id	sid	tid	token	lemma	pos
fis-3181	1	1	microsoft	microsoft	PROPN
fis-3181	1	2	word	word	NOUN
fis-3181	1	3	numero_58_art_18_3181.docx	numero_58_art_18_3181.docx	VERB
fis-3181	1	4	a.	a.	PROPN
fis-3181	1	5	mishra	mishra	PROPN
fis-3181	1	6	et	et	PROPN
fis-3181	1	7	alii	alii	PROPN
fis-3181	1	8	,	,	PUNCT
fis-3181	1	9	frattura	frattura	PROPN
fis-3181	1	10	ed	ed	PROPN
fis-3181	1	11	integrità	integrità	PROPN
fis-3181	1	12	strutturale	strutturale	PROPN
fis-3181	1	13	,	,	PUNCT
fis-3181	1	14	58	58	NUM
fis-3181	1	15	(	(	PUNCT
fis-3181	1	16	2021	2021	NUM
fis-3181	1	17	)	)	PUNCT
fis-3181	1	18	242	242	NUM
fis-3181	1	19	-	-	SYM
fis-3181	1	20	253	253	NUM
fis-3181	1	21	;	;	PUNCT
fis-3181	1	22	doi	doi	NOUN
fis-3181	1	23	:	:	PUNCT
fis-3181	1	24	10.3221	10.3221	NUM
fis-3181	1	25	/	/	SYM
fis-3181	1	26	igf	igf	PROPN
fis-3181	1	27	-	-	PUNCT
fis-3181	1	28	esis.58.18	esis.58.18	PROPN
fis-3181	1	29	242	242	NUM
fis-3181	1	30	supervised	supervised	ADJ
fis-3181	1	31	machine	machine	NOUN
fis-3181	1	32	learning	learn	VERB
fis-3181	1	33	classification	classification	NOUN
fis-3181	1	34	algorithms	algorithm	NOUN
fis-3181	1	35	for	for	ADP
fis-3181	1	36	detection	detection	NOUN
fis-3181	1	37	of	of	ADP
fis-3181	1	38	fracture	fracture	NOUN
fis-3181	1	39	location	location	NOUN
fis-3181	1	40	in	in	ADP
fis-3181	1	41	dissimilar	dissimilar	ADJ
fis-3181	1	42	friction	friction	NOUN
fis-3181	1	43	stir	stir	NOUN
fis-3181	1	44	welded	weld	VERB
fis-3181	1	45	joints	joint	NOUN
fis-3181	1	46	akshansh	akshansh	PROPN
fis-3181	1	47	mishra	mishra	PROPN
fis-3181	1	48	centre	centre	PROPN
fis-3181	1	49	for	for	ADP
fis-3181	1	50	artificial	artificial	ADJ
fis-3181	1	51	intelligent	intelligent	ADJ
fis-3181	1	52	manufacturing	manufacturing	NOUN
fis-3181	1	53	systems	system	NOUN
fis-3181	1	54	,	,	PUNCT
fis-3181	1	55	stir	stir	VERB
fis-3181	1	56	research	research	NOUN
fis-3181	1	57	technologies	technology	NOUN
fis-3181	1	58	,	,	PUNCT
fis-3181	1	59	india	india	PROPN
fis-3181	1	60	akshansh@stirresearchtech.in	akshansh@stirresearchtech.in	PROPN
fis-3181	1	61	,	,	PUNCT
fis-3181	1	62	https://orcid.org/0000-0003-4939-359x	https://orcid.org/0000-0003-4939-359x	ADJ
fis-3181	1	63	apoorv	apoorv	ADJ
fis-3181	1	64	vats	vat	NOUN
fis-3181	1	65	department	department	NOUN
fis-3181	1	66	of	of	ADP
fis-3181	1	67	computer	computer	NOUN
fis-3181	1	68	science	science	NOUN
fis-3181	1	69	and	and	CCONJ
fis-3181	1	70	engineering	engineering	NOUN
fis-3181	1	71	,	,	PUNCT
fis-3181	1	72	jaypee	jaypee	PROPN
fis-3181	1	73	university	university	PROPN
fis-3181	1	74	of	of	ADP
fis-3181	1	75	information	information	NOUN
fis-3181	1	76	technology	technology	NOUN
fis-3181	1	77	,	,	PUNCT
fis-3181	1	78	india	india	PROPN
fis-3181	1	79	apoorvvats181@gmail.com	apoorvvats181@gmail.com	PROPN
fis-3181	1	80	,	,	PUNCT
fis-3181	1	81	https://orcid.org/0000-0003-4339-4110	https://orcid.org/0000-0003-4339-4110	PROPN
fis-3181	1	82	abstract	abstract	NOUN
fis-3181	1	83	.	.	PUNCT
fis-3181	2	1	machine	machine	NOUN
fis-3181	2	2	learning	learning	NOUN
fis-3181	2	3	focuses	focus	VERB
fis-3181	2	4	on	on	ADP
fis-3181	2	5	the	the	DET
fis-3181	2	6	study	study	NOUN
fis-3181	2	7	of	of	ADP
fis-3181	2	8	algorithms	algorithm	NOUN
fis-3181	2	9	that	that	PRON
fis-3181	2	10	are	be	AUX
fis-3181	2	11	mathematical	mathematical	ADJ
fis-3181	2	12	or	or	CCONJ
fis-3181	2	13	statistical	statistical	ADJ
fis-3181	2	14	in	in	ADP
fis-3181	2	15	nature	nature	NOUN
fis-3181	2	16	in	in	ADP
fis-3181	2	17	order	order	NOUN
fis-3181	2	18	to	to	PART
fis-3181	2	19	extract	extract	VERB
fis-3181	2	20	the	the	DET
fis-3181	2	21	required	require	VERB
fis-3181	2	22	information	information	NOUN
fis-3181	2	23	pattern	pattern	NOUN
fis-3181	2	24	from	from	ADP
fis-3181	2	25	the	the	DET
fis-3181	2	26	available	available	ADJ
fis-3181	2	27	data	datum	NOUN
fis-3181	2	28	.	.	PUNCT
fis-3181	3	1	supervised	supervise	VERB
fis-3181	3	2	machine	machine	NOUN
fis-3181	3	3	learning	learning	NOUN
fis-3181	3	4	algorithms	algorithm	NOUN
fis-3181	3	5	are	be	AUX
fis-3181	3	6	further	far	ADV
fis-3181	3	7	sub	sub	ADJ
fis-3181	3	8	-	-	VERB
fis-3181	3	9	divided	divide	VERB
fis-3181	3	10	into	into	ADP
fis-3181	3	11	two	two	NUM
fis-3181	3	12	types	type	NOUN
fis-3181	3	13	i.e.	i.e.	X
fis-3181	3	14	regression	regression	NOUN
fis-3181	3	15	algorithms	algorithm	NOUN
fis-3181	3	16	and	and	CCONJ
fis-3181	3	17	classification	classification	NOUN
fis-3181	3	18	algorithms	algorithm	NOUN
fis-3181	3	19	.	.	PUNCT
fis-3181	4	1	in	in	ADP
fis-3181	4	2	the	the	DET
fis-3181	4	3	present	present	ADJ
fis-3181	4	4	study	study	NOUN
fis-3181	4	5	,	,	PUNCT
fis-3181	4	6	four	four	NUM
fis-3181	4	7	supervised	supervised	ADJ
fis-3181	4	8	machine	machine	NOUN
fis-3181	4	9	learning	learning	NOUN
fis-3181	4	10	-	-	PUNCT
fis-3181	4	11	based	base	VERB
fis-3181	4	12	classification	classification	NOUN
fis-3181	4	13	models	model	NOUN
fis-3181	4	14	i.e.	i.e.	X
fis-3181	4	15	decision	decision	NOUN
fis-3181	4	16	trees	tree	NOUN
fis-3181	4	17	algorithm	algorithm	NOUN
fis-3181	4	18	,	,	PUNCT
fis-3181	4	19	knearest	knearest	NOUN
fis-3181	4	20	neighbors	neighbor	NOUN
fis-3181	4	21	(	(	PUNCT
fis-3181	4	22	knn	knn	PROPN
fis-3181	4	23	)	)	PUNCT
fis-3181	4	24	algorithm	algorithm	NOUN
fis-3181	4	25	,	,	PUNCT
fis-3181	4	26	support	support	VERB
fis-3181	4	27	vector	vector	NOUN
fis-3181	4	28	machines	machine	NOUN
fis-3181	4	29	(	(	PUNCT
fis-3181	4	30	svm	svm	ADJ
fis-3181	4	31	)	)	PUNCT
fis-3181	4	32	algorithm	algorithm	NOUN
fis-3181	4	33	,	,	PUNCT
fis-3181	4	34	and	and	CCONJ
fis-3181	4	35	ada	ada	PROPN
fis-3181	4	36	boost	boost	PROPN
fis-3181	4	37	algorithm	algorithm	NOUN
fis-3181	4	38	were	be	AUX
fis-3181	4	39	subjected	subject	VERB
fis-3181	4	40	to	to	ADP
fis-3181	4	41	the	the	DET
fis-3181	4	42	given	give	VERB
fis-3181	4	43	dataset	dataset	NOUN
fis-3181	4	44	for	for	ADP
fis-3181	4	45	the	the	DET
fis-3181	4	46	determination	determination	NOUN
fis-3181	4	47	of	of	ADP
fis-3181	4	48	fracture	fracture	ADJ
fis-3181	4	49	location	location	NOUN
fis-3181	4	50	in	in	ADP
fis-3181	4	51	dissimilar	dissimilar	ADJ
fis-3181	4	52	friction	friction	NOUN
fis-3181	4	53	stir	stir	NOUN
fis-3181	4	54	welded	weld	VERB
fis-3181	4	55	aa6061t651	aa6061t651	ADV
fis-3181	4	56	and	and	CCONJ
fis-3181	4	57	aa7075	aa7075	NOUN
fis-3181	4	58	-	-	PUNCT
fis-3181	4	59	t651	t651	PROPN
fis-3181	4	60	alloy	alloy	NOUN
fis-3181	4	61	.	.	PUNCT
fis-3181	5	1	in	in	ADP
fis-3181	5	2	the	the	DET
fis-3181	5	3	given	give	VERB
fis-3181	5	4	dataset	dataset	NOUN
fis-3181	5	5	,	,	PUNCT
fis-3181	5	6	rotational	rotational	ADJ
fis-3181	5	7	speed	speed	NOUN
fis-3181	5	8	(	(	PUNCT
fis-3181	5	9	rpm	rpm	PROPN
fis-3181	5	10	)	)	PUNCT
fis-3181	5	11	,	,	PUNCT
fis-3181	5	12	welding	weld	VERB
fis-3181	5	13	speed	speed	NOUN
fis-3181	5	14	(	(	PUNCT
fis-3181	5	15	mm	mm	PROPN
fis-3181	5	16	/	/	SYM
fis-3181	5	17	min	min	NOUN
fis-3181	5	18	)	)	PUNCT
fis-3181	5	19	,	,	PUNCT
fis-3181	5	20	pin	pin	NOUN
fis-3181	5	21	profile	profile	VERB
fis-3181	5	22	,	,	PUNCT
fis-3181	5	23	and	and	CCONJ
fis-3181	5	24	axial	axial	ADJ
fis-3181	5	25	force	force	NOUN
fis-3181	5	26	(	(	PUNCT
fis-3181	5	27	kn	kn	PROPN
fis-3181	5	28	)	)	PUNCT
fis-3181	5	29	were	be	AUX
fis-3181	5	30	the	the	DET
fis-3181	5	31	input	input	NOUN
fis-3181	5	32	parameters	parameter	NOUN
fis-3181	5	33	while	while	SCONJ
fis-3181	5	34	fracture	fracture	NOUN
fis-3181	5	35	location	location	NOUN
fis-3181	5	36	is	be	AUX
fis-3181	5	37	the	the	DET
fis-3181	5	38	output	output	NOUN
fis-3181	5	39	parameter	parameter	NOUN
fis-3181	5	40	.	.	PUNCT
fis-3181	6	1	the	the	DET
fis-3181	6	2	obtained	obtain	VERB
fis-3181	6	3	results	result	NOUN
fis-3181	6	4	showed	show	VERB
fis-3181	6	5	that	that	SCONJ
fis-3181	6	6	the	the	DET
fis-3181	6	7	support	support	NOUN
fis-3181	6	8	vector	vector	NOUN
fis-3181	6	9	machine	machine	NOUN
fis-3181	6	10	(	(	PUNCT
fis-3181	6	11	svm	svm	ADJ
fis-3181	6	12	)	)	PUNCT
fis-3181	6	13	algorithm	algorithm	NOUN
fis-3181	6	14	classified	classify	VERB
fis-3181	6	15	the	the	DET
fis-3181	6	16	fracture	fracture	PROPN
fis-3181	6	17	location	location	NOUN
fis-3181	6	18	with	with	ADP
fis-3181	6	19	a	a	DET
fis-3181	6	20	good	good	ADJ
fis-3181	6	21	accuracy	accuracy	NOUN
fis-3181	6	22	score	score	NOUN
fis-3181	6	23	of	of	ADP
fis-3181	6	24	0.889	0.889	NUM
fis-3181	6	25	in	in	ADP
fis-3181	6	26	comparison	comparison	NOUN
fis-3181	6	27	to	to	ADP
fis-3181	6	28	the	the	DET
fis-3181	6	29	other	other	ADJ
fis-3181	6	30	algorithms	algorithm	NOUN
fis-3181	6	31	.	.	PUNCT
fis-3181	7	1	keywords	keyword	NOUN
fis-3181	7	2	.	.	PUNCT
fis-3181	8	1	fracture	fracture	ADJ
fis-3181	8	2	location	location	NOUN
fis-3181	8	3	;	;	PUNCT
fis-3181	8	4	machine	machine	NOUN
fis-3181	8	5	learning	learning	NOUN
fis-3181	8	6	;	;	PUNCT
fis-3181	8	7	classification	classification	NOUN
fis-3181	8	8	;	;	PUNCT
fis-3181	8	9	friction	friction	NOUN
fis-3181	8	10	stir	stir	NOUN
fis-3181	8	11	welding	welding	NOUN
fis-3181	8	12	;	;	PUNCT
fis-3181	8	13	dissimilar	dissimilar	ADJ
fis-3181	8	14	joints	joint	NOUN
fis-3181	8	15	;	;	PUNCT
fis-3181	8	16	python	python	NOUN
fis-3181	8	17	programming	programming	NOUN
fis-3181	8	18	citation	citation	NOUN
fis-3181	8	19	:	:	PUNCT
fis-3181	9	1	mishra	mishra	PROPN
fis-3181	9	2	,	,	PUNCT
fis-3181	9	3	a.	a.	NOUN
fis-3181	9	4	,	,	PUNCT
fis-3181	9	5	vats	vat	NOUN
fis-3181	9	6	,	,	PUNCT
fis-3181	9	7	a.	a.	NOUN
fis-3181	9	8	,	,	PUNCT
fis-3181	9	9	supervised	supervise	VERB
fis-3181	9	10	machine	machine	NOUN
fis-3181	9	11	learning	learn	VERB
fis-3181	9	12	classification	classification	NOUN
fis-3181	9	13	algorithms	algorithm	NOUN
fis-3181	9	14	for	for	ADP
fis-3181	9	15	detection	detection	NOUN
fis-3181	9	16	of	of	ADP
fis-3181	9	17	fracture	fracture	NOUN
fis-3181	9	18	location	location	NOUN
fis-3181	9	19	in	in	ADP
fis-3181	9	20	dissimilar	dissimilar	ADJ
fis-3181	9	21	friction	friction	NOUN
fis-3181	9	22	stir	stir	NOUN
fis-3181	9	23	welded	weld	VERB
fis-3181	9	24	joints	joint	NOUN
fis-3181	9	25	,	,	PUNCT
fis-3181	9	26	frattura	frattura	PROPN
fis-3181	9	27	ed	ed	PROPN
fis-3181	9	28	integrità	integrità	PROPN
fis-3181	9	29	strutturale	strutturale	PROPN
fis-3181	9	30	,	,	PUNCT
fis-3181	9	31	58	58	NUM
fis-3181	9	32	(	(	PUNCT
fis-3181	9	33	2021	2021	NUM
fis-3181	9	34	)	)	PUNCT
fis-3181	9	35	242	242	NUM
fis-3181	9	36	-	-	SYM
fis-3181	9	37	253	253	NUM
fis-3181	9	38	.	.	PUNCT
fis-3181	10	1	received	receive	VERB
fis-3181	10	2	:	:	PUNCT
fis-3181	10	3	09.07.2021	09.07.2021	NOUN
fis-3181	10	4	accepted	accept	VERB
fis-3181	10	5	:	:	PUNCT
fis-3181	10	6	23.08.2021	23.08.2021	NUM
fis-3181	10	7	published	publish	VERB
fis-3181	10	8	:	:	PUNCT
fis-3181	10	9	01.10.2021	01.10.2021	NUM
fis-3181	11	1	copyright	copyright	NOUN
fis-3181	11	2	:	:	PUNCT
fis-3181	11	3	©	©	PROPN
fis-3181	11	4	2021	2021	NUM
fis-3181	11	5	this	this	PRON
fis-3181	11	6	is	be	AUX
fis-3181	11	7	an	an	DET
fis-3181	11	8	open	open	ADJ
fis-3181	11	9	access	access	NOUN
fis-3181	11	10	article	article	NOUN
fis-3181	11	11	under	under	ADP
fis-3181	11	12	the	the	DET
fis-3181	11	13	terms	term	NOUN
fis-3181	11	14	of	of	ADP
fis-3181	11	15	the	the	DET
fis-3181	11	16	cc	cc	NOUN
fis-3181	11	17	-	-	PUNCT
fis-3181	11	18	by	by	ADP
fis-3181	11	19	4.0	4.0	NUM
fis-3181	11	20	,	,	PUNCT
fis-3181	11	21	which	which	PRON
fis-3181	11	22	permits	permit	VERB
fis-3181	11	23	unrestricted	unrestricted	ADJ
fis-3181	11	24	use	use	NOUN
fis-3181	11	25	,	,	PUNCT
fis-3181	11	26	distribution	distribution	NOUN
fis-3181	11	27	,	,	PUNCT
fis-3181	11	28	and	and	CCONJ
fis-3181	11	29	reproduction	reproduction	NOUN
fis-3181	11	30	in	in	ADP
fis-3181	11	31	any	any	DET
fis-3181	11	32	medium	medium	NOUN
fis-3181	11	33	,	,	PUNCT
fis-3181	11	34	provided	provide	VERB
fis-3181	11	35	the	the	DET
fis-3181	11	36	original	original	ADJ
fis-3181	11	37	author	author	NOUN
fis-3181	11	38	and	and	CCONJ
fis-3181	11	39	source	source	NOUN
fis-3181	11	40	are	be	AUX
fis-3181	11	41	credited	credit	VERB
fis-3181	11	42	.	.	PUNCT
fis-3181	12	1	introduction	introduction	NOUN
fis-3181	12	2	achine	achine	NOUN
fis-3181	12	3	learning	learn	VERB
fis-3181	12	4	algorithms	algorithm	NOUN
fis-3181	12	5	are	be	AUX
fis-3181	12	6	vital	vital	ADJ
fis-3181	12	7	tools	tool	NOUN
fis-3181	12	8	or	or	CCONJ
fis-3181	12	9	methods	method	NOUN
fis-3181	12	10	for	for	ADP
fis-3181	12	11	understanding	understanding	NOUN
fis-3181	12	12	and	and	CCONJ
fis-3181	12	13	handling	handle	VERB
fis-3181	12	14	the	the	DET
fis-3181	12	15	data	datum	NOUN
fis-3181	12	16	.	.	PUNCT
fis-3181	13	1	it	it	PRON
fis-3181	13	2	should	should	AUX
fis-3181	13	3	be	be	AUX
fis-3181	13	4	noted	note	VERB
fis-3181	13	5	that	that	SCONJ
fis-3181	13	6	a	a	DET
fis-3181	13	7	statistic	statistic	NOUN
fis-3181	13	8	can	can	AUX
fis-3181	13	9	be	be	AUX
fis-3181	13	10	a	a	DET
fis-3181	13	11	graphical	graphical	ADJ
fis-3181	13	12	or	or	CCONJ
fis-3181	13	13	numerical	numerical	ADJ
fis-3181	13	14	summary	summary	NOUN
fis-3181	13	15	of	of	ADP
fis-3181	13	16	a	a	DET
fis-3181	13	17	collection	collection	NOUN
fis-3181	13	18	of	of	ADP
fis-3181	13	19	the	the	DET
fis-3181	13	20	given	give	VERB
fis-3181	13	21	data	datum	NOUN
fis-3181	13	22	[	[	X
fis-3181	13	23	1	1	NUM
fis-3181	13	24	-	-	SYM
fis-3181	13	25	3	3	NUM
fis-3181	13	26	]	]	PUNCT
fis-3181	13	27	.	.	PUNCT
fis-3181	14	1	data	datum	NOUN
fis-3181	14	2	is	be	AUX
fis-3181	14	3	overwhelming	overwhelming	ADJ
fis-3181	14	4	in	in	ADP
fis-3181	14	5	nature	nature	NOUN
fis-3181	14	6	which	which	PRON
fis-3181	14	7	involves	involve	VERB
fis-3181	14	8	summarization	summarization	NOUN
