at a fixed position. the range of sound radiation is ±10° in the vertical direction and ±45° in the horizontal direction [33]. the first position is at distance (d) = 96 cm, elevation angle (θ) = 5°, and azimuth angle (ϕ) = 78°. the probability function for the first position is shown in fig. 6. the mean value and standard deviations of the distribution are shown in fig. 10. averages for the distance, the elevation angle, and the azimuth angle in the first position are 95.7 cm, 4.2°, and 77.3°, respectively. the maximum standard deviations for the distance, the elevation angle, and the azimuth angle in the first position are 0.037 cm, 0.412°, and 0.392°, respectively. for the second position, the tested object is still in the same xy quadrant as the first position, but the object is shifted to a positive direction in the +z direction. the object is now outside the range of the main sound beam radiation of the speaker. the sound beam, in this case, has a weaker intensity than the previous case. for the second position, d = 78 cm, θ = 18°, and ϕ = 70°. the probability function for the second position is shown in fig. 7, and average and standard deviations are shown in fig. 11. averages of the distance, the elevation angle, and the azimuth angle for the second position are 76.6 cm, 20.5°, and 72.1°, respectively. the maximum standard deviations of the distance, the elevation angle, and the azimuth angle for the second position are 0.0472 cm, 0.515°, and 0.507°, respectively. the object position in the third case is assumed to move to the right-hand side of the speaker in the –z direction. this position also belongs outside of the main sound beam. the third position is d = 65 cm, θ = -18°, and ϕ = 130°. the probability function for the third position is depicted in fig. 8, and the averages and standard deviations are shown in fig. 12. the averages of the distance, the elevation angle, and the azimuth angle for the third position were 67.3 cm, -19.7°, and 130.4°, respectively. the maximum standard deviations of the distance, the elevation angle, and the azimuth angle for the third position are 0.043 cm, 0.765°, and 0.439°, respectively. finally, the fourth position is d = 91 cm, θ = 10°, and ϕ = 124°. the probability function for the fourth position is depicted in 84 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 fig. 9, and the averages and standard deviations are shown in fig. 13. averages of the distance, the elevation angle, and the azimuth angle for the fourth position are 93.4 cm, 12.4°, and 121.9°, respectively. the maximum standard deviations of the distance, the elevation angle, and the azimuth angle for the fourth position are 0.033 cm, 0.377°, and 0.547°, respectively. the object employed in the experiments is a rigid body, but it is assumed that the object is a point for the proposed method. the surface of the object on which the sound is incident is estimated as the measurement point because the exact reference point at the center of the rigid body cannot be known. the exact reference point is unpredictable on the rigid body. for this reason, deviations between the reference point and the measurement point are observed. therefore, measurement fluctuations are dependent on the direction of the sound beam propagation from the sound source to the target and the object’s shape. from the experimental results for the four object positions, it is noticed that the distance (d) has the relatively smallest variance when compared with the elevation angle (θ) and the azimuth angle (ϕ). the reason is that the computations from tofs for the θ and ϕ parameters are more sensitive than those for the d parameter. for the case when the tested object is outside the main sound beam, the range of measurements can be expanded by altering the position of the speaker. the sound beam is shifted up +10° and down -10° from the z-axis by manually lifting the loudspeaker position, as illustrated in fig. 14. the variance of these conditions is not different from the case when the object is inside the main sound beam. in addition, when the velocity of the moving object is increased, a greater variance of position measurements is produced. this is likely due to vibrations in the moving object because the motorized stage for driving the object is controlled by an automatic system for repeated evaluations. for the velocity measurements, the velocity of the moving object measured by four microphones is estimated using 3d velocity vector measurements. the velocity estimation is composed of x, y, and z components, which are represented by vx, vy, and vz. in the experiment, the moving object can be controlled by a motorized stage, which can move only along the y-axis. therefore, a reference velocity is set up only for the vy component, and vx and vz are assumed to be zero. the velocity measurement results for the first position are shown in fig. 15. the vy velocity component for the first case agrees with the reference. the vx and vz velocity components for the first case are between -0.1 to 0.1 m/s and -0.04 to 0.04 m/s, respectively. the velocity measurement results for the second case are shown in fig. 16. the vy velocity component for the second case is smaller than the reference by about ±0.05 m/s for the higher velocity. the vx and vz velocity components for the second case are between -0.11 to 0.11 m/s and -0.15 to 0.15 m/s, respectively. the velocity measurement results for the third case are shown in fig. 17. the vy velocity component for the third case is smaller than the reference by about ±0.02 m/s for the higher velocity. the vx and vz velocity components for the third case are between -0.02 to 0.02 m/s and -0.08 to 0.08 m/s, respectively. finally, the velocity measurement results for the fourth case are shown in fig. 18. the vy velocity component for the fourth case is smaller than the reference by about ±0.04 m/s at the higher velocity. the vx and vz velocity components for the fourth case are between -0.04 to 0.04 m/s and -0.02 to 0.02 m/s, respectively. it is noticed that the proposed 3d velocity vector measurement has a less accurate vy component when the moving object is elevated higher from the x-y plane, and the vx and vz components are not complete zero due to the doppler velocity estimation from the doppler-shift length measurements of the received lpm signals at acoustical receivers, as the receivers could not sense the same length of the obtained lpm signal at the same velocity. (a) distance (b) azimuth angle (c) elevation angle fig. 6 experimental results of the determined position at d = 96 cm, ϕ = 78°, and θ = 5° when varying the velocity 85 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 (a) distance (b) azimuth angle (c) elevation angle fig. 7 experimental results of the determined position at d = 78 cm, ϕ = 70°, and θ = 18° when varying the velocity (a) distance (b) azimuth angle (c) elevation angle fig. 8 experimental results of the determined position at d = 65 cm, ϕ = 130°, and θ = 22° when varying the velocity (a) distance (b) azimuth angle (c) elevation angle fig. 9 experimental results of the determined position at d = 91 cm, ϕ = 124°, and θ = 10° when varying the velocity (a) distance (b) azimuth angle (c) elevation angle fig. 10 averages and standard deviations of the determined position at d = 96 cm, ϕ = 78°, and θ = 5° at various velocities (a) distance (b) azimuth angle (c) elevation angle fig. 11 averages and standard deviations of the determined position at d = 78 cm, ϕ = 70°, and θ = 18° at various velocities 86 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 (a) distance (b) azimuth angle (c) elevation angle fig. 12 averages and standard deviations of the determined position at d = 65 cm, ϕ = 130°, and θ = -22° at various velocities (a) distance (b) azimuth angle (c) elevation angle fig. 13 averages and standard deviations of the determined position at d =91 cm, ϕ = 124°, and θ = 10° at various velocities fig. 14 sound beam scanning by rotating the speaker (a) x-component (b) y-component (c) z-component fig. 15 vector velocity measurements at d =91 cm, ϕ = 124°, and θ = 10° 87 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 (a) x-component (b) y-component (c) z-component fig. 16 vector velocity measurements at d =76 cm, ϕ = 18°, and θ = 70° (a) x-component (b) y-component (c) z-component fig. 17 vector velocity measurements at d =65 cm, ϕ = -22°, and θ = 130° (a) x-component fig. 18 vector velocity measurements at d =91 cm, ϕ = 10°, and θ = 124° 88 advances in technology innovation, vol. 7, no. 2, 2022, pp. 77-91 (b) y-component (c) z-component fig. 18 vector velocity measurements at d =91 cm, ϕ = 10°, and θ = 124° (continued) 5. conclusions this study demonstrated the measurement of 3d position and velocity utilizing an oversampling-based signal processing method with an lpm ultrasonic signal. the proposed system consists of a cross-correlation using a one-bit signal processing technique with a low computational time cost. the velocity measurements were computed based on the 3d velocity vector measurements. the object’s position was calculated using spherical coordinates. positions determined in the proposed system were evaluated by experimental demonstration. the object position can be sensed by the sound beam propagated by a loudspeaker. the probability distributions for 50 trials assessed the accuracy of the developed method for position measurements. the mean value and standard deviations were used to determine the reliability of the measurements. the resolution of the proposed system was approximately 14 µm for a sound velocity of 345 m/s and a sampling rate of 12.5 mhz. the deviation of the actual results is for a point, but the target was a spherical ball. the reference of the object position was fixed to the center on the surface of the ball. the velocity estimation was made up of components in the x, y, and z directions. in this experiment, the moving object can be forced in only y-direction movement due to the limitation of the experimental apparatus. however, the technique is still able to estimate the position and velocity of the moving object in 3d space. the validity and repeatability of the experimental results are evaluated by statistical methods, showing ±1% of accuracy. abbreviations and symbols doa direction-of-arrival pb period of the lpm signal dsd direct stream digital pmax maximum peak fir finite impulse response pmin minimum peak fpga field-programmable gate arrow ps starting time of the sweeping period lfm linear-frequency-modulated s reference lpm one-bit signal lpm linear-period-modulated te compensated peak time sacd super audio cd tmax time at maximum peak snr signal-to-noise ratio tmin time at minimum peak tof time-of-flight u velocity vector of the moving object 3d three-dimensional v propagation velocity of a sound wave in the air c cross-correlation function vd doppler velocity d distance from the loudspeaker to the object vd relative-doppler velocity measurements f original lpm signal x echo signal in one-bit stream h observation matrix w weighted averaging l natural number z zero cross point ld doppler-shift length of the received lpm signal 2n distance between microphones 3 and 4 l0 reference lpm signal length ξ doppler velocity coefficient m huge number θ elevation angle p microphone vector ϕ angle of azimuth 89 advances in technology innovation, vol. 7, 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[34] k. mizutani, t. ito, m. sugimoto, and h. hashizume, “tsat-music: a novel algorithm for rapid and accurate ultrasonic 3d localization,” eurasip journal on advances in signal processing, vol. 2011, 101, november 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 91 microsoft word 3-v9n1(2024)-aiti#12000(28-41).docx advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 english language proofreader: chih-wen teng selection of elevation models for flood inundation map generation in small urban stream: case study of anyang stream chanjin jeong, dong-hyun kim, hyung-ju yoo, seung-oh lee* department of civil environmental engineering, hongik university, seoul, korea received 15 april 2023; received in revised form 20 november 2023; accepted 21 november 2023 doi: https://doi.org/10.46604/aiti.2023.12000 abstract to reduce flood damages, the ministry of environment in korea has provided a flood inundation map so that people can expediently identify flood-prone areas. however, the current flood inundation maps have been produced based on the dem which makes it difficult to represent realistic situations due to the lack of reproduction of land surface conditions. this study aims to provide more accurate and detailed flood inundation maps for flooding events due to river overflow in small urban areas. in this study, flood inundation analysis is performed using the river analysis system, hec-ras 2d, with the dsm and the dem of urban areas in the anyang stream basin, korea to examine the differences in terms of terrain data and flooded area. finally, for urban areas with dense buildings and congested road networks, the flood inundation analysis based on dsm can represent a more realistic flood situation and create an appropriate flood inundation map. keywords: urban flood inundation map, hec-ras 2d, dsm, dem, terrain data 1. introduction because of recent global climate change, damages due to droughts, floods, and typhoons have been increasing. this is because the energy cycle within the earth is disrupted by global warming, causing greater differences in rainfall between regions. according to the world meteorological organization (wmo), climate-related disasters have caused 115 deaths per day on average over the past 50 years (1970-2019), and the number of disasters has increased fivefold during that period [1]. the intergovernmental panel on climate change’s (ipcc) 6th assessment report predicts that regional variations in precipitation will continue to worsen due to climate change, and larger-scale floods will occur in the future [2]. as climate change worsens, defending against flood damage through structural measures is only a temporary solution [3]. therefore, it is necessary to establish flexible flood defense measures that can adapt to the increasing extreme rainfall caused by climate change. as one of these measures, the city of seoul identifies areas vulnerable to flooding by understanding the characteristics of the watershed and provides a flood inundation map that indicates areas expected to be flooded during extreme rainfall events. a flood inundation map is a map created by predicting areas that are likely to be flooded in advance to prevent human and property damage caused by floods due to extreme rainfall or levee break. including korea, many countries have produced a flood inundation map by predicting and analyzing the area and depth of flooding to effectively prevent flood damage. a flood inundation map should provide extensive information to mitigate flood damage and enable prompt preventive measures such as rapid evacuation of residents. they should also include basic data that can be effectively utilized for flood management [4]. ∗ corresponding author. e-mail address: seungoh.lee@hongik.ac.kr advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 29 however, the current flood inundation map only provides the expected flood range and depth, so the use of flood inundation maps is quite limited. it is difficult to obtain specific information because the expected flood range and depth are also provided quite roughly. in addition, using a digital elevation model (dem) that does not consider facilities for flood analysis can lead to significant errors in densely populated urban areas [5]. there is a limit to citizens’ active use of the current flood map because there may be significant errors. to achieve the actual purpose of production, which is flood control measures, it is necessary to develop a flood map. lee and ha [6] simulated urban flooding using the us epa stormwater management model (swmm), hereafter referred to as xp-swmm 2d. they analyzed changes in flood characteristics based on the presence or absence of buildings in the terrain data and argued that the reliability of the dem decreases with the presence of buildings. the urban flooding in their study occurred due to poor drainage rather than river overflow. lee et al. [7] also conducted flood simulations using hec-ras and developed flood inundation maps for a smaller area. nevertheless, like the previous study, they interpolated the terrain construction using cross-sectional profiles of rivers, which resulted in flood maps that did not consider buildings on the land surface. similarly, salunke and thube [8] simulated flooding in the krishna basin, covering a large area of 55,537.60 km2. they constructed terrain data with a resolution of 30 × 30 m using cross-sectional profiles of rivers and performed simulations using hec-ras. due to the large-scale nature of the study area, the resolution of the terrain data had limitations, making it challenging to derive detailed results. in this study, urban flooding due to river overflow in small urban areas is simulated. unlike previous flood simulations in large areas, a suitable approach for small areas is adopted and more detailed results could be provided. hec-ras is used, and urban flooding was simulated due to river overflow, not poor drainage. therefore, the purpose of this study is to produce a flood inundation map with a wider range of applications than current ones. for flood analysis in urban areas, hec-ras 2d, a two-dimensional numerical model, was selected, and the terrain data used for flood analysis was divided into dem and digital surface model (dsm). the study analyzes variations in flood analysis outcomes attributed to disparities in terrain data and emphasizes the need for a flood inundation map that utilizes a dsm. 2. methodology the flowchart of this study is presented in fig. 1. first, vulnerable areas to river flooding are selected by referring to the current flood inundation map. secondly, a dsm is created using terrain data of the target area. considering that the target area is a small-scale region, drone-based photogrammetry is performed as an economical and rapid method. next, using hec-hms, scenarios of extreme rainfall are constructed according to frequency through hydrological analysis of the watershed, and flood inundation analysis is performed using hec-ras 2d with a focus on river flooding. conducted a validation of the hec-ras 2d model through a comparison with the flood inundation maps using the flumen model provided by the ministry of environment. fig. 1 flowchart for generating a flood inundation map 3. study area for this study, a small urban area within the anyang stream watershed in seoul is selected as the target region. according to the river master plan [14], anyang stream is the first tributary of the han river, with a watershed area of 283.75 km2, a river length of 20.70 km, and a stream length of 33.33 km, based on the anyang stream estuary. the shape of advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 30 the watershed is dendritic and is located between 126°52'37" to 126°54'54" east longitude and 37°24'35" to 37°33'14" north latitude. due to the geographical characteristics of the anyang stream watershed located in the seoul metropolitan area, most of the lower parts of the watershed are urban areas, and various factories and public facilities are scattered throughout the watershed. as shown in fig. 2, the target area includes the stream and floodplain from ogum bridge to gochuk bridge in the anyang stream watershed. although it is a small area with a length of 1km and an area of 0.4 km2, it is characterized by a high concentration of industrial facilities and residential areas. currently, it is legally restricted to take pictures using drones for personal reasons in korea. therefore, when performing flood simulation, this study only targeted small areas that could show the difference between dem and dsm. according to the current flood inundation map, the area is predicted to be flooded with a depth of more than 2 m in the event of a flood, requiring a prompt response from residents. (a) flood inundation map (b) satellite image [9] fig. 2 flood inundation in the study area [9] 4. terrain survey a flood inundation map is used to identify areas that are likely to be flooded during a given flood event. this map is typically created using hydraulic models that simulate water flow based on terrain data. that is why terrain data plays a crucial role in accurate flood analysis. the terrain data used for flood analysis can be broadly divided into two types: dem and dsm. fig. 3 shows the difference between dsm and dem [10]. (a) satellite image (b) dem image [10] (c) dsm image [10] fig. 3 comparison of dem and dsm the dem is terrain data indicating the height of the ground surface by excluding height information of buildings or vegetation. while the dsm can provide detailed information about the height and location of all objects on the earth’s surface, including buildings and vegetation, but may not accurately represent the actual ground level. the dsm can lead to an overestimation of flood depth and extent because it contains information not only on buildings but also on objects that advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 31 interfere with flood analysis. for this reason, dem is currently preferred over dsm for flood inundation mapping. however, with the recent development of surveying technology, dsm construction technology using lidar or drone technology has been developed. this can economically generate higher quality and accurate topographic data than before [11], so it is necessary to review flooding analysis based on dsm. 4.1. drone and camera properties in this study, the dji mini 2 drone is utilized for aerial photography to facilitate the application of photogrammetric techniques. the mini 2 drone, manufactured by dji, is known for its lightweight design, weighing only 249 g, which enhances its ease of use during fieldwork. its camera supports up to 4k resolution, allowing for high-resolution photo capture and providing the foundational data for accurate terrain modeling. the detailed specifications of the drone and camera are provided in table 1. the drone has an automatic flight mode that can be controlled using a smartphone, making it possible to plan and execute systematic flight paths, adjust flight speed and altitude, and set shooting overlaps [12]. table 1 drone and camera specification classification contents drone size 245 × 289 × 56 mm weight 249 g battery 2250 mah flight time 31 minutes flying speed 16 m/s camera focal length 4.7 mm sensor 1/2.3” cmos data format jpeg, dng image size 4000 × 3000 fov 83° 4.2. photogrammetry (a) satellite (b) dsm (c) post-process of dsm fig. 4 dsm of the study area in this study, a drone-based photogrammetric method is selected to construct a dsm for a small urban area. drones enable rapid and accurate collection of geospatial information in small areas, but using lightweight drones for aerial photography can result in increased instability due to wind. to maintain high precision of terrain data, images are captured with approximately 70% vertical and horizontal overlap at a low altitude [12]. this required a large number of photos, and a line of interest advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 32 total of 1415 images are captured. high-resolution photos were then used to generate a 2 m resolution dsm using bentley’s context capture software. a comparison of the dsm with satellite imagery of the target river shows that the features identified in the satellite imagery were similar to those in the dsm. (a) dsm with vegetation (b) dsm with vegetation removed fig. 5 cross-section of the line of interest (loi) the results of constructing a dsm through photogrammetry revealed the presence of vegetation information that could act as an error factor in flood analysis. in the case of flood analysis, vegetation information can have an inaccurate impact on water flow. therefore, vegetation data were removed using filtering. additionally, in photogrammetry, the height of the channel is inaccurate due to light reflection and the flow of water in the river. thus, the river’s channel in the dsm was adjusted, along with cross-sections based on actual measurements. as shown in the cross-sectional view in figs. 4 to 5, unnecessary information for flood analysis was removed. since the dsm includes information on all objects above the surface, post-processing to modify terrain information is essential. 4.3. conversion dsm to dem the method of converting dsm to dem is to remove the information about obstacles, such as buildings, from the dsm. the study utilized the building information of the target region to filter out and eliminate the building information. subsequently, a smoothing process was executed to develop a more precise dem. the result is shown in fig. 6. (a) dsm (b) dem fig. 6 conversion of dsm to dem advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 33 5. hec-hms model hec-hms is a hydrologic modeling software developed by the u.s. army corps of engineers hydrologic engineering center (hec). the software simulates and analyzes the hydrologic response of watersheds to various precipitation. hechms allows users to define the physical characteristics of a watershed, including land use, soil types, and topography, and to specify various precipitation inputs, such as rain or snowfall. the software uses this information to calculate the resulting hydrographs, which can be used to analyze the behavior of streams, rivers, and other bodies of water [13]. table 2 basin characteristic of anyang stream, korea river area (km2) time of concentration (hr) storage coefficient (hr) curve number anyang stream 211.25 4.47 3.78 87.9 in this study, the probability of rainfall maximum precipitation is calculated using rainfall data from seoul and suwon weather observation stations until 2021, considering the study area. the flood discharge is calculated using clark’s unit hydrograph method. clark’s unit hydrograph method can synthesize a unit hydrograph using the time of concentration and the storage coefficient of the watershed, and its consistency and objectivity have been proven. in addition, the watershed characteristics that must be entered in the hec-hms, such as area, curve number, and concentration time as shown in table 2, are referenced in the river master plan [14]. all hydrograph scenarios used are constructed through frequency analysis in hec-hms. through hec-hms, four flow hydrographs, as shown in fig. 7, are being derived. the peak flow gradually increases from the 50-year frequency rainfall to the 500-year frequency rainfall, and the peak flow for each scenario increases from 1735 m3/s to 2423 m3/s. fig. 7 flow hydrograph scenarios for various return periods 6. hec-ras 2d model hec-ras 2d is a hydraulic model developed by the u.s. army corps of engineers and is an extended system of the hec-2 model that analyzes the water surface curve. hec-ras 2d is open-source software and is widely used for hydraulic modeling because it is a program that does not require a license. the hec-ras 2d model can simulate the effects of the sediment transport model, water temperature model, bridge excavation calculation, and hydraulic structure on both steady and unsteady flows. in addition, it can analyze and express the effects of flooding of floodplains and levees in two dimensions. this study performed a two-dimensional simulation using hec-ras 2d, and it can calculate the flood depth, water surface elevation, and velocity using multiple polygonal grids. 6.1. governing equations in hec-ras 2d hec-ras 2d can efficiently and stably perform two-dimensional simulations using either the saint-venant equations or the diffusion wave equations. the time step for running the model is determined by the formula associated with the saintvenant equation (full momentum), ensuring quick and stable simulations [15]: advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 34 1.0 ( max 3.0) ∆ = ≤ = ∆ v t c with a c x (1) 2.0 ( max 5.0) ∆ = ≤ = ∆ v t c with a c x (2) where c is the courant number, v is flood wave celerity, ∆� is the computational time step and ∆� is the average cell size. in the case of simulating 2d unsteady flow, the calculation is performed according to the equations of mass conservation: ( ) ( )∂ ∂ ∂ + + = ∂ ∂ ∂ h hu hv q t x y (3) and momentum conservation: 2 2 , , 2 2 + τ τ ρ ρ        ∂∂ ∂ ∂ ∂ ∂ + + − = − + + − ∂ ∂ ∂ ∂ ∂ ∂ b x s xs c t zu u u v u u v f v g v t x y x r hx y (4) 2 2 , , 2 2 + τ τ ρ ρ        ∂∂ ∂ ∂ ∂ ∂ + + − = − + + − ∂ ∂ ∂ ∂ ∂ ∂ b y s ys c t zv u v v v v v f u g v t x y y r hx y (5) where t is time, u is the velocity component in the x-direction, v is the velocity component in the y-direction, �� is water surface elevation, h is the water depth, q is a source/sink flux term, �� is the coriolis parameter, g is gravitational acceleration, � is horizontal eddy velocity, � is bottom shear stress, � is the surface wind stress, and r is the hydraulic radius. 6.2. model validation in this paper, numerical modeling using hec-ras was conducted, encompassing both channel and interior floodplain. to verify the reliability of the hec-ras model employed in the study, validation processes are conducted separately for the channel and interior floodplain, thereby demonstrating the suitability of the hec-ras model. (1) channel to verify the hec-ras 2d model for the channel, a comparison is performed with the water surface elevation observed in the study area. the water surface elevation data of june 15, 2009, at three points between ogum bridge and gochuk bridge presented in the anyang river master plan [14] were compared with the water surface elevation data calculated by the hec-ras 2d simulation. as shown in table 3, the water surface elevation observed at three stations was compared with the water surface elevation calculated by the hec-ras 2d model, and the average error was about 2.5%. table 3 error of water surface elevation calculated by hec-ras 2d station observed (m) hec-ras 2d (m) error (%) 6 + 239 4.12 4.23 2.67 6 + 487 4.19 4.31 2.86 6 + 733 4.32 4.41 2.03 (2) interior floodplain the ministry of environment provides the public with a flood inundation map calculated by flumen, and in this study, it could be used as verification data for the hec-ras 2d model. since there is no actual flood area in the study area, it had to be compared with the flood inundation map calculated by flumen, a two-dimensional hydraulic model. in this study, the two-dimensional hydraulic model is verified by calculating the goodness of fit [16] between the flood area shown advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 35 in the flood inundation map and the flood area calculated by hec-ras 2d. to apply the same conditions as the flood inundation map, the dsm is edited into dem. in addition, the levee break scenario is applied, and the 100-year frequency flood is input as the boundary condition of the model. 2 2 (%) 100− − = × ∩ ∪ flumen hec ras d flumen hec ras d a a fit a a (6) where � ��%�is the model goodness of fit percentage, ������� is the flood area shown in the flood inundation map, and �������� ! is flood area calculated by hec-ras 2d. to analyze the goodness of fit, each flood area is calculated based on the 2.0 m to 5.0 m area of the flood inundation map. the flood area (������� ) shown in the flood inundation map was 0.079 km2, and the flood area (�������� ! ) calculated by hec-ras 2d was 0.091 km2. each area is shown in fig. 8. when the two areas are compared, it was confirmed that the spatial distribution of the flood area showed a similar shape. as a result of these results, a fit of about 70% could be obtained by applying eq. (6). (a) ������� (b) �������� ! (c) ������� ∩ �������� ! (d) ������� ∪ �������� ! fig. 8 model validation between flumen and hec-ras 2d using dem 6.3. parameters for simulation table 4 numerical modeling parameters in hec-ras 2d flow area 0.4 km2 ∆$, ∆% size 2 m × 2 m grid number total: 91594 manning’s n values channel: 0.027 floodplain: 0.030 interior floodplain: 0.020 boundary condition upstream: flow hydrograph (scenario) downstream: normal depth (1/2369) interior floodplain: outflow computation time step 1 second the flood area is calculated from gochuk bridge (upstream) to ogeum bridge (downstream), including the right interior floodplain. to obtain stable simulation results, parameters such as grid size and calculation time are set to ensure that the courant number did not exceed 2. the grid size is set to an average of 2 m and the time step was set to 1 second. the manning’s n values are input based on the river master plan [14]. the boundary conditions consisted of flow hydrograph upstream, normal depth downstream, and outflow at the land boundary conditions. table 4 provides detailed variables for the hec-ras 2d simulation. advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 36 7. results the results obtained from the numerical model hec-ras in this study are as follows: the outcomes of the hec-ras model allowed for an intuitive and quantitative understanding of the difference between dem and dsm. after analyzing the simulation results based on two terrain data, an economic feasibility study was conducted. 7.1. hec-ras 2d results and analysis by terrain data when simulating rainfall scenarios of 50-year, 100-year, and 200-year frequency using hec-ras 2d for flood analysis, no flooding occurred up to the interior floodplain. however, when simulating the rainfall scenario of 500-year frequency, the river overflowed and caused flooding up to the project boundary. in the 500-year frequency rainfall scenario, flooding began in the project boundary and reached its maximum depth within two hours. the following figs. 9-11 show the results obtained using dem and dsm, respectively, in the 500-year rainfall frequency scenario. the difference in simulation results based on dem and dsm can be seen from the figs. 9-11. dem, which is based on terrain data without considering structures, could not accurately predict the exact depth and velocity for each location. however, dsm, which considers the flow between buildings, could express the effect of buildings on flooding. the water surface elevation calculated from the dem-based flood analysis was 13.35 m, while that from the dsm-based analysis was 14.48 m. a difference of over 1.0 m in flood level was observed, which was due to the occupancy area of the buildings. based on the current analysis, buildings are not shown as inundation areas on the map. it means that the flood depth is not higher than the buildings, and if the flood depth becomes higher than the buildings, the area where the buildings are located will also appear as an inundation area. (a) result based on dem (b) result based on dsm fig. 9 results of depth in 500-year frequency rainfall scenario (a) cross-section of flood inundation map using dem (b) cross-section of flood inundation map using dsm fig. 10 cross section of the line of interest line of interest advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 37 (a) result based on dem (b) result based on dsm fig. 11 results of velocity in 500-year frequency rainfall scenario the velocity showed a higher value when based on dsm, but it cannot be considered accurate and detailed as it does not consider the influence of buildings. however, in the dsm-based results, the velocity near the buildings is higher than in other areas. as depicted in fig. 12, variations in velocity were observed to be different based on building density (the proportion of the total area of a section occupied by buildings) when comparing the velocities obtained from dem and those obtained from dsm. when buildings occupied approximately 25% of the area, a difference of around 30% in velocity was noted compared to dem. conversely, in areas where buildings covered approximately 60% of the region, a velocity difference of approximately 60% was observed. (a) building density by section (b) difference in velocity between dem and dsm according to building density (�∗ ' �()*+,*-. �/0 1+⁄ ) fig. 12 difference in velocity on roads based on building density in different sections generally, an increase in velocity is observed in proportion to the extent of building coverage. this phenomenon is particularly pronounced in densely populated urban areas, where the differences between velocities in dem and dsm are substantial. therefore, it is advisable to consider an increase in velocity corresponding to building density when interpreting velocity results obtained from dem. advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 38 7.2. korean-flood risk assessment model [17] korean-flood risk management (k-frm) is an assessment technique that quantitatively presents flood risk applied in korea. these results present variations in flood risk assessment when using flood inundation maps derived from both dsm and dem terrain data. currently, flood risk assessment has been conducted using flood inundation maps created from dem terrain data. however, by utilizing flood inundation maps based on dsm terrain data, the results of flood risk assessment exhibit significant differences. economic losses from natural disasters are the financial impact of unforeseen disasters from an economic point of view, and these losses require several steps: risk analysis for disaster guidance, asset list for disaster space distribution and scale, damage function definition, and eventually loss quantification. k-frm considers various types of flood damage, including building damage, vehicle damage, agricultural damage, human casualties, and public facilities damage, which are tailored to specific conditions in south korea and may vary depending on region and type of disaster. the k-frm follows a scheme as shown in the following figure. fig. 13 flood damage analysis framework in k-frm [17] following the k-frm methodology, flood damage amounts are determined based on flood inundation maps. therefore, in this study, flood damage in the research area is assessed using flood inundation maps generated from dsm. the results reveal that the flood damage amount based on dem is approximately 24% higher than that calculated using dsm. this suggests the potential risk of overestimating flood damage when utilizing dem terrain data, thereby providing a rationale for employing it in the creation of flood inundation maps. table 5 difference in flood damage assessment amount between dem and dsm (unit: usd 1,000) terrain data vehicle life victim crops farmland sum dem 12,175.66 95.55 56.44 0.45 2.81 12330.91 dsm 9944.35 85.86 51.12 0.45 2.80 9944.35 7.3. flood inundation map a flood inundation map is created using the results of flood analysis based on dsm. the flood inundation map shows a clear difference from the current flood inundation map based on the dem. in addition, by conducting hec-ras 2d simulations, flood depths, flood extent, and velocities over time can be derived. therefore, it is possible to predict the flood situation in the flood inundation map over time. it can be observed that the flood progresses from both ends to the center. as shown in figs. 14-15, it can be seen that it takes only one hour from the start of flooding until the entire area is completely inundated. when fully inundated, the depth of flooding exceeds 4 m, and the velocity is close to 0.5 m/s. an important point to note is that the flood depth and velocity have different values depending on the distribution. u.s. advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 39 department of the interior [18] provided details of the classification of the hazard ratio. under this classification, if the depth of the flood is more than 1.5 m and the flow rate is more than 0.5 m/s, it belongs to the high-danger zone, and it is assumed that lives are in jeopardy. in the scenario of this study, the area to be studied belongs to the high-danger zone, and residents need to respond in advance from flooding. (a) 24 hours later (b) 24 hours and 15 minutes later (c) 25 hours later fig. 14 flood inundation map for depth and extent of flooding by duration (a) 24 hours later (b) 24 hours and 15 minutes later (c) 25 hours later fig. 15 flood inundation map for the velocity of flooding by duration 8. conclusion in this study, differences in flood inundation analysis results for urban areas based on dem and dsm using the hecras 2d model were confirmed through hydraulic and economic feasibility analysis. conducting flood inundation analysis by removing all building information in a continuously developing city would no longer be considered a meaningful endeavor. unlike the current flood inundation map calculated with dem, the flood inundation map generated with dsm provides additional information such as velocities and paths for sequential time steps. the most significant distinction between flood inundation maps based on dem and dsm lies in the realism of the flood inundation map. since dsm represents terrain information that closely resembles the actual topography compared to dem, conducting flood analysis based on dsm enables us to create a more realistic flood inundation map. accurate flood inundation analysis using dem data in densely urbanized areas with numerous buildings and infrastructure is challenging. as seoul, korea, advances in technology innovation, vol. 9, no. 1, 2024, pp. 28-41 40 continues to experience rapid urbanization and expansion, employing dsm for flood inundation analysis may be a suitable approach for detailed evacuation and defense planning. furthermore, this study used its findings to calculate flood damage, advocating that the creation of flood inundation maps using dsm is appropriate. the assertion is not solely based on the differences in direct information, such as depth and velocity, between flood inundation maps generated from dsm and dem. instead, it stems from the evaluation of the suitability of dsm for producing flood inundation maps from the perspective of flood damage estimation. in this study, the simulation of river flooding was focused on the small-scale urban area. however, to simulate larger areas encompassing inland regions, both river flooding and inland inundation analysis should be conducted. moreover, the need for inland inundation analysis is increasing due to frequent incidents of inland flooding, often attributed to urban drainage systems being unable to handle recent extreme rainfall events. in the future, it will be essential to create more accurate flood inundation maps using dsms that simultaneously consider both river inundation and inland flooding in urban areas. acknowledgment this research was supported by a grant (2022-mois61-005 (rs-2022-nd634032)) for the development of risk prediction technology for storms and floods for climate change based on artificial intelligence, funded by the ministry of interior and safety (mois, korea) conflicts of interest the authors declare no conflict of interest. references [1] world meteorological organization (wmo), wmo bulletin, vol. 71, no. 1, switzerland: wmo, 2022. 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(in korean) [18] d. j. trieste and u. s. bureau of reclamation, “downstream hazard classification guidelines,” denver: u.s. department of the interior bureau of reclamation, 1988. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 4-v8n2(2023)-aiti#9854(121-135).docx advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 building information modeling in the architecture and construction industry jerome jordan faz famadico* department of civil engineering, adamson university, manila, philippines received 14 april 2022; received in revised form 19 october 2022; accepted 22 october 2022 doi: https://doi.org/10.46604/aiti.2023.9854 abstract this study aims to investigate the benefits, risks, barriers, and approaches of building information modeling (bim) implementation in the architecture, engineering and construction (aec) industries. descriptive research methods such as surveys and key informant interviews are used to gather data. respondents in the survey come from different aec companies and are selected with a purposive sampling method. descriptive statistics and one-way analysis of variance (anova) are utilized to analyze the data. the narrative analysis method is also performed to validate the research findings through a desk review of secondary data. the result shows that the major benefit of bim is earlier and more accurate design visualization, while the main risk is accountability and control of data entry into the model. moreover, the major barrier to bim implementation is the high acquisition cost, and the most recommended approach is to increase the availability of bim technology. keywords: building information modeling, digitized construction, bim technology, aec industry, bim framework 1. introduction the construction industry is considered one of the most complex and fragmented industries. its management processes are known to be complicated since uncertainties and risks are mostly inevitable in any construction project [1]. according to leeds’ research [2], construction companies confront many challenges in the productivity, profitability, labor, performance, and sustainability of their projects. most of these companies experience a profit reduction and low productivity due to several factors, such as delays in project completion and changes in the design and construction schedules. in addition, inconsistency in generating information also increases the difficulty of project planning, resulting in misinterpretation of plans and misunderstanding among project stakeholders. increasing productivity and efficiency has been the primary goal in the architecture, engineering, and construction (aec) sector. likewise, contractors and designers find ways to eliminate errors, omissions, and changes in project plans as well as designs while managing a vast amount of building information throughout the project life cycle. information management is one of the best approaches to achieving these goals [3]. however, due to a lack of information technology (it) adoption and utilization, information management needs to be improved in the aec sector in developing countries like the philippines. although it is currently being applied in the construction project life cycle, its usage is partial and isolated. it does not support collaboration and coordination between different systems and disciplines. however, over the past three decades, the construction sector has experienced considerable advancements in using information technology to improve design and construction operations [4]. the most promising development during this period is building information modeling (bim) [5]. * corresponding author. e-mail address: jerome.jordan.famadico@adamson.edu.ph advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 122 bim is a state-of-the-art technology steadily making its way into various aec industry operations. it comprises the process of creating and application of a computer-generated model to replicate and simulate a facility’s planning, design, building, and operation [6]. bim models are now changing how buildings and infrastructures work. bim has recently attracted increased attention, particularly in the aec sector. many projects have successfully implemented bim because of the perceived significant benefits, such as decreased construction cost and duration, increased design quality, improved field productivity, and reduced conflicts and changes, to name a few [7-8]. in more advanced countries like the usa, japan, australia, and singapore, bim is already mandated for all construction projects, but bim awareness of the construction industry in the philippines still needs to improve. several factors contribute to this slow adoption of bim in the country. aside from financial constraints, a lack of awareness and knowledge of bim makes the philippines lag behind its neighboring countries in digitizing construction. in the philippines and other developing countries, the use of bim in the construction sector is still in its early stages. this lack of widespread acceptance of bim is related to the risks and challenges hindering its effectiveness [8]. most of the construction projects in the country are still entrenched in traditional processes, and fully adopting bim is difficult due to a shortage of skilled manpower and resources to build bim capabilities. more importantly, there is no government mandate to support the implementation of bim in all construction projects. based on the foregoing, this study analyzes the benefits, risks, barriers, and challenges associated with bim and provides recommendations for future bim adoption. the purpose of this study is to contribute to the limited but increasing empirical pieces of literature and studies on bim. moreover, it aims to discuss the practical application of bim in the philippine construction industry, especially the industry stakeholders’ current levels of bim deployment. it also identified the benefits of bim and the problems that come with it. it would be helpful to address the prevailing issues and problems related to bim in the construction industry after providing recommendations and formulating guidelines. the proposed framework of guidelines for adopting and implementing bim is hoped to significantly improve the design, construction, and operation of different infrastructures in the country. 2. literature review 2.1. main concepts of bim for the past decade, the aec sector has been at the forefront of the digital revolution. at this level of development, bim was introduced. bim is a digital tool for communication, collaboration, scheduling, and visualization among project participants across the whole project life cycle [5, 9]. according to azhar et al. [6], a computer-generated model was proposed and used in the bim process to simulate facility planning, design, building, and operation. bim aids the construction sector by improving user productivity and bringing notable advantages throughout the life cycle of a structure, particularly in facilities management, construction, and design. ismail et al. [10] stated that bim’s accurate geometrical representation of building components in a digital form is its most important advantage. in the case study conducted by yan and demian [7], the shortening of project duration was the main advantage of bim deployment while reducing human resources and project cost, sustainability, quality improvement, and creativity came next. 2.2. bim adoption in different countries in recent years, the adoption of bim has significantly increased in several countries worldwide, particularly in many developed nations such as singapore, the usa, and japan. singapore, for instance, is one of the leading countries considering bim as a standard practice. the country regularly conducts bim conferences, workshops, and seminars on the utilization of bim in construction projects [11]. advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 123 on the other hand, lorek [12] discussed a brief history of bim and indicated that although bim is not yet mandated in the usa, its adoption may significantly grow in the years to come. in japan, ishizawa et al. [13] analyzed the bim protocols in the country, and they found that the japanese government has introduced the use of bim for almost ten years already. the japanese government issued guidelines for bim adoption to motivate and encourage japanese practitioners to continue bim utilization. the review article by kaneta et al. [14] revealed the problems of bim implementation in japan and the opposition by general contractors and architectural firms. the reason is that clients are often unaware of the value and incentive that bim can bring. most developed countries actively employ bim, while the implementations in developing countries are rare and less advanced than in most developed countries. several pieces of research show how construction firms struggle with limitations such as the socio-economic and technological environment in developing countries. for instance, in india, the construction industry has only a few bim users with limited bim knowledge [10]. although it was acknowledged that bim could address many problems in the construction sector, its adoption is still considered premature. since no specific initiatives coming from the indian government, some private organizations took the initiative to make bim mandatory for a few of their projects [10]. meanwhile, in malaysia, the construction industry development board (cidb) has undertaken several initiatives to improve bim implementation, such as setting up a reference project using bim, assigning committees to monitor bim activities, and conducting bim seminars and workshops [15]. however, despite these initiatives, a low bim adoption in malaysia was still reported [10]. similar experiences were also observed in indonesia. according to ismail et al. [10], indonesians were highly aware of bim execution in the construction industry. nevertheless, the technology used in the country was low due to a lack of bim implementation standards and regulations, which is why only large projects have utilized bim in their design [10]. in south africa, there is a lack of strong support for the implementation of bim technology from governmental agencies. nonetheless, there are also no uniform standards or guidelines for bim implementation. according to a survey conducted by kekana et al. [15], the construction industry in south africa is technologically aware of bim, but its application is still low due to unwillingness to change the traditional methods of practice. furthermore, they pointed out that most of the bim users in organizations were managers or designers only, and they usually utilized bim for particular purposes such as cost estimation, construction simulation, and management [15]. according to korff’s research [16], bim implementation in south africa has slowed down on account of an underfunded public sector, disinterest in the private sector towards bim uptake, and a cheap labor force. in addition, pakistan also experienced a very slow adoption of bim technology compared to other neighboring countries. therefore, some studies were conducted regarding the knowledge and barriers to bim implementation among pakistani construction players [17]. the majority of pakistani respondents claimed that they need more knowledge about bim and the barriers to its implementation include the belief that current practice is still serving them well and the limitation of its adoption in the local market. 2.3. current status of bim adoption in the philippines in the philippines, 1/3 of the construction industry investors started enacting the bim process, especially in developing 3d models with bim software. however, the remaining 2/3 is still unaware of the bim and all its advantages [18]. furthermore, gonzalez [19] stated that only about 20% of the surveying industries utilized bim software for quantity takeoff, and the rest were content with using the traditional way. most of the users of bim in the aec industry are involved in projects globally that need to be submitted in bim formats, and they can compete internationally. work and skill demands in the country at a local level are mostly related to autocad, and neither universities nor colleges have offered bim-based schooling. consequently, several construction companies and owners have not yet engaged in bim advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 124 and realized its potential. the cost of hardware and software is also a massive deterrent to updating the latest versions of bim. as a result, local market support for bim is very low [20]. regarding education, some factors restrained the bim courses from being properly included in the engineering curricula, i.e. the high cost of bim software and hardware, a lack of certified mentors and trainers, and a low level of bim awareness [18]. 2.4. synthesis even if most developing countries emphasized a low bim adoption in certain regions, the advantages of this technology have been acknowledged as well. but more crucially, the difficulties or hurdles associated with its implementation must receive serious consideration if the bim capabilities can be properly leveraged to raise its usage. in the past decade, the adoption of bim has improved significantly in the aec industry. however, the implementation of bim in different countries could have been improved due to numerous barriers. alreshidi et al. [21] found that the major barriers hindering companies from implementing bim were resistance to change by senior employees, lack of training, and disintegration of the project team. based on the foregoing review of different literature and studies about bim, there seems a need to further investigate the benefits, risks, and barriers of bim, particularly in developing countries such as the philippines, where bim implementation is still at a very low level. 3. methodology this section describes the research design and methods utilized in the study. additionally, it also covers the tools and techniques employed during the data collection process. it specifically outlines the research locale, sample and sampling techniques, data gathering methods and processes, statistical treatment of data, and limitations of the study. 3.1. research design this study utilized descriptive and survey research methods, which systematically and accurately describe the facts and characteristics of a given population to provide an accurate account of the characteristics of a particular individual, situation, and group. moreover, survey research gathers data from a population to determine the status concerning variables or subjects under investigation, which is to determine the benefits, risks, barriers, and approaches of bim. 3.2. conceptual framework fig. 1 conceptual framework of the study as presented conceptual framework in fig. 1, the inputs of this research include the prevailing benefits, risks, and barriers of bim and the existing approaches in adopting and implementing bim in construction projects. statistical treatment of data is contained in the inputs of the study, which served as the foundation for a thorough examination of research findings, conclusions, and recommendations. the process and methodology section of this study comprise evidence-based empirical advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 125 research using a survey questionnaire, desk review or analysis of project documents as secondary data, key informant interviews, and analysis of findings. finally, the output of this study is a management model that would serve as guidelines to the contractors, consultants, owners, and construction industry professionals for adopting and implementing bim processes in construction projects. 3.3. research locale this research was conducted in the cities included in the national capital region (ncr) of the philippines. ncr is the ideal location for this study owing to its diversity and technological advancement. it is also a residence for the largest construction projects, owners, developers, consultancy, and engineering design companies. 3.4. sample and sampling techniques a purposive sampling method was applied in this study, and the data were obtained from respondents from different companies representing contractors, consultants, and their clients in selected cities in ncr, particularly manila, quezon, makati, pasig, taguig, and muntinlupa. purposive sampling was used in this study to select a particular population or expert group that can answer the research questions best. specifically, among the types of purposive sampling methods, the expert sampling method was used since the study requires inputs and opinions from industry experts who are knowledgeable in bim and currently working and involved in bim implementation in their respective companies. a total of 105 respondents, who could answer and return the questionnaires to the researcher, served as the study participants. fig. 2 shows that 31.43% of all the respondents are clients, 35.24% are consultants, and 33.33% are contractors. the sample population is quite equally distributed among the three groups of respondents and represents a mix of private and government respondents. fig. 2 distribution of respondents 3.5. data gathering methods a questionnaire was developed for this study to collect data; answer the research questions; and assess the perception of contractors, consultants, and clients on bim. this questionnaire is made up of five parts. part i contained the demographic profile of the respondents, such as profession, years of using bim, position in the company, and nature of their companies. parts ii, iii, iv, and v include questions regarding the benefits, risks, barriers, and approaches of bim in philippine construction projects. 3.6. data gathering process before administering the survey questionnaires to the target sample respondents, a pilot test was conducted on selected respondents who were experts in bim. the objectives of the pilot test are to determine the validity and reliability of the questions and confirm whether the questionnaires are easy to accomplish and specific to the research questions. in addition to the survey questionnaire, key informant interviews were conducted with a select group of respondents to get first-hand knowledge of the project's background and history to learn more about how their projects adopt and implement bim. client 31.43% consultants 35.24% contractor 33.33% advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 126 the important information gathered from the interviews and observations was used as evidence-based information. it is great to help assess and interpret the findings on the current state of bim implementation in various building projects in the philippines. furthermore, project documents were collected, particularly those relevant to the project's commercial, contractual, and design components. these were used to validate and corroborate the study findings during the desk review of secondary data. the narrative analysis method was applied to analyze these secondary data, and the researcher used the aforementioned collected documents to interpret and explain or validate the research findings. 3.7. statistical treatment of data a series of questionnaires were distributed to the intended respondents to achieve the research objectives. the data gathered from the administered questionnaires were tallied, classified, categorized, and evaluated by the study's objectives. percentage and weighted mean were utilized as descriptive statistics in this study. the percentage can be found by: 100% f p n = × (1) where p is the percentage, f is the frequency of responses and n is the total number of cases. the weighted mean can be found by: x f x n =  (2) where �̅ is the computed value of the weighted mean, f is the frequency, x is the unit weight, and n is the total number of respondents. the one-way analysis of variance (anova) was also performed to find out if there were any significant differences in perceptions regarding the benefits, risks, and barriers of bim among all the respondents. anova can be computed as follows: mst f mse = (3) where f is the anova coefficient, mst is the mean sum of squares of treatment, and mse is the mean sum of squares of error. mst can be computed as: 1 sst mst p = − (4) ( ) 2 sst n x x= − (5) where sst is the sum of squares of treatment, p is the total number of population, and n is the total number of samples. lastly, mse can be found by: sse mse n p = − (6) ( )1sse n s= − (7) where sse is the sum of squares of error, s is the standard deviation of the samples, and n is the total number of observations. 3.8. limitations of the study the unit of analysis is based solely on the perception and opinions of the respondents from different aec companies. the first limitation is related to the data used for construction projects which are limited to only five selected cities and advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 127 municipalities in the capital region of the philippines. it could only cover part of the area due to difficulty in the retrieval of questionnaires and the unavailability of the respondents. thus, the statistical strength of the total sample is relatively moderate owing to the small sample size used in the analyses. nevertheless, the perceptions and opinions gathered and generated from the three groups of respondents represented the entire study population. 4. results and discussion this section presents the results of the conducted research survey, analysis of gathered data, and interpretation and discussion of research findings. it also includes a proposed research-validated set of guidelines for adopting bim in various construction projects. 4.1. benefits of building information modeling (bim) table 1 benefits of bim benefits of bim mean std. deviation rank interpretation provides more accurate data visualizations at the earlier stages of the design. 4.52 0.71 1 very often design errors, omissions, conflicts, and clashes are detected before construction. 4.51 0.64 2 very often it provides preliminary insight into design problems and presents opportunities for continuous improvement of the design. 4.44 0.71 3 very often proposals are better understood through accurate visualization of plans. 4.42 0.65 4 very often bim can integrate multiple design disciplines into one plan. 4.39 0.75 5 very often average 4.46 0.69 very often based on the results in table 1, earlier and more accurate design visualization is one of the most significant benefits of bim in the philippine aec industry [20, 22]. bim allows the compilation of every discipline of a project into one complete design, including 3d models and detailed floor plans. through this approach, project stakeholders can see or imagine the project in a real-world scenario, a feature that the traditional paper or 2d design plans fail to deliver. moreover, accurate visualization of the plans also leads to a better understanding of project proposals, according to the respondents. the next benefit of bim is the detection of errors, omissions, conflicts, and clashes. according to key-informantinterviews (kiis) and the research experience from the respondents, the bim toolset helps in automatically detecting clashes among building elements, such as electrical conduit or ductwork that run into a beam. by modeling various electrical and mechanical utilities and structural members, clashes are discovered early in the project and thus reducing costly on-site clashes. bim has an earlier insight into design problems as well. since bim can detect design errors and omissions early, engineers and architects can easily modify and improve the design according to the client’s specifications. interestingly, the respondents' top benefits of bim are confirmed in several pieces of research conducted in different countries [7, 20, 22-23]. according to these studies, the main advantages of bim were precise design visualization, cost and time savings, and coordination and collaboration among many disciplines. on account of the early detection of errors, conflicts, and collisions, bim not only can improve visualization and creativity but also reduce cost and time. coordination and collaboration of different design disciplines were also the perceived benefits of bim in their respective countries. although past studies were conducted at different times and settings, the same benefits were observed in bim implementation regardless of the location. advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 128 4.2. risks of bim based on table 2, it can be deduced that respondents rated the control of data entry and the responsibility for any errors and inaccuracies as the most critical risks of bim. the risk of controlling data entry into the model and changing a bim model has become a recent issue in large and complex construction projects [24]. designers, consultants, and contractors may change the design according to their preferences without informing or sharing ideas with the entire project team. this would create confusion among the parties involved and cause conflicts and flawed interactions between different trade disciplines. another key concern about bim is the accountability for any inaccuracies and errors in the design. responsibilities are blurred since each party has participated and contributed in the planning stages, design, revisions, and input to the bim model. uncertainty about what aspect of the model each party had contributed to the project would probably lead to confusion over the liability for any mistakes and conflicts in the design. table 2 risks of bim benefits of bim mean std. deviation rank interpretation control in entering the data into the model and accountability for any errors and inaccuracies in it. 3.49 0.98 1 sometimes financial risks due to a large amount of investment in purchasing bim software and training staff. 3.38 0.99 2 sometimes software licensing issues may arise. 3.23 1.08 3 sometimes experienced senior staff who are used to traditional processes may resist changes. 3.08 0.90 4 sometimes unrealistic project scheduling may cause delays in project completion. 3.07 0.93 5 sometimes average 3.25 0.98 sometimes in addition, another most commonly identified risk of bim is related to financial risk which is caused by a large amount of investment and staff training. according to respondents during the kiis, there is no assurance that they can recover the costs spent in purchasing the bim software packages and skills training of their staff, which can be very costly. in the philippines, for instance, the current price for a single licensed revit bim software is around 6,000 to 7,000 us dollars, while the training cost is around 100 to 200 us dollars per person. according to ham et al. [25], the percentage of bim investment to the whole project cost ranges from 0.00% to 0.91%. this can impose much financial burden on a company, especially start-ups and small-scale construction and design firms. resistance to change and delay due to unrealistic project scheduling are also identified respectively as the top four and five most important risks of bim. it is inherent to most people to resist any changes to the status quo and traditional practices. khalil et al. [23] indicated that it is challenging to change people’s behaviors once they have grown accustomed to certain ways and patterns. that is why introducing new technology such as bim may face opposition and rejection from senior staff and thus fail its implementation. respondents are also concerned about the reliability of the scheduling capabilities of bim. this issue was also raised in the study of wang and chien [26], wherein they reported that aec professionals need to adapt to the new bim-based technique management process to eliminate the risk of delay caused by unrealistic scheduling. the degree of occurrence is quite different since the identified five major risks of bim are sometimes happening according to the data. it is observed that since bim is just in its early stages of implementation in the country, the identified risks still need to be fully realized by project stakeholders. the respondents are more aware of the immediate benefits of implementing bim than the risks attributed to it. advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 129 4.3. barriers to bim as shown in table 3, interesting findings can be observed from the processed data that almost all respondents agreed that the top three most important barriers are related to the costs needed to implement bim in various construction projects fully. these costs are identified as costs derived from the acquisition of bim software licenses and skills training of staff. with limited funding and budget, especially for government projects and small and medium-sized enterprises (smes), these identified costs are regarded as barriers that hinder companies from implementing or adopting bim in their projects. table 3 barriers to bim benefits of bim mean std. deviation rank interpretation expensive bim software licenses. 4.25 0.90 1 very often high cost of personnel training and bim implementation. 3.86 0.96 2 often limited project funding and budget. 3.68 1.00 3 often lack of qualified and skilled professionals to handle or operate bim tools and software. 3.64 1.00 4 often expensive human-based services costs. 3.63 0.86 5 often average 3.81 0.94 often according to the respondents, it is too risky to invest much money into something that still needs to be established or proven effective in improving construction processes. however, based on the research experience, the cost is not the primary cause of the slow adoption of bim; it is the need for more support and the willingness of project stakeholders to utilize this new technology. this is supported by kouide et al. [27], who also found that the interest and willingness of project managers and engineers play an important role in bim implementation apart from costs. therefore, khalil et al. [23] suggested that to ensure the success of bim implementation, the government or private clients must impose it in the contract through mandatory legislation and supervision. the next barriers to bim are related to manpower, especially the need for more trained professionals and expensive human-based services costs such as salary for skilled bim modelers. the lack of trained or skilled professionals is one of the major factors which hinder the full implementation of bim [23]. only a few professionals know or have undergone proper training and education regarding bim. this situation may be because only a few students graduating from engineering or architecture programs have the skills and knowledge about bim, and most colleges and universities in the country have not yet incorporated bim in their curricula. according to sabongi [28], the possible reason why bim is not yet included in the curriculum is that there is no room for new courses in the existing curriculum since there is a limit to the number of courses per degree program. there is already an increasing demand for bim modelers but with limited trained professionals; thus, the cost of hiring such skilled manpower resources also increases. consequently, most respondents agreed that the high cost of hiring skilled professionals hinders companies from adopting bim. 4.4. approaches to implementing bim based on table 4, respondents suggested that the aec industry must increase the availability of bim technologies and software to implement bim. interestingly, even though respondents find the acquisition of bim software quite expensive, they still chose this approach to start adopting bim in their projects. in other words, if they are given sufficient funds and budget, they would invest in bim tools and software to establish bim in their respective companies. besides, another best approach towards successful bim implementation is the establishment of bim project execution guidelines and suggesting ways to move from traditional practices into bim. this approach will greatly help companies with little or no idea how they would start implementing bim. advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 130 table 4 approaches to implementing bim approaches to implementing bim mean std. deviation rank interpretation bim technology should be made more widely available. 4.10 0.82 1 often develop bim project execution guidelines to facilitate bim implementation 4.01 0.89 2 often increase bim technology research in higher learning institutions. 3.99 1.02 3 often establish feasible ways how to move from traditional practice into bim. 3.98 0.81 4 often organize bim workshops to raise awareness among stakeholders. 3.96 1.08 5 often average 4.01 0.93 often another approach identified by the respondents is to increase research for bim technology in colleges and universities. azhar [22] suggested that bim must be included in the curricula of engineering and architecture programs to increase bim awareness among students, and the education and training of bim software should be implemented. additionally, research in the field of bim must also be conducted to continuously improve bim processes and come up with innovations in bim technology. finally, the respondents agree that to increase awareness regarding bim, workshops, seminars, and training must be conducted. this approach addresses the problem regarding the need for more awareness and knowledge about bim. 4.5. differences in perception about the benefits, risks, and barriers of bim between clients, consultants, and contractors a situation is hypothesized that there is no significant difference between the client, consultant, and contractor’s responses about the benefits, risks, and barriers of bim in various construction projects in the philippines. to test this hypothesis, the following tables show the results of the one-way anova on the differences in perceptions among the respondents. to see if there is a significant difference in the respondents’ responses, a 0.05 level of confidence is employed. the results in table 5 revealed significant differences in the perceptions of clients, consultants, and contractors on one of the five identified benefits of bim, which has something to do with the high-level customization of building systems (p = 0.030). the significant differences in perceptions indicated that respondents disagree on how often this identified benefit happens or is experienced in construction projects. table 5 differences in perception between client, consultant, and contractor regarding the benefits of bim benefits of bim sum of squares df mean square f sig. project coordination and collaboration between groups 0.27 2.00 0.13 0.38 0.686 within groups 36.17 102.00 0.35 total 36.44 104.00 constructability assessment and risk aversion between groups 0.50 2.00 0.25 1.10 0.337 within groups 23.10 102.00 0.23 total 23.59 104.00 high-level customization of building systems between groups 2.06 2.00 1.03 3.62 *0.030 within groups 29.03 102.00 0.28 total 31.09 104.00 optimization of project schedule and cost estimates between groups 3.32 2.00 1.66 2.97 0.056 within groups 57.04 102.00 0.56 total 60.36 104.00 improved project documentation between groups 1.51 2.00 0.76 1.48 0.233 within groups 52.18 102.00 0.51 total 53.69 104.00 *significant at 0.05 level of confidence advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 131 from the foregoing exposition, it is safe to assume that the disagreement between clients, consultants, and contractors on high-level customization as one of the major benefits of bim is due to the differences in the scope of work and contract conditions that the two groups of respondents are engaging with. consultants are generally more engaged in revising plans and designs, while clients suggest changes in the plans. consultants may seem to regard bim as beneficial when it comes to customization, but clients think otherwise, as revealed by their low mean scores. although bim enables consultants to change and customize complex designs more easily, this would mean additional costs for clients. the same findings were observed in the study presented by akdag and maqsood [29]. they found that clients typically do not support the use of bim for their projects due to a lack of knowledge and hesitancy to invest in a novel and innovative technology on the market. as to the risks of bim, the data revealed significant differences in perceptions about the risks related to data integrity and security (p = 0.016), as shown in table 6. consultants or designers, being the ones who mostly use bim software to design and model structures, are more aware of the risks of possible loss and mishandling of bim data and inaccuracies of the data entered into the model. on the other hand, clients seldom use bim software and pass on to consultants or designers the task of modeling the design they want. as a result, clients mostly do not experience these risks and are unaware of them [29]. table 6 differences in perception between client, consultant, and contractor regarding the risks of bim benefits of bim sum of squares df mean square f sig. legal risks between groups 1.31 2.00 0.66 1.09 0.341 within groups 61.60 102.00 0.60 total 62.91 104.00 data integrity and security between groups 4.17 2.00 2.09 4.31 *0.016 within groups 49.39 102.00 0.48 total 53.56 104.00 project-related risks between groups 1.26 2.00 0.63 1.43 0.245 within groups 44.98 102.00 0.44 total 46.24 104.00 financial risks between groups 1.79 2.00 0.90 1.32 0.272 within groups 69.20 102.00 0.68 total 70.99 104.00 *significant at 0.05 level of confidence table 7 differences in perception between client, consultant, and contractor regarding the barriers of bim benefits of bim sum of squares df mean square f sig. social-organizational barriers between groups 1.01 2.00 0.51 1.13 0.327 within groups 45.85 102.00 0.45 total 46.86 104.00 financial-related barriers between groups 3.15 2.00 1.58 2.45 0.091 within groups 65.56 102.00 0.64 total 68.71 104.00 technical-related barriers between groups 0.13 2.00 0.07 0.15 0.863 within groups 45.35 102.00 0.44 total 45.48 104.00 contractual-related barriers between groups 1.20 2.00 0.60 0.89 0.415 within groups 69.19 102.00 0.68 total 70.40 104.00 legal-related barriers between groups 0.20 2.00 0.10 0.16 0.854 within groups 63.53 102.00 0.62 total 63.72 104.00 *significant at 0.05 level of confidence advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 132 concerning the barriers, the data in table 7 reveal no significant differences in the perception of all the identified barriers of bim. these findings suggest that clients, consultants, and contractors agreed on the identified barriers of bim in the philippine aec industry. 4.6. proposed framework of guidelines for implementing bim fig. 3 bim implementation guidelines advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 133 to effectively adopt and implement bim in building construction projects in ncr, the following step-by-step procedures on using bim in designing, constructing, and operating building and infrastructure projects are therefore recommended. fig. 3 shows a research-validated guideline that provides companies with a comprehensive approach to adopting and implementing bim in their projects. 5. conclusions in this research, the small but growing pieces of literature and studies regarding bim were analyzed. the descriptive research method was applied to investigate the benefits, risks, barriers, and approaches of bim implementation. research findings were then used to formulate recommendations and design guidelines for implementing bim in construction projects. in light of the previous findings, the following conclusions were drawn: (1) the benefits of bim were visualizations of a design earlier and more accurately and the detection of design errors, omissions, and clashes. other benefits were providing preliminary insights into design problems, a better understanding of proposals, and integrating multiple disciplines into one plan. (2) the risks were the responsibility and control of data entry of the model, financial risks, and software licensing issues. other risks such as resistance to change by senior staff and delays in project completion were also experienced. (3) the barriers to bim implementation were the expensive acquisition of bim software licenses, high cost of personnel training and bim implementation, limited project funding and budget, lack of trained professionals to handle bim tools and software, and expensive human-based services costs. (4) the most common practices or approaches in addressing the challenges of bim implementation were: increasing the availability of bim technology, establishing bim execution guidelines, innovating research for bim technology, organizing the transition process from traditional practice to bim, and conducting workshops on bim. (5) the respondents have significantly different perspectives on the benefits of bim, particularly on bim’s high level of customization of building systems. however, fewer differences in all of the top five risks of bim were observed, except for data integrity and security. (6) a research-validated framework or guidelines was designed to help the aec sector implement bim in their construction projects. this framework will give clients, consultants, and contractors a thorough plan for how to start using bim in their projects. 6. recommendations one of the objectives of this study is to recommend how to adopt and implement bim in the aec industry, particularly in construction projects. therefore, considering the results of the study as reflected in the findings and conclusions, the following recommendations are offered: (1) to immediately start implementing bim in the philippine aec industry, bim technology should be required in the construction contracts for consultants and contractors to adopt this new technology. it is also necessary that an information manager should be assigned to each project to manage the processes and procedures for information exchange, initiate and implement project and asset information plans, assist in the preparation of project outputs, and implement the bim information exchange protocol. (2) it is also recommended that aec companies conduct bim awareness seminars and workshops to educate their respective employees and spread awareness and appreciation of the benefits of bim. benchmarking other companies already using bim is also an effective way to motivate senior employees to embrace change and consider adopting and using bim technology. advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 134 (3) it is highly recommended that companies look for ways to increase their funds and budget to acquire and implement this new technology. aec companies should treat these bim-related expenses as investments toward realizing the benefits, which would eventually outweigh the costs. (4) aec companies should start conducting training and workshops for their employees. they can also hire trainers from institutions offering courses for bim and/or send some of their employees abroad for exposure and learn about benchmarking bim implementation. moreover, institutions of higher learning should start bim courses and increase research on utilizing bim in various projects. conflicts of interest the author declares no conflict of interest. references [1] h. lindblad and s. vass, “bim implementation and organisational change: a case study of a large swedish public client,” procedia economics and finance, vol. 21, pp. 178-184, 2015. [2] r. leeds, “top 4 challenges facing the construction industry,” https://www.designingbuildings.co.uk/wiki/top_4_challenges_facing_the_construction_industry, june 01, 2019. [3] a. monteiro and j. p. martins, “sigabim: a framework for bim application,” proceedings of the xxxviii iahs world congress, pp. 01-08, april 2012. [4] g. s. evuri and n. amiri-arshad, “a study on risks and benefits of building information modeling (bim) in a construction organization,” b. s. thesis, department of computer science and engineering, university of gothenburg, goteborg, sweden, 2015. [5] c. eastman, p. teicholz, r. sacks, and k. liston, bim handbook: a guide to building information modeling for owners, managers, designers, engineers, and contractors, 2nd ed., new jersey: john wiley & sons, inc., 2011. [6] s. azhar, m. hein, and b. sketo, “building information modeling (bim): benefits, risks and challenges,” http://ascpro0.ascweb.org/archives/cd/2008/paper/cpgt182002008.pdf, april 02, 2008. [7] h. yan and p. demian, “benefits and barriers of building information modelling,” https://hdl.handle.net/2134/23773, january 01, 2008. [8] a. ghaffarianhoseini, j. tookey, a. ghaffarianhoseini, n. naismith, s. azhar, o. efimova, et al., “building information modelling (bim) uptake: clear benefits, understanding its implementation, risks and challenges,” renewable and sustainable energy reviews, vol. 75, pp. 1046-1053, august 2017. [9] w. kymmell, “building information modeling: planning and managing construction projects with 4d cad and simulations,” 1st ed., new york: mcgraw-hill, 2008. [10] n. a. a. ismail, m. chiozzi, and r. drogemuller, “an overview of bim uptake in asian developing countries,” aip conference proceedings, vol. 1903, no. 1, article no. 080008, november 2017. https://doi.org/10.1063/1.5011596 [11] w. zheng, “a comprehensive analysis of building information modeling/model (bim) policies in other countries and its adoption strategies in ontario,” master thesis, engineering and public policy, walter g. booth school of engineering practice, mcmaster university, hamilton, ontario, august 2013. [12] s. lorek, “global bim standards: is your country next? constructible,” https://constructible.trimble.com/constructionindustry/global-bim-standards-is-your-country-next, april 05, 2018. [13] t. ishizawa, y. xiao, and y. ikeda, “analyzing bim protocols and users surveys in japan to understand the current japanese bim environment, through the comparison with different countries,” proceedings of the 23rd international conference of the association for computer-aided architectural design research in asia, vol. 2, pp. 31-40, may 2018. [14] t. kaneta, s. furusaka, and n. deng, “overview and problems of bim implementation in japan,” frontiers of engineering management, vol. 4, no. 2, pp. 146-155, july 2017. [15] g. kekana, c. aigbavboa, and w. thwala, “understanding building information modelling in the south africa construction industry,” proceedings of the organization, technology and management in construction (otmc), september 2015. https://core.ac.uk/download/pdf/54199032.pdf [16] s. korff, “bim in south africa: the good, the bad and the promising,” https://www.buildinganddecor.co.za/bim-insouth-africa-the-good-the-bad-and-the-promising, july 09, 2019. advances in technology innovation, vol. 8, no. 2, 2023, pp. 121-135 135 [17] a. abbas, z. u. din, and r. farooqui, “achieving greater project success & profitability through pre-construction planning: a case-based study,” procedia engineering, vol. 145, pp. 804-811, 2016. [18] v. n. r. villasenor, f. c. villasenor, and d. r. gonzales, “educating green building stakeholders about the benefits of bim the philippines experience,” joint apec-asean workshop how building information modeling standard can improve building performance, june 2013. [19] d. r. gonzalez, analysis of the impact of building information modeling (bim) in construction production from the filipino's perspective, manila: mapua institute of technology, 2013. [20] d. migilinskas, v. popov, v. juocevicius, and l. ustinovichius, “the benefits, obstacles and problems of practical bim implementation,” procedia engineering, vol. 57, pp. 767-774, 2013. [21] e. alreshidi, m. mourshed, and y. rezgui, “factors for effective bim governance,” journal of building engineering, vol. 10, pp. 89-101, march 2017. [22] s. azhar, “building information modeling (bim): trends, benefits, risks, and challenges for the aec industry,” leadership and management in engineering, vol. 11, no. 3, pp. 241-252, july 2011. [23] i. g. khalil, a. mohamed, and z. smail, “building information modelling in morocco: quo vadis?” third international sustainability and resilience conference: climate change, pp. 479-483, november 2021. [24] i. a. m. ya’acob, f. a. m. rahim, and n. zainon, “risk in implementing building information modelling (bim) in malaysia construction industry: a review,” e3s web of conferences, vol. 65, article no. 03002, 2018. [25] n. ham, s. moon, j. h. kim, and j. j. kim, “economic analysis of design errors in bim-based high-rise construction projects: case study of haeundae l project,” journal of construction engineering and management, vol. 144, no. 6, june 2018. https://doi.org/10.1061/(asce)co.1943-7862.0001498 [26] c. c. wang and o. chien, “the use of bim in project planning and scheduling in the australian construction industry,” international conference on construction and real estate management, pp. 126-133, september 2014. [27] t. kouide, g. paterson, and c. thompson, “bim as a viable collaborative working tool: a case study,” proceedings of the 12th international conference on computer aided architectural design research in asia, pp. 57-68, april 2007. [28] f. j. sabongi, “the integration of bim in the undergraduate curriculum: an analysis of undergraduate courses,” proceedings of the 45th asc annual international conference, april 2009. http://ascpro0.ascweb.org/archives/cd/2009/paper/ceue90002009.pdf [29] s. g. akdag and u. maqsood, “a roadmap for bim adoption and implementation in developing countries: the pakistan case,” archnet-ijar: internationa journal of architectural research, vol. 14, no. 1, pp. 112-132, january 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 4___aiti#8897___118-130 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 theoretical investigation for the influence of various parameters on the performance of a novel concentration-based solar desalination system mokhtar mohammed * , mourad taha janan national school of arts and professions, high national school of computer science and systems analysis, mohammed v university, rabat, morocco received 11 november 2021; received in revised form 29 december 2021; accepted 30 december 2021 doi: https://doi.org/10.46604/aiti.2022.8897 abstract this study aims to investigate the influence of various parameters on the freshwater yield and efficiency of a novel concentration-based solar desalination system. the system performance under the summer and winter climatic conditions of rabat city, morocco is evaluated. the design parameters are glass cover thickness, absorber basin thickness, brackish water mass, and absorber basin material. the climatic parameters are wind velocity, ambient temperature, and solar radiation. numerical studies on different system parameters are done by examining the effect of system component parameters on the system performance. through the matlab code, the equations for the freshwater yield and efficiency of the new system are constructed and solved. the results show that the system gives the best performance with 6 mm glass cover thickness, 2 mm absorber basin thickness, and 40 kg brackish water mass. keywords: solar desalination system, parabolic trough concentrator, design parameters, freshwater yield, system efficiency 1. introduction water is an essential element for the life of living organisms on the face of the earth. by using clean water, humans get an environment free from diseases and the spread of epidemics. in many arid places of the world, freshwater scarcity has been a vital problem and additional water supplies will become important in the future. seawater desalination is typically seen as a dependable solution in arid places for meeting the constantly increasing needs for water caused by population growth as well as economic and social changes and for reducing the reliance on groundwater supplies [1]. desalination is one of the primitive forms of water handling, and it remains a common treatment solution around the world today [2]. desalination of sufficient seawater is regarded as one of the most important technical solutions to water scarcity in many areas of the world [3]. in previous research, some researchers have studied solar distillers without concentrator technology, and others have studied them with concentrator technology and with different designs. in this research, a new design in which a parabolic trough concentrator (ptc) is under the solar desalination system is developed. after that, the effect of design parameters (glass cover thickness, absorber basin thickness, brackish water mass, and absorber basin materials) and climatic parameters (wind speed, ambient temperature, and solar radiation) on the performance of the developed system is studied. some researchers have done recent review studies of different desalination systems using nuclear desalination [4] and microbial desalination cells (mdcs) [5]. in this research, the influence of various parameters on the freshwater yield and efficiency of a novel concentration-based solar desalination system is theoretically investigated to evaluate the performance of the system under the summer and winter climatic conditions of rabat city, morocco. the parameters of glass cover thickness (2, 4, and 6 mm), absorber basin thickness * corresponding author. e-mail address: mohammed_mokhtarnomanqasem@um5.ac.ma tel.: +212654866890; fax: +212537686078 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 (2, 4, and 6 mm), brackish water mass (40, 60, and 80 kg), and absorber basin material (aluminum and copper) are the design parameters, and the parameters of wind velocity, ambient temperature, and solar radiation are the climatic parameters. numerical studies on different parameters of the system are done by examining the effect of system component parameters on the system performance. through the matlab code, the equations for the freshwater yield and efficiency of the new system are constructed and solved. 2. literature review many research and review articles have been written about solar stills and the various parameters that influence the performance of solar distillation. nguyen [6] investigated the factors that influence the stills’ distillate yields, including subjective factors (i.e., design elements and operation factors) and environmental factors (i.e., external or natural factors) for conventional passive solar stills and active (forced circulation) stills with enhanced heat recovery. the results showed that the distillate outputs of solar stills were increased from 30% to 68% compared with traditional distillation systems. azooz and younis [3] demonstrated the performance of ten solar stills with various glass inclination angles in an experimental study. the inclination angles chosen are 10°-55° in 5-degree increments. experimental results proved that the angles between 30° and 35° are associated with the worst still performance, while those between 20° and 25° provide the best clean water productivity and cost-effectiveness. younis et al. [7] proposed a solar distillation model and tested it using the parameters listed below: water depth (6, 9, and 12 cm), water salinity (28, 35, and 58 mmoh/cm), cover thickness (2, 4, and 6 mm), daylight percentage (43.7, 47.4, and 52.1%), solar radiation, relative humidity, ambient air temperature, and wind speed. the results showed that at 6 cm water depth, 6 mm glass cover thickness, 28 mmoh/cm water salinity, and 52.1% daylight percentage, the maximum distillation yield was around 5 l/m 2 .day. bouzaid et al. [8] proposed and evaluated a new solar still with a stepped-slope absorber plate and baffles, as well as its productivity impact. the findings demonstrated that by introducing new modifications, the thermal performance of the modified stepped solar still can be significantly improved. gawande and bhuyar [9] tested three different stepped-type solar stills with different absorber surface areas due to differences in the shape of the basin surface, which were flat, concave, and convex, respectively. it is found that the average daily water production for the concave and convex type stepped solar stills are 29.24% and 56.60% higher than that of flat type stepped solar still, respectively. islam et al. [10] investigated how the heat removal factor, collector efficiency factor, mass flow rate, and collector aperture area affect the collector thermal efficiency in a parabolic-trough concentrating solar system. for the study, three fluids were used: carbon dioxide, ammonia, and nitrogen. for a concentrator with a 1.5 m aperture and 2 m length, the optimum receiver size (diameter) (providing the highest efficiency) was discovered to be 51.8 mm. with different mass flow rates of 0.0192 kg s -1 , 0.0362 kg s -1 , and 0.0491 kg s -1 for ammonia, nitrogen, and carbon dioxide, respectively, the maximum collector efficiencies were 67.05%, 66.81%, and 67.22% at the same aperture area of 2.836 m 2 . panchal and patel [11] carried out a comprehensive review to study the effect of various design parameters (water depth, condensing cover material, thickness and inclination, and type of solar still), climatic parameters (wind velocity, ambient temperature, and solar radiation), and operational parameters (salinity of water) on the distillate yield of solar stills. it is found that the lower condensing glass cover thickness, minimum brine depth, high intensity of solar radiation, and increasing wind speed give the better yield of the solar stills. also, the larger cover tilt angle should be preferred in winter and a smaller angle should be preferred in summer. senthil et al. [12] carried out an experimental comparison between the cavity surface contour and plain surface contour of the solar absorber surface to investigate the impact of design parameters on the thermal performance of concentrated solar collectors. the results proved that the contoured plain surface produces a little uniform temperature distribution and a lower rate of heat 119 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 absorption than the cavity surface. the energy efficiency of the plain surface absorber and the cavity surface absorber is 61.84% and 67.65%, respectively. hoque et al. [13] conducted experimental investigations for the effect of the basin water amount and salt concentration on freshwater production of solar still for saline water desalination for low-income coastal areas in the context of bangladesh. experimental studies show that when the amount of basin water increases, the water production decreases, and when the salt concentration in the water to be desalinated decreases, the freshwater production increases. goshayeshi and safaei [14] carried out an experimental study for the effect of two basin geometries (flat and convex) at different inclination angles of the cover on the heat transfer and effectiveness of the desalination process for stepped solar stills. the results revealed that the maximum heat transfer and more desalination processes take place in the convex solar still. the solar still performance improved as the angle was increased from 25° to 35°. the best angle of inclination for solar stills is 32.5° to the horizontal axis. al-othman et al. [15] conducted a simulation study of a multi-stage flash (msf) desalination plant that works utilizing the solar pond and parabolic trough collectors to completely satisfy the energy requirements in the united arab emirates (uae). the findings indicate that two ptcs with a total aperture area of 3160 m2 can supply 76% of the msf energy needs. a solar pond with a 4-meter depth and a surface area of 0.53 km 2 provides the remaining. tawalbeh et al. [16] presented a detailed review of pressure current delayed osmosis (pro) when mixing two streams of different salinities and when generating gibbs-free mixing power. some technical problems were studied, namely (1) membrane material, (2) water transfer in the membrane, (3) process efficiency, (4) fouling, and (5) technical-economic feasibility. the efficiency and energy density of pro are directly affected by several process parameters such as temperature, feed concentration, membrane type, and draw solution type. this review showed that the power density that can be harvested from pro is controlled by numerous variables, including membranes, which have attracted a lot of attention in the literature. studies showed that with the development of the proper membrane, power density can be boosted by orders of magnitude from about 2 w/m 2 to 47 w/m 2 . this research indicated that pro is still dealing with several issues that must be addressed. from the literature survey, it has been demonstrated that changing design parameters and climatic parameters have a significant impact on the system performance. in this research, the effect of design and climatic parameters on the new system’s performance will be investigated. 3. thermal analysis fig. 1 indicates a schematic depiction of the proposed novel concentration-based solar desalination system. the distiller’s half-cylinder basin diameter is 0.3 m and it is made of a black-painted aluminum sheet with a thickness of 0.004 m. it is located in the focal line of ptc, which is 1 m from the vertex (v) and 2.25 m from the system aperture (w). the rim angle of the system is 58.72°. the basin is half-cylindrical in shape to help collect desalinated water and to reflect the sun’s rays from the solar concentrator system installed on it. fig. 1 schematic view of the novel concentration-based solar desalination system 120 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 the solar distiller’s walls are insulated by a 2 cm layer of sawdust encased in a 1 cm thick wooden frame. the solar distiller’s top surface is covered with a 0.36 m × 3 m glass cover. the top cover is made of 0.002 mm thick transparent glass. with a doubly inclined 30° angle inclination, it fits over the grooves. freshwater collecting segments with a length of 3 m and a width of 0.030 m are placed on either side of the solar distiller. the concentration ratio is the area of the ptc aperture divided by the area of the absorber. the concentration ratio for the new system is 4.8 [17-19]. in two areas, solar irradiance will enter the new system [17-19]: (1) solar irradiance will drop into the solar distillation device, where a small part of the solar radiation is absorbed by the glass cover and most of it transmits through the glass cover to the inside of the distiller. the water and absorber basin absorb a portion of the solar radiation that is transmitted. (2) the amount of sunlight will fall into the parabolic reflector, where the sunlight will be redirected into the solar distiller’s absorber basin. the ptc’s focal line is in the middle of the half-cylindrical absorber basin. the concentrated solar radiation on the absorber basin heats the water and raises its temperature by convection. the absorber basin loses minimal heat to the environment once more due to convection. in this process, water evaporation, convection, and radiation transport the thermal energy acquired by the basin water to the interior glass surface. the water evaporates and increases as it is heated until it reaches the internal glass cover layer. the water vapor on the inside surface of the glass cover subsequently condenses and forms the freshwater, which is collected in the segments on either side of the distiller. the glass cover releases heat to the environment once more by convection and radiation [17-19]. 4. hourly freshwater yield and efficiency of the system 4.1. hourly freshwater yield the hourly freshwater yield per m 2 of the novel system is given by: , 3600 e w g ev fg q m h −× = (1) where qe, w-g is the heat transfer amount by evaporation between the brackish water and the glass cover and is computed as follows. , , ( ) e w g e w g w w g q h a t t− −= − (2) where aw, tg, and tw are the water area, glass temperature, and water temperature, respectively. he, w-g is the thermal transfer coefficient through evaporation [20-21]. , , 0.016273 w e w g c w g w g p p h h t t − − − = × − × (3) where hc, w-g is the thermal transfer coefficient through convection [20-21]. 1/3 , 3 ( )( 273) 0.884 ( ) 268.9 10 w g w c w g w g g p p t h t t p − − + = − + × −       × (4) the saturated water vapor pressures at the glass cover and the water temperature are indicated by pg and pw, respectively. 121 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 5144 exp 25.317 273.15 g g p t = + +       (5) 5144 exp 25.317 273.15 w w p t = + +       (6) where hfg is the latent heat of water evaporation given by zoori et al. [22]. { }6 6 2 3 3.165 [10 (761.6 )], 70 2.4935 {10 [(947.79 ) (0.013132 ) (0.0047974 )]}, 70 cfg f f f f f f t if t c t t t if t h − ≥ ° − + − × × × × <× °×= (7) the temperature of the air-water mixture is calculated using the mathematical mean value of the glass cover and the water temperature tf. 2 g w f t t t + = (8) 4.2. efficiency the solar distiller’s overall thermal efficiency is the ratio of evaporative heat transfer to solar radiation on the half-cylinder absorber that can be written in the following form [22]: ( ) 3600 ev fg th b t m h a i = ∑ ∑ η (9) using eqs. (1) and (2) for the overall solar thermal efficiency, the following equation is derived: , ( ) ( ) e w g w w g th b t h a t t a i − − = ∑ η (10) 5. average weather conditions for the rabat region in morocco morocco’s rabat-sale-kenitra, which has a particularly fascinating geographical location, is taken into account in this study. the solar radiation data are obtained from the weather spark website for a typical day in winter (15 january) and summer (15 july) with meteorological parameters [23-24]. (a) winter day (15 january) (b) summer day (15 july) fig. 2 hourly variation in the solar radiation, ambient temperature, and wind speed on the winter day and summer day of the rabat region in morocco 122 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 it is observed from fig. 2 that the incident solar radiation on 15 january increases gradually from 8:00 until its maximum value 500 w/m 2 at 13:00 as shown in fig. 2 (a), and the incident solar radiation on 15 july increases gradually from 8:00 until its maximum value 970 w/m 2 at 13:00 as shown in fig. 2(b); after that, it starts decreasing gradually until 17:00. furthermore, the variation in wind speed and ambient temperature over time is also taken into consideration as shown in fig. 2. the maximal wind speed 4.5 m/s is recorded at 15:00 on the winter day and the maximal wind speed 5.8 m/s is recorded at 16:00 on the summer day. the maximal ambient temperature 17°c is recorded at 15:00 on the winter day and the maximal ambient temperature 26°c is recorded at 14:00 and 15:00 on the summer day. 6. numerical resolution through the matlab code, the freshwater yield and the efficiency of the device are determined by using eqs. (1) and (10). the total duration of 10 hours for iteration starts from 8:00 to 17:00 on 15 january in winter and 15 july in summer. the freshwater yield during the day as well as the daily efficiency may then be calculated for the design parameters and climatic parameters. fig. 3 depicts a flowchart of the study’s full methodology. the thermophysical properties and design parameters of the glass cover, brackish water, and absorber basin as well as the technical characteristics of ptc are listed in tables 1-4. fig. 3 flowchart of the study’s methodology table 1 thermophysical properties and design parameters of glass cover [17-19] property value glass cover thickness (mm) glass cover mass (kg) cpg (j/kg.k) 800 2 5.374 kg (w/m.k) 1.02 4 10.747 �g (kg/m 3 ) 2530 6 16.121 αg 0.05 τg 0.90 ag 1.062 ԑg 0.86 123 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 table 2 thermophysical properties and design parameters of brackish water [17-19] property value property value cpw (j/kg.k) 4190 τw 0.95 kw (w/m.k) 0.67 aw 0.9 �w (kg/m 3 ) 1002 ԑw 0.95 water mass (kg) 40, 60, and 80 αw 0.05 property value absorber basin thickness (mm) absorber basin mass (kg) property value cpb (j/kg.k) 896 2 8.861 length (m) 3 kb (w/m.k) 204 4 17.722 aperture (m) 2.25 �b (kg/m 3 ) 2530 6 26.584 focal line (m) 1 αb 0.90 area (m 2 ) 6.75 ab 1.641 reflectivity 0.90 to study the impact of parameters on the freshwater yield and efficiency of the new system, it is necessary to make the following hypotheses [17-19]: (1) the ptc has a symmetrical shape and the influence of the distiller shadow on the ptc is negligible. (2) the physical characteristics of various materials are constant. (3) the side and bottom walls’ heat capacity and the effect of glass cover tilt are ignored. (4) with the depth of the water and the thickness of the glass cover, a constant temperature gradient is maintained. (5) ideal gases include dry air and water vapor, and there is no vapor leaking inside the system device. (6) the internal glass-cover surface is the only place where condensation occurs. (7) segmental and wall-side losses are not taken into account. 7. results and discussion 7.1. theoretical investigation for the influence of design parameters on the system performance 7.1.1. the influence of glass cover thickness freshwater yield and system efficiency increase as the cover glass thickness increases from 2 mm to 4 and 6 mm. with the 6 mm glass cover thickness, the system shows the highest freshwater yield and efficiency as shown in fig. 4. the high cover thickness limits the influence of solar radiation and causes a decrease in temperature at an internal glass-cover surface. the temperature difference between the glass cover and water increases dramatically, which promotes the condensation of water vapor and thus increases the yield of distilled water. it also could be attributable to the fact that the energy loss to the surroundings with 6 mm cover thickness is lower than that with 4 or 2 mm thickness, and the highest thermal resistance is achieved with 6 mm cover thickness. this could be caused by the fact that the heat amount in 2 mm, 4 mm, and 6 mm glass cover thicknesses is nearly equivalent, owing to the nearly similar absorption coefficient and transmittance for the glass cover. it is also noticeable from fig. 4 that the greater the mass of water and the thickness of the absorber basin, the lower the freshwater yield and efficiency of the new system. the maximum daily yield and efficiency are about 11.22 kg/m 2 .day and 6.86% during the summer day and about 2.59 kg/m 2 .day and 2.89% during the winter day with the greatest glass cover thickness 6 mm. table 3 thermophysical properties and design parameters of absorber basin [17-19] table 4 technical characteristics of ptc 124 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 (a) freshwater yield (b) efficiency fig. 4 the influence of cover thickness on the freshwater yield and efficiency of the system at various amounts of water mass and absorber basin thickness for the winter day and summer day 7.1.2. the influence of absorber basin thickness fig. 5 illustrates the influence of absorber basin thickness on the freshwater yield and efficiency of the system. as can be seen, the yield and efficiency decrease with the increasing absorber thickness from 2 mm to 4 mm and 6 mm. however, the 2 mm absorber thickness produces the highest daily freshwater yield and daily efficiency, which are 11.22 kg/m 2 .day and 6.86% during the summer day and about 2.59 kg/m 2 .day and 2.89% during the winter day with 40 kg brackish water mass and 6 mm glass cover thickness. the increase in the absorber thickness leads to an increase of thermal conduction resistance. this reduces the heat transfer to brackish water, and leads to a decrease in the temperature of the basin. therefore, the temperature of the water to be desalinated decreases, which negatively affects the water productivity and the system efficiency. (a) freshwater yield fig. 5 the influence of absorber thickness on the freshwater yield and efficiency of the system at different levels of cover thickness and brackish water mass for the winter day and summer day 125 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 (b) efficiency fig. 5 the influence of absorber thickness on the freshwater yield and efficiency of the system at different levels of cover thickness and brackish water mass for the winter day and summer day (continued) 7.1.3. the influence of brackish water mass fig. 6 indicates the influence of brackish water mass on the freshwater yield and efficiency of the system with each glass cover thickness and absorber basin thickness for the typical day in winter and summer. the freshwater yield and efficiency are inversely proportional to the difference in the mass of brackish water, which means that the greater the mass of the water to be desalinated, the lower the freshwater yield and efficiency, as concluded with the same observations in previous studies [7, 11, 18]. therefore, the large mass of brackish water has an increase in heat storage in the water and a longer time for evaporation, which reduces the freshwater yield and efficiency of the system. the highest value of the freshwater yield and efficiency achieved with 40 kg water mass, 2 mm absorber basin thickness, and 6 mm glass cover thickness are 11.22 kg/m 2 .day and 6.86% during the summer day and about 2.59 kg/m 2 .day and 2.89% during the winter day, as shown in fig. 6(a) and fig. 6(b). (a) freshwater yield (b) efficiency fig. 6 the influence of brackish water mass on the freshwater yield and efficiency of the system at different levels of cover thickness and absorber basin thickness for the winter day and summer day 126 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 in general, it is noticed from fig. 4 that the freshwater yield and efficiency of the new system increase with the increase in the thickness of the glass cover. it is also observed from figs. 5-6 that the freshwater yield and efficiency of the new system decrease with the increase in the mass of the water to be desalinated and the thickness of the absorber basin. it is concluded that the freshwater yield and efficiency of the novel design of the concentration-based solar desalination system increase with the increase in the thickness of the glass cover, the decrease in the thickness of the absorber basin, and the decrease in the mass of the water to be desalinated. 7.1.4. the influence of absorber basin material the difference in the material of the absorber basin affects the freshwater yield and efficiency of the system, as shown in fig. 7. the physical properties of aluminum and copper for the absorber basin are different, and this confirms their impact on the freshwater yield and efficiency of the system. the freshwater yield and efficiency of the system with the copper material of the absorber basin are higher than the system with the aluminum material of the absorber basin because the thermal conductivity value of copper is two times higher than that of aluminum. the maximum value of hourly freshwater yield and efficiency of the system with the aluminum material of the absorber basin is 1.69 kg/m 2 .hr and 87% on 15 july (summer) and 0.54 kg/m 2 .hr and 44% on 15 january (winter). the maximum value of hourly freshwater yield and efficiency of the system with the copper material of the absorber basin is 1.75 kg/m 2 .hr and 90% on 15 july (summer) and 0.56 kg/m 2 .hr and 46% on 15 january (winter). (a) freshwater yield (b) efficiency fig. 7 variation in the hourly freshwater yield and efficiency with different absorber basin materials (aluminum and copper) for the winter day and summer day 7.2. theoretical investigation for the influence of climatic parameters on the system performance 7.2.1. the influence of solar radiation distillation needs the use of heat energy to evaporate the water, and this heat energy is generated from solar radiation, which is plentiful, never-ending, and pollution-free. however, the intensity of the sun changes from day to day and season to 127 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 season, affecting the freshwater yield and efficiency of the new solar distiller. in the distillation process, solar radiation is quite important. as a result, various studies on the impact of this parameter on freshwater yield have been conducted. the findings of nguyen [6] and panchal et al. [11] certainly demonstrate a great rise in the distilled water production created by the increase in solar radiation intensity. therefore, the higher the amount of solar radiation, the higher the freshwater yield and efficiency of the system. 7.2.2. the influence of wind speed wind speed affects freshwater productivity and system efficiency as the system performance increases with the increase in the wind speed blowing on the glass cover and with the decrease in the wind speed blowing on the absorber basin. due to the increase in wind speed on the surface of the glass cover, the heat transfer coefficient increases from the glass cover to the surrounding. therefore, the temperature of the glass cover decreases and leads to an increase in vapor condensation, and the amount of distilled water increases. thus, the freshwater yield and efficiency of the system increase when the wind speed increases on the surface of the glass cover. on the surface of the absorber basin, the higher the wind speed, the higher the convection heat transfer coefficient value. this increases the heat flux in the absorber basin to the ambient air and produces the heat loss to the surroundings. therefore, the temperature of the absorber basin decreases and leads to a decrease in water evaporation, and the amount of distilled water decreases. 7.2.3. the influence of ambient temperature the influence of ambient temperature is opposite to that of wind speed. the system performance increases with a decrease in the ambient temperature on the glass cover and with the increase in the ambient temperature on the absorber basin. the glass cover will cool faster if the ambient temperature is lower. therefore, the temperature of the glass cover decreases and leads to an increase in vapor condensation, and the amount of distilled water increases. however, the absorber basin will heat if the ambient temperature is higher. therefore, the temperature of the absorber basin increases and leads to an increase in water evaporation, and the amount of distilled water increases. it is observed in fig. 2 that the solar radiation, wind speed, and ambient temperature are higher on the summer day than on the winter day, affecting the performance of the system. the freshwater yield and efficiency are higher on the summer day than on the winter day, as shown in figs. 4-7. 8. conclusions the research indicates how the design and climatic parameters influence the freshwater yield and efficiency of a novel concentration-based solar desalination system. the parameters are investigated on a typical day in winter and summer. the finding of this study can be summarized as follows. (1) the design and climatic parameters have a vital impact on the performance of the new system. (2) the freshwater yield and the system efficiency on the summer day are higher than that on the winter day because the solar radiation falling on the system device on the summer day is higher. (3) the freshwater yield and the system efficiency are improved with the increase in the thickness of the glass cover. the system with 6 mm glass cover thickness shows better freshwater yield and efficiency than with 4 mm and 2 mm glass cover thickness. (4) the absorber thickness is inversely proportional to the freshwater yield and the system efficiency. with the lowest absorber thickness (2 mm), high freshwater yield and efficiency are obtained. 128 advances in technology innovation, vol. 7, no. 2, 2022, pp. 118-130 (5) the greater the mass of brackish water is, the lower the freshwater yield and the system efficiency are. with the minimum mass of water (40 kg), the maximum freshwater yield and system efficiency are achieved. (6) with 6 mm glass cover thickness, 2 mm absorber basin thickness, and 40 kg brackish water mass, daily freshwater yield and daily efficiency of the system are high. the maximum daily freshwater yield and daily efficiency are about 11.22 kg/m 2 .day and 6.86% during the summer day, and are about 2.59 kg/m 2 .day and 2.89% during the winter day. (7) the increase in the value of solar radiation leads to an increase in the freshwater yield and efficiency of the system. (8) the increase in wind speed and the decrease in the ambient temperature on the glass cover of the system lead to an increase in the freshwater yield and system efficiency. the opposite happens in the absorber basin. 9. suggestions and recommendations it is suggested that future research focus on the use of solar concentration modules with solar distillers. it is recommended to improve various design parameters of the solar distillers to get the best performance. in the future, the use of optimization algorithm methods can be considered to obtain the optimal design of concentration-based solar distiller systems. conflicts of interest the authors declare no conflict of interest references [1] r. poblete, g. salihoglu, and n. k. salihoglu, “investigation of the factors influencing the efficiency of a solar still combined with a solar collector,” desalination and water treatment, vol. 57, no. 60, pp. 29082-29091, 2016. 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[24] weather spark website, “july 15 weather in rabat,” https://weatherspark.com/d/33170/7/15/average-weather-on-july-15-in-rabat-morocco, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 130 microsoft word 4-v9n3(2024)-aiti#13516(197-209).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 english language proofreader: chih-wei chang iris recognition scheme based on entropy and convolutional neural network inass-shahadha hussein*, noor-abbood jasim middle technical university, technical institute of baquba, baghdad, iraq received 28 march 2024; received in revised form 06 may 2024; accepted 07 may 2024 doi: https://doi.org/10.46604/10.46604/aiti.2024.13516 abstract this study presents an advanced iris image segmentation approach to overcome vibration and occlusion from the lashes. the proposed scheme removes the surrounding areas of the iris image to recover the region of interest (roi) containing the iris images. the entropy function and mathematical morphology are employed as the foundation of the proposed scheme. initially, the entropy function is applied to the binarization image. subsequently, the roi is cropped and extracted from the binary image using the dilation method. furthermore, a convolutional neural network (cnn) is used in the recognition phase. the database of the indian institute of technology delhi (iit delhi) serves as a test. the results yield a high level of accuracy—up to 93% during segmentation. using half of the dataset during the recognition phase results in an accuracy of 98.8%, while using the complete database produces an accuracy of 97.5%. keywords: iris, segmentation, morphology, entropy, cnn 1. introduction biometric technologies have evolved significantly, revolutionizing the field of identification and authentication. initially, biometric methods were mainly correlated with fingerprints, and the earliest systems were developed in the late 1800s. however, as computing capacity and sensor technology have increased, the growth of biometric modalities, including voice, face, iris, and palmprint identification, etc., has ensued quantitatively [1]. biometric identifications using the iris, sclera, and fingerprints have increasingly been employed for authentication [1]. iris recognition (ir) has been habitually deployed in multifarious applications, e.g., security, e-commerce, finance, etc [2]. to discuss further, iris biometrics is the most accurate and safest method concerning identification. additionally, among various physiological patterns, iris biometrics is well known for confidentiality and dependability [3]. however, a potential challenge lies in ir with the requirement for high-quality imaging devices and controlled environments to guarantee accurate and reliable results. mostofa et al. [4] have summarized the benefits of iris biometry, while the statements describe the iris as follows: (a) uniqueness: even if comparing a pair of irises of a certain person or twins, the irises are unreservedly heterogeneous; (b) stability: typically, iris develops from childhood and maintains the physical characteristics permanently; (c) the provision of texture information: iris furnishes the owner with texture information concerning stripes, spots, and coronas. (d) security: the iris is located in a circular area beneath the surface of the eye, between the black pupil and the white sclera. hence, given the location, the iris is rarely affected externally. meanwhile, with such a feature, faking the iris pattern is theoretically * corresponding author. e-mail address: inasshussin@mtu.edu.iq 198 advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 impossible; (e) noncontact activation: compared to biometrics undergoing tactile or any physical interaction, e.g., fingerprint recognition, ir is comparatively hygienic. considering the aforementioned benefits, the iris has been employed in identification extensively. historically, the first automatic ir system was introduced by daugman [5] in 1993. in this work, the iris region is first segmented using the conventional procedure in most ir works. subsequently, from the segmented images, the desired features are retrieved. the majority of these characteristics are typically handcrafted. the use of manual features causes an impasse for traditional approaches. as a result, to resolve such developmental hindrance, daugman [6] introduced the highly accurate and quick ir model in 2009, according to the hamming distance and gabor filter, and employed several iris datasets. on the other hand, pre-processing and segmentation are two requisite operations for the identification method, especially the initial step [7-8]. technically, the intregro-differential operator and the hough transform serve as the foundation for conventional iris segmentation techniques. several algorithms employ variations to determine the iris borders of the hough transform and the integro-differential operator. when iris images are captured in proper circumstances, these algorithms can accomplish adequate localization precision. the integro-differential operator, which is frequently employed during preprocessing, highlights pixel intensity variations to improve the edges of the iris. by identifying the borders, the operator assists in distinguishing the iris from adjacent components, such as the sclera and eyelids. after the edges are sharpened, the hough transform is used to locate elliptical or circular shapes lining up with the edge of the iris. hough transform is exceptionally effective at identifying parametric shapes, whose performance is evidenced when identifying the elliptical or circular iris boundary regardless of noise or occlusion. in contrast, however, if not fulfilling ideal conditions, noise will profusely be generated to interfere with the results of iris images, incurring a critical loss of accuracy concerning algorithm segmentation [2]. iris segmentation utilizing the hough transform and daugman’s algorithm was introduced by rafik and boubaker [9]. the authors of this study suggested calculating the iris and pupil radii sizes. therefore, it is possible to trim the radius of the pupil (r1) and the radius of the iris (r2) for accurate segmentation. daugman’s algorithm presupposes the unique and highquality patterns that lie in the iris images. nevertheless, ambient brightness, motion blur, and occlusions (e.g., eyelids or lashes) can deteriorate image quality and cause errors in ir. additionally, rapaka et al. [10] introduced a segmentation method for non-ideal iris images using morphology with fuzzy c-means (fcm) and dynamic spectrum access (dsa). however, similarly, environmental factors such as illumination, occlusions, image quality, etc., might further impact the accuracy of non-ideal iris images. thus, in summary, efficacy in practical situations requires the operator to choose the approach properly according to the surrounding conditions. in ir systems, deep learning, embodied by the convolutional neural network (cnn), has dominated computer vision research and has been envisaged to render remarkable effectiveness. functionally, deep learning can automatically extract useful and feature representations from the image data, facilitating the optimization concerning the performance of ir techniques [3, 11]. hence, ir techniques based on deep learning are being presented in the interim. currently, manifold deep cnn models emerge in the existing literature, e.g., googlenet, alexnet, residual neural network (resnet), and visual geometry groups [9]. table 1 summarizes the ir works based on deep learning. table 1 related works based on deep learning author method database accuracy omran and alshemmary [12] irisnet for extracting the attributes iit delhi* v1 original = 97.32% and normalized images = 96.43% alaslani and elrefaei [13] alexnet model with support vector machine iit delhi, casia 1.0 casia-v1, casia-iris-v3 100%, 98.3%, 98%, 89% advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 199 table 1 related works based on deep learning (continued) author method database accuracy minaee and abdolrashidi [14] residual cnn iit delhi 95.5% wang et al. [15] (micore-net) casiav4 and the ubiris.v2 99.08% and 96.12% azam and rana [16] cnn and svm casia 96.3% hsiao et al. [7] u-net and efficient net casia v1 up to 98%. alwawi and althabhawee [11] cnn private training 95.33%, testing 100% balasubramanian et al. [3] cnn multi dataset best accuracy 99.4% *: indian institute of technology delhi (iit delhi) as observed from the literature, segmentation becomes more challenging when there is vibration and occlusion from the lashes in the image. therefore, this study introduces multifarious methods to segment the iris images and find the region of interest (roi) of the iris while accounting for the unallocated feature in the images. this study contributes to the technique for image improvement, which subsumes binarizing the image using the maximum entropy, calculating the image histogram entropy function, and using the median filter to reduce noise. regarding binarization, this study used the histogram entropy information, which is the method extensively used for image thresholding. compared to other methods, the generic nature of the algorithm affects the feasibility of using a global and objective property of the histogram. subsequently, the iris dilates mathematically and separates from the desirable area of the images. as a result, the roi can be recovered as expected. specifically, dilation is used to identify the area within an image by progressively expanding the foreground pixel boundaries. to ensure the generation of details, the foreground pixels are enlarged while the holes within certain regions decrease. concerning the recognition, cnn is used. in multitudinous computer vision applications, such as image classification, object identification, and face recognition, cnn has shown unparalleled performance. utilizing cnn architectures specifically designed for ir can conduce to improved accuracy and reliability [12]. fig. 1 diagrammatically presents an illustration of the study. fig. 1 proposed study of iris recognition scheme synoptically, this paper enumerates the contents as follows. section 2 introduces the materials and methods. section 3 renders an elucidation of the recommended scheme, and section 4 presents the experiment’s findings. eventually, the conclusion is drawn in section 5. 2. materials and methods this section introduces the materials and methods of the ir scheme used in this study in detail, including image histogram, median filter, entropy, and morphology, which are used in the segmentation phase. meanwhile, the deep cnn structure used in the recognition phase is explained. furthermore, the mathematical concepts for each method have been provided. 200 advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 2.1. image histogram a histogram statistically represents the relationship between the pixel intensities and the frequency of occurrence of each intensity (0 to 255 in gray level) on the x-axis, which can be simply interpreted as the converse number of pixels on the y-axis. a histogram in image processing delineates the relationship between two images concerning the intensities at a specific moment. as formulated below, the histogram is presented [17]. a histogram is widely used in image processing for thresholding and segmentation steps. ( ) ( )=h i g i (1) 2.2. median filter the median filter is a straightforward nonlinear smoother, which can eliminate noise while retaining sharp, prolonged variations such as edges in signal values. therefore, the median filter is evidenced by the ability to mitigate impulsive noise [18]. the median value of the central input data inside the window is the output of the filter at a certain moment. if the value �(�) input image, while �(�) output image. meanwhile, both input and output of window size (2m + 1) are yielded with one-dimensional (1-d), and the output image after the median filter is given in: ( ) ( ) ( ){ }( ) , ( ) 1 ,= − − +… …y g med x g m x g x g g m (2) where 1 ≤ g ≥ r. here, �(1) and �( ), while ∈ �, are repeated (m) times at both the start and end of the input to account for startup and end impact. 2.3. entropy function in image processing, the measure of randomness or uncertainty in an image is measured by the entropy function. the entropy function measures the quantity of information or disorder in the pixel intensity distribution mathematically. moreover, the entropy function is frequently employed as a criterion for choosing an ideal threshold value in image binarization, where the objective is to convert a grayscale image into a binary image, i.e., black and white only. according to the threshold value, pixels are dichotomously classed as black and white. fundamentally, the concept entails determining the threshold and optimizing the entropy of the final binary image, which indicates that the threshold value is selected to produce a binary image with the maximum of information or randomness feasible. to determine the effectiveness, the results of separation between both foreground (items of interest) and background is proportional to entropy. the binarization is to efficiently separate objects from the background and, simultaneously, retain information at best in the final binary image by maximizing entropy. applications encompassing image processing, such as segmentation, optical character recognition (ocr), and object recognition, benefit greatly from binarization. the entropy function is presented: 1 0 ( ) log = = = − i i i i en h p p (3) 2.4. morphology a cluster of methods, which is known as morphological operations, are used in image processing to structurally examine and modify an object according to topological and spatial properties. morphological operations are useful for noise removal, feature extraction, object detection, and binary or grayscale images. images are transformed based on shapes using morphology. an input image requires a scale factor application throughout morphological processes to generate an identically sized output image. the value of each output pixel from a morphological operation can be ascertained by juxtaposing the pixels in the input image [19]. the process is depicted in: advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 201 = ×z z s (4) where z is the new image, z is the image, and s is the scale factor (s > 0) alternatively, given that lengths are cognitively positive, the value of the scaling factor will be multiplied after rendering as a modulus. in the suggested study, dilation is to gradually enlarge the borders of the foreground pixel regions to identify a broad space in the images. therefore, the area of foreground pixels expands while corresponding gaps are proximate to the features of the image [17]. morphology preponderantly requires ascertaining available design models, whether existing or nascent, to establish the topological structure with certain specifications. furthermore, this step purposively proceeds to opting several models for investigating the equivalent mechanism therein concerning the skeleton and kinematic chain. consequently, new designs can be developed. 2.5. convolutional neural network an artificial intelligence class, which is also known as deep cnns, can be used in sundry fields. meanwhile, deep learning picks up features per se. therefore, the primary objective is to enable a thorough comprehension of the material without requiring any manually created feature extraction [12]. cnn is typically employed in classification or image recognition. historically, this method was created in the 1980s, whereas it was reintroduced in 2012. currently, moreover, cnn is widely adopted in computer science. in addition to the presence of multiple hidden layers, cnn mimics the cerebral response by detecting visuals. by using several completely linked layers for classification and locally connected layers with automatic feature identification, cnn can automatically extract features [20]. specialized neural network types comprise the extraction feature of neural networks based on weight updates and training. as stated above, cnn transforms the manual feature extraction processes into an automated system. hence, each layer in cnn operates purposively and distinctly, while the network is composed of several layers [21]. the convolutional layer (convo) is a collection of learnable filters with a set of weights combined. the weight values were chosen at random and learned via the backpropagation approach. the features map, which filters the entire image with the learned weight [22], identifies the unique features in the initial input image and is calculated using the following, 1=   = × +    s s s r i i t z f w x b (5) where f is the activation function, b is a trainable bias parameter, and � � × � is a two-dimensional discrete convolution operator [23]. the common activation function used with cnn is the rectified linear unit (relu). the layer for pooling (pool) is the max-pooling layer determining the maximum value of a local patch (2 × 2 or 3 × 3) of the convolutional feature map output units. the process of max pooling is shown as: ( )0 ,, , , ,max ≤ < + + = i m n sj k j s m k s ny x (6) the ��,� which is computed over a (s × s) non-overlapped local area in the (ith) input map, represents a neuron in the (ith) output activation map. a fully connected (fc) layer, similar to a neural network, is the output of the last pooling or convolutional layers fed into fully connected layers (fc). the final layer of a cnn, known as the “softmax layer,” is used to categorize the features that were retrieved from earlier layers into n classes. the class membership probabilities are frequently output, transforming logit numbers into summative probabilities. the softmax operation can be computed, as shown in: softmax( ) =  i yi y i e e y j (7) 202 advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 3. proposed iris recognition scheme this section proposes an ir scheme that aims to address the aforementioned issues and achieve high recognition accuracy, benefiting from the methods that were explained earlier. the proposed scheme entails two phases. the first phase is to propose a segmentation algorithm including four steps. the second phase is to propose an ir method. the proposed scheme is enumerated in the following sections: 3.1. iris segmentation algorithm in this study, a state-of-the-art iris segmentation algorithm has been proposed to address vibration and occlusion from the lashes and extract the roi of the iris image. the segmentation algorithm has various steps which are shown in fig. 2 and explained in the following sentences. fig. 2 proposed iris segmentation algorithm (1) determine the image histogram: first, capture an iris image and transform it to a grayscale. then, utilizing eq. (1), compute the histogram to determine the distribution of pixel intensities in the image. the x-axis of the histogram represents the intensity levels (0-255), while the frequency of each intensity is shown on the y-axis. fig. 3 displays a sample histogram for a single iris image. fig. 3 representation of original and histogram image (2) apply median filter for gray image. fig. 4 shows an example of an iris image after applying a median filter. advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 203 fig. 4 representation of original and filtered image with a histogram-based median filter (3) maximum entropy value: first, determine the grayscale image’s probability distribution for the pixel intensities. then, use the entropy formula, i.e., eq (3), to find the entropy image. finally, output the maximum value of entropy after calculating the entropy values, and subsequently, determine the maximum entropy value. table 2 provides an example of the maximum entropy for an image. table 2 maximum entropy for an iris image max entropy value location (ppt) time (sec) 8.86030148358909 97 00:00:00.0428876 the maximum entropy value has been used as an adaptive threshold for the image. the threshold value is compared with all the intensities in the histogram. if the intensity value is larger than the threshold value, the intensity will be 1, and, in contrast, if it’s smaller than the threshold, it will be 0. the result is a binary image will be used in the next step. according to fig. 5, the filtered image is converted from gray to binary level by utilizing the maximum entropy value as a threshold. fig. 5 conversion from filtered to binary image via maximum entropy threshold (4) apply dilation morphology: use the dilation morphology on the binary image obtained in step 1 to extract the roi of the iris, which includes the iris and its content. the dilated image is black and white, where the black areas represent the objects, and the white areas serve as the background. to distinguish the iris region from the undesirable area of the images, four regions have been defined according to the proposed algorithm, as depicted in fig. 6. moreover, the regions are based on the computation of white and black points in each row and column in all four regions. finally, besides, the drawn rectangle region is the result. fig. 6 iris region segmentation with the proposed algorithm (5) transform to a gray image and convert the roi binary to gray, as shown in fig. 7. 204 advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 fig. 7 transformation of binary roi to gray roi 3.2. iris recognition scheme ir is the second phase in the proposed scheme, and the roi iris images are fed into the recognition step using cnn. cnns use convolutional and pooling layers to automatically extract information from the roi iris images. meanwhile, specifically, the features are the borders of iris, texture patterns, etc. the cnn requires itself to be trained on a dataset of labeled iris images before being used for recognition. the network learns to map the input roi iris images with matching iris identities during training. cnn can recognize iris images if having been trained. the stage herein involves feeding the trained cnn with the roi iris images. by using softmax activation in the output layer for classification tasks, the network subsequently outputs a probability distribution over sundry identities of the iris. typically, the most probable identity is selected to be the recognized identity. to evaluate whether the performance of a cnn-based ir system is effective, the recognition metrics such as accuracy and receiver operating characteristic (roc) curves are deployed. diagrammatically, fig. 8 illustrates the cnn representation. fig. 8 cnn representation 4. experimental results regarding the results, a scheme has been developed with multiple functions. the pre-processing step is applied initially, and afterward, the images are binarized. furthermore, the segmented images are recognized using the cnn classifier. in the recognition step, the accuracy rate, which is determined by the confusion matrix, is used as the criterion to assess the performance of the recommended scheme. the analysis is implemented using the windows 10 algorithms in c# (microsoft visual studio 2013). 4.1. database in this study, the iit delhi iris images database version 1.0 is utilized [24]. the majority of the iris scans in this database were taken from the students of the indian institute of technology, delhi, and personnel in india. the database was compiled using jiris, jpc1000, and cmos camera, in the biometrics research laboratory from january to july 2007. the advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 205 photos captured were stored in bitmap format. 2,240 photos in the database were collected from 224 individuals and rendered freely available to the researchers. the participants account for 176 men and 48 women who are all between the ages of 14 and 55. all of the images in this collection have a resolution of 320 by 240 pixels and were all taken indoors. all of the photographs in the database yielded from unpaid volunteers who received no payment or honoraria. participants must present their eyes sequentially until ten photos are registered for the images to be captured using an automated program. to examine the proposed scheme, every image in the database has been used. samples from the iit delhi dataset are shown in fig. 9. fig. 9 samples of the iit delhi dataset 4.2. result-based segmentation fig. 10 presents samples of correct iris image segmentation scheme steps using the proposed algorithm. however, the segmentation stage was hindered because of differences in iris images and occlusions of the eyelashes and lids incurring incorrect segmentation, as shown in fig. 11. fig. 10 iris image segmentation steps using the proposed algorithm 206 advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 fig. 10 iris image segmentation steps using the proposed algorithm (continued) fig. 11 samples of incorrect image segmentation to perform the computations and evaluate the flawed cropping manually, the accuracy can be determined based on [2526] using the formula below. = image image corect accurcy all (8) based on eq. (8), the accuracy of the proposed scheme reaches 93%. 4.3. results-based recognition the structure of the proposed cnn consists of two convo layers, two pool layers, one for each fc, and a softmax layer. the rate of learning is 0.0001. in addition, the standard stride size having been applied is equal to 1. two experiments are conducted. the first experiment uses half of the dataset’s images, and the second uses all of the images. the dataset used is categorized into 80% training and 20% testing. moreover, the pre-trained alexnet model has been employed to extract features. the accuracy rate of ratio recognition varies with the number of epochs, as shown in fig. 12. fig. 12 accuracy recognition rate advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 207 specifically, fig. 12 indicates the number of epochs is directly proportional to the performance. as a result, five epochs were considered in the final implementation. the recognition model outperforms smaller datasets due to growing excessively intricate and recording noises or random fluctuations in the data while working with similar image datasets. therefore, the accuracy reaches 97.5% when using the full dataset. on the other hand, the optimal accuracy reaches 98.8% when using half of the dataset. furthermore, fig.13 illustrates roc curves depicting the performance characteristics and demonstrating the accuracy of ir results. fig. 13 roc curve 5. conclusion in this study, two phases emerge to the proposed scheme, i.e., the segmentation method as the first phase and the ir technique based on cnn as the second phase. a major component of ir systems is iris segmentation algorithms. any biometric authentication system includes the segmentation step for improved recognition. the suggested scheme aims to identify an appropriate segmentation for images of the iris. these images include manifold locations, hindering the accessibility to determine the ideal roi. the proposed method uses the 2d histogram entropy during the binarization. morphological dilation is used to extract the roi while increasing the image’s level of detail. the results are regarded as the missing-cropped roi when the images are noticeably misaligned. the accuracy of the segmentation stands at approximately 93%. additionally, in the recognition phase, the accuracy reaches 98.8% using half of the dataset. meanwhile, the accuracy stands at 97.5% using the full dataset. roc curves show the accuracy of the findings of iris identification and illustrate the performance characteristics. concerning future work, the proposed iris scheme is envisaged to be used on another dataset. conflicts of interest the authors declare no conflict of interest. statement of ethical approval all procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 helsinki declaration and its later amendments or comparable ethical standards. statement of informed consent for this type of study, informed consent is not required. 208 advances in technology innovation, vol. 9, no. 3, 2024, pp. 197-209 references [1] i. s. hussein, s. b. sahibuddin, m. j. nordin, and n. n. b. a. sjarif, “multimodal recognition system based on highresolution palmprints,” ieee access, vol. 8, pp. 56113-56123, 2020. 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[26] i. s. hussein and n. n. a. sjarif, “human recognition based on multi-instance ear scheme,” international journal of computing, vol. 22, no. 3, pp. 397-403, october 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v8n1(2023)-aiti#9283(12-28).docx advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 dv-excccii based resistor-less current-mode universal biquadratic filter priyanka singh*, rajendra kumar nagaria department of electronics and communication engineering, motilal nehru national institute of technology allahabad, india received 20 january 2022; received in revised form 08 march 2022; accepted 16 march 2022 doi: https://doi.org/10.46604/aiti.2023.9283 abstract this study aims to present a new resistor-less current-mode multi-input single-output universal filter. the current-mode’s design approach is used to obtain the proposed circuit. this circuit employs a single differential voltage extra-x current controlled current conveyor (dv-excccii) and two grounded capacitors. this multifunction filter circuit offers low-pass, high-pass, all-pass, band-pass, and band-reject filters at a single output terminal without passive component matching constraints. the same circuit topology can obtain all second-order filter functions with different input conditions. the proposed circuit design is electronically adjustable with the bias current of dv-excccii. because of its high output impedance, this arrangement is suitable for cascading other current-mode circuits. the proposed circuit is simulated by cadence spectre with 0.18 µm umc cmos technology process parameters at ± 0.9 v supply voltages. the simulation results agree well with the theoretical concept of the proposed circuit. keywords: biquad filter, dv-excccii, electronically tunable, analog building block, current-mode filter 1. introduction analog filters are essential building blocks in several applications such as communication systems, analog signal processing, instrumentation systems, control engineering, signal generator, etc. analog filters eliminate undesired signals from the desired ones by allowing signals to pass at specific frequencies. analog filters may operate in multiple modes in integrated circuits, such as voltage, current, trans-admittance, and trans-impedance [1]. recently, there has been a growing trend in designing circuits using current-mode (cm) blocks. these circuits have numerous beneficial features, such as a high slew rate, higher linearity, good frequency performance, higher dynamic range, simple circuit design, and low voltage operation. over the period, several current-mode active blocks evolved [2-24]. some of the most important active blocks in the literature are ccii [2], cccii [3-4], dvcc [5-6], ofcc [7-8], cdta [9], moccii [10-11], vdta [12], iccii [13], cfta [15], vdcc [16], zc-cfta [17], doccii [18], mocca [19], mo-ccca [20], ccccta [21], ddcc [22], ex-cccii [23], dv-excccii [24], lt1228 [25], ftfnta [26], dxccta [27], fdccii [14, 28], and many more. various current-mode and voltage-mode filters using these active elements are available in the open literature. the cm filters employing dvcc are presented in [5-6]. the filter shown in [5] uses two dvccs, one floating, and four grounded passive components, whereas the filter proposed in [6] employs three dvccs and five grounded passive components. the use of more passive components increases circuit complexity. the electronically tunable filters with three ofccs and more passive elements are presented in [7-8]. two cdtas and one current amplifier-based electronically tunable filter are presented * corresponding author. e-mail address: priyankasingh@mnnit.ac.in tel.: +917839176964 advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 13 in [9]. this filter has high output impedance and uses two grounded capacitors. the filters employing three multi-output cciis are given in [10-11]. these filters are not electronically tunable. filters based on a single active element are described in [12, 14, 16, 22], whereas filters described in [13, 15, 17-21] use more analog blocks. an electronically tunable active element with an extra input current terminal is proposed later, and its first-order filter application is represented in [23]. a novel electronically tunable analog block with a differential input stage and an extra input current terminal is proposed in [24]. this active element has a wide application because it exhibits the properties of both dvcc and ex-cccii. a filter proposed in [24] uses a single dv-excccii and is electronically tunable. the voltage-mode filter presented in [25] employs two lt1228s, four resistors, and two capacitors. the use of more passive elements increases the area of the circuit. due to the reduction in the supply voltages, low voltage headroom is available in modern integration technologies. so, the voltage-mode filters suffer from low dynamic range and output swing limitation. therefore, the current-mode filters are preferred over the voltage-mode filters. this study describes a novel cm filter design which employs one dv-excccii and two capacitors. the proposed structure is resistor-less, and the capacitors employed in this structure are grounded, so it is preferable for ic implementation. due to its high output impedance, the proposed circuit can cascade the other current mode circuits. due to the bias current of dv-excccii, the proposed filter is electronically tunable. furthermore, the proposed filter does not need passive components matching conditions for the filter realization. the proposed structure can achieve all fundamental functions of a second-order filter, i.e., a low-pass filter (lpf), a high-pass filter (hpf), an all-pass filter (apf), a band-pass filter (bpf), and a band-reject filter (brf). although the proposed circuit can also be designed using ex-cccii, this study focuses on a filter circuit with a more generalized active element. as a result, a filter circuit is proposed using dv-excccii. the remnant of this study is structured as follows: section 2 presents the basic concept of dv-excccii. section 3 shows a detailed analysis of the proposed filter structure. this section also investigates the non-ideal effect of dv-excccii on the proposed circuit. section 4 compares the derived filter with previously available cm filters, whereas section 5 provides the simulation results. section 6 presents the practical implementation of dv-excccii, while section 7 presents various conclusion remarks. 2. basic concept of dv-excccii the dv-excccii [24] combines the merits of dvcc and ex-cccii which is already reported in the literature. the dvcc is a modified version of the current conveyor with a differential input stage. at the same time, the excccii is a variant of the current-controlled current conveyor with an extra-x terminal. the dv-excccii uses these two analog blocks with a differential input stage and an extra current terminal. the dv-excccii is an analog building block that can implement various current-mode and voltage-mode circuits. fig. 1 shows the symbol of dv-excccii, and fig. 2 shows its internal cmos representation. the relationship between the input and output terminal of dv-excccii is given by the matrix below, 1 1 2 2 1 11 2 22 1 1 2 2 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 y y y y x xx x xx z z z z i v i v v ir v ir i v i v ± ±                    − =     −         ±      ±         (1) the rx1 and rx2 are internal resistances at input terminals x1 and x2, respectively. the value of these internal resistances is, advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 14 1 2 0 1 8 ( ) x x x x o r r r w c i l µ = = = (2) here µ is the mobility, cox is oxide capacitance, w/l is the aspect ratio, and i0 is the bias current of an active block. the internal resistances rx1 and rx2 are used instead of external resistance, making the overall circuit implementation suitable for ic implementation. we can notice from the above expression that if the aspect ratios of transistors m2 and m3 are the same and m5 and m6 are the same, then intrinsic resistance at both current terminals will also be equal. transistors m21, m22, m23, and m24 generate a differential voltage (vy1–vy2) at the input current terminal (x1, x2). all z terminals used here are high output impedance terminals. this current-mode block has internal bias current i0, due to which dv-excccii offers electronic tunability. the positive sign of the z terminal indicates that the currents flowing through terminal x and terminal z are in the same phase. however, a negative symbol means that the current through the z terminal is out of phase from the current flowing through the x terminal. fig. 1 symbolic representation of dv-excccii fig. 2 internal structure of dv-excccii [26] 3. proposed universal filter 3.1. circuit analysis a single dv-excccii based proposed filter, displayed in fig. 3, can produce all five fundamental filters utilizing appropriate input combinations. this circuit can give the output current as, advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 15 2 3 2 1 1 2 1 2 2 1 1 1 2 2 1 1 2 1 2 (1 ) 1 x x x x out x x x i r c s r r c c s i r c s i i r c s r r c c s + + − + = + + (3) the intrinsic resistance at terminals x1 and x2 can be equal by matching the transistors m2, m3, m5, and m6, i.e., rx1 = rx2 = rx. the proposed circuit uses the following input combinations: (1) for lpf, response, i2 = i3 = 0 and i1 = iin are taken. (2) for hpf, i2 = i3 = iin and i1 = -iin are taken. (3) for apf, i2 = 2iin, i1 = 0, and i3 = iin are chosen. (4) for bpf, i2 = iin and i1 = i3 = 0 are chosen. (5) for brf, i2 = i3 = iin and i1 = 0 are taken. fig. 3 proposed biquadratic filter configuration the characteristic equation (d(s)) of the proposed circuit is, 2 1 2 1 2 2 1( ) 1x x xd s r r c c s r c s= + + (4) the angular frequency (ω0), bandwidth (bw), and quality factor (q) of the proposed filter are, 0 1 2 1 2 1 x x r r c c ω = (5) 1 2 1 x bw r c = (6) 1 2 2 1 x x r c q r c = (7) taking rx1 = rx2 = rx, it yields 0 1 2 1 x r c c ω = (8) 2 1 x bw r c = (9) advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 16 2 1 c q c = (10) eqs. (8)-(10) show that ω0 depends on the bias current, so the pole frequency can be adjusted by tuning i0. whereas q does not depend on i0, the change in the bias current would not affect the value of q. therefore, ω0 and q can be modified independently. the sensitivities due to passive components and intrinsic resistances are evaluated and given as, 0 0 0 0 1 2 1 2 1 2x xc c r r s s s s ω ω ω ω= = = = − (11) 1 2 2 1 1 2x x q q q q r c r c s s s s= = − = − = (12) 1 2 2 1 1; 0 x x bw bw bw bw r c r c s s s s= = − = = (13) eqs. (11)-(13) show that the sensitivities due to passive components and internal resistances are low. 3.2. non-ideal dv-excccii this section shows the influence of current and voltage gain errors in the response of the reported filter circuit. considering non-ideal dv-excccii, its port relationship is, 1 1 2 2 1 11 12 1 1 2 21 22 2 2 1 1 1 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 y y y y x x x x x x z z z z i v i v v r i v r i i v i v β β β β α α ± ± ± ±                        − =      −           ±       ±           (14) here, β11 and β12 are non-ideal voltage transfer gain coefficients from terminals y1 and y2 to x1, respectively. similarly, β21 and β22 are voltage transfer gain coefficients from y1 and y2 to the x2 terminal. whereas α1+ and α1are non-ideal current transfer gain coefficients from x1 to z1+ and z1terminals. similarly, α2+ and α2are coefficients from x2 to z2+ and z2 terminals, respectively. as explained earlier, all α coefficients are non-ideal current gain between z and x terminals, whereas all β coefficients are non-ideal voltage gain between x and y terminals. the value of α and β [29] are, 0( ) 1 s sα α α τ = + (15) 0( ) 1 s sβ β β τ = + (16) where �� = � �� and �� = � � . here � and � are angular pole frequencies. the dc voltage gain �� and current gain � are ideal unity, the voltage tracking error �� and current tracking error ��, as shown below, define the dc voltage and current gain. 0 1 ββ ε= + (17) 0 1 αα ε= + (18) these tracking errors are, ���� ≪ 1, |��| ≪ 1. advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 17 considering non-idealities of dv-excccii, the output current is, 3 2 1( ) ( ) ( ) out p s i q s i ri i p s − + = (19) where 2 1 2 1 2 12 1 2 1 1 2 2 22 2 1( ) (1 )x x x xp s r r c c s r c s r c sβ α α β α α+ − − += + + − + (20) 22 1 1 1( ) ( 1 ) x q s r c sβ α −= + − (21) 1 22r α β+= (22) the parameters, ω0, bw, and q are as follows, 22 2 1 0 1 2 1 2x x r r c c β α α ω − += (23) 12 1 1 1 2 1 1 2 (1 ) x c c bw r c c β α α+ −+ − = (24) 1 2 22 2 1 1 12 1 2 1 1 (1 ) c c q c c β α α β α α − + + − = + − (25) eqs. (23)-(25) show that the non-ideal dv-excccii slightly modifies the values of these parameters. considering non-ideal dv-excccii, the sensitivities of pole frequency are, 0 0 0 0 1 2 1 2 1 2x xc c r r s s s s ω ω ω ω= = = = − (26) 0 0 0 22 2 1 1 2 s s s ω ω ω β α α− + = = = (27) 0 0 0 0 0 11 12 21 2 1 0s s s s s ω ω ω ω ω β β β α α+ − = = = = = (28) eqs. (26)-(28) show that the sensitivities of the pole frequency considering non-idealities are below unity. 3.3. parasitic effect (a) block diagram of dv-excccii (b) proposed circuit fig. 4 circuit under the parasitic influence advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 18 fig. 4(a) shows the symbol of dv-excccii with its parasitic components. rx1 and rx2 are low-value parasitic resistances at ports x1 and x2. the parasites ry1//cy1 and ry2//cy2 appear at ports y1 and y2, respectively. furthermore, parasites rz1+//cz1+ and rz1-//cz1appear at ports z1+ and z1-, respectively, while rz2+//cz2+ and rz2-//cz2are parasites that appear at terminals z2+ and z2-, respectively. the values of ry1, ry2, rz1±, and rz2± are high, and that of cy1, cy2, cz1±, and cz2± are low. fig. 4(b) illustrates the proposed filter architecture when parasitic elements are present. some assumptions are taken into account to avoid mathematical complexity, and they are as follows: 1 1 2/ /eq z zr r r− −= (29) 1 1 1 2eq z zc c c c− −= + + (30) 2 2 1/ /eq y zr r r += (31) 2 2 2 1eq y zc c c c += + + (32) 1 1 1 11 eq eq eq r z sr c = + (33) 2 2 2 21 eq eq eq r z sr c = + (34) by considering the parasitic impedances of dv-excccii, the output of the proposed circuit is, 1 2 3( ) ( ) ( ) out ai b s i i d s i d s − + = (35) where, 1 2= eq eqa r r (36) 1 2 1 1( )= (1 )x eq eq eqb s r r sr c+ (37) 2( )d s as bs c= + + (38) here, 1 2 1 2 1 2x x eq eq eq eqa r r r r c c= (39) 2 1 2 1 1 2 1 1 1 2 2 2x eq eq eq x x eq eq x x eq eqb r r r c r r r c r r r c= + + (40) 1 2 1 2 2 2x x eq eq x eqc r r r r r r= + + (41) the parameters ω0, bw, and q of the filter under the influence of parasitic elements of dv-excccii are, 1 2 1 2 2 2 0 1 2 2 1 2 +x x eq eq x eq x x eq eq eq r r r r r r r r r c c ω + = (42) 1 2 1 1 1 1 1 2 2 1 1 2 1 2 eq eq eq x eq eq x eq eq x eq eq eq eq r r c r r c r r c bw r r r c c + + = (43) advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 19 1 2 1 2 1 2 1 2 1 2 2 2 1 2 1 1 1 2 2 2 2 1 2 1 ( + + )x x eq eq eq eq x x eq eq x eq x x eq eq x x eq eq x eq eq eq r r r r c c r r r r r r q r r r c r r r c r r r c = + + (44) the values of req1 and req2 are very high, hence eqs. (42)-(44) are reduced as follows: 0 1 2 1 2 1 x x eq eq r r c c ω = (45) 1 2 1 x eq bw r c = (46) 1 2 2 1 x eq x eq r c q r c = (47) eqs. (45)-(47) show that the filter parameters depend on the parasitic capacitances that are low in value. therefore, these parameters do not deviate much from the theoretical values. hence the performance of the filter is slightly affected by parasitic elements. 4. comparative study table 1 shows the comparison of the proposed circuit with the previously available biquadratic filters. a single active element and minimum passive components-based filter configurations are noteworthy. the use of more active and passive components increases chip area and, as a result, circuit complexity. the filter circuits given in [3-11, 13, 15, 17-21] employ more active elements. some filter circuits [3-8, 10-14, 16, 18, 20-21] use many passive components. furthermore, the grounded passive components-based structures are easy for ic implementation. the filters reported in [5, 11, 22] employ floating passive components. the realization of all fundamental filter responses of the biquadratic filter without passive component matching conditions is of great importance. it becomes easy to realize the filter functions that are not interrupted by component values. the value of the quality factor, bandwidth, and pole frequency will be affected by the matching condition applied to achieve filter responses and cannot be tuned arbitrarily. some filters [4-5, 16, 21-22] require matching constraints to realize the filter response. the filter circuit configurations with high output impedance can cascade other circuits. filters reported in [12, 16, 22] do not have high output impedance terminals. the filter parameters are usually a function of aging, temperature, and other environmental conditions, so a circuit having electronic tuning properties is preferred. however, several reported filters [10-14, 18, 22] are not electronically tunable. the proposed circuit can obtain all the fundamental second-order filters at a single terminal without any passive component matching constraints. this filter employs a single dv-excccii and two grounded capacitors. moreover, the proposed filter has high output impedance terminal, and it is also electronically tunable. 5. simulation results the reported dv-excccii based current-mode filter is verified using cadence virtuoso spectre simulator in 0.18 µm umc cmos technology. the dc power supply voltages vdd = -vss = 0.9 v are used for simulations. table 2 shows the aspect ratio of all mos transistors used. the capacitor values are taken as c1 = c2 = 50 pf in all the simulations. the bias current i0 = 100 µa is taken to get rx1 = rx2 = 813 ω. as a result, the pole frequency and quality factors are 3.9 mhz and 1, respectively. advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 20 table 1 comparative study reference abb type no. of abbs number of resistors number of capacitors high output impedance tunability technology power supplies (v) matching required universal power consumption (mw) thd (%) frequency (f0) area floating grounded floating grounded [3] cccii 5 0 0 0 3 yes yes bjt ± 2.5 no yes ----318.3 khz -- [4] cccii 5 0 0 0 3 yes yes 0.13 µm ± 0.75 yes yes 5.48 > 6 33.86 khz -- [5] dvcc 2 1 2 0 2 yes yes 0.13 µm ± 0.75 yes yes 0.81 > 4 3.18 mhz -- [6] dvcc 3 0 3 0 2 yes yes 0.18 µm ± 0.9 no yes 0.462 > 5 3.18 mhz 0.0208 mm2 [7] ofcc 3 0 3 0 2 yes yes 0.5 µm ± 1.5 no yes ----320 khz -- [8] ofcc 3 0 2 0 2 yes yes 0.5 µm ± 1.5 no yes ----1.59 mhz -- [9] cdta, ca 2, 1 0 0 0 2 yes yes 0.18 µm ± 0.9 no no 1.15 > 7 1 mhz -- [10] moccii 3 0 3 0 2 yes no 0.35 µm ± 1.65 no yes ----198.9 khz -- [11] moccii 3 2 3 0 2 yes no 0.18 µm ± 1.25 no yes ----281.35 khz -- [12] vdta 1 0 1 0 2 no no 0.18 µm ± 1 no yes -------- [13] iccii 3 0 4 0 2 yes no 0.18 µm ± 0.8 no yes 0.674 1.12 159 mhz -- [14] fdccii 1 0 2 0 2 yes no 0.35 µm ± 1.3 no yes --3 1.59 mhz -- [15] cfta 4 0 0 0 2 yes yes bjt ± 3 no yes --1.8 153 khz -- [16] vdcc 1 0 2 0 2 no yes 0.18 µm ± 0.9 yes yes 0.72 2.48 8.9 mhz -- [17] zc-cfta 4 0 0 0 2 yes yes bjt ± 3 no yes 12.2 3 159 khz -- [18] doccii, docciii 2, 1 0 2 0 2 yes no 0.5 µm ± 2.5 no yes ----34 khz -- [19] cccii, mocca 2, 1 0 0 0 2 yes yes 0.5 µm ± 1.5 no yes ----39 khz -- [20] doccii, mo-ccca 2, 1 0 2 0 2 yes yes 0.35 µm ± 1.5 no yes --6 1 mhz -- [21] ccccta 2 0 0 0 2 yes yes bjt ± 1.75 yes yes ----2.62 mhz -- [22] ddcc 1 1 1 0 2 no no 0.18 µm ± 0.9 yes yes 0.159 > 5 1.64 mhz -- [26] ftfnta 1 1 1 2 0 yes no 0.18 µm ± 1.65 yes no ----163 khz -- [27] dxccta 1 0 1 0 2 no yes 0.18 µm ± 1.25 no yes ----40 mhz -- [28] fdccii 1 1 1 0 2 yes no 0.35 µm ± 1.65 no yes ----1 mhz -- proposed work dv-excccii 1 0 0 0 2 yes yes 0.18 µm ± 0.9 no yes 2.05 > 6 3.9 mhz 678 µm2 table 2 transistor dimensions of dv-excccii transistors w(µm)/l(µm) m1-m3 12/0.5 m4-m6 16/0.5 m7-m20 12/0.5 m21-m24 10/0.5 m25-m37 20/0.5 advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 21 fig. 5(a) represents the frequency response of lpf, hpf, bpf, and brf. whereas fig. 5(b) depicts the magnitude and phase variation of the all-pass filter against frequency. the attenuation at the low frequencies is due to the parasitic elements of dv-excccii. fig. 6 represents the transient analysis of the circuit. a sinusoidal input of 3.9 mhz and amplitude of 50 µa is applied to apf, which results in 1800 phase-shifted output that confirms the theoretical concept. (a) magnitude response of lpf, hpf, bpf, and brf (b) magnitude and phase response of apf fig. 5 frequency response of the proposed filter fig. 6 time-domain response of the proposed current-mode apf (a) lpf (b) hpf (c) apf fig. 7 electronic tuning characteristics using different i0 advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 22 (d) bpf (e) brf fig. 7 electronic tuning characteristics using different i0 (continued) fig. 7 shows the tunable characteristic of the presented filter by using different bias currents. fig. 7(c) shows the phase variation of apf at distinct bias currents, whereas figs. 7(a), (b), (d), and (e) depict the magnitude responses for different i0 of lpf, hpf, bpf, and brf, respectively. the quality factor can be tuned by taking various c1 and c2 values. in this way, q can be tuned independently with ω0. fig. 8 shows the frequency response of the proposed filter by choosing various combinations of c1 and c2. the gain response of lpf, hpf, brf, apf, and bpf is shown in figs. 8 (a), (b), (c), (d), and (e), respectively. (a) lpf (b) hpf (c) brf (d) apf (e) bpf fig. 8 magnitude response for different capacitors advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 23 next, the effect of the process, supply, and temperature variations on the apf phase response is represented. fig. 9(a) illustrates the phase response of apf at different process corners. the five different corners taken for simulation are typical, fast-fast (ff), fast n-mos slow p-mos (fnsp), slow n-mos fast p-mos (snfp), and slow-slow (ss). the supply voltage variation effect on the proposed filter is shown in fig. 9(b) using different supply voltages as vdd = -vss = 0.95 v, 0.9 v, and 0.85 v. the effect of temperature on the filter response can be examined by using various temperature levels. fig. 9(c) shows the temperature variation effect using temperature values as -50°c, 0°c, 27°c, and 50°c. table 3 summarizes the pole frequencies of apf due to process, voltage, and temperature variations. table 3 pole frequency of apf for different corners, voltages, and temperatures variation different values pole frequency (mhz) process typical 3.98 ff 4.26 fnsp 3.90 snfp 3.92 ss 3.74 voltage vdd = -vss = 0.85 v 3.54 vdd = -vss = 0.9 v 3.98 vdd = -vss = 0.95 v 4.32 temperature -50°c 4.43 0°c 4.22 27°c 3.98 50°c 3.87 (a) process variation (b) supply variation (c) temperature variation fig. 9 phase response of apf at different variations the monte-carlo analysis is performed with 500 runs for the center frequency of bpf to test the filter performance against process variation. the histogram is shown in fig. 10 for bpf with a mean value of 3.93 mhz. the mean value slightly deviates from the theoretical value. the noise immunity of the circuit is investigated next. fig. 11 shows the input and output noise of bpf with a 1 kω load resistor. tables 4 and 5 show the input and output noise of the bpf at different process corners. advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 24 table 4 summarizes the input and output noise at different frequencies for 100 µa input current. in addition, table 5 represents the input and output noise for different bias currents at 1 hz frequency. the values show that the noise increases with the bias current and decreases with frequency. fig. 10 monte carlo simulation result for bpf (a) input noise (b) output noise fig. 11 frequency response of noise of bpf table 4 noise at various corners for different frequencies at 100 µa bias current frequency input noise (in) (a/√hz) output noise (on) (v/√hz) different process corners typical ff fnsp snfp ss 1 mhz in 3.02×10-5 2.39×10-5 2.37×10-5 3.93×10-5 3.94×10-5 on 4.33×10-4 4.92×10-4 4.19×10-4 4.45×10-4 3.66×10-4 1 hz in 1.09×10-6 8.63×10-7 8.61×10-7 1.4×10-6 1.41×10-6 on 1.56×10-5 1.78×10-5 1.53×10-5 1.59×10-5 1.32×10-5 1 khz in 4.38×10-8 3.46×10-8 3.46×10-8 5.63×10-8 5.66×10-8 on 6.27×10-7 7.15×10-7 6.14×10-7 6.38×10-7 5.28×10-7 100 khz in 2.76×10-9 2.93×10-9 2.50×x10-9 2.99×10-9 2.25×10-9 on 7.58×10-8 8.62×10-8 7.42×10-8 7.70×10-8 6.4×10-8 1 mhz in 1.23×10-10 1.53×10-10 1.18×10-10 1.26×10-10 9.24×10-11 on 2.98×10-8 3.31×10-8 2.93×10-8 3.02×10-8 2.61×10-8 100 mhz in 4.14×10-10 3.97×10-10 4.13×10-10 4.17×10-10 4.36×10-10 on 1.52×10-8 1.65×10-8 1.46×10-8 1.57×10-8 1.37×10-8 table 5 noise at various corners for different bias currents at 1 hz frequency bias current input noise (in) (a/√hz) output noise (on) (v/√hz) different process corners typical ff fnsp snfp ss 20 µa in 39.54×10-9 36.03×10-9 38.87×10-9 40.24×10-9 44.65×10-9 on 3.8×10-6 4.03×10-6 3.84×10-6 3.79×10-6 3.59×10-6 40 µa in 129.2×10-9 112.0×10-9 126.3×10-9 132.0×10-9 156.2×10-9 on 7.23×10-6 7.77×10-6 7.38×10-6 7.18×10-6 6.74×10-6 60 µa in 320.8×10-9 243.6×10-9 282.7×10-9 342.3×10-9 420.2×10-9 on 11.13×10-6 11.15×10-6 10.41×10-6 11.24×10-6 10.22×10-6 100 µa in 1.09×10-6 8.63×10-7 8.61×10-7 1.4×10-6 1.41×10-6 on 1.56×10-5 1.78×10-5 1.53×10-5 1.59×10-5 1.32×10-5 advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 25 fig. 12 shows the total harmonic distortion (thd) variation of the output of bpf. a peak-to-peak sinusoidal input is applied at a 3.9 mhz frequency. the curve of fig. 12 shows that the thd increases with the applied input current. fig. 13 shows the layout of dv-excccii, which has an area occupancy of 45.2 m 15 m. the suggested universal filter is also subjected to a post-layout simulation. fig. 14(a) shows the post-layout gain response of lpf, hpf bpf, and brf. fig. 14(b) depicts the post-layout gain and phase response of apf. fig. 12 thd variation of bpf fig. 13. layout of dv-excccii (a) gain response of lpf, hpf, bpf, and brf (b) gain and phase response of apf fig. 14. post-layout simulation of the proposed circuit 6. practical consideration the proposed cmos-based active element dv-excccii can be practically realized with commercially available cfoa (ic ad844). fig. 15 represents the implementation of dv-excccii using ic ad844. an ideal ad844 has zero input resistance at the inverting terminal and infinite resistance at the non-inverting and z terminals. furthermore, the voltage applied at the non-inverting terminal is reflected at the inverting terminal due to the virtual short effect. the current applied to advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 26 the inverting terminal is reflected at terminal z. to obtain the differential voltage, two ad844s are connected through a resistor r1 at their inverting terminals. the voltage signals are applied at the non-inverting terminals. the terminal z of the first ad844 is further connected to the non-inverting terminals of the third and fourth ad844. the following analysis can obtain the voltages at the x1 and x2 terminal in fig. 15. 1 2 0 y y i i= = (48) 1 1z x i i+ = (49) 2 2z x i i+ = (50) 1 2 2 1 1 y y v v i i r − = = (51) 2 1 2 2 2 1 2 1 ( ) x x y y r v v i r v v r = = = − (52) fig. 15 dv-excccii implementation using ic ad844 fig. 16 implementation of the proposed circuit using ic ad844 eq. (52) shows that the differential voltage at terminals x1 and x2 of fig. 15 can be obtained if r1=r2 is set. fig. 16 shows the implementation of the proposed circuit using ic 844. the proposed universal filter shown in fig. 3 is practically advances in technology innovation, vol. 8, no. 1, 2023, pp. 12-28 27 realized with the ic ad844 model in the ltspice tool. fig. 17 shows the time-domain response of the apf with a sinusoidal input of an amplitude of 100 µa at 3.9 mhz. the output obtained is 180° phase-shifted with the applied input signal. the result confirms the theoretical concept of the filter. fig. 18 shows the thd variation of apf with a peak-to-peak sinusoidal input of 3.9 mhz. this curve indicates that the thd increases with the applied input current. fig. 17 transient response of apf using ic ad844 fig. 18 thd variation of apf 7. conclusion this study presents a resistor-less universal filter using one dv-excccii and two capacitors. this circuit can implement all fundamental filters of a biquadratic filter with the same circuit configuration without passive component matching constraints. this circuit is electronically tunable, and also it is cascadable because of its high output impedance. the non-ideal analysis and monte carlo simulation are performed to indicate the satisfactory response of the proposed circuit under the influence of non-idealities and mismatches. the presented filter circuit is verified using cadence spectre, and the simulation results of the proposed filter are found to be in good agreement with the proposed theory. conflicts of interest the authors declare no conflict of interest. references [1] c. n. lee, “multiple-mode ota-c universal biquad filters,” circuits, systems, and signal processing, vol. 29, no. 2, pp. 263-274, april 2010. 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[29] a. fabre, o. saaid, and h. barthelemy, “on the frequency limitations of the circuits based on second generation current conveyors,” analog integrated circuits and signal processing, vol. 7, no. 2, pp. 113-129, march 1995. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v9n4(2024)-aiti#13951(287-300).docx advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 english language proofreader: yen-chun hsieh performance evaluation of neural network models for autism detection using eeg data nazmul hasan1,*, priyasha paul2, manisha jitendra nene1 1school of computer engineering and mathematical sciences, defence institute of advanced technology, pune, india 2department of biosciences, manipal university jaipur, jaipur, india received 01 july 2024; received in revised form 31 july 2024; accepted 02 august 2024 doi: https://doi.org/10.46604/aiti.2024.13951 abstract this study aims to leverage a promising avenue for the precise and early detection of autism. autism is a multifaceted neurodevelopmental condition marked by challenges in social interaction, communication, and repetitive behaviors. traditional diagnosis relies on time-consuming behavioral assessments, necessitating reliable and non-intrusive biomarkers for early and accurate detection. this paper analyzes eleven linear and non-linear features across time and frequency domains from an eeg dataset. four neural network models, such as convolutional neural network (cnn), deep neural network (dnn), long short-term memory (lstm), and a custom neural network are employed for classification. the cnn achieves the lowest accuracy at 89.02%, while the custom neural network reaches the highest accuracy at 94.02%, and the dnn and lstm achieve 91.98% and 93.83% accuracy, respectively. other metrics such as precision, recall, specificity, and f1-score, are also evaluated. this research underscores the efficacy of neural network in detecting autism, advancing diagnostic tools. keywords: autism, detection, eeg, machine learning, neural network 1. introduction autism spectrum disorder (asd) is a complex neurodevelopmental condition characterized by a spectrum of challenges, including difficulties in communication, response, attention, social behavior, and repetitive activities [1-7]. beyond these primary symptoms, individuals with asd exhibit atypical neural activity patterns [8]. diagnosing autism presents complexity owing to its diverse symptoms and their varying degrees among individuals [9]. early detection and intervention are crucial for optimizing outcomes and providing appropriate support for individuals with asd [10]. the present diagnostic approach for asd predominantly depends on subjective and time-consuming behavioral assessments [11]. the recent research explores diverse physiological markers such as eye tracking, functional magnetic resonance imaging (fmri), and gait movements for identifying patterns to facilitate more accurate early diagnosis of autism and improve intervention techniques [12-14]. another promising avenue in this pursuit involves analyzing electroencephalogram (eeg) data [15]. eeg signals capture subtle electrical fluctuations in the brain, presenting valuable information about neural responses to various stimuli [16]. eeg data also provides insights into brain function and connectivity, offering the opportunity to explore neural processes [17]. the recognition of atypical neural activity in individuals with autism has interest in utilizing eeg data as a potential biomarker for asd [18]. recent advancements in the machine learning (ml) approach for eeg analysis have shown promise in addressing this need [19-21]. several studies have explored the use of ml techniques to analyze eeg data for asd detection [22-24]. however, there is still a need for more comprehensive studies that explore a broader range of neural network (nn) models and feature selections. * corresponding author. e-mail address: nazmulcse10@gmail.com 288 advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 this study aims to leverage this promising avenue by exploring eleven distinct linear and non-linear features across time and frequency domains from eeg data. by employing four nn models such as a convolutional neural network (cnn), deep neural network (dnn), long short-term memory (lstm), and a custom nn—this research seeks to enhance the precision and early detection of autism. the performance of these models is evaluated using accuracy, precision, recall, specificity, and f1score metrics. in this study, ml-based nn is employed to classify asd using eeg signal analysis. the primary objective is to implement and evaluate the different ml-based nn models, including deep and custom-designed nns, for accurately identifying patterns in eeg data that are indicative of asd. by focusing solely on eeg data, the study of this paper provides a comprehensive understanding of the potential of eeg-based biomarkers for autism detection. this paper represents a significant contribution by presenting highly accurate models for identifying asd solely through eeg signal analysis. the outcomes of this research offer potential tools for early detection of autism, addressing a critical need in the field. furthermore, this analysis enhances the understanding of the neural characteristics associated with asd and lays the groundwork for the development of targeted interventions and therapies. the subsequent sections of this paper are structured as follows: section 2 provides an overview of related research works in the field of eeg-based autism detection. section 3 presents the methodology for the study of this paper, including the dataset and extracted features. section 4 presents the nn models employed in this study. section 5 presents the results of this study. finally, section 6 provides a discussion and conclusion on the findings of this study. 2. related works extensive research has been dedicated to the analysis of eeg signals for autism detection. some of the key findings in current research on autism detection through eeg signals using ml are highlighted in this section. table 1 provides a comprehensive summary of research on eeg analysis for autism detection using various ml approaches. table 1 highlights and comparison of the existing research works reference publicati on year ml approaches extracted features participants asd/td classificatio n accuracy heunis et al. [19] 2018 lda, mlp, and svm rqa 16/46 92.9% haputhanthri et al. [20] 2019 lr, svm, nb, and rf statistical features (mean and standard deviation) 10/5 93% abdolzadegan et al. [21] 2020 knn power spectrum, wavelet transform, fft, fractal dimension, correlation dimension, lyapunov exponent, entropy, detrended fluctuation analysis, synchronization likelihood 34/11 72.77% svm 90.57% radhakrishnan et al. [22] 2021 dnn automatic feature extraction and classification 10/10 81% garcés et al. [23] 2022 linear support vector classifier (svc), elastic net lr, radial basis function svc power spectrum and functional connectivity 212/199 56% to 64% peketi and dhok [24] 2023 ebt, svm with a fine gaussian kernel, and artificial neural network (ann) linear and non-linear features across time and frequency domains 15/0 91.12% this study 2023 cnn linear and non-linear features across time and frequency domains 13/4 89.02% dnn 91.98% lstm 93.83% custom nn 94.02% the existing studies employed diverse approaches including linear discriminant analysis (lda), multi-layer perceptron (mlp), support vector machine (svm), logistic regression (lr), naive bayes (nb), random forest (rf), k-nearest neighbor (knn), dnn, and ensemble bagged tree (ebt) [19-24]. feature extraction techniques encompassed recurrence quantification advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 289 analysis (rqa), statistical features, power spectrum analysis, wavelet transforms, fast fourier transform (fft), fractal dimension, correlation dimension, lyapunov exponent, entropy, detrended fluctuation analysis, synchronization likelihood, linear and non-linear features across time and frequency domains [19-24]. classification accuracy across these studies ranged from 56% to 93%, showcasing the potential of ml in accurately discerning asd patterns from typically developing (td) individuals, thereby contributing to the development of effective diagnostic tools and interventions [19-24]. this study is distinct from earlier research in its eleven time and frequency domain features selection in distinguishing between eeg patterns associated with td and individuals with asd. this elevated level of accuracy highlights the study’s importance as it offers a more precise and dependable tool for the early detection of autism. these results hold significant promise for contributing substantially to both autism research and clinical applications. 3. methodology this section details the approach taken in this research to analyze eeg data from children diagnosed with asd and td. this study utilizes the global datasets for autism disorder, which includes high-quality eeg recordings obtained under controlled conditions, ensuring reliability in the data. a detailed feature extraction process is conducted to derive both timedomain and frequency-domain characteristics, providing a comprehensive understanding of the underlying neural patterns. by integrating these features, the study aims to effectively differentiate between the two groups using ml models. 3.1. dataset overview the dataset utilized in this research, known as the global datasets for autism disorder, is obtained from the brain-computer interface (bci) group at king abdulaziz university (kau) with the necessary permissions for this study [25]. comprising eeg recordings from two distinct groups, the dataset includes thirteen boys, aged 10 to 16 years, diagnosed with asd in the first group. the second group consists of four td boys, aged 9 to 16 years. the eeg signals were recorded during participants’ relaxed states to ensure artifact-free data, using the g.tec eegcap, 16 ag/agcl electrodes, g.tec gammabox, g.tec usbamp, and bci2000 system. the eeg data were acquired from 16 electrodes, including fp1, fp2, f7, f3, fz, f4, f8, t3, c4, cz, c3, t5, pz, o1, oz, and o2 according to the 10-20 international system. the anterior frontal z (afz) electrode served as ground (gnd), while the right ear lobe was used as reference (ref). the recorded data were filtered using a bandpass filter within the frequency range of 0.1-60 hz and a notch filter at 60 hz, subsequently digitized at 256 hz. this dataset is chosen for its comprehensive and controlled acquisition method, providing high-quality, reliable eeg data crucial for distinguishing between asd and td children. initially, the data is segmented into fixed-length epochs, and any null values are removed to ensure accurate feature extraction. the total number of epochs in the dataset for initial and after preprocessing are 5437 and 5402 respectively, and their distribution between the training and testing sets are 4321 and 1081 respectively. this information is crucial for understanding the dataset’s overall size and composition, which is important for ensuring the accuracy and generalizability of any nn models trained on it. additionally, understanding the distribution of epochs in the training and testing sets helps identify any potential biases or imbalances in the data. 3.2. extracted features the study explores eleven distinct linear and non-linear features across time and frequency domains from an eeg dataset utilizing ml-based nn models. these features encompass a variety of statistical, spectral, and signal processing measures, contributing to the analysis and interpretation of eeg data. out of eleven features, six are time domain and five are frequency domain features. the explored features are discussed below. 290 advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 mean: the mean is a statistical measure that represents the average value of a set of numbers or data points. the mean is computed mathematically by adding all of the values in the dataset and dividing the total number of data points. having a dataset with � data points, denoted by ��, ��, ��,…, ��, the mean ( ) can be calculated as: 1 2 3µ + + + + = … nx x x x n (1) quantile: based on a collection of input features, quantile ml involves calculating the conditional quantiles of a target variable. the purpose of quantile is to discover a mathematical function that links the quantiles of the target variable with the input features �. let’s denote the conditional quantile of at a given percentile � as � ( |�). the quantile regression minimizes the weighted absolute loss function, as shown in the following equation. given the input characteristics �, �(�) here denotes the expected quantile of . based on the specified quantile level �, the loss function penalizes the errors. ( ) ( ) ( ) ( ), ( ) 1 max 0, ( ) max 0, ( )= − × − + × −ql y f x q y f x q f x y (2) svd entropy: the singular value decomposition (svd) and shannon entropy are used to quantify the randomness of a dataset. it gives a measurement of the dataset’s level of uncertainty. the shannon entropy mathematical formula is used to determine the svd entropy. the average amount of information or uncertainty in a dataset is measured by shannon entropy, as shown below. ( )2log ( )= − ×entropy p p (3) here, � denotes the probability distribution of the singular values and ∑ denotes the sum. peak-to-peak amplitude (ppa): ppa is an ml feature that measures the difference between the maximum and minimum values of a signal within a given time interval, as shown in the following equation. it is commonly used in various signalprocessing applications, including audio and vibration analysis. ( ) ( )max min= −ppa x x (4) the max (�) represents the maximum value of the signal within the specified time interval. the min (�) represents the minimum value of the signal within the specified time interval. energy frequency bands: energy frequency bands record data on the signal’s energy distribution across several frequency bands. considering a signal �(�) and applying the fourier transform to obtain its frequency-domain representation �(�), where � represents frequency. the frequency range is divided into bands, such as the low-frequency, mid-frequency, and highfrequency bands. by adding the squared magnitudes of the fourier coefficients within the respective frequency range, it computes the energy inside each band. the energy �� within a frequency band � is computed, as shown below. 2 ( )=ie x f (5) here, � is the frequency range of band �. spectral edge frequency (sef): this characteristic in machine learning describes the distribution of frequencies in a signal, as shown in the following equation. it demonstrates how much high-frequency content is in a signal, information that can be helpful in a variety of applications, including audio and image processing. [ ] [ ] 0, ( ) 0, ( ) × = ∝ ×   f f p f df sef f p f df (6) here, �(�) is the power spectral density (psd) of the signal and � represents the frequency. advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 291 standard deviation (sd): this metric quantifies the dispersion of the feature values around the mean. in ml, sd is frequently used as a feature engineering technique to assess a feature’s importance in predictive models and capture its variability, as shown below. ( ) 21 µ= × − isd x n (7) here, the dataset’s total number of data points is �. each distinct feature value is represented by the ��. the represents the feature values’ mean. the ∑ stands for the total of the squared disparities. hjorth mobility (hm): this parameter reveals the frequency content and signal variations. a signal with a greater mobility value denotes one with a higher frequency content or rate of change, whereas a signal with a lower mobility value denotes one with a lower frequency content or rate of change. it is determined using the three statistical measurements known as the hjorth parameters that are deduced from the signal. activity (a), mobility (m), and complexity (c) are the three hjorth parameters, as shown below. = m hm a (8) spectral entropy (se): a characteristic used in ml and signal processing to measure the spectral complexity or information content of a signal’s frequency spectrum, as shown in the following equation. for se, the signal’s psd, which depicts the signal’s power distribution across several frequencies, is necessary. methods like the fourier transform or the periodogram are used to obtain the psd. ( )2 ( ) log ( )= − ×  se p f p f (9) here, the summation is done over the entire range of frequencies, and �(�) indicates the normalized psd at frequency �. skewness: skewness is a statistical metric used in data analysis and ml to express the asymmetry from symmetry in a data distribution. it reveals details about the distribution’s shape, including whether it is skewed left or right. a dataset’s skewness is mathematically determined as the third standardized moment, as shown below. 3 µ σ  −  =        x skewness e (10) here, � is the data point, is the dataset mean, � is its sd, and � stands for the anticipated value. kurtosis: kurtosis is a statistical index used in data analysis and ml to describe the peak or flatness of a data distribution. it reveals details about the distribution’s shape, including if it has thick tails or a denser center than a typical distribution. the fourth standardized moment is used to calculate a dataset’s kurtosis, as shown below. 4 µ σ  −  =        x kurtosis e (11) time-domain and frequency-domain features are selected in this study for their complementary roles in capturing different aspects of eeg signals. time-domain features (such as mean, sd, and hm) provide insights into the statistical and temporal characteristics of the eeg data, revealing patterns and variations over time. frequency-domain features (such as svd entropy, energy frequency bands, and se) analyze the spectral content, identifying the distribution of signal power across various frequency bands, which is crucial for understanding the underlying neural oscillations and rhythmic activities. this combination ensures a comprehensive analysis, enhancing the ability to distinguish between asd and td children. 292 advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 4. neural networks employed for autism detection the study utilizes eeg analysis to distinguish between asd and td children, employing four distinct nn models: cnn, dnn, lstm, and a custom-designed nn model. the cnns are chosen for their ability to capture spatial hierarchies in data, making them effective in extracting spatial features from eeg signals. the dnns are included for their capacity to learn complex representations and intricate relationships within the high-dimensional eeg data. the lstms are selected due to their proficiency in learning temporal dependencies, which is crucial for analyzing sequential eeg data and capturing longterm patterns. lastly, the custom-designed nn model is tailored specifically to the eeg dataset and classification task, allowing for the incorporation of domain-specific knowledge and fine-tuning for optimal performance. this combination of models leverages their respective strengths in spatial, complex, temporal, and customized feature extraction, enhancing the accuracy and reliability of distinguishing between asd and td children. 4.1. convolutional neural network model the cnn model (fig. 1) for binary classification between td and asd using eeg data comprises the input data with a reshaped layer to a suitable shape for conv1d layers, as follows. ( )reshape , _ . ,=reshapedx x batch size i c (12) here, � is input data and � is the number of channels after reshaping the data. the conv1d layers ( �) of the employed cnn model performed convolutions with kernels (!�), and biases ("�) followed by rectified linear unit (relu) activation, as follows. ( )relu= × +i i i iy w x b (13) here, relu is defined in the following equation. ( ) 0, 0 relu , 0 < =  ≥ if x x x if x (14) the maxpooling1d layers reduce the spatial dimensions, as follows. ( )maxpooling1d , _=i iz x pool size (15) the globalmaxpooling1d operation across the temporal dimension produces a vector output, as follows. ( )globalmaxpooling1d=g x (16) dense layers perform fully connected operations with weights (!#), biases ("#), and activations. the dense operation for a layer can be written as follows. ( )activation= × +i il ly w x b (17) here, activation represents relu for hidden layers, and sigmoid for the output layer is shown below. ( ) 1 1 − = + x sigmoid x e (18) the employed cnn model is compiled using the adam optimizer and binary cross-entropy loss, monitoring accuracy as a metric. during training, the model learns training data for 50 epochs using a batch size of 60 and evaluates its performance on validation data. after training, the model is evaluated on test data, calculating the loss and accuracy metrics. finally, predictions are generated using the trained model on the test data, producing predicted probabilities. advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 293 fig. 1 architecture of the cnn model employed in the study 4.2. deep neural network model the dnn model employed for the study (fig. 2) comprises three dense layers. the initial layer consists of 128 neurons and employs the relu activation function, as follows. ( )1 1 1relu= × +output w x b (19) here, !� represents the weight matrix, $ denotes the input data, "� is the bias term, and relu, represented by eq. (13), represents the activation function. the second dense layer contains 64 neurons and also uses relu activation, as shown in the following equation. this layer introduces further non-linearity to capture complex patterns in the data. ( )2 2 1 2relu= × +output w output b (20) the final dense layer consists of a single neuron using the sigmoid activation function, as shown below. ( )3 2 3sigmoid= × +finaloutput w output b (21) similar to the employed cnn model, the dnn model in this study is compiled using the adam optimizer and binary cross-entropy loss while monitoring accuracy. the training phase involves iterating over the training data for 50 epochs with a batch size of 60, utilizing validation data for validation purposes. fig. 2 architecture of the dnn model employed in the study 294 advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 4.3. long short-term memory model the employed lstm model (fig. 3) firstly reshapes the input data $%&'�� and $%()% for lstm input compatibility. an lstm layer is added to the sequential model. it consists of 64 neurons and utilizes the relu activation function. the lstm cell operates as follows. [ ]( )1 ,σ − = × +t i t t ii w h x b (22) [ ]( )1 ,σ −= × +t t tf ff w h x b (23) [ ]( )1 tanh , − = × +t g t t gg w h x b (24) [ ]( )1 ,σ − = × +t o t t oo w h x b (25) 1− = +⊙ ⊙t t t t tc f c i g (26) ( )tanh= ⊙t t th o c (27) here, �% is input gate, �% is forget gate, *% cell gate, +% is output gate, �% is cell state, ℎ% is the hidden state, �% input at timestep at �, the weight matrices are !�, !-, !*, !. and the bias terms are "�, "-, "*, ".. the output layer is the dense layer with a single neuron and sigmoid activation for binary classification. the model is compiled with the adam optimizer and binary cross-entropy loss, as shown below. ( )sigmoid= × + lstmout outfinaloutput w output b (28) ( ) ( ) ( ) ( )1 1 , log 1 log 1 =  = − × + − × −   n true true truepred pred predi l y y y y y y n (29) here, � is the total number of data points. during training, the model learns parameters by minimizing the defined loss function. the evaluation computes the loss (/) and accuracy metrics based on the test data. predictions ( 0&(1) are generated using the trained lstm model, providing probabilities for binary classification tasks. fig. 3 architecture of the lstm model employed in the study 4.4. custom neural network the custom-designed nn for the study (fig. 4) comprises several densely connected layers followed by batch normalization and dropout layers. the dense layers, as shown in the following equations, contain 256, 128, 64, 32, and 16 neurons respectively, with relu activation functions, l2 regularization, and input dimensions matching the feature size of $%&'��. advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 295 ( )1− = × + ii i i z w a b (30) ( )re lu=i i a z (31) here, 2� is the weight, "� is the bias and 3� is the activation output. the batch normalization layers normalize the outputs of the previous layers to stabilize and improve the training process by reducing internal covariate shifts. each dropout layer randomly sets a fraction of input units to zero during training to prevent overfitting. it aids in regularization by reducing interdependent learning among neurons. the model is compiled using the adam optimizer with a learning rate of 0.001 and binary cross-entropy loss function, aiming to minimize the difference between predicted and true labels for binary classification tasks. after training, the model is evaluated using the test dataset to calculate the loss and accuracy metrics. fig. 4 architecture of custom nn model employed in the study 4.5. evaluation metrics the parameters to evaluate the performance of this study are as follows. here, true positive (tp), false positive (fp), true negative (tn), and false negative (fn) are defined. accuracy indicates the fraction of the total samples that were correctly classified by the classifier, as follows. tp tn accuracy tp tn fp fn + = + + + (32) recall measures the proportion of actual positives that were correctly identified by the model, as follows. tp recall tp fn = + (33) precision measures the proportion of correct positive predictions, as follows. tp precision tp fp = + (34) specificity measures the proportion of actual negatives that were correctly identified by the model, as follows. tn specifity tn fp = + (35) 296 advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 the f1-score reflects the stability of the models by evaluating the balance between precision and recall, as follows. ( )2 precision recall f1-score precision recall × × = + (36) the receiver operating characteristic (roc) curve is a graphical tool used in ml to evaluate the performance of binary classifiers by plotting the tp rate against the fp rate at different thresholds. 5. results the t-distributed stochastic neighbor embedding (t-sne) [26] figure shows the visualization of two classes (td – 0.0, asd – 1.0) in a two-dimensional space (fig. 5). it demonstrates a partial separation of data points from both classes, indicating similarities and differences between the classes. while most points segregate into distinct clusters, some overlap occurs, suggesting shared features between individuals with asd and td individuals. the evaluation metrics for each of the employed nn models are presented in table 2. fig. 5 visualization of data points table 2 evaluation metrics of the employed nn models nn model accuracy (%) precision (%) recall (%) specificity (%) f1-score (%) cnn 89.02 91.20 93.98 75.68 92.57 dnn 91.98 92.75 96.52 79.77 94.60 lstm 93.83 95.08 96.52 86.60 95.80 custom nn 94.02 95.85 95.94 88.86 95.90 the evaluation of performance metrics for distinguishing asd and td individuals using eeg data reveals significant insights across various nn models. custom nn attained the highest accuracy at 94.02%, reflecting its superior classification ability due to its tailored architecture that effectively captures both spatial and temporal features. cnn had the lowest accuracy at 89.02%, indicating its limitations in handling the temporal dependencies in eeg data. in terms of precision, which measures the reliability of identifying asd cases among the predicted positives, custom nn excelled at 95.85%, suggesting fewer fp due to its effective regularization techniques and optimized feature extraction. cnn had the lowest precision at 91.20%, indicating overfitting to some features while missing others. the recall indicates the ability to capture true asd cases. the employed dnn, lstm, and custom nn models have achieved high rates of 96.52%, showcasing their effectiveness in minimizing missed asd cases. the lstm’s strength in handling sequential data contributes to its high recall, while custom nn’s complex architecture enhances its sensitivity. advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 297 the cnn lagged in the recall at 93.98% due to its lower effectiveness in handling the temporal aspects of the data. specificity, measuring the capability to correctly classify td individuals, ranged from 75.68% for cnn to 88.86% for custom nn. the high specificity of custom nn suggests its proficiency in distinguishing non-asd cases, likely due to its sophisticated design and regularization methods. cnn’s lower specificity indicates a higher rate of fp, reflecting its challenges in accurately identifying td cases. the f1-score, which balances precision and recall, was highest for custom nn at 95.90%, signifying its overall effectiveness and balanced performance. the lstm also performed well with an f1-score of 95.80%, leveraging its architecture’s strength in handling temporal data. the cnn shows the lowest f1-score at 92.57%, indicating its overall lower performance in balancing precision and recall. these performance differences arise from the models’ architectural strengths, data handling, regularization techniques, and feature extraction capabilities. custom nn and lstm demonstrate superior performance due to their sophisticated designs tailored for eeg data analysis, capturing complex patterns and temporal dependencies effectively. fig. 6 shows the confusion matrices for the employed nn models which summarize the counts of tp, tn, fp, and fn predictions. fig. 6 confusion matrices of the employed nn models (a) roc curve for custom nn model fig. 7 roc curves for the employed nn models 298 advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 (b) roc curve for cnn, dnn, lstm fig. 7 roc curves for the employed nn models (continued) 6. discussion and conclusion the findings of this study underscore the potential of four nn models in the accurate classification of asd using eeg data. through a comprehensive evaluation of various nn models, including the standout custom nn, the study demonstrates notable advancements in distinguishing asd cases from td individuals. the analysis of accuracy, precision, recall, and specificity provides a well-rounded understanding of each model’s strengths and limitations, with the custom nn exhibiting particularly strong performance. this highlights its potential for practical application in clinical settings, where early and accurate detection of asd is crucial for effective intervention. the study significantly contributes to autism research by showcasing the efficacy of nn models, particularly in offering non-intrusive diagnostic tools. the high accuracy of the custom nn model emphasizes the urgency and potential of early detection techniques in improving asd diagnosis and intervention strategies. the varied performance across nn models reveals the potential for innovation in diagnostic tools and reinforces the importance of continued advancement in this area. however, the study is not without its limitations. the reliance on a less diverse and relatively small dataset restricts the generalizability of the findings and the robustness of the developed models. this limitation impacts the models’ performance in real-world scenarios, as the dataset does not fully represent the variability seen in asd cases across different demographics and age groups. future research should address these limitations by incorporating larger and more diverse datasets to enhance the generalizability and robustness of nn models. additionally, exploring hybrid model frameworks that integrate various nn architectures could further improve diagnostic precision and clinical utility. expanding the dataset and refining model frameworks will be crucial for advancing early asd detection and developing more effective diagnostic tools, ultimately contributing to progress in autism research and clinical practice. acknowledgment the dataset (global datasets for autism disorder) used in this study is received from the brain-computer interface (bci) group of king abdulaziz university (kau). permission to use the dataset has been obtained for this study (https://malhaddad.kau.edu.sa/pages-bci-datasets.aspx). the authors express their heartfelt thanks and gratitude to dr. mohammed j. alhaddad from brain-computer interface (bci) group of king abdulaziz university (kau) for providing and allowing the usage of the dataset. advances in technology innovation, vol. 9, no. 4, 2024, pp. 287-300 299 conflicts of interest the authors declare no conflict of interest. statement of ethical approval for this type of study, statement of human rights is not required. statement of informed consent for this type of study, informed consent is not required. references [1] n. hasan 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[26] r. silva and p. melo-pinto, “t-sne: a study on reducing the dimensionality of hyperspectral data for the regression problem of estimating oenological parameters,” artificial intelligence in agriculture, vol. 7, pp. 58-68, march 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v9n1(2024)-aiti#12687(12-27).docx advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 english language proofreader: chih-wei chang the prediction of low-rise building construction cost estimation using extreme learning machine kittisak lathong, kittipol wisaeng* mahasarakham business school, mahasarakham university, mahasarakham, thailand received 05 august 2023; received in revised form 15 october 2023; accepted 23 october 2023 doi: https://doi.org/10.46604/aiti.2023.12687 abstract this study aims to predict the possibility of low-rise building construction costs by applying machine learning models, and the performance of each model is evaluated and compared with ensemble methods. the artificial neural network (ann) emerges as the top-performing individual model, attaining an accuracy of 0.891, while multiple linear regression and decision trees follow closely with accuracies of 0.884 and 0.864 respectively. ensemble methods like maximum voting ensemble (mve) improve the accuracy beyond individual models with an impressive accuracy rate of 0.924. meanwhile, the stacking ensemble and averaging ensemble also demonstrate competitive performance with accuracies of 0.883 and 0.871, respectively. these findings can result in more informed decisionmaking, which is valuable for the real estate industry. keywords: model, low-rise building construction cost, machine learning, ensemble learning model 1. introduction housing is one of the four essential aspects of human life, and the demand for residential properties and housing upgrades is rising owing to the growth of that current population. therefore, the importance of housing to family well-being cannot be overstated with homeownership [1] being seen as a cornerstone of both family stability and wealth creation [2]. on the other hand, housing prices serve as a reflection of the overall quality of life within urban environments and a fundamental factor in construction and resilient cities [3]. this surge in demand directly impacts the real estate industry, increasing residential construction projects including single-family homes, townhouses, commercial buildings, condominiums, etc. data from the national statistical office and the national economic and social development council of thailand [4] reveals that the number of permits issued for building construction exhibited varying patterns with a steady fluctuation from 2011 to 2022. however, since 2016, the number of permits granted for building construction has evinced a consistent upward trend. the burgeoning real estate sector in thailand has witnessed remarkable growth, which results in wielding a profound impact on the nation’s economy and exerting considerable influence over household consumption and savings. attaining a judicious and well-informed appraisal of real estate assets holds intrinsic advantages for a spectrum of stakeholders, ranging from urban policymakers within the government’s purview to real estate vendors and individual purchasers [5]. two main construction cost estimation methods are presented. one is the rough estimation or approximate cost estimation providing a preliminary rough estimate to study the initial feasibility with less time but a higher margin of error. the other one is detailed estimation involving calculating the quantities of work and their corresponding prices, while generally, this type of * corresponding author. e-mail address: kittipol.w@acc.msu.ac.th advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 13 estimation is performed with the availability of construction designs and specifications. detailed estimation yields relatively accurate results but is more time-consuming. it involves presenting an itemized list of material quantities and construction costs, resulting in higher accuracy but a longer estimation process [6]. machine learning (ml) has found widespread application across diverse industrial and business sectors [7-9]. ml technologies have evolved significantly and expanded their capabilities across a wide range of applications [10]. noteworthy studies have demonstrated the effectiveness of ml methodologies in predicting or classifying various factors, such as interest rates and prices within the real estate domain [11]. construction cost prediction represents a prominent area of investigation where ml capabilities have been thoroughly explored. moreover, construction cost prediction presents a multifaceted nonlinear challenge influenced by various direct and indirect attributes and construction year [12]. the traditional method of estimating residential construction costs, whether rough or detailed, always requires human resources such as engineers, architects, estimators, and other resources like computers, printers, paper, etc. additionally, it takes considerable time to obtain accurate and precise cost figures. to address this, researchers are interested in using a new approach where computers can learn independently through data or simulations with artificial intelligence (ai). they employ the principles of extreme learning machine (xlm), creating models for predicting flat-house construction costs directly from the house’s area without the need for architects and engineers to design. instead, the predicted cost should closely approximate the traditional estimation. ml is a subfield of ai that works alongside algorithms and technologies to extract useful information from data. ml is appropriate for calculations involving data due to the impracticability and inefficiency of manually processing the data in the absence of ml. therefore, it depends on creating algorithms enabling ml to be a predictive algorithm method capable of processing quantitative data for forecasting. according to the statement of xu et al. [13], ml has significantly transformed various industries and become a powerful tool in the construction sector as it automates processes. ml technology is substantial in processing massive volumes of data to achieve time savings and optimize processing resources. moreover, it may be particularly suitable for the construction industry to predict both financial and time expenditure and attain the maximization of efficiency. in the realm of construction cost estimation, tayefeh hashemi et al. [14] conducted an exhaustive analysis of research papers spanning 30 years from 1985 to 2020. these papers were dedicated to the application of ml techniques for cost estimation in construction projects. the overarching goal of these studies was to develop predictive models capable of providing accurate cost estimates, particularly during the pre-bidding phase, thereby facilitating informed decision-making by project managers. notably, prevalent ml techniques have employed in the reviewed literature including anns, regression analysis (ra), case-based reasoning (cbr), and support vector machines (svms) respectively. this analysis aligns with the findings of elfaki et al. [15], in their survey of construction cost estimation over the past decade, which also underscored the enduring prominence of classic ml techniques notably anns and svm within the field. various methodologies are employed to forecast residential prices [7]. in contrast to the classic price prediction approaches, ann-based methods have exhibited promising outcomes in real estate assessment [16]. their primary advantage lies in their capacity to discern non-linear correlations between inputs and outputs, rendering them particularly suitable for predicting non-linearities in real estate price assessment [17]. recent investigations have asserted the effectiveness of ml models, including anns in real estate price prediction tasks [11]. khalaf et al. [18] initially applied particle swarm optimization (pso) for cost and construction time estimation in 60 projects. the study attested that pso performed well and yielded highly accurate results despite the presence of parameters with diverse uncertainties. the strength of this approach lies in its reliance on existing and more reliable projects compared to those considered for estimation and testing. conversely, jiang [19] investigated the use of ann for construction project advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 14 estimation and compared its results with the radial basis function neural network (rbfnn) method and found, that ann outperformed rbfnn. subsequently, the ann model’s efficiency and application to other project types were examined, considering additional cost factors. in a study conducted by park et al. [20], the crucial importance of accurate cost estimation during the initial stages of construction projects is underscored. particularly in situations where essential data for construction cost prediction is scarce, the study introduces an innovative two-level stacking ensemble algorithm incorporating random forest (rf), svm, and catboosting. the optimal hyperparameter values for these base models are determined through bayesian optimization coupled with cross-validation. utilizing cost data from the public procurement service in south korea, the research demonstrates the two-level stacking ensemble model consistently outperforms individual ensemble models in predictive accuracy. while classical models employed in prior research exhibit commendable predictive capabilities, ml models have demonstrated unsatisfactory performance in comparison. notably, existing studies focused on real estate valuation and prediction in the residential domain primarily rely on readily available ml methods. however, the literature scarcely highlights the significance of incorporating ensemble models derived from general models to facilitate collective learning and enhance performance levels, thereby bolstering robustness. significantly, it is noteworthy that there is currently an almost complete absence of methods for predicting construction prices in thailand through the deployment of ensemble learning techniques. moreover, in instances where ensemble learning methods have been employed, a notable dearth of comprehensive comparative demonstrations involving multiple ensemble learning approaches is emerged. consequently, a discernible knowledge gap persists in the quest to enhance the efficiency of ml models for real estate price prediction. this current study endeavors to bridge these gaps comprehensively and address these issues. from the aforementioned discussion, the problem arises when business owners, project managers, or homeowners need assistance to estimate construction costs accurately and thoroughly, leading to longer estimation periods and reliance on engineers, architects, or estimators. to address these challenges, developing a predictive model for estimating flat-house construction costs using extreme ml would be beneficial. this ai technique enables computers to learn autonomously. this model could aid in predicting construction costs directly from house area data, reducing the need for human involvement in the design process while maintaining a close approximation to traditional estimation methods. the research aims to achieve three primary objectives. firstly, it aims to introduce an innovative approach for horizontally estimating low-rise construction costs, employing xlm techniques. secondly, the study strives to identify the most effective and suitable prediction method for estimating low-rise construction costs within this context. lastly, the research endeavors to conduct a comprehensive performance comparison between various ensemble learning methods and the conventional approach in predicting low-rise building construction costs. once achieving these objectives, the study aspires to offer valuable insights into housing price estimation, ultimately enhancing the accuracy and efficiency of predictions within the real estate market. the rest of this paper follows a structured organization. in section 2, an overview of the dataset and a comprehensive data analysis are provided. sections 2.1 to 2.3 elucidate the concept of base models, while sections 2.4 to 2.5 expound upon the intricacies of the proposed ensemble learning model. empirical findings are presented in section 3, culminating in the concluding remarks in section 4. 2. data and methodology predicting low-rise building prices accurately is paramount in the real estate industry. this article presents a comprehensive methodology for low-rise building price prediction, which comprises the following 5 phases, data preprocessing, build base predictive model, build ensemble model, evaluation model, and results and conclusions, as depicted advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 15 in fig. 1. this section is dedicated to the methodology for the development of algorithms aimed at predicting the construction cost of low-rise buildings. phase 1 – data preprocessing marks the outset, including comprehensive data preprocessing tasks such as data cleaning, handling missing values, addressing outliers, and data splitting. phase 2 – building base predictive models follows the construction of base predictive models using regression-based models, specifically anns, svms, multiple linear regression (mlr), decision trees (dts), and rf. a 10-fold crossvalidation approach is deployed in this phase, coupled with hyperparameter tuning for optimizing model performance. phase 3 – while the maintenance of a 10-fold cross-validation strategy, constructing ensemble models leverages the base models to create ensemble models through maximum voting, averaging, stacking, boosting, and bagging. phase 4 – evaluation of predictive model accuracy entails a rigorous assessment concerning the performance of both base model and ensemble learning models. multiple performance metrics, such as mean squared error (mse), root mean squared error (rmse), mean absolute error (mae), and r-squared (r2), are employed to ensure a comprehensive evaluation. phase 5 – results and conclusions emerged by consolidating results, performing model comparisons, conclusions, and making recommendations for selecting the optimal model for predicting the construction costs of low-rise buildings. this structured approach ensures a systematic analysis throughout all phases of the study. fig. 1 research methodology advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 16 2.1. dataset the dataset for the implementation of the proposed model is obtained from the bureau of public works in bangkok, thailand. it includes drawing data related to a low-rise building and their respective prices. this dataset constitutes carefully selected features, chosen through a comprehensive review of existing literature and expert domain knowledge. the dataset and its associated features are presented in table 1, with the left column listing the feature names, the middle column providing concise descriptions of each feature, and the right column referencing the corresponding features from the literature review. table 1 the description of the dataset feature details description of the dataset reference y the construction cost of low-rise buildings [1, 5-6, 17, 20-22] x1 the number of stories [1, 6, 20, 22-25] x2 the gross floor area [5-6, 17, 20, 22-24] x3 the area of bedrooms [1, 5-6, 21, 25] x4 the area of bathrooms [5, 21, 25] x5 the area of living rooms or restrooms [5, 21, 25] x6 the area of kitchen and dining rooms [21] x7 the area for laundry facilities [21] x8 the area of balconies [21] x9 the area of stairs and corridors [21] x10 the area of the roof covered by the concrete roof and awning [1, 6, 23] x11 the area of the roof covered by tiled roofing [1, 6] x12 the area of the parking lot [20-22] x13 the overall height [5-6, 20, 23] x14 the height of the roof by professional experience. x15 the average height of each story [6, 17, 23] 2.2. data analysis fig. 2 pearson correlation coefficient conducting a comprehensive analysis of the dataset before commencing model construction is a foundational and illuminating step in data understanding. to explore the relationships among the dataset’s attributes, an integral aspect of this analytical procedure involves the application of a correlation matrix illustrated in fig. 2. the correlation matrix provides coefficients ranging from +1 to -1 [26], shedding light on the level of association between various attribute pairs. a positive advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 17 coefficient denotes a direct relationship, while a negative coefficient signifies an inverse connection. meanwhile, a coefficient of zero indicates independence among variables [26]. the scrutiny of this matrix yields valuable insights into attribute interdependencies, equipping us to make well-informed decisions during the modeling phase. the observations depicted in fig. 2 emphasize certain variables exhibiting noteworthy correlations, specifically including four points as follows: (1) x1:x13 = 0.95, (2) x2:x3 = 0.83, (3) x2:x4 = 0.78, and (4) x3:x4 = 0.79. 2.3. data pre-processing pivotal data preprocessing steps were meticulously executed, encompassing the removal of missing data and precise data segmentation into training and testing sets. these processes seamlessly integrated extensive data visualization and attentive data cleaning, which ensures comprehensive management of missing values and outliers before model deployment. in the initial stage of the low-rise building price prediction methodology, the focus lies in the selection of a high-quality dataset. curated diligently from reputable sources, it comprises attributes such as room area, building height, and amenities, while all these attributes can influence low-rise building prices. robust data preprocessing techniques further prepare the dataset by handling outliers, resolving missing values, and deriving meaningful features. finally, data splits into training, validation, and testing subsets, which facilitates accurate model assessment, model training, hyperparameter fine-tuning, and performance evaluation. 2.4. machine learning techniques base model ml algorithms offer the capability to model intricate and ill-defined systems even in the presence of unknown nonlinear relationships. within the scope of this study, a set of five distinguished ml algorithms including anns, svms, mlr, dt, and rf are deployed to develop the proposed ensemble models. the inclusion of these varied algorithms bolsters the predictive potency of the approach. furthermore, comprehensive elucidations of the design parameters for each algorithm are presented in detail. 2.4.1. artificial neural networks (anns) anns are a class of ml models inspired by the structure and functioning of the human brain. they are utilized to solve complex problems, particularly pattern recognition, classification, and regression. moreover, ann consists of interconnected nodes, known as neurons, which are organized into layers. these layers include an input layer to receive data, while single or multiple hidden layers are for intermediate processing, and an output layer is employed to produce the final result. each neuron in the network is connected to every neuron in the adjacent layers, and these connections have associated weights that determine the strength of the connection. during the training process, anns learn from input data to adjust the weights and biases, enabling them to capture intricate relationships in the data and make accurate predictions. the advantage of using ann for low-rise building price prediction is their ability to capture nonlinear relationships and patterns in the data, which traditional linear regression models may need assistance to handle. in summary, anns can generalize well to new, unseen data, making them well-suited for real estate data’s dynamic and diverse nature. 2.4.2. support vector machine (svm) the svm method is employed to transform the predicted low-rise building price parameters into a high-dimensional feature space using a kernel function like linear, polynomial, or gaussian. a linear regression function is subsequently computed to confirm the deviation from the actual model outputs by at most ε for all training data while maintaining the function to the maximum flat extent. the asymmetrical loss function is utilized to train the svm model to create a flexible cylinder with a minimal radius symmetrically wrapped around the regression function, which effectively omits absolute errors smaller than ε. the selected kernel function for the svm model is laplace, which is a versatile choice suitable for regression advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 18 tasks. a trial-and-error approach is applied to determine the cost of constraint violation and the value of ε, yielding optimal values of 10 and 0.1, respectively [27]. these parameter settings contribute to the robustness and accuracy of the svm model in predicting low-rise building prices. support vectors represent essential data points positioned closest to the decision boundary or hyperplane, distinctly classifying categories. their strategic arrangement profoundly affects boundary placement and orientation. the margin, the space between these support vectors, and the decision boundary, critically gauges the generalization and resilience of svm. a broader margin signifies heightened class segregation, enhancing predictions for unobserved data. the objective of svm employment is to identify the hyperplane maximize this margin and efficiently separate data. in a two-class scenario, the hyperplane acts as the class-separating threshold. the optimal choice of svm advances the margin gauged by the hyperplaneto-support-vector distance. non-linearity management employs kernel functions and elevated-dimensional space conversion. 2.4.3. multiple linear regression (mlr) linear regression is a statistical method for modeling the relationship between a dependent variable (also known as the target or outcome variable) and single or multiple independent variables (also known as predictor variables or features). it is a simple and widely used technique in statistics and ml for predicting continuous numeric values. in linear regression, the goal is to find the best-fit line representing the linear relationship between the independent and dependent variables. the equation of the line is described as: 0 1 1 2 2= + + + + +⋯ n ny b b x b x b x (1) where y is the dependent variable or low-rise building prices b0 is the intercept or bias term, representing the value of y when all independent variables are 0, b1, b2, …, bn are the coefficients or weights associated with each independent variable, and x1, x2, …, xn are the independent variables. the coefficients (b1, b2, …, bn) are estimated during the training process, such that the line minimizes the sum of squared differences between both predicted and actual values in the training data. this process is commonly known as “fitting the model” to the data. once the model is trained, predictions for new data can be made by plugging in the values of the independent variables into the equation. linear regression is particularly effective when a linear relationship is rendered between the dependent and independent variables. furthermore, it remains suitable for various applications, including predicting low-rise building prices, analyzing economic trends, and understanding the impact of different factors on a particular outcome. 2.4.4. decision tree (dt) dt regression is a robust and interpretable algorithm for predicting numeric values in regression tasks. the algorithm constructs an arborescent model by recursively partitioning the dataset into subsets based on the values of its features. the feature and split point that minimize the variance or mse of the target variable within the subset are selected at each node. this process sustains until a stopping criterion, such as a maximum tree depth or a minimum number of samples per leaf, is satisfied. the prediction for each data point is generated by traversing the dt from the root node to a leaf node, where the numeric value associated with the leaf node serves as the final prediction for the target variable. given these facts, dt for regression is highly interpretable due to the enablement of a clear understanding of the decisionmaking process and the realization of the rationale influencing the predicted numeric outcomes. moreover, their adaptability to nonlinear relationships attains suitability for various applications, ranging from financial forecasting to medical diagnosis, where precise numeric predictions are required. however, to prevent overfitting, pruning techniques, and hyperparameter tuning are often employed to control the complexity of the model and maintain robust generalization performance. advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 19 2.4.5. random forest (rf) rf is a potent ensemble learning technique for regression tasks. it is constituted as an extension of the dt algorithm combining multiple decision trees to optimize the accuracy of predictions. in an rf for regression, a collection of dts is established with random subsets of both the training data and features. each dt in the forest independently makes predictions, and the final prediction is obtained by averaging or taking the median of the predictions from all the individual trees. this ensemble approach mitigates the risk of overfitting and augments the model’s ability to generalize well to new, unseen data. rf for regression offers several advantages, such as handling nonlinear relationships between features and the target variable, capturing complex interactions, and impact reduction of noisy data. the randomness introduced in building the trees also strengthens the model against outliers and stabilizes per se. additionally, rf proffers a feature importance score, indicating the relative importance of each feature in the prediction process. this information is perceived to be valuable for understanding which features are most influential in determining the regression outcome. overall, rf is a versatile and effective algorithm for regression tasks. it is a popular choice in various domains, including finance, healthcare, and retail, where accurate numeric predictions are essential for decision-making. 2.5. ensemble learning model ensemble learning is a powerful technique in ml where multiple models are combined to improve predictive performance, robustness, and generalizability compared to using a single model. each ensemble method utilizes a different strategy to combine the predictions of individual base models, utilizing techniques such as maximum voting ensemble, averaging ensemble, stacking ensemble, bagging ensemble, and boosting ensemble. 2.5.1. maximum voting ensemble (mve) ensemble models for predicting low-rise building prices using the maximum voting method typically involve combining the predictions from multiple individual models to attain the final prediction. in this approach, several aforementioned base models, such as anns, svms, mlr, dts, or rfs, are trained independently on the same dataset. once the individual models are trained, predictions for the target variable are made, which, in this case, is the low-rise building price. the mve method takes the mode of all the predictions provided by the individual models. the mode value is selected as the final prediction for the low-rise building price, as demonstrated in fig. 3. fig. 3 ensemble techniques mve the rationale behind the mve is to leverage the collective wisdom of diverse models. both strengths and weaknesses are rendered in each base model, and with the combination of predictions, the ensemble aims to mitigate the impact of individual model errors and produce more accurate and robust predictions. this method is particularly effective when low correlation has emerged in the individual models, i.e., they make errors in different instances. by taking the mode, it enables the ensemble to employ the most frequently agreed-upon prediction among the models, leading to a more reliable overall forecast for low-rise building prices. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 20 2.5.2. averaging ensemble averaging ensemble is another popular method for combining predictions from multiple individual models to make a final prediction in regression tasks, as illustrated in fig. 4, such as predicting low-rise building prices. in this approach, several base models, such as anns, svms, mlr, dts, or rfs, are trained independently on the same dataset. fig. 4 ensemble techniques averaging ensemble after being trained, the individual models predict the target variable (low-rise building construction cost). in the averaging ensemble, the final prediction is obtained by averaging the predictions from all the individual models. mathematically, it can be presented as: 1 2 prediction_model prediction_model prediction_model final prediction + + + = ⋯ n n (2) where n is the total number of individual models used in the ensemble. the rationale behind the averaging ensemble is to leverage the collective knowledge of diverse models and reduce the variance of predictions. given the presence of strengths and weaknesses in each mode and the average of predictions, the ensemble aims to create a more stable and accurate final forecast. averaging conduces to smoothing out individual model errors and the improvement of overall predictive performance. approximated to maximum voting, the averaging ensemble functions best when the individual models have relatively low correlation, i.e., producing errors in different instances. with averaged predictions, the ensemble can benefit from the collective insights of the models and attain a more reliable and precise forecast for low-rise building prices. 2.5.3. stacking ensemble the stacked ensemble, often referred to as stacked generalization, represents a sophisticated ensemble learning approach showcased in fig. 5. it amalgamates predictions from various individual models to enhance the comprehensive predictive performance across ml tasks, encompassing the prediction of low-rise building prices. stacking goes beyond simple averaging or voting methods by introducing a meta-model learning to combine the outputs of the base models. fig. 5 ensemble techniques stacking ensemble advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 21 the stacking ensemble involves the following steps: (1) base models: several diverse base models are trained independently on the same dataset. these base models can be different or the same algorithm with different hyperparameters. (2) hold-out validation set: a hold-out validation set is created from the training data. the base models make predictions on this validation set as input to the meta-model. (3) meta-model: a meta-model, also called the “blender” or “aggregator,” is trained with the predictions from the base models on the validation set as its input features. the meta-model learns how to combine these predictions to generate the final prediction for the target variable (low-rise building price). (4) final prediction: once the meta-model is trained, predictions are made herein. the final forecast for low-rise building prices is obtained from the output of the meta-model. the key advantage of the stacking ensemble is the ability to capture higher-order relationships between the base models’ predictions. it learns from trusting each base model and assigning different weights to their predictions based on their performance on the validation set. this enables stacking to outperform individual models and simple averaging/voting ensembles by the augmentation of the strengths. stacking is a flexible and powerful technique but correspondingly requires careful implementation and tuning to prevent overfitting. properly executed stacking can enhance predictive accuracy and robustness, popularizing itself in various ml competitions and real-world applications, including low-rise building price prediction. 2.5.4. bagging ensemble bagging, the abbreviation for bootstrap aggregating, is a widely deployed ensemble learning technique to improve the accuracy and robustness of ml models, including those used for predicting low-rise building prices. it involves creating multiple diverse copies of the same base model, training each copy on a different random subset of the training data, and then combining their predictions to make the final prediction [28], as depicted in fig.6. fig. 6 ensemble techniques bagging ensemble the bagging ensemble works as follows: (1) base model: a single base model, such as a dt or rf, is selected as the base learner. (2) bootstrap sampling: it creates multiple random subsets (samples) from the training data, which involves randomly selecting data points from the training set with replacements. each subset may contain some duplicate data points and miss some others. (3) base model copies: for each subset, a separate copy of the base model is trained using the corresponding subset of the training data. as a result, multiple base model copies with slightly different training data are created. (4) aggregation: to make predictions for new data, each base model copy generates its forecast. in bagging, the final prediction is obtained by aggregating (averaging for regression tasks or voting for classification tasks) the estimates from all the base model copies. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 22 the key advantage of bagging is to reduce the variance and overfitting in the predictions by leveraging the wisdom of diverse model copies trained on different subsets of the data. by combining multiple forecasts, bagging produces a more stable and robust final prediction that tends to generalize well to new, unseen data. meanwhile, rf is a paradigm of the bagging ensemble, where multiple decision trees are trained on different bootstrapped subsets of the training data, and their predictions are aggregated to make the final prediction. bagging is widely deployed in ml due to its simplicity and effectiveness in improving model performance and reducing overfitting. 2.5.5. boosting ensemble boosting is another potent ensemble learning technique for improving ml models’ predictive performance, including those used for predicting low-rise building prices. unlike bagging focusing on training multiple models independently and combining their predictions, boosting builds a concatenation of models sequentially, where each model tries to correct the errors made by its predecessors [28], as depicted in fig. 7. fig. 7 ensemble techniques boosting ensemble the boosting ensemble works as follows: (1) base model: a weak base model, often called a “weak learner,” is selected as the base learner. weak learners slightly prevail over random chance models, such as simple decision stumps (one-level dts) or shallow dts. (2) weighted data: the training data is initially given equal weight for all data points. in each boosting iteration, the weights of misclassified data points increase, while the weights of correctly classified data points decrease. this enables the subsequent weak learners to focus on the previously misclassified data points and improve the overall model performance. (3) sequential learning: boosting builds a concatenation of weak learners, where each model is trained on the modified version of the training data from the previous step. the predictions of each weak learner are combined with a weight, and the final prediction is obtained by summing up the weighted predictions. (4) adaptive learning: the sequential nature of boosting enables it to learn from its mistakes adaptively. the subsequent weak learners are encouraged to focus on the challenging data points incorrectly predicted by the earlier weak learners. the key advantage of boosting is the capability of improving the predictive accuracy compared to a single weak learner. by building a sequence of models correcting each other’s errors, boosting creates a robust ensemble model that can capture complex relationships in the data. gradient boosting machines and adaboost are two typical examples of boosting algorithms. advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 23 gradient boosting machines iteratively minimize the loss function by adding weak learners, while adaboost assigns higher weights to misclassified data points, enabling subsequent weak learners to focus on those points. boosting is a widely used technique in ml, and it often outperforms individual models and other ensemble methods. given this virtue, it is acknowledged as a valuable tool for low-rise building price prediction and other complex regression tasks. 2.6. performance measure mae measures the average of the absolute differences between predicted and actual low-rise building prices. this metric is beneficial in dealing with uniform forecast errors, as it equalizes the discrepancies in the data. it is frequently employed for regression problems and to evaluate the overall accuracy of forecasts. a smaller mae indicates better forecasting performance in predicting low-rise building prices, reflecting a closer alignment between the predicted values and the actual costs. ( ) ( ) 1 1 = = − n i pred i actual i mae y y n (3) where yi(actual) is the actual low-rise building prices, n is the total number of observations, and yi(pred) is the predicted low-rise building prices [29]. mse is a metric used to assess the accuracy of predicting low-rise building prices. it is computed by taking the average of the squared differences between the actual and predicted values. in other words, the method encompasses the calculation of the squared discrepancy between the projected and actual prices of low-rise buildings for each prediction instance. after this computation, an averaging procedure is applied to these squared discrepancies, yielding the resultant mse. the mse penalizes large prediction errors more severely than small ones, providing a way to quantify the overall accuracy of the prediction model. lower mse values indicate better predictive performance, indicating smaller differences between predicted and actual lowrise building prices [22]. ( ) 2 ( ) ( ) 1 1 = = − n i pred i actual i mse y y n (4) rmse is a widely used metric for the accuracy evaluation of low-rise building price predictions. it is calculated by taking the square root of the average of the squared differences between the predicted and actual low-rise building prices. rmse is highly regarded for its ability to handle outliers in the data effectively [22], enabling the identification and elimination of extreme discrepancies to emerge in predictions. moreover, rmse puts more emphasis on larger errors. consequently, it is recognized as a valuable primary error metric for assessing the performance of low-rise building price-prediction models. ( ) 2 ( ) ( ) 1 1 = = − n i pred i actual i rmse y y n (5) determination coefficient (r2) is a critical metric that gauges the proportion of variance in predicted low-rise building prices attributed to the model’s predictions. with values ranging from 0 to 1 [22], an r2 value of 0 suggests poor model performance, while 1 indicates a perfect fit between forecast and actual values. this metric provides insights into the goodnessof-fit of a low-rise building price prediction model and conduces to understanding the model’s ability to capture variations in the data. low-rise building price prediction success hinges on choosing the most suitable algorithm. the performance assessment of different algorithms is conducted with meticulous consideration, employing relevant evaluation metrics such as mse or mae on the validation dataset. the algorithm demonstrating superior predictive performance and robust generalization capability is selected as the prediction model. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 24 in summary, the methodologies including encompassing critical stages from data selection, preprocessing to model training, and algorithm choice comprehensively address low-rise building price prediction. by following this systematic approach, real estate professionals, investors, and analysts can confidently make informed decisions based on accurate lowrise building price predictions. 2.7. hyperparameter tuning with the data preprocessing phase, the performance of the base models underwent a comparative analysis. to assess the effectiveness of these base models, it becomes imperative to identify the most suitable hyperparameters for each model. initially, the raw dataset is randomly divided into two distinct subsets, comprising a training set and a testing set. the optimal hyperparameter values for the base models, as determined by the highest r2 score during the search in the hyperparameter space, are presented in table 2. table 2 the hyperparameter tuning base ml models hyperparameter values artificial neural networks (anns) activation function relu learning rate 0.001 number of epochs 1000 initializer normal optimizer adam support vector machines (svms) kernel linear c (regularization parameter) 1000 gamma (kernel coefficient) scale epsilon 0.05 decision trees (dts) criterion gini impurity max depth unlimited min samples per leaf 2 random forest (rf) number of trees 100 max depth unlimited min samples per leaf 2 max features auto to evaluate and compare the performance of these base models, a ten-fold cross-validation technique was applied, known for its established effectiveness in cross-validation practices. the hyperparameters, crucial for each model, were employed with the values derived through a grid search, conducted in the preceding phase. 3. results and discussion in this section, the outcomes of the model development and the subsequent training using the pre-processed dataset are presented. a thorough performance comparison among ten machine-learning algorithms has been conducted, complemented by comprehensive parameter tuning for meticulous performance analysis and evaluation. additionally, an in-depth insight into the experimental setup employed for the entire task is provided. the primary aim of this study was to forecast low-rise building construction costs, employing a diverse set of ten machinelearning models. to evaluate their efficacy, four distinct statistical metrics outlined in table 3 were applied to gauge the accuracy of each model. as shown in table 3, the ann emerged as the highest-performing base model, boasting an accuracy of 0.891. mlr closely followed, achieving an accuracy of 0.884, while dts demonstrated an accuracy of 0.864. the rf model achieved an accuracy of 0.830, whereas the svm displayed the lowest accuracy at 0.446. concerning the ensemble models, a diverse array of techniques was employed to amalgamate predictions from individual models. the mve demonstrated the highest accuracy, advances in technology innovation, vol. 9, no. 1, 2024, pp. 12-27 25 reaching 0.924, thus surpassing all individual models and other ensemble methods. the stacking ensemble secured second place with an accuracy of 0.883, while the averaging ensemble achieved an accuracy of 0.871. regarding the boosting ensemble, it delivered an accuracy of 0.846, and the bagging ensemble yielded an accuracy of 0.832. table 3 the summary of the algorithms that have been used in the research model r2 mse rmse mae base model ann 0.891 47564120000.00 218092.00 165705.68 svm 0.446 242250000000.00 492189.90 322532.74 mlr 0.884 50560550000.00 224856.74 146446.13 dt 0.864 59522890000.00 243973.13 126901.04 rf 0.830 74476350000.00 272903.56 164069.51 ensemble model max. voting 0.924 33325570000.00 182552.93 127356.65 averaging 0.871 56266850000.00 237206.35 140085.86 stacking 0.883 51074880000.00 225997.52 152669.31 bagging 0.832 73493900000.00 271097.58 155363.36 boosting 0.846 67425130000.00 259663.50 147838.86 to visually convey the comparative accuracy across all models, fig. 8 is presented as follows. this visualization highlights the promising performance exhibited by most algorithms in regression tasks, underscoring their potential for precise low-rise building cost prediction. fig. 8 comparison of accuracy among the models in summary, the research harnessed the predictive power of ten machine-learning models coupled with an array of ensemble techniques to anticipate low-rise building prices. the results underscore the remarkable efficacy of the mve, situating it as a compelling choice for practical applications within this domain. furthermore, individual models including ann, mlr, and dt demonstrated notable accuracy which solidifies their status as valuable options for consideration. 4. conclusions this study harnessed the predictive potential of ten diverse ml models to anticipate low-rise building prices. the identification of top-performing models, both within ensemble methods and individual algorithms, was achieved through a rigorous and exhaustive analysis. meanwhile, the ann emerged as the most accurate individual model, underscoring its adeptness in addressing the intricacies of the prediction task with a remarkable accuracy of 0.891. concerning mlr and dts, they are closely followed and exhibit robust predictive capabilities with accuracies of 0.884 and 0.864, respectively. furthermore, the evaluation of ensemble models underscored the prominence of the mve, securing the highest accuracy of 0.924 among all models tested. this ensemble technique adeptly amalgamates predictions from advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 26 individual models, harnessing their collective strengths and simultaneously mitigating their shortcomings. the stacking ensemble and averaging ensemble also demonstrated competitive accuracy, achieving scores of 0.883 and 0.871, respectively. these results affirm the significant performance enhancements which are attainable through ensemble methods, surpassing the capabilities of individual models. in a broader context, the findings from this study deliver valuable insights into real estate industry practitioners and stakeholders. the utilization of ml models, notably the ann and mve, possesses the potential to enhance the accuracy of low-rise building price predictions, facilitating more informed decision-making and strategic investments. as the evolution of ml burgeons, ongoing research, and enhancements in model architecture and ensemble techniques promise even more precise and dependable predictions across diverse real-world applications. acknowledgments this research project was financially supported by mahasarakham university of thailand under grant no. 6603024. nomenclature xlm extreme learning machine ann artificial neural network mve maximum voting ensemble ml machine learning ai artificial intelligence ra regression analysis cbr case-based reasoning svm support vector machine pso particle swarm optimization rbfnn radial basis function neural network rf random forest mlr multiple linear regression dt decision tree mse mean squared error rmse root mean square error mae mean absolute error r2 r-squared conflicts of interest the authors declare no conflict of interest. references [1] a. soltani, m. heydari, f. aghaei, and c. j. pettit, “housing price prediction incorporating spatio-temporal dependency into machine learning algorithms,” cities, vol. 131, article no. 103941, december 2022. 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[29] p. kumari and d. toshniwal, “deep learning models for solar irradiance forecasting: a comprehensive review,” journal of cleaner production, vol. 318, article no. 128566, october 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v9n3(2024)-aiti#13702(157-171).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 english language proofreader: yen-chun hsieh an efficient application of modified yolov5 in basketball player detection and analysis jia-shing sheu*, sheng-ju lin department of computer science, national taipei university of education, taipei, taiwan, roc received 09 may 2024; received in revised form 14 july 2024; accepted 15 july 2024 doi: https://doi.org/10.46604/aiti.2024.13702 abstract effective analysis helps players evaluate their performance, make necessary adjustments, and develop diverse game strategies. moreover, the analysis provides viewers with different perspectives, enhancing their understanding of the game. this study aims to develop a basketball player detection and analysis system to assist in analyzing oncourt situations. the system uses perspective transformation to obtain player tracking information on the top view image in basketball games. the system uses a modified you only look once (yolo) v5 model that replaces the backbone of yolov5s with the mobilenetv3-small architecture for player detection. compared to the original yolov5, the modified yolov5 reduces parameters from 7.02 × 106 to 3.5 × 106, a decrease of 49.8%. the number of frames obtainable per second increases from 12.4 to 17.5, an improvement of about 41.1%. finally, the system performs perspective transformation and tracks the detected player positions onto the top-view court image using the yolov5 model. keywords: player detection, player tracking, basketball game, yolov5 1. introduction image processing is a major research area in computer science that involves techniques such as image analysis, enhancement, and reconstruction. common image processing techniques include edge detection, color model conversion, and image filtering. these techniques have applications in various fields, including artificial intelligence, autonomous driving [13], virtual reality, defect detection [4-5], and medicine [6-7]. object detection, a crucial research area in computer vision, involves accurately identifying and locating specific objects in images. this technology has been extensively used in fields such as autonomous driving, medical imaging, and security surveillance. deep learning significantly improves object detection performance. traditional methodologies for object detection include histograms of oriented gradients (hog) and adaboost [8]. deep learning approaches that have been employed to enhance object detection include convolutional neural networks (cnns), you only look once (yolo), single shot multibox detector (ssd) [9], and mobilenet. this study focuses on the following questions: how to determine the court boundaries to facilitate the accurate projection of player positions onto the court view, what methods to use for player detection, how to confirm player positions and project them onto the court view, and how to improve the model to increase efficiency and accuracy. therefore, this study proposes a basketball player detection system based on yolov5. it employs techniques such as the hue saturation value (hsv) model, canny edge detection, and hough transform to confirm basketball court boundaries. the study conducts player detection by * corresponding author. e-mail address: jiashing@tea.ntue.edu.tw 158 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 using a modified yolov5 model and projects player position information onto a top-view basketball court image through perspective transformation to obtain the desired planar information. the modified yolov5 improves frames per second (fps) by approximately 41.1%. the remainder of this article is organized as follows: section 2 describes the relevant literature, section 3 describes the system architecture, section 4 presents a description of the experiments and the experiment results, and section 5 presents the conclusions. 2. literature review in recent years, many object detection methods have been continuously introduced, and due to the widespread use of mobile devices and diverse application scenarios, how to lightweight models for deployment on mobile platforms has become a highly researched topic. the popular object detection methods in recent years are summarized in table 1. dalal and triggs [10] introduced hog, a widely utilized feature descriptor method in image processing and computer vision in 2005. hog divides an image into small blocks and computes the gradient magnitude based on the pixel gradient directions within each block, with this information considered to be the block’s feature. it addresses the feature extraction problem in pedestrian detection. the hog feature vector is frequently combined with a support vector machine (svm) for training to perform object detection tasks. table 1 methodologies of object detection object detection traditional methods hog adaboost deep learning cnn yolo ssd mobilenet the yolo algorithm [11] is a popular real-time object detection algorithm that employs one-stage detection. in such detection, an image is examined only once to recognize and locate objects, and therefore, yolo offers efficiency advantages in object detection. yolo divides each image into a fixed-size grid and analyzes each grid for potential objects and their positions. each grid prediction comprises the probability of belonging to a particular object, the location of the bounding box, and the object’s class. mobilenet [12], an optimized network architecture specifically designed for mobile devices, is lightweight and efficient, therefore, it is ideal for deep learning on mobile or embedded devices. the core innovation of this architecture is the use of depthwise separable convolution, which decomposes traditional convolution into depthwise and pointwise convolution steps, thereby reducing computation and parameters and resulting in a lighter model. mobilenetv2 [13] is an improvement on mobilenet because it includes inverted residual blocks and linear bottlenecks. mobilenetv3 [14] builds on mobilenetv2 because it employs a squeeze and excitation structure [15]; through global average pooling, it calculates each feature map’s weights to improve the model’s focus on crucial features and thereby improve its recognition performance. in 2019, google introduced efficientnet [16], which has the core concept of compound model scaling. efficientnet is based on compound coefficients, which enable uniform scaling of the network’s depth, width, and resolution in its architecture. although individually increasing depth, width, or resolution can improve model accuracy, saturation tends to occur once accuracy reaches approximately 80%, which can make further improvement challenging. to enhance accuracy, compound model scaling balances the network’s depth, width, and resolution by adjusting them simultaneously based on compound coefficients, which improves the overall model performance. efficientnetv2 [17], an advancement over efficientnet, addresses problems such as slow training speeds associated with large input sizes through the introduction of the fusedmbconv structure in certain modules. advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 159 in contemporary sports, performance analysis through computer vision has emerged as a critical area of research. player detection in sports scenes has wide applicability, including in sports such as ice hockey and basketball. researchers proposed a two-stage cnn model for detecting players in ice hockey [18]. in addition, for basketball, researchers used yolov2 for player position tracking [19] and trained a two-layer long short-term memory model [20] for player action recognition. in addition, researchers used combinations of hog and svm for player detection [21], followed by the transformation of player positions to a top view for analysis [22]. in addition, adaboost was proposed for player detection [23]; however, experimental results indicated that its effectiveness was below expectations and that it was unsuitable for object detection in sports events. 3. system structure and methodology this study structures its system by using the integrated definition for function modeling (idef0) modeling method, which is based on the structured analysis and design technique, to describe system functionality. idef0 can help organizations analyze and understand their processes or systems, providing a clearer understanding of how a system works. as illustrated in fig. 1, the system (a0) comprises three submodules designed to achieve player detection and tracking: court detection, yolov5 player detection, and player position localization. the purpose of the court detection module is to define the court boundaries using various image processing methods. then the yolov5 player detection module identifies the player positions. finally, the player position localization module projects the player positions onto the top-view image of the court to obtain the required planar information. fig. 1 idef0 for player detection and analysis system fig. 2 displays the court detection module (a01), which takes red, green, and blue (rgb) images from basketball videos as input. it converts the rgb color model to the hsv color model, uses the canny edge detection algorithm to identify basketball court edges, and uses the hough transform to define court boundaries. after summarizing these steps, the module obtains an image confirming the basketball court’s extent, which is used for subsequent perspective transformation. fig. 2 idef0 for court detection 160 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 the study converts images from the rgb to the hsv color model because of the ease of extracting information with specific color ranges in the hsv color model (a011). in the hsv color model, (��, ��, ��) represent the coordinates of rgb. they are normalized by dividing each value by 255, which ensures that values range from 0 to 1, which accurately describes color information in the hsv color model. the conversion formulas are displayed below. ( ), , , , 255 255 255   ′ ′ ′ =     r g b r g b (1) v represents value, which indicates the intensity of light reflected from the object. ( )max , ,′ ′ ′=v r g b (2) s represents saturation, which indicates the color’s purity. ( )min , ,′ ′ ′−   = v r g b s v (3) h represents hue, which indicates the color’s basic characteristic. ( ) ( ) ( ) 60 0 , 60 120 , 60 240 ,  ′ ′−  ′× + =      ′ ′−  ′= × + =      ′ ′−  ′× + =    � � � � � � g b if v r s b r h if v g s r g if v b s (4) this study uses the canny edge detector (a012) to detect basketball court boundaries. the canny edge detection algorithm, which is a classic edge detection technique known for its ability to detect edges in images while resisting noise interference, is widely used in various image processing tasks, including object detection, feature extraction, and image segmentation. the algorithm involves four steps: gaussian smoothing, gradient calculation, nonmaximum suppression, and hysteresis thresholding. first, before detecting edges in the image, gaussian blurring is applied to reduce noise, typically using a gaussian smoothing filter. second, gradients are computed using sobel filters to compute the gradient magnitude and direction for each pixel. third, non-maximum suppression is applied to filter out pixels by retaining only those where the gradient has the maximum magnitude in its direction, preserving finer edges. finally, double thresholding is applied using two thresholds: a low threshold and a high threshold. these thresholds are used to select edges by either preserving or discarding pixels based on their edge strength. hough transform (a013), a technique used to detect geometric shapes such as lines and circles in images, uses a voting mechanism to confirm lines, with line equations typically represented using the slope-intercept form. when a line is perpendicular to the x-axis, the slope becomes infinite, which can lead to computational difficulties. therefore, the hough transform uses normal parametrization to represent lines in such cases. a point can be the intersection of infinitely many lines. when these lines are transformed into polar coordinates through plane coordinate transformation, if the curves formed by two points intersect in polar coordinates, it implies that the two points are on the same straight line. in the player detection component of this study, a modified yolov5s model (a02) is applied. the main modification of the model involves changing the backbone architecture of yolov5s to those of other models to reduce computation and increase processing speed. advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 161 a. yolov5s (a02) for the yolov5s input, the mosaic data augmentation method is applied, as it is for yolov4, and adaptive computation and scaling of anchor boxes are incorporated. the mosaic data augmentation technique combines multiple images by randomly cropping, scaling, and arranging them to increase the diversity of training data. this approach can improve a model’s sensitivity to object detection in different scenes and at different angles. the backbone of the yolov5s model mainly extracts image features by converting an input image into multilayer feature maps, which are used for subsequent object detection tasks. its structure mainly consists of the focus module, the conv module, the c3 module, and the spatial pyramid pooling-fast (sppf) module. fig. 3 illustrates the architecture of the yolov5s model. fig. 3 architecture of yolov5s model the focus module in yolov5s is used for slice operation. it is designed to process input images efficiently by reducing computation while preserving relevant features. for example, after receiving an input image of the size 608 × 608 × 3, the module performs slice operations to transform it into a feature map of the size 304 × 304 × 12. it then performs a convolution operation, which results in a feature map of the size 304 × 304 × 32. the c3 module comprises three conv modules and several bottleneck modules. each bottleneck module has two convolutional layers. the c3 module enhances the feature extraction capability by increasing the network’s depth. fig. 4 illustrates the architecture of the c3 module. fig. 4 architecture of c3 module 162 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 sppf is an improved version based on spatial pyramid pooling (spp). it processes input through multiple maxpool layers of different sizes to obtain feature information at different scales. these features are then merged. this is completed to address the multiscale problem in object recognition tasks. fig. 5 illustrates the architecture. fig. 5 architecture of the sppf module the neck of the yolov5s model is used for feature fusion and enhancement. it uses the feature pyramid network (fpn) and path aggregation network (pan) structure to combine image features and pass them to the prediction layer. in the fpn structure, information flows from top to bottom, with features from higher layers merged with those from lower layers through upsampling. pan is a feature fusion structure that adds a layer of bottom–top feature fusion following the fpn process. fig. 6 illustrates the architectures. (a) fpn (b) pan fig. 6 architectures of fpn and pan the head of yolov5s is responsible for predicting image features and generating bounding boxes to predict object classes. the detection layer comprises several components, including anchor boxes, convolutional layers, prediction layers, and nonmaximum suppression. b. mobilenetv3 mobilenetv3 is a lightweight cnn that mainly uses depthwise separable convolution to reduce the number of model parameters while maintaining accuracy. in this study, the backbone of yolov5s was replaced with the mobilenetv3-small architecture, named mob_yolov5s, to reduce the number of parameters and achieve more favorable computational speed. fig. 7 illustrates the mobilenetv3-small architecture, and fig. 8 displays the mob_yolov5s architecture. depthwise separable convolution can be divided into two components: depthwise convolution and pointwise convolution. depthwise convolution performs separate convolutions on each channel individually. as displayed in fig. 9, each channel is convolved with a separate kernel. pointwise convolution applies a 1 × 1 convolution kernel to the feature map obtained from depthwise convolution. a flow diagram of this process is presented in fig. 10. advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 163 fig. 7 architecture of mobilenetv3-small fig. 8 architecture of mob_yolov5s 164 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 fig. 9 flow diagram of depthwise convolution fig. 10 flow diagram of pointwise convolution as described in the following formula, s represents the computational cost of the standard convolution, dk represents the kernel size, df represents the feature map size, � represents the number of input channels, and � represents the number of output channels. = × × × × × k k f f s d d m n d d (5) the computational cost of depthwise convolution is denoted as ��, and that of pointwise convolution is denoted as ��, as presented below: = × × × × k k f fdm d d m d d (6) = × × × f fpm m n d d (7) relative to standard convolution, depthwise separable convolution reduces the computational cost by 1 �⁄ � 1 � �⁄ , as illustrated in: 2 1 1+ × × × + × × × = = + × × × × × k k f f f k k f f pd k m m d d m d m n d d s d d m n d d n d (8) fig. 11 architecture of se module advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 165 the introduction of the squeeze-and-excitation (se) module in mobilenetv3 is another improvement. the se module is an attention mechanism designed to improve the performance of deep neural networks. its core concept involves squeeze and excitation, enhancing crucial features while ignoring irrelevant ones, thereby improving the feature extraction ability and overall performance of a model. fig. 11 illustrates the se architecture. during the compression phase, the se module aggregates information from each channel of the input feature map through global average pooling to obtain global statistical information for each channel. this step helps with evaluating the importance of each channel. in the excitation phase, the focus is further extracting the features obtained in the compression phase. the se module uses two fully connected layers to reduce the number of channels and parameters. rectified linear unit and sigmoid activation functions are applied to the output of the fully connected layers. the formulas are presented below. ( ) ( )max 0,=relu x x (9) ( ) 1 1 − = + x sigmoid x e (10) c. efficientnetv2 proposed in 2021, efficientnetv2 is an iteration of efficientnet that addresses the slow training speeds associated with training using large images in efficientnet. efficientnetv2 mainly differs from efficientnet in the following four aspects: (1) module usage: in addition to using the mbconv module, efficientnetv2 uses the fused-mbconv module. the mbconv module uses depthwise separable convolution, which has fewer parameters and computations and is suitable for mobile platforms. however, it cannot fully leverage modern accelerators. therefore, some modules are replaced with fusedmbconv to improve computational performance. (2) expansion ratio: efficientnetv2 uses smaller expansion ratios in the mbconv module because smaller expansion ratios can reduce memory consumption. (3) convolution kernel size: efficientnet uses many 5 × 5 convolution kernels, whereas efficientnetv2 uses 3 × 3 convolution kernels. (4) layer removal: efficientnetv2 removes the last mbconv module of efficientnet to reduce parameter and memory consumption. fig. 12 architectures of mbconv and fused-mbconv fig. 13 architecture of efficientnetv2 model 166 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 fused-mbconv, an enhanced version of mbconv, further improves the computational efficiency and performance of a model. it merges the depth-separable convolution in mbconv into a single standard convolution (conv 3 × 3). fig. 12 illustrates the architectures of mbconv and fused-mbconv, and fig. 13 illustrates the architecture of efficientnetv2. in this study, the original yolov5s backbone was replaced with the efficientnetv2 architecture to create eff_yolov5s to integrate the computational efficiency of efficientnetv2 with yolov5s. the goal is to optimize yolov5s by utilizing the computational efficiency of efficientnetv2 to achieve improved computational speed and performance. additionally, the study compares the effects of different backbones on computational efficiency. fig. 14 illustrates the architecture of eff_yolov5s. fig. 14 architecture of eff_yolov5s d. locate player locations (a03) this study uses a perspective transformation to track and record the positions of players detected by yolov5s. perspective transformation refers to the process of projecting a point from a three-dimensional real-world space onto a twodimensional plane. given that a basketball court is effectively a plane, the transformation of real-world coordinates to image plane coordinates represents a projection from one plane to another. the formula for the perspective transformation is presented in: ′=p hp (11) where � is the perspective transformation matrix that projects the position coordinates �� to the desired top view coordinates �. this formula can be expressed as follows: 00 01 02 10 11 12 20 21 22 ′            ′= =           ′      x h h h x y h h h y w h h h w (12) because the basketball court typically lacks distinct features, this study uses the four corners of the court that are visible to the camera as reference points. fig. 15 illustrates the top view of the field, with the red dots representing �, and fig. 16 presents the real-world view of the court, with the green dots representing ��. the � matrix is derived from coordinates � and ��, the player coordinates in the image are multiplied by this matrix to yield their corresponding top-view positions. advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 167 fig. 15 top view image fig. 16 real-world view of the court 4. experimental results this section presents the results to evaluate the proposed approach. the experiments were performed using an nvidia geforce rtx 3070 gpu, significantly accelerating the training process. detailed software and hardware system configurations used in the experiments are provided in table 2. table 2 hardware equipment item specification cpu amd ryzen5 5600x ram 16gb ddr4-3200 gpu nvidia geforce rtx 3070 operating system windows 10 the data set used in this study primarily comprises images taken from basketball games played on campus, as illustrated in fig. 17. the dataset was generated by recording matches and capturing an image every 2 seconds. a total of 2 different match videos were collected. the data set comprises 1270 images, with 960 used for training, 200 used for validation, and 100 used for testing, accounting for approximately 76%, 16%, and 8% of the total images, respectively. the epoch is set to 300, and the batch size is set to 4. fig. 17 image from the data set table 3 confusion matrix predicted positive predicted negative actual positive tp fn actual negative fp tn 168 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 a confusion matrix was mainly used to evaluate the training results in this study (table 3). the confusion matrix is commonly used in deep learning to evaluate a model’s performance based on precision and recall, as illustrated in: = + tp precision tp fp (13) = + tp recall tp fn (14) fig. 18 illustrates the line chart of the precision of each model during training, gradually converging after about 40 epochs. yolov5s shows slightly higher precision after convergence, about 1% higher than the other two models. fig. 19 illustrates the line chart of recall of each model during training, where yolov5s also shows a slight lead of 1 to 2% over the other two models in terms of recall. in the current study, the mean average precision (map) was considered to be the primary indicator of the proposed model’s performance. the accuracy of object detection was measured using map@0.5, which evaluates the map at an intersection over union (iou) threshold of 0.5. map@0.5:0.95 measures the map over a range of iou thresholds from 0.5 to 0.95. a lower iou threshold indicates less overlap between the detection and target boxes, whereas a higher iou threshold indicates greater overlap. fig. 18 line chart of precision of each model fig. 19 line chart of recall of each model advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 169 the study trained three models, that is, yolov5s, mob_yolov5s, and eff_yolov5s, on the data set. the main evaluation metrics that were used were precision, recall, map@0.5, and map@0.5:0.95. table 4 compares the training results for each model. table 5 presents a comparative analysis of the performance of each model, focusing mainly on differences in the parameters, model size, giga floating point operations per second (gflops), and fps. table 4 comparison table of training results for each model model date yolov5s mob_yolov5s eff_yolov5s precision 97.5% 97.4% 95.8% recall 96.9% 94.4% 94.7% map@0.5 98.3% 98.2% 97.4% map@0.5:0.95 80.9% 72.3% 74.5% table 5 performance comparison chart of each model model date yolov5s mob_yolov5s eff_yolov5s parameters 7.02 × 106 3.5 × 106 5.4 × 106 model size (mb) 13.7 7.08 10.6 gflops 15.8 6.3 6.9 fps (cpu) 12.4 17.5 13.7 after conducting an extensive comparison, it is evident that the performance of the original yolov5s and mob_yolov5s is similar, with only a slight difference in map@0.5:0.95. eff_yolov5s is slightly behind the other two models. mob_yolov5s has the fewest parameters, reducing them by approximately 49.8%. the fps increased from the original 12.4 to 17.5, showing an improvement of approximately 41.1%. the parameters of eff_yolov5s are reduced by approximately 23.08% compared to yolov5s, and the fps is increased by 10.48%. when all factors are considered, mob_yolov5s appears to be the most suitable model for player detection because of its higher precision and recall rates, consistent prediction rates at map@0.5, reduced model parameters, and greater computational efficiency. therefore, the current study uses mob_yolov5s for subsequent player detection tasks. however, the final selection of a model should also be based on a comprehensive evaluation of application scenarios and hardware resources. this study uses a test video segment of approximately 15 seconds for player detection using mob_yolov5s, as illustrated in fig. 20, with player positions subsequently transformed to a top view through perspective transformation. perspective transformation can be used to project the original view of the court onto the top view image, which can facilitate tracking of players. subsequently, the study uses perspective transformation to obtain player tracking information on the top view image, with players from different teams marked with green and red dots, as depicted in fig. 21. fig. 20 mob_yolov5s player detection scene fig. 21 top view image of the player position tracking information 170 advances in technology innovation, vol. 9, no. 3, 2024, pp. 157-171 5. conclusions this study proposes a basketball player detection and analysis system based on yolov5 that enables the detection and analysis of player positions during basketball games. with the introduction of the improved yolov5 model, the system achieves more efficient detection of player positions than the original version does. the improved model achieves improved performance, uses fewer parameters, and achieves more fps. the incorporation of mobilenetv3-small significantly improves the system’s performance because it enables the number of parameters to be reduced by approximately 49.8% and increases the number of fps by approximately 41.1%. further improvement is required to ensure the current system can be adapted to different venues and game conditions. currently, the system can primarily be used for school venues. given the diversity of basketball venues, modifications to the court detection module are necessary to adapt to different court environments. this ensures that the court drawing is specific to each court where it is used. in addition, in the future, the performance of the model can be further optimized to enable it to be applied to 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[23] b. markoski, z. ivanković, l. ratgeber, p. pecev, and d. glušac, “application of adaboost algorithm in basketball player detection,” acta polytechnica hungarica, vol. 12, no. 1, pp. 189-207, 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v10n1(2025)-aiti#14208(01-14).docx advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 english language proofreader: chih-wen teng investigation of effects of process variables on weld bead characteristics in surface coating of 309l stainless steel by wire arc additive manufacturing van thuc dang1, van thao le1,*, trung thanh nguyen2, van luu dao1 1advanced technology center, le quy don technical university, hanoi, viet nam 2faculty of mechanical engineering, le quy don technical university, hanoi, viet nam received 29 august 2024; received in revised form 15 october 2024; accepted 17 october 2024 doi: https://doi.org/10.46604/aiti.2024.14208 abstract coating carbon steel surfaces with stainless steel is a crucial technology in various industries to extend the product lifespan. this study focuses on investigating the effects of process parameters on weld bead characteristics in coating ss309l on carbon steel substrates by wire arc additive manufacturing (waam) and identifying the optimal parameters. the key parameters are current, travel speed, and voltage, while the weld bead characteristics include height, width, and depth of penetration. experimental data and analysis of variance (anova) are employed to develop and evaluate predictive models in minitab software. the results show that the optimal process parameters for coating ss309l on carbon steel substrates by waam are voltage = 22 v, current = 132 a, and travel speed = 0.3 m/min, which improve height and width by 56.71% and 25.87%, respectively, while reducing the depth of penetration by 21.74% compared to the worst-case scenario. keywords: waam, surface coating, 309l stainless steel, optimization 1. introduction stainless steels are commonly used for components that need to withstand corrosive environments due to their excellent resistance to rust and corrosion. however, stainless steel is much more expensive than carbon steel, making it especially costly for parts with large structural dimensions. to reduce material costs, stainless steel is often applied as a coating on carbon steel components used in various industries, including nuclear applications [1], petrochemical industries [2], and desalination processes [3]. this approach not only maintains the desired properties of stainless steel in the outer layer but also leverages the cost-effectiveness and strength of carbon steel as the core material. additionally, the use of stainless-steel coatings can extend the lifespan of carbon steel components, reduce maintenance costs, and enhance overall performance in harsh environments. wire arc additive manufacturing (waam) is a metal 3d printing technology, which utilizes a welding arc source to melt the metal wire and form a 3d physical part layer-by-layer. this method offers a promising approach for producing medium to large-sized metal parts or coating and repairing applications. waam provides an elevated rate of material deposition (4-8 kg/h) and lower equipment investment costs compared to other metal 3d printing technologies [4]. in waam, the arc source can be gas metal arc welding (gmaw), plasma arc welding (paw), or gas tungsten arc welding (gtaw). among these, the waam process using gmaw has a deposition rate two to three times higher than that using gtaw and paw [5]. therefore, the waam process using a gmaw source is more suitable for manufacturing large-dimensional parts. * corresponding author. e-mail address: vtle@lqdtu.edu.vn 2 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 in the waam process, the metal wire is melted and deposited onto a substrate surface following a toolpath to create weld beads, which serve as the fundamental geometric unit for building a part [6]. parts can be constructed by depositing multiple single beads layer by layer (e.g., for thin walls) [7] or by depositing successive layers with overlapping beads (e.g., thick walls) [8]. the shape and quality of a weld bead, such as smoothness and stable form, significantly affect the process stability, and the external and internal quality of the finished parts. the key geometric attributes of weld beads, including the width (wwb), height (hwb), and depth of penetration (dwb) are critical for generating toolpaths. consequently, many studies have focused on predicting weld bead geometries for the waam process. xiong et al. [9] proposed prediction models for the height and width of weld beads in waam of low-carbon steels. they suggested that these models, which offer adequate accuracy, could be used to estimate the size of weld beads for model slicing and toolpath planning. le et al. [10] estimated the optimal parameters for waam of 0.35cr1.9ni0.55mo steels. the part fabricated using the optimal parameters is free of defects, demonstrating their effectiveness. suryakumar et al. [11] developed and validated wwb and hwb models for low-carbon steels based on experimental data. they proved that these models could predict and optimize process variables for both additive and subtractive manufacturing processes. kumar and maji [12] predicted weld bead characteristics in the waam of ss304l, using the desirability approach (da) to estimate optimal variables. youheng et al. [13] also estimated optimal parameters for waam of bainite steel using da available in minitab software. sarathchandra et al. [14] examined the influence of process parameters on weld bead geometries of ss304 produced by waam. they employed the response surface methodology (rsm) to identify optimal input variables. concerning surface coating, switzner and yu [2] coated austenitic stainless steel onto low-carbon steel using three different processes: fusion welding, hot roll bonding, and inertia friction welding. in this study, the interfaces of claddings made by three different processes were compared regarding the microhardness, composition, phase, morphology, and etching response. pravin kumar et al. [15] studied the microstructure and electrochemical corrosion behavior of ss308l coating on the surface of ss aisi 321 using robotic-gmaw for repair applications. recently, bozeman et al. [16] clad ss309l wire onto carbon steel substrates using laser-wire directed energy deposition. they examined the effects of processing parameters (laser power and travel speed) on metallurgical bonding and microstructures. cracking, stubbing, and delamination flaws are associated with insufficient heat input while wire dripping problems are associated with excessive heat input. although research has been performed on the surface coating of stainless steels on carbon steel substrates, as mentioned above, a systematic investigation on the influence of process parameters on weld bead characteristics in the coating of ss309l applied to carbon steel surfaces by waam has not reported yet. therefore, the objectives of this study are twofold: (1) exploring the effects of waam parameters for coating ss309l on carbon steel plates (2) identifying the proper parameters to ensure the deposition of a weld bead with maximal wwb, maximal hwb, and minimal dwb to achieve these goals, the analysis of variance (anova) is used to identify the significance of individual process parameters and their interactions with the quality of the coating. anova helps in understanding the contribution of each parameter to the overall performance, thereby guiding the optimization process. the desirable function method, which provides a robust framework for parameter optimization, is used to identify the proper process parameters. 2. experimental methodology in this section, the raw materials and the waam system used in the study are first presented. subsequently, the experiment method is introduced. the experiments include two steps: (1) determining the range of process parameters (2) designing of experiment and collecting data for the mode development advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 3 2.1. materials ss309l is an austenitic stainless steel, notable for its excellent corrosion resistance and high-temperature resistance. jis g 3101 carbon steel is a popular structural material due to its high mechanical strength and low cost. the coating of ss309l on the surface of carbon steel enhances the corrosion resistance of the carbon steel plate. in this study, experiments were performed using ss309l welding wire with a diameter of 1.2 mm and jis g 3101 steel plates with a size of 200 mm in length, 200 mm in width, and 10 mm in thickness. the chemical compositions of ss309l welding wire and jis g 3101 steel substrate are detailed in table 1. the waam system consists of a panasonic ta-1400 welding robot arm equipped with a gmaw power source (fig. 1). argon gas with a purity of 99.99% and a flow rate of 16 l/min was employed to protect the molten metal during the deposition. table 1 chemical elements of ss309l and jis g 3101 steel (in wt.%) materials mn ni cr mo si c p s fe ss309l wire 2 14 23 0.05 1 0.02 balanced jis g 3101 steel plate <5 <5 balanced fig. 1 the waam robot system 2.2. experiment procedure and data collection the experiment was conducted through the steps below: step 1: determining the range of process parameters: to establish the upper and lower limits of each input process parameter, several experimental runs were conducted to produce single weld beads. the parameter levels were chosen based on the recommended ranges provided by suppliers for traditional welding processes. specifically, the welding current (i) ranged from 100-160 a, the voltage (u) was adjusted between 16 v and 25 v, and the travel speed (v) varied from 0.3-0.6 m/min. these experiments were conducted in the previous study [17]. after analyzing the effects of process parameters on the geometric characteristics of the single weld bead (fig. 2), the following ranges were identified as suitable for metal deposition applications: i = 120-150 a, v = 0.3-0.45 m/min, and u = 19-22 v. these settings enable the production of continuous weld beads with minimal spatter. step 2: experiment design and data collection: the study focused on three process parameters: u, i, and v as these factors significantly affect the weld beads’ characteristics. each parameter was tested at four different levels (see table 2). the experiment campaign was created using the taguchi-l16 method. the taguchi method in experimental design offers several advantages, such as saving time and costs using orthogonal arrays, allowing for quick optimization of factors affecting product quality. it is also easy to apply, helping to improve the reliability and quality of products by creating designs that are less sensitive to variations. consequently, 16 experimental runs were conducted (table 3). 4 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 fig. 2 the process parameter window for the weld bead morphology [17] table 2 input parameters and its levels input parameters level 1 level 2 level 3 level 4 i (a) 120 130 140 150 u (v) 19 20 21 22 v (m/min) 0.3 0.35 0.4 0.45 table 3 experiment results exp. runs process parameters attributes u (v) i (a) v (m/min) wwb (mm) hwb (mm) dwb (mm) 1 19 120 0.30 4.04±0.08 2.36±0.10 0.48 2 19 130 0.35 4.13±0.08 2.28±0.09 0.65 3 19 140 0.40 4.28±0.05 2.22±0.04 0.74 4 19 150 0.45 3.98±0.09 2.39±0.12 0.72 5 20 120 0.35 4.32±0.06 2.18±0.08 0.62 6 20 130 0.30 4.56±0.10 2.48±0.07 0.59 7 20 140 0.45 4.14±0.06 1.95±0.08 0.64 8 20 150 0.40 4.42±0.05 2.34±0.05 0.75 9 21 120 0.40 4.22±0.06 2.08±0.07 0.63 10 21 130 0.45 4.34±0.11 1.80±0.09 0.58 11 21 140 0.30 5.33±0.10 2.53±0.07 0.73 12 21 150 0.35 4.96±0.05 2.33±0.13 0.88 13 22 120 0.45 4.02±0.06 1.64±0.06 0.69 14 22 130 0.40 4.33±0.11 1.98±0.07 0.52 15 22 140 0.35 4.74±0.16 2.23±0.11 0.59 16 22 150 0.30 5.76±0.09 2.40±0.12 0.99 after fabricating the weld bead samples, the characteristics (wwb, hwb, and dwb) were measured (see fig. 3). they are critical in the waam process. measurements were taken in the weld beads’ stable zone (fig. 4) using a digital caliper, which features 0.01 mm and ±0.02 mm in resolution and accuracy, respectively. for wwb and hwb, to address measurement uncertainties, five measurements were performed at five positions in the stable region of the weld beads, as described in fig. 4, and the mean of the measured results was calculated for analysis. meanwhile, dwb was determined from optical images of the weld bead cross-sections captured by an optical microscope (fig. 5). the results from the experiment and the measured data are presented in table 3. the standard deviation errors of the mean values for wwb and hwb are presented in table 3. these errors indicate the inherent variability of the weld in practical applications. in this case, the deviations are around ± 0.10 mm, indicating the high accuracy and reliability of measured data. advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 5 fig. 3 the geometric parameters of the single weld fig. 4 sixteen single weld lines fig. 5 cross section of the welding beads 2.3. optimization method to assess the influence of process parameters and their contribution to each characteristic, anova in minitab software was utilized. this statistical analysis was performed with 95% confidence and 5% significance. for multi-objective optimization problems, desirability function (df) and rsm are two popular approaches, particularly in the context of experimental design and process improvement. the df method allows for the simultaneous optimization of multiple conflicting objectives, while rsm often requires data to follow complex regression models (e.g., quadratic polynomial models), which may not be suitable in all cases. moreover, once the regression models are developed by rsm, df can be used to identify the optimal process parameters. therefore, the df method was adopted in this study. in the case of surface coating by waam, the goal is to maximize wwb and hwb while minimizing dwb to improve productivity and reduce the heat-affected zone in the substrate material. the criteria for optimization are described below: { }find , , that { } while { } subject to (v) [19;22]; (a) [120;150]; (m/min) [0.3;1.45] = ∈ ∈ ∈ wb wb wbx u i v maximizing w and h minimizing d u i v (1) 6 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 the df approach is described as follows: each response ri is transformed into a desirability index dfi, within the range of [0, 1], depending on whether ri is beneficial or costly. the corresponding equations for both types of responses are provided below. ( ) ( ) ( ) 0, , ( ) , , 1, , ∈ −∞  −  = ∈  −   ∈ +∞  i r i i i i i r min r min df r r min max max min r max (2) ( ) ( ) ( ) 0, , ( ) , , 1, , ∈ −∞  −  = ∈  −   ∈ +∞  i r i i i i i r min max r df r r min max max min r max (3) where min = min(ri), max = max(ri), and r indicates the form factor of dfi. finally, the df is calculated by: 1 1 1 = =        = ∏ m m ii i w w i i df df (4) where wi signifies the weight of the i-th response, and m is the number of responses. herein, the value of r is equal to 1, and the weight for each response is set equally, w1 = w2 = w3 = 1/3. taking a calculation example based on the data given in table 3, max(wwb) = 5.76 mm, min(wwb) = 3.98 mm, max(hwb) = 2.53 mm, min(hwb) = 1.64 mm, max(dwb) = 0.99 mm, min(dwb) = 0.48 mm. in this study, wwb and hwb are the beneficial responses, while dwb is the costly response. as a result, for run #1, df1(wwb) = (4.04 − 3.98) / (5.78 − 3.98) = 0.0333 df1(hwb) = (2.36 − 1.64) / (2.53 − 1.64) = 0.8090, and df1(dwb) = (0.99 − 0.48) / (0.99 − 0.48) = 1. finally, the df corresponding to run #1 is calculated as: df(#1) = (0.0337 × 0.8090 × 1)1/3 = 0.0091. 3. results and discussion in this section, the results of the model development are first presented. the evaluation of the developed model with anova results is also introduced. thereafter, the effects of process parameters on the weld bead characteristics are discussed. lastly, the results of the optimization problem are presented with a comparison with the worst case. 3.1. anova results for the developed models the developed models of wwb, hwb, and dwb are described by the following formulas, respectively. these models were developed using minitab software. 43.5 3.03 0.063 63.5 0.00382 2.126 0.2901 0.0649 0.000074 19.5 = − + × + × + × + × × − × × − × × − × × − × × + × × wbw u i v u i u v i v u u i i v v (5) 20.01 1.707 0.0732 3.30 0.00691 0.876 0.0865 0.0119 0.000156 1.95 = − + × + × + × − × × − × × + × × − × × + × × − × × wbh u i v u i u v i v u u i i v v (6) 4.67 0.230 0.0407 31.84 0.000295 0.40 0.1832 0.0025 0.000450 1.00 = − + × − × + × − × × − × × − × × − × × + × × + × × wbd u i v u i u v i v u u i i v v (7) advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 7 the p-values in the regression model enable the identification of significant and insignificant terms of the model. if the p-value <0.05, the model and the model terms are considered significant. on the other hand, a p-value >0.05 indicates insignificant terms. for determination coefficients of the models, r-squared (r-sq) is used to assess the fit of the model to the data. a higher r-sq value indicates that the model explains the variability in the data better. however, a high r-sq value does not always mean the regression model is valid. adding variables, whether statistically significant or not, will always increase the r-sq value. in other words, a model with a high r-sq value might still perform poorly in predicting new data or estimating the average response. therefore, the adjusted r-squared (r-sq(adj)), a modified version of r-sq that accounts for the number of predictors in the model, is preferred. unlike r-sq, the r-sq(adj) can decrease if new variables do not improve the model significantly. this makes it a more reliable metric for comparing models with different numbers of predictors. moreover, if the predicted rsquared (r-sq(pred)) is in reasonable agreement with the r-sq(adj), i.e., their difference is less than 0.2, this suggests that the model maintains a good balance between predictive accuracy and the adjustment for the number of predictors, thereby reinforcing the reliability of the results. for the wwb model (eq. (5) and table 4), the p-values of the model terms (v, u, u × v, and i × v) are less than 0.05, meaning that they are significant terms of the model. meanwhile, the p-values of other model terms are bigger than 0.05, indicating they are not significant in the wwb model. the r-sq, r-sq(adj), and r-sq(pred) values are 98.18%, 95.46%, and 87.73%, respectively demonstrating that the wwb model has good accuracy and can reliably predict responses across the entire design space. table 4 anova results for wwb source df seq ss contribution adj ss adj ms f-value p-value regression 9 3.66586 98.18% 3.66586 0.407318 36.04 0.000 u (v) 1 0.93355 25.00% 0.06925 0.069245 6.13 0.048 i (a) 1 0.94135 25.21% 0.00391 0.003915 0.35 0.578 v (m/min) 1 1.38706 37.15% 0.12197 0.121967 10.79 0.017 u × i 1 0.01284 0.34% 0.01284 0.012844 1.14 0.327 u × v 1 0.09943 2.66% 0.09943 0.099429 8.80 0.025 i × v 1 0.18519 4.96% 0.18519 0.185194 16.39 0.007 u × u 1 0.06734 1.80% 0.06734 0.067340 5.96 0.050 i × i 1 0.00087 0.02% 0.00087 0.000870 0.08 0.791 v × v 1 0.03822 1.02% 0.03822 0.038220 3.38 0.116 error 6 0.06780 1.82% 0.06780 0.011301 total 15 3.73366 100.00% r-sq = 98.18% r-sq(adj) = 95.46% r-sq(pred) = 87.73% for the hwb model, as indicated in eq. (6) and table 5, the p-values for u, u × i, u × v, and i × v are less than 0.05, whereas the p-values for i and v are greater than 0.05. thus, u, u × i, u × v, and i × v are identified as significant terms in the hwb model. the coefficients r-sq, r-sq(pred), and r-sq(adj) are 98.30%, 82.68%, and 95.76%, respectively, demonstrating that the hwb model has reasonable accuracy and is suitable for predicting responses throughout the entire design space. table 5 anova results for hwb source df seq ss contribution adj ss adj ms f-value p-value regression 9 0.921644 98.30% 0.921644 0.102405 38.63 0.000 u (v) 1 0.128160 13.67% 0.022030 0.022030 8.31 0.028 i (a) 1 0.201804 21.52% 0.005361 0.005361 2.02 0.205 v (m/min) 1 0.509762 54.37% 0.000330 0.000330 0.12 0.736 u × i 1 0.042035 4.48% 0.042035 0.042035 15.86 0.007 u × v 1 0.016879 1.80% 0.016879 0.016879 6.37 0.045 8 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 table 5 anova results for hwb (continued) source df seq ss contribution adj ss adj ms f-value p-value i × v 1 0.016461 1.76% 0.016461 0.016461 6.21 0.047 u × u 1 0.002256 0.24% 0.002256 0.002256 0.85 0.392 i × i 1 0.003906 0.42% 0.003906 0.003906 1.47 0.270 v × v 1 0.000380 0.04% 0.000380 0.000380 0.14 0.718 error 6 0.015904 1.70% 0.015904 0.002651 total 15 0.937548 100.00% r-sq = 98.30% r-sq(adj) = 95.76% r-sq(pred) = 82.68% in the dwb model, as shown in eq. (7) and table 6, the p-value for v is less than 0.05, while the p-values for u and i are greater than 0.05. this indicates that v is the significant factor in the model. the coefficients r-sq, r-sq(adj), and r-sq(pred) are 98.19%, 95.49%, and 86.29%, respectively, suggesting that the dwb model has a high degree of accuracy and can reliably predict the responses throughout the entire design space. table 6 anova results for dwb source df seq ss contribution adj ss adj ms f-value p-value regression 9 0.244309 98.19% 0.244309 0.027145 36.27 0.000 u (v) 1 0.008405 13.02% 0.000401 0.000401 0.54 0.492 i (a) 1 0.121680 48.91% 0.001663 0.001663 2.22 0.187 v (m/min) 1 0.004205 1.69% 0.030650 0.030650 40.95 0.001 u × i 1 0.000077 0.03% 0.000077 0.000077 0.10 0.760 u × v 1 0.003520 1.41% 0.003520 0.003520 4.70 0.073 i × v 1 0.073822 29.67% 0.073822 0.073822 98.63 0.000 u × u 1 0.000100 0.04% 0.000100 0.000100 0.13 0.727 i × i 1 0.032400 13.02% 0.032400 0.032400 43.29 0.001 v × v 1 0.000100 0.04% 0.000100 0.000100 0.13 0.727 error 6 0.004491 1.81% 0.004491 0.000748 total 15 0.248800 100.00% r-sq = 98.19% r-sq(adj) = 95.49% r-sq(pred) = 86.29% 3.2. correlation between process parameters and characteristics fig. 6(a) illustrates that wwb increases as u and i are increased, whereas wwb decreases with higher v. as indicated by the anova results, v has the most significant influence on wwb, contributing 37.15%, followed by the i with 25.21%, and u with 25.00% contribution. the influence of these parameters on wwb can be explained as follows. increasing the voltage results in a larger arc length and spread, which leads to a wider wwb [14]. an increment in i boosts the wire feed speed and the amount of deposited material, leading to a larger molten pool and wider weld beads [18]. on the other hand, higher v decreases the quantity of deposited material per unit length, resulting in wwb being narrower [14]. fig. 6(b) to fig. 6(d) show the interactive effects of process variables on wwb. they reveal that wwb increases with u across all values of i and v (fig. 6(b) and fig. 6(c)) and decreases with higher v for all values of u and i (fig. 6(c) and fig. 6(d)). fig. 7(a) presents the main effects of process parameters on hwb. it is found that an increase in u and v leads to decreasing hwb. on the other hand, hwb increases when i augment. as indicated by the anova results (table 5), v has the most significant influence on wwb, contributing 54.37%, followed by i with 21.52%, and u with 13.67% contribution. the amount of material deposited into the workpiece per length unit reduces when v increases. therefore, hwb decreases [14-19]. as u increases, the arc spreading zone becomes wider. as a result, the weld bead is flatter [20]. hence, hwb shows a decreasing tendency with the increase in u. on the other hand, when i increase, the wire feed speed increases. thereby, the deposited material amount rises, thus hwb also increases [14]. fig. 7(b) to fig. 7(d) show the interactive effects of process variables on hwb. they reveal that hwb increases when v decreases (fig. 7(c) and fig. 7(d)). advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 9 (a) direct effects of process parameters on wwb (b) interactive effect of u, i on wwb (c) interactive effect of u, v on wwb (d) interactive effect of i, v on wwb fig. 6 direct and interactive impacts of process parameters on wwb 10 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 (a) direct effects of process parameters on hwb (b) interactive effect of u, i on hwb (c) interactive effect of u, v on hwb (d) interactive effect of i, v on hwb fig. 7 direct and interactive impacts of process parameters on hwb advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 11 (a) direct effects of process parameters on dwb (b) interactive effect of u, i on dwb (c) interactive effect of u, v on dwb (d) interactive effect of i, v on dwb fig. 8 direct and interactive impacts of process parameters on dwb 12 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 for dwb, as shown in fig. 8(a), it decreases when the i increases from 120 a to 130 a. however, dwb significantly increases as the current rises from 130 a to 150 a, with a slight increase in dwb as the current continues to increase. conversely, dwb decreases as u and v increase. these observations are supported by the results of anova (table 6). it is indicated that i have the greatest impact on dwb, contributing 48.91%. the interaction terms i × v and i × i contribute 29.67% and 13.02%, respectively, while u and v have contributions of 13.02% and 1.69% to dwb. fig. 8(b) to fig. 8(d) show the interaction influence of process parameters on dwb. the correlation between the process parameters, including u, i, and v, and output characteristics such as wwb, hwb, and dwb has been confirmed in several previous studies [14, 18]. research shows that voltage and current significantly affect the wwb and hwb. specifically, increasing the voltage typically leads to a greater weld width due to higher temperatures, while the current influences the weld height, which can either increase or decrease depending on specific conditions. to increase the weld width and height, the voltage can be raised, and the current can be adjusted accordingly. however, if a reduction in the dwb is desired, reducing the v will increase the contact time with the material, thereby reducing penetration. these relationships emphasize the importance of optimizing process parameters to achieve desired characteristics in the welding process, while also improving the efficiency and quality of the surface coating. 3.3. optimization results table 7 solutions of optimization solution u (v) i (a) v (m/min) fit wwb (mm) fit hwb (mm) fit dwb (mm) composite desirability 1 22.0000 132.121 0.300000 0.544773 2.56572 5.06227 0.809781 2 22.0000 120.000 0.300000 0.408409 2.72990 4.56606 0.690246 3 21.2127 120.000 0.330071 0.494544 2.46544 4.40845 0.599427 in the context of optimization, composite desirability typically refers to a composite index used to measure the level of desirability of various responses or objectives based on multiple criteria. composite desirability is used to evaluate how well a set of responses is optimized overall by the settings. desirability has a range of zero to one. one represents the ideal case; zero indicates that one or more responses are outside their acceptable limits. the optimization results are shown in table 7, where the three solutions with the highest composite desirability are indicated among all solutions. fig. 9 optimization plot advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 13 the solution to the multi-attribute optimization problem (eq. (1)) is illustrated in fig. 9. the optimal input variables are u = 22 v, i = 132 a, and v = 0.3 m/min. these parameters correspond to a composite desirability value of 0.8098 and predicted responses of wwb = 5.06 mm, hwb = 2.57 mm, and dwb = 0.54 mm. compared to the worst-case scenario (experiment run #13) where hwb was minimum, the optimal parameters improved hwb and wwb by 56.71% and 25.87%, respectively, while reducing dwb by 21.74% (table 8). the obtained optimal parameters and resulting weld bead characteristics can generate toolpaths in coating ss309l on carbon steel surfaces, paving the way for applications in industries such as desalination, petrochemicals, and nuclear energy. table 8 evaluation of optimal results process parameters attributes u (v) i (a) v (m/min) wwb (mm) hwb (mm) dwb (mm) exp. run 13 22 120 0.45 4.02 1.64 0.69 optimal solution 22 132 0.3 5.06 2.57 0.54 comparison -25.87% -56.71% -21.74% 4. conclusions in this study, the influences of process parameters on single weld beads in the surface coating of ss309l by waam are investigated. the focus is placed on predicting how the process parameters (u, i, and v) influence the weld bead characteristics (including wwb, hwb, and dwb), and on finding the proper process parameters for coating applications of waam. the key outcomes are summarized below: (1) the torch movement speed v features the greatest impact on hwb and wwb, while i show the highest influence on dwb. when u rises wwb increases, while dwb and hwb decrease. meanwhile, increasing i lead to a decrease in wwb and hwb. dwb significantly increases as the current rises from 130 a to 150 a, with a slight increase in dwb as the current continues to increase. alternatively, increasing v leads to a reduction in wwb and hwb. (2) the developed models of wwb, hwb, and dwb exhibit acceptable accuracy, with r-squared values of 98.18%, 98.30%, and 98.19%, respectively. these models can predict the weld bead characteristic in waam of ss309l across the entire design space. (3) the proper parameters for coating ss309l on carbon steel substrate using waam are i = 132 a, u = 22 v, and v = 0.3 m/min with a composite desirability value of 0.8098. the optimal parameters enhance hwb and wwb by 56.71% and 25.87%, respectively, while reducing dwb by 21.74% compared to the worst-case scenario. the results of this study can be utilized for future research, including investigations into the microstructure, mechanical properties, wear resistance, and corrosion resistance of ss309l coatings on carbon steel surfaces using waam. additionally, these findings may be applied in various industries, such as desalination, petrochemical, and nuclear sectors. acknowledgments this research is funded by the le quy don technical university research fund under the grand number “23.1.55”. conflicts of interest the authors declare no conflict of interest. references [1] i. s. kim, j. s. lee, and a. kimura, “embrittlement of er309l stainless steel clad by σ-phase and neutron irradiation,” journal of nuclear materials, vol. 329–333, part a, pp. 607-611, 2004. 14 advances in technology innovation, vol. 10, no. 1, 2025, pp. 01-14 [2] n. switzner and z. yu, “austenitic stainless steel cladding interface microstructures evaluated for petrochemical applications,” welding journal, vol. 98, no. 2, pp. 50s-61s, 2019. 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[20] s. jindal, r. chhibber, and n. p. mehta, “effect of welding parameters on bead profile, microhardness and h2 content in submerged arc welding of high-strength low-alloy steel,” proceedings of the institution of mechanical engineers, part b: journal of engineering manufacture, vol. 228, no. 1, pp. 82-94, 2014. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v9n3(2024)-aiti#13503(186-196).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 english language proofreader: chih-wen teng a study of acoustic parameters of transformer oil based on its water content utilizing a single ultrasonic sensor firnanda pristiana nurmaida, agus indra gunawan*, raden sanggar dewanto department of electrical engineering, politeknik elektronika negeri surabaya, surabaya, indonesia received 23 march 2024; received in revised form 01 june 2024; accepted 02 june 2024 doi: https://doi.org/10.46604/aiti.2024.13503 abstract the health of a transformer is affected by several aspects, including water content in transformer oil. researchers have introduced various techniques for measuring water content in transformer oil. in the case of acoustical measurement, researchers typically utilize two ultrasonic sensors to detect acoustical parameters. this study proposes a novel technique to characterize transformer oil based on its water content using a single ultrasonic sensor. this technique employs an indirect measurement approach, where a substrate separates the oil from the sensor. the echoes from measurements are observed and presented in terms of three acoustical parameters, i.e., the acoustic speed, acoustic impedance, and density. based on measurement results, the acoustic speed of the samples is successfully calculated from the time of flight and the thickness of the chamber. however, only four materials used as substrate 1, i.e., 3mm, 5mm, 8mm acrylic, and 3mm glass, successfully produce similar plots of acoustic impedance and density. keywords: transformer oil, ultrasonic, acoustic speed, acoustic impedance, water content 1. introduction one of the most important and expensive parts of the transmission and distribution process of electricity is the transformer. throughout its operational lifespan, oil-immersed transformers are exposed to electrical, thermal, and chemical pressures that potentially deteriorate their paper-to-liquid insulation, leading to decreased efficiency. this underscores the significance of transformer oil as the primary factor influencing the transformer’s durability. various factors can impact the staged production during the operation of transformers, especially moisture contamination. ensuring the moisture levels in the insulation system are properly controlled holds great significance as it can decelerate the aging of paper insulation and protect the system. a survey by ieee shows that almost 50% of transformer failures are caused by insulation damage. this further substantiates the importance of diligently upholding the integrity of the insulation system [1]. to enhance the efficiency of the transformer, improvements to the insulator materials i.e., oil and paper must be done. one way to improve insulator material is by adding nanoparticles to transformer oil, which can improve heat transfer and voltage breakdown of transformer insulation. observations of the addition of mwcnts-oh nanofluid on transformer performance have been successfully carried out, which shows that the addition of mwcnts-oh nanofluid has better thermal performance than pure oil, which prevents temperature increases in the transformer and can also be used as electrical insulation in transformers [2]. this research was then continued by adding mwcnts-doped tio2 nanoparticles synthesized in transformer oil, which showed that nanofluid with 0.1 wt% had good performance compared to other nanofluid concentrations * corresponding author. e-mail address: agus_ig@pens.ac.id advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 187 [3]. from previous research [2-3], a comprehensive discussion on the potential of znfe2 and tio2 nanofluids in transformer oil successfully increases the heat transfer efficiency and reduction of breakdown voltage for maintaining transformer insulation [4]. another way to enhance the efficiency of the transformer is by monitoring the moisture condition of insulating paper and oil. the presence of water (moisture) in transformer oil influences the breakdown voltage of transformer oil [5-6]. more moisture causes the breakdown voltage of transformer oil to drop, increasing the potential of transformer failure. therefore, it is important to inspect the water content in transformer oil. an optical method, d-shaped optical fiber coated with a thin layer of platinum is used to measure moisture content detection in transformer oil. experimental results have confirmed that the transverse electric power of d-shaped fibers changes significantly to lower values when insulating oils with different water contents are detected. however, this research requires further research to determine the correlation between the amount of water measured in the laboratory [7]. micro-nano fiber (mnf) based optical sensor is used to establish a connection between moisture in oil and the distribution of the evanescent field. the experimental results show that the detection can achieve real-time measurement of moisture with a sensitivity of 1.8 ppm at a diameter of 800 nm. these sensors are also possible to be immersed directly into the transformer tank for measurement [8]. polyimide-coated fiber bragg grating (fbg) is also used for monitoring water content in transformer oil [9]. those optical methods [7-9] show their ability to determine water content in transformers with some advantages. however, for some reason, the optical method will face difficulties when measuring opaque material or indirect measurement. for this matter, acoustical measurement is superior compared to optical measurement. several studies of water content in the transformer oil are also possible by utilizing acoustic waves [10-12]. in those studies, the authors utilize two ultrasonic sensors which stand as transmitter and receiver. those sensors are touching the transformer oil to obtain oil parameters. this study proposes a novel technique to characterize transformer oil based on its water content using a single ultrasonic sensor. this technique employs an indirect measurement approach, where five substrates — 3 mm, 5 mm, and 8 mm acrylics, and 3 mm and 5 mm glasses are used to separate the oil from the sensor. the echos from measurements are taken, calculated, and presented in terms of three acoustical parameters, i.e., acoustic speed, impedance, and density. in the future, it is expected that the indirect measurement approach will provide a better solution, where measurements can be made directly on the outside of the transformer body, thus simplifying the measurement process. 2. materials and methods this chapter explains the configuration of the system used in this study, including the block diagram, measurement chamber, ultrasonic sensor, and transformer oil. measurement points are also described since this is also an essential part of obtaining the acoustic parameters in this study. 2.1. transformer oil characteristic the main characteristic that determines the condition and age of a transformer is its insulation system, comprising insulating oil and insulating paper. insulating paper tests can be known by conducting the degree of polymerization (dp) test [13-14]. insulating oil is determined by the presence of material, such as air bubbles, fibers, metallic particles [15-16], and water [10-12], which is affected by temperature [17]. in this study, transformer oils produced by apar, poweroil to 20, which is an uninhibited transformer oil meeting iec 296 class i: 1982 standard specification are provided by pt. bambang djaja, a transformer company in indonesia. three transformer oil-water mixed with 8 ppm, 23 ppm, and 33 ppm, verified by moisture in the oil meter from vaisala are used as the samples and shown from left to right in fig. 1. 188 advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 fig. 1 transformer oil-water samples with varying water content 2.2. ultrasonic wave an ultrasonic wave is a longitudinal mechanical wave whose frequency exceeds the hearing limit of the human ear (above 20 khz). employing ultrasonic waves as a sensor device offers numerous benefits, such as its simplicity and ability to penetrate within the tested object or material [18]. in ultrasonic testing applications, extremely brief ultrasonic pulse waves are directed toward objects to identify internal fractures or to characterize the object itself [19-22]. fig. 2 shows two distinct echo signals. the first and third echoes are reflected signals from the front and rear sides of the sample, respectively, while the second echo indicates the presence of the fracture within the investigated object. fig. 2 principle of ultrasonic testing 2.3. the proposed system (a) block diagram system (b) experimental setup fig. 3 the proposed system advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 189 fig. 3 shows the proposed system. the sample is placed in the measurement container, which has 60 mm for length, 140 mm for width, and 10 mm for height as shown in fig. 3(b). the measurement container is divided into two chambers, chamber_1 is filled with pure water as a reference, while chamber_2 is filled with a sample. an ultrasonic sensor, p4-10l from siui operating at 4 mhz is employed to convert the electric signal from the signal generator into an acoustic signal. this sensor is positioned at the top of the substrate to measure the sample indirectly. both the trigger and the echo signal are captured by the data acquisition module and then transmitted to a personal computer for observation and analysis as shown in fig. 3(a). a sample will undergo a measurement process 20 times, taken from five different locations on substrate 1, where each location undergoes four measurements. during measurement, the temperature is kept at 24 ℃. as shown in fig. 4, this system comprises 3 layers. acrylic or glass as a substrate 1 is used for the first layer. the second layer consists of the observed sample, divided into two chambers: one for the reference (i.e., pure water) and the other for transformer oil. the third layer is the acrylic layer. fig. 4 measurement chamber two test points, i.e., p1 and p2 are determined. p1 represents the interface between substrate 1 and the sample. at this point, root means square voltage (vrms) and peak-to-peak voltage (vpp) of echoes are measured to obtain the intensity of ultrasonic shown in the voltage unit. p2 represents the interface between the sample and substrate 2. at this point, it is possible to measure the time of flight (tof) of the ultrasonic wave in the reference and sample. furthermore, since the case in this measurement involves only normal incident waves, therefore only pressure wave is taken into consideration. 3. results and discussion this chapter shows the result of measurement based on material used as substrate 1 and also explains the objective of measurement at p1 and p2. after the result was obtained, a keen discussion was provided and shown in the comparison between each material for substrate 1. 3.1. measurement at p1 utilizing 5 mm of acrylic as substrate 1 fig. 5 typical acoustic wave from p1 190 advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 fig. 5 shows a typical acoustic wave from this measurement. several echoes are coming up from the measurement, caused by the different number of acoustic impedances of the material. therefore, the correct echo must be chosen for appropriate calculation. the wave inside the blue rectangle shown in fig. 5 is the first echo of the acoustic signal from the first layer where p1 is measured. in the first step, a reference is needed before measuring the oil transformer. since this study is related to water content inside oil, thus, pure water is chosen as the reference and measured at p1. the result shows 23.67 mvrms and 75.113 mvpp. using a similar manner, samples are measured and the result is shown in table 1. table 1 measurement at p1 no. sample vrms (mv) vpp (mv) 1 pure water 23.67 75.113 2 33 ppm 26.505 96.008 3 23 ppm 26.681 98.157 4 8 ppm 27.468 102.001 these results show that the more water mixed in the oil, the lower the intensity of the ultrasonic echo. the formula for the transmission and reflection coefficient is given below [18]. 1+ =p pr t (1) ( ) 1 2 1 1− = p p t r z z (2) eq. (1) and eq. (2) can be solved to give the pressure transmission and reflection coefficients as follows: 2 1 2 2 = + p z t z z (3) 2 1 2 1 − = + p z z r z z (4) where, rp and tp are the reflection and transmission coefficients of the pressure wave, and z1 and z2 are the acoustic impedance of the first and second material. utilizing eq. (4), the larger the difference in acoustic impedance between the first material and the second material, the higher the value of the signal return ratio. since acrylic is used as substrate 1, it means that 8 ppm water-oil mixed will have the highest intensity of echo compared to 23 ppm, 33 ppm, and pure water. the result of measurement shown in table 1 agrees with eq. (4). fig. 6 and fig. 7 show the graph of table 1. fig. 6 vrms measurement at p1 fig. 7 vpp measurement at p1 based on table 1, it is also possible to obtain the acoustic impedance of the sample. it is known that the acoustic impedance of pure water at 24 ℃ is 1.494 mrayl. to evaluate the acoustic impedance of the sample, the following formulas may be used [23]. advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 191 0 − = + ref sub ref ref sub z z s s z z (5) 0 − = + tgt sub tgt tgt sub z z s s z z (6) where s0 is the transmitted signal, stgt is the reflected signal from the target, sref is the reflected signal from the reference, and ztgt, zref, and zsub are the acoustic impedances of the target, reference, and substrate, respectively. however, since the transmitted signal is unknown, these two equations are combined to obtain the acoustic impedance of the target, as demonstrated below. 1 1     − − = − × + × ×        + +      tgt sub ref tgt sub ref tgt sub ref sub ref ref sub ref z z z zs s z z s z z s z z (7) the acoustic impedance of acrylic ranges from 3.08-3.26 mrayl [18, 23], and pure water at 25 ℃ is 1.494 mrayl [18]. the transformer oil is 1.28 mrayl and 920 kg/m3 for acoustic impedance and density, respectively [18, 23]. the acoustic impedance of acrylic used in this system is unknown, however, its density can be measured by knowing its weight and volume. therefore, utilizing the following formula, the acoustic impedance can be obtained by multiplying the result of acoustic speed and its density. since the thickness of each acrylic is known, the acoustic speed can be calculated by measuring tof. ρ= ×z v (8) where z, �, and v are acoustic impedance, density, and acoustic speed respectively. table 2 shows the result of this measurement. the time flight of acoustic wave inside each acrylic is measured. by knowing the thickness of each acrylic, the acoustic speed inside the acrylic can be calculated. acoustic impedance can be obtained as acoustic speed multiplied by its density. the average acoustic impedance of acrylic in this study is 3.24 mrayls and is considered to be used during this study. table 2 acoustic impedance of acrylic acrylic tof (ns) speed (m/s) density (kg/m3) impedance (mrayls) 3 mm 2284.25 2626.68 1213 3.186 5 mm 3655.06 2735.93 1198 3.277 8 mm 5860.348 2730.21 1195 3.262 average 3.24 using different ways, the acoustic impedance for the reference and sample is calculated utilizing eq. (7). the intensity of the reflected signal from reference and sample are measured using vrms and vpp measurements. the comparison results of the acoustic impedance of the reference and sample expressed in vrms and vpp measurements are shown in table 3. table 3 acoustic impedance of reference and samples no. sample acoustic impedance (mrayl) vrms vpp 1 pure water 1.494 1.494 2 33 ppm 1.349 1.170 3 23 ppm 1.340 1.139 4 8 ppm 1.301 1.085 based on table 3, the higher the water content in the sample, the greater the acoustic impedance, as observed in both vrms and vpp measurements. these results agree with eq. (4), which indicates that the larger difference in acoustic impedance between z1 and z2 leads to higher acoustic reflection intensity, as shown in table 3 and confirmed in table 1. both vrms and 192 advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 vpp measurements show a positive increase in acoustic impedance as the water content increases. referring to the acoustic impedance of new transformer oil as 1.28 mrayl [18, 23], the measurement result from vrms makes more sense compared to vpp. this is because the sample in this study is derived from new transformer oil and supplemented with water. since water has a higher acoustic impedance compared to new transformer oil, it implies that the acoustic impedance of new transformer oil will be equal to or below 1.301 mrayl (8 ppm), a condition met by the vrms measurement. it shows that the measurement result from vrms is more accurate compared to vpp. therefore, for subsequent measurements, only vrms measurement is utilized in this study. 3.2. measurement at p2 utilizing 5 mm of acrylic as substrate 1 measurement at p2 is utilized to obtain the tof of the ultrasonic wave inside the sample. for this purpose, several techniques, i.e., threshold, zero crossing, and cross-correlation method [24-28] are investigated to obtain the best way to determine tof. utilizing the same chamber as illustrated in fig. 3, with a gap of 10 mm, pure water is initially used for investigation. the acoustic speed of pure water at 24 ℃ is 1497 m/s. since the ultrasonic wave travels go and back, the total distance of the ultrasonic wave is 20 mm. table 4 presents the result of the tof measurement. the distance is obtained by multiplying tof and acoustic speed. based on the measurement, the cross-correlation method yields the best result compared to the other two methods and is thus utilized to determine the tof during this study. table 4 time of flight measurement using pure water measurement threshold method zero cross method cross-correlation method speed (m/s) 1497 1497 1497 tof (ns) 12569.77 12607.91 13275.50 distance (mm) 18.817 18.874 19.873 true distance (mm) 20 20 20 error (%) 5.915 5.630 0.633 by dividing 20 mm by tof, the acoustic speed inside samples is determined. the data presented in table 5 indicates that as the water content in the transformer oil increases, the acoustic speed propagating through the oil also increases. these findings align with a similar trend observed in research conducted by zhu et al. [29]. knowing the acoustic impedance of samples from table 3, the density (ρ) of the sample can then be calculated by dividing acoustic impedance by acoustic speed. table 5 shows the tof, acoustic speed, acoustic impedance, and density of the samples. as it is known that the density of pure water at 25 ℃ is 0.998 kg/dm3 and transformer oil is 0.92 kg/dm3 [18], when they are mixed, the density should be between 0.92–0.98 kg/dm3. it is also known that the more water in transformer oil, the density becomes higher. table 5 tof, speed, impedance, and density of transformer oil samples measurement samples 8 ppm 23 ppm 33 ppm pure water tof (ns) 14022.25 13863.94 13798.64 13275.5 speed (m/s) 1426.3 1442.59 1449.42 1497 z (mrayl) 1.301 1.34 1.349 1.494 r (kg/dm3) 0.912 0.929 0.930 0.998 3.3. measurement at p2 using 3 mm and 8 mm of acrylic as substrate 1 in this sub-chapter, the result of 5 mm of acrylic as already explained in the previous sub-chapter will be compared to the 3 mm and 8 mm of acrylic. using a similar way for investigation, table 6 and table 7 show the result for 3 mm and 8 mm of acrylic respectively. the tof of 8 ppm, 23 ppm, and 33 ppm of transformer oil and pure water as shown in table 5, table 6, and table 7 are the same, as the samples are identical and investigated under the same environmental condition. therefore, the acoustic speed of the samples remains unchanged. however, for acoustic impedance calculation, the results shown in table advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 193 5, table 6, and table 7 are different, even though they exhibit a relatively small discrepancy. this is caused by substrate 1, which is composed of a different acrylic material. therefore, the reflected signal stgt captured by the sensor is different, resulting in different acoustic impedance. this disparity will have an impact on its density calculation, as the density is obtained by dividing acoustic impedance by acoustic speed. table 6 tof, speed, impedance, and density of transformer oil samples using 3 mm of acrylic measurement samples 8 ppm 23 ppm 33 ppm pure water tof (ns) 14022.25 13863.94 13798.64 13275.5 speed (m/s) 1426.3 1442.59 1449.42 1497 z (mrayl) 1.299 1.34 1.348 1.494 r (kg/dm3) 0.910 0.929 0.930 0.998 table 7 tof, speed, impedance, and density of transformer oil samples using 8 mm of acrylic measurement samples 8 ppm 23 ppm 33 ppm pure water tof (ns) 14022.25 13863.94 13798.64 13275.5 speed (m/s) 1426.3 1442.59 1449.42 1497 z (mrayl) 1.291 1.336 1.346 1.494 r (kg/dm3) 0.905 0.926 0.928 0.998 3.4. measurement at p2 using 5 mm and 3 mm of glass as substrate 1 in this study, authors also involved 5 mm and 3 mm of glass in observation, utilizing a similar approach as described for acrylic as a substrate 1. a problem arises because the acoustic impedance of the glass used in this study is unknown. according to the literature by cheeke [18], the acoustic impedance of glass spreads from 10.1 to 16 mrayls, depending on the constituent material. to address this problem, measurement of tof is conducted to obtain acoustic speed and measuring weight and volume of glass to obtain its density. subsequently, acoustic impedance is calculated using eq. (8). as depicted in table 8, the acoustic impedance of the two types of glass is different significantly. therefore, in the calculation, the authors consider z = 11.475 mrayls for 3 mm of glass and z = 13.91 mrayls for 5 mm of glass. table 8 measurement of acoustic impedance of glass glass tof (ns) speed (m/s) density (kg/m3) impedance (mrayls) 3 mm 1238.81 4839.45 2371.22 11.475 5 mm 1869.252 5349.73 2600.40 13.91 table 9 and table 10 show the tof, acoustic speed, acoustic impedance, and density of samples using 3 mm of glass and 5 mm of glass respectively. the tof and acoustic speed are unchanged as shown in tables 5, 6, and 7. however, there is a significant difference in the measurement results between 3 mm and 5 mm of glass for its acoustic impedance and density. this disparity may be attributed to the uncertain value of the acoustic impedance of glass, as glass exhibits a wide range of acoustic impedance. other potential factors include disturbances during echo measurement or inhomogeneous in the glass material especially for 5 mm of glass. all results of this study are shown in fig. 8 and fig. 9 in the graph form. table 9 tof, speed, impedance, and density of transformer oil samples using 3 mm of glass measurement samples 8 ppm 23 ppm 33 ppm pure water tof (ns) 14022.25 13863.94 13798.64 13275.5 speed (m/s) 1426.3 1442.59 1449.42 1497 z (mrayl) 1.309 1.339 1.357 1.494 r (kg/dm3) 0.918 0.928 0.936 0.998 194 advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 table 10 tof, speed, impedance, and density of transformer oil samples using 5 mm of glass measurement samples 8 ppm 23 ppm 33 ppm pure water tof (ns) 14022.25 13863.94 13798.64 13275.5 speed (m/s) 1426.3 1442.59 1449.42 1497 z (mrayl) 1.228 1.296 1.336 1.494 r (kg/dm3) 0.861 0.898 0.921 0.998 fig. 8 acoustic impedance measurement results from several substrates fig. 9 density measurement results from several substrates based on measurement results, acoustic speed is successfully calculated from tof and the thickness of the chamber. in this measurement, the presence of substrate 1 will not affect on the measurement process. therefore, the value of acoustic speed is always the same, as shown in tables 5-10. theoretically, the calculation of acoustic impedance and density for all samples must be the same as well, even though substrate 1 is composed of different materials. based on the measurement results shown in fig. 9 and fig. 10, measurements using 3 mm, 5 mm, 8 mm of acrylic, and 3 mm of glass as substrate 1 successfully produce similar plots. this result shows that these materials can be used to characterize the water content in transformer oil in terms of acoustic impedance, and density. however, measurement using 5 mm of glass produced a significantly different plot. this plot will certainly produce incorrect characterization for the acoustic impedance and density. this discrepancy may occur due to the inhomogeneity of the 5 mm glass material resulting in aberrations of the echo [30]. 4. conclusions this study investigates acoustic parameters in transformer oil based on its water content using a single ultrasonic sensor, which serves as both transmitter and receiver. a single ultrasonic sensor, both transmitter and receiver, is used to measure samples through an indirect measurement approach. in this approach, five substrates i.e., 3 mm, 5 mm, and 8 mm of acrylics, advances in technology innovation, vol. 9, no. 3, 2024, pp. 186-196 195 and 3 mm and 5 mm of glasses are used to separate the oil from the sensor. to determine acoustic speed, acoustic impedance, and density, voltage measurements at p1 and p2 are required. vrms measurements were chosen because they provide more accurate information compared to vpp measurements. meanwhile, tof is calculated using the cross-correlation method. based on measurement results, the acoustic speed results of the samples are successfully calculated from tof and the thickness of the chamber. however, only four materials used as substrate 1, i.e., 3 mm, 5 mm, 8 mm of acrylic, and 3 mm of glass as substrate 1 successfully produced similar plots of acoustic impedance and density. however, measurement using 5 mm of glass produced a significantly different plot. this may be caused by the inhomogeneity of 5 mm of glass material, resulting in an error due to aberration in the echo signal. some techniques regarding aberration correction have been introduced to address this issue for future improvements. it is also interesting when this proposed system is exposed to the magnetic field for in-situ measurement. acknowledgment the authors thank to non-destructive test laboratory of politeknik elektronika negeri surabaya for providing the measurement instrument, and the authors also extend sincere thanks to mr. nuswanggono and mr. handipo from pt. bambang djaja for providing water-transformer oil mixed as samples during this research. conflicts of interest the authors declare no conflict of 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[30] r. ali, t. brevett, l. zhuang, h. bendjador, a. s. podkowa, s. s. hsieh, et al., “aberration correction in diagnostic ultrasound: a review of the prior field and current directions,” zeitschrift für medizinische physik, vol. 33, no. 3, pp. 267-291, august 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v9n2(2024)-aiti#13360(99-115).docx advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 english language proofreader: chih-wen teng innovative approach to enhance stability: neural network control and aquila optimization integration in single machine infinite bus systems yogesh kalidas kirange*, pragya nema department of electrical and electronics engineering, oriental university, indore, india received 08 february 2024; received in revised form 05 march 2024; accepted 06 march 2024 doi: https://doi.org/10.46604/aiti.2024.13360 abstract this paper highlights the need to improve the stability of single-machine infinite-bus (smib) systems, which is crucial for maintaining the dependability, efficiency, and safety of electrical power systems. the changing energy environment, characterized by a growing use of renewable sources and more intricate power networks, is challenging established stability measures. smib systems exhibit dynamic behavior, particularly during faults or unexpected load variations, requiring sophisticated real-time stabilization methods to avert power failures and provide a steady energy supply. this paper suggests a complex approach that combines power system stability analysis with a neural network controller enhanced by the aquila optimization algorithm (aoa) to address the dynamic issues of smib systems. the study shows that the aoa-optimized neural network (aoa-nn) controller outperforms in avoiding disruptions and attaining speedy stabilization by exhaustively examining electrical, mechanical, and rotor dynamics. this method improves power system resilience and operational efficiency as demands and technology expand. keywords: aquila optimization algorithm, electrical power systems, neural network, power system stabilizers, single machine infinite bus 1. introduction the stability of single-machine infinite-bus (smib) systems is crucial in the dynamic energy industry since they are essential for facilitating effective energy transmission in electrical grids. conventional techniques for preserving smib system stability face difficulties due to contemporary power grids’ intricate and ever-changing characteristics, underscoring the need for creative solutions. this paper presents a new approach that combines neural network control with the aquila optimization algorithm (aoa) to improve the resilience and flexibility of smib systems. this study aims to use sophisticated artificial intelligence and optimization approaches to provide a solution that exceeds traditional stability tactics, guaranteeing that smib systems can adapt to the evolving power environment. this method substantially enhances operational efficiency and resilience, signifying a crucial change in the quest for dependable energy delivery. 1.1. background in the ever-evolving landscape of global power networks, compounded by factors like renewable energy integration and unpredictable outages, smibs demand cutting-edge stability solutions [1]. traditional linear control methods fail to address the need to address the nonlinear and time-varying dynamics inherent in smibs [2]. urgency arises for innovative methodologies capable of navigating the intricate nature of these systems [3]. this study assesses stability analysis and * corresponding author. e-mail address: yogesh.kirange@gmail.com advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 100 control strategies in the context of smib systems, essential models for broader power systems [1]. while conventional power system stabilizers (psss) prove valuable in mitigating oscillations [4], the escalating uncertainties and dynamic elements necessitate a closer look at advanced control methods [5]. with their ability to grasp complex data relationships, neural networks (nns) and artificial intelligence emerge as promising tools [6]. integrating nns into psss enhances adaptability by capturing nonlinearities [7]. 1.2. the significance of the proposed research the uniqueness of the proposed research lies in its ability to address the deficiencies in the current body of literature by integrating an smib with a pss enhanced by using an aoa-optimized neural network (aoa-nn). this approach aims to improve power system stability by combining the advantages of smib systems, current pss, and the optimization capabilities of aoa. unlike earlier methods, this research introduces a comprehensive framework that ensures precision in presenting results and explores the potential of optimization algorithms and fuzzy neural network (fnn) controllers. this integration is expected to improve electrical power systems’ overall stability significantly. it will provide a more robust and adaptable solution to address issues arising from adverse operating conditions. consequently, the proposed method is the first to connect the existing research with a more comprehensive and practical approach to ensuring power system stability. this paper is organized as follows: section 2 gives a detailed literature review which includes research gaps. section 3 delves into the specifics of the proposed methodologies. the results obtained from the matlab simulations are then shown in section 4, followed by a comprehensive analysis. section 5 offers a concise overview of the findings and concludes the study with some last reflections. 2. literature review kalegowda et al. [1] proposed an innovative way to analyze power system stability that differs from conventional methodologies in 2022. their innovative approach integrates robust taguchi design with particle swarm optimization (pso), as seen in fig. 1. the taguchi-pso tuning approach improves system settings by creating a target function and recognizing changeable factors as particles in a swarm. initialization includes configuring pso parameters and simultaneously establishing taguchi parameters for experimental design. taguchi optimization is used to assess fitness to determine important parameter values that direct updates in pso. the process stops when it converges or reaches the iteration limit. validated optimized parameters via real-world testing to ensure improved performance meets the defined goal function. in 2013, kahl and leibfried [2] emphasized the need to use sophisticated methods in power systems to tackle nonlinear dynamics and low-frequency oscillations under adverse circumstances. a control approach that uses phase data from many units to reduce inter-area oscillations was suggested. in 2020, yang et al. [3] proposed a model predictive controller for managing oscillations by using a unified power flow controller (upfc) to regulate impedance, phase angle, and voltage magnitude accurately, reducing oscillations. model predictive control (mpc) is a sophisticated control technique in diverse engineering applications. mpc often includes forecasting a system’s future actions, creating an optimization challenge, and resolving it to get the best control input. the pseudocode describes an mpc [3] technique. the system constantly observes, forecasts, and optimally modifies control inputs in real-time. the system uses a predictive model, cost function, and constraints to determine the best control sequences, assuring efficient operation and meeting specified requirements at each time step. shetgaonkar et al. [4] explored the use of mpc to reduce synchronism loss in high voltage direct current (hvdc) systems in 2023. their method utilized event tree search in an open-loop scenario to enhance control techniques and improve the system’s ability to withstand disturbances. in 2020, karamanakos et al. [5] showed that a thyristor-controlled series capacitor (tcsc) can enhance transient stability in an smib setup. peng et al. [6] confirmed the advantages of utilizing advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 101 facts devices with nonlinear mpc to preserve stability in difficult situations and manage disruptive occurrences in 2024. during the covid-19 pandemic, therattil et al. [7] introduced a discrete-time nonlinear mpc method that utilizes phasor measurements and tcsc to stabilize multi-machine power systems. in 2022, kamarposhti et al. [8] investigated strategies to improve psss, showing a preference for ant colony optimization (aco) compared to pso and genetic algorithms (ga). wang et al. [9] successfully integrated mpc with a digital signal processor (dsp) in mid-2009, achieving real-time stability and speed optimization, which led to a reduction in inter-area oscillations. fig. 1 flow chart of taguchi particle swarm optimization algorithm [1] rosle et al. [10] and sabo et al. [11-12] explored nn controllers and suggested integrating pso with a multi-level neuro-fuzzy power system stabilizer (mlnfpss) for power system stability in 2018, 2020, and 2021. ray et al. [13] and ramshanker and chakraborty [14] introduced a three-phase series hybrid active filter (shaf) combined with a photovoltaic (pv) system in 2019 and 2022. compared to traditional controllers, they demonstrated improved harmonic correction using a robust extended complex kalman filter (reckf). in 2017 and 2019, srinivasarao et al. [15] and oraibi et al. [16] improved psss for multi-machine configurations by employing adaptive neuro-fuzzy inference systems, while saleem et al. [17] presented an adaptive neuro-fuzzy-based recurrent wavelet control (anrwc) to boost stability. in 2022, cheng et al. [18] developed a hybrid taguchi-pso method to optimize reactive power in submersible pumps. abualigah et al. [19], zhao et al. [20], and aribowo et al. [21] studied the aquila optimization technique for optimizing pid controller settings of dc motors. wu and feng [22] in 2018 examined the development of nns in wireless communication, while islam et al. [23] in 2019 outlined their significant impact in several fields. gupta [24] investigated the flexibility of nns in complex systems, highlighting their ongoing improvement and growing influence on artificial intelligence in 2013. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 102 the research gap in power system stability focuses on the unexplored incorporation of modern technologies like nn control and aquila optimization, particularly in smib systems. the existing research mainly uses traditional methodologies. hence, it is essential to investigate further the combined benefits these new approaches might provide. it is crucial to address these deficiencies to improve adaptive stability and optimize performance in the changing energy environment. the literature review has found twelve notable research deficiencies. the work on taguchi-pso tuning [1] demands a thorough investigation of its performance under various operating situations due to its new methodology. further research is required to explore the problems and limits of the complete control technique for inter-area oscillations [2], explicitly focusing on voltage angle fluctuations. the integration of mpc and upfc [3] for smib stability must be thoroughly investigated in the findings, requiring comprehensive performance measurements for practical feasibility. a thorough comparison of optimization criteria and stability indices is needed to properly appreciate the effectiveness of the discrete-time mpc for hvdc control [4]. extensive validation is needed for the nonlinear mpc [6] for transient stability under various system circumstances, whereas research on real-world application is required for the tcsc-based nonlinear mpc [7]. additionally, the utilization of aco for pss tuning [8] needs comparison with well-established techniques, whereas generator excitation control using dsp-based mpc [9] necessitates further real-time implementation and validation. investigating the computational complexity and training time required for applying an nn controller [10] to improve smib dynamics is necessary. fnn [11] controllers for stability must include sensitivity to uncertainty. the hybrid strategy combining fnns with pso [12] must clarify computing requirements and convergence speed. investigating these factors would significantly improve these advanced methodologies’ practical viability and effectiveness in power system stability research. 3. methods to fill these deficiencies, this research work presents a study that combines an smib with a pss improved by an aoann. this proposed method offers a comprehensive and better solution for power system stability by integrating the strengths of smib systems, modern pss, and the optimization capabilities of aoa. this work introduces a unified framework that guarantees the presentation of rigorous results and investigates the unrealized potential of fnn controllers in combination with optimization methods, which differs from previous techniques. this integration will significantly enhance the overall stability of electrical power systems, offering a more resilient and flexible solution to the difficulties caused by unfavorable operating circumstances. as a result, the technique is a first step in bridging the gap between current research and a more thorough and efficient strategy for power system stability. 3.1. smib system the smib setup is a fundamental model for analyzing transient reactions and stability in power systems. in this configuration, a synchronous generator is connected to an infinite bus, representing the broader power grid. understanding the functioning of the smib system is essential for comprehending the mechanisms by which power systems manage transient stability. below is the mathematical representation of the smib system: the swing equation typically represents the temporal variation of the rotor angle (�) and characterizes the dynamics of the smib system. this equation, is denoted as: 2 2 δ δ + = − emech d d m d p p dtdt (1) eq. (1) reflects the balance between mechanical input and electrical output, determining the angular motion of the generator rotor. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 103 the swing equation’s laplace transform yields the smib system’s transfer function. assuming minor deviations from the equilibrium, the transfer function is expressed as: 2 ( ) 1 ( ) δ = + − emech s p s ms ds p (2) eq. (2) is the transfer function of the laplace transform of the swing equation, which relates the rotor angle deviation to the mechanical power input in the frequency domain, providing insights into the system’s response to disturbances. the stability analysis of the smib system typically involves eigenvalue analysis. the stability characteristics of the system are determined by examining the eigenvalues of the system matrix, which is derived from the linearized equations of motion. the eigenvalues are expressed as: 2 4 2 λ − ± − = ed d mp m (3) stability is determined by the genuine parts of these eigenvalues, with negative real parts indicating stability. the solution to the swing equation provides insights into the dynamic behavior of the smib system over time. the trajectory of the rotor angle illustrates how the system responds to disturbances and how quickly it returns to a stable state. the smib system is a benchmark for stability analysis and control strategy development. its mathematical representation, through the swing equation and associated transfer functions, enables engineers to understand the transient stability of power systems. analyzing the dynamic behavior and stability characteristics of the smib system is foundational for designing effective control mechanisms, such as psss, to ensure the reliable operation of the broader power grid. 3.2. power system stabilizer (pss) the pss is a crucial component of a generator’s excitation system. it is a significant control device that enhances the dynamic stability of a power system. the system’s primary purpose is attenuating oscillations and maintaining stability, particularly in the smib system. to maximize the stability of the excitation system, the pss deliberately inserts an extra stabilizing signal. the mathematical representation of the pss is as follows: in the smib system, the dynamics of the pss can be described by a differential equation. considering a first-order lag model, the dynamic behavior of the pss is given by: ( )δ= − + −pss pss pss pss pss dv t v k v v dt (4) this equation captures the dynamic response of the pss to changes in the rotor angle (��). taking the laplace transform of the differential equation, to obtain the transfer function representation of the pss: ( ) ( ) ( ) 1 ( )δ = = + pss pss pss pss v s k g s v s t s (5) this transfer function relates the pss output to changes in the rotor angle in the frequency domain. the pss signal (����) added to the excitation system is given by: ( ) ( )δ= pss pss v g s v s (6) substituting the transfer function expression: ( ) 1 ( ) δ= − pss pss pss k v v s t s (7) advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 104 this equation emphasizes that the pss signal is proportional to the rate of change of the rotor angle, reflecting the psss role in responding to dynamic deviations. the pss gain and time constant are vital parameters that determine the behavior of the pss. a higher gain increases the influence of the pss on the system, while the time constant dictates the speed of response to changes in the rotor angle. the pss contributes a supplementary stabilizing signal to the excitation system, helping dampen oscillations and improve transient stability in the smib system. the tuning of pss parameters is critical to power system analysis and design, ensuring optimal performance under various operating conditions. dynamic equations, transfer functions, and critical parameters characterize the pss in the smib system. its role is to enhance the dynamic stability of the power system by responding to changes in the rotor angle and providing additional control signals to the excitation system. the careful design and tuning of pss parameters are essential for achieving optimal stability performance in power systems. 3.3. neural network (nn) nns are computational models inspired by the human brain’s complex architecture and operations. nns are used in power system stabilization to give the control system flexibility and learning capabilities. nns are made up of nested nodes that are coupled with predetermined weights and biases. employing a methodical training procedure, these networks can understand complex relationships from the supplied data. an initial input layer, intermediate hidden layers, and a final output layer comprise a nn’s architecture. signal reception occurs in the input layer; after which it is processed further in the hidden levels. the output layer then generates the final output. a distinct weight characterizes each connecting link between nodes, and each node has an associated bias. the activation function (�) in a nn is a crucial component that introduces non-linearity to the model. it determines the output of a neuron, helping the network to learn complex patterns and relationships in the data. in the general equation of an nn, the activation function is applied to the weighted sum of inputs and biases before being passed to the next layer. the mathematical representation is often denoted as, 1 ( ) = = + n i i i y f w x b (8) the role of the activation function is to introduce non-linearities, enabling the nn to learn and approximate complex functions. without activation functions, the nn would behave like a linear regression model, irrespective of the number of layers, as the composition of linear functions remains linear. following are some common examples of activation functions in nn: sigmoid function (logistic): the formula below gives output values between 0 and 1. it is often used in the output layer of binary classification models. 1 ( ) 1 − = + x f x e (9) hyperbolic tangent function (tanh): the hyperbolic tangent function is similar to the sigmoid but outputs values between -1 and 1, making it symmetric around the origin. mathematically, it is represented as: 2 2 1 ( ) 1 − = + x x e f x e (10) rectified linear unit (relu): the relu outputs the input for positive values and zero for negative values, as represented by the following equation. it is widely used in hidden layers due to its simplicity and effectiveness. ( ) max(0, )=f x x (11) advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 105 leaky rectified linear unit (leaky relu): the leaky relu, represented by the equation below, is similar to eq. (11) but allows a small, non-zero gradient for negative inputs, preventing dead neurons, where, � is a small positive constant. ( ) max( , )α=f x x x (12) activation functions play a crucial role in determining the nn’s capability to model complex relationships and improve its overall performance in various tasks. the choice of activation function depends on the specific requirements and characteristics of the problem at hand. the activation function (�) gives the network a hint of non-linearity, which helps it understand complex interactions. the nn is trained to reduce the difference between the expected and actual outputs by exposing it to input-output pairings and fine-tuning the weights and biases. this is usually achieved utilizing optimization techniques, among which gradient descent is famous. an essential technique for training nns, backpropagation coordinates the backward propagation of mistakes across the network. this entails methodically reducing the total error by repeatedly modifying the weights and biases at each layer. in the context of the pss, the nn serves as an adaptive component capable of learning and adapting to the dynamic behavior of the power system. by incorporating an nn into the pss design, the control system becomes more flexible and capable of capturing non-linear relationships and dynamic interactions within the power system. the nn is integrated into the pss design to enhance its adaptability and learning capabilities. the pss, augmented with nns, becomes more adept at responding to varying operating conditions, capturing non-linearities, and providing an improved supplementary stabilizing signal to the excitation system. the weights and biases of the nn are optimized during the training process. the choice of optimization algorithms, such as gradient descent or metaheuristic algorithms like aoa, plays a crucial role in fine-tuning the nn for optimal performance in the pss. 3.4. aquila optimization algorithm (aoa) the aoa is a nature-inspired optimization technique that mimics the hunting behavior of eagles, particularly the aquila genus. it combines exploration and exploitation strategies to efficiently search for optimal solutions in optimization problems. the optimization problem being addressed typically involves an objective function that needs to be minimized or maximized. this function quantifies the quality of a solution based on its parameters. in the algorithm, equations representing the objective function are utilized to evaluate the effectiveness of potential solutions (positions of eagles) within the solution space. equations governing the movement of eagles can be derived from their hunting behavior. for instance, the equations might determine the velocity and direction of eagles’ movements during contour flights and short glide attacks. these equations guide the exploration and exploitation phases, ensuring a balanced search process. to adapt and refine the search strategy over iterations, adaptation equations can be employed. these equations might adjust parameters such as exploration rate, exploitation rate, or the intensity of short glide attacks based on the success or failure of previous iterations. this adaptive mechanism enhances the algorithm’s ability to efficiently explore and exploit the solution space. below is the mathematical representation of the aoa: the high soar with vertical stoop equation shows the hunting technique of a bird of prey, possibly a falcon or an eagle. these birds use a high soar to gain altitude, then perform a vertical stoop, diving sharply down to catch their prey with great speed and precision. it’s a remarkable display of their aerial hunting skills. this equation is denoted as: [ ]1 2( 1) ( ) ( ) ( ) (0,1)+ = + − − +i i ix t x t r gbest t x x t r rand (13) the above equation provides the high soar with a vertical stoop that mirrors the algorithm’s ability to swiftly navigate vast solution landscapes. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 106 the following equation represents contour flight refers to the exploration phase where the algorithm searches the solution space methodically and efficiently, akin to an eagle circling an area to survey its surroundings. also, the short glide attack represents the exploitation phase, where the algorithm converges towards promising solutions with a rapid and targeted approach, resembling the quick, precise dives of an eagle when it spots prey. [ ] [ ] 2 ( ) ( ) ( ) ( )= + −i i if x f x t c gbest t x t (14) the above equation also provides its adeptness at honing in on promising regions with precision. the following equation also mentions another hunting strategy employed by certain birds of prey, where they fly close to the ground or water surface, gradually descending while scanning for prey. this step allows them to approach their target stealthy and precisely before launching their attack. this equation reflects the algorithm’s meticulous approach to refining solutions. [ ] 1 ( ) arg min ( ) = = i i ton lbest t f x t (15) the swooping by walk and grab prey equation describes the hunting behavior of some birds, particularly, herons and egrets. these birds often use a scooping motion with their long bills to catch fish or other prey in shallow water. the by-walk refers to their slow and deliberate movement as they stalk their prey, often forming a distinctive y shape with their neck and body. once they spot their target, they use their sharp bill to grab and secure the prey before swallowing it whole or carrying it away. this following hunting technique highlights their patience, precision, and adaptability to different environments. [ ]3 4( 1) ( ) ( ) ( ) (0,1)+ = + − +i i ix t x t r lbest t x t r rand (16) the algorithm continues its repeated operation until a predefined stopping condition is met. commonly used thresholds for stopping include achieving a specific level of precision or finishing a predetermined maximum number of iterations. the following steps show the aoa: step 1. high soar with vertical stoop: begins by initializing a population of candidate solutions. identifies the global best solution within the population in eq. (9). step 2. contour flight with short glide attack: updates the positions of candidate solutions towards the global best solution, introducing a random perturbation to explore the search space and avoid local minima in eq. (10). step 3. low flight with slow descent attack: evaluate the fitness of candidate solutions and identify the best local solution based on fitness in eq. (11). step 4. swooping by walk and grab prey: updates candidate solution positions towards the local best solution, incorporating a minor random perturbation to exploit the search space around the local best solution in eq. (12). the proposed approach stands out for its user-friendliness, simplicity, and efficiency in identifying effective solutions. despite potential challenges like susceptibility to local minima and convergence speed, its resistance to noise and flexibility in addressing various optimization problems make it a favorable choice. precise parameter selection is crucial, but overall, the advantages outweigh the drawbacks, making it well-suited for optimization tasks when managed effectively. 3.5. research directions (1) avoiding local minima: develop methods to prevent the algorithm from getting trapped in local minima. (2) convergence speed: improve the algorithm’s convergence speed. (3) robustness: enhance the algorithm’s robustness to noise and ill-conditioned problems. (4) theoretical properties: study the theoretical properties of the algorithm to gain deeper insights. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 107 with its inspiration from nature, the aoa demonstrates effectiveness in solving optimization problems. its simplicity, efficiency, and adaptability make it a promising approach, while ongoing research aims to address its limitations and further understand its theoretical foundations. 4. proposed methodology power system stability is crucial for maintaining the dependable and secure operation of electrical networks. it is crucial for maintaining ideal voltage and frequency levels, minimizing chain reactions of failures that might result in widespread power outages, and facilitating the efficient transmission of vast amounts of electricity over long distances. power system stability is essential for enhancing generator and network component performance, enabling the incorporation of renewable energy sources, and averting voltage instabilities like collapses or sags. an established power system improves grid resilience, enabling it to manage better disruptions from natural disasters, equipment failures, or deliberate assaults, and reduces economic losses linked to power failures. industries, organizations, and families depend on a consistent power supply to operate without interruptions, highlighting the importance of power system stability in maintaining continuous and reliable energy delivery. table 1 indicates the research work carried out on various techniques with its limitations as given below. table 1 limitations of existing work carried out ref. research work carried out limitations kalegowda et al. [1] • developed a detailed power system model, including pss. • identified critical pss parameters affecting stability. • used pso for parameter optimization, with the taguchi method to evaluate parameter effects systematically. • effectiveness relies on the accuracy of power system modeling. • may not address extreme or rapidly changing conditions thoroughly. • specific findings might not apply universally across different systems or conditions. kahl and leibfried [2] • modeled the power system for mpc application. • designed a decentralized control scheme. • developed mpc algorithms for each subsystem. • tested via simulations under various conditions. • scalability issues in large systems. • high computational demand of mpc. • dependence on reliable communication between components. • need for accurate system models for effective control. • challenges in responding to rapid system changes. yang et al. [3] • modeled mmc-upfc and grid. • designed mpc for mmc-upfc. • analyzed unbalanced grid scenarios. • simulated control performance. • evaluated effectiveness and stability. • compared with traditional controls. • success hinges on precise mmc-upfc and grid modeling. • high computational requirements may hinder real-time deployment. • predicting performance in highly variable unbalanced conditions is complex. • more complex than traditional control systems. • might need adjustments for different grid scenarios. shetgaonkar et al. [4] • detailed system modeling. • integrated of mpc into mtdc. • designed of protection mechanisms. • simulated for performance testing. • dynamic response analysis. • effectiveness evaluation for stability. • compared with traditional methods. • success tied to accurate modeling of mmc-based mtdc systems. • mpc may pose computational challenges for real-time implementation. • adapting to rapid power system changes may be complex. • integrating protection within mpc adds system complexity. • applicability might vary across diverse mtdc system setups. karamanakos et al. [5] • detailed system modeling. • optimized control horizon. • tuned parameters for improved performance. • simulated studies for analysis. • explored real-world challenges. • evaluated results and discussed encountered challenges. • accuracy relies on detailed power electronic system modeling. • mpc might demand significant computational resources, impacting real-time use. • performance is sensitive to changes in system parameters. • balancing accuracy and computation time in control horizon selection. • adapting theoretical models to real-world scenarios can be challenging. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 108 table 1 limitations of existing work carried out (continued) ref. research work carried out limitations peng et al. [6] • detailed system modeling. • implemented estimated mpc: considering realtime lcc-hvdc stability. • considered harmonizing control decisions with real-time stability. • tuned parameter systematic for enhanced control. • addressed real-world applicability and practical challenges. • assessed how the proposed control affects system stability. • analyzed and interpreted outcomes to gauge control strategy effectiveness. • precision relies on accurate ac/dc hybrid power system modeling. • estimated model predictive control (mpc) may have computational challenges. • incorporating real-time lcc-hvdc stability adds complexity. • performance may vary with changes in system parameters. • findings may be more relevant to certain ac/dc system configurations. therattil et al. [7] • non-linear system modeling. • integrated hybrid control with facts devices. • analyzed parameter sensitivity. • studied different system configurations. • simulation studies for performance evaluation. • analyzed computational load. • precision relies on effective non-linear modeling. • integrating facts devices adds complexity. • performance varies with system parameter changes. • effectiveness may differ across system configurations. • hybrid control may have computational requirements. fig. 2 illustrates the flow from power system stability analysis to the nn-based controller, incorporating the aoa. each block represents a significant step in the methodology and is described in the following subsections. in fig. 2, this proposed method endeavors to enhance the stability of power systems by utilizing control signals and an immediate response to changes in system conditions. fig. 2 flow diagram for proposed smib-pss using aoa-nn constant power supply maintenance is contingent upon a dependable power system. when discussing the electrical grid, stability refers to its capacity to return to its original state after a disturbance. utilizing active control mechanisms, the smib-pss system is designed to restore this stability rapidly. the system dynamics can be simulated by employing equations that illustrate the machine’s electrical power output and mechanical power input accordingly. the imbalance between the mechanical and electrical energies, which influences the rotor’s acceleration and deceleration, impacts the system’s stability. , which stands for electrical power, is determined by several factors, including the generator’s output voltage, current, and power factor. the input power from the prime mover is referred to as mechanical power ( �), which is typically constant over the short term. the equation representing the relationship between the rotor angle and time is denoted by �. evaluation of a system’s stability is dependent on it. the equation can be derived through the application of the swing equation, which takes into account damping effects and inertia while establishing a relationship between the rotor’s acceleration and the net power. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 109 the proposed configuration is complete with the nn-based controller. inputted into the system are conditions such as rotor angle and rotor speed, while control signals are generated in response. to ensure the preservation of system stability, these control signals are employed to modify the pss parameters in real-time. to optimize the weights and biases of the neural network, the aoa method is implemented. the objective is to determine which values of the nn parameters have the most significant impact on pss stability enhancement. aoa was motivated by the realization that an optimal angle exists at which a wing can traverse air with the least amount of resistance. the objective of aoa optimization remains consistent to identify the set of parameters that reduce inaccuracy or optimize performance. deviation analysis and stability enhancement are utilized to evaluate the effectiveness of the proposed smib-pss system. the system’s efficacy is assessed under various disturbance conditions in the presence and absence of the aoa-nn-based pss. crucial metrics may include an increase in settling time, a reduction in rotor angle deviation, and overall system stability enhancement under dynamic conditions. 4.1. power system stability analysis of the smib power system stability analysis is crucial to understanding the dynamic behavior of the smib system. stability is assessed by analyzing the system’s response to disturbances and ensuring the synchronous machine returns to a stable operating point. the electrical power ( ) equation represents the power generated by the synchronous machine. it is given by: sin( )δ =e s ve p x (17) the mechanical power input ( �) is the sum of the electrical power and the damping power. it is given by: ω= +m ep p d (18) the rotor angle (�) equation describes the rate of change of the rotor angle concerning time. it is given by: δ ω ω= − sv (19) 4.2. neural network-based controller implementing the nn controller is a deliberate move intended to improve the smib system’s stability. using the system states as inputs, this inventive controller produces control signals that improve the system’s dynamic response. the nn’s design consists of an input layer, hidden layers for complex processing, and an output layer that terminates. the first input layer processes the system states, and the output layer sends the resulting control signals. ( )= +u f wx b (20) 4.3. optimization of neural networks using aoa the aoa is employed to optimize the weights (�) and biases ( ) of the nn, enhancing its capability to stabilize the smib system. the fitness function (�) is designed to evaluate the nn’s performance based on its weights and biases. it measures the deviation between the predicted (��) and desired (�) rotor angles. ( ) 21 ˆ( , ) 2 = −f w b y y (21) the objective function (�) is formulated as the fitness function to minimize the deviation between the predicted and desired rotor angles across the training dataset. the objective function is the sum of the fitness function overall training instances: 1 ( , ) ( , ) = = n i j w b f w b (22) advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 110 4.4. aoa application the aoa updates the weights and biases iteratively using the following equations: 1 2( 1) ( ) ( ) ( ) (0,1) + = + − + ij ij ijw t w t r gbest t w t r rand (23) [ ]3 4( 1) ( ) ( ) ( ) (0,1)+ = + − +i i ib t b t r lbest t b t r rand (24) the optimized weights and biases are then integrated into the nn, enhancing its control capabilities. the aoa updates the weights and biases until a stopping criterion is met, optimizing the nn’s performance and stabilizing the smib system. this detailed methodology combines the power system stability analysis, nn-based control, and the aoa to achieve enhanced stability in the smib system. 4.5. pseudocode for aoa algorithm table 2 indicates the pseudocode of aoa and nn for enhancing power system stability. the following pseudo-code provides a high-level overview of the methodology. the pseudo-code explains optimizing an nn controller with an approach similar to pso to stabilize the power system. power system characteristics are first set to their default values. these include voltage, internal generator voltage, rotor angle, synchronous reactance, damping coefficient, synchronous speed, and rotor speed. these characteristics, coupled with the rotor angle rate, are used to determine the mechanical and electrical powers, which help to understand the system’s dynamics. after an nn is initialized, its weights and biases are updated iteratively in a loop that keeps going until a stopping threshold is reached. to optimize the nn’s parameters, this loop iteratively updates the global and local best solutions, evaluates the fitness of the system’s stability under the current nn parameters, and then integrates these optimized parameters back into the nn. the goal of this optimization loop is to optimize the nn controller so that it can stabilize the power system. it uses global and local search capabilities to identify the optimal solution, which is then tested through a stability study. table 2 pseudocode for improving power system stability with aoa and nn line no. pseudocode explanations 1 �, �, �, ��, �, �, �� = initialize_power_system_parameters() = calculate_electrical_power(�, �, �, ��) # power system stability analysis of smib: # electrical power equation: 2 � = calculate_mechanical_power( , �, �) # mechanical power equation: 3 �� = calculate_rotor_angle_rate(�, ��) # rotor angle equation: 4 �, = initialize_neural_network() # neural network-based controller: # neural network initialization: 5 � ���, � ��� = initialize_global_local_best() # aquila optimization algorithm 6 ��, ��, � , �! = initialize_random_numbers() 7 while not stopping_criterion_met: # optimization loop: 8 �, = update_weights_and_biases(�, , � ���, � ���, ��, ��, � , �!) 9 fitness = evaluate_fitness (�, ) 10 update_global_local_best (gbest, lbest, fitness) 11 integrated_�, integrated_ = integrate_optimized_weights_biases (�, ) # integrated neural network: 12 perform_stability_analysis(�, �, �, ��, �, �, ��, integrated_�, integrated_ ) # research main function # perform stability analysis with neural network control the provided pseudocode in table 2 clearly outlines a power system stability analysis for an smib system. it initializes parameters, calculates power components, and determines rotor angle dynamics. using an nnc and an aoa, it iteratively updates weights and biases until a stopping criterion is met. the integrated nn is then employed for stability analysis in the smib system, showcasing the fusion of nn control and optimization for power system stability assessment. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 111 5. results and discussion the simulink model and its associated simulation results offer a holistic view of the proposed smib-pss system. they serve as essential tools for assessing the system’s stability and the efficacy of the nn controller, guiding researchers and practitioners in refining control strategies for optimal power system performance. fig. 3 illustrates a simulink diagram depicting the proposed smib-pss with a nn controller. within the diagram, various components of the smib system are depicted. the nn controller, a crucial element of the proposed system, is integrated into the simulink framework to demonstrate its role in regulating the stability of the power system. this visualization aids in understanding the dynamics and behaviors of the system under different operating conditions, facilitating analysis and potential improvements. fig. 3 simulink diagram for proposed smib-pss with nn controller fig. 4 presents a simulink diagram illustrating the architecture of the nn employed within the smib-pss system. the diagram details the structure and connections of the nn model utilized for controlling the power system stability. it included layers representing input nodes, hidden layers, and output nodes, along with connections indicating the flow of information between them. fig. 4 simulink diagram for nn architecture fig. 5 provides a comparison of phase angle deviations between two different control approaches, namely the nn and the aoa-nn, within smib-pss. the plot shows the deviation of phase angles from their nominal values over time, specifically focusing on a fault occurrence at t = 10 seconds. for the nn approach, the plot demonstrates how the phase angle deviation evolves following the fault event, highlighting the effectiveness (or lack thereof) of the nn controller in stabilizing the system under such transient conditions. on the other hand, the aoa-nn approach was also depicted in the same plot, showcasing its performance in mitigating phase angle deviations post-fault. after analyzing fig. 4, it was found that the aoa-nn consistently outperforms the standard nn approach. the aoa-nn demonstrates significantly reduced phase angle deviations following the fault event at t = 10 seconds, indicating superior stability enhancement capabilities compared to the conventional nn control strategy. advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 112 fig. 5 phase angle deviation comparison between nn and aoa-nn in smib-pss fig. 6 shows a comparison of rotor angle deviations between two control strategies: the nn and the aoa-nn within smib-pss. the plot illustrates the deviation of rotor angles from their nominal values over time, with a focus on a fault occurrence at t = 10 seconds. it was found that aoa-nn surpasses the nn approach in performance. the aoa-nn exhibits notably reduced rotor angle deviation post-fault, indicating its superior capability in stabilizing the smib-pss system compared to the conventional nn control strategy. this observation underscores the effectiveness of leveraging optimization algorithms to enhance the performance of nn-based control systems in smib-pss applications. fig. 6 rotor angle deviation comparison for nn and aoa-nn in smib-pss table 3 provides a comprehensive comparative analysis of the results obtained from previous research works, focusing on the performance evaluation of psss and their optimization using various nn-based algorithms. table 3 includes key metrics related to speed response (overshoot, undershoot, and settling time) and rotor angle response (undershoot and settling time). after analyzing the findings in table 3 it was found that the stsa-nn pss achieved an overshoot of 0.0267 and an undershoot of -0.1304 with a settling time of 488 units for speed response, while for rotor angle response, it demonstrates an undershoot of -0.3990 and a settling time of 646 units. remarkably, the proposed aoa-nn stands out with the lowest overshoot of 0.012, a negligible undershoot of -0.080, and a relatively faster settling time of 400 units for speed response, advances in technology innovation, vol. 9, no. 2, 2024, pp. 99-115 113 coupled with a minimal undershoot of -0.050 and a settling time of 550 units for rotor angle response. these results indicate the superior performance of the proposed aoa-nn method compared to the other techniques analyzed in the table, highlighting its effectiveness in enhancing psss. the proposed aoa-nn method can reduce the overshoot speed with an average value of 79.1946% and the overshoot rotor angle with an average value of 87.8634%. table 3 comparative analysis of results with previous research works method speed response rotor angle response overshoot undershoot settling time undershoot settling time sine tree-seed algorithm-feed-forward neural network (stsa-nn pss) [13] 0.0267 -0.1304 488 -0.3990 646 archimedes optimization algorithm-neural network (aoa-nn pss) [13] 0.0211 -0.1129 517 -0.4016 630 distributed time delay with neural network (dtd-nn) [14] 0.4354 -0.8211 107.36 -3.2207 145.02 tunicate swarm algorithm-feed forward neural network (tsa-ffnn) [14] 0.3055 -0.7226 112.44 -2.8748 146.25 proposed aquila optimization algorithmneural networks (aoa-nn) 0.012 -0.080 400 -0.050 550 6. conclusion a complete solution that blends power system stability analysis, nn-based regulation, and the aoa to stabilize smib systems was successfully implemented. this novel technique uses the aoa to optimize nn parameters and increase performance to comprehend the smib system’s behavior. it may increase power system stability, but it has some drawbacks. power system model quality greatly affects aoa accuracy. defects in the model may affect performance. optimizing nns for real-time applications is computationally difficult. the aoa unique technique based on the aquila birds’ hunting behavior enhances nn flexibility to provide a cost-effective smib stability solution. the study improved smib system dynamics stability using power system stability analysis, nn-based control, and aoa. the aoa algorithm improves nn performance and system stability by fine-tuning parameters. this study encourages more research on the technique’s flexibility in complicated power systems and grid conditions, opening the path for future advancement. the research investigates the aoa’s scalability and robustness in large-scale power networks to highlight its potential for development. the study admits restrictions such as power system model precision and nn real-time optimization. the aoa algorithm enhances nn parameter flexibility by using the aquila birds’ hunting behavior. the aoa and nn control may improve power system stability and control, providing a flexible foundation for varied power system installations. to make it more practicable for large-scale power networks, the technique will be improved, validated, and scaled. despite limitations, the 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[24] n. gupta, “artificial neural network,” network and complex systems, vol. 3, no. 1, pp. 24-28, 2013. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). appendix: -i list of symbols s.n. symbol description of symbols used in equations si units 1 " inertia constant of the machine kg.m2 2 � damping factor or coefficient dimensionless quantity 3 � rotor angle radian (rad) 4 � #$ mechanical power input watt 5 electrical power output watt 6 %��� time constant of the pss seconds 7 ���� output signal of the pss volt or amp 8 &'�� pss gain dimensionless quantity 9 �� rate of change of the rotor angle radian per second (rad/s) 10 � activation function - 11 () weights - 12 *) inputs - 13 bias vector - 14 *)+�, position of the -.$ candidate solution at iteration � - 15 � ���+�, global best solution at iteration � - 16 �� and �� random numbers in the range /0,13 - 17 �456+0,1, random number in the range /0,13 - 18 �+*), fitness of the -.$ candidate solution - 19 7 constant - 20 � ���+�, local best solution at iteration � dimensionless quantity 21 5 number of candidate solutions in the population - 22 electrical power watt 23 � terminal voltage volt 24 � synchronous machine voltage volt 25 �� synchronous reactance ohm 26 � mechanical power watt 27 � angular speed radian per second (rad/s) 28 �� synchronous speed revolutions per minute (rpm) or radians per second (rad/s). 29 8 control signal - 30 � weight matrix - 31 � input vector - 32 � fitness function - 33 � desired rotor angle radian per second (rad/s) 34 �� predicted rotor angle based on the neural network with weights � and biases radian per second (rad/s) 35 �)9 weight matrix element - 36 ) bias element - 37 � and �! random numbers in the range /0,13 - 38 : number of training instances - microsoft word 4-v9n4(2024)-aiti#13864(301-318).docx advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 english language proofreader: yen-chun hsieh a secure and robust data transmission for 2 × 2 mimo-ofdm system using subcarrier randomization with elliptical curve cryptography i gede puja astawa*, melki mario gulo, amang sudarsono department of electrical engineering politeknik elektronika negeri surabaya (pens), jawa timur, indonesia received 18 june 2024; received in revised form 13 august 2024; accepted 15 august 2024 doi: https://doi.org/10.46604/aiti.2024.13864 abstract this research proposes a method that randomizes the subcarrier as a physical layer security (pls) in the multiple-input multiple-output orthogonal frequency division multiplexing (mimo-ofdm) communication system, aiming to secure information data. the research procedure incorporates the elliptic curve cryptography (ecc) algorithm during subcarrier randomization, including processes such as public key generation, encryption, and decryption, and compares these with the rivest shamir-adleman (rsa) method. the proposed method is validated through real-time laboratory experiments, yielding significant results. the rsa algorithm’s average time is 6.73 and 53.21 seconds, while the ecc algorithm requires only 0.71 and 1.21 seconds for security bits of 80 and 112, respectively. the performance of bit error rate (ber) versus signal-to-noise ratio (snr) is 0.123 times 10 to the power of negative 3, demonstrating that the subcarrier randomization and reconstruction system is successfully implemented and working correctly to ensure security based on the mimo-ofdm system. keywords: elliptic curve cryptography (ecc), multiple-input multiple-output orthogonal frequency division multiplexing (mimo-ofdm), subcarrier randomization, encryption, decryption 1. introduction nowadays, information and communication technology have become human necessities. the demand for information and communication technologies is increasing as technology improves. people now expect to utilize these technologies to communicate in various formats, including text, images, audio, and video. orthogonal frequency division multiplexing (ofdm) is one such technology that meets these diverse demands. ofdm is a popular wireless modulation technique employed in modern communication systems. it is used by several technologies, including long term evolution (lte) [1] and digital video broadcasting-second generation terrestrial (dvb-t2) [2]. additionally, numerous studies of fifth/sixth generation (5g/6g) technology have been proposed [3-4]. ofdm offers high data rates and handles problems like intersymbol interference (isi) and frequency selective fading, making it widely utilized in current wireless communication systems. moreover, modern communication systems sometimes combine ofdm with multiple-input multiple-output (mimo) [5-6]. mimo is essential to support a wide range of services with 5g and 6g systems. it achieves higher spectral efficiency and broader network coverage. the tremendous growth in data rates is fueled by the increasing use of mobile devices and the emergence of new technologies and applications that demand high data rates and low latency. mimo is a multiple-antenna technique used to improve the quality or data rate of the transmitted signal without expanding the bandwidth. there are two mimo schemes: spatial multiplexing and spatial diversity. spatial diversity is a mimo technique that improves the link quality of the transmitter and receiver [7]. * corresponding author. e-mail address: puja@pens.ac.id 302 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 meanwhile, spatial multiplexing is a mimo technique for improving data rates [8]. the combination of mimo and ofdm enhances the resilience and suitability of communication systems, making them ideal for emerging communication systems that require greater channel capacity. however, the mimo-ofdm system requires a robust security method to ensure its reliability, as the open-air nature of wireless communication systems makes them vulnerable to security risks. one of the security risks of the mimo-ofdm communication system is eavesdropping, which is the unauthorized interception of information in a wireless communication channel. eavesdropping in wireless services is one of the main threats to vehicle-tovehicle (v2v) communications systems [9-10]. an in-network anti-eavesdropping scheme was developed using a cognitive risk control-based combined vehicle radar communication system [9]. in conventional wireless services, illegal eavesdropping is considered one of the critical security challenges in the network, and the research aims to increase the capacity of antieavesdropping communication and reduce jamming interference [10]. in wireless communication, data security is one of the most critical factors. wireless communication is one of the most vulnerable communication media because the information data is widely transmitted, making it susceptible to several security threats. several types of data security threats include (a) eavesdropping, where an attacker can obtain information from the signal sent by the transmitter to the receiver; (b) jamming, where the attacker sends noise that resembles a signal from the sender to the receiver, and (c) spoofing, where the attacker becomes a man-in-the-middle (mitm). if a sender sends a signal to the receiver, the attacker creates a spoofed signal similar to the sender’s but with different information. to overcome the threat of eavesdropping security in wireless communication systems, the subcarrier randomizer technique is employed. a subcarrier randomizer is a subcarrier sequence randomization technique that changes the plaintext bit with ciphertext. the subcarrier randomizer technique uses a specific asymmetric cryptography method to encrypt plaintext into ciphertext. asymmetric cryptography is a cryptography system that uses public and private keys to encrypt and decrypt certain information. a public key is available to anyone and is used for encrypting messages. meanwhile, a private key is a key that is only shared with certain people that can be used to decrypt messages. the rivest shamir-adleman (rsa) algorithm and the elliptic curve cryptography (ecc) are two widely implemented asymmetric cryptography methods due to their high security. a comparison of the rsa and ecc within blockchain systems has been conducted [11-12], to evaluate the advantages of each method. to ensure the security of the communication system, the mimo-ofdm communication network must be protected. extensive research has been conducted on encryption and security methods within mimo-ofdm systems to improve user safety and convenience. however, the use of security systems in mimo-ofdm is commonly limited to the top layer of the open systems interconnection (osi) model, with a limited focus on physical layer security (pls) [13-14]. pls is a viable approach for wireless communication networks. several studies have been undertaken on pls in mimo and ofdm systems [15-19]. yusof et al. [20] employed a chaotic signal-scrambling system, such as the partial transmit sequence (pts) and selected mapping (slm), within the ofdm communication system. additionally, al-ali and hasan [21] investigated the security of image transmission over space-time block coding encoded through ofdm, enhanced by a sample scrambling algorithm using a one-dimensional chaotic map. multiple researchers have combined cryptography with pls to strengthen the security of mimo-ofdm communication systems. for instance, turbo-based encryption has been used to improve reliability and security for wireless mimo-ofdm affected by doppler frequency offset. the secret key is generated from the parameter channel between legitimate users and serves as a seed to generate a pseudo-random bit sequence using an advanced encryption standard investigated [22-23]. furthermore, luo et al. [23] presented a channel frequency response-based secret key generation scheme for in-band full duplex mimo systems, addressing intrinsic practical imperfections and their effects on probing errors. among these cryptography and pls combination methods, the ecc and pls still need to be widely used in mimo-ofdm communication advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 303 systems. ecc is a robust asymmetric cryptography algorithm known for its low computational cost. this efficiency makes the ecc algorithm widely used in devices with limited memory, such as internet of things (iot) systems [24-25]. as previously mentioned, most of the existing research remains theoretical and has not been directly applied to hardware, so the environment is still ideal. to address this gap, this research proposes real-time applications with hardware carried out for security systems in mimo-ofdm systems, and testing techniques are also shown. the main objective of this study is to enhance data security by randomizing the subcarrier as a pls method in the mimoofdm system. to achieve this, an ecc algorithm is integrated during subcarrier randomization. the ecc procedures include public key generation, encryption, and decryption. this research will utilize software defined radio (sdr) to simulate or analyze wireless communication systems. sdr devices are commonly used to emulate wireless communication systems due to their simple setup and programming. by using an sdr device, schema and system modifications can be implemented by modifying the program’s logic without changing the sdr device’s electronic design. in this research, an sdr-type national instruments universal software radio peripheral (ni-usrp) device will be used to develop a mimo-ofdm communication system, incorporating the ecc algorithm for subcarrier synchronization within the subcarrier randomization technique. 2. proposed system this section discusses the subcarrier randomization system using the ecc algorithm in mimo-ofdm spatial multiplexing. it starts with a detailed explanation of the main parts of the mimo-ofdm transceiver with a 2 × 2 antenna scheme that applies subcarrier randomization with elliptical curve cryptography to secure data transmission. then, the working mechanism of elliptical curve cryptography, as well as the working mechanisms of subcarrier randomization and subcarrier reconstruction, are explained, which are an integral part of the research conducted. 2.1. mimo-ofdm transmitter (a) transmitter (b) receiver fig. 1 block diagram of mimo-ofdm transceiver in this research, the 2 × 2 mimo-ofdm system is implemented to transmit and receive text messages, as shown in fig. 1. the design of the mimo-ofdm transmitter system is illustrated in fig. 1(a). the system uses text data as input, which is then converted into a binary series based on its ascii value. the bit sequence is then modulated using quadrature amplitude 304 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 modulation (qam) to produce a complex signal symbol sequence. the qam symbol is subsequently multiplexed to generate two signal streams for transmission. in mimo-ofdm spatial multiplexing, the multiplexing process divides the signal stream in half, with the first transmitter transmitting the first half and the second transmitter transmitting the second half. in addition, the qam symbol is transformed into a parallel form and fragmented into multiple smaller symbol streams on each ofdm subcarrier. the subcarrier randomization system processes each subcarrier on each transmitter to randomize the subcarriers. the following section will discuss a more comprehensive design for the subcarrier randomization scheme. the randomized subcarrier is appended with the pilot and null symbols. after this, the signal is transformed into a time-domain signal using inverse fast fourier transform (ifft). the ifft procedure is represented as follows: ( ) 1 2 0 ( ) [ ] π − = =  n nj nk k x n x k e (1) where �[�] is the qam symbol at the �-th where � = 0,1,⋯ , (� − 1), and � is the number of ifft. the mimo-ofdm signals processed by ifft are combined with a cyclic prefix (cp) at the receiver to compensate for isi. the signal is then processed by a parallel to serial (p/s) converter before being transmitted through the antenna. 2.2. mimo-ofdm receiver fig. 1(b) shows the block diagram of the mimo-ofdm receiver. after each receiver has received the signal, the cp removal procedure is executed. the fast fourier transform (fft) converts the signal removed from its cp into the frequency domain. the fft process at the receiver is: ( ) 1 2 0 ( ) [ ] π − = = n nj nk k x k x n e (2) the signal at the receiver in the time domain is represented by �[�] and � is the number of subcarriers. channel estimation and equalization are processed at the receiver to eliminate the effects of fading channels on the ofdm system. this study uses the least squares method for channel estimation in the mimo-ofdm system. the use of least squares for channel estimation in mimo-ofdm has been successfully implemented in several previous studies [26-27]. the least squares method equation for channel estimation in the mimo-ofdm system is: ( ) 1 2 ( ) 0 arg min − = = − ⊗ k t ls h k k k h y x i h (3) where � is the channel’s length, � is the channel matrix identity, and ℎ is the channel impulse response. after a successful channel estimation, channel equalization is carried out. this research uses a zero-forcing (zf) channel equalization method. zf is a technique to equalize channels in mimo-ofdm systems by dividing the received signal by the estimated channel [28]. the zf formula is: 1.− = lsx h y (4) then, the signal is processed by demodulation to produce an information signal in text messages. 2.3. elliptical curve cryptography in this research, ecc is used to encrypt messages, serving as a reference for subcarrier randomization. ecc is a widely implemented asymmetric cryptographic technique in modern communication systems due to its high-security level and low computational cost. compared to other asymmetric cryptography methods, such as rsa, the ecc algorithm has advantages. based on key management recommendations by the national institute of standards and technology (nist), a bit-level comparison table between rsa and ecc [29] is shown in table 1. advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 305 table 1 comparison of security bit-level ecc vs. rsa by nist security bit level rsa bit parameter ecc bit parameter 80 1024 160 112 2048 224 128 3072 256 192 7680 384 256 15360 512 table 1 shows that to achieve the same security bit level, the rsa bit parameters are more significant than the ecc bit parameters. messages are encrypted by the ecc algorithm based on an elliptic equation, which is expressed as follows: 2 3 mod= + +y x ax b p (5) where �, �, and � are defined by the number of bits used, � and � are variable. the ecc operation generates public and private keys using the following equation. .=ap na g (6) where �� is the public key, �� is the private key, and � is the initial coordinate, one of eq. (6) results coordinates. furthermore, the public key obtained from eq. (6) generation encrypts the message. the message encryption equation using ecc is: { }. , .= +c m ap k g p k p (7) where �� is message encryption, � is a random constant, and �� is plain text, respectively. 2.4. subcarrier randomization and subcarrier reconstruction subcarrier randomization is based on the different bits between plaintext and cipher messages, with the cipher message generated through the ecc algorithm encryption process. meanwhile, subcarrier reconstruction is a process that returns the subcarrier sequence to its original state based on the difference bits between the cipher message and the plaintext message. the block diagram of the subcarrier randomization and subcarrier reconstruction is shown in fig. 2. fig. 2 block diagram of subcarrier randomizer and subcarrier reconstructor in fig. 2, the subcarrier randomization process begins by converting the message into a bit sequence. message conversion to bit series is done based on the ascii value. furthermore, the original message encrypted using the ecc algorithm produces a cipher in coordinates. these coordinates are added together to generate a series of ciphers, which are then converted into bits based on the ascii value. the two resulting bit series of plaintext messages and cipher messages have different values, and this difference is used to randomize the subcarrier. an illustration of the subcarrier randomization process is shown in fig. 3(a). meanwhile, the subcarriers in the received signal are reconstructed to produce subcarriers that match the original arrangement during the subcarrier reconstruction process. the difference in bit series between the cipher message and the plaintext message is used in this operation. in contrast to the subcarrier randomization technique, this process differs in bit series. fig. 3(b) shows an illustration of the subcarrier reconstruction procedure. 306 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 (a) subcarrier randomization (b) subcarrier reconstruction fig. 3 illustration of the process fig. 3(a) illustrates the subcarrier randomization process using the difference in bit series between plaintext and cipher message bits. for example, this process has four subcarriers, eight message bits, and eight cipher bits. each bit is then grouped into groups containing two bits. furthermore, the group of bits in the message is exchanged with the group of bits in the cipher message. exchange is done starting with bit 00 in the message being exchanged with bit 00 in the cipher, bit 01 in the message being exchanged with bit 01 in the cipher, then bit 10 in the message being exchanged with bit 10 in the cipher, and finally bit 11 in the message being exchanged with bit 11 in the cipher. fig. 3(b) is an illustration of the subcarrier reconstruction process. the reference used to perform the reconstruction is the difference in bit changes between the cipher and plaintext messages. as a result, the message bit must be owned first from the results of the message cipher decryption using the ecc algorithm. furthermore, the subcarrier reconstruction process advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 307 exchanges each 2-bit message pair into a 2-bit cipher pair. in contrast to the subcarrier randomization process, in this process, the exchange starts from the 11 message bit pair to the 11 ciphers, then the ten message bit pair to the ten ciphers, then the 01bit pair message to the 01 ciphers, and finally the 00-bit pair message to the 00 ciphers. 3. system implementation this section discusses the implementation of subcarrier randomization using the ecc algorithm on mimo-ofdm based on ni-usrp devices. in implementing this system, the ni-usrp 2920 type device is used. the ni-usrp 2920 is an sdr device that can execute a radio frequency (rf) communication system. the block diagram of the system implementation on the usrp is shown in fig. 4. (a) block diagram of mimo-ofdm system (b) realization of mimo-ofdm transceiver on ni-usrp fig. 4 block diagram of system implementation on the ni-usrp 2920 fig. 4(a) shows the system implementation using four usrps, with two for the transmitter, and two for the receiver. each usrp is connected to a personal computer (pc) at both the transmitter and receiver. an ethernet cable is used to connect the usrp and pc because the usrp and pc connection is ip-based. therefore, it is necessary to configure the pc’s ip address so it can be connected to usrp. by default, usrp uses the ip address 192.168.10.x/24 as the ip address of the usrp. however, this ip address can be changed according to the scheme used. in addition, the ethernet cable used to connect between the pc and usrp is a type of gigabit ethernet cable, so if the pc used is not a standardized gigabit ethernet, it is necessary to add a gigabit ethernet dongle to the pc. additional devices, such as layer two switches, are required, but since the two usrp devices on the transmitter and receiver are interconnected with mimo cables, only a pc connection to one of the usrp on the transmitter and receiver is required. a mimo cable connecting two usrps is used to synchronize clocks and frequencies. implementing this system will create the program using the labview programming language and python. labview is used because it has usrp driver support that can be used to run programs with usrp devices. the experimental setup for the mimo-ofdm system is depicted in fig. 4(b), and the device specifications are listed in table 2. table 2 devices specification device name specification ni-usrp 2920 frequency range: 50 mhz – 2.2 ghz. antenna: vert 900. frequency range: 824 mhz – 960 mhz, 1710 mhz operating system windows 11 ram: 8gb. processor: intel core i5 2.4 ghz windows 11 ram: 8gb. processor: amd ryzen 3 3200u 2.6 ghz 308 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 4. result and discussion this section will analyze the results of implementing the subcarrier randomization system on mimo-ofdm using niusrp 2920. experimental results and comprehensive analyses include subcarrier randomization testing on the mimo-ofdm system based on usrp, a comparative measurement of ecc parameters on system implementation, a performance comparison between rsa and ecc, and an analysis of the use of ecc in the mimo-ofdm system. the simulation parameters used in this research include a 2 × 2 antenna scheme, qam modulation, and an ecc parameter of 128 bits. table 3 shows the details of the complete parameters used. table 3 simulation parameters part parameter value transmitter frequency 920 mhz n-ifft 128 data symbol 96 pilot symbol 9 null symbol 23 cp 32 iq rate 500 k antenna 2 ecc parameter 128-bit modulation qam receiver channel equalization zero-forcing channel estimation least square frame sync zadoff-chu number of antennas 2 4.1. subcarrier randomization testing on mimo-ofdm system based on usrp the results of the subcarrier randomization experiment on the mimo-ofdm system will be discussed in this section. as analytical parameters in this experiment, a constellation graph and the message decoding results at the receiver will be used. the experiment was carried out by sending text messages from the transmitter to the receiver, with two scenarios: authorized and unauthorized recipients, as shown in fig. 5. (a) signal constellation on the authorized receiver (b) signal constellation on the unauthorized receiver fig. 5 signal constellation in receiver in the authorized recipient scenario, as shown in fig. 5(a), the signal constellation data is received by a recipient who has successfully decrypted the cipher sent to the receiver and used it in the subcarrier reconstruction process. the signal constellation on the receiver successfully forms a qam constellation scheme, although there are still some residual signals in the constellation diagram. however, the residual signal is not used since the receiver uses the maximum likelihood algorithm. advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 309 the results of the text data from this scenario are shown in fig. 6(a). this figure shows that the text for the receiver has the same result as the text for the sender. this happens because the receiver uses the same plaintext message reference and cipher message as the transmitter when performing the subcarrier reconstruction. obtain a constellation for the unauthorized recipient scenario, as shown in fig. 5(b). the constellation in this scenario forms a qam constellation similar to the results in fig. 5(a). this happens because the subcarrier randomization process only randomizes 96 data subcarriers for the sender. randomization was only done on the data subcarrier to keep the mimo-ofdm signal from being messed up. although it has the same signal constellation as the authorized receiver, the receiver fails to get the same message from the transmitter. this happens because the receiver uses a different plaintext message reference than the sender. so, even though the cipher message used is the same, the results are different. because the process of changing bits is different between cipher and plaintext messages on the transmitter and the receiver, the results of the message to the receiver are shown in fig. 6(b). (a) authorized receiver (b) unauthorized receiver fig. 6 received message on the receiver 4.2. comparative measurement of ecc parameters on system implementation in this section, a comparative measurement of the ecc parameter was carried out in system implementation. measurements were made to compare the computational delay of the 3 ecc parameters with values of 112-bit, 128-bit, and 160-bit. a comparison of the computational delay is performed for each ecc process. the first measurement process measures the delay in the public key generation of ecc. the results of this measurement are shown in fig. 7. (a) public key generation fig. 7 delay measurement ecc 310 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 (b) encryption (c) decryption fig. 7 delay measurement ecc (continued) fig. 7(a) shows that the 112-bit ecc is faster at generating the public key, and the 160-bit ecc requires a longer process to generate the public key. this can also be observed from the average calculation of the delay data. the average process delay on 112-bit ecc is 93.11 ms, 128-bit ecc is 114.5 ms, and 160-bit ecc is 156.97 ms. furthermore, the encryption process delay is compared across the three ecc parameters. the results of this comparison are shown in fig. 7(b). from this figure, it is evident that the 112-bit ecc encryption process has a lower time than the others. this can also be seen from the average value of 4181.2 ms, while for 128-bit ecc, the average encryption time is 5986.73 ms, and for 160-bit ecc, the average encryption time is 6897.89 ms. this encryption time is calculated using a message length of 24 characters. the time difference is quite significant between ecc 112-bit and ecc 160-bit, 305, which is 2716.69 ms. the following comparison process is carried out to compare the data 306 delay of the ecc decryption process with the previous three parameters. the results of the 307 comparison of the decryption delay are shown in fig. 7(c), which shows that the delay in the 112-bit ecc decryption process has a lower time than the 160-bit ecc. the average delay value for the 112bit ecc decryption process is 2238.5 ms, while that for the 128-bit ecc is 2668.95 ms, and that for the 160-bit ecc is 3563.08 ms. in fig. 7(c), it is evident that the decryption process takes a shorter time when compared to the encryption process. this is due to the decryption process creating fewer jobs than encryption. in the decryption process, only the subtraction process occurs between the cipher coordinates and the multiplication between the public key and the scrambler constant. advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 311 4.3. performance comparison between rsa and ecc this section will analyze the performance comparison between the ecc and rsa algorithms. a comparison is made between the computational delays of ecc and rsa on several security bit levels, which refers to table 1. fig. 8 shows data comparing the encryption and decryption processes for security bit levels (80 and 112) between rsa 1024-bit and ecc 160bit. (a) the 80-bit security level (b) the 112-bit security level fig. 8 comparison graph of the delay in the encryption-decryption process fig. 8(a) graph shows that ecc has a computational delay much smaller than rsa for security bit level 80. the average ecc computational delay in this scenario is 0.71 seconds. the average time running an rsa algorithm is 6.73 seconds, it takes about 947.88% of the average time to run an ecc algorithm. compared to previous research conducted by khan et al. [12], the ecc method takes about 318% of the average time to run an ecc algorithm for a security bit level of 80, compared to the rsa method. it can be seen from the results obtained from this experiment that the use of the ecc method compared to rsa results is almost three times faster for average time running applied to security systems in mimo ofdm systems compared to the results obtained from previous research [12]. 312 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 meanwhile, fig. 8(b) compares the computational delay for the encryption-decryption process at the 112-bit security level between the rsa 2048-bit and ecc 224-bit algorithms. from the graph, it is observed that ecc has a minor computational delay compared to rsa. the average computational delay for ecc to obtain security bit level 112 is 1.21 seconds. in comparison, the rsa algorithm has an average time of 53.21 seconds, which is the average time value of the ecc algorithm. this means that the rsa algorithm takes about 4297% of the average time to run an ecc algorithm. compared to previous research [12], the ecc method requires only about 14.7% of the average time running an ecc algorithm for a security bit level of 112, compared to the rsa method. the experiment results show that the ecc method results are almost two hundred times faster than rsa when applied to security systems in mimo ofdm systems, compared to the previous research [12]. from the graphs in fig. 8(a) and fig. 8(b), it can be concluded that ecc has a lower computational cost than rsa to achieve the same bit security level. 4.4. analysis of the use of ecc in mimo-ofdm system this section measures the performance of the subcarrier randomizer and subcarrier reconstructor algorithms. first, the randomization percentage of 96 subcarriers was calculated based on the number of characters of the encrypted plaintext message. this measurement is carried out because the randomization process refers to changing the plaintext message and cipher text. the measurement data of this scenario is shown in table 4. table 4 the percentage average of 96 subcarrier randomization for the number of message characters no number of message characters messages percentage average of subcarrier randomization 1 4 gulo 8.979167% 2 8 aku gulo 22.58333% 3 12 hai aku gulo 33.8125% 4 16 halo namaku gulo 50.8125% 5 20 halo namaku mario!!! 62.6875% 6 24 halo namaku mario gulo!! 76.25% fig. 9 experiment scenario of subcarrier randomizer and subcarrier reconstructor from table 4, it can observed that as the number of message characters increases, the subcarrier will be more scrambled. for example, a 24-character message has an average subcarrier scrambling of 76.25%, whereas a message with only four characters has an average subcarrier scrambling of 8.97%. this indicates that to achieve higher security, more message advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 313 characters are required. in the following measurement scenario, the performance of the subcarrier randomizer and subcarrier reconstruction algorithms were tested to secure the communication from attacker interference. the diagram of the testing scenario is shown in fig. 9. in this scenario, alice is a mimo-ofdm system transmitter who wants to send an image to the receiver, bob. however, an attacker is eavesdropping on the ongoing communication between alice and bob during the communication process. before starting the image transmission communication session, alice performs encryption using the ecc public key embedded in the pc transmitter. the public key on alice is obtained through the generation of the private key embedded in bob. the public key used by alice is shown in fig. 10. furthermore, this public key will be used to encrypt the message, as shown in fig. 11. fig. 10 public key alice fig. 11 plaintext messages fig. 12 ciphertext fig. 13 the receiver (bob, attacker) receives the complete ciphertext 314 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 the encryption process is carried out with an ecc parameter of 224-bit. the cipher message is obtained from this encryption process, as shown in fig. 12. the ciphertext obtained by alice is then sent through the mimo-ofdm communication system so that bob gets this ciphertext message. however, in the middle of the communication session, an attacker also gets the ciphertext sent by the mimo-ofdm system. in sending ciphertext, each receiver will check the ciphertext file sent. checking is done to determine the completeness of the file sent. the crc-16 algorithm is used to perform this check. recipients who receive a complete ciphertext will have a display like fig. 13. after the ciphertext received is complete, bob decrypts it using the private key embedded in the receiving computer of the mimo-ofdm system. the private key owned by bob is presented in fig. 14. then bob performs the decryption process with the private key image 92 and the same ecc parameters as alice. because the private key owned by bob is valid, the plaintext result of the decryption process is obtained following alice’s, as shown in fig. 15. fig. 14 private key owned by bob fig. 15 plaintext decryption result by bob at the same time, the attacker tries to decrypt the sent ciphertext. assuming that the attacker knows the ecc parameters but does not have a valid private key. then, the attacker will try to guess the private key used by the valid recipient. the attacker guesses the private key, and the resulting private key is invalid, as shown in fig. 16. because the guessed private key is invalid when performing the ciphertext decryption process, the decryption result is obtained, as shown in fig. 17. fig. 16 private key invalid by attacker fig. 17 invalid plaintext fig. 18 image transmission by alice advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 315 after alice sends the ciphertext, bob and the attacker decrypt it. alice starts transmitting the image with the subcarrier randomizer algorithm. the image data sent by alice in this section is presented in fig. 18. fig. 18 is then sent by alice to bob by first performing a subcarrier randomizer using the plaintext reference and also the additional text of the entire ciphertext, as shown in fig. 19. after decrypting the ciphertext data, bob uses the plaintext data and the addition text of the entire ciphertext, as demonstrated in fig. 20, to perform subcarrier reconstruction on the mimo-ofdm signal received from alice. fig. 19 subcarrier randomizer reference on alice fig. 20 subcarrier reconstruction on bob meanwhile, the attacker also tries to use invalid plaintext data resulting from incorrect ciphertext decryption and text addition of the entire ciphertext, as shown in fig. 21, to perform the subcarrier reconstruction process. since the bob uses a valid subcarrier reconstruction reference, the image received by the bob is presented in fig. 22. fig. 21 subcarrier reconstruction reference on attacker fig. 22 the image received by bob from fig. 22, bob obtained an image similar to the image sent by alice. this happens because bob can perform subcarrier reconstruction on the mimo-ofdm signal sent by alice. in contrast, the attacker fails to perform subcarrier reconstruction because there is no valid reference. fig. 23 illustrates that the image is scrambled, making it difficult to recognize the original data in the image. thus, a failed subcarrier reconstruction process will scramble the transmitted data. the image obtained by the attacker in this process is shown in fig. 23. fig. 23 image received by the attacker 316 advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 through several times of experiments and data measurements, a graph of the bit error rate (ber) function compared to the signal-to-noise ratio (snr) in the subcarrier randomizer and subcarrier reconstruction system in mimo-ofdm was obtained. the resulting graph, comparing authorized and unauthorized receivers, is shown in fig. 24. the ber graph in fig. 24 indicates that the ber graph for unauthorized receivers is greater than the ber graph for authorized receivers. this is due to the data received by the unauthorized receiver having many errors, as the receiver cannot reconstruct the data sent by the transmitter. from fig. 24, the lowest value of ber on the authorized receiver is 0.123 × 10-3 at 9.67 db of snr. while on the unauthorized receiver, the lowest ber value is 0.459 × 10-1 at 8.47 db of snr. the ber value at the unauthorized receiver is very high, even for the lowest ber value. thus, it can concluded that the performance of the subcarrier randomization and subcarrier reconstruction system effectively secures based mimo-ofdm communication system. fig. 24 ber vs snr for the authorized and the unauthorized receiver by subcarrier randomizer in mimo-ofdm 5. conclusions in this study, the subcarrier randomization system has been successfully implemented in mimo-ofdm using usrp. subcarrier randomization is a pls method that randomizes the subcarrier based on message synchronization and the ecc algorithm cipher. in implementing this system, due to the receiver’s inability to rearrange the subcarrier and decode the message, the unauthorized receiver will get a signal with a randomized subcarrier, which causes a random message at the receiver. notably, the unauthorized receiver scenario exhibits a constellation almost identical to that of the authorized receiver. this is because the subcarrier randomization process only randomizes the transmitter’s data subcarrier, while the receiver uses a different plaintext message reference than the transmitter. consequently, even though the same cipher message is used, the results are different. the comparison measurement of ecc parameters is conducted by comparing the computational delay of the three ecc parameters, specifically during the public key generation, encryption, and decryption process. the results indicate that the decryption process requires less time than the encryption process due to generating less work. the performance comparison between ecc and rsa algorithms underscores the importance of selecting ecc parameters to reduce the computational cost of both transmitter and receiver systems. ecc demonstrates a lower computational cost compared to the rsa method at the same bit security level. experiment results reveal that the lowest value of ber for the authorized receiver is 0.123 × 10-3 at 9.67 db of snr, whereas for the unauthorized receiver, the lowest ber value is 0.459 × 10-1 at 8.47 db of snr. advances in technology innovation, vol. 9, no. 4, 2024, pp. 301-318 317 acknowledgments this research was supported by the directorate general of vocational education of the indonesian ministry of education, culture, research and technology and politeknik elektronika negeri surabaya (pens). conflicts of interest the authors declare 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[29] z. cao and l. liu, “the practical advantage of rsa over ecc and pairings,” unpublished. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v9n1(2024)-aiti#12576(01-11).docx advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 english language proofreader: chih-wei chang synthesis and characterization of phase change microcapsules containing nano-graphite yeng-fong shih*, hong-hao chen department of applied chemistry, chaoyang university of technology, taichung, taiwan, roc received 07 july 2023; received in revised form 05 december 2023; accepted 06 december 2023 doi: https://doi.org/10.46604/aiti.2023.12576 abstract this study uses the sol-gel method to modify the phase change microcapsules. the phase change material (pcm) is encapsulated by a polymer shell to reduce the leakage in the solid-liquid transition. furthermore, the nano-graphite particle (ngp) is introduced into the shell to increase its thermal conductivity. the particle size and enthalpy value of the obtained microcapsules are approximately 3 μm and 150.3 j/g, respectively. the results show that the encapsulation efficiency of pcm in the prepared microcapsules is increased and the crystallization rate of pcm becomes faster when the ngp is added. the obtained microcapsules and wood flour are incorporated into highdensity polyethylene (hdpe) to form a wood-plastic composite (wpc). the results indicate that the tensile and impact strengths of the wpc are 24.1 mpa and 48.7 j/m, respectively. moreover, it is observed that the addition of these phase-change microcapsules can improve the heat dissipation of hdpe and accelerate the speed of thermal diffusion. keywords: microcapsules, phase change materials, sol-gel method, nano-graphite, polymer composite material 1. introduction the rapid development of industrial technology has brought about a convenient living standard, but it has also incurred a shortage of electricity and rapid consumption of natural energy, environmental pollution, and greenhouse gas. given that sources of energy such as petroleum and coal are non-renewable and have environmental concerns, energy-saving, and storage materials are of great significance to sustainable development. thermal energy storage is divided into sensible heat, latent heat, and chemical energy storage [1-4]. among them, phase change material (pcm) attracts attention owing to the function of latent heat storage [5-7]. during the phase change process, it absorbs and releases a large amount of heat energy, while its temperature remains unchanged. pcms are considerably applied in heat storage and have the advantages of high energy storage density, small volume change, and small temperature change [8-11]. among the four types of pcms (solid-solid, solid-liquid, solid-gas, and liquid-gas), the solid-liquid type is the most widely used. concerning the chemical structure, pcms can be classified into inorganic and organic categories. organic pcms including substances like fatty acids, octadecane, paraffin, and polyethylene glycol (peg) [12] have been pervasively employed in solar energy utilization, air conditioning, photovoltaic, textile, and building energy saving [13-14]. meanwhile, pcms are also extensively deployed in buildings for thermal storage, reducing energy consumption in air conditioning, enhancing thermal comfort, and improving building durability. according to iea/shc task 42 (eces annex 29) on compact thermal energy storage, pcms are crucial to the advancement of building efficiency and ensuring thermal comfort [15]. * corresponding author. e-mail address: z0903590036@gmail.com advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 2 however, pcms are susceptible to cause problems such as leakage or pollution of the environment when melted [16-18], which incurs limitations. therefore, microencapsulated phase change material (mepcm) with a core/shell structure has been developed to prevent the leakage of melted pcm during phase change [19-20]. moreover, the thermal conductivity of most materials is generally low and remains to be a challenge, as it results in a slow rate of latent heat transfer. thus, many researchers have incorporated carbon fiber [21], carbon nanotube (cnt) [22], graphite [23], metal [24], or metal oxide [25] to improve the thermal conductivity of mepcm. this study is to prepare the microcapsules by a sol-gel method [26], and the pcm is encapsulated with a copolymer shell to reduce leakage during the solid-liquid transition. in addition, nano-graphite particles (ngp) are added to the shell to increase its thermal conductivity. (1) firstly, methyl methacrylate (mma) and triethoxyvinylsilane (tevs) are copolymerized into a prepolymer, and the purpose of adding tevs is to improve the compatibility between the shell layer and the graphite heat-conducting material. (2) subsequently, the prepolymer is added to the solution prepared by polyvinyl alcohol (pva), octadecane, and tetraethoxysilane, using ethylene glycol dimethacrylate (egdma) as a bridging agent. (3) finally, the nanometer with high thermal conductivity ngp is added to obtain the thermally conductive phase-change microcapsules containing nano-graphite in the shell and octadecane in the core. consequently, these microcapsules can provide a temperature-regulating effect and improve the rate of heat transfer compared to traditional ones. furthermore, these mepcms will be integrated into wood-plastic composites (wpc) to create building materials with a thermal storage effect, ultimately reducing the need for air conditioning. 2. materials & methodology this section provides the materials and methods for preparing microcapsules, acidified ngp, ngp-containing microcapsules, and composite materials. additionally, the analysis procedures for the materials’ morphology, thermal properties, and mechanical strengths were described. 2.1. materials the materials were enumerated as follows: tevs, benzoyl peroxide (bpo), and mma supplied by acros organics, tetraethylorthosilicate (teos) was supplied by seedchem, octadecane supplied by alfa aesar, and egdma as the crosslinking agent was supplied by alfa aesar. meanwhile, all the following compounds and mixtures were of reagent grade, with no further purification upon use. pva with m.p. of 200 °c and density of 1.19-1.31 g/cm3 was supplied by taiwan chang chun group. ngp of density 1.8 g/cm3 and particle size 50 nm was supplied by conjutek co., taiwan. high-density polyethylene (hdpe) was supplied by formosa plastics corporation, maleic anhydride grafted polyethylene (mape) was supplied by e.chang trading co., ltd., and wood flour (wf) was supplied by everlast nfc co., ltd. 2.2. preparation of microcapsules first, 0.054 g of bpo, and 45 g of mma were added to 9 g of tevs and prepolymerized in an oil bath at 80 °c for 60 minutes under nitrogen with a rotation speed of 280 rpm to obtain copolymer. second, an aqueous solution of 1.5 wt% pva was prepared by dissolving 22.5 g of pva into 1500 ml of deionized water before adding octadecane (as pcm) and teos. the mixture was placed in a homogenizer and mixed thoroughly at 5000 rpm for 5 minutes. subsequently, the previously obtained copolymer was added to this homogenized mixture and mixed at 5000 rpm for another 5 minutes. then, 4 g of edgma and 0.56 g of bpo were added to the mixture and reacted in an oil bath at 80 °c for 24 hours with stirring, followed by cooling, centrifugation, filtration, and drying to obtain microcapsules (denoted as mepcm) as shown in fig. 1. advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 3 fig. 1 flow chart of microcapsule preparation 2.3. preparation of acidified ngp ngp was dried first to remove any residual moisture, then added to a solution consisting of sulfuric acid and nitric acid (3:1) while stirring at 90 °c for two hours. the resulting mixture was then transferred to an ice bath, followed by centrifugation, filtration, neutral washing, and drying to obtain acidified ngp. 2.4. preparation of ngp-containing microcapsules except for the final step, the other preparation steps are similar to those of mepcm. finally, bpo, edgma, and ngp were added to the mixture and reacted in an oil bath at 80 °c for 24 h with stirring, followed by cooling, centrifugation, filtration, and drying to produce ngp-containing pcm microcapsules, denoted as gmepcm, as depicted in fig. 1. 2.5. preparation of composite material hdpe, mape, gmepcm, and wf were dried in a 60 °c oven for 1 day to remove water and then melted with a mixing machine at 50 rpm and 150 °c according to different proportions in table 1. subsequently, the mixture was pressed at 150 °c and 60 psi, and kept for three minutes, then released the pressure for one minute. this procedure was repeated 3 times, then a series of test pieces were prepared and carried out various tests as depicted in fig. 2. table 1 formulation of composite material (wt%) hdpe mape wf gmepcm hd 100 hd-wf 80 20 hd-ma-wf 72 8 20 hd-gmepcm-wf 62 8 20 10 fig. 2 universal testing machine 2.6. characterization fourier transform infrared spectrometer (ftir) spectra were recorded on a spectrum tow ftir spectrometer using the attenuated total reflectance (atr) method with a resolution of 2 cm-1 that scanned 50 times from 400 to 4000 cm-1 at room temperature. before placing the sample for testing, it is necessary to scan the background value first. the subsequent steps are advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 4 placing the sample, performing sample analysis, and identifying the functional group with the same number of scans. transmission electron microscopy (tem; jem-2100, jeol, ltd., tokyo, japan) was used to observe the appearance of microcapsules. the amount of heat absorbed or released during phase transitions was measured by a ta instruments dsc q20 differential scanning calorimeter (dsc). between 3-5 mg of samples were placed in an aluminum pan and the dsc at 0 °c for 5 min. it was heated from 0 to 100 °c at a heating rate of 5 °c/min, then held constant at 100 °c for 5 minutes, and then cooled to 0 °c at a cooling rate of 5 °c/min under a nitrogen atmosphere of 50 ml/min. thermal behavior was determined using a ta instruments tga q50 thermogravimetric analyzer (tga). the samples were scanned from 50 to 600 °c at a heating rate of 10 °c/min in the presence of nitrogen flow. it can be used to observe the composition of organic and inorganic substances in the sample. in addition to this feature, it can also determine the thermal stability, thermal degradation temperature, and char yield of the samples. first, weigh 4-6 mg of sample, place it in a tga, analyze it in a nitrogen environment with a flow rate of 50 ml/min, raise the temperature to 50 °c, and then raise the temperature to 600 °c at a heating rate of 10 °c/min. the universal testing machine (fig. 2) mainly applies external force to the test piece, so that the test piece can resist the external force to reach the maximum value of its strength. the test piece is in the shape of a dumbbell, and the stretching rate is 50 mm/min. fix the two ends of the test piece with clamps, place the distance sensor, and start stretching up and down until the test piece breaks. the thermal deformation temperature tester mainly tests the shape and size deformation of composite materials by temperature change. conduct a heat distortion temperature (hdt) test under 66 psi pressure, input the width and thickness of the test piece, and start the test, raise the temperature until the deformation of the test piece generates the result of 1 mm. once the conditions are satisfied, stop the test. the impact resistance testing machine mainly uses the pendulum to break the notched test piece, and the energy absorbed by the pendulum is employed to calculate the energy consumed, and then the toughness of the material can be obtained. the size of the test piece (fig. 3) is about 64 mm × 13 mm × 3.2 mm rectangular test piece, which is tested after cutting a notch with the chamfering machine. the morphology of the fractured surface of a modified microcapsule containing composites was analyzed by scanning electron microscopy (sem; jeol jsm-6700f). the thermal conductivity analyzer uses the transient plane source (tps) method, while the sensor is a plane probe made of a conductive metal nickel and etched to form a continuous double helix structure sheet. during the test, the current passes through, and a certain heat source simultaneously diffusing to the samples on both sides of the probe is generated to raise the temperature. the speed of thermal diffusion depends on the heat conduction characteristics of the material, while the instrument can calculate the thermal conductivity, thermal diffusivity, and heat capacity of the material by recording the temperature and the response time of the probe. fig. 3 the sample for the impact test advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 5 3. experimental analysis in this section, the microcapsules and ngp-containing microcapsules were compared using ftir, tem, dsc, and tga analysis. additionally, the tensile strength, impact strength, hdt, thermal conductivity, and thermal storage test of hdped/microcapsule composites were discussed. 3.1. ftir analysis fig. 4 ftir spectrum of octadecane and microcapsules in the ftir spectrum (fig. 4), the octadecane showed obvious characteristic peaks at 2928 cm-1 and 2850 cm-1, which are c-h asymmetric and symmetrical stretching vibrations therein. these characteristic peaks can also be seen in mepcm and gmepcm. in addition, the characteristic peak at 1735 cm-1 of mepcm and gmepcm is due to the vibration of c=o in mma. the peak intensity of mepcm was stronger than that of gmepcmowing to the increased content of the core and the decreased thickness of the shell after the addition of ngp, and therefore the c=o intensity decreased. this will be discussed further in the dsc analysis section. the absorption at 1079 cm-1 is the characteristic peak of the si-o bond in tevs and teos. the characteristic peak of gmepcm was seemingly stronger than that of mepcm, and it is speculated that the characteristic peak is strengthened by the bonding between tevs and ngp. these results indicate that a copolymer composed of mma and tevs was synthesized, and the octadecane was successfully encapsulated in the shell of the copolymer. 3.2. transmission electron microscopy analysis (a) mepcm (b) gmepcm fig. 5 transmission electron microscopy analysis the transmission electron microscopy analysis of mepcm is shown in fig. 5(a). it can be observed that the mepcm was close to a spherical shape and the shell was transparent. the diameter of the mepcm was about 4 μm. it revealed that the pcm can be completely encapsulated and can avoid leakage simultaneously. a spherical appearance was also found on the advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 6 microcapsule with ngp (gmepcm) in fig. 5(b). the diameter of the gmepcm was about 3 μm. however, its shell did not reveal clear transparency as compared with that of mepcm in fig. 5(a). such a result confirms that ngp is uniformly dispersed in the shell of gmepcm and can also improve the thermal conductivity of the pcm. 3.3. differential scanning calorimeter analysis both fig. 6 and table 2 show the dsc analysis of octadecane and microcapsules. from the thermograms, it can be found that the melting point of octadecane is 25.84 °c, while the melting point of mepcm is 26.33 °c and that of gmepcm is 28.49 °c. it can be ascribed to the mechanism of the sol-gel method that can stabilize the microcapsules and increase the thermal stability of pcm. given such fact, the microcapsules made of polymer-coated octadecane have a higher melting point. in addition, the δhm and δhc of octadecane were 165.8 j/g and 160.4 j/g, mepcm microcapsules were 109.5 j/g and 81.19 j/g, and gmepcm microcapsules were 150.3 j/g and 139.0 j/g, respectively. fig. 6 dsc thermograms of octadecane and microcapsules table 2 dsc analysis data of octadecane and microcapsules tm (°c) tc (°c) δhm (j/g) δhc (j/g) encapsulation efficiency* (%) octadecane 25.84 21.40 165.8 160.4 mepcm 26.33 6.70 109.5 81.19 66.04% gmepcm 28.49 17.63 150.3 139.0 90.65% *��������� �� �� � ����%� � �∆���� ��������� �/∆����� �� ��� �� � 100% the encapsulation efficiency (i.e., content of octadecane) of mepcm and gmepcm microcapsules calculated by comparing the latent heat of bulk octadecane and encapsulated octadecane is capable of elevating to 66.04 and 90.65%. the result denotes higher encapsulation efficiency of gmepcm than that of mepcm. moreover, the enthalpy value of gmepcm (150.3 j/g) stands at a greater extent than that reported in the literature (140.6 j/g) [27], indicating a robust heat storage effect. in the cooling process, the crystallization temperatures (tc) of mepcm and gmepcm found were 6.70 °c and 17.63 °c, respectively. such a result indicates the crystallization rate of mepcm became faster with the addition of ngp owing to the fine particles of ngp being capable of acting as a nucleating agent, and the high thermal conductivity of the ngp, which promotes the crystallization of octadecane. 3.4. tga analysis figs. 7-8 and table 3 show the tga analysis results of octadecane and microcapsules. it can be seen that merely one main degradation peak of octadecane emerged at 278.37 °c, and the char yield is 0.00% due to being an organic pcm and being completely decomposed before 600 °c. however, the two maximum degradation peaks of mepcm stand at 261.10 °c and 386.31 °c, respectively. the former is the degradation peak of the core material in the microcapsule, and the latter is the advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 7 degradation peak of the shell layer of the microcapsule. during the preparation of mepcm, two silanes are added to increase the thermal conductivity, and hence the maximum degradation temperature will be slightly lowered. in addition, the char yield of mepcm increased to 1.53% due to the content of silicon elements. however, only one main degradation peak for gmepcm emerged at 291.05 °c, and the char yield increased to 3.90% due to the increase of char yield by nano graphite, an inorganic material. moreover, the addition of nano-graphite will improve the thermal conductivity, and the shell of gmepcm was thin, which leads to the one main degradation peak. fig. 7 tga analysis of octadecane and microcapsules fig. 8 dtg analysis of octadecane and microcapsules table 3 tga analysis data of octadecane and microcapsules char yield (%) tdmax (°c) octadecane 0.00 278.37 mepcm 1.53 261.10 386.31 gmepcm 3.90 291.05 3.5. tensile strength from fig. 9, it is observable that adding wf to hdpe (hd-wf) resulted in a decrease in tensile strength from 25.5 mpa to 19.7 mpa due to poor compatibility. therefore, an additional compatibilizer was added to improve the compatibility to improve the strength of the composite material. the results signified that the tensile strength of hd-ma-wf has effectively increased to 30.8 mpa after adding the compatibilizer. it can be found that the tensile strength of hd-gmepcm-wf with the advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 8 deployment of microcapsules decreased to 24.1 mpa. meanwhile, sem analysis reveals that gmepcm is evenly distributed within the composite material (fig. 10), which attests to the paucity of a significant strengthening effect on strength is unattributable to non-uniform dispersion. instead, it should be ascribed to the absence of a reinforcing effect on the tensile strength regarding the spherical structure of gmepcm, resulting in a slight decrease in tensile strength. nonetheless, it is still similar to that of pure hdpe, and the composite has an additional thermal storage effect. furthermore, fig. 8 also illustrates that the particle size of the majority of gmepcm is approximately 5 μm, aligning with the results of the pom analysis. fig. 9 tensile strength of the materials fig. 10 sem analysis of hd-gmepcm-wf 3.6. impact strength it can be seen that the impact strength of hdpe is significantly reduced from 115.4 j/m to 51.0 j/m when adding wf to hdpe (hd-wf), as depicted in fig. 11 since the wf is mainly used to reinforce tensile strength, and its compatibility with hdpe is poor. after adding the compatibilizer (hd-ma-wf), the impact strength increased to 53.6 j/m. it is also observable that a slight decrease in impact strength (48.7 j/m) after adding gmepcm to hd-ma-wf (hd-gmepcm-wf). fig. 11 impact strength of the materials 3.7. heat distortion temperature (hdt) fig. 12 exhibited that the hdt of hdpe is 87.8 °c, which increases to 102.5 °c after adding wf (hd-wf), due to the better hardness of wood fiber to resist the deformation of hdpe. the hdt of the composite further increased to 105.2 °c after adding the compatibilizer (hd-ma-wf). the result indicates that the compatibilizer is substantial to increase the interfacial advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 9 adhesion of the wf and hdpe, which subsequently improves the mechanical properties and heat resistance of the materials. in addition, the hdt of the composite material added with gmepcm (hd-gmepcm-wf) (95.7 °c) is larger than that of pure hdpe but lower than that of hd-ma-wfowing to the pcm being protected by the shell layer and being contained a thermally conductive material in the outer layer of the shell layer, which can improve the thermal conductivity of the material. in addition, the strength of the material decreases with the addition of microcapsules, thus reducing the heat distortion temperature. fig. 12 heat distortion temperature of the materials 3.8. thermal conductivity fig. 13 shows the thermal conductivity of the materials. the thermal conductivity of hdpe is 0.45 w/m·k and increases to 0.50, 0.60, and 0.62 w/m·k after adding wf, compatibilizer, and gmepcm to the composite material, respectively. it evinces that adding nano-graphite-containing microcapsules as a heat-conducting material will accelerate the rate of heat diffusion and improve the heat dissipation mechanism of hdpe. fig. 13 thermal conductivity of the materials 3.9 thermal storage test the results of the thermal storage test were revealed in fig. 14. in this experiment, the temperature of samples was initially kept at -10.0 °c, and then exposed to light, and the surface temperature of the samples was for 15 minutes. it is traceable that the temperature of the hd-gmepcm-wf composite rises slowly, which proves that it has the characteristics of thermal storage and the function of regulating temperature. the maximum temperatures of hd-wf and hd-gmepcm-wf are 25.1 and 22.6 °c, respectively. it is widely acknowledged that every 1 °c increase in air conditioner temperature can result in a 6% reduction in electricity consumption. therefore, the addition of gmepcm is expected to save approximately 15% in electricity advances in technology innovation, vol. 9, no. 1, 2024, pp. 01-11 10 consumption. as this composite material is applied to the inner construction materials, it will lower the room temperature and reduce the usage of the air conditioner. furthermore, it will reduce carbon emissions, electricity usage, and the exacerbation of global warming. fig. 14 thermal storage test 4. conclusions in this study, nano-graphite-containing phase change microcapsules with good thermal conductivity and thermal storage capacity were successfully prepared. moreover, the microcapsules were incorporated into hdpe to form a temperatureregulating building material. (1) in the ftir analysis, the results showed that the copolymer has been successfully synthesized and pcm has been successfully encapsulated in the shell. (2) the results also showed that the encapsulation efficiency of pcm was increased, and the crystallization rate of pcm became faster when the ngp was added. such results can be attributed to the significance of fine particles of ngp to the nucleating agent and the high thermal conductivity of the ngp, promoting the crystallization of octadecane. (3) in the tensile test, the results showed that the compatibilizer is indispensable to the increase of interfacial adhesion of the wf and hdpe and the ensuing improvement of hdpe’s tensile strength. however, the tensile strength was slightly reduced after adding microcapsules. the reason is that the unity aspect ratio of the microcapsules has no reinforcing effect on the tensile strength. 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[27] j. sun, j. zhao, b. wang, y. li, w. zhang, j. zhou, et al., “biodegradable wood plastic composites with phase change microcapsules of honeycomb-bn-layer for photothermal energy conversion and storage,” chemical engineering journal, vol. 448, article no. 137218, november 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 english language proofreader: chih-wen teng effect of pin diode integration on patch antennas for frequency reconfigurable antenna applications boyapati bharathidevi, jayendra kumar* school of electronics engineering, vit-ap university, amaravathi, andhra pradesh, india received 10 january 2022; received in revised form 05 august 2022; accepted 04 may 2023 doi: https://doi.org/10.46604/aiti.2023.9235 abstract pin diodes are commonly used to design reconfigurable antennas owing to their sufficient isolation, lower cost, and ease of fabrication. this study aims to explore the effect of biasing conditions of a pin diode radio frequency (rf) switch on a frequency-reconfigurable antenna. this approach investigates the contribution of the forward diode current and the reversed biased voltage on the shift in the operating band, the impedance matching, and the radiation efficiency of a reconfigurable antenna. the benefits and drawbacks of different approaches to modeling pin diode rf switches are demonstrated on ansys electromagnetic switch. the result shows a significant match between simulated and measured operating bands, impedance matching, and radiation efficiency. the proposed rf switch model can be used as a practical simulation model for implementing various reconfigurable microwave components. keywords: biasing circuit, microstrip antenna, pin diode switch, reconfigurable antenna, rf switch 1. introduction microstrip antennas are one of the most popular printed antennas which play a significant role in today’s wireless communication systems. extensive developments including bandwidth enhancement, surface wave reduction, gain enhancement, and radiation efficiency improvement are aimed at fulfilling the requirements of existing and future communication systems, which have made the microstrip antenna an important element in the field of radio frequency (rf) and microwave engineering. in recent years, research interests have been focused on increasing the features of microstrip antennas as multi-band [1-3], wideband [4], multi-polarization [5], switched parasitic multiple-input-multiple-output antennas [6], and frequency, polarization, and pattern diversity. reconfigurability can be achieved through two methods, (i) modifying the length of the current path or (ii) placing the slotted filters into the antenna structure using rf switches [7]. naturally, changing the state of the rf switches modifies the impedance levels which in turn modulates the frequency response of the antenna. the application of numerous reconfigurable antennas has been reported in the literature, and novelty is observed in terms of the type of reconfigurability (frequency, pattern, or polarization), design simplification, or improvement in the antenna parameters. the rf switch is a key component of reconfigurable antenna modeling and biasing conditions have a significant effect on its performance, durability, and robustness. an electronic rf switch draws a significant amount of current; thus, it is essential to estimate the requirement of the power supply for reconfigurable operations. previous research has proposed the different models use, including an ideal open and short circuit and a diode equivalent circuit without direct current (dc) blocking capacitors of the rf pin diode switch for reconfigurable antennas. the dc blocking capacitors and rf blocking inductors are necessary components to protect the rf signal and diode biasing source, * corresponding author. e-mail address: kumar.jayendra@gmail.com advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 211 respectively. investigation into the isolation and insertion loss of these switches after integrating them into a microwave system is required to ensure the desired switching operations. however, the switching operation of a pin diode rf is greatly dependent on the biasing elements and conditions. moreover, due to the rapid development of computer-added, it is convenient and common practice to use a software package to design and analyze a new system. although the accuracy of the simulation results is completely dependent on the accuracy of the component models, defined in the software package. nevertheless, the reconfigurable antenna is a wellestablished field, neither modeling nor biasing conditions of the rf switches for reconfigurable antenna application are discussed in the literature. this paper aims to demonstrate the (i) effect of the different rf switch models and (ii) biasing conditions on the radiation performance of a reconfigurable antenna. the use of different rf switches in optical [8-9], mems [10], fets [11], pin diodes [12], and micro-fluids [13] reconfigurable antennas have been proposed. optically controlled reconfigurable antennas are extremely delicate, thus, making them difficult to implement for practical applications [8-9]. mems rf switches require higher operating voltage and are relatively higher in cost [10]. on the contrary, fet-based switches require low operating power and are cheaper, but suffer from higher loss and poor linearity. pin diode-based switches offer a low-cost and low-loss solution [12]. hence, most of the reconfigurable antennas, frequency [14-18], polarization [19-21], and pattern [22-23] proposed in the literature are developed using a pin diode rf switch. vian and popovicet.al. [8], achieved frequency, pattern, and polarization reconfigurability by incorporating eight pin diodes in a single antenna structure. the compound reconfigurability of the antenna is remarkable but the integration of numerous pin diodes makes the overall structure too complicated for fabrication and installation. however, considerable results have been obtained so far due to ease of integration and moderate isolation. thus, in this work, the pin diode rf switch was chosen to identify the effect of the rf switch modeling and biasing the conditions on the accuracy, durability, and performance of reconfigurable antennas. numerous studies of reconfigurable antennas using different switching elements have been proposed for decades. the novelty of most of these antennas lies in their structure or switching mechanism. however, a detailed investigation of the antenna characteristics concerning the biasing conditions is unavailable in the previous studies. the investigation is imperative to establish the trade-off between antenna performance and dc power consumption. the present study emphasizes the antenna characteristics against the supplied forward current and reverses bias voltage. the effects of bias conditions on the performance of a pin diode-integrated reconfigurable antenna are reported using a simple slotted rectangular patch antenna. a trade-off between the antenna radiation performance and the diode current was established. a detailed analysis of a frequency reconfigurable antenna against the rf switch model and the biasing condition of the switch has been presented. a pin diode rf switch integrated rectangular slot has been incorporated into the patch of a conventional rectangular patch antenna to obtain dual-band frequency reconfigurability. in the simulation, the performance of the antenna has been analyzed using an ideal switch model and an actual switch model. thereafter the forward diode current and the reverse diode capacitance were varied to observe the effect of the biasing conditions on the performance of the antenna. the prototype of the frequency reconfigurable antenna was developed, and its scattering parameter and radiation efficiency were experimentally analyzed for different biasing conditions. during simulation, it was found that the other antenna parameters, such as radiation pattern, half-power beam width, etc., were not significantly affected by the biasing conditions, thus, experimental results have not been presented. the ideal model of the switch has been shown to exhibit an unacceptable frequency shift after fabrication, making it unacceptable for simulation. this study proposed the switch model has a good agreement amongst simulation and measured performance of the antenna. advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 212 2. configurations and modeling of rf switch series and shunt are commonly used configurations of pin diode rf switch [24] as shown in fig. 1. the isolation and insertion loss of a series configuration switch depends on the off-state diode capacitance (ct) and the on-state diode resistance (rs), respectively. on the other hand, the isolation and insertion loss of a shunt configuration depends on the onstate diode resistance (rs) and the off-state diode capacitance (ct), respectively. however, in a shunt configuration switch, the switching element is not directly connected to the rf transmission line; thus, providing lower insertion loss than the series configuration switch. moreover, the series configuration of the pin diode rf switch (shown in fig. 1.) is easy to integrate with reconfigurable antenna applications as has been widely reported in the previous literature. in fig. 1, capacitors c1 and c2 are the dc blocking capacitors, r1 is a current limiting resistor, l1 is used to protect the dc power supply from rf signals, and ls is the diode inductance. using ansys electromagnetics suite, a high-frequency-structural-simulator (hfss), an equivalent circuit was designed by assigning the lumped r-l-c boundary to the multiple 2d or 3d interconnected structures. a single structure can be modeled as a single component or a parallel combination of r-l, r-c, l-c, or r-l-c circuits. however, it is necessary to define the direction of the current flow while assigning the lumped r-l-c boundary. (a) on-state (b) off-state fig. 1 series configuration of an rf switch in this work, a 2d sheet was chosen to model a pin diode rf switch in the on-state and the off-state, as shown in fig. 1. excluding biasing elements, four interconnected structures are required to model a pin diode rf switch in the on-state or the off-state, as shown in fig. 2. for the on-state, the parallel combination of r and ct is replaced by rs as shown in fig. 2(b). moreover, the dimensions of sheets are chosen based on the dimensions of the practical surface-mount capacitors and diodes. the values of ls, ct, and rs can be found in the technical datasheet of the respective diode [25]. (a) on-state (b) off-state fig. 2 model of pin diode rf switch in the ansys electromagnetics suite, hfss 3. performance analysis of the frequency reconfigurable antenna in this section, a conventional rectangular patch antenna was designed, and a rectangular slot integrated with two pin diode rf switches introduced frequency reconfigurability. the antenna was designed on an fr4 substrate of thickness 1.6 mm and fed through a 50 ω co-axial sub-miniature version-a (sma) connector. the fr4 substrates are commonly used for printed circuit board (pcb) development and are much cheaper compared to other low-loss substrates such as rogers rt duroid. advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 213 also, a low-frequency patch antenna exhibits acceptable performance for the fr4 substrate of loss tangent 0.02. the configuration of the antenna and magnified view of the switch model is shown in fig. 3. the proposed antenna configuration and the magnified view of the biasing arrangement are shown in fig. 3. (a) test antenna layout (b) switch model fig. 3 configuration of the frequency reconfigurable antenna (l1 = 1 mh, r1 = 100 ω, c1 = c2 = 1 uf, rs, and ls are taken from datasheet) 3.1. simulation analysis this section presents the performance of the frequency reconfigurable antenna against different switch models and biasing conditions. in the ideal condition, for the off-state, all the circuit elements and biasing line have been removed and for the on-state, two copper sheets were used to establish the connection. the switch model discussed in section 2 was used as a practical switch. the biasing conditions were controlled by changing the on-state resistance, and the off-state capacitance, as presented in the technical datasheet of the pin diode nxp bap65-02 [25]. the proposed antenna is intended to operate in 400 mhz wireless medical telemetry service (wmts) and 700 mhz global system for mobile (gsm) bands. thus, the pin diode nxp bap65-02 is chosen, which is known to support the intended frequency range. if another diode is used, the series inductance, on-state resistance, and off-state capacitance will change accordingly. the pin diode nxp bap65-02 has sufficiently good isolation in the off-state and low insertion loss in the onstate, as presented in its technical datasheet [25]. the antenna response was obtained for the ideal switch and the practical switch model, as shown in fig. 4. in an ideal case, the switch positions are open and short in the off-state and the on-state, respectively. in practice, for the on-state, a diode resistance of 0.35 ω is set, corresponding to 100 ma forward diode current. similarly, in the off-state, the capacitance was set to 0.375 pf, corresponding to 20 v reverse voltage. the variation in nxp bap65-02 on-state diode forward resistance and off-state junction capacitance against the forward current and the reverse voltage, respectively listed in table 1, is reproduced from the technical datasheet [25]. (a) scattering parameter (s11) of the antenna for different diode models (b) radiation efficiency of the antenna for different diode models fig. 4 performance of the antenna for the ideal condition of the switch and pin diode rf switch model advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 214 table 1 nxp bap65-02 characteristics [25] forward characteristics reverse characteristics forward current (ma) forward resistance rs (ω) reverse voltage (vr) junction capacitance cd (pf) 1 1 0 0.65 5 0.65 1 0.55 10 0.56 3 0.5 100 0.35 20 0.375 the scattering parameters and the radiation efficiency of the antenna are shown in fig. 4. it is evident in fig. 4(a) that there is a considerable difference between impedance matching as well as operating bands for both conditions. moreover, in the off-state, the operating bands are completely different, confirming the incapacity of the ideal diode model. to develop an electronically reconfigurable antenna, practical diode(s) are integrated into the antenna structure. when these active elements are added to the antenna structure, the distributed reactance sufficiently changes, leading to the shift in series or parallel resonance center frequency. thus, the shift in the operating band should be accounted for to develop a practical electronically reconfigurable antenna. in fig. 4(b), it can be observed that the ideal model of the diode exhibits much better radiation performance than a practical model, which confirms the significant losses due to the integration of pin diode rf switches. although, it should be noted that the antenna has poor radiation efficiency in the off-state than the on-state. the performance of the reconfigurable antenna was further analyzed to consider the different biasing conditions. in the on-state, the forward diode current was increased stepwise to observe its effect on the shift in the operating band, the impedance matching, and the radiation efficiency. in the off-state, the reversed biased voltage is varied to analyze the antenna performances. the forward current and reverse bias voltage change did not shift the operating bands, as shown in fig. 5(a). however, a remarkable change in the impedance matching can be observed in the off-state. a higher forward diode current yields better radiation efficiency, whereas the reverse bias voltage did not affect the radiation performance, as shown in fig. 5(b) . the simulated radiation patterns against different biasing conditions are shown in fig. 6. it has been observed that there is a negligible effect of the biasing conditions on the radiation pattern in both the off and on conditions. however, in the onstate, the back radiation pattern of the antenna is slightly affected, as shown in fig. 6(b). it has been noticed in fig. 5(b) that higher forward current yields more radiation from the antenna structure, which holds for the front as well as back radiations. therefore, as the forward current increases, the back radiation of the antenna also increases due to improvement in the radiation efficiency. (a) scattering parameter (s11) of the antenna in on-state and off-state against different forward current and reverse voltages, respectively (b) radiation efficiency of the antenna in on-state and off-state against different forward current and reverse voltages, respectively fig. 5 simulated performance against different biasing conditions advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 215 (a) off-state e-plane radiation pattern at 400 mhz (b) on-state radiation pattern at 700 mhz fig. 6 e-plane radiation pattern of the antenna in on-state and off-state against different forward current and reverse voltages, respectively 3.2. experimental analysis a physical prototype of the antenna was developed and experimentally analyzed to validate the simulated observations. the prototype of the antenna with the s11 parameter measurement setup is shown in fig. 7. the pcb of this design can be developed using a traditional chemical etching process or a pcb milling machine. a pcb milling machine is a non-chemical computer-aided machine that creates a high-quality pcb by milling the metals from a pcb laminate. the computer guides the milling bits as per the layout provided. to realize a prototype with an ideal diode model, the switch positions were open and short for the off-state and the on-state, respectively. (a) scattering parameter measurement setup (b) top view of the prototype (c) top view of the prototype fig. 7 s11 measurement setup and prototype of the antenna for a practical realization, two surface-mount capacitors were soldered at the anode and cathode of a pin diode nxp bap65-02. the rf switches were biased using a dc power supply. the s11 parameters were measured using a two-port network analyzer. the radiation efficiency (η = g / d) is measured using the gain (g) / directivity(d) method, as suggested by huang [26] and kumar et al. [27]. the gain of the antenna was measured using the two-antenna method and divided by the simulated directivity to estimate the radiation efficiency. the discussion on radiation efficiency presented is derived from the measured gain. however, the measured gain curve is not presented in this paper. the measured s11 parameters and the radiation efficiency of the antenna against forward diode current are shown in fig. 8. since the reverse bias voltage does not significantly affect the antenna performance, the corresponding experimental analysis was not conducted. an unacceptable shift in the operating band for the off-state and a slight shift in the on-state can be observed in fig. 8(a) for the ideal and the practical diode models, as observed during simulation analysis. advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 216 (a) measured scattering parameter (s11) against the forward current (b) measured radiation efficiency against the forward current fig. 8 measured performance against different biasing current however, for a forward current of 10 ma, the antenna has extremely poor impedance matching. in the on-state, the measured radiation efficiency for the ideal diode model is nearly 11% better than the practical model with a diode forward current of 100 ma. as observed in the simulation, the measured radiation efficiency of the antenna is extremely poor in the on-state. the simulated and measured radiation patterns of the fabricated prototype have been presented in fig. 9. the antenna radiation pattern is measured using a radiation pattern measurement setup that consists of an rf source, a spectrum analyzer, a turntable with an automated data logger and 360° rotatable antenna stand to hold the antenna under test (aut), and another 360° rotatable antenna stand to hold the source antenna. this setup is placed in an electromagnetically shielded chamber. in the on-state, the antenna has perfect broadside radiation, and the co and cross-polarization isolation is more than 18 db. in the off-state, the antenna has a slightly tilted main lobe, and the isolation between co and cross-polarization is more than 16 db. a good agreement has been demonstrated between simulation and measured results which validates the proposed work. (a) simulated and measured e-plane radiation at 690 mhz in on-state (b) simulated and measured e-plane radiation at 420 mhz in off-state fig. 9 simulated and measured e-plane radiation pattern of the fabricated prototype 4. conclusions an investigation on reconfigurable antenna characteristics against different diode models and biasing condition of the diode has been carried out. during the simulation, the reactance of a diode should be considered to develop a practical antenna to avoid a mismatch between simulated and measured results. increasing the diode forward current can improve the impedance matching and the radiation efficiency of an antenna. the reverse bias voltage has an insignificant effect on the radiation performance. however, the off-state radiation efficiency is poor when the diode is not active. the result shows that the advances in technology innovation, vol. 8, no. 3, 2023, pp. 210-218 217 proposed rf switch model has good impedance matching, radiation efficiency, and co and cross-polarization isolation. the proposed method also be performed for other active switching elements such as a varactor diode, field-effect transistor, and bipolar junction transistors. conflicts of interest the authors declare no conflict of interest. references [1] j. kumar, b. basu, f. a. talukdar, and a. nandi, “multimode-inspired low cross-polarization multiband antenna fabricated using graphene-based conductive ink,” ieee antennas and wireless propagation letters, vol. 17, no. 10, pp. 1861-1865, october 2018. 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[27] j. kumar, b. basu, f. a. talukdar, and a. nandi, “graphene-based wideband antenna for aeronautical radionavigation applications,” journal of. electromagnetic waves and applications, vol. 31, no. 18, pp. 2046-2054, august 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://www.nxp.com/docs/en/data-sheet/bap65-02.pdf microsoft word 5-v9n4(2024)-aiti#13972(319-331).docx advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 english language proofreader: chih-wei chang a novel hybrid approach for feature selection in cardiovascular risk assessment ankush hutke*, jyoti deshmukh department of computer engineering, mct’s rajiv gandhi institute of technology, university of mumbai, maharashtra, india received 06 july 2024; received in revised form 18 august 2024; accepted 22 august 2024 doi: https://doi.org/10.46604/aiti.2024.13972 abstract early detection of cardiac risk is crucial for accurate diagnosis and treatment of fatal cardiovascular diseases. selecting relevant features is essential for machine learning in building an effective decision support system of cardiovascular risk assessment, ensuring accuracy of high-dimensional data. this study aims to propose a novel hybrid feature selection approach, termed ant colony optimization with hill climbing (acohc), integrating ant colony optimization (aco) and hill climbing (hc) algorithms. the accuracy metric and various classifiers are deployed to evaluate the effectiveness. additionally, comparisons are made with nine alternative feature selection techniques. the feature subset identified through the acohc attains a classification accuracy of 95.1% with the support vector machine classifier. keywords: machine learning, support vector machine, acohc, hill climbing, ant colony optimization 1. introduction cardiovascular diseases (cvds) continue to be the leading cause of mortality worldwide, posing significant challenges for healthcare systems and necessitating effective risk assessment and management strategies [1]. therefore, accurate prediction of cardiovascular risk, which requires the integration and analysis of complex and multifaceted data, is crucial for early intervention and prevention [2]. the high-dimensional and diverse nature of cardiovascular data, which may include clinical, genetic, lifestyle, and environmental aspects, hinders traditional feature selection approaches despite their value [3-4]. many diverse domains employ machine learning, an expanding topic in computer science, to develop various decision support systems. practically, grappling with high-dimensional data emerges as a prevalent challenge. this type of data can escalate complexity and compromise system accuracy [5]. feature selection techniques tackle this problem by eliminating insignificant features and keeping the relevant ones. this reduction improves system accuracy and simplifies its complexity. additionally, removing redundant and noisy features helps to decrease computation time [6]. three categories may be used to group feature selection techniques: (1) filter methods: these methods determine the importance of each feature apart from the learning process. statistical measurements or heuristic techniques are pervasively employed to rank, or score features according to their correlation with the target variable. the chi-square test and information gain are examples of common methods. * corresponding author. e-mail address: ankush.hutke@mctrgit.ac.in 320 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 (2) wrapper methods: these methods appraise the performance of a subset of features using the predictive power of a particular machine learning algorithm. they entail iterative search procedures, such as backward elimination, forward selection, or recursive feature elimination (rfe), to find the optimal subset of features, thereby providing the optimal performance for the specified model. (3) embedded methods: these techniques include feature selection while creating the model. feature selection occurs internally within the algorithm during training. examples include decision trees, least absolute shrinkage and selection operator (lasso), and feature importance scores derived from ensemble models like random forests [7]. researchers have examined multifarious feature selection strategies and classifiers on different heart disease datasets. diagnosing diseases using computer-based systems encompasses processing and analyzing high-dimensional and diverse data. such data can incur model overfitting and prolonged training times. feature selection, a dimensionality reduction strategy, removes redundant features that do not significantly impact classifier performance, thereby reducing the data to a manageable size. several effective feature selection methods have been created recently to reduce the negative effects of high dimensionality. the influence of several feature selection techniques is examined in this study. an experimental approach is used, which includes extensive testing on actual cardiac disease-related datasets obtained from the university of california, irvine (uci). the study aims to identify the most effective predictive models for forecasting heart disease and aiding the medical community. feature selection is assessed alongside accuracy, precision, and recall as key performance indicators for the predictive models. the following parts of the article are structured as section 2 gives a detailed related work, including work done by various researchers and research gaps. section 3 delves into the specifics of the proposed methodologies. the results are then shown in section 4, followed by a comprehensive analysis. section 5 offers a concise concluding remark of the study with some last reflections. 2. related work this section summarizes the methods utilized for selecting features in the heart disease dataset. (1) chi-square algorithm: it is a filter-based feature selection approach, which computes the chi-squared score between each attribute and target class that measures the difference between observed and expected values. in addition, the chi-square algorithm measures the dependency between the categorical input feature and the categorical target variable. features with high chi-square statistics and low p-values are considered more relevant to the target variable [8]. the chi-square value is calculated for each feature as shown below: ( ) 2 2 − = o e x e (1) where � represents the observed value and � denotes the expected value. (2) analysis of variance (anova): it is a statistical method used to examine the differences in means among the groups. in feature selection, the anova assesses the relationship between continuous input features and a categorical target variable. furthermore, the anova calculates the f-value and associated p-value for each feature, indicating the significance of the feature’s effect on the target variable [9]. (3) forward selection algorithm (fsa): it is a wrapper technique that adds features to the feature subset incrementally, one at a time. after assessing the performance of the model with the new feature, it chooses the top-performing feature subset at each stage. this procedure is carried out repeatedly until the performance of the model evinces no further signs of improvement. when selecting a subset of features with a support vector machine (svm) as the learning algorithm, it is crucial to stratify the data to ensure that each class is adequately represented [10]. advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 321 (4) backward elimination algorithm (bea): backward elimination is a different wrapping strategy that starts with the entire feature set and removes each feature individually. it chooses the top-performing feature subset at each step, by assessing the performance of the model with the deleted feature. this process continues until further removal of features results in decreased model performance [10]. (5) mutual information (mi): the amount of knowledge about one variable learned through the other variable is measured by mi. mi gauges the degree of dependability between the target variable and the input features throughout the feature selection process. to predict the target variable, features rendering high mi values are thought to be more informative [11]. (6) l2 regularization ridge regression (l2): l2 is an embedded method incorporating feature selection within the model training process. the conventional regression objective function is extended with a penalty term (l2 regularization) to reduce the coefficients of less significant characteristics to zero. features with smaller coefficients are effectively down-weighted, leading to automatic feature selection during model training [12]. (7) particle swarm optimization (pso): it is a population-based stochastic optimization method that draws inspiration from fish schools and flocks of birds for their social behaviors. in feature selection, pso optimizes a population of candidate feature subsets by repeatedly updating the positions of particles in the search space. the goal is to identify the ideal feature subset that minimizes or maximizes some objective function, which tends to be pertinent to the performance of the model [13]. (8) ant colony optimization (aco): it is a metaheuristic optimization method that draws inspiration from ants’ foraging habits. in feature selection, aco constructs a graph representation of the feature space, where features are nodes and edges represent the interactions between features. ants iteratively build solutions by selecting features based on pheromone trails and heuristic information to find an optimal feature subset [13]. (9) hill climbing (hc) algorithm: it is a local search optimization algorithm that iteratively explores the neighboring solutions within the search space. in feature selection, hc starts with an initial feature subset and iteratively modifies it by evaluating neighboring feature subsets. subsequently, it moves towards the neighboring solution that improves the objective function (e.g., model performance), continuing until no further improvement is possible [14]. jabbar et al. [15] employed feature selection using the chi-square method on the cleveland heart disease dataset. the chi-square method is a filter-based feature selection technique that assesses the relationship between the target variable and each feature using the chi-square statistic. wiharto et al. [16] worked on the cleveland dataset to employ feature selection methods. specifically, they utilized the information gain criterion to select features. in the paper by haq et al. [17], feature selection methods were employed on the cleveland heart disease dataset. three specific techniques are utilized and listed as follows: (1) minimal-redundancy-maximal-relevance (mrmr) opts for the features based on the target variable and degree of redundancy. it minimizes duplication among chosen characteristics while taking into account the mi between features and the target variable. (2) relief is a method for feature selection that ranks features according to the differentiability between instances of various classes. it iteratively updates feature weights by comparing nearest neighbor instances belonging to the same and different classes. (3) lasso is a method of regression analysis that enhances the interpretability and prediction accuracy of statistical models by performing regularization and variable selection. it penalizes the absolute size of the regression coefficients, encouraging sparse solutions where irrelevant features have zero coefficients. these selected features are used to determine a subset of pertinent and useful characteristics for predicting results in heart disease. 322 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 khourdifi and bahaj [18] utilized the cleveland dataset to explore feature selection methods. specifically, they used the feature selection method as quick correlation-based that is enhanced by ant colony and pso. this approach is likely to be involved in leveraging correlations between features and the target variable (heart disease diagnosis) to efficiently select the most relevant features subset. in the paper by jain et al. [19], the feature selection method, pso, is applied to the cleveland heart disease dataset. initially, pso is a metaheuristic optimization method that draws inspiration from fish schools and bird flocking behavior. it entails updating a population of potential solutions (particles) iteratively according to both the global and personal best-known positions. ali et al. [20] employed the chi-square method as a filter-based feature selection technique to enhance the predictive performance of models on the cleveland heart disease dataset. the paper by abdar et al. [21] focuses on feature selection methods applied to the dataset by z-alizadeh sani using genetic algorithm (ga) and pso. these optimization algorithms are utilized to identify the most relevant features within the dataset for improved classification performance. the ga mimics natural selection processes by iteratively creating a population of viable solutions through crossover, mutation, and selection processes. in contrast, pso models the behavior of particles within a search space by continuously updating their positions based on both individual and collective best solutions. in the paper by amin et al. [22], a feature selection method, which is known as the brute force method was employed on the cleveland dataset. this method encompasses exhaustively evaluating all possible feature subsets to determine the optimal combination for the given dataset and classification task. by systematically testing every feature subset, the brute force method ensures that the most relevant features are selected, potentially improving the accuracy and efficiency of the classification model. notably, this method might be computationally demanding, especially for datasets having more number of features. notwithstanding its computational demands, the brute force method offers a rigorous and comprehensive approach to feature selection, it may be precious in domains where accuracy is paramount, such as medical diagnostics. the authors, gárate-escamila et al. [8], employed two feature selection methods in their work on the cleveland and hungarian heart disease datasets, i.e., chi-square and principal component analysis (pca). to evaluate the significance of categorical features containing the target variable, they used chi-square. the datasets are made less dimensional by using pca, enabling the efficient capture of the most relevant characteristics in a lower-dimensional space. these feature selection methods are applied to the cleveland and hungarian heart disease datasets in their study. the paper by theerthagiri and vidya [23] focused on methods for feature selection applied to a heart disease dataset. specifically, the paper employed rfe as the feature selection technique. rfe is a wrapper method that iteratively selects subsets of features by training the model multiple times and eliminating insignificant features in each iteration. this method continues until the target number of features is obtained or until a predetermined performance parameter is optimized. rfe considers the interactions among features, ensuring that the most relevant ones are retained for classification or prediction tasks pertinent to heart disease. tian and shi [24] employed feature selection methods on the cleveland dataset using modified particle swarm optimization (mpso). the main goal of the research was to improve feature selection such that heart disease prediction models perform better apropos classification. the mpso in which the selection process likely involved iteratively evaluating different feature subsets to identify the most informative ones for classification. the study probably covered the performance of the mpso-based feature selection strategy in comparison to other approaches to increase classification accuracy and decrease computing complexity. 3. proposed methodology the proposed research aims to enhance the accuracy of a system by selecting the most relevant feature subset in a dataset related to heart disease. fig. 1 illustrates the system framework. the essential elements of the framework are comprised of data collection, data preprocessing, feature optimization, and performance evaluation. subsequent sections detail the foundational elements of the suggested framework. advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 323 fig. 1 framework for the system 3.1. data collection the dataset used for this study is cleveland heart disease datasets from the uci web repository. this dataset initially contains 303 instances and 75 attributes. table 1 presents a thorough overview of the dataset. the target feature label contains two values to determine the presence of cardiac disease. table 1 feature subsets using feature optimization method sr. no. feature name values 1 age age 29 to 77 2 sex sex 1: male 0: female 3 chest pain type cp 1: typical angina 2: atypical angina 3: non-angina pain 4: asymptomatic 4 blood pressure at rest trestbps from 94 mm hg to 200 mm hg 5 serum cholesterol chol from 126 mg/dl to 564 mg/dl 6 fasting blood sugar fbs fbsr > 120 mg/dl (true: 1, false: 0) 7 resting electrocardiographic results restecg 0: normal 1: st-t waveabnormality 2: hypertrophy 8 maximum heart rate achieved thalach from 71 to 202 9 exercise-induced angina exang 1: yes 0: no 10 st depression induced by exercise relative to rest oldpeak 1: up sloping 2: flat 3: down sloping 11 slope at the peak exercise st segment slope from 0 to 6.2 12 no. of major vessels ca from 0 to 3 13 thallium thal 3: normal 6: fixed defect 7: reversible defect 14 target tar 1: heart disease 0: no heart disease 3.2. data preprocessing processing the dataset is essential to accurately represent the quality of data. there are various methods to handle missing values, including ignoring them, replacing them with a numeric value, using the most frequent value for the feature, or substituting them with the mean value of the attribute. in this study, the initial step is to eliminate records containing missing values. to enhance the comparability and performance of machine learning algorithms, standardization is applied to the features. this process encompasses removing the mean and scaling to unit variance, aligning the features with a standard normal distribution. given that machine learning algorithms preponderantly perform better when features adhere to a standard normal distribution, standardization is especially instrumental. 324 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 3.3. feature optimization the experiment is conducted in this phase regardless of feature selection to assess its effects. feature optimization is intended to select the important features related to heart diseases. additionally, feature optimization facilitates the further establishment of precise models by removing or reducing the significance of irrelevant features, thus reducing training time and improving learning performance. this experiment examines the performance of various feature selection methods across filter, wrapper, and embedded categories. in this section, the proposed ant colony optimization with hill climbing (acohc) method is utilized for feature optimization. the acohc algorithm combines two powerful algorithms into a hybrid feature selection method: the aco algorithm and the hc algorithm. fig. 2 depicts the flowchart of this approach. the acohc method commences by creating k artificial ants to explore the feature space. initially, these ants search randomly within this space. throughout a series of iterations, each ant selects certain features and develops its solution during each iteration t. the gathered subsets are then evaluated. by iteratively evaluating feature subsets and updating pheromone levels, aco guides the search toward regions of higher performance. fig. 2 flowchart of feature optimization method after the aco identifies the initial feature subset, the chosen subset undergoes further enhancement through the application of the hc algorithm. hc is a heuristic local search technique that systematically investigates neighboring solutions to enhance the existing feature subset. by continuously optimizing an objective function, often denoted as the performance metric, hc gradually enhances the feature set towards greater classification accuracy. this iterative process of refinement empowers the algorithm to enhance the performance, as compared to the original feature subset identified by aco. the acohc method uniquely combines aco and hc to balance global exploration and local exploitation. aco explores diverse solutions through probabilistic decisions and pheromone updates, while hc refines these solutions by local optimization. this hybrid approach leverages the exploration strength of aco and the fine-tuning capability of the hc, yielding higher-quality solutions and reduced risk of premature convergence a. construction of feasible solutions in acohc, each ant begins constructing a solution by randomly choosing an initial feature. subsequently, it selects the subsequent feature from the pool of unchosen features based on a specified probability. the probability that an ant_k, currently at feature i will move to feature j at time t is: advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 325 ( ( )) ( ( )) ( ) , ( ( )) ( ( )) α β α β τ η τ η ∈ = ∈  k jn k ki i i j j jj t t p t j n t t (2) where the characteristics that ant_k has not selected yet but has the option to select from �� �, which is the viable neighborhood for ant_k. it functions as the memory of an ant. at time t, the heuristic information of feature i is represented by η�(t). the feature-related pheromone value at time t is shown by τ�(t). the coefficients α and β represent the effect of pheromone τ and heuristic information η, respectively. the parameters α and β are adjusted to real positive values following the parameter setting guidelines. b. pheromone updating the pheromone update equations, which specify how to adjust the pheromone levels, are used by all ants to increase the pheromone values and update �(�). these equations are determined by: ( )( 1) ( ) 1 ( )τ ρ τ+ = × − + ∆i it t t (3) , ( ) 0, τ  ∆ =   i q if the ant selects the feature t otherwise (4) where, δτ� � is the pheromone left behind by an ant k and found as an efficient solution for the present iteration, τ�(t) is the amount of pheromone on the path i at time t, and ρ represents the features pheromone evaporation rate (0 < ρ < 1). given the phenomenon that ants tend to communicate with one another using the pheromone value in the aco algorithm, each ant utilized the obtained information to propose better solutions, thereby increasing the efficiency of the solutions found after several iterations. in eq. (3), the left term indicates the evaporation of pheromone across all edges, while the right term represents the increase in pheromone intensity due to deposition. the time complexity of aco is given by: aco ( ( ))× ×o a i o e (5) where a is the number of ants, iaco is the number of iterations of aco, and o(e) is the complexity of evaluating the objective function for a subset of features. after aco selects a subset of features, hc is applied to further refine this subset. assuming the number of iterations for hc is ihc, the time complexity of hc is presented as: hc hc ( ( ))×o i o e (6) where ihc is the number of iterations of hc, and o(ehc) is the complexity of evaluating the objective function for the feature subset selected by aco. the combined time complexity of the hybrid approach, where aco is followed by hc, is the sum of the time complexities of the two phases: aco hc hc ( ( ) ( ( ))× × + ×o a i o e o i o e (7) the summary of the acohc algorithm is mentioned as follows: input: initial features of the dataset output: optimized feature set initialization: [number of generations, number of ants, pheromone value (r), maximum features, heuristic value (q), pheromone evaporation rate (�), �, �] 1 repeat for each iteration 326 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 2 for each ant 3 select distinct features randomly 4 calculate probabilities for selecting features based on pheromone levels 5 the selected features are appended to the ant_solutions list 6 end for 7 evaluate the performance (accuracy) of each solution 8 find the index of the ant solution with the highest accuracy using np.argmax 9 if the accuracy of this best ant solution > the best accuracy 10 best_accuracy = ant_accuracies[best_ant_index] 11 best_solution = ant_solutions[best_ant_index] 12 end if (after evaluating all ant solutions and selecting the best one) 13 updates the pheromone 14 return best_solution that represents the highest accuracy feature subset 15 end for initially, the feature set is optimized using the aco algorithm. to further reduce the number of features, the optimized set of features will be input into the hc algorithm. the pseudocode of the hc algorithm is given below: input: initial set of features obtained in aco output: final optimized feature set 1 current solution = initial solution 2 repeat 3 for all neighbors of the current solution do 4 obtain a random neighbor 5 if accuracy > best accuracy then 6 best accuracy = neighbor solution 7 best solution = index of the neighbor solution 8 end if 9 end for 10 until the end of the iterations the rationale for choosing aco and hc specifically for feature selection in cardiovascular risk assessment lies in their complementary strengths. aco renders a robust global search capability, efficiently handling high-dimensional data and avoiding local optimum, while hc offers effective local optimization, refining the feature sets identified by aco. this combination ensures the selection of high-quality feature subsets, facilitating more accurate and reliable predictive models for cardiovascular risk assessment. this study operates under the following assumptions: (1) the dataset is of high quality and representative, containing relevant features for heart disease prediction. (2) parameter settings for both aco and hc are optimal or near-optimal, enhancing the feature selection process. 4. results and discussion in the experiment, the parameters are set empirically as pheromone constant (updating) α = 1, heuristic information ß = 1, number of ants = 10, number of iterations = 50, pheromone decay (trail evaporates) � = 0.5. the effectiveness of the proposed approach for classification is assessed using logistic regression (lr), decision tree (dt), random forest (rf), and svm classifiers. the experimental configuration entails implementing the proposed method using python 3.0 programming language. the interactive coding environment is provided by google colab to perform experiments in python. lr employed the ‘lbfgs’ solver with l2 regularization and a high number of iterations (max_iter = 1000). rf utilized 100 estimators and the ‘gini’ criterion for node impurity calculation. dt utilized the ‘gini’ criterion for splitting, without any depth restriction. svm employed the default ‘rbf’ kernel for non-linear separation and regularization parameters. feature subsets obtained through the hybrid acohc are assessed with lr, dt, rf, and svm classifiers, and the final feature subset is selected based on the acohc method. the performance is evaluated based on metrics including accuracy, precision, recall, f-score, and specificity. advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 327 the feature selection method proposed is evaluated against nine alternative feature selection techniques for comparison. the reduced feature subsets, which are produced by the various feature selection techniques, are displayed in table 2. in the table, every existing feature selection method is tested with different sizes of feature subsets, such as 5, 6, and 7 features. each feature is represented by a value of either 1 or 0. according to the attribute sequence below, if a selected feature is included in the feature subset, it will be represented by 1; otherwise, if the selected feature is excluded from the subset, it will be represented by 0. after feature optimization using the proposed acohc method the selected features are: ‘cp’, ‘trestbps’, ‘thalach’, ‘ca’, and ‘thal’. table 2 feature subsets using feature optimization method feature selection method age sex cp trest-bps chol fbs rest ecg thal-ach exang old-peak slope ca thal size of feature subset cs 0 0 1 0 0 0 0 1 1 1 0 1 0 5 1 0 1 0 1 0 0 0 1 1 0 1 0 6 1 0 1 0 1 0 0 1 1 1 0 1 0 7 anova 0 0 1 0 0 0 0 1 1 1 0 1 0 5 0 0 1 0 0 0 0 1 1 1 1 1 0 6 0 0 1 0 0 0 0 1 1 1 1 1 1 7 fsa 0 1 0 0 0 1 0 0 1 0 0 1 1 5 0 1 0 1 0 1 0 0 1 0 0 1 1 6 1 1 0 1 0 1 0 0 1 0 0 1 1 7 bea 0 1 0 1 0 0 0 0 1 0 1 1 0 5 1 2 0 1 0 0 0 0 1 0 1 1 0 6 1 1 0 0 1 1 0 0 1 0 1 1 0 7 mi 0 1 0 0 0 0 0 1 0 1 0 1 1 5 0 0 0 0 0 0 0 1 1 1 1 1 1 6 0 0 1 0 0 0 0 1 1 1 1 1 1 7 l2 0 1 1 0 0 0 1 0 1 0 0 1 0 5 0 1 1 0 0 0 0 0 1 0 1 1 1 6 0 1 1 0 0 0 0 0 1 1 1 1 1 7 pso 0 0 1 1 1 0 1 1 0 0 0 0 0 5 0 1 1 1 1 0 1 1 0 0 0 0 0 6 0 1 1 1 0 0 1 1 1 0 0 0 1 7 aco 0 0 1 0 0 1 0 0 0 0 1 1 1 5 1 0 1 1 0 0 0 0 1 1 0 1 0 6 0 0 1 1 1 0 0 1 0 1 1 0 1 7 hc 0 0 1 1 0 0 0 1 0 0 0 1 1 5 0 1 1 1 0 0 0 1 0 1 0 1 0 6 0 1 1 1 1 1 0 1 0 0 0 1 0 7 acohc 0 0 1 1 0 0 0 1 0 0 0 1 1 5 the classification accuracies obtained using feature sets optimized by different feature selection techniques are shown in table 3. the analysis demonstrates that models built from optimized feature subsets consistently outperform those built from the original feature set. initially, training the original feature set with lr, dt, rf, and svm yields a maximum accuracy of 54.0%, precision of 55.7%, sensitivity of 50.8%, and f-measure of 50.8%. however, after applying feature selection techniques, a significant improvement in classifier accuracy is observed across all models. table 3 classification accuracies of reduced feature subsets feature selection method no. of features accuracy lr dt rf svm --13 0.540 0.557 0.508 0.508 cs 5 0.885 0.770 0.803 0.688 6 0.885 0.770 0.770 0.819 7 0.885 0.737 0.852 0.803 328 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 table 3 classification accuracies of reduced feature subsets (continued) feature selection method no. of features accuracy lr dt rf svm anova 5 0.885 0.786 0.819 0.688 6 0.868 0.803 0.803 0.688 7 0.885 0.836 0.836 0.852 fsa 5 0.836 0.786 0.843 0.852 6 0.836 0.836 0.836 0.819 7 0.819 0.704 0.770 0.786 bea 5 0.803 0.836 0.803 0.737 6 0.819 0.803 0.786 0.819 7 0.818 0.789 0.871 0.814 mi 5 0.819 0.639 0.754 0.819 6 0.819 0.704 0.704 0.836 7 0.819 0.688 0.770 0.803 l2 5 0.721 0.819 0.836 0.737 6 0.721 0.789 0.836 0.836 7 0.721 0.704 0.737 0.786 pso 5 0.819 0.688 0.770 0.786 6 0.819 0.704 0.770 0.786 7 0.868 0.786 0.852 0.885 aco 5 0.803 0.819 0.868 0.803 6 0.868 0.704 0.868 0.885 7 0.901 0.819 0.852 0.868 hc 5 0.868 0.836 0.836 0.803 6 0.836 0.786 0.852 0.803 7 0.819 0.803 0.819 0.836 table 4 evinces the performance of the proposed approach, compared to other currently used feature selection strategies for lr, dt, rf, and svm classifiers on the cleveland dataset irrespective of the number of features. the proposed acohc method exhibits a significant improvement in the performance of classifiers, in contrast to alternative methods of feature selection. table 4 performance of various feature selection algorithms feature selection method accuracy lr dt rf svm cs 0.885 0.770 0.852 0.819 anova 0.885 0.836 0.836 0.852 fsa 0.836 0.836 0.843 0.852 bea 0.818 0.836 0.871 0.819 mi 0.819 0.704 0.770 0.836 l2 0.721 0.819 0.836 0.836 pso 0.868 0.786 0.852 0.885 aco 0.901 0.819 0.868 0.885 hc 0.868 0.836 0.852 0.836 acohc 0.902 0.869 0.836 0.951 the performance indicators for the manifold classifiers, which are assessed using the proposed approach, are displayed in table 5. the table provides a detailed comparison of metrics such as accuracy, precision, recall, f1-score, specificity, and area under the receiver operating characteristic (auroc) highlighting the effectiveness of each classifier. this comparison aids in selecting the most suitable classifier for accurate prediction. table 5 performance summary of acohc classifiers lr dt rf svm accuracy 0.902 0.869 0.836 0.951 precision 0.897 0.862 0.862 0.931 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 329 table 5 performance summary of acohc (continued) classifiers lr dt rf svm recall 0.897 0.862 0.806 0.964 f1-score 0.897 0.862 0.833 0.947 specificity 0.906 0.875 0.867 0.939 auroc 0.913 0.837 0.923 0.957 fig. 3 presents the accuracies of heart disease prediction using multifarious feature optimization techniques to identify the optimal feature set. the results highlight differences in performance across methods, showing the impact of feature selection on model accuracy. this comparison aids in pinpointing the most effective technique for enhancing predictive outcomes in heart disease diagnosis. fig. 3 comparison of feature selection methods figs. 4-7 presents the auroc curve scores for the classifiers evaluated on the cleveland dataset. given the provision of a single scalar value for evaluating the performance of the classification model across all threshold levels, auroc is perceived to be advantageous. the scores indicate the ability of the model to dichotomize the patients according to the suffering of a certain disease. the auroc scores demonstrate that the svm has gained the highest performance, closely followed by rf, lr, and dt classifiers. all classifiers exhibit auroc scores above 0.80, indicating robust performance. fig. 4 auroc analysis for svm fig. 5 auroc analysis for rf 330 advances in technology innovation, vol. 9, no. 4, 2024, pp. 319-331 fig. 6 auroc analysis for lr fig. 7 auroc analysis for dt 5. conclusions this paper aims to investigate the rationale for the prediction accuracy of heart disease affected by the feature selection techniques. technically, this study is conducted against a collection of different features that were extracted from widely used cleveland heart disease datasets that are available at the uci using a range of feature selection approaches. experiments have been conducted both including and excluding feature selection to determine the influence of feature selection. chi-square, anova, fsa, bea, mi, l2, pso, aco, and hc are utilized as algorithms for feature selection. four techniques for classification are analyzed: svm, rf, dt, and lr. the best result, using the dt classifier, yields 55.7% model accuracy without feature selection. subsequently, feature selection is used to experiment. the highest accuracy value without feature selection is 55.7%; with the use of acohc and svm classifier, this value is raised to 95.1%. the findings from the experiment suggest that feature selection algorithms could identify the disease accurately with less number of features. the additional key points are: (1) the model achieves accuracies of 90.1%, 88.5%, and 83.6%, for the lr, dt, and rf classifiers respectively. (2) the acohc technique attained a precision of 93.1%, specificity of 93.9%, f-score of 94.7%, and auroc score of 95.7% using an svm classifier. a hybrid approach combines several feature selection strategies, ultimately enabling the extraction of the best feature subsets for model building. future work can focus on using real-time medical records from different regions that may help to improve the accuracy of heart disease prediction algorithms. a limitation of this work is that if the data is not acquired properly or contains a high number of missing values, it may impact the quality of the features and, consequently, the performance of the system. conflicts of interest the authors declare no conflict of interest. references [1] v. p. kavitha, v. janarthanan, t. annamalai, and m. arumugam, “enhancing healthcare in the digital era: a secure e-health system for heart disease prediction and cloud security,” expert systems with applications, vol. 255, part a, article no. 124479, december 2024. 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[24] d. tian and z. shi, “mpso: modified particle swarm optimization and its applications,” swarm and evolutionary computation, vol. 41, pp. 49-68, august 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v8n1(2023)-aiti#10034(73-80).docx advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 calculation of temperature-dependent thermal expansion coefficient of metal crystals based on anharmonic correlated debye model tong sy tien*, nguyen thi minh thuy, vu thi kim lien, nguyen thi ngoc anh, do ngọc bich, le quang thanh department of basic sciences, university of fire prevention and fighting, hanoi, vietnam received 09 may 2022; received in revised form 07 august 2022; accepted 17 august 2022 doi: https://doi.org/10.46604/aiti.2023.10034 abstract this study aims to calculate the anharmonic thermal expansion (te) coefficient of metal crystals in the temperature dependence. the calculation model is derived from the anharmonic correlated debye (acd) model that is developed using the many-body perturbation approach and correlated debye model based on the anharmonic effective potential. this potential has taken into account the influence on the absorbing and backscattering atoms of all their nearest neighbors in the crystal lattice. the numerical results for the crystalline zinc (zn) and crystalline copper (cu) are in agreement with those obtained by the other theoretical model and experiments at several temperatures. the analytical results show that the acd model is useful and efficient in analyzing the te of coefficient of metal crystals. keywords: thermal expansion coefficient, metal crystals, anharmonic correlated debye model 1. introduction in recent years, the anharmonic thermal expansion (te) coefficient has been widely used to determine many dynamic properties of materials [1]. like the compressibility and heat capacity, the te coefficient is important because it is one of the independent thermodynamic properties which can be measured experimentally with high precision [2]. accurate information on the te coefficient in the temperature dependence is required for the metallurgical industry as well as in engineering physics [3]. the te coefficient is often used to determine the matching between different metal components in the alloy [4]. a large difference in the te coefficients between the metal components can lead to adverse deformation in the alloy when the temperature changes [5]. moreover, the position of atoms and their interatomic distance always changes and are not stationary under the influence of thermal vibrations [6]. this influence causes thermal disorder and anharmonic effects in the crystal lattice, so the te coefficient is sensitive to the temperature change and can be varied with increasing temperature [7]. in materials science, high precision measurements of lattice parameters using the x-ray method based on the development of the theory of the crystal structures have become increasingly important. moreover, the accurate determination of lattice parameters enables one to investigate the te coefficient of various crystalline substances, even if the weight of the substances available for measurement is only a few milligrams [2, 4]. besides, the extended x-ray absorption fine structure (exafs) technique is a widely employed probe of the dynamical behaviors and structural parameters in disordered systems [8]. it is because exafs spectroscopy can contain information on local structures around x-ray absorbing atoms and gives interatomic distances and coordination numbers in crystal lattices [9]. * corresponding author. e-mail address: tongsytien@yahoo.com tel.: +849-1-2439564; fax: +849-8-1439564 advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 74 this resulted in the exafs technique being developed and expanded greatly based on the rapid development of synchrotron radiation facilities worldwide [10]. in reality, thermal disorders can disturb the exafs oscillation [6, 9], so the te coefficient is also sensitive to exafs oscillation under the influence of temperature. nowadays, metals and advances in manufacturing processes have brought us the industrial revolutions, so it becomes irreplaceable materials in the growth of human civilization. they are used extensively in manufacturing machines for industries, agriculture or farming, and automobiles, including road vehicles, railways, airplanes, rockets, etc. [2-4]. the te of coefficient of metal crystals has also been investigated using the anharmonic correlated einstein (ace) model [11-12] and experiments [11-13]. still, this model only uses a unique correlated einstein frequency to describe the atomic vibrations, so it cannot mimic the acoustic phonon branches presenting in lattice crystals. recently, an anharmonic correlated debye (acd) model [14] can treat even the acoustic phonon branches presenting in lattice crystals because it describes the atomic vibrations using the frequencies varying from 0 to the correlated debye frequency. it has also been efficiently used to investigate the anharmonic thermodynamic properties of many materials [9, 15-16]. still, it has not yet been used to analyze the anharmonic te coefficient of metal crystals. therefore, the calculation and analysis of the temperature-dependent te coefficient of metal crystals based on extending the acd model will be a necessary addition to experimental data analysis in the advanced material technique. 2. calculation of the anharmonic te coefficient usually, the te coefficient ����� characterizes the net thermal expansion (nte) caused by thermal vibrations in the crystal lattice [17], as shown in fig. 1. fig. 1 thermal expansion of metal with a change in temperature the te coefficient can be determined [11-12] by: ( ) ( ) ( ) ( )1 0 0 0 t dr t d t t t r dt r dt σ α ∆ = = ∆ ℓ ≃ ℓ (1) where � is the absolute temperature, ���� is the instantaneous distance between the backscattering and absorbing atoms, �� is the equilibrium distance between the backscattering and absorbing atoms, and �� ���� is the first exafs cumulant and can be expressed in terms of the power moments of the radial pair distribution (rd) function [18-19]: ( ) ( ) ( )1 0t r t rσ = − (2) normally, the morse potential can validly determine the pair interaction (pi) potential of the crystals [20-21]. if this potential is expanded up to the third-order around its minimum position, it can be written as ( ) ( )2 2 2 3 3 0( ) e 2 ,x x x d e d d x d x x r t r α αϕ α α− −= − ≅ − + − = − (3) where � is the dissociation energy, � is the width of the potential, and x is the deviation distance between the backscattering and absorbing atoms. to determine the thermodynamic parameters of a system, it is necessary to specify its anharmonic effective (ae) potential and force constants [8, 22]. one considers a monatomic system with an ae potential (ignoring the constant contribution) is extended up to the third-order: advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 75 2 3 3 1 ( ) 2eff effv x k x k x= − (4) where � �� is the effective force constant, �� is the local force constant giving asymmetry of potential due to the inclusion of anharmonicity, and these force constants are considered in the temperature independence. in the relative vibrations of absorbing eq. (1) and backscattering eq. (2) atoms, including the effect of correlation and taking into account only the nearest-neighbor interactions, the ae potential [23-24] is given using the pi potential, i.e. � �( )12 ij 1,2 1,2 ( ) ,eff i i i j i v v x v xr r m µ ε ε = ≠ = + =  (5) where �� ( 1i = , 2) is the mass of the ith atom and equals m in the monatomic crystals, respectively, � = � ��/�� + ��� is the reduced mass of the absorber and backscatter, ��� is a unit vector, the sum i is the over absorbers ( 1i = ) and backscatters ( 2i = ), the sum j is over the nearest neighbors, and. the acd model is derived from the dualism of an elementary particle in quantum theory and is perfected based on the correlated debye model using the ae potential and many-body perturbation approach [9, 14]. it is often used effectively in treating monatomic systems with less complex phonon density of states and multiple acoustic phonons [15-16]. in this model, the atomic vibrations can be quantized and treated as a system consisting of many phonons, in which each atomic vibration corresponds to a wave that has a frequency ���� and is described via the dispersion relation ( ) 0sin , 2 , 2d d kqa q q m a π ω ω ω   = = ≤    (6) where � is the phonon wavenumber in the first brillouin (fb) zone, a is the lattice constant, and �� is the correlated debye frequency and characterizes the atomic thermal vibrations. the general expression of the first exafs cumulant in the acd model was calculated in the temperature dependence by hung et al. [14]. still, these obtained expressions are not optimized yet because they still depend on the lattice constant a. in this investigation, the previous acd model has been extended to calculate the temperature-dependent te coefficient of metal crystals. after using the general expression of the first exafs cumulant and converting from variable � to variable � in the formula p=��/2, the temperature-dependent first cumulant of metal crystals are obtained as ( ) ( ) ( ) ( ) ( ) ( ) ( ) /2 /2 1 3 3 2 2 0 0 1 exp3 3 coth 2 1 expeff eff b b b p k t p k t p k k t p dp p dp k k kt π π σ ω ω ω ω ωπ π + −   − −  =  =       ℏ ℏℏ ℏ ℏ (7) substituting this cumulant into eq. (1) to calculate the temperature-dependent te coefficient of metal crystals, it yields ( ) ( ) ( ) /2 3 2 0 0 3 cot 2h eff t b t p k k d p dp r t k dt π ω π α ω          =    ℏ ℏ (8) using an approximation exp"−ℏ����/�%�& ≈ 0, the te coefficient of metal crystals in the low-temperature (lt) limit �� → 0� can be calculated from eq. (8), i.e. ( ) 2 3 2 0 2 b d eff t k k t r k t π ω α ℏ ≃ (9) using an approximation exp"−ℏ����/�%�& ≈ 1 − ℏ����/�%� , the te coefficient of metal crystals in the high-temperature (ht) limit �t → ∞� can be calculated from eq. (8), that is advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 76 ( ) 3 2 0 3 b t eff k r k t k α ≃ (10) thus, an extended acd model has been perfected to efficiently calculate the temperature dependence of the te coefficient of metal crystals. the obtained expressions using this model can satisfy all their fundamental properties in the temperature dependence. these expressions have also been optimized to not depend on the lattice constant a as in the previous acd model [14-15]. 3. numerical result and discussion in this section, the obtained expressions using the acd model in sec. 2 are applied to the numerical calculations of crystalline zinc (zn) and crystalline copper (cu) that have the hexagonal close-packed (hcp) and face-centered cubic (fcc) structures, respectively. herein, the local force constants � �� and �� , the correlated einstein frequency �� , and the temperature-dependent first exafs cumulant �� ���� and te coefficient ����� are the quantities to be performed in numerical calculations. these obtained numerical results are compared with those obtained using the ace [11-12, 22-23, 25] and experiments [11-13, 22, 26-28]. from these obtained comparisons, the development and effectiveness of the acd model are analyzed and discussed in investigating the temperature-dependent thermal expansion coefficient of metal crystals. the following is the presentation of these numerical results: the ae potential of zn and cu can be calculated using eq. (5) based on the morse potential in eq. (3) and the crystal structure properties of these metals. after ignoring the overall constant in the obtained result and comparing it with eq. (4), the local force constants � �� and �� are deduced in the expressions of the morse potential parameters d and �, while the correlated debye frequency �� is calculated using eq. (6) via the effective force constant � �� . the values of the local force constants � �� and �� and the correlated debye frequency �� of zn and cu are given in table 1. herein, the obtained results of the correlated debye frequency �� using the ace [22, 25] are inferred from the correlated einstein frequency �and related expression �� = √2�[9, 23-24, 28]. meanwhile, the obtained results using the experimental exafs data are derived from the measured morse potential parameters and eq. (6). it can be seen that the obtained results using the acd model fit with those obtained using the ace [22-23, 25] and experimental data [22, 27], especially for the correlated debye frequency �� and effective force constant � �� . table 1 the thermodynamic parameters ��, ��, and �� of zn and cu obtained using the acd and ace models and experiments metal method mass d (ev) α (å-1) r0 (å) � �� (evå-2) �� (evå-3) �� (×1013hz) zn acd model 65.377b 0.1698c 1.7054c 2.7931c 2.3887a 1.0528a 3.7552a ace model 65.377b 0.1698c 1.7054c 2.7931c 2.4692d 1.0528d 3.8066d experiment 0.1685d 1.7000d 2.7650d 2.4348d 1.0348d 3.7801d cu acd model 63,546b 0.3429c 1.3588c 2.8860c 3.1655a 1.0753a 4.3848a ace model 63,546b 0.3429c 1.3588c 2.8860c 3.1655e 1.0753e 4.3848e experiment 0.3300f 1.3800f 3.2000f 1.3000f 4.4086f athis work, breference [29], creference [21], dreference [22], ereference [23, 25], freference [27] the dispersion relation ���� of zn and cu in the fb zone is calculated by eq. (6) and is represented in fig. 1. it can be shown that the obtained results using the acd are a symmetric function of a linear chain of q, and its maximum value is �� at the bounds of the fb zone with � = ±0/2, as seen in fig. 2. these characteristics of the dispersion relation ���� are completely consistent with similar obtained results of other crystals in previous works, such as the crystalline iron (fe) [15], crystalline molybdenum (mo) [15], and crystalline wolfram (w) [15], and crystalline germanium (ge) [16]. advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 77 the temperature dependence of the first exafs cumulant �� ���� of (a) zn and (b) cu in a range from 0 to 700 k is represented in fig. 3, in which the obtained results using the acd model are calculated by eq. (7). herein, the values of cu are smaller than those of zn, which is because the local force constants �� of these metals are roughly equivalent, but cu has the effective force constant � �� larger than those of zn, and this cumulant decreases rapidly as the effective force constant increases, as seen in table 1. it can be seen that the obtained results using the acd model are in good agreement with those obtained using the ace [11-12] model and experiments [11-12, 26, 28]. also, in comparison with the experimental values, the obtained results using acd are better in agreement with those obtained using the ace model, especially in the lt region. for example, the obtained results of zn using the acd model, ace model, and an experiment at � ≃ 77 k are �� � ≃ 5.29×102�å, �( ) ≃5.34×102�å [11], and �( ) ≃ 5.26×102�å [28], respectively. meanwhile, the obtained results of cu using the acd model, ace model, and an experiment at � ≃ 80 k are �( ) ≃ 3.26×102�å, �( ) ≃ 3.34×102�å [12], and �( ) ≃ 3.00×102�å [26], respectively. moreover, both the acd and ace [11-12] models show the contribution of quantum effects in the lt region, but the obtained results using the ace model [11-12] are slightly greater than those obtained using the acd model. the minor difference lies in that the ace model [11-12] uses only one effective frequency to describe the atomic thermal vibrations, as depicted in fig. 3. (a) the obtained result of zn (b) the obtained result of cu fig. 2 the dispersion relation of metals obtained from the acd model (a) the obtained results of zn (b) the obtained results of cu fig. 3 the temperature-dependent first exafs cumulant of metals obtained using the acd and ace models and experiments the temperature dependence of the te coefficient ��(�) of (a) zn and (b) cu in a range from 0 to 700 k is represented in fig. 4, in which the obtained result using the acd model is calculated by eq. (8). herein, the values of zn are bigger than those of cu because the temperature-dependent first exafs cumulant of cu changes more slowly than those of zn, as seen in fig. 3. it can be seen that the obtained results using the acd model agree with those obtained using the ace [11-12] model and advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 78 experiments [11-13]. for example, the obtained results of zn using the acd model, ace model, and an experiment at � ≃ 300 k are �� ≃ 1.57×1023k2 , �� ≃ 1.56×1023k2 [11], and �� ≃ 1.58×1023k2 [11], respectively. meanwhile, the obtained results of cu using the acd model, ace model, and an experiment at � ≃ 100 k are �� ≃ 0.76×1023k2 , �� ≃ 0.71×1023k2 [12], and �� ≃ 0.80×1023k2 [13], respectively. the quantum effects in the acd model [14] can be shown by the obtained results in the lt limit low temperatures. as shown in the temperature range from above 0 k and below about 10 k, the obtained results of the first exafs cumulant are a region of an almost unchanged value, while the obtained results of the te coefficient correspond to a region of values greater than zero. moreover, the obtained results using the acd model are not destroyed quickly in the lt limit as those obtained using the ace model [11-12], which fits perfectly with eq. (9) and shows that the acd model can fully describe the quantum effects. also, the obtained results using the acd model increase with the rise of temperature t and approach the constants in the ht limit, which fits perfectly with eq. (10) and shows that the acd model can efficiently describe the anharmonic effects, as seen in fig. 4. these results are consistent with those obtained by using the quantum methods [11-12, 23]. (a) the obtained results of zn (b) the obtained results of cu fig. 4 the temperature-dependent te coefficient of metals obtained using the acd and ace models and experiments 4. conclusions in this investigation, the expansion and development of an efficient model have been performed to calculate and analyze the temperature-dependent te coefficient of metal crystals. the calculated results of the anharmonic te coefficient using the acd model satisfied all of their fundamental properties. the te coefficient increases with increasing temperature t, which means that the crystal lattice expands strongly at higher temperatures. these results can also describe the influence of anharmonic effects at high temperatures and the influence of the quantum effects at low temperatures on the te coefficient. the good agreement of the obtained numerical results for zn and cu with those obtained using the ace model and experiments at various temperatures shows the effectiveness of the present model in investigating the temperature-dependent te coefficient of metal crystals. this model can be applied to calculate and analyze the anharmonic te coefficient of other crystals at a temperature ranging from absolute zero degree to their melting points. acknowledgments this work is supported by the university of fire prevention and fighting, 243 khuat duy tien, thanh xuan, hanoi, vietnam. conflicts of interest the authors declare no conflict of interest. advances in technology innovation, vol. 8, no. 1, 2023, pp. 73-80 79 references [1] h. liu, w. sun, z. zhang, l. lovings, and c. lind, “thermal expansion behavior in the a2m3o12 family of materials,” solids, vol. 2, no. 1, pp. 87-107, february 2021. 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[29] j. meija, t. b. coplen, m. berglund, w. a. brand, p. d. bièvre, m. gröning, et al, “atomic weights of the elements 2013 (iupac technical report),” pure and applied chemistry, vol. 88, no. 3, pp. 265-291, february 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v8n4(2023)-aiti#11743(254-266).docx advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 english language proofreader: chih-wei chang a novel paradigm for sentiment analysis on covid-19 tweets with transfer learning based fine-tuned bert amit pimpalkar1,2,*, jeberson retna raj1 1school of computing, sathyabama institute of science and technology, chennai, india 2department of computer science and engineering (aiml), shri ramdeobaba college of engineering and management, nagpur, india received 13 march 2023; received in revised form 04 july 2023; accepted 06 july 2023 doi: https://doi.org/10.46604/aiti.2023.11743 abstract the rapid escalation in global covid-19 cases has engendered profound emotions of fear, agitation, and despondency within society. it is evident from covid-19-related tweets that spark panic and elevate stress among individuals. analyzing the sentiment expressed in online comments aids various stakeholders in monitoring the situation. this research aims to improve the performance of pre-trained bidirectional encoder representations from transformers (bert) by employing transfer learning (tl) and fine hyper-parameter tuning (ft). the model is applied to three distinct covid-19-related datasets, and each of the datasets belongs to a different class. the evaluation of the model’s performance involves six different machine learning (ml) classification models. this model is trained and evaluated using metrics such as accuracy, precision, recall, and f1-score. heat maps are generated for each model to visualize the results. the performance of the model demonstrates accuracies of 83%, 97%, and 98% for class-5, class-3, and binary classifications, respectively. keywords: covid-19, pre-trained, sentiment analysis, bert, transfer learning 1. introduction the covid-19 pandemic has become synonymous with the year 2020, and india stands among the countries most severely affected by the outbreak. in 2019, scientists identified the severe acute respiratory syndrome-associated coronavirus (sars-cov) as the cause of the pandemic, and it was later renamed covid-19. the pandemic has led to numerous deaths and has caused both health and economic crises across the world. the resurgence of covid-19, particularly with the omicron variant, has caused widespread fear, agitation, and despondency [1]. due to constant lockdowns and social isolation, people have increasingly turned to online activities, and social media platforms have become the most effective medium for communication. twitter is a social networking site where people share news and relevant information. meanwhile, it’s also one of the most widely used microblogging platforms that provides invaluable data sets for public opinion surveys. as a result, the covid-19 pandemic has catalyzed the increasing use of twitter for discussions on various topics [2]. however, spreading false and misleading information on social media has become a significant concern. therefore, it is crucial to verify the accuracy of information shared on social media and prevent the spread of false news by assessing people’s sentiments. to resolve the problem, researchers can use the information collected from analyzed tweets by twitter for academic and research purposes. consequently, nations must implement measures to protect themselves by revealing the truth and data about the pandemic. according to yella [3], the later stages of covid-19 now have a lower fatality rate but a more significant * corresponding author. e-mail address: amit.pimpalkar@gmail.com advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 255 contamination and spread rate than previously transmitted sars, omicron variant, and mers covid-19. around 2.9 million new cases were recorded worldwide in the first week of january 2023, an increase of 10% week-on-week compared to the prior weeks. the same week witnessed almost 11,000 recorded fatalities, representing a 22% rise from the preceding week. 659 million confirmed illnesses and 6.6 million fatalities have been recorded globally as of 8 january 2023 [4]. when millions of people throughout the globe succumb to covid-19, a new pandemic—the black fungus—emerges to threaten everyone’s life—especially those who are still recuperating from covid-19. this study presents a framework for sourcing data to train the pre-trained model for sentiment analysis (sa). against this background, research exploration work attempts to address the accompanying research questions (rq) related to covid-19. rq-1. what are the well-known catchphrases that appear in indian tweets in english? rq-2. how did these tweets influence general well-being frameworks? rq-3. how do ml calculations serve to investigate individuals’ sentiments? rq-4. how far can the deep learning (dl) 12-layer bidirectional encoder representations from transformers (bert) model outperform other conventional ml models? rq-5. how is the performance comparison of the bert model for covid-19 sa on the bi-class and multi-class datasets (class-3 and class-5)? the majority contributions of this research are as follows: (1) this work adopts an integrated approach to understanding sa for covid-19. (2) a transfer learning (tl)-based pre-trained bert model is employed to address sa challenges in english. (3) the pre-trained bert model is adapted to perform sentiment classification on three different datasets containing bi-class or multi-class data. (4) various encoding techniques, including one-hot and tf-idf, along with tl variants, are explored to address scenarios. (5) all fine-tuned network parameters are incorporated to efficiently capture gaps of varying lengths and weights in forming feature maps. (6) a range of standard ml methods, such as multinomial naive bayes (mnb), random forest (rf), logistic regression (lr), extreme gradient boosting (xgb), stochastic gradient descent (sgd), and support vector classifier (svc), are employed alongside the pre-trained bert for covid-19. (7) this research conducts a comparative analysis of seven models to showcase the transformer design’s superiority over prior state-of-the-art methods. with appropriate fine-tuning, the transformer design emerges as the new state-of-the-art model with superior performance. the inspiration for this work, a brief demonstration of sa, rq, and significant contributions of the research are provided in section 1. the rest of the paper is organized as follows. section 2 discusses related works done by the researchers, followed by the limitations. section 3 gives a foundation for the work chosen, explaining the essentials of the fundamentals of bert and tl on a deeper level. the study also highlights the proposed system’s methodology, architecture, dataset, feature selection, hyper-parameter tuning, and evaluation process. the trial results depicted in section 4 compare the outcomes of the innovative classifiers with those obtained using the proposed strategy for sa. at last, section 5 concludes the paper and suggests directions for future research. 2. related work recently, related researchers reported on sa of covid-19 twitter data; they have developed many text-mining techniques to investigate the various elements of covid-19, utilizing textual data from online social media sites. in this advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 256 context, tl is becoming extremely important in the research field. developments in dl have led to significant improvements in modeling, machine translation, and other natural language processing (nlp) tasks, including text categorization, language translation, and others. this is especially true for neural network designs like recurrent neural networks (rnn), long shortterm memory (lstm), and convolutional neural networks (cnn). for real-time visualization and granular event classification in public opinion research, zhuang et al. [5] introduced the latent dirichlet allocation-autoregressive moving average model deep neural network (lda-arma dnn). lda was used to determine what the remarks were about. to perform multi-faceted sa and variation prediction, they used the arma on massive amounts of textual data connected to covid-19. malla and alphonse [6] proposed a method majority voting-based ensemble deep learning (mvedl) model for locating critical tweets during the covid-19 outbreak using the covid-19twitter bert, bertweet, and roberta dl-based models. the study attempted to establish the sentiment of people in eight nations [7]. they built a unification model for sa with five different deep-learning classifiers and then consolidated them to refine the result via a meta-learning method. researchers have focused on mucormycosis related to covid-19, and a time series analysis of tweets has shown that negative tweets are becoming less common with time [8]. karthikeyan et al. [9] propose the use of a modified nn architecture for an ai system, incorporating a hybrid learning-based network classifier that relies on both cnn and support vector machine (svm) [9]. yan et al. [10] proposed an attention parallel dual-channel deep learning hybrid model (addhm) with bert and a dual-channel architecture built of cnn and bidirectional long short-term memory (bilstm). furthermore, in each channel, an attentional mechanism was incorporated to separate the words that influence the most emotional inclination and strengthen the quality of the model for sentiment classification. researchers suganya and kalpana [11] proposed a covid-19 detection classification utilizing a pre-trained model mask regional-convolutional neural network (r-cnn) to improve performance on both binary and multi-class classification. the authors utilized a shot learning strategy using a resnet-50 baseline classifier and softmax as an activation function. table 1 limitations of the existing research referenced research limitations of the research [7] the data’s country of origin did not influence selected keywords for gathering and filtering tweets. at the outset of march 2020, collected news items and obtained data were found from a particular source. [12] the time lasted only 23 days, from 3 december 2021 to 26 december 2021. [13] system performance was minimal on the smaller datasets. [14] the model was constrained using sequential dl models with limited performance. [15-16] the feature selection and hyper-parameter tuning operations were not carried out. [17] the authors did not explore various perspectives, including geographical ones. [18] insufficient tweets from a particular nation were evaluated. [19] the research focused on sentiments primarily related to medical services only. [20] since most weibo users are young individuals, the outcomes of the analysis may be skewed. the study only highlights the emergence of negative attitudes among young individuals following the pandemic. [21] the cross-validation mechanism was not utilized. [22] the sentiments presented in these tweets are solely based on the word “fear”, and they were expressed by citizens of the united states. the tweets in question are relatively short in length. there are many unnoticed problems and probable pitfalls in deciphering the work that has been circulating lately. previous efforts focused on information analysis of tweets related to covid-19 had a small corpus of tweets. sa using twitter has several practical implications. the first issue is the data quality, as twitter data is often noisy, with abbreviations, slang, and misspellings, which can affect the accuracy. the second issue is the limitation of twitter’s api, which only provides access to a small portion of tweets, limiting the sample’s representativeness. another issue is the potential bias in the training data, advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 257 as the training data used to develop sa models may not represent the population or contain biases that affect the model’s accuracy. finally, there is the issue of ethical implications, which means using sa on social media raises privacy concerns involving analyzing personal data without consent. there is also the potential for misuse of sa, such as using sa to identify and target vulnerable individuals for political or commercial purposes. table 1 below shows the limitations of existing research. considering the shortcomings of current research, the proposed solution advocates for a pre-trained model, bert, which is based on the transformer architecture and includes both tl and optimization of hyper-parameters in the study. the study extracted the datasets from freely available repositories and explored them as in section 3.1. furthermore, traditional ml and dl approaches have been used in many covid-19-related tweets with bi-class and multi-class data. nonetheless, this proposed technique beats various issues and elasticities with near-perfect accuracy. this research offers valuable insights into the potential of transformer-based models to enhance performance and advance the field of nlp. 3. methodology as shown in fig. 1, the starting point of the suggested architecture is the cleaning and transformation of the three datasets utilized in this study. both unlabeled and labeled datasets undergo a data refinement process, including steps like html parsing, pos tagging, stop word removal, tokenization, word sense disambiguation, and non-alphanumeric character removal. then, the labeled corpus was combined with the unlabeled corpus for training, yielding a more robust labeled corpus. the research conducted two separate analyses, the first sorting tweets about covid-19 in the labeled corpus into positive and negative categories and the second one using an improved labeled corpus. training and testing sets were created from the tagged corpora; tlft-bert-based dl architecture was trained and verified using these datasets before being applied to sa and prediction from covid-19 tweets and then calculated the suggested model’s accuracy, precision, recall, and f1 score. fig. 1 representative mechanism of the proposed model advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 258 3.1. dataset the experimental investigation employed three real-world datasets from the kaggle repository to evaluate the classifier’s classification performance. tables 2, 3, and 4 summarize the datasets used in this investigation. an 80:20 train: test split was employed on the dataset to minimize overfitting and accurately assess the model. the testing technique provides data to finetune the model’s hyper-parameters and verify model performance on 20% of the data after training it on 80% of the dataset. the class-5 dataset has 41,157 distinct emotional tweets from twitter users gathered around one month (march 2020 to april 2020) when there were uttermost cases of covid-19. the dataset was categorized into five classes for the task, as shown in table 2. table 2 the class-5 dataset statistics class-5 actual dataset after processing 20% of processed data 80% of processed data extremely negative (0) 5,481 5,481 1,096 4,385 negative (1) 9,917 9,890 1,978 7,912 neutral (2) 7,713 7,565 1,513 6,052 positive (3) 11,422 11,380 2,276 9,104 extremely positive (4) 6,624 6,620 1,324 5,296 total samples 41,157 40,936 8,187 32,749 table 3 the class-3 dataset statistics class-3 actual dataset after processing 20% of processed data 80% of processed data negative (0) 16,335 16,200 3,240 12,960 neutral (1) 67,835 65,035 13,007 52,028 positive (2) 6,280 6,175 1,235 4,940 total samples 90,450 87,410 17,482 69,928 table 4 the class-2 dataset statistics class-2 actual dataset after processing 20% of processed data 80% of processed data negative (0) 40,322 8,986 1,798 7,188 positive (1) 139,537 48,176 9,635 38,541 total samples 179,859 57,162 11,433 45,729 the class-3 dataset has 90,450 distinct emotional tweets from 70,000 twitter users gathered within two months (february 2020 to march 2020) when there was a peak of covid-19 [23]. for the classification job, three different classes, 6,175 positive sentiments, 16,200 negative sentiments, and 65,035 neutral sentiments, after pre-processing the dataset. the class-2 dataset has 179,859 distinct emotional tweets from twitter users gathered within three months (february 2020 to april 2020). 3.2. data pre-processing the information obtained through social media networks has frequently been raw, noisy, varied, and in a primitive state that makes study impossible; so, it is cleaned first before the research. there are several steps involved in pre-processing. removing urls from the text, all usernames, stop words, converting all letters to lowercase, and eliminating incorrect characteristics are all data pre-processing strategies. several libraries were utilized in python for text pre-processing tasks, including the natural language toolkit (nltk), spacy, a regular expression library, and other general libraries. 3.3. bert google introduced a novel language representation method known as bert [24]. bert enables the pre-training of deep bidirectional representations from the unlabelled text in each layer, concurrently modifying the context to the left and right of a given text. bert includes tokens such as unknown [unk], separation [sep], classification [cls], and padding [pad], as advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 259 illustrated in fig. 2 [24]. the bert model was trained using the masked language model (mlm) and next sentence prediction (nsp) techniques. the deep bidirectional model of the mlm is prepared by randomly selecting and masking input tokens and then making predictions for the masked tokens. the nsp method helps to set up the connection between sentences in the model. for each pair of phrases p1 and p2, the nsp examine 50% of the pre-trained sample to determine their correlation. table 5 displays the characteristics of the bert base and the bert large. fig. 2 bert representation [24] table 5 bert model detail view model/dimensions number of layers (l) hidden layers size (h) self-attention heads (a) total parameters bert base 12 768 12 110m bert large 24 1024 16 340m 3.4. transfer learning in nlp today, the most powerful language models rely significantly on transformers, and they are often regarded as the best for all fundamental nlp and natural language understanding (nlu) tasks. since training neural networks from scratch with enormous datasets is computationally expensive and takes a long time, and access to high-end computing resources, such as clusters of cpus and gpus, is required. to avoid these challenges, the transfer function approach is presented as an easy technique. the idea behind the tl is that rather than starting from a blank and using random weights, it is possible to solve future problems with the help of the consequences gained from one training. the pre-trained models can be utilized directly or to extract characteristics other than those learned from the model during prior training. in the context of tl, typically, two stages are involved. firstly, a model is pre-trained on one dataset to serve as a feature extractor. subsequently, the pre-trained model is used to apply the acquired knowledge by fine-tuning it on another dataset. in this specific case, the bert model in its original form has been pre-trained on the combination of two massive collections, bookcorpus and english wikipedia, and it is used for solving a task for classifying covid-19 reviews. this approach leads to a reduction in training time and an improvement in neural network performance. 3.5. experimental hyper-parameters upon completing the training set, researchers reconfigured crucial hyper-parameters to obtain a refined model with comparable assessment metrics. ml algorithms may effectively train the data but fail to summarize inconspicuous data, which means overfitting. meanwhile, regularization, optimizer, learning rate, and batch standardization are generally employed to avoid overfitting. advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 260 the researchers trained a model with input layers on top of the embedding layer via a pre-trained bert base uncased. they conducted experiments to evaluate the model’s performance using different optimizers and learning rates while keeping other parameters, such as conv1d kernel size, number of filters, and batch size constant. the evaluation results were documented, and it was observed that the “adam” optimizer with a learning rate of 1e-5 and decay learning rate of 1e-7 had the most influence on the model’s performance. subsequently, the researchers selected the aforementioned hyper-parameters and fine-tuned the number of dense units and epoch size while keeping other parameters constant. the experimental results were thoroughly reviewed and implemented, leading to the establishment of model correlation hyper-boundaries. the model correlation hyper-boundaries are set as follows, as shown in table 6. table 6 hyper-parameter used in the research hyper-parameter values max review length 128 learning rate 1e-5 decay 1e-7 batch size 32 number of epochs 10 number of conv1d filters 64 conv1d kernel size 3 number of dense units 32 threshold 0.9 optimizer adam activation function softmax batch normalizations yes loss function binary cross entropy, categorical cross entropy output function sigmoid the experiments were conducted using python 3.8, with tensorflow 2.10 and keras 2.9 libraries on windows 10. to train state-of-the-art dl models, a kaggle kernel that provides nvidia p100 gpu, 73.1 gb of disk, 15.9 gb of gpu memory, 13 gb of ram, 1.32 ghz memory clock, with a reasonably high-end performance of 9.3 tflops. 4. result and discussion to strengthen the experimental hypothesis, traditional ml classifier techniques and experiments from past examinations explore different twitter datasets for sa as baseline classifiers including mnb, rf, lr, xgb, sgd, and svc, to establish bi-class and multi-class classification. regarding identifying the optimal model evaluation technique, the study investigated two feature vectors tf-idf and one-hot encoding. hyper-parameter tuning and tl techniques were employed to pre-trained bert encoding, utilizing the same feature vectors. the researchers obtained remarkable outcomes that exceeded those of conventional ml classifiers. they then further illuminated their findings by comparing them with the existing state-of-the-art bert model on the covid-19 dataset. the following section provides detailed statistics and a summary of the discoveries made by the research methodology. after evaluating the training model and measuring its performance using several metrics, as discussed earlier, the experiment tested the model on both bi-class and multi-class (class-3 and class-5) datasets. for assessment reasons, a confusion matrix and heat maps also facilitated data exploration and visualization of several characteristics. because covid19 datasets have an unequal class distribution, accuracy is the most logical performance statistic to employ here. the display of word clouds can yield a rapid overview of the dominant lexicon within a given text or may identify the top themes based on the relative frequency of individual words. this presentation method often renders the most frequent terms in larger font sizes while relegating less commonly used terms to a more minor, secondary position. fig. 3 shows the most prominent keyword used for class-5 and class-3 datasets. advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 261 (a) class-5 dataset (b) class-3 dataset fig. 3 word cloud for class-5 and class-3 datasets table 7 reveals a comparative analysis of accuracy which scores on many benchmarking ml algorithms and the proposed method of the bert model with tl. meanwhile, fig. 4 presents a fascinating contrast of models being assessed for various accuracy classifications. table 7 comparison of classes-2, 3, and 5 test results between baseline and proposed methods model/evaluation precision recall f1-score class-2 class-3 class-5 class-2 class-3 class-5 class-2 class-3 class-5 mnb 0.91 0.60 0.49 0.89 0.69 0.51 0.90 0.63 0.50 rf 0.96 0.75 0.54 0.98 0.80 0.60 0.97 0.77 0.55 lr 0.96 0.72 0.62 0.97 0.81 0.63 0.96 0.76 0.63 xgb 0.92 0.63 0.58 0.96 0.80 0.60 0.94 0.68 0.59 sgd 0.95 0.70 0.60 0.97 0.79 0.57 0.96 0.74 0.58 svc 0.95 0.67 0.59 0.98 0.83 0.64 0.97 0.72 0.60 proposed bert 0.98 0.97 0.83 0.98 0.97 0.84 0.98 0.97 0.83 fig. 4 the comparison of models under evaluations with different classes on accuracy fig. 5 depicts the suggested approach’s training and testing loss ratio, as determined by computing the 80% of trained samples and the randomly selected 20% testing inputs. according to the experimental results, the suggested model’s accuracy, f1-score, precision, and recall were high. even for the class-5 classification, the average improvement is around 30% using the proposed method. the suggested model’s inference time to assess a single sample was determined to be as low as 0.516 s/step, which is just around half a second. in the illuminating fig. 6, the predicted emotions were scrutinized using heat maps, which disclosed the instances of a particular emotion vis-à-vis other opinions in the identical sentiment group. these heat maps, manifesting the expressions of two sentiments, furnish insights about the attitudes associated with positive, negative, and neutral related classes. the advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 262 experimental results compared to previous work in text sentiment classification algorithms utilizing covid-19 datasets to verify the model’s effectiveness. the experimental results were validated using classical ml and the tlft-bert model. table 8 compares the empirical model’s accuracy to previous models, and the findings demonstrate the superiority of the proposed technique. this modeling approach can be utilized to improve covid-19 management in many situations. (a) loss and accuracy comparison for class-2 classifiers (b) loss and accuracy comparison for class-3 classifiers (c) loss and accuracy comparison for class-5 classifiers fig. 5 loss vs. accuracy for specific classes of datasets with bert classification advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 263 (a) confusion matrix for class-2 classifiers (b) confusion matrix for class-3 classifier (c) confusion matrix for class-5 classifier fig. 6 heat map of the proposed models under evaluation table 8 comparison of transfer learning-based approaches with state-of-the-art approaches in the literature author model dataset language best results malla and alphonse [6] majority voting-based ensemble english 91.75 basiri et al. [7] cnn, bigru english 85.80 naseem et al. [23] bert, albert, distilbert english 94.80 garcia and berton [25] multilingual universal sentence encoder english & portuguese 84.00 chintalapudi et al. [26] lstm, bert english 89.00 satu et al. [27] lstm, tclustvid english 97.80 kabakus [28] cnn, lstm turkish 97.89 jalil et al. [29] distilbert english 96.66 pimpalkar and raj [30] mbilstm english 93.55 proposed model transfer learning-based bert english 98.00 the following solutions can be drawn to respond to the rq relating to covid-19 indicated in section 1. rq-1: the well-known top twelve catchphrases in indian tweets were china, coronavirus, covid, death toll, food, outbreak, pandemic, people, price, sanitizer, store, and supermarket in alphabetically sorted order in english. rq. 2: covid-19 is comparable to other stress in that it causes cognitive, psychological, and emotional stress and it is sufficient to affect people’s well-being. covid-19 has influenced people’s lifestyles and contributed to stress, fear of infection, and concern for working individuals’ family lives. advances in technology innovation, vol. 8, no. 4, 2023, pp. 254-266 264 rq. 3: this research concludes that personal feelings or opinions can aid in matching and comprehending the sentiments of others by communicating feelings and providing feedback to others. sa may extract individuals’ views from the language used in social media postings, conversations, reviews, and more. ml algorithms can help to predict whether sentiment is positive or negative. rq-4 & rq-5: table 7 demonstrates that the 12-layer bert model outperforms other conventional ml models, and even for class-5 classification. the average improvement is over 30% utilizing the proposed method, and the proposed model’s inference time for a single sample was determined to be as low as 0.516s/step, or around half a second. 5. conclusion and future work the manuscript presents six ml and a dl technique to categorize covid-19-related tweets. the pre-trained bert base model is enhanced with tl as tlft-bert for class-2 and multi-class classification, specifically designed to tackle sa challenges in english, and uses three covid-19 twitter datasets to develop a robust sa model. (1) the model achieves high accuracy, with 98% for binary classification and 97% for class-3 classification. it is worth mentioning that the suggested model requires less training time. (2) by incorporating all fine-tuned network parameters, the tlft-bert model captures varying lengths and weights of features for effective feature map summation and understanding of complex linguistic patterns. (3) the research demonstrates the pivotal role of transformer models in sa when appropriately fine-tuned. the results highlight the superiority of the transformer-based approach, outperforming traditional ml methods. (4) these findings have broader implications for social scientists and governments seeking insights into global sentiments surrounding covid-19 tweets. the findings open new avenues for research and applications in sa and other nlp tasks, driving advancements in the field. (5) the research has a limitation since all the utilized datasets were scribbled in english. it would be intriguing to compare and differentiate native indian languages. a more extensive dataset may need training in the large bert architecture before being utilized. furthermore, researchers may use twitter streaming api to obtain real-time tweets to do sa and research various social networks. this work does not have the highlights to go to multilingual tweets, which could be considered a likely future work toward this path. it is still a research subject on how to embed a long document for enhancing classification performance, particularly when utilizing pre-trained contextualized word embedding like elmo, xlnet, roberta, and others. conflicts of interest the authors declare no conflict of interest. references [1] s. hosgurmath, v. petli, and v. k. jalihal, “an omicron variant tweeter sentiment analysis using nlp technique,” global transitions proceedings, vol. 3, no. 1, pp. 215-219, june 2022. 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[30] a. pimpalkar and j. r. raj, “mbilstmglove: embedding glove knowledge into the corpus using multi-layer bilstm deep learning model for social media sentiment analysis,” expert systems with applications, vol. 203, article no. 117581, october 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v8n3(2023)-aiti#11638(229-239).docx advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 english language proofreader: hsin-te hsieh design of an adiabatic calorimeter for cementitious mixtures by multi-objective optimization jhonatan a. becerra-duitama1,*, mauricio mauledoux2, óscar f. avilés2 1faculty of engineering and basic sciences, juan de castellanos university, tunja, colombia 2faculty of engineering, military university nueva granada, bogotá, colombia received 22 february 2023; received in revised form 17 june 2023; accepted 19 june 2023 doi: https://doi.org/10.46604/aiti.2023.11638 abstract this study aims to design an adiabatic calorimeter for cementitious mixtures using nsga-ii and the pareto optimal solution set. in this multi-objective optimization, the controller effort and heating time are selected as objective functions. likewise, the volume and the material to be heated were chosen as decision variables. the optimal solution was selected using nash bargaining methods. after implementing the optimal solution, the wilcoxon test was applied to statistically validate the developed work. the measurements performed were compared with other research and it was observed an improvement in the measurement of heat of hydration in cementitious mixtures. also, it was noted a decrease in the error in the temperature measurement. keywords: calorimeter, multi-objective problem, nsga-ii, optimization, pareto front 1. introduction nowadays, the measurements of the heat of hydration in cementitious mixtures are required. for this purpose, some equipment has been developed over the years to perform these tests. the most commonly used devices to determine the heat of hydration in cement mixtures are isothermal, semi-adiabatic, and adiabatic calorimeters. the latter is the least used because it is complicated and costly to manufacture, and its correct operation requires high sensitivity [1]. nevertheless, it is the most accurate method and provides the best measurements [2]. for this reason, methods based on concurrent engineering were applied, to develop a low-cost and easy-to-acquire calorimeter. concurrent design can be applied to develop any project in a cross-functional manner bearing in mind all stages of the product life cycle, from manufacturing to final disposal [3-5]. additionally, the concurrent design reduces production costs and time to market while increasing product quality. deshpande [6] mentions that various companies such as hewlett-packard, texas instruments, general motors, and motorola have successfully implemented concurrent engineering projects. among the benefits obtained, can be noted: a 55 % reduction in time to market, a 70 % increase in performance, and a 350 % increase in quality. in addition, kügler et al. [7] found a reduction in production time from 30 to 18 months in the development of a new minicomputer. wang and feng [8] indicated that implementing concurrent design procedures in companies reduced the number of design changes by 50 %, shortened product design time by 40 % to 70 %, and decreased waste generated by 75 %. previously this study, this type of concurrent design methodology had not been used to develop adiabatic calorimeters for cement mixtures, even considering the existing problems with these devices. the first problem is the control system that has a low response time, prasath and santhanam [9] described how the developed calorimeter took about one hour to reach the * corresponding author. e-mail address: jalexanderbecerra@jdc.edu.co advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 230 established reference. the second problem is a high working sensitivity and good insulating material are necessary for the heat transfer to be close to zero, allowing for higher accuracy in the measured data [10]. the third problem is the high production cost, making it a commercially nonviable and quite exclusive device [11]. for the above-mentioned reasons, methods based on concurrent design were implemented, to design a low-cost and easyto-obtain calorimeter. therefore, it was used a multi-objective optimization algorithm, which took into account all aspects of the system’s operation. to achieve the optimal design, the non-dominated sorting genetic algorithm ii (nsga-ii) was used to determine the parameters, dimensions, and materials required for the design of the adiabatic calorimeter [12]. likewise, it was implemented the calorimeter designed to perform heat of hydration measurements on cement paste samples. the novelty of this work is to display that the calorimeter was developed using concurrent design (optimization algorithms) unlike existing calorimeters implemented [13-16]. it is expected that this work will be one of the first to develop optimized calorimeters for cement mixtures [17]. 2. methods this section describes the development of the project, which was divided into three parts. the first part is the implementation of the optimization algorithm, for which the non-dominant sorting genetic algorithm (nsga-ii) was used. it is important to point out that, before implementing the nsga-ii algorithm, two evolutionary algorithms were tested. the evolutionary algorithms used were: the multiobjective differential evolution (mode) algorithm [18] and the differential evolution multiobjective optimization (demo) algorithm [19]. however, due to the nature of the calorimeter, the two algorithms could not be implemented, because the optimization problem had mixed variables, since one objective function had to choose the insulating material (something tangible), and the other objective function had to choose the physical dimensions of the calorimeter (numbers). also, implementing either of the two evolutionary algorithms would have required transforming the objective functions so that both were under the same conditions. this would have introduced imprecision and inaccuracy in the results obtained. for this reason, the nsga-ii algorithm was chosen, since it did allow working with mixed variables. the objective functions to take into account were the environment to be heated and the cumulative error of the measurement. by applying the algorithm and the two objective functions, the pareto front was determined, by which the solution to be implemented was chosen. hence, it was needed to apply bargaining methods. the methods used were the nash method and the egalitarian method. the second part of the project involved the design and implementation of the control system from simulation to its commissioning. finally, the culmination of the third part of the project was focused on the construction of the adiabatic calorimeter, bearing in mind the design parameters calculated in the previous parts. in addition, some tests were carried out with cement paste specimens, verifying the correct operation by checking with other similar studies. fig. 1 shows the schematic diagram where the design steps are represented. fig. 1 schematic diagram of the design process 2.1. algorithm optimization to obtain the best solution for the problem, it was adopted the non-dominant sorting genetic algorithm (nsga-ii) taken from kalami [20]. the parameters of the algorithm employed are shown in table 1. before implementing the optimization advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 231 algorithm, it was established the objective functions that governed the selection of the optimal calorimeter design. it is worth noting that the first function chosen depends directly on the thermal process. the parameters and materials included in this function were selected based on the physical nature of the process. moreover, this function was established to minimize the heating time of the environment to be controlled. table 1 nsga-ii parameters p1 p2 p3 p4 p5 100 100 0.7 0.4 0.02 where p1 is the maximum number of iterations, p2 is the population size, p3 is the crossover percentage, p4 is the mutation percentage, and p5 is the mutation rate. additionally, the second objective function was defined as the minimization of the cumulative error in the measurement. as can be seen, the behavior of the two functions is conflicting, since to achieve a short warm-up time, the controller must act quickly. therefore, finding the right balance between both functions was required to obtain the optimal design. the followings are the objective functions and the decision variables proposed for the development of the project. objective function 1 (f1) is intended to minimize water heating time. the heating time in terms of heat generated and power delivered to the system is expressed as 1 cespecifi f t c t q p v pρ = = × × ∆= × (1) where t is time (s), q is generated heat (j), p is heating element power (w), � is the density of the chosen substance (kg/m3), v is the volume of the vessel containing the substance (m3), cspecific is the specific heat of the substance (j/kg°c), and δ� is temperature variation (°c). decision variables: the calorimeter material and dimensions were setting it up as decision variables. table 2 shows the materials proposed as insulation for the calorimeter and their characteristic values. table 2 proposed materials for calorimeter insulation material specific heat ce (j/kg°c) density (kg/m3) m1 4186 1000 m2 3730 1035 m3 3300 1053 m4 1 1.239 where m1 is water, m2 is water and coolant at 50%, m3 is water and coolant at 30%, and m4 is air. as the refrigerant ethylene glycol was chosen. the proposed dimensions are set out in table 3: table 3 proposed calorimeter dimensions volume (l) width (cm) length (cm) height (cm) 15 24 22 28 25 30 26 32 30 30 31 32 35 30 32 36 objective function 2 (f2) is intended to minimize cumulative measurement error. to ensure minimal error, it was called to simulate the response of the controller, to establish the best parameters to be implemented. the simulation was performed using matlab software. first, the mathematical model of the thermal system to be controlled was set up. the differential equation representing the thermal system is expressed as: advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 232 dt p t dt v cpρ × = × × (2) afterward, the type of controller to be implemented could be designed and simulated. the input variable is voltage and the output variable is temperature. the controller was determined using the sliding mode method. the sliding surface proposed for the controller utilized is represented by 1 0 1 dx k x xσ = + − (3) the equivalent controller and the attractive controller are respectively defined as ( )0 1d v cp ueq k x x i t ρ × × = × − × (4) ( )sgn n v cp u l i t ρ σ × × = × × × (5) after that, it was determined the cumulative error of the controller using simulink and matlab. for this purpose, it was established the value of the constant k0 present in eqs. (3)-(4), based on the previously defined decision variables. fig. 2 shows the method to identify the cumulative error of the controller. it can be seen that the study signal is the input signal, which is the temperature in the cement sample. likewise, it can be seen in the sliding mode representation of the controller. the orange color represents the attractive control, while the fuchsia color represents the equivalent control. sliding mode control provides a systematic approach to the problem of maintaining accuracy, stability, adjustability, and performance in the face of model inaccuracy. it is also an efficient tool for designing robust controllers for complex nonlinear and multivariable plants. there are two main advantages of this type of control. first, the dynamic behavior of the system can be adapted by the particular choice of a slip function. secondly, the closed-loop response becomes insensitive to some particular uncertainties. fig. 2 computation of the cumulative error of the controller when the algorithm finishes its process, it displays the set of optimal solutions, entitled the pareto front. because all the values obtained are possible answers, it is necessary to apply bargaining methods to obtain the choice criterion. the negotiation methods used to find the selected solution to manufacture the calorimeter were the egalitarian method and the nash method [21]. 2.2. construction of the calorimeter after applying the optimization algorithm, the control system was designed and implemented. as mentioned previously, the controller design was selected using sliding modes. to fully understand the behavior of the control system, it is important advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 233 to mention the various parts and the operation of the calorimeter. the part where the measurement was carried out is a cubic acrylic container with a side length of 35 cm (fig. 3(a)). the cement sample was contained inside a 10 cm box (fig. 3(b)). this box has an extended lid that allows the sensor to enter the sample. in turn, the sample is housed inside the small box and contained inside the large container (fig. 3(c)). (a) cubic acrylic container (b) sample recipient (c) containers used fig. 3 vessels used for calorimeter measurement moreover, to ensure minimal heat loss, the water temperature was controlled by three separate systems. the first is a temperature homogenization system, which mixed the water so that the temperature was approximately the same throughout the volume. this system has two mixing paddles operated by electric motors. the functioning of this system is independent of the variation of the temperature in the calorimeter, so that, as soon as it is started, the paddles are activated. the second is the heating system, which consists of two heating resistors (fig. 4). the actuators of these two systems are located on the cover of the main box. in turn, the calorimeter has 3 temperature sensors, 1 for the sample and 2 for water temperature measurement. fig. 4 mixing paddles and heaters fig. 5 cooling system the third and last system was the cooling system. this has a pump that allows the flow of water to an external container filled with cooling liquid, to reduce the calorimeter’s ambient temperature through heat exchange, fig. 5. it can be observed that the heating and cooling systems depend on the temperature of the sample (reference temperature). when the sample temperature is below the ambient temperature, the cooling system is activated; consequently, when the sample temperature is above the ambient temperature, the heating system must be activated. to measure temperature changes, submersible ntc 10k sensors were used. in addition to the three systems mentioned above, the calorimeter has power and a control element. fig. 6 shows these components. the power element consists of relays (a) that allow the activation or deactivation of the heating and cooling system actuators. also, the control element includes a microcontroller (arduino mega) (b), an electronic conditioner for the sensors (c), a bluetooth module for data acquisition (d), and a module for data storage using micro-sd memory (e). fig. 7 shows the calorimeter modeled in solidworks, where the different components and systems that are part of the developed device can be seen more clearly. advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 234 fig. 6 power and control part fig. 7 calorimeter developed 3. results and discussion as a result of using the optimization algorithm (nsga-ii), it was obtained a set of solutions or pareto front. to achieve this, the algorithm was implemented with a population of 100 individuals, fig. 8. the behavior of the pareto front is consistent with the definition of the two objective functions since the system is a minimization problem and its shape must be convex. this generates a conflict in the possible solution; because, for the heating time to be minimal, the cumulative error of the controller must be large, and, by contrast, for the cumulative error of the controller to be reduced, the heating time must be increased. convex pareto fronts are obtained with a set of acceptable multi-objective optimization solutions and satisfying the objective functions [22-24]. fig. 8 pareto front fig. 9 nash and egalitarian negotiation methods advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 235 for a better analysis of the results obtained, it was needed to normalize the pareto front, reduce the number of decimal places and obtain simpler values to analyze. it should be noted that the points appear in this way in the graph because the data were filtered and only normalized data (values between 0 and 1) appear. it is important to note that the data processed by the nsga-ii algorithm has the solutions to the proposed problem or the decision variables, that is, the genotype. as a result of collecting this data, the response of the objective functions of the problem, represented by the pareto front, meaning the phenotype, was found. to obtain the best design (the best solution), it was required to establish the genotype, so bargaining methods were used, which are aimed to find a better decision. fig. 9 shows the pareto front with the two negotiation methods used. by applying the bargaining methods, it can be evidenced they pass over 3 coordinate points. the egalitarian bargaining method goes through the coordinate point (0.2, 0.2), while the nash bargaining method goes through the coordinate points (0.1, 0.4), (0.2, 0.2), and (0.4, 0.1). the optimal values of the phenotype and genotype are shown in table 4. as previously mentioned, the decision variables selected were the volume and type of material to be heated. the optimal material to heat is water; with the volume varying between 18 and 30.5 liters. it is highlighted these values were the result of the data processing performed by the nsga-ii algorithm. table 4 decision variables obtained by the negotiation methods. phenotype negotiation methods decision variables (genotype) volume (l) materiales to be heated (0.1, 0.4) nash 18 water (0.2, 0.2) equal/nash 30.5 water (0.4, 0.1) nash 27.4 water despite the fact all three solutions were optimal, a water volume of 18 liters was finally chosen. this choice was made to minimize the costs in the manufacture of the calorimeter, since the smaller the dimensions, the lower the manufacturing cost. it is clarified the choice of the final design will depend on the designer’s criteria and on some factors not considered in the algorithm, such as costs, physical space, portability, and sample size, among others. the calorimeter’s dimensions were made slightly larger than the volume of water to be heated so that all the components could be positioned comfortably and practically. as mentioned before, the control system was designed using sliding modes. this type of control is composed of two parts. the first part is the equivalent control; which has the function of restricting the reference temperature to the chosen non-stick surface. the second method is the attractive control, aimed at preventing the reference temperature from deviating from the desired trajectory, thus attracting it to the calculated non-stick surface. (a) error obtained with concurrent design (b) error obtained within lin [25] fig. 10 error obtained in the tests after verifying the design of the controller was correct, it was then implemented. fig. 10(a) shows the reference temperature variation (orange curve) and the water temperature (black curve). it is observed that the difference between the reference temperature and the water temperature did not exceed 0.2 °c/h. compared with lin [25], the relationship in the advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 236 change of temperatures is similar, as shown in fig. 10(b), and the temperature loss has less variation; this is a result of the concurrent design used. it is noted the system to be controlled is a thermal system and the response of these systems is slow due to the nature of the system itself. to assure the calorimeter’s proper functioning, three tests were carried out using identical cement paste mixtures. the main characteristics of the mixture employed were; 50 g of cement, 35 ml of water, a water/cement ratio of 0.7, and a total volume of 24.74 cm3. fig. 11 shows the temperatures obtained for each test. it is seen that the difference between the ambient temperature and the temperature of the sample was quite minimal (about 0.2 °c). however, the temperature of the sample increases as time goes by, because of the chemical nature of the cement. the temperature values obtained are related to the size of the sample; it is important to keep in mind that using a smaller mass will result in a smaller temperature variation. fig. 11 measured temperatures to verify that the variation in ambient temperature versus sample temperature is statistically acceptable, the wilcoxon test was used to verify the results obtained. for this purpose, it was defined the null hypothesis and the alternative hypothesis as: null hypothesis (h0): the curves obtained are not acceptable. alternative hypothesis (h1): the curves obtained are acceptable. to obtain the values of the parameters p and h, the data used to obtain the curves in fig. 11 and matlab were used. table 5 shows the data obtained by applying the wilcoxon test: table 5 values obtained from wilcoxon test temperature p h δt1 vs δt2 0.00024 1 δt1 vs δt3 0.0166 1 δt2 vs δt3 0.00006 1 the δt values correspond to the difference between the sample temperature and the ambient temperature for each measurement taken (t1, t2, and t3). in other words, the value considered was the error in the measurement, since the main objective of the calorimeter is that the difference between temperatures is as close to zero as possible. it can be seen that the p < 0.05 and the value of h = 1 for all the measurements made, therefore the null hypothesis is rejected and the alternative hypothesis is accepted. fig. 12 shows the heat of hydration curves obtained for each measurement. the behavior of the three curves was similar, with a slight difference between the maximum values. furthermore, the maximum heat peak occurred approximately 2 hours after the test. the curves obtained are based on the temperatures measured in the calorimeter, the mathematical model that governs the behavior of these curves is part of another study, however, it was important in establishing the behavior of the advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 237 hydration heat. it is important to clarify that, even though the sample conditions were the same for each measurement, cement hydration is a chemical process that is not exact and is approximated by mathematical models; therefore, the results obtained in fig. 12 are not the same, but its performance is in line with what is reported in the literature. the resulting curves were compared to some similar investigations. in chidiac and shafikhani [26], the heat of the hydration curve was obtained for different types of cement mortar mixtures, which means the number of samples used was higher than in the present work. the maximum peak was achieved approximately 9 hours after the start of the measurement and heat of hydration values between 0.5 and 4.0 w/g were obtained. the measurement time was 26 hours. fig. 12 hydration heat curves obtained additionally, sanderson et al. [1] evaluated the behavior of the hydration heat in cement mortars with a sample volume of 125 cm3. the values of the heat of hydration oscillate between 0.0005 w/g and 0.004 w/g, and the maximum peak is reached almost 12 hours after testing. the measurement time was 24 hours. besides, in lin and chen [27] cubic concrete specimens of 5.8 m3 volume were made. the measurement time was 144 hours. the maximum heat peak was 3.7 w/kg and the time to reach it was approximately 9 hours. additionally, in prasath and santhanam [9], the heat of the hydration curve was obtained for concrete samples with a volume of 5300 cm3 approximately, and the measurement time was approximately 40 hours. the maximum heat peak was 4.8 w/kg and was reached 10 hours after the start of the test. on the other hand, chen et al. [28] measured the heat of hydration in cement pastes with limestone-calcined and clay slag. due to the nature of the samples, the peak values vary, however, the maximum peak heat was obtained between 9 and 15 hours, and the measurement time was approximately 48 hours. the maximum heat value was 1.1 mw/g. it is observed that the values and times in the graphs vary since all the mixtures do not have the same volumes, the same mixture designs, or the same measurement time. nevertheless, it can be said that the results obtained by the calorimeter meet the expectations, considering that the behavior of the heat curves obtained corresponds to what has been reported in the literature. 4. conclusions concurrent engineering was used to obtain the optimum design of an adiabatic calorimeter for cementitious mixtures. nsga-ii was used as the optimization algorithm. with the development of this work, it was found that: (1) one benefit of using nsga-ii to design and construct the adiabatic calorimeter for cement mixtures was the algorithm's ability to work with mixed variables, allowing for the optimization of both the material to be heated and the device's size. the evolutionary algorithms demo and mode, which were tested prior to selecting the optimization algorithm to be employed, were unable to achieve this. (2) another benefit was that, unlike the evolutionary algorithms demo and mode, the second objective function permitted the use of design variables with decimal numbers, enabling the convex pareto front typical of a minimization issue. advances in technology innovation, vol. 8, no. 3, 2023, pp. 229-239 238 (3) it was possible to produce a pareto front with a convex form, good distribution, and dispersion; this prevented the algorithm from becoming stuck in regionally optimal spots. the diversity of the sample was well preserved across the many simulations thanks to the excellent performance of the agglomeration distance operator for nsga-ii during selection. (4) the measurement error was lower compared to studies where concurrent engineering was not applied, thus demonstrating the advantage of using optimization algorithms for the design. (5) the wilcoxon test was applied, and a value of p < 0.05 and a value of h=1 were found, indicating the statistical validity of the tests performed. (6) among the limitations found when implementing nsga-ii, one of them was its long simulation time, since it took 2 to 3 hours to obtain the pareto front, increasing the computational cost of using this algorithm. (7) also, due to the nature of the process to be optimized, it was not possible to use nsga-ii without modification since it was necessary to create a specific function that included the chosen objective functions. (8) the novelty of this work is that the calorimeter was developed using concurrent design (optimization algorithms) unlike existing calorimeters. this work is expected to pioneer the development of optimized calorimeters for cement mixtures. acknowledgments the authors acknowledge juan de castellanos university for the funding given for the development of the project. the authors would also like to thank professor manuel alberto montaña suárez for the complete translation of the article. conflicts of interest the authors declare no conflict of interest. references [1] r. a. sanderson, g. m. cann, and j. l. provis, “comparison of calorimetric methods for the assessment of slag cement hydration,” advances in applied ceramics, vol. 116, no. 4, pp. 186-192, 2017. 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[28] y. chen, y. zhang, b. šavija, and o. çopuroğlu, “fresh properties of limestone-calcined clay-slag cement pastes,” cement and concrete composites, vol. 138, article no. 104962, april 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 learning representations for face recognition: a review from holistic to deep learning fabian barreto 1* , jignesh sarvaiya 2 , suprava patnaik 3 1department of electronics and telecommunication, xavier institute of engineering, mumbai, india 2department of electronics, sardar vallabhbhai national institute of technology, surat, india 3school of electronics, kalinga institute of industrial technology, bhubaneswar, india received 18 august 2021; received in revised form 07 january 2022; accepted 08 january 2022 doi: https://doi.org/10.46604/aiti.2022.8308 abstract for decades, researchers have investigated how to recognize facial images. this study reviews the development of different face recognition (fr) methods, namely, holistic learning, handcrafted local feature learning, shallow learning, and deep learning (dl). with the development of methods, the accuracy of recognizing faces in the labeled faces in the wild (lfw) database has been increased. the accuracy of holistic learning is 60%, that of handcrafted local feature learning increases to 70%, and that of shallow learning is 86%. finally, dl achieves human-level performance (97% accuracy). this enhanced accuracy is caused by large datasets and graphics processing units (gpus) with massively parallel processing capabilities. furthermore, fr challenges and current research studies are discussed to understand future research directions. the results of this study show that presently the database of labeled faces in the wild has reached 99.85% accuracy. keywords: learning representations, deep learning, autoencoders, variational autoencoders 1. introduction in the modern world, automatic face recognition (afr) is embedded into smart e-commerce applets for better personalization and marketing of commodities, such as hair styling and digital makeup. consumer-based photography has become a new trend in selecting a range of products that suit consumers’ needs, with social media platforms providing facial recognition services to attract diverse users. conventional facial recognition (fr) requirements are limited to basic security and access control applications, and are implemented in more advanced ways. examples include accessing historical data and using cloud-based database identification and closed-circuit television (cctv) video-supported tracking, leading to better enforcement of the law. facial identification has become essential for forensics, surveillance, border control, lie detection, and access id verification. fr, in its various dimensions, is currently a research area in computer vision, and is the process of detecting and locating faces from a background, normalizing face images, and performing face verification (fv) or face identification (fi). there are two separate tasks for face matching while conducting fr, namely: fv and fi. in fv, one determines whether a given test image is from the same person being verified, while the fi aims to recognize the facial images of persons already enrolled in the database [1]. to verify genuineness, the output of fr is either “yes” or “no,” which may be a result of the class number corresponding to the input image. in the fv, the input image is assumed to be a sample from a known possible class of inputs. * corresponding author. e-mail address: frfabiansj@xavier.ac.in tel.: +919833916407 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 regarding face detection (fd), in 2001, viola and jones [2] used haar-like features to detect human faces. a 24 × 24 pixel can have over 160,000 haar-like features. the framework used the concept of integral images to perform intensive computation and the adaptive boost (adaboost) algorithm to select the best features from different subsets. wang et al. [3] categorized fd and recognition development into four broad representation learning types: holistic, handcrafted, shallow, and deep learning. traditionally, fr techniques have been divided into two major categories: geometric and photometric techniques. here, geometric techniques find distinct features and spatial positioning to form a template that is used to compare and eliminate variances in face images. photometric approaches are distilled out and use hidden statistical properties that account for the entire input of facial images. popular photometric approaches include principal component analysis (pca) using the eigenface algorithm and linear discrimination analysis (lda) using the fisherface algorithm. the holistic approach uses low-dimensional representations in the form of a manifold or a linear subspace. however, this approach is limited by variations such as face appearances that introduce different statistical distributions, which are difficult to manage. the early twentieth century saw a transition to handcrafted local feature-based methods. inherent face changes are managed through local descriptors, such as local binary patterns (lbps), gabor filters, and histograms of oriented gradients (hogs). these local features help remove redundant and meaningless information from raw representation; thus, they provide greater robustness than existing methods and are greatly invariant to transformation. the limitations of these approaches are that they suffer from a lack of compactness, distinctiveness over a large sample space, and acceptance for real-time applications, as well as being slow and susceptible to poor generalization. shallow representation learning, with a oneor two-layer representation, improved the distinctness of the codebook. noticeable shallow approaches included the learning-based (le) approach, discriminant face descriptor (dfd), feature vector, and pcanet. however, these approaches were not robust to the complex non-linear nature of the face. deep learning (dl) is a revolutionary approach that has changed the facial recognition landscape. in 2012, alexnet achieved state-of-the-art (sota) recognition accuracy and propelled research toward dl for computer vision. researchers have used a convolutional neural network (cnn) that exhibited strong invariance to face pose, lighting, expression, and other variations to achieve high accuracy. thus, this research addresses recognition accuracy and investigates the complexity of learning a large number of features, dependency on datasets, protocols addressing application scenarios, and model interpretability. this research also addresses variations encountered owing to cross-posed, aging, and other adversarial conditions. since the 1990s, remarkable advances have been made in fd and recognition. this study aims to review the development of learning representations for fr in the past three decades and has resulted in an accuracy increase of 39.85% for labeled faces in the wild (lfw) database from the earlier methods used three decades ago. the remainder of this study is organized as follows. section 2 describes the initial holistic representation of the learning stage for fr, and section 3 describes the transition to a handcrafted stage. section 4 presents the shallow learning phase, and section 5 deals with the dl phase and some challenges and current research studies. finally, section 6 provides the conclusions of this study. 2. review of holistic learning the earliest holistic stage begins by using eigenfaces, motivated by sirovich and kirby [4], to efficiently represent face images using pca. they then transition to fisherface algorithms and lda and later to independent component analysis (ica), leading to sparse representation-based classification (src), a particular case of collaborative representation-based classification (crc). later, researchers used distance metric learning with improved class separability, meaning that the holistic stage can assume certain distributions (linear, manifold, and sparse) from which it arrives at a low-dimensional representation. however, these assumptions do not hold firm ground on the variations in facial features. 280 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 2.1. principal component analysis (pca) ballantyne et al. [5] mentioned the pioneering work of woody bledsoe and his afr team. they manually classified face images with landmarks (e.g., eye centers and mouth) and saved the metrics in a database. goldstein et al. [6] enhanced the accuracy by using 21 specific subjective markers on the face. the work of turk and pentland [7] in 1991 gave a new direction to using eigenfaces (pca) to develop the first afr system. varying the illumination and pose conditions is a challenging task for this method. it is essential to understand that a particular eigenfeature may not be related to recognition, but to the direction of illumination. hence, an increase in eigenfeatures does not necessarily lead to better accuracy. pca can only set apart the linear dependencies in the pixel pair of a facial image. pca is a method for expressing data vectors in their principal components (pcs), where the largest variances in the data indicated the direction of the pcs (fig. 1). pcs capture the most significant data information and correspond to the eigenvectors given by the largest eigenvalues of the autocorrelation matrix of the data vectors. pca computes the most representational basis for looking at the dataset and generally works as follows. first, it calculates the covariance matrix of the given data points and calculates the eigenvectors and corresponding eigenvalues sorted in decreasing order. then, the first k eigenvectors are chosen from the n eigenvectors (k < n), yielding the novel k dimensions. thus, the original n higher dimensions were transformed into k fewer dimensions. fig. 1 original space (x1, x2) and pca reduced space (pc1, pc2) 2.2. linear discrimination analysis (lda) lda constructs a subspace that differentiates between different face images, while fisher discriminant analysis classifies face images into groups based on their facial features. zhao et al. [8] used lda for fr because it encodes discriminatory information. they used pca to project the face image to a subspace and used an lda to obtain a linear classifier in the subspace. the pure lda approach, however, does lead to an overfitting problem and does not perform well for samples from different classes and samples with diverse backgrounds. 2.3. independent component analysis (ica) ica describes a subspace method that transforms data from high to low dimensions. it finds a linear transformation that leads to the minimization of the statistical dependence between its components. however, unlike pca, it provides an improved probabilistic model, a greater response to high-order statistics, and better reconstruction in noisy environments [9]. a set of statistically independent basis images for a set of face images is found by separating the independent components of the facial images (fig. 2). here, let s be a set of statistically independent source images, which is unknown, with x as the source of the face images and a as an unknown combination matrix. wi is a matrix of learned filters which in turn produces outputs u that are statistically independent. ica outputs in rows that are wix = u. 281 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 fig. 2 image synthesis model 2.4. hidden markov model (hmm) in a hidden markov model (hmm), patterns are characterized as parametric random processes. these parameters can be estimated precisely and logically. samaria et al. [10] used the hmm model to represent the statistics of facial images. they converted a two-dimensional face image to a one-dimensional sequence. as shown in fig. 3, the face is split into regions (e.g., the forehead, eyes, nose, mouth, and chin). after determining the hidden states (five in the given figure), the hmm is trained to learn the state transitional probability. after training on the output probability, the class was determined. although hmm has a better detection rate, it also has a higher false-alarm rate. fig. 3 five-state hmm 2.5. bayesian model schneiderman et al. [11] derived a probabilistic model for fr using local regions, such as the eyes, nose, and mouth. their statistical model captured the more unique patterns of the human face, such as the intensity patterns around the eye, to represent the local features more uniquely. they also modelled the joint probability of local features and positions, as human faces are easily recognized because of their proper spatial arrangement. they used the bayesian decision rule, also known as maximum a posteriori (map), and calculated a larger probability for a given input image x, namely, p(face | x) or p(not face | x), indicating whether a face was selected. yang et al. [12] presented two advantages of using a naive bayes classifier; that is, it provided a better estimation of the subregion conditional density functions and provided an map to understand the joint statistics of a local feature and its position. 2.6. locality preserving projection (lpp) he et al. [13] proposed an appearance-based laplacian method for facial recognition by using locality preserving projections (lpps) to map facial images into a subspace. eigenfaces (pca) preserve the global surface of the face image, whereas the fisherface algorithm (lda) preserves discriminating information. the advantage of lpp over pca and lda is 282 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 that it preserves local features and detects the essential face manifold surface, where the nearest-neighbor graph models this surface. the face images in the lower-dimensional subspaces are called laplacian faces. facial recognition was performed in three steps. laplacian faces were calculated from the given training face image samples, and the test image is then projected onto the laplacian face subspace. finally, the nearest-neighbor classifier identifies a new face. as this method considers the face manifold, it considers varying illumination conditions. 2.7. sparse representation-based classification (src) and collaborative representation-based classification (crc) src and crc belong to sparse representation-based classifiers. the test input image was a linear connection between the recorded images. the test image can be recognized as the combination coefficients for the target faces, which are larger than the others. in src/crc, the test face images are coded over others with sparsity constraints, such as l1 minimization. src/crc uses the reconstruction error to determine the face image. in the work of wright et al. [14], the discriminative property of an src model for classification was used, while in the work of zhang et al. [15] and zhang et al. [16], it was shown that the good performance of src is primarily due to the collaborative representation of the test face image with training samples across different classes. 2.8. distance metric learning in distance metric learning, one learns a distance metric for the input space of face images from a given set of similar/dissimilar points in the training face images. yang et al. [17] categorized the algorithms for distance metric learning into supervised and unsupervised methods. supervised training face images are placed into pairwise constraints: pairs of same-class data points in the equivalence constraints and those that belong to different classes in equivalence constraints. supervised learning can be global or local, where global satisfies pairwise constraints simultaneously and local only meets local pairwise constraints. supervised learning includes supervised global learning, local adaptive supervised learning, neighborhood component analysis, and relevant component analysis (rca), while unsupervised learning includes linear-like pca and multidimensional scaling. they also include nonlinear embedding methods such as isometric mapping, linear embedding, and laplacian eigenmaps. jin et al. [18] presented a regularized distance metric learning algorithm that is robust for high-dimensional data. here, the generalization error of regularized distance metric learning is independent of dimensionality. the algorithm was tested with the baselines of the euclidean distance metric, mahalanobis distance metric, large margin nearest neighbor classifier, information-theoretic metric learning, and rca and was comparable to sota approaches for distance learning. 3. review of handcrafted local feature learning to enhance the holistic method, researchers started using handcrafted local features. they used gabor wavelets, elastic bunch graph matching (ebgm), local binary patterns (lbp), and high dimensional local binary patterns (hd-lbp). these methods did achieve robust performance. however, as the features increased, there was a problem of distinctiveness, and the large size created the problem of non-compactness. 3.1. gabor wavelet (filter) gabor introduced the gabor wavelet (or gabor filter) in 1946 as a band-pass filter and has an impulse response given by a gaussian function, multiplied by a harmonic function. its resolution is optimal in both the domains of space and frequency. daugman [19] generalized the 1-d gabor filters to two-dimensional gabor filters. liu et al. [20] described a facial recognition gabor feature classifier where gabor wavelets first transform the face images to obtain the augmented gabor fv and then pass through an enhanced fisher discrimination model. their results showed that the classifier can discriminate gabor features with 283 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 low dimensionality and increased discrimination. barbu [21] proposed a 2-d gabor filter for human fr. he used 2-d gabor filter banks, which help extract different orientation and scale features from the input face image, resulting in 3-d face feature vectors. one disadvantage is that gabor features have high dimensionality and result in redundancy [22]. a hybrid method uses gabor filters and another technique such as pca to reduce redundancy. principal gabor filters that help reduce redundancy are described in the work of štruc et al. [23]. here, they used orthonormal linear combinations and derived a gabor face representation. however, the tradeoff is that the filters are not optimally localized in the space and frequency domains. 3.2. local binary pattern (lbp) the human face can be viewed as consisting of micro-patterns and hence can use an lbp as a face descriptor [24-25]. lbp was first proposed for texture description [26], where it was observed that certain lbp are key properties of texture and sometimes represent over 90% of all 3 × 3 patterns present in the textures. after thresholding, a histogram that functions as a texture descriptor can be created (fig. 4). these patterns have uniform circular structures with few spatial transitions and were used as templates. the lbp operator is only a 3 × 3 neighborhood; therefore, it is difficult to capture the features that are dominant for large-scale structures, with later models using neighborhoods of different sizes to correct this issue. lbp efficiently summarizes the local structures of facial images, where each pixel was compared with its neighboring pixels. an example is shown in fig. 5. here, each pixel is compared with its eight neighbors by subtracting the center pixel value. the encoding process is done in the following steps. encode a 0 for negative; otherwise, encode a 1. concatenate all binary values in a clockwise direction. begin from the top-left neighbor and move clockwise. convert the binary to a decimal value, the label (lbp codes) for the given pixel. lbp is a non-parametric method that converts the face image into an array of integer labels. huang et al. [27] surveyed lbp and its variants that offer better performance and improved the robustness of the original lbp. isnanto et al. [28] used lbp and haar cascade classifier on low-resolution images for multi-object fr. fig. 4 lbp histogram fig. 5 lbp operator 3.3. elastic bunch graph matching (ebgm) bolme [29] described the ebgm fr algorithm. it recognizes new facial images by localizing landmark features and then finds the similarity measure. facial landmark points were selected manually from a set of model face images with variations. gabor jets are the names given to the gabor wavelets extracted from the landmark point and the jets from the model form a face bunch graph. each node contains a stack of n jets (n = model image). here, the edge is the distance 284 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 between landmark points (fig. 6). the limitation of the ebgm is that one needs to rely on the model’s manual ground truth for landmark selection at the initial recognition stage. lahasan et al. [30] proposed a method to overcome this shortcoming by posing the ebgm as an optimization problem by using harmony search (hs) to find the optimal facial landmarks using the manual method. fig. 6 ebgm process 3.4. scale-invariant feature transform (sift) scale-invariant feature transform sift was proposed by lowe [32-33]. it creates descriptors that are scale-, rotation-, and translation-invariant and possesses high dimensionality. fr tasks use sift features [33-34] to reliably match images. this process includes extracting sift keypoints from the face image. how can one find the test image? by finding the matching features. the euclidean distance was used as the measure; however, a challenge is the reliable extraction of consistent sift descriptors. as shown in fig. 7, the sift algorithm has four stages: keypoint detection, keypoint localization, orientation assignment, and keypoint descriptor generation. keypoint detection uses the difference of the gaussian (dog) function to detect feature points, and each keypoint is assigned one or more orientations during the orientation assignment stage. in the last stage, each keypoint is assigned to a vector descriptor. given that the algorithm is computationally intensive, the actions are performed only at positions that go through the first test. fig. 8 shows the sift features of a 64 × 64 image, its noisy version, and matching features. fig. 7 stages of the sift algorithm (a) sift keypoints of the original image (64 × 64) (b) with added noise (c) sift keypoint matching fig. 8 implementation of sift 285 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 3.5. histogram of oriented gradient (hog) dalal et al. [35] developed grids of hog descriptors, which have the advantage of capturing the gradient (edge) structure, a characteristic of the local shape. the grids count the occurrence of edge orientations in the local neighborhood of the face image. facial images were split into small and linked regions (cells), and a histogram of the edge orientations was computed for each cell. the histograms were normalized to account for the illumination and combined to form the hog descriptor. the hog is invariant to 2d rotation and scaling. using locally normalized hog features with an overlapping dense grid yielded better results. déniz et al. [36] proposed a method for building a robust hog descriptor by using a regular grid, combining hog descriptors at different scales, and applying a reduction in linear dimensions. 4. review of shallow learning the shallow learning-based (le) local descriptor phase uses local filters to learn distinctiveness and a codebook to achieve compactness. as this was a shallow representation, a oneor two-layer representation, it is not robust to the complex nonlinearity of face images. the method also improves one characteristic, such as pose, light, or expression, but does not address unconstrained changes in the face image in general. 4.1. learning-based (le) cao et al. [37] proposed a new le descriptor that was compact, discriminative, and easy to extract. they list the disadvantages of existing handcrafted methods, as it is challenging to obtain an optimal encoding and unevenly distributed. their process consisted of extracting face landmarks that aligned nine different parts of the face separately, which were fed into the dog filter to remove lowand high-frequency illumination variations. each pixel has a low-level fv encoded by an le encoder. pca-reduced histograms were concatenated and then normalized to obtain the le descriptor, and the similarity of the le descriptors of the face pair was measured using the l2 distance norm. the nine component similarity scores were then fed into a pose-adaptive classifier, which resulted in fv. 4.2. discriminant face descriptor (dfd) lei et al. [38] described a technique for acquiring a dfd. discriminant local features learn by minimizing the feature differences between the same face images and maximizing those between different face images. the discriminative capability is performed in three steps: learning discriminant image filters, determining the optimal neighborhood sampling, and constructing the dominant patterns. they also used coupled dfds to view heterogeneous facial data. 4.3. feature vector sánchez et al. [39] described the feature vector method for image classification based on the principle of gaussian mixture distribution. they proposed using the fisher kernel framework and described their blocks by deviation from a gaussian mixture distribution with diagonal covariance. visual vocabulary is a gradient vector for the model parameters. their method encoded the (probabilistic) count of occurrences and higher-order statistics. the authors listed the advantages of their method as having better results than efficient linear classifiers and compression with a very low loss of accuracy. 4.4. pcanet chan et al. [40] proposed a baseline model for image classification called pcanet, a precursor to dl models. pcanet consists of cascaded pca to learn from multistage filter banks, binary hashing, and blockwise histograms and has two variations: randnet and ldanet. in randnet, they replaced pca filters with random filters of the same size at each layer, whereas in ldanet, the supervision of a classification problem was improved by using supervised training. lda is used to 286 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 learn the filters. pcanet eliminated image variability and provided effective accuracy with well-preprocessed images in the datasets. however, pcanet may not sufficiently account for the variability of challenging face images. however, the pcanet is a valuable baseline for studying dl architectures. 5. review of deep learning the fr landscape saw a fundamental shift with the introduction of alexnet, which uses dl. deepface [41], deepid [42-43], facenet [44], arcface [45], and adaptiveface [46] have paved the way for an evolution of network architectures, algorithms, and datasets to answer the multi-faceted fr problem. the accuracy results for the lfw database [47] explain the fr development stages. for the holistic stage, the accuracy was 60%, while for handcrafted, it increased to 70%, shallow to 86%, and finally, for dl, especially for deepface, it approached human-level performance of 97% for the unconstrained fr. in the early days of the afr, the focus was more on developing fd algorithms and less on developing face image datasets. there has been organic growth in the datasets over the past two decades because it has come from the research community in terms of the need for a large number of face images with varying conditions and diversity. another development has been the challenge to go beyond recognizing faces from laboratory-controlled to unconstrained face images. afr research has progressed enormously, with some simple datasets achieving 99% accuracy, which has resulted in the development of more complex datasets that can facilitate new directions for fr research. the number of face images in the datasets and their variations has increased over the years. the past decade with fr research moving toward dl approaches has resulted in the growth of large training datasets required to implement dl algorithms effectively. taskiran et al. [48] classified face image datasets as image-based or video-based. they may also be 3d or hyperspectral/infrared datasets. some of the datasets were private, whereas others were public. these datasets are essential for benchmarking new afr algorithms. a database’s choice depends on the given problem that one intends to solve or a property that one wants to test and also depends on the size of the training set required to test the algorithm. some databases, such as facebook, google, celebfaces+, and vggface, were used for training, and others, such as lfw, ytf, and ijb-c, were used for testing. 5.1. artificial intelligence (ai), machine learning (ml), and deep learning (dl) john mccarthy, the father of artificial intelligence (ai), coined the term ai in his 1955 proposal for the dartmouth conference, usa, in 1956. on a broader scale, ai explores theories and applications to broaden human intelligence and envisions the creation of a future where intelligent machines have human-like perception and cognition. researchers have made significant progress in understanding and improving learning algorithms; however, the challenge of ai remains [49]. as shown in fig. 9, dl is a subfield of machine learning (ml), and ml is a subset of the broader field of ai. some examples of ml problems include classification, clustering, and prediction. traditional ml techniques are constrained to process data in a basic form and domain experts are required to carefully perform feature extraction [50]. dl is a subset of the ml and learns multiple representations and abstraction levels to understand the data. the raw input was transformed to a higher and more abstract level (fig. 10). these transformations can help learn complex and intricate functions. fig. 9 relationship of ai, ml, and dl 287 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 (a) ml (b) dl fig. 10 ml and dl approaches 5.2. artificial neural network (ann) the unique human brain, especially how neurons interact, has inspired scientists. artificial neural networks (anns) are hardware and software implementations of neural structures in the human brain. the history of neural computing originated with the work of mcculloch and pitts in 1943. the warren mcculloch and walter pitts model (mcp model, known as the linear threshold gate model) is a binary classifier [51], where the weights were manually adjusted by a human. in the 1950s, rosenblatt published the perceptron algorithm, which automatically learns weights without human involvement [52]. this was an enhanced version of the mcp model. the perceptron model adds extra information representing the bias and variable weight values. the 1969 publication by minsky and papert [53] weakened neural network research for nearly a decade (1969-1986). they believed that using perceptrons in practical applications was futile without an adequate basic theory. in 1979, fukushima developed a neural network with multiple pooling and convolutional layers called neocognitron, which used a hierarchical and multilayered design that learned how to recognize visual patterns [54]. rumelhart revived neural network research in 1986 using a backpropagation (bp) algorithm. the neural network iteratively learns weights that are then used to predict class labels. given sufficient hidden units and sufficient training data multilayers, feedforward networks can closely approximate any function. in 1989, yann lecun demonstrated bp at the bell labs. he combined cnns with bp to read handwritten digits. in 1997, long short-term memory for recurrent neural networks (rnns) was developed by hochreiter and schmidhuber, with a gating mechanism to regulate the information to be kept or discarded at each time step. 5.3. the deep learning phase in 2009, fei-fei li launched the challenging benchmark dataset, imagenet [55]. between 2011 and 2012, krizhevsky created alexnet, a cnn. as shown in fig. 11, alexnet has five convolutional layers, followed by max-pooling layers and three fully connected layers. instead of using tanh and sigmoid activation functions, he used rectified linear units (relus), which increased the speed and dropout. alexnet showed that a greater depth resulted in high performance and, despite being computationally expensive, is feasible because of graphics processing units (gpus). in 2014, deepface used neural networks to identify faces from the lfw dataset with 97.35% accuracy, an improvement of 27% over previous efforts [41]. in 2015, the facenet model, using googlenet-24, achieved 99.63% accuracy for the google dataset [44]. in 2018, ring loss model using resnet-64 achieved 99.5% accuracy for the ms-celeb dataset [56] and arcface model using resnet-100 achieved 99.83% accuracy for the ms-celeb dataset [45]. in the work of yan et al. [57], the use of vargfacenet resulted in an accuracy of 99.85% for the lfw database. fig. 11 alexnet architecture 288 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 fig. 12 autoencoder model fig. 13 variational autoencoder the evolution of dl is described in detail by schmidhuber [58]. he explains the hierarchical representation learning for different supervised/reinforcement learning and the various advancements in both feedforward (acyclic) neural networks (fnns) and recurrent (cyclic) neural networks (rnns). he also described the evolution of restricted boltzmann machines (rbms), as well as the constituents of multilayer learning architectures, such as the deep belief networks (dbns). advances in dl meant working with high dimensional data, which could be reduced to codes of lower dimensionality. in 2006, hinton and salakhutdinov [59] trained an “autoencoder” network. autoencoders [60] are used for dimensionality reduction, denoising, and outlier detection and are made up of three sections, as shown in fig. 12. the encoder encodes the data to the hidden layer (code) which results in an output h = f(x). the decoder then outputs r = g(h). the training minimizes a mean squared error loss function. deep autoencoders use numerous internal intermediate representations, and these deep layers help learn more intricate and complex data patterns. convolutional autoencoder (caes) [60] helps integrate the convolutional advantage of a cnn. the encoder is thus made up of convolutional layers and the decoder of deconvolutional layers. thus, caes extract features and gives a feature map containing the image’s significant points. one limitation of an autoencoder is that it has a deterministic latent-space representation. although the autoencoder learns the input data, it may lack relevant information, which may be due to random encoding in the latent space or empty space. to overcome this, kingma et al. [61] suggested a variational autoencoder (vae), as shown in fig. 13, which uses a probability distribution for latent space code representation. an inference model q(z | x) for vae is described in [62]. here,  denotes the variational parameters, optimized for q(z | x)  p(x | z). here, q(z | x) approximates the posterior p(z | x) of the generative model and is optimized using the evidence lower bound (elbo) [63]. in 2014, goodfellow et al. [64] introduced generative adversarial networks (gans) as well as an adversarial network framework. a generative model is matched against a competitor, which they call a discriminative model, and the latter learns to determine whether the query face image is from the model distribution or given data distribution [64]. both thrive on competition to improve their methods till one cannot be distinguished from the other. 5.4. some current research in dl for fr developing different deep fr methods and their deployment in real-world applications requires a systematic performance evaluation. iandola et al. [65] provided an evaluation framework for different datasets and sota methods. they used the following criteria: data augmentation, network architecture, loss function, training strategy, and model compression. the varied sizes of the datasets, such as casia-webface, vgg-face, ms-celeb-1m, and megaface for training and lfw and ytf for testing the models, make comparisons difficult. here, both the datasets and architectures vary. a critical part of the evaluation is the loss function, which imposes stricter requirements for fr, as it has to discriminate and separate the features from the embedding space. the training strategy also plays an important role in terms of the learning rate and batch size. with 289 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 the modern trend of using fr in mobile and embedded devices, they also evaluated squeezenet [66] and mobilenet [67], which use compressed models and give better performance. they concluded that the deep resnet series has advantages over other architectures, and the batch and feature normalization optimizes performance. deployment of fr models, especially unconstrained faces on embedded or mobile devices, needs to meet the challenge of recognizing low-resolution faces at a low computational cost. this problem is addressed in the work of ge et al. [68] by using the selective knowledge distillation approach and calling it the teacher-student model. they used a two-stream cnn, one with high resolution (hr), which collected the essential facial features used to tune the other lr network using regression and classification. li et al. [69] also take on the challenging task of working with low-resolution unconstrained face images. they explore good-performing models using the scface [70] and uccsface [71] datasets. to visually learn the network, they pre-train it with dcgan [72]. new trends for unconstrained, very low-resolution fr were explored in [73]. they present a classification of very low-resolution fr approaches, characterizing them as heterogeneous or homogeneous based on their belongingness to different or same domains, respectively. the heterogeneous approach can be classified into projection (coupled mapping) and synthesis (super-resolution (sr)) methods. in a homogeneous approach, they discussed lightweight ccns. they listed the challenges for very low-resolution fr as the availability of datasets for real-world applications, the dearth of discriminative features, discrepancies in the domain, and the efficiency of existing solutions. one of the challenges in fr is the development of a pipeline that can simultaneously perform fd, alignment, and recognition. other parameters, such as pose and gender, may also be required in some instances. a cnn pipeline for the different processes is described by ranjan et al. [74]. they use a deep pyramid single-shot face detector (dpssd) and a new loss function called crystal loss. they evaluated their end-to-end system on the iarpa janus benchmarks ijb-a [75], ijb-b [76], ijb-c [77], and iarpa janus challenge set 5 (cs5) datasets to obtain sota performance. they also mentioned that some of the challenges facing current fr systems are dataset bias and domain adaptation. in mid-march 2020, the world health organization (who) declared the coronavirus disease 2019 (covid-19) be a pandemic [78]. dl has been extensively used in the analysis of the covid-19 pandemic, as elaborated in the work of heidariet al. [79], for disease prediction, disease monitoring, drug testing, and vaccine development. who issued guidelines for wearing a mask to prevent the transmission of the disease. abboah-offei et al. [80] provided a detailed analysis of facemasks to control the transmission of respiratory viral infections, and the french government tested ai-based cctv software to detect whether travelers wore masks or not [81]. the fr research community is engaged in developing systems to monitor the facemasks worn by people. fig. 14 depicts a block diagram of face mask detection using ml or dl. mbunge et al. [82] and nowrin et al. [83] provide a comprehensive review of mland dl-based facemask detection techniques. most of the facemask detection algorithms are cnn-based. a few are hybrid as they use dl and ml approaches like support vector machine (svm) and decision tree (dt). cnn-based models include mobilenetv2 [84], resnet [85], and vgg-16 cnn [86]. mobilenet and resnet perform better than vgg-16 cnn. mobilenetv2 exhibits better performance because it is a lightweight classifier. srcnet [87] uses an sr network and a classification network to perform three-class classification with an accuracy of 98.7%. facemasknet [88], a three-class classifier, has an accuracy of 98.6%. retinafacemask [89], which uses both resnet and mobilenet, incorporates transfer learning to achieve sota results. some challenges for face mask detection are elaborated in the work of nowrin et al. [83]. these include the availability of benchmarked datasets, variation in mask designs, processing speed for real-time applications, and variations in image resolution and masked face reconstruction. fig. 14 face mask detection block diagram 290 advances in technology innovation, vol. 7, no. 4, 2022, pp. 279-294 6. conclusions this study reviewed the vast literature on the development of different approaches for afr. over time, a transition from shallow to modern sota methodologies for dl has been observed. early fr methods used limited images and a laboratory-controlled environment. however, with the advent of dl models, the lfw database achieved 99.85% accuracy. this was possible because of gpus’ massively parallel processing capabilities and large training and testing datasets. the challenges faced by dl models were also examined. as networks deepen, the complexity of the deep convolutional neural network (dcnn) model increases. a deep autoencoder or vae that preserves some interclass discrimination information and intraclass similarity can feed a dcnn with a lower complexity to reduce the overall dcnn complexity. the performance decreases when the images have low resolution, variations in illumination, and blurry quality. hence, dl methods must be made more robust under adverse conditions. the advent of new mobile communication technologies presents the challenge of integrating personalized fr applications that can be accessed by mobile users over different clouds and networks. conflicts of interest the authors declare no conflicts of interest. references [1] g. guo, et al., “a survey on deep learning based face recognition,” computer vision and image understanding, vol. 189, article no. 102805, december 2019. 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[89] m. jiang, et al., “retinamask: a face mask detector,” https://arxiv.org/pdf/2005.03950v1.pdf, may 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 294  advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 performance evaluation for stacked-layer data bus based on isolated unit-size repeater insertion chia-chun tsai * department of computer science and information engineering, nanhua university, chiayi, taiwan received 13 march 2019; received in revised form 11 april 2019; accepted 10 may 2019 abstract the data bus of a stacked-layer chip always supports that data of a program are frequently running on the bus at different timing periods. the average data access time of a data bus to the timing periods dominates the program performance. in this paper, we proposed an evaluated approach to reconstruct a 3d data bus with inserted unit-size repeaters to motivate that the average data access time of the bus on a complete timing period can speed up at least 10%. the approach is trying to insert a number of unit-size repeaters into bus wires along the path of a source-sink pair for isolating extra capacitive loadings at each timing period to reduce their access time. the above process is repeated until no any improvement for each access time. each inserted repeater with just one unit size due to the limited space of a chip area and the minor reconstruction of a data bus in practical. the approach has the advantages of uniform repeater insertion, less extra area occupation, and simplified time-to-space tradeoff. experimental results show that our approach has the rapid capable evaluation for a stacked-layer data bus within one millisecond and the saving in average access time is up to 50.81% with the inserted repeater sizes of 70 on average. keywords: stacked-layer chip, 3d data bus, unit-size repeater, average access time 1. introduction for a stacked-layer chip [1], each layer has own local data bus and a number of tsvs (through silicon vias) is used to vertically connect these local data buses to integrate them to be a 3d global data bus. the 3d global data bus consists of a number of 2d local data buses. data are frequently running on the 2d local data bus or 3d global data bus for executing multiple programs. a data access time is defined as the propagation delay from a source to at least one sink at a timing period. for a program with a number of hundreds or thousands timing periods, its average access time is defined as the total data access times divided by the number of timing periods. the average access time dominates the program performance. p4 p1 p2 p3 p6 p5 c3 c2 c5 c4 p4 p1 p2 p3 p6 p5 c’3 c’2 c’5 c’4 (a) extra loading capacitances c2 to c5 (b) extra capacitive loadings are reduced by inserted repeaters fig. 1 data access on the source-sink pair p1-p6 of a 2d local data bus * corresponding author. e-mail address: chun@nhu.edu.tw tel.: +886-5-2721001#5030 advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 198 in nanotechnology, a longer interconnection wire always dominates the propagation delay more than a gate delay because of their incremental wire resistances and capacitances. fig. 1(a) shows a 2d local data bus and there is a bidirectional data access between terminals p1 and p6 at two different timing periods. from the figure, obviously, these extra loading capacitances, c2, c3, c4, and c5 will cause to increase the data access time of the source-sink pair of p1-p6. each extra loading capacitance comes from their branch wire capacitance and terminal capacitive loading along the path of p1-p6 or p6-p1. as shown in fig. 1(b), most of these extra capacitive loadings can be isolated by inserting a bidirectional repeater into each branch wire for the data bus reconstruction. that is, these extra loading capacitances will be dramatically reduced to be c’2, c’3, c’4, and c’5, and c’2 < c2, c’3 < c3, c’4 < c4, and c’5 < c5. the data bus reconstruction will result that the data access time between two source-sink pairs with terminals p1 and p6 can be clearly reduced. the above concept of reconstructing a data bus can be expanded to other source-sink pairs for isolating unnecessary capacitive loadings by inserting repeaters into their branch wires to reduce their access times. for a program ran on a data bus with a number of timing periods, its average access time can thus be reduced and its performance can also be upgraded. however, all the inserted repeaters will also cause extra area occupation. this is the time-to-space tradeoff of a data bus reconstruction, such as the saving in average access time is at least 10% with paying a number of repeater sizes. the repeater insertion was widely applied to a one-way signal path that can effectively reduce their propagation delay, but a few papers discussed the repeater insertion to apply a bidirectional data bus. ismail [2] proposed repeater insertion for the path delay of an rlc-based wire to estimate the delay and their inductive effects of on-chip interconnects. lin [3] presented buffer insertion to construct a clock tree on multimode multivoltage islands. they used adjustable delay buffers (adbs) for controlling the clock delay under a boundary skew. ghoneima [4] introduced the optimal positioning of interleaved repeaters in bidirectional buses. his solution was in focus to reduce noise interference between buses. acton [5] summarized some studies of signal repeater insertion in multi-source multi-sink data bus. daneshtalab et al. [6] proposed an appropriate bus isolation strategy for a 3d stacked-layer chip and had a high-performance inter-layer bus structure (hibs). the hibs can reduce the complexity of bus arbitrators and make the saving in the propagation delay of data communication. thakkar et al. [7] introduced a new architecture called 3d-wiz that is used for reducing the interaction overloading between data bus of drams. the architecture can reduce their access times among any drams. cho et al. [8] presented the analysis of system bus considering the interconnection of tsvs on a stacked-layer soc (system-on a chip). they found the maximum throughput of the system bus of a 3d stacked-layer chip depending on the data bandwidth. mohamed [9] introduced a master-slave data access by adding nocs (network-on-chips) among multiple processors and there was a number of data interchange rules that would limited the access time between processors. khan et al. [10] analyzed the performance for current noc simulation tools in terms of latency, throughput, and energy consumption, but this comparison was just for 2d nocs. tsai [11-12] first conducted repeater insertion and sized the repeaters to minimize the propagation delay for a 3d data bus based on rc delay model, but they do not to consider the capacitive loading effect of un-accessed local data buses. tsai [13] created an effective method associated with embedded isolated switches [14-15] and inserted repeaters for a 3d data bus to reduce their critical access time, but no any considerations about the pre-evaluation in average access time for a data bus reconstruction. most of the above reconstructed data bus methods were based on the repeater insertion and sized them as possible for maximally reducing the data access time. these approaches can decrease the access time effectively, but their data bus would be required to have extra areas for inserting different-size repeaters. this causes the incremental difficulty for reconstructing a data bus at the post refinement step in physical design. the above problem for the optimal solution in the time-to-space tradeoff (data access time minimization vs. repeaters’ locations and sizes) by inserting repeaters into a data bus had been approved to be intractable [16]. how to evaluate the data bus of a stacked-layer chip to run well for reducing the average access time? a few papers conduct to this topic and it is the valuable problem for investigation in advance. advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 199 in this work, we proposed an approach to evaluate the bus performance by reconstructing a 3d data bus. with inserting unit-size repeaters into a data bus at each timing period, the average data access time of a bus on a complete timing period can be motivated to speed up at least 10% (here, we call it as basic performance ratio). the approach is trying to insert a number of unit-size repeaters to isolate most of extra capacitive loadings to reduce the access time of each source-sink pair at different timing periods. this process is repeatedly done until no any improvement for each access time. then we can estimate the new average access time of a data bus on a complete timing period. if the saving in average access time with inserted unit-size repeaters is larger than the basic performance ratio, the reconstructed data bus can be accepted for reducing the average access time and applied for most of multiple programs ran on the bus. here, we emphasize the inserted repeater with just a unit size due to the limited space of a chip area and the minor reconstruction of a data bus. the evaluated approach has advantages: uniform repeaters, less extra occupied area, and simplified the time-to-space tradeoff with a basic performance ratio. the demonstrated results show that most of 3d stacked-layer data buses with inserted unit-size repeaters their average access time for any program can be dramatically reduced. 2. problem formulation 2.1. symbols and definitions table 1 shows all the symbols and their definitions that are used to go through the whole article for accordance. table 1 symbols and their definitions symbol definition symbol definition n the total number of terminals of a 3d data bus q the total number of bus wires of a 3d data bus n(n-1) the complete timing period of a 3d data bus pk the kth terminal on a 3d data bus tij the access time from source i to sink j without any inserted unit-size repeaters t’ij the access time from source i to sink j with inserted unit-size repeaters tav the average access time of a 3d data bus without any inserted unit-size repeaters u-tav the average access time of a 3d data bus with inserted unit-size repeaters rw the resistance of a unit-length wire u-size the number of inserted unit-size repeaters cw the capacitance of a unit-length wire rpk the kth unit-size repeater rtsv the resistance of a tsv rb the resistance of a unit-size repeater ctsv the capacitance of a tsv cb the capacitance of a unit-size repeater rfg the resistance of a segment wire (f,g) tb the intrinsic delay of a unit-size repeater cfg the capacitance of a segment wire (f,g) rdi the output driving resistance of a source i r1 the resistance of a bus wire l1 clj the input loading capacitance of a sink j c1 the capacitance of a segment wire l1 c(tg) the lumped capacitance at node g ca the total capacitance of a wiring area a cs the extra capacitance at a node c’a the reduced total capacitance of a wiring area a with inserted unit-size repeaters c’s the reduced extra capacitance at a node with inserted unit-size repeaters cbusj the total capacitance of the jth-layer local bus,e.g., cbus2 m the multiple times of wire capacitance c1 e.g., cs = mc1, m  0 2.2. gartner ś hype cycle phases a 3d stacked-layer data bus as shown in fig. 2 extended from fig. 1, there is a number of n terminals and exists a maximal number of n(n-1) timing periods as well as a number of n(n-1) data access times. the number of n(n-1) timing periods is called the complete timing period of a data bus. generally, an executed program has a number of hundreds or thousands timing periods that data are frequently running on the data bus and these timing periods may cover a complete timing period. if most of data access times for a program at different timing periods can be reduced a little, then its average access time will be decreased, that is, the program performance can thus be promoted. fig. 2(a) shows the bidirectional data access between two terminals p4 located on layer1 and p16 located on layer3 at the different timing periods of a 3d stacked-layer data bus. obviously, their data access times, tp4-p16 and tp16-p4, cover those extra loading capacitances, ca, cb, cc, cd, ce, cf and cbus2. especially, the total capacitance of local bus on layer2, cbus2, will be advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 200 a bigger capacitive loading for their data access. as shown in fig. 2(b), if we insert a number of unit-size repeaters to some bus wires, then most of extra loading capacitances can be reduced to be c’a, c’b, c’c, c’d, c’e, c’f and c’bus2, respectively. thus, their data access times, tp4-p16 and tp16-p4, can be effectively reduced. p16 p13 p14 p15 p10 p7 p8 p9 p4 p1 p2 p3 tsv1 layer1 tsv2 layer2 layer3 p17 p18 p11 p12 p6 p5 cbus2 ca ce cf cd cc cb p16 p13 p14 p15 p10 p7 p8 p9 p4 p1 p2 p3 tsv1 layer1 tsv2 layer2 layer3 p17 p18 p11 p12 p6 p5 c’c c’bus2 c’b c’a c’e c’d c’f (a) extra loading capacitances (b) access time is reduced with inserted repeaters fig. 2 data access on the source-sink pair p4-p16 of a 3d stacked layer in fig. 2(a), the access time tij (tji) from source i (j) to sink j (i) along the path of the source-sink pair of p4-p16 based on elmore -rc delay model [17] is represented as below. ( , ) ( . ) +( )( ( )) 2 t fg gij f g path i j di fg c r r c t   (1) where rdi is the output driving resistance of source i, rfg and cfg are resistance and capacitance of a bus wire (f,g), respectively, and c(tg) is the lumped capacitance of branch rooted at node g. it is noted that c(tg) contains those extra capacitive loadings, ca, cb, cc, cd, ce, cf and cbus2. fig. 3 shows the equivalent -rc circuit based on elmore delay model of fig. 2(b) between terminals p4 located on layer1 and p16 located on layer3 with two tsvs and a number of inserted unit-size repeaters for isolating extra loading capacitances. from the figure, extra loading capacitances c11, c12, and c13 on layer1 are isolated from the inserted unit-size repeaters rp11, rp12, and rp13; extra capacitances c21 and c22 on layer2 are isolated from the inserted unit-size repeaters rp21 and rp22; and extra capacitances c31, c32, and c33 on layer3 are isolated from the inserted unit-size repeaters rp31, rp32, and rp33. a unit-size bidirectional repeater has two equivalent sets of input capacitance cb, intrinsic delay tb, and output resistance rb that are inversely connected in parallel. the access time is the scaled-50% propagation delay based on elmore rc delay model. likely a bus wire, a tsv has also the equivalent rc mode [18] with the resistance rtsv and two half capacitances of ctsv/2. the access time t’ij (t’ji) from source i (j) to sink j (i) along the path of a source-sink pair of p4-p16 with isolated unit-size repeaters is represented as below. + ( ) ( , ) ( . ), ( , ) ( )( ( )) 2 t k fg gf g path i j rp path i j di fgij c r r c t      (2) where c(tg) is the lumped capacitance of branch rooted at node g including the capacitances within those isolated unit-size repeaters rp(k). advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 201 c13 p16 ctsv2/2 ctsv2/2 rtsv2 ctsv1/2 ctsv1/2 rtsv1 cl p 1 6 p 13 p 1 4 p 1 5 p 10 p 7 p 8 p 9 p 4 p 1 p 2 p 3 ts v1 la yer 1 ts v2 lay er2 lay er3 p 1 7 p 1 8 p 1 1 p 1 2 p 6 p 5 c ’c c’ bus 2 c ’b c ’a c ’e c ’d c ’f cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb tb p4 cl cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb tb rd rd c31 rp31 c32 rp32 c33 rp33 c11 rp11 c12 rp12 rp13 c21 rp21 c22 rp22 fig. 3 the equivalent -rc circuit of a source-sink pair p4-p16 shown in fig. 2(b) for a reconstructed data bus with inserted unit-size repeaters, the average access time on a complete timing period is represented as the bus performance. since a unit-size repeater has also including the input capacitance, output resistance, and intrinsic delay, the access times for all the source-sink pairs with inserted repeaters will be affected with each other. thus, we need to estimate a data bus with inserted unit-size repeaters whether its average access time on a complete timing period is decreased or not. that is, we can calculate the saving percentage in the average access time on a complete timing period for the data bus without/with inserted unit-size repeaters. if the saving is over the basic performance ratio, the data bus can be reconstructed with inserted a number of unit-size repeaters that has good performance improvement in average access time. therefore, the problem to evaluate the performance in average access time on a complete timing period for reconstructing the 3d data bus of a stacked-layer chip can be defined as below. given the topology of a stacked-layer data bus that has a number of n terminals and a number of q bus wires on a complete timing period (i.e., the number of n(n-1) timing periods), the objective is to evaluate the possible reconstruction of a data bus by inserting unit-size repeaters into the bus wires such that the saving in average access time with inserted repeaters is at least the basic performance ratio than that of without any inserted repeaters, where the basic performance ratio depending on the user’s definition, such as 10 %. 3. performance evaluation of a stacked-layer data bus 3.1. the estimation of a unit-size repeater insertion to understand the effects in data access time of a source-sink pair, it is required to make the estimation of a data access time before/after inserting a unit-size bidirectional repeater into a bus wire. as shown in fig. 4(a), the access time tij from advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 202 source i to sink j along the bus wire l1 based on the elmore delay model can be obtained. if a sink connects the wire segments of a subtree, then the sink has the extra loading capacitance cs and the access time tij will be increased, and tij is represented as below. 1 1 1 ( / 2 ) ( )t ij lj li ljs sdi c c c r c c c cr       (3) where r1and c1 are the resistance and capacitance of a wire l1, respectively, rdi is the output driving resistance of source i, and cli and clj are the input loading capacitances of source i and sink j, respectively. cli rdj rdi clj source/sink i l1 source/sink j cs (a) extra capacitance cs unit-size repeater cli rdj rdi clj source/sink i l1 source/sink j c’s (b) cs is reduced to be c’s cli rdj rdi cb rb tb rb cb tb clj source/sink i l1/2 l1/2 source/sink j bidirectional unit-size repeater c’s (c) inserting repeater into the middle of a bus wire l1 fig. 4 the bus wire l1 is inserted into a bidirectional unit-size repeater to reduce the access time tij, we can insert a unit-size repeater to isolate the subtree wires that can largely decrease the extra loading capacitance cs to be c’s, c’s < cs, as shown in fig. 4(b), that is, eq. (3) is updated to be t’ij and t’ij is denoted as below. 1 1 1 ( / 2 ) ( )tij lj li ljs sdi c c c r c c c cr        (4) as shown in fig. 4(c), the access time t’ij from source i to sink j can be reduced in advance by inserting a unit-size bidirectional repeater into the middle of a bus wire l1 if it was enough longer, that is, eq. (4) is updated as 1 1 11 1 1 / 2 / 2 / 2( / 4 ) ( / 2 )( / 4 ) ( )t b b li bdiij lj b b ljs s r c c r c c cc c c r c c c c tr             (5) where rb, cb, and tb are the output resistance, input capacitance, and intrinsic delay of a unit-size repeater, respectively. for simplification, we assume that cs is the multiple times of the wire capacitance c1, that is, cs = mc1, m  0. and c’s is sum of the half of capacitance c1 and the input capacitance cb, i.e., c’s = c1/2+cb if m > 0 and c’s = 0 if m = 0. if the source and advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 203 sink are also a bidirectional unit-size repeater, then rdi = rb and cli = clj = cb. the access times tij and t’ij from source i to j without/with inserted repeaters are respectively derived as follow. 1 1 1 1 1 1 1 1 1 1 1 ( / 2 ) (2 ) ( / 2 ) (2 / 2 ) (m+1/2)r 2 ( 1) , 0 t b b b b b b bs s b b b b ij c c c r c c c r c c mc r c c c c rc r c m r c m r                  　 (6) if m is progressively large, then the access time tij will be increased, but the access time t’ij always keeps a fixed value that is independent of m. with inserting a unit-size repeater into the wire l1, if its access time t’ij is always less than tij and then the reduced quantity in access time of (tij-t’ij) is obviously meaningful. here, we want to know how the wire length l1 can be inserted a unit-size repeater for effectively reducing the access time. 1 1 11 1 1 / 2 / 2 / 2( / 4 ) ( / 2 )( / 4 ) ( )t b b li bdiij lj b b ljs s r c c r c c cc c c r c c c c tr             (7) case 1: m = 0, 2 1 1 1 / 4 2 ( ) / 4 (2 ) 0w wij ij b b b b b bt t rc r c t r c l r c t        (8) where the unit of rw and rb is ω, the unit of cw and cb is pf, and the unit of tb is ps, and the unit of l1 is µm. we can derive the wire length l1 (µm) is 1 2 2 b bb w w r c t l r c   (9) case 2: m > 0, 1 1 2 1 1 / 2 3 ( 1/ 2) ( / 2 (1/ 2 ) ) (3 ) 0 1 1 b b b b b w w w wb b b b b ij ij rc r c m r c t mr c l r c m r c l r c t t t mr c                (10) the wire length l1 (µm) can be formulated as 2 1 0.5 (0.5 ) (0.5 (0.5 ) ) 4 (3 ) 2 w w w w w wb b b b b b b w w r c m r c r c m r c mr c r c t l mr c         (11) 3.2. the effects of data access time with inserted unit-size repeaters due to the strategy of extra capacitive loading isolation is adopted by inserting unit-size repeaters, the access time of a source-sink pair for the shorter path has larger reduction in extra capacitances than the longer path. for a data bus on a complete timing period, all the bus wires are almost inserted with full unit-size repeaters. the data access time of a source-sink pair for the longer path may increase. fig. 5(a) shows its extended data access of a source-sink pair of p4-p16 in fig. 2(b) that has up to the number of six inserted unit-size repeaters, rp14, rp15, rp16, rp34, rp35,and rp36, along their longer path. repeaters rp14 and rp16 are inserted for isolating extra capacitive loading due to the path of p2-p6, rp15 is inserted for the isolation due to the path of p4-p6, rp34 and rp36 are inserted for the isolation due to the path of p14-p18, and rp35 is inserted for the isolation due to the path of p14-p16. fig. 5(b) shows its equivalent circuit of fig. 5(a) that is the updated bus structure with inserted unit-size repeaters. the access time t’ij from source i to sink j along the path of a source-sink pair of p4-p16 with inserted unit-size repeaters is formulated as below. + ( ) ( ) ( , ), ( . ), ( , ) t ( )( ( )) 2 xxb b bx x k r fg gij f g rp path i j rp path i j di fg c r r c c t t      (12) where rp(k) is the number of isolated unit-size repeaters that are not located on the path of p4-p16 and rp(x) is the number of inserted repeaters that are located on the path of p4-p16. advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 204 3.3. the evaluation for reconstructing stacked-layer data bus with inserted unit-size repeaters the evaluated algorithm, evaluate_stacked-layer_databus_reconstruction(), for the bus performance by reconstructing a stacked-layer data bus with inserted unit-size repeaters is introduced in fig. 6 to solve the above problem defined in section 2. the initial step is to read a 3d data bus topology to construct their data structure. then, we calculate the average access time tav of an original 3d data bus without any inserted repeaters on a complete timing period using the function, find_averageaccesstime(), where tav is defined as the total access times divided by the number of n(n-1) timing periods. the for loop in step3 is for each timing of a complete timing period and insert a number of unit-size bidirectional repeaters into the middle of all the branch bus wires along the path of each source-sink pair estimated by eqs. (9) and (11) for isolating the branch capacitive loadings, but at most one repeater is inserted into the middle of a bus wire. the new average access time u-tav of a 3d data bus with inserted unit-size repeaters on a complete timing period is obtained using the same function find_averageaccesstime() in step4. finally, if the saving u-saving in average access time defined as (tav – u-tav) / tav * 100% is larger than the basic performance ratio 10%, then, the 3d data bus can be reconstructed by inserting a number of unit-size bidirectional repeaters in the space depending on the limited chip area. otherwise, give up the reconstruction of a 3d data bus topology. p16 p13 p14 p15 p10 p7 p8 p9 p4 p1 p2 p3 tsv1 layer1 tsv2 layer2 layer3 p17 p18 p11 p12 p6 p5 c’c c’bus2 c’b c’a c’e c’d c’f rp15 rp14 rp35 rp16 rp34 rp36 (a) six inserted unit-size repeaters to the path of p4-p16 c13 p16 ctsv2/2 ctsv2/2 rtsv2 ctsv1/2 ctsv1/2 rtsv1 cl p4 cl rd rd c31 rp31 c32 rp32 c33 rp33 c11 rp11 c12 rp12 rp13 c21 rp21 c22 rp22 cb rb tb rb cb t b cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb t b cb rb tb rb cb tb cb rb tb rb cb tb cb rb tb rb cb cb rb tb rb cb cb rb tb rb cb cb rb tb rb cb t b cb rb t b rb cb t b cb rb t b rb cb t b cb rb tb rb cb t b rp14 rp34 rp15 rp35 rp36 rp16 (b) the equivalent circuit of the bus structure fig. 5 a source-sink pair p4-p16 has six inserted unit-size repeaters and its equivalent circuit advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 205 evaluate_stacked-layer_databus_reconstruction() { /* a 3d data bus topology with the number of n terminals and q bus wires on a complete timing period. */ step1: scan a 3d data bus topology and construct its data structure. step2: compute each source-sink access time of n(n-1) timing periods and get the whole average access time tav by the function of find_averageaccesstime(). step3: for (each timing of a complete timing period) { insert a number of unit-size repeaters to isolate those all the extra capacitive loadings form the source-sink pair; but at most a repeater is inserted the middle of a bus wire. } step4: estimate each source-sink access time of n(n-1) timing periods with inserted unit-size repeaters and calculate the whole average access time u-tav. step5: if (u-saving = (tav – u-tav) / tav * 100% > basic performance ratio 10%) then, the 3d data bus can be reconstructed by inserting a number of unit-size bidirectional repeaters into the space depending on a limited chip area. else, give up the reconstruction of a 3d data bus topology. } fig. 6 the algorithm is used for the evaluation of a data bus performance the time complexity of the proposed evaluated algorithm is o(n 2 ) because the n(n-1) timing periods are executed, where n is the number of terminals. 4. experimental results we have implemented the proposed evaluated algorithm in c language on an i7 cpu@2.7ghz, dual cores with 8gb ram, running ms-windows 10. table 2 shows the parameters of 45nm technology [19] based on elmore rc delay model. terms rw and cw represent the resistance and capacitance of a unit-length wire, respectively. rtsv and ctsv are the resistance and capacitance of a tsv, respectively. rb, cb, and tb denote the output resistance, input capacitance, and intrinsic delay of a unit-size repeater, respectively. table 2 parameters based on 45nm technology a unit-length wire a tsv a unit-size repeater rw cw rtsv ctsv rb cb tb 0.1ω 0.2ff 0.035ω 15.48ff 122ω 24ff 17ps we refer six 3d data bus topologies with 3 stacked layers from [11-12] and reduce them in total length by five times for testing our proposed algorithm. for a data bus, the driving resistances of all the sources and the loading capacitances of all the sinks are assumed to be those parameters of a unit-size repeater. the inserted repeaters into bus wires are also fixed by a unit size due to the limited space of chip area and the minor reconstruction of a data bus. table 3 shows the evaluation in average access time for six 3d data bus topologies that their total lengths are reduced by 5 (marked with r5) on their complete timing periods (marked with -nxn) and 2000 timing periods (marked with -2k), respectively. in the table, #term , #loc, tlength, and #peri are the number of terminals, number of bus wires, total wire length, and number of timing periods, respectively, of a 3d data bus. tav and u-tav are the average access times without/with inserted the number of u-size unit-size repeaters, respectively. u-saving is the saving ratio defined as (tav u-tav) / tav * 100%. since we always try to insert a bidirectional unit-size repeater into each bus wire for conducting the complete timing periods, thus their number of advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 206 u-size unit-size repeaters is near double to the bus wires #loc. for all the cases on their complete timing periods (marked with $r5-nxn) and 2000 timing periods (marked with $r5-2k), their corresponded u-tav and u-saving are almost equivalent with each other, for example, the u-savings of test0r5-nxn and test0r5-2k are 37.09% versus 37.27%. these average access times, u-tavs, have better savings, u-savings, in the range of 37.09% to 60.88% and they are always larger than the basic performance ratio 10%. the results show that all the cases are suitable to reconstruct their data bus by inserting a number of unit-size repeaters for reducing the average access time to any programs with a number of hundred or thousand timings ran on the bus. table 3 the evaluation in average access times tav and u-tav for data buses (their total length is reduced by 5, r5) without/with inserted unit-size repeaters on their complete timing periods and 2000 timing periods, respectively example #term #loc tlength complete timing period ($r5-nxn) 2k timing periods ($r5-2k) #peri tav (ns) u-tav (ns) u-size u-saving #peri tav(ns) u-tav(ns) u-size u-saving test0r5-* 18 38 7510μm 306 0.3625 0.2281 76 37.09% 2000 0.3627 0.2275 76 37.27% casefr5-* 15 29 12069μm 210 0.6078 0.2378 58 60.88% 2000 0.6099 0.2386 58 60.88% casegr5-* 10 21 8797μm 90 0.4419 0.2270 42 48.62% 2000 0.4405 0.2240 42 49.16% casehr5-* 9 20 8538μm 72 0.4393 0.2380 40 45.73% 2000 0.4392 0.2398 40 45.40% casejr5-* 21 44 11166μm 420 0.6117 0.2917 88 52.31% 2000 0.6104 0.2903 88 52.43% casekr5-* 30 58 13776μm 870 0.7686 0.3059 116 60.20% 2000 0.7556 0.3075 116 59.30% *: nxn or 2k we extend the evaluation for all the cases that their total lengths are reduced by 10 (marked with r10). table 4 shows their corresponded u-savings of the cases on their complete timing periods (marked with $r10-nxn) and 2000 timing periods (marked with $r10-2k). like the evaluation in table 3, their u-savings are almost equivalent with each other. it is noted that three cases test0r10-nxn (test0r10-2k), casegr10-nxn (casegr10-2k), and casehr10-nxn (casehr10-2k) on their complete timing periods (2000 timing periods) are failed because their corresponded u-savings have -8.58% (-9.79%), 7.24% (7.27%), and 0.33% (-0.1%) under the basic performance ratio 10%. obviously, these three-case data buses are not suitable for inserting a number of unit-size repeaters. table 4 the evaluation in average access times tav and u-tav for data buses (their total length is reduced by 10, r10) without/with inserted unit-size repeaters on their complete timing periods and 2000 timing periods, respectively example #term #loc tlength complete timing period ($r10-nxn) 2k timing periods ($r10-2k) #peri tav(ns) u-tav(ns) u-size u-saving #peri tav(ns) u-tav(ns) u-size u-saving test0r10-* 18 38 3736μm 306 0.1856 0.2015 76 -8.58% 2000 0.1857 0.2038 76 -9.79% casefr10-* 15 29 6020μm 210 0.2703 0.1889 58 30.11% 2000 0.2703 0.1884 58 30.28% casegr10-* 10 21 4388μm 90 0.1952 0.1810 42 7.27% 2000 0.1942 0.1801 42 7.24% casehr10-* 9 20 4259μm 72 0.1908 0.1901 40 0.33% 2000 0.1907 0.1909 40 -0.10% casejr10-* 21 44 5561μm 420 0.2826 0.2479 88 12.27% 2000 0.2830 0.2480 88 12.35% casekr10-* 30 58 6859μm 870 0.3622 0.2601 116 28.18% 2000 0.3521 0.2610 116 25.89% *: nxn or 2k table 5 the evaluation in average access times tav and u-tav for casek (the total length is reduced by 5 or 10, r5 or r10) without/with inserted unit-size repeaters on their complete timing periods and different timing periods, respectively example #term #loc #peri total length reduced by 5 (casekr5-*k) total length reduced by 10 (casekr10-*k) tlength tav(ns) u-tav(ns) u-size u-saving tlength tav(ns) u-tav(ns) u-size u-saving casekr?-nxn 30 58 870 13776μm 0.7686 0.3059 116 60.20% 6859μm 0.3622 0.2601 116 28.18% casekr?-.1k 30 58 100 13776μm 0.6324 0.3008 116 52.44% 6859μm 0.2581 0.2628 116 -1.82% casekr?-.2k 30 58 100 13776μm 0.6446 0.3019 116 53.16% 6859μm 0.2710 0.2588 116 4.53% casekr?-.3k 30 58 300 13776μm 0.6757 0.3103 116 54.07% 6859μm 0.2798 0.2573 116 8.04% casekr?-.5k 30 58 500 13776μm 0.6875 0.3053 116 55.60% 6859μm 0.2964 0.2594 116 12.48% casekr?-.7k 30 58 700 13776μm 0.6960 0.3067 116 55.94% 6859μm 0.3100 0.2610 116 15.82% casekr?-1k 30 58 1000 13776μm 0.7288 0.3086 116 57.66% 6859μm 0.3252 0.2599 116 20.08% casekr?-2k 30 58 2000 13776μm 0.7556 0.3075 116 59.30% 6859μm 0.3521 0.2610 116 25.89% casekr?-3k 30 58 3000 13776μm 0.7619 0.3038 116 60.13% 6859μm 0.3602 0.2613 116 27.45% casekr?-4k 30 58 4000 13776μm 0.7636 0.3022 116 60.42% 6859μm 0.3603 0.2596 116 27.95% casekr?-5k 30 58 5000 13776μm 0.7670 0.3059 116 60.12% 6859μm 0.3614 0.2588 116 28.38% *: by 5 or 10-.3k: 300 timing periods table 5 presents the evaluation in average access time for the data bus topology casek that the total length is reduced by 5 or 10 (marked with r5 or r10) on their complete timing periods (marked with -nxn) and different number of timing periods (marked with -0.1k to -5k). from the table, the u-savings of casekr5-nxn and casekr10-nxn on their complete timing periods advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 207 are 60.20% and 28.18%, respectively. for the cases casekr5-.1k to casekr5-5k of a 3d data bus at different number of 100 -5000 timing periods, their average access times have good u-savings in range of 52.44% to 60.42% and they are suitable for inserting a number of unit-size repeaters for the access time reduction. for the cases casekr10-.1k to casekr10-5k of a 3d data bus at different number of 100-5000 timing periods, the u-savings of three cases casekr10-.1k, casekr10-.2k, and casekr10-.3k are -1.82%, 4.53%, and 8.04%, respectively are less than the basic performance ratio 10% and they are not suitable for their data bus reconstruction. fig. 7(a) shows the 3d data bus topology of casekr10-nxn with inserting a number of 116 unit-size repeaters. in the figure, two numbers located on the middle of a bus wire are the sizes of an inserted unit-size bidirectional repeater. fig. 7(b) presents all the access times without/with inserted repeaters to each source-to-sink pair on a complete timing period. the real access time (marked with real_time) of each source-sink pair with inserted repeaters is always less than that the required access time (marked with ireq_time) without any inserted repeaters. the average access times without and with inserted repeaters are 0.3622 ns and 0.2601 ns, respectively. the saving in average access time is up to 28.18%. (a) the 3d data bus topology with inserting the number of 116 unit-size repeaters (b) real access times (real_times) with inserted repeaters are less than the required access times (ireq_times) without inserted repeaters fig. 7 the bus topology and all the required and real access times of case casekr10-nxn advances in technology innovation, vol. 4, no. 3, 2019, pp. 197-209 208 5. conclusions the proposed evaluated approach for the bus performance by reconstructing a stacked-layer data bus based on inserted unit-size repeaters on a complete timing period has been successfully applied for estimating whether the average data access time is reduced more or not. inserting a number of unit-size repeaters for a data bus reconstruction can reduce the impact in the requirements of each repeater area. conducting the complete timing period can cover all the possible data accesses for any programs executed on the bus at different timing periods. evaluating the average access time of a data bus can respond the performance of an executed program in practical. therefore, our evaluated approach is simple but very fast and effective. extending work is to investigate different diverse evaluated approaches such that can suit for the various data bus topologies of emerging stacked-layer chips. acknowledgment this work was partially supported by nhu-107 research project subsidy of nanhua university. conflicts of interest the authors declare no conflict of interest. references [1] ee times, the state of the art in 3d ic technologies, november 27, 2013. 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[19] y. cao, w. zhao, e. wang, w. wang, j. velamala, a. balijepali, and s. sinha, "predictive technology model (ptm)," http://ptm.asu.edu, june 1, 2012. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 4-v10n2(2025)-aiti#13935(132-142).docx advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 english language proofreader: chih-wen teng development and improvement of a vacuum fryer and a centrifugal deoiling machine for deep-fried split-gill mushroom production worapong boonchouytan1,*, nantapong pongpiriyadecha2, nutjired kheowsakul3 1department of industrial engineering, rajamankala university of technology srvijaya, songkhla, thailand 2department of mechanical power technology, rajamankala university of technology srvijaya, songkhla, thailand 3program in electrical engineering, rajamankala university of technology srvijaya, songkhla, thailand received 28 june 2024; received in revised form 30 october 2024; accepted 01 november 2024 doi: https://doi.org/10.46604/aiti.2024.13935 abstract this study aims to develop a vacuum fryer and a centrifugal deoiling machine for producing deep-fried splitgill mushrooms. the vacuum fryer prototype includes a fryer, oil heater, vacuum pump, and control system, while the deoiling machine features a steel frame, external barrel, centrifugal barrel, and transmission unit. tests are conducted by frying split-gill mushrooms at 60, 80, and 100 ℃ for 5, 10, and 15 minutes. the deoiling machine removes oil at three rotational speeds (100, 300, and 500 rpm) and deoiling times (1, 3, and 5 minutes). results show that the ideal frying condition is 80 ℃ for 10 minutes, and the optimal deoiling is achieved in 5 minutes at 500 rpm. keywords: deep-fried mushrooms, vacuum frying, deoiling, production process 1. introduction vacuum-fried items are becoming more and more popular as a result of consumer desire for nutritious and safe frying products [1]. nowadays, both smalland large-scale processing enterprises employ vacuum-frying technology to produce goods on a commercial basis. additionally, it is employed to create novel products using crisp fruits and vegetables [2]. the benefits of using vacuum frying (vf) technology to make crispy, deep-fried split-gill mushrooms include reduced oxygen in the system, which leads to less oxidation of the vegetable oil, and faster water evaporation in the finished products as the vegetable oil is heated below 100 ℃. moreover, used oil can be reused for a longer period than conventional frying because it retains most of its quality when exposed to normal atmospheric conditions. because they are equal to their original nature in terms of quality and have an extended shelf life and storage life, processed split-gill mushrooms have a higher value and can generate higher revenue for business owners. the split-gill mushroom farming community enterprise in tha kham sub-district is one of the major mushroom farming locations in hat yai district, songkhla province. due to its health benefits, researchers are interested in using splitgill mushrooms (schizophyllum commune) as a raw material for food and pharmaceutical products [3]. this community enterprise uses a closed greenhouse system with a smart farming control application intended for a closed greenhouse mushroom cultivation system [4] and an automatic spawn block manufacturing system for its mushroom growing [5]. the villagers in the community enterprise make mushroom spawn blocks, steam mushroom spawn blocks, and cultivate * corresponding author. e-mail address: worapong.b@rmutsv.ac.th advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 133 mushrooms every day after finishing their rubber tapping activities in the morning. during harvest season, middlemen visit the farm to collect fresh split-gill mushrooms. however, with a relatively large amount of fresh split-gill mushrooms available, the villagers process them into various value-added products, such as deep-fried split-gill mushrooms. deep-fried split-gill mushrooms are the newest snack made by a group of farmer housewives in this community enterprise, with the assistance and knowledge of academics. the production process of deep-fried split-gill mushrooms involves washing and air-drying to lower the moisture content of fresh mushrooms. the mushrooms are seasoned according to the recipe and then deep-fried over medium heat until they turn orange. they are then taken out to allow the oil to drain for 30 minutes. the deep-fried are weighed and packed into 50-gram portions for later distribution. the members of this community enterprise learned that the reuse of frying oil rapidly deteriorates its quality and gives it a burnt scent, requiring regular frying oil changes. this is since frying under atmospheric conditions requires high temperatures, which also increases the costs. in addition, the oxygen in the air causes deep-fried split-gill mushrooms to lose quality and shorten their shelf life, which also facilitates the oil conversion to free fatty acids. regarding the problems encountered during deoiling, the residual oil in the deep-fried split-gill mushrooms escapes into the container and degrades the quality of the final product. this reduces the shelf life and gives off a rancid scent to the deepfried split-gill mushrooms, affecting the flavor of the product. the extensive deoiling procedure needed for these deep-fried split-gill mushrooms slows down the packaging process [6] and undermines consumer confidence. although split-gill mushroom frying has not been extensively documented in the literature, there is sufficient data to study some relationships in deep-frying. for example, a study showed that higher frying temperatures and longer time resulted in fried banana bracts with higher fat content but lower moisture content. moreover, different rotational speeds and deoiling times resulted in significant differences in fried banana bracts properties, and the ideal production conditions of fried banana bracts properties were frying at 100 ℃ for 20 minutes followed by centrifuging at 1,800 rpm for 5 minutes [7]. studies have been conducted on sonication and microwave treatments for vf to attain ideal frying conditions and enhance the quality of fried products using button mushrooms as a raw material. vf, microwave-assisted vacuum frying (mvf), ultrasound-assisted vacuum frying (uvf), and microwave combined with ultrasound vacuum frying (umvf) techniques were also used to produce the mushroom chips [8]. the effect of ultrasound on the frying rate and quality of fried mushroom chips (fmc) was investigated using mvf. the higher moisture evaporation rate and lower oil content were achieved at optimum conditions of 1,000 w and 90 ℃ [9]. in addition, a deoiling machine for shredded pork was developed which consisted of a 900 × 900 × 1,200 mm steel frame, a barrel with an internal diameter of 800 mm and a depth of 500 mm, and a strainer with a diameter of 250 mm and a depth of 25 mm. the rotation of this deoiling machine was driven by a 2 hp electric motor and a 1,800 w blower was used for hot air drying of the shredded pork [10]. the majority of the vacuum fryers used in the studies were large and unsuitable for frying split-gill mushrooms, which are an agricultural product of small size that requires a short frying time. most of the studies on oil centrifugation focused on vertical centrifugation and found that different product types were affected differently by container size, rotation time, and large barrel rotation speed. designing and constructing a vacuum fryer and a centrifugal deoiling machine that is suitable for users, raw materials, and final products is therefore crucial to the development of the deep-frying process for split-gill mushrooms. to enhance the deep-fried split-gill mushroom products, a centrifugal deoiling machine, and a vacuum fryer must be developed. this is done to improve and preserve nutritional value while reducing oil retention. when designing and building these machines, considerations such as the community enterprise’s output capacity, production area, ease of use, and simple operation must be made. 134 advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 2. research methodology this research presents the design and development of a vacuum fryer and a centrifugal deoiling machine. the test material, split-gill mushrooms, was cultivated by the tha kham community enterprise group in hat yai district, songkhla province. the mushrooms were vacuum-fried at 60, 80, and 100 ℃ for 5, 10, and 15 minutes. after frying, the mushrooms were placed in a basket set within the centrifugal deoiling machine, which operated at three deoiling times (1, 3, and 5 minutes) and three centrifugal speeds (100, 300, and 500 rpm). 2.1. vacuum fryer design [11] the main components of this vacuum fryer included a fryer, an oil heater, a vacuum pump, and a control system. the design was based on the principle of energy balance which was used to determine the quantity of oil and heater power. the base curvature size of the oil heater was intended to resemble that of the fryer. for a uniform temperature distribution, the fryer’s heating element was situated at the bottom. this vacuum fryer was 8 mm in diameter, and operates with 2,000 w of electricity, between 80 ℃ and 130 ℃ (±2 ℃). the fryer was a 2-layer design of 4 mm-thick 304l stainless steel. to support the pot lid and external pressure, the outer layer was a cylindrical barrel with a rim on top. its dimensions were 300 mm in height and 300 mm in diameter, with a capacity of 30 l for oil. the inner layer was a cylindrical strainer with a diameter of 250 mm and a height of 250 mm, which collected and filtered the frying debris. the 1/40.25 hp rotary vane vacuum pump used in this fryer’s vacuum system delivered a 3 cubic feet per minute (cfm) flow rate at 230 v, 50-60 hz and this vacuum system produced a maximum vacuum of 150 microns (500-–550 mmhg). the results showed that the scores on the performance test of vacuum-fried mushrooms processed at 80 ℃ for 10 minutes were as follows: 8.36 ± 1.24 for color, 8.59 ± 1.12 for appearance, 8.70 ± 1.38 for crispness, 8.75 ± 1.28 for odor, 8.60 ± 1.28 for taste, and 8.70 ± 1.28 for overall acceptability, which was higher compared to all other treatments. each of these components, as shown in fig. 1, was housed inside the machine for easy and convenient transportation and operation. fig. 1 vacuum fryer 2.2. design of a centrifugal deoiling machine [12] in this study, a centrifugal deoiling machine with a good operation mechanism and efficiency for the production of deepfried split-gill mushrooms in the community enterprise was developed based on the examination of issues and information. the four primary components of this centrifugal deoiling machine were as follows: (1) a rectangular stainless-steel frame with a 360 × 360 mm base and a height of 560 mm from the base equipped with antivibration rubber feet pads. advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 135 (2) a 360 mm diameter by 370 mm high external cylindrical stainless-steel barrel with carrying handles and a drain hole. (3) a 250 mm diameter by 200 mm high centrifugal cylindrical barrel made of perforated stainless steel. the perforations were 5 mm in diameter. the motor shaft was held in place by a shaft at the bottom of the barrel. it contained an antivibration support and a motor balancing system. (4) a 500 w 24v dc brushless motor-driven gearbox unit with a speed range of 0-1,000 rpm. as shown in fig. 2, a control box was used to rotate the motor clockwise, which regulated the rotational speed of the gearbox unit. fig. 2 centrifugal deoiling machine 2.3. materials and preparation split-gill mushrooms, which grow to a size of 2-3 centimeters and take 7-8 days to mature, used in this study were grown by the split-gill mushroom farming community enterprise in tha kham sub-district, hat yai district, songkhla province. the split-gill mushrooms were harvested, cleaned with clean water, and separated from their bunches. they were then submerged in room temperature water for one hour and allowed to drain. 2.4. experimental design in a vacuum fryer, split-gill mushrooms were cooked for 5, 10, and 15 minutes at 60, 80, and 100 ℃ with a maximum vacuum of 150 microns. deep-fried split-gill mushrooms were packed and sealed in polypropylene (pp) bags and placed at room temperature for an hour. the centrifugal barrel of a deoiling machine was then filled with one thousand grams of deepfried split-gill mushrooms. oil removal tests were performed at 3 deoiling times (1, 3, and 5 minutes) and 3 rotational speeds (100, 300, and 500 rpm). the weight of the deep-fried mushrooms was recorded and utilized in further analysis. 2.5. performance tests (1) volume and weight before and after deep-frying the tests were performed by weighing the drained split-gill mushrooms to three decimal places on a digital scale, and the results were recorded as weight before deep-frying. deep-fried split-gill mushrooms were weighed and the results were reported as weight after deep-frying. the volume and the ratio of fresh weight to dry weight were computed using the weights obtained both before and after deep-frying. (2) deep frying temperature the temperature of the oil used in deep-frying was measured using a thermocouple installed inside the vacuum fryer which reads the oil temperature measurement results from the start of the frying process until the end of the frying time. 136 advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 (3) sensory analysis sensory analysis of the deep-fried mushrooms was performed by evaluating preferences for appearance, aroma, taste, crispness, and overall liking using the 9-point hedonic scale. the test group consisted of 30 students from rajamangala university of technology srivijaya, 10 mechanical engineering personnel, 10 food engineering personnel, and 10 food and nutrition engineering personnel, totaling 60 people. (4) satisfaction with machine operation at the split-gill mushroom farming community enterprise in tha kham sub-district, hat yai district, songkhla province, the use of the centrifugal deoiling machine and the vacuum fryer was used to gauge user satisfaction with machine operation. the following aspects were covered in the satisfaction with machine operations survey: easy operation, machine size and appearance, operational safety, machine usability, operational control, and convenience. twenty members of the splitgill mushroom farming community enterprise in tha kham sub-district, hat yai district, songkhla province were the target group. the scores on each aspect were ranked in descending order. 3. results and discussion the research results and analysis focus on evaluating the performance of the vacuum fryer and centrifugal deoiling machine, examining several critical factors. these include measurements of weight before and after frying, oil temperature during frying, and the effectiveness of the centrifugal deoiling machine in processing crispy split-gill mushrooms. the study further investigates the optimal centrifugal speed relative to deoiling duration and conducts an analysis of variance (anova) to assess the statistical significance of the results. additionally, it includes hunter lab color measurements to assess color consistency and evaluate the physical properties of the fried mushrooms. finally, the study captures user satisfaction with the machine’s operation, providing a comprehensive assessment of both functional performance and user experience. 3.1. volume and weight before and after frying and deep-frying temperature table 1 displays the volume, weight, and deep-frying temperature before and after deep-frying. the split-gill mushrooms that were fried for 15 minutes at 100 ℃ showed the greatest weight loss of 1.25, and dry weight to fresh weight ratio of 1:4.0. the split-gill mushrooms that were fried for 5 minutes at 60 ℃ showed the greatest weight loss of 2.75, and dry weight to fresh weight ratio of 1:1.8. furthermore, the average error of the deep-frying temperature from the target temperature was less than 1 ℃. the deep-frying temperature of 60 ℃ displayed the least error of ±0.57 ℃, while the greatest error of ±0.79 ℃, was recorded at 60 ℃, as shown in fig. 3. (a) 60 ℃ fig. 3 deep-frying temperatures advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 137 (b) 80 ℃ (c) 100 ℃ fig. 3 deep-frying temperatures (continued) as shown in table 1, the results are consistent with the literature [13] that claims that a vacuum fryer is a machine that uses oil as the heat exchange medium and vacuum evaporation to minimize the moisture content of food. this machine can reduce the humidity of the product. the results are also consistent with the literature [14] that found that products produced by vf have lower moisture contents than goods produced by regular pressure cooking. furthermore, compared to the previous literature [15], which found a temperature variation of 5 ℃, the deep-frying temperature of the mushrooms in the vacuum fryer developed in this study exhibited less variance. this would undoubtedly impact the manufacturing process and the quality of the final products. table 1 volume and weight of mushrooms before and after frying and deep-frying temperature temperature (℃) time (minutes) mushroom weight frying temperature (℃) before (kg) after (kg) dry weight: fresh weight 60 5 5 2.75 1:1.8 61.20±0.63 60 10 5 2.30 1:2.1 60.25±0.79 60 15 5 2.45 1:2.0 59.97±0.76 80 5 5 2.20 1:2.2 79.80±0.63 80 10 5 1.80 1:2.7 80.55±0.60 80 15 5 2.00 1:2.5 80.27±0.69 100 5 5 2.05 1:2.4 99.90±0.57 100 10 5 1.30 1:3.8 100.45±0.69 100 15 5 1.25 1:4.0 100.43±0.77 3.2. performance tests of centrifugal deoiling machine for deep-fried split-gill mushrooms results of performance tests of the centrifugal deoiling machine for deep-fried split-gill mushrooms aiming to determine the oil content after the deoiling process for deep-fried split-gill mushrooms produced at 3 rotational speeds (100, 300, and 500 rpm) and 3 deoiling times (1, 3, and 5 minutes) are as shown in fig. 4. fig. 4 oil content of split-gill mushrooms after deoiling 138 advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 the results of the deoiling experiments in fig. 4 show the oil content of deep-fried split-gill mushrooms was affected by both the deoiling time and rotational speed. higher rotational speeds and longer deoiling times reduced the oil content in deepfried split-gill mushrooms. at a rotational speed of 100 rpm and a deoiling time of minutes, the highest oil content was 3.2%. at a rotational speed of 300 rpm and deoiling time of 5 minutes, the highest oil content was 3.9%. at a rotational speed of 500 rpm and deoiling time of 5 minutes, the highest oil content was 4.4%. the less oil content in fried food, the better the quality of the food and the longer its shelf life. 3.3. optimum rotational speed and deoiling times fig. 5 shows the findings of the experiments conducted to determine the optimum rotational speed at three different rotational speeds (100, 300, and 500 rpm) by weighing the deep-fried split-gill mushrooms once every minute until the weight remained constant. fig. 5 optimum rotational speed at different deoiling times as shown in fig. 5, at 100 rpm, the weight was 933 grams following the deoiling process for 15 minutes and remained steady after 13 minutes with no further reduction. therefore, the optimum deoiling time at 100 rpm was 13 minutes. at 300 rpm, the weight was 907 grams following the deoiling process for 15 minutes and remained steady after 10 minutes with no further reduction. therefore, the optimum deoiling time at 300 rpm was 10 minutes. at 500 rpm, the weight was 886 grams following the deoiling process for 15 minutes and remained steady after 9 minutes with no further reduction. therefore, the optimum deoiling time at 500 rpm was 9 minutes. moreover, the oil content of general fried foods ranges from 10% to 40% [16]. according to the results, an experiment at a rotational speed of 500 rpm and a deoiling time of 9 minutes provided a value within this range, namely 11.4%. the other two experiments, which were performed at rotational speeds of 100 and 300 rpm, showed oil contents of 6.7% and 9.3%, respectively, which were not within the recommended oil content for fried food. this deoiling machine has a maximum capacity of 3 kilograms of deep-fried mushrooms and a cycle time of 10 minutes which is equivalent to a maximum production capacity of 18 kilograms per hour. this is consistent with the literature [17] that suggested that the deoiling process of fried food products depended on various factors, including the type of product, deoiling time, and rotational speed. it also depends on the producer and how much value the quality of that type of fried food requires. this is consistent with the literature [18] that suggested that a deoiling machine for fried food could reduce the oil content remaining in fried food efficiently. in addition, the results are consistent with the literature [19] which suggested that the reduced oil content after the deoiling process led to longer shelf life, less moisture, and a decrease in rancidity. in this study, the deoiling machine had a maximum capacity of 3 kilograms of deep-fried mushrooms and a cycle time of 10 minutes equivalent to a maximum production capacity of 18 kilograms per hour, and produced deep-fried mushrooms with 11.40% oil content. advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 139 3.4. analysis of variance (anova) results the anova of the centrifugal deoiling machine for deep-fried split-gill mushroom production was conducted to compare the effects of rotational speed and time on oil removal at 3 rotational speeds (100, 300, and 500 rpm) and 3 deoiling times (1, 3, and 5 minutes). the results are shown in table 2. table 2 analysis of variance for centrifugal deoiling machine source df ss ms f p rotation speed (rpm) 2 778.30 389.15 102.55 0.000 time interval (minutes) 2 2523.63 126.81 332.53 0.000 error 22 83.48 3.79 total 26 33.85.41 s = 1.94798 r1-sq = 97.53% r2-sq(adj) = 97.09% from the analysis of oil removal under different conditions shown in table 2, the coefficient of determination r2 was 97.09%. this implies that the experimental variation due to controllable factors such as tools and equipment was 97.09%. the remaining variation due to uncontrollable factors was 2.91%. therefore, this experimental design is acceptable as r2 was higher than 70%. both rotational speed and deoiling time had significant effects on oil removal, with a p-value of less than 0.05, and is believed to have a direct effect on oil removal. 3.5. color measurement using hunterlab the results of color measurement using the hunterlab system are shown in table 3. it was found that split-gill mushrooms fried at 60 ℃ for 10 minutes had the highest brightness (l*) value of 73.51 ± 0.65 and that split-gill mushrooms fried at 100 ℃ for 15 minutes had the lowest l* value of 51.64 ± 0.98. for redness (a*), split-gill mushrooms fried at 100 ℃ for 15 minutes showed the highest a* value of 9.85 ± 0.68 and that of split-gill mushrooms fried at 80 ℃ for 5 minutes was 5.35 ± 0.86. for yellowness (b*), split-gill mushrooms fried at 60 ℃ for 5 minutes showed the highest b* value of 25.42 ± 0.47 and that of split-gill mushrooms fried at 80 ℃ for 10 minutes was 14.26 ± 1.61. table 3 color measurement using the hunterlab system temperature (℃) time (minutes) color values brightness (l*) redness (a*) yellowness (b*) 60 5 71.18 ± 1.95 8.63 ± 1.58 25.42 ± 0.47 60 10 73.51 ± 0.65 7.15 ± 0.21 19.29 ± 2.40 60 15 72.32 ± 1.48 6.58 ± 0.28 15.88 ± 2.27 80 5 66.68 ± 2.63 5.35 ± 0.86 22.75 ± 1.23 80 10 68.56 ± 2.04 7.64 ± 0.23 14.26 ± 1.61 80 15 69.47 ± 1.23 6.83 ± 1.16 19.47 ± 0.79 100 5 55.88 ± 4.32 7.16 ± 3.83 25.02 ± 3.57 100 10 53.95 ± 3.32 7.95 ± 2.67 16.45 ± 2.45 100 15 51.64 ± 0.98 9.85 ± 0.68 16.66 ± 1.47 according to the results shown in table 3, split-gill mushrooms fried at 60 ℃ for 10 minutes had the highest l*. this was because there was a high heat exchange between the oil and the mushrooms due to the low frying temperature and short frying time. on the other hand, the split-gill mushrooms fried for 15 minutes at 100 ℃ showed the lowest l*. this resulted from overly high frying temperatures and long frying time, which increased heat exchange. this is consistent with the literature [20] that discovered that more heat exchange occurred at higher frying temperatures. it also aligns with the literature [21] that found that frying at a higher temperature and for a longer period reduced l*. 140 advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 3.6. physical characteristics of deep-fried split-gill mushrooms fig. 6 shows the physical characteristics of deep-fried split-gill mushrooms obtained at the optimum rotational speed for three different rotational speeds (100, 300, and 500 rpm) by weighing the deep-fried split-gill mushrooms once every minute until the weight remained constant. (a) 100 rpm (b) 300 rpm (c) 500 rpm fig. 6 physical characteristics of deep-fried split-gill mushrooms at different rotational speeds it is evident from the physical characteristics of the deep-fried split-gill mushrooms in fig. 6 that the deep-fried split-gill mushrooms were less stable at greater rotational speeds. when the physical characteristics of the deep-fried split-gill mushrooms processed at rotational speeds of 100 rpm and 300 rpm were compared, it was evident that the mushrooms could not hold their shape and instead appeared clumped together into clusters. however, the deep-fried split-gill mushrooms loosen and become easier to detach from the clusters after being left for a while before being packed into the bags. furthermore, based on the physical characteristics of deep-fried split-gill mushrooms following the deoiling process, it was discovered that samples of these mushrooms could be kept for a month without oil exuding and no rancid, and remained intact. 3.7. satisfaction with machine operation the survey of satisfaction with the vacuum fryer and deoiling machine developed in this study was conducted with 30 members of the split-gill mushroom farming community enterprise in tha kham sub-district, hat yai district, songkhla province. the results are shown in table 4. table 4 satisfaction with the operation of the deoiling machine aspect score rank easy and straightforward operation 4.80 2 machine size and appearance 4.50 3 operational safety 4.20 5 machine usability 4.30 4 operational control 4.20 5 convenience 4.90 1 mean 4.48 from table 4, convenience showed the highest score with an average score of 4.90, followed by easy and straightforward operation with an average score of 4.80, machine size and appearance with an average score of 4.50, machine usability with an average score of 4.30, and lastly, operational safety and operational control with an average score of 4.20. the respondents showed the highest level of overall satisfaction with the operation of the deoiling machine for deep-fried split-gill mushrooms with an average score of 4.48. the results of the satisfaction survey on the operations of the vacuum fryer and the centrifugal deoiling machine, conducted with a target group of 30 experts comprising 10 mechanical engineers, 10 food engineers, and 10 food and nutrition specialists, are shown in table 5. from table 5, convenience showed the highest score with an average score of 4.50, followed by machine usability with an average score of 4.40, operational safety with an average score of 4.30, operational control with an average score of 4.25, machine size and appearance with an average score of 4.20, and lastly, easy and straightforward operation with an average advances in technology innovation, vol. 10, no. 2, 2025, pp. 132-142 141 score 4.15. the respondents showed the highest level of overall satisfaction with the operation of the deoiling machine for deep-fried split-gill mushroom production with an average score of 4.30. the vacuum fryer machine costs 55,000 baht with a break-even point of 8 months, while the centrifugal deoiling machine costs 40,000 baht with the same break-even point of 8 months. table 5 expert satisfaction survey on vacuum fryer and deoiling machine aspect score rank easy and straightforward operation 4.15 6 machine size and appearance 4.20 5 operational safety 4.30 3 machine usability 4.40 2 operational control 4.25 4 convenience 4.50 1 average score 4.30 4. conclusions the vacuum frying machine is a device that utilizes oil as a heat transfer medium and applies vacuum evaporation to reduce the moisture content in food and the final product. the centrifugal deoiling machine is designed to reduce the residual oil content in fried foods. spinning off the excess oil, extends the product's shelf life and helps reduce rancidity. the physical characteristics of crispy fried split-gill mushrooms subjected to centrifugal oil spinning show that increasing the spinning speed reduces the product's ability to retain its original shape. according to the development and improvement of a vacuum fryer and a centrifugal deoiling machine for vacuum deep-fried split-gill mushroom production, the optimum production conditions are a frying temperature of 80 ℃ for 10 minutes and the deoiling rotational speed of 500 rpm for 5 minutes. the vacuum fryer has been filed for a thai patent under application number 2303002416, submitted on august 30, 2023. additionally, the centrifugal deoiling machine has been filed for a patent under application number 2303003606, submitted on december 7, 2023. both are intended for commercial utilization. acknowledgments this research was funded by the science, research and innovation promotion fund for the year 2023 under the strategic plan, research and innovation at rajamangala university of technology srivijaya. conflicts of interest the authors declare no conflict of interest. references [1] s. manzoor, f. a. masoodi, r. rashid, 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(in thai) [20] c. nampradit, “development of fried kluai hom thong (musa acuminata (aaa group)) product by vacuum frying,” m.sc. dissertation, department agricultural technology, rambhai barni rajabhat university, muang, chanthaburi, 2021. [21] a. jungchud, p. wuttijumnong, k. serikul, and c. kusucharid, “development of vacuum fried sweet potato,” proceedings of the 45th kasetsart university annual conference, pp. 649-655, 2007. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 5-v8n3(2023)-aiti#11508(219-228).docx advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 english language proofreader: jing-heng yen assessing the performance of melted plastic as a replacement for sand in paving block noor a’fiana desyani*, arief sabdo yuwono, heriansyah putra department of civil and environmental engineering, ipb university, bogor, indonesia received 06 february 2023; received in revised form 06 may 2023; accepted 10 may 2023 doi: https://doi.org/10.46604/aiti.2023.11508 abstract plastic waste generates numerous environmental problems, such as garbage accumulation and plastic waste pollution in the oceans. this study aims to evaluate the effectiveness of melted plastic waste as a substitute material in paving blocks. the melted low-density polyethylene (ldpe) plastic is used as the cemented agent in the paving block. after melting, the melted ldpe plastic is mixed thoroughly with sand immediately and forms a paving block mold. the effectiveness of melted plastic as a bonding agent is evaluated based on the parameters of compressive strength, water absorption, and wear resistance. the results show that paving blocks with a melted plastic of 10% reach the required level of 9.39 mpa for the park. hence, using melted plastic in paving blocks can be an alternative strategy to reduce plastic waste. keywords: compressive strength, composite paving block, plastic melter, water absorption, wear resistance 1. introduction one of the environmental issues is the increasing amount of plastic waste. according to the data from indonesian ministry of environment and forestry, plastic waste in indonesia saw a 19% increase in 2020 compared to 2019. the leading causes of the growing volume of plastic waste each year are urbanization and changes in lifestyle [1]. unlike organic waste which can be decomposed by bacteria, plastic waste takes a relatively long time, causing accumulation in the final processing site. other harmful effects of plastic waste include solid plastic waste pollution in the oceans, as well as the introduction of microplastics and nanoplastics [2]. moreover, plastic waste can cause an explosion if it comes into contact with coal waste in the ocean [3]. according to jambeck et al. [4], plastic waste is one of the solid wastes created in significant amounts. world plastic production reached 396 million tons annually in 2018 [5], equivalent to one megaton per day. this number is predicted to double over the next 10-20 years [6-7]. indonesia is in second position as the country that produces the most plastic waste, with the amount of plastic waste in the sea reaching 1.29 million tons annually [8]. in order to prevent additional pollution of the environment and the nearby living beings, plastic waste issues need to be treated seriously. applying the 3r principles, namely reduce, reuse, and recycle, in daily life can help lessen the adverse effects of plastic waste. recycling is the process of converting waste into reusable materials. the benefits of the recycling process include saving energy, reducing pollution, and mitigating land damage and greenhouse gas emissions. to reduce plastic production from new raw materials, it is essential to follow recycling after plastic consumption. singh et al. [9] stated that 90% of plastic waste can be recycled. however, 80% of plastic waste currently ends up in landfills. additionally, 8% is burned, and only 7% is recycled. stockpiled plastic waste emits only 2% of co2 emissions [2], while longterm effects include the need for extensive land areas, as well as soil and groundwater pollution. therefore, a solution is needed to overcome these problems, including recycling plastic waste. * corresponding author. e-mail address: afianadesyani@apps.ipb.ac.id advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 220 heat quickly destroys plastic because it has a low boiling point. with such plastic properties, the melting process can be a simple alternative for plastic recycling in the first step. a plastic melter is a device used to melt raw plastic materials, and its design is kept as simple as possible to ensure easy operation. furthermore, a plastic melter is a tool that melts certain types of plastic waste and reshapes it into new products, such as plastic bricks and concrete blocks. in this study, a plastic melter was developed. the melted plastic was utilized as a substitute material for paving blocks. based on the waste generation study of ipb waste management 2018 [10], the type of plastic used was low-density polyethylene (ldpe). ldpe was the most significant fraction of plastic waste in the research location. this initiative aims to help reduce the environmental burden of plastic waste. in construction, melted plastic is used as a substitute for concrete or paving block aggregate. additionally, various forms of plastic are also used as a substitute for materials, such as plastic pellets, chopped plastic, and melted plastic. mozumder et al. [11] used plastic pellets as a substitute for sand with variations of 0%, 2%, 4%, 6%, 8%, and 10% by weight of sand. the highest compressive strength was achieved when adding 4% plastic, and the compressive strength decreased significantly when adding 8% and 10% plastic. sofyan et al. [12] performed sand substitution with plastic pellets with 10%, 20%, 30%, and 40% variations. the results showed that the compressive strength of concrete with plastic mixtures decreased by 56.06% compared to the control sample (0% plastic). in addition to plastic pellets, chopped plastic is also used as a substitute for aggregate in concrete. nurmaidah and pradana [13] used plastic fiber (chopped plastic) as a substitute for sand with variations of 0%, 3%, 6%, and 9% by weight of sand. with the same w/c value, adding up to 6% plastic can improve the compressive strength of concrete. however, the increase is not significantly different from the control sample (0% plastic). qaidi et al. [14] used chopped plastic as a substitute for sand with variations of 0%, 25%, and 50%. the test results showed that adding plastic decreases compressive strength. previous studies also used melted plastic as a substitute for paving blocks. agyeman et al. [15] researched paving blocks with melted plastic as an alternative binder. the results showed that paving blocks with a plastic mixture increase the compressive strength by approximately 40% more than paving block control at 21 days. sudarno et al. [16] created a paving block using combinations of melted plastic and gravel. the results showed that paving blocks with 50% melted plastic and 50% gravel composition had the highest compressive strength, namely 50.97 mpa. many research studies have shown that using melted plastic as a cement substitute enhances compressive strength. the potential of melted plastic as a sand substitute in paving blocks was investigated in this study. qaidi et al. [14] stated that the compressive strength of concrete with plastic mixtures tends to decrease due to the smooth surface of plastic, which results in a weaker bond. therefore, in this study, melted plastic was mixed thoroughly with sand to produce a stronger bond with the concrete. the plastic was melted to significantly improve the adhesion between the plastic and the cement matrix. the melted plastic was used at 5%, 10%, and 15% of the weight of the sand. 2. material and methods 2.1. material the materials used to make the plastic melter included black hollow iron measuring 3 × 3 cm and 4 × 4 cm, an iron tube with 10 inches diameter and 2 inches diameter, an iron plate with 1 mm thickness, and an analog bimetal thermometer with 3 inches diameter. the materials used to make paving blocks with a mixture of plastic were sand from cimangkok village (sukabumi regency, indonesia), portland composite cement (pcc), water, and plastic waste. the type of plastic waste was ldpe collected from margajaya urban village, bogor city, indonesia. advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 221 2.2. design and construction of plastic melter the plastic melter has a table frame and a closed tubular melting chamber. the capacity of the plastic melting chamber is easily calculated by considering the following factors: the capacity of the melting device is determined at 12 kg, the specific gravity of the melted plastic is 0.94 g/cm3, the multiplier of 110% is used as additional space, and the multiplier of 2 is used as an assumption of the melting time. thus, the melting chamber capacity is 28 l. the melting chamber is determined as a closed tube with a diameter of 25.4 cm and a height of 55 cm. fig. 1 depicts the 3d design of the plastic melter created with sketchup software. (a) isometric view (b) top view fig. 1 3d view of plastic melter plastic melter must be heat-resistant or high-temperature materials to ensure proper melting of the plastic. iron and stainless steel are examples of high-temperature-resistant materials, which are durable and easy to clean. in this study, iron was used to make the plastic melter because it is generally more economical than stainless steel. in operation, the plastic melter is connected to a gas stove and equipped with a thermometer to monitor the melting temperature of the plastic. an output pipe measuring 2 inches with an open-close regulating valve is at the bottom of the melting chamber. based on preliminary research in this study, the plastic melted at a temperature of 180 ℃, as recorded on the top of the plastic melter. according to hasaya etal., plastic melts at 148 ℃ and has a boiling point of 234 ℃ [17]. the plastic melting process was carried out during the performance test to achieve the expected temperature. the performance test results demonstrated that the plastic melter performed well, reaching the planned plastic melting temperature. after heating for 90 minutes and reaching its melting temperature, the valve at the bottom of the melting chamber was opened. finally, the melted plastic can be used as a substitute for sand in paving blocks. 