id sid tid token lemma pos ajst-29628 1 1 academic academic ADJ ajst-29628 1 2 journal journal NOUN ajst-29628 1 3 of of ADP ajst-29628 1 4 science science NOUN ajst-29628 1 5 and and CCONJ ajst-29628 1 6 technology technology NOUN ajst-29628 1 7 issn issn NOUN ajst-29628 1 8 : : PUNCT ajst-29628 1 9 2771 2771 NUM ajst-29628 1 10 - - SYM ajst-29628 1 11 3032 3032 NUM ajst-29628 1 12 | | NOUN ajst-29628 1 13 vol vol NOUN ajst-29628 1 14 . . PUNCT ajst-29628 2 1 14 14 NUM ajst-29628 2 2 , , PUNCT ajst-29628 2 3 no no INTJ ajst-29628 2 4 . . NOUN ajst-29628 2 5 1 1 NUM ajst-29628 2 6 , , PUNCT ajst-29628 2 7 2025 2025 NUM ajst-29628 2 8 320 320 NUM ajst-29628 2 9 study study NOUN ajst-29628 2 10 on on ADP ajst-29628 2 11 oil oil NOUN ajst-29628 2 12 production production NOUN ajst-29628 2 13 conditions condition NOUN ajst-29628 2 14 recognition recognition NOUN ajst-29628 2 15 based base VERB ajst-29628 2 16 on on ADP ajst-29628 2 17 standard standard ADJ ajst-29628 2 18 error error NOUN ajst-29628 2 19 algorithm algorithm NOUN ajst-29628 2 20 xinhao xinhao PROPN ajst-29628 2 21 yan1 yan1 PROPN ajst-29628 2 22 , , PUNCT ajst-29628 2 23 * * SYM ajst-29628 2 24 1 1 NUM ajst-29628 2 25 school school NOUN ajst-29628 2 26 of of ADP ajst-29628 2 27 mechanical mechanical ADJ ajst-29628 2 28 engineering engineering NOUN ajst-29628 2 29 , , PUNCT ajst-29628 2 30 xi’an xi’an PROPN ajst-29628 2 31 shiyou shiyou PROPN ajst-29628 2 32 university university PROPN ajst-29628 2 33 , , PUNCT ajst-29628 2 34 xi’an xi’an PROPN ajst-29628 2 35 710000 710000 NUM ajst-29628 2 36 , , PUNCT ajst-29628 2 37 china china PROPN ajst-29628 2 38 * * PUNCT ajst-29628 2 39 corresponding correspond VERB ajst-29628 2 40 author author NOUN ajst-29628 2 41 : : PUNCT ajst-29628 2 42 xinhao xinhao PROPN ajst-29628 2 43 yan yan PROPN ajst-29628 3 1 ( ( PUNCT ajst-29628 3 2 email email NOUN ajst-29628 3 3 : : PUNCT ajst-29628 3 4 13137882873@163.com 13137882873@163.com X ajst-29628 3 5 ) ) PUNCT ajst-29628 3 6 abstract abstract NOUN ajst-29628 3 7 : : PUNCT ajst-29628 3 8 the the DET ajst-29628 3 9 dynamometer dynamometer NOUN ajst-29628 3 10 card card NOUN ajst-29628 3 11 contains contain VERB ajst-29628 3 12 plenty plenty NOUN ajst-29628 3 13 of of ADP ajst-29628 3 14 information information NOUN ajst-29628 3 15 features feature NOUN ajst-29628 3 16 of of ADP ajst-29628 3 17 equipment equipment NOUN ajst-29628 3 18 status status NOUN ajst-29628 3 19 , , PUNCT ajst-29628 3 20 technology technology NOUN ajst-29628 3 21 , , PUNCT ajst-29628 3 22 and and CCONJ ajst-29628 3 23 conditions condition NOUN ajst-29628 3 24 in in ADP ajst-29628 3 25 oil oil NOUN ajst-29628 3 26 production production NOUN ajst-29628 3 27 . . PUNCT ajst-29628 4 1 it it PRON ajst-29628 4 2 is be AUX ajst-29628 4 3 of of ADP ajst-29628 4 4 great great ADJ ajst-29628 4 5 significance significance NOUN ajst-29628 4 6 to to PART ajst-29628 4 7 identify identify VERB ajst-29628 4 8 such such ADJ ajst-29628 4 9 important important ADJ ajst-29628 4 10 information information NOUN ajst-29628 4 11 accurately accurately ADV ajst-29628 4 12 , , PUNCT ajst-29628 4 13 rapidly rapidly ADV ajst-29628 4 14 , , PUNCT ajst-29628 4 15 and and CCONJ ajst-29628 4 16 conveniently conveniently ADV ajst-29628 4 17 for for ADP ajst-29628 4 18 safe safe ADJ ajst-29628 4 19 and and CCONJ ajst-29628 4 20 reliable reliable ADJ ajst-29628 4 21 operation operation NOUN ajst-29628 4 22 of of ADP ajst-29628 4 23 the the DET ajst-29628 4 24 pumping pump VERB ajst-29628 4 25 unit unit NOUN ajst-29628 4 26 , , PUNCT ajst-29628 4 27 improving improve VERB ajst-29628 4 28 oil oil NOUN ajst-29628 4 29 production production NOUN ajst-29628 4 30 technology technology NOUN ajst-29628 4 31 , , PUNCT ajst-29628 4 32 and and CCONJ ajst-29628 4 33 real real ADJ ajst-29628 4 34 - - PUNCT ajst-29628 4 35 time time NOUN ajst-29628 4 36 monitoring monitoring NOUN ajst-29628 4 37 of of ADP ajst-29628 4 38 oil oil NOUN ajst-29628 4 39 production production NOUN ajst-29628 4 40 performance performance NOUN ajst-29628 4 41 . . PUNCT ajst-29628 5 1 a a DET ajst-29628 5 2 new new ADJ ajst-29628 5 3 method method NOUN ajst-29628 5 4 was be AUX ajst-29628 5 5 presented present VERB ajst-29628 5 6 to to PART ajst-29628 5 7 recognize recognize VERB ajst-29628 5 8 oil oil NOUN ajst-29628 5 9 production production NOUN ajst-29628 5 10 equipment equipment NOUN ajst-29628 5 11 conditions condition NOUN ajst-29628 5 12 based base VERB ajst-29628 5 13 on on ADP ajst-29628 5 14 a a DET ajst-29628 5 15 standard standard ADJ ajst-29628 5 16 error error NOUN ajst-29628 5 17 algorithm algorithm NOUN ajst-29628 5 18 and and CCONJ ajst-29628 5 19 also also ADV ajst-29628 5 20 develop develop VERB ajst-29628 5 21 a a DET ajst-29628 5 22 mathematical mathematical ADJ ajst-29628 5 23 model model NOUN ajst-29628 5 24 of of ADP ajst-29628 5 25 a a DET ajst-29628 5 26 standard standard ADJ ajst-29628 5 27 error error NOUN ajst-29628 5 28 matching matching NOUN ajst-29628 5 29 algorithm algorithm NOUN ajst-29628 5 30 . . PUNCT ajst-29628 6 1 an an DET ajst-29628 6 2 argument argument NOUN ajst-29628 6 3 about about ADP ajst-29628 6 4 matching match VERB ajst-29628 6 5 algorithms algorithm NOUN ajst-29628 6 6 correlating correlate VERB ajst-29628 6 7 to to ADP ajst-29628 6 8 the the DET ajst-29628 6 9 degree degree NOUN ajst-29628 6 10 of of ADP ajst-29628 6 11 difference difference NOUN ajst-29628 6 12 between between ADP ajst-29628 6 13 graphics graphic NOUN ajst-29628 6 14 is be AUX ajst-29628 6 15 first first ADV ajst-29628 6 16 proposed propose VERB ajst-29628 6 17 . . PUNCT ajst-29628 7 1 the the DET ajst-29628 7 2 reliability reliability NOUN ajst-29628 7 3 of of ADP ajst-29628 7 4 the the DET ajst-29628 7 5 standard standard ADJ ajst-29628 7 6 error error NOUN ajst-29628 7 7 matching matching NOUN ajst-29628 7 8 algorithm algorithm NOUN ajst-29628 7 9 and and CCONJ ajst-29628 7 10 classic classic ADJ ajst-29628 7 11 matching matching NOUN ajst-29628 7 12 algorithm algorithm NOUN ajst-29628 7 13 are be AUX ajst-29628 7 14 compared compare VERB ajst-29628 7 15 in in ADP ajst-29628 7 16 detail detail NOUN ajst-29628 7 17 . . PUNCT ajst-29628 8 1 an an DET ajst-29628 8 2 intensive intensive ADJ ajst-29628 8 3 study study NOUN ajst-29628 8 4 shows show VERB ajst-29628 8 5 that that SCONJ ajst-29628 8 6 the the DET ajst-29628 8 7 standard standard ADJ ajst-29628 8 8 error error NOUN ajst-29628 8 9 matching matching NOUN ajst-29628 8 10 algorithm algorithm NOUN ajst-29628 8 11 highly highly ADV ajst-29628 8 12 correlates correlate VERB ajst-29628 8 13 to to ADP ajst-29628 8 14 the the DET ajst-29628 8 15 degree degree NOUN ajst-29628 8 16 of of ADP ajst-29628 8 17 difference difference NOUN ajst-29628 8 18 between between ADP ajst-29628 8 19 graphics graphic NOUN ajst-29628 8 20 , , PUNCT ajst-29628 8 21 and and CCONJ ajst-29628 8 22 the the DET ajst-29628 8 23 reliability reliability NOUN ajst-29628 8 24 of of ADP ajst-29628 8 25 the the DET ajst-29628 8 26 standard standard ADJ ajst-29628 8 27 error error NOUN ajst-29628 8 28 algorithm algorithm NOUN ajst-29628 8 29 is be AUX ajst-29628 8 30 better well ADJ ajst-29628 8 31 than than ADP ajst-29628 8 32 that that PRON ajst-29628 8 33 of of ADP ajst-29628 8 34 the the DET ajst-29628 8 35 classical classical ADJ ajst-29628 8 36 matching matching NOUN ajst-29628 8 37 algorithms algorithm NOUN ajst-29628 8 38 . . PUNCT ajst-29628 9 1 a a DET ajst-29628 9 2 large large ADJ ajst-29628 9 3 number number NOUN ajst-29628 9 4 of of ADP ajst-29628 9 5 dynamometer dynamometer NOUN ajst-29628 9 6 card card NOUN ajst-29628 9 7 recognitions recognition NOUN ajst-29628 9 8 have have AUX ajst-29628 9 9 shown show VERB ajst-29628 9 10 that that SCONJ ajst-29628 9 11 standard standard ADJ ajst-29628 9 12 errormatching errormatching NOUN ajst-29628 9 13 algorithm algorithm NOUN ajst-29628 9 14 has have VERB ajst-29628 9 15 a a DET ajst-29628 9 16 fairly fairly ADV ajst-29628 9 17 high high ADJ ajst-29628 9 18 reliability reliability NOUN ajst-29628 9 19 . . PUNCT ajst-29628 10 1 furthermore furthermore ADV ajst-29628 10 2 , , PUNCT ajst-29628 10 3 this this DET ajst-29628 10 4 algorithm algorithm NOUN ajst-29628 10 5 has have VERB ajst-29628 10 6 terrific terrific ADJ ajst-29628 10 7 recognition recognition NOUN ajst-29628 10 8 accuracy accuracy NOUN ajst-29628 10 9 especially especially ADV ajst-29628 10 10 to to ADP ajst-29628 10 11 those those DET ajst-29628 10 12 dynamometer dynamometer NOUN ajst-29628 10 13 cards card NOUN ajst-29628 10 14 with with ADP ajst-29628 10 15 minute minute ADJ ajst-29628 10 16 differences difference NOUN ajst-29628 10 17 . . PUNCT ajst-29628 11 1 keywords keyword NOUN ajst-29628 11 2 : : PUNCT ajst-29628 11 3 standard standard ADJ ajst-29628 11 4 error error NOUN ajst-29628 11 5 ; ; PUNCT ajst-29628 11 6 oil oil NOUN ajst-29628 11 7 production production NOUN ajst-29628 11 8 conditions condition NOUN ajst-29628 11 9 ; ; PUNCT ajst-29628 11 10 dynamometer dynamometer NOUN ajst-29628 11 11 cards card NOUN ajst-29628 11 12 ; ; PUNCT ajst-29628 11 13 recognition recognition NOUN ajst-29628 11 14 technique technique NOUN ajst-29628 11 15 . . PUNCT ajst-29628 12 1 1 1 X ajst-29628 12 2 . . X ajst-29628 12 3 introduction introduction NOUN ajst-29628 12 4 at at ADP ajst-29628 12 5 present present ADJ ajst-29628 12 6 , , PUNCT ajst-29628 12 7 indicator indicator NOUN ajst-29628 12 8 diagram diagram NOUN ajst-29628 12 9 diagnosis diagnosis NOUN ajst-29628 12 10 and and CCONJ ajst-29628 12 11 identification identification NOUN ajst-29628 12 12 technology technology NOUN ajst-29628 12 13 has have AUX ajst-29628 12 14 been be AUX ajst-29628 12 15 developed develop VERB ajst-29628 12 16 rapidly rapidly ADV ajst-29628 12 17 in in ADP ajst-29628 12 18 china china PROPN ajst-29628 12 19 and and CCONJ ajst-29628 12 20 has have AUX ajst-29628 12 21 become become VERB ajst-29628 12 22 the the DET ajst-29628 12 23 most most ADV ajst-29628 12 24 important important ADJ ajst-29628 12 25 practical practical ADJ ajst-29628 12 26 tool tool NOUN ajst-29628 12 27 for for ADP ajst-29628 12 28 oil oil NOUN ajst-29628 12 29 well well NOUN ajst-29628 12 30 condition condition NOUN ajst-29628 12 31 diagnosis diagnosis NOUN ajst-29628 12 32 . . PUNCT ajst-29628 13 1 china china PROPN ajst-29628 13 2 currently currently ADV ajst-29628 13 3 has have VERB ajst-29628 13 4 hundreds hundred NOUN ajst-29628 13 5 of of ADP ajst-29628 13 6 thousands thousand NOUN ajst-29628 13 7 of of ADP ajst-29628 13 8 pumping pump VERB ajst-29628 13 9 wells well NOUN ajst-29628 13 10 . . PUNCT ajst-29628 14 1 in in ADP ajst-29628 14 2 recent recent ADJ ajst-29628 14 3 years year NOUN ajst-29628 14 4 , , PUNCT ajst-29628 14 5 the the DET ajst-29628 14 6 oilfield oilfield NOUN ajst-29628 14 7 has have AUX ajst-29628 14 8 been be AUX ajst-29628 14 9 committed commit VERB ajst-29628 14 10 to to ADP ajst-29628 14 11 the the DET ajst-29628 14 12 research research NOUN ajst-29628 14 13 of of ADP ajst-29628 14 14 oil oil NOUN ajst-29628 14 15 well well NOUN ajst-29628 14 16 condition condition NOUN ajst-29628 14 17 diagnosis diagnosis NOUN ajst-29628 14 18 technology technology NOUN ajst-29628 14 19 . . PUNCT ajst-29628 15 1 because because SCONJ ajst-29628 15 2 the the DET ajst-29628 15 3 indicator indicator NOUN ajst-29628 15 4 diagram diagram NOUN ajst-29628 15 5 contains contain VERB ajst-29628 15 6 multidimensional multidimensional ADJ ajst-29628 15 7 information information NOUN ajst-29628 15 8 characteristics characteristic NOUN ajst-29628 15 9 of of ADP ajst-29628 15 10 oil oil NOUN ajst-29628 15 11 production production NOUN ajst-29628 15 12 conditions condition NOUN ajst-29628 15 13 , , PUNCT ajst-29628 15 14 the the DET ajst-29628 15 15 establishment establishment NOUN ajst-29628 15 16 of of ADP ajst-29628 15 17 a a DET ajst-29628 15 18 sample sample NOUN ajst-29628 15 19 indicator indicator NOUN ajst-29628 15 20 diagram diagram NOUN ajst-29628 15 21 database database NOUN ajst-29628 15 22 of of ADP ajst-29628 15 23 oil oil NOUN ajst-29628 15 24 well well NOUN ajst-29628 15 25 conditions condition NOUN ajst-29628 15 26 is be AUX ajst-29628 15 27 the the DET ajst-29628 15 28 basis basis NOUN ajst-29628 15 29 of of ADP ajst-29628 15 30 oil oil NOUN ajst-29628 15 31 well well NOUN ajst-29628 15 32 conditions condition NOUN ajst-29628 15 33 diagnosis diagnosis NOUN ajst-29628 15 34 technology technology NOUN ajst-29628 15 35 . . PUNCT ajst-29628 16 1 through through ADP ajst-29628 16 2 the the DET ajst-29628 16 3 realtime realtime ADJ ajst-29628 16 4 acquisition acquisition NOUN ajst-29628 16 5 of of ADP ajst-29628 16 6 the the DET ajst-29628 16 7 pumping pump VERB ajst-29628 16 8 unit unit NOUN ajst-29628 16 9 indicator indicator NOUN ajst-29628 16 10 diagram diagram PROPN ajst-29628 16 11 , , PUNCT ajst-29628 16 12 and and CCONJ ajst-29628 16 13 the the DET ajst-29628 16 14 comparison comparison NOUN ajst-29628 16 15 and and CCONJ ajst-29628 16 16 identification identification NOUN ajst-29628 16 17 with with ADP ajst-29628 16 18 the the DET ajst-29628 16 19 sample sample NOUN ajst-29628 16 20 database database NOUN ajst-29628 16 21 , , PUNCT ajst-29628 16 22 the the DET ajst-29628 16 23 working work VERB ajst-29628 16 24 condition condition NOUN ajst-29628 16 25 of of ADP ajst-29628 16 26 the the DET ajst-29628 16 27 oil oil NOUN ajst-29628 16 28 production production NOUN ajst-29628 16 29 system system NOUN ajst-29628 16 30 is be AUX ajst-29628 16 31 determined determine VERB ajst-29628 16 32 , , PUNCT ajst-29628 16 33 to to PART ajst-29628 16 34 realize realize VERB ajst-29628 16 35 the the DET ajst-29628 16 36 real real ADJ ajst-29628 16 37 - - PUNCT ajst-29628 16 38 time time NOUN ajst-29628 16 39 monitoring monitoring NOUN ajst-29628 16 40 and and CCONJ ajst-29628 16 41 production production NOUN ajst-29628 16 42 guidance guidance NOUN ajst-29628 16 43 of of ADP ajst-29628 16 44 the the DET ajst-29628 16 45 oil oil NOUN ajst-29628 16 46 well well NOUN ajst-29628 16 47 working working NOUN ajst-29628 16 48 condition condition NOUN ajst-29628 16 49 . . PUNCT ajst-29628 17 1 the the DET ajst-29628 17 2 key key NOUN ajst-29628 17 3 to to ADP ajst-29628 17 4 oil oil NOUN ajst-29628 17 5 well well NOUN ajst-29628 17 6 condition condition NOUN ajst-29628 17 7 diagnosis diagnosis NOUN ajst-29628 17 8 is be AUX ajst-29628 17 9 the the DET ajst-29628 17 10 accurate accurate ADJ ajst-29628 17 11 identification identification NOUN ajst-29628 17 12 of of ADP ajst-29628 17 13 indicator indicator NOUN ajst-29628 17 14 diagrams diagram NOUN ajst-29628 17 15 . . PUNCT ajst-29628 18 1 at at ADP ajst-29628 18 2 present present ADJ ajst-29628 18 3 , , PUNCT ajst-29628 18 4 the the DET ajst-29628 18 5 main main ADJ ajst-29628 18 6 methods method NOUN ajst-29628 18 7 used use VERB ajst-29628 18 8 in in ADP ajst-29628 18 9 indicator indicator NOUN ajst-29628 18 10 diagram diagram NOUN ajst-29628 18 11 recognition recognition NOUN ajst-29628 18 12 are be AUX ajst-29628 18 13 the the DET ajst-29628 18 14 grid grid NOUN ajst-29628 18 15 method method NOUN ajst-29628 18 16 , , PUNCT ajst-29628 18 17 gray gray ADJ ajst-29628 18 18 matrix matrix NOUN ajst-29628 18 19 method method NOUN ajst-29628 18 20 , , PUNCT ajst-29628 18 21 vector vector NOUN ajst-29628 18 22 method method NOUN ajst-29628 18 23 , , PUNCT ajst-29628 18 24 artificial artificial ADJ ajst-29628 18 25 neural neural ADJ ajst-29628 18 26 network network NOUN ajst-29628 18 27 method method NOUN ajst-29628 18 28 , , PUNCT ajst-29628 18 29 etc etc X ajst-29628 18 30 . . X ajst-29628 19 1 the the DET ajst-29628 19 2 core core NOUN ajst-29628 19 3 of of ADP ajst-29628 19 4 the the DET ajst-29628 19 5 above above ADJ ajst-29628 19 6 method method NOUN ajst-29628 19 7 is be AUX ajst-29628 19 8 feature feature NOUN ajst-29628 19 9 extraction extraction NOUN ajst-29628 19 10 , , PUNCT ajst-29628 19 11 which which PRON ajst-29628 19 12 is be AUX ajst-29628 19 13 to to PART ajst-29628 19 14 extract extract VERB ajst-29628 19 15 the the DET ajst-29628 19 16 relevant relevant ADJ ajst-29628 19 17 feature feature NOUN ajst-29628 19 18 information information NOUN ajst-29628 19 19 from from ADP ajst-29628 19 20 the the DET ajst-29628 19 21 two two NUM ajst-29628 19 22 - - PUNCT ajst-29628 19 23 dimensional dimensional ADJ ajst-29628 19 24 array array NOUN ajst-29628 19 25 of of ADP ajst-29628 19 26 indicator indicator NOUN ajst-29628 19 27 diagrams diagram NOUN ajst-29628 19 28 of of ADP ajst-29628 19 29 different different ADJ ajst-29628 19 30 scenes scene NOUN ajst-29628 19 31 and and CCONJ ajst-29628 19 32 eliminate eliminate VERB ajst-29628 19 33 the the DET ajst-29628 19 34 irrelevant irrelevant ADJ ajst-29628 19 35 information information NOUN ajst-29628 19 36 . . PUNCT ajst-29628 20 1 the the DET ajst-29628 20 2 second second NOUN ajst-29628 20 3 is be AUX ajst-29628 20 4 to to PART ajst-29628 20 5 establish establish VERB ajst-29628 20 6 a a DET ajst-29628 20 7 classifier classifier NOUN ajst-29628 20 8 , , PUNCT ajst-29628 20 9 which which PRON ajst-29628 20 10 is be AUX ajst-29628 20 11 a a DET ajst-29628 20 12 kind kind NOUN ajst-29628 20 13 of of ADP ajst-29628 20 14 matching match VERB ajst-29628 20 15 algorithm algorithm NOUN ajst-29628 20 16 to to PART ajst-29628 20 17 identify identify VERB ajst-29628 20 18 the the DET ajst-29628 20 19 working working NOUN ajst-29628 20 20 conditions condition NOUN ajst-29628 20 21 . . PUNCT ajst-29628 21 1 the the DET ajst-29628 21 2 key key NOUN ajst-29628 21 3 to to ADP ajst-29628 21 4 indicator indicator PROPN ajst-29628 21 5 diagram diagram NOUN ajst-29628 21 6 recognition recognition NOUN ajst-29628 21 7 is be AUX ajst-29628 21 8 how how SCONJ ajst-29628 21 9 to to PART ajst-29628 21 10 extract extract VERB ajst-29628 