fis-3181	14	9	and	and	CCONJ
fis-3181	14	10	reduction	reduction	NOUN
fis-3181	14	11	which	which	PRON
fis-3181	14	12	makes	make	VERB
fis-3181	14	13	the	the	DET
fis-3181	14	14	dataset	dataset	NOUN
fis-3181	14	15	comprehensible	comprehensible	ADJ
fis-3181	14	16	to	to	ADP
fis-3181	14	17	a	a	DET
fis-3181	14	18	human	human	ADJ
fis-3181	14	19	observer	observer	NOUN
fis-3181	14	20	.	.	PUNCT
fis-3181	15	1	understanding	understand	VERB
fis-3181	15	2	the	the	DET
fis-3181	15	3	data	data	NOUN
fis-3181	15	4	is	be	AUX
fis-3181	15	5	very	very	ADV
fis-3181	15	6	important	important	ADJ
fis-3181	15	7	because	because	SCONJ
fis-3181	15	8	sometimes	sometimes	ADV
fis-3181	15	9	the	the	DET
fis-3181	15	10	available	available	ADJ
fis-3181	15	11	data	datum	NOUN
fis-3181	15	12	can	can	AUX
fis-3181	15	13	be	be	AUX
fis-3181	15	14	misleading	misleading	ADJ
fis-3181	15	15	.	.	PUNCT
fis-3181	16	1	so	so	ADV
fis-3181	16	2	,	,	PUNCT
fis-3181	16	3	the	the	DET
fis-3181	16	4	implementation	implementation	NOUN
fis-3181	16	5	of	of	ADP
fis-3181	16	6	machine	machine	NOUN
fis-3181	16	7	learning	learn	VERB
fis-3181	16	8	algorithms	algorithm	NOUN
fis-3181	16	9	provides	provide	VERB
fis-3181	16	10	statistical	statistical	ADJ
fis-3181	16	11	framework	framework	NOUN
fis-3181	16	12	for	for	ADP
fis-3181	16	13	assessing	assess	VERB
fis-3181	16	14	the	the	DET
fis-3181	16	15	quality	quality	NOUN
fis-3181	16	16	of	of	ADP
fis-3181	16	17	available	available	ADJ
fis-3181	16	18	data	datum	NOUN
fis-3181	16	19	[	[	X
fis-3181	16	20	4	4	NUM
fis-3181	16	21	-	-	SYM
fis-3181	16	22	5	5	NUM
fis-3181	16	23	]	]	PUNCT
fis-3181	16	24	.	.	PUNCT
fis-3181	17	1	m	m	VERB
fis-3181	17	2	https://youtu.be/ycrrozmsbos	https://youtu.be/ycrrozmsbos	PUNCT
fis-3181	17	3	a.	a.	PROPN
fis-3181	17	4	mishra	mishra	PROPN
fis-3181	17	5	et	et	PROPN
fis-3181	17	6	alii	alii	PROPN
fis-3181	17	7	,	,	PUNCT
fis-3181	17	8	frattura	frattura	PROPN
fis-3181	17	9	ed	ed	PROPN
fis-3181	17	10	integrità	integrità	PROPN
fis-3181	17	11	strutturale	strutturale	PROPN
fis-3181	17	12	,	,	PUNCT
fis-3181	17	13	58	58	NUM
fis-3181	17	14	(	(	PUNCT
fis-3181	17	15	2021	2021	NUM
fis-3181	17	16	)	)	PUNCT
fis-3181	17	17	242	242	NUM
fis-3181	17	18	-	-	SYM
fis-3181	17	19	253	253	NUM
fis-3181	17	20	;	;	PUNCT
fis-3181	17	21	doi	doi	NOUN
fis-3181	17	22	:	:	PUNCT
fis-3181	17	23	10.3221	10.3221	NUM
fis-3181	17	24	/	/	SYM
fis-3181	17	25	igf	igf	PROPN
fis-3181	17	26	-	-	PUNCT
fis-3181	17	27	esis.58.18	esis.58.18	PROPN
fis-3181	17	28	243	243	NUM
fis-3181	17	29	data	datum	NOUN
fis-3181	17	30	is	be	AUX
fis-3181	17	31	further	far	ADV
fis-3181	17	32	classified	classify	VERB
fis-3181	17	33	into	into	ADP
fis-3181	17	34	two	two	NUM
fis-3181	17	35	key	key	ADJ
fis-3181	17	36	types	type	NOUN
fis-3181	17	37	i.e.	i.e.	X
fis-3181	17	38	organic	organic	ADJ
fis-3181	17	39	/	/	SYM
fis-3181	17	40	processed	process	VERB
fis-3181	17	41	data	datum	NOUN
fis-3181	17	42	and	and	CCONJ
fis-3181	17	43	"	"	PUNCT
fis-3181	17	44	designed	design	VERB
fis-3181	17	45	"	"	PUNCT
fis-3181	17	46	data	datum	NOUN
fis-3181	17	47	collection	collection	NOUN
fis-3181	18	1	[	[	X
fis-3181	18	2	6	6	NUM
fis-3181	18	3	]	]	PUNCT
fis-3181	18	4	.	.	PUNCT
fis-3181	19	1	organic	organic	ADJ
fis-3181	19	2	data	datum	NOUN
fis-3181	19	3	is	be	AUX
fis-3181	19	4	extracted	extract	VERB
fis-3181	19	5	by	by	ADP
fis-3181	19	6	a	a	DET
fis-3181	19	7	computerized	computerized	ADJ
fis-3181	19	8	system	system	NOUN
fis-3181	19	9	or	or	CCONJ
fis-3181	19	10	from	from	ADP
fis-3181	19	11	audio	audio	ADJ
fis-3181	19	12	and	and	CCONJ
fis-3181	19	13	video	video	NOUN
fis-3181	19	14	recordings	recording	NOUN
fis-3181	19	15	.	.	PUNCT
fis-3181	20	1	this	this	DET
fis-3181	20	2	type	type	NOUN
fis-3181	20	3	of	of	ADP
fis-3181	20	4	data	datum	NOUN
fis-3181	20	5	is	be	AUX
fis-3181	20	6	generated	generate	VERB
fis-3181	20	7	organically	organically	ADV
fis-3181	20	8	as	as	ADP
fis-3181	20	9	a	a	DET
fis-3181	20	10	result	result	NOUN
fis-3181	20	11	of	of	ADP
fis-3181	20	12	some	some	DET
fis-3181	20	13	process	process	NOUN
fis-3181	20	14	and	and	CCONJ
fis-3181	20	15	is	be	AUX
fis-3181	20	16	generated	generate	VERB
fis-3181	20	17	over	over	ADP
fis-3181	20	18	time	time	NOUN
fis-3181	20	19	.	.	PUNCT
fis-3181	21	1	these	these	DET
fis-3181	21	2	processes	process	NOUN
fis-3181	21	3	generate	generate	VERB
fis-3181	21	4	massive	massive	ADJ
fis-3181	21	5	quantities	quantity	NOUN
fis-3181	21	6	of	of	ADP
fis-3181	21	7	data	datum	NOUN
fis-3181	21	8	which	which	PRON
fis-3181	21	9	is	be	AUX
fis-3181	21	10	called	call	VERB
fis-3181	21	11	big	big	ADJ
fis-3181	21	12	data	datum	NOUN
fis-3181	21	13	.	.	PUNCT
fis-3181	22	1	in	in	ADP
fis-3181	22	2	order	order	NOUN
fis-3181	22	3	to	to	PART
fis-3181	22	4	process	process	VERB
fis-3181	22	5	this	this	DET
fis-3181	22	6	type	type	NOUN
fis-3181	22	7	of	of	ADP
fis-3181	22	8	data	datum	NOUN
fis-3181	22	9	,	,	PUNCT
fis-3181	22	10	significant	significant	ADJ
fis-3181	22	11	computational	computational	ADJ
fis-3181	22	12	resources	resource	NOUN
fis-3181	22	13	are	be	AUX
fis-3181	22	14	required	require	VERB
fis-3181	22	15	.	.	PUNCT
fis-3181	23	1	on	on	ADP
fis-3181	23	2	the	the	DET
fis-3181	23	3	other	other	ADJ
fis-3181	23	4	hand	hand	NOUN
fis-3181	23	5	,	,	PUNCT
fis-3181	23	6	"	"	PUNCT
fis-3181	23	7	designed	design	VERB
fis-3181	23	8	"	"	PUNCT
fis-3181	23	9	data	datum	NOUN
fis-3181	23	10	collection	collection	NOUN
fis-3181	23	11	is	be	AUX
fis-3181	23	12	used	use	VERB
fis-3181	23	13	to	to	PART
fis-3181	23	14	specifically	specifically	ADV
fis-3181	23	15	address	address	VERB
fis-3181	23	16	a	a	DET
fis-3181	23	17	stated	state	VERB
fis-3181	23	18	research	research	NOUN
fis-3181	23	19	objective	objective	NOUN
fis-3181	23	20	for	for	ADP
fis-3181	23	21	example	example	NOUN
fis-3181	23	22	a	a	DET
fis-3181	23	23	particular	particular	ADJ
fis-3181	23	24	individual	individual	NOUN
fis-3181	23	25	sampled	sample	VERB
fis-3181	23	26	from	from	ADP
fis-3181	23	27	the	the	DET
fis-3181	23	28	population	population	NOUN
fis-3181	23	29	.	.	PUNCT
fis-3181	24	1	machine	machine	NOUN
fis-3181	24	2	learning	learn	VERB
fis-3181	24	3	algorithms	algorithm	NOUN
fis-3181	24	4	have	have	AUX
fis-3181	24	5	gained	gain	VERB
fis-3181	24	6	some	some	DET
fis-3181	24	7	popularity	popularity	NOUN
fis-3181	24	8	in	in	ADP
fis-3181	24	9	the	the	DET
fis-3181	24	10	friction	friction	NOUN
fis-3181	24	11	stir	stir	NOUN
fis-3181	24	12	welding	welding	NOUN
fis-3181	24	13	process	process	NOUN
fis-3181	24	14	[	[	X
fis-3181	24	15	7–9	7–9	NUM
fis-3181	24	16	]	]	PUNCT
fis-3181	24	17	.	.	PUNCT
fis-3181	25	1	machine	machine	NOUN
fis-3181	25	2	learning	learn	VERB
fis-3181	25	3	classification	classification	NOUN
fis-3181	25	4	-	-	PUNCT
fis-3181	25	5	based	base	VERB
fis-3181	25	6	approach	approach	NOUN
fis-3181	25	7	was	be	AUX
fis-3181	25	8	used	use	VERB
fis-3181	25	9	for	for	ADP
fis-3181	25	10	predicting	predict	VERB
fis-3181	25	11	the	the	DET
fis-3181	25	12	mechanical	mechanical	ADJ
fis-3181	25	13	properties	property	NOUN
fis-3181	25	14	of	of	ADP
fis-3181	25	15	friction	friction	NOUN
fis-3181	25	16	stir	stir	NOUN
fis-3181	25	17	welded	weld	VERB
fis-3181	25	18	copper	copper	NOUN
fis-3181	25	19	joints	joint	NOUN
fis-3181	25	20	[	[	X
fis-3181	25	21	10	10	NUM
fis-3181	25	22	]	]	PUNCT
fis-3181	25	23	.	.	PUNCT
fis-3181	26	1	the	the	DET
fis-3181	26	2	results	result	NOUN
fis-3181	26	3	showed	show	VERB
fis-3181	26	4	that	that	SCONJ
fis-3181	26	5	the	the	DET
fis-3181	26	6	artificial	artificial	ADJ
fis-3181	26	7	neural	neural	ADJ
fis-3181	26	8	network	network	NOUN
fis-3181	26	9	model	model	NOUN
fis-3181	26	10	resulted	result	VERB
fis-3181	26	11	in	in	ADP
fis-3181	26	12	a	a	DET
fis-3181	26	13	good	good	ADJ
fis-3181	26	14	accuracy	accuracy	NOUN
fis-3181	26	15	score	score	NOUN
fis-3181	26	16	of	of	ADP
fis-3181	26	17	0.94	0.94	NUM
fis-3181	26	18	.	.	PUNCT
fis-3181	27	1	balachandar	balachandar	PROPN
fis-3181	27	2	et	et	PROPN
fis-3181	27	3	al	al	PROPN
fis-3181	27	4	.	.	PUNCT
fis-3181	28	1	[	[	X
fis-3181	28	2	11	11	NUM
fis-3181	28	3	]	]	PUNCT
fis-3181	28	4	monitored	monitor	VERB
fis-3181	28	5	the	the	DET
fis-3181	28	6	friction	friction	NOUN
fis-3181	28	7	stir	stir	NOUN
fis-3181	28	8	welding	weld	VERB
fis-3181	28	9	tool	tool	NOUN
fis-3181	28	10	condition	condition	NOUN
fis-3181	28	11	by	by	ADP
fis-3181	28	12	using	use	VERB
fis-3181	28	13	the	the	DET
fis-3181	28	14	random	random	ADJ
fis-3181	28	15	forest	forest	NOUN
fis-3181	28	16	algorithm	algorithm	NOUN
fis-3181	28	17	which	which	PRON
fis-3181	28	18	gave	give	VERB
fis-3181	28	19	better	well	ADJ
fis-3181	28	20	results	result	NOUN
fis-3181	28	21	.	.	PUNCT
fis-3181	29	1	there	there	PRON
fis-3181	29	2	is	be	VERB
fis-3181	29	3	limited	limited	ADJ
fis-3181	29	4	number	number	NOUN
fis-3181	29	5	of	of	ADP
fis-3181	29	6	research	research	NOUN
fis-3181	29	7	studies	study	NOUN
fis-3181	29	8	available	available	ADJ
fis-3181	29	9	on	on	ADP
fis-3181	29	10	the	the	DET
fis-3181	29	11	application	application	NOUN
fis-3181	29	12	of	of	ADP
fis-3181	29	13	supervised	supervised	ADJ
fis-3181	29	14	machine	machine	NOUN
fis-3181	29	15	learning	learn	VERB
fis-3181	29	16	classification	classification	NOUN
fis-3181	29	17	models	model	NOUN
fis-3181	29	18	in	in	ADP
fis-3181	29	19	the	the	DET
fis-3181	29	20	friction	friction	NOUN
fis-3181	29	21	stir	stir	NOUN
fis-3181	29	22	welding	welding	NOUN
fis-3181	29	23	process	process	NOUN
fis-3181	29	24	.	.	PUNCT
fis-3181	30	1	du	du	PROPN
fis-3181	30	2	et	et	PROPN
fis-3181	30	3	al	al	PROPN
fis-3181	30	4	.	.	PUNCT
fis-3181	31	1	[	[	X
fis-3181	31	2	12	12	NUM
fis-3181	31	3	]	]	PUNCT
fis-3181	31	4	used	use	VERB
fis-3181	31	5	machine	machine	NOUN
fis-3181	31	6	learning	learning	NOUN
fis-3181	31	7	based	base	VERB
fis-3181	31	8	classification	classification	NOUN
fis-3181	31	9	models	model	NOUN
fis-3181	31	10	for	for	ADP
fis-3181	31	11	studying	study	VERB
fis-3181	31	12	the	the	DET
fis-3181	31	13	conditions	condition	NOUN
fis-3181	31	14	of	of	ADP
fis-3181	31	15	void	void	ADJ
fis-3181	31	16	formation	formation	NOUN
fis-3181	31	17	in	in	ADP
fis-3181	31	18	friction	friction	NOUN
fis-3181	31	19	stir	stir	NOUN
fis-3181	31	20	welding	welding	NOUN
fis-3181	31	21	process	process	NOUN
fis-3181	31	22	.	.	PUNCT
fis-3181	32	1	the	the	DET
fis-3181	32	2	results	result	NOUN
fis-3181	32	3	showed	show	VERB
fis-3181	32	4	that	that	SCONJ
fis-3181	32	5	the	the	DET
fis-3181	32	6	implemented	implement	VERB
fis-3181	32	7	artificial	artificial	ADJ
fis-3181	32	8	neural	neural	ADJ
fis-3181	32	9	network	network	NOUN
fis-3181	32	10	(	(	PUNCT
fis-3181	32	11	ann	ann	PROPN
fis-3181	32	12	)	)	PUNCT
fis-3181	32	13	and	and	CCONJ
fis-3181	32	14	decision	decision	NOUN
fis-3181	32	15	tree	tree	NOUN
fis-3181	32	16	(	(	PUNCT
fis-3181	32	17	dt	dt	NOUN
fis-3181	32	18	)	)	PUNCT
fis-3181	32	19	algorithms	algorithm	NOUN
fis-3181	32	20	resulted	result	VERB
fis-3181	32	21	in	in	ADP
fis-3181	32	22	the	the	DET
fis-3181	32	23	accuracy	accuracy	NOUN
fis-3181	32	24	of	of	ADP
fis-3181	32	25	96.6	96.6	NUM
fis-3181	32	26	%	%	NOUN
fis-3181	32	27	.	.	PUNCT
fis-3181	33	1	machine	machine	NOUN
fis-3181	33	2	learning	learning	NOUN
fis-3181	33	3	based	base	VERB
fis-3181	33	4	classification	classification	NOUN
fis-3181	33	5	algorithms	algorithm	NOUN
fis-3181	33	6	were	be	AUX
fis-3181	33	7	used	use	VERB
fis-3181	33	8	for	for	ADP
fis-3181	33	9	the	the	DET
fis-3181	33	10	determination	determination	NOUN
fis-3181	33	11	of	of	ADP
fis-3181	33	12	mechanical	mechanical	ADJ
fis-3181	33	13	properties	property	NOUN
fis-3181	33	14	of	of	ADP
fis-3181	33	15	friction	friction	NOUN
fis-3181	33	16	stir	stir	NOUN
fis-3181	33	17	welded	weld	VERB
fis-3181	33	18	copper	copper	NOUN
fis-3181	33	19	joints	joint	NOUN
fis-3181	33	20	[	[	X
fis-3181	33	21	13	13	NUM
fis-3181	33	22	]	]	PUNCT
fis-3181	33	23	.	.	PUNCT
fis-3181	34	1	the	the	DET
fis-3181	34	2	results	result	NOUN
fis-3181	34	3	showed	show	VERB
fis-3181	34	4	that	that	SCONJ
fis-3181	34	5	the	the	DET
fis-3181	34	6	artificial	artificial	ADJ
fis-3181	34	7	neural	neural	ADJ
fis-3181	34	8	network	network	NOUN
fis-3181	34	9	(	(	PUNCT
fis-3181	34	10	ann	ann	PROPN
fis-3181	34	11	)	)	PUNCT
fis-3181	34	12	resulted	result	VERB
fis-3181	34	13	in	in	ADP
fis-3181	34	14	the	the	DET
fis-3181	34	15	accuracy	accuracy	NOUN
fis-3181	34	16	of	of	ADP
fis-3181	34	17	96.6	96.6	NUM
fis-3181	34	18	%	%	NOUN
fis-3181	34	19	.	.	PUNCT
fis-3181	35	1	in	in	ADP
fis-3181	35	2	the	the	DET
fis-3181	35	3	present	present	ADJ
fis-3181	35	4	work	work	NOUN
fis-3181	35	5	,	,	PUNCT
fis-3181	35	6	the	the	DET
fis-3181	35	7	fracture	fracture	NOUN
fis-3181	35	8	position	position	NOUN
fis-3181	35	9	of	of	ADP
fis-3181	35	10	dissimilar	dissimilar	ADJ
fis-3181	35	11	friction	friction	NOUN
fis-3181	35	12	stir	stir	NOUN
fis-3181	35	13	welded	weld	VERB
fis-3181	35	14	joints	joint	NOUN
fis-3181	35	15	is	be	AUX
fis-3181	35	16	determined	determine	VERB
fis-3181	35	17	by	by	ADP
fis-3181	35	18	using	use	VERB
fis-3181	35	19	four	four	NUM
fis-3181	35	20	supervised	supervised	ADJ
fis-3181	35	21	machine	machine	NOUN
fis-3181	35	22	learning	learn	VERB
fis-3181	35	23	classification	classification	NOUN
fis-3181	35	24	algorithms	algorithm	NOUN
fis-3181	35	25	which	which	PRON
fis-3181	35	26	will	will	AUX
fis-3181	35	27	be	be	AUX
fis-3181	35	28	discussed	discuss	VERB
fis-3181	35	29	in	in	ADP
fis-3181	35	30	the	the	DET
fis-3181	35	31	next	next	ADJ
fis-3181	35	32	sections	section	NOUN
fis-3181	35	33	.	.	PUNCT
fis-3181	36	1	rotational	rotational	ADJ
fis-3181	36	2	speed	speed	NOUN