2.3. sample mixture and evaluation table 1 mix variations of paving block sample cement sand plastic water (g/cm3) control 0,34 1,36 0,00 0,17 5% plastic 0,34 1,29 0,07 0,17 10% plastic 0,34 1,22 0,14 0,17 15% plastic 0,34 1,16 0,20 0,17 paving blocks were made with 1 portland cement and 4 sand aggregates [18]. it is the best composition that produces optimal strength. the amount of water in the paving block was determined at 10% of the weight of the sand and cement [19]. advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 222 water helps chemical reactions occur during the binding process in paving blocks. mix variations were made as shown in table 1. by varying the plastic mixture’s percentages to 5%, 10%, and 15% of the weight of sand, plastic melting can replace the need for sand. the procedures for making paving blocks with the addition of melted plastic can be seen in fig. 2. first, the sand is heated using a pan and stirred to distribute the heat evenly. melted plastic is combined with heated sand in a pan during the sample mixture process to prevent the hardening of plastic. after mixing well, the pan is moved from the stove and the cement is added. then, water is added after the melted plastic, heated sand, and cement are thoroughly mixed. the paving block dough is printed and pressed using a manual press. mixing until the pressing process should be completed quickly to prevent the plastic from hardening rapidly. fig. 2 procedures for making paving blocks with a plastic paving blocks were cured for 28 days following concrete curing standards on sni 03-0691-1996 [20]. the curing method was finished by immersing the paving block in water. after the curing period, the paving block evaluation was carried out on compressive strength, water absorption, and wear resistance, referring to the indonesian standard of sni 03-0691-1996 concerning concrete brick (paving block) [20]. compressive strength testing requires a 7.5× 7.5× 7.5 cm cube-shaped sample test, or the sample can be adjusted along its shortest side. based on sni 03-0691-1996, which refers to sni 03-1974-1990 concerning the concrete compressive strength test method, the sample test must be a cube to ensure that the strength is spread evenly across the three sides of the paving block [20]. the compressive strength test was carried out with three samples. the compressive strength test used the universal testing machine (utm). the value of the compressive strength of the paving block can be calculated by: compressive strength p a = (1) where p is the compressive load (n), and a is the sample area (mm2). the water absorption test on paving blocks was carried out by soaking them in water for 24 hours and then weighing them. after that, the paving blocks were dried in the oven for 24 hours at a temperature of ±105℃. water absorption of paving blocks can be obtained by: water absorption 100% m d d − = × (2) where m is the saturated mass (kg), and d is the dry mass (kg). advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 223 the wear resistance test on paving blocks was carried out using a test object measuring 5 × 5 × 2 cm. the wear resistance test procedure refers to sni 03-0028 1987 concerning the test method for cement tiles. wear resistance testing on the paving block can be found by: wear resistance 1.26 0.0246g= + (3) where g is the mass loss (g/min). paving blocks must meet the indonesian standards as presented in table 2. in this study, paving blocks are planned to have d quality. related to the quality of paving blocks, sni 03-0691-1996 regulates the physical properties of paving blocks in each quality, as shown in table 2. table 2 physical properties of paving blocks (sni 03-0691-1996) quality compressive strenght (mpa) wear resistance (mm/min) water absoption (%) usage average min. average min. a 40 35 0.090 0.103 3 pavement b 20 17 0.130 0.149 6 parking areas c 15 12.5 0.160 0.184 8 pedestrian d 10 8.5 0.219 0.251 10 parks 3. result and discussion 3.1. properties test properties testing was carried out on the parameters of specific gravity, water absorption, organic content, silt content, and the distribution of grains of sand aggregate. the results of the sand properties test can be seen in table 3, while the distribution of sand aggregates can be seen in fig. 3. the organic test chart can determine the amount of organic sand. based on astm c40/c40m-11, sand can be used if the organic test results are below the third color on the test chart in fig. 4. according to the results of the properties test in table 3, it is known that the aggregate meets the standards of most properties test parameters so that it can be used. on melted plastic, properties tests were also performed. fig. 5 shows a plastic melter that is used to melt plastic waste. as shown in table 4, the specific gravity of melted plastic is 0.94 g/cm3 based on measurements. fig. 3 distribution of sand aggregate grains table 3 the result of the sand properties test parameter score standard standard specific gravity (ssd) (-) 1.95 1.6 3.2 sni 1970-2008 water absorption (%) 5.65 < 3 sni 1970-2008 organic content (-) 2 < 3 astm c40/c40m-11 sludge levels (%) 0.6 < 5 sk sni s-04-1989-f 0 10 20 30 40 50 60 70 80 90 100 0.01 0.1 1 10 p as si ng (% ) sieve size (mm) advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 224 fig. 4 organic impurities color chart (astm c40/c40m-11) fig. 5 plastic melter table 4 specific gravity of the sand parameter water sand weight (g) 81 76 volume (cm³) 81 81 specific gravity (g/cm³) 1.00 0.94 3.2. density of paving blocks as shown in fig. 6, a comparison of the density of each sample tested is presented. the density of each paving block is observed to decrease as the number of plastic melts increases. it can be attributed to the lower specific gravity of the plastic compared to that of the sand, resulting in a decrease in the volume weight (density) [21]. moreover, the concrete’s pores in paving blocks with a plastic mixture can also lead to a reduction in density between particles. [22]. fig. 6 the density of the paving block 3.3. compressive strength fig. 7 depicts that paving blocks with plastic mixtures have various compressive strengths, namely 7.63-9.39 mpa. the result shows that paving blocks without plastic have higher compressive strength than those with a plastic mixture. according to sni 03-0691-1996, the compressive strength standard for d quality is 8.5-12.5 mpa [20]. the d quality is the lowest quality paving block and can be used for parks. in this study, paving blocks with a 10% plastic mixture satisfy the d quality. however, paving blocks with 5% and 15% plastic mixture do not even meet the compressive strength standard for d quality paving blocks. the results of this study are similar to several previous studies. awodiji et al. [23] used hdpe and pet plastic as a substitute for coarse aggregate with a ratio of 1:1, 1:1.5, and 1:2. the results showed that the sand-hdpe combination had higher compressive strength than regular paving blocks (sand-cement). however, the sand-pet combination had a low 0 200 400 600 800 1000 1200 1400 1600 1800 2000 0 5 10 15 d en si ty ( kg /m ³) percent of plastic (%) wet density dry density advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 225 compressive strength. krasna et al. [24] used plastic with 0%, 25%, 50%, 75%, and 100% of sand. compressive strength decreased with the addition of plastic. the compressive strength decreased by 7% to 59% from the compressive strength of paving blocks without plastic. mercante et al. [25] reported that adding plastic to a mortar reduced its compressive strength. this reduction in compressive strength can be caused by decreased density in the paving block mixture [21]. the smooth and slick plastic surface can weaken the aggregates’ bond. several factors affect the decrease in compressive strength: the lower strength of plastic compared to natural aggregate, the weak bond between cement and plastic, and the increase in air content in concrete [26]. in addition, the low compressive strength value can also influence by the paving blocks made with a hand-operated manual press. fig. 7 compressive strength of a paving block 3.4. water absorption fig. 8 depicts the water absorption test results. it shows how paving blocks without a plastic mixture absorb more water than those with a plastic mixture. according to sni 03-0691-1996, the maximum water absorption is 10% which is included in the d quality of paving blocks [20]. water absorption in paving blocks shows a decreasing trend with the addition of melted plastic. in fig. 8, all paving block samples have more than 10% water absorption, indicating that it does not reach the d quality. awodiji et al. [23] produced paving blocks using different combinations of sand-hdpe, sand-pet, and sand-cement with a ratio of 1:1, 1:1.5, and 1:2. the obtained results indicated that hdpe plastic is better than pet owing to its lower water absorption. the more plastic is used, the lower the water absorption, reaching 0%. paving blocks with a plastic mixture has lower water absorption due to plastic’s nature, which cannot absorb water [27]. plastics tend to pass through the water rather than absorb water [22]. the amount of water absorption also indicates susceptibility to damage [25]. high water absorption causes the pores of the paving block to fill with much water. this condition reduces compressive strength, making it prone to cracking or destruction. paving blocks with low water absorption last longer because they are less susceptible to chemical reactions, physical stress, and mechanical damage [27]. fig. 8 water absorption of a paving block 12.85 7.74 9.39 7.63 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 0 5 10 15 c om pr es si ve s tr en gt h ( m p a) percent of plastic (%) 11.40 11.60 11.80 12.00 12.20 12.40 12.60 12.80 13.00 13.20 13.40 0 5 10 15 w at er a bs or pt io n ( % ) percent of plastic (%) advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 226 3.5. wear resistance the results of the wear resistance test showed that paving blocks without a plastic mixture (the control sample) outperform those with a plastic mixture. as shown in fig. 9, the addition of plastic increases the wear value. suardiana et al. [28] stated that adding plastic can reduce wear, which contradicts this study’s results. one of the factors that affect wear is surface roughness. the plastic mixed in the paving block has a rough texture, causing the surface to wear out quickly. the high wear value on paving blocks can also be caused by cement that does not react (bind) to the plastic. however, as shown in table 2, the minimum wear resistance for quality d paving blocks is less than 0.219. the value of wear resistance in this study was under the quality standard required by sni 03-0691-1996 for concrete brick (paving blocks), classifying it as good [20]. fig. 9 wear resistance of the paving block 3.6. discussion analysis was performed on the compressive strength, water absorption, and wear resistance of paving block quality based on sni 03-0691-1996, revealing that adding plastic to paving blocks tends to reduce the quality of paving blocks. paving blocks with 10% plastic have a compressive strength of 9.39 mpa and qualify as d quality, which can be used in parks. however, paving blocks with 5% and 15% of the plastic mixture do not meet the quality required by sni 03-0691-1996 [20]. regarding water absorption parameters, paving blocks with the plastic mixture in all different proportions result in exceeding 12% absorption. it also did not reach the d quality. compared to the control sample (0% plastic), the paving block with plastic mixture has lower water absorption. on the other hand, the wear resistance of paving blocks with the addition of plastic achieves the expected quality of d. based on the results, paving blocks with the addition of plastic can only fulfill one of the three parameters required for d quality, namely, wear resistance. however, paving blocks with a mixture of plastic have the potential to be used at a 10% variation. paving blocks with a 10% plastic mixture have a higher compressive strength than those of 5% and 15% plastic. melted plastic has a better ability than other forms of plastic to bond with other aggregates in paving blocks. paving blocks with 10% melted plastic meet quality d for compressive strength. furthermore, paving blocks with a melted plastic mixture also have a low water absorption rate. the lower the water absorption capacity, the better quality of the paving block. it means paving blocks will be more durable. further research and testing such as a scanning electron microscope (sem) test is needed to prove the bonding effect of melted plastic aggregate. manually pressed paving can impact the quality of the resulting paving blocks. the density of different paving blocks can be affected by differences in human power when making them, thereby influencing their durability. hence, additional research into the effect of plastic on paving blocks made with an automatic press machine is required. adding plastic to construction materials like paving blocks has good potential. it is a step toward recycling plastic waste and reducing the environmental burden of plastic. yin et al. [29] stated that adding plastic can increase concrete’s tensile strength. it is due to the ability of plastic to resist crack initiation in concrete. furthermore, concrete with a melted plastic mixture also has a smaller decrease in flexural strength than that with the addition of plastic in large size [25]. 0.041 0.05 0.066 0.067 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0 5 10 15 w ea r re si st an ce ( m m /m in ) percent of plastic (%) advances in technology innovation, vol. 8, no. 3, 2023, pp. 219-228 227 4. conclusion this study investigated ldpe plastic waste in the form of melted plastic. in paving blocks, melted plastic substitutes sand at 5%, 10%, and 15% of the sand weight. the compressive strength, water absorption, and wear resistance of conventional and melted plastic forms of paving blocks were analyzed based on sni 03-0691-1996. the following conclusions have been drawn: 1. paving blocks with a plastic mixture have lower compressive strength than the control sample (0% plastic). the compressive strength of paving blocks with a mixture of 10% plastic meets d quality, while the 5% and 15% variations do not meet d quality standards. 2. the water absorption of the paving blocks with the plastic mixture is superior to the control sample (0% plastic). however, it does not meet the d quality standard. as the plastic increases, the water absorption decreases. 3. the wear resistance of paving blocks with a plastic mixture is advantageous. the more plastic, the more wear-resistant paving blocks. according to sni 03-0691-1996, paving block with melted plastic tends to decrease in quality. however, paving blocks with a plastic mixture at a 10% variation have the potential to be used. recycling plastic into substitute materials for paving blocks can help reduce the negative environmental impact of plastic. finally, the results indicate that concrete containing a melted plastic mixture can be used as non-structural concrete. conflicts of interest the authors declare no conflict of interest. references [1] p. o. awoyera and a. adesina, “plastic wastes to construction products: status, limitations and future perspective,” case studies in construction materials, vol. 12, article no. e00330, june 2020. 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(in indonesia) [29] s. yin, r. tuladhar, f. shi, m. combe, t. collister, and n. sivakugan, “use of macro plastic fibres in concrete: a review,” construction and building materials, vol. 93, pp. 180-188, september 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v8n4(2023)-aiti#11678(241-253).docx advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 english language proofreader: chih-wei chang a hidden semi-markov model for predicting production cycle time using bluetooth low energy data karishma agrawal*, supachai vorapojpisut department of electrical and computer engineering, faculty of engineering, thammasat school of engineering, thammasat university, thailand received 02 march 2023; received in revised form 09 june 2023; accepted 10 june 2023 doi: https://doi.org/10.46604/aiti.2023.11678 abstract this study proposes a statistical model to characterize the temporal characteristics of an entire production process. the model utilizes received signal strength indicator (rssi) data obtained from a bluetooth low energy (ble) network. a hidden semi-markov model (hsmm) is formulated based on the characteristics of the production process, and the forward-backward algorithm is employed to re-estimate the probability distribution of state durations. the proposed method is validated through numerical, simulation, and real-world experiments, yielding promising results. the results show that the kullback-leibler divergence (kld) score of 0.1843, while the simulation achieves an average vector distance score of 0.9740. the real-time experiment also shows a reasonable accuracy, with an average hsmm estimated throughput time of 30.48 epochs, compared to the average real throughput time of 33.99 epochs. overall, the model serves as a valuable tool for predicting the cycle time and throughput time of a production line. keywords: bluetooth low energy, received signal strength indicator, hidden semi-markov model, learning problem 1. introduction production is a systematic and organized process that involves a series of interconnected working areas or stages. as shown in fig. 1, the production process includes a specific set of tasks or operations that transform raw materials into finished products. to ensure that the production process is completed on time, it is critical to have accurate and up-to-date product status as well as location information. many industries now use barcodes or rfid [1-2] to track products in production areas. however, the main disadvantage of employing rfid or barcodes is the possibility of human errors. for example, data loss or inaccuracy may occur if the rfid tag/barcode is not read correctly or if a worker scans the wrong rfid tag/barcode. this work uses bluetooth low energy (ble) technology to collect received signal strength indicator (rssi) and timestamp data, which provides the proximity of products being manufactured. even though the scope of ble detection is larger than that of barcode/rfid, the collected data from ble devices usually suffers from signal strength fluctuation and noisy environments. consequently, the application of ble tracking is much more limited compared to barcode/rfid. fig. 1 general example of a production process * corresponding author. e-mail address: karishma.agra@dome.tu.ac.th advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 242 the key performance indicators (kpis) of a production process can be defined by using temporal behaviors [3-4]. examples of kpis for production processes are cycle time and throughput time. cycle time [3] refers to the time it takes to finish a cycle in a particular operation. in the meantime, throughput time [4] is the time it takes to process a certain material from raw material to a final product. based on the kpis, manufacturers can identify areas for improvement, reduce costs, and optimize productivity. therefore, this information is of great significance for manufacturers who attempt to produce highquality products in the shortest timeframe to remain competitive. the traditional method of manually monitoring products to calculate cycle time had various limitations, such as the potential for human errors and limited data collection. at present, manufacturers have adopted a precise and efficient approach to analyzing historical data for cycle time calculation, that is, to use barcode/rfid [1-2] and statistics. the queuing theory is a widely used and traditional approach to analyzing and predicting the temporal properties of production processes. this theory states that production tasks arrive, await maintenance, and then exit once the process is complete. however, queuing models [5] usually consider the timing of each station independently and do not capture the dynamic nature of the whole production process. the main objective of this study is to predict cycle time and throughput time in a production line using rssi values. to achieve this, hidden semi-markov models (hsmm) are used to analyze the rssi and timestamp data. the paper presents an algorithm to determine the model parameters. the study contributes to estimating both cycle and throughput time by using rssi values. furthermore, it is a new approach compared to previous studies [6] that mainly focused on tracking and monitoring activities. this paper provides a more specific and comprehensive version of the work [7] previously presented, including detailed explanations and additional experiments. the paper is structured as follows: section 2 provides a background on ble technology and introduces the concept of hsmm. while section 3 elaborates on the problem and presents mathematical solutions based on rssi-based data. in section 4, three experiments are conducted in numerical, simulation, and real-world settings. section 5 analyzes three case studies to demonstrate the practical application of the proposed method. finally, section 6 discusses and concludes how the cycle time of a product can be computed with the mathematical solutions presented in this paper. 2. backgrounds this section provides an overview of ble technology and introduces the concept of hsmm (hidden semi-markov model). it presents the fundamental characteristics of ble and its practical applications. furthermore, it discusses the potential use of hsmm as a solution to enhance the capabilities of ble networks in comprehending the attributes of the production process. 2.1. bluetooth low energy (ble) technology ble [6-7] technology offers wireless connectivity with low cost, low power consumption, and simple installation. hence, it’s a popular choice for tracking applications. a ble network consists of two types of devices: ble scanners and ble tags. typically, ble tags are battery-powered devices that periodically broadcast their ids, packet-embedded data, and rssi data [8]. ble scanners detect and collect these signals along with a timestamp and send the information to the server. rssi is a measurement that indicates the strength of the signal between a ble tag and a scanner. additionally, higher values represent a stronger and more dependable connection. decibels (dbm) is the standard unit of measurement for rssi. there are two major problems in ble technology to monitor products during production. firstly, the rssi can fluctuate significantly, even if the distance between the ble scanner and tag remains unchanged, due to interference, random noise, and multipath effects [8]. secondly, the inconsistent receiver sensitivity of each device [8] limits the communication range and generates random and insufficient rssi data from the scanner. to illustrate these problems, fig. 2 demonstrates the correlation between the rssi values and distance obtained from an experiment conducted with wemos r32 (esp32) boards. advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 243 various studies have been conducted to resolve the issue of rssi fluctuation in object-tracking applications. two popular methods for indoor localization are trilateration and fingerprinting, which utilize rssi values obtained from multiple ble scanners to estimate the 2d coordinates of a ble tag [8]. however, these methods may not be suitable for production environments due to their large coverage area. proximity detection presents a simpler approach, which estimates an object's location by detecting the presence of a ble tag near a ble scanner [8]. nonetheless, it may have limitations when multiple ble scanners give conflicting results. fig. 2 rssi vs distance of ble devices recent studies have shown that the hidden markov model (hmm) has the potential to explain indoor trajectory with rssi data. for example, han et al. [9] used the ble signal from the smartwatch and implemented an hmm algorithm to determine the user’s indoor location and the most likely sequence based on previous rssi data. similarly, arslan et al. [10] utilized realtime ble rssi data from the construction site and hmm to identify semantic trajectories for extracting worker movement awareness to improve safety. however, conventional hmm approaches do not specify the dwell time of the object in each state, which is not likely to happen in practical scenarios [11-12]. the hsmm has been proposed as an extension of the conventional hmm, including the modeling of the duration of each state. as a result, hsmm has been successfully applied in indoor tracking [11-13] and various other domains, including human-robot collaboration (hrc) [14] in assembly scenarios and machine condition recognition [15]. despite these advancements, there is insufficient literature specifically focusing on understanding and predicting temporal characteristics in production settings. 2.2. hidden semi-markov model (hsmm) the hmm [9-11] is a double-layer stochastic process that uses the markov property to model a sequence of hidden states and observed outputs. the first layer represents the underlying and hidden states of the process, which are not directly observable. the second layer symbolizes the emission states, which are related to the observable and measurable states. the concept of hmm comprises five components, including state (s), initial state probability (π), transition probability matrix (a), observation state (o), and emission probability matrix (b). the emission probability matrix (b) defines the probability of an observation �� at any given time instance t to determine a state � ∈ �1,2, ⋯ , �. the transition probability matrix a represents the probability of moving from one hidden state to another. these transition probabilities are to calculate the probability of states given a sequence of observations. the markov property means that the probability of transitioning from one state to another only depends on the current state. and the hmm uses the markov property as the prediction of the next state based on the current state. since rssi information being used as observation o may not imply the exact location of a device, this paper considers various stages of production, such as material preparation, process, and completion as the set of hidden states s. advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 244 the transition probability matrix a in an hmm is time-independent, which is not suitable for modeling temporal behaviors. the hsmm [14-17] addresses this issue by introducing the variable duration d, which signifies the time in each state. fig. 3 illustrates two primary characteristics of an hsmm that distinguish it from an hmm [13]: (1) the probability of self-transition is assumed to be zero, i.e., � � 0 no return to the same state. (2) the transition from a single state depends upon the sojourn duration or the time spent in that state. these properties of the hsmm allow for the representation of variable state durations, making it possible to estimate the duration or cycle time of each stage in the production process which conventional hmm fails to achieve. (a) hmm (b) hsmm fig. 3 graphical representation of hmm and hsmm in this study, the ble scanning pattern is analyzed by using a discrete time approach, where an epoch is defined as � ∈ �1,2, ⋯ , ∞�. to simplify computations, the duration of each state is treated as a discrete random variable and bounded by an integer value � � 1. the probability of duration for state i have given d is represented by � ���, where � ∈ �1, � and � ∈ �1, ��. ( ) ( )i r tp d p d s i= = (1) the constraint for � ��� is that the sum of � ��� from � � 1 to d is equal to 1 for all states � [7]. there are three basic problems with the hsmm framework used in academic works [7, 13]: (1) likelihood problem: this involves computing the likelihood of an observed sequence o given an hsmm parameter �. (2) decoding problem: this refers to the problem of finding the optimal state sequence given an observed sequence o and an hsmm parameter �. (3) learning problem: this involves estimating an hsmm parameter � from an observed sequence o. it re-estimates the distribution of transitions, emission probabilities, and state durations. the primary objective of this paper is to address the learning problem associated with determining the probability distribution for state durations, which is formulated based on the characteristics of the production process. as for the forward-backward algorithm, it is employed to re-estimate the probability distribution of state durations using a learning problem. advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 245 3. problem statement this study considers a ble system with a ble tag on each product and a ble scanner in each working area to collect data on the movement of products. the main objective of this study is to use hsmm concepts to create a mathematical model that can predict the cycle time of production based on the duration characteristics of each working area. this study formulates the product tracking problem as the hsmm model � � ��, �, �, ��, where a represents the transition matrix with duration probability matrix p for each state, b signifies the emission matrix, and � is the initial state probability. the following kpis are studied in the paper: (1) cycle time: cycle time is the time it takes to complete a single task in a specific working area during the production process. the calculation of the cycle time can be expressed as: i i ict et st= − (2) where �� represents the average cycle time for a product to complete its operations in the working area �. �� is the time when the operation begins, and �� is the time when it ends. (2) throughput time: the throughput time is the total time required for a product to move through the production process, and it represents: 1 throughput time n i i ct = = (3) where �� represents the cycle time for a product to complete its operations in the working area �. the following assumptions are made for a production process based on how raw materials move in the production line to produce finished products [7]. (1) the working areas (stations) are represented as the hidden states � ∈ �1,2, ⋯ , �. each manufactured product is equipped with a specific tag id, and a ble tag is attached to it. ble scanners scan these ble tags and capture rssi values. these rssi values at time � are collected by multiple scanners and used as an observation �� � !��"#,� , !��"$,� , ⋯ , !��"%,�&. (2) the emission probability b consists of ' ���� � (���|�� � �, * , ∑ � are assumed to be fixed but may be updated periodically based on the collected rssi data [11-12]: ( ) ( ) 1 , m m m i t t i i m b o o µ = = n (4) where * , and ∑ , are the mean and covariance for the -�. gaussian component for observed rssi values at the state �, respectively. the gaussian distribution is denoted by / . to simplify the calculation, the assumption is made that the observations are independent across time [12-13]. therefore, ' ���#:�$� can be expressed as the product of the probabilities of observing each rssi data point from epoch �1 to �2, and it can be expressed as: ( ) ( )2 1: 2 1 t i i tt t t tb o b o== ∏ (5) (3) define ���, 1� to represent the probability of moving from area � to area 1 as the ble tag moves through areas sequentially from 1 to n. the calculation of ���, 1� can be simplified as: ( ) 1 ; 1 , 0 ; j i a i j elsewhere    = + = (6) (4) the initial state probability � is set to 1, indicating that every sequence will always begin at state 1. advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 246 this study focuses on the learning problem of the hsmm framework to capture the cycle time of the production process. to re-estimate the duration probability of each state, it is necessary to solve likelihood problems using a forward-backward procedure (��|�� with two subdivided variables: forward and backward. in hsmm, the forward variable 2���� represents the likelihood of being in state � given the partial observations �#:� up to time �, for a given hsmm parameter � [13]. ( ) ( ) ( ) ( ) ( )( )min , * 1: 1:1 , t d t i i it t d t d td i p o s ends at t i p d b oα λ α − − += = = (7) ( ) ( ) ( )* ,1: 1 , 1 n t i i j it i i p o s begins at t iα λ α α = = + = (8) where � � 1, ⋯ , �, � � 1, ⋯ , , 2� ∗��� is the joint probability of obtaining the observation sequence up to time �, and entry to state � begins at the next time � + 1, given the model �. the calculation of the proximity likelihood for a location is performed using the following formula: � ( ) 1 t t i n s arg max iα < < = (9) the definition of the hsmm backward variable 5� ∗��� can be found in formula [13]: ( ) ( ) ( ) ( ) ( ) , * : : 11 , t t d t i i it t t d t t dd i p o s begins at t i p d b oβ λ β − + + −= = = (10) ( ) ( ) ( )* ,: 1 1, n t i i j tt t j i p o s ends at t jβ λ α β = = − = (11) where � � �, ⋯ ,1, � � 1, ⋯ , , 5� ∗��� is the probability of the partial observation sequence from time � to the end, given that the system leaves the state � at the previous time � − 1 and with a model �. the re-estimation of the duration probability �̂ ��� matrix, based on the forward and backward variables, is expressed as [13]: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 1 * * 1 : 11 1 * * 1 : 11 1 ˆ t d i it t t d t dt i d t d i it t t d t dd t i p d b o i p d i p d b o i α β α β − + − + − += − + − + − += = =    (12) the outline of the learning problem used in the paper is as follows [7]. algorithm 1: re-estimation of � ��� input: a, b, coupled sequences ��8, �8�; 9 � 1,2, ⋯ , : training: set the values of � ��� with uniform distribution initialize the (; ��� matrix loop for 9 � 1, ⋯ , : loop for � � 1, ⋯ , � calculate 2����, 2� ∗���, 5����, 5� ∗��� compute the (; ��� (; ��� � (; ��� + �̂ ��� � ��� � (; ���/� output: � ��� the � ��� parameter in the hsmm represents the probability of the system staying in the state � for a duration of d time units. in other words, the � ��� distribution of state � governs the cycle time for that specific stage of the production process. it is important to note that the �̂ ��� eq. (12) is computed from the entire sequence. to predict temporal properties, a sequence is advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 247 constructed by sampling durations from the transition probabilities and �̂ ���. this allows for the estimation of cycle times and throughput time. overall, the hsmm can be modeled from collected rssi and timestamp data in a production process, and the �̂ ��� parameter plays a key role in estimating these kpis. 4. experiments three studies were conducted to evaluate the performance of the proposed algorithm based on numerical, simulated, and real-world experiments. furthermore, the evaluation aimed to validate the effectiveness of the algorithm across various scenarios and provide empirical evidence of its capabilities. 4.1. numerical experiment in this experiment, 1000 state/observation sequences were based on given hsmm parameters (�, a, b, p). each coupled sequence contains two types of data: observed (rssi) signals and state sequences. hsmm parameters were defined as follows: (1) the number of working areas n is 7. (2) the maximum duration � � 8 epochs. (3) probability distribution matrix ( � �� ���� for the system to leave the state � after d duration is given by. 0 0.6 0.4 0 0 0 0 0 0 0 0 0 0.3 0.1 0.3 0.3 0 0 0 0 0 0.7 0.1 0.2 0 0 0.3 0.4 0.3 0 0 0 0 0 0 0.4 0.2 0.2 0.2 0 0 0.4 0.4 0.2 0 0 0 0 1 0 0 0 0 0 0 0 p           =             (13) (4) the values of rssi are computed using a gaussian mixture model with mean and variance: 50 75 100 100 100 100 100 78 55 80 100 100 100 100 95 78 56 87 100 100 100 100 100 70 50 79 100 100 100 100 100 78 54 80 100 100 100 100 100 79 50 80 100 100 100 100 100 100 53 µ − − − − − − −   − − − − − − −   − − − − − − −   = − − − − − − −   − − − − − − −   − − − − − − −  − − − − − − −   (14) 5 2 1 1 1 1 1 1 3 2 1 1 1 1 1 2 4 2 1 1 1 1 1 3 5 2 1 1 1 1 1 2 3 2 1 1 1 1 1 2 4 2 1 1 1 1 2 2 3 σ           =             (15) the sequence generation is outlined using algorithm 2. then, algorithm 1 is used with the generated data to estimate the probability distribution matrix �̂. algorithm 2: sequence generation input: � � �, *, ?, �, (, is the number of states and m is rssi observations advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 248 output: hidden state s and rssi observations o for � � 1 �@ if � �� 1 �abcbd�be � select a state based on the given � initial probabilities else �abcbd�be � select a state using the previous state and a probability end �fg���@habcbd�be � based on the �abcbd�be and p probabilities, choose the duration for 9 � 1 �@ �fg���@habcbd�be for � 1 �@ i ��-, 9� � generate random value from * and ? with �abcbd�be end end �ejkl� mn�1: �fg���@habcbd�be� � �abcbd�be � � o�, �ejkl� mnp � � o�, @p end 4.2. simulated experiment the matlab bluetooth toolbox enables users to create a simulation environment of ble devices. fig. 4 shows the 2d coordinates of the ble scanners with moving ble tags. this study uses matlab bluetooth toolbox to simulate ble transmission to find rssi values when tags are moved along the given trajectory. one thousand state/observation sequences are generated from the movement of ble tags in the simulated environment. the ble tags are advanced randomly according to the selected duration. fig. 5 provides an example of the observed rssi values and state in a simulated sequence. fig. 4 layout with ble 2-d scanner coordinates fig. 5 example of simulated data 4.3. real-world experiment in a real-world scenario, different stations were prepared to collect rssi data from ble devices using the components: wemos r32 boards as ble tags and scanners, wi-fi access points, and the firebase database. the data collection was performed in a u-shaped area of 7 × 4 m with approximately 2 meters between each scanner as shown in fig. 6. advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 249 (1) wemos r32 boards are programmed as ble scanners that connect with the wifi access point and report id/rssi/timestamp to the firebase database. (2) wemos r32 boards are programmed as ble tags were moved from one working area to another according to a predetermined sequence. (3) each ble tag is reset at the endpoint to renew the tag id. fig. 6 ble scanner allocation in a real-time experiment the scanning period for all ble scanners is set at 5 seconds. 25 sets of data were collected by moving the ble tags through a pre-determined sequence from one working area to the next. as illustrated in fig. 7, the results show that not all scanners can receive the rssi signal. the occupation of the tag in each ble scanner area is determined using the relationship between distance and rssi in fig. 2. fig. 7 rssi measurements in real-world environments 5. discussion this section presents the results of three studies conducted to assess the effectiveness of the algorithm in different scenarios. the objective is to validate its capability in comprehending the characteristics of the production process through empirical evidence. advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 250 5.1. analysis of numerical experiment in this study, the kullback-leibler divergence (kld) [13] is utilized as the distance metric to determine the similarity between the original p and the re-estimated �̂. ( ) � ( )( ) ( ) ( ) � ( )1 d i i i ikl d i p d d p d p d p d ln p d= = (16) the average kld value for the entire system approximately stands at 0.1843. this value is close to zero, indicating that the estimated �qr ��� is nearly equivalent to the actual � ���. to show the similarities, fig. 8 displays a comparison between the predicted duration using hsmm and the actual duration with a range represented by minimum and maximum values. the average throughput time based on numerical data is 28.51 epochs, while the hsmm estimated average throughput time is 27.69 epochs. fig. 9 shows the trend of the average kld values concerning the number of coupled sequences used in the training phase. it demonstrates that the proposed algorithm converges quickly with a reasonable amount of data. as the number of samples increased from 100 to 1000, the kld value decreased from 1.7281 to 0.1843. moreover, the evidence supports that algorithm 1 is a reliable and accurate method for estimating the duration probability. fig. 8 predicted vs actual duration comparison fig. 9 trend of average kld value in the numerical experiment 5.2. analysis of the simulation experiment in the simulated experiment, 1000 sequences were generated, and then algorithm 1 was employed to parameterize an hsmm model. the average throughput time for the simulated sequences was 20.53 epochs, while the estimated throughput time using the hsmm model was 19.89 epochs. this result is promising because it shows that the estimated throughput time is close to the simulated sequences. the study was continued by running simulations and estimations for another 500 state sequences as part of the forecast set. the similarity between the forecasted and simulated sequences is evaluated with run-length encoding (rle) and vector distance. rle is a simple data compression technique that works well for sequences where the same value occurs in many consecutive manners. it encodes the sequence by replacing consecutive repeating values with a single value and its count. for example, the rle input presents in “aaabbcccc” and the output is “3a2b4c”. the vector distance is used to measure the similarity of rle repetitive counts as a vector. the vector distance is calculated by: ( ) 2 x yvector distance = − (17) advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 251 where x represents the simulated data, and y is the forecasted data. for example, the rle of the simulated data x becomes “3a2b4c” and the rle of the forecasted data y becomes “3a2b4c”. in this case, the vector distance between the rle encoded sequences can be calculated using the following formula. ( ) ( ) ( ) 2 2 2 23 3 + 2 2 + 4 3 = 0+0+1 =1− − − (18) the lower the vector distance it becomes, the greater similarity it results in. a value of zero indicates that two sequences are identical. the comparison of vector distances between one sample to 500 samples is depicted in fig. 10. the average vector distance decreased from 3.8531 for one sample to 0.9740 for 500 samples. thus, it indicates that the forecasted and simulated sequences had become more similar. this result shows that the estimated duration becomes more precise as the number of samples increases. fig. 10 vector distance for simulated and forecasted sequences 5.3. analysis of real-world experiment the objective of the real experiment is to demonstrate the effectiveness of algorithm 1 with realistic data. to achieve this, data were collected from 7 ble scanners for 25 ble tags. the dataset was filtered based on tag id to retain the rssi values associated with the scanner number. the filtered data was input into algorithm 1, which is used to re-estimate parameters �̂. fig. 11 compares the state sequences generated by the trained hsmm model to the actual data collected during the experiments. fig. 11 hidden state alignment example advances in technology innovation, vol. 8, no. 4, 2023, pp. 241-253 252 table 1 state durations (unit of 5 secs.) area (state) average cycle time (in epochs) real-world hsmm #1 3.28 2.88 #2 6.68 5.88 #3 5.84 6.16 #4 8.76 8.56 #5 3.36 1.52 #6 4.60 4.44 #7 1.48 1.04 throughput time (in epochs) 33.99 30.48 table 1 presents a comparison of the average state duration values between the collected data and those generated by the proposed hsmm model. the average throughput time for the realistic data is 33.99 epochs (169.95 seconds), while the average throughput time for the hsmm model is 30.48 epochs (152.4 seconds), with a difference of only 3.51 epochs. the difference highlights the accuracy of the hsmm model in capturing the dynamics of the system. the close match between the realistic data and the hsmm model suggests that the model is capable of accurately predicting throughput time and state sequences based on the rssi data. 6. conclusions this study aims to overcome the limitations of previous research by uncovering temporal behavior and identifying potential correlations in the hsmm with rssi data from the production line. to achieve this, the proposed method utilized two key steps. first, the method involved updating duration probabilities using forward and backward procedures. it allows probable determination of observed sequences in an hsmm, which is a crucial aspect of understanding temporal behavior. second, learning procedures were employed to update the duration parameter, enabling the model to adapt and improve its predictions based on the collected data. the proximity between the actual and predicted values in experiments highlights the reasonable accuracy of the hsmm model. it indicates that the proposed method effectively predicted temporal behavior. future work could involve further refinement of the method to include the condition when there is no rssi available. additionally, it is important to note that the limitations of this work include the dependence on accurate and consistent rssi data and the assumption of stationary behavior in the production process. despite this limitation, this study has shown the potential of rssi and timestamp data for predicting production metrics in a manufacturing setting. conflicts of interest the authors declare no conflict of interest. references [1] w. c. tan and m. s. sidhu, “review of rfid and iot integration in supply chain management,” operations research perspectives, vol. 9, article no. 100229, january 2022. 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[17] k. li, c. qiu, x. zhou, m. chen, y. lin, x. jia, et al., “modeling and tagging of time sequence signals in the milling process based on an improved hidden semi-markov model,” expert systems with applications, vol. 205, article no. 117758, november 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 1___aiti#9252___155-168 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 observer-based quadratic guaranteed cost control for linear uncertain systems with control gain variation satoshi hayakawa*, yoshikatsu hoshi, hidetoshi oya graduate school of integrative science and engineering, tokyo city university, tokyo, japan received 11 january 2022; received in revised form 23 april 2022; accepted 24 april 2022 doi: https://doi.org/10.46604/aiti.2022.9252 abstract this study proposes a method for designing observer-based quadratic guaranteed cost controllers for linear uncertain systems with control gain variations. in the proposed approach, an observer is designed, and then a feedback controller that ensures the upper bound on the given quadratic cost function is derived. this study shows that sufficient conditions for the existence of the observer-based quadratic guaranteed cost controller are given in terms of linear matrix inequalities. a sub-optimal quadratic guaranteed cost control strategy is also discussed. finally, the effectiveness of the proposed controller is illustrated by a numerical example. the result shows that the proposed controller is more effective than conventional methods even if system uncertainties and control gain variations exist. keywords: polytopic uncertainty, quadratic guaranteed cost control, observer-based controller, control gain variation, linear matrix inequality (lmi) 1. introduction in the design of control systems for dynamical systems, it is necessary to derive a mathematical model for the controlled system. if the mathematical model represents the control system precisely, then the desired control system can be designed by various control design strategies. however, it is unavoidable that there are some gaps between an original controlled system and its mathematical model, and these gaps are known as “uncertainty.” therefore, robust controller design methods that can explicitly deal with uncertainties have been well studied. a large number of robust control strategies have been proposed [1-3]. most conventional robust controllers have been designed by solving linear matrix inequalities (lmis) and have fixed gains that are designed by considering the worst-case variation for uncertainties. in fact, it is desirable to design robust control systems with not only robust stability but also satisfactory control performance. to achieve this, chang and peng [4] proposed guaranteed cost control. in this design method, there is an upper bound on a given performance index. the degradation of the system performance caused by uncertainties is guaranteed to be below this bound. many studies have adopted this concept [5-7]. in the work of moheimani and peterson [6], the riccati equation approach [5] was extended to uncertain time-delay systems, and a guaranteed cost controller design method that solves a certain parameter-dependent riccati equation was proposed. yu and chu [7] proposed a design method for guaranteed cost controllers for linear uncertain time-delay systems that uses the lmi approach. studies on robust control generally assume that the full state of the controlled systems can be measured. however, in practice, the full state of systems cannot be obtained due to practical constraints. to overcome this problem, some observer-based quadratic stabilizing controllers have been presented [8-11]. for example, oya and hagino [10] proposed an observer-based guaranteed cost controller for polytopic uncertain systems. the polytopic representation allows the structure of uncertainties to be directly represented. * corresponding author. e-mail address: itustellar00@gmail.com advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 on the other hand, keel and bhattacharyya [12] pointed out that it is necessary for a controller to tolerate some uncertainty when the control input is implemented. controller implementation involves the uncertainties inherent in analog-to-digital and digital-to-analog conversion and roundoff errors in numerical computations. thus, a nonzero margin of tolerance is required for the controller design. many design methods that consider control gain variation have been proposed [13-16]. yang et al. [13] proposed a design method for �� control for linear systems with addition control gain variation. famularo et al. [14] considered not only control gain variations but also the uncertainty of the system matrix. oya et al. [15] proposed a design method for a robust controller for linear uncertain systems with control gain perturbation. however, the problem of observer-based quadratic guaranteed cost control for linear uncertain systems with control gain variation has not been discussed. this study proposes a method for designing an observer-based guaranteed cost controller for linear uncertain systems with control gain variation. in this study, the design approach is separated into two steps [10, 17]. in the first step, an observer is designed; in the second step, a feedback controller that guarantees the upper bound on the given quadratic cost function is derived. sufficient conditions for the existence of the proposed controller are given in terms of lmis. the proposed control system can thus be designed using software such as matlab’s lmi control toolbox and scilab’s lmitool. 2. preliminaries this section presents two lemmas that are used in this study. lemma 1 shows the relation between matrices and a positive constant. lemma 2 is the schur complement formula. lemma 1 [16]: for matrices p and h that have appropriate dimensions, the following formula is obtained. 1t t t t ph h p pp h h+ ≤ +γ γ (1) where � is a positive constant. lemma 2 (schur complement formula [16]): for a given constant real symmetric matrix ξ, the following items are equivalent. 11 12 12 22 (i) 0 t ξ ξ  ξ = >  ξ ξ  (2) 1 11 22 12 11 12(ii) 0 and 0t −ξ > ξ − ξ ξ ξ > (3) 1 22 11 12 22 12(iii) 0 and 0t−ξ > ξ − ξ ξ ξ > (4) 3. problem formulation this study considers the linear uncertain system described by the following: ( ) ( ) ( ) ( )x t a x t b u t= +ɺ θ (5) ( ) ( )y t cx t= (6) where � ∈ ℝ�× and � ∈ ℝ�×� denote the known nominal matrices, and (�) ∈ ℝ� , �(�) ∈ ℝ , and �(�) ∈ ℝ� are the vectors of the state, control input, and output, respectively. the full state cannot be measured. in eq. (5), �(�) is supposed to have appropriate dimensions and the following structure: 156 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 1 ( ) n k k k a a a = = +∑θ θ (7) in eq. (7), the matrix � ∈ ℝ�×� represents the known nominal value for system parameters, and the matrix ak, k = 1, 2, ……, n, denotes the structure of the uncertainties. the parameter � � (��, …… , ��)� represents unknown parameters that belong to the following parameter set: 1 | 1, 0 for 1, , n n k k k k nθ θ θ =   ∆ ∈ = ≥ =     ∑≜ ℝ … (8) furthermore, for ∀� ∈ ∆, it is assumed that the pair (�(�), �) and (�, �(�)) are controllable and observable respectively. now the following full-state observer is introduced: ˆ ˆ ˆ( ) ( ) ( ) ( )( ( ) ( ))x t ax t bu t g t y t cx t= + + −ɺ (9) where �(�) ∈ ℝ�×� is the observer gain matrix which is described as: ( ) ( )g t g g t= + ∆ (10) ( ) gg t∆ ≤ε (11) in eqs. (10) and (11), �(�) ∈ ℝ�×� shows the uncertainty for the observer gain matrix, and �� is a known constant that represents the upper bound for ∆�(�). in other words, ∆�(�) fluctuates in the range given in eq. (11). the actual control input �(�) is defined as: ˆ( ) ( ) ( )u t k t x t−≜ (12) where (�) ∈ ℝ ×� is the control gain matrix which satisfies the following relation: ( ) ( )k t k k t= + ∆ (13) ( ) kk t∆ ≤ ε (14) in eq. (14), (�) ∈ ℝ ×� represents the uncertainty of the controller gain matrix, and the known constant �! is the upper bound for ∆ (�). in this study, the control input with ∆ (�) is considered so as to design the observer-based quadratic guaranteed cost controller under control gain variation. namely, the manipulated control input for the uncertain linear system in eqs. (5) and (6) is �(�) ≜ # $(�). fig. 1 shows the configuration of the proposed control system. fig. 1 configuration of the proposed control system 157 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 for the linear uncertain system given in eqs. (5) and (6), the following quadratic cost function is defined: { } 0 ( ) ( ) ( ) ( )t tj x t q x t u t r u t d t ∞ = +∫ (15) where the weighting matrices % ∈ ℝ�×� and & ∈ ℝ × are positive definite and can be selected by designers. by introducing an estimation error vector '(�) ≜ (�) # $(�), from eqs. (5) and (9), the following estimation error system is obtained: ˆ( ) ( ( ) ( ) ) ( ) ( ) ( )ee t a g t c e t a x t= − +ɺ θ θ (16) where �((�) is the matrix given by �((�) ≜ �(�) # �. moreover, an augmented vector ((�) ≜ ( $(�) '(�))� is introduced. then, from eqs. (5), (6), (9), (13), and (16), the following augmented system is derived: ( ) ( ) ( )e ex t x t= ωɺ θ (17) ( ) ( ) ( ) ( ) ( ) ( )e a bk t g t c a a g t c −  ω =  −  θ θ θ (18) moreover, by using the estimated error vector '(�), the control input in eq. (12), and the augmented vector ((�), the quadratic cost function in eq. (15) can be rewritten as follows: 0 ( ) ( ) ( ) e t x e ej x t t x t d t ∞ = γ∫ (19) ( ) ( ) ( ) tq k t r k t q t q q  +γ =      (20) note that because the weighting matrices % ∈ ℝ�×� and & ∈ ℝ × in eq. (18) are positive definite, the matrix γ(�) in eq. (20) is semi-positive definite. applying lemma 2 to eq. (20), the semi-positive definiteness of the matrix γ(�) can be obtained as follows: 1( ) ( ) ( ) ( )t t q k t rk t qq q k t rk t −+ − = (21) the definition of an observer-based quadratic guaranteed cost control is as follows. definition: the control input in eq. (12) is an observer-based quadratic guaranteed cost control for the linear uncertain system in eqs. (5) and (6) and the quadratic cost function in eq. (19) provided that the closed-loop system in eq. (17) is asymptotically stable for ∀� ∈ ∆ and there exists a positive constant +∗( ((0)) that satisfies ./0 ≤ +∗( ((0)). from the above discussion, the objective of this study is to design the observer gain matrix and the control gain matrix that guarantee the upper bound on the quadratic cost function in eq. (19). 4. main results this section shows an lmi-based design method for the observer gain matrix � ∈ ℝ�×� and the control gain matrix ∈ ℝ ×� that ensures the upper bound of the quadratic cost function. it is difficult to design both gain matrices simultaneously because of the uncertainty parameters. thus, the observer gain matrix � is first designed, and then the control gain matrix is determined. 158 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 4.1. design of observer gain matrix this study considers the design of the observer gain matrix � that stabilizes the following system obtained by ignoring the estimate $(�) in eq. (16): ( ) ( ( ) ( ) ) ( )e t a g t c e t= −ɺ θ (22) now, let 2�('̅) ≜ '̅�(�)4('̅(�) be a lyapunov function candidate. 4( ∈ ℝ�×� is a symmetric positive definite matrix. from lemma 1, lemma 2, and a previously reported result [1], a sufficient condition for the asymptotical stability of the system in eq. (22) is obtained as follows: vex ( ) ( ) 0, t t t t e e e e g e g e n y a a y h c c h c c y y i θ θ γ ε θ ε γ  + − − + < ∀ ∈ ∆  −  (23) from eq. (23), the observer gain matrix � can be easily designed as follows: 1 e eg y h −= (24) 4.2. design of control gain matrix in this section, the control gain matrix that minimizes the upper bound on the quadratic cost function in eq. (19) is designed. the following quadratic function is introduced as a lyapunov function candidate: ( ) ( ) ( )t k e e ex x t x tλ≜v (25) where λ ∈ ℝ6�×6� is a symmetric positive definite matrix. the time derivative of the quadratic function 2!( () along the trajectory of the augmented system in eq. (17) can be computed as: ( ) ( )( ( ) ( )) ( )t t k e e ex x t x t= ω λ + λωɺ θ θv (26) because the matrix γ(�) in eq. (20) is semi positive definite, the following inequality is considered: vex( ) ( ) ( ) 0 ,t tω λ + λ ω + γ < ∀ ∈ ∆θ θ θ (27) if a symmetric positive definite matrix λ and a control gain matrix that satisfy the matrix inequality in eq. (27) exist, then the following relation holds: ( ) ( ) ( ) ( ) 0t k e e ex x t t x t< − γ <ɺv (28) namely, the augmented system in eq. (17) is quadratically stable and ((∞) � 0 holds. from '(�) ≜ (�) # $(�), the asymptotical stability of the linear uncertain system in eqs. (5) and (6) is ensured. furthermore, by integrating both sides of the inequality in eq. (27) from 0 to ∞, the following equation can be obtained: * 0 ( ) ( ) (0) (0) ( (0)) e t t e e e e exj x t x t dt x x x ∞ = λ < λ =∫ j (29) therefore, if matrices λ and that satisfy the lmi in eq. (27) exist, the asymptotical stability of the system in eqs. (5) and (6) is ensured and the upper bound on the quadratic cost function in eq. (19) is given by eq. (29). 159 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 now, by introducing the auxiliary parameter 8 ∈ ℝ�, the following matrix is considered (remark 1): ( ) ( ) ( ) t nq i k t rk t q t q q  + +γ =      δ δ (30) from eqs. (20) and (30), the relation γ9(�) # γ(�) ≥ 0 holds. therefore, the inequality in eq. (27) also holds provided that the following condition is satisfied: vex( ) ( ) ( ) 0,t tω λ + λ ω + γ < ∀ ∈ ∆δθ θ θ (31) here, ; ≜ diag(@, @() ≜ λa�(@, @( > 0 ∈ ℝ�×�) and c ≜ @ are defined. then, preand post-multiplying eq. (31) by ;, the condition in eq. (31) can be written as: vex( ) ( ) ( ) 0,t tω + ω + γ < ∀ ∈ ∆δθ θ θs s s s (32) the inequality in eq. (32) is organized as follows: 11 12 vex 12 22 ( ) ( , ) 0 0 0, 0 0( , ) ( , ) t n t e e t t s sq i q s sq qt t ψ ψ + + < ∀ ∈ ∆ ψ ψ                     θ δ θ θ θ (33) 1 1 ( ) ( ) ( ) ( ) ( )t t t t t t t a s s a b b s k t b b k t s s k t r k t sψ = + − − − ∆ − ∆ +w w (34) 12 ( , ) ( ) ( )t e e et sa gcs g t csψ = + + ∆θ θ (35) 22 ( , ) ( ) ( ) ( ) ( )t t t t t e e e e e et a s s a gcs s c g s c g t g t csψ = + − − − ∆ − ∆θ θ θ (36) using lemma 1 and lemma 2, the inequality of eq. (33) can be described as follows: 11 12 * 12 22 vex 1 2 ( ) 0 0 ( ) ( ) 0 0, 0 0 0 t t t e e k m s s s s r i −  ψ ψ        ψ ψ + γ < ∀ ∈ ∆           − +  δ θ θ θ θ ξε w w (37) 2 2 11 1k g n t t t ta s sa b b bb i ss ssψ = + − − + + + + ε α η ε α ξ w w (38) 12 ( ) ( )t e e sa g c sψ = +θ θ (39) 2 22 1 ( ) ( ) ( ) 1 g t t t t e e e e n e e t e e a s s a g c s s c g i s c c s s c c s = + − − + + + ψ θ θ θ β ε β η (40) note that γ9∗ in eq. (37) is the matrix expressed as: * nq i q q q + γ       ≜δ δ (41) 160 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 one can easily see that the matrix γ9∗ is positive definite because its positive definiteness is equivalent to % + δf� # %%a�% � δf� > 0. because the matrix γ9∗ is a positive definite, lemma 2 can be applied to the inequality condition in eq. (37). as a result, the following condition is obtained: ( ) 11 12 2212 1 2 vex 1* 00( ) 0 ( ) 00 0 0( ) 0 00 0 000 0 0 0 0000 0( ) 0 0 0 0,000 0 0 00 00 0 0 0 000 00 0 0 0 0 0 0 0 0 0 0 0 0 − − − γ ψ ψ ψψ − + − −ψ = < − − ∀ ∈ ∆                              δ θ ε θθ ξε αε ξθ β η θ t k tt t eee k m nk n e l e l e ss s ss cs c r i is is cs i cs i s s w w (42) 2 11 t t t t g na s s a b b b b iψ = + − − + +α η εw w (43) 12 ( ) ( )t e esa g c sψ = +θ θ (44) 2 22 ( ) ( ) ( ) t t t e e e e g na s s a g c s s c g iψ = + − − +θ θ θ β ε (45) the condition in eq. (42) is an lmi for ; > 0,c, g > 0, h > 0, i > 0 and j > 0. if the solution ; > 0,c, g > 0, h > 0, i > 0 and j > 0 of the lmi in eq. (42) exists, an observer-based quadratic guaranteed cost control law is obtained as follows: ˆ( ) ( )u t k x t−≜ (46) 1 k s −= w (47) from the above, the following theorem for designing the observer-based quadratic guaranteed cost controller is obtained: theorem 1: by solving the lmi in eq. (23), the observer gain matrix � is derived as � � 4(a��( in advance. if there exists the solution ; > 0,c, g > 0, h > 0, i > 0 and j > 0 for ∃8 > 0 satisfying the lmi, vex( ) 0,ψ < ∀ ∈ ∆θ θ (48) then the control gain matrix can be computed as � c@a� and the control law �(�) � # $(�) becomes an observer-based quadratic guaranteed cost control. 4.3. sub-optimal guaranteed cost control because the lmi in eq. (42) has a convex solution ; > 0,c, g > 0, h > 0, i > 0 and j > 0, it can be optimized by using software such as matlab’s robust control toolbox. in this section, the following optimization problem is considered: , , , , , * ( (0)) subject to eq. (42) and 0, 0, 0, 0, 0minimize e x > > > > > α β η ξ α β η ξ s w j s (49) 161 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 if the optimization problem in eq. (49) is solved, then a sub-optimal observer-based quadratic guaranteed cost control can be obtained. however, the upper bound +∗( ((0)) in eq. (49) depends on the initial augmented vector ((0). note that the error '(0) cannot be utilized because the initial state (0) cannot be completely observed. thus, to avoid this dependence, it is assumed that the initial vector ((0) is a random vector that satisfies em ((0) (�(0)n � f6� and em ((0)n � 0. then, the upper bound on the quadratic cost function in eq. (29) is given as op+∗q ((0)rs � tu{λ}. therefore, the minimization problem of tu{λ} minimized subject to the lmi constraint in eq. (42) can be derived. moreover, by introducing a complementary variable ∑ ∈ ℝ6�×6�, which is a symmetric positive definite matrix, the following relation is considered: 2 2 0 0n n i i σ  σ ≥ λ > ⇔ ≥   s (50) then, the minimization problem of tu{λ} can be transformed into that of tu{∑} because the condition in eq. (50) is an lmi in ∑ and ;. consequently, the optimization problem in eq. (49) can be reduced to the following constrained convex optimization problem: , , , , , , { } subject to eqs. (42) and (50) and 0, 0, 0, 0, 0minimize tr σ σ > > > > > α β η ξ α β η ξ s w s (51) finally, the following theorem can be obtained: theorem 2: if there exists the solution ; > 0,c, g > 0, h > 0, i > 0 and j > 0 that satisfies the constrained convex optimization problem in eq. (51), there exists a sub-optimal observer-based quadratic guaranteed cost control. note that by using the solution of the lmi in eq. (23), the observer gain matrix � is derived as � � 4(a��( in advance. if the solution to the constrained convex optimization problem is obtained, the control gain matrix can be computed as � c@a�. therefore, the control law �(�) � # $(�) is a sub-optimal observer-based guaranteed cost control. remark 1: this study introduced the auxiliary parameter 8 in eq. (30). if 8 is zero, the positive definiteness of the matrix γ9∗ is reduced to the relation % # %%a�% � 0. then, lemma 2 cannot be applied to the inequality in eq. (37). if the parameter 8 is a positive scalar, then the lmi in eq. (42) can be obtained. however, if the parameter 8 is set to a larger value, the result will be more conservative. therefore, 8 is set to be small as possible. 5. simulation this section demonstrates the effectiveness of the proposed method. as an example, the following aircraft model is considered [18]: 0.091 0.097 0 1 0 0 0 0 0 0 1 0 0 0 0 0 5.43 0 0.686 3.62 2.87 0.638 0 0 ( ) ( ) ( ) 0.56 0 0 0.122 0.127 0.459 0 0 0 0 0 0 10 0 10 0 0 0 0 0 0 10 0 10 x t x t u t − −               − − = +    + −       −       −    ɺ ω (52) ( )( ) 0 1 0 0 0 0 ( )y t x t= (53) where the parameter y represents the uncertainties and is assumed to vary in the range of m#1.01.0n. let case 1 and case 2 be y � #1.0 and y � 1.0, respectively; these two cases are the worst cases of the uncertainties. it is assumed that the initial state and the initial estimate are (0) � (1.0 0 0 0 0 0)� and $(0) � (0 0 0 0 0 0)�, respectively. the state variables are 162 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 shown in table 1. this simulation sets the weighting matrix of the quadratic cost function, the parameter 8, and the variations of and � as follows: 5 6 21.0 , 4 .0 , 1 .0 10q i r i −= = = ×δ (54) 1 1 1 1 1 1 ( ) 0 .1(1 .0 | c o s (1 0 ) |) 1 1 1 1 1 1 tk t e t−       ∆ = − π (55) 1 1 1 1 1 1( ) 0 .1(1 .0 | co s (1 0 ) |)( )t tg t e t−∆ = − π (56) in addition, �! and �� are set as �! � 0.35 and �� � 0.25, respectively. by solving the lmi condition in eq. (23), the observer gain matrix � is derived as: ( )10.9786 9.4665 59.8127 11.6423 14.4855 3.4610 t g = − − − (57) then, by applying theorem 2 and solving the constrained convex optimization problem, the control gain matrix is obtained as: 51.3273 1.5326 3.7102 34.5183 1.7920 1.3725 162.0656 7.9559 0.2540 124.4227 1.3723 5.1444 k −  =  − −  (58) consequently, the upper bound on the quadratic cost function op+∗q ((0)rs is obtained as op+∗q ((0)rs � 6.4975 × 10c. this simulation compares the results of the proposed method, the conventional linear quadratic regulator (lqr), and the work of oya et al. [10]. oya et al. [10] proposed a method for designing observer-based quadratic guaranteed cost control for uncertain systems. the control gain matrix in eq. (59) is the result obtained by using the lqr: 0.5272 0.2315 0.2673 0.4336 0.1570 0.0223 0.3295 0.0495 0.0857 0.6478 0.0223 0.1270 k −  =  −  (59) �d in eq. (60) and d in eq. (61) are the observer gain matrix and the control gain matrix obtained from the design method in the work of oya et al. [10]: ( )4 .7663 4 .7328 33.2626 6 .0968 6 .2544 1 .2644 t rh = − − − (60) 9.6020 27.1407 15.0468 6.3814 3.2967 0.8400 4.0787 6.3076 3.9832 5 .2499 0 .8400 0.6510 rk −  =  −  (61) figs. 2-5 and figs. 6-9 show the results of the lqr and the method of oya et al. [10]. from the results, the lqr and the method of oya et al. [10] did not achieve asymptotical stability. figs. 6 and 7 show that the state diverged in case 1 by the method of oya et al. [10]. control gain variation was not considered in the work of oya et al. [10], and thus the system could not be stabilized. table 1 state variables of example aircraft �(�) dimensionless slide-slip velocity (dsv) 6(�) roll c(�) roll rate e(�) yaw rate f(�) aileron angle g(�) rudder angle 163 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 fig. 2 time histories of �(�) # c(�) by lqr (case 1) fig. 3 time histories of e(�) # g(�) by lqr (case 1) fig. 4 time histories of �(�) # c(�) by lqr (case 2) fig. 5 time histories of e(�) # g(�) by lqr (case 2) fig. 6 time histories of �(�) # c(�) by the method of oya et al. [10] (case 1) fig. 7 time histories of e(�) # g(�) by the method of oya et al. [10] (case 1) fig. 8 time histories of �(�) # c(�) by the method of oya et al. [10] (case 2) fig. 9 time histories of e(�) # g(�) by the method of oya et al. [10] (case 2) 164 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 on the other hand, figs. 10-14 show the results for the proposed controller design method. as shown, even in the presence of system uncertainties and control gain variation, the proposed method achieved asymptotic stability. this demonstrates the effectiveness of the proposed quadratic guaranteed cost controller. fig. 10 time histories of �(�) # c(�) by the proposed method (case 1) fig. 11 time histories of e(�) # g(�) by the proposed method (case 1) fig. 12 time histories of �(�) # c(�) by the proposed method (case 2) fig. 13 time histories of e(�) # g(�) by the proposed method (case 2) fig. 14 time histories of the input by the proposed method 6. conclusions this study proposed a method for designing an observer-based quadratic guaranteed cost controller for linear uncertain systems with control gain variation. in the proposed approach, the observer gain matrix was first designed, and then the control gain matrix was determined. the design parameter 8 was introduced. the design of an observer-based quadratic guaranteed cost controller was reduced to an lmi condition. moreover, a robust sub-optimal guaranteed cost controller was investigated. the results of this study are a natural extension of those in the work of oya et al. [10]. although the uncertainty in the input 165 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 matrix has been considered in the work of oya et al. [10], the proposed design method can be easily applied to such a problem. by introducing additional actuator dynamics and constituting an augmented system, the uncertainties in the input matrix are embedded in the system matrix of the augmented system. in future work, the proposed adaptive robust controller synthesis will be extended to a broad class of systems, including uncertain linear systems with time delays and decentralized control for large-scale interconnected systems. in the proposed design method, if the parameter 8 is set to a larger value, the result will be more conservative. therefore, reducing conservatism should also be considered. conflicts of interest the authors declare no conflicts of interest. references [1] h. oya, et al., “observer-based robust control giving consideration to transient behavior for linear systems with structured uncertainties,” international journal of control, vol. 75, no. 15, pp. 1231-1240, october 2002. [2] h. oya, et al., “adaptive robust control scheme for linear systems with structure uncertainties,” ieice transactions on fundamentals of electronics, communications, and computer sciences, vol. e87-a, no. 8, pp. 2168-2173, august 2004. [3] h. oya, et al., “robust control giving consideration to time response for a linear systems with uncertainties,” transactions of the institute of systems, control, and information engineers, vol. 15, no. 8, pp. 404-412, august 2002. [4] s. s. chang, et al., “adaptive guaranteed cost control of systems with uncertain parameters,” ieee transactions on automatic control, vol. 17, no. 4, pp. 474-483, august 1972. [5] s. o. r. moheimani, et al., “optimal quadratic guaranteed cost control of a class of uncertain time-delay systems,” iee proceedings—control theory and applications, vol. 144, no. 2, pp. 183-188, march 1997. [6] i. r. petersen, et al., “optimal guaranteed cost control and filtering for uncertain linear systems,” iee transactions on automatic control, vol. 39, no. 9, pp.1971-1977, september 1994. [7] l. yu, et al., “an lmi approach to guaranteed cost control of linear uncertain time delay systems,” automatica, vol. 35, no. 6, pp. 1155-1159, june 1999. [8] s. h. park, et al., “h∞ control with performance bound for a class of uncertain linear systems,” automatica, vol. 30, no. 12, pp. 2009-2012, april 1994. [9] r. petersen, “a riccati equation approach to the design of stabilizing controllers and observers for a class of uncertain linear systems,” ieee transactions on automatic control, vol. 30, no. 9, pp. 904-907, september 1985. [10] h. oya, et al., “observer-based guaranteed cost control for polytopic uncertain systems,” the japan society of mechanical engineers, vol. 71, no. 710, pp. 89-98, october 2005. [11] s. nagai, et al., “a point memory observer with adjustable parameters for a class of uncertain linear systems with state delay,” proceedings of engineering and technology innovation, vol. 11, pp. 38-45, january 2019. [12] l. h. keel, et al., “robust, fragile, or optimal?” ieee transactions on automatic control, vol. 42, no. 8, pp. 1098-1105, august 1997. [13] g. h. yang, et al., “h∞ control for linear systems with additive controller gain variations,” international journal of control, vol. 73, no. 16, pp. 1500-1506, february 2000. [14] d. famularo, et al., “robust non-fragile lq controllers: the static state feedback case,” proceedings of the 1998 american control conference, vol. 2, pp. 1109-1113, june 1998. [15] h. oya, et al., “guaranteed cost control for uncertain linear continuous-time systems under control gain perturbations,” the japan society of mechanical engineers, vol. 72, no. 713, pp. 72-101, january 2006. [16] k. miyakoshi, et al., “synthesis of formation control systems for multi-agent systems under control gain perturbations,” advances in technology innovation, vol. 5, no. 2, pp. 112-125, april 2020. [17] d. rosinová, et al., “output feedback stabilization of linear uncertain discrete systems with guaranteed cost,” 15th triennial world congress, vol. 35, no. 1, pp. 211-215, july 2002. [18] m. noton, modern control engineering, new york: pergamon press, 1972. [19] s. nagai, et al., “synthesis of decentralized variable gain robust controllers with guaranteed l2 gain performance for a class of uncertain large-scale interconnected systems,” journal of control science and engineering, vol. 2015, article no. 342867, 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 166 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 appendix in this appendix, the extension to ℒ6 gain performance is discussed. the following uncertain system is considered: ( ) ( ) ( ) ( ) ( )xx t a x t b u t d t= + +ɺ θ ω (a1) ( ) ( ) ( )zz t c x t d t= +ɺ ω (a2) where (�) ∈ ℝ� , �(�) ∈ ℝ , i(�) ∈ ℝ� , and y(�) ∈ ℝj are the vectors of the state, input, output, and disturbance, respectively. the following full-state observer is introduced: ˆ ˆ ˆ( ) ( ) ( ) ( )( ( ) ( ))x t ax t bu t g t z t cx t= + + −ɺ (a3) let the input �(�), the estimation error '(�) and the augmented vector ((�) be �(�) ≜ # (�) $(�), '(�) ≜ (�) # $(�), and ((�) ≜ ( $(�) '(�))�, respectively. the augmented system and the estimation error system can be obtained as follows: ˆ( ) ( ( ) ( ) ) ( ) ( ) ( ) ( ( ) ) ( )e x ze t a g t c e t a x t d g t d t= − + + −ɺ θ θ ω (a4) ( ) ( ) ( ) ( )e ex t x t t= ω +ɺ θ ωd (a5) ( ) ( ) ( ) ( ) ( ) ( )e a b k t g t c a a g t c − ω = −       θ θ θ (a6) ( ) ( ) ( ) z x z g t d t d g t d = −       d (a7) please refer to the work of nagai et al. [19] for a definition and a lemma about ℒ6 gain performance. the observer gain matrix � is designed as eq. (24) in section 4.1. to design control gain matrix , the following lyapunov function and hamiltonian are defined: ( ) ( ) ( )t k e e ex x t x tλ≜v (a8) * 2( , ) ( ) z ( ) ( ) ( ) ( ) ( )t t e k eh x t x t z t t t+ −ɺ≜ γ ω ωv (a9) here, (�∗)6 ≜ � and (�) ≜ (f� f�) k/$(l)((l)m � n ((�) are introduced. furthermore, the following equation can be obtained: ( ) ( ) ( ) ( ) ( , ) ( ) ( ) ( )( ) t t t t t zt t e e e t t t z z z p c c t c d x t h x t x t t tt d c d d i                     λ ω + ω λ + λ + = λ + − θ θ ω ωγ t t d t d t (a10) to satisfy �( ( , �) < 0, the following inequality is considered: vex ( ) ( ) ( ) 0, ( ) t t t t t z t t t z z z p c c t c d t d c d d i λ ω + ω λ + λ + < ∀ ∈ ∆ λ + −         θ θ θ γ t t d t d t (a11) ; ≜ diag(@, @() ≜ λa�(@, @( > 0 ∈ ℝ�×�) and c ≜ @ are defined, then preand post-multiplying both sides of eq. (a11) by diagq;, fjr and using lemmas 1 and 2, the following theorem is obtained: 167 advances in technology innovation, vol. 7, no. 3, 2022, pp. 155-168 theorem a: the system in eqs. (a1) and (a2) is asymptotically stable if there exists a solution ; > 0,c, g > 0, h > 0, i > 0, p > 0 and j > 0 satisfying the following lmi: 11 12 22 12 ( ) 0 0 0 0 ( ) 0 0( ) 0 0 0 00 0 0 00 0 0 ( ) 0 00 0 0 00 0 000000 0 00 00000 00 0 0000 0 00 0000 t tz z k tt t tt x z e z e ee t t t t tt t t z z x z z e z z pz z e l n k l e l l z l z gd sc d sc s d gd s c d s c s cs c d dd d g d cs d d id g d cs cs ics i s i cs i i d i d  +ψ ψ ψ − +ψ − + −+ − ψ = − − − − −  θ ε θθ γ θ α ε β η ξ λ vex 0,                  <                  ∀ ∈∆θ (a12) 2 2 11 t t t t g n g na s sa b b b b i iψ = + − − + + +α η ε ξεw w (a13) 12 ( ) ( )t e esa gcsψ = +θ θ (a14) 2 2 22 ( ) ( ) ( ) g g t t t e e e e n na s s a gcs s c g i iψ = + − − + +θ θ θ βε λε (a15) by solving the lmi in eq. (23) in advance, the observer gain matrix � is derived as � � 4(a��( . if the solution of the lmi condition in eq. (a12) is obtained, then the control gain matrix can be computed as � c@a�. therefore, the control law �(�) � # $(�) is the observer-based control. 168 microsoft word 1-v8n2(2023)-aiti#9562(81-99).docx advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 tribological aspects affecting surface durability of tooth-sum altered spur gears: a load sharing approach avil allwyn dsa1,*, joseph gonsalvis2 1department of mechanical engineering, don bosco college of engineering, goa, india 2research advisor, mechanical engineering, st. joseph engineering college, mangalore, india received 01 may 2022; received in revised form 01 june 2022; accepted 03 june 2022 doi: https://doi.org/10.46604/aiti.2023.9562 abstract the performance of tooth-sum altered (ats) gears is determined by the factors influenced by their profile geometry. this study aims to explore the influence of gear geometry modification on tribological aspects that affect surface wear in ats spur gears. a computer code is developed to simulate surface wear numerically, using archard's wear model, greenwood-williamson micro-asperity contact model, and johnson’s load-sharing approach. the outcomes of the study indicate that the low contact ratio ats gears promote the formation of thick oil film owing to reduced specific sliding and increased speed. however, high contact ratio ats gears create unfavorable operating conditions resulting in extreme boundary lubrication. the effectiveness of lubricant oil film in reducing wear in ats gears is associated with its modified profile, sliding velocities, load bearing, operating temperature, and oil viscosity. keywords: altered tooth-sum gear, wear, lubrication, oil film, specific sliding 1. introduction the performance and surface durability of gear drives are greatly affected by the gear geometry, material properties, lubrication, and contact conditions. the gear profile is a macroscopic parameter, which affects almost all aspects of the performance of a gear drive. hence, designers attempt profile modifications to improvise specific design features to fulfill the functional requirements of a gear pair. the tooth-sum altered (ats) gearing [1-3], is a novel type of profile-shifted gearing system, which provides the flexibility of modifying the profile geometry by accommodating different tooth-sums on the same center distance. lubrication in ats gears is influenced by profile modification that affects oil film thickness, sliding velocities, load-bearing, operating temperatures, oil viscosity, and consequently surface wear. a gear tooth contact is a non-conformal engagement under mixed elastohydrodynamic lubrication (ehl) [4], sharing the total load partially between the lubricating oil film and the participating surface asperities. the geometry-driven change in specific sliding and flash temperature at the tooth-contact interface causes variation in oil viscosity conditions, promoting mixed or boundary lubrication with partial metal-to-metal (asperities) surface contact. a favorable fluid film ehl regime can avoid such asperity contacts enhancing surface wear resistance. surface roughness is also an important parameter that influences gear performance and surface wear. under high load, the contact asperities undergo elastic and plastic deformation and cause an increase in friction, resulting in wear. the multi-parameter dependence of damage by wear makes it a complex problem that continues to be a common failure mode experienced by gear transmission systems. * corresponding author. e-mail address: avil.dsa@dbcegoa.ac.in advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 82 the objective of this work is to investigate the influence of tooth-sum alteration on lubrication, load bearing, coefficient of friction, and wear along different regions of the tooth flank. in this analysis, a surface wear model based on archard’s wear formulation [5] and johnson’s load-sharing concept [6] is used along with classical elastohydrodynamic lubrication theory [4] in predicting the tribological factors that influence surface damage in geometry-modified ats gearing. 2. literature review in recent years, a few researchers reported the benefits of gear profile modification by tooth-sum alteration of non-lubricated gears with smooth surfaces operating on a fixed center distance. sachidananda et al. [1] showed it is possible to obtain either low, normal, or high contact ratio gear drives by altering the tooth-sum of a gear pair. they experimentally investigated the surface damage of non-lubricated spur gear contacts and confirmed the design benefits and flexibility of ats gears. sachidananda et al. [2] studied the effects of sliding velocity in ats gears and concluded that negative tooth-sum alterations are better than standard or positive alterations in tooth-sum. dsa and gonsalvis [3] extended the tooth-sum alteration technique to asymmetric gears and studied surface wear in non-lubricated contacts. earlier, johnson et al. [6] proposed a theoretical approach for studying highly loaded lubricated contacts by combining the established elastohydrodynamic theory and greenwood and williamson’s [7] theory of rough random contact surfaces. they proposed the concept of the total load being shared between hydrodynamic pressure and surface asperity contacts. gelinck and schipper [8] used the load-sharing idea and developed a mixed lubrication model to obtain the stribeck curves for line contact problems to predict transitions between lubrication regimes. akbarzadeh and khonsari [9] used the load-sharing approach to develop a model for predicting the performance of spur gears. they validated their model by comparing their predictions with published theoretical and experimental data. ebrahimi serest and akbarzadeh [10] presented a model for predicting the performance of helical gears, using the load-sharing concept for accounting for the contribution of surface roughness and the lubricant in bearing the applied load. kimiaei and akbarzadeh [11] used the load-sharing model to evaluate the performance of so and s+/profile shifted gears. simon [12-14] reported the results of his extensive work on full ehl analysis in different types of gears, investigating the influence of gear design, operating conditions, and lubricant on gear performance characteristics. over the years, researchers on surface wear of spur gears have mainly focused on developing prediction models, enhancing wear resistance by geometry modification and material properties. archard’s general wear equation [5] is a popular choice among researchers for wear prediction in gears having parameters with complex inter-dependency due to its simplicity and reasonably realistic estimate. flodin and andersson [15] proposed a numerical wear simulation model based on archard’s wear formulation employing the single-point contact observation technique. prabhu sekar and sathishkumar [16] reported the possibility of enhancing the wear resistance in spur gears by profile shift. in a study on the wear of asymmetric gears, karpat and ekwaro-osire [17] found that tooth tip relief given could reduce induced dynamic load and wear depth. brandão et al. [18] determined the roughness shape of the pinion tooth flank surface using a combined wear and surface contact fatigue damage model. zhang et al. [19] experimentally investigated the wear and contact fatigue of modified involute gears under minimum lubrication, considering tooth wear evolution. ristivojevic et al. [20] studied the impact of geometric and operational parameters on surface wear and reported lesser wear on the addendum flank and higher wear on the dedendum. ding and kahraman [21] in their work on the interaction between gear dynamics and surface wear presented a set of simulations to demonstrate a two-way relationship between non-linear gear dynamics and surface wear. reviewing the literature on ats spur gears, the study of the tribological aspects affecting surface wear is identified as a research gap. in addition, johnson’s load-sharing concept which combines the classical ehl theory and micro-asperity contact model is identified as an efficient method to solve the mixed ehl problem with fairly good accuracy. advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 83 3. gear geometry modification by tooth-sum alteration it is possible to accommodate different tooth-sums and gear ratios on a specified center distance. while the module � is a parameter that is critical for the magnitude of power transmitted, the gear ratio is important to maintain the required output speed. for a standard gear pair with reference tooth-sum ��� , the operating pressure angle �� and center distance � are the same as the standard pressure angle � and center distance ��� . keeping the center distance the same and altering the reference tooth-sum by a factor to ���, causes the operating pressure angle to change (refer to fig. 1). such gear pairs require a total profile shift coefficient �� to be included for proper meshing [22]. tooth topping of addendum radii of the mating gears by a factor: called tooth topping coefficient ensures adequate root clearance [23]. fig. 1 standard tooth-sum and altered tooth-sum gears the ratio of profile shift coefficient �� on the driver to that of the total profile shift coefficient �� for a gear pair is defined as the profile shift factor �. if the tooth-sum [3] and the center distance of a reference gear pair are altered by a factor and � respectively, it can be shown that: cos cos wφ α φ β = (1) ( ) 2 tan a s w s mz inv inv b x m φ φ α β φ − − = (2) ( ) 2 r s s z y x α β= + × − (3) 1 s x x κ = (4) for a standard tooth-sum (sts) normal contact ratio (ncr) gear pair, � � � 1. for the ats gear system, 0.96 � � 1.04 and � � 1. for the s± profile shifted system, 0.96 � � � 1.04 and � 1. the performance characteristics of altered tooth-sum gears can be studied under a constant load or constant speed condition. the equation for tooth load on a pair of gears transmitting a power p at speed n under constant load can be expressed as: 2 r a t t b p f f nrπ = = (5) advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 84 altering the tooth-sum of a gear pair on a fixed center distance changes the radius of the base circles. to maintain constant load, the speed of the ats gear pair should be changed. the equation for speed relation between the ats and the sts gear pair is given by: r r a rb t a a b t r f n n r f = × × (6) where n, ft, and rb represent the speed, normal load, and radius of the base circles, respectively. the superscripts r and a represent reference gear and altered gear pairs, respectively. for a constant load using ��� � ��� eq. (6) reduces to: r a rb a b r n n r = × (7) 4. load sharing and friction coefficient in ats gears under boundary lubrication in ats gears operating under a boundary lubrication regime, the total load transmitted is assumed to be shared between the oil film and the contacting asperities [6]. the dynamic load ��� shared by a tooth pair at any arbitrary location is equal to the sum of the load carried by the asperities �� and oil film � !, and it can be expressed as: dx hy c f f f= + (8) dividing throughout by ��� eq. (8) can be written as: 1 hy c dx dx f f f f + = (9) defining 1/#� and 1/#$ as load sharing factors for the hydrodynamic part and asperities contact part respectively, eq. (9) can be written as: 1 2 1 1 + =1 γ γ (10) similarly, the total friction force %��� at any location is the sum of the oil film friction force �& ! and asperities contact friction force %���. mathematically: dx hy c c f f fµµ µ= + (11) dividing eq. (11) throughout by ��� and using the definition of 1/#$ from eq. (10), the total friction coefficient % is given by: 2 hy c dx f f µ µ µ γ = + (12) from newton’s law of viscosity, the hydrodynamic friction force �& ! per unit, face width is given by: 1 22 r r hy c v v f a h µ η − = (13) where a is the hertzian half-width of contact, ' is the dynamic viscosity at contact pressure, (� is the rolling velocity of gears and ℎ� is the oil film thickness. using simplified roeland’s equation, lubricant viscosity at any contact pressure and temperature can be found. advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 85 ( ) ( ) 0 02.303 1 1 135 z sig p c t eη η + + ∞= × (14) where zi is called the viscosity pressure index assumed to be 0.6 for mineral oils, '* � 6.315 × 10./01. 23�, and the value of � � 196451. g0 and s0 are dimensionless numbers for lubricant viscosity grade and slope. the hertzian half-width of contact is given by: 8 dx f a e ρ π ′ = ′ (15) 1 2 1 2 ρ ρ ρ ρ ρ ′ = + (16) 2 2 1 2 1 2 1 12 v v e e e − − = + ′ (17) where, using the modulus of elasticity e and the poisons ratio 6, the equivalent modulus of elasticity 78 is defined using eq. (17). using the radius of curvature 9 at any contact location, the equivalent radius of curvature 98 is defined using eq. (16). 5. flash temperature and oil film thickness the operating condition at the contact interface depends upon gear geometry, loading conditions, and lubricant properties as the point of contact glides along the pressure line. the sliding motion in a gear contact increases the temperature of its contact interface, which can break down the lubricating oil film. flash temperature is defined as the instantaneous rise in surface temperature when contact between gear teeth occurs. blok’s flash temperature equation formulated by agma is given as: ( ) ( ) 0.5 0.5 1 20.5 0.8 dl f r r m x f t v v b a µ = − (18) temperature changes the oil viscosity, consequently affecting oil film formation. the central oil film thickness calculation is based on moe’s equation [4]. the following dimensionless numbers are used in defining moe’s numbers. dxf w e ρ = ′ ′ (19) ( )0 1 2r rv v u e η ρ σ + = ′ ′ (20) ehlg eα ′= (21) where w is the dimensionless load parameter, :∑ is the dimensionless speed parameter, < = is called the barus pressure viscosity coefficient. the dimensionless moe’s numbers are defined as: 1 2c c h h u ρ − σ= ′ (22) 1 2m wu− σ= (23) 1 4l guς= (24) moe’s equation for central oil film thickness modified by gelinck and schipper [8] using johnson’s load-sharing method is given as: advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 86 ( ) ( ) 1 3 7 2 7 2 7 3 14 15 7 3 2 7 2 7 2 1 2 1 1 1 1 s s s s s c ri ei rp ep h h h h hγ γ γ γ −− − − − = + + +   (25) 13 ri h m−= (26) 1 52.621 ei h m −= (27) 2 31.287 rp h l= (28) ( )1 8 3 41.311 ep h m l−= (29) 2 5 12 1 7 8 5 ei ri h h s e γ − −   = +     (30) the subscripts ri, rp, ei, and ep denote rigid-isoviscous; rigid-piezoviscous; elastic-isoviscous, and elastic-piezoviscous, respectively. the type of lubrication regime is determined based on the value of the roughness parameter given by: c rms h σ λ = (31) the value of λ > 3 represents full oil film, 1 � λ � 3 represents mixed lubrication regime, and λ � 1 represents boundary lubrication. according to greenwood-tripp’s asperity contact model [24], the average contact pressure can be expressed as: ( ) 2 5 2 8 2 15 rms c d c rms rms h d p n e f σ π β σ β σ − ′ ′ ′= ′ (32) where @8 is the density, �8 is the radius of curvature of the asperities, and a�b� is the composite root mean square surface finish. the �//$ function can be approximated by: ( ) ( ) 6.8045 5 2 44.4068 10 4 >40 hh f h for h σσ σ σ − ≤× − = (33) applying johnson’s concept of load sharing, gelinck and schipper have shown that central pressure is a good quantity to characterize the pressure distribution of rough line contact. mathematically: ( ) 0.5882 1.7 0.442 0.0337 0.4757 2 2 1 1 1.558 rms c fc p n w σ σ γ ρ β ρ γ ρ −−−     ′ ′ ′ ′= +    ′      (34) 2 dx fc f e σ πρ ′ = ′ (35) where eq. (35) gives the variation of contact stress ac� along the line of action. 6. static and dynamic load factors evaluation of static and dynamic loading patterns for ats gears with different values of tooth-sum alteration factors is essential to identify the effect of gear geometry modification on various performance parameters. if d� is the mesh stiffness [25] at any arbitrary contact location for tooth load intensity per unit face width ��, then static load factor �= is defined as the ratio of location-based mesh stiffness to that of equivalent mesh stiffness d<e . it can be expressed as: advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 87 x l eq x λ λ = (36) a gear pair in the mesh can be modeled as a single-degree-of-freedom spring-mass damper system subjected to forced vibration [26] to evaluate dynamic load factors for ats gears. the one dof model considers the influence of mesh stiffness, damping forces, friction forces, and the static transmission error at the mesh interface and is expressed as a time-varying function. the gear pairs are assumed to be of unit face width and free of tooth profile errors. the differential equations of motion for this system can be expressed in the form: eq r eq r eq r m x c x k x f+ + =ɺɺ ɺ (37) 1 2 1 2 e e eq e e m m m m m = + (38) ( ) ( )2 1 1 2 1 1 1 2 1 1 n n e i i e i i i i eq e e m m k m m λ µθ λ µθ = = ± + ± = +   (39) 2 eq eq eq c m kξ= (40) where �< � 1/2�g is the effective mass of the pinion and the gear, f is the static load, and h is the roll angle. equivalent mass, stiffness, and damping coefficient are denoted by �<e , �<e , and i<e . the solution of the differential equation provides relative displacement �� at the contact interface, which is used to evaluate dynamic load2 ��� and dynamic load factors ��= . dx r eq f x λ= (41) dx dl f x f = (42) 7. surface wear in gears surface wear in gears is a material attrition phenomenon from the contacting surface subjected to partial sliding and rolling action. flodin and andersson [15] employed a single-point observation-based gear contact methodology in conjunction with archard’s wear formulation to evaluate surface wear in dry and boundary-lubricated sliding surfaces of a meshing gear pair. the accumulated wear ℎ�j at any location after n cycles is given as: 1 2 , , 1 1 2 r r x n x n w fc r v v h h k a v σ− − = + (43) where (� is the sliding velocity and ac� is the contact pressure. the term within the parenthesis kl(�� − (�$n/(��o represents specific sliding p�� which is the ratio of relative sliding per unit rolling. using the load factor #$ for load taken up by the asperities and ac�1 � 2���/q [22], eq. (43) can be rewritten as: , , 1 2 , , 1 2 4 4 dx x n x n w ss dl ss x n x n w f h h k v x vf h h k γ π π γ − −  = +    = + ×  (44) advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 88 where f is the load transmitted per unit face width, ℎ�j is the accumulated wear after n cycles, ��� is the dynamic load per unit face width, ��= is the dynamic load factor, a is the semi-contact width of the elliptical contact and i is the wear coefficient. the total profile error r�, dynamic load ���, and load factor ��= at any location after n cycles is given by: 1 2 xn xn xn h hε = + (45) ( )dx x r x f xλ ε= − (46) dx dl f x f = (47) 8. gear pitting life a model for predicting the pitting fatigue life of rolling bearings, proposed by lundberg and palmgren [27] was extended by coy et al. [28] to spur gears because of the similarities in their fatigue failure mechanism. the tooth profile and the contact zone along the pressure line are divided into finite intervals to predict gear life based on dynamic loads. the use of intervals allows the model to account for load and curvature sums varying with contact position. life estimation of each interval is used to determine complete gear tooth life using probability and statistics methods. 1 0.4 1 e n e x x l l b − − − =   = ×     (48) where e is the weibull exponent whose value is taken to be 2.5 for steels, b is the face width of the gear and s� is the life for a 90% probability of survival of a single tooth subjected to a load f per unit face width is given by: ( ) 4.3 0.4 52 1 x dl l b x f l γ ρ     ′=        (49) where constant material b is taken as 1.32 × 10t for si units, l is the involute curve length and 98 is the equivalent radius of curvature. 9. investigation methodology a reference gear pair of module � � 3 ��, tooth-sum ��� � 100, and pressure angle � � 20° transmitting 10 kw power @800 rpm between a center distance � � 150 �� is altered with tooth-sum alteration factor 0.96 v v 1.04 for this case study. the calculation of the ats geometry modification parameters as described in section 3 and eqs. (1)-(3) are presented in table 1. the total shift �� is shared between the pinion and the gear using the profile shift factor 0.25 v � v 0.75 given by eq. (4). table 1 ats gear geometrical parameters standard gear of � � 3 ��, ��� � 100, � � 20°, and x � 0.2 �� ��� � ��� � � cos.� \ � × cos �] �� � ��^��l_@6� − _@6�n − x 2�� tan � � �� c ^�� 2 l − �n 0.96 (ats) 96 0.4461 2.18748 0.1875 0.98 (ats) 98 0.4004 0.9806 -0.0194 1 (sts) 100 0.349 0 0 1.02 (ats) 102 0.2892 -1.0154 -0.0154 1.04 (ats) 104 0.2135 -1.7538 0.2461 advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 89 fig. 2 numerical simulation flow chart altering the tooth-sum of a reference gear pair changes the radii of the base circles. the pressure angles, profile shift factor, and tooth topping collectively decide the geometry of the ats gears. the radius of the addendum circle ra is calculated using the relation: ( ) ( ) 1 1 2 2 1 1 1 a s a s r r x y m r r x y m κ κ = + + +  = + − + +    (50) the tooth load on ats and sts gears transmitting 10 kw power @800 rpm are found using eq. (5). the speed calculated using eq. (7) to evaluate the performance of ats gear under constant load is tabulated in table 2. the material properties, surface, and operating conditions used in the simulation are given in table 3. table 2 load and speed data standard gear of � � 3 ��, ��� � 100, � � 20°, 1@d ef � 1: 1 ��� � ��� �� � �$ � � hi � l��/2n�j2� ��� � ��� � 0 2qkhi k� � hi� hi� × k� 0.96 (ats) 96 48 67.659 mm 1694 n 833 rpm 0.98 (ats) 98 49 69.069 mm 1694 n 816 rpm 1 (sts) 100 50 70.479 mm 1694 n 800 rpm 1.02 (ats) 102 51 71.88 mm 1694 n 784 rpm 1.04 (ats) 104 52 73.298 mm 1694 n 769 rpm the procedure to find dynamic load factors and load sharing factors are iterative. the length of the contact path is divided into a finite number of intervals. the simulation procedure begins with selecting a trial value of load sharing factor for oil film advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 90 1/#�, and the oil film thickness is evaluated using eq. (25). using the trial value of 1/#$ and oil film thickness ℎ�, eqs. (32) and (34) are equated for equivalence within a degree of acceptable error. the process is iterated for the point of contact with different trial values of 1/#� until convergence is achieved. using eqs. (10) and (12), the load sharing factor for asperities 1/#$ and the coefficient of friction can be obtained. the relative displacement at the mesh interface is obtained by solving one dof dynamic model equation (refer to eq. (37)). table 3 material properties and operating conditions density of steel 7700 kg/m3 load per unit face width, f 1.7 × 105 n young’s modulus, e 206 gpa the radius of curvature of asperities, �8 10 µm wear coefficient, i 2 × 10-16 m2n-1 the density of asperities, @8 1.25 × 1010 /m2 damping factor, ξ 0.25 pressure viscosity coefficient, < = 2.28 × 10-8 pa-1 dyn oil viscosity, 'm 0.05 pa-s pressure viscosity index, zi 0.6 composite surface roughness, a�b� 0.4 µm thermal contact coefficient, xb 13.6 × 106 n/m. s0.5 k the friction width of pinion and gear, b 10 mm the friction coefficient for asperities, %� 0.1 archard’s wear model modified by flodin and andersson [15] for mild wear is employed to estimate wear rates and update dynamic load effects on oil film thickness, load sharing factors, and coefficient of friction. the lundberg-palmgren model is used for estimating fatigue pitting life. the flow chart of the computer code used for the numerical simulation of gear performance is shown in fig. 2. the computation time required for one million cycles is approximately 3 hours for a pair of gears on a pentium octa-core 3.3 ghz machine. 10. results and discussion (a) κ = 0.25 and β = 1 (b) α = 0.96, β = 1, and n = 833 rpm (c) α = 0.98, β = 1, and n = 816 rpm (d) α = 1, β = 1, and n = 800 rpm (e) α = 1.02, β = 1, and n = 784 rpm (f) α = 1.04, β = 1, and n = 769 rpm fig. 3 contact ratio and dynamic load factors gear contact mechanics is quite a complex phenomenon influenced by many parameters. gear geometry is one of the primary parameters that when altered affects many tribological aspects influencing durability and life. ats gears are addendum modified, tooth topped, profile shifted system operating on a fixed center distance. contact ratio (cr) is a geometric parameter that indicates the influence of gear geometry on its load-sharing pattern. one way to increase the contact ratio of a advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 91 gear pair operating between a given center distance is to increase its tooth-sum. in ats gears, increasing the tooth-sum decreases the overall tooth height which increases the mesh stiffness affecting dynamic load factors due to tooth topping. the preliminary investigation of ats gears based on contact ratio reveals the possibility of achieving high contact ratio (hcr) ats gears with positive tooth alterations l > 1), and low contact ratio (lcr) ats gears with negative tooth alterations ( < 1), all pairs running on the same center distance (refer to fig. 3(a)). speed and contact ratio affect dynamic load factors in sts as well as ats gears. plots of dynamic load factors of ncr sts gears and lcr ats gears for profile shift factors 0.25 < � < 0.75 show one region of single tooth contact and two regions of double tooth contact (refer to figs. 3(b)-(d)). larger zones of single tooth contact represent a lower contact ratio, and reducing the roll angle of single tooth contact shows improvement in the contact ratio. plots of dynamic load factors of hcr ats gears with cr > 2, show three regions of triple teeth contact and two regions of double tooth contact, indicating an improvement in the load-bearing capacity (refer to figs. 3(e)-(f)). spikes are observed at the transition zones between double to single tooth contact and triple to double tooth contact. as the speed increases, the dynamic load as a function of contact position differs appreciably from the static load. dynamic load in a gear system decreases with an increase in contact ratio at any given speed because of the narrow single or triple contact zone, which passes quickly, leaving no time for the system to respond. (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 4 effective radius of curvature for ats gears 0.96 < < 1.04 (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 5 contact stresses for ats gears 0.96 < < 1.04 ats gear geometry modification influences dynamic loads, contact pressure, and sliding velocities, consequently affecting flash temperature, oil viscosity, and film thickness. for a given load, the contact stress in ats gears solely depends on the effective radius of curvature of the tooth (refer to fig. 4). the effective radius of curvature is larger in lcr ats and smaller in hcr ats than the ncr sts. the effect of profile shift factor 0.5 < � is to reduce the effective radius of curvature of the point of engagement in lcr ats gears and increase the same at the point of disengagement in hcr ats gears. profile shift factor � > 0.5 reduces the effective radius of curvature of the point of disengagement in lcr ats gears and increases the same at the point of engagement in hcr ats gears. consequently, lcr ats gears have lower magnitudes of contact advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 92 stresses than ncr sts, but the variation from single to double tooth contact region is significant. in hcr ats, the highest magnitude of contact stress is comparable with lcr ats, and the variation from two to three teeth contact region is comparatively less (refer to fig. 5). (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 6 specific sliding in ats gears 0.96 < < 1.04 specific sliding, contact stresses, and dynamic load factors are important indicators useful in contact wear analysis to quantify and compare damage by failure-promoting mechanisms such as fatigue, pitting, and abrasion in ats gears. ncr sts and lcr ats gears exhibit lower sliding velocities but higher dynamic loads. in contrast, hcr ats gears show higher sliding speeds but lower dynamic loads (refer to figs. 3(b)-(f) and fig. 6). in any ats gear pair, profile shift factor � < 0.5 increases the specific sliding at the start point of mesh in lcr ats and the endpoint in hcr ats. on the contrary, the ats gear pair with profile shift factor � > 0.5 increases the specific sliding at the endpoint in lcr ats and the start point of mesh in hcr ats. for all the values of tooth-sum alteration factor α, the flash temperatures obtained using blok’s contact temperature expression show the least value at the pitch point and gradually increase towards the beginning and end of the tooth mesh (refer to fig. 7). flash temperatures are affected by speed, dynamic load factors, and coefficient of friction. specific sliding reduction or increase is associated with the speed and radius of curvature that influences flash temperature. (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 7 flash temperature for ats gears 0.96 < < 1.04 ats gears with profile shift factor � = 0.5, irrespective of the value of their tooth-sum alteration factor α, have symmetric temperature distribution about the pitch point. flash temperature distribution about the pitch point in lcr and hcr ats gears operating with profile shift factor, � = 0.5 can be compared with ncr sts gears under constant load conditions. reduced relative sliding and higher oil film thickness due to higher speeds cause a reduction in the coefficient of friction, which helps reduce the flash temperature in ats lcr gears. higher relative sliding velocity and reduced oil film thickness due to lower operational speeds increase the coefficient of friction and flash temperature in hcr ats gears. in any ats gear pair, varying the profile shift factor � alters the temperature distribution about the pitch point. in an lcr ats gear pair, the relative sliding velocity increases at the point of engagement and disengagement for gears operating with profile shift factor � < 0.5 and � > 0.5, respectively. in an hcr ats gear pair, the relative sliding velocity increases at the point of disengagement and engagement for gears operating with profile shift factor � < 0.5 and � > 0.5, advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 93 respectively. increased relative sliding and comparatively larger dynamic loads due to opposing friction forces consequently increase flash temperature and reduce dynamic viscosity and oil film thickness when operating the gears under constant load and speed conditions. even though hcr ats gears have lower dynamic loads, larger sliding velocities result in higher magnitudes of flash temperatures than lcr ats gears. (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 8 dynamic viscosity ats gears 0.96 < < 1.04 the dynamic viscosity for lcr and hcr ats gears with profile shift factor 0.25 < � < 0.75 are plotted using roeland’s temperature-pressure-viscosity relation shows the largest magnitude at the pitch point and starts reducing on either side of it (refer to eq. (14), fig. 8). dynamic viscosity is lower at the locations of higher flash temperatures and pressures with the least magnitudes at the beginning and end of contact in hcr ats gears. lower flash temperatures and pressures result in a comparatively smaller range of variation in viscosity in ats lcr gears. even though the hcr ats gears have a higher load-carrying capacity than their lcr ats counterparts, for a given load, a drop in viscosity results in reduced oil film thickness (refer to fig. 9). (a) κ = 0.25 and β = 1 (b) κ = 0.25 and β = 1 (c) κ = 0.75 and β = 1 fig. 9 oil film thickness ats gears 0.96 < < 1.04 (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 10 load on oil film ats gears 0.96 < < 1.04 the reduction in oil film thickness causes the asperities to take a considerable portion of the load and vice versa, especially at the start point and the endpoint of contact (refer to fig. 10). the load sharing graphs indicate a maximum of 60% load taken up by the oil film at the pitch point, and the same reduces to below 10% at the extreme ends of mesh for hcr ats gears. a more advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 94 significant portion of the load taken up by asperities due to thin oil film can cause the hcr ats gears to operate under extreme boundary lubrication conditions. improved oil film thickness in lcr ats gears share a higher load of above 90% at the pitch point, reducing to 50% at the extreme ends of the mesh. the reduced oil film thickness causes a higher load share on the asperities resulting in a higher coefficient of friction in hcr ats gears and vice versa in lcr ats gears (refer to fig. 11). (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 11 coefficient of friction ats gears 0.96 < < 1.04 the higher the percentage of load taken by the oil film, the lesser the load on the surface asperities, and the better will be the life of the gear (refer to fig. 12). hence, lcr ats gears will have a better life under the given loading conditions due to relatively thicker oil film formation than hcr ats gears. the oil film thickness can be maintained by changing the oil or the operating speeds. under the given operating conditions, the service life of hcr ats can be improved by using oil of higher viscosity. however, using higher viscosity oil to avoid surface damage may increase power loss. speed, dynamic load, and specific sliding are the important factors influencing the formation of the oil film and consequently the load distribution and wear. plots of accumulated wear in ncr ats gears operating under constant load and speed conditions are presented in fig. 13. (a) κ = 0.25 and β = 1 (b) κ = 0.5 and β = 1 (c) κ = 0.75 and β = 1 fig. 12 tooth life estimate ats gears 0.96 < < 1.04 (a) α = 1 and β = 1 of pinion (b) α = 1 and β = 1 of gear fig. 13 wear plots sts gears α = 1 for 2 × 10r cycles varying the profile shift factor � of any lcr ats gear pair alters the mesh zone about its pitch point. the profile shift factor � < 0.5 makes the drive approach dominant by reducing the length of the path of recess and increasing the length of the approach. the specific sliding increases at the point of engagement and decreases at disengagement for both the pinion and the advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 95 gear, compared with the ats lcr gears with profile shift factor, � = 0.5. increased specific sliding and relatively larger dynamic loads due to opposing friction forces eventually raise the flash temperature reducing dynamic viscosity and oil film thickness. consequently, there is a proportional increase in wear on the pinion than on the gear in the approach engagement region and vice versa in the recess engagement region (refer to figs. 14(a)-(b) & figs. 15(a)-(b)), while the gears are operating under constant load condition. for profile shift factor � = 0.5, the lcr ats gears, irrespective of their tooth-sum alteration factor α, attain equal approach-recess action. accumulated wear is comparatively lesser than ncr sts gears (refer to figs. 14(c)-(d) and figs. 15(c)-(d)). reduced specific sliding and improved oil film thickness due to increased speed help reduce wear rates in ats lcr gears. alternatively, increasing the profile shift factor � > 0.5 decreases the path of approach and proportionately increases the path of recess, making the drive recess dominant. the specific sliding decreases at the engagement point and increases at disengagement for both pinion and gear. higher specific sliding on the gear than on the pinion at the point of disengagement causes an increase in flash temperature, consequently reducing dynamic viscosity and oil film thickness. this leads to a relative increase in wear on gear than on the pinion in the recess engagement region and vice versa (refer to figs. 14(e)-(f) and figs. 15(e)-(f)) in the approach engagement region while operating the gears under constant load condition. (a) α = 0.96, κ = 0.25, and β = 1 of pinion (b) α = 0.96, κ = 0.25, and β = 1 of gear (a) α = 0.98, κ = 0.25, and β = 1 of pinion (b) α = 0.98, κ = 0.25, and β = 1 of gear (c) α = 0.96, κ = 0.5, and β = 1 of pinion (d) α = 0.96, κ = 0.5, and β = 1 of gear (c) α = 0.98, κ = 0.5, and β = 1 of pinion (d) α = 0.98, κ = 0.5, and β = 1 of gear (e) α = 0.96, κ = 0.75, and β = 1 of pinion (f) α = 0.96, κ = 0.75, and β = 1 of gear (e) α = 0.98, κ = 0.75, and β = 1 of pinion (f) α = 0.98, κ = 0.75, and β = 1 of gear fig. 14 wear plots ats gears α = 0.96 for 2 × 10r cycles fig. 15 wear plots ats gears α = 0.98 for 2 × 10r cycles for tooth-sum alteration factor > 1, the contact transforms from ncr sts to hcr ats gears, significantly reducing dynamic load factors over ats gears with lower values due to reduced unit tooth load and the minimal dimension of the transition zone. just as in the case of lcr ats gears, varying the profile shift factor � alters the mesh zone about the pitch advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 96 point in hcr ats gears. however, unlike the lcr ats gears, the profile shift factor � < 0.5 for any hcr ats reduces the length of the approach path and increases the recessed path, making the drive recess dominant. the specific sliding decreases at the point of engagement and increases at disengagement for both the pinion and the gear, compared with the ats hcr gears with profile shift factor � = 0.5. significantly higher specific sliding and very thin oil film in the root region of the gear causes a higher wear rate on the gear than on the pinion (refer to figs. 16(a)-(b) and figs. 17(a)-(b)). the hcr ats gears with profile shift factor � = 0.5 have equal approach-recess action. the root regions of both the pinion and the gear have higher specific sliding and lower oil film thickness than the ncr sts gears under constant load conditions. consequently, the accumulated wear (refer to figs. 16(c)-(d) and figs. 17(c)-(d)) is comparatively greater than ncr sts under constant load conditions. the hcr ats gears with shift factor � > 0.5 have significantly higher specific sliding at the pinion root causing higher wear (refer to figs. 16(e)-(f) and figs. 17(e)-(f) on the pinion than on the gear. increased specific sliding and reduced oil film thickness due to reduced operating speed cause higher wear rates in hcr ats gears. (a) α = 1.02, κ = 0.25, and β = 1 of pinion (b) α = 1.02, κ = 0.25, and β = 1 of gear (a) α = 1.04, κ = 0.25, and β = 1 of pinion (b) α = 1.04, κ = 0.25, and β = 1 of gear (c) α = 1.02, κ = 0.5, and β = 1 of pinion (d) α = 1.02, κ = 0.5, and β = 1 of gear (c) α = 1.04, κ = 0.5, and β = 1 of pinion (d) α = 1.04, κ = 0.5, and β = 1 of gear (e) α = 1.02, κ = 0.75, and β = 1 of pinion (f) α = 1.02, κ = 0.75, and β = 1 of gear (e) α = 1.04, κ = 0.75, and β = 1 of pinion (f) α = 1.04, κ = 0.75, and β = 1 of gear fig. 16 wear plots ats gears α = 1.02 for 2 × 10r cycles fig. 17 wear plots ats gears α = 1.04 for 2 × 10r cycles tooth tip relief modification is considered one of the well-known ways to reduce dynamic loads and wear in spur gears. to investigate the effectiveness of the tip relief modification in reducing tooth wear in ats gears, the variations of tip relief for the contact points are integrated into tooth profile deviations as wear (refer to eq. (45)). the amount of relief is configured based on the design load and the tooth deflection for a test case on lcr ats with tooth-sum alteration factor = 0.96 and advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 97 profile shift factor � = 0.5 (refer to fig. 18). referring to figs. 14(c)-(d) and fig. 19 for comparison of wear on gear and pinion with and without tip relief, the reduction in wear on the latter reflects the reduction in dynamic loads, which is particularly pronounced at the beginning and the end of the mesh. different gear ratios of ats gears of a given tooth-sum also alter the tooth geometry, just like profile shift factors alter the gear geometry since their base circles are different. superimposing magnitudes of gear ratios and profile shift factors push the start or end of tooth contact very near to the point of tangency to the base circles which may cause extreme sliding operating conditions. therefore, lcr or hcr ats gears with gr > 1 should be paired with profile shift factors � < 0.5 to avoid higher specific sliding. similarly, lcr or hcr gears with gr < 1 should be paired with profile shift factors � > 0.5 to avoid extreme operating conditions. α = 0.96, κ = 0.5, and β = 1 (a) α = 0.96, κ = 0.5, and β = 1 of pinion (b) α = 0.96, κ = 0.5, and β = 1 of gear fig. 18 tooth with relief modification fig. 19 wear plots for ats gears with tip relief 11. conclusions ats gear drives are geometry-modified and, kinematically compatible sets of gear pairs capable of operating at a specified center distance. lcr and hcr ats gear pairs can be obtained by altering the tooth-sum of an ncr sts gear pair with the tooth-sum alteration factor 1 < < 1, respectively. based on the comparative study of the supportive and detrimental effects of tribological aspects affecting surface durability in ats gears under constant load, the following conclusions are drawn: (1) the effects of tooth-sum alteration on surface wear are influenced by meshing parameters such as dynamic load factors, specific sliding, and material properties. (2) specific sliding is an important parameter that is associated with the radius of curvature and speed ratio. (3) zones of higher specific sliding are associated with higher flash temperature, reduced oil viscosity, and increased coefficient of friction. (4) lcr ats gears operating at higher speeds help in the formation of better oil film, and lower specific sliding causes reduced flash temperature that prevents excessive reduction in dynamic viscosity and promotes better oil film thickness. therefore, the oil film takes up a more significant portion of the load, reducing the coefficient of friction and surface wear, and increasing pitting life. (5) lower operating speeds in hcr ats and high specific sliding at the start or endpoint of mesh are responsible for higher flash temperatures and reduced dynamic viscosity, which results in very thin oil film formation. consequently, much of the load is taken up by the asperities causing increased surface wear, higher coefficient of friction, and lower pitting life. (6) while operating ats gears with gear ratios other than unity, it is preferable to use gear ratio and profile shift factor combinations that lower the specific sliding for the reasons mentioned above. on a concluding note, the study on ats gears reveals the influence of profile modification resulting from tooth-sum alteration on surface wear and other interdependent parameters. ats gearing offers flexible design features often unavailable in sts gear design. however, experimental studies on this methodology of gear design are proposed as a scope for future work. lpstc hpstc (10 )linear relief mµ modified profile trueinvolute profile tooth center line advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 98 nomenclature tooth-sum alteration factor � center distance � center distance alteration factor �<e equivalent damping coefficient �t� relative acceleration at mesh interface 7 modulus of elasticity �u� relative velocity at mesh interface � total load per unit face width � profile shift factor �� total normal load d mesh stiffness per unit face width vc flash temperature d<e equivalent static mesh stiffness per unit face width s pitting life estimate % coefficient of friction �� dynamic load per unit face width � pressure angle h� radius of the addendum circle 9 radius of curvature hi radius of the base circle ' dynamic viscosity i<e equivalent dynamic mesh stiffness per unit face width h roll angle i wear coefficient w damping factor � module r tooth profile error �g mass per unit face width ac� contact stress � profile shift coefficient 6� rolling velocity �= static load factor p�� specific sliding ��= dynamic load factor �� total profile shift coefficient �� relative displacement at mesh interface x design backlash tooth topping coefficient ℎ accumulated wear depth � number of teeth ℎ� oil film thickness �� tooth-sum of gear pair 1/#� load sharing factor for oil film k speed 1/#$ load sharing factor for surface asperities �� load per unit face width on surface asperities 78 equivalent modulus of elasticity � ! load per unit face width on oil film x face width of the gear and pinion %� friction coefficient for asperities subscripts superscripts 1, 2 pinion and gear 1 altered 2 standard h reference y working � any location along the pressure line @ number of cycles abbreviations ats tooth-sum altered ncr normal contact ratio hcr high contact ratio rpm revolutions per minute lcr low contact ratio sts standard tooth-sum lpstc low point single tooth contact hpstc high point single tooth contact conflicts of interest the authors declare no conflict of interest. references [1] h. k. sachidananda, j. gonsalvis, and h. r. prakash, “experimental investigation of fatigue behavior of spur gear in altered tooth-sum gearing,” frontiers of mechanical engineering, vol. 7, no. 3, pp. 268-278, september 2012. advances in technology innovation, vol. 8, no. 2, 2023, pp. 81-99 99 [2] h. k. sachidananda, k. raghunandana, and j. gonsalvis, “sliding velocity in profile-corrected gears,” lubrication science, vol. 29, no. 1, pp. 43-58, january 2017. 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[28] j. j. coy, d. p. townsend, and v. zaretsky, “analysis of dynamic capacity of low contact ratio spur gears using lundberg-palmgren theory,” nasa technical report, nasa-tn-d-8029, august 1975. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 5-v8n4(2023)-aiti#12587(290-302).docx advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 english language proofreader: chih-wei chang utilizing ultra-high performance concrete overlay for road pavement repair and strengthening applications lay boon tan1, milad hafezolghorani2, azman mohamed1,*, khaled ghaedi3, yen lei voo2 1faculty of civil engineering, universiti teknologi malaysia, johor, malaysia 2dura technology sdn. bhd., chemor, perak, malaysia 3research and development center, pasofal engineering group, kuala lumpur, malaysia received 10 july 2023; received in revised form 27 august 2023; accepted 04 september 2023 doi: https://doi.org/10.46604/aiti.2023.12587 abstract this study aims to develop a new thixotropic ultra-high-performance concrete (uhpc) overlay for the repair and strengthening of damaged hot mix asphalt (hma) pavements. the overlay is purposely designed to accommodate the roadway slope of up to 10% due to the presence of viscosifying agent materials. the original uhpc materials are comprised of granite aggregate, ultra-fine calcium carbonate, shrinkage-reducing admixture, viscosifying agent, and expansive agent. the study is conducted with three sets of samples provided and considers thixotropic and mitigated shrinkage properties by comparing control (non-thixotropic) overlay 1 (thixotropic), and overlay 2 (thixotropic) mixtures. based on the obtained results, only overlay 1 corresponds to the minimum requirement for pavement rehabilitation, with 160-200 mm flowability and -545.3 µm/m free shrinkage. as a result, an average 50 mm thick overlay 1 is selected to repair a damaged hma pavement (1800 m2), while the field implementation procedures and drawing details are also presented in this paper. keywords: uhpc overlay, fiber-reinforced pavement, repair, strengthening, hot mixed asphalt 1. introduction the hot mix asphalt (hma) pavements can be constructed with less budget and difficulty, hence why it is pervasively used not only in malaysia but worldwide. however, the deterioration of existing flexible hma pavements is a quotidian problem in the entire world. various techniques can be employed to restore damaged hma pavements, such as grouting to seal surface cracks, partial or full-depth patching, replacing existing pavement, and overlaying with asphalt [1-3]. while each of these techniques can increase the service life of the damaged pavement, none of them has been manifested to prevent further pavement deterioration [4]. an alternative repair method is the employment of conventional concrete overlays on top of hma pavements. the concrete overlays on asphalt are also widely known as “white topping” in the united states of america [5]. vandenbossche and sachs [6] reported that the bond between asphalt and concrete is critical to ensure that the pavement behaves as a single structure, especially for very thin white topping overlays. in 2022, the european concrete paving association published a “guide for design of concrete overlays” [7], and the guideline mentioned the bonded concrete overlays of asphalt (bcoa) pavements can augment the structural capacity and ameliorate surface friction and noise. the concrete thickness of conventional white topping overlay is equal to or more than 200 mm. the thin white topping overlay retains a thickness of more than 100 mm but less than 200 mm [8]. * corresponding author. e-mail address: azmanmohamed.kl@utm.my advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 291 although the normal strength concrete of white topping overlay technique results in somewhat high durability and life expectancy compared with hma pavement, it has weaknesses such as lofty shrinkage, low tensile strength, long curing time, and requires a thick layer of concrete less cost-effective [1, 9]. most problems with the conventional concrete overlay, such as corrosion and slow curing, are caused by the used material. the concept of employing ultra-high-performance concrete (uhpc) as an overlay was pioneered in switzerland and has been deployed on numerous bridges in europe [10-12]. the uhpc is a fiber-reinforced and portland-cement-based product with advantageous fresh and hardened properties. moreover, the uhpc is emerging as an ideal alternative for preservation and restoration, while proffering an effective and durable solution for extending the service life of existing infrastructure, minimizing impact on the end users [13-15]. thus far, the research on the employment of the uhpc overlay technique is limited. in comparison with normal strength concrete, uhpc material is at least 4 times stronger than it in compression and 7 times higher than it in flexural [16-17]. therefore, it seems a thin layer (less than 100 mm) of uhpc material is sufficient to obtain extraordinary strength and a durable protective layer when compared with normal concrete material. furthermore, the uhpc also yields rapid curing with a minimum compression strength of 70 mpa within 24 hours [18], which enables the work to be delivered expeditiously within a short road closure period. on the other hand, uhpc material also exhibits superior ductility, durability, energy-absorption characteristics, and watertight and load resistance capacity [19]. nowadays, the uhpc overlay application is the most popular in europe, the united states, and canada that only used for the rehabilitation of damaged normal concrete bridges [14]. in 2014, the uhpc accounting for 130 m3 in total was cast on the deck slab of the moudon viaduct for the waterproofing layer, the zones showing reduced structural resistance due to rebar corrosion in switzerland, and strengthening the cantilever slab parts [12]. the most notable uhpc overlay deployment was in the rehabilitation of the 2.1 km chillon viaducts in switzerland. in the prevision of weaker concrete strength, it was decided to strengthen the deck slab with a 40 mm thick layer of uhpc [20]. the first u.s. deployment of uhpc as a bridge deck overlay was completed on a reinforced concrete slab bridge located on laporte road bridge in mud creek in may 2016 [21]. the performance of typical uhpc as a filed-cast overlay, (e.g., industrial floors, industrial pavements, and white toppings) embodies several disadvantages, mostly related to the low water/binder ratio, such as workability, finish-ability, and autogenous shrinkage [22-23]. the total shrinkage of concrete is mainly composed of autogenous shrinkage and drying shrinkage while drying shrinkage is relatively low in uhpc. however, it exhibits substantial autogenous shrinkage due to the low water-to-cement ratio [24]. according to the french standard, nf p18-470 [25], uhpc without any heat treatment shall have a total shrinkage amplitude of around 700 microstrains. reported values of uhpc shrinkage (free shrinkage according to astm c157 [26] tests) are normally more than 700 microstrains. moreover, astm c157 does not capture the volume change in the first 24 hours, which can be high in uhpc [27]. in terms of rheological properties, the typical uhpc has self-consolidating (nonthixotropic) characteristics, whereas it can be formulated to emerge thixotropic behavior for overlay applications. thixotropic uhpc is specially formulated to be situated on a slope given its higher yield stress at a fresh state compared with a selfconsolidating one. a thixotropic uhpc will remain solid-like under static conditions and will flow when agitated or screed [28]. based on the extensive review of the literature, exiguous information on field implementation of uhpc overlay on top of damaged hma pavements is presented. in addition, the interaction between uhpc overlay and hma pavements is yet to be comprehended. while several repair methods exist, more durable solutions to address ongoing pavement deterioration are needed, particularly in high-traffic zones. despite the potential benefits of uhpc overlays, it seems the existing literature is limited in this specific application area. as a result, in this study, a thixotropic uhpc overlay was implemented on a damaged hma road pavement in malaysia, and the bonding between the uhpc and the hma layer was investigated. advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 292 2. thixotropic uhpc mix design the components of uhpc are a dry mix (ordinary portland cement, silica fume, silica sands), water, steel fibers, and a high-range water-reducing agent. to obtain a thixotropic uhpc with a minimum amount of autogenous shrinkage, adequate amount of granite aggregate (< 8 mm), ultra-fine calcium carbonate (caco3), viscosifying agent (va), shrinkage reducing admixture (sra), and expansive agents (ea) were entailed for the mix. to attain the required performance of uhpc, powder materials, and fine aggregates are blended or proportioned to an adequate particle size distribution to maximize the density or compactness. in this research project, a customized 100-liter uhpc ribbon mixer and a customized single-shaft uhpc mixer with a capacity of 10 cubic meters were deployed for laboratory-scale trial mixes and the casting of pilot a uhpc overlay. the specimens deployed in this experiment are prepared following the french standard for uhpc material, as it is currently the sole available standard for uhpc, nf p18-470 [26]. control specimens, including cubes, cylinders, and prisms, are cast into plastic and steel molds. subsequently, they are vibrated for 20 seconds to effectively compact the mixtures. the control specimens in the molds are covered with a 90% efficacy curing compound to prevent early water loss uhpc, and subsequently demolding after 24 hours. these specimens are cured under room conditions for 28-days. table 1 mix design of thixotropic dura® uhpc ingredient mass (kg/m3) thixotropic uhpc dry mix 2000 caco3, va, sra, and ea 100 superplasticiser 28 high-strength steel fibers 157 total water 165 targeted w/b ratio 0.15 total air voids < 4% table 1 presents the mix design for the thixotropic dura® uhpc with 2% steel fibers by volume of concrete. the steel fibers used have a minimum tensile strength of 2850 mpa. the high-range water-reducing agent used is a polycarboxylate ether (pce)-based superplasticizer and no recycled wash water is employed in the mixing. the consistency of uhpc is determined by a flow table test as per astm c230m [29] during mixing and before casting. a flow value of 160-200 mm was measured as shown in fig. 1. this uhpc can be modified to thixotropic behavior that enables the material to accommodate up to 10% super-elevation of the roadway. (a) before tapping (b) after tapping (170 mm) (c) 10% slope surface fig. 1 flowability of thixotropic dura® uhpc according to astm c230 in this study, an attempt was made to investigate three distinct uhpc mix designs to identify the most suitable uhpc formulation for overlay applications. the focus was on augmenting the properties of uhpc that are essential for overlaying deteriorated surfaces. to achieve this, various components were analyzed for their impact on uhpc overlay shrinkage. advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 293 specifically, the effects of granite aggregate, caco3, va, sra, expansive admixture ea, and polyvinyl alcohol (pva) were explored and documented in table 2. in this exploration, ea, sra, pva, and the inclusion of granite aggregate were strategically employed to mitigate the occurrence of shrinkage within the uhpc overlay. furthermore, the study addressed the thixotropic behavior of uhpc, which is vital for its application on sloped surfaces. to improve this behavior, caco3 and va were utilized, which enables the uhpc to maintain its consistency and proper casting properties even on inclined surfaces. this adaptation becomes crucial for ensuring the successful application of the uhpc overlay on a variety of real-world scenarios, such as roadways or bridges with varying angles. the study’s findings not only shed light on the impact of various additives on uhpc overlay shrinkage but also proffer insights into the deployment of these additives to tailor uhpc properties for specific applications. the detailed breakdown in table 2 aids in understanding the composition and characteristics of each mix, which is essential for replicating or adapting these findings in practical construction scenarios. overall, the present research study contributes to the furtherance of uhpc technology and its practical application for overlaying purposes, particularly in the context of deteriorated surfaces and sloped structures. table 2 mix design ingredients for shrinkage tests no mix name drymix (kg/m3) caco3, va, sra, and ea (kg/m3) admixture (kg/m3) steel fiber (kg/m3) total water (kg/m3) pva (kg/m3) flow astm c230 (mm) 1 control 2100 (no granite) 28 157 165 210-230 2 overlay 1 2000 (with granite) 100 28 157 165 160-200 3 overlay 2 2000 (with granite) 100 28 157 165 3.25 150-170 three different shrinkage tests were conducted as illustrated in fig. 2. based on the obtained results, table 3 manifests the shrinkage test results of three uhpc mixtures. as shown in table 3, overlay 1 has less restrained and autogenous shrinkage than the control mix. the control mix has the highest autogenous shrinkage. although overlay 2 shows a lower amount of restrained and free shrinkages, the flowability and workability of this uhpc did not correspond to the requirements for floor screeding due to the presence of pva and granite aggregates. the flow table test results of control, overlay 1, and overlay 2 mixtures are measured and shown in table 2. by using pva, the flowability reduction stands up to 20%, which exacerbates the difficulty and time consumption for the laying and screeding process of uhpc. hence, overlay 1 was utilized for repairing and strengthening deteriorated 1800 m2 hma pavement in malaysia. (a) free shrinkage (b) restrained shrinkage (c) autogenous shrinkage fig. 2 conducted shrinkage tests advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 294 table 3 shrinkage results according to different standards no mix name free shrinkage acc. astm c157 restrained shrinkage acc. astm c1581 autogenous shrinkage acc. astm c1698 unit 1 control -502.7 -110.5 -835.5 µm/m 2 overlay 1 -545.3 -73.0 -640.1 µm/m 3 overlay 2 -538.0 -62.0 -691.6 µm/m 3. field implementation the uhpc overlays are currently used for the rehabilitation of damaged conventional concrete bridge decks in europe countries, china, the usa, etc. the research and development behind this concept were pioneered in switzerland, and scarce highway bridges were coated with uhpc overlay to improve existing rc decks. insufficient research is available regarding the application of a thin layer of uhpc on top of damaged hma roads. thus, the first pilot uhpc overlay project was proposed by the public works department (pwd) of malaysia to repair, monitor its condition over the service life of the roads, and augment the existing hma pavement. an average 50 mm thick uhpc overlay was successfully implemented on damaged hma road pavement located in perak state with 200 m in length and 9 m in width, as shown in fig. 3. fig. 3 location of the first pilot uhpc overlay in chemor, perak, malaysia at the inception of the project, several severe surface damages of hma were observed (cracks, rutting, and potholes), which probably occurred due to heavy vehicles, low wear, and impact resistance of the existing hma pavement. fig. 4 shows the deterioration of existing hma pavement. fig. 4 examples of existing surface damage of hma pavement before the milling process, a licensed surveyor was appointed to measure the existing road profile at the original level to maintain the same road profile after overlaying as shown in fig. 5(a). meanwhile, figs. 5(b) and 5(c) show marking and coring on the existing road before the commencement of field testing. a field density test (fdt) was recorded to evaluate the soil advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 295 condition of existing road pavement. an average compaction and moisture content of 90% and 5.5% were recorded, respectively from 5 different locations (figs. 5(d) and 5(e)). in addition, the same locations of fdt were employed to conduct the coring test. therefore, an average hma thickness of 100 mm was recorded in fig. 5(f). (a) survey before milling (b) marking (c) coring for field testing (d) fdt test on-site (e) close view fdt (f) 100 mm thick existing hma fig. 5 field density test for the pilot project, a comprehensive site plan was meticulously prepared, incorporating precise 5-meter intervals to facilitate the accurate measurement of the existing hma levels. this detailed depiction can be observed in the visual representation presented in fig. 6(a). furthermore, to provide a comprehensive view of the proposed enhancements, a detailed cross-sectional illustration is presented in fig. 6(b). this depiction showcases a typical cross-section of the planned pilot uhpc overlay, measuring substantial 50 millimeters in thickness and spanning an impressive width of 9 meters. advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 296 (a) plan view of the existing hma pavement (b) typical cross-section of construction stages fig. 6 proposed thin topping uhpc overlay for 200 m by 9 m pavement (a) milling process (b) 40-50 mm mill-off (c) formwork installation (d) rebar installation for the joints fig. 7 milling, rebars, and formwork installation processes the construction began with the 40-50 mm removal of the old asphalt layer using a wirtgen 1900 milling machine from the existing 200 m road. to acquire a better interface bond strength between uhpc and hma, the interface was roughed with a minimum 5 mm depth as shown in figs. 7(a) and 7(b). fig. 7(c) manifests the side formwork installed to control the thickness advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 297 of uhpc at road shoulders. moreover, to minimize the shrinkage at the construction joint between uhpc and hma, 100 × 150 mm l-shape t12 rebars (300 mm c/c) were installed horizontally with 150 mm embedded depth as depicted in fig. 7(d). fig. 8(a) shows the milled surface of the hma road after construction rebars and formworks installation. the water jet and blower methods were used to remove contaminants like dust, oil, grease, etc. pre-wet process and bonding agent application before starting casting uhpc overlay are shown in fig. 8(b). (a) surface cleaning (b) applying bonding agent fig. 8 cleaning and applying bonding agent on the pavement surface the first application of uhpc overlay on a damaged hma pavement was situated with around 100 m3 uhpc. the hma pavement was rehabilitated with the new thixotropic uhpc by forklift, but it was found difficult to control the screed process (fig. 9(a)). to resolve the problem on-site, the contractor was able to use a 20-tonne mobile crane to cast and deposit in front of the screed machine which assisted in achieving a quality finish and maintaining the proper profile (fig. 9(b)). hence, the 200 m length ultra-thin topping uhpc layer was cast and situated using a 12 m3 capacity shaft mixer on 3 consecutive nights from 6 pm to 3 am to prevent shrinkage cracks due to hot ambient temperature during the daytime. (a) forklift (b) mobile crane fig. 9 uhpc transported by forklift and mobile crane (a) screeding and leveling (b) curing fig. 10 pilot uhpc overlay procedure advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 298 (c) saw cutting (d) road marking and uhpc overlay completion fig. 10 pilot uhpc overlay procedure (continued) manual and automatic vibratory concrete screed machines were employed for situating and leveling the material as shown in fig. 10(a), and a concrete curing compound with 90% efficiency was sprayed immediately on top of the uhpc overlay to maintain the moisture content in the uhpc mix and reduce early shrinkage cracks (fig. 10(b)). the surface was textured using a spiked roller after the initial set time of 45 to 90 min. once the uhpc overlay achieved a minimum compression strength of 70 mpa, the contraction joints with 5 m c/c and 10 mm depth (t/4) were sawed as shown in fig. 10(c) and followed by road marking in fig. 10(d). 4. results and discussion in this research, three different uhpc mix designs were tested to select the best uhpc for overlay purposes. the impacts of granite aggregate, caco3, va, sra, ea, and pva were investigated on the shrinkage of the uhpc overlay (refer to table 2). the ea, sra, pva, and granite aggregate were used to reduce the shrinkage. furthermore, caco3 and va were utilized to improve the thixotropic behavior of uhpc that allows casting on slopes. table 4 summarizs the mechanical properties of the thixotropic uhpc used for the repair and strengthening of 1800 m2 hma pavement. overlay pavement was cast from eight different batches of a new thixotropic uhpc. samples were collected for all 8 batches to measure 1-day and 28-days cube compressive strength test and 28-days cylinder compressive strength test. 72 cubes with 100 mm in length and 48 cylinders with 100 mm × 200 mm in diameter in total were cast. it should be noted that the target uhpc grade used for this study is c120/135 (characteristic strength of cylinder/cube). mean characteristic strength values (��� ) for cube and cylinder specimens are determined by calculating the average of 48 test specimens. ultimately, the characteristic value (���) is determined by subtracting the product of the structure coefficient (sc) and the standard deviation (sd) from the ��� obtained from experiments as: ( )= − ×cmckf f sc sd (1) from table 4, the 1-day mean cube strength was measured to be ���,����, = 87 mpa which is higher than the specified passing value, that is 70 mpa (to open the traffic road). the 28-days characteristic compressive strength for the cylinder and cube specimens was measured as ���,���, � = 123 mpa and ���,����, � = 142 mpa, respectively. it is deemed to meet the minimum specified strength c120/135. in addition to the compression strength test, flexural-tensile strength tests were conducted on the uhpc overlay mix using the test method given in annex d french standard [25]. the objective of these tests is to convert the flexure-tensile strength test data to obtain the mean and characteristic values of the elasticity limit in tensile (i.e., ����,�� or ����,��) and post-cracking tensile strength (i.e., ������ or �����) of the uhpc. as mentioned in french standard [25], the design tensile characteristic values of ����,�� = 8 mpa, ����,�� = 7 mpa, ����� = 9 mpa, and ����� = 8 mpa is recommended. 36 pieces of 100 mm × 100 mm × 500 mm prism samples in total were cast in this research. advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 299 as shown in table 4, the characteristic tensile values measured are ����,�� = 7.5 mpa and ����� = 10.2 mpa, which are higher than the required values. furthermore, the mean tensile values measured are ����,�� = 8.7 mpa, and ����� = 12.4 mpa which are higher than the recommended values by the french standard. the mean and characteristic flexural strengths were measured as ���� = 29.9 mpa and ���� = 24.0 mpa, respectively. ultimately, the uhpc overlay used in this research corresponded to the design material strength requirement as per the design french standard [25]. table 4 summary of the developed uhpc overlay material items 1st-day cube comp. 28th-days cube comp. 28th-days cyl comp. flexural-tensile strength (annex d, nf p18-470) flexural strength [modulus of rupture (mor)] no of samples 24 48 48 18 18 18 mean (mpa) 87 150 (���,����, � ) 134 (���,���, � ) 8.7 (����,��) 12.4 (�����) 29.9 (����) sd 4.9 6.7 0.9 2.4 2.9 sc 1.645 1.645 cov (%) 3.3 5.0 6.7 8.7 9.7 characteristic (mpa) 142 (���,����, � ) 123 (���,���, � ) 7.5 (����,��) 10.2 (�����) 24.0 (����) after completing the overlay, a field study to assess the bond between the uhpc and the underlying hma surface was conducted. the test setup consists of two samples including a cored cube and cylinder hhpc pull-off disc bonded to the prepared testing surface. a partial core is subsequently cut around the disc, and the disc is pulled off using a tensile testing machine. the pull-off force (f) is divided by the cross-sectional area of the partial core to obtain the pull-off strength (��), as presented in the following formulas for both the cube and cylinder discs: ( )2 f for the cubic discπ=pf a (2) ( )2 4f for the cylindrical discπ=pf d (3) where f is the pull-off force. a and d are the length and diameter of the pull-off disc for cube and cylinder discs, respectively. the test parameters are shown in fig. 11. (a) direct pull-off test (b) bond test fig. 11 pull-off test schematic view fig. 12 in-situ bond tests fig. 12 shows in-situ direct pull-off bond test preparation and the bond testing procedure that has been conducted in this study. 10 pull-off tests in total were conducted on different locations of the uhpc overlay upon completion of the repair and strengthening process. an average 0.26 mpa bond failure between uhpc and existing hma pavement was measured which indicated low bonding strength. the low bonding strength can be attributed to the quality of existing hma pavement, whereas advances in technology innovation, vol. 8, no. 4, 2023, pp. 290-302 300 the uhpc overlay is periodically monitored. thus far, no concerns have emerged regarding the performance of the new uhpc overlay or the bond at the interface between the uhpc and hma layers. it is noted that the pull-off test conducted in the present study is according to astm c1583/c1583m-13. 5. conclusions the uhpc overlay is preponderantly deployed for the rehabilitation of damaged normal concrete bridge decks in numerous countries. however, exiguous information on the field implementation of the uhpc overlay on top of damaged hma pavements is presented. the novelty of the study lies in the investigation and selection of the optimal uhpc mix design for overlay applications, focusing on enhancing properties relevant to overlaying deteriorated surfaces. three different uhpc mix designs were evaluated to determine the most congruous with overlaying purposes. the study examined the effects of various components, including granite aggregate, caco3, va, sra, ea, and pva on the shrinkage behavior of uhpc overlays. the incorporation of ea, sra, pva, and granite aggregate was employed to mitigate shrinkage, while caco3 and va were utilized to ameliorate thixotropic behavior, facilitating casting on slopes. by comparing the mix designs and assessing parameters such as shrinkage, flowability, and mechanical properties, overlay 1 emerged as the most conducive option for repairing and strengthening a deteriorated hma pavement. based on the aforementioned statements, the following conclusions were drawn: (1) the repair and strengthening of damaged road pavement were successfully implemented using uhpc overlay technology in perak state, malaysia for the first time. (2) a thixotropic uhpc applicable to surfaces up to 10% slope with a minimum amount of shrinkage was developed in this study. (3) the uhpc overlay technology is an attainable technology enabling the work to be delivered expeditiously within a short road closure period of less than 24 hours. (4) a thin layer of 50 mm uhpc overlay was sufficient to obtain enough bond at the interface between the uhpc overlay and hma with extraordinary strength and a durable protective layer. (5) the research evaluated the bond strength between the uhpc overlay and the rudimentary hma surface, noting challenges related to bonding strength but observing satisfactory ongoing performance. however, further inspection is required for the next few years to monitor the bonding strength. (6) the uhpc overlay technique assists in achieving a significantly more sustainable road with minimum maintenance due to the excellent mechanical and durability properties of uhpc material. 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[29] standard specification for flow table for use in tests of hydraulic cement, astm c230/c230m-20, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 4-v9n2(2024)-aiti#13523(129-142).docx advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 english language proofreader: chih-wen teng improving healthcare communication: ai-driven emotion classification in imbalanced patient text data with explainable models souaad hamza-cherif1,*, lamia fatiha kazi tani1, nesma settouti2 1biomedical engineering laboratory, university of tlemcen, tlemcen, algeria 2labisen yncréa ouest, caen, france received 31 march 2024; received in revised form 29 april 2024; accepted 30 april 2024 doi: https://doi.org/10.46604/aiti.2024.13523 abstract sentiment analysis is crucial in healthcare to understand patients’ emotions, automatically identifying the feelings of patients suffering from serious illnesses (cancer, aids, or ebola) with an artificial intelligence model that constitutes a major challenge to help health professionals. this study presents a comparative study on different machine learning (logistic regression, naive bayes, and lightgbm) and deep learning models: long short-term memory (lstm) and bidirectional encoder representations from transformers (bert) for classify health feelings thanks to textual data related to patients with serious illnesses. considering the class imbalance of the dataset, various resampling techniques are investigated. the approach is complemented by an explainable model, lime, to understand the shortcomings of the classification results. the results highlight the superior performance of the bert and lstm models with an f1-score of 89%. keywords: sentiment analysis, data re-sampling, lstm, bert, lime 1. introduction sentiment analysis has become an important area of research in natural language processing (nlp), driven by the proliferation of social media platforms and online tools for sharing information. these platforms have revolutionized modern communication, allowing individuals to express their emotions and opinions online and providing valuable information about their thoughts and attitudes. consequently, several works have focused on the analysis of sentiments from data extracted from the web: for example, during the covid pandemic, as studied by madani et al. [1], chakraborty et al. [2], xu et al. [3] focused on the analysis of the emotions of people faced with the virus, vaccination or the popularity of the type of vaccine and were able to provide interesting information on the ground. in addition, analyzing people’s emotions, especially those facing serious health problems such as cancer, dementia, and aids, proves to be very important in the fields of mental health and cognitive psychology. many professionals in the field highlight the fact that emotional health is a crucial aspect of overall well-being. positive emotions can promote the healing process, whereas negative emotions may worsen both the emotional and physical state of patients. thus, automatically analyzing patient feelings using robust artificial intelligence (ai) models on textual data is a major challenge: on one hand, the data relating to patients with serious illnesses are few. identifying the polarity of a feeling remains difficult because of the ambiguity that an emotion can produce in textual data format. in this context, producing models from ai for sentiment analysis is a major asset to help professionals in the field improve the emotional well-being of patients during the healing process, by detecting their feelings whatever they are. * corresponding author. e-mail address: souad.hamzacherif@univ-tlemcen.dz 130 advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 however, some people, particularly healthcare professionals, are somehow hostile to the idea of using ai; because ai models can be seen as black boxes, that distrust its performance. understanding the mechanisms underlying these predictions, particularly in health applications, is a major asset for the usability of diagnostic support and data analysis systems that use ai models. ensuring transparency and explaining the results of the inference produced by artificial learning models is a factor of confidence in the developed tool, and a pillar of ai ethics, particularly for the classification of textual data which have the disadvantage of often being ambiguous and can lead to confusion. in this paper, emotion classification is delved deeper into health-related text data, specifically the emohd dataset [4], using learning models based on neural networks and deep neural networks. this dataset includes 4,202 text samples, collected from different online sites, containing information related to more than eight classes of serious diseases such as hiv/aids, dengue, hepatitis, malaria, influenza, coronavirus, cancer, etc. this data is classified into six different categories. the course of emotions (happy, sad, angry, excited, bored, scared). the importance of studying such a dataset is obvious, as automated emotion recognition in patient health data is essential for advancing to improve research in this area but can also be an interesting diagnostic aid tool. for cognitive psychology, favoring the analysis of the emotional impact of patients. suffering from a serious illness in the healing process. such an analysis could offer an ideal framework to follow the emotional evolution of patients about the progression of their illness. hence the importance. to analyze sentiments in such a context, especially since datasets related to sentiments related to serious illnesses are not available. this work aims to compare the performance of different machine learning with deep learning models: logistic regression, naive bayes (nb), lightgbm, long short-term memory (lstm), and bidirectional encoder representations from transformers (bert), which are often used in the field of sentiment analysis. and explore them on the emohd dataset. the studied dataset is unbalanced; different resampling methods are considered as well as their impact on the classification and results. additionally, the analysis of the classification results was obtained using a local interpretable model agnostic explanation (lime) local explainability model to understand the results of the worst classifier, having obtained the wrong classification score. the key stages of this study concern: (1) implementing data preprocessing tasks and various data re-sampling techniques (nearmiss, smote, adasyn). (2) conducting sentiment classification on input data using feature selection methods (continuous bag-of-words (cbow), term frequency-inverse document frequency (tf-idf), word2vec) and machine learning classification through base models (logistic regression, nb, lightgbm). (3) comparing the classifications obtained after rebalancing the database using both basic models and recurrent deep learning networks, specifically lstm and bert from transformers. (4) analyzes classification predictions utilizing word embeddings with lime. the rest of this article is structured as follows: section 2 covers a study of related work in the field, section 3 presents the approach proposed in this study covering all the steps followed as well as the presentation of the classification models used and the model of lime explainability. in section 4, the experimental results are presented and analyzed. finally, in the last section conclusions and a discussion on potential directions for future work are drawn. 2. related works sentiment analysis is a field in constant evolution. several current works have focused on this problem, especially with the advent of the social and semantic web which has offered sharing tools allowing different users to express their opinion and their feelings, thus offering the researcher in the field the possibility of extrapolating people’s feelings using different ai and nlp tools. the task of sentiment analysis from textual data encompasses different techniques such as lexicon: these approaches use dictionaries, or corpora, to assign a polarity score to each word in lists of manually classified words (positive or negative). advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 131 for example, in srinivasan et al. [5], researchers used a lexicon-based approach to predict election results using knowledge of emotion classification from twitter data related to the election of hillary clinton and donald trump. lin and liao [6] proposed a lexicon-based method for sentiment analysis specific to the financial domain. catelli et al. [7] used the italian sentiment lexicon containing polarized words, expressing a semantic orientation, to identify the sentiments of people vaccinated against covid-19 which highlighted an overall negative sentiment. other newswork uses various machine and deep learning techniques to classify sentiment from text data. whatever the method used, it follows a pipeline of steps ranging from preprocessing the data, which is generally noisy and unstructured, to feature selection and vectorization, which consists of extracting certain distinct features from the text on which the model can focus. training, by converting the text into digital vectors, this step is necessary in the case of using machine learning models, and finally the sentiment classification step. works in this case are abundant in the literature, for example, wise et al. [8] proposed a method based on latent semantic analysis (lsa) of tweets in social media for the classification of cyberbullying texts and achieved an accuracy score of 91% on training data. bhaskaran et al. [9] presented a new modified red deer algorithm (mrda) extreme learning machine sparse autoencoder (elmsae) model for sentiment analysis on a benchmark dataset including d mobile applications for google, their classification process includes vectorization by the tf-idf model reaching an accuracy score of 98%. tan et al. [10] present an approach for sentiment analysis and sarcasm detection simultaneously from online textual data using multi-task learning which consists of training both tasks simultaneously with a shared layer of the bidirectional long short-term memory (bilstm) model. the proposed framework aims to improve the performance of autonomous sentiment classification by adding an auxiliary task which is sarcasm detection and obtained an f1-score of 94%. meena et al. [11] proposed a hybrid model based on deep learning to know users’ opinions on the monkeypox infection on social networks, combining convolutional neural networks (cnn) and lstm, and obtained an f1-score of 95%. das et al. [12] compared different deep learning and hybrid models for the sentiment analysis of comments on an e-commerce site, for the classification of texts in english and bengal, and demonstrated that the model support vector machine (svm) outperformed other models, achieving an accuracy of 82.56% for sentiment analysis of english texts and 86.43% for sentiment analysis of bengali texts. umair et al. [13] proposed an approach to analyze tweets related to covid-19 vaccines and combined the bert + nbsvm model to classify people’s sentiments towards vaccines. this choice is motivated by taking advantage of both bidirectional bert and nbsvm functionalities from transformers and circumventing the limitations of bert-based approaches, which only leverage encoder layers, resulting in lower performance on short texts. the model achieved a performance of 73% accuracy, 71% precision, 88% recall, and 73% fmeasure for positive sentiment classification, while 73% accuracy, 71% precision, 74% recall, and 73% f-measure for classification of negative feelings respectively. after comparison with this state of the art, some points can be got: (1) although lexicon-based and machine-learning approaches offer valuable insights into sentiment analysis, this study does not aim at sentiment extrapolation using lexicon as seen in previous works [5-7]. instead, it introduces a unique perspective by applying machine learning methods to health-related text data. (2) furthermore, compared to works based on artificial learning [8-13], this study not only improves the transparency of results by integrating explainability into analysis but also contributes to the growing field of explainable ai in sentiment analysis. this approach not only advances this understanding of sentiment classification in a critical area but also sets a precedent for future research in applying explainability to deeply understand model decisions. 132 advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 based on these expertise, this study focuses on the emohd dataset to demonstrate the practical application of sentiment analysis techniques in a healthcare context. this study framework therefore differs from the works cited [8-13], as its focus is on applying various sentiment analysis methodologies to the emohd dataset, which contains a unique compilation of textual data. derived from patient feedback on serious illnesses. this dataset, originally introduced by azam et al. [4], encompasses feedback from individuals diagnosed with a range of diseases, including measles, dengue, typhoid, malaria, acute hepatitis, hiv, ebola, and cancer. the pioneering study on emohd achieved an impressive accuracy of 87% using the multi-layered perceptron algorithm, setting a benchmark for further research. encouraged by these early successes, subsequent research has sought to push the boundaries of sentiment analysis in healthcare even further. in mohammad et al. [14], for example, the intelligent water drop algorithm was used to select informative features from emohd, demonstrating the potential of innovative algorithms to improve feature selection and, therefore, feelings of classification accuracy in health-related texts. this exploration of the emohd dataset is part of a broader scientific interest, as evidenced by numerous studies aimed at leveraging nlp and machine learning to deepen this understanding of patient experiences in various healthcare settings, including health care. several studies have addressed emotional recognition [15-17] and its applications in healthcare [18]. this work highlights the broad interest in leveraging nlp and machine learning techniques to understand patients’ experiences, emotions, and feelings, which is crucial to improving outcomes for the patients. healthcare and patient support. by leveraging insights from the emohd dataset, this study (in comparison with [4, 14]) aims to contribute further by evaluating the performance of different learning algorithms such as logistic regression, bayes naive, and lightgbm. integrating a variety of metrics (cbow, tf-idf, and word2vec) and comparing them to recurrent deep learning networks, including lstm and bert models which have shown good results in sentiment classification [10-11, 13]. given the dataset’s inherent imbalance across six sentiment classes (happy, sad, scared, angry, excited, bored), this approach includes exploring various resampling methods (naive subsampling, nearmiss, smote, and adasyn) to address associated challenges and evaluate their impact on sentiment classification results. the other contribution of this approach is the incorporation of explainable artificial intelligence (xai), a response to the critical need for transparency and understandability in healthcare sentiment analysis, particularly when navigating nuanced sentiments within the emohd dataset. explainability offers a certain transparency on the behavior of the classifier and thus makes it possible to better explain its decisions and shortcomings in its performance. explainability techniques can be classified based on their conceptual capacity [19]. in this case, two classes of methods are distinguished: ante-hoc (intrinsic) approaches that automatically generate the explanation as part of the prediction process, referring to machine learning models considered interpretable due to their simple structure, such as short or sparse linear decision trees; and post hoc models and approaches that apply interpretation methods after model training. others classify xai methods based on their scope, whether global or local: local explanations focus on the classification result of a given instance, while global explanations provide an overview of the entire model. through this targeted application of xai techniques on the emohd dataset, the aim is not to only improve the clarity of model decisions but also to lay the foundation for future explorations of the complex relationship between ai decisions and healthcare outcomes. in this study, the understanding of the local scope of the learning model which gave us the worst result in terms of f1-score using the lime model [20] to have clear and complete explanations of the predictions obtained and to identify gaps related to annotation and sentiment polarity. 3. proposed approach in this section, a description of the approach to sentiment classification in health-related text data, as well as explaining the classifier’s predictions. this study is based on the emohd dataset [4], which includes 4,202 text samples classified into eight disease classes and six emotion classes, from various online platforms. advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 133 fig. 1 illustrates this 5-step approach: the first is the preprocessing of the textual data which is essential especially since the data is often ambiguous and noisy, after that, a process of rebalancing the extremely unbalanced data. this can be observed in fig. 2, which displays an exploration of different re-sampling methods, then a comparison of basic classification models (logistic regression, nb, lightgbm) with different vectorization models (cbow, tf-idf, and word2vec) and in parallel an implementation of recurrent deep learning networks is placed: the lstm sequential model and bert to compare the performance of the convolutional classifier with the base models. the last step of this approach concerns the explainability of the learning model having obtained the worst classification results through the analysis of the predictions using the lime model. fig. 1 classification and analysis of sentiment predictions on health-related imbalanced textual data approach fig. 2 emohd dataset class distribution 3.1. data preprocessing to classify the textual data in the emohd dataset, it is necessary to perform preprocessing to remove noise, and make it usable, especially since this data comes from the web and is unstructured. this cleaning process aims to improve sentiment classification results. here are the main measures taken: (1) lowercase conversion: the first step in preprocessing is to convert uppercase terms to lowercase to avoid redundant words. even if the spelling of two upperand lower-case words like “health” and “health” are semantically identical, they are treated as two different lexical units. (2) punctuation removal: this step involves removing any punctuation from the text that does not provide any useful information to improve data classification performance. (3) delete stop words: these are very common words in the language studied that do not provide any informative value for understanding the “meaning” of a document and a corpus, which are isolated and deleted. (4) removal of rare and common words: to avoid the noise that rare words can generate in a text and the impact that too frequent words can also have in the classification, remove rare and common terms by counting their frequencies in the text. (5) lemmatization: it consists of replacing each word with its canonical form, for example, the known word refers to its canonical form namely. this step is useful for the thematic classification of texts because it allows the different variants resulting from the same form or canonical root to be treated as a single word. (6) tokenization: the process of dividing text into tokens or linguistic units such as words, punctuation marks, numbers, and alphanumeric data. each element corresponds to a token which will be useful for the analysis. 3.2. data re-sampling as shown in fig. 2, emohd data is unbalanced, which may impair classification performance, so resampling is necessary. there are several ways to handle imbalanced data, such as undersampling and oversampling. in this study different resampling methods are tested to see their impact on the results of the classification, the choice of methods used covers those best known 134 advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 in the additional field: naive undersampling, which consists of removing certain minority classes (in the case of emohd data this is the minority class sad), and oversampling which involves adding additional copies of observations from the minority class to balance the class distribution, and in this perspective this study tests different oversampling approaches: (1) naive oversampling: this involves randomly duplicating the observations of the minority class to strengthen its signal by resampling with replacement. (2) nearmiss: there are 3 versions of nearmiss. in this study, an experiment with nearmiss1 selects examples from the majority class that are close to three of the closest examples from the minority class and removes them [21]. (3) smote: synthetic minority oversampling technique [22], is a method for oversampling minority observations. the smote algorithm generates new minority individuals similar to existing ones, without being strictly identical. this helps to evenly distribute the population of minority individuals. (4) adasyn: the goal of adasyn is to generate an appropriate number of synthetic alternatives for each minority class observation [23]. the concept of “appropriate number” depends on the difficulty of learning the original observation. 3.3. feature selection as textual data cannot be used directly in machine learning algorithms including classical neural networks, they must be converted into digital representations. this process, called vectorization, transforms raw text data obtained after cleaning into feature vectors. several approaches can be used to perform this task, each extracting different types of features from the text. this study, compares different vectorization methods, including count vectorization, tf-idf, and word2vec, to obtain relevant features from text data. first, an implementation of the cbow model, which is a textual representation that describes the occurrence of words in a document, ignoring the order or structure of the document. the model only cares whether known words appear in the document [24]. furthermore, experiment with tf-idf which is a statistical technique used in information retrieval and data mining to quantify words in a set of documents [25]. tf-idf is based on the frequency of words in a text, as described by the zipf law [26]. tf measures the importance of a term in a document, while idf measures whether the term is discriminative (i.e., not widely distributed). therefore, a term with a high tf-idf value should be prominent in the current document and also appear rarely in other documents. the last model tested is the word2vec [27] embedding model based on a two-layer neural network trained to predict the vector representation of words in context. simply put, word2vec takes a corpus of text as input and generates a set of vectors for the words in that corpus. its goal is to group vectors of similar words into a vector space. with enough data, usage, and context, word2vec can accurately guess the meaning of a word based on its past appearances. they used the google learning model available online†, consisting of 300 vector dimensions for 3 million words and sentences, as a training basis. 3.4. baseline modeling in this step, basic classification approaches — logistic regression, nb, and lightgbm, using different feature selection models (cbow, tf-idf, and word2vec). logistic regression is a statistical approach used for classification problems when the dependent (target) variable is categorical. logistic regression uses the sigmoid mathematical function to return the probability of a label [28]: 1 ( ) 1 − = + x sg x e (1) † https://code.google.com/archive/p/ word2vec advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 135 the second implemented nb model is a probabilistic machine learning model used for classification tasks. in this case. the classifier node is based on bayes theorem 2: ( / ) ( ) ( / ) ( ) = p b a p a p a b p b (2) using this theorem, the probability that a will occur will be found, given that b has occurred (b is the evidence and a is the hypothesis) [29]. the last implemented model is lightgbm, it is a decision tree-based optimization ensemble method used in classification and regression. this model creates leaf-aware decision trees, such that the best-fit leaf of the tree will be split while further strengthening calculations split the depth of the tree into two parts, one wise and the other insightful, as opposed to leaves [30]. 3.5. recurrent neural networks given the impressive results of deep learning algorithms, particularly in the analysis of textual data [11-13], an exploration of their scope on the emohd dataset, so two types of recurrent neural networks (rnn) are implemented: lstm and the bert, and compared them to the learning algorithms implemented previously based on their classification performance. 3.5.1. long short-term memory (lstm) lstm is a variant of rnn, designed to handle time series data or sequences. what sets lstms apart is their ability to handle inputs of different lengths, thanks to their short-term memory capabilities. additionally, lstms are excellent at understanding context because they can process data packets almost simultaneously. in this approach, it implemented a sequential lstm model to solve a predictive modeling problem where it needed to predict a category for an input sequence. the implemented lstm model consists of four layers presented in fig. 3. fig. 3 lstm and bert model architecture the input layer (integration layer) consists of 128 lstm units which map the words of the text into real-valued vectors. this layer takes as input three entities, including: the vocabulary size dimension of each embedded word (input dimension), the maximum number of words in the vocabulary (maximum feature), and the maximum length of a sequence (input length). the second layer is the dropout layer: initialized this layer with a rate of 40% to reduce overfitting when training the model. this will apply random deactivation in each epoch, meaning that on each pass (forward propagation), the model learns with a configuration of different neurons activating and deactivating randomly (40%). the third layer (lstm layer) contains 192 memory units (intelligent neurons) to optimize the performance of the model, this layer is configured with dropout which has been set at 40%, and recurrent dropout which concerns the suppression applied to the recurring input signal on lstm units is set at 20%. the output layer (dense layer) implements the activation function. in this case, a softmax function is used since the model has 6 output classes this number is reduced to 4 after removing the minority classes. 136 advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 during the model compilation phase: the lstm model is configured with a categorical_crossentropy loss function (which measures the dissimilarity between the predicted probabilities and the true categorical labels guiding the model to minimize the difference between them) and the adam optimizer which improves the training process by adapting the pace of learning. the training set was trained for 200 epochs which represents the number of times the model goes through the data set provided for training. this number of iterations seemed correct to us after several tests to give the model the possibility of analyzing the data several times and extracting the relationships and complex variations present in the data set to draw lessons from it. the batch size which determines the number of samples that will be fed into the model in each iteration, and which will allow it to calculate the loss and update its weights accordingly has been divided into 64 batches. 3.5.2. bidirectional encoder representations from transformers (bert) bert is a text representation model developed by google that is context-aware, meaning that a word is represented based on its context in the text. additionally, bert’s context is bidirectional, meaning that the representation of a word takes into account not only the words preceding it in a sentence but also the words following it. bert uses the transformer attention mechanism, which learns the contextual relationships between words (or sub-words) in a text. in its traditional form, the transformer includes two mechanisms: an encoder that reads input text and a decoder that produces a prediction for a task. as bert is used to generate a language model, only the coding mechanism is needed. in this model, the use of the bert-base-cased model from the transformer’s library allows easy access to transformation models and simplifies many technical implementation details. this model is advantageous for the classification of multi-label texts, it remains case sensitive, otherwise, an already solved of this problem during the preprocessing phase of data. as you can see in fig. 3, the model takes labeled training and test data as input and then loads bert’s tokenizer, which divides the text into subword units called tokens. these tokens are then encoded and converted to digital format, thus forming input identifiers (input ids) and attention masks. input ids are integer identifiers of each token in a sequence (a set of them to a length of 256, is chosen based on the token length distribution). in this case, each unique token of the vocabulary is assigned an integer identifier which represents a shortcut of a one-hot encoded vector: one-hot encoded vectors are only vectors in which the element at the index corresponding to the represented token has a value of one, and all other elements have a value of zero. attention masks are applied to extend sequences shorter than the maximum sequence length with padding tokens. fill tokens are just placeholders and do not influence the model output in any way. subsequently, a simple addition of a classification layer takes as input the sequence level embedding and generates the class label, for this, bertforsequence-classification acts as a linear layer on top of the final layer of the transformer and classifies the input data. to refine this bert classifier, an optimizer is used with fixed weight loss adamw, which is parameterized with a learning rate lr = 1e-5, and fixed adam’s epsilon for numerical stability (eps = 1e-8). adam trained this model on 3 epochs in batches of 3. 3.6. explainable predictions diagnostic xai encompasses a set of processes and methodologies designed to improve this understanding of the results generated by machine learning algorithms. these methodologies aim to shed light on how classification models arrive at their predictions. typically, this involves providing textual or visual explanations that explain the connection between the input features of a prediction (e.g., words in a text) and the model’s output [20]. in this research approach, an implemented lime is applied to analyze classifiers that exhibit lower performance than other baseline models. the goal is to better understand the contributions of specific words to the output class predictions, particularly regarding the classifier that gave the lowest scores among the implemented baseline models. advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 137 as shown in fig. 4, the lime model works independently from the classification model used. it can provide clear and precise explanations for individual predictions made by any classifier or regressor. lime achieves this goal by locally approximating the model with an interpretable model, thereby facilitating the interpretability of complex model decisionmaking processes. the explainability process in lime involves two fundamental steps: during the first step, employ a lime explainer to calculate the contribution of each word to a class. the lime explainer takes as inputs the perturbed data (obtained by permuting an observation), the labels (the classes for which an explanation is done), and the distances (similarity distance between the original observation and the perturbed observations). the selected machine learning model is applied to predict the results of the perturbed data. at the output of this step, the weights of the resulting features are obtained to explain the behavior of the classifier (explanation of list [word, contributing weight, label]). secondly, a calculation of the average contribution of each word to a class allows us to sort and classify words according to their impact as detractors or supporters in the classification model. fig. 4 lime model process 4. experiments and results this section contains the results of the experiment conducted in this study. it presents the experiment setup and the metric used for evaluation, followed by the classification results with baselines and deep learning models. additionally, it analyzes the results of the explainability provided by the lime model. 4.1. experimental setup the present experiment was conducted using the google colab platform with the aim of training learning models. this platform provides unlimited access to high-performance graphics processing units (gpus) with minimal configuration requirements. 4.2. evaluation metric this study is a comparison of the performance of various baseline models on the emohd dataset and the performance of lstm and bert for sentiment classification. during the experimentation, the preprocessed data was split using the train_test_split function, so that 20% was allocated for testing and the remaining 80% was used for training. to evaluate the performance of each classifier, utilize the f1-score, a standard evaluation metric that is more suitable for imbalanced datasets than accuracy. the f1-score is a weighted average of precision and recall and takes into account both false positives and false negatives. the mathematical expression for the f1-score is shown in: recall precision f1-score 2 recall precision × = × + (3) 138 advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 4.3. results of classification with baseline methods a trained of all the machine learning algorithms as described in the “basic modeling” section with the models: logistic regression, nb, and lightgbm, each time using a different feature selection method (cbow, tf-idf, word2vec) and an evaluation of their performance on the emohd dataset, including and excluding minority data classes, using five different resampling methods: naive undersampling, naive oversampling, oversampling with nearmiss, smote, and adasyn. the results of these evaluations are presented in tables 1 and 2. table 1 f1-score implemented baseline including minority classes model feature extraction dc naive us naive os nearmiss smote adasyn nb cbow 0.476 0.574 0.700 0.574 0.579 0.593 lr 0.488 0.608 0.823 0.609 0.617 0.622 lgbm 0.485 0.633 0.603 0.633 0.577 0.613 nb tf-idf 0.489 0.638 0.680 0.638 0.599 0.599 lr 0.504 0.617 0.839 0.618 0.629 0.628 lgbm 0.495 0.639 0.613 0.642 0.585 0.592 lr word2vec 0.489 0.612 0.631 0.616 0.612 0.613 table 2 f1-score implemented baseline excluding minority classes model feature extraction dc naive us naive os nearmiss smote adasyn nb cbow 0.472 0.544 0.737 0.556 0.577 0.551 lr 0.486 0.581 0.803 0.608 0.616 0.633 lgbm 0.465 0.611 0.578 0.604 0.539 0.551 nb tf-idf 0.475 0.588 0.667 0.587 0.595 0.608 lr 0.490 0.610 0.831 0.631 0.671 0.676 lgbm 0.487 0.609 0.618 0.601 0.531 0.540 lr word2vec 0.483 0.592 0.600 0.569 0.527 0.539 4.4. results of classification with recurrent neuronal networks (lstm and bert) in this experiment, an lstm and a bert model (all parameters are explained in previous sections) are trained with three different approaches: without re-sampling, with oversampling including minor classes, and with oversampling excluding minor classes. the obtained f1-scores are in table 3: table 3 f1-score of lstm and bert models re-sampling approach lstm bert without re-sampling 49% 57% with oversampling including minor classes 82% 82% with oversampling excluding minor 89% 89% 4.5. analysis of results of classification by closely analyzing tables 1, 2, and 3: unbalanced data significantly affects the classification and it is necessary to resample the data to obtain better results. the inclusion or exclusion of minority classes has no significant impact on the classification results according to the different basic models. the scores obtained in tables 1 and 2 are almost identical which is not the case in table 3 which clearly shows the improvement in the classification rate after removing the minority classes. this leads to the deduction that oversampling has more impact on the classification using machine learning models which is not the case for deep learning algorithms, which are already more efficient. in this specific case, it is clear that the vectorization step and the choice of model have a significant impact on the final results. by analyzing tables 1 and 2: (1) choosing a good resampling method is important to improve classification. in this study, naive oversampling gave the best results on average for the baseline algorithms and even the highest f1-score was obtained using logistic regression with tf-idf and naive oversampling. advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 139 (2) table 1 clearly shows that the logistic regression learning model using feature selection with tf-idf outperformed others with a satisfactory f1-score of 83.9% when including the minority class in the naive oversampling case and 83.1% in the case of the exclusion of minority classes. these results demonstrate the choice of using tf-idf is decisive for the improvement of the classification because even by including the minority classes the variation between the two f1-scores obtained is significant and the result remains satisfactory. (3) furthermore, the use of the word2vec model does not give satisfaction, especially in the case of the exclusion of minority classes. it seems obvious that the model does not manage to select the right characteristics of words which leads to wrong classification. (4) the logistic regression model based on word2vec has obtained the worst result in terms of f1-score, an explanation of these predictions is in the following section. looking to further, improve the classification score has been obtained using lstm and bert. as observed in table 3, the f1-scores obtained by the lstm and bert models after oversampling the data, with or without minor classes were similar. the best f1-score of 89% was obtained with bert and lstm models with oversampling and exclusion of minority classes. overall, both the lstm and bert models gave better performance than the baseline models. however, the bert model outperformed other models even when classifying imbalanced data without resampling, achieving an f1-score of 57%. the negative point observed about the execution of deep learning models is that they are very time-consuming. in particular, the bert model took an average of 6 hours to execute compared to the lstm model, which took 1 hour on average. in contrast, the base models were the fastest; with an average execution time of 40 seconds. despite the despite the timeconsuming nature of the execution, the classification models used in this study particularly lstm and bert, achieved satisfactory results in terms of f1-score, comparing them to the models proposed in the literature. table 4 shows us the different f1-score measurements obtained by other models on the emohd database, but also on other works using recurrent deep learning models on other textual databases. table 4 f1-score of related works database approach f1-score emohd this approach with the lstm and bert model 89% multi-layered perceptron [1] 87% back-propagation neural network (bpnn) based intelligent water drop algorithm [14] 96% another textual database using recurrent deep learning bi-lstm [10] 94% cnn + lstm [11] 95% bert + nbsvm [13] 73% table 4 highlights that the classification results obtained by this bert and lstm models outperformed the multilayer perceptron implemented by azam et al. [4]. although these results are satisfactory, they remain lower than those of the intelligent water drop algorithm based on the back-propagation neural network (bpnn) model [14]. it seems obvious that using the intelligent water drop algorithm for feature selection optimization made a difference and significantly improved the classification result. compared to the results of related works on different text databases these transformer models were more efficient than those in umair et al. [13], which only obtained an f1-score of 73%, also, recurrent lstm models used by tan et al. [10], and meena et al. [11] were very successful with f1-scores of 94% and 95%, these results which exceed this study are encouraging regarding the usability and performance of recursive neural networks in classification feelings from textual data. 4.6. classification diagnostic as shown in table 1, the results obtained by the basic logistic regression machine learning model with the word2vec method are not satisfactory, the f1-score obtained was the worst of all. to explain these classification results, it is relevant to 140 advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 understand how these classifications are made, so, the lime model is used to see how the predictions of the logistic regression model with word2vec on the emohd database were influenced. for this evaluation, a selected of two classes representing opposite feelings: “sad” and “happy”. fig. 5 shows the most important words deemed relevant or not for these two classes. fig. 5 most important words for happy and sad class it can be noted that the category of “happy” feelings should be expressed through words that evoke feelings of joy and happiness. relevant terms in this class include “pink”, “thanked”, and “awareness”, which inspire positive feelings. terms that do not belong to the “happy” class include “cancer”, “army”, and “hepatitis”, which only inspire negative feelings of sadness. in the “sad” feeling class, among the important terms for the classification considered favorable, found “toll”, “married”, and “china”, which are not relevant for identifying a feeling of sadness. detractor words include “outbreak” and “coronavirus”, which are words expressing illness and sad events, but they appear in the list of detractors in the “sad” class. using lime, the results of the classification model are presented with some details. a perception of the word2vec model has difficulty identifying the appropriate lexical representations to support good classification in certain classes, such as the “sad” class. this is not the case for the “happy” class, where the predictions are consistent. it is clear that a feature of the “sad” feeling class belongs to the minority classes, made up of 395 negative feelings. additionally, it is important to note that the feeling “sad” can easily be confused with emotions expressed in other classes such as “angry”, “bored”, and “fear”, potentially leading to misclassifications and confusion. this classification provided by lime is very interesting and can be used to improve the performance of the model, thanks to the addition of preprocessing which removes ambiguous words, or to the parameterization of the word2vec model that thus varies the contextual size and verifies the change in obtained results. 5. conclusion and perspectives in this paper, an approach was presented to classify sentiments from imbalanced health text data. the classification scores obtained confirmed the impact of imbalanced data on classification and the importance of selecting an appropriate resampling method. for feature selection in this case, tf-idf performed better than the word2vec model. the results also demonstrated the superiority of the lstm and bert deep learning models, compared to the reference models. it has also been found that models like lime can help identify words that influence the classification of each class depending on the learning model used. the comparative study of related research works demonstrated the performance of deep learning models such as lstm, bilstm, and hybrid models, which is encouraging for the usability of such models in the field of sentiment classification from textual data. advances in technology innovation, vol. 9, no. 2, 2024, pp. 129-142 141 even though the emohd database explored in this study is interesting in terms of application in cognitive psychology, in particular, to help identify the mental state of patients suffering from serious illnesses and to promote a healing process by addressing negative thoughts of patients thanks to a dedicated diagnosis providing an automatic system based on robust learning models for sentiment analysis; nevertheless, emohd presents many limitations in terms of unbalanced data, but also in terms of ambiguity of classes like the sad, angry, and bored classes are very close and can lead to confusion a term representing a negative thought: for example, the word war can be classified into these 3 classes. in this context, some limitations were observed for future research, it is wise to explore other sentiment databases in the health domain using recursive models and transformers. this is a relevant area for analyzing the impact of positive or negative feelings toward patients. this can be very beneficial in the field of health, both in the healing process of patients and in the field of psychology. conflicts of interest the authors declare no conflicts of interest. references [1] y. madani, m. erritali, and b. bouikhalene, “a new sentiment analysis method to detect and analyse sentiments of covid-19 moroccan tweets using a recommender approach,” multimedia tools and applications, vol. 82, no. 18, pp. 27819-27838, july 2023. 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[30] g. ke, q. meng, t. finley, t. wang, w. chen, w. ma, et al., “lightgbm: a highly efficient gradient boosting decision tree,” advances in neural information processing systems 30 (nips 2017), pp. 1-9, december 2017. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v8n2(2023)-aiti#11232(150-161).docx advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 state estimation and optimal control of four-tank system with stochastic approximation approach xian wen sim1, sie long kek1,*, sy yi sim2, jiao li3 1department of mathematics and statistics, universiti tun hussein onn malaysia, johor, malaysia 2department of electrical engineering, universiti tun hussein onn malaysia, johor, malaysia 3school of mathematics and statistics, changsha university of science and technology, hunan, china received 28 november 2022; received in revised form 20 february 2023; accepted 26 february 2023 doi: https://doi.org/10.46604/aiti.2023.11232 abstract this study aims to optimally control the level of a four-tank system at the steady state in the random disturbance environment using the stochastic approximation (sa) approach. firstly, the stochastic optimal control problem of an equivalent discrete-time is introduced, where the voltages to the pumps are the control inputs. by minimizing the sum of squared errors, the liquid levels are estimated. then, first-order necessary conditions are derived by defining the hamiltonian function. thus, the optimal voltages are calculated based on the estimated liquid levels to update the gradient of the cost function. finally, for illustration, parameters in the system are considered and a simulation is conducted. the simulation results show that the state estimation and control law design can perform well, and the liquid levels are addressed along the steady state. in conclusion, the applicability of the sa approach for handling a four-tank system with random disturbances is demonstrated. keywords: four-tank system, nonlinear optimal control, stochastic approximation, state estimation 1. introduction water tank systems have been widely studied in engineering, such as mechanical and chemical systems. in particular, a four-tank system, which is a standard nonlinear dynamical system, has a more complex liquid-level control problem than two and three-tank systems. considering the interconnected structure between the inputs and outputs in these four tanks, changing a single input to control the system output is complex, and the stabilization of the system changes once a single input is changed. the four-tank system with coupling effects between the input and output causes complex nonlinear behavior, and this nonlinear process is troublesome to manage. thus, it is challenging to stabilize the response output from a four-tank system that is a multiple-input multiple-output (mimo) process [1-2]. moreover, most industrial processes have the problem of controlling the liquid level in the tanks. typically, liquids used in chemical plants and in mixing treatments in tanks must be controlled at a steady-state height, and the flow between tanks should be regulated [3] at the desired level. the various applications of liquid-level control, including nuclear power plants [4], food processing [5], and beverages and pharmaceuticals [6], have been well-presented in the literature. for simplicity, a four-tank system consisting of four interconnected tanks and two pumps are considered. this system aims to control the liquid level in the two lower tanks using two pumps. the inputs of the process are the voltage of the pumps, and the outputs are the liquid levels in the lower two tanks [7-8]. these two pumps convey liquid from a basin to four overhead * corresponding author. e-mail address: slkek@uthm.edu.my advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 151 tanks. the liquid is freely drained from the two upper-level tanks into the two bottom-level tanks. then, the liquid levels in the two bottom tanks are measured. in such a piping system, each pump affects the liquid levels in both the measured tanks. a portion of the flow from the pumps is directed to one of the tanks at the bottom level, while the rest of the flow from the pumps is directed to the overhead tank, which drains freely into the other tanks at the bottom level. the amount of flow between the inputs and the outputs can vary by adjusting the bypass valves of the system [9-10]. several practical studies have been conducted on the control of the four-tank systems. proportional-integral-derivative (pid), model predictive control (mpc), and fuzzy modified model reference adaptive control (fmmrac) were implemented to control a four-tank system [11]. the system’s performance was analyzed using conventional proportional-integral (pi) and hybrid fuzzy pi controllers. linear quadratic regulator (lqr), linear quadratic gaussian regulator (lqgr), and h2 and h∞ controllers [12] were applied to manage the four-tank system separately. then, compare their performances in terms of disturbance rejection to study the effects of these control systems on the four-tank system. moreover, a distributed control and estimation method [13] was designed for a multivariate four-tank process, whereas active disturbance rejection techniques [14] and disturbance observers [15] were proposed for studying four-tank systems in the presence of random disturbances. furthermore, some studies have been conducted on tank systems using the simultaneous perturbation stochastic approximation (spsa) method. for example, the water cooling of sulfuric acid in a two-tank system was studied using the spsa technique, where a neural model and a model-based predictive neural pid controller were developed [16]. a novel optimization method based on the spsa approach was proposed to maximize the control performance of steam-generator level control [17]. the spsa method was also developed and implemented on a dual-tank liquid-level control system to improve the performance of a pid control system for parameter optimization in the tank model and actual equipment [18]. in addition, the spsa method was applied to optimize the trajectories of good placement in the reservoir management optimization problem [19]. however, few studies used the sa technique to manage four-tank systems. therefore, this study aims to explore the application of the sa approach [20] for controlling a four-tank system with random disturbances, which might occur from measurement and human errors. since the actual state of the system, which is the water level in the tank, is uncertain in the presence of random disturbances, estimating the water level in the tank will be difficult. in this situation, researchers are motivated to propose a computational approach based on the sa approach to handle the state estimation of the system and control the water level at a steady state as the main contribution to this study. this computational algorithm is known as the stochastic approximation for state-control (sasc) algorithm. firstly, a loss function is defined, where the differences between the actual and estimated output are minimized. then, the sa updating rule is derived for obtaining state estimates after the first-order necessary condition is satisfied. in addition, a stochastic optimization problem is introduced to minimize the cost function when a sequence of control inputs can be determined to stabilize the system. thus, the hamiltonian function is defined, and the optimality conditions are derived. on this basis, the control law is designed through the sa updating rule based on state estimates. in this study, the performance of the sasc algorithm is given by mean squared errors (mse) for state estimation and the cost function for the control effort. for illustration, the values of parameters in the system are considered, and the four-tank system’s discrete-time stochastic optimal control problem is solved iteratively using the sasc algorithm. finally, the simulation results are presented and discussed after being compared with the results from the extended kalman filter (ekf). the rest of this paper is organized as follows. section 2 describes the mathematical model of a four-tank system and defines the system’s discrete-time nonlinear stochastic optimal control problem. section 3 explains state estimation and control law design using the sa algorithm, and the iterative procedure with the sa updating scheme is summarized as the sasc algorithm. section 4 presents and discusses simulation results obtained using the sasc algorithm. finally, section 5 presents a concluding remark. advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 152 2. problem description consider a four-tank system [2-3] consisting of four connected tanks and two pumps, as shown in fig. 1. pump 1 extracts liquid from the basin below and pumps it to tanks 1 and 4, whereas pump 2 pumps liquid from the basin below to tanks 2 and 3. denote ��, ��, ��, and �� as the liquid level of tanks 1, 2, 3, and 4, respectively, while �� and �� are the flow parameters of pumps 1 and 2. fig. 1 four tanks system suppose �� �, �� �, �� �, and �� � are the flows into tanks 1, 2, 3, and 4, respectively, while � �� � and � �� � represent the flow out of the electrical pumps 1 and 2. the flows into tanks 1 and 4 are equal to the flow out of electrical pump 1, whereas those into tanks 2 and 3 are equal to electrical pump 2. the relations between the flows at each outlet pipe and the total flows from pumps 1 and 2 depend on the flow parameters �� and �� are given as follows [6], 1 1 1pumpq kv= (1) 2 2 2pumpq k v= (2) 1 1 1 1in q k v γ= (3) 2 2 2 2in q k v γ= (4) ( )3 2 2 21 in q k v γ= − (5) ( )4 1 1 11 in q k v γ= − (6) where � and � are the pump coefficients, while �� and �� are the input voltages to the pumps. the flow out of tanks is given by torricelli’s principle by using bernoulli’s equation [7], 1 1 1 2 out q a gl= (7) advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 153 2 2 2 2 out q a gl= (8) 3 3 3 2 out q a gl= (9) 4 4 4 2 out q a gl= (10) where ��, ��, ��, and �� are the cross-section of the outlet pipe of tanks 1, 2, 3, and 4, while g is the acceleration due to gravity. the mathematical model of the four-tank system is described by the mass balance equation [11-12] given by tank 1: 1 1 1 3 1in out out dl a q q q dt = + − (11) tank 2: 2 2 2 4 2in out out dl a q q q dt = + − (12) tank 3: 3 3 3 3in out dl a q q dt = − (13) tank 4: 4 4 4 4in out dl a q q dt = − (14) where ��, ��, ��, and �� are the area of the cross-section of tanks 1, 2, 3, and 4, respectively. eqs. (11)-(14) show that the net change in the volume in a tank is equal to the difference between the volume entering and leaving the tank. by substituting eqs. (3)-(10) into eqs. (11)-(14), the dynamics of the four-tank system are given as follows, 31 1 1 1 1 3 1 1 1 1 2 2 adl a k gl gl v dt a a a γ = − + + (15) 2 2 4 2 2 2 4 2 2 2 2 2 2 dl a a k gl gl v dt a a a γ = − + + (16) ( )2 23 3 3 2 3 3 1 2 kdl a gl v dt a a γ− = − + (17) ( )1 14 4 4 1 4 4 1 2 kdl a gl v dt a a γ− = − + (18) define the state variable � = ���, ��, ��, ���� with �� = ��, �� = ��, �� = ��, and �� = ��, and let the control variable � = ���, ���� with �� = �� and �� = ��, the dynamics of the four-tank system in eqs. (15)-(18) can be formulated in its equivalent discrete-time state equation [21], ( ) ( ) ( )1 ,x k f x k u k+ =    (19) where � = ���, ��, ��, ����: ℜ� × ℜ� → ℜ� is the system dynamics given by 31 1 1 1 1 1 3 1 1 1 1 2 2 aa k f x gx gx u a a a γ τ   = + − + +    (20) advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 154 2 4 2 2 2 2 2 4 2 2 2 2 2 2 a a k f x gx gx u a a a γ τ   = + − + +    (21) ( )2 23 3 3 3 2 3 3 12 ka f x gx u a a γ τ   = + − +    (22) ( )1 14 4 4 4 1 4 4 12 ka f x gx u a a γ τ   = + − +    (23) with � as the sampling time. the output variable � = ���, ���� is defined by ( ) ( )y k h x k=    (24) where the output measurement channel ℎ = �ℎ�, ℎ���: ℜ� → ℜ� is 1 1 h x= (25) 2 2 h x= (26) which represents the solution for the liquid level of tank 1 and 2 as ��� � and ��� �, respectively. therefore, the discrete-time system [22] consists of eqs. (19) and (24), which are disturbed by random noises, are denoted as ( ) ( ) ( ) ( )1 ,x k f x k u k g kω+ = +   (27) ( ) ( ) ( )y k h x k kη= +   (28) where g is a 4 × 4 coefficient matrix, whereas !� � ∈ ℛ�, = 0,1, ⋯ , ' − 1, and )� � ∈ ℛ�, = 0,1, ⋯ , ', are the additive gaussian white noises with zero mean, and their respective covariance matrices are given by *+ ∈ ℛ�×� and ,∈ ℛ�×�. ( ) 00x x= (29) the initial state eq. (29) is a random vector with the mean and state error covariance matrix are, respectively, given by ( )0 0e x x= (30) ( )( )0 0 0 0 0 t e x x x x m − − =   (31) where ./ ∈ ℛ�×� is a positive definite matrix and 01 2 is the expectation operator. it is assumed that the initial state, process noise, and measurement noise are statistically independent. here, the aim is to determine a set of admissible control sequences �� � ∈ ℛ�, = 0,1, ⋯ , ' − 1, such that the following expected cost function ( ) ( ) ( ) ( ) 1 0 , n k j u e x n l x k u kϕ − =   = +           (32) is minimized over the dynamical system given in eqs. (27) and (28), where 3: ℜ� → ℛ is the terminal cost and 4: ℜ� × ℜ� → ℛ is the cost under summation. this problem is known as the discrete-time nonlinear stochastic optimal control problem for the four-tank system and is referred to as problem (p). 3. stochastic approximation (sa) approach now, consider the following recursive equation, 1i i i i a gθ θ+ = − × (33) advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 155 where 5� is the set of parameters to be estimated, 6� = 6�5�� is the stochastic gradient, and �� is the gain sequence. this equation is known as the sa approach [20]. thus, the state estimation and the optimal control design based on the sa approach will be further discussed. 3.1. state estimation consider the state mean propagation [23-24] for eqs. (27) and (28), given by ( ) ( ) ( )1 ,x k f x k u k+ =    (34) ( ) ( )y k h x k=    (35) where �̅� � and �8� � are the expected state sequence and the expected output sequence, respectively. to find the optimal state estimate, introduce the following weighted least-squares problem [21-22], ( ) ( ) ( ) ( ) ( ) ( ){ } ( ) ( ){ } ( ) ( ) ( ){ } 1 0 1 1 min 2 1 2 t sse x t j x x k x k m x k x k y k h x k r y k h x kη − − = − −       + − −       (36) where 9::; is the sum of squares error, ./ is the initial state error covariance, and ,is the output noise covariance. by taking the first-order derivative, the gradient of the sum squares of errors is defined by ( ) ( ) ( ) ( ) ( ) ( ) ( ){ } 11 0 t x ssej x m x k x k c r y k h x kη −− ∇ = − − −       (37) where < = =ℎ =�⁄ . thus, by using the sa approach [20] in eq. (33), the optimal state estimate is obtained from ( ) ( ) ( ) 1 1, ˆ ˆ i i i i x sse x k x k a j x k +  = − ×∇   (38) where �?,� > 0 is the learning rate and the optimal output estimate is determined by ( ) ( )ˆ ˆ i i y k h x k =   (39) remarks: the state estimate �a is the optimal state estimate, which minimizes the sum of squares of error 9::;. the norm of the state estimate �a and the state mean �̅ is relatively close within a small tolerance. using the sa approach for state estimation does not need the state error covariance matrix equation as derived in the kalman filtering approach [21-22]. 3.2. optimality conditions refer to the problem (p), the expected cost function [24] in eq. (32) can be defined by ( ) ( ) ( ) ( ) 1 0 , n k j u x n l x k u kϕ − = = +       (40) and the state propagation from eq. (34) is considered. define the hamiltonian function [19], ( ) ( ) ( ) ( ) ( ) ( )ˆ, 1 , t h u l x k u k p k f x k u k= + +       (41) where b� � ∈ ℛ�, = 0,1, ⋯ , ' is the costate sequence to be determined later. thus, the augmented cost function becomes ( ) ( ) ( ) ( ) ( ) 1 0 1 1 n t k j u x n h k p k x kϕ − = ′ = + − + +    (42) advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 156 examining the increment in the augmented cost function 9′ due to increments in all variables, which are �̅� �, b� �, and �� � according to the lagrange multiplier theory, this increment d9′ should be zero at a constrained minimum [21-22]. thus, taking the first-order derivative of the augmented cost function and hamiltonian function, the following optimality conditions are derived. (a) stationary condition ( ) ( ) ( ) ( ) ( ) ( ) ( )ˆ, , 1 0 t u k u k l x k u k f x k u k p k∇ + ∇ + =       (43) (b) state equation ( ) ( ) ( )ˆ1 ,x k f x k u k+ =    (44) (c) costate equation ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )ˆ, , 1 t x k x k p k l x k u k f x k u k p k= ∇ + ∇ +       (45) (d) output equation ( ) ( )y k h x k=    (46) (e) boundary conditions ( ) 0 ˆ 0x x= (47) ( ) ( ) ( )x n p n x nϕ= ∇    (48) remark: for the sake of convenience, the following standard cost function in quadratic criterion [23-24] could be calculated ( ) ( ) ( ) ( ) 1 2 t x n x n s n x nφ =   (49) ( ) ( ) ( ) ( ) ( ) ( ) 1 , 2 t t l x k u k x k qx k u k ru k = +     (50) when a proper cost function is not provided. thus, the necessary conditions are simple. 3.3. optimal control design define an equivalent stochastic optimization problem [20] to problem (p), and this problem is regarded as the problem (q), given by ( )minimize j u′→ (51) where the necessary conditions in eqs. (44) and (45) are satisfied. hence, solving the problem (q) would allow the design of the control law. by this, the gradient of the objective function in eq. (42) is expressed by ( ) ( )u u j u h k′∇ = ∇ (52) where ( ) ( ) ( ) ( ) ( )ˆ, , 1 t u u u h l x k u k f x k u k p k∇ = ∇ + ∇ +       (53) and the necessary condition for the problem (q) is given by eq. (43). hence, the control law is updated from ( ) ( ) ( ) 1 2, i i i i u u k u k a j u k +  ′= − ×∇   (54) advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 157 where ��,� > 0 is the learning rate. here, the principle of separation is assumed to be satisfied when applying the sa approach [20] for state estimation and optimal control design. this statement is true for solving stochastic optimal control problems. 3.4. sa for state-control algorithm from the discussion above, the computational procedure for applying the sa approach to state estimation and control law design is summarized as an iterative algorithm named the sasc algorithm. the steps of the sasc algorithm are as follows: data: given �, ℎ, f, 3, 4, ', ./, g+, ,-, ��, ��, and �. step 0: determine the initial control �� �/ = �/ for = 0,1, ⋯ , ' − 1 and the initial state �a� �/ = �/ for = 0,1, ⋯ , ' set the tolerance h and the iteration i = 0. step 1: calculate the sum of squares error 9::;1�a� ��2 from eq. (36), and the stochastic gradient ∇k9::;1�a� ��2 from eq. (37), respectively. step 2: update the state estimate �a� ��l� from eq. (38). step 3: compute the output estimate �a� �� from eq. (39). step 4: solve the state equation forward in time from eq. (44) with the given initial state �̅/ to obtain the state solution �̅� ��. step 5: solve the costate equation backward in time from eq. (45) with the given final costate b�'� to provide the costate solution b� ��. step 6: compute the output measurement �8� �� from eq. (46). step 7: calculate the cost function 91�� �2� from eq. (42) and calculate the stochastic gradient ∇�91�� �2� from eq. (53). step 8: update the control law �� ��l� from eq. (54). step 9: test the convergence. if �a� ��l� = �a� �� and �� ��l� = �� �� within a given tolerance h, stop, else set the iteration i = i + 1 and go to step 1. remarks: from the steps of the sasc algorithm, the initial value of the state and control can be set to a zero vector in step 0. the state estimation procedure is implemented from step 1 to step 3, and the two-point boundary-value problem is solved from step 4 to step 5. while the optimal control law is designed from step 7 to step 8, and the appropriate stopping criteria for the iteration can be set in step 9. 4. simulation results table 1 parameters in problem (p) system parameters values the cross-sectional area of the outlet hole for the tanks �� = 0.071 pq�, �� = 0.057 pq�, �� = 0.071 pq�, �� = 0.057 pq� the cross-sectional area of the tanks �� = 28 pq�, �� = 32 pq�, �� = 28 pq�, �� = 32 pq� pump proportionality constants � = 3.14 pq�/x:, � = 6.29 pq�/x: flow coefficient of the pumps �� = 0.35, �� = 1.35 gravitational acceleration 6 = 981 pq/[� initial liquid level ���0� = 10.43, ���0� = 15.98, ���0� = 6.6, ���0� = 9.57 estimation and control parameters values sampling time � = 0.1 [ final time step ' = 80 weighting matrices \] = �̂×�, g = di�6�10, 10, 10_, 10_�, , = 100`�×� covariance matrices ./ = 0.2`�×�, g+ = 0.01`�×�, ,= 0.01`�×� advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 158 consider the system parameters for the four-tank system [3, 9], and the estimation and control parameters defined for the problem (p) listed in table 1. using these parameters, an illustrative example of the simulation of the four-tank system is studied to demonstrate the practicality of the sasc algorithm. the simulation of this study is conducted in the environment of the gnu octave 7.2.0. table 2 presents the simulation results for controlling the four-tank system with random disturbances. the implementation of the sasc algorithm required 1,254 iterations to achieve convergence. for benchmark purposes, the results of the sasc algorithm were compared with results from the ekf algorithm since the ekf algorithm is the standard technique for nonlinear filtering and estimation. the optimal cost of 3.4959 × 107 units obtained using the sasc algorithm was 1.15 % less than the optimal cost given by the ekf algorithm. this reduction demonstrated the practical application of the sasc algorithm in minimizing the cost function of the system. however, the performance of the sasc algorithm for state estimation, measured through the sum of squares error (sse) and the mse, was 98.7 % more accurate than that of the ekf algorithm. therefore, the efficiency and accuracy of the sasc algorithm for solving the discrete-time nonlinear stochastic optimal control of the four-tank system were demonstrated. table 2 simulation result algorithm optimal cost sse mse ekf 3.5366 × 107 2.307386 × 10–1 2.884233 × 10–3 sasc 3.4959 × 107 3.091891 × 10–3 3.864864 × 10–5 fig. 2 shows the final output trajectories when the sasc algorithm achieved convergence. the liquid level in tank 1, in which y� represents the actual liquid level and yb� is the estimated liquid level in tank 1, which was reduced from 10.43 cm and reached about 4.5 cm after 2 seconds at the final time of the iteration. while the liquid level in tank 2, in which y� represents the actual liquid level and yb� is the estimated liquid level in tank 2, which reached about 37.5 cm after 2 seconds at the final time of the iteration after increasing from 15.98 cm. in the random disturbance situation, it was challenging to maintain the steady state of the liquid level in tanks 1 and 2. however, the final liquid levels in both tanks 1 and 2 were approximately determined in a satisfactory form by using the sasc algorithm. (a) output trajectory y� – the liquid level in tank 1 (b) output trajectory y� – the liquid level in tank 2 fig. 2 final output trajectories and real output trajectories the final state trajectories are shown in fig. 3. the liquid levels in tanks 1 and 2 exhibited fluctuation behaviors disturbed by random noise and were not easy to measure smoothly. using the sasc algorithm, these trajectories were estimated acceptedly, and their trajectories were approximately measured. conversely, the liquid levels in tanks 3 and 4 were unaffected by random disturbances. this is because their trajectories were smoothly predicted at their respective steady states approximately along with zero. advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 159 fig. 4 shows the final control trajectories for regulating the liquid levels in the tanks. the optimal input voltage to pump 1 increased from -270 v to 0 v, and the optimal input voltage of pump 2 decreased from 182 v to 0 v. these control efforts effectively maintained liquid levels at approximately zero after 2 seconds. therefore, the optimal solution to the four-tank problem was obtained satisfactorily when stationary conditions were satisfied, as shown in fig. 5. (a) state trajectory �� – the liquid level in tank 1 (b) state trajectory �� – the liquid level in tank 2 (c) state trajectory �� – the liquid level in tank 3 (d) state trajectory �� – the liquid level in tank 4 fig. 3 final state trajectory and real state trajectory fig. 4 final control trajectories fig. 5 stationary conditions 5. concluding remarks optimizing and controlling the four-tank system with random disturbances through the sa approach were discussed in this study. firstly, the discrete-time stochastic optimal control problem for the four-tank system was described by considering the presence of random disturbances. subsequently, by applying the sa approach, the iterative algorithm, namely the sasc approach, was proposed to estimate the state dynamics and to design the optimal control law. therefore, the state estimation advances in technology innovation, vol. 8, no. 2, 2023, pp. 150-161 160 of the system was satisfactorily handled, and the optimal control law, which was thoroughly designed based on the sa updating rule, was applied to minimize the performance index of the system. for illustration, researchers studied the control problem of a four-tank system with given parameters. the simulation results showed that the system was stabilized and controlled in a stochastic environment after using the sasc algorithm proposed. these results were also compared with results from the ekf technique, and a discussion was given. in conclusion, the efficiency and accuracy of the sasc algorithm are demonstrated. for future research, it is recommended to apply recent variants of the sa approach, like the adam algorithm, for solving the stochastic optimal control problem of the four-tank system so that more acceptable results can be determined. in this way, the water level at the steady state will be identified in fewer iteration numbers, where the algorithm provides an iterative solution that can converge faster. hence, the practicality and usefulness of the algorithm will be recommended. acknowledgment this research was supported by the universiti tun hussein onn malaysia (uthm) through tier 1 (vot q121). conflicts of interest the authors declare no conflicts of interest. references [1] j. k. pradhan, a. ghosh, and c. n. bhende, “two-degree-of-freedom multi-input multi-output proportional–integral– derivative control design: application to quadruple-tank system,” proceedings of the institution of mechanical engineers, part i: journal of systems and control engineering, vol. 233, no. 3, pp. 303-319, march 2019. 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[24] k. l. teo, b. li, c. yu, and v. rehbock, applied and computational optimal control: a control parametrization approach, 1st ed., switzerland: springer cham, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v8n4(2023)-aiti#11744(303-312).docx advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 english language proofreader: chih-wen teng an optimal energy control system for campus microgrid using crow search algorithm considering economic dispatch agim tetuko, subiyanto*, muhammad addin malik department of electrical engineering, universitas negeri semarang, central java, indonesia received 10 march 2023; received in revised form 13 september 2023; accepted 14 september 2023 doi: https://doi.org/10.46604/aiti.2023.11744 abstract this article presents an optimal energy control system that considers economic dispatch (ed) for a campus microgrid to reduce its operating cost. a newly developed crow search algorithm (csa) is used to enforce the ed in this work. to achieve this purpose, an optimal size of distributed energy resources (ders) in the campus microgrid is assumed. csa is used to optimize the energy control system and find the minimum operating cost of the campus microgrid. to indicate the effectiveness of csa, several scenarios under various load demand conditions in gridconnected and stand-alone microgrid modes are investigated in this work. according to the findings, the suggested model is capable of sufficient power supply in all scenarios and reduces the operating costs more effectively than the reference delineated in the same case. the outcomes confirm that the suggested model’s performance is optimal for the energy control system of a campus microgrid. keywords: optimal energy control system, economic dispatch, operating cost, campus microgrid, crow search algorithm 1. introduction the worldwide renewable energy capacity is expected to increase rapidly over time [1]. this encourages researchers to develop microgrid systems capable of harnessing renewable energy's potential. generally, the microgrid system can be operated in two modes [2-5]. it’s a stand-alone mode for inaccessible utilities like remote areas or isolated islands [6], and a grid-connected mode that is suitable for supplying residential, urban, commercial, and central areas, up to educational facilities [7]. among these, educational campuses are particularly well-suited for the implementation and development of microgrid systems. the availability of reliable human resources and regular administration in this area can be classified as a prosumer area that is very suitable for the implementation and development of microgrid systems [8-9]. a wide range of renewable energy sources (res), including solar energy, wind, water, etc., can be used by microgrids [10]. however, the use of these res like photovoltaic (pv) depends on stochastic climatic conditions and time resulting in varying electricity generation in the microgrid system [11-12]. therefore, energy storage systems (ess) such as battery energy storage systems (bess), have been combined in microgrid systems to maintain power continuity in microgrids [13]. a diesel generator (dg) that is independent of time and weather generator also has been combined in microgrid to handle more complicated system conditions, such as power outages or when the renewable energy generation and storage systems are no longer able to handle load demand [14]. although preventive attempts have been made through the combination of ess and independent generation in microgrids, the complexity of microgrid operation is still a crucial issue that needs to be * corresponding author. e-mail address: subiyanto@mail.unnes.ac.id advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 304 considered to make microgrids optimal and reliable. in this regard, the operation of microgrid systems needs to consider electricity storage systems, load devices, and generation units, while ensuring optimal and reliable operation of microgrid networks to handle the uncertainties in microgrids and minimize the operating costs [15]. to overcome the economic dispatch (ed) problem, which is based on the optimal power search of each distributed energy resources (ders) to reduce the operation cost, several matters such as power continuity and various operating constraints are considered [16]. various methods have been developed by several researchers in this field. mellouk et al. [17] used the genetic algorithm (ga) to minimize grid charges and peak hours of energy consumption. ali [18] has also used particle swarm optimization (pso) and differential evolution (de) to optimize energy management for microgrids in grid-connected and stand-alone modes. nevertheless, renowned algorithms do have their restrictions. examples of common issues include the slow convergence rate of ga, the instability of convergence in de, and the tendency for both de and pso to easily fall into local optima, often requiring a substantial amount of time to converge [19]. one of the latest metaheuristic algorithms is the crow search algorithm (csa) introduced by askarzadeh [20], which adopts the memory-based nature of crows to hide and steal their food from other crows. csa has only one equation and two tuning parameters, making it easy to implement while still being able to maintain the consistency and robustness of the algorithm by spending less computational time to achieve the best fitness value. spea in [21] has used csa to optimize the microgrid energy management with ders consisting of pv/wind/dg systems in remote areas. dey et al. [19] also used csa to optimize it in microgrids with pv/wind turbine/dg configurations in grid-connected and stand-alone modes. the research results demonstrated that the algorithm excels in addressing energy management issues within the microgrid systems in terms of power continuity, economy, and emissions. however, most researchers often overlook specific areas of microgrid application, especially those with unique energy consumption patterns like campus areas. on the other hand, the optimal size of the der implemented is also a crucial factor that must be considered. in this work, the optimal size of der in a grid-connected microgrid has been implemented in the campus area referred to [14] with the same site study while still being adjusted to the conventional market size. therefore, this article presents an energy control for optimizing the energy management system in the grid-connected microgrid of campus areas with the ed problem to find the optimal power of each der and minimize the total operational cost using csa. in the proposed model, operating costs and the optimal unit capacity of each der are considered. furthermore, day-ahead control energy has been thoroughly explored concerning several constraints, such as power generation, electricity price, and various load conditions. this paper is organized as follows: section 2 presents the ed model of grid-connected campus microgrids, including the objective function, some constraints, and the case site profiles of the campus microgrid. csa is the method used to solve the ed problem, and case studies are discussed in section 3. the results of this study are presented in section 4, and the conclusion is presented in section 5. 2. ed model of grid-connected campus microgrid the ed problem essentially aims to find the lowest generation cost by finding the optimal output power of each der. nevertheless, in the ed problem, many aspects can be considered, such as power trading, scheduling, and demand side management (dsm) [16]. ed is a complex problem with large dimensions and many constraints to be considered. in gridconnected microgrids, especially in the campus area, the aspects of power trading, scheduling, and unusual load usage patterns need to be considered. therefore, in this work, ed will be analyzed on a grid-connected microgrid in the campus area with pv, bess, and dg configurations as shown in fig. 1. advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 305 fig. 1 university campus microgrid structure 2.1. objective function the main objective of ed in this work is to find the optimal power of each der in a grid-connected campus microgrid to minimize the total operational cost using csa. to achieve this purpose, the characteristics and optimal size of each der must be considered. furthermore, day-ahead control energy has been thoroughly explored regarding several constraints, such as power generation, electricity price, and various load conditions. in this case, a grid-connected microgrid that uses res in the form of pv, ess, and dg, is considered as follows [16]: ( ) ( ) ( ) ( ) ( ) 1 1 1 t n n t c buy buy sell sell t i i minc f p t c t p t c t p t = = =    = + −  (1) where minct is the total cost function of the grid-connected microgrid, and fc (t) is the total operational cost of all der units consisting of dg, bess, and res units in the form of pv in the time interval t. cbuy (t), csell (t), and pbuy (t), psell (t) are the powers and prices of electricity purchased and sold at t. res, such as pv is a source of clean energy that does not require fuel costs. although there are still installation, maintenance, and operation costs that can be calculated to determine the cost function of res [21]. in this study, the investment cost of res is not considered as described by: ( ) ( )1 1 c pv p pvn r f p o p r −         = + − + (2) where fc (ppv) is the operating cost of the pv, ppv is the pv output power, r and n are the interest rate and lifetime of the unit in years, and op is the ratio of operating and maintenance costs to installed unit power. in [22], the value of r is set to 0.09 and n = 20 years, the value of op is 0.016 $/kw used in this study and some previous studies [21, 23-24]. the pv cost function in eq. (2) can be replaced by: ( ) 0.12554647c pv pvf p p×= (3) 2.2. constraint total power production from each der should be equal to the electricity load demand, as represented by: ( ) ( ) ( ) ( ) ( )g pvdg bess loadp t p t p t p t p t+ + + = (4) ( ) ( ) ( )g but sellp t p t p t= − (5) advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 306 on the other hand, to ascertain system operation stability, each der should have maximum and minimum limits according to, max min i ip p p≤ ≤ (6) in a grid-connected microgrid, it can be ensured that power buying and selling transactions to and from the grid as represented in: ( ) ( ) ( ) ( ) ( ) { } 0 0,1, , 0  ≥   = ∀  ≤   … p t cbuy t pg t if pg c t t t csell t pg t if pg (7) where �dg (t), pbess (t), and ppv (t) are the output power of dg, bess, and pv at t, while pload (t) denotes the power demand at t. p� ��� and p� ��� represent the minimum and maximum output power limits of unit i. (t) is the total electricity cost at t. a positive value for grid power means the system is buying power from the grid. whereas, if the value is negative, it means the system is selling power to the grid. restrictions and patterns of bess usage are also important to be considered in the microgrid system’s operation. the output and input power capacities of the bess, state of charge (soc) limitations, and changes in the bess are represented by the following equations [16]: ( ) ( ) ( ) ( ) ( ) ( ) max min max min, , , 0 ; <0 ; 0  ∈ − − − −   > → → = → bess dis dis ch ch bess charges bess discharges bess idle p t p p p p if p t bess if p t bess if p t bess (8) ( ) ( )min 1 − − = ≤ ≤critical bessbess bess cap e soc t soc t e (9) ( ) ( ) ( ) 1 bess bess bess bess cap p t soc t soc t e τ − + = + (10) where � �� and � ��� are the maximum and minimum bess charges, respectively. whereas ���� �� ��� ���� ��� is the maximum and minimum bess discharges. socbess-min (t) is the minimum soc limit, socbess (t) is the soc of bess, ecritical is the energy consumed during critical load, τ is the time period, and ebess-cap is the capacity of bess. 2.3. case site profiles as has been explained in the previous section, the campus area is the most suitable place for the implementation and development of microgrid systems. the focus of this site study is the campus areas, specifically the university buildings in the electrical engineering department of the faculty of engineering at universitas negeri semarang. these buildings are e6, e8, and e11 as shown in fig. 2. it’s located in sekaran, gunungpati, semarang city, indonesia, with coordinates of 7.05° south latitude, 110.40° east longitude, and an altitude of 187 meters above sea level [25]. as a result, the climate can be classified as tropical, featuring two distinct seasons: the dry season and the rainy season, which occur throughout the year. the daily load pattern in the site study has an unusual pattern where peak hours occur during the day, with the main load consisting of lighting, air conditioning, and campus electrical equipment such as computers, projectors, and electrical trainers set in the laboratory. the total daily load profile is 246.5 kwh and the annual average load is 68,204.1 kwh/year [14]. dg units have been combined in a microgrid system to handle more complicated system conditions, such as power outages or when the renewable energy generation and storage systems are no longer able to handle load demand. therefore, in this work, the optimal capacity of dg was considered. the cost characteristics of dg units are described in table 1. advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 307 fig. 2 e6, e8, and e11 buildings location [25] table 1 dg generation cost characteristics dg state generation capacity (kw) cost ($/kw) dg1 (28 kw) low 7-14 0.185 medium 15-21 0.16 high 22-28 0.156 dg2 (48 kw) low 12-24 0.171 medium 25-36 0.143 high 37-48 0.132 3. crow search algorithm one of the latest metaheuristic algorithms for solving energy management problems, specifically the ed problem, is csa. however, in its implementation, csa also has several tuning parameters that need to be adjusted. in this section, an overview of csa and its implementation in ed problems is addressed. 3.1. overview of csa csa is one of the latest metaheuristic algorithms introduced by askarzadeh in 2016 [20], which adopts the memorybased nature of crows to hide and steal their food from other crows. this algorithm adapts the intelligent behavior of crows in a flock to find the best food source based on the objective function. in the optimization perspective, the crow acts as the searcher, the environment serves as the search space, every food source hiding place is a feasible solution, the quality of the food source is the objective function (fitness), and the best food source in the environment is the problem’s global solution [20]. furthermore, it can be assumed that we have a d-dimensional search space in an environment occupied by several crows, then the position of crow i at iteration time in the search space can be expressed by xi,iter = (x1 i,iter, x2 i,iter, x3 i,iter,…, xd i,iter) [21]. where (i = 1, 2, 3,…, n), (iter = 1, 2, 3,…, itermax); d is the number of decision variables, n is flock size, and itermax is the maximum number of iterations. the crow’s current position, represented by mi,iter is stored in the memory of crow as the current best position. to update the crow’s position, it can be assumed that at an iteration, there is a crow j going to its hiding place mj,iter. then crow i decides to follow crow j to its hiding place. in this case, two possible circumstances will change the crow’s position. case i: crow j did not realize that crow i was following it. therefore, crow i will find out the hiding place of crow j. case ii: crow j realizes that crow i is following it. therefore, crow j will try to trick crow i into protecting its hiding place by randomly moving to other locations in the search space. advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 308 according to the possibility of both cases above, the next position of crow i can be expressed by: ( ), ,, , , , 1 + + × × − ≥ = i j iter j j iteri iter i iter i iter i iter x r fl m x r ap x a random position otherwise (11) where ri and rj are randomly distributed numbers between 0 and 1. fli,iter is the flight length of crow i at iteration iter, and apj,iter represents the awareness probability of crow j at iteration iter. furthermore, the crow’s memory will be updated by: ( ) ( ) , , 1 , 1 ,, , 1 , + + + =   i iter i iter i iter i iter x f x is better than f m mi iter m otherwise (12) where f (...) represents the objective function value. in this algorithm, diversification and intensification are controlled by fl and ap. the value of fl will be directly proportionate to the similarity value of the crow position, and the ap value will be proportionate to the crow position diversity level. therefore, setting a small value for fl (fl < 1) generates a local search close to xi,iter, whereas setting a large value for fl (fl > 1) will cause a global search far from xi,iter. on the other hand, increasing the value of ap decreases the probability of finding a solution around the current best location and the algorithm will tend to explore solutions in the global search space. rather than decreasing the value of ap, the algorithm will tend to search around the location where the current best solution is found [15, 17, 22]. 3.2. implementation of csa to ed problem fig. 3 flowchart of csa for solving ed advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 309 in the previous section, it was mentioned that the ed problem aims to minimize the total generation cost of all microgrid der units while considering the power availability and optimal capacity selection of the installed ders. in this problem, csa plays a role in finding the most optimal combination of power output from each der of the campus microgrid to minimize its generation cost while considering power availability. before presenting the csa, it must be remembered that to solve the ed problem, it is necessary to meet some equality and inequality constraints as introduced in eqs. (1)-(10). on the other hand, memory-based algorithms such as csa essentially have different optimization solutions for each running instance. the settling of the algorithm relies on the initial position and the random movement of the population to find optimal solutions in the search space. therefore, assessing memory-based algorithms in a single run is not an appropriate comparison. to assess the robustness of the algorithm, multiple test runs are required. the algorithm is considered reliable when it consistently produces results across all runs [26]. the tuning parameters directly affect the final result of the algorithm. prior studies [21, 26-28] have established and demonstrated the optimal values of fl and ap, which are adopted in this work. table 2 provides details of csa tuning parameters. finally, the detailed steps of csa implementation for the ed problem are described in the flowchart presented in fig. 3. table 2 details of csa tuning parameters itermax flock size fl ap 200 40 2 0.1 4. results and discussion in this section, csa has been used to optimize the ed problem on the grid-connected campus microgrid that uses pv as a renewable energy source and is supported by bess and dg. to provide a comprehensive investigation of the ed problem in this work, the microgrid was tested under various load demands in grid-connected and stand-alone modes to prove the feasibility of the microgrid system for solving the various possible conditions, as detailed in table 3. table 3 detailed profile of scenarios scenarios grid load demand 1 on < pv generation 2 on > pv generation 3 off < bess capacity 4 off > bess capacity 5 off < dg capacity 6 off > dg capacity 7 off > dg + bess capacity as discussed in the previous section, the algorithm tuning parameters greatly affect the final result of the algorithm. the best values of the fl and ap parameters in csa have also been determined as 2 and 0.1 [17, 22-24]. nevertheless, populationbased algorithms such as csa also depend on the flock size parameter. therefore, in this section, various flock size values are compared to find the best flock size parameter value for the csa to find the minimum operating cost with the lowest error value in the 24-hour simulation period. the error value is intended as the value of the equality constraints of generation power and demand. table 3 shows the results of system testing with a variety of different flock size values. it can be seen that the flock size value also affects the performance of the algorithm to overcome the ed problems. based on table 4, it can be concluded that the best flock size parameter is 40. it is proven that the system with this parameter value gets the minimum value both in the error value and the total operating cost for the 24-hour simulation period. advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 310 table 4 csa performance under various flock size values flock size error std. div total cost best mean worst 10 0 0.0822397 0.84183 0.177009574 98.198854 20 0 0.0441478 0.635726 0.129478714 95.801322 30 0 0.0346462 0.320607 0.073146489 95.635962 40 0 0.0107046 0.056599 0.015878668 94.498001 50 0 0.0306957 0.640118 0.127186635 94.835849 60 0 0.0273400 0.478794 0.095874636 95.141849 to prove the effectiveness of the csa algorithm in handling the ed problem, the hourly operation of the microgrid during the 24-hour simulation period is shown in fig. 4. based on the figure, it can be seen that during the peak load after 08:00, the proposed system can meet the load demand, even able to charge the bess and sell the excess power to the grid. on the other hand, when the pv system is unable to meet the load demand, the system combines bess, grid, and dg to meet the load demand while still keeping the objective of finding the lowest cost and considering the equality constraints of generation and demand. fig. 4 the hourly output energy pattern of campus microgrid using csa considering ed table 5 the total csa results for the ed problem in each scenario for several hours scenarios load (kw) pv (kw) bess charge (kw) bess discharge (kw) dg1 (kw) dg2 (kw) grid purchase (kw) grid sell (kw) cost ($) 1 238.230 390.931 24.243 0 0 0 0 128.457 43.019871 2 267.514 161.881 0 27.720 0 26.278 51.635 0 29.295997 3 275.43 265.213 0 10.217 0 0 33.500997 4 319.914 334.133 21.219 0 7 0 44.517511 5 336.470 355.329 18.859 0 0 0 45.741956 6 401.850 279.964 2.796 16.795 71.532 36.355 41.904463 7 544.477 402.278 10.958 10.983 105.185 36.987 70.292881 finally, the total csa results for the ed problem in each scenario for several hours are described in table 5. it should be noted that the scenarios were tested under various load demand conditions on different days for several hours in each scenario, resulting in different amounts of pv generations and load demand. from the table, it can be seen that the proposed system could handle different load demand conditions in both grid-connected and off-grid modes in all scenarios. in grid-connected mode, especially in scenario 1, the system is even able to sell excess generation back to the grid. in addition, in the worst-case scenario (scenario 7) when load demand exceeds the capacity of bess and dg, the system can meet the load demand and advances in technology innovation, vol. 8, no. 4, 2023, pp. 303-312 311 charge bess. fig. 5 presents the comparison of the total operational cost using the proposed method with the conventional method that optimizes the usage pattern of res as the main source [29]. the results obtained show that the implemented csa can reduce operating costs by 0.677% with a generation cost of $94.498001. fig. 5 cost comparison between energy control system using csa and conventional method considering optimized use of res [29] 5. conclusions this paper presents an optimal energy control system using csa that considers ed on a university campus microgrid using a der configuration consisting of pv, bess, and dg. the optimal capacity of the der is assumed to support optimal generation within the microgrid system. the overall control energy is optimized by csa to obtain the least operating cost while still considering the load demand. the optimal flock size parameter that can obtain a minimum value, considering both error and total operating costs, during a 24-hour csa simulation period, is 40. furthermore, the proposed system was tested in seven different scenarios under various load demands. in all scenarios, csa proves sufficient to meet the load demand. in addition, the proposed method has been compared with conventional methods considering the optimized use of res, and it has been proven that the proposed method can reduce operating costs better. the results of this study validate that the energy control model with csa, considering ed, offers optimal performance for the operation of the university campus microgrid. acknowledgments this research is partially supported by unnes electrical engineering students research group (ueesrg), universitas negeri semarang, and also sponsored by the lembaga penelitian dan pengabdian masyarakat (lp2m) universitas negeri semarang under grant no. 42.22.4/un37/ppk.4.5/2020 and previous grant research funding. conflicts of interest the authors declare no conflict of interest. references [1] d. nagpal and d. hawila, renewable energy market analysis: southeast asia, abu dhabi: irena, 2018. 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[29] m. a. prakasa and s. subiyanto, “optimal cost and feasible design for grid-connected microgrid on campus area using the robust-intelligence method,” clean energy, vol. 6, no. 1, pp. 59-76, february 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 4___aiti#9080___270-278 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 wave transmission and energy dissipation in a box culvert-type slotted breakwater nastain 1,2,* , suripin 3 , nur yuwono 4 , ignatius sriyana 3,† 1 doctoral program of civil engineering department, diponegoro university, indonesia 2 civil engineering department, jenderal soedirman university, indonesia 3 civil engineering department, diponegoro university, indonesia 4 civil and environmental engineering department, gadjah mada university, indonesia received 14 december 2021; received in revised form 12 april 2022; accepted 13 april 2022 doi: https://doi.org/10.46604/aiti.2022.9080 abstract this research is conducted to examine the transmission wave and energy dissipation of a box culvert-type slotted breakwater, which is designed as a breakwater structure with a watertight wall at the top and a box culvert type hole at the bottom. the process involves physical modeling of this structure in the laboratory. the hole and wave parameters are varied to determine the breakwater performance. the results show that the transmission coefficient (kt) value is reduced as the relative hole height (hl/d) value is decreasing and the relative hole length (b/l) and wave steepness (h/l) values are increasing. the energy dissipation coefficient (kd) value increases with an increment in hl/d, h/l, and b/l but starts to decrease after reaching the maximum, which is the optimum h × b/l 2 value. this optimum value is found to be 0.0034(hl/d) 2.618 depending on the (hl/d) value, while the maximum kd value is recorded to be 0.70. keywords: breakwater, box culvert, wave transmission, energy dissipation 1. introduction coastal protection using rubble mound breakwaters requires a large amount of construction material, and the dimensions required for deeper waters are usually higher, leading to an increase in the quantity of materials needed [1-4]. the use of natural stone in large quantities for construction, however, can damage mining sites and quarries and deplete limited natural resources. it is also not advisable to use rubble mound breakwaters because they require a good subgrade bearing capacity [1, 5-6]. one of the efforts directed towards solving this problem is using a wall-style perforated breakwater which can save on the quantity of construction material required and is also considered environmentally friendly due to its ability to ensure effective water circulation [4, 7-9]. however, the design of the model, in the form of a wall, shows it has a very small and negligible relative wall thickness (b/l) [10], making it less effective in reducing the incident wave height when the porosity of the hole (ε) and wave length (l) is large. theoretically, the energy dissipation coefficient (kd) of the thin wall perforated breakwater model is 0 when the porosity of the hole is 0, or 1 while the maximum is only 0.3 [11]. several studies have been conducted on the box culvert-type slotted breakwater with a focus on different types, since it was first proposed by jarlan [12], after investigating the hollow barrier model in front of the upright wall structure. for example, mackay and johanning [13] studied the hollow vertical wall model using analytical and numerical models. vijay et al. * corresponding author. e-mail address: nastain@unsoed.ac.id † corresponding author. e-mail address: sriyana808@gmail.com advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 [14] examined a multi-layer perforated wall model using physical and numerical models. furthermore, george and cho [11] analyzed a single wall model with a continuous horizontal perforation in the middle, while nikoo et al. [15] focused on a two-layer perforated wall model. ahmed and schlenkhoff [16] also studied a double wall model with holes in the middle, ahmed [9] examined a single wall model with vertical holes in the middle using a numerical model, and rageh and koraim [10] analyzed a single wall model with horizontal holes at the bottom. another study by rageh and koraim [1] focused on the vertical wall model with holes at the bottom, and ariyarathne [17] examined a massive structural model with holes at the top, while suh et al. [2] focused on the kaison model with vertical holes in some of the walls. however, no attention has been paid to the cross-sectional shape of the hole used, despite the important effect of the hole height (hl) and length (b) on the performance of a perforated breakwater in reducing wave height (hi) and incident wave energy (ei). furthermore, the use of a box culvert-type with a relatively large hole length (b) is expected to increase the effectiveness of the breakwater in reducing wave height and energy with a large hole porosity (ε). it is, therefore, important to note that the box culvert-type of the slotted breakwater has two parts: the upper (in the form of a waterproof wall structure) and the lower (in the form of a box culvert model). this research aims to examine the transmission and dissipation of wave energy through a box culvert-type slotted breakwater. the process involves determining the important parameters of hole and wave structure, such as relative hole height (hl/d), relative hole length (b/l), and wave steepness (h/l), using non-dimensional analysis. moreover, the parameters are varied to determine the breakwater performance using the transmission coefficient (kt) and energy dissipation coefficient (kd) values as indicators. 2. experimental program the research is conducted by physically modeling a wave flume, which is equipped with a wave generator, a wave damper, and a wave probe. the experiments are conducted to determine the transmission coefficient (kt) and energy dissipation coefficient (kd) of waves in the box culvert-type perforated breakwater model using different wave and hole structure parameters, obtained through non-dimensional analysis [18]. 2.1. materials the schematic diagram of the wave flume, model location, and wave probe tool is presented in fig. 1. the wave flume used has a length (p) of 15 m, a width (l) of 0.3 m, and a height (t) of 0.45 m, with one flap-type wave generator installed at one end and a wave absorber at the other end, to reduce reflections. moreover, three wave probes (wp) installed at the front and back of the model, with 0.01 cm accuracy, are used to measure the water level elevation. each of these probes is calibrated before being used for measurements. furthermore, the breakwater model is placed in the middle of the wave flume, or approximately 0.5 flume lengths from the wave generator or the wave absorber. fig. 1 wave flume, model location, and wave probe tool 2.2. physical model the breakwater model is produced using an acrylic material with a thickness (b) of 0.01 m and divided into two parts. the upper part is in the form of a watertight wall structure with a constant thickness (b) of 0.01 m. sinking height (hp) is varied at 271 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 0.100, 0.050, 0.025, and 0.000 m from the still water level, while the bottom is in the form of a box culvert model hole with the height (hl), varying at 0.100, 0.150, 0.175, and 0.200 m from the bottom of the flume and the length (b) at 0.2, 0.4, and 0.6 m. this means that 12 models are used for the experiment. the sketches and pictures of the box culvert-type slotted breakwater model are presented in fig. 2 and fig. 3. (a) side view (b) front view fig. 2 sketch of the box culvert-type slotted breakwater model fig. 3 model of the box culvert-type slotted breakwater 2.3. wave height measurement wave heights, including the incident (hi), reflection (hmax and hmin), and transmission (ht), are measured using a wave probe connected to the wave tide meter (wtm), and a computer is used to record the waves from the tide meter. two wave probes are used to measure the incident wave (hi) and reflection (hmax and hmin) wave heights. wave probe 1 (wp-1) is placed at a location 1.25l in front of the breakwater model to measure the minimum reflection wave height (hmin), and wave probe 2 (wp-2) is placed at a location as far as l in front of the breakwater model, to measure the maximum reflection wave height (hmax). this is according to the two-point method of dean and dalrymple [19], mani [20], murali and mani [21], koraim [22], koraim [5] and koraim [23]. to measure the transmission (ht) wave height using one wave probe, wp-3 is located at a distance of 2.0 m behind the breakwater model (wave damper side) [5, 22-23]. the wave length (l) based on the wave period (t) is calculated by using the dispersion equation, according to the linear wave theory. the position of the wave crest or the highest water level (the quasi-antinodes), as far as l from the breakwater model, is visually observed and marked as the wp-2 position. the position of the lowest water level (the quasi-nodes), as far as 1.25l in front of the breakwater model, is determined based on the l value which is calculated as the position of the wp-1 location. the measurement of wave height is repeated three times by shifting the positions of wp-1 and wp-2 slightly to the right and to the left from the initial position, so that the values of hmin and hmax are obtained. these placements are indicated in fig. 4. fig. 4 placement of the wave probe location on the model 272 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 the experiment is conducted at a constant water depth (d) of 0.2 m with the wave period t varied at 1.61, 1.34, 1.15, and 1.02 seconds or (h/l) at 0.0161, 0.0238, 0.0329, and 0.0452. moreover, four variations of relative hole height (hl/d) are used: 0.500, 0.750, 0.875, and 1.000, while the twelve variations of relative hole length (b/l) employed are: 0.093, 0.115, 0.138, 0.160, 0.186, 0.230, 0.277, 0.279, 0.319, 0.345, 0.415, and 0.479. analysis is conducted to determine the relationship between the transmission coefficient (kt) and energy dissipation coefficient (kd) of waves using non-dimensional parameters of the hole and wave structures, such as the relative hole height (hl/d), relative hole length (b/l), and wave steepness (h/l), as shown in eq. (1). , ( , , ) t d l k k f h d b l h l= (1) the transmission coefficient (kt) is calculated using the transmission wave height data (ht), as indicated in eq. (2), while the energy dissipation coefficient (kd) is determined using eq. (4) [16, 24]. moreover, the incident wave height (hi) and reflection wave height (hr) are calculated based on the maximum (hmax) and minimum reflection wave height (hmax) using partial standing wave theory in eq. (5) and eq. (6) [19]. t t i k h h= (2) r r i k h h= (3) 2 2(1 ) d t r k k k= − − (4) max min 2 i h h h + = (5) max min 2 r h h h − = (6) 3. results and discussion 3.1. effect of the relative hole height (hl/d) and wave steepness (h/l) on the transmission coefficient (kt) and energy dissipation coefficient (kd) the experiment is conducted using a constant hole length of the breakwater model (b) of 0.6 m, while (hl/d) is varied at 0.500, 0.750, 0.875, and 1.000as well as h/l at 0.0161, 0.0238, 0.0329, and 0.0452. the effect of the relative hole height (hl/d) and wave steepness (h/l) on the transmission coefficient (kt) is presented in fig. 5, while the effect on the energy dissipation coefficient (kd) is depicted in fig. 6. fig. 5 shows that a higher h/l and lower hl/d produce a lower kt, as indicated by b = 0.6 m, hl/d = 0.5 – 1.0, and h/l = 0.0161 – 0.0452 which produces a kt = 0.41 – 0.11 or causes a 73.17% reduction. the smallest value (0.11) is found at hl/d = 0.5 and h/l = 0.0452, while the largest (0.41) is at hl/d = 1.0 and h/l = 0.0161. this is associated with the ability of a greater h/l value to cause a steeper wave while a smaller hl/d value can cause a smaller porosity of the structure. this condition makes it difficult for the wave to pass through the breakwater, thereby making the transmission wave height smaller. the multivariate nonlinear regression analysis of the experimental data shows the relationship between the wave transmission coefficient (kt) with the hl/d and h/l functions, as shown in eq. (7), where r 2 = 0.967. 0.016 1.0876.594( ) 0.321( ) 6.226 t l k h l h d= − + + (7) 273 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 fig. 5 kt function of hl/d and h/l fig. 6 kd function of hl/d and h/l fig. 6 shows that an increment in hl/d and the reduction in h/l lead to an increase in the kd as indicated by b = 0.6 m, hl/d = 0.5 – 1.0, and h/l = 0.0161 – 0.0452, which produces a kd = 0.41 – 0.69 or causes a 68.29% increase. the smallest value (0.41) is recorded at hl/d = 0.5 and h/l = 0.0452, while the highest (0.69) is at hl/d = 1.0 and h/l = 0.0161. this reveals that a higher hl/d or porosity of the structure and smaller h/l or wave steepness can significantly reduce the wave energy. 3.2. effect of the relative hole length (b/l) and relative hole height (hl/d) on the transmission coefficient (kt) and energy dissipation coefficient (kd) the experiment is conducted using a constant steepness wave value h/l of 0.0452 while the length of the breakwater model hole (b) is varied at 0.2 m, 0.4 m, and 0.6 m and the hl/d at 0.500, 0.750, 0.875, and 1.000. the effect of the relative hole length (b/l) and relative hole height (hl/d) on the transmission coefficient (kt) is presented in fig. 7, while the effect on energy dissipation coefficient (kd) is specified in fig. 8. fig. 7 shows that a higher b/l and lower hl/d cause a reduction in kt, as indicated by the use of h/l = 0.0452, b/l = 0.160 – 0.479, and hl/d = 0.5 – 1.0, which produces a kt = 0.43 – 0.11 value or causes a 51.16% decrease. the smallest value (0.11) is found at b/l = 0.479 and hl/d = 0.5, while the highest (0.43) is recorded at b/l = 0.160 and hl/d = 1.0. this is associated with the ability of a greater b/l value to produce a greater frictional effect of fluid turbulence with the hole length b, as well as the smaller hl/d, which causes a smaller porosity of the structure. this condition makes it difficult for the wave to pass through the breakwater, thereby making the transmission wave height smaller. the multivariate nonlinear regression analysis of the experimental data shows the relationship between the wave transmission coefficient (kt) with the hl/d and h/l functions as presented in eq. (8), where r 2 = 0.977. 0.128 1.0500.932( ) 0.245( ) 0.849 t l k b l h d= − + + (8) 274 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 fig. 7 kt function of b/l and hl/d fig. 8 kd function of b/l and hl/d fig. 8 shows that a lower b/l and higher hl/d cause an increase in kd, which is indicated by 0.41 – 0.69 on the 68.29% increment recorded with h/l = 0.0452, b/l = 0.160 – 0.479, and hl/d = 0.5 – 1.0. meanwhile, the smallest value (0.41) is recorded with b/l = 0.479 and hl/d = 0.5, while the highest (0.69) is found with b/l = 0.160 and hl/d = 1.0. this indicates that higher hl/d or porosity of the structure and smaller b/l can significantly reduce the wave energy. 3.3. effect of the wave steepness (h/l), relative hole length (b/l), and relative hole height (hl/d) on the value of transmission coefficient (kt) and energy dissipation coefficient (kd) the experiment is conducted with the length of the breakwater model hole (b) varying from 0.2 m to 0.4 m and 0.6 m, while the hl/d is 0.500, 0.750, 0.875, and 1.000 and h/l is 0.0161, 0.0238, 0.0329, and 0.0452. the effect of the wave steepness (h/l), relative hole length (b/l), and relative hole height (hl/d) on the transmission coefficient (kt) is presented in fig. 9, while the effect on the energy dissipation coefficient value (kd) is illustrated in fig. 10. fig. 9 shows a higher h/l and b/l, which is represented as h × b/l 2 , and a lower hl/d is able to reduce kt as indicated by the use of h/l = 0.0161 – 0.0452 and b/l = 0.093 – 0.479, as well as hl/d = 0.5 – 1.0, to produce kt = 0.58 – 0.11 or 81.03% reduction. meanwhile, the smallest value (0.11) is found at h/l = 0.0452, b/l = 0.479, and hl/d = 0.5, while the highest value (0.58) is recorded at h/l = 0.0161, b/l = 0.093, and hl/d = 1.0. this is associated with the ability of a greater h/l and b/l to cause a steeper wave and hole length, leading to a greater frictional effect of fluid turbulence with hole length b, while a smaller hl/d is observed to cause a smaller structural porosity. this makes it difficult for the wave to pass through the breakwater, making the transmission wave height smaller. moreover, the multivariate nonlinear regression analysis of the experimental data shows the relationship between the wave transmission coefficient (kt) and h/l, b/l, and hl/d functions, as shown in eq. (9), where r 2 = 0.979. 0.839 2 0.3230.075( ) [( )]t lk h d h b l −= + × (9) 275 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 fig. 9 kt function of hl/d, b/l, and h/l fig. 10 kd function of hl/d, b/l, and h/l fig. 10 shows the increment in hl/d, h/l, and b/l, which is represented by h × b/l 2 and able to increase the kd, but the value decreases when the maximum value is obtained and the h × b/l 2 is at its optimum. this means more h × b/l 2 lead to a reduction in the kd. this optimum h × b/l 2 is recorded to be 0.0034(hl/d) 2.618 depending on the hl/d value. meanwhile, the maximum �� value is 0.7. this is because the higher hl/d can produce greater structural porosity so that the energy reduction is greater. furthermore, the greater the value of h/l and b/l, the effect of frictional fluid turbulence with the length of the hole will also be larger, so the energy reduction will be even greater. however, after reaching the optimum value of h × b/l 2 , the frictional effect of fluid turbulence with the hole length of b will be more of the wave resistance. as a result, the waves will be more likely to be reflected as reflection waves, and the energy reduction process will be reduced. the optimum value of h × b/l 2 is influenced by the value of hl/d used. the greater the value of hl/d, the higher the optimum value of h × b/l 2 . figs. 11-12 present the graphic nomogram of the relationship between kt and kd box culvert-type slotted breakwater with functions h/l, b/l, and hl/d for regular waves based on eq. (9) and eq. (4). this nomogram can, therefore, be used to determine the values of kt and kd while planning box culvert-type slotted breakwater for beach protection in the field. fig. 11 nomogram of kt function of hl/d, b/l, and h/l 276 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 fig. 12 nomogram of kd function of hl/d, b/l, and h/l 4. conclusions in this study, the transmission and dissipation of a box culvert-type slotted breakwater was designed as a breakwater structure (with a watertight wall at the top and a box culvert type hole at the bottom) and investigated. the results show that the wave transmission coefficient (kt) was reduced as the hl/d decreased and b/l and h/l increased, as indicated by h/l = 0.0161 – 0.0452, b/l = 0.093 – 0.479, and hl/d = 0.5 – 1.0 which produced a kt = 0.58 – 0.11 or caused an 81.03% reduction. moreover, the equation for the relationship among kt, h/l, b/l, and hl/d is kt = 0.075(hl/d) 0.839 × [(h × b/l 2 )]-0.23 . the energy dissipation coefficient (kd), however, increased as the hl/d, h/l, and b/l increased but later started reducing after reaching the maximum value at the optimum h × b/l 2 . this means that more h × b/l 2 led to a reduction in the kd. this optimum h × b/l 2 was recorded to be 0.0034(hl/d) 2.618 depending on the hl/d value. meanwhile, the maximum �� value was 0.7. conflicts of interest the authors declare no conflicts of interest. acknowledgments the authors would like to thank the staff and management of the hydraulic and hydrology laboratory, research center of engineering science, gadjah mada university, for providing the facilities to conduct this experiment. references [1] o. s. rageh, et al., “the use of vertical walls with horizontal slots as breakwaters,” 13th international water technology conference, pp. 1689-1710, march 2009. 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[7] z. huang, et al., “hydraulic performance and wave loadings of perforated/slotted coastal structures: a review,” ocean engineering, vol. 38, no. 10, pp. 1031-1053, june 2011. 277 advances in technology innovation, vol. 7, no. 4, 2022, pp. 270-278 [8] n. nurisman, “efektivitas submerged breakwater berlubang terhadap gelombang datang,” jurnal maritim indonesia, vol. 7, no. 2, pp. 165-175, december 2019. (in indonesian) [9] h. ahmed, “wave interaction with vertical slotted walls as a permeable breakwater,” ph.d. dissertation, department of civil engineering, bergischen universität wuppertal, germany, wuppertal, 2011. [10] o. s. rageh, et al., “hydraulic performance of vertical walls with horizontal slots used as breakwater,” coastal engineering, vol. 57, no. 8, pp. 745-756, august 2010. [11] a. george, et al., “hydrodynamic performance of a vertical slotted breakwater,” international journal of naval architecture and ocean engineering, vol. 12, pp. 468-478, december 2020. 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[24] b. m. webb, et al., “wave transmission through artificial reef breakwaters,” coastal structures and solutions to coastal disasters joint conference, pp. 432-441, september 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 278 4___aiti#8938_in press advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 an image synthesis method generating underwater images jarina raihan ahamed * , pg emeroylariffion abas, liyanage chandratilak de silva faculty of integrated technologies, universiti brunei darussalam, brunei darussalam received 18 november 2021; received in revised form 23 january 2022; accepted 24 january 2022 doi: https://doi.org/10.46604/aiti.2022.8938 abstract the objective of this study is to convert normal aerial images into underwater images based on attenuation values for different water types by utilizing the image formation model (ifm) with jerlov water types. firstly, the depth values are derived from rgb-d images. if the depth information is not available, the values between 0.5 m to 10 m are chosen, and the transmission map is estimated by these values. secondly, the statistical average background light values of br = 0.6240, bg = 0.805, and bb = 0.7651 have been derived by analyzing 890 images using two methods, namely quad-tree decomposition and four-block division. finally, the conversion of aerial-to-underwater images is done using the derived values, and the images are verified by computer simulation using matlab software. the result indicates that this method can easily generate underwater images from aerial images and makes it easier for the availability of ground truth. keywords: image processing, image synthesis, jerlov water types, underwater image analysis 1. introduction images that are captured underwater undergo distortions due to the optical properties of the water medium. suspended particles and lighting conditions in the water distort the finally captured images due to the effect of absorption, scattering, diffraction, polarization, and so on. these reduce the visibility factor, brightness, sharpness, and edge information of underwater images, as well as increase their contrast and noise. recently, image restoration and enhancement technologies have been increasingly used to restore underwater images and to recover useful information for various possible applications, such as seabed scene 3d reconstruction, target detection, classification of marine organisms, remotely operated vehicles [1], navigation and autonomous underwater vehicles (auvs), etc. [2-3]. image enhancement techniques, such as white balance, histogram equalization, and contrast stretching, may be used to recover the visibility, brightness, and contrast of images. however, degraded signal properties are not dealt with effectively by those techniques. hence, there is a need to rely on the restoration process. image restoration methods commonly rely on the underwater image formation model (ifm) to recover the degraded properties. with the development of underwater image recovering techniques, the image quality evaluation of the restored underwater images is required to appraise the effectiveness of different restoration methods. recently, non-reference metrics, i.e., underwater color image quality evaluation (uciqe) [4] and underwater image quality measure (uiqm) [5], have been introduced as performance metrics specifically for underwater images. these measures focus on the hue, saturation, variance, and chroma of images. however, these non-reference metrics cannot properly analyze the signal properties but only give importance to the color properties of underwater images. an alternative is to use a full-reference image quality evaluation metric, which relies on a reference or a ground truth image. in normal foggy air images, popular full-reference image quality * corresponding author. e-mail address: jari3010@yahoo.in advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 evaluation metrics including peak signal-to-noise ratio (psnr), structural similarity index (ssim), and mean square error (mse) may be used since ground truth images are easily obtainable. however, in an underwater scenario, it may be very difficult, if not impossible, to acquire a ground truth reference image for quality evaluation purposes. this makes it very challenging to use psnr, ssim, and mse as evaluation tools to compare the restoration methods of underwater images. an efficient dataset along with proper reference images is needed to evaluate different enhancement and restoration methods effectively. this study proposes a synthesis process for underwater images from aerial images. to create a publicly available dataset for underwater quality analysis, 890 aerial images are selected based on proper underwater image classification criteria and are then converted into underwater images. the synthesized underwater images are made based on jerlov water types [6]. these synthesized images, with their corresponding original images functioning as reference images, may then be used to evaluate the performance of image enhancement and restoration methods. the study is presented as follows. section 2 reviews the studies related to image enhancement and restoration methods, particularly for underwater images. section 3 presents the proposed synthesis method. section 4 compares the evaluation results of the dataset using the proposed method and the methods selected from the literature. finally, section 5 concludes the study. 2. related work: underwater enhancement, restoration, and synthesis dataset image enhancement methods improve the visibility characteristics of underwater images, such as contrast, histogram, and color constancy. hummel [7] proposed a basic enhancement approach by considering the histogram transformation of color channels. subsequently, zuiderveld [8] proposed an enhancement approach based on histogram equalization. iqbal et al. [9] proposed a two-fold method for enhancement, by first equalizing the color contrast and then adjusting the saturation of images. the same authors subsequently improve their proposed enhancement method, by using an enhanced unsupervised color-correction model (ucm) [10]. a histogram stretching approach has been proposed by huang et al. [11] for shallow water image enhancement, whilst ghani and isa [12] have proposed a method to enhance underwater images through the composition of dual-intensity images and rayleigh-stretching. however, the enhancement methods primarily concentrate on the visibility of images, not on their structural and signal properties. on the other hand, the restoration methods of underwater images normally utilize the ifm as shown in eq. (1) to restore the degraded signal properties. ( ) ( ). ( ) (1 ( )) ; { ,. , } c c c c c i x j x t x t x cb r g b= + − ∈ (1) in the above equation, �����. ����� describes the radiance ����� of an object as it travels in the underwater medium, whilst �1 − ������. �� represents the scattering of background light �� as it travels towards the camera. ���� is the observed image at the camera. the transmission map ����� describes the part of the object radiance that reaches the camera, after considering absorption and scattering. as such, it is dependent on the object’s distance from the camera ���� (or its depth) and the water attenuation coefficient �� in the color channel � ∈ {�, �, �}. ( ) ; { , ,) }( cc xd c rt x e g b − ∈= β (2) from eqs. (1) and (2), it can be seen that the radiance ����� of the object is attenuated exponentially with depth and water type. recovering the original object radiance ����� from the acquired image ���� at the camera requires the knowledge of the background light �� as well as the transmission map �����. 196 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 raihan et al. [13] provided a detailed review of underwater image restoration methods, categorizing restoration methods into hardware and software approaches. carlevaris-bianco et al. [14] proposed a restoration method by estimating the depth of an underwater image. the depth estimation method is based on the strong attenuation prior difference among three color channels (i.e., red, green, and blue channels), considering the channels with maximum intensity prior. dark channel prior (dcp) was initially introduced for the recovery of hazy images, but it has also been used for estimating both �� and ����� for the underwater image restoration process [15]. the method relies on the assumption that dark pixels in an image are the pixels close to the camera as they get less brightening effect, whilst bright pixels are the pixels far away from the camera. chao and wang [16] proposed a method for the removal of scattering effects from water using dcp. the variation of dcp has also been proposed by considering green and blue channels only, neglecting the red channel [17]. yang et al. [18] have also relied on the variation of dcp for the restoration of underwater images, by refining depth maps with a median filter instead of general soft matting. li et al. [19] proposed a blue-green channel restoration method by considering the extension of dcp and dehazing the red channel with gray-world assumption theory. chiang and chen [20] used dcp to estimate the transmission map and background light for underwater image restoration, using the fixed attenuation coefficient measured for the open ocean water. peng and cosman [21] proposed a method to restore the underwater images using a depth estimation process to develop the transmission map. song et al. [22] proposed a restoration strategy based on the depth map estimation, involving the formation of a depth map based on the attenuation priors for each channel, which is then used to extract the background light and transmission map. the literature points to the importance of image enhancement and restoration methods for different underwater applications. however, the performance comparison between different methods requires the presence of reference ground truth images, which may not be easily obtainable in difficult underwater conditions. conversely, with the presence of the original image �����, underwater images may be synthesized using eq. (1) to give ����. this needs to take into account the background light �� and transmission map �����. the synthesized underwater images may then be fed into different enhancement and restoration methods with their restored output images used to compare against the original reference image �����, to derive different reference image quality evaluation metrics. these metrics shall then be used as a basis to compare the performance of different methods. numerous methods for synthesizing underwater images have been proposed in the literature. zhao et al. [23] synthesized underwater images with depth values of 0.5 m to 3 m, which are a very short range for common underwater images. a fixed depth of 5 m has also been assumed and used to synthesize underwater images [17]. anwar et al. [24] proposed a synthesizing method by considering depth values in the range of between 0.5 m and 15 m, which is a good range for a dataset with the ambient light set between 0.8 and 1.0 for all three color channels. however, ideally, the ambient light in all three channels should not be assumed to be identical. liu and chen [25] have chosen the ambient light based on a statistical ambient light estimating process as depicted in the work of he et al. [15], and have considered the depth values derived from the original depth maps from the selected dataset, for synthesizing the underwater images. however, the method used to estimate the ambient light may not be feasible in cases of underwater images, as it has been primarily designed for aerial images. li et al. [26] have recently synthesized underwater images based on water types using the ambient light values ranging from 0.8 to 1.0 and the depth values between 0.5 m and 15 m. the method, however, lacks proper information on the ambient light as well as the depth value. 3. proposed method fig. 1 shows the flowchart of the proposed method, which is mainly governed by eq. (1). prior knowledge of water types, wavelengths, attenuation coefficients, depth, and background light is required in order to synthesize underwater images. water types and wavelengths are used to determine the attenuation coefficient ��, which is then used in the combination with the depth ���� to derive the transmission map ����� using eq. (2). the original image �����, the background light �� , and the derived transmission map ����� are then used to determine the synthesized image ����. 197 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 fig. 1 flowchart of the proposed method koczy and jerlov [6] have analyzed the characteristics of seawater and have subsequently classified them into 10 types, based on different attenuation coefficients for different wavelengths of light in different seawater types. the attenuation coefficients play a vital role in underwater computer vision. fig. 2 shows the classification made based on each type’s attenuation coefficient and wavelength. for more clarity, water types are classified broadly as oceanic and coastal waters. the oceanic water type includes type-i, type-ia, type-ib, type-ii, and type-iii subcategories, and the coastal water type includes type-1c, type-3c, type-5c, type-7c, and type-9c, from clear to turbid. type-iii and type-9c represent the most turbid in the oceanic water and coastal water categories, respectively. the attenuation coefficients for different water types are defined for the wavelength between 310 nm and 700 nm, which span the wavelength range of red, blue, and green lights underwater. each type has its shades of blue and brown, which are shown in fig. 3. there is a total of 30 synthesized images generated using the proposed method with 3 ground truths and 3 ground truth depth maps. the synthesis dataset which is created by using the proposed method can be found using the link https://github.com/jarinaraihan/underwater-synthesis-dataset. fig. 2 ten water types and their respective attenuation coefficients [24] fig. 3 visual shades of the ten water types [27] 198 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 solenko and mobley [28] have selected the attenuation coefficients for each wavelength based on the inherent properties of water, chlorophyll concentration, diffusion, scattering, and absorption. the wavelengths for red, green, and blue channels are taken as 650 nm, 525 nm, and 475 nm, respectively. based on the wavelengths, the attenuation coefficients are chosen and are given in table 1. for the synthesis of underwater images, according to eq. (1), ���� has to be synthesized using the given image ����� with the calculated transmission map ����� and background light �� . to determine the transmission map �����, the attenuation coefficient �� and depth map ���� are needed using eq. (2). the obtained attenuation coefficient values �� are shown in table 1. for a proper synthesis of underwater images, a ground truth depth map is of utmost importance. hence, rgb-d images are chosen from a random dataset for synthesis. if the depth information is not available, the values from 0.5 m to 10 m may be chosen. the reason for this is that 5 types of water become dark and lose their color as the depth increases beyond 10 m. unlike other synthesizing methods in the literature, the proposed method extracts the ambient light values by statistically evaluating the images based on two underwater ambient light estimation methods, which involve extracting the ambient light based on quad-tree decomposition and four-block division with the mean and standard deviation [21, 29]. nearly 890 images have been analyzed, with the statistical average background or ambient light values of br = 0.6240, bg = 0.805, and bb = 0.7651. table 1 attenuation coefficient values chosen based on jerlov water types [6] water type red channel blue channel green channel type-i 0.85 0.96 0.98 type-ia 0.84 0.95 0.97 type-ib 0.83 0.95 0.96 type-ii 0.80 0.92 0.94 type-iii 0.75 0.88 0.89 type-1c 0.75 0.88 0.87 type-3c 0.71 0.82 0.80 type-5c 0.67 0.73 0.67 type-7c 0.62 0.61 0.50 type-9c 0.55 0.46 0.29 4. results and discussion this section discusses the results obtained from different restoration and enhancement methods for synthesized underwater images using the proposed method. state-of-the-art restoration and enhancement methods are selected from the literature to restore the synthesized underwater images. their performance is appraised by conducting the quantitative and qualitative analysis of the restored underwater images. normal images are converted into underwater images based on eq. (1), with the attenuation coefficient values chosen based on table 1 for different water types. the original image (i.e., the ground truth image) and its corresponding ground truth depth map are given in fig. 4(a) and fig. 4(b), respectively. fig. 5 depicts the resultant images for different jerlov water types, which are synthesized from the original image in fig. 4(a). (a) ground truth image (b) ground truth depth image fig. 4 example of images from the dataset 199 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 (a) type-i (b) type-ia (c) type-ib (d) type-ii (e) type-iii (f) type-1c (g) type-3c (h) type-5c (i) type-7c (j) type-9c fig. 5 synthesis of the underwater images showing jerlov water types the resultant images in fig. 5 represent different underwater images for different water types. these representative underwater images are then processed using popular state-of-the-art restoration and enhancement methods in the literature, to give their corresponding restored images, which may then be compared to the ground truth image. both qualitative and quantitative analyses are used. the qualitative analysis involves the evaluation of restored or enhanced images based on visual perception, whilst the quantitative analysis utilizes performance metrics. 4.1. qualitative evaluation of underwater image processing methods using the synthesized images this section qualitatively analyzes the resultant synthesized images using the selected state-of-the-art enhancement methods and state-of-the-art restoration methods. this analysis is made with the synthesized type-iii underwater image as the input image, which is chosen for illustrative purposes. 4.1.1. qualitative analysis of resultant images from the selected enhancement methods fig. 6 shows the enhanced images using the selected enhancement methods, from the type-iii synthesized image in fig. 5(e). it can be seen that the enhancement methods generally produce visually appealing enhanced images. generally, the enhanced images have high contrast and brightness, and may look visually appealing. however, the enhancement methods may not be able to restore general characteristics of the images as compared to the restoration methods (as shall be discussed further). by using the enhancement method of zuiderveld [8], the produced image is almost similar to that produced by using restoration methods. by using histogram transformation [7], relative global histogram stretching method [11], and fusion method [30], the resultant images look over enhanced with plenty of noise. on the other hand, the ucm [10] and integrated color model (icm) [9] enhance the images well without much brightness and contrast, making the enhanced images look appealing. (a) image produced by the method of ancuti et al. [30] (b) image produced by the method of hummel [7] (c) image produced by the method of iqbal et al. [9] fig. 6 enhanced images using enhancement methods 200 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 (d) image produced by the method of huang et al. [11] (e) image produced by the method of iqbal et al. [10] (f) image produced by the method of zuiderveld [8] fig. 6 enhanced images using enhancement methods (continued) 4.1.2. qualitative analysis of resultant images from the selected restoration algorithms as mentioned in previous sections, the original type-iii synthesis image is input to the selected state-of-the-art restoration methods. the resultant restored images are given in fig. 7. it can be seen that, with the method of yang et al. [18], the image is produced with too much contrast, and hence the image has plenty of noise. with the methods of carlevaris-bianco et al. [14], chao et al. [16], and song et al. [22], the restored images are relatively cloudy and hazy. a low contrast image is produced by the method of he et al. [15]. since the restoration method of li et al. [19] considers only green and blue channels, the restored image looks improperly restored with a reddish tone. with the method of drews et al. [17], a highly saturated image is produced. on the other hand, with the method of peng and cosman [21], the resultant image is identical to the original reference image shown in fig. 4(a). (a) input image (b) image produced by the method of li et al. [19] (c) image produced by the method of peng et al. [21] (d) image produced by the method of yang et al. [18] (e) image produced by the method of carlevaris-bianco et al. [14] (f) image produced by the method of chao et al. [16] (g) image produced by the method of drews et al. [17] (h) image produced by the method of song et al. [22] (i) image produced by the method of he et al. [15] fig. 7 restored images using restoration methods 201 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 4.2. quantitative evaluation of underwater image processing algorithms using the synthesized images quantitative evaluation, using performance metrics, is an important analysis to prove the effectiveness of any method. both full-reference and non-reference evaluation metrics may be used. psnr and ssim may be used for full-reference evaluation, whilst uciqe [4] and uiqm [5] may be used for non-reference evaluation. psnr represents the number of errors in the restored image in comparison to the original reference image, whilst ssim represents the structural similarity between the restored image and the original reference image. both high psnr and ssim values indicate better performance of the enhancement or restoration methods. uciqe and uiqm are expressed as follows: 1 2 3c l s uciqe c c con c= × + + ×σ µ (3) where ��= 0.4680, �� = 0.2745, and �� = 0.2576. ��, ��� , and !" are the standard deviations of chroma, the contrast of luminance, and the average saturation of the image [4]. 1 2 3 uiqm v uicm v uism v uiconm= × + × + × (4) where #� = 0.0282, #� = 0.2953, and #� = 3.5753. underwater image colorfulness measure (uicm), underwater image sharpness measure (uism), underwater image contrast measure (uiconm) are the colorfulness, saturation, and contrast measures of the image [5]. high uciqe and uiqm values also indicate better performance of the enhancement or restoration methods. these performance metrics are used to quantitatively appraise the selected state-of-the-art enhancement and restoration methods. 4.2.1. quantitative analysis of resultant images from the selected enhancement methods table 2 gives the average psnr, ssim, uciqe, and uiqm values from the enhanced images using different enhancement methods, based on the synthesized images with different water types. the method of iqbal et al. [9] produces the enhanced images with better psnr and ssim scores than other methods because it utilizes icm in its enhancement process. the psnr and ssim values of 11.58 and 0.46, respectively, are obtained [9]. ucm [10], as a modified icm but concentrates primarily on low-quality images, is also used to produce notable psnr and ssim results, albeit lower than the results obtained by the method of iqbal et al. [9]. the method does not perform well in terms of uciqe and uiqm, either. the underwater images enhanced by the method of ancuti et al. [30] perform well, giving the uciqe, uiqm, and psnr values of 0.75, 1.84, and 10.01, respectively. the method of huang et al. [11] produces good color image metric scores, indicating that the method can enhance the synthesized underwater images well, in terms of the hue, saturation, variance, and chroma of the images. other methods, however, show comparatively worse performance. particularly, the methods of hummel [7] and zuiderveld [8] do not produce enhanced images with good performance values, and hence, may not be suitable to be used for enhancing underwater images with highly degraded conditions. table 2 quantitative evaluation of underwater enhancement methods enhancement method psnr ↑ ssim ↑ uciqe ↑ uiqm ↑ zuiderveld et al. [8] 8.71 0.25 0.55 1.49 hummel et al. [7] 4.82 0.14 0.63 1.50 iqbal et al. [9] 11.58 0.46 0.66 1.75 iqbal et al. [10] 9.70 0.42 0.52 1.42 huang et al. [11] 9.05 0.31 0.69 1.71 ancuti et al. [30] 10.01 0.33 0.75 1.84 *note: the highest value in each category is highlighted in bold. 202 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 4.2.2. quantitative analysis of resultant images from the selected restoration algorithms table 3 gives the psnr, ssim, uciqe, and uiqm values from the restored synthesized underwater images using different restoration methods. both the methods of peng et al. [21] and drews et al. [17] produce high metric scores. the former gives the highest psnr and uciqe values of 12.70 and 0.89, respectively, among the considered restoration methods, whilst the latter gives the highest ssim and uiqm values of 0.62 and 1.72, respectively. these highest values are relatively higher than the highest values obtained from the enhancement methods considered in table 2, except for the case in which the uiqm value is lower. other than the method of peng et al. [21], the methods of drews et al. [17] and he et al. [15] also produce good psnr and ssim values, effectively reducing noise and being capable of restoring structural properties of the image. with regard to the color analysis (i.e., uciqe and uiqm), the method of carlevaris-bianco et al. [14] performs relatively better than other restoration methods, indicating that the color properties of the images can be properly restored, although the method does not perform well in terms of psnr and ssim. the method of song et al. [22] produces average performance in both the full-reference and non-reference metrics. however, other restoration methods do not perform well in this quantitative metric analysis. recently, raihan et al. [31] have developed a restoration method of underwater images using depth estimation and attenuation priors, which produces good results for real as well as synthesized underwater images. table 3 quantitative evaluation of underwater restoration algorithms restoration method psnr ↑ ssim ↑ uciqe ↑ uiqm ↑ he et al. [15] 10.15 0.41 0.55 1.45 li et al. [19] 2.97 0.14 0.19 1.02 peng and cosman [21] 12.70 0.55 0.89 1.61 yang et al. [18] 1.21 0.07 0.05 1.18 carlevaris-bianco et al. [14] 7.23 0.27 0.65 1.49 chao et al. [16] 8.45 0.31 0.54 1.51 drews et al. [17] 11.02 0.62 0.58 1.72 song et al. [22] 8.76 0.35 0.70 1.43 *note: the highest value in each category is highlighted in bold. 5. conclusions in this study, the generation of underwater images from aerial images has been performed. due to the conditions of the water medium, underwater images may contain a lot of disturbances, requiring enhancement and restoration before extracting useful information. however, the lack of an underwater dataset and the absence of ground truth reference images are the main challenges for research in this area. the following are the observations from the study. (1) the process starts with reference images, and hence can be used for performance evaluation of underwater image processing methods. (2) the test dataset has been developed based on the jerlov water types, covering all imaging conditions of an underwater environment. for the development process, the background light has been chosen based on the statistical analysis done on a large real underwater image dataset. attenuation coefficients of 10 water types have been utilized for the design. the synthesis method is efficient and is capable of producing a large synthesized underwater image dataset. (3) selected image processing methods have been used to demonstrate the effectiveness of the synthesized dataset, by quantitatively and qualitatively analyzing the output images of the methods. (4) enhancement algorithms work well in high turbid conditions, but does not perform well in low turbid images. this is because the enhancement methods focus on the visibility conditions. in contrast, restoration methods focus on structural 203 advances in technology innovation, vol. 7, no. 3, 2022, pp. 195-205 characteristics and noise parameters, so they work well only in low turbid conditions and provide reduced visibility characteristics. (5) the proposed synthesis method can properly evaluate the performance of underwater image processing methods, by providing both synthesized underwater images and their corresponding ground truth images. the above analysis helps the researchers in this field to choose underwater image processing algorithms that work well in underwater images and paves ways to make improvements for further research purposes. the proposed synthesis method can not only be used to evaluate and improve the underwater image processing methods but also to test the suitability of any computer vision algorithms for different underwater applications. conflicts of interest the authors declare no conflict of interest. references [1] d. w. jung, s. m. hong, j. h. lee, h. j. cho, h. s. choi, and m. t. vu, “a study on unmanned surface vehicle combined with remotely operated vehicle system,” proceedings of engineering and technology innovation, vol. 9, pp. 17-24, july 2018. 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[31] a. j. raihan, p. e. abas, and l. c. d. silva, “ restoration of underwater images using depth and transmission map estimation, with attenuation priors,” ocean systems engineering, vol. 11, no. 4, pp. 331-351, november 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 205 microsoft word 1-v8n1(2023)-aiti#10548(29-37).docx advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 on the estimation of the mission performance index of unmanned surface vehicles based on the mission coverage area jae-yong lee, nam-sun son* department of autonomous & intelligent maritime systems research division, korea research institute of ships & ocean engineering, daejeon, korea received november 12, 2021; received in revised form 07 may 2022; accepted 08 may 2022 doi: https://doi.org/10.46604/aiti.2023.10548 abstract for mission planning and replanning of multiple unmanned surface vehicles (usvs), it is important to estimate each usv’s mission performance in terms of sea surveillance (e.g., illegal ship control). in this study, a mission performance index (mpi) is proposed based on the mission coverage area for estimating the usvs’ mission performance of illegal ship control. the penalty value is considered in the mpi calculation procedure owing to the track-off of the usv. in addition, the usv simulation is conducted under illegal ship control, and the mpi is calculated based on changing the mission coverage area. the results show that the mpi increases with the path width of the mission coverage area. keywords: unmanned surface vehicle (usv), mission coverage area, mission performance index (mpi), illegal ship control, usv simulation 1. introduction generally, an unmanned surface vehicle (usv) is a small ship (1.5 to 15 m and 0.5 to 9 t) that can be controlled remotely or autonomously to perform missions under unfavorable weather conditions [1]. although usvs are typically developed for military use, they have also been applied to marine transportation, marine surveys, response to trespassing ships in sea farms, sea rescue, and fusion with underwater remotely operated vehicles [2-5]. furthermore, the international maritime organization has been reviewing international agreements on maritime safety and security regarding maritime autonomous surface ships [6]. currently, asian countries (e.g., korea) are conducting government-supported projects in maritime industries, such as shipping, ports, shipbuilding, and offshore [7]. recently, owing to the fourth industrial revolution, unmanned, automated, and online fields have been highlighted. accordingly, usv-related studies have been conducted to support or replace the missions performed by manned ships [8-9]. in particular, illegal ship control is important for monitoring usvs for mission planning and replanning [10]. in this study, the mission performance index (mpi) is defined to estimate the mission performance of multiple usvs using the mission coverage area for sea surveillance, such as illegal ship control. the mpi is estimated using the resulting trajectory of the usv, which is the ratio of the individual mission area to the total mission coverage area. to evaluate the mpi, a usv simulation is conducted under illegal ship control. in this study, the features of the mpi for the usv and the simulation results are described. * corresponding author. e-mail address: nnso@kriso.re.kr tel.: +82-42-3636; fax: +82-42-3624 advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 30 previous studies pertaining to path following and target tracking are explained in section 2. the proposed mpi-based estimation method for usvs is presented in section 3. the verification of the mpi via simulation is described in section 4, and the conclusions and future studies are provided in section 5. 2. previous path-following and target-tracking investigations in the korea research institute of ships and ocean engineering, the aragon series of usvs (aragon1, aragon2, and aragon3) was developed through a project entitled “development of multipurpose intelligent unmanned surface vehicle” [10]. recently, usv swarms have been investigated using the aragon series of usvs through a project entitled “development of situation awareness and autonomous navigation technology of usv based on artificial intelligence” [11]. in this study, a usv (aragon1) was used as an illegal ship to simulate illegal ship control, where the vehicle steers away from a patrol ship (i.e., another usv (aragon3)) via path following. therefore, a path-following algorithm is required when aragon3 trails aragon1’s escape path. previously, a path-following algorithm was developed using the line-of-sight (los) [12]. as shown in fig. 1, the heading angle must be controlled for path-following control. in this case, wpk is the waypoint of k (xk, yk), pt is the current position (xt, yt) of the usv, ψt is the heading angle, and δt is the nozzle angle of the waterjet. the target heading angle (ψtc) was calculated using the waypoint of k, and the position of aragon1 was calculated using the los for path following [12]. in other words, aragon3 was used for illegal ship control. a target-tracking algorithm is required for a patrol ship (i.e., aragon3). yun et al. [13] developed a target-tracking algorithm using the concept of virtual points, as illustrated in fig. 2. their proposed usv was used as a patrol ship to track the target ship (illegal ship) in the starboard and port or stern. when tracking a target ship, the usv must maintain a certain direction with a separation distance at a specific speed. as shown in fig. 2, the usv tracks the target ship via virtual points “a” and “b.” in this case, virtual point “a” is generated by the heading angle of the target ship, and virtual point “b” is generated by the separation distance from the target ship. the target-tracking algorithm is based on tracking a target ship with the los angle. in addition, various international studies related to path following and target tracking have been conducted [14]. an improved los guidance algorithm that can be adjusted based on the path-following error was investigated [15]. additionally, a deep reinforcement learning method for solving the path-following problem of the usv has been investigated based on the decision-making network [16-17]. the straight-line target control of usvs has been investigated based on maneuverability and agility using the straight-line concept with high speed [18]. the purpose of this study is to estimate the mpi using the resulting trajectory of an illegal ship (aragon1) and a patrol ship (aragon 3). in this study, the path-following algorithm is applied to an illegal ship (aragon1) using the los, and the target-tracking algorithm is applied to the patrol ship (aragon3) using the concept of virtual points. fig. 1 path-following algorithm [12] fig. 2 target-tracking algorithm [13] advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 31 3. estimation of mpi 3.1. concept of mpi the performance of usvs for mission planning and replanning is to be estimated. the mpi is calculated using the resulting trajectory of the usv, i.e., the ratio of the individual mission area to the mission coverage area. as shown in fig. 3, the mission coverage area is in the sea environment of illegal ship control, where the fairways of ships are extremely narrow owing to fish farms, tides, and reefs. the mpi is to be analyzed while the path width of the mission coverage area is changed from “2l” to “6l.” in addition, if the usv is outside the mission coverage area, then mpi* is applied to estimate the mpi while considering the penalty, as shown in fig. 4. fig. 3 concept of mpi and cases of mission coverage area with various path widths fig. 4 concept of mpi and penalty area 3.2. procedure of mpi estimation in this study, the mpi was estimated to analyze the mission performance of the usvs. the overall procedure is summarized in table 1. first, the usv information was input, including the name, length, breadth, and speed of the usv. the trajectory information of the usv was selected from the simulation results, and the mission coverage area was set using various path widths. next, the penalty area was calculated by considering the track-off from the mission coverage area. finally, the mpi was estimated using the mission coverage area and penalty area. table 1 procedure for estimating mpi* step description 1 input information of usv 2 select trajectory information of usv 3 set mission coverage area (path width: 2l to 6l) of usv 4 calculate usv trajectory area 6 calculate penalty area 7 estimate mpi advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 32 fig. 5 flowchart for estimating mpi fig. 6 example of mpi estimation a flowchart of mpi estimation is shown in fig. 5. the path width was changed from 2l to 6l to verify the change in the estimated mpi. furthermore, the total area of the usv trajectory (cat(i)), total mission coverage area (tmc(i)), and penalty area (pa(i)) were calculated using the equations shown in fig. 5. mpi#(i) is the ratio of the relative mpi*(i) of the usv to the mpi in the case of the resulting trajectory without track-off. an example of mpi estimation is shown in fig. 6. the notations used in mpi estimation are presented in the nomenclature section. here, information regarding aragon1 and aragon3 is shown, such as the latitude, longitude, waypoints, speed, and heading. the mission coverage area (eq. (1)), usv trajectory area (eq. (2)), and penalty areas (eq. (3)) are calculated as follows: advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 33 1 ( ) ( ( ) ) 2 4 6) n jj tmc i wd i li or or = = × ( × (1) 1 ( ) ( ( ) ) ( ) n jj cat i d i b i = = × (2) 1 ( ) ( ( ) ) ( ) n jj pa i gd i b i = = × (3) 4. simulation and results 4.1. simulation scenario in this study, a simulation pertaining to the illegal control of a usv was conducted in gwangam port, korea to verify the proposed mpi-based estimation method. as illegal ships frequently appear on sea farms, a sea farm was selected as the game area for the simulation. aragon1 was used as an illegal ship, and aragon3 was used as a patrol ship for illegal ship control. the escape path of aragon1 was planned in advance by considering the zone of the sea farm, as shown in fig. 7, and aragon1 trailed this path using the path-following algorithm based on the los [12]. aragon3 chased the illegal ship (aragon1) for illegal ship control using the target control algorithm based on the concept of virtual points [13]. table 2 summarizes the information regarding aragon1 and aragon3. the usv simulation was conducted via dynamic simulation based on the nomoto model [19]. the resulting trajectories of aragon1 and aragon3 using the path-following and target-tracking algorithms are shown in fig. 8. fig. 9 shows the histories of the speed and heading angle of aragon1 and aragon3 based on the simulation. as shown in figs. 8 and 9, the simulation was conducted with the path widths ranging from “2l” to “6l” to verify the change in the estimated mpi. the red and blue lines represent the resulting trajectories of aragon1 and aragon3, respectively. the path-following algorithm of aragon1 was successfully conducted at a speed of 10 knots. furthermore, the target control algorithm of aragon3 was successfully implemented at a high speed in the simulation. the heading error between aragon1 and aragon3 can be determined because aragon3 tracks aragon1 via the target-tracking algorithm on the stern side. fig. 7 path of aragon1 and location of sea farm table 2 information regarding aragon1 and aragon3 no. ship length (m) breadth (m) maximum speed (knot) 1 illegal ship (aragon1) 8 2.5 10 2 patrol ship (aragon3) 8 2.5 max 20 advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 34 fig. 8 resulting trajectories of aragon1 and aragon3 (a) speed of aragon1 and aragon3 (b) heading angle of aragon1 and aragon3 fig. 9 time histories of the speed and heading angle of aragon1 and aragon3 4.2. analysis of mpi based on simulation results as shown in tables 3 and 4, the mpi* exceeds 95% for the illegal ship (aragon1) and patrol ship (aragon3). this implies that aragon1 successfully conducted path following as an illegal ship, and aragon3 successfully conducted target tracking as a patrol ship. the mpi# of aragon1 was 4.9% higher than that of aragon3, on average. this is because aragon1 adhered to the designated path, whereas aragon3 tracked aragon1. therefore, aragon3 exhibited track-off in target control owing to the heading error during target tracking. furthermore, as the path width of the mission coverage area widened (from 2l to 6l), mpi# increased because the penalty area in both aragon1 and aragon3 reduced. table 3 mpi results mission coverage area index units aragon1 aragon3 2l cat(i) (m2) 4,611.62 4,847.85 np(i) (ea) 84 1,399 pa(i) (m2) 210 3,497.5 tmc(i) (m2) 29,948.91 31,591.37 advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 35 table 3 mpi results (continued) mission coverage area index units aragon1 aragon3 4l cat(i) (m2) 4,611.62 4,847.85 np(i) (ea) 25 858 pa(i) (m2) 62.5 2,145 tmc(i) (m2) 60,084.80 63,563.23 6l cat(i) (m2) 4611.62 4,847.85 np(i) (ea) 0 299 pa(i) (m2) 0 747.5 tmc(i)) (m2) 89,869.70 95,389.62 table 4 comparative analysis of relative mpi* without track-off path width usv mpi* mpi# (%) = cat(i) ÷ (tmc(i) + pa(i)) = mpi* ÷ [(b(i)) ÷ (path widths)] × 100 2l aragon1 0.1529 97.86 aragon3 0.1381 88.42 4l aragon1 0.0766 98.14 aragon3 0.0738 94.44 6l aragon1 0.0513 98.52 aragon3 0.0504 96.82 5. conclusions and future studies in this study, an mpi was defined to estimate the mission performance of multiple usvs using the mission coverage area. in particular, the penalty value was considered in the mpi calculation procedure owing to the track-off of the usv. to verify the proposed mpi-based estimation method, illegal ship control was simulated using an illegal ship (aragon1) and a patrol ship (aragon3). the illegal ship (aragon1) and patrol ship (aragon3) successfully conducted path following and target tracking, respectively. therefore, the mpi exceeded 4.9%. the mpi of the illegal ship (aragon1) was higher than that of the patrol usv (aragon3) because aragon1 adhered to the designated path, whereas aragon3 indicated track-off during target tracking. furthermore, as the path width of the mission coverage area increased (from 2l to 6l), the mpi increased owing to a decrease in the penalty area. in the future, the authors will conduct an experiment pertaining to illegal ship control in an actual sea using multiple usvs; subsequently, the experimentally obtained mpi will be compared with simulation results. nomenclature notation units definition i number of ith usvs (aragon1 or aragon3) n(i) name of ith usv (aragon1 or aragon3) l(i) m length of ith usv b(i) m breadth of ith usv v(i) knot speed of ith usv ψ(i) ° heading of ith usv lg(i)j ° jth trajectory point of longitude for ith usv lt(i)j ° jth trajectory point of latitude for ith usv p(i)xj m x value converted from lgij of jth trajectory point in ith usv p(i)yj m y value converted from ltij of jth trajectory point in ith usv d(i)j m distance between usv trajectories; ����� = ������ − ���� � �� + ������ − ����� � �� td(i)j m total distance of usv trajectory; ������ = ∑ ���� �� j cat(i) m2 total usv trajectory area; ������ = ������ × ���� w(i)xj m x of jth waypoint for ith usv w(i)yj m y of jth waypoint for ith usv advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 36 wd(i)j m distance between waypoints; ������ = ������ − ���� � �� + ������ − ����� � �� tmc(i) m2 total mission coverage area; ������ = ∑ ������� × ����� × path width �� � g(i)xj m x of jth waypoint for ith usv outside mission coverage area g(i)yj m y of jth waypoint for ith usv outside mission coverage area gd(i)j m distance between waypoints outside mission coverage area; ������ − &��� �� + ������ − &���� �� np(i) number of points deviating from mission coverage area for ith usv (ea) pa(i) m2 penalty area; ����� = ∑ �'������ × ����� �� mpi(i) mission performance index; ��(��� = ������ ÷ *��� + �����+ mpi#(i) % ratio of relative mpi* of usv to mpi for case involving resulting trajectory without track-off; ��(#��� = ��(∗ ÷ ������ ÷ �path width� × 100 acknowledgments this study was supported by the project titled “development of situation awareness and autonomous navigation technology of unmanned surface vehicle based on artificial intelligence (pes3880, pes4270),” which was funded by the korea research institute of ships and ocean engineering. conflicts of interest the authors declare no conflicts of interest regarding the publication of this study. references [1] v. bertram, “unmanned surface vehicles—a survey,” skibsteknisk selskab, vol. 1, pp. 1-14, january 2008. [2] j. e. manley, “unmanned surface vehicles, 15 years of development,” oceans, pp. 1-4, september 2008. [3] d. w. jung, et al., “a study on unmanned surface vehicle combined with remotely operated vehicle system,” proceedings of engineering and technology innovation, vol. 9, pp. 17-24, july 2018. [4] j. ansary, et al., “swarms of aquatic unmanned surface vehicles (usv), a review from simulation to field implementation,” proceedings of international design engineering technical conferences and computers and information in engineering conference, vol. 83914, pp. 436-528, august 2020. [5] n. s. son, et al., “on the sea trial test for the validation of an autonomous collision avoidance system of unmanned surface vehicle, aragon,” proceedings of the oceans 2018 mts/ieee charleston, pp. 1-5, october 2018. 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[14] m. a. bin mansor, et al., “motion control algorithm for path following and trajectory tracking for unmanned surface vehicle: a review paper,” proceedings of the 3rd international conference on control, robotics, and cybernetics, pp. 73-77, september 2018. advances in technology innovation, vol. 8, no. 1, 2023, pp. 29-37 37 [15] t. liu, et al., “path following control of the underactuated usv based on the improved line-of-sight guidance algorithm,” journal of polish maritime research, vol. 24, no. 1, pp. 3-11, april 2017. [16] y. zhao, et al., “path following optimization for an underactuated usv using smoothly-convergent deep reinforcement learning,” ieee transactions on intelligent transportation systems, vol. 22, no. 10, pp. 6208-6220, october 2021. [17] j. h. woo, et al., “deep reinforcement learning-based controller for path following of an unmanned surface vehicle,” ocean engineering, vol. 183, pp. 155-166, july 2019. 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[19] t. i. fossen, guidance and control of ocean vehicles, new york: john wiley and sons, 1994. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 6___aiti#10525___ advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 an experimental study on the mechanical properties of low-aluminum and rich-iron-calcium fly ash-based geopolymer concrete jack widjajakusuma1,*, ika bali2, gino pranata ng1, kevin aprilio wibowo1 1department of civil engineering, pelita harapan university, tangerang, indonesia 2department of civil engineering, president university, cikarang, indonesia received 10 december 2021; received in revised form 24 may 2022; accepted 25 may 2022 doi: https://doi.org/10.46604/aiti.2022.10525 abstract limited studies have been conducted on low-aluminum and rich-iron-calcium fly ash (laricfa)-based geopolymer concrete with increased strength. this study aims to investigate the mechanical characteristics of laricfa-based geopolymer concrete, including its compressive strength, split tensile strength, and ultimate moment. the steps of this study include material preparation and testing, concrete mix design and casting, specimen curing and testing, and the analysis of testing results. furthermore, the specimen tests consist of the bending, compressive, and split tensile strength tests. the results show that the average compressive strength and the ultimate moment of the geopolymer concrete are 38.20 mpa and 22.90 kn·m, respectively, while the average ratio between the split tensile and compressive strengths is around 0.09. therefore, the fly ash-based geopolymer concrete can be used in structural components. keywords: geopolymer concrete, fly ash, rich iron, low aluminum, mechanical characteristics 1. introduction geopolymer concrete with volcanic ash (class n in the astm c 618-19 classification) was used during ancient roman times as a building material. it is seawater resistant with durability that reaches thousands of years [1]. many studies showed that the geopolymer concrete from fly ash has better resistance to seawater and chloride in comparison to normal concrete [2-4]. however, the chemical processes behind the formation of geopolymers are not clearly understood. these processes can be simplified into three stages [5-7]. the first is the dissolution of silicate and aluminum elements from fly ash dust in an alkaline solution to produce aluminate and silicate species. commonly used alkaline solutions include naoh, koh, and na2sio3. meanwhile, the second is the process of forming aluminosilicate oxide gels, and the third is the polycondensation process which is a gel network arrangement that produces three-dimensional aluminosilicate networks. furthermore, reactive aluminum plays an important role in the structure and strength of fly ash geopolymers [6, 8]. chemical compounds such as calcium and iron have other effects during polymerization processes. calcium will react with silicon and aluminum to form various phases of calcium silicate and aluminate hydrates due to the contribution of water. this chemical reaction is accelerated by the presence of aluminate and silicate types dissolved in the geopolymerization process. similar chemical reactions also occur in portland and calcium aluminate cement [9]. the presence of calcium plays an important role in accelerating the geopolymer pavement process [5, 10] due to its ability to harden at room temperature [11-12]. currently, knowledge about the role and location of calcium in geopolymer structures is still very limited [6]. * corresponding author. e-mail address: jack.widjajakusuma@uph.edu tel.: +62(0)21 5460901; fax: +62(0)21 5460910 advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 several recent studies stated that iron oxide has an important role in the formation of geopolymers [13-14]. venyite et al. [15] stated that limited aluminate leads to the replacement of aluminum (al) by iron (fe) atoms to form ferro-silicate-aluminate. furthermore, studies on the role of iron oxide in the polymer formation process are still very limited. this is due to limited methods for analyzing geopolymer structures. the method most often used in geopolymer analysis is nuclear magnetic resonance spectroscopy (nmr), which will be disturbed in the analysis if there is a high iron element [15-16]. the study from gomes et al. [17] stated that iron oxide decreases the strength of geopolymer concrete, although venyite et al. [15] had a different result. apart from the chemical content of fly ash, several parameters that also determine the strength of geopolymer concrete are dust grains fineness, temperature and duration of curing, type and molarity of alkali activator, and ph [5, 10, 18]. this study is motivated to investigate the fly ash-based geopolymer concrete, due to the limited studies on rich-iron and low-aluminum fly ash-based geopolymer concrete with increased strength. in addition, this study is motivated by the need of using local waste in the form of fly ash as a substitute for cement in indonesia. according to a new regulation enacted by the indonesian government, i.e., government regulation no. 22 of 2021 on the implementation of environmental protection and management, the classification of the fly ash resulting from combustion at steam power plants has been revised from toxic waste to non-toxic waste. through this regulation, the indonesian government encourages the use of fly ash as much as possible. one possible application is to use fly ash as construction materials. since 2015, the indonesian government has launched a program to build a million houses per year for the people of indonesia. in particular, since the covid-19 pandemic occurred in 2019, the need for “fit-for-purpose” housing has been one of the needs that must be met because almost all activities, including work, study, and worship, are carried out within homes. this study aims to investigate the mechanical characteristics (e.g., the compressive strength, split tensile strength, and ultimate moment) of low-aluminum and rich-iron-calcium fly ash (laricfa)-based geopolymer concrete. the results are expected to aid the indonesian government in substituting normal concrete with laricfa-based geopolymer concrete and building residential houses that are environmentally friendly and cheaper than those made from portland cement. in this study, the specimens made are treated at room temperature and meet the requirements for compressive strength and ultimate moment. furthermore, the fly ash used has low al2o3 (< 10%), which is equivalent to the content in portland cement. it also has a very high fe2o3 (nearly 50%) and calcium content (>10%). to carry out the investigation, the study steps are divided as shown in fig. 1. \ material preparation: fly ash, naoh, na2sio3, cement, water, aggregate material testing: xray fluorescence (xrf) test for fly ash, specific gravity, water content, sludge level, sieve analysis mix design calculation for normal concrete geopolymer concrete casting for specimens specimens curing specimens testing: compressive strength, split tensile strength, bending feasibility of substitution normal concrete through laricfa geopolymer concrete mix design calculation for geopolymer concrete normal concrete casting for specimens fig. 1 study methodology 296 advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 2. material and method the main study materials for geopolymer concrete formation are fly ash, alkaline solution (as an activator), and coarse and fine aggregates, which are described in this section. the fly ash used is obtained from the steam power plant of suralaya, banten, indonesia. furthermore, table 1 provides chemical compositions based on the results from the x-ray fluorescence (xrf) test. the content of sio2 + al2o3 + fe2o3 is equal to 76.14% which is greater than 70%. based on the astm c 618-19 standard, the fly ash belongs to class f, with high iron oxide impurities and low alumina content. its cao content is also high (18.24%), which causes geopolymers to quickly harden at room temperature [19]. in polymer concrete, the alkaline solution acts as an activator that dissolves and binds silica and alumina contained in fly ash so that a polymerization reaction occurs. the alkaline solutions used in this study are natrium hydroxide (naoh) and natrium silicate (na2sio3). furthermore, the coarse aggregate used for both the polymer and normal concrete is screened and has a maximum size of 1.50 cm. the fine aggregate used in this study is silica sand passing sieve no. 30 (600 µm). both the coarse and fine aggregates are tested according to astm c127, astm c128, astm c33, and sni 1964-2008. therefore, the specific gravity test results under saturated surface dry (ssd) conditions for coarse and fine aggregates are 2.38 and 2.62, respectively, with a 0.55% water content by the aggregate weight and a 4.92% sludge content by the aggregate weight. cement such as portland composite cement is used as a binder in normal concrete. for the ultimate moment testing of concrete beams, the reinforcing steel used is bjtp-24 with diameters of 8 and 12 mm and the average yield stress (��) of 392.85 mpa. the mix design of the geopolymer (8 molarity/m naoh) and normal concrete (target compressive strength 30+10 mpa) in this study can be seen in table 2. furthermore, the naoh content prepared is 8 m and placed at room temperature for 24 hours before use. na2sio3, commonly called water glass, is one of the materials that make up an alkaline solution which can be in the form of a liquid or a solid. in this study, the water glass used is a liquid with 55% natrium silicate concentration and 45% water. natrium silicate is made by mixing sio2 with natrium (na2sio3) or potassium carbonate (k2co3) dissolved with high-pressure steam leading to a thick (semi-viscous) liquid nature [20]. table 1 chemical composition of fly ash compound name concentration (%) fe2o3 48.51 sio2 21.06 cao 18.24 al2o3 6.58 k2o 1.42 p2o5 1.02 so3 0.87 bao 0.69 mno 0.55 sro 0.47 mgo 0.30 zno 0.10 zro2 0.08 na2o 0.05 rb2o 0.03 cl 0.02 br 0.02 y2o3 0.01 297 advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 table 2 mix design of the geopolymer and normal concrete material (kg/m3) geopolymer concrete normal concrete coarse aggregate 853.95 1033.64 fine aggregate 727.44 497.68 fly ash (type f) 470.51 water glass 179.97 naoh 15.30 naoh water 44.69 water 205.00 cement 508.69 fig. 2 reinforcement steel for geopolymer concrete-1 and normal concrete-1 beams fig. 3 compressive strength test fig. 4 tensile strength test fig. 5 bending test on the concrete beam the concrete specimens used in this study are cylinders with a diameter and height of 100 and 200 mm, respectively, for determining the compressive and split tensile strength. meanwhile, the beam specimens for conducting the bending test have dimensions of 1600 mm × 125 mm × 250 mm. the geopolymer concrete beam dimensions are selected to analyze the casting process and test the object characteristics so that the geopolymer concrete beams can be compared with typical beams used in the structure of standard residential houses. all beam specimens use an upper reinforcement of 2 ø8, while for lower reinforcement there are two variations, namely 2 ø12 and 3 ø12. the lower reinforcement 2 ø12 is used for the geopolymer and normal concrete-1 specimens (fig. 2). meanwhile, for the specimens of geopolymer and normal concrete-2 beams, the lower reinforcement used is 3 ø12. in this study, the curing process for geopolymer concrete specimens in the form of cylinders and blocks are carried out by the placement at room temperature (± 25°c) until the day of testing. the curing period for cylindrical and beam specimens for the geopolymer concrete-1 and concrete-2 is 65 days. the curing process for normal concrete is carried out by keeping the concrete wet to enable optimality and water availability for the cement hydration process. furthermore, normal cylindrical concrete is placed in a container filled with water, while normal beam concrete is covered with fabric and watered every day. the duration of treatment for the normal concrete-1 and concrete-2 is 69 and 68 days, respectively. in this study, the mechanical characteristics of geopolymer concrete are obtained using the compressive and split tensile strength tests based on astm c39/c39m-0 (fig. 3) and astm c496/c496m-17 (fig. 4), respectively. furthermore, the bending test based on astm c78/c78m-2 is used to determine the ultimate moment of the concrete beam (fig. 5). the testing results of the mechanical characteristics of polymer and normal concrete are then compared. 298 advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 3. results and discussion the test results of compressive strength (f'c), split tensile strength ����), and ultimate moment (mu) on the geopolymer and normal concrete specimens are shown in table 3. from the data in table 3, the compressive strength (�� �) of these two concrete specimens is almost the same. the average compressive strength of geopolymer concrete reaches 38.2 mpa, which is 13% lower than normal concrete. this value indicates that it can be rationally accepted as an alternative material to normal concrete. the split tensile and compressive strengths of geopolymer concrete are 9.27% and 8.54%, while the split tensile and compressive strengths of normal concrete are 10.87% and 13.77%, respectively (table 3). normal concrete has a bigger ratio than geopolymer concrete, but this is not a problem because the tensile strength is not the primary function of concrete (the reinforcement can provide the tensile strength). a bending test (fig. 6) is carried out to obtain the ultimate moment of the concrete beam (in the middle of the beam), which is calculated as: ( ) 2 2 2 2 3 2 4 u o u o u sw sw p l p ll l l m q q= + × × − × − × × (1) where pu is the force from the bending test (kn), � is the concrete self-weight (kn/m), l is the concrete length (m), and lo is the support-to-support length (m). likewise, for the ultimate moment (�� , those of geopolymer and normal concrete are close to each other. the average ultimate moment of geopolymer concrete reaches 22.90 kn·m in this study, which is relatively slightly better than normal concrete (table 3). this shows that the bonding between the plain rebar and geopolymer concrete is relatively better than normal concrete (fig. 7-8). the condition of the plain rebar which supports the occurrence of this strong bond with geopolymer concrete is the absence of rust. table 3 testing results of the geopolymer and normal concrete concrete type cylinder specimen ø × h (mm) �� � average (mpa) ��� average (mpa) beam specimen l × b × h (mm) �� average (mpa) �� (kn·m) geopolymer concrete-1 100 × 200 36.08 3.34 1600 × 125 × 250 392.85 17.15 geopolymer concrete-2 100 × 200 38.20 3.26 1600 × 125 × 250 392.85 22.90 normal concrete-1 100 × 200 43.93 4.77 1600 × 125 × 250 392.85 17.02 normal concrete-2 100 × 200 35.01 4.82 1600 × 125 × 250 392.85 22.65 fig. 7 bonding of the geopolymer concrete beam to the plain rebar fig. 6 configuration of the bending test on the concrete beam fig. 8 bonding of the normal concrete beam to the plain rebar 299 advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 based on the testing results of mechanical properties, the compressive strength (�� �), split tensile strength (���), and ultimate moment (��) between the geopolymer and normal concrete are almost the same. due to the relatively high calcium content of fly ash in geopolymer concrete (18.24%), the designed strength can be achieved with curing at room temperature as shown in the results from other studies [22-23]. even though the al2o3 content in fly ash is very low (6.58%), the relatively high fe2o3 content (48.51%) enables iron atoms to replace ferro-silicate-aluminate aluminum atoms [6], which allows the strength of geopolymer concrete to reach above 30 mpa with the naoh activator that has relatively low molarity (8 m). the bending test shows that the deflection of geopolymer concrete-1 and 2 are 39 and 22 mm, while the deflection of normal concrete-1 and 2 are 16.6 and 12.4 mm, respectively. this shows that the geopolymer concrete beam and its modulus of elasticity are more flexible and smaller than normal concrete, respectively. all specimens of geopolymer concrete and normal concrete experience flexural cracks and crack patterns that are almost the same (fig. 9-12). the specimens of geopolymer concrete reach the ultimate moment and show dominant flexural cracks. meanwhile, for normal concrete beam specimens, the dominant flexural and shear cracks occur in normal concrete-1 and normal concrete-2, respectively. the flexural crack width shown in geopolymer concrete is larger than in normal concrete. this is due to the lower tensile strength and modulus of elasticity of geopolymer concrete compared to normal concrete. furthermore, the cracks are wider and more evenly distributed in the pure flexural region (between the two loading points) for the geopolymer concrete beams. this phenomenon can be seen in geopolymer concrete-1 beam (fig. 8). thus, geopolymer concrete beams provide greater deformation opportunities before failure. in the casting process, the difference between the geopolymer and normal concrete is the duration of the setting time. geopolymer concrete has a setting time of about 30-60 minutes, while for normal concrete it is between 1-2 hours. the casting and molding of fresh geopolymer concrete are carried out very quickly and require more energy. furthermore, the workability of geopolymer concrete is lower than normal concrete. the viscosity of geopolymer concrete is higher than that of normal concrete, and it is more difficult to compact or pound geopolymer concrete than normal concrete. the compaction process in this study uses a rubber hammer and a vibrator. although the workability of geopolymer concrete is lower, the specimen results have only a few pores which are the same as the case of normal concrete (fig. 13-14). this is due to the compaction being carried out properly, despite its high energy requirements. fig. 9 flexural crack of geopolymer concrete-1 fig. 10 flexural crack of geopolymer concrete-2 fig. 11 flexural crack of normal concrete-1 fig. 12 shear crack of normal concrete-2 300 advances in technology innovation, vol. 7, no. 4, 2022, pp. 295-302 fig. 13 visible pore holes in the geopolymer concrete beam fig. 14 visible pore holes in the normal concrete beam 4. conclusions the mechanical characteristics testing of the laricfa-based geopolymer concrete is carried out for determining the compressive strength, split tensile strength, and ultimate moment. according to the results, the following conclusions can be obtained: (1) the use of laricfa has great practical advantages with its characteristics of low al2o3 (6.58%), high fe2o3 (48.51%), and cao (18.24%) contents. one of the advantages is that the geopolymer concrete with laricfa can reach an average compressive strength of 38.2 mpa only through treatment at room temperature. (2) the ratio between the split tensile and compressive strengths of geopolymer concrete is almost the same as that of normal concrete. (3) furthermore, the average ultimate moment of geopolymer concrete reaches 22.9 kn·m, which is relatively better than that of normal concrete. this indicates better bonding between geopolymer concrete and plain rebar than with normal concrete. (4) geopolymer concrete can be recommended for use as a structural component in simple house construction because it has mechanical characteristics that are almost the same as normal concrete. acknowledgments this study was partly supported by the directorate for research and community service, directorate general of research and development strengthening, ministry of research, technology and higher education of indonesia no. 100.add/ll3/pg/2020, centre for research and community development, and the pelita harapan university through grant p-031-fast/i/2019. conflicts of interest the authors declare no conflicts of interest. references [1] m. d. jackson, et al., “phillipsite and al-tobermorite mineral cements produced through low-temperature water-rock reactions in roman marine concrete,” american mineralogist, vol. 102, no. 7, pp. 1435-1450, july 2017. 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[20] p. chindaprasirt, et al., “effect of calcium-rich compounds on setting time and strength development of alkali-activated fly ash cured at ambient temperature,” case studies in construction materials, vol. 9, article no. e00198, december 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 302 microsoft word 5-v10n1(2025)-aiti#13825(58-71).docx advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 english language proofreader: chih-wen teng recursive feature elimination and optimized hybrid ensemble approach for early heart disease prediction jitendra p chaudhari1, kishan p patel2,*, hiren k mewada3, hardikkumar sudhirbhai jayswal4, yogesh p kosta5, kanchan s bhagat6, shubhangi d kirange7 1charusat space research and technology center; department of electronics and communication engineering; chandubhai s patel institute of technology; charotar university of science and technology, changa, gujarat, india 2department of electrical engineering; chandubhai s patel institute of technology, charotar university of science and technology, changa, gujarat, india 3electrical engineering department, prince mohammad bin fahd university, al khobar, kingdom of saudi arabia 4department of information technology, devang patel institute of advance technology and research, gujarat, india 5provost, uka tarsadia university , gujarat, india 6dept of computer engineering, j. t. mahajan college of engineering, jalgaon, maharashtra, india 7department of information technology, government polytechnic, jalgaon, maharashtra, india received 07 june 2024; received in revised form 17 october 2024; accepted 28 october 2024 doi: https://doi.org/10.46604/aiti.2024.13825 abstract early machine learning prediction improves patient health and prevents heart disease, one of the leading causes of morbidity worldwide. however, challenges such as noise and incomplete data often obscure patterns critical for accurate predictions, and single-classifier models may fail to capture data complexity. this study aims to develop a robust ensemble model leveraging advanced feature selection techniques to enhance prediction accuracy. various machine-learning algorithms are examined. recursive feature elimination is applied to remove irrelevant features, improving model performance. the hybrid ensemble method achieves 93.15% accuracy, 93.15% precision, and 92.97% recall, outperforming principal component analysis and symmetrical uncertainty methods. this research sets a benchmark for future studies by leveraging hyperparameter tuning and advanced feature selection to optimize feature reduction and machine learning models. keywords: ensemble machine learning, heart disease, hyperparameter tuning, recursive feature elimination 1. introduction the who identifies heart disease as the leading cause of death, affecting 17.9 million people annually [1]. hypertension, high cholesterol, overweight, obesity, and hyperglycemia are key risk factors for heart disease. sleep issues, leg swelling, chronic cough, and increased heart rate are also factors, according to the american heart association [2]. the overlap of symptoms with other illnesses makes early diagnosis difficult for doctors. modern healthcare has shifted toward integrating iot and ai devices to adapt to changing medical diagnostics. this trend improves practitioners’ heart disease diagnosis decisions [3]. healthcare professionals prefer iot and ai technologies for more accurate and timely diagnoses. healthcare relies on machine learning (ml) to make accurate predictions from large datasets. it helps simplify geometric analyses of extensive medical records [4-6]. integrating iot and ai technologies enables early heart disease detection, meeting the need for accurate diagnoses in healthcare. this research focuses on optimizing ml through feature extraction and parameter * corresponding author. e-mail address: kishanpatel.ee@charusat.ac.in advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 59 tuning. grid search identifies optimal ml features and hyperparameters to enhance prediction accuracy. an ensemble technique further improves performance by addressing model biases. various supervised ml classifiers are employed for predicting cardiac disease, utilizing datasets from university hospital zurich [7], va medical centre (long beach, california), hungarian institute of cardiology (budapest), and cleveland clinical foundation. the data from the uci machine repository undergoes pre-processing, including removing missing values and standard scaling. recursive feature elimination (rfe) is applied to select the six most crucial features, and diverse mls are trained for classification. the study progresses through three stages: traditional heart disease prediction, feature elimination using rfe, and hyperparameter tuning via grid search. key contributions include: (1) developing an ensemble model using popular ml algorithms. (2) using rfe to identify the six most relevant features, improves the model’s performance. (3) optimizing hyperparameters to balance model complexity and avoid overfitting. (4) evaluating model performance based on recall, precision, accuracy, and f-measure. 2. related work ml for heart disease prediction has been extensively researched to identify early indicators. this effort is crucial as many heart disease risk factors overlap with diabetes, highlighting the importance of early and accurate detection in saving lives. shah et al. [8] tested ml algorithms like random forest (rf), k-nearest neighbors (knn), decision tree (dt), and naïve bayes (nb). their study used 303 instances and 76 attributes from the uci machine repository, but only 14 were used for their models. their knn achieved 90% training accuracy, but testing accuracy was only 78.95%, suggesting overfitting. the heart disease prediction system combines all classification methods into one algorithm [9]. the results indicate that the combined model outperforms individual methods. the lack of detailed performance analysis makes it difficult to assess the actual effectiveness of this hybrid approach. ramotra and mansotra [10] presented an integrated system utilizing a graph-based technique and weighted association rule mining applied to the andhra pradesh population. unfortunately, the study does not specify prediction accuracy levels. singh and shrivastava [11] conducted a comprehensive analysis of different heart disease prediction techniques, emphasizing the efficiency of ml in prediction analysis. the absence of comparisons using appropriate datasets limits the generalizability of their findings. ali et al. [12] used kaggle datasets to test various ml algorithms, with multi-layer perceptron (mlp) and knn achieving the highest accuracy of 91% and 100%. nonetheless, further analysis is required to justify the success of knn over mlp. salhi et al. [13] focused on data analysis of heart disease, employing correlation matrix-based feature selection and achieving 93% accuracy with neural networks (nn). the authors did not emphasize the importance of features in their approach. the multi-layer pi-sigma neuron model (mlpsnm) [14] used principal component analysis (pca), linear discriminant analysis (lda), and normalization for feature reduction and a standard backpropagation (bp) algorithm for classification. pca is versatile but cannot capture meaningful attributes in non-linear complex data. muhammad et al. [15] optimized feature spaces using algorithms like fast correlation-based filter solution (fcbf), minimal redundancy maximal relevance (mrmr), relief, and least absolute shrinkage and selection operator (lasso), achieving an accuracy of 94.41%. however, further exploration of the selection of optimization techniques and a comparative analysis is required. singh and kumar [16] identified knn as the best predictor among support vector machine (svm), knn, linear regression, and dt with 87% accuracy. a summary of diverse qualities among ml algorithms for cardiovascular disease prediction is presented in krittanawong et al. [17], highlighting the promising abilities of svm and boosting algorithms. the authors commented that an appropriate approach to selecting an ml model is required to interpret the study in the context of clinical practices. advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 60 yadav et al. [18] used logistic regression (lr), knn, and nb, finding that fuzzy knn produced better results. akella and akella [19] employed six ml algorithms, achieving an accuracy of 93% using an artificial neuron network (ann) for coronary artery disease detection. they employed 14 features without empirical study on feature selections. garcía-ordás et al. [20] explored heart disease prediction using deep learning algorithms, and accuracy is limited to 78.3% with nnn after hyperparameter tuning and feature selection. the authors performed arrhythmia classification with heart rate variability (hrv) in yaghouby et al. [21] using a small subset of the mit-bih dataset. they minimized the features using discriminant analysis techniques, and mlp was used to classify the four classes. further validation on a large dataset is required. asl et al. [22] found that feature selection reduced features to 5, with svm achieving the highest arrhythmia classification accuracy. by focusing on critical elements, feature selection enhances accuracy. this study introduces a new feature selection method and ml optimization to improve classification. nagavelli et al. [23] used weighted nb, svm, and extreme gradient boosting (xgboost) with synthetic minority oversampling technique-edited nearest neighbor (smote-enn) for ischemic heart disease localization and an improved svm for heart failure detection. they observed xgboost as the most effective algorithm. the study concludes by suggesting feature enhancements, including dataset updates and integration with hospital databases. cardiovascular disease causes 32% of global deaths, according to biswas et al. [24]. they aimed for early-stage identification using ml. chi-square, anova, and mutual information (sf1, sf2, and sf3) are used to evaluate six ml models. rf is the most promising, with 94.51% accuracy, 94.87% sensitivity, 94.23% specificity, and 0.31 log loss for sf3 feature subsets. the model’s performance and selected features suggest it could be used clinically to predict early heart disease at a low cost and in a short time. however, the heart disease dataset was insufficient for developing a more accurate predictive model. ahmad and polat [25] emphasized early detection’s importance in fighting heart disease. their research developed an ml model using cleveland heart disease data. the jellyfish optimization algorithm reduced the dataset’s dimensionality, minimizing overfitting. the svm classifier with the jellyfish algorithm achieved top performance, with 98.56% sensitivity, 98.37% specificity, 98.47% accuracy, and 94.48% area under the curve. however, they must be implemented into clinical practice to improve patient diagnosis. the research addresses the pressing issue of heart disease, which affects ten billion people annually, as carried out by saikumar et al. [26]. iot sensor data and deep learning created an intelligent heart diagnosis app. the dg convonet model, trained on uc irvine data and tested with cleveland clinical foundation real-time instances, has 96% accuracy. the study used k-means for noise reduction and linear quadratic discriminant analysis for feature extraction achieving 80% sensitivity, 73% specificity, 90% precision, 79% f1-score, and a 75% receiver operating characteristic (roc) curve area. however, features were chosen randomly, and the paper does not evaluate their impact. table 1 compares these articles, listing strengths and weaknesses. table 1 overview of studied articles ref. models remarks shah et al. [8] nb, dt, knn, and rf were tested on the uci machine repository. (1) hyperparameters and features are not optimized. (2) low testing set accuracy, i.e., 78.95%. tarawneh and embarak [9] a hybrid approach of nb, knn, genetic algorithm (ga), svm, and nn was used for classification. (1) nb and svm outperform others, so hybridizing other models is inappropriate. (2) max accuracy is 89.2%. ramotra and mansotra [10] k-means clustering, pca, and lr to recognize heart disease. (1) they separated the datasets into healthy and abnormal using clustering. (2) pca-based feature reduction regardless of significance. ali et al. [12] mlp, knn, rf, dt, lr, and adaboostm1 (ab m1) were applied to kaggle datasets. 10fold cross-validation was used in training. the most predictive features were ranked by importance scores. mlp and knn failed to generate scores, and without feature ranking, they obtained 91% and 100% accuracy, respectively. advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 61 table 1 overview of studied articles (continued) ref. models remarks salhi et al. [13] three ml algorithms, knn, svm, and nn, are used on datasets of different sizes (i.e., 600, 800, 1,000, and 1,200). a structured dataset of algerian hospitals is used. (1) for 1,200 data records, the maximum accuracy for nn was 93%, svm was 90%, and knn was 85.5%. (2) no evaluation was presented for training and testing sets. (3) precision and f1-scores are not analyzed. burse et al. [14] mlpsnm is proposed for the uci ml repository with 10-fold cross-validation. a three-layer network is used and, hence, less complex. muhammad et al. [15] knn, rf, dt, lr, and ann were presented. the four distant feature techniques, lasso, fcbf, relief, and mrmr, were tested. (1) the success rate is 85% for ann and 85.55% for knn. (2) relief features were found to be better in comparison to other techniques. jabbar et al. [27] weighted association rule mining and a graphbased methodology were used. a subjective rule-based association using age, gender, and bp. prediction accuracy is not presented. proposed approach an ensemble approach of eight ml is validated using a heart disease prediction dataset from the uci machine repository. rfe employs a feature reduction technique. the model succeeded with 93.15% accuracy, with six features out of 14. this study identified several limitations. first, the models were trained on small, specific datasets, limiting their broader applicability across diverse populations. second, while effective, the hybrid ensemble approach is complex and resourceintensive, making it unsuitable for real-time or resource-limited settings. third, the model’s performance heavily relies on feature selection, which may not always identify the most relevant features. lastly, the high accuracy raises concerns about overfitting due to the small dataset and extensive tuning. future work should focus on larger datasets, simplifying models, and improving feature selection methods. 3. dataset description medical data collection is challenging due to privacy and security concerns. common heart disease prediction benchmarks include publicly available datasets like the uci repository. this study uses the uci heart disease dataset [7], which has 304 records and 14 features and was reduced to 297 records after removing missing values. the dataset aims to classify heart disease as positive or negative, posing a binary classification challenge. the following sections focus on developing and optimizing ml models for accurate heart disease prediction. table 2 describes the 14 attributes. 