21 11 its its PRON ajst-29628 21 12 most most ADV ajst-29628 21 13 representative representative ADJ ajst-29628 21 14 features feature NOUN ajst-29628 21 15 and and CCONJ ajst-29628 21 16 what what DET ajst-29628 21 17 kind kind NOUN ajst-29628 21 18 of of ADP ajst-29628 21 19 classifier classifier NOUN ajst-29628 21 20 to to PART ajst-29628 21 21 use use VERB ajst-29628 21 22 for for ADP ajst-29628 21 23 type type NOUN ajst-29628 21 24 recognition recognition NOUN ajst-29628 21 25 . . PUNCT ajst-29628 22 1 both both CCONJ ajst-29628 22 2 the the DET ajst-29628 22 3 grid grid NOUN ajst-29628 22 4 method method NOUN ajst-29628 22 5 and and CCONJ ajst-29628 22 6 gray gray ADJ ajst-29628 22 7 matrix matrix NOUN ajst-29628 22 8 extract extract VERB ajst-29628 22 9 the the DET ajst-29628 22 10 information information NOUN ajst-29628 22 11 of of ADP ajst-29628 22 12 the the DET ajst-29628 22 13 indicator indicator NOUN ajst-29628 22 14 diagram diagram NOUN ajst-29628 22 15 boundary boundary ADV ajst-29628 22 16 through through ADP ajst-29628 22 17 the the DET ajst-29628 22 18 characteristic characteristic ADJ ajst-29628 22 19 matrix matrix NOUN ajst-29628 22 20 , , PUNCT ajst-29628 22 21 which which PRON ajst-29628 22 22 is be AUX ajst-29628 22 23 either either CCONJ ajst-29628 22 24 true true ADJ ajst-29628 22 25 ( ( PUNCT ajst-29628 22 26 1 1 NUM ajst-29628 22 27 ) ) PUNCT ajst-29628 22 28 or or CCONJ ajst-29628 22 29 false false ADJ ajst-29628 22 30 ( ( PUNCT ajst-29628 22 31 0 0 NUM ajst-29628 22 32 ) ) PUNCT ajst-29628 23 1 [ [ X ajst-29628 23 2 1 1 NUM ajst-29628 23 3 , , PUNCT ajst-29628 23 4 2 2 NUM ajst-29628 23 5 ] ] PUNCT ajst-29628 23 6 . . PUNCT ajst-29628 24 1 due due ADP ajst-29628 24 2 to to ADP ajst-29628 24 3 the the DET ajst-29628 24 4 fluctuation fluctuation NOUN ajst-29628 24 5 of of ADP ajst-29628 24 6 the the DET ajst-29628 24 7 contour contour NOUN ajst-29628 24 8 line line NOUN ajst-29628 24 9 of of ADP ajst-29628 24 10 the the DET ajst-29628 24 11 indicator indicator NOUN ajst-29628 24 12 diagram diagram NOUN ajst-29628 24 13 , , PUNCT ajst-29628 24 14 there there PRON ajst-29628 24 15 is be VERB ajst-29628 24 16 a a DET ajst-29628 24 17 possibility possibility NOUN ajst-29628 24 18 that that SCONJ ajst-29628 24 19 different different ADJ ajst-29628 24 20 curves curve NOUN ajst-29628 24 21 will will AUX ajst-29628 24 22 have have AUX ajst-29628 24 23 great great ADJ ajst-29628 24 24 differences difference NOUN ajst-29628 24 25 when when SCONJ ajst-29628 24 26 passing pass VERB ajst-29628 24 27 through through ADP ajst-29628 24 28 the the DET ajst-29628 24 29 same same ADJ ajst-29628 24 30 grid grid NOUN ajst-29628 24 31 point point NOUN ajst-29628 24 32 . . PUNCT ajst-29628 25 1 as as SCONJ ajst-29628 25 2 shown show VERB ajst-29628 25 3 in in ADP ajst-29628 25 4 fig fig NOUN ajst-29628 25 5 . . PUNCT ajst-29628 26 1 1 1 NUM ajst-29628 26 2 ( ( PUNCT ajst-29628 26 3 a a NOUN ajst-29628 26 4 ) ) PUNCT ajst-29628 26 5 and and CCONJ ajst-29628 26 6 ( ( PUNCT ajst-29628 26 7 b b NOUN ajst-29628 26 8 ) ) PUNCT ajst-29628 26 9 , , PUNCT ajst-29628 26 10 both both PRON ajst-29628 26 11 a a PRON ajst-29628 26 12 and and CCONJ ajst-29628 26 13 b b NOUN ajst-29628 26 14 curves curve NOUN ajst-29628 26 15 pass pass VERB ajst-29628 26 16 through through ADP ajst-29628 26 17 the the DET ajst-29628 26 18 same same ADJ ajst-29628 26 19 grid grid NOUN ajst-29628 26 20 , , PUNCT ajst-29628 26 21 and and CCONJ ajst-29628 26 22 the the DET ajst-29628 26 23 value value NOUN ajst-29628 26 24 is be AUX ajst-29628 26 25 1 1 NUM ajst-29628 26 26 . . PUNCT ajst-29628 27 1 however however ADV ajst-29628 27 2 , , PUNCT ajst-29628 27 3 the the DET ajst-29628 27 4 local local ADJ ajst-29628 27 5 difference difference NOUN ajst-29628 27 6 between between ADP ajst-29628 27 7 a a DET ajst-29628 27 8 curve curve NOUN ajst-29628 27 9 and and CCONJ ajst-29628 27 10 a a DET ajst-29628 27 11 b b NOUN ajst-29628 27 12 curve curve NOUN ajst-29628 27 13 is be AUX ajst-29628 27 14 very very ADV ajst-29628 27 15 large large ADJ ajst-29628 27 16 , , PUNCT ajst-29628 27 17 so so ADV ajst-29628 27 18 the the DET ajst-29628 27 19 extracted extract VERB ajst-29628 27 20 feature feature NOUN ajst-29628 27 21 matrix matrix NOUN ajst-29628 27 22 can can AUX ajst-29628 27 23 not not PART ajst-29628 27 24 accurately accurately ADV ajst-29628 27 25 reflect reflect VERB ajst-29628 27 26 the the DET ajst-29628 27 27 local local ADJ ajst-29628 27 28 features feature NOUN ajst-29628 27 29 of of ADP ajst-29628 27 30 the the DET ajst-29628 27 31 indicator indicator NOUN ajst-29628 27 32 diagram diagram NOUN ajst-29628 27 33 . . PUNCT ajst-29628 28 1 even even ADV ajst-29628 28 2 if if SCONJ ajst-29628 28 3 the the DET ajst-29628 28 4 classifier classifier NOUN ajst-29628 28 5 algorithm algorithm NOUN ajst-29628 28 6 is be AUX ajst-29628 28 7 very very ADV ajst-29628 28 8 accurate accurate ADJ ajst-29628 28 9 , , PUNCT ajst-29628 28 10 it it PRON ajst-29628 28 11 is be AUX ajst-29628 28 12 still still ADV ajst-29628 28 13 inaccurate inaccurate ADJ ajst-29628 28 14 . . PUNCT ajst-29628 29 1 the the DET ajst-29628 29 2 artificial artificial ADJ ajst-29628 29 3 neural neural ADJ ajst-29628 29 4 network network NOUN ajst-29628 29 5 method method NOUN ajst-29628 29 6 [ [ X ajst-29628 29 7 3 3 NUM ajst-29628 29 8 - - SYM ajst-29628 29 9 5 5 NUM ajst-29628 29 10 ] ] PUNCT ajst-29628 29 11 is be AUX ajst-29628 29 12 also also ADV ajst-29628 29 13 based base VERB ajst-29628 29 14 on on ADP ajst-29628 29 15 the the DET ajst-29628 29 16 grid grid NOUN ajst-29628 29 17 method method NOUN ajst-29628 29 18 and and CCONJ ajst-29628 29 19 gray gray ADJ ajst-29628 29 20 matrix matrix NOUN ajst-29628 29 21 to to PART ajst-29628 29 22 extract extract VERB ajst-29628 29 23 feature feature NOUN ajst-29628 29 24 information information NOUN ajst-29628 29 25 , , PUNCT ajst-29628 29 26 so so CCONJ ajst-29628 29 27 it it PRON ajst-29628 29 28 still still ADV ajst-29628 29 29 has have VERB ajst-29628 29 30 the the DET ajst-29628 29 31 defects defect NOUN ajst-29628 29 32 of of ADP ajst-29628 29 33 the the DET ajst-29628 29 34 grid grid NOUN ajst-29628 29 35 method method NOUN ajst-29628 29 36 and and CCONJ ajst-29628 29 37 gray gray ADJ ajst-29628 29 38 matrix matrix NOUN ajst-29628 29 39 . . PUNCT ajst-29628 30 1 these these DET ajst-29628 30 2 three three NUM ajst-29628 30 3 methods method NOUN ajst-29628 30 4 belong belong VERB ajst-29628 30 5 to to ADP ajst-29628 30 6 feature feature NOUN ajst-29628 30 7 recognition recognition NOUN ajst-29628 30 8 , , PUNCT ajst-29628 30 9 they they PRON ajst-29628 30 10 are be AUX ajst-29628 30 11 only only ADV ajst-29628 30 12 applicable applicable ADJ ajst-29628 30 13 to to ADP ajst-29628 30 14 the the DET ajst-29628 30 15 classification classification NOUN ajst-29628 30 16 and and CCONJ ajst-29628 30 17 recognition recognition NOUN ajst-29628 30 18 of of ADP ajst-29628 30 19 graphics graphic NOUN ajst-29628 30 20 , , PUNCT ajst-29628 30 21 and and CCONJ ajst-29628 30 22 can can AUX ajst-29628 30 23 not not PART ajst-29628 30 24 realize realize VERB ajst-29628 30 25 the the DET ajst-29628 30 26 accurate accurate ADJ ajst-29628 30 27 recognition recognition NOUN ajst-29628 30 28 of of ADP ajst-29628 30 29 graphics graphic NOUN ajst-29628 30 30 . . PUNCT ajst-29628 31 1 the the DET ajst-29628 31 2 vector vector NOUN ajst-29628 31 3 method method NOUN ajst-29628 31 4 belongs belong VERB ajst-29628 31 5 to to ADP ajst-29628 31 6 pattern pattern NOUN ajst-29628 31 7 recognition recognition NOUN ajst-29628 31 8 , , PUNCT ajst-29628 31 9 its its PRON ajst-29628 31 10 characteristic characteristic ADJ ajst-29628 31 11 matrix matrix NOUN ajst-29628 31 12 is be AUX ajst-29628 31 13 the the DET ajst-29628 31 14 quotient quotient NOUN ajst-29628 31 15 of of ADP ajst-29628 31 16 matrix matrix NOUN ajst-29628 31 17 elements element NOUN ajst-29628 31 18 and and CCONJ ajst-29628 31 19 matrix matrix NOUN ajst-29628 31 20 modulus modulus NOUN ajst-29628 31 21 , , PUNCT ajst-29628 31 22 and and CCONJ ajst-29628 31 23 its its PRON ajst-29628 31 24 matching matching NOUN ajst-29628 31 25 value value NOUN ajst-29628 31 26 is be AUX ajst-29628 31 27 the the DET ajst-29628 31 28 cosine cosine ADJ ajst-29628 31 29 value value NOUN ajst-29628 31 30 of of ADP ajst-29628 31 31 the the DET ajst-29628 31 32 vector vector NOUN ajst-29628 31 33 angle angle NOUN ajst-29628 31 34 . . PUNCT ajst-29628 32 1 both both CCONJ ajst-29628 32 2 the the DET ajst-29628 32 3 grid grid NOUN ajst-29628 32 4 method method NOUN ajst-29628 32 5 and and CCONJ ajst-29628 32 6 gray gray ADJ ajst-29628 32 7 matrix matrix NOUN ajst-29628 32 8 extract extract VERB ajst-29628 32 9 the the DET ajst-29628 32 10 information information NOUN ajst-29628 32 11 of of ADP ajst-29628 32 12 the the DET ajst-29628 32 13 indicator indicator NOUN ajst-29628 32 14 diagram diagram NOUN ajst-29628 32 15 boundary boundary ADV ajst-29628 32 16 through through ADP ajst-29628 32 17 the the DET ajst-29628 32 18 characteristic characteristic ADJ ajst-29628 32 19 matrix matrix NOUN ajst-29628 32 20 , , PUNCT ajst-29628 32 21 which which PRON ajst-29628 32 22 is be AUX ajst-29628 32 23 either either CCONJ ajst-29628 32 24 true true ADJ ajst-29628 32 25 ( ( PUNCT ajst-29628 32 26 1 1 NUM ajst-29628 32 27 ) ) PUNCT ajst-29628 32 28 or or CCONJ ajst-29628 32 29 false false ADJ ajst-29628 32 30 ( ( PUNCT ajst-29628 32 31 0 0 NUM ajst-29628 32 32 ) ) PUNCT ajst-29628 33 1 [ [ X ajst-29628 33 2 1 1 NUM ajst-29628 33 3 , , PUNCT ajst-29628 33 4 2 2 NUM ajst-29628 33 5 ] ] PUNCT ajst-29628 33 6 . . PUNCT ajst-29628 34 1 due due ADP ajst-29628 34 2 to to ADP ajst-29628 34 3 the the DET ajst-29628 34 4 fluctuation fluctuation NOUN ajst-29628 34 5 of of ADP ajst-29628 34 6 the the DET ajst-29628 34 7 contour contour NOUN ajst-29628 34 8 line line NOUN ajst-29628 34 9 of of ADP ajst-29628 34 10 the the DET ajst-29628 34 11 indicator indicator NOUN ajst-29628 34 12 diagram diagram NOUN ajst-29628 34 13 , , PUNCT ajst-29628 34 14 there there PRON ajst-29628 34 15 is be VERB ajst-29628 34 16 a a DET ajst-29628 34 17 possibility possibility NOUN ajst-29628 34 18 that that SCONJ ajst-29628 34 19 different different ADJ ajst-29628 34 20 curves curve NOUN ajst-29628 34 21 will will AUX ajst-29628 34 22 have have AUX ajst-29628 34 23 great great ADJ ajst-29628 34 24 differences difference NOUN ajst-29628 34 25 when when SCONJ ajst-29628 34 26 passing pass VERB ajst-29628 34 27 through through ADP ajst-29628 34 28 the the DET ajst-29628 34 29 same same ADJ ajst-29628 34 30 grid grid NOUN ajst-29628 34 31 point point NOUN ajst-29628 34 32 . . PUNCT ajst-29628 35 1 as as SCONJ ajst-29628 35 2 shown show VERB ajst-29628 35 3 in in ADP ajst-29628 35 4 fig fig NOUN ajst-29628 35 5 . . PUNCT ajst-29628 36 1 1 1 NUM ajst-29628 36 2 ( ( PUNCT ajst-29628 36 3 a a NOUN ajst-29628 36 4 ) ) PUNCT ajst-29628 36 5 and and CCONJ ajst-29628 36 6 ( ( PUNCT ajst-29628 36 7 b b NOUN ajst-29628 36 8 ) ) PUNCT ajst-29628 36 9 , , PUNCT ajst-29628 36 10 both both PRON ajst-29628 36 11 a a PRON ajst-29628 36 12 and and CCONJ ajst-29628 36 13 b b NOUN ajst-29628 36 14 curves curve NOUN ajst-29628 36 15 pass pass VERB ajst-29628 36 16 through through ADP ajst-29628 36 17 the the DET ajst-29628 36 18 same same ADJ ajst-29628 36 19 grid grid NOUN ajst-29628 36 20 , , PUNCT ajst-29628 36 21 and and CCONJ ajst-29628 36 22 the the DET ajst-29628 36 23 value value NOUN ajst-29628 36 24 is be AUX ajst-29628 36 25 1 1 NUM ajst-29628 36 26 . . PUNCT ajst-29628 37 1 however however ADV ajst-29628 37 2 , , PUNCT ajst-29628 37 3 the the DET ajst-29628 37 4 local local ADJ ajst-29628 37 5 difference difference NOUN ajst-29628 37 6 between between ADP ajst-29628 37 7 the the DET ajst-29628 37 8 a a DET ajst-29628 37 9 curve curve NOUN ajst-29628 37 10 and and CCONJ ajst-29628 37 11 the the DET ajst-29628 37 12 b b PROPN ajst-29628 37 13 curve curve NOUN ajst-29628 37 14 is be AUX ajst-29628 37 15 very very ADV ajst-29628 37 16 large large ADJ ajst-29628 37 17 , , PUNCT ajst-29628 37 18 so so ADV ajst-29628 37 19 the the DET ajst-29628 37 20 extracted extract VERB ajst-29628 37 21 feature feature NOUN ajst-29628 37 22 matrix matrix NOUN ajst-29628 37 23 can can AUX ajst-29628 37 24 not not PART ajst-29628 37 25 accurately accurately ADV ajst-29628 37 26 reflect reflect VERB ajst-29628 37 27 the the DET ajst-29628 37 28 local local ADJ ajst-29628 37 29 features feature NOUN ajst-29628 37 30 of of ADP ajst-29628 37 31 the the DET ajst-29628 37 32 indicator indicator NOUN ajst-29628 37 33 diagram diagram NOUN ajst-29628 37 34 . . PUNCT ajst-29628 38 1 even even ADV ajst-29628 38 2 if if SCONJ ajst-29628 38 3 the the DET ajst-29628 38 4 classifier classifier NOUN ajst-29628 38 5 algorithm algorithm NOUN ajst-29628 38 6 is be AUX ajst-29628 38 7 very very ADV ajst-29628 38 8 accurate accurate ADJ ajst-29628 38 9 , , PUNCT ajst-29628 38 10 it it PRON ajst-29628 38 11 is be AUX ajst-29628 38 12 still still ADV ajst-29628 38 13 inaccurate inaccurate ADJ ajst-29628 38 14 . . PUNCT ajst-29628 39 1 the the DET ajst-29628 39 2 artificial artificial ADJ ajst-29628 39 3 neural neural ADJ ajst-29628 39 4 network network NOUN ajst-29628 39 5 method method NOUN ajst-29628 39 6 [ [ X ajst-29628 39 7 3 3 NUM ajst-29628 39 8 - - SYM ajst-29628 39 9 5 5 NUM ajst-29628 39 10 ] ] PUNCT ajst-29628 39 11 is be AUX ajst-29628 39 12 also also ADV ajst-29628 39 13 based base VERB ajst-29628 39 14 on on ADP ajst-29628 39 15 the the DET ajst-29628 39 16 grid grid NOUN ajst-29628 39 17 method method NOUN ajst-29628 39 18 and and CCONJ ajst-29628 39 19 gray gray ADJ ajst-29628 39 20 matrix matrix NOUN ajst-29628 39 21 to to PART ajst-29628 39 22 extract extract VERB ajst-29628 39 23 feature feature NOUN ajst-29628 39 24 information information NOUN ajst-29628 39 25 , , PUNCT ajst-29628 39 26 so so CCONJ ajst-29628 39 27 it it PRON ajst-29628 39 28 still still ADV ajst-29628 39 29 has have VERB ajst-29628 39 30 the the DET ajst-29628 39 31 defects defect NOUN ajst-29628 39 32 of of ADP ajst-29628 39 33 the the DET ajst-29628 39 34 grid grid NOUN ajst-29628 39 35 method method NOUN ajst-29628 39 36 and and CCONJ ajst-29628 39 37 gray gray ADJ ajst-29628 39 38 matrix matrix NOUN ajst-29628 39 39 . . PUNCT ajst-29628 40 1 these these DET ajst-29628 40 2 three three NUM ajst-29628 40 3 methods method NOUN ajst-29628 40 4 belong belong VERB ajst-29628 40 5 to to ADP ajst-29628 40 6 feature feature NOUN ajst-29628 40 7 recognition recognition NOUN ajst-29628 40 8 , , PUNCT ajst-29628 40 9 they they PRON ajst-29628 40 10 are be AUX ajst-29628 40 11 only only ADV ajst-29628 40 12 applicable applicable ADJ ajst-29628 40 13 to to ADP ajst-29628 40 14 the the DET ajst-29628 40 15 classification classification NOUN ajst-29628 40 16 and and CCONJ ajst-29628 40 17 recognition recognition NOUN ajst-29628 40 18 of of ADP ajst-29628 40 19 graphics graphic NOUN ajst-29628 40 20 , , PUNCT ajst-29628 40 21 and and CCONJ ajst-29628 40 22 can can AUX ajst-29628 40 23 not not PART ajst-29628 40 24 realize realize VERB ajst-29628 40 25 the the DET ajst-29628 40 26 accurate accurate ADJ ajst-29628 40 27 recognition recognition NOUN ajst-29628 40 28 of of ADP ajst-29628 40 29 graphics graphic NOUN ajst-29628 40 30 . . PUNCT ajst-29628 41 1 the the DET ajst-29628 41 2 vector vector NOUN ajst-29628 41 3 method method NOUN ajst-29628 41 4 belongs belong VERB ajst-29628 41 5 to to ADP ajst-29628 41 6 pattern pattern NOUN ajst-29628 41 7 recognition recognition NOUN ajst-29628 41 8 , , PUNCT ajst-29628 41 9 its its PRON ajst-29628 41 10 characteristic characteristic ADJ ajst-29628 41 11 matrix matrix NOUN ajst-29628 41 12 is be AUX ajst-29628 41 13 the the DET ajst-29628 41 14 quotient quotient NOUN ajst-29628 41 15 of of ADP ajst-29628 41 16 matrix matrix NOUN ajst-29628 41 17 elements element NOUN ajst-29628 41 18 and and CCONJ ajst-29628 41 19 matrix matrix NOUN ajst-29628 41 20 modulus modulus NOUN ajst-29628 41 21 , , PUNCT ajst-29628 41 22 and and CCONJ ajst-29628 41 23 its its PRON ajst-29628 41 24 matching matching NOUN ajst-29628 41 25 value value NOUN ajst-29628 41 26 is be AUX ajst-29628 41 27 the the DET ajst-29628 41 28 cosine cosine ADJ ajst-29628 41 29 value value NOUN ajst-29628 41 30 of of ADP ajst-29628 41 31 the the DET ajst-29628 41 32 vector vector NOUN ajst-29628 41 33 angle angle NOUN ajst-29628 41 34 . . PUNCT ajst-29628 42 1 321 321 NUM ajst-29628 42 2 figure figure NOUN ajst-29628 42 3 1 1 NUM ajst-29628 42 4 . . NOUN ajst-29628 42 5 difference difference NOUN ajst-29628 42 6 diagram diagram NOUN ajst-29628 42 7 of of ADP ajst-29628 42 8 dynamometer dynamometer NOUN ajst-29628 42 9 card card NOUN ajst-29628 42 10 contour contour NOUN ajst-29628 42 11 through through ADP ajst-29628 42 12 the the DET ajst-29628 42 13 grid grid NOUN ajst-29628 42 14 with with ADP ajst-29628 42 15 the the DET ajst-29628 42 16 continuous continuous ADJ ajst-29628 42 17 accumulation accumulation NOUN ajst-29628 42 18 of of ADP ajst-29628 42 19 the the DET ajst-29628 42 20 historical historical ADJ ajst-29628 42 21 data datum NOUN ajst-29628 42 22 of of ADP ajst-29628 42 23 the the DET ajst-29628 42 24 indicator indicator NOUN ajst-29628 42 25 diagram diagram NOUN ajst-29628 42 26 of of ADP ajst-29628 42 27 the the DET ajst-29628 42 28 oilfield oilfield NOUN ajst-29628 42 29 , , PUNCT ajst-29628 42 30 the the DET ajst-29628 42 31 types type NOUN ajst-29628 42 32 of of ADP ajst-29628 42 33 oil oil NOUN ajst-29628 42 34 production production NOUN ajst-29628 42 35 conditions condition NOUN ajst-29628 42 36 that that PRON ajst-29628 42 37 have have AUX ajst-29628 42 38 been be AUX ajst-29628 42 39 identified identify VERB ajst-29628 42 40 are be AUX ajst-29628 42 41 more more ADV