id	sid	tid	token	lemma	pos
fis-5022	1	1	microsoft	microsoft	PROPN
fis-5022	1	2	word	word	NOUN
fis-5022	1	3	numero_70_art_10_5022.docx	numero_70_art_10_5022.docx	PROPN
fis-5022	1	4	a.	a.	NOUN
fis-5022	1	5	chulkov	chulkov	PROPN
fis-5022	1	6	et	et	PROPN
fis-5022	1	7	alii	alii	PROPN
fis-5022	1	8	,	,	PUNCT
fis-5022	1	9	frattura	frattura	PROPN
fis-5022	1	10	ed	ed	PROPN
fis-5022	1	11	integrità	integrità	PROPN
fis-5022	1	12	strutturale	strutturale	PROPN
fis-5022	1	13	,	,	PUNCT
fis-5022	1	14	70	70	NUM
fis-5022	1	15	(	(	PUNCT
fis-5022	1	16	2024	2024	NUM
fis-5022	1	17	)	)	PUNCT
fis-5022	1	18	177	177	NUM
fis-5022	1	19	-	-	SYM
fis-5022	1	20	191	191	NUM
fis-5022	1	21	;	;	PUNCT
fis-5022	1	22	doi	doi	NOUN
fis-5022	1	23	:	:	PUNCT
fis-5022	1	24	10.3221	10.3221	NUM
fis-5022	1	25	/	/	SYM
fis-5022	1	26	igf	igf	NOUN
fis-5022	1	27	-	-	ADJ
fis-5022	1	28	esis.70.10	esis.70.10	ADJ
fis-5022	1	29	177	177	NUM
fis-5022	1	30	enhancing	enhance	VERB
fis-5022	1	31	generalizability	generalizability	NOUN
fis-5022	1	32	of	of	ADP
fis-5022	1	33	a	a	DET
fis-5022	1	34	machine	machine	NOUN
fis-5022	1	35	learning	learn	VERB
fis-5022	1	36	model	model	NOUN
fis-5022	1	37	for	for	ADP
fis-5022	1	38	infrared	infrared	ADJ
fis-5022	1	39	thermographic	thermographic	ADJ
fis-5022	1	40	defect	defect	NOUN
fis-5022	1	41	detection	detection	NOUN
fis-5022	1	42	by	by	ADP
fis-5022	1	43	using	use	VERB
fis-5022	1	44	3d	3d	PROPN
fis-5022	1	45	numerical	numerical	PROPN
fis-5022	1	46	modeling	modeling	NOUN
fis-5022	1	47	arsenii	arsenii	NOUN
fis-5022	1	48	chulkov	chulkov	VERB
fis-5022	1	49	tomsk	tomsk	PROPN
fis-5022	1	50	polytechnic	polytechnic	PROPN
fis-5022	1	51	university	university	PROPN
fis-5022	1	52	,	,	PUNCT
fis-5022	1	53	russia	russia	PROPN
fis-5022	1	54	chulkovao@tpu.ru	chulkovao@tpu.ru	PROPN
fis-5022	1	55	,	,	PUNCT
fis-5022	1	56	http://orcid.org/0000-0003-1226-0013	http://orcid.org/0000-0003-1226-0013	PROPN
fis-5022	1	57	alexey	alexey	PROPN
fis-5022	1	58	moskovchenko	moskovchenko	PROPN
fis-5022	1	59	university	university	PROPN
fis-5022	1	60	of	of	ADP
fis-5022	1	61	west	west	PROPN
fis-5022	1	62	bohemia	bohemia	PROPN
fis-5022	1	63	,	,	PUNCT
fis-5022	1	64	czech	czech	PROPN
fis-5022	1	65	republic	republic	PROPN
fis-5022	1	66	alexeym@ntc.zcu.cz	alexeym@ntc.zcu.cz	PROPN
fis-5022	1	67	,	,	PUNCT
fis-5022	1	68	http://orcid.org/0000-0002-2813-2529	http://orcid.org/0000-0002-2813-2529	PROPN
fis-5022	1	69	vladimir	vladimir	PROPN
fis-5022	1	70	vavilov	vavilov	PROPN
fis-5022	1	71	tomsk	tomsk	PROPN
fis-5022	1	72	polytechnic	polytechnic	PROPN
fis-5022	1	73	university	university	PROPN
fis-5022	1	74	,	,	PUNCT
fis-5022	1	75	russia	russia	PROPN
fis-5022	1	76	vavilov@tpu.ru	vavilov@tpu.ru	PRON
fis-5022	1	77	,	,	PUNCT
fis-5022	1	78	http://orcid.org/	http://orcid.org/	PROPN
fis-5022	1	79	0000	0000	NUM
fis-5022	1	80	-	-	PUNCT
fis-5022	1	81	0002	0002	NUM
fis-5022	1	82	-	-	PUNCT
fis-5022	1	83	9828	9828	NUM
fis-5022	1	84	-	-	PUNCT
fis-5022	1	85	7374	7374	NUM
fis-5022	1	86	keywords	keyword	NOUN
fis-5022	1	87	.	.	PUNCT
fis-5022	2	1	infrared	infrared	ADJ
fis-5022	2	2	thermography	thermography	NOUN
fis-5022	2	3	,	,	PUNCT
fis-5022	2	4	nondestructive	nondestructive	ADJ
fis-5022	2	5	testing	testing	NOUN
fis-5022	2	6	,	,	PUNCT
fis-5022	2	7	machine	machine	NOUN
fis-5022	2	8	learning	learning	PROPN
fis-5022	2	9	,	,	PUNCT
fis-5022	2	10	numerical	numerical	PROPN
fis-5022	2	11	simulation	simulation	PROPN
fis-5022	2	12	,	,	PUNCT
fis-5022	2	13	defect	defect	ADJ
fis-5022	2	14	detection	detection	NOUN
fis-5022	2	15	.	.	PUNCT
fis-5022	3	1	citation	citation	NOUN
fis-5022	3	2	:	:	PUNCT
fis-5022	3	3	chulkov	chulkov	PROPN
fis-5022	3	4	,	,	PUNCT
fis-5022	3	5	a.	a.	NOUN
fis-5022	3	6	,	,	PUNCT
fis-5022	3	7	moskovchenko	moskovchenko	ADJ
fis-5022	3	8	,	,	PUNCT
fis-5022	3	9	a.	a.	NOUN
fis-5022	3	10	,	,	PUNCT
fis-5022	3	11	vavilov	vavilov	PROPN
fis-5022	3	12	,	,	PUNCT
fis-5022	3	13	v.	v.	ADV
fis-5022	3	14	,	,	PUNCT
fis-5022	3	15	enhancing	enhance	VERB
fis-5022	3	16	generalizability	generalizability	NOUN
fis-5022	3	17	of	of	ADP
fis-5022	3	18	a	a	DET
fis-5022	3	19	machine	machine	NOUN
fis-5022	3	20	learning	learn	VERB
fis-5022	3	21	model	model	NOUN
fis-5022	3	22	for	for	ADP
fis-5022	3	23	infrared	infrared	ADJ
fis-5022	3	24	thermographic	thermographic	ADJ
fis-5022	3	25	defect	defect	NOUN
fis-5022	3	26	detection	detection	NOUN
fis-5022	3	27	by	by	ADP
fis-5022	3	28	using	use	VERB
fis-5022	3	29	3d	3d	PROPN
fis-5022	3	30	numerical	numerical	PROPN
fis-5022	3	31	modeling	modeling	PROPN
fis-5022	3	32	,	,	PUNCT
fis-5022	3	33	frattura	frattura	PROPN
fis-5022	3	34	ed	ed	PROPN
fis-5022	3	35	integrità	integrità	PROPN
fis-5022	3	36	strutturale	strutturale	PROPN
fis-5022	3	37	,	,	PUNCT
fis-5022	3	38	70	70	NUM
fis-5022	3	39	(	(	PUNCT
fis-5022	3	40	2024	2024	NUM
fis-5022	3	41	)	)	PUNCT
fis-5022	3	42	177	177	NUM
fis-5022	3	43	-	-	SYM
fis-5022	3	44	191	191	NUM
fis-5022	3	45	.	.	PUNCT
fis-5022	3	46	received	receive	VERB
fis-5022	3	47	:	:	PUNCT
fis-5022	3	48	28.05.2024	28.05.2024	NUM
fis-5022	3	49	accepted	accept	VERB
fis-5022	3	50	:	:	PUNCT
fis-5022	3	51	26.07.2024	26.07.2024	NUM
fis-5022	3	52	published	publish	VERB
fis-5022	3	53	:	:	PUNCT
fis-5022	3	54	19.08.2024	19.08.2024	NUM
fis-5022	3	55	issue	issue	NOUN
fis-5022	3	56	:	:	PUNCT
fis-5022	3	57	10.2024	10.2024	NUM
fis-5022	3	58	copyright	copyright	NOUN
fis-5022	3	59	:	:	PUNCT
fis-5022	3	60	©	©	PROPN
fis-5022	3	61	2024	2024	NUM
fis-5022	3	62	this	this	PRON
fis-5022	3	63	is	be	AUX
fis-5022	3	64	an	an	DET
fis-5022	3	65	open	open	ADJ
fis-5022	3	66	access	access	NOUN
fis-5022	3	67	article	article	NOUN
fis-5022	3	68	under	under	ADP
fis-5022	3	69	the	the	DET
fis-5022	3	70	terms	term	NOUN
fis-5022	3	71	of	of	ADP
fis-5022	3	72	the	the	DET
fis-5022	3	73	cc	cc	NOUN
fis-5022	3	74	-	-	PUNCT
fis-5022	3	75	by	by	ADP
fis-5022	3	76	4.0	4.0	NUM
fis-5022	3	77	,	,	PUNCT
fis-5022	3	78	which	which	PRON
fis-5022	3	79	permits	permit	VERB
fis-5022	3	80	unrestricted	unrestricted	ADJ
fis-5022	3	81	use	use	NOUN
fis-5022	3	82	,	,	PUNCT
fis-5022	3	83	distribution	distribution	NOUN
fis-5022	3	84	,	,	PUNCT
fis-5022	3	85	and	and	CCONJ
fis-5022	3	86	reproduction	reproduction	NOUN
fis-5022	3	87	in	in	ADP
fis-5022	3	88	any	any	DET
fis-5022	3	89	medium	medium	NOUN
fis-5022	3	90	,	,	PUNCT
fis-5022	3	91	provided	provide	VERB
fis-5022	3	92	the	the	DET
fis-5022	3	93	original	original	ADJ
fis-5022	3	94	author	author	NOUN
fis-5022	3	95	and	and	CCONJ
fis-5022	3	96	source	source	NOUN
fis-5022	3	97	are	be	AUX
fis-5022	3	98	credited	credit	VERB
fis-5022	3	99	.	.	PUNCT
fis-5022	4	1	introduction	introduction	NOUN
fis-5022	4	2	nfrared	nfrare	VERB
fis-5022	4	3	(	(	PUNCT
fis-5022	4	4	ir	ir	NOUN
fis-5022	4	5	)	)	PUNCT
fis-5022	4	6	thermography	thermography	NOUN
fis-5022	4	7	is	be	AUX
fis-5022	4	8	a	a	DET
fis-5022	4	9	method	method	NOUN