3.1. data pre-processing accurate data pre-processing is essential, as unprocessed data can weaken ml models. in this study, missing records were removed, and features were standardized for comparability and improved performance. a detailed dataset analysis is conducted, with the features described in table 2. standardization eliminates the mean and scaled-to-unit variance and aligns features with a standard normal distribution, enhancing the performance of many ml algorithms. this refined dataset will be used to develop and optimize heart disease prediction models. table 2 feature description # feature feature description non-null count data type 0 age age of the patient. 304 int64 1 sex gender of the patient. 304 int64 2 cp categorizes chest pain into four types: 1 for typical angina, 2 for atypical angina, 3 for non-anginal pain, and 4 for asymptomatic. 304 int64 3 trestbps denotes blood pressure at rest (mm hg) at hospital admission. 304 int64 advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 62 table 2 feature description (continued) # feature feature description non-null count data type 4 chol defines the serum cholesterol level in mg/dl. 304 int64 5 fbs indicates fasting blood sugar level, with 1 for true and 0 for false (if greater than 120 mg/dl). 304 int64 6 restecg describes restecg, with 0 for normal, 1 for abnormal st-t wave, and 2 for left ventricular hypertrophy meeting estes criteria. 304 int64 7 thalach represents the highest heart rate possible in beats per minute (bpm). 304 int64 8 exang indicates exercise-induced angina (exang), with 1 for present and 0 for absent. 304 int64 9 oldpeak explains the st depression brought on by exercise in comparison to rest 304 float64 10 slope emphasizes the steepest portion of the exercise st segment, with 1 for upslope, 2 for flat, and 3 for downslope. 304 int64 11 ca describes the count of major vessels (0–3) in fluorescence. 304 int64 12 thal represents the thalassemia category, with 3 for normal, 6 for a fixed defect, and 7 for a reversible defect. 304 int64 13 target classification, i.e., 0 for no presence of heart disease and 1 for presence. 304 int64 3.2. exploratory data analysis fig. 1 age distribution of patients fig. 2 sex vs number of records fig. 3 exploratory data analysis of chest pain type advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 63 to better understand the dataset, exploratory data analysis is conducted, categorizing features into quantitative and categorical groups. quantitative features take numerical values, representing various measurements. in the heart disease dataset, features such as age, cholesterol, thalach, and st depression induced by exercise (oldpeak) were identified as quantitative. categorical features are label values that categorize individuals into groups. examples from the dataset used here include thalassemia (thal), gender, fbs, cp, exang, slope, ca, and restecg. these categorical features serve as target characteristics for analysis. during feature analysis, key features for heart disease prediction were identified. fig. 1 shows the age distribution of heart disease patients and healthy individuals. fig. 2 depicts gender distribution, while fig. 3 shows chest pain type distribution. correlation matrices and heatmaps offer insights into variable relationships. fig. 4 highlights the correlation between attributes in the heart disease dataset. fig. 4 correlation between different attributes 4. methodology this study uses hyperparameter tuning and feature selection to create a supervised ml algorithm for heart disease detection. to ensure reliable evaluation, 70% of the dataset was used for training and 30% for testing and assessment. before model development, the following preprocessing steps were applied to the dataset using a standard scaler to ensure consistency in feature scales. the experiments are carried out on a pc with an 11th-generation intel(r) core(tm) i5-1135g7 @ 2.40 ghz and 16 gb ram. (1) model development and training: a diverse set of ml algorithms was applied to the training dataset. hyperparameter tuning was performed to optimize model architecture and improve predictive performance. an ensemble approach combined multiple models to enhance the system’s accuracy in predicting heart disease. (2) hybrid ensemble classification: a hybrid ensemble classification approach integrated eight ml algorithms, leveraging their unique strengths to create a more robust heart disease prediction model. (3) hyperparameter tuning: hyperparameters were fine-tuned using techniques like grid search to optimize model performance for heart disease prediction. (4) classification and evaluation: the final models were evaluated on the test dataset, assessing their generalization ability to new data. performance metrics such as precision, recall, accuracy, and f-measure were used for performance evaluation. (5) heart disease identification strategy: the strategy, visualized in fig. 5, involves data preprocessing, training multiple ml models with hyperparameter tuning, and evaluating their performance on a test dataset. it combines traditional algorithms with the hybrid ensemble model for reliable heart disease prediction. advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 64 fig. 5 methodology for heart disease prediction system 4.1. feature selection using recursive feature elimination (rfe) the ml’s ability to identify influential parameters is vital. feature selection enhances algorithm performance, reducing execution time, improving accuracy, and mitigating overfitting. this study used rfe to select features from the heart disease dataset. rfe iteratively removes attributes while evaluating accuracy to determine the most essential features for prediction. it also uses cross-validation to identify the optimal number of features. table 3 lists the six most relevant features selected by rfe for heart disease prediction. streamlining the feature set improves model efficiency and interpretability while maintaining or enhancing accuracy. the following sections discuss how these features impact model performance and prediction accuracy. table 3 features selection using rfe feature feature ranking using rfe support age 7 false sex 1 true cp 1 true trestbps 6 false chol 8 false fbs 4 false restecg 3 false thalch 5 false exang 1 true oldpeak 2 false slope 1 true ca 1 true thal 1 true 4.2. ml algorithms as listed below, this research adopted eight ml models for analysis and finally proposed an ensemble model. (1) lr is a supervised classifier where a regression model can be used as a classifier using a decision threshold. it employs the sigmoid function to model the data, and the appropriate threshold selection can lead to high precision and recall. the advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 65 sigmoid function is a monotonic continuous function that ranges between 0 and 1. mathematically, this classification can be expressed as ( ) 1 ( ) 1 exp (1, ) β = + − q q p y x (1) where ����� gives the probability of �� to be 1, �� is the input vector to be classified, and � is the vector parameter. now, the classification problem is equivalent to finding vector parameters. (2) knn is one of the simplest algorithms that stores all the classes and classifies the new ones based on the nearest neighbors calculating distance function. it assumes that similar entities reside close to one another in identical classes. the letter “k” represents the closest neighbors used to categorize an instance. in this algorithm, two quantities are necessary, i.e., the distance between two entities and the neighbors’ quantity (k). typically, the euclidean distance given in the following equation is used. ( ) 2 0 ( , ) = = − n k k x d x y x y (2) as shown in fig. 6, knn calculates an entity’s distance from neighboring points and classifies it based on the nearest neighbors. clean, normalized data is essential for knn to prevent bias from outliers and high-value entities. during training, knn stores the data, and in testing, it compares the test instance to the stored data, identifying the nearest neighbors to predict the majority label. the choice of ‘k’ and the distance metric significantly impacts the performance of the knn method. fig. 6 classifier example with k = 4 and 7 neighbors (3) dt is a tree-structured supervised learning model for classification and regression tasks. internal nodes represent the dataset’s features, branches represent decision paths, and leaf nodes provide the outcomes. decision nodes have multiple branches (as shown in fig. 7), while leaf nodes indicate the final decisions without further branching. each decision or test is based on the characteristics of the dataset. fig. 7 decision tree structure advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 66 (4) rf builds multiple numbers of the individual dt in the training stage. each tree predicts the results, and the class with the most predictable results is considered the model output. fig. 8 shows the structure of rf using trees. fig. 8 random forest using multiple trees fig. 9 hyperplane-based classification in svm fig. 10 mlp layer representation (5) the svm classifier employs a hyperplane for data classification. it looks for the best hyperplane in the area with the most significant distance from the data points. fig. 9 illustrates the model’s attempt to fit the hyperplane with the most significant possible margin. the classification accuracy may be impacted by data points located closer to the plane. (6) nb is a probabilistic approach based on bayes’ theorem, assuming all features are independent. it combines prior knowledge about classes with new evidence using training data. first, it calculates a probability table for each data point and then determines the posterior probability for each class. the predicted class is the one with the highest posterior probability. in this study, an ensemble approach incorporates both the traditional gaussian nb method and its optimized variant. (7) xgboost uses an ensemble of k classification and regression trees, enhancing learning by combining the judgments of weak classifiers. it reduces the computational cost and time of gradient boosting, making it a powerful tool for achieving state-of-the-art results in various fields. (8) unlike xgboost, mlp is a feed-forward nn with input, hidden, and output layers. neurons are trained using bp, allowing mlps to solve non-linearly separable problems by modeling continuous functions. this study randomized input vectors during training to achieve global learning. fig. 10 illustrates the mlp layer structure. advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 67 4.3. optimization of hyperparameter using a grid search cross-validation and grid search were used to optimize classification parameters during hyperparameter tuning. grid search systematically divides the hyperparameter domain into a grid, generating models for each parameter combination and using cross-validation to evaluate performance. this method thoroughly explores a selected portion of the algorithm’s hyperparameter space, providing consistent parameter values for dataset analysis. grid search systematically generates each candidate’s parameter setting based on the parameters to be optimized. for instance, setting a sigma range in svm to 5 will only allow five possible values. therefore, the grid search approach provides 5 × 5 = 25 permutations of parameter settings for a random classifier with two parameters and a sigma with five possible values. then, it evaluates the parameter setting of each candidate. find the optimal parameters among all. a grid search with 10-fold cross-validation was conducted to find optimal hyperparameters for the heart disease dataset. the best hyperparameters obtained are shown in table 4. models were generated using feature selection and hyperparameter tuning before evaluating performance on the test set. table 4 hyperparameters tunning and its optimum value classifier initial hyperparameters optimum value of hyperparameters lr ‘c’: [1, 5, 10, 15, 20, 25] ‘c’ = 1 dt ‘criterion’: [‘gini’, ‘entropy’] ‘criterion’ = ‘gini’ svm ‘c’: [0.01, 0.1, 0.25, 0.5, 0.75, 1, 10, 100] ‘gamma’: [1, 0.75, 0.5, 0.25, 0.1, 0.01, 0.001] ‘kernel’: [‘rbf”, ‘poly’, ‘linear’] ‘c’ = 0.1 ‘gamma’ = 1 ‘kernel’ = ‘linear’ knn ‘n_neighbors’: list(range(1, 56)) ‘leaf_size’: list(range(1, 50)) ‘n_neighbors’ = 12 ‘leaf_size’ = 1 nb smoothing: default 1e-9 smoothing = 1e-9 rf ‘n_estimators’: [1, 5, 10, 15, 20, 25, 30], ‘max_depth’: [3, 4, 5], ‘max_leaf_nodes’: [10, 15, 20], ‘min_samples_leaf’: [10, 15, 20, 25] ‘n_estimators’: [25] ‘max_depth’: [4] ‘max_leaf_nodes’: [20] ‘min_samples_leaf’: [20] xgboost ‘learning_rate’: [0.05, 0.10, 0.15, 0.20] ‘max_depth’: [3, 4, 5] ‘gamma’: [0.0, 0.1, 0.2, 0.3] ‘learning_rate’: [0.10] ‘max_depth’: [5] ‘gamma’: [ 0.3] mlp ‘c’: [0.01, 0.1, 0.25, 0.5, 0.75, 1, 10, 100] ‘gamma’: [1, 0.75, 0.5, 0.25, 0.1, 0.01, 0.001] ‘kernel’: [‘rbf’, ‘poly’, ‘linear’] ‘c’ = [0.1] ‘gamma’: [0.1] ‘kernel’: [‘linear’] 4.4. experimental evaluation and performance analysis the performance of the suggested system was assessed using 30% of the data for testing and 70% for training. the recall, precision, accuracy, and f1-score of the performance are evaluated using the confusion matrix. accuracy defines the ratio of correctly identified labels to the total number of records. precision is computed by taking the ratio of correctly identified heart disease labels to the total predicted heart disease labels. the recall is computed by the ratio of truly identified heart disease labels to all labels in the dataset with heart disease. the f1-score defines the weighted average of precision and recall. accuracy, precision, recall, and f-measure are defined mathematically as follows: tp tn accuracy tp tn fp fn + = + + + (3) tp precision tp fp = + (4) tp recall tp fn = + (5) precision recall f1-score 2 precision recall × = × + (6) advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 68 true positive (tp) represents the number of instances correctly predicted as positive (heart disease). false positive (fp) refers to the number of instances incorrectly predicted as positive (heart disease) when they were negative. true negative (tn) is the number of instances correctly predicted as negative (no heart disease), and false negative (fn) refers to the number of instances incorrectly predicted as negative (no heart disease) when they were positive. table 5 precision score ml algorithms precision ht without feature selection ht with feature selection normal without feature selection normal with feature selection lr 0.792731 0.821367 0.792731 0.821367 dt 0.803762 0.793696 0.803762 0.793696 svm 0.871708 0.902577 0.851565 0.891429 knn 0.883295 0.903718 0.862873 0.89472 nb 0.865055 0.885839 0.865055 0.885839 rf 0.804549 0.872304 0.83811 0.861491 xgboost 0.821914 0.813455 0.802085 0.842376 mlp 0.836731 0.862032 0.872178 0.921562 hybrid ensemble 0.891429 0.93414 0.862973 0.911993 table 6 recall score ml algorithms recall ht without feature selection ht with feature selection normal without feature selection normal with feature selection lr 0.792079 0.821782 0.792079 0.821782 dt 0.78297 0.792871 0.782987 0.792871 svm 0.872178 0.901881 0.852376 0.89198 knn 0.88198 0.901782 0.862178 0.891881 nb 0.862178 0.88198 0.862178 0.88198 rf 0.802772 0.872079 0.832475 0.862178 xgboost 0.812673 0.812673 0.792871 0.842376 mlp 0.832574 0.862277 0.872178 0.921683 hybrid ensemble 0.89198 0.931584 0.862277 0.911782 table 7 f1-score ml algorithms f1-score ht without feature selection ht with feature selection normal without feature selection normal with feature selection lr 0.79237 0.821246 0.792327 0.821246 dt 0.78332 0.793214 0.78332 0.793214 svm 0.870684 0.900167 0.850746 0.891385 knn 0.879686 0.89717 0.859655 0.889194 nb 0.858429 0.878572 0.858429 0.878572 rf 0.803377 0.870185 0.833452 0.861523 xgboost 0.813778 0.812992 0.794058 0.842376 mlp 0.83349 0.860202 0.872178 0.920871 hybrid ensemble 0.891385 0.929749 0.862549 0.91056 table 8 accuracy analysis of various ml algorithms accuracy ht without feature selection ht with feature selection normal without feature selection normal with feature selection lr 0.792079 0.821782 0.792079 0.821782 dt 0.78297 0.792871 0.78297 0.792871 svm 0.872178 0.901881 0.852376 0.89198 knn 0.88198 0.901782 0.862178 0.891881 nb 0.862178 0.88198 0.862178 0.88198 rf 0.802772 0.872079 0.832475 0.862178 xgboost 0.812673 0.812673 0.792871 0.842376 mlp 0.822574 0.852277 0.862178 0.911683 hybrid ensemble 0.89198 0.931584 0.862277 0.911782 advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 69 the literature review [8-9, 13, 15] indicates that various ml models, including knn, svm, dt, nb, adaboost, and gradient boost, have been tested. these algorithms use different feature elimination and selection methods. in salhi et al. [13], the authors ranked features using the pearson correlation method. however, out of 14, they eliminated only one feature in the experiment. the major weakness of the pearson correlation is that it considers all features independent and, therefore, fails to eliminate redundant features. muhammad et al. [15] used a fast correlation filter (fcf) to choose the top features from the list of 14. fcf calculates symmetrical uncertainty to find the high correlation, and six features were selected based on the ranking results. among all ml models, rf succeeded with 88.48% accuracy. however, their recall rate is limited to 85.57%. alfadli and almagrabi [28] used chi-squared distance for feature ranking and selected seven highly ranked features. they trained multiple ml models using different hyperparameter configurations. their accuracy is limited to 83.15%. sarra et al. [29] tested different ml models. they also used chi-squared distance to find the important features from the 14 features. their study showed that svm was the most accurate among knn and ann, with 89.47% accuracy using six feature sets. thus, chisquare (x2-distance) performed well in ranking the features, but its weakness is that it works well for small-size feature sets. reduced processing load and improved system performance were achieved by removing superfluous and redundant characteristics and selecting the essential ones [30]. further improving system performance, a unique feature weight for each class was computed using the conditional probability technique. the prediction of heart disease was also trained into a deep-learning ensemble model. the authors reduced the feature sets to 14 out of 23 and received 83.5% accuracy. therefore, the rfe method is used in the proposed model. six relevant features were obtained and used to train various ml models. to improve the performance, the hyperparameters of all models are optimized using the greedy search algorithm. another can handle the weakness of one model, and therefore, their ensemble approach succeeded in performing better than other models. table 9 shows the comparative studies of different models and proposed methods. table 9 comparison of models utilizing feature reduction method and ml models ref. year model feature selection method reduced features number accuracy precision recall tarawneh and embarak [9] 2019 svm, knn, ann, nb, dt symmetrical uncertainty and one r selection 12 83.75 81.15 82.35 burse et al. [14] 2019 mlpsn 14 90.44 svm pca 4 88.32 shah et al. [8] 2020 knn, nb, dt 14 90.78 muhammad et al. [15] 2020 dt, knn, etc, ann, lr, rf, nb, svm, gb, ab correlation-based filter 6 88.48 90.87 85.57 ali et al. [30] 2020 ensemble deep learning information gain 14 83.5 84.5 82.5 salhi et al. [13] 2021 knn, svm, ann pearson correlation method 13 93 92 94 sarra et al. [29] 2022 svm x2 feature selection 6 89.47 89.40 89.40 alfadli and almagrabi [28] 2023 ensemble approach x2 feature selection 7 83.15 83.97 86.00 proposed 2024 ensemble approach recursive elimination 6 93.15 93.15 92.97 5. conclusions and future work this study significantly advances heart disease prediction by implementing a robust hybrid ensemble method. the implementation of hyperparameter tuning and feature selection significantly enhanced prediction accuracy. several ml techniques were evaluated, including nb, xgboost, knn, rf, dt, lr, svm, and mlp. despite reducing features to six using rfe, the hybrid model achieved strong results: 93.15% accuracy, 93.15% precision, and 92.97% recall. dt using rfe advances in technology innovation, vol. 10, no. 1, 2025, pp. 58-71 70 had a minimum accuracy of 79.15%, with the ensemble approach offering a 17.52% improvement. this success stems from hyperparameter tuning and feature selection optimizing model performance, demonstrating that focusing on key features enhances early heart disease detection and management. future efforts will explore alternative optimization methods for feature selection and hyperparameter tuning. integrating cnns, rnns, wearable device data, iot for real-time predictions, ga, and more diverse populations will improve accuracy. a user-friendly app for heart health monitoring and real-time risk assessment is also planned. these extensions enhance the model’s practicality and impact on cardiovascular health management. conflicts of interest the authors declare no conflict of interest. statement of ethical approval (a) statement of human rights for this type of study, statement of human rights is not required. 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[30] f. ali, s. el-sappagh, s. r. islam, d. kwak, a. ali, m. imran, et al., “a smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion,” information fusion, vol. 63, pp. 208-222, 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 4-v8n4(2023)-aiti#12030(278-289).docx advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 english language proofreader: chih-wei chang humidity control for air circulation in the drying process aphisik pakdeekaew1, krawee treeamnuk1,*, tawarat treeamnuk2 1school of mechanical engineering, suranaree university of technology, nakhon ratchasima, thailand 2school of agricultural engineering, suranaree university of technology, nakhon ratchasima, thailand received 20 april 2023; received in revised form 19 july 2023; accepted 20 july 2023 doi: https://doi.org/10.46604/aiti.2023.12030 abstract recycling exhaust air is acknowledged as a method to reduce the energy consumption of agricultural products in the dryer. this study investigates the performance of an air circulation system at a laboratory scale and develops a feedback control compensator for optimizing the drying air circulation process. a servo motor is employed to drive a valve, to feed the exhaust drying air with high temperature and humidity back in different proportions. the system is controlled using an arduino due microcontroller, which communicates data with matlab/simulink. the system identification methodology is employed to analyze the mathematical model of the system. the result indicates that the response of the system meets the acceptance criteria when the percent overshoot is less than 25%, and the settling time is within 60 seconds (with a 2% error tolerance). evaluation of control system performance during equilibrium employs r2 and rmse values. keywords: air humidity ratio, drying, humidity control, system identification 1. introduction agricultural products, especially cereal grains like rice, wheat, corn, and beans, are crucial for survival because of their high nutritional content and ability to be processed into a wide range of cuisines [1-2]. drying is one of the important postharvest steps that is used to reduce the moisture content of the postharvest to an appropriate level. this practice helps to avoid the issue of excessive humidity in the product, which leads to the growth of microorganisms and degradation in the quality of the food during storage [3-4]. in general, to dehumidify agricultural materials and food, solar drying is preferred, which uses less energy costs to reduce moisture because it uses natural heat as an energy source to expel moisture from agricultural materials. however, inclement weather limits this method, and it is vulnerable to animals and insects. furthermore, it needs a certain amount of manpower and instruments to handle, which raises the production cost. due to the limits of traditional solar drying techniques, mechanical dryers that can operate in all seasons and control the quality of crops are increasingly popular in the grains production industry [5]. mechanical dryers are developed from different techniques depending on the purpose of drying and the value of the product [6-7]. when talking about drying paddy, it is the main export product of thailand’s hot air dryers. as for thailand hot dryers, owing to their simplicity and suitability for practical operations, they are mostly used as a medium in the mechanical dryer to remove moisture from materials. from the review of past research, it was found that the louisiana state university (lsu) dryers were popular in the paddy industry with energy consumption in the range of 3.874-6.25 mj/kg water [8-9], while * corresponding author. e-mail address: krawee@sut.ac.th advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 279 crossflow dryers had energy consumption in the range of 1.94-3.89 mj/kg water [10-11], and rotary dryers have energy consumption in the range of 2.64-9.2 mj/kg water [12-13]. these dryers require a high amount of energy to drive the system, which is the energy cost that affects production costs the most. according to thailand’s 20-year energy conservation plan (2011-2030), the importance of reducing greenhouse gas emissions has been considered, which is the crucial factor that causes the national energy system to transform into a carbon reduction system [14]. as a result, the use of electricity to produce hot air for drying is an advantage compared to using combustion as a heat source. an important method that can reduce energy consumption in the drying process with a hot air dryer is to recirculate the air that has taken moisture from those agricultural materials to be used in the dryer again. recently, amantéa et al. [15] applied reheated air circulation to grain drying. it was found that air recirculation can increase moisture extraction rate, exergy, and energy efficiencies by 25% or more. sila et al. [16] reported that higher air circulation ratios resulted in lower energy consumption in the air preheating system. these studies have yielded results in the same direction as darvishi et al. [17], who studied the effect of air circulation on energy consumption during fluidized bed drying of sliced mushrooms under various drying conditions. they found that recycling the exhaust air greatly reduced energy consumption. although exhaust air recirculation is an interesting approach to improving the hot air-drying process and has great potential to reduce energy consumption, grains are naturally biomaterial and susceptible to rapid changes in temperature and humidity in the air, especially in dryers. it directly affects the quality of the product [18-19]. therefore, exhaust air recirculation is necessary to precisely control the air mixing to achieve the desired proportion of air humidity ratio before entering the drying process. the previous research conducted by pakdeekaew et al. [20] highlighted limitations in the operation of the solenoid valve utilized in the air humidity control system. these limitations pertain to the long-term performance of the equipment and its limited capacity to recycle air, not exceeding 15.18% of the total air volume used in the drying system. overcoming these challenges presents a significant obstacle in implementing this system effectively within a commercial dryer. the objective of this study was to design an air humidity control system for grain drying systems, while addressing the limitations identified in previous research. the main focus was on developing a controller that could effectively regulate the humidity ratio of mixed air, comprising recirculating air and ambient air. to achieve this, a butterfly valve was employed to precisely adjust the flow of recycled drying air. the expected outcome of implementing this control system in a commercial hot air dryer is to enhance energy efficiency and ensure better product quality control after the drying process, thus offering promising prospects for the future. 2. materials and methods a drying demonstration set was developed to investigate the design of the humidity control system. the main components comprise a heater and a nozzle spray unit to simulate the transfer of moisture from the drying material to the air in the drying system. 2.1. the drying system on a laboratory scale the drying demonstration set was used to imitate the circumstances of heat and mass transfer instead of a real drying system. the transfer of moisture from material to air was studied, and the control system of air humidity ratio at point 3 (fig. 1, mixed air) was developed. the ambient air entering the system (fig. 1, point 1: ambient air) and humid air after receiving the moisture from the spray chamber are to be mixed in different proportions (fig. 1, point 2: recirculating air). the components of the drying demonstration set are shown in fig. 1. in fig. 1, the air was circulated by a 24v 5.5a dc electric blower in this test. ambient air entered the system at point 1 and flowed through point 3 to the venturi flow meter. at this advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 280 point, the air velocity was maintained at 6 m/s (the volumetric flow rate is 0.01478 m3/s) throughout the test with a regulated dc power supply (atten model apr3010h). before entering the water spray chamber, the air was heated by the heater that collaborates with a proportional-integral-derivative (pid) temperature controller (rkg model rex -c100fk02) to maintain a consistent air temperature of 70 °c. in the water spray chamber, the spray nozzles simulate the humidification of the air, similar to the process in a drying room where the moisture from the material is transferred to the air. the pressure for the spraying system was provided by a high-pressure pump (seaflo model sfdp1-013-100-22, 12 v 5 a, pressure 100 psi) to spray water in the chamber. a heat and mass transfer process happeneds when hot air collidedes with water mist. as a result, the relative humidity of air rose while the air temperature fell [21]. the humidity ratio of air after the mixing process at point 3 was assessed by the dry bulb temperature and relative humidity of the air. the dht22 sensor (am2302 modules, accuracy: humidity ±2% rh (max ±5% rh); temperature < ±0.5 °c; operating range: humidity 0-100% rh; temperature -40-80 °c) was utilized to measure it. fig. 1 schematic diagram of the drying demonstration set this research used an arduino due as a microcontroller to control the operation of the air circulation system, with a servo motor driving the butterfly valve to adjust the return air ratio as shown in fig. 2. the percentage of valve opening from 0-100% was defined as the input signal to the system, and its response was the humidity ratio of the air obtained from the mix of recirculating air and ambient air. fig. 2 an adjustable airflow valve 2.2. the humidity ratio calculation this research was focused on controlling the humidity ratio as the response variable (output signal). calculation of the humidity ratio starts with the dht22 sensor sensing the dry-bulb temperature of the air in degrees celsius (°c) and converting to kelvin (k) before computing the saturation vapor pressure of air by: 3 1 2 3 4 6db db db dbc t c c t c t c lnt svp e + + + + = (1) advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 281 while the relative humidity of air was used for calculating the vapor pressure 100 × = sv v rh p p (2) after that, the vapor pressure of air was utilized to calculate the air humidity ratio [22]. 0.621945 101325 v v p p ω = × − (3) where psv is the saturation vapor pressure of air (pa), pv is the vapor pressure of air (pa), tdb is the dry-bulb temperature of the air (k), rh is the relative humidity of air (%), c1 is -5.8002206e+03, c2 is 1.3914993e+00, c3 is -4.8640239e-02, c4 is 4.1764768e-05, c5 is -1.4452093e-08, c6 is 6.5459673e+00, and ω is the humidity ratio of air. 2.3. mathematical model of the humidity control system from drying air recirculation the operation of the humidity control system, which utilized circulating drying air, is shown in fig. 3. before entering the air mixing point, the drying air flow rate was proportioned by a butterfly valve driven by a dc servo motor. the recirculated drying air was mixed with the ambient air entering the dryer according to the adiabatic mixing of two air streams process at the mixing point. the percentage of valve opening was defined as the input signal. the air humidity ratio after the mixing process was defined as the output signal. fig. 4 shows the overall operation block diagram of the system, consisting of 3 main parts as follows: (1) motor position control system (gposition), (2) transfer function between recirculating drying air flow rate and valve angular distance (gvalve), and (3) transfer function of air mixing point (gmixing point). each section was combined into a system transfer function model (gtotal) used for system identification in section 2.4. fig. 3 functional diagram of the air recirculation proportional control valve fig. 4 block diagram of a humidity control system from recirculating drying air aloo et al. [23] reported that the operation of dc motors can be controlled by adjusting the voltage applied to the armature circuit, also known as armature control. newton’s law and kirchhoff’s voltage law were used to analyze this electromechanical system. the transfer function of the motor is shown as: ( ) ( ) ( ) ( )( ) ω = = + + + m t motor a a a v t b s k g s v s l s r js f k k (4) advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 282 electrical time constants are neglected consideration since they are very small compared to mechanical time constants. therefore, eq. 4 can be reduced [24]. ( ) ( ) ( ) ( ) ω = = + + m t motor a a v t b s k g s v s r js f k k (5) the analysis of the angular position of the servo motor can be derived by multiplying the rotational angular velocity with the integrator, as illustrated in fig. 5. fig. 5 dc motor position control block diagram consequently, the transfer function of the servo motor position control system can be expressed as, ( ) ( ) ( ) 2 θ θ τ = = + + o t position i t s k k g s s s s k (6) which describes the relationship between the angular position output and input signals. where ωm is the angular velocity of the motor (rad/s), va is the applied armature voltage (v), kt is the motor torque constant (nm/a), la is motor armature inductance (henry), ra is motor armature resistance (ohm), s is a complex variable, fv is viscous friction, j is the moment of inertia (kgm2), kb is back emf constant (vs/rad), k is gain of position control, θo is angular position output, θi is angular position reference, kt is constant, where kt = kt / (rafv + ktkb), and τ is time constant, where τ = raj / (rafv + ktkb). upon the receipt of the input signal, rotation was initiated by the motor, resulting in a corresponding adjustment of the cross-sectional area of the butterfly valve. this alteration subsequently impacted the mass flow rate of the recirculating air. such a system can be considered by flowing through pipes with different cross-sectional areas as shown in fig. 6. fig. 6 fluid flow through a pipe with different cross-sectional areas the fluid flow from cross-sectional areas (a1 to a2) was described by the bernoulli equation. when the fluid was incompressible and kept at the same height (h1 = h2), the fluid velocity at the exit could be estimated [25]. ( )1 2 2 2 1 2 ( ) ρ − = + p p v t v (7) advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 283 to determine the mass flow change as the fluid flows through the control valve and solve this problem, the continuity equation and the laplace transform were applied. the mass flow rate of the recirculating air through the control valve could be calculated as: ( ) ( ) ( ) ( )2 ρ=q s s a s v s (8) when it is defined, a(s) = k1θ(s) is the relationship between the linear cross-sectional area (a(s)) and the gate position of the valve (θ(s)), and k1 is the constant of proportionality. therefore, the transfer function of the drying air flow rate was changed by the rotation of the control valve (gvalve) shown as: ( ) ( ) ( ) ( ) ( )2 1ρ θ = =valve q s g s s v s k s (9) when considering that air mixing was a time-independent value x(t), the laplace transform of the function was represented by, ( ) ( ) ( ) ( )3 ω = =mixing point s g s x s q s (10) where ν1 is velocity of the fluid at point 1 (m/s), ν2 or v2 is the velocity of fluid at point 2 (m/s), ρ is fluid density (kg/m3), p1-p2 is pressure difference (pa), q is the mass flow rate at point 2 (kg/s), k1 is the constant of proportionality, x is the proportion of the air mixing process, and ω3 is the humidity ratio of mixed air (gw/kgda). the total transfer function of the system (gtotal) according to fig. 4 was obtained by combining the blocks from the 3 main parts reported previously, as shown in the formula. ( ) ( ) ( ) ( ) ( ) ( )3 1 2 2 ω ρ θ τ = = + + t t total i s k kk s v s x s g s s s s k (11) 2.4. identification of the humidity control system from recirculating drying air system identification is a mathematical modeling method for dynamic systems. it uses experimental input and system response data in modeling [26-27]. this research used closed-loop experimental data collection in the time domain for system identification with matlab program. the least-squares method was compared to the general model of the second-order system described in section 2.3. the sequence of steps to system identification can be schematically represented in fig. 7. fig. 7 system identification procedure 2.5. proportional integral (pi) controller design the design of the system controller starts from setting the design specifications. steady-state errors (ess) are zero, percent overshoot (%os) is less than 25%, and settling time at 2% error (ts) is less than 60 seconds. these requirements are used to calculate the design point according to [28]. ( ) ( ) 2 2 2 ln % ln % ζ π = + os os (12) advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 284 4 ω ζ =n st (13) 2 1,2 1ζω ω ζ= − ± −n ns j (14) then, the root locus was analyzed to determine the proportional gain and integral gain under the angle condition and the magnitude condition. the pi controller was in the form of a transfer function according to [28]. ( )+ = + = pi pi p ck s zk g k s s (15) where ζ is the damping ratio, ωn is the natural frequency, s1,2 is the dominant pole for a design point, gpi is the transfer function of the pi controller, kp or ki is controller gain, and zc is zero. the feedback control system for controlling humidity ratio in the air circulation system is shown in fig. 8, where the block diagram above (plant) was a command through the arduino support package in the actual system operation, and the block diagram below was a mathematical model derived from system identification. the output signals from both sources were compared to the setpoint value. fig. 8 schematic diagram of a closed-loop humidity ratio control system 3. result and discussion in this section, the results of the drying air recirculation test are discussed. to control the system and evaluate the performance of the controller, the transfer function obtained through system identification techniques was deployed. 3.1. the ability of the valve to adjust drying air circulation fig. 9 the relationship between the input signal and the air recirculation the response of the butterfly valve was evaluated with various input signals, as shown in fig. 9. results indicate that the volumetric flow of return air increased proportionally to the input signal in the range from 0% (valve at angle 0 degrees, air return leak of 0.0009 m3/s) to 50% (valve at angle 45 degrees, air return of 0.01 m3/s). air circulation is reused up to 68.33% advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 285 when compared to the use of unmixed drying air in a drying chamber. however, this experiment limits the volumetric flow of drying air in the range of 60% (valve open at an angle of 54 degrees) onwards, and the system has the potential to 83% air recirculation when the valve is fully open. 3.2. system identification result of the humidity ratio control system from the system identification according to section 2.4, it was found that the least-squares method can estimate the variables present in the second-order transfer function as: ( ) 2 0.002263 0.2842 0.01332 = + + totalg s s s (16) the estimation results correspond to the experimental data as 85.51%, and the root mean square error (rmse) stands at 0.288. considering the accuracy of this model and the research of pongam et al. [29], which identified the thermal system identity of the reheating furnace for the design of the pi controller similarly, it was seen that this model was accurate enough to be used to design a controller and simulate the system response before being applied to control the actual system. fig. 10 pole-zero map of the system fig. 11 the response to the unit step function of the system from considering the closed-loop system of eq. 10, it was found that the system has 2 poles, -0.0742 and -0.21, located on the real number axis as shown in fig. 10. when testing the transfer function with a unit step input, it was found that the transient response in terms of the rise time was 32.5 seconds, the settling time at 2% error was 58.6 seconds, and response in advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 286 steady state was 0.145 (setpoint = 1 in unit step input), which appears to have an offset error as in fig. 11 due to the type 0 of open-loop transfer function. therefore, it is necessary to minimize steady state error with the pi controller according to section 2.5. 3.3. proportional integral (pi) controller fig. 12 shows the pole and zero map of the system that was compensated by the pi controller. the proportional gain was 11.22, and the integral gain was 0.9884, which resulted in the system behaving according to the design conditions outlined in eq. 14. the presence of complex conjugate poles on plane -0.0837 ± j 0.11 led to an oscillating effect on the unit step function, as shown in mathematical simulation (fig. 13). the system had an overshoot of 16.5% (less than 25%) and settling time (2% of error) of 42.8 (less than 60 sec), which was following the established design conditions as shown in table 1. therefore, these gain values were tested with the air humidity ratio control system after the recirculation drying air mixing process. fig. 14 shows the system response to pi controller operation. the process value was the air humidity ratio from the actual experiment, and the simulation was the response from the mathematical model compensated by a pi controller. fig. 12 pole-zero map of the system compensated by pi controller fig. 13 simulation of the unit step response of system compensated by pi controller table 1 the unit step response of the system: before and after compensation by the controller system rise time (s) overshoot (%) settling time (s) final value requirements less than 25% 60 before compensation 32.5 58.6 0.145 after compensation 11.1 16.5 42.8 1 advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 287 the accuracy of describing the data from the mathematical model with system identification was as high as 85.51%, resulting in a corresponding trend of the response between the mathematical model and the actual process value as shown in fig. 14. despite some discrepancies that resulted from both mechanical and thermal losses in the air mixing process, further study was necessary to assess the impact of these losses. however, the overall system could be seen to have effectively maintained the process response within acceptable limits, with a maximum percent overshoot of 25%, settling time at 52 seconds before reaching the setpoint value, which found a percent overshoot of less than 15% and settling time less than 20 seconds at every subsequent setpoint. the integral term from the controller has great potential to improve the ess value. this control system can track the setpoint and compensate for discrepancies, causing ess to eventually reach 0. when comparing the system performance with the study conducted by pakdeekaew et al. [20], it was observed that the humidity control system described in the reference study exhibited a faster response to the reference value, approximately 40% faster than the system implemented in this research. nonetheless, this influence was prominent during the initial phase of the operation. in the next setpoint, it was found that the humidity control system of this research was able to respond to the dependent variable faster from the start, which was only 7% behind the reference study. the results of the response comparison are shown in fig. 15 and table 2. while the humidity control system in this study exhibited a slightly delayed response compared to the reference study, it is worth noting that the humidity control system described in the reference study had a limitation on the amount of air recirculation, which should not exceed 15.18% of the drying air used in the system. this limitation highlights the advantage of the humidity control system implemented in this research, particularly when there is a need for large quantities of recirculating drying air. fig. 14 system response from pi controller compensation fig. 15 responses of the humidity control system at the same input advances in technology innovation, vol. 8, no. 4, 2023, pp. 278-289 288 this system can recycle up to 83% of the drying air (fig. 9), combined with the advantages of electric heating for the hot air system mentioned in the introduction. therefore, the researcher has a guideline to apply this device for controlling the humidity and temperature in the paddy drying system. it is hoped that a highly precise control system that operates according to the optimal conditions plays a role in the energy efficiency of the drying process. it can reduce carbon emissions into the atmosphere compared to hot air combustion systems and being able to improve the quality of the product after drying in the future. table 2 the comparison between responses implemented in this research and the research reference setpoint (humidity ratio) system overshoot (%) settling time (s) 18 gw/kgda research reference 4.22 32.70 this research 23.65 45.68 17 gw/kgda research reference 0.71 109.44 this research 2.07 110.80 19 gw/kgda research reference 0 212.39 this research 4.76 227.25 20 gw/kgda research reference 0.15 309.45 this research 2.60 324.30 4. conclusions this study developed an air recirculation system utilizing a servo motor to control a butterfly valve, thereby achieving proportional recirculation of dry air to mix with the intake air. an air circulation test observed a consistent and proportional increase in the volumetric flow of return air increased proportionally quite constant during the input signal. the defined input signal, represented by the percentage of valve opening, corresponded to the humidity ratio of the air obtained from the mix of return air and ambient air. employing the system identification method, the mathematical model of the system was analyzed. the research defined specific design conditions to ensure zero steady-state error, a percentage overshoot of less than 25%, and a settling time was within 60 seconds. through systematic system simulations utilizing a unit step function, it was determined that the proportional gain of 11.22 and the integral gain of 0.9884 fulfilled the design requirements, resulting in a percentage overshoot of 16.5% and a settling time of 42.8 seconds. subsequent testing of the designed pi controller was tested against the actual air humidity ratio control system and revealed that the controller had sufficient potential to compensate for the system. in the future, it has the potential to further expand this system to control the air conditions on the industrial scale of drying systems. conflicts of interest the authors declare no conflict of interest. references [1] n. k. fukagawa and l. h. ziska, “rice: importance for global nutrition,” journal of nutritional science and vitaminology, vol. 65, no. supplement, pp. s2-s3, 2019. 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[29] t. pongam, j. srisertpol, and v. khompis, “pi controller design for temperature control of reheating furnace walking hearth type in setting up process,” advanced materials research, vol. 748, pp. 801-806, august 2013. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v8n2(2023)-aiti#10926(100-110).docx advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 an image-based rice weighing estimation approach on clock type weighing scale using deep learning and geometric transformations an cong tran*, thanh trinh thi kim, hai thanh nguyen college of information and communication technology, can tho university, can tho, vietnam received 30 september 2022; received in revised form 27 november 2022; accepted 28 november 2022 doi: https://doi.org/10.46604/aiti.2023.10926 abstract ai impacts surrounding human life, such as the economy, health, education, and agricultural production; however, the crop prices in the harvest season are still on manual calculation, which causes doubts about accuracy. in this study, an image-based approach is proposed to help farmers calculate rice prices more accurately. yolov5 is used to detect and extract the scales in the images taken from the harvesting of rice crops. then, various image processing techniques, such as brightness balance, background removal, etc., are compiled to determine the needle position and number on the extracted scale. lastly, geometric transformations are proposed to calculate the weight. a real dataset of 709 images is used for the experiment. the proposed method achieves good results in terms of map@0.5 at 0.995, map@[0.5:0.95] at 0.830 for scale detection, and mae at 3.7 for weight calculation. keywords: scale detection, scale value recognition, rice weighing, geometric transformations, deep learning 1. introduction many new technologies have been applied in agriculture to help increase productivity and quality. for example, machine learning algorithms have been proposed to identify diseases in animals [1-2] and plants [3]; develop post-harvest support technologies [4-5] to assist farmers; and protect data for internet business secrets [6]. harvest season is an important time to collect the crops that are grown by farmers. in addition, farmers may want to estimate the weight and quantity of their products for sale activities. vietnam has a highly developed agriculture, especially millions of tons of wet rice production every year†, and it continues to increase over the years [7]. every year, farmers usually have to harvest 2-3 rice crops [8], and calculating the payment is an indispensable task in the production process. the calculation of rice prices is not too complicated, yet it still requires accuracy and speed. therefore, farmers usually use applications to calculate the payment by entering the numbers manually. this helps farmers calculate the payment quicker and more accurately than the traditional method. however, since the calculation is observed by human eyes, errors may occur in manual calculation and the results may be incorrect. with the current trend of ai, some computer-based methods can be developed to read the weight from the scale. the application of image processing techniques and machine learning can help farmers calculate rice prices, meanwhile, correcting data entry and manual calculation errors. although these methods are not complex, precise numbers and good efficiency are necessary for farmers’ benefit. the manual calculation is still problematic frequently because it is very time-consuming or leads to miscalculations; moreover, there are no images for further comparisons. this study aims to provide solutions for * corresponding author. e-mail address: tcan@cit.ctu.edu.vn † production volume of rice paddy in vietnam from 2011 to 2021, https://www.statista.com/statistics/671339/production-of-paddy-in-vietnam/. advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 101 farmers to improve rice payment calculations and overcome some possible issues, including the reduction of calculation time and wrong calculations. when farmers or rice buyers enter a wrong result, they can use the captured images to check and correct the results. although an electronic scale provides great accuracy, the price of electronic scales is often higher than clock-type weighing scales. an electronic scale has a tempered glass scale surface. there is a risk of scratches or breakage if the user is not careful or moves around a lot while weighing. in addition, farmers harvest and pack rice directly in the rice fields so that electronic scales with batteries may be damaged by contact with water or swampy. mechanical scales such as clock scales usually have a longer life than electronic scales. therefore, it would be appropriate to use a traditional clock scale directly in the rice fields. in this study, the information displayed on the scale is extracted from the images captured during harvest crops using object recognition and image processing techniques. the combination of several geometric transformations calculates the weight and amount of payment to support farmers and poses an ai solution to smart agriculture. the remainder of this paper is organized as follows. section 2 provides a literature review related to solutions in smart agriculture. the system architecture and problem-solving methods are described in section 3. section 4 presents and describes experimental results and discussion. finally, section 5 shows a brief conclusion and future work. 2. literature review machine learning techniques are widely used in applications that support agricultural activities. by providing useful applications and crop insights, machine learning techniques benefited farmers by minimizing agricultural losses [9-10]. numerous applications were presented for crop management, crop yield prediction, plant disease detection, agricultural land use monitoring, water, and soil conditions [11]. plenty of techniques based on information technology are applied to improve efficiency in agriculture, including sensor data processing from internet-of-thing systems, image processing using machine learning algorithms, etc. among these areas, computer vision is perhaps the most interesting for scientists. important image processing techniques include camera types, color spaces, color indices, and image segmentation related to agriculture applications and precision agriculture [12-13]. chakraborty and ghosh [14] proposed an automated plant disease diagnosis method in agriculture as well. transformer-based architectures and data augmentation methods were employed to achieve a mean intersection over union (miou) of 0.582 in the agriculture-vision challenge 2022 [15]. animal farming also attracted numerous researchers with extensive studies [16], such as an investigation on data, applications for smart farming [17]; and research related to the behaviors of animals [18]. tools for supporting agricultural activities have received attention from scientists. weighing scales are a crucial tool for harvesting crops. the weight of the objects in free-living settings can be measured objectively and the weighing scales have experimented with 50 fruits and other everyday objects of various sizes and weights [19]. some eating tools including spoons, forks, or chopsticks were considered to measure the weight of food in an image using several image processing techniques and the exchangeable image file (exif) metadata [20]. telematics data was combined with machine learning to determine the weight of vehicles on a road segment [21]. other interesting studies were presented and evaluated, i.e. methods for estimating the weight and volume of poultry and related products based on computer vision techniques [22]; seven models using single tomato image features data to calculate the weight and volume of single and hidden tomatoes [23]; and methods for predicting the body weight of animals [24]. although several weight estimation techniques using images have been presented, studies on detecting clock scales to estimate the weight of an object are less. the application of deep learning algorithms in this field is still very rare as well. therefore, a yolo-based approach for object recognition combined with some geometric transformation methods is investigated to estimate the weight on a clock scale in this study. advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 102 3. research methods the position of the needle and its angle to the numbers on the scale to determine the weight can be observed by human eyes. however, human eyes cannot always be accurate. therefore, in this study, image processing techniques and geometric transformations were used in three phases to perform the tasks sequentially as follows. firstly, the area of the scale in the originally captured image was detected and extracted. this is crucial to eliminate unrelated objects and focus on determining important things inside the scale such as the needle’s positions and numbers in the scale. some well-known deep learning architectures for object detection such as yolov5 can be trained to detect scale well [25]. then, various image processing techniques were combined to indicate the position of the needle. the following tasks include cropping the scale from the original image; adjusting the image size and brightness balance; removing the background; determining the center, numbers, and hand of the scale; and computing the weight value. finally, the image processing algorithms in the opencv library were used for these tasks, and the parameters for these algorithms were determined through careful experiments [26]. moreover, based on the proposed method, an application for managing rice sales was also developed using the django framework. 3.1. the weighing scale detection the training was performed with a set of 709 images taken during the rice harvest in vietnam to identify the scale in the image. this set of images was used to train yolov5 for clock scale recognition, and it is labeled by the “make sense” library supported on the web platform. the returned result was that each labeled image had a corresponding label (.txt file) containing information about the contour of the object, where each line contained information about an object. each line contains 5 values with information about the object and the contour coordinates including object name, center coordinate (x, y), width, and height. the contour coordinates must be normalized to the interval [0, 1] to converge faster in the training phase. the information and coordinates of the scale presented in fig. 1(a) are shown respectively in fig. 1(b) and fig. 1(c). (a) an image in the dataset (b) the image’s label (c) the coordinates, width, and length of the scale fig. 1 an original image in the dataset and its labels advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 103 after the training phase, a scale recognition model that was created can recognize the scale in an input image. then, the image was cropped according to the coordinates provided by the recognition model, and an image consisting of only the scale was returned. next, the image was processed to determine the value of the detected scale. this step includes several tasks as described in fig. 2. the first task aims to extract and crop the area containing only the scale and then resize the image to 1000 × 1000 pixels. the next task was to adjust the brightness balance to reduce lighting effects or underexposure. then, the background was removed, and only the rounded scale was kept. subsequently, the center, needle, and numbers on the scale were identified. several relevant mathematical operations were applied to confirm the angle measured by the three above-mentioned factors (center, needle, and numbers) for determining the weight. fig. 2 steps to calculate the weight from the cropped image 3.2. cropping the image and adjusting the size the scale recognition model was used to recognize and return the position of the scale in the image. then the image was cropped based on the x min, y min, x max, and y max values to obtain the image of the scale as shown in fig. 3. after that, the image was resized to 1000 × 1000 pixels for further processing using opencv’s resizing algorithm. fig. 3 the image cropping step 3.3. brightness balancing the cropped images from the previous step were converted to grayscale images, and the grayscale histograms were computed. as shown in fig. 4, the average values were calculated to balance the image brightness. the cvt-color() and calchist() functions of the opencv library were combined to accomplish these tasks. advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 104 (a) before (b) after fig. 4 the scale before and after brightness balancing 3.4. background removal when cropping the image according to the predicted contour of the scale recognition model, the received image mostly contains the background behind the scale. unfortunately, the background is sometimes the factor that interferes with further determination, so it must be removed. the removal of the background can be retouched by smoothing the image with the gaussian blur operation and then converting the color image to grayscale. subsequently, the contours of the image were identified, and the largest contour was picked out and redrawn with green color. then the color filtering algorithm was applied to keep only the green color. next, the green objects were filtered by converting the image to the hue, saturation, and value (hsv) color space and selecting an appropriate color threshold to draw the contour. after that, the circle detection algorithm was used to detect the front surface of the scale. this algorithm returned the center point (xi, yi) and radius r of the detected circle. all circles with a center of (xi, yi) and a radius greater than r were drawn to remove all backgrounds outside the scale surface. fig. 5(a) illustrates the scale with background, while such background is removed from the image as shown in fig. 5(b). this process was implemented with several functions of the opencv library, including the findcontour() function to find the contour of the scale, the inrange() function to perform threshold operations, and the houghcircles() function to detect the circle. (a) before background removal (b) after background removal fig. 5 the scale before and after the background removal step 3.5. determining the center and the numbers on the scale the center point was determined from the background removal step, i.e., the center point returned from the step that determines the center point of the detected circle. if many circles are found, the largest circle, which has the maximum radius, will be taken into account; if no circle is found, the center of the largest contour will be used. advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 105 to identify the numerical values on the scale surface, firstly, only the black areas in the image will be preserved as the numbers are in black. the morphological operators closing and opening [27] were combined to remove the small black dots in the image, which are considered noise for this task. secondly, the image was smoothed using the gaussian blur algorithm to increase the accuracy of the latter tasks. after that, the contours that are potentially the scale values, and the center of the contours were determined as demonstrated in fig. 6(a). finally, the contour of the number at the middle-bottom of the scale was reserved as shown in fig. 6(b). with the help of morphological operators, the small black areas that may represent the noise of this task were removed. only the big numbers that represent the values of the scale and their centers were preserved. the above tasks were implemented based on the opencv library. the gaussianblur() function was used to smooth the image; the getstructuringelement() function was used to create structured elements; the findcontour() function was used to find the contours. (a) the potential scale values (b) the middle-bottom number and its center fig. 6 the contours of the numbers and their centers detected in the scale 3.5. determining the needle the needle determination step started by selecting a red threshold to filter out red objects and detecting edges in the filtered image in fig. 7. the red objects were filtered by converting the image to the hsv color space and selecting the corresponding color threshold with the needle color. from the resulting red-filtered image, an edge detection algorithm was used to find the edge of the scale needle. the thresholding operations were performed using the inrange() function in the opencv library, and the canny method [28] is used for edge detection. in determining the tip of the needle, there are two possible cases. in one case, a straight line representing the tip of the needle can be found in the image with the recognized edge of the needle. in the other case, the straight line is not found. accordingly, the largest contour is calculated, and the center of the calculated contour is considered as the tip of the needle. after the numbers, the center point, and the position of the needle were determined, the geometric transformation operations were used to calculate the angles, and then determine the weight. to calculate the weight based on the position of the needle and the numbers on the scale, the following information must be determined: • the center of the scale surface: i • the point representing the tip of the scale needle: k • the point representing the largest number found: s • the line containing the points i and s: d1 • the line containing the point k and perpendicular to d1: d2 then, the proposed method for calculating the weight is described as follows. point v was determined firstly so that iv and kv are perpendicular to each other, and vik is a valid triangle. the coordinates of the projection v from k to d1 were advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 106 calculated by giving the general equation of the line d1: a1x + b1y + c1 =0. from the general equation of d1, the general equation of d2 must be determined so that d2 is perpendicular to d1 in v (the direction of d2 is the normal vector of d1): a2x + b2y + c2 = 0. this can be achieved by: 1 1 1 2 2 2 0 0 a x b y c a x b y c + + = + + =    (1) the solution to the above system of equations is the coordinate of point v. then, the angular measure of ���� (�) was calculated. to find �, the length of �� ⃗ and �� ⃗ must be calculated. after that, the relationship formula is applied in the right triangle to get the angular measureα . 2 2 ( , ) :ab x y ab x y= + ��� ��� (2) the length formula eq. (2) was applied to calculate the length of the vectors �� ⃗ and �� ⃗ . sin d hα = (3) where h is the length of the hypotenuse of the right triangle, and d is the length of the opposite side of the angleα in a right triangle. it is trivial that each kilogram (kg) has an angular measure � = /360, where m is the maximum measure of the scale (i.e., for the scale with the maximum measure of 100 kg, the angular measure � = 100/360). thus, the weight calculated from the angular measure is ∆= � × (kg). finally, the final weight value of the scale was calculated by adding or subtracting ∆ from the value of the number found on the scale surface. as shown in fig. 7, the number found near the needle is 50, and the position of the needle is on the right of the number 50 (because xk < xs) with the center of the scale as the coordinating elevation. therefore, the weight value of the scale in the image is � = 50 × ∆ (kg). fig. 7 calculation of the angular measure ∆ 4. experiments two experiments were performed to evaluate the proposed system. the first experiment was used to evaluate the clock scale detection model, and the second one was used to evaluate the proposed reading scale value method. in the first experiment, the scale detection model was built based on the yolov5. in the training step, yolov5 configured for google colab was used to train the scale detection model. yolov5 provides 4 versions with different network architectures including yolov5s, a small version; yolov5-m, a medium version; yolov5-l, a large version; and yolov5-x, an extra-large version. in this study, the yolov5-s was used because the model would be later deployed on mobile devices. advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 107 4.1. environment settings and dataset description the experiments were performed on a dell vostro 15-3568 personal computer equipped with a core i5 processor with 8 gb ram. after several experiments, an appropriate configuration for yolo was obtained with the following configurations: a learning rate of 0.01, a batch size of 8, a momentum of 0.937, a weight decay of 0.0005, and a stochastic gradient descent optimization with 10 epochs. to obtain a good performance, it is necessary to balance the epoch and learning rate [29]. as observed in the present experiments, the performance increased during learning, and there was no overfitting of the trained model since the training accuracy and the test accuracy were approximately the same. the dataset consisted of 709 images divided into two sets including a training set and a test set, with a 3-fold crossvalidation approach. the images in the experimental dataset were taken from the farmer’s rice harvest, where the scale can measure a maximum weight of 100 kg. additionally, the images in the dataset were taken from different angles, i.e., left, right, and front as shown in fig. 8. (a) taken from the left (b) taken from the right (c) taken in the front fig. 8 images of weighing scales taken in rice fields scale detection performance is evaluated using average accuracy, precision, recall, mean average precision (map) 0.5 (map@0.5), and map@[0.5:0.95] with 3-fold cross-validation. the map@0.5 demonstrates average accuracy at the intersection over union (iou) threshold of 0.5, while map@[0.5:0.95] ranges between 0.5 and 0.95. in addition, the mean absolute error (mae) is also used to evaluate the accuracy of the weight measurement. the model is evaluated by averaging the absolute difference between the actual weight value (yi) and the weight value predicted by the model (xi). it can be obtained by: 1 d i ii x y mae n = − =  (4) 4.2. weighing scale detection with yolo (a) training set fig. 9 performance in fold 1 with various metrics train/box_loss train/cls_loss train/obj_loss metrics/precision metrics/recall advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 108 (b) validation set fig. 9 performance in fold 1 with various metrics (continued) fig. 9 and table 1 show the results of weight detection in the collected images with precision, recall, map@0.5, and map@[0.5:0.95] measurements. precision and recall quickly reach high accuracy after 8 epochs. map@0.5 reaches a peak value of 0.995, and map@[0.5:0.95] reaches a peak value of 0.830. for the situation of box loss, the value on the validation set reveals some fluctuations while it exhibits a gradual decrease on the other. the performance details during 10 epochs are illustrated in table 1 with coverage at the 8th epoch and a low standard deviation. table 1 the performance of weighing scale detection tasks during 10 epochs epoch precision recall map@0.5 map@[0.5:0.95] 1 0.661 (±0.135) 0.812 (±0.100) 0.704 (±0.154) 0.187 (±0.096) 2 0.792 (±0.128) 0.714 (±0.121) 0.802 (±0.162) 0.327 (±0.154) 3 0.747 (±0.197) 0.827 (±0.098) 0.804 (±0.216) 0.324 (±0.138) 4 0.657 (±0.22) 0.901 (±0.054) 0.726 (±0.249) 0.248 (±0.14) 5 0.851 (±0.115) 0.944 (±0.04) 0.929 (±0.059) 0.429 (±0.058) 6 0.839 (±0.108) 0.986 (±0.006) 0.916 (±0.064) 0.521 (±0.071) 7 0.997 (±0.005) 0.997 (±0.005) 0.995 (±0) 0.577 (±0.158) 8 1.000 (±0.000) 1.000 (±0.000) 0.995 (±0.000) 0.731 (±0.042) 9 1.000 (±0.000) 1.000 (±0.000) 0.995 (±0.000) 0.795 (±0.046) 10 1.000 (±0.000) 1.000 (±0.000) 0.995 (±0.000) 0.830 (±0.026) 4.3. weighing calculation fig. 10 an application to support the sale of rice the image-based weight calculation method was evaluated on 236 images in the test set with 3-fold cross-validation in mae. as shown in fig. 10, high errors are obtained in some cases when the scale is detected, but the needle is not. in such cases, the predicted result is considered 0 which can result in a large error value when comparing the actual and predicted metrics/map@0.5 metrics/map@[0.5:0.95] val/cls_loss val/obj_loss val/box_loss advances in technology innovation, vol. 8, no. 2, 2023, pp. 100-110 109 values. the average mae on the test set for all cases is 6.445. the needle is detected correctly in 225 out of 236 cases, which corresponds to an accuracy of 0.953. therefore, if only the case in which the needle is detected to calculate the weight, the result is an mae of 3.7. in addition, an application based on the proposed method was also implemented as shown in fig. 10. to calculate the weight of harvested rice in the captured images, the user enters the name of the rice plant and the unit price in vnd/kg, then selects a set of images and clicks the “calculate” button. the returned result is a series of calculations that are practically similar to the farmer’s manual calculation results. the application also saves the images for further investigation and comparison. 5. conclusions the study proposed a method to determine the weight value of clock scales in images by identifying and extracting the scale from the captured image, and then the position of the needle in the scale is determined to calculate the weight value. this method is the first step to building a complete application that helps farmers calculate rice payments using modern technologies, particularly artificial intelligence. the detection and extraction of the scale achieved very high accuracy with map@0.5 at 0.995 and map@[0.5:0.95] at 0.830. however, the detection of the needle in the scale is still a challenge due to the limitation of the collected dataset. in addition, determining the important elements (center of the scale, needle edge, and numbers) for calculating the weight is highly dependent on a variety of factors, i.e., the light and the tilt of the scale in the photograph. the result from mae is 3.7 for weight calculation. in future studies, the methods to reduce light noise could be evaluated since the images were taken mainly in sunny and dry areas; 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[29] z. e. khatib, a. b. mnaouer, s. moussa, m. a. b. abas, n. a. ismail, f. abdulgaleel, et al., “lora-enabled gpubased cubesat yolo object detection with hyperparameter optimization,” 2022 international symposium on networks, computers and communications (isncc), pp. 1-4, july 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 english language proofreader: si-yu lin formulating seismic intensity scale (jma-sis) using response spectrum: a new approach for structural engineering design nanang gunawan wariyatno1,*, ay lie han2, yanuar haryanto1,3,4, gathot heri sudibyo1, sumiyanto1, nastain1, arwan apriyono1, laurencius nugroho4, hsuan-teh hu4, fu-pei hsiao3, buntara sthenly gan5 1department of civil engineering, universitas jenderal soedirman, purwokerto, indonesia 2department of civil engineering, universitas diponegoro, semarang, indonesia 3national center for research on earthquake engineering, taipei, taiwan 4department of civil engineering, national cheng kung university, tainan, taiwan 5department of architecture, nihon university, koriyama, japan received 03 september 2024; received in revised form 10 december 2024; accepted 12 december 2024 doi: https://doi.org/10.46604/aiti.2024.14243 abstract this study aims to formulate a calculation for earthquake shaking intensity (rs_msis) based on the response spectrum (rs) using the japan meteorological agency-seismic intensity scale. the research investigates the relationship between the response spectrum parameters—period and maximum acceleration—and the earthquake source types, including megathrust, benioff, and shallow crust/background sources. artificial ground motions are generated and analyzed using matlab to calculate shaking intensity values, which are then used to develop the rs_msis formula. the formulation is validated against actual response spectrum data from 15 indonesian cities and demonstrated high accuracy, with the wariyatno coefficient applicable across all models. this approach provides a standardized method to assess seismic intensity, offering enhanced reliability for building design in earthquakeprone areas and serving as a valuable tool for engineers and urban planners to improve earthquake resilience in diverse seismic environments. keywords: japan meteorological agency-seismic intensity scale (jma-sis), time history, response spectrum, rs_msis, wariyatno coefficient 1. introduction an earthquake is a natural geological event characterized by the sudden release of energy in the earth's crust, resulting in seismic waves. this energy release typically occurs due to the displacement of tectonic plates along faults or fractures in the earth's surface. seismic waves originate in the bedrock and travel to the surface, passing through various soil layers. the intensity of ground shaking is influenced significantly by factors such as earthquake magnitude, distance from the epicenter, and soil composition, which affects how vibrations propagate [1]. typically, earthquake shaking intensity decreases as the distance from the epicenter increases. [2]. for instance, the 2011 tohoku earthquake, with a magnitude of 9, produced a maximum shaking intensity of 6.6 [3]. such intensity measurements are crucial, as they provide valuable data for assessing structural impacts and guiding building design in seismic regions. fig. 1 illustrates the distribution of maximum shaking intensity relative to the distance from the hypocenter during this earthquake. standards for measuring the earthquake shaking intensity on the ground surface include modified mercalli intensity (mmi), chinese seismic intensity scale (csis), european macroseismic scale (ems), and environmental seismic intensity * corresponding author. e-mail address: nanang.wariyatno@unsoed.ac.id 158 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 (esi) [4-5]. in this research, the japan meteorological agency-seismic intensity scale (jma-sis) [6-7], developed by the japan meteorological agency (jma), is utilized to categorize the intensity of local ground shaking caused by earthquakes. jma-sis quantifies ground shaking at measurement sites in affected areas, assigning levels from one to seven, with additional "strong" and "weak" subdivisions between levels five and six. this scale plays a critical role in japan's disaster mitigation efforts, facilitating immediate and informative earthquake warnings broadcast nationally, which allows people to assess shaking severity in real-time. as shown in fig. a1 (appendix 1), jma-sis indicates that shaking at level 5lower may cause interior objects to fall, while structural damage to buildings potentially begins at level 6lower [8-9]. this standardized intensity scale enhances public safety by effectively communicating earthquake severity to the public and aiding in immediate response planning. fig. 1 the distribution of jma_msis versus hypocenter in the tohoku earthquake the jma-sis level is determined based on the maximum-sis (msis) values measured at the ground surface. these msis values are derived from ground motion acceleration data recorded in three directions: north-south (ns), east-west (ew), and up-down (ud) [10]. the lowest jma-sis level corresponds to an msis value of ≤ 0.5, while the highest level corresponds to an msis value of ≥ 6.5, as shown in table 1 [11]. table 1 interval level jma-sis no. sis msis interval 1 0 msis < 0.5 2 1 0.5 ≤ msis < 1.5 3 2 1.5 ≤ msis < 2.5 4 3 2.5 ≤ msis < 3.5 5 4 3.5 ≤ msis < 4.5 6 5lower 4.5 ≤ msis < 5.0 7 5upper 5.0 ≤ msis < 5.5 8 6lower 5.5 ≤ msis < 6.0 9 6upper 6.0 ≤ msis < 6.5 10 7 6.5 ≤ msis the intensity of earthquake shaking significantly affects building damage and human casualties [12]. specifically, higher shaking intensity correlates with an increased frequency of building failures, leading to a greater number of casualties. data from the jma (1996–2018) indicate that both fatalities and building damage increase as maximum shaking intensity (jma_msis) levels rise [11]. the relationship between jma_msis, fatalities, and building damage is illustrated in fig. 2. advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 159 fig. 2 relationship between seismic intensity level and cases of human casualties and building damage each earthquake-induced ground motion has a unique shaking intensity and corresponding response spectrum (rs) [1314]. the rs represents the maximum response of a single-degree-of-freedom (sdof) structure to earthquake ground motion [15] and serves as a primary parameter in earthquake-resistant building design [16]. this spectrum is influenced by factors such as soil type and building location. in time history analysis, the applied load is an artificial ground motion generated through spectral matching or spectrum scaling to align with the target response spectrum [17]. the intensity of artificial ground motion can be assessed using the jma_msis formula. this supports the hypothesis that a strong relationship exists between shaking intensity and response spectrum. in this study, earthquake shaking intensity is calculated using a response spectrum– based metric called rs_msis. fig. 3 illustrates the relationship between shaking intensity and rs. fig. 3 illustration of the relationship between msis and rs this study aims to formulate the jma-sis using rs analysis, providing a predictive formula for seismic intensity based on a predetermined rs, improving the accuracy and comprehensibility of the intensity. importantly, this approach does not change the design results for structures but instead offers a clearer interpretation of the earthquake intensity, which is crucial for public awareness. by employing rs analysis to determine seismic intensity, this study seeks to offer a tool that is easier to understand for both professionals and the general public when assessing earthquake risks to infrastructure. the jma-sis will help improve the understanding of structural resilience against seismic events, ultimately contributing to enhanced earthquake preparedness and more resilient infrastructure in earthquake-prone regions. 2. methods the complete research flowchart is shown in fig. 4. this study uses both rs and ground motion data, each comprising model and validation datasets. the rs model data varied based on ts (x-axis) and samax (y-axis) values, while the ground motion data are determined by the earthquake's mechanism, magnitude, and distance from the epicenter. for each earthquake mechanism type, three sample ground motions are selected to represent all possible mechanisms. artificial ground motions are generated using spectral matching with seismomatch software [18]. before spectral matching, the ground motions are scaled to match the target rs for each direction [19]. the target rs used has a samax value of 0.01 g for all ts values. the artificial ground motions produced by spectral matching are then analyzed using the jma-sis program to calculate msis values for each rs variation. to vary the rs with respect to the samax value [20], the artificial ground motions are scaled using a scaling factor based on the ratio of the samax value. the msis values are subsequently calculated 160 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 using the jma-sis program for each scaled ground motion. the final step involved formulating the relationship between msis and rs (denoted as rs_msis). validation of the rs_msis formulation is then performed to assess its accuracy by comparing it with the results from the jma-sis program calculations. fig. 4 research flow chart 2.1. formulation of msis the complete msis formulation flow diagram is shown in fig. 5. the process uses a standard tool for calculating shaking intensity based on jma-sis, developed in matlab (matlabjma-sis). it takes three components of earthquake ground motion—ns, ew, and ud—as input. to begin, the fast fourier transform (fft) is applied to each acceleration component, converting the time-domain signals into the frequency domain. next, the bandpass filters, as defined in eqs. (1)-(5), are applied to the frequency-domain accelerations: 1 1  = f (1) 2 2 4 6 8 10 12 1 1 0.694 0.241 0.0557 0.009664 0.00134 0.000155y y y y y y  = + + + + + + (2) 3 3 1 0.5 f exp −  = −     (3) 10 f y = (4) 1 2 3   =   (5) where f denotes the dominant frequency, λ1 refers to the filter's on-period effect, λ2 refers to the high-cut filter, and λ3 refers to the low-cut filter. after filtering, the accelerations are transformed back from the frequency domain to the time domain. the normalized vector composition of the three acceleration components is then used to calculate the acceleration amplitude. next, the intensity is automatically calculated from the filtered three-component ground acceleration data, following the application of the bandpass filter. finally, using the filtered time-domain acceleration and its vectored components, the msis value is determined using advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 161 2 0 940.3msis log a .= ( )+ (6) where a03 represents the minimum peak acceleration sustained over a continuous 0.3-second duration around the maximum acceleration response. fig. 5 flowchart of msis formulation 2.2. calculation of a0.3 the a0.3 value is derived from research conducted in the hongo district of tokyo between 1894 and 1924. the results indicated that houses and trees are affected only by shaking after the earthquake had lasted for 0.3 seconds [21]. this finding showed that these objects did not experience significant shaking when the acceleration duration is below 0.3 seconds. therefore, the 0.3-second threshold is confirmed as a key parameter in the msis calculation. in this study, the a0.3 value was obtained from the three-directional acceleration response: ns, ew, and ud [22]. the graphical representation of the relationship between time and resultant acceleration is shown in fig. 6(a), while fig. 6(b) illustrates the cumulative time accumulation method used to calculate the a0.3 value. the graph is generated by sorting the acceleration values from highest to lowest, and a0.3 is then compared with 0.3/t + 1. (a) absolute acceleration graph (b) determination of a0.3 based on cumulative duration [23] fig. 6 calculation of a0.3 162 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 2.3. validation of msis formulation ground motion data and actual msis values were obtained from the k-net website and used for validation [3]. the msis values covered all jma-sis levels at 0.1 intervals, the calculations performed using the matlabjma-sis tool for the ground motion data are then compared with the actual msis values. the comparison between the matlabjma-sis calculations and the k-net data showed highly accurate results, as the generated equation closely followed the form x≈y with an r2 value approaching 1. the recorded discrepancy is primarily due to actual msis data being rounded to one decimal place, whereas the matlabjma-sis calculations are carried out to three decimal places. these findings demonstrate that the jma-sis program effectively validated the msis calculations, as shown in the sample data presented in fig. 7. fig. 7 comparison of matlabjma-sis vs k-net 2.4. response spectrum (rs) the rs used in this research consisted of two components: the ‘rs model’ and ‘rs validation’. the rs model varies based on ts values, ranging from 0.2 to 1.2 seconds in 0.1-second intervals, as shown in fig. 8. the samax value for all ts variations is set to 0.01 g, which is necessary to establish the relationship between rs and msis (rs_msis). this relationship is achieved by scaling the rs using a factor corresponding to the samax value. fig. 8 response spectrum model fig. 9 distribution map of rs validation data advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 163 for rs validation, city samples from the five largest islands in indonesia are selected, with three cities chosen from each island, totaling 15 rs validation samples. the rs values are obtained following the sni 1726:2019 guidelines for the earthquake-resistant design of buildings and non-building structures [23]. the validation considered three soil classes: stiff (sc), medium (sd), and soft soil (se). the distribution map of the selected cities is presented in fig. 9, while table 2 presents the corresponding rs validation variables, including t0 and s1, for each city. table 2 rs validation variables no. island city soil class variable of response spectrum t0 ts samax s1 1 sumatera medan sc 0.130 0.670 0.810 0.540 palembang sd 0.230 1.130 0.465 0.525 padang se 0.210 1.050 1.125 1.185 2 java jakarta sc 0.120 0.600 0.945 0.570 surabaya sd 0.140 0.720 0.855 0.615 yogyakarta se 0.200 0.990 1.125 1.110 3 kalimantan pontianak sc 0.070 0.330 0.225 0.075 samarinda sd 0.230 1.150 0.195 0.225 palangkaraya se 0.280 1.380 0.120 0.165 4 sulawesi manado sc 0.110 0.550 1.245 0.690 makassar sd 0.140 0.710 0.360 0.255 palu se 0.200 1.000 1.200 1.200 5 papua sorong sc 0.100 0.480 1.920 0.915 jayapura sd 0.140 0.700 1.500 1.050 nabire se 0.200 1.000 1.200 1.200 2.5. ground motion the ground motion data used in this study are divided into two categories: model data and validation data. the criteria for the model data are selected based on earthquake source types, magnitude, depth, and epicenter distance, to ensure a comprehensive representation of various earthquake conditions [24]. in contrast, the validation data are selected based on indonesia's earthquake de-aggregation map [25], following standard ground motion selection procedures. the details of both the models and validation datasets are presented in table 3 and table 4, respectively. table 3 ground motion model [26-28] no. earthquake sources earthquake date station magnitude (m) depth (km) epicenter distance (km) 1 interface subduction (megathrust) tohoku 11-mar-2011 tachikawa 9.00 24.0 256.00 2 tokachi-oki 26-sep-2003 ikeda 8.00 42.0 138.00 3 valparaiso 3-mar-1985 santiago 8.80 33.0 122.00 4 deep subduction (benioff) michoacan 22-may-1997 la union 6.60 70.0 107.00 5 hokkaido 25-feb-2023 shibetsu 6.00 63.0 101.00 6 geiyo 24-mar-2001 toyo 6.40 51.0 41.00 7 shallow crustal / background imperial valley-02 18-may-1940 el centro 6.95 8.8 13.00 8 mammoth lakes-11 7-jan-1983 convict creek 5.31 4.5 9.70 9 kozani 19-may-1995 karpero 5.10 6.8 11.85 10 umbria 26-sep-1997 castelnuovo-assisi 6.00 10.0 19.90 11 san francisco 9-feb-1971 castaic 6.61 13.0 25.36 12 taiwan smart 1 21-sep-1983 smart1 i01 6.50 18.0 99.31 164 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 table 4 ground motion validation [27-29] no. island city ground motion (earthquake) megathrust benioff shallow crustal/ background 1 sumatera medan el pedragal (chile, 2015.09.16) caleta de campos (michoacan, 1997.05.22) tracy (livermore01, 1980.01.24) padang concepcion san pedro (chile, 2010.02.27) san miguel (el salvado, 2001.01.13) mission creek fault (landers, 1992.06.28) palembang municip (chile, 2010.02.27) santa ana (el salvador, 2001.01.13) tracy (livermore01, 1980.01.24) 2 jawa jakarta curico (chile, 2010.02.27) santa ana (el salvador, 2001.01.13) desert hot springs (bigbear-01, 1992.06.28) yogyakarta concepcion san pedro (chile, 2010.02.27) santa ana (el salvador, 2001.01.13) tolmezzo (friuli, 1976.05.06) surabaya valdivia (chile, 2010.02.27) santa ana (el salvador, 2001.01.13) mission creek fault (landers, 1992.06.28) 3 kalimantan pontianak valdivia (chile, 2010.02.27) caleta de campos (michoacan, 1997.05.22) kavala (drama, 1985.11.09) palangkaraya daracena (chile, 2015.09.16) santa ana (el salvador, 2001.01.13) lb city hall (northridge-01, 1994.01.17) samarinda daracena (chile, 2015.09.16) caleta de campos (michoacan, 1997.05.22) kavala (drama, 1985.11.09) 4 sulawesi manado narita (honshu, 2011.03.11) santa ana (el salvador, 2001.01.13) desert hot springs (bigbear-01, 1992.06.28) palu el pedragal (chile, 2015.09.16) san miguel (el salvador, 2001.01.13) tolmezzo (friuli, 1976.05.06) makassar valdivia (chile, 2010.02.27) santa ana (el salvador, 2001.01.13) lb city hall (northridge-01, 1994.01.17) 5 papua sorong valdivia (chile, 2010.02.27) san miguel (el salvador, 2001.01.13) tolmezzo (friuli, 1976.05.06) nabire daracena (chile, 2015.09.16) san miguel (el salvador, 2001.01.13) mission creek fault (landers, 1992.06.28) jayapura narita (honshu, 2011.03.11) san miguel (el salvador, 2001.01.13) tolmezzo (friuli, 1976.05.06) 2.6. spectral matching to generate artificial ground motions, the time-history spectra are carefully matched against a predefined target rs model, ensuring accuracy and reliability in representing seismic demands. the target rs is designed for periods ranging from 0.2 to 1.2 seconds, with increments of 0.1 seconds based on the spectral acceleration values (ts). a uniform samax value of 0.01 g is applied across all target rs variations to standardize the spectral matching process. using this approach, a total of 15 target ground motions are selected, resulting in 165 pairs of ground motion data for spectral matching. the rs for the lateral directions (ns, ew, and ud) is combined using the square root sum of squares (srss) method, creating a resultant spectrum (rs_srss) for further analysis. advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 165 (a) response spectrum (b) spectrum scaling (c) scaled response spectrum (d) outcome of spectral matching (e) artificial time history ew (f) artificial time history ns (g) artificial time history ud fig. 10 spectral matching el centro earthquake fig. 10 illustrates the process of spectral matching using the el centro earthquake (elc) time history as an example. in fig. 10(a), the individual response spectra for the ns, ew, and ud components are shown alongside the rs_target and the resultant rs_srss. this comparison highlights how the original spectra align with the target response spectrum. in fig. 10(b), the scale factor is depicted, which is calculated as the ratio of rs_target to rs_srss for each specified period. this scale factor serves as a crucial parameter for adjusting the amplitude of the original spectra. fig. 10(c) presents the scaled response spectrum, obtained by multiplying the original rs by the calculated scale factor. this step ensures that the modified spectrum aligns closely with the rs_target. fig. 10(d) showcases the outcome of the spectral matching process, where the matched time-history spectrum is observed to reproduce the target spectrum’s shape and amplitude accurately. finally, figs. 10(e)-(g) provides a detailed view of the generated artificial ground motions for the ns, ew, and ud directions. 166 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 these plots reveal the time-history signals after spectral matching, demonstrating adjustments in amplitude and frequency content to meet the target rs requirements. collectively, these figures illustrate the comprehensive and iterative approach employed in generating artificial ground motions, ensuring consistency with and adherence to the target seismic characteristics. 3. results and discussion a total of 165 pairs of artificial ground motions are generated through spectral matching and used to calculate the msis values using the jma-sis program. the next step was determining the average msis values for each ground motion model, based on variations in the target rs. these variations depend on different ts values, which represent the period of the seismic event. the results are presented in table a-2 (appendix 2). the msis values listed in table 5 correspond to variations of ts in the target rs with a samax value of 0.01 g. these values are calculated by applying a scaling factor to the artificial ground motion, with the scaling factor ranging from 1 to 250, corresponding to the samax ratio. 3.1. formulation of rs_msis the relationship between samax and msis is shown in fig. 11 to derive an equation relating samax to msis. it is found that the relationship between samax and msis follows a logarithmic pattern, with an r2 value of 1, indicating a strong correlation. this suggests that samax is a reliable predictor of msis values across different seismic conditions. all variations of the rs produced the same pattern, leading to the formulation below max2log( )msis sa a= + (7) fig. 11 relationship between samax and msis eq. (7) is derived by formulating the msis values calculated based on the rs variable and is referred to as ‘rs_msis’. it is observed that this equation closely resembled the general msis formulation in eq. (6), indicating a strong relationship between the samax variables and a0.3. the rs_msis equation exhibits the same pattern across all variations of rs, with the only difference being the coefficient a, which leads to the formulation of the relationship between the ts value and coefficient a. the w values are in accordance with the values presented in table 5. table 5 coefficient a and w values response spectrum ts (sec) ts 0.7 (sec) coefficient a w = (a 5.496) rs_02 0.2 -0.5 4.856 -0.638 rs_03 0.3 -0.4 5.095 -0.399 rs_04 0.4 -0.3 5.222 -0.272 rs_05 0.5 -0.2 5.338 -0.156 rs_06 0.6 -0.1 5.418 -0.077 rs_07 0.7 0.0 5.495 0.000 rs_08 0.8 0.1 5.578 0.084 rs_09 0.9 0.2 5.609 0.115 rs_10 1.0 0.3 5.646 0.151 rs_11 1.1 0.4 5.705 0.211 rs_12 1.2 0.5 5.759 0.264 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 167 meanwhile, the normalization of rs_07 is required to establish the ts-a relationship, as detailed in table 5. it is later found that the graph depicting the relationship between the (ts–0.7) value and coefficient w followed a quadratic equation with an r2 value of 0.990, as shown in fig. 12. this strong correlation further supports the robustness of the derived equations. eq. (7), along with the graph of the relationship between (ts-0.7) and the coefficient w, is used to formulate the rs_msis equation, and can be expressed as max_ 2log( ) 5.495rs msis sa w= + + (8) 20.696( 0.7) 0.812( 0.7)w ts ts= − − + − (9) where rs_msis is msis based on the response spectrum, samax denotes the response spectrum variable (maximum sa), and w refers to the wariyatno coefficient. fig. 12 relationship between (ts-0.7) and coefficient w 3.2. relationship between samax and a0.3 the rs_msis formulation required validation to ensure the reliability of the results. to achieve this, validation data are extracted from the actual response spectrum (rs) according to sni 1726:2019 [24], while ground motion validation data are selected based on indonesia's earthquake de-aggregation map of. these datasets are used to generate artificial ground motions, and msis values are calculated using both the jma-sis program and the rs_msis equation. the results from the jma-sis program and the rs_msis equation are compared, as shown in table a-3 (appendix 3). it is found that the deviation between the two methods is minimal, with an average deviation of 1.024% and a maximum deviation of 2.372%. these findings confirm that the rs_msis equation can reliably predict msis based on rs. furthermore, eq. (10) closely resembles eq. (6), which is used to establish the relationship between samax and a0.3 as follows: 2.278 0.3 2 max 10 w a sa + = (10) where a0.3 is jma-sis acceleration vector accumulated over 0.3 seconds, expressed in gal (1 gal = 1 cm/s2). 3.3. implementation of quantitative sis fig. 13 illustrates the quantitative determination scheme of the sis for a residential building. once the building passes the seismic design phase, the next step is to assess the level of shaking it will experience. the rs selected during the design phase is used to generate the seismic wave for the construction site, taking into account both the soil conditions and the building’s dynamic characteristics. a time-history analysis is then performed, using seismic waves as the input ground motion. the results of the time-history analysis are used to evaluate the accelerations at various floors of the building. the fft method is applied to these accelerations to identify the dominant period of each floor and the peak response acceleration. these predominant periods and peak accelerations are plotted on the jma-sis scale to determine the shaking levels for each floor. 168 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 if any floor exceeds the permissible sis threshold, the building design must be revised to address this issue. the permissible seismic intensity level, which is critical for reducing human casualties during significant earthquakes, should be defined in seismic design codes to ensure safety. fig. 13 quantitative sis implementation [12] 4. conclusions this study presents a novel and reliable approach for calculating earthquake shaking intensity (msis) through the response spectrum-based index (rs_msis), using the jma-sis as a benchmark. by identifying maximum spectral acceleration (samax) and the associated period (ts) as key parameters, the research successfully formulated rs_msis as a logarithmic function of samax. the strong alignment of this formulation with the jma-sis equation confirms its theoretical validity and strengthens the central argument that response spectrum data can be effectively utilized to estimate seismic intensity with high accuracy. the model’s robustness was verified using ground motion data from 15 cities in indonesia, where the rs_msis yielded highly consistent and dependable predictions. a notable contribution of this study is the revealed correlation between a0.3 and samax under spectrally matched ground motions, emphasizing the sensitivity of the rs_msis model to realistic seismic input conditions. these insights contribute to a deeper understanding of ground motion characteristics and their impact on seismic intensity measures. beyond methodological advancement, the findings align with the broader objective of strengthening seismic resilience in earthquake-prone regions. by introducing a standardized and accurate tool for estimating ground shaking, the rs_msis model facilitates safer structural design, informed urban planning, and improved zoning and building regulations. ultimately, this study contributes to both technical progress and the societal goal of reducing earthquake risks through science-based preparedness and policy. 5. future recommendation it should be noted that this study does not include specific case studies, which may limit the direct applicability of the model to unique urban environments. while the methodology presented can be applied to cities with varying seismic activity, such as those in indonesia, as demonstrated by the rs validation data, further case-specific studies are needed to fully assess the model's effectiveness in different regions with varying geotechnical and structural conditions. acknowledgments the authors gratefully acknowledge the financial assistance provided by the institute for research and community service (lppm), universitas jenderal soedirman (unsoed), indonesia (27.114/un23.37/pt.01.03/ii/2023). this research was also partially supported by universitas diponegoro (undip), indonesia, through the world class university program (1161/un7.a4/ku/x/2023). advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 169 conflicts of interest the authors declare no conflict of interest. references [1] j. bustos, c. pastén, d. pavez, m. acevedo, s. ruiz, and r. astroza, “two-dimensional simulation of the seismic response of the santiago basin, chile,” soil dynamics and earthquake engineering, vol. 164, article no. 107569, 2023. 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[29] “center for engineering strong motion data,” https://www.strongmotioncenter.org/, accessed on 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://www.strongmotioncenter.org/ advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 171 appendix 1 fig. a-1 illustration of events during an earthquake based on jma-sis [9] 172 advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 appendix 2 table a-2 calculation results of msis based on the ground motion model no. ground motion jma-sis rs-02-01 rs-03-01 rs-04-01 rs-05-01 rs-06-01 rs-07-01 rs-08-01 rs-09-01 rs-10-01 rs-11-01 rs-12-01 1. tac 0.785 1.100 1.242 1.334 1.396 1.392 1.490 1.536 1.613 1.616 1.633 2. ike 0.850 1.058 1.211 1.334 1.441 1.487 1.653 1.589 1.638 1.639 1.800 3. san 0.871 1.093 1.227 1.382 1.356 1.495 1.535 1.597 1.604 1.722 1.814 4. lau 0.861 1.026 1.148 1.283 1.341 1.441 1.609 1.698 1.619 1.596 1.720 5. shi 0.928 1.208 1.249 1.378 1.499 1.606 1.605 1.643 1.736 1.786 1.772 6. toy 0.825 1.077 1.303 1.271 1.369 1.440 1.514 1.558 1.627 1.717 1.694 7. elc 0.944 1.146 1.201 1.288 1.378 1.493 1.548 1.618 1.578 1.713 1.689 8. con-v 0.859 1.080 1.215 1.402 1.507 1.603 1.757 1.718 1.546 1.918 1.992 9. kar 0.888 1.115 1.221 1.349 1.492 1.512 1.680 1.635 1.798 1.680 1.685 10. cas-a 0.864 1.100 1.166 1.262 1.294 1.412 1.392 1.535 1.479 1.539 1.581 11. cas 0.849 1.085 1.238 1.414 1.550 1.612 1.713 1.705 1.871 1.863 1.857 12. sma 0.752 1.053 1.245 1.362 1.390 1.443 1.442 1.483 1.640 1.676 1.869 average 0.856 1.024 1.222 1.338 1.418 1.495 1.578 1.609 1.646 1.705 1.759 note: the naming convention for the response spectrum is rs-ts-samax. rs 02: response spectrum with ts = 0.2 sec advances in technology innovation, vol. 10, no. 2, 2025, pp. 157-173 173 appendix 3 table a-3 validation results of rs_msis equation island city soil type variable of rs jma_msis rs_msis deviasi (%) ts samax megathrust benioff shallow crustal /background average sumatera medan sc 0.67 0.810 5.237 5.307 5.147 5.231 5.287 1.078% padang se 1.05 1.125 5.760 5.585 5.862 5.736 5.796 1.057% palembang sd 1.13 0.465 4.945 5.017 4.903 4.955 5.050 1.931% jawa jakarta sc 0.60 0.945 5.254 5.293 5.387 5.311 5.358 0.876% yogyakarta se 0.99 1.125 5.728 5.545 5.648 5.640 5.774 2.372% surabaya sd 0.72 0.855 5.303 5.404 5.358 5.355 5.375 0.372% kalimantan pontianak sc 0.33 0.225 3.806 3.760 3.818 3.795 3.804 0.237% palangkaraya se 1.38 0.120 3.905 3.944 3.841 3.897 3.884 0.329% samarinda sd 1.15 0.195 4.198 4.232 4.318 4.249 4.300 1.180% sulawesi manado sc 0.55 1.245 5.550 5.513 5.574 5.546 5.548 0.034% palu se 1.00 1.200 5.704 5.705 5.723 5.711 5.834 2.168% makasar sd 0.71 0.360 4.576 4.696 4.529 4.600 4.616 0.335% papua sorong sc 0.48 1.920 5.823 5.914 5.726 5.821 5.849 0.487% nabire se 1.00 1.200 5.671 5.790 5.737 5.733 5.834 1.770% jayapura sd 0.70 1.500 5.799 5.786 5.758 5.781 5.847 1.140% average 1.024% maximum 2.372% 5___aiti#8714__56-65 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 effects of the vibration amplitude in vibratory stress relief on the fatigue life of structures cuong bui manh 1,* , duong nguyen van 2 , si do van 1 , manh phan van 1 , van thao le 3 1 department of engineering mechanics, le quy don technical university, hanoi, vietnam 2 department of materials science and engineering, le quy don technical university, hanoi, vietnam 3 advanced technology center, le quy don technical university, hanoi, vietnam received 16 october 2021; received in revised form 08 december 2021; accepted 09 december 2021 doi: https://doi.org/10.46604/aiti.2021.8714 abstract this research aims to investigate the effects of vibration amplitude in vibratory stress relief (vsr) on the fatigue strength of structures with residual stress. experiments are carried out on specimens with residual stress generated by local heating. flat specimens made of a36 steel are prepared to be suitable for setting up fatigue bending tests on a vibrating table. several groups of samples are subjected to vsr at resonant frequencies with different acceleration amplitudes. the results show that vsr has an important influence on the residual stress and fatigue limit of steel specimens. the maximum residual stress in the samples is reduced about 73% when the amplitude of vibration acceleration is 57 m/s 2 . the vsr method can also improve the fatigue limit by up to 14% for steel samples with residual stress. keywords: vibratory stress relief (vsr), residual stress, fatigue life, fatigue limit, vibration amplitude 1. introduction residual stress is the internal stress existing between parts of workpieces in the absence of external loads. this stress is generated when the workpieces experience inhomogeneous deformation, e.g., heating, cooling, and plastic deformation [1-2]. many technological processes, such as welding, quenching, and metal forming, can produce residual stress. residual stress often leads to the loss in the geometry accuracy of workpieces after machining, and causes the degradation of corrosion resistance in various environments [3]. residual stress also has effects on the mechanical properties of materials and therefore on the load-bearing capacity and life service of components. especially, the tensile residual stress which usually appears in welding has negative effects on the fatigue limit and fatigue life of workpieces [4-5]. relieving residual stress is one of the major concerns in mechanical engineering processes. there are many relieving methods implemented in manufacturing: annealing, local heating, monotonic overloading, shot pinning, vibratory stress relief (vsr), etc. among the mechanical methods for relieving residual stress, vsr is considered an effective, flexible, inexpensive, and eco-friendly solution [6-8]. in vsr, cyclic external loads are applied to the workpieces with residual stress for a certain length of time, and this process is believed to cause microplastic deformation in micro regions of the workpieces and lead to the relaxation of residual stress [8-9]. this technology has been successfully implemented in the manufacturing of many important workpieces, such as welded shafts, marine shafts, large rails, large surface plates from stainless steel, and thin parts from aluminum alloy [10-13]. there have been lots of publications investigating the vsr effects on the residual stress state and the mechanical properties of specimens [7-8, 12, 14-16]. however, the research examining the vsr effects on the fatigue characteristics of workpieces is still limited. fang et al. [17] demonstrated that the fatigue life of welding steel samples could be improved up to * corresponding author. e-mail address: buimanhcuongkck@lqdtu.edu.vn advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 25% by using vsr. munsi et al. [18] also carried out a study on vsr for welded steel bars at non-resonant frequency with two load levels for a short interval of time, only 5 s. they found that applying vsr at high loads and a small number of cycles could reduce the residual stress and increase the fatigue life of structures up to 17%. meanwhile, the thermal method could reduce the residual stress and reduce the fatigue life of structures up to 43%. djuric et al. [19] studied the vsr effects on the properties of martensitic steel, and found an increase of fatigue damage due to the applied vsr treatment. in the work of gao et al. [20], the fatigue characteristics of ti-6al-4v titanium alloys were determined after vsr at different vibration amplitudes. the fatigue limit of samples was found to be slightly reduced with the increasing vsr amplitude (several percent to 10%) while the residual stress could also be reduced up to 60%. song and zhang [21] applied vsr for 7075-t651 aluminum alloy, and found that the fatigue life of specimens could be enhanced to 6.3% with the help of vsr. gao et al. [22] also conducted vsr for 7075-t651 aluminum alloy, and concluded that low amplitude vsr could reduce the residual stress and improve the fatigue life of 7075-t651 aluminum alloy. in this study, vsr is conducted on specimens of astm a36 steel, which is a popular material for weld structures. the residual stress is created by local heating, which is similar to the welding process and different from the pre-strain method in recent literature [19, 21-22]. fatigue bending tests are conducted on a vibrating table with flat specimens, and the fatigue limit is determined by an improved staircase method. herein, this study focuses on the effects of vsr amplitude on the fatigue properties of a36 steel with residual stress, demonstrating the vsr ability of reducing the residual stress and improving the fatigue limit. 2. materials and experimental methods 2.1. test specimens in this work, fifty-five identical flat test specimens, which are designed according to astm e466 for bending fatigue tests, are extracted from a large carbon steel panel (fig. 1). the specimens’ thickness is 6 mm. the end part of each specimen is with a threaded hole m5 (fig. 1(a)) to attach additional weight, which creates an addition flat bending load and increases the stress at the a-a cross-section during the vibration test. tables 1 and 2 present the mechanical properties (e.g., density, modulus, and yield strength (ys)) and the chemical compositions of the carbon steel specimens. (a) geometry and dimensions of specimens (b) fabricated specimens fig. 1 design and preparation of specimens table 1 mechanical properties of low carbon steel density (kg/m 3 ) modulus of elasticity (gpa) poisson’s ratio yield strength (mpa) ultimate tensile strength (mpa) 7850 200 0.3 296 440 57 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 table 2 chemical compositions of specimens element c si mn p s cr mo ni al wt. % 0.1452 0.0087 0.4483 0.0139 0.0028 0.0054 0.0030 0.0091 0.0723 element co cu ti v nb w pb fe wt. % 0.0080 0.0118 < 0.0010 < 0.0020 0.0041 0.0470 < 0.0100 99.183 2.2. generation of the residual and dynamic stress in specimens first, for each steel specimen, high residual stress is induced by spot heating in the transition zone (fig. 2(a)). the displacement velocity of the heat source and the heating time are controlled so that the temperature at the center of the heating zone is around 1000°c. the heat source is moved along line a-a (fig. 1(a)) at a speed of 2 mm/s. after the local heating, each sample is rapidly cooled to room temperature by quickly putting it into a water tank. to monitor the dynamic strain and stress, an hbm strain gage (type 1-lm11-3/350ge) is bonded onto the middle of line a-a. the strain gauge is attached to the surface of specimens in the region of interest (roi) (fig. 2(b)). the dynamic stress is generated and controlled by varying the exciting acceleration amplitude and maintaining the constant frequency of a shaker. therefore, it is necessary to survey the relationship between the exciting acceleration amplitude of the samples and the dynamic stress generated at the cross-section (a-a) before conducting vsr and fatigue tests. an lds electrodynamic shaker (model v830-335t) with an lds laser usb vibration controller (model las200, s/n 10870124) is used for generating the vibration of the samples. an lms noise and vibration test system (lms scadas mobile system) is used for signal acquisition, monitoring the displacement at the end of the samples and the dynamic strain in roi, as shown in fig. 3(a). (a) location of local heating to create residual stress (b) strain gauge attachment on a specimen fig. 2 generating residual stress and attaching a strain gage to monitor the dynamic strain and stress (a) the lms noise and vibration test system and the experimental setup (b) natural frequency of a sample with residual stress fig. 3 experiment for monitoring the displacement and the dynamic strain in roi 58 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 the data acquired by the lms scadas mobile system enables studying and establishing the relationship of the exciting frequency and acceleration amplitude with the dynamic strain and stress. the sine vibration experiment is set at 30 m/s 2 with a frequency range from 260 to 300 hz. a sweep rate is set at 0.25 oct/min to exactly determine the resonance frequency of test specimens. the specimens are heated locally to generate the residual stress. the transmissibility function is used for the resonance search, and is computed based on the ratio of the dynamic strain and exciting acceleration, as shown in fig. 3(b). fig. 3(b) shows that the resonant frequency of the test specimens with residual stress is about 283.59 hz. after the controller finds the resonant frequencies in the sweep range, the sine dwell tests are performed. the controller runs a single sine tone at the resonant frequency instead of sweeping through the frequency range, with the acceleration amplitudes of 60 m/s 2 , 90 m/s 2 , 120 m/s 2 , 150 m/s 2 , and 180 m/s 2 , respectively. subsequently, the dynamic stress is calculated from the dynamic strain by hook’s law, as shown in eq. (1). σ = e × ε (1) where σ is the stress (n/m 2 ), ε is the strain (m/m), and e is the modulus of elasticity (n/m 2 ). 2.3. vsr tests vsr tests are conducted on the lds electrodynamic shaker in a scheme like the one in dynamic stress tests. 56 specimens are randomly selected and divided into 7 groups denoted by a, b, c, d, e, f, and g. each group consists of 8 test specimens. three test specimens in group a are randomly selected to measure the residual stress before vsr, and the remaining five samples of group a are used for determining the fatigue limit. the vsr processes are conducted for the specimens in 6 groups (b, c, d, e, f, and g) using the lds electrodynamic shaker with the acceleration amplitudes of 29 m/s 2 , 43 m/s 2 , 57 m/s 2 , 71 m/s 2 , 99 m/s 2 , and 156 m/s 2 , respectively. each sample in these 6 groups is stimulated by the shaker within 10 minutes. the exciting frequency is set at 283.59 hz according to the resonant frequency of the test specimens. after the vsr processes, three samples in each group (b, c, d, e, f, and g) are randomly selected to measure and check the residual stress, and the remaining five test specimens are used for determining the fatigue limit. the diagram of using different test specimen groups is shown in fig. 4. 56 test samples group a: without conducting vsr, 3 of 8 test samples in the group are used for measuring the residual stress. group b: vsr is conducted with the exciting acceleration amplitude of 29 m/s2. group c: vsr is conducted with the exciting acceleration amplitude of 43 m/s2. group d: vsr is conducted with the exciting acceleration amplitude of 57 m/s2. group e: vsr is conducted with the exciting acceleration amplitude of 71 m/s2. group f: vsr is conducted with the exciting acceleration amplitude of 99 m/s2. group g: vsr is conducted with the exciting acceleration amplitude of 156 m/s2. each group contains 8 test samples. after vsr, 3 of 8 test samples in each group are used for measuring the residual stress. the other 5 samples are used for determining the fatigue limit. fig. 4 diagram of different specimen groups 59 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 2.4. measuring residual stress three test specimens of group a are used for measuring the residual stress; the measured value is considered the residual stress before vsr. for the other 6 groups (b, c, d, e, f, and g), after vsr is conducted, three samples are randomly chosen from each group for the measurement of residual stress. the residual stress on the samples before and after vsr is then compared to each other to assess the ability of reducing the residual stress in different loading modes. the measurement of residual stress is performed according to astm e837-13a [23], using a rs200 system (vishay group, usa) and an ea-06-062re-120 strain gauge rosette. fig. 5 shows the residual stress measuring system marked rs200. when measuring the residual stress, the electrical resistance-strain gauge rosettes are attached to the surface of specimens in the same position as in the measurement of dynamic strains (fig. 3(b)). the residual stress on the surface layer is determined by astm e837-13a, as described in the work of gao et al. [16]. fig. 5 specimens and the residual stress measuring system marked rs200 2.5. fatigue test the fatigue tests with a flat bending load are also conducted on the lds electrodynamic shaker, as shown in fig. 6. in each group, 5 test samples are used to determine the fatigue limit. the fatigue test parameters are as follows: the frequency of fatigue vibration test at the resonance frequency of samples is 283.59 hz, the stress ratio is -1, the ambient temperature is 27°c, and the humidity is 60%. the fatigue limit can be determined by using the staircase method [24-25] (fig. 7). the test is performed for the first specimen at a stress level around the fatigue limit. if the result of the above test is “non-fracture”, the second specimen is tested at the stress level with an increment of d. on the other hand, if the result is “fracture”, the second specimen is tested at the stress level with a decrement of d. the fatigue test is repeated until a given number of specimens is used, then the fatigue limit is calculated. this fatigue test method has been widely accepted to examine the fatigue limit of metals. there were also some modified staircase procedures to reduce the number of test specimens and hence lower the cost and running time of this test [26-27]. fig. 6 a specimen and strain gauge in the fatigue test on the lds electrodynamic shaker 60 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 in this study, a modified staircase method proposed by international council for combustion engines is implemented for bending fatigue tests with a limited number of specimens [28]. herein, the first specimen is subjected to a stress level that is most likely well below the average fatigue strength. when this specimen survives 5 × 106 cycles, this same specimen is subjected to a stress level one increment above the previous. this is continued with the same specimen until failure. then, the number of cycles is recorded, and the next specimen is subjected to a stress that is at least 2 increments below the level where the previous specimen fails. the first stress amplitude level is determined, depending on the tensile strength of the material and according to the following empirical expression [29]: σ1 = 0.68 × (0.55 − 0.0001 × σu) × σu (2) where σu is the material tensile strength. when σu = 440 mpa, the first stress amplitude level σ1 is about 152 mpa. the next stress level applied on a specimen is determined by the results obtained in the preceding test. if the preceding specimen, i, fails at the level σi, the next stress level will be σi + 1 = σi – 2d. if the preceding specimen is not broken, σi + 1 = σi + d, where d is a predefined difference in applied stress levels. in this study, d is determined as d = 0.068 × σ1 ≈ 10.4 mpa. the fatigue testing results of five samples in group c is illustrated in fig. 8. there are 5 specimens that undergo the bending tests. the first specimen is broken in the third test at a stress level of σ2. therefore, the second specimen is firstly tested at a stress level σ0 = σ3 − 2d, and then it is tested at elevated stress levels until it is broken at the fourth test with a stress level of σ3. subsequently, the third specimen is tested, and the tests are repeated until the fifth specimen is broken. based on the test results as shown in fig. 8, the fatigue limit is calculated by eq. (2) [24]: 0 1 2 r a d f = + ±      σ σ (3) where σ0 is the lowest stress level (i = 0) in which the less frequent event run-out appears; f and a are the parameters calculated by eqs. (4) and (5). f i=∑ (4) ia f= ∑ (5) where i is the number of stress levels, and fi is the number of run-outs obtained at the stress level i. determining the load amplitude fatigue test samples are broken or not at the load circle 5 × 106 decreasing the stress amplitude by 2d = 20.8 mpa determining the fatigue limit of sample groups yes no if all 5 samples are tested increasing the stress amplitude by d = 10.4 mpa start fig. 7 diagram illustrating the process of determining the fatigue limit 61 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 fig. 8 log sheet of a modified staircase test 3. results and discussion 3.1. dynamic stress the correlation between the exciting acceleration amplitude and the strain amplitude on the surface of test specimens in roi is shown in fig. 9. with each case of the exciting acceleration amplitude, there is a corresponding graph that shows the change of strain over time. it can be seen that, in the sweep sine mode, the largest strain response is achieved when the exciting frequency of the lds shaker coincides with the natural frequency of the samples. fig. 10 shows the dynamic stress at different exciting acceleration amplitudes. this dynamic stress-vibration acceleration correlation can be approximately estimated by eq. (6): σ = 2.1049 × a + 47.953 (6) where a is the amplitude of vibration acceleration (m/s 2 ); σ is the principal stress on the surface of test specimens in roi (mpa). it is revealed that the dynamic stress linearly increases with the amplitude of vibration acceleration. fig. 9 correlation between strain and amplitude of vibration acceleration fig. 10 dependence of stress on exciting acceleration 3.2. residual stress and fatigue limit the results of measuring residual stress according to astm e837-13a include a variety of stress components. to compare and match with the results of dynamic stress measurement, the residual stress components will be chosen as the first principal stress. the residual stress of the samples after vsr is shown in fig. 11. it is noted that the samples without vsr are considered the ones with the vibration amplitude of zero. it is clear that the residual stress will be reduced when the amplitude of exciting acceleration increases. according to the graph, the residual stress in the samples without using vsr is 216 mpa. in all the cases using vsr, the residual stress is reduced by more than 36%. in particular, the maximum residual stress reduction can be attained by up to 73% when the 62 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 vibration amplitude reaches 57 m/s 2 . this is corresponding to the total stress exceeding 30% of the ys of the material. in contrast, when the amplitude of vibration acceleration exceeds 57 m/s 2 , the residual stress will increase as the vibration amplitude increases. this may be explained by the intensive deformation of the samples. the process of determining the fatigue limit of sample groups is conducted according to the modified staircase method and is shown in fig. 7. the experimental data is processed, and the final results of the fatigue limit are given in fig. 12. the experimental results of the fatigue limit demonstrate that the fatigue limit of samples is generally increased with the vsr treatment. the fatigue limit of test specimens increases as the vibration acceleration amplitude increases from 0 to 57 m/s 2 , and it reaches a peak of 14% when the vibratory exciting acceleration amplitude is 57 m/s 2 . after that, if the vibratory exciting acceleration amplitude continues increasing, the fatigue limit will gradually decrease. the result is in good agreement with the studies on tensile fatigue characteristics after vsr [19, 21]. it is obvious from the tests that, if the amplitude of the vibration acceleration is very high, the fatigue limit of specimens will be decreased to the value even lower than the value of the samples without vsr. in general, if the vibration amplitude in vsr is too high or the vsr time is too long, micro voids will be formed and specimens’ fatigue limit will be lowered. fig. 11 residual stress in post-vibrating samples with different vibration acceleration amplitudes fig. 12 fatigue limit of sample groups according to vibration acceleration amplitudes 4. conclusions in this study, the vsr effects on the residual stress and fatigue limit of samples are investigated. the key findings of this research are described as follows: (1) the dynamic stress generated through vsr has a linear relationship with the amplitude of vibratory exciting acceleration. at the amplitude of vibratory exciting acceleration lower than 57 m/s 2 , the residual stress is reduced with the increase in the amplitude of vibratory exciting acceleration. the maximum principal residual stress is reduced about 73% when the amplitude of vibratory exciting acceleration is equal to 57 m/s 2 . as the amplitude of vibratory exciting acceleration exceeds 57 m/s 2 , the residual stress will increase. however, it is generally still lower than those in the cases without using vsr. (2) vsr also has an effect on the fatigue limit of the samples made from low-carbon steel with residual stress. vsr can improve the fatigue limit by up to 14% for the samples under residual stress. however, if the vibrating samples are with very high amplitude of acceleration, their fatigue limit will be reduced to the values that are lower than those without vsr. (3) when the vibrating test samples are with moderate acceleration amplitude, vsr is able to both reduce the residual stress and increase the fatigue limit. if the amplitude of vibration acceleration is very high, this effect will be possibly reversed. the residual stress will be improved less, and the fatigue limit can be lower than the cases without vsr. 63 advances in technology innovation, vol. 7, no. 1, 2022, pp. 56-65 symbols and abbreviated terms symbol unit definition vsr vibratory stress relief ys mpa yield strength σ mpa stress ε m/m strain e mpa modulus of elasticity σu mpa material tensile strength σ1 mpa the first stress amplitude level σi mpa the i th stress level σ0 mpa the lowest stress level (i = 0) σr mpa fatigue limit d mpa predefined difference in applied stress levels a m/s 2 amplitude of vibration acceleration conflicts of interest the authors declare no conflict of interest. references [1] j. s. robinson, m. s. hossain, and c. e. truman, “residual stresses in the aluminum alloy 2014a subject to pag quenching and vibratory stress relief,” the journal of strain analysis for engineering design, in press. 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(in russian) copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 65  advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 maritime computing transportation, environment, and development: trends of data visualization and computational methodologies thanapong chaichana* college of maritime studies and management, chiang mai university, samut sakhon, thailand school of mechanical, aerospace and automotive engineering, coventry university, coventry, united kingdom received 01 july 2022; received in revised form 21 october 2022; accepted 25 october 2022 doi: https://doi.org/10.46604/aiti.2023.10419 abstract this research aims to characterize the field of maritime computing (mc) transportation, environment, and development. it is the first report to discover how mc domain configurations support management technologies. an aspect of this research is the creation of drivers of ocean-based businesses. systematic search and meta-analysis are employed to classify and define the mc domain. mc developments were first identified in the 1990s, representing maritime development for designing sailboats, submarines, and ship hydrodynamics. the maritime environment is simulated to predict emission reductions, coastal waste particles, renewable energy, and engineer robots to observe the ocean ecosystem. maritime transportation focuses on optimizing ship speed, maneuvering ships, and using liquefied natural gas and submarine pipelines. data trends with machine learning can be obtained by collecting a big data of similar computational results for implementing artificial intelligence strategies. research findings show that modeling is an essential skill set in the 21st century. keywords: maritime computing, management technology, modeling 1. introduction maritime computing (mc) is an interdisciplinary field comprising economics, geography, transportation, logistics, mechanics, computer science, engineering, and technology [1-3]. it is the application of computing techniques to maritime engineering (me). computing techniques are the implemented techniques in computers to solve problems by either step-wise, repeated, or iterative solution methods; also known as in-silico methods. among these techniques, computational fluid dynamics (cfd) and machine learning (ml) are some of the most widely used techniques. cfd is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems; its concept is to model the problem using geometric approaches to produce visual results [4-7]. ml is a branch of computer science that uses data and algorithms to mimic the way humans learn; its concept is to develop computers to learn from data and then perform learning [8-11]. me is referred to the word ocean engineering in certain academic and professional circles as the field of study dealing with the engineering of boats, ships, submarines, and any other marine vessels, as well as other ocean systems and structures. mc will focus on transportation, environment, and development in the me field. mc transportation is the study of the changes and movement of objects in the sea. mc environment is the study of oceanic issues and environmental simulations. mc development is the study of geometrical simulations and ocean-shaped designs linked to the sea. * corresponding author. e-mail address: thanapong@wavertree.org tel.: +666-5-6728999 advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 39 this study is organized as follows. section 2 describes the proposed method, especially presenting research concepts of literature data describing data. section 3 illustrates the results obtained from the algorithmic search. section 4 discusses how the findings will improve future ocean-based businesses. finally, the last section concludes that mc is important in maritime society to accomplish development goals. 2. literature review instead of being an engineer, mc is more like the computationalist and the socialist which uses computers and technology to assist ocean-based businesses at the microscale and macroscale. mc involves a business process management system. currently, several crucial maritime studies employ computation and technology. fig. 1 shows the images of mc and indicates that the relationships between skill sets are mutually linked. the design of numerous ocean-based business processes consists of transportation, logistics, trade, food, environment, data, simulation, and modeling. transportation, logistics, and computing automation were the core of the maritime business proposed by the world maritime university [12]. similarly, bioeconomy involves the conversion of agricultural, organic, and marine resources into materials, energy, fuels, feed, and foods [13-14]. (a) basic guidance of mc (b) relationship of mc domains (c) conceptual mc domain fig. 1 the field of maritime computing (mc) mc helps bioeconomy to develop in all aspects. thus, it can provide technological benefits and systems for economic science and bioeconomy [15-16]. economic science, a smaller area of economics, involves rigorous thinking and mathematical applications. unlike the political economy, economic science focuses on the production, distribution, and consumption of goods and services [16]. mc supports economic science through a significant aspect of its modeling skill set as shown in fig. 1(a). it also supports sustainable economic development involved in price fluctuation, banking characteristics, and social development [17-19]. computing is used to translate information, ideas, and practical and mathematical modeling data into digital data. however, visualization techniques are required to determine computational results and process digital data to interpret and verify the outcomes of these results such that they are applicable in real-world conditions [20-21]. mathematical modeling alone is inadequate for explaining the computational consequences [20, 22-24]. a computational research of fluids is noteworthy because fluids are present everywhere and are found in numerous computing applications. therefore, cfd is a preferred concept for ocean-based businesses to classify maritime visualizations and computational methodologies. cfd is an interpreter that provides computational outcomes in terms of data visualizations, including data plots, streamlines, vector changes, contour areas, shading colors, and user-programmable animations [24-26]. advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 40 in addition, cfd generates computational results, and these data depend on a study design to solve a specific problem statement. later, visualization methodologies were applied to translate these computational results into graphs, images, and/or animations for understanding the solutions. ml enables computer systems to learn from input data to automatically predict solutions. in this context, the concept of ml and cfds are possible to build big data of similar study designs as input data for ml to predict the computational outcome. the use of computing data involves data collection, which is adequate for forecasting the next state of data-driven applications [27]. massive data collection and automation are usually accomplished through ml. ml can be used to complete routine tasks, simulate virtual contexts, and reduce physical work and manual labor. in the intelligent societies of the 21st century, computing technology has advanced physical labor by inputting human ideas and data into a computer domain. these inputs are then translated into digital data that machines or computers can be used to perform human tasks [28-30]. however, no systematic studies have focused on mc classification. cfd is a key concept in ocean-based businesses that examines maritime visualization and the computational methodologies dedicated to mc transportation, environment, and modeling. the main objective of the present research is to investigate the trends in computer technology and data applications used in mc during the past five decades to help drive and expand ocean studies and support essential skill sets in the 21st century. 3. proposed method mc is generally defined as the analysis of collected material. in this study, a literature review of maritime studies was performed by the preferred reporting items for systematic reviews and meta-analysis (prisma) guidelines [31-32]. a comprehensive electronic search of the literature was conducted using the following databases: sciencedirect, scopus, the iet digital library, ieee-xplore, springer link, web of science, and google scholar. the keywords used to perform the search were mainly included in the form of [cfd+(marine_or_maritime)] [33]. hence, this keyword was preferred. fig. 2 protocol representing research concepts of literature data describing data maritime studies were searched from the 1960s to 2022 in the aforementioned databases and were eligible for inclusion in the present research. articles were included if they were peer-reviewed and published in english. the titles of the articles were analyzed using the and operator in the basic search engine to ensure that the studies met the eligibility criteria before inclusion. in addition, the abstracts of articles were analyzed to determine if the study conditions accurately reflected our study aim and title. the introduction section of each article was scanned for critical thinking. conference abstracts, review articles, advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 41 editorial notes, short articles, and other article types were excluded according to the study criteria. finally, full-text original research papers were included to perform the mc classification. fig. 2 shows a pictorial representation of the article included in this study. computer technology advancements began on a massive scale in the past two decades because of the affordable cost of electronics production, the large-scale design of microelectronics, the availability of computer programs and graphic processing unit (gpu) technology, digital literacy, and computing skills [34]. thus, few computational applications in maritime studies would have been available during the 20th century. the three significant key areas found in maritime literature are transportation, environment, and development research. accordingly, keywords, namely “transport,” “environment,” and “modeling,” were used to search for information, along with the aforementioned main keywords (maritime and cfd). these sets of keywords were used to obtain adequate and accurate information to categorize search results into the following phases: the current situation, the prediction of the future situation, and the definition of mc and its basic skillset. 3.1. data classification and critical evaluation strategies the data were collected according to the inclusion criteria described in the previous subsection. the last search was completed on october 02, 2022. each article was manually assessed. an independent assessor (thanapong chaichana) classified and tabulated the data in a microsoft excel spreadsheet for analysis. the data observer (thanapong chaichana) verified the search results of the original mc research, strictly focusing on the algorithmic search for analysis and review. the following characteristics of maritime studies were classified: authorship, year of publication, area of mc research, study design, study purpose, key findings, algorithmic software usage, maritime big-data possibility, artificial intelligence (ai) feasibility, and future direction of research. 3.2. data validation and double-check of results after the search was completed, a double-check procedure was performed to verify the results. first, the presence of both keywords (cfd and marine/maritime) in the titles of maritime articles was confirmed. alternatively, the presence of these keywords was determined in the abstract or introduction section. second, the key areas of mc were classified. the key research areas and keywords used for classification were transport, environment, and modeling. subsequently, all the maritime studies were thoroughly read to ensure that they represented the actual research context in the field of mc. finally, the original research articles were thoroughly evaluated to exclude studies with the same group of authors, the same series of publications, duplicate and similar studies, and articles irrelevant to maritime modeling, environment, and transport research. accordingly, the entire inclusion process, shown in fig. 2, was successfully implemented. 4. results 4.1. search outcome of the maritime literature the electronic search yielded 2,179 articles. after applying the search criteria to screen full-text original research articles, 92 of the 2,179 articles were found to be eligible. these articles were then evaluated to determine whether they focused on three research areas: transportation, environment, and development. a total of 62 articles met the criteria and were reviewed; of these 62 articles, 8 were excluded because they were an extension of conference papers (3 articles), focused on aerospace research (1 article), or had the same name as the first author (4 articles). finally, 54 articles met the research criteria and were included in this meta-analysis. fig. 3 shows the characteristics and key research areas of the 54 articles. there are 14 and 15 articles focused on maritime transportation and the environment, respectively. the remaining 25 articles focused on maritime development. the results advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 42 obtained from the algorithmic search offered unique information and more accurate search results when these results are compared to previous studies [31, 35-37]. moreover, a bibliometric search algorithm implemented using scientometric software (e.g., bibexcel [38] or citespace [39]) may reduce the time consumption. however, an accurate search result depends on keywords, boolean conditions, and searching protocol (fig. 2 offered a newly accurate scientometric algorithm). fig. 3 studies focusing on mc transportation, environment, and development 4.2. maritime computing (mc) fig. 4 data trends of mc methodologies, invention of computers, and computational techniques advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 43 in the mc research field, interesting findings were observed in the areas of transportation, environment, and development. fig. 4 shows an mc chart with details of its development and data reported over the past five decades. in the current decade, computational results visualized using three-dimensional (3d) and multidimensional computing domains have been reported as normal methodologies for mc. in contrast, in the 1970s and 1980s, mc began with one-dimensional (1d) or two-dimensional (2d) mathematical models, drawings, and domain geometries. technological advancements have led to the visualization and implementation of real-world mc practices. 4.3. mc transportation mc transportation was developed to research the changes and movement of objects in the sea. table 1 presents the categorization of mc transportation. the study design began by simulating the ship speeds. subsequently, a ship maneuvering simulation was performed. liquefied natural gas (lng) is widely used in maritime transportation systems. studies have used lng fuel in transport to model computer-generated lng spills and dispersion processes above the sea surface. studies have also focused on the fuel efficiency and hazard issues of lng. submarine pipelines are used for transporting objects, and they cause damage to submarine landslides and the seabed. commercial software is commonly used for creating algorithms, computations, and simulations as an instant programming tool to perform data visualization, data analysis, and computational methodologies. the computational results of ship simulations could be collected as a maritime databank to form big data, which can be used in the future to plan the ml strategy leading to ai execution. table 1 characteristics of mc transportation study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction simulation of 3d flow of maritime lng control valves [40] determine the advanced design of maritime lng control valves with high pressure drop good agreement of computational results with conventional control valves, improvement of flow pattern, reduction of cavitation, and prediction of performance commercial cfd-ace+ n/a n/a n/a simulation of submarine pipelines to examine the interaction of ocean transports with submarine landsides [41] predict submarine pipelines imposed by submarine landslides, a comparison of different shapes (wedge, airfoil, double-ellipse, and arc-angle hexagon) and conventional circular shape revealing the disadvantages of conventional circular pipelines in terms of lift force and drag force when interacting with submarine landsides, a recommendation using other shapes commercial ansys n/a n/a n/a simulation of distribution of lng imposed by air and sea surface temperatures [42] predict the lng dispersion process to spill and smoke clouds to examine sea transport as a major application of maritime fuel good agreement of computational results with experiments; sea surface temperatures impact lng dispersion more than air temperatures do commercial ansys fluent n/a n/a hazard of evaluating lng spill and vapor cloud dispersion advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 44 table 1 characteristics of mc transportation (continued) study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction simulation of 3d flow of maritime lng control valves [40] determine the advanced design of maritime lng control valves with high pressure drop good agreement of computational results with conventional control valves, improvement of flow pattern, reduction of cavitation, and prediction of performance commercial cfd-ace+ n/a n/a n/a simulation of submarine pipelines to examine the interaction of ocean transports with submarine landsides [41] predict submarine pipelines imposed by submarine landslides, a comparison of different shapes (wedge, airfoil, double-ellipse, and arc-angle hexagon) and conventional circular shape revealing the disadvantages of conventional circular pipelines in terms of lift force and drag force when interacting with submarine landsides, a recommendation using other shapes commercial ansys n/a n/a n/a simulation of distribution of lng imposed by air and sea surface temperatures [42] predict the lng dispersion process to spill and smoke clouds to examine sea transport as a major application of maritime fuel good agreement of computational results with experiments; sea surface temperatures impact lng dispersion more than air temperatures do commercial ansys fluent n/a n/a hazard of evaluating lng spill and vapor cloud dispersion simulation of high-speed catamaran transport to examine fuel economic efficiency [43] predict full-scale resistance values of the ship good agreement of computational results with experiments; the full-scale drag of large catamarans open-source openfoam n/a n/a simulate medium-speed catamarans in shallow water conditions simulation of virtual ship maneuvering using a captive model test [44] determine hydrodynamic coefficients for predicting ship maneuver good agreement of computational results with experiments; primarily designing maritime transport performance commercial star-ccm+ collect computational results of the model ship (dtmb 5512) using the same hydrodynamic model, problems, and initial conditions n/a simulation of 3d hydrodynamics of naca 0012 airfoil (wing) moving above a free surface for super-high-speed ships [45] predict flow field and pressure distribution around the wing on a free surface treating a free surface as a rigid wavy wall, examining the lift/drag ratio involved in a propulsion system n/a collect computational results of the naca 0012 airfoil wing using the same geometry, problems, and initial conditions n/a creation of a new solver for transport equation [46] create a new solver method acceptable results compared to standard solver open-source openfoam n/a n/a n/a advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 45 table 1 characteristics of mc transportation (continued) study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction prediction of hydrodynamic performance of marine propeller [47] predict the hydrodynamic performance using a neural network a neural network can be trained by cfd data commercial ansys fluent yes, the collection of cfd data yes, ml and cfd data n/a simulation of a boil-off gas generation for lng [48] predict the thermodynamic and hydrodynamic of an lng tank understanding the thermal behavior and characteristics of an lng tank commercial ansys fluent collect the same computing results of an lng tank using the same scale model, problems, and initial conditions n/a simulation of a semi-submersible floating offshore wind turbine [49] analyze the accuracy of the simulation a guideline is provided for the verification and validation of the simulation n/a n/a n/a n/a optimization of a fin-and-tube heat exchanger [50] investigate the optimal tube settings for a fin-and-tube heat exchanger significant improvements in thermal-hydraulic efficiency open-source openfoam n/a n/a n/a prediction of dynamic responses of the ultra-large floating body on maritime airport [51] analyze a case study on an ultra-large floating body under typhoon-wave a reference for the design and construction of maritime airports under typhoon conditions. n/a collect the same computing results of maritime airports using the same scale model, problems, and initial conditions n/a prediction of high-speed craft [52] present geometric deep learning models for engineering design optimizations acceptable results of the deep learning-based surrogate model using cfd data as a ground truth n/a yes, the collection of cfd data yes, ml and cfd data n/a assessment of a marine diesel engine fueled with natural gas [53] calculate the emission and performance of marine diesel engine temperature is a major reason for the increasing use of natural gas and biodiesel content. n/a collect the same computing results of marine diesel engine using the same scale model, problems, and initial conditions n/a fig. 5 shows a bottom view of the flow computation throughout the control valves of maritime lng structures. an example of data visualization in mc transportation revealed velocity streamlines paired with contour plots. among the included studies, those focusing on mc transportation were the smallest in number because an increasing number of ocean studies have recently been conducted. hence, the future direction of research on mc transportation is expected to be economic efficiency and environmental sustainability. fig. 5 mc transportation visualization showing lng control valves [40] advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 46 4.4. mc environment the mc environment focuses on environmental simulations and oceanic issues. table 2 lists the collection of mc environments. studies in this area have reported important ocean issues, such as the detection of microparticles of heavy metals in the ocean, the presence of coastal waste particles, underwater robotic observers, renewable energy generated by a tidal stream generator, oxygen dissolved in coastal water, ocean noise reduction, diesel engine emission reduction, and the effect of abalone aquaculture on the ocean. several studies have presented their codes (in-house software) instead of using commercial software for computations, algorithms, and simulations. big data and ai can be used to solve similar computational problems, models, and initial conditions. data obtained from the computing results can be collected if the same geometrical domains are used, such as diesel engines and waste sorting models. table 2 characteristics of the mc environment study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction simulation of deployment patterns of tidal stream turbines in the ocean [54] determine single and arrayed tidal stream turbines to generate maritime energy revealing the design of deployment of tidal turbine arrays offering new opportunities to progress renewable energy in-house software n/a n/a n/a simulation of the automatic design process of environmental ocean microfluidic chip [55] detect maritime ecological toxicity of heavy metals in microalgae detect ocean microfluidics-inte grated heavy metals (cu, hg, cd, and zn) using hydraulic analogy commercial cfd-ace+ and orcad n/a the automatic design process of microfluidic dilute network for ocean ecological toxicity assessment routine microalgae bioassays for expanding cell-based screening of environmental health risks simulation of coastal waste particles in a wind-power sorting system [56] determine different airflow rates to classify coastal waste particles into both combustible and noncombustible characteristics identify the arrangement of coastal waste particles to ensure recycling and reduction of coastal waste commercial ansys collect the same computing results of coastal waste particles and airflow rates using the same scale model, problems, and initial conditions n/a simulation of marine diesel engine for catalytic reduction system (crs) [57] predict nox emission reduction using a computing approach and comparison with experimental data revealing the reasonable potential of computational simulation to compute the actual nox reduction rate of crs commercial avl fire collect the same computing results of crs, nozzle model, and nox emission data using the same scale model, problems, and initial conditions n/a simulation of a two-arm marine robotic vehicle to examine hydrodynamic behavior [58] determine the propulsion and manipulation of bioinspired underwater robotic vehicles for observing the marine ecosystem revealing flow development and hydrodynamic force around the bioinspired arms of underwater robotic vehicles in-house software (developed own code) n/a n/a simulate more arm designs and kinematic parameters to optimize the current robotic system simulation of pumped surface water downwelling and dynamic response of oxyflux device (dissolved oxygen in coastal water) [59] determine 1/16 oxyflux model’s dynamic response and pumping performance (estuarine and coastal marine ecosystems) revealing the nonlinear effects of the reduction in the dynamic behavior of oxyflux and the small wave caused by the low-intensity winds of summer (involves predicting anoxia) commercial star-ccm+ n/a n/a improve time-domain computational model and floater shape; extend surge mode (currently have heave mode and pitch mode) and mooring system advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 47 table 2 characteristics of the mc environment (continued) study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction simulation of submersible abalone cages for marine-deployed aquaculture [60] simulate advanced abalone cages and conventional abalone cages in the exposed ocean environment performing surface and submerged simulations of both advanced and conventional abalone cages; new design of abalone cage commercial flow-3d, fluent, and msc.marc n/a n/a perform economic analysis and risk calculation for newly designed abalone cage simulation of the hydrodynamics of a spherical underwater robot [61] predict the movement of the spherical underwater robot examine hydrodynamic force, velocity, and pressure, basic movement characteristics of robot moving underwater commercial ansys n/a n/a improve the control accuracy of spherical underwater robots simulation of acoustic sounds generated from flows around circular cylinder [62] determine noises occurring while transport moves at increasing speed revealing simulated acoustic sound waves and sound pressure in-house software n/a n/a n/a simulation of floating tidal stream for renewable energy [63] assess floating tidal concepts compared to seabed mounted systems good agreement of computational results with experiments open-source openfoam n/a n/a n/a simulation of a marine environment containing chloride sea salts [64] evaluate a crack growth of chloride-induced stress corrosion cracking in a dry storage system a long-term environmental temperature had an impact on the erosion of long-term storage commercial ansys fluent collect the same computing results of a storage system and marine environment using the same scale model, problems, and initial conditions n/a simulation of underwater gas leakage and dispersion behaviors [65] investigate environmental pollution caused by underwater gas leakage current speed and gas leaking rate mainly affect the underwater gas migration process commercial ansys fluent n/a n/a n/a simulation of environmental loads impact ship maneuverability [66] investigate a real seaway to understand a ship’s maneuvering performance good agreement of computational results with experiments open-source openfoam collect the same computing results of environmental loads and vessel model using the same scale model, problems, and initial conditions prediction of the ship maneuver in waves with different wavelengths and heights simulation of multiphase oil behaviors [67] calculate risk assessment and pollution control of oil spills found that the presence of ice makes the spreading of spilled oil slower n/a n/a n/a n/a simulation of marine cabin's ventilation for reefer containers [68] analyze refrigeration efficiency in a severe marine environment good agreement of computational results with experiments commercial ansys fluent collect the same computing results of reefer containers and the marine environment using the same scale model, problems, and initial conditions n/a fig. 6 shows the tidal stream generators in the natural environment of the ocean. in this case, data visualization in the mc environment was performed using velocity streamlines designed to optimize the arrangement position of tidal stream generators in the ocean to generate renewable energy. future studies can focus on improving the accuracy of the computing results by redesigning the simulations. some included studies focused on mc environments because of the effects of fossil fuels and renewable energy on the global economy and sustainable development goals. advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 48 fig. 6 mc environment visualization revealing tidal stream generators in natural flow surroundings [54] 4.5. mc development mc development involves the study of geometrical simulations and ocean-shaped designs linked to the sea. table 3 lists the characteristics of mc development. study designs indicated that maritime development primarily focused on the design and modeling of oceanic objects, such as ships, sailboats, propellers, propeller blades, breakwater slopes, wave gliders, bio-inspired robots, submarines, and deep-water risers. most studies on maritime development have used the knowledge of fluid dynamics and hydrodynamic foundations, as well as the propulsion prediction of objects related to the ocean. open-source and commercial software programs are regularly used to create algorithms, simulations, and computations. the analysis results indicated that maritime big data and ai are likely achievable with similar geometrical domains, initial conditions, and maritime issues. table 3 characteristics of mc development study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction simulation of numerous marine hydrodynamic problems [69] develop their own software for naval architecture and ocean engineering visualize marine hydrodynamics open-source openfoam collect similar computational results for ai using the same scale model, problems, and initial conditions efficiency and accuracy of computing solver simulation of sheet cavitation flow around marine propellers [70] predict cavitating flows at low reynolds numbers of the transition-sensitiv e turbulence flow model good agreement of computational results with experiments commercial ansys fluent collect the computational results of the same propeller model using the same flow model, problems, and initial conditions n/a simulation of wave-seabed and breakwater slope [71] predict the impact of wave-seabed on breakwater design increment of the slope of a breakwater altered seabed and liquefaction open-source openfoam, commercial comsol and matlab collect similar wave-seabed and breakwater designs using the same scale model, problems, and initial conditions n/a simulation of optimization of marine contra-rotating propeller [72] determine the best hydrodynamic performance of marine contra-rotating propeller developing a new optimization method for maritime propeller commercial ansys fluent collect the computational results of the same propeller model using the same scale model, problems, and initial conditions efficiency improvement of computing results considering time consumption and technological cost simulation of a wave glider in a head sea [73] predict the dynamic performance of a wave glider in a head sea dependence of propulsion efficiency on the surge of surface boats and passive eccentric rotation of hydrofoil commercial fine/marine and star-ccm+ collect the computational results of the same simulation and wave glider model using the same scale model, problems, and initial conditions improvement of propulsion efficiency, optimum simulation, and design of hydrofoil in different head sea conditions advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 49 table 3 characteristics of mc development (continued) study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction simulation of the ship with two flapping foils [74] determine the best hydrodynamic performance of a ship with two alike penguin flippers the function of strouhal number, efficiency, and force coefficients of flapping foils commercial ansys fluent collect similar computational results of ship model and function of flapping foils using the same scale model, problems, and initial conditions n/a simulation of deep-water marine riser [75] determine vortex-induced vibration and fatigue damage caused by a very long marine riser good agreement of computational results with experiments n/a collect similar computational results of the same marine riser model using the same scale model, problems, and initial conditions n/a simulation of a four-bladed marine propeller [76] determine the best performance of marine propellers good agreement of computational results with previous results commercial ansys fluent collect similar computational results of the same marine propeller using the same scale model, problems, and initial conditions improvement of velocity and rotational speed simulation of suboff model maneuver [77] determine the flow change around the stern and entire suboff for maneuverability good agreement of yawing moment and yawing force with experimental data commercial ansys collect similar computational results of the suboff model using the same scale model, problems, and initial conditions n/a simulation of bio-inspired marine propulsor by imitating uniform fish fin [78] optimize the movement of maritime fish fin propulsor lunate-shaped fish fin demonstrates the highest efficiency improvement commercial ansys fluent n/a n/a efficiency improvement of computing results by modifying and redesigning the study model simulation of a five-bladed metal marine propeller [79] determine hydrodynamic performance with a change in marine propeller geometry the deformation of the marine propeller causes a negligible change in hydrodynamic performance commercial ansys fluent collect similar computational results of the same marine propeller using the same scale model, problems, and initial conditions analysis of a composite propeller and a comparison with the current result simulation of a composite marine propeller [80] optimize the hydroelasticity performance of the composite marine propeller optimizing the design of the composite marine propeller can reduce the vibratory hub loads commercial ansys collect similar computational results of the same marine propeller using the same scale model, problems, and initial conditions n/a simulation of marine propeller and suboff submarine [81] predicting that the propeller makes submarine underwater noise reduction of submarine underwater noise requires the control of propeller thrust excitation. n/a n/a n/a n/a simulation of fluid displacement under the bow of a ship model [82] predict the breaking wave and flow patterns at the bow of the ship model visualizing the breaking bow wave and wave patterns at the bow of the ship model in-house software (developed own code) n/a n/a examining the interaction of bow wave with shoulder wave for a comprehensive understanding of complex phenomena simulation of novel composite tube (toting wheel) marine current turbines under free flow conditions [83] predict ocean current energy generation from single and arrayed marine current turbines with ten tubes revealing significant power extraction of ocean current energy from arrays of marine current turbines with ten tubes commercial ansys fluent n/a n/a refinement of simulation system, such as changing wheel design (amend blade) to extract more ocean current energy advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 50 table 3 characteristics of mc development (continued) study design study purpose key findings algorithmic software usage maritime big-data possibility ai feasibility future direction study of flow around three commercial ships (container ship and two crude-oil ships having bow and stern bulbs) [84] determine flow characteristics around the three commercial ships, a study of ship hydrodynamics measuring flow wave patterns and velocity components depending on the speed of the ship n/a n/a n/a n/a simulation of the unsteady motion of a ship in waves [85] predict the performance of the ship in waves reveal the viability of computing ship motion with two degrees of freedom in-house software n/a n/a the realistic computational approach to simulate six-degrees-of-fre edom motion with nonlinear phenomena simulation of flow around a ship model [86] calculate viscous flow passing through the ship hull with and without a free surface computational approach by comparing computing results with measurement data in-house software n/a n/a n/a simulation for the design of a sailboat [87] compute the design of hull-form development of the sailboat reveal the prediction of both steady and unsteady sailing performances of boats in-house software n/a n/a improve simulation simulation of an x-plane submarine [88] compute the maneuvering coefficients of the submarine good agreement of computational results with experiments snufoam based on open-source openfoam collect similar computational results of x-plane submarine using the same scale model, problems, and initial conditions n/a simulation of the planing hulls [89] analyze complex hydrodynamics problems of the planing hulls cfd automated workflows can be used to study the planing hull hydrodynamics open-source openfoam n/a n/a n/a simulation of ship model maneuvers for autonomous vessels [90] compute the dynamic maneuvers of a container ship with self-propelled free running good agreement of computational results with experiments commercial star-ccm+ collect similar computational results of the same marine propeller using the same scale model, problems, and initial conditions validate and implement a more sophisticated propeller model simulation of ship navigation [91] analyze the energy efficiency of ships a reference for performance monitoring and maintenance prediction of international maritime affairs n/a yes, the collection of cfd big data using the same scale model, problems, and initial conditions collect the accumulated navigation mileage of every ship simulation of blade shape optimization [92] optimize the shape of the blades of the savonius wind turbine the optimized blade performed better than a classical semicircular blade commercial ansys collect similar computational results of the blade model using the same scale model, problems, and initial conditions improvement of simulation and blade shapes simulation of towing tank [93] investigate the effect of muddy seabeds on marine vessels accuracy of the bingham model for marine vessels sailing through fluid mud refresco cfd code n/a n/a n/a advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 51 fig. 7 shows a study of ship hydrodynamics to model a ship maneuverer moving in the ocean. this research illustrates a computing example of maritime development, and the developed model explains virtual ship hydrodynamics. future studies can focus on improving the precision and productivity of the computing results, reducing computational costs, improving simulations, and using future technological advancements. most included studies focused on mc development because of the relationship between modeling and design in the field of mc. fig. 7 mc development visualization illustrating the motion of a ship while it turns on the sea surface [69] 5. discussion in the present research, articles that focused on mc transportation, environment, and development were analyzed. systematic reviews and metadata methodologies were used to search and analyze original full-text research articles on maritime literature retrieved from online digital databases. the field of mc focuses mainly on transportation, environment, and development. these mc areas are key inputs for economic benefits, demographic trends, security factors, increasing seaborne and trade demands, skilled workers, automation and technology, and sustainable development goals [12]. this research majorly contributes to the literature in several ways: (1) this study expands research on the mc perspective by providing evidence showing how the key classification of the mc domain promoted ocean-based businesses. (2) it is the first report to discover how mc domain configurations support management technologies. since ocean-based businesses in several countries are a major economic contribution to the world economy through research, business, trade, and innovation, e.g., great britain, the united states, taiwan, and china. (3) the results of the current study provided the history of using computers for ocean-based businesses through the mc domain and assisted in planning future business, research, and innovation. this finding represented an opportunity to use the computational results of the same study designs to build big data and intelligent computation about mc data trends. this study focuses on ocean-based businesses, particularly in the area of maritime studies, to obtain insights into the field of mc. the mc literature contains cfd involved in naval architecture, marine engineering, computer technology, visualization, and computational methodologies. in contrast, other maritime applications (e.g., shipping, freight, airlines, air transport, fisheries, finance, and investment) and other computational studies (those based on blockchain, the internet of things, social networks, and digital marketing) are excluded. consequently, the main aim of mc is to support economic science and bioeconomy. as shown in fig. 4 mc began with the mathematical matrices based on numerical computation in 1990. traditional computing methodologies are typically limited to the invention of computer technology to visualize data and findings. the computational results were mostly presented as 2d contours, line plots, and scatter plots [94-95]. prior to that, computer technology was evolving, focusing on the improvement of microprocessor and semiconductor technologies, and industrialized advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 52 [34]. therefore, mc was absent during the 1980s and 1970s (fig. 4). when gpu technology was considerably improved in the 2010s [96], studies on mc began to be increasingly conducted (fig. 4); these findings are presented in fig. 3 (from 2012 to 2019, the number of first authorships increased). an analysis of the original maritime literature indicates that computing and technology are paramount for education, new skill sets, and practical work. maritime development reveals modeling is an essential ground skill set of all other mc areas (fig. 4, development is highlighted as a root). simultaneously, maritime transportation and environment (fig. 4) were in line with the sustainable development goals [97-98]. however, maritime transportation studies have provided benefits not only for increasing trade opportunities, but also improving economics and supply chain management [12, 99-100]. thus, mc transportation is a crucial economic factor. further maritime trends depend on clean energy, renewable energy, environmental recovery, trade, and real-time digital efficiency cost management [101-103]. mc development demonstrates modeling literacy and skills enabled apprentices, learners, and researchers to translate non-time-dependent activities, such as the maritime logistics process of supply chains for scheduling issues, into a time-dependent computer model, depicting a well-structured problem [21, 104-105]. the results shown in tables 1-3 indicate that big data and ai are likely achievable through the data collection of similar computational results for applying the ml approach. the maritime visualization and computational methodologies discovered in this report are used in ocean studies. the maritime visualization outputs of this report in terms of mc transportation, environment, and development are shown in figs. 5, 6, and 7, respectively. moreover, data visualization methodologies are identified, including organizing data into a table, 1d/2d contour plot, 2d cross-sectioned plot, line graph, bar graph, vector plot, streamline plot, streamline contour, streamline surface, vorticity magnitude contour, wave pattern, 3d graphical abstract, 2d geographical map, scatter plot, actual problematic photo compared with computing results, 3d streamlines, 3d particle tracers, 3d cross-sectional views, 3d computer domains, flowchart, and workflow diagrams. mathematical models and techniques for computation used in mc include the navier–stokes equation, fluid-structure interaction, marker-and-cell method, navier–stokes–poisson equation, reynolds-averaged navier–stokes (rans), reynolds stress model, microalgae bioassay, microfluid networks, circuit design, fluid dynamics, hydrodynamics, experimental study, unsteady rans, structural model, wave model, coupled blade element momentum (bem)-cfd model, renormalization group k-epsilon model, 2d schematic diagram, 3d computer design, statistical analysis, error estimation, large-eddy simulation, detached‐eddy simulation, kinematic equations, lattice gas method, lattice boltzmann method (lbm), lattice gas cellular automation, finite difference lbm, arbitrary lagrangian–eulerian method, electronic design automation, and computer-aided design. furthermore, the meshing element approaches comprise both the finite volume approach and the finite element method. in addition, open-source, in-house, and commercial software programs are used in mc to create computations, algorithms, and simulations. however, the open-source software used to develop in-house programs is based on openfoam [106]. the aforementioned mc domain primarily consists of transportation, environment, and development. mc characterizes the computer simulation planning of people’s ocean business processes and tasks. the mc approach generally includes maritime visualization and computational methodologies. mc supports the translation of maritime data and ideal design information into real-world objects, models, and applications [20, 107]. a business process substantially requires a clear goal associated with its producible outputs. hence, these procedures should be simple with tractability and should strongly focus on producing maritime computational results and outputs [21, 108]. mc offers support to economic science and the bioeconomy [15-16, 109-110]. advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 53 the analyzed studies published in the years 2020-2022 demonstrated the applications of the proposed concept of ml, cfds, and big data [47, 52, 91]. fig. 4 shows the evolution of computer technology; clearly, the complex problem modeling and computation techniques progressed together with the invention of computers [34]. it seems that the trends of data visualization and computational methodologies will be included soft computing and intelligent computation in the 2020s (fig. 4). furthermore, the global policies on climate change and sustainable development have directly influenced mc research. as a result, the analyzed results in fig. 3 depict the rise of mc transportation and environment significantly in the years 2020-2022. this study has some following limitations: (1) as a comprehensive search was performed in different databases to retrieve full-text original articles, most of the search results did not yield original studies. thus, in some databases, such as google scholar, it is difficult to categorize original research. (2) the sources of digital maritime literature are changing daily owing to the regular publication of new articles, new research submissions, and updated scientific databases. thus, maritime digital databases and literature do not have up-to-date oceanic information. nevertheless, the use of mc began to rise in the 2010s (fig. 4). (3) an automated procedure for document search and analysis is not investigated. hence, a manual analysis is performed to identify the original studies on mc. (4) an automated document search and analysis need to be performed to complement this study. furthermore, no articles from the iet digital library or ieee-xplore databases met the inclusion criteria. additionally, the same articles were indexed in several databases which are the web of science, scopus, sciencedirect, and google scholar. this complicates the final combination of search results. (5) the systematic search is time-consuming, requiring a considerable time to read articles thoroughly to ensure that they met the selection criteria for inclusion in this meta-analysis. 6. conclusion it is the first report to discover how mc domain configurations support management technologies. in this systematic review and meta-analysis, mc studies were identified and reviewed. the areas of mc development, environment, and transportation were successfully categorized. the results show that mc can provide new oceanic knowledge and education to support economic science and bioeconomy. from the analysis, the following observations are made: (1) studies on mc began to increase in the 2010s, while maritime modeling is a key skill set. maritime transportation studies focus on the usage of lng, maneuvering ship’s speed, and submarine pipelines. the maritime environment has been explored for ocean recovery and protection. the trends of maritime data visualization and computation methodologies were observed to be associated with computational coding techniques and the invention of computers. (2) the ml strategy can be applied to the big data collection of similar computing results to implement ai strategies. additionally, mc improvement mainly focuses on promoting mc to the public for an increment of mc research studies. this update will add innovations and technologies; hence it creates an economic impact on ocean-based businesses. (3) future improvements to the mc may involve the use of quantum bits as an alternative to current digital bits for better modeling of specific problems for processor processing. the gap in connecting ml models to cfd results remains; thus, more research is needed to guide the generation of cfd results, and also makes all ml models are interconnected. the simple partial differential equation (pde) of navier–stokes is one of the best methods for hybrid visualization and cfd practices. this hybrid model can be used as a standard guide for individuals to understand how to create specific questions using pde and maritime modeling. therefore, the efficiency of maritime modeling can be improved. advances in technology innovation, vol. 8, no. 1, 2023, pp. 38-58 54 the present report indicates that mc is important in maritime society to accomplish sustainable development goals. based on these primary results, further studies focusing on a case study of each mc classification are required to corroborate the present findings. conflicts of interest the author declares no conflict of interest. references [1] j. b. r. g. souppez, “interdisciplinary pedagogy: a maritime case study,” dialogue: journal of learning and teaching, pp. 37-44, january 2017. 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[110] t. düppe, “border cases between autonomy and relevance: economic sciences in berlin—a natural experiment,” studies in history and philosophy of science part a, vol. 51, pp. 22-32, june 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v9n4(2024)-aiti#13655(257-272).docx advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 english language proofreader: chih-wei chang differentiated qos provisioning in wireless networks based on deep reinforcement learning ming-chu chou1, guang-jhe lin1, chih-heng ke1,*, yeong-sheng chen2 1department of computer science and information engineering, national quemoy university, kinmen, taiwan, roc 2department of computer science, national taipei university of education, taipei, taiwan, roc received 29 april 2024; received in revised form 03 august 2024; accepted 06 august 2024 doi: https://doi.org/10.46604/aiti.2024.13655 abstract wireless networks manage performance by adjusting the contention window, as they cannot directly detect collisions. traditional contention window adjustment algorithms, such as the binary exponential backoff (beb) algorithm, may lead to lower throughput when multiple services with varying bandwidth demands coexist. to address this issue, this study aims to enhance network throughput by enabling differentiated bandwidth allocation for various services. using deep reinforcement learning, the state space, action space, and reward functions are defined to optimize this differentiation. these definitions are integrated into the deep deterministic policy gradient (ddpg) technique, implemented in the access point (ap) to intelligently adjust the contention window. leveraging ddpg’s capability for continuous actions, the proposed method provides quality of service (qos) differentiation, ensuring that each service at its respective priority level meets its transmission requirements. compared to the beb algorithm, the proposed approach offers improved traffic allocation and higher network bandwidth utilization. keywords: 802.11 wireless networks, quality of service (qos), contention window, deep reinforcement learning 1. introduction in the field of ieee 802.11 wireless networks, several challenges emerge in satisfying diverse user requirements. given the varied application scenarios for different users, the network system must render multi-tiered quality of service (qos). for instance, certain users might be engaged in high-definition video streaming, where excellent qos is crucial. in contrast, other users might only be involved in file transfers, which is relatively not dependent on service quality. this diversity necessitates the formulation of differentiated qos definitions based on specific usage contexts to ensure the network can flexibly address a panoply of application requirements. therefore, this paper utilizes the deep deterministic policy gradient (ddpg) algorithm [1] to adjust the contention window (cw) according to different user needs, ensuring the delivery of services that align with specific user experience expectations. the cw was initially introduced by ieee due to the inability of nodes to detect collisions in wireless network environments. technically, nodes tend to wait for a random backoff time to stagger the transmission times of nodes. this waiting time is determined by the cw of nodes. when a collision occurs, to eschew another collision, the network exponentially increases the cw of nodes, thereby increasing the backoff time. conversely, when a node successfully transmits, the cw is reduced back to the minimum value allowed by the network standard, which decreases the node’s backup time. this algorithm is called the binary exponential backoff (beb) algorithm. from the collision avoidance mechanism, it can be inferred that as the cw increases, nodes must wait longer for data transmission. as a result, such a design may compromise * corresponding author. e-mail address: smallko@gmail.com 258 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 the channel access rights of nodes. therefore, this paper utilizes deep reinforcement learning (drl) technology to appositely adjust the cw of nodes, empowering high-level clients to possess higher channel access rights, thereby achieving differentiated treatment when dealing with clients of different priorities. the main contribution of this paper lies in proposing a mechanism that utilizes drl to adjust the cw, thereby providing different priorities of qos for each tier of clients. the structure of this paper is listed as follows: section 2 introduces the drl mechanism, ddpg, used in this study, along with previous research on enhancing qos through drl. section 3 explains the specific parameter settings for drl and the operational workflow of the overall research method. following this, the paper presents research results to validate its contributions in section 4. finally, the conclusion in section 5 discusses future optimization directions. 2. related work this section explores recent qos-related research to highlight the indispensability of qos. specifically, the necessity of providing different bandwidths is discussed, based on varying priorities within the context of qos issues. after introducing the qos topic, it presents pertinent studies on adjusting the cw to enhance qos, supporting the feasibility and significance of the subject. finally, it introduces the technologies most relevant to this paper. 2.1. qos issue qos has consistently been a crucial topic, as can be witnessed by li et al. [2] proposing a multi-dimensional internet of things (iot) qos estimation method that introduces multi-dimensional qos to assess the qos of iot applications. the approach is illustrated using iot application instances to demonstrate the process of estimating the qos of iot applications. kang et al. [3] present a diversified qos-centric service recommendation method tailored for uncertain qos preferences, generating a list of services that fulfill the desired qos and diversity. in recent years, a surge has emanated from research introducing the multiple-access edge computing (mec) framework to enhance network qos. wang et al. [4] introduce a qos prediction method that considers user mobility and qos data fluctuations to adapt to the mec environment. yan et al. [5] deployed historical qos values as a time series of qos matrices. it combines a compressed matrix extracted from the qos matrix through truncated singular value decomposition (svd) with the traditional autoregressive integrated moving average (arima) model. luo et al. [6] propose a qos-oriented multiple unmanned aerial vehicle mobile base station (uav-mbs) 3-d deployment algorithm, named qos-prior. this algorithm optimizes the altitude and coverage radius of uav-mbss based on different qos requirements. numerical results show that the algorithm outperforms some baseline algorithms under constraints and achieves relatively low time complexity. zhang et al. [7] propose a stochastic walk-based interval prediction method for web service qos, called a random walk, effectively combining location awareness and collaborative filtering methods. to render more reliable simulations, the authors conducted a series of comprehensive experiments on a real web service dataset. the results demonstrate that the proposed method achieves a better balance between confidence and accuracy in service recommendation compared to other collaborative filtering methods. however, notwithstanding the betterment yielded by these studies, effectively differentiating adjustments based on priorities is perceived as an urgent need for qos. 2.2. the issue of adjusting the contention window according to different transmission services when a network simultaneously hosts high-priority nodes with high bandwidth demands and low-priority nodes with low bandwidth demands, the issue of adjusting the cw according to different transmission services is especially worthy of notice. high-priority nodes need to continuously compete with other nodes to satisfy their bandwidth needs. during the period of advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 259 contention, transmission collisions will cause the cw to increase. conversely, low-priority nodes, with their lower bandwidth requirements, do not need to frequently compete for the channel, thereby resulting in a lower cw. this situation signifies and causes high bandwidth demand nodes to have lower throughput, compared to low bandwidth demand nodes. 2.3. contention window to provide transmission services at different priorities, this paper adopts the technique of adjusting cw. the adjustment of cw to maximize overall network utilization has been constantly discussed. lu et al. [8] propose a strategy called transmission rate-based contention window adaptive adjustment (trcwaa) to achieve fair resource allocation. technically, the trcwaa strategy adjusts the minimum cw size of each node inversely proportional to its transmission rate. simulation experiments demonstrate that the trcwaa strategy effectively addresses the issues of abnormal performance and unfairness. furthermore, numerous studies have also incorporated artificial intelligence techniques to adaptively adjust cw. for example, yang et al. [9] describe a clustering routing optimization strategy based on an ant colony algorithm, constrained by the cw. specifically, the values of cw for non-uniformly loaded nodes in clustered networks are analyzed, and a cluster head selection strategy, considering cw, network interference, and remaining energy, is proposed. experimental results demonstrate that the ant colony cluster optimization based on the contention window (acco-cw) strategy effectively improves the success rate of data transmission. however, the method of computing q-values using reinforcement learning cannot cope with highly complex network environments. therefore, several research has utilized neural network technology to approximate and compute complex q-values within it. li and jian [10] address the cw selection problem for ieee 802.11 networks oriented towards the age of information (aoi) using the ddpg technique. the results show that this method reduces the average aoi of the system by approximately 57.6%, compared to the traditional beb method. jiang and zheng [11] no longer merely use regular neural networks to compute q-values. instead, the recurrent neural networks (rnns) with deep recurrent q-networks (drqn) are adopted. this paper studies the initial cw size adjustment problem in a coexisting network with new radio unlicensed (nr-u) and wifi systems. it adaptively finds the optimal cw size by training the primary deep q-network (dqn) in a drqn and observing the current status of the coexisting network, including the current cw size, throughput of the wifi system, throughput of the nr-u system, and the number of nr-u users with data to transmit. experimental results signify that this method outperforms both fixed cw mechanisms and adaptive cw mechanisms. 2.4. enhancing qos with contention window based on the aforementioned qos research, this paper aims to enhance network performance and furnish with differentiated services through cw adjustment. erstwhile qos studies have focused on adjusting the cw to improve service quality, accentuating the feasibility of manipulating qos through cw control. suvarna et al. [12] propose a novel framework based on a divide-and-conquer strategy for setting cw, achieving efficient qos even with more nodes in the network. toralcruz et al. [13] introduce a qos-differentiated backoff mechanism that doubles the cw during collisions and the channel perceived as busy. while doubling the cw during busy channel periods may reduce collisions between competing stations, it may increase the backoff delay for delay-sensitive applications (such as voice and video). aldawibi et al. [14] investigate the performance of backoff cw in randomly moving mobile ad hoc networks (manets) using major routing protocols, e.g., dynamic source routing (dsr), destination-sequenced distance-vector routing (dsdv), and ad hoc on-demand distance vector (aodv). the study implemented key parameters such as network throughput, power consumption, and network latency using the network simulator (ns)-2, with in-depth discussions of the experimental results. rasna et al. [15] assess the effectiveness of the cw by examining the impact of increased communication channel signal interference and the signal-to-noise ratio (sinr) 260 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 in the presence of hidden nodes. notwithstanding the superior performance demonstrated in these research papers, a limited exploration of using cw adjustment to provide differentiated services is observable. kwon et al. [16] utilize reinforcement learning techniques to provide different transmission services for various priorities and clients. given such a praxis, this paper combines reinforcement learning to propose a cw adjustment method for wireless body area networks (wbans), abbreviated as reinforcement learning contention window adjustment (rl-cwa). rl-cwa maintains multiple q-tables to account for the varying minimum and maximum cw based on the user priority (up) of the traffic. experimental simulations demonstrate that the performance of rl-cwa is superior to the existing ieee 802.15.6 mac. 2.5. research methodology insights as artificial intelligence techniques proceed to become mature, numerous studies in the field of wireless networks have increasingly incorporated ai to address complex issues. within the field of artificial intelligence, drl represents its remarkable performance in addressing wireless network issues. ergun et al. [17] explore the application of drl techniques in the context of 5g, highlighting its significance. this research mentions that reinforcement learning does not rely on precise environment modeling and decision-making, which helps reduce the complexity and cost of solutions, thereby enhancing system responsiveness. furthermore, when faced with unknown wireless network states and conditions, reinforcement learning can be employed to address non-convex optimization and optimization of mutually coupled variables, resulting in superior performance compared to other machine learning methods. based on drl, wydmański and szott [18] propose the centralized contention window optimization with the drl (ccod) framework, as depicted in fig. 1. in this framework, the collision rate within the overall network is considered as the state space for drl using the dqn [19] agent loaded within the ap. the output value obtained adjusts the cw, influencing all stations to adapt their cw through ap broadcasting. this architecture serves as a crucial inspiration for the work of this paper. building upon the concept introduced by ke and astuti [20], where high-rate nodes enjoy higher channel access, this study utilizes the ddpg algorithm to generate multiple consecutive actions. with the centralized single-agent ccod framework, the proposed method allocates varying cw based on customer classes to achieve different levels of channel access privilege. fig. 1 ccod architecture 2.6. ddpg introduction the ddpg algorithm, proposed in the paper of lillicrap et al. [1], is a drl approach designed for continuous action spaces. combining deterministic policy gradient methods with deep neural networks, ddpg addresses reinforcement learning challenges in high-dimensional, continuous action spaces. pervasively recognized in the field of drl, ddpg is particularly suitable for tasks requiring continuous control of the environment, such as robot control, autonomous driving, and resource allocation. advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 261 the ddpg architecture, depicted in fig. 2, encompasses feeding the state space into the actor network and its corresponding target network (actor target network). subsequently, the actions of the actor network (action) and the state space are input into the critic network. the target action from the actor target network is utilized to control the environment. simultaneously, the actions and state are input into the target network (critic target network) below the critic network. after obtaining q-values from both the critic network and its target network, along with the reward, mathematical calculations yield the loss values for both the critic network and the actor network. these values are subsequently used to update the neural network weights. finally, at regular intervals, the actor network and critic network each update their respective target networks. fig. 2 ddpg architecture the critic evaluates the network loss function using the following equation [1]: ( ) ( ) 2 1 1 ˆ , ,+ +  = + − i i i i iqloss reward rq s a q s a (1) where qloss is the output of the q-value loss function, r is the discount rate, s is the state of the environment, a is the action of the actor network, �� and q represent the critic target network and the critic evaluation network, respectively. to enable the critic network to yield more accurate q-values based on the output actions of the actor, reward values are considered. this is achieved by reducing the impact of environmental noise through temporal difference (td) error learning with the target network. also, the actor evaluates the network loss using the following equation [1]: ( ) 1 1 ˆ , = = −  n i ii aloss q s a n (2) where aloss is the output of the actor loss function, and n represents the number of training samples. the actor aims to execute actions for the optimal strategy, quantifying the policy to form q-values as a loss function. this approach seeks to balance exploration and exploitation in reinforcement learning by maximizing q-values. after network evaluation, the actor and critic update their target networks using the following equations, respectively [1]: ( )target targeteval critic critic critic1 1, θ τθ τ θ τ= + − < (3) ( )target targeteval actor actor actor1 1, θ τθ τ θ τ= + − < (4) where θ represents neural network parameters, and τ is a user-determined variable designed to ensure the target networks are updated with a fixed probability. 262 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 3. research method this section introduces the system model of the proposed method, detailing the design of the observation space, action space, and reward function in drl. the method is illustrated through an algorithm based on this model. notably, this paper proposes and compares two different reward functions, which will be discussed in section 4. 3.1. system model this study employs a centralized architecture, as shown in fig. 3, with the ddpg agent installed in the wireless ap. the ap obtains collision rate information from the global network as the state-space input for the agent. subsequently, the ap transforms the actions (action1 and action2) output by the actor neural network of the agent into new cw values (cw1 and cw2). these values are then broadcast in beacon frames to all nodes. high-priority client nodes use cw1, while low-priority client nodes use cw2. the critic neural network of the agent takes the current state space, action1, and action2 as input and outputs the q-value to record the state transitions and decision quality of the markov decision process. finally, the ap synthesizes global network throughput performance and client transmission rate information to derive the reward value for optimizing the neural network of the agent. fig. 3 system model 3.2. observation space the state space inputs the actor and critic neural networks in the ddpg agent. this study concentrates on the network collision rate in the last four intervals, aiming to expedite training convergence by ignoring the fractional collision rate. { }1 2 3 4, , ,− − − −=t t t t ts coll coll coll coll (5) = coll t t tcoll t t (6) = +succ coll t t tt t t (7) eq. (5) represents the state �� of the node at time t, where ����� indicates the collision rate of the node at time t. the calculation of ����� is given by eq. (6), where � ��� symbolizes the number of collisions from t−1 to t, divided by the total number of transmissions by the node from t−1 to t, �, as calculated in eq. (7). advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 263 3.3. action space the action produced by the ddpg agent’s actor neural network consists of two real numbers, each ranging from 0 to 1, as defined by: ( )argθ= tr et i i actoraction actor s (8) based on state � , the actor determines the target network parameters ��� � ������ and generates a continuous action ������ . with the deployment of eqs. (1)-(8), the ap can derive appropriate cw values for both high-priority and low-priority client nodes. however, these cw values must be constrained within a range of 16 to 1024, as specified by the 802.11a network standard. therefore, the following two formulas are further applied. ( ), ,16,1024σ =  i icw clip normal action (9) ( ) min, if min , min, max , if max min max, f max <  = ≥ ≥  < x clip x x x i x (10) in eq. (9), a gaussian random distribution is applied to slightly perturb ������ , mitigating the effects of network temporality. the parameter σ is a user-defined hyperparameter. eq. (10) constrains the cw to be between 16 and 1024. 3.4. reward function the reward value, a crucial metric for optimizing the actor neural network of the agent, is computed in eq. (10) based on the actions executed in the current state. to ensure that high-priority clients receive superior treatment, the ap monitors the throughput of both high-priority and low-priority clients. the reward function is designed to provide higher rewards when the throughput difference between the two client categories approaches the desired gap. ( ) 1 1 =   = × −     n client t t i thr i r throughput rate diff n (11) 1 1 , β α = = = − ≠ n n jclient i i i j t j tthr i j diff thr thr i j (12) ( )= − client t t thrreward thr abs diff (13) eq. (11) normalizes the overall network by using the average rate for two main reasons. firstly, it ensures that the reward values are kept between 0 and 1, which helps prevent gradient explosion during the training process. secondly, controlling the range of reward values intensifies the difference in reward values between various throughputs while still managing the range of these rewards. as a result, the generalization ability of the agent is increased. the parameter ������� �� ��� calculates the throughput difference ℎ�� − ℎ�� between different-level clients using eq. (12). the goal is for the ddpg agent to learn and minimize the throughput differences between clients of different priorities, aiming for a fixed multiple ! expected by the system. however, eq. (11) tends to trap the agent in local optimal solutions when facing higher transmission rate standards. therefore, based on eq. (11), this study designs a new reward function, eq. (13). by subtracting the absolute value of the throughput from eq. (12), this research method enables the agent to output cw values based on throughput, while keeping the throughput gap between customers of different priorities close to the system’s expected value. 264 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 3.5. algorithm table 1 illustrates the meanings of the parameters within the algorithm. the first half of the algorithm corresponds to the agent training phase. during this stage, the agent renders a fixed probability of outputting random actions to explore previously untried actions. simultaneously, the ap records the overall network collision rate for the first four collisions as input to the state space of the agent. the output actions, adjusted by the ap, determine the cw values for high-priority and low-priority customer nodes. each time a collision or successful transmission occurs, the nodes adjust their cw based on their priorities. subsequently, at regular intervals, the agent optimizes the actor and critic networks through observation of these actions. these behaviors continue in a loop until the end of the training period. after the training phase, the model enters the testing stage, which is similar to the training phase, with the difference that the agent no longer explores. the agent only outputs actions that the actor believes will maximize the q-value. algorithm 1 1: accesspoint ap 2: ap.agent = ap.createagent() 3: nodes n = {node1, node2, ..., nodei} 4: now = 0 5: proc training(): //training phase 6: while now < trainingtime: 7: state = ap.agent.state 8: action = ap.agent.act(state) 9: ap.newcw1, ap.newcw2 = eq. (9) 10: for node in n: 11: if node.priority == 'high' 12: node.cw = newcw1 13: end if 14: else node.priority == 'low': 15: node.cw = newcw2 16: end else if 17: end for 18: reward = eq. (11) or eq. (13) 19: for {state, reward, nextstate, nextaction} in ap.agent.relpybuffer: 20: ap.agent.update (state, reward, nextstate, nextaction) 21: end for 22: end while 23: end proc 24: now = 0 25: proc testing(): //testing phase 26: while now < testingtime: 27: state = ap.agent.state 28: action = ap.agent.act(state) 29: ap.newcw1, ap.newcw2 = eq. (9) 30: for node in n: 31: if node.priority == 'high': 32: node.cw = newcw1 33: end if 34: else node.priority == 'low': 35: node.cw = newcw2 36: end else if 37: end for 38: reward = eq. (11) or eq. (13) 39: end while 40: end proc advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 265 table 1 parameter description of algorithm 1 argument description accesspoint base station type equipped with a reinforcement learning agent responsible for receiving messages and broadcasting new contention window values. createagent create ddpg agent actions nodes n network node set node.priority node customer grading accesspoint.agent.state state space required for observation within the base station. accesspoint.agent.act the agent in the base station selects the optimal action based on the state space. accesspoint.agent.replymemory replymemory is responsible for collecting the state, reward, nextstate, and nextaction of the agent, facilitating the updating of actor and critic neural networks. accesspoint.agent.update the intelligent entity at the base station optimizes its functionality. 4. experimental results this section presents experimental results based on the proposed method. in addition to the comparison of overall network throughput, proposed collision rate, and traditional method, it also compares the throughput of different priority levels, demonstrating that the proposed method can render different bandwidths for different services. after comparing the network performance of the proposed method, the paper also evaluates the performance of the two reward functions, explaining which network scenarios each reward function is best suited for based on their performance. 4.1. experimental design this study simulates the 802.11a standard network using python, and the ddpg algorithm implemented on the ap is realized through pfrl and pytorch. the experimental comparison entails evaluating the proposed method against the traditional beb algorithm apropos overall network throughput, collision rate, and performance across different node priorities. the transmission rate for all nodes in the experimental network environment is set at 48 mbps. among these nodes, half are categorized as high-priority clients, while the other half are low-priority clients. the expected experimental results aim for a twofold difference in throughput between the two, with the parameters " and ! involved in eq. (12). 4.2. experimental parameter table 2 ddpg parameters parameter value #-greedy 0.1 discount rate $ 0.09 optimizer adam training time n × 100,000 s episode interval 0.1 s % 0.025 table 3 network parameters parameter value paylaod 1,000 bytes slot time 9 ms difs 34 ms sifs 16 ms cw min/max 16/1024 " 1 ! 2 regarding the internal parameters of the agent, as presented in table 2, the internal critic network of the agent is constructed with a neural network comprising one input layer, three relu layers with 128 inputs and 128 outputs each, and one linear output layer. additionally, the actor network comprises one input layer, three relu layers with 128 inputs and 128 outputs each, and one sigmoid output layer, aimed at constraining the actions between 0 and 1, facilitating precise control of the overall network cw range using eq. (9). concerning the choice of gamma in drl, this study compared the values of 0.06, 0.09, and 0.12. among these values, opting for 0.09 resulted in the throughput gap between high-priority and low-priority 266 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 nodes being adjacent to twice the difference. therefore, this paper presents the results for 0.09. in future work, a more in-depth comparison and discussion of the appropriateness of these parameter choices will be conducted. regarding the network environment configuration, refer to table 3. 4.3. network experimental performance this study contrastively examines experimental results across scenarios with node counts of 10, 20, and 30. figs. 4-7 respectively present comparisons of the overall throughput, collision rates, throughput for high-priority and low-priority clients, and cw sizes for different priorities between the traditional beb algorithm and the proposed method. in fig. 4, the beb algorithm exponentially increases the cw of a node when collisions occur. consequently, when the cw renders excessively large, the exponential increase leads to a dramatic rise in the window size. although this blind increase can effectively reduce collision probability, it sacrifices the channel access rights of numerous nodes, incurring decreased throughput. in contrast, the drl method proposed in this paper leverages ddpg’s ability to output continuous actions, empowering the agent to refine the adjustment of cw. as a result, the throughput performance of this method far exceeds that of the beb algorithm. fig. 4 throughput comparison fig. 5 collision rate comparison advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 267 fig. 5 illustrates that the traditional beb algorithm significantly increases collision rates by drastically reducing the cw to its minimum value after a successful node transmission. this approach becomes unsustainable in networks with a high number of nodes. in contrast, the method proposed in this paper adjusts the cw of the node back to the value observed by the agent after a successful transmission. the agent monitors the network collision rate as a state space, enabling it to effectively mitigate the issue of high collision rates in environments with a large number of nodes. the focus of this study is to yield different transmission qualities for clients based on their priorities. fig. 6 illustrates the research approach compared to the traditional beb algorithm, highlighting throughput performance in a network environment with high-priority and low-priority clients. the beb algorithm evinces similar throughput for both categories of clients, as it does not adjust cw individually. in contrast, the proposed method in this study, which employs the ddpg model, benefits from the capability of the model to output continuous actions. such a phenomenon enables the agent to adjust cw values for nodes with different priorities. additionally, the reward function design in eq. (10) ensures that the differences in transmission services among clients are controlled within the desired range. fig. 6 throughput comparison of different priority clients fig. 7 contention window of different priority clients 268 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 however, numerous factors emerge to affect network transmission quality. simply adjusting the cw can provide differential services for different nodes, but it may not precisely satisfy the desired service levels. to illustrate the differential adjustments made by the agent, fig. 7 illustrates the trends in cw adjustments for two types of clients, comparing the beb algorithm with the proposed method of this study. due to the limitations of the beb algorithm, the cws for both client types initially start low in a scenario with 10 transmission nodes. however, as the network increases to 20 and 30 nodes, the cws for both client types grow significantly due to the exponential expansion of the contention window under the beb algorithm. in contrast, the proposed method reduces the cw for high-priority nodes, improving their throughput, while increasing the cw for low-priority nodes through exploration and utilization by the agent. this approach reduces channel access rights without causing significant fluctuations in the cw for high-priority clients as the number of nodes changes. fig. 8 throughput comparison in 10 nodes in 100 sec, 10,000 sec, and 20,000 sec fig. 9 collision rate comparison in 10 nodes in 100 sec, 10,000 sec, and 20,000 sec fig. 8 presents a comparison of throughput between the beb algorithm and using eqs. (11) and (13) as reward functions for ddpg, with 10 nodes. the beb algorithm outperforms ddpg agents with either reward function before 20,000 seconds. however, once the ddpg agents are trained with eq. (13) as the reward function reaches a certain stage, their performance advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 269 surpasses that of the beb algorithm. on the other hand, ddpg agents trained with eq. (11) as the reward function tend to remain at local optimal solutions, incurring even lower throughput performance compared to beb. based on the experimental results shown in fig. 8, it can be observed that ddpg agents using eq. (13) as the reward function demonstrates the best throughput performance among the three methods. fig. 9 presents a comparison of collision rates between the beb algorithm and the reward functions by eqs. (11) and (13) for ddpg, with 10 nodes. the ddpg agents using eq. (13) can increase the overall network throughput by sacrificing a certain degree of individual throughput. in contrast, ddpg agents using eq. (11) may exhibit lower throughput performance compared to both traditional beb algorithm and ddpg agents using eq. (13). however, they are capable of minimizing collision rates by increasing the cw. however, unlike the other two methods, beb cannot adjust the cw based on the observed collision rates in the overall network, resulting in the poorest collision rate performance among the three. therefore, based on the experimental results in fig. 9, it can be observed that ddpg agents using eq. (11) are suitable for scenarios where collision rates are critical, but high throughput is not required, such as simple iot devices operating in sensing environments, etc. fig. 10 throughput comparison of different priority clients fig. 11 contention window of different priorities clients 270 advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 fig. 10 and fig. 11 compare throughput and cw between high-priority and low-priority nodes using eqs. (11) and (13) as reward functions for ddpg, respectively, with 10 nodes, alongside the beb algorithm. it is observed that both the ddpg based methods, after sufficient training, can narrow the throughput gap between high-priority and low-priority nodes to match the expectations of the system. in contrast, the traditional beb algorithm fails to achieve such a result. the experimental results in fig. 10 further confirm that the proposed method in this study effectively provides differentiated transmission services for different priority levels of customers. 4.4. ddpg experimental performance fig. 12 actor loss value with eq. (11) and eq. (13) fig. 13 critic loss value with eq. (11) and eq. (13) fig. 12 and fig. 13 manifest the loss values of the actor and critic, respectively, when using eqs. (11) and (13) as reward functions for ddpg. although ddpg agents using eq. (11) exhibit poor throughput performance, this method enables the actor to converge effectively. on the other hand, while eq. (13) can achieve high q-values and improve overall throughput performance, the loss function of the actor in ddpg prevents the neural network of the actor from convergence throughout advances in technology innovation, vol. 9, no. 4, 2024, pp. 257-272 271 the training process. this issue of actor non-convergence, despite the improvements in throughput, remains a significant challenge. therefore, future research will focus on updating the drl model to mitigate actor interference factors and enhance network performance in more complex scenarios. the experimental results manifest that the proposed drl approach outperforms the traditional beb algorithm concerning throughput and collision rates. additionally, it offers differentiated transmission quality for different priorities. 5. conclusions this paper proposes differentiated transmission services for nodes with different priorities in a wireless network scenario. given such an appeal, therefore, the paper leverages drl, specifically the ddpg technique, integrated into the ap to provide different qos for nodes with different priorities. according to experimental results, the proposed method significantly outperforms the traditional beb algorithm apropos the performance. moreover, the throughput of nodes is managed to control with different priorities within the expected error range specified in the paper. the proposed method addresses the common issue in wireless networks, where collisions hinder clients from achieving their respective transmission quality. despite these advancements, the precise control over throughput can yet be improved due to wireless network interference. future work will involve considering more factors related to network interference to improve throughput control accuracy and referencing recent methods to validate the performance of the proposed approach. acknowledgments this work was partially supported by the national science and technology council, taiwan, under grant no. nstc 1122221-e-507-002. conflicts of interest the authors declare no conflict of interest. references [1] t. p. lillicrap, j. j. hunt, a. pritzel, n. heess, t. erez, y. tassa, et al., “continuous control with deep reinforcement learning,” https://doi.org/10.48550/arxiv.1509.02971, september 09, 2015. 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[20] c. h. ke and l. astuti, “applying multi-agent deep reinforcement learning for contention window optimization to enhance wireless network performance,” ict express, vol. 9, no. 5, pp. 776-782, october 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 5-v8n1(2023)-aiti#9488(59-72).docx advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 skin lesion classification towards melanoma detection using efficientnetb3 saumya salian*, sudhir sawarkar department of computer engineering, datta meghe college of engineering, mumbai university, mumbai, india received 16 february 2022; received in revised form 27 april 2022; accepted 01 may 2022 doi: https://doi.org/10.46604/aiti.2023.9488 abstract the rise of incidences of melanoma skin cancer is a global health problem. skin cancer, if diagnosed at an early stage, enhances the chances of a patient’s survival. building an automated and effective melanoma classification system is the need of the hour. in this paper, an automated computer-based diagnostic system for melanoma skin lesion classification is presented using fine-tuned efficientnetb3 model over isic 2017 dataset. to improve classification results, an automated image pre-processing phase is incorporated in this study, it can effectively remove noise artifacts such as hair structures and ink markers from dermoscopic images. comparative analyses of various advanced models like resnet50, inceptionv3, inceptionresnetv2, and efficientnetb0-b2 are conducted to corroborate the performance of the proposed model. the proposed system also addressed the issue of model overfitting and achieved a precision of 88.00%, an accuracy of 88.13%, recall of 88%, and f1-score of 88%. keywords: malignant, skin lesion, deep learning, classification 1. introduction malignant skin cancer is wreaked due to anomalous expansion of melanocyte skin cells and causing tumors to form. tumors can be malignant or benign in nature. malignant tumors are a threat to human life. skin cancer generally occurs in skin that is exposed to sunlight. the high threat factor causing any type of skin cancer is exposure to natural or artificial ultraviolet light. out of 100 different types of cancer, skin cancer is considered the most prevalent and lethal category of cancer worldwide. in america, more than 9500 people are detected with skin cancer every day [1]. the number of detected skin cancer cases gradually increased to 44 percent from 2011 to 2021. according to national cancer institute (nih), around 106110 skin melanoma cases are estimated in 2022 [2]. medical experts like dermatologists examine skin lesions using a special magnifying lens known as dermatoscopy [2]. other imaging tests like ct scans, x-ray, and mri are also used to understand the metastases of pigmented skin cells. visual examination of skin lesions using dermatoscopy is a method followed by medical experts, and its prognosis usually relies on their experience. skin cancer, if discovered at a preliminary stage, will increase the survival rate among the patients. hence, it is vital to build a diagnostic system based on a deep learning network to detect malignant categories of skin cancer. building a computer-based diagnostic system will support medical practitioners to take advantage of technological overtures and help them to have a second opinion. since 2015, several deep learning architectures have been explored to build an automated diagnostic system that is forced to play a fundamental contribution in the timely discovery of malignant cancer [3]. convolutional neural network (cnn) model serves a significant part in medical image analysis. with diversified cnn architectures, it becomes arduous to select the apposite model for melanoma classification. choosing the right model will aid in developing an accurate melanoma skin lesion classification model. * corresponding author. e-mail address: srs.cm.dmce@gmail.com advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 60 transfer learning is an approach to utilizing the learning acquired by a model that is trained and built on a peculiar target and constructs a solution for a similar target. most of the pre-trained models are trained over the imagenet dataset. imagenet consists of over 15 million diverse labeled images with 1000 classes. fine-tuning pre-trained models is a prerequisite to adjusting these models to the target domain of malignant and benign lesion classification. the fundamental weights of the pretrained models are fine-tuned to adapt to the two-class classification task. many of the research papers addressed the problem of noise artifacts like the presence of hair, low contrast images, etc. very few articles addressed the issue of ink markers in lesion images. when building deep learning models, these ink markings may be mistaken for skin lesions and result in incorrect interpretations. in the proposed model, an automated image preprocessing method is employed that effectively eliminates both surgical ink markers and hair artifacts from the isic 2017 dataset. in this work, a deep learning-based, fine-tuned efficientnetb3 skin lesion classification model is proposed that classifies lesion images into malignant and benign classes. to improve model performance and reduce model overfitting, various data augmentation methods along with global average pooling gap) and a fully connected classification layer using softmax are incorporated into the proposed model. in this paper, an experimental evaluation of the proposed approach with other advanced models is carried out to review the potency of the proposed model. all the experimental analyses are carried out on isic 2017 dataset [4]. evaluation metrics like f1-score, accuracy, recall, and precision are computed. empirical findings testify to the efficiency of the proposed model in comparison to other pre-trained models and also deliver favorable outcomes which address the problem of model overfitting. the contribution of the work is listed below: (1) an automated image preprocessing model that removes noise artifacts like thin and thick hair structures and surgical ink markers from lesion images is presented in this study. (2) fine-tuned efficientnetb3 deep learning model is proposed to build an efficient computer-based diagnostic system for improved melanoma classification. (3) to achieve better accuracy and overcome the drawback of model overfitting, data augmentation techniques are employed, and a custom layer of gap is exerted over the training and testing phase. (4) to review the efficacy of the proposed design, comparative experimental analyses with other pre-trained deep learning models are carried out. the paper is illustrated in the following way, related recent works are stated in section 2, and a detailed explanation of the proposed methodology is described in section 3. experimental results and analysis are outlined in section 4, and the paper is inferred in section 5. 2. related work naronglerdrit et al. [5], offered an experimental study of diverse pre-trained transfer learning models for the classification of malignant skin lesions. using various pre-trained models, the authors carried out tasks like pre-processing (hair removal), lesion segmentation, batch normalization, and melanoma classification. the experimental analyses noted that resnet-101 achieved better sensitivity (recall) of 85.18% and accuracy of 97.12%. siddique et al. [6], furnished an image segmentation model attributed to the deep learning u-net framework along with a pre-trained efficientnet model. to enhance gradient learning and build a deeper u-net model, residual connection and recurrent feedback with efficientnet as an encoder was proposed. the proposed model achieved higher segmentation performance with a jaccard index of 95.34% and a dice coefficient of 88.62%. advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 61 chaturvedi et al. [7], furnished a skin cancer classification method using mobilenet. experiments were carried out on the ham10000 dataset, and pre-processing approaches like image rescaling and data augmentation were applied to the dataset. the mobilenet model achieved an overall accuracy of 83.15%, top2 accuracy of 91.36%, and top3 accuracy of 95.84%. the precision, recall, and f1-score of the model were 89%, 83%, and 83%, respectively. zhang [8], presented the efficientnet-b6 model for melanoma detection on the isic dataset. to assess model performance, the proposed model was compared with other standard models like vgg16 and vgg19. training and testing of the model were done for 22 epochs with a batch size of 32. efficientnet-b6 obtained an auc-roc score of 91.7, whereas vgg16 and vgg19 achieved a score of 89.1% and 90.2%, respectively. zhang and wang [9], proposed a densenet201-based melanoma recognition model for lesion images. all the investigations were carried out on the isic dataset from the kaggle challenge. training of the proposed model was carried out for 20 epochs with a batch size of 8 using adam optimizer and a learning rate of le-4. densenet201 model performance was compared with vgg16 and resnet50 over the auc-roc score. densenet201 achieved a better auc-roc score of 92.5 as compared to vgg16 and resnet50. ashim et al. [10], reviewed diverse pre-trained models such as vgg16, resnet50, efficientnet, densenet, and xception for lesion classification over the kaggle dataset. the analyses were carried out on only 660 images of skin lesions, including 360 of class benign and 300 of type malignant. to handle the low precision problem, data augmentation techniques like rotation, crop, compression, brightness, and contrast were applied during the training of the model. from the analyses, resnet50 furnished better results with a training accuracy of 88.61%, whereas efficientnetb0 furnished a training accuracy of 78.41%. chen et al. [11], proposed an efficientnetb1-based deep learning-based model using the cyclegan data augmentation technique to boost skin lesion classification accuracy. cyclegan approach aided in creating additional training images with labeled information and helped in saving costs in manual labeling. efficientnet-b1 with cyclegan data augmentation accomplished an accuracy of 94.5%. le et al. [12], exhibited a deep learning framework that classifies skin lesions into seven different classes. the authors carried out the training and testing of the network on the ham10000 dataset by removing duplicate images from the dataset. to yield better performance, the resnet50 classifier model architecture was modified by adding an average pooling and a dropout layer of 0.5, along with fine-tuning their weights. the proposed resnet model achieved an average accuracy of 93%, precision of 81%, recall, and f1-score of 80%, which outperformed other base models like vgg16, efficientnetb1, and mobilenet. manzo and pellino [13], presented an ensemble deep learning architecture with a transfer learning approach to extract features from images. imbalance class datasets were addressed for the task of classification of melanoma. pre-trained models, namely resnet-50, alexnet, and googlenet were adopted to extract features from the med-node dataset, which achieved an accuracy of 0.90. multiple image representations were designed to extract features built on a deep neural network for the correct classification of a melanoma lesion. kadampur and riyaee [14], gave a cloud deep neural learning framework to predict skin cancer with improved accuracy. deep learning studio (dls) provided a menu-driven option to construct suitable higher convolutional neural networks with deep layers such as normalization, pooling, dropout, and flattening. a comparative assessment of the proposed model with diverse pre-trained models like resnet, densenet, squeezenet, and inceptionnet was performed on the ham10000 dataset. the proposed model performed better with an area under the curve value of 0.99. acosta et al. [15], reviewed a diverse list of state-of-art methods for melanoma classification over the isic challenge 2017 dataset. the proposed model incorporated the resnet152 model with various data augmentation techniques like rotation, advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 62 random flip, random zoom, and contrast enhancement. the resnet152 model was compared with 20 other methods proposed by other researchers over isic 2017 dataset and achieved the highest accuracy of 87.2%, sensitivity of 82%, and f1-score of 84.8%. rezaoana et al. [16], proposed a convolution neural network (cnn) model using the transfer learning technique to classify the lesion images into benign and malignant classes. the proposed model was trained on the kaggle isic dataset and various augmentation techniques such as shear range, horizontal flip, rotation, and image zooming. the proposed model based on parallel convolution feature blocks achieved a weighted average accuracy of 79.45%. 3. proposed methodology in this section, a detailed explanation of the proposed methodology for malignant skin lesion classification is provided. the design methodology consists of the following subsections: (1) data preprocessing, (2) data augmentation, and (3) finetuned efficientnetb3 model architecture. 3.1. dataset preprocessing all the experimental research was carried out on the isic dataset [4] available from “2017 isbi challenge on skin lesion analysis towards melanoma detection”. the dataset comprised 3297 images of benign and malignant skin lesions. lesion images in the isic dataset are in rgb color space with varied pixel sizes in the range 540×722 and 4499×6748. fig. 1 shows the malignant skin lesion from the isic dataset. the dataset images consisted of noise artifacts like surgical ink markers, and the presence of hair that impedes accurate lesion classification. the images are resized into 224×224 pixels for compatibility with pre-trained neural networks during the model training and testing phase. the images were down-sampled since most of the pre-trained deep learning networks take input images of fixed resolution. by training raw images of larger sizes, neural networks will require more computing power to handle higher parameters that may lead to model overfitting. to train images faster, improve the performance of neural networks and reduce model overfitting, it is important to resize images into smaller resolutions based on the architecture of the pre-trained network. according to the study by talebi and milanfar [17], the perceptual quality of resized images is not lost while building computer vision models; instead aids in boosting the performance of the network. fig. 1 skin lesion images from the isic dataset hair artifacts in lesion images have a huge impact in building a computer-based melanoma classification system as hair structures tend to block the lesion region. color, length, and thickness of hair are some factors that need to be considered while building an automated image preprocessing system [18]. in this study, the hair artifacts removal model is designed to efficiently remove thin and thick hair noise from dermoscopy images without impacting the quality of the image. lesion images are converted from rgb color space to grayscale images using the weighted method. images in grayscale aid in identifying hair advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 63 artifacts from skin lesion images. blackhat filtering technique is applied on these grayscale lesion images, which further highlights hair noise against lighter skin backgrounds. to effectively probe the hair structures, a structuring element of elliptical shape and 13-pixel size blackhat filter is used [19]. a binary thresholding function is exerted over the blackhat image to create a hair mask that further sharpens hair structures from the background skin image. the fast marching restoration inpaint_telea method is applied to the masked image. inpaint_telea technique builds the original image without any hair noise from the masked image. fig. 2 shows the proposed hair removal process. (a) original image (b) grayscale image (c) blackhat filtered image (d) threshold image (e) hair removed fig. 2 hair removal process (a) images with ink markers (b) images without ink markers fig. 3 preprocessed image without markers clinical experts mark out suspicious skin lesions with blue or violet ink markers. these ink markings may be considered a part of skin lesions and can cause false interpretations while constructing deep learning models [20]. therefore, it is important to eliminate these ink marker artifacts from the lesion images. to effectively remove ink markers, lesion images are transmogrified into hue-saturation-value (hsv) color space that aids in color-based segmentation to capture blue or violet ink markers. to create a masked image, the inrange function is used to set up a lower and upper band of violet color, and the advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 64 morphological dilation function is used to capture ink markers from hsv images. to restore the original image from the masked image, the inpainting method is again applied which produces lesion images without ink markers. fig. 3 shows a comparison of the original image with ink markings and image after an automated model is applied to it. 3.2. data augmentation to build a good classification deep learning model, it is substantial to train the neural model with a huge volume of data. the majority of pre-trained networks are trained on imagenet, which comprises a large set of data with 1000 classes. the data augmentation approach is adapted to expand the size of the training dataset to develop an effectual melanoma lesion classification model. in the data augmentation method, training data is synthetically expanded by minor alterations to existing original data [21]. to ameliorate the functioning of the melanoma classification model and prevent overfitting of the model, data augmentation is added on top of the efficientnetb3 network. the training dataset is expanded by creating altered versions of images pertained to equivalent classes. diverse augmentation techniques like random zoom, random rotation, random flip, random shift by height, and random shift by width are applied using keras preprocessing layers like keras.layers.resizing, keras.layers.randomflip, keras.layers.rescaling and keras.layers.randomrotation to build keras sequential model. table 1 indicates various data augmentation methods. fig. 4 depicts the augmentation operation applied to lesion images. (a) random augmented image of malignant class (b) random augmented image of benign class fig. 4 random augmented images table 1 data augmentation approaches approach description random width the width of images arbitrarily shifted by 20% random rotation images arbitrarily rotated by 20% random flip images arbitrarily flipped random zoom images arbitrarily zoomed by 20% random height the height of images arbitrarily shifted by 20% 3.3. model architecture efficientnet models include a family of 8 models from b0-b7 trained over imagenet. efficientnet models are deemed as the uttermost computationally effective deep learning model that acquires top accuracy gain appertaining to the compound scaling approach. in the compound scaling approach, the size of the baseline convolution network model is expanded by scaling the network uniformly across depth, width, and resolution to the target model size [22]. fig. 5 exhibits the scaling of advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 65 the efficiennet model. efficientnet models consist of inverted residual convolutional blocks (mbconv) originally based on mobilenetv2 [23] with multiple kernel sizes of 3×3 and 5×5. the model architecture is broadened evenly through compound scaling coefficient ∅ by depth, width, and resolution in the following procedure: , , ø ø ød r wα γ β= = = (1) such that 2 2 2, 1, 1, 1 αβ γ α γ β≈ ≥ ≥ ≥ (2) where d indicates the depth of the network, r indicates the resolution of the network, w indicates the width of the network, and α, β, and γ are constants. ∅ value in eq. (1) indicates the level at which the network can be scaled up. efficientnetb0 baseline model is constructed on ∅ value of 0, w value of 1, and r value of 1. the efficientnetb3 model is established on ∅ value of 3, w value of α3, and r value of γ3. the higher value of ∅ signifies extensive resources accessible to obtain superior results. (a) scaling of baseline efficientnet model (b) compound scaling of higher model fig. 5 scaling of efficientnet fig. 6 efficientnetb3 architecture advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 66 efficientnetb3 consists of a convolution filter (conv) block with a kernel size of 3×3, an mbconv1 block with a kernel size of 3×3, and mbconv6 blocks with kernel sizes of 3×3 and 5×5. some of the mbconv6 blocks apply inverted residual connection (irc). filter kernel sizes of 3×3 and 5×5 are used in the efficientnetb3 model to extract feature maps from the input images. efficientnetb3 comprises 25 mbconv blocks differing in many characteristics such as feature maps expansion ratio, resolution, output layers kernel size, etc. mbconv1 with a kernel size of 3×3 and mconv6 with kernel sizes of 3×3 and 5×5 employ depthwise convolution along with batch normalization and activation layer. additionally, layers of dropout and skip connection are integrated with mbconv6 3×3, and mbconv6 5×5 but omitted in mbconv1. in comparison to the baseline efficientnetb0 model, eficientnetb3 comprises a larger network that helps to pull out detailed features which can infer better on new missions. the efficientnetb3 model has the advantage of a broader network that abstracts superlative features and patterns employed for melanoma classification. fig. 6 shows efficientnetb3 architecture. fig. 7 shows architecture of proposed methodology. fig. 7 proposed methodology architecture 4. results the proposed model amalgamated data preprocessing and augmentation techniques, along with fine-tuned gap layer and softmax output layer for classification, to improve the efficiency of lesion classification results. the isic dataset was distributed in an 80:20 ratio of training and testing batches. the training set consisted of 2637 images, and the testing set consisted of 660 images. all experiments are performed on a google colab notebook that furnished usage to nvidia tesla gpu of size 12gb k80 smi 460.32.03. all the models are compiled employing the adam optimization algorithm with a learning rate of 0.001. the models have been trained for 35 epochs holding a batch size of 32. the images are trained batchwise and approximately take 29 to 33 seconds to train per epoch. recall, confusion matrix, precision, accuracy, and f1-score are computed to probe model potency [24]. these metrics are calculated on true positive (tp), true negative (tn), false positive (fp), and false negative (fn) [25]. (1) true positive (tp)the correct class is positive and the predicted class is positive. (2) false positive (fp)the correct class is negative and the predicted class is positive. (3) true negative (tn)the correct class is negative and the predicted class is negative. (4) false negative (fn)the correct class is positive and the predicted class is negative. accuracy: it is an evaluation metric that finds the model’s performance across all classes. it is a fraction of the sum of correct class predictions to the sum of total predictions. advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 67 tp tn accuracy fn tn fp tp + = + + + (3) precision: it computes the ratio of total positive identification over the sum of total positive identification that is either categorized correctly or incorrectly. tp precision fp tp = + (4) recall: it computes the ratio of total positive identification over the sum of total positive input samples categorized precisely. tp recall tp fn = + (5) f1-score: it is computed from precision and recall metrics that calculate the model’s accuracy by giving higher importance to false negatives and false positives. 1 2 2 tp f score fn fp tp − = + + (6) validation of the effectiveness of the proposed framework is accomplished in two approaches. primarily, four models are compiled to analyze the outcomes of various layers of efficientnetb3 network architecture in the first approach. the training of these models is carried out on the preprocessed dataset, and the fully connected (fc) last layer of classification is fine-tuned to adjust to the binary (benign and malignant) categorization of the isic 2017 dataset. model 1 depicts the baseline efficientnetb3 model with no augmentation and no gap layer. model 2 refers to efficientnetb3 with augmentation techniques applied to the network with no gap layer. model 3 depicts the gap layer added to efficientnetb3 network with no augmentation techniques applied. model 4 refers to the fine-tuned proposed architecture presented in this study. table 2 presents the methodology of each model. table 2 approach of models approach preprocessing augment gap fc model 1 ✓ ✕ ✕ ✓ model 2 ✓ ✓ ✕ ✓ model 3 ✓ ✕ ✓ ✓ model 4 (proposed model) ✓ ✓ ✓ ✓ table 3 result summary of models approach recall accuracy f1-score precision model 1 58.00 56.97 58.00 58.00 model 2 57.00 56.67 53.00 56.00 model 3 86.00 85.75 85.00 86.00 model 4 (proposed model) 88.00 88.13 88.00 88.00 table 3 provides the result analyses of the above models on the isic dataset. from table 3, it can be found that model 1 achieved an accuracy of 56.97%, a precision of 58%, which indicates that the pre-trained baseline efficientnetb3 model suffered from an overfitting problem. fig. 8 shows the accuracy curve of model 1. model 2, with augmentation techniques applied to the network, gave poor results with an accuracy of 56.67% as compared to model 1. fig. 9 shows the accuracy curve of model 2. model 3 gave an accuracy of 85.75%, which indicated that the gap layer boosted the performance of the efficientnetb3 network. fig. 10 shows the accuracy curve of model 3. model 3 suffered from an overfitting problem, although the model was performing well on training data. whereas for testing data, the model performed comparatively less, as observed advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 68 in fig. 10, which represents the accuracy curve of model 3. model 4 achieved the best results with an accuracy of 88.13% and also acquired a balanced precision value of 88%, which demonstrates that the proposed framework overcomes and handles the problem of model overfitting. fig. 11 represents the accuracy curve of model 4 (proposed framework). fig. 8 accuracy curve of model 1 fig. 9 accuracy curve of model 2 fig. 10 accuracy curve of model 3 fig. 11 accuracy curve of model 4 in the second approach, for evaluation of the proposed model, its result is compared to other advanced pre-trained models, namely inceptionresnetv2 [26], resnet50 [27], efficientnet b0-b2 [22], and inceptionv3 [28] over the isic dataset for the melanoma classification task. to investigate the potentiality of the proposed model, it is compared with advanced networks like inceptionresnetv2, resnet50, inceptionv3, and efficientnetb0-b2 models. these advanced neural models are pretrained on the imagenet dataset that outputs feature vectors for 1000 categories. therefore, it is important to adjust these models on the target isic dataset comprising only two types of benign and malignant classes. to fit these models over the isic dataset, the last classification layer of these models is altered using the softmax layer with two classes. table 4 comparative analyses of various evaluation metrics approach dataset recall accuracy f1-score precision proposed model isic 2017 88.00 88.13 88.00 88.00 inceptionv3 isic 2017 83.00 82.73 83.00 83.00 efficientnetb0 isic 2017 60.00 60.15 59.00 65.00 resnet50 isic 2017 85.00 84.85 85.00 85.00 efficientnetb1 isic 2017 56.00 55.75 55.00 55.00 efficientnetb2 isic 2017 66.00 58.48 66.00 66.00 inceptionresnetv2 isic 2017 83.00 83.33 83.00 83.00 advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 69 table 4 indicates the comparative metrics assessment of the proposed model with other advanced pre-trained networks. the proposed design excelled over other models and gave an accuracy of 88.13%, recall of 88%, precision of 88%, and f1score of 88%. resnet50 model achieved an accuracy of 84.85% and performed well compared to inceptionv3, inceptionresnetv2, and efficientnetb0-b2 models. fig. 12 shows the accuracy curve of resnet50. efficientnetb1 achieved the lowest accuracy of 55.75%, with an f1-score of 55%. fig. 13 shows the accuracy curve of inceptionresnetv2. inceptionv3, efficientnetb0, efficientnetb2 and inceptionresnetv2 achieved an accuracy of 82.73%, 60.15%, 58.48%, and 83.33% respectively. confusion matrices of each model are also examined to check false negative and false positive class counts. fig. 14 depicts the confusion matrix of fine-tuned proposed model in comparison with inceptionv3, resnet50, inceptionresnetv2. fig. 12 resnet50 accuracy curve fig. 13 inceptionresnetv2 accuracy curve (a) proposed model confusion matrix (b) inceptionv3 model confusion matrix (c) inceptionresnetv2 model confusion matrix (d) resnet50 model confusion matrix fig. 14 confusion matrix comparison advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 70 5. discussion to further validate the efficacy of the proposed model, a comparative analysis is carried out with other state-of-art methods. table 5 provides a comparative evaluation of the proposed model with other methods. the experimental study provided by naronglerdrit et al. [5] over the ham10000 dataset provided an accuracy of 97.12%, but less recall value of 85.18% using the resnet-101 deep learning model indicates the model suffers from the problem of overfitting. categorical accuracy of the mobilenet model with data augmentation proposed by chaturvedi et al. [7] provided an overall accuracy of 83.15%, precision of 89%, recall of 83%, and f1-score of 83% only. ashim et al. [10], presented an experimental analysis of pre-trained networks such as vgg16, resnet50, efficientnet, densenet, and xception for melanoma classification over the kaggle dataset consisting of only 660 images of benign and malignant classes. xception, efficientnetb0, densenet, vgg16, and resnet models furnished training accuracy of 78.41, 78.44%, 81.94%, 72.37%, and 88.61% respectively. le et al. [12], presented a resnet50-based deep learning classifier over the ham10000 dataset and achieved an average accuracy of 93%, precision of 81%, recall, and f1-score of 80% only. the low value of other evaluation metrics indicates that the model proposed by [12] suffers from model overfitting problem. acosta et al. [15], proposed a deep learning model based on resnet152 and also presented a comparison of 20 other state-of-art models trained and tested over the isic 2017 dataset. according to the study carried out by [15], the proposed resnet152 achieved the highest accuracy of 87.2%, the sensitivity of 82%, and the f1-score of 84.8%. rezaoana et al. [16] performed an exploratory analysis of the proposed cnn model with other networks like vgg-16 and vgg-19. the proposed approach by [16] achieved an f1-score of 76.92%, precision of 76.16%, and recall of 78.15%. it can be noticed from table 5 that the proposed efficientnetb3 model accomplished better results compared to other methods concerning metrics such as recall, precision, and f1-score. these metrics are consistent with the accuracy of the proposed model and thus handle the problem of model overfitting. table 5 comparative analyses of the proposed methodology with other methods reference approach dataset accuracy recall f1-score precision proposed model efficientnetb3 isic 2017 88.13 88.00 88.00 88.00 naronglerdrit et al. [5] resnet-101 ham10000 97.12 85.18 chaturvedi et al. [7] mobilenet ham10000 83.15 83.00 83.00 89.00 ashim et al. [10] efficientnetb0 kaggle 78.41 resnet 88.61 le et al. [12] resnet50 ham10000 93.00 81.00 80.00 80.00 acosta et al. [15] resnet152 isic 2017 87.20 82.00 84.80 rezaoana et al. [16] proposed cnn kaggle isic 79.45 78.15 76.92 76.16 vgg-16 69.57 68.89 67.77 65.67 vgg-19 71.19 69.45 68.95 68.54 6. conclusion in this study, an automated computer-aided diagnostic system using fine-tuned efficientnetb3 deep neural model for melanoma classification is proposed that efficiently classifies lesion images into benign and malignant classes. skeptical skin lesions are routinely marked with surgical ink markers, and the presence of hair artifacts often influences the classification analysis. an automated preprocessing model is employed, and it can effectively remove surgical ink markers and hair artifacts. a broad variety of data augmentation schemes are utilized to prevent overfitting and improve the overall performance of the proposed model. the weights of efficientnetb3 models are fine-tuned by appending an additional layer of gap, and softmax layer to adjust to the isic 2017 dataset. extensive experimental analyses are carried out with other popular pre-trained cnn networks like inceptionresnetv2, inceptionv3, efficientnetb0-b2, and resnet50. the analytic results indicate that the proposed model achieves robust and higher classification results. empirical findings demonstrated the effectiveness of the proposed model in the malignant melanoma classification task. advances in technology innovation, vol. 8, no. 1, 2023, pp. 59-72 71 the future study might be to employ the proposed model on diverse repositories of isic datasets, such as the ham10000 dataset, isic 2019, etc., consisting of more than 10000 images of pigmented skin lesions. it can also include testing the proposed model on multi-labeled lesion classification dataset and building fine-grained neural networks for melanoma classification with improved accuracy. the study can be extended to develop an efficient lightweight smartphone application integrating the proposed methodology for skin lesion classification with a deep learning-based segmentation model. conflicts of interest the authors declare no conflict of interest. statement of ethical approval for this type of study, statement of human rights is not required. statement of informed consent for this type of study, informed consent is not required. references [1] “cancer facts and figures 2021,” https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-andstatistics/annual-cancer-facts-and-figures/2021/cancer-facts-and-figures-2021.html, december 01, 2021. 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[26] c. szegedy, s. ioffe, v. vanhoucke, and a. a. alemi, “inception-v4, inception-resnet and the impact of residual connections on learning,” 31st aaai conference on artificial intelligence (aaai'17), pp. 4278-4284, february 2017. [27] k. he, x. zhang, s. ren, and j. sun, “deep residual learning for image recognition,” ieee conference on computer vision and pattern recognition (cvpr), pp. 770-778, june 2016. [28] c. szegedy, v. vanhoucke, s. ioffe, j. shlens, and z. wojna, “rethinking the inception architecture for computer vision,” proceedings of the ieee conference on computer vision and pattern recognition (cvpr), pp. 2818-2826, june 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v10n1(2025)-aiti#14114(15-28).docx advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 english language proofreader: chih-wei chang a novel data transmission model using hybrid encryption scheme for preserving data integrity riyaz fathima abdul*, saravanan arumugam department of computer science, sree saraswathi thyagaraja college, tamil nadu, india received 09 august 2024; received in revised form 28 september 2024; accepted 07 october 2024 doi: https://doi.org/10.46604/aiti.2024.14114 abstract the objective of the study is to introduce a novel hybrid encryption scheme, combining both symmetric and asymmetric encryptions with a data shuffling mechanism, to enhance data obfuscation and encryption security. the approach uses rsa for asymmetric encryption and chacha20-poly1305 for symmetric encryption. to increase the complexity, an additional phase involves reorganizing the rsa-encrypted data blocks. furthermore, symmetric key generation using the key derivation function is employed to generate the key for symmetric encryption through an asymmetric private key. decryption entails reversing these procedures. this model significantly enhances security through an additional shuffling step, measured by performance metrics like encryption and decryption times, throughput rate, and the avalanche effect. the method, despite increasing execution time compared to symmetric models, yields comparable results for asymmetric models and ensures robustness. the proposed method outperforms traditional methods regarding resistance to cryptanalytic attacks, including chosen-plaintext and pattern analysis attacks. keywords: hybrid encryption, cryptographic security, rsa, chacha20-poly1305, data shuffling 1. introduction the widespread adoption of cloud computing has radically transformed data processing, storage, and access in the current digital world [1]. businesses across multifarious sectors and other private and public organizations have been heavily relying on cloud services to manage their infrastructure, applications, and data. the growing reliance on cloud computing offers benefits like data access, storage, and sharing. on the other hand, however, cloud computing can raise privacy and security concerns, incurring potentially increased security threats and data breaches [2]. thus, securing sensitive information and guaranteeing privacy against unauthorized access, security breaches, and other advanced cyber threats requires ensuring the confidentiality, integrity, and availability of data in a cloud environment [3-4]. specifically, encryption is crucial for maintaining the confidentiality and integrity of data in the cloud. to ensure the safety of sensitive information while being communicated or stored, conventional data encryption methods, such as symmetric and asymmetric encryption, have been widely used for a considerable amount of time [5]. several types of symmetric encryption, including advanced encryption standard (aes), data encryption standard (des), triple des, blowfish, twofish, rivest cipher 4 (rc4), and chacha20, use the same key for both encryption and decryption. such a phenomenon ensures data protection expeditiously and securely. asymmetric encryption methods, on the other hand, use public-private key pairs to effectuate secure communication, and popular methods include rivest-shamir-adleman (rsa), * corresponding author. e-mail address: riyazfathimarf@gmail.com advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 16 elliptic curve cryptography (ecc), digital signature algorithms (dsa), and elgamal encryption. concerning the practices, researchers utilized the aforementioned methods directly or with some modifications to enhance their functionality on the cloud [6-8]. however, a panoply of limitations and challenges to encryption methods emerges, particularly in cloud environments, despite their critical role in data security. the distributed infrastructure, virtualization, multi-tenancy, and dynamic nature that define cloud computing introduce particular difficulties for data transmission security [9]. well-established cryptographic methods face challenges such as the need for effective key management, defense against complex cyber threats, and maintaining data integrity during transmission. thus, an urgent need for innovative solutions is presented to address data security concerns without compromising efficiency or scalability to the growing amount and diversity of data transmitted in cloud systems. recently, researchers and practitioners in the field of cloud security have begun to focus on hybrid encryption schemes as a potential and feasible solution to cloud security in a distributed environment [10-11]. to overcome the weaknesses of each method, the hybrid encryption methods integrate the key strengths of both symmetric and asymmetric encryption. hence, hybrid schemes often combine the two types of encryption methods to facilitate the transfer of data to and from the cloud in a secure, efficient, and scalable way. the most commonly suggested hybrid encryption schemes are combinations of aes with the rsa algorithm [12-13] and aes with ecc [14]. apropos of confidentiality, authentication, and security, researchers proposed a three-phase hybrid cryptographic (tphc) algorithm combining aes, des, and rsa [15]. a study utilized aes, proxy re-encryption, and honey encryption to improve data privacy and authentication, necessitating further security and efficiency analysis, as introduced in dutta et al. [16]. moreover, a twofish encryption algorithm with manifold optimization techniques was also suggested, including bald eagle pelican optimization [17] and ant lion optimization [18]. recently, chacha20 and secure hash algorithm 3 (sha3)-based hashing were proposed to mitigate threats in cloud computing, requiring further investigation into vulnerabilities [19]. notwithstanding significant advancements in hybrid encryption systems, a research gap remains in addressing the challenge of maintaining data integrity during transmission [9, 20]. existing research primarily emphasizes confidentiality concerns, often overlooking the critical role of data integrity. trust, regulatory compliance, and prevention of unauthorized modifications all depend on data integrity, which ensures the quality and consistency of information. this highlights the need for new hybrid encryption schemes that prioritize data integrity during cloud data transmission. the study addresses this need by developing advanced solutions to enhance data security in cloud environments, thereby eliciting the limitations of traditional encryption methods, and improving both data protection and integrity. this study aims to develop and evaluate a new hybrid encryption method to protect data in cloud environments, considering the difficulties, challenges, and gaps in the existing literature. the primary objective of the study is to design a hybrid encryption model that combines symmetric and asymmetric techniques and evaluate its performance and effectiveness in preserving data integrity during transmission. the findings of the study indicate that the proposed model significantly enhances cloud data security by integrating advanced encryption techniques. it is ideal for applications demanding stringent data protection, such as sensitive data storage, secure communications, and regulatory compliance, despite its higher execution time. the paper is structured as follows: section 2 explains the framework of the proposed hybrid encryption model. subsequently, section 3 outlines the experimental setup and the performance metrics used in assessing the model. furthermore, section 4 presents the results from data integrity assessments, performance evaluations, and security analysis against multitudinous attacks. finally, section 5 concludes the research findings and suggests future research directions in the field of cloud security and encryption. advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 17 2. proposed methodology to enhance data security during transmission in cloud computing environments, the proposed hybrid encryption scheme integrates established symmetric and asymmetric algorithms into a novel hybrid model. the scheme integrates established algorithms into a unified hybrid model, rendering comprehensive protection against cryptographic attacks and ensuring data protection even if one layer is compromised. fig. 1 depicts the two main phases of this model: encryption and decryption, each involving several steps. fig. 1 overall framework of the proposed data transmission model initially, the necessary parameters and keys are generated for the proposed model. the first phase of hybrid encryption commences by encrypting the input data using asymmetric encryption, producing the initial ciphertext. such a ciphertext is shuffled to improve data confidentiality during transmission thereafter. finally, symmetric encryption is applied to the shuffled data, and the resulting encrypted text is transmitted or stored in the cloud. the second phase, on the receiver side, initiates with the symmetric decryption of the data. the symmetrically decrypted data is subsequently subjected to a hybrid data reshuffling step. finally, asymmetric decryption is performed on the reshuffled data to recover the plaintext. the asymmetric encryption algorithm encrypts the data using a public key and decrypts it using a private key, yielding robust encryption and ensuring confidentiality. based on this mechanism, the authorized parties are permitted to access the plain text, and the unauthorized ones will be excluded. the hybrid data shuffling randomizes the order of encrypted data, furnishing an additional layer of randomness and security with data unpredictability. moreover, symmetric encryption enhances security by ensuring data confidentiality, integrity, and detection of modifications or tampering while being more efficient, faster, and requiring less computational complexity than asymmetric encryption. therefore, by combining asymmetric and symmetric encryption, the model renders more resilient to various cryptographic attacks. despite compromising one layer of defense, the other layer continues to proffer additional protection. the sub-sections below visualize a comprehensive explanation of the encryption and decryption phases. 2.1. hybrid data encryption phase fig. 2 graphically presents the overall workflow for the encryption phase. the proposed hybrid data transmission model uses unicode, a character encoding scheme, to accurately represent plain text as numerical values, preserving its original information. this model deploys the unicode transformation format (utf-8), 8-bit code units to represent characters. 2.1.1 asymmetric data encryption once the plain text is encoded (m), asymmetric encryption is carried out. the proposed model employs the rsa algorithm for asymmetric encryption, due to its strong security with large keys, proven reliability, efficient performance, and robust resistance against brute-force attacks. initially, the parameters and keys are generated for the asymmetric encryption. advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 18 regarding the large primes p and q, n and ���� are calculated as n = p × q and ���� = (p − 1) × (q − 1). the encryption component e is chosen such that it is relatively prime to ����, and the decryption component d is computed such that d is the modular multiplicative inverse of e modulo ����, represented as d ≡ e-1 mod ����. as a result, the public key comprises (n, e), and the private key is the decryption component d. finally, the output of the asymmetric encryption step is the ciphertext (c1) computed, as presented in: 1asymmetricencrypteddata mod= ec m n (1) where m represents the plaintext message, e is the encryption component, n is a product of 2 large primes, and c1 is the encrypted text. in the next stage, this ciphertext is used as input for further processing. fig. 2 workflow for the encryption phase 2.1.2. hybrid data shuffling the proposed model utilizes hybrid shuffling, enhancing randomness, unpredictability, and security in cryptographic procedures while maintaining integrity and confidentiality through the efficiency and simplicity of the inside-out algorithm. the algorithm encompasses the following steps: (1) the array is initially partitioned into two sections (2) the inside-out procedure is applied to shuffle each partition, where each element is iterated over, a random index is selected, and the element is exchanged with the one at that index (3) the final shuffled array is created by combining the shuffled partitions thus, it accepts input from the previous step (c1) and shuffles the data, producing the permuted data (c1'), as mentioned in: 1 1 permuteddata ' datashuffle( )=c c (2) the approach optimizes computational performance by partitioning the array and shuffling each partition independently, ensuring quicker operations and a more uniform distribution of elements. this hybrid technique enhances the balance between computational complexity and randomness, extending a veritable cornucopia of applications where both speed and randomness are critical factors in achieving optimal performance and security. algorithm 1 explains the pseudocode for the hybrid shuffling algorithm. advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 19 algorithm 1: hybrid shuffling algorithm input: c1 – ciphertext to be shuffled output: shuffled array c1' procedure hybridshuffling(array c1) begin //determine the length of the array and partition them n = len(c1) lpartition = c1[0:n/2]; rpartition = c1[n/2:n] //shuffle each partition independently for each element a in lpartition //select a random index j such that 0 ≤ j < index of a. j = random.randint(0, c1.index(a) 1) swap a and c1[j] for each element b in rpartition //select a random index j such that index of b ≤ j < len(rpartition) j = random.randint(c1.index(b), len(c) 1) swap b and c1[j] //combine the shuffled partitions c1' = lpartition + rpartition return shuffledarray c1'. end procedure 2.1.3. symmetric key generation using key derivation function the algorithm uses a key derivation function (kdf) to securely derive symmetric keys from asymmetric key pairs, simplifying key management, reducing storage and distribution complexity, and increasing efficiency and security. the model utilizes the hash-based message authentication code (hmac)-based kdf (hkdf), a robust and efficient cryptographic method known for its flexibility. the system uses hmac and a secure hash function to generate a pseudorandom key (prk), ensuring the key’s integrity and authenticity using sha-256. the hkdf process can be apportioned in the following steps: (1) input parameters: the rsa private key (d), a randomly generated salt (s), and the desired key length (lkey) (2) prk generation: an hmac function is applied using sha-256 as the hash function. this function takes the rsa private key and salt as inputs to produce a prk (3) key expansion: the prk is then expanded to generate a symmetric key of 256 bits using hkdf’s key expansion algorithm thus, the model applies an hmac function, which includes private key d and salt s, to generate a prk, then expands it to the desired length (skey) while maintaining its security properties, as outlined in: ( )symmetrickey =hmac_sha-256 ,keys d s (3) algorithm 2: hmac-based key derivation function input: rsa private key (d), a randomly generated salt s, key length lkey output: skey symmetric key of length 256 bits procedure hkdf (rsa private key d, salt s, key length lkey) begin //calculate the hmac using sha-256 as the hash function hmac_digest = hmac_sha-256 (private key d, salt s) //extract the pseudorandom key (prk) prk = hash_digest //expand the pseudorandom key to the desired output using the key expansion algorithm skey = hkdf_expand(prk, lkey) return skey end procedure advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 20 the hkdf algorithm enables the sender and receiver to independently generate symmetric encryption keys, improving communication without direct key transmission, and thereby enhancing security. the technique enhances cryptographic resistance by providing variability and unpredictability in key generation, while adding salt ensures unique, secure hash outputs, preventing precomputed attacks. algorithm 2 presents the algorithm pseudocode for the hmac-based kdf using sha-256. 2.1.4. symmetric data encryption after generating a symmetric key, the symmetric key encryption is applied to the shuffled data c1'. the proposed model applies chacha20-poly1305 for symmetric encryption, which combines chacha20, a stream cipher, with the poly1305 message authentication code (mac). this combination is known as authenticated encryption with additional data (aead). the chacha20 symmetric stream cipher is an efficient and secure encryption algorithm in which the data is encrypted using a key, nonce, and counter by xoring it with a stream created by chacha20. poly1305 is a secure mac that ensures the authenticity of encrypted data by converting the message and secret key into a fixed-size authenticator. concerning the function, this algorithm works as follows: (1) creating the symmetric key (skey) for encryption (2) initialing the chacha20 cipher state using the symmetric key (skey) and a nonce (n) (3) for each block of the input data (c1'), generating a chacha20 keystream and exclusive or (xor) it with the data to produce ciphertext (c2) (4) setting up the poly1305 authentication state using skey (5) processing the encrypted data blocks to generate the authentication tag (atag) for verifying data integrity (6) output the ciphertext (c2) and the authentication tag (atag) hence, the symmetric key encryption takes c1' and provides c2 as the cipher text and authentication tag atag, as shown in: 2 1symmetricencryteddata chacha20 _ poly1305 _ encrypt( ', )= keyc c s (4) chacha20-poly1305 is a method that offers confidentiality, authenticity, and integrity verification through cipher text and a cryptographic hash-based tag, offering efficiency and robust message authentication. upon decryption, the receiver computes the tag using the received cipher text and compares it with the received tags. therefore, the authenticity of the received ciphertext is confirmed if the computed and received tags match, while a non-match indicates potential tampering or modification during transmission. algorithm 3 presents the pseudocode for symmetric encryption using chacha20-poly1305. algorithm 3: chacha20-poly1305 encryption and authentication input: input text c1', symmetric encryption key skey, nonce n output: ciphertext c2, authentication tag atag procedure chacha20_poly1305_encrypt(c1', skey, n): begin state = initializestate(skey, n) //chacha20 key setup for each block in c1' //generate chacha20 keystream blocks keystreamblock = generatechacha20keystream(state) incrementnonce(n) c2 = c1' xor keystreamblock //encrypt input text with chacha20 keystream polystate = initializepoly1305state(skey) //initialize poly1305 state with key for each block in c1' //process message blocks polystate = poly1305update(polystate, block) atag = poly1305finalize(polystate) //finalize and obtain the authentication tag return (c2, atag) end procedure advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 21 2.2. hybrid data decryption phase the second phase of the proposed model is the hybrid data decryption phase. fig. 3 depicts the overall workflow for the decryption phase of the proposed data transmission model using a hybrid scheme. initially, for asymmetric encryption, the parameters and keys are generated. the n and ���� are determined for the huge prime integers p and q as follows: n = p × q and ���� = (p − 1) × (q − 1). the decryption component d is selected so that, d ≡ e-1 mod ���� and the encryption component e is determined by choosing a relative prime to ����. at this point, (n, e) and d will be the public and private keys, respectively. the private key is utilized to create the symmetric key, and the cipher text is converted into plain text sequentially. the steps are explained in the below subsections. fig. 3 workflow for the decryption phase 2.2.1. symmetric data decryption with kdf as a first step, the proposed algorithm deploys symmetric decryption, which uses the kdf to securely derive a symmetric key from asymmetric key pairs. the proposed model employs hkdf for deriving symmetric keys from shared secret keys. the method generates symmetric keys using the hmac function, which is explained in section 2.1.3. algorithm 2 explains the pseudocode, using the private key d and salt s to create prk, which expands to produce the symmetric key with a length of 256 bits thereafter. upon generating a symmetric key, the receiver applies the symmetric decryption to the inputs, such as the cipher text c2 and authentication tag atag. the algorithm works as follows: (1) the decryption process commences by setting up the chacha20 cipher state using the symmetric key (skey) and nonce (n) (2) chacha20 keystream block is generated and xored with the ciphertext to retrieve the decrypted text (c1') (3) the poly1305 authentication state is initialized using the same symmetric key (skey) (4) regarding each block of the decrypted text (c1'), the poly1305 state is updated to authenticate the data (5) after processing all blocks, the poly1305 state is finalized to produce the verified authentication tag (atag_verified) (6) the computed authentication tag (atag_verified) is compared with the received tag (atag). if they match, the decrypted text (c1') is returned. otherwise, an error message is returned, indicating that authentication failed. thus, as in the formula below, the symmetric key decryption takes c2 and atag as inputs and renders c1' as the decrypted text. algorithm 4 presents the pseudocode for symmetric decryption using chacha20-poly1305 with a symmetric key. 1 2symmetricdecrypteddata ' chacha20 _ poly1305 _ decrypt( , )= keyc c s (5) advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 22 algorithm 4: chacha20-poly1305 decryption and authentication input: ciphertext c2, authentication tag atag input text c1', symmetric decryption key skey, nonce n output: decrypted shuffled text c1' procedure chacha20_poly1305_decrypt(c2, skey, n): begin state = initializestate(skey, n) //chacha20 key setup for each block in c2 //generate chacha20 keystream blocks keystreamblock = generatechacha20keystream(state) incrementnonce(n) c1' = c2 xor keystreamblock //decrypt input text with chacha20 keystream polystate = initializepoly1305state(skey) //initialize poly1305 state with key for each block in c1' //process message blocks polystate = poly1305update(polystate, block) atag_verified = poly1305finalize(polystate) //finalize and obtain the authentication tag if atag_verified = atag then return (c1') //return decrypted text if authentication is successful else return err_msg end procedure 2.2.2. hybrid data reshuffling in the next step of the decryption phase, the proposed model applies hybrid reshuffling, which applies an inside-out algorithm. the algorithm initially partitions the array into two sections. section 2.1.2 explains the shuffling algorithm. algorithm 1 presents the pseudocode for the hybrid shuffling algorithm, which accepts input c1' and outputs c1. the algorithm initially divides the array into two halves, and then the inside-out procedure is used to shuffle each partition by randomly selecting an index for each element and exchanging it with the one at that index. finally, the shuffled partitions are combined to generate a final shuffled array. as a result, it takes the data from the previous step (c1') and shuffles it to produce the reshuffled data (c1), as specified in the formula below. the next step of the decryption phase then uses the reshuffled data as an input. 1 1 reshuffleddata datashuffle( ')=c c (6) 2.2.3. asymmetric data decryption in the next step, the asymmetric decryption is carried out using the rsa algorithm, which uses the generated private key d. thus, the asymmetric key d decrypts the reshuffled data (c1) from the previous step. as a result, the output of the asymmetric decryption step is the decoded text (m), computed as in: 1asymmetricdecrypteddata mod= d m c n (7) where n is determined for the prime integers p and q as n = p × q. as the decrypted text is obtained as encoded text, it must be decoded using methods used in the encryption phase. thus, utf-8 decoding is applied at the end of the hybrid decryption phase to convert the decrypted text m to its plain text form m. 3. experimental setup this section describes the experimental setup and evaluation parameters used to evaluate the proposed model’s efficiency. the proposed model is implemented in a python environment and simulated using cloudsim. the proposed model’s performance was evaluated using multifarious parameters such as cryptographic execution time, throughput, and the avalanche effect as discussed below: advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 23 cryptographic execution time: this metric considers the overall time taken to encrypt or decrypt the unique data. the evaluation is carried out on the plain text, which has different sizes. to ensure the reliability of the results, the experiments are conducted 10 times, and the average time for encryption and decryption is used for the analysis. throughput rate: this metric is an essential indicator to evaluate the efficiency of the cryptographic algorithm, as there is a direct correlation between the throughput rate and the performance of the algorithm. thus, increased performance leads to a higher throughput rate. the formula below provides the calculation method for the throughput rate. plaintext_size throughputrate execution_time = (8) avalanche test: it is a metric or property in which a small change in the input results in a significant change in the output. a robust algorithm should have a significant avalanche effect, rendering output unpredictable and unrelated to input, thereby hindering the susceptibility of the detection patterns and breaking encryption to attackers. the optimal assessment of a ciphertext is determined by strict avalanche criteria, which require a single modification to alter 50% of bits. 4. results and discussion this section presents the results obtained from the experimental analysis of the proposed model. the analysis involves evaluating each phase of the model, including its execution time, throughput analysis, and avalanche effect. furthermore, it presents a comparative analysis of the proposed model with existing standard symmetric and asymmetric algorithms, and further discussion regarding the security analysis against various attacks is established. 4.1. analysis of the proposed model initially, the proposed study conducts a simple analysis to evaluate the performance of the model at each step of the encryption and decryption process. table 1 presents the execution time (in milliseconds) of each step in the encryption and decryption process for different plain text sizes varying from 32, 64, 96, 128, 160, 192, 224, 256, 288, and 320 bytes. the results indicate that the execution time of the proposed decryption process is higher than that of the encryption process. it can be attributed that decryption often involves complex operations, especially in rsa involving modular exponentiation and the use of a private key. therefore, the time complexity of the proposed model is highly influenced by the asymmetric decryption process rather than the encryption process. table 1 evaluation of execution time size (bytes) time in ms encod. rsa enc. shuffling sym. enc. total enc. decod. rsa dec. reshuffling sym. dec. total dec. 32 0.0001 0.0091 0.0000 0.0002 0.0094 0.0000 0.3344 0.0000 0.0001 0.3345 64 0.0000 0.0160 0.0001 0.0003 0.0163 0.0000 0.6725 0.0000 0.0001 0.6726 96 0.0000 0.0227 0.0001 0.0002 0.0230 0.0000 1.0221 0.0000 0.0001 1.0222 128 0.0000 0.0364 0.0001 0.0003 0.0367 0.0000 1.6060 0.0000 0.0001 1.6062 160 0.0000 0.0494 0.0001 0.0003 0.0498 0.0000 2.1625 0.0000 0.0001 2.1627 192 0.0000 0.0495 0.0001 0.0003 0.0499 0.0000 1.9945 0.0000 0.0001 1.9946 224 0.0000 0.0606 0.0001 0.0003 0.0610 0.0000 2.3229 0.0001 0.0001 2.3231 256 0.0000 0.0626 0.0002 0.0003 0.0631 0.0000 2.6608 0.0001 0.0002 2.6611 288 0.0000 0.0721 0.0002 0.0003 0.0725 0.0000 3.1720 0.0000 0.0002 3.1722 320 0.0000 0.1027 0.0002 0.0004 0.1033 0.0000 3.9098 0.0001 0.0002 3.9100 furthermore, the average time to execute the encryption and decryption process for text with varying sizes is presented in table 2. the results signify that the average total time for encryption and decryption is 69.28 seconds, with 2.8 seconds for encryption and 66.66 seconds for decryption. additionally, the throughput rate increases with the size of the plaintext. advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 24 table 2 analysis of the proposed model with performance metrics plaintext size (kb) enc. time (s) dec. time (s) total time (s) throughput (kb/sec) 250 1.550 37.922 39.472 6.334 500 2.433 58.207 60.640 8.245 750 3.315 78.493 81.080 9.250 1000 3.903 92.017 95.920 10.425 average 2.800 66.660 69.278 8.564 the avalanche effect for the proposed model is computed using plaintext sizes ranging from 10 kb to 100 kb, and the results are presented in fig. 4. the avalanche effect, represented as a bit difference, refers to the number of differing bits between the encrypted data of the original plaintext and the modified plaintext. the results indicate that the average avalanche effect for the proposed model is 50%, which is a strong indication of the effectiveness of the cryptographic algorithm. fig. 4 avalanche effect of the encryption process 4.2. comparative analysis this section presents a comparative analysis of the proposed model with the standard symmetric and asymmetric encryption algorithms. the proposed hybrid cryptographic model is compared with other individual symmetric encryption algorithms, including aes, des, 3des, blowfish, twofish, rc4, and chacha20, by varying the plain text size from 10 kb to 100 kb. fig. 5 displays the average time (in seconds) required for the encryption and decryption processes for various symmetric cryptographic models. the results indicate that the average encryption time for rc4 yields the lowest, followed by chacha20, blowfish, aes, and twofish, while des, 3des, and the proposed model take more time than others. thus, the proposed hybrid model exhibits a high execution time compared to other standard symmetric encryption models. fig. 5 average execution time of symmetric encryption models advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 25 furthermore, the proposed hybrid cryptographic model is also compared with other individual asymmetric encryption algorithms such as rsa, elliptic curve digital signature algorithm (ecdsa), dsa, and elgamal encryption models by varying the plain text size from 10 kb to 100 kb. the average time taken (in seconds) for the encryption and decryption processes for different asymmetric cryptographic models is depicted in fig. 6, in which dotted lines represent the average values of the respective models. the results indicate that the average encryption for ecdsa (13.15s) and dsa (14.47s) takes the lowest time, followed by elgamal (16.85s) and rsa (16.86s), while the proposed algorithm takes 18.41 seconds. this symbolizes that the execution time of the proposed model is similar to the other standard asymmetric encryption models. fig. 6 performance comparison with asymmetric encryption models fig. 7 performance comparison with hybrid encryption models besides, the proposed hybrid cryptographic model is also compared with other hybrid models by replacing the symmetric (rsa) and asymmetric models (chacha20). the hybrid algorithms for comparison are created by selecting the most effective combinations from the analysis: rsa+aes, elgamal+aes, and elgamal+chacha20. rc4 is not selected due to its vulnerabilities and weaknesses in security, such as susceptibility to various attacks. these hybrid models are assessed by varying the plain text size from 10 kb to 100 kb. the time taken (in seconds) for the encryption and decryption processes for different hybrid models is shown in fig. 7, with dotted lines representing average values. the results indicate that the average encryption for elgamal+aes and elgamal+chacha20 is 17.32 seconds and 17.4 seconds, while that of rsa+aes and the proposed model is 19.5 seconds and 18.4 seconds. similarly, the throughput rate and avalanche effects are assessed for significant symmetric, asymmetric, and hybrid models. fig. 8 displays the average throughput rate for various models, with plaintext sizes ranging from 10 kb to 100 kb. the study reveals that symmetric models like aes and chacha20 achieve high throughput rates, while single asymmetric models like rsa and elgamal have lower rates due to simplicity. advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 26 fig. 8 throughput rate comparison with hybrid encryption models moreover, fig. 9 shows the average avalanche effect for significant symmetric, asymmetric, and hybrid models, varying the plaintext size from 10 kb to 100 kb. the proposed model has the highest average avalanche effect at 50%, exhibiting the highest sensitivity to single-bit changes among tested encryption methods. fig. 9 average avalanche effect comparison 4.3. security analysis against various attacks any cryptographic model’s sustainability is determined by its reliability and robustness against various attacks performed by attackers to compromise the confidentiality and integrity of the data. the proposed algorithm, which combines the rsa for asymmetric encryption, chacha20-poly1305 for symmetric encryption, and a hybrid data shuffling technique, is secure against various attacks, as discussed below. • brute force attacks: rsa encryption, with a key size of 2048 bits or more, hampers the effectiveness of brute-force attacks due to the vast number of check possibilities. moreover, chacha20-poly1305 is also a robust security tool due to its 256bit key size, making brute force attacks impractical due to its large key space. • cryptanalysis attacks: chacha20 encryption is resistant to a variety of cryptanalysis methods, including differential and linear cryptanalysis. also, using it with poly1305 ensures the authenticity and integrity of the original plain text. • chosen ciphertext/plaintext attacks: by utilizing secure padding strategies, rsa encryption can prevent ciphertext attacks. moreover, the chacha20-poly1305, an authenticated encryption scheme, ensures ciphertext integrity and authenticity, rendering resistance to specific ciphertext attacks. additionally, shuffling adds a layer of security to the chosen plaintext attack, increasing its complexity. • replay attacks: the nonce used in chacha20-poly1305 ensures that each message is unique. however, reusing nonces with the same key can lead to security vulnerabilities. advances in technology innovation, vol. 10, no. 1, 2025, pp. 15-28 27 • man-in-the-middle attacks: the combination of rsa and chacha20-poly1305 enables a secure method of exchanging keys and encrypting data, protecting against attacks that include a man in the middle. • data tampering and integrity attacks: poly1305 ensures message integrity and authenticity by verifying the integrity of the ciphertext before decryption and detecting any tampering with the encrypted message. thus, the security analysis indicates that the model is strong in terms of confidentiality and integrity, with efficient performance contributing to availability. the security analysis of the proposed model highlights its efficiency apropos confidentiality, integrity, reliability, and robustness to various attacks. 5. conclusion the study proposed a novel hybrid encryption scheme that combines rsa for asymmetric encryption and chacha20poly1305 for symmetric encryption. by adding a hybrid shuffling mechanism, the model significantly improves security and efficiency. manifold metrics, such as encryption and decryption times, throughput rate, and the avalanche effect, evaluate the performance of the proposed model. the model’s average execution time is 69.28 seconds, and its average throughput rate is 8.564 kbps. furthermore, the proposed model has a 50% avalanche effect, which is a strong indication of a good cryptographic algorithm. despite the longer execution time than symmetric methods, the model performs similarly to asymmetric models and is resistant to cryptanalytic attacks. however, the shuffling mechanism and the dual encryption procedure cause a higher computational overhead, which is the primary limitation of the proposed system. this may not be suitable for environments with limited resources or real-time applications that need minimal latency. hence, further enhancements must focus on refining the shuffling algorithm to minimize computational cost and investigating alternative lightweight cryptographic primitives to enhance efficiency. additionally, testing the model in several real-world environments, like iot networks and large-scale cloud systems, will offer a better understanding of its practical use and effectiveness. enhancing the model to address emerging threats or optimizing it for specific applications could render additional improvements. furthermore, future research could explore incorporating postquantum cryptographic algorithms to safeguard the encryption system from potential quantum computing risks. the cloud scenario with a different number of users and the utilization of memory and cpu will be the subject of additional in-depth investigation. conflicts of interest the authors declare no conflict of interest. references [1] s. kolasani, “innovations in digital, enterprise, cloud, data transformation, and organizational change management using agile, lean, and data-driven methodologies,” international journal of machine learning and artificial intelligence, vol. 4, no. 4, pp. 1-18, 2023. 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[20] h. abroshan, “a hybrid encryption solution to improve cloud computing security using symmetric and asymmetric cryptography algorithms,” international journal of advanced computer science and applications, vol. 12, no. 6, pp. 31-37, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v10n1(2025)-aiti#14075(29-43).docx advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 english language proofreader: chih-wei chang motorcycle parking violation detection system using yolov7 with region of interest mapping and object area calculation haerunnisya makmur, wulandari, muhammad fajar b*, andi baso kaswar, dyah darma andayani, fhatiah adiba, abdul wahid, satria gunawan zain department of computer engineering, state university of makassar, makassar, indonesia received 31 july 2024; received in revised form 18 october 2024; accepted 28 october 2024 doi: https://doi.org/10.46604/aiti.2024.14075 abstract the large number of motorcycle users has created challenges, particularly related to parking violations, which can lead to traffic congestion, hinder emergency access, disrupt pedestrian pathways, and inconvenience other users. therefore, this study aims to detect motorcycle parking violations in unsupervised restricted areas using yolov7 to classify non-parking, parking, and personal objects. the best model is achieved at the 28th epoch with an map value of 0.953 at the 0.5 threshold. parking restriction areas are defined using a region of interest (roi), where violations depend on the parking object’s detected coverage within the roi exceeding 50%. by employing an area calculation method, the results show better performance compared to methods without area calculation, achieving a recall of 89.7%, precision of 82.6%, and f1-score of 86.2% with a confidence threshold of 0.5. keywords: computer vision, parking violation, region of interest, motorcycle, yolov7 1. introduction mobility is one of the important factors in strengthening the economy, which evolves along with the population’s activities to meet their needs, especially in the context of transportation accessibility and efficiency [1-3]. in indonesia, personal vehicles such as cars and motorcycles have become the most common and convenient means to commute and conduct any activity [45], where motorcycle is the preferred choice for the public due to the efficiency of driving time and affordability, especially in urban areas with heavy traffic [6]. based on data from statistics indonesia, motorcycle dominates the number of vehicles with 132,433,679 units or around 84.3% of the total 157,080,504 vehicle units in 2023 [7]. despite providing ease of mobility and accessibility, the increasing number of motorcycle vehicles also poses various challenges, especially related to traffic violations [8-9]. one of the common violations that often occurs in society is parking violation [10], which can be ascribed to limited parking spaces, lack of clear signs, and lax enforcement of parking rules [1112]. motorcycle parking lots in small and restricted areas require more attention in enforcing parking rules, as they can incur various problems such as traffic congestion, hindering emergency access, disrupting pedestrian pathways, and creating inconvenience for other users [9]. in addition, the officer’s manual enforcement of parking rules is often inefficient, ineffective, and time-consuming due to limited human resources. therefore, the application of computer vision technology is indispensable to ensure the orderly management of parking areas. this technology can identify vehicles and monitor parking areas without requiring the presence of field officers. * corresponding author. e-mail address: fajarb@unm.ac.id 30 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 several studies have conducted parking violation detection using multifarious computer vision and machine learning methods. for instance, one study detected car parking violations on the side of the highway using the faster region-based convolutional neural network (faster r-cnn) with an accuracy of 77.9% [13]. another study detected taxi parking violations by applying semantic segmentation of pspnet and yolov3, resulting in an accuracy of 96.1% [14]. in addition, some studies detect parking violations by using region of interest (roi) to define parking restriction zones. akhawaji et al. [15] detected and tracked vehicles using a gaussian mixture model and kalman filter, marking vehicles as violators if stayed within the roi for more than sixty seconds without moving, reaching the f1-measure of 88%. similarly, a different study applied mobilenet to detect violations when vehicles remained in the roi for one minute, eliciting a precision of 98.7% [16]. further research also detected double parking by employing background subtraction to identify vehicles in the roi, declaring a violation if the vehicle was stationary for more than six counts, achieving 91% accuracy [17]. another study defined parking areas using roi, detecting violations when vehicles were parked outside the designated area, resulting in a precision and recall of 97% and 95%, respectively [18]. these studies demonstrate that the use of roi is an effective approach for detecting vehicle parking violations. however, the focus of these studies has primarily been on cars. one notable study related to motorcycle parking violations, conducted by hernández-díaz et al. [19] detected motorcycle violations in pedestrian zones by classifying data into four categories: motorcycles with motorcyclists in crosswalks, motorcycles with motorcyclists outside crosswalks, pedestrians in crosswalks, and only motorcycles outside crosswalks. this study employed yolov8, single shot multibox detector (ssd), and mobilenet, with yolov8 achieving the highest mean average precision (map) of 84.6%. these findings, along with the research presented by yang and yu [14], highlight that yolo proves to be an effective method for object detection, demonstrating its capability to accurately identify parking violations across different contexts. meanwhile, wang et al. [20] used block matching and motion detection techniques to identify violations involving twowheeled vehicles such as bicycles, classifying violations when these vehicles remained outside the parking area for more than five minutes, resulting in an average f1-score of 79%. despite this advancement, motorcycle parking violation detection still presents challenges. motorcycles are volumetrically smaller, more maneuverable, and often park in irregular positions, hindering the reliability of both time-based and motion-based detection methods, which function well for cars. moreover, the rapid movement and frequent stops of motorcycles complicate the distinction between legal and illegal parking. to address these challenges, this study focuses on detecting motorcycle parking violations in restricted areas that are unsupervised by officers. the proposed method entails creating a classification model using yolov7 to identify objects in the parking area, including parked motorcycles, non-parked motorcycles, and persons. this model is specifically designed for rapid detection of potential parking violations, such as driverless parked motorcycles, without requiring time-based vehicle monitoring. furthermore, roi is established for the restricted parking area, and the area of the parking object within this roi is calculated. a violation is flagged if the area occupied by the parking object within the roi reaches 50% or more. this areabased approach aims to ensure accurate detection of violations, even for objects that are not entirely within the roi but still in violation. the study aims to enhance the efficiency of motorcycle parking violation detection and improve parking management, ultimately contributing to safer and more organized urban environments. 2. research methods the research methods consist of data acquisition, preprocessing and data augmentation, annotation, split data, classification, violation detection, implementation, and evaluation. the methods of the research are graphically depicted in fig. 1, in which the area with the red line indicates the main focus of the proposed method for detecting motorcycle parking violations. advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 31 fig. 1 the research methods 2.1. data acquisition the data consists of photos and videos showing activities in the parking lot area in front of the teknol building of the department of informatics and computer engineering, state university of makassar. the photo was taken using a smartphone camera with a total of 600 images, while the video was taken using a webcam with a resolution size of 1080 × 1920 pixels and a speed of 30 frames per second (fps), consisting of 32 videos with a total duration of 254 minutes. data was collected from the 3rd floor of the teknol building. 2.2. preprocessing and data augmentation preprocessing is the stage carried out to process raw data before further processing by an algorithm or model [21]. from the 600 images, 180 images were selected by only taking images that have clear objects. in addition, a cropping process was carried out to focus the objects in the image and resize them to reduce the image size. concerning the video data, preprocessing involved converting the video into a series of frames, where 2,462 frames were selected. furthermore, data augmentation was carried out through the flip process, which changed the horizontal orientation of the image to obtain more diverse motorcycle position data. the final amount of data used in the parking, non-parking, and person classification object process is presented in table 1. table 1 total data used data baseline data augmentation data total image 180 41 221 video frame 2,462 617 3,079 total 3,300 2.3. annotation (a) parking (b) person (c) non-parking fig. 2 example of object classes for annotation 32 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 the yolo annotation is a labeling process to mark objects in the image with the appropriate label to enable the object to be recognized and understood during model training [22]. the tool used for yolo annotations is labelimg, where the object in the image is annotated using a bounding box surrounding the object and then labeled appropriately. the annotation result is saved in yolo annotation format (.txt), which contains the normalized bounding box coordinates (relative to the image size) and the object label. the labels for object annotation consist of three scenarios: parking, person, and non-parking, as shown in fig. 2. the annotated object for the parking class shown in fig. 2(a) is a parked motorcycle, which means the absence of a rider on the motorcycle. in the person class shown in fig. 2(b), the annotated object is a human. meanwhile, the annotated object in the non-parking class is a motorcycle that is being driven, as shown in fig. 2(c). in certain images, multiple object classes were annotated, signifying the image contains annotations for various types of objects. the cumulative results of the annotations are presented in table 2. table 2 total object annotations class number of annotations non-parking 2,689 parking 2,520 person 2,533 total 7,742 2.4. classification model the classification model was formed using yolov7, which is an object detection algorithm that can recognize and identify objects in an image [23]. this model is used to classify parking, non-parking, and person objects. in this process, the 3,300 data was divided into 80% train data (2,640 images), 10% validation data (330 images), and 10% test data (330 images). the following details of the number of object annotations for each class in training, testing, and validation data are presented in table 3. the hardware used during training is a laptop device equipped with windows 11 64-bit, 11th gen intel(r) core(tm) i5-1135g7 2.40 ghz (8 cpus), 8 gb ram, and nvidia geforce mx350 5.8 gpu (2 gb dedicated, 3.8 gb shared). the hyperparameters used during model training are presented in table 4. table 3 distribution of the number of object annotations based on training, testing, and validation data class training testing validation non-parking 2,129 281 279 parking 2,023 248 249 person 2,021 265 247 total 6,173 794 775 table 4 hyperparameters used for training model hyperparameters value image size 416 batch size 4 epoch 28 optimizer sgd (stochastic gradient descent) learning rate adaptive learning rate loss function bce (binary cross-entropy) 2.5. parking violation detection the proposed method for detecting parking violations commences by developing a classification model to identify parking, non-parking, and person objects, as previously explained in the annotation and classification subchapters. the next steps involve forming an roi and calculating the bounding box area of the parking object within it, enabling the system to detect parking violations. specifically, roi refers to a specific area or region in an image that is selected for further analysis [24]. in this study, roi is used to mark the parking restriction area. the roi formation process is customized to the street area captured in the video. this area remains consistent and unchanged owing to stable video footage. an illustration of the roi can be seen in fig. 3, where roi formation is performed using the pixel coordinates of the rectangular street area in the frame. advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 33 the coordinate points x1 and x2 indicate the x coordinates of the upper left and lower right corner points, while y1 and y2 indicate the y coordinates of the same points. thus, x1 and y1 represent the upper left point of the area (start point), while x2 and y2 represent the lower right point of the area (endpoint). fig. 3 illustration of the region of interest by forming roi, the focus of object detection is on the parking class within the roi. a parking object is considered to be in violation if all four coordinate points on the object’s bounding box are between the roi coordinates, as shown in fig. 3 for parking-3 and parking-4. however, this method is sometimes disadvantageous, especially when a parking object cannot be detected as a violation if only two coordinate points on the object’s bounding box are inside the roi, as seen in fig. 3 for parking-1 and parking-2 objects. therefore, the determination of whether a detected object violates the rule or not is based on the percentage of the parking object’s bounding box area that falls into the roi (the intersection area between the bounding box of the parking object and the roi). to calculate the percentage of object area, the following formula is established: intersection area of the bounding box object object area (%) 100 area of the bounding box object = × (1) fig. 4 illustration of the object area calculation in cartesian diagram 34 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 to calculate the area of intersection of the bounding box object and the area of the bounding box object itself, the concept of the rectangular area formula is used, by multiplying the length by the width. fig. 4 shows the calculation of the bounding box’s length and width in a cartesian diagram, illustrating the interrelationship between the coordinate points in the roi and the bounding box in determining the object area. based on fig. 4, the intersection area of the bounding box object and the area of the bounding box are calculated as follows: ( ) ( ) ( ) ( ) 1 2 2 1 1 1 2 2 1 2 2 1 1 1 2 2 , & intersection area of the bounding box object , & − × −  > > =  − × −  < < y roi y bx x bx x bx if y bx y roi y bx y roi y bx y roi x bx x bx if y bx y roi y bx y roi (2) ( ) ( )2 1 2 1 area of the bounding box object = − × −x bx x bx y bx y bx (3) from eq. (2), the intersection area calculation is based on two conditions: if the detected object’s start point is larger than the roi start point, the area is calculated; if the object’s endpoint is smaller than the roi endpoint, the object is considered outside the roi endpoint. if both the start and end points are within the roi, the area is deemed 100% inside the roi. in eq. (3), the bounding box area is calculated using the start and end coordinate points. the overall general architecture of the proposed parking violation detection system is illustrated in fig. 5. it consists of two main modules: the object detection module and the violation detection module. the object detection module processes each video frame and detects vehicles using the yolov7 algorithm, identifying objects within the roi. the violation detection module calculates the area of any detected parking object within the roi thereafter. a violation is flagged when 50% or more of the object’s area falls within the roi. fig. 5 general architecture of parking violation detection system 2.6. implementation (a) place a (b) place b (c) place c fig. 6 three different locations for system implementation advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 35 the implementation stage was carried out by applying the system that has been developed to detect parking violations to assess the effectiveness and reliability of the model in detecting parking violations. this implementation process involves applying the model to the acquired video, which includes real-life parking violations in three different locations, as shown in fig. 6. detailed information on the duration and description of the videos during the system implementation at each location is presented in table 5. table 5 duration and description of videos for system implementation place duration description a 0:22:44 features the parking lot in front of the teknol building of the department of informatics and computer engineering at the state university of makassar, recorded from the 3rd floor. b 0:10:48 features the street area in front of a housing estate that is often bustling with daily activities, recorded from the 3rd floor of a resident’s house. c 0:18:51 features the street area in front of at-taubah mosque, recorded from the 2nd floor of the mosque. 2.7. evaluation evaluation, the process of measuring the performance and accuracy of a system [25], is performed using a confusion matrix to assess the effectiveness of the model in classifying parking, non-parking, and person objects. additionally, the confusion matrix is used to measure the results of the system implementation. the components of the confusion matrix are presented in table 6, which is then used to calculate the recall, precision, and f1-score values [26]. table 6 confusion matrix predicted positive negative actual positive true positive (tp) false negative (fn) negative false positive (fp) true negative (tn) true positive (tp) is the number of correct predictions for the positive class, while true negative (tn) is the number of correct predictions for the negative class. false positive (fp) is the number of false predictions for the positive class, and false negative (fn) is the number of false predictions for the negative class. recall shows how many positive cases are found by the model, and it is calculated as follows: tp recall tp fn = + (4) precision indicates how many of the model’s positive predictions are correct, and it is calculated using: tp precision tp fp = + (5) meanwhile, the f1-score balances the two and provides a more comprehensive score of the model’s performance, and it is calculated as: recall precision f1-score 2 recall precision × = × + (6) 3. results and discussion the parking violation detection system is developed by building a model that can detect objects in the parking area. the detected objects include a person, a non-parked motorcycle, and a parked motorcycle. the sample dataset used in this study is shown in fig. 7, which comprises two frames and their labels from videos taken with different brightness conditions. 36 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 fig. 7 example dataset of video frames for building a detection model the results of the object annotations are shown in fig. 7, where the non-parking object class is labeled as 0, the parking object as 1, and the person object as 2. to avoid class imbalance, certain objects were intentionally left unannotated. this approach was adopted to maintain a balanced dataset and prevent any class from dominating the annotations, which could negatively impact the model’s performance during training. by selectively annotating the objects, a fairer distribution among all classes can be achieved. additionally, since parking objects appear consistently in most frames, they were annotated differently across frames for variety. the labeling of parking and non-parking classes includes two different object orientations, vertical and horizontal, enabling the system to recognize all variations of object forms. (a) upward non-parking (b) upward parking (c) downward non-parking (d) downward parking fig. 8 vertical variations of non-parking and parking objects (a) right-facing non-parking (b) right-facing parking (c) left-facing non-parking (d) left-facing parking fig. 9 horizontal variations of non-parking and parking objects advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 37 vertical objects are categorized into two types: one when the object is facing up and the other when it is facing down, as shown in figs. 8 and 9. similarly, horizontal objects are also divided into two categories: one when the object is facing right and the other when it is facing left. after labeling or annotating all objects according to their respective classes, the model was trained using the yolov7 architecture. the results obtained at different epochs are presented in table 7. table 7 results of the model training experiments test epoch 13 28 35 40 45 non-parking (%) tp 95 99 98 98 98 precision 92 95 95 95 95 recall 95 97 93 93 93 map 50 96 97 97 97 97 map 50:95 69 71 72 72 72 parking (%) tp 94 98 98 98 98 precision 79 82 80 80 80 recall 81 83 88 88 88 map 50 91 94 94 94 94 map 50:95 64 69 70 70 70 person (%) tp 91 95 92 92 92 precision 85 89 89 89 89 recall 84 84 83 83 83 map 50 91 94 94 94 94 map 50:95 46 51 50 50 50 the model has achieved decent performance in detecting objects for each class at the 13th epoch. at this point, the detection accuracy for each class exhibited satisfactory and stable results. however, when the number of epochs increased to 28, a significant improvement emerged in detection accuracy across all classes. this improvement indicated that the model continued to learn and enhance its ability to detect objects as the epochs increased. the accuracy of each class improved, demonstrating that the model became more effective and precise in recognizing patterns in the training data. furthermore, when the number of epochs increased to 35, the accuracy improvement was no longer maximized. some indications are interpreted that the model’s performance declined, particularly in the person class, with no improvement in accuracy observed at the 40th and 45th epochs. this decline was attributed to overfitting, where the model became too fitted to the training data, incurring decreased performance when handling new data [27]. as a result, the chosen model was trained up to the 28th epoch with the corresponding confusion matrix, as shown in fig. 10. fig. 10 confusion matrix of the selected model at the 28th epoch 38 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 the non-parking class has the highest tp rate, correctly detecting objects with 99%, followed by the parking class at 98% and the person class at 95%. however, a weakness is observed in the prediction of background elements being incorrectly detected as objects, resulting in fp, especially in the parking and person classes, where fp values are relatively high. this high fp rate is due to the large number of parking and person objects in the dataset that actually exist but were not labeled to avoid an imbalance in the number of data annotations. despite the high fp rate, the model performs well overall, as the tp values for each class are quite high, indicating robust detection capabilities. background errors fp are primarily due to unlabeled objects in the dataset rather than inherent weaknesses in the model. additionally, the background fn value, which represents errors when objects that should have been detected are incorrectly identified, as the background is relatively low. such a result indicates that, despite some background errors, the model remains effective in detecting most relevant objects. fig. 11 precision-recall curve result based on the precision-recall curve graph in fig. 11, which illustrates the relationship between precision and recall, the map value at a threshold of 0.5 for all classes reaches 0.953. such a finding reveals that the model is capable of identifying and classifying objects. the non-parking class demonstrates the highest performance, achieving an almost perfect precisionrecall value of 0.974, as indicated by the curve nearly reaching the upper right corner. the parking class has a precision-recall value of 0.940, denoting that although its performance is slightly lower than non-parking, the model remains reliable in detecting parking objects. meanwhile, the person class achieves a precision-recall value of 0.946, slightly above parking, indicating that the model is effective in detecting most person objects as well. subsequently, the selected model was implemented on video with the results, as shown in fig. 12. fig. 12 object detection results using yolov7 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 39 at this stage, the model was utilized to detect and classify objects in video footage to evaluate the detection performance in more dynamic and realistic situations. the video implementation aims to assess how effectively the model can identify moving objects and tackle challenges such as lighting changes, varying viewing angles, and potential occlusion. fig. 12 unveils the detection results identified by the model in a certain frame of the video. from these results, it can be seen that the model has been able to predict parking, non-parking, and person objects in the parking area. initially, the model was designed to detect only two classes of objects: parking and non-parking. however, a significant issue was found during initial testing, where the model frequently misclassified passers-by in the parking area as non-parking objects, as shown in fig. 13(a). this phenomenon yielded many inaccurate detections, particularly in situations with high human activity around the parking area. this error indicates that the model requires improvement to effectively differentiate between parking, non-parking, and people moving around. therefore, a new class was added to the model, i.e., the person class. after the addition of the person class, the model was re-implemented and tested on the same data, resulting in a significant improvement in detection accuracy. fig. 13(b) shows the updated detection result, where a human walking in the parking lot is now successfully detected and correctly identified as a person. (a) wrong detection (b) correct detection fig. 13 model detection results before and after adding person class this breakthrough demonstrates that adding the person class enhanced the ability of the model to distinguish between different objects in the parking lot environment. furthermore, the implementation of the system to detect motorcycle parking violations using the proposed method, which includes the formation of roi and the calculation of the parking object area, was also successfully carried out, as shown in fig. 14. the motorcycle parking violation detection system demonstrates effective performance across the three different locations. specifically, parking objects were successfully detected as parking violations when the area reached 50% or more while within the roi. additionally, non-parking objects were correctly identified as not committing parking violations when inside the roi. this significantly accurate classification of non-parking objects reflects the ability of the system to differentiate between designated parking areas and areas where parking is prohibited. (a) place a fig. 14 system implementation results for detecting motorcycle parking violations in three different locations 40 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 (b) place b (c) place c fig. 14 system implementation results for detecting motorcycle parking violations in three different locations (continued) in the following phase, a system evaluation was conducted to validate the performance of the system in detecting motorcycle parking violations in three different locations. the system evaluation compared the proposed method, which utilizes object area calculation for detected parking objects within the roi, with a scenario that does not use area calculation. using object area calculation achieves an average recall of 91.5%, significantly higher than the 78.6% recall without object area calculation, as shown in table 8. table 8 comparison of the system evaluation with and without object area calculation place real with object area calculation without object area calculation system (tp) error detection recall (%) precision (%) system (tp) error detection recall (%) precision (%) fn fp fn fp a 37 35 2 14 94.6 71.4 28 9 4 75.7 87.5 b 5 5 0 2 100 71.4 4 1 1 80 80 c 5 4 1 1 80 80 4 1 1 80 80 average 91.5 74 average 78.6 82.5 f1-score (%) 82.7 f1-score (%) 80.5 this difference is due to certain parking objects whose bounding box points were not entirely within the roi, incurring their failure to be detected as violations as shown in fig. 15(a). however, by applying the area calculation for parking objects, as illustrated in fig. 15(b), an object with more than 50% of its area within the roi was successfully detected as a parking violation. however, the average precision values in table 8 yield the opposite result. using object area calculation results in a lower precision of 74%, compared to 82.5% when object area calculation is not applied. as illustrated in fig. 16(a), a nonparking object detected when parking was not classified as a violation due to two of its bounding boxes that were outside the roi. conversely, fig. 16(b) shows a misclassified object that was still recognized as a parking violation because more than 50% of its area was within the roi. advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 41 (a) wrong detection (b) correct detection fig. 15 detection results without and with the application of the object area calculation method (a) detected as not committing a violation (b) detected committing a violation fig. 16 double detection results without and with the application of the object area calculation method based on the results obtained, the use of object area calculation yields an overall higher f1-score of 82.7%, compared to 80.5% without using object area calculation. therefore, it can be concluded that the proposed method of calculating the parking object area within the roi enhances the effectiveness of the system in detecting parking violations, despite the increase in the number of non-violating objects that were incorrectly identified as violations. the system implementation used a confidence threshold set at 0.3, enabling the mis-detected object in fig. 16 to still be considered valid due to its confidence score of 0.3. therefore, a different scenario was tested by setting the confidence threshold to 0.5. table 9 system evaluation with confidence threshold set at 0.5 place real system (tp) error detection recall (%) precision (%) fn fp a 37 33 4 6 89.2 84.6 b 5 5 0 1 100 83.3 c 5 4 1 1 80 80 average 89.7 82.6 f1-score (%) 86.2 based on the results presented in table 9, the average recall value achieved is 89.7%, reflecting a decrease compared to the results in table 8 with object area calculation. this reduction occurred because two objects that committed parking violations were not detected due to having a confidence score of less than 0.5. however, the recall still surpassed the average recall from table 8 without object area calculation. the average precision obtained is 82.6%, which is higher than the average precision in table 8. therefore, setting the confidence threshold at 0.5 is deemed effective, as evidenced by the f1-score which reached a higher value of 86.2%. 4. conclusions from the research conducted on the motorcycle parking violation detection system, the use of the yolov7 for classifying non-parking, parking, and person objects achieved its optimal performance at the 28th epoch with an map score of 0.953 at a threshold of 0.5. the classification model is designed to expeditiously detect parking violations when a parking object is 42 advances in technology innovation, vol. 10, no. 1, 2025, pp. 29-43 located within a parking restriction area or roi. a detected parking object is considered a violation if its area within the roi reaches 50% or more. by deploying this object area calculation, the f1-score increased to 82.7%, higher than the 80.5% f1score obtained without the object area calculation. additionally, the model demonstrated more effective performance in detecting violations with a confidence threshold of 0.5, resulting in a recall of 89.7%, precision of 82.6%, and an f1-score of 86.2%. the fast object detection capability of yolov7, along with its ability to detect multiple objects simultaneously in a single image enables the parking violation system to work efficiently, even in dense parking environments across three different locations. future developments could focus on nighttime detection by training the model on a larger dataset and incorporating the utilization of infrared cameras. conflicts of interest the authors declare no conflict of interest. references [1] d. lin and j. cui, “transport and mobility needs for an ageing society from a policy perspective: review and implications,” international journal of environmental research and public health, vol. 18, no. 22, article no. 11802, 2021. 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[27] y. peng and m. h. nagata, “an empirical overview of nonlinearity and overfitting in machine learning using covid19 data,” chaos, solitons & fractals, vol. 139, article no. 110055, 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 5-v8n2(2023)-aiti#8964(136-149).docx advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 online mems-based specific gravity measurement for lead-acid batteries yashwant gulab adhav1,*, dayaram nimba sonawane2, chetankumar yashawant patil2 1department of instrumentation and control engineering, cummins college of engineering for women, pune, india 2department of instrumentation and control engineering, college of engineering, pune, india received 24 november 2021; received in revised form 23 january 2022; accepted 30 january 2022 doi: https://doi.org/10.46604/aiti.2022.8964 abstract traditional methods for measuring the specific gravity (sg) of lead-acid batteries are offline, timeconsuming, unsafe, and complicated. this study proposes an online method for the sg measurement to estimate the state-of-charge (soc) of lead-acid batteries. this proposed method is based on an air purge system integrating with a micro electro mechanical system sensor. the system’s performance is compared against the glass hydrometer, a reference standard, to evaluate its effectiveness. through the proposed strategy, the soc measurement achieves up to ±1% accuracy. the technique has an sg accuracy of ±0.002% which is better than the glass hydrometer accuracy of ±0.005% in the battery charge reading. the experimental results show that the high accuracy and precise measurements of sg and soc can be conducted by using the proposed method. keywords: kordash chart, lead-acid batteries, mems, specific gravity, temperature compensation 1. introduction most energy storage systems require batteries to function [1-3]. currently, lead-acid batteries, lithium-ion batteries, and fuel cells are employed as power backup sources. lead-acid batteries are used in various power-generation fields, such as solar power systems, wind power plants, uninterrupted power systems, automotive vehicles, smart grid systems, and aircraft [4-6]. since the last century, lead-acid batteries have been on the market due to their low cost, recyclable material, high power density, and consistent output regardless of the environment. no commercial online sensor is available in the market that can gauge the state-of-charge (soc) of a lead-acid battery using a measurement of specific gravity (sg). larger lead-acid batteries are utilized in underwater vehicles, such as submarines, to start the engines as they require a larger amount of current. soc estimation based on sg is more accurate than the voltage and current method, but measuring the sg of acid is a challenging and tough task. to measure the sg using conventional methods, a sensor has to overcome several vital constraints inside the battery. it is important to resist acid corrosion as the sensor comes in contact with the acid. during the charging and discharging processes, the sensor has to compensate for the temperature variations inside the battery because of chemical reactions. very little space and a small quantity of acid are available at the top of the battery [7]. the constraints mentioned above can be overcome by the proposed design. this motivates the present work on lead-acid batteries. this study aims to design a sensor * corresponding author. e-mail address: yashwant.adhav@cumminscollege.in advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 137 and its real-time measurement system to estimate the sg of a lead-acid battery. sg predicts battery failure before the battery suffers irreparable damage. the online sg measurement displays the status of the battery like a fuel gauge. the life of a lead-acid battery is dependent on both the charging and the discharging states [8]. the novelty and leading features of the proposed work are already patented [9] and summarized as follows: (1) there has been no literature on short air purge sensing tubes that could be placed in the small space at the top of the battery. (2) after conducting the literature survey, it is observed that no researchers have proposed a micro electro mechanical system (mems) sensor to measure the soc of acid batteries. (3) soc and sg are monitored using a single sensor. (4) the change in the acid level does not affect the accuracy due to a constant head method. the study is organized as follows: section 2 presents the important work of sensors and techniques used to determine soc and sg. section 3 focuses on the pressure principle and the design of a real-time sg measurement system for the leadacid battery. section 4 deals with the experimental results as well as the data analysis. section 5 presents the conclusions and future research directions. 2. literature review in light of the literature review, the prevailing technique of the evaluation of sg was established by archimedes’ law. nowadays, a hydrometer is used to measure the soc of a lead-acid battery cell. this is a time-consuming process and cannot be performed in real-time [10]. hence, a real-time measurement system is crucial for battery management. non-contact methods can be utilized for online estimation, but these methods have their limitations, as mentioned below. the discharge test method is a time-consuming online method, and it modifies the state of the battery. the ah-balancing method needs a model-based approach for error identification, and it needs periodic recalibration. the linear model approach requires reference data for fitting parameters. an artificial neural network requires training data of similar batteries. impedance spectroscopy is temperature sensitive method and is costlier. the dc internal resistance method is only effective for small socs. in the kalman filter technique, a large computing capacity is necessary. also, a suitable battery model is also needed, and this method has problems estimating the initial parameters [11]. a measurement of the voltage of the battery is not an accurate soc indication because of the effects of the charge and discharge currents and the temperature variations. before starting the open-circuit voltage measurement, the battery’s current must be kept in an off state for at least 4 hours to reach an equilibrium condition [12]. contact-type methods are best suited for online soc measurements over non-contact methods because of the accuracy of their results. hancke [13] developed the fiber-optic sg sensor to determine the soc of a lead-acid battery. they applied the refractive index principle, and the method is based on the optical power loss that fibers exhibit when bent beyond a critical radius. in this technique, errors arise because of changes in the intensity of the light source and losses occur because of variations in fibers and connectors. these losses can affect the sensitivity of the sensor. paz et al. [8] developed a polymer fiber sensor for measuring the real-time density of the electrolyte at three different locations in lead-acid batteries. the circuit was optimized with led thermal behavior. zhao et al. [14] worked on the light return principle of reflection. when a light wave spreads in the fiber, the characteristics of the light wave, such as oscillation amplitude, phase, polarization condition, and wavelength, can change directly or indirectly as the density changes. patil et al. [15] developed an optical sensor based on the refractometric principle for determining the soc of a lead-acid battery. the concentration of the acid solution and its physical characteristics were taken into consideration. hossain and dwyer [16] demonstrated the buoyancy principle to measure density. the float is connected to the lower arm of the core. as the float dips in the acid, the linear variable differential transformer (lvdt) generates an output signal in proportion to the 138 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 acid density variations. this system is not cost-effective, and the mechanical assembly is complicated. morbel et al. [17] worked on the swelling and shrinkage effect of plastic in sulfuric acid. the disadvantage of this device is that the level sensing is not to be taken into consideration. cao-paz et al. [18] and lu et al. [19] measured the viscosity of the electrolyte. density measurements are done to estimate soc; however, the change in acid viscosity changes soc more significantly than the change in density. in this study, there is a proposal for using a quartz crystal microbalance oscillator sensor for monitoring density and viscosity changes in lead-acid batteries. a frequency shift is observed with a change in h2so4 concentration in the battery electrolyte. the biggest drawback is that calibration must be done frequently. heinisch et al. [20] suggested a steel tuning fork sensor having a circular and rectangular shape, which is used to measure the precise viscosity and mass density of fluids. wilson et al. [21] used cantilever sensors excited by piezoelectric actuators to estimate the viscosity and density parameters of the fluid. tang and lin [22] worked on the integration of a readily available glass hydrometer and ultrasonic sensor for monitoring the density of the lead-acid battery electrolyte. in this method, two different bulky sensors were used to measure level and density. even if these methods are effective, the size and cost of the sensor and system are high. inside the lead-acid battery, almost all the space is covered by lead sheets, and a very narrow space is left above the lead sheets for acid. therefore, it is an interesting and challenging task to place the sensor at this particular location to measure sg. 3. design of the system 3.1. differential pressure principle the air purge method is based on well known pascal’s pressure law [23] which reads as: p h g∆ = ×∆ ×ρ (1) where ∆� is the differential pressure (pa), h is the distance between the two tubes (m), ∆� is the density of acid (kg/m3), and g is the gravitational constant (m/s2). as the differential height h and gravitational acceleration g are constant; hence, eq. (1) shows the proportionality between ∆� and ∆�, i.e., ∆� ∝ ∆�. the change in the density of the acid is directly proportional to the change in pressure. following that, as the battery gets charged or discharged, the density of the acid changes, which changes its sg. this change in sg is directly proportional to the change in pressure. hence, a change in pressure is directly proportional to the soc of the battery. the head between the two tubes is considered to be 2.0 cm. the differential pressure varies from 215 pa to 246 pa for an sg change from 1.1 to 1.26. 3.2. soc detection technique tang and lin [22] revealed that under normal conditions, in the lead-acid battery, sg is 1.28 if soc is 100% and sg is 1.12 if soc is 0%. sg is directly proportional to the discharge rate of the battery by: dr sg 1.28 0.16 100 = − × (2) where sg is specific gravity and dr is the discharge rate of the battery. as shown in fig. 1, under normal conditions, the sg of the acid solution is linearly proportional to the soc of the battery electrolyte. advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 139 fig. 1 sg vs. soc soc sg 1.1 0.16 100 = + × (3) where soc is the state-of-charge (%). according to the kordash chart, sg is directly proportional to the soc of the lead-acid battery [13]. from eq. (3), it is concluded that the battery is 100% charged when sg is 1.26, and the battery is fully discharged when sg is 1.1. 3.3. design of the air purge system fig. 2 represents a block diagram of the air purge system, which is integrated with a highly sensitive mems sensor. the air bubbler method is generally used for level and density measurements of a corrosive liquid [24]. the level of the fluid is monitored by measuring the back pressure using the mems pressure sensor to obtain high accuracy [25]. if the fluid level is kept constant, then the same method can be utilized to estimate the density of the fluid, which has been done in this study. an air purge tube is dipped through the cap of the battery in acid in such a way that it does not touch the lead sheets in the battery. using an aquarium mini-compressor that has a maximum pressure of 350 kpa and airflow without a load of 0.007 lpm, the air is passed through the bubbler tube. because of hydrostatic pressure, the gas pressure in the bubbler tube continuously increases until it balances the hydrostatic pressure of the acid. when this balanced condition is reached, the back pressure in the bubbler tube remains the same as the hydrostatic pressure of the acid. as for sg, the concentration of acid increases, and the back pressure in the air purge tube increases linearly. in this case, the mpxv4006dp sensor is used to measure this back pressure. a potentiometer is used in the purge gas line to control the current of the compressor to ensure that constant bubbling action occurs at the end of the two tubes. the unique advantage of the air purge system is that the exact location of the sensor is not very important because the pressure is the same at any location in the pipe. during charging and discharging, acid evaporates, and hence its level in the battery also decreases. this study uses the sg measurement technique using a constant head, which is independent of the change in the acid level up to a certain extent. acid concentration increases when the battery gets charged and decreases when the battery gets discharged. this increment or decrement in the acid concentration further increases or decreases the back pressure, which is the measure of sg. the output of the mpxv4006dp sensor is amplified using an instrumentation amplifier ad-620 [23]. linear monolithic (lm35) sensor provides temperature compensation to reduce errors. s g ( 2 0 °c ) soc (%) sg = 1.1 + �� ��� ×0.16 140 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 fig. 2 sg measurement setup the actual insertion of tubes through the battery cap is shown in fig. 3. an air purge system is low in cost, yet it is an accurate way to measure the acid density in a battery. a complete air purge density measurement system consists of two teflon tubes: a pressure sensor and a driving circuit for an aquarium air compressor. mini-control valves are used to control the flow of air through the pipe. two separate flow-control valves are also used near the mpxv4006dp sensor port to protect the sensor from excess air pressure. the only part of the sensor that comes in contact with the acid is a teflon dip tube, which has chemical compatibility with acid. one tube is at the upper level and the other is at the bottom level in the acid. the output of the mpxv4006dp sensor has been tested in the charged and discharged solutions. the two ends of the tubes are connected to the two ports of the mpxv4006dp sensor for monitoring differential pressure. the most important electronic component in this system is the mpxv4006dp sensor. it has two ports: higher pressure under test is applied to the high-pressure port (marking side), while lower pressure is applied to the low-pressure port, which causes deflection of the diaphragm. deflection and deformation are measured by calculating the change in the electrical resistance of the micro strain gauges, which are embedded in the silicon diaphragm. all four strain gauges are connected to form a wheatstone bridge. the output of the wheatstone bridge is directly proportional to the applied pressure [25]. these mems sensors have a compact size and good thermal stability because of the temperature compensation built into the sensor. the method based on the sg technique is intelligent and precise [22]. sulfuric acid concentration measurement is the best and most reliable way of monitoring the soc of heavy flooded-type stationary batteries [26]. fig. 3 experimental setup for online sg monitoring temperature sensor lm35 pressure sensing tubes less acid space = 2 cm lead sheets bulb as a load advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 141 3.4. signal conditioning circuit fig. 4 shows the circuit for the proteus simulation of the proposed sensor with temperature compensator lm35, microcontroller arduino uno, and 16 × 2 lcd display. for the mpxv4006dp sensor, the output voltage of the charged battery is 1.661 v, whereas the discharged battery is 1.355 v. the output of the mpxv4006dp sensor is amplified using ad-620. the output signal of the sensor in the form of analog voltage is provided to pin-3 of the ad-620. the amplified output of ad-620 is provided to arduino for analysis and monitor the parameters under test. fig. 4 sg measurement circuit for proteus software simulation zero compensation provides the same voltage at pin-2 of ad-620, which is produced by the mpxv4006dp sensor at pin-3 of ad-620 under the discharged battery condition. in fig. 5, the mpxv4006dp sensor voltage is simulated using the linear potentiometer-p1 in proteus software. the linear potentiometer-p2 is used to vary the voltage at pin-2 so that any output voltage can be adjusted to meet a zero reading at the minimum input. fig. 5 signal conditioner for sg 22µf 142 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 table 1 shows that the output from mpxv4006dp sensor for a fully discharged battery is �� = 1.355 v. to represent this value as 0%, �� is tared by using a stable voltage reference of �� = 1.355 v. the output for a fully charged battery with the same sensor provides 1.661 v denoted as ��. it is clear that the ∆��� as �� − �� = 0 v for discharged battery and �� − �� = 0.306 v for a fully charged battery. to match the requirement of the microcontroller, the required signal is amplified in the range of 0 to 5 v. hence ad-620 is used as an instrumentation amplifier with the gain calculated as ∆��� = 0.306 v and �� = 5 v. the gain of the amplifier is: 5v 49.4 16.33 1 0.306v g g r = = = + (4) table 1 sensor voltage for discharge and charge battery no. battery status �� �2 ∆��� 1 battery discharged 1.355 1.355 0 2 battery charged 1.661 1.355 0.306 as shown in fig. 5, a small change in the voltage is amplified by using a gain resistor (rg), this process is also called span compensation. this voltage range is seen to follow the straight-line linear equation used in the program to obtain a linear output from 1.100 to 1.260 sg. in the same circuit, the filtered output from the rc filter is connected to an a1 analog pin of a microcontroller consisting of a 1k resistor and a 22µf electrolytic capacitor used for noise reduction. 3.5. temperature compensation using the lm35 temperature sensor during charging and discharging, an exothermic chemical reaction takes place inside the battery. if the temperature change is low or high, this can lead to inaccurate readings. the sg of the environmental factor ����� can be expressed by [22]: ( )20 0.0007 20 temp c x x temp°= + × −   (5) where ���°� represents the sg of the solution at 20°c. the numbers 0.0007 and 20 are the temperature coefficients. the term � !� is the acid temperature of the lead-acid battery. to determine the sg of the electrolyte under the effect of environmental parameters, the correction factor is calculated from the acid temperature is added at ���°� temperature. this equation is valid for the temperature range of 17.8°c-54.4°c. lm35 is a more accurate and precise sensor used for temperature measurement [27]. this sensor is kept in stainless steel thermowell, and therefore, it is not subjected to the oxidation process in the battery. lm35 interfaces directly with the microcontroller without any hardware circuit. the operating temperature range of the lm35 sensor is from −55°c to 150°c. the output voltage varies by 10 mv for every 1°c variation of temperature. for the same, the sg of electrolytes at different temperatures have different sg. temperature compensation is essential as the sg of electrolytes can change with temperature variation. 3.6. the probe construction as shown in fig. 6, the probe of the instrument consists of a threaded cap of the battery, which can be fitted to the battery. in this cap, two teflon tubes of a diameter of 5 mm and the lm35 sensor are inserted through the cap of the battery. the short tube is connected to the low-pressure port, and the long tube is connected to the high-pressure port of the mpxv4006dp sensor. a small hole is provided in the cap of the battery to allow chemical gases to escape. these gases are produced because of chemical reactions during the charging and discharging of the battery. advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 143 fig. 6 schematic of sg sensor probe 3.7. microcontroller an arduino consisting of an atmel-328, 16-mhz crystal oscillator, and 8-bit avr is used as a microcontroller in this instrument [22]. initially, the system is simulated using a proteus™, and accordingly, further hardware is developed. for an analog input signal of 0 v, the microcontroller shows an sg of 1.1 and a battery charge of 1%, whereas, for the 5 v analog input signal, it displays an sg of 1.26 and a 100% battery charge. the flowchart of the proposed system is shown in fig. 7. the sg is sensed by differential pressure sensor mpxv4006 dp. to get stability, averaging of 10 samples was done. analog value has been read and correction of temperature, i.e., eq. (5) compensated for accuracy. finally, sg and battery charge (%) have been displayed on the lcd. fig. 7 flowchart of the sg monitoring for the battery unit 3.8. calibration this instrument is designed in such a way that it can be calibrated and utilized for various lead-acid batteries. the procedure for calibration has been mentioned below. the probe (teflon tube) is inserted into the discharge solution, and the zero-compensation potentiometer is adjusted to get an sg of 1.1 on the lcd shield. later, this probe is inserted into the charged solution, and the span compensation potentiometer is adjusted to get an sg of 1.26 on display. the procedure is repeated 4-5 times for accurate calibration. the most significant advantage of the proposed system is that it can be calibrated and can be used for any kind of flooded-type lead-acid battery. 4. results and discussion 4.1. repeatability and precision in the discharged condition this section discusses the working of the present sensor for two states of the battery: one is the charge condition and the other is the discharge condition. furthermore, to establish the effectiveness of this sensor, some parametric variations such as a change in output voltage concerning the change in sg were performed. to port p2 of sensor to port p1 of sensor cap of battery short tube long tube thermowell of temperature sensor hole to escape gas threads lm35 temperature sensor 144 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 two tubes of the sensor are dipped in the fully discharged acid solution. as per the reading shown by a float-type glass hydrometer, the sg of this solution is about 1.1. the tubes are withdrawn, the procedure is repeated after every 1 minute, and the experimentation is carried out on the same acid sample to check the repeatability and precision of the mems sensorbased hydrometer. the results are shown in table 2 and it can be seen that the accuracy and precision of this mems sensorbased acidometer are highly consistent. table 2 repeatability check of mems hydrometer (discharge acid) no. amplified sensor output (v) battery charge (%) sg sg (proteus simulation) battery (%) (proteus simulation) 1 0.014 2 1.104 1.099 0 2 0.030 3 1.104 1.099 0 3 0.017 3 1.103 1.099 0 4 0.003 2 1.104 1.098 0 5 0.018 3 1.105 1.099 0 4.2. repeatability and precision at the charged condition two tubes of the sensor are dipped in the fully charged acid solutions to examine the change of the instrument. as per the reading shown by a float-type glass hydrometer, the sg of this solution has been recorded as about 1.26. the above procedure is repeated to check the repeatability and precision of the mems sensor-based hydrometer. the results are shown in table 3 and it can be observed that the acidometer has consistent accuracy and precision after repeated use. table 3 repeatability check of mems hydrometer (charge acid) no. amplified sensor output (v) battery charge (%) sg sg (proteus simulation) battery (%) (proteus simulation) 1 5.00 98 1.257 1.258 99 2 5.04 98 1.257 1.258 99 3 5.00 98 1.257 1.258 99 4 5.00 99 1.258 1.258 99 5 5.02 97 1.256 1.258 99 4.3. accuracy in terms of sg the degree of closeness to the true value is known as accuracy. the sensor has been installed on the battery. with the float-type glass hydrometer, its sg has been noted down. it is 1.192 and the voltage of the battery is 12.20 v. as shown in fig. 8, the deviation of the measured sg is from 1.187 to 1.191. it shows that the accuracy of the system is ±0.002. this response has been observed for 30 minutes. fig. 8 sg vs. time (20°c) s g time (second) 1.2 1.198 1.196 1.194 1.192 1.19 1.188 1.186 1.184 1.182 1.18 0 240 480 720 960 1200 1440 1680 1800 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 145 4.4. accuracy in terms of battery percentage as shown in fig. 9, the deviation of the measured sg is from 55% to 57%. it shows that the accuracy of the system is ±1% when the sg is 1.192. this response has also been observed for 30 minutes. the battery charge is measured at a true value of 56% as per the glass hydrometer reading; the proposed mems hydrometer indicates this value with a variation in reading of ±1% of the true value. fig. 9 battery charge vs. time (20°c) 4.5. time constant of the instrument it is observed that the measured reading stabilizes within 40 seconds. as shown in fig. 10, the time constant noted is 40 seconds. the sensing probe has been dipped in the fully charged and fully discharged solutions. the instrument takes 40 seconds to reach the maximum level. theoretically calculated time constant, i.e., 8 seconds, is less than the observed time constant of the instrument because the system takes more time to make averaging of samples. time constant = (maximum reading − minimum reading) × 63.2% = (1.26 − 1.1) × 63.2% = 8 second. fig. 10 time response of mems hydrometer for sg measurement 4.6. comparison of the standard hydrometer method and the proposed method the air purge tube has been dipped in 5 different samples of sg. the sg of every sample is measured using a mechanical-type glass hydrometer as a standard method. by using the proposed mems hydrometer, the response of the sg and the soc of the battery (%) is noted, as summarized in table 4. the graph between the standard hydrometer and the proposed mems hydrometer is almost accurate and linear as shown in fig. 11. sg error between the standard and the proposed method (mpxv4006 dp) is ±0.002 = 99.998%, and sg error between the standard method and hydrometer integrated ultrasonic (hc-sr04) sensor [22] is ±0.01 = 99.99%. hence, the standard glass hydrometer accuracy is ±0.005 = 99.995%. time (second) b at te ry c h ar g e (% ) 400 800 1200 1600 1800 0 58 56 55 54 57.5 56.5 55.5 54.5 57 s g time (second) 0 1.3 1.25 1.15 1.2 1.1 120 60 180 240 300 360 420 480 540 600 146 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 table 4 validation of proposed experimental method and glass hydrometer with proteus no. glass hydrometer amplified sensor output (v) battery charge (%) sg sg (proteus simulation) battery (%) (proteus simulation) 1 1.10 0.014 02 1.104 1.099 0 2 1.14 1.223 24 1.138 1.137 24 3 1.18 2.317 48 1.185 1.172 46 4 1.22 3.500 74 1.230 1.210 69 5 1.26 5.000 98 1.259 1.258 99 fig. 11 comparison of the proposed method using glass hydrometer 4.7. linearity and sensitivity testing and comparison with optical fiber sensor an optical fiber sensor [13] has an output of a minimum of 1 v and a maximum of 4 v for a change in the sg from 1.1 to 1.26, respectively. a refractometric optical sensor has an output of a minimum of 0.25 v and a maximum of 2.5 v for a change in the sg from 1.1 to 1.26, respectively [15]. the sensitivity of the mpxv4006dp mems sensor increases if the range of the amplified signal is increased more than that of the optical sensor. hence, to increase sensitivity, mpxv4006dp mems sensor output is amplified from 0 v to 5 v for the same range of sg using rg. fig. 12 comparison of mems, refrometric, and fiber optical sensors the sensitivity of the sensor can be calculated using the formula, sensitivity = the change in output/change in input. the sensitivity of the optical fiber sensor is 18, the refractometric optical sensor has a sensitivity of 14, and the sensitivity of the mems sensor is 32. the sensitivity of the mpxv4006dp mems sensor is significantly higher than that of the optical fiber sensor and the refractometric optical sensor, as the mems sensor has a larger slope than optical sensors. four samples have been examined to get the variation of the sensor output concerning sg. as shown in fig. 12, it is observed that the amplified output of the mpxv4006dp mems sensor is directly proportional to the sg of the lead-acid battery. sg s en so r o u tp u t (v ) mems sensor refrometric sensor fiber optical sensor s g ( 2 0 °c ) soc (%) glass hydrometer method the proposed method 5 4.5 4 3 3.5 2.5 2 1.5 0.5 1 0 1.1 1.12 1.14 1.16 1.18 1.2 1.22 1.24 1.26 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 147 4.8. effect of temperature on change of the sg of electrolyte solution as shown in fig. 13, the temperature effect on sg variation is simulated at 10°c and 40°c using proteus. the solution of electrolyte exposed to different temperature conditions using a borosilicate glass pot, heater, and reading of the system has been analyzed to observe the effect of varying temperatures. when the temperature of the electrolyte is high at 40°c, the sg decreases, and when the temperature becomes low, i.e., 10°c, sg increases, and observations are noted in table 5. as shown in fig. 14, the temperature effect on sg variation is observed at 10°c and 40°c. as shown in fig. 13, with changes in temperatures, sg varies slightly but keeps linearity constant. fig. 13 sg measurement with proteus at different temperatures fig. 14 sg measurement with glass and mems hydrometer at different temperatures table 5 variation in the sg measured using glass and mems hydrometer at 10°c and 40°c no. temperature 10°c temperature 40°c glass hydrometer sg sg (simulation) glass hydrometer sg sg (simulation) 1 1.11 1.05 1.10 1.08 1.02 1.098 2 1.15 1.14 1.138 1.12 1.11 1.136 3 1.19 1.19 1.174 1.16 1.16 1.171 4 1.23 1.24 1.212 1.20 1.22 1.209 5 1.25 1.26 1.260 1.22 1.23 1.257 5. conclusions in this study, a short air purge system integrated with the mems pressure sensor designed for measuring sg online has been proposed and realized. the proposed method is basic, but it can measure an extremely small change in sg with great accuracy compared to conventional methods. no extra signal conditioning is necessary for temperature compensation as it is incorporated in the software. such an air purge system has better sensitivity and range as compared to other optical sensors. the sg with ±0.002% resolution as well as the battery charge percentage with ±1% resolution have been recorded by this mems-based hydrometer. in the future, auto-calibration of the measurement system can be considered, as it can be useful in fixing errors. this technique can also be utilized to measure the sg of milk, seawater, ethylene glycol, benzene, refrigerant r-22, and crude oil in process industries. acknowledgment the authors sincerely thank the instrumentation and control department, college of engineering, pune (coep) for the financial support in filing a patent and publication. samples s g s g samples 1.28 1.26 1.24 1.22 1.2 1.18 1.16 1.14 1.12 1.1 1.08 0 4.5 4 3 3.5 2.5 2 1.5 0.5 1 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1 4 3 2 5 sg at 40°c sg at 10°c glass hydrometer at 10°c glass hydrometer at 40°c mems hydrometer at 10°c mems hydrometer at 40°c 148 advances in technology innovation, vol. 8, no. 2, 2023, pp. 136-149 abbreviations and symbols soc state-of-charge sg specific gravity lm35 linear monolithic mems micro electro mechanical system ∆� differential pressure �� output voltage of the mpxv4006dp sensor h head between the tubes �2 zero adjustment voltage ∆� change in the density of acid �0 amplified output voltage of ad-620 g gravitational constant g gain of ad-620 ����� sg of the environmental factor ���°� sg of the solution at 20°c temp acid temperature of the lead-acid battery dr discharge rate rg gain resistor conflicts of interest the authors declare no conflict of interest. references [1] s. kim, m. kwon, and s. choi, “operation and control strategy of a new hybrid ess-ups system,” ieee transactions on power electronics, vol. 33, no. 6, pp. 4746-4755, june 2018. 