fis-3181	36	3	(	(	PUNCT
fis-3181	36	4	rpm	rpm	NOUN
fis-3181	36	5	)	)	PUNCT
fis-3181	36	6	welding	welding	NOUN
fis-3181	36	7	speed	speed	NOUN
fis-3181	36	8	(	(	PUNCT
fis-3181	36	9	mm	mm	NOUN
fis-3181	36	10	/	/	SYM
fis-3181	36	11	min	min	NOUN
fis-3181	36	12	)	)	PUNCT
fis-3181	36	13	pin	pin	NOUN
fis-3181	36	14	profile	profile	VERB
fis-3181	36	15	axial	axial	ADJ
fis-3181	36	16	force	force	NOUN
fis-3181	36	17	(	(	PUNCT
fis-3181	36	18	kn	kn	NOUN
fis-3181	36	19	)	)	PUNCT
fis-3181	36	20	fracture	fracture	PROPN
fis-3181	36	21	position	position	NOUN
fis-3181	36	22	800	800	NUM
fis-3181	36	23	90	90	NUM
fis-3181	36	24	1	1	NUM
fis-3181	36	25	12	12	NUM
fis-3181	36	26	0	0	NUM
fis-3181	36	27	800	800	NUM
fis-3181	36	28	100	100	NUM
fis-3181	36	29	1	1	NUM
fis-3181	36	30	12	12	NUM
fis-3181	36	31	1	1	NUM
fis-3181	36	32	800	800	NUM
fis-3181	36	33	110	110	NUM
fis-3181	36	34	1	1	NUM
fis-3181	36	35	12	12	NUM
fis-3181	36	36	1	1	NUM
fis-3181	36	37	800	800	NUM
fis-3181	36	38	90	90	NUM
fis-3181	36	39	2	2	NUM
fis-3181	36	40	12	12	NUM
fis-3181	36	41	1	1	NUM
fis-3181	36	42	800	800	NUM
fis-3181	36	43	100	100	NUM
fis-3181	36	44	2	2	NUM
fis-3181	36	45	12	12	NUM
fis-3181	36	46	1	1	NUM
fis-3181	36	47	800	800	NUM
fis-3181	36	48	110	110	NUM
fis-3181	36	49	2	2	NUM
fis-3181	36	50	12	12	NUM
fis-3181	36	51	1	1	NUM
fis-3181	36	52	800	800	NUM
fis-3181	36	53	90	90	NUM
fis-3181	36	54	3	3	NUM
fis-3181	36	55	12	12	NUM
fis-3181	36	56	0	0	NUM
fis-3181	36	57	800	800	NUM
fis-3181	36	58	100	100	NUM
fis-3181	36	59	3	3	NUM
fis-3181	36	60	12	12	NUM
fis-3181	36	61	0	0	NUM
fis-3181	36	62	800	800	NUM
fis-3181	36	63	110	110	NUM
fis-3181	36	64	3	3	NUM
fis-3181	36	65	12	12	NUM
fis-3181	36	66	0	0	NUM
fis-3181	36	67	900	900	NUM
fis-3181	36	68	90	90	NUM
fis-3181	36	69	1	1	NUM
fis-3181	36	70	12	12	NUM
fis-3181	36	71	1	1	NUM
fis-3181	36	72	900	900	NUM
fis-3181	36	73	100	100	NUM
fis-3181	36	74	1	1	NUM
fis-3181	36	75	12	12	NUM
fis-3181	36	76	1	1	NUM
fis-3181	36	77	900	900	NUM
fis-3181	36	78	110	110	NUM
fis-3181	36	79	1	1	NUM
fis-3181	36	80	12	12	NUM
fis-3181	36	81	1	1	NUM
fis-3181	36	82	900	900	NUM
fis-3181	36	83	90	90	NUM
fis-3181	36	84	2	2	NUM
fis-3181	36	85	12	12	NUM
fis-3181	36	86	1	1	NUM
fis-3181	36	87	900	900	NUM
fis-3181	36	88	100	100	NUM
fis-3181	36	89	2	2	NUM
fis-3181	36	90	12	12	NUM
fis-3181	36	91	1	1	NUM
fis-3181	36	92	900	900	NUM
fis-3181	36	93	110	110	NUM
fis-3181	36	94	2	2	NUM
fis-3181	36	95	12	12	NUM
fis-3181	36	96	1	1	NUM
fis-3181	36	97	900	900	NUM
fis-3181	36	98	90	90	NUM
fis-3181	36	99	3	3	NUM
fis-3181	36	100	12	12	NUM
fis-3181	36	101	1	1	NUM
fis-3181	36	102	900	900	NUM
fis-3181	36	103	100	100	NUM
fis-3181	36	104	3	3	NUM
fis-3181	36	105	12	12	NUM
fis-3181	36	106	1	1	NUM
fis-3181	36	107	900	900	NUM
fis-3181	36	108	110	110	NUM
fis-3181	36	109	3	3	NUM
fis-3181	36	110	12	12	NUM
fis-3181	36	111	1	1	NUM
fis-3181	36	112	1000	1000	NUM
fis-3181	36	113	90	90	NUM
fis-3181	36	114	1	1	NUM
fis-3181	36	115	12	12	NUM
fis-3181	36	116	0	0	NUM
fis-3181	36	117	1000	1000	NUM
fis-3181	36	118	100	100	NUM
fis-3181	36	119	1	1	NUM
fis-3181	36	120	12	12	NUM
fis-3181	36	121	0	0	NUM
fis-3181	36	122	1000	1000	NUM
fis-3181	36	123	110	110	NUM
fis-3181	36	124	1	1	NUM
fis-3181	36	125	12	12	NUM
fis-3181	36	126	0	0	NUM
fis-3181	36	127	1000	1000	NUM
fis-3181	36	128	90	90	NUM
fis-3181	36	129	2	2	NUM
fis-3181	36	130	12	12	NUM
fis-3181	36	131	1	1	NUM
fis-3181	36	132	1000	1000	NUM
fis-3181	36	133	100	100	NUM
fis-3181	36	134	2	2	NUM
fis-3181	36	135	12	12	NUM
fis-3181	36	136	1	1	NUM
fis-3181	36	137	1000	1000	NUM
fis-3181	36	138	110	110	NUM
fis-3181	36	139	2	2	NUM
fis-3181	36	140	12	12	NUM
fis-3181	36	141	1	1	NUM
fis-3181	36	142	1000	1000	NUM
fis-3181	36	143	90	90	NUM
fis-3181	36	144	3	3	NUM
fis-3181	36	145	12	12	NUM
fis-3181	36	146	1	1	NUM
fis-3181	36	147	1000	1000	NUM
fis-3181	36	148	100	100	NUM
fis-3181	36	149	3	3	NUM
fis-3181	36	150	12	12	NUM
fis-3181	36	151	1	1	NUM
fis-3181	36	152	1000	1000	NUM
fis-3181	36	153	110	110	NUM
fis-3181	36	154	3	3	NUM
fis-3181	36	155	12	12	NUM
fis-3181	36	156	0	0	NUM
fis-3181	36	157	table	table	NOUN
fis-3181	36	158	1	1	NUM
fis-3181	36	159	:	:	PUNCT
fis-3181	36	160	experimental	experimental	ADJ
fis-3181	36	161	dataset	dataset	NOUN
fis-3181	36	162	.	.	PUNCT
fis-3181	37	1	a.	a.	PROPN
fis-3181	37	2	mishra	mishra	PROPN
fis-3181	37	3	et	et	PROPN
fis-3181	37	4	alii	alii	PROPN
fis-3181	37	5	,	,	PUNCT
fis-3181	37	6	frattura	frattura	PROPN
fis-3181	37	7	ed	ed	PROPN
fis-3181	37	8	integrità	integrità	PROPN
fis-3181	37	9	strutturale	strutturale	PROPN
fis-3181	37	10	,	,	PUNCT
fis-3181	37	11	58	58	NUM
fis-3181	37	12	(	(	PUNCT
fis-3181	37	13	2021	2021	NUM
fis-3181	37	14	)	)	PUNCT
fis-3181	37	15	242	242	NUM
fis-3181	37	16	-	-	SYM
fis-3181	37	17	253	253	NUM
fis-3181	37	18	;	;	PUNCT
fis-3181	37	19	doi	doi	NOUN
fis-3181	37	20	:	:	PUNCT
fis-3181	37	21	10.3221	10.3221	NUM
fis-3181	37	22	/	/	SYM
fis-3181	37	23	igf	igf	PROPN
fis-3181	37	24	-	-	PUNCT
fis-3181	37	25	esis.58.18	esis.58.18	PROPN
fis-3181	37	26	244	244	NUM
fis-3181	37	27	experimental	experimental	ADJ
fis-3181	37	28	procedure	procedure	NOUN
fis-3181	37	29	he	he	PRON
fis-3181	37	30	material	material	NOUN
fis-3181	37	31	used	use	VERB
fis-3181	37	32	for	for	ADP
fis-3181	37	33	welding	welding	NOUN
fis-3181	37	34	purpose	purpose	NOUN
fis-3181	37	35	belonged	belong	VERB
fis-3181	37	36	to	to	ADP
fis-3181	37	37	6xxx	6xxx	NUM
fis-3181	37	38	and	and	CCONJ
fis-3181	37	39	7xxx	7xxx	NUM
fis-3181	37	40	aluminium	aluminium	NOUN
fis-3181	37	41	series	series	NOUN
fis-3181	37	42	.	.	PUNCT
fis-3181	38	1	in	in	ADP
fis-3181	38	2	order	order	NOUN
fis-3181	38	3	to	to	PART
fis-3181	38	4	prepare	prepare	VERB
fis-3181	38	5	the	the	DET
fis-3181	38	6	plate	plate	NOUN
fis-3181	38	7	specimens	specimen	NOUN
fis-3181	38	8	machining	machining	NOUN
fis-3181	38	9	process	process	NOUN
fis-3181	38	10	was	be	AUX
fis-3181	38	11	done	do	VERB
fis-3181	38	12	to	to	PART
fis-3181	38	13	remove	remove	VERB
fis-3181	38	14	the	the	DET
fis-3181	38	15	uneven	uneven	ADJ
fis-3181	38	16	surfaces	surface	NOUN
fis-3181	38	17	.	.	PUNCT
fis-3181	39	1	the	the	DET
fis-3181	39	2	experimental	experimental	ADJ
fis-3181	39	3	dataset	dataset	NOUN
fis-3181	39	4	is	be	AUX
fis-3181	39	5	prepared	prepare	VERB
fis-3181	39	6	on	on	ADP
fis-3181	39	7	27	27	NUM
fis-3181	39	8	friction	friction	NOUN
fis-3181	39	9	stir	stir	NOUN
fis-3181	39	10	welded	weld	VERB
fis-3181	39	11	specimens	specimen	NOUN
fis-3181	39	12	[	[	X
fis-3181	39	13	12	12	NUM
fis-3181	39	14	]	]	PUNCT
fis-3181	39	15	.	.	PUNCT
fis-3181	40	1	for	for	ADP
fis-3181	40	2	testing	testing	NOUN
fis-3181	40	3	purpose	purpose	NOUN
fis-3181	40	4	the	the	DET
fis-3181	40	5	transverse	transverse	ADJ
fis-3181	40	6	tensile	tensile	NOUN
fis-3181	40	7	specimens	specimen	NOUN
fis-3181	40	8	were	be	AUX
fis-3181	40	9	prepared	prepare	VERB
fis-3181	40	10	according	accord	VERB
fis-3181	40	11	to	to	ADP
fis-3181	40	12	astm	astm	PROPN
fis-3181	40	13	e8m-04	e8m-04	PROPN
fis-3181	40	14	standard	standard	PROPN
fis-3181	40	15	shown	show	VERB
fis-3181	40	16	in	in	ADP
fis-3181	40	17	fig	fig	NOUN
fis-3181	40	18	.	.	PUNCT
fis-3181	41	1	1	1	X
fis-3181	41	2	.	.	X
fis-3181	41	3	tensile	tensile	NOUN
fis-3181	41	4	testing	testing	NOUN
fis-3181	41	5	was	be	AUX
fis-3181	41	6	carried	carry	VERB
fis-3181	41	7	out	out	ADP
fis-3181	41	8	at	at	ADP
fis-3181	41	9	a	a	DET
fis-3181	41	10	room	room	NOUN
fis-3181	41	11	temperature	temperature	NOUN
fis-3181	41	12	according	accord	VERB
fis-3181	41	13	to	to	ADP
fis-3181	41	14	astm	astm	PROPN
fis-3181	41	15	d	d	PROPN
fis-3181	41	16	557	557	NUM
fis-3181	41	17	m94	m94	NOUN
fis-3181	41	18	standards	standard	NOUN
fis-3181	41	19	.	.	PUNCT
fis-3181	42	1	in	in	ADP
fis-3181	42	2	the	the	DET
fis-3181	42	3	present	present	ADJ
fis-3181	42	4	research	research	NOUN
fis-3181	42	5	work	work	NOUN
fis-3181	42	6	,	,	PUNCT
fis-3181	42	7	python	python	NOUN
fis-3181	42	8	programming	programming	NOUN
fis-3181	42	9	language	language	NOUN
fis-3181	42	10	was	be	AUX
fis-3181	42	11	executed	execute	VERB
fis-3181	42	12	on	on	ADP
fis-3181	42	13	jupyter	jupyter	ADJ
fis-3181	42	14	lab	lab	NOUN
fis-3181	42	15	notebook	notebook	NOUN
fis-3181	42	16	for	for	ADP
fis-3181	42	17	subjecting	subject	VERB
fis-3181	42	18	the	the	DET
fis-3181	42	19	supervised	supervised	ADJ
fis-3181	42	20	machine	machine	NOUN
fis-3181	42	21	learning	learn	VERB
fis-3181	42	22	algorithms	algorithm	NOUN
fis-3181	42	23	on	on	ADP
fis-3181	42	24	the	the	DET
fis-3181	42	25	given	give	VERB
fis-3181	42	26	dataset	dataset	NOUN
fis-3181	42	27	[	[	X
fis-3181	42	28	12	12	NUM
fis-3181	42	29	]	]	PUNCT
fis-3181	42	30	.	.	PUNCT
fis-3181	43	1	jupyter	jupyter	PROPN
fis-3181	43	2	is	be	AUX
fis-3181	43	3	a	a	DET
fis-3181	43	4	web	web	NOUN
fis-3181	43	5	-	-	PUNCT
fis-3181	43	6	based	base	VERB
fis-3181	43	7	interactive	interactive	ADJ
fis-3181	43	8	development	development	NOUN
fis-3181	43	9	environment	environment	NOUN
fis-3181	43	10	that	that	PRON
fis-3181	43	11	supports	support	VERB
fis-3181	43	12	multiple	multiple	ADJ
fis-3181	43	13	programming	programming	NOUN
fis-3181	43	14	languages	language	NOUN
fis-3181	43	15	used	use	VERB
fis-3181	43	16	in	in	ADP
fis-3181	43	17	which	which	PRON
fis-3181	43	18	commonly	commonly	ADV
fis-3181	43	19	used	use	VERB
fis-3181	43	20	language	language	NOUN
fis-3181	43	21	is	be	AUX
fis-3181	43	22	python	python	NOUN
fis-3181	43	23	programming	programming	NOUN
fis-3181	43	24	.	.	PUNCT
fis-3181	44	1	tab	tab	PROPN
fis-3181	44	2	.	.	PUNCT
fis-3181	44	3	1	1	NUM
fis-3181	44	4	shows	show	VERB
fis-3181	44	5	the	the	DET
fis-3181	44	6	parameters	parameter	NOUN
fis-3181	44	7	involved	involve	VERB
fis-3181	44	8	in	in	ADP
fis-3181	44	9	the	the	DET
fis-3181	44	10	experimental	experimental	ADJ
fis-3181	44	11	study	study	NOUN
fis-3181	44	12	.	.	PUNCT
fis-3181	45	1	rotational	rotational	ADJ
fis-3181	45	2	speed	speed	NOUN
fis-3181	45	3	(	(	PUNCT
fis-3181	45	4	rpm	rpm	PROPN
fis-3181	45	5	)	)	PUNCT
fis-3181	45	6	,	,	PUNCT
fis-3181	45	7	welding	weld	VERB
fis-3181	45	8	speed	speed	NOUN
fis-3181	45	9	(	(	PUNCT
fis-3181	45	10	mm	mm	PROPN
fis-3181	45	11	/	/	SYM
fis-3181	45	12	min	min	NOUN
fis-3181	45	13	)	)	PUNCT
fis-3181	45	14	,	,	PUNCT
fis-3181	45	15	pin	pin	NOUN
fis-3181	45	16	profile	profile	VERB
fis-3181	45	17	,	,	PUNCT
fis-3181	45	18	and	and	CCONJ
fis-3181	45	19	axial	axial	ADJ
fis-3181	45	20	force	force	NOUN
fis-3181	45	21	(	(	PUNCT
fis-3181	45	22	kn	kn	PROPN
fis-3181	45	23	)	)	PUNCT
fis-3181	45	24	are	be	AUX
fis-3181	45	25	input	input	NOUN
fis-3181	45	26	parameters	parameter	NOUN
fis-3181	45	27	while	while	SCONJ
fis-3181	45	28	fracture	fracture	NOUN
fis-3181	45	29	position	position	NOUN
fis-3181	45	30	is	be	AUX
fis-3181	45	31	an	an	DET
fis-3181	45	32	output	output	NOUN
fis-3181	45	33	parameter	parameter	NOUN
fis-3181	45	34	.	.	PUNCT
fis-3181	46	1	figure	figure	NOUN
fis-3181	46	2	1	1	NUM
fis-3181	46	3	:	:	PUNCT
fis-3181	46	4	tensile	tensile	NOUN
fis-3181	46	5	test	test	NOUN
fis-3181	46	6	specimen	speciman	NOUN
fis-3181	47	1	[	[	X
fis-3181	47	2	12	12	NUM
fis-3181	47	3	]	]	X
fis-3181	47	4	pin	pin	NOUN
fis-3181	47	5	profiles	profile	NOUN
fis-3181	47	6	such	such	ADJ
fis-3181	47	7	as	as	ADP
fis-3181	47	8	simple	simple	ADJ
fis-3181	47	9	square	square	NOUN
fis-3181	47	10	is	be	AUX
fis-3181	47	11	labelled	label	VERB
fis-3181	47	12	as	as	ADP
fis-3181	47	13	1	1	NUM
fis-3181	47	14	,	,	PUNCT
fis-3181	47	15	taper	taper	NOUN
fis-3181	47	16	cylindrical	cylindrical	ADJ
fis-3181	47	17	threaded	threaded	NOUN
fis-3181	47	18	is	be	AUX
fis-3181	47	19	labelled	label	VERB
fis-3181	47	20	as	as	ADP
fis-3181	47	21	2	2	NUM
fis-3181	47	22	and	and	CCONJ
fis-3181	47	23	taper	taper	NOUN
fis-3181	47	24	square	square	ADJ
fis-3181	47	25	threaded	threaded	NOUN
fis-3181	47	26	is	be	AUX
fis-3181	47	27	labelled	label	VERB
fis-3181	47	28	as	as	ADP
fis-3181	47	29	3	3	NUM
fis-3181	47	30	while	while	SCONJ
fis-3181	47	31	the	the	DET
fis-3181	47	32	output	output	NOUN
fis-3181	47	33	column	column	NOUN
fis-3181	47	34	i.e.	i.e.	X
fis-3181	47	35	in	in	ADP
fis-3181	47	36	fracture	fracture	NOUN
fis-3181	47	37	position	position	NOUN
fis-3181	47	38	column	column	NOUN
fis-3181	47	39	,	,	PUNCT
fis-3181	47	40	the	the	DET
fis-3181	47	41	fracture	fracture	NOUN
fis-3181	47	42	occurring	occur	VERB
fis-3181	47	43	in	in	ADP
fis-3181	47	44	stir	stir	NOUN
fis-3181	47	45	zone	zone	NOUN
fis-3181	47	46	(	(	PUNCT
fis-3181	47	47	sz	sz	NOUN
fis-3181	47	48	)	)	PUNCT
fis-3181	47	49	is	be	AUX
fis-3181	47	50	labelled	label	VERB
fis-3181	47	51	as	as	ADP
fis-3181	47	52	0	0	NUM
fis-3181	47	53	and	and	CCONJ
fis-3181	47	54	fracture	fracture	NOUN
fis-3181	47	55	occurring	occur	VERB
fis-3181	47	56	at	at	ADP
fis-3181	47	57	heat	heat	NOUN
fis-3181	47	58	affected	affect	VERB
fis-3181	47	59	zone	zone	NOUN
fis-3181	47	60	(	(	PUNCT
fis-3181	47	61	haz	haz	PROPN
fis-3181	47	62	)	)	PUNCT
fis-3181	47	63	of	of	ADP
fis-3181	47	64	6061	6061	NUM
fis-3181	47	65	is	be	AUX
fis-3181	47	66	labelled	label	VERB
fis-3181	47	67	as	as	ADP
fis-3181	47	68	1	1	NUM
fis-3181	47	69	.	.	PUNCT
fis-3181	47	70	specimens	specimen	NOUN
fis-3181	47	71	after	after	ADP
fis-3181	47	72	and	and	CCONJ
fis-3181	47	73	before	before	SCONJ
fis-3181	47	74	tensile	tensile	NOUN
fis-3181	47	75	testing	testing	NOUN
fis-3181	47	76	are	be	AUX
fis-3181	47	77	shown	show	VERB
fis-3181	47	78	in	in	ADP
fis-3181	47	79	fig	fig	NOUN
fis-3181	47	80	.	.	PUNCT
fis-3181	48	1	2	2	NUM
fis-3181	48	2	a	a	NOUN
fis-3181	48	3	)	)	PUNCT
fis-3181	48	4	and	and	CCONJ
fis-3181	48	5	2	2	NUM
fis-3181	48	6	b	b	NOUN