fis-5022	4	10	of	of	ADP
fis-5022	4	11	non	non	ADJ
fis-5022	4	12	-	-	ADJ
fis-5022	4	13	destructive	destructive	ADJ
fis-5022	4	14	testing	testing	NOUN
fis-5022	4	15	(	(	PUNCT
fis-5022	4	16	ndt	ndt	PROPN
fis-5022	4	17	)	)	PUNCT
fis-5022	4	18	based	base	VERB
fis-5022	4	19	on	on	ADP
fis-5022	4	20	the	the	DET
fis-5022	4	21	analysis	analysis	NOUN
fis-5022	4	22	of	of	ADP
fis-5022	4	23	thermal	thermal	ADJ
fis-5022	4	24	patterns	pattern	NOUN
fis-5022	4	25	on	on	ADP
fis-5022	4	26	the	the	DET
fis-5022	4	27	surface	surface	NOUN
fis-5022	4	28	of	of	ADP
fis-5022	4	29	objects	object	NOUN
fis-5022	4	30	under	under	ADP
fis-5022	4	31	test	test	NOUN
fis-5022	4	32	by	by	ADP
fis-5022	4	33	using	use	VERB
fis-5022	4	34	thermal	thermal	ADJ
fis-5022	4	35	imagers	imager	NOUN
fis-5022	4	36	[	[	X
fis-5022	4	37	1	1	NUM
fis-5022	4	38	]	]	PUNCT
fis-5022	4	39	.	.	PUNCT
fis-5022	5	1	thermal	thermal	ADJ
fis-5022	5	2	stimulation	stimulation	NOUN
fis-5022	5	3	of	of	ADP
fis-5022	5	4	objects	object	NOUN
fis-5022	5	5	and	and	CCONJ
fis-5022	5	6	subsequent	subsequent	ADJ
fis-5022	5	7	analysis	analysis	NOUN
fis-5022	5	8	of	of	ADP
fis-5022	5	9	temperature	temperature	NOUN
fis-5022	5	10	distributions	distribution	NOUN
fis-5022	5	11	allow	allow	VERB
fis-5022	5	12	detecting	detect	VERB
fis-5022	5	13	structural	structural	ADJ
fis-5022	5	14	defects	defect	NOUN
fis-5022	5	15	and	and	CCONJ
fis-5022	5	16	thermal	thermal	ADJ
fis-5022	5	17	anomalies	anomaly	NOUN
fis-5022	5	18	in	in	ADP
fis-5022	5	19	various	various	ADJ
fis-5022	5	20	materials	material	NOUN
fis-5022	5	21	.	.	PUNCT
fis-5022	6	1	due	due	ADP
fis-5022	6	2	to	to	ADP
fis-5022	6	3	its	its	PRON
fis-5022	6	4	simplicity	simplicity	NOUN
fis-5022	6	5	,	,	PUNCT
fis-5022	6	6	non	non	ADJ
fis-5022	6	7	-	-	ADJ
fis-5022	6	8	contact	contact	ADJ
fis-5022	6	9	nature	nature	NOUN
fis-5022	6	10	of	of	ADP
fis-5022	6	11	testing	testing	NOUN
fis-5022	6	12	and	and	CCONJ
fis-5022	6	13	capacity	capacity	NOUN
fis-5022	6	14	to	to	PART
fis-5022	6	15	swiftly	swiftly	ADV
fis-5022	6	16	assess	assess	VERB
fis-5022	6	17	large	large	ADJ
fis-5022	6	18	areas	area	NOUN
fis-5022	6	19	,	,	PUNCT
fis-5022	6	20	ir	ir	PROPN
fis-5022	6	21	thermographic	thermographic	PROPN
fis-5022	6	22	ndt	ndt	PROPN
fis-5022	6	23	has	have	AUX
fis-5022	6	24	become	become	VERB
fis-5022	6	25	i	i	PRON
fis-5022	6	26	https://youtu.be/erittw-oq8k	https://youtu.be/erittw-oq8k	NOUN
fis-5022	6	27	a.	a.	NOUN
fis-5022	6	28	chulkov	chulkov	PROPN
fis-5022	6	29	et	et	PROPN
fis-5022	6	30	alii	alii	PROPN
fis-5022	6	31	,	,	PUNCT
fis-5022	6	32	frattura	frattura	PROPN
fis-5022	6	33	ed	ed	PROPN
fis-5022	6	34	integrità	integrità	PROPN
fis-5022	6	35	strutturale	strutturale	PROPN
fis-5022	6	36	,	,	PUNCT
fis-5022	6	37	70	70	NUM
fis-5022	6	38	(	(	PUNCT
fis-5022	6	39	2024	2024	NUM
fis-5022	6	40	)	)	PUNCT
fis-5022	6	41	177	177	NUM
fis-5022	6	42	-	-	SYM
fis-5022	6	43	191	191	NUM
fis-5022	6	44	;	;	PUNCT
fis-5022	6	45	doi	doi	NOUN
fis-5022	6	46	:	:	PUNCT
fis-5022	6	47	10.3221	10.3221	NUM
fis-5022	6	48	/	/	SYM
fis-5022	6	49	igf	igf	NOUN
fis-5022	6	50	-	-	ADJ
fis-5022	6	51	esis.70.10	esis.70.10	ADJ
fis-5022	6	52	178	178	NUM
fis-5022	6	53	widespread	widespread	ADJ
fis-5022	6	54	in	in	ADP
fis-5022	6	55	the	the	DET
fis-5022	6	56	aerospace	aerospace	NOUN
fis-5022	6	57	industry	industry	NOUN
fis-5022	6	58	[	[	X
fis-5022	6	59	2	2	NUM
fis-5022	6	60	,	,	PUNCT
fis-5022	6	61	3	3	NUM
fis-5022	6	62	]	]	PUNCT
fis-5022	6	63	,	,	PUNCT
fis-5022	6	64	power	power	NOUN
fis-5022	6	65	production	production	NOUN
fis-5022	6	66	and	and	CCONJ
fis-5022	6	67	civil	civil	ADJ
fis-5022	6	68	engineering	engineering	NOUN
fis-5022	6	69	[	[	X
fis-5022	6	70	4–6	4–6	X
fis-5022	6	71	]	]	X
fis-5022	6	72	,	,	PUNCT
fis-5022	6	73	including	include	VERB
fis-5022	6	74	evaluation	evaluation	NOUN
fis-5022	6	75	of	of	ADP
fis-5022	6	76	composite	composite	ADJ
fis-5022	6	77	materials	material	NOUN
fis-5022	6	78	(	(	PUNCT
fis-5022	6	79	carbon	carbon	NOUN
fis-5022	6	80	and	and	CCONJ
fis-5022	6	81	glass	glass	NOUN
fis-5022	6	82	fiber	fiber	NOUN
fis-5022	6	83	plastics	plastic	NOUN
fis-5022	6	84	)	)	PUNCT
fis-5022	7	1	[	[	X
fis-5022	7	2	7	7	NUM
fis-5022	7	3	]	]	PUNCT
fis-5022	7	4	.	.	PUNCT
fis-5022	8	1	however	however	ADV
fis-5022	8	2	,	,	PUNCT
fis-5022	8	3	ir	ir	PROPN
fis-5022	8	4	thermography	thermography	NOUN
fis-5022	8	5	possesses	possess	VERB
fis-5022	8	6	some	some	DET
fis-5022	8	7	drawbacks	drawback	NOUN
fis-5022	8	8	,	,	PUNCT
fis-5022	8	9	such	such	ADJ
fis-5022	8	10	as	as	ADP
fis-5022	8	11	a	a	DET
fis-5022	8	12	diffusive	diffusive	ADJ
fis-5022	8	13	nature	nature	NOUN
fis-5022	8	14	of	of	ADP
fis-5022	8	15	heat	heat	NOUN
fis-5022	8	16	conduction	conduction	NOUN
fis-5022	8	17	,	,	PUNCT
fis-5022	8	18	sensitivity	sensitivity	NOUN
fis-5022	8	19	to	to	ADP
fis-5022	8	20	environmental	environmental	ADJ
fis-5022	8	21	conditions	condition	NOUN
fis-5022	8	22	,	,	PUNCT
fis-5022	8	23	need	need	VERB
fis-5022	8	24	for	for	ADP
fis-5022	8	25	properly	properly	ADV
fis-5022	8	26	-	-	PUNCT
fis-5022	8	27	trained	train	VERB
fis-5022	8	28	operators	operator	NOUN
fis-5022	8	29	,	,	PUNCT
fis-5022	8	30	etc	etc	X
fis-5022	8	31	.	.	X
fis-5022	8	32	flash	flash	NOUN
fis-5022	8	33	thermography	thermography	NOUN
fis-5022	8	34	(	(	PUNCT
fis-5022	8	35	ft	ft	NOUN
fis-5022	8	36	)	)	PUNCT
fis-5022	8	37	involves	involve	VERB
fis-5022	8	38	the	the	DET
fis-5022	8	39	use	use	NOUN
fis-5022	8	40	of	of	ADP
fis-5022	8	41	powerful	powerful	ADJ
fis-5022	8	42	heat	heat	NOUN
fis-5022	8	43	sources	source	NOUN
fis-5022	8	44	(	(	PUNCT
fis-5022	8	45	e.g.	e.g.	ADV
fis-5022	8	46	flash	flash	VERB
fis-5022	8	47	tubes	tube	NOUN
fis-5022	8	48	and	and	CCONJ
fis-5022	8	49	lasers	laser	NOUN
fis-5022	8	50	)	)	PUNCT
fis-5022	8	51	generating	generate	VERB
fis-5022	8	52	short	short	ADJ
fis-5022	8	53	optical	optical	ADJ
fis-5022	8	54	pulses	pulse	NOUN
fis-5022	8	55	which	which	PRON
fis-5022	8	56	can	can	AUX
fis-5022	8	57	be	be	AUX
fis-5022	8	58	considered	consider	VERB
fis-5022	8	59	as	as	ADP
fis-5022	8	60	dirac	dirac	NOUN
fis-5022	8	61	pulses	pulse	NOUN
fis-5022	8	62	[	[	X
fis-5022	8	63	8	8	NUM
fis-5022	8	64	]	]	PUNCT
fis-5022	8	65	.	.	PUNCT
fis-5022	9	1	due	due	ADP
fis-5022	9	2	to	to	ADP
fis-5022	9	3	short	short	ADJ
fis-5022	9	4	observation	observation	NOUN
fis-5022	9	5	times	time	NOUN
fis-5022	9	6	,	,	PUNCT
fis-5022	9	7	flash	flash	NOUN
fis-5022	9	8	thermography	thermography	NOUN
fis-5022	9	9	provides	provide	VERB
fis-5022	9	10	highresolution	highresolution	NOUN
fis-5022	9	11	thermal	thermal	ADJ
fis-5022	9	12	images	image	NOUN
fis-5022	9	13	facilitating	facilitate	VERB
fis-5022	9	14	the	the	DET
fis-5022	9	15	detection	detection	NOUN
fis-5022	9	16	of	of	ADP
fis-5022	9	17	small	small	ADJ
fis-5022	9	18	-	-	PUNCT
fis-5022	9	19	size	size	NOUN
fis-5022	9	20	defects	defect	NOUN