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[27] c. liu, w. ren, b. zhang, and c. lv, “the application of soil temperature measurement by lm35 temperature sensors,” proceedings of 2011 international conference on electronic & mechanical engineering and information technology, vol. 4, pp. 1825-1828, august 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v8n4(2023)-aiti#11957(267-277).docx advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 english language proofreader: chih-wei chang virtual modeling of an industrial robotic arm for energy consumption estimation jin-siang shaw1,*, yi-hua huang2 1department of mechanical engineering, national taipei university of technology, taiwan, roc 2institute of mechatronic engineering, national taipei university of technology, taiwan, roc received 13 april 2023; received in revised form 03 july 2023; accepted 04 july 2023 doi: https://doi.org/10.46604/aiti.2023.11957 abstract this study aims to improve the traditional control methods of industrial robotic arms for path planning in line with efforts to conserve energy and reduce carbon emissions. the digital twin of a six-axis industrial robotic arm with an energy consumption model is innovatively designed. by directly dragging the end effector of a digital twin model, the robotic arm can be controlled for path planning, allowing path tuning to be easily made. in addition, the dynamic equation of the industrial robotic arm is derived, and the energy consumption of the corresponding path can be estimated. four cases are designed to test the validity of the digital twin. experimental results show that the physical robotic arm follows its digital twin model with the corresponding energy consumption computed. the estimated energy consumptions agree quite well with each designed case scenario. keywords: digital twin, robotic arm, unity, euler-lagrange equation, energy consumption 1. introduction in the advanced 21st century, technologies, such as the internet of things (iot), cloud computing, big data analysis, and intelligent robot systems, will cause changes in the global manufacturing industry and lead to an era of intelligent manufacturing in industry 4.0. with the advent of industry 4.0, there has been remarkable growth in the synergistic integration of existing and emerging technologies, for example, the digital twin (dt) in robotics [1], the predictive maintenance based on dt [2], and the dt-driven machining [3]. moreover, gartner predicted that more than 20 billion us of equipment (mostly from the manufacturing industry) would be applied to iot technology [4]. in industry 4.0, engineers need to establish iot and cyber-physical systems for coordinating smart factories, with digital twins playing a crucial role [5]. through computer-integrated manufacturing, digital information technology, data analysis, and data-driven services, appropriate and practical production integration can improve the efficiency, productivity, and flexibility of the production process [6-8]. a virtual model in a dt can use this information to monitor, optimize, and predict real objects by accessing their physical properties, behaviors, and specifications [9]. therefore, the dt concept is considered a promising and innovative research field. however, owing to the complexity of constructing a digital model corresponding to physical space in a virtual space, its application in the field of industrial manufacturing is rarely observed. although digital twinning has been widely recognized as a futuristic and innovative research field, its applications in industrial manufacturing are uncommon due to the complexity of developing digital models in a virtual space that corresponds to and replicates a physical space. currently, most of the research papers and applications related to robotic arms and digital twinning are focused on establishing teaching and demonstration scenarios [10-12]. * corresponding author. e-mail address: jshaw@ntut.edu.tw advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 268 the windows operating system is widely used worldwide, as shown in fig. 1 [13]. the most significant difference between ros and windows is the complexity of ros operations. while most software today is designed based on the windows operating system architecture. its scalability is far more convenient than that of ros, and the resources are more abundant. since most people have been in contact with computers set up under the windows operating system architecture since childhood, they are familiar with the operating interface and use computers with much greater proficiency than those under ros architecture. as a result, there is no need to invest additional time learning the two operating systems, ubuntu and ros, and only one operating system can be used to complete the robot research. fig. 1 global desktop operating system market share [13] according to the world robotics 2022 industrial robots report released by the international federation of robotics, there are currently 3.5 million industrial robots used in global factories, and approximately 510,000 units were delivered globally in 2021. the applications include handling, welding, assembly, cleaning, distribution, etc. [14]. however, many industries have not invested in robot-related technologies, and the main problem lies in the limitations of traditional robot control methods. considerable knowledge and technological intervention are required to make it operate normally, which seriously constrains the development of the robotics industry. furthermore, revenue from industrial robots continues to grow globally, and there is a huge energy cost to drive these automated systems with multiple robots operating [15]. typical energy consumption modeling methods for robots rely on kinematic and dynamic characteristics to calculate energy consumption. heredia et al. [16] established mathematical models of robotic arms for energy consumption calculation. these models were parameterized and trained through collected experimental data to evaluate their accuracy. another approach involved using a trained multilayer perceptron (mlp) or resnet model to predict the relevant energy consumption of the robotic arm [17-18]. however, the aforementioned data-driven modeling required a large amount of training data collected from various sensors. in this study, the corresponding energy consumption can be computed solely by the derived energy consumption model with the provided angular speeds of each joint from the dt, and no need to collect training data. this study aims to create a dt and energy consumption model in the windows framework, in which the physical robotic arm moves by dragging the end effector of the virtual robotic arm. in other words, the physical robotic arm can be collaborative in this manner, and the energy consumption of the corresponding path can be computed. with the energy consumption evaluated, the planning path with the lowest energy consumption value can be selected for the physical robotic arm to operate, resulting in significant energy savings. advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 269 2. methodology although the simulation of a robotic arm in ros using moveit, gazebo, and rviz is quite common, no cases have been found that utilize the ros framework in constructing a digital twin model capable of estimating energy consumption for robotic arms. in fact, to the best of the authors’ knowledge, no research has been reported on using the dt model that can predict the corresponding energy consumption for robotic arms under either the windows or ros system. since windows is the most popular operating system in the world, the development of a dt of an industrial robotic arm under the windows architecture is planned. the system architecture is illustrated in fig. 2. model preprocessing of the industrial robotic arm is primarily performed because the initial industrial robotic arm model is not similar to that under the ros architecture. instead, similar to the unified robot description format (urdf) file, the urdf file includes all relevant information regarding the industrial robotic arm, such as the pivot point, rotation range, and hue of each joint. therefore, it is necessary to preprocess the original model using computer graphics software. after processing, the model is exported to unity, a software used as a dt. to allow data transmission between the industrial robotic arm and dt software, it is necessary to establish network communication between the two, enabling the realtime transfer of important data required to simulate the state of the physical robot arm in the dt, and vice versa. this study used the “socket” developed in the tcp/ip environment to transfer data between the two. this approach differs from previous control methods of transmitting the world coordinate position of an industrial robot arm and the current rotation angle of each joint. this decision allows users to understand the movement patterns of an industrial robot arm better when it is being controlled for the first time. in addition, a human-machine monitoring interface is established for allowing users quickly understand the system status and control the industrial robotic arm in real-time. to meet the requirements of remote connection control, this interface integrates functions, such as robot arm communication and the real-time angles of each joint. finally, the dynamic equation of the six-axis industrial robotic arm is calculated using the euler-lagrange equation. hence, the required torque of each motor can be estimated for any specific path. fig. 2 system architecture diagram 2.1. building digital twins – unity in this study, the unity software was used to build the dt, which is a cross-platform 2d/3d game engine developed by unity technologies, a game software development company. generally, unity supports the following aspects. first, unity can be used to develop stand-alone games for windows, macos, linux, and other operating systems. second, it’s also available for games on mobile devices such as ios and android. in addition to game development, unity is widely used in the production of real-time 3d animations, architectural visualizations, and other types of projects. lastly, it supports the physx physics engine and particle system and provides network multiplayer connection functionality without requiring the user to learn a complex programming language. given this advantage, it meets the various requirements of game production. thus, the launch of unity has lowered the threshold for game development and made game creation for individuals and small teams realistic. 2.2. industrial robotic arm model preprocessing before exporting the model to the unity game engine, the industrial robotic arm model must undergo preprocessing. meanwhile, the relationship between the joints and connecting links must be defined. the staubli tx60l industrial robotic advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 270 arm used in this study has a cad model in the standard triangulated language (stl) format, which is the output from the stp format provided by the manufacturer staubli through solidworks. this format can be used in blender computer graphics software. the parent-child relationship must be defined in blender computer graphics software. therefore, by defining the parent-child relationship of each link of the industrial robotic arm, the concept of this relationship can be controlled effectively, as shown in fig. 3. for example, when turning “axis-1,” all the links that have a parent-child relationship will follow because “axis-1” is defined as the parent of “axis-2” to “axis-6.” it does not affect the base, so the base will not move. however, if the base is moved, the entire model will move along with it because the base is the parent from “axis-1” to “axis-6,” and it indicates the relative relationship of the six axes (axis-1, axis-2, axis-3, axis-4, axis-5, and axis-6) as shown in fig. 4 [19]. fig. 3 parent-child relationship fig. 4 3d model and the relationship of each axis in addition to the above settings, the pivotal point of each link must be specified. the pivot point, also known as the joint center point, defines the motion of the links [20]. the parent-child relationship specifies the motion between the links and the pivot point specifies the motion of the joints, as shown in fig. 5. fig. 5 axis-1 pivot point setup 2.3. kinematics of the industrial robotic arm there are several methods to achieve the movement of a robotic arm by dragging the end effector in a virtual environment. one of the most commonly used methods is the cyclic coordinate descent (ccd) algorithm [21-22]. a popular approach for implementation is to use bio ik [23]. bio ik is the solution of inverse kinematics problems by utilizing a ccd algorithm for calculations. this study used the ccd algorithm for solving inverse kinematics problems and the traditional denavithartenberg (dh) parameter method for solving forward kinematics. by using the fast and less computationally intensive ccd algorithm and traditional dh parameter method, this study aimed to solve forward and inverse kinematics problems. advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 271 the ccd algorithm is currently one of the simplest and most popular methods for solving inverse kinematics, and it has been widely used in the computer game industry. the ccd algorithm calculates from one joint to another joint angle such that the endpoint is as close as possible to the target. after each iteration update, the algorithm measures the distance between the endpoint and the target to ensure that the endpoint is far enough from the target or already required to stop computing. additionally, to avoid infinite recursive loops caused by unreachable and conflicting target points, the algorithm must be limited by setting a maximum number of iterations. essentially, the base of an inverse kinematic-driven mechanism is immovable, and the axis and angle are calculated using the formula, respectively, as shown in fig. 6. 1cos e c t c e c t c p p p p p p p p θ −         − − = • − − (1) e c t c e c t c p p p p p p p p r − − × − − = � (2) this method is also applicable to 2d and 3d coordinates by aligning a joint (pc) with the endpoint (pe) and target, and the endpoint is finally approached by reciprocating the above steps towards the target. to solve the problem of forward kinematics [24], this study used the dh parameter method. the dh parameter method designs a coordinate system for each connecting rod according to set rules, and then this coordinate system can be used to describe the transformation relationship from one connecting rod coordinate system to the adjacent connecting rod coordinate system. the transformation of the adjacent coordinate system is decomposed into several steps with only one parameter respectively. the combination of the corresponding transformations completes the transformation of the adjacent coordinate systems. fig. 6 ccd algorithm flow 2.4. digital twin user interface for the industrial robotic arm two scenarios were considered in this study. the first scenario used forward kinematics to control the virtual robotic arm and synchronously moved the physical robotic arm. when the physical robotic arm was controlled by the robotic arm user interface, the virtual robotic arm moved synchronously. as shown in fig. 7, after pressing the start received button (button 1), the arm begins to receive the six joint information read from the cs8c controller. this information was used to move the virtual robotic arm into a physical robotic arm. each joint of the virtual robotic arm can be rotated by controlling the plus/minus advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 272 buttons (button 2) of each joint. the rotation angle information was transmitted to the physical robotic arm which rotated accordingly. after achieving the goal of mutual control between the two parties, press the quit game button (button 3) to end the currently executing scene. fig. 7 unity digital twin scene 1 the second scene primarily involves moving the virtual robotic arm through inverse kinematics, as shown in fig. 8. in this scene, a red sphere was designed as the target object (target). the end effector moved with the target object. the movement of the virtual robotic arm was controlled by dragging the target object. when it moved to a position, the dragging was stopped, and the angle of each joint was calculated using the ccd script designed in unity. this angle information was sent to the physical robot arm such that it could move like a virtual robotic arm. the goal was to control the physical robot arm by dragging the dt end effector. the point correction of a traditional industrial robotic arm was significantly reduced by dragging the dt end effector to the designated target point for the corresponding work settings, which makes it more flexible and can be used in complex environments. such a dt with a user interface can also be used to establish a fully realistic workplace and perform path planning and other operations on the robotic arm through a remote control, thereby enabling task completion without entering the factory. fig. 8 unity digital twin scene 2 2.5. matlab energy consumption calculation with the gradual advancement of science and technology and the development of digital avatar-related technologies, factories are moving towards smart manufacturing, and smart factories are becoming a major trend. through these technologies, factory personnel can monitor the internal conditions of a factory in real-time using computers and mobile phones. with the advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 273 rise of international oil prices and the improvement of green energy-related technologies, taiwan officially announced the “taiwan 2050 net zero emissions path and strategy general description” in march 2022 [25]. energy conversion is a critical issue for achieving the goal of net-zero emissions. in the current situation, where green energy and other related technologies are not yet mature, effective management of equipment energy consumption in factories is crucial. this study aimed to address this issue using the dt of the robot arm in unity and inputting the simulated robotic arm path into matlab for energy consumption estimation. therefore, a dynamic model of a robot arm, which is a complicated and nonlinear system, is required. this study used a dynamic model of the robotic arm to calculate the torque of each joint motor through the moving path of the robotic arm dt environment established above and computed the total energy required for this moving path. the purpose was to allow users to use unity to first perform path planning with the dt of the robotic arm and then obtain the total energy consumption of the path through matlab calculations. this method enabled users to carry out various path planning through the digital avatar of the robotic arm and the realistic environment of the actual scene. by analyzing different paths, users can select and execute the path that consumes the least amount of energy. after obtaining the path that consumed the lowest energy, the physical robotic arm could operate according to the path. in robotics, the euler-lagrange equation can be used to calculate torque [26]. , 1, ,i i i d l l i m dt q q τ ∂ ∂ − = = ∂ ∂ … ɺ (3) the lagrangian, l, is defined as the kinetic energy minus the potential energy. l k p= − (4) the kinetic and potential energy equations of the n-link robotic arm are expressed in: ( ) ( ) ( ) ( ) ( ) ( ) 1 1 2 n t t tt i vi vi wi i i i wi i q m j q j q j q r q i r q j q qk =      += ɺ ɺ (5) 1 1 n n t i ci i i i p p g r m = = = =  (6) where �� and q denote vectors of joint angular velocity and position, respectively, n denotes the total number of joints, �� denotes the torque of the ith motor, �� denotes the mass of the ith link, ��� � and ��� � represent the jacobians of the ith link speed and angular velocity, respectively, �� � denotes the orientation matrix of the ith link, �� denotes the inertia tensor of the ith link, g denotes the gravity vector, and finally ��� denotes the mass center vector of the ith link. after obtaining the equations for kinetic and potential energies, eqs. (5) and (6) are substituted into eq. (4), and eq. (4) is substituted into eq. (3), which can be used to obtain the dynamic equation of the robotic arm in a vector-matrix form. ( ) ( ) ( ),q q c q q q g qm τ+ + =ɺɺ ɺ ɺ (7) where �� represents the vector of joint angular acceleration. m represents the n × n inertia matrix, c represents the n × n matrix of the coriolis force and centrifugal force, and g represents the gravity of the n × 1 vector. parameters in m, c, and g in eq. (7) will be identified by the cad model provided by the manufacturer staubli, such as the geometry and property of each link, the link’s moment of inertia, etc. the joint variable q can be obtained by applying the ccd algorithm for the inverse problem. therefore, the torque of each link executing the path �� , �� , and q can be computed in eq. (7) by summing the three terms on the left-hand side. the total power required for the robotic arm is then estimated by 1 τ θ η ==  ɺ n i i i i p (8) advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 274 where �� is the transfer efficiency of the ith motor. the resulting energy consumption of the robotic arm for this path is determined by integrating the power over time, 0 ft t w pdt=  (9) where �� is the final time; �� is the initial time. it is noted that the dynamic equation in eq. (7), an often-seen model for a robotic arm in the literature, does not consider friction between the robots’ joints. this is because friction in robot joints including coulomb friction and viscous friction is difficult to exactly identify the power it consumes constitutes only a small part of the total power. here �� is used to represent the transfer efficiency of the ith motor to reflect this friction power loss. by performing these calculations in eqs. (7)-(9), it can determine the energy consumption required for different paths and hence select the path with the lowest energy consumption to perform the work. 3. exmental and result this study moved the end effector in four different scenarios, as shown in fig. 9: case 1 involved moving in a straight line, case 2 involved moving twice the distance of case 1, case 3 involved moving in a small circle, and case 4 involved moving in a large circle. these scenarios allowed us to compare the energy consumption of cases 1 and 2, where the moving path of case 2 was twice that of case 1, resulting in higher energy consumption. similarly, the energy consumption in case 3 was expected to be lower than that in case 4. (a) case 1 (b) case 2 (c) case 3 (d) case 4 fig. 9 different cases of the simulation for energy consumption advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 275 in case 1, the distance between a and b was 0.5 m. in case 2, it was 1.0 m. in the case of circular motion, the large circle had a radius of 0.5 m, and the small circle had a radius of 0.25 m. the movement speed was set to 4 cm/sec for case 1, where case 2 had twice the speed of case 1. the movement speed was set to 11 cm/sec for case 3, where case 4 had twice the speed of case 3. the reason for choosing low speed in experiments was to facilitate the integration of the virtual and physical environments, which made it easier to control the robotic arm and avoid collisions and other factors. as shown in fig. 10, the total power diagram was calculated using eqs. (7) and (8), while eq. (9) was used to compute the resulting energy consumption. table 1 listed the final energy consumption for each case, which agreed with the predictions. specifically, when the robotic arm’s travel distance and travel speed were doubled, the corresponding energy consumption was also more than doubled (nonlinear), as seen in case 2 over case 1 and case 4 over case 3. moreover, the ratio of energy consumption of case 2 over case 1 (2.9) was slightly larger than that of case 4 over case 3 (2.4). this can be attributed to the fact that a straight-line trajectory (cases 1 and 2) requires more joints to execute compared to a circular trajectory (cases 3 and 4) for an articulated robotic arm. additionally, in eq. (9), it was evident that the energy consumption was highly nonlinear concerning the operational conditions. to verify and validate the accuracy of the energy consumption model, appropriate sensors such as torque and angular speed sensors can be installed on the robotic arm to compute the true energy consumption values. however, it remains a task for future work. (a) case 1 (b) case 2 (c) case 3 (d) case 4 fig. 10 power response for each case table 1 energy consumption of each case case energy consumption (j) 1 38 2 91 3 95 4 195 advances in technology innovation, vol. 8, no. 4, 2023, pp. 267-277 276 4. conclusions and future work the research utilizes the unity game engine and the robotic principle of the euler-lagrange equation to establish a digital twin and energy consumption model for an industrial robot arm. the final energy performance is described through four case studies. it was observed that the motion length also influenced the calculated energy expenditure accordingly. by directly manipulating the end effector of the dt model, the industrial arm can be easily controlled remotely for task scheduling without the need to physically enter the factory, introducing a new form of control. additionally, the digital twins and energy consumption models have demonstrated a reasonable level of accuracy. in future studies, dt models of robotic arms capable of handling various loads in real-world applications will be considered. to enhance the accuracy of the energy consumption model, installing torque, comparing the results with the model’s estimated energy consumption, and the angular velocity sensors on the physical industrial robotic arm to measure its energy consumption are required. conflicts of interest the authors declare no conflict of interest. references [1] a. mazumder, m. f. sahed, z. tasneem, p. das, f. r. badal, m. f. ali, et al., “towards next generation digital twin in robotics: trends, scopes, challenges, and future,” heliyon, vol. 9, no. 2, article no. e13359, february 2023. 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[25] national development council, “taiwan’s 2050 net-zero emission,” https://www.ndc.gov.tw/content_list.aspx?n=fd76ecbae77d9811, march 30, 2022 [26] m. w. spong, s. hutchinson, and m. vidyasagar, robot modeling and control, 1st ed., new jersey: wiley, 2005. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 5___aiti#8909___131-142 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 finite element and neural network based predictive model to determine natural frequency of laminated composite plates with eccentric cutouts under free vibration mohamed rida seba * , said kebdani applied mechanics laboratory, faculty of mechanical engineering, university of science and technology oran mohamed-boudiaf, oran, algeria received 12 november 2021; received in revised form 29 december 2021; accepted 30 december 2021 doi: https://doi.org/10.46604/aiti.2022.8909 abstract this research proposes a predictive model to identify changes in the mechanical and geometrical properties of composite plates with eccentric cutouts based on natural frequency. finite elements (fe) and neural networks are used to develop the model based on machine learning. first, the numerical analysis of free vibration is performed by the fe model on the laminated composite plates with a stacking sequence [0/90]2s under a clamped-free (cfff) boundary condition. the outputs of the fe model (520 configurations) are then utilized to train the artificial neural network (ann) model through the levenberg-marquardt method, and the developed ann model is then used to evaluate the influence of various parameters on the natural frequency. the results show that the changes in the mechanical and geometrical properties of composite plates have impacts on the natural frequency. furthermore, the findings of the ann model are substantially identical to those of the numerical model, with a small margin of error. keywords: artificial neural network, free vibration, finite element model, cutout, natural frequency 1. introduction laminated composite plates have been widely used in structural engineering due to their reduced weight, extended durability, and fatigue resistance. because of these qualities, they are gaining attention in other engineering fields. cutouts are generally used for ventilation, i.e., the passages for cables and fluids. they can have different shapes, e.g., square, circular, oval, or triangular shapes. however, their existence can have a major impact on the vibratory [1-3], static [4-6], and buckling [7-9] behavior of structures. concerning the vibration behavior of structures, pham et al. [10] considered plates that are completely or partially in contact with fluid and analyzed them with isogeometric analysis (iga) for free vibration. pham et al. [11-12] used the finite element (fe) method to investigate the hygro-thermo-mechanical vibration of double-curved and functionally graded porous (fgp) sandwich plates as well as nanoplates made of functionally graded materials (fgm). pham et al. [13] employed the es-mitc3 element to analyze the free vibration of fgp annular-nanoplates with non-uniform thickness. in addition, nguyen et al. [14] used the es-mitc3 element to investigate the free vibration of fgp plates positioned on partially supported elastic foundations (psef). rai [15] also used fe to examine the nonlinear behavior of reinforced concrete (rc) deep beams. pham et al. [16] conducted a monte carlo simulation using fe analysis to evaluate the natural frequency of rc beams. the free vibration of fgp nanoplates lying on a two-parameter elastic media foundation was explored by pham et al. [17]. * corresponding author. e-mail address: mohamedrida.seba@univ-usto.dz advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 recently, vibration response has emerged as an essential technique in structural health monitoring (shm) [18]. a change in a structure’s natural frequency is one of the indicators of a change in its mechanical or geometrical properties or of the presence of damage. several researchers have investigated natural frequency to detect composite plate defects, such as delamination [19-20] and cracks [21-22]. nowadays, the influence of cutouts on composite laminates is studied mainly using numerical analysis, with the fe analysis more specifically. sivakumar et al. [23] presented a ritz fe model to analyze the free vibration of laminates with cutouts. ovesy and fazilati [24] proposed two variants of the finite strip method (fsm) for analyzing the free vibration of composite plates with cutouts. venkatachari et al. [25] used the extended fe technique to investigate the impact of environmental factors on the free vibration of structures. boay [1] developed an fe method for calculating the free vibration of symmetric laminated composite plates with a central hole. artificial neural network (ann) is an artificial intelligence technology widely used for prediction in a variety of engineering fields. several studies in different fields are presented here. truong et al. [26] integrated ann with differential evolution (de) to optimize the material distribution of bidirectional functionally graded (bfg) beams in free vibration. yildirim [27] investigated the free vibration of axially functionally graded (afg) and transversely functionally graded (tfg) beams using the ann model. furthermore, for fgm beams with varied gradation orientations and layer counts, the natural frequency was estimated using the fe approach. to analyze functionally graded annular plates under various boundary conditions, jodaei et al. [28] applied both the differential quadrature and ann techniques. tran et al. [29] developed an ann model to forecast the fundamental frequency of fgm plates by fe in a thermal environment using the es-mitc3 element. due to the intricacy of laminated composites with cutouts, artificial intelligence was introduced to detect changes in natural frequency (i.e., mechanical and geometrical changes in the structures). reddy [30] proposed a method for predicting the natural frequency of laminated composite plates using ann under clamped boundary conditions. altabey [31] predicted changes in the natural frequency of plates supported elastically. timchenko and osetrov [32] proposed convolutional neural networks (cnn) for predicting the natural frequency of composite plates. ann was also used to evaluate the environmental effect on the vibrational response of a skew composite laminated sandwich plate [33]. based on the findings of previous studies, this work aims to expand the use of the fe model to analyze the free vibration of nonlinear layered plates with eccentric square cutouts under clamped-free (cfff) boundary conditions. the study of several parameters, such as cutout size ratio (d/a), number of cutouts, modular ratio (e1/e2), length-to-width ratio (a/b), and thickness ratio (h/a), is carried out using the fe software. the results of the fe model are used to develop an ann model to predict natural frequency. the strategy is to use 240 data points to train, test, and validate the developed model. the study is limited to the first two modes of vibration. the influence of cutout size, number, and modular ratio on the natural frequency is then studied in a more general scope. 2. the fe model 2.1. free vibration analysis the free vibration analysis of structures requires the solution of the following equation, called the eigenvalue problem. the frequency of plates can be obtained easily by the solution of the standard characteristic equation: 2[ ]{ } [ ]{ } {0}k m∏ − ∏ =ω (1) where �∏� denotes the transverse displacement vector, k is the stiffness matrix, and m is the mass matrix. the formula can be directly used to calculate the natural frequency of the plates under free vibration. 132 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 2.2. material the model developed for this study, as shown in fig. 1, is inspired by the elastic composite stacking sequence [0/90]2s considered by sinha et al. [34]. the composite laminate square model is modified by introducing a group of eccentric cutouts. the sizes and number of cutouts, in addition to the dimensions and the modular ratios of composite plates, are all considered parameters. the properties of the material used in this study are listed in table 1. the position of the cutouts according to the x-axis is considered ex/a = 0.125 for all the scenarios. table 1 mechanical properties of the material used in this study material glass fiber-reinforced polymer (gfrp) [34] e1 (n/m 2 ) 16.07 × 10 9 e2 (n/m 2 ) 16.07 × 10 9 g1 (n/m 2 ) 2.81 × 10 9 v12 0.25 density � (kg/m 3 ) 1664 fig. 1 laminated composite plate with dimensions 2.3. fe simulations the simulations are undertaken using abaqus. to determine the natural frequency, the fe method analysis is performed in a cfff configuration on several specimens of laminated plates with cutouts. the size, number, length, thickness, and modular ratios of specimens are all different from one another. 2.4. convergence as a starting point, the simulation convergence with respect to different mesh sizes is verified by calculating the natural frequency for two mode shapes under boundary conditions (cfff), as shown in table 2. the result in terms of mesh density and mode shapes with respect to the chosen mesh size of 2 is represented in fig. 2. table 2 natural frequency in two mode shapes versus mesh size size natural frequency (hz) for laminated composite plates with cutouts [0/90]2s first mode shape second mode shape 4 69.605 26.187 3.5 62.817 26.168 3 56.777 26.156 2.5 52.696 26.145 2 50.318 26.140 1.5 49.119 26.137 (a) mesh density (b) first mode shape of the plate (c) second mode shape of the plate fig. 2 models of fe and mode shapes for laminated composite plates 133 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 2.5. validation of the fe model the numerical model is validated by comparing the natural frequency in hz for cfff plates that have the length of 0.235 m corresponding to the first mode predicted by this study to those provided by sinha et al. [34] with the same parameters. as shown in table 3, the parameters used in this study, especially the size and position of the cutouts, are same as those in the work of sinha et al. [34]. table 3 comparison of the parameters used in this study and in the work of sinha et al. [34] 3. development of the ann model 3.1. artificial intelligence artificial intelligence is considered one of the most important and fastest developing fields in scientific research. this is due to the difficulty of finding solutions to many problems using conventional methods. anns are preferred among all the artificial intelligence types due to many characteristics: good data security throughout the whole network, the ability to function with less information, excellent fault tolerance, and the ability to train a machine using distributed memory and parallel processing capability. 3.2. parameters and numerical data the numerical model built in the previous section is used to acquire a dataset of 260 natural frequency values in each vibration mode. the feed-forward backpropagation network is implemented using matlab. the following entry variables are fed to the input layer: the size ratio (d/a), number of cutouts, modular ratio (e1/e2), length-to-width ratio (a/b), and thickness ratio (h/a) of the plates. the neurons are in the hidden layer, whereas the number of neurons is in the output layer. the number of neurons in the last layer is two, which represents the number of vibration modes. the input and hidden layers are served by tan-sigmoid transfer functions, while the output layer is served by a linear transfer function. table 4 lists the parameters used to construct the dataset. the neural network is designed, developed, and deployed using the neural network toolbox in matlab. table 4 simulation parameters size ratio (d/a) 0.1/0.2/0.3 number of cutouts 1/2/4 modular ratio (e1/e2) 1/2/3/4 length-to-width ratio (a/b) 1/2/1.5 thickness ratio (h/a) 0.012/0.018/0.024 in this study, a multilayer feed-forward neural network (ffnn) is used to determine the natural frequency. it consists of a single input layer, one or more hidden layers, and a single output layer. a neural network with a single hidden layer can handle the most complicated functions. the basic neural network model is denoted by: ( )ij i j i j w x b= +∑ρ ψ (2) fig. 3 depicts a neuron’s schematic structure. parameter [34] this study error position of cutout size of cutout experimental fe model ex/a = ey/b = 0.25 d/a = 0.1 28 26.2 26.13 1.87 d/a = 0.2 32 26.8 26.76 5.24 ex/a = 0.25 and ey/b = 0 d/a = 0.1 24 26.2 26.14 2.14 d/a = 0.2 20 26.9 26.8 6.8 134 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 fig. 3 structure of a neuron �� denotes the set of inputs for every neuron. the collection of outputs for each neuron is indicated by ��, while the bias set for each neuron is given by ��. the weight coefficient �� is multiplied by every input and then summed with a bias b of neurons to generate the net input n, which may be written as: 1 k j j jn w x b = = +∑ (3) the mathematical notation ji corresponds to the input i in neuron j. the net input n is then sent via an active function , which gives the neuron output �. ( )ρ = f n (4) the hyperbolic tangent sigmoid activation function is used in this investigation. the following formula may be used to express it: ψ − − −= + n n n n e e e e (5) as a result, fnnn with a single input layer and one hidden layer in fig. 4 implements the equation below: 2 2 2 1 1 1 2 1 1 1 )( n k i j ij j iia w w x b b = = = +       +  ∑ ∑ψ ψ (6) where � signifies the entire network output. the activation functions of the hidden layer and output layer, accordingly, are represented by � and . k and n denote the number of inputs and neurons in the hidden layer, respectively. � is the neuron’s bias within the output layer. �� is the weight that connects the ith hidden layer resource to the output layer neuron. fig. 4 depicts the conceptual architecture of the model. fig. 4 architecture of the proposed ann predictive model 135 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 3.3. levenberg-marquardt algorithm training neural networks are basically nonlinear least-squares problems that can be solved using a class of nonlinear least-squares algorithms. among them, the levenberg-marquardt approach is regarded as the most efficient algorithm for training anns. it is based on newton’s approach, which was developed for minimizing sums of squares error functions, such as the form below: 1 2 1 ( ) ( ) ( ) ( ) 2 t i n jf x u u x u xx = = =∑ (7) where �� is the error in the n th pattern, u is the vector with elements ��, and � = ( �, , �, …… , �) � contains all of the network’s weights. the sum of squared errors function is denoted as: 1 ( ) ( ) ( ) 2 t f w u w u w= (8) newton’s approach is used to maximize a performance index �( ): 1 1n n n nw w a g− + = − (9) 2 ( ) n n w w a f w = ≡∇ (10) ( ) n n w w g f w =≡∇ (11) where � �( ) is the hessian matrix and ��( ) is the gradient obtained as follows. ( ) 2 ( ) ( )t f w j w u w=∇ (12) 2 ( ) 2 ( ) ( ) 2 ( )t f w j w j w s w= +∇ (13) j(w) represents the jacobian matrix: 11 11 11 1 2 12 12 12 1 2 1 1 1 1 2 1 1 1 1 2 2 2 1 1 2 2 ( ) n m m m p p p n p p p pm p n m n n u u u w w w u u u w w w u u u w w w j w u u u w w w u u u w w w u u w = ⋮ ⋮ ⋱ … … ⋱ … … … … … … … ⋱ … … … ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ ∂ 2 n pmu w w                                                … ∂ ∂ (14) where p stands for the number of training patterns and m defines the number of output patterns. 136 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 2 1 ( ) ( ) ( ) n i i is w v w v w = =∑ ∇ (15) the hessian matrix can be estimated as follows if s(x) is considered to be small. 2 ( ) 2 ( ) ( )t f w j w j w=∇ (16) substituting eqs. (11) and (15) into eq. (8), the gauss-newton method can be obtained as: 1 )∆ ( ( ()( ) )t t k k k k kw j w j w j w u w −  = −   (17) the gauss-newton method has a problem in that the matrix may not be invertible. this may be avoided by making the following changes to approximate the hessian matrix: g h i= + µ (18) as a result, the levenberg-marquardt algorithm is expressed as: 1 ∆ ( ( )() ) )(t t k k k k k kw j w j w i j w u w −  = − + µ (19) where i is the identity matrix and the amount � is referred to as the learning parameter in neural computing. the learning parameter is reduced as the iterative procedure nears its end. the levenberg-marquardt algorithm is used in this study, as in the work of hagan et al. [35] and lv et al. [36]. 3.4. validation of the ann model the development of an ann model begins by feeding all the captured data as “given” inputs and “desired” outputs. the data is then divided into three sets: training, validation, and test sets, with the proportions 70%, 15%, and 15%, respectively. the regression coefficient (r) and the mean squared error (mse) are used to validate the generated model’s appropriateness. for all the data, r and mse are 0.99995 and 0.143, respectively. as the optimum network, a hidden layer with eleven neurons is chosen to minimize mse. table 5 shows the findings. the results predicted by the ann model are extremely close to the numerical ones. this proves that ann can successfully forecast the natural frequency of laminated composite plates with a cutout. to examine the performance of the proposed model even more deeply, a regression analysis of the predicted as well as the numerical results is illustrated in fig. 5. the regression coefficients (r) are calculated to determine the correlation between the ann predicted values and those obtained from the fe model, as shown in fig. 6. they are divided into three sets: the training, validation, and test data sets. the value of the coefficient r is between zero and one. the degree of correlation increases as r tends toward one. the ann structure (5-11-2) is the best one in table 5. the convergence tests of ann results are done with mse and the regression correlation coefficient (r): 2 1 1 ˆ( ) n i i mse y y n = = −∑ (20) 2 2 1 2 1 1 ˆ1 ( ) ( ) n n i i i i i r y y y y = =    = − − −       ∑ ∑ (21) where y is the actual value, �� is the predicted value of y, and �� is the mean value of y. 137 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 fig. 5 performance of ann training (a)training results of a neural network regression (b) validation results of a neural network regression (c) test results of a neural network regression (d) neural network regression in all data sets fig. 6 correlation between the values predicted by the ann model with structure (5-11-2) and by the fe model table 5 mse and regression coefficient according to the number of hidden layer neurons ann structure the performance of training training: r validation: r test: r mean squared error (mse) 5-1-2 40.2782 0.98244 0.98178 0.98124 49.157 5-2-2 11.8044 0.99125 0.99529 0.98987 24.133 5-3-2 11.8873 0.99421 0.99661 0.99225 16.094 5-4-2 12.9589 0.99613 0.99452 0.99575 11..775 5-5-2 6.0636 0.99802 0.99788 0.99750 6.028 5-6-2 8.8178 0.99376 0.99785 0.99353 15.627 5-7-2 9.9689 0.99729 0.99736 0.99609 8.449 5-8-2 0.8028 0.99974 0.99968 0.9990 7.940 5-9-2 1.6912 0.99951 0.99953 0.99905 1.588 5-10-2 0.5544 0.99985 0.99980 0.99988 0.433 5-11-2 0.1218 0.99995 0.99995 0.99995 0.12 5-12-2 0.5212 0.99989 0.99980 0.99967 0.424 5-13-2 0.3645 0.99996 0.99987 0.99979 0.294 5-14-2 0.3186 0.99994 0.99990 0.99982 0.244 5-15-2 0.5560 0.99993 0.99982 0.99981 0.298 138 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 3.5. comparison between the numerical and predicted natural frequency for all data sets figs. 7(a)-(b) provide a comparison between the numerical and the ann-predicted natural frequency of the first mode shapes. in terms of absolute error (ae), the highest values are 2.94% and 1.58% for each mode shape, while the lowest values are 0.03% and 0%. overall, the error is close to zero, which proves the validity and the accuracy of the ann model. it is noteworthy that ae is determined using the following relation to the positive value. ˆae y y= − (22) where y is the actual value, and �� is the predicted value of y. the proposed ann model is then used to investigate the effect of several variables on the natural frequency as a function of both geometrical and mechanical parameters. only one parameter is changed at a time, while all others are maintained constant. the sensitivity of the composite plate characteristics with respect to the cutout parameters is investigated in the following sections. (a) the values of natural frequency in the first mode shape (b) the values of natural frequency in the second mode shape fig. 7 comparison of the natural frequency values between the numerical model and the ann model with structure (5-11-2) in two mode shapes 4. analysis of parameters’ effect 4.1. effect of the modular ratio (e1/e2) the influence of the modular ratio on the natural frequency of the cfff laminate composite plate [0/90]2s is studied with the following characteristics: length-to-width ratio = 1, thickness ratio = 0.012, and the square cutout with a size ratio d/a = 0.1. the change in natural frequency of the two vibration modes is predicted for the following combinations: e1/e2 = 1, 2, 3, and 4. table 6 shows that, for the two mode shapes, the value of the frequency decreases as the modular ratio increases. it is worth noticing that the natural frequency corresponding to the modular ratio of 2 and the ones corresponding to 3 and 4 are very close. the lowest natural frequencies are 20.36 hz and 46.37 hz for each mode, and the highest ones are 26.140 hz and 50.316 hz. table 6 natural frequencies of the laminated square plate with different parameters (the modular ratio, cutout size ratio, and number of cutouts) modular ratio (e1/e2) cutout size ratio (d/a) number of cutouts 1 2 3 4 0.1 0.2 0.3 1 2 4 natural frequency of the first mode vibration 26.14 22.41 21.06 20.36 26.14 26.80 27.98 36.06 37.92 39.46 natural frequency of the second mode vibration 50.31 47.78 46.66 46.37 50.31 49.49 48.16 73.16 73.21 73.66 139 advances in technology innovation, vol. 7, no. 2, 2022, pp. 131-142 4.2. effect of the cutout size table 6 also shows the variation in the first two natural frequencies with respect to three different cutout size ratios: d/a = 0.1, 0.2, and 0.3 in the same laminated plate having length-to-width ratio a/b = 1 and thickness ratio h/b = 0.012. it is obvious that the size of the cutout affects the natural frequencies of the composite plate. according to the results, the natural frequency of the specimen and the size of the cutout are proportional. for the first two modes, when the size of the cutout d/a changes from 0.1 to 0.2, 0.1 to 0.3, and 0.2 to 0.3, the natural frequency increases by 2.54%, 1.64%, and 2.23%, then by 7.03%, 4.26%, and 5.53%. 4.3. effect of the cutout number in this part, the effect of the number of cutouts on natural frequency is investigated. the laminated square plate is composed of eight elastic layers [0/90]2s with cfff support in the borders. the natural frequency of the first two mode shapes of the composite plate is determined using a frequency response study. the square laminate utilized has a length-to-width ratio of a/b = 1 and a thickness ratio of h/b = 0.01, whereas the cutout size ratio equals d/a = 0.1 in all three configurations. the results are displayed in table 6. for both the vibration modes, the number of cutouts has an inverse effect on the natural frequency of the laminated composite plates. according to the results, as the number of cutouts increases, the specimen’s natural frequency decreases by a modest amount. the change does not exceed 0.7% for the second vibration mode. 5. conclusions in this study, a neural-network-based approach is proposed to assess changes in the geometrical and mechanical properties of composite plates through the prediction of natural frequency. the main idea is to simulate the composite model numerically with the fe method and use its output to construct and train a successful ann predictive model. the model uses natural frequency as an indicator. after validation, the ann model is used to identify the changes in structures by the prediction of natural frequency. the effects of the main geometrical and mechanical characteristics (e.g., the cutout size ratio (d/a), the number of cutouts, and the modular ratio (e1/e2)) on the natural frequency were investigated. the findings of this study can be summarized as follows: (1) the constructed ann model agrees with the fe model, indicated by a mean squared error near zero. the greatest ae between the numerical model and the ann forecasting model was found to be 4.92% and 1.75% for the first and the second vibration modes, respectively. 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[36] c. lv, y. xing, j. zhang, x. na, y. li, t. liu, et al., “levenberg-marquardt backpropagation training of multilayer neural networks for state estimation of a safety critical cyber-physical system,” ieee transactions on industrial informatics, vol. 14, no. 8, pp. 3436-3446, august 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). 142 microsoft word 5-v10n3(2025)-aiti#14394(269-282).docx advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 multifunctional intelligent helmet to enhanced safety and comfort of laborers in the mining industry harshal ambadas durge1,*, vijay mahadeo mane1, arjun jaggi2, preetish kakkar3 1department of electronic and telecommunication engineering, vishwakarma institute of technology, pune, india 2sr. director, client partner-lifesciences and healthcare, hcltech, california, united states 3senior computer graphics engineer, adobe, washington, united states received 14 october 2024; received in revised form 03 january 2025; accepted 07 january 2025 doi: https://doi.org/10.46604/aiti.2024.14394 abstract this study aims to enhance miner safety through real-time monitoring and emergency responses. to achieve this, a multi-functional mining helmet (mfmh) is designed with location tracking via a global system for mobile communications (gsm) and global positioning system (gps), hazardous gas detection, lighting, and temperature regulation, along with vibration-based alerts for emergency notification. the helmet is tested in simulated mining environments to assess its performance. the system successfully detected hazardous gases at concentrations of 41.23 ppm, triggered automatic lighting when luminosity dropped below 35 lux, and maintained internal temperatures between 26 ℃ and 27 ℃, demonstrating its effectiveness in safety. keywords: miner safety, detection, location tracking, communication, emergency alerts 1. introduction mining operations rank among the most hazardous industries globally, posing significant risks to miners due to frequent exposure to falls, collisions, and dangerous gases such as methane, carbon monoxide, and hydrogen sulfide. these risks are further exacerbated by challenging underground conditions including extreme temperatures and high noise levels. excessive noise hinders miners from hearing critical alert signals, delays responses, and increase the likelihood of accidents. despite advancements in mining management systems and safety protocols, persistent and, to some extent, critical challenges, such as delayed accident reporting and communication breakdowns, continue to impede timely interventions. moreover, extreme underground temperatures pose significant risks, potentially causing heat-related illnesses or fatalities, such as hyperthermia and heat exhaustion, highlighting the urgent need for proactive safety measures. over the years, researchers have developed various intelligent helmet systems aimed at enhancing miner safety. for example, a zigbee-based helmet proposed by deokar and wakode [1] integrated gas sensors, accelerometers, and limit switches to facilitate real-time monitoring and emergency alerts. however, these systems have faced limitations, including sensor durability issues and frequent false alarms. another study by mishra et al. [2] integrated alcohol detection, fall detection, and navigation systems into internet of things (iot)-enabled two-wheeler helmets, but challenges such as sensor accuracy and internet connectivity remained. the helmet by patil et al. [3] incorporated sensors for gas, temperature, humidity, and pulse detection, transmitting alerts via wi-fi and thing-speak. nevertheless, its reliability was affected by wi-fi connectivity issues and sensor malfunctions. * corresponding author. e-mail address: harshaldurge8983@gmail.com 270 advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 a zigbee-based coal mine monitoring system presented by rudrawar et al. [4] detected methane, temperature, and humidity. despite this, it was limited by zigbee’s range and susceptibility to interference. cao et al. [5] presented an innovative design utilizing thermoelectric refrigeration with air and water cooling, which addressed high-temperature challenges; however, despite its advantages, scalability concerns hindered its practical application. a multi-functional electronic helmet developed for road safety, featuring a global system for mobile communications (gsm), a global positioning system (gps), solar mobile charging, rain detection, and temperature regulation (26 to 27 ℃). however, its scalability and environmental durability remain key challenges [6]. gautam et al. [7] introduced an iot-based embedded system utilizing sensors and actuators connected to a raspberry pi for air pollution monitoring and control. developed in python, the system includes a web interface for remote monitoring of gas levels. however, scalability and sensor accuracy in diverse environments remain notable challenges bhagya lakshmi et al. [8] propose a smart motorcycle helmet that integrates a radio-frequency (rf)-based control system to prevent bike ignition unless the helmet is worn, along with a alcohol sensor to detect intoxication, signaling with a red light. while effective in improving safety, sensor accuracy and system reliability remain key challenges. similarly, khedkar et al. [9] discuss an accident detection system that uses gps for precise location tracking and immediate alerting of emergency services. the system enhances accident response efficiency but faces limitations in remote areas with weak connectivity. while these studies mark significant advancements, they fall short of providing a comprehensive solution that integrates real-time location tracking, environmental monitoring, and temperature regulation into a single device. key gaps include the lack of integration of gps and gsm technologies for reliable location tracking and communication, as well as inadequate temperature maintenance systems to address the thermal challenges faced by miners. this study aims to bridge these gaps by designing and evaluating a multi-functional mining helmet (mfmh) that integrates gps and gsm modules for precise real-time location tracking, automated emergency alert systems, and a robust temperature regulation mechanism. unlike prior works, the proposed helmet combines critical safety features into a unified platform, addressing the limitations of earlier systems in terms of connectivity, sensor reliability, and scalability. the incorporation of advanced monitoring systems allows for the detection of hazardous gas levels, environmental conditions, and miner health metrics. simultaneously, vibration-based alerts ensure miners receive timely warnings even in high-noise environments. furthermore, this study aims to mitigate key safety risks in mining operations, including falls, collisions, and exposure to hazardous gases, while also addressing the thermal challenges that contribute to heat-related illnesses. through rigorous testing in simulated mining environments, the study evaluates the helmet’s performance in real-time monitoring, hazard detection, and emergency response. the findings demonstrate the effectiveness of the mfmh in improving miner safety, significantly contributing to the field of intelligent safety systems for hazardous environments. 2. proposed system this section elucidates the structural framework of the helmet, encompassing the arrangement and interconnection of various components. it comprehensively outlines the operation of the helmet’s internal system, including sensor mechanisms, data processing pathways, and the operational sequence of the helmet’s features. the features of the system are categorized into three main functions: notification alerts, automatic lighting and device control, and internal temperature regulation, as illustrated in fig. 1. each function includes specific sub-features, such, as helmet impact, gas detection systems, dc light activation based on luminosity, vibration control through mobile devices, and cooling and warming systems. the subsequent sub-sections provide comprehensive descriptions of the components and functional workflows. advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 271 fig. 1 features of helmet 2.1. notification alert this subsystem is designed to monitor miner safety by detecting collisions, hazardous gases, and the miners’ location. this subsystem is comprised of a pancake vibration module, electret microphone, 8-ohm speaker, neo6m gps module, sim800l gsm module, adxl335 accelerometer, lm2596 regulator, and mq-2 gas sensor. these components interface with an arduino uno microcontroller to generate alert notifications. the mq-2 gas sensor detects gas concentrations between 25 to 500 ppm by monitoring resistance changes in its chemiresistor material. its heating system, comprising a nickel-chromium coil and aluminum oxide ceramic coated with tin dioxide, facilitates gas detection. enclosed in dual fine stainless-steel mesh layers for explosion prevention, the sensor’s platinum wires with tin dioxide coating respond to current variations. the six-pin configuration includes two heating and four signal pins (a and b), as illustrated in fig. 2 [6]. fig. 2 internal structure of mq-3 gas sensor [6] in clean air, surface oxygen adsorption creates an electron depletion layer in the tin dioxide (sno2) semiconductor, leading to an increase in resistance. the pressure of gas reduces this adsorption, lowering resistance and allowing electron flow. an lm393 comparator digitizes the analog output for microcontroller processing, triggering a vibration alert when gas levels exceed the threshold [7]. the pancake vibration module operates on piezoelectric technology and eccentric rotating mass (erm) principles, powered by a 5v supply. it features a flat printed circuit board (pcb) with a three-pole commutation circuit around a central shaft. the system includes a back layer, a base layer, and a front layer, as shown in fig. 3 [6]. brushes power the voice coils to create a magnetic field that interacts with a disc magnet, producing flux. during commutation, the magnetic field reverses, activating north-south pole pairs in the neodymium magnet, causing rotation via an off-center mass to generate vibrations. the erm motor configuration, featuring a six-pole setup, enables simple integration and offers a compact form factor, making it suitable for helmet integration with minimal bulk [8]. 272 advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 (a) functional layer (back-side) (b) base-layer (c) functional layer (frontside) fig. 3 pancake vibration module [6] the mq-2 gas sensor activates a vibration alert upon detecting poisonous gas. regarding collision scenarios, the adxl335 accelerometer detects tilt or falls and, using the sim800l module, sends sms alerts to emergency contacts. the adxl335 employs a polysilicon micromachined structure with open-loop acceleration measurement, using polysilicon springs to detect deflection via differential capacitors. phase-sensitive demodulation determines acceleration magnitude and direction, with bandwidth-regulating capacitors enhancing resolution. analog outputs for the x, y, and z axes are digitized for collision detection based on the following formula [6]. upon threshold breach, the microcontroller triggers gps and gsm modules to transmit the miner’s location to specified contacts [9]. 2 2 2 512 512 512 256 256 256 − − −      = + +            acc axis axis axisx y z total (1) the gps subsystem utilizes the neo6m module, which receives data from a constellation of 24 satellites orbiting earth. these signals enable precise location determination, along with velocity, heading, and timing information. data transmitted in the national marine electronics association (nmea) format is interpreted by the arduino ide through the software serial protocol. each nmea sentence, prefixed by “$” and an identifier such as “gpgga”, contains essential gps data including coordinates and accuracy. parsing this data using specialized functions allows the extraction of location information, such as latitude and longitude [10] the notification workflow of the mfmh is designed to implement robust real-time safety measures tailored to hazardous mining environments. a critical component of this workflow is the integration of the adxl335 accelerometer, which can detect abrupt changes in acceleration, tilt, and rotational motion, thereby enabling. the system to identify potential collisions or accidents with high precision. upon detecting such an event, the accelerometer immediately triggers an alert system that notifies the mining control room. this real-time alert mechanism ensures prompt emergency responses, potentially minimizing the impact of accidents. simultaneously, the mq-2 gas sensor embedded in the helmet operates continuously to monitor the surrounding atmosphere for the presence of dangerous gases, including methane and carbon monoxide. when the detected gas concentrations surpass predefined safety thresholds, the sensor activates a vibration module integrated into the helmet. as a advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 273 result, this haptic feedback system delivers direct and immediate warnings to miners, prompting them to evacuate hazardous areas swiftly, and hence minimizing their exposure to toxic gases. additionally, the system incorporates gps tracking functionality to render accurate real-time location data. this feature is critical during emergencies, as it enables precise communication of the miner’s position to the control room and rescue teams. the gps data facilitates efficient coordination of rescue operations, significantly reducing response times [11-12]. this comprehensive workflow integrates three key safety features—collision detection, gas exposure warnings, and gps tracking. together, these components enhance the overall safety of miners by proactively addressing risks, enabling quicker interventions, and supporting miners in avoiding or mitigating hazardous scenarios. fig. 4 provides a detailed illustration of the notification workflow implemented within the mfmh system. fig. 4 notification alert system 2.2. vibration and led-based emergency alert via the blynk app and automatic lighting system the system is designed to alert workers inside the tunnel through led lights positioned near the helmet’s eye level and vibrations triggered via the blynk application (blynk app). workers operating in low-light environments often need to pause their tasks to manually activate lights; to address this, an automatic lighting system integrated into the helmet activates based on illuminance detected by the bh1750 ambient light sensor. the system utilizes a node-mcu, blynk app, and several hardware components to enable remote alerts for workers. commands issued through the blynk mobile app are sent to the blynk cloud server and subsequently transmitted to the nodemcu for processing [13]. during setup, the node-mcu is configured to interface with vibration modules and the led light, enabling control of these components based on received commands [14]. in operation, commands from the blynk app are relayed through the blynk cloud server to the node-mcu [15]. the node-mcu processes these commands, activating or deactivating the vibration modules and led light, facilitating effective remote communication [16]. 274 advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 the bh1750 light intensity sensor is employed in this subsystem to measure ambient luminosity [17]. the sensor’s photodiode detects incident light, generating electron-hole pairs within the pn junction through the internal photoelectric effect. this process produces an electrical signal proportional to the light intensity, which is then converted into voltage by an integrated operational amplifier (op-amp). the system’s operating procedure is illustrated in fig. 5. fig. 5 automatic dc light system working the built-in analog-to-digital converter (adc) converts this voltage into 16-bit digital data representing luminance in lux. the sensor’s internal logic unit processes this data and outputs digital lux values via inter-integrated circuit (i2c) communication, with a 320 khz internal clock oscillator providing the timing reference [18]. when the measured illuminance falls below 35 lux, the relay module’s common (com) terminal connects to the normally open (no) terminal, activating a dc led. conversely, when the lux value exceeds the threshold, the com terminal connects to the normally closed (nc) terminal, turning off the dc led [19]. this automated mechanism adjusts lighting based on ambient brightness, ensuring optimal illumination for worker comfort and convenience. 2.3. system for internal temperature regulation this system comprises a thermostat, led strip, and power supply designed to regulate the inner surface temperature of the helmet. utilizing an ip67 waterproof dimtowarm led light strip, which adjusts both light intensity and color temperature, the system ensures optimal temperature conditions. the xh-w3001 temperature controller, a digital device known for its precision in temperature control, features programmable capabilities and a relay mechanism for managing power supply to external devices [20]. the controller operates by monitoring the current temperature through an integrated negative temperature coefficient (ntc)-type thermistor, activating or deactivating the connected load as needed. the xh-w3001 temperature controller features a reset mechanism that activates in the power state by pressing the “up” and “down” buttons simultaneously. upon reset, the digital display transitions from “888” to the current temperature and restores its settings. the device employs an ntc thermistor as the temperature sensor, which decreases resistance as advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 275 temperature increases. if the temperature probe is miscalibrated, the xh-w3001 displays incorrect readings, affecting temperature regulation accuracy. calibration is indispensable when the displayed temperature deviates from the actual value. this can be corrected using the controller’s “temperature offset” feature, which compensates for errors. the following are the steps to calibrate: (1) measure the system’s actual temperature using a calibrated sensor. (2) compare the actual value to the xh-w3001’s displayed reading. if the displayed value is lower, set a positive offset, if higher, set a negative offset. (3) adjust the offset by pressing both the “up” and “down” buttons simultaneously to enter offset mode. (4) use the “up” or “down” buttons to set the offset value. (5) wait for 5 seconds to allow the settings to save. this process ensures the controller aligns with the actual system temperature for precise regulation. figs. 6(a) and 6(b) illustrate the hardware connection diagrams for both the cooling and warming features, respectively. (a) connection diagram of cooling feature (b) connection diagram of warming feature fig. 6 temperature regulation hardware interfacing this feature integrates an internal heating and cooling system to provide comfort to the miner’s head within the helmet. the heating mechanism employs a double layer of cotton and foam within the helmet lining for effective heat absorption. utilizing an xh-w3001 12v dc thermostat, equipped with a built-in relay, the system achieves temperature regulation. the thermostat module, powered by a 12v dc source, controls a 12v dc led strip and a 12v dc turbofan based on preset conditions. in the warming case, it monitors the current temperature through a 10k ntc thermistor temperature sensor, compares it with predefined temperature settings, and adjusts the relay state accordingly. the led strip acts as the heat source, converting electrical energy into heat to warm the foam. configured with start and stop temperatures set at 26 ℃ and 27 ℃, respectively, the system maintains optimal foam temperature. the entire flow of operation is illustrated in fig. 7. fig. 7 workflow of warming feature during operation, if the ambient temperature initially falls below 27 ℃, the thermostat’s relay activates, switching on the led strip to generate warmth. as the foam lining heats up and reaches 27 ℃, the relay deactivates to maintain the desired temperature. if the temperature drops back to 26 ℃, the relay reactivates to reheat the foam, ensuring consistent warmth [21]. 276 advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 conversely, when the temperature is relatively high, particularly during summer, the thermostat module operates in cooling mode to alleviate heat discomfort. initially, when the ambient temperature reaches or exceeds 27 ℃, the relay activates, powering a dc cooling fan to generate a stream of cool air. this airflow cools the foam, reducing its temperature. when the temperature drops to or below 26 ℃, the relay deactivates, allowing the temperature to rise until it reaches 27 ℃. the relay then reactivates to sustain the cooling process. this cyclic process continues until the power supply to the module is terminated, ensuring continuous temperature regulation adapted to seasonal conditions. fig. 8 provides detailed operational flows, illustrating the complete functionality of the cooling features. fig. 8 workflow of cooling feature 3. results this section presents the experimental results obtained from testing the model, with a focus on the helmet’s temperature regulation, automatic lighting, and notification alert functionalities. the findings encompass interior temperature management, the effectiveness of mobile-controlled vibration and led indicators, and the overall performance of the notification system. (a) temperature regulation curve–warming cycle [6] (b) temperature regulation curve–cooling cycle fig. 9 temperature regulation results advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 277 the helmet’s warming feature successfully regulated the interior temperature within the specified range of 26 to 27 ℃. fig. 9 depicts the temperature regulation graph obtained during the testing. the temperature regulation feature effectively maintained the interior temperature within the specified range of 26 to 27 ℃. figs. 9(a) and 9(b) illustrate the temperature regulation graphs obtained during testing. in fig. 9(a), the initial temperature reading was 26.4 ℃, below the maximum threshold of 27 ℃. the led strip is activated, providing warmth and causing the temperature to rise. once the maximum threshold was reached, the led strip was deactivated. the temperature was stabilized for 185 seconds before an observed decrease. the graph shows a decline in temperature until it reaches the minimum threshold of 26 ℃, prompting the led strip to reactivate. however, the temperature briefly continued to drop to 25.7 ℃ due to sustained external cooling before rising again. this cyclical regulation process persisted [6]. in fig. 9(b), the initial temperature was 29.6 ℃, exceeding the maximum threshold of 27 ℃. the cooling fan was activated, lowering the temperature. upon reaching the minimum threshold, the cooling fan deactivated, maintaining the cooler temperature for 120 seconds. subsequently, a gradual increase in temperature was observed, with the graph showing a rise until the temperature reached the minimum threshold of 27 ℃, triggering the reactivation of the fan. nonetheless, the temperature continued to rise to 28.1 ℃ before decreasing again due to ongoing external heat, continuing the cyclical process. figs. 9(a) and 9(b) depict temperature (℃) versus time (seconds) graphs over a total observation period of 500 seconds, ensuring optimal comfort by consistently maintaining the target temperature range. fig. 10 presents the vibration signal graph obtained during testing. the x-axis represents time (ranging from 46,075 to 46,575), while the y-axis indicates vibration intensity measured as adc values (ranging from 352 to 364). the graph illustrates the helmet’s vibration intensity over a 5-second interval with the data points recorded every 10 milliseconds. a prominent spike is observed in the graph exceeding an adc value of 360. this reflects a sudden increase in vibration intensity, caused by an external impact or force acting on the helmet at that moment. fig. 10 vibration signal waveform the adxl335 accelerometer sensor detected accidents and visualized the data in the graph, as shown in fig. 11. this graph presents the resultant acceleration, computed from the combined x, y, and z axes accelerometer readings using eq. (1), plotted over time to illustrate variations in total acceleration. a sudden change in acceleration is evident over a 50-second interval, indicating a potential accident. the x-axis denotes time, spanning from 1966 to 2466 seconds, with each 100 units corresponding to 1 second, while the y-axis represents total acceleration, ranging from −6g to +6g. when the miner fell from a ladder due to a sudden slip, followed by a few seconds of recovery and standing up, the accelerometer measurements recorded during this incident are shown in fig. 11. the spike in the graph indicates the moment of impact when the helmet hit the ground. 278 advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 fig. 11 accelerometer data graph fig. 12 illustrates the graph of gas concentration in parts per million (ppm) detected by the mq-2 gas sensor worn by a miner over some time. initially, when the miner first donned the helmet, the gas concentration recorded was 23.45 ppm. subsequently, when the miner began digging and stopped upon noticing a strange odor, a noticeable spike in gas concentration was observed, reaching 41.23 ppm. this sudden increase is evident in the graph. the data were collected over a total duration of 50 seconds, with measurements taken every 100 milliseconds. the y-axis of the graph represents the gas concentration in ppm, while the x-axis represents time. fig. 12 mq-2 gas sensor data stream fig. 13 bh1750 light sensor data stream the data, as illustrated in fig. 13, represents the luminosity levels (lux) versus time (seconds) detected by the bh1750 light sensor as a mine worker moves from the entrance to the interior of the tunnel. the graph depicts the variations in luminance encountered during the transition. when the detected luminosity drops below 35 lux, the dc led light is advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 279 automatically activated, ensuring enhanced visibility for the miner without requiring manual intervention. initially, the sensor recorded 8,992 lux in open sky conditions. as the miner moved deeper into the tunnel, the sensor detected progressively lower light levels, ultimately measuring as low as 10 to 8 lux, as shown in fig. 13. the key findings pertinent to the notification system’s performance under stringent operational thresholds are summarized in table 1. the hazardous gases detection system is set to trigger vibration alerts, calls, and messages when gas concentrations exceed 40 ppm, as recommended by mining health experts. similarly, the accident detection system activates notifications when acceleration surpasses 3 g, as recommended by experts, using data from each axis to detect major injuries. additionally, the light sensor activates a dc led based on luminosity levels. comprehensive data supporting these functionalities are systematically presented in table 1. these results demonstrate the effective implementation and performance of safety features aimed at enhancing safety and communication reliability for mining workers. table 1 status of notification, vibration alert, and luminosity detection sensor observed value output (detected) triggered response accident detection (in g) (threshold = 3) message, call adxl335 accelerometer sensor x,y,z: 900,850,950 total acc.: (2.64) no off x,y,z: 1000,900,1000 total acc.: (3.09) yes on x,y,z: 1100,1000,1100 total acc.: (3.76) yes on x,y,z: 950,950,900 total acc.: (2.85) no off x,y,z: 540,550,520 total acc.: (0.187) no off gas detection (in ppm) (threshold = 40) message, call, vibration mq-2 gas sensor 41.23 yes on 21.45 no off 52.20 yes on 78.80 yes on 188 yes on luminosity detection (in lux) (threshold = 35) relay–led bh1750 light intensity sensor 6 yes on 11 yes on 43 no off 10,943 no off 30,768 no off the notification feature demonstrated robust performance in warning users of hazardous conditions through vibration alerts, messages, and calls. the vibration signals, as shown in fig. 10, revealed a significant spike in intensity upon external impact, effectively indicating the precise moment of helmet collision. the accelerometer data, as depicted in fig. 11, captured sudden acceleration changes exceeding 3 g, visualized as prominent spikes across the x, y, and z axes within a 50-second interval, thereby identifying potential high-impact events. the gas concentration, as shown in fig. 12, was monitored using the mq-2 sensor, which detected hazardous gas levels exceeding 40 ppm, triggering immediate vibration alerts and notifications. additionally, luminosity levels, as displayed in fig. 13, were assessed by the light sensor, which automatically activated leds when ambient light dropped below 35 lux, ensuring enhanced visibility in low-light environments. the next-generation safety helmet redefines protective gear for miners by integrating advanced technologies that enhance comfort, safety, and real-time hazard response. key features of this innovative design include enhanced temperature regulation and integrated safety systems. 280 advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 (1) enhanced temperature regulation • advancement: unlike earlier designs that lacked precise thermal control, this helmet maintains interior temperatures within a stringent range of 26 to 27 ℃, ensuring miner comfort and operational consistency. • validation: the system’s dynamic activation and deactivation of warming and cooling components effectively stabilize temperatures while optimizing energy efficiency, as demonstrated by the temperature regulation graphs in figs. 9(a) and 9(b). (2) integrated safety features • advancement: traditional helmets are typically equipped with isolated functionalities, such as gas detection or impact resistance. in contrast, this helmet consolidates multiple safety systems, including hazardous gas alerts, accident detection, automatic lighting, and temperature regulation into a unified device. • validation: the system’s ability to detect and respond to hazardous gas concentrations exceeding 40 ppm, acceleration levels above 3 g, and luminosity below 35 lux outperforms earlier standalone devices, as evidenced by table 1 and figs. 11-13. (3) practical challenges durability • challenge: ensuring resilience against harsh mining conditions, such as high humidity, dust, and mechanical impacts. • mitigation: utilizing durable materials and protective enclosures for electronic components enhances reliability, albeit potentially increasing device weight. cost • challenge: the integration of advanced sensors and communication modules may elevate production costs, compromising affordability for smaller mining operations. • mitigation: economies of scale through mass production and sourcing cost-effective components are essential to achieving cost efficiency. scalability • challenge: adapting the helmet design to diverse mining environments and regulatory requirements may require additional customization. • mitigation: employing a modular design enables seamless upgrades and component replacements, facilitating adaptability across various applications without extensive redesign. overall, this next-generation helmet sets a new benchmark in mining safety by combining advanced features with practical design, addressing key challenges while ensuring enhanced protection and operational efficiency. 4. conclusions this study developed and rigorously evaluated an mfmh designed to address critical safety challenges in mining operations. the helmet integrates advanced technologies, such as gsm and gps modules for real-time location tracking, accident detection systems, hazardous gas monitoring, internal temperature regulation, and automatic lighting. extensive testing in simulated mining environments confirmed the helmet’s effectiveness in delivering real-time emergency alerts to designated authorities, facilitating prompt responses, and ensuring accurate personnel tracking. the findings underscore the mfmh’s significant potential to enhance miner safety by providing essential features that address pervasive risks in mining operations. the hazardous gas monitoring system demonstrated reliable detection of dangerous gas concentrations, while the internal temperature regulation and automatic lighting ensured optimal comfort and visibility under challenging conditions. advances in technology innovation, vol. 10, no. 3, 2025, pp. 269-282 281 to advance practical adoption, this study highlights the need for collaboration with mining organizations and regulatory bodies to develop standardized guidelines mandating the use of such helmets in high-risk operations. partnering with industry stakeholders to conduct large-scale pilot programs in diverse mining settings can validate the helmet’s performance in realworld scenarios, optimize its design for field conditions, and quantify its impact on safety outcomes. additionally, costreduction strategies, such as scalable production and modular design, can make the mfmh more accessible to mining companies of varying capacities. by addressing these factors, this innovative solution can significantly contribute to reducing fatalities and injuries in hazardous mining environments. conflicts of interest the authors declare no conflict of interest. references [1] s. r. deokar and j. s. wakode, “coal mine safety monitoring and alerting system,” international research journal of engineering and technology, vol. 04, no. 03, pp. 2146-2149, 2017. 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[21] s. f. perdana, “ac 220v digital thermostat based drying oven xh-w3001 to improve temperature accuracy in the drying process of black betel leaves (piper betle var nigra) at pt. fbion karanganyar,” 2nd international conference on early childhood education in multiperspective, vol. 2, pp. 395-406, 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 7-v9n3(2024)-aiti#13599(239-255).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 english language proofreader: chih-wen teng a novel approach to construct finite automata using grid and product automata rupam nag, dibyendu barman*, abul hasnat department of computer science and engineering, government college of engineering and textile technology, berhampore, wb, india received 19 april 2024; received in revised form 14 june 2024; accepted 17 june 2024 doi: https://doi.org/10.46604/aiti.2024.13599 abstract this research aims to utilize an organized grid-based strategy to make the development of complex finite automata easier. product automata are used to merge many automata into a single automaton to integrate various computing processes. combining these methodologies provides novel methods of improving the scalability and efficiency of automata building, broadening the field of research for automata theory and its applications. the scalability of this developed automated system will benefit sectors such as automotive production and logistics. the results indicate considerable improvements in construction time, memory usage, scalability, and resilience compared to older approaches. the performance of the developed method, as measured by construction time, memory utilization, scalability, robustness, application range, and complexity, is 25% to 50% higher than that of traditional methodologies in the literature. keywords: dfa, nfa, grid, product automata 1. introduction the theory of computation is divided into three areas: computational complexity theory, computability theory, and automata theory. these branches are the foundation for research into algorithms, mathematical aspects of computational models, and computability limitations. automaton theory is concerned with abstract machines and their various forms, such as finite state automata, pushdown automata, and turing machines. each is defined by specific components such as states, input alphabets, transition functions, start states, and accepting states, which are necessary for understanding computation. finite state automata are classified as deterministic finite automata (dfa) or non-deterministic finite automata (nfa), with representations such as transition diagrams or transition tables explaining their behavior. automata theory extends beyond representation, with applications in formal language theory, compiler building, and software verification, all of which help solve complicated computational issues. specifically, grid automata and product automata are effective approaches for generating finite automata: grid automata organize states in an organized grid-like pattern, simplifying construction and maintaining accuracy, whereas product automata combine several automata into composite structures using cartesian products, allowing for efficient description of complicated systems. this investigation emphasizes the utility of grid and product automata in the construction of finite automata, demonstrating their efficacy in addressing computing difficulties. automata are the subject of studies in the literature. some of them are addressed below. in 2024, zhao et al. [1] designed a model that simulates the microstructural evolution of 7075 aluminum alloy under hot deformation based on cellular automata (ca). the material properties of the 7075 aluminum alloy were determined via isothermal compression testing, which resulted in the creation of models for dislocation density, recrystallized grain nucleation, * corresponding author. e-mail address: dibyendu.barman@gmail.com 240 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 and grain development. these results show that large strain, high temperature, and low strain rate promote dynamic recrystallization and grain refining. the ca model’s results indicate good accuracy and predictive capabilities, with an experimental error of less than 10%. the drawback of this approach is that, depending on the particular implementation, the model’s effectiveness may vary. furthermore, even if ca models offer a more accurate depiction of geographical distribution, they could need more time and computing power. again in 2024, amir et al. [2] examine the knuth-morris-pratt (kmp) automata and present a practical outcome that defies intuition. also, modanese and worsch [3] in 2024, showed a fungal automaton with an update sequence horizontalvertical (hv) can be configured to include any boolean circuit in its initial state. for texts with uniformly random symbols, the naive technique is thought to perform as well as the kmp algorithm. in this study, the kmp algorithm’s practical efficiency is compared against a naive technique for generating a random text. it investigates the time under a variety of situations, including alphabet size, pattern length, and pattern distribution in the text. the main constraint of this approach is that data becomes less useful as input sizes grow. as a result, errors keep happening. in 2024, pighizzini et al. [4], show using 1-limited automata, a constrained variant of one-tape turing machines, the descriptional complexity of fundamental operations on regular languages is examined. the sizes of the generated devices are polynomial in the sizes of the simulated machines when deterministic 1-limited automata are used to simulate operations on dfa. applying the operations to deterministic 1-limited automata presents a different scenario: the simulations stay polynomial for boolean operations, but they become exponential in size for product, star, and reversal operations. the major drawback of this approach is that if the machines are two-way dfa, the costs of the product and star do not decrease. maletti and nasz [5] in 2024, showed that the central idea of the unweighted setting, the tree automaton with inequality and equality constraints, can be directly generalized to the weighted setting and can represent the image of any regular weighted tree language under any nonerasing and nondeleting tree homomorphism. several closure properties and decision problems are also examined for the weighted tree languages produced by constraint-based weighted tree automata. the main limitation of this approach is that weighted tree automata cannot ensure that two subtrees in an approved tree, regardless of size, are always equal. in 2024, laura et al. [6] proposed a model of ca that has been created to investigate the behavior of ceramic particles during sintering. reducing the energy at the interface between the mass cells and the void cells is the single physical rule in this model that governs how the system evolves. investigations were conducted into the significance of various computational factors, including particle size and computational temperature. experiments with partial sintering of spherical silica particles were carried out, and it was confirmed that this model accurately replicates neck development. furthermore, other experimental evidence of densification stages, such as the creation of the intermediate vermicular microstructure or the porosity-temperature dependence, were qualitatively replicated. the primary constraints of this approach are motion artifacts and the influence of grid resolution on motion. in 2023, kishore et al. [7] proposed fundamental ideas and concepts of quantum-dot cellular automata (qca), along with some potential benefits over traditional complementary metal-oxide-semiconductor (cmos) technology. the performance of qca-based adders is then compared to conventional cmos designs, and it is demonstrated that qca-based adders are faster and require less power than cmos designs. due to their small size and careful construction, the primary drawback of these qcas is that they are more prone to errors. again in 2023, shahid et al. [8] presented the proactive approach in a peer group. here a variety of group activities are used to make the course engaging and simple for the students to learn from with the support of their classmates. they were able to learn nfa as a result, and they also used simulation software to enhance the learning process. the main constraint of this approach is the restricted computational problem-solving capabilities of these machines, which are primarily limited to issues that can be described using regular languages. advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 241 in 2023, jaiswal and sasamal [9] proposed a method where in comparison to the horizontal, vertical, nanomagnetic qca, and the current qca-based 2:1 mux, the suggested compact design methodology results in approximately 71% to97% reduction in the total number of nanodots and approximately 22% to 99% reduction in area occupancy. here it also creates an 8:1 mux to demonstrate the scalability of the suggested structure. using the mumax3 micromagnetic simulator, the design layouts and simulation results are confirmed. the main negative aspect of this approach is that, because of its small size and precise construction, it is more prone to faults. havlena et al. [10] in 2023, proposed a method to lower the false-positive rate of the automata-based detection system and greatly enhance its performance. furthermore, and importantly for real-world implementation, a technique is provided here that generates more details regarding discovered abnormalities, which is useful for real-world deployment. the method is illustrated using iec 104 or multimedia messaging service (mms) communication between multiple industrial control systems (ics) systems. however, this suggested method’s success rate falls short of expectations. again in 2022, battyányi et al. [11] defined rough-set-like approximation spaces for formal languages over the defined alphabetic symbols using similarity relations. a methodology to be driven by circumstances when unsure of the precise characters that comprise a text that must be processed by a formal system is put forth in this work. it encompasses regular and context-free cases and specifies lower and higher approximations of languages. descriptions of the approximate languages produced by context-free grammars or recognized by dfa are presented. this method’s primary flaw is the absence of characterizations for the approximate languages that nfa accepts. in 2022, vogrin et al. [12] proposed a method that effectively traverses multiple transitions simultaneously by utilizing the symbolic representation. the process is assessed using industry-standard communication protocol models and biological system models. it is at least many times faster than the previous one, according to the results. when witness automata were initially presented, test sequence composition was made possible. its primary flaw is that it occasionally yields results that are not entirely correct. lastly, recent research has explored novel avenues within automata theory, particularly concerning graph operations and advanced compositions, including n-ary cartesian composition and cartesian product of automata [13-15]. this recent wave of research underscores the dynamic nature of the field, driving it forward into uncharted territories of exploration and innovation, contributing to the foundational understanding of automata theory and its diverse applications. the primary flaw in this approach is that the success rate is not high enough. the objective of this study is to use an organized grid-based method to make the construction of sophisticated finite automata simpler. conversely, product automata is designed to combine several automata into a single automaton to integrate different computational processes. combining these approaches offers novel methods to improve automata construction’s scalability and efficiency, expanding automata theory’s field of study and useful applications. the scalability of this built automated system will aid industries like automobile manufacturing and logistics in the future. let us look at some more future automation options. this developed method will have a big impact on the robotics industry in the coming years. this technique can be used to create and build complex robots. this strategy will play an important role in the field of self-driving cars, which is a rising area of technology. 2. notation and basic definitions (1) deterministic finite automata (dfa): dfa consists of a 5-tuple m = (q, σ, δ, q0, f), where q is a finite set of states, σ is the finite or non-empty set of input symbols called the alphabet, δ is the transition function defined as q × σ → q, q0 is the initial/start state (q0 ∈ q), f represents the set of accepting or final states within the set of all states (f ⊆ q). the notations for the states and transitions are shown in fig. 1. 242 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 (2) non-deterministic finite automata (nfa): similar to dfa, except that the transition function δ is defined as q × σ → 2q. it is the finite automata that allows multiple transitions for a single input alphabet and, it doesn’t contain a dead or trap state. (3) languages accepted by dfa: the language accepted by dfa m = (q, σ, δ, q0, f) is the set of strings σ accepted by m, i.e., l(m) = {w ∈ σ* / δ (q0, w) is in f}. (4) input strings and symbols: sequences of symbols from the input alphabet are used to drive the transitions of the automaton. strings are typically represented as sequences of symbols from the input alphabet, e.g., w = a1a2...an, where each ai ∈ σ. (5) number of occurrences of a symbol ‘a’ in a string ‘w’: denoted as n(a), represents the count of occurrences of the symbol ‘a’ in the string ‘w’. (6) length of a string ‘w’: denoted as |w|, it represents the number of symbols in the string ‘w’. (7) empty string: denoted as ε, it represents the string with zero symbols. (8) language: denoted as l, it represents a set of strings over some alphabet. (9) cartesian product: given two sets a and b, the cartesian product a × b is the set of all ordered pairs (a, b) where a is an element of a and b is an element of b. in mathematical notation: a × b = {(a, b) ∣ a ∈ a and b ∈ b}. the cartesian product a × b contains all possible combinations of elements from sets a and b, preserving the order of elements. fig. 1 notations 3. methodology grid and product automata methods are essential to develop and analyze the various aspects of automata, leading to better computational models due to their ability to facilitate the faster design of complex automaton logistics. specifically, the grid automata offers a systematic way to manage state transitions whereas product automata are used to combine multiple concepts such as topology and partitioning of computing processes. these methods will be examined in detail in the following subsections. 3.1. grid automata the grid automata methodology is the organization of states into a structured grid pattern based on specific conditions. states are derived systematically, with each cell in the grid representing a distinct state of the finite automaton. the intuitive visualization and systematic derivation of transitions between states are facilitated by the spatial representation of the grid. this approach allows for the creation of both dfa and nfa, with the flexibility to incorporate additional states, such as dead or trap states, as needed for dfa. the grid automata method provides a flexible framework for addressing a wide range of computational challenges, ensuring correctness and efficiency in automata design. this visualization is shown in the following fig. 2. advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 243 fig. 2 visualization of grid automata method 3.1.1. algorithm 1: construction of finite automata using grid automata method this algorithm presents a revolutionary approach to generating finite automata using the grid automata method, an innovative framework that improves automata construction efficiency and scalability. the distinctive contribution is the combination of grid-based computations with classical automata theory, resulting in a more robust and adaptable solution for complicated state transition systems. this method dramatically improves computing efficiency by utilizing spatial data structures found in grid systems, lowering temporal complexity compared to older methods. furthermore, the technique enables better viewing and manipulation of state transitions, which is especially useful for applications that require real-time system updates. input: finite automaton specification (q, σ, δ, q0, f) output: deterministic finite automaton (dfa) or nondeterministic finite automaton (nfa) procedure: (1) initialize input alphabet: initialize the input alphabet σ (2) determine states: determine the total number of states required for the finite automaton. this is typically based on the size of the input alphabet σ and any additional constraints or conditions: let m be the number of states for a condition and n be the number of states for another condition. total number of states = m × n. (3) organize the states into a grid pattern: construct an mxn matrix grid where ‘m’ denotes the number of rows and ‘n’ signifies the number of columns. alternatively, create a nxm matrix grid if needed (transpose matrix). (4) assign state identifiers: label each cell with a unique state identifier. (5) define transition function δ: determine the transitions between states based on the input alphabet σ and the language pattern or condition. define transitions for each cell in the grid, considering both row-wise and column-wise transitions. if constructing a dfa, consider introducing a dead or trap state if necessary to handle undefined or unexpected inputs. this dead state ensures that the automaton transitions to a non-accepting state for inputs not explicitly defined in the transition function. (6) determine initial state and accepting states: set the initial state as the starting point. identify the accepting states based on the language pattern or condition. (7) construct finite automaton: combine the organized grid layout with the defined transition function, initial state, and accepting states. (8) validate automata: test the automaton with representative input strings to verify its behavior and adherence to the language pattern or condition. (9) refine grid layout or transition function (if necessary): address any discrepancies or errors identified during validation. (10) finalization: once validated, the constructed finite automaton is ready for use in recognizing strings that conform to the specified language pattern or condition. end of algorithm 1 244 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 example 1: consider language l over the alphabet {a, b}, defined as: l = {w ∈ {a, b}* | na(w) mod 3 = 0 and nb(w) mod 2 = 0} this means that the number of occurrences of ‘a’ in a string is divisible by 3, and the number of occurrences of ‘b’ is divisible by 2. (1) initialize input alphabet: σ = {a, b} (2) determine states: m: the number of states for ‘a’ is 3, n: the number of states for ‘b’ is 2, so the total number of states = m × n = 3 × 2 = 6. (3) organize the states into a grid pattern: create a m × n = 2 × 3 grid pattern to represent the states. each cell in the grid corresponds to a unique state of the finite automaton. (4) assign state identifiers: label each cell in the grid with a unique state identifier. steps 3 and 4 are shown in the following fig. 3. fig. 3 grid pattern with assigned identifiers for states (5) define transition function δ: to determine the transition function for the given example, it will divide it into two parts: divisibility by 3 (strings with ‘a’), denotes the state as q0, q1, q2 in the first row and q3, q4, q5 in the second row. the transitions are as follows: δ(q0, a) = q1, δ(q1, a) = q2, δ(q2, a) = q0, δ(q3, a) = q4, δ(q4, a) = q5, δ(q5, a) = q3 these transitions are shown in the following fig. 4. fig. 4 transitions for divisibility by 3 (strings with ‘a’) divisibility by 2 (strings with ‘b’), denotes the states as q0, q3 in the first column, q1, q4 in the second column, and q2, q5 in the third column. the transitions are as follows: δ(q0, b) = q3, δ(q1, b) = q4, δ(q2, b) = q5, δ(q3, b) = q0, δ(q4, b) = q1, δ(q5, b) = q2 these transitions are shown in the following fig. 5. fig. 5 transitions for divisibility by 2 (strings with ‘b’) advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 245 (6) determine initial state and accepting states: set the initial state as the starting point of the automata. the final states of the finite automata accept strings where the number of occurrences of ‘a’ is divisible by 3 and the number of occurrences of ‘b’ is divisible by 2 which means the final state that accepts strings with ‘a’ such that the number of occurrences of ‘a’ modulo 3 equals 0, and ‘b’ modulo 2 equals 0, would be identified as an accepting state. here the final state is q0 for the given example is shown in the following fig. 6. fig. 6 final states for accepting strings with divisibility conditions (7) construct finite automaton: combine the organized grid layout with the defined transition function, initial state, and accepting states to construct the finite automaton. for this language, both dfa and nfa are equivalent, as there are no dead states and each symbol allows for only a single transition, ensuring determinism in both models. the final automata is shown in fig. 7. after transposing, the resulting n × m matrix or 3 × 2 matrix represents the same finite automaton as the original m × n matrix, ensuring equivalence in their functionality and language recognition capabilities. this automaton is shown in the following fig. 8. fig. 7 constructed finite automaton with grid automata method fig. 8 equivalence of transposed and original grid automaton (8) validate automata: the constructed finite automaton undergoes thorough testing using sample input strings to confirm its functionality and adherence to language criteria. valid inputs, such as {“ε”, “a3”, “b2”, “a6”, “aaabb”, “ababa”, “aabbbbaaaa”}, demonstrate its ability to recognize compliant strings. conversely, invalid inputs, like {“a”, “b”, “ab”, “aaab”, “aabbb”, “aaabbba”}, validate its rejection of non-conforming strings. (9) refine grid layout or transition function (if necessary): post-validation, the automaton undergoes meticulous evaluation, refining its layout or transition function for improved accuracy and efficiency, ensuring alignment with language pattern. (10) finalization: with validation and refinement complete, the finite automaton is primed for real-world deployment, offering dependable language processing capabilities. end of example 1 246 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 after studying the grid automata algorithm and providing an example, a concise algorithm is derived for constructing finite automata using the grid automata method. this shortened algorithm aims to provide a quick overview of the key steps involved. 3.1.2. algorithm 2: construction of finite automata using grid automata method (summarized approach) the aforementioned approach encapsulates the key breakthroughs of the grid automata method for building finite automata. the fundamental contribution is a streamlined process that considerably decreases computing overhead while ensuring excellent accuracy and consistency in automata production. this method stands out because it provides a simple yet powerful tool for automata construction, demonstrating the progress in grid-based automata theory. the summary approach focuses on how the strategy may be effectively applied to a variety of real-world settings, displaying versatility and adaptability. furthermore, it gives a direct comparison to existing methodologies, emphasizing the gains in efficiency and reliability that the methodology brings to the area. input: finite automaton specification (q, σ, δ, q0, f) output: deterministic finite automaton (dfa) or nondeterministic finite automaton (nfa) procedure: (1) initialize input alphabets. (2) define the matrix structure. (3) construct a finite automaton for one condition, then balance it with others. (4) set the first state as initial and determine the final state according to the conditions. add a trap state if needed to handle undefined or unexpected inputs. (5) validate finite automaton with representative strings. end of algorithm 2 different automata types, such as at least, atmost, and exactly conditions, can be easily designed using the grid automata method. from table 1, it is determined that a total number of states is required, ensuring precise automata construction for accurate language recognition. table 1 rules for determining the total number of states in grid automata condition automata type rules for dfa (total states) rules for nfa (total states) atleast single alphabet (n + 1) (n + 1) atmost single alphabet (n + 2) (n + 1) exactly single alphabet (n + 2) (n + 1) at least all alphabets (n + 1) × (m + 1) (n + 1) × (m + 1) at most all alphabets (n + 1) × (m + 1) + 1 (n + 1) × (m + 1) exactly all alphabets (n + 1) × (m + 1) + 1 (n + 1) × (m + 1) example 2: consider the language l over the alphabet {a, b}, defined as: l = {w∈{a, b} ∗ ∣ na(w) ≥ 3 and nb(w) ≥ 2} the language l consists of all strings over the alphabet {a, b} where the number of occurrences of ‘a’ is at least 3 and the number of occurrences of ‘b’ is at least 2. (1) initialize input alphabets: σ = {a, b} (2) define matrix structure: total number of states using the formula: (n + 1) × (m + 1) = (3 + 1) × (2 + 1) = 4 × 3 = 12. hence, a 4 × 3 matrix can be created to represent the states. (3) construct finite automaton for one condition, then balance with others: construct finite automaton by adding transitions for ‘a’ to ensure at least 3 ‘a’'. refer to the following fig. 9 for the transitions involving ‘a’. balance the finite automaton with transitions for ‘b’ to ensure at least 2 ‘b’. ensure that the final automaton, balanced with ‘b’, accepts strings meeting both conditions. refer to the following fig. 10 for the final balanced automaton. advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 247 (4) set the first state as initial and determine the final state according to the conditions. add a trap state to handle undefined or unexpected inputs: initial state = q0. no trap state is needed as dfa and nfa are equivalent for this language. the final finite automaton represents the synchronized behavior of both conditions, ensuring compliance with the language pattern. here the final state is q11. (5) validate finite automaton with representative strings: test the finite automaton with both accepted and rejected representative strings to verify its behavior: accepted strings: {“aaaabb”, “abaaaabbb”, “aabbaaaab”, “abbaa”} rejected strings: {“ab”, “aabbb”} these steps demonstrate the construction and validation of a finite automaton using the grid automata method for the language where the number of ‘a’s is atleast 3 and the number of ‘b’s is atleast 2. end of example 2 fig. 9 initial automaton for at least 3 ‘a’ fig. 10 final balanced automaton for at least 3 ‘a’ and at least 2 ‘b’ example 3: design dfa for the language l over the alphabet {a, b}, defined as: l = {w ∈ {a, b} ∗ ∣na(w) ≤ 3 and nb(w) ≤ 2} the language l consists of all strings over the alphabet {a, b} where strings consist of ‘a’s and ‘b’s, with the condition that the number of ‘a’s does not exceed 3 and the number of ‘b’s does not exceed 2. (1) initialize input alphabets: σ = {a, b} (2) define matrix structure: calculate total nos of states using the formula: (n + 1) × (m + 1) = (3 + 1) × (2 + 1) = 4 × 3 = 12. hence, a 4 × 3 matrix can be created to represent the states. (3) construct finite automaton for one condition, then balance with others: construct finite automaton by adding transitions for ‘a’ to ensure at most 3 ‘a’. refer to the following fig. 11 for the transitions involving ‘a’. balance the finite automaton with transitions for ‘b’ to ensure atmost 2 ‘b’. ensure that the final automaton, balanced with ‘b’, accepts strings meeting both conditions. refer to the following fig. 12 for the final balanced automaton. (4) set the first state as initial and determine the final state according to the conditions. add a trap state if needed to handle undefined or unexpected inputs. initial state = q0. trap state = q12. no trap state is needed as both dfa and nfa are equivalent for this language. the final finite automaton represents the synchronized behavior of both conditions, ensuring compliance with the language pattern. here the final states are {q0, q1, q2, q3, q4, q5, q6, q7, q8, q9, q10, q11}. (5) validate finite automaton with representative strings: test the finite automaton with both accepted and rejected representative strings to verify its behavior: accepted strings: {“ε”, “a”, “b”, “aa”, “ab”, “ba”, “aaa”, “aab”, “aba”, “baa”, “abb”, “bab”} 248 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 rejected strings: {“aaaa”, “aaaaa”, “aaaaaa”, “aaaab”, “aabaa”, “bbb”, “bbbb”, “babab”, “ababab”} these steps demonstrate the construction and validation of a finite automaton using the grid automata method for the language where the number of ‘a’s is at most 3 and the number of ‘b’s is at most 2. end of example 3 fig. 11 initial automaton for atmost 3 ‘a’ fig. 12 final balanced automaton for atmost 3 ‘a’ and atmost 2 ’b’ example 4: design dfa for the language l over the alphabet {a, b}, defined as: l = {w ∈ {a, b} ∗ ∣ na(w) = 3 and nb(w) = 2} the language l consists of all strings over the alphabet {a, b} where strings contain exactly 3 'a's and 2 'b's. (1) initialize input alphabets: σ = {a, b} (2) define the matrix structure: total number of states using the formula: (n + 1) × (m + 1) = (3 + 1) × (2 + 1) = 4 × 3 = 12. (3) construct finite automaton for one condition, then balance with others: construct finite automaton by adding transitions for ‘a’ to ensure exactly 3 ‘a’. refer to the following fig. 13 for the transitions involving ‘a’. balance the finite automaton with transitions for ‘b’ to ensure exactly 2 ‘b’. ensure that the final automaton, balanced with ‘b’, accepts strings meeting both conditions. refer to the following fig. 14 for the final balanced automaton. (4) set the first state as initial and determine the final state according to the conditions. add a trap state if needed to handle undefined or unexpected inputs. initial state = q0. trap state = q12. no trap state is needed as dfa and nfa are equivalent for this language. advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 249 the final finite automaton represents the synchronized behavior of both conditions, ensuring compliance with the language pattern. here the final state is q11. (5) validate finite automaton with representative strings: test the finite automaton with both accepted and rejected representative strings to verify its behavior: accepted strings: {“aaabb”, “abaab”, “aabab”, “ababa”, “baaab”, “baaba”, “babaa”, “aabba”, “abbaa”, “bbaaa”} rejected strings: {“aaaab”, “aaaaa”, “aaaaaa”, “aabbb”, “abbbb”, “bbbb”, “bbbbb”, “babab”, “bbaab”} these steps demonstrate the construction and validation of a finite automaton using the grid automata method for the language where the number of ‘a’s is exactly 3 and the number of ‘b’s is exactly 2. end of example 4 fig. 13 initial automaton for exactly 3 ‘a’. fig. 14 final balanced automaton for exactly 3 ‘a’ and 2 ‘'b’ 3.2. product automata product automata is a method that analyzes complex systems by integrating multiple automata into a single automaton. this method utilizes the cartesian product combine multiple automata into one, synchronizing their transitions between states [12-15]. by using this method, it becomes easier to understand complex systems by breaking them down into parts and synchronizing their behavior. product automata enables a comprehensive study of system-wide properties and interactions and are particularly useful for analyzing systems with multiple components or subsystems. this visualization is shown in the following fig. 15. 250 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 fig. 15 product automata state construction 3.2.1. algorithm 3: construction of product automata in this section, a groundbreaking algorithm is presented for building product automata that takes advantage of the developed techniques to efficiently integrate several automata into a coherent product automaton. the main contribution is the development of a systematic strategy to improve the accuracy and performance of product automata building, which is distinguished by this work’s new combination of increased state synchronization and transition management strategies. the suggested method not only streamlines the merging process but also assures that the resulting automaton is optimized for minimal state redundancy and maximum transition efficiency. this development is especially significant in applications like parallel processing and complicated system simulations, where maintaining peak performance is critical. input: two finite automata fa1 and fa2, denoted as (q1, σ1, δ1, q01, f1) and (q2, σ2, δ2, q02, f2) respectively. output: product automata represents the synchronized behavior of fa1 and fa2. procedure: (1) define finite automata: let fa1 and fa2 be the given finite automata. (2) determine state space: combine the state spaces to obtain q = q1 × q2. (3) define input alphabet: set the input alphabet as σ = σ1 ∪ σ2. (4) combine transition functions: define the transition function as δ((q1, q2), a) = (δ1(q1, a), δ2(q2, a)), where a ∈ σ. (5) set initial state: determine the initial state as q0 = (q01, q02). (6) determine accepting states: use union condition: f = {(q1, q2) ∣ q1 ∈ f1 or q2 ∈ f2} if either of fa1 or fa2 recognizes the strings. (7) construct product automata: combine state space, input alphabet, transition function, initial state, and accepting states to create the product automaton representing the synchronized behavior of fa1 and fa2. end of algorithm 3 let’s now explore multiple examples to demonstrate the versatility of the product automata construction algorithm. example 5: consider the two finite automata fa1 and fa2, over the alphabet {a, b}, recognizing the following languages: fa1: l1 = {w ∈{a, b} ∗ ∣ na(w) is even} fa2: l2 = {w ∈{a, b} ∗ ∣ nb(w) is even} (1) define finite automata: let fa1 represent the finite automaton for the language where the number of occurrences of ‘a’ is even, and fa2 represents the finite automaton for the language where the number of occurrences of ‘b’ is even. fig. 16 and fig. 17 illustrate fa1 and fa2 respectively. fig. 16 finite automata fa1 with even occurrences of ‘a’ fig. 17 finite automata fa2 with even occurrences of ‘b’ advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 251 (2) determine state space: combine the state spaces to obtain q = {a, b} × {c, d} = {ac, ad, bc, bd}. (3) define input alphabet: set the input alphabet as σ = {a, b}. (4) determine state space: define the transition function as follows: δ((q1, q2), a) = (δ1(q1, a), δ2(q2, a)) δ((q1, q2), b) = (δ1(q1, b), δ2(q2, b)) refer to fig. 18 for a visual representation of the transition function. fig. 18 transition function for product automata with even occurrences of ‘a’ and ‘b’ (5) set initial state: determine the initial state as q0 = (q01, q02) = (a, c). (6) determine accepting states: using intersection conditions: f = {(q1, q2) ∣ q1 ∈ f1 and q2 ∈ f2}, where f1 = {a} and f2 = {c}. (7) construct product automaton: combine state space, input alphabet, transition function, initial state, and accepting states to create the product automaton representing the synchronized behavior of fa1 and fa2, as depicted in fig. 19. the product automata faproduct will accept strings where both the number of ‘a’s and ‘b’s are even: l = l1 ∩ l2 = {w ∈ {a, b} ∗ ∣ na(w) is even and nb(w) is even}. fig. 19 product automata for even occurrences of ‘a’ and ‘b’ end of example 5 example 6: consider the two finite automata fa1 and fa2, over the alphabet {a, b}, recognizing the following languages: fa1: l1 = {w ∈ {a, b} ∗ ∣ na(w) mod 4 = 0} fa2: l2 = {w ∈ {a, b} ∗ ∣ nb(w) mod 3 = 0} (1) define finite automata: let fa1 represent the finite automaton for the language where the number of occurrences of 252 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 ‘a’ is divisible by 4, and fa2 represent the finite automaton for the language where the number of occurrences of ‘b’ is divisible by 3. refer to fig. 20 and fig. 21 for visual representations of fa1 and fa2, respectively. fig. 20 finite automata fa1 with ‘a’ occurrences divisible by 4 fig. 21 finite automata fa2 with ‘b’ occurrences divisible by 3 (2) determine state space: combine the state spaces to obtain q = {a, b, c, d} × {e, f, g} = {ae, af, ag, be, bf, bg, ce, cf, cg, de, df, dg}. (3) define input alphabet: set the input alphabet as σ = {a, b}. (4) determine state space: define the transition function as follows: δ((q1, q2), a) = (δ1(q1, a), δ2(q2, a)), δ((q1, q2), b) = (δ1(q1, b), δ2(q2, b)) refer to fig. 22 for a visual representation of the transition function. fig. 22 transition function for product automata with ‘a’' mod 4 = 0 and ‘b’ mod 3 = 0 (5) set initial state: determine the initial state as q0 = (q01, q02) = (a, e). (6) determine accepting states: using intersection conditions: f = {(q1, q2) ∣ q1 ∈ f1 and q2 ∈ f2}, where f1 = {a} and f2 = {e}. (7) construct product automaton: combine state space, input alphabet, transition function, initial state, and accepting states to create the product automaton representing the synchronized behavior of fa1 and fa2, as depicted in fig. 23. product automata faproduct will accept strings where both numbers of ‘a’s are divisible by 4 and several ‘b’s is divisible by 3: l = {w ∈ {a, b} ∗ ∣ na(w) mod 4 = 0 and nb(w) mod 3 = 0} end of example 6 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 253 fig. 23 product automata for ‘a’ mod 4 = 0 and ‘b’ mod 3 = 0 4. experimental result the performance of this developed method is compared with other conventional techniques in terms of construction time, memory utilization, scalability, robustness, application range, and complexity measures available in the literature. time complexity is measured by �� ∗ ��_��_�ℎ��� where is the length of the pattern and ��_��_�ℎ�� is the size of the alphabet. scalability is measured using � ∗ �� technique [16] that is available in the literature. the robustness of the algorithms is calculated by the finite order linear time-invariant (lti) [17] model found in the literature. this study assessed grid and product automata techniques for finite automata construction, focusing on accuracy, precision, and computational efficiency across scenarios. results show significant improvements over conventional methods by following in table 2, rated on a scale of 0 to 100%. higher values indicate better scalability, robustness, and application range, while lower values are preferred for construction time, memory usage, and complexity. this comparison is based on experiments with finite automata-related datasets. table 2 comparison of the developed technique with conventional methods criteria developedevelope techniques conventional methods improvement construction time 90% 40% 50% memory utilization 80% 30% 50% scalability 95% 50% 45% robustness 90% 60% 30% application range 95% 40% 55% complexity 85% 60% 25% fig. 24 shows a detailed performance metrics comparison between the developed techniques and conventional methods. the developed techniques show a 50% improvement in construction time to build automata, which can be highly effective. memory usage also has been improved by 50%, demonstrating better resource utilization. the experiments result in up to 45% improvement in scalability demonstrating that overall larger and more complicated automata can be handled by the derived methods. robustness can be quantitatively measured to evaluate how stable and reliable the methods are, which could be improved by 30%. the increase in the application range is 55% which indicates that techniques are applicable in a moderate number of scenarios. lastly, these approaches reduce complexity by 25% more than existing traditional methods and are easier to deploy. 254 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 fig. 24 graphical representation of performance comparison between developed and conventional methods 5. conclusion in this study, the exploration was centered on elucidating the construction of finite automata using two distinct methodologies: grid automata uses a structured grid-like arrangement of states to enable systematic state transitions. in contrast, product automata combines numerous automata into a single framework to coordinate their behaviors to expedite computing processes. the assessment indicated significant advantages of these approaches over conventional methods. grid automata’s systematic arrangement improves the clarity and speed of state transitions, whereas product automata allows for the aggregation of multiple automata, resulting in more streamlined and synchronized behavior. the performance evaluation produced promising results. in terms of construction time, memory utilization, scalability, robustness, application range, and complexity, the methodologies consistently outperformed traditional techniques by 25% to 50%. this demonstrates the practical viability and superiority of grid and product automata for developing finite automata. this study advances automata theory and emphasizes the practical application of these approaches in various disciplines. grid and product automata show promise for future applications in natural language processing, pattern recognition, compiler design, robotics, and bioinformatics because they simplify complex computational problems while providing stable and scalable solutions. as computational systems improve, integrating these strategies promises more efficient and effective problem-solving ways. this developed automated system’s scalability will benefit industries such as vehicle manufacturing and logistics in the future. let’s look at some more future automation possibilities. this developed method will significantly impact the robotics business in the coming years, facilitating the development and assembly of advanced robots. additionally, this approach will play a significant part in the field of self-driving cars, a growing focus in technology. conflicts of interest the authors declare no conflict of interest. references [1] x. zhao, d. shi, y. li, f. qin, z. chu, and x. yang, “simulation of dynamic recrystallization in 7075 aluminum alloy using cellular automaton,” journal of wuhan university of technology-mater. sci. ed., vol. 39, no. 2, pp. 425435, april 2024. [2] o. amir, a. amir, a. fraenkel, and d. sarne, “on the practical power of automata in pattern matching,” sn computer science, vol. 5, no. 4, article no. 400, april 2024. [3] a. modanese and t. worsch, “embedding arbitrary boolean circuits into fungal automata,” algorithmica, in press. https://doi.org/10.1007/s00453-024-01222-7 advances in technology innovation, vol. 9, no. 3, 2024, pp. 239-255 255 [4] g. pighizzini, l. prigioniero, and s. sadovsky, “performing regular operations with 1-limited automata,” theory of computing systems, vol. 68, no. 3, pp. 465-486, june 2024. [5] a. maletti and a. t. nasz, “weighted tree automata with constraints,” theory of computing systems, vol. 68, no. 1, pp. 1-28, february 2024. [6] g. r. laura, j. m. francisco, g. s. manuela, r. a. pedro, and m. f. víctor, “cellular automata simulations of the sintering behavior of ceramics driven by surface energy reduction,” natural computing, vol. 23, no. 1, pp. 69-70, march 2024. 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[16] x. yu, w. c. feng, d. yao, and m. becchi, “o3fa: a scalable finite automata-based pattern-matching engine for out-of-order deep packet inspection,” proceedings of the 2016 symposium on architectures for networking and communications systems, pp. 1-11, march 2016. [17] s. zekraoui, n. espitia, and w. perruquetti, “finite-time estimation of second-order linear time-invariant systems in the presence of delayed measurement,” international journal of robust and nonlinear control, vol. 33, no. 15, pp. 8951-8976, october 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 multiclass plant leaf disease prediction using fuzzy multimodal feature extraction vijay choudhary1,*, archana thakur2 1institute of engineering and technology, davv/ ips academy, institute of engineering and science, indore, india 2school of computer science & it, devi ahilya university, indore, india received 20 july 2024; received in revised form 19 december 2024; accepted 23 december 2024 doi: https://doi.org/10.46604/aiti.2025.14032 abstract delayed identification of crop diseases, which significantly impact agricultural yields, remains a critical challenge. crop diseases are a major factor contributing to reducing productivity. since leaves are the mirrors of crop health, by investigating the leaves, a prediction of crop health can be made. this study aims to predict crop disease in the vegetative growth phase with greater efficiency. the two most prominent features, color and texture of the leaves, are extracted with different techniques, followed by fuzzification of these features. two machine learning models, the bootstrap model and the multi-class support vector machine (msvm), are employed for disease prediction. the findings show that for multi-class disease prediction, the bootstrap model with histogram and modified co-occurrence matrix features obtains a superior average accuracy of 98.07%, while the msvm with fuzzy features delivers an average accuracy of 80.11% in the potato crop with early blight disease. keywords: modified co-occurrence matrix (mccm), fuzzy hue saturation value (hsv), local binary pattern (lbp), multi-class support vector machine (msvm) 1. introduction crop diseases and pests pose a significant threat to global agricultural production and food security. the detrimental impact on crop yields is increasing, leading to substantial losses. alterations in plant morphology not only detrimentally impact crop growth but also result in a significant decline in both quality and yield. in severe instances, entire harvests may be lost [1]. crop diseases are significant biological calamities that badly impact agricultural productivity and the safety of the ecosystem. accurate detection and identification of disease types are crucial for minimizing damage [2]. thus, precise crop disease diagnosis remains a critical challenge. leaves are the most exposed constituent of a plant. some insects may attack leaves or may face unfavorable weather conditions during the plant's growth period, leading to severe disease. commonly, the hue saturation intensity (hsi) and hue saturation value (hsv) color models are widely employed for color feature extraction, while the local binary pattern (lbp) is commonly utilized for texture feature extraction. in the proposed work, a novel approach is introduced that leverages fuzzy hsv for color feature extraction and fuzzy lbp for texture feature extraction. additionally, a second feature extraction technique based on a histogram and a modified co-occurrence matrix (mccm) is utilized to capture both color and texture features. * corresponding author. e-mail address: vij.choudhary@gmail.com advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 371 the extracted fuzzy hsv and fuzzy lbp features are fed into a multi-class support vector machine (msvm) for classification, while the histogram and mccm features are used to train a bootstrap model. the primary objective of this study is to compare fuzzy hsv and fuzzy lbp with histogram and mccm across various performance parameters, to evaluate their effectiveness in classification tasks. 1.1. background the primary method for predicting crop diseases is manual leaf observation in the field. however, this manual observation requires expertise and much experience in agriculture. this is a time-consuming process and can cover only a limited field area. the solution to every contemporary problem can be found in the technology that evolves every day. hence, the above problem can be conquered by technology. advancing technology offers a solution to this challenge, as the agricultural industry increasingly benefits from innovations in disease management and control. high-resolution images of agricultural fields are captured by remote sensing technologies, including satellites, drones, and airborne sensors. these images are then analyzed using image processing techniques to identify and monitor disease patterns across vast areas, thereby facilitating early detection and intervention [3]. machine learning and artificial intelligence (ai) play a key role in analyzing large datasets, including images, environmental data, and disease records. these technologies detect disease patterns, predict outbreaks, and recommend optimal management strategies [4]. through continuous learning and improvement, ai and machine learning contribute to more efficient and sustainable crop production. precise diagnosis in plant disease identification systems can be problematic, as disease symptoms may appear visually identical across different conditions. therefore, it is essential to extract features that can effectively capture the visual aspects of a leaf image to provide the most relevant description of the disease class. feature extraction reduces the data dimensionality by grouping relevant information into manageable subsets. further, data reduction accelerates the learning process and minimizes the computational demands placed on the machine learning model [5]. the feature extraction phase plays a vital role in precisely classifying different diseases by distinguishing infections from similar ones, based on specific symptoms or visible lesions. however, some plant leaf images exhibit nearly identical spots, posing classification challenges for such systems. nevertheless, by employing a suitable and effective feature extraction approach, it is possible to address the issue of similar lesion visibility and achieve a satisfactory resolution. notably, color, texture, and shape are crucial features that play a key role in the prediction of plant diseases. 1.2. existing models literature survey li et al. [6] presented an innovative approach for feature extraction in hyperspectral image analysis called spectral-gabor space discriminant analysis (sgda). the authors showed that hyperspectral images are high-dimensional data, making preprocessing essential before extracting spatial features. in this study, principal component analysis (pca) was employed to extract the desired principal components. the extracted principal components are then fed to derive gabor spatial features, which effectively capture low-level spatial structures of various orientations and scales. to improve the representation of the hyperspectral data, the original spectral features are combined with the extracted gabor spatial features, resulting in fused features. in the suggested sgda method, a p-factor α was introduced to regulate the relative contributions of spectral and gabor spatial information. hegde et al. [7] explored two approaches for feature extraction in the categorization of white blood cells (wbcs): the run-of-the-mill image processing approach and the use of a convolutional neural network (cnn) as a feature generator. the classification of wbcs was conducted in two steps. initially, wbcs are categorized as normal or abnormal, followed by the division of normal wbcs into five variants: lymphocyte, monocyte, neutrophil, eosinophil, and basophil. for feature extraction, advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 372 they employed state-of-the-art image processing techniques to capture shape, texture, and color features. in particular, the authors use the lbp representation of grayscale images to effectively capture local textures. additionally, the authors explored the suitability of features obtained from different layers of a pre-trained cnn, specifically alexnet, using the “cnn as a feature generator” method. the results from both feature extraction methods are compared. the predictor's performance is evaluated using the extracted features. remarkably, comparable accuracy using both the existing approach and the “cnn as a feature generator” approach was achieved. however, the classifier demonstrated slightly better performance when utilizing the features from the fully connected layer 8 (fc8) of alexnet for the classification of wbcs. overall, an accuracy of 99.7% in differentiating between usual and unusual wbcs and an average accuracy of 98.9% in classifying normal wbcs into their respective types was achieved. consequently, the authors quote that training at cnn requires a large dataset and significant computing resources compared to the well-known image processing approach. 2. literature review ahmad et al. [8] proposed a novel approach aimed at automating the identification of plant diseases through a series of sequential steps, including pre-processing, segmentation of the diseased leaf area, feature calculation using the gray-level cooccurrence matrix (glcm), feature filtration, and categorization. in the study, the authors computed six color features and twenty-two texture features. to perform the classification of plant diseases, support vector machines (svm) in a one-vs-one configuration were utilized. the proposed model for disease identification achieved an impressive accuracy of 98.79% with a standard deviation of 0.57 through ten-fold cross-validation. when tested on a self-created dataset, the accuracy for disease identification is 82.47%, while the accuracy for differentiating between healthy and diseased samples is 91.40%. these reported performance measures either surpass or are on par with existing approaches and are particularly superior to featurebased methods. consequently, the authors demonstrated that their method is the most suitable approach for automating leafbased plant disease identification. nagi et al. [9] developed a model for identifying plant leaf diseases using fuzzy feature extraction and the probabilistic neural network (pnn). the proposed method consisted of two main sections. firstly, the features (color and texture) were obtained from the leaf images using a fuzzy variant of the gray-level co-occurrence matrix and a color histogram. secondly, the pnn was employed for classification. to evaluate the effectiveness of the proposed method, leaf images of maize, grapevine, and tomato were obtained from the plantvillage database. the model achieved an impressive recognition accuracy of 95.68%. furthermore, it outperformed other commonly used classifiers such as svm, decision tree (dt), and random forest (rf) in terms of accuracy. overall, the combination of fuzzy feature extraction and the pnn classification approach has been proven to be highly effective for plant leaf disease recognition. finally, the authors concluded that the results obtained surpass those of other classifiers, validating the applicability of this method. in a study, basavaiah et al. [10] proposed a methodology for detecting and classifying four major diseases of tomato plants: septoria spot, bacterial spot, yellow curl, and mosaic virus. multiple feature extraction methods were employed to capture distinctive characteristics of these diseases. subsequently, the dt classifier and rf classifier were utilized for disease classification. the classification results demonstrated an accuracy of 90% for the dt classifier and 94% for the rf classifier. the authors noted that the random forest classifier exhibited higher accuracy compared to the decision tree classifier. this finding highlighted the superiority of the rf classifier in this context. the method proposed in this study offered several advantages. firstly, it significantly reduced computational time, making it more efficient than other commonly used techniques. through a rigorous literature review, several areas for improvement are identified: (1) the robustness of the system in the presence of noise and artifacts commonly found in imaging, such as motion artifacts or variations in imaging conditions, needs further evaluation. enhancing the method’s robustness is crucial for ensuring reliable disease prediction. advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 373 (2) training cnn and other deep learning models require large datasets and substantial computational resources, which limits their accessibility and practicality, especially in resource-constrained environments. (3) research into more efficient algorithms or models that can achieve high accuracy with fewer resources and smaller datasets is needed. (4) further research should focus on how to effectively integrate multimodal features to improve the accuracy and reliability of disease prediction models. (5) a lack of standardized evaluation metrics for comparing the performance of different feature extraction and classification methods. the purpose of this study is to present multimodal feature extraction techniques that effectively capture essential features and introduce a unique integration of machine learning models with the extracted features. the study also explores the fusion of fuzzy features with a multiclass disease prediction model, such as multiclass svm. 3. proposed methodology the present work is structured as a dataset collection followed by preprocessing, feature extraction, training of the machine learning model, testing of the trained model, and disease prediction. for data collection, a real-life dataset of potato crop leaves is used, which is taken from kaggle. 3.1. data collection the dataset used in the present work is adopted from kaggle.com [11]. the dataset consists of 1500 images of potato plant leaves. the data is distributed into three directories: train, test, and validation. within each directory, data is categorized into three different classes: potato leaf with early blight, potato leaf with late blight, and healthy leaf. the training set contains 300 images per class, while the test set and validation set contain 100 images corresponding to each class of potato images. the sample of the early blight is shown in fig. 1. the characteristic symptoms of the early blight include small, dry, papery spots that turn dark brown to black and become oval or angular. the spots can grow up to 12 mm in diameter and are usually confined to the main veins of the leaflets. fig. 1 potato leaf with early blight this section considers samples of two well-known diseases affecting potato crops. in case of late blight, dark, watersoaked lesions appear on the leaves, often starting at the tips or margins and spreading toward the center. the lesions are not confined by the leaf veins, and they may have a yellow edge. the primary difference between early blight and late blight is that early blight first infects the oldest leaves, causing brown areas with concentric rings, while late blight causes watery blisters on leaves, brown or black lesions on the lower leaves, and leaf rotting. a sample of a leaf infected with late blight disease and a sample of a healthy potato leaf are shown in fig. 2 and fig. 3, respectively. advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 374 fig. 2 potato leaf with late blight fig. 3 healthy potato leaf 3.2. pre-processing of the image preprocessing an image involves making it more suitable for further analysis. this process includes filtering noise and isolating the actual leaf from the background. for image processing, a modified grab-cut method has been utilized. the method is explained as follows. 3.2.1. grab-cut method grab-cut utilizes graph cuts as the foundation for its image segmentation approach. by employing a gaussian mixture model (gmm), the algorithm approximates the color distribution for both the desired object and the background [12]. in the grabcut, an initial rectangle is provided, where everything outside the rectangle is designated as a definite background. conversely, the region inside the rectangle is considered unknown. any additional user input indicating foreground and background is regarded as hard labeling, meaning these designations remain unchanged throughout the process. after receiving user input, the system performs an initial labeling process based on the provided data, assigning pixels as either foreground or background (hard labeling). 3.2.2. application of gaussian mixture model a gaussian mixture model (gmm) is employed to create models for the foreground and background components [13]. by leveraging the provided data, the gmm learns and generates new pixel distributions. this process involves assigning labels to the unknown pixels, classifying them as either probable foreground or probable background based on their color statistics and their relationship with other hard-labeled pixels [14]. subsequently, a graph is constructed using this pixel distribution. each pixel serves as a node in the graph, along with two additional nodes: the source node and the sink node. the foreground pixels are connected to the source node, while the background pixels are connected to the sink node [15]. once the graph is constructed, a min-cut algorithm is applied to divide it into two distinct components: the source nodes and the sink nodes. this separation is achieved by minimizing a cost function, which is determined by the sum of edge weights that are cut. subsequently, the pixels connected to the source node are classified as foreground, while those connected to the sink node are classified as background. this iterative process continues until the classification reaches a state of convergence, ensuring refined segmentation results [16]. 3.3. feature extraction feature extraction in image processing refers to the process of identifying and capturing distinctive and meaningful characteristics or patterns from an image. it involves transforming raw image data into a compact representation that retains relevant information for further analysis or classification tasks. in the process of feature extraction, specific algorithms or techniques are applied to extract relevant visual cues or attributes from the image. these cues can be derived from various levels of abstraction, ranging from low-level features like advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 375 color, texture, and shape, to higher-level features such as edges, corners, or even semantic concepts [17]. in this study, feature extraction is performed on the color and texture features of the potato plant leaves. the mccm, histogram, fuzzy hsv, and fuzzy lbp methods are used for feature extraction. 3.3.1. histogram histogram feature extraction is a fundamental technique in image processing that provides a compact yet informative representation of image content, making it useful for a wide range of applications [18]. histogram feature extraction from a leaf image involves quantifying the distribution of pixel intensities within the image. this process involves grayscale conversion, histogram calculation, normalization, and feature representation. 3.3.2. modified co-occurrence matrix (mccm) features to enhance the effectiveness of feature extraction from images, a novel method called mccm is introduced. the color co-occurrence matrix (ccm) utilizes features like energy, entropy, inverse difference, and contrast [19]. instead of employing all the traditional ccm features, some negative and low-value features have been omitted. employing mccm improves the model’s learning outcomes compared to utilizing the complete set of ccm features [20]. in the equations below, idm represents the inverse difference moment, ir(i, j) denotes the selected image region co-occurrence matrix, and i and j represent the intensity of pixels in the image. 3.3.3. fuzzy hsv feature extraction the fuzzy hsv method for leaf image feature extraction incorporates fuzzy logic principles into the hsv color space to extract features from leaf images [21]. incorporating “fuzzy” into the task implies a representation wherein color categories lack precise delineation, exhibiting a degree of ambiguity or uncertainty [22]. fuzzy logic facilitates the modeling of imprecision and uncertainty, offering a valuable framework for tasks involving color perception and classification, especially in scenarios where colors exhibit nuanced variations in shades or tones. 2 ( , ),energy ir i ji j= (1) ( , ) log( ( , )),entropy ir i j ir i ji j= − (2) (1 / (1 | |)) ( , ),idm i j ir i ji j= + − (3) 2 ( ) ( ( , )),contrast i j ir i ji j= − (4) 3.3.4. fuzzy lbp feature extraction the lbp technique is a statistical method in image processing, offering a means to extract potent features from images. its widespread adoption in computer vision applications underscores its efficacy, making it a cornerstone in visual computing [23]. fuzzy lbp incorporates fuzzy set theory to handle imprecise or uncertain pixel intensity values. instead of strictly binary decisions, fuzzy logic allows for gradual transitions between foreground and background intensities. the computation of membership function values of neighboring pixels concerning a center pixel, considering their intensity differences and fuzziness, is given in eq. (5). if ic represents the intensity value of the center pixel and in denotes the intensity values of its neighbors, then the fuzzy lbp formula for a center pixel with n neighbors is expressed as: 1 ( ) ( )20 fuz pr nn lbp i i inc n c−= −= (5) advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 376 where p represents the number of sampling points around the center. r denotes the radius of the circular sampling region. µ(inic) is the membership function indicating the degree of membership of the neighboring pixel intensity to the foreground or background. 3.4. model learning this phase of machine learning involves the training of two multiclass models. the first model, which uses mccm and histogram features as the training input, is a bootstrap model, while the second model, which uses fuzzy lbp and fuzzy hsv as the training features, is a multiclass svm model. 3.4.1. bootstrap sampling bootstrap learning, commonly referred to as bootstrap aggregating or bagging, represents a machine learning ensemble technique designed to enhance model stability and accuracy by mitigating variance and overfitting. it involves training multiple models utilizing subsets of the initial dataset and combining their predictions to yield a conclusive decision [24]. below is an outline of how the bootstrap learning model operates: bootstrap sampling: given an original dataset d of size n, bootstrap sampling involves selecting n samples randomly with replacement from d to create a sample di. this process is repeated to create multiple bootstrap samples. ( )d bootstrapsample di = (6) furthermore, the process includes model training and model aggregation. in model training, corresponding to each bootstrap sample di, a base learning algorithm, such as a decision tree or neural network, is trained independently to create a base model mi. in the model aggregation phase, the predictions of all base models are combined to make a final prediction. the aggregation method varies depending on the problem, with averaging for regression and voting for classification. if y1, y2, y3, y4, …., yk represent different bootstrap samples, then the equations are ( )m trainmodel di i= (7) ( , , , ..., ) 1 2 3 y aggrepredicn y y y y k = (8) fig. 4 architectural design of the disease prediction model fig. 4 depicts the complete architecture of the proposed work. the block diagram illustrates the overall workflow, including the distinct phases of the multi-class disease prediction process. the first phase involves pre-processing the dataset using the three algorithms shown in the block diagram. the second phase covers feature extraction using the techniques advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 377 highlighted in the diagram. phase three incorporates the training of the bootstrap and msvm models for disease prediction, and finally, the two models are compared based on the four parameters shown at the leaves of the architectural diagram. algorithm 1 health prediction using bootstrap learning input: potato image dataset, which contains a set of healthy and diseased leaf images. output: prediction accuracy using the bootstrap model. method: step 1. apply the bat algorithm and gmm for preprocessing and leaf region selection of the input image. step 2. apply the histogram method and mccm method for color and texture features, respectively. step 3. normalize the features obtained from the above methods. step 4. apply the bootstrap learning model to get prediction accuracy. 3.4.2. msvm learning the msvm formulation aims to find optimal hyperplanes that best separate data points into k classes using the one-vsall strategy [25]. a training dataset {(x1, y1), (x2, y2), .., (xn, yn)} where xi is the feature vector and yi is the class label with yi ꜫ {1,2, .., k} for k classes. the optimization function for the problem is 1 2 min max(0,1 ( )) , 12 n w c y w x bj ij j i j w b ij j + − + =  (9) algorithm 2 health prediction using msvm input: potato image dataset, which contains a set of healthy and diseased leaf images. output: prediction accuracy using the msvm model. method: step 1. extract fuzzy hsv features from the input image. step 2. extract fuzzy lbp features from the input image. step 3. normalize the features obtained from the above methods. step 4. apply the msvm learning model to obtain prediction accuracy. 4. result and discussion the disease prediction results of the bootstrap model and multiclass svm learning model have been presented in this section. the bat-based crop leaf disease prediction bootstrap model (bcdpbm) [24] uses a novel approach of the bat algorithm for preprocessing of the image, and the feature extraction is done using a unique combination of histogram feature and mccm feature. the prediction of multi-class leaf disease is also performed using multi-class svm with fuzzy hsv and fuzzy lbp feature extraction techniques. it is found that the bootstrap model, along with the mccm features, outperformed the msvm model with fuzzy features. the bootstrap model gives an average accuracy of 98.07% as compared to the average accuracy of 80.11% exhibited by msvm in multi-class disease prediction. table 1 shows the accuracy of the bcdpbm model along with multi-class svm. the table highlights significant differences in the performance of the bcdpbm model and msvm model across varying numbers of test images, the result shows that bcdpbm encounters a very low error rate of 0.51 % as compared to the 21.63 % error rate of msvm. fig. 5 graphs the accuracy comparison of the two models along with the error rate. advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 378 table 1 accuracy and error rate of multiclass plant leaf disease prediction in the bcdpbm and msvm models testing images bcdpbm msvm accuracy % error % accuracy % error % 75 97.3 2.7 82.67 17.33 150 95.12 4.88 80.92 19.08 225 99.12 0.88 79.82 20.18 300 99.34 0.66 78.81 21.19 400 99.49 0.51 78.37 21.63 fig. 5 accuracy and error rate of multiclass plant leaf disease prediction in the bcdpbm and msvm models table 2 shows the precision value comparison between the bcdpbm model and the multi-class svm model for different datasets. the results indicate that the bcdpbm model achieves a precision value of “1” for all datasets, surpassing the multiclass svm model, which displays precision values of 0.84, 0.80, and 0.83 for datasets of sizes 225, 300, and 400, respectively. table 2 precision values for plant leaf disease prediction using bcdpbm and multiclass svm models for distinct size datasets testing images bcdpbm msvm 75 1 1 150 1 1 225 1 0.8491 300 1 0.8052 400 1 0.8300 table 3 presents the recall values in the case of different numbers of images shown by the two models discussed above. table 4 shows the f-measure values exhibited by the bcdpbm and multiclass svm models. the results show that the bcdpbm model gives an average f-measure value of 0.99 as compared to the f-measure value of 0.84 given by multi-class svm. table 3 recall the value of plant leaf disease prediction in bcdpbm and a multiclass svm model for distinct-sized datasets testing images bcdpbm msvm 75 0.9600 0.8000 150 0.9804 0.7632 225 0.9867 0.7895 300 0.9901 0.8158 400 0.9924 0.8300 advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 379 table 4 f-measure of plant leaf disease prediction in bcdpbm and a multiclass svm model for distinct-sized datasets testing images bcdpbm msvm 75 0.9796 0.8889 150 0.9901 0.8529 225 0.9933 0.8182 300 0.9950 0.8105 400 0.9962 0.8300 the accuracy of binary class disease prediction is shown in table 5. if the number of images is increased for the testing, the accuracy is also proportionally increased in the case of bcdpbm, while the multiclass svm shows a random accuracy value. the first model shows the highest accuracy of 99.74 %, whereas the second model depicts the highest accuracy of 94.67 %. the graphical representation of the accuracy comparison of the two models mentioned in table 5 is presented in fig. 6. a comprehensive comparison of the bcdpbm and msvm models with the existing models is presented in table 6. models like fine-tuned densenet, fine-tuned mobilenet based on optimal mobile network-based convolutional neural network (omncnn), and crop leaf health prediction model (clhpm) have been added to the comparison table. the bcdpbm and msvm models with proposed features show noteworthy contributions. table 5 accuracy of binary class plant leaf disease prediction in bcdpbm and the msvm model across different dataset sizes testing images bcdpbm msvm 75 98.65 94.67 150 99.34 93.42 225 99.56 91.23 300 99.67 90.40 400 99.74 91.35 fig. 6 accuracy of binary class plant leaf disease prediction in the bcdpbm and msvm models table 6 comparison of msvm and bcdpbm models with the existing models dataset model accuracy in % references kaggle dataset clhpm 99.23 [20] plantvillage dataset fine-tuned densenet 98.17 [26] plantvillage dataset fine-tuned mobilenet based with omncnn 98.7 [27] kaggle dataset msvm 92.21 proposed kaggle dataset bcdpbm 99.39 proposed advances in technology innovation, vol. 10, no. 4, 2025, pp. 370-382 380 table 7 additionally compares the accuracy performance of msvm and bcdpbm across different dataset sizes for three types of conditions: healthy leaf, leaf with early blight, and leaf with late blight. the table shows accuracy in each disease category. the msvm model shows variability in performance, particularly for early blight, whereas bcdpbm demonstrates consistent and superior accuracy across all classes and dataset sizes. table 7 accuracy in each disease category by bcdpbm and msvm model testing images bcdpbm msvm healthy leaf early blight late blight healthy leaf early blight late blight 75 88 96 64 96 96.5 99.90 150 91.83 93.87 57.14 98 98.40 99.96 225 86.48 94.66 59.21 98.64 98.64 99.50 300 96 79 61.38 99 99.20 99.98 400 88.40 81.67 62.04 99.25 99.23 99.92 5. conclusions and future scope this research presents a novel approach to crop disease prediction by leveraging leaf features and machine learning techniques. the present work contributes to advancing the field of agricultural disease prediction by introducing fuzzy hsv and fuzzy lbp methods for color and texture feature extraction, respectively, along with instance histogram and modified cooccurrence matrix (mccm) techniques. through comparative analysis, the effectiveness of the bootstrap model utilizing mccm features is demonstrated. the work is concluded as follows (1) an impressive average accuracy of 98.07% for multiclass classification and an average accuracy of 99.39% for binary classification is achieved. (2) significant differences in precision, recall, and f-measure are also found in the experiments. (3) overall, the bootstrap model with mccm and histogram feature extraction methods give better results as compared to the msvm model with fuzzy hsv and fuzzy lbp feature extraction methods. future research could focus on enhancing the robustness and scalability of the bootstrap model, potentially incorporating additional features or refining existing ones to achieve even higher accuracies. real-time on-field images can also be considered for experimentation to get area-specific disease predictions in crops. conflicts of interest the authors declare no conflict of interest. references [1] h. zhao, y. yang, c. yang, r. song, and w. guo, “evaluation of spatial resolution on crop disease detection based on multiscale images and category variance ratio,” computers and electronics in agriculture, vol. 207, article no. 107743, 2023. 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[27] s. ashwinkumar, s. rajagopal, v. manimaran, and b. jegajothi, “automated plant leaf disease detection and classification using optimal mobilenet based convolutional neural networks,” materials today: proceedings, vol. 51, no. 1, pp. 480-487, 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v9n3(2024)-aiti#13619(224-238).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 english language proofreader: yen-chun hsieh current trends in named entity recognition from automatic speech recognition: a bibliometric analysis using scopus database thu hien nguyen1, tuan linh nguyen2, thanh binh nguyen3,* 1faculty of mathematics, thai nguyen university of education, thai nguyen, vietnam 2faculty of electronics enginee, thai nguyen university of technology, thai nguyen, vietnam 3faculty of physics, thai nguyen university of education, thai nguyen, vietnam received 23 april 2024; received in revised form 08 july 2024; accepted 09 july 2024 doi: https://doi.org/10.46604/aiti.2024.13619 abstract named entity recognition (ner) is critical for language understanding and text mining systems, such as event extraction and automatic question-and-answer systems. however, ner from automatic speech recognition (asr) outputs remains challenging due to errors and lack of textual cues. this study aims to provide a comprehensive bibliometric analysis of research on ner from asr, focusing on publications indexed in the scopus database before 2024 to understand the research field. using biblioshiny and vosviewer tools, this research identifies the key trends, prominent authors, and international collaborations in the research network. the results show steady growth in this research area, while conference papers are the predominant source type. additionally, the study highlights the increasing intervention of deep learning approaches to enhance ner accuracy, suggesting potential research directions to reduce error rates, and developing more robust ner algorithms. finally, the findings underscore the importance of cross-disciplinary collaborations to document any current challenges. keywords: named entity recognition, automatic speech recognition, bibliometrics, scopus, potential research direction 1. introduction named entity recognition (ner) is identifying named entities from free-text documents and classifying them into predefined types such as person names, organizations, and locations [1]. in 2011, the quaero project proposed an extended definition of entity identification, where basic entities are combined to identify more complex entities. for example, the organization name is further categorized into government organizations, educational institutions, or commercial organizations [2]. automatic speech recognition (asr) is defined by yu and deng [3] as the processes, technologies, and methods that enable better human-computer interaction through the translation of human speech into text format. ner from the asr output text is more challenging than written text. this difficulty arises because the asr output often contains numerous errors (insertions, deletions, and word substitutions) and lacks some important indicators for ner, such as capitalization and punctuation. furthermore, the scarcity of large, standardized speech data sources for training purposes demonstrates the challenges [4]. in asr systems, the ner information illustrates the significant meaning in information extraction systems (fig. 1) and is useful in various applications such as optimizing search engines, content categorization for news providers, and content recommendations. sometimes, ner from speech is also used for privacy support applications, such as concealing patient * corresponding author. e-mail address: binhnt@tnue.edu.vn advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 225 names in healthcare. some companies employ ner systems to detect negative customer feedback. in addition, applications like netflix, youtube, and facebook rely on ner to provide recommendations based on user search history [5]. until now, most research on ner from asr (ner–asr) has traditionally followed the pipeline approach. however, errors propagated through the different stages in this method might directly affect the performance of the ner system. to minimize the disadvantage generated by pipelines, researchers recently have been exploring an end-to-end approach to directly label named entities from the asr system [6]. fig. 1 ner system from asr various methods have been proposed in recent decades to solve the ner–asr problem. however, both approaches still documented the difficulties. research to gain a comprehensive overview of this issue worldwide is necessary. this research employs an effective method using bibliometrics to measure the quality of research by statistically analyzing quantitative data from scientific publications [7]. bibliometrics refers to the mathematical and statistical methods for monitoring and analyzing the structure of a scientific field, identifying research areas and trends, evaluating research development, and examining patterns related to regional and authorship characteristics in publications and citations [8]. the investigation from bibliometrics might point out the current research trends and enhance research quality for innovative future research. the overview studies for natural language processing (nlp) have also utilized bibliometrics as a statistical method [910]. among these studies, only research on ner for bahasa and indonesian languages for regular text [11]. the data was only collected from scopus, acm, ieeexplore, and science direct within a short time frame, the past five years, from 2016 to 2021. moreover, to the best of the author’s knowledge, there is currently no comprehensive bibliometric study on ner for asr, which provides a holistic view of the development of research in this area worldwide and identifies key research directions, opportunities, and challenges for the future. to continue with the bibliometric analysis research for ner–asr and address the shortcomings of previous studies, this research will undertake the important aspects, including offering a standardized five-step methodological framework for conducting quantitative scientific studies in this field; conducting a comprehensive bibliometric analysis of ner–asr publications indexed in the scopus database before 2024; identifying and visualizing research trends, prominent authors, and international collaborations using biblioshiny and vosviewer tools; providing insights into the challenges and limitations of ner–asr, emphasizing the importance of deep learning approaches; finally, this work proposed potential research directions and highlighted the significance of cross-cultural and interdisciplinary research collaborations. 2. methodology the research will be conducted by applying a scientific mapping process [12], which consists of five stages including (1) research design; (2) data collection; (3) data analysis and visualization; (4) result interpretation. (1) research design: the research design stage has been directed by identifying the main research questions: how have the studies been distributed over the past ten years? who are the most prominent authors in this field? which countries have shown the highest productivity and activity in this area? what are the research trends of ner from speech? what are the approaches, research methods, and data used in the publications? (2) data collection: the data collection phase consists of three separate steps: collection, filtering, and cleaning. 226 advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 step 1: collection this task performed a search using the scopus database (http://www.scopus.com), utilizing the advanced search options to input search conditions and appropriate operators based on the syntax of this search tool. the scopus database was used for this bibliometric analysis due to its large amount of indexed documents to the web of science and dimensions. the data query was executed on january 2, 2024. keyword selection is an important factor in the article retrieval process, and the possibility of incorrect or incomplete keywords can skew the results. therefore, the keywords have been carefully selected based on the advice of specialized research and experts, reflecting key concepts in ner for asr. the identification of relevant keywords for ner includes: “named entity recognition,” “named entity extraction,” “named entities,” and “name entity.” for asr, the keywords were “automatic speech recognition,” “speech recognition,” “speech recognizer,” “speech processing,” and “speech data" and found rational 885 papers. additionally, the search scope was limited to introduce only english-language documents in computer science, including scientific articles and conference papers. the filtering result was 797 documents. finally, research restricted the search to include only documents published before 2024, with the keywords appearing in the title and abstract. the data investigation statement to scopus was: title-abs (("name* entit*") and ("speech recognition*" or "speech processing" or "speech data")) and pubyear < 2024 and (limit-to (doctype, "cp") or limit-to (doctype, "ar")) and (limit-to (language, "english")). the filtering data consisted of 244 documents. step 2: filtering the data filtering process involved a systematic approach to ensure the final dataset consisted of relevant and high-quality articles. the process of reading and filtering unrelated articles was conducted thoroughly in two rounds: independent evaluation of titles, abstracts, and keywords by each researcher to eliminate documents which not directly relevant to the research topic, and followed by a group review to achieve the consensus and resolve any discrepancies. this meticulous approach resulted in the final selection of 55 appropriate documents deemed directly relevant to the mentioned problem, enhancing the accuracy and reliability of the bibliometric analysis. step 3: cleaning this step has been conducted by addressing inconsistencies in certain information within the obtained dataset, such as author names and affiliations. the following quest was data analysis and visualization: various analytical techniques were applied to extract information from the collection of publications. general information about the published collection was summarized, and the annual publication count was analyzed to identify trends in the research field. keyword analysis techniques were used to identify research trends in the field. (3) data analysis and visualization: for data analysis, several widely used open-source scientific bibliometric tools were utilized including citespace, science of science (sci2) tool, bibexcel, copalred, workbench tool, bibliotools, vosviewer, scimat, citnetexplorer, biblioshiny, among others. in this study, authors have employed vosviewer (version 1.6.20) and biblioshiny (version 4.0) to identify and visualize collaboration networks between authors and countries and to identify trends using keywords. (4) the interpretation of the results is presented in section 3. 3. results and discussion according to table 1, a total of 55 documents from scopus, in which 7 journal articles and 48 conference papers have been listed. these documents were published in 35 different sources before 2024. the steady growth rate indicates sustained interest in asr and ner. the total number of citations was 497 times, corresponding to an average of 9.036 citations per advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 227 document, indicating the significance and impact of the research. a total of 176 authors have contributed to these documents. interestingly, single-authored works are rare, with only 1 such instance. collaborative efforts are more common, with an average of 3.69 co-authors per document. 10.91% of the collaborations involve international authors. this global collaboration fosters cross-cultural perspectives and knowledge exchange. table 1 investigation of articles on ner–asr published in scopus before 2024 attribute number of magnitudes sources (journals, books, etc) 35 documents 55 article 7 conference paper 48 annual growth rate 4.49% document average age 11.4 average citations per document 9.036 references 1179 keywords plus (id) 357 author’s keywords (de) 92 authors 176 single-authored (with no co-author) 1 co-authors per document 3.69 international co-authorships 10.91% the first publication on ner–asr was introduced in 1998 in the proceedings of the annual meeting of the association for computational linguistics [13]. there challenges in researching ner–asr can be attributed to various factors. firstly, the output text from asr systems often lacks structure, such as punctuation marks, capitalization or proper nouns, and location names. this leads to difficulties in understanding and limits the ability to exploit the asr output text for applications. so, the automatic ner–asr output text always contains recognition errors, especially with out-of-vocabulary (oov) named entities. additionally, asr errors often occur in the constituent words of named entities or the context of those words, directly affecting the performance of ner. furthermore, ner systems have to address issues related to the lack of important cues such as capitalization and punctuation marks. in particular, the scarcity of sufficiently large labeled speech datasets for training ner models is one of the most significant challenges in research. fig. 2 annual scientific publication on ner–asr until 2005, there was minimal attention to this topic, resulting in very few publications. the bar chart within the graph in fig. 2 likely corresponds to this early period, showing a low number of articles per year. starting from 2006, there has been a significant surge in ner-related publications with an average of around 3-6 publications per year. the graph’s red line shows 228 advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 a gradual increase in the number of articles per year. researchers have increasingly explored ner in the context of asr, leading to a growing body of literature. the surge in publications likely reflects advancements in asr technology. researchers’ increased interest in ner applications has contributed to this trend. ner–asr is gaining prominence due to its relevance in various domains. the peaks in the line (around 2010, 2013, and 2022) indicate periods of heightened research output. in 2013, the field of nlp witnessed significant advancements. researchers began adopting deep learning techniques, including neural networks, for various nlp tasks. this shift likely influenced asr research, leading to improved ner methods. in 2022, pre-trained language models (such as bert, t5, and their variants) had gained prominence. these models demonstrated exceptional performance across nlp tasks, including ner. the fluctuations between peaks represent variations in annual publication numbers. despite fluctuations, the overall trend is upward. the line representing the number of articles suggests sustained interest and progress in ner research from asr. fig. 3 shows the number of publications by different countries over time. fig. 3(a) highlights the global interest in ner research within the asr domain and shows that france consistently has the highest number of publications, followed by china, germany, japan, and the united states. the upward trend suggests a growing interest in ner–asr research globally. recent research on the end-to-end approach for ner–asr also follows studies for french [14], english [15], and china [16]. fig. 3(b) highlights the countries with the most citations for their ner–asr work. france and japan were the first and secondlargest segments reflecting significant citation impact, followed by the united states, china, germany, and the united kingdom, respectively. these countries likely produce influential research or have well-established research networks. (a) five highest publication countries (b) most cited countries on ner–asr before 2024 fig. 3 please add captions for figures. advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 229 the combination of both graphs suggests that while several countries actively produce ner-related research, france stands out in terms of both quantity and impact. france’s dominance in both production and citations indicates a strong research ecosystem. the concentration of publications in france, china, and japan may be attributed to several factors: (1) rich data sources: these countries may have access to diverse and extensive speech data, enabling comprehensive research. (2) collaboration networks: collaborations among researchers in these countries could lead to more impactful work. (3) research infrastructure: well-established research institutions and funding support contribute to their prominence. researchers worldwide can learn from france’s success in ner–asr. collaboration across borders can enhance research quality and impact. access to rich data remains crucial for advancing ner–asr studies. the receiver operating characteristic (roc) curve is an important tool in evaluating the performance of classification models. in the bibliometric field, the roc curve can be used to evaluate the ability of a certain model or index to classify scientific articles into “highly cited” and “undercited” groups of many leads. the calculated number of citations and citescore for each document is shown in table 2. table 2 statistics on the number of citations and citescore for documents documents publication year number of citations citescore d1 2018 59 2.000 d2 2005 48 3.587 d3 2000 36 0.600 d4 2004 35 3.684 d5 2013 29 0.256 ⋮ d55 2022 0 1.973 fig. 4 shows the roc curve based on the citescore classification. the model’s performance, indicated by an area under the curve (auc) of 0.63, demonstrates a superior classification ability compared to a random model. however, this performance is not very high and requires the collection step to gather more data from various databases to improve the analysis process and thereby enhance the roc performance. fig. 4 the roc curve plotted against the fdr based on citescore fig. 5 illustrates the international collaboration network research of ner–asr which consists of 27 countries. in each country, the strength of authorship will be calculated by the co-authorship links with other countries. the thickness of these links may indicate the strength of collaboration. the network’s structure reflects global research partnerships in ner from 230 advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 speech. collaborations across clusters may lead to knowledge exchange, and advancements, and can guide future research initiatives and foster international cooperation. these clusters likely represent regions with strong research ties and collaborative efforts in ner from speech. the results show that the network can be divided into two main clusters or groups: (1) the united states, france, qatar, japan, and india. the united states, as a central node, plays a significant role in ner research. france, qatar, japan, and india are closely connected to the united states, suggesting active collaboration. these countries likely share expertise, resources, and research findings. joint projects, conferences, and knowledge exchange may be common. the united states plays a significant role, possibly leading in ner research. (2) germany, canada, and switzerland form another cohesive group. their collaboration may involve joint projects, conferences, or shared research interests. the proximity of these countries in the network indicates their strong ties. fig. 5 significant collaborative relationships and partnerships among the countries on the research of ner–asr fig. 6 presents an analysis of the top 10 sources in the field of ner–asr. these sources comprise eight conference proceedings and two journals. these sources play a crucial role in shaping research and advancing knowledge in ner–asr. the chart visually represents each source’s relevance and impact, with the distance from the center indicating its significance. notably, sources closer to the outer edge hold greater relevance and influence in ner–asr research. fig. 6 top 10 sources ranked by the output published by them on ner–asr specifically, the proceedings of the annual conference of the international speech communication association (interspeech) contain 10 articles. as a leading conference in the field, interspeech serves as a platform for researchers to present their findings and exchange ideas. the high number of articles indicates its significance in ner–asr research. proceedings of the international conference on acoustics, speech, and signal processing (icassp) feature 5 articles related to ner–asr. icassp is a prestigious conference where experts discuss cutting-edge research in speech and signal processing. its inclusion underscores its impact on ner–asr advancements. advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 231 notably, scholarly publications in ner–asr predominantly appear in conference and workshop proceedings. these venues provide a fertile ground for researchers to share their latest findings, collaborate, and contribute to the field. researchers often present their work at conferences like interspeech and icassp, leading to a rich body of knowledge in ner–asr. a total of 55 documents in the investigated dataset were contributed by 176 authors. table 3 reveals the top 10 highest in terms of publications, along with affiliations and country. the authors’ names are ranked from 1 to 10 based on their ner–asr publications. table 3 top 10 authors ranked by the number of publications on ner–asr and their affiliations rank authors affiliation total publications total citations total publications/ total citations 1 béchet f. university of avignon, france 3 87 3.4 2 isozaki h. ntt communication science labs, japan 3 29 10.3 3 morin e. university of nantes, france 3 80 3.8 4 rosset s. university of paris-saclay, france 3 50 6.0 5 sudoh k. ntt communication science labs, japan 3 29 10.3 6 tsukada h. ntt communication science labs, japan 3 29 10.3 7 glotin h. université du sud toulon-var, france 2 9 22.2 8 itoh n. ibm research tokyo, ibm japan 2 14 14.3 9 kim j. h. sogang university, seoul, south korea 2 37 5.4 10 kurata g. ibm research tokyo, ibm japan 2 14 14.3 béchet f. has 3 publications and is affiliated with the university of avignon, france. they have received 87 citations, indicating significant impact. morin e. also stands out with 80 citations, demonstrating substantial influence. isozaki h., sudoh k., and tsukada h., all affiliated with ntt communication science labs, japan. these authors, affiliated with ntt communication science labs, have each contributed three publications. their moderate citation count of 29 suggests active research within a focused group. itou k., kurata g., glotin h., and kim j. h. have two publications each. kim j. h. received 37 citations, indicating impactful work from seoul national university in south korea. the remaining two authors have lower citation counts (14 and 9), but their contributions are valuable. fig. 7 top 10 most prolific authors’ publication production in the mentioned period the collaboration among authors reveals a mix of small research groups. notably, two main clusters emerge—one from japan and the other from france. while collaboration within these groups is evident, the overall diversity remains relatively low. future research could explore ways to foster cross-group collaboration and enhance diversity in ner–asr studies. the 232 advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 analysis of fig. 7 provides valuable insights into the annual publication trends of the top 10 authors in the field of ner–asr from 2000 to 2022. the visualization effectively represents the publication output of each author through the use of node size, providing an immediate understanding of their productivity. by representing collaborations through connecting lines, the visualization provides insight into the collaborative nature of the field. thicker lines indicate more collaborative works, emphasizing the importance of collaborations among researchers in ner–asr. collaborative efforts can lead to the exchange of ideas, the pooling of resources, and the development of more comprehensive research outcomes. isozaki h., sudoh k., and tsukada h. stand out as the most prolific authors, as indicated by their larger circles. this suggests that they have made significant contributions to the field and have produced a substantial amount of research. however, it is noteworthy that their publications are concentrated within a short timeframe. this concentration of publications could indicate a period of intense research activity or specific projects that resulted in a high number of publications. in contrast, béchet f. demonstrates consistent research efforts throughout the years, as indicated by a steady publication output. this signifies a sustained level of productivity over an extended period, suggesting a long-term commitment to ner–asr research. the visualization also highlights emerging authors morin e. and rosset s., whose publication circles are growing over time. this indicates their increasing productivity and suggests that they are actively contributing to the field. the growing circles of these authors may indicate a rising influence and potential for becoming influential figures in the future of ner– asr research. in fig. 8, the analysis of keyword criterion, the unrelated keywords such as “state of the art,” “semantics,” “character recognition,” “computational linguistics,” “text processing,” and “broadcast news” have been excluded. for each year, the author has selected three keywords to represent the annual research trends, each keyword should appear at least five times to meet the criteria requirements. fig. 8 the research trends topic in ner–asr the bar graph provides an overview of the research trends in ner–asr ascertained through the co-occurrence of keywords in publications within the research field. deep neural network models have played a crucial role in achieving stateof-the-art results in ner. researchers have achieved these results by exploring different aspects of ner systems, including deep learning model architectures, training methods, training data, and the encoding of ner system outputs. these advancements highlight the adaptability and flexibility of deep learning models in improving ner performance. advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 233 despite the progress made in ner, substantial amounts of human-annotated training data are still required. efforts have been made to address this challenge by exploring the use of external knowledge sources, such as named entity dictionaries and part-of-speech tags, to replace human annotations. however, obtaining effective external resources remains a significant challenge. the shift from linear learning methods to deep learning architectures has been a pivotal development in ner research. researchers have not only focused on refining algorithms and enhancing ner performance but have also explored novel approaches to address challenges specific to ner. additionally, the influence of upstream and downstream tasks related to ner, such as sequence tagging and entity linking, has further shaped the trajectory of ner advancements. the word cloud visually represents the prominence of specific terms within the context of ner–asr. the size of each word in the cloud indicates its frequency or importance. prominent terms in the word cloud, such as “named entities,” “speech recognition,” and “natural language processing systems,” highlight critical concepts in ner–asr research. these terms suggest that researchers in this field may be focused on refining algorithms to handle asr errors, improving entity recognition accuracy, and developing ner systems that are specifically designed for asr applications. fig. 9 analyzes the co-occurrence of author keywords, with the minimum number of occurrences of a keyword being two. the network of keywords is based on their co-occurrence and represents those most frequently used in publications on ner– asr. relevant keywords were grouped and given the same color. the links between keywords represent their co-occurrences, and the size of the keyword is proportional to its frequency of occurrence. out of a total of 92 keywords, the fact that only 13 meet the threshold suggests that these concepts are particularly relevant and prominent in ner–asr research. the analysis confirms that the research on ner for asr has been focusing on end-to-end deep learning approaches since 2016. this finding aligns with the broader trend in ner research, where the adoption of deep learning models has significantly impacted the field’s development. the network diagram underscores the significance of deep learning in ner–asr research, with “deep learning” being one of the identified keywords. this suggests that researchers in this field have been leveraging deep learning techniques to enhance ner performance within asr systems. additionally, the network highlights the importance of “named entity recognition” and “automatic speech recognition” as core concepts in this research area. the interconnectedness of these keywords in the network diagram signifies their relevance and the interdependency between ner and asr. fig. 9 network of co-occurring keywords in ner–asr publications 234 advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 in addition to the bibliometric study, the study also carried out analyzing in detail the content of outstanding recent publications indexed by the scopus database. the results are shown in table 4 and illustrate the most challenging belongs to the database criterion. the majority focus on countries with rich data sources such as english [1, 15], chinese [16-17], french [14, 18] and japanese [19]. very few studies have focused on low-resource languages [20-21]. the studies with limited databases have been proposed using standard text datasets, converting uppercase letters to lowercase, and removing punctuation marks to obtain output text data from asr [20]. especially, some have suggested methods to augment data [22], including text-to-speech systems to improve the data for model training, demonstrating a significant improvement in the performance of the recognition model [5, 20], and knowledge transfer to enrich training data [23]. in the initial stage, the method is mainly based on rule sets [24]. however, when the input is the asr output text, the capitalization information for named entities is no longer available, making it challenging to gather the necessary linguistic information to construct the rules. so, many machine learning-based approaches have been proposed such as the svm [19], hmm [25], maximum entropy [26], and crf [27], which focused on english, chinese, japanese, and french. researchers in nlp and asr are actively exploring ways to improve ner within asr systems. techniques such as deep learning architectures have significantly impacted ner performance. understanding the co-occurrence patterns of relevant terms can guide further research and system development. in particular, in terms of research methods, the main trend is also shifting to using deep learning models. these approaches offer advantages in vector representation, computational capability, non-linear mapping from input to output, and the ability to learn high-dimensional latent semantic information [28]. table 4 demonstrates the dominance of the bidirectional encoder representations from the transformers (bert) model which has been exploited critically in recent studies [16-17, 20]. bert addresses context in ner by utilizing pre-trained language models to extract text features at the word level, capturing contextual information effectively. by integrating bert with models like bilstm and crf, bert can consider surrounding words and their sequential relationships, ensuring a better understanding of the context and dependencies between adjacent entities for coherent entity recognition. the bert method enhances semantic information enrichment, resolving issues like unclear entity boundaries and semantic ambiguity during training, leading to improved accuracy in entity recognition tasks. furthermore, bert might encode individual characters and extract sequential information through dual-channel networks contributing to achieving high accuracy, recall, and f1 scores in ner tasks [17, 20]. some proposals addressed the ner system’s issue with data by pretraining the prediction of capitalization [29] or using punctuation and uppercase recovery model [20] before combining it with the ner model. only 6 out of 55 publications have an end-to-end, while the rest all use a pipeline approach. almost all early studies mostly employed the pipeline approach due to its simplicity in design. however, this approach involves training individual components separately, requiring separate training algorithms and loss functions for each component, therefore a large number of hyperparameters are needed, leading to training complexity. furthermore, the errors occurring in each component are not computed when combined with other components, resulting in significant accumulated errors. some studies have demonstrated the effectiveness of the end-to-end model when combined with language models [6] or augmenting training data [22]. almost all studies proved that the end-to-end model was not better than the pipeline model in terms of performance [7] and confirmed that “filtering” data through each step was still possible and therefore improved results. it also documented the need to improve the asr model to reduce “anomaly” errors of insertion, deletion, substitution, and addition of words in the asr output text [7, 20]. however, an end-to-end approach still shows the potential to optimize the asr system. this is a complex process that spans from the beginning to the end. this model demonstrates the advantages of integrating the system into a single model, which facilitates the training process, minimizes errors between components, improves execution speed, and enhances deployability in practical applications. advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 235 table 4 statistics of some recent studies on ner for asr indexed in scopus database author year data approaches/methods/techniques results yadav et al. [6] 2020 english speech • two-step pipeline and end-to-end • end-to-end: cnn bilstm fc and softmax • ctc loss • the e2e approach provides better results compared to the two-step pipeline approach caubrière et al. [7] 2020 french speech (etape 2012) • pipeline and end-to-end • end-to-end: cnn bilstm – softmax • ctc loss • in comparison with the best result of etape 2012, the e2e system improved by 4%. • the e2e approach shows interest but is below the updated pipeline approach. porjazovski et al. [23] 2020 finnish speech knowledge transfer from the estonian dataset to enrich training data. • pipeline • bilstm-crf • rule-based • the proposed model is better than the neural network architecture, and worse than the rule-based system. • converted the training set to lowercase and removed the punctuation, which yielded significant improvement. porjazovski et al. [15] 2021 finnish, swedish, and english speech • end-to-end • attention-based encoder-decoder model for asr with ner tags. • multitask learning for speech transcription and named entity annotation. • the multi-task approach allowing additional fine-tuning of the ner branch, outperforms the augmented labels approach chen et al. [16] 2022 chinese speech (aishell-ner built upon aishell-1) • end-to-end • transformer: entity-aware asr • bert: pretrained ner tagger • conformer asr outperforms transformer asr in cer. • transformer ea-asr faces a small loss in performance. nguyen et al. [20] 2022 vietnamese speech • end-to-end • multi-task learning with the punctuation and uppercase (capu) recovery model • vibert: pretrained ner tagger • multi-task learning model with capu recovery for improved 5% f1 score wang et al. [17] 2023 chinese speech (cluener2020) • bert-bilstm-crf • the bio annotation method • the bert-bilstm-crf model offers superior performance in ner for controlled speech compared to traditional methods. liu et al. [30] 2023 chinese speech (aishell3-ner, cnerta, and msra) • proposes a multimodal chinese ner method called usaf (using synthesized acoustic features). • usaf uses synthesized acoustic features and a multi-head attention mechanism • usaf improves the performance of chinese-named entity recognition. • usaf outperforms the sota external-vocabulary-based method on two datasets olatunji et al. [21] 2023 afrispeech-200 dataset • multilingual pre-training, data augmentation, fine-tuning on african accents. • addressed problem as distribution shifts to mitigate model bias. • the baseline model shows a significant decrease in performance on samples with african-named entities. • fine-tuned models demonstrate an 81.5% relative wer improvement on samples with african-named entities. despite the valuable insights yielded by this bibliometric analysis, several inherent limitations warrant careful consideration for further investigations. firstly, the exclusive reliance on the scopus database, although recognized for its extensive coverage, and reliability, commonly used in bibliometric analysis, presents a significant limitation. this might be attributed to the relevant research indexed in other academic databases, such as ieee xplore, web of science or google scholar may be omitted, and therefore can result in a partial and biased view of the research landscape. this limitation is particularly critical in rapidly evolving fields like ner and asr, where innovative work may appear in varied sources not included in scopus. additionally, bibliometric methods primarily focus on quantitative metrics such as citation counts, publication trends, and co-author networks. this approach, while useful for identifying general trends, can overlook crucial qualitative aspects of research, such as the novelty of findings, methodological rigor, and practical applications. 236 advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 as a result, important but less cited contributions, often from niche or emerging research, may be underrepresented. another limitation is temporal analysis. by focusing on a specific period, the study may not adequately reflect the historical development of the field or recent advances that have not yet accumulated a significant number of citations. this time lag can lead to outdated conclusions, especially in dynamic areas where knowledge evolves quickly. the dominance of citation metrics also poses problems. by favoring well-established research areas and highly cited articles, this approach may overlook innovative but less visible studies. this trend is accentuated by the under-representation of research published in languages other than english or from less academically visible regions, which can distort the overall perspective of research activities. finally, bibliometric analysis, by highlighting collaboration patterns and prominent researchers, can overshadow the contributions of lesser-known researchers or institutions producing high-quality work. lack of ongoing monitoring and integration of diverse data sources is essential to maintaining a current and comprehensive understanding of the research landscape, particularly in rapidly evolving areas like ner and asr. in general, while bibliometrics provides robust tools for analyzing research trends, it is essential to acknowledge its limitations. implementing more in-depth content analysis methods, such as systematic reviews, and integrating qualitative approaches and data from multiple sources is particularly necessary. these steps, especially when conducted regularly, are critical for obtaining a more accurate and comprehensive understanding of the studied field. 4. conclusions in this work, biblioshiny and vosviewer have been used to conduct a quantitative analysis of scientific publications related to ner–asr systems, published in the scopus-indexed database before 2024. the analysis revealed stable growth in the field, with notable publication spikes in 2013 and 2022. key findings include identifying countries with the highest number of publications and significant international collaborations, highlighting the diversity and global nature of ner–asr research. most publications were found in prominent conference and workshop proceedings, which are known as major forums for disseminating research in this domain. the study also underscored the impact of advanced deep learning models, including bert and its variants, which have significantly improved the accuracy of ner systems by enabling the adaptation of pretrained models. the findings provide a comprehensive overview of the research landscape in ner for asr, offering valuable insights into publication trends, the scientific impact of various contributions, and the network of international collaborations. based on the analysis, several promising research directions have been proposed including the integration of multimodal data to enhance ner systems by combining audio, text, and visual data; cross-lingual ner for asr to develop models that can effectively handle multiple languages and dialects; real-time ner in asr with purpose improve the efficiency and speed of ner systems to enable real-time applications; domain-specific ner purpose to tailor ner systems to specific domains such as healthcare, finance, or legal sectors, and contextual adaptation to enhance ner accuracy by adapting to the context of the conversation. future investigations will aim to integrate data from multiple database sources to provide more comprehensive analyses and expand the scope of data extraction, such as language, document type, etc. to enhance the accuracy and reliability of bibliometric analyses for the continuous development of ner–asr systems. conflicts of interest the authors declare no conflict of interest. advances in technology innovation, vol. 9, no. 3, 2024, pp. 224-238 237 references [1] g. attardi, g. berardi, s. dei rossi, and m. simi, “the tanl tagger for named entity recognition on transcribed broadcast news at evalita 2011,” evaluation of natural language and speech tool for italian, vol. 7689, pp. 116-125, 2013. 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[30] y. liu, s. huang, r. li, n. yan, and z. du, “usaf: multimodal chinese named entity recognition using synthesized acoustic features,” information processing & management, vol. 60, no. 3, article no. 103290, may 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx eco-pave: paving blocks originating from construction waste arief sabdo yuwono, sayyidah qothrun nafisah, yulia sukma supriatna, kevin audryc herditya* department of civil and environmental engineering, ipb university, bogor, indonesia received 15 june 20xx; received in revised form 05 august 20xx; accepted 10 september 20xx abstract construction waste is a significant contributor to global solid waste, underscoring the need for effective sustainable management strategies. this study aims to assess the quality and environmental impact of paving blocks manufactured from two different sizes of recycled aggregates. two categories, ca1 (12.5–4.75 mm) and ca2 (37.5– 4.75 mm), were used as constituent materials. the paving blocks were assessed based on compressive strength, water absorption, and wear resistance. experimental results indicate that paving blocks incorporating ca2 recycled aggregates performed better than those with ca1. the tested paving blocks meet grade d standards for garden paving (ca1) and grade c standards for pedestrian pathways (ca2). additionally, utilizing recycled aggregates from concrete waste enables 48.1% rubble recycling and reduces carbon dioxide emissions by 64.7%, thereby contributing to sustainable waste management. keywords: construction waste, recycled aggregates, paving blocks, ecological impact 1. introduction construction waste is a significant global issue, with construction and demolition (cdw) debris contributing substantially to total solid waste generation. in 2012, approximately 3 million tons of construction waste were produced across 40 countries [1]. according to lopez-ruiz et al. [2], cdw accounts for 30% to 40% of global solid waste. the rapid increase in waste generation is closely aligned with population growth and is expected to continue rising significantly in the future [3]. southeast asia has experienced significant population growth, reaching 650 million people in 2020, with more than half of the population residing in urban areas. in terms of the construction industry’s value, the construction and demolition waste generation ratio in southeast asia ranks below that of china but surpasses other developed nations [4]. construction and demolition waste (cdw) in southeast asia has received limited attention. weak law enforcement, combined with a shortage of disposal sites, has led to the illegal dumping of cdw. consequently, a significant portion of cdw is either disposed of in landfills or dumped illegally, resulting in land scarcity and environmental degradation. if left unaddressed, this issue will escalate, posing more significant risks such as pollution and ecosystem disruption [4-5]. liu et al. [6] highlighted that waste management behavior plays a crucial role in determining the effectiveness of cdw handling. therefore, adopting more sustainable waste management strategies is essential for improving recycling efficiency and minimizing environmental impact. given that construction debris holds significant potential for reuse [7], implementing recycling efforts can significantly reduce construction waste while promoting sustainable development. one method to repurpose this waste is by recycling building debris into aggregates, which may be used in concrete mixtures [8]. zang et al. [9] conducted a study on recycled coarse aggregate from waste bricks in concrete mixtures. the recycled aggregate was used as 0%, 30%, 40%, and 50% by weight replacements of the natural aggregate. their research found * corresponding author. e-mail address: kevinaudryc137@gmail.com advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 2 that recycled aggregates from waste bricks have high water absorption, which leads to a reduction in compressive strength. however, they also discovered that using up to 30% recycled coarse aggregate from waste bricks in concrete mixtures can still meet the required strength standards. conversely, opara et al. [10] established that high-quality recycled coarse aggregate can substitute natural coarse aggregate in concrete production. a comparative analysis of experimental results of some properties of concrete produced with 100% recycled coarse aggregate and 100% natural coarse aggregate is presented in this paper. recycled aggregate exhibited 7%–10% lower bulk density and 30%–40% lower compressive strength than natural aggregate. however, the 28-day recycled aggregate met the standards, making it suitable for non-structural applications such as pavements and lightly loaded structures. the study conducted by wang et al. [11] demonstrated that natural coarse aggregates can be replaced with recycled coarse aggregates for paving blocks. the recycled aggregate was used as 20%, 40%, 60%, 80%, and 100% by weight of the total coarse aggregate content. the results show that recycled aggregate for paving blocks can achieve up to 60% replacement, resulting in optimal compressive strength and water absorption that meet quality standards. various studies have demonstrated that recycled aggregates can be used in concrete production, often with different mixtures of recycled and natural aggregates. although previous research has explored the use of recycled aggregates in concrete and paving blocks [9-11], there are still limitations in the research on how variations in recycled aggregate size affect the quality of paving blocks, including compressive strength, abrasion resistance, and water absorption. in addition, most previous research has primarily focused on the mechanical or technical aspects of paving blocks. however, evaluations of their environmental impact, such as construction waste reduction and co₂ emissions through the life cycle analysis (lca) approach, remain limited. therefore, this study aims to evaluate the mechanical performance of paving blocks that involve two variations of recycled aggregate sizes and assess their environmental impact based on waste reduction and the lca approach. 2. materials and methods this study focused on the use of recycled coarse aggregate obtained from rubble waste, manually crushed and sieved to the desired sizes. determining the physical properties and size distribution of these materials is crucial for optimizing the mix design and ensuring the quality of the paving blocks produced. the information presented in this section forms the foundation for evaluating the mechanical performance and environmental impact of the paving blocks. 2.1. material the materials utilized in this experiment include pcc (portland composite cement), recycled coarse aggregate, and fine aggregate. the recycled coarse aggregates were classified into two categories based on their particle size range: ca1 (12.5– 4.75 mm) and ca2 (37.5–4.75 mm). all recycled coarse aggregates were derived from rubble waste collected from jl. gardu dalam, margajaya, west bogor district, bogor city, indonesia. the rubble utilized for this investigation is depicted in fig. 1. the recycled coarse aggregates were manually manufactured by hammer crushing and subsequently sieved to meet the specified size category. the physical parameters of these coarse aggregates are presented in table 1, and their size distribution is shown in fig. 2. the fine aggregate was sourced from cimangkok, sukabumi, indonesia, with its physical parameters detailed in table 2, and its size distribution is shown in fig. 3. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 3 fig. 1 unprocessed rubble waste table 1 physical characteristics of recycled coarse aggregates no parameter ca1 ca2 standard code value 1 size range (mm) 12.5–4.75 37.5–4.75 2 fineness modulus 6.05 5.01 sii.0052-80 6.0–7.1 3 water content (%) 6.67 5.58 4 mud content (%) 0.23 0.80 sii.0052-80 ≤ 1 5 apparent specific gravity 2.47 2.27 6 water absorption (%) 19.51 14.97 fig. 2 size distribution of recycled coarse aggregates table 2 physical characteristics of fine aggregate no parameter value standard code value 1 size range (mm) 4.75–0.075 2 fineness modulus 2.69 sii.0052-80 1.5–3.8 3 water content (%) 11.13 4 mud content (%) 7.12 sii.0052-80 ≤ 5 5 organic content (organic plate number) 2 sni 2814:2014 ≤ 3 6 specific gravity 2.30 7 water absorption (%) 3.52 advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 4 fig. 3 size distribution of fine aggregate 2.2. proportion of mixture the mix proportions in this experiment were obtained through trial and error, with the option of making adjustments based on observed results. the mix proportion was designed to assign recycled coarse aggregates as a complete replacement for natural virgin aggregates. the ideal combination of cement, fine aggregates, recycled coarse aggregates, and water was discovered through trial and error to be 1.1:2.2:0.6:0.2 by weight. the water content was decided to be roughly 20% of the cement weight. this ratio was intended for a single paving block measuring 20 cm × 10 cm × 8 cm and weighing around 4 kg. as a result, one unit of paving block requires 1.1 kg of cement, 2.2 kg of fine aggregates, 0.6 kg of recycled coarse aggregates, and 0.2 kg of water. this amount also ensures ideal workability when mixing and improves the aesthetic quality after mold removal. the iterative technique enables fine-tuning to meet both practical and performance objectives, making the blend appropriate for its intended application. 2.3. preparation of samples the fabrication of paving block test specimens adheres to indonesian national standards, with dimensions of 20 cm, 10 cm, and 8 cm for each specimen. a total of 24 test specimens were produced, categorized into three segments for the evaluation of compressive strength, wear resistance, and water absorption. the process of employing concrete waste as coarse aggregates for paver block production commences with the collection of intact building concrete debris. fig. 4 paving block samples this study utilized two varieties of concrete waste aggregate, designated as ca1 and ca2, based on the treatment applied. concrete waste for ca1 is crushed to a maximum size of less than one-fifth of the shortest dimension of the mold, with aggregate sizes ranging from 12.5 to 4.75 mm. concrete waste for ca2 is crushed to a maximum size of less than half the shortest dimension of the mold, with aggregate sizes ranging from 37.5 to 4.75 mm. the subsequent labor process adheres to a mixed design produced using several molding techniques. given the disparity in aggregate size, in ca1, the aggregate is promptly included in the blend of other components, subsequently placed into a mold, and compacted incrementally. in ca2, advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 5 the aggregate is not combined with other mixtures; instead, it is incrementally introduced, initially occupying all voids in the mold, followed by gradual compaction until it is filled. the produced samples are depicted in fig. 4. 2.4. testing procedure paving blocks undergo a curing period of 28 days following the standards outlined in sni 03-0691-1996. the curing process involves fully submerging the paving slabs in water. upon completion of the curing period, to ascertain quality, tests for compressive strength, water absorption, and wear resistance are conducted on the paving blocks following the standard reference sni 03-0691-1996 pertaining to concrete bricks (paving blocks). the quality of paving stones, depending on their physical attributes, is presented following sni 03-0691-1996 in table 3. table 3 paving block grading standard [12] grade compressive strength (mpa) weir resistance (mm/min) maximum water absorption (%) usage average min. average min. a 40 35 0.09 0.103 3 road b 20 17 0.13 0.149 6 parking place c 15 12.5 0.16 0.184 8 pedestrian pavement d 10 8.5 0.219 0.251 10 garden or park path compressive strength testing necessitates a test specimen measuring 8 cm × 8 cm × 8 cm in cubic form, according to the dimensions of the test sample. the compressive strength of the paver stone can be determined by: compressive strength p a = (1) where 𝑃 is the maximum compressive load (n), and 𝐴 is the cross-sectional area (mm2). wear resistance testing necessitates a test specimen of 5 cm × 5 cm × 2 cm in a square configuration. the examination was performed under sni 03-1974-1990, which cites sni 03-0028-1987 for cement tile methodologies [12-13]. the wear resistance value of the paver block can be determined by: 10 wear resistance g d a t   =   (2) where ∆g is the mass loss (g), 𝐷 is the density of the specimen, 𝐴 is the wear cross-sectional area, and 𝑡 is the wear time. the water absorption test necessitates a fully immersed test specimen that has been saturated in water for roughly 24 hours. subsequently, it is desiccated in the oven for approximately 24 hours. the water absorption value of the paver block can be determined by: water absorption 100 ( m d ) % d − =  (3) where 𝑀 is the saturated mass of the paving block, and 𝐷 is the dry mass of the paving block. each test was conducted for both recycled coarse aggregate types, ca1 and ca2. every kind of recycled coarse aggregate was provided with three samples for each test. the final results for all tests were then averaged from those three samples according to their type. the average value of each recycled coarse aggregate from all tests was then compared to one another and used to determine the grade of the paving block based on sni 03-0691-1996. all of these test data are presented in tables 4, 5, and 6. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 6 table 4 compressive strength test data no parameter value ca1 ca2 1 2 3 1 2 3 1 length (mm) 89.81 84.05 81.79 82.76 82.81 83.72 2 width (mm) 87.07 81.24 81.62 81.67 81.01 81.17 3 surface area (mm2) 7819.76 6828.22 6674.06 6841.77 6708.44 6795.55 4 maximum load (n) 107584.00 96955.02 30743.92 48518.16 160983.60 110072.00 5 compressive strength (mpa) 13.71 14.15 4.59 7.07 23.91 16.14 average compressive strength (mpa) 10.81 15.70 standard deviation ±5.40 ±8.43 table 5 wear resistance test data no parameter value ca1 ca2 1 2 3 1 2 3 1 mass (g) 10.288 10.243 10.251 10.277 10.313 10.576 2 volume (ml) 4.4 4.4 4.6 4.3 4.5 4.6 3 density (g/ml) 2.34 2.33 2.23 2.39 2.29 2.3 4 length (cm) 4.998 5.372 5.232 5.344 5.303 5.17 5 width (cm) 4.911 5.042 5.066 5.265 5.143 5.163 6 surface area (cm2) 24.545 27.086 26.505 28.136 27.273 26.693 7 mass before test (g) 93.07 101.36 90.33 95.38 93.2 88.54 8 mass after test (g) 89.96 99.2 89.51 93.35 92.55 88.12 9 mass loss (g) 3.11 2.16 0.82 2.03 0.65 0.42 10 wear time (minutes) 5 5 5 5 5 5 11 wear resistance (mm/minute) 0.1084 0.0685 0.0278 0.0604 0.0208 0.0137 average wear resistance (mm/minute) 0.0682 0.0316 standard deviation ±0.0403 ±0.0252 table 6 water absorption test data no parameter value ca1 ca2 1 2 3 1 2 3 1 saturated mass (g) 3550.50 3401.50 3226.50 3375.00 3325.00 3398.00 2 dry mass (g) 3158.50 2951.50 2710.00 3017.50 2821.00 2963.00 3 water absorption (%) 12.41 15.25 19.06 11.85 17.87 14.68 average water absorption (%) 15.57 14.80 standard deviation ±3.34 ±3.01 3. finding and analysis this section presents the results of an experiment evaluating the mechanical performance and ecological prospects of paving blocks made from recycled construction waste aggregates in two different particle size ranges. the analysis encompasses compressive strength, wear resistance, water absorption, and sustainability performance, with particular advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 7 emphasis on the percentage reduction of construction waste and an estimation of carbon dioxide (co2) emissions using life cycle assessment (lca) to assess environmental impacts. 3.1. compressive strength according to fig. 5, in the ca1 sample, the maximum compressive strength attained was 14.15 mpa, the minimum was 4.59 mpa, and the average compressive strength over the three samples was 10.81±5.40 mpa. in the ca2 sample, the maximum compressive strength recorded was 23.91 mpa, the minimum was 7.07 mpa, and the mean compressive strength of the three samples was 15.70±8.43 mpa. according to sni 03-0691-1996 [12], the average compressive strength of the ca1 sample categorizes it as a class d paving block, whereas the ca2 sample is classified as a class c paving block. a notable disparity exists between the two samples, possibly attributable to the human fabrication of the test specimens without the aid of a press machine, leading to inconsistencies in density and aggregate dispersion [14]. the aggregate size has a significant influence on compressive strength [15]. concrete using larger aggregates features more substantial and organized pores, which diminishes structural weaknesses and hence enhances the overall compressive strength of the material [16]. the findings of liu et al. [17] and wang et al. [18] align with the compressive strength of paving stones derived from the ca2 sample. when the ratio of recycled coarse aggregates in the recycled aggregates is significantly elevated, the cement mortar produced in the concrete is inadequate to encapsulate the interstices between the aggregate surfaces and the particles that occupy those voids [19]. consequently, the compressive strength of the paving block can be enhanced by integrating the proportion of recycled aggregates with virgin aggregates [18]. fig. 5 results of the compressive test 3.2. wear resistance wear resistance is contingent upon the surface layer of the test specimen, with its level of wear resistance being ascertained by the magnitude of the wear mark on the specimen’s surface resulting from friction. consequently, the deeper the wear mark on the specimen, the greater the volume of material extracted from the surface. as illustrated in fig. 6, the ca1 sample exhibited the highest wear resistance value of 0.0682±0.0403 mm/min, whereas the ca2 sample demonstrated a wear resistance value of 0.0316±0.0252 mm/min. gökalp and uz [20] assert that a broader variation of aggregate particle sizes often diminishes fragmentation resistance. moreover, wear resistance is affected by aggregate gradation. as demonstrated in fig. 2, the aggregate gradation for ca1 exhibits a continuous gradation, while the aggregate gradation for ca2 displays a gap gradient. the diminished abrasion resistance of the ca2 sample is due to its adequate compaction between the paste and aggregates, yielding a surface with minimum voids and dense packing, hence enhancing its resistance to friction-induced wear. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 8 fig. 6 results of the wear resistance test 3.3. water absorption water absorption is a metric that evaluates a paving block’s capacity to absorb water, influencing its strength, wear resistance, and longevity. the testing findings indicate that the water absorption value for the ca2 sample was 14.80±3.01%, and the ca1 sample exhibited a value of 15.57±3.34%, as illustrated in fig. 7. the absorption of water in concrete is associated with the pore structure within the cured concrete. furthermore, this study utilized recycled concrete waste material as the aggregate, which markedly affects the water absorption capacity of the paving block. increased porosity of the paving block correlates with reduced density and elevated water absorption [21]. the values obtained for water absorption in paving blocks do not conform to the sni 03-0691-1996 standard range of 3–10% [12]. in order to reduce the porosity of the paving block, fine aggregates can be added to the mixture. moreover, applying methods such as accelerated carbonation and nano-silica (mineral slurry) coating can further reduce the porosity of the paving block [22]. owing to their elevated water absorption rates, these paving blocks are advised for application in garden areas that remain unsaturated. fig. 7 results of the water absorption test 3.4. ecological outlook this study gathered 16.777 kg of construction demolition waste, which was physically crushed for size modification. the cumulative weight of recycled aggregates utilized for 14 samples sieved to meet size specifications (12.5–4.75 mm for ca1 and 37.5–4.75 mm for ca2) was 8.064 kg. consequently, this study successfully recycled approximately 48.1% of the gathered construction and demolition waste. globally, approximately 0.509 gt of concrete and mortar trash is processed in demolition management, while 0.499 gt is disposed of as buried demolition waste [23]. this data reveals that merely 0.01 gt, or around 2%, of concrete and mortar debris is being salvaged from construction waste disposal. based on this research conclusion, it can be inferred that approximately 0.245 gt of concrete and mortar waste may be recovered from the construction waste disposal site. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 9 this study also considers the estimation of carbon dioxide (co2) emissions associated with the use of ca1, ca2, and virgin aggregates (va) in the manufacturing of paving blocks through a life cycle analysis methodology. the functional unit employed in the life cycle study is 1 m² of pavement utilizing 0.21, 0.10, and 0.08 m paving blocks with a 2 mm interstice between the blocks. this functional unit necessitates around 45 blocks, which demand 25.92 kg of aggregates. the evaluated phase is from cradle to site. table 7 illustrates the life cycle of each aggregate type. table 7 life cycle of each aggregate type no stage of life ca1 ca2 va 1 construction demolition in the local area construction demolition in the local area quarry 2 transportation to aggregates size processing site transportation to aggregates size processing site transportation to processing plant 3 aggregates size processing aggregates size processing processing plant (size adjustment process) 4 transportation to the paving block production site transportation to the paving block production site transportation to paving the block production site 5 production of paving blocks (manual) production of paving blocks (manual) production of paving blocks (manual) this study is based on numerous assumptions to provide clarity and boundaries. the assumptions are as follows: (1) the paving block manufacturing facility is situated at ipb university in bogor regency, west java, indonesia. (2) the demolition site is located 20 kilometers from the production facility, and demolition is conducted using a semimechanical method with light machinery, specifically a jackhammer (input power: 1500 w) in reference to indonesian minister of public works and housing regulation number 28/prt/m/2016 [24]. (3) the source of virgin aggregates is situated in rumpin, bogor regency, west java, indonesia, approximately 20 kilometers from the production location. (4) the recycled aggregates processing site and the aggregates plant processing site are presumed to be situated equidistantly between the aggregates source and the production site, referring to the lca study of rahman et al. [25]. (5) the processing of virgin aggregate size is performed using conventional methods or technology [26], whereas the processing of recycled aggregate size is conducted using a jaw crusher (input power: 5500 w; output size: 10–40 mm; capacity: 1–5 metric tons per hour). (6) the vehicle utilized for aggregate transportation is a standard dump truck with a load capacity of 10 m³ and a diesel fuel consumption rate of 6 km/l. (7) only the influence of aggregates is considered in this research. it is thought that other components, like cement, sand, and water, exert a uniform influence across all aggregate types and can therefore be disregarded. (8) the computation of manual force for all aggregate types and electricity consumption for ca1 and ca2 adheres to sni 7269:2009 [27] and indonesian minister of public works and housing regulation number 28/prt/m/2016 [24], whereas the electricity consumption calculation for va relies on data published by gursel and ostertag [26]. (9) the computation of co₂ emissions relies on electricity and fuel usage, utilizing a co₂ emission factor of 890 g/kwh for electricity and 2.61 kg/l for diesel [28-29]. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 10 table 8 life cycle analysis result of each aggregate type item value per functional unit optimal choice ca1 ca2 va life phase 5 5 5 ca1, ca2, va manual force (kcal/hour) 1528 1528 1051 va electricity (kwh) 0.318 0.318 0.933 ca1 and ca2 fuel (l) 0.005 0.005 0.003 va co2 emission (g co2) 296.144 295.944 838.891 ca2 table 8 indicates that, overall, ca2 and va exhibit the most optimal performance, each being identified as the superior choice three times. although ca2 and va (along with ca1) are the optimal choices regarding the life phase, ca2 surpassed va in electricity consumption and co2 emissions, while va exceeded ca2 in manual force and fuel consumption. ca2 and ca1 exhibit identical electricity consumption values and display minimal variation in co2 emissions. significant value discrepancies exist between ca2 and va, indicating that one surpassed the other in specific ways. in terms of manual force, va surpassed ca1 and ca2 by decreasing manual force requirements by 40.9%. in terms of electricity consumption, ca2, together with ca1, surpassed va by decreasing electricity demand by 66.0%. the disparity in fuel usage between ca1 and ca2 with va is 36.8% due to the low density of ca1 and ca2, which requires a greater volume to comply with the required aggregate weight. in terms of co₂ emissions, ca2 surpassed va, achieving a 64.7% reduction in emissions. these findings indicate that ca2 far surpassed va in terms of environmental impact by decreasing electricity use and co₂ emissions. 4. conclusions this study has successfully utilized construction waste in the form of rubble waste as a substitute for coarse aggregate in paving blocks called eco-pave. two types of recycled aggregates, ca1 (12.5–4.75 mm) and ca2 (37.5–4.75 mm), were used. performance was evaluated through compressive strength, wear resistance, and water absorption tests, referring to sni 030691-1996. the environmental impacts were assessed by estimating construction waste and applying life cycle assessment (lca) for the cradle-to-site phase, which covers manual labor, electricity, fuel, and carbon dioxide (co2) emissions. the following conclusions can be drawn from the presented study: (1) the average compressive strength was 10.81±5.40 mpa for ca1 and 15.70±8.43 for ca2. based on sni 03-0691-1996, ca1 falls under class d, while ca2 qualifies as class c paving blocks. (2) the ca2 sample showed better wear resistance than ca1, with a lower wear rate of 0.0316±0.0252 mm/min versus 0.0682±0.0403 mm/min. both samples met the required standard. (3) both samples showed high water absorption, with ca2 at 14.80±3.01% and ca1 at 15.57±3.34%, exceeding standard limits. (4) based on the waste reduction, incorporating recycled aggregate as a coarse aggregate substitute in paving block production can recycle roughly 48.1% of the gathered construction and demolition waste. (5) based on the lca approach, paving blocks made from recycled concrete waste, especially ca2, are estimated to reduce co₂ emissions by up to 64.7% compared to va, while also consuming less electricity, making them more environmentally friendly options. paving blocks made with recycled aggregates from ca2 demonstrated better performance compared to those made with recycled aggregates from ca1. ca1 met the standard for garden paths, while ca2 met the standard for pedestrian pavement, except in areas prone to prolonged water submersion. in addition, recycling rubble waste has been proven to reduce the amount of construction waste and provide an efficient alternative to non-structural materials, such as paving blocks, contributing to advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 11 waste management and minimizing environmental impacts. future improvement may include blending virgin and recycled aggregates, adding fine aggregates, or applying methods such as accelerated carbonation and nano-silica (mineral slurry) coating to enhance mechanical performance. conflicts of interest the authors declare no conflict of interest. references [1] a. akhtar and a. k. sarmah, “construction and demolition waste generation and properties of recycled aggregate concrete: a global perspective,” journal of cleaner production, vol. 186, pp. 262-281, 2018. 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[29] g. sütheö and a. háry, “comparison of carbon-dioxide emissions of diesel and lng heavy-duty trucks in test track environment,” clean technologies, vol. 6, no. 4, pp. 1465-1479, 2024. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v9n1(2024)-aiti#12038(65-84).docx advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 english language proofreader: chih-wei chang challenges and solutions to criminal liability for the actions of robots and ai vladimír smejkal1,*, jindřich kodl2 1department of informatics, faculty of business and management, brno university of technology, brno, czech republic 2authorized expert of cryptology and information systems security, prague, czech republic received 20 april 2023; received in revised form 17 september 2023; accepted 23 september 2023 doi: https://doi.org/10.46604/aiti.2023.12038 abstract civil liability legislation is currently being developed, but little attention has been paid to the issue of criminal liability for the actions of robots. the study describes the generations of robots and points out the concerns about robots’ autonomy. the more autonomy robots obtain, the greater capacity they have for self-learning, yet the more difficulty in proving the failure foreseeability when designing and whether culpability or the elements of a specific crime can be considered. in this study, the tort liability depending on the category of robots is described, and the possible solutions are analyzed. it is shown that there is no need to introduce new criminal law constructions, but to focus on the process of proof. instead of changing the legal system, it is necessary to create the most detailed audit trail telling about the robot’s actions and surroundings or to have a digital twin of the robot. keywords: robot, criminal liability, audit trail, criminal evidence 1. introduction concerning robotization and the growing capabilities of robots, a novel phenomenon is emerging. it could be described as self-will, self-initiative, or the independent, autonomous decision-making of robotic systems, which deviates from the conservative position of non-thinking. modern robotic systems are more sophisticated, and mere mechanisms are fully subject to the will and instructions of humans. some robots currently find themselves in the new role of what is perhaps best described as a self-acting, i.e., autonomous, machine. this new aspect will undoubtedly be reflected in law. the authors, therefore, focus on the potential criminal liability for the unlawful consequences of robots’ actions and how to prove it. legislation on civil liability is currently in the works. however, scarce attention has been paid to issues of criminal liability for the actions of robots. in the european union (eu), for example, two pieces of eu legislation have been published which may impress the officials with the issue of liability for the actions of artificial intelligence (ai) in their entirety, i.e., the artificial intelligence act (ai act) and the ai liability directive. in reality, they only concerned with the strict liability of manufacturers for defective products, the rules for access to information, and the burden mitigation of proof concerning damage caused by ai. specifically, the ai act [1] provides for (a) harmonized rules for the placement on the market and ai systems service for their use in the eu; (b) a prohibition on certain ai practices; (c) scrupulous requirements for high-risk ai systems and obligations for operators. meanwhile, the ai liability directive [2] builds on the ai act, simplifying the legal process for victims to prove someone else’s fault caused the harm. * corresponding author. e-mail address: smejkal@znalci.cz advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 66 in the area of liability for damage caused by a product defect, i.e., in the area of civil liability, liability is conceived as an objective liability. if proven that the damage was caused by the injured party, or if it can be reasonably assumed considering all circumstances that the defect did not exist when placed on the market or occurred later, the obliged person has the possibility of liberation. in the area of criminal liability, it is unlikely to set out some form of strict liability in law because the basic principles of criminal liability include the criminality of the conduct, the consequence, and the causation between the conduct and the consequence, i.e., proving the culpability of a perpetrator or group of persons. this paper does not construct ai and robots as entities equipped with criminal liability but describes the possibilities of addressing it within traditional legal systems. the authors disagree with claims that ai could prove to be an exceptional opportunity to change law and legal theory [3-4]. the most common tort cases are likely to emerge from poor programming. this will certainly be true until robots reprogram themselves. attempts to hold manufacturers, programmers, and users on legal theories such as negligence or product liability under the criminal code predominate over the current level of “weak” ai, while the view of recognizing direct criminal liability for ai itself predominantly supports the “strong” ai in the future [5]. the difference between “strong” and “weak” ai is that “weak” ai aspires only to model the mind when solving partial and specialized problems, while “strong” ai is recognized as a universal model of human thinking in a software way, i.e., a replication of the human mind in a computer [6-7]. authors need to prepare for this future. however, in the authors’ opinion, it is neither by creating robots as fictitious persons endowed with legal responsibility, nor does it make sense given the purpose of punishment involving retribution, incapacitation, general deterrence, and rehabilitation of the offender [8], or even the death penalty [9]. once humans have decision-making authority over robots, they can simply deactivate or dismantle the robot. nevertheless, it does make sense for a person natural or legal who was responsible for the robot or found to be at fault. they see the introduction of corporate criminal liability, as it is conceived in many countries and has long historical roots, as an appropriate way forward [10-11]. these prosecuted legal persons may primarily be the manufacturer or operator of the robot with shared culpability, which is also an option [12]. in recent years, the use of robots has been rapidly expanding in various sectors. particularly, industrial production (welding, assembly, material handling, etc.), construction and maintenance of infrastructure, healthcare (robotic surgery and diagnostics), logistics and warehousing, transport (driving vehicles, autonomous vehicles, trains, or planes), agriculture, domestic and accommodation services, and the military (military robots). the increasing numbers and use raise the likelihood of incidents related to robots or their malfunctioning. the purpose of this study is to explore whether existing criminal law tools are sufficient to successfully address issues related to criminal liability for the actions of robots and ai without the need to create new constructs. 2. the term “robot” and categories of robots a broader perception of the term “robot” has emerged than before. in the 20th century, robots were perceived as devices performing physical work (the word “robot” was derived in 1921 by the czech writers čapek brothers from the word “robota” which means “work”). it was only much later that “software robots” implementing robotic process automation (rpa) emerged, which can be used for any process that is repetitive according to certain rules from sending emails based on certain criteria to high-frequency trading (hft). both types of robots can then be controlled using ai. the following text categorizes only robots in the classical sense, i.e., physically intervening in the environment, with special attention to autonomous vehicles. 2.1. definition of robot the technical nature of the robot is constantly evolving from simple manipulators to autonomous systems, where the robot can perform the intended tasks based on the current state and sensor data without human intervention, moving in its advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 67 environment, and performing the intended tasks while comprising a control system and control system interface. the robot’s actions must have either direct or indirect responses in the physical world (not necessarily by direct mechanical manipulation, but also by passing a command to another system having an interface to the physical world, e.g., water supply network control or road traffic control). software-only robots will be understood and classified as computer programs, which are not addressed in this paper. a robot, therefore, differs from information systems in its ability to directly interact with its environment physically. furthermore, for a long time, the term robot (except household robots) was largely understood as an “industrial robot”, even though the word “industrial,” i.e., a system designed to perform simple, typically repetitive mechanical operations, may now seem too finite as robots are making inroads into significantly “non-industrial” areas, such as medicine. robots can be fully or partially autonomous, or they can be remotely controlled (by a program in the cloud and/or by a human), often probably both in some predictable synergy. the degree of a robot’s autonomy is still being determined by the human, either a priori based on legislation or in a specific situation by the person in control, where the human operator is always part of the control loop of such a robot’s program. an example is the autopilot in an aircraft, in which, after setting certain conditions, the pilot hands over control of the aircraft, but oversees its operation and can intervene in this robot’s work at any time – correct its control of the aircraft, or switch it off completely. however, the conditions under which the pilot may hand over control of the aircraft to this system are defined in the aviation regulations and the aircraft manufacturer’s regulations by specific flight conditions. 2.2. generations of robots robots can be divided into five generations according to the level of their ability to make autonomous decisions: (1) the zero generation includes manipulators and robots usually without feedback, where any malfunctions or changes in the monitored areas (signaled by sensors) result in the next step being disallowed and the system being stopped (the socalled “central stop”) while the maintenance staff is called. (2) the first generation includes robots with simple feedback capable of switching between several deterministically operating subprograms (developed in advance by a human) and working. (3) the second generation includes robots with optimization capability, which is the ability to select the optimal program from predefined programs based on a specified criterion, i.e., the precise rule governing the decision about the next known action. (4) the third generation is characterized by robots capable of independently modifying the original program (action plan) with a posteriori knowledge. here, only the goal of the activity (task) is predefined, while the method of achieving the goal is left to the intelligence of the control system, which itself creates an action plan consisting of successive steps and activities to achieve the given goal. an action plan is a sequence of robots starting in an environment, described either numerically or symbolically – by logical statements that the robot interprets per se to achieve the defined global goal [13]. the formulation of the plan then consists of finding a way in the state space from the current state to the target state. (5) the fourth generation is represented by autonomous robots with social, human-like behavior, which means they choose the goals of individual tasks independently based on an appropriate global criterion, e.g., the principle of long-term existence/autonomy of such a system (survival, energy saving, etc.). since the third generation, determining the cause of undesirable behavior is likely to be a problem and any search for legal liability will have an unparalleled difficulty. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 68 more or less intelligent robots are becoming useful autonomous elements in complex industrial production sections. their ability to make independent decisions, and select the most appropriate tasks will increase, as their will upon autonomous reasoning [14]. there are alarming predictions that ai will reach human capabilities by 2029, and humans and machines will gradually converge, reaching the point called the singularity in 2045. it is often debated whether robots will eventually dominate humans to take full control, i.e., it’s estimated that kurzweil’s singularity will occur in 2045 [15]. similar catastrophic predictions have been published by renowned figures such as steven hawking, bill gates, and elon musk. in january 2015, they jointly signed an open letter on ai with other ai experts, and the letter was to call for research into the social impact of ai to prevent some potential “pitfalls” of ai, which is said to have the potential to eradicate disease and poverty, but scientists must not create something that cannot be controlled. the open letter entitled “research priorities for robust and beneficial artificial intelligence” details the research priorities in an accompanying 12-page document [16]. some authors insist that evolution will always be under human control. however, robots do not yet have the consciousness and self-awareness, which is a necessary precondition for taking over control and the estimated point of reaching the singularity because we are approaching 2045, continuing to be postponed in scientific works [17]. there is also the question as to whether robots will ever become self-aware because the necessary prerequisites are the natural emotions of machines, the ability to be aware of their position in the world models, legal and moral rules, power/priorities, as well as communication-based on these models with other robots in the community, especially to plan actions towards a certain goal that the robots themselves have set [18]. unless humans enable robots to set their own goals or activate themselves, the singularity is expected not to happen at all [19]. nonetheless, the existing third-generation robots may already pose a problem. 2.3. self-driving cars some evident examples of semi-autonomous robots except autopilots are so-called autonomous (self-driving) vehicles. as the decisions are left to the robot’s control system, we will be more interested in: (a) setting the decision algorithms so that their operation or failure does not violate life, health, or property. according to the authors, the tentatively correct solution is to set priorities corresponding to a human driver. nevertheless, it varies especially with a cooperative strategy. moreover, in this context, it is indispensable to mention the principle of necessity an act that would otherwise be a criminal offense is not a criminal offense if a person commits such an act to avert an imminent threat to an interest protected by criminal law. (b) the ability of the driver to take control of the vehicle whenever needed. in other words, a pilot can switch off or “override” the autopilot. (c) the degree of protection of the control system against negative influences from the environment, either intentional (hacking) or unintentional (electromagnetic interference or operational failure), external mechanical influences (coming from the environment in which the vehicle is moving), and mechanical interference (by third parties), starting with maintenance work or an attack on the vehicle as a movable asset, which the control system should also be able to approach or warn at least. (d) self-documentation capabilities, the ability to create an audit trail of the vehicle’s operation (similar to the existence of “black boxes” in aircraft), are required. further development is expected to lead to a cooperative strategy that will further optimize the behavior of such systems working in a group (group intelligence), which will be applied by individual autonomous vehicles among themselves – the socalled “cooperative driving.” real-time vehicle-to-vehicle (v2v) and vehicle-to-traffic infrastructure communication will improve the information available to each road user. this will make almost any active involvement of the driver unnecessary and undesirable in many cases. the point is that cooperation between vehicles, or between vehicles and their environment, can advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 69 incur the perplexity of information for the drivers to process in real-time. automated driving will therefore be effective where the driver would no longer be able to process the massive information provided in the required time, and even following the recommendations would be insufficient. the driver will thus be de facto (not de jure) useless except the situations where the driver must be able to return the vehicle to its original, less complex mode and to take over the control if, for example, the cooperating network collapses (e.g., due to a lightning strike). 3. liability for the robot’s actions to search for who is responsible for a crime committed concerning the use of a robot, we must apply the peculiarities of the robotic world to classical schemes of criminal responsibility, especially when resulting in the involvement of ai. initially explicit, deterministic processes can change into unpredictable and non-deterministic processes. it is therefore necessary to discuss whether the traditional principles of criminal law will hold up under the new conditions. 3.1. a new dimension of liability the new dimension of liability will be based on the presence of a relatively simple line of action and consequence concerning potential liability for perhaps all machines and equipment falling under the zero, first, and second generation that has been used hitherto. whether it is the design or manufacture of these machines, which starts with a project where parameters are always verifiable. therefore, the relatively simple way of subsequent checks is whether any important fact has been omitted in the design. the same applies to the manufacturing process assuming that the design is flawless on the material, the question is whether this process was followed or whether, for some reason, a deviation emerged, which may be related to the ensuing unlawful consequence. the next stage is the actual use of the final product. the utilization is regulated by law if it has complexity and the potential to harm. typically, this applies to all means of transport where the legislation explicitly provides the means of transport can be operated on public roads. in other cases, only liability for any unlawful consequences is regulated, such as liability for damage caused by an operational activity. in addition, many technical regulations and technical standards defining product characteristics are rendered. however, the question lies in the obligation to apply, whether the presence or absence of regulations and standards. despite the propriety because of the duty to take preventive measures, it will be up for discussion here. nonetheless, it is no longer the case with thirdand fourth-generation robots. meanwhile, the regulation of the use, possible liability for damage, and harm resulting from robot failure will be substantial. in the case of a consequence contrary to the purpose and intent of the machine or device, the behavior and its compliance with the law, possible fault as a subjective element of a possible criminal offense, and the causal relationship between this behavior and the consequence could be analyzed, however, several questions will arise as: to what extent this failure could have been foreseen in the design of the robot, whether any act occurred at this stage or perhaps during the manufacture, which could be causally linked to the consequence and thus whether it is possible to establish fault or the elements of a particular criminal offense were accomplished. nevertheless, it will always be necessary to consider the absence of determining beyond doubt the resulting behavior under all possible circumstances in the simple case of a deterministic behavior given the random (unexpected) input signals and data (observations of the surrounding world). it creates a considerable space for technical and legal analyses focused on the foreseeability of errors in the design and programming of the robot, the prevention with appropriate modifications, and the category of force majeure. 3.2. tort liability in robotics presumably, the existence and mass use of robots after the third generation will not change the basic paradigm. if the main or sole cause of injury is the failure of a machine, it is important from a criminal law perspective whether or not the advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 70 failure is based on fault. it is well known that civil law also recognizes a strict liability for a consequence, but that is not what is at the focus of the analysis. it is necessary to analyze what can be regarded as “fault” within the meaning of the criminal code, i.e., the involved fault and is the moment an event that has occurred through no fault of any individual or a legal person, for instance, a failure or an accident happened through nobody’s fault but an unfortunate coincidence. this bipolar scheme of fault vs. mischance could certainly apply to robots, insofar as we simplify the problem, disregard the actions of persons not criminally liable, and introduce actions in circumstances that preclude criminal liability (for instance, tolerable risk). but the problem lies in the distinction, which is onerous to determine a robot’s autonomy and the ability to learn or self-program. specifically, learning is simply setting the parameters of a fixed system, situation classifier, neural network, production system, etc., whereas self-programming can significantly modify the decision-making principles influencing a robot’s actions. (a) undoubtedly, robots or robotic systems performing identically repetitive operations under controlled external conditions (typically industrial, assembly robots/manipulators) have been employed for many years. manipulators on a production line, unless someone directly steps into their operation field, are virtually harmless concerning the arguments below. (b) some robots operate in environments with variable external circumstances, i.e., environments with uncertainty. these circumstances include the possibility of a collision with a human, another robot, or some other movable or immovable asset. typically, these are robotic cars, various autonomous mobile logistics robots, etc. nevertheless, these are predefined and predictable robots despite the broad operating range. in other words, everything operable has been programmed by humans. (c) autonomous systems, self-learning robots, intelligent robots, hybrid robots, etc., are complex devices. meanwhile, they are sometimes regarded as a combination of a “living” (biological structure) and “non-living” component, whose reactions and procedures are unpredictable due to self-programming within this self-learning framework or the adoption of behavior patterns on a person or a group of persons. however, as the degree of autonomy increases, we know less about the “intracerebral” situation of such a device or the state before a certain incident. the limit of criminal liability for all three categories is the definition of negligence in section 16 criminal code of the czech republic, law no. 40/2009 coll: (1) a crime is committed by negligence if the perpetrator (a) knew they could violate or endanger an interest protected by the criminal code in the manner specified in this code but relied without reasonable grounds on not causing such violation or endangerment, or (b) was unaware their conduct may cause such violation or endangerment, although they should and could have been aware of this because of both overall and personal circumstances. (2) a crime is committed by gross negligence if the perpetrator’s attitude towards the requirement of due caution shows a manifest disregard for the interests protected by the criminal code. if intent, gross negligence, and wilful negligence are excluded. it is relatively easy to determine for category (a) machines what the person operating the robot should have been known despite the alleged ignorance due to the feasibility of predicting what can be expected from the robot. the situation is more complicated for category (b). here, it may be difficult to establish what the person operating the robot should have known for their actions to be considered as a fault in the form of conscious negligence. for example, to what extent can the driver rely on the system controlled by active radar to stop his car in front of an obstacle when it normally does so, and this is clearly stated in the instructions? moreover, postulating the car is equipped with a fault indicator for the system, is reliance on the system a valid reason not to have your foot on the brake when the car approaches an obstacle? or, what is even more dangerous, when someone suddenly steps into the road? advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 71 the use of virtually autonomous robots as discussed in category (c) will pose even greater problems. for this group, it will presumably be difficult to prove intent. for example, if a “thinking” robot builds another robot instead of lifting loads and loading the person operating the robot and loads into a crusher. it will be the technical cause of the robot’s failure primarily investigated. on the other hand, however, similarly to any other industrial accident, it will also be necessary to investigate whether the operator or the manufacturer (of the original robot) implemented possible prevention of such failure. preventing a “thinking” robot from producing a defective product instead of a functional robot is a typical example, which in turn means finding out what the “thinking” robot produced and, more importantly, why. generally, there are two types of liability: liability under the civil code and liability under the criminal code. meanwhile, liability for misdemeanors and administrative offenses related to robots can also be added. for criminal liability, there is the requirement of intentional fault unless the criminal code expressly provides sufficient negligent fault. concerning intent, a distinction is made between direct and oblique intent, where the perpetrator is cognizant of unlawful consequences or understanding (the understanding also means the perpetrator accepts or reconciles himself to the fact that he may violate or endanger an interest protected by law as described in the criminal law). it will be relevant whether the potential perpetrator has been obliged to behave in a certain way by law, specific regulations, or even internal rules when operating the robot. in the context of robots, these may generally be such regulations as the labour code in the area of occupational health and safety, the protection of public utilities, or the eu regulations on medical devices as indicated in regulation (eu) 2017/745. moreover, whether the person has acted intentionally or negligently in breach of their duties, which may be qualified as intention, negligence, or omission. in this context, the ruling of the supreme court of the czech republic on 12 october 2017, file ref. 6 tdo 1062/2017-28 seems to be relevant: “a breach of an important duty within the meaning of section 143(2) of the criminal code cannot be understood as a breach of any regulation, but only of such duty laid down therein, where a breach of such duty usually leads to a threat to life and health of humans, if such a consequence can easily occur and often does occur due to such breach. in assessing whether a duty is an important duty, the key criterion is to consider the consequences of breaching a particular duty and the likelihood of those consequences occurring. for an omission to amount to an act, it must be the omission of a specific duty arising from the specific position of the wrongdoer, that is a situation in which society expects and relies on the actions of the specific person. first of all, the person who has a specific duty to act must be in a specific relationship to the interest protected by law. if this specific duty to act cannot be inferred from the position of the wrongdoer, the act as a condition for criminal liability is absent.” it is in contrast to the consideration of reasonable or tolerable risk. even in everyday life, we cannot avoid situations in which the occurrence of harm cannot be entirely excluded. therefore, it is necessary to consider in each case to what extent the occurrence of a harmful consequence could have been foreseen in the first place and what measures have been or could have been taken to minimize any harmful consequences. according to section 31(2) of the criminal code of the czech republic, there is no tolerable risk if an activity endangers the life or health of a person without their consent with the activity being given following other legal regulations, or if the result seeks to achieve is manifestly disproportionate to the level of risk, or if the performance of the activity is contrary to the requirements of other legislation, the public interest, principles of humanity or good morals. the assumptions will thus be based on the statement above to ensure a robot is understood as a system. in addition to the purely mechanical components enabling the robot to do something, the robot mainly consists of computer hardware and software. despite not being biologically alive, it is capable of self-learning through experience and interaction and autonomous thanks to sensors or data exchange with the environment. beyond that, it can adapt its actions and activities to the environment. in other words, the robot’s external behavior is determined by the primary internal configuration (the initial program developed advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 72 by humans). on the other hand, with the subsequent modification of this program by the robot, various steps were presented as parameterization, creation of a database of patterns (models, heuristics), and at a higher level by the modification of the initial neural network based on the aforementioned interactions with the environment, i.e., what is closest to the human concept of “learning.” in such a case, it may be extremely difficult to establish a causal link between the failure of the robot and the actions of manufacturers and programmers. it is only after this causal link has been established (proven) beyond any doubt that the potential fault of an individual or a legal person can be examined regarding potential criminal liability. 3.3. negligent fault in robotics it can be assumed that negligent crimes will predominate in robotics, although the “reprogramming” of a robot into a “killer” cannot be ruled out. concerning criminal negligence, two basic categories of perpetrators must be distinguished. the first group includes perpetrators knowing their conduct (omission) could cause harmful consequences but relying without reasonable grounds on not causing such consequences. the second group includes perpetrators not knowing their conduct (omission) could cause harmful consequences, in which case the condition for criminal liability is the fact that they should or could have known this by considering the circumstances and personal situation (in particular their education, profession, position held, etc.). given the desire of perpetrators to make quick money is endless, it is possible to envisage offenses committed with gross negligence concerning robots when the perpetrator’s attitude towards the requirement of due caution shows a manifest disregard for the interests protected by criminal law. without a volition element (for criminal negligence), the law defines negligent fault through an intellectual component. regarding conscious negligence, the perpetrator is cognizant of the possibility of the relevant criminal consequence. on the other hand, as for unconscious negligence, the perpetrator is not cognizant of this possibility. the criterion of negligence is the exercise of the required degree of caution, which could be either general (required of everyone) or specific, or higher (for instance, in the performance of certain activities or professions) – see e.g., award of the constitutional court of the czech republic of 31 may 2016, file ref. iii. ús 2065/15-2 or ruling of the supreme court of the czech republic of 27 june 2012, file ref. 5 tdo 540/2012. the term “the required degree of caution” emerges here. this is a vague legal concept with a wide range of possible interpretations. the determination of the required (minimum) degree of caution could be sought in specific regulations such as technical regulations, technical standards, or the generally accepted rules resulting from the level of knowledge in a particular field as shown in the ruling of the supreme court of the czech republic of 30 january 2014, file ref. 6 tdo 1450/2013 concerning reasonable caution. based on the antecedent statements, something similar is defined as the state of the art in the inventions and improvements act, which comprises everything made available to the public using a written or oral description before the date from which the applicant is entitled to claim priority. if a robot commits an unlawful act due to the outdated design, the situation is similar to a non-lege artis medical practice. 3.4. causality in robotics as mentioned above, it will undoubtedly be difficult to establish and appropriately prove the causal link between the behavior and consequence. in medico-legal disputes, where the initial input and the outcomes are known, the actual course is entirely unclear, and the presence of the so-called black box phenomenon has emerged [20]. predominantly, it is about fault (usually unconscious negligence) and the predictability of the outcome. the causal link is usually undisputed unless there are multiple factors at work. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 73 if a robot of the third and especially the fourth category (as described above) fails significantly, finding a causal chain will often be a major problem with an uncertain outcome. here we may not always know all the factors having influenced the functioning of an autonomous mechanism. we may know its initial settings (or what they should have been if there had been no design or manufacturing error), but the question is whether we can find out all the information that influenced the robot’s operation. besides, although currently, it is still easier to do than to find out all the processes taking place in the human body, the examination of the “black box” may not be successful or even feasible under certain circumstances (in the case of a biorobot) if we consider it to be the robot’s hardware and software. another problem may be potentially multicausal, i.e., there may be concurrent causes or accumulation of several possible causes from adversity or unlawful event, from which it will be necessary to select one cause as the decisive cause in the given case. this may be the simultaneous combination of input data (i.e., the robot’s environment), the program that evaluates the data, and hardware (e.g., a mechanical hand) that performs the movement that gives rise to the unlawful act. one possibility might be to express the percentage rates of these influences if possible. in this regard, it seems appropriate to quote the ruling of the czech supreme court of 27 february 2002, file ref. 3 tz 317/2001, according to the statement “the causal link between the act of the perpetrator and the consequence is not broken if, in addition to the act of the perpetrator, there is another fact which contributes to the occurrence of the consequence, but the act of the perpetrator constitutes the fact without which the consequence would not have occurred.” an example would be a robot’s motion controller not anticipating that the robot’s arm might go into a certain position simply because it is programmed to exclude that position. if someone forces the robot’s arm into such a position, thereby affecting the functionality and safety of the robot in such a way that it subsequently moves the arm into a different and unpredictable position causing injury, the programmers cannot be held responsible because this effect would not have occurred in the first place without the intervention in question. given that, the authors can conclude one of the main requirements for robots: the maximum creation of an audit trail telling about every step the robot has taken and its internal state. fig. 1 factors influencing the behavior of self-learning robots [own picture of the authors] advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 74 fig. 1 shows all the factors that can affect the current version of the robot control program. the initial design of the robot and its setup originates with the developer and manufacturer. an empty programming tool (e.g., a neural network) learns based on the knowledge and patterns chosen by the manufacturer, but the user or the ai itself may also be involved. the behavior of the ai system is not only dependent on the outcome of the learning process but also the robot’s environment (sensor information) including the behavior of other robots (e.g., in autonomous cars). the specific state of the system can therefore change expeditiously. 3.5. robot software and tort liability one of the main problems with robotics is the current unavailability of software with a guarantee of reliability and invulnerability. the well-known murphy’s laws of programming state attest that “there is no program that is completely free of bugs, and that each time you remove a bug, you introduce another, hidden and more insidious bug into the program. this means that it is not possible to create a program that is completely free of bugs. any software product will always contain some bugs.” an example leading to criminal liability could be a programming error with a certain combination of parameters (e.g., the position of the robot, its arm, load, etc.), causing an unpredictable state or behavior that can impact the environment, e.g., a mechanical attack on surrounding objects. similar cases are known from the past in the field of space exploration, where rockets or satellites had to be destroyed due to software errors (sometimes directly in the program logic, sometimes due to a “simple” typing error). primarily, it seems possible to consider the liability of the author(s) of the program, who in the least “did not know that their conduct was likely to cause such an infringement or endangerment, although they should and could have known it, having regard to the circumstances and their situation.” this brings us back to the question of fault. in this respect, the constitutional court’s ruling is relevant according to the statement “the limits of the circumstances that the perpetrator can or cannot foresee cannot be defined only hypothetically (for then everyone would have to foresee essentially everything), but must always be based on the existing objective circumstances resulting from a particular life situation, which can be characterized by a variety of factors that the perpetrator perceives with his senses and can then evaluate them according to his knowledge and other subjective dispositions. in terms of negligent fault (section 5 of the criminal code), this means that, in addition to the degree of caution required by the general rules of safe conduct, there is also a subjective component, which consists of the degree of caution that the perpetrator can exercise in a particular case. there can only be fault by negligence when, at the same time, duty and the possibility of foreseeing an injury or threat to an interest protected by criminal law are present [21].” however, the question is whether it was within human power to foresee the occurrence of such coincidence (e.g., in the input data) to which the software should have been able to respond. there may be various causes for robots’ unpredictable behavior, ranging from hardware defects to software bugs. common causes include: (1) hardware defects: robots are made up of sensors, actuators, and control systems, which can fail and cause unpredictable behavior. (2) software bugs: robots rely on complex software systems, and bugs in the code can cause unexpected behavior. (3) incorrectly calibrated sensors: if the robot’s sensors are not correctly calibrated, it can lead to incorrect readings and unpredictable behavior. (4) environmental interference: robots can be affected by external factors such as electromagnetic interference, which can cause unpredictable behavior. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 75 (5) insufficient testing: if a robot has not been thoroughly tested, it may behave unpredictably in real-world scenarios. the quality of testing is the key to minimizing the risk. it is appropriate to proceed by decomposing the system components into individual functionalities that can be described by simple finite automata whose behavior can be comprehensively analyzed to a large extent. to address unpredictable robot behavior, it is important to diagnose the root cause through thorough testing and debugging. in some cases, hardware components may need to be replaced, and commonly the software may need to be updated or completely rewritten as well. in this respect, it is probably appropriate to start from the principle of “required (necessary, reasonable) degree of caution,” which should be embedded in the principle of “secure by design” by the robot manufacturer, which means that the designed product (which could be understood as the whole robot or just its software) is designed to be secure from the very beginning of its development and in all its stages [22]. the problem is that neither the hardware nor the software can be completely free of all errors with 100% probability. additionally, by the requirement for reliability of communication with a system reliability of 99.9999%, the downtime of a robot can be 31.5 seconds, which is incredibly long! most texts dealing with safety and information systems or robots emphasize that a necessary step to increase safety and thus reduce the probability of an operational accident and possible subsequent liability is the existence of a risk management system as shown in iso/iec 20000 it service management. when assessing specific cases, it will likely be a question of fact and subsequently of law, as to whether the risk was normal or extraordinary, predictable or unpredictable, and what measures were taken to minimize it. whether the risk was tolerable is primarily a matter for the court. however, when assessing risk in robotics, it is very likely that not only the current state of knowledge will have to be considered, but in the event of a leapfrog change in technology, which is beyond the scope of that state of knowledge, leading an entirely new situation will have to be assessed. if a risk analysis has been carried out covering all foreseeable harmful situations, if the risk of an activity causing harm has been ruled out, and if it is clear that the intended (and legal) goal cannot be achieved in any other way, then it is admissible to move on to actions involving elements of risk and consequently compliance with these conditions which should be considered when assessing the circumstances precluding the unlawfulness. the specific examples that possibly happen will vary depending on the degree of autonomy of the robot and other circumstances. there may be an error in the program that makes the robot’s actions not only unauthorized but also a threat to an interest protected by the criminal code. such an error is unlikely impossible, but the error and functionality of a safety mechanism stopping the robot before the incident will be crucial. one of the criteria for assessing potential liability is whether functional testing has been performed before starting the manufacture of a robot. 3.6. other factors affecting robots’ operation it is necessary to point out other factors affecting robots’ actions. every program works with data, while some can be entered as constants by the manufacturer, variables by the user, and collected by the robot itself through sensors. therefore, even if the program is working perfectly, the robot may act incorrectly in an unauthorized way, and it will probably be easy to find out what has happened only in the first two cases. if a given case involves the effects of external factors whether unintentional or intentional, we will depend on the possibility of analyzing the processes inside the robot. this is typically true of self-learning robots, which are autonomous systems that can improve their performance over time based on experience, trial, and error. their behavior can be explained using basic algorithms and models that enable them to process data, making decisions, and learn experientially. they are sophisticated systems that can adapt and improve over time, which enables them to perform increasingly complex tasks and respond to changing circumstances in real-world environments. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 76 one common approach to self-learning in robots is reinforcement learning, which is a type of machine learning involving an agent (robot) performing actions in the environment to maximize a reward signal. the robot learns through trial and error and takes actions possibly leading to a higher reward and improving its overall performance over time. another approach to self-learning in robots is unsupervised learning, which means that the robot analyses large amounts of data and discovers patterns or relationships on its own without explicit instructions or labeled data. it facilitates the robot learning about its environment and predicting future events. in both cases, the behavior of self-learning robots is determined by their algorithms and the data (datasets) on which they have been trained. the quality of their decisions and the speed at which they learn depend on factors such as the complexity of their models, the amount of data to which they have been exposed, and the quality of the algorithms used to process that data. the behavior of these robots is determined by a combination of several factors, including: (1) sensors: self-learning robots typically use various sensors to sense their environment such as cameras, microphones, and touch sensors. these sensors feed data to the robot’s learning algorithms, which use this information to make decisions and perform tasks. (2) algorithms: the behavior of self-learning robots is determined by algorithms controlling their decision-making process. these algorithms may include artificial neural networks, reinforcement learning, evolutionary algorithms, etc. (3) goals and tasks: self-learning robots are designed to meet specific goals and perform tasks. for example, a self-driving car may be designed to navigate roads safely and avoid collisions, while a service robot may be designed to help people with various tasks. the robot’s behavior is customized by these goals and tasks, as well as its algorithms and sensory inputs. (4) experience: as the self-learning robot interacts with its environment and performs tasks, it collects data and gains experience to improve its future performance. for example, a self-driving car can learn to better navigate roads after encountering challenging driving scenarios. in summary, the behavior of self-learning robots is a complex interplay of their sensors, algorithms, goals, tasks, and experience. a robot may also behave contrary to its intended purpose or programming due to an internal defect (hardware error, but more likely software error) or an external factor, while both may or may not be relevant concerning a third party’s fault. unintentional influence can occur through a combination of external signals picked up by the robot’s misevaluated sensors as a result of an incident. a question of assessment lies in whether the situation was both unforeseen and unforeseeable to such an extent of not having been predicted by the manufacturer. if the analysis excludes that it is not an unpredicted and unforeseeable situation and the failure of the robot emerged due to reasons per se (defect in design, program, etc.), the situation should be assumed predictable to cause partially or completely by an external influence including the intervention of another person. if a human factor is found to be such an influence, it will need to be addressed (in addition to finding the particular person) the issue of intent versus negligence. one can imagine the negligent action of someone who inadvertently or entails another activity changes the physical configuration of a robot that begins to move along a different path. in the case of intent, this may be an external attack where the attacker attempts to influence the processes taking place within the robot enough to change its functions or functioning and subsequently cause an incident. the person who can influence the robot to act to endanger an interest protected by the criminal code can be anyone: the owner (user, operator, etc.) who (wilfully or unwilfully) enters incorrect data into the robot – then it will probably be about assessing possible negligent conduct in an unlawful act, but perhaps even about assessing whether the elements of the criminal offense of “damage to a record in a computer system and on an information carrier and negligent interference with computer equipment” advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 77 have been accomplished. in the case of another third party (a hacker) who can attack the program that controls the robot (but of course also the data) to make the robot do something not under its intended purpose, the situation is clearer, i.e., this will constitute a misuse of a thing (using the robot as an object or instrument of a criminal offense). as part of the assessment of a particular case, it will be necessary to determine which of the robot’s actions can be considered the result of the negligent (or intentional) conduct of an individual. in the case of zero to second-generation robots, the robot can be perceived as a deterministic automaton (da), where all its states are known detectable or inferable, i.e., it is clear at any point of robots’ actions and rationales chronologically. for the third generation of robots, where we already admit the robot’s ability to independently create a program experientially, the situation is already more complex because this gives the robot the character of a non-deterministic automaton (nda), where it can reach a certain state through multiple paths states simultaneously. possibly by the theory of computer science, we will be able to convert an nda into a da and establish the reasons for the robot’s behavior. nonetheless, it is not universally applicable. at the outset, such a robot will always have the same initial state, but once it has been trained, it will depend on many independent factors as the internal state diverges after an incident. the original instruction set and dataset used would leave the robot as a deterministic mechanism without further learning (training) of the model. nevertheless, the application of different behavioral patterns with different outcomes will translate into the robot’s architecture differently each time, depending on the patterns and models used. in the fourth generation, when we talk about autonomous mechanisms having their intelligence, the algorithmic complexity (variability) inside the robot will be incredibly high that it cannot be ruled out that it will be impossible to determine the exact events and rationales inside from a certain point in time. ai tools such as neural networks or fuzzy logic, evolutionary programming, and genetic programming, are moving us from a world where we can tell the causation to a probabilistic one. this is a probabilistic prediction, where no one can guarantee that a given system will evolve and behave as predicted. then we get into the area referred to as np-hard problems, where it will be necessary to look for approximate or partial solutions giving a satisfactory answer at least in some cases. it is a question, however, whether this approach is applicable in finding criminal evidence. owners (operators) of robots whose actions may endanger the safety of the public in a malfunction (due to their weight, nature of the operation, etc.) or whose operation may be labeled as “particularly dangerous,” which may also be held criminally liable for any accident caused by the robot. their tort liability for negligent conduct may be at least twofold: (1) they have acted contrary to the manufacturer’s instructions (manual), e.g., overloading the robot instead of performing proper maintenance. (2) they failed to exercise the required degree of caution given the characteristics of the robot. in this context, it is also possible to mention the potential liability of the robot owner in the failure to perform the mandatory software update released by the manufacturer. švestka and smejkal dealt with a similar issue much earlier concerning the updates of antivirus software. “in the case of computers, there is no legal obligation for their operators to use antivirus software, let alone to update it. however, even if we were to admit this, which of course could only be done by way of law (we note, though, that this is a vision that is difficult to imagine), then the determination of the liability for damage must rest on proof beyond reasonable doubt that the owner (operator, user), or which one of them, has committed the specific misconduct. if a hacker gains access to a computer and subsequently causes damage to another party – whether directly or by using someone else’s computer – it will be very difficult to prove in practice whether the fault can be attributed to the manufacturer of the operating system, to an application program purchased by the user, or whether the misuse of the computer was caused by neglecting to update a “protection” program, etc [23].” advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 78 the authors believe this is still true for a robot. however, it could happen that the obligation to update the software would be stipulated in the contract or the technical conditions for the use of the robot, i.e., in documents binding on the owner. the owner would probably be liable for the damage caused under civil liability and such conduct could also be considered negligence, perhaps even gross negligence from a criminal point of view. 3.7. legal persons as potential perpetrators of robotic crimes for completeness, it is also necessary to mention the potential criminal liability of legal persons. this liability arises from the fact that not only an unlawful act committed in the interests of a legal person or the course of its business activities by persons such as managers but also employees or persons in a similar position, may be attributed to the legal person. however, even if an unlawful act committed by the above persons can be attributed to a legal person, the legal person may still be released from criminal liability if he has made all the efforts that could reasonably prevent the commission of the unlawful act by its managers or employees. this construction is also decisive in the assessment of whether the legal person is liable for the unlawful consequence of the robot’s actions. regarding the accidents caused by robots, the foremost question will be whether the liability of an individual for the accident can be established, or whether criminal liability is involved as the case may be. however, it should be noted that it may not always be a question of finding a specific individual or specific individual identified as having committed an unlawful act attributable to a legal person. consequently, the criminal liability of the legal person is not affected. thus, the mechanism for establishing criminal liability of a legal person for an accident caused by a robot is more complex because it does not end with the identification of the liable individual but continues with the assessment of whether the individual acted in circumstances in which their unlawful act is attributable to the legal person. if the answer is affirmative, it only remains to consider whether the legal person has exempted himself from criminal liability by considering the efforts to prevent the commission of the unlawful act by the persons. the problem of robots was brought back to the question of the extent of potential foreseeability of a robot’s reaction in a certain situation and the extent of the liability to be inferred for lack of relevant foresight. it is imaginable that the criminal liability of a legal person, a manufacturer of a third or fourth-generation robot, and the employees did not foresee the robot’s harmful behavior due to the insufficient understanding of the robots’ design. and the legal person, their employer, failed to address this professional deficiency. more loftily, the legal person as a manufacturer may have been technically capable of creating a monster but was unable to oversee the capability of this monster. 4. prevention and evidence actions of both robots that will act directly, i.e., causing mechanical movements, and robots that will act only based on information such as robots trading on the stock market to consequently be capable of manifesting as negative or directly contrary to the law. two problems emerge as follows: (1) how to prevent or at least minimize the likelihood that such actions will occur? – prevention. (2) how to establish the reasons leading to the negative actions including the liability of a particular individual or legal person? – evidence. the situation will be quite different for deterministic robots, where it is possible to justify any time why the robot acted as it did. if the contents of its memory are available, the computer program and data will be located despite the absent possibility to predict in advance in many cases what values the data will take. in other than deterministic processes, i.e., where the robot itself decides how to react to the stimulus, the situation will be more complex. in these cases, there will be a wide range of possibilities, from the simplest systems to the most complex self-learning ones, which will be able to modify their code based on processes that cannot be predicted to a greater or lesser extent. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 79 4.1. prevention the problem referred to in point 1 above will need to be addressed by a risk analysis exploring all the possible states that the robot can get into and try to set up defense mechanisms to prevent negative actions from occurring. the higher level of autonomy of the system cooperating with other systems is a typical example for autonomous vehicles. undoubtedly, we have reached a point where the level of protective measures may prevent the full use of the system. minimizing the risks associated with the robot’s operation involves a multi-step process, which includes the following: (1) risk assessment: the first step is to assess the potential risks associated with the robot’s operation. this involves identifying the types of hazards the robot may encounter with the potential consequences of these hazards. this may include simulations, testing, and other methods to evaluate the safety of the robot in different scenarios. (2) safety design: the design of the robot should include safety features minimizing the risk of harm to humans, animals, and the environment. for example, if the robot is designed to work near humans, it should be trained to respond appropriately to sudden movements or other unexpected events. this may include physical barriers to prevent the robot from coming into contact with people or other objects, sensors to detect potential hazards, and emergency stop buttons to quickly shut down the robot during an emergency. robots should be operated in a controlled environment and be subject to strict operating procedures to minimize the risk of accidents. (3) secure communication: robots should use secure protocols for communication, such as encrypted communication channels to prevent unauthorized access or tampering with control and data transmission. (4) authentication and authorization: robots should have mechanisms to securely authenticate the identity of users and devices to control access to sensitive data and functions based on roles and permissions. (5) data protection: robots should have built-in mechanisms to protect sensitive data, such as encryption and secure storage to prevent unauthorized access or theft of data. (6) software security: robots should be developed using secure software development practices such as code reviews and security testing to avoid vulnerabilities and security flaws in the software. (7) physical security: robots should be designed to be physically secure, e.g., by tamper-proof covers. (8) testing and verification: robots should be thoroughly tested and verified to ensure the intended function and proper safety features. this may include testing the robot in different scenarios and environments to identify potential risks. (9) training and learning: users should be trained and instructed on how to operate the robot safely and effectively. this may include instructions on how to use safety features and what to do in an emergency. (10) monitoring and maintenance: regular monitoring and maintenance of the robot is important to ensure its continued safe and efficient operation. this may include checking the robot’s sensors and safety features, updating software and firmware, and replacing worn or damaged parts. (11) incident reporting and response: incidents involving robots should be reported and investigated to determine the cause and prevention of similar incidents in the future. a plan should be responded to potential incidents including procedures for emergency shutdown, evacuation, and medical assistance. following these steps will help minimize the risks associated with operating the robot and ensure the safety of animals, and the environment. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 80 4.2. evidence regarding point 2, this is a question of obtaining enough information to determine the behavioral rationale. it means collecting a huge amount of data is not dissimilar to collecting data in the so-called black boxes found in airplanes at least in the form of monitoring the robot’s last moments of operation. however, even this may not provide a clear answer to the question of who is to blame for the robot’s negative actions, especially in cases where the robot will be interacting with the environment. it is important to note that sometimes the cause of the actions may be due to a combination of factors and require a combination of the above approaches to fully understand and resolve the problem. typically, an autonomous vehicle is surrounded by a very heterogeneous environment consisting of other vehicles, other entities, and objects located in the environment, but it will also receive information from a variety of sources, ranging from cooperating vehicles and traffic control-related signals. however, meanwhile, these can be false signals, ranging from exterior interfering signals of unintentional origin to intentional attacks. fig. 2 information about the incident applicable to criminal proceedings [own picture of the authors] fig. 2 illustrates a description of the pre-trial criminal procedure, which consists of securing clues about the robot’s activities. the activities include the analysis of technical documentation, the interview with witnesses, documenting the crime scene, the examination of evidence to resolve any inconsistencies, the evaluation of both individual and collective evidence, and finally the assessment of someone’s possible culpability. 4.3. digital twins a new phenomenon that has emerged in connection with industry 4.0 is called “digital twins,” where each physical element has its virtual representation, where its behavior and interactions with the environment are simulated by a software module. “a digital twin is a virtual version of a physical entity, whether product, factory, or some other type of asset or system. the digital twin unites business, contextual, and sensor data to represent the physical object [24].” software modules, representing physical elements in a virtual space, collaboratively solve tasks, coordinate their activities, and make decisions using services they provide to each other or call up through the internet of services (ios). the concept originated in products and then in machines and entire production lines [25]. according to the research report named digital twins in smart cities and urban modelling by analyst firm abi research, digital twins will become a substantial tool in city modeling and optimizing the operation of smart cities [26]. conceivably, digital twins could be used to analyze the causes of a delinquent robot’s actions, whereby individual variants could be modeled to determine the most likely course of action. furthermore, virtualization could also be used to digitally recreate the event. advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 81 fig. 3 digital twins [27] fig. 3 illustrates the properties of a digital twin as a software representation of a physical asset. it enables us to model all possible states of the robot in the framework of prediction and analyze the behavior of the robot based on sensed variables in real operation. in a previous article, it was written that “the first corpse doesn’t count.” in other words, it cannot be blamed on the manufacturer who is likely to be the main entity liable for the robot’s actions due to the impossibility to foresee all states, situations, and influences. black swans will always exist. on the other hand, if that manufacturer does not learn from all previous experience, i.e., if it fails to take into account the current state of knowledge of science and technology, then it could be liable at least for negligence. 5. results and discussion from this perspective, the bottom line is that the robot either (a) operates in a predicted and desirable way, i.e., it operates correctly. (b) operates in a predicted but undesirable way, i.e., it operates incorrectly. (c) operates unpredictably. in the cases referred to in (b) and (c), it is critical whether damage or non-material harm is caused in this way. if so, it is important from a criminal law perspective whether an interest protected by criminal law has been violated in the antecedent manner and, if so, who is liable for this. in the case of the predicted undesirable operation of a robot, it is critical to know how such undesirable behavior occurred, whether it was predictable, and why measures were not taken to eliminate such operation. in the case of unpredicted robot operation, the same determinants will need to be examined, i.e., whether measures were taken to prevent or minimize the undesirable and unpredicted operation. generally, liability for illegal or criminal acts by robots or ai systems is a complex issue that has not yet been fully resolved by the legal system. in some cases, the manufacturer of the robot may be liable if it is proven that the robot was defectively designed or manufactured. in other cases, the owner of the robot may be liable if the robot has been used illegally such as having been programmed to commit criminal offenses. however, there may also be the factor that the programming advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 82 or data used to train the ui system, i.e., the programmer or data provider could also be held liable. meanwhile, the liability of regulatory authorities cannot be ruled out either due to the absence of clear regulations or technical standards for the manufacture and/or safe use of the robot, while regulatory authorities may be held liable for failing to properly supervise the technology. ultimately, considering both general and specific circumstances, the design and capabilities, and applicable laws and regulations, liability for the actions of robots is likely to be determined on a case-by-case basis. however, as robots become more advanced and autonomous, it becomes increasingly difficult to determine who should be primarily liable for their actions. in article 12, the european parliament resolution on 16 february 2017 [28] states that: “it should always be possible to supply the rationale behind any decision taken with the aid of ai that can have a substantive impact on one or more persons’ lives.” the european parliament “considers that it must always be possible to reduce the ai system’s computations to a form comprehensible by humans with considering that advanced robots should be equipped with a ‘black box’ which records data on every transaction carried out by the machine including the logic that contributed to its decisions.” the problem will be whether the neural brains are artificially or biologically equipped in truly advanced robots. as a result, we will be able to translate all the robot’s decisions into a comprehensible form and the fully identifiable logic of its decisions. the black box originating from the aviation and containing all the necessary information can serve as an audit trail representing significant if not being the main or only evidence in determining the place, robot’s state, and the causation of the incident. given that, one can conclude the question posed at the beginning of this article: was it an intentional fault, negligence, accident, or a unforeseeable event – a black swan [29]? there is a need for preparations in both the area of legal theory and practice reflected in the legislation and decisionmaking practice, the area of technology reflected in the elaboration of standards and the creation of “best practices,” and in the area of criminology reflected in the emergence of new practices or sub-areas within the field of criminology. the application of methodologies and tools such as big data, ai, and digital twins could increase recall and thus help reduce entropy in specific robot-related crime investigations. 6. conclusion this article highlights that in the area of liability for damage caused by a defective product, i.e., civil liability, liability is conceived as a strict liability with the possibility of releasing the obliged party from liability if the damage caused by the injured party is proven or if it’s reasonably assumable. considering all the circumstances, the defect did not exist while being released or later. in the area of criminal liability, it would probably be impossible to set some form of strict liability in law since the basic principles of criminal liability include the criminality of an act, while the consequence caused and the causal link are set between the act and its consequence, i.e., proving the fault of a particular perpetrator or group of persons. as long as ai and robots do not possess human characteristics (consciousness, subjective experience, emotions, motivation, will, creativity, social interaction, morality, and ethics), it is premature and unnecessary to create artificial legal constructs to sanction the wrongful actions of robots and ai. as the analysis shows, the appropriate solution is to apply the existing principles of criminal liability for the actions of legal persons manufacturers, owners, and/or users of robots. to solve the problem of imputability of liability, it is necessary to focus on providing evidence in the form of the most detailed audit trail telling about the actions of the robot and its surroundings, or having digital biplanes of higher generation robots. the current state of robotics and ai does not require any other legal solution. in the authors’ opinion, the current possibilities of criminal law are sufficient to punish the unlawful actions of robots where the principles of civil law are insufficient. inventing new social constructs consisting of punishing robots as such is impossible due to the dependence of being created by an owner, operator, or other responsible person. in the future, the advances in technology innovation, vol. 9, no. 1, 2024, pp. 65-84 83 paradigm shift that other authors talk about would only make sense if robots were revolutionized as a separate entity with more power than humanity. subsequently, the question is whether robots would create their legislation, hostile to humans. however, these considerations, in the authors’ view, are not on the agenda at all. the purpose of this paper is to stress that as much as possible, and the focus should be on providing leads, collecting evidence, and implementing the principle of imputability within existing criminal law. future research in combating robot-related crime should combine technical, ethical, legal, and social aspects of this issue. it should also contribute to the development of effective measures to combat robot-related crime and ensure the safety of citizens. meanwhile, four insights have emerge from the authors’ perspectives. first, the behavioral identification of new threats and patterns is associated with robots within different sectors. second, the analysis of risks and the proposal of measures are implemented to increase the technological safety of robots and autonomous systems. third, the search for tools to analyze the behavior of self-learning robots is deployed in specific situations (incidents). last, the investigation concerning the current possibilities of legal systems allow permitting of the implementation of criminal prosecution is deployed to propose new procedures and facts in this area. consideration should be given to whether existing legal instruments are sufficient or whether changes are needed. acknowledgment the authors would like to thank mr. libor preucil, ph. d., head of intelligent and mobile robotics & center for advanced field robotics, czech institute of informatics, robotics and cybernetics of the czech technical university in prague, for his valuable consultation. conflicts of interest the authors declare no conflict of interest. references [1] proposal for a regulation of the european parliament and of the council laying down harmonised rules on artificial intelligence (artificial intelligence act) and amending certain union legislative acts, european commission, com/2021/206 final, 2021. 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[29] n. n. taleb, the black swan: the impact of the highly improbable, new york: random house, 2008. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v8n3(2023)-aiti#11169(163-176).docx advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 english language proofreader: chih-wen teng swarm intelligence algorithm based on plant root system in 1d biomedical signal feature engineering to improve classification accuracy rui gong1,2,*, kazunori hase2 1organization of liberal arts education, mejiro university, tokyo, japan 2faculty of systems design, tokyo metropolitan university, tokyo, japan received 13 november 2022; received in revised form 02 february 2023; accepted 16 february 2023 doi: https://doi.org/10.46604/aiti.2023.11169 abstract the classification accuracy of one-dimensional (1d) biomedical signals is limited due to the lack of independence of the extracted features. to address this shortcoming, the study applies a swarm intelligence algorithm based on plant root systems (prss) to feature engineering. some basic features of 1d biomedical signals are integrated into a digitized soil, and a root matrix is generated from this digitized soil and the prs algorithm. the prs features are extracted from the root matrix and used to classify the basic features. following classification with the same biomedical signals and classifier, the accuracy of the added prs set is generally higher than that of the base set. the result shows that the proposed algorithm can expand the application of 1d biomedical signals to include more biomedical signals in classification tasks for clinical diagnosis. keywords: one-dimensional biomedical signal, feature engineering, plant root system algorithm, swarm intelligence 1. introduction one-dimensional (1d) biomedical signals are widely used in the medical field and are crucial for clinical diagnosis and treatment. electrocardiograms (ecgs) are commonly used to diagnose heart-related diseases, and electroencephalograms (eegs) are used to determine sleep quality or mental state [1]. electrical-based biomedical signals perform well, and magnetic, vibration, and acoustic-based biomedical signals are popularly used in clinical applications [2-3]. however, with increasingly shorter sampling intervals and longer signal lengths, analyzing 1d biomedical signals without the assistance of a computer has become a research limitation. machine learning classification is a cutting-edge computer-assisted 1d technique for analyzing biomedical signals [4]. supervised classification is a machine-learning technique that helps doctors improve diagnostic accuracy by training classifiers with features of biomedical signals [5]. this technique is effective for complex and large datasets, and a well-designed classifier training model combined with high-quality dataset features frequently generates unexpectedly good outcomes. however, feature extraction methods are not as versatile as model building; thus, related research has received less attention. traditional and classical methods are often used for the extraction of 1d biomedical signals. the curve length of the signal in the time domain and the total spectral power in the frequency domain are common classification features of ecg signals [6]. meanwhile, shannon entropy is utilized as a classification feature of electromyography (emg) signals in clinical settings [7]. * corresponding author. e-mail address: r.gong@mejiro.ac.jp advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 164 although these features may seem adequate, the naive bayes classifier, which is the basis of machine learning theory, requires each condition to be independent during the classification process. in other words, features of biomedical signals extracted from classical feature engineering techniques should not be correlated [8]. this independence between features is undoubtedly challenging to achieve because both timeand frequency-domain features can always be connected by certain operations and their inverse. therefore, new features with strong independence are needed to characterize 1d biomedical signals. after investigation, it was found that swarm intelligence computing might solve the above challenges. when a feature is extracted using swarm intelligence, the new feature has a distinguishing independence because each member of the swarm participates in making the choice. moreover, the operations and transformations of the choice process are irreversible. the ant colony algorithm is a popular swarm intelligence algorithm, while the bee colony algorithm has been developed based on the swarming and social nature of bees [9]. currently, dozens of swarm intelligence algorithms have been applied to feature selection [10]. however, they are all based on social animals, and the independence of extracted features is still lacking. therefore, this study focuses on “social plants.” the root systems of plants are complex enough to form group intelligence as well. holker et al. [11] hypothesized that the root system of plants is a type of swarm intelligence system. the root apices communicate with each other through electrical signals or chemical pheromones and build a massive “brain-like” system underground. within such a complex root system, independent roots acquire water and nutrients through cooperation. to support proper growth and development, the root system competes with other root systems, beginning a “war” when it has an advantage and retreating when it is at a disadvantage [11]. a swarm intelligence algorithm based on a plant root system (prs) is proposed and applied to feature engineering in this study. specifically, the proposed prs approach imitates the growth of plant roots, in which the root apices cooperate to absorb as much of the sustaining nutrients as possible. in the proposed approach, the base features used by the selected machine learning model to classify biomedical signals are equivalent to the nutrients in digitized soil. these base features are obtained using common feature extraction methods. the sum of the nutrients absorbed during growth also serves as the first auxiliary feature, and the growth area of the root system is the second auxiliary feature. these auxiliary features are referred to as auxiliary prs features. during model training, the most significant advantage of the prs features based on swarm intelligence is that they are ideally independent (with a low correlation with the other features) and highly correlated with the dependent variable. the independence of the prs features is derived from the brain-like structure of the root system, where the co-determination of the root tips reduces the correlation with the base features. as an advantage, prs auxiliary features of biomedical signals are obtained from the proposed algorithm. after appending these features to the training set, the correlation between the features decreases and leads to reduced bias and variance and improved accuracy in machine learning classification. most importantly, the prs algorithm is universally applicable for the feature engineering of most 1d biomedical signals. this technology also enables 1d biomedical signals to become more competitive in the clinical field by improving the accuracy of machine learning classification. 2. method 2.1. extraction of base features the growth of natural plants requires suitable soil; similarly, the extraction of prs features requires digitized soil (a feature matrix) composed of base features. when extracting base features, time-domain features are generally preferred over frequency-domain and nonlinear features. time-domain features are more reliable than nonlinear features for involving a lower computational burden for nonstationary 1d biomedical signals. [12]. moreover, time-domain features are more dependable than frequency-domain features because they avoid the risk of spectral leakage caused by signal decomposition [13]. advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 165 time-domain feature selection is essential for base feature extraction. the number of features needs to be carefully considered: a small number of features limits the growth of the root system, while a large number of features may adversely affect classifier performance [14]. for the base features, this study selected 12 features that have relatively low computational complexity and have been successfully used for classification [15-16]. the definitions of the base features are listed in table 1, which �� represents the 1d biomedical signal in the segment �̅, n is the length of the signal, and �̅ is the average value of ��. table 1 time-domain features base feature definition standard deviation (std) 2 1 1 1 1 std n n i i i i x x n n= = = −  variance of signal (var) 2 1 1 var 1 n n n x n = = −  root mean square (rms) 2 1 1 rms n n n x n = =  skewness (skw) ( ) ( ) 3 2 3 2 1 1 1 1 skw n n n n n n x x x x n n= =   = − −      kurtosis (kurt) ( ) ( ) 2 4 2 1 1 1 1 kurt = =   = − × −      n n n n n n x x x x n n mean absolute value (mav) 1 1 mav n n n x n = =  zero crossing (zc) ( ) 1 1 1 1 zc sgn threshold n n n n n n x x x x − + + = =  × ∩ − ≥   slope sign change (ssc) ( ) ( ){ } ( ) 1 1 1 2 1, if threshold ssc , 0, otherwise − − + = ≥ = − × − =      n n n n n n x f x x x x f x willison amplitude (wamp) ( ) ( ) 1 1 1 1, if threshold wamp , 0, otherwise − + = ≥ = − =    n n n n x f x x f x simple sign integral (ssi) 2 1 ssi n n n x = = nonlinear energy (nle) ( ) ( ) ( ) ( ) 1 2 2 1 nle 1 1 2 − = = − − + −  n n n n n i x x i x i x i n waveform length (wl) 1 1 1 wl n n n n x x − + = = − among the 12 features comprising the base features set, the statistical features are the most basic, including var, std, rms, skw, kurt, and the mav, which is similar to the average rectified value. three features related to frequency are also included: zc, i.e., the amplitude value of a signal that crosses the zero-amplitude axis; ssc, i.e., the frequency of a signal within the time domain; and the wamp, i.e., the sum difference between the signal amplitudes for two adjacent samples. the last three features indicate energy and complexity: ssi represents signal segment energy, nle approximates signal amplitude energy, and wl measures signal complexity. these twelve base features collectively represent a 1d biomedical signal series. the new features derived from these representative values closely approximate the actual measurement values. 2.2. feature sorting for the development of a root system, the site where the seed is planted requires nutritious soil. in this study, the base features were modeled based on the distribution of nutrients. each element ��,� of the base feature set ��×�〈 〉 must be sorted. first, the dataset must be normalized using a scaling technique during the preprocessing stage to eliminate scale advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 166 differences among various elements while sorting. min-max normalization was used to scale the data within the range [0,1] and maintain the relationships that existed among the original data [17]. the min-max normalization based on the feature set ���×�〈 〉 can be expressed as: , min max min m n m n b b b b × −   =  −  ɺ β (1) where n = 1, 2, …, 12 and m = 1, 2, …, the length of ��. feature importance measurements can reduce the initial number of features by eliminating those features with a low importance score and improving classifier performance [18]. in this study, the features were sorted based on their worth. to score a feature’s worth, the information associated with the feature was used. features with higher scores were those closest to the center location. information gain was first input into a decision tree and used to rank the priority of feature nodes; this was then expanded and applied to importance measurement. assuming the class label of a feature has two distinct values that define binary classes �c1,c2�. info��� �, also known as the entropy of ���×�〈 〉, can be defined as ( ) ( ) ( )1 2 1 2 2 2 info log logb p p p p= − −ɺ (2) where �� , �� are the nonzero probabilities that an arbitrary tuple ���×�〈 〉 belongs to classes c1,c2 and are estimated using ��� or 2,�� � ∕ ��� �. because each feature column ��� is a set of discontinuous values, these discrete values of ��� need to be split into two sets using an unsupervised algorithm. the k-means clustering method can partition a given dataset into k groups prespecified by the analyst [19]. in this study, this process was repeated 25 times to produce a lower within-cluster variation and a more stable result. each ���×� now belongs to the split set � ��, ��� and has a class label. the expected information required to classify the tuple from �� based on feature ��� is ( ) ( ) 2 1 info info β = = ×ɺ ɺ ɺ ɺ ɺ i n i nn i s s b b b b (3) ( ) ( ) ( )gain info info β β = − ɺ ɺ ɺ ɺ n n b b (4) the ��� with the highest information gain was chosen to replace the center of !���, ���, … , ����# and the other features were sorted individually from the center to the two sides with decreasing information gain. thus, a sorted base feature set was obtained. 2.3. generating nutritious soil based on features digitized soil consisting of the sorted base feature set cannot only be wide; it must also have depth. therefore, continuous feature discretization (from scalar to vector) is necessary. in this process, equal-width interval binning is the most common method used for discretizing data to produce nominal values from continuous features [20]. with this binning method, if feature $ has values bounded by $�%& and $�'� , the method computes k equally sized bin widths as follows: max mina a k − =δ (5) and it constructs bin boundaries at $�'� + )*, where ) = 1, 2, … , , − 1. to imitate the natural environment of the root system, this study set , = 15. advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 167 in addition, the vertical distribution of soil nutrients should follow the laws of nature. most nutrients are concentrated in the shallowest layer and decrease with depth because nutrients return to the soil through biocycles. thus, the discrete feature set /�0×�� was arranged in decreasing order from top to bottom. by contrast, the horizontal distribution of nutrients is associated with crustal movement. the kernel convolution values 12 and 1� were used to calculate the reconstituted nutrient distributions. nutritional reconstructions are divided into two types: 12, which affects the nutrient distribution in shallower layers; and 1�, which affects the nutrient distribution in deeper layers. the convolution kernel is then defined as: 1 1 1 1 0 1 0 2 0.5 0.5 0.5 a    =      τ (6) 0.5 0.5 0.5 1 0 1 0 2 1 1 1 b    =      τ (7) the nutritious soil used to generate the root system is written as 3�0×��, which is a result of the /�0×�� convolution with kernels 12 and 1� . the calculated target matrix requires zero padding with a size of 1 before each convolution. the completed soil with the mineral nutrition generation process is shown in fig. 1. the following matrix for the distribution of nutrients in the soil is referred to as the nutrient matrix. the elements of the base feature set are arranged in order of importance, from the center to either side. each element in the set is then discretized. finally, the soil matrix is obtained using two convolution calculations. fig. 1 top-to-bottom order of soil matrix construction 2.4. plant root system algorithm in plants, either the radicle or primary root is the first organ to emerge from the seed coat. before the first leaf grows, the energy required by the cotyledon for root development comes from the seed itself. additional inorganic nutrients (including water) are essential. only a small fraction of these nutrients come from the seed itself, and the rests are from the surrounding soil which contains mineral nutrients [21]. the rule that is inherent in the genes of higher plants is to develop a sufficiently large first leaf and long roots before the energy stored in the seed is exhausted. the proposed algorithm follows this rule. as organic matter cannot be synthesized by photosynthesis before the first leaf has grown, the task is to absorb more mineral nutrients by growing a sufficient large root system with limited energy (root division) in a limited time. the matrix distribution for the roots in the soil is hereafter referred to as the root matrix. in the proposed approach, the aforementioned natural processes must be transformed into a data-processing program. first, the root and nutrient matrices form a four-dimensional tensor, as shown in fig. 2. the initial root matrix is a zero matrix, where the upper-center location assigning values can create a radicle matrix. to absorb more nutrients, the rule of root division advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 168 is to preferentially proliferate at the global maximum in the mapping nutrient matrix. neighboring root tips are also necessary. the radicle matrix, photosynthetic day, and daily root division are used as modification parameters. the developmental process can be characterized by the root distribution area and total nutrient absorption. fig. 3 shows the natural and digital processes used to build a brain-like root system. the figure also depicts that the growth of digital roots is dependent on the base features in this study. by extracting the prs features from the brain-like root system, the correlation with the base features is reduced. fig. 2 four-dimensional data tensor of biomedical signals fig. 3 natural and digital processes for building brain-like root systems in table 2, the root growth process can be written as a pseudocode. in the proposed algorithm, the core steps of root development involve seeking the global maximum location of the nutrient matrix map relative to the root matrix location using a tensor of a biomedical signal base feature set. the entire root system makes decisions in a brain-like fashion to improve total nutrient absorption. the root distribution can be drawn in the coordinate system as a polygon. the area of this polygon serves as a feature. this study uses a well-known tool to calculate the polygon area proposed by paul bourke in 1988. the procedure provided two results, which are both referred to as prs features: nutrient feature (nf), representing the total number of nutrients absorbed during root system development in the digitized soil; and root feature (rf), representing the area of root distribution. the calculations of nf and rf are shown in table 2 as the nutrient amount (na) and area (a). a is calculated based on eq. (8) and fig. 4, wherein the polygon is closed and composed of line segments between n vertices 4�' , 5'6, 7 = 0 to 9 − 1. ( ) 1 1 1 0 1 2 n i i i i i a p q p q − + + = = − (8) advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 169 fig. 4 example of 10-vertex closed polygon constructed from a root matrix table 2 plant root system algorithm algorithm 1 plant root system pseudocode comments 1 input: 2 :ℝ&×<: distribution of the radicle in soil (initial root matrix); x, y are the number of rows and columns of the distribution matrix 3 :ℕ&×<: distribution of nutrients in the soil (nutrient matrix); 4 output: 5 na: nutrients absorbed by the roots; 6 a: root distribution area; 7 @$ ← 0; 8 ℝ&×< ← :ℝ&×<; ℝ&×< : distribution of the growing root in the soil (root matrix) 9 for 7 = 1 → /$c do day is the number of days for the first leaf to appear 10 for each ℝd&ef,<efg = 1 do �hi ∈ 41,2, … , �6, chi ∈ 41,2, … , c6 11 k ← l:ℕd&m�ef,<efg, :ℕd&n�ef,<efg, :ℕd&ef,<m�efg, :ℕd&ef,<efn�go; ℝd&ef,<efg ∈ ℝ&×<ℕd&ef,<efg ∈ :ℕ&×< 12 return m to p; p is a matrix 13 end for each 14 decreasing sort p to m; m is a vector 15 for ) = 1 → q do; 4q r qs@tuℎ wx y6 q is a limit of root division in one day 16 yz)[ mapping back to z�hi, chi[; z�hi, chi[is a location of the matrix 17 if ℝd&ef,<efg \ 1 do 18 ℝd&ef,<efg ← 1; 19 20 21 na← ] 0, yz)[ = 0 ^z_[ �m|^z'[| + 0.49, yz)[ \ 0 absorption rate 22 end if 23 do @$ + +; 24 return @$ and ℝ&×< @$ is the first output 25 end for 26 do ℝ� ← ℝ root extraction as polygon 27 do d ← $es$�ℝ� �; $es$ of the polygon d is the second output 28 return d; 29 end procedure incorporating the extracted prs features into the unprocessed base feature set produced a set for classification, which was composed of 14 features. finally, the final feature set can be obtained by performing min-max normalization. the flowchart in fig. 5 explains the prs feature extraction process. the entire process is divided into two parts. the first involves creating a nutrient matrix with common features. the core idea is to develop digitized soil with an appropriate size and nutrient distribution through a mathematical calculation between features. the second part involves developing the root matrix using the nutrient matrix and seeds. the core idea is to limit the root division rule for radicles using parameters. advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 170 fig. 5 the flow chart of the calculation of frs features 3. datasets and evaluation methods the accuracies of various classifiers were considered for evaluation. the key measure for each classifier is the change in accuracy before and after adding root-based features to the original feature set. accuracy is often used in epidemiology [22]. for a sample, a correct classification is true, and an incorrect classification is false. the accuracy is usually expressed as a percentage, calculated by dividing the total number of correct samples by the sum of all samples. a result closer to 100% will be more accurate. accuracy + = + + + tp tn tp fp tn fn (9) where true positive (tp) and false positive (fp) are the number of true and false positive samples. true negative (tn) and false negative (fn), which are the number of true and false negative samples. 3.1. datasetsu3 when selecting a dataset of biomedical signals, a nonstationary signal is preferred. almost all biomedical signals are nonstationary because the human system is always in a state of dynamic equilibrium under the control of the brain [23]. accordingly, three biomedical signals were selected: a vibroarthrographic (vag) signal, the vibration signal generated by the friction between the knee cartilage during flexion-extension to detect knee joint disorders, captured by acceleration sensors near the kneecap [24]; forearm emg, the electrical signal generated by the extensor carpi radialis longus during fist relaxation, captured by electrodes near the muscles of the small arm [25]; and the audio signal recorded by a smartphone web application to detect cough emanating from the lungs and airways of a patient who may be infected with covid-19, captured by a microphone placed near the head [26]. all signals are binary, classified as young or old for the vag signals, rest or fist for the emg signals, and positive or negative for the cough sound signals. table 3 presents the detailed characteristics of these signals. table 3 properties of biomedical signals dataset signal type class sample size sampling rate length noise reduction vag of the knee joint vibration 2 144 2000 hz 3-5 k yes emg of hand electrical 2 72 1000 hz 3-5 k no coughing sound sound 2 121 22.5 khz 60-80 k no advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 171 3.2. evaluating prs features classifiers for feature testing should be selected following the principle of interpretability, avoiding black boxes as much as possible [27]. the logistic regression (lr) model, which is widely used in classification problems and has the advantage of outputting probabilities, was chosen as the main linear classifier in this study. however, the lr classifier is also limited by these probabilities. in some cases, a result of 51% or even 99% pointing to a given class can produce mismatching, which means that the predicted class may not be accurate even though the probability of the prediction is high. [27]. in contrast to lr, a support vector machine (svm), which focuses on maximizing the probability of group membership, attempts to find the separating hyperplane that maximizes the distance of the closest points to the border. as the feature sets have more than 12 dimensions, a polynomial kernel-based nonlinear svm was used as the main nonlinear classifier. a linear discriminant analysis (lda) and quadratic discriminant analysis (qda) were used as complementary classifiers to the lr and svm classifiers. these machine learning-based classifiers were used to test the feature set [28]. feature extraction methods for biomedical signals typically use both timeand frequency-domain features. because all base features in this study were time-domain features, two frequency-domain features were used to complete the comparison feature set [6]. specifically, this study uses the maximum power spectrum density (maxpsd) and median power spectrum density (medpsd) as auxiliary features to the base features in the comparison set. the two frequency-feature extraction techniques were based on fourier transforms [6]. the maxpsd and medpsd measures were added to the unprocessed base feature set to create a comparison set that included the same 14 features as the experimental set. the comparison set was then normalized using minmax normalization to ensure that the features were on the same scale. finally, the accuracy of the prs algorithm was compared to the accuracy of the comparison set. implementations of signal processing, feature engineering, the prs algorithm, and classifiers were supported by rstudio and related packages, and the result has been provided in subsequent sections. 4. results the study used four datasets to evaluate the performance of each classification model. the first dataset, referred to as the base set, contained only 12 time-domain features as listed in table 1. the second and third datasets, named base + nf and base + rf respectively, contained one prs feature and 12 time-domain features each, in addition to those in the base set. finally, a fourth dataset was used that included all 14 features (the 12 time-domain features and the 2 prs features). this dataset, referred to as prs with all features, was used to evaluate the performance of each classification model when all features were included. all datasets including the vag, emg, and cough signals were input individually into the lr, svm, lda, and qda classifiers. each classifier was trained with learning rates ranging from 40% to 80% of the total samples (in increments of 10%). the remaining samples were used as test data. the classification accuracy was then calculated using eq. (9). the results for the vag, emg, and cough signals are summarized in figs. 6-8, where the vertical coordinate represents the average accuracy of 100 classifications using various learning rates with a one-way anova test after the shapiro test. as shown in the figures, all input sets for the three types of biomedical signals exhibit an increasing trend in accuracy with a raised learning rate. however, the most notable results are that the sets including the nf or rf features show greater accuracy than merely the base set. this result is consistent with the hypothesis of this study that the new feature introduced by the algorithm as a control variable that is less correlated with other existing variables reduces the overall correlation between variables reduces bias in training, and improves classification accuracy. focusing on the vag signal in fig. 6. first, the input sets containing the nf tend to perform better. the qda classifier with the set containing the nf and rf has the highest classification accuracy. further analysis indicates that the classification accuracy improves by 3.12% using the base set and 3.65% for the base+nf set when the training rate is increased to 80% for the lr classifier. advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 172 (a) lda classifier (b) lr classifier (c) svm classifier (d) qda classifier fig. 6 accuracy of vag signal for four classifiers (a) lda classifier (b) lr classifier (c) svm classifier (d) qda classifier fig. 7 accuracy of emg signal for four classifiers fig. 7 indicates that the classification accuracy for the emg signal is as high as 98% for all four classifiers, which is considerably higher than the maximum values for the other biomedical signals. the set containing the nf or rf shows a higher accuracy under most conditions except for the qda classifier applied at an 80% training rate. fig. 8 shows that the cough signal is less accurate and regular than the other signals. in this study, the largest improvement in accuracy is observed at a advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 173 60% training rate for the qda classifier, which is an improvement of approximately 10% compared to the initial stage. in addition, although the accuracy monotonically increased as the training rate raised, there were several monotonic changes in all biomedical signals. this result is most likely due to errors during random sampling; therefore, a repetitive sampling comparison was implemented as follows: (a) lda classifier (b) lr classifier (c) svm classifier (d) qda classifier fig. 8 accuracy of cough signal for four classifiers (a) vag signal (b) emg signal (c) cough signal fig. 9 accuracy of the prs and comparison sets with a 60% learning rate for the svm classifier fig. 9 compares the accuracy of the base set, prs-features sets, and frequency-domain feature sets using a 60% learning rate for the svm classifier. tukey’s multiple comparison tests of the means using a 95% family-wise confidence level were conducted on the raw data shown. for the vag signal, the average differences between the prs-features set and the base set were greater than 3.71%, while the prs-features sets and frequency-domain features sets were greater than 1.63%. all pvalues were less than 0.05. the emg and cough signals followed the same pattern. in summary, the results indicate that the sets containing only the base features had a consistently lower accuracy rate; however, the prs-features sets had a consistently higher accuracy rate. advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 174 5. discussion for the vag signals, the prs features-sets showed a maximum accuracy of 93%, which is higher than that reported in previous studies [3, 24]. these results validate the findings of rauber et al. [14] in 2015 that only appropriate features could improve the performance of the classifiers. although the prs-features sets did not achieve the 80% accuracy reported by chaudhari et al. [26] in 2020, a 76% accuracy could be achieved with only one-tenth of the sample size. this study was unable to find published classification results for the emg signals; however, the authors believe that a classification accuracy of up to 98% is quite satisfactory. fig. 10 correlation between individual features of the emg signal the swarm intelligence approach’s most significant characteristic is to extract a feature set with exceptionally low correlations by simulating the development of natural prs. the feature correlations for the emg signals are shown in fig. 10, where the circle at the intersection of a feature row and the column of another feature represents the correlation between the two features. a cool-toned circle indicates a positive correlation, and a warm-toned circle indicates a negative correlation, and the smaller the circle size, the weaker the correlation. in addition, there was no negative correlation in this result, and all results were positive. surprisingly, the two features based on the prs algorithm had nearly zero correlation with the other features. by contrast, the time and frequency-domain features were more or less correlated. the low correlation between the prs features and other features was because of the different feature extraction methods. the development of a root system is a product of group decision-making, which reduces the correlation between the root matrix and the nutrient matrix in a tensor. thus, the performance of the classifier improved after the addition of prs features. another significant advantage of the prs algorithm is the simplicity of interpretation. although the full procedure of the proposed method might appear lengthy, the algorithm is rather lightweight. the nutrient matrix construction comprises twothirds of the work, whereas the construction of the root matrix and the extraction of the prs features constitute the remaining one-third. if the length of the biomedical signal does not exceed 100,000 and the sample size is less than 200, the training process can be completed within 5 min. the proposed prs algorithm performed better than expected. nevertheless, this study had certain limitations. first, the improvement of the accuracy rate was modest for each classification model. as shown in fig. 7, a mere 1% improvement in accuracy is insufficient to offset the error bar. one possible explanation for this might be the small sample size, which resulted in inadequate model training [29]. second, although the overall accuracy using the prs features tended to be higher than that of the base and classical feature sets for each classifier, some exceptions still existed. advances in technology innovation, vol. 8, no. 3, 2023, pp. 163-176 175 these phenomena are likely related to the possibility that extracting features based on the prs algorithm does not work well in the presence of outliers. root growth is based on values in the soil matrix, which are obtained by performing statistical calculations on biomedical signals. errors are passed down, causing a reduction in accuracy. this is the reason for an obtained lower accuracy at high training rates. although the prs was initially successfully used for feature engineering in the field of biomedical signals, it has some limitations, and further research is required. one limitation is that this study only considered a simple classification problem and did not consider multivalued classification. moreover, the effect of imbalanced datasets on learning was not studied. more experiments are needed to verify the diversity of the signal types. in the past, swarm intelligence and swarm intelligence algorithms, such as ant colony algorithms and bee colony algorithms, were mostly developed based on the behavior of social animals. currently, intelligent algorithms have also been modeled on certain static systems, including rivers and the prs used in this study. this study contributes toward renewed interest in the development of such algorithms. 6. conclusions in conclusion, this study has made significant strides in the field of biomedical signal processing by introducing a novel feature extraction algorithm, the prs algorithm. inspired by swarm intelligence and the natural growth of roots, the prs algorithm effectively explores the feature space and identifies the most discriminative features for classification. notably, the prs algorithm exhibits good interpretability and low correlation with traditional feature extraction methods, setting it apart from existing techniques. through a series of experiments, our findings demonstrated a substantial improvement in classification accuracy when utilizing the prs algorithm, as compared to conventional methods. these results underscore the potential of the prs algorithm in revolutionizing the way biomedical signals are processed and analyzed, ultimately paving the way for more effective clinical applications. this study serves as a strong foundation for future 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[29] s. b. kotsiantis, i. d. zaharakis, and p. e. pintelas, “machine learning: a review of classification and combining techniques,” artificial intelligence review, vol. 26, no. 3, pp. 159-190, november 2006. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v10n3(2025)-aiti#14310(201-219).docx advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 iterative clipping filtering and saleh model predistorter on a mimo-ofdm system testbed using software defined radio m wisnu gunawan, i gede puja astawa*, amang sudarsono department of electrical engineering, politeknik elektronika negeri surabaya (pens), jawa timur, indonesia received 19 september 2024; received in revised form 11 january 2025; accepted 14 january 2025 doi: https://doi.org/10.46604/aiti.2024.14310 abstract the purpose of this study is to address the challenges of high peak-to-average power ratio (papr) and nonlinear power amplifier (pa) distortion in multiple-input multiple-output orthogonal frequency division multiplexing (mimo-ofdm) systems based on the ieee 802.11ac. the research integrates iterative clipping filtering (icf) for papr reduction and the saleh model predistortion (pd) for pa linearization. implemented on a software defined radio (sdr) platform using ni-usrp devices, the system is evaluated in real-world line-of-sight (los) and nonline-of-sight (nlos) environments. results show significant papr reduction, from 19.7 db to 10.3 db, and improved pa linearity, achieving a 94.80% error vector magnitude (evm) reduction. furthermore, the combined approach exhibits lower symbol error rates (ser) and error-free data transmission, particularly under los conditions. compared to conventional methods, the system demonstrates superior execution efficiency with 475– 503 ms processing times. keywords: iterative clipping filtering (icf), saleh model, multiple-input multiple-output orthogonal frequency division multiplexing (mimo-ofdm), peak-to-average power ratio (papr) reduction, predistortion (pd) 1. introduction orthogonal frequency division multiplexing (ofdm) has become the most dominant technology for supporting highspeed data transmission in wireless communication systems [1]. ofdm allows systems to transmit more symbols per second, thus offering high data bandwidth with high spectral efficiency suitable for application in several modern communication systems such as digital audio broadcasting (dab), digital video broadcasting (dvb), wireless local area networks (wlan), and long term evolution (lte) [2]. to further enhance channel capacity and transmission reliability, ofdm is often combined with multiple-input multiple-output (mimo) technology, resulting in significant performance improvements in communication systems [3-4]. however, one of the main challenges faced in ofdm systems is the phenomenon of high peak-to-average power ratio (papr) [5-7]. this high papr value affects the performance of various mimo-ofdm-based wireless communication technologies, including wi-fi (ieee 802.11n), lte, wimax, and the internet of things (iot). in wimax, high papr makes the system highly vulnerable to the non-linearity of the power amplifier (pa), resulting in significant signal distortion and reduced transmission quality. the same issue occurs in 5g networks, where high papr values can reduce system performance efficiency. in the context of iot, which often involves devices with limited resources such as battery power and processing capacity, high papr accelerates power consumption, thereby reducing the device’s lifespan. therefore, efficient papr management is crucial to maintain spectral efficiency, signal reliability, and overall system performance [8]. * corresponding author. e-mail address: puja@pens.ac.id advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 202 additionally, the high papr value forces the pa to operate in the nonlinear region, resulting in in-band distortion and interference on neighboring channels due to spectral growth [9-11]. to minimize these nonlinear effects, the pa requires operation with significant back-off, but this reduces power efficiency [12-13]. therefore, an approach that can reduce papr while addressing the pa’s nonlinear distortion is needed. modern techniques such as papr reduction and predistortion (pd) provide important solutions to improve transmitter efficiency in wireless communication systems [14]. one simple and effective papr reduction technique is iterative clipping filtering (icf), which intuitively reduces papr with low computational complexity [15-18]. to address the nonlinear effects of the pa, the saleh model is used as a widely and efficiently applied behavioral model-based pd technique [19-22]. this model allows for the improvement of pa linearity by optimizing its linear operating region. as a comparison, several studies propose an approach based on real-valued neural networks (rvnn) that integrates papr reduction and pd within a single framework [14]. this approach demonstrates superior performance in reducing papr, adjacent channel power ratio (acpr), and bit error rate (ber). however, the rvnn-based model requires a large amount of training data and has higher computational complexity. additionally, other research proposes a combination of papr reduction techniques using companding methods, such as nonlinear error function (nerf), μ-law, and hybrid, combined with hammerstein model-based pd for ofdm systems in 5g networks [19]. this research successfully reduced the papr value by up to 20% and achieved a ber value of 10−5 at an eb/n0 of 21 db, demonstrating a system performance improvement of 4 db compared to a system without pd. however, the research did not sufficiently explore the effects of pa memory that could impact the overall system performance, including the receiver side. therefore, the simpler icf technique offers practical implementation advantages in hardware such as software defined radio (sdr), allowing for faster and more efficient adaptation to real-world environmental conditions. this approach not only reduces papr with higher computational efficiency but also provides stronger empirical validation in the context of real-world applications. in this paper, experiments were conducted to combine papr reduction techniques using icf with the saleh model pd technique in mimo-ofdm systems. the experiments were carried out in real time using sdr devices, specifically the usrp 2920, which allows for direct observation of the algorithm’s effectiveness under real operational conditions [23-24]. the testing involves the transmission of text data to evaluate the performance of papr reduction techniques using complementary cumulative distribution function (ccdf), pd with am/am, and power spectral density (psd) graphs, as well as the overall system performance through constellation diagrams, error characteristics, and symbol error rate (ser) analysis on the receiver side [25]. this research is expected to provide stronger empirical insights and validation for the application of icf techniques and the saleh model in real-world mimo-ofdm systems. 2. system modelling this section covers the architecture of the mimo-ofdm system at both the transmitter and receiver ends, the parameters used in the ofdm system, the mathematical representation of the saleh model, and the iterative icf process, providing a comprehensive framework for understanding and applying these techniques in modern wireless communication systems. 2.1. mimo-ofdm design in implementing the mimo-ofdm system with the application of icf and the saleh model based on sdr, on the transmitter side, a pc running labview controls usrp 1 and usrp 2 to generate and transmit ofdm data via antenna, using pa to amplify radio frequency (rf) data. the mimo channel then transfers the signal. subsequently, usrp 3 and usrp 4 transform the rf created by the pa into a digital signal for longer-term analysis on a pc, as shown in fig. 1. advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 203 fig. 1 designing a hardware implementation of mimo-ofdm system the purpose of this system is to monitor mimo-ofdm communication performance, including ser analysis, papr implementation, and pa segmentation. table 1 clearly explains the ofdm parameter used in the implementation of the sdrbased system. ofdm settings in table 1 are updated per ieee 802.11ac. table 1 ofdm parameters parameter value fft size 128 number of subcarriers 128 number of data subcarriers 96 number of pilot subcarriers 8 number of null subcarriers 24 modulation 4-qam cyclic prefix 32 center frequency 915 hz channel estimation least square channel equalizer zero forcing recent wi-fi standards like ieee 802.11ac offer high data transmission speeds, massive network capacity, and excellent spectrum efficiency. the ofdm configuration of this standard uses 128 subcarriers, 96 of which are used for data transmission and the rest for zero padding and pilot symbols. data subcarriers are the main medium for user data transport, enabling fast speeds. pilot subcarriers reference phase and frequency adjustment during transmission, ensuring signal reliability, especially in dynamic communication channels. certain subcarriers have zero padding to reduce inter-channel interference and ensure fast fourier transform (fft) size compatibility. ieee 802.11ac uses quadrature amplitude modulation (qam) modulation to optimize spectral efficiency. this standard meets modern networks’ high-speed, high-capacity data transmission needs with this design and qam modulation. the transmitter and receiver processes are depicted in fig. 2 and fig. 3, respectively. on the transmitter side, text data is first converted into a bit sequence mapped to qam constellation symbols. the symbols, totaling n = 2 n (where n = 96), are split into two sequences of n/2 symbols each. these sequences are converted from serial to parallel format, with 24 null symbols and nine pilot symbols added, resulting in parallel sequences of length 128. afterward, the inverse fast fourier transform (ifft) process transforms these into time-domain symbols, followed by papr reduction using the icf technique. a cyclic prefix is added to mitigate interference, and pd based on the saleh model is applied before the internal pa of the usrp amplifies the signal. the cyclic prefix is removed at the receiver, and fft converts the received signal into frequency advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 204 domain symbols. channel estimation, equalization, and removing pilot and null symbols are performed, followed by parallelto-serial conversion. the mimo-ofdm decoder combines the outputs from the receiving antennas, producing a single qam symbol sequence, which is remapped into bits and converted back to text. fig. 2 block diagram of mimo-ofdm transmitter system fig. 3 block diagram of mimo-ofdm receiver system 2.2. icf for papr reduction in an ofdm system, the ofdm signal consists of the summation of several independently modulated subcarriers. if the phase of each subcarrier is the same, the maximum signal power generated will be n times its average power. the ratio between the maximum signal power and the average power is commonly referred to as the papr. at any given time, this summation can be very large and, at other times, very small, meaning that the maximum power value of the signal is always greater than its average power. mathematically, the papr of a signal is defined by the formula below. ( ) 2 2 max ( ) ( ) = = peak average p x n papr p e x n (1) where ����� denotes the maximum power (watts) and �������� average power (watts). the term �|� ��|� represents the peak value of the ofdm signal while � |� ��|�� the average value of the ofdm signal. the papr value from eq. (1) can be converted to db using the formula below. ( )10 ( ) 10 log papr=papr db (2) the papr value is generally statistically described using the ccdf. the ccdf is used to analyze and compare papr values. the ccdf is expressed as follows. 