fis-3181	48	7	)	)	PUNCT
fis-3181	48	8	.	.	PUNCT
fis-3181	49	1	(	(	PUNCT
fis-3181	49	2	a	a	X
fis-3181	49	3	)	)	PUNCT
fis-3181	49	4	(	(	PUNCT
fis-3181	49	5	b	b	X
fis-3181	49	6	)	)	PUNCT
fis-3181	49	7	figure	figure	NOUN
fis-3181	49	8	2	2	NUM
fis-3181	49	9	:	:	PUNCT
fis-3181	49	10	a	a	X
fis-3181	49	11	)	)	PUNCT
fis-3181	49	12	specimens	specimen	NOUN
fis-3181	49	13	before	before	ADP
fis-3181	49	14	testing	testing	NOUN
fis-3181	49	15	;	;	PUNCT
fis-3181	49	16	b	b	X
fis-3181	49	17	)	)	PUNCT
fis-3181	49	18	specimens	specimen	NOUN
fis-3181	49	19	after	after	ADP
fis-3181	49	20	testing	testing	NOUN
fis-3181	49	21	.	.	PUNCT
fis-3181	50	1	the	the	DET
fis-3181	50	2	required	require	VERB
fis-3181	50	3	python	python	NOUN
fis-3181	50	4	libraries	library	NOUN
fis-3181	50	5	such	such	ADJ
fis-3181	50	6	as	as	ADP
fis-3181	50	7	pandas	panda	NOUN
fis-3181	50	8	,	,	PUNCT
fis-3181	50	9	numpy	numpy	NOUN
fis-3181	50	10	,	,	PUNCT
fis-3181	50	11	seaborn	seaborn	NOUN
fis-3181	50	12	,	,	PUNCT
fis-3181	50	13	and	and	CCONJ
fis-3181	50	14	pyplot	pyplot	NOUN
fis-3181	50	15	were	be	AUX
fis-3181	50	16	imported	import	VERB
fis-3181	50	17	.	.	PUNCT
fis-3181	51	1	after	after	ADP
fis-3181	51	2	importing	import	VERB
fis-3181	51	3	the	the	DET
fis-3181	51	4	libraries	library	NOUN
fis-3181	51	5	,	,	PUNCT
fis-3181	51	6	the	the	DET
fis-3181	51	7	dataset	dataset	NOUN
fis-3181	51	8	was	be	AUX
fis-3181	51	9	loaded	load	VERB
fis-3181	51	10	into	into	ADP
fis-3181	51	11	the	the	DET
fis-3181	51	12	jupyter	jupyter	ADJ
fis-3181	51	13	environment	environment	NOUN
fis-3181	51	14	.	.	PUNCT
fis-3181	52	1	pair	pair	NOUN
fis-3181	52	2	plot	plot	NOUN
fis-3181	52	3	function	function	NOUN
fis-3181	52	4	is	be	AUX
fis-3181	52	5	used	use	VERB
fis-3181	52	6	for	for	ADP
fis-3181	52	7	establishing	establish	VERB
fis-3181	52	8	the	the	DET
fis-3181	52	9	relationship	relationship	NOUN
fis-3181	52	10	between	between	ADP
fis-3181	52	11	t	t	PROPN
fis-3181	52	12	a.	a.	PROPN
fis-3181	52	13	mishra	mishra	PROPN
fis-3181	52	14	et	et	PROPN
fis-3181	52	15	alii	alii	PROPN
fis-3181	52	16	,	,	PUNCT
fis-3181	52	17	frattura	frattura	PROPN
fis-3181	52	18	ed	ed	PROPN
fis-3181	52	19	integrità	integrità	PROPN
fis-3181	52	20	strutturale	strutturale	PROPN
fis-3181	52	21	,	,	PUNCT
fis-3181	52	22	58	58	NUM
fis-3181	52	23	(	(	PUNCT
fis-3181	52	24	2021	2021	NUM
fis-3181	52	25	)	)	PUNCT
fis-3181	52	26	242	242	NUM
fis-3181	52	27	-	-	SYM
fis-3181	52	28	253	253	NUM
fis-3181	52	29	;	;	PUNCT
fis-3181	52	30	doi	doi	NOUN
fis-3181	52	31	:	:	PUNCT
fis-3181	52	32	10.3221	10.3221	NUM
fis-3181	52	33	/	/	SYM
fis-3181	52	34	igf	igf	PROPN
fis-3181	52	35	-	-	PUNCT
fis-3181	52	36	esis.58.18	esis.58.18	PROPN
fis-3181	52	37	245	245	NUM
fis-3181	52	38	the	the	DET
fis-3181	52	39	multiple	multiple	ADJ
fis-3181	52	40	pairwise	pairwise	NOUN
fis-3181	52	41	bivariate	bivariate	ADJ
fis-3181	52	42	distributions	distribution	NOUN
fis-3181	52	43	in	in	ADP
fis-3181	52	44	a	a	DET
fis-3181	52	45	given	give	VERB
fis-3181	52	46	dataset	dataset	NOUN
fis-3181	52	47	as	as	SCONJ
fis-3181	52	48	shown	show	VERB
fis-3181	52	49	in	in	ADP
fis-3181	52	50	fig	fig	NOUN
fis-3181	52	51	.	.	PUNCT
fis-3181	53	1	3	3	X
fis-3181	53	2	.	.	X
fis-3181	53	3	count	count	NOUN
fis-3181	53	4	function	function	NOUN
fis-3181	53	5	was	be	AUX
fis-3181	53	6	subjected	subject	VERB
fis-3181	53	7	to	to	ADP
fis-3181	53	8	the	the	DET
fis-3181	53	9	given	give	VERB
fis-3181	53	10	dataset	dataset	NOUN
fis-3181	53	11	to	to	PART
fis-3181	53	12	obtain	obtain	VERB
fis-3181	53	13	the	the	DET
fis-3181	53	14	number	number	NOUN
fis-3181	53	15	of	of	ADP
fis-3181	53	16	0s	0s	NUM
fis-3181	53	17	and	and	CCONJ
fis-3181	53	18	1s	1s	NUM
fis-3181	53	19	in	in	ADP
fis-3181	53	20	the	the	DET
fis-3181	53	21	output	output	NOUN
fis-3181	53	22	column	column	NOUN
fis-3181	53	23	i.e.	i.e.	X
fis-3181	53	24	in	in	ADP
fis-3181	53	25	the	the	DET
fis-3181	53	26	fracture	fracture	NOUN
fis-3181	53	27	position	position	NOUN
fis-3181	53	28	column	column	NOUN
fis-3181	53	29	as	as	SCONJ
fis-3181	53	30	shown	show	VERB
fis-3181	53	31	in	in	ADP
fis-3181	53	32	fig	fig	NOUN
fis-3181	53	33	.	.	PUNCT
fis-3181	54	1	4	4	X
fis-3181	54	2	.	.	X
fis-3181	54	3	figure	figure	VERB
fis-3181	54	4	3	3	NUM
fis-3181	54	5	:	:	PUNCT
fis-3181	54	6	multiple	multiple	ADJ
fis-3181	54	7	pairwise	pairwise	NOUN
fis-3181	54	8	bivariate	bivariate	ADJ
fis-3181	54	9	distributions	distribution	NOUN
fis-3181	54	10	.	.	PUNCT
fis-3181	55	1	a.	a.	PROPN
fis-3181	55	2	mishra	mishra	PROPN
fis-3181	55	3	et	et	PROPN
fis-3181	55	4	alii	alii	PROPN
fis-3181	55	5	,	,	PUNCT
fis-3181	55	6	frattura	frattura	PROPN
fis-3181	55	7	ed	ed	PROPN
fis-3181	55	8	integrità	integrità	PROPN
fis-3181	55	9	strutturale	strutturale	PROPN
fis-3181	55	10	,	,	PUNCT
fis-3181	55	11	58	58	NUM
fis-3181	55	12	(	(	PUNCT
fis-3181	55	13	2021	2021	NUM
fis-3181	55	14	)	)	PUNCT
fis-3181	55	15	242	242	NUM
fis-3181	55	16	-	-	SYM
fis-3181	55	17	253	253	NUM
fis-3181	55	18	;	;	PUNCT
fis-3181	55	19	doi	doi	NOUN
fis-3181	55	20	:	:	PUNCT
fis-3181	55	21	10.3221	10.3221	NUM
fis-3181	55	22	/	/	SYM
fis-3181	55	23	igf	igf	PROPN
fis-3181	55	24	-	-	PUNCT
fis-3181	55	25	esis.58.18	esis.58.18	PROPN
fis-3181	55	26	246	246	NUM
fis-3181	55	27	figure	figure	NOUN
fis-3181	55	28	4	4	NUM
fis-3181	55	29	:	:	PUNCT
fis-3181	55	30	counting	count	VERB
fis-3181	55	31	numbers	number	NOUN
fis-3181	55	32	of	of	ADP
fis-3181	55	33	0s	0s	NUM
fis-3181	55	34	and	and	CCONJ
fis-3181	55	35	1s	1s	NUM
fis-3181	55	36	.	.	PUNCT
fis-3181	56	1	as	as	SCONJ
fis-3181	56	2	shown	show	VERB
fis-3181	56	3	in	in	ADP
fis-3181	56	4	fig	fig	NOUN
fis-3181	56	5	.	.	PUNCT
fis-3181	57	1	5	5	NUM
fis-3181	57	2	,	,	PUNCT
fis-3181	57	3	exploratory	exploratory	ADJ
fis-3181	57	4	data	datum	NOUN
fis-3181	57	5	analysis	analysis	NOUN
fis-3181	57	6	is	be	AUX
fis-3181	57	7	used	use	VERB
fis-3181	57	8	to	to	PART
fis-3181	57	9	know	know	VERB
fis-3181	57	10	about	about	ADP
fis-3181	57	11	the	the	DET
fis-3181	57	12	data	datum	NOUN
fis-3181	57	13	pattern	pattern	NOUN
fis-3181	57	14	and	and	CCONJ
fis-3181	57	15	further	far	ADV
fis-3181	57	16	summarize	summarize	VERB
fis-3181	57	17	their	their	PRON
fis-3181	57	18	main	main	ADJ
fis-3181	57	19	characteristics	characteristic	NOUN
fis-3181	57	20	.	.	PUNCT
fis-3181	58	1	figure	figure	NOUN
fis-3181	58	2	5	5	NUM
fis-3181	58	3	:	:	PUNCT
fis-3181	58	4	exploratory	exploratory	ADJ
fis-3181	58	5	data	datum	NOUN
fis-3181	58	6	analysis	analysis	NOUN
fis-3181	58	7	in	in	ADP
fis-3181	58	8	order	order	NOUN
fis-3181	58	9	to	to	PART
fis-3181	58	10	find	find	VERB
fis-3181	58	11	out	out	ADP
fis-3181	58	12	the	the	DET
fis-3181	58	13	important	important	ADJ
fis-3181	58	14	input	input	NOUN
fis-3181	58	15	parameters	parameter	NOUN
fis-3181	58	16	affecting	affect	VERB
fis-3181	58	17	the	the	DET
fis-3181	58	18	output	output	NOUN
fis-3181	58	19	parameter	parameter	NOUN
fis-3181	58	20	,	,	PUNCT
fis-3181	58	21	the	the	DET
fis-3181	58	22	feature	feature	NOUN
fis-3181	58	23	importance	importance	NOUN
fis-3181	58	24	method	method	NOUN
fis-3181	58	25	was	be	AUX
fis-3181	58	26	used	use	VERB
fis-3181	58	27	.	.	PUNCT
fis-3181	59	1	from	from	ADP
fis-3181	59	2	fig	fig	NOUN
fis-3181	59	3	.	.	PUNCT
fis-3181	60	1	6	6	NUM
fis-3181	60	2	it	it	PRON
fis-3181	60	3	is	be	AUX
fis-3181	60	4	observed	observe	VERB
fis-3181	60	5	that	that	SCONJ
fis-3181	60	6	the	the	DET
fis-3181	60	7	axial	axial	ADJ
fis-3181	60	8	force	force	NOUN
fis-3181	60	9	(	(	PUNCT
fis-3181	60	10	kn	kn	NOUN
fis-3181	60	11	)	)	PUNCT
fis-3181	60	12	parameter	parameter	NOUN
fis-3181	60	13	creates	create	VERB
fis-3181	60	14	no	no	DET
fis-3181	60	15	effect	effect	NOUN
fis-3181	60	16	on	on	ADP
fis-3181	60	17	the	the	DET
fis-3181	60	18	output	output	NOUN
fis-3181	60	19	parameter	parameter	NOUN
fis-3181	60	20	.	.	PUNCT
fis-3181	61	1	so	so	ADV
fis-3181	61	2	due	due	ADP
fis-3181	61	3	to	to	ADP
fis-3181	61	4	this	this	DET
fis-3181	61	5	reason	reason	NOUN
fis-3181	61	6	,	,	PUNCT
fis-3181	61	7	this	this	DET
fis-3181	61	8	parameter	parameter	NOUN
fis-3181	61	9	is	be	AUX
fis-3181	61	10	dropped	drop	VERB
fis-3181	61	11	from	from	ADP
fis-3181	61	12	the	the	DET
fis-3181	61	13	input	input	NOUN
fis-3181	61	14	parameters	parameter	NOUN
fis-3181	61	15	which	which	PRON
fis-3181	61	16	are	be	AUX
fis-3181	61	17	subjected	subject	VERB
fis-3181	61	18	to	to	ADP
fis-3181	61	19	machine	machine	NOUN
fis-3181	61	20	learning	learning	NOUN
fis-3181	61	21	algorithms	algorithm	NOUN
fis-3181	61	22	.	.	PUNCT
fis-3181	62	1	a.	a.	PROPN
fis-3181	62	2	mishra	mishra	PROPN
fis-3181	62	3	et	et	PROPN
fis-3181	62	4	alii	alii	PROPN
fis-3181	62	5	,	,	PUNCT
fis-3181	62	6	frattura	frattura	PROPN
fis-3181	62	7	ed	ed	PROPN
fis-3181	62	8	integrità	integrità	PROPN
fis-3181	62	9	strutturale	strutturale	PROPN
fis-3181	62	10	,	,	PUNCT
fis-3181	62	11	58	58	NUM
fis-3181	62	12	(	(	PUNCT
fis-3181	62	13	2021	2021	NUM
fis-3181	62	14	)	)	PUNCT
fis-3181	62	15	242	242	NUM
fis-3181	62	16	-	-	SYM
fis-3181	62	17	253	253	NUM
fis-3181	62	18	;	;	PUNCT
fis-3181	62	19	doi	doi	NOUN
fis-3181	62	20	:	:	PUNCT
fis-3181	62	21	10.3221	10.3221	NUM
fis-3181	62	22	/	/	SYM
fis-3181	62	23	igf	igf	PROPN
fis-3181	62	24	-	-	PUNCT
fis-3181	62	25	esis.58.18	esis.58.18	VERB
fis-3181	62	26	247	247	NUM
fis-3181	62	27	figure	figure	NOUN
fis-3181	62	28	6	6	NUM
fis-3181	62	29	:	:	PUNCT
fis-3181	62	30	calculation	calculation	NOUN
fis-3181	62	31	of	of	ADP
fis-3181	62	32	feature	feature	NOUN
fis-3181	62	33	importance	importance	NOUN
fis-3181	62	34	results	result	NOUN
fis-3181	62	35	and	and	CCONJ
fis-3181	62	36	discussion	discussion	NOUN
fis-3181	62	37	decision	decision	NOUN
fis-3181	62	38	tree	tree	NOUN
fis-3181	62	39	algorithm	algorithm	NOUN
fis-3181	62	40	decision	decision	NOUN
fis-3181	62	41	tree	tree	NOUN
fis-3181	62	42	is	be	AUX
fis-3181	62	43	a	a	DET
fis-3181	62	44	supervised	supervised	ADJ
fis-3181	62	45	machine	machine	NOUN
fis-3181	62	46	learning	learn	VERB
fis-3181	62	47	algorithm	algorithm	NOUN
fis-3181	62	48	that	that	PRON
fis-3181	62	49	can	can	AUX
fis-3181	62	50	be	be	AUX
fis-3181	62	51	both	both	PRON
fis-3181	62	52	implemented	implement	VERB
fis-3181	62	53	for	for	ADP
fis-3181	62	54	classification	classification	NOUN
fis-3181	62	55	and	and	CCONJ
fis-3181	62	56	regression	regression	NOUN
fis-3181	62	57	analysis	analysis	NOUN
fis-3181	62	58	.	.	PUNCT
fis-3181	63	1	a	a	DET
fis-3181	63	2	decision	decision	NOUN
fis-3181	63	3	tree	tree	NOUN
fis-3181	63	4	model	model	NOUN
fis-3181	63	5	consists	consist	VERB
fis-3181	63	6	of	of	ADP
fis-3181	63	7	a	a	DET
fis-3181	63	8	terminal	terminal	ADJ
fis-3181	63	9	node	node	NOUN
fis-3181	63	10	,	,	PUNCT
fis-3181	63	11	a	a	DET
fis-3181	63	12	decision	decision	NOUN
fis-3181	63	13	node	node	NOUN
fis-3181	63	14	,	,	PUNCT
fis-3181	63	15	and	and	CCONJ
fis-3181	63	16	a	a	DET
fis-3181	63	17	root	root	NOUN
fis-3181	63	18	node	node	NOUN
fis-3181	63	19	as	as	SCONJ
fis-3181	63	20	seen	see	VERB
fis-3181	63	21	in	in	ADP
fis-3181	63	22	fig	fig	NOUN
fis-3181	63	23	.	.	PUNCT
fis-3181	64	1	7	7	X
fis-3181	64	2	.	.	X
fis-3181	64	3	figure	figure	NOUN
fis-3181	64	4	7	7	NUM
fis-3181	64	5	:	:	PUNCT
fis-3181	64	6	decision	decision	NOUN
fis-3181	64	7	tree	tree	NOUN
fis-3181	64	8	algorithm	algorithm	NOUN
fis-3181	64	9	architecture	architecture	NOUN
fis-3181	64	10	.	.	PUNCT
fis-3181	65	1	the	the	DET
fis-3181	65	2	main	main	ADJ
fis-3181	65	3	objective	objective	NOUN
fis-3181	65	4	is	be	AUX
fis-3181	65	5	to	to	PART
fis-3181	65	6	create	create	VERB
fis-3181	65	7	many	many	ADJ
fis-3181	65	8	pure	pure	ADJ
fis-3181	65	9	nodes	node	NOUN
fis-3181	65	10	with	with	ADP
fis-3181	65	11	the	the	DET
fis-3181	65	12	help	help	NOUN
fis-3181	65	13	of	of	ADP
fis-3181	65	14	the	the	DET
fis-3181	65	15	splitting	splitting	NOUN
fis-3181	65	16	process	process	NOUN
fis-3181	65	17	.	.	PUNCT
fis-3181	66	1	the	the	DET
fis-3181	66	2	nodes	node	NOUN
fis-3181	66	3	can	can	AUX
fis-3181	66	4	be	be	AUX
fis-3181	66	5	further	far	ADV
fis-3181	66	6	categorized	categorize	VERB
fis-3181	66	7	as	as	ADP
fis-3181	66	8	pure	pure	ADJ
fis-3181	66	9	or	or	CCONJ
fis-3181	66	10	homogenous	homogenous	ADJ
fis-3181	66	11	nodes	node	NOUN
fis-3181	66	12	and	and	CCONJ
fis-3181	66	13	impure	impure	NOUN
fis-3181	66	14	or	or	CCONJ
fis-3181	66	15	heterogeneous	heterogeneous	ADJ
fis-3181	66	16	nodes	node	NOUN
fis-3181	66	17	.	.	PUNCT
fis-3181	67	1	after	after	ADP
fis-3181	67	2	the	the	DET
fis-3181	67	3	splitting	splitting	NOUN
fis-3181	67	4	operation	operation	NOUN
fis-3181	67	5	,	,	PUNCT
fis-3181	67	6	the	the	DET
fis-3181	67	7	pure	pure	ADJ
fis-3181	67	8	node	node	NOUN
fis-3181	67	9	contains	contain	VERB
fis-3181	67	10	the	the	DET
fis-3181	67	11	data	data	NOUN
fis-3181	67	12	points	point	NOUN
fis-3181	67	13	which	which	PRON
fis-3181	67	14	belong	belong	VERB
fis-3181	67	15	to	to	ADP
fis-3181	67	16	the	the	DET
fis-3181	67	17	same	same	ADJ
fis-3181	67	18	class	class	NOUN
fis-3181	67	19	while	while	SCONJ
fis-3181	67	20	the	the	DET
fis-3181	67	21	impure	impure	NOUN
fis-3181	67	22	node	node	NOUN
fis-3181	67	23	contains	contain	VERB
fis-3181	67	24	the	the	DET
fis-3181	67	25	data	data	NOUN
fis-3181	67	26	points	point	NOUN
fis-3181	67	27	that	that	PRON
fis-3181	67	28	belong	belong	VERB
fis-3181	67	29	to	to	ADP
fis-3181	67	30	a	a	DET
fis-3181	67	31	different	different	ADJ
fis-3181	67	32	class	class	NOUN
fis-3181	67	33	.	.	PUNCT
fis-3181	68	1	the	the	DET
fis-3181	68	2	three	three	NUM
fis-3181	68	3	important	important	ADJ
fis-3181	68	4	parameters	parameter	NOUN
fis-3181	68	5	which	which	PRON