fis-5022	9	21	in	in	ADP
fis-5022	9	22	materials	material	NOUN
fis-5022	9	23	and	and	CCONJ
fis-5022	9	24	structures	structure	NOUN
fis-5022	9	25	.	.	PUNCT
fis-5022	10	1	the	the	DET
fis-5022	10	2	integration	integration	NOUN
fis-5022	10	3	of	of	ADP
fis-5022	10	4	automation	automation	NOUN
fis-5022	10	5	and	and	CCONJ
fis-5022	10	6	machine	machine	NOUN
fis-5022	10	7	learning	learn	VERB
fis-5022	10	8	into	into	ADP
fis-5022	10	9	ir	ir	PROPN
fis-5022	10	10	thermography	thermography	NOUN
fis-5022	10	11	has	have	AUX
fis-5022	10	12	significantly	significantly	ADV
fis-5022	10	13	expanded	expand	VERB
fis-5022	10	14	potentials	potential	NOUN
fis-5022	10	15	of	of	ADP
fis-5022	10	16	this	this	DET
fis-5022	10	17	technique	technique	NOUN
fis-5022	10	18	[	[	X
fis-5022	10	19	9–11	9–11	NOUN
fis-5022	10	20	]	]	PUNCT
fis-5022	10	21	.	.	PUNCT
fis-5022	11	1	in	in	ADP
fis-5022	11	2	2016	2016	NUM
fis-5022	11	3	,	,	PUNCT
fis-5022	11	4	khodayar	khodayar	PROPN
fis-5022	11	5	et	et	PROPN
fis-5022	11	6	al	al	PROPN
fis-5022	11	7	.	.	PROPN
fis-5022	11	8	outlined	outline	VERB
fis-5022	11	9	the	the	DET
fis-5022	11	10	use	use	NOUN
fis-5022	11	11	of	of	ADP
fis-5022	11	12	artificial	artificial	ADJ
fis-5022	11	13	intelligence	intelligence	NOUN
fis-5022	11	14	as	as	ADP
fis-5022	11	15	the	the	DET
fis-5022	11	16	“	"	PUNCT
fis-5022	11	17	2050	2050	NUM
fis-5022	11	18	-	-	PUNCT
fis-5022	11	19	horizon	horizon	NOUN
fis-5022	11	20	”	"	PUNCT
fis-5022	11	21	in	in	ADP
fis-5022	11	22	ir	ir	PROPN
fis-5022	11	23	thermographic	thermographic	ADJ
fis-5022	11	24	ndt	ndt	PROPN
fis-5022	12	1	[	[	X
fis-5022	12	2	12	12	NUM
fis-5022	12	3	]	]	PUNCT
fis-5022	12	4	.	.	PUNCT
fis-5022	13	1	the	the	DET
fis-5022	13	2	state	state	NOUN
fis-5022	13	3	-	-	PUNCT
fis-5022	13	4	of	of	ADP
fis-5022	13	5	-	-	PUNCT
fis-5022	13	6	the	the	DET
fis-5022	13	7	-	-	PUNCT
fis-5022	13	8	art	art	NOUN
fis-5022	13	9	and	and	CCONJ
fis-5022	13	10	recent	recent	ADJ
fis-5022	13	11	improvements	improvement	NOUN
fis-5022	13	12	in	in	ADP
fis-5022	13	13	convolutional	convolutional	ADJ
fis-5022	13	14	neural	neural	ADJ
fis-5022	13	15	networks	network	NOUN
fis-5022	13	16	(	(	PUNCT
fis-5022	13	17	cnn	cnn	PROPN
fis-5022	13	18	)	)	PUNCT
fis-5022	13	19	was	be	AUX
fis-5022	13	20	presented	present	VERB
fis-5022	13	21	in	in	ADP
fis-5022	13	22	2018	2018	NUM
fis-5022	13	23	by	by	ADP
fis-5022	13	24	jiuxiang	jiuxiang	PROPN
fis-5022	13	25	gu	gu	PROPN
fis-5022	13	26	et	et	PROPN
fis-5022	13	27	al	al	PROPN
fis-5022	13	28	.	.	PUNCT
fis-5022	14	1	[	[	X
fis-5022	14	2	13	13	NUM
fis-5022	14	3	]	]	PUNCT
fis-5022	14	4	.	.	PUNCT
fis-5022	15	1	in	in	ADP
fis-5022	15	2	the	the	DET
fis-5022	15	3	recent	recent	ADJ
fis-5022	15	4	review	review	NOUN
fis-5022	15	5	paper	paper	NOUN
fis-5022	15	6	,	,	PUNCT
fis-5022	15	7	yunze	yunze	NOUN
fis-5022	15	8	he	he	PRON
fis-5022	15	9	et	et	PROPN
fis-5022	15	10	al	al	PROPN
fis-5022	15	11	.	.	PROPN
fis-5022	15	12	stated	state	VERB
fis-5022	15	13	that	that	SCONJ
fis-5022	15	14	the	the	DET
fis-5022	15	15	rapid	rapid	ADJ
fis-5022	15	16	development	development	NOUN
fis-5022	15	17	of	of	ADP
fis-5022	15	18	deep	deep	ADJ
fis-5022	15	19	learning	learning	NOUN
fis-5022	15	20	makes	make	VERB
fis-5022	15	21	ir	ir	PROPN
fis-5022	15	22	machine	machine	NOUN
fis-5022	15	23	vision	vision	NOUN
fis-5022	15	24	and	and	CCONJ
fis-5022	15	25	ir	ir	PROPN
fis-5022	15	26	thermographic	thermographic	ADJ
fis-5022	15	27	ndt	ndt	PROPN
fis-5022	15	28	more	more	ADV
fis-5022	15	29	intelligent	intelligent	ADJ
fis-5022	15	30	thus	thus	ADV
fis-5022	15	31	contributing	contribute	VERB
fis-5022	15	32	to	to	ADP
fis-5022	15	33	broadening	broaden	VERB
fis-5022	15	34	applications	application	NOUN
fis-5022	15	35	of	of	ADP
fis-5022	15	36	these	these	DET
fis-5022	15	37	techniques	technique	NOUN
fis-5022	15	38	[	[	X
fis-5022	15	39	14	14	NUM
fis-5022	15	40	]	]	PUNCT
fis-5022	15	41	.	.	PUNCT
fis-5022	16	1	in	in	ADP
fis-5022	16	2	active	active	ADJ
fis-5022	16	3	ir	ir	PROPN
fis-5022	16	4	thermographic	thermographic	ADJ
fis-5022	16	5	ndt	ndt	PROPN
fis-5022	16	6	of	of	ADP
fis-5022	16	7	materials	material	NOUN
fis-5022	16	8	,	,	PUNCT
fis-5022	16	9	the	the	DET
fis-5022	16	10	principles	principle	NOUN
fis-5022	16	11	of	of	ADP
fis-5022	16	12	deep	deep	ADJ
fis-5022	16	13	learning	learning	NOUN
fis-5022	16	14	can	can	AUX
fis-5022	16	15	be	be	AUX
fis-5022	16	16	helpful	helpful	ADJ
fis-5022	16	17	in	in	ADP
fis-5022	16	18	solving	solve	VERB
fis-5022	16	19	inverse	inverse	ADJ
fis-5022	16	20	heat	heat	NOUN
fis-5022	16	21	conduction	conduction	NOUN
fis-5022	16	22	problems	problem	NOUN
fis-5022	16	23	,	,	PUNCT
fis-5022	16	24	i.e.	i.e.	X
fis-5022	16	25	performing	perform	VERB
fis-5022	16	26	defect	defect	NOUN
fis-5022	16	27	characterization	characterization	NOUN
fis-5022	16	28	of	of	ADP
fis-5022	16	29	hidden	hide	VERB
fis-5022	16	30	defects	defect	NOUN
fis-5022	16	31	that	that	PRON
fis-5022	16	32	is	be	AUX
fis-5022	16	33	a	a	DET
fis-5022	16	34	permanent	permanent	ADJ
fis-5022	16	35	challenge	challenge	NOUN
fis-5022	16	36	in	in	ADP
fis-5022	16	37	thermal	thermal	ADJ
fis-5022	16	38	ndt	ndt	PROPN
fis-5022	16	39	(	(	PUNCT
fis-5022	16	40	tndt	tndt	ADV
fis-5022	16	41	)	)	PUNCT
fis-5022	16	42	.	.	PUNCT
fis-5022	17	1	for	for	ADP
fis-5022	17	2	example	example	NOUN
fis-5022	17	3	,	,	PUNCT
fis-5022	17	4	yousefi	yousefi	PROPN
fis-5022	17	5	et	et	PROPN
fis-5022	17	6	al	al	PROPN
fis-5022	17	7	.	.	PROPN
fis-5022	17	8	showed	show	VERB
fis-5022	17	9	that	that	SCONJ
fis-5022	17	10	cnns	cnn	NOUN
fis-5022	17	11	can	can	AUX
fis-5022	17	12	serve	serve	VERB
fis-5022	17	13	as	as	ADP
fis-5022	17	14	an	an	DET
fis-5022	17	15	unsupervised	unsupervised	ADJ
fis-5022	17	16	extractor	extractor	NOUN
fis-5022	17	17	of	of	ADP
fis-5022	17	18	defect	defect	ADJ
fis-5022	17	19	features	feature	NOUN
fis-5022	17	20	in	in	ADP
fis-5022	17	21	ir	ir	PROPN
fis-5022	17	22	ndt	ndt	PROPN
fis-5022	18	1	[	[	X
fis-5022	18	2	15	15	NUM
fis-5022	18	3	]	]	PUNCT
fis-5022	18	4	.	.	PUNCT
fis-5022	19	1	haiyi	haiyi	PROPN
fis-5022	19	2	wu	wu	PROPN
fis-5022	19	3	et	et	PROPN
fis-5022	19	4	al	al	PROPN
fis-5022	19	5	.	.	PROPN
fis-5022	19	6	proposed	propose	VERB
fis-5022	19	7	the	the	DET
fis-5022	19	8	deep	deep	ADJ
fis-5022	19	9	learning	learning	NOUN
fis-5022	19	10	model	model	NOUN
fis-5022	19	11	based	base	VERB
fis-5022	19	12	on	on	ADP
fis-5022	19	13	cnns	cnn	NOUN
fis-5022	19	14	with	with	ADP
fis-5022	19	15	a	a	DET
fis-5022	19	16	u	u	NOUN
fis-5022	19	17	-	-	NOUN
fis-5022	19	18	shape	shape	NOUN
fis-5022	19	19	architecture	architecture	NOUN
fis-5022	19	20	to	to	PART
fis-5022	19	21	predict	predict	VERB
fis-5022	19	22	the	the	DET
fis-5022	19	23	heterogeneous	heterogeneous	ADJ
fis-5022	19	24	distribution	distribution	NOUN
fis-5022	19	25	of	of	ADP
fis-5022	19	26	circle	circle	NOUN
fis-5022	19	27	-	-	PUNCT
fis-5022	19	28	shaped	shape	VERB