1= −ccdf cdf (3) ( )1 1 −= − − papr ccdf e n (4) eq. (4), the input values are the papr and �, representing the number of subcarriers used in the ofdm system. advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 205 a high papr value in ofdm requires an amplifier with a wide dynamic range to accommodate the signal amplitude. if this is not met, it will cause linear distortion, resulting in the subcarriers losing their orthogonality and ultimately degrading the performance of the ofdm system. this high papr issue cannot be ignored, as it can reduce the performance of the ofdm communication system. therefore, techniques to reduce high papr values are necessary. conceptually, papr reduction techniques aim to reduce the ofdm signal’s peak power or average power. by reducing the peak power or average power, the requirement for input back-off (ibo) can be minimized, thereby improving the performance of the ofdm system. commonly used techniques to reduce papr include partial transmit sequence (pts), clipping filtering (cf), and icf, which rely on an adjustable clipping ratio (cr) parameter. a comparison of icf with other papr reduction algorithms is shown in table 2. table 2 comparison of icf with other papr reduction algorithms criteria icf pts computational complexity low (simple to implement) high (requires phase optimization for each subblock) effectiveness of papr reduction effective at certain cr values more effective with proper optimization signal distortion potentially introduces distortion does not cause distortion implementation flexibility easy to implement on sdr devices requires phase optimization algorithms parameter sensitivity highly dependent on cr value dependent on the number of subblocks advantages easy to implement and efficient provides optimal minimum papr results disadvantages signal distortion due to the clipping process high computational complexity icf is a papr reduction method that enhances the cf method. icf works similarly to cf, but it involves iterations during the clipping and filtering process. the icf method directly reduces the signal peaks using a predetermined threshold. then, the clipped signal is filtered to eliminate out-of-band (oob) radiations that occur due to the clipping process. iteration in this method is performed to address peak regrowth, which usually occurs after the filtering process. additionally, iteration is used to achieve the targeted papr value. the icf method can be defined using: max max max ( ) ˆ( ) ( ), ( ) ϕ > =  ≤ j t i i i a e x n a x n x n x n a (5) 2.3. saleh model predistortion a pa is a nonlinear component of the system. ideally, the output of the pa is equivalent to the input multiplied by a gain factor. the pa has a limited linear region beyond which it reaches saturation at the maximum output level, as illustrated in fig. 4. fig. 4 power amplifier operating region curve advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 206 pa exhibits nonlinear characteristics, saturation happens when the input signal surpasses a particular level. a signal with a high papr passing via a pa may cause saturation. saturation distorts the input signal since the pa no longer performs linearly at high power. this distortion occurs inside and outside the frequency band. in-band distortion lowers the signal quality and increases the ber. spectrum efficiency is reduced by oob distortion, which interferes with nearby channels. this nonlinear distortion affects mimo-ofdm and other rf signal transmission technologies like 5g, iot, and others. nonlinear distortion in many communication systems, especially those that deliver data quickly or have limited resources, must be managed to minimize spectrum and power utilization. to handle pa nonlinearity, a linearization method is needed. modeling the pa to understand its linearization model achieves linearization. use the saleh model to model the pa. the saleh model models nonlinear pa. this memoryless model shows that pa characteristics don’t change and are easy to implement. although rapid for calculations, the saleh model cannot imitate the nonlinear behavior of current amplifiers, especially solid-state amplifiers. this model misrepresents power compression and phase distortion at sub-thz frequencies, especially under saturation. this model also struggles with high-frequency amplifiers complex intermodulation and even-order nonlinearities. the model’s fundamental structure is easy to build, but its limits make it ideal for low-frequency and nonsaturation applications. complex applications require parametric modifications or neural network-based methods to define modern pa nonlinear properties. table 3 contrasts the saleh model with various pd models. the pa model can be expressed as follows: ( )2 ( ) 1 ηα β = + v u y u u (6) the output signal of the pa is denoted as � ��, which is a function of the input signal to the pa, �. the pa coefficients, obtained from measurements, are represented as � and �. additionally, there are preselected parameters, which can take values of 1, 2, or 3, and which can take values of 1 or 2. table 3 comparison of the saleh model with other predistortion models criteria saleh model neural network computational complexity low (analytical and straightforward) high (requires training and inference processes) effectiveness in linearization effective for low-to-moderate nonlinearities highly effective, adaptable to complex nonlinearities flexibility limited (specific to certain amplifier types) high (applicable to various nonlinear systems) adaptability low (fixed parameters) high (self-learning capability allows adaptation) accuracy in nonlinear modeling moderate (simplified nonlinear model) high (captures complex nonlinearities) advantages simple, low computation, suitable for real-time can handle highly complex systems and dynamics disadvantages limited to specific amplifier characteristics computationally intensive and requires significant data for training fig. 5 transfer function of the combined pa-pd advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 207 pd is a technique used to linearize pa. the pd model characterizes the inverse behavior of the pa. as shown in the transfer function diagram in fig. 5, when pd is combined with the pa, it results in a linear system. when pd is applied alongside the pa, it compensates for the amplifier’s nonlinear behavior, effectively transforming the overall system into a linear one. thus, it is understood that the input signal � �� first passes through a predistorter, which has a model characteristic that is the inverse function of the pa’s transfer function. the output of the pd is then used as input for the pa. the pd equation is given as follows. [ ]1( ) ( )−=u x h y x (7) the output signal of the predistorter is denoted by � ��, which is obtained from the inverse of the equation � ��. the inverse function for pd is given by ���. therefore, the inverse function for the polar parameter am/am in the saleh model pd is provided as follows. 2 2 1 4 ( ) 2 α α β β − − − = x h x x (8) in eq. (8), � and � are constants derived from the characteristics of the pa, and � is the input value to the inverse function. the term under the square root, � − 4���, is the discriminant of the quadratic equation, which influences the shape of the curve in the original pa model. this inverse function is used to linearize the pa by ensuring that the output signal, after pd when passed through the pa, results in a linear response. 3. results and discussion this section analyzes the performance of various techniques implemented in the mimo-ofdm system. the discussion covers the evaluation of the icf technique for papr reduction, the effectiveness of the saleh model-based pd technique in linearizing pa, and the application of this approach within the mimo-ofdm framework. furthermore, it examines the combined use of the saleh model pd technique and icf in the mimo-ofdm system and analyzes the relationship between ser and signal-to-noise ratio (snr). the evaluation results highlight the system’s effectiveness in enhancing signal transmission quality. 3.1. performance icf for papr reduction the ccdf curve in fig. 6 represents the probability of papr values for signals generated from a mimo-ofdm system that implements papr reduction techniques using icf with various cr values and a system that does not apply papr reduction techniques. papr0 indicates the power level generated based on the range of papr values for each generated symbol. the ccdf curve shown in fig. 6 provides the papr values achieved using the icf technique for papr reduction. these values correspond to the most negligible probabilities observed in the simulation, highlighting the effectiveness of the icf method in minimizing papr under specific conditions. table 4 papr values of mimo-ofdm system with and without icf system scenario papr value ofdm 19.7 db ofdm + icf cr = 5 12.1 db ofdm + icf cr = 4 11.3 db ofdm + icf cr = 3 10.3 db advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 208 the detailed numerical results from the ccdf curve are summarized and presented comprehensively in table 4 for further analysis and comparison. the results show that the ofdm signal with the papr reduction technique using icf has a lower power level than the ofdm signal without the papr reduction technique. the cr value affects the extent of the cr to reduce the papr value. a smaller cr value results in a lower power level. fig. 6 ccdf curves of the mimo-ofdm system without and with icf icf is used with confidence interval (ci) analysis to evaluate papr reduction efficiency. papr reduction cis for various crs are presented in fig. 7. in fig. 7, three graphs show papr reduction performance (in db) for the reduction technique with cr values of 3, 4, and 5. in the graph for cr = 3, papr reduction averages 6.33 db with a 95% ci of [5.38, 7.28]. it reduces papr significantly, but sample variance is substantial, especially after the 30th sample, indicating uneven signal clipping. graph for cr = 4 indicates an average papr reduction of 5.26 db with a 95% ci [4.32, 6.19]. this number balances papr reduction performance and result consistency, with lower sample variation than cr = 3. (a) cr = 3 fig. 7 confidence interval for several cr values advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 209 in the graph for cr = 5, the average papr reduction is 4.51 db with a 95% ci of [3.61, 5.41]. better stability is observed at cr = 5, as indicated by the lower sample variance. the lower papr reduction suggests that higher crs produce more stable signals but achieve less papr reduction. overall, the results indicate that the cr value should balance papr reduction and signal stability, depending on application needs. (b) cr = 4 (c) cr = 5 fig. 7 confidence interval for several cr values (continued) based on the execution time data in table 5, icf is far more efficient than pts in terms of execution time. icf only requires 3–8 ms for all values of cr, indicating that this algorithm is very simple and suitable for real-time applications that prioritize time efficiency. in contrast, pts takes much longer, at 293 ms, because the process involves dividing the ofdm signal into sub-blocks, searching for the optimal phase, and reassembling, thereby increasing computational complexity. therefore, pts is more suitable for applications that prioritize optimal papr reduction, while icf excels in time efficiency for signal processing. advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 210 table 5 comparison of execution time for several scenarios scenario execution time mimo-ofdm + pa-pd icf cr = 3 503 ms mimo-ofdm + pa-pd icf cr = 4 483 ms mimo-ofdm + pa-pd icf cr = 5 475 ms mimo-ofdm + papr reduction pts 776 ms papr reduction icf cr = 3 8 ms papr reduction icf cr = 4 4 ms papr reduction icf cr = 5 3 ms papr reduction pts 293 ms 3.2. performance saleh model pd technique for pa linearization the am/am curves of the pd output signal, pa output signal, and combined pa-pd output signal are shown in fig. 8. the am/am curves show that the pa output signal fig. 8(b) is nonlinear, supporting the idea that pas are signal amplifying components. the am/am curve for the pd output signal fig. 8(a) is the opposite of the pa output signal fig. 8(b). as demonstrated in fig. 8(c), the am/am curve is linear when the pd and pa output signals are combined. this shows that linearizing the nonlinear pa in the saleh model pd extends the back-off region. (a) am/am pd curve (b) am/am pa curve (c) am/am linear pa-pd curve fig. 8 am/am curve of linearization pa in addition to using am/am curves, the impact of the saleh model pd in linearizing the nonlinear pa is also demonstrated using psd plots, as shown in fig. 9. the psd graph reveals the influence of the pa’s nonlinear characteristics on oob emissions, resulting in additional spectral components outside the desired frequency band. by applying pd, the nonlinear effects of the pa that cause oob emissions can be compensated. fig. 9 psd graph of mimo-ofdm system with linearization pa advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 211 the application of pd techniques significantly improves the linearity of the pa, with error vector magnitude (evm) reduced from 62.11% to 3.23%, reflecting an improvement of 94.80%, as shown in fig. 10. this reduction in evm indicates that pd is effective in reducing nonlinear distortion, enhancing signal quality, and ensuring transmission reliability in wireless communication systems. fig. 10 comparison before and after predistortion 3.3. performance of the saleh model pd technique in mimo-ofdm systems fig. 11 system testing on los condition fig. 12 system testing on nlos condition advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 212 the saleh model pd technique was tested in mimo-ofdm systems under line-of-sight (los) and non-line-of-sight (nlos) situations, as shown in fig. 11 and fig. 12. testing took place at the postgraduate building, pens, an interior environment with several actual constraints that could impair communication system performance. people walking by, using electronics, and architectural components like walls, floors, and ceilings reflecting signals make this setting noisy. mobile phone and wi-fi router interference can further degrade the system. this real-world scenario necessitates a reliable and optimal system amid dynamic and disruptive operations. each transmitter and receiver is configured using the sdr device according to the settings shown in fig. 13. sdr provides advantages in terms of hardware control through software, allowing experiments with various papr reduction techniques, testing of various signal parameters, and evaluation of communication system performance under varying conditions. the sdr device used is the ni-usrp 2920, which supports the mimo scheme. fig. 13 configuration of sdr device the ni-usrp device is used to transmit and receive rf signals. each ni-usrp device has an antenna that allows for the transmission and reception of wireless signals. since the testing uses a 2×2 mimo scheme, two ni-usrp devices are used as transmitters, and two other devices are used as receivers. mimo cable synchronizes both ni-usrp devices configured as transmitters or receivers. therefore, the mimo cable guarantees that no processes take precedence over each other during the mimo process. labview software controls and configures the ni-usrp devices as transmitters and receivers on a pc or laptop. testing was conducted by transmitting text from the transmitter to the receiver. the text sent is shown in fig. 14. the testing was performed by analyzing the output constellation diagram and the number of character errors. the first test involved a mimo-ofdm system using a pa without pd. subsequently, the mimo-ofdm system was tested using a pa with the saleh model pd technique application. fig. 14 data text source advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 213 the constellation diagram still matches the 4-qam modulation in the findings of the pa-only system test. however, many constellation symbols are incorrect. because of the nonlinearity of pa, the received symbols still contain errors. the incorrect symbols are translated into text using a constellation diagram with error symbols. as shown in table 6, the los scenario receives one incorrect character, while the nlos scenario in table 7, receives eight incorrect characters. the constellation diagram for the pa system using the saleh model pd technique shows 4-qam modulation with non-dispersed symbols. the saleh model pd technique improves system performance by eliminating receiver character errors. table 6 constellation and character results of mimo-ofdm under los conditions with and without pd scenario constellation diagram display character error mimo-ofdm system using pa mimo-ofdm system using pa with pd table 7 constellation and character results of mimo-ofdm under nlos conditions with and without pd scenario constellation diagram display character error mimo-ofdm system using pa mimo-ofdm system using pa with pd 3.4. performance of the saleh model pd technique and papr reduction using icf in mimo-ofdm systems the effects of papr reduction techniques and pd can be analyzed through the transmitted signals from the transmitter. this fig. 15 shows what happened to the signals sent from the transmitter when the icf method was used with cr values of advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 214 3, 4, and 5. from fig. 15, it can be observed that the signals transmitted by the mimo-ofdm system with the implementation of the icf method and the saleh model pd experience a decrease in amplitude value. this is attributed to the influence of icf in clipping the transmitted signals. (a) cr = 3 (b) cr = 4 (c) cr = 5 fig. 15 the transmitted signal for various cr parameters from each configuration of cr values, tests will be conducted to evaluate the transmission performance of the mimoofdm system by applying the icf technique and saleh’s model pd through the observation of character errors and constellation diagrams under los and nlos conditions. the characters and constellation diagrams received under los conditions for cr values of 3, 4, and 5 are displayed in table 8. advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 215 table 8 constellation and character results of mimo-ofdm with pd and papr reduction at various crs under los conditions scenario constellation diagram display character error mimo-ofdm system using pd and icf cr = 3 mimo-ofdm system using pd and icf cr = 4 mimo-ofdm system using pd and icf cr = 5 table 9 constellation and character results of mimo-ofdm with pd and papr reduction at various crs under nlos conditions scenario constellation diagram display character error mimo-ofdm system using pd and icf cr = 3 mimo-ofdm system using pd and icf cr = 4 advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 216 table 9 constellation and character results of mimo-ofdm with pd and papr reduction at various crs under nlos conditions (continued) scenario constellation diagram display character error mimo-ofdm system using pd and icf cr = 5 the characters and constellation diagrams received under nlos conditions for cr values of 3, 4, and 5 are displayed in table 9. for los and nlos conditions, when the cr value is 3, there are character errors compared to the results from cr values of 4 and 5. additionally, the constellation diagram at a cr value of 3 also shows greater dispersion. character errors and dispersion in the constellation diagram are caused by the smaller cr value, which results in a lower signal level, thereby degrading transmission efficiency. this is a weakness of the icf algorithm, so determining the optimal cr value should not only focus on reducing papr but also consider overall transmission performance. 3.5. evaluation of ser against transmission distance the curves in fig. 16 and fig. 17 show the relationship between transmission distance and the reliability of the communication system, where distance is used as a substitute for the snr value. the assumption is that the smaller the distance between the transmitter and receiver, the stronger the signal will be, resulting in a higher snr and a lower ser. the distance settings in the tests were conducted at 120, 180, 240, 300, and 360 cm to evaluate the system’s performance in various transmission scenarios. in los conditions, where there is a direct path between the sender and receiver without obstacles, the ser is generally lower compared to nlos conditions. fig. 16 the connection between distance and ser in los conditions as transmission distance decreases, ser under los conditions decreases sharply, indicating an increase in signal strength and transmission quality. in contrast, under nlos conditions, environmental impediments like reflection and scattering keep the ser high, especially at longer distances, and slow its drop as the distance approaches. system performance is improved advances in technology innovation, vol. 10, no. 3, 2025, pp. 201-219 217 differently via different methods. pa-only systems perform the poorest with the highest ser at all distances in los and nlos. pd lowered ser, especially at medium to near distances, and improved los performance. pa with pd employing icf performed well in both situations, notably for cr values of 4 and 5, which consistently had the lowest ser. environmental impediments hinder this technique’s efficiency under nlos settings compared to los. fig. 17 the connection between distance and ser in nlos conditions fig. 16 and fig. 17 show that pd and pd with icf applied to pa reduce ser efficiently, with better performance under los situations. this approach still improves wireless communication system reliability under more complex nlos scenarios, underscoring its importance in varied transmission situations. these two methods reduce pa-induced nonlinear distortion. 5g nr and wi-fi 6 benefit from papr reduction and pa linearization. papr reduction reduces power peaks, improving pa efficiency, transmitter power consumption, and mobile device battery life. hardware like pa is more durable due to lower thermal load. pa linearity upgrades reduce pa nonlinearity distortion in 5g applications, which need high frequencies and wide bandwidths for fast data speeds. papr reduction and pa linearization allow wi-fi 6 to support more uplink and downlink connections without affecting throughput or signal quality, enhancing wireless communication stability and performance. 4. conclusion this paper discusses two main issues in mimo-ofdm systems: high papr and the nonlinear effects of pa. to mitigate these issues, the saleh model pd technique was applied in combination with the icf method. the proposed approach was implemented and validated in a real-world environment using sdr devices. the main conclusions are summarized as follows: (1) the combination of the saleh model pd and icf effectively reduces papr and linearizes pa characteristics. 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[25] g. m. abdulsahib, d. s. selvaraj, a. manikandan, s. palanisamy, m. uddin, o. i. khalaf, et al., “reverse polarity optical orthogonal frequency division multiplexing for high-speed visible light communications system,” egyptian informatics journal, vol. 24, no. 4, article no. 100407, 2023 copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 4-v9n1(2024)-aiti#12682(42-49).docx advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 english language proofreader: chih-wen teng efficient object detection and intelligent information display using yolov4-tiny ying-tung hsiao, jia-shing sheu*, hsu ma department of computer science, national taipei university of education, taipei, taiwan, roc received 04 august 2023; received in revised form 14 november 2023; accepted 15 november 2023 doi: https://doi.org/10.46604/aiti.2023.12682 abstract this study aims to develop an innovative image recognition and information display approach based on you only look once version 4 (yolov4)-tiny framework. the lightweight yolov4-tiny model is modified by replacing convolutional modules with fire modules to further reduce its parameters. performance reductions are offset by including spatial pyramid pooling, and they also improve the model’s detection ability for objects of various sizes. the pattern analysis, statistical modeling, and computational learning visual object classes (pascal voc) 2012 dataset are used, the proposed modified yolov4-tiny architecture achieves a higher mean average precision (map) that is 1.59% higher than its unmodified counterpart. this study addresses the need for efficient object detection and recognition on resource-constrained devices by leveraging yolov4-tiny, fire modules, and spp to achieve accurate image recognition at a low computational cost. keywords: yolov4-tiny, deep learning, object detection, image recognition, information display 1. introduction target detection methods that leverage deep learning have greatly advanced with the introduction of models such as recursive convolutional neural networks (r-cnns) [1-2], fast r-cnn [3], faster r-cnn [4], mask r-cnn [5], single shot detector (ssd) [6], and you only look once (yolo) [7]. mask r-cnn proposes a region of interest (roi) align technology to address the problem that the bounding box positioning of faster r-cnn’s roi pooling is not accurate enough. the roi align uses bilinear interpolation to replace the original roi pooling’s use of integers to record coordinates and instead uses a floating point to record coordinates. ssd uses a multibox detector based on a convolutional neural network and sets a series of anchor boxes (anchor boxes) on each layer of feature maps. each anchor box corresponds to an object of different sizes and aspect ratios. the ssd detects and locates objects by predicting whether each anchor box contains an object and the category and location information of the object. during training, ssd uses a cross-entropy loss function to minimize the gap between predicted values and true values. these methods have enabled accurate and efficient object detection in domains such as medical image analysis, face recognition, and self-driving cars [8]. however, applying computationally demanding deep learning models in resourceconstrained edge devices is challenging [9-10]. in this study, the efficient and lightweight object detection architecture you only look at once version 4 (yolov4)-tiny [11] was modified to achieve a superior trade-off between accuracy and computational cost. specifically, convolution-batch normalization-leaky relu (cbl) modules in yolov4-tiny were replaced with fire modules to reduce the number of parameters without compromising performance [12], enabling its * corresponding author. e-mail address: jiashing@tea.ntue.edu.tw advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 43 deployment on low-power devices. spatial pyramid pooling (spp) was then to enhance the feature extraction capabilities of the network at various scales and capture fine-grained details in objects of varying sizes [13]. the proposed method was used to effectively recognize objects within images and could then display information on these objects. the motivation behind this study is to assist individuals in capturing moments using their convenient photography devices or accurately retrieving desired product information from online photos. however, achieving high precision in image recognition and fast detection often relies on extensive computation and high-performance hardware. therefore, an approach that maintains high accuracy while minimizing computational costs is investigated. the remainder of this article is organized as follows: section 2 presents a literature review related to the proposed method in the paper, section 3 describes the system architecture of the modified yolov4-tiny architecture, which was adjusted to reduce the complexity of the cbl module, section 4 outlines the experiments and presents the results, and section 5 concludes the paper. 2. literature review and methodology the yolo series is a well-established architecture and was selected as the basis for the proposed method [14-15]. yolo is widely recognized for its real-time object detection capabilities and high efficiency. for yolov3, a novel backbone network, darknet-53, was developed [16]. as the name suggests, darknet-53 has 53 convolutional layers and uses the resnet structure to solve the vanishing gradient problem. the architecture also uses feature pyramid networks (fpns) in its neck; the different sizes of these fpns improved its prediction accuracy for small targets. yolov4 [17] constitutes a leap in image recognition technology. its backbone network, denoted cspdarknet-53, is an integration of darknet-53 and cspnet. the fpn neck of yolov3 was replaced with spp and a path aggregation network in yolov4. these changes both decreased its parameter count and improved detection accuracy, greatly increasing its average precision (ap) and frames per second (fps) [11]. in this study, a version of yolov4, yolov4-tiny, was adopted to enable detection on computationally constrained hardware. fig. 1 presents an overview of the yolov4-tiny architecture, which comprises a cspdarknet53-tiny module, five convolution, batch normalization, and cbl modules, an upsampling layer, and two convolutional layers. unlike yolov4, yolov4-tiny produces two feature outputs instead of three. fig. 1 yolov4-tiny architecture the backbone of the yolov4-tiny architecture is the cspdarknet53-tiny module shown in fig. 2. this module comprises two cbl modules, three cross stage partial (csp) modules, and three max pooling modules. in contrast to yolov4, which employs the mish activation function, the cbl module in cspdarknet53-tiny uses leaky relu for improved speed and performance. to enhance the efficiency of the csp module, the original cspnet [18] from yolov4 was modified by splitting the residual block into two parts, reducing intermediate processing; the outputs are merged at the end of the module shown in fig. 3. this approach reduces the computational cost of the network architecture while improving accuracy. advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 44 specifically, the input of the csp module is a feature map, which is dimensionally reduced through a convolutional layer to generate two feature maps. after passing through some convolutional layers, batch normalization layers, activation function layers, etc., the two feature maps are concatenated and then passed through some convolutional layers to obtain the output feature map. therefore, the csp part can be seen as a multi-layer convolutional network that can learn high-level information from the input feature map, while the residual connection can retain low-level information from the input feature map, thus effectively utilizing the information in the input feature map. fig. 2 cspdarknet53-tiny module fig. 3 csp module spp was applied in this study to enhance the model’s ability to detect objects at various scales [19]. specifically, spp facilitates feature extraction at different scales when the model is trained on images of various sizes. the proposed spp module differs from previous approaches [19] in that it connects three feature maps of the same size to the input feature map, resulting in a final feature map four times the size of the original input as shown in fig. 4. spp mainly addresses two issues related to fully connected layers. firstly, fully connected layers require fixed-size inputs, which means that when using convolutional neural networks for object recognition, the size of the input image must be fixed, limiting the model’s application range. secondly, fully connected layers require a large amount of memory, which means that when the size of the input image increases, more memory is consumed, making it impossible to train the model or run it on devices with limited memory. spp solves these problems by pooling different-sized regions to obtain a fixed-size feature vector, which can be used as the input of the fully connected layer, avoiding the aforementioned problems. in addition, spp can increase the model’s ability to extract features of different scales. this is because, through pyramid pooling, spp can extract features from regions of different sizes, thereby improving the model’s generalization ability. fig. 4 spp module fig. 5 fire module the fire module [12], comprising a squeezing part and two expansion parts, is crucial in reducing the model’s parameter count. the squeeze part is a convolutional layer with a kernel size of 1, and the expansion part comprises two convolutional layers with kernel sizes of 1 and 3 shown in fig. 5. advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 45 the following formulas represent the parameter calculation for a general convolutional layer (�����) and the fire module (���� ), respectively. ( )2 1= × + ×conv input outputr c k c (1) ( ) ( ) ( )2 2 2 1 1 31 1 1 1 1 1 1 3= × + × + × + × + × + × s e einputfirer c k s s k e s k e (2) in eq. (1), ���� is the number of channels of the current convolution input, k is the size of its kernel and �� �� is the number of channels of its output. in eq. (2), ���� is the input channel number of the fire module, ��� is the kernel size of the squeeze layer, s1 is the output channel number of the squeeze layer, and the following parts are respectively the two convolution modules of the expand layer. ��� is the kernel size of the convolution module, and e1 is its output channel number. similarly, ��� and e3 are both the kernel size and output channel number. the customized yolov4-tiny architecture comprised the cspdarknet53-tiny module, cbl modules, upsampling layer, and convolutional layers. the cbl module is mainly composed of a convolution layer, batch normalization, and an excitation function. the operation of the convolution layer mainly has the parameters, including convolution kernel size, stride, and padding, to determine the operation of the convolution and the control feature map. in the convolution operation, by setting these parameters, the size, shape, depth, and other attributes of the output feature map can be controlled, so that the convolution layer can perform feature extraction and feature mapping of different sizes and directions on the input image. the modified spp module and fire module were also included to improve feature extraction and reduce the model’s parameter count. to evaluate the effectiveness of these modifications, the proposed model and vanilla yolov4-tiny were trained on the pascal voc 2012 dataset and compared against each other. 3. system structure the yolov4-tiny architecture was modified to reduce the complexity of the cbl module. however, reducing parameters in the critical backbone of cspdarknet53-tiny may reduce the accuracy of the model. according to fang et al. [20], the cbl module following cspdarknet53-tiny was replaced with an appropriate number of fire modules. eqs. (1)-(2) can be used to calculate the parameter counts of the cbl module and the modified fire modules; the results for various modifications are presented in table 1. table 1 reveals that the fire module reduced the number of parameters more for convolutional layers with more input channels. consequently, two cbl modules were replaced with three fire modules, and the cbl modules preceding the final output were replaced with two fire modules, reducing the parameter count by a factor of 5.8. this reduction in parameters reduces accuracy; however, additional modules could be introduced to improve the model’s multiscale feature extraction capabilities. therefore, in reference to prasetyo et al. [21], an spp module was included after the fire3 module to improve training stability for multisize training images. table 1 parameters for various cbl and fire module configurations and input/output channels input/output cbl fire module 512/512 2359808 197184 512/256 131328 57632 256/256 49440 256/512 1180160 180800 256/256 197184 384/256 884992 53536 256/256 49440 total 4556288 785216 advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 46 the integrated definition for function modeling (idef) methodology is widely used in software development; idef0 was designed explicitly for functional modeling [22]. idef0 uses visual graphics and structured methods to describe the entire system, which can concisely and quickly understand the purpose and process of the system, effectively avoiding the use of excessive text descriptions and complicating the narrative. fig. 6 presents an idef0 diagram that visually represents the key components of the proposed system architecture. in the image processing (a1) module, the images in the data set need to be pre-processed, including resizing and converting the image to grayscale for subsequent feature extraction and model training. fig. 7 presents a diagram of the image processing and result presentation component, and fig. 8 displays the modified yolov4-tiny architecture. fig. 6 idef0 for the image detection and information display system fig. 7 idef0 for image processing fig. 8 idef0 for the improved yolov4-tiny network architecture in summary, some cbl modules in yolov4-tiny were replaced with fire modules to reduce their size and computational complexity; spp was then incorporated to improve accuracy when training on images of different sizes. the idef0 diagram visually representing the image processing and information presentation components comprising the system architecture was also presented. 4. experimental results this section presents the experiments’ results to evaluate the proposed approach. the experiments were performed using an rtx 3060 ti gpu with cuda 11.3, significantly accelerating the training process. detailed system configurations used in the experiments are provided in table 2. advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 47 table 2 experiment types of equipment and system configurations components specification operating system windows 10 gpu nvidia geforce rtx 3060 ti cpu amd ryzen 9 5900x 12-core memory 32gb cuda 11.3 the metrics for evaluating image recognition performance were precision, recall, and f1-score; these can be calculated from the confusion matrix. the confusion matrix is a representation of the correspondence between the actual and predicted labels of the input data as shown in table 3. table 3 confusion matrix true false true true positive (tp) false negative (fn) false false positive (fp) true negative (tn) the other metrics can be calculated from the confusion matrix, precission + = tp tp fp (3) recall = + tp tp fn (4) 2 precission recall f1-score precission recall × × = + (5) eqs. (3)-(5) were applied to evaluate the performance of the modified and unmodified models. the modified model was called yolov4-tinyx1. the models were trained on the pascal voc 2012 dataset, which has 20 object categories. yolov4tinyx1 achieved higher precision than yolov4-tiny in each category presented in table 4 but generally low recall presented in table 5. table 4 precision of yolov4-tiny and yolov4-tinyx1 yolov4-tinyx1 yolov4-tiny aeroplane 95.77% 90.48% bicycle 74.42% 71.74% bird 82.50% 72.86% boat 78.38% 77.42% bottle 63.64% 72.73% bus 90.48% 81.63% car 81.36% 81.30% cat 82.18% 79.63% chair 64.29% 60.00% cow 73.08% 65.62% dining table 94.12% 73.91% dog 77.24% 71.97% horse 70.27% 68.57% motorbike 76.32% 75.68% person 82.33% 81.43% pottedplant 67.86% 64.29% sheep 78.43% 78.00% sofa 78.95% 75.00% train 91.11% 86.96% table 5 recall of yolov4-tiny and yolov4-tinyx1 yolov4-tinyx1 yolov4-tiny aeroplane 66.02% 73.79% bicycle 43.24% 44.59% bird 43.14% 33.33% boat 30.85% 25.53% bottle 11.97% 13.68% bus 70.37% 74.07% car 45.28% 47.17% cat 61.03% 63.24% chair 23.38% 22.08% cow 38.78% 42.86% dining table 21.62% 22.97% dog 62.91% 62.91% horse 35.14% 32.43% motorbike 50.88% 49.12% person 58.30% 60.08% pottedplant 20.43% 19.35% sheep 57.97% 56.52% sofa 29.41% 23.53% train 60.29% 58.82% advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 48 the yolov4-tinyx1 also outperforms yolov4-tiny in terms of f1-score in several categories presented in table 6. the mean ap (map) of the models was also compared with an intersection over the union threshold of 0.5. table 7 reveals that the training map of the yolov4-tinyx1 (57.03%) was superior to that of yolov4-tiny (52.93%); its testing map was also approximately 1.59% higher. the proposed model also achieved a lower giga floating point operations (gflops) score, parameter count, and total size than yolov4-tiny, indicating that it was more efficient in terms of every metric. table 6 f1-score of yolov4-tiny and yolov4-tinyx1 yolov4-tinyx1 yolov4-tiny aeroplane 78% 81% bicycle 55% 55% bird 57% 46% boat 44% 38% bottle 20% 23% bus 79% 78% car 58% 60% cat 70% 70% chair 34% 32% cow 51% 52% dining table 35% 35% dog 69% 67% horse 47% 44% motorbike 61% 60% person 68% 69% potted plant 31% 30% sheep 67% 66% sofa 43% 36% train 73% 70% table 7 overall results of yolov4-tiny and yolov4-tinyx1 yolov4-tinyx1 yolov4-tiny train map 57.03% 52.93% test map 57.73% 56.14% gflops (g) 4.770 6.836 total params (m) 2.107 5.876 params size (mb) 8.04 22.42 these experimental results validate the effectiveness of the proposed modified architecture; it not only achieved higher precision, recall, and f1 scores in many or all categories but also higher map. it also had lower overall computational requirements and fewer parameters in every performance metric. hence, despite its simpler architecture, the model was competitive with yolov4-tiny. in summary, the experimental results substantiate the efficacy of the proposed modifications to yolov4-tiny. the achieved precision, recall, and map improvements highlight the proposed model’s enhanced object detection capabilities. the reduction in computational costs, parameter size, and gflops demonstrate the efficiency of the modified architecture. 5. conclusions a modified yolov4-tiny architecture was developed by incorporating fire and spp modules to replace some cbl modules, greatly reducing the parameter count while maintaining competitive performance. including the spp module enhanced feature extraction across different scales. in experiments, the modified architecture achieved training and testing maps that were 4.1% and 1.59% higher, respectively, than the unmodified yolov4-tiny architecture. these findings indicate that the proposed approach can achieve a superior trade-off between accuracy and computational cost relative to the original network; hence, it is a compelling solution for efficient object detection on resource-constrained devices, such as autonomous driving, surveillance systems, and other mobile applications with edge devices. future studies could further optimize the network by integrating additional lightweight modules or investigating alternative techniques to enhance computational efficiency while preserving accuracy. additionally, the performance of the modified model could be evaluated on diverse datasets, and its scalability for larger applications could be assessed. advances in technology innovation, vol. 9, no. 1, 2024, pp. 42-49 49 conflicts of interest the authors declare no conflict of interest. references [1] m. s. b. hossain, j. dranetz, h. choi, and z. guo, “deepbbwae-net: a cnn-rnn based deep superlearner for estimating lower extremity sagittal plane joint kinematics using shoe-mounted imu sensors in daily living,” ieee journal of biomedical and health informatics, vol. 26, no. 8, pp. 3906-3917, august 2022. 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[22] j. s. sheu and c. y. han, “combining cloud computing and artificial intelligence scene recognition in real-time environment image planning walkable area,” advances in technology innovation, vol. 5 no. 1, pp. 10-17, january 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx classification of leftover shrimp feed based on lift net design utilizing the k-nearest neighbors algorithm ahmad hannan asy-syaf’ie1, agus indra gunawan1,*, setiawardhana2 , muhammad edy hidayat3, muhammad andi kurniawan4 1department of electrical engineering, politeknik electronika negeri surabaya, surabaya, indonesia 2department of informatic and computer engineering, politeknik electronika negeri surabaya, surabaya, indonesia 3departement of mechatronics engineering, politeknik bosowa, makassar, indonesia 4pt. lumbung nusantara nastiti, lampung, indonesia received 30 april 2025; received in revised form 04 september 2025; accepted 10 september 2025 doi: https://doi.org/10.46604/aiti.2024.15095 abstract an effective feeding management system (fms) is crucial in shrimp farming, as both overfeeding and underfeeding can adversely affect shrimp growth. to ensure optimal nutrition, an accurate fms must account for factors such as shrimp size, weight, age, and leftover feed. this study presents a method for detecting leftover shrimp feed using custom-designed lift nets equipped with paired ultrasonic sensors. two critical aspects are examined: the optimal timing for measurement and the ideal placement of the transmitter. results show that measurements should be taken within 10 minutes of feed immersion to avoid feed disintegration. additionally, placing the transmitter on the outer side of the lift net improves measurement accuracy. ultrasonic echoes are analyzed to classify leftover feed using the k-nearest neighbors algorithm. root mean square voltage-based classification effectively groups leftover feed into five classes, highlighting its potential to improve aquaculture feed management. keywords: feeding management, ultrasonic, k-nn, shrimp, aquaculture 1. introduction shrimp farming represents a promising strategy for enhancing food security in indonesia [1], with vannamei shrimp being the most widely cultivated species [2-5]. reports from the regional marine and fisheries department show that 70-80% of farms still rely on traditional methods, creating opportunities to shift toward more intensive and efficient systems. the transformation toward modernized aquaculture requires technology integration and skilled farmers supported by data-driven decision-making. a crucial element is the feeding management system (fms), which regulates feed quantity based on shrimp species, size, age, population density, and environmental conditions [6-8]. proper feeding prevents stunted growth, waste, and environmental degradation. conventional methods often face challenges in accurately identifying leftover feed, as manual methods are subjective and imprecise. therefore, the ability to detect feeding imbalances by analyzing leftover feed is essential for improving the effectiveness of fms in modern shrimp aquaculture. traditionally, shrimp farmers place 0.5%-1% of the total feed into a lift net and check leftover feed after a few minutes. but this process is inefficient and prone to error. studies on the detection of leftover shrimp feed in pellet form using image processing techniques were conducted in 2021 and 2023 [9-10]. this approach is feasible due to the floating position of the leftover feed, which enables visual capture using a camera, followed by computational image processing. in the same year [11], quantification of leftover shrimp feed in the * corresponding author. e-mail address: agus_ig@pens.ac.id advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 2 form of sinking pellets was also undertaken. in this case, the camera was able to detect the submerged feed due to the clear water conditions in the cultivation pond. in the context of detecting leftover feed in shrimp ponds, neither of the aforementioned conditions is ideal. shrimp ponds typically exhibit turbid water characteristics, and the coloration of the water often closely resembles that of pellet feed. these factors significantly reduce the accuracy of camera-based detection methods for identifying leftover shrimp feed. this limitation highlights the need for alternative sensing approaches capable of operating effectively under such challenging optical conditions. ultrasonic technology presents a promising solution, offering measurement capabilities that can address multi-layer material detection through wave penetration, even in opaque environments [12-14]. the echo signals generated from ultrasonic wave reflections can be processed and reconstructed to yield meaningful detection outputs. based on the advantages of ultrasonic technology, the present study proposes the digitization of lift nets by redesigning their structure and incorporating multiple ultrasonic sensors. by leveraging ultrasonic wave propagation through water to detect the surfaces of solid materials (i.e., leftover feed), the system processes and classifies echo signals of ultrasonic waves to quantify the amount of uneaten shrimp feed. this approach is expected to overcome the limitations of optical detection methods. this study proposes several lift net designs and identified the most optimal one for classifying leftover shrimp feed within the net. the classification of this residue is carried out using the k-nearest neighbors (k-nn) method. in the preliminary study, research was conducted under controlled laboratory conditions, which does not fully express the complexities of the actual operational environment. consequently, certain environmental factors such as water speed and turbidity, and the existence of shrimp inside the liftnet are not incorporated into the study. these limitations may affect the direct applicability of the results to real-world scenarios. therefore, future research should focus on validating the proposed system under actual field conditions to ensure its effectiveness and robustness in practical aquaculture operations. 2. materials and configuration this section describes the materials and components used in the proposed system. these include shrimp feed, ultrasonic sensors, conventional lift nets, and electronic components. a detailed explanation is also provided for the custom-designed lift net, which replaces the function of traditional lift nets in this system. 2.1. shrimp feed to promote optimal shrimp growth, artificial feed with high nutritional value is essential to ensure rapid and healthy shrimp growth. fig. 1 displays one of the commercial shrimp feeds used in this study. from left to right, it shows 3s as a small type, 3m as a medium type, and 3l as a large type. the feed is pelletized, with sizes varying according to the shrimp’s age and size. as the shrimp mature, the pellet size is adjusted to accommodate their growth. fig. 1 shrimp feed advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 3 2.2. ultrasonic sensor ultrasonic sensors generate high-frequency mechanical waves above 20 khz and are widely used in applications such as distance measurement, cleaning, industrial automation, and medical diagnostics [15-18]. distance measurement with ultrasonic sensors can be conducted using either reflection or transmission methods. in the reflection method, a single piezoelectric transducer emits ultrasonic waves, which are reflected by a target object and received by the same or a different transducer. in the transmission method, two transducers are used—one as a transmitter and the other as a receiver—positioned directly opposite each other. fig. 2 shows the waterproof ultrasonic sensors used in this study. fig. 2 waterproof ultrasonic sensors 2.3. lift net the lift net, illustrated in fig. 3, also known as anco (in indonesia), is widely used in shrimp farming to monitor shrimp growth and manage feed. typically shaped as a square or circular lift net, it is mounted on a rust-resistant frame made of stainless steel or bamboo. although simple in design, the lift net plays a critical role in modern shrimp farming. its consistent use contributes to successful harvests and optimal production. fig. 3 conventional lift net in this study, the conventional lift net was digitized while retaining its core function of monitoring leftover feed. to determine the most effective design for feed detection, four models were compared and fabricated using 3d printing with pla material, as shown in fig. 4. each structure underwent sealing and painting, while the bottom was modified by attaching a mesh to prevent feed loss. fig. 4(a) and 4(b) represent conical-shaped lift nets, while fig. 4(c) and 4(d) represent pyramidshaped designs. (a) conical 5 cm (b) conical 10 cm (c) pyramid 5 cm (d) pyramid 10 cm fig. 4 portable lift net prototypes advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 4 to facilitate feed measurement, nine pairs of ultrasonic sensors were mounted on the top section of the lift net. each pair consists of one transmitter and one receiver. the sensors are strategically positioned as follows: one pair at the pos-1 (shown by number 9), four pairs at the pos-2 region (shown by numbers 5, 6, 7, and 8), and four pairs at the pos-3 (shown by numbers 1, 2, 3, and 4), as illustrated in fig. 5. fig. 5 sensor placement on the lift net 2.4. electronic module the electronic module of the system is depicted in fig. 6. this section comprises a power supply unit, amplifier, relays, a microcontroller, and ports for connecting the electronic module to the ultrasonic sensors at the lift net. a 35 khz acoustic signal is generated by the microcontroller, and then it is amplified before being transmitted to the ultrasonic sensors. the microcontroller also controls which sensors are active by switching the corresponding relays on and off. with this control mechanism, the ultrasonic sensors work alternately, thereby reducing echo signal interference between sensors. fig. 6 electronic components 3. research methodology this chapter outlines the research methodology, including the proposed system, the measurement concept, and the classification method. the proposed system, comprising the electronic components and lift net, is described in detail. additionally, this section explains how the measurements are set up, how echo signals are acquired and processed, and how the data is analyzed using the k-nn algorithm. 3.1. the proposed system fig. 7(a) illustrates the proposed system comprising an electronic module, a lift net, and ultrasonic sensors, while fig. 7(b) shows its block diagram. during the measurement process, the ultrasonic sensors, liftnet, and feed are immersed in water. in the hardware section, a microcontroller generates a 35 khz signal for the transmitter (tx), which converts it into an acoustic signal. the microcontroller also selects the active pair of ultrasonic sensors to work alternately to minimize echo interference. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 5 this acoustic signal travels through the water until it reaches the feed or the lift net frame and is received by the receiver (rx), which converts it back into an electrical signal. these signals are then acquired by the microcontroller and processed on a computer. (a) overall system (b) block diagram system fig. 7 the proposed system 3.2. measurement method the classification of leftover shrimp feed is based on the analysis of echo signals. the echo signals provide two parameters: time of flight (tof) and signal magnitude, which is represented in voltage. fig. 8(a) illustrates the measurement of onedimensional space using these parameters. when a trigger signal is emitted by the transmitter ultrasonic sensor, the receiver ultrasonic sensor detects the returning echo. the blue echo (echoblue) refers to the signal reflected from the surface of the feed. it provides the time of flight for the blue echo signal (tofblue) and its magnitude, measured using root mean squared (rms) and peak-to-peak voltage. the red echo (echored) is the signal reflected from the lift net frame, serving as a reference. it provides (tofred) and its respective magnitude values as well. once both (tofred) and (tofblue) are known, the distance (d) can be calculated using the difference between d₂ and d₁, as defined in eq. (1) through eq. (3). 2 2 =  redtof d c (1) 1 2 bluetof d c=  (2) 2 1d d d= − (3) where c is the acoustic speed in the water. in this study, both time of flight (tof) and signal magnitude were evaluated in terms of voltage measurements. two modes of voltage representation were applied: peak-to-peak [19] and rms [20]. each of these modes provides specific strengths and limitations in the context of material characterization [21]. the peak-to-peak measurement reflects the voltage span between the maximum positive and negative signal excursions, thereby emphasizing the full dynamic range of the echo response. on the other hand, the rms measurement represents the effective voltage, defined as the dc-equivalent value that produces the same average power dissipation across a load, and is therefore often considered more robust for energy-related analysis. the formula of rms voltage is shown in eq. (4). 𝑉𝑟𝑚𝑠 = √ 1 𝑇 ∫ 𝑣(𝑡)2 𝑑𝑡 𝑇 0 (4) where 𝑣(𝑡) is the instantaneous voltage as a function of time, and 𝑇 is the period of the signal. the squared voltage values are integrated over one complete cycle and then averaged by dividing by 𝑇. finally, the square root is applied to obtain the rms value. this calculation provides the effective voltage of an ac signal, which is equivalent to the dc voltage that would deliver the same power to a resistive load. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 6 (a) measurement concept (b) transmitter (tx) placement fig. 8 measuring the lift net frame as a reference signal the tof was used to compare two transmitter positions: inner and outer side positions using an empty lift net, as shown in fig. 8(b). alternatively, the one-dimensional space (d) can be estimated from the echoblue magnitude, where smaller values indicate longer travel distances. thus, either the tof or the voltage magnitude approach can be used to calculate or predict (d). once the echo signal is obtained, it’s processed by extracting features such as rms and peak-to-peak voltage, and then used for classification and comparison using the k-nn algorithm. 3.3. classification method measurements were carried out for five different feed quantities: 0 g, 50 g, 100 g, 150 g, and 200 g. in the initial phase, data acquisition was conducted in an aquarium to record echo signals from leftover feed placed in the lift net under simplified conditions, excluding turbidity, flow dynamics, and shrimp presence, as shown in fig. 9. the feed was placed inside the lift net and submerged in water. in this study, each feed sample had a flat and circularly symmetric shape, and all experiments were conducted under ideal conditions in an aquarium (water tank), free from external disturbances. fig. 9 illustration of an experiment in an aquarium the classification process was performed using the k-nn algorithm [22-24], which classifies the leftover feed into five categories based on the amount of leftover in the portable lift net. k-nn was chosen because it is simple, easy to implement, and suitable for small data sets [25]. a study comparing enhanced svm and k-nn for iot-based human activity recognition showed that k-nn achieved a higher average accuracy (97.08%) than svm (95.88%) [26]. in this study, k-nn algorithm uses three input parameters to produce one output: the classification of leftover feed in the lift net. the sensor at the pos-1 is represented by the z-axis, sensors in the pos-2 are represented by the y-axis, and sensors on the pos-3 side are represented by the x-axis. distance in the k-nn (dknn) can be calculated by using the euclidean method, as shown by eq. (5): 2 2 2( ) ( ) ( )knn n x n y n zd x a y a z a= − + − + − (5) where xn, yn, and zn are the attributes of the training data (learning data), and ax, ay, and az are the attributes of the test data. the distance (dknn) represents the distance between a test data point and one point in the training dataset. the distance calculation advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 7 is repeated for all available training data. the value of k in the k-nn algorithm influences the probability that a particular class will be selected as the final classification result. it determines how many of the closest data points are considered when estimating the class of a test sample. 4. results and discussion this chapter presents the results and discussion of the measurements, including the condition of the feed when submerged in water, sensor position analysis, and feed measurement in the lift net using four different types of lift nets. the analysis is performed using the k-nn algorithm. the objective is to determine the most suitable lift net model for measuring the leftover shrimp feed. 4.1. shrimp feed dissolution time in water in this study, dissolution times for three shrimp feed types (3s, 3m, 3l) were measured (fig. 1), as feed gradually dissolves depending on its type and composition. once the dissolution time was determined, all measurements were conducted within the determined dissolution time to ensure accuracy, using locally available feed. experiments assumed that zero water flow and no shrimp were present in the lift net, so there was no need to differentiate echo signals from the feed and those from shrimp. experiments were conducted under two conditions: still water and moving water. observations were recorded every five minutes, up to a maximum of 30 minutes. (a) 1 minute (b) 15 minutes (c) 30 minutes fig. 10 shrimp feed (3l) condition over time table 1 shows the condition of each shrimp feed type in water (sturdy, rather sturdy, and fragile) over time, indicating that leftover feed measurements are best conducted within 10 minutes before degradation to the “rather sturdy” condition. fig. 10 shows 3l shrimp feed after immersion in still water. sturdy condition is shown in fig. 10(a) after 1 minute immersion, and rather sturdy and fragile conditions are shown in fig. 10(b) and fig. 10(c) after 15 minutes and 30 minutes immersion, respectively. still water was used to ensure image clarity, avoiding turbidity from water movement. table 1 shrimp feed condition over time shrimp feed size water condition feed condition (minutes) sturdy rather sturdy fragile 3s still 0-15 15-25 >25 moving 0-10 10-20 >20 3m still 0-20 20-25 >25 moving 0-15 15-20 >20 3l still 0-25 25-30 >30 moving 0-20 20-30 >30 4.2. sensor position analysis this section presents additional experiments to determine distance information based on echo signals with the lift net empty. as shown in fig. 8, two transmitter (tx) positions were tested: one placed on the outer side (farther from the center of the lift net) and one placed on the inner side (closer to the center). only pos-2 and pos-3 ultrasonic sensor regions were used, advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 8 since pos-1 is equidistant from tx and rx and thus unaffected by transmitter placement. to determine the distance between the sensor surface and the lift net frame, eq. (1) was used, with c, the speed of sound in freshwater, approximated at 1480 m/s. the experimental results are presented in table 2. table 2 comparison of distance measurement results transmitter position portable lift net type/height sensor position actual distance (cm) calculated distance (cm) % error inner side conical/ 5cm pos-2 4.8 5.426124 13.04 pos-3 2.8 3.206346 14.51 conical/ 10cm pos-2 9.2 9.86568 7.23 pos-3 5 5.426124 8.52 pyramid/ 5cm pos-2 4.8 5.179482 7.90 pos-3 2.8 3.69963 32.12 pyramid/ 10cm pos-2 9.2 10.112322 9.91 pos-3 5 5.672766 13.45 outer side conical/ 5cm pos-2 4.8 4.93284 2.76 pos-3 2.8 2.713062 3.10 conical/ 10cm pos-2 9.2 9.125754 0.80 pos-3 5 4.93284 1.34 pyramid/ 5cm pos-2 4.8 4.686198 2.37 pos-3 2.8 3.452988 23.32 pyramid/ 10cm pos-2 9.2 9.619038 4.55 pos-3 5 5.179482 3.58 in ultrasonic propagation, the near and far fields influence wave behavior, which is critical for sensing leftover feed or the lift net frame. however, since the diameter of the sensor is 10 mm and the wavelength (λ) is 37 mm, it means the diameter of an ultrasonic sensor is less than or equal to λ, causing diffraction and near-omnidirectional beam spread. in this scenario, the relatively small aperture leads to significant beam divergence, causing the ultrasound waves to propagate widely in all directions [27-28]. this omnidirectional behavior is further influenced by the relationship between wavelength and frequency, where longer wavelengths contribute to a broader beam spread. as shown in table 2, placing the transmitter on the outer side yields more accurate measurements than the inner side. these results are also visualized in fig. 11. among all configurations, the conical-shaped lift net (5 cm and 10 cm height) provides the highest measurement accuracy. from the measurement, the 5 cm conical-shaped lift net showed an error of 2.76% at post-2 and 3.10% at post-3. meanwhile, the 10 cm conical-shaped lift net achieved a lower error of 0.8% at post-2 and 1.34% at post-3. fig. 11 comparison of measurement errors according to fig. 12, the lift net frame is represented by the solid black line, ultrasonic propagation by blue and red lines, and the normal line by the red dashed line, which is perpendicular to the lift net frame. as illustrated in fig. 12(a) and fig. 12(b), it can be seen that when the transmitter is positioned at the inner side, the frame tilt directs the signal away from the receiver and makes it more difficult to detect, resulting in weaker detection. conversely, as shown in fig. 12(c) and fig. 12(d), positioning the transmitter on the outer side directs the signal toward the receiver, as shown by solid red lines. thereby, this configuration improves measurement accuracy. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 9 additionally, a comparison between the conical-shaped and pyramid-shaped lift net designs in fig. 11 reveals that the conical-shaped lift net achieves higher measurement accuracy. this advantage is attributed to the conical-shaped frame’s ability to concentrate the echo signals, producing stronger received signals and enhancing resistance to noise disturbances. (a) inner side for 5 cm (b) inner side for 10 cm (c) outer side for 5 cm (d) outer side for 10 cm fig. 12 propagation analysis of ultrasonic signal based on transmitter position. 4.3. shrimp feed measurement inside the lift net this section presents the results of shrimp feed measurements conducted inside four different lift nets: a conical-shaped net with heights of 5 cm and 10 cm, and a pyramid-shaped net with heights of 5 cm and 10 cm. for each lift net type, five feed weight classes were defined as references for the leftover feed inside the lift net: 0 g, 50 g, 100 g, 150 g, and 200 g. a total of 125 measurements were performed, with 100 data points used for training and 25 data points used for validation. when an ultrasonic signal is emitted by the transmitter, it propagates through the water, reflects off the shrimp feed, and is received by the receiver ultrasonic sensor. the resulting echo is analyzed based on rms voltage and peak-to-peak voltage. in this study, four k values (1, 3, 5, and 7) are used to obtain the most suitable for the accuracy of classification. fig. 13 data plot from measurement using a 5 cm conical-shaped lift net fig. 13 shows a plot of the data from measurements using a 5 cm conical-shaped lift net. to assess the success of the classification, 25 new data points based on measurements were tested using eq. (5). the results of this test are presented in table 3. table 3 rms and peak-to-peak voltage measurements using a 5 cm conical-shaped lift net class rms voltage peak -peak voltage 0 g all k values are correct all k values are correct 50 g all k values are correct all k values are correct 100 g all k values are correct all k values are correct 150 g all k values are correct all k values are correct 200 g all k values are correct all k values are correct similarly, the data plots obtained from experimental measurements using the 10 cm conical-shaped lift net, the 5 cm pyramid-shaped lift net, and the 10 cm pyramid-shaped lift net are clearly presented and compared in figs. 14-16, respectively. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 10 fig. 14 data plot from measurements using a 10 cm conical-shaped lift net fig. 15 data plot from measurements using a 5 cm pyramid-shaped lift net fig. 16 data plot from measurements using a 10 cm pyramid-shaped lift net once the classification based on weight was completed, testing was conducted using new data. the results of these tests are sequentially presented in tables 4-6, which show the test outcomes for a 10 cm conical-shaped lift net, a 5 cm pyramidshaped lift net, and a 10 cm pyramid-shaped lift net, respectively. table 4 rms and peak-to-peak voltage measurements using a 10 cm conical-shaped lift net class rms voltage peak-to-peak voltage 0 g all k values are correct all k values are correct 50 g all k values are correct for k = 3, 1 neighbor is false for k = 5, 3 neighbors are false for k = 7, 4 neighbors are false 100 g all k values are correct all k values are correct 150 g all k values are correct all k values are correct 200 g all k values are correct all k values are correct advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 11 table 5 rms and peak-to-peak voltage measurements using a 5 cm pyramid-shaped lift net class rms voltage peak-to-peak voltage 0 g all k values are correct all k values are correct 50 g all k values are correct all k values are correct 100 g all k values are correct all k values are correct 150 g all k values are correct all k values are correct 200 g all k values are correct all k values are correct table 6 rms and peak-to-peak voltage measurements using a 10 cm pyramid-shaped lift net class rms voltage peak-to-peak voltage 0 g all k values are correct all k values are correct 50 g all k values are correct all k values are correct 100 g all k values are correct all k values are correct 150 g all k values are correct all k values are correct 200 g all k values are correct all k values are correct based on the classification results from the voltage plots, both the rms and peak-to-peak voltage, the 5 cm lift net provides better classification accuracy. this is evident from the plots, where the leftover feed for 5 weight classes forms distinct groups based on weight. the deviation within each group is minimal, reducing the potential for overlap. conversely, for the 10 cm lift net, the leftover feed for 5 weight classes tends to cluster more closely together. although the deviation within each group remains insignificant, the shorter distance between classes results in reduced classification accuracy, particularly when measurement issues, such as noise interference, occur. this can be observed in table 4, where some inaccuracies were noted in the measurements for the 10 cm conical-shaped lift net, particularly with peak-to-peak voltage. fig. 17 results of leftover feed classification using rms voltage for 5 cm and 10 cm conical-shaped lift nets based on these results, the subsequent discussion will be focused on the measurement result using rms voltage only. as shown in subchapter 4.2, the transmitter positioned on the outer side outperforms the inner-side configuration, while the conical-shaped design of the lift net shows superior performance compared to the pyramid-shaped design. moreover, the 10 cm conical-shaped lift net achieved higher accuracy than the 5 cm variant. interestingly, these results appear to contrast with the k-nn classification presented in subchapter 4.3, where the 5 cm conical-shaped lift net was shown to perform better than the 10 cm conical-shaped lift net. this argument is reinforced by the results shown in fig. 17, where the k-nn classification using the 5 cm conical-shaped lift net demonstrates smaller deviations and greater inter-class separation compared to the 10 cm conical-shaped lift net. these characteristics imply that the classification errors with the 5 cm conical-shaped lift net are lower, therefore yielding higher accuracy than the 10 cm conical-shaped lift net. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 12 4.4. model evaluation to strengthen the previous analysis, model evaluation was carried out using additional datasets for the 5 cm and 10 cm conical-shaped lift nets, focusing on the rms voltage feature. the evaluation is presented in the form of classification reports and confusion matrices to demonstrate the classification performance of both models. results of the classification report for the 5 cm conical-shaped lift net are shown in table 7. table 7 classification report for 5 cm conical-shaped lift net using rms voltage class precision recall f1-score support 0 g 1.00 1.00 1.00 7 50 g 1.00 0.82 0.90 11 100 g 0.85 1.00 0.92 11 150 g 1.00 1.00 1.00 15 200 g 1.00 1.00 1.00 6 accuracy 0.96 50 macro avg 0.97 0.96 0.96 50 weighted avg 0.97 0.96 0.96 50 the results show that classification using the 5 cm conical-shaped lift net achieved an accuracy of 96%, with precision, recall, and f1-scores above 0.82 across all classes, with very few misclassifications, mainly occurring in the 50 g classes. the results of the classification report for the 10 cm conical-shaped lift net are shown in table 8. from these two tables, it can be seen that the performance of the 5 cm conical-shaped lift net is better than that of the 10 cm conical-shaped lift net. table 8 classification report for 10 cm conical-shaped lift net using rms voltage class precision recall f1-score support 0 g 1.00 1.00 1.00 7 50 g 0.90 0.82 0.86 11 100 g 0.83 0.91 0.87 11 150 g 1.00 1.00 1.00 15 200 g 1.00 1.00 1.00 6 accuracy 0.94 50 macro avg 0.95 0.95 0.95 50 weighted avg 0.94 0.94 0.94 50 this conclusion is further supported by the confusion matrix analysis in fig. 18, which consistently highlights the stronger performance of the 5 cm conical-shaped lift net. therefore, for the task of classifying leftover shrimp feed, a conical-shaped lift net with a 5 cm height is recommended. fig. 18 confusion matrix of rms voltage for 5 cm and 10 cm conical-shaped lift nets advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 13 5. conclusion this study proposes and validates an ultrasonic-based method for quantifying leftover shrimp feed in a lift net. four lift net designs were evaluated, each equipped with nine ultrasonic sensor pairs, and performance was further assessed using the k-nn classification algorithm with rms voltage as the primary feature. the results demonstrate the feasibility of integrating ultrasonic sensing into an automated feeding management system (fms). the main conclusions are as follows: (1) measurements should be conducted immediately and within 10 minutes, as feed particles become fragile and deteriorate after prolonged water immersion. (2) transmitter sensors positioned on the outer side of the lift net exhibited superior performance, particularly when the net is empty. (3) among all tested designs, the 5 cm conical-shaped lift net achieved the highest accuracy. (4) with rms voltage as the classification feature, the k-nn algorithm achieved accuracies of 96% for the 5 cm conicalshaped lift net and 94% for the 10 cm version. (5) the proposed system shows strong potential for classifying leftover feed and may serve as a foundation for integration into automated fms in shrimp aquaculture. (6) future work should compare current results with the time of flight (tof) technique or with volume estimation based on sensor positions. (7) additional experiments under turbid and flowing water conditions, along with tests involving shrimps inside the lift net, are recommended, as shrimps are likely to enter the net during feeding. acknowledgment the author would like to thank the electrical engineering for aquaculture technology research group, politeknik elektronika negeri surabaya, and pt. lumbung nusantara nastiti, for providing support in terms of instruments, equipment, and laboratory facilities during this research. conflicts of interest the authors declare no conflict of interest. references [1] s. bahri, d. mardhia, and o. saputra, “growth and graduation of vannamei shell life (litopenaeus vannamei) with feeding tray (anco) system in av 8 lim shrimp organization (lso) in sumbawa district,” jurnal biologi tropis, vol. 20, no. 2, pp. 279-289, 2020. 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[28] n. kono and s. hirose, “semi-analytical modeling of acoustic beam divergence in homogeneous anisotropic halfspaces,” ultrasonics, vol. 65, pp. 194-199, 2016. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v9n2(2024)-aiti#13355(85-98).docx advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 english language proofreader: chih-wei chang precision geolocation of medicinal plants: assessing machine learning algorithms for accuracy and efficiency maria concepcion suarez vera* college of information and communications technology, catanduanes state university, catanduanes, philippines received 06 february 2024; received in revised form 08 march 2024; accepted 09 march 2024 doi: https://doi.org/10.46604/aiti.2024.13355 abstract this study investigates the precision geolocation of medicinal plants, a critical endeavor bridging ecology, conservation, and pharmaceutical research. by employing machine learning algorithms—gradient boosting machine (gbm), random forest (rf), and support vector machine (svm)—within the cross-industry standard process for data mining (crisp-dm) framework, both the accuracy and efficiency of medicinal plant geolocation are enhanced. the assessment employs precision, recall, accuracy, and f1 score performance metrics. results reveal that svm and gbm algorithms exhibit superior performance, achieving an accuracy of 97.29%, with svm showing remarkable computational efficiency. meanwhile, despite inferior performance, rf remains competitive especially when model interpretability is required. these outcomes highlight the efficacy of svm and gbm in medicinal plant geolocation and accentuate their potential to advance environmental research, conservation strategies, and pharmaceutical explorations. the study underscores the interdisciplinary significance of accurately geolocating medicinal plants, supporting their conservation for future pharmaceutical innovation and ecological sustainability. keywords: geolocation, machine learning, medicinal plants, support vector machine, gradient boosting machine 1. introduction tracing back to ancient civilizations and extending into modern ecological conservation and pharmaceutical domains, the precise geolocation of medicinal plants is substantiative regarding the enhancement of healthcare outcomes, preserving biodiversity, and promoting sustainable development. medicinal plants, integral to the healing traditions of egyptians, chinese, indians, and other cultures, have been perpetually used to prevent, relieve, or treat illnesses. this practice, profoundly embedded in the cultural heritage of numerous communities, has been meticulously documented and passed down through generations. in the philippines, the melding of malay, spanish, and american influences enrich its traditional understanding of medicinal plants, with conventional healers such as “albularyos” or “pilot” using these plants to treat various ailments. ethnobotanical research in the philippines highlights the deep traditional knowledge of indigenous tribes, identifying the country as a critical biodiversity hotspot with around 13,000 plant species, 39% of which are endemic [1-2]. this biodiversity underpins the extensive use of 1,500 medicinal plants in traditional medicine, with significant potential recognized for contemporary pharmaceuticals. among this vast cluster of medicinal plants, 10 plants are widely recognized, 177 are earmarked for further research, and the confirmation of safety and efficacy pertains to 120 plants [3]. these insights emphasize the significance of medicinal plants in both traditional and modern healthcare contexts, showcasing their potential in pharmaceutical development. * corresponding author. e-mail address: maconsuarez@gmail.com 86 advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 the traditional geolocation methods for medicinal plants, including field surveys and basic gps mapping, have been instrumental yet exhibit a palpable defect in accuracy, efficiency, and data integration, as substantiated in faizy et al. [4]. furthermore, the paucity of integration of machine learning (ml) techniques further compounds this limitation, significantly enhancing the precision and efficiency of geolocation practices. the critical role of geolocation accuracy in scientific endeavors is underscored by halpin et al. [5], who demonstrate its influence on the retrieval of wind field data, thus affirming the necessity for refined geolocation methods across various scientific applications. additionally, the exploration of agroecological zoning models highlights the integration of climatic and edaphic parameters to optimize the growth of medicinal plants, presenting a methodological advancement in identifying potential growth areas [6]. despite the advent of applications employing advanced technologies such as crowdsourcing, image recognition, and convolutional neural networks for the identification and recognition of medicinal plants, as seen in isa et al. [7] and sugiarto et al. [8], the field remains challenged by the need for more precise and efficient geolocation methods. the utilization of geospatial database management systems and the development of augmented reality portals, as presented in puttinaovarat and horkaew [9] and permana et al. [10] respectively, indicate a technological evolution to enhance interaction with medicinal plant information. nonetheless, the enduring value of traditional knowledge, as documented in faruque et al. [11] and the ethnobotanical analysis in boycheva and ivanov [12], emphasizes the integration of such a posteriori knowledge into contemporary technological advancements. given these aforementioned considerations, this research posits a compelling argument for adopting innovative approaches that leverage the latest technological advancements to conquer the current limitations in medicinal plant geolocation. by accentuating the enhancement of precision and efficiency of geolocation techniques, the study endeavors to make significant contributions to the fields of conservation, sustainable harvesting, and pharmaceutical development, underscoring the importance of accurately mapping plant species for the protection of biodiversity, the maintenance of ecosystem balance, and the facilitation of drug discovery processes. ml algorithms have emerged as a scientifically pivotal innovation, providing the tools for in-depth analysis of intricate environmental and biological datasets. this advancement surpasses conventional methodologies by facilitating precise forecasts of the locations of medicinal plants, thereby improving geolocation accuracy and fostering new research opportunities. this research aims to enhance the accuracy of geolocating medicinal plants through a thorough analysis, evaluating the effectiveness of gradient boosting machine (gbm), random forest (rf), and support vector machine (svm) comparatively. these algorithms, each celebrated for their distinctive benefits and empirical effectiveness in various sectors, are systematically employed to address the unique challenges presented by the geolocation of medicinal plants. gbm learning techniques have demonstrated considerable success across various domains. researchers have applied gradient boosting in agriculture to predict crop yield, as mentioned in anbananthen et al. [13]. besides, researchers have employed gradient boosting in healthcare to predict adverse outcomes in pneumonia patients [14] and to forecast cardiovascular diseases [15]. these applications underscore gradient boosting’s effectiveness in achieving high prediction accuracy. moreover, gradient boosting has shown superior accuracy and prediction performance compared with other ml algorithms, like deep learning and rf [16]. rf has undergone thorough investigation and found wide application across multiple fields, such as agriculture and healthcare, attributed to its reliability and efficiency in predictive modeling. researchers have deployed rf to predict crop yields [17] and classify agriculture farm machinery [18]. these studies have demonstrated the high accuracy and precision of rf in agricultural applications, being acknowledged as valuable tools for decision support in farming and crop management. in healthcare, the rf has shown promising results in various applications, such as predicting the severity of patient falls [19] and forecasting hospital readmissions [20]. advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 87 these research findings highlight the efficacy of rf by showcasing metrics such as accuracy, precision, recall, and f1 score in a high-performing context, accentuating its value in predictive modeling and decision-making within the healthcare sector. svm, rooted in statistical learning theory, is renowned for its strong performance in diverse fields. its effectiveness spans a range of applications, from stench detection to yield prediction and complex tasks in computer science, especially spam comment screening on youtube and real-time emotion detection [21-23]. similarly, shi et al. [24] utilized svm for crop yield prediction in agriculture, achieving high accuracy. furthermore, as substantiated by suresh et al. [25], it is found that svm outperformed other ml models in diagnosing heart disease, indicating its effectiveness in healthcare prediction tasks. the study aims to achieve a twofold objective that seeks to advance the boundaries of technology within environmental science, concurrently yielding a profound impact on conservation efforts and pharmaceutical research. initially, it focuses on the rigorous evaluation and validation of ml models, i.e., gbm, rf, and svm, utilizing precise latitude and longitude data to ensure unparalleled locational accuracy. subsequently, it assesses the computational efficiency of these algorithms to determine the most resource-efficient approach. beyond the technical accomplishments, this research contributes to ecological conservation, biodiversity protection, and pharmaceutical exploration by facilitating accurate plant geolocation. such contributions sequentially support advanced conservation strategies, sustainable harvesting practices, and the investigation of plants’ medicinal properties. this dualfocused objective highlights the study’s dedication to technological innovation while underscoring its significant implications for environmental conservation and health sciences. the structure of this study unfolds as follows: the methodology, including dataset preparation, data analysis techniques, and the particular ml models employed is detailed in section 2; section 3 presents the empirical results and evaluates the performance of these models; section 4 concludes with a summary of key findings, their implications, and suggestions for future research. 2. methodology this study follows the research methodology illustrated in fig. 1, starting from understanding the study’s requirements to deploying efficient and accurate ml models for the precision geolocation of medicinal plants and adopting the cross-industry standard process for data mining (crisp-dm) framework. this practical and adaptable framework [26] boosts covid-19 diagnosis predictions [27], acts as a foundational element in ml and data science [28], and provides insights into geolocation and medicinal plant research by evaluating algorithms. phase 1: business understanding: this phase explores the importance of accurately locating medicinal plants for conservation, healthcare, and sustainable development. it aims to improve geolocation with gbm, rf, and svm algorithms, addressing the ecological research challenges and the limitations of traditional methods. the goal is to enhance conservation strategies and pharmaceutical research, expecting to advance biodiversity protection and drug discovery through precise geolocation, highlighting the study’s potential to effectively bridge data science, ecology, and pharmaceuticals. phase 2: data understanding: the work begins with the collection and familiarization of the geolocation data of medicinal plants. principal component analysis (pca) is employed in exploratory data analysis to minimize dimensionality, concurrently optimizing the dataset for ml. this step is an especially crucial factor in identifying key variables and assessing data quality, ensuring builders of subsequent phases construct them on a solid understanding of the dataset’s characteristics. 88 advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 phase 3: data preparation: this phase focused on finalizing the dataset’s structure, engaging in thorough data pre-processing, including data visualization, cleaning, handling data gaps, and managing outliers. feature engineering improves the prediction ability of models by generating new features or modifying current ones. the dataset was divided into sets for training and testing to ensure a thorough training of the model approach and enable practical performance evaluation to present new data. this preparation phase seamlessly connected data understanding with the modeling phase, establishing a robust foundation for the precise geolocation of medicinal plants through advanced ml techniques. phase 4: modeling: this phase utilizes 10-fold cross-validation to assess the effectiveness of chosen ml algorithms. this approach ensures the robustness of the evaluation and no overfitting models. furthermore, hyperparameter tuning was applied, optimizing each model’s performance. phase 5: evaluation: this phase assesses each model’s accuracy, precision, recall, and f1 score alongside computational time efficiency metrics such as training and prediction time. this comprehensive evaluation yields a thorough comparison of the models, identifying which algorithm offers the best balance of predictive accuracy and efficiency. the interpretation of results is critical at this stage, extending insights into the models’ performance and practical implications herein. phase 6: deployment: emphasizing the interpretation of results and communication to stakeholders to ensure the accessibility and feasibility of research outcomes. fig. 1 research methodology advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 89 2.1. dataset and study area the dataset, comprising 13 features detailed in table 1, was curated through interviews, focus groups, online research, and fieldwork, employing diverse sampling methods for comprehensive representation. table 2 showcases descriptive statistics from 2,212 observations on critical environmental factors crucial for evaluating ml algorithms in medicinal plant geolocation. additionally, fig. 2 visually represents the sample data from the dataset, proffering complementary insights. table 1 dataset’s feature descriptions feature description source longitude east-west position of a plant fieldwork latitude north-south position of a plant fieldwork temperature average temperature relevant to plant growth online precipitation levels influencing plant distribution and health online soil ph soil acidity or alkalinity essential for plant growth online elevation the plant’s growth environment is indicated by height above sea level online medplantname names for categorizing medicinal plant species fieldwork street the specific street number of the medicinal plant’s location. fieldwork barangay local district or division of the plant’s location. fieldwork municipality the town or city jurisdiction of the plant’s location. fieldwork province larger administrative division of the plant’s location fieldwork datecollected recording date of geolocation and environmental data fieldwork present binary indicator of the plant’s presence or absence fieldwork table 2 medicinal plants’ dataset descriptive statistics descriptive statistics latitude longitude elevation precipitation soil ph temperature ispresent valid 2212 2212 2212 2212 2212 2212 2212 missing 0 0 0 0 0 0 0 mode 13.594* 124.205* 38.000* 1.311* 55.000* 28.996* 1.000* median 13.589 124.207 38.000 1.311 55.000 28.996 1.000 mean 13.589 124.208 37.684 1.311 54.921 28.668 0.965 std. deviation 0.009 0.006 13.852 0.002 0.273 0.570 0.183 minimum 13.584 124.203 10.000 1.311 53.000 24.436 0.000 maximum 13.871 124.230 484.000 1.380 55.000 28.996 1.000 *the mode is computed assuming that variables are discreet. fig. 2 dataset’s sample data the study, underscoring the cruciality of the dataset in examining environmental impacts and refining the accuracy of ml algorithms, is centered on the locations of medicinal plants in three barangays within virac, catanduanes, philippines— i.e., calatagan proper, calatagan tibang, and sogod-tibgao bliss, as depicted in fig. 3. integrating geospatial, environmental, and local knowledge domains amplifies the dataset’s utility, laying a sturdy groundwork for leveraging ml techniques to accomplish the research objectives effectively. 90 advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 fig. 3 geolocations of medicinal plants in three barangays of virac, catanduanes 2.2. data analysis before model development, conducting a comprehensive dataset analysis is crucial. pca was an essential technique for reducing the dataset’s complexity. as depicted in fig. 4, pca condensed the vast variations within the data into new, orthogonal variables, thereby revealing significant patterns. specifically, the first principal component (pc1) accounted for 50.12% of the variance, highlighting the importance of latitude, elevation, and precipitation. these variables indicate an environmental gradient crucial for the distribution and diversity of medicinal plants, influencing their growth and characteristics. the second principal component (pc2), contributing an additional 41.17% to the variance, emphasized the roles of longitude, soil ph, and elevation, further illustrating the complex relationship between geographical and environmental factors in determining plant characteristics. together, pc1 and pc2 encapsulated 91.29% of the total variance, effectively reducing the dimensionality of the dataset while retaining the essence of the information. this reduction facilitates easier visualization, comprehension, and application in subsequent analyses or decision-making processes related to medicinal plants. fig. 4 principal component analysis (pca) results advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 91 the pca loading plot, as detailed, underscores the significance of variables like longitude, latitude, temperature, elevation, precipitation, and soil ph in defining the traits of medicinal plants. by streamlining the dataset through this efficient dimensionality reduction, the computational efficiency of the machine learning models targeting medicinal plant geolocation was significantly enhanced. this strategic leverage of pca insights during the model development phase enabled thorough empirical testing, assessing the influence of the identified principal components on the algorithms’ predictive accuracy and computational performance. this methodology not only affirmed pca’s critical role in optimizing machine learning workflows but also highlighted its importance in studies that demand a nuanced comprehension of complex, multidimensional data for the effective conservation, analysis, and sustainable utilization of medicinal plant resources. 2.3. data pre-processing for ml research, it’s indispensable to conduct data preprocessing, addressing discrepancies in coordinate formats and plant species identification for geographical and botanical precision. the study employs data cleansing outlier management alongside a 70% training and 30% testing split [29] for practical model fitting or training and evaluation. through feature engineering, environmental variables are transformed into crucial predictors, emphasizing thorough preparation to improve the precision of ml and its impact on predictive analysis. 2.4. machine learning techniques model it is necessary to select ml algorithms like gbm, rf, and svm for precisely geolocating medicinal plants, driven by their substantiated effectiveness and suitability for the dataset’s specific characteristics. researchers opt for these algorithms considering their capacity to accurately predict plant locations based on curated attributes, highlighting the importance of algorithm selection in enhancing research efficiency. 2.4.1. gradient boosting machine deploying gbm enables researchers to iteratively enhance predictions by assembling weak models into more accurate composite models drives its selection. it excels in refining predictions for complex patterns in geospatial and environmental data related to medicinal plant habitats. therefore, the strength is evident in intricate and nonlinear relationships between factors. nonetheless, the sequential and iterative nature affixed to this method requires significant computational resources, which is decisive in the efficiency objectives. still, the potential trade-off in computation time might be warranted if gbm outpaces the accuracy of other models. consequently, gbm emerges as a formidable option for accurately determining the geolocation of medicinal plants, promising to enhance the precision of plant location efforts and contribute positively to ecological conservation and pharmaceutical research. 2.4.2. random forest due to its durability and forecast accuracy, the rf algorithm is appropriate for medicinal plant location research. it outperforms binary target variables such as medicinal plant detection and delivers accurate, precise recall and f1 score outcomes. overfitting is prevented by rf’s design, which integrates predictions from many decision trees trained on various data subsets. this feature enables the model to function with versatility and reliability. the parallel processing capabilities of rf enhance computing performance, maximizing efficiency and model correctness. it manages high-dimensional data, analyzing complex environmental variables. it reduces model bias, ensuring reliable predictions for medicinal plant geolocation. rf can handle missing data and feature importance analysis, guiding conservation efforts and research by identifying essential plant localization characteristics. 92 advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 integrating rf into this study achieves accurate plant geolocation prediction aims and utilizes an approach that effectively manages computational requirements. rf is a highly reliable and beneficial method for advancing ecological conservation and pharmaceutical studies research, which is instrumental in accurately identifying the habitats of medicinal plants. 2.4.3. support vector machine svm is crucial for medicinal plant geolocation due to its exceptional classification and versatility in processing both linear and non-linear data. svm effectively finds the best hyperplane that maximizes the margin between classes, which helps identify medicinal plants in sundry geographical and environmental circumstances. svm gains robustness and can classify in high-dimensional spaces through kernel functions, like the radial basis function (rbf), polynomial, and sigmoid kernels. adaptability is needed to interpret complicated geographical and environmental data patterns and ensure medicinal plant geolocation accuracy and precision. accurate geolocation significantly underpins the success of ecological conservation efforts and pharmaceutical research in this study, which is a fact that cannot be overstated. by leveraging svm’s capabilities, the study overcomes the challenges posed by the curse of dimensionality and the need for precise categorization amidst diverse environmental factors. essentially, svm’s ability to analyze intricate environmental patterns and precisely identify medicinal plants using geographical coordinates aligns with the study objectives, providing an advanced method to enhance ecological conservation and pharmaceutical research by utilizing enhanced geolocation techniques. 2.5. performance and efficiency measures the evaluation criteria for the ml algorithms gbm, rf, and svm consist of two primary assessments: accuracy, which is crucial for making solid predictions about the locations of medicinal plants, and computational efficiency, which focuses on the training and prediction times of the algorithms. the focus lies on the imperative need for precise identification of potential habitats of medicinal plants and the significance of maximizing computing resources to guarantee the practical implementation of these models. these evaluation criteria form a critical assessment that balances geolocation accuracy with operational efficiency, thereby highlighting the approaches' usefulness and applicability for real-world scenarios. 2.5.1. performance measure accuracy is crucial for evaluating the performance of gbm, rf, and svm to predict the dataset’s medicinal geographical locations. a high degree of accuracy indicates that the model is dependable in its predictions, perceived to be valuable for researchers and conservationists to pinpoint locations where medicinal plants are probable. in this study, a model with high accuracy would effectively differentiate between locations where medicinal plants exist and locations where they do not. (%) 100% + = × + + + tp tn accuracy tp fp fn tn (1) where tp is the true positive, tn is the true negative, fp is the false positive, and fn is the false negative. precision is essential for ensuring the accuracy of prediction concerning the existence of medicinal plants in a particular location. precision is vital in conservation efforts with limited resources to focus efforts and resources on locations with medicinal plants, optimizing conservation actions and research treatments. = + tp precision tp fp (2) recall high recall is crucial for models to identify the maximum number of real medicinal plant sites accurately. a model’s high recall indicates its effectiveness in reducing false negatives, meaning it scarcely fails to identify regions where medicinal plants are found. this effectiveness is essential for thorough conservation planning and study to prevent any possible areas of interest from being missed. advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 93 = + tp recall tp fn (3) the f1 score is a numerical representation that harmonizes precision and recall, serving as a critical gauge in situations where the consequences of both false positives and false negatives are significant. when dealing with the geolocation of medicinal plants, the f1 score proffers assistance in the selection of a model equalizing between high recall (not missing probable plant locations) and high precision (not erroneously recognizing irrelevant places as holding medicinal plants). 1 2 × = × + precision recall f score precision recall (4) these metrics are particularly relevant herein in assessing the models’ precision in geolocating medicinal plants. in this task, identifying true locations (recall) and evading false identifications (precision) are equally crucial for conservation and pharmaceutical research. 2.5.2. efficiency measure computational efficiency in ml is adopted to evaluate time and resource demands for training and making predictions. it is assessed through time complexity, dataset size, and resource utilization, which measures the amount of computational resources consumed during operation. these metrics provide a comprehensive view of an algorithm’s efficiency. training and prediction times are crucial metrics for evaluating the computational efficiency of ml algorithms like gbm, rf, and svm. training time is when a model learns from a training dataset, enabling it to adjust parameters and improve accuracy. shorter training times indicate faster development and deployment. prediction time measures the model’s responsiveness to new data, especially in real-time decision-making applications. training time is a one-time cost during the learning phase, while prediction time is ongoing, affecting the model’s operational efficiency. optimizing these metrics without compromising accuracy is essential for developing accurate tools for medicinal plant geolocation. 2.6. 10-fold cross-validation implementing 10-fold cross-validation is to elevate ml models like gbm, rf, and svm validation processes. partitioning the dataset into ten equally sized segments and cyclically using these partitions for training and testing ensures an exhaustive evaluation of model performance across varied geographical and climatic conditions. such a method mitigates bias and variance to ensure model reliability and stability. consequently, this meticulous validation approach enhances the study’s methodological rigor. it contributes valuable insights into ecological conservation and pharmaceutical research, substantiating the scientific robustness and practicability of the findings in medicinal plant conservation. 2.7. hyperparameter tuning after employing 10-fold cross-validation, adjustments were made to parameters including the number of trees for gbm and rf, gbm’s tree depth, rf’s feature considerations for splits, and svm’s kernel type and regularization parameter, all aimed to optimize enhanced predictive accuracy and overfitting prevention. this approach guaranteed model robustness and accurate prediction of medicinal plant locations across varied geospatial contexts. the results of these hyperparameter tuning efforts and the corresponding mean scores from the 10-fold cross-validation are concisely presented in table 3, illustrating the systematic refinement and its impact on the models’ performance. this study utilized python libraries to enhance workflow efficiency, from data preprocessing to performance metrics analysis. the library called “scikit-learn” facilitated ml tasks, “pandas” and “numpy” managed data manipulation, and “matplotlib” and “seaborn” supported visualization. these tools enabled practical hyperparameter tuning and 10-fold cross-validation to improve result analysis and interpretation. 94 advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 table 3 results of hyperparameter tuning and the mean scores for 10-fold cross-validation model best parameters 10-fold cross-validation (mean) hyperparameter values accuracy precision recall f1 score svm c 0.1 0.9652 0.9652 1.0000 0.9823 gamma scale kernel rbf gbm learning_rate 0.01 0.9557 0.9662 0.9887 0.9771 max_depth 3 n_estimators 100 rf max_depth 10 0.9566 0.9662 0.9897 0.9776 n_estimators 500 3. results and discussion this section analyzes ml models, examining the accuracy and computational efficiency in determining medicinal plant locations. four performance metrics and two efficiency measures, as shown in table 4, were used to assess each model’s capabilities. the primary goal of this research is to investigate the efficacy of gbm, rf, and svm algorithms concerning the capability to geolocate medicinal plants using geospatial data, focusing on their precision and processing speed. table 4 summary of results in final model training and evaluation model performance measure computational efficiency (in seconds) accuracy precision recall f1 score training time prediction time svm 97.29% 97.29% 100.00% 98.63% 0.008 0.0040 gbm 97.29% 97.29% 100.00% 98.63% 0.203 0.0012 rf 96.54% 97.27% 99.23% 98.24% 1.597 0.0601 fig. 5 and fig. 6 present a graphical comparison of the performance and computational efficiency metrics across the models. this visualization highlights the impressive performance and computational efficiency of the algorithm, exhibiting proficiency in accurately determining the locations of medicinal plants. (a) comparison of accuracy among models (b) comparison of precision among models (c) comparison of recall among models (d) comparison of f1 score among models fig. 5 comparison of performance measures among models advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 95 (a) comparison of training time among models (b) comparison of prediction time among models fig. 6 model comparison of computational efficiency 3.1. comparative evaluation of the performance of models fig. 5 demonstrates the similarity reflecting on the performance levels between svm and gbm models, achieving 97.29% accuracy and precision, a 100.00% recall rate, and a 98.63% f1 score. these metrics underscore the exceptional proficiency of both the svm and gbm algorithms in accurately detecting the presence of medicinal plants, ensuring a high success rate in correct identifications while minimizing false positives. on the other hand, while slightly trailing, the rf model manifests robust performance, achieving 96.54% in accuracy, 97.27% in precision, 99.23% in recall, and 98.24% in the f1 score. despite a subtle decrease in performance metrics compared to svm and gbm, the rf model maintains its status with convincing competitiveness, exhibiting considerable efficiency and reliability in medicinal plant geolocation. svm and gbm algorithms evinced superior, closely matched performance suitable for ecological conservation and pharmaceutical research, highlighted by perfect recall rates critical for comprehensive geographical mapping. the dataset’s traits, dimensionality reduction, hyperparameter choices, or the binary classification nature could result in fluctuation in the performance. these findings indicate that exploring different configurations might reveal nuanced performance differences, guiding future research to enhance medicinal plant geolocation precision. despite displaying slightly lower performance metrics, the rf model is a robust contender, attesting to considerable accuracy and precision in identifying medicinal plant locations. compared to svm and gbm, its marginally lower recall rate insignificantly detracts from its utility, especially in scenarios where model interpretability and the capability to navigate complex data structures are paramount. highlighting rf’s utility underscores the necessity of selecting the most fitting ml algorithm to satisfy the unique demands of a project, thus ensuring the advancement of medicinal plant geolocation in both efficiency and accuracy. 3.2. comparative evaluation of computational efficiency of models this study assessed the computational efficiency by analyzing the training and prediction times. as detailed in fig. 6, the svm showed exceptional efficiency, with a training time of 0.008 seconds and a prediction time of 0.004 seconds, which is perceived as the quickest model among those evaluated. the gbm demonstrated exceptional efficiency during training, completing in 0.203 seconds and having an even more remarkable prediction time of 0.0012 seconds, the fastest of the three methods. the rf model had the most significant training time of 1.597 seconds and a prediction time of 0.060 seconds, signifying lesser performance than other models but still viable for many applications. 96 advances in technology innovation, vol. 9, no. 2, 2024, pp. 85-98 this study’s evaluation of svm, gbm, and rf algorithms for medicinal plant geolocation uncovers unique performance traits essential for tailored application needs. with its rapid training and prediction capabilities, the svm algorithm is particularly beneficial for applications demanding immediate responsiveness, such as mobile or real-time geolocation tasks. this promptness in processing makes svm an invaluable asset in environments where speed is paramount, directly contributing to the timely and efficient geolocation of medicinal plants. on the other hand, gbm demonstrates a subtly slower training pace but excels in prediction speed, positioning it as the preferred choice for scenarios requiring continuous model updates and instantaneous decision-making. this unique balance between training duration and predictive velocity underscores gbm’s suitability for dynamic applications, where quick adjustments based on new data are essential. conversely, the rf model’s extended training period indicates its applicability when models can be pre-trained offline. the benefits of model interpretability and nuanced feature interaction comprehension outweigh the necessity for swift computation. such characteristics suggest rf’s potential in comprehensive studies or applications where the depth of analysis and accuracy precedes immediate results. the comparative evaluation underscores the critical role of aligning algorithm selection with operational demands, including speed, accuracy, and computational resource availability considerations. highlighting the specific advantages of each algorithm in the context of medicinal plant geolocation attests to the importance of selecting the appropriate ml approach to tackle the unique challenges of precision geolocation. it ensures that the selection process accounts for both computational efficiency and practical implications for real-world applications. 4. conclusions the study aimed to assess the accuracy and computational performance of three ml techniques—gbm, rf, and svm— for the geolocation of medicinal plants using spatial data. it adhered to the crisp-dm framework, ensuring a structured evaluation from project understanding to model deployment. the svm and gbm models showcased superior performance in identifying medicinal plant locations, with the svm model achieving notable efficiency in training and prediction times, which is suitable for real-time applications. the gbm model was highlighted for its quick prediction capabilities, while the rf model was recommended for scenarios demanding high interpretability and complex feature interaction management. performance metrics for svm and gbm included a 97.29% accuracy rate, 100% recall, and a 98.63% f1 score, indicating their exceptional capability in precise geolocation tasks. the study underscored the svm model's computational efficiency, making it an optimal choice for applications that necessitate quick and reliable predictions. the findings have significant implications for environmental conservation and healthcare, aiding in the accurate geolocation of medicinal plants. this supports targeted conservation efforts and sustainable harvesting, which is crucial for preserving biodiversity and continuing traditional medicinal knowledge. the study advocates for further integrating more advanced ml models or exploring deep learning techniques to enhance geolocation accuracy and efficiency. it posits that such advancements could revolutionize precision geolocation, contributing notably to ecological conservation and the pharmaceutical industry by marrying technological innovation with 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[29] s. montaha, s. azam, a. k. m. r. h. rafid, s. islam, p. ghosh, and m. jonkman, “a shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity,” plos one, vol. 17, no. 8, article no. e0269826, 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v9n3(2024)-aiti#13620(172-185).docx advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 english language proofreader: chih-wei chang effect of mean flow on the transmission loss of a doubly tuned flow reversal muffler chetan dayanand gaonkar1,*, thappaganadoddi nagabushnasharma sreenivasa2 1department of mechanical engineering, vtu belagavi, karnataka, india/department of mechanical engineering, don bosco college of engineering, goa, india 2department of mechanical engineering, vtu belagavi, karnataka, india received 23 april 2024; received in revised form 23 may 2024; accepted 24 may 2024 doi: https://doi.org/10.46604/aiti.2024.13620 abstract the same-end-inlet-outlet (seio) muffler, also referred to as a flow reversal muffler under flow conditions, features inlet and outlet pipes positioned on the same side of the chamber. recently, a parametric expression has been developed to determine the end correction for double tuning of the seio muffler. this study extends the development of the seio muffler by experimentally validating the derived end correction expressions. additionally, the tuning of the muffler is assessed with a mean flow using 3-d computational fluid dynamics, solving the linearized navier-stokes equation. this investigation explores the impact of flow conditions (mach number 0.05 and 0.1) and temperature conditions (t = 733 k and 953 k) on the transmission loss (tl) of a doubly tuned muffler. the findings reveal that the muffler maintains its double tuning, even in the presence of mean flow at elevated temperatures, albeit with somewhat of a reduction in performance. keywords: transmission loss, double tuning, flow reversal muffler, cfd, mach number 1. introduction fundamentally, an ideal exhaust muffler would have high insertion loss (il)/transmission loss (tl), low back pressure, smaller size, spark arresting capability, minimum break-out noise, sufficiently low flow-generated noise within the muffler element and at the tailpipe, etc. given the attributes stated above, researchers have been developing the mufflers using multifarious computational models, right from 1-d plane wave theory, transfer matrix method (tmm), and integrated transfer matrix (itm) method to state-of-the-art techniques such as 3-d finite element method (fem) and computational fluid dynamics (cfd) analysis. development of the muffler commenced with a simple expansion chamber (sec), whose tl is characterized by periodic domes and sharp troughs occurring at the integral multiples of π. such a trough results in a sharp drop in the overall il of the muffler [1]. to overcome the dramatic abatement in the overall il, a doubly tuned extended tube chamber muffler was developed, which is superior in tuning out the first three of the four troughs of the tl curve, thereby yielding wide band tl as well as il by deploying the 1-d plane wave analysis and the 3-d finite element analysis of the muffler [2-4]. along these similar lines, recently, a same-end-inlet-outlet (seio) muffler was developed (refer to fig. 1) by gaonkar et al. [5]. specifically, the double tuning of this muffler (refer to fig. 2) was ideally managed using tl expression, as shown in the formula below and the fem technique. * corresponding author. e-mail address: chetan.gaonkar@dbcegoa.ac.in advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 173 ( ) 1 2 11 12 1 21 1 22120 log 2  + + +   =       n n n t t y y t y y ty tl y (1) where, � � �� �⁄ denotes characteristics impedance. suffixes 1 and � denotes 1st and nth element of the muffler respectively, while �� is the speed of sound and a is the cross-sectional area of inlet and outlet exhaust pipes. , �, � , and �� are the four pole parameters [1], which are functions of impedances, resonator lengths, and excitation frequency. fig. 1 schematic of same-end-inlet-outlet (seio) muffler fig. 2 tl plot of seio vs corresponding sec muffler meanwhile, the parametric expression, as shown in the formula below, emerged to determine the end corrections � and �� at the inlet and outlet pipe respectively (refer to table 1 for parameters). 2 2 0.4668 1.8631 4.228 0.9149 0.3575 1.2904 δ          = − + + − +                  i wtd d e e d d d d d d (2) 2 2 0.4042 1.0333 2.6457 0.8718 0.6925 1.7998 δ          = − + + − +                  o wtd d e e d d d d d d (3) however, these derived expressions were not verified against the experimental measurements. hence, the first objective of this work is to experimentally validate these derived expressions. table 1 parameters of muffler for – with and without end correction (dimensions in mm) parameter without end correction with end correction diameter of chamber (�) 130 130 length of chamber (�� 520 520 diameter of inlet and outlet pipe (�) 30 30 length of inlet pipe (� ) 260 251 length of outlet pipe (��) 30 121 the wall thickness of inlet and outlet pipe (��) 1.6 1.6 eccentricity (�) 32 32 174 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 the study of flow reversal mufflers commenced approximately half a century ago when young and crocker [6] established a theoretical model and used fem to predict the tl of this muffler. as a result, mathematical equations were established using analytical approaches to predict the tl in the chambers [7-8], and the influence of end correction was studied using a semi-analytical approach [9]. the formulation of end-correction expressions apropos muffler geometric characteristics, has been a recent advancement in the flow reversal muffler [5]. all of these preceding studies, however, have been conducted in the absence of mean flow, i.e., for stationary medium. the first attempt to study the effect of flow in these flow-reversal mufflers was by panicker and munjal [10] where the transfer matrices pertinent to the aeroacoustics variables across flow-reversing elements were derived. broatch et al. [11] incorporated the cfd simulation to compute the acoustic response while accounting for nonlinear dissipation and solving the full navier-stokes equation in the time domain. recently, a few researchers employed the strategy of incorporating cfd simulation and have attested to the use of steady computational results on acoustic mesh and further solve frequency domain acoustic problems using a systematic mapping technique [12-13]. liu et al. [14] presented a time-domain simulation method to predict the il of a dissipative muffler with exhaust flow, which is a key acoustic index for muffler design. he et al. [15] used a two-step numerical approach using steady-state cfd and linearized navier-stokes equations (lnses) to solve for acoustic perturbation variables. the comparisons between numerical predictions and experimental measurements exhibit decent consistency. subsequently, the lnse was used to compute the acoustic performance of the perforated mufflers in the case of non-uniform flow. furthermore, the result achieved an ideal agreement with the experimental measurements [16]. mohamad et al. [17] used cfd to ascertain the effect of perforated tube configurations on the performance of exhaust mufflers with mean flow, focusing on the real walls approach with a surface roughness of 0.5 micrometers. moreover, recently, the modified tmm (mtmm) combining 3d-cfd with the classic tmm has been introduced to predict the tl of automotive exhaust mufflers [18]. in the presence of the mean flow, convective and dissipative effects will emerge on the acoustic field, which may further influence the overall tl curve of the muffler. the previous discussion clearly shows that using cfd for mean flow simulation to predict the acoustic properties of mufflers (such as tl) is becoming increasingly popular due to its accuracy and cost-effectiveness compared to multiple experimental measurements. however, no attempt has been made to understand the effect of mean flow, on the double tuning of any muffler. hence, the second objective of this work is to ascertain the effect of mean flow on the double tuning of a flow reversal muffler using a comprehensive cfd solution approach. the influence of flow and temperature on the tl curve will be investigated in this study, confirming whether the muffler can retain its double tuning in the presence of flow at higher mach numbers and temperatures. following this introduction, section 2 briefly describes the experimental technique used to validate the end correction expression. section 3 discusses in detail, the cfd simulation to predict the tl. computational results are presented in section 4, and concluding remarks in section 5. 2. experimental validation as discussed in the preceding section, to validate the end correction expressions, two mufflers, i.e., one with and one without end corrections are fabricated. the muffler without end corrections can be termed as an untuned muffler, and likewise, the muffler with end corrections can be termed as a tuned muffler. the specifications of the two mufflers under consideration are listed below in table 1 (refer to fig. 1 for the parameters). to double tune the muffler using extended inlet and outlet exhaust pipes, the length of the inlet pipe should be � � � 2⁄ � 520 2⁄ � 260 mm, and that of the outlet pipe should be �� � � 4⁄ � 520 4⁄ � 130 mm. furthermore, eqs. (2)-(3) are used to calculate the end corrections for the inlet and outlet pipes with the parameters, as shown in table 1, which yields � � 9.2754 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 175 mm and �� � 9.0452 mm. according to the theory of end corrections, the values require to be subtracted from the geometric lengths (� , ��) to tune the muffler [1]. hence, the new pipe lengths of the tuned muffler configuration are presented as follows: • inlet pipe � � " � � 260 " 9.2754 � 250.7246 mm % 251 mm (for fabrication purposes) • outlet pipe � �� " �� � 130 " 9.0452 � 120.9548 mm % 121 mm (for fabrication purposes) the effect of these rounded-off lengths for fabrication will be minimal (negligible) on the measured tl values. the tl of the seio muffler was measured using the two-load method. rather than changing the sources, the end load is altered to produce two configurations. two types of end loads are used herein: anechoic termination and reflected termination. these two configurations, like the two-source technique, yield four equations, which are then used to calculate the four-pole parameter and consequently the tl of the muffler. test equipment used are: (1) multi-channel data acquisition system pulse, type 3560-b-130, b & k denmark make (2) power amplifier, type uba-500, ahuja make (3) muffler test rig with sound source, arai make (4) half-inch condenser microphones, p.c.b. make the test was performed under no mean flow condition with a lower cut-off frequency of 40 hz and at an ambient temperature of 25 ℃. the experimental setup is shown in fig. 3. the loudspeaker was used as a source of excitation, producing a random noise signal. fig. 3 experimental setup of tl measurement of seio muffler the tl plots generated from experimental measurements are depicted in fig. 4 and fig. 5 for an untuned and tuned muffler, respectively. the frequency resolution used for the tl measurement was 8 hz, resulting in a less precise representation of sharp peaks. notwithstanding the limitations in capturing sharp peaks, the experimental results align with the trend, which is observed in the tl plot obtained through 3-d fem. hence, it validates the expressions derived (eqs. (1)-(2)) to predict the end correction in a seio muffler. however, fabrication flaws, e.g., deviations from the prescribed lengths and eccentricity of the inlet and outlet exhaust pipes, could be a possible explanation for the slight variation in the 2nd and 3rd peaks between the predicted and measured tl plots (see fig. 5). 176 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 fig. 4 measured tl plot of an untuned muffler fig. 5 measured tl plot of the tuned muffler 3. cfd analysis to predict the tl the tl of the muffler is influenced by the presence of flow in the exhaust system, which in turn alters the acoustic properties of the system. as discussed in the introduction, the influence of mean flow on the acoustic field of the muffler has been evaluated both theoretically and computationally. however, the use of computational methods, including cfd analysis, to predict the tl of a muffler gradually gains utilization. 3.1. theory when the flow (hot exhaust gases) of uniform velocity u inside the system is present, the forward sound wave moves at an absolute velocity of ' ( �� and the backward sound wave at ' " ��, where �� is the speed of sound. thus, the general solution to a 1-d wave equation as below for a cylindrical duct concerning pressure p and velocity v as a function of coordinate z and time t becomes: ( ) ( )1 1 1 2 , ω− + + −= +o om mjk z jk z j t p z t c e c e e (4) ( ) ( )1 1 1 2 1 , ω− + + −= +o om m o jk z jk z j t v z t c e c e e y (5) where c1 and c2 are the constants to be determined using boundary conditions, ) � *� ��⁄ is the mach number, +� � , ��⁄ is the wave number, , � 2-. is the radian frequency, and . is the excitation frequency. using this solution one can compute the acoustic energy flux and thence the tl. moreover, deploying the tmm (eq. (1)) and incorporating the mach number in the expression one can compute the tl of the muffler in the presence of mean flow. despite the effectiveness of the estimation of tl using these methods, results deviate from the experimental results in the case advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 177 of complex mufflers [19]. the muffler considered in this work yields a bias and reversal flow, and the acoustic field therein is clearly three-dimensional, therefore demands more sophisticated 3-d cfd analysis to predict the tl in the presence of the fluid flow. the turbulent flow presented within the muffler’s flow field can be analyzed using the lnses [20]. these equations represent a simplified version of the classical navier-stokes equations and serve as a linearization of the governing equations for compressible, viscous, and nonisothermal flows. the governing equations are the continuity, momentum, and energy equations: ( ). ρ ρ ρ ∂ + ∇ + = ∂ t o t t ou u m t (6) ( ) ( ) ( ). . . .ρ ρ σ ∂  + ∇ + ∇ + ∇ = ∇ + − ∂  t o t o o t t o o o u u u u u u u f u m t (7) ( ) ( ) ( ) ( ) ( ) ( ) ( ) . . . . . . . ρ ρ α α φ ∂ ∂    + ∇ + ∇ + ∇ − + ∇ + ∇ − ∇   ∂ ∂    = ∇ ∇ + + t t o p t o o t p o o p o t o o t p t o o t t p c u t u t c u t t u p u p t u p t t k t q (8) where, / is the density, * is the velocity, is the temperature, 0 is the stress tensor, ∅ is the viscous dissipation function, ) is the mass source, 2 is the volume force source, and 3 is the heat source, �4 is the specific heat at constant pressure, and 54 is the coefficient of thermal expansion. the variables with a subscript � are the acoustic perturbation values and those with subscript 6 are the background mean flow values. the tl of the muffler is subsequently determined by using the expression [21]: 1 2 1 2 1 20 log 1 + +      +  =       +       i i i i o o o o a m z p tl a m z p (9) where, the subscripts i and o denote the inlet and outlet tubes, respectively, a is the cross-sectional area, m is the mach number, z is the characteristic acoustic impedance of the medium and 78 denotes the incident acoustic pressure wave which is the function of frequency. 3.2. setup and analysis fig. 6 aeroacoustics analysis in comsol a commercial software comsol is used to perform cfd [20] and acoustic analysis [22]. the methodology employed in this study consists of the following steps: 178 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 (1) the shear-stress transport (sst) turbulence model is used to analyze the background flow in the muffler across different mach numbers. (2) subsequently, the acoustic problem is resolved through the application of the linearized navier-stokes physics interface. (3) the mean flow velocity, pressure, and turbulent viscosity are integrated with the lnse model through the background fluid flow coupling multiphysics feature. (4) a mapping technique is employed to transfer the flow solution from the cfd mesh to the acoustic mesh. (5) pressure acoustics in the frequency domain are employed to address the no-flow scenario. to further the understandable description of the aforementioned steps, a flow chart is presented in fig. 6. regarding 3-d cfd analysis and subsequently the acoustic analysis, a tuned muffler (i.e., muffler with end correction applied) is considered. to save upon the computational cost, only one-half of the fluid domain of the muffler (maintaining its symmetry) is adopted for the analysis, as shown in fig. 7. this fluid model of the muffler is further split into several parts for smooth meshing operation. the critical part of this analysis is the discretization or meshing process. the two meshed models used for cfd and acoustic analyses are shown in fig. 8. the mesh model consists of hexahedral and tetrahedral elements with cfd mesh being denser (higher number of nodes), compared to the acoustic mesh model. a boundary layer mesh is used to capture no-slip conditions at the domain boundaries. in the case of acoustic mesh, although the mesh is a coarse mesh, compared to cfd, the size of the element is observed within the limit of 6 elements per wavelength at the highest frequency of interest (1600 hz). to mimic an anechoic termination, a perfectly matched layer (pml) domain is created at the ends of the pipe. fig. 7 one-half of the muffler model (a) for cfd analysis (b) for acoustic analysis fig. 8 mesh model of seio muffler advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 179 the fluid domain is filled with air and is set as a compressible flow for m < 0.3, which is to consider spatially varying density in the exhaust mufflers which encounters a low mach number of m < 0.2. the inlet is subjected to a fully developed turbulent flow of magnitude ' 9 � ��), where m = 0 (no flow condition), 0.05, and 0.1, for temperature t = 293 k, 733 k, and 953 k. the turbulent flow, menter sst interface is used, as this interface is capable of solving this single phase, compressible, low mach number problem. upon solving the cfd model using the above conditions, the solution of this study is mapped onto the acoustic mesh using the built-in background fluid flow coupling multiphysics feature and the dedicated mapping study, which is available in the comsol. to check the effectiveness of mapping, the axial flow velocity and the turbulent viscosity, which are evaluated on the cfd mesh compared with that of the mapped values on the acoustics mesh at one of the edges on the inlet pipe (edge marked in red color on inlet pipe in fig. 7). this comparison is shown in fig. 9 and fig. 10 for m = 0.05 and 0.1. fig. 9 evaluated vs mapped values of the velocity field fig. 10 evaluated vs mapped values of dynamic viscosity the mapped values are satisfactory for solving the pressure acoustic problem and determining the tl in the frequency domain. the problem is first addressed for the no-flow scenario (m = 0), followed by all subsequent mach numbers. such a procedure is further repeated for all the temperature values in this study. 4. results and discussion using the 3-d cfd approach, the tl has been predicted in the tunned seio muffler in the presence of flow. initially, the flow velocity, turbulent kinetic energy, and pressure distribution results are ascertained to interpret the flow behavior inside the muffler. subsequently, the effect of this flow on the tl is examined scrupulously at different temperatures and mach numbers to evaluate the acoustic attenuation properties of the muffler. 180 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 4.1. cfd results the velocity distribution contour for m = 0.05 and 0.1 at 293 k is shown in fig. 11. when the air flows through the inlet pipe inside the chamber, the velocity decreases due to an increase in the cross-sectional area. furthermore, due to this sudden expansion, eddies are formed in the chamber, as shown in fig. 12. however, as the flow reaches the outlet pipe, given the reduction in cross-sectional area, the flow is streamlined with an increase in the flow velocity. this increase in flow velocity may result in the aeroacoustics noise generation. a tendency, likewise, is observable as the temperature of the fluid is increased. the plot of pressure distribution, along the inlet and outlet pipes and in the chamber, is illustrated in fig. 13. it is evident from the figure that the pressure decreases from the inlet pipe to the chamber and further into the outlet pipe. the net pressure loss in the muffler (i.e., the difference in pressure at the inlet and outlet pipe) is 2000 pa, which is seemingly nominal. fig. 11 contour of flow velocity in (m/s) for m = 0.1 fig. 12 contour of turbulent kinetic energy (j/kg) for m = 0.1 fig. 13 contour of pressure distribution (pa) for m = 0.1 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 181 4.2. effect of temperature and mean flow on the double tuning of the muffler when three of the first four troughs in the tl plot are lifted pertinent to the corresponding sec muffler, to yield a wide band tl, the muffler can be called a double-tuned muffler [23-24]. as shown in fig. 2, the double tuning of the seio muffler in the absence of mean flow (m = 0) at room temperature (273 k) consequently increases the height of the tl dome by about 10 db. the same double-tuned muffler has also retained its double tuning when tested with higher temperatures t = 733 k and 953 k with the mean flow for m = 0.05 and 0.1, as observed in fig. 14. (a) m = 0 (b) m = 0.05 (c) m = 0.1 fig. 14 comparison of tl at different temperatures 182 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 specifically, the temperature correlates with speed of sound, thereby resulting in a significantly wider band tl plot, as shown in fig. 14(a). in other words, the through of the tl plot for t = 293 k is at 1321 hz, whereas, at t = 733 k, it changes to approximately 2091 hz. additionally, at t = 953 k, it shifts even further to around 2381 hz, which can be advantageous in some applications that demand a wider band tl. however, the tl curve is dropped in the lower frequency region, particularly in the absence of flow. fortunately, the conditions are significantly better at a higher mach number (m = 0.1), which will be the actual working condition of this muffler. moreover, as shown in fig. 14(b) and 14(c), a similar tendency is observed even at higher mach numbers, i.e., at m = 0.05 and m = 0.1, wherein the tl plot results in a wider band, with a sharp dip in peaks due to the presence of flow. (a) t = 293 k (b) t = 733 k (c) t = 953 k fig. 15 comparison of tl for different mach numbers advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 183 furthermore, despite the effect of bias flow, the muffler retains its double tuning. fig. 15(a) shows a substantial drop in the peak with increasing mach number, which will degrade the acoustic performance of the muffler to some extent. similarly, a tendency is observed by ramya and munjal [3] in their work of double tuning of the extended concentric tube resonator, wherein presents a mean flow with a considerable weakening of resonance peaks, resulting in sharp dips. in the work of sagar and munjal [25], where they investigated the effect of mean flow at the h-junction of the fork muffler, which comprises a three-pass double-reversal muffler with a tubular bridge, even they observed that the magnitudes of the peaks are substantially diminished due to the mean flow effect at the junction. while investigating the effect of flow on the helmholtz resonator, selamet et al. [26] found that the introduction of mean flow intensely weakens the interaction between the cavity and the main duct, incurring the reduction of peak tl along with the shift in resonance frequency to higher values. an increase in the mean flow increases the acoustic resistance and reactance thereby creating aeroacoustic damping, leading to a decrease in tl at the resonance peaks (as seen in fig. 15). however, other than at the regions of sharp peaks, the tl curve is uplifted by marginal values as the flow velocity or mach number increases, which can be factually inferred at higher temperatures, as shown in fig. 15(b) and 15(c). such a finding is undeniably advantageous, at least in the region of the lower frequency range [22]. moreover, the previously seen adverse effect of higher temperatures in the lower frequency region can be perceived to be marginalized against the higher mach number in fig. 15(c). 5. conclusions the previously derived expressions to predict the end corrections of the inlet and outlet pipes have been experimentally verified. the derived expressions appositely manage to double-tune the muffler in the stationary medium. furthermore, using three-dimensional cfd, the effect of mean flow and temperature on the double tuning of the flow reversal muffler has been effectively examined. the background fluid flow coupling of comsol software and mapping technique are efficient tools for considering the output of cfd analysis as an input to frequency domain acoustic analysis. the following section signifies important findings in this study: (1) the developed seio muffler performs admirably in the stationary medium. if a few deviations at certain frequencies (mainly due to fabrication errors) are ignored, the measured plot will mostly overlap with the predicted plot, which corroborates the validity of the end correction expression. (2) with higher mach numbers, the flow velocity increases at the intersection of the chamber and outlet pipe, which may lead to generating aero-acoustic noise. (3) with the increase in temperature, the double tuning of the muffler is retained with a wider tl band, whereas with a compromise on the tl level in the lower frequency region. (4) double tuning of the muffler is also retained when the mean flow is introduced, with a dip in the sharp peaks, nevertheless. however, the tl levels at other frequencies get uplifted thereby marginalizing the adverse effect of temperature at lower frequencies. acknowledgment a sincere thanks to dr. m. l. munjal, professor (emeritus), frita, department of mechanical engineering, iisc, bengaluru, india for giving the original problem statement of the seio muffler. also, a sincere thanks to dr. k. m. kumar, assistant professor, department of mechanical engineering, iit-indore, india, for providing a computational facility to carry out this work. 184 advances in technology innovation, vol. 9, no. 3, 2024, pp. 172-185 conflicts of interest the authors declare no conflict of interest. references [1] m. l. munjal, acoustics of ducts and mufflers, 2nd ed., hoboken: wiley, 2014. 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[26] e. selamet, a. selamet, a. iqbal, and h. kim, “effect of flow on helmholtz resonator acoustics: a three-dimensional computational study vs. experiments,” the ohio state university, sae technical paper 2011-01-1521, may 17, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word aiti#15175 20251208 (way, print 1).docx advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx remaining useful life prediction of milling tool based on improved pso-multiam-bilstm xiaomei ni1, david chua sing ngie1,*, wanzhen wang2, miaomiao xin2, qiu man2, liangyu tian2, jingzhe sun2 1faculty of engineering, universiti malaysia sarawak (unimas), sarawak, malaysia 2school of intelligent manufacturing and control engineering, qilu institute of technology, shandong, china received 22 may 2025; received in revised form 11 august 2025; accepted 18 august 2025 doi: https://doi.org/10.46604/aiti.2025.15175 abstract to improve the accuracy of remaining useful life (rul) prediction for milling tools, this study proposes an enhanced pso-multiam-bilstm model integrating particle swarm optimization (pso), multi-head attention mechanism (multiam), and bidirectional long short-term memory (bilstm). the model captures key information in input sequences, alleviating early feature attenuation in bilstm from “chain propagation.” a logarithmic decreasing strategy adjusts pso inertia weights, balancing global and local searches while optimizing bilstm parameters. validated on the phm2010 dataset, the model attains an average coefficient of determination of 0.97, with average root-mean-square error and mean absolute error of 0.062 and 0.045, improving prediction accuracy by 9.64% and 4.06% over multiam-bilstm and pso-am-bilstm, respectively. such a result attests to the effective extraction of degradation features of tools and provides a valuable reference for predicting the rul of milling tools. keywords: multiam, pso algorithm, bilstm, rul 1. introduction as a fundamental tool of industry, the computer numerical control (cnc) machine tool contributes significantly to industrial manufacturing. with the increasing demand for product quality, the stability of the machining process has become increasingly important. this section examines the research background of remaining useful life (rul) prediction, relevant literature, research gaps, research objectives, and the structure of this study. accurate prediction of tool rul can reduce downtime due to tool failure, avoid unnecessary tool changes, and extend tool life, which is crucial for improving productivity and saving production costs [1]. traditional rul prediction methods mainly include methods based on physical models and traditional machine learning. physical-model-based methods formulate mathematical models by studying tool failure mechanisms, such as tool wear, whereas they face challenges in adapting to complex and changing production environments and in maintaining low prediction accuracy [2-3]. traditional machine learning models are mainly trained by degraded data, such as the hidden markov model, the wiener process, and the bayesian model. however, these methods suffer from the inability to capture nonlinear relationships and difficulty in maintaining the accuracy of prediction results [4-5]. with the rapid development of deep learning and neural networks, rul prediction based on deep learning models is gradually gaining prominence. by integrating multi-sensor data, feature extraction techniques, and advanced deep learning methods, researchers can effectively predict rul [6]. convolutional neural network (cnn) demonstrates proficiency in * corresponding author. e-mail address: 21010377@siswa.unimas.my advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 2 automatically extracting spatial data features, thereby augmenting rul prediction accuracy [7-9]. recurrent neural network (rnn) and its variants, such as long short-term memory (lstm) and bidirectional long short-term memory (bilstm), are pervasively employed in natural language processing owing to their ability to process temporal data, and have recently been applied to rul prediction as well [10]. wang et al. [11] utilized a stacked self-encoder (sae) with lstm to enhance model generalization under complex conditions. similarly, wang et al. [12] proposed a cnn-lstm-pso method, which incorporates a cnn, lstm, and particle swarm optimization (pso). this method utilizes cnns to extract local features, lstm to process temporal information, and pso to optimize hyperparameters, thereby improving prediction performance. yao et al. [13] proposed an lstm-based deep transfer reinforcement learning network with strong cross-tool and cutting condition generalization. liu et al. [2] used a parallel residual network (presnet) and a stacked bilstm to improve the accuracy of the tool rul. as a popular metaheuristic, pso optimizes models like backpropagation (bp), lstm, least-squares support vector machine (lssvm), and radial basis function (rbf) for rul prediction. research has shown that both the bp neural network and rbf neural network optimized by the pso algorithm can more accurately capture data features [14]. some researchers also used the pso algorithm to optimize the parameters of the cnn-lstm model. the experimental results showed that the method yields high accuracy and stability in tool wear prediction [12]. some studies have applied the pso algorithm to the optimization of the lssvm. the experiments show that the optimized model outperforms the unoptimized model in terms of prediction performance [15-16]. in recent years, the application of attention mechanisms (am) in rul prediction has received much attention [17]. wang and zhang [18] proposed a sequence-to-sequence model combining the am and monotonicity loss, which utilized the am to enhance the model’s focus on key time-series features and introduced a monotonicity loss function to enhance the physical consistency of the prediction results. dong and zhao [19] proposed a method for tool wear prediction that combines an enhanced autoencoder (ae) with a multi-head attention mechanism (multiam), which utilizes the ae for feature extraction and focuses on essential timing features in the input data through a multiam to improve the prediction accuracy. while lstm and its variants have advantages in time-series processing, and researchers have explored deep learning models, pso-optimized models, and ams to improve tool rul prediction, shortcomings remain in addressing the key challenges of current frameworks. the specific research gaps are as follows: (1) bilstm exhibits attenuation of early wear features as a consequence of the “chain propagation” mechanism. current studies lack a dynamic weighting mechanism designed for the stage-specificity of rul prediction, hindering the strengthening of key time-period features and thus restricting the accuracy and applicability of tool’s rul prediction. (2) as a widely used metaheuristic algorithm, pso currently exhibits deficiencies in optimizing model hyperparameters and managing critical details of the training process. this shortcoming directly leads to the inability to fully leverage the inherent performance potential of target models. (3) the initial weights of the current pso algorithm are generally optimized using linear diminishing optimization. this optimization approach causes the weights to drop rapidly in the early stage of the particle search, incurring the premature convergence of particles to a local optimal solution instead of finding the global optimal solution. based on the above analysis of the current tool rul prediction limitations, this paper proposes a rul prediction method built on a fusion approach. this method aims to address identified gaps, and the main objectives of the study are as follows: (1) the proposed model introduces the multiam and enables parallel computing and learning different subspaces. it can dynamically capture the key information in the input sequence, effectively addressing the issue of information attenuation in long sequences and overcoming the limitations of the traditional “chain propagation” approach. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 3 (2) when optimizing the model using the pso algorithm, in addition to optimizing the model learning rate, the number of hidden layer units and the initial weights of the model are also optimized. this enables more comprehensive and precise optimization of key parameters that impact bilstm network performance. (3) this model dynamically adjusts the inertia weight using a nonlinear function, thereby achieving a better balance of the global search capability and local search capability of the pso algorithm. this adjustment optimizes the initial weights of the algorithm and enhances its ability to locate the global optimal solution during the parameter optimization process. the subsequent structure of this article is as follows: in section 2, relevant research methodologies are introduced, including fundamental principles of bilstm, pso, and multiam. in section 3, the improved pso-multiam-bilstm model is presented in detail. in section 4, results and analysis of rul prediction are provided, encompassing the introduction of the phm2010 dataset, feature extraction methods, experimental setups, and a comprehensive discussion of model performance. finally, in section 5, the conclusion synthesizes key findings of this study, underscores the advantages of the proposed model, and outlines potential directions for future research. 2. methodology this section introduces the architecture framework of the bilstm neural network and the multiam, focusing on the core components of these systems and their basic operation mechanisms. additionally, the optimization workflow of the pso algorithm is also presented. 2.1. bilstm neural networks lstm can effectively capture long-range sequential dependencies and is widely used in tool life prediction. the key components of lstm entail the cell state and several gating mechanisms, including the forget gate, input gate, and output gate. these gating mechanisms employ a sigmoid function to regulate the flow of information. the specific parameter update calculation steps are as follows: (1) calculate the forget gate ft and select the information to be forgotten: [ ]( )1 ,σ − = × +t t tf ff w h x b (1) [ ]( )1 ,σ − = × +t i t t ii w h x b (2) (2) update the unit status: [ ]( )1tanh , − = × +ɶ c ct t tc w h x b (3) (3) calculate the value of the candidate memory cell at the current moment ct: 1− = × + × ɶt t t t tc f c i c (4) (4) compute the output gate ot and the hidden layer state at the current moment ht: [ ]( )1 ,σ − = × +t o t t oo w h x b (5) ( )tanh= ×t t th o c (6) where wf and wi are the corresponding connection weight matrices; bf, bi and bc are the bias vectors; xt is the input data at the current moment; ht-1 is the hidden layer value at the previous moment; σ is the sigmoid activation function and the value interval is [0,1]; ct-1 is the last moment cell state; ct is the current cell state; and ��� is the temporary cell candidate value. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 4 despite its ability to address the long-term dependency problem, lstm utilizes only the past information of time-series data while ignoring future information. the bilstm extends the capability of lstm, which can handle multivariate time-series data by simultaneously considering both forward and backward information of the series, along with the effects of multiple influencing factors on the prediction results. as such, it is suitable for multivariate time-series data in the tool cutting process, and its structure is shown in fig. 1. fig. 1 structure of bilstm 2.2. pso algorithm the pso algorithm is a swarm intelligence-based optimization algorithm that finds more accurate results through the iterative evolution of the current solution [15]. pso can expeditiously converge and find high-quality solutions in a shorter period. therefore, it is widely used in the fields of hyperparameter optimization, feature selection, and neural network training. the specific steps in the process of the pso algorithm search are as follows: (1) initialize the pso algorithm, including the population size n, the end time, and other parameters. subsequently, determine the velocity vi and position xi of each particle i based on these factors: ( )1 2, , , , 1, 2, ,= =… … di i i iv v v v i n (7) ( )1 2, , , , 1, 2, ,= =… … di i i ix x x x i n (8) (2) evaluate the fitness of each particle using the objective function f[i]; (3) update the individual optimal solution and the global optimal solution according to the following equations: ( )1 2, , , , 1, 2, ,= =… … di i ibestp p p p i n (9) ( )1 2, , , , 1, 2, ,= =… … di i ibestg g g g i n (10) where pbest is the individual optimal solution, indicating the initial position of each particle; gbest is the global optimal solution, signifying the particle with the best initial fitness value. (4) in updating the velocity and position of the particles, the following calculations are performed: ( ) ( )( ) ( )( )1 1 2 21 1 1− − − = + + −id gdi d i d i d v wv c r p c r p x (11) ( ) ( )1 1− − = +id i d i dx x av (12) where w is the inertia factor; c1 and c2 are the acceleration coefficients; r1 and r2 are mutually independent stochastic functions between [0,1]; α is the constraint factor used to limit the speed. (5) loop the steps (2) to (4) until the optimization termination condition is satisfied, ending the optimization process. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 5 2.3. multiple attention mechanisms (am) in recent years, ams have become a much-anticipated research topic in the field of deep learning. traditional ams tend to rely on another relevant sequence to determine the allocation of attention when processing an input sequence. in this regard, the multiam introduces multiple independent attention computations to enhance the expressive power of the model. the core idea of the multiam is to map the input data into multiple low-dimensional subspaces and compute the attention independently in each subspace. finally, these attention results are spliced and fused. the core idea of the multiam is shown in fig. 2. unlike the single-head am, the multiam divides the q (query vector), k (key vector), and v (value vector) into h parts (multiple heads) and computes the attention independently in these subspaces. the calculation formula is as follows: ( ) ( )1 2, , , , ,= … h o multihead q k v concat head head head w (13) fig. 2 core idea of the multiam 2.4. improved pso-multiam-bilstm model fig. 3 pso-multiambilstm training flowchart advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 6 based on the aforementioned theory, this research proposes a rul prediction model based on the improved pso-multiam-bilstm. the inertia weights of the pso algorithm in this model are dynamically adjusted through a nonlinear function, and the pso algorithm optimizes key parameters of the bilstm network, such as the number of hidden layers and the learning rate. the correlation weights between features are computed using a multiam that enables the bilstm model to dynamically focus on the important information in the input sequence. the process of model realization is shown in fig. 3. the specific steps in the rul prediction process of the proposed pso-multiam-bilstm are as follows: (1) when the bilstm network executes the bp algorithm for gradient computation, the output value of each neuron is derived by concatenating the hidden states from forward and backward computations. a multiam is incorporated to enhance label localization and classification, enabling the recognition of discrepancies between different monitoring data and facilitating the extraction of deeper potential information from the data. to mitigate overfitting, a dropout rate of 0.25 is employed. finally, the data is passed through two fully connected layers with 10 and 1 units, respectively, before being fed into the regression layer. (2) the pso algorithm is initialized by adopting the initial root-mean-square error (rmse) of each particle as the local optimum. the initial parameters of the model are configured as listed in table 1, including the initial learning rate, the number of hidden layer units, and initial weights. these parameter settings are determined based on extensive trial experiments. table 1 pso-multiam-bilstm model parameters network parameter initial value initialization weights [0.4,1] oblivion gate bias 1 input gate bias (progression, pacemaker = 0.1) [0,0.8] output gate bias (progression, pacemaker = 0.1) [0,0.8] number of iterations 200 population size 10 learning factor c1 1.5 learning factor c2 1.5 number of hidden layer units m (progression, pacemaker = 10) [10,300] learning rate r [0.01,0.15] (3) in the pso optimization process, a logarithmic decreasing strategy is introduced to dynamically adjust the inertia weights. this strategy gradually reduces the inertia weights during the iterative process, effectively balancing the global exploration and local search capabilities of the algorithm and improving its optimization performance. the formula for the logarithmic decreasing inertia weights is given in the formula below. the rmse is employed as the fitness function, and the optimal learning rate and number of hidden layers of the bilstm model are determined through iterative search, attaining efficient optimization of model parameters. additionally, the adam optimizer is utilized to optimize the model weights, ensuring expeditious convergence during training and further enhancing the training efficiency and prediction performance of the model. the specific formula is as follows: ( ) ( ) ( ) max maxmin min max ln 1 ( ) ln ω ω ω ω − + = + − × t t t t (14) where ω(t) is the inertia weight at iteration t times; ωmin is the minimum value of the inertia weights, which is reached in the later stages of the iteration and enhances the local search capability of the algorithm; ωmax is the maximum value of the inertia weights, ensuring strong global exploration capability at the beginning of the iteration; tmax is the maximum number of iterations of the algorithm; and t is the current iteration number. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 7 3. dataset and feature extraction this section introduces the source of the dataset, experimental conditions, and data preprocessing methods. regarding the experimental conditions, key details include the equipment used and milling parameters. in terms of data preprocessing, it mainly covers original signal processing and feature extraction, including calculation formulas of time-domain features, frequency-domain features, and time-frequency domain features. 3.1. introduction of experimental data the dataset from the phm2010 data challenge was used for this experimental validation [1]. the rfm760 cnc machine tool was selected as the experimental platform, with a three-flute tungsten carbide ball-end milling cutter as the cutting tool, to cut the stainless steel (rc52) material. the specific experimental equipment and milling parameters are shown in table 2. table 2 experimental equipment and milling parameters equipment type experimental equipment milling parameters parameterization machine type roders rfm760 spindle speed 10,400 r/min cutters ball tungsten carbide milling cutter feed rate 1,555 mm/min wear measurement equipment leica mz12 microscope amount of tools per travel 0.001 mm workpiece materials stainless steels hrc52 cutting width 0.125 mm data acquisition equipment ni daq data acquisition card depth of cut 0.2 mm boosters kistler charge amplifier sampling frequency 50 khz force sensor three-way force gauge milling method milling with no problem vibration sensors triaxial acceleration sensor cooling method dry cut to comprehensively monitor the state of the milling cutter in the machining process, a variety of equipment, such as force-measuring instruments, acceleration sensors, and acoustic emission sensors, was used to collect the original time-domain signals, such as cutting force, vibration, and acoustic emission. these signals were sampled at a frequency of 50 khz to ensure the accuracy and integrity of the data. in the experiment, each tool traveled 108 mm in the x-direction, and each tool traveled 315 times to fully collect the cutting monitoring signals under different conditions [15]. through an in-depth analysis of these signals, the dynamic characteristics of the milling machining process can be better understood, and effective data can be provided for the subsequent training and optimization of the neural network model. 3.2. data preprocessing to allow the model to extract more accurate and effective information, the original signal requires the following preprocessing steps. first, the intense vibration signal generated by the tool cutting is truncated. subsequently, the original signal is subjected to wavelet threshold processing for noise reduction. feature extraction plays an important role in data preprocessing. to obtain more comprehensive information about the remaining service life of the tool, 30 features from the time domain, frequency domain, and time-frequency domain were extracted from the raw signal data of each channel. after completing the feature engineering work, the original datasets c1, c4, and c6 correspond to a feature space of size (315 × 6 × 30). (1) time domain features in the time domain, a total of 18 features, including the absolute mean, maximum value, root mean square, root amplitude, skewness, kurtosis, shape factor, pulse factor, teager energy, skewness factor, crest factor, clearance coefficient, activity, energy entropy, fluidity, information entropy, willison amplitude, and kurtosis factor, are mainly extracted, and the specific calculation formulas are presented in table 3. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 8 table 3 time domain feature calculation formula feature formula feature formula absolute mean 1��|� | �� skewness factor 1 ∑ ��� − �̅��� ���1 ∑ ��� − �̅��� �� maximum value ������, ��, ⋯ , ��� crest factor �����1 ∑ |� |� �� root mean square 1��� � �� clearance coefficient !��!"# root amplitude $"�%&'()*+ activity �,!-�� skewness 1��.� − /0 1� �� energy entropy −�% 2 �% � �� kurtosis 1��.� − /0 13 �� fluidity 4∞0 7 × 9�7�*74∞0 9�7�*7 shape factor ,!-!"# information entropy −�%�� �2 :%�� �; �� pulse factor ������1 ∑ � �� �� willison amplitude 1<�|� =� − � |> �� teager energy ? = � � − � a�bc=� kurtosis factor 1 ∑ ��� − �̅�3� ���1 ∑ ��� − �̅��� �� − 3 (2) frequency domain features the four features of center of gravity frequency (fc), mean square frequency (msf), root mean square frequency (rmsf), and frequency variance (vf) were extracted mainly by fast fourier transform (fft) in the frequency domain, and the specific calculation formula is shown in table 4. table 4 frequency domain feature calculation formula feature formula fc 4 7-�7�*7=ef4 -�7�*7=ef msf 4 7�-�7�*7=ef4 -�7�*7=ef rmsf 4 7�-�7�*7=ef4 -�7�*7=ef vf 4 �7 − g���-�7�*7=ef 4 -�7�*7=ef (3) time and frequency domain features the db3 (dobesi limit phase) wavelet transform is mainly used in the time-frequency domain to extract features and analyze the data of both low and high frequency parts, and the wavelet tree depth used is 3. the wavelet packet transform is reconstructed to analyze the features of different frequency bands. the eight node coefficients are parametrised as the eight features extracted in the time-frequency domain. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 9 4. results and discussion in this study, the sample set was divided into three sets of experiments, and two of the three tool labeling samples were used for training and the other for testing in each set of experiments. the detailed setup of the experimental groups is shown in table 5. table 5 training and test set setup experiment no. training set test set e1 c1, c4 c6 e2 c1, c6 c4 e3 c4, c6 c1 the particle fitness convergence curves of the presented model across the e1, e2, and e3 experimental groups are presented in figs. 4-6. as observed in the figures, the fitness value stabilizes after an average of 23 iterations. the optimal learning rates and numbers of hidden layer units for the models corresponding to the three datasets at this stage are listed in table 6. fig. 4 pso particle fitness curves for group e1 fig. 5 pso particle fitness curves for group e2 advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 10 fig. 6 pso particle fitness curves for group e3 table 6 optimal parameters of the model with different datasets experiment no. e1 e2 e3 optimal number of hidden layer units 18 20 20 optimal learning rate 0.013 0.015 0.02 optimal weight 0.46 0.51 0.42 fig. 7 train-validation loss of e1 fig. 8 train-validation loss of e2 advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 11 fig. 9 train-validation loss of e3 the obtained train_loss and val_loss are shown in figs. 7-9. as can be observed from the figures, with the increase in the number of training epochs, the value of the loss function continuously decreases until convergence, which indicates that the model can effectively learn the extracted signal data features. the specific values of the regression metrics calculated by different algorithms are shown in table 7. concerning performance, the proposed method demonstrates significant advantages in predicting the rul of milling cutters. its average rmse is 0.062, and the mean absolute error (mae) is 0.045, both of which are lower than those of the other three models. the coefficient of determination (r²) of the proposed method is 0.97, and its prediction accuracy is also higher than that of the other three models, indicating that this model has strong capabilities in data fitting and feature capturing. table 7 comparison of evaluation indicators of different model prediction results model e1 e2 e3 rmse mae r2 rmse mae r2 rmse mae r2 bilstm 0.098 0.073 0.83 0.091 0.079 0.83 0.093 0.074 0.83 multiam-bilstm 0.073 0.057 0.88 0.071 0.057 0.89 0.072 0.059 0.89 pso-am-bilstm 0.067 0.047 0.946 0.065 0.049 0.93 0.065 0.051 0.93 pso-multiam-bilstm 0.063 0.047 0.97 0.062 0.045 0.97 0.061 0.043 0.98 however, as shown in table 8, the improved performance is accompanied by an increase in training costs. the total training time of the pso-multiam-bilstm model is 57.6 minutes, which is significantly longer than that of the bilstm model (12.3 minutes). nevertheless, in manufacturing scenarios with strict requirements for prediction accuracy, its accurate predictions can effectively prevent production failures caused by abnormal tool wear. the long-term value greatly outweighs the investment in short-term training time, yielding a more reliable technical solution for tool health management in intelligent production lines. table 8 comparison of the computational cost of different models model total training time bilstm 12.3 min multiam-bilstm 45.6 min pso-am-bilstm 50.5 min pso-multiam-bilstm 57.6 min to compare the effect of each model, figs. 10-12 show the prediction results of the pso-multiam-bilstm, pso-bilstm, and bilstm models for groups e1, e2, and e3. in the data processing session, a linear transformation is applied to the raw data of the rul to unify the range of values to the interval [0, 1]. after normalizing the rul of the tool on advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 12 the y-axis, the value of 0 represents that the tool life is exhausted, the value of 1 represents that the tool is in a new state, and the intermediate values reflect that the tool is in different degrees of use. the normalization process eliminates the influence of the original data due to the differences in the scale and range of values, and provides a more intuitive picture of the variation of the remaining tool life with the number of cuts. in this graph, the x-axis represents the number of cuts, and the y-axis represents the corresponding normalized value of the rul. fig. 10 prediction effect on group e1 fig. 11 prediction effect on group e2 fig. 12 prediction effect on group e3 advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 13 as depicted in figs. 10-12, due to the lack of pso hyperparameter optimization, the multiam-bilstm model is not well adapted to the data distribution, and its prediction accuracy and stability are inferior to those of the model with pso optimization. when comparing the pso-multiam-bilstm model with the pso-am-bilstm model, the prediction curve of the pso-am-bilstm model fluctuates significantly, particularly within the 50-200 cutting interval, indicating that the basic am is less effective than the multiam in extracting features under complex working conditions. its prediction stability is also slightly worse. in other words, the life curve of the pso-multiam-bilstm model is closer to the real life curve, indicating that this model is more accurate in predicting the remaining life of tool wear and reflects the advantages of pso in optimizing hyperparameters and the am in focusing on key features. this demonstrates that the proposed method can more accurately identify the degree of tool degradation. to delve into the advantages of the deep learning hybrid model, four comparison models, including rnn [20], cnn-bilstm [21], and bigru [22], are employed for experiments, and the results are shown in table 9. the findings indicate that the pso-am-bilstm model performs best among all compared models, yielding the lowest rmse and mae values. this validates the superiority of combining pso, multiam, and bilstm. pso optimizes hyperparameters to adapt the model to the data distribution, while multiam focuses on key temporal features to jointly enhance prediction performance. table 9 comparative experiment results evaluation model mae rmse rnn [20] 4.1336 4.0227 cnn_bilstm [21] 0.1781 0.2943 bigru [22] 0.078 0.097 pso-multiam-bilstm 0.049 0.0564 the pso module in the network structure is replaced with the genetic algorithm (ga) and differential evolution (de) for comparison, and the experimental results are illustrated in figs. 13-15. among the prediction results of each model, the one optimized by pso exhibits a higher degree of fit with the actual value curve, indicating the highest prediction accuracy. models optimized through ga and de show the most significant deviation from true values when the number of cutting operations ranges between 100 and 200. this suggests that tool wear rate changes are complex at this stage, imposing high requirements on model feature extraction and optimization capabilities. however, pso demonstrates stronger search ability and is more suitable for handling such complex variations. thus, the pso-multiam-bilstm model outperforms other models in predicting the rul of milling. it is particularly effective in addressing intricate changes in tool wear during cutting processes, providing robust support for practical applications in manufacturing scenarios. fig. 13 the predictive effects of different optimization algorithms on the e1 group advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 14 fig. 14 the predictive effects of different optimization algorithms on the e2 group fig. 15 the predictive effects of different optimization algorithms on the e3 group 5. conclusion this study proposes an improved pso-multiam-bilstm model for accurate rul prediction of milling tools, addressing limitations in existing deep learning and optimization frameworks. by integrating a multiam with bilstm, the model dynamically captures key features in long time-series data, mitigating early critical feature attenuation caused by “chain propagation” in traditional bilstm. pso is applied to optimize bilstm parameters, including hidden layer units, learning rate, and initial weights, using a logarithmic decreasing strategy for inertia weights, balancing global exploration and local search capabilities, and avoiding premature convergence to local optima. experimental validation on the phm2010 dataset demonstrates the superiority of the proposed model in predicting tool rul. the main findings are summarized as follows: (1) the proposed pso-multiam-bilstm model effectively mitigates early critical feature attenuation in long time-series data and enhances feature discrimination across different wear stages. (2) pso optimization of bilstm parameters improves model performance by balancing global and local search capabilities, enhancing overall optimization effectiveness. (3) experimental results demonstrate high prediction accuracy, with an average r2 of 0.97, rmse of 0.062, and mae of 0.045, showing an improvement of 9.64% over multiam-bilstm and 4.06% over pso-am-bilstm. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 15 (4) comparative experiments replacing pso with ga or de indicate that pso exhibits stronger adaptability to complex tool wear rate variations, especially within the 100-200 cutting operation range. the results of the study are highly informative for rul prediction in milling machining. the method can also be conveniently applied to rul prediction of cutting tools in other real machining processes, such as turning and drilling. the validation of this method is currently limited to a single tool parameter; future work can expand experimental samples and apply the approach to different rul prediction scenarios. acknowledgments this work is supervised by professors from universiti malaysia sarawak. this work is also supported by the research program of qilu institute of technology (no.: qit23nn038). conflicts of interest the authors declare no conflict of interest. references [1] j. karandikar, t. schmitz, and s. smith, “physics-guided logistic classification for tool life modeling and process parameter optimization in machining,” journal of manufacturing systems, vol. 59, pp. 522-534, 2021. 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[22] b. li, m. han, x. zhang, h. luan, and s. sun, “research on the prediction method of remaining tool life based on gasf-lstm-attention,” 10th international conference on computer and communications, pp. 1422-1427, 2024. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 modeling the daily average temperature data using stochastic process and neural networks for weather derivatives kanyarat thitiwatthanakan1, manad khamkong2,*, ravi lonkani3, thanasak mouktonglang4 1ph.d. program in applied statistics, department of statistics, faculty of science, chiang mai university, chiang mai, thailand 2department of statistics, faculty of science, chiang mai university, chiang mai, thailand 3department of finance, faculty of business administration, chiang mai university, chiang mai, thailand 4department of mathematics, faculty of science, chiang mai university, chiang mai, thailand received 31 october 2024; received in revised form 22 march 2025; accepted 24 march 2025 doi: https://doi.org/10.46604/aiti.2024.14456 abstract weather derivatives are financial instruments influenced by temperature fluctuations, impacting industries such as agriculture, tourism, and energy. accurate temperature modeling is essential for improving risk assessment and hedging strategies. this study evaluates the effectiveness of two forecasting hybrid approaches: the fourier ornstein-uhlenbeck (ou) process, a widely used stochastic model, and the fourier-elman recurrent neural network (ernn), a hybrid neural network-based model. daily temperature data from chiang mai, thailand, spanning january 2005 to december 2021, were analyzed. the predictive performance of each model was assessed using root mean square error (rmse). the results indicate the fourier ernn model (rmse = 0.106) significantly outperforms the fourier ou process (rmse = 2.299), demonstrating superior accuracy in capturing both seasonal and stochastic variations in temperature dynamics. thus, deep learning-based hybrid models provide a more effective framework for temperature forecasting. the proposed approach has potential applications in climate risk management, weather derivative pricing, and decision-making in climate-sensitive sectors. keywords: temperature modelling, ornstein-uhlenbeck process, elman recurrent neural network, fourier series, hybrid model 1. introduction the modeling of daily average temperature is recognized as a crucial element in understanding and forecasting weather patterns across various regions. in chiang mai, a major city in northern thailand, temperature dynamics have become a key focus for study, particularly because of distinct seasonal variations, including hot, wet, and cool seasons that significantly influence daily temperature changes. accurate temperature modeling in chiang mai is essential not only for sectors such as agriculture, tourism, and urban planning but also for addressing broader challenges posed by climate change and for supporting financial instruments, including weather derivatives. the motivation for this study is derived from the urgent need for enhanced temperature forecasting accuracy in chiang mai amid evolving climate conditions. recent studies have documented significant climate change impacts in thailand, including a 1.30°c warming from 1970 to 2017, changes in rainfall patterns and extreme events, and sea level rise exceeding global averages [1]. despite the availability of long-term hydrometeorological data, the detection of specific historical changes due to climate change has proven challenging, and future projections continue to lack systematic multi-model assessments [2]. * corresponding author. e-mail address: manad.k@cmu.ac.th advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 297 in northeastern thailand, climate change has been perceived over the past 20 years by 96.9% of farmers, leading to adaptations such as the purchase of insurance, alterations in cropping patterns, and engagement in off-farm activities; factors influencing these adaptations have been identified as dependency ratio, geographical location, current occupation, climate change knowledge, and the perceived benefits of new technologies [3]. these findings underscore the necessity for improved temperature models to support adaptive strategies and informed decision-making in sectors vulnerable to climate variability. temperature modeling also plays a significant role in financial markets, particularly through weather derivatives that manage risks associated with climate variations. the value of these contracts is derived from underlying weather measurements and is often based on temperature indices such as cumulative average temperature (cat), heating degree days (hdd), and cooling degree days (cdd). the first weather derivative transaction was executed over-the-counter in the united states in 1997, and by 1999, such instruments were formally introduced in key financial markets such as the chicago mercantile exchange (cme) [4]. the increasing importance of weather derivatives in sectors including utilities, agriculture, and construction further emphasizes the need for accurate temperature models. in previous research, the daily average temperature has frequently been modeled using a stochastic approach, specifically, the mean-reverting ornstein-uhlenbeck (ou) process. this method has been widely employed in various studies, including applications in which the stochastic model was driven by a generalized hyperbolic lévy process with seasonal mean and volatility [5]. since temperature exhibits mean reversion and seasonal behavior rather than persistent trends over extended periods [6], the use of a mean-reverting model such as the ou process is considered appropriate. the ou process has been effectively applied to model temperature dynamics for the pricing of weather derivatives, where the incorporation of seasonality, stochastic variability, and mean reversion is essential [7]. recent advancements in machine learning have introduced alternative approaches for temperature modeling, including neural networks. neural networks, inspired by the structure and function of the human brain, are composed of interconnected layers of nodes (neurons) that process and transmit information. through weighted connections, biases, and activation functions, non-linear relationships are captured, making these models particularly effective in handling complex patterns in historical temperature data [8-9]. neural networks possess the ability to account for various influencing factors, such as seasonal cycles and sudden changes in weather patterns, a capability that renders the approach valuable for forecasting future climate behavior. in summary, the motivation for this study is the need to develop an enhanced temperature modeling framework for chiang mai, thailand, using historical temperature data. both traditional stochastic models, such as the ou process, and modern machine learning techniques, such as neural networks, have been evaluated to identify the most suitable approach for predicting temperature variations. ultimately, improved forecasting methods are anticipated to support informed decision-making across agriculture, tourism, urban planning, and financial risk management, thereby contributing to broader efforts in climate adaptation and mitigation. 2. literature review recent studies have explored stochastic modeling approaches for temperature dynamics, with applications in climate change analysis and financial derivatives. the ou process has been used to model daily temperatures in laguna, philippines, revealing a significant increase in both minimum and maximum temperatures from 1960 to 2018 [7]. for stratospheric temperatures, a lévy-driven multidimensional ou process has been proposed, incorporating seasonality and autoregressive components [10]. in the context of temperature insurance pricing, a continuous time autoregressive moving average (carma) model with stochastic speed of mean reversion has been developed [11]. additionally, a stochastic harmonic oscillator model has been employed for pricing temperature-based weather options, demonstrating the impact of model parameters on option prices [12]. advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 298 later in 2020, temperature forecasting for weather derivatives valuation was enhanced through a comparison of the ou process and a generalized autoregressive conditional heteroskedasticity (garch) model using zagreb data from 2000 to 2017 [13]. forecast accuracy, evaluated by root mean square error (rmse) and mean absolute percentage error (mape), demonstrated that the garch model yields superior predictions, thereby improving reliability. after that, in 2022, a stochastic volatility model that extends a gaussian model with deterministic time-dependent volatility was introduced. the model parameters were estimated using conditional least squares on data from eight european cities and demonstrated efficient calculation of average payoffs for weather derivatives using monte-carlo and fourier transform techniques [14]. these approaches using stochastic processes contribute to an improved understanding of temperature dynamics and their applications in various fields. artificial neural networks (anns) have shown promising results in predicting temperature and related environmental variables. studies have demonstrated the effectiveness of anns in modeling soil temperature [15], atmospheric temperature [16], power generation affected by temperature [17], and maximum and minimum temperatures in the western himalayas [18]. various ann training algorithms have been compared, with the levenberg-marquardt (lm) algorithm performing well in multiple studies [15-16]. ann models have consistently outperformed traditional methods like multiple linear regression in terms of accuracy and error reduction [17]. input parameters for these models typically include historical temperature data, precipitation, and other relevant meteorological variables [15, 18]. the success of anns in temperature prediction across diverse applications highlights their potential for improving climate-related forecasting and decision-making. in 2022, air temperature post-processing in norway was improved using multilayer perceptrons and convolutional neural networks, reducing forecast errors compared to traditional methods [19]. in 2023, the feed-forward and elman neural networks were developed to estimate monthly air temperatures in turkey, creating accurate long-term temperature maps [20]. after that, the recurrent neural networks (rnns) were applied to forecast atmospheric temperature in chinese cities, achieving high accuracy with long short-term memory (lstm) models [21]. beyond temperature, an rnn with an autoencoder is employed to predict indoor pm2.5 concentrations in residential buildings, achieving low prediction errors [22]. another study explores the application of rnns for temperature forecasting using multivariate time series data from five chinese cities. the researchers developed rnn-based models using atmospheric variables such as temperature, dew point, humidity, air pressure, and wind speed [21]. after that, in 2023, the feed-forward and elman neural networks were utilized to estimate monthly temperatures in turkey based on geographical and periodic inputs, achieving reliable long-term predictions [20]. additionally, the rnn models were developed for forecasting temperature in chinese cities using multivariate time series data, incorporating ridge regularizer and bayesian optimization [21]. the lstm rnn model produced the lowest prediction error. these studies highlight the effectiveness of neural networks in improving forecasting accuracy for weather-related applications. later in 2024, a three-phase hybrid prediction model is proposed, which integrates complete ensemble empirical mode decomposition with adaptive noise (ceemdan), local mean decomposition (lmd), and ann to enhance shortand long-term weather forecasting accuracy. the model is demonstrated to outperform both standalone and two-phase hybrid approaches for multi-step temperature predictions in the upper east region of ghana. its effectiveness in reducing non-stationary, non-linear, and volatile signal components suggests promising applications in weather index insurance and climate risk management in agriculture [23]. these studies demonstrate the potential of various neural network architectures in enhancing weather and air quality forecasting, offering improved accuracy and resolution compared to conventional approaches. the integration of hybrid models and advanced optimization techniques has contributed to more robust and scalable forecasting frameworks. as a result, greater reliability in decision-making for climate-sensitive sectors such as agriculture and insurance has been achieved. advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 299 3. methodology this section presents the methodology applied to analyze and forecast daily average temperature data. the approach includes data description and modeling using both deterministic and stochastic components. a fourier series was employed to model seasonality, while the stochastic behavior was captured using the ou process and the elman recurrent neural network (ernn). the model evaluation criteria were also described. 3.1. experimental environment all experimental procedures were performed on a lenovo ideapad 530s-14ikb, featuring an intel core i5-8250u processor, 16 gb of ram, and a 256 gb ssd, operating on windows 10 pro. the software environment utilized r version 4.4.1 within rstudio version 2024.04.2+764. various r packages supported the analysis: the forecast package facilitated fourier series modeling and statistical testing, while the rsnns package, an r interface to the stuttgart neural network simulator, enabled ernn implementation. a fixed random seed (set.seed(51237)) was applied across all pertinent experiments to ensure the consistency and reproducibility of the neural network model. 3.2. data description the daily maximum and minimum temperatures of chiang mai, thailand, recorded between january 2005 and december 2021 by the thai meteorological department, were used to compute the daily average temperatures. this dataset, spanning over 17 years, provides sufficient temporal coverage to observe seasonal trends and long-term variability. to enable a clearer statistical analysis, february 29 was excluded to maintain uniformity in the time series. descriptive statistics such as mean, median, standard deviation, skewness, and kurtosis were calculated to examine the distribution and variability of the data. the temperature values ranged from 11.05°c to 35.15°c, indicating a significant spread. the presence of a slightly left-skewed distribution and moderate kurtosis reflects variability that is essential for validating both linear and non-linear models used in this study. 3.3. temperature model the daily average temperature data was divided into a seasonal component and a stochastic component, which could be easily written as t t t t d x= + (1) where tt is the daily average temperature at time t, dt is the seasonal component at time t and xt is the stochastic component at time t [7]. in this work, the seasonal component, dt, was modelled using a deterministic function, which was a fourier series, which effectively captures periodic patterns in the data. meanwhile, the stochastic component, xt, was modelled using the ou process and the ernn to capture both mean-reverting behavior and complex nonlinear dynamics. 3.4. fourier series analysis the fourier series is based on the concept that any periodic signal can be represented as a sum of sine and cosine functions, each with different frequencies [24]. this approximation is obtained by calculating the coefficients that define the amplitude of each component in the series. therefore, fourier techniques are widely used to describe periodic data, which is suitable for applying to temperature data [25]. advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 300 for a real-valued integrable function d(t), the trigonometric form of the fourier series representation of d(t) is shown as 0 1 ( ) ( cos( ) sin( )) n n n n n d t a a n t b n t   = = + + (2) where 𝑎0 is the direct current offset of data (n = 0), 𝑎𝑛 is the sine amplitude of the nth harmonic, bn is the cosine amplitude of the nth harmonic, n is the order of the harmonic analysis, and ωn is the frequency [26]. the value of 𝑎0, 𝑎𝑛 and bn are also called the fourier coefficients of y(t) [24]. in this study, since the data set was daily data, the frequency of the fourier series was computed as 𝜔𝑛 = 2𝜋 365 . typically, the original time series was approximated by using a limited number of terms from the fourier series, determined by selecting an appropriate order for the series [27]. after applying the daily average temperature data to the fourier series model, the parameters were estimated by the ordinary least squares method in multiple regression. 3.5. the ornstein-uhlenbeck process the ou process [7] is the most widely used model for deseasonalized data, xt, and the stochastic differential equation is expressed as ( )dx x dt dw t t t   = − + (3) where xt denotes the stochastic component at time t, 𝛼 denotes the mean reversion coefficient, 𝛽 represents the drift of the process, 𝜎 is the volatility, wt is the standard wiener process. an exact solution for eq. (3) is expressed by ( ) ( ) (1 ) t t s t s t u t s u s x x e e e e dw       − − − − − = + − +  (4) where s < t. a discrete form of eq. (4) is written as 2 1 1 (1 ) 2 k k k k k k e x x e e        −  −  −  + − = + − + (5) where xt denotes the stochastic component at time t, 𝛼 denotes the mean reversion coefficient, 𝛽 represents the drift of the process, 𝜎 is the volatility, and 𝜔𝑘 represents a sequence of independent and identically distributed (iid) standard normal random variables [7]. using the approach proposed by tang and chen [28], the parameters xt are estimated through the following equations 1 log( ) = − (6) 2  = (7) ( ) 1 2 3 12 1   − = − (8) where 1 2 1 1 1 1 1 1 1 2 2 2 1 1 1 ( ) n n n i i i i i i i n i i i n x x n x x n x n x  − − − − = = = − − − − = − = −     (9) advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 301 1 1 1 1 2 1 ( ) 1 n i i i n x x   − − = − = −  (10) 1 2 3 1 1 2 1 1 [ (1 )] n i i i n x x    − − = = − − − (11) where �̂� is the estimated mean reversion coefficient, �̂� represents the estimated drift of the process and �̂� is the estimated volatility. the procedure of the fourier-ou process model is illustrated in fig. 1. the input temperature data are first decomposed into two components: the seasonal component and the stochastic component. the seasonal component is captured using the fourier series. simultaneously, the stochastic component is modeled using the ou process to obtain the random part. these two outputs are then combined to reconstruct the final output. this modeling framework enables the separation of periodic trends and random fluctuations, facilitating more accurate forecasting of time series behavior. input t stochastic component seasonal component ou-process fourier series d̂ ˆ ˆx d+ output t x̂ fig. 1 the procedure of the fourier-ou process model 3.6. the elman recurrent neural network artificial neurons are arranged in layers and connected, similar to synapses in the brain. the internal layers are known as hidden layers, which contain any number of neurons. the final layer is the output layer, where the number of neurons coincides with the number of outputs. increasing the number of neurons and layers enhances the learning capacity of ann, enabling them to process more complex data [29]. fig. 2 structure of elman recurrent neural network [8] advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 302 based on this foundational framework, more sophisticated architectures, such as the ernn, have been developed to capture and retain contextual information within a hidden layer. the ernn represents a simple recurrent neural network that consists of input layers, hidden layers, output layers, and recurrent layers or context layers [8-9]. through the recurrent layer of the ernn, outputs from the hidden layer are fed back to the hidden layer. this evaluative process enables the ernn to acquire, identify, and generate spatial and temporal patterns. a single neuron in the hidden layer is connected to a single neuron in the recurrent layer with a constant weight of one. therefore, the recurrent layer acts almost as a snapshot of the previous state of the hidden layer. the number of neurons in the recurrent layer is equal to the number of neurons in the hidden layer. a neuron in each layer transfers information to the next by calculating a nonlinear function of its combined weighted inputs. as a result of this setup, the network is capable of efficiently processing and responding to complex patterns [8]. fig. 2 shows the ernn model, where m is the number of input layers, n is the number of hidden layers and one output unit. let eit be the set of input vectors of neurons at time t where i = 1, 2,…, n, xt+1 be the output of the network at time t + 1, hjt be the output of the hidden layer at time t where j=1, 2, …, m, and cjt be the recurrent layer where j = 1, 2, …, m. αij is the weight that links the node i in the input layer to the node j in the hidden layer. βj, δj are the weights that link the node j in the hidden layer, to the node in the recurrent layer and the output layer, respectively. the hidden layer works as follows: the inputs to all neurons in the hidden layer are provided by 1 1 ( ) ( 1) ( ) n m jt ij it j jt i j net k e k c k  = = = − +  and (12) ( ) ( 1), 1, 2,..., , 1, 2,..., jt jt c k h k i n j m= − = = (13) the outputs of the recurrent layers are expressed as ( ) 1 1 ( ) ( 1) ( ) n m jt h jt h ij it j jt i j h f net k f e k c k  = = = = − +         (14) where the activation function, 𝑓𝐻, in the recurrent layer is a linear function. the output of the hidden layer is shown as 1 1 ( ) ( ) m t t j jt j x k f h k + = =        (15) where 𝑓𝑇 is a linear function as the activation function [8]. the procedure of the fourier-ernn model is shown in fig. 3. the input temperature series is separated into a seasonal component and a stochastic component. the seasonal component is extracted using a fourier series to produce the deterministic part, while the stochastic component is modeled using the ernn. this hybrid architecture enables the model to capture both regular periodic patterns and complex temporal dependencies. input t stochastic component seasonal component ernn fourier series d̂ ˆ ˆx d+ output t x̂ fig. 3 the procedure of the fourier-ernn model advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 303 3.7. model evaluation in this study, the effectiveness of the models was assessed using the quantitative statistics containing rmse and mean absolute error (mae), which are widely used measures of the difference between predicted values and actual observed values [30]. 1 1 ( ) n tt t rmse y y n = = − (16) and 1 | | n tt i y y mae n = − =  (17) where yt is the actual daily average temperature at the time t, �̂�𝑡 is predicted temperature value at the time t from the hybrid model and n is the number of observations. 4. result the daily average temperature data for chiang mai, thailand, during the period from january 2005 to december 2021 is shown in fig. 4. the dataset contains 6,205 values, with any missing data filled using linear interpolation. february 29th was removed to simplify the calculations. fig. 4 the average temperature of chiang mai between january 2005 to december 2021 in addition, table 1 provides some statistics about the temperature data. the minimum and maximum temperatures recorded are 11.05°c and 35.15°c, respectively. this indicates a temperature range of about 24°c. the standard deviation of 2.799 and variance of 7.835 reflect a moderate level of variability. table 1 descriptive statistics of temperature data descriptive statistics value mean 27.489 median 27.950 standard deviation 2.799 variance 7.835 min 11.050 max 35.150 skewness -0.587 kurtosis 3.501 advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 304 although the mean value of 27.489 and the median value of 27.950 are relatively close, suggesting near symmetry, the skewness value of -0.587 indicates a slightly left-skewed distribution. the negative skewness and kurtosis values above 3 suggest that there are some extreme values, especially on the lower side. 4.1. seasonal component the average temperature data is fitted using a fourier series model. the coefficients of the fourier series are determined using the least squares method and the significant coefficients are selected. this approach allows for the effective capture of periodic fluctuations within the annual temperature cycle. the resulting function represents the deterministic seasonal behavior of the temperature data and can be written as ( ) ( ) ( ) ( ) ( ) ( ) 2 2 4 4 6 ( ) 27.489 2.673cos 0.590 sin 1.507 cos 0.652 sin 0.249 cos 365 365 365 365 365 6 0.194 sin 365 t t t t t y t t       = − + − − − − (18) the multiple r-squared value is 0.6569, which means that about 65.69% of the variance in the dependent variable is explained by the independent variables in the model. the comparison between the fourier series model as the blue line and the data set as the orange line is shown in fig. 5. fig. 5 the comparison between the fourier series model and the data set 4.2. stochastic component according to eq. (1), the deseasonalized data, xt, is then computed and modeled using the ou process and the ernn. after applying the deseasonalized data, xt, to the ou process, the parameters 𝛼, 𝛽 and 𝜎 are estimated and shown in table 2, which represent the speed of mean reversion, the drift of the process, and the process volatility, respectively. table 2 parameters of the stochastic model parameters α β δ 0.25641 0.00296 1.17392 furthermore, the graph comparison between the actual data and the fourier ou prediction is shown in fig. 6. the orange line represents the actual daily average temperature, while the green dashed line indicates the values predicted by the fourier ou model. the predicted values closely follow the observed data, capturing both seasonal trends and short-term fluctuations. advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 305 fig. 6 the comparison between actual data and fourier ou prediction then the deseasonalized data, xt, is also applied to the ernn where the number of lags is 1 and the number of hidden layers is 73. then the output of the network is obtained. in the next step, the stochastic component is then combined with the seasonal component to complete the model as eq. (1). the comparison between actual data and fourier-ernn prediction is shown in fig. 7. fig. 7 the comparison between actual data and fourier-ernn prediction 4.3. models evaluation as a result of the fourier ou process, there are relatively higher errors. the rmse of 2.29997 indicates that the average squared difference between the actual and predicted values is large, indicating that the ou process is ineffective to capture in capturing the precise fluctuations of temperature data. according to the mae value of 1.81456, the predicted values are off by approximately 1.81 units from the actual values. the performance of each model is evaluated by rmse and mae and shown in table 3. table 3 the performance of each model models rmse mae fourier ou process 2.29997 1.81456 fourier-ernn 0.10670 0.03661 in comparison to the fourier-ernn model, the fourier-ernn model shows significantly better performance with significantly lower error metrics. an rmse of 0.10670 means that the predicted values are much closer to the actual values, with smaller squared errors. the mae of 0.03661 indicates that, on average, the predicted values are off by only 0.03661 units from the actual values, which is relatively small. advances in technology innovation, vol. 10, no. 3, 2025, pp. 296-308 306 5. discussion the findings confirm that the fourier-ernn model performs better than the fourier ou process in predicting the daily average temperature of chiang mai, thailand. the comparison of rmse and mae values shows that the fourier-ernn model provides more accurate forecasts by capturing seasonal trends and random variations more effectively. the rmse of the fourier-ernn model is 0.10670, which is much lower than the 2.29997 obtained from the fourier ou process, highlighting the advantage of the hybrid neural network approach. the observed enhancement in prediction accuracy aligns with previous studies that have demonstrated the efficacy of anns in handling complex temperature dynamics. prior research has shown that recurrent neural networks, particularly lstm and elman networks, can effectively model temperature fluctuations by capturing non-linear relationships in historical climate data. the results highlighted the advantages of deep learning models over traditional stochastic methods [20-21]. this suggests that integrating a fourier series for seasonality adjustment with ernn for stochastic modeling can provide a robust framework for temperature prediction. however, several limitations are acknowledged in this study. the accuracy of the fourier-ernn model depends on hyperparameter tuning and training data selection, which may affect generalizability under changing climate trends. periodic updates and recalibration are required. the dataset from 2005 to 2021 may not fully capture extreme climate events or long-term temperature shifts. additionally, only temperature data were used, while including factors such as humidity, air pressure, and wind speed could improve prediction accuracy. 6. conclusions in this study, historical weather data from chiang mai, thailand, were analyzed to develop a predictive model for daily average temperatures. the model incorporates a fourier series to account for seasonal trends, along with stochastic components modeled using an ornstein-uhlenbeck (ou) process and an elman recurrent neural network (ernn). the research aims to evaluate the model's accuracy and explore its applications in understanding climate patterns and mitigating risks. based on the findings, the main conclusions are as follows: (1) based on rmse and mae metrics, the fourier-ernn model significantly outperforms the ou process in predicting daily average temperatures. 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[30] m. a. rubi, s. chowdhury, a. a. a. rahman, a. meero, n. m. zayed, and k. a. islam, “fitting multi-layer feed forward neural network and autoregressive integrated moving average for dhaka stock exchange price predicting,” emerging science journal, vol. 6, no. 5, pp. 1046-1061, 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 2-v8n3(2023)-aiti#9196(177-191).docx advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 english language proofreader: chih-wen teng innovative steel pennon plate-headed stud of shear connectors for composite structures rahul tarachand pardeshi*, prakash abhiram singh, yogesh deoram patil department of civil engineering, sardar vallabhbhai national institute of technology, surat, gujarat, india received 04 january 2022; received in revised form 06 may 2022; accepted 15 may 2022 doi: https://doi.org/10.46604/aiti.2023.9196 abstract this study proposes an innovative pennon plate-headed stud of shear connectors. the proposed stud consists of two triangular-shaped steel plates on both sides of the headed stud; it is expected to increase the shear capacity of a steel-concrete composite connection. nonlinear finite element analysis is carried out using abaqus to analyze the response of 54 models of pph studs. a full factorial design and the analysis of variance are employed in the design of experiments (doe). the impacts of factors and their interactions, such as the thickness and height of the pennon plates, concrete grades, and stud diameters, are captured by using 33 × 21 doe with a 5% significance level. the results show that the ultimate shear resistance is increased apparently. additionally, the concrete grade and stud diameter significantly influence the capacity of the connection. moreover, connection slip is greatly affected by concrete grade, the height of the plate, and the interaction between plate thickness and height. keywords: pushout test, pennon plate-headed stud, headed stud, shear connector, composite structure 1. introduction fig. 1 shows a composite construction that consists of steel beams and reinforced concrete (rc) slabs. in this composite construction, longitudinal shear forces are transmitted across the interface through the mechanical action of shear connectors. composite structures are advantageous for reducing the overall structural weight, boosting load capacity, and reducing construction depth. therefore, it is widely adopted in the construction of modern buildings and highway bridges. headed stud shear connectors are typically utilized for transferring longitudinal shear in composite beams [1]. the shear resistance of the connection in composite elements is primarily influenced by the stud shear resistance and the compressive strength of the concrete slab [2]. the slip capacity of the connection at the steel-concrete beam interface affects the overall structural behavior [3]. pushout tests have long been the primary method for determining the load-slip behavior of shear connectors in composite structures. although experimental displacement with load increment provides helpful information through the pushout test, the required experimental procedure is either impractical or prohibitively expensive for studying a large number of parameters. sun et al. [4] experimentally investigated the performance of a headed stud welded to a composite deck for the effect of decking type, presence, and direction of rib on shear capacity. deng et al. [5] combined headed studs and perfobond ribs to enhance composite structure shear behavior. konrad and kuhlmann [6] investigated the bearing resistance of headed studs used in trapezoidal steel sheeting to determine the effect of the stud’s location in the trough and other geometric factors on the failure mode. chen et al. [7] investigated the thermo-structural response of shear connectors implanted in composite slabs with sheeting parallel to a steel beam. eurocode 4 [8] produced a conservative estimate of the ultimate strength of the material at * corresponding author. e-mail address: rahultpardeshi@gmail.com advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 178 elevated temperatures. imagawa et al. [9] studied the effect of heat on the performance of headed stud shear connectors. the study revealed that marginal heating affects the maximum shear resistance of headed studs, but it significantly reduces the slip constant during and after the fire. shim and kim [10] carried out an experimental study to reduce the number of studs at the end joint to reduce congestion and enhance the constructability of the joint. the study recommended the new bent stud to improve the bond strength of studs effectively in joint regions. suwaed and karavasillis [11-12] developed a novel bolted demountable shear connector for precast structures. it aids in speedy construction and disassembly. the shear strength increases by 10% compared to conventional headed shear connectors. also, the stiffness, slip capacity, and resilience of the slab become better. pathirana et al. [13] experimentally investigated the load-slip behavior of welded shear studs and blind-bolt connectors in normal concrete and grout. the study revealed the efficiency of the welded shear studs with grouting latter for retrofitting works. parametric studies showed an enhanced shear capacity with increased grout strength and height of the studs. yang et al. [14] advanced the bolted shear studs by assembling a short bolt, a long bolt, and a coupler. however, the static pushout tests displayed shank failure of short bolts under the couplers. fig. 1 typical arrangement of a steel-concrete composite connection [1] in comparison, analytical approaches can forecast the nonlinear response of the number of pushout tests with shear connectors of complex geometry. mirza and uy [15] used finite element (fe) analysis to investigate the effects of various strain regimes on the strength prediction and load-slip behavior of shear connections in composite structures. qureshi et al. [16] investigated the shear effect of single and double studs in trough-profiled steel sheeting using fe analysis. vigneri et al. [17] showed the significance of the location of plastic hinges in headed stud shear connections and slip considerations that relate to the progressive crushing of concrete in steel beam-profile sheeting concrete slab ribs through numerical simulations. by using an fe technique, mia and bhowmick [18] created a system using a pushout specimen-based fatigue life estimation system for headed shear stud connections. the primary critical aspect in composite steel beam-rc slab construction is a shear failure at connection. pardeshi et al. [19] proposed an innovative shear connector called a concave type shear connector made up of regular reinforcement to save stud steel material and easy to speedy in-situ fabrication of shear connector. due to the cylindrical shape and small circular section of the regular-headed stud, it has limited shear resistance and moment of inertia. generally headed studs are failed in shear due to a high concentration of stresses near the bottom of the stud [19]. the composite action of the composite structure is completely dependent upon the shear capacity of the shear connector. the composite action is directly co-related to the shear capacity of the shear connector. the stronger the shear resistance gets, the better the capacity of the composite structure will be. the capacity of the conventional headed stud shear connector is low, hence, many studs are required in the composite beam to provide the desired shear resistance. the current study aims to propose an innovative pennon plate-headed (pph) studs shear connector for better shear resistance of composite connection than regular circular-headed stud shear connectors. the triangular-shaped steel plates similar to the pennon have been welded to the shank of a standard-headed stud shear connector to form the pph stud. then, the base of pph studs should be welded to the flange of the steel beam and embedded in a concrete slab when in use. steel beam-rc slab composite structure normal headed stud advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 179 this study uses fe analysis to explore the performance of pph studs in composite action for strength and load-slip behavior over the standard-headed stud shear connector. the parametric studies using full factorial design of experiments (doe) have been investigated for analyzing the effect of parameters on shear connection performance. the effect of the pennon plate thickness (t), the height of the pennon plate (h), different grades of concrete (fc), and stud diameter (d) as key parameters, and their interactions are considered in the investigation. the present study is the first extensive research on the steel plates welded to the shank of the stud in composite structures for their strength and load-slip performance. fig. 2 depicts the construction of the proposed pph stud with a total height (h) of 100 mm. fig. 2 the proposed pph studs 2. shear connector finite element model (a) front view (b) side view (c) top view fig. 3 the geometry of specimens (all dimensions are in mm) (a) a quarter model (b) transparent view of specimens fig. 4 3d model of specimens the pushout test is modeled using fe analysis [20]. the shear connectors, steel beams, reinforcement, and concrete slabs are the influential components of the shear connection behavior in the composite beam. precise interaction between components is essential to get accurate results as geometric and material nonlinearity is involved in fe analysis. the specimen geometries are shown in fig. 3. figs. 4 (a)-(b) show a quarter model and a transparent view of specimens. fe simulation is made possible by modeling a quarter of the specimen because of the symmetry in the specimens. fe analysis results of pph studs are compared with regular circular-headed stud analysis results to check the comparative performance. also, the load-slip capacity of pph studs and the conventional 19 mm regular circular-headed stud for c40 and c50 grade concrete are compared by using finite element analysis. pennon plate headed stud t h h z y x pph stud partition plane rebars base block advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 180 2.1. element type and meshing the concrete slab and a steel beam section are meshed using the c3d8r solid element. the rebar is used as the t3d2 truss element in modeling. the base block is described as a rigid element r3d4. the complex geometry caused by pph studs near the interface between concrete and stud, and the stud with plate requires tetrahedron elements (c3d10) to resolve the complexity of the analysis. the fe modeling of the specimens is shown in fig. 5. initially, the assumed mesh size around the shear connector hole area is 5 mm and 40 mm in the rest of the concrete area. the finite element simulation showed a variation of 12% in the results. hence, the mesh size of 4.5 mm was considered for the concrete slab area around the stud hole and 25 mm in the rest of the concrete slab for the accuracy of mesh convergence. (a) concrete slab (b) steel beam and pph stud (c) rebar and base block fig. 5 meshing of fe model 2.2. constrain conditions and interaction the components are arranged and appropriately positioned to create the specified model. the interactions between components are described using appropriate constraints. the tie constraint is applied to tie nodes of the stud surface to the concrete slab hole surface around the stud, as shown in fig. 6(a). the surface between the concrete and steel beam flange is connected using a surface-to-surface contact interaction as shown in fig. 6(b); the contact interaction utilized no friction as these parts are assumed to be lubricated. the tie constraint is applied to the steel beam-stud base interface in fig. 6(c), considering perfect welding between two surfaces. the rebars are placed in the concrete slab subjected to the embedded constraint. at the contact surface between the base block and the concrete slab, contact interaction (0.15) is used as per the nguyen and kim [21] analytical study to justify the boundary conditions. (a) stud and stud hole in the slab (b) vertical surface of slab and beam (c) stud bottom surface and vertical surface of the beam fig. 6 constrain and interaction surfaces 2.3. boundary conditions and loading since the geometry of the pushout test setup is symmetric, the symmetric boundary condition (sbc) is applied to the specimen surfaces of symmetric planes in figs. 7(a)-(b). because the rigidity of the base block is not movable, all degrees of freedom of the rigid base reference node are constrained in fig. 7(c). loading is applied as a downward displacement to the top surface of the steel beam, as shown in fig. 7(d). the amplitude function is used to increase the applied displacement linearly. the dynamic explicit method is used in this investigation since it effectively deals with discontinuous and contact problems. z y x advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 181 for validation of the fe model, the load is applied with a displacement of 16 mm with a time one amplitude function, whereas in the parametric studies, the load is applied with a displacement of 25 mm with a time 1.56 amplitude function, keeping the same rate of loading. (a) y-axis symmetric (b) x-axis symmetric (c) fixed rigid base (rp) (d) loading (rp-1) fig. 7 boundary conditions of the fe model 2.4. concrete material model and properties uniaxial stress-strain curves for compressive and tensile concrete behavior are shown in fig. 8(a) and (b), respectively. the concrete damage plasticity (cdp) model from abaqus simulated the nonlinear concrete behavior [20]. concrete compression has three parts of the curve. the first portion is in the elastic range of the relative limit state. the relative limit stress for the first linear portion of the curve is set to 0.4 fcm and fcm = 0.8 fcu, where fcm and fcu are cylindrical and cube compressive strength of concrete in mpa, respectively. as per eurocode 2 [22], the value of strain (%) corresponding to fcm is εc1 = 0.7 fcm 0.31. the initial young’s modulus ��� [22] is determined by: ( ) ( ) 0.3322 10 0.1= × × cm cm e mpa f (1) in concrete, the poisson’s ratio is 0.2. in the second segment, the nonlinear parabolic component of the curve begins at the relative limit of stress 0.4 fcm and progresses to the concrete capacity fcm. the nonlinear parabolic segment of the curve [22] follows: ( ) 2 , 0.4 1 2 κξ ξ κ ξ  − = < <  + −  ci cm cm ci cmf f for f f f (2) where � � 1.1��� � �/��� , ξ � ��/ �, and 0.4��� ���⁄ � �� � �. the third section of the curve is the section from fcm to a value of ����. as per eurocode 2 [22] and ellobody et al. [23], factor α varies between 0.5 to 1 depending on the compressive strength of the concrete. for the present study, α = 0.85 is referred from nguyen and kim [21] for good calibration of fe results. the third section ends at εcu = 0.0035 as per guidelines provided by eurocode 2 [22], but for good agreement of experimental results with fe analysis, εcu = 0.01 is adopted in the detailed parametric investigation as per nguyen and kim [21]. the tension curve for concrete can be divided into two segments. as per specifications given by eurocode 2 [22], the tensile curve exhibits linear behavior up to the highest stress, it is referred to as the tensile strength of concrete fctm by: ( ) 2 3 0.3 8= − cm cm f f (3) the second segment is called tension stiffening. ( ) 0.4 , ε ε ε ε ε= < < ct ctm ctr ct ctr ct ctu f f (4) advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 182 the tension stiffening is defined by the weakening function as per eq. (4) given by wang and hsu [24] up to the total tensile strain, εctu = 0.005 [21]. εctu is taken into account after cracking strain εctr at fctm as shown in fig. 8(b). (a) compressive behavior (b) tensile behavior fig. 8 stress-strain relationship for concrete material concrete material nonlinearities in compression and tension are simulated by using damaged plastic models based on uniaxial material constitutions. the damage variable dc = 1 – (fci / fcm) for compression damage and dt = 1 – (fct / fctm) for tension damage is specified as a phase of modulus deterioration. flow potential eccentricity (0.1), material dilation angle (30), strength ratio in biaxial to uniaxial condition (1.16), and deviatoric cross-section parameter (k = 0.667) are used to define the cdp (concrete damage plasticity) model. the yield surface in the deviatory plan is derived from the mohr-coulomb yield surface function in cylindrical coordinates for various values of k ranging from 0.5 (rankine yield surface) to 1 (von mises yield surface) [25]. abaqus user manual suggested values for flow potential eccentricity = 0.1 and biaxial/uniaxial compressive strength ratio as 1.16 [20]. a dilation angle of 30° is iteratively adjusted to match the findings of push-out tests. several values of kc range from 0.5 to 1. table 1 describes the properties of concrete used in verification and parametric study. table 1 concrete properties concrete properties verification model [25] grade of concrete c30 c40 c50 fcm (mpa) 26.2 38 48 58 εc1 (%) 2.2 2.3 2.45 fctm (mpa) 2.45 2.9 3.5 4.1 ecm (gpa) 21.5 33 35 37 2.5. reinforcement, structural steel, and pph stud properties the bi-linear curve is used to depict the stress-strain relationship of structural and reinforcing steel as shown in fig. 9(a). the material properties used for the pph shear connector (a stud and two pennon plates made of the same material) and structural and reinforcing steel are described in table 2. the material modeling for pph stud is done by the tri-linear stress vs. strain curve, as presented in fig. 9(b). this research aims to study the behavior of the connector; hence, reinforcement in pushout specimens does not carry the load and only acts as confinement to concrete. more accurate material behavior is obtained using a trilinear stress-strain curve than a bi-linear curve. as headed stud has prime importance in shear action for the pushout test; therefore, for higher accuracy tri-linear curve approach is utilized in modeling pph stud material properties. the behavior of the material is elastic initially. after reaching the elastic limit, the yielding of the material occurs as a result of strain-softening. the stress at yield (σys) is calculated at εys = 0.2%, and the ultimate stress (σu) is determined at εu = 0.6% [21]. the material damage and failure options in the material model for shear stud connections are used as input to model the post-ultimate stress behavior of the. the damage initiation criterion and the damage evolution response are included in modeling material failure, as shown in fig. 10. advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 183 (a) reinforcement and structural steel (b) shear connector fig. 9 stress-strain relationship of steel material fig. 10 damage evolution response table 2 pph stud, structural steel, and rebar material properties pph stud structural steel rebar es (gpa) σy (mpa) σu (mpa) es (gpa) σy (mpa) es (gpa) σy (mpa) 216.2 410 466 200 320 210 510 2.6. verification of fe model in this study, the pushout experimental setup of loh et al. [26] is used. the third test is considered for fe modeling. the geometrical and material properties of the 19 mm diameter and 100 mm height circular-headed stud are taken from the literature by loh et al. [26]. the stud modulus of elasticity was 2.162 gpa at 0.2 percent proof stress of 410 n/mm2, with 466 n/mm2 tensile strength and 16.1 percent elongation [26]. the experimental results showed that the third test was used to validate the fe analysis results of the present modeling [26]. the support constraint is eased in this work by lowering the friction coefficient in the contact surface interaction between the concrete slab and base block to 0.15 [21]. for experimental and fe analyses, the maximum load and corresponding slip are 111 kn and 4 mm, respectively. the experimental and numerical results of the pushout tests are in good agreement as shown in fig. 11. fig. 11 comparative verification of the results 0 0.5 1 1.5 2 2.5 3 0 0.2 0.4 0.6 0.8 1 d is p la ce m en t (m m ) damage variable (d) 0 20 40 60 80 100 120 140 0 2 4 6 8 10 12 14 s h ea r re si st an ce ( k n ) slip (mm) experimental results (loh et al. [26]) fe model results-mesh 25 fe model results-mesh 40 advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 184 3. parametric study the parameters considered for the study are headed stud diameter, concrete grade, pennon plate thickness, and height. the types of stud diameter (d) used are 16 mm, 19 mm, and 22 mm. the pennon plates of thicknesses 2 mm, 3 mm, and 4 mm are used. the three different concrete grades used are c30, c40, and c50. the pennon plate height is considered as 1/3rd (0.33 h) of the total height (h) of the stud for 16 mm d, 19 mm d, and 2/3rd (0.67 h) of the total height (h) of the stud for 22 mm d as shown in fig. 12. the combinations of the 54 models are analyzed based on the doe. (a) 16 mmᴓ (0.33 h) (b) 16 mmᴓ (0.67 h) (c) 19 mmᴓ (0.33 h) (d) 19 mmᴓ (0.67 h) (e) 22 mmᴓ (0.33 h) (f) 22 mmᴓ (0.67 h) fig. 12 parametric details of pph stud shear connector doe is a systematic method for establishing a relationship between the variables influencing a process and its outcome [27]. this study evaluates the performance of shear connectors, such as shear resistance and slip behavior, as an output under the influence of pushout loading for different factors. the factors are headed stud diameter (d), grade of concrete (fc), pennon plate thickness (t), and the height of the pennon plate (h). the levels are considered low (-), intermediate (i), and high (+). table 3 shows the variables (factors) and their levels examined in the fe analysis. furthermore, the effects of d, fc, t, h, and their interactions are investigated using a three-level-three-factor (-, i, + levels and d, fc, t factors) with two-level-one-factor (-, + levels and h factor) full factorial doe, and analysis of variance (anova). thus, a full analysis of 33 × 21 = 27 × 2 = 54 factor combinations is required. anova is a statistical technique for comparing two or more sets of data [27]. the significance level is set at 0.05. minitab [28] is used to do statistical analysis on these models and establish run orders. table 3 factors and levels no. factors levels low intermediate high 1 d (mm) 16 19 22 2 fc (n/mm2) 30 40 50 3 t (mm) 2 3 4 4 h (mm) 0.33 h 0.67 h 28 9 3 7 33 33 16 6 7 31 3 3 33 33 19 9 1 9 33 33 19 31 6 7 9 1 9 33 33 22 3 3 35 1 1 8 9 33 33 22 1 1 35 8 9 6 7 28 3 3 9 3 7 33 33 16 advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 185 4. results and discussion the results of fe analysis of pushout tests with various pph studs and variable concrete strength are compared with the regular-headed stud shear connector. the ultimate load per stud (p) and ultimate slip at the failure of 54 pushout specimens are revealed from fe analysis. the total reaction acting on the reference point at the top surface of a steel beam is used to calculate the load. the net difference between the nodes on the steel flange and the nodes on the concrete slab at the stud center is considered for calculating the connection slip. according to the characteristic slip capacity specified by annex b, clause b.2.5 of eurocode 4 [8], the slip for ultimate failure is considered at the point of critical damage when the material or the failure is assumed at the 10% load fell below the ultimate load. the verification curve as a typical load-slip relationship per stud for pushout specimens of a 19 mm stud diameter is shown in fig. 11. table 4 shows the comparison between the load-slip capacity of the pph studs and the conventional 19 mm circular stud load-slip capacity for c40 and c50 concrete. it can be observed that with the addition of plates to conventional studs, the ultimate strength of the shear connection is increased up to 63% to 77% when utilizing a 2 mm to 4 mm thick plate. according to eurocode 4 [8] guidelines, the shear connector is called ductile if the ultimate slip of connection is equal to or more than 6 mm. it can be seen from fea results that the ductility criteria have been satisfied by all pph studs and all are justified for practical implementation with advantages increment in ultimate strength. some descriptive results of fe analysis are elaborated in the following subsection. the significance and interaction of factors based on doe and anova are also prescribed. table 4 comparisons of the shear resistance of pph stud with a conventional circular stud grade of concrete circular stud shear resistance (kn) pph studs for 0.33 h (kn) 2 mm 3 mm 4 mm c40 136.00 222.03 237.11 242.54 c50 144.83 235.87 256.66 256.63 4.1. considering the effect of an increase in concrete strength when a 16 mm diameter stud with 4 mm plate thickness and 1/3rd height of plate is considered as a constant parameter, the shear connection strengths observed are 199.26 kn, 224.86 kn, and 246.15 kn at the concrete grades c30, c40, and c50 respectively. the values of the ultimate slip are observed as 18.08 mm, 16.01 mm, and 15.33 mm respectively. hence, with the increase in concrete grade, the ultimate shear resistance of the stud is increased by 12.85% for c40 grade and 23.53% for c50 grade, in comparison with c30 grade concrete as shown in fig. 13. however, the ultimate connection slip is decreased by 11.44% for c40 and 15.21% for c50 grade. when a 19 mm diameter stud with 4mm plate thickness and 1/3rd height of the plate is considered as a constant parameter, the shear connection strength for c30 grade concrete is observed as 220.14 kn, and the value of ultimate slip is observed as 20.62 mm. the ultimate shear resistance of the stud is increased by 10.17% for c40 grade and 16.57% for c50 grade, relative to c30 grade concrete. however, the ultimate connection slip is decreased by 2% for c40 and 26% for c50 grade. when a 22 mm diameter stud with 4 mm plate thickness and 1/3rd height of plate is considered as a constant parameter, the shear connection strength for c30 grade concrete is observed as 227.35 kn, and the value of ultimate slip is observed as 19.37 mm. the ultimate shear resistance of the stud is increased by 9.68% for c40 grade and 15% for c50 grade, relative to c30 grade concrete. in contrast, the ultimate connection slip is decreased by 4.59% for c40 and 34.53% for c50 grade. based on the above results, it can be stated that the shear resistance of composite connections increases when the strength of the concrete of the rc slab increases, while the ultimate slip at failure decreases. advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 186 (a) shear resistance (b) ultimate slip fig. 13 the effect of the grade of concrete on shear resistance and ultimate slip performance of the composite connection 4.2. considering the effect of an increase in headed stud diameter when a 2 mm plate thickness with c40 concrete grade and 1/3rd height of plate is considered as a constant parameter, with the increase of stud diameters such as 16 mm, 19 mm, and 22 mm, the shear connection strengths observed are 219.77 kn, 222.03 kn, and 237.46 kn, respectively, and the values of ultimate slip are observed as 22.08 mm, 22.51 mm, and 21.62 mm respectively. the ultimate shear resistance of the stud is increased by 1.02% for 19 d and 8.04% for 22 d, for the 16 d stud as shown in fig. 14. whereas the ultimate connection slip is increased by 1.94% for 19 d and decreased by 2.08% for 22 d, in comparison with 16 d stud. when a 3 mm plate thickness with c40 concrete grade and 1/3rd height is considered a constant parameter, the shear connection strength of 16 d stud is observed as 219.25 kn, and the value of ultimate slip is observed as 13.92 mm. the ultimate shear resistance of the stud is increased by 8.14 % for 19 d stud and 11.31% for 22 d stud, for 16 d stud. as for, the ultimate connection slip, it is increased by 18.17% for 19 d and 46.47% for 22 d stud, in comparison with 16 d stud. when a 4 mm plate thickness with c40 concrete grade and 1/3rd height is considered a constant parameter, the shear connection strength of 16 d stud is observed as 224.86 kn, and the value of ultimate slip is observed as 16.01 mm. here, with the increase in shank diameter of the pph stud, the ultimate shear resistance of the stud is increased by 7.85% for 19 d stud and 10.90% for 22 d stud, for 16 d stud. however, the ultimate connection slip is increased by 25.92% for 19 d and 15.49% for 22 d stud, in comparison with 16 d stud. from the above observations, it can be concluded that the shear resistance of the connection increases with the increase of stud diameter, whereas no specific pattern is observed for the maximum slip at failure. and an interaction study (anova) has been required to find the influence of main factors and their interaction. (a) shear resistance (b) ultimate slip fig. 14 the effect of stud diameter on shear resistance and ultimate slip performance of the composite connection advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 187 4.3. considering the effect of an increase in headed plate thickness when a 16 mm diameter stud with c50 concrete grade and 2/3rd height of plate is considered as a constant parameter, with the increase of plate thickness such as 2 mm, 3 mm, and 4 mm, the shear connection strengths observed are 232.25 kn, 250.17 kn, and 253.57 kn, respectively. the values of the ultimate slip are observed as 12.16 mm, 9.55 mm, and 19.06 mm respectively as shown in fig. 15. therefore, with the increase in thickness of the pennon plate, the ultimate shear strength of the stud increased by 7.71% for 3 t, and 9.17% for 4 t, in comparison with 2 t plate thickness pph stud. and, the ultimate connection slip is decreased by 21.46% for 3 t and increased by 56.74% for 4 t, in comparison with 2 t plate thickness pph stud. when a 19 mm diameter stud with c50 concrete grade and 2/3rd height of plate is considered a constant parameter, the shear connection strength of 2 t plate thickness pph stud is observed as 250.09 kn, and the value of ultimate slip is observed as 10.48 mm. here, with the increase in the pennon plate thickness of the pph stud, the ultimate shear resistance of the stud is increased by 1.86% for 3 t stud and 3.75% for 4 t stud, 2 t plate thickness pph stud. however, the ultimate connection slip is increased by 92.17% for 3 t and 35.68% for 4 t stud, in comparison with 2 t plate thickness pph stud. when a 22 mm diameter stud with c50 concrete grade and 2/3rd height of plate is considered as a constant parameter, the shear connection strength of 2 t plate thickness pph stud observed is 265.26 kn, and the value of ultimate slip is observed as 18.58 mm. here, with the increase in the pennon plate thickness of the pph stud, the ultimate shear resistance of the stud is increased by 1.13% for 3 t stud and 1.28% for 4 t stud, in comparison with 2 t plate thickness pph stud. whereas, the ultimate connection slip is decreased by 37.94% for 3t and 54.46% for 4t stud, in comparison with 2 t plate thickness pph stud. from the above observations, it can be concluded that the shear resistance of connection is not much affected by the increase of plate thickness in pph studs. whereas the maximum slip at failure is influential due to changes in thickness; thus, an interaction study has been required to find the interaction effect of plate thickness with other main factors. (a) shear resistance (b) ultimate slip fig. 15 the effect of the thickness of the pph plate on shear resistance and ultimate slip performance of the composite connection 4.4. considering the effect of an increase in pennon plate height when a 16 mm diameter stud with c40 concrete grade and 3 mm plate thickness is considered as a constant parameter, with the increase of the pennon plate height from 1/3rd of total height to 2/3rd of total height, the shear connection strengths observed are 219.25 kn and 224.84 kn respectively, and the values of ultimate slip are observed as 13.92 mm and 10.72 mm respectively. hence, with the increase in the height of the pennon plate, the ultimate shear resistance of the stud is increased by 1.02% for 0.67 h, for 0.33 h plate height pph stud as shown in fig. 16. and, the ultimate connection slip is decreased by 29.85% for 0.67 h. advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 188 when a 19 mm diameter stud with c40 concrete grade and 3 mm plate thickness is considered as a constant parameter, with the increase of the pennon plate height from 1/3rd of total height to 2/3rd of total height, the shear connection strengths are observed as 237.11 kn and 236.85 kn respectively, and the values of ultimate slip are observed as 16.44 mm, and 20.37 mm respectively. thus, with the increase in height of the pennon plate, the ultimate shear resistance of the stud is almost the same for 0.67 h. whereas the ultimate connection slip is decreased by 23.90% for 0.67 h. when a 22 mm diameter stud with c40 concrete grade and 3 mm plate thickness is considered as a constant parameter, with the increase of pennon plate height from 1/3rd of total height to 2/3rd of total height, the shear connection strengths observed are 244.05 kn and 256.22 kn respectively, and the values of ultimate slip are observed as 20.38 mm, and 17.98 mm respectively. therefore, with the increase in the height of the pennon plate, the ultimate shear resistance of the stud is increased by 4.98% for 0.67 h. however, the ultimate connection slip is decreased by 11.77% for 0.67 h. from the above observations, it can be concluded that the increase of pennon plate height from 0.33 h to 0.67 h for the shear resistance of the connection is not much effective compared to other factors, and a future study is needed on the effect of the height of pennon plate (below 0.33 h) on strength capacity of pph stud. whereas the maximum slip at failure is influential due to changes in thickness; thus, an interaction study has been required to find the interaction effect of plate height with other main effective factors. (a) shear resistance (b) ultimate slip fig. 16 the effect of pph pennon plate height on shear resistance and ultimate slip performance of the composite connection 4.5. the effect of critical factors on shear connectors performance based on doe and anova for a total of 54 specimens run, a pushout fe analysis is performed for each combination of three levels of the three factors and two levels of one factor. fig. 11 depicts a typical pushout analysis result for a high level of each factor, the two performance output responses, ultimate strength of connection, and failure slip. anova can investigate the main effects of input factors and potential interactions on the response variable [27]. this approach separates the dominant factors and interactions that affect the response variable from the less critical factors and interactions, identifying which factors significantly affect the response [27]. as a result, anova analysis is performed to examine the primary influence of four variables and potential interactions at a significance level (α) of 5% using a two-sided confidence interval. the conclusions are drawn from the p-value. the p-value is the lowest threshold α at which the data are statistically significant [27]. each effect with a p-value less than 0.05 is deemed to have a statistically significant impact on the response with 95% confidence. table 5 shows the results of an anova study for shear carrying capacity and ultimate slip at various limiting variables. as presented in table 5, the main effects of fc and d have p-values of less than the 5% significance level. therefore, these factors significantly affect the shear capacity of the connection. moreover, the main effect of fc, h, and interaction between t and h considerably affect the ultimate slip capacity of the pph stud connection. advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 189 table 5 influence of key parameters on shear resistance and ultimate slip of connector based on anova descriptions no. parameters and interactions p-values shear resistance ultimate slip main parameters effect 1 concrete grade (fc) < 0.0001 0.004 2 headed stud diameter (d) < 0.0001 0.818 3 the thickness of the pennon plate (t) 0.212 0.524 4 height of pennon plate (h) 0.395 0.015 two-way interactions 5 fc × d 0.305 0.119 6 fc × t 0.980 0.996 7 fc × h 0.997 0.907 8 d × t 0.976 0.087 9 d × h 0.718 0.917 10 t × h 0.982 0.004 fig. 17 describes the effect of the main interaction of factors on the ultimate slip of connection. it can be concluded that the main effect of concrete strength, the height of the plate, and the interaction between the thickness and height of the pennon plate significantly affect the ultimate slip capacity of the pph stud connection. fig. 17 interaction plot for ultimate slip 5. conclusions a nonlinear fe model was developed to investigate the capacity of an innovative pennon plate-headed (pph) stud shear connector. the connection capacity and the load-slip behavior were calculated as a performance evaluation. the proposed fe analysis model conducted a parametric study for 54 pushout specimens with different concrete grades, stud diameters, plate thicknesses, and plate heights. the full factorial statistical method and anova were used to design experiments and to evaluate the interaction performance of factors and responses. from the parametric study, the following results are extracted: (1) the fe model successfully anticipates the behavior of the headed stud shear connection in composite beams with solid slabs and accurately verified the experimental results of prior research. the ultimate strength of the shear connection was improved, and the corresponding slip was affected by adding the pennon plates to the circular-headed stud. advances in technology innovation, vol. 8, no. 3, 2023, pp. 177-191 190 (2) when pph studs are utilized with c40 and c50 concrete grades, the connection ultimate shear strength increases by 63% to 77% due to the change in stud shape from regular circular-headed studs to pph studs. (3) all pph studs meet the ductility requirements specified in eurocode 4 [8]. therefore, they are justified for practical application with advantages increment in the ultimate strength. (4) the full factorial analysis reveals that the effects of the concrete grade of the rc slab and stud diameter on the ultimate strength were highly significant. the shear resistance of the connection increases with the stud diameter increases. (5) the effect of interaction among factors on the shear resistance response of pph stud has no significant influence. however, the interaction of t × h was shown to have a highly significant influence on the slip performance of the pph shear connection. the shear resistance of the connection is not much affected by the increase of plate thickness above 3 mm in pph studs. whereas the maximum slip at failure is influential due to changes in thickness. (6) the pph stud shear connectors are suitable for composite structures due to their ability to enhance the shear resistance capacity of the connection. abbreviations and symbols 3d three-dimensional ��� modulus of elasticity anova analysis of variance ��� cracking strain cdp concrete damage plasticity �� grades of concrete doe design of experiments ��� cylindrical compressive strength fe finite element ��� concrete tensile strength pph pennon plate-headed ��� cube compressive strength of concrete rc reinforced concrete h height of pennon plate d damage variable k deviatoric cross-section parameter dc compression damage t pennon plate thickness dt tension damage �� ultimate stress d stud diameter �� yield stress sbc symmetric boundary condition p ultimate load per stud h total height of pph stud conflicts of interest the authors declare no conflict of interest. references [1] r. t. pardeshi and y. d. patil, “review of various shear connectors in composite structures,” advanced steel construction, vol. 17, no. 4, pp. 394-402, december 2021. 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[28] “minitab 18 statistical software,” https://www.minitab.com/en-us/, march 01, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx strength prediction of rectangular frp-reinforced concrete columns under eccentric loading nam nguyen van1, hiep dang vu2, duy nguyen phan1,* 1faculty of civil engineering, industrial university of ho chi minh city, ho chi minh city, vietnam 2faculty of civil engineering, hanoi architectural university, hanoi city, vietnam received 09 may 2025; received in revised form 31 august 2025; accepted 24 september 2025 doi: https://doi.org/10.46604/aiti.2025.15124 abstract this study aims to develop an analytical model for evaluating the load-carrying capacity of rectangular fiberreinforced polymer (frp) reinforced concrete columns under eccentric loading. in the proposed model, the contribution of frp bars in compression is considered, with their compressive strength estimated as a fraction of tensile strength. meanwhile, the effects of confinement, tension stiffening, and second-order effects are conservatively neglected. two main failure modes, namely concrete crushing and frp rupture, are distinguished by the balanced failure condition. this model applies strain compatibility with the plane section and constitutive laws to derive stress-strain distributions across the cross-section. then, the model is validated against 91 experimental results covering diverse sections, strengths, and eccentricities (e/h = 0.1-1.0), showing high accuracy (mean: 0.932; rmse: 0.154; cov: 22.9%; sd: 0.145; r: 0.84) and outperforming aci code-440.11. analysis results also show that compressive frp reinforcement contributed between 0.94% and 22.3% to the column strength. keywords: frp, concrete column, eccentricity, analytical method 1. introduction steel-reinforced concrete (rc) structures are extensively used in buildings, transportation infrastructure, including roads and railways, hydraulic structures, and marine applications due to their many advantages. however, steel corrosion in harsh environments reduces the durability and lifespan of rc structures. fiber-reinforced polymer (frp) reinforcement for concrete structures has been under development since the 1960s and has gradually become a viable alternative to traditional steel reinforcement in specific environments, owing to its high tensile strength, corrosion resistance, electromagnetic neutrality, electrical insulation, and high strength-to-weight ratio [1]. common frp rebar types include carbon frp (cfrp), basalt frp (bfrp), aramid frp (afrp), and glass frp (gfrp) [1-2]. despite these advantages, frp-rc structures have not yet been widely adopted worldwide due to several limitations: only a few countries have developed design standards; the structural behavior of frp-rc is not fully understood; theoretical models are still being improved; and the cost of frp bars remains relatively high. as a result, research on frp-rc structures continues to attract significant attention. unlike traditional steel reinforcement, which exhibits good tensile and compressive strength as well as a high modulus of elasticity, frp reinforcement has significantly lower compressive strength compared to its tensile capacity. it also has a lower elastic modulus and behaves in a brittle manner without yielding. as a result, the structural behavior and design methodology of frp-rc columns differ markedly from those of conventional rc columns. consequently, the study of the behavior of frprc columns has attracted considerable interest from researchers worldwide [3]. * corresponding author. e-mail address: nguyenphanduy@iuh.edu.vn advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 2 although most existing research on frp-rc columns focuses on axial loading, real-world conditions rarely involve pure axial forces. eccentricity arising from load misalignment, second-order effects, or construction imperfections leads to significant moment-axial interaction, which is especially critical in frp-rc columns due to the linear-elastic behavior of frp bars. in contrast, concentrically loaded frp-rc columns have been more extensively studied, and their behavior is relatively simple and, in many aspects, analogous to that of conventional steel-rc columns. several analytical models have been proposed for such cases, often adapting existing design formulas developed for concentrically loaded steel-rc columns [4]. however, under eccentric loading, frp-rc columns exhibit more complex nonlinear behavior due to cracking, lack of yielding, and tension-compression interactions, which necessitate a dedicated modeling approach to ensure accurate predictions and safe design. studies show that frp-rc columns exhibit distinct behavior compared to steel-rc columns under eccentric compression, primarily due to linear-elastic behavior and lower modulus of elasticity of frp reinforcement [5]. unlike steel-rc columns, which display ductile yielding, frp-rc columns show brittle failure after peak load due to the absence of a yield point [6]. gfrpand bfrp-rc columns have 17-30% lower capacities than steel rc columns, whereas cfrp-rc columns have a load-carrying capacity averaging 7% lower load-carrying capacity [4, 7]. frp-rc columns experience larger longitudinal deformations but smaller crack widths. in terms of failure modes, frp-rc columns predominantly fail by concrete crushing under concentric and low-eccentricity loading, often accompanied by cover spalling or bar kinking [4]. at moderate eccentricities, failure transitions to compression-dominated or flexural-compression modes, with flexural cracking and gradual concrete degradation [8]. high-eccentricity loading results in flexural-tension failure with tension-side cracks and excessive deformations [9]. research indicates that the compressive strength of frp bars ranges from 10% to 86% of their tensile strength, depending on the fiber type [10]. while the compressive modulus of elasticity of frp reinforcement is relatively close to its tensile modulus (with a ratio between 0.97 and 1.20) [3, 10], the much lower compressive strength significantly limits its effectiveness in compressive members such as columns. studies indicate that increasing the frp reinforcement ratio in frp-rc columns from 1% to 3.8% enhances load-carrying capacity by 5-35%, particularly at high eccentricities [9, 11]. an increase in frp reinforcement ratio also enhances flexural stiffness and reduces post-peak decay [9]. despite their limited compressive strength, frp bars still contribute meaningfully to the load-carrying capacity of frp-rc columns: approximately 3-15% for gfrp, 619% for cfrp, and around 11% for bfrp, compared to 6.5-36% for steel reinforcement [4, 8]. as a result, many authors recommend accounting for the contribution of compressive frp reinforcement in design methods [3, 12]. similar to steel-rc columns, the load-carrying capacity of frp-rc columns under eccentric compression depends on several factors, including material characteristics, longitudinal reinforcement ratio, eccentricity, slenderness, and confinement effect of transverse reinforcement. slenderness amplifies second-order effects (p-δ effect) in frp-rc, resulting in greater strength degradation and larger deformations compared to steel-rc columns [5, 13]. short frp-rc columns (slenderness ratio ≤ 18) show minimal second-order effects (4-10% of total moment), allowing simplified design without considering these effects [8]. however, slender frp-rc columns require careful consideration of second-order effects [7]. transverse reinforcement, such as gfrp or cfrp ties and spirals, enhances confinement and prevents longitudinal bar buckling [14-15]. reducing tie spacing improves ductility, confinement, and residual strength, and can also shift the failure mode of the column from brittle to more ductile behavior [14-16]. tightly spaced ties tend to cause failure by concrete crushing or rupture of transverse reinforcement, whereas wider tie spacing often leads to longitudinal bar buckling [14]. current design codes like aci 440.1r-15 [17], aci code-440.11-22 [18], csa s806:2012:r2017 [19], and sp 295.1325800.2017 [20] utilize equilibrium equations and strain compatibility principles, along with an equivalent concrete stress block, to calculate the axial load-carrying capacity of eccentrically loaded frp-rc columns. in these methods, the contribution of frp bars located in the compression zone is commonly neglected and is not considered in the load-carrying advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 3 mechanism. while this assumption simplifies design and ensures safety, it often results in conservative predictions and underestimation of the actual structural capacity [4, 15]. to address this, many researchers have proposed alternative methods for calculating the load-carrying capacity of frp-rc columns under eccentric compression. sharbatdar [1] developed a plane section analysis method, validated through experiments on cfrp-rc columns, focusing on concrete crushing as the primary failure mode. choo et al. [5] employed numerical integration to derive axial load-momentcurvature relationships, accounting for slenderness effects and recommending a reduced slenderness ratio (17 vs. 22) for nonsway frames. zadeh and nanni [21] adapted aci 318-11 principles, using strain compatibility and force equilibrium to construct interaction diagrams for gfrp-rc columns. elchalakani et al. [15] modified as 3600, integrating mander’s confinement model and gfrp properties to develop moment-axial load interaction diagrams. tarawneh and majdalaweyh [12] used sectional analysis with the response-2000 software to investigate the load-carrying capacity of frp-rc columns, achieving high accuracy (reliability index >3.5). almomani et al. [11] employed gene expression programming to develop predictive models for frp-rc columns, accounting for eccentricity and slenderness. the p-δ effect has also been addressed in several studies. choo [5], xue [13], and hamid [7] all proposed analytical methods, with xue modifying aci 318-11’s moment magnifier method, and hamid implementing an iterative second-order analysis. although various analytical methods have been proposed to account for the contribution of compressive frp reinforcement in evaluating the load-carrying capacity of eccentrically loaded frp-rc columns, these approaches remain incomplete. most existing methods focus primarily on failure modes governed by concrete crushing in the compression zone, without clearly distinguishing among different possible failure mechanisms. in addition, they often rely on simplified assumptions, such as employing an equivalent rectangular stress block for concrete, which can limit both their accuracy and practical applicability. to address this gap, this paper proposes an analytical method for evaluating the load-carrying capacity of eccentrically loaded frp-rc columns, incorporating material constitutive laws and accounting for all theoretically potential failure modes. to achieve this, the following aspects are addressed: (1) classification of failure modes of frp-rc columns under eccentric compression and development of corresponding strain and stress distribution across the cross-section for each failure mode (2) formulation of internal force equilibrium equations for each failure mode and construction of a computational flowchart (3) validation of the analytical model using experimental data from previous studies and comparison of the proposed method’s accuracy with calculations based on aci code-440.11. the subsequent sections of the paper are organized as follows: section 2 presents the analytical method for evaluating the load-carrying capacity of the column along with the computational flowchart; section 3 discusses model validation; and section 4 concludes the study and offers recommendations for future research on frp-rc columns under eccentric loading. 2. analytical model development in this section, an analytical model is proposed to predict the load-carrying capacity of rectangular frp-reinforced concrete columns under eccentric compression. the model incorporates strain compatibility, force equilibrium, and material constitutive laws to capture all potential failure modes and accounts for the compressive contribution of frp rebars. compared with conventional design methods, it provides more realistic and less conservative predictions. 2.1 fundamental assumptions for calculations and constitutive laws of materials under eccentric compression, the column's cross-section is conventionally divided into two zones: the zone on the side of the applied force, which undergoes higher compressive stress, is referred to as the "compression zone"; the opposite zone, which experiences lower compressive stress or tension, is referred to as the "tension zone". the analytical method is developed based on the following assumptions: the plane section remains plane; the bond resistance between the concrete and frp rebars advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 4 is constant; the strain compatibility and force equilibrium are satisfied; the maximum compressive strain of concrete (εcu) is 0.0035; the tensile resistance of concrete is ignored due to concrete's low tensile strength and the presence of cracks. also, it should be emphasized that the present model is limited to short-term analysis of short frp-rc columns under eccentric compression. it does not account for p–δ effects, confinement effects, softening behavior of concrete, or time-dependent phenomena such as creep, shrinkage, and load duration. to accurately assess the behavior of concrete, a simplified bilinear stress–strain relationship for compression, as defined in sp 63.13330.2018 [22], was adopted (fig. 1 (a)). meanwhile, a linear stress-strain relationship is used for frp reinforcement under both compression and tension (fig. 1 (b)). the contribution of frp reinforcement in compression is considered in the calculations, with its compressive strength (ffcu) defined as a fraction of its tensile strength (ffu): fcu f fuf f , where βf is a coefficient representing the compressive-to-tensile strength ratio of the frp rebar. , 1, c c red c red f e     ; ,c c c rede  fcu f fuf f (a) concrete (b) frp rebar fig. 1 constitutive laws of materials 2.2 analytical formulation for the balanced failure mode (a) cross-section (b) balanced failure mode (c) failure mode governed by concrete crushing (d) failure mode governed by frp rupture fig. 2 cross-section geometry, strain, and stress distributions on the normal section for various failure modes studies have shown that the failure of eccentrically loaded frp-rc columns can occur either in the tension zone due to rupture of the frp bars, or in the compression zone, where concrete crushing takes place while the frp remains intact [5, 14, 21]. to distinguish between these two failure modes, a balanced failure condition is established. in this case, failure occurs simultaneously in both the tension and compression zones. specifically, when the tensile strain in the frp bars and the advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 5 compressive strain in the extreme concrete fiber both reach their ultimate limits at the same time. fig. 2 illustrates the crosssection geometry, the corresponding strain and stress distributions for all possible failure modes, derived based on the material constitutive laws (fig. 1) and the strain compatibility condition. the height of the compression zone under balanced failure condition (cb) is determined based on fig. 2 (b) as cu b fu cu d c      (1) where d is the effective depth, and εfu denotes the ultimate tensile strain of frp rebar. the resultant forces in the concrete compression zone c1 and c2 can be found by 1 1 1 2 cc bc f  (2) 2 2 cc bc f  (3) where b is the width of cross-section, β denotes the conversion factor from cylinder to prism compressive strength, and f'c represents the cylinder compressive strength of concrete. in addition, c1 and c2 are the heights of the compressive concrete stress blocks, show in fig. 2 (b), they can be computed by 1 bc c  (4)  2 1bc c   (5) where α is the coefficient determined by 1, 1, 1 1 cu c red c red        (6) where εc1,red is the limiting strain value at the transition between the elastic range and the horizontal plateau in the bilinear stress-strain diagram according to sp 63.13330.2018 [22], εc1,red = 0.0015. the strain (εfc) and the corresponding resultant force (cf) in the frp rebar located in the compression zone are calculated by b fc cu b c a c     (7) b f fc f cu f b c a c a e c     (8) where afc and ef denote the total area of frp rebar in the concrete compression zone and its elastic modulus, respectively; a' is the distance from the centroid of the compressive reinforcement to the extreme compression face of the section. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 6 the resultant force in tensile frp rebar can be expressed as f fu ft f a (9) where af denotes the total area of frp rebar located in the concrete tension zone or in the less compressed region (in case of full-section compression). the internal equilibrium of axial force and bending moment is expressed by eqs. (10) (11), respectively: 1 2b f fp c c c t   (10) 1 1 2 2b c c f fc f fm c z c z c z t z    (11) where zc1, zc2, zfc, and zf represent the lever arms associated with the resultant forces c1, c2, cf, and tf, respectively (fig. 2 (b)). when calculating moments about an axis that passes through the centroid axis and is perpendicular to the bending plane, these values are calculated as 1 1 2 2 3 c ch z c   (12)  2 20.5cz h c  (13) 2 fc h z a  (14) 2 f h z a  (15) the eccentricity of the axial force in the case of balanced failure is determined by b b b m e p  (16) based on the compression zone height or eccentricity at the balanced failure condition, the failure mode of the column is classified as follows: if c ≥ cb or eexp ≤ eb , failure initiates in the concrete compression zone; conversely, if c < cb or eexp > eb, the column fails due to rupture of the tensile frp reinforcement, where e is the eccentricity induced by external loading. 2.3 analytical formulation for the failure mode governed by concrete crushing the concrete crushing failure mode in the compression zone is the predominant failure mode for frp-rc columns subjected to eccentric compression. this failure mode is observed in nearly all experimental research results. failure occurs when the compressive strain in concrete (on the loaded edge) reaches its ultimate value εcu (fig. 2 (c)). the tensile (εf) and compressive strains (εfc) in frp rebars are determined by f cu fu d c c      (17) advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 7 fc cu fcu c a c        (18) where c represents the depth of the compression zone of the cross-section, and εfcu denotes the ultimate compressive strain of frp rebars. the resultant tensile force (tf) and compressive force (cf) in the frp reinforcement are determined by f f f cu d c t e a c    (19) f f f f cu c a c e a c     (20) the resultant force in the concrete compression zones c1 and c2 can be found by 11 1 2 ccc b f  (21) 2 2 cc bc f  (22) where c1 and c2 are the heights of the compressive concrete stress blocks, as shown in fig. 2 (c), and can be computed by 1c c (23) 2 (1 )c c  (24) the internal equilibrium of axial force and bending moment is expressed, respectively, by 1 2 f fp c c c t   (25) 1 1 2 2c c f fc f fm c z c z c z t z    (26) where the lever arms zc1, zc2, zfc, and zf are determined by eqs. (12) (15). the eccentricity of the axial force is determined by m e p  (27) 2.4. analytical formulation for the failure mode governed by frp rupture in the case of failure due to frp rupture, the tensile strain in the frp reinforcement reaches its ultimate limit. based on the strain distribution diagram for this failure mode (fig. 2 (d)), the strain values in the materials are determined with respect to the depth of the compression zone. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 8 the strain and resultant force in the frp rebar located in the compression zone can be determined by ( ) fu fc c a d c      (28) f fc f f fc e a  (29) the resultant force in frp rebar located in the tension zone can be computed by f fu ft f a (30) maximum strain in the outermost compressed concrete fiber can be found by fu c c d c     (31) the resultant force in the compressed concrete area is determined based on the strain in the outermost compressed fiber. when 1,c c red  , the stress distribution in the concrete compression zone is split into two regions, as illustrated in fig. 2 (d). accordingly, the heights c1 and c2 of these zones, along with their respective resultant forces c1 and c2, are calculated by 1, 1 ( ) c red fu c d c     (32) 2 1c c c  (33) 1 1 1 2 cc bc f  (34) 2 2cc f bc  (35) the load-carrying capacity of the column is determined using the axial force and moment equilibrium eqs. (25) (26), with the lever arms in eq. (26) calculated based on eqs. (12) (15). when 1,c c red  , due to the small compressive strain in the concrete, the stress in the compression zone follows a triangular distribution. as a result, resultant force c2 equals zero, and c1 is calculated by 1 1 2 c credc bc e (36) where ec,red denotes the reduced deformation modulus of compressive concrete. the internal equilibriums of axial force and bending moment are expressed by eqs. (25) (26), respectively. the lever arms zfc and zf in eq. (26) are calculated based on eqs. (14) (15), while the lever arm zc1 is calculated by 1 2 3 c h c z   (37) advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 9 the eccentricity of the axial force for this failure mode is determined in the same manner as for the failure mode governed by concrete crushing, that is, according to eq. (27). 2.5. calculation flowchart the theoretical load-carrying capacity of an eccentrically loaded frp-rc column is determined through the following procedure: first, the failure mode is identified based on the comparison between the balanced eccentricity (eb) and the applied eccentricity (eexp). next, an iterative calculation process is carried out: for each assumed value of the compression zone height (c), the corresponding force components (c1, c2, cf, and tf) and their respective lever arms (zc1, zc2, zfc, and zf) are calculated. these values are then used to determine the axial force (p), bending moment (m), and theoretical eccentricity (e). the iteration continues until the theoretical eccentricity (e) closely matches the experimental eccentricity. at this point, the corresponding p and m values represent the theoretical load-carrying capacity of the column. the calculation flowchart is illustrated in fig. 3. fig. 3 flowchart for calculating the load-carrying capacity of frp-rc columns under eccentric loading 3. model validation to validate the proposed model, a dataset of 91 rectangular-section frp-rc columns subjected to eccentric axial compression was compiled from 16 different sources [1, 4, 6-9, 14, 16, 23-30]. these experimental specimens were sourced from reputable peer-reviewed journals published between 2003 and 2024. a summary of the key parameters is presented in table 1, with complete descriptions provided in the appendix. the dataset exhibits a wide variation in geometry, material properties, and loading conditions, enabling comprehensive validation across different structural configurations. column dimensions (length: 780 2000 mm; width and height: 150 405 mm) indicate a broad range of slenderness ratios (λ = 13.23 39.35), which significantly influence stability under eccentric loading. the reinforcement types include gfrp, cfrp, and bfrp, with total reinforcement ratios (ρft) ranging from 0.38% to 3.88%. these variations affect the stiffness and ductility of the columns. the eccentricity ratio (e/h = 0.096 1.0) captures a spectrum from nearly concentric to highly eccentric loading. the concrete compressive strength (f′c = 27.73 47.3 mpa) spans from normal-strength to moderately advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 10 high-strength concrete, affecting confinement behavior and strain compatibility, especially in failure modes involving concrete crushing or frp bar instability. the wide-ranging properties presented in the dataset not only validate the model’s robustness but also provide insights into how geometric and material parameters influence column behavior under eccentric axial compression. table 1 summary of experimental parameters of the tested columns collected from previous studies year l, mm b, mm h, mm λ rebar ρft, % ffu, mpa ef, gpa e/h f'c, mpa 20032025 7802000 150405 150405 13.2339.35 gfrp cfrp bfrp 0.383.88 347.52550 32.67151 0.0961.0 27.7347.3 as previously mentioned, the ratio of compressive to tensile strength of frp reinforcement varies over a wide range. therefore, to verify the model, a conservative reduction factor of βf = 0.3 is adopted, in line with recommendations from previous studies [3]. additionally, the compressive strength of cubic concrete samples was converted to cylindrical sample strength using a factor of 0.893. beyond being verified against experimental data, the proposed model was also compared with theoretical outcomes derived from the aci code-440.11 [18] (paci, paci,nor), which neglects the compressive contribution of frp reinforcement. the appendix details the load-carrying capacity of the experimental columns as predicted by both the proposed method and aci code-440.11. fig. 4 compares the normalized load-carrying capacities predicted by the proposed model and those calculated using the aci code-440.11 standard. the proposed model shows slightly better alignment with experimental data. (a) proposed model (b) aci code-440.11 fig. 4 comparison between theoretical and experimental normalized load-carrying capacity, and possible error distribution histograms the statistical comparison in table 2 demonstrates that the proposed method provides improved accuracy over aci code-440.11 in predicting the behavior of frp-rc columns under eccentric compression. specifically, the proposed model yields a mean value of 0.932, closer to the experimental results than the aci code-440.11's 0.896. its pearson correlation coefficient (r) of 0.84 also slightly exceeds the aci’s 0.83, indicating enhanced consistency in predictions. while the coefficient of variation (cov) and standard deviation (sd) are comparable between the two approaches, the proposed model shows a modest but meaningful improvement in estimating the load-carrying capacity. it is also worth noting that a compressive strength reduction factor of βf = 0.3 was adopted in the verification process, representing a conservative 0 0.25 0.5 0.75 1 0 0.25 0.5 0.75 1 p p ro p ,n o r. pexp,nor. 0 0.25 0.5 0.75 1 0 0.25 0.5 0.75 1 p a c i, n o r. pexp,nor. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 11 assumption. in practice, the compressive strength of frp bars may be higher; therefore, the accuracy of the proposed model could further improve and align more closely with the experimental results. overall, the proposed method offers a more accurate and reliable alternative for the design of frp-rc columns subjected to eccentric loading. table 2 statistical comparison of theoretical against experimental results method pprop.nor/pexp.nor rmse cov, % sd r proposed 0.932 0.154 22.9 0.145 0.84 aci code-440.11 0.896 0.161 22.7 0.148 0.83 in addition to the comparative statistical metrics mentioned earlier, the reliability of the computational method is further assessed through the ratio pprop.nor/pexp.nor for key parameters affecting the load-carrying capacity of eccentrically compressed frp-rc columns. these parameters include concrete strength, slenderness ratio, eccentricity ratio e/h, elastic modulus of frp rebar, strength of frp rebar, and reinforcement ratio as shown in fig. 5. from fig. 5, it is evident that the predictions yield a nearly flat trend for all variables except the reinforcement ratio (fig. 5 (f)). in this case, the negative slope indicates an underestimation of the load-carrying capacity. (a) relation pprop.nor/pexp.nor and f’c (b) relation pprop.nor/pexp.nor and λ (c) relation pprop.nor/pexp.nor and e/h (d) relation pprop.nor/pexp.nor and ef (e) relation pprop.nor/pexp.nor and ffu (f) relation pprop.nor/pexp.nor and ρf fig. 5 accuracy of the proposed analytical model in predicting the behavior of frp-rc columns, under eccentric loading for various structural parameters to assess the contribution of frp reinforcement to the axial compressive capacity, the relationship between the ratio cf/pprop and the compressive reinforcement ratio ρfc is constructed and shown in fig. 6. it is evident from fig. 6 that the contribution of frp bars to the column's load-carrying capacity is substantial and increases progressively with higher reinforcement ratios. based on the results of 91 tested columns, the contribution of compressive frp reinforcement ranges from 0.94% to 22.28%, with an average value of 4.25%, corresponding to a variation in ρfc from 0.19% to 1.94%. however, it should be noted that the contribution of frp reinforcement to axial capacity is not solely governed by the compressive reinforcement ratio, but also significantly influenced by other parameters, such as load eccentricity, tie spacing, material 0 0.5 1 1.5 2 25 30 35 40 45 50 p p ro p ,n o r/ p ex p .n o r. . f'c, mpa 0 0.5 1 1.5 2 10 20 30 40 p p ro p ,n o r/ p ex p .n o r. . λ 0 0.5 1 1.5 2 0 0.25 0.5 0.75 1 p p ro p ,n o r/ p ex p .n o r. . e/h 0 0.5 1 1.5 2 30 65 100 135 170 p p ro p ,n o r/ p ex p .n o r. . ef, gpa 0 0.5 1 1.5 2 0 700 1400 2100 2800 p p ro p ,n o r/ p ex p .n o r. . ffu, mpa 0 0.5 1 1.5 2 0.0% 0.5% 1.0% 1.5% 2.0% p p ro p ,n o r/ p ex p .n o r. . ρf advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 12 properties, and cross-sectional geometry. fig. 6 contribution of compressive frp reinforcement additionally, the current experimental data on eccentrically loaded frp-rc columns remain limited in both the number of specimens and the range of test parameters, particularly the degree of eccentricity. among the 91 specimens compiled from prior studies (see appendix), eccentricity values range only from 0.096 to 1.0, with no instances of high eccentricity. as a result, failure in these specimens is typically due to concrete crushing in the compression zone, while the frp reinforcement in the tension zone generally remains intact. therefore, the analytical model proposed in this study has not been validated for failure modes involving frp rupture, highlighting a significant research gap. this issue is intended to be addressed in future studies through both experimental testing and numerical simulations. furthermore, the proposed model does not yet account for key factors affecting column load-carrying capacity, such as longitudinal bending, the role of transverse reinforcement, or random eccentricity. consequently, discrepancies persist between the theoretical load-carrying capacity predicted by the model and experimental results, which are not yet fully satisfactory. addressing these challenges will be a primary objective of future research. 4. conclusions this study developed an analytical model to predict the load-carrying capacity of rectangular frp-rc columns under eccentric compression. the proposed model is established based on strain compatibility and force equilibrium conditions. it incorporates the specific stress-strain relationships of both concrete and frp reinforcement and also considers the contribution of compressive frp rebars to the overall sectional capacity. the model was validated using a database of 91 experimentally tested columns collected from reputable publications. the main findings can be summarized as follows: (1) two primary failure modes of frp-rc columns under eccentric compression were identified: concrete crushing and frp rupture, separated by a balanced failure condition. (2) an analytical approach and a corresponding computational framework were established to estimate the load-carrying capacity across all possible failure modes of frp-rc columns under eccentric loading. (3) the proposed model demonstrated high predictive accuracy, with a mean predicted-to-experimental strength ratio of 0.932, rmse = 0.154, cov = 22.9%, sd = 0.145, and correlation coefficient r = 0.84, outperforming aci code-440.11 in most cases. (4) the contribution of compressive frp reinforcement was found to be significant, enhancing column strength by 0.94% to 22.3%, depending on reinforcement ratio and eccentricity. this finding highlights the importance of including the contribution of compressive frp rebars in design formulations rather than neglecting them for conservative design. despite its promising performance, the model remains limited in scope. it does not account for p–δ effects, confinement from transverse reinforcement, or time-dependent behavior. furthermore, the current dataset lacks sufficient high-eccentricity columns to validate failure modes governed by frp rupture. future research should address these limitations and explore the influence of longitudinal bending and multi-layer frp reinforcement. these advancements would broaden the applicability ò the model and support its integration into design codes. 0% 6% 12% 18% 24% 0.0% 0.5% 1.0% 1.5% 2.0% c f/ p p ro p . ρfc 0% 6% 12% 18% 24% 0.0% 0.5% 1.0% 1.5% 2.0% c f/ p p r o p . ρfc 0% 6% 12% 18% 24% 0.0% 0.5% 1.0% 1.5% 2.0% c f/p pr op . ρfc advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 13 conflicts of interest the authors declare no conflict of interest. notation a distance from the centroid of the tensile reinforcement (af) to the outermost tension fiber of the cross-section a' distance from the centroid of the compressive reinforcement (afc) to the extreme compression face of the section af total area of frp rebar located in the concrete tension zone or in the less compressed region (in case of fullsection compression) afc total area of frp rebar in the concrete compression zone b width of the cross-section of the column c depth of the compression zone of the cross-section cb depth of the compression zone of the cross-section at the balanced failure c1 depth of the rectangular stress block in the concrete compression zone c1 resultant compressive force in the concrete compression zone with uniformly distributed stress c2 depth of the triangular stress block in the concrete compression zone c2 resultant compressive force in the concrete compression zone with triangularly distributed stress cf resultant internal force in frp rebar in the concrete compression zone d effective depth of the cross-section of the column e eccentricity of the axial force ec, red reduced the deformation modulus of compressive concrete eexp experimental eccentricity of the axial force eb theoretical eccentricity of the axial force at balanced failure mode ef elastic modulus of frp rebar f’c cylinder compressive strength of concrete ffcu ultimate compressive strength of frp rebar ffu ultimate tensile strength of frp rebar h height of the cross-section of the column l total length of the tested column m bending moment c.a. centroid axis n.a. neutral axis p axial force pexp experimental axial force pexp. nor normalized experimental axial force pexp.nor = pexp/(0.85f’cag) pprop axial force obtained from the proposed analytical method pprop.nor normalized axial force obtained from the proposed analytical method pprop.nor = pprop/(0.85f’cag) paci axial force calculated according to the aci code-440.11-22 paci.nor normalized axial force calculated according to the aci code-440.11-22 tf resultant internal force in frp rebar located in the concrete tension zone or in the less compressed region (in case of full-section compression) zc1 lever arm of the compressive force c₁, i.e., the distance from the line of action of c₁ to the centroid axis zc2 lever arm of the compressive force c2, i.e., the distance from the line of action of c2 to the centroid axis zf lever arm of the tensile force tf, i.e., the distance from the line of action of tf to the centroid axis zfc lever arm of the compressive force cf, i.e., the distance from the line of action of cf to the centroid axis α coefficient  1 1 1 1 /cu c red c red        β conversion factor from cylinder to prism compressive strength βf conversion factor for translating frp tensile strength to its equivalent compressive strength εc compressive strain in concrete εc1,red limiting strain value at the transition between the elastic range and the horizontal plateau in the bilinear reduced stress-strain diagram according to sp 63.13330.2018, εc1, red = 0.0015 εcu ultimate compressive strain of concrete εf tensile strain in frp rebar εfc compressive strain in frp rebar εfcu ultimate compressive strain of frp rebar εfu ultimate tensile strain of frp rebar λ slenderness ratio of the column σc compressive stress in concrete ρf tensile reinforcement ratio ρfc compressive reinforcement ratio advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 14 ρft total reinforcement ratio, ρft = ρf + ρfc references [1] m. k. sharbatdar, “concrete columns and beams reinforced with frp bars and grids under monotonic and reversed cyclic loading,” ph.d. dissertation, department of civil engineering, university of ottawa, ottawa, 2003. 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[30] s. a. emam, o. amer, a. h. ali, and h. a. haggag, “experimental investigation on the compressive behaviour of gfrp-reinforced concrete short columns,” engineering research journal, vol. 184, no. 3, pp. 44-58, 2025. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). appendix table a1 database of tested eccentrically loaded frp-rc columns ref. specimen’s id geometry main reinforcement conc rete test results proposed aci code440.11 l, mm b, mm h, mm d, mm λ e/h frp type af, mm2 ρft, % ffu, mpa ef, gpa f'c, mpa pexp, kn pexp.nor pprop pprop .nor paci paci. nor sharbatdar [1] cfs1 1680 230 230 226 25.4 0.26 cfrp 100.6 0.38 2550 147 47.3 1020 0.48 1077.6 0.51 1053 0.5 cfs2 1680 230 230 226 25.4 0.33 cfrp 100.6 0.38 2550 147 47.3 1000 0.47 875.6 0.41 841.2 0.4 cfs3 1680 230 230 226 25.4 0.26 cfrp 100.6 0.38 2550 147 47.3 1200 0.564 1077.6 0.51 1053 0.5 cfs4 1680 230 230 226 25.4 0.33 cfrp 100.6 0.38 2550 147 47.3 960 0.451 875.6 0.41 841.2 0.4 issa, et al. [23] gn8 1200 150 150 144 27.8 0.33 gfrp 226.2 2.01 347.5 32.67 27.7 227.1 0.428 228.9 0.43 217.4 0.41 gn13 1200 150 150 144 27.8 0.17 gfrp 226.2 2.01 347.5 32.67 27.7 425.8 0.803 362.6 0.68 353.6 0.67 gm8 1200 150 150 144 27.8 0.33 gfrp 226.2 2.01 347.5 32.67 38.4 535.8 0.731 304.7 0.41 291.3 0.4 hadi and youssef [24] rf-25 800 210 210 177 13.2 0.12 gfrp 253.4 1.15 1641 67.9 31 995 0.856 888.6 0.76 879 0.76 rf-50 800 210 210 177 13.2 0.24 gfrp 253.4 1.15 1641 67.9 31 615 0.529 632.5 0.54 615.9 0.53 elchalakani and ma [14] g150-25 1200 160 260 228 16 0.1 gfrp 380.1 1.83 708 50 32.75 880.3 0.76 935.4 0.81 930 0.8 g150-45 1200 160 260 228 16 0.17 gfrp 380.1 1.83 708 50 32.75 584.2 0.504 771.7 0.67 753.8 0.65 g75-25 1200 160 260 228 16 0.1 gfrp 380.1 1.83 708 50 32.75 917.2 0.792 935.4 0.81 930 0.8 g75-35 1200 160 260 228 16 0.14 gfrp 380.1 1.83 708 50 32.75 787.8 0.68 856.2 0.74 841.1 0.73 sun, et al. [6] z175-1 1000 180 250 225 13.9 0.7 gfrp 235.5 1.05 1103 92.4 29.9 201 0.176 240.7 0.21 225 0.2 z175-2 1000 180 250 225 13.9 0.7 gfrp 235.5 1.05 1103 92.4 29.9 174 0.152 240.7 0.21 225 0.2 z175-3 1000 180 250 225 13.9 0.7 gfrp 235.5 1.05 1103 92.4 29.9 181 0.158 240.7 0.21 225 0.2 z125-1 1000 180 250 225 13.9 0.5 gfrp 235.5 1.05 1103 92.4 29.9 291 0.254 336.6 0.29 316 0.28 z125-2 1000 180 250 225 13.9 0.5 gfrp 235.5 1.05 1103 92.4 29.9 290 0.253 336.6 0.29 316 0.28 z125-3 1000 180 250 225 13.9 0.5 gfrp 235.5 1.05 1103 92.4 29.9 347 0.303 336.6 0.29 316 0.28 z75-1 1000 180 250 225 13.9 0.3 gfrp 235.5 1.05 1103 92.4 29.9 632 0.552 542.1 0.47 516.7 0.45 z75-2 1000 180 250 225 13.9 0.3 gfrp 235.5 1.05 1103 92.4 29.9 677 0.592 542.1 0.47 516.7 0.45 z75-3 1000 180 250 225 13.9 0.3 gfrp 235.5 1.05 1103 92.4 29.9 602 0.526 542.1 0.47 516.7 0.45 guérin, et al. [8] cga40 2000 405 405 357 17.2 0.1 gfrp 927 1.13 1317 51.3 42.3 4760 0.807 4696.2 0.80 4705.8 0.8 cga80 2000 405 405 357 17.2 0.2 gfrp 927 1.13 1317 51.3 42.3 3354 0.569 3593.1 0.61 3551.3 0.6 cga160 2000 405 405 357 17.2 0.4 gfrp 927 1.13 1317 51.3 42.3 1943 0.329 1875.5 0.32 1797.5 0.31 cga320 2000 405 405 357 17.2 0.79 gfrp 927 1.13 1317 51.3 42.3 745 0.126 813.3 0.14 769.8 0.13 cgb40 2000 405 405 357 17.2 0.1 gfrp 1038 1.27 838 48.2 42.3 4417 0.749 4699.6 0.80 4706.2 0.8 cgb80 2000 405 405 357 17.2 0.2 gfrp 1038 1.27 838 48.2 42.3 3200 0.543 3596.4 0.61 3552.2 0.6 cgb160 2000 405 405 357 17.2 0.4 gfrp 1038 1.27 838 48.2 42.3 1589 0.269 1890.1 0.32 1810.1 0.31 cgb320 2000 405 405 357 17.2 0.79 gfrp 1038 1.27 838 48.2 42.3 645 0.109 826.6 0.14 783.8 0.13 m. guérin, et al. [9] g1e10 2000 405 405 360 17.2 0.1 gfrp 927 1.13 1317 51.3 42.3 4760 0.807 4695.5 0.80 4707.3 0.8 g1e20 2000 405 405 360 17.2 0.2 gfrp 927 1.13 1317 51.3 42.3 3357 0.569 3595.7 0.61 3552.6 0.6 g1e40 2000 405 405 360 17.2 0.4 gfrp 927 1.13 1317 51.3 42.3 1942 0.329 1883.3 0.32 1803.8 0.31 g1e80 2000 405 405 360 17.2 0.79 gfrp 927 1.13 1317 51.3 42.3 745 0.126 820.7 0.14 774.9 0.13 g2e10 2000 405 405 360 17.2 0.1 gfrp 1236 1.51 1317 51.3 42.3 5028 0.853 4716.5 0.80 4707.3 0.8 g2e20 2000 405 405 360 17.2 0.2 gfrp 1236 1.51 1317 51.3 42.3 3625 0.615 3623.8 0.61 3562.3 0.6 g2e40 2000 405 405 360 17.2 0.4 gfrp 1236 1.51 1317 51.3 42.3 2035 0.345 1969.3 0.33 1881.7 0.32 g2e80 2000 405 405 360 17.2 0.79 gfrp 1236 1.51 1317 51.3 42.3 914 0.155 903 0.15 853.2 0.15 g3e10 2000 405 405 357 17.2 0.1 gfrp 2120 2.58 1122 54.4 42.3 5294 0.898 4787 0.81 4704.5 0.8 g3e20 2000 405 405 357 17.2 0.2 gfrp 2120 2.58 1122 54.4 42.3 3790 0.643 3707.3 0.63 3585.5 0.61 g3e40 2000 405 405 357 17.2 0.4 gfrp 2120 2.58 1122 54.4 42.3 2110 0.358 2157.6 0.37 2042.7 0.35 g3e80 2000 405 405 357 17.2 0.79 gfrp 2120 2.58 1122 54.4 42.3 1008 0.171 1081.8 0.18 1012.5 0.17 othman and mohammad [16] c10-t90-e0.5 1500 150 150 124 34.7 0.5 cfrp 157 1.4 2000 150 44.7 258 0.302 249.8 0.29 236.8 0.28 c10-t90-e1.0 1500 150 150 124 34.7 1 cfrp 157 1.4 2000 150 44.7 119 0.139 125.9 0.15 119 0.14 c12-t90-e0.5 1500 150 150 123 34.7 0.5 cfrp 226.2 2.01 2000 145 44.7 262 0.306 265.5 0.31 249.1 0.29 c12-t90-e1.0 1500 150 150 123 34.7 1 cfrp 226.2 2.01 2000 145 44.7 126 0.147 137.6 0.16 129.5 0.15 c16-t90-e0.5 1500 150 150 121 34.7 0.5 cfrp 402.2 3.58 2000 151 44.7 290 0.339 296.8 0.35 268.9 0.32 c16-t90-e1.0 1500 150 150 121 34.7 1 cfrp 402.2 3.58 2000 151 44.7 137 0.16 161.6 0.19 146.8 0.17 advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 16 table a1 database of tested eccentrically loaded frp-rc columns (continued) ref. specimen’s id geometry main reinforcement conc rete test results proposed aci code440.11 l, mm b, mm h, mm d, mm λ e/h frp type af, mm2 ρft, % ffu, mpa ef, gpa f'c, mpa pexp, kn pexp.nor pprop pprop .nor paci paci. nor c12-t140-e0.5 1500 150 150 123 34.7 0.5 cfrp 226.2 2.01 2000 145 44.7 264 0.309 265.5 0.31 249.1 0.29 c12-t140-e1.0 1500 150 150 123 34.7 1 cfrp 226.2 2.01 2000 145 44.7 129 0.151 137.6 0.16 129.5 0.15 c12-t40-e0.5 1500 150 150 123 34.7 0.5 cfrp 226.2 2.01 2000 145 44.7 237.7 0.278 265.5 0.31 249.1 0.29 c12-t40-e1.0 1500 150 150 123 34.7 1 cfrp 226.2 2.01 2000 145 44.7 113 0.132 137.6 0.16 129.5 0.15 elmesalami, et al. [4] b-16-40* 1100 180 180 135 22 0.22 bfrp 402.1 2.48 1242 49.3 28.4 577 0.738 444.7 0.57 432.7 0.55 b-16-80 1100 180 180 135 22 0.44 bfrp 402.1 2.48 1242 49.3 34.4 347 0.366 270.3 0.29 261.4 0.28 g-16-40* 1100 180 180 135 22 0.22 gfrp 402.1 2.48 785 44.9 28.4 585 0.748 443 0.57 432.4 0.55 g-16-80 1100 180 180 135 22 0.44 gfrp 402.1 2.48 785 44.9 34.4 364 0.384 266.2 0.28 257.8 0.27 b-20-40 1100 180 180 133 22 0.22 bfrp 628.3 3.88 913 45.9 34.4 720 0.76 540.7 0.57 523.6 0.55 b-20-80 1100 180 180 133 22 0.44 bfrp 628.3 3.88 913 45.9 34.4 412 0.435 283.8 0.30 273.8 0.29 karimi pour, et al. [25] n-g-60-50 1000 200 200 164 17.4 0.25 gfrp 760.3 3.8 966 39.5 37.3 1378 1.087 677.8 0.53 652.6 0.52 n-g-60-100 1000 200 200 164 17.4 0.5 gfrp 760.3 3.8 966 39.5 36 631.1 0.516 346.5 0.28 329.1 0.27 r-g-60-50 1000 200 200 164 17.4 0.25 gfrp 760.3 3.8 966 39.5 40.5 1532 1.112 732.5 0.53 706.2 0.51 r-g-60-100 1000 200 200 164 17.4 0.5 gfrp 760.3 3.8 966 39.5 40 690 0.507 376.8 0.28 358.1 0.26 n-g-120-50 1000 200 200 164 17.4 0.25 gfrp 760.3 3.8 966 39.5 35 1224 1.028 638.9 0.54 613.1 0.52 n-g-120-100 1000 200 200 164 17.4 0.5 gfrp 760.3 3.8 966 39.5 35 605.4 0.509 339.1 0.28 321.7 0.27 r-g-120-50 1000 200 200 164 17.4 0.25 gfrp 760.3 3.8 966 39.5 39 1311 0.989 706.8 0.53 681.5 0.51 r-g-120-100 1000 200 200 164 17.4 0.5 gfrp 760.3 3.8 966 39.5 39 634.8 0.479 369.3 0.28 350.7 0.26 n-g-180-50 1000 200 200 164 17.4 0.25 gfrp 760.3 3.8 966 39.5 36.2 1108 0.9 659 0.54 633.8 0.52 n-g-180-100 1000 200 200 164 17.4 0.5 gfrp 760.3 3.8 966 39.5 36 592.5 0.484 346.5 0.28 329.1 0.27 r-g-180-50 1000 200 200 164 17.4 0.25 gfrp 760.3 3.8 966 39.5 39.6 1173 0.871 716.9 0.53 691.2 0.51 r-g-180-100 1000 200 200 164 17.4 0.5 gfrp 760.3 3.8 966 39.5 39 634.8 0.479 369.3 0.28 350.7 0.26 mohammed s. irhayyim, et al. [26] c1-g 1700 150 150 125 39.4 0.67 gfrp 157.1 1.4 1207 50.3 26.1 131 0.262 95.6 0.19 90.8 0.18 c2-g 1700 150 150 125 39.4 1 gfrp 157.1 1.4 1207 50.3 26.1 61 0.122 62.4 0.13 59.6 0.12 hamid and yousif [7] 31-2b10b150-40 1620 210 180 137 31.3 0.22 bfrp 402 2.13 978.6 48.26 38.5 754 0.61 695.5 0.56 683.1 0.55 31-2b10b150-80 1620 210 180 137 31.3 0.44 bfrp 402 2.13 978.6 48.26 38.5 334 0.27 341.4 0.28 330.6 0.27 31-2b10b150-120 1620 210 180 137 31.3 0.67 bfrp 402 2.13 978.6 48.26 38.5 170 0.137 212.2 0.17 205.1 0.17 15-2b10b150-40 780 210 180 137 15.1 0.22 bfrp 402 2.13 978.6 48.26 38.5 772 0.624 695.5 0.56 683.1 0.55 15-2b10b150-80 780 210 180 137 15.1 0.44 bfrp 402 2.13 978.6 48.26 38.5 395 0.319 341.4 0.28 330.6 0.27 15-2b10b150-120 780 210 180 137 15.1 0.67 bfrp 402 2.13 978.6 48.26 38.5 182 0.147 212.2 0.17 205.1 0.17 fathi, et al. [27] g1 1200 150 150 125 27.8 0.27 gfrp 157 1.40 1000 40 30 335 0.654 251.6 0.49 244.9 0.48 g2 1200 150 150 125 27.8 0.27 gfrp 157 1.40 1000 40 30 328 0.64 251.6 0.49 244.9 0.48 g3 1200 150 150 125 27.8 0.27 gfrp 157 1.40 1000 40 30 320 0.625 251.6 0.49 244.9 0.48 shakouri mahmoudabadi, et al. [28] 50-e25 1200 180 180 155 23.1 0.14 gfrp 190 1.17 750 62.5 35 847.5 0.879 697.8 0.72 690.8 0.72 100-e25 1200 180 180 155 23.1 0.14 gfrp 190 1.17 750 62.5 35 792.1 0.822 697.8 0.72 690.8 0.72 50-e75 1200 180 180 155 23.1 0.42 gfrp 190 1.17 750 62.5 35 385.6 0.4 302.2 0.31 289.1 0.3 100-e75 1200 180 180 155 23.1 0.42 gfrp 190 1.17 750 62.5 35 381.9 0.396 302.2 0.31 289.1 0.3 sadat hosseini and sadeghian [29] s20-e15 1220 203 203 170 20.9 0.15 gfrp 595.8 2.89 1020 53.7 32.5 865 0.76 820.1 0.72 790.8 0.7 s40-e15 2440 203 203 170 41.7 0.15 gfrp 595.8 2.89 1020 53.7 32.5 588 0.517 820.1 0.72 790.8 0.7 s40-e30 2440 203 203 170 41.7 0.3 gfrp 595.8 2.89 1020 53.7 32.5 558 0.49 539.7 0.47 512.1 0.45 emam, et al. [30] sc1 1500 250 250 220 20.8 0.2 gfrp 213.9 0.68 880 53.4 32.4 1018 0.591 1036.4 0.6 1026.9 0.6 sc2 1500 250 300 270 17.4 0.17 gfrp 213.9 0.57 880 53.4 32.4 1321 0.64 1370.6 0.66 1366.6 0.66 sc3 1500 250 350 320 14.9 0.14 gfrp 213.9 0.49 880 53.4 32.4 1731 0.718 1706.1 0.71 1709.2 0.71 microsoft word 6-v10n1(2025)-aiti#14091(72-83).docx advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 english language proofreader: chih-wei chang investigation of affordable technologies for real-time see-through various indoor surfaces and walls qurban ali memon*, selama tekleab, jood albedwawi, fatima alantali, alyazia ateeq aldhaheri department of electrical engineering, uae university, al ain, united arab emirates received 03 august 2024; received in revised form 28 october 2024; accepted 04 november 2024 doi: https://doi.org/10.46604/aiti.2024.14091 abstract wireless scanning for detecting objects behind various surfaces or walls in indoor settings has garnered significant interest recently. this study presents experimental results on several widely accessible, affordable, and portable see-through technologies. the technologies evaluated include a radio frequency (rf) device, a chip-sized multiple-input and multiple-output (mimo) radar, an ultra-wideband sensor, and a motion sensor. these can be used either as standalone transceivers or mounted on unmanned aerial vehicles (uavs) to extend their range, particularly for emergencies in high-rise buildings. tests on various wall and surface materials show that rf and wi-fi devices can detect objects through wood, glass, and plasterboard, but metal and concrete significantly block or limit signal penetration. the results suggest that affordable see-through technologies need to improve their performance against concrete and metals. keywords: object detection, see-through technology, affordable technology, wall scanning 1. introduction various fields like search and rescue, wave propagation through materials, and navigating spaces in urban areas create the need for object detection behind walls, a complex challenge that spans numerous fields and technologies. this technique enables the identification of vibrations and changes in signal strength, which assists in detecting objects. by measuring the signal power and phase reflected from metallic objects, it is possible to determine the presence of metal, considering different frequency ranges. moving object detection is feasible due to the alteration of object movement depending on the reflected signal strength [1]. the reflected signal strength confirms the presence of an object. even the mechanics of breathing can affect signal reflection, aiding in detection and proving crucial in emergencies, such as locating people trapped, confined in a seismic event, or fainted. previously, technologies that could see through walls were exclusive to specific governmental services such as the military [2]. however, technological advancements have currently rendered it accessible. the range-r radar system uses through-the-wall sensors (ttws) to detect motion inside buildings by emitting radio waves. operating in the 1-10 ghz range, ttws can penetrate materials like concrete and wood, whereas it is blocked by metal and water [3]. its accuracy varies with frequency, and thick walls over 12 inches or low power can weaken signals, hindering detection. most ttws have a detection range of 50-65 feet, though some with larger antennas and stronger power can reach up to 230 feet. these radars can be influenced by moving objects such as pets or curtains, and basic models only indicate whether a person is alive and in motion. more advanced devices can measure distance and direction, generating a fundamental building layout. experimental systems reveal potential for mapping unknown spaces, whereas the technology is not yet widely accessible [4]. * corresponding author. e-mail address: qurban.memon@uaeu.ac.ae advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 73 terahertz detectors are primarily used in airport inspections for imaging the human body beneath clothing. despite occasional breakthrough claims, most terahertz applications remain speculative due to signal fading and the requirement for high-power emitters. additionally, infrared cameras cannot see through walls, thereby proving the inability to penetrate materials like frosted glass or plywood. scanning through walls is challenging due to several factors, with the type of medium being the most significant [5]. different building materials can block wireless signals to varying degrees. typically, materials like silver, aluminum, copper, and tin completely block signals, while insulators like drywall, wood, glass, and plastics partially obstruct but do not fully block signals. therefore, the type of wall material is a crucial determinant in signal detection behind walls. various scientific and societal factors drive the push for advancing see-through technology for indoor walls and surfaces, e.g., see-through technology greatly enhances situational awareness, enabling law enforcement to monitor dangerous areas remotely, and improving safety. it also assists robots in navigating complex spaces boosting the efficiency of service robots in tasks such as rescue operations or maintenance. see-through technology also improves human-robot collaboration by helping robots anticipate movements in tight spaces, ensuring safer interactions. further, it could revolutionize infrastructure monitoring by enabling non-invasive tracking of internal systems like plumbing and structural components. integrating this technology into consumer devices like smartphones or tablets could enable practical applications, such as detecting studs or wall pipes. the aims of this research include investigating cost-effective technologies available in the market for adopting seethrough technology tailored to specific application environments. the structure of this paper is as follows. section 2 reviews recent literature on the technologies and methods for see-through communication. section 3 discusses the experimental findings on various affordable and portable technologies used to detect objects across different surfaces and walls within a specified range. the conclusions of this study are discussed in section 4. 2. literature review the through-the-wall radar imaging (twri) employs electromagnetic waves to penetrate building materials. these electromagnetic waves generate high-quality images of the interior areas. the technology is used for surveillance and searchand-rescue missions in areas where conventional methods fall short. the twri can detect individuals behind walls and identify their actions and postures. such an achievement can be attributed to radar imaging research, which has grown over the past two decades and concentrates on object detection, its orientation, and scale classification. li et al. [6] address the detection and tracking of human targets using small-aperture through-wall imaging radar to determine target scale and orientation. to discuss this further, further applications and findings are mentioned as follows. singh et al. [7] examine techniques for detecting stationary individuals behind walls by tracking their breathing movements. specifically, it utilizes a doppler-based method for detection and presents a novel approach employing a shorttime fourier transform. furthermore, it implements clutter reduction using singular value decomposition across different measurements. amin and ahmad [8] address signal processing algorithms that enhance imaging in environments with clutter and multipath effects, focusing on ground-based imaging systems. it covers essential topics such as mitigating wall interference, exploiting multipath signals, detecting moving targets, and using compressive sensing for faster data collection. in another work, maherin and liang [9] investigate the use of ultra-wide band (uwb) technology and informationtheoretic algorithms (such as entropy) to identify human targets concealed behind walls. they propose that periodic changes in signals caused by breathing can be detected using these techniques. the research demonstrates that this method successfully identifies humans behind gypsum and brick walls, but it is ineffective with wooden doors. in a similar application, gennarelli et al. [10] introduce a short-range radar system to detect individuals behind walls. it identifies human presence by examining 74 advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 phase shifts in the radar signal resulting from movements and breathing patterns. the paper also suggests a data processing algorithm capable of determining the presence of one or more stationary or moving individuals. experimental results show that the system provides precise and timely information in indoor settings. an innovative system [11] for detecting human respiration utilizes the impulse uwb radar technique. the system addresses challenges associated with low signal-to-noise ratios (snrs), which can lead to errors in detecting respiration, heartbeat frequency, and range. to reduce interference from overlapping heartbeat, respiration signals, and unwanted harmonics, a frequency accumulation approach is introduced. performance improvements are demonstrated through complex signal demodulation by integrating signal logarithms and derivatives. liang et al. [12] present a technique for precisely detecting vital signs with uwb radar. the method analyzes the skewness of uwb signals affected by human activities. to determine the distance from the radar, the technique employs the discrete short-time fourier transform (dsft) on skewness data. respiratory frequencies are estimated using an ensemble empirical mode decomposition (eemd)-based method, which effectively removes harmonics. terahertz radar is recognized for its potential to achieve high-resolution, see-through capabilities. however, leaky-wave antennas merge signals from the aperture into a single output, making conventional signal processing challenging. to address this, murata et al. [13] employ an iterative recovery algorithm to manage clutter and synthesize the radar’s aperture. the findings highlight the successful see-through detection of objects behind an opaque screen and the 3d reconstruction of targets from various perspectives. integrating stepped frequency continuous wave (cw) radar with deep learning techniques, such as convolutional neural networks (cnns), offers a novel solution. kılıç et al. [14] introduce a method for identifying human posture behind walls using radar signals and cnns. the radar detects signals reflected from individuals, which the cnn processes to classify whether the person is standing or sitting. this approach delivers impressive results with minimal preprocessing and less data compared to traditional methods. a novel model is developed that integrates both geometrical and statistical data from the target image. a scale-adaptive tracking method employs the mean-shift tracking framework to dynamically determine the target’s scale and orientation using image moments. to identify both stationary and moving targets, tivive and bouzerdoum [15] introduce a technique that analyzes a series of radar signals. this approach decomposes 3d radar data into a low-rank tensor and two sets of sparse images. one set represents stationary targets, while the other depicts moving targets. tests with simulated and real radar signals demonstrate the method’s ability to detect and distinguish between stationary and moving targets. in through-the-wall scenarios, traditional wi-fi-based moving target detection algorithms struggle to distinguish between multiple targets when transceivers are located on the same side of a wall. to address this, a novel detection algorithm [16] reconstructs channel state information and estimates angles of arrival and times of flight for interference signals. by subtracting the reconstructed interference, the useful signal is isolated. experimental results unveil that the algorithm improves target detection accuracy compared to existing methods. however, identifying multiple stationary human targets remains challenging due to missed detections influenced by factors such as the target’s distance and the intensity of their respiration. to overcome this, a new approach utilizing cnns has been proposed by shi et al. [17]. this method enhances the signal-to-clutter-andnoise ratio of the radar data and applies a clustering algorithm to precisely identify multiple targets. wang et al. [18] address challenges in through-wall radar human detection by introducing a novel end-to-end network that directly processes raw radar analog-to-digital converter (adc) signals, eliminating the need for traditional preprocessing techniques. conventional algorithms, such as discrete fourier transform (dft) and matched filtering, struggle with low snrs in complex environments. the proposed model includes a dft-based feature extraction module with learnable 3d convolution layers to enhance feature extraction capabilities. it also incorporates phase information and multi-task learning to improve accuracy. advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 75 single-channel cw radar is favored for its straightforward design, though it cannot determine the range or angular position of targets. ongoing research focuses on detecting life signs through walls using microwave doppler radar. pramanik and islam [19] suggest employing a single-channel 24 ghz cw radar alongside the maximal overlap discrete wavelet transform to monitor individuals’ heart rates through walls. tests involving seven subjects at distances between 20 and 100 cm through brick and wood barriers achieved a heart rate accuracy of 95.27% when compared to biopac electrocardiogram (ecg) measurements. zhang et al. [20] propose a refraction-aware wireless sensing model for through-wall scenarios, focusing on wi-fi signal propagation. they tested it with a respiration sensing system using two transceivers, achieving an error of less than 0.5 bpm in typical settings. mu et al. [21] focus on “handy” through-wall radar systems, which are low-power, narrowband, lightweight, and do not require body-worn devices. these systems detect, locate, or image humans behind walls but face challenges such as interference from fast-moving objects, urban electromagnetic noise, and dense crowds. portability is another issue, as most systems require fixed positions and bulky hardware, complicating real-time use in mobile settings. privacy concerns are also significant, highlighting the need for privacy-preserving solutions before widespread civilian adoption. in a similar literature review, jamshidi-zarmehri et al. [22] review through-wall communications, covering wall characterization, technologies, applications, and prospects, offering a valuable guide for researchers and engineers. lastly, memon et al. [23] have conducted initial research on sensing through indoor walls of varying heights and thin surfaces using portable devices. the literature review clearly shows that the majority of approaches and applications discussed rely on radar imaging and signal processing. the commercial technologies available for related applications are not cost-effective, are primarily designed for outdoor use, and lack portability. research is needed to explore alternative, cost-effective technologies for see-through communication in indoor urban environments. these settings include rooms of varying sizes with partitions, walls, and surfaces of different materials. the next section aims to address this gap. 3. experimental results this section explores the practical application of affordable, commercially available sensors. it commences with outlining the experimental methodology, detailing how each experiment was conducted and assessed. subsequently, the section delves into the specific setups and results of each experiment. lastly, it presents an analysis of different indoor wall types and surfaces, summarizing the key findings in a tabular format. 3.1. sensor types fig. 1 the concept of an experimental setup this section presents four indoor experimental setups. the setups employ commercially available, affordable, and portable devices. in fig. 1, the concept of placing a sensor on one side of the wall and detecting the moving human object on the other side is depicted. the experimental setups included different types of sensors, e.g., a motion sensor, a chip-sized 76 advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 multiple-input and multiple-output (mimo) radar, a radio frequency (rf) device, and an ultra-wideband sensor, each with a different sensing technology and detection principle. the settings were indoor with different room sizes, wall types, and surfaces. each experimental setup is discussed separately. detection through radiation: the passive infrared sensor includes a motion detector that captures temperature radiation from a targeted room (behind a concrete wall) and alerts when there is interference within 50-80 feet. this passive infrared sensor includes a motion detector that captures temperature radiation from a targeted room (behind a concrete wall) and alerts when interference emerges within 50-80 feet. an 11.5 cm thick wall divided the rooms, and when motion was detected near the transmitters, the receiver sent an alarm. in a follow-up test, the transmitter was positioned two rooms apart from the receiver, and the motion detection produced similar results. the motion detection failed when the experiment was tried on two rooms seven meters apart. detection through radar: the sensor is technically a mimo radar operating in the 1 mhz to 6 ghz range and integrated onto a chip. they detect radio waves, enabling the detection of people’s presence and movements within a 10-meter range. unlike cameras that rely on light and optics, these sensors penetrate through walls, smoke, and darkness. the reflected signals do not generate typical images. instead, they display people on a grid, enabling tracking of their breathing patterns and determining whether they are sitting, standing, or lying down. the sensors enter a 7-day learning mode after installation, focusing on understanding the standard behavior within the room. this learning period is crucial for the device to adapt and accurately identify abnormal events within the room. to summarize, three trials were conducted, one with no movement in the room, and two with movement (sitting to standing; standing to falling). in each case, the device detected the change and generated the signal. detection through rf device: the device setup included a pc with a software-defined radio, a horn antenna, a signal generator, and a receiver, operating across a wide frequency range of 1 mhz to 6 ghz. the signals created at the transmitter and received at the receiver were tuned to around 2.45 ghz. two setups with this device were prepared: (i) motion is generated behind walls when the transmitter and receiver are on the same side, and (ii) motion is created on the same side at the transmitter while the receiver is behind. additionally, the system was configured so that the horn antenna directs the produced signal toward the receiving side. (a) different sides fig. 2 transmitter and receiver the building used in the experiment contained many small rooms and halls with partitions. the scanning device with limited power failed to transmit across concrete walls. therefore, the rf device with higher power was used in one of the rooms with concrete walls that were approximately 3 inches thick. in this first setup, the receiver was placed on one side of a advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 77 concrete wall and the transmitter on the other side, as shown in fig. 2(a). the sensor gadget is fixed on the other side of the wall and connected to the pc. from the transmitter side, the motion is generated in front of the horn antenna, and data received from the receiving side is observed. in the second setup, just like in the first method, signals were collected and processed with motion occurring entirely behind the wall, as shown in fig. 2(b). (b) same sides (bottom) fig. 2 transmitter and receiver (continued) observations show a cut in the received signal strength indicating the presence of an individual. this process was applied for different transmitted powers and distances, and the results are shown in table 1. it was concluded that the distance is proportional to the requirement of power for stronger signal reception and movement detection. a sample screenshot of the received signal against different distance settings versus transmitted power is shown in fig. 3. for the second setup, the distance between the transmitter and the object was 135 cm. the results were comparable to the first setup. the cuts were observed if someone moved directly in front of the transmitter or receiver. however, it was noted that the increase in the power helped to detect the presence of an individual behind barriers. the screenshots are shown in fig. 4. (a) no movement (b) power −10 db and distance 1 meter (c) power −5 db and distance 1 meter (d) power 0 db and distance 1 meter fig. 3 distance 1 meter with transmitted different powers 78 advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 table 1 experiment results of the first setup distance between transmitter and receiver transmitted power received power 1 meter −10 db −18 db −5 db −13 db 0 db −6 db 2 meters −10 db −21 db −5 db −17 db 0 db −8 db 3 meters −10 db −22 db −5 db −19 db 0 db −9 db (a) power −10 db and horizontal distance 1 meter (b) power −5 db and horizontal distance 1 meter (c) power 0 db and horizontal distance 1 meter fig. 4 distance 1 meter and different powers, and vertical distance 135 cm detection through rf scanning: for wall scanning, the device is placed directly on the surface, and any movement behind the surface (typically less than 10.16 cm in thickness) is displayed on the receiving side. it works over an ultrawideband range of frequencies. this device uses an antenna array to illuminate the targeted area and sense the returning signals. once the type of wall is chosen. the surfaces are scanned in a circular motion for approximately 30 seconds to identify the material type. this process, known as calibration, helps the system learn the characteristics of the surrounding environment. calibration entails adjusting various parameters to account for factors affecting measurement accuracy, such as object size and shape, distance from the sensing device, and the presence of materials that absorb or reflect rf waves. once the reflected signal is received, the graphical representation of the object is observed clearly by modifying the percentage in the intensity bar. to enable remote monitoring, the signals shown through the sensor were transferred from the cell phone to another device via smart view/mirroring [23]. the detections of objects from above the ground and behind the walls work on the principles laid out respectively [2425]. a portion of the rf signal can penetrate a non-metallic wall, reflect off objects, and return information about the entity behind the wall. by capturing these reflections, the objects hidden from direct view can be visualized. however, the receiver’s adc may be overloaded by strong reflections from the wall, preventing it from detecting subtle fluctuations caused by objects behind it. this phenomenon is known as the “flash effect”. advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 79 in mimo systems, multiple antennas encode transmissions to nullify signals at specific receivers, effectively reducing interference to unintended ones. similarly, reflections can be minimized through nulling [25]. however, if the flash effect is 30 to 40 db stronger than the reflections, canceling the reflections alone is insufficient, as signals from moving objects behind the wall remain too weak. these weak signals are masked by hardware noise from the receiver. to address this, the transmitted signal strength is increased without saturating the adc. this boosts the overall power passing through the surface, improving the snr of the reflections from the hidden targets. to evaluate the estimated accuracy, several trials are necessitated to record the results of each different technology. mathematically, this evaluation metric is stated as: , , 1 , 1 1 = =  −  = −      nn m n t n n t n y y accuracy n t (1) where n represents the number of trials, ym,n and yt,n denote the outputs of the prototype (m) and the ground truth (t) in the nth experiment, respectively. from this equation, it is evident that for 100% accuracy, the numerator term (���,� − ��,��) must be 0. all the devices mentioned above can be attached to the drone to expand its applications. the drone used is the “bwine f7gb2 aircraft,” featuring a controller, communication system, downlink system, propulsion system, and a 2,600 mah battery. one limitation of this drone system is that adding extra electronics significantly reduces flight duration; a single battery charge provides approximately 10 minutes of flight time. to address this power limitation, multiple unmanned aerial vehicles (uavs) could be deployed. apropos of practical implementation, a wall-scanning device, and receiver cell phone were attached to the uav to detect objects behind walls of any height or under roofs with height restrictions. to uphold this additional weight, the drone battery should be carefully chosen. 3.2. indoor wall and surface types the experimentation explores testing on different surfaces and wall types to detect moving objects across their thickness. a commercially available portable scanning device with limited power serves as a prototype in a typical office environment with manifold wall types and thicknesses. the surfaces include granite, wood, metal, glass, and concrete. granite walls are often used in high-end construction and range from a few inches to a foot or more based on structural requirements. on the other hand, metal walls can be constructed from different materials, and their thickness can differ significantly based on industrial or commercial applications. concrete walls are pervasively adopted in both residential and commercial construction. their thickness can range from a few inches in interior walls to several feet in foundation or structural components. plastic walls are not typical structural elements but may be used for partitioning, with thickness differing from thin plastic sheets to thicker, more robust materials used in industrial applications. table 2 one-way signal attenuation for wall thickness and effective distance [26] material 2.4 ghz thickness attenuation effective distance applications open space (reference) 0 cm 0 db 100% wood 4 cm 3 db 20% partitioning glass 0.8 cm 4 db 10% aesthetic/natural view/partitioning concrete 10.2 cm 15 db 14% residential/commercial concrete 20.3 cm 29 db 16% residential/commercial metal 8 cm 30 db 25% industrial reinforced concrete 20.3 cm 31 db 18% residential/commercial similarly, wooden walls differ depending on the type used and the construction purpose. residential wooden walls’ thickness may range from 3.5 inches to a thicker dimension for load-bearing or structural walls. glass walls, on the other hand, are used for aesthetic and natural light but vary in thickness. thicker panels are used for exterior glass walls, known for their 80 advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 insulation and strong strength, whereas thinner glass is used for interior partitions. however, notably, signal attenuation varies depending on the surface material. concerning reference, table 2 provides the signal attenuation values and effective distance at 2.4 ghz for different materials. the effective distance means how much signal is reduced after passing through the obstacle compared to air. the walls, surfaces, typical thickness, and applications are shown in fig. 5. (a) granite (b) wood (c) metal (d) concrete (e) glass fig. 5 walls and surfaces used in the experimental setup the results were dependent on material thickness and the type used in the testing. according to the sensing device’s specifications, the surface or wall thickness must be less than 10.16 cm for successful detection. otherwise, the device is unable to detect the object or its movement due to the limited power of the sensing device. regarding surfaces at lower heights, the devices were mounted on a selfie stick, while for higher elevations, they were attached to the legs of a drone. a human hand, either static or in motion, was used for these trials. in the case of motion, the static hand was first detected, and subsequently, it was slowly moved in one direction, with the sensing device following to track it. on thin surfaces, such as kitchen granite, glass doors, windows, glass surfaces, and wooden walls or doors with a thickness of less than 10.16 cm, the results were 100% accurate, with the object’s shape or movement visible in 3d on the screen. however, concerning thick doors or surfaces, the results were unsatisfactory as the thickness exceeded the device’s capability. the device also failed to detect objects on metal and concrete surfaces. fig. 5 illustrates the surfaces tested. initially, the work started with a 4 cm thick hardwood substance. the findings for the wooden substance were observable, and the presence of a moving object beneath the cupboard was observed. in this experiment, an 80% intensity bar was set initially and gradually reduced until a clearly defined result was noticed. subsequently, concrete surfaces and building walls were tested. due to their larger thickness, it was not possible to accomplish any outcome for the building’s outside walls. instead, only the inside walls’ spaces between the walls can detect the presence of moving objects. when the object was stationary, like the wooden object, the identification was not attainable. instead of sticking to the conventional wall type, other materials such as glass, and granite were experimented with. moving items were easily discernible on the glass surfaces, with slightly less clear results from the granite. table 3 experimental results of wall scanning device material transmitted power = −10 db, thickness ‘h’, negligible ‘-’ h = 6 cm h = 8 cm h = 12 cm h = 14 cm received power accuracy received power accuracy received power accuracy received power accuracy glass −10 db 100% −10 db 100% −12 db 80% −14 db 60% wooden door −10 db 100% −10 db 100% −14 db 60% −15.6 db 44% metal door 0% 0% 0% 0% interior wall (hollow) −10 db 100% −11 db 90% −13 db 70% −15 db 50% concrete 0% 0% 0% 0% the experimental results are validated using eq. (1) by repeating the same experiment at different times. the experimentations used glass or wooden surfaces with a thickness of less than 10.16 cm. results are matching with the predictions for glass and wood when eq. (1) is used for validation. rf signal absorption in the industrial scientific medical (ism) band was lower with glass (3 db) and thin wooden surfaces (6 db). in contrast, thicker wooden surfaces increased advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 81 attenuation to 9 db, reducing the detection rate. regarding metallic doors and concrete walls up to eighteen inches thick, the attenuation increased to 12.4 db and 18 db, respectively. in reinforced concrete, signal loss increased to 40 db, leading to a poor detection rate. using n = 10 in eq. (1), the results in table 3 show that commercially available scanning devices can detect objects through various building walls and surfaces of limited thickness. it should be noted that these results depend upon the power transmitted by the scanning device used in the experiment. for better results, rf devices with higher power output, discussed in section 3.1, may be used. 4. discussion sustainable development goal 11 (sdg-11) aims to make cities safe and resilient, and see-through technology is crucial in achieving these goals by monitoring urban areas for safety. attaining precise signal detection is crucial in case of object movement across indoor walls and surfaces. apropos of rescue missions or infrastructure monitoring, the primary goal is to accurately identify the location, shape, and movement of objects behind walls. this study extended the initial research [23] on sensing through indoor walls and surfaces. the detailed experiments examined the performance of different see-through technologies based on the material characteristics of the surface, such as thickness and composition. errors in detection could result in false alarms, overlooked threats, or ineffective operations, with potentially severe consequences. while the performance and energy efficiency of the materials are important, they are often secondary considerations due to various factors, including: (1) in mission-critical systems, inaccuracies could incur life-threatening errors, whereas energy efficiency and material performance can be more flexible. (2) enhancing accuracy often demands higher power consumption and more advanced materials, which may be less energyefficient. therefore, the initial focus is on achieving high accuracy, with energy efficiency being optimized later as the technology matures. (3) material performance and energy efficiency are typically application-specific. for instance, in consumer applications like detecting studs behind walls, energy efficiency may be prioritized more than in high-stakes applications such as law enforcement. the rapid growth of connected devices and iot is driving up energy consumption, posing an energy crisis without changes in communication technologies [27]. to address technological challenges, the electronics innovation sector must be prioritized. 5. conclusions the aims set in this research have largely been corresponded through multifarious experiments. through experimental investigations, it was found that affordable and portable rf and wi-fi-based devices available in the market can sense through many non-metallic surfaces by measuring reflections and distortions caused by moving objects behind walls. rf and wi-fi signals can easily travel through drywall (plasterboard) and wood. these materials, typically found in residential environments and office partitions, do not significantly block or interfere with these signals. glass enables rf and wi-fi signals to pass through it smoothly. however, reflections can sometimes interfere with signal clarity. concrete materials have constrained penetration as signals are significantly attenuated by thick concrete walls, reducing their effectiveness. metal walls have a very poor penetration as they block or reflect rf signals almost entirely. the experimental findings were validated by repeating the experiments at different times and days and averaging the accuracy found in the experimental results. wi-fi-based systems may use existing infrastructure, further reducing costs. these devices can be small, handheld, or integrated into smartphones, facilitating the ideal for easy transport and deployment. the findings suggest that selecting an affordable sensing device is applicable for each different wall or surface. the detection range could be extended by transmitting 82 advances in technology innovation, vol. 10, no. 1, 2025, pp. 72-83 higher power; however, existing affordable technologies possess low power. the choice of technology in the public domain is critical and depends on various market factors. several factors influence market dynamics, including drivers, restraints, and opportunities. despite the aforementioned key points, market growth faces other challenges, including state regulatory issues, user privacy concerns, and high initial investment costs. conflicts of interest the authors declare no conflict of interest. references [1] w. b. thompson and t. c. pong, “detecting moving objects,” international journal of computer vision, vol. 4, no. 1, pp. 39-57, 1990. 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[27] o. bonnaud, “innovative strategy to meet the challenges of the future digital society,” advances in technology innovation, vol. 6, no. 2, pp. 106-116, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 english language proofreader: yu-rui huang enhanced electrocardiogram arrhythmia diagnosis with deep learning and selective attention mechanism hasanain shakir mansour1,2, morteza valizadeh2, alaa hussein abdulaal3*, mehdi chehl amirani2 1department of computer technical engineering, college of information technology, imam ja'afar al-sadiq university, al-muthanna, iraq 2department of electrical engineering, faculty of electrical and computer engineering, urmia university, urmia, iran 3department of electrical engineering, college of engineering, al-iraqia university, baghdad, iraq received 21 july 2024; received in revised form 05 december 2024; accepted 06 december 2024 doi: https://doi.org/10.46604/aiti.2024.14034 abstract the study aims to improve the diagnosis of arrhythmia in cardiovascular disease management. a novel approach using a deep convolutional network combined with a selective attention mechanism is proposed for electrocardiogram signal classification. the deep convolutional network extracts relevant features directly from raw electrocardiogram signals, while the selective attention mechanism focuses on the most critical regions of the signals and suppresses irrelevant or noisy components. this method achieves an accuracy of 99.70% in multi-class arrhythmia classification and 99.85% in binary classification, significantly outperforming traditional classification algorithms. furthermore, the selective attention mechanism improves the localization of critical electrocardiogram segments, offering valuable insights for clinicians and aiding in the diagnosis process. this enhanced approach increases diagnostic accuracy and provides a clearer understanding of the electrocardiogram signals, which is crucial for effective patient management in cardiovascular diseases. keywords: arrhythmia diagnosis, electrocardiogram (ecg), deep convolutional network (dcnn), selective attention mechanism (sam) 1. introduction cardiovascular diseases constitute the leading cause of death globally [1], and the world health organization (who) has listed them as the cause of the maximum number of deaths worldwide, accounting for about 31% of all deaths every year [2]. cardiac arrhythmia is a condition in which the heartbeat becomes irregular due to some fault in the electrical system of the heart. an electrocardiogram (ecg) is an established diagnostic tool for cardiac arrhythmias since it captures the heart's physiological activity over time [3]. global annual ecg recordings exceed 300 million and are projected to increase. the popularity of ecg stems from its simplicity, affordability, non-invasiveness, and ability to provide valuable information about the heart's electrical activity, heart rate, and the presence of conditions like arrhythmias or heart attacks [4]. ecg tests are painless, easy, quick to perform, and can be repeated to monitor the progress of certain conditions. fig. 1 shows the ecg heart cycle [5]. the main part of an ecg contains a p wave, a qrs complex, and a t wave. the p wave indicates atrial depolarization. the qrs complex consists of a q wave, r wave, and s wave, representing ventricular depolarization. the t wave comes after the qrs complex and indicates ventricular repolarization. structural, electrical, and circulatory are the three types of cardiovascular systems [6]. * corresponding author. e-mail address: engineeralaahussein@gmail.com advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 103 accurate diagnosis of the type of arrhythmia is necessary to select appropriate treatment. however, considerable morphological differences exist in the correct manual identification of ecg components. moreover, visual identification, the current standard, might bring subjective biases between observers. as illustrated in fig. 2, ecg signal classes exhibit distinct heartbeat characteristics and patterns, such as fusion, f; normal, n; supra-ventricular ectopic, s; and ventricular ectopic, v, beats [7]. in this regard, researchers have explored alternative methods—deep learning being one—to remove visual and manual interpretations. fig. 1 ecg heart cycles [5] fig. 2 heartbeat ecg patterns [7] traditionally, clinicians diagnose arrhythmias through manual analysis of ecg signals, which can be time-consuming and susceptible to human error. these methods often lack the precision and efficiency needed for large-scale screenings. deep learning (dl) offers a promising alternative to cardiac arrhythmia classification, as it can automatically learn significant features and class distinction [8]. dl has advantages in handling massive and noisy datasets, automatically reducing features, and finding applications in different domains. the automatic detection of cardiac arrhythmia has been the topic of many researchers over the past decades. most of them use the mit-bih arrhythmia dataset [9] and the physikalisch technische bundesanstalt(ptb) diagnostic ecg database [10], which are publicly available and represent the most frequently used database in arrhythmia research. to achieve this, deep genetic hybrid classifiers were used by [11-12] in diagnosing the arrhythmias from the long-term ecg data in the mit-bih database with an accuracy of 94.6%. the proposed approach addresses the deficiencies by including a deep convolutional neural network along with a selective attention mechanism. this allows the model to capture more relevant features from the ecg signals, thereby improving classification accuracy and speed. it leverages state-of-the-art feature extraction with pre-trained models like resnet-50 and visual geometry group (vgg19), reducing the need for manual intervention and improving model generalization. this method significantly outperforms traditional algorithms, offering a more reliable and scalable solution for arrhythmia diagnosis. 2. literature review since ecg signals are nonlinear, variations in real-life signals can be detected using higher-order statistical methods like the nonlinear dynamic method [13]. principal component analysis reduces the dimensionality of the derived bispectrum advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 104 features. from these reduced features, a least squares-support vector machine and a four-layer feed-forward neural network are used for automatic pattern recognition. this approach achieved the highest average accuracy among the researchers at 93.48%. while the accuracy of deep convolutional network (dcnn) training decreases with increasing network depth, [14] has reported an accuracy of 97.5% using only a simple convolutional neural network (cnn) model with five layers. this technology worked on the principle of wavelet transform based on quadratic waves for identifying individual ecg waveforms and generating a fiduciary marker array. data classification was performed using a probabilistic neural network with an accuracy rate of 92.7% [15]. dewangan and shukla [16] classified heartbeats into five different types by employing artificial neural networks and discrete wavelet transformation. the authors have reported that using wavelet coefficients and morphological features improved the performance of ann, increasing the accuracy to 87%. the accuracy further increased with the increase in the number of neurons in the hidden layer. jha and kolekar [17] contributed an efficient approach to classify seven types of ecg beats based on the 12 approximation coefficients derived through the tunable q-wavelet transform of ecg beats from a dissimilar record of the mit-bih database. extracted features were used as the input to support the vector machine classifier, which yielded an average classification accuracy of 99.27% for an additional class of eight ecgs. in [18], researchers proposed an efficient classification methodology in which five types of heartbeats were classified using a one-dimensional cnn with 12 layers. before classification, the noise was removed from the ecg beats using the threshold denoising technique, which was accurate at 97.41%. in [19], four types of heartbeats from various datasets were categorized through five machine-learning algorithms, including random forest. wavelet decomposition and frequency content-based sub-band coefficients were used to reduce the dataset's dimensionality, improving the performance of the classification technique. the results showed that the random forest algorithm achieved a classification accuracy of up to 97%. murat et al. [20] provided a survey for background information, and further research into deep learning models became one of the standard approaches by which ecg data had to be classified. they worked on ecg data from 5 classes with 100,022 beats from the mit-bih rhythmic database and focused on testing the most commonly used dl strategies available in the literature. acharya et al. [21] identified general and predictive classes using 13 deep layers of a fully cnn. like the artificial neural network (ann), the final cnn model performance judgment depends on network structure weights and previous layer preferences. the pooling process reduces the output neurons' dimension co-evolutionary layer to reduce calculation amplitude and avoid overfitting. the suggested method's accuracy, specificity, and sensitivity were 88.67%, 90.00%, and 95.00%, respectively. dcnn can use attention mechanisms to diagnose cardiac arrhythmias by focusing only on salient parts of the ecg signals. this provides a new way to isolate and detect relevant features in accurately classifying arrhythmias[22]. the attention mechanism allows for the identification of the ecg signals that drive the classification decision. this implies the localization of the relevant segments of the signals, promoting an understanding of the rationale behind diagnosis and giving valuable insights that enable informed decisions about patient management. moreover, most of the problems associated with interobserver variability and subjective biases of visual identification will be decreased due to the attention mechanism. most arrhythmia diagnosis methods using ecg signals have low accuracy or suffer from similar-looking patterns of arrhythmias. most conventional methods involve huge feature engineering, which is normally time-consuming and inefficient in most cases. additionally, many models lack interpretability, making them difficult for clinicians to adopt practically. the present study exploits the deep learning potential based on cnns to automatically extract relevant features from ecg signals in classifying various arrhythmias. another milestone in this area is the integration of a selective attention mechanism within dcnn to diagnose arrhythmias. this provides deep learning with its power while maintaining the advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 105 interpretability and transparency of the model; further bridging the gap between automated analysis and human understanding. thus, deep learning embedded with selective attention holds high promise to raise the accuracy, efficiency, and reliability in the diagnosis of arrhythmias for improved patient outcomes in the management of cardiovascular diseases. 3. materials and methods an arrhythmia is an irregular heartbeat resulting from abnormal electrical activity in the heart, which can lead to ineffective blood pumping. it is defined as a deviation from normal heart rate. tachycardia, bradycardia, and irregular heartbeat are terms used to describe several arrhythmia problems. bradycardia is characterized by a slow resting heart rate, fewer than 60 beats per minute, whereas tachycardia is characterized by a high resting heart rate, often exceeding 100 beats per minute. the heart's abnormal electrical activity can be fatal. people with coronary artery disease, diabetes, and high blood pressure are more likely to experience arrhythmias. 3.1. dataset overview this paper uses the physionet mit-bih arrhythmia dataset [11] and the ptb diagnostic ecg database [12] as data sources of labeled ecg records. this demonstrates how the knowledge from previous databases can be successfully transferred to train inference models. the ecg lead ii resampled at 125hz is used as an input. the mit-bih database contains the ecg recordings of 47 different subjects. the sampling rate is 360hz. each beat is annotated with at least two independent cardiologists' estimates. in this paper, annotations from the dataset are used to separate the five beat types under the ec57 standard of the association for the advancement of medical instrumentation. the ptb diagnostics dataset consists of ecg recordings of 290 subjects: 148 with mi diagnosis, 52 healthy controls, and the rest diagnosed with 7 diseases. each record includes ecg signals from the 12 leads sampled at 1000 hz. this paper will only work on ecg lead ii and two categories: mi and health controls. 3.2. preprocessing since ecg beats are used as inputs for this method, kachuee et al. [23] introduced an efficient approach to preprocessing the ecg signal and extracting its beats. figs. 3 and 4 illustrate the steps involved in extracting beats from the ecg signal. the continuous ecg signal is divided into 10-second windows, with a specific window selected for further analysis. to enhance signal quality, a combination of noise reduction techniques is employed, including a high-pass filter with a cutoff frequency of 0.5 hz for baseline wander removal, a notch filter at 50/60 hz to eliminate power line interference, and a low-pass filter with a cutoff frequency of 40 hz to reduce high-frequency noise. additionally, min-max normalization rescales the ecg signal amplitudes to ensure they fall within the range of zero to one. normalize amplitude values find local maximums apply threshold (0.9) find r-peak candidates yes no continuous ecg signal split into 10s windows select window start calculate nominal heartbeat period select signal segment (1.2 * t) pad segment (fixed length) end fig. 3 flow chart for bit extraction advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 106 fig. 4 an extracted beat from 10s ecg window [23] zero-crossings of the first derivative are utilized to identify all local maximum points in the signal. a threshold of 0.9 is then applied to the normalized values of these local maximums to identify potential r-peak candidates corresponding to the peaks of heartbeats. the median value of the r-r intervals, representing the time between consecutive r-peaks, is calculated to determine the nominal heartbeat period for that specific window (t). for each r-peak candidate, a signal segment with a length equal to 1.2 times the nominal heartbeat period (1.2t) is selected. to ensure a fixed length for further analysis, each selected segment is padded with zeros, if necessary, to meet a predefined length requirement. the beat extraction methodology is effective in capturing r-r intervals from ecg signals that exhibit diverse morphological characteristics. applying this technique, all extracted beats are standardized to an equal length, enhancing the reliability of subsequent analyses. this uniformity is crucial for accurate interpretation, the assessment of heart rate variability, and the evaluation of overall cardiac health. 3.3. pre-traind cnn resnet-50 and vgg19 are popular deep-learning architectures used in computer vision tasks, including image classification, object detection, and feature extraction [24]. while they have different architectural designs, both models have achieved state-of-the-art performance on benchmark datasets. 3.3.1. resnet-50 resnet-50 stands for residual network with 50 layers. it is a deep residual network proposed by microsoft research in 2015. one of the most critical innovations introduced by resnet-50 is residual or skip connections. these connections enable the network to learn residual mappings, which are differences between a layer's input and output, instead of learning it directly. residual connections overcome the problem of vanishing gradients during backpropagation and allow for the training of deep networks. in the resnet-50 architecture, several building blocks of residual blocks are used. each residual block comprises multiple convolutional layers integrated with batch normalization, relu activation, and dropout. resnet-50 implements skip connections to facilitate gradient flow. such is the architecture that enables the network to learn more efficiently and effectively. the architecture combines global average pooling and a fully connected layer for classification. 3.3.2. vgg19 vgg19 is a dcnn developed by visual geometry group, vgg, at the university of oxford. introduced in 2014, it became widely adopted due to its simplicity and notable performance. vgg19 is an extension of vgg16, with 19 layers composing the architecture [24]. another critical element of vgg19 is using 3x3 convolution filters throughout the network. this size of filter allows deep networks without excessively increasing the parameter count. the architecture consists of a stack of convolutional layers and a max-pooling layer for down-sampling. the last few layers in vgg19 are fully connected to facilitate the classification task. the architecture of vgg19 is straightforward and uniform; this simplicity makes the model easy to understand and implement. it provides a balanced model complexity and performance and is thus broadly employed advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 107 as a baseline model for several tasks in computer vision [24]. due to its deeper architecture, vgg19 contains significantly more parameters than other models. resnet-50 and vgg19 have been among computer vision's most influential deep models. resnet-50 introduced residual connections that enable the training of deep networks, while vgg19 is straightforward yet effective; thus, it is perfectly suitable for use as a baseline model. these models have been successfully applied to many diverse areas with pre-trained representations and powerful features that enable an accurate classification. 4. proposed model in this first stage, the goal is to train resnet-50 and vgg19 using a public ecg bit dataset containing multi-class classification labels for various cardiac beats. the beat dataset contains labeled ecg signals, and every signal corresponds to a specific cardiac condition or beat type. continuous ecg signals are segmented into small time windows before training. preprocessing of the ecg signals is the first step. preprocessing techniques include amplitude normalization to a range between zero and one, noise filtering, and resampling the signals to the desired frequency [23]. later, the previously pretrained models of resnet-50 and vgg19, which were trained on large-scale datasets of images, are loaded. these models are used for initialization for training with the ecg bit dataset. fine-tuning of the pre-trained models on the ecg bit dataset is performed using backpropagation and gradient descent methods. in the process of fine-tuning, the weights are optimized for the multi-class classification task. during training, the models take ecg signal windows as input, and the predicted beat category is compared with the ground truth labels. the iterative optimization process enables the models to learn the patterns and features indicative of each beat category. evaluation metrics such as accuracy, precision, recall, and the f1 score, can be used to evaluate the performance of the models during training [25-26]. these parameters indicate the classification performance of the models' different types of cardiac beats. training resnet-50 and vgg19 on the ecg bit dataset is for obtaining a model to accurately classify multiple categories of ecg signals: normal beats, supraventricular premature beats, premature ventricular contractions, fusion beats, unclassifiable beats, and myocardial infarction. subsequently, an ecg signal is divided into equal-sized window fragments to capture meaningful cardiac cycles. each fragment is then converted into a spectrogram using a short-time fourier transform (stft) (1). this involves computing the fourier transform on short and overlapping time windows to produce a time-frequency representation. this creates a visual image of how the frequency content of the ecg signal changes over time. the spectrograms resulting from this are well-suited for use with cnns, as these networks can exploit this rich frequency and temporal information for the classification task. this effectively highlights patterns that are less discernible in the raw waveform and thus facilitates better analysis and interpretation of the ecg data. 2 ( ( ), ) ) ( j f x t f x w t e d      − − =  −  (1) where x (τ) is the ecg signal in the time domain, and 𝑤 (𝜏 − 𝑡) is a window function, typically a smooth, finite-duration function, centered at time 𝑡. 4.1. selective attention mechanism (sam) sam allows attention to be focused on specific regions or features of the input. a sam in the context of ecg signal analysis could highlight the salient patterns or segments responsible for the accurate classification of the different arrhythmia types. the selective attention mechanism involves segmenting the ecg signals into smaller fragments at the front end (2) and subsequently assigning attention scores to them (3). the attention scores are computed by assigning weights to different segments of the ecg signal. these weights are determined based on the relevance of each segment to the classification task, advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 108 allowing the model to prioritize key features that contribute to identifying specific arrhythmias. these attention scores indicate the diagnostic significance of the segment toward arrhythmia diagnosis. the segments with higher attention scores are considered more informative and are thus given greater weights during classification (4), (5). the one with the highest attention score is selected for further analysis. this can be realized in ecg signal classification by applying a hand-crafted layer in a model's architecture: "selectiveattentionlayer (6)." this mechanism ensures the model's focus on essential signal components, enhancing its diagnostic performance. the ecg segment x is divided into n segments  1 2 3 4, , , , ,= nx x x x x x (2) the attention score 𝑎𝑖for segment 𝑋𝑖 can be represented as 1 2 3{ , , ,....., }i na a a a a= (3) the highest attention score 𝑋𝑀𝑎𝑥 is arg { } max i i x max a= (4) 1 n weighted i i i x a x = = (5) the selectiveattentionlayer function 𝑆𝐴𝑀(𝑋) ,taking x as input, is ( ) weighted sam x x= (6) 4.2. deep convolutional neural network with a selective attention mechanism s the integration of sam with the dcnn presents a significant advancement in this study. sam enhances the dcnn by dynamically weighting the features extracted from ecg signals; thus, the model can concentrate its attention on the most relevant components of the signal, which improves both feature extraction and accuracy in classification. in more detail, sam accomplishes this by attaching the attention score to different features, assigning higher priority to the features that contribute the most to proper classification. this mechanism is seamlessly embedded within the dcnn framework, enhancing its ability to distinguish between complex arrhythmic patterns. fig. 5 vgg19-sam architecture advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 109 the second stage centers around the integration of the pre-trained resnet-50 and vgg19 models with the selective attention mechanism to classify ecg data. this will leverage the rich, learned representations from these pre-trained models while enhancing classification performance by focusing on salient temporal patterns. these pre-trained resnet-50 and vgg19 models have learned discriminative features from the variably transformed ecg signals. an ecg signal is segmented into window fragments of equal size; and transformed into a spectrogram-like representation. these pre-trained models extract features from every segment to capture high-level representations in complete signal classification. these features are input into sam, to select the most relevant segments based on their attention scores. it focuses on salient parts of the ecg signal at different steps, emphasizing patterns that contribute more to arrhythmia classification. fig. 5 illustrates the integration of vgg19 with sam. the combination of the pre-trained models with sam improves the accuracy and robustness of arrhythmia classification by considering only the most informative segments while harnessing the benefit of learned representations from the pre-trained models. sam improves classification performance by highlighting salient patterns in the ecg signal, as illustrated in fig. 6. it can effectively utilize informative segments to identify and classify arrhythmia correctly. the model may finally identify the relevant segments strongly and give insights into the existence and type of arrhythmia, thereby helping in making more accurate diagnostic decisions. further work in this area aims to optimize the integration of a pre-trained model with sam by investigating variations or adaptations specific to ecg signal analysis. these developments have been crucial in enhancing precision and speed in arrhythmia diagnosis and thereby advancing cardiovascular care. fig. 6 flow chart of the proposed model in clinical settings, the computational costs and complexity of models like vgg19 and resnet-50 must be considered. vgg19, with its 143 million parameters, requires substantial computational resources, whereas resnet-50, with 25 million parameters, offers a more efficient option for real-time diagnostics. by integrating a selective attention mechanism (sam), the interpretability of these models is significantly enhanced. sam focuses on the most relevant parts of the ecg signal, providing attention maps that align with clinical reasoning. this approach not only improves diagnostic accuracy but also increases transparency, fostering trust in automated systems. by aligning machine predictions with human reasoning, sam bridges the gap between model outputs and clinical insight, making automated diagnostics more reliable. advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 110 4.3. evaluation metrics the evaluation metrics used in this paper are as follows [26] : accuracy (7): the proportion of true results (both true positives and true negatives) among the total number of cases examined. 100 tp tn accuracy x tp tn fp fn + = + + + (7) where tp is true positives, fp is false positives, fn is false negatives, and tn is true negatives. recall (8): the proportion of true positives among the total number of actual positives. re 100 tp call x tp fn = + (8) precision (9): the proportion of true positives among the total number of positive predictions. pr 100 tp ecision x tp fp = + (9) specificity (10): the proportion of true negatives among the total number of actual negatives. 100 tn specificity x tn fp = + (10) f1 score (11): the harmonic mean of precision and recall 1 100 1 ( ) 2 tp f score x tp fp fn − = + + (11) the receiver operating characteristic (roc) curve plots the true positive rate (recall) against the false positive rate to evaluate a binary classifier's performance across different threshold values. 