fis-3181	68	6	are	be	AUX
fis-3181	68	7	used	use	VERB
fis-3181	68	8	to	to	PART
fis-3181	68	9	determine	determine	VERB
fis-3181	68	10	the	the	DET
fis-3181	68	11	level	level	NOUN
fis-3181	68	12	of	of	ADP
fis-3181	68	13	impurity	impurity	NOUN
fis-3181	68	14	are	be	AUX
fis-3181	68	15	gini	gini	PROPN
fis-3181	68	16	index	index	PROPN
fis-3181	68	17	,	,	PUNCT
fis-3181	68	18	entropy	entropy	NOUN
fis-3181	68	19	,	,	PUNCT
fis-3181	68	20	and	and	CCONJ
fis-3181	68	21	classification	classification	NOUN
fis-3181	68	22	error	error	NOUN
fis-3181	68	23	.	.	PUNCT
fis-3181	69	1	it	it	PRON
fis-3181	69	2	should	should	AUX
fis-3181	69	3	be	be	AUX
fis-3181	69	4	noted	note	VERB
fis-3181	69	5	that	that	SCONJ
fis-3181	69	6	the	the	DET
fis-3181	69	7	information	information	NOUN
fis-3181	69	8	gain	gain	NOUN
fis-3181	69	9	and	and	CCONJ
fis-3181	69	10	entropy	entropy	NOUN
fis-3181	69	11	are	be	AUX
fis-3181	69	12	related	relate	VERB
fis-3181	69	13	to	to	ADP
fis-3181	69	14	each	each	DET
fis-3181	69	15	other	other	ADJ
fis-3181	69	16	as	as	SCONJ
fis-3181	69	17	seen	see	VERB
fis-3181	69	18	in	in	ADP
fis-3181	69	19	eqn	eqn	NOUN
fis-3181	69	20	.	.	PUNCT
fis-3181	70	1	1	1	NUM
fis-3181	70	2	while	while	SCONJ
fis-3181	70	3	entropy	entropy	NOUN
fis-3181	70	4	can	can	AUX
fis-3181	70	5	be	be	AUX
fis-3181	70	6	further	far	ADV
fis-3181	70	7	calculated	calculate	VERB
fis-3181	70	8	by	by	ADP
fis-3181	70	9	eqn	eqn	NOUN
fis-3181	70	10	.	.	PUNCT
fis-3181	71	1	2	2	X
fis-3181	71	2	.	.	X
fis-3181	71	3	a	a	DET
fis-3181	71	4	a.	a.	NOUN
fis-3181	71	5	mishra	mishra	PROPN
fis-3181	71	6	et	et	PROPN
fis-3181	71	7	alii	alii	PROPN
fis-3181	71	8	,	,	PUNCT
fis-3181	71	9	frattura	frattura	PROPN
fis-3181	71	10	ed	ed	PROPN
fis-3181	71	11	integrità	integrità	PROPN
fis-3181	71	12	strutturale	strutturale	PROPN
fis-3181	71	13	,	,	PUNCT
fis-3181	71	14	58	58	NUM
fis-3181	71	15	(	(	PUNCT
fis-3181	71	16	2021	2021	NUM
fis-3181	71	17	)	)	PUNCT
fis-3181	71	18	242	242	NUM
fis-3181	71	19	-	-	SYM
fis-3181	71	20	253	253	NUM
fis-3181	71	21	;	;	PUNCT
fis-3181	71	22	doi	doi	NOUN
fis-3181	71	23	:	:	PUNCT
fis-3181	71	24	10.3221	10.3221	NUM
fis-3181	71	25	/	/	SYM
fis-3181	71	26	igf	igf	PROPN
fis-3181	71	27	-	-	PUNCT
fis-3181	71	28	esis.58.18	esis.58.18	PROPN
fis-3181	71	29	248	248	NUM
fis-3181	71	30			NUM
fis-3181	71	31			NOUN
fis-3181	71	32	  	  	SPACE
fis-3181	71	33	1informationgain	1informationgain	NUM
fis-3181	71	34	entropy	entropy	NOUN
fis-3181	71	35	(	(	PUNCT
fis-3181	71	36	1	1	NUM
fis-3181	71	37	)	)	PUNCT
fis-3181	71	38			PROPN
fis-3181	71	39			PROPN
fis-3181	71	40			VERB
fis-3181	71	41			NOUN
fis-3181	71	42	2	2	VERB
fis-3181	71	43	2entropy	2entropy	NUM
fis-3181	71	44	p	p	NOUN
fis-3181	71	45	log	log	NOUN
fis-3181	71	46	p	p	NOUN
fis-3181	71	47	q	q	NOUN
fis-3181	71	48	log	log	NOUN
fis-3181	71	49	q	q	NOUN
fis-3181	71	50	(	(	PUNCT
fis-3181	71	51	2	2	NUM
fis-3181	71	52	)	)	PUNCT
fis-3181	71	53	where	where	SCONJ
fis-3181	71	54	probabilities	probability	NOUN
fis-3181	71	55	of	of	ADP
fis-3181	71	56	success	success	NOUN
fis-3181	71	57	and	and	CCONJ
fis-3181	71	58	failure	failure	NOUN
fis-3181	71	59	are	be	AUX
fis-3181	71	60	represented	represent	VERB
fis-3181	71	61	by	by	ADP
fis-3181	71	62	p	p	NOUN
fis-3181	71	63	and	and	CCONJ
fis-3181	71	64	q	q	NOUN
fis-3181	71	65	respectively	respectively	ADV
fis-3181	71	66	.	.	PUNCT
fis-3181	72	1	fig	fig	NOUN
fis-3181	72	2	.	.	PUNCT
fis-3181	73	1	8	8	NUM
fis-3181	73	2	shows	show	VERB
fis-3181	73	3	the	the	DET
fis-3181	73	4	decision	decision	NOUN
fis-3181	73	5	tree	tree	NOUN
fis-3181	73	6	plot	plot	NOUN
fis-3181	73	7	for	for	ADP
fis-3181	73	8	the	the	DET
fis-3181	73	9	given	give	VERB
fis-3181	73	10	parameters	parameter	NOUN
fis-3181	73	11	in	in	ADP
fis-3181	73	12	the	the	DET
fis-3181	73	13	dataset	dataset	NOUN
fis-3181	73	14	.	.	PUNCT
fis-3181	74	1	fig	fig	NOUN
fis-3181	74	2	.	.	PUNCT
fis-3181	75	1	9	9	NUM
fis-3181	75	2	shows	show	VERB
fis-3181	75	3	the	the	DET
fis-3181	75	4	confusion	confusion	NOUN
fis-3181	75	5	matrix	matrix	NOUN
fis-3181	75	6	which	which	PRON
fis-3181	75	7	is	be	AUX
fis-3181	75	8	used	use	VERB
fis-3181	75	9	to	to	PART
fis-3181	75	10	describe	describe	VERB
fis-3181	75	11	the	the	DET
fis-3181	75	12	performance	performance	NOUN
fis-3181	75	13	of	of	ADP
fis-3181	75	14	the	the	DET
fis-3181	75	15	classification	classification	NOUN
fis-3181	75	16	model	model	NOUN
fis-3181	75	17	.	.	PUNCT
fis-3181	76	1	tab	tab	NOUN
fis-3181	76	2	.	.	PUNCT
fis-3181	76	3	2	2	NUM
fis-3181	76	4	shows	show	VERB
fis-3181	76	5	the	the	DET
fis-3181	76	6	classification	classification	NOUN
fis-3181	76	7	report	report	NOUN
fis-3181	76	8	of	of	ADP
fis-3181	76	9	the	the	DET
fis-3181	76	10	decision	decision	NOUN
fis-3181	76	11	tree	tree	NOUN
fis-3181	76	12	algorithm	algorithm	NOUN
fis-3181	76	13	.	.	PUNCT
fis-3181	77	1	figure	figure	VERB
fis-3181	77	2	8	8	NUM
fis-3181	77	3	:	:	PUNCT
fis-3181	77	4	decision	decision	NOUN
fis-3181	77	5	tree	tree	NOUN
fis-3181	77	6	plot	plot	NOUN
fis-3181	77	7	for	for	ADP
fis-3181	77	8	the	the	DET
fis-3181	77	9	experimental	experimental	ADJ
fis-3181	77	10	study	study	NOUN
fis-3181	77	11	.	.	PUNCT
fis-3181	78	1	figure	figure	VERB
fis-3181	78	2	9	9	NUM
fis-3181	78	3	:	:	PUNCT
fis-3181	78	4	confusion	confusion	NOUN
fis-3181	78	5	matrix	matrix	NOUN
fis-3181	78	6	showing	show	VERB
fis-3181	78	7	the	the	DET
fis-3181	78	8	performance	performance	NOUN
fis-3181	78	9	of	of	ADP
fis-3181	78	10	decision	decision	NOUN
fis-3181	78	11	tree	tree	NOUN
fis-3181	78	12	algorithm	algorithm	NOUN
fis-3181	78	13	.	.	PUNCT
fis-3181	79	1	a.	a.	PROPN
fis-3181	79	2	mishra	mishra	PROPN
fis-3181	79	3	et	et	PROPN
fis-3181	79	4	alii	alii	PROPN
fis-3181	79	5	,	,	PUNCT
fis-3181	79	6	frattura	frattura	PROPN
fis-3181	79	7	ed	ed	PROPN
fis-3181	79	8	integrità	integrità	PROPN
fis-3181	79	9	strutturale	strutturale	PROPN
fis-3181	79	10	,	,	PUNCT
fis-3181	79	11	58	58	NUM
fis-3181	79	12	(	(	PUNCT
fis-3181	79	13	2021	2021	NUM
fis-3181	79	14	)	)	PUNCT
fis-3181	79	15	242	242	NUM
fis-3181	79	16	-	-	SYM
fis-3181	79	17	253	253	NUM
fis-3181	79	18	;	;	PUNCT
fis-3181	79	19	doi	doi	NOUN
fis-3181	79	20	:	:	PUNCT
fis-3181	79	21	10.3221	10.3221	NUM
fis-3181	79	22	/	/	SYM
fis-3181	79	23	igf	igf	PROPN
fis-3181	79	24	-	-	PUNCT
fis-3181	79	25	esis.58.18	esis.58.18	PROPN
fis-3181	79	26	249	249	NUM
fis-3181	79	27	precision	precision	NOUN
fis-3181	79	28	recall	recall	NOUN
fis-3181	79	29	f1	f1	NOUN
fis-3181	79	30	-	-	PUNCT
fis-3181	79	31	score	score	NOUN
fis-3181	79	32	0	0	NUM
fis-3181	79	33	0.00	0.00	NUM
fis-3181	79	34	0.00	0.00	NUM
fis-3181	79	35	0.00	0.00	NUM
fis-3181	79	36	1	1	NUM
fis-3181	79	37	0.88	0.88	NUM
fis-3181	79	38	0.88	0.88	NUM
fis-3181	79	39	0.88	0.88	NUM
fis-3181	79	40	accuracy	accuracy	NOUN
fis-3181	79	41	0.78	0.78	NUM
fis-3181	79	42	macro	macro	NOUN
fis-3181	79	43	average	average	ADJ
fis-3181	79	44	0.44	0.44	NUM
fis-3181	79	45	0.44	0.44	NUM
fis-3181	79	46	0.44	0.44	NUM
fis-3181	79	47	weighted	weight	VERB
fis-3181	79	48	average	average	ADJ
fis-3181	79	49	0.78	0.78	NUM
fis-3181	79	50	0.78	0.78	NUM
fis-3181	79	51	0.78	0.78	NUM
fis-3181	79	52	table	table	NOUN
fis-3181	79	53	2	2	NUM
fis-3181	79	54	:	:	PUNCT
fis-3181	79	55	classification	classification	NOUN
fis-3181	79	56	report	report	NOUN
fis-3181	79	57	of	of	ADP
fis-3181	79	58	decision	decision	NOUN
fis-3181	79	59	tree	tree	NOUN
fis-3181	79	60	algorithm	algorithm	NOUN
fis-3181	79	61	.	.	PUNCT
fis-3181	80	1	from	from	ADP
fis-3181	80	2	the	the	DET
fis-3181	80	3	tab	tab	NOUN
fis-3181	80	4	.	.	PUNCT
fis-3181	81	1	2	2	NUM
fis-3181	81	2	it	it	PRON
fis-3181	81	3	is	be	AUX
fis-3181	81	4	observed	observe	VERB
fis-3181	81	5	that	that	SCONJ
fis-3181	81	6	the	the	DET
fis-3181	81	7	accuracy	accuracy	NOUN
fis-3181	81	8	score	score	NOUN
fis-3181	81	9	obtained	obtain	VERB
fis-3181	81	10	from	from	ADP
fis-3181	81	11	the	the	DET
fis-3181	81	12	decision	decision	NOUN
fis-3181	81	13	tree	tree	NOUN
fis-3181	81	14	algorithm	algorithm	NOUN
fis-3181	81	15	is	be	AUX
fis-3181	81	16	0.78	0.78	NUM
fis-3181	81	17	.	.	PUNCT
fis-3181	82	1	k	k	X
fis-3181	82	2	-	-	PUNCT
fis-3181	82	3	nearest	near	ADJ
fis-3181	82	4	neighbor	neighbor	NOUN
fis-3181	82	5	algorithm	algorithm	NOUN
fis-3181	82	6	-nearest	-near	ADJ
fis-3181	82	7	neighbors	neighbor	NOUN
fis-3181	82	8	(	(	PUNCT
fis-3181	82	9	knn	knn	PROPN
fis-3181	82	10	)	)	PUNCT
fis-3181	82	11	are	be	AUX
fis-3181	82	12	the	the	DET
fis-3181	82	13	most	most	ADV
fis-3181	82	14	popularly	popularly	ADV
fis-3181	82	15	used	use	VERB
fis-3181	82	16	machine	machine	NOUN
fis-3181	82	17	learning	learn	VERB
fis-3181	82	18	algorithm	algorithm	NOUN
fis-3181	82	19	where	where	SCONJ
fis-3181	82	20	learning	learning	NOUN
fis-3181	82	21	is	be	AUX
fis-3181	82	22	based	base	VERB
fis-3181	82	23	on	on	ADP
fis-3181	82	24	the	the	DET
fis-3181	82	25	availability	availability	NOUN
fis-3181	82	26	of	of	ADP
fis-3181	82	27	similar	similar	ADJ
fis-3181	82	28	data	datum	NOUN
fis-3181	82	29	points	point	NOUN
fis-3181	82	30	.	.	PUNCT
fis-3181	83	1	knn	knn	PROPN
fis-3181	83	2	represents	represent	VERB
fis-3181	83	3	the	the	DET
fis-3181	83	4	model	model	NOUN
fis-3181	83	5	which	which	PRON
fis-3181	83	6	is	be	AUX
fis-3181	83	7	nonparametric	nonparametric	NOUN
fis-3181	83	8	in	in	ADP
fis-3181	83	9	nature	nature	NOUN
fis-3181	83	10	and	and	CCONJ
fis-3181	83	11	its	its	PRON
fis-3181	83	12	classification	classification	NOUN
fis-3181	83	13	mechanism	mechanism	NOUN
fis-3181	83	14	depends	depend	VERB
fis-3181	83	15	on	on	ADP
fis-3181	83	16	the	the	DET
fis-3181	83	17	simple	simple	ADJ
fis-3181	83	18	majority	majority	NOUN
fis-3181	83	19	votes	vote	NOUN
fis-3181	83	20	obtained	obtain	VERB
fis-3181	83	21	from	from	ADP
fis-3181	83	22	the	the	DET
fis-3181	83	23	neighbors	neighbor	NOUN
fis-3181	83	24	.	.	PUNCT
fis-3181	84	1	the	the	DET
fis-3181	84	2	knn	knn	PROPN
fis-3181	84	3	model	model	NOUN
fis-3181	84	4	can	can	AUX
fis-3181	84	5	be	be	AUX
fis-3181	84	6	successfully	successfully	ADV
fis-3181	84	7	implemented	implement	VERB
fis-3181	84	8	on	on	ADP
fis-3181	84	9	classification	classification	NOUN
fis-3181	84	10	tasks	task	NOUN
fis-3181	84	11	where	where	SCONJ
fis-3181	84	12	there	there	PRON
fis-3181	84	13	is	be	VERB
fis-3181	84	14	a	a	DET
fis-3181	84	15	complex	complex	ADJ
fis-3181	84	16	relationship	relationship	NOUN
fis-3181	84	17	between	between	ADP
fis-3181	84	18	the	the	DET
fis-3181	84	19	target	target	NOUN
fis-3181	84	20	class	class	NOUN
fis-3181	84	21	and	and	CCONJ
fis-3181	84	22	attributes	attribute	NOUN
fis-3181	84	23	.	.	PUNCT
fis-3181	85	1	fig	fig	NOUN
fis-3181	85	2	.	.	PUNCT
fis-3181	86	1	10	10	NUM
fis-3181	86	2	a	a	X
fis-3181	86	3	)	)	PUNCT
fis-3181	86	4	shows	show	VERB
fis-3181	86	5	the	the	DET
fis-3181	86	6	representation	representation	NOUN
fis-3181	86	7	of	of	ADP
fis-3181	86	8	two	two	NUM
fis-3181	86	9	classes	class	NOUN
fis-3181	86	10	i.e.	i.e.	X
fis-3181	86	11	fracture	fracture	NOUN
fis-3181	86	12	position	position	NOUN
fis-3181	86	13	at	at	ADP
fis-3181	86	14	stir	stir	NOUN
fis-3181	86	15	zone	zone	NOUN
fis-3181	86	16	represented	represent	VERB
fis-3181	86	17	by	by	ADP
fis-3181	86	18	red	red	ADJ
fis-3181	86	19	dots	dot	NOUN
fis-3181	86	20	and	and	CCONJ
fis-3181	86	21	fracture	fracture	NOUN
fis-3181	86	22	position	position	NOUN
fis-3181	86	23	at	at	ADP
fis-3181	86	24	heat	heat	NOUN
fis-3181	86	25	affected	affect	VERB
fis-3181	86	26	zone	zone	NOUN
fis-3181	86	27	of	of	ADP
fis-3181	86	28	6061	6061	NUM
fis-3181	86	29	by	by	ADP
fis-3181	86	30	green	green	ADJ
fis-3181	86	31	dots	dot	NOUN
fis-3181	86	32	.	.	PUNCT
fis-3181	87	1	fig	fig	NOUN
fis-3181	87	2	.	.	PUNCT
fis-3181	88	1	10	10	NUM
fis-3181	88	2	b	b	NOUN
fis-3181	88	3	)	)	PUNCT
fis-3181	88	4	shows	show	VERB
fis-3181	88	5	the	the	DET
fis-3181	88	6	yellow	yellow	ADJ
fis-3181	88	7	new	new	ADJ
fis-3181	88	8	data	datum	NOUN
fis-3181	88	9	point	point	NOUN
fis-3181	88	10	which	which	PRON
fis-3181	88	11	has	have	VERB
fis-3181	88	12	to	to	PART
fis-3181	88	13	be	be	AUX
fis-3181	88	14	classified	classify	VERB
fis-3181	88	15	.	.	PUNCT
fis-3181	89	1	the	the	DET
fis-3181	89	2	new	new	ADJ
fis-3181	89	3	data	data	NOUN
fis-3181	89	4	point	point	NOUN
fis-3181	89	5	can	can	AUX
fis-3181	89	6	fall	fall	VERB
fis-3181	89	7	into	into	ADP
fis-3181	89	8	the	the	DET
fis-3181	89	9	class	class	NOUN
fis-3181	89	10	of	of	ADP
fis-3181	89	11	fracture	fracture	NOUN
fis-3181	89	12	location	location	NOUN
fis-3181	89	13	at	at	ADP
fis-3181	89	14	stir	stir	NOUN
fis-3181	89	15	zone	zone	NOUN
fis-3181	89	16	or	or	CCONJ
fis-3181	89	17	to	to	ADP
fis-3181	89	18	the	the	DET
fis-3181	89	19	class	class	NOUN
fis-3181	89	20	of	of	ADP
fis-3181	89	21	fracture	fracture	NOUN
fis-3181	89	22	location	location	NOUN
fis-3181	89	23	at	at	ADP
fis-3181	89	24	heat	heat	NOUN
fis-3181	89	25	affected	affect	VERB
fis-3181	89	26	zone	zone	NOUN
fis-3181	89	27	of	of	ADP
fis-3181	89	28	6061	6061	NUM
fis-3181	89	29	.	.	PUNCT
fis-3181	90	1	in	in	ADP
fis-3181	90	2	order	order	NOUN
fis-3181	90	3	to	to	PART
fis-3181	90	4	perfectly	perfectly	ADV
fis-3181	90	5	classify	classify	VERB
fis-3181	90	6	to	to	PART
fis-3181	90	7	which	which	DET
fis-3181	90	8	class	class	NOUN
fis-3181	90	9	this	this	DET
fis-3181	90	10	new	new	ADJ
fis-3181	90	11	point	point	NOUN
fis-3181	90	12	belongs	belong	VERB
fis-3181	90	13	,	,	PUNCT
fis-3181	90	14	the	the	DET
fis-3181	90	15	knn	knn	PROPN
fis-3181	90	16	algorithm	algorithm	PROPN
fis-3181	90	17	is	be	AUX
fis-3181	90	18	used	use	VERB
fis-3181	90	19	to	to	PART
fis-3181	90	20	make	make	VERB