fis-5022	19	29	fillers	filler	NOUN
fis-5022	19	30	in	in	ADP
fis-5022	19	31	composites	composite	NOUN
fis-5022	19	32	[	[	X
fis-5022	19	33	16	16	NUM
fis-5022	19	34	]	]	PUNCT
fis-5022	19	35	.	.	PUNCT
fis-5022	20	1	in	in	ADP
fis-5022	20	2	pulsed	pulsed	NOUN
fis-5022	20	3	tndt	tndt	ADP
fis-5022	20	4	,	,	PUNCT
fis-5022	20	5	a	a	DET
fis-5022	20	6	couple	couple	NOUN
fis-5022	20	7	of	of	ADP
fis-5022	20	8	different	different	ADJ
fis-5022	20	9	cnns	cnn	NOUN
fis-5022	20	10	were	be	AUX
fis-5022	20	11	investigated	investigate	VERB
fis-5022	20	12	by	by	ADP
fis-5022	20	13	qiang	qiang	PROPN
fis-5022	20	14	fang	fang	PROPN
fis-5022	20	15	et	et	PROPN
fis-5022	20	16	al	al	PROPN
fis-5022	20	17	.	.	PROPN
fis-5022	21	1	with	with	ADP
fis-5022	21	2	experiments	experiment	NOUN
fis-5022	21	3	being	be	AUX
fis-5022	21	4	fulfilled	fulfil	VERB
fis-5022	21	5	on	on	ADP
fis-5022	21	6	a	a	DET
fis-5022	21	7	series	series	NOUN
fis-5022	21	8	of	of	ADP
fis-5022	21	9	academic	academic	ADJ
fis-5022	21	10	test	test	NOUN
fis-5022	21	11	samples	sample	NOUN
fis-5022	21	12	with	with	ADP
fis-5022	21	13	bottom	bottom	ADJ
fis-5022	21	14	hole	hole	NOUN
fis-5022	21	15	defects	defect	NOUN
fis-5022	21	16	and	and	CCONJ
fis-5022	21	17	teflon	teflon	NOUN
fis-5022	21	18	inserts	insert	NOUN
fis-5022	21	19	[	[	X
fis-5022	21	20	17	17	NUM
fis-5022	21	21	]	]	PUNCT
fis-5022	21	22	.	.	PUNCT
fis-5022	22	1	the	the	DET
fis-5022	22	2	same	same	ADJ
fis-5022	22	3	team	team	NOUN
fis-5022	22	4	used	use	VERB
fis-5022	22	5	a	a	DET
fis-5022	22	6	finite	finite	ADJ
fis-5022	22	7	-	-	ADJ
fis-5022	22	8	element	element	ADJ
fis-5022	22	9	model	model	NOUN
fis-5022	22	10	to	to	PART
fis-5022	22	11	calculate	calculate	VERB
fis-5022	22	12	defect	defect	NOUN
fis-5022	22	13	responses	response	NOUN
fis-5022	22	14	in	in	ADP
fis-5022	22	15	carbon	carbon	NOUN
fis-5022	22	16	fiber	fiber	NOUN
fis-5022	22	17	reinforced	reinforce	VERB
fis-5022	22	18	polymer	polymer	NOUN
fis-5022	22	19	(	(	PUNCT
fis-5022	22	20	cfrp	cfrp	NOUN
fis-5022	22	21	)	)	PUNCT
fis-5022	22	22	to	to	PART
fis-5022	22	23	be	be	AUX
fis-5022	22	24	further	far	ADV
fis-5022	22	25	used	use	VERB
fis-5022	22	26	for	for	ADP
fis-5022	22	27	determining	determine	VERB
fis-5022	22	28	defect	defect	ADJ
fis-5022	22	29	depth	depth	NOUN
fis-5022	22	30	by	by	ADP
fis-5022	22	31	means	mean	NOUN
fis-5022	22	32	of	of	ADP
fis-5022	22	33	a	a	DET
fis-5022	22	34	new	new	ADJ
fis-5022	22	35	technique	technique	NOUN
fis-5022	22	36	,	,	PUNCT
fis-5022	22	37	which	which	PRON
fis-5022	22	38	employed	employ	VERB
fis-5022	22	39	the	the	DET
fis-5022	22	40	so	so	ADV
fis-5022	22	41	-	-	PUNCT
fis-5022	22	42	called	call	VERB
fis-5022	22	43	gated	gate	VERB
fis-5022	22	44	recurrent	recurrent	ADJ
fis-5022	22	45	units	unit	NOUN
fis-5022	22	46	[	[	X
fis-5022	22	47	18	18	NUM
fis-5022	22	48	]	]	PUNCT
fis-5022	22	49	.	.	PUNCT
fis-5022	23	1	to	to	PART
fis-5022	23	2	summarize	summarize	VERB
fis-5022	23	3	the	the	DET
fis-5022	23	4	above	above	ADV
fis-5022	23	5	-	-	PUNCT
fis-5022	23	6	mentioned	mention	VERB
fis-5022	23	7	,	,	PUNCT
fis-5022	23	8	one	one	PRON
fis-5022	23	9	may	may	AUX
fis-5022	23	10	state	state	VERB
fis-5022	23	11	that	that	DET
fis-5022	23	12	machine	machine	NOUN
fis-5022	23	13	learning	learn	VERB
fis-5022	23	14	algorithms	algorithm	NOUN
fis-5022	23	15	,	,	PUNCT
fis-5022	23	16	being	be	AUX
fis-5022	23	17	trained	train	VERB
fis-5022	23	18	on	on	ADP
fis-5022	23	19	appropriate	appropriate	ADJ
fis-5022	23	20	datasets	dataset	NOUN
fis-5022	23	21	,	,	PUNCT
fis-5022	23	22	can	can	AUX
fis-5022	23	23	autonomously	autonomously	ADV
fis-5022	23	24	analyze	analyze	VERB
fis-5022	23	25	ir	ir	PROPN
fis-5022	23	26	thermographic	thermographic	ADJ
fis-5022	23	27	data	datum	NOUN
fis-5022	23	28	,	,	PUNCT
fis-5022	23	29	enhance	enhance	VERB
fis-5022	23	30	defect	defect	NOUN
fis-5022	23	31	detection	detection	NOUN
fis-5022	23	32	and	and	CCONJ
fis-5022	23	33	make	make	VERB
fis-5022	23	34	trust	trust	NOUN
fis-5022	23	35	-	-	PUNCT
fis-5022	23	36	worthy	worthy	ADJ
fis-5022	23	37	decisions	decision	NOUN
fis-5022	23	38	.	.	PUNCT
fis-5022	24	1	however	however	ADV
fis-5022	24	2	,	,	PUNCT
fis-5022	24	3	a	a	DET
fis-5022	24	4	problem	problem	NOUN
fis-5022	24	5	of	of	ADP
fis-5022	24	6	generalizability	generalizability	NOUN
fis-5022	24	7	remains	remain	VERB
fis-5022	24	8	one	one	NUM
fis-5022	24	9	of	of	ADP
fis-5022	24	10	the	the	DET
fis-5022	24	11	most	most	ADV
fis-5022	24	12	challenging	challenging	ADJ
fis-5022	24	13	while	while	SCONJ
fis-5022	24	14	using	use	VERB
fis-5022	24	15	artificial	artificial	ADJ
fis-5022	24	16	intelligence	intelligence	NOUN
fis-5022	24	17	approaches	approach	NOUN
fis-5022	24	18	.	.	PUNCT
fis-5022	25	1	the	the	DET
fis-5022	25	2	respective	respective	ADJ
fis-5022	25	3	neural	neural	ADJ
fis-5022	25	4	network	network	NOUN
fis-5022	25	5	models	model	NOUN
fis-5022	25	6	often	often	ADV
fis-5022	25	7	prove	prove	VERB
fis-5022	25	8	their	their	PRON
fis-5022	25	9	efficiency	efficiency	NOUN
fis-5022	25	10	only	only	ADV
fis-5022	25	11	under	under	ADP
fis-5022	25	12	specific	specific	ADJ
fis-5022	25	13	conditions	condition	NOUN
fis-5022	25	14	,	,	PUNCT
fis-5022	25	15	i.e.	i.e.	X
fis-5022	25	16	if	if	SCONJ
fis-5022	25	17	they	they	PRON
fis-5022	25	18	are	be	AUX
fis-5022	25	19	trained	train	VERB
fis-5022	25	20	on	on	ADP
fis-5022	25	21	particular	particular	ADJ
fis-5022	25	22	training	training	NOUN
fis-5022	25	23	setups	setup	NOUN
fis-5022	25	24	and	and	CCONJ
fis-5022	25	25	sample	sample	NOUN
fis-5022	25	26	datasets	dataset	NOUN
fis-5022	25	27	[	[	X
fis-5022	25	28	19	19	NUM
fis-5022	25	29	,	,	PUNCT
fis-5022	25	30	20	20	NUM
fis-5022	25	31	]	]	PUNCT
fis-5022	25	32	.	.	PUNCT
fis-5022	26	1	this	this	DET
fis-5022	26	2	study	study	NOUN
fis-5022	26	3	was	be	AUX
fis-5022	26	4	motivated	motivate	VERB
fis-5022	26	5	by	by	ADP
fis-5022	26	6	the	the	DET
fis-5022	26	7	fact	fact	NOUN
fis-5022	26	8	that	that	SCONJ
fis-5022	26	9	the	the	DET
fis-5022	26	10	machine	machine	NOUN
fis-5022	26	11	learning	learning	NOUN
fis-5022	26	12	models	model	NOUN
fis-5022	26	13	trained	train	VERB
fis-5022	26	14	on	on	ADP
fis-5022	26	15	datasets	dataset	NOUN
fis-5022	26	16	with	with	ADP
fis-5022	26	17	fixed	fix	VERB
fis-5022	26	18	parameters	parameter	NOUN
fis-5022	26	19	yield	yield	VERB
fis-5022	26	20	limited	limited	ADJ
fis-5022	26	21	defect	defect	NOUN
fis-5022	26	22	detection	detection	NOUN
fis-5022	26	23	and	and	CCONJ
fis-5022	26	24	characterization	characterization	NOUN
fis-5022	26	25	capabilities	capability	NOUN
fis-5022	26	26	.	.	PUNCT
fis-5022	27	1	the	the	DET
fis-5022	27	2	results	result	NOUN
fis-5022	27	3	obtained	obtain	VERB
fis-5022	27	4	provide	provide	VERB
fis-5022	27	5	a	a	DET
fis-5022	27	6	useful	useful	ADJ
fis-5022	27	7	scientific	scientific	ADJ
fis-5022	27	8	contribution	contribution	NOUN