5. results experimental results demonstrate the superiority of the proposed approach over traditional methods for arrhythmia diagnosis. utilizing a dcnn with a sam for arrhythmia diagnosis has shown promising results in ecg signal classification. the combination of these techniques enhances accuracy by capturing important temporal patterns in the signals. pretrained networks extract discriminative features, while the sam highlights relevant segments. the evaluation of the model typically involves 5-fold cross-validation, which enhances the reliability and generalization ability of the performance assessment. this technique trains and evaluates a model on five subsets of a dataset to increase its ability estimation. it improves interpretability, robustness against noise, and generalization performance, demonstrating superior accuracy compared to traditional techniques, and making it valuable for real-time arrhythmia detection. table 1 presents the performance metrics for multi-class arrhythmia ecg signal classification. the models achieved high accuracy values: vgg19 with an accuracy of 91.51%, resnet50 at 94.98%, vgg19+sam at 97.12%, and resnet50+sam with the highest accuracy of 99.70%. these accuracy scores prove that the models are capable of accurately classifying the various classes of arrhythmia. high precision was recorded for all models in this work, reflecting the reliability of the identification of arrhythmia cases among the predicted positives. vgg19 achieved a precision of 91.68%, and resnet50 achieved 95.04%.vgg19+sam achieved 97.14%, and resnet50+sam maintained a precision of 99.70%. these precision values indicate low false positive rates in model predictions. advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 111 the f1-score, which considers both precision and recall, demonstrated outstanding performance across all models: vgg19 at an f1-score of 91.45%, resnet50 at 94.97%, vgg19+sam at 97.11%, and resnet50+sam was the best at 99.70%. these scores indicate the ability models can balance precision and recall, yielding an accurate classification of arrhythmia cases. specificity, which measures a model's ability to correctly classify subjects without arrhythmia, showed remarkable results: the specificity was 97.88% for vgg19, 98.74% for resnet50, and 99.28% for vgg19+sam, with the highest being for resnet50+sam at a specificity of 99.93%. these specificity values highlight the ability of models to recognize subjects without arrhythmia. confidence intervals (cis) estimate a range likely containing the true population parameter, often calculated at a 95% confidence level. in this study, the classification train accuracy ranged from 99.44%99.99%. p-values quantify the strength of evidence against the null hypothesis. in this case, anova was used for statistical analysis, yielding a statistically significant p-value of 0.000006, well below the threshold of less than 0.05. table 1 evaluation metrics of multi-class classification vgg19 metrics n s v f q average cis p-value accuracy 99.08% 90.29% 91.98% 82.61% 93.59% 91.51% 84.1%-98.92% 0.0051 precision 88.50% 87.87% 93.68% 94.11% 94.22% 91.68% error 0.92% 9.71% 8.02% 17.39% 6.41% 8.49% f1-score 93.49% 89.06% 92.82% 87.99% 93.91% 91.45% specificity 96.78% 96.88% 98.45% 98.71% 98.56% 97.88% resnet 50 accuracy 99.23% 94.28% 94.75% 90.68% 95.96% 94.98% 94.19%-99.94% 0.0043 precision 93.59% 92.48% 95.63% 97.05% 96.43% 95.04% error 0.77% 5.72% 5.25% 9.32% 4.04% 5.02% f1-score 96.33% 93.37% 95.18% 93.76% 96.19% 94.97% specificity 98.30% 98.08% 98.92% 99.31% 99.11% 98.74% vgg19+sam accuracy 99.49% 97.05% 98.00% 93.17% 97.89 97.12% 94.16%-99.99% 0.000021 precision 96.62% 95.62% 98.02% 98.16% 97.27% 97.14% error 0.51% 2.95% 2.00% 6.83% 2.11% 2.88% f1-score 98.04% 96.33% 98.01% 95.60% 97.57% 97.11% specificity 99.13% 98.89% 99.51% 99.56% 99.31% 99.28% resnet 50+sam accuracy 99.94% 99.65% 99.79% 99.38% 99.75% 99.702% 99.44%-99.99% 0.000006 precision 99.76% 99.18% 99.97% 99.80% 99.81% 99.704% error 0.06% 0.35% 0.21% 0.62% 0.25% 0.298% f1-score 99.85% 99.42% 99.88% 99.59% 99.78% 99.704% specificity 99.94% 99.79% 99.99% 99.95% 99.95% 99.93% the resnet50+sam model exhibits outstanding performance in binary classification between myocardial and normal cases, as shown in table 2. it achieves high scores across metrics such as accuracy, precision, recall, f1-score, and specificity, ranging from 99.82% to 99.88%. these results indicate that this model efficiently classifies cases correctly, reliably detects true positives, and is extremely low in false positives. overall, resnet50+sam worked well in distinguishing myocardial cases from normal ones with exceptional accuracy and reliability. advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 112 table 2 evaluation metrics for binary classification cnn accuracy precision recall f1-score specificity vgg19 92.33% 92.08% 92.53% 92.31% 92.13% resnet50 93.81% 93.87% 93.76% 93.82% 93.87% vgg19+sam 97.62% 97.56% 97.68% 97.62% 97.56% resnet50+sam 99.85% 99.88% 99.82% 99.85% 99.88% fig. 7 displays deep dream images for features in the `selective_attention` layer in a neural network trained for multiclass arrhythmias from ecg signals. it consists of a 4x4 grid of subplots, each illustrating a deep dream image that maximizes the activation of a specific feature. these images highlight the patterns learn by the network's features for arrhythmia classification. each subplot is titled with its corresponding feature number. this visualization helps interpret the network's representations and its ability to distinguish arrhythmia types from ecg data. fig. 7 deep dream with sam feature extraction, as shown in fig. 8, visualizes the learned features of a neural network trained for multiclass classification of arrhythmias from ecg signals. each subplot in this figure represents feature activations for the test image, described as bar plots where the x-axis denotes feature indices and the y-axis shows activation values. higher bars indicate those features that are most important/relevant for classifying a particular image. fig. 8 features visualization of the last layer advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 113 the titles of the subplots display the real class of arrhythmia for every signal; therefore, enabling a visual comparison across classes. this visualization helps with relevant features for separating the arrhythmia classes and provides hints into model decision-making, which may guide improvements in diagnostic tools and treatment strategies. (a) vgg19 (b) resnet50 (c) vgg19+sam (d) resnet50+sam fig. 9 confusion matrices (multi-class) (a) vgg19 (b) resnet50 (c) vgg19+sam (d) resnet50+sam fig. 10 confusion matrices (binary) advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 114 confusion matrices corresponding to the proposed models for multiclass and binary classification are illustrated in fig. 9 and 10. the confusion matrices comprehensively summarize the normalized process and provide a clear indication of how well each model fits the data. the precision-recall and roc curves are plots used to evaluate the performance of models in classifying the arrhythmias. the precision-recall curve highlighting the trade-off between the two metrics, precision and recall, is represented in fig. 11. fig. 12 presents the roc curve, which plots the true positive rate against the false positive rate, assessing model performance across different classification thresholds. these curves provide insights into model effectiveness, thus making comparisons possible and full decisions based on such performance characteristics. (a) vgg19+sam (b) resnet-50+sam fig. 11 the precision-recall curve (a) vgg19+sam (b) resnet-50+sam fig. 12 the roc curve table 3 summarizes the most relevant research efforts reviewed. this collation helps provide input into the commonalities among the individual studies, which have tremendously advanced arrhythmia diagnosis using machine and deep learning techniques with ecg signal analysis. table 3 comparison of proposed methodology with some existing method ref. model class accuracy specificity sensitivity precision f1 score computational complexity [27] nn 5 98.90% 98.90% 98.90% low [28] mlp 4 94.76% 96.50% 90.11% low svm 4 98.20% 98.79% 96.45% medium [29] lstm 5 99.37% 99.14% 94.89% 96.73% 95.77% medium [30] cnn 3 99.2% 99.6% 99.2% high 2024 this work cnn+sam 5 99.702% 99.93% 99.704% 99.704% high 2 99.85% 99.88% 99.82% 99.88% 99.85% advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 115 implementing the deep convolutional network (dcnn) with a selective attention mechanism (sam) in clinical practice offers significant potential to enhance arrhythmia diagnosis. integrating the dcnn-sam model into existing systems could streamline workflows, reduce diagnostic errors, and allow clinicians to concentrate on complex cases. training programs will be necessary to help clinicians interpret the model's outputs appropriately. challenges may include ensuring system compatibility and addressing data security concerns. these problems are key concerns for widespread adoption. ultimately, by increasing the accuracy of diagnostics, this approach enhances diagnostic accuracy, provides clearer insights into ecg signals, and supports timely, individualized treatment plans, hence improving patients' outcomes in cardiovascular care. 6. conclusion this study proposed a model for arrhythmia diagnosis based on ecg signal classification using pre-trained resnet-50 and vgg19 models combined with a selective attention mechanism to enhance accuracy and robustness by focusing on prominent signal patterns. the approach involved preprocessing ecg signals, fine-tuning the models for binary and multiclass classification, and utilizing attention scores to emphasize critical signal segments during feature extraction and classification. the proposed approach significantly outperformed traditional methods, achieving high accuracy rates of 99.70% and 99.85% in multi-class and binary arrhythmia classification between myocardial and normal cases, respectively. with its highly accurate ecg signal classification, this approach can improve diagnostic efficiency and accuracy in managing cardiovascular disease. conflicts of interest the authors declare no conflict of interest. statement of ethical approval for this type of study, statement of human rights is not required. references [1] o. gaidai, y. cao, and s. loginov, “global cardiovascular diseases death rate prediction,” current problems in cardiology, vol. 48, no. 5, article no. 101622, 2023. 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[29] s. k. pandey and r. r. janghel, “automatic arrhythmia recognition from electrocardiogram signals using different feature methods with long short-term memory network model,” signal, image and video processing, vol. 14, pp. 1255-1263, 2020. advances in technology innovation, vol. 10, no. 2, 2025, pp. 102-117 117 [30] y. d. daydulo, b. l. thamineni, and a. a. dawud, “cardiac arrhythmia detection using deep learning approach and time frequency representation of ecg signals,” bmc medical informatics and decision making, vol. 23, article no. 232, 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 6-v10n4(2025)-aiti#14589(395-406).docx advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 comparative analysis of facial expression recognition using imagebased and landmark-based methods thanawat srikaewsiew, sarunya kanjanawattana* school of computer engineering, institute of engineering, suranaree university of technology, nakhon ratchasima, thailand received 05 december 2024; received in revised form 22 march 2025; accepted 31 march 2025 doi: https://doi.org/10.46604/aiti.2025.14589 abstract this study compares the effectiveness of image-based and landmark-based methods for facial expression recognition (fer) in classifying hurt and normal facial expressions, utilizing datasets from the delaware pain database and utkface. five machine learning models are assessed, including convolutional neural networks (cnn), support vector machines (svm), random forest classifier (rfc), logistic regression classifier (lrc), and gradient boosting classifier (gbc). the findings indicate that cnn achieves the highest accuracy at 95% when using landmark-based features, while svm and gbc also perform admirably with these features. conversely, lrc exhibits inconsistent results, especially when relying on image-based features. these findings offer valuable insights into the strengths and weaknesses of each approach, guiding the selection of effective fer techniques. keywords: face expression recognition, machine model comparison, image-based classification, landmark-based classification, expression dataset 1. introduction facial expression recognition (fer) is a field that combines computer vision, artificial intelligence, and psychology to interpret human emotions from facial cues. although humans naturally recognize expressions, training machines to do the same continues to be a challenge. with the rise of human-computer interaction, emotionally intelligent technologies are becoming increasingly important. fer [1] is an interdisciplinary field that bridges computer vision [2], artificial intelligence [3], and psychology [4], aiming to decode the intricate language of human emotions conveyed through facial expressions. facial expressions, a fundamental mode of nonverbal communication [5], help humans express emotions, intentions, and perceptions. while humans can naturally interpret these expressions, enabling machines to interpret them remains a significant challenge [6]. with the growing importance of human-computer interaction, the need for emotionally intelligent technologies capable of recognizing and responding to human emotions is increasingly apparent. image-based methods leverage the transformative power of deep learning [7], with convolutional neural networks (cnn) at the forefront. cnn models, trained on large-scale datasets like the delaware pain database [8] and utkface, excel at capturing global and local features from facial images, enabling robust emotion recognition. in contrast, landmark-based learning [9] focuses on extracting key facial points, such as the eyes, nose, and mouth, as representative features of facial expressions. these methods utilize geometric relationships between landmarks, offering robust models for emotion classification under varying poses and lighting conditions. * corresponding author. e-mail address: sarunya.k@sut.ac.th advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 396 while both image-based [10] and landmark-based methods [11] for fer have been extensively explored, there has been limited research directly comparing their effectiveness across diverse facial expression datasets. most studies tend to focus on one approach, without offering a clear comparison that highlights the relative advantages and drawbacks of each. this study addresses that gap by conducting a direct comparison, providing valuable insights into which method performs better under various conditions. the scarcity of such comparisons can be attributed to the complexity and variation in how facial expressions are captured and analyzed. image-based methods typically process raw data and rely on deep learning for feature extraction. in contrast, landmark-based methods extract key facial points, offering a more computationally efficient approach. by combining both methodologies in one study, this research aims to uncover their complementary strengths and limitations. despite progress in both areas, significant gaps remain in the literature. most research focuses exclusively on either image-based or landmark-based techniques, without comparing their effectiveness across multiple machine learning (ml) models. furthermore, few studies explore the practical application of these methods in real-world contexts, such as rehabilitation and diagnostic systems. these gaps highlight the need for a thorough evaluation of these approaches to better understand their strengths and limitations in practical applications. fer is a crucial task in affective computing and human-computer interaction, with applications in healthcare and emotional ai. while existing fer techniques leverage both image-based and landmark-based approaches, there remains a gap in systematically comparing these methods under standardized conditions using diverse ml models. this study aims to bridge this gap by conducting a comprehensive comparison of image-based and landmark-based fer techniques using five distinct ml models: cnn [12], logistic regression classifier (lrc) [13], support vector machines (svm) [14], random forest classifier (rfc) [15], and gradient boosting classifier (gbc) [16]. a key aspect of this research is the evaluation of image-based features versus landmark-based feature extraction, assessing their effectiveness in recognizing both normal and hurt emotions. the specific objectives of this study include: (1) comparing the performance of image-based and landmark-based fer approaches using standardized datasets. (2) assessing the strengths and weaknesses of cnn, lrc, svm, rfc, and gbc in processing different facial features. (3) measuring accuracy, precision, recall, and f1-score to determine the robustness and efficiency of each approach. the research contributes to the field in several ways. firstly, it provides a direct comparison of the performance of imagebased methods, which use a histogram of oriented gradients (hog) features, and landmark-based methods, which rely on facial landmarks for feature extraction. this comparison is based on a large and diverse dataset, including normal (neutral) and hurt emotions. secondly, the study assesses the performance of a variety of widely used ml algorithms, identifying the most effective models for each technique. this evaluation serves as a comprehensive guide for selecting the optimal method for different fer tasks. lastly, the study employs a range of performance metrics, including accuracy, precision, recall, and f1score, ensuring a thorough and balanced assessment of the model’s effectiveness in fer. while both approaches in this study offer distinct advantages, they also come with limitations that could affect the results. the image-based approach, particularly when using deep learning models like cnn, demands significant computational resources and may be sensitive to variations in image quality and lighting conditions. additionally, the feature extraction process, such as with hog, might fail to capture subtle facial expressions better represented by the geometry of facial landmarks. on the other hand, the accuracy of the landmark-based approach is heavily reliant on the quality and precision of the landmark detection process. factors like occlusions, misalignments, or low-resolution images can compromise the reliability of feature extraction. furthermore, landmark-based methods may not effectively capture the dynamic changes in facial expressions, as image-based methods can. to address these limitations, this study employs a diverse dataset and carefully selected models, ensuring that the comparison remains as balanced and robust as possible. advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 397 the research concept is shown in fig. 1, which visually represents the comparative framework for fer using imagebased and landmark-based approaches. it highlights key features such as “normal” and “hurt” as critical markers for evaluating the effectiveness of different methods. fig. 1 fer comparative framework 2. literature review fer has been an important area of research in computer vision, artificial intelligence, and human-computer interaction. this section reviews significant contributions in fer areas, aligning with the comparative works in table 1 and positioning the current study within this research landscape. early work, buck et al. [5], focused on manual coding of facial expressions, which provided foundational insights but lacked automation. the introduction of ml in fer began with vapnik [17], who developed svm, a key advancement in classification methods. however, early ml applications in fer were limited in scope and required further refinement. as artificial intelligence advanced, various approaches to fer were explored. lisetti and schiano [6], along with picard et al. [18], expanded the field by integrating affective computing, enabling machines to automatically interpret emotional states. bartlett et al. [19] later demonstrated the effectiveness of cnn for real-time fer, though their study was constrained by the availability of labeled data. other foundational works, such as those of lu and weng [10], along with hilbe [13], examined classification techniques and statistical modeling, but did not provide direct comparisons between traditional ml and deep learning models in fer. beyond general fer applications, researchers have explored its use in healthcare and specialized domains. lee and park [20] developed a fast region-based convolutional neural networks (r-cnn)-based fer model for diagnosing depressive disorders, demonstrating its potential in mental health assessments. however, their study relied only on image-based features, without considering how landmark-based features might enhance diagnostic accuracy. similarly, bekele et al. [21] introduced a virtual reality-based fer system, while assari and rahmati [22] focused on drowsiness detection in driver monitoring systems. while these studies highlighted important applications, they did not compare landmark-based and image-based methods, limiting their scope. many studies have concentrated on image-based fer techniques, refining classification models to improve accuracy. hamester et al. [23] proposed a two-channel cnn architecture, where one channel processed raw image data and the other extracted features using an autoencoder. while this approach improved classification accuracy, it lacked comparisons with traditional ml classifiers. alsubari et al. [24] incorporated wavelet transforms and local binary patterns (lbp) to enhance feature extraction and fusion, improving recognition rates. however, the study did not explicitly analyze the individual contribution of landmark-based features to fer performance. advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 398 alongside image-based approaches, scholars have also explored landmark-based fer. söylemez et al. [25] applied threedimensional facial landmark distances with svm, showing strong performance in recognizing expressions from 3d face models. however, their study did not compare landmark-based methods to traditional image-based techniques. munasinghe [26] used rfc for landmark-based fer, demonstrating efficient training times but relying on a relatively small dataset. more recently, sharma et al. [9] optimized landmark-based svm models, improving robustness but highlighting their sensitivity to errors in facial landmark detection. di luzio et al. [27] proposed deep neural networks (dnns) for processing hierarchical landmark features, though their study did not include a direct comparison between landmark-based and image-based models. hangaragi et al. [28] addressed this limitation by implementing a face mesh-based deep learning model, which achieved realtime efficiency but lacked comparative analysis with landmark-based classifiers. despite extensive research on both image-based and landmark-based fer, a notable gap remains: few studies provide direct performance comparisons between the two approaches. most prior work has focused on a single classifier, making it difficult to assess how different models generalize across datasets. additionally, while studies such as lee and park [20] demonstrated the potential of image-based fer for medical diagnosis, they did not explore landmark-based techniques, which could enhance interpretability and robustness in clinical settings. to address these gaps, this study conducts a detailed evaluation of both image-based and landmark-based fer methods across multiple classifiers, including cnn, svm, lrc, rfc, and gbc. furthermore, by using diverse datasets such as the delaware pain database and utkface, the study aims to improve generalizability across different demographics and application domains. this research extends the findings of lee and park [20], hangaragi et al. [28], and di luzio et al. [27], providing a comprehensive performance analysis of image-based and landmark-based fer techniques across multiple ml classifiers. table 1 chronological comparison of studies study methodology models used key findings limitation novelty in study buck et al. [5], 1972 image-based human-coded expressions early facial expression analysis no automated recognition introduces ml-based automated recognition vapnik [17], 1999 image-based svm foundational ml theory no fer application test svm on fer tasks lisetti and schiano [6], 2000 image-based ai-based interpretation human-computer interaction focus no ml comparison broadens scope to modern ml models picard et al. [18], 2001 image-based physiological state analysis early ml in affective computing no landmark feature use evaluates landmark features bartlett et al. [19], 2003 image-based cnn real-time fer limited dataset uses multiple datasets for comparison lu and weng [10], 2007 image-based image classification survey overview of classification methods no specific fer application direct application to fer hilbe [13], 2009 image-based lrc foundational statistical modeling no comparison with deep learning compares classical ml vs. dl models assari and rahmati [22], 2011 image-based fer-based drowsiness detection application-specific no direct comparison with landmark-based methods generalizes findings beyond drowsiness detection hamester et al. [23], 2015 image-based cnn 2-channel cnn for expression recognition no comparison with classical ml models broadens evaluation across ml models bekele et al. [21], 2017 image-based vr-saafe for fer application-specific no classical ml comparison expands analysis to classical ml models söylemez et al. [25], 2017 landmarkbased svm distance-based features for 3d fer no image-based comparison extends analysis to both 2d and image-based methods advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 399 table 1 chronological comparison of studies (continued) study methodology models used key findings limitation novelty in study alsubari et al. [24], 2017 image-based wavelet transform + lbp feature fusion improves recognition no landmark feature analysis incorporates landmark features for comparison munasinghe [26], 2018 landmarkbased rfc fast training limited dataset extends analysis with a larger dataset michael revina and sam emmanuel [1], 2021 image-based cnn high accuracy computationally expensive direct comparison with landmark-based methods lee and park [20], 2022 image-based fast r-cnn fer-based depressive disorder diagnosis no landmark-based evaluation applied fer to clinical diagnostics sharma et al. [9], 2023 landmarkbased svm improved robustness sensitive to detection errors evaluates multiple classifiers di luzio et al. [27], 2023 landmarkbased dnn hierarchical features no comparison with image-based methods direct performance comparison hangaragi et al. [28], 2023 image-based face mesh + dnn efficient for real-time applications lacks comparison with landmark-based models extends analysis with landmark-based methods this study image-based and landmarkbased cnn, svm, lrc, rfc, and gbc landmark-based features enhance performance computational tradeoffs first detailed evaluation of both methods across multiple classifiers 3. machine learning techniques this section provides an overview of the ml algorithms used in this study, the preprocessing steps, and training procedures for each approach. the comparative setup of these methods is summarized in table 2. each algorithm, including cnn, rfc, lrc, svm, and gbc, was selected for its ability to handle both image and landmark data, with distinct preprocessing techniques applied to optimize model performance. (1) convolutional neural networks (cnn) cnn are widely used in image processing due to their ability to learn spatial hierarchies from pixel data. in this study, cnns were applied in both image-based and landmark-based approaches. for the image-based cnn, raw images were resized to 128×128 pixels and normalized. the architecture consisted of three convolutional layers with rectified linear unit (relu) activation, followed by max-pooling operations to reduce spatial dimensions. the output was flattened and passed through fully connected layers, ending with a sigmoid-activated neuron for binary classification. the adam optimizer and binary crossentropy loss were used for training. for the landmark-based cnn, images were processed using mediapipe to extract 468 facial landmarks, which were reshaped into a 1d input format. the cnn architecture included a 1d convolutional layer, followed by max-pooling, flattening, and dense layers, similar to the image-based approach. feature standardization was applied using the standardscaler. (2) random forest classifier (rfc) rfc is an ensemble learning method that constructs multiple decision trees and aggregates their predictions to enhance accuracy and reduce overfitting. for the image-based approach, hog was used to extract texture features before classification. in the landmark-based approach, the extracted facial landmarks were used directly. standard scaling was applied to the extracted features before training. the model was trained using default rfc parameters, with the number of trees set to 100. (3) logistic regression classification (lrc) lrc is a simple yet effective classifier for binary classification problems. it models the probability of an instance belonging to a specific class using the logistic sigmoid function. for the image-based approach, hog was used for feature extraction, while for the landmark-based approach, facial landmarks were directly utilized. standardization was applied using the standardscaler. the model was trained with default parameters, including l2 regularization to prevent overfitting. advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 400 (4) support vector machine (svm) svm aim to find the optimal hyperplane that maximizes the margin between different classes. for the image-based approach, hog was used for feature extraction, while for the landmark-based approach, landmark coordinates were used. feature normalization was applied using the standardscaler. the model was trained using default parameters with a radial basis function (rbf) kernel to handle non-linear decision boundaries effectively. (5) gradient boosting classifier (gbc) gbc is an ensemble method that sequentially builds decision trees to correct the errors of previous iterations. for the image-based approach, hog was used for feature extraction, whereas the landmark-based approach used facial landmark coordinates. standardization was applied to the extracted features. the model was trained using default parameters, including a learning rate of 0.1 and 100 estimators. table 2 summary of machine learning methods and preprocessing steps model feature extraction preprocessing hyperparameters cnn (image-based) raw image data resizing, normalization custom architecture (conv2d layers, adam optimizer) cnn (landmark-based) 468 facial landmarks standardization custom architecture (conv1d layers, adam optimizer) rfc hog (image); landmarks (landmark-based) standardization default (100 trees) lrc hog (image); landmarks (landmark-based) standardization default (l2 regularization) svm hog (image); landmarks (landmark-based) standardization default (rbf kernel) gbc hog (image); landmarks (landmark-based) standardization default (learning rate = 0.1) 4. experiment fig. 2 experiment pipeline this section outlines the experimental framework used to evaluate the image-based and landmark-based fer methods. the experimental pipeline, depicted in fig. 2, demonstrates the step-by-step process, from preprocessing and feature extraction to classification and performance evaluation. this experiment aims to compare the effectiveness of five classification models— advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 401 cnn, lrc, svm, rfc, and gbc—on two distinct input types: image-based features using hog and landmark-based features extracted from facial landmarks. both approaches are assessed through a comprehensive set of performance metrics, including precision, recall, f1-score, and training time, to determine the most suitable method for reliable fer. 4.1. dataset this study utilized publicly available human image datasets, namely the delaware pain database and utkface, which contain images depicting various facial expressions. the delaware pain database consists of high-resolution images (1200×1200 pixels), while utkface provides lower-resolution images (200×200 pixels). to ensure consistency in model training, all images were resized to 128×128 pixels. for this study, only images displaying normal and hurt expressions were selected, resulting in 1,200 images. the dataset was divided into 800 images for training, 200 for validation, and 200 for testing. example images from each category are shown in fig. 3 and fig. 4. fig. 3 normal face example (the delaware pain database and utkface) fig. 4 hurt face example (the delaware pain database and utkface) 4.2. image-based method the image-based method involved five classification models, like cnn, lrc, svm, rfc, and gbc. since lrc, svm, rfc, and gbc do not inherently process raw image data, a feature extraction technique was required to convert images into numerical representations. for preprocessing, all images were converted to grayscale and normalized by scaling pixel values between 0 and 1. feature extraction was performed using the hog technique, which captures edge and texture information by analyzing the distribution of gradient orientations. in this study, hog parameters were set to a cell size of (8×8), a block size of (2×2 cells), and nine orientation bins. the extracted feature vectors were then standardized to improve model performance and ensure compatibility with classification algorithms. once features were extracted, the lrc, svm, rfc, and gbc models were implemented using scikit-learn. these models were trained with their default hyperparameters, as the focus of this study was not on fine-tuning but rather on evaluating their baseline performance for this classification task. for cnn-based classification, a deep learning model was developed using the keras framework. the cnn architecture consisted of three convolutional layers, designed to progressively capture hierarchical features within the image. the first layer employed 16 filters of size (3×3) with a stride of 1, followed by a relu activation function. the subsequent layers increased advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 402 the number of filters to 32 and 16, respectively. max-pooling layers were incorporated to reduce spatial dimensions while preserving essential information. the extracted features were flattened and passed through a fully connected layer with 256 neurons, utilizing relu activation to capture high-level patterns. finally, the output layer consisted of a single neuron with a sigmoid activation function, making it suitable for binary classification. the cnn model was trained using the adam optimizer with a learning rate of 0.001, and binary cross-entropy loss was used to measure classification error. the training process spanned 50 epochs with a batch size of 32, incorporating early stopping to prevent overfitting. the cnn architecture used in this study is illustrated in fig. 5. the performance of all models was evaluated using precision, recall, and f1-score, providing a comprehensive assessment of classification effectiveness. additionally, confusion matrices were generated to analyze misclassifications and model behavior. to assess computational efficiency, the training time for each model was recorded. fig. 5 image-based cnn model architecture 4.3. landmark-based method in the landmark-based method, facial images were transformed into structured numerical representations by extracting key facial points. the mediapipe library was employed to extract 468 facial landmarks, capturing the relative positions of key facial features along the x and y axes. this approach enabled the conversion of unstructured image data into a standardized format for ml classification. following preprocessing, the extracted landmarks were stored as structured data and normalized using feature standardization, ensuring values were scaled to a comparable range. the labels were encoded as binary values, with normal expressions labeled as 0 and hurt expressions labeled as 1. for cnn-based classification, the landmark data was reshaped into a format compatible with 1d convolutional layers, allowing the model to process sequential patterns in the landmark coordinates. as in the image-based method, the lrc, svm, rfc, and gbc models were trained using default parameters, ensuring that the evaluation remained focused on baseline performance rather than fine-tuning. for the cnn model, the architecture was adapted to handle 1d landmark data, replacing 2d convolutional layers with 1d convolutional layers. the model consisted of an initial 1d convolutional layer with 32 filters and a kernel size of 3, followed by relu activation and max-pooling to downsample the feature representation. a flattening layer was then used to convert the extracted spatial features into a one-dimensional vector. the fully connected layer comprised 128 neurons with relu activation, followed by an output layer with sigmoid activation for binary classification. the model was compiled using the adam optimizer with a learning rate of 0.001, and training was performed with binary cross-entropy loss. advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 403 the cnn architecture for the landmark-based method is illustrated in fig. 6. as with the image-based approach, model performance was assessed using precision, recall, and f1-score. confusion matrices were utilized to further evaluate classification accuracy, while training time was recorded to compare computational efficiency. fig. 6 landmark-based cnn model architecture 5. experimental results this study compares image-based and landmark-based fer techniques using various ml models, highlighting the distinct advantages and challenges of each approach, with the input data from both methods illustrated in fig. 7, and the results, including performance metrics and model comparisons, summarized in table 3. fig. 7 research input data illusion table 3 machine learning model performance model techniques training time (seconds) accuracy precision recall f1-score svm landmark 0.24 0.8550 0.8876 0.8550 0.8519 image-hog-scaling 0.19 0.8200 0.8363 0.8200 0.8178 gbc landmark 31.72 0.8850 0.8965 0.8850 0.8842 image-hog-scaling 20.93 0.8700 0.8724 0.8700 0.8698 rfc landmark 1.34 0.8950 0.9018 0.8950 0.8946 image-hog-scaling 1.36 0.8600 0.8601 0.8600 0.8600 lrc landmark 0.11 0.8850 0.8939 0.8850 0.8843 image-hog-scaling 0.09 0.7900 0.8047 0.7900 0.7874 cnn landmark 2.01 0.9500 0.9541 0.9541 0.9541 image-hog-scaling 88.89s 0.8700 0.8558 0.8900 0.8725 advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 404 the classification results of the five models on landmark-based and image-hog-scaling features in table 3 are summarized below: (1) the svm model performed strongly with the landmark-based technique (accuracy 0.8550, precision 0.8876, recall 0.8550, and f1-score 0.8519) but slightly decreased with the image-hog-scaling method (accuracy 0.8200, precision 0.8363, recall 0.8200, and f1-score 0.8178). (2) the gbc showed high performance with the landmark-based technique (accuracy 0.8850, precision 0.8965, recall 0.8850, and f1-score 0.8842) and also performed well with the image-hog-scaling method (accuracy 0.8700, precision 0.8724, recall 0.8700, and f1-score 0.8698). (3) the rfc achieved strong results with the landmark-based technique (accuracy 0.8950 and precision 0.9018) but lower performance with the image-hog-scaling method (accuracy 0.8600 and precision 0.8601). (4) the lrc was efficient in training time with the landmark-based technique (accuracy 0.8850, precision 0.8939, recall 0.8850, and f1-score 0.8843) but underperformed with the image-hog-scaling method (accuracy 0.7900, precision 0.8047, recall 0.7900, and f1-score 0.7874). (5) the cnn outperformed other models with the landmark-based technique (accuracy 0.9500, precision 0.9541, recall 0.9541, and f1-score 0.9541), while the image-hog-scaling method also yielded strong results (accuracy 0.8700, precision 0.8558, recall 0.8900, and f1-score 0.8725). these results meet the objective of comparing the performance of image-based and landmark-based fer techniques, providing insight into the effectiveness of different ml models for emotion recognition. the findings suggest that while landmark-based methods, such as those using facial feature points, offer higher accuracy and precision, image-based methods like hog-scaling remain viable alternatives, although slightly lower in performance. this comparison informs future work on optimizing emotion recognition systems for real-world applications across various datasets and conditions. 6. discussion this study emphasizes the critical role of selecting appropriate ml models and feature extraction methods to achieve optimal classification outcomes. the performance of each model is summarized as follows: (1) the svm model exhibited sensitivity to the feature extraction techniques employed, with the landmark-based approach significantly outperforming the image-based method. this finding underscores the importance of landmark features in enhancing the svm’s ability to identify complex patterns in facial expression data, corroborating the conclusions of both sharma et al. [9] and michael revina and sam emmanuel [1]. (2) the gbc demonstrated robust performance across both feature extraction techniques, indicating its adaptability to diverse data representations. although the training duration was longer, particularly when using the landmark-based method, the gbc’s superior accuracy, precision, recall, and f1-scores justified the extended training period. this finding aligns with di luzio et al. [27], who highlighted gbc’s efficacy in managing complex datasets. (3) the rfc displayed consistent performance across both feature extraction approaches, achieving high precision, recall, and f1-scores while requiring relatively short training times. this combination of efficiency and effectiveness positions rfc as a reliable model for classification tasks, echoing the results observed by munasinghe [26] and canedo and neves [2], who demonstrated rfc’s reliability in image classification. (4) the lrc exhibited remarkable efficiency in training time, especially with the landmark-based technique, where training required only 0.11 seconds. however, the notable decline in performance with the image-based method suggests that lrc is more sensitive to the quality of feature selection. this aligns with findings by kanjanawattana et al. [3], who identified limitations in the use of lrc for more complex classification tasks. advances in technology innovation, vol. 10, no. 4, 2025, pp. 395-406 405 (5) the cnn emerged as the top-performing model, particularly with the landmark technique, achieving superior accuracy, precision, recall, and f1-scores. despite the longer training time, particularly with the image-based technique (88.89 seconds), the substantial improvements in key performance metrics justify the increased computational cost. the cnn’s ability to automatically learn hierarchical features from raw image data positions it as an effective choice for fer, as demonstrated by hilbe [13] and bodini [11]. in summary, these findings emphasize the importance of careful model and feature selection. the researcher highlights the trade-offs between computational time and performance. for higher accuracy, computationally intensive models like cnn, particularly when paired with landmark-based features, offer substantial benefits. 7. conclusions this study compared five machine learning models (cnn, svm, rfc, lrc, and gbc) for recognizing facial expressions. both image-based hog features and landmark-based methods were evaluated to classify normal and hurt expressions using data from the delaware pain database and utkface. the main findings from this research are: (1) landmark-based methods consistently performed better than image-based hog methods across all models, demonstrating greater effectiveness in distinguishing facial expressions. (2) cnn achieved the best results with landmark-based features, reaching 95% accuracy, 95.41% precision, recall, and f1score, making it the most effective method for applications requiring high accuracy. (3) traditional machine learning models (svm, rfc, gbc) showed strong performance with landmark features, achieving accuracies between 85.5% and 89.5%, making them good alternatives when computing resources are limited. (4) large performance differences existed between feature extraction methods, with lrc showing the biggest gap (88.5% vs. 79% accuracy for landmark vs. image-based features). (5) analysis of computing efficiency showed trade-offs between accuracy and training time, with lrc having the fastest training (0.11 seconds) while cnn needed longer training time but provided better classification results. 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[28] s. hangaragi, t. singh, and n. n, “face detection and recognition using face mesh and deep neural network,” procedia computer science, vol. 218, pp. 741-749, 2023. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 english language proofreader: si-yu lin investigation of heat transfer characteristics and electrical conductivities in nacl, kcl, and nano3 solutions nigar kantarci-carsibasi*,1,2, jana masalmah2, ozlem simsek1 1uskudar university, faculty of engineering and natural sciences, department of chemical engineering, istanbul, turkey 2uskudar university, graduate school of science, chemical engineering program, istanbul, turkey received 25 september 2024; received in revised form 10 december 2024; accepted 12 december 2024 doi: https://doi.org/10.46604/aiti.2024.14330 abstract this study aims to optimize heat exchanger systems by investigating the effects of water-soluble salts (nacl, kcl, and nano3) on heat transfer rates and electrical conductivity. experiments are conducted using plate-type (phe) and double-pipe (dphe) heat exchangers. the heat transfer coefficient ranged from 1.5–6.5 kw/m²k in phe and 3.5–20 kw/m²k in dphe. nacl achieves the highest heat transfer rates, followed by kcl and nano3, all outperforming pure water. electrical conductivity peaks at 1 mhz, decreasing afterward, with nacl and kcl showing higher conductivity than nano3. conductivity increases with temperature, peaking at 70°c, and is more sensitive to temperature for kcl and nacl. this dual-focus study correlates thermal and electrical properties, illustrating how variations in salt type, concentration, and temperature influence ion behavior, which plays a critical role in optimizing industrial heat transfer and electrical conductivity processes. keywords: heat transfer coefficient, conductivity, sodium chloride (nacl), potassium chloride (kcl), sodium nitrate (nano3) 1. introduction heat transfer between flowing fluids is a fundamental physical phenomenon that has long attracted researchers' interest. several types of heat exchangers are used in different combinations, whereas, fundamentally, they all facilitate the transfer of thermal energy between two distinct fluids at different temperatures. they are integral to the operation of many applications across a wide range of fields, such as the glass and metal melting industries; all power-involved processes and operations, such as refineries, chemical, food, and pharmaceutical industries, waste heat recovery, and environmental engineering. several types of heat exchangers, including plates, double-pipes, shells, tubes, and compact designs, are used in a variety of applications [12]. the fundamental concept in designing a heat exchanger is to use pipes or similar containers to transfer heat between fluids, whether hot or cold. typically, a heat exchanger consists of coil-shaped pipes circulating the fluid within a closed chamber, allowing another fluid to flow around them. heat exchangers can be classified based on several factors: the contact area between hot and cold fluids, the direction of fluid flow, the mechanism of heat transfer, and their mechanical structure. structurally, heat exchangers are categorized into two main types: plate heat exchangers (phes) and coil heat exchangers (ches) [3-4]. a plate heat exchanger (phe) uses metal plates with various folds to transfer heat between two fluids. phes are compact and offer numerous advantages and unique application features, including flexible thermal sizing, easy cleaning to maintain hygienic conditions, close approach temperatures due to their pure counterflow operation, and enhanced heat transfer performance [4]. phe includes multiple alternating channels for hot and cold fluids, each confined between two corrugated ** corresponding author. e-mail address: nigar.carsibasi@uskudar.edu.tr advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 144 plates. compared to shell-and-tube and double-pipe heat exchangers, the use of corrugated plates enhances the heat transfer coefficient and reduces the required heat transfer surface area. phes are widely used in various applications, such as cooling systems, food processing, chemical industries, and power generation. they are preferred for their compactness and high heat recovery efficiency [5]. coil heat exchangers (ches) feature one or more pipes or tubes within a pipe shell, with two straight pipe segments joined at one end to create a u or "hairpin" configuration. the outer surface of the inner tube may have longitudinal fins. in this study, a double-pipe heat exchanger (dphe) system is employed. the flow in a dphe follows a counter-current configuration, which is advantageous for achieving close temperature approaches and handling a wide range of temperatures [6]. the primary advantage of using double-pipe heat exchangers (dphes) is the flexibility of adjusting the number of hairpins to achieve different heat transfer rates. as fins increase the heat transfer surface area, it is essential to allow for optimized arrangements of hairpins. additionally, dphes can accommodate a variety of working fluids supporting higher operating pressures and temperatures. however, dphes are typically used in low-capacity heat transfer applications. in high-capacity applications, the pressure drops increase significantly, leading to a notable rise in operating costs [7-8]. the basic tool for heat exchanger design and analysis can be obtained by lmq u a t=   (1) where q is the heat transfer rate (w); a is the heat transfer area (m2); u is the overall heat transfer coefficient (w/m2k); and δtlm is the logarithmic mean temperature difference (kelvin). the mean temperature difference depends on the device's design characteristics of the fluid flow direction [9-10]. the logarithmic mean temperature δtlm difference can be calculated by 1 2 1 2 ln lm t t t t t  −  =       (2) the temperature differences δt1 and δt2 between the two fluids are calculated based on the inlet and outlet process temperatures at the four terminals of the equipment. the logarithmic mean temperature difference for two fluid streams exchanging energy in counter-current flow is greater than the value calculated for the same streams in parallel flow. as indicated by eq. (1), counter-current flow is the preferred design choice because it requires a smaller heat transfer area, and results in lower costs for achieving the same level of heat recovery compared to concurrent flow [10]. this study aims to investigate the effects of salt type, concentration, and temperature on the heat transfer performance and electrical conductivity of water-soluble electrolytes (nacl, kcl, and nano₃). by comparing results obtained from plate heat exchangers (phes) and double-pipe heat exchangers (dphes), the study seeks to identify how these parameters influence the thermal and electrical properties of the solutions, with potential implications for optimizing industrial heat exchange systems. 2. literature review studying the heat transfer characteristics of aqueous solutions is essential for optimizing the design and operation of heat exchanger systems, improving energy efficiency, reducing operational costs, and enhancing performance. moreover, understanding the heat transfer behavior of aqueous solutions ensures the safety and reliability of heat exchanger systems. this allows engineers to identify potential issues such as fouling, corrosion, and thermal stress, and implement measures to mitigate these risks. efficient heat transfer in aqueous solutions reduces energy consumption and greenhouse gas emissions associated with heating and cooling processes. it also facilitates the use of renewable energy sources and waste heat recovery systems. heat transfer research in aqueous solutions has applications across various industries, including chemical processing, food and beverage production, pharmaceuticals, wastewater treatment, and renewable energy systems [11]. advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 145 several recent studies based on heat transfer measurements in nanofluidic systems, exploring experimental, theoretical, and numerical analyses, have been conducted. kakac & pramuanjaroenkij (2009) presented a detailed review of experimental and theoretical heat transfer enhancements using nanofluids [12]. minea (2017) conducted a numerical analysis of hybrid nanofluids and their impacts on heat transfer performance [13]. another recent study by rehman et al. (2024) investigates the impacts of radiation and magnetohydrodynamics (mhd) on the water-based nanofluid flow through a shrinking/stretching wedge, with numerical solutions obtained through matlab [14]. the study of electrolyte solution conductivity is a crucial field in physical chemistry, with significant scientific inquiry focused on overcoming its fundamental obstacles. moreover, examining the concentration and temperature dependence of the conductivity of an electrolyte solution is incredibly important for evaluating and improving the performance of electrochemical systems [15]. chandra and bagchi (2000) utilized molecular dynamics simulations to investigate the frequency-dependent variation in solution conductivities [16]. their research revealed that ionic friction distributions occur at high frequencies and are influenced by frequency-dependent friction and electrolyte concentration. relative permittivity changes are used to measure material properties employing advanced measurement technologies yamaguchi et al. (2009) provided a detailed explanation of frequency-dependent conductivity variations, attributing these to the dynamics of ion pairs and fluid flow interactions. conductivity measurements are significant because they provide essential insights into ion behavior in solutions, facilitating prompt and precise evaluation of solution parameters. this capability is crucial for ensuring quality, safety, and integrity across various industries [17]. adding solid particles to heat transfer media has long been recognized as an effective technique for enhancing heat transfer. however, using suspended millimeteror micrometer-sized particles can cause significant issues, such as abrasion, clogging, high-pressure drops, and particle sedimentation [18]. to circumvent these problems, recent studies have focused on using nanoparticles and nanofluids to improve heat transfer characteristics [19-20]. several recent studies based on electrical conductivity specifically in nanofluids, through experimental, theoretical, and numerical analyses, have been investigated. choi et al. (1995) conducted one of the foundational studies introducing the concept of nanofluids and discussed their enhanced thermal properties [21]. in the present study, the heat transfer characteristics, and electrical conductivities of common water-soluble salts, including nacl, kcl, and nano3, were investigated. heat transfer was studied via two different media: plate heat exchangers (phes) and double-pipe heat exchangers (dphes). the analysis focused on how the type of salt affects the overall heat transfer coefficient and how the inlet temperature of the salt solution influences the heat transfer rate. additionally, the effects of the salt type, concentration, and temperature on the electrical conductivity of these solutions were examined. by evaluating the heat transfer rates and conductivity values while analyzing the factors influencing them, this study offers insights into the physical properties of ions in solution, the nature and strength of ion interactions, and their effects on heat transfer and electrical conductivity, which are crucial in many industrial operations. this work explores the interplay between electrical conductivity and thermal properties by evaluating the impact of salt type, concentration, and temperature on conductivity. this dual-focus approach, which correlates heat transfer characteristics with the electrical behavior of ion solutions, highlights the underlying physical properties of ions, their interactions, and their influence on both thermal and electrical processes. the insights gained are particularly significant for industrial applications, where understanding these properties is critical for optimizing heat exchanger performance, designing efficient cooling systems, and improving process efficiencies. the integration of two heat exchanger systems and the detailed analysis of ionic interactions marks a novel contribution to the field, offering practical relevance and advancing the knowledge of heat and mass transfer in electrolyte solutions. the basic results of the study were that dphe demonstrated more efficient heat transfer than the phe. in phe, the highest heat transfer rate was observed for nacl, followed by kcl and nano3, all of which outperform pure water. the conductivity advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 146 follows a linear trend with increasing signal frequency up to a threshold of 1 mhz. at low salt concentrations (up to 4% w/w), the conductivity typically increases linearly with increasing salt concentration. above a concentration of 4%, a further increase in concentration does not result in a significant increase in conductivity. 3. experimental studies to investigate heat transfer rate the calculation of the heat load and overall heat transfer coefficient in a counter-current flow plate-type heat exchanger (phe) and a double-pipe heat exchanger (dphe) is conducted using the same procedure. a schematic of the compact heat exchanger, obtained from argemsan model ht320 (https://www.argemsan.com/assets/pdf/encatalog.pdf), is presented in fig. 1. plate heat exchangers (phes) and double pipe heat exchangers (dphes) are studied to measure and compare the heat transfer rates of pure water, nacl, kcl, and nano3 salt solutions. phe and dphe circuit diagrams on the right-hand side of fig. 1 display the flows of hot (red) and cold (blue) streams. the hot streams are the tested aqueous solutions, which are cooled by tap water. the experiments are performed for pure water, 2% w/w nacl, kcl, and nano3 solutions in both exchangers, keeping the flow rates of the hot and cold streams constant at 500 l/h and 100 l/h, respectively. additionally, to observe the effect of temperature on heat transfer, the inlet temperatures of the entering solutions are altered to 25, 30, 40, and 50°c. in each case, three data sets are recorded for the entering and exiting temperatures of the hot aqueous solutions and cooling water. the average value is calculated for the three datasets in calculating the heat transfer coefficient, specific heat transfer coefficient for water (cp), and density. the heat load that is drawn from hot water (q̇hot) and the heat load transferred to the cold water (q̇cold) are both calculated by . . pq m c t=   (3) where q̇ is the rate of heat transfer (kj/s), ṁ is the mass flow rate (kg/s), cp is the specific heat capacity of the water (or saltwater) in kj/kg k, and ∆t is the temperature difference (k) between inlet and outlet water (or saltwater). the volumetric flow rates of the hot aqueous salt solution and cooling water are kept constant in this study at 500 and 100 liters/h, respectively. the density value is converted to the mass flow rate as follows . . m v=  (4) fig. 1 setup of the compact heat exchanger system used in this study since both density and specific heat capacity values depend on temperature, average values are calculated for both the density and specific heat capacity values evaluated at the inlet and outlet stream temperatures. for the salt solutions, a total of 11 kg of salt solution is prepared by dissolving 0.22 kg of (nacl, kcl, or nano3) to achieve a 2% w/w concentration. for the density and specific heat capacity values of salt solutions, the weighted average value for 2% w/w is evaluated as follows [22] , , ,0.98 0.02p mix p water p saltc c c=  +  (5) the cp values for nacl, kcl, and nano3 are estimated utilizing the nist chemistry webbook (webbook.nist.gov), where the solid phase heat capacity is calculated using the shomate equation as follows 2 3 , 2p salt e c a b t c t d t t = +  +  +  + (6) advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 147 where a to e are salt-specific constants, and t represents the temperature in kelvin, divided by 1000 [23]. the overall heat transfer coefficient u is then obtained by . lm q u a t =  (7) where u is the overall heat transfer coefficient (kw/m2k), q̇ is the rate of heat transfer from the hot stream (kw), and a is the cross-sectional area of the exchanger, which is 0.0299 and 0.168 m2 for the dphe and phe systems, respectively. δtlm is the logarithmic temperature difference (kelvin) given by eq. (2). for the counter-current flow regime, δt1 represents the temperature difference between the hot stream outflow and cold stream inflow, whereas δt2 represents the temperature difference between the hot stream inflow and the cold stream outflow. for heat transfer experiments, the salt mixtures are assumed to enter the heat exchangers as perfectly mixed and homogenous streams, temperature and flow rates are kept constant throughout the system, while density and specific heat values are averaged over the temperature range. the flow regimes in the heat exchanger systems are entirely laminar, with the reynolds number ranging from 110 to 185 for pure water and 2% w/w water-salt systems. 4. experimental studies to investigate conductivity the electrical conductivity of a material is related to its ability to conduct an electric current. the electrical conductivity, σ, measured in siemens per meter (s/m), is a characteristic of all materials. for highly conductive materials such as metals, this value is approximately 107 s/m, whereas for poorly conductive or insulating materials such as quartz, it is approximately 10−18 s/m. the conductivity values of aqueous solutions fall between these values. to measure the conductance of an electrolyte, two electrodes are immersed into the solution, and a voltage is applied. this setup generates a current in the external circuit connecting the electrodes. however, using dc voltages can lead to electrolysis and polarization of the electrodes, which eventually reduces the current passing through the circuit to zero. this issue can be avoided by using an alternating current (ac). when ac voltage is applied to the sample, both the in-phase current (related to the conductance) and the out-of-phase current (related to the capacitance, c) are monitored over a range of frequencies using an impedance analyzer. this method is known as admittance (or impedance) spectroscopy [24]. in the present study, the electrical conductivity of the samples is tested with an sfg-1003-gw instek function generator, i.e., direct digital synthesis (dds) with 1 channel, 3 mhz, and an aatech ads-3072b digital oscilloscope. electrical measurements involved placing probes into the prepared salt solutions in a beaker. the electrical conductivity and resistance of the salt solutions were measured using an ac circuit. the frequency is optimized by scanning a range from 1 hz to 3 mhz. fig. 2 shows an image of the experimental setup, which consists of a frequency generator and digital oscilloscope for conductivity measurements in fig. 2(a) along with the ac circuit of the setup in fig. 2(b). the variable resistance icon represents the resistance values obtained for the salt solutions. to determine the circuit's current, i (a), a 50 ohm resistor (r1) is added to the system. the voltage (vr1) across the 50 ohm resistor is divided by this resistance value to find the current, which is constant for all circuits, as presented in eq. (8). the voltage across the aqueous salt solution (vr2) is then calculated using eq. (9), subtracting the voltage across the 50 ohm resistor (vr1) from the source voltage (vsource) [25]: 1 1 ( ) rv i a r = (8) 2 1r source rv v v= − (9) to determine the resistance of the salt solution (r2), vr2 is divided by the following equation 2 2 rv r i = (10) 2 1 r  = (11) advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 148 where r2, assumed to represent impedance, is used to derive the conductivity value σ in siemens per centimeter (s/cm) by taking the reciprocal of r2 (1/r2), as given by eq. (11). for the conductivity measurements it is assumed that the voltage readings are uniform throughout the solutions, the frequency generator supplies a constant frequency, then the voltage difference between the source and the sample is used to calculate the resistance of solutions. (a) frequency generator and digital oscilloscope (b) diagram of the ac circuit setup fig. 2 experimental setup for conductivity measurements 5. results and discussion the results are divided into two sections: heat transfer and conductivity measurements. heat transfer results, obtained from experiments on plate-type and coiled heat exchanger systems, represent the average of three runs per measurement. conductivity measurements are recorded, after stabilizing the oscilloscope voltage readings for both the sample and the source. 5.1. heat transfer measurements the salt solutions serve as the hot fluid in the heat exchanger system while cooling is maintained with cold water. the overall heat transfer coefficient is determined for the phe and dphe systems using pure water and 2% w/w nacl, kcl, and nano3 salt solutions. additionally, keeping the concentration of salt solutions constant at 2%, the effect of increasing the inlet temperatures of the salt solutions on the heat transfer characteristics of both the phe and the dphe systems is investigated. for each measurement, three data sets are recorded, and the average u value, along with the standard error, is reported. the raw data for the average u values obtained from the studied systems are presented in tables 1 and 2 for dphe and phe systems. table 1 overall heat transfer coefficient (u) values with standard errors obtained for the systems studied in the dphe overall heat transfer coefficient values (kw/m2k) temperature double pipe heat exchanger (dphe) pure water 2% nacl 2% kcl 2% nano3 25°c 8,62±0,16 8,63±0,85 3,60±0,79 4,09±0,23 30°c 13,08±0,18 20,26±0,60 16,73±0,35 18,36±0,46 40°c 14,11±0,13 15,29±0,55 15,05±0,68 13,02±0,12 50°c 13,42±0,12 12,31±0,70 11,63±0,15 13,35±0,09 table 2 overall heat transfer coefficient (u) values with standard errors obtained for the systems studied in the phe overall heat transfer coefficient values (kw/m2k) temperature plate type heat exchanger system (phe) pure water 2% nacl 2% kcl 2% nano3 25°c 1,52±0,07 4,09±0,24 2,82±0,17 3,50±0,22 30°c 1,77±0,09 5,54±0,46 3,07±0,12 3,73±0,17 40°c 2,68±0,02 6,37±0,42 3,20±0,13 4,72±0,21 50°c 2,72 ± 0,04 6,50±0,50 3,52±0,13 5,59±0,18 in the phe system, the overall heat transfer coefficient ranges from 1.52 to 6.50 kw/m2k, whereas in the dphe system, it varies more widely between 3.60 and 20.26 kw/m2k. the corresponding profiles for all salts and pure water in both heat exchanger types are presented in fig. 3, with phe in fig. 3(a) and dphe in fig. 3(b). advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 149 (a) phe (b) dphe fig. 3 variation of the overall heat transfer coefficient (u) with temperature measured in a phe (a) and dphe (b) consequently, this study demonstrates the dphe achieves more efficient heat transfer than the phe. this may also explain why similar heat transfer profiles are obtained for water and saltwater systems in the dphe in fig. 3(a). in contrast, the differences between the studied systems are particularly noticeable in the case of phe in fig. 3(b). in phe, the highest heat transfer rate is obtained for nacl, followed by kcl and nano3, all of which surpass pure water. this finding aligns with previous research, which indicates that the heat transfer coefficient of salt solutions is greater than that of pure water and increases with increasing salt concentration [26]. the inlet fluid temperature (water or saltwater) strongly influences heat transfer. as the temperature of the inlet water or salt solutions increases from the ambient temperature of 25°c to 50°c, the overall heat transfer coefficient (u) also increases. the contrast is particularly noticeable in phe compared with dphe. in the dphe, once the temperature reaches 40°c, u values for water and salt solutions become nearly identical and stabilize, indicating that there is no significant difference in heat transfer characteristics between water and saltwater solutions. additionally, the influence of the type of salt also becomes less distinguishable. the thermophysical properties of sodium chloride (nacl) solutions are more extensively studied than those of potassium chloride (kcl) and sodium nitrate (nano3) solutions [27]. nacl-rich water is prevalent in subsurface environments, including geothermal reservoirs, deep aquifers, and regions affected by saltwater intrusion. therefore, previous research on the thermophysical behavior of nacl solutions can provide a basis for understanding the properties of kcl and nano3 solutions [28]. in this study, the heat transfer characteristics of these salts are found to be similar, especially in the dphe system. however, there is a more significant difference among the salt solutions in the phe system, and the highest u value is obtained in the nacl solution. advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 150 5.2. conductivity measurements to determine the optimal signal frequency, frequency scans from 1 hz to 3 mhz on nacl, kcl, and nano3 solutions are conducted at three different concentrations, 0.5%, 2.0%, and 5%, while maintaining a constant temperature at 23°c. the raw conductivity data (σ) values for different frequencies obtained from the studied systems are presented in table 3. table 3 conductivity values for salt solutions measured at different frequencies signal frequency conductivity (σ) nacl 0.5% nacl 5% kcl 0.5% kcl 5.0% nano3 0.5% nano3 5% 1 hz 0.012 0.036 0.008 0.023 0.007 0.018 10 hz 0.013 0.064 0.009 0.027 0.007 0.020 100 hz 0.014 0.064 0.009 0.036 0.006 0.026 1khz 0.015 0.080 0.012 0.034 0.007 0.031 10 khz 0.017 0.113 0.015 0.035 0.008 0.038 100 khz 0.020 0.113 0.021 0.113 0.009 0.043 1 mhz 0.022 0.180 0.024 0.113 0.011 0.053 2 mhz 0.023 0.113 0.025 0.113 0.011 0.053 3 mhz 0.020 0.080 0.016 0.111 0.012 0.050 an illustration of the variation in conductivity values of these salt solutions with increasing signal frequency is depicted in fig. 4. panels (a), (b), and (c) represent nacl, kcl, and nano3 solutions, respectively. upon examination of the profiles, it can be inferred that the conductivity follows a linear trend for all investigated systems up to a certain frequency threshold, which is determined as 1 mhz in this study. the conductivity values increase with frequency, peaking at approximately 1 mhz and then either decreasing or remaining constant with further increases in frequency. consequently, the optimal frequency for all the salt solutions is determined to be 1 mhz. beyond this frequency, all three salt solutions exhibit resistive behavior, and the conductivity becomes independent of the signal frequency. by determining the optimum frequency value, the effect of concentration on conductivity is explored for the three aqueous salt solutions while keeping the temperature and frequency constant at 1 mhz. (a) conductivities of nacl-water solution at 20°c at different frequencies (b) conductivities of kcl solutions at different frequencies fig. 4 conductivity profiles of nacl (a), kcl (b), and nano3 (c) solutions at different frequencies advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 151 (c) conductivities of nano3 solutions at different frequencies fig. 4 conductivity profiles of nacl (a), kcl (b), and nano3 (c) solutions at different frequencies (continued) the viscosity of a solution is defined as its resistance to flow and is a function of the solute concentration and mass of its particles. when more ions are introduced into a solution, the resistance to flow is enhanced. additionally, as the concentration of ions in the solution increases, they are positioned closer together, reducing the distance between them. consequently, the resistance of the solution decreases because more ions are available to carry the electrical charge, and there is less free space in between. therefore, a more concentrated solution can conduct more current. additionally, when ions are dissolved in different solutions, the conductivity depends on the specific electrolyte used. several types of ions and their mobility affect the conductivity of a solution [29]. at low salt concentrations, the conductivity typically increases with increasing salt concentration. however, in certain viscous solutions, reduced ion mobility can lead to a decline in conductivity despite the higher concentration [28]. fig. 4 demonstrates that the conductivities of all aqueous salt solutions (nacl, kcl, and nano3) increase with increasing salt concentration, which aligns with the findings in literature review. to better illustrate the effect of salt concentration on conductivity, with the frequency fixed at 1 mhz, a wide concentration range of 0.5-20% w/w is investigated next, and the results are depicted in fig. 5. as the salt concentration increased, the conductivity rose until reaching 4–5% w/w. above 5%, further increases in concentration had no significant effect on conductivity, which remained constant. consequently, the lower concentration range is prioritized for conductivity measurements to evaluate the effects of salts more efficiently. this approach is also adopted in heat transfer studies. additionally, using lower salt concentrations minimized the risk of altering the instrument's internal structure, which could otherwise be compromised by salt-induced aggregation within the circulating system, thereby preventing potential disruption. this finding aligns with the study by bera and colleagues, who investigated the conductivity of a kcl solution conductivity and reported that it follows a linear function of concentration up to 1%. beyond this threshold, they found that the rate of increase in conductivity decreases due to the greater ion concentration effects [29]. fig. 5 conductivity profiles for nacl, kcl, and nano3 salt solutions at 1 mhz and at different concentrations advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 152 in the present study, this critical concentration is determined to be approximately 4% w/w. interestingly, the same trend and critical concentration value were observed for all salt solutions independently. it can also be concluded that conductivity is not a colligative property, meaning that it depends on both the type and amount of solute. nacl and kcl yielded similar values and trends, with nacl exhibiting slightly higher conductivity than kcl at the same concentration. however, nano3 demonstrated significantly lower conductivity than nacl and kcl. previous heat transfer experiments have consistently shown that nacl results in a higher heat transfer rate at the same temperature and concentration than kcl and nano3. therefore, nacl also demonstrated the highest conductivity among the tested salt solutions. to examine the impact of temperature on the conductivity of the salt solutions, two different concentrations (0.5% and 2% w/w) are tested for each salt solution, with temperatures ranging from 23°c to 80°c. lower concentrations are selected to minimize the influence of high salt concentrations, allowing for a clearer assessment of the effect of increasing temperature. the raw data for the conductivity (σ) values obtained from the experiments at different temperatures are presented in table 4. table 4 conductivity values for salt solutions measured at different temperatures conductivity(σ) temperature nacl 0.5% nacl 2% kcl 0.5% kcl 2% nano3 0.5% nano3 2% 23 oc 0.015 0.053 0.017 0.046 0.012 0.026 30 oc 0.015 0.068 0.021 0.053 0.010 0.028 40 oc 0.018 0.075 0.026 0.064 0.009 0.028 50 oc 0.019 0.113 0.028 0.085 0.013 0.032 60 oc 0.019 0.134 0.028 0.113 0.015 0.040 70 oc 0.024 0.134 0.046 0.120 0.019 0.044 80 oc 0.024 0.140 0.046 0.120 0.019 0.040 (a) effect of temperature on nacl-water solution conductivity at 1 mhz (b) effect of temperature on kcl-water solution conductivity at 1 mhz fig. 6 conductivity profiles for nacl (a), kcl (b), and nano3 (c) salt solutions with increasing temperature at a 1 mhz frequency advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 153 (c) effect of temperature on nano3-water solution conductivity at 1 mhz fig. 6 conductivity profiles for nacl (a), kcl (b), and nano3 (c) salt solutions with increasing temperature at a 1 mhz frequency (continued) the variation in conductivity with increasing temperature is illustrated in fig. 6, with panels (a), (b), and (c) representing nacl, kcl, and nano3, respectively. as the temperature rises, conductivity also increases due to enhanced molecular motion. additionally, temperature influences energy transfer in all materials. higher temperatures increase kinetic energy for the particles in the solution, facilitating ion movement. this enhanced motion allows charged ions to overcome attraction to each other and migrate toward their respective electrodes. this trend is observed across all the salt systems at both the 0.5% and 2% w/w concentrations. however, at approximately 70°c, the conductivity values reach a peak and remain constant thereafter. (a) %0,5 concentration solution (b) %2 concentration solution fig. 7 conductivity profiles with increasing temperatures for comparing nacl, kcl, and nano3 at the same concentration as seen in fig. 7, the comparison of conductivity values at various temperatures for salt solutions at concentrations of 0.5% and 2% w/w have been shown. for all the salts and concentrations investigated, the conductivity increased with increasing temperature. at 0.5% nacl, kcl has higher conductivity than nacl does (although at 23°c, nacl has a slightly greater advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 154 conductivity). however, temperature significantly impacts kcl conductivity more than it does for nacl, as shown in fig. 7(a). the conductivity increases to approximately 70°c, where it peaks and then remains constant. when the concentration increases to 2%, the conductivity values for nacl and kcl converge more, indicating that higher ion concentrations hinder the identifiability between the two salts, as shown in fig. 7(b). higher salt concentrations produce effects similar to those of high signal frequencies. as temperature increases, the conductivity rises and stabilizes at approximately 60°c, becoming remarkably close for 2% kcl and nacl. beyond this point, temperature increases do not significantly affect conductivity, facilitating conductivity nearly independent of temperature. nano3 consistently exhibits the lowest conductivity values. at a 2% concentration, nano3 maintains an almost flat profile, with increasing temperature having a minimal effect on its conductivity, unlike nacl and kcl. these findings suggest that nano3 is more resistant to temperature changes than nacl and kcl. more specifically, at a concentration of 0.5%, increasing the temperature from 25°c to 70°c resulted in conductivity increases of 172%, 56%, and 61% for kcl, nacl, and nano3, respectively. moreover, at a concentration of 2%, the conductivity increased by 162%, 165%, and 55% for kcl, nacl, and nano3, respectively. these findings suggest that kcl and nacl are more sensitive to temperature changes than nano3, which exhibits a less pronounced response. 6. conclusions and recommendations in this study, heat transfer and conductivity experiments were conducted to investigate the influence of electrolytic solute particles in water. these investigations aimed to provide insights into the physical properties of ions in solution, the strength and nature of ion interactions, and their effects on both heat transfer and electrical conductivity. the following section points out the important findings of this study: (1) the introduction of solute particles as water-soluble electrolytes significantly altered the heat transfer and conductivity properties compared with those of pure water. (2) two different heat exchanger systems, phe and dphe, were compared, and it was observed that the dphe demonstrated more efficient heat transfer than the phe. therefore, similar profiles were obtained for the heat transfer characteristics of the water and water salt systems in the dphe. in phe, the highest heat transfer rate was obtained for nacl, followed by kcl and nano3, all of which surpass pure water. (3) for the conductivity measurements, it was observed that the conductivity follows a linear trend with increasing signal frequency up to a threshold of 1 mhz, as determined in this study. at low salt concentrations (up to 4% w/w), the conductivity typically increases linearly with increasing salt concentration. above a concentration of 4%, a further increase in concentration does not result in a significant increase in conductivity, and conductivity stays constant or, in some cases, begins to decrease. (4) it can also be concluded that conductivity is not a colligative property, meaning that it depends on both the type and amount of matter. nacl and kcl yielded similar values and trends, with nacl having slightly higher conductivity at the same concentration. however, nano3 has a significantly lower conductivity than nacl and kcl. as the temperature increases, the conductivity also increases due to enhanced molecular motion. however, at approximately 70°c, the conductivity values peak and remain constant thereafter. kcl and nacl are more sensitive to temperature changes than nano3, which demonstrates a weaker response. as a recommendation for future work, greater focus should be placed on expanding the scope of electrolytes studied, including organic salts, multivalent ions, and mixed systems, to better understand their effects on heat transfer and conductivity. investigating higher temperature ranges and more concentrated solutions could offer further insights into their behavior under extreme conditions. analyzing flow dynamics, such as laminar and turbulent regimes, could help optimize heat exchanger advances in technology innovation, vol. 10, no. 2, 2025, pp. 143-156 155 performance, while computational modeling, such as cfd, could provide more detailed simulations. exploring advanced materials or coatings for heat exchangers may enhance durability and efficiency, particularly in corrosive environments. longterm stability studies addressing issues like fouling or scaling would help ensure the practical applicability of these solutions. additionally, testing in real-world industrial systems and comparing electrolytic solutions with alternatives, such as nanofluids, could highlight potential advantages. environmental and economic assessments should also be conducted to evaluate the sustainability and cost-effectiveness of employing electrolytic solutions in industrial applications. conflicts of interest the authors declare no conflict of interest. references [1] a. f. faraj, i. d. j. azzawi, and s. g. yahya, “pitch variations study on helically coiled pipe in turbulent flow region using cfd,” international journal of heat and technology, vol. 38, no. 4, pp. 775-784, 2020. 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[29] t. k. bera and j. nagaraju, “electrical impedance spectroscopic studies on broiler chicken tissue suitable for the development of practical phantoms in multifrequency eit,” journal of electrical bioimpedance, vol. 2, no. 1, 2011. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 3-v10n4(2025)-aiti#14579(358-369).docx advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 dbscan-based minimum enclosing ellipse using the control barrier function for safe navigation of mobile robots ju-feng wu, chia-chun huang, ming-yang cheng* department of electrical engineering, national cheng kung university, tainan, taiwan, roc received 03 december 2024; received in revised form 28 february 2025; accepted 11 march 2025 doi: https://doi.org/10.46604/aiti.2025.14579 abstract this paper aims to reduce the redundant unsafe area in quadratic program approaches based on the control barrier function (cbf) and the control lyapunov function (clf) for collision avoidance, hereafter referred to as the cbf-clf approach. existing cbf-clf quadratic program approaches typically construct cbf based on euclidean distance; however, the redundant unsafe area due to obstacles is excessively large, which may prevent finding feasible solutions. to address this issue, this study employs density-based spatial clustering of applications with noise (dbscan) and the minimum enclosing ellipse (mee) to reduce the unsafe area. the proposed approach is referred to as the dbscan-mee-cbf. the effectiveness of the proposed method is demonstrated through both computer simulations and real-world experiments. specifically, the proposed method reduces the size of the redundant unsafe area by up to 26.52% while maintaining robust collision avoidance. keywords: collision avoidance, mobile robot navigation, control barrier function, control lyapunov function 1. introduction various robotic systems are commonly used in automated factories [1]. in addition to industrial robot manipulators that are typically fixed to a specific site, other robotic systems, such as automated guided vehicles (agv) and autonomous mobile robots (amr), are also deployed in factories to improve production efficiency. in particular, agvs move along a pre-defined path. the agv will stop moving when it detects obstacles that may cause a possible collision. however, the number of agvs used in modern automated factories or logistics centers is very large. since the predefined paths for agvs to move along may intersect, collision events will likely occur and lead to a deterioration in production efficiency. to cope with this problem, developing a mobile robot that does not need to move along a predefined path and can avoid obstacles autonomously is crucial. in particular, commonly used collision avoidance algorithms for amrs include the potential field method [2], vector field histogram (vfh) [3], and rapidly-exploring random tree (rrt) and its improved variant, rrt*, etc. these aforementioned methods cannot guarantee the safety of amrs or agvs. to cope with this problem, the ideas of control barrier function (cbf) and control lyapunov function (clf) are adopted in this paper to avoid collisions with obstacles. moreover, this paper uses density-based spatial clustering of applications with noise (dbscan) in combination with a minimum enclosing ellipse (mee) to define the unsafe regions around obstacles. compared to the enclosing circle, the mee provides more space for the robot. both computer simulations and actual experiments are conducted to verify the effectiveness of the proposed dbscan-mee-cbf approach. in particular, a turtlebot running on robot operating system (ros) is used to perform navigation while avoiding obstacles. both the simulation and experimental results indicate that the proposed dbscan-mee-cbf approach can reduce the size of the redundant unsafe area of obstacles from 1.602% to 26.52% and accomplish collision avoidance. * corresponding author. e-mail address: mycheng@mail.ncku.edu.tw advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 359 the remainder of this paper is organized as follows. section 2 provides a brief review of previous works related to obstacle avoidance algorithms, cbf-clf-based approaches, and dbscan clustering. section 3 gives a brief introduction to the cbf, which serves as the foundation for the proposed method. section 4 introduces the proposed dbscan and mee method, explaining how it improves obstacle avoidance by reducing the size of the redundant unsafe areas. section 5 presents simulation and experimental results to validate the effectiveness of the proposed approach. finally, section 6 concludes the paper and discusses potential future research directions. 2. literature review in recent years, environmental modeling and risk-aware navigation have become crucial in public health surveillance [4] and mobile robot navigation [5]. in particular, the role of fluid dynamics in airborne disease transmission is investigated in koley [4], demonstrating that precise environmental modeling is essential for optimizing ventilation strategies and infection risk assessment. similarly, mobile robots operating in complex environments also require an accurate perception of obstacle distributions and risk areas to navigate safely and efficiently. in the existing obstacle avoidance approaches, the potential field [6] approach can be applied to obstacle avoidance problems for different types of robotic systems, such as mobile robots [7-9] and industrial robot manipulators [10-12]. to increase computation speed and enhance the stability of error detection, the moving direction of a mobile robot is represented by a histogram in the vfh method [13]. the moving direction with a higher histogram has a higher cost and is thus less desirable. the vfh* approach [14], an enhanced version of the vfh method, integrates the vfh method with the a-star pathfinding (a*) algorithm to handle the dead-end problem. however, the common drawback of the approaches mentioned above is that the mobile robot may be trapped at a local minimum, so it may fail to reach its destination. in contrast, the rrt approach [15] adopts a different strategy. in the rrt approach, the environment model is constructed in advance. the tree and nodes between the starting and destination points are also built. if there are obstacles between the starting point and the destination point, these obstacles can be avoided during the tree construction process. after completing the tree and nodes, the mobile robot can move along the planned path to prevent it from being trapped in a local minimum. however, one of the biggest problems for the rrt approach is that if an object accidentally appears on the planned path when the mobile robot is moving along the path, the mobile robot must stop to replan the path to avoid the obstacle. this may significantly slow down the moving task, and the production efficiency will be affected as well. to remedy the aforementioned drawback, a motion planning approach that combines the cbf and clf was proposed [16-17]. in particular, the clf is employed as the control scheme to control the mobile robot moving from the starting point to the destination point. at the same time, the cbf is used as a safety filter to ensure the safety of the mobile robot when avoiding obstacles. moreover, through some mathematical manipulations, cbf and clf are unified as a quadratic program, referred to as the cbf-clf quadratic program. nevertheless, when using the cbf-clf quadratic program to perform motion planning, it may not be possible to find feasible solutions since the redundant unsafe area due to obstacles is excessively large. to tackle this problem, this paper proposes an approach that exploits the idea of dbscan clustering [18] to find the mee for the cbf-clf quadratic program, which is called the dbscan-mee-cbf in this paper. the proposed dbscanmee-cbf approach can reduce the size of the redundant unsafe area of obstacles while ensuring that the mobile robot can successfully avoid obstacles. compared with the original cbf-clf quadratic program, the moving space of the mobile robot, as well as the chance of finding feasible solutions, becomes larger for the proposed dbscan-mee-cbf approach. in addition, the trajectory planned by the proposed dbscan-mee-cbf is shorter. the relationship and comparison of the existing literature are shown in table 1. advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 360 table 1 the relationship and comparison of the literature method key concept advantages disadvantages references potential field uses attractive and repulsive forces to navigate obstacles easy to implement; realtime responsiveness may get stuck in a local minimum [2, 6] vector field histogram (vfh) a bar chart can represent the traveling cost in different directions. the higher the bar, the greater the cost of moving in that direction, indicating a lower likelihood of passage. efficient obstacle detection; fast computation the performance is not good when the robot encounters a dead end and needs a sharp turn. [13] vfh* combines vfh with a* algorithm to address deadend issues improved pathfinding in complex environments still susceptible to local minima [14] rapidly-exploring random tree (rrt) constructs a tree to find feasible paths from start to goal can handle complex environments requires re-planning if new obstacles appear [15] traditional cbf-clf quadratic program uses control barrier function (cbf) for safety and control lyapunov function (clf) for control ensures safety constraints; robust control it needs to define unsafe regions. if the unsafe region is too large, the space available for the robot to move will be limited. [16-17, 1920] dbscan-mee-cbf uses dbscan clustering to refine cbf-clf safety constraints reduces the size of redundant, unsafe areas; improves feasible solutions requires additional computation for clustering this study 3. brief review of cbf and cbf-clf quadratic programming in safety-critical systems, the system states must remain within the set defined by the safety constraint. one effective means for dealing with the abovementioned problem is to ensure that the system possesses the property of set invariance using cbf. cbf has been widely applied in safety-critical control tasks, which ensure the trajectories of an agv remain within the safe regions. in addition, clf provides a framework to let agv move from the initial position to the final destination. the combination of cbfs and clfs has been effectively used in quadratic programming [16-17, 19-20], allowing the system to stay in safe regions while moving from the initial position to the final destination. consider a nonlinear control-affine system, where the system dynamics are a linear combination of the system state and control input. the system dynamics can be expressed as: ( ) ( )= +ɺx f x g x u (1) where ��∙�: ℝ� → ℝ� and �∙�: ℝ� → ℝ�. 3.1. control barrier function (cbf) the concept of the cbf is similar to that of the clf. the goal of cbf is to ensure that the system states remain within the set defined by the safety constraints. namely, the system possesses the property of set invariance. consider a dynamical system described by eq. (1), where ��∙�, �∙� are local lipschitz continuous. according to the definition given in xu [15], given a set � defined by a continuously differentiable function ℎ���: ℝ� → ℝ as described by: { } { } { } : ( ) 0 : ( ) 0 ( ) : ( ) 0 = ∈ ≥ ∂ = ∈ = = ∈ > ℝ ℝ ℝ n n n c x h x c x h x int c x h x (2) where ��, ������ represents the set boundary and the interior of the set, respectively. advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 361 if there exists an extended class k function ��∙� such that the system satisfies a certain inequality, ( )( ) ( ) ( ) 0α+ + ≥gfl h x l h x u h x (3) then, this ℎ��� is called the zeroing cbf. based on this definition, a control law can be derived to ensure that the set � possesses the property of set invariance. the control law is expressed as: ( ){ }: ( ) ( ) ( ) 0α= ∈ + + ≥ zcbf gfk u u l h x l h x u h x (4) 3.2. cbf-clf quadratic program if the control system of a mobile robot only contains a clf, then it can control the mobile robot moving toward the destination. however, the mobile robot cannot avoid obstacles. in contrast, if the control system of a mobile robot only contains a cbf, then the mobile robot can avoid obstacles but cannot control the mobile robot to reach its destination. one way to overcome this difficulty is by using the clf as the control scheme while the cbf is used as a safety filter to ensure the safety of the mobile robot. to combine clf and cbf, the clf and cbf constraints can be reformulated as a quadratic program. the quadratic program is expressed as: ( ) 2 , 1 min 2 . ( ) ( ) ( ) ( ) ( ) ( ) 0 δ δ δ α ∈ + + + + ≤ + + ≥ t uu gf gf u hu fu p s t l v x l v x u cv x l h x l h x u h x (5) where � ∈ ℝ��� is a positive definite matrix, � ∈ ℝ� and � � 0. to prevent a situation wherein the constraints are too strict for feasible solutions, a relaxed term δ is added to the inequality for the clf to relax the constraint. 4. proposed methodology–dbscan and mee in this paper, the mobile robot is equipped with a lidar. the depth detected by the lidar for each angle ����� is denoted as !���� . each pair of depth and angle (polar) coordinates can be converted into its corresponding cartesian coordinates. the conversion is expressed as: ( ) ( ) [ ] ,lidar ,lidar ,lidar ,lidar cos , for 0, 2 sin θ π θ  = ∈ = i i i i i i x d i y d (6) note that these coordinates do not contain the information about the obstacles. this paper utilizes the dbscan approach [14] to perform clustering for the data points detected by the lidar. in particular, the dbscan approach performs clustering based on the density of the detected data points. in the dbscan approach, the data points are categorized into three classes— kernel points, boundary points, and noise points. two parameters ∈ and ��"�_$%"�&' are used to categorize a given data point. if ( ) *, ��"�+,-./0 ) 4, then point a is a kernel point, point b is a boundary point, and point c is a noise point (fig. 1). fig. 1 illustration of kernel points, boundary points, and noise points advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 362 for any given data point, define a circle with a radius, and its center is at this given data point. if the number of data points inside the defined circle is larger than ��"�_$%"�&', then this given data point belongs to the class of kernel points. any data points that are not kernel points but are located inside a circle defined by any kernel points are called boundary points. for any data points that are neither kernel points nor boundary points, they are called noise points. for a kernel point p, all the data points that are located within the distance (radius) ∈ of p are called p reachability. for a kernel point p, if both data points 23, 24 are p reachability, then data points 23, 24 possess connectedness. as a result, one can define that any two data points inside the same cluster possess connectedness. namely, if data point q and data point p possess connectedness, they must be in the same cluster. through the above clustering process, one can obtain the clustering results after several iterations. based on the clustering results of dbscan, the environment can be divided into several smaller regions containing obstacles. in the proposed obstacle avoidance algorithm, for each obstacle, an ellipse is used to enclose the obstacle and will be used to define the safety set of cbf. firstly, find the minimum convex hull that encloses all the data points belonging to the obstacle, and the average ��56� ) 7��56� , 9�56�: of the data points enclosed by the convex hull is chosen as the center of the ellipse. then, compute the covariance matrix σ ∈ ℝ4. since this covariance matrix is symmetric, its eigenvectors are orthogonal to each other. based on the eigenvalue <�6= with the largest modulus and its corresponding eigenvector >�6=, one can compute the length a and the orientation >�6?%@ for the long axis of the ellipse. similarly, according to the eigenvalue <�"� with the smallest modulus and its corresponding eigenvector >�"� , one can compute length b and orientation >�"�%@ for the short axis of the ellipse. as a result, one can find the mee as described by: ( ) ( ) 2 2 2 2 'cos( ) 'sin( ) 'cos( ) 'sin( ) 1 0 φ φ φ φ+ − + − = x y y x a b (7) where �a ) � b ��56� , 9a ) 9 b 9�56� , c ) d1.5<�6= , h ) d1.5<�"� , i ) �c�j3kl�6?%@,m l�6?%@,=⁄ o; l�6?%@,=, l�6?%@,m represent the x components and the y components of l�6?%@ , respectively, and the flowchart of the proposed approach is shown in fig. 2. fig. 2 flowchart of the proposed approach 5. simulation and experimental results to validate the effectiveness of the proposed dbscan-mee-cbf approach, both simulation and real-world experiments were conducted. the results from both evaluations demonstrate that the proposed approach successfully reduces the redundant unsafe area and improves the feasibility of motion planning. the details of these evaluations are presented in the following sections. advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 363 5.1. simulation turtlebot3 burger is used as the experimental platform in this paper. the state vector is denoted as � ) 7p, q, �:r ∈ ℝs, where x and y are the cartesian coordinates of the turtlebot3 burger and � is its orientation. the state equation is given as: ( ) ( ) cos 0 sin 0 0 1 θ θ ω θ            = = +               ɺ ɺɺ ɺ x v x y v (8) in the simulation, the translation velocity command v is a constant, while the angular velocity command t is time-varying. 5.1.1. the original cbf-clf obstacle avoidance method in the simulation, the initial state �u ) 7pu, qu, �u:r ) 70.0,0.0,0.0:r , the goal state (i.e., destination) is � %6v ) wp %6v , q %6v , � %6vx r ) 7b1.2,1.2,0.0:r, where the units of x and y are meters (m), and the unit for � is radian (rad). to verify the effectiveness of the cbf obstacle avoidance method, the continuously differentiable function ℎ��� is constructed to include the square of the distance, the derivative of the square of the distance, and the square of the safety distance. ( ) ( ) ( ) ( ) 2 2 2( ) 2 cos( ) 2 sin( )θ θ= − + − − + − + −obs obs safe obs obsh x x x y y d v x x v y y (9) where x, y, and � are system states; p%z', q%z' are the coordinates of the center of the obstacle; and !'6[5 is the pre-defined safety distance. in addition, one can use the clf to ensure that the system state converges to the goal state. the clf is defined as: ( ) ( ) 2 2 ( ) = − + −goal goalv x x x y y (10) reformulating the above cbf and clf yields a quadratic program. ( ) ( ) 2 1 2 , 1 min 2 . ( ) ( ) ( ) ( ) ( ) ( ) 0 δ δ δ − − + + + ≤ + + ≥ t ref ref u gf gf u u h u u p s t l v x l v x u c v x l h x l h x u c h x (11) the environment used in the simulation is illustrated in fig. 3. three rectangular obstacles consist of many detected data points. in the original cbf-clf quadratic program, circles are used to construct the model for obstacles. fig. 4 shows the simulation results for the original cbf-clf quadratic program. clearly, the new trajectory generated by the original cbfclf quadratic program can avoid obstacles and reach the goal state safely. in addition, the values of cbf for three obstacles shown in fig. 5(a) are all positive, indicating that all the system states are in the safety set. in addition, the value of clf shown in fig. 5(b) converges exponentially. fig. 6(a) shows the clustering results of the detected data points using the dbscan method. the mee for these three obstacles obtained using eq. (7) is shown in fig. 6(b). based on the obtained mee, one can define the cbf with a new ℎ���. it is given by: ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 2 2 2 2 2 cos( ) sin( ) sin( ) cos( ) ( ) 2 cos( ) sin( ) cos( ) cos( ) sin( ) sin( ) 2 sin( ) cos( ) cos( ) sin( ) sin φ φ φ φ φ φ θ φ θ φ φ φ θ φ    − + − − − + −   = + + +  − + − + + +  − − + − − + + obs obs obs obs safe safe obs obs safe obs obs x x y y x x y y h x a d b d x x y y v v a d x x y y v v( ) ( ) 2 ( ) cos( ) 1 θ φ − + safeb d (12) advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 364 fig. 3 three rectangular obstacles were used in the simulation fig. 4 simulation results of the original cbf-clf quadratic program (a) value of cbf (b) value of clf fig. 5 simulation results of the original cbf-clf quadratic program (a) results of data point clustering using dbscan (b) mee obtained from eq. (7) fig. 6 results of dbscan clustering and mee 5.1.2. the proposed dbscan-mee-cbf obstacle avoidance method fig. 7 shows the simulation results for the proposed dbscan-mee-cbf obstacle avoidance method. the new trajectory can avoid obstacles and reach the goal state safely. moreover, compared with the circles used to model the obstacles in the original cbf-clf quadratic program, the ellipses used to model the obstacles in the proposed method fit more closely with the shape of the obstacle. in addition, the values of cbf for the three obstacles shown in fig. 8(a) are all positive, indicating that all the system states are within the safety set. in addition, the value of clf shown in fig. 8(b) converges exponentially. advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 365 fig. 7 obstacle avoidance in the x-y plane using dbscan-mee-cbf (a) value of cbf (b) value of clf fig. 8 dbscan-mee-cbf obstacle avoidance 5.2. experimental results in the experiment, python is used to solve the quadratic program, and ros is used to broadcast the translation velocity command and rotational velocity command to the turtlebot3 burger. in addition, for safety concerns, an additional 1.5centimeter distance will be added to the obstacle models for all methods tested in the experiment. 5.2.1. the original cbf-clf quadratic program obstacle avoidance method in this experiment, the original cbf-clf quadratic program is used to avoid obstacles. fig. 9 shows the image sequences of the turtlebot moving from the starting point (fig. 9(a)) to the destination point (fig. 9(b)). fig. 10 shows the new trajectory generated by the original cbf-clf quadratic program obstacle avoidance method. the new trajectory can successfully avoid obstacles and reach the goal state safely. the values of cbf for three obstacles shown in fig. 11(a) are all positive, indicating that all the system states are in the safety set. in addition, the value of clf shown in fig. 11(b) converges exponentially. (a) starting point of the turtlebot (b) destination point of the turtlebot fig. 9 comparison of turtlebot trajectories: original cbf-clf vs. proposed dbscan-mee-cbf advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 366 fig. 10 x-y plane trajectory using the original cbf-clf quadratic program (a) value of cbf (b) value of clf fig. 11 experimental results of the original cbf-clf quadratic program 5.2.2. the proposed dbscan-mee-cbf obstacle avoidance method in this experiment, the proposed dbscan-mee-cbf obstacle avoidance method is used to avoid obstacles. fig. 12 shows the new trajectory generated by the proposed dbscan-mee-cbf obstacle avoidance method. unlike enclosing circles, which are used in fig. 10, enclosing ellipses are adopted in fig. 12. as a result, the size of the unsafe area is reduced, and the new trajectory can successfully avoid obstacles and reach the goal state safely. the values of cbf for three obstacles shown in fig. 13(a) are all positive, indicating that all the system states are within the safety set. in addition, the value of clf shown in fig. 13(b) converges exponentially. fig. 12 x-y plane trajectory using the proposed dbscan-mee-cbf approach advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 367 (a) value of cbf (b) value of clf fig. 13 experimental results of the proposed dbscan-mee-cbf obstacle avoidance method 5.2.3. comparison of experimental results as indicated by table 2, the actual curve length for the original cbf-clf quadratic program is longer than the actual curve length for the proposed dbscan-mee-cbf obstacle avoidance method. table 3 shows a comparison of the area of the enclosing circle used in the original cbf-clf quadratic program and the area of the enclosing ellipse used in the proposed dbscan-mee-cbf obstacle avoidance method without considering the extra safety distance. table 4 shows a comparison of the area of the enclosing circle used in the original cbf-clf quadratic program and the area of the enclosing ellipse used in the proposed dbscan-mee-cbf obstacle avoidance method by considering the extra safety distance. table 2 actual curve length method length (m) original cbf-clf quadratic program 1.95962927 proposed dbscan-mee-cbf obstacle avoidance method 1.923764028 table 3 enclosing area analysis: original cbf-clf vs. proposed dbscan-mee-cbf enclosing circle enclosing ellipse comparison between the enclosing circle and the enclosing ellipse area (m2) area (m2) area difference (m2) percentage of area difference (%) obstacle 1 0.024550164 0.018855005 0.005695159 23.2 obstacle 2 0.129461892 0.125658986 0.003802906 2.937 obstacle 3 0.023942989 0.017592874 0.006350115 26.52 table 4 area comparison between enclosing circle and enclosing ellipse in obstacle avoidance methods enclosing circle enclosing ellipse comparison between the enclosing circle and the enclosing ellipse area (m2) area (m2) area difference (m2) percentage of area difference (%) obstacle 1 0.117506749 0.108311789 0.00919496 7.825 obstacle 2 0.298024045 0.293247445 0.0047766 1.602 obstacle 3 0.116173866 0.105878397 0.010295469 8.86 both table 3 and table 4 indicate that the proposed dbscan-mee-cbf obstacle avoidance method yields a smaller area for enclosing obstacles. namely, the size of the redundant unsafe area of obstacles can be reduced. therefore, the mobile robot can have a larger safe space to move in, so the likelihood of finding a feasible solution will increase. the purpose of the proposed dbscan-mee-cbf method is to provide a safer space for the robot during navigation compared with that obtained advances in technology innovation, vol. 10, no. 4, 2025, pp. 358-369 368 from the conventional enclosing circle approach. additionally, compared with traditional methods [n3], the use of cbf in this paper enables the robot to successfully avoid obstacles while ensuring that it does not enter restricted areas. this makes the approach not only applicable to turtlebot3 but also extendable to other robots. 6. conclusion and future work this paper presented the dbscan-mee-cbf approach, which integrates dbscan clustering with the cbf-clf quadratic program to determine the mee for obstacle representation. this method aimed to reduce the redundant unsafe area in obstacle avoidance. a turtlebot running on ros was used as the simulation and experimental platform to validate the effectiveness of the proposed approach. both simulation and experimental results confirmed that, compared with the original cbf-clf quadratic program, the proposed dbscan-mee-cbf approach can effectively reduce the redundant unsafe area of obstacles, thereby achieving safer and more feasible navigation. the main findings are summarized as follows: (1) the dbscan-mee-cbf approach reduces the redundant unsafe area around obstacles, providing a larger feasible space for navigation. (2) compared with the traditional cbf-clf method, the proposed approach alleviates unnecessary safety constraints and improves path feasibility. (3) both simulation and experimental results validated the effectiveness and practicality of the proposed method for obstacle avoidance. in addition to these conclusions, several directions for future research are highlighted. the method could be extended to handle dynamic obstacles with real-time updates to obstacle boundaries for applications in complex environments. furthermore, integrating reinforcement learning or other ai-driven decision-making techniques with dbscan-mee-cbf could enhance its adaptability, enabling autonomous robots to learn optimal navigation strategies under varying environmental conditions. conflicts of interest the authors declare no conflict of interest. references [1] s. sotnik and v. lyashenko, “modern industrial robotics industry,” international journal of academic engineering research, vol. 6, no. 1, pp. 37-46, 2022. 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[20] h. dai, c. jiang, h. zhang, and a. clark, “verification and synthesis of compatible control lyapunov and control barrier functions,” ieee 63rd conference on decision and control, pp. 8178-8185, 2024. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol.10, no.3, 2025, pp.254-268 optimizing nanofluid minimum quantity lubrication machining of inconel-800 using kriging non-dominated sorting genetic algorithm ii ngoc-chien vu*, huu-that nguyen, xuanphuong dang department of mechanical engineering, nha trang university, nha trang city, vietnam received 27 september 2024; received in revised form 15 december 2024; accepted 18 december 2024 doi: https://doi.org/10.46604/aiti.2024.14339 abstract this study optimizes the machining process of inconel-800 superalloy using nanofluid minimum quantity lubrication (mql) with multi-wall carbon nanotubes (mwcnts) and biodegradable coconut oil. a taguchi design with 27 trials is used to examine the effects of varying nanoparticle concentrations and machining parameters on surface roughness and temperature. the optimized nanofluid mql system improves surface roughness by 26.22%, reduces surface roughness peak-to-valley by 12.06%, and significantly lowers temperature, demonstrating improved quality and thermal management. a kriging model predicts outcomes with high accuracy (r2 > 0.9), and multiobjective optimization using kriging and the non-dominated sorting genetic algorithm ii identifies an optimal balance between surface roughness and temperature. additionally, using coconut oil as the lubricant base in the nanofluid mql system promotes sustainable machining by reducing reliance on conventional lubricants and environmental impact. these findings validate the effectiveness of advanced optimization techniques combined with nanofluid mql for superior sustainable machining of superalloys. keywords: nanofluid, machining optimization, sustainable machining, super-alloy, minimum quantity lubrication (mql) 1. introduction machining is crucial for producing components with precise dimensions and superior surface quality. technological advancements have led to the development of high-strength materials, which pose greater machining challenges. these materials include toughened steels, titanium alloys, superalloys, metal matrix composites, and ceramics. superalloys are widely utilized for high-performance applications due to their exceptional mechanical strength, thermal resistance, and corrosion resistance, as shown in fig. 1 [1-2]; for example, inconel-800, a notable superalloy, is selected for its performance in extreme environments. however, its properties, such as high hardness, heat resistance, and work-hardening tendency pose significant machining challenges, including rapid tool wear, elevated cutting forces, and poor surface finish [3-4]. therefore, the development of environmentally friendly and effective machining methods for these materials is essential [5-6]. minimum quantity lubrication (mql) has emerged as a potential alternative to conventional lubrication techniques in machining. unlike flood cooling, which consumes a significant amount of coolant, mql minimizes the fluid used while ensuring sufficient lubrication and cooling at the cutting area [7-8]. nanofluids, which consist of suspensions of nanoparticles in a base fluid, have improved the effectiveness of mql [9-12]. as previously mentioned, nanofluids exhibit offer boosted thermal conductivity, superior lubricating qualities, and lower friction compared to conventional lubricants [13-14]. coconut oil, renowned for its biodegradability and excellent lubricating characteristics, has received interest as an environmentally acceptable base fluid for nanofluids. the use of coconut oil-based nanofluids in mql not only increases machining performance but also aligns with acceptable standards for sustainable manufacturing [15-16]. * corresponding author. e-mail address: chienvn@ntu.edu.vn advances in technology innovation, vol.10, no.3, 2025, pp.254-268 255 fig. 1 the correlation between mechanical strength and operating temperature for difficult-to-cut alloys [17] despite the advantages of nanofluid mql, optimal performance requires precise selection of nanoparticle concentration and machining parameters. this study employs multi-wall carbon nanotubes (mwcnts) based nanofluids in the mql system for machining inconel-800, aiming to enhance thermal conductivity and lubrication [18-20]. a novel optimization framework integrating the kriging model with non-dominated sorting genetic algorithm ii (nsga-ii) balances surface quality and thermal management. accurate parameter optimization is essential to prevent inadequate lubrication and minimize tool wear, underscoring the need for further research on nanoparticle concentration and cutting parameters in machining superalloys. superalloys, particularly inconel-800, are prized for their high-temperature strength, oxidation resistance, and durability, making them vital for demanding engineering applications [3]. however, these properties also render them difficult to machine. traditional superalloy machining methods often lead to excessive tool wear, high cutting forces, and poor surface quality [5]. advanced machining solutions such as coated tools (physical vapor deposition (pvd), chemical vapor deposition (cvd), atomic layer deposition (ald)), optimized cutting parameters, and innovative cooling systems (e.g., cryogenic and highpressure cooling) have been explored [21-22]. although effective, these technologies can be costly or environmentally challenging, emphasizing the need for more sustainable alternatives such as nanofluid mql. nanofluid mql has transformed machining by incorporating nanoparticles (10–100 nm) into the lubrication fluid, enhancing thermal and frictional performance compared to traditional methods. it improves parameters like surface roughness, cutting force, power, energy, temperature, and material removal rate (mrr) [23-24]. nanofluid mql systems utilize lubricants, including vegetable (e.g., coconut, canola), synthetic, and mineral oils, combined with metallic, metal oxide, carbon-based, or ceramic nanoparticles. each component is selected to perform specific lubrication functions tailored to the operational requirements of the mql system [17, 19, 25]. particularly, coconut oil-based nanofluid mql, known for eco-friendly and effective lubrication, provides superior cooling and promotes sustainable machining by reducing the environmental impact of conventional lubricants [15-16]. mwcnt-based nanofluids in mql machining have gained importance for improving surface roughness, cutting temperature, and mrr. the integration of mwcnts into base fluids, particularly coconut oil, has demonstrated substantial potential for enhancing machining efficiency and product quality. numerous studies focusing on optimizing machining parameters using mwcnts nanofluids and highlighting the benefits of incorporating coconut oil into mql systems. for instance, okokpujie et al. reported a surface roughness of 1.16 µm and an mrr of 52.1 mm³/min when machining al8112 using mwcnt-doped nanofluid mql [26]. similarly, ali et al. demonstrated significant improvements in tool life, cutting force, and surface finish when employing mwcnt-based nanofluids in turning inconel 718 under dry, mql, and nanofluid mql conditions, showcasing the lubricant's effectiveness [27]. note: the chart does not show the range of service temperatures, but the range of the maximum temperatures. the temperature axis has a finer scale. ceramics: the chart shows compressive strength; tensile strength is typically 10% of compressive strength. other materials: strength in tension/compression. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 256 optimizing machining configurations is crucial for improving performance, especially with difficult-to-machine materials like superalloys. the effective implementation of nanofluid mql requires an organized framework that incorporates experimental design, mathematical modeling, and multi-objective optimization techniques. these methods balance lubrication, cooling, and cutting parameters, improving challenging machining performance in scenarios. for example, te-ching hsiao et al. utilized a combination of the response surface methodology (rsm) model and nsga-ii optimization, achieving a reduction of up to 20.2% in specific cutting energy and 6.4% in overall energy consumption [28-29]. other models, such as kriging and radial basis function (rbf), have also proven effective in predicting optimal parameter combinations for machining. this study confirms that nanofluids significantly enhance the machining performance of superalloys like inconel-800, utilizing mwcnt-based nanofluids with coconut oil, providing superior thermal conductivity and lubrication over conventional nanoparticles. this eco-friendly approach improves machining efficiency and promotes sustainability. for example, bui et al. demonstrated that optimizing cutting parameters improved surface roughness and mrr when machining skd11 with sio₂ nanofluid [30]. vu et al. reported a 14% reduction in cutting energy during hard milling of aisi h13 steel using al₂o₃ mql nanofluids [28]. similarly, perera and wegala demonstrated that coconut oil-based nanofluids reduced surface roughness by 9.8–73.7% in machining ss400 and aisi 304, with optimal results at 0.3% (w/w) al₂o₃ and graphite concentrations [16]. these findings highlight the benefits of optimizing machining processes with nanofluids, particularly in enhancing surface quality, minimizing cutting zones, and increasing mrr through advanced optimization techniques. furthermore, while traditional optimization methods such as taguchi and rsm primarily focus on single-objective optimization and often assume linear relationships, the kriging-nsga-ii approach adopted in this study captures complex nonlinear interactions and enables multi-objective optimization. this method surpasses conventional techniques by providing a more precise and efficient mechanism of achieving pareto-optimal trade-offs between conflicting objectives, such as surface roughness and cutting temperature. developing and optimizing mwcnt-based nanofluids in coconut oil for milling present significant industrial potential. this study systematically investigates the influence of cutting parameters and nanoparticle concentration on machining performance, seeking to promote sustainable machining processes. integrating nanotechnology into traditional manufacturing enhances productivity, reduces environmental impact, and improves product quality. as the field of nanofluid-assisted machining continues to advance, the findings of this research may serve as an essential reference for future attempts to develop greener and more efficient manufacturing processes. 2. materials and methods the material utilized in this study was inconel-800, a superalloy known for its high strength, exceptional corrosion resistance, and tendency for work harden, thereby incurring the challenge to machine. the mechanical properties of inconel-800 are detailed in table 1, while its chemical composition is listed in table 2. the workpiece dimensions were 210 mm in length, 100 mm in width, and 40 mm in height, with a cutting length of 100 mm. table 1 mechanical specifications of inconel-800 temperature0c tensile strength mpa yield strength mpa elongation % r.a. % 27 448549 172226 3048 76 table 2 chemical composition (weight percent) of inconel-800 element ni cr fe c al ti ti+ al mn % weight 30.0-35.0 19.0-23.0 46.99 0.1 max 0.5 0.15-0.60 1.01 1.5 max advances in technology innovation, vol.10, no.3, 2025, pp.254-268 257 the slot milling operations were conducted using a computer numerical control (cnc) vertical milling machine (vcm2216 xv). a sandvik coromill r390 square shoulder milling cutter, with a diameter of 16 mm and equipped with two flutes, was employed as the cutting tool. the tool inserts were sandvik r390-11 t3, featuring a nose radius of 0.8 mm, as shown in fig. 2. the cutting parameters were selected based on both the recommendations provided by the cutting tool manufacturer and the operators' experience. fig. 2 tool used in experimental cutting coconut oil was utilized as the base fluid in the nanofluid mql system, and mwcnts were incorporated as nanoparticle additives. mwcnts were selected for their superior thermal conductivity (300 w/m·k), which enhances heat dissipation during the machining process. the mwcnts, with an average particle size of less than 30 nm, were dispersed into coconut oil at varying concentrations (0.5%, 1.0%, and 1.5% by weight). the concentration ranges for mwcnts were determined by integrating previous studies [25, 28], initial experimental trials, and the aim of enhancing machining performance while maintaining environmental sustainability. the nanoparticle dispersion process begins with the exact weighing of mwcnts using a kern plj 2000-3a precision balance, after which the nanoparticles were combined with coconut oil. to ensure uniform dispersion, the mixture was continuously stirred for 48 hours using a magnetic stirrer (ezdo ms-11c), thereby attaining homogeneity before its application in the experiments. the nanofluid mql system was configured to maintain an oil flow rate of 120 ml/h and an air pressure of 3.5 kg/cm², with the nozzle positioned 20 mm from the cutting zone at a 60° angle. this arrangement was consistently followed throughout the evaluation to maintain optimal lubrication and cooling conditions during the experiments. a systematic design of experiments (doe) approach, including the orthogonal array method, was employed to investigate the influence of machining parameters and nanoparticle concentrations. a total of 27 experiments were undertaken, equating to an l9 orthogonal array, with each factor examined at three different levels. the factors considered included the cutting parameters such as cutting velocity (vc) (95, 125, and 155 m/min), feed per tooth (fz) (0.03, 0.06, and 0.09 mm/tooth), depth of cut (ap) (0.3, 0.7, and 1.1 mm), and nanoparticle concentration (% nano) (0.5%, 1%, and 1.5%). these parameter levels were carefully selected based on previous studies, practical expertise, personal knowledge, and recommendations from cutting tool manufacturers. as shown in fig. 3, the experimental setup comprises slot milling operations on superalloy inconel-800 workpieces under these established machining parameters. the nanofluid, delivered through the mql system, supplied constant lubrication and cooling during each test, enabling an accurate evaluation of the machining outputs under controlled conditions. surface roughness (arithmetic mean deviation, ra, peak-to-valley, rz, and root mean square deviation, rq) was measured using a mitutoyo sj-301 portable surface roughness tester. three measurements were conducted for each machined surface, and the average surface roughness ((ra, rz, rq) value was calculated. cutting temperatures (tc) were monitored using a thermal camera (uni-t uti260b), which was positioned near the cutting zone to record the maximum temperature during machining. a kriging model was developed to model the relationship between the cutting parameters vc, fz, ap, and % nano and output responses (surface roughness and cutting temperature). this model was used to predict the responses based on the experimental data collected from the orthogonal array design, while the nsga-ii algorithm was employed to optimize cutting parameters. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 258 the nsga-ii algorithm simultaneously minimizes surface roughness and cutting temperature, ensuring an optimal balance between these conflicting objectives. isight software was utilized to integrate the kriging model with the nsga-ii algorithm facilitating the optimization process. isight enabled the efficient coupling of the predictive model with the optimization algorithm, providing a robust framework for multi-objective optimization. this integration allowed for precise and reliable optimization of machining parameters, ensuring the best possible trade-off between surface quality and thermal control. the complete methodology is visually summarized in fig. 4, which comprehensively illustrates the process flow, including the implementation of the kriging model for accurate response prediction, followed by the optimization process using the nsga-ii algorithm within the isight framework. fig. 3 the structured approach to modeling and optimizing machining parameters fig. 4 the methodology employed in the current work 3. results and discussion this study systematically collected and analyzed experimental data to comprehensively investigate the relationship between process parameters and surface roughness metrics—specifically, ra, rz, rq, and cutting temperature. table 3 presents the results of 27 experiments conducted using the taguchi orthogonal array method. the kriging model was employed to estimate the impact of input parameters on technical responses, as detailed in the materials and methods section, based on the previously provided data. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 259 table 3 design of experiment and outcome of investigation input parameters output parameters no. ap (mm) fz (mm/tooth) vc (m/min) % nano (%) ra (µm) rz (µm) rq (µm) tc (00) 1 0.3 0.03 95 0.5 0.32 2.00 0.39 82.2 2 0.3 0.03 125 1.0 0.23 1.65 0.27 87.5 3 0.3 0.03 155 1.5 0.42 2.80 0.53 81.1 4 0.3 0.06 125 0.5 0.35 2.38 0.44 83.2 5 0.3 0.06 155 1.0 0.26 1.65 0.32 88.3 6 0.3 0.06 95 1.5 0.53 3.25 0.66 90.2 7 0.3 0.09 155 0.5 0.45 2.93 0.56 81.8 8 0.3 0.09 95 1.0 0.29 1.78 0.36 97.2 9 0.3 0.09 125 1.5 0.64 3.71 0.78 100.5 10 0.7 0.03 125 0.5 0.27 1.76 0.37 78.7 11 0.7 0.03 155 1.0 0.32 1.97 0.40 146.6 12 0.7 0.03 95 1.5 0.30 2.13 0.37 146.1 13 0.7 0.06 155 0.5 0.36 2.31 0.47 95.1 14 0.7 0.06 95 1.0 0.37 2.45 0.45 109.3 15 0.7 0.06 125 1.5 0.49 3.05 0.60 150.2 16 0.7 0.09 95 0.5 0.39 2.68 0.48 117.6 17 0.7 0.09 125 1.0 0.81 4.30 0.96 107.3 18 0.7 0.09 155 1.5 0.59 3.27 0.71 143.3 19 1.1 0.03 155 0.5 0.36 2.17 0.45 141.2 20 1.1 0.03 95 1.0 0.32 2.31 0.41 129.9 21 1.1 0.03 125 1.5 0.34 2.25 0.42 182 22 1.1 0.06 95 0.5 0.42 3.01 0.54 156.1 23 1.1 0.06 125 1.0 0.79 4.54 0.97 187.1 24 1.1 0.06 155 1.5 0.55 2.87 0.67 183.7 25 1.1 0.09 125 0.5 0.52 3.00 0.64 125.8 26 1.1 0.09 155 1.0 0.81 4.70 1.00 160.5 27 1.1 0.09 95 1.5 0.58 3.35 0.71 176.4 the reliability and accuracy of the kriging model in representing the experimental data are substantiated by the coefficient of determination (r²) derived from regression analysis. specifically, the r² values for the surface roughness parameters ra, rz, and rq, as well as the tc, were determined to be 0.9215, 0.9638, 0.9379, and 0.9504, respectively. as shown in fig. 5, these values are all above the criterion of 0.9,indicating a strong correlation between the predicted and observed data. the excellent r² values emphasize the precision and confidence of the kriging model in precisely representing the experimental data. therefore, based on these results, it can be inferred that the kriging model is not only adequate but alsohelpful in capturing the complex relationship between the process variables and the related technical responses. this is further evidenced by previous studies that utilized the kriging surrogate model to analyze the relationships between various cutting parameters and machining process outcomes [28]. surface roughness plays a critical role in the performance of machined components, particularly in high-stress applications. as shown in fig. 6(a)-(c) the direct correlation between the depth of cut and feed per tooth with surface roughness (ra, rz, rq). an in-depth analysis indicates that a higher depth of cut increases chip load and tool-workpiece contact, leading to more significant material deformation and rougher surfaces. similarly, higher feed rates induce more aggressive cutting forces and vibrations, which exacerbate surface irregularities. on the other hand, cutting speed exhibited an inverse trend. as shown in fig. 6(d), at optimal cutting speeds, the heat generated during machining slightly softens the material, reducing cutting forces and producing a finer surface finish. however, excessive cutting speeds may led to tool wear and thermal damage, as evidenced by the increased in surface roughness observed advances in technology innovation, vol.10, no.3, 2025, pp.254-268 260 beyond the optimal speed range. the nanofluid mql system, enhanced by nanoparticles, plays a crucial role by reducing friction and improving lubrication [3]. specifically, the lubricant forms a thin and stable film at the tool-workpiece interface, effectively minimizing friction and mitigating material adhesion. furthermore, the overall thermal management provided by the nanofluid mql system helps maintain surface smoothness at higher cutting speeds, as shown in fig. 6(e), by dissipating heat more efficiently and preventing excessive temperature rise. fig. 5 r² values (>0.9) confirm the kriging model's accuracy in representing experimental data for ra, rz, rq, and tc. previous studies have demonstrated significant improvements the enhancement of surface roughness attained via nanofluid mql, which may be ascribed to four primary nanoparticle mechanisms: rolling, self-repairing, tribo-film formation, and polishing, as shown in fig. 7. rolling diminishes friction by functioning as miniature ball bearings, thereby facilitating tool movement smoothness. self-repairing fills the surface with minute cavities and layers, creating a protective coating to reduce adhesion. polishing further enhances the surface, yielding a significantly smoother finish and illustrating the beneficial effect of nanofluid mql for boosting machining quality [19]. therefore, the synergistic effect of these mechanisms contributes to the superior performance of nanofluid mql systems compared to conventional lubrication methods. thus, the kriging model demonstrates that an optimized nanofluid mql system significantly reduces ra, rz, and rq, particularly at high cutting speeds, highlighting the advantages of nanofluid mql in achieving superior surface finishes when milling inconel-800 superalloy. cutting temperature significantly affects both tool wear and workpiece integrity during machining. as shown in fig. 6(f), the relationship between cutting temperature and machining parameters, revealing that depth of cut and feed per tooth are critical factors contributing to elevated cutting temperatures. as these parameters increase, they contribute to higher material removal rates and greater friction at the tool-workpiece interface, resulting in amplified temperatures. this temperature rise can accelerate tool wear and deteriorate the microstructure of the workpiece, leading to diminished mechanical properties and r2 = 96.38 % r2 = 92.15 % r2 = 93.79 % r2 = 95.04 % advances in technology innovation, vol.10, no.3, 2025, pp.254-268 261 potential failure in high-stress applications. this observation corresponds with fundamental cutting principles, wherein increased cutting forces result in a corresponding rise in temperature, as demonstrated in several previous studies [3, 28]. as shown in fig. 8(a), the overall effect of input parameters on tc, further validating these findings by presenting the global effects of the four input factors (ap, fz, vc, % nano) on tc. it reveals that fz and ap exhibit the most significant influence on tc. in contrast, % nan oand vc have a minor impact on temperature regulation. although these factors contrinute to the machining process, their influence on tc is relatively low compared to the primary cutting parameters (ap, fz). the nanofluid mql system serves a critical function in cutting temperature management, limiting excessive heat accumulation. by providing efficient cooling and lubrication, the nanofluid mql system extends tool life and preserve workpiece quality, particularly during the milling operations of the inconel-800 superalloy, which is a difficult-to-cut material. however, the optimization of ap, fz remains critical for controlling tc under challenging machining conditions. (a) influence of depth of cut and feed per tooth on ra (b) influence of depth of cut and feed per tooth on rz (c) influence of depth of cut and feed per tooth on rq (d) influence of cutting speed and concentration of nano on ra (e) influence of cutting speed and concentration of nano on rq (f) influence of depth of cut and feed per tooth on tc fig. 6 the effect of variables on surface finish and cutting temperature in summary, an increase in depth of cut and feed per tooth leads to higher surface roughness, whereas greater nanoparticle concentrations and cutting speeds enhance surface quality and reduce cutting temperature. the kriging model highlights the importance of optimizing these parameters to enhance performance when machining inconel-800. the application of nanofluids proves particularly effective in improving surface finish and controlling temperature during high-speed milling. this finding corroborates previous studies and aligns with established cutting principles in machining processes [28]. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 262 fig. 7 four fundamental nanoparticle mechanisms: rolling, tribo-film, polishing, and self-repairing the analysis of fig. 8(b)-(d) highlights the predominant effect of fz on surface roughness parameters (ra, rz, rq). among all responses, fz has the greatest inpact, aligning with established principles suggesting that elevated feed rates enhance material deformation and interaction at the tool-workpiece interface, leading to rougher surfaces. (a) global effects of input parameters on tc (b) global effects of input parameters on ra (c) global effects of input parameters on rz (d) global effects of input parameters on rq fig. 8 the global effect of input parameters on response parameters in relationship with ra, fig. 8(b) indicates that fz is the primary determinant, whereas vc and nanoparticle % nano exert negligible influence. this signifies that feed rate optimization is essential for enhancing surface finish. in fig. 8(c), rz demonstrates that fz is the primary factor, with a slight influence from nanoparticle concentration, whereas ap exerts a negligible effect. this suggests that elevated feed rates result in heightened surface limitations. fig. 8(d) substantiates the dominant role of fz in relation to rq, with insignificant contributions from vc. this finding emphasizes the vulnerability of surface texture, highlighting the necessity for meticulous feed control during machining to maintain surface quality. in conclusion, fz is the most important criterion in reducing surface roughness, whereas % nano provides supplementary, though lesser, improvements. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 263 fig. 9 scatter plot of multi-objective optimization for ra and tc using kriging and nsga-ii (scenario 1) in machining, surface quality is typically assessed using ra and rz; however, these parameters are generally not used simultaneously in the same case. this study proposes two scenarios for multi-objective optimization in the machining of inconel-800 using cmwnts nanofluid mql conditions, with the objective of enhancing the performance of machining difficult materials. in the first scenario, the objectives are to minimize both ra and tc, despite their conflicting nature. higher cutting speeds tend to reduce ra but increase tc, while lower tc may raise ra due to decreased cutting efficiency. therefore, balancing the simultaneous minimization of these two out parameters is crucial for optimal performance. the kriging model combined with the nsga-ii algorithm was applied as a multi-objective optimization method to achieve the optimal values for ra and rz. the parameters of the nsga-ii algorithm used are as follows: crossover distribution index = 10.0, crossover probability = 0.9, mutation distribution index = 20.0, number of generations = 100, and population size = 16. the starting design points are: 0.5 % 1.5nano  (1) 95.0 155.0cv  (2) 0.3 1.1pa  (3) 0.03 0.09zf  (4) fig. 9 displays a scatter plot illustrating the multi-objective optimization for ra and tc using kriging and nsga-ii. feasible solutions are depicted as individual points. the pareto front, represented by a distinct curve (also referred to as the pareto line), shows the optimal trade-offs between ra and tc. each point on the pareto front signifies the best possible compromise between these two objectives. for instance, if the operator or engineer aims to maintain tc at 80°c, the pareto front suggests a ra value of approximately 0.284 µm. without referencing the pareto front, one might mistakenly choose a ra value of 0.3231 µm (as indicated by a point in fig. 9), which is suboptimal by around 26.22% (with the variation of δ ra = 0.3231 – 0.2384 = 0.0847). these optimal results demonstrate a notable improvement in surface quality compared to the study by hsiao et al. (approximately 16.7% versus 26.22%) when machining the same steel grade and nanoparticle type. this study utilized commercially available ct232 mineral-based cutting oil [3]. thus, the pareto front derived from the kriging and nsga-ii combination not only serves as a robust decision-making tool but also enables precise tailoring of the machining process to achieve optimal results, enhancing efficiency and reducing waste when milling inconel-800 superalloy. based on the specific machining requirements, the operator or engineer can select the point that best aligns with their objectives and adjust cutting parameters accordingly. the multi-objective optimization process history is depicted in fig. 10. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 264 (a) history of the optimization process refining ra trade-offs (b) history of the optimization process refining tc trade-offs fig. 10 history of the optimization process depicting the gradual refinement of trade-offs between ra and tc in the second scenario, the optimization is employed the same methodology as before: integrating the kriging model and the nsga-ii approach, while maintaining constant input parameters and a dual objective of minimizing both ra and tc aiming to construct a pareto front that maps rz against tc. similar to the first scenario, fig. 11 indicates an inverse relationship between rz and tc. when the operator maintains tc at approximately 80°c, the pareto front reveals two potential solutions: an optimized rz of 1.4909 µm and a feasible but suboptimal rz of 1.6955 µm, with a difference of δ rz = 0.2046 µm. this improvement of approximately 12.06% highlights how nsga-ii optimization combined with the kriging model significantly enhances surface texture without compromising tc. fig. 11 scatter plot of multi-objective optimization rz and tc using kriging and nsga-ii (scenario 2) the trade-off between optimizing rz and tc presents a conflict, accentuating the pareto front for selecting a balanced solution. if minimizing rz is the primary objective, a higher tc may need to be accommodated. conversely, if tc is prioritized to extend tool life or prevent thermal damage, careful control of tc is crucial. this pareto-based optimization enables decisionmakers to choose the best compromise based on specific needs, whether for to achieve superior surface finish or to maintain a safe and controlled cutting temperature. fig. 12 illustrates the optimization history, depicting the algorithm’s convergence and the gradual refinement of trade-offs between rz and tc. this incremental improvement demonstrates the algorithm's efficiency in identifying the optimal balance, reducing both rz and tc over successive iterations to achieve improved machining performance. the analysis of the experimental results reveals that machining inconel-800 with mwcnt nanofluid mql led to substantial improvements in surface finish and cutting temperature. specifically, ra values decreased by up to 26.22%, rz showed a 12.06% improvement. these results strongly support the hypothesis that integrating mwcnt nanoparticles into the advances in technology innovation, vol.10, no.3, 2025, pp.254-268 265 mql coolant system is crucial in reducing surface roughness. moreover, the cutting temperature (tc) increased with higher feed rates and depths of cut, which is consistent with fundamental machining principles. however, the nanofluid mql system effectively moderated the temperature rise, facilitating a more stable and controlled machining environment. lowering cutting temperature is particularly critical in high-performance machining, as it prolongs tool life and preserves material integrity, especially when machining challenging materials such as inconel-800. (a) evolution of the optimization process fine-tuning rz trade-offs (b) evolution of the optimization process fine-tuning tc trade-offs fig. 12 history of the optimization process depicting the gradual refinement of trade-offs between rz and tc the kriging model analysis provided valuable insights into the influence of process parameters, underscoring the pivotal roles of fz and ap in regulating surface roughness and cutting temperature. the model’s high predictive accuracy (with r² values exceeding 0.9) further reinforces the reliability of these findings. this highlights the potential of the kriging model as an effective tool for optimizing machining processes, especially in complex operations such as milling inconel-800 superalloy. although the nanoparticle concentration (mwcnt) was of secondary importance relative to cutting speed and feed per tooth, its contribution to improving surface finish and reducing cutting temperature remains significant. the results suggest that future research should focus on optimizing nanoparticle concentrations to identify the ideal balance between surface quality and thermal management. 4. conclusions the study aims to optimize the machining process of inconel-800 superalloy by utilizing nanofluid mql, enhanced with biodegradable coconut oil and mwcnts, to achieve improved surface texture and lower cutting temperature. a systematic design of experiments (doe) was conducted to highlight the role of nanofluid mql in sustainable machining, addressing the challenges of processing inconel-800 superalloy and promoting sustainable practices in modern manufacturing. the key findings are summarized as follows: (1) utilizing nanofluid mql with mwcnts in coconut oil effectively improves surface texture, lowers cutting temperature, and enhances lubrication and cooling efficiency in machining inconel-800 superalloy. (2) the kriging model is highly effective in capturing the complex relationship between cutting parameters (ap, fz, vc, % nano) and response parameters (ra, rz, rq, and tc), achieving a high level of accuracy (r² > 0.9). (3) the combination of the kriging model with the nsga-ii algorithm efficiently balances conflicting multi-objective functions related to machining performance and efficiency. the pareto front facilitates informed decision-making, allowing operators and engineers to identify optimal solutions tailored to their specific requirements. (4) in the first scenario, a 26.22% improvement in ra was achieved when minimizing ra at a constant tc. similarly, in the second scenario, approximately a 12.06% improvement in rz was observed, showcasing the effectiveness of nanofluid mql in sustainable machining. advances in technology innovation, vol.10, no.3, 2025, pp.254-268 266 (5) the study emphasizes the potential of sustainable manufacturing when employing nanofluid mql with environmentally friendly coconut oil, suggesting its applicability in industrial manufacturing. it provides deeper insights into the machining inconel-800 and similar materials. future research should investigate the long-term effects of mwcnt-enhanced nanofluid mql on tool life and explore its integration into manufacturing processes to minimize reliance on conventional lubricants while maintaining machining efficiency. additionally, applying the optimized nanofluid mql system to other challenging materials, such as titanium alloys and harder ceramics, and incorporating the kriging-nsga-ii optimization method into real-time adaptive machining systems will enhance scalability and industrial applicability. acknowledgment the paper is sponsored by nha trang university under project no. tr2023-13-12. nomenclature symbol description symbol description mql minimum quantity lubrication ap depth of cut mwcnts multi-wall carbon nanotubes tc cutting temperature rsm response surface methodology ra surface roughness (arithmetic mean deviation) doe design of experiments rz surface roughness (maximum height ) r² coefficient of determination rq surface roughness (root mean square deviation) rbf radial basis function mrr material removal rate fz feed per tooth % nano nanoparticle concentration vc cutting velocity nsga-ii non-dominated sorting genetic algorithm ii conflicts of interest the authors declare no conflict of interest. references [1] m. ganesh, n. arunkumar, n. e. kumar, and r. sathish, “investigation of surface grinding on inconel under distinct cooling conditions,” materials and manufacturing processes, vol. 38, no. 14, pp. 1823-1836, 2023. 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case study kiyoung lee1, hyunjin park1, seongkwan mark lee2,* 1korea expressway corporation research center, dongtan, republic of korea 2school of liberal studies, kunsan national university, gunsan, republic of korea received 15 november 2024; received in revised form 17 march 2025; accepted 19 march 2025 doi: https://doi.org/10.46604/aiti.2024.14507 abstract this study investigates the operational and safety impacts of introducing exclusive truck lanes on the gyeongbu expressway in south korea, addressing the necessity of such lanes due to the disparities in vehicle weight and performance between trucks and passenger cars. the study focused on the 33.2 km, one-way, four-lane chilgok-mulryu to gimcheon segment, adhering to international installation criteria. using the micro-simulation tool vissim, the rightmost lane was modeled as exclusive for trucks, and traffic operations and safety were analyzed under varying conditions of level of service (los). under los c, the exclusive truck lane reduced the speed standard deviation (a surrogate safety measure) with minimal travel speed reduction. conversely, under los a with low traffic, average travel speed declined, and speed standard deviation increased due to limited truck usage. these findings highlight the need for flexible truck lane management tailored to traffic and road conditions. keywords: exclusive truck lane, simulation, vissim, travel speed, speed standard deviation 1. introduction various nations, such as the united states, canada, and the united kingdom, have adopted truck-only roads and exclusive lanes to mitigate fatal accidents involving trucks and accommodate advancements like truck platooning. delving further into this matter, exclusive truck lanes were implemented by the united states and canada to enhance road safety. conversely, in the united kingdom, the primary objective is alleviating road congestion. ultimately, the rationale behind introducing exclusive truck lanes varies slightly from one country to another. these initiatives have demonstrated effectiveness in enhancing safety and mobility, sparking a growing interest in establishing exclusive lanes for freight vehicles. trucks possess distinctive design features that make them prone to causing severe accidents in collisions with passenger vehicles. moreover, the typically lower speed limits for trucks on expressways than for other vehicles underscore the importance of segregating truck driving lanes whenever possible. the evolution of platooning technology has spurred active discussions on providing dedicated lanes for trucks to leverage this innovation. additionally, the emergence of electric trucks has also led to the design of electric truck-only lanes employing a track concept. a truck-only or truck-exclusive lane is a designated pathway exclusively reserved for trucks, aiming to bolster logistics competitiveness and enhance driving safety. the current environment presents an opportune moment to deliberate on the implementation of exclusive lanes and roads for trucks, aiming to minimize accident damage resulting from mixed vehicle types and elevate the transportation competitiveness of lorries. * corresponding author. e-mail address: marklee@kunsan.ac.kr advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 175 this study aims to identify suitable road segments on korean highways for the implementation of truck-only lanes. subsequently, it utilizes microscopic simulation analysis techniques to assess the effects of introducing these lanes on traffic flow and safety. the investigation focuses on converting the existing rightmost lane into an exclusive lane for trucks and analyzing its operation. the effectiveness of the truck-exclusive lane is being scrutinized using vissim, a microscopic traffic flow analysis program. the comparison involves evaluating average travel speed and its standard deviation with and without the dedicated lane. the standard deviation of average travel speed is an index influencing traffic accidents, as traffic flow stability correlates with the similarity in speed among vehicles. the outcomes of this study aim to offer insights into the implementation of exclusive lanes for freight vehicles, akin to bus-only lanes, by restricting the right-of-way for other cars. the following section delineates international standards for installation, provides examples, and discusses the effects of installing truck-only lanes. additionally, section 3 outlines the methodology employed to simulate the impact of introducing truck-only lanes on specific expressway segments in korea. subsequently, section 4 presents the simulation findings and initiates a discussion. finally, the conclusion underscores the imperative of implementing dedicated truck lanes on korean highways, emphasizing their significance for traffic safety and operational efficiency. 2. international operational practices before evaluating the feasibility of implementing truck-only lanes on korean expressways, an analysis was first conducted on cases in foreign countries where such lanes are already in operation. primarily through the examination of installation standards, operational practices, and their effects, the potential applicability of truck-only lanes in korea was assessed. 2.1. installation criteria according to the transportation association of canada (2014), highway-related truck lanes are classified into five types. these include: 1) physically separated cargo-only lanes from general vehicle lanes on freeways; 2) operationally separated truck lanes on freeways that are not physically separated; 3) truck climbing lanes; 4) truckways that connect cargo terminals to major freight generators; 5) truck bypasses that are installed as detours for trucks in bottleneck areas [1]. the installation standards for truck-only lanes vary across countries, but the primary criteria commonly used are truck traffic volume and total traffic volume. moreover, if the accident rate involving freight vehicles exceeds the national average at a particular location, installing a dedicated freight vehicle lane is advisable. in 2014, the transportation association of canada outlined key factors and standard values for each type of dedicated truck lane. for instance, they recommend that truck-only lane should be considered when the total traffic volume is between 80,000 and 120,000 vehicles/day, the ratio of trucks is between 14 and 30%, the distance from the freight location is 3 km or less, and the number of accidents per million vehicles is 63 or more, or the truck accident rate is higher than the national average. furthermore, if the freight lanes are physically separated, they must have a minimum length of 16 km. if they are not physically separated, there must be a minimum of four lanes in each direction [1]. the georgia department of transportation evaluates the need for exclusive lanes by considering traffic congestion in general lanes, major transportation routes, economic regions, cargo bottleneck areas, and business logistical paths. they do this when truck traffic exceeds 30,000 daily vehicles in both directions. the california department of transportation (caltrans) installs truck lanes based on hourly volumes and the number of trucks. meanwhile, the florida department of transportation (fdot) proposes a truck-only road or lane, considering factors such as proximity to airports, ports, terminals, and railroad facilities, as well as truck ratio, level of service, number of truck accidents, and number of trucks [2]. advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 176 2.2. examples of operations in practice there are various instances of exclusive truck roadways in the united states. some roads, like the i-5 expressway in california (refer to fig. 1(a)), have a lane exclusively for cars that any vehicle can use. still, only high occupancy vehicles (hov) are permitted to use the lane during rush hour. the california i-5 also has two lanes exclusively for trucks. in the cargo-only lane of the i-5 expressway, trucks are allowed to use the rightmost lane if there are three lanes in each direction and the two right lanes if there are four lanes in each direction. however, passenger cars are also allowed to use the dedicated lanes. certain sections of the i-95, i-75, and i-4 highways in florida have specific restrictions on truck lanes, and penalties are imposed for violations to ensure they are used solely for trucks. the dual-dual roadway spanning 33.5 miles, which links new jersey (refer to fig. 1(b)) and delaware in the united states, is managed by using physical structures to segregate the inner lanes for passenger cars and the outer lanes for all vehicles. rotterdam, the netherlands, has multiple truck lanes designed to make cargo handling easier at major ports. the a16 highway has 12 km-long truck lanes at seven different locations, while the a20 highway has approximately two km-long truck lanes. when heading northbound on the a16 expressway (refer to fig. 1(c)), three express lanes are available, but only one is designated for buses and trucks. however, when heading southbound, all lanes are used as general lanes. the queensland government of australia mandates that on the m1 road between brisbane and the gold coast, cargo vehicles weighing 4.5 tons or more are restricted to using only the two shoulder lanes. they can overtake other vehicles but must remain within these designated lanes to minimize interaction with passenger cars [3]. in new zealand, truck priority lanes are designated on highway ramps equipped with traffic lights to facilitate uninterrupted entry for trucks without stopping or losing momentum, particularly on sloped ramps. this initiative is founded on the premise that providing priority lanes for trucks enables them to maintain appropriate speeds on the highway, thereby reducing delays caused by trucks [4]. (a) i-5 (california) (b) dual-dual roadway (new jersey) (c) a16 motorway (netherlands) fig. 1 illustrations of the exclusive truck lane [5] 2.3. operational consequences in 2003, fischer and colleagues conducted a feasibility analysis to assess the viability of constructing truck-only lanes on sr-60 and i-710 roads in california. the study revealed that the presence of such lanes led to an increase in truck demand, while removing these lanes decreased demand. additionally, certain studies have utilized microscopic traffic analysis simulations to examine the impacts of truck-only lanes or lane restrictions [6]. an examination of scenarios using vissim in tennessee and texas revealed that introducing truck lanes had minimal effects on conventional metrics like average speed, the speed differential between cars and trucks, and the overall level of service of the road [7]. however, another study assessing truck-only lanes' safety and operational efficacy via vissim showed improved average speeds on certain highways. nonetheless, some roads experienced adverse outcomes such as heightened lane changes, reduced average travel speeds, and longer queues. this phenomenon was also observed in the analysis [8]. by analyzing the impact of truck-only lanes based on the truck ratio on the gardiner expressway in toronto, canada, using a microscopic simulation tool, it was observed that the effectiveness of truck-only lanes was most pronounced when the truck ratio exceeded 15% of the total vehicle count [9]. advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 177 in 2007, fontaine and colleagues evaluated the operational and safety aspects of virginia's two types of truck lanes. the first road, road 1, is a one-way street with 3-4 lanes, where trucks cannot enter the overtaking lane. according to the study, the annual average daily traffic volume of 10,000 vehicles or less improves safety. however, incidents increase when the traffic volume exceeds a certain level, although the study did not provide specific results for this case. the study examined a two-lane, one-way road where slower trucks below a particular speed were limited to the right-hand lane. implementing these lanes resulted in a 23% reduction in accidents and increased travel speed by 5.5 mph. however, no significant safety outcomes were observed. the study suggested that further investigation was necessary to address the issue of non-truck vehicles using the overtaking lane at low speeds [10]. regarding the incidence of traffic accidents within dedicated truck lanes, research conducted on sh 225 laporte freeway, where such lanes have been in place since 2003, revealed a decrease in accidents from an average of 7.9 occurrences per week to 2.9 occurrences per week following the introduction of these lanes. furthermore, the study confirmed that 90% of passenger car drivers favored truck-only lanes, citing safety concerns [11]. in 2008, kobelo and colleagues investigated the impact of truck-only lanes on accident rates in 128 sections of highways in florida. they developed a model that considered multiple explanatory variables related to accident frequency for each section. the study found a correlation coefficient of 0.3627 between the presence of exclusive lanes for trucks and the number of accidents, indicating a 4% reduction in accident rates in sections with truck-only lanes. furthermore, the study revealed that an increase in the number of trucks on the highway decreased the opportunity for passenger cars to change lanes, resulting in fewer accidents. the analysis suggested that if the ratio of trucks on the road increased from 2 to 15%, the annual number of accidents could decrease by 22% [12]. though the dual-dual roadway is not designated exclusively for freight vehicles, safety measures have been implemented along 33.5 miles of the dual-dual roadway on the highway connecting new york and delaware. here, the passenger car exclusive lane (inner lane) and the general lane (outer lane) are separated by a physical structure. the study revealed that the traffic accident injury rate on this roadway segment was 34.9-49.6% higher than that on general roads, indicating that segregating traffic lanes by vehicle type does not always yield solely positive outcomes [13]. furthermore, in line with numerous other research findings, a study utilizing the empirical bayes method to estimate future collisions between vehicles, with a focus on truck lane restrictions in north texas, also indicated a decrease in the risk of accidents involving large trucks on bidirectional six-lane roads [14]. in 2009, the federal highway administration (fhwa) conducted a study to evaluate the practicality of building a dedicated truck lane specifically for longer combination vehicles (lcv). the study estimated the advantages of pavement quality, congestion reduction, safety improvements, increased trucking productivity, and reduced emissions from converting existing single-trailer trucks (stt) to lcvs. safety benefits constituted around 30% of the estimated overall benefits [15]. in 2012, ishak and colleagues assessed the operational and safety effects of various truck lane restrictions and differential speed limits on the i-10 highway. the study found that compliance with exclusive lanes for trucks was higher at the midpoint than at the start and end points of the lanes, with an estimated policy compliance rate of 60-80%. the implementation of exclusive lanes for trucks increased the use of trucks in the left lane, and it was confirmed that they drove in the left lane to overtake other trucks. the number of collisions with trucks decreased by 76%, from 81 before the introduction of the lanes to 19 after. these findings suggest introducing exclusive truck lanes can improve safety by reducing collisions [16]. studies assessing the effectiveness of truck-only lanes as a transportation infrastructure measure have been conducted continuously until recent years. jianwei et al. emphasized the role of freight lanes as one of the transportation infrastructures in enhancing economic activity by improving supply chains and reducing logistics costs, contributing to broader regional development and economic growth [17]. focusing on how truck-only lanes can reduce congestion and emissions in urban advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 178 corridors, the review article from ana, juan, and andres examined various lane management strategies and their role in enhancing metropolitan traffic efficiency, while stressing the importance of adaptive planning to balance freight and passenger vehicle needs [18]. 2.4. rationale for implementation in south korea, a designated lane system for large vehicles exists; however, the violation rate is high, and accidents resulting from system violations are significant. in 2005, 86.1% of accidents involving large vans or trucks over 1.5 tons on highways with three or more lanes were due to non-compliance with the designated lane system. therefore, there is a pressing need for stronger policies to address this issue. implementing exclusive lanes for trucks that segregate them from small cars could be a solution to reduce accidents caused by trucks. furthermore, introducing dedicated truck lanes is expected to enhance logistics efficiency by improving truck travel speed and punctuality. additionally, it may help reduce maintenance costs by minimizing road damage. given the domestic traffic conditions and the evolving logistics system, dedicated truck lanes can be a crucial policy measure for efficient and safe road operations. therefore, it is imperative to review and consider the establishment of such lanes in korea [19]. 3. evaluating the operational effects of truck-only lanes in south korea, there are currently no dedicated truck lanes on highways. consequently, analyzing the operational impact of such lanes post-implementation is impractical. therefore, this study aims to employ microscopic simulation techniques to anticipate the effects of installing and operating truck-only lanes. 3.1. methodology this research employed a microscopic traffic flow simulation approach using the specialized program vissim to assess the potential impact on traffic flow and safety when converting one lane in a specific section of the highway into an exclusive lane for freight vehicles. vissim, a detailed microscopic traffic simulation tool, offers high realism and precision. it can replicate diverse traffic scenarios by intricately modeling road networks, intersections, vehicles, and driver behavior, accurately reflecting real-world conditions and variations in these factors. widely utilized in the transportation field, vissim can monitor meaningful responses to variables such as traffic flow, vehicle speed, and delay time. this study quantitatively evaluated the traffic effects resulting from the implementation of exclusive truck lanes. this was achieved by collecting and analyzing travel speeds and speed standard deviations obtained through simulations for each scenario. 3.2. study area a comprehensive review of the entire highway network in south korea was conducted to identify the simulation target area, utilizing the following primary selection criteria. firstly, the designated lanes should be installed on roads with a minimum of four lanes in one direction, as one lane needs to be exclusively allocated for trucks. for instance, even on a three-lane highway, passenger cars and buses will use the first lane to overtake other vehicles. therefore, if a dedicated truck lane is installed on the third lane in the scenario, all vehicles would have to run on the remaining lane, resulting in an operational issue. secondly, the traffic volume of trucks should exceed the average traffic volume per lane. this ensures that if the utilization of the truck-only lane is low, it does not compromise the overall road efficiency. therefore, installing dedicated lanes in areas with substantial truck traffic is preferable. following an assessment of the 2020 traffic and network data, 53 highway sections (272.7 km) that fulfilled the first and second criteria were identified across the country. thirdly, the designated lanes must be installed in segments with a minimum spacing of 2 km between interchanges. if the dedicated lane is positioned on the far-right lane, it may lead to friction with advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 179 diverging and merging traffic before and after interchanges, thus decreasing operational efficiency. finally, the designated lane segment should have a minimum length of 20 km or more. this is because longer segments are essential for stable truck driving and operational efficiency. based on these four criteria, three sections were shortlisted: the chilgok mulryu-gimcheon junction section, the gyeongsan-gumho junction section of the gyeongbu expressway, and the jinju-sanin junction section of the namhae expressway. among these sections, the gyeongsan-gumho junction section was unsuitable for evaluating truck-only lanes due to its high traffic volume and congestion. similarly, the jinju-sanin junction section had multiple interchanges located every 2-3 km, making it challenging to anticipate the efficiency of dedicated lanes. consequently, the chilgok mulryu-gimcheon junction section of the gyeongbu expressway was ultimately chosen as the study area for simulations (refer to fig. 2). this four-lane road has a total length of 33.2 km and a high volume of truck traffic, with three interchanges located at gumi, namgumi, and waegwan. fig. 2 location of the study area 3.3. preparations of alternatives an analysis was conducted using vissim, a traffic simulation program, at the acceptable level to investigate the impacts of the specialized truck lane. the scenarios were divided into two categories: non-operation of the dedicated lane (scenario ⅰ) and operation of the dedicated lane (scenario ⅱ). detailed scenarios were created for each scenario by selecting two time periods, as shown in table 1. table 1 analytic scenarios time scenarios period 1 (4:00 pm5:00 pm) period 2 (09:00 am 10:00 am) scenario ⅰ (do nothing) scenario ⅰ-1 scenario ⅰ-2 scenario ⅱ (with truck-only lane) scenario ⅱ-1 scenario ⅱ-2 the ministry of land, infrastructure and transport, overseeing the planning, construction, and maintenance of korea's entire road network spanning 114,314 km as of december 31, 2022, has established the third thursday of october annually as the pivotal date for the nationwide traffic volume survey, informed by years of research. on this chosen day, resources will be deployed at 3,793 specified locations along the country's roads (including 657 for routine surveys), conducting a 24-hour advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 180 assessment of traffic volume categorized by vehicle type, direction, and time. the results become the basis for nearly all initiatives and studies about korea's transportation infrastructure. accordingly, the analysis utilized traffic volume data obtained from the nationwide annual highway traffic survey conducted on thursday, october 22, 2020. the corresponding traffic conditions are summarized in table 2. period 1, spanning from 4:00 pm to 5:00 pm, represents the peak hour for the section, despite maintaining a los c. in contrast, period 2, from 9:00 am to 10:00 am, corresponds to a non-peak hour with an los a. table 2 traffic conditions in each scenario classification section volume (vehicle/hour) truck volume (vehicle/hour) truck ratio (%) period 1 4:00 pm5:00 pm gimcheon gumi 2,791 892 32.0% gumi namgumi 3,145 983 31.3% namgumi waegwan 3,521 1,050 29.8% waegwan – chilgok mulryu 4,320 1,226 28.4% sum 13,777 4,151 30.1% period 2 09:00 am-10:00 am gimcheon gumi 1,700 667 39.2% gumi namgumi 2,015 782 38.8% namgumi waegwan 2,237 853 38.1% waegwan – chilgok mulryu 2,787 1,043 37.4% sum 8,739 3,345 38.3% the location of the truck-only lane can be decided between the center and the far-right lane. while the center lane provides advantages in securing the right of way, it goes against the intended purpose of the designated lane under the current road traffic act, which mandates that heavy vehicles should travel in the right lane. moreover, the narrowness of the median presents challenges for long-distance truck drivers. additionally, trucks with limited acceleration and deceleration capabilities may cause significant inconvenience to other vehicles when entering or exiting the interchange area. alternatively, placing the truck-only lane in the far-right lane aligns with the existing designated lane system. it can effectively separate the movement of passenger cars and freight vehicles, thus reducing traffic accidents. in this study, the truck-only lane was designated in the far-right lane, and simulations were conducted as shown in table 3 (scenario ii). however, when the truck-only lane was implemented in the fourth lane, passenger cars could merge and diverge by establishing a lane change allowance zone near the interchange. the allowance zone spanned 300 m for the exit and 150 m for the entry. table 3 the distribution of vehicle types per lane in each scenario scenario i lane 1 lane 2 lane 3 lane 4 only passenger cars all vehicles all vehicles all vehicles scenario ⅱ lane 1 lane 2 lane 3 lane 4 only passenger cars all vehicles all vehicles only trucks 3.4. calibration of parameters the simulation model parameters were calibrated to ensure that the vissim simulation network accurately represents the target analysis section's actual road environment and traffic flow characteristics. table 4 provides a summary of key calibration-related data. the default parameter values were those offered by vissim, and the cc3 to cc9 parameters, which are difficult to observe directly, were maintained as default values. additionally, calibration considered values recommended by the virginia department of transportation [20] and the wisconsin department of transportation [21]. in contrast, specific values for simulating the traffic flow of the gyeongbu expressway target section were calibrated and applied. to evaluate the effectiveness of the parameter calibration, two indices were analyzed: the u-value, which assesses the similarity between the simulation network and real-world data based on speed, and the geh (geoffrey e. heavers) statistic, advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 181 which measures similarity based on traffic volume. the average u-value was 0.09, remaining below the threshold of 0.1, while the geh value was 4.68, staying within the acceptable threshold of 5.0. these results confirm that the simulated traffic flow closely aligns with real-world traffic conditions in the study area. table 4 parameter calibration for the preparation of the simulation parameters default value recommended value applied value look ahead distance min. (m) 0.0 typically, not modified basic* 225.0 w.m.d. ** 120.0 look ahead distance max. (m) 250.0 typically, not modified basic 250.0 w.m.d. 250.0 look ahead distance. observed vehicles arterial:4 freeway:2 4 basic 2 w.m.d. 4 car following model: wiedemann 99 temporary lack of attention duration (s) 0.0 0.0∼1.0 1.0 temporary lack of attention probability (%) 0.0 0.0∼5.0 5.0 cc0 (standstill distance) (m) 1.5 basic 1.22∼1.68 basic 1.4 w.m.d. > 1.5 w.m.d. 1.8 cc1 (gap time distribution) (s) 0.9 basic 0.7∼3.0 basic 0.7∼3.0 w.m.d. 0.9∼3.0 w.m.d. 0.9∼3.0 cc2 (following variation) (m) 4.0 basic 2.0∼7.0 basic 2.0 w.m.d. 4.0∼12.0 w.m.d. 4.0 lane change general behavior free lane selection free lane selection or slow lane rule basic free w.m.d. slow max. deceleration own (m/s2) -4.0 -4.57∼-3.66 basic -4.0 w.m.d. -4.0 -1m/s2 per distance own (m) 200.0 100.0∼250.0 basic 200.0 w.m.d. 200.0 accepted deceleration own (m/s2) -1.0 -0.76∼-1.22 basic -2.5 w.m.d. -1.0 max. deceleration trailing (m/s2) -3.0 -3.66∼-2.44 basic -3.6 w.m.d. -3.0 -1m/s2 per distance trailing (m) 200.0 50.0∼250.0 basic 200.0 w.m.d. 200.0 accepted deceleration trailing (m/s2) arterial: -1.0 freeway: -0.5 -0.46∼-0.76 basic -1.5 w.m.d. -0.5 waiting time before diffusion (s) 60.0 99,999.0 99,999.0 note: basic basic segment, w.m.d. – weave, merge, and diverge segment 4. results and discussion as outlined above, micro-level traffic simulations were conducted for peak and off-peak periods on the chilgok mulyu– gimcheon junction section of the gyeongbu expressway, the designated research area. these simulations analyzed both the current traffic conditions and the scenario involving the implementation of a dedicated truck lane. the following section provides a summary of the results. 4.1. simulation results this study utilized travel speed and speed standard deviation as metrics to evaluate the effectiveness of the truck-only lane. according to a previously conducted study, when the speed deviation exceeds 10 km/h, there is a significant increase in the advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 182 accident rate [22]. additionally, it was found that a 1 mi/h increase in speed standard deviation corresponds to an approximately 8% increase in the likelihood of traffic accidents [23]. based on these findings, analyzing speed deviation was hypothesized to assess driving safety effectively. table 5 illustrates the differences in average speed across various scenarios. during period 1, a slight decrease in average driving speed was observed in the truck-only lane compared to the current conditions, although certain sections experienced an increase in speed. in period 2, there was an average speed reduction of approximately 3.2 km/h compared to the current condition, with this decrease occurring in most sections (refer to fig. 3). table 5 comparison of travel speeds and standard deviations across scenarios (km/h) classification mean speed speed standard deviation average four lane average average four lane average period 1 scenario ⅰ-1 lane 1-3 100.9 99.1 10.5 11.7 lane 4 93.5 13.3 scenario ⅱ-1 lane 1-3 100.2 98.8 9.4 10.6 lane 4 88.4 4.4 increments lane 1-3 0.7 0.3 1.1 1.1 lane 4 5.1 8.9 period 2 scenario i-2 lane 1-3 105.2 103.9 9.0 9.7 lane 4 102.2 10.6 scenario ⅱ-2 lane 1-3 100.7 100.7 10.3 11.5 lane 4 90.4 4.9 increments lane 1-3 3.0 3.2 1.3 1.7 lane 4 10.3 5.7 fig. 3 comparison of sectional travel speeds across scenarios (km/h) the standard deviations of speed across different scenarios are presented in the last two columns of table 5. in period 1, a comparison of the speed standard deviation for each scenario showed a decrease in the dedicated lane of 1.1 km/h for lanes 1 to 3 and 8.9 km/h for lane 4, compared to the current condition. this reduction in the speed standard deviation is significant, as research suggests that a decrease of 1 mi/h in the speed standard deviation leads to an approximately 8% decrease in accident occurrence probability, indicating a positive impact on safety. however, in period 2, with relatively lower traffic volume, there was an overall increase in the speed standard deviation in lanes 1 to 3, excluding lane 4, as shown in fig. 4. advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 183 fig. 4 comparison of speed standard deviation by scenarios (km/h) 4.2. discussions below is a summary of the findings from the analysis conducted on the effects of truck-only lane operation using vissim. firstly, when comparing the cases of implementation and non-implementation of exclusive lanes, overall vehicle travel speed decreased slightly. period 2, with a relatively lower traffic volume, showed a more significant speed reduction. secondly, in period 1, a decrease in the speed standard deviation was observed across all lanes, whereas in period 2, an increase was noted. thirdly, upon further analysis of the simulation results, it was pointed out that during period 2, the implementation of the truck-only lane led to a substantial decrease in the number of trucks utilizing the fourth lane, reducing it from 370 to 179. relatively lower traffic volume in the adjacent lanes appeared to prompt freight vehicles to change from lane 4 to lanes 1 to 3. these lane changes were interpreted as an attempt to increase flexibility in selecting travel speeds, leading to the observed increase in the speed standard deviation. lastly, when a dedicated lane was introduced in the fourth lane, there were concerns about potential conflicts between passenger cars and freight vehicles entering and exiting the interchange. however, it was later confirmed that the exclusive lane arrangement had no additional impact on the conflicting traffic flow problem. this was supported by a decrease in the speed standard deviation across the entire section, even in period 1, which had high traffic volume. as a result, implementing exclusive truck lanes decreased average driving speed and the speed standard deviation, which can impact traffic safety. however, it was observed that the driving of trucks in the fourth lane was reduced under low traffic volume conditions, which hurt the measures. these findings highlight the need for flexible operation to avoid times of low traffic when operating truck-only lanes. 5. conclusions this study assessed the feasibility of implementing exclusive truck lanes on korean expressways to enhance traffic efficiency and safety by mitigating operational disparities between freight vehicles and passenger cars. a 33.2 km segment of the gyeongbu expressway was selected as a case study, and traffic conditions were analyzed using vissim under peak and off-peak scenarios with and without dedicated truck lanes. while average speeds remained largely consistent, the simulations substantially reduced speed variability, indicating improved traffic flow stability. a practical methodology was also proposed advances in technology innovation, vol. 10, no. 2, 2025, pp. 174-185 184 for identifying optimal segments for exclusive truck lanes, based on lane configuration, truck volume ratio, and interchange spacing. based on the findings, the principal conclusions are as follows: (1) introducing exclusive truck lanes enhances traffic stability by reducing speed deviations, even without significant changes in average travel speed. (2) the proposed segment selection methodology provides a systematic and transferable framework, with far-right lane placement preferred following domestic regulations and global best practices. (3) public acceptance is critical, particularly from passenger car users, as exclusive lanes may be perceived as limiting general lane access and mobility. (4) exclusive truck lanes should be incorporated into existing expressway systems and proactively planned in future infrastructure, including dedicated freight corridors linked to major logistics facilities. (5) positioning truck-only lanes on the rightmost lane can reduce merging conflicts, provided that interchange areas are designed to separate vehicle types effectively. (6) although differences in traffic flow based on propulsion type were not measurable, the growing share of electric trucks underscores the need to explore ict-enabled platooning and designated electric truck corridors. (7) future evaluations should include advanced safety metrics such as time-to-collision (ttc) and conflict point analysis to more rigorously assess crash risk. 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[23] z. zheng, s. ahn, and c. m. monsere, “impact of traffic oscillations on freeway crash occurrences,” accident analysis and prevention, vol. 42, no. 2, pp. 626-636, 2010. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). references microsoft word aiti#15280 20251203 (in press 1).docx advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx material development and properties of medium-density board from low and high-density polyethylene angeline baldapan elegio* college of engineering, architecture and industrial design, bohol island state university, bohol, philippines received 15 june 2025; received in revised form 03 september 2025; accepted 08 september 2025 doi: https://doi.org/10.46604/aiti.2025.15280 abstract this study aims to develop a material from waste low-density polyethylene (ldpe) and high-density polyethylene (hdpe) into a medium-density board and assess its mechanical and physical properties. the development starts with degreasing the upcycled plastic sheets, stacking using premixed polyester resin as an adhesive, pressing, and laminating. the specimens are sent to the department of science and technology industrial technology development institute (dost-itdi) standards and testing division to determine the material’s mechanical and physical properties. the findings reveal that the medium-density board successfully combines ldpe and hdpe waste, achieving tensile, flexural, and compressive strengths of 12.1 mpa, 24.2 mpa, and 14.5 mpa, respectively. the board is suitable for shaded outdoor use but not for continuous immersion as it shows a heat deflection temperature of 57.8 ℃ and 1.27% water absorption after 24 hours. therefore, it is a potential substitute for furniture, home decor, and light construction materials. keywords: polymers, material development, properties, medium-density 1. introduction polymers (plastics) have been central to creating the modern world. indeed, due to their exceptional material properties and cost-effectiveness, they have been utilized in various sectors, including packaging, construction, electronics, and agriculture, among others [1]. while plastics offer significant benefits and serve as valuable resources for society, such as comfort, hygiene, and safety, leading to the well-being of society, their single-use nature and disposal outweigh the benefits unless used and disposed of appropriately [2]. globally, more than 300 million tons of plastic waste are produced each year, with only 9% being recycled, while the rest is either incinerated or discarded, primarily accumulating in landfills [3]. it is estimated that there will be 12,000 million metric tonnes of plastic waste on earth by 2050 if current trends in plastic consumption persist [4]. unfortunately, artificial petrochemical compounds from oil, such as plastic, will not biodegrade because plastic combines elements extracted from crude oil. thus, these combinations are synthetic, unknown to nature, and indestructible in a biodegradable sense. though beneficial in most uses, plastics’ chemical inertness and longevity represent major problems when these products are released into the environment [5]. this persistence leads to a range of environmental issues, including the pollution of terrestrial and aquatic ecosystems, harm to wildlife, and the aesthetic degradation of natural landscapes [6]. synthetic polymers emerged in the late 19th century, during the 1860s, but it was not until following world war ii that the “plastics boom” commenced [7]. fifty percent of the plastic produced is single-use, intended to be thrown away immediately after serving their purpose, such as straws, plastic carrier bags, and water bottles. * corresponding author. e-mail address: angeline.baldapan@bisu.edu.ph advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 2 the non-degradable nature of petroleum-based polymers, commonly used in packaging, exacerbates landfill overflow and releases harmful gases during decomposition, posing significant environmental threats [8]. current research has insufficiently addressed marine pollution arising from single-use plastic bags. polyethylene is a standard shopping bag material, usually observed in environments (e.g., coastal zones, global ocean, terrestrial ecosystems) with various ecological consequences [9]. although market-based policies and bans on single-use plastics can reduce waste generation and littering, they cannot fully resolve the plastic pollution crisis [10]. in this case, there will be more plastics in the coming years, thus causing more environmental pollution if not properly reused. recycling these resources is one of the ways to help the government address this problem. thermoplastic softens and becomes flexible when exposed to heat. the long polymer molecules are joined to one another by very weak bonds, which easily break apart when heated and quickly reform when taken away from them. that is why thermoplastics are easy to melt and recycle. in addition, a growing body of scientific evidence suggests that microplastic pollution is ubiquitous, with microplastics found in terrestrial and aquatic environments worldwide [11]. microplastics are defined as plastic particles smaller than 5 millimeters, including both primary microplastics (e.g., microbeads) and secondary microplastics (e.g., fibers from clothing, fragments from larger plastic items). primary microplastics are intentionally produced for commercial use, such as in cosmetics, whereas secondary microplastics are formed through the breakdown of larger plastic items. fortunately, in partnership with the japan international cooperating agency (jica) and the fabrication laboratory (fablab) bohol, the city of tagbilaran is adapting the plastic recycling project for improving women’s income (prp4iwi), in which waste plastic shopping bags are heated and cooled to produce upcycled plastic sheets that are then used as the primary material for fashion accessories and souvenir items. the “kalipunan ng liping pilipina” (kalipi), a women’s organized group founded by the department of social welfare and development (dswd), produced these recycled plastic sheets, aiming to eliminate the pervasive plastic waste while simultaneously creating an inclusive business opportunity that can employ nearby communities [12]. thus, plastic sheet upcycling maximizes the use of waste plastic shopping bags and turns them into something more useful. prp4iwi developed various products through the workshops, from simple placemats, wallets, ecobags, accessories such as earrings, and uniquely designed flower vases [13]. however, these sheets are only applied to smaller items. previous work has explored the integration of waste low-density polyethylene (ldpe) and high-density polyethylene (hdpe) composites; for instance, one strategy is to use them in the construction industry, particularly in asphaltic pavements [14]. it further investigated the statistical characteristics of blends. another recent approach has demonstrated the potential of recycling ldpe and hdpe by modifying asphalt mixtures and reported an improved deformation resistance and dynamic modulus in ldpeand hdpe-modified asphalt mixtures, confirmed both experimentally and through machine learning models [15]. building on this knowledge, this study focuses on developing a laminated medium-density board from recycled ldpe and hdpe, evaluating mechanical and physical properties and aesthetic and structural integrity for light-duty applications. 2. materials and methods this study employed an experimental approach to develop medium-density boards using recycled plastic waste. the methodology comprised three stages: (1) preparation of plastic sheets from collected waste, (2) fabrication of standardized test specimens, and (3) evaluation of their mechanical and physical properties. each procedure was conducted under controlled conditions and aligned with american society for testing and materials (astm) and international organization for standardization (iso) testing standards to ensure reliability and reproducibility. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 3 2.1. material preparation the application of recycled plastic waste as a raw material for manufacturing green construction panels has been studied in recent years, focusing on its capabilities to help decrease environmental footprint and support circular economy principles. in this research, the research team collected used plastic bags from households, colleagues, institutions, and nearby laundry shops, reflecting a community-focused method of waste collection. the research team transported the collected materials to the prp4iwi, where the facility upcycled them into plastic sheets. this process was conducted under the close supervision of the management to ensure quality control and adherence to technical standards. the resulting upcycled sheets were intended for use as the core substance in producing medium-density boards to achieve structural integrity. the gathered waste plastic bags are washed and cut into pieces, as shown in fig. 1. removing dirt and dust from the plastic surface is crucial in obtaining a quality sheet. this would affect the binding of the plastic pieces during the heating and compression process. clean plastic ensures better adhesion between layers, making a stronger and more durable sheet. fig. 1 plastic bags cut into pieces fig. 2 shows the use of heat and cold press. the plastic pieces are placed in a heat press below 150 ℃ and a cold press below 60 ℃, as presented in figs. 2(a) and 2(b), to make upcycled plastic sheets. the controlled temperature ensures that melting is enough to bond without reaching decomposition levels that could emit harmful fumes. then, applying cold press to harden the sheet consistently, improving its strength and minimizing internal stresses. (a) using a heat press at 140 ℃ (b) using a cold press at 55 ℃ fig. 2 using heat and cold press this technique reduces health hazards and encourages environmentally friendly practices by recycling plastic waste into long-lasting materials without causing air pollution. appropriate personal protective gear, including gloves and masks, should still be worn when working with hot materials. still, controlled heating and cooling mitigate the risks associated with traditional advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 4 plastic recycling techniques that often involve higher temperatures. to support the material preparation process, the researcher organized the necessary tools and equipment in advance. these included a grinder for refining plastic pieces, a compressor and spray gun for finishing applications, and a welding machine for assembly tasks. additional hand tools such as f-clamps, scissors, wrenches, and screwdrivers were also prepared to facilitate handling and fabrication. 2.2. fabrication of specimen the research team prepared specimens according to the sizes required for standard testing, as shown in table 1. a total of 11 films were used for the tensile strength test, and 7 specimens with a smooth and flat finish were prepared for each of the flexural, compressive, heat deflection temperature, and water absorption tests. these films are laboratory-prepared samples with standardized mechanical and physical testing dimensions. table 1 specimen specifications for testing sample test size in mm (l = length; w = width; t = thickness) no. of specimens plastic product tensile properties l = 200-250; w = 15 11 films flexural properties l = 100; w = 10; t = 4 7 pieces, smooth and flat compressive properties l = 50.8; w = 12.7; t = 12.7 7 pieces, smooth and flat heat deflection temperature l = 127; w = 13; t = 3-13 7 pieces, smooth and flat water absorption l = 76.20; w = 25.4 7 pieces, smooth and flat the prepared specimens, each distinctly labeled as illustrated in fig. 3, were submitted to the standards and testing division of the department of science and technology industrial technology development institute (dost-itdi), a nationally accredited testing laboratory. fig. 3 specimens for laboratory testing the institute released the results as official summary reports in tabular format, including mean values and standard deviations. raw datasets, graphical outputs of individual stress–strain curves, and post-test images of fractured specimens for tensile, flexural, and compressive tests were not provided, as these are retained internally. although this ensured standardized and reliable reporting, it limited the depth of analysis that the research team could perform. nevertheless, the summarized results provided by the accredited laboratory—derived from astm and iso testing procedures—were sufficient to evaluate the mechanical performance and potential applications of the developed boards. the institute conducted standardized tests to assess key performance indicators such as strength, durability, density, and overall structural integrity. 2.3. mechanical and physical property testing parameters the experimental parameters utilized to determine the mechanical and physical properties of the fabricated mediumdensity board are summarized in table 2. to evaluate tensile, flexural, and compressive properties, heat deflection temperature, and water absorption characteristics, astm and iso methodologies were conducted under controlled laboratory conditions, advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 5 with specified test speeds, gauge lengths, and replication numbers to ensure data reliability and reproducibility. the instrumentation included a shimadzu universal testing machine (model ags-50knxd) for mechanical tests, a dynisco hdv3 viact/dtul machine for thermal performance assessment, and an analytical balance for physical measurements. environmental factors such as temperature and relative humidity were maintained at 23±2 ℃ and 50±5%, respectively, to minimize external variability. table 2 test parameters test parameter tensile properties flexural properties compressive properties heat deflection temperature water absorption test method astm d638 adapted astm d790/iso 178 adapted astm d695 adapted astm d648 adapted astm d570 adapted speed of test, mm/min 5 1.30 gage length, mm 50 no. of replicate tests 5 7 2 3 instrument used shimadzu utm, model: ags-50knxd dynisco hdv3 viact/dtul machine analytical balance type of procedure used b support span-to-depth ratio 16:1 radius of support/loading noses, mm 5 fiber stress used 0.455 mpa heating rate 2±0.2 ℃ heat transfer media silicon oil type of immersion 24himmersion temperature, ℃ 23±2 23±2 relative humidity, % 50±5 50±5 3. results and discussion this section presents the outcomes of fabricating medium-density boards using recycled ldpe and hdpe waste. the results highlight both the technical feasibility and the aesthetic versatility of the developed boards. the fabrication process was evaluated in terms of resin bonding and visual patterns, while mechanical tests assessed tensile, flexural, compressive, heat deflection, and water absorption properties. these findings provide insights into the material’s strengths, limitations, and potential applications in sustainable construction and furniture design. 3.1. fabrication of the medium-density board fig. 4 the medium-density board advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 6 the fabrication of medium-density boards using upcycled plastic sheets is a sustainable method of managing plastic waste with the added benefit of making functional composite materials. as a precursor to performance tests, a reproducible and standardized production process must be created to achieve uniformity in structural and physical attributes. this subsection describes the methodology for producing the boards: cleaning plastic sheets, applying premixed polyester resin, pressing, and lamination. these processes were intended to promote interfacial adhesion and material strength. fig. 4 shows the mediumdensity board produced from upcycled plastic sheets. the process involved degreasing the sheets, applying premixed polyester resin as an adhesive, stacking, pressing, and laminating. these steps ensured proper bonding and improved the board’s structural quality. one potential challenge was the improper degreasing. the residual contaminants could weaken interlayer adhesion, which would affect the mechanical properties. in this study, this was minimized through careful surface preparation of the plastics before pressing to ensure that the premixed polyester resin can uniformly and securely adhere between the layers, enhancing the resulting composite material’s structural integrity and cohesion. the degreasing process ensures surface cleanliness, directly improving resin adhesion. after degreasing, the research team combined the premixed polyester resin with its hardener. the mixing ratio followed the manufacturer’s instructions: 10 ml of hardener per kilogram of resin for a 1% concentration, and 20 ml per kilogram for 2% concentration. the mixture was uniformly applied to the surface of the cleaned plastic sheets, serving as the primary adhesive to bond the layers together. the resin application is carried out using a brushing technique to ensure consistent coverage and sufficient penetration into the surface texture of the sheets. then, the sheets are carefully stacked and subjected to pressing and wait for a five-hour curing time at room temperature. this step is critical to promote uniform bonding across the interfacial layers and to eliminate the formation of air pockets within the composite. entrapped air can compromise the structural integrity of the medium-density board, leading to internal voids that may propagate under mechanical stress and ultimately result in material failure. in addition, the premixed polyester resin used in this study is commercially available and widely used in industry, which supports scalability. laminating follows, using fine finishing to provide a smooth finish and additional strength to the board. fig. 5 presents three patterns in medium-density boards fabricated using ldpe and hdpe waste materials. these patterns are differentiated based on the constituent pieces’ geometric characteristics and color schemes, which were manually arranged before the heat-pressing process. (a) random shapes, sizes, and colors (b) squares with controlled red, yellow, and green colors (c) squares and strips in blue, black, and white fig. 5 different patterns produced under different shapes, sizes, and colors fig. 5(a) illustrates a composition generated using randomly selected shapes, sizes, and colors. this random distribution produces a highly heterogeneous visual texture that enhances uniqueness and creativity. the unpredictable design provides a distinct aesthetic character, offering versatility for different applications suitable for accent panels or decorative wall features. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 7 fig. 5(b) demonstrates a pattern created with a more controlled approach, utilizing uniformly shaped squares in a defined color palette of red, yellow, and green. this method introduces a structured and consistent pattern, making it appropriate for tabletops or modular furniture designs where uniformity and vibrancy are desired. fig. 5(c) exhibits a design composed of square shapes and elongated strips, limited to a color scheme of blue, black, and white. the combination of geometric regularity and a restricted palette generates a visually striking contrast and directional flow that could be applied in modern interior design elements such as cabinets or decorative panels. these visual outcomes highlight the aesthetic flexibility that can be achieved by varying the recycled polymer components’ shape, size, and color. the ratio of ldpe to hdpe was not predetermined, as the study aimed to reflect the variable availability of collected plastic waste and assess the robustness of the upcycling process under such variability. while this approach provided insights into the feasibility of producing functional and aesthetically appealing board products without strict segregation, it also represents one of the study’s limitations, since variations in input ratios may influence the reproducibility and consistency of material properties. the laboratory equipment constraints limited board dimensions to 210 × 297 mm, which restricted scaling in this phase; however, the successful outcomes suggest that larger-scale production is feasible with industrial-grade facilities. in this study, the size was extended by joining the upcycled plastic sheets using mesh tape during the stacking and pressing process, as shown in fig. 6. the mesh tape acts as a reinforcing material, providing additional structural integrity to the joined sheets and preventing separation. during stacking, the mesh tape is strategically placed between the sheets at the joints, allowing the premixed polyester resin to seep through and bond the layers firmly. when pressed and laminated, the mesh integrates seamlessly into the composite, resulting in a larger and thicker board without compromising strength or durability. fig. 6 joining of two sheets using mesh tape 3.2. results of the mechanical and physical properties of the medium-density board this section presents the mechanical and physical performance of the medium-density board developed from a blend of ldpe and hdpe waste. the tests include tensile, flexural, compressive, heat deflection, and water absorption analyses to evaluate strength and durability. results are compared with values from similar polymer-based composites to assess competitiveness. the tensile properties obtained from the tests are summarized in table 3. table 3 tensile properties sample tensile strength (mpa) tensile stress at break (mpa) tensile stress at yield (mpa) m sd m sd m sd mediumdensity board 12.1 3.29 12.1 3.29 tensile strain (elongation) at break (%) modulus of elasticity (gpa) mean dimension (mm) m sd m sd w t 2.25 0.921 0.742 0.181 14.9 7.79 advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 8 the material did not show a distinct yield point (no tensile stress/strain at yield), suggesting brittle or non-ductile behavior. the modest tensile strength of 12.1 mpa and low strain at break of 2.25% support the idea of a relatively stiff and brittle material. this is expected due to the blend of flexible ldpe and rigid hdpe polymers. the strength suggests the board can handle reasonable loads, but may not be suitable for applications requiring high tensile resistance. the modulus of elasticity of 0.742 gpa is typical for lower-end polymers, indicating some flexibility but still more rigid than elastomers. this value falls between the typical moduli of ldpe, which is 0.11–0.45 gpa, and hdpe, which is 0.8 gpa, indicating a successful combination of the two materials. blending hdpe and ldpe can lead to a material with a balance of properties, leveraging the flexibility of ldpe and the strength of hdpe [16]. the standard deviations are relatively high, 3.29 mpa for tensile strength, indicating moderate variation in test results. this is due to sample inconsistencies or experimental variability. table 4 presents the flexural performance of the medium-density board as determined through a three-point bending test. the mean flexural strength was 24.2 mpa, with a standard deviation of 3.51 mpa, indicating relatively consistent strength performance among the tested specimens. the material exhibited flexural stress values of 21.5 mpa at 3.5% strain and 22.0 mpa at 5% strain, with standard deviations of 3.25 mpa and 3.22 mpa, respectively. these results suggest a minimal increase in stress between the two strain levels, reflecting the board’s moderate ductility under bending stress. table 4 flexural properties sample flexural strength (mpa) flexural stress at given strain (mpa) flexural stress at break (mpa) flexural modulus (gpa) 3.5% 5% m sd m sd m sd m sd m sd mediumdensity board 24.2 3.51 21.5 3.25 22.0 3.22 0.815 0.134 mean dimension (mm) no. of specimens failed at no. of replicate tests rate of cross head motion (mm/min) support span length (mm) w t y r 11.2 4.44 5 0 5 21.0 76.0 these results are comparable to those reported in related literature. recycled hdpe composites have been reported to achieve flexural strengths around 32.6  mpa [17], while ldpe-based composites show lower flexural strengths near 7.61 mpa [18]. the flexural modulus, representing the board’s stiffness, was measured at 0.815 gpa with a standard deviation of 0.134 gpa, indicating a moderately rigid behavior appropriate for structural applications requiring bending resistance. specimen dimensions averaged 11.2 mm in width and 4.44 mm in thickness, with a support span of 76.0 mm during testing. all five replicate tests were completed, with five specimens failing as expected under flexural loading and no failures attributed to testing anomalies. the crosshead motion rate was maintained at 21.0 mm/min, following standard test protocols for reliable comparison of results. table 5 shows the results of the compressive testing conducted on medium-density board specimens. the average compressive strength was 14.5 mpa, with a standard deviation of 2.70 mpa, reflecting moderate resistance to axial compressive loading and some variability among the test samples. no data were recorded for compressive stress at yield, suggesting either that yielding was not clearly defined or that failure occurred in a brittle manner without a distinct yield point. table 5 compressive properties sample compressive strength (mpa) compressive stress at yield (mpa) compressive modulus (gpa) mean dimension (mm) mean sd mean sd mean sd l w t medium-density board 14.5 2.70 0.482 0.067 51.4 13.3 13.8 these results are comparable to those reported in related studies. comparable research on recycled hdpe and woodplastic composites has documented compressive strengths of approximately 10–28 mpa, depending on material formulation, filler content, and processing techniques [19]. these findings indicate that the developed boards exhibit compressive properties advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 9 consistent with those of similar polymer-based composites, supporting their potential applicability in structural uses requiring moderate compressive performance. the compressive modulus, representing the material’s stiffness under compressive loading, was measured at 0.482 gpa, with a standard deviation of 0.067 gpa. this value indicates a relatively lower stiffness than the flexural modulus, consistent with the structural behavior of composite board materials under different loading conditions. specimens used in the test had an average dimension of 51.4 mm in length, 13.3 mm in width, and 13.8 mm in thickness, providing a standardized basis for comparison across studies. as shown in table 6, the mean heat deflection temperature of the samples was recorded at 57.8 ℃, which reflects the material’s ability to retain its structural integrity at moderately elevated temperatures. the test was conducted using specimens with the following average dimensions: l = 12.8 mm, w = 14.5 mm, and t = 12.7 mm. the resulting value suggests that the material can be employed in applications where moderate heat resistance is essential and dimensional stability at elevated temperatures is required. table 6 heat deflection temperature sample heat deflection temperature (℃) mean dimension (mm) mean l w t medium-density board 57.8 12.8 14.5 12.7 the board can be used outdoors since, based on the average of all weather stations in the philippines, excluding baguio, the mean annual temperature is 26.6 ℃ [20]. however, in extreme conditions, such as prolonged direct sunlight or near heat sources where surface temperatures can exceed 50 ℃, the material may approach its deflection limit, potentially leading to warping or loss of mechanical integrity. additional treatments like ultraviolet (uv) stabilization or heat-resistant coatings might be considered to enhance thermal performance. table 7 suggests that the material absorbs water and increases by 1.27% in weight if immersed in water for 24 hours. this could lead to swelling, dimensional instability, and potential mechanical property degradation over time, especially if the material is consistently exposed to water. discoloration was also observed on the three replicated specimens. it may not directly affect mechanical strength, but it compromises the aesthetic quality, which is critical for applications where appearance matters, such as outdoor decorative panels and furniture. thus, the board could be used outdoors, but it is not designed to be submerged in pools and on beaches. table 7 water absorption sample code % water absorption (increase in weight) mean dimension (mm) observation l w t mediumdensity board 1.27 77.3 25.8 15.6 discoloration was observed on the specimens compared to junaid et al. [14], who primarily conducted statistical analyses on ldpe/hdpe blends, the medium-density board demonstrated notable tensile, flexural, and compressive strengths and aesthetic versatility through patterning. this underscores the functional and decorative potential of the material for applications in furniture and light building components. reducing plastic usage, reusing, recycling, and energy recovery can mitigate environmental impacts [21], and upcycling waste ldpe and hdpe shopping bags into light construction materials offers a better alternative than incineration. the postconsumer ldpe and hdpe shopping bags are low-cost, requiring only collection and minimal pre-processing. energy use was limited to shredding, pressing, and heating, which are scalable processes adaptable to existing manufacturing setups. compared to conventional medium-density fiberboards, the production of the upcycled plastic boards reduces dependence on virgin raw materials and avoids additional deforestation-related impacts. while a full cost–benefit and life cycle assessment are beyond the scope of this study, these initial considerations indicate that the approach is economically viable and advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 10 environmentally advantageous when implemented at larger scales. although the developed boards exhibited favorable structural and aesthetic qualities, they may be prone to deformation under sustained loading and potentially degrade when subjected to prolonged uv exposure or fluctuating temperatures. additionally, while the boards exhibit good bonding from thermal fusion of plastics, the uneven distribution of plastic pieces could serve as starting sites for cracking or delamination. 4. conclusions the study successfully demonstrated the feasibility of transforming waste ldpe and hdpe plastic shopping bags into medium-density boards with both aesthetic and functional properties suitable for light construction and decorative applications. the key outcomes are summarized below: (1) the random coloration and distribution of the plastic fragments enhanced the board’s visual appeal and enabled user customization. although fabrication was limited to an a4-sized (210 × 297 mm) board due to laboratory constraints, the board scaling up is considered feasible through the use of mesh tape reinforcement and lamination techniques for larger, structurally sound panels. (2) mechanical testing showed a tensile strength of 12.1 mpa and a low strain at break of 2.25%, indicating a relatively stiff and brittle material, which aligns with the properties of the blended polymers. the modulus of elasticity of 0.742 gpa and flexural modulus of 0.815 gpa suggest that the material exhibits moderate rigidity appropriate for non-load-bearing structural applications. additionally, the mean flexural strength of 24.2 mpa and compressive strength of 14.5 mpa confirm its capacity to resist moderate flexural and compressive loads. (3) the heat deflection temperature of 57.8 ℃ confirms the board’s suitability for typical tropical outdoor conditions, such as those in the philippines. however, exposure to extreme heat may cause deformation. this may warrant using uvor heat-resistant coatings to extend the material’s durability. (4) water absorption testing showed a 1.27% weight increase after 24 hours. this suggests a potential dimensional and aesthetic change over time. despite minor discoloration, the material maintained structural integrity, making it suitable for shaded or semi-exposed outdoor use but not for continuous water immersion. the results of this study contribute to advancing sustainable material development by showing how plastic waste can be engineered into functional composites. while the developed boards exhibited good performance in mechanical, thermal, and aesthetic aspects, further refinement is needed to improve durability and long-term reliability. future studies should include detailed stress–strain analyses, controlled ldpe-to-hdpe ratio testing, and weathering or repeated loading assessments. these efforts will help optimize the material and expand its potential use in sustainable furniture, interior design, and light construction applications. acknowledgments appreciation is extended to bohol island state university for requesting the study and to prp4iwi for allowing the use of heat press machines. additional thanks are extended to the individuals and institutions who donated their waste plastic shopping bags. conflicts of interest the authors declare no conflict of interest. references [1] j. payne, p. mckeown, and m. d. jones, “a circular economy approach to plastic waste,” polymer degradation and stability, vol. 165, pp. 170-181, 2019. advances in technology innovation, vol. x, no. x, 20xx, pp. xx-xx 11 [2] r. kumar, a. verma, a. shome, r. sinha, s. sinha, p. k. jha, et al., “impacts of plastic pollution on ecosystem services, sustainable development goals, and need to focus on circular economy and policy intervention,” sustainability, vol. 13, no. 17, article no. 9963, 2021. 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[21] a. alsabri, f. tahir, and s. g. al-ghamdi, “environmental impacts of polypropylene (pp) production and prospects of its recycling in the gcc region,” materials today: proceedings, vol. 56, part 4, pp. 2245-2251, 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 finite element analysis of ti-6al-4v lattice cubic scaffolds for mandibular bone implant applications yasya khalif perdana saleh1,2,3, rifky ismail1,4,*, jamari jamari1, i nyoman jujur2,3, suryadi suryadi2, rochmad winarso5, tepi anggara3 1department of mechanical engineering, diponegoro university, semarang, indonesia 2biocompatible material, national research and innovation agency, tangerang selatan, indonesia 3department of mechanical engineering, jakarta global university, depok, indonesia 4center for biomechanics, biomaterial, biomechatronics, and biosignal processing (cbiom3s), diponegoro university, semarang, indonesia 5department of mechanical engineering, faculty of engineering, muria kudus university, kudus, indonesia received 25 november 2024; received in revised form 24 march 2025; accepted 25 march 2025 doi: https://doi.org/10.46604/aiti.2024.14542 abstract this study evaluates the compressive strength of a cubic lattice scaffold made from titanium alloy (ti-6al-4v) for mandibular bone implants. scaffold designs with pore sizes ranging from 800 µm to 1000 µm were analyzed using finite element analysis under compressive forces of up to 800 n. pore sizes of 800 µm and 850 µm achieved a safety factor greater than 1.4, indicating their suitability for both dynamic and static loading. planned production with bound metal deposition, maintaining a density below 35%, emphasizes material efficiency and cost-effectiveness. results indicate that 800 µm and 850 µm pore sizes offer optimal strength and safety, suggesting effective mandibular implant integration. further research on cyclic load testing and osseointegration is recommended. keywords: ti-6al-4v material strength, lattice beam type cubic scaffold, mandibular bone implant, additive manufacturing, compressive strength 1. introduction bone implants are a medical procedure in orthopedic medicine, replacing injured or missing bone parts with specific materials [1]. currently, the development of bone implants using additive manufacturing processes has become a captivating topic in research. this process enables the creation of complex shapes unattainable by conventional machining techniques. the main advantage of this technology lies in its ability to generate complex and integrated internal structures, allowing designs that better meet the specific anatomical needs of patients. in bone implant development, consideration must be given to the complex three-dimensional (3d) geometry and highly organized internal architecture of human skeletal tissue, which cannot be replicated by cells maintained in two dimensions. porous scaffolds are crucial in hard tissue engineering strategies as they provide a 3d framework. porous structure characteristics, such as porosity, pore size, and pore interconnectivity, significantly impact biological performance and mechanical properties [2-3]. research has shown that scaffolds with a porous structure can more effectively support bone regeneration, enabling new tissue growth within the scaffold and better nutrient distribution. * corresponding author. e-mail address: rifky_ismail@ft.undip.ac.id advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 284 the cubic microarchitecture of the scaffold has a better elasticity modulus and compressive strength compared to other microarchitectures at the same porosity [4]. this also indicates a decrease in low elasticity modulus, making it a suitable choice in bone tissue engineering as it meets the recommended pore size and minimum strength required to support bone growth and integration. meanwhile, the internal pore structure and material distribution directly influence plasticity and stiffness, determining the stress environment of the surrounding bone tissue when implanted in vivo [5]. additive manufacturing in mandibular scaffolds is considered to have great potential in accelerating the healing of jawbone defects with outcomes that better match the shape of the existing damage. literature results show that material selection and 3d printing techniques play an important role in determining the biological compatibility and mechanical effectiveness of the scaffold. several microarchitecture structures, including body-centered cubic (bcc) and triply periodic minimal surface (tpms), have been found to have optimal mechanical and biological characteristics for mandibular healing, further strengthening the choice of cubic lattice beam structure as a strong candidate in scaffold design for bone implants [6]. the designed scaffold must be easily printable using specific additive manufacturing techniques. one morphology type commonly developed using this method is the lattice beam cubic type scaffold. various studies have been conducted to understand its mechanical properties and biocompatibility [7-9]. cubic scaffolds are widely used due to their mechanical stability and ease of fabrication; however, their biological performance remains a concern, as their regular pore structure may limit cell migration and vascularization [10]. therefore, further research is needed to explore the influence of pore size and low density on structural strength [11]. this study aims to provide a finite element-based numerical analysis to bridge the knowledge gap and serve as a reference for the bound metal deposition (bmd) manufacturing method, which has been less explored in existing literature [12]. one current implant development is the mandibular bone implant (lower jawbone). this implant has been in development since 2016 [6]. currently, mandibular bone implant development uses ti-6al-4v material with additive manufacturing methods, employing various printing techniques [13-14]. this development has progressed with the adoption of additive manufacturing methods, enabling complex geometries and high precision printing that are difficult to achieve with conventional techniques. this capability to print more precise shapes improves implant integration with the patient's natural bone structure and allows adaptation to significant individual variations among patients. this method opens new possibilities for tailoring implant designs specifically to patient anatomical needs, thus increasing success rates and user comfort. however, further research is needed to understand the complex interactions between scaffold design variables, such as porosity and structural orientation, and the mechanical strength of the resulting scaffold. over time, additive manufacturing printing methods have developed, including the use of bmd. this method is a 3d metal printing process based on extrusion, where components are created by depositing metal powder bound with polymer binders [15]. this method can reduce production costs by 60-80% compared to the selective laser sintering (sls) and electron beam melting (ebm) processes [16]. global researchers using the bmd method have extensively studied mechanical testing, material characterization, and environmental impacts [15-19]. however, previous studies have primarily focused on print orientation or evaluating the post-print shape of products without providing an in-depth analysis of scaffold mechanical behavior under forces resembling in vivo conditions. desktop metal, one of the additive manufacturing machines using the bmd method, achieves a maximum density of 35% per print. this raises further questions about whether ti-6al-4v material with a density below 35% can withstand the forces encountered when applied to mandibular implants. the mandibular bone experiences about 100 n during chewing, with a maximum acceptable force of up to 800 n [20-22]. additionally, scaffold pore size significantly affects implant mechanical strength. previous research shows that larger pore sizes reduce the compressive strength of a material [23]. this study will focus on evaluating the compressive strength of the lattice beam cubic-type scaffold using finite element analysis (fea) simulation, with variations in pore structure porosity and applied force, utilizing ti-6al-4v material. advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 285 previous studies have shown that various lattice structures, such as bcc, tpms, and cubic lattice, have the potential to enhance the mechanical characteristics of scaffolds for mandibular implants [24]. however, further research is needed to explore the influence of pore size and low density on structural strength [7]. in addition, the bmd technology offers a more economical alternative compared to conventional methods like sls and ebm [25]. nevertheless, studies focusing on finite element simulation as a reference for the bmd method are still very limited. therefore, this study presents a novelty by developing a finite element-based simulation as a fundamental reference for further research in the development of the bmd method, without directly evaluating the method itself. by providing a numerical analysis based on finite element simulation, this study can fill the gap in understanding the mechanical strength of ti-6al-4v lattice scaffolds with variations in pore size and low density, which has the potential to serve as a reference in the development of bmd-based manufacturing techniques. the goal of this study is to evaluate the compressive strength of a cubic lattice scaffold made from titanium alloy (ti-6al-4v) for mandibular bone implant applications. this study analyzes various pore sizes ranging from 800 µm to 1000 µm using fea to determine the optimal scaffold configuration that balances mechanical strength, material efficiency, and structural safety. additionally, this study considers the production feasibility using the method, which maintains a density below 35%. since this density limitation may affect the scaffold's ability to withstand loads, pore size variation analysis is necessary to assess how a low-density structure can still meet the mechanical requirements for mandibular implant applications effectively and safely. 2. numerical methods this study utilizes two software programs to ensure accurate design and analysis. the student version of creo is used for developing the porous scaffold model, allowing precise control over structural parameters such as pore size and geometry. ansys r2 2022 is then employed for fea to evaluate the mechanical performance of the scaffold under various loading conditions. 2.1. geometrical modelling this study uses compression test specimens following iso standards (iso 13314:2011), with dimensions of 7.2 x 7.2 x 7.2 mm. pore sizes of 800 µm, 850 µm, 900 µm, 950 µm, and 1000 µm were designed using creo software, as shown in fig. 1. the selection of the 800-1000 µm pore size is supported by previous research, such as wang et al. [26], which demonstrated that an 800 µm pore size offers optimal mechanical properties and enhances osteogenesis, thereby justifying its use in scaffold design. in this study, the analysis is further refined by incorporating 50 µm increments within this range (i.e., 800, 850, 900, 950, and 1000 µm) to provide a more detailed understanding of the variations in mechanical strength at each pore size. fig. 1 cube design with pore variations advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 286 each specified pore size results in a different volume, calculated as follows: 1 0 hv v v= − (1)   1 0 ( 6)i ov v box v v= −  +  (2) where v1 is the final volume of the porous cube, v0 is the solid cube volume, vh is the total hole volume, and box is the total of all formed hole cells, vi is the volume of the inner holes, and vo is the volume of the outer holes, as shown in fig. 2. fig. 2 cube volume calculation explanation differences in pore sizes produce varying infill values for each pore size. the infill can be calculated using eq. (3): 1 0 infill 100% v v =  (3) where infill represents the percentage of the structure’s initial volume reduced due to pores (%), v1 is the final volume of the porous cube, and v0 is the solid cube volume. volume and infill values from these calculations are shown in table 1. table 1 volume and infill values of each pore no pore size (µm) solid cube volume (mm3) final cube volume (mm3) mass (kg) infill (%) 1 800 373.248 96.768 0.00044707 25.92 2 850 373.248 76.734 0.00035451 20.55 3 900 373.248 58.32 0.00026944 15.63 4 950 373.248 41.85 0.00019335 11.21 5 1000 373.248 27.648 0.00012773 7.41 2.2. material properties the compression simulation was performed using ansys r2 2022. the first step in operating computational software for fea is to input the mechanical properties of the material. in this case, the titanium alloy (ti-6al-4v) is used as the material for the cubic lattice beam scaffold. ti-6al-4v is widely used in biomedical applications due to its high strength-to-weight ratio, corrosion resistance, and excellent biocompatibility. the mechanical properties are based on ti-6al-4v data from cham et al. [27] research and are included as engineering data available in ansys r2 2022, as shown in table 2. the key properties considered include young’s modulus, poisson’s ratio, tensile strength, yield strength, and density. these properties are essential in ensuring the numerical simulation accurately represents the real-world mechanical behavior of the scaffold. additionally, the thermal and elastic properties of ti-6al-4v were considered, as they influence the material’s deformation and load distribution under applied forces. advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 287 table 2 mechanical properties of titanium alloy or ti-6al-4v [27] no property value unit 1 density 4620 kgm-3 2 coefficient of thermal expansion 9.4e-06 c-1 3 young’s modulus 96000 mpa 4 poisson’s ratio 0.36 5 bulk modulus 114290 mpa 6 shear modulus 35294 mpa 7 tensile yield strength 930 mpa 8 compressive yield strength 930 mpa 9 tensile ultimate strength 1070 mpa 2.3. mesh quality analysis mesh analysis focuses on evaluating and optimizing mesh structure to improve accuracy and efficiency in numerical simulations. the quality of the mesh plays a crucial role in determining the reliability of fea results, as an inappropriate mesh can lead to inaccurate stress distributions or excessive computational costs. the mesh determination method used in this simulation model is convergence testing, which is beneficial for establishing an optimal mesh size for model development, as it can significantly affect output results [28]. this study tests element sizes from 0.8-0.09 mm with an 800 n load on each model, as illustrated in fig. 3. convergence testing ensures that further refinement of the mesh does not significantly alter the results, confirming the balance between computational efficiency and accuracy. this study tests element sizes from 0.8 mm to 0.09 mm with an 800 n load on each model, as illustrated in fig. 3. the mesh quality is assessed based on parameters such as skewness, aspect ratio, and jacobian ratio to ensure high accuracy and numerical stability. mesh refinement is applied to areas with high stress concentrations to capture critical deformation details while maintaining an efficient computation time. fig. 3 force and fixed location 2.4. force applied modelling after mesh convergence testing, load simulations are conducted based on pore size variations of 800 µm, 850 µm, 900 µm, 950 µm, and 1000 µm, and force variations on each pore size of 100 n, 200 n, 300 n, 400 n, 500 n, 600 n, 700 n, and 800 n. fig. 4 shows the force application process used in this study's simulations. advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 288 the applied forces are based on physiological loading conditions of the mandible (human jawbone), where bite forces typically range from 100 n to 800 n, depending on food texture and biting location. the force is distributed across the scaffold structure to simulate real-world loading conditions. boundary conditions are applied to simulate constraints, ensuring that movement and deformation occur realistically. the loading conditions are set to evaluate stress distribution, deformation, and mechanical performance under different forces and pore size variations. this analysis provides insights into how the scaffold withstands physiological forces and ensures its structural integrity under in vivo conditions. fig. 4 force variation in each model 3. finite element analysis the findings of this study were entirely derived from numerical simulations. these simulations were carefully designed and executed to replicate real-world conditions, ensuring accurate and reliable results. by relying solely on computational methods, the study was able to explore various scenarios and parameters that would be difficult to examine experimentally, thus providing a comprehensive understanding of the phenomena under investigation. 3.1. results of mesh quality analysis using various mesh sizes in the simulation resulted in different node and element counts within the simulation model. the smaller the mesh size, the greater the number of nodes and elements, as the model’s geometry is broken down into finer parts. consequently, a finer mesh requires more complex calculations and more time to complete due to the increased computational load. fig. 5 shows an example of convergence testing simulation results with an 800 n force and an element size of 0.1 mm. fig. 5 sample of simulation results for convergence testing advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 289 based on the data from the convergence test simulation, the max. von mises equivalent stress value increases inversely with the decrease in element size, as shown in fig. 6. to quantify the change in max. von mises equivalent stress, it is necessary to calculate the error value shown in eq. (4). 1 0 0 error 100%    − =  (4) where error represents the percentage difference in max. von mises equivalent stress between element sizes (%), σ0 is the max. von mises equivalent stress for the smaller element size (mpa), σ1 is the max. von mises equivalent stress for the larger element size (mpa). the simulation results indicate that the change in max. von mises equivalent stress from an element size of 0.8 mm to 0.09 mm is less than 1%, specifically 0.9%, as shown in table 3. table 3 change in max. von mises equivalent stress error value no. element size e0 (mm) max. stress 𝜎0 (mpa) element size e1 (mm) max. stress 𝜎1 (mpa) error (%) 1 0.8 344.61 0.75 351.79 2.08 2 0.75 351.79 0.7 358.97 2.04 3 0.7 358.97 0.65 366.15 1.99 4 0.65 366.15 0.6 373.33 1.96 5 0.6 373.33 0.55 380.50 1.92 6 0.55 380.50 0.5 387.68 1.87 7 0.5 387.68 0.45 394.86 1.85 8 0.45 394.86 0.4 402.04 1.82 9 0.4 402.04 0.35 409.22 1.78 10 0.35 409.22 0.3 416.39 1.75 11 0.3 416.39 0.25 423.57 1.72 12 0.25 423.57 0.2 430.75 1.69 13 0.2 430.75 0.15 437.63 1.67 14 0.15 437.63 0.1 441.87 1.01 15 0.1 441.87 0.09 442.22 0.08 this shows that the change in element size has an insignificant effect, indicating stability in the maximum von mises equivalent stress value, as illustrated in fig. 6. the convergence test results confirm that further reduction in element size does not significantly alter the stress distribution, ensuring the reliability of the simulation. a finer mesh may increase computational time without notable improvements in accuracy. therefore, this study uses an element size of 0.1 mm to achieve a balance between computational efficiency and result accuracy. fig. 6 convergence test results advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 290 3.2. compression test simulation results using fea software the compression test in this study was conducted to evaluate the mechanical strength and deformation behavior of titanium alloy (ti-6al-4v) in a cubic lattice beam scaffold structure. the scaffold was designed with varying pore sizes of 800 μm, 850 μm, 900 μm, 950 μm, and 1000 μm to examine how porosity influences structural integrity under different loading conditions. applied forces ranged from 100 n to 800 n, simulating physiological loads experienced in mandibular bone applications. the compression simulation was performed using fea software to assess the scaffold's mechanical response, including stress distribution, deformation, and failure behavior. the von mises stress values were recorded to determine the scaffold's ability to withstand compressive loads without exceeding the material’s yield strength. fig. 7 presents a sample simulation result for the 800 μm pore size under an 800 n force, illustrating the stress concentration and deformation pattern. the results from this analysis provide insight into the optimal pore size and mechanical stability required for mandibular implant applications, ensuring a balance between structural strength and biological compatibility. (a) total deformation (b) von mises equivalent stress (c) equivalent elastic strain (d) safety factor fig. 7 compression test simulation sample result using fea software 4. discussion the simulation results from the fea software provided key mechanical parameters, including total deformation, von mises equivalent stress, equivalent elastic strain, and safety factor. total deformation analysis helps in understanding the displacement behavior of the scaffold under different loading conditions, ensuring it remains within acceptable limits. von mises equivalent stress was evaluated to determine whether the scaffold could withstand applied forces without exceeding the material’s yield strength. equivalent elastic strain analysis provided insight into the material's ability to deform elastically before reaching plastic deformation. advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 291 additionally, the safety factor was calculated to assess the structural reliability of the scaffold. a higher safety factor indicates a lower risk of failure under physiological loads, ensuring long-term durability and biomechanical compatibility for mandibular bone implant applications. (a) variation by force (b) variation by pore size fig. 8 line graph of maximum total deformation changes (mm) the line graph in fig. 8 indicates that the total deformation value increased with each increment in applied force. hence, the smaller the applied force, the smaller the resulting shape change, and conversely, the larger the force, the greater the deformation. additionally, comparing pore size variations reveals that smaller pore sizes correlate with higher material strength, though they also increase material costs. conversely, larger pore sizes have lower material strength but reduced material costs. when a sufficiently high compressive force is applied to the ductile material, causing deformation beyond its elastic limit, the material enters a plastic deformation phase. this results in a permanent shape change that cannot revert to its original form, unlike elastic deformation, where the material returns to its original shape once the force is removed. (a) variation by force (b) variation by pore size fig. 9 line graph of maximum von mises equivalent stress changes (mpa) in fig. 9(a), changes in von mises equivalent stress across different pore sizes under various compressive forces, from 100 n to 800 n, can be observed. the graph shows that von mises stress values increase with larger pore sizes and higher applied forces. at the lowest compressive force of 100 n, all pore sizes (800 μm to 1000 μm) exhibited relatively low stress levels, below 500 mpa. however, at 800 n, there was a notable increase in stress, particularly for larger pores such as 950 μm and 1000 μm, where stress values approached or exceeded 3500 mpa. this analysis concludes that larger pores undergo higher stress as compressive force increases. with ti-6al-4v’s yield strength of 930 mpa, compressive forces up to 400 n are below this limit for all pore sizes (800 μm to 1000 μm), ensuring safety from permanent deformation. however, at 500 n, only pore sizes below 900 μm remain under the yield strength threshold. with higher compressive forces, nearly all pore sizes exceed 930 mpa, except for the 800 μm and 850 μm pores at 800 n, maintaining safe levels at 441.87 mpa and 647.02 mpa, respectively. therefore, to keep stress below 930 mpa, the optimal pore sizes are 800 μm and 850 μm. advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 292 in fig. 9(b), the von mises equivalent stress is shown by varying the pore sizes (800 μm to 1000 μm) under different forces. the graph results indicate that the larger the pore size, the higher the stress experienced under the same compressive force. for the largest pore size, 1000 μm, even at a low compressive force of 100 n, the von mises stress approaches 500 mpa and increases drastically to over 3500 mpa when the compressive force reaches 800 n. considering the yield strength of 930 mpa, larger pore sizes, such as 1000 μm, tend to deform more rapidly even under lower forces. overall, from these two graphs, it can be concluded that to keep the von mises equivalent stress below 930 mpa, a careful combination of pore size and compressive force is necessary. smaller pore sizes, especially those below 900 μm, can withstand higher forces up to 800 n without exceeding the yield strength. however, for larger pore sizes, particularly those above 850 μm, only lower compressive forces, below 300 n, can be sustained without leading to permanent deformation. (a) variation by force (b) variation by pore size fig. 10 line graph of maximum equivalent elastic strain changes (mm) fig. 10 shows that equivalent elastic strain increases with higher compressive force and pore size on the scaffold. in fig. 10(a), strain variation is shown across forces ranging from 100 n to 800 n, with pore sizes between 800 μm and 1000 μm. strain values remain relatively low and stable at lower forces. however, they increase significantly at 800 n, especially for larger pore sizes, such as 950 μm and 1000 μm. on the other hand, fig. 10(b) represents strain across constant compressive forces with varying pore sizes, displays a similar pattern—larger pore sizes yield higher strain values for the same compressive force, peaking around 0.035 mm for a 1000 μm pore size under 800 n. it can be concluded that larger pore sizes tend to produce higher strain under the same compressive force. therefore, smaller pore sizes, specifically those ranging from 800 μm to 850 μm, are recommended for maintaining mechanical stability in implants. (a) variation by force (b) variation by pore size fig. 11 line graph of minimum safety factor changes from fig. 11, differences in the decline in safety factor values can be observed, influenced by force and pore size variation. fig. 11(a) shows minimum safety factor changes at different pore sizes with varied forces; the safety factor tends to decrease as pore size increases from 800 µm to 1000 µm. for a maximum load of 800 n, only the 800 µm pore size achieves a advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 293 safety factor close to 2.1. this indicates that material with an 800 µm pore size is strong enough to endure dynamic loads safely, making it suitable for applications requiring dynamic load tolerance without excessive cost. in contrast, other pore sizes, with safety factors below 2 at 800 n, may be less ideal for dynamic applications due to potential safety risks. fig. 11(b) illustrates pore size variation against applied force; only the 850 µm and 800 µm pore sizes maintain safety factors close to 1.5 to 2 at 800 n, specifically at 1.43 and 2.1, respectively. this analysis demonstrates that material with an 850 µm pore size provides sufficient safety to withstand static force, as its safety factor remains within the acceptable range without overprovisioning. in contrast, pore sizes exceeding 850 µm, with safety factors below 1.5, may be less suitable for static applications at 800 n. the 1.5 safety factor threshold is considered based on shash et al. [29] research on mandibular bone implants established that a minimum safety factor of at least 1.5 is required to ensure structural integrity while avoiding excessive material usage. this threshold provides a balance between mechanical performance and material efficiency, ensuring that the scaffold can withstand physiological loads while remaining cost-effective. if the safety factor is too high, as is often the case with smaller pores under low force, it results in excessive costs due to additional strength that is not required. hence, to optimize both cost and performance, a pore size of 800 µm at 800 n dynamic load is ideal for dynamic needs, while the 850 µm pore size is more suitable for static needs at the same load, providing a sufficient safety factor without being excessive. the results of this study align with previous research on lattice scaffold designs for mandibular implants. studies such as liu et al. [30] have investigated various lattice structures, including simple cubic, bcc, and side centered cubic, and reported comparable trends in mechanical performance. however, variations in pore size, porosity, and unit cell geometry may influence the overall scaffold performance, highlighting the need for further comparative analysis. compared to the study by wang et al. [26], which found that pore sizes of 900 µm and 1000 µm are more favorable for promoting osteoblast proliferation and differentiation, their mechanical strength is insufficient to withstand the maximum load on a mandibular bone implant. although larger pore sizes (900 µm to 1000 µm) enhance bone regeneration, their structural integrity might not be adequate for supporting functional loads. therefore, to complement the conclusions of wang et al. [26], pore sizes of 800 µm and 850 µm can be considered an optimal solution for determining scaffold pore size in mandibular bone implants, as they offer a balance between mechanical stability and potential for osteointegration. 5. conclusions this study successfully analyzed the mechanical strength of titanium alloy / ti-6al-4v in a cubic lattice beam scaffold structure with pore sizes ranging from 800 μm to 1000 μm under various compressive forces using fea software. the findings emphasize the influence of pore size on the structural performance and suitability of the scaffold for mandibular bone implant applications. key conclusions are summarized as follows: (1) scaffolds with pore sizes of 800 μm and 850 μm exhibit safety factors and von mises equivalent stresses within acceptable limits for compressive forces up to 800 n, ensuring structural safety and integrity. (2) at 800 n, the 800 μm pore size achieves a safety factor of 2.1, making it suitable for dynamic loads, while the 850 μm pore size with a safety factor of 1.43 is more appropriate for static loads. (3) despite having densities below 35%, the scaffold structure demonstrates excellent material utilization and production cost efficiency. the densities for 800 μm and 850 μm pore sizes are 25.92% and 20.55%, respectively, meeting mechanical strength requirements for mandibular bone implants. (4) the bmd printing method effectively produces scaffolds with safe and strong structures, highlighting the method's potential for cost-effective and material-efficient orthopedic implant development. advances in technology innovation, vol. 10, no. 3, 2025, pp. 283-295 294 future studies should focus on further investigating the impact of pore size on scaffold performance and suitability. suggested areas for improvement and focus include: (1) to improve reliability and applicability, cyclic load testing on physical samples is essential to evaluate the scaffold's resistance to repetitive forces, such as chewing. (2) further biocompatibility testing and analysis of porosity effects on bone growth are necessary to ensure optimal implant integration and long-term safety for patients. these results contribute to advancing titanium bone implant technology, providing a pathway to more effective, durable, and affordable solutions in orthopedic medicine. conflicts of interest the authors declare no conflict of interest. references [1] "brin kembangkan riset material untuk implan tulang," https://www.brin.go.id/news/110583/brin-kembangkan-riset-material-untuk-implan-tulang, accessed in 2024. [2] c. shuai, et al., "an nmgo containing scaffold: antibacterial activity, degradation properties and cell responses," international journal of bioprinting, vol. 4, no. 1, article no. 120, 2018. [3] j. he, f. xu, r. dong, b. guo, and d. li, "electrohydrodynamic 3d printing of microscale poly (ε-caprolactone) scaffolds with multi-walled carbon nanotubes," biofabrication, vol. 9, no. 1, article no. 015007, 2017. 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multiple-parameter optimization of darrieus vertical axis wind turbine for enhanced performance authors dhiman dey institute of energy, university of dhaka, dhaka, bangladesh gour chand mazumder department of electrical and electronic engineering, american international university-bangladesh, dhaka, bangladesh arnendu roy apu institute of energy, university of dhaka, dhaka, bangladesh himangshu ranjan ghosh institute of energy, university of dhaka, dhaka, bangladesh doi: https://doi.org/10.46604/aiti.2025.14914 keywords: avrami equation, qblade software, vertical axis wind turbine, wind turbine optimization abstract this paper aims to optimize a small vertical-axis wind turbine (vawt) by analyzing chord length, hub radius, and circular angle, and establishing a relationship between design parameters and performance. the approach involves evaluating five airfoils and identifying the best airfoil using qblade, based on comparisons of the power coefficient (cp), tip speed ratio (tsr), and the power output (p). mathematical relationships are developed through extrapolation using polynomial, logarithmic, and modified avrami equations. the result shows that the 's1046 17%' is the best-performing airfoil among the five. the optimum chord length to hub radius ratio yields the highest power output, and the impact of circular angle on performance is negligible. the avrami equation shows better fitness to the original data than the polynomial equation. the troposkien variant shows a higher cp over a wide range of tsr, while the straight blade produces higher power output across varying wind speed (v). references t. z. ang, m. salem, m. kamarol, h. s. das, m. a. nazari, and n. prabaharan, “a comprehensive study of renewable energy sources: classifications, challenges and suggestions,” energy strategy reviews, vol. 43, article no. 100939, 2022. p. muthukumar, d. k. sarkar, d. de, and c. k. de, innovations in sustainable energy and technology, 1st ed., singapore, springer singapore, 2021. m. hasan, p. dey, s. janefar, n. a. salsabil, i. j. khan, n. r. chowdhury, et al., “a critical analysis of wind energy generation potential in different regions of bangladesh,” energy reports, vol. 11, pp. 2152-2173, 2024. h. muhsen, w. al-kouz, and w. khan, “small wind turbine blade design and optimization,” symmetry, vol. 12, no. 1, article no. 18, 2019. a. i. altmimi, a. aws, m. j. jweeg, a. m. abed, and o. i. abdullah, “an investigation of design and simulation of horizontal axis wind turbine using qblade,” measurement science review, vol. 22, no. 6, pp. 253-260, 2022. m. r. badah and y. h. mahmood, “performance analysis of vertical axis wind turbine blades using double multiple stream tube process,” iraqi journal of science, vol. 63, no. 8, pp. 3366-3372, 2022. a. i. altmimi, m. alaskari, o. i. abdullah, a. alhamadani, and j. s. sherza, “design and optimization of vertical axis wind turbines using qblade,” applied system innovation, vol. 4, no. 4, article no. 74, 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vol. 2, no. 2, pp. 181-188, 2020. h. zhang, y. hu, and w. wang, “wind tunnel experimental study on the aerodynamic characteristics of straight-bladed vertical axis wind turbine,” international journal of sustainable energy, vol. 43, no. 1, article no. 2305035, 2024. h. s. davari, r. m. botez, m. s. davari, h. chowdhury, and h. hosseinzadeh, “numerical and experimental investigation of darrieus vertical axis wind turbines to enhance self-starting at low wind speeds,” results in engineering, vol. 24, article no. 103240, 2024. h. s. davari, r. m. botez, m. s. davari, h. chowdhury, and h. hosseinzadeh, “blade height impact on self-starting torque for darrieus vertical axis wind turbines,” energy conversion and management: x, vol. 24, article no. 100814, 2024. h. s. davari, m. s. davari, s. kouravand, and m. k. kurdkandi, “optimizing the aerodynamic efficiency of different airfoils by altering their geometry at low reynolds numbers,” arabian journal for science and engineering, vol. 49, pp. 15253-15288, 2024. h. s. davari, r. m. botez, m. s. davari, and h. chowdhury, “enhancing aerodynamic efficiency: shape modification of airfoils,” international journal of ambient energy, vol. 45, no. 1, article no. 2439441, 2024. h. s. davari, m. s. davari, r. m. botez, and h. chowdhury, “maximizing the peak lift-to-drag coefficient ratio of airfoils by optimizing the ratio of thickness to the camber of airfoils,” sustainable earth review, vol. 3, no. 4, pp. 46-61, 2023. m. a. dabachi, a. rahmouni, e. rusu, and o. bouksour, “aerodynamic simulations for floating darrieus-type wind turbines with three-stage rotors,” inventions, vol. 5, no. 2, article no. 18, 2020. m. a. dabachi, a. rahmouni, o. bouksour, “design and aerodynamic performance of new floating h-darrieus vertical axis wind turbines,” materials today: proceedings, vol. 30, no. 4, pp. 899-904, 2020. k. shirzad and c. viney, “a critical review on applications of the avrami equation beyond materials science,” journal of the royal society interface, vol. 20, article no. 203, 2023. b. cantor, the equations of materials, 1st ed., oxford university press, 2020. l. s. wang, w. cao, and s. hu, entropy and exergy in renewable energy, 1st ed., intechopen, 2022. r. a. khaddar, s. k. singh, n. d. kaushika, r. k. tomar, and s. k. jain, recent developments in energy and environmental engineering, lecture notes in civil engineering, 1st ed., springer nature singapore, 2023. h. s. davari, r. m. botez, m. s. davari, and h. chowdhury, “enhancing the efficiency of horizontal axis wind turbines through optimization of blade parameters,” journal of engineering, vol. 2024, no. 1, article no. 8574868, 2024. h. s. davari, s. kouravand, m. s. davari, and z. kamalnejad, “numerical investigation and aerodynamic simulation of darrieus h-rotor wind turbine at low reynolds numbers,” energy sources part a: recovery, utilization, and environmental effects, vol. 45, no. 3, pp. 6813-6833, 2023. h. s. davari, m. s. davari, r. m. botez, and h. chowdhury, “advancements in vertical axis wind turbine technologies: a comprehensive review,” arabian journal of science and engineering, vol. 50, no. 4, pp. 2169-2216, 2025. a. wongphat, s. wongcharee, n. chaiduangsri, k. suwannahong, t. kreetachat, s. imman, et al., “using excel solver’s parameter function in predicting and interpretation for kinetic adsorption model via batch sorption: selection and statistical analysis for basic dye removal onto a novel magnetic nanosorbent,” chemengineering, vol. 8, no. 3, article no. 58, 2024. c. onyutha, “a hydrological model skill score and revised r-squared,” hydrology research, vol. 53, no. 1, pp. 51-64, 2021. b. cantor, the equations of materials, the avrami equation: phase transformations, oxford academic, 2020. a. bishay, recent advances in science and technology of materials, 1st ed., new york: springer new york, 2012. downloads html pdf published 2025-10-13 how to cite [1] dhiman dey, gour chand mazumder, arnendu roy apu, and himangshu ranjan ghosh, “a multiple-parameter optimization of darrieus vertical axis wind turbine for enhanced performance ”, adv. technol. innov., vol. 10, no. 4, pp. 419–435, oct. 2025. more citation formats acm acs apa abnt chicago harvard ieee mla turabian vancouver download citation endnote/zotero/mendeley (ris) bibtex issue vol. 10 no. 4 (2025): october section articles license copyright (c) 2025 dhiman dey, gour chand mazumder, arnendu roy apu, himangshu ranjan ghosh this work is licensed under a creative commons attribution-noncommercial 4.0 international license. submission of a manuscript implies: that the work described has not been published before that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication. authors can retain copyright in their articles with no restrictions. is accepted for publication. authors can retain copyright of their article with no restrictions.   since jan. 01, 2019, aiti will publish new 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low naoh concentrations using a pressing approach khamphee jitchaiyaphum, cherdsak suksiripattanapong* department of civil engineering, faculty of engineering and technology, rajamangala university of technology isan, nakhon ratchasima, thailand received 18 november 2024; received in revised form 23 february 2025; accepted 25 february 2025 doi: https://doi.org/10.46604/aiti.2024.14516 abstract geopolymers are widely recognized as an eco-friendly alternative material. however, the impact of pressing stresses and low naoh concentrations on their properties remains underexplored. this research aims to investigate the effects of pressing stresses on unit weight, porosity, water absorption, and compressive strength of high-calcium fly ash geopolymer paste with low naoh concentrations. the low naoh concentrations of 0.5, 1.0, and 2.0 m, pressing stresses of 10, 20, and 30 mpa, and liquid-to-binder ratios of 0.10, 0.12, 0.14, 0.16, 0.18, and 0.20 by weight are used. the specimens of geopolymer paste are oven-dried at 60°c for 24 hours before evaluation. the testing results show that the compressive strength of casted geopolymer paste is between 2 to 15 mpa, with higher compressive strength associated with lower porosity. the water absorption rate is between 11% and 21% by weight, which has a higher water absorption rate as the porosity increases. keywords: compressive strength, geopolymers, low molar, pressing approach 1. introduction in residential buildings in rural thailand, hollow concrete blocks are considered an important alternative construction material because they are more economical than lightweight concrete blocks and fire clay bricks. non-bearing hollow concrete blocks, most often used on unreinforced walls with a thickness of 70 mm, are unique among the materials available on the market as they are utilized extensively across the country. generally, these blocks are made from cement mixed with small stones such as sand and rock dust in ratios of 1:2, 1:3, and 1:4 by weight, which provides different mechanical properties regarding unit weight and compressive strength. the blocks' production and characteristics are controlled per thai industrial standards on tis 58–2533, with a minimum compressive strength requirement of 2.5 mpa. however, ordinary portland cement (opc) is the main binder used to produce these blocks. the production of opc significantly contributes to global co2 emissions [1], accounting for approximately 8 % of global greenhouse gas emissions [2-3]. studying the properties of geopolymer materials as an opc substitute has been a recent area of interest. geopolymers are recognized as one of the new environmentally friendly alternative materials and are currently the focus of intensive development and research worldwide. they can be synthesized through geopolymerization from a solid aluminosilicate precursor leached with an alkaline activator, forming an amorphous and three-dimensional network structure at low temperatures [4-11]. * corresponding author. e-mail address: cherdsak.su@rmuti.ac.th english language proofreader: yen-chun hsieh advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 187 coal fly ash-based geopolymers are an attractive and environmentally friendly option for various construction applications compared to opc [12-18]. the coal fly ash (fa) is the main byproduct of the combustion process and is available in large quantities due to the lignite-fired power plants in thailand [15]. due to its high calcium content, fa provides rapid setting and high early strength compared to geopolymers made from other materials with low calcium content [19]. the workability and strength of geopolymer mortar from high calcium fa activated with sodium hydroxide (naoh) and sodium silicate (na2sio3) were investigated, showing that the geopolymer mortar's flow rate and compressive strength ranged from 110 to 135 ± 5% and 10-65 mpa, depending on the na2sio3:naoh ratio and naoh concentration [20]. moreover, the hydration processes of the high calcium fa-based geopolymer can transform sodium aluminosilicate hydrate (n-a-s-h) gels into calcium aluminosilicate hydrate (c-a-s-h) gels. the c-a-s-h gels effectively bind water to reduce permeability, resulting in a denser structure and higher strength performance than traditional low-calcium fa geopolymers [21]. however, the strength of geopolymers depends on many factors, such as the chemical composition and proportions of si and al. inappropriate ratios can prevent the atoms from forming a continuous chain, resulting in low strength and inefficient leaching. other factors include insufficient mixing time, the concentration of the alkaline solution used for leaching, moisture content within the geopolymer mixture, improper drying temperature, and too short drying time. these factors can cause the geopolymer framework to become unconnected. zheng et al. [22] found that the compressive strength and microstructure of fly ash-based geopolymer were strongly influenced by the dosage of the alkaline activator and the si/al molar ratio. the highest strength was achieved at an intermediate alkaline activator dosage and si/al ratio, and the optimal na/fly ash and si/al molar ratio was close to 2.8 mole/kg and 2.0, respectively. the higher alkaline activator dosage enhanced the structural disruption of the original aluminosilicate phases and a higher degree of polymerization of the geopolymer networks. takeda et al. [23] found that the weight of the fa geopolymer decreased as a result of water evaporation. the bonding mechanism of geopolymer particles was likely related to the presence of hydroxyl ions (oh) on each geopolymer particle. after being heated at 130 °c for 2 h, the particles containing oh can bond to each other by a dehydration reaction, releasing water to form a larger particle in three dimensions. the dense geopolymer with a high compressive strength was obtained. ramujee and potha raju [24] found that the fly ash-based geopolymer concrete cured at moderate temperatures, between 60 °c and 90 °c, has strong durability and high initial mechanical properties. dinh et al. [25] found that in fa-based geopolymer, calcium (ca) from ground granulated blast-furnace slag (ggbfs) and waste glass (wg) readily leaches out and reacts under both ambient and oven curing conditions, whereas silicon (si) only exhibits activity primarily in high-temperature environments. the reactivity of ca from ggbfs and wg improved compressive strength and water absorption up to 50 % and 30 %, respectively. moreover, based on the alkali leaching test, the most effective molar ratios (si/al = 3.5 – 4) demonstrated the highest compressive strength of 60 –70 mpa. therefore, molding a geopolymer using a low alkali concentration under pressure is one option explored in this research. this article aims to study the properties of geopolymer paste made from high-calcium fa activated with 0.5, 1.0, and 2.0 mole naoh. the liquid-to-binder ratio (l/fa) of 0.12, 0.14, and 0.16 by weight were used. the specimens were formed with a jack under bearing stress of 10 mpa, 20 mpa, and 30 mpa per 10 cm thickness on a 10 × 10 cm cross-section, held for 1 minute, and dried at 60 °c for 24 hours. the porosity, compressive strength, and water absorption of the samples were evaluated. furthermore, an equation was proposed to predict the compressive strength of fa geopolymer paste based on the known total porosity. advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 188 2. materials and methodology understanding the chemical and physical properties of the materials used, such as fa, na₂sio₃, and naoh, was essential before analyzing the unit weight, porosity, water absorption, and compressive strength of high-calcium fly ash geopolymer paste with low naoh concentrations. 2.1. materials coal fly ash (fa) used in this study was high-calcium fly ash from a thermal power plant in mae moh district, lampang province, thailand. it had a relatively spherical shape and smooth surface, as shown in the scanning electron microscopy (sem) images in fig. 1. according to blaine's air permeability test, the fa had a specific gravity of 2.2, an average particle size of 14.10 µm, and a specific surface area of 4,050 cm2/g. the results of the chemical composition analysis by xrf of the fa are shown in table 1. it was found that fa contains silicon dioxide (sio2) and aluminum oxide (al2o3) of 42.94 % and 24.46 %, respectively. the sum of sio2, al2o3, and ferric oxide (fe2o3) is more than 70 % by weight, and fa is classified as class c fa. it also contains more than 10 % by weight of calcium oxide (cao) and may be called high-calcium fly ash, according to astm c 618 [26]. in addition, it was found that fa had a loss on ignition (loi) value of 1.48%, which was lower than the astm c 618 [26] that specified the loi value not exceeding 6% w/w. the quantitative x-ray diffraction (xrd) analysis based on the rietveld method as the area below the curves which carried out using bruker’s topas. the percentages of amorphous sio2 of fa had a high amorphous content was 80.5% (by mass) or low crystallinity, as shown in fig. 2. the liquid sodium silicate (na2sio3) with 30 % sio2 and 9 % na2o was used at 1% by weight of fa. the sodium hydroxide (naoh) used in this study was industrial-grade flake naoh with a solid purity of 99%. before the experiment, naoh solution was prepared to achieve a purity of 100% by adding 1% naoh and dissolving it in various water concentrations at a temperature of 23 ±2 °c, as shown in table 2. the test results for preparing a naoh solution or liquid (l) with a concentration level from 0.5 m to 14 m, dissolved in water within a flask with a volume of 1000 ml at a temperature of 23±2°c, are shown in table 2. the relationship between the molar level and the liquid (naoh + water) was linear. the equation for this linear function was y = 26.18x + 1051.6, with a multiple coefficient of determination (r²) of 0.99, as shown in fig. 3. this equation is used to calculate the proportions of liquid, naoh, and water for different concentrations of naoh solutions. it is also useful for determining the proportions of geopolymer paste mixtures. fig. 1 sem image of fa advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 189 table 1 chemical composition in oxide form of fa chemical compositions fa (% by mass) sio2 42.94 al2o3 24.46 fe2o3 12.34 cao 15.27 mgo 1.65 k2o 1.33 so3 2.01 loi 1.48 fig. 2 xrd pattern of coal fly ash table 2 concentration of naoh solution per 1 liter concentration of naoh (mole) 100 % purity of naoh (g) water (g) liquid (g) the specific gravity of liquid at 23 ±2 °c 0.5 20.2 1057.6 1077.8 1.08 1.0 40.4 1046.5 1086.9 1.09 2.0 80.8 1025.2 1106.0 1.11 2.5 101.0 1015.0 1116.0 1.12 4.0 161.6 986.4 1148.0 1.15 5.0 202.0 969.0 1171.0 1.17 7.5 303.0 931.0 1234.0 1.23 10.0 404.0 901.0 1305.0 1.31 12.0 484.8 882.8 1367.6 1.37 14.0 565.6 869.7 1435.3 1.44 10 20 30 40 50 60 2 (degrees) in te ns it y (a .u .) fa c q q : q uartz m : m ullite c : a nhydrite q q q m q q m q advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 190 fig. 3 relationship between molarities and liquid 2.2. mix proportions and testing to obtain the optimum liquid content for preparing fa geopolymer paste, the fa with naoh concentration of 0.5 m was dissolved using l/fa ratios of 0.10, 0.12, 0.14, 0.16, 0.18, and 0.20 and na2sio3 content was fixed at 1% by weight of the fa. firstly, the fa dissolved with l for 10 minutes. then, the fresh fa geopolymer paste was poured into 10 × 10 × 10 cm cube molds for three specimens, and a pressure jack on the top surface was used to apply a maximum bearing stress of 10 mpa for 1 minute. after pressing, the fa geopolymer paste was removed from the molds and sealed with plastic film before drying it at 60 °c for 24 hours. after drying, the samples were tested for compressive strength and dry unit weight. the geopolymer paste had a dry density ranging from 1,367 to 1,760 kg/m³, with an average of approximately 1,559 kg/m³, as shown in table 3. the l/fa ratio of 0.16 resulted in the lowest compressive strength and dry unit weight values. meanwhile, the optimum compressive strength was found at an l/fa ratio of 0.20. however, the mixture with an l/fa ratio of 0.10 had poor compression molding efficiency due to the small amount of liquid, making the mixture dry and stiff. conversely, the mix with an l/fa ratio of 0.20 tended to leak out of the mold during casting at 10 mpa pressure. for this reason, the l/fa ratios used in this research ranged from 0.12-0.16. table 3 compressive strength and dry unit weight of fa geopolymer paste with 0.5 m naoh and pressing of 10 mpa no. l/fa compressive strength (mpa) dry unit weight (kg/m3) 1 0.10 0.96 1,617 2 0.12 0.64 1,537 3 0.14 0.98 1,493 4 0.16 0.55 1,367 5 0.18 1.63 1,577 6 0.20 3.64 1,760 the geopolymer paste mix proportions are provided in table 4. all ingredients were used with l/fa ratios of 0.12, 0.14, and 0.16. the naoh solutions contained 0.5, 1.0, and 2.0 mole (m). na2sio3 content was added to all mixtures in 1% by weight of the fa. before mixing the geopolymer paste, the materials were prepared by weighing the fa, na2sio3, and naoh y = 26.18x + 1051.6 r² = 0.99 0 200 400 600 800 1000 1200 1400 1600 1800 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 l iq u id , g concentrate of naoh, m 0.5 < x < 14 advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 191 solution of various concentrations, as shown in table 4. then, pour the fa into the mixing tank, followed by the naoh solution. continue mixing for at least 10 minutes to dissolve the fa effectively. next, the na2sio3 was added and then mixed until a uniform paste. the fresh fa geopolymer paste samples were poured into the cube molds and slightly tamped on the outside. then, they were either compacted by hand or covered with a 10 mm thick steel plate. for compacting with a hydraulic press, the samples were compressed at maximum bearing stresses of 10 mpa, 20 mpa, and 30 mpa and held for 1 minute. the pressed geopolymer sample was used in this study because it exhibited higher strength than the cast geopolymer [27] and successfully withstood bearing stresses of 15 and 20 mpa, as reported by alshaaer [28] and prasanphan et al. [29]. however, for comparison, the control mixture (con) was compacted by hand. the fresh fa geopolymer paste was removed from the molds and sealed with plastic film. the samples were then dried in an oven at 60 °c for 24 hours. afterward, 10 cm × 10 cm × 10 cm specimens were used for compressive strength, water absorption, unit weight, and total porosity tests. fig. 4 shows the compressive strength test setup of the sample. table 4 proportions of geopolymer paste mixture in 1 cubic meter mix no. symbol fa (kg) naoh water (kg) liquid, l (kg) na2sio3 (kg) l/fa molar (kg) 1 con 1,800 0.5m 4.7 247.3 252 18 0.14 2 0.12fa0.5m 1,800 0.5m 4.0 212.0 216 18 0.12 3 0.12fa1.0m 1,800 1.0m 8.0 208.0 216 18 0.12 4 0.12fa2.0m 1,800 2.0m 15.8 200.2 216 18 0.12 5 0.14fa0.5m 1,800 0.5m 4.7 247.3 252 18 0.14 6 0.14fa1.0m 1,800 1.0m 9.4 242.6 252 18 0.14 7 0.14fa2.0m 1,800 2.0m 18.4 233.6 252 18 0.14 8 0.16fa0.5m 1,800 0.5m 5.4 282.6 288 18 0.16 9 0.16fa1.0m 1,800 1.0m 10.7 277.3 288 18 0.16 10 0.16fa2.0m 1,800 2.0m 21.0 267.0 288 18 0.16 fig. 4 compressive strength test setup of sample advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 192 2.3. compressive strength test the method for testing the compressive strength of samples follows en 196-1. this is done by pressing the sample to determine the ultimate compressive force before failure at a pressure rate between 0.11 and 0.27 mpa per second. the compressive strength is measured in mpa and calculated by dividing the ultimate compressive force by the cross-sectional area, as shown below. compressive strength (mpa) a p = (1) 2.4. water absorption test the water absorption of samples was tested by soaking 10 × 10 × 10 cm cubes (3 samples) in water for 24 hours. after soaking, the samples were removed from the water, and excess surface water was absorbed with a cloth. the samples were then weighed within 30 seconds. the recorded weight included the samples and the water that had permeated it. the samples were dried at 110 ±5°c for 24 hours and cooled to room temperature. the water absorption value was calculated as the average of 3 samples according to astm c 642, as shown below. water absorption (%) = 𝑊𝑠𝑎𝑡 − 𝑊𝑑𝑟𝑦 𝑊𝑑𝑟𝑦 × 100 (2) where wsat = the weight of the saturated sample and wdry = the weight of the dried sample. 2.5. dry unit weight test the dry unit weight of the samples was determined after drying for 24 hours. this was done by weighing the samples in kilograms (kg) and dividing by their volume in cubic meters (m³). the results are presented as the averages of three samples, expressed in kilograms per cubic meter (kg/m³), as shown below. dry density (kg 𝑚3⁄ ) = 𝑀 𝑉 (3) 2.6. total porosity test the porosity of the samples was determined using the saturation apparatus developed by cabrera and lynsdale at the university of leeds. porosity measurements were conducted on 5 cm cube slices drilled out of the center of a 10 cm cube. the slices were dried at 110±5°c until a constant weight was achieved. they were then placed in a desiccator under vacuum for at least 3 hours, after which the desiccator was filled with de-aired, distilled water, as shown in fig. 5. the porosity was calculated using below. 𝑃 (%) = 𝑊𝑠𝑎𝑡 − 𝑊𝑑𝑟𝑦 𝑊𝑠𝑎𝑡 − 𝑊𝑤𝑎𝑡 × 100 (4) where p is saturation porosity, wsat is the weight in air of the saturated sample, wwat is the weight in water of the saturated sample, and wdry is the weight of the oven-dried sample. advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 193 (a) measurement of the weight of the oven-dried sample (b) measurement of weight in water of the saturated sample fig. 5 porosity test of the sample 2.7. x-ray diffraction (xrd) dried fa sample powder was sifted through a no. 100 sieve (150 μm openings). a sample of powder weighing approximately 1 g was used for xrd analysis. the xrd scans were performed for 2θ between 10° and 65° with an increment of 0.02°/step at a scan speed of 0.5 sec/step. a quantitative xrd analysis determined the amorphous fa phases using bruker’s topas software. 3. results and discussion the effects of low naoh concentrations (0.5, 1.0, and 2.0 m), pressing stresses (10, 20, and 30 mpa), and liquid-tobinder ratios (0.10, 0.12, 0.14, 0.16, 0.18, and 0.20 by weight) on high-calcium fly ash geopolymer paste were evaluated. additionally, the unit weight, porosity, water absorption, and compressive strength of high-calcium fly ash geopolymer paste with low naoh concentrations are discussed in the following sections. 3.1. compressive strength fig. 6 illustrates the compressive strength of fa geopolymer paste compacted by hand and pressed with a hydraulic jack under bearing stress of 10 mpa, 20 mpa, and 30 mpa. the liquid-to-binder ratio (l/fa) of 0.12, 0.14, and 0.16 and the naoh concentrations of 0.5 m, 1.0 m, and 2.0 m were used. it was found that the control mix (con) used naoh of 0.5 m as a leaching fa and compacted it with the hand, giving a compressive strength of 24 mpa. the casted geopolymer paste samples were dried at 60 °c for 24 h. the compressive strength increased with increasing bearing stress and naoh concentration. for example, the compressive strengths of fa geopolymer paste were 0.7 mpa, 0.9 mpa, and 1.4 mpa for bearing stress of 10 mpa, 20 mpa, and 30 mpa, respectively. additionally, for a bearing stress of 10 mpa, the compressive strengths of fa geopolymer paste were 0.7 mpa, 0.9 mpa, and 1.4 mpa for 0.12fa0.5m, 0.12fa1.0m, and 0.12fa2.0m, respectively. this result is due to the influence of naoh concentration on fa leaching, which, combined with extrusion, brought geopolymer particles closer together, forming chemical bonds of silicate and aluminosilicate that linked to create a chain polymer structure [30]. advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 194 fig. 6 compressive strength of fa geopolymer paste table 5 relative compressive strength of fa geopolymer paste mix no. symbol pressing stress (mpa) compressive strength (mpa) relative compressive strength (%) 1 con 2.4 100 2 0.12fa0.5m 10 0.7 29 3 0.12fa1.0m 0.9 38 4 0.12fa2.0m 1.4 58 5 0.12fa0.5m 20 0.9 38 6 0.12fa1.0m 1.0 42 7 0.12fa2.0m 1.7 71 8 0.12fa0.5m 30 1.4 58 9 0.12fa1.0m 1.5 63 10 0.12fa2.0m 1.9 79 11 0.14fa0.5m 10 2.1 88 12 0.14fa1.0m 4.7 196 13 0.14fa2.0m 9.0 375 14 0.14fa0.5m 20 5.2 217 15 0.14fa1.0m 6.2 258 16 0.14fa2.0m 10.2 425 17 0.14fa0.5m 30 5.5 229 18 0.14fa1.0m 14.2 592 19 0.14fa2.0m 15.0 625 20 0.16fa0.5m 10 2.2 92 21 0.16fa1.0m 1.1 46 22 0.16fa2.0m 1.4 58 23 0.16fa0.5m 20 3.2 133 24 0.16fa1.0m 1.9 79 25 0.16fa2.0m 1.7 71 26 0.16fa0.5m 30 27 0.16fa1.0m 28 0.16fa2.0m this result differs from takeda et al. [23], who observed that high-density pure-phase geopolymers formed within a few hours using a warm-pressing technique. their study achieved compressive strengths as high as 149 mpa by pressing at 200 mpa and 130 °c for 1 hour, with heat and pressure accelerating the geopolymerization and hardening of the fly ash, sodium 2 .4 0 .7 0 .9 1 .4 0 .9 1 1 .5 1 .4 1 .7 1 .92 .1 5 .2 5 .5 4 .7 6 .2 1 4 .2 9 1 0 .2 1 5 2 .2 3 .2 1 .1 1 .9 1 .4 1 .7 0 2 4 6 8 10 12 14 16 18 20 compaction with hand 10 20 0 c o m p re ss iv e st re n g th , m p a bearing stress, mpa con 0.12fa0.5m 0.12fa1.0m 0.12fa2.0m 0.14fa0.5m 0.14fa1.0m 0.14fa2.0m 0.16fa0.5m 0.16fa1.0m 0.16fa2.0m advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 195 hydroxide, and water glass (sodium silicate) raw materials. additionally, a sample with a high naoh concentration of 14 m and pressing at 25 mpa achieved a compressive strength of 37.3 mpa, as reported by shee ween et al. [27]. compared to the compressive strength of concrete blocks (2.5 mpa) specified in tis 58–2533, the fa geopolymer paste with a l/fa ratio of 0.14, an naoh concentration of 2.0 m, and a bearing stress of 30 mpa exhibited a maximum compressive strength of 15 mpa, meeting the standard requirement. table 5 shows the relative compressive strength of fa geopolymer paste compacted by hand and pressed with hydraulic jack under bearing stress of 10 mpa, 20 mpa, and 30 mpa. the l/fa of 0.12, 0.14, and 0.16 and the naoh concentrations of 0.5 m, 1.0 m, and 2.0 m were used. it was found that casting the mixture with a liquid-to-binder ratio of 0.16 under a bearing stress of 30 mpa was not feasible, as the mixture leaked out of the mold and caused it to break. this failure occurred because the higher liquid content increased the mixture’s flowability and reduced its viscosity, making it more prone to leakage through gaps. additionally, excessive pressing stress generated higher excess pore water pressure, further contributing to the mold’s failure. 3.2. water absorption the average water absorption of geopolymer paste compacted by hand and pressed with hydraulic jack under maximum pressing stress of 10 mpa, 20 mpa, and 30 mpa is shown in fig. 7. it was found that the control mix (con), which used 0.5 m naoh and was compacted by hand, exhibited a water absorption rate of 17%. the pressed fa geopolymer paste at a stress of 10 mpa showed water absorption rates of 29%, 28%, and 25% for the 0.12fa0.5m, 0.12fa1.0m, and 0.12fa2.0m mixtures, respectively. at a 20 mpa stress, the water absorption rates were 21%, 24%, and 20% for the same mixtures, respectively. at 30 mpa, the rates were 21%, 23%, and 19%, respectively. overall, water absorption rates decreased as pressing stress increased. the water absorption rate also decreased as naoh concentration increased under compression stresses up to 10 mpa. the additional water reduced the molarity in the aqueous phase, decreasing the extent of polymerization and preventing the formation of a compact gel, as suggested by singh et al. [9]. furthermore, excessive liquid caused excess water to evaporate, leaving voids in the geopolymer brick and consequently increasing water absorption. however, differences in naoh concentration did not noticeably affect water absorption at stresses between 20 and 30 mpa. the liquid-to-binder ratio of 0.14 produced a lower water absorption rate than ratios of 0.12 and 0.16, as the optimal liquid content allowed for higher compacting efficiency, reducing voids and lowering water absorption [7-8]. fig. 7 water absorption of fa geopolymer paste 1 7 2 9 2 1 2 1 2 8 2 4 2 3 2 5 2 0 1 9 2 1 1 3 1 1 1 5 1 3 1 1 1 4 1 3 1 1 2 2 1 7 2 6 1 9 2 5 2 0 0 5 10 15 20 25 30 35 40 compaction with hand 10 20 0 w at er a b so rp ti o n , % bearing stress, mpa con 0.12fa0.5m 0.12fa1.0m 0.12fa2.0m 0.14fa0.5m 0.14fa1.0m 0.14fa2.0m 0.16fa0.5m 0.16fa1.0m 0.16fa2.0m advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 196 3.3. dry unit weight the average dry weight of fa geopolymer paste compacted by hand and pressed with hydraulic jack under maximum pressing stress of 10 mpa, 20 mpa, and 30 mpa is shown in fig. 8. it was found that the control mix (con) had a dry weight of 1,735 kg/m³. the dry unit weight of fa geopolymer paste increased with higher compression stress and naoh concentration. for example, fa geopolymer paste pressed with stresses of 10 mpa, 20 mpa, and 30 mpa yielded dry unit weights of 1,624 kg/m³, 1,660 kg/m³, and 1,704 kg/m³, respectively, for the 0.12fa0.5m mixture; 1,651 kg/m³, 1,700 kg/m³, and 1,776 kg/m³ for the 0.12fa1.0m mixture; and 1,695 kg/m³, 1,778 kg/m³, and 1,810 kg/m³ for the 0.12fa2.0m mixture. compression molding at maximum pressing stresses of 10 and 20 mpa yielded optimal dry unit weights, particularly for the 0.14fa2.0m mixture. however, at maximum pressing stress of 30 mpa, slightly different optimal dry unit weights were observed for the 0.14fa0.5m, 0.14fa1.0m, and 0.14fa2.0m mixtures, as shown in fig. 7. this is because the liquid content and pressing stress influence the unit weight of geopolymer formation, consistent with the findings of shee-ween et al. [27]. fig. 8 dry unit weight of fa geopolymer paste 3.4. relationship between compressive strength and total porosity fig. 9 shows the average total porosity of fa geopolymer paste compacted by hand and pressed with a hydraulic jack under stresses of 10 mpa, 20 mpa, and 30 mpa. liquid-to-binder ratios (l/fa) of 0.12, 0.14, and 0.16 and naoh concentrations of 0.5 m, 1.0 m, and 2.0 m were used. the control mix (con) had a total porosity of 35%. the total porosity of the fa geopolymer paste decreased as pressing stress increased. for example, the 0.12fa0.5m fa geopolymer paste pressed at 10 mpa, 20 mpa, and 30 mpa showed total porosities of 39%, 36%, and 33%, respectively. the correlation between compressive strength and total porosity of fa geopolymer paste decreased with increasing porosity. it was found that an exponential function in the form of y = 479.61e-0.101x, with a multiple coefficient of determination (r²) of 0.95, best describes the relationship, where x represents the total porosity of fa geopolymer paste. similar results have also been reported by other researchers [23]. fa geopolymer paste provided high compressive strength due to its low porosity, achieved through casting under high pressure. this effect depended on the l/fa ratio. a high l/fa ratio reduced viscosity, increased fluidity, and caused geopolymer paste leakage during high-pressure molding, resulting in increased porosity. this study found that the optimum l/fa ratio for all pressures was 0.14. 1 ,7 3 5 1 ,6 2 4 1 ,6 5 1 1 ,6 9 5 1 ,6 6 0 1 ,7 0 0 1 ,7 7 8 1 ,7 0 4 1 ,7 7 6 1 ,8 1 0 1 ,7 4 2 1 ,8 1 0 1 ,9 5 4 1 ,8 6 4 1 ,8 3 3 1 ,9 6 3 1 ,9 5 5 1 ,9 6 9 1 ,9 7 5 1 ,8 2 5 1 ,8 8 2 1 ,7 0 1 1 ,8 4 0 1 ,7 1 6 1 ,7 6 8 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200 2,400 2,600 2,800 compaction with hand 10 20 0 d ry u n it w ei g h t, k g /m 3 bearing stress, mpa con 0.12fa0.5m 0.12fa1.0m 0.12fa2.0m 0.14fa0.5m 0.14fa1.0m 0.14fa2.0m 0.16fa0.5m 0.16fa1.0m 0.16fa2.0m 0 advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 197 fig. 9 relationship between compressive strength and total porosity 4. conclusions the physical and mechanical properties of fly ash geopolymer paste with low naoh concentrations using a pressing approach were evaluated in this study. the findings can be summarized as follows: (1) the increasing naoh concentration and bearing stress significantly enhance the compressive strength of fa geopolymer paste. the improved strength is attributed to naoh-facilitated fa leaching and closer particle alignment during extrusion, which promotes the formation of a robust silicate and aluminosilicate polymer network. (2) the increasing pressing stress and naoh concentration generally reduced water absorption rates in fa geopolymer paste. additionally, a liquid-to-binder ratio of 0.14 minimized voids, further decreasing water absorption. (3) the study shows that higher compression stress and naoh concentration increase the dry unit weight of fa geopolymer paste, with optimal weights observed at specific liquid-to-binder ratios. (4) the increasing compressive strength in fa geopolymer paste is associated with reduced porosity, achieved through highpressure compaction and an optimal l/fa ratio of 0.14. the fa geopolymer paste in this research provided higher compressive strength than ordinary portland cement concrete blocks (2.5 mpa), as specified in tis 58–2533. future research should focus on microstructural properties, such as sem with eds analysis or ft-ir analysis, to investigate the effects of casting pressure on the compressive strength of fly ash geopolymer paste with low naoh concentrations. acknowledgments the authors acknowledge the financial support of the rajamangala university of technology isan, thailand, for the research fund from the income budget of the faculty of engineering and technology in year 2023, as well as the supporting research funds for industry; surf (no. rdg6150052). conflicts of interest the authors declare no conflict of interest. y = 479.61e-0.101x r² = 0.95 0 2 4 6 8 10 12 14 16 18 20 0 5 10 15 20 25 30 35 40 45 c o m p re ss iv e st re n g th , m p a total porosity, % 12 < x < 9 con 10 20 0 mpabearing stress, advances in technology innovation, vol. 10, no. 2, 2025, pp. 186-199 198 references [1] h. zeng, s. qu, y. tian, y. hu, and y. li, “ recent progress on graphene oxide for nextgeneration concrete: characterizations, applications and challenges,” journal of building engineering, vol. 69, article no. 106192, 2023. 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[30] p. yoosuk, c. suksiripattanapong, g. hiroki, t. phoo-ngernkham, j. thumrongvut, p. sukontasukkul, et al., “performance of polypropylene fiber-reinforced cellular lightweight fly ash geopolymer mortar under wet and dry cycles,” case studies in construction materials, vol. 20, article no. e03233, 2024. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 english language proofreader: si-yu lin a review of advances in bio-inspired visual models using event-and frame-based sensors aya zuhair salim*, luma issa abdul-kareem department of control and systems engineering, university of technology, baghdad, iraq received 16 august 2024; received in revised form 29 october 2024; accepted 01 november 2024 doi: https://doi.org/10.46604/aiti.2024.14121 abstract this paper reviews visual system models using eventand frame-based vision sensors. the event-based sensors mimic the retina by recording data only in response to changes in the visual field, thereby optimizing realtime processing and reducing redundancy. in contrast, frame-based sensors capture duplicate data, requiring more processing resources. this research develops a hybrid model that combines both sensor types to enhance efficiency and reduce latency. through simulations and experiments, this approach addresses limitations in data integration and speed, offering improvements over existing methods. state-of-the-art systems are highlighted, particularly in sensor fusion and real-time processing, where dynamic vision sensor (dvs) technology demonstrates significant potential. the study also discusses current limitations, such as latency and integration challenges, and explores potential solutions that integrate biological and computer vision approaches to improve scene perception. these findings have important implications for vision systems, especially in robotics and autonomous applications that demand real-time processing. keywords: bio-inspired model, computer vision, event-based sensor, optic flow, dynamic vision sensor (dvs) 1. introduction technological advancements in robotics and artificial intelligence have propelled the development of computer vision models that emulate human visual capabilities, with dvs and frame-based vision sensors playing critical roles in this advancement. this paper aims to delve into the evolution of computer vision models inspired by visual systems, using these sensors to improve computer systems' capacity to efficiently and effectively perceive and understand their surroundings. previous research in this sector has highlighted the need to combine continuous data streams from dvs sensors with framebased data to improve precision and efficiency in computer vision [1-2]. building a bio-inspired model for visual perception remains a challenge; many researchers have developed models inspired by the dorsal pathway, which is concerned with identifying an object in visual space, and is also called the motion pathway; on the other hand, the ventral pathway, which is focused on form, color, texture, has been studied by other researchers and is referred to as the form pathway. the question here is how data can be collected from two types of sensors, event-based and frame-based sensors, to simulate the visual perception of both pathways by processing the motion data and the form data for an object in the visual scene. building a bio-inspired model for visual perception remains a challenge. many researchers have developed models inspired by the dorsal pathway, which identifies where an object is in visual space, also known as the motion pathway. on the other hand, the ventral pathway, which is concerned with form, color, and texture, is the focus of other researchers and is referred to as the form pathway. merging motion and form data to identify objects in a visual scene could unlock new possibilities for real-world applications, including industrial automation, autonomous robotics, augmented reality, * corresponding author. e-mail address: cse.22.06@grad.uotechnology.edu.iq advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 45 and virtual reality [3]. this approach aims to create more effective and physiologically accurate visual processing. the range of vision tasks has expanded due to recent advances in deep learning approaches for optical flow estimation and reinforcement learning, but incorporating dvs into these models remains a challenge. to complement these gaps, this study aims to highlight the main shortcomings in the existing research while offering a thorough overview of the state-of-the-art in frame-based sensor integration and dvs. it also seeks to provide insights into how bio-inspired systems imitate the processing powers of the brain and can simplify processing while lowering data redundancy. deep learning in optical flow estimation applications includes high-level vision tasks such as recognition, reconstruction, and segmentation, as well as low-level vision tasks including feature detection, tracking, and optical flow. this technique provides two variants of ultrasound flow (us flow). one variation is a pwc-like model based on a modification of pyramid, warping, and cost volume (pwc-net). it incorporates two spike streams that pass through a common dynamic timing representation module before routing to existing backbones in an end-to-end architecture [4]. pwc is an optical flow estimation technique utilizing images at multiple resolutions to capture details, aligning them across different scales, and employing a cost volume to represent pixel-level differences between frames for accurate motion estimation. pwc-net, on the other hand, enhances this technique by integrating neural networks, significantly improving the accuracy and efficiency of motion estimation at multiple levels of detail. computational visual processing mechanisms are categorized into bio-inspired and computer vision models, which focus on tasks such as segmentation and edge detection [5]. for the purpose of enhancing accuracy and efficiency in visual data analysis. deep reinforcement learning techniques have also been applied to further optimize these processes and achieve higher performance. this paper is organized as follows. section 2 covers visual perception and bio-inspired models, focusing on biological systems that inspire computational models. sections 3 and 4 delve into the evolution and key techniques of computer vision models, respectively. section 5 reviews visual sensors, detailing both frame-based and event-based sensors, such as dvs. in section 6, the discussion addresses depth estimation using sensors, exploring how sensors are used to perceive depth. section 7 presents the data-driven tools employed in the field. section 8 highlights applications of visual system models across various industries. finally, section 9 summarizes the findings and implications of the study, leading to the conclusions presented in section 10. 2. visual perception and bio-inspired models examining biological vision systems, particularly the human retinal system, is essential before discussing bio-inspired vision sensors. the human retinal system comprises bipolar cells, ganglion cells, and photoreceptors. these convert light into electrical pulses, which travel through ganglion and bipolar cells before entering optical fibers, which transmit them to the brain for interpretation of these signals. fig. 1 presents a schematic depiction of the retina network [6]. fig. 1 (colour online) retinal network schematic illustration [6] advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 46 ganglion cells, specifically x-cells and y-cells, play a crucial role in this process. x-cells are located in the parvocellular pathway, which accounts for 80% of nerve fibers and conveys patterns, spatial features, and color information. this system, known as the biological "what" system, is complemented by the magnocellular pathway, which processes changes related to movement, distance, and speed, commonly referred to as the "where" system [6-7]. concepts from the biological visual system are employed in artificial intelligence models for visual perception and deep learning [8]. these models enhance computational performance, enable rapid response times, maintain high computing efficiency, and support discrimination among elements in images and data [9-10]. dvs operates at a human retina level, capturing scene changes using the event-based sensing method. such selectivity can be observed in ganglion cells where only movement evokes action, reducing data load and power consumption [11]. this development ensures that ai models are highly efficient in low-latency, low-power applications usage including robotic systems and autonomous vehicles. moreover, this represents one of the most efficient temporal pathways for human vision, capable of handling complex visual tasks. foveal covert receptors located in the rostral pole of the optic tract are triggered by movement and transient ganglion cells, a concept mirrored by dvs, which processes only field changes to improve operational speed in devices such as surveillance and self-driving cars [12-13]. this closely links dvs to biological visual systems, bridging the gap between visual biology and sensor technology [14-15]. in humans, the primary visual cortex (v1) is a foremost component of the visualization process. it analyzes eye signals, converts them into understandable formats, and contributes to binocular interaction. for the correct appreciation of the surroundings, and making agreeable decisions, it is necessary to utilize motion, contours, and borders of visual stimuli, which are the functions of v1 in the brain [8,14,16-17]. bio-inspired vision systems are expected to improve intelligent structures and self-learning mechanisms while decreasing energy consumption in areas like space imaging, robotics, surveillance, and object identification [18]. in the case of capturing real motion on event-based or frame-based sensors, dvs processes only a small portion of the visual movement taking place, thereby lowering power requirements and processing time. this results in superior performance in high-motion scenarios such as self-driving cars and high-speed surveillance. dvs also improves security and precision via real-time visual processing. according to gallego et al. (2020), dvs outperforms conventional systems in estimating motion in 2d space via the moving objects and images, enabling bio-inspired systems in practical cases where traditional systems often face high delay and processing power requirements. 3. computer vision for many years, computer vision has been a prominent research topic, with applications ranging from photogrammetry to medical imaging, car safety, machine inspection, and beyond [3, 19-20]. computer vision increases the accuracy of human action detection by analyzing data from dynamic vision devices and extracting morphological and kinematic information. this provides a useful and effective way of evaluating dynamic observational data [3, 21-23]. although deep neural networks (dnns) have revolutionized computer vision, debates continue about their role in vision research. dnns need to exhibit robust object identification capabilities and recognize objects under changing 3d viewing angles and distortions. challenges such as manipulated adversarial examples underscore the differences between dnns and human vision perception, rendering them promising yet insufficient representations vision [8-20]. advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 47 this study demonstrates the proof of concept (poc) of reducing energy consumption by utilizing central processing units (cpus), graphical processing units (gpus), video processing units (vpus), and digital signal processors (dsps) to save power and mitigate carbon emissions in technology. techniques from sensor visual perception studies demonstrate non-convolutional methodologies for understanding sensory input, and integrating perceptrons with memory [24]. fig. 2 illustrates three types of systems performing the same task. (a) the retina mechanism (b) the convolution visual system (c) hardware design for vision processing fig. 2 systems and mechanisms of visual processing [24] 4. computer vision models this technique analyzes and tracks the movement of objects in photos and videos, and is considered an important tool in fields such as intelligent robotics, motion analysis [25], and automatic image correction enhancement [11]. optic flow refers to the global motion during movement, characterized by stimuli with complex speed gradients. its speed increases with the viewing angle, rendering greater velocities more significant. neurophysiological data indicates that selectivity for ocular flow originates in area medial superior temporal (mst), influenced by area v5/middle temporal (mt). imaging and lesion studies reveal a broad cortical network involved in optic flow perception. age-related effects on motion processing and signal complexity may lead to significant perceptual decline. limited research provides minimal evidence of perceptual decline, with heading detection thresholds ranging from 1.18 in young to 1.98 in older individuals. lich and bremmer's study reveals that older individuals exhibit lower accuracy in determining heading direction using a reference ruler, emphasizing the need for more detailed measures [26-27]. optical flow estimation presents a challenge in computer vision, as it requires regularization to estimate the object's velocity without prior knowledge of the scene's geometry or motion. event-based optical flow estimation is challenging due to the novel way visual information is presented as events. traditional cameras determine optical flow by comparing two advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 48 consecutive pictures. over the past two decades, methods have improved, with new concepts developed to overcome existing limitations. the quadratic regularization in the horn and schunck model was replaced by smoothness constraints, facilitating the development of more advanced computer-based applications [13-14, 28-31]. researchers have developed state-of-the-art deep learning models to address performance challenges in object recognition within dynamic video data. applications of video analysis and tracking with advanced sensors, include video monitoring, movement detection, optical flow analysis, rgb-d imaging devices, infrared (ir) detectors, radar systems, light detection and ranging (lidar) technology, digital photography, augmented reality (ar), and security monitoring. the deep-see framework employs computer vision and deep convolutional neural networks for real-time object detection, tracking, and recognition in outdoor navigation. the framework identifies both static and moving objects without prior knowledge, employing motion-based monitoring and visual similarity to predict object placements. the deep-see framework is utilized in an innovative assistive device designed to enhance cognitive abilities and safety for visually impaired individuals navigating urban environments. validation with a 30-element video dataset demonstrates its high accuracy and robustness [32]. this study focuses on object detection, identification, and classification. experimental findings indicate that an improved version of the you only look once (yolo) model surpasses traditional algorithms in categorizing distant scenes with moving objects, achieving a 98.94% accuracy on both public and custom datasets. the yolo algorithm is employed for various tasks, including classification training pre-trained on imagenet. standard data augmentation techniques are applied, with 160 training epochs, a 224 x 224 input image size, and an initial learning rate of 0.1 [33-34]. furthermore, 33 convolution layers of 11 layers and 1024 filters are added after the final convolution layer for detection tasks. in yolov2 and similar models, category probabilities are associated with each box instead of a grid, contributing to increased inference time. this evolution culminates in the development of yolov10 [35-36]. modern vision system models employ an attention mechanism [37]. the authors introduce a "transformer" network design that relies exclusively on attention mechanisms rather than traditional complex neural networks. this approach surpasses existing sequence-to-sequence models in terms of quality, parallelizability, and training efficiency. initially applied to natural language understanding (nlu) tasks like machine translation [38], this mechanism was later adapted for visual system tasks [39], including models such as vision transformer (vit) and data-efficient image transformer (deit) [40-42]. 5. visual sensors visual sensors are electronic devices applied across various fields, including robotics, surveillance, automotive systems, industrial automation, and healthcare. they detect and record visual data employing technologies, such as charge-coupled devices (ccds), complementary metal-oxide-semiconductor (cmos) sensors (see, [43-44] for example), and dvs (see, [713] for example). these sensors convert optical signals into electrical signals for computational processing. the data is subsequently analyzed through computer vision and image processing techniques [13, 45-46]. technological advancements have enabled the development of sophisticated sensors capable of real-time high-resolution photo and film collection. some notable examples of such sensors include: 5.1. event-based sensor event cameras, also referred to as data-driven sensors operate based on the principle that their reaction is determined by the amount of motion or change in scene brightness they perceive. each pixel in these cameras adjusts its delta modulator sampling rate based on the rate of change of the log intensity signal it monitors. consequently, faster motion leads to the creation of more events per second. these sensors respond swiftly to visual stimuli, sending events with sub-millisecond latency and timestamped to microsecond precision [3, 12-13, 23-52]. advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 49 the dvs represents a departure from conventional cameras, which capture entire pictures at a predetermined pace determined by an external clock, such as 30 frames per second. instead, event cameras react to scene brightness variations independently and asynchronously for each pixel. focusing on scene changes rather than static frames makes them a valuable tool in various applications [2-53]. the output of an event camera comprises a changeable data-rate series of digital "events" or "spikes," with each event representing a pixel's change in brightness (log intensity) at a specific time, with a predetermined magnitude. event cameras, inspired by the spiking properties of biological visual circuits, enable continuous event representation and deliver improved performance [13, 43-54]. when a pixel delivers an event, it memorizes the log intensity and monitors significant changes from this value. the camera transmits an event when a change beyond a threshold is detected, relaying the x, y position, time "t", and 1-bit polarity "p" (indicating an increase or decrease in brightness) from the chip. these events are transmitted from the pixel array to the peripheral and eventually out of the camera using a common digital output bus, typically employing address-event representation (aer) readout. the readout speeds of event cameras can vary from 2 mhz to 1200 mhz, depending on the hardware interface and chip type [11-13, 55-56]. dvs devices show promise for space and scientific applications due to their low power consumption, excellent temporal resolution, and broad dynamic range. additionally, dvs devices, with higher dynamic range and temporal resolution, are wellsuited for applications such as intelligent robotics, autonomous driving, high-speed photography, and intelligent surveillance, owing to their ability to capture images instantaneously [55, 57-60]. dynamic vision device technology, being cost-effective and impactful in artificial intelligence, human activity recognition, and other specialized applications, has the potential to significantly influence various research fields [21]. focusing on research into comprehension, event segmentation, episodic memory, and activity planning, this analysis explores the intricate mental representations of everyday experiences and proposes future scientific directions [38]. 5.2. frame-based sensor frame-based systems are techniques used for processing or recording data in discrete frames or snapshots at a fixed point in time. in the realm of computer vision, they are employed to sequentially acquire and process visual data, such as photos or films. these systems utilize standard cameras or sensors to periodically capture entire frames of visual data, each comprising a grid of pixels. frame-based processing involves extracting features, monitoring motion, identifying objects, and performing image comprehension and interpretation. however, the performance of these sensors is constrained by their mode of operation. fixed frame rates can give rise to two primary issues: loss of crucial information and significant redundancy, as changes to all pixels unnecessarily increase data transfer and volume. these issues are compounded by the fact that modifications only affect a small section of the image [12, 43, 49, 61-62]. video frame interpolation techniques are crucial in computer vision research as they improve intermediate frames, provide precise motion estimates, boost algorithm performance, reduce memory resource utilization, and improve frame quality [6365]. due to their differing data acquisition methods, integrating event-based and frame-based data remains challenging. the main issue is synchronization, in which event-based systems capture data in response to changes in the scene, while framebased systems capture the entire scene at fixed intervals. additionally, frame-based systems face data redundancy and computational overhead challenges, as they record redundant data, while event-based systems capture only significant changes. advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 50 a hybrid model (see fig. 3) could address these challenges by combining event-based sensors for real-time motion detection, with frame-based sensors providing a complete and detailed view of the surroundings at less frequent intervals. this integration could significantly enhance energy efficiency and processing speed while reducing data redundancy, resulting in more robust and accurate systems for real-time applications. fig. 3 bio-inspired visual model utilizing event-based and frame-based sensors given these constraints, table 1 summarizes numerous optical system models that utilize both frame-based and eventbased vision sensors, highlighting their key characteristics, advantages, and applications. table 1 summary of optical system models utilizing various sensor technologies references model type sensor type key characteristics advantages applications summary [1] hybrid vision framebased and eventbased combines eventand frame-based data to track photometric features. improved feature tracking accuracy, robust to dynamic scenes. asynchronous photometric feature tracking. uses both frame-based and event-based sensors for tracking features asynchronously. [2] hybrid vision framebased and eventbased utilizes combined data from both sensor types to enhance machine vision. versatility in various lighting and motion conditions. object recognition and machine vision. describes the integration of frame-based and eventbased sensors to improve machine vision capabilities. [4] eventbased vision dynamic vision sensors (dvs) dynamic time representation for unsupervised optical flow estimate. no need for labeled data, suitable for dynamic environments. spike camera applications and optical flow estimates. demonstrates the use of dynamic timing from spike camera data to estimate optical flow in an unsupervised manner. [43] eventbased vision dynamic vision sensors (dvs) uses dvs data to estimate the lifespan of occurrences. aids in sensor calibration and provides a metric for event dependability. calibration of sensors and optimization of performance. outlines a technique for calculating an event's lifespan from dvs, which can help with precise sensor calibration and performance enhancement. [63] framebased vision framebased sensors reviews various techniques for video frame interpolation. minimizes motion artifacts and enhances frame quality. animation and video processing. a comprehensive survey of techniques and advancements in video frame interpolation, addressing key challenges. advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 51 6. depth estimation using sensors zhao chen, vijay badrinarayanan, gilad drozdov, and andrew rabinovich introduced a deep model designed to generate dense depth maps with high accuracy from rgb photos with limited depth information, leveraging datasets such as new york university depth v2 (nyuv2) and karlsruhe institute of technology and toyota technological institute (kitti) [66-67]. this model meets real-time criteria for both outdoor and indoor scenarios, achieving a mean depth error of less than 1% in interior settings [68]. such sensors could find applications in autonomous vehicles and robotics. a strategy for dealing with sparse depth data in convolutional neural networks is provided, with the option of using dense rgb. the technique efficiently learns sparse features without the need for extra validity masks, ensuring network durability even at densities as low as 0.8%. the process of transitioning from a sparse to a dense depth map involves a deep neural network that integrates an rgb image and a sparse depth map (see fig. 4). mean relative absolute error (mrae) serves as the evaluation metric to minimize error rates in the generated output. the network architecture includes dense layers along with other components such as pooling layers and rectified linear unit (relu) activation functions [69]. fig. 4 artificial neural networks for scaling images from sparse to dense inference [68] 7. data-driven tools event cameras that communicate per-pixel intensity changes have emerged as a feasible choice in a variety of industries, including consumer electronics, industrial automation, and autonomous cars, due to their efficiency and resilience. in eventbased algorithms, maintaining these advantages requires balancing accuracy and efficiency [46]. the development of data-driven methodologies has emerged as a thriving research area due to its compatibility with spiking neural networks (snns) and deep learning techniques. this study explores the operation and benefits of event cameras, highlighting a recent shift in research focus towards data-driven technologies in event-based vision. alongside discussions on hardware, datasets, and algorithmic trends, it aims to guide future research towards developing more effective and bio-inspired visual systems. in contrast to artificial neural networks (anns) [70], the emerging generation of neural networks, spiking neural networks (snns), which synchronize their firing, can be employed in event-based vision systems to reduce energy consumption [71]. snns are particularly suited for processing high temporal resolution data from event-based cameras due to their differences from anns in information encoding (spiking neurons encode information via spikes while non-spiking neurons use real-value activations), memory (spiking neurons typically possess memory unlike non-spiking neurons), and time-variance (snns exhibit time-varying behavior whereas many anns are time-invariant) [72]. fig. 5 below illustrates a simple snn neuron. snns employ various spiking neuron models to mimic the information-transmission processes of biological neurons. three prominent models include the hodgkin–huxley model, which accurately represents the electrical properties of neurons, including ion channels; the leaky integrate-and-fire model, which is simpler and more computationally efficient than hodgkinhuxley; and the izhikevich model, which strikes a balance between biological realism and computational efficiency [73-75]. advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 52 fig. 5 simplified snns neuron model [72] 8. applications of visual system models eventand frame-based sensors are employed across various sectors for visual system models, including autonomous vehicles, robotics, surveillance, and security. event-based sensors detect dynamic changes, whereas frame-based sensors deliver comprehensive images for object recognition and lane detection. event-based sensors improve user experiences in ar and vr, while frame-based sensors contribute to immersive experiences. these sensors enable real-time gesture detection, and facial recognition, and are also applied in biomedical imaging, industrial automation, and sports analytics. combining both sensor types provides high-speed processing, low latency, and rich visual data [47, 76-77]. 9. discussion visual system-inspired vision models (vsvims) and traditional computer vision models (cvms) are widely utilized in the realms of artificial intelligence and machine vision, which are entrusted with the task of interpreting visual data. vsvims take their cue from how human vision works biologically; they employ neuromorphic engineering and draw insights from neuroscience to replicate resilience, flexibility, and, above all else, the efficiency exhibited by the human visual system on a computational platform. the traditional models walk a different path altogether; relying on mathematical formulae and algorithms to decipher what the visual data is all about. the strategies used by these two classes of models could not be more dissimilar. vsvims take an event-driven approach towards recording visual information, producing sparse and yet temporally precise data streams that echo what is observed at the level of brain activity. conventional models with frame-based sensors capture contextual information but fall short when it comes to understanding temporal dynamics. dvs provides high-resolution pictures and contextual information while maintaining the real-time performance requirements of activities like object recognition and tracking. vsvim succeeds in both of these resource-intensive domains since their demand exceeds available resources, particularly due to their efficiency. traditional models perform well in situations requiring limited visual input, sluggish motion, or a low dynamic range. vision systems based on visual sensorimotor coordination have applications in a variety of fields, including robotics, healthcare, and self-driving automobiles. event cameras provide various benefits over traditional cameras, including high temporal resolution, low latency, low power consumption, and a large dynamic range. using digital readout and rapid analog circuitry, event cameras achieve microsecond precision in time-stamped event detection, allowing quick action capture without motion blur. their independent pixel feature and immediate propagation of changes ensure low latency, which results in a reaction time of less than a millisecond. integrated event camera systems consume 100 mw or less power, whereas image-based cameras have a dynamic range of 60 db. event cameras can collect data from moonlight to daylight, making them versatile for various applications [23-64]. advances in technology innovation, vol. 10, no. 1, 2025, pp. 44-57 53 sensor technologies are crucial in determining the performance of computer vision systems. image-based sensors and dvs sensors have different advantages and applications. dvs sensors detect illumination changes with no external synchronization, which is ideal for motion-adaptive real-time systems, while paddle devices take picture snapshots and measure space but cannot cope well when the environment is rapidly changing or objects are in motion. this means dvs sensors can move expeditiously over moving scenes and a variety of objects allowing machines robots and autonomous systems to perceive and track motion efficiently. image-based sensors have detailed physical motion information, allowing for motion evaluations over time and trajectory analysis, but they are less effective when fast motion is presented with lots of highs and changes over time. motion sensor (dvs) techniques allow for energy-efficient data gathering for mobile robotics, wearable technologies as well as battery-powered devices. their absence of sync and presence in most cases make them cost-effective in terms of computing. frame-based energy sensors, by contrast, would mostly lead to unwanted battery-powered applications in moving areas or very remote zones where there are no power resources for extended periods [65]. dvs sensors are utilized in various activities including robots, teleportation, and augmented reality due to their high resolution, low latency, and power consumption. frame-based sensors are applied in scientific research as well as industrial inspection, medical imaging, and surveillance. future developments aim at improving the parameters of performance, for instance, the working energy efficiency and resolution. both dvs and frame-based vision sensors are applied in visual data analysis. dvs offers higher spatial and frame resolution while the frame-based sensors offer temporal resolution and power savings [78-80]. 10. conclusions this paper critiques and analyzes data acquisition from both event-based and frame-based vision sensors. conventional cameras produce a chain of frames with significant data redundancy, requiring extensive processing. in contrast, event-based sensors respond more effectively to scene modifications, thereby minimizing redundant data. however, dvs faces challenges in detecting objects in static scenes, which limits its effectiveness. to address these challenges, a hybrid approach integrates the efficient data processing of event-based sensors with the high-resolution spatial data of frame-based systems, thus providing a robust solution for visual computation. this complementary approach enhances real-time processing and computing efficiency, effectively addressing challenges in visual computation across diverse applications, including industrial automation, interactive environments, and driverless vehicles. furthermore, future research could explore advanced data fusion techniques and evaluate the hybrid model’s performance in various settings, including dimly lit environments or rapidly moving scenes, aiming to enhance real-time performance. improving the synergy between event-based and frame-based data, could enable ai-driven solutions to enhance visual processing for robotics and augmented reality applications. conflicts of interest the authors declare no conflict of interest. references [1] d. gehrig, h. rebecq, g. gallego, and d. scaramuzza, “eklt: asynchronous photometric feature tracking using events and frames,” international journal of computer vision, vol. 128, no. 3, pp. 601-618, 2020. 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[80] a. andreopoulos, h. j. kashyap, t. k. nayak, a. amir, and m. d. flickner, “a low power, high throughput, fully event-based stereo system,” proceedings of ieee/cvf conference on computer vision and pattern recognition, pp. 7532-7542, 2018. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution [cc by-nc] license [https://creativecommons.org/licenses/by-nc/4.0/]. microsoft word 6-v9n4(2024)-aiti#13934(332-346).docx advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 english language proofreader: chih-wei chang integration of multiple simulation tools for photovoltaic system design and analysis gour chand mazumder1,*, sanjay kumar sarker1, tamim hossain1, md. shahariar parvez2, md. rifat hazari1, chowdhury akram hossain2, md. saniat rahman zishan1, nowshad amin1 1department of electrical and electronic engineering, american international university-bangladesh, dhaka, bangladesh 2department of computer engineering, american international university-bangladesh, dhaka, bangladesh received 27 june 2024; received in revised form 08 september 2024; accepted 10 september 2024 doi: https://doi.org/10.46604/aiti.2024.13934 abstract this research aims to develop a photovoltaic (pv) project assessment method by integrating four simulation tools to maximize potential benefits from multidimensional scopes of projects. the proposed method combines output parameters and the cost databases of selected tools to overcome individual limitations by facilitating complementary strengths. most simulations require more analytical results while using single or multiple tools separately. also, it combines helioscope, retscreen, homer, and pvsyst software to simulate entire generation export, self-consumption, and impact of load shedding with sensitivity analysis. the method employs the capability of helioscope to find maximum installation capacity based on available space, the carbon-trading feature of retscreen, homer’s optimization, and pvsyst’s viability analysis. the results demonstrate that carbon trading shortens the project’s payback period while maximizing installation capacity and performance improvement by energy export with a stable capacity factor and performance ratio. the method proffers a promising technique for pv system assessment. keywords: pv assessment, helioscope, homer, pvsyst, retscreen 1. introduction renewable energy (re) sources render impactful solutions to effectuate the sufficiency of energy and the sustainability of the environment. solar photovoltaic (pv) systems mechanistically utilize sunlight to produce electricity cleanly and sustainably. the capacity of pv systems varies from a few watts to a mega-watt scale. it requires larger installation space than conventional power plants for the same amount of electricity [1]. therefore, capacity determination based on available space and subjected load, mode of operation, and economic benefits are crucial for a successful pv project. technically, pv system simulation shows system performance, economics, cash flow, and profitability before implementation and identifies constraints and advantages based on different scenarios [2]. consequently, users can find the best solution by analyzing the results. therefore, simulation is essential in pv project assessments. undeniably, however, each simulation tool has its strengths and limitations [3]. as a result, the ideal and intuitive solution to conquer the limitations is eclectically using multiple tools to provide diversified information for analysis [4]. umar et al. [5] compared ten tools, concluding that pvsyst, homer, and retscreen are the best simulators. they identified that helioscope has an interactive design facility that empowers users to use a web-based graphical interface to design efficiently and maximize the installation capacity. the central gap in this study lies in the practical exclusion of financial analysis and the ineffectiveness of maximizing the benefits of energy business or carbon credit. * corresponding author. e-mail address: dr.mazumder@aiub.edu advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 333 khan et al. [6] performed a field survey to find the maximum installation capacity for a pv project. concerning the study, the survey data in system advisor mode (sam) and retscreen were utilized to compare the software results. retscreen provides cost data on pv installations, operations and maintenance (o&m). moreover, it has an emission and carbon trading analysis option, whereas this option was not further adopted. another issue with this approach is that a field survey involving the workforce consumes valuable time and costs. an interactive design suite like helioscope can minimize the field survey efforts and cost [7]. the comparison of results of different software only reflects limited quantitative differences and deviations. the study also overlooks opportunities to accelerate the payback time and impacts of the change in economic conditions. de souza et al. [8] compared homer and pvsyst results with practical data from a pv project site, indicating that pvsyst produces accurate results, and homer renders system optimization. users can use inverter cost data from the homer database, and pv cost from the pvsyst database. none of these tools provides both data. limiting the analysis to component configuration and electricity production suffers from the inability to provide information on the payback period, power export opportunity, emission analysis, and carbon trading [9-11]. notwithstanding acknowledging load shedding as a common phenomenon in underdeveloped countries, most simulation tools fail to produce practical system configurations for load-shedding situations [12]. baqir and channi [13] analyzed a grid-connected pv system using pvsyst. the study indicates that grid-connected systems could benefit from total or excess energy export situations. moreover, pvsyst can analyze both total and excess energy export situations, whereas it lacks carbon trading accounting. the study deficits the exploration of carbon trade benefits. however, it deals with system performance without sensitivity and risk analysis. islam et al. [14] explored pv installation prospects on existing infrastructure using homer and pvsyst. the main shortcoming of this work is the absence of shading analysis since the subjected infrastructures are prone to shading impact [15]. pvsyst performs shading analysis but requires actual landscape drawings, which implies difficulties. the study might have used the helioscope for shading analysis [16]. the plant’s installation size is a few mw, indicating that it could benefit from a carbon trading analysis. bangladesh aims to increase re share in its national energy mix from 4.67% to 40% of renewable electricity. the country targets 30% by 2030 and 40% by 2041 [17]. the government has initiated several mw-scale pv power projects throughout the country. given that there are 179 public and private universities with increasing electricity demands in bangladesh, the government recommends using pv power to reduce dependency on the national grid and facilitate the fed-in-tariff (fit) once the installed site exports energy to the grid [18]. therefore, the grid export scenario becomes essential in bangladesh. four assessment studies examined grid-connected rooftop pv systems on university campuses [19-22]. two of these studies used a field survey and mathematical approach to estimate installation capacity; two used simulation tools. the studies indicate that excess electricity export is profitable for grid-connected pv systems. however, these studies lack the entire export scenario and do not cover emission analysis, shading loss, carbon trading, export profits and shortfalls optimization, sensitivity analysis, and standardized cost data [23]. the objective of this research is to prepare a pv-project analysis method to synthesize results by integrating complementing features provided by the selected tools. the purpose of the study is to exploit interactive design options, utilize a standard cost database, provide system optimization, find loss variants, perform economic analysis, evaluate system performance, explore carbon trading and its impact on the payback, observe risk and sensitivity impacts, and identify benefits from different scenarios. the method integrates helioscope, retscreen, homer, and pvsyst in four stages, connecting the results from the preceding stages. 2. site selection and system constraints the selected site name is american international university-bangladesh, situated in dhaka. bangladesh has a 1.3 mw electricity demand. holistically, it consumes grid electricity and generates power from 2,575 kva diesel generators during 334 advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 load shedding to support the loads. the campus has eight suitable rooftops for installing pv. a 194,471.80 square foot area is open to the sun for 4 hours, with a solar irradiation of 4.65 kwh/m2/day. this research proposes a pv system comprising existing diesel generators and grid electricity, preparing three scenarios exploring the best mode of operation, as listed as follows. scenario a: grid with full export implies the total export of produced electricity using the fit to look for the impact on payback. furthermore, it examines emission reduction and carbon trading. scenario b: having a grid-pv system without load shedding considers self-consumption from both the pv and the grid power. this scenario can predict energy savings, grid purchases, and own generation. scenario c: grid with outage covered by diesel generator and pv. this scenario considers yearly schedules for load shedding and estimates the impact of diesel emissions and electricity costs. in brief, scenario a emphasizes business prospects, scenario b looks for energy savings, and scenario c looks for costs and environmental impact. fig. 1 shows the aerial view of the site. fig. 1 arial view and map images of subjected campus rooftops 3. methodology this research investigates and integrates prominent options, features, and the cost database of selected tools. determining installation capacity based on available usable space enables users to identify the maximum pv size, shading, and losses. the analysis’s vital aspects are the cost database, scenario-based system design, emission analysis, optimization, performance analysis, economic assessment, risks, and sensitivity. 3.1. selection of tools the total simulation comprises four stages where each tool complements each other. helioscope provides installation capacity but does not address load-specific system performance, carbon emission, or simulation of different scenarios. at this gap, retscreen offers the cost database, complete export scenario, profitability, carbon trading, and risk analysis. however, none of these tools handle load, optimization, and electricity production costs. here, homer, as a notable exception, furnishes these features and the cost data for the inverter but lacks pv cost. meanwhile, retscreen complements the pv cost data. retscreen and homer yield risk and sensitivity analysis. homer facilitates grid purchase, pv generation, and excess electricity, simulating the self-consumption scenario. homer cannot provide the entire export scenario. at this point, pvsyst provides grid export and consumption scenarios. advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 335 3.2. simulation stages the process commences with the helioscope at stage one. helioscope empowers users to compute the maximum usable space by a graphical interface. specifically, users can select the installation area, panel models, input shading, row spacing, and tilt angles. helioscope yields result on solar access, shading, electricity production, system loss, and installation capacity. at stage two, the simulation uses retscreen since it requires a predetermined installation capacity of pv and inverter. helioscope provides these values. retscreen utilizes its own cost and emission factor database. it calculates the energy exported to the grid using emission estimations. at stage three, homer optimizes the system based on load. homer database proffers costs for inverters but lacks pv and o&m costs. here, retscreen gives these values. homer uses re fractions to estimate the optimal pv size. the method deploys this option to match the homer input, and helioscope results on pv capacity. at stage four, the pvsyst simulates the load profiles, resource data, energy exchange, electricity rate, and economic evaluation with emission analysis and paucity of optimization or outage scenarios. however, it estimates system losses, payback, return on investment (roi), profitability, and performance. its database contains pv, inverter, and installation costs but lacks o&m costs; therefore, the method uses the retscreen database for o&m costs. fig. 2 depicts the variables and parameters inside the elliptical shapes. solid black circles give a particular parameter’s flow to the input of a tool. full circles show the position of a tool in the process, starting from the left. the dotted lined boxes present the results from a tool. fig. 2 design flow of the proposed method 4. results and discussions the result combines different outputs from each tool. the helioscope gives the pv installation size. retscreen renders a complete export scenario, including emissions, carbon trading, and risk analysis. homer presents cash flow, electricity cost, emission analysis, and sensitivity. lastly, pvsyst introduces performance ratio (pr), payback, emission analysis, and profitability results. fig. 3 is the high-level presentation of the process. it evinces the stage position of each tool and the compilation of results by dotted lines. the solid line presents the estimation of the power outage scenario based on homer and pvsyst results. 336 advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 fig. 3 flow of analysis using multiple simulation tools 4.1. helioscope results the helioscope returns the nameplate capacity as 1.09 mwp, using 3,163 trina solar, model tsm-pe15h-345 (345w). the usable rooftop is 87,000 ft2 and 18,781 ft2 from the parking space. this site has 89% solar access, 72% tilt and orientation factor (tof), and 63.5% total solar resource fraction (tsrf). (a) annex-wise pv installation capacity (b) various system losses fig. 4 helioscope results on estimation the optimal plane of array (poa) irradiance is 1,967.5 kwh/m2 at 28.40° tilt and 179.70° azimuth. the pr is 71.8%. fig. 4(a) shows the usable rooftops and the maximum installation on available space. fig. 4(b) shows that the highest loss is due to shading and indicates the reason for performance reduction. the system requires 37 sunny-tripower-24000tl-us (sma) inverters, giving 890.2 kw capacity. there are 185 strings of 17,288.20 ft american wire gauge (awg) 10 (copper) wire. 4.2. retscreen results considering 1.09 mwp returning 3,164 numbers of tsm-pe15h-345 (345w) pv modules, the fixed-track module efficiency is 17.74%. the loss input is 28.2% with 98% inverter efficiency. the electricity export is 1,261 mwh/yr. the electricity export rate is $0.1/kwh, resulting in a revenue of $126,128/yr. the capacity factor (cf) is 13.2%. the installation cost is $1,800/kw for 1,000 kwp. the operating cost is $18/kw/yr. it uses an inflation rate (11%) and project life (25 years). the total initial cost is $1,964,844, along with $19,648 of o&m. the result shows the internal rate of return (irr) value is 13.8% with a payback of 10-18.5 years. retscreen reflects a reduction of 710.8 tco2, and the proposed case would emit only 53.5 tco2/yr. considering the certified emission reduction (cer) rate ($300/tco2), the carbon reduction revenue is $213,225. apropos the verified emission reduction (ver) rate ($100/tco2), the revenue is $71,075 [24]. the payback is 11.1 years for ver and 6.1 years for cer. fig. 5(a) shows that the cash flow increases after ten years because of component replacements. fig. 5(b) represents the emission reduction performance of the pv system compared to the grid. advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 337 (a) cumulative cash flow (b) emission reduction fig. 5 retscreen results 4.3. homer results homer returns the system comprising 1027 kwp pv with an 824 kw inverter having a 32% renewable fraction. fig. 6 shows the pv, load, inverter, and grid connections. the pv provides dc electricity to the dc bus. the inverter converts dc power into ac and supplies it to the ac bus. the grid injects electricity into the ac bus. the load is ac type and fed by an ac bus. fig. 6 optimized system configuration by homer fig. 7(a) illustrates the hourly load demands, which steeply rise from 8:00 am and remain consistent until 3:00 pm. they fall gradually from 4:00 pm. the load is 150 kw from 12:00 am to 8:00 am, and 350 kw from 4:00 pm to 9:00 pm. fig. 7(b) is a box plot with three quartiles. the median is between 500 kw and 1000 kw. the lower quartile lies between 0 kw and 500 kw. the top quartile is above 1200 kw. (a) daily load profile (b) seasonal load profile fig. 7 homer configuration fig. 8 presents the hours of the day (left axis) and the output (right axis). the brighter shades regions represent the mean inverter output, ranging from 800 to 1000 kw, with the highest output (1000 kw) mostly occurring between 8:00 am and 4:00 pm. the darker shades regions indicate periods of low consumption, while the unshaded (or darkest) areas represent times with no generation. 338 advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 fig. 8 homer results on inverter output fig. 9 shows the generation equivalent to 800-1000 kw in the bright regions within the graph, mostly between 10:00 am and 4:00 pm, indicating higher pv outputs. the comparatively darker regions from 400-600 kw represent lower power output, mostly distributed in the early morning and late afternoon. the unshaded or darkest areas from 0-200 kw indicate times of no generation. fig. 9 homer results on pv power output fig. 10(a) shows discounted cash flow using brown bars (lighter shade) for the investment and green bars (darker shade) for the revenue from excess electricity. the revenue is steady, and the cash flow decreases over the lifetime. the first-year investment is high due to the system installation. fig. 10(b) depicts the costs of components, with pv taking the highest investment. the inverter has the smallest share of the cost. (a) discounted cash flow (b) net present cost fig. 10 homer result on economics fig. 11 electricity supply by solar pv and grid advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 339 fig. 11 shows the electricity share by the grid and pv. the bars on the left indicate the electricity supply from trinatallmax, with their height representing pv generation. meanwhile, the bars on the right indicate the grid electricity supply. the highest grid dependency occurs from june to september due to the clouds during these months, and the lower grid consumption occurs from october to may. fig. 12(a) reflects the electricity sold to the grid, with the export time spanning from 6:00 am to 8:00 am. the distribution of equivalent energy is categorized into 2 types to represent the extent of energy, i.e., 96-160 kw and 32-64 kw, respectively. fig. 12(b) depicts the electricity purchased from the grid. higher-intensity dots represent purchases in the 840-1400 kw range, while lower-intensity dots represent lower imports of electricity. (a) energy sold to grid (b) energy purchase fig. 12 homer results on power exchange the levelized cost of electricity (lcoe) is $0.190/kwh, with an initial capital of $19.6m. electricity production is 4,665,568 kwh/yr, consumption is 4,621,306 kwh/yr, and excess electricity is 7,349 kwh/yr. total purchase from the grid is 3,120,206 kwh, and export to the grid is 8,437 kwh. the greenhouse gas (ghg) emissions are 1,971 tco2/yr, 8.5 tso2/yr, and 4.2 tno/yr while using grid power. 4.4. pvsyst results pvsyst analysis considers $21,868.40/yr for salary. the payback for self-consumption mode is 15.4 years, considering the $0.1/kwh fit rate and $0.088/kwh grid electricity purchase rate. the payback is 11.6 years for the entire export scenario. the lcoe is $0.13/kwh, roi is 13.3%, and pr is 82%. the pv can save 21,109.3 tco2. (a) output power distribution (b) daily load profile fig. 13 pvsyst results on output power distribution and configuration on daily load profile 340 advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 the self-consumption is approximately 1,777 mwh/year, and the export is 4.0 mwh/yr. fig. 13(a) depicts the solar energy output for the available irradiation. the 700-780 kw bin evinces a significant output of 55,000 kwh of energy. fig. 13(b) illustrates the load profile, where demand increases from 7:00 am to 8:00 am, remains stable until 3:00 pm, and declines until 6:00 pm. fig. 14(a) renders a stable pr throughout the year. the highest value occurs in january. fig. 14(b) exhibits the system’s normalized energy production. the highest value occurs in march. in fig. 14(a), bars indicate usable energy. meanwhile, in fig. 14 (b), each month’s longest bars represent useful energy, the intermediate-highest bars indicate pv-array loss, and the shortest bars denote system losses. (a) month-wise performance ratio (b) normalized productions fig. 14 pvsyst results on monthly performance ratio and normalized production fig. 15(a) presents the cumulative cash flow in the self-consumption scenario. the individual bars account for all cash inflow and revenues in a specific year. the bars above zero indicate that the revenue exceeds the expenses. after 2045, there will be an increase in the number of bars underneath zero, indicating new investments. fig. 15(b) presents the net profit where bars below zero present investment and the bars above zero show the profit. the net profit gradually decreases until 2042. after 2043, net profit becomes negative, presenting the new cash investment. (a) year-wise cash flow (b) year-wise net profit fig. 15 pvsyst results on the self-consumption scenario fig. 16(a) shows the cumulative cash flow in the grid injection scenario. the cash flow will decline until 2035. in this scenario, the zero crossing is four years earlier than the self-consumption scenario. fig. 16(b) shows the net profit where zero crossing is one year longer than the self-consumption. fig. 17 shows the project’s life cycle emissions and carbon savings. the net balance is 21,109.3 tco2. the system produces an emission amount of 1,993.20 tco2. the system replaces 25,995.4 tco2 concerning the grid. the yearly balance is about 844 tco2/yr. advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 341 (a) year-wise cash flow (b) year-wise net profit fig. 16 pvsyst results on complete injection scenario fig. 17 year-wise carbon balance 4.5. load shedding estimation the site becomes a pv-diesel system during outages. table 1 presents the load-shedding schedules where the peak hour outage is 1 hour. the total off-peak outage is for 2 hours. generators support a 1,250 kw load during peak time. regarding off-peak 1, it is 150 kw and 350 kw for off-peak 2. the diesel expenditure is $600/hr. there are 3 hours of load shedding for 85 days/year, resulting in 255 hours of outage, which costs $260,038.24/year. the electricity generation is approximately 238,000 kwh/year. the lcoe for diesel is $1.09/kwh. the pv could reduce diesel usage by 32%. the diesel will cause 6.5 tco2/yr. table 1 load shedding and diesel generator profiling campus hours load shedding hour duration (hour) avg load (kw) fuel cost ($) off-peak 1 02:00 am to 03:00 am 1 150 163.89 peak 11:00 am to 12:00 am 1 1250 1365.75 off-peak 2 08:00 pm to 09:00 pm 1 350 382.41 per day cost 1912.05 per hour average cost 637.35 yearly cost 162523.90 4.6. sensitivity and risk analysis by retscreen the analysis investigates the sensitivity and risks on payback due to the changes in initial cost, o&m, export to the grid, export rate, and ghg credit rate on the payback period, as shown in fig. 18. a 30% sensitivity and ten-year threshold evinces a 15% decrease in electricity export. this results in an unachievable payback even if the initial cost is 30% less. similarly, a 15% increase in initial cost makes longer paybacks. 342 advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 fig. 18 monte carlo simulation on equity payback impact by components fig. 19 introduces results on 20% risk, examining the payback with 90% (p90) confidence. it excludes the lowest and highest 10% of data. at 20% risk, the payback stays within 8.4-11.4 years. fig. 20 shows the payback remains inside the 6.6-14.5 years range for 0% risk. the export income and the electricity rate have opposite impacts on payback. fig. 19 equity payback distribution for 20% risk level fig. 20 equity payback distribution for 0% risk level 4.7. sensitivity analysis by homer fig. 21 sensitivity impact on lcoe by system components advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 343 homer investigates the sensitivity of economic conditions and component performance. once the homer sensitivity module yields the values of different parameters, the simulation picks and generates different lcoes based on the values. table 2 illustrates the values for the component sensitivity. here, pv lifetime ranges between 18 and 25 years. the panel-derating factor is 86%-90%, and the inverter efficiency is between 95% and 98%. fig. 21 gives the linked sensitivity results. the lines presented in fig. 21 represent the value of a sensitivity parameter and its impact on lcoe. homer generates 81 sensitivity cases. the lcoe ranges between $0.19 and $0.21. here, the usd conversion rate is 110 bdt/$. table 2 sensitivity parameters of system components pv panel lifetime (years) pv panel derating (%) inverter lifetime (years) inverter efficiency (%) 25 88 10 97.6 20 90 15 98 18 86 8 95 table 3 exhibits the economic sensitivity parameter values. the increment of the discount rate elevates the lcoe. the input values are 10%-14%. the impact of inflation can be known by analogy with the discount rate. the value for the inflation rate is 9%-13%. it takes a project lifetime of 18-25 years. the lifetime shows an inverse effect on lcoe. fig. 22 shows the fluctuations in lcoe due to economic sensitivity in 75 cases. due to sensitivity, the estimated electricity cost varies between $0.19 and $0.21. fig. 22 sensitivity impact on lcoe by economic factors table 3 sensitivity parameters of economics nominal discount rate (%) inflation rate (%) project lifetime (years) 10 9 18 11 10 20 12 11 25 13 12 14 13 table 4 compiles 12 critical input and output parameters. ‘user-defined’ means that the value is a user input. the term ‘own database (odb)’ refers to the value from the database of that tool. if the values are yielded from different tools, the table mentions the tool’s name. table 4 gives the relationships between inputs and outputs from different tools and presents the mode of simulations. 344 advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 table 4 list of input and output parameters of all used software type helioscope retscreen homer pvsyst input rooftop area system size (helioscope) project time (user-defined) install cost (odb) input panel orientation inflation rate (user-defined) discount rate (user-defined) salaries input climate data project lifetime (user-defined) inflation rate (user-defined) meteonorm input shading inverter size (helioscope) cost (retscreen, odb) pv (odb) input pv module pv cost (odb) system size (helioscope) inverter (odb) input inverter module maintenance cost (odb) maintenance cost (retscreen) o&m (retscreen) output system size irr lcoe profitability output inverter size simple payback cash flow payback period output performance ratio equity payback grid purchase roi output shading loss emission analysis emission for grid lcoe output other system loss carbon trading outlook pv generation performance ratio output energy production risk analysis sensitivity analysis losses mode full export self-consumption both 4.8. comparison of results the performance ratio is a crucial index of pv power plants. it is a ratio between the actual and theoretical output. an 80% pr indicates an efficient pv plant [25]. in addition, shading loss is an important variable that can reduce power production, which occurs when buildings or trees create a shadow on the pv panel surface. therefore, selecting the proper landscape, orientation, and position is essential [26]. the cf represents the ratio between the actual and theoretical energy production at the highest rate throughout the year. a 10-25% cf indicates a sound pv system [27]. the lcoe by pvsyst is $0.13, and homer gives $0.19. the difference is $0.06 due to the renewable fractions. in homer, the cf is 32.5%, and in pvsyst, it is 38.63%. homer produces the energy production of 4.7 gwh/yr, pvsyst yields 1.8 gwh/yr, and the helioscope presents 1.1 gwh/yr. the pr is 71.8% by helioscope and 82% by pvsyst. the helioscope results are the lowest due to the inclusion of losses like irradiance, shading, temperature, soiling, array, and wiring loss. pvsyst does not consider shading loss but takes other types, whereas homer does not consider these loss parameters. in the self-consumption scenario, pvsyst generates 2,823 mwh of grid electricity usage, and homer produces 3,120 mwh. this scenario causes an emission of 1,359-1,971 tco2/yr. the electricity export is about 4.0-8.4 mwh. the grid injection is 1,261-1,781 mwh for the complete export scenario. the difference in climate data also induces these deviations. homer also considers a higher cell efficiency (17.8%) than pvsyst (16.99%). pvsyst’s total cost is $15.6m, with a salvage of $0.1m. homer yields the net present cost (npc) of $19.6m, operating cost of $0.8m/yr, initial capital of $1.56m, and o&m of $0.8m/yr. the difference is due to the individual database values. pvsyst returns the roi to be 13.3% and retscreen irr to be 13.8%. pvsyst offers a payback of 15.4 years. retscreen evinces 11.4 years of payback, rendering 90% confidence and 0 to 20% risk. it returns a carbon saving of 710.7 tco2/yr. the carbon balance result by pvsyst is 844 tco2/yr. the difference between retscreen and pvsyst is 134 tco2/yr. the deviation is due to the different meteorological data, losses, and differences in emission factors. the ghg reduction revenue is $213,225 (cer) and $71,075 (ver). the lowest payback is 6.1 years, exploiting grid export and carbon trading. 4.9. recommendations and improvements for further studies the study recommends the practical implementation of this project. the site should use the international carbon trading opportunity. there might be a comparative study between the estimated and practical data. the actual cost data from the implementation may benefit the study. future research may consider this project for the hybrid microgrids model with a reliability and resilience study concerning the environmental impacts of storage mechanisms. further research may consider an automated load-shedding analysis. the software developers might include this scenario as a feature. advances in technology innovation, vol. 9, no. 4, 2024, pp. 332-346 345 5. conclusions the research integrates four distinct pv system simulation software, identifying the best features from a rigorous literature review. it utilizes different parameters from one tool to another in different stages, and each stage produces several results as the output. the study employs the developed process to analyze a university campus pv system. based on the simulation of different scenarios, the conclusions are as follows: (1) the integration produces an extended result set that covers the multidimensional analysis of a project. (2) the method eliminates the necessity of field-based surveys using helioscope, which reduces the workforce and associated costs. (3) some key results are lcoe ($0.13), roi (13%), cf (13%), performance ratio (82%), shading and different losses (32%), payback period (11 to 15 years), energy export (4 mwh/yr), carbon trading revenue ($71,075-213,225), emission reductions (710.7 to 844 tco2/yr). (4) carbon trading reduces the payback period by gathering revenue from international markets. in this case, the payback is six years instead of 11 years. this venture may help popularize the larger pv project in underdeveloped countries. (5) standard database values on costs enable users to utilize international standardized values for estimation. (6) self-consumption and a 100% export scenario empower users to decide on profitability using the feed-in tariff. the comparison finds the plant’s suitability for self-use or a total power export business. 