ajst-29628 42 42 and and CCONJ ajst-29628 42 43 more more ADV ajst-29628 42 44 accurate accurate ADJ ajst-29628 42 45 and and CCONJ ajst-29628 42 46 refined refined ADJ ajst-29628 42 47 . . PUNCT ajst-29628 43 1 the the DET ajst-29628 43 2 fine fine ADJ ajst-29628 43 3 classification classification NOUN ajst-29628 43 4 of of ADP ajst-29628 43 5 indicator indicator NOUN ajst-29628 43 6 diagrams diagram NOUN ajst-29628 43 7 of of ADP ajst-29628 43 8 the the DET ajst-29628 43 9 same same ADJ ajst-29628 43 10 working working NOUN ajst-29628 43 11 condition condition NOUN ajst-29628 43 12 type type NOUN ajst-29628 43 13 can can AUX ajst-29628 43 14 reach reach VERB ajst-29628 43 15 several several ADJ ajst-29628 43 16 or or CCONJ ajst-29628 43 17 even even ADV ajst-29628 43 18 dozens dozen NOUN ajst-29628 43 19 . . PUNCT ajst-29628 44 1 the the DET ajst-29628 44 2 accuracy accuracy NOUN ajst-29628 44 3 of of ADP ajst-29628 44 4 the the DET ajst-29628 44 5 final final ADJ ajst-29628 44 6 conditiontype conditiontype NOUN ajst-29628 44 7 diagnosis diagnosis NOUN ajst-29628 44 8 results result NOUN ajst-29628 44 9 depends depend VERB ajst-29628 44 10 heavily heavily ADV ajst-29628 44 11 on on ADP ajst-29628 44 12 the the DET ajst-29628 44 13 quality quality NOUN ajst-29628 44 14 of of ADP ajst-29628 44 15 the the DET ajst-29628 44 16 contour contour NOUN ajst-29628 44 17 extraction extraction NOUN ajst-29628 44 18 of of ADP ajst-29628 44 19 the the DET ajst-29628 44 20 indicator indicator NOUN ajst-29628 44 21 diagram diagram NOUN ajst-29628 44 22 , , PUNCT ajst-29628 44 23 or or CCONJ ajst-29628 44 24 the the DET ajst-29628 44 25 low low ADJ ajst-29628 44 26 correlation correlation NOUN ajst-29628 44 27 between between ADP ajst-29628 44 28 the the DET ajst-29628 44 29 matching matching NOUN ajst-29628 44 30 algorithm algorithm NOUN ajst-29628 44 31 and and CCONJ ajst-29628 44 32 the the DET ajst-29628 44 33 degree degree NOUN ajst-29628 44 34 of of ADP ajst-29628 44 35 graphic graphic ADJ ajst-29628 44 36 difference difference NOUN ajst-29628 44 37 is be AUX ajst-29628 44 38 low low ADJ ajst-29628 44 39 . . PUNCT ajst-29628 45 1 therefore therefore ADV ajst-29628 45 2 , , PUNCT ajst-29628 45 3 they they PRON ajst-29628 45 4 can can AUX ajst-29628 45 5 not not PART ajst-29628 45 6 meet meet VERB ajst-29628 45 7 the the DET ajst-29628 45 8 requirements requirement NOUN ajst-29628 45 9 of of ADP ajst-29628 45 10 fine fine ADJ ajst-29628 45 11 identification identification NOUN ajst-29628 45 12 of of ADP ajst-29628 45 13 modern modern ADJ ajst-29628 45 14 indicator indicator NOUN ajst-29628 45 15 diagrams diagram NOUN ajst-29628 45 16 . . PUNCT ajst-29628 46 1 this this DET ajst-29628 46 2 paper paper NOUN ajst-29628 46 3 proposes propose VERB ajst-29628 46 4 a a DET ajst-29628 46 5 matching match VERB ajst-29628 46 6 algorithm algorithm NOUN ajst-29628 46 7 based base VERB ajst-29628 46 8 on on ADP ajst-29628 46 9 the the DET ajst-29628 46 10 standard standard ADJ ajst-29628 46 11 error error NOUN ajst-29628 46 12 ( ( PUNCT ajst-29628 46 13 se se X ajst-29628 46 14 ) ) PUNCT ajst-29628 46 15 algorithm algorithm NOUN ajst-29628 46 16 to to PART ajst-29628 46 17 realize realize VERB ajst-29628 46 18 the the DET ajst-29628 46 19 matching matching NOUN ajst-29628 46 20 between between ADP ajst-29628 46 21 the the DET ajst-29628 46 22 indicator indicator NOUN ajst-29628 46 23 diagram diagram NOUN ajst-29628 46 24 to to PART ajst-29628 46 25 be be AUX ajst-29628 46 26 identified identify VERB ajst-29628 46 27 and and CCONJ ajst-29628 46 28 the the DET ajst-29628 46 29 sample sample NOUN ajst-29628 46 30 indicator indicator NOUN ajst-29628 46 31 diagram diagram PROPN ajst-29628 46 32 . . PUNCT ajst-29628 47 1 the the DET ajst-29628 47 2 recognition recognition NOUN ajst-29628 47 3 algorithm algorithm NOUN ajst-29628 47 4 based base VERB ajst-29628 47 5 on on ADP ajst-29628 47 6 se se PROPN ajst-29628 47 7 theory theory NOUN ajst-29628 47 8 can can AUX ajst-29628 47 9 also also ADV ajst-29628 47 10 be be AUX ajst-29628 47 11 applied apply VERB ajst-29628 47 12 to to ADP ajst-29628 47 13 the the DET ajst-29628 47 14 accurate accurate ADJ ajst-29628 47 15 recognition recognition NOUN ajst-29628 47 16 of of ADP ajst-29628 47 17 two two NUM ajst-29628 47 18 - - PUNCT ajst-29628 47 19 dimensional dimensional ADJ ajst-29628 47 20 graphics graphic NOUN ajst-29628 47 21 . . PUNCT ajst-29628 48 1 at at ADP ajst-29628 48 2 present present ADJ ajst-29628 48 3 , , PUNCT ajst-29628 48 4 there there PRON ajst-29628 48 5 are be VERB ajst-29628 48 6 many many ADJ ajst-29628 48 7 algorithms algorithm NOUN ajst-29628 48 8 to to PART ajst-29628 48 9 measure measure VERB ajst-29628 48 10 the the DET ajst-29628 48 11 similarity similarity NOUN ajst-29628 48 12 of of ADP ajst-29628 48 13 graphics graphic NOUN ajst-29628 48 14 . . PUNCT ajst-29628 49 1 the the DET ajst-29628 49 2 main main ADJ ajst-29628 49 3 algorithms algorithm NOUN ajst-29628 49 4 are be AUX ajst-29628 49 5 crosscorrelation crosscorrelation NOUN ajst-29628 49 6 algorithm algorithm NOUN ajst-29628 49 7 [ [ X ajst-29628 49 8 6 6 NUM ajst-29628 49 9 ] ] PUNCT ajst-29628 49 10 ( ( PUNCT ajst-29628 49 11 cor cor NOUN ajst-29628 49 12 ) ) PUNCT ajst-29628 49 13 , , PUNCT ajst-29628 49 14 mean mean VERB ajst-29628 49 15 absolute absolute ADJ ajst-29628 49 16 difference difference NOUN ajst-29628 49 17 algorithm algorithm NOUN ajst-29628 49 18 ( ( PUNCT ajst-29628 49 19 mad mad ADJ ajst-29628 49 20 ) ) PUNCT ajst-29628 50 1 [ [ X ajst-29628 50 2 6,7 6,7 NUM ajst-29628 50 3 ] ] PUNCT ajst-29628 50 4 , , PUNCT ajst-29628 50 5 mean mean ADJ ajst-29628 50 6 square square ADJ ajst-29628 50 7 deviation deviation NOUN ajst-29628 50 8 algorithm algorithm NOUN ajst-29628 50 9 ( ( PUNCT ajst-29628 50 10 msd msd NOUN ajst-29628 50 11 ) ) PUNCT ajst-29628 51 1 [ [ X ajst-29628 51 2 6,8,9 6,8,9 NUM ajst-29628 51 3 ] ] X ajst-29628 51 4 , , PUNCT ajst-29628 51 5 camper camper PROPN ajst-29628 51 6 distance distance NOUN ajst-29628 51 7 algorithm algorithm NOUN ajst-29628 52 1 [ [ X ajst-29628 52 2 10 10 NUM ajst-29628 52 3 ] ] PUNCT ajst-29628 52 4 , , PUNCT ajst-29628 52 5 hausdorff hausdorff NOUN ajst-29628 52 6 algorithm algorithm NOUN ajst-29628 52 7 [ [ X ajst-29628 52 8 8,11 8,11 NOUN ajst-29628 52 9 ] ] PUNCT ajst-29628 52 10 , , PUNCT ajst-29628 52 11 normalized normalize VERB ajst-29628 52 12 product product NOUN ajst-29628 52 13 correlation correlation NOUN ajst-29628 52 14 algorithm algorithm NOUN ajst-29628 52 15 ( ( PUNCT ajst-29628 52 16 nprod nprod PROPN ajst-29628 52 17 ) ) PUNCT ajst-29628 53 1 [ [ X ajst-29628 53 2 12 12 NUM ajst-29628 53 3 ] ] PUNCT ajst-29628 53 4 , , PUNCT ajst-29628 53 5 which which PRON ajst-29628 53 6 are be AUX ajst-29628 53 7 the the DET ajst-29628 53 8 most most ADV ajst-29628 53 9 widely widely ADV ajst-29628 53 10 used use VERB ajst-29628 53 11 and and CCONJ ajst-29628 53 12 classic classic ADJ ajst-29628 53 13 graphics graphic NOUN ajst-29628 53 14 recognition recognition NOUN ajst-29628 53 15 algorithms algorithm NOUN ajst-29628 53 16 . . PUNCT ajst-29628 54 1 the the DET ajst-29628 54 2 reliability reliability NOUN ajst-29628 54 3 of of ADP ajst-29628 54 4 these these DET ajst-29628 54 5 algorithms algorithm NOUN ajst-29628 54 6 is be AUX ajst-29628 54 7 studied study VERB ajst-29628 54 8 in in ADP ajst-29628 54 9 detail detail NOUN ajst-29628 54 10 . . PUNCT ajst-29628 55 1 2 2 X ajst-29628 55 2 . . X ajst-29628 55 3 working work VERB ajst-29628 55 4 condition condition NOUN ajst-29628 55 5 identification identification NOUN ajst-29628 55 6 of of ADP ajst-29628 55 7 indicator indicator NOUN ajst-29628 55 8 diagram diagram NOUN ajst-29628 55 9 based base VERB ajst-29628 55 10 on on ADP ajst-29628 55 11 standard standard ADJ ajst-29628 55 12 error error NOUN ajst-29628 55 13 algorithm algorithm NOUN ajst-29628 55 14 2.1 2.1 NUM ajst-29628 55 15 . . PUNCT ajst-29628 55 16 isometric isometric ADJ ajst-29628 55 17 displacement displacement NOUN ajst-29628 55 18 and and CCONJ ajst-29628 55 19 dimensionless dimensionless NOUN ajst-29628 55 20 calibration calibration NOUN ajst-29628 55 21 of of ADP ajst-29628 55 22 the the DET ajst-29628 55 23 indicator indicator NOUN ajst-29628 55 24 diagram diagram VERB ajst-29628 55 25 the the DET ajst-29628 55 26 indicator indicator PROPN ajst-29628 55 27 diagram diagram NOUN ajst-29628 55 28 data data NOUN ajst-29628 55 29 is be AUX ajst-29628 55 30 a a DET ajst-29628 55 31 discrete discrete ADJ ajst-29628 55 32 two two NUM ajst-29628 55 33 - - PUNCT ajst-29628 55 34 dimensional dimensional ADJ ajst-29628 55 35 array array NOUN ajst-29628 56 1 [ [ X ajst-29628 56 2 si si X ajst-29628 56 3 , , PUNCT ajst-29628 56 4 wi wi PROPN ajst-29628 56 5 ] ] X ajst-29628 56 6 ( ( PUNCT ajst-29628 56 7 i=1 i=1 PROPN ajst-29628 56 8 , , PUNCT ajst-29628 56 9 2 2 NUM ajst-29628 56 10 , , PUNCT ajst-29628 56 11 ... ... PUNCT ajst-29628 56 12 ) ) PUNCT ajst-29628 56 13 , , PUNCT ajst-29628 56 14 si si X ajst-29628 56 15 is be AUX ajst-29628 56 16 the the DET ajst-29628 56 17 displacement displacement NOUN ajst-29628 56 18 , , PUNCT ajst-29628 56 19 and and CCONJ ajst-29628 56 20 wi wi PROPN ajst-29628 56 21 is be AUX ajst-29628 56 22 the the DET ajst-29628 56 23 load load NOUN ajst-29628 56 24 . . PUNCT ajst-29628 57 1 since since SCONJ ajst-29628 57 2 the the DET ajst-29628 57 3 displacement displacement ADJ ajst-29628 57 4 value value NOUN ajst-29628 57 5 points point NOUN ajst-29628 57 6 of of ADP ajst-29628 57 7 the the DET ajst-29628 57 8 indicator indicator NOUN ajst-29628 57 9 diagram diagram NOUN ajst-29628 57 10 are be AUX ajst-29628 57 11 different different ADJ ajst-29628 57 12 , , PUNCT ajst-29628 57 13 it it PRON ajst-29628 57 14 is be AUX ajst-29628 57 15 necessary necessary ADJ ajst-29628 57 16 to to PART ajst-29628 57 17 carry carry VERB ajst-29628 57 18 out out ADP ajst-29628 57 19 si si NOUN ajst-29628 57 20 coordinate coordinate NOUN ajst-29628 57 21 equivalent equivalent ADJ ajst-29628 57 22 calibration calibration NOUN ajst-29628 57 23 for for ADP ajst-29628 57 24 the the DET ajst-29628 57 25 indicator indicator PROPN ajst-29628 57 26 diagram diagram NOUN ajst-29628 57 27 to to PART ajst-29628 57 28 be be AUX ajst-29628 57 29 identified identify VERB ajst-29628 57 30 and and CCONJ ajst-29628 57 31 the the DET ajst-29628 57 32 sample sample NOUN ajst-29628 57 33 indicator indicator NOUN ajst-29628 57 34 diagram diagram PROPN ajst-29628 57 35 . . PUNCT ajst-29628 58 1 our our PRON ajst-29628 58 2 value value NOUN ajst-29628 58 3 can can AUX ajst-29628 58 4 be be AUX ajst-29628 58 5 obtained obtain VERB ajst-29628 58 6 by by ADP ajst-29628 58 7 the the DET ajst-29628 58 8 lagrange lagrange PROPN ajst-29628 58 9 algorithm algorithm NOUN ajst-29628 58 10 . . PUNCT ajst-29628 59 1 the the DET ajst-29628 59 2 geometric geometric ADJ ajst-29628 59 3 contour contour NOUN ajst-29628 59 4 shape shape NOUN ajst-29628 59 5 of of ADP ajst-29628 59 6 a a DET ajst-29628 59 7 figure figure NOUN ajst-29628 59 8 is be AUX ajst-29628 59 9 the the DET ajst-29628 59 10 relevant relevant ADJ ajst-29628 59 11 element element NOUN ajst-29628 59 12 to to PART ajst-29628 59 13 be be AUX ajst-29628 59 14 extracted extract VERB ajst-29628 59 15 , , PUNCT ajst-29628 59 16 while while SCONJ ajst-29628 59 17 the the DET ajst-29628 59 18 size size NOUN ajst-29628 59 19 of of ADP ajst-29628 59 20 the the DET ajst-29628 59 21 actual actual ADJ ajst-29628 59 22 [ [ X ajst-29628 59 23 si si X ajst-29628 59 24 , , PUNCT ajst-29628 59 25 wi wi PROPN ajst-29628 59 26 ] ] PUNCT ajst-29628 59 27 value value NOUN ajst-29628 59 28 is be AUX ajst-29628 59 29 irrelevant irrelevant ADJ ajst-29628 59 30 to to ADP ajst-29628 59 31 the the DET ajst-29628 59 32 figure figure NOUN ajst-29628 59 33 recognition recognition NOUN ajst-29628 59 34 . . PUNCT ajst-29628 60 1 therefore therefore ADV ajst-29628 60 2 , , PUNCT ajst-29628 60 3 the the DET ajst-29628 60 4 graph graph NOUN ajst-29628 60 5 must must AUX ajst-29628 60 6 be be AUX ajst-29628 60 7 dimensionless dimensionless NOUN ajst-29628 60 8 calibrated calibrate VERB ajst-29628 60 9 . . PUNCT ajst-29628 61 1 π‘Œ π‘Œ PROPN ajst-29628 61 2 𝑋 𝑋 PROPN ajst-29628 61 3 ( ( PUNCT ajst-29628 61 4 1 1 NUM ajst-29628 61 5 ) ) PUNCT ajst-29628 61 6 in in ADP ajst-29628 61 7 equation equation NOUN ajst-29628 61 8 ( ( PUNCT ajst-29628 61 9 1 1 NUM ajst-29628 61 10 ) ) PUNCT ajst-29628 61 11 , , PUNCT ajst-29628 61 12 wmax wmax PROPN ajst-29628 61 13 is be AUX ajst-29628 61 14 the the DET ajst-29628 61 15 maximum maximum ADJ ajst-29628 61 16 load load NOUN ajst-29628 61 17 on on ADP ajst-29628 61 18 the the DET ajst-29628 61 19 dynamometer dynamometer NOUN ajst-29628 61 20 diagram diagram NOUN ajst-29628 61 21 , , PUNCT ajst-29628 61 22 n. n. PROPN ajst-29628 61 23 wmin wmin PROPN ajst-29628 61 24 is be AUX ajst-29628 61 25 the the DET ajst-29628 61 26 minimum minimum ADJ ajst-29628 61 27 load load NOUN ajst-29628 61 28 on on ADP ajst-29628 61 29 the the DET ajst-29628 61 30 dynamometer dynamometer NOUN ajst-29628 61 31 diagram diagram NOUN ajst-29628 61 32 , , PUNCT ajst-29628 61 33 n. n. PROPN ajst-29628 61 34 smax smax PROPN ajst-29628 61 35 is be AUX ajst-29628 61 36 the the DET ajst-29628 61 37 maximum maximum ADJ ajst-29628 61 38 displacement displacement NOUN ajst-29628 61 39 , , PUNCT ajst-29628 61 40 m. m. NOUN ajst-29628 61 41 smin smin PROPN ajst-29628 61 42 is be AUX ajst-29628 61 43 the the DET ajst-29628 61 44 minimum minimum ADJ ajst-29628 61 45 displacement displacement NOUN ajst-29628 61 46 , , PUNCT ajst-29628 61 47 m m PROPN ajst-29628 61 48 。 。 PROPN ajst-29628 61 49 2.2 2.2 NUM ajst-29628 61 50 . . PUNCT ajst-29628 62 1 classifier classifier NOUN ajst-29628 62 2 algorithm algorithm PROPN ajst-29628 62 3 β€”β€” β€”β€” PUNCT ajst-29628 62 4 standard standard ADJ ajst-29628 62 5 error error NOUN ajst-29628 62 6 in in ADP ajst-29628 62 7 a a DET ajst-29628 62 8 dimensionless dimensionless NOUN ajst-29628 62 9 coordinate coordinate NOUN ajst-29628 62 10 system system NOUN ajst-29628 62 11 , , PUNCT ajst-29628 62 12 the the DET ajst-29628 62 13 similarity similarity NOUN ajst-29628 62 14 between between ADP ajst-29628 62 15 two two NUM ajst-29628 62 16 geometric geometric ADJ ajst-29628 62 17 shapes shape NOUN ajst-29628 62 18 is be AUX ajst-29628 62 19 characterized characterize VERB ajst-29628 62 20 by by ADP ajst-29628 62 21 the the DET ajst-29628 62 22 degree degree NOUN ajst-29628 62 23 of of ADP ajst-29628 62 24 convergence convergence NOUN ajst-29628 62 25 of of ADP ajst-29628 62 26 the the DET ajst-29628 62 27 same same ADJ ajst-29628 62 28 displacement displacement ADJ ajst-29628 62 29 point point NOUN ajst-29628 62 30 . . PUNCT ajst-29628 63 1 the the DET ajst-29628 63 2 indicator indicator NOUN ajst-29628 63 3 diagram diagram NOUN ajst-29628 63 4 consists consist VERB ajst-29628 63 5 of of ADP ajst-29628 63 6 a a DET ajst-29628 63 7 dataset dataset NOUN ajst-29628 63 8 , , PUNCT ajst-29628 63 9 with with ADP ajst-29628 63 10 the the DET ajst-29628 63 11 calibration calibration NOUN ajst-29628 63 12 sample sample NOUN ajst-29628 63 13 indicator indicator NOUN ajst-29628 63 14 diagram diagram PROPN ajst-29628 63 15 dataset dataset NOUN ajst-29628 63 16 being be AUX ajst-29628 63 17 the the DET ajst-29628 63 18 true true ADJ ajst-29628 63 19 value value NOUN ajst-29628 63 20 and and CCONJ ajst-29628 63 21 the the DET ajst-29628 63 22 identification identification NOUN ajst-29628 63 23 indicator indicator NOUN ajst-29628 63 24 diagram diagram NOUN ajst-29628 63 25 dataset dataset NOUN ajst-29628 63 26 being be AUX ajst-29628 63 27 the the DET ajst-29628 63 28 measured measured ADJ ajst-29628 63 29 value value NOUN ajst-29628 63 30 . . PUNCT ajst-29628 64 1 in in ADP ajst-29628 64 2 this this DET ajst-29628 64 3 way way NOUN ajst-29628 64 4 , , PUNCT ajst-29628 64 5 the the DET ajst-29628 64 6 similarity similarity NOUN ajst-29628 64 7 between between ADP ajst-29628 64 8 the the DET ajst-29628 64 9 indicator indicator NOUN ajst-29628 64 10 diagram diagram NOUN ajst-29628 64 11 to to PART ajst-29628 64 12 be be AUX ajst-29628 64 13 identified identify VERB ajst-29628 64 14 and and CCONJ ajst-29628 64 15 the the DET ajst-29628 64 16 sample sample NOUN ajst-29628 64 17 indicator indicator NOUN ajst-29628 64 18 diagram diagram NOUN ajst-29628 64 19 can can AUX ajst-29628 64 20 be be AUX ajst-29628 64 21 defined define VERB ajst-29628 64 22 as as ADP ajst-29628 64 23 the the DET ajst-29628 64 24 degree degree NOUN ajst-29628 64 25 to to PART ajst-29628 64 26 which which PRON ajst-29628 64 27 the the DET ajst-29628 64 28 measured measured ADJ ajst-29628 64 29 value value NOUN ajst-29628 64 30 approaches approach VERB ajst-29628 64 31 the the DET ajst-29628 64 32 true true ADJ ajst-29628 64 33 value value NOUN ajst-29628 64 34 , , PUNCT ajst-29628 64 35 that that ADV ajst-29628 64 36 is is ADV ajst-29628 64 37 , , PUNCT ajst-29628 64 38 the the DET ajst-29628 64 39 deviation deviation NOUN ajst-29628 64 40 between between ADP ajst-29628 64 41 the the DET ajst-29628 64 42 measured measure VERB ajst-29628 64 43 value value NOUN ajst-29628 64 44 and and CCONJ ajst-29628 64 45 the the DET ajst-29628 64 46 true true ADJ ajst-29628 64 47 value value NOUN ajst-29628 64 48 , , PUNCT ajst-29628 64 49 which which PRON ajst-29628 64 50 is be AUX ajst-29628 64 51 called call VERB ajst-29628 64 52 the the DET ajst-29628 64 53 standard standard ADJ ajst-29628 64 54 error error NOUN ajst-29628 64 55 ( ( PUNCT ajst-29628 64 56 se se ADJ ajst-29628 64 57 ) ) PUNCT ajst-29628 64 58 . . PUNCT ajst-29628 65 1 se se PROPN ajst-29628 65 2 is be AUX ajst-29628 65 3 very very ADV ajst-29628 65 4 sensitive sensitive ADJ ajst-29628 65 5 to to ADP ajst-29628 65 6 large large ADJ ajst-29628 