fis-3181	90	21	classification	classification	NOUN
fis-3181	90	22	on	on	ADP
fis-3181	90	23	the	the	DET
fis-3181	90	24	basis	basis	NOUN
fis-3181	90	25	of	of	ADP
fis-3181	90	26	majority	majority	NOUN
fis-3181	90	27	votes	vote	NOUN
fis-3181	90	28	from	from	ADP
fis-3181	90	29	the	the	DET
fis-3181	90	30	neighborhood	neighborhood	NOUN
fis-3181	90	31	data	datum	NOUN
fis-3181	90	32	points	point	NOUN
fis-3181	90	33	.	.	PUNCT
fis-3181	91	1	to	to	PART
fis-3181	91	2	achieve	achieve	VERB
fis-3181	91	3	this	this	DET
fis-3181	91	4	state	state	NOUN
fis-3181	91	5	,	,	PUNCT
fis-3181	91	6	nearest	near	ADJ
fis-3181	91	7	neighbor	neighbor	NOUN
fis-3181	91	8	points	point	NOUN
fis-3181	91	9	are	be	AUX
fis-3181	91	10	selected	select	VERB
fis-3181	91	11	on	on	ADP
fis-3181	91	12	the	the	DET
fis-3181	91	13	basis	basis	NOUN
fis-3181	91	14	of	of	ADP
fis-3181	91	15	distance	distance	NOUN
fis-3181	91	16	matrices	matrix	NOUN
fis-3181	91	17	which	which	PRON
fis-3181	91	18	can	can	AUX
fis-3181	91	19	be	be	AUX
fis-3181	91	20	euclidean	euclidean	ADJ
fis-3181	91	21	distance	distance	NOUN
fis-3181	91	22	as	as	SCONJ
fis-3181	91	23	shown	show	VERB
fis-3181	91	24	in	in	ADP
fis-3181	91	25	eqn	eqn	NOUN
fis-3181	91	26	.	.	PUNCT
fis-3181	92	1	3	3	NUM
fis-3181	92	2	,	,	PUNCT
fis-3181	92	3	manhattan	manhattan	NOUN
fis-3181	92	4	distance	distance	NOUN
fis-3181	92	5	as	as	SCONJ
fis-3181	92	6	shown	show	VERB
fis-3181	92	7	in	in	ADP
fis-3181	92	8	eqn	eqn	NOUN
fis-3181	92	9	.	.	PUNCT
fis-3181	93	1	4	4	NUM
fis-3181	93	2	,	,	PUNCT
fis-3181	93	3	and	and	CCONJ
fis-3181	93	4	minkowski	minkowski	ADJ
fis-3181	93	5	distance	distance	NOUN
fis-3181	93	6	as	as	SCONJ
fis-3181	93	7	shown	show	VERB
fis-3181	93	8	in	in	ADP
fis-3181	93	9	eqn	eqn	NOUN
fis-3181	93	10	.	.	PUNCT
fis-3181	94	1	5	5	X
fis-3181	94	2	.	.	X
fis-3181	94	3			NOUN
fis-3181	94	4			PROPN
fis-3181	94	5			PROPN
fis-3181	95	1			PROPN
fis-3181	95	2			PROPN
fis-3181	95	3			VERB
fis-3181	95	4	2	2	NUM
fis-3181	95	5	2	2	NUM
fis-3181	95	6	2	2	NUM
fis-3181	95	7	1	1	NUM
fis-3181	95	8	2	2	NUM
fis-3181	95	9	1	1	NUM
fis-3181	95	10	         	         	SPACE
fis-3181	95	11	eucledian	eucledian	ADJ
fis-3181	95	12	distance	distance	NOUN
fis-3181	95	13	between	between	ADP
fis-3181	95	14	data	datum	NOUN
fis-3181	95	15	points	point	NOUN
fis-3181	95	16	x	x	PUNCT
fis-3181	95	17	x	x	VERB
fis-3181	95	18	y	y	PROPN
fis-3181	95	19	y	y	PROPN
fis-3181	95	20	(	(	PUNCT
fis-3181	95	21	3	3	NUM
fis-3181	95	22	)	)	PUNCT
fis-3181	95	23			PROPN
fis-3181	95	24			PROPN
fis-3181	95	25			SYM
fis-3181	95	26	1	1	ADJ
fis-3181	95	27	2	2	NUM
fis-3181	95	28	1	1	NUM
fis-3181	95	29	2	2	NUM
fis-3181	95	30	 	 	SPACE
fis-3181	95	31	manhattan	manhattan	NOUN
fis-3181	95	32	distance	distance	NOUN
fis-3181	95	33	x	x	X
fis-3181	95	34	x	x	VERB
fis-3181	95	35	y	y	PROPN
fis-3181	95	36	y	y	PROPN
fis-3181	95	37	(	(	PUNCT
fis-3181	95	38	4	4	X
fis-3181	95	39	)	)	PUNCT
fis-3181	96	1			PROPN
fis-3181	96	2			NOUN
fis-3181	96	3			NOUN
fis-3181	96	4			PROPN
fis-3181	97	1			PROPN
fis-3181	97	2			CCONJ
fis-3181	98	1			ADJ
fis-3181	98	2			NOUN
fis-3181	98	3			VERB
fis-3181	98	4	1	1	NUM
fis-3181	98	5	1	1	NUM
fis-3181	98	6	    	    	SPACE
fis-3181	98	7	n	n	PRON
fis-3181	99	1	p	p	NOUN
fis-3181	99	2	p	p	X
fis-3181	100	1	i	i	PRON
fis-3181	101	1	i	i	PRON
fis-3181	102	1	i	i	PRON
fis-3181	102	2	minkowski	minkowski	VERB
fis-3181	102	3	distance	distance	NOUN
fis-3181	102	4	x	x	X
fis-3181	102	5	y	y	NOUN
fis-3181	102	6	(	(	PUNCT
fis-3181	102	7	5	5	NUM
fis-3181	102	8	)	)	PUNCT
fis-3181	102	9	a	a	DET
fis-3181	102	10	)	)	PUNCT
fis-3181	102	11	b	b	NOUN
fis-3181	102	12	)	)	PUNCT
fis-3181	102	13	figure	figure	NOUN
fis-3181	102	14	10	10	NUM
fis-3181	102	15	:	:	PUNCT
fis-3181	102	16	a	a	X
fis-3181	102	17	)	)	PUNCT
fis-3181	102	18	representation	representation	NOUN
fis-3181	102	19	of	of	ADP
fis-3181	102	20	two	two	NUM
fis-3181	102	21	classes	class	NOUN
fis-3181	102	22	of	of	ADP
fis-3181	102	23	fracture	fracture	PROPN
fis-3181	102	24	location	location	NOUN
fis-3181	102	25	b	b	NOUN
fis-3181	102	26	)	)	PUNCT
fis-3181	102	27	evaluating	evaluate	VERB
fis-3181	102	28	the	the	DET
fis-3181	102	29	nearest	near	ADJ
fis-3181	102	30	neighbours	neighbour	NOUN
fis-3181	102	31	for	for	ADP
fis-3181	102	32	a	a	DET
fis-3181	102	33	new	new	ADJ
fis-3181	102	34	data	data	NOUN
fis-3181	102	35	point	point	NOUN
fis-3181	102	36	.	.	PUNCT
fis-3181	103	1	k	k	PROPN
fis-3181	103	2	a.	a.	PROPN
fis-3181	103	3	mishra	mishra	PROPN
fis-3181	103	4	et	et	PROPN
fis-3181	103	5	alii	alii	PROPN
fis-3181	103	6	,	,	PUNCT
fis-3181	103	7	frattura	frattura	PROPN
fis-3181	103	8	ed	ed	PROPN
fis-3181	103	9	integrità	integrità	PROPN
fis-3181	103	10	strutturale	strutturale	PROPN
fis-3181	103	11	,	,	PUNCT
fis-3181	103	12	58	58	NUM
fis-3181	103	13	(	(	PUNCT
fis-3181	103	14	2021	2021	NUM
fis-3181	103	15	)	)	PUNCT
fis-3181	103	16	242	242	NUM
fis-3181	103	17	-	-	SYM
fis-3181	103	18	253	253	NUM
fis-3181	103	19	;	;	PUNCT
fis-3181	103	20	doi	doi	NOUN
fis-3181	103	21	:	:	PUNCT
fis-3181	103	22	10.3221	10.3221	NUM
fis-3181	103	23	/	/	SYM
fis-3181	103	24	igf	igf	PROPN
fis-3181	103	25	-	-	PUNCT
fis-3181	103	26	esis.58.18	esis.58.18	PROPN
fis-3181	103	27	250	250	NUM
fis-3181	103	28	tab	tab	NOUN
fis-3181	103	29	.	.	PUNCT
fis-3181	103	30	3	3	NUM
fis-3181	103	31	shows	show	VERB
fis-3181	103	32	the	the	DET
fis-3181	103	33	classification	classification	NOUN
fis-3181	103	34	report	report	NOUN
fis-3181	103	35	of	of	ADP
fis-3181	103	36	k	k	X
fis-3181	103	37	-	-	PUNCT
fis-3181	103	38	nearest	near	ADJ
fis-3181	103	39	neighbour	neighbour	ADJ
fis-3181	103	40	algorithm	algorithm	NOUN
fis-3181	103	41	and	and	CCONJ
fis-3181	103	42	fig	fig	NOUN
fis-3181	103	43	.	.	PUNCT
fis-3181	104	1	11	11	NUM
fis-3181	104	2	shows	show	VERB
fis-3181	104	3	the	the	DET
fis-3181	104	4	confusion	confusion	NOUN
fis-3181	104	5	matrix	matrix	NOUN
fis-3181	104	6	obtained	obtain	VERB
fis-3181	104	7	.	.	PUNCT
fis-3181	104	8	precision	precision	NOUN
fis-3181	104	9	recall	recall	NOUN
fis-3181	104	10	f1	f1	NOUN
fis-3181	104	11	-	-	PUNCT
fis-3181	104	12	score	score	NOUN
fis-3181	104	13	0	0	NUM
fis-3181	104	14	0.00	0.00	NUM
fis-3181	104	15	0.00	0.00	NUM
fis-3181	104	16	0.00	0.00	NUM
fis-3181	104	17	1	1	NUM
fis-3181	104	18	0.86	0.86	NUM
fis-3181	104	19	0.75	0.75	NUM
fis-3181	104	20	0.80	0.80	NUM
fis-3181	104	21	accuracy	accuracy	NOUN
fis-3181	104	22	0.67	0.67	NUM
fis-3181	104	23	macro	macro	NOUN
fis-3181	104	24	average	average	ADJ
fis-3181	104	25	0.43	0.43	NUM
fis-3181	104	26	0.38	0.38	NUM
fis-3181	104	27	0.40	0.40	NUM
fis-3181	104	28	weighted	weight	VERB
fis-3181	104	29	average	average	ADJ
fis-3181	104	30	0.76	0.76	NUM
fis-3181	104	31	0.67	0.67	NUM
fis-3181	104	32	0.71	0.71	NUM
fis-3181	104	33	table	table	NOUN
fis-3181	104	34	3	3	NUM
fis-3181	104	35	:	:	PUNCT
fis-3181	104	36	classification	classification	NOUN
fis-3181	104	37	report	report	NOUN
fis-3181	104	38	of	of	ADP
fis-3181	104	39	k	k	NOUN
fis-3181	104	40	-	-	PUNCT
fis-3181	104	41	nearest	near	ADJ
fis-3181	104	42	algorithm	algorithm	NOUN
fis-3181	104	43	.	.	PUNCT
fis-3181	105	1	figure	figure	VERB
fis-3181	105	2	11	11	NUM
fis-3181	105	3	:	:	PUNCT
fis-3181	105	4	confusion	confusion	NOUN
fis-3181	105	5	matrix	matrix	NOUN
fis-3181	105	6	showing	show	VERB
fis-3181	105	7	the	the	DET
fis-3181	105	8	performance	performance	NOUN
fis-3181	105	9	of	of	ADP
fis-3181	105	10	k	k	X
fis-3181	105	11	-	-	PUNCT
fis-3181	105	12	nearest	near	ADJ
fis-3181	105	13	neighbor	neighbor	NOUN
fis-3181	105	14	algorithm	algorithm	NOUN
fis-3181	105	15	.	.	PUNCT
fis-3181	106	1	from	from	ADP
fis-3181	106	2	tab	tab	PROPN
fis-3181	106	3	.	.	PUNCT
fis-3181	107	1	3	3	NUM
fis-3181	108	1	it	it	PRON
fis-3181	108	2	is	be	AUX
fis-3181	108	3	observed	observe	VERB
fis-3181	108	4	that	that	SCONJ
fis-3181	108	5	the	the	DET
fis-3181	108	6	accuracy	accuracy	NOUN
fis-3181	108	7	score	score	NOUN
fis-3181	108	8	of	of	ADP
fis-3181	108	9	k	k	NOUN
fis-3181	108	10	-	-	PUNCT
fis-3181	108	11	nearest	near	ADJ
fis-3181	108	12	neighbor	neighbor	NOUN
fis-3181	108	13	is	be	AUX
fis-3181	108	14	0.67	0.67	NUM
fis-3181	108	15	which	which	PRON
fis-3181	108	16	is	be	AUX
fis-3181	108	17	less	less	ADJ
fis-3181	108	18	than	than	ADP
fis-3181	108	19	the	the	DET
fis-3181	108	20	accuracy	accuracy	NOUN
fis-3181	108	21	score	score	NOUN
fis-3181	108	22	of	of	ADP
fis-3181	108	23	decision	decision	NOUN
fis-3181	108	24	tree	tree	NOUN
fis-3181	108	25	algorithm	algorithm	NOUN
fis-3181	108	26	.	.	PUNCT
fis-3181	109	1	support	support	NOUN
fis-3181	109	2	vector	vector	NOUN
fis-3181	109	3	machine	machine	NOUN
fis-3181	109	4	(	(	PUNCT
fis-3181	109	5	svm	svm	ADJ
fis-3181	109	6	)	)	PUNCT
fis-3181	109	7	algorithm	algorithm	NOUN
fis-3181	109	8	ecision	ecision	NOUN
fis-3181	109	9	boundaries	boundary	NOUN
fis-3181	109	10	generally	generally	ADV
fis-3181	109	11	classify	classify	VERB
fis-3181	109	12	the	the	DET
fis-3181	109	13	class	class	NOUN
fis-3181	109	14	based	base	VERB
fis-3181	109	15	on	on	ADP
fis-3181	109	16	which	which	PRON
fis-3181	109	17	the	the	DET
fis-3181	109	18	data	data	NOUN
fis-3181	109	19	point	point	NOUN
fis-3181	109	20	falls	fall	VERB
fis-3181	109	21	on	on	ADP
fis-3181	109	22	as	as	SCONJ
fis-3181	109	23	shown	show	VERB
fis-3181	109	24	in	in	ADP
fis-3181	109	25	fig	fig	NOUN
fis-3181	109	26	.	.	PUNCT
fis-3181	110	1	12	12	NUM
fis-3181	110	2	a	a	PRON
fis-3181	110	3	)	)	PUNCT
fis-3181	110	4	which	which	PRON
fis-3181	110	5	represents	represent	VERB
fis-3181	110	6	a	a	DET
fis-3181	110	7	bad	bad	ADJ
fis-3181	110	8	decision	decision	NOUN
fis-3181	110	9	boundary	boundary	ADJ
fis-3181	110	10	as	as	SCONJ
fis-3181	110	11	it	it	PRON
fis-3181	110	12	is	be	AUX
fis-3181	110	13	unable	unable	ADJ
fis-3181	110	14	to	to	PART
fis-3181	110	15	properly	properly	ADV
fis-3181	110	16	separate	separate	VERB
fis-3181	110	17	the	the	DET
fis-3181	110	18	two	two	NUM
fis-3181	110	19	classes	class	NOUN
fis-3181	110	20	.	.	PUNCT
fis-3181	111	1	there	there	PRON
fis-3181	111	2	is	be	VERB
fis-3181	111	3	an	an	DET
fis-3181	111	4	infinite	infinite	ADJ
fis-3181	111	5	number	number	NOUN
fis-3181	111	6	of	of	ADP
fis-3181	111	7	decision	decision	NOUN
fis-3181	111	8	boundaries	boundary	NOUN
fis-3181	111	9	so	so	SCONJ
fis-3181	111	10	the	the	DET
fis-3181	111	11	main	main	ADJ
fis-3181	111	12	goal	goal	NOUN
fis-3181	111	13	is	be	AUX
fis-3181	111	14	to	to	PART
fis-3181	111	15	choose	choose	VERB
fis-3181	111	16	the	the	DET
fis-3181	111	17	best	good	ADJ
fis-3181	111	18	decision	decision	NOUN
fis-3181	111	19	boundary	boundary	NOUN
fis-3181	111	20	.	.	PUNCT
fis-3181	112	1	in	in	ADP
fis-3181	112	2	order	order	NOUN
fis-3181	112	3	to	to	PART
fis-3181	112	4	find	find	VERB
fis-3181	112	5	the	the	DET
fis-3181	112	6	optimal	optimal	ADJ
fis-3181	112	7	line	line	NOUN
fis-3181	112	8	,	,	PUNCT
fis-3181	112	9	the	the	DET
fis-3181	112	10	support	support	NOUN
fis-3181	112	11	vector	vector	NOUN
fis-3181	112	12	machine	machine	NOUN
fis-3181	112	13	(	(	PUNCT
fis-3181	112	14	svm	svm	ADJ
fis-3181	112	15	)	)	PUNCT
fis-3181	112	16	algorithm	algorithm	NOUN
fis-3181	112	17	is	be	AUX
fis-3181	112	18	used	use	VERB
fis-3181	112	19	that	that	PRON
fis-3181	112	20	can	can	AUX
fis-3181	112	21	perfectly	perfectly	ADV
fis-3181	112	22	separate	separate	VERB
fis-3181	112	23	the	the	DET
fis-3181	112	24	two	two	NUM
fis-3181	112	25	classes	class	NOUN
fis-3181	112	26	i.e.	i.e.	X
fis-3181	112	27	fracture	fracture	NOUN
fis-3181	112	28	location	location	NOUN
fis-3181	112	29	at	at	ADP
fis-3181	112	30	stir	stir	NOUN
fis-3181	112	31	zone	zone	NOUN
fis-3181	112	32	and	and	CCONJ
fis-3181	112	33	fracture	fracture	NOUN
fis-3181	112	34	position	position	NOUN
fis-3181	112	35	at	at	ADP
fis-3181	112	36	the	the	DET
fis-3181	112	37	heat	heat	NOUN
fis-3181	112	38	-	-	PUNCT
fis-3181	112	39	affected	affect	VERB
fis-3181	112	40	zone	zone	NOUN
fis-3181	112	41	of	of	ADP
fis-3181	112	42	6061	6061	NUM
fis-3181	112	43	as	as	SCONJ
fis-3181	112	44	shown	show	VERB
fis-3181	112	45	in	in	ADP
fis-3181	112	46	fig	fig	NOUN
fis-3181	112	47	.	.	PUNCT
fis-3181	113	1	12	12	NUM
fis-3181	113	2	b	b	NOUN
fis-3181	113	3	)	)	PUNCT
fis-3181	113	4	.	.	PUNCT
fis-3181	114	1	the	the	DET
fis-3181	114	2	decision	decision	NOUN
fis-3181	114	3	boundary	boundary	ADJ
fis-3181	114	4	line	line	NOUN
fis-3181	114	5	can	can	AUX
fis-3181	114	6	be	be	AUX
fis-3181	114	7	represented	represent	VERB
fis-3181	114	8	by	by	ADP
fis-3181	114	9	eqn	eqn	NOUN
fis-3181	114	10	.	.	PUNCT
fis-3181	115	1	6	6	NUM
fis-3181	115	2	.	.	PUNCT
fis-3181	116	1	in	in	ADP
fis-3181	116	2	order	order	NOUN
fis-3181	116	3	to	to	PART
fis-3181	116	4	calculate	calculate	VERB
fis-3181	116	5	the	the	DET
fis-3181	116	6	distance	distance	NOUN
fis-3181	116	7	from	from	ADP
fis-3181	116	8	the	the	DET
fis-3181	116	9	decision	decision	NOUN
fis-3181	116	10	boundary	boundary	ADJ
fis-3181	116	11	to	to	ADP
fis-3181	116	12	any	any	DET
fis-3181	116	13	point	point	NOUN
fis-3181	116	14	eqn	eqn	NOUN
fis-3181	116	15	.	.	PUNCT
fis-3181	116	16	7	7	NUM
fis-3181	116	17	is	be	AUX
fis-3181	116	18	used	use	VERB
fis-3181	116	19	.	.	PUNCT
fis-3181	117	1	the	the	DET
fis-3181	117	2	main	main	ADJ
fis-3181	117	3	goal	goal	NOUN
fis-3181	117	4	is	be	AUX
fis-3181	117	5	to	to	PART
fis-3181	117	6	maximize	maximize	VERB
fis-3181	117	7	the	the	DET
fis-3181	117	8	value	value	NOUN
fis-3181	117	9	of	of	ADP
fis-3181	117	10	r	r	NOUN
fis-3181	117	11	for	for	ADP
fis-3181	117	12	the	the	DET
fis-3181	117	13	support	support	NOUN
fis-3181	117	14	vectors	vector	NOUN
fis-3181	117	15	points	point	VERB