fis-5022	27	9	to	to	ADP
fis-5022	27	10	the	the	DET
fis-5022	27	11	field	field	NOUN
fis-5022	27	12	of	of	ADP
fis-5022	27	13	defect	defect	ADJ
fis-5022	27	14	detection	detection	NOUN
fis-5022	27	15	using	use	VERB
fis-5022	27	16	ir	ir	PROPN
fis-5022	27	17	data	datum	NOUN
fis-5022	27	18	and	and	CCONJ
fis-5022	27	19	machine	machine	NOUN
fis-5022	27	20	learning	learning	NOUN
fis-5022	27	21	.	.	PUNCT
fis-5022	28	1	first	first	ADV
fis-5022	28	2	,	,	PUNCT
fis-5022	28	3	it	it	PRON
fis-5022	28	4	presents	present	VERB
fis-5022	28	5	a	a	DET
fis-5022	28	6	comprehensive	comprehensive	ADJ
fis-5022	28	7	evaluation	evaluation	NOUN
fis-5022	28	8	of	of	ADP
fis-5022	28	9	the	the	DET
fis-5022	28	10	generalizability	generalizability	NOUN
fis-5022	28	11	of	of	ADP
fis-5022	28	12	machine	machine	NOUN
fis-5022	28	13	learning	learning	NOUN
fis-5022	28	14	models	model	NOUN
fis-5022	28	15	trained	train	VERB
fis-5022	28	16	on	on	ADP
fis-5022	28	17	datasets	dataset	NOUN
fis-5022	28	18	with	with	ADP
fis-5022	28	19	varying	vary	VERB
fis-5022	28	20	degrees	degree	NOUN
fis-5022	28	21	of	of	ADP
fis-5022	28	22	parameter	parameter	NOUN
fis-5022	28	23	variability	variability	NOUN
fis-5022	28	24	.	.	PUNCT
fis-5022	29	1	by	by	ADP
fis-5022	29	2	systematically	systematically	ADV
fis-5022	29	3	manipulating	manipulate	VERB
fis-5022	29	4	numerical	numerical	ADJ
fis-5022	29	5	model	model	NOUN
fis-5022	29	6	parameters	parameter	NOUN
fis-5022	29	7	,	,	PUNCT
fis-5022	29	8	such	such	ADJ
fis-5022	29	9	as	as	ADP
fis-5022	29	10	defect	defect	NOUN
fis-5022	29	11	depth	depth	NOUN
fis-5022	29	12	,	,	PUNCT
fis-5022	29	13	material	material	NOUN
fis-5022	29	14	thermal	thermal	ADJ
fis-5022	29	15	conductivity	conductivity	NOUN
fis-5022	29	16	and	and	CCONJ
fis-5022	29	17	sample	sample	NOUN
fis-5022	29	18	thickness	thickness	NOUN
fis-5022	29	19	,	,	PUNCT
fis-5022	29	20	this	this	DET
fis-5022	29	21	study	study	NOUN
fis-5022	29	22	provides	provide	VERB
fis-5022	29	23	a	a	DET
fis-5022	29	24	detailed	detailed	ADJ
fis-5022	29	25	understanding	understanding	NOUN
fis-5022	29	26	of	of	ADP
fis-5022	29	27	how	how	SCONJ
fis-5022	29	28	these	these	DET
fis-5022	29	29	factors	factor	NOUN
fis-5022	29	30	influence	influence	VERB
fis-5022	29	31	model	model	NOUN
fis-5022	29	32	performance	performance	NOUN
fis-5022	29	33	.	.	PUNCT
fis-5022	30	1	this	this	DET
fis-5022	30	2	approach	approach	NOUN
fis-5022	30	3	offers	offer	VERB
fis-5022	30	4	valuable	valuable	ADJ
fis-5022	30	5	insights	insight	NOUN
fis-5022	30	6	into	into	ADP
fis-5022	30	7	the	the	DET
fis-5022	30	8	optimal	optimal	ADJ
fis-5022	30	9	design	design	NOUN
fis-5022	30	10	of	of	ADP
fis-5022	30	11	training	training	NOUN
fis-5022	30	12	datasets	dataset	NOUN
fis-5022	30	13	,	,	PUNCT
fis-5022	30	14	highlighting	highlight	VERB
fis-5022	30	15	the	the	DET
fis-5022	30	16	need	need	NOUN
fis-5022	30	17	for	for	ADP
fis-5022	30	18	a	a	DET
fis-5022	30	19	balanced	balanced	ADJ
fis-5022	30	20	data	datum	NOUN
fis-5022	30	21	variability	variability	NOUN
fis-5022	30	22	to	to	PART
fis-5022	30	23	enhance	enhance	VERB
fis-5022	30	24	model	model	NOUN
fis-5022	30	25	robustness	robustness	NOUN
fis-5022	30	26	without	without	ADP
fis-5022	30	27	compromising	compromise	VERB
fis-5022	30	28	accuracy	accuracy	NOUN
fis-5022	30	29	.	.	PUNCT
fis-5022	31	1	secondly	secondly	ADV
fis-5022	31	2	,	,	PUNCT
fis-5022	31	3	the	the	DET
fis-5022	31	4	introduction	introduction	NOUN
fis-5022	31	5	of	of	ADP
fis-5022	31	6	multiple	multiple	ADJ
fis-5022	31	7	test	test	NOUN
fis-5022	31	8	datasets	dataset	NOUN
fis-5022	31	9	,	,	PUNCT
fis-5022	31	10	each	each	PRON
fis-5022	31	11	with	with	ADP
fis-5022	31	12	distinct	distinct	ADJ
fis-5022	31	13	unseen	unseen	ADJ
fis-5022	31	14	parameter	parameter	NOUN
fis-5022	31	15	variations	variation	NOUN
fis-5022	31	16	,	,	PUNCT
fis-5022	31	17	represents	represent	VERB
fis-5022	31	18	a	a	DET
fis-5022	31	19	novel	novel	ADJ
fis-5022	31	20	methodology	methodology	NOUN
fis-5022	31	21	for	for	ADP
fis-5022	31	22	assessing	assess	VERB
fis-5022	31	23	model	model	NOUN
fis-5022	31	24	generalizability	generalizability	NOUN
fis-5022	31	25	.	.	PUNCT
fis-5022	32	1	this	this	DET
fis-5022	32	2	rigorous	rigorous	ADJ
fis-5022	32	3	testing	testing	NOUN
fis-5022	32	4	framework	framework	NOUN
fis-5022	32	5	goes	go	VERB
fis-5022	32	6	beyond	beyond	ADP
fis-5022	32	7	conventional	conventional	ADJ
fis-5022	32	8	validation	validation	NOUN
fis-5022	32	9	approaches	approach	NOUN
fis-5022	32	10	by	by	ADP
fis-5022	32	11	simulating	simulate	VERB
fis-5022	32	12	real	real	ADJ
fis-5022	32	13	-	-	PUNCT
fis-5022	32	14	world	world	NOUN
fis-5022	32	15	scenarios	scenario	NOUN
fis-5022	32	16	where	where	SCONJ
fis-5022	32	17	defects	defect	NOUN
fis-5022	32	18	and	and	CCONJ
fis-5022	32	19	material	material	NOUN
fis-5022	32	20	properties	property	NOUN
fis-5022	32	21	may	may	AUX
fis-5022	32	22	differ	differ	VERB
fis-5022	32	23	significantly	significantly	ADV
fis-5022	32	24	from	from	ADP
fis-5022	32	25	those	those	PRON
fis-5022	32	26	used	use	VERB
fis-5022	32	27	in	in	ADP
fis-5022	32	28	training	training	NOUN
fis-5022	32	29	.	.	PUNCT
fis-5022	33	1	this	this	DET
fis-5022	33	2	aspect	aspect	NOUN
fis-5022	33	3	of	of	ADP
fis-5022	33	4	the	the	DET
fis-5022	33	5	study	study	NOUN
fis-5022	33	6	demonstrates	demonstrate	VERB
fis-5022	33	7	the	the	DET
fis-5022	33	8	practical	practical	ADJ
fis-5022	33	9	applicability	applicability	NOUN
fis-5022	33	10	of	of	ADP
fis-5022	33	11	the	the	DET
fis-5022	33	12	proposed	propose	VERB
fis-5022	33	13	machine	machine	NOUN
fis-5022	33	14	learning	learning	NOUN
fis-5022	33	15	models	model	NOUN
fis-5022	33	16	,	,	PUNCT
fis-5022	33	17	showcasing	showcase	VERB
fis-5022	33	18	their	their	PRON
fis-5022	33	19	potential	potential	NOUN
fis-5022	33	20	to	to	PART
fis-5022	33	21	reliably	reliably	ADV
fis-5022	33	22	detect	detect	VERB
fis-5022	33	23	defects	defect	NOUN
fis-5022	33	24	in	in	ADP
fis-5022	33	25	diverse	diverse	ADJ
fis-5022	33	26	and	and	CCONJ
fis-5022	33	27	unpredictable	unpredictable	ADJ
fis-5022	33	28	environments	environment	NOUN
fis-5022	33	29	.	.	PUNCT
fis-5022	34	1	the	the	DET
fis-5022	34	2	outline	outline	NOUN
fis-5022	34	3	of	of	ADP
fis-5022	34	4	the	the	DET
fis-5022	34	5	paper	paper	NOUN
fis-5022	34	6	is	be	AUX
fis-5022	34	7	as	as	SCONJ
fis-5022	34	8	follows	follow	VERB
fis-5022	34	9	.	.	PUNCT
fis-5022	35	1	first	first	ADV
fis-5022	35	2	,	,	PUNCT
fis-5022	35	3	the	the	DET
fis-5022	35	4	theory	theory	NOUN
fis-5022	35	5	of	of	ADP
fis-5022	35	6	ft	ft	NOUN
fis-5022	35	7	and	and	CCONJ
fis-5022	35	8	basic	basic	ADJ
fis-5022	35	9	processing	processing	NOUN
fis-5022	35	10	approaches	approach	NOUN
fis-5022	35	11	will	will	AUX
fis-5022	35	12	shortly	shortly	ADV
fis-5022	35	13	be	be	AUX
fis-5022	35	14	introduced	introduce	VERB
fis-5022	35	15	.	.	PUNCT
fis-5022	36	1	next	next	ADV