65 7 or or CCONJ ajst-29628 65 8 small small ADJ ajst-29628 65 9 errors error NOUN ajst-29628 65 10 in in ADP ajst-29628 65 11 a a DET ajst-29628 65 12 set set NOUN ajst-29628 65 13 of of ADP ajst-29628 65 14 measurement measurement NOUN ajst-29628 65 15 values value NOUN ajst-29628 65 16 , , PUNCT ajst-29628 65 17 so so ADV ajst-29628 65 18 , , PUNCT ajst-29628 65 19 se se X ajst-29628 65 20 can can AUX ajst-29628 65 21 effectively effectively ADV ajst-29628 65 22 reflect reflect VERB ajst-29628 65 23 the the DET ajst-29628 65 24 degree degree NOUN ajst-29628 65 25 to to PART ajst-29628 65 26 which which PRON ajst-29628 65 27 the the DET ajst-29628 65 28 identified identify VERB ajst-29628 65 29 indicator indicator NOUN ajst-29628 65 30 diagram diagram NOUN ajst-29628 65 31 dataset dataset NOUN ajst-29628 65 32 approaches approach VERB ajst-29628 65 33 the the DET ajst-29628 65 34 sample sample NOUN ajst-29628 65 35 indicator indicator NOUN ajst-29628 65 36 diagram diagram PROPN ajst-29628 65 37 dataset dataset PROPN ajst-29628 65 38 . . PUNCT ajst-29628 66 1 the the DET ajst-29628 66 2 se se PROPN ajst-29628 66 3 of of ADP ajst-29628 66 4 the the DET ajst-29628 66 5 indicator indicator PROPN ajst-29628 66 6 diagram diagram NOUN ajst-29628 66 7 dataset dataset VERB ajst-29628 66 8 a a DET ajst-29628 66 9 ( ( PUNCT ajst-29628 66 10 ya ya PROPN ajst-29628 66 11 , , PUNCT ajst-29628 66 12 xa xa PROPN ajst-29628 66 13 ) ) PUNCT ajst-29628 66 14 is be AUX ajst-29628 66 15 to to PART ajst-29628 66 16 be be AUX ajst-29628 66 17 identified identify VERB ajst-29628 66 18 and and CCONJ ajst-29628 67 1 the the DET ajst-29628 67 2 sample sample NOUN ajst-29628 67 3 indicator indicator NOUN ajst-29628 67 4 diagram diagram PROPN ajst-29628 67 5 dataset dataset PROPN ajst-29628 67 6 b b PROPN ajst-29628 67 7 ( ( PUNCT ajst-29628 67 8 yb yb PROPN ajst-29628 67 9 , , PUNCT ajst-29628 67 10 xb xb PROPN ajst-29628 67 11 ) ) PUNCT ajst-29628 67 12 is be AUX ajst-29628 67 13 𝑑 𝑑 PROPN ajst-29628 67 14 𝐴 𝐴 PROPN ajst-29628 67 15 , , PUNCT ajst-29628 67 16 𝐡 𝐡 NOUN ajst-29628 67 17 1 1 NUM ajst-29628 67 18 𝑁 𝑁 PROPN ajst-29628 67 19 β€Š β€Š SPACE ajst-29628 67 20 𝑦 𝑦 NOUN ajst-29628 67 21 π‘₯ π‘₯ PROPN ajst-29628 67 22 𝑦 𝑦 NUM ajst-29628 67 23 π‘₯ π‘₯ X ajst-29628 67 24 ( ( PUNCT ajst-29628 67 25 2 2 NUM ajst-29628 67 26 ) ) PUNCT ajst-29628 67 27 se se X ajst-29628 67 28 matching matching NOUN ajst-29628 67 29 value value NOUN ajst-29628 67 30 range range NOUN ajst-29628 67 31 : : PUNCT ajst-29628 67 32 0 0 NUM ajst-29628 67 33 ≀ ≀ NUM ajst-29628 67 34 d d PUNCT ajst-29628 67 35 ≀ ≀ NUM ajst-29628 67 36 1 1 NUM ajst-29628 67 37 . . PUNCT ajst-29628 68 1 two two NUM ajst-29628 68 2 geometric geometric ADJ ajst-29628 68 3 shapes shape NOUN ajst-29628 68 4 that that PRON ajst-29628 68 5 are be AUX ajst-29628 68 6 completely completely ADV ajst-29628 68 7 similar similar ADJ ajst-29628 68 8 have have VERB ajst-29628 68 9 d=0 d=0 PROPN ajst-29628 68 10 ; ; PUNCT ajst-29628 68 11 the the PRON ajst-29628 68 12 closer close ADV ajst-29628 68 13 the the DET ajst-29628 68 14 geometric geometric ADJ ajst-29628 68 15 shape shape NOUN ajst-29628 68 16 , , PUNCT ajst-29628 68 17 the the PRON ajst-29628 68 18 smaller small ADJ ajst-29628 68 19 the the DET ajst-29628 68 20 se se PROPN ajst-29628 68 21 value value NOUN ajst-29628 68 22 of of ADP ajst-29628 68 23 the the DET ajst-29628 68 24 shape shape NOUN ajst-29628 68 25 . . PUNCT ajst-29628 69 1 0 0 NUM ajst-29628 69 2 similarity similarity NOUN ajst-29628 69 3 is be AUX ajst-29628 69 4 an an DET ajst-29628 69 5 equivalent equivalent ADJ ajst-29628 69 6 scale scale NOUN ajst-29628 69 7 used use VERB ajst-29628 69 8 to to PART ajst-29628 69 9 measure measure VERB ajst-29628 69 10 the the DET ajst-29628 69 11 degree degree NOUN ajst-29628 69 12 of of ADP ajst-29628 69 13 similarity similarity NOUN ajst-29628 69 14 between between ADP ajst-29628 69 15 two two NUM ajst-29628 69 16 geometric geometric ADJ ajst-29628 69 17 shapes shape NOUN ajst-29628 69 18 . . PUNCT ajst-29628 70 1 the the DET ajst-29628 70 2 similarity similarity NOUN ajst-29628 70 3 of of ADP ajst-29628 70 4 completely completely ADV ajst-29628 70 5 similar similar ADJ ajst-29628 70 6 shapes shape NOUN ajst-29628 70 7 is be AUX ajst-29628 70 8 1 1 NUM ajst-29628 70 9 , , PUNCT ajst-29628 70 10 and and CCONJ ajst-29628 70 11 the the DET ajst-29628 70 12 more more ADV ajst-29628 70 13 similar similar ADJ ajst-29628 70 14 the the DET ajst-29628 70 15 shapes shape NOUN ajst-29628 70 16 are be AUX ajst-29628 70 17 , , PUNCT ajst-29628 70 18 the the PRON ajst-29628 70 19 higher high ADJ ajst-29628 70 20 their their PRON ajst-29628 70 21 similarity similarity NOUN ajst-29628 70 22 . . PUNCT ajst-29628 71 1 define define VERB ajst-29628 71 2 the the DET ajst-29628 71 3 similarity similarity NOUN ajst-29628 71 4 between between ADP ajst-29628 71 5 two two NUM ajst-29628 71 6 graphics graphic NOUN ajst-29628 71 7 as as ADP ajst-29628 71 8 𝑅 𝑅 PROPN ajst-29628 71 9 1 1 PROPN ajst-29628 71 10 𝑑 𝑑 PROPN ajst-29628 71 11 ( ( PUNCT ajst-29628 71 12 3 3 NUM ajst-29628 71 13 ) ) PUNCT ajst-29628 71 14 by by ADP ajst-29628 71 15 performing perform VERB ajst-29628 71 16 similarity similarity NOUN ajst-29628 71 17 recognition recognition NOUN ajst-29628 71 18 between between ADP ajst-29628 71 19 the the DET ajst-29628 71 20 comparison comparison NOUN ajst-29628 71 21 image image NOUN ajst-29628 71 22 and and CCONJ ajst-29628 71 23 the the DET ajst-29628 71 24 reference reference NOUN ajst-29628 71 25 image image NOUN ajst-29628 71 26 , , PUNCT ajst-29628 71 27 the the DET ajst-29628 71 28 degree degree NOUN ajst-29628 71 29 of of ADP ajst-29628 71 30 similarity similarity NOUN ajst-29628 71 31 of of ADP ajst-29628 71 32 the the DET ajst-29628 71 33 graphics graphic NOUN ajst-29628 71 34 can can AUX ajst-29628 71 35 be be AUX ajst-29628 71 36 accurately accurately ADV ajst-29628 71 37 determined determine VERB ajst-29628 71 38 based base VERB ajst-29628 71 39 on on ADP ajst-29628 71 40 the the DET ajst-29628 71 41 similarity similarity NOUN ajst-29628 71 42 level level NOUN ajst-29628 71 43 . . PUNCT ajst-29628 72 1 3 3 X ajst-29628 72 2 . . X ajst-29628 72 3 research research NOUN ajst-29628 72 4 on on ADP ajst-29628 72 5 the the DET ajst-29628 72 6 correlation correlation NOUN ajst-29628 72 7 between between ADP ajst-29628 72 8 similarity similarity NOUN ajst-29628 72 9 matching matching NOUN ajst-29628 72 10 algorithm algorithm NOUN ajst-29628 72 11 and and CCONJ ajst-29628 72 12 graphic graphic ADJ ajst-29628 72 13 difference difference NOUN ajst-29628 72 14 degree degree NOUN ajst-29628 72 15 at at ADP ajst-29628 72 16 present present NOUN ajst-29628 72 17 , , PUNCT ajst-29628 72 18 the the DET ajst-29628 72 19 main main ADJ ajst-29628 72 20 similarity similarity NOUN ajst-29628 72 21 - - PUNCT ajst-29628 72 22 matching match VERB ajst-29628 72 23 algorithm algorithm NOUN ajst-29628 72 24 models model NOUN ajst-29628 72 25 based base VERB ajst-29628 72 26 on on ADP ajst-29628 72 27 graphics graphic NOUN ajst-29628 72 28 include include VERB ajst-29628 72 29 vector vector NOUN ajst-29628 72 30 , , PUNCT ajst-29628 72 31 cor cor PROPN ajst-29628 72 32 , , PUNCT ajst-29628 72 33 mad mad ADJ ajst-29628 72 34 , , PUNCT ajst-29628 72 35 msd msd NOUN ajst-29628 72 36 , , PUNCT ajst-29628 72 37 comberra comberra NOUN ajst-29628 72 38 , , PUNCT ajst-29628 72 39 hausdorff hausdorff NOUN ajst-29628 72 40 , , PUNCT ajst-29628 72 41 and and CCONJ ajst-29628 72 42 nprod nprod ADJ ajst-29628 72 43 algorithms algorithm NOUN ajst-29628 72 44 . . PUNCT ajst-29628 73 1 these these DET ajst-29628 73 2 algorithms algorithm NOUN ajst-29628 73 3 are be AUX ajst-29628 73 4 classic classic ADJ ajst-29628 73 5 algorithms algorithm NOUN ajst-29628 73 6 for for ADP ajst-29628 73 7 determining determine VERB ajst-29628 73 8 whether whether SCONJ ajst-29628 73 9 two two NUM ajst-29628 73 10 shapes shape NOUN ajst-29628 73 11 are be AUX ajst-29628 73 12 similar similar ADJ ajst-29628 73 13 . . PUNCT ajst-29628 74 1 however however ADV ajst-29628 74 2 , , PUNCT ajst-29628 74 3 there there PRON ajst-29628 74 4 is be VERB ajst-29628 74 5 currently currently ADV ajst-29628 74 6 no no DET ajst-29628 74 7 report report NOUN ajst-29628 74 8 in in ADP ajst-29628 74 9 domestic domestic ADJ ajst-29628 74 10 and and CCONJ ajst-29628 74 11 foreign foreign ADJ ajst-29628 74 12 literature literature NOUN ajst-29628 74 13 on on ADP ajst-29628 74 14 whether whether SCONJ ajst-29628 74 15 these these DET ajst-29628 74 16 algorithms algorithm NOUN ajst-29628 74 17 can can AUX ajst-29628 74 18 accurately accurately ADV ajst-29628 74 19 determine determine VERB ajst-29628 74 20 the the DET ajst-29628 74 21 similarity similarity NOUN ajst-29628 74 22 of of ADP ajst-29628 74 23 graphics graphic NOUN ajst-29628 74 24 , , PUNCT ajst-29628 74 25 or or CCONJ ajst-29628 74 26 which which DET ajst-29628 74 27 algorithm algorithm NOUN ajst-29628 74 28 can can AUX ajst-29628 74 29 more more ADV ajst-29628 74 30 accurately accurately ADV ajst-29628 74 31 determine determine VERB ajst-29628 74 32 the the DET ajst-29628 74 33 degree degree NOUN ajst-29628 74 34 of of ADP ajst-29628 74 35 similarity similarity NOUN ajst-29628 74 36 of of ADP ajst-29628 74 37 graphics graphic NOUN ajst-29628 74 38 . . PUNCT ajst-29628 75 1 the the DET ajst-29628 75 2 argument argument NOUN ajst-29628 75 3 that that SCONJ ajst-29628 75 4 there there PRON ajst-29628 75 5 is be VERB ajst-29628 75 6 a a DET ajst-29628 75 7 correlation correlation NOUN ajst-29628 75 8 between between ADP ajst-29628 75 9 the the DET ajst-29628 75 10 similarity similarity NOUN ajst-29628 75 11 - - PUNCT ajst-29628 75 12 matching match VERB ajst-29628 75 13 calculation calculation NOUN ajst-29628 75 14 model model NOUN ajst-29628 75 15 and and CCONJ ajst-29628 75 16 the the DET ajst-29628 75 17 degree degree NOUN ajst-29628 75 18 of of ADP ajst-29628 75 19 geometric geometric ADJ ajst-29628 75 20 difference difference NOUN ajst-29628 75 21 has have AUX ajst-29628 75 22 been be AUX ajst-29628 75 23 proposed propose VERB ajst-29628 75 24 for for ADP ajst-29628 75 25 the the DET ajst-29628 75 26 first first ADJ ajst-29628 75 27 time time NOUN ajst-29628 75 28 . . PUNCT ajst-29628 76 1 the the DET ajst-29628 76 2 size size NOUN ajst-29628 76 3 of of ADP ajst-29628 76 4 the the DET ajst-29628 76 5 matching matching NOUN ajst-29628 76 6 value value NOUN ajst-29628 76 7 should should AUX ajst-29628 76 8 be be AUX ajst-29628 76 9 able able ADJ ajst-29628 76 10 to to PART ajst-29628 76 11 reflect reflect VERB ajst-29628 76 12 the the DET ajst-29628 76 13 degree degree NOUN ajst-29628 76 14 of of ADP ajst-29628 76 15 difference difference NOUN ajst-29628 76 16 between between ADP ajst-29628 76 17 two two NUM ajst-29628 76 18 geometric geometric ADJ ajst-29628 76 19 shapes shape NOUN ajst-29628 76 20 , , PUNCT ajst-29628 76 21 that that ADV ajst-29628 76 22 is is ADV ajst-29628 76 23 , , PUNCT ajst-29628 76 24 the the PRON ajst-29628 76 25 greater great ADJ ajst-29628 76 26 the the DET ajst-29628 76 27 difference difference NOUN ajst-29628 76 28 between between ADP ajst-29628 76 29 two two NUM ajst-29628 76 30 geometric geometric ADJ ajst-29628 76 31 shapes shape NOUN ajst-29628 76 32 , , PUNCT ajst-29628 76 33 the the PRON ajst-29628 76 34 greater great ADJ ajst-29628 76 35 the the DET ajst-29628 76 36 difference difference NOUN ajst-29628 76 37 in in ADP ajst-29628 76 38 their their PRON ajst-29628 76 39 matching match VERB ajst-29628 76 40 values value NOUN ajst-29628 76 41 should should AUX ajst-29628 76 42 also also ADV ajst-29628 76 43 be be AUX ajst-29628 76 44 , , PUNCT ajst-29628 76 45 and and CCONJ ajst-29628 76 46 they they PRON ajst-29628 76 47 should should AUX ajst-29628 76 48 have have VERB ajst-29628 76 49 monotonicity monotonicity NOUN ajst-29628 76 50 . . PUNCT ajst-29628 77 1 therefore therefore ADV ajst-29628 77 2 , , PUNCT ajst-29628 77 3 the the DET ajst-29628 77 4 correlation correlation NOUN ajst-29628 77 5 between between ADP ajst-29628 77 6 the the DET ajst-29628 77 7 similarity similarity NOUN ajst-29628 77 8 matching matching NOUN ajst-29628 77 9 algorithm algorithm NOUN ajst-29628 77 10 and and CCONJ ajst-29628 77 11 the the DET ajst-29628 77 12 322 322 NUM ajst-29628 77 13 degree degree NOUN ajst-29628 77 14 of of ADP ajst-29628 77 15 graphical graphical ADJ ajst-29628 77 16 difference difference NOUN ajst-29628 77 17 between between ADP ajst-29628 77 18 the the DET ajst-29628 77 19 identified identify VERB ajst-29628 77 20 indicator indicator NOUN ajst-29628 77 21 diagram diagram NOUN ajst-29628 77 22 a a PRON ajst-29628 77 23 and and CCONJ ajst-29628 77 24 the the DET ajst-29628 77 25 sample sample NOUN ajst-29628 77 26 indicator indicator NOUN ajst-29628 77 27 diagram diagram PROPN ajst-29628 77 28 dataset dataset PROPN ajst-29628 77 29 b b PROPN ajst-29628 77 30 based base VERB ajst-29628 77 31 on on ADP ajst-29628 77 32 dimensionless dimensionless NOUN ajst-29628 77 33 calibration calibration NOUN ajst-29628 77 34 can can AUX ajst-29628 77 35 be be AUX ajst-29628 77 36 expressed express VERB ajst-29628 77 37 as as SCONJ ajst-29628 77 38 follows follow VERB ajst-29628 77 39 : : PUNCT ajst-29628 77 40 the the DET ajst-29628 77 41 change change NOUN ajst-29628 77 42 in in ADP ajst-29628 77 43 matching matching NOUN ajst-29628 77 44 value value NOUN ajst-29628 77 45 Ξ΄ Ξ΄ PROPN ajst-29628 77 46 d d NOUN ajst-29628 77 47 has have VERB ajst-29628 77 48 the the DET ajst-29628 77 49 same same ADJ ajst-29628 77 50 trend trend NOUN ajst-29628 77 51 as as ADP ajst-29628 77 52 the the DET ajst-29628 77 53 degree degree NOUN ajst-29628 77 54 of of ADP ajst-29628 77 55 graphical graphical ADJ ajst-29628 77 56 difference difference NOUN ajst-29628 77 57 Ξ΄ Ξ΄ PROPN ajst-29628 77 58 r. r. PROPN ajst-29628 77 59 δ𝑑 δ𝑑 PROPN ajst-29628 77 60 𝐴 𝐴 PROPN ajst-29628 77 61 , , PUNCT ajst-29628 77 62 𝐡 𝐡 PROPN ajst-29628 77 63 ∝ ∝ PROPN ajst-29628 77 64 δ𝑅 δ𝑅 PROPN ajst-29628 77 65 𝐴 𝐴 PROPN ajst-29628 77 66 , , PUNCT ajst-29628 77 67 𝐡 𝐡 NOUN ajst-29628 77 68 ( ( PUNCT ajst-29628 77 69 4 4 NUM ajst-29628 77 70 ) ) PUNCT ajst-29628 77 71 figure figure NOUN ajst-29628 77 72 2 2 NUM ajst-29628 77 73 shows show VERB ajst-29628 77 74 a a DET ajst-29628 77 75 sample sample NOUN ajst-29628 77 76 dynamometer dynamometer NOUN ajst-29628 77 77 diagram diagram PROPN ajst-29628 77 78 b. b. PROPN ajst-29628 77 79 applying apply VERB ajst-29628 77 80 fluctuations fluctuation NOUN ajst-29628 77 81 locally locally ADV ajst-29628 77 82 to to ADP ajst-29628 77 83 this this DET ajst-29628 77 84 sample sample NOUN ajst-29628 77 85 diagram diagram NOUN ajst-29628 77 86 can can AUX ajst-29628 77 87 obtain obtain VERB ajst-29628 77 88 the the DET ajst-29628 77 89 dynamometer dynamometer NOUN ajst-29628 77 90 diagram diagram NOUN ajst-29628 77 91 a a PRON ajst-29628 77 92 to to PART ajst-29628 77 93 be be AUX ajst-29628 77 94 recognized recognize VERB ajst-29628 77 95 , , PUNCT ajst-29628 77 96 as as SCONJ ajst-29628 77 97 shown show VERB ajst-29628 77 98 in in ADP ajst-29628 77 99 figure figure NOUN ajst-29628 77 100 3 3 NUM ajst-29628 77 101 . . PUNCT ajst-29628 77 102 by by ADP ajst-29628 77 103 gradually gradually ADV ajst-29628 77 104 increasing increase VERB ajst-29628 77 105 the the DET ajst-29628 77 106 fluctuation fluctuation NOUN ajst-29628 77 107 points point NOUN ajst-29628 77 108 of of ADP ajst-29628 77 109 dataset dataset NOUN ajst-29628 77 110 a a PRON ajst-29628 77 111 , , PUNCT ajst-29628 77 112 the the DET ajst-29628 77 113 difference difference NOUN ajst-29628 77 114 between between ADP ajst-29628 77 115 dataset dataset NOUN ajst-29628 77 116 a a PRON ajst-29628 77 117 and and CCONJ ajst-29628 77 118 dataset dataset ADJ ajst-29628 77 119 b b PROPN ajst-29628 77 120 is be AUX ajst-29628 77 121 increased increase VERB ajst-29628 77 122 . . PUNCT ajst-29628 78 1 apply apply VERB ajst-29628 78 2 vector vector PROPN ajst-29628 78 3 , , PUNCT ajst-29628 78 4 cor cor PROPN ajst-29628 78 5 , , PUNCT ajst-29628 78 6 mad mad ADJ ajst-29628 78 7 , , PUNCT ajst-29628 78 8 msd msd NOUN ajst-29628 78 9 , , PUNCT ajst-29628 78 10 comberra comberra PROPN ajst-29628 78 11 , , PUNCT ajst-29628 78 12 hausdorff hausdorff NOUN ajst-29628 78 13 , , PUNCT ajst-29628 78 14 nprod nprod ADJ ajst-29628 78 15 , , PUNCT ajst-29628 78 16 and and CCONJ ajst-29628 78 17 se se X ajst-29628 78 18 algorithms algorithm NOUN ajst-29628 78 19 to to PART ajst-29628 78 20 study study VERB ajst-29628 78 21 the the DET ajst-29628 78 22 changing change VERB ajst-29628 78 23 trends trend NOUN ajst-29628 78 24 of of ADP ajst-29628 78 25 matching match VERB ajst-29628 78 26 values value NOUN ajst-29628 78 27 . . PUNCT ajst-29628 79 1 figure figure NOUN ajst-29628 79 2 2 2 NUM ajst-29628 79 3 . . PUNCT ajst-29628 79 4 sample sample NOUN ajst-29628 79 5 dynamometer dynamometer NOUN ajst-29628 79 6 card card NOUN ajst-29628 79 7 b b NOUN ajst-29628 79 8 figure figure NOUN ajst-29628 79 9 3 3 NUM ajst-29628 79 10 . . PUNCT ajst-29628 79 11 waiting wait VERB ajst-29628 79 12 for for ADP ajst-29628 79 13 recognizing recognize VERB ajst-29628 79 14 dynamometer dynamometer NOUN ajst-29628 79 15 card card NOUN ajst-29628 79 16 a a DET ajst-29628 79 17 3.1 3.1 NUM ajst-29628 79 18 . . PUNCT ajst-29628 80 1 vector vector NOUN ajst-29628 80 2 algorithm algorithm NOUN ajst-29628 80 3 the the DET ajst-29628 80 4 indicator indicator NOUN ajst-29628 80 5 diagram diagram NOUN ajst-29628 80 6 to to PART ajst-29628 80 7 be be AUX ajst-29628 80 8 identified identify VERB ajst-29628 80 9 and and CCONJ ajst-29628 80 10 the the DET ajst-29628 80 11 sample sample NOUN ajst-29628 80 12 indicator indicator NOUN ajst-29628 80 13 diagram diagram NOUN ajst-29628 80 14 are be