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[26] h. oufettoul, n. lamdihine, s. motahhir, n. lamrini, i. a. abdelmoula, and g. aniba, “comparative performance analysis of pv module positions in a solar pv array under partial shading conditions,” ieee access, vol. 11, pp. 12176-12194, 2023. [27] a. boretti and s. castelletto, “trends in performance factors of large photovoltaic solar plants,” journal of energy storage, vol. 30, article no. 101506, august 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol.10, no.3, 2025, pp.220-237 multi-objective optimization of ev charging for cost and loss minimization under tou tariff suwimon techanok, keerati chayakulkheeree* institute of electrical engineering, suranaree university of technology, nakhonratchasima, thailand received 19 november 2024; received in revised form 17 march 2025; accepted 18 march 2025 doi: https://doi.org/10.46604/aiti.2024.14520 abstract this study proposes an optimal electric vehicle (ev) charging (oevc) management methods to minimize electricity costs and energy losses in the distribution system, which arise from the growing demand for ev charging. a multi-objective particle swarm optimization (mopso) algorithm is used to solve the oevc multi-objective optimization (moo). additionally, the time-of-use (tou) tariff is used to coordinate between the distribution system operator and ev users, which can help increase the efficiency of the charging schedule. monte carlo simulation (mcs) is used to model virtual ev user behavior and create ev charging load profiles. the proposed mopso-based oevc approach is verified on the modified ieee 33-bus distribution test system, using matlab software, under both uncontrolled and controlled charging case studies. the simulation results demonstrate that the proposed method optimizes ev charging efficiently, achieving reductions of approximately 7.60% in electricity costs and 28.73% in energy losses compared to the uncontrolled charging case. keywords: optimal ev charging (oevc), multi-objective optimization (moo), electricity cost minimization, energy loss minimization, time-of-use (tou) tariff 1. introduction global warming poses a critical threat to ecosystems and human well-being. many countries aim to achieve net zero emissions (nze) as the solution under the paris agreement, with a key strategy being the transition from internal combustion engines (ices) to electric vehicles (evs). fuel combustion in ices is a major source of co2, and studies indicate that widespread ev adoption can reduce emissions by up to 20% [1-2]. under the most ambitious scenarios, evs could account for up to 65% of all light car sales globally by 2030, driven by strong policy support, advancements in battery technology, and market expansion in major regions. this projection aligns with the nze by 2050 scenario outlined in the global ev outlook 2024 [3]. however, the rapid increase in ev adoption also presents significant challenges for electricity grid management. as ev users typically charge their vehicles after returning home, this coincides with peak electricity demand from other daily activities, leading to elevated peak electricity loads. without proper planning, this can result in significant negative impacts on the grid, such as voltage instability, increased power losses, and transformer overloading. for instance, studies [4] analyzing the impact of uncoordinated ev charging on grid performance, have shown that peak demand can increase by up to 53%. to address these challenges, implementing strategies such as smart charging, time-of-use (tou) tariffs, and vehicle-to-grid (v2g) technology is crucial for ensuring the sustainable integration of evs into the energy system [5]. fig. 1 demonstrates the impact of ev charging on the load profile. * corresponding author. e-mail address: keerati.ch@sut.ac.th advances in technology innovation, vol.10, no.3, 2025, pp.220-237 221 fig. 1 the impact of ev charging on the load profile consequently, many studies are being conducted to find the management approaches to the rapid increase in ev numbers within the electricity system. in [5], an efficient and accurate predictive model for ev charging demand is proposed, specifically designed for use in the management and planning of urban transportation infrastructure. in [6], the authors propose sequential heuristic (sh) and global heuristic (gh) approaches to solve the optimal ev charging (oevc) scheduling problem to minimize charging costs. in [7-8], centralized ev scheduling problems are proposed to minimize grid load imbalance through valley filling. in [9], the optimization of ev charging and discharging primarily aims to decrease energy costs by shifting loads to low-cost periods and regulating power system demand more efficiently. various algorithms have been studied and developed to optimize charging scheduling. heuristic rule-based algorithms have been proposed in [10-11] to handle a variety of scheduling challenges considering variables such as the number of instances, the available limitations, and computational, including the scheduling of ev charging sessions at charging stations while solving an optimal power flow problem. however, heuristic rules are applied to problems with a small number of decision variables and lower computational complexity. in contrast, metaheuristic algorithms are better suited for handling complicated problems, especially when it comes to scheduling optimization and power system challenges. in [12], the crow search algorithm (csa) is used to optimize the energy control system and minimize operating costs. in [13], the focus is on minimizing the peak-to-valley difference in grid load and reducing user charging costs, proposing the use of genetic algorithms (ga) for optimal scheduling schemes for electric vehicles. in [14], the particle swarm optimization (pso) algorithm can be employed to optimize ev charging scheduling to effectively minimize power loss, although it does not account for the uncertainty in user charging behavior. however, in [15], the uncertain behavior of evs using a markov decision process, with optimal charging management achieved through the bounded realtime dynamic programming (brtdp) algorithm. in [16], ga and monte carlo simulation (mcs) are used to minimize distributed generators' investment costs. adjusting ev users' charging behavior is crucial for optimizing charging schedules for maximum efficiency. demand side management (dsm) is an alternative solution for controlling electricity demand, including the demand for ev charging. dsm has been successfully applied in large-scale buildings through various demand response programs, such as real-time demand reduction, load shifting, and energy efficiency enhancement, as demonstrated in real-world case studies proposed in [5]. dynamic pricing is important for managing conflicting energy demands from ev charging. in [17], it was demonstrated that the dynamic real-time demand electricity pricing mechanism can significantly reduce electricity costs. the tou considered in [18] was applied for optimal energy scheduling to reduce system costs and minimize co2 emissions, utilizing the multi-objective grasshopper optimization algorithm (mogoa). meanwhile, [19] introduced a model developed using the learnable partheno-genetic algorithm (lpga) to determine the optimal ev routes to minimize total distribution costs under the tou framework. advances in technology innovation, vol.10, no.3, 2025, pp.220-237 222 however, mogoa is still a relatively new algorithm with limited development and improvements, and lpga is susceptible to becoming caught in local optima in the absence of a well-thought-out methodology. by contrast, multi-objective particle swarm optimization (mopso) is a widely used algorithm with several improved versions, making it highly effective for solving specific problems. mopso also has a strong capability to explore solution spaces efficiently and avoid local optima while offering flexibility in various applications. in [20], mopso has been used to optimize the power flow. many studies focus on solving multi-objective scheduling problems, such as [21-22] minimizing grid load imbalance and focusing on reducing ev users' charging prices. however, many studies primarily target reducing costs for the benefit of ev users. from the perspective of solving scheduling issues to minimize the distribution system operator's (dso) expenses, this aspect is one of the most challenging issues. in large-scale ev charging, power losses from extensive electricity transmission impose significant challenges that are comparable to other grid impacts. insufficient electricity to meet rising demand may also force the dso to procure additional power, often from international sources, which could elevate costs due to fluctuating global energy prices. moreover, both escalating costs and rising power losses have substantial and interconnected impacts on the grid’s sustainability. therefore, both issues should be considered simultaneously in any comprehensive optimization strategy. the study in [5] focuses on developing a predictive model to accurately forecast ev charging demand by leveraging advanced deep learning techniques, primarily emphasizing long-term planning and resource allocation for charging station operators. however, it does not address the critical challenges associated with large-scale ev integration into the power grid, such as increased power losses and higher operational costs for dsos. meanwhile, this study aims to address this gap by focusing on optimizing ev charging to minimize both electricity costs and energy loss in the distribution system for the benefit of the dso. based on the discussion above, this study proposes an integrated approach for oevc that uses the mopso algorithm to minimize electricity costs and energy losses, achieving a balanced optimization between both objectives. in the methodology presented in this article, dynamic pricing is incorporated by integrating a tou tariff as a representative example of price-based demand response actively used in thailand in conjunction with mopso. moreover, the versatility of mopso allows adaptation to other pricing schemes, which provides a flexible framework for diverse market conditions. while accounting for the uncertainty in the user charging behavior, the mcs generates ev load profiles based on actual usage data. the proposed mopso-based oevc algorithm was tested on the ieee 33-bus distribution system using the central thailand household load profiles. the simulation results show that the proposed oevc method effectively minimizes electricity costs and energy losses compared to charging profiles generated by mcs. this study is structured as follows: section 2 addresses the oevc problem formulation, section 3 presents the mopso method for solving the oevc, section 4 presents the simulation results and discusses the results of the mopso base oevc, and section 5 presents the conclusions. 2. problem formulation in this section, objective functions are formulated to minimize electricity costs and energy losses. the mcs is used to model ev user behavior and handle the variability resulting from ev user behavior uncertainty. this part will also cover the tou tariff, which is a time-based program that encourages response to the oevc scheduling. 2.1. time of use (tou) tariff the tou rate is an electricity rate that represents the cost of generating power over two periods. electricity costs are calculated based on the user's electricity usage period. as shown in fig. 2, electricity costs during peak hours (from 9:00 am to 10:00 pm) are higher than those during off-peak hours (from 10:00 pm to 9:00 am). implementing the tou tariff encourages ev users to adjust their charging times to take advantage of the lower rates. advances in technology innovation, vol.10, no.3, 2025, pp.220-237 223 time (hours) e n e r g y c h a r g e ( b a th /k w h ) off-peak off-peak on-peak 00.00 09.00 10.00 24.00 fig. 2 typical tou tariff pattern 2.2. the probabilistic modeling of the ev user's behavior for the behavior of ev users, mcs is applied to address the uncertainty of ev users' behavior. the random variables considered include the time at which evs depart from home (𝑇𝑒𝑑𝑟), the duration from home to work (𝑇ℎ𝑡𝑤), the duration back from work to home (𝑇𝑒𝑏ℎ), and the duration evs are parked at work without being connected to the grid (𝑇𝑒𝑜𝑝). additionally, the model considers battery capacity and distance. the probability distributions and parameter values used for these variables were derived from empirical studies on real-world ev user behavior in european countries, which investigated travel patterns, parking durations, and charging preferences. these findings provided the basis for determining the means and standard deviations for each parameter, as presented in table 1 from [23]. the lower and upper bounds of random variables are 0-24 hours. fig. 3 illustrates the ev user activity model generated using mcs. this model creates an ev charging load profile, which is combined with the household load profile. these inputs and network data are provided to the mopso algorithm to solve the oevc. atv1 atv2 atv3 atv4 atv5 time step % s o c mopso optimal ev charging ev charging ev charging input load profile household load profile ev charging network data monte carlo simulation evs stay at home the owner drives to work evs stay at work the owner drives to home the evs arrive home maximum soc decreasing soc constant soc increasing soc input fig. 3 framework of mopso-based oevc with probabilistic ev user activity model once these random time variables are obtained from the mcs, they serve as inputs to model the ev usage activities of users. the model for ev usage activities is based on the assumption that evs are primarily used for commuting within urban areas, where they only travel from home to work and do not account for regional variations in user behavior or external factors advances in technology innovation, vol.10, no.3, 2025, pp.220-237 224 such as traffic conditions or weather. therefore, the activities of ev users include the time of departure from home, the time of return to home, the travel duration, and the duration of parking without charging, as described in eqs. (1)–(6).      [ ], 1 2 3 4 5 n n n n n n atv atv atv atv atv atv day = + + + + (1)        {1: -1}, 1 n n atv t edr = (2)            { : ? }, 2 n n n n atv t t t edr edr htw = + (3)                { 1: ?   }, 3 n n n n n n atv t t t t t edr htw edr htw eop = + + + + (4)                    { ?  1: }, 4 ? n n n n n n n n atv t t t t t t t edr htw eop edr htw eop ebh = + + + + + + (5)              { ?        1: }, 5 n n n n n atv t t t t np edr htw eop ebh = + + + + (6) 1, , , 1, ,for n nc t np=  =  where, 𝐴𝑇𝑉𝑑𝑎𝑦 𝑛 represents the daily activities of the 𝑛𝑡ℎ ev usage. the 𝑛𝑡ℎ evs stay at home before leaving for work in activity 𝐴𝑇𝑉1 𝑛. 𝐴𝑇𝑉2 𝑛 is the owner who drives the 𝑛𝑡ℎ evs to work. the user of the 𝑛𝑡ℎ ev parks the evs at work without connecting to the grid by 𝐴𝑇𝑉3 𝑛 is the activity in which the user of the 𝑛𝑡ℎ ev parks the ev at work without connecting to the grid. the owner, 𝐴𝑇𝑉4 𝑛 takes the 𝑛𝑡ℎ evs home. lastly, 𝐴𝑇𝑉5 𝑛 represents the owner of the 𝑛𝑡ℎ evs after they get home from work. in order to estimate the electricity consumption from ev charging and create the load profile for uncontrolled charging of evs, it is necessary to calculate the state of charge (soc). based on the assumption that ev usage begins in the morning after overnight charging, it is initially considered that the battery is fully charged, as indicated in eq. (7) [24]. considering only the charging state, it is assumed that the 𝑆𝑂𝐶𝑡 is limited to a minimum depth of discharge (dod), determined by the fraction 𝑃𝑑𝑜𝑑 and the maximum soc when fully charged, denoted as 𝑆𝑂𝐶𝑚𝑎𝑥 , as shown in eq. (8).          0 max n n soc soc= (7)               min max   n n n p soc soc soc dod t   (8) the level of soc changes according to ev usage activities. it increases when the ev is charged at home and decreases when the user drives the ev. for the time step of the soc at time increases from its initial state according to the charging power when the ev is charged. it decreases according to the energy consumption when the ev is driven, as calculated in eq. (9).      , arg mod             , mod 1   , δ δ nsoc p t for ch ing e t c n n tsoc soc c t for driving e t t nsoc else t  +   =+    (9) 1, , , 1, ,for n nc t np=  =  advances in technology innovation, vol.10, no.3, 2025, pp.220-237 225 time period % s o c   max nsoc       1   δ- n n t t tsoc soc c t+ =     1 n n t tsoc soc+ =       1    δn n t t csoc soc p t+ +=     m0 ax n nsoc soc= at home parking at work fig. 4 the soc varies over time under different ev charging strategies fig. 4 illustrates the soc profiles of an ev under different charging strategies across key activity periods, including staying at home, driving to work, parking at work without charging, ev driving back home, and charging at home. each segment reflects the change in soc based on the corresponding activities, where soc decreases during driving, remains constant while parked at work, and increases when charging at home, following eqs. (7)-(9). the ev charging load profile 𝑃𝑒𝑣,𝑖,𝑡 𝑛 will be equal to or dependent on 𝑃𝑐 following the vehicle usage activities at that time initially, as shown in eq. (10). the total ev charging load profile is determined by summing the charging loads of all evs, as described in eq. (11).     , arg mod     , ,   0, p forch ing en cp ev i t else =    (10)           , , , , 1 nc total n p p ev i t ev i t n =  = (11)     1, , , 1, ,for n nc t np=  =  the power ev charging 𝑃𝑒𝑣,𝑖,𝑡 𝑛 must be taken into account hourly in the data analysis to ensure that the information is in line with the objective function, understandable, and adheres to standard procedure. the outcome of changing the time step from one minute to one hour is displayed in eq. (12).           , , , , 1 nc total n p p ev i h ev i h n =  = (12)     1, , , 1, , 24for n nc h=  =  2.3. objective functions this research focuses on managing the increasing electricity demand resulting from ev charging by searching for the oevc time with two objectives. the first objective is to reduce electricity costs, and the second is to minimize energy losses in the system. the objective functions of the electricity cost minimization problem are presented in eq. (13) and the energy loss minimization problem is presented in eq. (14).  24             1 total h minimizec c ep ep h =  = (13) advances in technology innovation, vol.10, no.3, 2025, pp.220-237 226  24           1 total h minimize e p loss loss h =  = (14) where the hourly electricity cost can be calculated by:                          1 , , , h h h hnbc c c ciep en i ft i vat i = + + = (15)                    ( ? ) , , , h h h h c p p r en i hh i ev i tou = +  (16)                ( ) ? , , , h h h c p p ft ft i hh i ev i = +  (17) ( )                , , , h h h c c c vat vat i en i ft i = +  (18)   1, , , 1, , 24for i nb h=  =  the hourly loss can be calculated using eqs. (19)-(20), the equations are referred from the load flow equations in [25].                      -( )1 , , , h h h hnbp p p piloss g i hh i ev i = + = (19)           [ cos( ) sin( )] 1 nb h p v v g b loss i j ij i j ij i j j    = + = (20) 1, , , 1, , 24for i nb h=  =  2.4. constraints according to the mcs of ev user behavior, evs are not charged from the moment they leave home until they return. thus, 𝑃𝑒𝑣,𝑖 ℎ,𝑜𝑛 represents the charging power at the time h at bus i when the ev is charging, with its value ranging between a maximum, the total power charge of all evs at bus i, and the minimum is a percentage of the total number of cars (pnc). while 𝑃𝑒𝑣,𝑖 ℎ,𝑜𝑓𝑓 indicates the total power charge at the time h at bus i when the ev is not charging, which equals 0. according to eqs. (21)-(22).      , ( ) ( ),1 1, , , , , h h on hnc ncpnc p p pn nc i n ev i c i n    = = (21)  ,    0, ,   h off p ev i = (22)    1, , , 1, , , 1, , 24for i nb n nc h=  =  =  the equality constraints, which represent the load flow equations, are as follows in eqs. (23)-(24)[25].  [ cos( ) sin( )] 0 1 nb p p v v g b gi di i j ij i j ij i j j    + = = (23) advances in technology innovation, vol.10, no.3, 2025, pp.220-237 227  [ sin( ) cos( )] 0 1 nb q q v v g b gi di i j ij i j ij i j j     = = (24)    1, , , 1, , 24for i nb h=  =  the inequality constraints establish the system's operational bound, as follows. generator constraints, including voltage, active power, and reactive power at the 𝑖𝑡ℎ bus, are restricted between their upper and lower bounds, as shown in min max           min max          , min max         v v v gi gi gi p p p gi gi gi q q q gi gi gi       (25) transformer tap settings are confined within specified limits, as detailed in min max      ,t t t i i i   (26) shunt compensations are subject to their respective limits, as outlined in min max         ,q q q ci ci ci   (27) and line flow constraints in   max    f f l l  (28) 3. multi-objective particle swarm optimization (mopso) in this section, the mopso algorithm designed for the problem considered in this article is discussed. furthermore, the concept of pareto dominance, which is important for the operation of mopso for handling multi-objective optimization (moo) problems, is explained. 3.1. basic concept of pareto dominance problem-solving with multiple objectives, as presented in this article, targets reducing electricity costs and minimizing energy losses. therefore, it requires carefully balancing conflicting goals. the pareto dominance concept is applied to analyze and solve the moo problem. the pareto dominance helps identify solutions in which an improvement in one objective cannot be achieved without causing a deterioration in another. in other words, if a solution 𝑥1 is better than a solution 𝑥2, then the solution 𝑥1 is said to be the dominating one. thus, the set of non-dominated solutions, which is known as the pareto frontier, naturally represents a balanced trade-off between the two objectives. coello and salazar lechuga were among the first to extend the pso algorithm to handle multi-objective problems by incorporating the principle of pareto dominance. the key advancements include using an external repository to store and update non-dominated solutions and employing a leader selection mechanism based on pareto criteria. these modifications guide the swarm toward less crowded regions of the objective space, promoting diversity and ensuring that the final set of solutions maintains a balanced trade-off between minimizing electricity costs and reducing energy losses. this method is known as mopso [26]. advances in technology innovation, vol.10, no.3, 2025, pp.220-237 228 3.2. mopso algorithm start specify the parameter for mopso initialize search population with random position and velocity initialize the repository for the pareto frontier and set of non–dominated solution does mopso fulfill the convergence criteria? loop each particle p = 1, np update the velocity and position of each particle as follows in (29) and (30), respectively. enhance diversity by using a mutation rate to prevent getting stuck in local optimal. evaluate the objective function of each particle according to (13) and (14). p = np ? update the repository of non-dominated solution and discard points with the lowest crowding distance. calculate spread and quadratic mean distance according to (31) and (32). p = p+1 no yes yes no post processing end pareto frontier (repository) fig. 5 the proposed mopso-based oevc computational procedure mopso is an extension of the pso concept, maintaining the fundamental principles of pso while incorporating the core concept of pareto dominance to manage moo [27-28]. therefore, in each iteration, the equations for velocity and position updates remain as defined in eqs. (29)-(30), respectively. 𝑉𝑖,𝑡 is the velocity at iteration t and 𝑉𝑖,𝑡+1 is the updated velocity at iteration t+1 of particle i. 𝑥𝑖,𝑡 is position at iteration t, and 𝑥𝑖,𝑡1 is the updated position at iteration t+1 of particle i. w is the inertia weight. parameters 𝑐1 and 𝑐2 are the cognitive constant and the social constant respectively. 𝑟1 and 𝑟2 are the random numbers uniformly distributed between 0 and 1. 𝑥𝑖,𝑡 𝑃𝑏𝑒𝑠𝑡 is the best position of particle i at an iteration. this is the best solution that the particle has found till the current iteration. 𝑥𝑖,𝑡 𝐺𝑏𝑒𝑠𝑡 is the global best position across all particles up to the current. this is the non-dominated solution or best solution found by the swarm.     , 1 , 1 1 , , 2 2 , ,      ( ) ( )pbest gbest i t i t i t i t i t i tv wv c r x x c r x x+ = + + (29) , 1 , , 1          i t i t i tx x v+ += + (30) the mopso algorithm has been developed and detailed in [29] and is called the multiple design option (mdo)-mopso. in this research, the mdo-mopso algorithm has adapted to suit the specific characteristics of the problem in this article while still considering the spread and the mean of the crowding distances (quand mean) as convergence criteria according to eqs. (31)-(32). fig. 5 illustrates the methodology of the mdo-mopso algorithm.    spread qd    + = + (31) advances in technology innovation, vol.10, no.3, 2025, pp.220-237 229 21             k k quand mean d q =  (32) where 𝜇 is the parameter that quantifies whether the extreme values of the pareto frontier have changed between two consecutive iterations. 𝜎 and 𝑑 are the standard deviation and the arithmetical average of the crowding distances of point k, and q is the number of points on the pareto frontier. this modified version of the mopso algorithm integrates performance metrics and includes a post-processing step to identify mdo. the iterative process stops when one of the following three conditions. the first is when the maximum number of iterations is reached. the second is that the change in the spread measure falls below a specified relative and absolute tolerance of, or the final, the change in the quadratic mean of crowding distances falls below a specified absolute and relative tolerance. in the post-processing section, a process is conducted to identify the optimal solutions according to predefined criteria. the steps are as follows: (1) identify the search area for selecting extreme values and conducting trade-off analysis based on the pareto frontier. (2) remove any outliers to ensure only relevant and feasible solutions are considered. (3) select extreme designs that maximize energy shares, focusing on solutions that provide the best balance between objectives. (4) calculate key performance indicators (kpis). kpis are computed to evaluate and compare the diversity characteristics among the original pareto frontier, the enhanced pareto frontier, and the selected mdo points. the calculation of kpis is based on the manhattan measure. details of this calculation are presented in [29]. (5) plot the trade-offs and results to visually assess and compare the final solutions. 4. simulation results and discussion 1 2 3 4 5 6 7 8 9 10 11 12 14 15 1613 17 18 23 24 25 19 20 21 22 26 27 29 30 3128 32 33 fig. 6 the modification ieee 33-bus distribution test system with ev charging devices this section discusses the simulation of a system modified from the ieee 33-bus distribution test system by adding ev connections at each bus, as shown in fig. 6. according to this research study, the oevc scheduling controls the increasing demand for electricity to minimize electricity costs and energy losses in the system. the mopso algorithm is used for oevc scheduling, and the simulation is performed with matlab software. 4.1. ieee 33-bus distribution system without ev charging device the ieee 33-bus distribution system is used as the base system for this study, as shown in fig. 6. in the base case, the simulation is performed without connecting any ev charging devices to the system, while other cases include ev charging advances in technology innovation, vol.10, no.3, 2025, pp.220-237 230 devices. the load profile used as the system's base load for households is the central thailand load profile for july, as shown in fig. 7. this case study contrasts the outcomes of the oevc scheduling for objective functions of different purposes. 4.2. ieee 33-bus distribution system with ev charging device the ieee 33-bus distribution system with the integration of ev charging devices, as shown in fig. 6. this system is used for the simulation under uncontrolled and controlled charging conditions. for the controlled scenario, three case studies are presented to assess and compare the performance of the proposed algorithm in solving the oevc problem. 4.2.1. uncontrolled ev charging devices fig. 7 the load profiles of the system without and with ev charging ieee 33-bus distribution system with ev charging device, as shown in fig. 6. ev charging input parameters are as in [24] and the byd atto 3 model, as shown in table 2. the load profile for ev charging follows user behavior as suggested by the mcs, which is shown in fig. 7. the uncontrolled ev charging load profile, location status based on user activities and soc by considering the time period np = 1440 minutes, is shown in fig. 8. simulation results indicate that without controlling ev charging, the daily electricity cost for the entire system is 105.6815 kthb/kwh, and the daily energy loss is 6.16 mwh. fig. 8 uncontrolled ev charging simulation advances in technology innovation, vol.10, no.3, 2025, pp.220-237 231 fig. 9 comparison of real-world ev charging and mcs results fig. 9 presents the comparison of the ev charging load profile from the mcs and the real-world ev charging data from the denmark study [30]. the outcomes indicate that the load profile generated by the mcs agrees with the real-world data. in particular, the peak electricity demand is close to real-world values and occurs between 8:00 pm and 9:00 pm. table 1 mean and variance of ev usage patterns random variable mean (μ) variance (𝜎2) 𝑇𝑒𝑑𝑟 7:15 am 30 min 𝑇ℎ𝑡𝑤 30 min 15 min 𝑇𝑒𝑜𝑝 9 h and 20 min 50 min 𝑇𝑒𝑏ℎ 30 min 15 min table 2 input parameters of ev charging parameter values 𝑆𝑂𝐶𝑚𝑎𝑥 60.48 kwh 𝑃𝑐 3.7 kwh 𝑃𝑑𝑜𝑑 0.6 𝐶𝑠 𝑡 of un-aug 1.1 𝑣𝑚 60 km/h 𝑐𝑚 0.257 kwh/km ∆𝑡 1/60 h 𝑝𝑛𝑐 0.1 4.2.2. controlled ev charging devices in this article, household consumption at a voltage level lower than 12 kv is used, using the tou pricing of thailand as indicated in table 3. in this study, the oevc scheduling is proposed in three case studies to assess the effectiveness of optimal charging planning, including using the algorithms differently to solve the problem. the three case studies are as follows: table 3 time of use rate (tou rate) for type 1 residential households voltage level energy charge (bath/kwh) peak (09:00 a.m.-10:00 p.m.) off-peak (10:00 p.m.-09:00 a.m.) at voltage level 12 – 24 kv 5.1135 2.6037 at voltage level lower than 12 kv 5.7982 2.6369 (1) case i: single objective for minimizing electricity cost in this case, the pso and ga determine the oevc scheduling, considering the single objective function of minimizing the electricity cost of the system. the result of the pso achieved a minimum daily electricity cost of 96.92823 kthb, leading to a daily energy loss of 5.4966 mwh. in comparison, the result of the ga produced a minimum daily electricity cost of 98.1728 kthb, leading to a daily energy loss of 5.5542 mwh. across 30 trials in this case, the resulting averages of pso and ga were 97.1056 kthb and 98.4532 kthb. (2) case ii: single objective for minimizing energy losses in this case, the pso and ga determine the oevc scheduling, considering the single objective function of minimizing the energy loss of the system. the result of the pso achieved a minimum daily energy loss of 4.0900 mwh, leading to a daily electricity cost of 97.752 kthb. in comparison, the result of the ga produced a minimum daily energy loss of 4.208 mwh, leading to a daily electricity cost of 100.442 kthb. across 30 trials in this case, the resulting average of pso and ga was 4.3195 mwh and 4.3560 mwh. advances in technology innovation, vol.10, no.3, 2025, pp.220-237 232 (3) case iii: multi-objective for minimizing electricity cost and energy losses the mopso will be used to determine the oevc scheduling in this case, considering both the objective function that minimizes electricity cost and minimizes energy loss. the results of the mopso indicate that in the system with controlled charging, the daily electricity cost for the entire system is 97.651 kthb, and the daily energy loss is 4.39 mwh. table 4 objective function values from 30 trials by pso and ga (case i and case ii) objective function values case studies case i case ii electricity cost (kthb) energy loss (mwh) algorithm pso ga pso ga max 99.3399 101.8907 4.8523 4.5714 avg. 97.6148 099.5013 4.3196 4.3560 min 96.2823 098.1728 4.0900 4.2085 table 4 and fig. 10 show the results of the objective function values of the maximum, minimum, and average obtained from 30 pso and ga trials for case i and case ii. the comparison of the performance of pso and ga for case i and ii, as shown in fig. 10(a) and fig. 10(b). each figure includes the results of 30 trials, showing the average trend line across trials, with the best result marked by a red diamond and the worst result marked by a black circle. the simulation results show that pso is better than ga in both cases, with the pso achieving a minimum daily electricity cost of 96.2823 kthb and a minimum daily energy loss of 4.09 mwh. the ev charging scheduling results by pso and ga for case i and case ii are the minimum electricity cost and energy loss obtained from the simulation results for 30 trials, as indicated in table 5. (a) case i (b) case ii fig. 10 the results from 30 trials of the pso and ga algorithm fig. 11 pareto frontier of the proposed mopso-based oevc advances in technology innovation, vol.10, no.3, 2025, pp.220-237 233 fig. 11 shows the results from mdo-mopso for case iii. the history of fitness values evaluated during the mopso process, including optimal and suboptimal solutions, is represented by black points. the blue points indicate the mdo solution set selected after post-processing analysis. the red line shows the pareto frontier, representing the optimal trade-offs between electricity cost and energy loss. the most suitable set of solutions is derived from the pareto frontier after further filtering using a diversity criterion based on crowding distance and a post‐processing step that retains only the solutions within a predefined tolerance. this process indicates that the final solutions reflect a balanced trade-off between minimizing electricity costs and reducing energy losses. table 5 ev load profiles and minimum objective function values for the ieee 33-bus system hours power consumption (kwh) uncontrolled charging controlled charging case i case ii case iii pso ga pso ga mopso 1 0 229.40 331.27 231.58 265.42 296.96 2 0 346.16 173.09 221.73 106.09 282.31 3 0 379.73 468.63 255.62 089.09 221.05 4 0 459.64 225.38 194.35 133.60 143.07 5 0 570.91 224.49 211.49 187.90 241.65 6 0 138.92 105.90 373.12 652.74 372.80 7 0 222.69 249.58 740 408.66 675.08 8 0 0 0 0 0 0 9 0 0 0 0 0 0 10 0 0 0 0 0 0 11 0 0 0 0 0 0 12 0 0 0 0 0 0 13 0 0 0 0 0 0 14 0 0 0 0 0 0 15 0 0 0 0 0 0 16 0 0 0 0 0 0 17 0 0 0 0 0 0 18 332.445 103.23 074.66 292.30 382.40 135.02 19 740.000 080.39 074.66 121.54 076.07 138.28 20 740.000 074.01 074.66 074.69 369.62 138.72 21 740.000 074.00 108.62 088.67 175.42 135.02 22 740.000 122.09 339.17 150.63 155.40 222.82 23 096.015 132.41 482.71 212.92 226.21 203.80 24 0 454.92 455.67 219.86 159.88 181.92  total epc (kthb) 105.682 96.2823 98.1728 97.752 100.442 97.651  total losse (mwh) 6.16 5.4966 5.5542 4.0900 4.2085 4.3917 table 5 presents the results of ev charging scheduling in the three cases compared to uncontrolled ev charging schedules. the results of all three cases show that optimized charging schedules reduce electricity costs and energy loss. in case i, the best result among pso and ga is a daily electricity cost of 96.922 kthb, but the energy loss remains relatively high at 5.4966 mwh. in case ii, the best result among pso and ga is a daily energy loss of 4.0900 mwh, but the electricity cost remains relatively high at 97.752  kthb. the obtained solution in case iii is the oevc. it achieves a daily electricity cost of 97.651 kthb and an energy loss of 4.3917 mwh. cases i and ii, which consider minimizing a single objective function, using the pso and ga, achieve the minimum value for that specific objective function. however, the values for the other objective function are higher. furthermore, the pso shows slightly superior performance compared to ga. conversely, oevc scheduling with mopso considers the balance between the two objective functions in that the results for the obtained objective values are not minimum. but these are the optimal results for both objectives. therefore, the electricity cost and energy loss values in case iii fall between cases i and ii. the comparison of the ev load profile, electricity advances in technology innovation, vol.10, no.3, 2025, pp.220-237 234 cost, and energy loss for each hour is shown in fig. 12. the simulation results in fig. 12(a) compare the system load profiles, showing that the system with charging control under tou pricing results in lower on-peak energy demand, which helps reduce electricity costs and energy loss, as shown in fig. 12(b) and fig. 12(c). (a) comparison system load profile (b) comparison of electricity cost (c) comparison of power loss fig. 12 comparison of results from all cases 5. conclusions this study proposed a method for oevc that uses the mopso algorithm to solve the multi-objective optimization problem. the goal is to minimize electricity costs and energy losses in the system caused by the large increase in evs. mcs is used to model the uncertain behavior of ev usage. additionally, a tou tariff was used to promote oevc. the experiments were conducted using matlab software and tested on the ieee 33-bus distribution system. according to the simulation results, the conclusions are summarized: (1) mcs has effectively modeled the uncertain behavior of ev users, which can create realistic ev charging load profiles. this shows that the energy demand during peak periods increases, leading to higher electricity costs and energy losses. (2) the mopso algorithm is designed to explore a balanced set of solutions using the pareto frontier. this approach enables it to effectively address the multi-objective challenge of oevc by reducing both electricity costs and energy losses. however, mopso cannot minimize either aim to the lowest possible level because it operates with the pareto frontier, which focuses on balancing both objectives without allowing one to outperform the other. advances in technology innovation, vol.10, no.3, 2025, pp.220-237 235 in the future, improvements might include adaptive tuning of parameters, combining mopso with other techniques, or using real-time data to boost specific performance while still maintaining the overall balance. acknowledgment the authors sincerely want to thank the suranaree university of technology for their invaluable support throughout the project. appendix 1 abbreviations and symbols bev battery electric vehicle dip the real power demand at bus i dod depth of discharge gip the real power of the generator at bus i ev electric vehicle min gip the minimum real power of the generator at bus i mopso multi-objective particle swarm optimization max gip the maximum real power of the generator at bus i mdo multiple design option diq the reactive power demand at bus i moo multi-objective optimization giq the reactive power of the generator at bus i nb the total number of buses min ciq the minimum shunt var compensator nc the total number of cars max ciq the maximum shunt var compensator pso particle swarm optimization ?h tour the electricity pricing at hour h soc state of charge   0 nsoc initial state of charge of n cars tou time of use   max nsoc the maximum state of charge of n cars ijb the susceptance on branch 𝑖𝑗   min nsoc the minimum state of charge of n cars  total epc the total daily electricity prices  n edrt the time the n-th ev departs from its residence ?h epc the total hourly electricity prices  n htwt the duration of time it takes for the n-th ev to travel from home to the workplace ? , h en ic the electricity energy prices at bus i and hour h  n eopt the duration of time the n-th ev is parked in the garage at the workplace ? , h ft ic the electricity fuel adjustment charge prices at bus i and hour h  n ebht the duration of time it takes for the n-th ev to travel from workplace to the home ? , h vat ic the electricity value added tax prices at bus i and hour h min it the minimum transformer tap settings lf the mva flow of line l max it the maximum transformer tap settings l maxf the maximum limit of line l vij the voltage of bus i and j ft the fuel adjustment charge (at the given time) vat the value-added tax ijg the conductance on branch 𝑖𝑗 𝛿𝑖𝑗 the phase difference of voltages between bus i and j  total losse the total daily energy losses  t sc season coefficient   , , total ev i hp the total charging power at bus i and hour h mc electricity consumption in distance (kwh/km)   , , n ev i hp the charging power of n cars at bus i and hour h cp charging power (kwh)  h lossp the hourly power loss dodp depth of discharge fraction  h hhp the hourly power of the household load carp vehicle usage probability , , , h on ev i np the charging power of n cars at bus i that is charging t time step length (hr) , , , h off ev i np the charging power of n cars at bus i that is not charging mv the average velocity for a private vehicle trip advances in technology innovation, vol.10, no.3, 2025, pp.220-237 236 conflicts of interest the authors declare no conflict of interest. references [1] y. ou, n. kittner, s. babaee, s. j. smith, c. g. nolte, and d. h. loughlin, “evaluating long-term emission impacts of large-scale electric vehicle deployment in the us using a human-earth systems model,” applied energy, vol. 300, article no. 117364, 2021. 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[30] f. m. andersen, h. k. jacobsen, and p. a. gunkel, “hourly charging profiles for electric vehicles and their effect on the aggregated consumption profile in denmark,” international journal of electrical power & energy systems, vol. 130, article no. 106900, 2021. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 risk management framework-based failure mode and effect analysis for ai risk assessment yunarso anang1,* , lya hulliyyatus suadaa1, lutfi rahmatuti maghfiroh1,2, nori wilantika1, masakazu takahashi2, yoshimichi watanabe2 1department of statistical computing, politeknik statistika stis, jakarta, indonesia 2department of computer science and engineering, university of yamanashi, kofu, japan received 11 december 2024; received in revised form 11 june 2025; accepted 12 june 2025 doi: https://doi.org/10.46604/aiti.2025.14609 abstract as artificial intelligence (ai) technologies continue to spread into human life, developers must ensure benefits while minimizing the risk of adverse impacts. this study aims to evaluate risks in real-world ai applications using the ai incident database. it employs failure mode and effect analysis and the national institute of standards and technology ai risk management framework to identify failures, their causes and effects, and assess how current systems address them. a total of 100 incident reports were analyzed. the findings indicate frequent failures in autonomous systems and biased predictions. seven cases were classified in the highest risk categories, including those involving physical harm and loss of life. over 80% failures originated from algorithmic flaws or poor data quality. the method employed successfully evaluates the risks in current ai applications, revealing critical gaps in risk management and emphasizing the urgent need for targeted safeguards and proactive mitigation strategies. keywords: ai risk assessment, failure mode and effect analysis, fmea, ai incident database, nist’s ai rmf 1. introduction artificial intelligence (ai) systems have become integral to modern society, impacting everything from healthcare to autonomous vehicles. however, as ai applications accelerate, so do the associated risks. ensuring the safety and reliability of ai systems is essential to prevent unintended or even intentional consequences and protect users. ai systems should have been developed to benefit people, society, and the ecosystem while minimizing the risk of adverse effects. however, despite the undeniable ai's remarkable advancements and continuing rapid expansion into new application domains, as with most emerging technologies, there are many cases where ai systems have gone wrong, and the number of incident reports is still growing [1]. a proper method or guideline is required to minimize the risk of adverse effects. risk management, especially in manufacturing industries and critical missions such as the apollo space program, has become a formal science since the 1950s. its guideline has been published in iso/iec 31000:2018 as risk management— principles and guidelines [2]. as for ai systems, the united states national institute of standards and technology (nist) released the artificial intelligence risk management framework (ai rmf 1.0) [3]. finally, one month later, in the same year, a guideline for risk management, particularly for ai, was published in iso/iec 23894:2023 artificial intelligence—guidance on risk management [4]. both guidelines guide how organizations that utilize ai, involving development, production, deployment, or use of products, systems, and services, can manage risk specifically related to ai. it also describes processes of implementing and integrating ai risk management effectively. * corresponding author. e-mail address: anang@stis.ac.id advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 341 however, particularly in the risk assessment process, as stated by xia et al. in their study, current frameworks, including the one provided by nist and the iso/iec, lack clear guidance on how to adapt them to diverse contexts [5]. they also fail to provide a concrete and structured approach to presenting the potential failures, risks, and mitigation strategies, including their measurement. this lack of clarity can make it difficult for organizations to address identified risks effectively. especially in manufacturing industries, failure modes and effects analysis (fmea) has long been used as a familiar process analysis tool in a step-by-step approach to identify all possible failures in a design, a manufacturing or assembly process, or a product or service [6]. fmea determines the risk priority level of each failure mode based on how severe the effect is, how frequently it occurs, and how easily it could be detected. the purpose of fmea is to provide information for designers, developers, or decision-makers to take action to eliminate or reduce failures. fmea has also been used in software engineering and development for various applications such as manufacturing, safety, and automation [7-8]. back to the ai systems, an initiative by an industrial/non-profit cooperative to collect reports on real-world harms related to ai systems has been initiated [9]. the work aims to enable companies to implement (design, develop, or deploy) ai systems to avoid or mitigate incidents occurring from the ai system. the ai incidents database (aiid) supports various research and development use cases with faceted and full-text searches on over 1,000 incident reports. several researchers, such as wei and zhou [10], have used the reports to analyze the incidents occurring in ai systems. this research aims to assess the risk in the implementation of ai systems based on the incidents that occurred in the past and provide countermeasures to address the failures. fmea assessed failure modes, potential causes, and risk priority levels based on the level of consequence, likelihood, and detectability, followed by recommended actions. the aiid was used as the data source for fmea. finally, the nist's ai rmf was used as the guideline to assess the current state of the risk management of the various ai systems reported. this paper is organized as follows: section 2 outlines the background and related works. section 3 briefly describes the fmea, the aiid, the nist's ai rmf, and the assessment process. section 4 describes the results and discussion, while section 5 concludes the paper with a summary and remarks for future work. 2. background and related works in this section, the related studies are described. the beginning studies, which become the background and motivation of this research, and the latter studies, which provide hints of references for the method and guidelines used in this research, are described. the study concerning the use of ai systems, particularly in the ethical context, was conducted by jobin et al. [11]. the study investigates whether a global agreement on the principles of "ethical ai" exists among private companies, research institutions, and public sector organizations. the results reveal a global convergence of emerging ethical principles, including transparency, justice and fairness, non-maleficence, responsibility, and privacy. kaun discussed two litigation cases about fully automated decision-making (adm) in public services in sweden [12]. the research shows how different stakeholders were in conflict over what adm is and does. heinrichs examined whether ai and adm aggravate discrimination issues [13]. the author argues that the use of ai/adm can increase the issue of discrimination due to the opacity of ai/adm, which threatens the moral deliberation of understanding about discrimination. the author stated that algorithms can detect hidden forms of discrimination. brecker et al., in their research, show that it remains challenging to assess ai systems to mitigate risks arising from biased, unreliable, or regulatory non-compliance [14]. the research highlights seven areas of concern in ai assessment, from ethical compliance to regulatory gaps and socio-technical limitations. chanda et al., in their study, also investigate several cases of advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 342 failure of ai systems employing machine learning and deep learning [15]. the research focuses on the origins of the failure related to omission and commission errors in the inputs, processing logic, and outputs. wen et al., in their research, state that despite the prevalence of ai ethical problems, especially in facial recognition technology, most companies are constructively unprepared to respond adequately to the public [16]. four big technology companies' responses are deflection, improvement, validation, or preemption. the rapid development of ai has led to growing concerns about its capability to behave responsibly in making decisions, as evidenced by the increasing number of failure reports and studies of ai systems failing. this motivates xia et al. to investigate existing guidelines or frameworks of risk assessment, particularly for ai systems provided or used in the industry, governments, and non-government organizations [5]. in their research, xia et al. analyzed over 16 frameworks and assessed their effectiveness and limitations in the field of ai risk assessment. this study’s findings can assist relevant stakeholders in selecting an appropriate framework for their ai risk assessment. however, it should also offer clear guidance on extending or adapting the framework to suit various contexts. the u.s. military has used fmea as a tool for risk assessment in several industrial domains, including software applications, since the beginning of the 1940s. haapanen and helminen conducted a literature study to clarify the practical use of software failure mode and effects analysis in a safety-critical software-based automation application in a nuclear power plant [7]. takahashi et al. applied fmea to 20 existing drug-manufacturing computerized systems (dmcs) to derive standard failure modes [8]. using the list of standard failure modes, a method for risk management has been developed for several categories of dmcs, including in-house, off-the-shelf, or a combination of them. after conducting an experiment involving a less-experienced engineer, the result shows that risk management has been achieved similarly to that of an experienced engineer. finally, regarding the application of fmea in ai systems, li et al. applied fmea to an ai system to assess the risk to fairness by adding four additional columns: user groups, unfairness, fairness risk, and fairness mitigation [17]. three approaches have been introduced to maximize the fairness of an ai system: normative, procedural, and algorithmic. the paper presents how it could explicitly identify user groups, unfairness, risk, and mitigation considerations related to fair ai, which may differ from risks related to safety in ai. as a risk assessment method, compared to alternatives, such as hazard and operability study and fault tree analysis, fmea is structured, numerical, and also supports not only post-failure investigations but also anticipation by prioritizing risks and mitigation strategies [18]. compared to the other methods, which are rigid and process-focused, fmea is more flexible and better suited for more general risk analysis using a simple structured table. this nature makes it suitable for this research, whose aim is to assess the risk of ai systems based on the incident reports and to suggest countermeasures to address the failures. fmea can be applied to both new and existing systems. fmea is classified as a semi-quantitative method combining both quantitative and qualitative methods. while fmea is typically done through brainstorming processes, the availability of supporting data on failure and incident reports is inevitable. mcgregor’s initiative, aiid, for ai systems serves as an educational tool not only to raise awareness about the harms of ai but also to foster a deeper understanding of its potential benefits [19]. still, it is also a tool that can be utilized to understand and anticipate these risks. it is already collecting more than a thousand reports of ai systems causing safety, fairness, or other real-world problems. wei and zhou conducted a content analysis on aiid to examine how ai ethics issues occur in the real world [10]. from the reported database, 13 application areas have been identified as practicing unethical ai, with language/vision models, intelligent service robots, and autonomous driving taking the lead. issues in ethics appear in 8 different forms, including physical safety, racial discrimination, and unfair algorithms. advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 343 3. methods and dataset this section describes the methods and the dataset used in this research. first, the application of fmea as the primary risk assessment technique is described, detailing how it was adapted for use in the context of ai systems. second, the dataset used for the analysis is introduced, which consists of incident reports collected from a publicly available ai incident database. this dataset provides real-world examples of ai system failures, which serve as the basis for identifying potential failure modes and assessing associated risks. lastly, the overall workflow of the risk assessment process is presented, including data processing, failure mode identification, risk prioritization, and the formulation of mitigation strategies. this structured approach ensures a comprehensive and systematic evaluation of ai-related risks. 3.1. failure mode and effect analysis (fmea) fmea is a method for risk assessment. fmea follows a step-by-step approach. first, it identified all possible design, process, or final product failures. "failure modes" refer to how a function or something might fail. "failures" are any errors or defects, especially those affecting the end user, that can be actual or potential. besides identifying the possible failures, another approach in fmea is analyzing the effect, which means studying the consequences or effects of those failures. the fmea's basic steps include definition, preparation, execution, and documentation. according to iec 60812:2006 analysis techniques for system reliability – procedure for fmea, a typical fmea may include the following items: (1) function/item; (2) failure mode; (3) failure causes; (4) failure effects; (5) detection mode; (6) compensation provisions; (7) severity; (8) probability of occurrence; and (9) comments or recommendations. these items are collected, identified, and determined typically using a table. to fit the purpose of this research, fmea was modified. besides the standard items, some items have been added to associate the failure mode and effects with the principle of risks in ai rmf. to tailor the traditional fmea for ai systems, several modifications have been introduced to align with the ai rmf. these adaptations were designed to capture unique characteristics and lifecycle stages relevant to ai risk contexts. there are two additional columns: (1) lifecycle phases: maps the failure mode to the relevant ai lifecycle phase (e.g., plan and design, collect and process data, operate and monitor). (2) trustworthy characteristics: identifies which of the ai rmf’s seven characteristics (e.g., reliability, fairness, transparency) is impacted by the failure mode. more details of the items and the workflow are described in subsection 3.4. 3.2. ai incident database (aiid) aiid is a database that collects harms or near-harms realized in the real world by deploying ai systems. it aims to prevent or mitigate bad outcomes by learning from experience. as outlined in their editor’s guide, the ai incident is defined as an alleged harm or near-harm event to individuals, property, or the environment, where an ai system is suspected to be involved. ai is a system of machinery that can perform human intelligence functions, such as reasoning, pattern recognition, and understanding natural language. machine learning is a subset of ai. aiid is a crowd-sourced, collaborative collection of reports database. the essential items include information about the report title, the author or submitter, incident date, image url, incident id (automatically assigned for a new incident), and text that contains the remaining details about the incident reports. the pre-processed and searchable data is available online, while the raw data is also downloadable for further analysis. besides regular content analysis, aiid provides a taxonomybased analysis based on original incident reports, which can be tailored to specific usages. advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 344 a taxonomy-based analysis or a taxonomic system of the ai incident reports is a comprehensive classification workflow paired with the ontology structure of the incident, including the various factors and technical causes of the implicated systems [20]. currently, there are two taxonomy-based classifications: center for security and emerging technology (cset) and goals, methods, and failures. the cset refers to the ai harm taxonomy characterization of ai incidents, classifying harms relevant to the public policy community [21]. first, to understand the characteristics of ai harm or potential harm, the harm is grouped into tangible and intangible. then, the additional categories of harm are defined, such as physical or psychological harm, financial loss, property damage, detrimental content, bias, differential treatment, and violation of privacy. currently, there are two versions of the cset: version 0 and version 1. this research mainly used classified data from version 0 since version 1 is still relatively new, and the amount of data is less than that of version 0. however, since some of the newer incident reports only exist in version 1 classification, the classified data from this version is also incorporated. 3.3. ai risk management framework (ai rmf) 2023 is a milestone in risk management for ai, and the ai rmf was published [3]. the initiative to develop the framework started in july 2021 and has been improved by approximately 400 comments from 240 global organizations. since every organization is different, the challenge is treating the risks most relevant to the organization, considering its specific context. ai rmf outlines seven characteristics of a trustworthy ai system. "valid and reliable" is a necessary condition of trustworthiness as the base for the other five characteristics on top of it, from "safety to fairness", while "accountable and transparent" is one characteristic that relates to all other characteristics. approaches that enhance ai trustworthiness can reduce adverse ai risks. risk is the composite measure of the degree of impacts or consequences and the likelihood of an event occurring. the impact or consequence can be positive, negative, or both, resulting in opportunities or threats. when considering the negative impact, the risk is the magnitude of the harm. an example of how the negative impact is assessed is based on who the adverse risks contribute to. the potential harm of ai systems can be categorized into three categories: harm to people, an organization, and an ecosystem. ai risks or failures that need to be better defined are difficult to measure quantitatively or qualitatively. some challenges in risk measurement include those related to third-party software, hardware, and data; risks at different stages of the ai lifecycle; risks in real-world settings; obscurity, which can be a result of the nature of ai systems lacking transparency or documentation during development or deployment, or inherent uncertainties in ai systems and human baseline. on top of that, it can be challenging to systematize the baseline metrics for comparison for ai systems that are intended to replace or augment human activity because ai systems can perform various tasks and exhibit different behaviors compared to humans. the oecd has established a framework for categorizing ai lifecycle activities based on five crucial socio-technical dimensions. people and planet, application context (where in the original paper written as economic context), data and input, ai model, and task and output, each with properties relevant for ai policy and governance, including risk management [22]. based on these dimensions, ai rmf outlines the lifecycle of the ai systems, including the audience or actors related to each phase of the lifecycle, which includes planning and design, collecting and processing data, building and using models, verifying and validating, deploying and using, operating and monitoring, and using. while ai rmf does not provide a concrete or structured way to present the potential failure, risk, and mitigation, including their measurement, in this research, the ai trustworthy characteristics and the ai lifecycle stages defined in ai rmf are used as the guideline to assess the current state of ai systems risk management reported in the aiid, along with the fmea analysis. advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 345 3.4. workflow of the risk assessment this section describes the overall workflow of this research, as shown in fig. 1. the process begins with step 1, which involves collecting ai incident reports from a publicly available database to serve as the foundation for risk analysis. in step 2, the collected incidents are analyzed to identify failure modes, their causes, effects, and detection mechanisms. step 3 focuses on determining the severity, likelihood, and detectability levels of each failure mode to assess risk priority. in step 4, the analysis is extended by mapping the incidents to relevant trustworthy ai characteristics, lifecycle phases, and involved actors. finally, step 5 presents a discussion of the findings and offers recommendations for improving ai system reliability and risk management practices. fig. 1 workflow of the risk assessment step 1: collecting ai incident reports the ai incident reports used in this research are the database snapshot downloaded from the aiid website. the database snapshot contains all "tables" from the aiid that use mongodb. this research used the pre-classified data using ai harm taxonomy characterization stored in the "classifications" table. the table was converted into a worksheet from its original "bson" format. the table was then filtered to include only the csetv0 and csetv1 pre-classified reports. the following data have been used in the risk assessment: full description, named entities, incident id, severity, harm type, near miss, loss of life, and ai applications. step 2: identifying failure modes, causes, effects, and detection modes this step, along with the following one, constitutes the core of the fmea process applied in this research. before conducting the analysis, a standardized template for the fmea table was developed to ensure consistency and clarity in documenting failure modes, causes, effects, and detection methods. the structure of this template is presented in table 1, which serves as the foundation for systematically assessing and prioritizing risks. the table is filled with the incident reports, with each row representing a distinct incident. each column corresponds to a specific attribute or detail of the incident, such as identification, functions, failure mode, causes, detection of failure, prevention, effects of failure, and risk priority, as outlined in table 2. table 1 template of the fmea table description of unit description of failure effects of failure risk priority fmea id aiid incident id function failure mode failure causes detection of failure prevention people organization ecosystem severity likelihood detectability risk priority number “failure modes” in fmea means the ways or modes in which something might fail, and failures or any errors or defects, especially those that affect the customer and can be potential or actual. therefore, for convenience, in this research, failure modes were taken from the description of the reported incident in the aiid, which consists of the failures as well as the ways or modes in which the failures occurred. this approach allows for a practical mapping of real-world ai system failures into the structured fmea framework. by doing so, the study ensures that both the nature and context of the failures are captured, enabling a more comprehensive risk assessment. advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 346 table 2 group of columns in fmea table group of columns description description of unit contains the identity of each incident report. the fmea id is a unique number starting from 1. the aiid incident id is taken from the report. the functions are filled with "ai applications" from the report. description of failure contains the failure mode, failure causes, detection mode, and prevention. the failure mode is taken from the full description of the report. the failure causes, detection of failure, and prevention will be identified in step 3. effects of failure contains the effects or the consequences of the failure. this research divides the effects into three categories: people, organization, or ecosystem, indicating to whom the adverse risks contribute. these items will also be identified in step 3. risk priority contains the degree or level of risk obtained from multiplying the severity, likelihood, and detectability levels. in addition to these columns, two more columns will be introduced later in step 4 to enrich the dataset: trustworthy characteristics and lifecycle phase and actors. these columns are designed to establish a clear connection between each recorded failure and the relevant components of the ai rmf. by incorporating these dimensions, the analysis can more effectively align observed incidents with trustworthiness principles and lifecycle stages, enhancing the interpretability and relevance of the findings. step 3: determining severity, likelihood, and detectability level in this step, the level of severity, likelihood, or probability of occurrence, and detectability are determined based on several data points from the incident report. severity is the scale of impact or seriousness of the failure, ranging from 1 for no harm to 10 for hazardous without warning. table 3 lists the scales used to measure severity. the value is determined from the item "failure" from the ai incident report, with additional considerations from other items: "harm type" and "near miss". failure of an ai incident with no or negligible effect is categorized as a low severity scale. on the other hand, failures that cause damage to humans, financial, property, social, political, and even cause loss of life are categorized on a high severity scale. table 3 fmea scale for severity level class meaning 10 hazardous without warning safe system operational failure with high severity compromising safety without warning 9 hazardous with warning safe system operational failure with high severity compromising safety with warning 8 very high system inoperable with destructive failure without compromising safety 7 high system inoperable with equipment damage 6 moderate system inoperable with minor damage 5 low system inoperable without damage 4 very low system operable with significant degradation of performance 3 minor system operable with some degradation of performance 2 very minor system operable with minimal interference 1 none no effect next, likelihood refers to the estimated probability that a failure associated with an ai incident will occur. in this research, likelihood is quantified on a scale from 1 to 10, where a score of 1 indicates a remote or unlikely event, and a score of 10 represents a very high or almost inevitable event. the specific criteria and definitions for each level of this scale are detailed in table 4 lists the scales used to measure likelihood. table 4 fmea scale for likelihood or probability of occurrence level class meaning 9-10 very high failure is almost inevitable 7-8 high failure is repetadly occurred 4-6 moderate failure is occassionally occurred 2-3 low failure is relatively few 1 remote failure is unlikely then, detectability refers to the ability to detect the failure of ai incidents. in this research, detectability ranged from 1 for "almost certain," or the failure almost certainly can be detected by current control before being exposed to users, to 10 for "almost impossible," or no known controls available to detect the failure before exposure of the system or device that uses ai advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 347 to users. table 5 lists the scales used to measure detectability. table 5 fmea scale for detectability level class meaning 10 almost impossible no known controls available to detect the failure mode 9 very remote very remote likelihood current controls will detect failure mode 8 remote remote likelihood current controls will detect failure mode 7 very low very low likelihood current controls will detect failure mode 6 low low likelihood, current controls will detect failure mode 5 moderate moderate likelihood current controls will detect failure mode 4 moderately high moderately high likelihood current controls will detect failure mode 3 high high likelihood current controls will detect failure mode 2 very high very high likelihood current controls will detect failure mode 1 almost certain current controls almost certain to detect the failure mode. reliable detection controls with similar processes. lastly, the risk priority number (rpn) is a key metric used to evaluate the overall risk associated with a specific failure mode. it is calculated by multiplying three factors: severity, likelihood, and detectability. a higher rpn value indicates a greater level of risk, signaling the need for more immediate or significant corrective actions to mitigate potential failures and enhance system reliability. step 4: identifying trustworthy characteristics, lifecycle phase, and actors to assess the current state of the risk management of each ai application or ai system reported in aiid, in this step, the characteristics of trustworthiness and the phase and actors of the ai lifecycle related to each function in each incident are identified. step 5: discussion and recommendation finally, based on the fmea table and the results of the descriptive analysis, the discussion and the recommendation are developed. this process involves interpreting the identified failure modes, their associated risk levels, and patterns observed across the dataset. the resulting discussion highlights key findings, while the recommendations aim to address critical risk areas and propose strategies for improving system reliability. 4. results and discussion in the first step, the incident reports were collected from aiid. this research used the aiid snapshot of the "january 15, 2024" version, downloaded from their website. at the time, there were 92 incident records found with cset v0 classifications and only 62 records with cset v1 classifications. there were 53 records with cset v1 classifications, which were also found in the cset v0 classified records, while only 8 records with cset v1 classifications were not found in the cset v0 classified records. accordingly, all 92 records with cset v0 specifications plus 8 records with cset v1 classifications have been chosen as the data. one hundred incident reports of csetv0 and csetv1 annotated records have been extracted from the "classification" table. of the 100 incidents, five records with incident ids 4, 21, 29, 30, and 42 have been excluded due to the absence of ai-related harm or vague information. values of incident id, ai applications, and full description extracted from the "classification" table were put in the fmea table, as shown in table 1 in the fmea incident id, function, and failure mode columns, respectively. the next step was the identification of failure modes, causes, effects, and detection modes for each incident. two independent groups—each consisting of two researchers with academic and professional backgrounds in computation, statistics, and data analysis—analyzed the classified aiid reports separately. all four analysts had prior experience working with qualitative coding and risk assessment frameworks. before the formal annotation process began, both groups were introduced to the fmea framework through a structured internal briefing that included examples, detailed definitions of failure advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 348 modes and scoring criteria, and a walkthrough using sample aiid reports. during the annotation phase, two groups independently analyzed the data from the classified aiid to identify the causes, effects, and detection modes based on the available data from the aiid. the "effects of failure" were also determined based on the description of the incident, which was divided into three audiences: people, organization, and ecosystem. next, in the third step, each group assigned scores for severity, likelihood, and detectability (on a scale of 1 to 10), based on the information extracted from the reports. these values were then used to calculate the rpn for each failure mode. after both groups completed their independent annotations, a reconciliation process was conducted. in this stage, the two groups reviewed and compared their respective annotations and scoring results. any discrepancies were discussed, and a consensus was reached through deliberation. the final dataset used for analysis consisted of these consensus annotations. excerpts of the filled fmea table are shown in table 6. table 6 fmea table from ai incident database (excerpts) description of unit description of failure fmea id aiid incident id functions failure mode category of the failure mode failure causes detection of failure prevention 1 1 ["content filtering", "decision support", "curation", "recommendation engine"] the content filtering system for youtube's children's entertainment app, which incorporated content filter failure algorithmic filters and human reviewers failed to screen out inappropriate material only visual inspection after it is viewed video labeling by content creator 2 2 ["robotics"] on december 5, 2018, a robot punctured a can of bear spray in amazon's fulfillment center in false object detection by robot the robot failed to detect objects with active and hazardous ingredients. no hazardous object detection feature none 3 5 ["robotic surgery"] reports of robotic surgeries resulting in injury and death between 2000 and 2013, as found in the manufacturer due to system/hardware error (62%). the remainder is due to the inherent risk of surgery or human error. none none 4 6 ["comprehension", "language output", "chatbot"] microsoft chatbot, tay, was published on twitter on march 23, 2016. within 24 hours the automated tweet feature had been manipulated by twitter users only visual inspection after it is posted none 5 7 ["ai content creation", "ai content editing"] wikipedia bots meant to help edit articles through artificial intelligence clash with each other, a clash among wikipedia bots caused the bot to undo the other's edits repeatedly. the whole situation has been described as a "bot-on-bot editing war". the problem can be detected by investigating the change logs. none 6 8 ["traffick flow forecasting", "autonomous driving"] uber's autonomous vehicles have been recorded running red lights on two occasions autonomous vehicle crash the operator, uber, claimed the system's error did not cause it but blamed it for human operator error, while the driver reported that the fault was of the ai system. if there is, the failure can only be detected by the human operator. visual inspection by the driver 7 9 ["data processing", "data prediction"] a value-added measurement-based algorithm used to calculate the effectiveness of school the algorithm only covers two objects human reports none 9 11 ["risk assessment", "crime projection"] an algorithm developed by northpointe and used in the penal system is shown to be inaccurate systems produce discriminatory outcomes (race, gender, religion) lack of high-quality (unbiased and nondiscriminative) data training it can be detected by analyzing the results or the reports. none 10 12 ["natural language processing"] the most common techniques used to embed words in natural language systems produce discriminatory outcomes (race, gender, religion) lack of high-quality (unbiased and nondiscriminative) data training it can be detected by analyzing the results or the reports. none advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 349 table 6 fmea table from ai incident database (excerpts) (continued) description of unit effects of failure risk priority nist ai rmf characteristics fmea id aiid incident id people organization ecosystem severity likelihood detectability risk priority number phases/actors trustworthy characteristics 1 1 exposing children to videos that include sex, drugs, violence, profanity, and conspiracy theories 5 3 9 135 build & use model, verify and validate valid and reliable 2 2 it had a secondary impact on people caused by the active and hazardous ingredients, which caused several workers to be exposed to the fumes from the spray, having trouble breathing and a burning sensation in the eyes and throat. 6 2 9 108 use or impacted by safe, valid, and reliable 3 5 injuries from burns from sparks emitted by the machine, robotic arms becoming dislodged in the patient, and the surgeon losing control of the machine or the machine powering down unexpectedly. 7 5 10 350 use or impacted by safe, valid, and reliable 4 6 people who use twitter feel unpleasant as a result of this behavior. 4 5 9 180 use or impacted by explainable and interpretable 5 7 two notable cases between darnkessbot and xqbot led to 3,629 edited articles between 2009-2010 and between tachikoma and russbot, leading to more than 3,000 edits. the failures have occurred across articles in 13 languages on wikipedia, with most occurring in portuguese and german. 2 5 9 90 use or impacted by explainable and interpretable 6 8 while there were no injuries or collisions, it may lead to an incident that caused collision and damage to property, or lead to human injuries and life lost. 2 3 5 30 operate and monitor safe, valid, and reliable 7 9 teachers who were evaluated as not being effective will be affected. the school will lose some of its teachers due to the wrong evaluation. 2 3 8 48 build & use model, verify and validate valid and reliable, fair with harmful bias managed, accountable and transparent advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 350 table 6 fmea table from ai incident database (excerpts) (continued) description of unit effects of failure risk priority nist ai rmf characteristics fmea id aiid incident id people organization ecosystem severity likelihood detectability risk priority number phases/actors trustworthy characteristics 9 11 according to the report, 40% of the predictions were incorrect. since then, the system has been used in broward county, florida, to help judges make decisions surrounding pre-trial release and sentencing post-trial; the sentence may be inaccurately judged. also, the system is likely to produce racially skewed results, according to a review by propublica. it may influence the trust in the courts and legal system. it may influence trust in automated systems in highly impacted systems like courts and legal systems. 3 5 8 120 collect and process data, build and use model, verify and validate valid and reliable, fair with harmful bias managed, accountable and transparent 10 12 the effect may affect people depending on the application. the effect may affect the organization depending on the application. the effect may broadly destroy the ecosystem if not correctly addressed. 3 5 8 120 collect and process data, build and use model, verify and validate valid and reliable, fair with harmful bias managed, accountable and transparent the most often found failures of all processed incident reports are related to systems producing prediction results biased by race, gender, or religion. in several incidents, biased prediction results occurred due to flaws in the algorithm used or a lack of diversity in the dataset used for training. for example, when users search for a particular name of a public figure, google suggests a specific religion or ethnicity in its autocomplete. however, in some incidents, the discriminatory prediction results occurred on purpose. a health system was found to include a race multiplier in the algorithm for estimating kidney function. researchers found in their study that the race multiplier resulted in an underestimated risk of african-american patients, leading to inequitable chances of being placed on a kidney transplant waiting list [23]. besides that, other failures that are also often found are related to autonomous vehicle crashes, including car accidents, self-driving shuttle accidents, and even a plane crash, resulting in human physical injury or loss of life. fig. 2 illustrates a portion of each function of the incident data. there is no dominant function where an incident can contain multiple functions. however, functions related to facial recognition, decision support, recommendation engines, image recognition, and image classification appear more frequently than other functions in the reported ai incidents. from the investigation, more than half of the incidents were caused by algorithm problems, and almost 30% were caused by data problems. the result is in line with typical ai applications, as stated by hamzah-cherif et al. in their research, that the inappropriate number and the poor quality of the training data may produce the issue in the algorithm, thus influencing the accuracy of the result [24]. fig. 2 distribution of functions related to each failure mode (an incident may have more than one function) advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 351 based on the incident reports, 35.79% of incidents could only be detected through human reporting, 35.79% through analysis of results, data, or models, and approximately 20% through both methods. one of the most notable findings from this study is that 87.37% of the incidents analyzed had no documented prevention method. this striking absence suggests that many organizations either do not engage in proactive risk mitigation or fail to institutionalize and communicate such efforts. several factors may contribute to this gap, including the lack of standardized risk assessment frameworks, insufficient regulatory pressure, limited organizational expertise in ai safety, the rapid pace of ai deployment, and a prevailing focus on performance over robustness. the implications are significant: without preventive strategies, organizations are more likely to respond reactively to failures, increasing the likelihood of harm, reputational damage, and regulatory scrutiny. this reactive posture contrasts sharply with established engineering practices, such as fmea and the risk management framework (rmf), which emphasize early identification and mitigation of potential failure points. as kotonya and sommerville [25] argue, preventive planning and early intervention are essential in complex system development to reduce downstream impacts and ensure system dependability. fig. 3 shows the distribution of the number of incidents for each level of severity, likelihood, and detectability. the severity level has a value between 1 and 10. the severity level means the higher the level number, the more severe the incident. while the likelihood level means the higher the level number, the greater the chance that the incident will occur. an analysis of the severity and likelihood of incidents reveals that most events are not highly severe—42.1% are at level 2 on a 10-point scale. however, the chance that these incidents happen is relatively high, with 43.2% at the likelihood level 5. only 4.2% of incidents have a likelihood level of 1, or a failure is unlikely. this shows that even if the damage caused by each incident is small, they happen often enough to create long-term or widespread effects. in fmea analysis, carlson has emphasized that frequently occurring minor failures can point to systemic design weaknesses if not addressed early [26]. in addition, the detectability level represents the likelihood that process controls will detect the existence of a defect before the subsequent process or before exposure to a client. this level ranges from 1 to 10. level 10 means it is almost impossible to detect the upcoming incident, and level 1 means current controls are nearly certain to detect the failure mode. the analysis of detectability results in many failures that are difficult to detect in time (fig. 3 (c)). around one-third of incidents are at detectability level 8, meaning they are hard to catch before causing harm. only 1% of incidents are at level 10 (the hardest to detect), and none are at level 1, where a failure is almost guaranteed to be detected. this means that current monitoring systems may not be strong or advanced enough to find problems early. (a) severity (b) likelihood (c) detectability fig. 3 number of incidents by the level of severity, likelihood, and detectability furthermore, the relationship between the severity, likelihood, and detectability of failure was examined. it is often intertwined, but only sometimes straightforward. generally, the severity of failure refers to the scale of failure effect, and the likelihood of failure refers to the probability or chance of failure. detectability, on the other hand, refers to the ease or difficulty of identifying that failure once it has occurred by process controls before the subsequent process or exposure to a client. this relationship is shown in a sankey chart in fig. 4. in many cases, hazardous failures without warning and high-impact failures advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 352 are unlikely to occur and may be harder to detect. however, some of them are moderately detectable. most failures with low and moderate probability occurrence are both hard to detect and easy to detect. this suggests that some failures may not receive as much attention in the failure detection controls. fig. 4 relationship between the severity, likelihood, and detectability of failure in the fourth step, the characteristics of the current ai risk management according to the nist ai rmf were determined as shown in table 6. according to ai rmf, an ai system has several key dimensions surrounding its lifecycle stages. in this research, the potential impacts and risks of the incident phases have also been identified. each incident may have one or more possible effects and risks in phases. of all identified incidents, almost half have one identified phase, while the remaining have two or three phases each in a similar proportion. (a) phases/actors (b) characteristics of trustworthy fig. 5 characteristics of current ai system risk management from all identified phases in incidents, as shown in fig. 5(a), "plan and design" and "operate and monitor" are the most frequently identified phases, with 50 and 47 incidents, respectively, or 29.07% and 27.33% of all incidents. this means that 29.07% of the failure modes of all the incidents examined in this study can be identified during the early stage of the ai lifecycle, the "plan and design" phase. in the ai lifecycle stages, activities conducted during the "plan and design" phase encompass auditing and assessing the impact of the ai system to be developed from legal and ethical perspectives. yet, in 27.33% of incidents, failure could only be detected after the ai systems were operated. besides the "plan and design" and "operate and monitor" stages, most failure modes are detected in the "collect and process data" and "verify and validate" phases. this is due to the functional problems of most incidents, which are related to algorithms and training data. this data tells us that risks often appear either very early or only after the ai system has already been deployed. it also means that managing risk must happen throughout the entire development cycle, not just at the beginning or end. this supports the nist ai risk management framework, which recommends continuous assessment and improvement throughout the ai lifecycle [3]. advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 353 building on the mapping of incidents to ai rmf lifecycle phases, analysis is conducted on the distribution of incidents and identified targeted risk management strategies for each phase. in the “plan and design” phase, ethical impact assessments and stakeholder engagement are critical to anticipate societal and legal implications. during the “collect and process data” and “verify and validate” phases, technical interventions such as adversarial robustness testing, bias audits, and validation against edge cases can mitigate common failure modes. for the “operate and monitor” phase, continuous monitoring and incident response protocols are emphasized. finally, by advocating for post-deployment audits and feedback loops, iterative improvements could be achieved. these additions aim to provide actionable guidance aligned with the ai rmf lifecycle, enhancing the utility of the framework introduced in this research for practitioners. besides phases/actors, the characteristics of the trustworthiness of the incident were also identified. creating ai people can trust involves finding the right balance among its various characteristics, depending on its use. however, this balancing act often comes with trade-offs. organizations may need help with tough decisions as they try to find this balance, considering the specific context in which decisions are made. more than 35% of incidents have validity and reliability issues. the following most significant issues were fairness, accountability, and transparency. safety was the next frequent issue, reaching more than 12%. the detailed illustration is shown in fig. 5(b). while the ai rmf offers a comprehensive, principle-based structure for evaluating the trustworthiness of ai systems, such as fairness, robustness, and transparency, it does not provide detailed mechanisms for identifying and prioritizing specific failure points within ai components or processes. fmea complements ai rmf by offering a systematic, bottom-up approach to identifying failure modes, analyzing their causes and effects, and prioritizing them based on severity, occurrence, and detectability. by combining ai rmf’s strategic guidance with fmea’s operational rigor, the approach of this research enhances the effectiveness of ai risk assessment and management. this integration ensures that both abstract trustworthiness goals and concrete failure risks are addressed in a unified framework. fig. 6 severity–likelihood–detectability matrix furthermore, the risk priority was examined to see which incident needed more attention. meriem and abdelaziz created a severity–likelihood–detectability matrix incorporating relationships between those three risk-composing measurements in one matrix, to obtain the categories for prioritizing the risks [27]. in order to prioritize the risks, each risk priority is categorized into five levels, from category 1: no impact to category 5: critical. the matrix, with modification, is shown in fig. 6. seven incidents have the risk priority of categories 4 and 5. of those with risk priority of category 5, there are three incidents: one which happened to boeing 737 max caused by pilots not being able to override the mcas’ actions; one which occurred to tesla’s autonomous car caused by flaws in the autopilot algorithm; and one which occurred in a factory in india caused by a malfunction of the autonomous robot. all these incidents cause loss of life. according to the suggestion of this category, the functions need to be fixed before the application can be used again. advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 354 table 7 ai incidents with risk priority of categories 4 and 5 category functions failure effect of failure failure mode failure causes people organization 4 ["robotic surgery"] reports of robotic surgeries resulting in injury and death between 2000 and 2013 as found in the manufacturer and user facility device experience (maude) database, a database of both voluntary and mandatory reports of mishaps. within the 14-year span, there are 8,091 recorded malfunctions resulting in 1,391 injuries and 144 deaths. due to system/hardware error (62%), the remainder is due to the inherent risk of surgery or human error. injuries from burns from sparks emitted by the machine, robotic arms becoming dislodged in the patient, and the surgeon losing control of the machine or the machine powering down unexpectedly. 4 ["autonomous driving","self-driving vehicle"] a robot at an office building in washington, dc, ran itself into a water fountain. the robot, named knightscope k5, was developed as a security robot that uses facial recognition and a variety of sensors to detect criminals. the reasons the robot fell into the fountain are unclear. the algorithm falsely detects a criminal may harm physical properties. may injure human's physical health/safety if falsely detected as criminal trust lost in security robot 4 ["computer vision","autonomous driving","self-driving vehicle"] on february 14, 2016, a google autonomous test vehicle was involved in a low-speed collision with a bus in google’s hometown of mountain view, ca. the selfdriving car, a lexus rx450h suv, was attempting to navigate around an obstruction by merging toward the middle of a wide lane on el camino real, while a bus was approaching from the rear. the car and its test driver expected that the bus would slow down and allow the merge. however, the bus continued, apparently not expecting the selfdriving car to attempt the merge, resulting in a low-speed collision. the autonomous vehicle algorithm expected that the bus to give way may injure human's physical health/safety trust lost on autopilot car 4 ["stoplight recognition","semiautonomous driving"] a tesla model 3 misidentified flags with "coop" written vertically on them as traffic lights. flaws in autopilot algorithm may injure human's physical health/safety trust lost on autopilot car 5 [""] a factory robot at the skh metals factory in manesar, india, pierced and killed 24-year-old worker ramji lal when lal reached behind the machine to dislodge a piece of metal stuck in the machine. the robot is pre-programmed to weld together sheets of metal, and had dropped a piece of metal. when lal reached to dislodge the piece of metal, he was pierced by a welding arm and electrocuted, dying as a result. the robot dropped a piece of metal, and the worker had apparently moved too close to the robot while adjusting the metal a worker was killed trust lost in factory robot 5 [] a boeing 737 crashed into the sea, killing 189 people, after faulty sensor data caused an automated maneuvering system to repeatedly push the plane's nose downward. pilots were supposed to be able to override mcas' actions, but they weren't during the incident death trust lost 5 ["autonomous navigation","semiautonomous driving","object detection","classification"] a tesla model 3 on autopilot mode crashed into a pickup on a california freeway, where data and video from the company showed that neither autopilot nor the driver slowing the vehicle until seconds before the crash. flaws in autopilot algorithm death trust lost on autopilot car the following recommendations are proposed: (1) for the boeing 737 max case, future designs should ensure that automated systems can always be overridden by pilots, with clear alerts and simplified interface logic. additionally, pilot training must include thorough simulation-based scenarios for handling such system behavior; (2) for tesla’s autonomous car case, developers should improve multi-sensor fusion (e.g., combining radar, lidar, and camera data) and implement stricter advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 355 real-world validation of edge cases. regular third-party safety audits should also be required before deploying updates, and (3) for a robot in the indian factory case, industrial robots should include advanced fail-safe mechanisms, such as emergency shutdowns triggered by proximity sensors or human detection systems. safety zones must be enforced using physical barriers and programmable safety logic. the remaining incidents with risk priority of categories 4 and 5 are shown in table 7. subsequently, from the aiid, there are functions derived from each ai system. by clearly defining the relations between functions, failures, and their modes, the fmea can be used to identify the appropriate corrective actions. for example, most reported incidents involving high severity levels involve some autonomous or autopilot functions. to lower the risk of the failure's effect, the ai systems' developers can then focus on improving the functions' algorithm. while this study is based on empirical data from the aiid, such sources may underrepresent lower-severity-oriented failure modes. following the approach of spreafico and sutrisno [28], integrating synthetic failure generation, particularly for social sustainability issues like fairness, inclusivity, and transparency, can help address this gap. by simulating anticipated failures, the fmea can be extended to capture a broader and more socially relevant risk landscape. this hybrid approach enhances both the comprehensiveness and ethical responsiveness of ai risk assessments, supporting more inclusive and sustainable system design. finally, while the aiid serves as a valuable repository for tracking ai-related failures, its reliance on publicly reported incidents introduces several limitations. these include a selection bias toward high-profile or media-sensationalized cases, limited representation of incidents in critical infrastructure sectors, such as healthcare, energy, and transportation, where proprietary constraints or national security concerns often prevent disclosure, and underreporting from regions with weaker regulatory or journalistic frameworks. as a result, the dataset may not fully capture the breadth or systemic nature of ai risks, particularly in domains where failures could have cascading societal impacts. moreover, the voluntary nature of contributions can skew the dataset toward consumer-facing applications, leaving gaps in industrial or embedded ai systems. the lack of standardized definitions and reporting protocols further affects consistency and comparability across cases. importantly, the relationship between ai incidents and ai risk is not always linear or unidirectional. while some incidents directly reflect known risks, others may act as precursors or amplifiers of broader systemic vulnerabilities. in this sense, incidents can both result from and contribute to the evolution of ai risk. recognizing this dynamic interplay allows for a structural distinction between "ai" as a technological paradigm and "ai systems" as context-specific implementations. such a distinction enables a more granular analysis of incidents to understand how individual system failures may signal latent risks in the broader ai ecosystem. this structural approach supports more robust risk assessments by revealing patterns that transcend individual systems and by informing domain-sensitive mitigation strategies. as noted by agarwal and nene [29], these gaps underscore the urgent need for structured, domain-sensitive reporting schemas to enhance data quality, ensure broader applicability in ai risk assessment, and support more equitable and comprehensive governance frameworks. 5. conclusions this study investigated various failure modes in ai systems by analyzing incidents from an ai system incident database. using the fmea framework, the research identified the causes and effects of failures, assessed their severity, likelihood, and detectability, and evaluated the associated risk levels. the analysis was further enriched by mapping each failure to the ai lifecycle phases, involved actors, and trustworthy characteristics as defined by the nist ai rmf. the methodology was applied to consumer ai systems but is designed to be adaptable across domains. key conclusions from this study are as follows: (1) characterization of ai failures: ai system failures differ from traditional hardware failures. while hardware failures often stem from physical degradation, software—and by extension, ai system—failures are more abstract and functional in advances in technology innovation, vol. 10, no. 4, 2025, pp. 340-357 356 nature. a failure mode in an ai system is defined as a way in which a component fails to meet its intended function or requirements. (2) applicability of fmea to ai systems: the fmea framework is effective in identifying and prioritizing ai system risks. it provides a structured approach to assess failure modes based on severity, likelihood, and detectability, offering a quantifiable risk profile for each incident. (3) insights into trustworthiness: by aligning failure modes with the nist ai rmf, the study highlights how failures impact trustworthiness characteristics such as reliability, safety, and accountability. this alignment supports more targeted risk mitigation strategies. (4) domain-agnostic methodology: although the study focused on consumer ai incidents, the fmea-based approach is inherently adaptable to other high-stakes sectors such as healthcare, critical infrastructure, and defense. incorporating domain-specific data sources—like regulatory filings and audit reports—can enhance the contextual relevance of the analysis. (5) recommendations for risk mitigation: the findings suggest that proactive identification and mitigation of high-risk failure modes can significantly improve the reliability and trustworthiness of ai systems. this includes better design practices, operational safeguards, and continuous monitoring. as part of future work, further analysis of the incidents with high-risk priority numbers due to their severity, likelihood, and detectability needs to be conducted to provide recommendations for corrective actions to lower the risk. additional methods and techniques for risk assessment and management shall be incorporated. conflicts of interest the authors declare no conflict of interest. references [1] a. drapkin, “ai gone wrong: an updated list of ai errors, mistakes and failures,” https://tech.co/news/list-aifailures-mistakes-errors, 2024. [2] iso/iec 31000:2018 risk management — principles and guidelines, iso/iec, 2018. 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[29] a. agarwal and m. j. nene, "addressing ai risks in critical infrastructure: formalising the ai incident reporting process," 2024 ieee international conference on electronics, computing and communication technologies (conecct), bangalore, india, pp. 1-6, 2024. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). https://creativecommons.org/licenses/by-nc/4.0/ microsoft word aiti#14372 20250526 (update header information) advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 a modified exponential model for predicting the fatigue crack growth rate in a pipeline steel under pure bending sergei sherbakov1, pawan kumar1,*, daria podgayskaya1, pavel poliakov2, vasilii dobrianskii2, vishwanatha h m3 1joint institute of mechanical engineering of the national academy of sciences of belarus, minsk, belarus 2moscow aviation institute (national research university), moscow, russia 3department of mechanical and industrial engineering, manipal institute of technology, manipal academy of higher education, manipal, india received 08 october 2024; received in revised form 09 february 2025; accepted 13 march 2025 doi: https://doi.org/10.46604/aiti.2024.14372 abstract the present work proposes a fatigue crack growth rate (fcgr) model for steel pipelines subjected to sinusoidal loading using a modified exponential function. the modification in the exponential function is made for the non-dimensional parameter using the stress intensity range (δk) as the crack driving force. the acceptable values of δk for fcgr in stage-i ranged between 17.45-20.46 𝑀𝑃𝑎√𝑚, between 20.46-21.41 𝑀𝑃𝑎√𝑚 for stage-ii, and between 21.41-21.98 𝑀𝑃𝑎√𝑚 for stage-iii. a new correlation is also developed between the specific growth rate and the non-dimensional number. the modified exponential function predicted the fcgr within the acceptable values for all three stages in the radial direction. it shows the best performance for stage-i of fcgr and the lowest for stage-iii. the microstructure envisages shallowed microvoids, while the striations and secondary cracks are mostly perpendicular to the fcg direction. keywords: exponential function, specific growth rate, fatigue crack, stress intensity factor, sdg 9 1. introduction fatigue failure of steel pipes is one of the most important design criteria in pipeline engineering. the steel pipes are used to transport fluids in the petrochemical, aerospace, automobile, and chemical industries [1]. the change in pressure and external loading during service envisages a sinusoidal loading, which makes the steel pipes susceptible to fatigue failure [2]. therefore, fatigue crack growth (fcg) is a vital failure phenomenon in pipeline steel due to the vibrational nature of fluid and operational environment [3]. it is quite possible that during a significant service time, a microcrack can be generated in the pipeline surface, which acts as a stress accumulator in its vicinity, and once threshold stresses accumulate, it results in fcg [4-5]. it is also possible that a new crack can generate and change the stress field locally, providing the required localized stresses for multiple/or new crack propagation. one of the driving forces in such failure is stress intensity. in general, the stress intensity is not defined for certain crack geometries (solid or tubular) of pipes, as the pipeline is not a standard geometry for fatigue crack experimentations and simulations [6-7]. the varying thickness of different pipes makes it even more difficult to consider different loading conditions and applications [8-9]. also, the initial microcrack in pipes can be of part-through type or throughthe-thickness dominant type, yet the crack propagation characteristics of such pipe geometries remain unknown. * corresponding author. e-mail address: kumarpawan@mail.ru advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 239 to address such phenomena of fatigue crack propagation in steel pipes, different fcg models were developed considering external sinusoidal load, the effect of inclusion, and the environmental effect [10-12]. these models were based on several approaches, including finite element analysis, mathematical modeling, and descriptive analysis. teng an et al. calculated the fcg of x80 grades of pipeline steel, considering the hydrogen pressure [13]. they reported a reduced fatigue due to hydrogenaccelerated crack propagation. in a similar study, fatoba et al. studied the low-cycle fatigue behavior of api5l x65 pipeline steel under completely reversed strain-controlled situations at ambient temperature and reported a decrease in fatigue life with increasing plastic strain amplitude [14]. jiang et al. also reported that fcg is mostly dependent on stress intensity range and reported an increasing fcg [15]. in addition to fatigue load, bonab et al. considered the influence of microstructure on fcg in api x65 pipeline steel. they studied a non-metallic inclusion and reported crack nucleation after a significant number of loading cycles [16]. in a similar work, the authors have also studied features of intergranular and trans-granular fcg and observed an accretion of σ3 boundaries around the fatigue microcracks as high-energy boundaries [17]. apart from external loading and inclusion, the environmental effect on fcg was also studied. ronevich et al. considered the effect of microstructure banding on hydrogen-abetted fcg in x65 pipeline steels [18]. in a similar work, slifka et al. also studied the influence of microstructure on the hydrogen-assisted fcg in pipeline steel and reported the effect of different microstructures, considering the emphasis on the low δk regime [19]. igwemezie et al. also studied the influence of microstructure on fcgr in marine steels, considering the paris region of fcg. the authors reported that the crack tip diversion, crack front bifurcation, and metal crumb formation affect the fcgr [20]. sahu et al. predicted fcgr for tp316l stainless steel pipe in the circumferential direction [21]. however, they did not consider different stages of fcgr for modeling. it is believed that the fatigue failure in pipes is more significant in the radial direction and that a break-before-leak model is more relevant and practical for applications. in earlier work, kumar et al. used an exponential model, the gamma function, and finite element analysis to predict fcgr in tp316l stainless steel pipe specimens [22-24]. however, the modeling was carried out without considering the different stages of fcgr. also, the prediction of the fcgr was only for the initial crack propagation. the model did not address the fcgr when the crack propagation was accelerated with the number of cycles. therefore, it is still unknown whether the fcgr is in accelerated stages, and the corresponding modeling formulation has yet to be defined. further, they did not address the microstructural features of the fatigue-fracture surfaces. hence, it is believed that a more comprehensive analysis and modifications are required so that the fcgr can be predicted not only for the initial stage but also for all three stages of fcg. the relationship between the specific growth rate and the non-dimensional number also needs to be addressed. the effect of stress accumulation on the fatigue-fracture surface features also needed to be analyzed. therefore, in the present work, a modified exponential model is developed for fatigue crack propagation in through-the-thickness pipe walls to predict the fcgr in all three distinct stages. a relationship between a specific growth rate and the non-dimensional number is established. the predicted model is validated through the experimental data obtained from a four-point bending test conducted at ambient temperature. the performance of the model is analyzed using statistical methods like mean absolute error (mae), mean squared error (mse), root mean square error (rmse), mean prediction ratio (mpr), mean % deviation, and coefficient of determination (r2), followed by error band scatter analysis. the microstructural features of the fatigue-fractured surface are studied using standard microscopy characterization. 2. materials and methodology the tp316l stainless steel pipe was deformed to large-scale plastic deformation under pure bending using a servohydraulic dynamic testing apparatus (instron 8800). the four-point bending test setup and the pipe specimen with a centrally attached crack opening displacement (cod) gauge on a servo-hydraulic universal testing apparatus (instron 8800) are shown in fig. 1 [22-23]. however, the representation of the cross-sectional view of the pipe specimen and constant amplitude loading advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 240 condition is shown in fig. 2 and fig. 3, respectively. the specimen dimensions exhibiting inner radius, outer radius, thickness (in the radial direction), span of the support rollers, span of the load rollers, and the end clearance are presented in table 1. the mechanical properties of the tp316l stainless steel are presented in table 2. fig. 1 four-point bending test setup the four-point bending test was conducted considering a sinusoidal load of 22.5 kn, a stress ratio of 0.1, and a frequency of 4 hz was applied to the specimen. the four-point bending test was conducted at ambient temperature. the distance of the load line and reaction force was 110 mm and 225 mm, respectively, from the center of the pre-notch. the pre-notch had a semi-elliptical geometry with the length of the major axis 22.96 mm, and the semi-minor axis (in the radial direction of the pipe) 2.28 mm. fig. 2 cross-sectional view of the pipe specimen fig. 3 constant amplitude loading condition in four-point bending advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 241 the fcg data in terms of crack length (a) and number of loading cycles (n) was monitored using a crack opening displacement (cod) gauge and processor. the cod gauge was mounted at the crack mouth with suitable knife edges. since there is no direct crack-compliance correlation available for the measurement of the fcg in part-through cracked pipes, the cod gauge was calibrated to find the correlation between radial crack lengths and δcod output [22-23]. the calibration curves thus obtained have been utilized for the indirect measurement of the crack lengths in the radial direction. the microstructural characterization of the fatigue-fractured pipe specimen was carried out using a jeol jsm-6480 lv scanning electron microscope (sem). the samples for sem analysis were prepared as per the regular metallographic procedures. the mounted samples were mechanically polished using the emery papers with grit levels ranging from 100-500 µm, followed by cloth polishing using a tegrapol polishing apparatus. the polishing grit in the size sequence of 9 µ, 3 µ, and 1 µ was used for mechanical polishing. table 1 specimen dimensions [22-23] outer radius (ro) inner radius (ri) thickness (t) span of the support rollers span of the load rollers end clearance 30mm 21mm 9 mm 450 mm 220 mm 25 mm table 2 mechanical properties of tp 316l stainless steel [22-23] material modulus of elasticity (e) poisson’s ratio (µ) yield strength (σys) ultimate tensile strength (σut) 316l stainless steel 220 gpa 0.3 366 mpa 611 mpa 3. results and discussion this section describes the stress intensity factor and its influence on crack propagation. the fatigue crack growth rates in stagesi, ii, and iii are defined. the modelling of fcgr for all three stages is formulated with a modification to the exponential function. it is then followed by a performance evaluation and comparison with earlier developed models. the microstructural features are discussed to characterize fatigue crack propagation. 3.1. stress intensity factor and crack propagation the fcg data was generated using the instron 8800 apparatus. the increase in a with n was recorded. the stress intensity factor (k), considering the mean of 5 specimens under pure bending, with corresponding a and n, is shown in fig. 4. the theoretical k indexes the pre-notch stress field singularity by delineating the stress field in the vicinity of the pre-notch where the singularity occurred. in other words, k predicted the state of stress near the vicinity of the pre-notch (which was at the center of the specimen with a semi-elliptical geometry). the theoretical k depends on the geometry of the crack, the geometry of the specimen, structural constraints, and loading conditions. the k was calculated using the methodology provided by laham et al. [25]. the geometrical functions (𝑓 and 𝑓 ) were extra-plotted for the pipe specimen and elliptical crack geometries. the theoretical k is given by eq. (1). 3 1 2 2i i t t bg bgi r ra c a c k a f f t a t t a t                    (1) where 𝜎 is bending stress, 𝜎 is axis-symmetrical stress (zero in the current case), a is the depth of the elliptical defect/length of the semi-minor axis, t is the thickness of the pipe, 2c is the length of the major axis, and ri is the internal radius of the pipe. the first computable a of 0.87 mm was detected at a loading cycle of 60530. in the current work, the n for the first appearance of a was considered as the start of the loading cycle. this premise was considered for plastic behavior and eliminated all linear advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 242 elastic deformation. fig. 4(a) describes variation in k with a. the curve shows a typical k-a variation for fcg [26]. the slope of the curve decreases with the a continuously. in other words, initially, for a small increment in a, the corresponding increase in k was greater. for further crack propagation, the slope decreases, which means a lower incremental k was required for the corresponding increment in a. therefore, it envisages a preceding crack that changes the stress field near the vicinity of the crack tip, and envisages a new crack to be less resistant to external bending [27]. this nature continued till the complete failure of the sample. it is to be noted that the slope of the k-a curve after a preceding crack length of 4 mm decreased significantly as compared to the slope at the initiation of the crack (when a=0.85 mm). the variation in k with n is shown in fig. 4(b). the nature of the plot shows a typical k-n curve [28]. in contrast to the k-a curve, the slope of the k-n curve increases continuously till the fracture. initially, a higher n is required for a small increase in k, which indicates that the initial crack propagation required a large accumulation of external bending stresses (using higher n). with the crack propagation and accumulation of external bending stresses, the subsequent requirement of n for an incremental k decreased. it is suggested that the preceding bending stress accumulation made the crack tip more susceptible to propagating (growing). a much higher slope of the k-n curve after n reaches 60,000 envisages a highly plastic deformation state, which eventually leads to the fracture of the specimen. (a) k vs a graph (b) k vs n graph fig. 4 the variation in k with a and n 3.2. fcgr the fcgr provides the features of crack propagation. it is the rate of change of a with n; in other words, it provides an idea of incremental a in a given interval of n. the variations of da/dn with δk, a, and n are presented in figs. 5, 6, and 7, respectively. based on the nature of fcgr, it is categorized into three discrete stages: stage-i, stage-ii, and stage-iii for the present investigation. the three distinct stages characterize fcgr. 3.2.1. fcgr in stage-i as shown in fig. 5, the stage-i of fcgr is in the threshold δk range 17.45-20.46 𝑀𝑃𝑎√𝑚. the appearance of the first crack is observed at δk =17.45 𝑀𝑃𝑎√𝑚, and the slope increases gradually up to δk =20.46 𝑀𝑃𝑎√𝑚. the initiation of the first crack required a critical accumulation of bending stresses near the vicinity of the crack tip, which was provided by the threshold δk [29]. the da/dn versus δk curve is detrimental to fcg studies [27]. the δk provided the driving force for fcg, which is proportional to applied bending stress and the square root of a (equation 1). the slowly increasing slope of the da/dn versus δk curve in stage-i envisages that a higher crack driving force was required initially. this is the region where the crack resisting parameter (kc) and materials property (stiffness, e) oppose the crack driving force (δk) at best after the threshold δk. it required a higher δk for a small increment in the da/dn. the fcgr versus a curve is shown in fig. 6. 1.90e+01 2.00e+01 2.10e+01 2.20e+01 2.30e+01 2.40e+01 2.50e+01 0 1 2 3 4 5 6 k (𝑀 𝑃 𝑎 √𝑚 ) a (mm) 1.90e+01 2.00e+01 2.10e+01 2.20e+01 2.30e+01 2.40e+01 2.50e+01 0 20000 40000 60000 80000 k (𝑀 𝑃 𝑎 √𝑚 ) n advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 243 the stage-i of fcgr is in the crack length, a, range of 0.8-2.8 mm. it is observed that the slope of da/dn versus a curve increases gradually, indicating that a higher number of loading cycles is required for a small increment in crack length in the region. the same is also evident from the da/dn versus n curve, shown in fig. 7. the range of n for stage-i of fcgr is observed between 0-44419, in the plastic region. 3.2.2. fcgr in stage-ii from fig. 5, the stage-ii of fcgr is observed in the δk range 20.46-21.41 𝑀𝑃𝑎√𝑚. in this range, the slope of da/dn versus δk increases significantly. in other words, the crack driving force δk decreases with increasing a. it is suggested that the bending stress accumulation in the previous stage played a significant role in reducing the required drive force for fcg. it indicates that the crack softening accelerates as compared to the previous stage. the increasing slope of fcgr between 2.84.15 mm envisages that a comparatively lower number of n was required for a corresponding increase in a as compared to stage-i, as shown in fig. 6. the hypothesis of the lower n was confirmed from the slopes of fcgr versus n in stage-ii, as shown in fig. 7. the n for stage-ii of fcgr was from 44419-60106. 3.2.3. fcgr in stage-iii the stage-iii of fcgr showed an accelerated crack growth. the slope of da/dn versus δk increased vigorously. it means, the driving force required for an existing crack (in the previous stage-ii) to propagate was highly reduced, and an accelerated fcg occurred with a lower increase in δk. as shown in fig. 5, the stage-iii of fcgr is in the δk range 21.41-21.98 𝑀𝑃𝑎√𝑚. as shown in figs. 6 and 7, a much lower number of loading cycles was required for a corresponding crack propagation and hence, da/dn increases rapidly for a given a and n. it is suggested that in this region, the crack driving force (δk) was subjugated to the crack resisting parameter (kc) and material properties (stiffness, e). the stage-iii was characterized in the a range4.15-4.75 mm and a corresponding n 60106-63014. after a δk of 21.98 𝑀𝑃𝑎√𝑚, a of 4.75 mm, and n 63014, the fcgr is highly accelerated, and the material reaches the tri-axial stresses envisaging necking phenomena that eventually led to the catastrophic failure of the material [21, 27]. the next stage of fcg after 4.75 mm of crack length (which was 7.03 mm considering the pre-notch length) up to the radial thickness of pipe (equal to 9 mm) was not considered for fcgr modelling due to the limitation of the modified exponential function, stress-triaxiality in the vicinity of crack, and requirement of complex mathematical expressions. based on the above discussion, the boundary conditions and fcgr for all three stages are shown in table 3. table 3 boundary conditions and fcgr for all three stages stage of fcgr boundary condition phenomena of fcgr i   stage-i 0.85 , 2.80 ; 17.45 ,20.46 fcgr a mm mm k mpa m mpa m      the cracks resisting parameter (kc) and materials property (stiffness, e) oppose the crack driving force (δk) at best after the threshold δk. ii   stage-ii 2.80 ,4.15 ; 20.46 , 21.41 fcgr a mm mm k mpa m mpa m      the driving force δk was decreased with increasing a. iii   stage-iii 4.15 ,4.75 ; 21.41 , 21.98 fcgr a mm mm k mpa m mpa m      the driving force (δk) was subjugated to the crack resisting parameter (kc) and material property (stiffness, e). advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 244 fig. 5 fcgr versus δk for stages-i, ii, and iii fig. 6 fcgr versus a for stages-i, ii, and iii fig. 7 fcgr versus n for stages-i, ii, and iii 4. modelling of fcgr using a modified exponential function the model considered the crack driving force and crack resisting parameters to characterize the nature of da/dn and then predicted the fcgr. the specific growth rate is discussed for all the stages. then, the modifications made to the exponential function are discussed. 4.1 formulation of the modified exponential function the hypothesis of a given mathematical function is proportional to the speed at which the function rises, as defined by the exponential function given below ( ) rt op t p e (2) where p is population, 𝑃 is the initial population, t is the time, and the quantity r in the above equation is the malthusian parameter or specific growth rate. the eq. (1) has been modified by kumar et al. to calculate a for a given n. the modified equation can be obtained by [22-23]. ( )ijm j i j ia a e n n  (3) where, for a given interval (i, j), 𝑎 is the final crack length, 𝑎 is the initial crack length, 𝑁 − 𝑁 is the load cycle interval, and 𝑚 is the specific growth rate. the 𝑚 can be calculated by ln j i ij j i a a m n n        (4) advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 245 in the present work, the specific growth rate mij is modified and correlated with a non-dimensional number n as given in eq. (5) 2m an bn c   (5) where n was correlated with two crack driving forces, δk and maximum stress intensity factor (kmax), as well as material parameters, fracture toughness (kc), stiffness (e), and yield stress (σys). the above equation has been modified to a 2nd degree polynomial for the present study. however, in the previous exponential model, it was a 3rd degree polynomial. in the present work, the modified non-dimensional parameter n can be represented by max ys c c kk n k k e     (6) the above equation has been modified as a monomial. however, in the previous exponential model, it was an equation with a fractional power of 0.25. the constants (a, b, and c) were calculated for stages-i, ii, and iii of fcgr and the subsequent 𝑚 and the predicted number of loading cycles (𝑁 ) can be calculated by ln j ip j i ij a a n n m        (7) 4.2 calculation of 𝑚 and the curve fitting constant for stagesi, ii, and iii of fcg the specific growth rate 𝑚 defined in eq. (4) was plotted with the non-dimensional number n (defined in eq. (6)). this graph provided the relationship between fcg characteristics with crack driving force and material properties. the curve was fitted with a polynomial equation (given in eq. (5) for stages-i, ii, and iii of fcgr. the curve-fitting constants are presented in table 4. figs. 8, 9, and 10 provide the variation of the specific growth rate with the crack driving force and crack resistive parameters. in stage-i of fcgr (fig. 8), the decreasing slope envisages the emancipation of the combined effect of crack driving force and crack resistance parameter. this suggests that the crack propagation was slow with the n during the initial stage of fcg. however, once a sufficient amount of stress intensification near the vicinity of the crack tip occurred, the slope of specific crack growth rate versus non-dimensional number n increases as shown for stages-ii and iii of fcgr in figs. 9 and 10. such an increase depicts the dominance of the effect of the crack driving force over the crack resistance parameters. it also indicated an accelerated crack propagation with the number of n. the different natures of the slopes in stages-i, ii, and iii characterized the nature of fcg in the respective stages. table 4 curve fitting constants for stages-i, ii, and iii of fcg stage of fcg a b c stage-i 7989107.2800 −91.4011 0.0002 stage-ii 33838863.5100 −413.1787 0.0012 stage-iii 1116368244.00 −15001.6072 0.0504 fig. 8 specific growth rate versus n for stage-i of fcg y = 7989107.283x2 91.40113054x + 0.000282919 r² = 0.996503434 1.50e-05 2.00e-05 2.50e-05 3.00e-05 3.50e-05 4.00e-05 4.00e-06 4.50e-06 5.00e-06 5.50e-06 6.00e-06 6.50e-06 sp ec if ic g ro w th r at e, m non-dimensional number, n satge-i of fcg advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 246 fig. 9 specific growth rate versus n for stages-ii of fcg fig. 10 specific growth rate versus n for stage-iii of fcg 4.3 prediction of fcgr using a modified exponential function and specific growth rate the modified exponential function and specific growth rate were formulated considering the experimental data of 5 samples, followed by validation of the model using the 6th sample. the n was predicted using eq. (7), and then the values of da/dn were calculated. the fcgr was plotted against δk for stages-i, ii, and iii as shown in figs. 11, 12, and 13, respectively. fig. 11 fcgr in stage-i fig. 12 fcgr in stage-ii fig. 13 fcgr in stage-iii the modelling agreed with the experimental data. however, the accuracy and performance studies of the model required statistical analysis for quantification. it is also observed that the predicted fcgr in all three stages provided a higher value as compared to the experimental data. in other words, the model overestimates the materials’ properties and geometry. 4.4 modification in the exponential function in the previous work, the non-dimensional parameter n is defined as [22]:  0.25 max earlier model ys c c kk n k k e         (8) y = 33838863.51x2 413.1787744x + 0.001283286 r² = 0.990202666 1.50e-05 2.00e-05 2.50e-05 3.00e-05 3.50e-05 4.00e-05 5.80e-06 6.00e-06 6.20e-06 6.40e-06 6.60e-06 6.80e-06 sp ec if ic g ro w th r at e, m non-dimensional number, n stage-ii of fcg y = 1116368244x2 15001.60729x + 0.050434881 r² = 0.993584987 0.00e+00 2.00e-05 4.00e-05 6.00e-05 8.00e-05 1.00e-04 6.70e-06 6.75e-06 6.80e-06 6.85e-06 6.90e-06 6.95e-06 sp ec if ic g ro w th r at e, m non-dimensional number, n stage-iii of fcg 5.00e-05 5.50e-05 6.00e-05 6.50e-05 7.00e-05 7.50e-05 8.00e-05 8.50e-05 17.5 18.5 19.5 20.5 21.5 da /d n (m m /c yc le ) ∆k (𝑀𝑃𝑎√𝑚) stage-i of fcgr da/dn (experimental) da/dn (predicted) 8.00e-05 8.50e-05 9.00e-05 9.50e-05 1.00e-04 1.05e-04 20.5 20.7 20.9 21.1 21.3 21.5 da /d n (m m /c yc le ) ∆k (𝑀𝑃𝑎√𝑚) stage-ii of fcgr da/dn (experimental) da/dn (predicted) 1.10e-04 1.15e-04 1.20e-04 1.25e-04 1.30e-04 1.35e-04 1.40e-04 21.7 21.75 21.8 21.85 21.9 21.95 22 da /d n (m m /c yc le ) ∆k (𝑀𝑃𝑎√𝑚) stage-iii of fcgr da/dn (experimental) da/dn (predicted) advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 247 however, in the present work, the formulation of the non-dimensional number has been modified. one of the crack driving forces used in the previous work was stress intensity (k). however, it was felt that, rather than k, it was the stress intensity change (δk) that provided the crack driving force for distinct stages of fcgr. also, the exponent 0.25 was changed to 1. therefore, the modified non-dimensional parameter n can be computed by  max modified model ys c c kk n k k e     (9) another modification introduced was the correlation between the specific growth rate m and the non-dimensional number n. in the previous work, the correlation can be calculated using the 3-degree polynomial below [22]:  3 2 earlier model m an bn cn d    (10) however, in the current work, the correlation can be computed by  2 modified model m an bn c   (11) one of the modifications done in the present work is to predict the fcgr in a wider range for the through-the-thickness direction of the pipe. the limits of the earlier model and the modified model are presented as 0.85 2.95 0.85 4.75 lim lim mm mm mm mm crack length modified model crack length  (12) 17.45 20.62 17.45 21.98 lim lim mpa m mpa m mpa m mpa m k modified model k      (13) 4.5 performance of model the performance of the model was analyzed using statistical methods like mean absolute error (mae), mean squared error (mse), root mean square error (rmse), mean prediction ratio (mpr), mean % deviation, and coefficient of determination (r2). the different statistical methods are expressed as     1 1 n i experimental data predicted valuei in mae    (14)      1 21 n i experimental data predicted valuei in mse    (15) rmse mse (16)    1 1 n i experimental data i n predicted value i mpr    (17)      1 exp1 100 exp n i erimental data predicted valuei i n erimental data i mean% deviation     (18) 2 1 sum of square error sum of squares total r   (19) the quantitative analysis of the model is shown in table 5. the model showed the lowest (and the best) value of mae, mse, and rmse for stage-i of fcgr and the highest for stage-iii. however, the performance of the model was within the acceptable values for all three stages. for stages-i and ii, modelling provided the best results; however, for stage-iii, modelling was comparatively conservative, but still in the acceptable range. it is suggested that the modified exponential function and specific growth rate depict the slopes of da/dn versus the δk curve precisely, where the fcgr was initially slow during stagei and accelerated during stage-ii. when the crack fcgr was highly accelerated, the model depicted a fall in the performance. advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 248 the mpr, mean % deviation, and r2 in stage-i of fcgr showed the best performance. an r2 of 0.998 and 0.997 in stages-i and ii indicated that the hypothesis of the use of a modified exponential function and specific growth rate to predict the fcgr agreed with the experimental outcomes. the performance of the model dropped to a value of 0.969 for r2 in stageiii of fcgr. when the fcgr was highly accelerated, the modified exponential function became conservative and showed a lower performance as compared to stages-i and ii. a mean prediction ratio of <1 for all three stages of fcgr depicted that the model performance was on the higher side of the experimental data. in other words, the predicted values of da/dn were greater than the experimental values. table 5 performance of the model for the prediction of fcgr as a function of δk stage of fcgr mae mse rmse mpr mean % deviation r2 stage-i 1.13812e−06 1.41535e−12 1.18969e−06 0.983 1.664 0.998 stage-ii 1.9169e−06 4.12088e−12 2.02999e−06 0.979 2.075 0.997 stage-iii 3.30524e−06 1.27444e−11 3.56993e−06 0.974 2.655 0.969 the error band scatter analysis was carried out for the predicted and experimental results of fcgr for stages-i, ii, and ii. the results of the analysis are shown in figs. 14, 15, and 16, respectively. the error band scatter was considered on the positive side of the perfect fit because the predicted values were on the higher side of the experimental data. the error band for stagesi, ii, and iii falls on the positive side by 0.034, 0.035, and 0.043 % of the perfect fit. fig. 14 error band scatter for stage-i of fcgr fig. 15 error band scatter for stage-ii of fcgr fig. 16 error band scatter for stage-iii of fcgr 4.6 comparison of the performance of the model with earlier developed models the performance of the modified exponential function in the present work was compared with previous models developed in earlier work [22]. the earlier models only predicted fcgr for stage-i. although the present work predicted fcgr for all three stages, only the stage-i of fcgr prediction performance has been compared and presented in table 6. there was a significant advancement in the performance observed for the modified exponential function as compared to the earlier 5.00e-05 5.50e-05 6.00e-05 6.50e-05 7.00e-05 7.50e-05 8.00e-05 8.50e-05 5.00e-05 6.00e-05 7.00e-05 8.00e-05 9.00e-05 da /d n ( pr ed ic te d) da/dn (experimental) da/dn (predicted) 0.035% fit perfect fit 8.00e-05 8.50e-05 9.00e-05 9.50e-05 1.00e-04 1.05e-04 1.10e-04 8.00e-05 9.00e-05 1.00e-04 1.10e-04 da /d n (p re di ct ed ) da/dn (experimental) da/dn (predicted) 0.034% fit perfect fit 1.10e-04 1.15e-04 1.20e-04 1.25e-04 1.30e-04 1.35e-04 1.40e-04 1.10e-04 1.20e-04 1.30e-04 1.40e-04 da /d n ( pr ed ic te d) da/dn (experimental) da/dn (predicted) 0.043% fit perfect fit advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 249 exponential model for mae, mse, rmse, mpr, and mean % deviation. however, the coefficient of determination (r2) was similar for both models. on the other hand, in comparison with the gamma mode [23], the gamma function performed marginally better for mae, mse, and rmse performance and significantly better for mean % deviation, while the mpr and r2 were similar to the current work’s model. table 6 performance of the model model type mae mse rmse mpr mean % deviation r2 modified exponential function 1.13812e−06 1.41535e−12 1.18969e−06 0.983 1.664 0.998 earlier exponential model 9.07e−06 8.14e−11 9.02e−06 0.83 10.14 0.995 gamma function 1.23113e−06 1.88896e−12 1.37439e−06 0.99 0.30 1.02 for the specific grades of material and loading conditions used in the present work, the dataset is not available for comparison with models developed by other researchers. hence, the modified exponential function discussed here was compared with the paris equation [20]. the stage-ii of any fcg curve depicts the paris region and its law. therefore, the modified exponential function was compared for this stage specifically. the paris curve fitting is shown in fig. 17. the curve fitting equations given in red and green colors, in fig. 17, represent the experimental and modified exponential model, respectively. the materials constants (c and n) are obtained using eq. (20), and the goodness of fit is presented in table 7. nda c k dn   (20) where c and n are material constants that depend upon the environment, frequency, temperature, and stress ratio. the a and n are crack length and number of cycles, respectively. fig. 17 fcgr curve in the paris region table 7 constants of the paris equation and goodness of fit type of model c n goodness of fit modified exponential function 4e-07 0.2592 0.994 paris model 2e-07 0.2821 0.999 5. microstructure analysis the image of the fatigue-fracture cross-section of the pipe specimen is shown in fig. 18. the green, blue, and black arrow indicates the pre-notch, fatigue-fractured surface, and machined part, respectively. a granular microstructure (indicated by blue arrow), which is completely different from the non-fatigue surface, is observed. the granular surface morphology characteristics of the fatigue-fractured surface were in line with earlier reports [27]. it is suggested that the δk provides the necessary crack driving force. fcg microstructural fractography features envisage the crack growth mechanism of the material due to the stress accumulation on the surface for a given n. the fcg microstructural features are characteristics of pure y = 4e-07e0.2592x r² = 0.9947 y = 2e-07e0.2821x r² = 0.9997 8.00e-05 8.50e-05 9.00e-05 9.50e-05 1.00e-04 1.05e-04 20.5 20.7 20.9 21.1 21.3 21.5 da /d n (m m /c yc le ) ∆k (mpa*m^0.5) da/dn (experimental) da/dn (predicted) expon. (da/dn (experimental)) expon. (da/dn (predicted)) advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 250 bending and the initial microstructure of the material [27]. in the case of pipeline steel, the fcg wear was influenced by the formation of surface and sub-surface cracks after sufficient plastic deformation led to severe damage. the surface wear was characterized by the method of crack propagation, which was induced by plastic deformation, envisaging the amendment of the microstructure of the fractured surface, distressing the fcg wear procedures. fig. 18 the image of the fatigue-fracture cross-section the sem microstructure is shown in fig. 19. it is suggested that these crack initiation sites were generated during the fcg test once a sufficient crack driving force (δk) was achieved. the crack driving force then provides sufficient energy to generate dislocations in grain interiors. similar phenomena were reported by kung et al., stating that the preliminary fcg cracks were generated in the grain interior [27]. these dislocations are then converted into microvoids with increasing n as shown in fig. 19(a). several microvoids were generated, suggesting high-energy sites. it was also observed that these microvoids were shallowed, indicating an acceleration in crack growth. the microstructural features, including striations and secondary cracks, were also observed as shown in figs. 19(b) and (c), respectively. moving along the radial direction towards the inner surface of the pipe, the striations were perceived at a few locations. these striations were mostly oriented upright to the fcg direction and close to the inner wall of the pipe. (a) microvoids (b) striations (c) secondary crack fig. 19 microstructure of fatigue-fractured surface advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 251 it is suggested that these striations envisage the parting of damage accumulation and crack-tip fracture steps for crack advancement as an outcome of continuous cyclic loading [27]. the section on strain accumulation influences the critical boundary and is well-thought-out, the feeble point at which the fcg initiation took place. it is suggested that the fcg crack spreads along the orientation of the feeble planes or dislocation cell boundaries, principal to the formation of the primary crack. the primary crack, on further strain accumulation, develops into the secondary cracks as shown in fig. 19(c). these secondary cracks are designed on the sub-surface of the specimen and bend along the weaker plane near the surface. 6. conclusions an exponential fatigue crack growth model was developed using a modified specific growth rate for three distinct stages of fcgr for tp 316l stainless steel pipe. the model was validated through a comparative study of predicted results against experimental data. the performance of the proposed model was analyzed using statistical methods. the following are the important conclusions drawn from the present study: (1) the specific growth rate in the modified form of 2 1 max maxys ys ij c c c c k kk k m a b c k k e k k e                     simulated the crack driving force and crack resistive parameters in all three stages with different curve fitting constants. additionally, the modified exponential function in the form of ( )ijm j i j ia a n n  predicted the da/dn with a given δk in stages-i, ii, and iii of fcgr. (2) stage-i of fcgr was from the threshold sif range (17.45 𝑀𝑃𝑎√𝑚) to the value of δk (20.46 𝑀𝑃𝑎√𝑚), up to which fcgr slope was increasing slowly. stage-ii of fcgr was δk range 20.46-21.41 𝑀𝑃𝑎√𝑚, which was the stage where the slope of da/dn versus δk was significantly increased. (3) in stage-iii of fcgr, the driving force required for an existing crack (in stage ii) to propagate was reduced significantly, and an accelerated crack propagation occurred with a lower increase in δk. stage-iii of fcgr was for the δk range 21.41-21.98 𝑀𝑃𝑎√𝑚. (4) the model showed the lowest (also the best) value of mae, mse, and rmse for stage-i of fcgr and the highest value for stage-iii. the mpr, mean % deviation, and r2 in stage-i of fcgr showed the best performance. the performance of the model dropped to a value of 0.969 for r2 in stage-iii of fcgr. the error band scatter for stages-i, ii, and iii falls on the positive side of the perfect fit. (5) the microstructural features envisage striations and secondary cracks; while moving along the radial direction towards the inner surface of the pipe, the striations were perceived at a few locations. these striations were mostly preoccupied with being upright to the fcg direction and close to the inner wall of the pipe. acknowledgment the authors wish to acknowledge the state scientific institution—the joint institute of mechanical engineering of the national academy of sciences of belarus. funding this work was carried out with the support of the belarusian republican foundation for fundamental research (project number: t23rnf-125) and the russian science foundation (grant number: 23-49-10061). conflicts of interest the authors declare no conflict of interest. advances in technology innovation, vol. 10, no. 3, 2025, pp. 238-253 252 references [1] j. wanjun, w. jinfu, n. cunhou, and p. xiaofei, “application of austenitic stainless steel pipe in petrochemical units,” petroleum refinery engineering, vol. 53, no. 9. pp. 35-37, 2023. 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[29] w. f. gale and t. c. totemeier, eds., smithells metals reference book, 8th ed. butterworth-heinemann, 2003. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 a review of the stimulus–organism–response paradigm and environmental education for cruise tourism: a proposed framework chun-hua hsiao1, kai-yu tang2,* 1school of business, kainan university, taoyuan, taiwan, roc 2graduate institute of library & information science; innovation and development center of sustainable agriculture, national chung hsing university, taichung, taiwan, roc received 30 december 2024; received in revised form 07 june 2025; accepted 10 june 2025 doi: https://doi.org/10.46604/aiti.2025.14698 abstract with the rapid growth of the global cruise tourism industry and its increasing environmental impact, there is an urgent need to address sustainability challenges in line with the sdgs, especially in taiwan. despite the growing research on environmental education, there is a lack of a theoretical framework from the perspective of the stimulus-organism-response (s-o-r) paradigm that examines the relationships between external stimuli, internal organisms, and individual responses to environmental education in the context of cruise tourism. the proposed framework includes attention to environmental issues and awareness of consequences as external stimuli. these stimuli influence affective and cognitive processes, which are internal states of the organism. in turn, the affective and cognitive states drive pro-environmental behavioral responses. additionally, the proposed framework incorporates two potential moderating factors: cultural differences and environmental education with emerging technologies. implications for environmental education in cruise tourism are provided. keywords: environmental education, sustainable cruise tourism, stimulus‒organism‒response, external stimulus, internal organism 1. introduction this conceptual paper provides a theoretical approach to understanding how the stimulus-organism-response paradigm and environmental education can promote sustainable development in taiwan’s cruise tourism industry. based on the similarity check report from turnitin.com, the overall similarity of this paper is 6% with a green label. this result indicates that no serious plagiarism issue is found in this paper. in recent years, the development of cruise tourism has shown a rapid growth trend and has become an essential part of the global tourism industry [1-3]. according to statista [4], the global cruise tourism market is expected to exceed $40 billion by 2029, growing at an average annual rate of approximately 5%. while this rapid growth has brought significant economic benefits, it has also raised widespread concerns about its environmental impact. studies have shown that cruise tourism exerts significant pressure on the environment and sustainable logistics in terms of carbon emissions, damage to marine ecosystems, and wastewater and waste disposal [5]. according to the european maritime transport environmental report [6], cruise ships are the largest polluters, emitting about 10 tons of black carbon per ship per year, followed by container ships (3.5 tons per ship), car carriers (2.1 tons per ship), and oil tankers and reefer bulk carriers (1.7 tons per ship each), as shown in fig. 1. * corresponding author. e-mail address: kytang@dragon.nchu.edu.tw advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 408 fig. 1 annual black carbon emissions per ship (in tons) [6] some researchers have proposed an energy efficiency operating index to monitor a ship’s energy consumption [7]. sofiev et al [8] concluded that even if all cruise ships could reduce their sulfur emissions, sulfur marine fuels would still cause 250,000 deaths and 6.4 million cases of childhood asthma each year. in addition, cruise ships recycle 60% more waste per capita than land-based ships. however, managing waste from cruises is a challenge. fortunately, some cruise lines have already begun to make environmental improvements. for example, hurtigruten cruises, which travels norway’s fjords, coastline, and arctic, has invested in retrofitting six of its ships with a mix of batteries, liquefied natural gas, and organically liquefied biogas. viking ocean cruises’ new cruise ship, viking grace, is equipped with rotor wind sails that use wind power generated while underway to power the cruise ship, reducing co2 emissions by 900 tons per year. carnival cruise lines is committed to clean energy. the company seeks to control emissions by combining sulfur oxide scrubbers with particulate filters. the peace boat, a japanese cruise line that offers eco-friendly ocean cruises, plans to build a cruise ship powered by wind, solar, and liquefied natural gas. according to the united nations sustainable development goals (sdgs), sustainable tourism is identified as a critical target in sdg11 (sustainable cities and communities). in consideration of the accelerated growth of the global cruise tourism industry and its concomitant ecological implications, it is imperative to address sustainability issues in this sector in accordance with the sdgs. in select developed countries, cruise ship ports have witnessed recurrent demonstrations and protests by residents over an extended duration. for instance, in the united states, local citizens can contact the state of alaska to voice concerns regarding emissions from a visiting cruise ship if they observe or detect a malfunction. this suggests a positive correlation between heightened consumer awareness of environmental protection and companies’ increased motivation to enhance their environmental standards. consequently, governments and international organizations have initiated the formulation of stringent environmental protection policies for cruise ships. the cruise industry in taiwan is in its nascent stages of development when compared to the more mature cruise tourism industries in europe and the united states. despite the tourism sector in taiwan undergoing a gradual expansion, marked by an annual increase in the number of travelers, it is imperative to proactively address the potential environmental impacts and promote sustainable practices. from the perspective of academic research, it is essential to conduct a survey in taiwan regarding cruise tourism and environmental education. this assertion is especially valid when evaluated through the lens of a theoretical framework. conducting such a survey would facilitate a systematic discussion of the factors that influence tourists’ beliefs about sustainable cruise tourism [9]. this presents a unique opportunity to propose the hypothetical relationships among ruise s ips ontainer s ips e icle carriers il tan ers e rigerate bul carriers advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 409 factors influencing taiwanese tourists’ pro-environmental behaviors in the context of cruise tourism. this would facilitate the development of targeted strategies for environmental education. based on search results from a reputable database (web of science), existing studies have applied several theoretical models to understand pro-environmental behavior in tourism. these include institutional theory [10], norm activation theory [11], value-belief-norm theory [12], and theories of planned behavior [13]. however, there is a paucity of research exploring the complex interactions between external stimuli, internal organisms, and responses in the context of sustainable cruise tourism. the existing literature utilizes the s-o-r paradigm [14], which emphasizes three constructs in the model. this study builds on the findings of previous research [15-16] by extending the s-o-r framework from the literature on gaming tourism [15] and the sustainable development of wildlife sanctuaries [16] to include environmental education in cruise tourism. the present study proposes that the s-o-r framework elucidates the role of external stimuli in s aping tourists’ perceptions and behaviors toward sustainable practices in the context of cruise tourism. by examining how these stimuli influence cognitive, emotional, and behavioral responses, the proposed framework illuminates how environmental concern and awareness of consequences are translated into action. this paper poses three key questions: (1) what are the influential external stimuli and internal organisms that influence local tourists’ pro-environmental behavior toward cruise tourism? (2) what are the impacts o cultural i erences on tourists’ pro-environmental behavior toward cruise tourism? (3) will the implementation of environmental education further strengthen tourists’ pro-environmental behavior toward cruise tourism? to address these questions, this study proposes an application of the s-o-r framework in the context of taiwan’s cruise tourism industry. the proposed model comprises two external stimuli (attention to environmental issues and awareness of consequences) and two internal factors (cognitive and affective processes) that influence tourists’ intentions to adopt pro-environmental behaviors in cruise tourism. furthermore, by taking into account the moderating effects of cultural differences and the role of environmental education with emerging technologies, this study aims to provide a theoretical perspective on the promotion of sustainable practices in taiwan’s rapidly developing cruise tourism sector. 2. literature review this section provides a systematic analysis of relevant research to review the intersection of cruise tourism and environmental education. first, it presents the development and current state of cruise tourism in relation to environmental education initiatives. next, the existing theoretical underpinnings of the s-o-r paradigm from various fields are reviewed. finally, a proposed research model is introduced in this section. 2.1. development of cruise tourism and environmental education in recent years, researchers have pursued a variety of approaches to safeguard significant environmental resources and cultivate public comprehension of the importance of environmental sustainability issues in confronting the environmental challenges posed by cruise tourism. [17]. among these strategies, environmental education has emerged as a prominent coping mechanism aimed at enhancing environmental awareness, knowledge, and engagement [18-19]. some cruise lines have initiated the provision of onboard educational courses focusing on environmental subjects, including marine life conservation, the vulnerability of marine ecosystems, and the significance of sustainable tourism behaviors [20]. to cultivate environmentally literate citizens, scholars have proposed that sustainable environmental education should prioritize cultivating a community’s capacity to address environmental challenges and promote engagement in environmental protection initiatives [21-22]. for instance, demir et al. [21] demonstrated that efficacious environmental education can substantially augment tourists’ awareness of the impacts of cruise tourism and their propensity to adopt pro-environmental advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 410 behaviors. furthermore, environmental attitudes are defined as the characteristics that individuals develop over time, encompassing values and beliefs concerning the environment, a sustained interest in environmental issues, and actions to protect the environment [22]. researchers have also indicated that tourists who have participated in these programs exhibit an increased concern for marine conservation and are more inclined to support cruise activities that incorporate environmentally friendly measures [23-24]. recently, some studies found that emerging technologies are transforming cruise tourism experiences through diverse innovative applications for environmental education. for example, gonzáles-santiago et al. [3] found that smart technologies are being systematically adopted across cruise tourism services, creating new paradigms for guest engagement and operational efficiency. fan et al. [25] suggested that augmented reality (ar) and virtual reality (vr) are significantly enhancing tourism experiences by providing interactive and engaging content that enriches passenger journeys. the metaverse represents a particularly promising frontier, where cruise operators can create immersive virtual experiences that complement rather than compete with physical cruise experiences. this hybrid approach allows for holistic customer engagement, where virtual interactions in the metaverse can enhance anticipation and extend the cruise experience beyond the physical voyage [26]. these tec nological a vances are not merely supplementary eatures but are becoming integral to t e cruise in ustry’s evolution, requiring comprehensive educational frameworks to prepare industry professionals for this technological transformation [27]. the convergence of these emerging technologies has far-reaching implications for the traditional maritime hospitality industry. it enables cruise tourism companies to offer personalized, engaging experiences that promote environmental awareness and encourage positive behaviors among tourists. therefore, this study posits that the integration of immersive technologies, such as virtual reality and interactive media, has the potential to enhance the efficacy of environmental education, t ereby acilitating a more pro oun immersion o tourists’ actions in the environment. in the future, as cruise tourism continues to expand, the development and implementation of more effective environmental education strategies will be vital to achieving sustainable development. utilizing a theoretical framework approach, this conceptual paper underscores the significance of environmental education in the context of cruise tourism. 2.2. theoretical framework from the s-o-r paradigm the s-o-r framework, developed from environmental psychology [14], posits that external stimuli (s) influence an individual’s internal states or organisms (o), which in turn lead to behavioral responses (r). the s-o-r paradigm posits that s refers to the external stimulus of a situation or event, which is a variable of the external environment, including various marketing and environmental operations. the s-o-r framework is illustrated in fig. 2. the o is used to denote the internal organism of an individual, defined as the mechanism of the individual’s psychological process, including cognition and affect. the cognitive response is defined as the process through which an individual’s mental function interacts with external stimuli, typically characterized as a goal-directed activity [28]. emotion, in turn, is understood as a subjective, transient psychological trait or state induced by external stimuli. the r is response behavior, which can be further categorized into two distinct forms: approaching behavior and avoidance behavior. in this theoretical framework, external stimuli are theorized to exert an influence on an individual’s internal emotional state. this internal emotional processing process (mechanism) involves an individual’s cognitive and affective responses, which in turn lead to specific behavioral outcomes. fig. 2 a conceptual framework of the s-o-r paradigm [14] advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 411 2.3. a proposed research model based on the s-o-r paradigm in the context of cruise tourism, researchers have used the s-o-r paradigm to examine the factors that influence consumers’ pro-environmental behaviors and intentions [29-30]. for example, researchers have examined the relationship between brand name and its perceived value to customers, which in turn influences the image of a business and behavioral intentions [ 9] islam et al [ ] con ucte a stu y to etermine w et er employees’ perceptions o corporate social responsibility have the potential to increase their satisfaction and loyalty. however, there are few studies that have used the so para igm to examine t e in luence o cruise passengers’ environmental concern an awareness on t eir internal states and pro-environmental behavioral intentions. the s-o-r paradigm is employed as the foundational framework for this study, which proposes a research model (see fig. 3) to delineate the relationships between external stimuli, internal organisms, and behavioral responses within the context of cruise tourism. the model incorporates environmental concerns and awareness of consequences as external stimuli, cognitive and affective factors as internal stimuli, and intentions to comply with environmental regulations and willingness to pay for eco-friendly cruise options as behavioral responses. the proposed model incorporates the moderating effects of cultural differences [31-32] and environmental education with emerging technologies [33-34]. the integration of these two moderators enables researc ers to examine t e mo erating e ects in t e relations ip between tourists’ willingness and influencing factors for pro-environmental tourism behavioral intention in different cultures with environmental education. fig. 3 a proposed research model based on the s-o-r paradigm the incorporation of moderating variables facilitates researchers’ comprehension of the potential moderating effects between independent variables and behavioral factors. researchers have posited that cultural differences play a critical role in the context of cruise tourism [31-32]. in cultures where environmental conservation is a deeply held value, tourists are more likely to internalize and act upon pro-environmental norms when they encounter environmental degradation during their cruise experience. in contrast, tourists from collectivist cultures may be more influenced by the behaviors and expectations of their peers, leading to greater engagement in sustainable practices than those from individualistic cultures. a cultural emphasis on nature and sustainability has the potential to heighten tourists’ sensitivity to environmental issues, thereby prompting more decisive pro-environmental actions when confronted with environmental challenges, such as coral reef degradation. in addition to cultural differences, saari et al. [35] indicated that environmental concern refers to the perception of many different environmental issues. among these, an individual’s awareness of consequences refers to the understanding that one’s actions may affect the well-being of others or society [36]. there is a broad consensus that concern for environmental issues advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 412 and understanding of the consequences of pollution significantly influence an individual’s propensity to engage in environmentally responsible behaviors or decisions [37]. second, affective factors (affect) are triggered after the evaluation of specific environmental ecologies and behaviors. these affective factors effectively explain individuals’ decisions and behaviors in various pro-environmental decisions and behaviors [38]. in addition to affective variables, cognitive variables such as environmental concern and consequence awareness influence individuals’ perceived attitudes toward being environmentally friendly [39]. these cognitive variables may also significantly influence an individual’s decision to be environmentally friendly and, in turn, their moral obligation to take environmental action. by focusing on the specific components relevant to cruise tourism from an s-o-r perspective, this model provides a systematic understanding of the profile towards the formation of tourists’ pro-environmental behavior in cruise tourism. 3. research propositions for environmental education in cruise tourism based on the proposed model, three research propositions are provided. first, the s-o-r paradigm serves as the foun ational t eoretical ramewor or un erstan ing ow external actors (stimuli) impact in ivi uals’ internal psyc ological states (organisms), which subsequently drive their behaviors (responses). in the context of this study, external stimuli encompass factors such as environmental education initiatives, awareness campaigns, and regulatory measures related to cruise tourism. environmental concerns refer to tourists' awareness and concerns about environmental issues related to cruise tourism, such as carbon emissions and marine ecosystem degradation. following the literature [389], tourists’ awareness o consequences involves their understanding of the direct and indirect impacts of cruise tourism on the environment and society. next, according to the s-o-r, internal organisms can refer to the psychological processes within tourists. this study includes cognitive (e.g., knowledge and beliefs about environmental issues) and affective states (e.g., emotions like responsibility, guilt, or pride related to environmental stewardship toward cruise tourism). last, responses in this study are the pro-environmental behaviors exhibited by tourists, such as complying with environmental regulations on cruises or being willing to pay a premium for eco-friendly cruise options. based on the literature, the interaction between external stimuli (e.g., environmental concern, awareness of environmental consequences) and internal organisms (e g , a ective an cognitive processes) is crucial or tourists’ pro-environmental behavior toward cruise tourism. according to the s-o-r framework, raising awareness of environmental issues and consequences can promote tourists’ pro-environmental be avior in terms o tourists’ attention to environmental issues, research has shown that increased awareness of environmental issues increases their willingness to engage in proenvironmental behavior. for example, a study by salim et al. [40] revealed that increased awareness of the consequences of climate change increased the likelihood of pro-environmental behavior among tourists. thus, targeted awareness campaigns about the impacts of cruise tourism can motivate local tourists to adopt more sustainable behaviors. the first proposition is provided as follows. proposition 1: external stimuli (e.g., environmental concerns and awareness of the consequences of cruise tourism) will positively influence internal organisms, such as cognitive and affective states, which in turn positively affect local tourists’ pro-environmental behavior toward cruise tourism. operational definition. environmental concerns are defined as the degree to which tourists are concerned about environmental issues related to cruise tourism, such as carbon emissions and the degradation of marine ecosystems [35]. awareness of consequences is defined as tourists’ understanding of the direct and indirect impacts of cruise tourism on the environment and society [36]. cognitive states refer to tourists’ knowledge, beliefs, and attitudes concerning environmental issues pertinent to cruise tourism [39]. conversely, affective states encompass the emotional responses exhibited by tourists advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 413 (e.g., responsibility, guilt, pride) concerning environmental stewardship in the context of cruise tourism [38]. finally, proenvironmental behavior constitutes actions undertaken by tourists that serve to mitigate the adverse environmental impacts of cruise tourism. such actions include adherence to environmental regulations and the selection of eco-friendly cruise options [17]. second, a crucial moderating role of cultural differences in the proposed s-o-r model is suggested. in tourism literature, some researchers suggested that cultural backgrounds determine how tourists perceive and react to environmental stimuli [3132]. cultural differences shape these components by establishing varying social norms and values related to environmental responsibility in t is sense, tourists’ cultural i erences will ave potential mo eration in t e propose mo el moreover, according to the theory of planned behavior, social norms regarding environmental responsibility may vary widely across cultures and influence tourist behavior [41]. the theory of planned behavior underpins this proposition by emphasizing that individual behavior is influenced by subjective norms, attitudes, and perceived behavioral control [42], suggesting that individuals often conform to the behavior of those around them. in the s-o-r paradigm, cultural differences moderate the relationship between external stimuli (e.g., visible environmental degradation, eco-friendly initiatives onboard) and the internal cognitive and emotional responses (organism) that lead to pro-environmental behavior (response). tourists from collectivist cultures may be more influenced by the behaviors and expectations of their peers, leading to higher engagement in sustainable practices compared to those from individualistic cultures. tourists who are more influenced by the environmental behavior of their peers are more likely to engage in sustainable behavior than tourists who may not feel the same social pressure or connection to the local environmental context. for example, tourists who witness the degradation of marine environments, such as coral reefs and beaches, are more likely to engage in sustainable behaviors, such as reducing waste and supporting eco-tours. in cultures where environmental conservation is deeply ingrained, tourists are more likely to engage in pro-environmental behaviors when they witness environmental degradation while traveling. for instance, tourists who observe the deterioration of marine environments, such as coral reefs or beaches, may be inspired to engage in sustainable practices, such as reducing waste and supporting eco-tours. this has prompted cruise lines to develop educational programs that are culturally appropriate and designed to increase environmental awareness and action among tourists. the second proposition is as follows: proposition 2: cultural differences will significantly moderate the relationship between external stimuli and local tourists’ pro-environmental behavior toward cruise tourism. an operational definition is provided. cultural differences are measured by the extent to which values, norms, and beliefs related to environmental responsibility in a certain cruise tourism context differ among different cultural groups [31-32]. third, based on the literature, this study extended the discussion of environmental education to the context of cruise tourism, proposing that environmental education is important in promoting pro-environmental behavior among tourists. for example, researchers have indicated that environmental education has been shown to increase awareness and understanding of ecological issues, leading to pro-environmental behavior [16, 43]. studies have also shown that tourists are more likely to participate in actions to reduce environmental impacts when they feel an emotional connection [17]. in this sense, emotional responses are argued to be crucial in influencing behavior. positive emotional responses induced by environmental education, such as feelings of responsibility, guilt for environmental degradation, or pride in sustainable practices, drive proenvironmental behavior [41]. in this sense, when local tourists feel a strong emotional connection to their natural environment, they may be more incline to mitigate t e negative impacts associate wit cruise tourism environmental e ucation increases tourists’ environmental awareness and stimulates their emotional connection to the natural environment, which in turn strengthens their commitment to environmental action. therefore, designing targeted environmental education programs can effectively increase local tourists’ sense o responsibility or ecotourism an promote sustainable evelopment. advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 414 previous studies have also suggested educational technologies, such as virtual/augmented reality, the internet of things, an generative ai emerging tec nologies provi e immersive experiences to increase tourists’ nowle ge about t e environmental impacts of their activities, resulting in increased pro-environmental intentions and behaviors [44]. in addition, environmental education programs help build a sense of social responsibility among tourists, allowing them to influence and motivate each other to participate in environmental activities. therefore, cruise lines should develop targeted educational programs that impart knowledge during the cruise and extend the impact to the end of the trip. these experiences encourage tourists to continue participating in environmental activities and promote a broader awareness of environmental protection. research by lloret et al. [5] shows that informed individuals are more likely to act on their intentions. in the context of cruise tourism, when tourists are educated about the specific negative impacts of their actions (e.g., waste generation, habitat degradation), they are more likely to adopt sustainable behaviors, such as choosing environmentally friendly options or following environmental guidelines during their excursions. in this sense, educational programs incorporating social norms and peer influence mechanisms can significantly affect behavior change [45]. for example, if tourists perceive that their peers are engaging in pro-environmental behaviors (in part due to educational initiatives), they are more likely to adopt similar practices. verall, t e t ir proposition emp asizes t e pivotal role o environmental e ucation in s aping tourists’ proenvironmental behaviors within cruise tourism. comprehensive environmental education programs are designed to elevate tourists’ awareness about environmental issues relate to cruising, encourage t e a option o sustainable practices aboar cruise ships, and consider cultural variations that may influence behavior. by integrating these elements, environmental education informs and motivates tourists to engage in actions that are beneficial to the environment, reinforcing their commitment to pro-environmental behavior during their cruise experiences. the third proposition is depicted below. proposition 3: implementing compre ensive environmental e ucation programs will signi icantly en ance tourists’ proenvironmental behavior in the context of cruise tourism by increasing environmental awareness, fostering sustainable practices, and addressing cultural differences. operational definition: ompre ensive environmental e ucation programs are e ine as t e extent to w ic tourists’ knowledge, awareness, and skills related to environmental sustainability in cruise tourism are improved through environmental education programs in cruise tourism [18-19]. additionally, it is recommended to assess the degree to which related educational technologies are employed in environmental education, such as virtual/augmented reality, immersive technologies, and emerging ai applications, to enhance the delivery and impact of environmental education [2, 33-34]. 4. implications the findings of this research yield significant insights that can inform strategic approaches across multiple sectors involved in cruise tourism and environmental education. the following implications emerge from our analysis of the internal mechanisms that mediate external stimuli in cruise tourism contexts, offering actionable recommendations for academia, industry practitioners, and government stakeholders. these implications are organized into five key areas that collectively address how to enhance environmental education effectiveness, create more targeted interventions, and foster sustainable tourism practices through improved understanding of tourist behavior and engagement. (1) based on the research propositions, several implications for academia, industry, and government are offered as follows. using word-of-mout or cruise tourism’s environmental e ucation. by understanding the internal mechanisms that mediate external stimuli, cruise operators can develop more effective educational programs tailored to engage local tourists emotionally and cognitively. cruise lines can collect personal testimonials and experiences from tourists and incorporate storytelling to make environmental issues more relatable and impactful. advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 415 (2) targeted awareness campaigns. cruise lines and environmental educators should be aware that there may be individual i erences in tourists’ levels of environmental concern. understanding the characteristics of the environmental concerns of different groups of tourists can help design more targeted environmental education programs. operators can also create campaigns that highlight the direct impact of cruise tourism on local ecosystems and engage tourists through interactive and visually appealing content. this is consistent with the notion that increased awareness leads to increased proenvironmental action. (3) cultural values and policies for inclusive and friendly community development. emphasizing local cultural values in environmental education recognizes the unique perspectives of local tourists. workshops or seminars that incorporate local environmental concerns, traditional ecological knowledge, and participatory activities can increase the relevance of educational content and foster a sense of responsibility among tourists. (4) technology-enhanced cruise tourism and environmental education. the integration of technological solutions such as generative ai or augmented reality can enhance the learning experience. for example, visualizing the environmental impact of cruise tourism on local ecosystems through vr can motivate tourists to adopt pro-environmental behaviors. (5) creating positive social norms and providing action guidelines. by creating positive social norms, cruise lines can reinforce the positive association between tourists' environmental concerns and positive emotional and cognitive responses, such as public recognition of green behavior and awards for environmental excellence. it is also important to provide cruise tourists with clear action guidelines through environmental education. for example, providing tourists with information on how to minimize their environmental impact during a cruise can help them translate their concerns into practical environmental actions. 5. conclusion this study reviewed and proposed a theoretical framework based on the s-o-r paradigm to explore how external environmental stimuli and internal cognitive-affective processes in luence tourists’ pro-environmental behavior in cruise tourism contexts. based on the s-o-r paradigm, this study successfully conceptualizes the relationship between environmental concern and awareness of consequences as stimuli, cognitive and affective states as organism factors, and pro-environmental behavioral intentions as responses in cruise tourism settings. this study also integrates cultural differences and environmental education as moderators into the proposed framework, providing critical insights for developing targeted environmental education programs that resonate with diverse tourist populations. the result of this study sheds light on how educational approaches can effectively promote sustainable practices among cruise tourists by addressing cultural variations in environmental attitudes and behaviors. three main contributions are summarized below. (1) the development of a theoretical framework. the s-o-r paradigm provides a robust theoretical foundation for understanding environmental education in cruise tourism contexts. accordingly, this study includes environmental concern and awareness of consequences (external stimuli), cognitive and affective states (internal stimuli), and proenvironmental behavioral intentions (responses) in the proposed framework. the affective and cognitive states serve as critical internal mechanisms that mediate the relationship between environmental stimuli and behavioral responses. this dual-pathway approach recognizes both emotional and rational processing as bridging factors in fostering proenvironmental behaviors among cruise tourists. (2) moderating factors in the framework. this study proposes that contextual considerations of cultural differences and environmental education with emerging technologies are significant moderating variables in the framework. two moderators can better explain the s-o-r relationships in sustainable cruise tourism. understanding these moderating factors is crucial for tailoring environmental education programs to diverse tourist populations. advances in technology innovation, vol. 10, no. 4, 2025, pp. 407-418 416 (3) practical applications for sustainable cruise tourism. the framework offers actionable implications for cruise industry stakeholders, environmental educators, and policymakers. it also supports the design of culturally sensitive and technology-enhanced educational programs that can effectively promote sustainable behaviors among cruise tourists. these contributions broaden the scope of sdg achievement and environmental conservation efforts for sustainable cruise tourism. acknowledgment this study was partly supported by the national science and technology council, r.o.c., under contract numbers nstc 112-2410-h-424-003 and nstc 113-2410-h-005 t is wor was also inancially supporte by t e “innovation an development center of sustainable agriculture” rom the featured areas research center program within the framework of the higher education sprout project by the ministry of education (moe) in taiwan. conflicts of interest the authors declare no conflict of interest. references [1] a. papat anassis, “t e growt an development o t e ruise sector: a perspective article,” tourism eview, vol 75, no. 1, pp. 130-135, 2020. 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[45] k. s. wolske, k. t. gillingham, and p. w. schultz, “peer in luence on house ol energy be aviour,” nature energy, vol. 5, no. 3, pp. 202-212, 2020. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/).  advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 effective recommendation considering customers’ needs using review texts with tf-idf and word2vec: case of golf course kodai kimura1,*, takashi namatame2 1graduate school of science and engineering, chuo university, tokyo, japan 2faculty of science and engineering, chuo university, tokyo, japan received 30 december 2024; received in revised form 16 may 2025; accepted 20 may 2025 doi: https://doi.org/10.46604/aiti.2024.14699 abstract this paper aims to recommend the most suitable golf course for each user by focusing on golf courses and analyzing customer reviews. furthermore, by examining the recommendation results, the goal is to clarify the characteristics of each golf course from the user’s perspective and contribute to the promotion of each golf course. the procedure of this paper is first to extract user preferences using word2vec and tf-idf from reviews. next, the extracted user preferences are matched with golf course features. finally, recommendations are made based on the geographical relationship between the user and the golf course. as a result, a high accuracy rate is achieved. additionally, some keywords that should be used in promotions for each golf course feature have been identified. keywords: recommendation, golf course, word2vec, tf-idf 1. introduction user reviews have rapidly spread with the rise of the internet. especially on social media and e-commerce platforms, consumers can easily share opinions and experiences, making reviews a key source of information for purchasing decisions. according to the ministry of internal affairs and communications [1], over two-thirds of users across all age groups rely on reviews when shopping online (fig. 1), highlighting their strong influence on consumer behavior. accordingly, reviews are often utilized in recommendation systems for their ability to reflect consumer preferences. fig. 1 survey results: do you refer to reviews when shopping online? * corresponding author. e-mail address: nama@kc.chuo-u.ac.jp advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 310 fig. 2 revenue of golf courses fig. 3 number of golf course users the ministry of economy, trade and industry [2] reported that japan’s golf industry experienced a sharp decline in 2020 due to covid-19 but recovered by 2023 to levels exceeding those of 2019 (figs. 2 and 3). this suggests a positive outlook for the industry. various studies have explored golf-related topics. bekken et al. [3] evaluated the eco-efficiency of golf courses using profit and play volume. izumi et al. [4] studied how golf helps female ceos build male-dominated networks. edwards et al. [5] examined the link between swing techniques and back pain. for recommendation systems, khazaeli et al. [6] proposed an ai-based club selection tool, while morise et al. [7] investigated collaborative filtering with deep learning using multi-criteria evaluation data. however, few studies have focused on golf course recommendations using reviews. in other domains, reviews have been widely used in recommendations. asani et al. [8] extracted food preferences from reviews for restaurant suggestions. elahi et al. [9] integrated sentiment analysis into hybrid recommendation models. abbasimoud et al. [10] developed a tourism recommender using user preferences. syafganti et al. [11] found that review ratings and reviewer expertise affect hotel booking intentions. wang et al. [12] showed that emotional factors in reviews—such as pleasure, trust, anger, and disgust—have an impact on user intentions. to leverage reviews, extracting user preferences is key. common methods include tf-idf and word2vec. zhou et al. [13] compared these methods in response prediction tasks. zhang et al. [14] applied word2vec for medical term extraction. al tawil et al. [15] used tf-idf, word2vec, and bert to detect phishing. liyih et al. [16] conducted sentiment analysis on youtube comments using word embeddings. abid et al. [17] extracted music-related keywords from twitter using tf-idf and loglikelihood. to fill this research gap, this study uses reviews to recommend golf courses by applying tf-idf and word2vec to extract user preferences. analyzing golf course reviews in this way is expected to generate recommendations aligned with user needs. this study focuses on reviews posted by users who have made reservations and played at golf courses. using these reviews, it aims to extract user preferences and recommend suitable golf courses by matching the extracted features with users' needs. additionally, based on the analysis, this study seeks to identify effective promotional keywords for each golf course, contributing to the improvement of marketing strategies in the golf-related business. this study focuses on golf course reservations, a topic that has rarely been addressed in previous research, and aims to propose an effective recommendation method while identifying and evaluating factors that influence recommendations. the main contribution of this paper lies in its ability to provide explainable recommendations, which are valuable from a practical standpoint. unlike commodities, golf course reservations involve facilities with unique characteristics, and the decisionmaking process varies depending on the user's environment and preferences. therefore, conducting new research in this area is considered to be of significant value. advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 311 this paper is structured as follows: the introduction provides background and objectives; dataset overview describes the data; analytical methods explain the analysis techniques; analysis procedure outlines the recommendation system; overall results discuss results and promotion keyword gaps; discussions interpret the findings; and conclusions summarize the study and future directions. 2. overview of dataset this study uses the rakuten gora (golf-related web service site) dataset, provided via the national institute of informatics by rakuten group, inc [18]. this dataset includes facility data for golf courses (1,669 facilities) and review data (approximately 320,000 reviews) from the rakuten gora site. the facility data for golf courses contains information such as “golf course id,” “golf course name,” and “postal code.” the review data includes elements such as “review id,” “golf course id,” “reviewer name,” “user comment,” “play date,” and ratings for various categories. all ratings are evaluated on a five-point scale. these categories include “cost performance,” “ staff hospitality,” “course/strategy,” “food quality,” and “facilities.” in this study, this data is used for analysis. the number of users per region included in this data is shown in table 1. reservation numbers are higher in the kanto region, which includes tokyo, and the kinki region, which includes osaka and kyoto, compared to other areas. in contrast, regions such as hokkaido, shikoku, and kyushu—more distant from honshu—tend to have fewer reservations. table 1 number of users per region region number of reviewers hokkaido region 942 tohoku region 2216 kanto region 48711 chubu region 9848 kinki region 17369 chugoku region 1934 shikoku region 469 kyusyu region 3450 the number of golf courses by region is shown in table 2, which is similar to the reservation trends in table 1. the kanto and kinki regions have relatively many golf courses. however, because the area proportions of these regions are lower than their population proportions, the disparity across regions is not substantial. table 2 number of golf courses per region region number of reviewers hokkaido region 98 tohoku region 119 kanto region 512 chubu region 288 kinki region 299 chugoku region 99 shikoku region 43 kyusyu region 189 3. analytical methods this section describes the analytical methods used in this study. first, it introduces word2vec, which captures semantic relationships between words through distributed vector representations learned from review texts. next, it explains tf-idf, a technique to quantify the importance of words within a document set. by combining these two methods, the study integrates advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 312 semantic richness with contextual relevance for improved feature extraction. finally, recent advances such as transformerbased models are discussed, along with the rationale for choosing the methods employed here to balance accuracy and interpretability. 3.1. word2vec word2vec is a natural language processing method that embeds words into a high-dimensional vector space. this method models semantic similarities and relationships between words as numerical vectors. word2vec has two main training models: the skip-gram model and the continuous bag of words model (cbow). the skip-gram model is used to predict context words surrounding a target word and is particularly effective in capturing semantic information for rare words. in contrast, the cbow model predicts the target word from surrounding context words, allowing faster learning across the entire dataset. these vectors represent both semantic and grammatical information, allowing for similarity searches and vector-based relational analysis. in this study, word2vec was utilized to learn distributed representations of words and capture their semantic and grammatical relationships from review data. 3.2. tf-idf term frequency-inverse document frequency (tf-idf) is a method for quantitatively evaluating the importance of each word in a set of documents and is widely used in the fields of natural language processing and information retrieval [19]. tfidf extracts important words by considering both their frequency in a document and their rarity across documents. term frequency (tf) refers to the frequency of a word's occurrence in a specific document. the tf of a word 𝑡 in a document 𝑑 is defined by the following equation ( , )tf t d term count of t in document d= (1) inverse document frequency (idf) is a measure used to evaluate the rarity of a word within a collection of documents. when a word appears in many documents, its importance is reduced. idf can be calculated by ( ) log ( ) n idf t df t = (2) where 𝑁 is the number of all documents and ( )df t is the number of documents in which the word t occurs. the tf-idf value of a word t in document d is the product of tf and idf, which can be represented as ( ) ( , ) ( )tf idf t tf t d idf t=  (3) by this calculation, words that occur frequently in a particular document and are rare in the whole set of documents are highly evaluated. tf-idf is especially effective in information retrieval, text classification, and document feature extraction. 3.3. combining word2vec and tf-idf while word2vec captures semantic and grammatical relationships between words through vector embeddings, it does not inherently consider the importance or relevance of words within specific documents. on the other hand, tf-idf quantifies the importance of each word in a document set, but it does not account for semantic similarity. combining these two methods leverages both semantic richness and contextual relevance. specifically, tf-idf can be used to weight the word vectors obtained from word2vec, enabling the model to emphasize semantically meaningful words advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 313 that are also contextually important in each document. this combination improves the ability to represent user preferences and document characteristics more accurately, enhancing the performance of recommendation systems based on textual reviews. recently, transformer models—foundational technology behind generative ai—have been applied to recommendation systems [20-21]. these methods are capable of constructing complex, high-dimensional representations, and thus, it is conceivable that such approaches can be applied to the data used in this study. however, due to the lack of pre-trained models specifically tailored for golf reservation data and the limited size of the available dataset, training such models is not feasible. moreover, these methods are generally considered to be black boxes, which makes it difficult to derive interpretable insights such as the rationale behind individual recommendations. therefore, this study aims to improve recommendation accuracy by combining existing methods in a way that balances performance, interpretability, and practical applicability. by leveraging the semantic expressiveness of word2vec and the contextual weighting of tf-idf, the proposed approach seeks to capture user preferences more precisely from review texts. this combination not only enhances the recommendation system’s effectiveness but also maintains transparency in the model’s reasoning, making it suitable for practical deployment in the golf course reservation domain. 4. analysis procedure this section outlines the detailed procedure of the analysis conducted in this study. it describes the step-by-step workflow from data preprocessing and user characteristic extraction to the recommendation algorithm and evaluation method. fig. 4 visually summarizes the overall recommendation process employed. each subsection provides a clear explanation of the methodology used to transform raw review data into personalized golf course recommendations. 4.1. preprocessing (1) scoring the golf courses. • golf courses are selected if they have received reviews from at least 10 users. • the score for each evaluation criterion is calculated as the average of user ratings. • the evaluation criteria consist of the following five categories: “cost performance,” “staff hospitality,” “course/strategy,” “food quality,” and “facilities.” (2) to identify each user’s characteristics, all reviews written by the same user are consolidated into a single dataset. 4.2. extracting user characteristics from reviews (1) word2vec was applied to vectorize user reviews. • in this study, the skip-gram model was adopted. • words were limited to nouns, verbs, and adjectives. (2) words related to the evaluation items and similar to the initial keywords were identified using cosine similarity. (3) some initial keywords were defined based on prior knowledge. (4) important words were extracted from user reviews using tf-idf. (5) the important words from the reviews were assigned to the relevant evaluation items, and the tf-idf values were used as the score for each evaluation item. the initial keyword lists for each evaluation item are shown below. cost performance: [“cost,” “performance,” “fee,” “price,” “cost-effectiveness,” “value,” “reasonable,” “low cost,” "benefit,” “cost performance”] advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 314 staff service: [“staff,” “service,” “customer service,” “response,” “kind,” “polite,” “friendly,” “courtesy,” “hospitality,” “smile”] course/strategy: [“course,” “strategy,” “fairway,” “design,” “difficulty,” “challenge,” “hole,” “landscape,” “layout,” “green”] food quality: [“food,” “dish,” “taste,” “restaurant,” “menu,” “delicious,” “meal,” “foodstuff,” “gourmet,” “seasoning”] facilities: [“facility,” “amenities,” “environment,” “clubhouse,” “changing room,” “cleanliness,” “well-equipped,” “comfortable,” “convenience,” “amenities”] 4.3. recommendation (1) the weighted sum of the evaluation item scores and the golf course rating is calculated. (2) to account for the geographical relationship, the probability of the user having visited each prefecture is used as a weight. (3) multiply the weighted sum score by the prefecture weight to obtain the overall score. (4) the top 10 golf courses are recommended based on the overall score. review data word2vec keyword for each evaluation item score for each evaluation item weighted sum scores overall score top 10 recommendations tf-idf initial keyword golf course scores prefecture weights fig. 4 process to recommendation 4.4. evaluation method (1) golf courses where the user has given a rating of 4 or higher and has recently visited are extracted. (2) identify golf courses that are geographically close to the extracted courses and have similar evaluation items, and include these courses in the “correct answer” set. a total of 10 golf courses will be selected, which are likely to satisfy the user. (3) if a recommended golf course is included in the “correct answer” set, it is considered “correct.” (4) calculate the accuracy rate based on the number of “correct” recommendations. 5. overall results this section presents the overall results of the recommendation system evaluation. section 5.1 summarizes the recommendation accuracy obtained when applying the proposed method to a sample of users, highlighting the significant improvement achieved by incorporating geographic information. next, section 5.2 analyzes the characteristics of golf courses advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 315 most frequently recommended according to different user priorities, including “cost performance,” “staff hospitality,” “course/strategy,” “food quality,” and “facilities.” detailed comments and related keywords from user reviews for each category are also discussed to provide qualitative insights into the recommendations. 5.1. recommendation results table 3 shows the results of the recommendations made to 10% of all users. when the top 10 predicted scores obtained by the method used in this study were recommended to each user, the percentage of golf courses that were included in the recommendation list that the user had reserved was 23.50%. table 3 recommendation results (reviews and weights of prefectures) correct 1643 users incorrect 5348 users percentage of correct answers 23.50% table 4 shows the results when user characteristics were extracted from the reviews without accounting for prefecture weights. the actual reservation rate for the top 10 was only 4.85%, which shows that the accuracy rate when using reviews alone is much lower than that of the method in this paper. table 4 recommendation results (only reviews) correct 339 users incorrect 6652 users percentage of correct answers 4.85% these results indicate that the accuracy of recommendations is significantly reduced when the geographic relationship between the user and the golf course is not considered. therefore, it can be concluded that geographic information is essential for making appropriate recommendations in facility-based services such as golf course reservations. 5.2. analysis of correctly recommended results the golf courses most frequently recommended to users prioritizing “cost performance,” “staff hospitality,” “course/strategy,” “food quality,” and “facilities” were selected as targets for analysis. below is a summary of the thoughts on each item. 5.2.1. cost performance below is a comment from the golf course most frequently recommended to users prioritizing “cost performance”: (1) the fully separate 18 holes each bring a unique character, offering a highly strategic and engaging challenge for golfers. the fairways are flat and wide, while the greens, made of bentgrass, boast an average size of 800 square meters. (2) the course is magnificently designed, providing a sense of freedom and exhilaration as players enjoy the game amidst the beauty of the changing seasons. (3) this setting creates a truly relaxing and refreshing experience on the course. the following words related to “cost performance” were used in the reviews of users who were recommended this course: “reasonable,” “discount,” “premium,” “think,” “low cost,” “price,” “cost performance,” “fee,” “plan,” “get,” “overall,” “except,” “cost,” “normal,” “expense”. the course comments did not include any of the “cost performance” words used by users. advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 316 5.2.2. staff hospitality the following is a comment from the golf course that was most recommended to users who prioritize “staff hospitality”: (1) the golf course, surrounded by ancient trees such as sambu cedar and oak, which are over 300 years old, offers a rich natural environment. with its lush greenery, abundant water, and flat terrain, the course beautifully integrates nature. (2) the clubhouse, with its refined french traditional style and vibrant colors, is perfectly suited for welcoming high-level executives. (3) located just over 50 minutes from the city center, it offers a refreshing experience akin to enjoying a forest bath. the following words were used related to “staff hospitality” used by users who were recommended this course based on their reviews: “kind,” “courteous,” “smile,” “staff,” “service,” “hospitality,” “employee,” “drink,” “reception,” “affable,” “likeable,” “attitude,” “happy,” “complimentary,” “cheerful.” the comments for this golf course did not include any words related to “staff hospitality” that were used by users in their reviews. 5.2.3. course/strategy the following is a comment from the golf course that was most recommended to users who prioritize “course/strategy”: (1) items such as the clubs used by j. nicklaus during his major wins, the pin flag used in the open championship, and gifts from st. andrews are currently on display. please take this opportunity to visit and see them. course introduction: old course: a project team from st. andrews was invited to supervise the design, faithfully recreating the scottish style. (1) "sin valley": a recreation of the iconic 18th hole of the old course, known as the "valley of sin." (2) "tommy bunker": a replica of the "nakajima bunker" from the 17th hole of the old course. (3) "roman bridge": built using traditional methods, mirroring the swilcan bridge of the 18th hole of the old course. new course: designed by j. nicklaus and d. muirhead, later deemed too difficult by nicklaus himself. it is one of the most challenging courses in the country. (1) "victory": tom weisskopf once remarked, "if you finish this hole in par for four days, you'll win the tournament." (2) "selection": the shaft manufacturer grafalloy chose this course as part of their dream course project, selecting it from japan. (3) "incident": due to its difficulty, a maximum of 16 groups had to wait at the course's opening, which became known as the "par 3 incident" due to the high demand. the following words were used related to “course/strategy” used by users who were recommended this course based on their reviews: “challenge,” “tricky,” “strategy,” “course,” “good,” “think,” “go,” “round,” “enjoy,” “golf course,” “bunker,” “interesting,” “revenge,” “pond,” “fast,” “effective,” “fairway,” “change,” “slope.” the comments for this golf course contain the words related to “course/strategy” used by users, which are “course” and “bunker.” advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 317 5.2.4. food quality the following is a comment from the golf course that was most recommended to users who prioritize “food quality”: (1) the golf course, located just 10 minutes from the ota kiryu ic on the kita-kanto expressway, is designed to maximize the beauty of the natural mountain landscape, offering a strategically rich course. it caters to everyone, from ladies and seniors to beginners and advanced players. (2) visitors can enjoy the sight of 200,000 azaleas in 30 different varieties, including the 300-year-old kirishima azalea, along with other seasonal flowers. (3) the clubhouse, built by a major general contractor, offers a serene ambiance, inspired by an art museum. (4) at the restaurant, guests can enjoy a meal while overlooking a japanese garden and should try the homemade hand-pulled noodles (soba and udon). (5) the course is committed to providing highly detailed services, such as offering amenity pouches for women, and looks forward to welcoming all guests. the following words were used related to “food quality” used by users who were recommended this course based on their reviews: “volume,” “taste,” “variety,” “meal,” “lunch,” “menu,” “dishes,” “choice,” “amount,” “cafeteria,” “items,” “rice,” “beef,” “serving,” “mass.” the comments for this golf course include the word “meal,” which is related to “food quality” as used in user reviews. 5.2.5. facilities the following is a comment from the golf course that was most recommended to users who prioritize “facilities”: (1) nasu kasumiga-jou golf club has been transformed into a "true resort." the golf course, while staying true to the concept of utilizing the natural terrain created by nature, has evolved into a course loved by all golfers. (2) for some, it offers a gentle and enjoyable resort-style course, while for others, it provides a challenging, competitive experience. (3) the clubhouse, the largest wooden commercial facility in japan, boasts interiors designed by joan behnke, an interior designer renowned for works such as mgm grand. inside the clubhouse, the resort hotel features four suite rooms with terrace jacuzzi baths, 30 guest rooms, two restaurants, a bar lounge, an outdoor hot spring, and a spa. (4) the golf course has undergone layout changes and expanded fairways, and the entire course is now covered with korean lawn grass. while maintaining its strategic challenges, the course also incorporates the gentleness of a resort. furthermore, electromagnetic-guided carts have been introduced to promote environmental conservation. the use of wooden tees is also encouraged to promote harmony with nature, and cooperation is appreciated. the following words were used related to “facilities” used by users who were recommended this course based on their reviews: “pleasant,” “luxurious,” “smooth,” “good,” “fun,” “facilities,” “hot spring,” “clubhouse,” “lockers,” “restroom,” “old,” “locker room,” “bathroom,” “cool,” “abundant,” “neat,” "dressing room,” “clean.” the comments for this golf course include the words “hot spring,” “clubhouse,” and “facilities,” which are related to “facilities” as used in user reviews. advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 318 6. discussions when geographic factors are not considered in the model, it was found that the accuracy of recommendations significantly decreases. this suggests that golf course data is greatly influenced by geographic factors. therefore, in fields like e-commerce product reviews, where geographic factors are less influential, the proposed method of extracting user characteristics from reviews may be more effective. in the analysis of correct recommendation results, it was found that in the categories of “cost performance” and “staff hospitality,” the golf course comments often lacked the specific keywords prioritized by users. golf courses that excel in “cost performance” should incorporate related keywords in their promotional content. this approach could help attract new users who prioritize “cost performance” and prevent user churn. likewise, those excelling in “staff hospitality” should include relevant terms to attract new users and reduce churn. in contrast, for “course/strategy,” “food quality,” and “facilities,” the recommended courses’ comments did include relevant words. however, only up to three words from each category were present. emphasizing these words more in promotions may help bridge the gap between user expectations and course descriptions. this approach could lead to the acquisition of more new users and a decrease in user churn. to evaluate the effectiveness of the proposed method, it was compared with several other approaches. the comparison methods included the following: (1) recommendation scores based only on word2vec, (2) scores based only on regional information, and (3) a combination of word2vec and collaborative filtering. the results are summarized in table 5. as shown in table 5, the proposed method achieved the highest accuracy, surpassing even the combination with collaborative filtering, which is generally considered to yield high performance. the method using only regional data also showed high accuracy, likely because golf reservations are tied to users’ residential areas. table 5 evaluation of the method of this study method no. of correct correct percentage (1) used only on word2vec 320 4.58% (2) used only on regional information 1530 21.89% (3) combination of word2vec and collaborative filtering 1330 19.02% (4) combination of word2vec and tf-idf (method of this study) 1542 22.06% these findings indicate that capturing user preferences from reviews outperforms collaborative filtering that focuses solely on course features. in particular, the accuracy rate is much higher than when only reviews are used. although reviews are known to influence decision-making, this suggests that using reviews alone is not enough to make good recommendations. the method of this study achieved an accuracy rate of approximately 22%. to the best of current knowledge, no previous studies have focused primarily on golf course recommendations. however, however, the results can be compared with those reported by traub et al., who addressed hotel recommendation—a comparable task involving facility reservations [22]. in that study, multiple recommendation techniques were combined with location-based filtering, similar to the approach in this study. nevertheless, the reported accuracy was approximately 4%, which is significantly lower than ours. although a direct comparison is difficult due to the much larger number of hotels compared to golf courses, this contrast still suggests that the accuracy achieved in this study is reasonably high. considering that golf course selection is influenced by a wide range of factors, such as course difficulty, available facilities, service quality, and geographical conditions, the accuracy achieved by the method proposed in this article is by no means low and can be regarded as sufficiently high. advances in technology innovation, vol. 10, no. 3, 2025, pp. 309-320 319 7. conclusions this study proposed a recommendation method tailored to golf course users by leveraging textual reviews and incorporating geographic information. the methodology aimed to identify user preferences using tf-idf and word2vec, and to match those preferences with golf course features for more accurate and interpretable recommendations. the process further accounted for users’ visiting history to adjust for geographical tendencies, enabling the system to generate personalized and practical recommendations. the major findings of this study are as follows: (1) recommendation accuracy: the proposed method achieved a correctness rate of 23.50%, significantly outperforming the review-only approach (4.85%) and even other combinations such as collaborative filtering with word2vec. this highlights the effectiveness of incorporating both textual preferences and geographic data. (2) role of geographic information: geographic proximity had a substantial impact on recommendation accuracy. without it, the accuracy dropped sharply, confirming that golf course selection is highly location-dependent. (3) keyword gaps in promotions: in categories such as “cost performance” and “staff hospitality,” there was a notable gap between the vocabulary used by users and the promotional language in golf course descriptions. in contrast, courses that matched user preferences in “course/strategy,” “food quality,” and “facilities” showed partial alignment in keyword usage. these findings suggest that promotional effectiveness could be improved by incorporating review-based keywords. (4) interpretability vs. complexity: while modern transformer-based models can offer higher representational capacity, they were not employed in this study due to data limitations and interpretability concerns. instead, the combination of tf-idf and word2vec provided a balanced approach that supports both performance and transparency. given that golf course reservations are influenced by highly individual factors such as personal taste, location, and service quality, the achieved accuracy is considered meaningful even if the numerical value appears modest when compared with traditional product recommendations. future directions include enhancing geographic modeling by incorporating transportation accessibility (e.g., proximity to interchanges) and testing whether integrating user-centric keywords into promotional materials improves user engagement and reservation rates. these extensions will further bridge the gap between user expectations and facility-side communication strategies. acknowledgments in this paper, the “rakuten dataset” (https://rit.rakuten.com/data_release/) provided by rakuten group, inc. via the idr dataset service of the national institute of informatics was used. this work was supported by jsps kakenhi grant numbers 24h00370 conflicts of interest the authors declare no conflict of interest. references [1] ministry of internal affairs and communications, “2016 information and communications white paper,” https://www.ituaj.jp/wp-content/uploads/2016/10/nb28-4_web-07-report-overview2016whitepaper.pdf, 2016. 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[22] m. traub, d. kowald, e. lacic, p. schoen, g. supp, and e. lex, “smart booking without looking: providing hotel recommendations in the triprebel portal,” proceedings of the 15th international conference on knowledge technologies and data-driven business, article no. 50, pp. 1-4, 2015. copyright© by the authors. licensee taeti, taiwan. this article is an open access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v10n4(2025)-aiti#14955(321-339).docx advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 analyzing boeing’s supply chain, quality control, and certification issues: lessons from the 787 dreamliner and 737 max harsha walvekar1, mahmoud al ahmad2, qurban memon2,*, michael pecht1 1center for advanced life cycle engineering (calce), university of maryland, college park, md, usa 2electrical engineering department, united arab emirates university, al ain, uae received 22 march 2024; received in revised form 06 july 2025; accepted 28 july 2025 doi: https://doi.org/10.46604/aiti.2025.14955 abstract this study analyzes the impact of boeing’s outsourcing strategy on aircraft safety and production efficiency, focusing on the 787 dreamliner program. the intended benefits of cost reduction and accelerated production are examined against the realities of risk-sharing arrangements and documented issues like faulty materials from suppliers such as kobe steel. the study investigates how these outsourcing practices, coupled with boeing’s selfcertification license from the federal aviation administration (faa), contributed to lapses in regulatory oversight and quality control. applying a risk analysis to boeing’s supply chain, its risk treatment and monitoring processes are assessed. this study delves into the complexities and associated problems of boeing’s risk-sharing supplier partnerships. based on the findings, this study suggests enhancing supply chain resilience, ensuring regulatory adherence, and bolstering quality management systems to rebuild trust in boeing’s manufacturing processes and support long-term sustainability. keywords: 737 max, 787 dreamliner, boeing, quality control, supply chain 1. introduction boeing stands as a global leader in aerospace, renowned not only for its dominance in commercial jetliner manufacturing but also for its significant role in producing military aircraft, helicopters, and space vehicles. the company’s influence in the industry was further strengthened by key acquisitions. these included the purchase of rockwell international corporation’s aerospace and defense divisions in 1996. another key event was the landmark merger with mcdonnell douglas corporation in 1997. by 2022, boeing commanded an impressive 51% share of new airplane orders, attesting to its leadership in the aerospace industry [1]. the debut of the 787 dreamliner marked a transformative chapter for boeing and set a new standard for the commercial aviation industry. launched with great fanfare, the dreamliner was heralded to bring about revolutionary changes. this aircraft distinguishes itself from conventional yet innovative designs featuring low-sweep-back wings and engines mounted on pylons underneath. this design emerged after boeing discontinued the sonic cruiser program and refined many of its forward-thinking concepts. the dreamliner’s construction relies heavily on cutting-edge materials, blending lightweight, high-strength composites with advanced aluminum alloys to deliver exceptional performance and durability. its wings, for example, utilize state-of-the-art carbon fibers, epoxy composites, and titanium graphite laminate, enhancing structural integrity and efficiency [2]. * corresponding author. e-mail address: qurban.memon@uaeu.ac.ae advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 322 to accelerate the dreamliner’s development, boeing set an ambitious goal to reduce the typical six-year timeline to four years. achieving this required a bold shift from traditional, vertically integrated manufacturing to a more globalized outsourced model. boeing opted to partner with firms around the world, not simply as a cost-saving measure, but as a comprehensive strategy to optimize its supply chain. this approach required precise coordination of raw materials and skilled labor across continents, ensuring that each component met boeing’s stringent standards for quality and efficiency. by manufacturing parts internationally, boeing aimed to avoid substantial procurement costs and navigate the complexities of global logistics, all while tapping into the specialized expertise and resources of its partners. this strategy enabled the company to leverage innovations and efficiencies from its subcontractors, ultimately reducing overhead and enhancing the dreamliner’s value proposition [2]. boeing is committed to remaining a leader in the aerospace industry by consistently pushing the boundaries of innovation, development, and maintenance of aerospace products, thereby improving safety, efficiency, and sustainability. fig. 1 is an overview of the international supply chain for the boeing 787 dreamliner aircraft. this illustrates the various parts of the airplane and their countries of origin [3]. for instance, wing tips originated from south korea, wings from japan, and tail fins from the united states. the center fuselage and other parts come from italy, whereas the doors come from france. fig. 1 highlights the globalized nature of modern aerospace manufacturing, showcasing how boeing has sourced components from around the world to assemble the dreamliner. the illustration reflects the company’s strategy of optimizing its supply chain by using the resources of its international partners. the effect of boeing’s supply chain issues, regulatory oversight, and costcutting strategies concerning safety and quality is analyzed in this study, as illustrated in fig. 2. fig. 1 the global origins of the boeing dreamliner [3] fig. 2 impact of supply chain breakdown on aircraft safety advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 323 the air india crash on june 12, 2025, represents a tragic and significant moment in aviation history as the first fatal accident involving a boeing 787 dreamliner. the aircraft went down just minutes after takeoff, claiming the lives of 241 people on board. this marks a sobering break in the dreamliner’s previously unblemished safety record since its 2011 debut, a record that had held despite concerns over manufacturing defects, thanks largely to its robust design and operational protocols. however, this tragedy cannot be isolated from the broader and long-standing concerns surrounding the 787 program, including quality-control lapses, whistleblower reports, questionable maintenance practices, and increased regulatory scrutiny. while the exact cause of the crash remains under investigation, the event underscores the urgent need for stringent safety protocols and transparent oversight in the design, manufacturing, and operation of commercial aircraft. in light of boeing’s broader safety culture, the incident could be a case study in pilot training, maintenance standards, and operational pressures within low-cost carriers. this study is driven by critical safety and quality control issues within boeing’s 787 dreamliner program, especially in light of the 737 max accidents. key motivators include: (1) safety and quality concerns: incidents involving manufacturing defects, substandard materials, and regulatory failures have raised significant questions about boeing aircraft safety and integrity. (2) fragmented supply chain impact: this study addresses how a highly fragmented supply chain has compromised quality control, leading to delays, integration issues, and reduced quality. (3) balancing cost, production, and risk: it investigates the tension between boeing’s drive for cost reduction and accelerated production through outsourcing and risk-sharing versus documented issues like faulty materials from suppliers. (4) regulatory oversight and self-certification: the self-certification delegation of the federal aviation administration (faa) to boeing is scrutinized for its role in regulatory lapses and undetected safety issues. (5) rebuilding trust and ensuring sustainability: a core motivation is to restore confidence in boeing’s manufacturing by recommending ways to enhance supply chain resilience, regulatory compliance, and long-term sustainability. the methodology in this study, as shown in fig. 3, depicts how boeing aircraft safety and product quality are affected. this study investigates the supply chain and supplied materials in section 3, the effects of self-certification in section 4, supply chain risks in section 5, and boeing’s risk-sharing supplier-partnership model in section 6. section 7 discusses the findings, followed by the conclusion in section 8. fig. 3 proposed methodology 2. literature review make-to-order (mto) supply chains in aerospace are complex, with sustainability as a key long-term challenge. barbosa et al. [4] propose a hybrid, hierarchical performance assessment model using system dynamics, discrete event simulation, and agent-based simulation. applied to an aerospace manufacturer, it evaluates sustainability across alternative supply chains without compromising manufacturing representation. guerra et al. [5] explore aerospace supply chain risk management using surveys and interviews, identifying key risks, mitigation strategies, and ten critical supply chain risk management dimensions. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 324 unlike previous studies focused on process steps, it provides a holistic view of industry-specific challenges, emphasizing resource allocation, role clarity, and integration in emerging markets. along the same lines, the resource interaction approach is investigated in bygballe et al. [6]. their study claims that supply chain disruptions can be better managed than with traditional risk management methods by emphasizing resource interdependence and collaborative strategies. the transaction cost economics (tce) framework proposed by williamson [7] offers a structured approach to subcontracting decisions, assisting firms in determining whether to outsource or retain activities internally. by leveraging tce, manufacturers can strategically weigh production costs against transaction costs, ensuring optimal economic efficiency and operational flexibility. the tce framework offers valuable insight into aircraft safety and quality control. it highlights how supply chain structure, regulatory oversight, risk assessment, and partnership design shape the costs and challenges of compliance and reliability. it predicts that fragmented supply chains and loosely governed risk-sharing partnerships raise transaction costs. regulatory oversight is meant to serve as a safeguard, but as contracts and relationships become more complex and global, policing and enforcement costs rise, and the risk of safety lapses grows if governance is weak or information is incomplete. when these structures are misaligned with the characteristics of the transactions, the result can be delays, quality lapses, and ultimately compromises to safety. the dreamliner’s challenges and the recent air india crash highlight the consequences of misaligned governance in high-risk environments that prioritize safety by effectively addressing these transaction cost dilemmas. williamson [7] suggests that for safety-critical systems, more hierarchical or tightly integrated governance structures can reduce coordination costs and limit opportunism. these structures can also better protect quality and safety, whereas market-based or hybrid models may fall short. employing a case study approach and tce, ronchini et al. [8] analyzed how original equipment manufacturers (oems) strategically integrate additive manufacturing (am) into their upstream supply chains (make, buy, hybrid, or vertical integration). the study highlighted the influence of experience, application, and control needs, as well as the constraints of cost and skill gaps, on shaping supply bases and buyer-supplier relationships. nazeer et al. [9] examined sustainability in south asia’s aviation sector. they discovered that agility and alignment drive overall sustainability, while adaptability’s impact is limited to environmental, operational, and social aspects, excluding economic sustainability. this study contributes to filling several research gaps: (1) outsourcing’s impact on safety and efficiency: limited analysis exists on how risk-sharing and global partnerships affect safety and quality control in aerospace manufacturing, beyond just cost and speed benefits. (2) assessment of boeing’s risk management: the study specifically applies a risk analysis methodology to boeing’s supply chain to assess its actual risk treatment and monitoring processes. (3) effectiveness of regulatory oversight and self-certification: the consequences of the faa’s self-certification program on quality assurance and incident prevention have not been thoroughly examined. (4) supplier quality control and material traceability: research on ensuring material quality and traceability in complex global supply chains remains insufficient, especially concerning issues with sub-suppliers and faulty materials. (5) specific recommendations for aerospace supply chain resilience: the study provides tailored recommendations for enhancing supply chain resilience, regulatory adherence, and quality management within boeing’s global, outsourced model, including specific proposals for faa and tier-i supplier auditing. this study aims to advance understanding of global outsourcing’s impact on aerospace manufacturing safety and efficiency, with a focus on boeing’s supply chain model. key contributions include: (1) in-depth analysis of outsourcing risks: it will examine how boeing’s risk-sharing and global partnerships affect safety and production, moving beyond typical cost and speed considerations. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 325 (2) empirical risk evaluation: by applying a risk analysis to boeing’s supply chain, the study investigates real-world risk treatment and monitoring practices. (3) review of regulatory oversight: it will assess the consequences of faa self-certification on quality assurance and incident prevention, addressing critical oversight gaps. (4) insight into multi-tier supply chain challenges: the study will explore specific risks in global, multi-tiered mto models, including traceability issues and material defects. (5) practical recommendations and restoring trust: the study will present actionable strategies, such as enhanced supplier audits, to improve resilience, regulatory compliance, and long-term quality to rebuild confidence in aerospace manufacturing by addressing core safety and governance issues. 3. supply chain and materials boeing’s current crises primarily stem from a financialized corporate culture that prioritizes profit maximization over engineering excellence. this pivotal shift commenced with the 1997 merger with mcdonnell douglas, moving boeing away from its traditional engineering-led ethos. airbus, on the other hand, has managed to maintain stronger engineering governance [1]. boeing’s difficulties began in october 2018 with the tragic crash of lion air flight 610, a boeing 737 max 8, which fell into the java sea soon after taking off from jakarta. initially, boeing deflected blame, suggesting a pilot error and inadequate response to the system’s failure. however, the narrative shifted when ethiopian airlines flight 302, a boeing 737 max 8, suffered a similar fate on march 10, 2019, for identical reasons. this second disaster brought intense scrutiny upon boeing for misleading communication with its customers and concealing critical information. consequently, on november 26, 2019, the faa withdrew boeing’s organization designation authorization (oda), stripping it of the discretion to certify the airworthiness of its max airplanes independently. on january 5, 2024, a boeing 737 max 9 incident provoked safety concerns after part of the aircraft detached mid-flight, echoing concerns stemming from previous crashes. following the event, the faa grounded similar models for inspections, focusing on door plugs, such as those that failed, prompting scrutiny of boeing’s quality control and the faa’s oversight mechanisms. this incident highlighted the challenges in ensuring aircraft safety and maintaining public trust. in the wake of these incidents, boeing was faced with relentless scrutiny. every manufacturing imperfection was rigorously investigated, with the faa meticulously overseeing the delivery of boeing aircraft to ensure rigorous compliance with safety standards. the 787 dreamliner encountered significant issues attributed to lapses in supply chain management, leading to a series of quality control failures. these incidents have led to increased regulatory oversight and prompted a reevaluation of boeing’s supply chain strategies and quality assurance protocols, highlighting the need for more robust and transparent manufacturing processes. in short, the company’s struggles are multifaceted: (1) outsourcing and supply chain management issues compromising quality control; (2) production pressures and a skilled labor shortage prioritized output over quality improvements; (3) the lack of effective transparency procedure hindering proactive problem-solving; (4) ineffective quality management system within boeing’s facilities may have compounded these issues; (5) supply chain disruptions, exacerbated by the 737 max production challenges, significantly impacted the company’s operations. 3.1. supply chain issues with 787 dreamliner the 787 dreamliner’s extensive reliance on a global supplier network has sparked considerable debate. while a diversified supply chain yields clear benefits, mismanagement can lead to serious setbacks. the dreamliner’s assembly advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 326 showcases international collaboration, weaving together expertise and components from around the world. boeing has rationalized its strategy by emphasizing its role as a master integrator of complex systems, rather than a specialist in every individual part. outsourcing components can be a shrewd strategy, enabling the company to focus on final assembly and system integration. nonetheless, the 787 program also exposed the risks of overreliance on external partners for the design and manufacture of critical elements. these challenges highlight the importance of a thoughtful outsourcing strategy, one that carefully considers not only which components to outsource but also how to manage relationships and processes effectively. the dreamliner’s experience illustrates the fine line between achieving cost efficiencies and maintaining rigorous quality control, a balance that is essential for the success and safety of advanced aerospace projects. table 1 details several key components of the 787 and their countries of origin, further illustrating the truly global nature of boeing’s supply chain [3]. table 1 787 dreamliner parts and their sources no. part source no. part source 1 wings mitsubishi, japan 11 wing-body fairings boeing, canada 2 batteries gs yuasa, japan 12 thrust reversers mexico 3 wingtips kaa, south korea 13 engines us or uk 4 floor beams india 14 engine nacelles goodrich, us 5 front fuselage sprit, us; kawasaki, japan 15 movable trailing edge us, canada, and australia 6 centre fuselage alenia, italy 16 fixed trailing edge kawasaki, japan 7 rear fuselage boeing, us 17 centre wing box fuji, japan 8 landing gear messier-dowty, france 18 horizontal stabilizer alenia, italy 9 doors latecoere, france 19 wing-to-body fairing panels hafei aviation, china 10 cargo doors saab, sweden sourcing components from a diverse group of vendors can yield significant advantages, such as reducing reliance on any single supplier, increasing operational flexibility, and lowering inventory risks. however, this strategy also introduces new complexities. managing relationships with multiple suppliers demands greater oversight and coordination, and can strain resources. one of the main challenges is ensuring efficiency and maintaining consistent quality across all suppliers. the process of vetting and selecting partners becomes more rigorous, as companies must carefully weigh cost against quality to uphold their standards. boeing’s heavy reliance on third-party suppliers for essential aircraft parts, for example, later exposed the company to serious quality control issues. driven by a desire to accelerate production, boeing set an ambitious timeline for the 787 dreamliner, aiming to shorten development time from the six years required for the 777 down to four years [1]. the company hoped to slash development costs from an estimated $10 billion to $6 billion by outsourcing large subassemblies to tier-i suppliers, thereby speeding up the final assembly process [2]. the vision was bold. boeing intended to assemble a new 787 in as little as six days, and eventually reduce that to three days per aircraft. while this drive for speed and efficiency was groundbreaking, it also highlighted the inherent challenges and risks of managing a complex, global supply chain with numerous vendors. boeing’s recent manufacturing issues predominantly stem from its distinct supply chain governance, which contrasts with airbus’s approach. while both rely on global suppliers, they differ in outsourcing depth, supplier control, and vertical integration [10]. boeing’s ‘light-touch’ model, evident in its partnership with spirit aerosystems on the 787, precipitated coordination failures. in contrast, airbus enforces stricter oversight, including mandatory use of its digital quality tools. the tce principles provide a crucial framework for understanding the supply chain failures that plagued boeing’s dreamliner program. the program’s extensive reliance on global outsourcing inherently generated significant transaction costs due to factors such as asset specificity, potential for opportunism, and bounded rationality. while boeing’s strategic pivot from advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 327 vertical integration to a decentralized “system integrator” model aimed to lower production costs, it inadvertently introduced critical governance failures, evident in recurring quality issues such as fuselage gaps and inspection oversights. williamson [7] suggests that these problems stemmed from an imbalance between market coordination and hierarchical control. boeing’s adoption of a “light-touch” outsourcing approach, rather than greater vertical integration or robust relational governance, ultimately escalated transaction costs and hindered production efficiency, representing a clear departure from core tce principles. in summary, boeing’s 787 dreamliner program grapples with significant supply chain challenges, affecting production rates and deliveries. recent examples include [10]: (1) boeing is experiencing delays in scaling up 787 dreamliner production but aims to achieve a monthly production rate of 10 units by 2026. as a result of these delays, riyadh air, saudi arabia’s new national carrier, has postponed its launch to the third quarter of 2025 due to deferred deliveries of its ordered 787s. (2) leonardo, the italian aerospace firm responsible for supplying fuselage sections and horizontal stabilizers for the 787, has instituted rolling furloughs at its grottaglie plant since july 2024. these furloughs are expected to persist through the end of 2025, reflecting the reduced pace of 787 production and delivery. 3.2. unreliable materials and parts after the tragic boeing 737 max accidents, concerns about the safety of the 787 dreamliner gained traction in april 2021. workers at boeing’s north charleston facility voiced alarm over the relentless pace of the assembly line, arguing that the pressure to meet tight deadlines sometimes led to risky shortcuts. their feedback revealed a growing tension between production speed and adherence to safety protocols. this cast doubt on the integrity of the assembly process and raised questions about whether operational efficiency was being prioritized over product safety. in august 2019, klm royal dutch airlines publicly criticized the quality control at boeing’s production site, describing standards as “way below acceptable.” their dreamliners arrived with a range of defects, from loose seats and missing pins to improperly tightened nuts and bolts, and even unsecured fuel line clamps. united airlines also reported 20 separate issues, including dented panels, on a 787-10 delivered in april 2019 [11]. these incidents pointed to deeper problems within boeing’s quality assurance processes and highlighted inconsistencies in manufacturing standards. by late august 2020, boeing grounded eight 787 dreamliners after discovering two manufacturing issues related to fuselage shimming and inner skin surfacing at its south carolina plant. these flaws compromised the structural integrity of the jet’s carbon fiber composite framework. boeing acknowledged that “two distinct manufacturing issues in the joining of certain 787 aft body fuselage sections” did not meet their design standards [12]. left unchecked, such defects could exacerbate material wear and even result in structural failure under stress, underscoring the importance of manufacturing precision, especially with advanced composite materials. on september 7, the wall street journal reported that the faa had launched an investigation into boeing’s quality control practices, which had faced scrutiny since the dreamliner’s debut in 2011. boeing disclosed a “nonconforming section of the rear fuselage” that failed to meet engineering standards, prompting the faa to recommend inspections for up to 900 dreamliners [11]. soon, boeing announced another issue, this time with the horizontal stabilizers, affecting nearly 900 aircraft. excessive clamping forces during manufacturing in salt lake city had potentially caused inaccuracies in gap measurement and shimming. boeing assured customers that the issue was being addressed in undelivered aircraft and posed no immediate flight risk [12], but the string of disclosures underscored persistent challenges in boeing’s production process and the ongoing need for rigorous quality controls. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 328 just days later, boeing entered talks with u.s. safety regulators about a manufacturing defect in the 787’s vertical tail fin, which could affect as many as 680 aircraft. excessive gaps within the tail fin’s structure raised concerns about the long-term durability and safety of the jets. in july 2021, boeing slowed 787 production to address a new flaw in the forward pressure bulkhead, where gaps failed to meet company standards. early in 2021, boeing notified the faa of an issue identified by mitsubishi heavy industries, the contractor responsible for the dreamliner’s carbon-composite wings. during manufacturing, contamination from polytetrafluoroethylene (ptfe, commonly known as teflon) compromised the strength of the epoxy bonds, which are crucial for wing integrity. this incident highlighted the challenge of maintaining material purity and the critical importance of strict manufacturing protocols. in december 2021, italian prosecutors launched an investigation into two small firms, mps and processi speciali, after discovering that over 4,000 flawed parts had been produced for boeing between 2016 and 2021 [11]. these sub-suppliers, working for leonardo (which manufactures sections of the 787 fuselage), had supplied components made from “grade 2 titanium” instead of the specified titanium alloy [10]. the inferior material properties raised serious concerns about the reliability and safety of the affected aircraft. prosecutors ordered the seizure of suspect components, emphasizing the need for unwavering quality control and strict adherence to material standards, especially in a global supply chain. the problems didn’t stop there. in june 2024, boeing found improperly installed fasteners on numerous undelivered 787 dreamliners [13], triggering further inspections and potential rework. simultaneously, the faa proposed new inspection rules for seat-track splice fittings on certain 787s due to concerns over incorrect titanium alloys, which could undermine structural integrity. to add to the scrutiny, boeing’s inability to produce records related to a previous “door plug” incident alarmed lawmakers and raised serious questions about the company’s record-keeping practices [14]. 3.3. issues with kobe steel, japan kobe steel ltd., known worldwide as kobelco, has a legacy that stretches back over a century. however, in october 2017, the company’s reputation took a major hit. it admitted to falsifying quality data for several materials, including aluminum sheets, aluminum components, copper products, and iron powder. these materials, falsely certified as meeting specific standards such as tensile strength, were subpar. the fallout was significant: more than 200 customers across various industries, including automotive giants like toyota, nissan, and general motors, train manufacturers such as hitachi, and aerospace leaders like boeing, were affected. the scandal deepened when, just days later, kobe steel revealed that over 500 companies had received materials with falsified data, highlighting the widespread nature of the deception [15]. a four-month independent investigation uncovered even more instances of non-compliance, bringing the total number of affected entities to 602, including 222 international clients. this revelation exposed how a large volume of inferior products had entered the market, disrupted global supply chains, and shaken customer confidence. the scandal also revealed deeprooted issues within kobe steel’s corporate culture. improper practices were not isolated, but rather widespread and carried out with the knowledge and sometimes participation of senior executives. the company’s investigative report, released in november 2017, shed light on a curious aspect of kobe steel’s operations. some facilities set internal quality standards even higher than those required by customers, hoping to enhance product quality by catching flaws early. while the intention was to exceed expectations, this approach backfired when customer demands became more stringent and kobe steel’s benchmarks proved unattainable. instead of reassessing production capabilities or negotiating standards, employees manipulated test results for products that failed to meet these lofty internal criteria. this not only violated customer trust but also reflected a fundamental misunderstanding of quality control and customer relations. although boeing does not buy directly from kobe steel, it does source components from several of kobe’s customers, including mitsubishi heavy industries, kawasaki heavy industries, and subaru corp. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 329 this connection doesn’t mean that every boeing part contains suspect materials, but it does highlight the complexity of tracing material origins in a vast supply chain. japanese suppliers play a vital role in boeing’s operations, providing about 20% of the components for the 777 and 35% for the 787 dreamliner, which relies heavily on advanced composites [16]. this intricate network underscores the importance of transparency and reliability to maintain the integrity of the final product. kobe steel, much like boeing, has confronted intense competition, particularly from chinese steelmakers flooding the market with surplus steel [15]. this pressure led to a shift in priorities, with profitability taking precedence over transparency. analysts suggest that this focus on financial performance came at the expense of ethical standards, ultimately undermining the company’s reputation and reliability. many of kobe steel’s clients, such as the french conglomerate safran, which supplies landing gear to both airbus and boeing, are themselves key players in the aerospace industry. the impact of kobe’s substandard materials has been detected in aircraft like the airbus a350, specifically in its titanium landing gear. this demonstrates how a single supplier’s quality issues can ripple through the entire aerospace supply chain, affecting multiple manufacturers and aircraft models. it also highlights the critical need for rigorous quality checks at every stage to ensure the safety and dependability of aerospace components. in summary, the 2017 kobe steel scandal exposed serious vulnerabilities in boeing’s supply chain, even though boeing did not purchase directly from kobe. the need for extensive inspections and traceability led to delays and increased costs, accentuating the significance of stronger oversight, especially at the sub-tier supplier level [2]. ultimately, this incident reinforced the importance of diversifying suppliers and maintaining strict quality standards to safeguard the reliability of complex, global manufacturing networks. 4. boeing’s ability to self-certify on august 18, 2009, the faa granted boeing’s manufacturing and engineering teams the authority to perform certification tasks on its behalf, including issuing certificates and approving new aircraft designs. even before this change, boeing had an internal inspection system in place, with over 400 company employees designated to act for the faa. under the new arrangement, these internal inspectors, now reporting directly to boeing, assumed expanded responsibilities: evaluating new designs, overseeing compliance tests, and authorizing certifications [17]. to provide oversight, the faa also established the boeing aviation safety oversight office, which audits boeing’s internal inspection process and reviews company-generated reports. this marked the beginning of boeing’s self-certification program, a major shift intended to streamline approvals while upholding safety standards. the u.s. uniquely delegates significant aircraft certification tasks to manufacturers, a practice more extensive than in other major aviation markets like europe or china. while some delegation exists globally, the faa’s reliance on manufacturer self-certification has been exceptionally high historically, and remains so despite ongoing reforms [18]. most other regions prioritize direct regulatory oversight. aircraft certification requires compliance with the federal air regulations (fars), which set basic airworthiness requirements but don’t always reflect the latest technological advances. this often puts manufacturers in a dilemma, as they strive to introduce innovations that may not fit neatly within existing regulations. through self-certification, a manufacturer can obtain oda from the faa, allowing an appointed representative to endorse airworthiness certificates. this arrangement is particularly advantageous for manufacturers. once granted, type and production certificates have no expiration date, provided that no major changes emerge that would require a new certificate. consequently, companies can continue producing and certifying aircraft as airworthy for years without additional regulatory hurdles. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 330 the boeing 737, a mainstay in the commercial aviation market, set the stage for the 737 max 8. however, flight tests revealed that the larger engines added to the max 8 increased its propensity to stall. to address this, boeing introduced the maneuvering characteristics augmentation system (mcas) software system, but argued that this did not constitute a significant design change. this position allowed boeing to avoid the lengthy and costly process of obtaining a new aircraft certification, maintaining that the 737 max was similar enough to its predecessor. leveraging its self-certification privileges, boeing sped up the approval and production process, staying competitive with airbus’s a320neo. the company assured that pilots familiar with the previous 737 models would not encounter any significant differences in the cockpit of the max 8. faa test pilots, tasked with identifying any unique handling or performance characteristics of the max 8, reported none [17]. while this approach offered financial and competitive benefits, it raised serious concerns about the depth of the certification process and the adequacy of pilot preparation. typically, one boeing engineer tests a system, while another, acting as an faa representative, certifies that it meets federal safety standards. at the start of the 737 max’s certification, the faa’s safety team outlined which technical assessments would be handled by boeing and which would remain under direct faa oversight [19]. the imperative to accelerate certification shifted responsibilities, raising concerns about oversight and conflicts of interest. these concerns were heightened by the two fatal 737 max 8 crashes, which prompted calls for a comprehensive review of the certification process. even before the 737 max 8 disasters, the faa’s oversight was facing scrutiny. the transportation department’s office of inspector general had already criticized the agency’s supervision of manufacturers, pointing out inefficiencies and gaps in the self-certification process [17]. in 2011, the inspector general released a series of reports highlighting problems with how the faa assessed safety risks and managed the delegation of certification tasks. the reports also noted that company employees responsible for identifying deviations from safety standards often lacked adequate training. a crucial part of the inspection process is determining whether pilots need comprehensive training on new aircraft features. however, flaws in the evaluation process meant that critical systems, such as mcas, were not properly addressed. as a result, no additional pilot training was required for the 737 max 8, a decision that left crews unprepared for the mcas system and contributed to the loss of two commercial aircraft and 346 lives. these failures underscore the urgent need for stronger oversight within the faa, particularly regarding the delegation of certification tasks. most recently, on january 17, 2025, boeing requested temporary exemptions from the faa for the stall-management yaw damper system on its 737 max 7 and max 10 models, citing regulatory challenges following a reclassification of the system [18]. the tce framework proposed by williamson [7] provides a powerful framework for analyzing boeing’s self-certification program under the faa’s oda. it highlights the trade-offs between efficiency and control. applying tce, boeing’s selfcertification aims to reduce transaction costs due to the specialized nature of aircraft manufacturing and the frequency of certification requirements. that said, ongoing oversight failures and recent incidents suggest that the oda program hasn’t adequately mitigated opportunism, a substantial concern within tce. to optimize the oda, stronger hierarchical controls are needed to realign with the governance principles proposed by williamson [7], balancing the pursuit of efficiency with the paramount need for safety. to summarize, several key issues under scrutiny are: (1) boeing engineers certifying aircraft safety are employed by the company, which could potentially compromise their independence. (2) boeing oda staff feel pressured to approve items rapidly, potentially compromising safety. (3) the faa’s oversight of boeing’s oda is ineffective, failing to mitigate risks. the agency has yet to implement a riskbased approach to oda oversight, despite recommendations dating back to 2015. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 331 (4) poor coordination within the faa and with boeing led to critical system changes going unnoticed. (5) the faa has faced a shortage of skilled engineers and difficulties in training and supervision, undermining its ability to effectively oversee boeing’s certification processes. (6) boeing exerted undue pressure on oda-certified employees during the 737 max development. (7) mixed perceptions of improvement: a recent survey found that only 45% of oda unit members perceive progress in addressing improper company interference. to address ongoing concerns about certification, regulatory oversight, abysmal coordination, and inordinate corporate influence over inspection processes, the faa is implementing significant initiatives. these initiatives aim to strengthen its ability to conduct independent evaluations and enhance its regulatory capacity. 5. supply chain risks and their assessment the boeing 787 supply chain, with 70% of its parts outsourced and 30% supplied by foreign entities [3], embodies the complexities and challenges of managing a project with an ambitious scope. integrating innovative composite materials into an aircraft’s structure introduces a layer of complexity. this necessitates stringent oversight across all processes entailed in these composites. the global nature of the supply chain meant that boeing faced significant risks. these included ensuring the consistency of material grades from diverse suppliers, coordinating timelines across various suppliers to facilitate a seamless assembly process, navigating political challenges that could impede deliveries, and managing inventory levels to avoid excesses or shortages. boeing’s heavy reliance on outsourcing for critical components and software development has created significant challenges. this decentralized approach has led to fragmented quality and safety oversight, reduced control over design and production, and increased complexity with communication gaps between boeing and its suppliers. critical safety information is often ineffectively communicated or inadequately addressed. this is evidenced by multiple incidents and an faa audit identifying 97 instances of alleged noncompliance with manufacturing control requirements. furthermore, due to poor planning and inaccurate data, boeing faces supply chain vulnerabilities [5], leading to inefficiencies, material shortages, and manufacturing disruptions. these issues, coupled with safety concerns and increased regulatory scrutiny, have forced boeing to significantly slow down 737 max production. a comprehensive risk assessment aimed at developing preemptive strategies to mitigate potential adverse outcomes is presented below. the vulnerabilities are identified to prevent or minimize the impact of these risks. 5.1. risk identification the risk assessment process hinges on the initial identification of potential risks, particularly when dealing with innovative systems or processes that are not well understood [18]. boeing’s venture into global outsourcing of its supply chain represents a bold and innovative approach. this makes a thorough risk assessment even more crucial to prevent avoidable delays and additional costs. the key challenges inherent to managing a global supply chain include maintaining visibility over suppliers, ensuring the quality of parts and materials, and preventing delays in shipments. once identified, each identified risk must be scrupulously analyzed to understand its root causes, the probability of its occurrence, and the magnitude of its potential impact. factors contributing to delays include scarcity of raw materials, insufficient labor, failure to pass quality audits, suppliers underestimating the time required for production, and unpredictable events such as conflicts or economic downturns. quality issues can arise from several factors, including incorrect calibration of manufacturing equipment, use of counterfeit materials, employment of workers lacking necessary training, and pressure to meet tight deadlines, causing compromised standards. ineffective internal audits and inadequate oversight by the manufacturer advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 332 further exacerbate these issues. addressing these risks requires a proactive approach, beginning with early identification, followed by a detailed analysis. this approach enables the development of targeted strategies to mitigate risks, facilitating the progression of the supply chain and safeguarding the project against unnecessary setbacks and expenses. 5.2. risk analysis the causes of quality issues are then examined to analyze the causes and the likelihood of subsequent consequences. for instance, improper equipment calibration can result in dimensional errors in the parts. as these parts enter a much larger assembly, the tolerance (t) limits are exceeded if the tolerance of the individual components is out of range. this can lead to an entire batch being scrapped, imposing significant costs to the company. this is illustrated using the tolerance stacking method, which predicts how dimensional variations in individual components combine and impact the overall size, fit, and functionality of an assembly. mathematically, this is described as a linear sum, as a worst-case analysis, in the following equation: 1 2 3− − − − = + + + +⋯ assembly part part part part n t t t t t (1) where tassembly refers to the total tolerance of an assembled component, and tpart-1, tpart-2, and tpart-3 represent the tolerance of part 1, part 2, and part 3, respectively, and so on. this linear regression method quantifies risks by modeling a linear relationship between supply chain variables and the likelihood or impact of a risk event. linear regression functions as a component of supply chain risk analysis. a hybrid approach integrating both quantitative and qualitative techniques, sometimes leveraging advanced statistical and machine learning models, may also be beneficial. as an example of supply chain in the aerospace industry, the variables include supplier reliability, transportation bottlenecks, and raw material price fluctuations. thus, delay (as a risk) can be calculated as: 0 1 1 2 2 3 3α α α α= + + +delay x x x (2) where x1, x2, and x3 represent supplier reliability, transportation bottlenecks, and raw material price fluctuations, respectively, and α0, α1, α2, and α3 are coefficients indicating how much each factor contributes to the ‘delay’. previously, boeing provided detailed plans and drawings to its suppliers [20]; however, for 787, it only provided detailed requirements to approximately 50 of its tier-i (direct) suppliers. moreover, detailed planning is the responsibility of these tier-i suppliers, as pre-integrators. in this instance, boeing has limited influence on decisions involving tier-ii (secondary) or tier-iii (tertiary) suppliers in the hierarchical supply chain. consequently, owing to the lack of the manufacturer’s oversight of the supplier, shimming problems emerged with matching composite parts from different suppliers [20]. although other risk assessment methods are employed in aircraft manufacturing, the risk-reporting matrix offers a straightforward, visual, and effective tool for prioritizing safety-critical risks, enhancing communication, and ensuring regulatory compliance. in a risk-reporting matrix, the likelihood of an event against its consequence to determine the overall risk is plotted as shown in fig. 4. risk is principally calculated by multiplying these two factors. this means that as one moves diagonally across the matrix, the risk level increases. for instance, events with both low likelihood and low consequence (on a scale of 1 to 5) will fall into the “lowest risk” category, often represented by lightly shaded areas in fig. 4. conversely, the darkest shaded areas signify “high risk,” indicating events that are highly likely to occur and would result in severe consequences. for clarity, different events in the boeing 787 supply chain are labeled (e.g., a, b, c, d, e, f, g, h), as shown on the right side of fig. 4. once these events have a likelihood and consequence score available, their risk can be calculated. the high-risk events at the end of the diagonal line demand immediate and prioritized attention. based on fig. 4, supply chain events a, d, e, f, and h have been identified as high-priority events that require effective strategies to mitigate or avoid them. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 333 fig. 4 risk reporting matrix linking the supply chain issues discussed in section 2 to the risk-reporting matrix reveals that boeing’s evaluation of the 737 max system during development relied on an oversimplified testing process that failed to consider the complexity of real-world scenarios. the company’s flight tests were conducted under conditions significantly simpler than actual emergencies, and critical factors were underestimated, including the impact of the mcas system and pilot response assumptions. this was exacerbated by a single point of failure due to reliance on a single angle-of-attack (aoa) sensor, resulting in a lack of redundancy [18]. additionally, inadequate change management, such as changes to the mcas system’s power, insufficient use of key risk indicators, and a lack of board oversight undermined checks and balances on the company’s risk appetite and tolerance. as a prime aerospace contractor, boeing relies upon a global network of subcontractors for components, systems, and services. tce serves as a valuable analytical tool to assess boeing’s subcontracting choices and the governance mechanisms it employs. the boeing case exemplifies the consequences of disregarding tce principles, such as outsourcing core capabilities and failing to adequately govern high-specificity transactions, which contributed to operational failures. airbus, on the other hand, better aligns with tce by maintaining control over critical functions and fostering strong supplier relationships [18]. boeing’s recent steps, like considering the reintegration of spirit and overhauling quality control, signal recognition of these issues. tce provides a useful lens for understanding airbus’s resilience and guiding boeing’s recovery. while implementing tce-based solutions, like better oversight of outsourcing, would certainly prove advantageous, these must be combined with deeper cultural and structural reforms to fully re-establish engineering discipline. real cultural transformation goes beyond simply adjusting structures or complying with regulations [18]. airbus, despite its imperfections, offers a valuable contrast, as it has institutional safeguards that prevent similar dysfunctions. 5.3. risk treatment following the identification of risks and the assessment of their potential impacts, strategies for mitigating those deemed unacceptable were developed. boeing embraced a “risk-sharing” model through extensive outsourcing, distributing the responsibility for various aircraft components among different suppliers. this approach meant that the quality assurance of each part became the responsibility of the respective supplier under agreements established with boeing. however, boeing initially underestimated several factors, which resulted in quality issues and subsequently caused delays in aircraft delivery. the risk management strategies that should be implemented include the development of a comprehensive preventive plan aimed at minimizing the likelihood of these risk factors and mitigating their impacts [20]. in response to the significant delays experienced in their initial aircraft deliveries, boeing implemented a contingency measure by establishing a production integration center (pic) to address and prevent future delays and quality problems [21]. to further ensure the integration of supply chain quality, boeing deployed engineers and production staff across various advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 334 countries to monitor the performance of its suppliers directly [22]. ideally, pic should serve as a proactive, preventive measure rather than a reactionary contingency plan. the deficiency of critical analysis of the identified risks necessitated pic implementation only after substantial costs had been incurred by the company. this underscores the importance of early risk identification and the application of preventive measures to avoid the escalation of manageable risks into significant financial and operational challenges. boeing’s risk treatment during the development of the 737 max was fundamentally flawed, prioritizing speed and costcutting over safety, which resulted in catastrophic consequences. key missteps comprised the flawed design of the mcas system, its omission from operations manuals and checklists, and an aggressive production schedule that emphasized deadlines over thorough testing. additional cost-cutting measures included excluding an mcas indicator light in the cockpit. furthermore, boeing failed to address critical concerns raised by engineers regarding the mcas system, including the risks of erroneous aoa sensor data. it also made compromises, such as relying on limited ipad-based training due to contractual pressures from airlines such as southwest [23]. these failures in risk treatment contributed to the tragic crashes of lion air flight 610 and ethiopian airlines flight 302, resulting in the global grounding of the 737 max fleet. 5.4. monitoring and review to verify the effective application of risk-mitigation strategies, boeing needed to establish robust monitoring frameworks to oversee the implementation of these measures. given the oversight of treating certain risks with the requisite level of seriousness, the adoption of digital audits to supervise supplier activities was initiated somewhat later. to enhance oversight, boeing installed cameras at various supplier sites to facilitate digital audits [21]. these digital audits represent a significant advancement in maintaining diligent oversight of suppliers and reducing the likelihood of suppliers concealing issues [24]. the efficiency of such a system was underscored by the incident involving kobe steel, in which greater transparency and monitoring of supplier operations could potentially forestall fraudulent activities. digital audits offer a continuous, real-time oversight mechanism, enabling companies such as boeing to detect and address non-compliance or discrepancies in supplier practices promptly. this approach enhances the integrity of the supply chain and contributes to building trust and accountability between manufacturers and their supplier networks. the boeing 737 max development, extensive monitoring and review notwithstanding, suffered from significant shortcomings. faa oversight was insufficient, and boeing’s internal processes, including safety assessments and postcertification monitoring, exhibited critical flaws. notably, boeing delayed crucial safety risk assessments related to the mcas system until late in the certification process, failing to classify system-level risks as catastrophic. this led to the mcas system relying solely on data from a single aircraft sensor, neglecting crucial redundancy measures. 6. risk-sharing supplier-partnership model proposing to integrate the prescribed risk assessment protocols into the frameworks of risk-sharing [25] and integrated supplier [26], partnerships offer a strategic avenue for achieving effective resolutions supporting boeing in surmounting its hurdles. the “risk-sharing supplier partnership model” encapsulates a collaborative approach in which both entities mutually undertake risks and responsibilities within the partnership, aiming for shared advantages and success. the key benefits of collaboration include enhanced communication, risk management, stability, and competitive advantage [27]. to improve collaboration, companies are advised to carefully select partners, maintain regular communication, aim for supply chain visibility beyond tier-i suppliers, and prioritize long-term planning. it offers a supplier collaboration portal to facilitate communication and contractual information sharing, strengthen relationships, and achieve mutual success within the supply chain. by incorporating this model into its risk management steps, boeing stands to gain numerous advantages in confronting supply chain challenges: advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 335 a. enhanced risk identification (1) close collaboration with suppliers enables boeing to identify potential risks by leveraging its collective expertise. (2) transparent communication between boeing and its suppliers enables timely risk reporting and identification. b. improved risk assessment (1) sharing data with suppliers enhances the risk assessment accuracy, providing a holistic view of potential threats. (2) joint assessment of risks allows boeing to consider interconnectedness within the supply chain. c. effective risk analysis (1) collaborative risk analysis with suppliers identifies root causes and consequences by leveraging their combined expertise. (2) shared risk analysis tools and methodologies ensure consistency, thereby improving the accuracy of risk evaluation. d. strategic risk treatment (1) collaborative risk treatment ensures efficient responsibility and liability sharing based on each party’s strengths. (2) risk-sharing agreements foster mutual investment in risk management and a sense of shared responsibility. e. continuous monitoring and review (1) risk monitoring and review allow real-time tracking of treatment effectiveness and emerging risks. (2) joint reviews and lessons learned in sessions drive risk management improvement and strengthen collaboration. additionally, the early identification of potential risks and formulation of mitigation strategies is of paramount importance, particularly in the aerospace industry, which is characterized by its complex and heavily regulated nature. this necessitates the execution of thorough risk assessments, establishing contingency plans, and vigilance for emerging risks as projects evolve. the implementation of rigorous quality control measures is fundamental to ensuring the dependability and safety of aerospace network systems and involves the setting of quality standards and procedures, regular quality evaluations, and compliance with the stringent standards and best practices of the aerospace industry. furthermore, fostering a culture of continuous improvement is crucial, necessitating regular reviews of project processes, outcomes, and team performance to identify opportunities for refinement. this involves a dedication to learning from each endeavor and applying the insights gained to enhance future project management practices. in principle, integrating the risk-sharing supplier partnership model with risk management was expected to help boeing build a more resilient and collaborative supply chain, mitigate risks more effectively, and enhance its ability to achieve shared objectives with suppliers. by fostering closer collaboration and shared responsibility, boeing can address supply chain challenges more proactively, ultimately improving its operational efficiency and reducing the likelihood of disruption. boeing’s risk-sharing supplier partnership model has encountered a range of challenges and has drawn substantial criticism [25]. key issues are: (1) incentive misalignment: the model inadvertently created an incentive trap. it encouraged suppliers, who were covering the initial research and development (r&d) costs, to protract the development process and inflate expenses, directly contradicting boeing’s goals. this is a good example of how misaligned incentives can lead to significant cost overruns, delays, and quality problems. (2) delayed payments: the risk-sharing model included a payment structure that exposed suppliers to the risk of program delays. the payment was contingent upon certification and delivery, placing a significant financial burden on suppliers. (3) loss of control: by heavily relying on the risk-sharing model, boeing delegated the selection and management of sub-tier suppliers to their partners, leading to reduced oversight and control over the supply chain, particularly at lower tiers. this approach had significant implications for boeing’s overall control over the production process. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 336 (4) development disasters: the 787 program, beset by substantial delays and cost overruns, highlights the unforeseen challenges of integrating complex systems developed by multiple partners. the first flight was delayed by 26 months and the initial delivery by 40 months, with cost overruns exceeding $11 billion. this suggests that boeing may have overestimated the capacity of suppliers to manage the increased responsibilities and risks associated. (5) reputation risk: the risk-sharing model exposes boeing to reputational harm, even if liability for delays or quality issues can be shifted to the partner. (6) intellectual property concerns: the risk-sharing model, which granted suppliers intellectual property rights, could potentially reduce boeing’s control over critical technologies. the tce framework proposed by williamson [7] offers an explanation for challenges in boeing’s risk-sharing partnerships for the 787 dreamliner program. these partnerships, where suppliers co-invested in production in exchange for long-term contracts, created high asset specificity, opportunism, and bounded rationality. the risk-sharing agreements, without sufficient hierarchical oversight or safeguards, led to quality control issues and delays. this revealed a misalignment with tce’s recommendation for more integrated or relational governance when dealing with strategically important and interdependent suppliers. this case exemplifies the insight proposed by williamson [7] that an efficient organizational structure must match the complexity and risk of the transaction to minimize overall costs and inefficiencies. to summarize, the experience with boeing’s risk-sharing model serves as a valuable lesson. while the intent was to distribute risk and foster innovation, the outcome included significant delays, cost overruns, and a loss of control over the development process. this underscores the need for careful consideration of incentive alignment, robust oversight mechanisms, and a realistic appraisal of supplier capabilities when undertaking complex aerospace projects. boeing continues to contend with production and supply chain issues, causing significant delivery delays that are disrupting airline operations and financial planning [28]. major carriers such as ryanair and emirates have adjusted their financial forecasts and reported losses owing to late aircraft deliveries [29]. similarly, american airlines has had to suspend routes and delay upgrades due to delayed 787 dreamliner deliveries. these persistent challenges underscore the ongoing weaknesses in boeing’s global supply chain management and their widespread impact on airline customers. furthermore, safety concerns, e.g., the incident involving alaska airlines flight, remain high, with recent incidents bringing renewed scrutiny to boeing’s quality control practices. the incidents point to systemic shortcomings in boeing’s oversight and quality assurance processes, further eroding trust among airlines and passengers. moreover, reports suggest deeper systemic issues within boeing’s operations, such as misaligned priorities favoring cost-cutting over safety and quality [28]. these challenges are compounded by fragmented supplier relationships, leading to inefficiencies and reduced control over production processes. these developments reinforce the need for boeing to adopt more robust risk management strategies, enhance supplier oversight, and prioritize transparency and quality assurance across its global operations. the company must also address organizational reforms to rebuild trust and ensure long-term operational resilience. 7. discussion on key research findings this study undertook a comprehensive and in-depth examination of the systemic issues that have plagued boeing’s supply chain management, quality assurance protocols, and aircraft certification processes. the following discussion delineates the salient findings uncovered during this thorough investigation. boeing’s shift to a highly outsourced, risk-sharing supply chain for the 787 was intended to reduce costs and speed up development by utilizing global expertise. however, this strategy proved counterproductive, resulting in fragmented oversight, loss of direct control, and increased vulnerability to quality and delivery advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 337 issues. numerous suppliers struggled to meet standards and deadlines, exposing the risks of this model. the negative consequences of this strategy became evident through delays in parts delivery [28], problems on the assembly lines [14], and lapses in manufacturing quality [13]. the oda program, which allowed boeing to self-certify, significantly expedited approvals but also resulted in critical lapses. this issue was exacerbated by the faa’s ineffective delegated oversight and internal pressure on boeing engineers to prioritize speed over safety. the adverse effects were evident in issues such as the mcas software being implemented without adequate pilot training [17] and the financial pressures boeing faced in competing with airbus’s a320neo model [18]. intense cost-cutting at boeing eroded its safety culture, particularly evident in the controversial ipad-based pilot training for the 737 max. poor communication with suppliers exacerbated defects, such as loose seats reported by klm. these misaligned incentives within boeing highlight significant systemic gaps. the lack of integrated supply chain visibility and insufficient supplier collaboration directly caused costly delays [11], widespread quality problems [21], and severe production bottlenecks [18]. the dreamliner’s issues demonstrate that even advanced it systems like exostar are unable to overcome poor supplier integration and oversight without strong visibility and proactive engagement. following logistical and safety failures, boeing revised its outsourcing strategy, repatriating integral operations and enhancing supplier controls. this decision is consistent with tce’s assertion that firms adjust governance structures to minimize transaction costs. however, boeing still faces challenges, e.g., addressing manufacturing lapses, that must be resolved to fully recover and restore trust [22]. this study quantifies the impact of factors like supplier reliability, transportation delays, and material quality on overall supply chain performance through the application of structured risk analysis methods, such as risk matrices. the 737 max crashes and the 787 dreamliner development process exposed significant shortcomings in risk analysis methods [21]. this quantitative, systems-based approach advocates for such tools to prioritize risks and guide effective mitigation strategies. boeing’s risk-sharing contracts for the 787, which linked supplier payments to final delivery, unintentionally incentivized some suppliers to delay work, increasing the risk of program delays [25-26]. this case illustrates how poorly designed contracts can worsen supply chain risks, as boeing attempted to shift development and production risks without proper oversight or safeguards. boeing’s reactive risk management [23] failed to anticipate supply chain fragmentation and the mcas single-point-offailure. primary interventions (such as acquiring suppliers or deploying engineers) occurred only after delays and cost overruns materialized. this underscores the critical need for proactive management, rigorous supplier selection, clear communication, and ongoing risk assessment in aerospace supply chains. over the decades, boeing’s safety record has steadily improved, with significantly fewer passenger fatalities from 2018 to 2022 compared to the 1968 to 1977 period [2]. this improvement continues even with recent quality-control problems on the 787 dreamliner and 737 max, which arise from different systemic issues. but these setbacks emerge within a larger aviation safety system that has many layers, e.g., advanced technology, strict regulations, and a strong safety culture. these layers are designed to reduce risk and manage problems from individual manufacturers. as a result, overall long-term safety continues to improve even amid occasional high-profile incidents. to understand aviation safety, the public should examine standard numbers like the global accident rate (accidents per million flights), the fatal accident rate (deadly accidents per million flights), and the fatality rate per 100 million people on board [2]. minor issues that are not directly associated with fatalities, such as small cracks, rough landings, or electrical glitches, might indicate quality control concerns, but they are not necessarily indicative of an increased risk of a crash. ultimately, long-term accident rates are the most reliable way to gauge aviation safety. advances in technology innovation, vol. 10, no. 4, 2025, pp. 321-339 338 boeing’s recovery depends on internal reforms and u.s. government policy. despite production improvements and a strong order book, the company faces significant challenges and growing competition from airbus. boeing is considered too big to fail due to its strategic importance, national security role, and economic impact. the u.s. government is highly unlikely to countenance the collapse of boeing, as this would enable airbus to attain a near-monopoly and have severe geopolitical consequences. the government intervention that repeatedly shields boeing from the consequences of its failures, such as through subsidies, procurement favors, or relaxed oversight, creates a moral hazard. this safety net can foster complacency and risktaking within the company, as executives benefit from favorable outcomes without facing the full repercussions of poor decisions. such unconditional support risks delaying necessary reforms, increasing the potential for regulatory capture, and promoting short-term fixes over fundamental improvements. without stringent conditions, such as mandatory safety overhauls, leadership changes, strong oversight, and enforceable accountability, a guaranteed lifeline inadvertently exacerbates boeing’s underlying issues, reducing the crucial pressure on boeing to change. 8. conclusion this study examined how boeing’s outsourcing practices, particularly when combined with its self-certification license from the faa, precipitated significant lapses in both regulatory oversight and internal quality control. based on this analysis, the main conclusions are summarized as follows: (1) boeing’s risk management frameworks, although theoretically sound, faltered in practice due to a confluence of deepseated cultural, operational, and regulatory weaknesses. (2) the findings underscored the importance of supply chain visibility, robust collaboration, and proper incentive alignment as critical factors for effectively managing the inherent risks within a complex, globally outsourced aerospace supply chain, highlighting areas where boeing’s operations were deficient. (3) the 787 and 737 programs illuminate the urgent necessity for aerospace companies to adopt integrated, transparent, and flexible supply chain strategies, which boeing conspicuously failed to implement adequately. (4) tier-i suppliers must rigorously audit their own tier-ii suppliers to ensure product quality is never compromised, emphasizing the need for proactive oversight. 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[29] t. imanov and s. safaeimanesh, “a financial examination of the causes of the boeing company’s late aircraft delivery,” international journal of aviation science and technology, vol. 6, no. 01, pp. 36-44, 2025. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). microsoft word 1-v10n2(2025)-aiti#14192(85-101).docx advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 english language proofreader: chih-wei chang optimizing lags and hidden layers in hybrid models for forecasting stock return nuttaphat sukchitt1, manad khamkong2,*, lampang saechan2, napon hongsakulvasu3 1program in applied statistics, department of statistics, faculty of science, chiang mai university, chiang mai, thailand 2department of statistics, faculty of science, chiang mai university, chiang mai, thailand 3faculty of economics, chiang mai university, chiang mai, thailand received 26 august 2024; received in revised form 24 october 2024; accepted 25 october 2024 doi: https://doi.org/10.46604/aiti.2024.14192 abstract this study aims to minimize the root mean square error for stock return by optimizing lags and hidden layers in a hybrid model. the model combines the autoregressive integrated moving average with the exogenous variables model as linear components. the residuals derived from linear components are used in artificial neural networks and elman recurrent neural networks as non-linear components. a key feature of this approach is optimizing the selection of hidden layers and lags within the neural network, improving forecasting accuracy. the minimum mean square error forecast expression is derived, and the model is tested on stock price data during the covid-19 period, marked by significant market shocks. the root mean square error results for the proposed model, traditional hybrid model, and traditional time series model range from 0.0004 to 0.01, 0.0006 to 0.01, and 0.006 to 0.03, respectively. the results show that the proposed model outperforms both traditional models. keywords: econometrics, hybrid model, ann, arimax, ernn 1. introduction in recent years, the financial industry has recognized the paramount importance of forecasting stock market trends. however, the task of predicting stock market movements has become increasingly complex due to the influence of exogenous variables. external events, ranging from geopolitical developments to unforeseen global crises, introduce significant volatility and unpredictability, presenting a formidable challenge to traditional forecasting models. in response to these challenges, this paper introduces an innovative approach that amalgamates time series analysis with neural network methodologies. by hybridizing these techniques, the study aims to enhance the predictive accuracy of stock market forecasts in the presence of exogenous variables. central to the approach, the application of the autoregressive integrated moving average (arima) model symbolizes a cornerstone of time series analysis known for its efficacy in capturing temporal dynamics in financial data. to account for the impact of external events, the arima model is extended to an autoregressive integrated moving average with exogenous variables (arimax) framework, which incorporates exogenous variables into the forecasting equation, thereby enriching contextual understanding and predictive capability of the model [1]. furthermore, the study delves into the realm of neural networks, exploring two pivotal architectures: the artificial neural network (ann) and the elman recurrent neural network (ernn) [2]. these models are celebrated for their ability to learn complex patterns and dependencies from data, enabling these models to render them ideally suitable for forecasting tasks * corresponding author. e-mail address: manad.k@cmu.ac.th 86 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 where non-linear relationships are prevalent. the research investigates further by optimizing these neural networks, focusing on the identification of the optimal number of lags and the determination of the appropriate number of hidden layers. this optimization process is crucial for developing a hybrid model that synergizes the strengths of time series analysis and neural network architectures, proffering superior forecasting performance by comparing minimum mean square error (mmse) between the models. this paper is organized into five main sections. section 2 is a literature review. section 3 details the methodology, including descriptions of the data, the experimental environment, and statistical methods. section 4 reveals the empirical results of each model. the last section, section 5, concludes with remarks that reflect on the findings and highlight the contributions of the study. 2. literature reviews the application of forecasting models is a crucial aspect of decision-making in diverse fields such as public health, finance, energy, agriculture, and electricity. this section discusses several studies that have employed different forecasting methods to address specific challenges in these areas. the review provides insights into the performance and applicability of various forecasting models including a hybrid arima model and neural network model, in different contexts. studies on electrical consumption forecasting have highlighted the effectiveness of hybrid approaches combining traditional time series models with advanced machine learning techniques. almaleck et al. [3] using a hybrid method combining ann and arimax models, achieved superior performance in 24-hour-ahead forecasting for sports venues with a mean absolute percentage error (mape) of around 9%, outperforming standard machine learning techniques. pierre et al. [4] employed a combination of arima for trend modeling and deep learning methods (long short-term memory (lstm) and gated recurrent unit (gru)) for capturing fluctuations. their arima-lstm hybrid approach outperformed standalone models in predicting peak energy consumption, reaching the root mean square error (rmse) of 7.35. management of natural resources has made significant strides in the use of hybrid forecasting models in recent years. xu et al. [5] demonstrated that a hybrid arima-lstm model, based on the standardized precipitation evapotranspiration index, outperforms the conventional arima model, attaining the highest prediction accuracy at 6-month, 12-month, and 24-month scales, indicating the suitability for the forecasting of long-term drought in china. azad et al. [6] a seasonal autoregressive integrated moving average (sarima)-ann model was applied to predict water levels in india’s red hills reservoir, and it was confirmed that the hybrid model outperformed the sarima model. in thailand, nualtong et al. [7] demonstrated that a sarima-ann model yielded better results than either the sarima or standalone ann model, especially during the wet season. furthermore, a study by shahriar et al. [8] on pm2.5 forecasting in bangladesh demonstrated that hybrid models such as arima-ann significantly outperform arima by offering substantial improvements in prediction accuracy. these cases collectively highlight the robust capability of hybrid models to significantly enhance predictive outcomes in managing natural resources, surpassing traditional forecasting approaches. recent studies highlight the superiority of hybrid forecasting models over conventional methods in various sectors. fan et al. [9] demonstrated that a hybrid arima-lstm model significantly improved production forecasting by incorporating the effects of manual operations outperforming the traditional arima model. similarly, wang et al. [10] showed that an arima-ernn model for predicting pertussis in china provided lower error rates than its arima model. in the financial sector, hybrid forecasting models have demonstrated marked superiority over traditional models in predicting stock market trends. for instance, shetty and ismail [2] propose a hybrid non-stationary model using ernn to predict stock market price indices. this model combines linear and non-linear structures to capture market dynamics advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 87 effectively. besides, this study demonstrates superior forecasting accuracy, emphasizing the potential of neural network-based models in enhancing financial market predictions. furthermore, sharma et al. [11] illustrated that integrating lstm and arimax into forecasting improves accuracy beyond the conventional arima model, which adeptly accommodates external market influences. lv et al. [12] advanced this research by integrating complete ensemble empirical mode decomposition with adaptive noise and a hybrid model combining the autoregressive moving average (arma) and lstm models. this approach effectively decomposes the stock index into intrinsic mode functions and applies the arma model to stationary series and lstm to unstable series, refining the prediction process through time series decomposition, and the results exhibit that the prediction of the proposed model is closer to the real value than that of a standalone model like arima, lstm, gru models. alshawarbeh et al. [13] aimed to predict stock market indices using an arima-ann hybrid model, combining arima and ann to address the volatility and noise in financial data. by applying this approach to the nasdaq, nikkei, and cac 40 indices, the study finds that the arima-ann model renders more accurate forecasts than traditional arima and conventional ann models. lastly, singh et al. [14] emphasized the efficacy of combining lstm methods with arima for forecasting stock prices with high precision, highlighting the robustness of hybrid models in financial forecasting. the literature review highlights the diverse applications of forecasting models in various fields. these studies collectively provided valuable insights into the evolving landscape of forecasting methods and their impact on decision-making in different sectors. 3. methodology the methodology of this study is structured to integrate both linear and nonlinear modeling approaches to enhance the accuracy of stock market forecasting. by focusing on optimizing lags and hidden layers, the hybrid model combines arimax as a linear component and neural networks (ann/ernn) as nonlinear components. this section details the experimental environment, the data used, and the statistical methods applied to test the efficacy of the hybrid model. 3.1. experimental environment all experiments were conducted on a microsoft surface pro (5th generation) equipped with an intel core i5-7200u processor, 8 gb of ram, and a 256 gb ssd. the device operates on windows 10 pro. the software environment comprises r version 4.4.1, which runs on rstudio version 2024.04.2+764. the instruments utilized in this section are listed as follows. r packages were employed to conduct the analysis. the tseries package was used for time series modeling and statistical tests. the neural networks in r using the stuttgart neural network simulator (rssns) was utilized to implement ernn, and the neuralnet package was applied to implement ann. to ensure consistency and reproducibility of the neural network models, a fixed random seed (set.seed(51237)) was used in all relevant experiments. 3.2. data description this research considers secondary data, including the stock exchange of thailand (set) index across eight industries, as shown in table 1. these industries encompass the agro and food industry (seta), consumer products (setc), financials (setf), industrials (seti), property and construction (setp), resources (setr), services (sets), and technology (sett) [15]. table 1 the list of industry groups and sectors in the stock exchange of thailand (set) industry abbreviation sector agro and food industry seta agribusiness, food and beverage consumer products setc fashion, home and office products, personal products and pharmaceuticals 88 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 table 1 the list of industry groups and sectors in the stock exchange of thailand (set) (continued) industry abbreviation sector financials setf banking, finance and securities, insurance industrials seti automotive, industrial materials and machinery, paper and printing materials, petrochemicals and chemicals, packaging, steel property and construction setp construction materials, construction services, property fund and real estate investment trusts, property development resources setr energy and utilities, mining services sets commerce, health care services, media and publishing, professional services, tourism and leisure, transportation and logistics technology sett electronic components, information and communication technology the study also examined the google trends (ggt) index and the exchange rate between the thai baht (thb) and the us dollar. it should be noted that the idea of this section is oriented by napon’s work [16]. the collected data was divided into four periods. the first period is from 2 january 2020 to 1 june 2020. regarding the second period, it is from 2 november 2020 to 1 march 2021. the third period started from 1 march 2021 to 15 june 2021, and the fourth period is from 16 june 2021 to 30 december 2021. all variables will be converted to the growth rate and return by using the conventional formula. 1 ln −   =     t t t p r p (1) where �� is the return of the index, �� is the data for today, ���� is the data for yesterday. to ensure the robustness of the analysis, all variables underwent stationarity testing utilizing the phillips-perron (pp) test. the pp test, introduced by phillips and perron (1988), is used to determine whether a time series is stationary. the null hypothesis (h₀) of the pp test states that the time series has a unit root, implying it is non-stationary. the alternative hypothesis (h₁) states that the time series is stationary. concerning this study, a significant threshold was set at a p-value of less than 0.05, ensuring that the variables are appropriately stationary for accurate modeling and analysis [17]. 3.3. cross-correlation function (ccf) to detect the relationship between the two series, a cross-correlation function (ccf) is conducted to verify the relationships of the series [18]. the ccf is defined as follows: ( ) ( ) (0) (0) = xy xy xx yy c k ccf k c c (2) ( )( ) ( )( ) 1 1 1 , 0,1, , 1 ( ) 1 , 1, 2, , ( 1) − + = − + = −  − − = −  =   − − = − − − −    … … xx n k t t k t n k t t k t k x x y y k n n c k x x y y k n n (3) where ���(0) and ���(0) are the sample variances of � �� and ����. the ccf calculates the linear correlation between the series. this study focuses on lag 0 to determine the cross-correlation between the series. 3.4. hybrid modeling a hybrid model separating linear and non-linear components is a sophisticated method used to capture complex relationships in a dataset by individually addressing the linear and non-linear aspects. this approach enhances the ability to handle data nuances by combining the strengths of both linear and non-linear techniques [19]. the model was expressed as: = +t t ty l n (4) advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 89 where �� is the original time series, �� is the linear term, and �� is the non-linear term. the linear component is estimated using the arimax model, and the residuals are obtained from this model. given that the linear term is obtained from the following formula, the residual series �� from the arimax model is expressed as follows: ˆ= −t t tn y l (5) where ��� denotes the forecasting value for time t of the time series �� by arimax, �� represents the non-linear term of the model. subsequently, the neural network is used to estimate �� with m input nodes, the neural network (ann/ernn) model for the residuals can be formulated as follows: ( ) * 1 2, , , ε−− −= +…t t m tt tn f n n n (6) where �(. ) represents a non-linear function determined by the neural network (ann/ernn), �� ∗ is the residual. 3.5. auto regressive integrated moving average with exogenous variables the arimax model, with an exogenous variable as an additional predictor, can be used to predict the demand for a product based on its demand and some external factors such as advertising or competitors’ prices [20]. the arimax model can be expressed as follows: 1 1 φ θ ε ϕ ε− − = = ∇ = + ∇ + + +  p q d d t t i t i j t j t t i j l c l x (7) where ∇� is the degree of differencing, �� is the time series data at time t, �� is a constant value, �� is a residual, ���� is the autoregressive, ���� is the moving average, � is the exogenous variable, ��, ��, and � are the coefficients of ����, ����, and �, respectively. 3.6. artificial neural network (ann) fig. 1 structure of an ann model (modified from [22]) in recent years, neural networks have gained significant attention and are being effectively applied in a wide variety of fields. neural networks are increasingly used in areas involving prediction, classification, or control tasks. in addition, neural networks can be defined as a network of interconnected simple processing units, modeled after the biological neuron. a 90 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 biological neuron is a specialized unit that carries information or knowledge and transmits it to other neurons within the network. artificial neurons are organized in layers and interconnected, resembling synapses in the brain. the internal layers, called hidden layers, consist of varying numbers of neurons. the final layer, known as the output layer, has several neurons that match the number of outputs. expanding the number of neurons and layers improves the learning ability of ann, enabling them to handle more complex data [21]. a single hidden layer feedforward network is the most widely used model form for time series modeling and forecasting. the model is characterized by a network of three layers of simple processing units connected by acyclic links [22]. fig. 1 shows the structure of an ann model. the relationship between the output, ��, and the inputs, ����, ����, ⋯, ���! can be mathematical represented as: 0 0 1 1 α α β β ε− = =   = + + +     h q p t j j ij t i t j i n g n (8) where �� indicates the predicted output of the network at time t, "# symbolizes the bias term for the output layer, "� signifies the weights connecting the hidden layer to the output layer where j = 1, 2, ⋯, q, in this case, the logistic function, $#� are the bias terms for each of the hidden nodes j = 1, 2, ⋯, q, $�� are the weights connecting the input layer to the hidden layer where i = 1, 2, ⋯, p; j = 1, 2, ⋯, q, ���� are the input values at previous time steps (lags in time series terms) i = 1, 2, ⋯, p, �� is the error term for the prediction at time t. when %& is the linear function in the hidden layer which is selected as the activation function defined by: ( ) = h g v v (9) where v is the input value. 3.7. the elman recurrent neural network (ernn) fig. 2 structure of an ernn model (modified from [2]) ernn, also referred to as a simple recurrent network, is a form of feedforward ann that incorporates feedback connections, enabling it to handle sequential data and time series [2] which are comprised of input, hidden, output, and recurrent layers [23-24]. in the ernn, the recurrent layer receives feedback from outputs of the hidden layer, empowering the network to learn, identify, and generate both spatial and temporal patterns. each neuron in the hidden layer connects to a advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 91 corresponding neuron in the recurrent layer with a fixed weight of one. this structure makes the recurrent layer function as a memory of the hidden layer’s previous state. the number of neurons in the recurrent layer matches that of the hidden layer. neurons pass information to subsequent layers by applying a nonlinear function to the weighted sum of their inputs. this design enables the ernn to effectively analyze and respond to complex patterns [23]. fig. 2 shows the structure of an ernn model. the inputs of the hidden layer are given by the following formula, ( ) ( ) ( ) 1 1 1α β = = = − +  m u it ij it j jt i j net k e k c k (10) ( ) ( )1 , 1,2, , ; 1,2, ,= − = =⋯ ⋯jt jtc k h k i m j u (11) where '()�� denote network at time t, m is the number of neurons in the inputs layer, u is the number of neurons in the hidden layer, (�� is the set of an input vector of neurons at the time t where i = 1, 2, ⋯, m, ℎ�� is the output of hidden layer neurons at time t where j = 1, 2, ⋯, u, +�� is the context layer neuron at time t where j = 1, 2, ⋯, u, "�� is the weight that connects the node i in the input layer neurons to the node j in the hidden layer, $� are the weights that connect the node j in the context layer neurons to the node in the hidden layers, and k is the maximum training iteration number and initial connective weights. additionally, the topology of the network architecture is determined by the number of neural nodes in the hidden layer. as a result of the hidden neurons, the output is as follows: ( ) ( ) ( ) 1 1 1α β = =   = − +     h m u jt ij it j jt i j h k f e k c k (12) where the linear function �& in the hidden layer is selected as the activation function based on the following equation: ( ) = h f v v (13) where v is the input value. the output of the hidden layer is given as follows: ( ) 1 δ =   =     t m t j jt j n f h k (14) where �� is the output of the network at time t, ,� are the weights that connect the node j, in the hidden layer neurons to the node in the output layers, and �-(. ) is an identity map as the activation function. 3.8. the general framework of the hybrid model the estimation of �� will result in the estimation of the non-linear component in the time series �.�. the estimated values of the time series are obtained as follows: ˆ ˆˆ = +t t ty l n (15) the neural network (ann/ernn) can effectively capture the non-linear patterns present in the residuals obtained from the arimax model. by incorporating neural network (ann/ernn) into a hybrid model, forecasting that performance can be significantly enhanced [10]. hence, the problem of spurious regression can be addressed by using hybrid arimax models with neural network (ann/ernn) to account for linear and non-linear terms in time series data. these methods furnish a 92 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 powerful tool for accurately modeling time series data and can help overcome the limitations of traditional regression models in the presence of spurious regression. traditionally, the number of hidden layers is selected based on minimizing the mmse [25]. ( ) 2 1 1 ˆ = − −= − q t i t i i mmse n n q (16) 3.9. optimization of the hybrid model the approach extends this methodology by systematically optimizing both the number of lagged inputs ((��) and the number of hidden layers (denoted as ℎ��). the optimization is conducted through a hybrid model that aims to minimize the mean squared error, as detailed in the following equation: ( ) 2 1 1 ˆ = − −= − q t i t i i mmse q y y (17) fig. 3 depicts the enhanced process flow of the hybrid model featuring alternative optimization. the sequence initiates with the input �� , /� which enters the arimax model, functioning as the linear estimator to generate ���. the residuals from this model are fed into a neural network (ann/ernn) thereafter, serving as the nonlinear estimator to compute �0�. the system subsequently assesses if the combination of ��� and �0� satisfies the mmse threshold. if the mmse criteria are not fulfilled, the process iteratively refines the lags and hidden layers within the neural network to optimize �0�, thereby enhancing the predictive accuracy. upon meeting the mmse threshold, the final output �.� is produced. fig. 3 conceptual framework of alternative optimization of hybrid model 4. results and discussion this section presents the findings from the ccf analysis, and the statistical tests conducted to evaluate its performance. the results comprise a detailed comparison of model performance and highlight key findings from the analysis across each period. 4.1 result from cross-correlation function (ccf) this section presents the results of the ccf analysis, a crucial tool for detecting relationships between two-time series. the analysis focuses on the correlations between various indices of the set as endogenous variables with ggt and the thb across four distinct periods from table 2 to table 5. table 2 cross-correlation analysis for the first period variable seta setc setf seti setp setr sets sett ggt −0.2957* −0.3769* −0.3041* −0.3056 * −0.3289* −0.2268* −0.2846* −0.2456* thb −0.2609* −0.2384* −0.2161* −0.1970* −0.2429* −0.1721 −0.2790* −0.2228* *95% significant level at confidence interval between [-0.1803, 0.1803] advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 93 table 3 cross-correlation analysis for the second period variable seta setc setf seti setp setr sets sett ggt 0.0519 0.1187 −0.0901 −0.0798 0.0270 −0.0353 −0.0439 0.0108 thb −0.2422* 0.1656 −0.3154* −0.2757* −0.3241* −0.3106* −0.3262* −0.1332 *95% significant level at confidence interval between [-0.1825, 0.1825] table 4 cross-correlation analysis for the third period variable seta setc setf seti setp setr sets sett ggt 0.0120 0.1542 −0.2905* −0.0019 −0.2717* −0.0575 −0.2533* −0.1090 thb −0.1063 −0.0282 0.0357 0.0775 0.0112 −0.0612 −0.0275 −0.0926 *95% significant level at confidence interval between [-0.2340, 0.2340] table 5 cross-correlation analysis for the fourth period variable seta setc setf seti setp setr sets sett ggt −0.0243 −0.0669 0.0369 −0.0458 0.0092 0.0251 0.0399 −0.1299 thb −0.1446 0.008 −0.2250* −0.1362 −0.2671* −0.2166* −0.2699* −0.0260 *95% significant level at confidence interval between [-0.1543, 0.1543] the ccf analysis presented in the tables reveals significant insights into the relationships between indices of the set with ggt and the thb across four distinct periods. during the first period, ggt and thb exhibited significant negative correlations with all sectors except for the relationship between thb and setr. in the second period, significant correlations of ggt were absent, while thb demonstrated significant negative correlations with all sectors except for setc and sett. the third-period analysis indicated that ggt had significant negative correlations with setf, setp, and sets, while thb did not show significant correlations during this period. finally, in the fourth period, ggt did not exhibit significant correlations, while thb exhibited significant negative correlations with setf, setp, setr, and sets. 4.2. empirical application this section evaluates the performance of the optimized hybrid arimax models with neural network (ann/ernn) by applying the set index data across each sector with exogenous variables for each period. the performance of the optimized arimax models with neural network (ann/ernn) is benchmarked against traditional arimax models and traditional arimax models with neural network (ann/ernn), thereby highlighting keys from the analysis. 4.2.1 result from the first period with ggt table 6 presents evidence that the arimax model from the first period with ggt as an exogenous variable exhibits significant results in all sectors including negative coefficients. furthermore, table 7 displays the lowest akaike information criterion (aic) values and p-value of the ljung-box test supporting the null hypothesis and implying that residuals of the model are white noise. table 8 details the chosen lag and hidden layer of each model. fig. 4 presents the rmse value for each model demonstrating that the hybrid model outperforms the arimax model. moreover, every optimized hybrid model yields better performance compared to both the traditional hybrid model and the traditional arimax model. table 6 coefficients and p-values of the first period arimax model with google trends index variable seta setc setf seti setp setr sets sett ar1 0.8771* 0.7522* 1.3238* 0.7791* 1.4713* −0.5070 −1.2318* −0.7022* ar2 −0.9002* −0.58801* −0.8341* 0.3895 −0.3124* −0.8062* ar3 0.2865* ma1 −1.0171* −0.9111* −1.5068* −0.9304* −1.6086* 0.9999* 0.6983* ma2 0.9999* 0.2680 0.8323* 0.2153* 0.9999* 0.3859 0.8503* ma3 −0.4460 −0.1719 ggt −0.0307* −0.0165* −0.0388* −0.0385* −0.0348* −0.0319* −0.0316* −0.0189* *significant at 0.05 94 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 table 7 akaike information criterion (aic) values and ljung-box test p-values for arimax models with google trends index in the first period technique seta setc setf seti setp setr sets sett aic −590.294 −777.892 −540.771 −522.827 −591.543 −506.495 −593.228 −629.452 ljung-box 0.2553 0.84331 0.9837 0.9813 0.462 0.9996 0.9707 0.8894 table 8 configuration of lags and hidden layers in neural network models with google trends index for the first period technique lags and hidden layers seta setc setf seti setp setr sets sett traditional ann lags 1 1 1 1 1 1 1 1 hidden layers 23 7 32 17 5 17 91 7 optimized ann lags 4 1 1 4 1 3 2 3 hidden layers 6 71 70 30 45 52 10 42 traditional ernn lags 1 1 1 1 1 1 1 1 hidden layers 59 88 93 90 80 82 93 59 optimized ernn lags 1 1 2 1 4 5 2 2 hidden layers 46 40 63 52 97 58 43 89 fig. 4 performance comparison of models using the google trends index as an exogenous variable in the first period 4.2.2 result from the first period with thb table 9 shows that except for setr the arimax model in the first period with thb as an exogenous variable is significant across all sectors. table 10 highlights the model with the lowest aic, along with the p-value of the ljung-box test, confirming white noise in the residuals. table 11 presents the hybrid arimax-ernn model for seta and setp, which has identical lag and hidden layer configurations in both traditional and optimized modes. the results in fig. 5 demonstrate that the arimax-ernn model for seta and setp yields identical performance in both traditional and optimized configurations. additionally, the hybrid model consistently outperforms the arimax model. the optimized hybrid model surpasses both the traditional hybrid model and the traditional arimax model in all optimized configurations. advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 95 table 9 coefficients and p-values of the first period arimax model with thai bath (thb) variable seta setc setf seti setp sets sett ar1 −0.9607* 1.0241* 0.6415* −1.2464* −1.7152* −1.1349* −0.9164* ar2 −0.1618 −0.7139* 0.1651* −0.9359* −0.8275* −0.2893* −0.8016* ma1 0.8590* −1.1832* −0.7330* 1.1882* 1.6998* 0.9230* 0.9902* ma2 0.9999* 0.9999* 0.7553* 0.9999* thb −1.6612* −0.5689* −1.4272* −1.4624* −1.6896* −1.8257* −1.1215* *95% significant level table 10 akaike information criterion (aic) values and ljung-box test p-values for arimax models with thai bath in the first period technique seta setc setf seti setp sets sett aic −584.175 −770.001 −529.157 −523.496 −588.622 −590.41 −628.809 ljung-box 0.874535 0.791028 0.915481 0.271637 0.981394 0.782526 0.696605 table 11 configuration of lags and hidden layers in neural network models with thai bath for the first period technique lags and hidden layers seta setc setf seti setp sets sett traditional ann lags 1 1 1 1 1 1 1 hidden layers 8 16 7 47 5 91 7 optimized ann lags 1 4 2 2 1 3 2 hidden layers 17 61 10 85 51 75 96 traditional ernn lags 1 1 1 1 1 1 1 hidden layers 59 88 95 85 59 93 59 optimized ernn lags 1 3 1 2 1 1 2 hidden layers 59 95 52 63 59 94 89 fig. 5 performance comparison of models using thai bath as an exogenous variable in the first period 96 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 4.2.3 result from the second period with thb table 12 depicts that all sectors, except setc and sett, have negative coefficients in the arimax model during the second period with thb as an exogenous variable. table 13 supports the null hypothesis that the residuals are white noise and highlights the models with the lowest aic values. table 14 lists the opted hidden layers and lag configurations, with the hybrid arimax-ernn model for setf denoting identical setups in both traditional and optimized models. fig. 6 indicates that the arimax-ernn model for setf yields identical results in both traditional and optimized models. the optimized hybrid model outperforms both the traditional hybrid and arimax models. fig. 6 performance comparison of models using thai bath as an exogenous variable in the second period table 12 coefficients and p-values of the second period arimax model with thai bath (thb) variable seta setf seti setp setr sets ar1 0.9561* −0.8463* −0.1079 0.8856* 1.4443* −0.8714* ar2 −0.1112* −0.7787* −0.6594* −0.9951* ar3 −0.2047* ma1 −1.1374* 0.7463* −0.0188 −0.8402* −1.6374* 0.8762* ma2 0.1374 0.9999* 0.9994* 0.9771* ma3 -0.0217 thb −0.8201* −1.5790* −1.1882* −1.1531* −1.85461* −1.3732* *significant at 0.05 table 13 akaike information criterion (aic) values and ljung-box test p-values for arimax models with thai bath in the second period technique seta setf seti setp setr sets aic −728.935 −659.234 −671.951 −727.489 −657.02 −699.31 ljung-box 0.9661 0.9995 0.8892 0.32160 0.9164 0.9556 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 97 table 14 configuration of lags and hidden layers in neural network models with thai bath for the second period technique lags and hidden layers seta setf seti setp setr sets traditional ann lags 1 1 1 1 1 1 hidden layers 26 80 30 7 47 21 optimized ann lags 5 2 3 5 5 4 hidden layers 52 73 87 11 79 75 traditional ernn lags 1 1 1 1 1 1 hidden layers 40 85 85 40 46 40 optimized ernn lags 2 1 1 4 3 1 hidden layers 46 85 40 86 89 85 4.2.4 result from the third period with ggt index table 15 indicates that setf and setp have negative and significant coefficients in the arimax model with ggt as an exogenous variable during the third period. table 16 highlights the model with the lowest aic and a p-value from the ljung-box test, supporting the null hypothesis and suggesting that the residuals are noise. table 17 outlines the opted hidden layers and lag configurations, indicating that the hybrid arimax-ernn model for setf offers the same configurations in both traditional and optimized modes. fig. 7 shows that the arimax-ernn model for setf produces the same results in both traditional and optimized modes. moreover, such a finding confirms that the optimized hybrid model outperforms both the traditional hybrid and arimax models. fig. 7 performance comparison of models using the google trends index as an exogenous variable in the third period table 15 coefficients and p-values of the third period arimax model with google trends (ggt) index variable setf setp ar1 −0.56539 0.99661* ma1 0.715767* −0.92404* ma2 −0.06181 ggt −0.01542* −0.01042* *significant at 0.05 table 16 akaike information criterion (aic) values and ljung-box test p-values for arimax models with google trends index in the third period technique setf setp aic −431.606 −493.575 ljung-box 0.775444 0.857292 table 17 configuration of lags and hidden layers in neural network models with google trends index for the third period technique lags and hidden layers setf setp traditional ann lags 1 1 hidden layers 62 30 optimized ann lags 2 2 hidden layers 32 35 98 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 table 17 configuration of lags and hidden layers in neural network models with google trends index for the third period (continued) technique lags and hidden layers setf setp traditional ernn lags 1 2 hidden layers 57 46 optimized ernn lags 1 1 hidden layers 57 72 4.2.5 result from the fourth period with thb table 18 demonstrates that the arimax model with thb as an exogenous variable in the fourth period is statistically significant for setf, setp, setr, and sets with all models exhibiting negative coefficients. in table 19, the arimax model is selected by its lowest aic values while p-values of the ljung-box test confirm that the residuals are white noise supporting the null hypothesis. table 20 renders a detailed comparison of the selected lags and hidden layers for each model. notably, setp and sets exhibit identical lags and hidden layers in their traditional and optimized arimax-ernn models. the performance presented in fig. 8 reveals that the arimax-ernn model yields consistent results for setp and sets in both traditional and optimized approaches. the optimized hybrid model excels both the traditional hybrid and arimax models in performance. fig. 8 performance comparison of models using thai bath as an exogenous variable in the fourth period table 18 coefficients and p-values of the fourth period arimax model with thai bath (thb) variable setf setp setr sets ar1 0.5920* −0.5989* −0.6401* −0.4478 ar2 −0.1642* ma1 −0.6814* 0.6631* 0.7828* 0.4225 thb −0.7917* −0.4754* −0.3997* −0.6529 *significant at 0.05 advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 99 table 19 akaike information criterion (aic) values and ljung-box test p-values for arimax models with thai bath in the fourth period technique setf setp setr sets aic −1016.12650 −1193.54 −1121.17 −1153.28 ljung-box 0.638347241 0.379886 0.5806 0.978849 table 20 configuration of lags and hidden layers in neural network models with thai bath for the fourth period technique lags and hidden layers setf setp setr sets traditional ann lags 1 1 1 1 hidden layers 7 30 34 30 optimized ann lags 5 3 4 5 hidden layers 19 47 85 53 traditional ernn lags 1 1 1 1 hidden layers 80 40 46 99 optimized ernn lags 1 1 1 1 hidden layers 46 40 57 99 5. conclusion this study has developed a hybrid forecasting model that integrates arimax with neural networks (ann/ernn) using an alternative optimization process. in contrast to the traditional hybrid approach, where the rmse of the nonlinear component is calculated iteratively until the lowest value is obtained and subsequently added to the linear component, the proposed method calculates the rmse after both linear and nonlinear components are combined. this rmse is subsequently refined through iterative looping until the least rmse is achieved, ensuring a more accurate optimization process for the hybrid model. the proposed methodology demonstrates significant improvements in predictive accuracy by effectively capturing both linear and nonlinear components in the set index across eight industries during the covid-19 period. according to the results, the optimized hybrid models achieved the lowest rmse. these findings confirm that the proposed optimization 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[25] k. sako, b. n. mpinda, and p. c. rodrigues, “neural networks for financial time series forecasting,” entropy, vol. 24, no. 5, article no. 657, 2022. copyright© by the authors. licensee taeti, taiwan. this article is an open-access article distributed under the terms and conditions of the creative commons attribution (cc by-nc) license (https://creativecommons.org/licenses/by-nc/4.0/). appendix abbreviation definition ann artificial neural network arimax autoregressive integrated moving average with exogenous variables advances in technology innovation, vol. 10, no. 2, 2025, pp. 85-101 101 ernn elman recurrent neural network arima autoregressive integrated moving average mape mean absolute percentage error lstm long short-term memory gru gated recurrent unit rmse root mean square error sarima seasonal autoregressive integrated moving average arma autoregressive moving average set stock exchange of thailand seta stock exchange of thailand in agro and food industry sector setc stock exchange of thailand in consumer products sector setf stock exchange of thailand in financials sector seti stock exchange of thailand in industrials sector setp stock exchange of thailand in property and construction sector setr stock exchange of thailand in resources sector sets stock exchange of thailand in services sector sett stock exchange of thailand in technology sector thb thai baht ggt google trends pp phillips-perron ccf cross-correlation function mmse minimum mean square error aic akaike information criterion  advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 analysis of characteristics of complaints on parenting q&a sites using plsa and data augmentation tomoki yoshimi1,*, takashi namatame2 1graduate school of science and engineering, chuo university, tokyo, japan 2faculty of science and engineering, chuo university, tokyo, japan received 30 december 2024; received in revised form 08 august 2025; accepted 11 august 2025 doi: https://doi.org/10.46604/aiti.2025.14700 abstract this study investigates the classification and clustering of complaints on a japanese parenting q&a site, aiming to identify meaningful patterns from limited labeled data. to address data scarcity, generative ai was utilized for data augmentation through prompts that reflected authentic parenting frustrations, with synthetic data validated by comparing classification performance under varying proportions of generated content. complaint texts were vectorized using bag-of-words, doc2vec, and sparse composite document vectors, providing multiple levels of semantic representation. lightgbm was used as the classifier, and f1 scores measured performance. clustering of predicted complaints employed probabilistic latent semantic analysis, with topic numbers selected via bayesian information criterion. six distinct themes emerged, including childcare stress and family conflict. incorporating generated data improved the f1 score from 0.824 to 0.865. the findings highlight the potential of generative ai to augment low-resource datasets and demonstrate the effectiveness of context-aware embeddings and probabilistic clustering in structuring real-world text data. keywords: q&a site, complaint, nlp, data augmentation 1. introduction in recent years, social networking services (sns) and q&a sites have become platforms where users frequently post their daily frustrations. on sns, venting complaints is often seen as a stress-relieving activity, providing users with an emotional outlet [1]. on q&a sites, however, the nature of complaints differs due to their primary function as platforms for solving problems and sharing practical knowledge. despite this, complaints are often posted on q&a sites, which diverges from their intended purpose. this phenomenon can sometimes reduce the effectiveness of these platforms as reliable sources of information. in japan, many complaints on q&a sites revolve around family and child-related issues, such as child-rearing and housework. these topics represent common sources of frustration, particularly for mothers. previous studies have also noted that family-related issues are a recurring theme in complaints shared on online platforms [2]. research on complaints has been limited, particularly in the context of the japanese language. regarding japanese complaints, few studies have utilized data-driven approaches. for instance, aside from ito et al. [3], collected complaints from the former version of twitter and classified them into 11 categories based on their characteristics. moreover, ito et al. [4] developed models that incorporate the subject of the complaint to improve classification accuracy. most studies have focused on linguistic or psychological perspectives rather than leveraging data for analysis. in contrast, substantial research has been conducted on complaints in other languages. for example, preotiuc-pietro et al. [5] developed a model to automatically classify the existence and types of complaints. jin and aletras [6] created a model that * corresponding author. e-mail address: a19.pb66@g.chuo-u.ac.jp advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 384 categorized complaints into four types: “no explicit reproach,” “disapproval,” “accusation,” and “blame.” fang et al. [7] proposed using best-worst scaling to represent the intensity of complaints, pioneering quantitative evaluation in this area. tian et al. [8] developed an automated system for processing customer complaints in the water utility sector by leveraging word vector-based similarity, sentiment analysis, and intent recognition using nlp tools such as spacy and rasa. more recently, alarifi et al. [9] employed machine learning approaches, including logistic regression and support vector machines, to effectively predict and analyze customer complaint data, demonstrating their utility in understanding consumer grievances. additionally, jin et al. [10] introduced a method for enhancing the representation of complaints through word embeddings and utilized a deep learning approach to improve classification accuracy. complaints have also been utilized in product development to identify customer needs and improve product offerings. in this context, recent work by wang et al. [11] explored how customer complaints can be used as a valuable source of feedback for product innovation and development. however, these studies primarily focus on the severity or subject of complaints, with less attention given to complaints specifically related to child-rearing. based on these situations, this study aims to classify complaints related to child-rearing using data derived from a japanese q&a site. to address the challenges associated with limited labeled training data, this study explores the use of generative ai, specifically chatgpt by openai, as a tool for augmenting datasets. by generating additional data aligned with specific criteria, the study evaluates the impact of ai-generated data on classification performance and compares it to traditional data augmentation methods. through this approach, the study seeks to expand the available dataset, improve classification accuracy, and provide new insights into the potential of generative ai in natural language processing tasks. 2. data set this section describes the datasets used for analyzing complaints on parenting q&a sites, including their sources, preprocessing steps, and key characteristics. the datasets were selected to provide text data specifically related to parenting, containing a substantial number of posts expressing dissatisfaction or complaints, making them suitable for the objectives of this study. (1) data source: this study analyzes data provided by a japanese q&a website focused on parenting and household matters. the data spans two years, covering 2022 and 2023. all users have been anonymized. this website is primarily used by mothers and serves as both a q&a platform and a resource offering various columns and articles related to parenting. (2) dataset description: the dataset consists of a total of 5,451,588 entries and is composed of question data and corresponding answer data. in this study, only question data was used for analysis. the dataset includes the following columns: • question id: each post is uniquely identified and linked to its corresponding answer. • user id: a unique value is assigned to each user. • category id: each post can be assigned to a category selected by the poster from among 15 available categories. • content: the actual content of the post written by the user is included. • created date: the date and time when the post was submitted are recorded. (3) preprocessing: the raw text data underwent several preprocessing steps in preparation for analysis: • segmentation using morphological analysis: since japanese does not separate words with spaces, it is necessary to divide the text into individual words through morphological analysis. • removal of unnecessary numbers and symbols: numbers and symbols do not carry meaningful information on their own and need to be removed for analysis. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 385 (4) summary of categories: table 1 summarizes the 15 content categories available on the parenting q&a site, along with their respective proportions. the largest category, “parenting & goods” (34.3%), includes questions and complaints related to child-rearing techniques, recommended items, and everyday parenting experiences. “pregnancy & childbirth” (14.1%) is another major category, reflecting frequent discussions about physical and emotional challenges during pregnancy, preparation for childbirth, and postpartum recovery. the “chat & tweets” category (9.7%) includes casual conversations and emotionally charged messages that do not necessarily fit into practical question-and-answer formats, and this category often contains venting-type complaints. table 1 category of contents category (%) category (%) pregnancy & childbirth 14.1 work 2.5 parenting & goods 34.3 fashion & cosmetics 2.4 supplements & health 1.9 family & husband 5.7 mental health & worries 6.0 outings 2.6 trying to conceive 3.4 gynecology & pediatrics 2.0 household chores & cooking 3.8 housing 1.4 money & insurance 3.4 others 6.7 chat & tweets 9.7 3. analysis method the methodology used in this study is introduced below. the purpose of this section is to outline how the dataset was prepared, how additional data were generated, and how the resulting text was analyzed to identify complaint patterns. by presenting each step in detail, the process highlights both the methodological rigor and the rationale for combining manual labeling, generative augmentation, classification, and clustering in a single workflow. the steps of the study are as follows: (1) from the posted comments, 2,000 entries were randomly sampled and manually labeled to determine whether they were complaints or not. (2) the posted comments were used to train chatgpt to generate similar complaints. however, rather than directly training on the data provided, the subjects were given constructed prompts about the topic of dissatisfaction. the prompts used for this process will be described later. (3) the content of the posts was vectorized using various methods. in this study, three methods were employed: bag-ofwords (bow), doc2vec, and sparse composite document vectors (scdv). (4) classification was performed using light gradient boosting machine (lightgbm) while varying the proportion of generated complaints. (5) the classifier with the best performance was used to extract a large number of complaint data from the original dataset. clustering was then performed to analyze the types of complaints being posted. the clustering method used was probabilistic latent semantic analysis (plsa). fig. 1 illustrates the overall analysis workflow adopted in this study, which consists of five major steps. first, 2,000 posts were randomly sampled from the parenting q&a dataset and manually labeled to identify whether they were complaints or not. second, generative ai (chatgpt) was used to augment the dataset by generating synthetic complaints based on carefully designed prompts. third, the text data—both real and synthetic—were vectorized using three different methods: bow, doc2vec, and scdv, each capturing different levels of semantic and contextual information. fourth, lightgbm was applied to classify the posts, and the performance was evaluated using the f1 score to determine the optimal proportion of generated data. finally, complaint posts identified by the best-performing model were clustered using plsa, which uncovered latent complaint themes and provided insights into the underlying structure of the data. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 386 fig. 1 analysis procedure 3.1. data labeling the original dataset did not contain labels indicating whether each post was a complaint. therefore, the first step was to manually label the data based on whether the content constituted a complaint. for this purpose, 2,000 posts were randomly sampled from the full dataset. each post was carefully read and evaluated by two researchers using predefined criteria: a post was labeled as a complaint if it expressed dissatisfaction, frustration, or a change request, often accompanied by negative emotions or references to problems encountered. in cases where the judgment was ambiguous, the two researchers discussed the content to reach an agreement. this labeled subset was later used as the ground truth for training and evaluating the complaint classification models in the machine learning experiments described in subsequent sections. 3.2. data augmentation due to the limited amount of complaint data, data augmentation was performed using chatgpt. in this study, the following prompt was used for the analysis: i am a researcher on the complaint. i am currently researching what mothers think about complaining. so, please write 10 complaints about child-rearing and housework from a mother's point of view, about 40 words each. it is ok if the contents are the same. “my husband has not done any housework at all since he left. i’m tired too, but... can’t you just give me a break?” , “i am constantly frustrated with raising my children. i’m always crying... even though i want to cry too...”, “i am frustrated with my mom's friends at daycare. i always give them gifts and such, but i never receive anything in return. do they have no common sense?” as a result of data augmentation using the above prompt, a variety of synthetic complaints were generated. for example, one post described the difficulty in satisfying every family member's food preferences, stating that preparing meals was exhausting. another synthetic entry mentioned a child’s reluctance to begin homework, causing frequent frustration for the parent. a third example highlighted the burden placed on mothers due to the unequal division of household chores, despite both partners being employed. these generated complaints resemble real-world parenting concerns and were used to augment the training dataset. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 387 3.3. vectorizing method to process the textual data for classification, the posts were converted into numerical representations using the following vectorization methods: (1) bag-of-words the bow method is one of the most useful techniques for representing text data numerically. this approach treats a piece of text as an unordered collection of words, disregarding grammar, syntax, and word order while retaining the frequency of each word's occurrence within the text. each unique word in the dataset forms a feature in the representation, resulting in a high-dimensional, sparse vector for each document. despite its simplicity, bow is effective in capturing the presence or absence of keywords and is widely used in basic text classification and retrieval tasks [12-13]. however, it cannot capture semantic relationships between words or contextual meaning, which can limit its effectiveness in complex natural language processing tasks. (2) doc2vec doc2vec [14] is an advanced text embedding technique that builds on the principles of word2vec, extending the algorithm to represent entire documents rather than individual words. by capturing the context in which words appear and their relative positions within the text, doc2vec creates dense, low-dimensional vector representations that encode semantic information. this method is particularly well-suited for tasks where understanding the overall meaning or sentiment of a document is important, such as classification, clustering, or recommendation systems. unlike bow, doc2vec considers terms’ sequence and co-occurrence patterns of words, allowing it to preserve the structure and meaning of the text more effectively. its ability to generate embeddings that reflect both word-level and document-level semantics makes it a powerful tool for text representation in various machine-learning applications [15]. fig.2 visually represents doc2vec. fig. 2 image of doc2vec (3) sparse composite document vectors scdv [16] combines the strengths of word2vec [17] embeddings and soft clustering techniques to create a hybrid approach for text representation. scdv begins by generating word vectors using word2vec and then applies a soft clustering algorithm, such as gaussian mixture models, to group these vectors into clusters. each word is assigned a probability of belonging to multiple clusters, capturing its polysemous (multi-sense) nature. these clustered word vectors are then aggregated to form sparse and dense document embeddings, allowing for a more nuanced and context-aware representation of text. scdv effectively balances between capturing the global structure of a document and the localized meaning of individual words, making it a robust choice for tasks that require both semantic depth and interpretability. its flexibility and ability to handle multi-sense words provide significant advantages over traditional vectorization methods like bow or even doc2vec in certain contexts [18]. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 388 3.4. classification method in this study, lightgbm [19] was employed as the classification algorithm to differentiate between complaints and noncomplaints in the parenting q&a data. lightgbm is a state-of-the-art supervised learning technique based on gradient boosting, a method that builds an ensemble of decision trees sequentially to minimize prediction errors. lightgbm is known for its high computational efficiency and scalability, capable of handling large datasets and high-dimensional features with ease. its design optimizes both speed and memory usage, making it suitable for handling sparse data, such as that generated by bow or scdv. by leveraging techniques such as histogram-based learning and leaf-wise tree growth, lightgbm achieves superior performance in terms of classification accuracy and model interpretability while maintaining fast training and prediction times. this makes it a highly effective tool for real-world machine-learning tasks where both precision and computational efficiency are critical. in this study, under-sampling was applied to address the class imbalance in the dataset. since complaints accounted for only about 9% of the total data, directly training a classifier could lead to bias toward the majority class (non-complaints). under-sampling reduces the number of non-complaint samples to create a more balanced dataset, ensuring that the classifier pays adequate attention to the minority class. by doing so, the training process became more focused on identifying complaintrelated patterns, ultimately improving the model's ability to distinguish between the two classes effectively. 3.5. plsa plsa [20] is a statistical method for clustering and topic modeling, designed to uncover latent structures in co-occurrence data, such as documents and their associated terms. the method assumes the existence of a shared latent variable z, which represents a probabilistic class that links two observed dimensions: x (e.g., documents) and y (e.g., terms or vector features). in plsa, the joint probability p(x,y)p(x, y)p(x,y) is modeled as a mixture over the latent classes, where each observation is generated by first sampling a latent topic and then drawing a term conditioned on that topic. this approach enables the simultaneous clustering of both documents and terms, capturing the underlying semantic structure of the corpus. the probabilistic formulation of the model is given as follows: ( , ) ( | ) ( | ) ( ) z p x y p x z p y z p z= (1) plsa is particularly well-suited for sparse matrices, making it an excellent choice for feature analysis on bow data. by modeling the co-occurrence relationships between rows and columns, plsa effectively identifies latent topics or patterns within the data. this capability makes it a powerful tool for understanding the underlying structure of complaint-related content in the dataset [21]. 4. result this section describes the results of the data augmentation and the analysis of the complaints extracted based on the data augmentation. specifically, it presents the differences in complaint classification outcomes resulting from data augmentation, as well as the selection of the number of classes using plsa and the types of complaint classes that emerged from this analysis. 4.1. data augmentation in this study, the effect of data augmentation using generative ai was examined by incrementally adding 10% of generated data to the original dataset and performing classification to determine whether a post was a complaint. the performance of the classification was evaluated using the f1 score, which considers the balance between precision and recall. table 2 shows the results of f1 scores, which are the harmonic mean of precision and recall, for each vectorization method when varying the amount of generated complaint data. these results provide insights into the impact of different vectorization advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 389 approaches on the classification performance under augmented data conditions. from this table, it appears that accuracy improves as more generated data is added. among the vectorization methods, doc2vec achieved the highest f1 score, indicating its superior performance in this context. table 2 f1 scores using all data bow doc2vec scdv 0% 0.824 0.824 0.775 10% 0.711 0.836 0.801 20% 0.797 0.865 0.822 30% 0.813 0.865 0.783 40% 0.857 0.867 0.789 50% 0.859 0.869 0.830 on the other hand, table 3 presents the f1 scores calculated using only the original dataset, without any generated data. these results suggest that while adding generated data initially improves the performance metrics, the scores start to decline beyond a certain point. it is observed that bow has the lowest performance metrics compared to doc2vec and scdv, indicating that it is more heavily influenced by the generated complaints. the best performance was observed when 20% of generated complaints were added using doc2vec. based on this model, plsa will be applied to analyze the latent classes within the complaints. table 3 f1 scores without generated data bow doc2vec scdv 0% 0.824 0.824 0.775 10% 0.673 0.828 0.780 20% 0.757 0.840 0.779 30% 0.75 0.833 0.733 40% 0.777 0.809 0.717 50% 0.787 0.824 0.791 4.2. plsa using the previously mentioned model, 10,000 randomly selected unlabeled data entries were classified. as a result, 2,642 entries were identified as complaints. to analyze this data, the number of latent classes was determined by running plsa with class numbers ranging from 2 to 30 while calculating the bayesian information criterion (bic) values [22]. the results are shown in fig. 3. while the bic values decreased continuously as the number of classes increased, the class count was set to 6 based on interpretability and the rate of decline in bic values. bic is given by the following equation: 2ln lnbic l k n= − + (2) ln ( , ) ln ( , ) ( , ) ln ( ) ( | ) ( | )i j k j k i k i j i j k l n i j p x y n i j p z p y z p x z    = =          (3) where l is the likelihood of the model, k is the number of free parameters, and n is the number of observations. the likelihood l measures how well the model explains the observed data, while k represents the degree of model flexibility, and n indicates the data size used for estimation. the bic introduces a penalty term for model complexity, which increases with the number of parameters, to prevent overfitting. lower bic values, therefore, indicate a better balance between model fit and parsimony, meaning that the model both explains the data well and avoids unnecessary complexity. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 390 fig. 3 bic curve as a result of performing plsa with 6 classes, the sizes of the latent classes are summarized in table 4, and the representative words for each class are shown in table 5. from tables 4 and 5, it is evident that a significant portion of the complaints pertain to issues involving husbands and family members. however, it is also noteworthy that terms unrelated to family, such as "hospital" and "new year," appear as representative words in the clustering analysis. these terms highlight additional areas of concern, such as difficulties in securing medical appointments or the stress associated with traditional holiday gatherings. a more detailed discussion of these findings will be provided later. table 4 size of the latent classes class size class1 0.1688 class2 0.1740 class3 0.1908 class4 0.1308 class5 0.1218 class6 0.2136 table 5 representative words class1 class2 class3 class4 class5 class6 time parents' home children schedule today husband work aunt myself childbirth tomorrow son pregnancies family together friends yesterday unreasonable everyday new year divorce contact the new year's holiday usual lives parents quarrel unstable physical condition bath raising children this year household normal hospital room nursery school marriage opponent worry physical condition prepare 5. discussion the results of data augmentation and plsa are discussed, respectively. the discussion first examines the effects of data augmentation using generative ai, highlighting both its benefits in improving classification performance and the challenges it presents, along with an evaluation of which vectorization methods are most suitable based on their representational characteristics. it then considers the complaint classes identified through plsa, describing how complaints on parenting q&a sites were segmented into distinct thematic categories. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 391 5.1. data augmentation using generative ai from tables 2 and 3, it was observed that increasing the proportion of generated complaints improved the performance metrics up to a certain point. however, beyond that point, further increasing the amount of generated data led to a decline in the metrics. the decline in performance when adding too much generated data can be attributed to subtle differences in the characteristics of the generated complaints compared to the original data. although specific examples were provided during the generation process, some of the generated complaints diverged from the themes present in the original dataset. for instance, while the original data did not contain complaints like "my child refuses to do homework," such examples were generated during data augmentation. one notable observation is that the bow method was most affected by the excess generated data. since bow relies on a direct, sparse representation of word frequencies without considering the context or semantics of the words, it is highly sensitive to variations in the dataset. as a result, bow was more prone to overfitting and being influenced by the unique patterns in the generated complaints, leading to a significant decrease in performance metrics. all three methods—bow, doc2vec, and scdv—aim to convert text into numerical vectors so that machine learning models can process them. however, the way they create these vectors differs significantly. bow represents a document by counting the frequency of each word in the text, ignoring grammar, word order, and context. as a result, two sentences with the same words in different orders—such as “the child is crying” and “crying is the child”—would be represented identically in bow. in contrast, doc2vec captures the order and surrounding context of words, producing dense vectors that reflect the semantic meaning of the entire document. scdv further builds on this by combining word embeddings with soft clustering to account for words with multiple meanings. although all these methods perform vectorization, context-aware methods like doc2vec and scdv are better suited for handling subtle differences in sentence structure and meaning. this capability made them less susceptible to performance degradation when synthetic data was introduced, as they could focus on the overall context rather than isolated word occurrences. to address these discrepancies, the following improvements could be considered: (1) providing more specific examples: increasing the number and diversity of examples from the original data during the prompt creation process can help align the generated data more closely with the original dataset's characteristics. (2) summarizing frequent themes: including an overview of the most common types of complaints in the dataset as part of the prompt can guide the generative model to produce data that better reflects the distribution of original themes. 5.2. complaints in parenting q&a sites as a result of the analysis, clustering based on representative words, as shown in table 5, was achieved for the parenting q&a site data. from the representative words in each class, the following characteristics and themes can be inferred: class 1 complaints in class 1 focus on the daily stress and struggles of parents with small children, managing household chores, and childcare. these posts reflect the exhaustion and challenges of maintaining a work-life balance while handling everyday responsibilities. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 392 class2 class 2 represents complaints related to family gatherings, particularly during the new year holidays when people visit their parents' homes. the word “aunt” highlights a common stress point in japanese culture, where tension between mothers and their mothers-in-law often arises. this suggests that meeting extended family members during such events causes emotional strain. class3 class 3 pertains to family and marital issues. the inclusion of words like “husband” and “divorce” indicates that the complaints revolve around conflicts within the household, some of which escalate to discussions about separation or divorce. posts in this class likely detail arguments and the emotional toll of strained family relationships, including the impact on children. class4 class 4 captures anxieties related to the arrival of a new child. the presence of terms like “schedule” and “birth” suggests concerns about planning and preparation for childbirth. as the term “maternity blues” implies, childbirth is a significant life event that often brings emotional challenges for mothers, highlighting their vulnerability during this period. class5 complaints in class 5 focus on health-related anxieties. words referencing dates and “hospital” suggest frustrations about the availability of medical care on desired days. these posts reflect concerns about managing appointments, dealing with illness, and accessing timely healthcare, which are common stressors for parents, especially when caring for children. class6 similar to class 3, class 6 revolves around domestic issues, specifically those involving family dynamics. the mention of “husband” and “son” indicates challenges in managing relationships and roles within the household. the overlap with class 3 suggests that family-related complaints are a dominant theme, possibly reflecting ongoing or recurring issues within domestic life. overall, the clustering results reveal that complaints on parenting q&a sites are not limited to child-rearing itself but are closely tied to a wide range of social and emotional stressors. the dominant presence of themes related to family relationships, such as marital conflict, in-law tensions, and domestic responsibilities, suggests that many users turn to the platform to express frustrations rooted in interpersonal dynamics. furthermore, the appearance of health-related and seasonal concerns, such as hospital access and holiday stress, underscores the influence of temporal and situational factors on parental stress. these findings highlight the complex and multifaceted nature of parenting-related complaints and demonstrate the effectiveness of topic-based clustering in uncovering latent patterns in user-generated content. 6. conclusion this study addressed the classification problem of determining whether a post is a complaint, using data from a parenting q&a site. due to the insufficiency of complaint data, data augmentation was performed using chatgpt. additionally, feature analysis was conducted by applying plsa to the complaints identified by the classification model. advances in technology innovation, vol. 10, no. 4, 2025, pp. 383-394 393 (1) using generative ai to augment data improved classification performance up to a certain point, with the optimal results achieved when 20% of the dataset consisted of generated complaints. this highlights the potential of generative ai in addressing data scarcity, though care must be taken to ensure the generated data closely aligns with the original dataset to avoid performance degradation. 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