fis-5022	36	2	,	,	PUNCT
fis-5022	36	3	a	a	DET
fis-5022	36	4	couple	couple	NOUN
fis-5022	36	5	of	of	ADP
fis-5022	36	6	training	training	NOUN
fis-5022	36	7	datasets	dataset	NOUN
fis-5022	36	8	used	use	VERB
fis-5022	36	9	for	for	ADP
fis-5022	36	10	machine	machine	NOUN
fis-5022	36	11	learning	learning	NOUN
fis-5022	36	12	will	will	AUX
fis-5022	36	13	be	be	AUX
fis-5022	36	14	developed	develop	VERB
fis-5022	36	15	by	by	ADP
fis-5022	36	16	means	mean	NOUN
fis-5022	36	17	of	of	ADP
fis-5022	36	18	advanced	advanced	ADJ
fis-5022	36	19	3d	3d	PROPN
fis-5022	36	20	numerical	numerical	ADJ
fis-5022	36	21	modeling	modeling	NOUN
fis-5022	36	22	.	.	PUNCT
fis-5022	37	1	then	then	ADV
fis-5022	37	2	,	,	PUNCT
fis-5022	37	3	these	these	DET
fis-5022	37	4	datasets	dataset	NOUN
fis-5022	37	5	will	will	AUX
fis-5022	37	6	be	be	AUX
fis-5022	37	7	used	use	VERB
fis-5022	37	8	for	for	ADP
fis-5022	37	9	evaluating	evaluate	VERB
fis-5022	37	10	efficiency	efficiency	NOUN
fis-5022	37	11	of	of	ADP
fis-5022	37	12	a	a	DET
fis-5022	37	13	particular	particular	ADJ
fis-5022	37	14	gaussian	gaussian	ADJ
fis-5022	37	15	support	support	NOUN
fis-5022	37	16	vector	vector	NOUN
fis-5022	37	17	machine	machine	NOUN
fis-5022	37	18	(	(	PUNCT
fis-5022	37	19	svm	svm	PROPN
fis-5022	37	20	)	)	PUNCT
fis-5022	37	21	model	model	NOUN
fis-5022	37	22	in	in	ADP
fis-5022	37	23	characterizing	characterize	VERB
fis-5022	37	24	defect	defect	NOUN
fis-5022	37	25	parameters	parameter	NOUN
fis-5022	37	26	.	.	PUNCT
fis-5022	38	1	the	the	DET
fis-5022	38	2	robustness	robustness	NOUN
fis-5022	38	3	of	of	ADP
fis-5022	38	4	the	the	DET
fis-5022	38	5	suggested	suggested	ADJ
fis-5022	38	6	learning	learn	VERB
fis-5022	38	7	machine	machine	NOUN
fis-5022	38	8	model	model	NOUN
fis-5022	38	9	toward	toward	ADP
fis-5022	38	10	noise	noise	NOUN
fis-5022	38	11	of	of	ADP
fis-5022	38	12	an	an	DET
fis-5022	38	13	additive	additive	ADJ
fis-5022	38	14	and	and	CCONJ
fis-5022	38	15	multiplicative	multiplicative	ADJ
fis-5022	38	16	nature	nature	NOUN
fis-5022	38	17	will	will	AUX
fis-5022	38	18	be	be	AUX
fis-5022	38	19	explored	explore	VERB
fis-5022	38	20	.	.	PUNCT
fis-5022	39	1	finally	finally	ADV
fis-5022	39	2	,	,	PUNCT
fis-5022	39	3	some	some	DET
fis-5022	39	4	data	datum	NOUN
fis-5022	39	5	processing	processing	NOUN
fis-5022	39	6	algorithms	algorithm	NOUN
fis-5022	39	7	will	will	AUX
fis-5022	39	8	be	be	AUX
fis-5022	39	9	analyzed	analyze	VERB
fis-5022	39	10	to	to	PART
fis-5022	39	11	demonstrate	demonstrate	VERB
fis-5022	39	12	that	that	SCONJ
fis-5022	39	13	the	the	DET
fis-5022	39	14	use	use	NOUN
fis-5022	39	15	of	of	ADP
fis-5022	39	16	thermographic	thermographic	ADJ
fis-5022	39	17	signal	signal	NOUN
fis-5022	39	18	reconstruction	reconstruction	NOUN
fis-5022	39	19	(	(	PUNCT
fis-5022	39	20	tsr	tsr	PROPN
fis-5022	39	21	)	)	PUNCT
fis-5022	39	22	and	and	CCONJ
fis-5022	39	23	temperature	temperature	NOUN
fis-5022	39	24	contrast	contrast	NOUN
fis-5022	39	25	significantly	significantly	ADV
fis-5022	39	26	improve	improve	VERB
fis-5022	39	27	the	the	DET
fis-5022	39	28	model	model	NOUN
fis-5022	39	29	efficiency	efficiency	NOUN
fis-5022	39	30	.	.	PUNCT
fis-5022	40	1	theory	theory	NOUN
fis-5022	40	2	t	t	PROPN
fis-5022	40	3	is	be	AUX
fis-5022	40	4	based	base	VERB
fis-5022	40	5	on	on	ADP
fis-5022	40	6	applying	apply	VERB
fis-5022	40	7	a	a	DET
fis-5022	40	8	brief	brief	ADJ
fis-5022	40	9	heat	heat	NOUN
fis-5022	40	10	pulse	pulse	NOUN
fis-5022	40	11	onto	onto	ADP
fis-5022	40	12	a	a	DET
fis-5022	40	13	material	material	NOUN
fis-5022	40	14	under	under	ADP
fis-5022	40	15	examination	examination	NOUN
fis-5022	40	16	followed	follow	VERB
fis-5022	40	17	by	by	ADP
fis-5022	40	18	measurement	measurement	NOUN
fis-5022	40	19	of	of	ADP
fis-5022	40	20	material	material	ADJ
fis-5022	40	21	temperature	temperature	NOUN
fis-5022	40	22	response	response	NOUN
fis-5022	40	23	by	by	ADP
fis-5022	40	24	means	mean	NOUN
fis-5022	40	25	of	of	ADP
fis-5022	40	26	an	an	DET
fis-5022	40	27	ir	ir	NOUN
fis-5022	40	28	camera	camera	NOUN
fis-5022	41	1	[	[	X
fis-5022	41	2	21	21	NUM
fis-5022	41	3	]	]	PUNCT
fis-5022	41	4	.	.	PUNCT
fis-5022	42	1	typically	typically	ADV
fis-5022	42	2	,	,	PUNCT
fis-5022	42	3	such	such	ADJ
fis-5022	42	4	heat	heat	NOUN
fis-5022	42	5	pulses	pulse	NOUN
fis-5022	42	6	last	last	ADJ
fis-5022	42	7	only	only	ADV
fis-5022	42	8	few	few	ADJ
fis-5022	42	9	milliseconds	millisecond	NOUN
fis-5022	42	10	,	,	PUNCT
fis-5022	42	11	and	and	CCONJ
fis-5022	42	12	the	the	DET
fis-5022	42	13	analysis	analysis	NOUN
fis-5022	42	14	focuses	focus	VERB
fis-5022	42	15	solely	solely	ADV
fis-5022	42	16	on	on	ADP
fis-5022	42	17	the	the	DET
fis-5022	42	18	material	material	ADJ
fis-5022	42	19	thermal	thermal	ADJ
fis-5022	42	20	response	response	NOUN
fis-5022	42	21	following	follow	VERB
fis-5022	42	22	the	the	DET
fis-5022	42	23	pulse	pulse	NOUN
fis-5022	42	24	,	,	PUNCT
fis-5022	42	25	i.e.	i.e.	X
fis-5022	42	26	at	at	ADP
fis-5022	42	27	the	the	DET
fis-5022	42	28	cooling	cool	VERB
fis-5022	42	29	stage	stage	NOUN
fis-5022	42	30	of	of	ADP
fis-5022	42	31	the	the	DET
fis-5022	42	32	thermal	thermal	ADJ
fis-5022	42	33	process	process	NOUN
fis-5022	42	34	.	.	PUNCT
fis-5022	43	1	the	the	DET
fis-5022	43	2	time	time	NOUN
fis-5022	43	3	-	-	PUNCT
fis-5022	43	4	temperature	temperature	NOUN
fis-5022	43	5	responses	response	NOUN
fis-5022	43	6	at	at	ADP
fis-5022	43	7	sample	sample	NOUN
fis-5022	43	8	surface	surface	NOUN
fis-5022	43	9	points	point	NOUN
fis-5022	43	10	are	be	AUX
fis-5022	43	11	then	then	ADV
fis-5022	43	12	subjected	subject	VERB
fis-5022	43	13	to	to	ADP
fis-5022	43	14	processing	process	VERB
fis-5022	43	15	in	in	ADP
fis-5022	43	16	order	order	NOUN
fis-5022	43	17	to	to	PART
fis-5022	43	18	extract	extract	VERB
fis-5022	43	19	meaningful	meaningful	ADJ
fis-5022	43	20	information	information	NOUN
fis-5022	43	21	on	on	ADP
fis-5022	43	22	subsurface	subsurface	NOUN
fis-5022	43	23	defects	defect	NOUN
fis-5022	43	24	.	.	PUNCT
fis-5022	44	1	f	f	PROPN
fis-5022	44	2	a.	a.	NOUN
fis-5022	44	3	chulkov	chulkov	PROPN
fis-5022	44	4	et	et	PROPN
fis-5022	44	5	alii	alii	PROPN
fis-5022	44	6	,	,	PUNCT
fis-5022	44	7	frattura	frattura	PROPN
fis-5022	44	8	ed	ed	PROPN
fis-5022	44	9	integrità	integrità	PROPN
fis-5022	44	10	strutturale	strutturale	PROPN
fis-5022	44	11	,	,	PUNCT
fis-5022	44	12	70	70	NUM
fis-5022	44	13	(	(	PUNCT
fis-5022	44	14	2024	2024	NUM
fis-5022	44	15	)	)	PUNCT
fis-5022	44	16	177	177	NUM
fis-5022	44	17	-	-	SYM
fis-5022	44	18	191	191	NUM
fis-5022	44	19	;	;	PUNCT
fis-5022	44	20	doi	doi	NOUN
fis-5022	44	21	:	:	PUNCT
fis-5022	44	22	10.3221	10.3221	NUM
fis-5022	44	23	/	/	SYM
fis-5022	44	24	igf	igf	NOUN
fis-5022	44	25	-	-	ADJ
fis-5022	44	26	esis.70.10	esis.70.10	ADJ
fis-5022	44	27	179	179	NUM
fis-5022	44	28	classical	classical	ADJ
fis-5022	44	29	heat	heat	NOUN