AUX ajst-29628 80 15 represented represent VERB ajst-29628 80 16 by by ADP ajst-29628 80 17 2n 2n ADJ ajst-29628 80 18 dimensional dimensional ADJ ajst-29628 80 19 vectors vector NOUN ajst-29628 80 20 , , PUNCT ajst-29628 80 21 and and CCONJ ajst-29628 80 22 their their PRON ajst-29628 80 23 matching match VERB ajst-29628 80 24 algorithm algorithm NOUN ajst-29628 80 25 is be AUX ajst-29628 80 26 the the DET ajst-29628 80 27 dot dot NOUN ajst-29628 80 28 product product NOUN ajst-29628 80 29 of of ADP ajst-29628 80 30 the the DET ajst-29628 80 31 two two NUM ajst-29628 80 32 , , PUNCT ajst-29628 80 33 which which PRON ajst-29628 80 34 is be AUX ajst-29628 80 35 the the DET ajst-29628 80 36 cosine cosine ADJ ajst-29628 80 37 value value NOUN ajst-29628 80 38 of of ADP ajst-29628 80 39 the the DET ajst-29628 80 40 vector vector NOUN ajst-29628 80 41 angle angle NOUN ajst-29628 80 42 . . PUNCT ajst-29628 81 1 𝑅 𝑅 PROPN ajst-29628 81 2 𝐴 𝐴 PROPN ajst-29628 81 3 , , PUNCT ajst-29628 81 4 𝐡 𝐡 PROPN ajst-29628 81 5 𝐴 𝐴 PROPN ajst-29628 81 6 β‹… β‹… PROPN ajst-29628 81 7 𝐡 𝐡 PROPN ajst-29628 81 8 ( ( PUNCT ajst-29628 81 9 5 5 NUM ajst-29628 81 10 ) ) PUNCT ajst-29628 81 11 3.2 3.2 NUM ajst-29628 81 12 . . PUNCT ajst-29628 82 1 cor cor PROPN ajst-29628 82 2 algorithm algorithm PROPN ajst-29628 82 3 cross cross PROPN ajst-29628 82 4 - - ADJ ajst-29628 82 5 correlation correlation ADJ ajst-29628 82 6 algorithm algorithm NOUN ajst-29628 82 7 . . PUNCT ajst-29628 83 1 𝑅 𝑅 PROPN ajst-29628 83 2 𝐴 𝐴 PROPN ajst-29628 83 3 , , PUNCT ajst-29628 83 4 𝐡 𝐡 PROPN ajst-29628 83 5 βˆ‘ βˆ‘ PUNCT ajst-29628 83 6 β€Š β€Š SPACE ajst-29628 83 7 βˆ‘ βˆ‘ ADP ajst-29628 83 8 β€Š β€Š SPACE ajst-29628 83 9 βˆ‘ βˆ‘ ADV ajst-29628 83 10 β€Š β€Š SPACE ajst-29628 83 11 ( ( PUNCT ajst-29628 83 12 6 6 NUM ajst-29628 83 13 ) ) PUNCT ajst-29628 83 14 3.3 3.3 NUM ajst-29628 83 15 . . PUNCT ajst-29628 84 1 mad mad ADJ ajst-29628 84 2 algorithm algorithm NOUN ajst-29628 84 3 mean mean VERB ajst-29628 84 4 absolute absolute ADJ ajst-29628 84 5 difference difference NOUN ajst-29628 84 6 algorithm algorithm NOUN ajst-29628 84 7 . . PUNCT ajst-29628 85 1 𝑅 𝑅 PROPN ajst-29628 85 2 𝐴 𝐴 PROPN ajst-29628 85 3 , , PUNCT ajst-29628 85 4 𝐡 𝐡 NOUN ajst-29628 85 5 1 1 NUM ajst-29628 85 6 1 1 NUM ajst-29628 85 7 𝑁 𝑁 PROPN ajst-29628 85 8 β€Š β€Š SPACE ajst-29628 85 9 |𝑦 |𝑦 X ajst-29628 86 1 π‘₯ π‘₯ PROPN ajst-29628 86 2 𝑦 𝑦 NOUN ajst-29628 86 3 π‘₯ π‘₯ X ajst-29628 86 4 | | INTJ ajst-29628 86 5 ( ( PUNCT ajst-29628 86 6 7 7 NUM ajst-29628 86 7 ) ) PUNCT ajst-29628 86 8 3.4 3.4 NUM ajst-29628 86 9 . . PUNCT ajst-29628 87 1 msd msd NOUN ajst-29628 87 2 algorithm algorithm NOUN ajst-29628 87 3 mean mean VERB ajst-29628 87 4 square square ADJ ajst-29628 87 5 deviation deviation NOUN ajst-29628 87 6 algorithm algorithm NOUN ajst-29628 87 7 . . PUNCT ajst-29628 88 1 𝑅 𝑅 PROPN ajst-29628 88 2 𝐴 𝐴 PROPN ajst-29628 88 3 , , PUNCT ajst-29628 88 4 𝐡 𝐡 NOUN ajst-29628 88 5 1 1 NUM ajst-29628 88 6 1 1 NUM ajst-29628 88 7 𝑁 𝑁 PROPN ajst-29628 88 8 β€Š β€Š SPACE ajst-29628 88 9 𝑦 𝑦 NOUN ajst-29628 88 10 π‘₯ π‘₯ PROPN ajst-29628 88 11 𝑦 𝑦 NUM ajst-29628 88 12 π‘₯ π‘₯ X ajst-29628 88 13 ( ( PUNCT ajst-29628 88 14 8) 8) NUM ajst-29628 88 15 3.5 3.5 NUM ajst-29628 88 16 . . PUNCT ajst-29628 89 1 camberra camberra PROPN ajst-29628 89 2 algorithm algorithm PROPN ajst-29628 89 3 the the DET ajst-29628 89 4 camberra camberra NOUN ajst-29628 89 5 distance distance NOUN ajst-29628 89 6 between between ADP ajst-29628 89 7 the the DET ajst-29628 89 8 identified identify VERB ajst-29628 89 9 indicator indicator NOUN ajst-29628 89 10 vector vector NOUN ajst-29628 89 11 and and CCONJ ajst-29628 89 12 the the DET ajst-29628 89 13 sample sample NOUN ajst-29628 89 14 indicator indicator NOUN ajst-29628 89 15 vector vector NOUN ajst-29628 89 16 can can AUX ajst-29628 89 17 be be AUX ajst-29628 89 18 used use VERB ajst-29628 89 19 as as ADP ajst-29628 89 20 a a DET ajst-29628 89 21 distance distance NOUN ajst-29628 89 22 measure measure NOUN ajst-29628 89 23 between between ADP ajst-29628 89 24 the the DET ajst-29628 89 25 two two NUM ajst-29628 89 26 feature feature NOUN ajst-29628 89 27 vectors vector NOUN ajst-29628 89 28 . . PUNCT ajst-29628 90 1 𝑅 𝑅 PROPN ajst-29628 90 2 𝐴 𝐴 PROPN ajst-29628 90 3 , , PUNCT ajst-29628 90 4 𝐡 𝐡 PROPN ajst-29628 90 5 1 1 NUM ajst-29628 90 6 βˆ‘ βˆ‘ NOUN ajst-29628 90 7 β€Š β€Š SPACE ajst-29628 90 8 |𝑦 |𝑦 X ajst-29628 90 9 π‘₯ π‘₯ PROPN ajst-29628 90 10 𝑦 𝑦 NOUN ajst-29628 90 11 π‘₯ π‘₯ X ajst-29628 90 12 | | ADV ajst-29628 90 13 βˆ‘ βˆ‘ PUNCT ajst-29628 90 14 β€Š β€Š SPACE ajst-29628 90 15 |𝑦 |𝑦 X ajst-29628 90 16 π‘₯ π‘₯ PROPN ajst-29628 90 17 𝑦 𝑦 NOUN ajst-29628 90 18 π‘₯ π‘₯ X ajst-29628 91 1 | | INTJ ajst-29628 91 2 ( ( PUNCT ajst-29628 91 3 9 9 NUM ajst-29628 91 4 ) ) PUNCT ajst-29628 91 5 3.6 3.6 NUM ajst-29628 91 6 . . PUNCT ajst-29628 92 1 se se PROPN ajst-29628 92 2 algorithm algorithm PROPN ajst-29628 92 3 standard standard ADJ ajst-29628 92 4 error error NOUN ajst-29628 92 5 algorithm algorithm NOUN ajst-29628 92 6 . . PUNCT ajst-29628 93 1 𝑅 𝑅 PROPN ajst-29628 93 2 𝐴 𝐴 PROPN ajst-29628 93 3 , , PUNCT ajst-29628 93 4 𝐡 𝐡 NOUN ajst-29628 93 5 1 1 NUM ajst-29628 93 6 1 1 NUM ajst-29628 93 7 𝑁 𝑁 PROPN ajst-29628 93 8 β€Š β€Š SPACE ajst-29628 93 9 𝑦 𝑦 NOUN ajst-29628 93 10 π‘₯ π‘₯ PROPN ajst-29628 93 11 𝑦 𝑦 NUM ajst-29628 93 12 π‘₯ π‘₯ X ajst-29628 93 13 ( ( PUNCT ajst-29628 93 14 10 10 NUM ajst-29628 93 15 ) ) PUNCT ajst-29628 93 16 3.7 3.7 NUM ajst-29628 93 17 . . PUNCT ajst-29628 94 1 hausdorff hausdorff NOUN ajst-29628 94 2 algorithm algorithm PROPN ajst-29628 94 3 the the DET ajst-29628 94 4 hausdorff hausdorff NOUN ajst-29628 94 5 distance distance NOUN ajst-29628 94 6 is be AUX ajst-29628 94 7 defined define VERB ajst-29628 94 8 by by ADP ajst-29628 94 9 a a DET ajst-29628 94 10 general general ADJ ajst-29628 94 11 mathematical mathematical ADJ ajst-29628 94 12 formula formula NOUN ajst-29628 94 13 , , PUNCT ajst-29628 94 14 which which PRON ajst-29628 94 15 describes describe VERB ajst-29628 94 16 a a DET ajst-29628 94 17 measure measure NOUN ajst-29628 94 18 of of ADP ajst-29628 94 19 the the DET ajst-29628 94 20 similarity similarity NOUN ajst-29628 94 21 between between ADP ajst-29628 94 22 two two NUM ajst-29628 94 23 sets set NOUN ajst-29628 94 24 of of ADP ajst-29628 94 25 points point NOUN ajst-29628 94 26 . . PUNCT ajst-29628 95 1 it it PRON ajst-29628 95 2 is be AUX ajst-29628 95 3 a a DET ajst-29628 95 4 definition definition NOUN ajst-29628 95 5 of of ADP ajst-29628 95 6 the the DET ajst-29628 95 7 distance distance NOUN ajst-29628 95 8 between between ADP ajst-29628 95 9 two two NUM ajst-29628 95 10 sets set NOUN ajst-29628 95 11 of of ADP ajst-29628 95 12 points point NOUN ajst-29628 95 13 . . PUNCT ajst-29628 96 1 𝑅 𝑅 NOUN ajst-29628 96 2 𝑦 𝑦 PROPN ajst-29628 96 3 , , PUNCT ajst-29628 96 4 𝑦 𝑦 NOUN ajst-29628 96 5 1 1 NUM ajst-29628 96 6 π‘šπ‘Žπ‘₯ π‘šπ‘Žπ‘₯ NOUN ajst-29628 96 7 𝑑 𝑑 PROPN ajst-29628 96 8 𝑦 𝑦 PROPN ajst-29628 96 9 , , PUNCT ajst-29628 96 10 𝑦 𝑦 NOUN ajst-29628 96 11 , , PUNCT ajst-29628 96 12 𝑑 𝑑 PROPN ajst-29628 96 13 𝑦 𝑦 PROPN ajst-29628 96 14 , , PUNCT ajst-29628 96 15 𝑦 𝑦 PROPN ajst-29628 96 16 𝑑 𝑑 NOUN ajst-29628 96 17 maxmin maxmin PROPN ajst-29628 96 18 ∈ ∈ PROPN ajst-29628 96 19 ∈ ∈ PROPN ajst-29628 96 20 ‖𝑦 ‖𝑦 VERB ajst-29628 96 21 𝑦 𝑦 NOUN ajst-29628 96 22 β€– β€– PROPN ajst-29628 96 23 𝑑 𝑑 PROPN ajst-29628 96 24 maximin maximin NOUN ajst-29628 96 25 ∈ ∈ PROPN ajst-29628 96 26 ∈ ∈ PROPN ajst-29628 96 27 ‖𝑦 ‖𝑦 VERB ajst-29628 97 1 𝑦 𝑦 NOUN ajst-29628 97 2 β€– β€– PROPN ajst-29628 97 3 ( ( PUNCT ajst-29628 97 4 11 11 NUM ajst-29628 97 5 ) ) PUNCT ajst-29628 97 6 3.8 3.8 NUM ajst-29628 97 7 . . PUNCT ajst-29628 98 1 nprod nprod PROPN ajst-29628 98 2 algorithm algorithm PROPN ajst-29628 98 3 normalized normalize VERB ajst-29628 98 4 product product NOUN ajst-29628 98 5 correlation correlation NOUN ajst-29628 98 6 algorithm algorithm NOUN ajst-29628 98 7 . . PUNCT ajst-29628 99 1 𝑅 𝑅 PROPN ajst-29628 99 2 𝐴 𝐴 PROPN ajst-29628 99 3 , , PUNCT ajst-29628 99 4 𝐡 𝐡 PROPN ajst-29628 99 5 βˆ‘ βˆ‘ PUNCT ajst-29628 99 6 β€Š β€Š SPACE ajst-29628 99 7 βˆ‘ βˆ‘ ADP ajst-29628 99 8 β€Š β€Š SPACE ajst-29628 99 9 βˆ‘ βˆ‘ ADV ajst-29628 99 10 β€Š β€Š SPACE ajst-29628 99 11 ( ( PUNCT ajst-29628 99 12 12 12 NUM ajst-29628 99 13 ) ) PUNCT ajst-29628 99 14 in in ADP ajst-29628 99 15 equations equation NOUN ajst-29628 99 16 ( ( PUNCT ajst-29628 99 17 5 5 NUM ajst-29628 99 18 ) ) PUNCT ajst-29628 99 19 to to ADP ajst-29628 99 20 ( ( PUNCT ajst-29628 99 21 12 12 NUM ajst-29628 99 22 ) ) PUNCT ajst-29628 99 23 , , PUNCT ajst-29628 99 24 𝑦 𝑦 PRON ajst-29628 99 25 , , PUNCT ajst-29628 99 26 𝑦 𝑦 PRON ajst-29628 99 27 the the DET ajst-29628 99 28 mean mean ADJ ajst-29628 99 29 values value NOUN ajst-29628 99 30 of of ADP ajst-29628 99 31 datasets dataset NOUN ajst-29628 99 32 a a PRON ajst-29628 99 33 and and CCONJ ajst-29628 99 34 b b NOUN ajst-29628 99 35 respectively respectively ADV ajst-29628 99 36 ; ; PUNCT ajst-29628 99 37 n n PROPN ajst-29628 99 38 1 1 NUM ajst-29628 99 39 , , PUNCT ajst-29628 99 40 2 2 NUM ajst-29628 99 41 , , PUNCT ajst-29628 99 42 3 3 NUM ajst-29628 99 43 ... ... PUNCT ajst-29628 99 44 , , PUNCT ajst-29628 99 45 where where SCONJ ajst-29628 99 46 n n X ajst-29628 99 47 is be AUX ajst-29628 99 48 the the DET ajst-29628 99 49 number number NOUN ajst-29628 99 50 of of ADP ajst-29628 99 51 fluctuating fluctuate VERB ajst-29628 99 52 points point NOUN ajst-29628 99 53 ; ; PUNCT ajst-29628 99 54 β€– β€– PROPN ajst-29628 99 55 β‹… β‹… PROPN ajst-29628 99 56 β€–is β€–is PROPN ajst-29628 99 57 the the DET ajst-29628 99 58 distance distance NOUN ajst-29628 99 59 norm norm NOUN ajst-29628 99 60 of of ADP ajst-29628 99 61 datasets dataset NOUN ajst-29628 99 62 a a PRON ajst-29628 99 63 and and CCONJ ajst-29628 99 64 b b NOUN ajst-29628 99 65 e.g. e.g. ADJ ajst-29628 99 66 , , PUNCT ajst-29628 99 67 l2 l2 NOUN ajst-29628 99 68 or or CCONJ ajst-29628 99 69 euclidean euclidean ADJ ajst-29628 99 70 distance distance NOUN ajst-29628 99 71 . . PUNCT ajst-29628 100 1 323 323 NUM ajst-29628 100 2 according accord VERB ajst-29628 100 3 to to ADP ajst-29628 100 4 the the DET ajst-29628 100 5 above above ADJ ajst-29628 100 6 algorithm algorithm NOUN ajst-29628 100 7 , , PUNCT ajst-29628 100 8 a a DET ajst-29628 100 9 similarity similarity NOUN ajst-29628 100 10 curve curve NOUN ajst-29628 100 11 can can AUX ajst-29628 100 12 be be AUX ajst-29628 100 13 drawn draw VERB ajst-29628 100 14 . . PUNCT ajst-29628 101 1 the the DET ajst-29628 101 2 relationship relationship NOUN ajst-29628 101 3 curve curve NOUN ajst-29628 101 4 between between ADP ajst-29628 101 5 similarity similarity NOUN ajst-29628 101 6 and and CCONJ ajst-29628 101 7 fluctuation fluctuation NOUN ajst-29628 101 8 points point NOUN ajst-29628 101 9 of of ADP ajst-29628 101 10 the the DET ajst-29628 101 11 above above ADJ ajst-29628 101 12 algorithm algorithm NOUN ajst-29628 101 13 is be AUX ajst-29628 101 14 shown show VERB ajst-29628 101 15 in in ADP ajst-29628 101 16 figure figure NOUN ajst-29628 101 17 4 4 NUM ajst-29628 101 18 . . PUNCT ajst-29628 101 19 table table NOUN ajst-29628 101 20 1 1 NUM ajst-29628 101 21 shows show VERB ajst-29628 101 22 the the DET ajst-29628 101 23 similarity similarity NOUN ajst-29628 101 24 values value NOUN ajst-29628 101 25 of of ADP ajst-29628 101 26 the the DET ajst-29628 101 27 above above ADJ ajst-29628 101 28 algorithm algorithm NOUN ajst-29628 101 29 . . PUNCT ajst-29628 102 1 figure figure NOUN ajst-29628 102 2 4 4 NUM ajst-29628 102 3 . . PUNCT ajst-29628 102 4 relation relation NOUN ajst-29628 102 5 curves curve NOUN ajst-29628 102 6 of of ADP ajst-29628 102 7 similarity similarity NOUN ajst-29628 102 8 and and CCONJ ajst-29628 102 9 fluctuation fluctuation NOUN ajst-29628 102 10 points point NOUN ajst-29628 102 11 indifferent indifferent ADJ ajst-29628 102 12 algorithms algorithm NOUN ajst-29628 102 13 table table NOUN ajst-29628 102 14 1 1 NUM ajst-29628 102 15 . . PUNCT ajst-29628 102 16 similarity similarity NOUN ajst-29628 102 17 value value NOUN ajst-29628 102 18 of of ADP ajst-29628 102 19 different different ADJ ajst-29628 102 20 algorithms algorithm NOUN ajst-29628 102 21 as as SCONJ ajst-29628 102 22 shown show VERB ajst-29628 102 23 in in ADP ajst-29628 102 24 figure figure NOUN ajst-29628 102 25 4 4 NUM ajst-29628 102 26 and and CCONJ ajst-29628 102 27 table table NOUN ajst-29628 102 28 1 1 NUM ajst-29628 102 29 , , PUNCT ajst-29628 102 30 without without ADP ajst-29628 102 31 applying apply VERB ajst-29628 102 32 point point NOUN ajst-29628 102 33 fluctuations fluctuation NOUN ajst-29628 102 34 , , PUNCT ajst-29628 102 35 datasets dataset VERB ajst-29628 102 36 a a PRON ajst-29628 102 37 and and CCONJ ajst-29628 102 38 b b NOUN ajst-29628 102 39 are be AUX ajst-29628 102 40 completely completely ADV ajst-29628 102 41 similar similar ADJ ajst-29628 102 42 , , PUNCT ajst-29628 102 43 the the DET ajst-29628 102 44 similarity similarity NOUN ajst-29628 102 45 of of ADP ajst-29628 102 46 vector vector NOUN ajst-29628 102 47 , , PUNCT ajst-29628 102 48 mad mad ADJ ajst-29628 102 49 , , PUNCT ajst-29628 102 50 msd msd PROPN ajst-29628 102 51 , , PUNCT ajst-29628 102 52 camberra camberra PROPN ajst-29628 102 53 , , PUNCT ajst-29628 102 54 se se X ajst-29628 102 55 , , PUNCT ajst-29628 102 56 hausdorff hausdorff NOUN ajst-29628 102 57 , , PUNCT ajst-29628 102 58 and and CCONJ ajst-29628 102 59 nprod nprod ADJ ajst-29628 102 60 algorithms algorithms NOUN ajst-29628 102 61 is be AUX ajst-29628 102 62 all all PRON ajst-29628 102 63 1 1 NUM ajst-29628 102 64 , , PUNCT ajst-29628 102 65 while while SCONJ ajst-29628 102 66 the the DET ajst-29628 102 67 similarity similarity NOUN ajst-29628 102 68 of of ADP ajst-29628 102 69 cor cor PROPN ajst-29628 102 70 algorithm algorithm PROPN ajst-29628 102 71 is be AUX ajst-29628 102 72 an an DET ajst-29628 102 73 uncertain uncertain ADJ ajst-29628 102 74 value value NOUN ajst-29628 102 75 . . PUNCT ajst-29628 103 1 as as SCONJ ajst-29628 103 2 the the DET ajst-29628 103 3 number number NOUN ajst-29628 103 4 of of ADP ajst-29628 103 5 fluctuation fluctuation NOUN ajst-29628 103 6 points point NOUN ajst-29628 103 7 in in ADP ajst-29628 103 8 dataset dataset NOUN ajst-29628 103 9 a a DET ajst-29628 103 10 gradually gradually ADV ajst-29628 103 11 increases increase NOUN ajst-29628 103 12 , , PUNCT ajst-29628 103 13 it it PRON ajst-29628 103 14 indicates indicate VERB ajst-29628 103 15 that that SCONJ ajst-29628 103 16 the the DET ajst-29628 103 17 degree degree NOUN ajst-29628 103 18 of of ADP ajst-29628 103 19 difference difference NOUN ajst-29628 103 20 between between ADP ajst-29628 103 21 the the DET ajst-29628 103 22 identified identify VERB ajst-29628 103 23 indicator indicator NOUN ajst-29628 103 24 diagram diagram NOUN ajst-29628 103 25 a a PRON ajst-29628 103 26 and and CCONJ ajst-29628 103 27 the the DET ajst-29628 103 28 sample sample NOUN ajst-29628 103 29 indicator indicator NOUN ajst-29628 103 30 diagram diagram PROPN ajst-29628 103 31 b b PROPN ajst-29628 103 32 will will AUX ajst-29628 103 33 gradually gradually ADV ajst-29628 103 34 increase increase VERB ajst-29628 103 35 , , PUNCT ajst-29628 103 36 that that ADV ajst-29628 103 37 is is ADV ajst-29628 103 38 , , PUNCT ajst-29628 103 39 the the DET ajst-29628 103 40 degree degree NOUN ajst-29628 103 41 of of ADP ajst-29628 103 42 dissimilarity dissimilarity NOUN ajst-29628 103 43 between between ADP ajst-29628 103 44 a a PRON ajst-29628 103 45 and and CCONJ ajst-29628 103 46 b b NOUN ajst-29628 103 47 will will AUX ajst-29628 103 48 increase increase VERB ajst-29628 103 49 . . PUNCT ajst-29628 104 1 research research NOUN ajst-29628 104 2 has have AUX ajst-29628 104 3 shown show VERB ajst-29628 104 4 that that PRON ajst-29628 104 5 . . PUNCT ajst-29628 105 1 ( ( PUNCT ajst-29628 105 2 1 1 X ajst-29628 105 3 ) ) PUNCT ajst-29628 105 4 as as SCONJ ajst-29628 105 5 the the DET ajst-29628 105 6 degree degree NOUN ajst-29628 105 7 of of ADP ajst-29628 105 8 difference difference NOUN ajst-29628 105 9 between between ADP ajst-29628 105 10 datasets dataset NOUN ajst-29628 105 11 a a PRON ajst-29628 105 12 and and CCONJ ajst-29628 105 13 b b NOUN ajst-29628 105 14 gradually gradually ADV ajst-29628 105 15 increases increase VERB ajst-29628 105 16 , , PUNCT ajst-29628 105 17 the the DET ajst-29628 105 18 similarity similarity NOUN ajst-29628 105 19 changes change NOUN ajst-29628 105 20 of of ADP ajst-29628 105 21 vector vector NOUN ajst-29628 105 22 , , PUNCT ajst-29628 105 23 cor cor PROPN ajst-29628 105 24 , , PUNCT ajst-29628 105 25 msd msd PROPN ajst-29628 105 26 , , PUNCT ajst-29628 105 27 and and CCONJ ajst-29628 105 28 nprod nprod NOUN ajst-29628 105 29 are be AUX ajst-29628 105 30 very very ADV ajst-29628 105 31 small small ADJ ajst-29628 105 32 , , PUNCT ajst-29628 105 33 and and CCONJ ajst-29628 105 34 the the DET ajst-29628 105 35 difference difference NOUN ajst-29628 105 36 in in ADP ajst-29628 105 37 similarity similarity NOUN ajst-29628 105 38 can can AUX ajst-29628 105 39 not not PART ajst-29628 105 40 reflect reflect VERB ajst-29628 105 41 the the DET ajst-29628 105 42 degree degree NOUN ajst-29628 105 43 of of ADP ajst-29628 105 44 difference difference NOUN ajst-29628 105 45 between between ADP ajst-29628 105 46 the the DET ajst-29628 105 47 identified identify VERB ajst-29628 105 48 indicator indicator NOUN ajst-29628 105 49 diagram diagram NOUN ajst-29628 105 50 a a PRON ajst-29628 105 51 and and CCONJ ajst-29628 105 52 the the DET ajst-29628 105 53 sample sample NOUN ajst-29628 105 54 indicator indicator PROPN ajst-29628 105 55 diagram diagram PROPN ajst-29628 105 56 b. b. PROPN ajst-29628 106 1 this this PRON ajst-29628 106 2 indicates indicate VERB ajst-29628 106 3 