fis-3181	117	16	to	to	ADP
fis-3181	117	17	the	the	DET
fis-3181	117	18	required	require	VERB
fis-3181	117	19	optimal	optimal	ADJ
fis-3181	117	20	decision	decision	NOUN
fis-3181	117	21	boundary	boundary	NOUN
fis-3181	117	22	.	.	PUNCT
fis-3181	118	1			NOUN
fis-3181	119	1			PUNCT
fis-3181	119	2			PRON
fis-3181	119	3			ADV
fis-3181	119	4			NUM
fis-3181	119	5	0tg	0tg	NOUN
fis-3181	119	6	x	x	X
fis-3181	119	7	w	w	NOUN
fis-3181	119	8	x	x	SYM
fis-3181	119	9	b	b	PROPN
fis-3181	119	10	(	(	PUNCT
fis-3181	119	11	6	6	NUM
fis-3181	119	12	)	)	PUNCT
fis-3181	119	13	d	d	NOUN
fis-3181	119	14	a.	a.	PROPN
fis-3181	119	15	mishra	mishra	PROPN
fis-3181	119	16	et	et	PROPN
fis-3181	119	17	alii	alii	PROPN
fis-3181	119	18	,	,	PUNCT
fis-3181	119	19	frattura	frattura	PROPN
fis-3181	119	20	ed	ed	PROPN
fis-3181	119	21	integrità	integrità	PROPN
fis-3181	119	22	strutturale	strutturale	PROPN
fis-3181	119	23	,	,	PUNCT
fis-3181	119	24	58	58	NUM
fis-3181	119	25	(	(	PUNCT
fis-3181	119	26	2021	2021	NUM
fis-3181	119	27	)	)	PUNCT
fis-3181	119	28	242	242	NUM
fis-3181	119	29	-	-	SYM
fis-3181	119	30	253	253	NUM
fis-3181	119	31	;	;	PUNCT
fis-3181	119	32	doi	doi	NOUN
fis-3181	119	33	:	:	PUNCT
fis-3181	119	34	10.3221	10.3221	NUM
fis-3181	119	35	/	/	SYM
fis-3181	119	36	igf	igf	PROPN
fis-3181	119	37	-	-	PUNCT
fis-3181	119	38	esis.58.18	esis.58.18	PROPN
fis-3181	119	39	251	251	NUM
fis-3181	119	40			NOUN
fis-3181	119	41			PUNCT
fis-3181	120	1			NOUN
fis-3181	121	1	g	g	NOUN
fis-3181	121	2	x	x	X
fis-3181	121	3	r	r	NOUN
fis-3181	121	4	w	w	PROPN
fis-3181	121	5	(	(	PUNCT
fis-3181	121	6	7	7	NUM
fis-3181	121	7	)	)	PUNCT
fis-3181	121	8	tab	tab	NOUN
fis-3181	121	9	.	.	PUNCT
fis-3181	121	10	4	4	NUM
fis-3181	121	11	shows	show	VERB
fis-3181	121	12	the	the	DET
fis-3181	121	13	classification	classification	NOUN
fis-3181	121	14	report	report	NOUN
fis-3181	121	15	of	of	ADP
fis-3181	121	16	svm	svm	ADJ
fis-3181	121	17	algorithm	algorithm	NOUN
fis-3181	121	18	.	.	PUNCT
fis-3181	122	1	from	from	ADP
fis-3181	122	2	the	the	DET
fis-3181	122	3	results	result	NOUN
fis-3181	122	4	it	it	PRON
fis-3181	122	5	is	be	AUX
fis-3181	122	6	observed	observe	VERB
fis-3181	122	7	that	that	SCONJ
fis-3181	122	8	it	it	PRON
fis-3181	122	9	resulted	result	VERB
fis-3181	122	10	in	in	ADP
fis-3181	122	11	the	the	DET
fis-3181	122	12	accuracy	accuracy	NOUN
fis-3181	122	13	score	score	NOUN
fis-3181	122	14	of	of	ADP
fis-3181	122	15	0.89	0.89	NUM
fis-3181	122	16	.	.	PUNCT
fis-3181	122	17	fig	fig	NOUN
fis-3181	122	18	.	.	PUNCT
fis-3181	123	1	13	13	NUM
fis-3181	123	2	shows	show	VERB
fis-3181	123	3	the	the	DET
fis-3181	123	4	confusion	confusion	NOUN
fis-3181	123	5	matrix	matrix	NOUN
fis-3181	123	6	obtained	obtain	VERB
fis-3181	123	7	for	for	ADP
fis-3181	123	8	the	the	DET
fis-3181	123	9	svm	svm	ADJ
fis-3181	123	10	algorithm	algorithm	PROPN
fis-3181	123	11	precision	precision	PROPN
fis-3181	123	12	recall	recall	NOUN
fis-3181	123	13	f1	f1	NOUN
fis-3181	123	14	-	-	PUNCT
fis-3181	123	15	score	score	NOUN
fis-3181	123	16	0	0	NUM
fis-3181	123	17	0.00	0.00	NUM
fis-3181	123	18	0.00	0.00	NUM
fis-3181	123	19	0.00	0.00	NUM
fis-3181	123	20	1	1	NUM
fis-3181	123	21	0.89	0.89	NUM
fis-3181	123	22	1.00	1.00	NUM
fis-3181	123	23	0.94	0.94	NUM
fis-3181	123	24	accuracy	accuracy	NOUN
fis-3181	123	25	0.89	0.89	NUM
fis-3181	123	26	macro	macro	NOUN
fis-3181	123	27	average	average	ADJ
fis-3181	123	28	0.44	0.44	NUM
fis-3181	123	29	0.50	0.50	NUM
fis-3181	123	30	0.47	0.47	NUM
fis-3181	123	31	weighted	weight	VERB
fis-3181	123	32	average	average	ADJ
fis-3181	123	33	0.79	0.79	NUM
fis-3181	123	34	0.89	0.89	NUM
fis-3181	123	35	0.84	0.84	NUM
fis-3181	123	36	table	table	NOUN
fis-3181	123	37	4	4	NUM
fis-3181	123	38	:	:	PUNCT
fis-3181	123	39	classification	classification	NOUN
fis-3181	123	40	report	report	NOUN
fis-3181	123	41	of	of	ADP
fis-3181	123	42	svm	svm	ADJ
fis-3181	123	43	algorithm	algorithm	NOUN
fis-3181	123	44	.	.	PUNCT
fis-3181	124	1	(	(	PUNCT
fis-3181	124	2	a	a	X
fis-3181	124	3	)	)	PUNCT
fis-3181	124	4	(	(	PUNCT
fis-3181	124	5	b	b	X
fis-3181	124	6	)	)	PUNCT
fis-3181	124	7	figure	figure	NOUN
fis-3181	124	8	12	12	NUM
fis-3181	124	9	:	:	PUNCT
fis-3181	124	10	a	a	X
fis-3181	124	11	)	)	PUNCT
fis-3181	124	12	decision	decision	NOUN
fis-3181	124	13	boundary	boundary	NOUN
fis-3181	124	14	separating	separate	VERB
fis-3181	124	15	two	two	NUM
fis-3181	124	16	classes	class	NOUN
fis-3181	124	17	of	of	ADP
fis-3181	124	18	fracture	fracture	PROPN
fis-3181	124	19	location	location	NOUN
fis-3181	124	20	b	b	NOUN
fis-3181	124	21	)	)	PUNCT
fis-3181	124	22	optimal	optimal	ADJ
fis-3181	124	23	decision	decision	NOUN
fis-3181	124	24	boundary	boundary	NOUN
fis-3181	124	25	separating	separate	VERB
fis-3181	124	26	the	the	DET
fis-3181	124	27	two	two	NUM
fis-3181	124	28	classes	class	NOUN
fis-3181	124	29	of	of	ADP
fis-3181	124	30	fracture	fracture	PROPN
fis-3181	124	31	location	location	NOUN
fis-3181	124	32	.	.	PUNCT
fis-3181	125	1	figure	figure	VERB
fis-3181	125	2	13	13	NUM
fis-3181	125	3	:	:	PUNCT
fis-3181	125	4	confusion	confusion	NOUN
fis-3181	125	5	matrix	matrix	NOUN
fis-3181	125	6	showing	show	VERB
fis-3181	125	7	the	the	DET
fis-3181	125	8	performance	performance	NOUN
fis-3181	125	9	of	of	ADP
fis-3181	125	10	svm	svm	ADJ
fis-3181	125	11	algorithm	algorithm	NOUN
fis-3181	125	12	.	.	PUNCT
fis-3181	126	1	a.	a.	PROPN
fis-3181	126	2	mishra	mishra	PROPN
fis-3181	126	3	et	et	PROPN
fis-3181	126	4	alii	alii	PROPN
fis-3181	126	5	,	,	PUNCT
fis-3181	126	6	frattura	frattura	PROPN
fis-3181	126	7	ed	ed	PROPN
fis-3181	126	8	integrità	integrità	PROPN
fis-3181	126	9	strutturale	strutturale	PROPN
fis-3181	126	10	,	,	PUNCT
fis-3181	126	11	58	58	NUM
fis-3181	126	12	(	(	PUNCT
fis-3181	126	13	2021	2021	NUM
fis-3181	126	14	)	)	PUNCT
fis-3181	126	15	242	242	NUM
fis-3181	126	16	-	-	SYM
fis-3181	126	17	253	253	NUM
fis-3181	126	18	;	;	PUNCT
fis-3181	126	19	doi	doi	NOUN
fis-3181	126	20	:	:	PUNCT
fis-3181	126	21	10.3221	10.3221	NUM
fis-3181	126	22	/	/	SYM
fis-3181	126	23	igf	igf	PROPN
fis-3181	126	24	-	-	PUNCT
fis-3181	126	25	esis.58.18	esis.58.18	PROPN
fis-3181	126	26	252	252	NUM
fis-3181	126	27	ada	ada	NOUN
fis-3181	126	28	boost	boost	NOUN
fis-3181	126	29	algorithm	algorithm	NOUN
fis-3181	126	30	daboost	daboost	NOUN
fis-3181	126	31	is	be	AUX
fis-3181	126	32	also	also	ADV
fis-3181	126	33	known	know	VERB
fis-3181	126	34	as	as	ADP
fis-3181	126	35	adaptive	adaptive	ADJ
fis-3181	126	36	boosting	boosting	NOUN
fis-3181	126	37	falls	fall	NOUN
fis-3181	126	38	into	into	ADP
fis-3181	126	39	the	the	DET
fis-3181	126	40	classification	classification	NOUN
fis-3181	126	41	category	category	NOUN
fis-3181	126	42	of	of	ADP
fis-3181	126	43	ensemble	ensemble	ADJ
fis-3181	126	44	boosting	boosting	NOUN
fis-3181	126	45	as	as	SCONJ
fis-3181	126	46	shown	show	VERB
fis-3181	126	47	in	in	ADP
fis-3181	126	48	fig	fig	NOUN
fis-3181	126	49	.	.	PUNCT
fis-3181	127	1	14	14	NUM
fis-3181	127	2	.	.	PUNCT
fis-3181	128	1	the	the	DET
fis-3181	128	2	multiple	multiple	ADJ
fis-3181	128	3	weak	weak	ADJ
fis-3181	128	4	classifiers	classifier	NOUN
fis-3181	128	5	are	be	AUX
fis-3181	128	6	combined	combine	VERB
fis-3181	128	7	to	to	PART
fis-3181	128	8	increase	increase	VERB
fis-3181	128	9	the	the	DET
fis-3181	128	10	accuracy	accuracy	NOUN
fis-3181	128	11	of	of	ADP
fis-3181	128	12	the	the	DET
fis-3181	128	13	classifiers	classifier	NOUN
fis-3181	128	14	.	.	PUNCT
fis-3181	129	1	adaptive	adaptive	ADJ
fis-3181	129	2	boosting	boost	VERB
fis-3181	129	3	works	work	NOUN
fis-3181	129	4	on	on	ADP
fis-3181	129	5	an	an	DET
fis-3181	129	6	iterative	iterative	NOUN
fis-3181	129	7	ensemble	ensemble	ADJ
fis-3181	129	8	method	method	NOUN
fis-3181	129	9	that	that	PRON
fis-3181	129	10	allocates	allocate	VERB
fis-3181	129	11	the	the	DET
fis-3181	129	12	weights	weight	NOUN
fis-3181	129	13	of	of	ADP
fis-3181	129	14	the	the	DET
fis-3181	129	15	classifiers	classifier	NOUN
fis-3181	129	16	and	and	CCONJ
fis-3181	129	17	further	further	ADJ
fis-3181	129	18	data	data	NOUN
fis-3181	129	19	samples	sample	NOUN
fis-3181	129	20	are	be	AUX
fis-3181	129	21	trained	train	VERB
fis-3181	129	22	in	in	ADP
fis-3181	129	23	each	each	DET
fis-3181	129	24	iteration	iteration	NOUN
fis-3181	129	25	step	step	NOUN
fis-3181	129	26	.	.	PUNCT
fis-3181	130	1	figure	figure	NOUN
fis-3181	130	2	14	14	NUM
fis-3181	130	3	:	:	PUNCT
fis-3181	130	4	working	work	VERB
fis-3181	130	5	mechanism	mechanism	NOUN
fis-3181	130	6	of	of	ADP
fis-3181	130	7	adaptive	adaptive	ADJ
fis-3181	130	8	boosting	boost	VERB
fis-3181	130	9	algorithm	algorithm	NOUN
fis-3181	130	10	.	.	PUNCT
fis-3181	131	1	tab	tab	NOUN
fis-3181	131	2	.	.	PUNCT
fis-3181	131	3	5	5	NUM
fis-3181	131	4	shows	show	VERB
fis-3181	131	5	the	the	DET
fis-3181	131	6	classification	classification	NOUN
fis-3181	131	7	report	report	NOUN
fis-3181	131	8	of	of	ADP
fis-3181	131	9	ada	ada	PROPN
fis-3181	131	10	boost	boost	NOUN
fis-3181	131	11	algorithm	algorithm	NOUN
fis-3181	131	12	and	and	CCONJ
fis-3181	131	13	fig	fig	NOUN
fis-3181	131	14	.	.	PUNCT
fis-3181	132	1	15	15	NUM
fis-3181	132	2	shows	show	VERB
fis-3181	132	3	its	its	PRON
fis-3181	132	4	performance	performance	NOUN
fis-3181	132	5	.	.	PUNCT
fis-3181	133	1	it	it	PRON
fis-3181	133	2	is	be	AUX
fis-3181	133	3	observed	observe	VERB
fis-3181	133	4	that	that	SCONJ
fis-3181	133	5	the	the	DET
fis-3181	133	6	ada	ada	PROPN
fis-3181	133	7	boost	boost	PROPN
fis-3181	133	8	algorithm	algorithm	NOUN
fis-3181	133	9	resulted	result	VERB
fis-3181	133	10	in	in	ADP
fis-3181	133	11	lowest	low	ADJ
fis-3181	133	12	accuracy	accuracy	NOUN
fis-3181	133	13	score	score	NOUN
fis-3181	133	14	of	of	ADP
fis-3181	133	15	0.56	0.56	NUM
fis-3181	133	16	in	in	ADP
fis-3181	133	17	comparison	comparison	NOUN
fis-3181	133	18	to	to	ADP
fis-3181	133	19	the	the	DET
fis-3181	133	20	other	other	ADJ
fis-3181	133	21	algorithms	algorithm	NOUN
fis-3181	133	22	.	.	PUNCT
fis-3181	134	1	precision	precision	NOUN
fis-3181	134	2	recall	recall	VERB
fis-3181	134	3	f1	f1	NOUN
fis-3181	134	4	-	-	PUNCT
fis-3181	134	5	score	score	NOUN
fis-3181	134	6	0	0	NUM
fis-3181	134	7	0.00	0.00	NUM
fis-3181	134	8	0.00	0.00	NUM
fis-3181	134	9	0.00	0.00	NUM
fis-3181	134	10	1	1	NUM
fis-3181	134	11	0.83	0.83	NUM
fis-3181	134	12	0.62	0.62	NUM
fis-3181	134	13	0.71	0.71	NUM
fis-3181	134	14	accuracy	accuracy	NOUN
fis-3181	134	15	0.56	0.56	NUM
fis-3181	134	16	macro	macro	NOUN
fis-3181	134	17	average	average	ADJ
fis-3181	134	18	0.42	0.42	NUM
fis-3181	134	19	0.31	0.31	NUM
fis-3181	134	20	0.36	0.36	NUM
fis-3181	134	21	weighted	weight	VERB
fis-3181	134	22	average	average	ADJ
fis-3181	134	23	0.74	0.74	NUM
fis-3181	134	24	0.56	0.56	NUM
fis-3181	134	25	0.63	0.63	NUM
fis-3181	134	26	table	table	NOUN
fis-3181	134	27	5	5	NUM
fis-3181	134	28	:	:	PUNCT
fis-3181	134	29	classification	classification	NOUN
fis-3181	134	30	report	report	NOUN
fis-3181	134	31	of	of	ADP
fis-3181	134	32	ada	ada	PROPN
fis-3181	134	33	boost	boost	PROPN
fis-3181	134	34	algorithm	algorithm	NOUN
fis-3181	134	35	.	.	PUNCT
fis-3181	135	1	figure	figure	VERB
fis-3181	135	2	15	15	NUM
fis-3181	135	3	:	:	PUNCT
fis-3181	135	4	confusion	confusion	NOUN
fis-3181	135	5	matrix	matrix	NOUN
fis-3181	135	6	showing	show	VERB
fis-3181	135	7	the	the	DET
fis-3181	135	8	performance	performance	NOUN
fis-3181	135	9	of	of	ADP
fis-3181	135	10	ada	ada	PROPN
fis-3181	135	11	boost	boost	PROPN
fis-3181	135	12	algorithm	algorithm	NOUN
fis-3181	135	13	.	.	PUNCT
fis-3181	136	1	a	a	DET
fis-3181	136	2	a.	a.	NOUN
fis-3181	136	3	mishra	mishra	PROPN
fis-3181	136	4	et	et	PROPN
fis-3181	136	5	alii	alii	PROPN
fis-3181	136	6	,	,	PUNCT
fis-3181	136	7	frattura	frattura	PROPN
fis-3181	136	8	ed	ed	PROPN
fis-3181	136	9	integrità	integrità	PROPN
fis-3181	136	10	strutturale	strutturale	PROPN
fis-3181	136	11	,	,	PUNCT
fis-3181	136	12	58	58	NUM
fis-3181	136	13	(	(	PUNCT
fis-3181	136	14	2021	2021	NUM
fis-3181	136	15	)	)	PUNCT
fis-3181	136	16	242	242	NUM
fis-3181	136	17	-	-	SYM
fis-3181	136	18	253	253	NUM
fis-3181	136	19	;	;	PUNCT
fis-3181	136	20	doi	doi	NOUN
fis-3181	136	21	:	:	PUNCT
fis-3181	136	22	10.3221	10.3221	NUM
fis-3181	136	23	/	/	SYM
fis-3181	136	24	igf	igf	PROPN
fis-3181	136	25	-	-	PUNCT
fis-3181	136	26	esis.58.18	esis.58.18	VERB
fis-3181	136	27	253	253	NUM
fis-3181	136	28	conclusion	conclusion	NOUN
fis-3181	136	29	he	he	PRON
fis-3181	136	30	recent	recent	ADJ
fis-3181	136	31	work	work	NOUN
fis-3181	136	32	successfully	successfully	ADV
fis-3181	136	33	implemented	implement	VERB
fis-3181	136	34	the	the	DET
fis-3181	136	35	supervised	supervised	ADJ
fis-3181	136	36	machine	machine	NOUN
fis-3181	136	37	learning	learning	NOUN
fis-3181	136	38	based	base	VERB
fis-3181	136	39	classification	classification	NOUN
fis-3181	136	40	models	model	NOUN
fis-3181	136	41	for	for	ADP
fis-3181	136	42	first	first	ADJ
fis-3181	136	43	time	time	NOUN
fis-3181	136	44	detecting	detect	VERB
fis-3181	136	45	the	the	DET
fis-3181	136	46	fracture	fracture	NOUN
fis-3181	136	47	location	location	NOUN
fis-3181	136	48	dissimilar	dissimilar	ADJ
fis-3181	136	49	friction	friction	NOUN
fis-3181	136	50	stir	stir	NOUN
fis-3181	136	51	welded	weld	VERB
fis-3181	136	52	joints	joint	NOUN
fis-3181	136	53	.	.	PUNCT
fis-3181	137	1			PUNCT
fis-3181	138	1	the	the	DET
fis-3181	138	2	present	present	ADJ
fis-3181	138	3	study	study	NOUN
fis-3181	138	4	successfully	successfully	ADV
fis-3181	138	5	implemented	implement	VERB
fis-3181	138	6	the	the	DET
fis-3181	138	7	four	four	NUM
fis-3181	138	8	supervised	supervised	ADJ
fis-3181	138	9	machine	machine	NOUN
fis-3181	138	10	learning	learn	VERB