fis-5022	44	30	conduction	conduction	NOUN
fis-5022	44	31	solutions	solution	NOUN
fis-5022	44	32	were	be	AUX
fis-5022	44	33	exhaustively	exhaustively	ADV
fis-5022	44	34	summarized	summarize	VERB
fis-5022	44	35	by	by	ADP
fis-5022	44	36	carslaw	carslaw	NOUN
fis-5022	44	37	and	and	CCONJ
fis-5022	44	38	jaeger	jaeger	NOUN
fis-5022	45	1	[	[	X
fis-5022	45	2	22	22	NUM
fis-5022	45	3	]	]	PUNCT
fis-5022	45	4	.	.	PUNCT
fis-5022	46	1	the	the	DET
fis-5022	46	2	solutions	solution	NOUN
fis-5022	46	3	for	for	ADP
fis-5022	46	4	pulsed	pulse	VERB
fis-5022	46	5	,	,	PUNCT
fis-5022	46	6	continuous	continuous	ADJ
fis-5022	46	7	or	or	CCONJ
fis-5022	46	8	harmonic	harmonic	ADJ
fis-5022	46	9	heating	heating	NOUN
fis-5022	46	10	of	of	ADP
fis-5022	46	11	an	an	DET
fis-5022	46	12	adiabatic	adiabatic	ADJ
fis-5022	46	13	semi	semi	ADJ
fis-5022	46	14	-	-	ADJ
fis-5022	46	15	infinite	infinite	ADJ
fis-5022	46	16	body	body	NOUN
fis-5022	46	17	and	and	CCONJ
fis-5022	46	18	slab	slab	NOUN
fis-5022	46	19	are	be	AUX
fis-5022	46	20	often	often	ADV
fis-5022	46	21	used	use	VERB
fis-5022	46	22	.	.	PUNCT
fis-5022	47	1	for	for	ADP
fis-5022	47	2	example	example	NOUN
fis-5022	47	3	,	,	PUNCT
fis-5022	47	4	the	the	DET
fis-5022	47	5	surface	surface	NOUN
fis-5022	47	6	response	response	NOUN
fis-5022	47	7	of	of	ADP
fis-5022	47	8	a	a	DET
fis-5022	47	9	semi	semi	ADJ
fis-5022	47	10	-	-	ADJ
fis-5022	47	11	infinite	infinite	ADJ
fis-5022	47	12	body	body	NOUN
fis-5022	47	13	toward	toward	ADP
fis-5022	47	14	dirac	dirac	NOUN
fis-5022	47	15	-	-	PUNCT
fis-5022	47	16	pulse	pulse	NOUN
fis-5022	47	17	heating	heating	NOUN
fis-5022	47	18	is	be	AUX
fis-5022	47	19	given	give	VERB
fis-5022	47	20	by	by	ADP
fis-5022	47	21	a	a	DET
fis-5022	47	22	simple	simple	ADJ
fis-5022	47	23	formula	formula	NOUN
fis-5022	47	24	[	[	X
fis-5022	47	25	23	23	NUM
fis-5022	47	26	]	]	SYM
fis-5022	47	27	:	:	PUNCT
fis-5022	47	28	(	(	PUNCT
fis-5022	47	29	)	)	PUNCT
fis-5022	47	30	1	1	NUM
fis-5022	47	31	1	1	NUM
fis-5022	47	32	o	o	NOUN
fis-5022	48	1	t	t	NOUN
fis-5022	48	2	t	t	PROPN
fis-5022	48	3	q	q	PROPN
fis-5022	48	4	ckt	ckt	PROPN
fis-5022	48	5	e	e	X
fis-5022	48	6	t	t	NUM
fis-5022	48	7			PROPN
fis-5022	48	8			NUM
fis-5022	48	9			NOUN
fis-5022	48	10	(	(	PUNCT
fis-5022	48	11	1	1	NUM
fis-5022	48	12	)	)	PUNCT
fis-5022	48	13	where	where	SCONJ
fis-5022	48	14	(	(	PUNCT
fis-5022	48	15	)	)	PUNCT
fis-5022	48	16	t	t	NOUN
fis-5022	48	17	t	t	PROPN
fis-5022	48	18	represents	represent	VERB
fis-5022	48	19	the	the	DET
fis-5022	48	20	temperature	temperature	NOUN
fis-5022	48	21	on	on	ADP
fis-5022	48	22	the	the	DET
fis-5022	48	23	sample	sample	NOUN
fis-5022	48	24	surface	surface	NOUN
fis-5022	48	25	at	at	ADP
fis-5022	48	26	the	the	DET
fis-5022	48	27	time	time	NOUN
fis-5022	48	28	t	t	NOUN
fis-5022	48	29	,	,	PUNCT
fis-5022	48	30	oq	oq	PROPN
fis-5022	48	31	stands	stand	VERB
fis-5022	48	32	for	for	ADP
fis-5022	48	33	the	the	DET
fis-5022	48	34	energy	energy	NOUN
fis-5022	48	35	of	of	ADP
fis-5022	48	36	the	the	DET
fis-5022	48	37	heat	heat	NOUN
fis-5022	48	38	pulse	pulse	NOUN
fis-5022	48	39	,	,	PUNCT
fis-5022	48	40	while	while	SCONJ
fis-5022	48	41	,	,	PUNCT
fis-5022	48	42	,	,	PUNCT
fis-5022	48	43	c	c	PROPN
fis-5022	48	44	k	k	PROPN
fis-5022	48	45	and	and	CCONJ
fis-5022	48	46	e	e	NOUN
fis-5022	48	47	denote	denote	VERB
fis-5022	48	48	the	the	DET
fis-5022	48	49	material	material	NOUN
fis-5022	48	50	density	density	NOUN
fis-5022	48	51	,	,	PUNCT
fis-5022	48	52	specific	specific	ADJ
fis-5022	48	53	heat	heat	NOUN
fis-5022	48	54	capacity	capacity	NOUN
fis-5022	48	55	,	,	PUNCT
fis-5022	48	56	thermal	thermal	ADJ
fis-5022	48	57	conductivity	conductivity	NOUN
fis-5022	48	58	and	and	CCONJ
fis-5022	48	59	thermal	thermal	ADJ
fis-5022	48	60	effusivity	effusivity	NOUN
fis-5022	48	61	(	(	PUNCT
fis-5022	48	62	e	e	X
fis-5022	48	63	ck	ck	PROPN
fis-5022	48	64	)	)	PUNCT
fis-5022	48	65	,	,	PUNCT
fis-5022	48	66	respectively	respectively	ADV
fis-5022	48	67	.	.	PUNCT
fis-5022	49	1	a	a	DET
fis-5022	49	2	region	region	NOUN
fis-5022	49	3	containing	contain	VERB
fis-5022	49	4	a	a	DET
fis-5022	49	5	delamination	delamination	NOUN
fis-5022	49	6	-	-	PUNCT
fis-5022	49	7	like	like	ADJ
fis-5022	49	8	defect	defect	NOUN
fis-5022	49	9	may	may	AUX
fis-5022	49	10	be	be	AUX
fis-5022	49	11	considered	consider	VERB
fis-5022	49	12	as	as	ADP
fis-5022	49	13	a	a	DET
fis-5022	49	14	slab	slab	NOUN
fis-5022	49	15	of	of	ADP
fis-5022	49	16	the	the	DET
fis-5022	49	17	thickness	thickness	NOUN
fis-5022	49	18	d	d	NOUN
fis-5022	49	19	.	.	PUNCT
fis-5022	50	1	the	the	DET
fis-5022	50	2	pulse	pulse	NOUN
fis-5022	50	3	response	response	NOUN
fis-5022	50	4	of	of	ADP
fis-5022	50	5	a	a	DET
fis-5022	50	6	slab	slab	NOUN
fis-5022	50	7	can	can	AUX
fis-5022	50	8	be	be	AUX
fis-5022	50	9	expressed	express	VERB
fis-5022	50	10	as	as	ADP
fis-5022	50	11	[	[	X
fis-5022	50	12	24	24	NUM
fis-5022	50	13	]	]	X
fis-5022	50	14	:	:	PUNCT
fis-5022	50	15	2	2	NUM
fis-5022	50	16	(	(	PUNCT
fis-5022	50	17	)	)	PUNCT
fis-5022	50	18	1	1	NUM
fis-5022	50	19	(	(	PUNCT
fis-5022	50	20	)	)	PUNCT
fis-5022	51	1	[	[	X
fis-5022	51	2	1	1	NUM
fis-5022	51	3	2	2	NUM
fis-5022	51	4	]	]	PUNCT
fis-5022	51	5	nd	nd	ADP
fis-5022	51	6	no	no	DET
fis-5022	51	7	t	t	NOUN
fis-5022	51	8	n	n	CCONJ
fis-5022	51	9	q	q	PROPN
fis-5022	51	10	t	t	PROPN
fis-5022	51	11	t	t	NOUN
fis-5022	51	12	r	r	NOUN
fis-5022	51	13	e	e	PROPN
fis-5022	51	14	e	e	PROPN
fis-5022	51	15	t	t	X
fis-5022	51	16			X
fis-5022	51	17			PROPN
fis-5022	51	18			VERB
fis-5022	51	19			VERB
fis-5022	51	20			NUM
fis-5022	51	21			PROPN
fis-5022	51	22			ADV
fis-5022	51	23			X
fis-5022	51	24	(	(	PUNCT
fis-5022	51	25	2	2	NUM
fis-5022	51	26	)	)	PUNCT
fis-5022	51	27	where	where	SCONJ
fis-5022	51	28			NOUN
fis-5022	51	29	is	be	AUX
fis-5022	51	30	the	the	DET
fis-5022	51	31	thermal	thermal	ADJ
fis-5022	51	32	diffusivity	diffusivity	NOUN
fis-5022	51	33	,	,	PUNCT
fis-5022	51	34	r	r	NOUN
fis-5022	51	35	is	be	AUX
fis-5022	51	36	the	the	DET
fis-5022	51	37	thermal	thermal	ADJ
fis-5022	51	38	reflection	reflection	NOUN
fis-5022	51	39	coefficient	coefficient	NOUN
fis-5022	51	40	describing	describe	VERB
fis-5022	51	41	the	the	DET
fis-5022	51	42	effusivity	effusivity	NOUN
fis-5022	51	43	contrast	contrast	NOUN
fis-5022	51	44	between	between	ADP
fis-5022	51	45	two	two	NUM
fis-5022	51	46	materials	material	NOUN
fis-5022	51	47	at	at	ADP
fis-5022	51	48	the	the	DET
fis-5022	51	49	defect	defect	NOUN
fis-5022	51	50	boundary	boundary	NOUN
fis-5022	51	51	,	,	PUNCT
fis-5022	51	52	and	and	CCONJ
fis-5022	51	53	n	n	PRON
fis-5022	51	54	is	be	AUX
fis-5022	51	55	a	a	DET
fis-5022	51	56	summation	summation	NOUN
fis-5022	51	57	index	index	NOUN
fis-5022	51	58	.	.	PUNCT
fis-5022	52	1	the	the	DET
fis-5022	52	2	temperature	temperature	NOUN
fis-5022	52	3	contrast	contrast	NOUN
fis-5022	52	4	between	between	ADP
fis-5022	52	5	defect	defect	NOUN