that that SCONJ ajst-29628 106 4 these these DET ajst-29628 106 5 four four NUM ajst-29628 106 6 algorithms algorithm NOUN ajst-29628 106 7 have have VERB ajst-29628 106 8 low low ADJ ajst-29628 106 9 sensitivity sensitivity NOUN ajst-29628 106 10 to to ADP ajst-29628 106 11 local local ADJ ajst-29628 106 12 fluctuations fluctuation NOUN ajst-29628 106 13 in in ADP ajst-29628 106 14 the the DET ajst-29628 106 15 graph graph NOUN ajst-29628 106 16 and and CCONJ ajst-29628 106 17 low low ADJ ajst-29628 106 18 reliability reliability NOUN ajst-29628 106 19 . . PUNCT ajst-29628 107 1 when when SCONJ ajst-29628 107 2 the the DET ajst-29628 107 3 fluctuation fluctuation NOUN ajst-29628 107 4 of of ADP ajst-29628 107 5 the the DET ajst-29628 107 6 indicator indicator NOUN ajst-29628 107 7 diagram diagram NOUN ajst-29628 107 8 a a PRON ajst-29628 107 9 to to PART ajst-29628 107 10 be be AUX ajst-29628 107 11 identified identify VERB ajst-29628 107 12 is be AUX ajst-29628 107 13 significant significant ADJ ajst-29628 107 14 , , PUNCT ajst-29628 107 15 it it PRON ajst-29628 107 16 clearly clearly ADV ajst-29628 107 17 indicates indicate VERB ajst-29628 107 18 that that SCONJ ajst-29628 107 19 the the DET ajst-29628 107 20 indicator indicator NOUN ajst-29628 107 21 diagram diagram VERB ajst-29628 107 22 a a PRON ajst-29628 107 23 to to PART ajst-29628 107 24 be be AUX ajst-29628 107 25 identified identify VERB ajst-29628 107 26 is be AUX ajst-29628 107 27 not not PART ajst-29628 107 28 similar similar ADJ ajst-29628 107 29 to to ADP ajst-29628 107 30 the the DET ajst-29628 107 31 sample sample NOUN ajst-29628 107 32 indicator indicator PROPN ajst-29628 107 33 diagram diagram PROPN ajst-29628 107 34 b. b. PROPN ajst-29628 107 35 however however ADV ajst-29628 107 36 , , PUNCT ajst-29628 107 37 the the DET ajst-29628 107 38 matching match VERB ajst-29628 107 39 values value NOUN ajst-29628 107 40 of of ADP ajst-29628 107 41 vector vector NOUN ajst-29628 107 42 , , PUNCT ajst-29628 107 43 cor cor PROPN ajst-29628 107 44 , , PUNCT ajst-29628 107 45 msd msd PROPN ajst-29628 107 46 , , PUNCT ajst-29628 107 47 and and CCONJ ajst-29628 107 48 nprod nprod NOUN ajst-29628 107 49 are be AUX ajst-29628 107 50 still still ADV ajst-29628 107 51 equal equal ADJ ajst-29628 107 52 to to ADP ajst-29628 107 53 0.977 0.977 NUM ajst-29628 107 54 , , PUNCT ajst-29628 107 55 0.987 0.987 NUM ajst-29628 107 56 , , PUNCT ajst-29628 107 57 0.957 0.957 NUM ajst-29628 107 58 , , PUNCT ajst-29628 107 59 and and CCONJ ajst-29628 107 60 0.933 0.933 NUM ajst-29628 107 61 , , PUNCT ajst-29628 107 62 respectively respectively ADV ajst-29628 107 63 . . PUNCT ajst-29628 108 1 in in ADP ajst-29628 108 2 actual actual ADJ ajst-29628 108 3 discrimination discrimination NOUN ajst-29628 108 4 , , PUNCT ajst-29628 108 5 this this PRON ajst-29628 108 6 may may AUX ajst-29628 108 7 lead lead VERB ajst-29628 108 8 to to ADP ajst-29628 108 9 incorrect incorrect ADJ ajst-29628 108 10 identification identification NOUN ajst-29628 108 11 . . PUNCT ajst-29628 109 1 ( ( PUNCT ajst-29628 109 2 2 2 X ajst-29628 109 3 ) ) PUNCT ajst-29628 109 4 as as ADP ajst-29628 109 5 the the DET ajst-29628 109 6 number number NOUN ajst-29628 109 7 of of ADP ajst-29628 109 8 fluctuation fluctuation NOUN ajst-29628 109 9 points point NOUN ajst-29628 109 10 increases increase NOUN ajst-29628 109 11 , , PUNCT ajst-29628 109 12 the the DET ajst-29628 109 13 hausdorff hausdorff NOUN ajst-29628 109 14 similarity similarity NOUN ajst-29628 109 15 value value NOUN ajst-29628 109 16 no no ADV ajst-29628 109 17 longer long ADV ajst-29628 109 18 changes change NOUN ajst-29628 109 19 , , PUNCT ajst-29628 109 20 as as SCONJ ajst-29628 109 21 shown show VERB ajst-29628 109 22 in in ADP ajst-29628 109 23 figure figure NOUN ajst-29628 109 24 4 4 NUM ajst-29628 109 25 and and CCONJ ajst-29628 109 26 table table NOUN ajst-29628 109 27 1 1 NUM ajst-29628 109 28 . . PUNCT ajst-29628 110 1 this this PRON ajst-29628 110 2 is be AUX ajst-29628 110 3 because because SCONJ ajst-29628 110 4 the the DET ajst-29628 110 5 degree degree NOUN ajst-29628 110 6 of of ADP ajst-29628 110 7 difference difference NOUN ajst-29628 110 8 between between ADP ajst-29628 110 9 the the DET ajst-29628 110 10 two two NUM ajst-29628 110 11 datasets dataset NOUN ajst-29628 110 12 a a PRON ajst-29628 110 13 and and CCONJ ajst-29628 110 14 b b NOUN ajst-29628 110 15 is be AUX ajst-29628 110 16 determined determine VERB ajst-29628 110 17 by by ADP ajst-29628 110 18 the the DET ajst-29628 110 19 hausdorff hausdorff NOUN ajst-29628 110 20 distance distance NOUN ajst-29628 110 21 of of ADP ajst-29628 110 22 the the DET ajst-29628 110 23 least least ADV ajst-29628 110 24 similar similar ADJ ajst-29628 110 25 point point NOUN ajst-29628 110 26 . . PUNCT ajst-29628 111 1 once once SCONJ ajst-29628 111 2 the the DET ajst-29628 111 3 hausdorff hausdorff NOUN ajst-29628 111 4 distance distance NOUN ajst-29628 111 5 of of ADP ajst-29628 111 6 the the DET ajst-29628 111 7 newly newly ADV ajst-29628 111 8 added add VERB ajst-29628 111 9 wave wave NOUN ajst-29628 111 10 point point NOUN ajst-29628 111 11 is be AUX ajst-29628 111 12 not not PART ajst-29628 111 13 greater great ADJ ajst-29628 111 14 than than ADP ajst-29628 111 15 the the DET ajst-29628 111 16 distance distance NOUN ajst-29628 111 17 of of ADP ajst-29628 111 18 that that DET ajst-29628 111 19 point point NOUN ajst-29628 111 20 , , PUNCT ajst-29628 111 21 its its PRON ajst-29628 111 22 similarity similarity NOUN ajst-29628 111 23 will will AUX ajst-29628 111 24 no no ADV ajst-29628 111 25 longer long ADV ajst-29628 111 26 change change VERB ajst-29628 111 27 . . PUNCT ajst-29628 112 1 therefore therefore ADV ajst-29628 112 2 , , PUNCT ajst-29628 112 3 the the DET ajst-29628 112 4 hausdorff hausdorff NOUN ajst-29628 112 5 algorithm algorithm NOUN ajst-29628 112 6 is be AUX ajst-29628 112 7 not not PART ajst-29628 112 8 suitable suitable ADJ ajst-29628 112 9 for for ADP ajst-29628 112 10 discriminating discriminate VERB ajst-29628 112 11 overall overall ADJ ajst-29628 112 12 similarity similarity NOUN ajst-29628 112 13 between between ADP ajst-29628 112 14 two two NUM ajst-29628 112 15 datasets dataset NOUN ajst-29628 112 16 a a PRON ajst-29628 112 17 and and CCONJ ajst-29628 112 18 b. b. PROPN ajst-29628 112 19 ( ( PUNCT ajst-29628 112 20 3 3 NUM ajst-29628 112 21 ) ) PUNCT ajst-29628 112 22 as as SCONJ ajst-29628 112 23 the the DET ajst-29628 112 24 degree degree NOUN ajst-29628 112 25 of of ADP ajst-29628 112 26 difference difference NOUN ajst-29628 112 27 between between ADP ajst-29628 112 28 datasets dataset NOUN ajst-29628 112 29 a a PRON ajst-29628 112 30 and and CCONJ ajst-29628 112 31 b b NOUN ajst-29628 112 32 gradually gradually ADV ajst-29628 112 33 increases increase VERB ajst-29628 112 34 , , PUNCT ajst-29628 112 35 the the DET ajst-29628 112 36 similarity similarity NOUN ajst-29628 112 37 changes change VERB ajst-29628 112 38 between between ADP ajst-29628 112 39 mad mad ADJ ajst-29628 112 40 and and CCONJ ajst-29628 112 41 camberra camberra NOUN ajst-29628 112 42 basically basically ADV ajst-29628 112 43 reflect reflect VERB ajst-29628 112 44 the the DET ajst-29628 112 45 degree degree NOUN ajst-29628 112 46 of of ADP ajst-29628 112 47 difference difference NOUN ajst-29628 112 48 between between ADP ajst-29628 112 49 datasets dataset NOUN ajst-29628 112 50 a a PRON ajst-29628 112 51 and and CCONJ ajst-29628 112 52 b. b. PROPN ajst-29628 112 53 ( ( PUNCT ajst-29628 112 54 4 4 X ajst-29628 112 55 ) ) PUNCT ajst-29628 112 56 the the DET ajst-29628 112 57 similarity similarity NOUN ajst-29628 112 58 change change NOUN ajst-29628 112 59 of of ADP ajst-29628 112 60 se se X ajst-29628 112 61 can can AUX ajst-29628 112 62 well well ADV ajst-29628 112 63 reflect reflect VERB ajst-29628 112 64 the the DET ajst-29628 112 65 degree degree NOUN ajst-29628 112 66 of of ADP ajst-29628 112 67 difference difference NOUN ajst-29628 112 68 between between ADP ajst-29628 112 69 datasets dataset NOUN ajst-29628 112 70 a a PRON ajst-29628 112 71 and and CCONJ ajst-29628 112 72 b. b. NOUN ajst-29628 112 73 this this DET ajst-29628 112 74 algorithm algorithm NOUN ajst-29628 112 75 is be AUX ajst-29628 112 76 highly highly ADV ajst-29628 112 77 sensitive sensitive ADJ ajst-29628 112 78 to to ADP ajst-29628 112 79 local local ADJ ajst-29628 112 80 fluctuations fluctuation NOUN ajst-29628 112 81 in in ADP ajst-29628 112 82 graphics graphic NOUN ajst-29628 112 83 . . PUNCT ajst-29628 113 1 figure figure VERB ajst-29628 113 2 4 4 NUM ajst-29628 113 3 and and CCONJ ajst-29628 113 4 table table NOUN ajst-29628 113 5 1 1 NUM ajst-29628 113 6 indicate indicate VERB ajst-29628 113 7 that that SCONJ ajst-29628 113 8 the the DET ajst-29628 113 9 reliability reliability NOUN ajst-29628 113 10 of of ADP ajst-29628 113 11 the the DET ajst-29628 113 12 se se PROPN ajst-29628 113 13 algorithm algorithm PROPN ajst-29628 113 14 is be AUX ajst-29628 113 15 the the DET ajst-29628 113 16 highest high ADJ ajst-29628 113 17 among among ADP ajst-29628 113 18 all all DET ajst-29628 113 19 matching match VERB ajst-29628 113 20 algorithms algorithm NOUN ajst-29628 113 21 . . PUNCT ajst-29628 114 1 figure figure NOUN ajst-29628 114 2 5 5 NUM ajst-29628 114 3 shows show VERB ajst-29628 114 4 the the DET ajst-29628 114 5 displacement displacement NOUN ajst-29628 114 6 load load NOUN ajst-29628 114 7 dynamometer dynamometer NOUN ajst-29628 114 8 diagram diagram NOUN ajst-29628 114 9 of of ADP ajst-29628 114 10 the the DET ajst-29628 114 11 oil oil NOUN ajst-29628 114 12 well well ADV ajst-29628 114 13 , , PUNCT ajst-29628 114 14 the the DET ajst-29628 114 15 sample sample NOUN ajst-29628 114 16 dynamometer dynamometer NOUN ajst-29628 114 17 diagram diagram PROPN ajst-29628 114 18 nwc nwc PROPN ajst-29628 114 19 is be AUX ajst-29628 114 20 the the DET ajst-29628 114 21 dynamometer dynamometer NOUN ajst-29628 114 22 diagram diagram NOUN ajst-29628 114 23 under under ADP ajst-29628 114 24 standard standard ADJ ajst-29628 114 25 operating operating NOUN ajst-29628 114 26 conditions condition NOUN ajst-29628 114 27 of of ADP ajst-29628 114 28 the the DET ajst-29628 114 29 oil oil NOUN ajst-29628 114 30 well well NOUN ajst-29628 114 31 , , PUNCT ajst-29628 114 32 and and CCONJ ajst-29628 114 33 the the DET ajst-29628 114 34 to to PART ajst-29628 114 35 - - PUNCT ajst-29628 114 36 be be AUX ajst-29628 114 37 - - PUNCT ajst-29628 114 38 identified identify VERB ajst-29628 114 39 dynamometer dynamometer NOUN ajst-29628 114 40 diagram diagram NOUN ajst-29628 114 41 awc1 awc1 PROPN ajst-29628 114 42 - - PUNCT ajst-29628 114 43 7 7 NUM ajst-29628 114 44 is be AUX ajst-29628 114 45 the the DET ajst-29628 114 46 dynamometer dynamometer NOUN ajst-29628 114 47 diagram diagram NOUN ajst-29628 114 48 under under ADP ajst-29628 114 49 non non ADJ ajst-29628 114 50 - - ADJ ajst-29628 114 51 standard standard ADJ ajst-29628 114 52 operating operating NOUN ajst-29628 114 53 conditions condition NOUN ajst-29628 114 54 of of ADP ajst-29628 114 55 the the DET ajst-29628 114 56 oil oil NOUN ajst-29628 114 57 well well NOUN ajst-29628 114 58 . . PUNCT ajst-29628 115 1 the the DET ajst-29628 115 2 difference difference NOUN ajst-29628 115 3 between between ADP ajst-29628 115 4 awc1 awc1 PROPN ajst-29628 115 5 - - PUNCT ajst-29628 115 6 7 7 NUM ajst-29628 115 7 and and CCONJ ajst-29628 115 8 nwc nwc PROPN ajst-29628 115 9 gradually gradually ADV ajst-29628 115 10 increases increase VERB ajst-29628 115 11 . . PUNCT ajst-29628 116 1 apply apply VERB ajst-29628 116 2 vector vector NOUN ajst-29628 116 3 , , PUNCT ajst-29628 116 4 msd msd PROPN ajst-29628 116 5 , , PUNCT ajst-29628 116 6 cor cor PROPN ajst-29628 116 7 , , PUNCT ajst-29628 116 8 mad mad ADJ ajst-29628 116 9 , , PUNCT ajst-29628 116 10 camberra camberra NOUN ajst-29628 116 11 , , PUNCT ajst-29628 116 12 hausdorff hausdorff NOUN ajst-29628 116 13 , , PUNCT ajst-29628 116 14 nprod nprod ADJ ajst-29628 116 15 , , PUNCT ajst-29628 116 16 and and CCONJ ajst-29628 116 17 se se X ajst-29628 116 18 algorithms algorithm NOUN ajst-29628 116 19 to to PART ajst-29628 116 20 perform perform VERB ajst-29628 116 21 similarity similarity NOUN ajst-29628 116 22 recognition recognition NOUN ajst-29628 116 23 on on ADP ajst-29628 116 24 nwc nwc PROPN ajst-29628 116 25 and and CCONJ ajst-29628 116 26 awc1 awc1 PROPN ajst-29628 116 27 - - PUNCT ajst-29628 116 28 7 7 PROPN ajst-29628 116 29 . . PUNCT ajst-29628 117 1 the the DET ajst-29628 117 2 similarity similarity NOUN ajst-29628 117 3 relationship relationship NOUN ajst-29628 117 4 curve curve NOUN ajst-29628 117 5 between between ADP ajst-29628 117 6 nwc nwc PROPN ajst-29628 117 7 and and CCONJ ajst-29628 117 8 awc1 awc1 PROPN ajst-29628 117 9 - - PUNCT ajst-29628 117 10 7 7 NUM ajst-29628 117 11 of of ADP ajst-29628 117 12 the the DET ajst-29628 117 13 above above ADJ ajst-29628 117 14 algorithm algorithm NOUN ajst-29628 117 15 is be AUX ajst-29628 117 16 shown show VERB ajst-29628 117 17 in in ADP ajst-29628 117 18 figure figure NOUN ajst-29628 117 19 6 6 NUM ajst-29628 117 20 . . PUNCT ajst-29628 117 21 table table NOUN ajst-29628 117 22 2 2 NUM ajst-29628 117 23 shows show VERB ajst-29628 117 24 the the DET ajst-29628 117 25 324 324 NUM ajst-29628 117 26 similarity similarity NOUN ajst-29628 117 27 between between ADP ajst-29628 117 28 nwc nwc PROPN ajst-29628 117 29 and and CCONJ ajst-29628 117 30 awc1 awc1 PROPN ajst-29628 117 31 - - PUNCT ajst-29628 117 32 7 7 NUM ajst-29628 117 33 . . PUNCT ajst-29628 118 1 as as SCONJ ajst-29628 118 2 shown show VERB ajst-29628 118 3 in in ADP ajst-29628 118 4 figure figure NOUN ajst-29628 118 5 6 6 NUM ajst-29628 118 6 and and CCONJ ajst-29628 118 7 table table NOUN ajst-29628 118 8 2 2 NUM ajst-29628 118 9 , , PUNCT ajst-29628 118 10 when when SCONJ ajst-29628 118 11 the the DET ajst-29628 118 12 difference difference NOUN ajst-29628 118 13 between between ADP ajst-29628 118 14 the the DET ajst-29628 118 15 sample sample NOUN ajst-29628 118 16 dynamometer dynamometer NOUN ajst-29628 118 17 and and CCONJ ajst-29628 118 18 the the DET ajst-29628 118 19 dynamometer dynamometer NOUN ajst-29628 118 20 to to PART ajst-29628 118 21 be be AUX ajst-29628 118 22 identified identify VERB ajst-29628 118 23 gradually gradually ADV ajst-29628 118 24 increases increase VERB ajst-29628 118 25 , , PUNCT ajst-29628 118 26 we we PRON ajst-29628 118 27 can can AUX ajst-29628 118 28 draw draw VERB ajst-29628 118 29 the the DET ajst-29628 118 30 following following ADJ ajst-29628 118 31 conclusions conclusion NOUN ajst-29628 118 32 : : PUNCT ajst-29628 118 33 ( ( PUNCT ajst-29628 118 34 1 1 X ajst-29628 118 35 ) ) PUNCT ajst-29628 118 36 the the DET ajst-29628 118 37 similarity similarity NOUN ajst-29628 118 38 changes change NOUN ajst-29628 118 39 of of ADP ajst-29628 118 40 vector vector NOUN ajst-29628 118 41 , , PUNCT ajst-29628 118 42 msd msd NOUN ajst-29628 118 43 , , PUNCT ajst-29628 118 44 and and CCONJ ajst-29628 118 45 hausdorff hausdorff NOUN ajst-29628 118 46 are be AUX ajst-29628 118 47 small small ADJ ajst-29628 118 48 , , PUNCT ajst-29628 118 49 which which PRON ajst-29628 118 50 is be AUX ajst-29628 118 51 consistent consistent ADJ ajst-29628 118 52 with with ADP ajst-29628 118 53 the the DET ajst-29628 118 54 conclusion conclusion NOUN ajst-29628 118 55 of of ADP ajst-29628 118 56 point point NOUN ajst-29628 118 57 fluctuation fluctuation NOUN ajst-29628 118 58 , , PUNCT ajst-29628 118 59 indicating indicate VERB ajst-29628 118 60 that that SCONJ ajst-29628 118 61 the the DET ajst-29628 118 62 reliability reliability NOUN ajst-29628 118 63 of of ADP ajst-29628 118 64 the the DET ajst-29628 118 65 algorithm algorithm NOUN ajst-29628 118 66 is be AUX ajst-29628 118 67 not not PART ajst-29628 118 68 high high ADJ ajst-29628 118 69 . . PUNCT ajst-29628 119 1 ( ( PUNCT ajst-29628 119 2 2 2 X ajst-29628 119 3 ) ) PUNCT ajst-29628 119 4 the the DET ajst-29628 119 5 similarity similarity NOUN ajst-29628 119 6 between between ADP ajst-29628 119 7 cor cor PROPN ajst-29628 119 8 and and CCONJ ajst-29628 119 9 nprod nprod PROPN ajst-29628 119 10 varies vary VERB ajst-29628 119 11 greatly greatly ADV ajst-29628 119 12 , , PUNCT ajst-29628 119 13 which which PRON ajst-29628 119 14 is be AUX ajst-29628 119 15 inconsistent inconsistent ADJ ajst-29628 119 16 with with ADP ajst-29628 119 17 the the DET ajst-29628 119 18 results result NOUN ajst-29628 119 19 of of ADP ajst-29628 119 20 fluctuating fluctuate VERB ajst-29628 119 21 application application NOUN ajst-29628 119 22 points point NOUN ajst-29628 119 23 , , PUNCT ajst-29628 119 24 indicating indicate VERB ajst-29628 119 25 that that SCONJ ajst-29628 119 26 the the DET ajst-29628 119 27 reliability reliability NOUN ajst-29628 119 28 of of ADP ajst-29628 119 29 these these DET ajst-29628 119 30 two two NUM ajst-29628 119 31 algorithms algorithm NOUN ajst-29628 119 32 is be AUX ajst-29628 119 33 unstable unstable ADJ ajst-29628 119 34 , , PUNCT ajst-29628 119 35 and and CCONJ ajst-29628 119 36 the the DET ajst-29628 119 37 similarity similarity NOUN ajst-29628 119 38 between between ADP ajst-29628 119 39 cor cor PROPN ajst-29628 119 40 shows show VERB ajst-29628 119 41 non non ADJ ajst-29628 119 42 - - ADJ ajst-29628 119 43 monotonic monotonic ADJ ajst-29628 119 44 changes change NOUN ajst-29628 119 45 . . PUNCT ajst-29628 120 1 ( ( PUNCT ajst-29628 120 2 3 3 X ajst-29628 120 3 ) ) PUNCT ajst-29628 120 4 the the DET ajst-29628 120 5 conclusion conclusion NOUN ajst-29628 120 6 regarding regard VERB ajst-29628 120 7 the the DET ajst-29628 120 8 similarity similarity NOUN ajst-29628 120 9 changes change NOUN ajst-29628 120 10 and and CCONJ ajst-29628 120 11 application application NOUN ajst-29628 120 12 point point NOUN ajst-29628 120 13 