fis-3181	138	11	classification	classification	NOUN
fis-3181	138	12	-	-	PUNCT
fis-3181	138	13	based	base	VERB
fis-3181	138	14	algorithms	algorithm	NOUN
fis-3181	138	15	for	for	ADP
fis-3181	138	16	the	the	DET
fis-3181	138	17	determination	determination	NOUN
fis-3181	138	18	of	of	ADP
fis-3181	138	19	fracture	fracture	ADJ
fis-3181	138	20	location	location	NOUN
fis-3181	138	21	in	in	ADP
fis-3181	138	22	dissimilar	dissimilar	ADJ
fis-3181	138	23	friction	friction	NOUN
fis-3181	138	24	stir	stir	NOUN
fis-3181	138	25	welded	weld	VERB
fis-3181	138	26	joints	joint	NOUN
fis-3181	138	27	.	.	PUNCT
fis-3181	139	1	support	support	NOUN
fis-3181	139	2	vector	vector	NOUN
fis-3181	139	3	machine	machine	NOUN
fis-3181	139	4	algorithm	algorithm	NOUN
fis-3181	139	5	resulted	result	VERB
fis-3181	139	6	in	in	ADP
fis-3181	139	7	highest	high	ADJ
fis-3181	139	8	accuracy	accuracy	NOUN
fis-3181	139	9	score	score	NOUN
fis-3181	139	10	of	of	ADP
fis-3181	139	11	0.89	0.89	NUM
fis-3181	139	12	in	in	ADP
fis-3181	139	13	comparison	comparison	NOUN
fis-3181	139	14	to	to	ADP
fis-3181	139	15	the	the	DET
fis-3181	139	16	other	other	ADJ
fis-3181	139	17	algorithms	algorithm	NOUN
fis-3181	139	18	while	while	SCONJ
fis-3181	139	19	ada	ada	PROPN
fis-3181	139	20	boost	boost	PROPN
fis-3181	139	21	algorithm	algorithm	NOUN
fis-3181	139	22	resulted	result	VERB
fis-3181	139	23	in	in	ADP
fis-3181	139	24	the	the	DET
fis-3181	139	25	lowest	low	ADJ
fis-3181	139	26	accuracy	accuracy	NOUN
fis-3181	139	27	score	score	NOUN
fis-3181	139	28	of	of	ADP
fis-3181	139	29	0.56	0.56	NUM
fis-3181	139	30	.	.	PUNCT
fis-3181	140	1			NOUN
fis-3181	140	2	it	it	PRON
fis-3181	140	3	can	can	AUX
fis-3181	140	4	be	be	AUX
fis-3181	140	5	concluded	conclude	VERB
fis-3181	140	6	that	that	SCONJ
fis-3181	140	7	the	the	DET
fis-3181	140	8	support	support	NOUN
fis-3181	140	9	vector	vector	NOUN
fis-3181	140	10	machine	machine	NOUN
fis-3181	140	11	algorithm	algorithm	NOUN
fis-3181	140	12	works	work	VERB
fis-3181	140	13	really	really	ADV
fis-3181	140	14	well	well	ADV
fis-3181	140	15	with	with	ADP
fis-3181	140	16	a	a	DET
fis-3181	140	17	clear	clear	ADJ
fis-3181	140	18	margin	margin	NOUN
fis-3181	140	19	of	of	ADP
fis-3181	140	20	separation	separation	NOUN
fis-3181	140	21	and	and	CCONJ
fis-3181	140	22	is	be	AUX
fis-3181	140	23	effective	effective	ADJ
fis-3181	140	24	in	in	ADP
fis-3181	140	25	cases	case	NOUN
fis-3181	140	26	where	where	SCONJ
fis-3181	140	27	the	the	DET
fis-3181	140	28	number	number	NOUN
fis-3181	140	29	of	of	ADP
fis-3181	140	30	dimensions	dimension	NOUN
fis-3181	140	31	is	be	AUX
fis-3181	140	32	greater	great	ADJ
fis-3181	140	33	than	than	ADP
fis-3181	140	34	the	the	DET
fis-3181	140	35	number	number	NOUN
fis-3181	140	36	of	of	ADP
fis-3181	140	37	samples	sample	NOUN
fis-3181	140	38	i.e.	i.e.	X
fis-3181	140	39	in	in	ADP
fis-3181	140	40	high	high	ADJ
fis-3181	140	41	-	-	PUNCT
fis-3181	140	42	dimensional	dimensional	ADJ
fis-3181	140	43	spaces	space	NOUN
fis-3181	140	44	.	.	PUNCT
fis-3181	141	1			X
fis-3181	141	2	the	the	DET
fis-3181	141	3	main	main	ADJ
fis-3181	141	4	insight	insight	NOUN
fis-3181	141	5	of	of	ADP
fis-3181	141	6	the	the	DET
fis-3181	141	7	present	present	ADJ
fis-3181	141	8	work	work	NOUN
fis-3181	141	9	is	be	AUX
fis-3181	141	10	that	that	SCONJ
fis-3181	141	11	the	the	DET
fis-3181	141	12	machine	machine	NOUN
fis-3181	141	13	learning	learning	NOUN
fis-3181	141	14	based	base	VERB
fis-3181	141	15	algorithms	algorithm	NOUN
fis-3181	141	16	can	can	AUX
fis-3181	141	17	reduce	reduce	VERB
fis-3181	141	18	the	the	DET
fis-3181	141	19	experimental	experimental	ADJ
fis-3181	141	20	time	time	NOUN
fis-3181	141	21	and	and	CCONJ
fis-3181	141	22	cost	cost	NOUN
fis-3181	141	23	by	by	ADP
fis-3181	141	24	resulting	result	VERB
fis-3181	141	25	in	in	ADP
fis-3181	141	26	greater	great	ADJ
fis-3181	141	27	accuracy	accuracy	NOUN
fis-3181	141	28	for	for	ADP
fis-3181	141	29	prediction	prediction	NOUN
fis-3181	141	30	purpose	purpose	NOUN
fis-3181	141	31	.	.	PUNCT
fis-3181	142	1			X
fis-3181	142	2	the	the	DET
fis-3181	142	3	future	future	ADJ
fis-3181	142	4	scope	scope	NOUN
fis-3181	142	5	of	of	ADP
fis-3181	142	6	this	this	DET
fis-3181	142	7	work	work	NOUN
fis-3181	142	8	is	be	AUX
fis-3181	142	9	to	to	PART
fis-3181	142	10	implement	implement	VERB
fis-3181	142	11	genetic	genetic	ADJ
fis-3181	142	12	algorithms	algorithm	NOUN
fis-3181	142	13	and	and	CCONJ
fis-3181	142	14	to	to	PART
fis-3181	142	15	check	check	VERB
fis-3181	142	16	whether	whether	SCONJ
fis-3181	142	17	they	they	PRON
fis-3181	142	18	can	can	AUX
fis-3181	142	19	classify	classify	VERB
fis-3181	142	20	the	the	DET
fis-3181	142	21	given	give	VERB
fis-3181	142	22	task	task	NOUN
fis-3181	142	23	better	well	ADV
fis-3181	142	24	than	than	ADP
fis-3181	142	25	the	the	DET
fis-3181	142	26	machine	machine	NOUN
fis-3181	142	27	learning	learn	VERB
fis-3181	142	28	algorithms	algorithm	NOUN
fis-3181	142	29	.	.	PUNCT
fis-3181	143	1	references	reference	NOUN
fis-3181	143	2	[	[	X
fis-3181	143	3	1	1	NUM
fis-3181	143	4	]	]	X
fis-3181	143	5	mitchell	mitchell	PROPN
fis-3181	143	6	,	,	PUNCT
fis-3181	143	7	t.m	t.m	PROPN
fis-3181	143	8	.	.	PROPN
fis-3181	143	9	(	(	PUNCT
fis-3181	143	10	1999	1999	NUM
fis-3181	143	11	)	)	PUNCT
fis-3181	143	12	.	.	PUNCT
fis-3181	144	1	machine	machine	NOUN
fis-3181	144	2	learning	learning	NOUN
fis-3181	144	3	and	and	CCONJ
fis-3181	144	4	data	datum	NOUN
fis-3181	144	5	mining	mining	NOUN
fis-3181	144	6	.	.	PUNCT
fis-3181	145	1	communications	communication	NOUN
fis-3181	145	2	of	of	ADP
fis-3181	145	3	the	the	DET
fis-3181	145	4	acm	acm	PROPN
fis-3181	145	5	,	,	PUNCT
fis-3181	145	6	42(11	42(11	NUM
fis-3181	145	7	)	)	PUNCT
fis-3181	145	8	,	,	PUNCT
fis-3181	145	9	pp.30	pp.30	NOUN
fis-3181	145	10	-	-	PUNCT
fis-3181	145	11	36	36	NUM
fis-3181	145	12	.	.	PUNCT
fis-3181	146	1	[	[	X
fis-3181	146	2	2	2	NUM
fis-3181	146	3	]	]	PUNCT
fis-3181	146	4	sajda	sajda	NOUN
fis-3181	146	5	,	,	PUNCT
fis-3181	146	6	p.	p.	NOUN
fis-3181	146	7	,	,	PUNCT
fis-3181	146	8	gerson	gerson	PROPN
fis-3181	146	9	,	,	PUNCT
fis-3181	146	10	a.	a.	PROPN
fis-3181	146	11	,	,	PUNCT
fis-3181	146	12	muller	muller	PROPN
fis-3181	146	13	,	,	PUNCT
fis-3181	146	14	k.r	k.r	PROPN
fis-3181	146	15	.	.	PROPN
fis-3181	146	16	,	,	PUNCT
fis-3181	146	17	blankertz	blankertz	PROPN
fis-3181	146	18	,	,	PUNCT
fis-3181	146	19	b.	b.	PROPN
fis-3181	146	20	and	and	CCONJ
fis-3181	146	21	parra	parra	PROPN
fis-3181	146	22	,	,	PUNCT
fis-3181	146	23	l.	l.	PROPN
fis-3181	146	24	(	(	PUNCT
fis-3181	146	25	2003	2003	NUM
fis-3181	146	26	)	)	PUNCT
fis-3181	146	27	.	.	PUNCT
fis-3181	147	1	a	a	DET
fis-3181	147	2	data	data	NOUN
fis-3181	147	3	analysis	analysis	NOUN
fis-3181	147	4	competition	competition	NOUN
fis-3181	147	5	to	to	PART
fis-3181	147	6	evaluate	evaluate	VERB
fis-3181	147	7	machine	machine	NOUN
fis-3181	147	8	learning	learning	NOUN
fis-3181	147	9	algorithms	algorithm	NOUN
fis-3181	147	10	for	for	ADP
fis-3181	147	11	use	use	NOUN
fis-3181	147	12	in	in	ADP
fis-3181	147	13	brain	brain	NOUN
fis-3181	147	14	-	-	PUNCT
fis-3181	147	15	computer	computer	NOUN
fis-3181	147	16	interfaces	interface	NOUN
fis-3181	147	17	.	.	PUNCT
fis-3181	148	1	ieee	ieee	NOUN
fis-3181	148	2	transactions	transaction	NOUN
fis-3181	148	3	on	on	ADP
fis-3181	148	4	neural	neural	ADJ
fis-3181	148	5	systems	system	NOUN
fis-3181	148	6	and	and	CCONJ
fis-3181	148	7	rehabilitation	rehabilitation	NOUN
fis-3181	148	8	engineering	engineering	NOUN
fis-3181	148	9	,	,	PUNCT
fis-3181	148	10	11(2	11(2	NUM
fis-3181	148	11	)	)	PUNCT
fis-3181	148	12	,	,	PUNCT
fis-3181	148	13	pp.184	pp.184	NOUN
fis-3181	148	14	-	-	PUNCT
fis-3181	148	15	185	185	NUM
fis-3181	148	16	.	.	PUNCT
fis-3181	149	1	[	[	X
fis-3181	149	2	3	3	NUM
fis-3181	149	3	]	]	X
fis-3181	149	4	džeroski	džeroski	PROPN
fis-3181	149	5	,	,	PUNCT
fis-3181	149	6	s.	s.	PROPN
fis-3181	149	7	,	,	PUNCT
fis-3181	149	8	grbović	grbović	PROPN
fis-3181	149	9	,	,	PUNCT
fis-3181	149	10	j.	j.	PROPN
fis-3181	149	11	,	,	PUNCT
fis-3181	149	12	walley	walley	PROPN
fis-3181	149	13	,	,	PUNCT
fis-3181	149	14	w.j	w.j	PROPN
fis-3181	149	15	.	.	PROPN
fis-3181	149	16	and	and	CCONJ
fis-3181	149	17	kompare	kompare	PROPN
fis-3181	149	18	,	,	PUNCT
fis-3181	149	19	b.	b.	PROPN
fis-3181	149	20	(	(	PUNCT
fis-3181	149	21	1997	1997	NUM
fis-3181	149	22	)	)	PUNCT
fis-3181	149	23	.	.	PUNCT
fis-3181	150	1	using	use	VERB
fis-3181	150	2	machine	machine	NOUN
fis-3181	150	3	learning	learn	VERB
fis-3181	150	4	techniques	technique	NOUN
fis-3181	150	5	in	in	ADP
fis-3181	150	6	the	the	DET
fis-3181	150	7	construction	construction	NOUN
fis-3181	150	8	of	of	ADP
fis-3181	150	9	models	model	NOUN
fis-3181	150	10	.	.	PUNCT
fis-3181	151	1	ii	ii	PROPN
fis-3181	151	2	.	.	PUNCT
fis-3181	152	1	data	datum	NOUN
fis-3181	152	2	analysis	analysis	NOUN
fis-3181	152	3	with	with	ADP
fis-3181	152	4	rule	rule	NOUN
fis-3181	152	5	induction	induction	NOUN
fis-3181	152	6	.	.	PUNCT
fis-3181	153	1	ecological	ecological	ADJ
fis-3181	153	2	modelling	modelling	NOUN
fis-3181	153	3	,	,	PUNCT
fis-3181	153	4	95(1	95(1	NOUN
fis-3181	153	5	)	)	PUNCT
fis-3181	153	6	,	,	PUNCT
fis-3181	153	7	pp	pp	ADP
fis-3181	153	8	.	.	PUNCT
fis-3181	154	1	95	95	NUM
fis-3181	154	2	-	-	SYM
fis-3181	154	3	111	111	NUM
fis-3181	154	4	.	.	PUNCT
fis-3181	155	1	[	[	X
fis-3181	155	2	4	4	NUM
fis-3181	155	3	]	]	X
fis-3181	155	4	ratner	ratner	X
fis-3181	155	5	,	,	PUNCT
fis-3181	155	6	b.	b.	PROPN
fis-3181	155	7	(	(	PUNCT
fis-3181	155	8	2017	2017	NUM
fis-3181	155	9	)	)	PUNCT
fis-3181	155	10	.	.	PUNCT
fis-3181	156	1	statistical	statistical	ADJ
fis-3181	156	2	and	and	CCONJ
fis-3181	156	3	machine	machine	NOUN
fis-3181	156	4	-	-	PUNCT
fis-3181	156	5	learning	learn	VERB
fis-3181	156	6	data	datum	NOUN
fis-3181	156	7	mining	mining	NOUN
fis-3181	156	8	:	:	PUNCT
fis-3181	156	9	techniques	technique	NOUN
fis-3181	156	10	for	for	ADP
fis-3181	156	11	better	well	ADJ
fis-3181	156	12	predictive	predictive	ADJ
fis-3181	156	13	modeling	modeling	NOUN
fis-3181	156	14	and	and	CCONJ
fis-3181	156	15	analysis	analysis	NOUN
fis-3181	156	16	of	of	ADP
fis-3181	156	17	big	big	ADJ
fis-3181	156	18	data	datum	NOUN
fis-3181	156	19	.	.	PUNCT
fis-3181	157	1	crc	crc	PROPN
fis-3181	157	2	press	press	PROPN
fis-3181	157	3	.	.	PUNCT
fis-3181	158	1	[	[	X
fis-3181	158	2	5	5	NUM
fis-3181	158	3	]	]	X
fis-3181	158	4	gilardi	gilardi	NOUN
fis-3181	158	5	,	,	PUNCT
fis-3181	158	6	n.	n.	NOUN
fis-3181	158	7	and	and	CCONJ
fis-3181	158	8	bengio	bengio	PROPN
fis-3181	158	9	,	,	PUNCT
fis-3181	158	10	s.	s.	PROPN
fis-3181	158	11	(	(	PUNCT
fis-3181	158	12	2000	2000	NUM
fis-3181	158	13	)	)	PUNCT
fis-3181	158	14	.	.	PUNCT
fis-3181	159	1	local	local	ADJ
fis-3181	159	2	machine	machine	NOUN
fis-3181	159	3	learning	learning	NOUN
fis-3181	159	4	models	model	NOUN
fis-3181	159	5	for	for	ADP
fis-3181	159	6	spatial	spatial	ADJ
fis-3181	159	7	data	datum	NOUN
fis-3181	159	8	analysis	analysis	NOUN
fis-3181	159	9	.	.	PUNCT
fis-3181	160	1	journal	journal	PROPN
fis-3181	160	2	of	of	ADP
fis-3181	160	3	geographic	geographic	ADJ
fis-3181	160	4	information	information	NOUN
fis-3181	160	5	and	and	CCONJ
fis-3181	160	6	decision	decision	NOUN
fis-3181	160	7	analysis	analysis	NOUN
fis-3181	160	8	,	,	PUNCT
fis-3181	160	9	4	4	NUM
fis-3181	160	10	,	,	PUNCT
fis-3181	160	11	pp.11	pp.11	NOUN
fis-3181	160	12	-	-	PUNCT
fis-3181	160	13	28	28	NUM
fis-3181	160	14	.	.	PUNCT
fis-3181	161	1	[	[	X
fis-3181	161	2	6	6	NUM
fis-3181	161	3	]	]	X
fis-3181	161	4	xie	xie	PROPN
fis-3181	161	5	,	,	PUNCT
fis-3181	161	6	j.	j.	PROPN
fis-3181	161	7	,	,	PUNCT
fis-3181	161	8	song	song	PROPN
fis-3181	161	9	,	,	PUNCT
fis-3181	161	10	z.	z.	PROPN
fis-3181	161	11	,	,	PUNCT
fis-3181	161	12	li	li	PROPN
fis-3181	161	13	,	,	PUNCT
fis-3181	161	14	y.	y.	PROPN
fis-3181	161	15	,	,	PUNCT
fis-3181	161	16	zhang	zhang	PROPN
fis-3181	161	17	,	,	PUNCT
fis-3181	161	18	y.	y.	PROPN
fis-3181	161	19	,	,	PUNCT
fis-3181	161	20	yu	yu	PROPN
fis-3181	161	21	,	,	PUNCT
fis-3181	161	22	h.	h.	PROPN
fis-3181	161	23	,	,	PUNCT
fis-3181	161	24	zhan	zhan	PROPN
fis-3181	161	25	,	,	PUNCT
fis-3181	161	26	j.	j.	PROPN
fis-3181	161	27	,	,	PUNCT
fis-3181	161	28	ma	ma	PROPN
fis-3181	161	29	,	,	PUNCT
fis-3181	161	30	z.	z.	PROPN
fis-3181	161	31	,	,	PUNCT
fis-3181	161	32	qiao	qiao	PROPN
fis-3181	161	33	,	,	PUNCT
fis-3181	161	34	y.	y.	PROPN
fis-3181	161	35	,	,	PUNCT
fis-3181	161	36	zhang	zhang	PROPN
fis-3181	161	37	,	,	PUNCT
fis-3181	161	38	j.	j.	PROPN
fis-3181	161	39	and	and	CCONJ
fis-3181	161	40	guo	guo	PROPN
fis-3181	161	41	,	,	PUNCT
fis-3181	161	42	j.	j.	PROPN
fis-3181	161	43	(	(	PUNCT
fis-3181	161	44	2018	2018	NUM
fis-3181	161	45	)	)	PUNCT
fis-3181	161	46	.	.	PUNCT
fis-3181	162	1	a	a	DET
fis-3181	162	2	survey	survey	NOUN
fis-3181	162	3	on	on	ADP
fis-3181	162	4	machine	machine	NOUN
fis-3181	162	5	learning	learning	NOUN
fis-3181	162	6	-	-	PUNCT
fis-3181	162	7	based	base	VERB
fis-3181	162	8	mobile	mobile	ADJ
fis-3181	162	9	big	big	ADJ
fis-3181	162	10	data	datum	NOUN
fis-3181	162	11	analysis	analysis	NOUN
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fis-3181	166	7	)	)	PUNCT
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fis-3181	169	5	.	.	PUNCT
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fis-3181	170	3	]	]	SYM
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fis-3181	170	39	.	.	PUNCT
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fis-3181	171	4	)	)	PUNCT
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fis-3181	183	17	)	)	PUNCT
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