fluctuations fluctuation NOUN ajst-29628 120 14 between between ADP ajst-29628 120 15 mad mad ADJ ajst-29628 120 16 and and CCONJ ajst-29628 120 17 camberra camberra NOUN ajst-29628 120 18 is be AUX ajst-29628 120 19 consistent consistent ADJ ajst-29628 120 20 . . PUNCT ajst-29628 121 1 ( ( PUNCT ajst-29628 121 2 4 4 X ajst-29628 121 3 ) ) PUNCT ajst-29628 121 4 the the DET ajst-29628 121 5 similarity similarity NOUN ajst-29628 121 6 of of ADP ajst-29628 121 7 se se X ajst-29628 121 8 changes change VERB ajst-29628 121 9 the the DET ajst-29628 121 10 most most ADJ ajst-29628 121 11 and and CCONJ ajst-29628 121 12 is be AUX ajst-29628 121 13 highly highly ADV ajst-29628 121 14 consistent consistent ADJ ajst-29628 121 15 with with ADP ajst-29628 121 16 the the DET ajst-29628 121 17 fluctuation fluctuation NOUN ajst-29628 121 18 of of ADP ajst-29628 121 19 the the DET ajst-29628 121 20 application application NOUN ajst-29628 121 21 point point NOUN ajst-29628 121 22 . . PUNCT ajst-29628 122 1 therefore therefore ADV ajst-29628 122 2 , , PUNCT ajst-29628 122 3 the the DET ajst-29628 122 4 se se PROPN ajst-29628 122 5 algorithm algorithm PROPN ajst-29628 122 6 has have VERB ajst-29628 122 7 high high ADJ ajst-29628 122 8 reliability reliability NOUN ajst-29628 122 9 . . PUNCT ajst-29628 123 1 figure figure NOUN ajst-29628 123 2 6 6 NUM ajst-29628 123 3 and and CCONJ ajst-29628 123 4 table table NOUN ajst-29628 123 5 2 2 NUM ajst-29628 123 6 indicate indicate VERB ajst-29628 123 7 that that SCONJ ajst-29628 123 8 the the DET ajst-29628 123 9 reliability reliability NOUN ajst-29628 123 10 of of ADP ajst-29628 123 11 the the DET ajst-29628 123 12 se se PROPN ajst-29628 123 13 algorithm algorithm PROPN ajst-29628 123 14 is be AUX ajst-29628 123 15 the the DET ajst-29628 123 16 highest high ADJ ajst-29628 123 17 among among ADP ajst-29628 123 18 all all DET ajst-29628 123 19 algorithms algorithm NOUN ajst-29628 123 20 . . PUNCT ajst-29628 124 1 figure figure NOUN ajst-29628 124 2 5 5 NUM ajst-29628 124 3 . . PUNCT ajst-29628 124 4 displacement displacement NOUN ajst-29628 124 5 - - PUNCT ajst-29628 124 6 load load NOUN ajst-29628 124 7 dynamometer dynamometer NOUN ajst-29628 124 8 card card NOUN ajst-29628 124 9 of of ADP ajst-29628 124 10 oil oil NOUN ajst-29628 124 11 well well NOUN ajst-29628 124 12 figure figure NOUN ajst-29628 124 13 6 6 NUM ajst-29628 124 14 . . PUNCT ajst-29628 125 1 the the DET ajst-29628 125 2 similarity similarity NOUN ajst-29628 125 3 curves curve NOUN ajst-29628 125 4 of of ADP ajst-29628 125 5 nwc nwc PROPN ajst-29628 125 6 and and CCONJ ajst-29628 125 7 awc1 awc1 PROPN ajst-29628 125 8 - - PUNCT ajst-29628 125 9 7 7 NUM ajst-29628 125 10 4 4 NUM ajst-29628 125 11 . . PUNCT ajst-29628 125 12 application application NOUN ajst-29628 125 13 examples example NOUN ajst-29628 125 14 nearly nearly ADV ajst-29628 125 15 10000 10000 NUM ajst-29628 125 16 dynamometer dynamometer NOUN ajst-29628 125 17 diagrams diagram NOUN ajst-29628 125 18 were be AUX ajst-29628 125 19 collected collect VERB ajst-29628 125 20 from from ADP ajst-29628 125 21 more more ADJ ajst-29628 125 22 than than ADP ajst-29628 125 23 1000 1000 NUM ajst-29628 125 24 wells well NOUN ajst-29628 125 25 in in ADP ajst-29628 125 26 the the DET ajst-29628 125 27 chuankou chuankou PROPN ajst-29628 125 28 oil oil NOUN ajst-29628 125 29 production production NOUN ajst-29628 125 30 plant plant NOUN ajst-29628 125 31 of of ADP ajst-29628 125 32 yanchang yanchang PROPN ajst-29628 125 33 oilfield oilfield PROPN ajst-29628 125 34 , , PUNCT ajst-29628 125 35 and and CCONJ ajst-29628 125 36 nearly nearly ADV ajst-29628 125 37 300 300 NUM ajst-29628 125 38 suspected suspect VERB ajst-29628 125 39 faulty faulty ADJ ajst-29628 125 40 pump pump NOUN ajst-29628 125 41 dynamometer dynamometer NOUN ajst-29628 125 42 diagrams diagram NOUN ajst-29628 125 43 were be AUX ajst-29628 125 44 selected select VERB ajst-29628 125 45 . . PUNCT ajst-29628 126 1 table table NOUN ajst-29628 126 2 3 3 NUM ajst-29628 126 3 shows show VERB ajst-29628 126 4 some some PRON ajst-29628 126 5 of of ADP ajst-29628 126 6 the the DET ajst-29628 126 7 main main ADJ ajst-29628 126 8 fault fault NOUN ajst-29628 126 9 types type NOUN ajst-29628 126 10 selected select VERB ajst-29628 126 11 . . PUNCT ajst-29628 127 1 the the DET ajst-29628 127 2 se se PROPN ajst-29628 127 3 algorithm algorithm PROPN ajst-29628 127 4 was be AUX ajst-29628 127 5 used use VERB ajst-29628 127 6 to to PART ajst-29628 127 7 perform perform VERB ajst-29628 127 8 similarity similarity NOUN ajst-29628 127 9 recognition recognition NOUN ajst-29628 127 10 between between ADP ajst-29628 127 11 the the DET ajst-29628 127 12 indicator indicator NOUN ajst-29628 127 13 diagram diagram NOUN ajst-29628 127 14 to to PART ajst-29628 127 15 be be AUX ajst-29628 127 16 recognized recognize VERB ajst-29628 127 17 and and CCONJ ajst-29628 127 18 the the DET ajst-29628 127 19 established establish VERB ajst-29628 127 20 sample sample NOUN ajst-29628 127 21 indicator indicator NOUN ajst-29628 127 22 diagram diagram NOUN ajst-29628 127 23 database database NOUN ajst-29628 127 24 . . PUNCT ajst-29628 128 1 the the DET ajst-29628 128 2 recognition recognition NOUN ajst-29628 128 3 results result NOUN ajst-29628 128 4 are be AUX ajst-29628 128 5 shown show VERB ajst-29628 128 6 in in ADP ajst-29628 128 7 table table NOUN ajst-29628 128 8 3 3 NUM ajst-29628 128 9 , , PUNCT ajst-29628 128 10 and and CCONJ ajst-29628 128 11 the the DET ajst-29628 128 12 recognition recognition NOUN ajst-29628 128 13 success success NOUN ajst-29628 128 14 rate rate NOUN ajst-29628 128 15 reached reach VERB ajst-29628 128 16 100 100 NUM ajst-29628 128 17 % % NOUN ajst-29628 128 18 . . PUNCT ajst-29628 129 1 this this DET ajst-29628 129 2 algorithm algorithm NOUN ajst-29628 129 3 is be AUX ajst-29628 129 4 particularly particularly ADV ajst-29628 129 5 suitable suitable ADJ ajst-29628 129 6 for for ADP ajst-29628 129 7 identifying identify VERB ajst-29628 129 8 indicator indicator NOUN ajst-29628 129 9 diagrams diagram NOUN ajst-29628 129 10 with with ADP ajst-29628 129 11 slight slight ADJ ajst-29628 129 12 differences difference NOUN ajst-29628 129 13 . . PUNCT ajst-29628 130 1 table table NOUN ajst-29628 130 2 3 3 NUM ajst-29628 130 3 shows show VERB ajst-29628 130 4 the the DET ajst-29628 130 5 results result NOUN ajst-29628 130 6 of of ADP ajst-29628 130 7 identifying identify VERB ajst-29628 130 8 the the DET ajst-29628 130 9 standard standard ADJ ajst-29628 130 10 error error NOUN ajst-29628 130 11 of of ADP ajst-29628 130 12 oil oil NOUN ajst-29628 130 13 production production NOUN ajst-29628 130 14 conditions condition NOUN ajst-29628 130 15 . . PUNCT ajst-29628 131 1 325 325 NUM ajst-29628 131 2 table table NOUN ajst-29628 131 3 2 2 NUM ajst-29628 131 4 . . PUNCT ajst-29628 132 1 the the DET ajst-29628 132 2 similarity similarity NOUN ajst-29628 132 3 values value NOUN ajst-29628 132 4 of of ADP ajst-29628 132 5 nwc nwc PROPN ajst-29628 132 6 and and CCONJ ajst-29628 132 7 awc1 awc1 PROPN ajst-29628 132 8 - - PUNCT ajst-29628 132 9 7 7 NUM ajst-29628 132 10 table table NOUN ajst-29628 132 11 3 3 NUM ajst-29628 132 12 . . PUNCT ajst-29628 132 13 results result NOUN ajst-29628 132 14 of of ADP ajst-29628 132 15 production production NOUN ajst-29628 132 16 condition condition NOUN ajst-29628 132 17 recognition recognition NOUN ajst-29628 132 18 by by ADP ajst-29628 132 19 se se PROPN ajst-29628 132 20 algorithm algorithm PROPN ajst-29628 132 21 ( ( PUNCT ajst-29628 132 22 % % INTJ ajst-29628 132 23 ) ) PUNCT ajst-29628 132 24 failure failure NOUN ajst-29628 132 25 mode mode NOUN ajst-29628 132 26 similarity similarity NOUN ajst-29628 132 27 1 1 NUM ajst-29628 132 28 2 2 NUM ajst-29628 132 29 3 3 NUM ajst-29628 132 30 4 4 NUM ajst-29628 132 31 5 5 NUM ajst-29628 132 32 6 6 NUM ajst-29628 132 33 7 7 NUM ajst-29628 132 34 8 8 NUM ajst-29628 132 35 9 9 NUM ajst-29628 132 36 10 10 NUM ajst-29628 132 37 11 11 NUM ajst-29628 132 38 12 12 NUM ajst-29628 132 39 1 1 NUM ajst-29628 132 40 . . PUNCT ajst-29628 132 41 fixed fix VERB ajst-29628 132 42 valve valve NOUN ajst-29628 132 43 leakage leakage NOUN ajst-29628 132 44 99.9 99.9 NUM ajst-29628 132 45 76.3 76.3 NUM ajst-29628 132 46 79.1 79.1 NUM ajst-29628 132 47 77.6 77.6 NUM ajst-29628 132 48 80.5 80.5 NUM ajst-29628 132 49 79.3 79.3 NUM ajst-29628 132 50 80.4 80.4 NUM ajst-29628 132 51 82.8 82.8 NUM ajst-29628 132 52 77.1 77.1 NUM ajst-29628 132 53 76.8 76.8 NUM ajst-29628 132 54 82.1 82.1 NUM ajst-29628 132 55 53.1 53.1 NUM ajst-29628 132 56 2 2 NUM ajst-29628 132 57 . . PUNCT ajst-29628 132 58 moving move VERB ajst-29628 132 59 valve valve NOUN ajst-29628 132 60 leakage leakage NOUN ajst-29628 132 61 82.9 82.9 NUM ajst-29628 132 62 99.7 99.7 NUM ajst-29628 132 63 73.1 73.1 NUM ajst-29628 132 64 91.0 91.0 NUM ajst-29628 132 65 75.1 75.1 NUM ajst-29628 132 66 86.6 86.6 NUM ajst-29628 132 67 69.9 69.9 NUM ajst-29628 132 68 80.1 80.1 NUM ajst-29628 132 69 82.1 82.1 NUM ajst-29628 132 70 73.3 73.3 NUM ajst-29628 132 71 83.0 83.0 NUM ajst-29628 132 72 57.2 57.2 NUM ajst-29628 132 73 3 3 NUM ajst-29628 132 74 . . PUNCT ajst-29628 132 75 tubing tubing NOUN ajst-29628 132 76 breakage breakage NOUN ajst-29628 132 77 78.6 78.6 NUM ajst-29628 132 78 72.6 72.6 NUM ajst-29628 132 79 97.8 97.8 NUM ajst-29628 132 80 72.4 72.4 NUM ajst-29628 132 81 82.5 82.5 NUM ajst-29628 132 82 72.7 72.7 NUM ajst-29628 132 83 59.3 59.3 NUM ajst-29628 132 84 79.6 79.6 NUM ajst-29628 132 85 71.8 71.8 NUM ajst-29628 132 86 76.9 76.9 NUM ajst-29628 132 87 74.4 74.4 NUM ajst-29628 132 88 59.2 59.2 NUM ajst-29628 132 89 4 4 NUM ajst-29628 132 90 . . PUNCT ajst-29628 132 91 sucker sucker NOUN ajst-29628 132 92 rod rod VERB ajst-29628 132 93 upper upper ADJ ajst-29628 132 94 breakage breakage NOUN ajst-29628 132 95 77.7 77.7 NUM ajst-29628 132 96 91.0 91.0 NUM ajst-29628 132 97 72.9 72.9 NUM ajst-29628 132 98 98.6 98.6 NUM ajst-29628 132 99 71.8 71.8 NUM ajst-29628 132 100 86.3 86.3 NUM ajst-29628 132 101 71.9 71.9 NUM ajst-29628 132 102 76.3 76.3 NUM ajst-29628 132 103 84.0 84.0 NUM ajst-29628 132 104 72.3 72.3 NUM ajst-29628 132 105 79.8 79.8 NUM ajst-29628 132 106 59.0 59.0 NUM ajst-29628 132 107 5 5 NUM ajst-29628 132 108 . . PUNCT ajst-29628 132 109 tubing tubing NOUN ajst-29628 132 110 bending bend VERB ajst-29628 132 111 80.2 80.2 NUM ajst-29628 132 112 74.9 74.9 NUM ajst-29628 132 113 82.6 82.6 NUM ajst-29628 132 114 71.7 71.7 NUM ajst-29628 132 115 99.2 99.2 NUM ajst-29628 132 116 75.1 75.1 NUM ajst-29628 132 117 59.0 59.0 NUM ajst-29628 132 118 84.6 84.6 NUM ajst-29628 132 119 71.6 71.6 NUM ajst-29628 132 120 78.7 78.7 NUM ajst-29628 132 121 76.9 76.9 NUM ajst-29628 132 122 56.5 56.5 NUM ajst-29628 132 123 6 6 NUM ajst-29628 132 124 . . PUNCT ajst-29628 133 1 sand sand NOUN ajst-29628 133 2 lock lock NOUN ajst-29628 133 3 79.1 79.1 NUM ajst-29628 133 4 80.8 80.8 NUM ajst-29628 133 5 74.3 74.3 NUM ajst-29628 133 6 85.2 85.2 NUM ajst-29628 133 7 75.5 75.5 NUM ajst-29628 133 8 96.5 96.5 NUM ajst-29628 133 9 74.2 74.2 NUM ajst-29628 133 10 81.5 81.5 NUM ajst-29628 133 11 85.8 85.8 NUM ajst-29628 133 12 78.1 78.1 NUM ajst-29628 133 13 86.2 86.2 NUM ajst-29628 133 14 61.7 61.7 NUM ajst-29628 133 15 7 7 NUM ajst-29628 133 16 . . PUNCT ajst-29628 133 17 gas gas NOUN ajst-29628 133 18 interference interference NOUN ajst-29628 133 19 61.9 61.9 NUM ajst-29628 133 20 70.1 70.1 NUM ajst-29628 133 21 59.9 59.9 NUM ajst-29628 133 22 72.2 72.2 NUM ajst-29628 133 23 59.3 59.3 NUM ajst-29628 133 24 74.4 74.4 NUM ajst-29628 133 25 98.4 98.4 NUM ajst-29628 133 26 63.3 63.3 NUM ajst-29628 133 27 77.9 77.9 NUM ajst-29628 133 28 67.6 67.6 NUM ajst-29628 133 29 69.1 69.1 NUM ajst-29628 133 30 66.1 66.1 NUM ajst-29628 133 31 8 8 NUM ajst-29628 133 32 . . PUNCT ajst-29628 134 1 gearbox gearbox PROPN ajst-29628 134 2 wear wear VERB ajst-29628 134 3 83 83 NUM ajst-29628 134 4 78 78 NUM ajst-29628 134 5 81 81 NUM ajst-29628 134 6 77 77 NUM ajst-29628 134 7 85 85 NUM ajst-29628 134 8 82 82 NUM ajst-29628 134 9 64 64 NUM ajst-29628 134 10 98 98 NUM ajst-29628 134 11 79 79 NUM ajst-29628 134 12 86 86 NUM ajst-29628 134 13 83 83 NUM ajst-29628 134 14 57.9 57.9 NUM ajst-29628 134 15 9 9 NUM ajst-29628 134 16 . . PUNCT ajst-29628 134 17 belt belt NOUN ajst-29628 134 18 slippage slippage NOUN ajst-29628 134 19 76.7 76.7 NUM ajst-29628 134 20 81.8 81.8 NUM ajst-29628 134 21 72.1 72.1 NUM ajst-29628 134 22 83.9 83.9 NUM ajst-29628 134 23 71.7 71.7 NUM ajst-29628 134 24 85.8 85.8 NUM ajst-29628 134 25 78.2 78.2 NUM ajst-29628 134 26 77.0 77.0 NUM ajst-29628 134 27 98.8 98.8 NUM ajst-29628 134 28 76.3 76.3 NUM ajst-29628 134 29 80.0 80.0 NUM ajst-29628 134 30 65.6 65.6 NUM ajst-29628 134 31 10 10 NUM ajst-29628 134 32 . . PUNCT ajst-29628 135 1 gas gas NOUN ajst-29628 135 2 lock lock NOUN ajst-29628 135 3 73.8 73.8 NUM ajst-29628 135 4 71.2 71.2 NUM ajst-29628 135 5 74.7 74.7 NUM ajst-29628 135 6 70.9 70.9 NUM ajst-29628 135 7 75.4 75.4 NUM ajst-29628 135 8 75.6 75.6 NUM ajst-29628 135 9 68.6 68.6 NUM ajst-29628 135 10 79.7 79.7 NUM ajst-29628 135 11 75.4 75.4 NUM ajst-29628 135 12 95.4 95.4 NUM ajst-29628 135 13 79.7 79.7 NUM ajst-29628 135 14 61.5 61.5 NUM ajst-29628 135 15 11 11 NUM ajst-29628 135 16 . . PUNCT ajst-29628 136 1 subsurface subsurface NOUN ajst-29628 136 2 pump pump NOUN ajst-29628 136 3 collision collision NOUN ajst-29628 136 4 82.1 82.1 NUM ajst-29628 136 5 82.9 82.9 NUM ajst-29628 136 6 74.9 74.9 NUM ajst-29628 136 7 79.8 79.8 NUM ajst-29628 136 8 77.1 77.1 NUM ajst-29628 136 9 85.8 85.8 NUM ajst-29628 136 10 68.8 68.8 NUM ajst-29628 136 11 83.4 83.4 NUM ajst-29628 136 12 80.0 80.0 NUM ajst-29628 136 13 81.7 81.7 NUM ajst-29628 136 14 99.1 99.1 NUM ajst-29628 136 15 62.6 62.6 NUM ajst-29628 136 16 12 12 NUM ajst-29628 136 17 . . PUNCT ajst-29628 137 1 stuck stick VERB ajst-29628 137 2 pump pump VERB ajst-29628 137 3 52.9 52.9 NUM ajst-29628 137 4 57.1 57.1 NUM ajst-29628 137 5 59.1 59.1 NUM ajst-29628 137 6 58.9 58.9 NUM ajst-29628 137 7 56.2 56.2 NUM ajst-29628 137 8 60.8 60.8 NUM ajst-29628 137 9 65.5 65.5 NUM ajst-29628 137 10 56.5 56.5 NUM ajst-29628 137 11 65.2 65.2 NUM ajst-29628 137 12 61.9 61.9 NUM ajst-29628 137 13 62.2 62.2 NUM ajst-29628 137 14 99.2 99.2 NUM ajst-29628 137 15 5 5 NUM ajst-29628 137 16 . . PUNCT ajst-29628 137 17 conclusions conclusion NOUN ajst-29628 137 18 for for ADP ajst-29628 137 19 the the DET ajst-29628 137 20 first first ADJ ajst-29628 137 21 time time NOUN ajst-29628 137 22 , , PUNCT ajst-29628 137 23 the the DET ajst-29628 137 24 se se PROPN ajst-29628 137 25 algorithm algorithm PROPN ajst-29628 137 26 was be AUX ajst-29628 137 27 proposed propose VERB ajst-29628 137 28 to to PART ajst-29628 137 29 achieve achieve VERB ajst-29628 137 30 accurate accurate ADJ ajst-29628 137 31 recognition recognition NOUN ajst-29628 137 32 of of ADP ajst-29628 137 33 oil oil NOUN ajst-29628 137 34 well well NOUN ajst-29628 137 35 conditions condition NOUN ajst-29628 137 36 , , PUNCT ajst-29628 137 37 and and CCONJ ajst-29628 137 38 the the DET ajst-29628 137 39 algorithm algorithm NOUN ajst-29628 137 40 was be AUX ajst-29628 137 41 compared compare VERB ajst-29628 137 42 and and CCONJ ajst-29628 137 43 analyzed analyze VERB ajst-29628 137 44 with with ADP ajst-29628 137 45 existing exist VERB ajst-29628 137 46 similarity similarity NOUN ajst-29628 137 47 recognition recognition NOUN ajst-29628 137 48 matching matching NOUN ajst-29628 137 49 algorithms algorithm NOUN ajst-29628 137 50 . . PUNCT ajst-29628 138 1 the the DET ajst-29628 138 2 argument argument NOUN ajst-29628 138 3 that that SCONJ ajst-29628 138 4 similarity similarity NOUN ajst-29628 138 5 matching matching NOUN ajst-29628 138 6 algorithms algorithm NOUN ajst-29628 138 7 have have AUX ajst-29628 138 8 a a DET ajst-29628 138 9 great great ADJ ajst-29628 138 10 correlation correlation NOUN ajst-29628 138 11 with with ADP ajst-29628 138 12 the the DET ajst-29628 138 13 degree degree NOUN ajst-29628 138 14 of of ADP ajst-29628 138 15 graphic graphic ADJ ajst-29628 138 16 differences difference NOUN ajst-29628 138 17 was be AUX ajst-29628 138 18 also also ADV ajst-29628 138 19 put put VERB ajst-29628 138 20 forward forward ADV ajst-29628 138 21 for for ADP ajst-29628 138 22 the the DET ajst-29628 138 23 first first ADJ ajst-29628 138 24 time time NOUN ajst-29628 138 25 , , PUNCT ajst-29628 138 26 and and CCONJ ajst-29628 138 27 the the DET ajst-29628 138 28 degree degree NOUN ajst-29628 138 29 of of ADP ajst-29628 138 30 correlation correlation NOUN ajst-29628 138 31 determines determine VERB ajst-29628 138 32 the the DET ajst-29628 138 33 superiority superiority NOUN ajst-29628 138 34 or or CCONJ ajst-29628 138 35 inferiority inferiority NOUN ajst-29628 138 36 of of ADP ajst-29628 138 37 the the DET ajst-29628 138 38 algorithm algorithm NOUN ajst-29628 138 39 . . PUNCT ajst-29628 139 1 algorithms algorithm NOUN ajst-29628 139 2 with with ADP ajst-29628 139 3 high high ADJ ajst-29628 139 4 correlation correlation NOUN ajst-29628 139 5 have have VERB ajst-29628 139 6 high high ADJ ajst-29628 139 7 sensitivity sensitivity NOUN ajst-29628 139 8 to to ADP ajst-29628 139 9 recognizing recognize VERB ajst-29628 139 10 graphics graphic NOUN ajst-29628 139 11 with with ADP ajst-29628 139 12 slight slight ADJ ajst-29628 139 13 differences difference NOUN ajst-29628 139 14 , , PUNCT ajst-29628 139 15 indicating indicate VERB ajst-29628 139 16 high high ADJ ajst-29628 139 17 accuracy accuracy NOUN ajst-29628 139 18 in in ADP ajst-29628 139 19 recognition recognition NOUN ajst-29628 139 20 . . PUNCT ajst-29628 140 1 on on ADP ajst-29628 140 2 the the DET ajst-29628 140 3 contrary contrary NOUN ajst-29628 140 4 , , PUNCT ajst-29628 140 5 algorithms algorithm NOUN ajst-29628 140 6 with with ADP ajst-29628 140 7 low low ADJ ajst-29628 140 8 correlation correlation NOUN ajst-29628 140 9 have have VERB ajst-29628 140 10 low low ADJ ajst-29628 140 11 sensitivity sensitivity NOUN ajst-29628 140 12 to to ADP ajst-29628 140 13 recognizing recognize VERB ajst-29628 140 14 graphics graphic NOUN ajst-29628 140 15 with with ADP ajst-29628 140 16 small small ADJ ajst-29628 140 17 differences difference NOUN ajst-29628 140 18 , , PUNCT ajst-29628 140 19 that that ADV ajst-29628 140 20 is is ADV ajst-29628 140 21 , , PUNCT ajst-29628 140 22 the the DET ajst-29628 140 23 accuracy accuracy NOUN ajst-29628 140 24 of of ADP ajst-29628 140 25 recognition recognition NOUN ajst-29628 140 26 is be AUX ajst-29628 140 27 low low ADJ ajst-29628 140 28 . . PUNCT ajst-29628 141 1 figures figure NOUN ajst-29628 141 2 4 4 NUM ajst-29628 141 3 , , PUNCT ajst-29628 141 4 6 6 NUM ajst-29628 141 5 , , PUNCT ajst-29628 141 6 table table NOUN ajst-29628 141 7 1 1 NUM ajst-29628 141 8 , , PUNCT ajst-29628 141 9 and and CCONJ ajst-29628 141 10 table table NOUN ajst-29628 141 11 2 2 NUM ajst-29628 141 12 fully fully ADV ajst-29628 141 13 demonstrate demonstrate VERB ajst-29628 141 14 this this DET ajst-29628 141 15 argument argument NOUN ajst-29628 141 16 . . PUNCT ajst-29628 142 1 the the DET ajst-29628 142 2 research research NOUN ajst-29628 142 3 results result NOUN ajst-29628 142 4 indicate indicate VERB ajst-29628 142 5 that that SCONJ ajst-29628 142 6 there there PRON ajst-29628 142 7 is be VERB ajst-29628 142 8 a a DET ajst-29628 142 9 high high ADJ ajst-29628 142 10 degree degree NOUN ajst-29628 142 11 of of ADP ajst-29628 142 12 correlation correlation NOUN ajst-29628 142 13 between between ADP ajst-29628 142 14 the the DET ajst-29628 142 15 se se PROPN ajst-29628 142 16 algorithm algorithm PROPN ajst-29628 142 17 and and CCONJ ajst-29628 142 18 the the DET ajst-29628 142 19 graphics graphic NOUN ajst-29628 142 20 , , PUNCT ajst-29628 142 21 and and CCONJ ajst-29628 142 22 the the DET ajst-29628 142 23 reliability reliability NOUN ajst-29628 142 24 of of ADP ajst-29628 142 25 this this DET ajst-29628 142 26 algorithm algorithm NOUN ajst-29628 142 27 is be AUX ajst-29628 142 28 the the DET ajst-29628 142 29 highest high ADJ ajst-29628 142 30 among among ADP ajst-29628 142 31 all all DET ajst-29628 142 32 algorithms algorithm NOUN ajst-29628 142 33 . . PUNCT ajst-29628 143 1 the the DET ajst-29628 143 2 application application NOUN ajst-29628 143 3 of of ADP ajst-29628 143 4 this this DET ajst-29628 143 5 algorithm algorithm NOUN ajst-29628 143 6 reduces reduce VERB ajst-29628 143 7 the the DET ajst-29628 143 8 probability probability NOUN ajst-29628 143 9 of of ADP ajst-29628 143 10 misjudging misjudge VERB ajst-29628 143 11 similar similar ADJ ajst-29628 143 12 working working NOUN ajst-29628 143 13 conditions condition NOUN ajst-29628 143 14 and and CCONJ ajst-29628 143 15 improves improve VERB ajst-29628 143 16 the the DET ajst-29628 143 17 accuracy accuracy NOUN ajst-29628 143 18 and and CCONJ ajst-29628 143 19 precision precision NOUN ajst-29628 143 20 of of ADP ajst-29628 143 21 recognition recognition NOUN ajst-29628 143 22 . . PUNCT ajst-29628 144 1 references reference NOUN ajst-29628 144 2 [ [ X ajst-29628 144 3 1 1 NUM ajst-29628 144 4 ] ] PUNCT ajst-29628 144 5 ding ding NOUN ajst-29628 144 6 yi yi PROPN ajst-29628 144 7 , , PUNCT ajst-29628 144 8 li li PROPN ajst-29628 144 9 xunming xunming PROPN ajst-29628 144 10 . . PUNCT ajst-29628 145 1 the the DET ajst-29628 145 2 research research NOUN ajst-29628 145 3 and and CCONJ ajst-29628 145 4 application application NOUN ajst-29628 145 5 of of ADP ajst-29628 145 6 the the DET ajst-29628 145 7 eigenvalue eigenvalue NOUN ajst-29628 145 8 extraction extraction NOUN ajst-29628 145 9 and and CCONJ ajst-29628 145 10 selection selection NOUN ajst-29628 145 11 in in ADP ajst-29628 145 12 oilfield oilfield NOUN ajst-29628 145 13 fault fault NOUN ajst-29628 145 14 diagnosis diagnosis NOUN ajst-29628 145 15 . . PUNCT ajst-29628 146 1 electronic electronic ADJ ajst-29628 146 2 design design NOUN ajst-29628 146 3 engineering engineering NOUN ajst-29628 146 4 , , PUNCT ajst-29628 146 5 2014 2014 NUM ajst-29628 146 6 ; ; PUNCT ajst-29628 146 7 22(17 22(17 NUM ajst-29628 146 8 ): ): PUNCT ajst-29628 146 9 148β€”150 148β€”150 NOUN ajst-29628 146 10 . . PUNCT ajst-29628 147 1 [ [ X ajst-29628 147 2 2 2 X ajst-29628 147 3 ] ] PUNCT ajst-29628 147 4 wang wang PROPN ajst-29628 147 5 xiufang xiufang PROPN ajst-29628 147 6 , , PUNCT ajst-29628 147 7 guan guan PROPN ajst-29628 147 8 chuang chuang PROPN ajst-29628 147 9 , , PUNCT ajst-29628 147 10 wang wang PROPN ajst-29628 147 11 zi zi PROPN ajst-29628 147 12 . . PUNCT ajst-29628 147 13 study study NOUN ajst-29628 147 14 on on ADP ajst-29628 147 15 entropybased entropybase VERB ajst-29628 147 16 grey grey ADJ ajst-29628 147 17 correlation correlation NOUN ajst-29628 147 18 fault fault NOUN ajst-29628 147 19 diagnosis diagnosis NOUN ajst-29628 147 20 of of ADP ajst-29628 147 21 oil oil NOUN ajst-29628 147 22 pumping pump VERB ajst-29628 147 23 well well ADJ ajst-29628 147 24 indicator indicator NOUN ajst-29628 147 25 diagram diagram PROPN ajst-29628 147 26 . . PUNCT ajst-29628 148 1 control control NOUN ajst-29628 148 2 and and CCONJ ajst-29628 148 3 instruments instrument NOUN ajst-29628 148 4 in in ADP ajst-29628 148 5 chemical chemical NOUN ajst-29628 148 6 industry industry NOUN ajst-29628 148 7 , , PUNCT ajst-29628 148 8 2013 2013 NUM ajst-29628 148 9 ; ; PUNCT ajst-29628 148 10 40 40 NUM ajst-29628 148 11 ( ( PUNCT ajst-29628 148 12 11):1370 11):1370 NUM ajst-29628 148 13 - - SYM ajst-29628 148 14 1373 1373 NUM ajst-29628 148 15 . . PUNCT ajst-29628 149 1 [ [ X ajst-29628 149 2 3 3 X ajst-29628 149 3 ] ] X ajst-29628 149 4 zhang zhang PROPN ajst-29628 149 5 qiang qiang PROPN ajst-29628 149 6 , , PUNCT ajst-29628 149 7 xu xu PROPN ajst-29628 149 8 shaohua shaohua PROPN ajst-29628 149 9 , , PUNCT ajst-29628 149 10 li li PROPN ajst-29628 149 11 panchi panchi PROPN ajst-29628 149 12 . . PUNCT ajst-29628 150 1 pumping pump VERB ajst-29628 150 2 unit unit NOUN ajst-29628 150 3 fault fault NOUN ajst-29628 150 4 diagnosis diagnosis NOUN ajst-29628 150 5 based base VERB ajst-29628 150 6 on on ADP ajst-29628 150 7 quantum quantum NOUN ajst-29628 150 8 shuffled shuffle VERB ajst-29628 150 9 frog frog NOUN ajst-29628 150 10 leaping leap VERB ajst-29628 150 11 algorithm algorithm NOUN ajst-29628 150 12 and and CCONJ ajst-29628 150 13 process process NOUN ajst-29628 150 14 neural neural ADJ ajst-29628 150 15 networks network NOUN ajst-29628 150 16 . . PUNCT ajst-29628 151 1 china china PROPN ajst-29628 151 2 mechanical mechanical PROPN ajst-29628 151 3 engineering engineering PROPN ajst-29628 151 4 , , PUNCT ajst-29628 151 5 2014 2014 NUM ajst-29628 151 6 ; ; PUNCT ajst-29628 151 7 25 25 NUM ajst-29628 151 8 ( ( PUNCT ajst-29628 151 9 12):1609-β€”1614 12):1609-β€”1614 NUM ajst-29628 151 10 . . PUNCT ajst-29628 152 1 [ [ X ajst-29628 152 2 4 4 NUM ajst-29628 152 3 ] ] X ajst-29628 152 4 wen wen PROPN ajst-29628 152 5 bilong bilong PROPN ajst-29628 152 6 , , PUNCT ajst-29628 152 7 wang wang PROPN ajst-29628 152 8 zhiqun zhiqun PROPN ajst-29628 152 9 , , PUNCT ajst-29628 152 10 jin jin NOUN ajst-29628 152 11 zongze zongze PROPN ajst-29628 152 12 , , PUNCT ajst-29628 152 13 et et PROPN ajst-29628 152 14 al al PROPN ajst-29628 152 15 . . PUNCT ajst-29628 152 16 diagnosis diagnosis NOUN ajst-29628 152 17 of of ADP ajst-29628 152 18 pumping pump VERB ajst-29628 152 19 unit unit NOUN ajst-29628 152 20 with with ADP ajst-29628 152 21 combing comb VERB ajst-29628 152 22 indicator indicator NOUN ajst-29628 152 23 diagram diagram NOUN ajst-29628 152 24 with with ADP ajst-29628 152 25 fuzzy fuzzy ADJ ajst-29628 152 26 neural neural ADJ ajst-29628 152 27 networks network NOUN ajst-29628 152 28 . . PUNCT ajst-29628 153 1 computer computer NOUN ajst-29628 153 2 systems system NOUN ajst-29628 153 3 & & CCONJ ajst-29628 153 4 applications application NOUN ajst-29628 153 5 , , PUNCT ajst-29628 153 6 2016 2016 NUM ajst-29628 153 7 ; ; PUNCT ajst-29628 153 8 25(1 25(1 NUM ajst-29628 153 9 ): ): PUNCT ajst-29628 153 10 121β€”125 121β€”125 NOUN ajst-29628 153 11 . . PUNCT ajst-29628 154 1 [ [ X ajst-29628 154 2 5 5 NUM ajst-29628 154 3 ] ] X ajst-29628 154 4 li li PROPN ajst-29628 154 5 chunsheng chunsheng PROPN ajst-29628 154 6 , , PUNCT ajst-29628 154 7 su su PROPN ajst-29628 154 8 xiaowei xiaowei PROPN ajst-29628 154 9 , , PUNCT ajst-29628 154 10 wei wei PROPN ajst-29628 154 11 jun jun PROPN ajst-29628 154 12 , , PUNCT ajst-29628 154 13 et et PROPN ajst-29628 154 14 al al PROPN ajst-29628 154 15 . . PROPN ajst-29628 154 16 research research NOUN ajst-29628 154 17 on on ADP ajst-29628 154 18 diagrams diagram NOUN ajst-29628 154 19 identification identification NOUN ajst-29628 154 20 of of ADP ajst-29628 154 21 pumping pump VERB ajst-29628 154 22 unit unit NOUN ajst-29628 154 23 based base VERB ajst-29628 154 24 on on ADP ajst-29628 154 25 support support NOUN ajst-29628 154 26 vector vector NOUN ajst-29628 154 27 machine machine NOUN ajst-29628 154 28 . . PUNCT ajst-29628 155 1 computer computer NOUN ajst-29628 155 2 systems system NOUN ajst-29628 155 3 & & CCONJ ajst-29628 155 4 applications application NOUN ajst-29628 155 5 , , PUNCT ajst-29628 155 6 2014 2014 NUM ajst-29628 155 7 ; ; PUNCT ajst-29628 155 8 24(8 24(8 NUM ajst-29628 155 9 ): ): PUNCT ajst-29628 155 10 215 215 NUM ajst-29628 155 11 - - SYM ajst-29628 155 12 218 218 NUM ajst-29628 155 13 . . PUNCT ajst-29628 156 1 [ [ X ajst-29628 156 2 6 6 NUM ajst-29628 156 3 ] ] X ajst-29628 156 4 lu lu PROPN ajst-29628 156 5 wentao wentao PROPN ajst-29628 156 6 , , PUNCT ajst-29628 156 7 wang wang PROPN ajst-29628 156 8 honglun honglun PROPN ajst-29628 156 9 , , PUNCT ajst-29628 156 10 liu liu PROPN ajst-29628 156 11 chang chang PROPN ajst-29628 156 12 , , PUNCT ajst-29628 156 13 et et PROPN ajst-29628 157 1 al al PROPN ajst-29628 157 2 . . PROPN ajst-29628 157 3 design design NOUN ajst-29628 157 4 and and CCONJ ajst-29628 157 5 simulation simulation NOUN ajst-29628 157 6 of of ADP ajst-29628 157 7 terrain terrain NOUN ajst-29628 157 8 matching matching NOUN ajst-29628 157 9 aided aid VERB ajst-29628 157 10 navigation navigation NOUN ajst-29628 157 11 system system NOUN ajst-29628 157 12 for for ADP ajst-29628 157 13 uavs uavs NOUN ajst-29628 157 14 . . PUNCT ajst-29628 158 1 electronics electronic NOUN ajst-29628 158 2 optics optics PROPN ajst-29628 158 3 & & CCONJ ajst-29628 158 4 control control PROPN ajst-29628 158 5 , , PUNCT ajst-29628 158 6 2014 2014 NUM ajst-29628 158 7 ; ; PUNCT ajst-29628 158 8 21(5):63β€”67 21(5):63β€”67 NUM ajst-29628 158 9 . . PUNCT ajst-29628 159 1 [ [ X ajst-29628 159 2 7 7 X ajst-29628 159 3 ] ] X ajst-29628 159 4 fan fan NOUN ajst-29628 159 5 chengxiao chengxiao PROPN ajst-29628 159 6 , , PUNCT ajst-29628 159 7 zhang zhang PROPN ajst-29628 159 8 ying ying PROPN ajst-29628 159 9 , , PUNCT ajst-29628 159 10 hu hu PROPN ajst-29628 159 11 zhiqian zhiqian PROPN ajst-29628 159 12 . . PUNCT ajst-29628 159 13 improving improve VERB ajst-29628 159 14 project project NOUN ajst-29628 159 15 research research NOUN ajst-29628 159 16 . . PUNCT ajst-29628 160 1 of of ADP ajst-29628 160 2 digital digital ADJ ajst-29628 160 3 map map NOUN ajst-29628 160 4 application application NOUN ajst-29628 160 5 arithmetic arithmetic ADJ ajst-29628 160 6 in in ADP ajst-29628 160 7 terrain terrain NOUN ajst-29628 160 8 matching match VERB ajst-29628 160 9 assist assist NOUN ajst-29628 160 10 navigation navigation NOUN ajst-29628 160 11 . . PUNCT ajst-29628 161 1 science science NOUN ajst-29628 161 2 of of ADP ajst-29628 161 3 surveying surveying NOUN ajst-29628 161 4 and and CCONJ ajst-29628 161 5 mapping mapping NOUN ajst-29628 161 6 , , PUNCT ajst-29628 161 7 2010 2010 NUM ajst-29628 161 8 ; ; PUNCT ajst-29628 161 9 35(4 35(4 NUM ajst-29628 161 10 ): ): PUNCT ajst-29628 161 11 89 89 NUM ajst-29628 161 12 - - SYM ajst-29628 161 13 90 90 NUM ajst-29628 161 14 . . PUNCT ajst-29628 162 1 [ [ X ajst-29628 162 2 8 8 NUM ajst-29628 162 3 ] ] X ajst-29628 162 4 li li PROPN ajst-29628 162 5 yingnan yingnan PROPN ajst-29628 162 6 , , PUNCT ajst-29628 162 7 wang wang PROPN ajst-29628 162 8 yong yong PROPN ajst-29628 162 9 , , PUNCT ajst-29628 162 10 yan yan PROPN ajst-29628 162 11 zhiyu zhiyu PROPN ajst-29628 162 12 . . PUNCT ajst-29628 163 1 high high ADJ ajst-29628 163 2 - - PUNCT ajst-29628 163 3 speed speed NOUN ajst-29628 163 4 terrain terrain NOUN ajst-29628 163 5 matching matching NOUN ajst-29628 163 6 algorithm algorithm NOUN ajst-29628 163 7 and and CCONJ ajst-29628 163 8 its its PRON ajst-29628 163 9 realization realization NOUN ajst-29628 163 10 on on ADP ajst-29628 163 11 fpga fpga PROPN ajst-29628 163 12 . . PUNCT ajst-29628 164 1 journal journal PROPN ajst-29628 164 2 of of ADP ajst-29628 164 3 henan henan PROPN ajst-29628 164 4 institute institute PROPN ajst-29628 164 5 of of ADP ajst-29628 164 6 engineering engineering PROPN ajst-29628 164 7 , , PUNCT ajst-29628 164 8 2012 2012 NUM ajst-29628 164 9 ; ; PUNCT ajst-29628 164 10 24(4 24(4 NUM ajst-29628 164 11 ): ): PUNCT ajst-29628 164 12 57β€”62 57β€”62 X ajst-29628 164 13 . . PUNCT ajst-29628 165 1 [ [ X ajst-29628 165 2 9 9 NUM ajst-29628 165 3 ] ] X ajst-29628 165 4 liu liu PROPN ajst-29628 165 5 hong hong PROPN ajst-29628 165 6 , , PUNCT ajst-29628 165 7 gao gao PROPN ajst-29628 165 8 yongqi yongqi PROPN ajst-29628 165 9 , , PUNCT ajst-29628 165 10 shen shen PROPN ajst-29628 165 11 jian jian PROPN ajst-29628 165 12 . . PUNCT ajst-29628 166 1 underwater underwater ADJ ajst-29628 166 2 terrain terrain NOUN ajst-29628 166 3 matching matching NOUN ajst-29628 166 4 techniques technique NOUN ajst-29628 166 5 based base VERB ajst-29628 166 6 on on ADP ajst-29628 166 7 combination combination NOUN ajst-29628 166 8 of of ADP ajst-29628 166 9 pmf pmf NOUN ajst-29628 166 10 and and CCONJ ajst-29628 166 11 326 326 NUM ajst-29628 166 12 tercom tercom NOUN ajst-29628 166 13 algorithms algorithm NOUN ajst-29628 166 14 . . PUNCT ajst-29628 167 1 torpedo torpedo PROPN ajst-29628 167 2 technology technology NOUN ajst-29628 167 3 , , PUNCT ajst-29628 167 4 2012 2012 NUM ajst-29628 167 5 ; ; PUNCT ajst-29628 167 6 20(6 20(6 NUM ajst-29628 167 7 ): ): PUNCT ajst-29628 167 8 437β€”442 437β€”442 PROPN ajst-29628 167 9 . . PUNCT ajst-29628 168 1 [ [ X ajst-29628 168 2 10 10 NUM ajst-29628 168 3 ] ] X ajst-29628 168 4 ye ye PROPN ajst-29628 168 5 bin bin PROPN ajst-29628 168 6 , , PUNCT ajst-29628 168 7 hu hu PROPN ajst-29628 168 8 xiulin xiulin PROPN ajst-29628 168 9 , , PUNCT ajst-29628 168 10 zhang zhang PROPN ajst-29628 168 11 yunyu yunyu PROPN ajst-29628 168 12 , , PUNCT ajst-29628 168 13 et et PROPN ajst-29628 168 14 al al PROPN ajst-29628 168 15 . . PROPN ajst-29628 169 1 3d 3d NUM ajst-29628 169 2 terrain terrain NOUN ajst-29628 169 3 matching matching NOUN ajst-29628 169 4 algorithm algorithm NOUN ajst-29628 169 5 and and CCONJ ajst-29628 169 6 performance performance NOUN ajst-29628 169 7 analysis analysis NOUN ajst-29628 169 8 based base VERB ajst-29628 169 9 on on ADP ajst-29628 169 10 3d 3d NUM ajst-29628 169 11 zernike zernike ADJ ajst-29628 169 12 moments moment NOUN ajst-29628 169 13 . . PUNCT ajst-29628 170 1 journal journal PROPN ajst-29628 170 2 of of ADP ajst-29628 170 3 astronautics astronautic NOUN ajst-29628 170 4 , , PUNCT ajst-29628 170 5 2007;28(5):1241β€”1244 2007;28(5):1241β€”1244 NUM ajst-29628 170 6 . . PUNCT ajst-29628 171 1 [ [ X ajst-29628 171 2 11 11 NUM ajst-29628 171 3 ] ] X ajst-29628 171 4 ma ma PROPN ajst-29628 171 5 danshan danshan PROPN ajst-29628 171 6 , , PUNCT ajst-29628 171 7 wang wang PROPN ajst-29628 171 8 minghai minghai PROPN ajst-29628 171 9 , , PUNCT ajst-29628 171 10 nie nie PROPN ajst-29628 171 11 feng feng PROPN ajst-29628 171 12 , , PUNCT ajst-29628 171 13 et et PROPN ajst-29628 171 14 al al PROPN ajst-29628 171 15 . . PROPN ajst-29628 171 16 terrain terrain NOUN ajst-29628 171 17 matching matching NOUN ajst-29628 171 18 algorithm algorithm NOUN ajst-29628 171 19 based base VERB ajst-29628 171 20 on on ADP ajst-29628 171 21 contour contour NOUN ajst-29628 171 22 line line NOUN ajst-29628 171 23 and and CCONJ ajst-29628 171 24 hausdorff hausdorff NOUN ajst-29628 171 25 distance distance NOUN ajst-29628 171 26 . . PUNCT ajst-29628 172 1 journal journal NOUN ajst-29628 172 2 of of ADP ajst-29628 172 3 projectiles projectile NOUN ajst-29628 172 4 , , PUNCT ajst-29628 172 5 rockets rocket NOUN ajst-29628 172 6 , , PUNCT ajst-29628 172 7 missiles missile NOUN ajst-29628 172 8 and and CCONJ ajst-29628 172 9 guidance guidance NOUN ajst-29628 172 10 , , PUNCT ajst-29628 172 11 2009 2009 NUM ajst-29628 172 12 ; ; PUNCT ajst-29628 172 13 29 29 NUM ajst-29628 172 14 ( ( PUNCT ajst-29628 172 15 6):81 6):81 NUM ajst-29628 172 16 - - SYM ajst-29628 172 17 84 84 NUM ajst-29628 172 18 . . PUNCT ajst-29628 173 1 [ [ X ajst-29628 173 2 12 12 NUM ajst-29628 173 3 ] ] X ajst-29628 173 4 tong tong PROPN ajst-29628 173 5 guang guang PROPN ajst-29628 173 6 , , PUNCT ajst-29628 173 7 zha zha PROPN ajst-29628 173 8 yue yue PROPN ajst-29628 173 9 . . PUNCT ajst-29628 173 10 simulation simulation NOUN ajst-29628 173 11 of of ADP ajst-29628 173 12 confidence confidence NOUN ajst-29628 173 13 algorithm algorithm NOUN ajst-29628 173 14 of of ADP ajst-29628 173 15 underwater underwater ADJ ajst-29628 173 16 terrain terrain NOUN ajst-29628 173 17 matching matching NOUN ajst-29628 173 18 . . PUNCT ajst-29628 174 1 journal journal PROPN ajst-29628 174 2 of of ADP ajst-29628 174 3 chinese chinese ADJ ajst-29628 174 4 inertial inertial ADJ ajst-29628 174 5 technology technology NOUN ajst-29628 174 6 , , PUNCT ajst-29628 174 7 2011 2011 NUM ajst-29628 174 8 ; ; PUNCT ajst-29628 174 9 19(5):549β€”552 19(5):549β€”552 NUM ajst-29628 174 10 . . PUNCT