fis-5022	52	6	and	and	CCONJ
fis-5022	52	7	non	non	ADJ
fis-5022	52	8	-	-	ADJ
fis-5022	52	9	defect	defect	ADJ
fis-5022	52	10	areas	area	NOUN
fis-5022	52	11	can	can	AUX
fis-5022	52	12	be	be	AUX
fis-5022	52	13	obtained	obtain	VERB
fis-5022	52	14	by	by	ADP
fis-5022	52	15	subtracting	subtract	VERB
fis-5022	52	16	eq	eq	ADP
fis-5022	52	17	.	.	PUNCT
fis-5022	53	1	(	(	PUNCT
fis-5022	53	2	1	1	NUM
fis-5022	53	3	)	)	PUNCT
fis-5022	53	4	from	from	ADP
fis-5022	53	5	eq	eq	ADP
fis-5022	53	6	.	.	PUNCT
fis-5022	54	1	(	(	PUNCT
fis-5022	54	2	2	2	NUM
fis-5022	54	3	):	):	PUNCT
fis-5022	54	4	2	2	NUM
fis-5022	54	5	(	(	PUNCT
fis-5022	54	6	)	)	PUNCT
fis-5022	54	7	1	1	NUM
fis-5022	54	8	2	2	NUM
fis-5022	54	9	(	(	PUNCT
fis-5022	54	10	)	)	PUNCT
fis-5022	55	1	[	[	PUNCT
fis-5022	55	2	]	]	X
fis-5022	55	3	nd	nd	ADP
fis-5022	55	4	no	no	DET
fis-5022	55	5	t	t	NOUN
fis-5022	55	6	n	n	CCONJ
fis-5022	55	7	q	q	PROPN
fis-5022	55	8	t	t	PROPN
fis-5022	55	9	t	t	NOUN
fis-5022	55	10	r	r	NOUN
fis-5022	55	11	e	e	PROPN
fis-5022	55	12	e	e	PROPN
fis-5022	55	13	t	t	X
fis-5022	55	14			X
fis-5022	55	15			PROPN
fis-5022	55	16			VERB
fis-5022	55	17			NOUN
fis-5022	55	18			NUM
fis-5022	55	19			NOUN
fis-5022	55	20			NUM
fis-5022	55	21			X
fis-5022	55	22	(	(	PUNCT
fis-5022	55	23	3	3	X
fis-5022	55	24	)	)	PUNCT
fis-5022	55	25	nonetheless	nonetheless	ADV
fis-5022	55	26	,	,	PUNCT
fis-5022	55	27	practical	practical	ADJ
fis-5022	55	28	procedures	procedure	NOUN
fis-5022	55	29	of	of	ADP
fis-5022	55	30	tndt	tndt	NOUN
fis-5022	55	31	are	be	AUX
fis-5022	55	32	often	often	ADV
fis-5022	55	33	aggravated	aggravate	VERB
fis-5022	55	34	by	by	ADP
fis-5022	55	35	significant	significant	ADJ
fis-5022	55	36	noise	noise	NOUN
fis-5022	55	37	/	/	SYM
fis-5022	55	38	clutter	clutter	NOUN
fis-5022	55	39	,	,	PUNCT
fis-5022	55	40	non	non	ADJ
fis-5022	55	41	-	-	ADJ
fis-5022	55	42	uniform	uniform	ADJ
fis-5022	55	43	heating	heating	NOUN
fis-5022	55	44	,	,	PUNCT
fis-5022	55	45	variations	variation	NOUN
fis-5022	55	46	in	in	ADP
fis-5022	55	47	material	material	ADJ
fis-5022	55	48	thermal	thermal	ADJ
fis-5022	55	49	properties	property	NOUN
fis-5022	55	50	and	and	CCONJ
fis-5022	55	51	other	other	ADJ
fis-5022	55	52	complexities	complexity	NOUN
fis-5022	55	53	.	.	PUNCT
fis-5022	56	1	consequently	consequently	ADV
fis-5022	56	2	,	,	PUNCT
fis-5022	56	3	the	the	DET
fis-5022	56	4	applicability	applicability	NOUN
fis-5022	56	5	of	of	ADP
fis-5022	56	6	robust	robust	ADJ
fis-5022	56	7	but	but	CCONJ
fis-5022	56	8	simple	simple	ADJ
fis-5022	56	9	analytical	analytical	ADJ
fis-5022	56	10	methods	method	NOUN
fis-5022	56	11	may	may	AUX
fis-5022	56	12	be	be	AUX
fis-5022	56	13	limited	limit	VERB
fis-5022	56	14	in	in	ADP
fis-5022	56	15	practical	practical	ADJ
fis-5022	56	16	tndt	tndt	NOUN
fis-5022	56	17	problems	problem	NOUN
fis-5022	56	18	.	.	PUNCT
fis-5022	57	1	thermographic	thermographic	ADJ
fis-5022	57	2	data	datum	NOUN
fis-5022	57	3	processing	processing	NOUN
fis-5022	57	4	techniques	technique	NOUN
fis-5022	57	5	in	in	ADP
fis-5022	57	6	tndt	tndt	ADV
fis-5022	57	7	,	,	PUNCT
fis-5022	57	8	similarly	similarly	ADV
fis-5022	57	9	to	to	ADP
fis-5022	57	10	many	many	ADJ
fis-5022	57	11	other	other	ADJ
fis-5022	57	12	inspection	inspection	NOUN
fis-5022	57	13	techniques	technique	NOUN
fis-5022	57	14	,	,	PUNCT
fis-5022	57	15	the	the	DET
fis-5022	57	16	data	data	NOUN
fis-5022	57	17	analysis	analysis	NOUN
fis-5022	57	18	focuses	focus	VERB
fis-5022	57	19	on	on	ADP
fis-5022	57	20	evaluating	evaluate	VERB
fis-5022	57	21	various	various	ADJ
fis-5022	57	22	forms	form	NOUN
fis-5022	57	23	of	of	ADP
fis-5022	57	24	signal	signal	NOUN
fis-5022	57	25	contrasts	contrast	VERB
fis-5022	58	1	[	[	X
fis-5022	58	2	25	25	NUM
fis-5022	58	3	]	]	PUNCT
fis-5022	58	4	.	.	PUNCT
fis-5022	59	1	these	these	PRON
fis-5022	59	2	contrasts	contrast	VERB
fis-5022	59	3	underline	underline	ADJ
fis-5022	59	4	difference	difference	NOUN
fis-5022	59	5	between	between	ADP
fis-5022	59	6	signals	signal	NOUN
fis-5022	59	7	in	in	ADP
fis-5022	59	8	defect	defect	NOUN
fis-5022	59	9	and	and	CCONJ
fis-5022	59	10	defect	defect	NOUN
fis-5022	59	11	-	-	PUNCT
fis-5022	59	12	free	free	ADJ
fis-5022	59	13	areas	area	NOUN
fis-5022	59	14	.	.	PUNCT
fis-5022	60	1	tndt	tndt	VERB
fis-5022	60	2	employs	employ	VERB
fis-5022	60	3	some	some	DET
fis-5022	60	4	definitions	definition	NOUN
fis-5022	60	5	of	of	ADP
fis-5022	60	6	contrasts	contrast	NOUN
fis-5022	60	7	used	use	VERB
fis-5022	60	8	as	as	ADP
fis-5022	60	9	figures	figure	NOUN
fis-5022	60	10	of	of	ADP
fis-5022	60	11	merit	merit	NOUN
fis-5022	60	12	,	,	PUNCT
fis-5022	60	13	including	include	VERB
fis-5022	60	14	but	but	CCONJ
fis-5022	60	15	not	not	PART
fis-5022	60	16	limited	limit	VERB
fis-5022	60	17	to	to	ADP
fis-5022	60	18	absolute	absolute	ADJ
fis-5022	60	19	contrast	contrast	NOUN
fis-5022	60	20	(	(	PUNCT
fis-5022	60	21	ac	ac	PROPN
fis-5022	60	22	)	)	PUNCT
fis-5022	60	23	,	,	PUNCT
fis-5022	60	24	running	run	VERB
fis-5022	60	25	and	and	CCONJ
fis-5022	60	26	normalized	normalize	VERB
fis-5022	60	27	contrasts	contrast	NOUN
fis-5022	60	28	(	(	PUNCT
fis-5022	60	29	nc	nc	NOUN
fis-5022	60	30	)	)	PUNCT
fis-5022	60	31	.	.	PUNCT
fis-5022	61	1	absolute	absolute	ADJ
fis-5022	61	2	thermal	thermal	ADJ
fis-5022	61	3	contrast	contrast	NOUN
fis-5022	61	4	involves	involve	VERB
fis-5022	61	5	calculating	calculate	VERB
fis-5022	61	6	the	the	DET
fis-5022	61	7	temperature	temperature	NOUN
fis-5022	61	8	difference	difference	NOUN
fis-5022	61	9	between	between	ADP
fis-5022	61	10	defect	defect	NOUN
fis-5022	61	11	(	(	PUNCT
fis-5022	61	12	d	d	NOUN
fis-5022	61	13	)	)	PUNCT
fis-5022	61	14	and	and	CCONJ
fis-5022	61	15	non	non	ADJ
fis-5022	61	16	-	-	NOUN
fis-5022	61	17	defect	defect	ADJ
fis-5022	61	18	(	(	PUNCT
fis-5022	61	19	nd	nd	NOUN
fis-5022	61	20	)	)	PUNCT
fis-5022	61	21	areas	area	NOUN
fis-5022	61	22	.	.	PUNCT
fis-5022	62	1	however	however	ADV
fis-5022	62	2	,	,	PUNCT
fis-5022	62	3	a	a	DET
fis-5022	62	4	significant	significant	ADJ
fis-5022	62	5	limitation	limitation	NOUN
fis-5022	62	6	of	of	ADP
fis-5022	62	7	both	both	CCONJ
fis-5022	62	8	ac	ac	PROPN
fis-5022	62	9	and	and	CCONJ
fis-5022	62	10	nc	nc	PROPN
fis-5022	62	11	is	be	AUX
fis-5022	62	12	the	the	DET
fis-5022	62	13	necessity	necessity	NOUN
fis-5022	62	14	to	to	PART
fis-5022	62	15	identify	identify	VERB
fis-5022	62	16	a	a	DET
fis-5022	62	17	non	non	ADJ
fis-5022	62	18	-	-	NOUN
fis-5022	62	19	defect	defect	ADJ
fis-5022	62	20	,	,	PUNCT
fis-5022	62	21	or	or	CCONJ
fis-5022	62	22	sound	sound	ADJ
fis-5022	62	23	,	,	PUNCT
fis-5022	62	24	area	area	NOUN
fis-5022	62	25	.	.	PUNCT
fis-5022	63	1	this	this	DET
fis-5022	63	2	requirement	requirement	NOUN
fis-5022	63	3	poses	pose	VERB
fis-5022	63	4	a	a	DET
fis-5022	63	5	challenge	challenge	NOUN
fis-5022	63	6	in	in	ADP
fis-5022	63	7	data	datum	NOUN
fis-5022	63	8	processing	processing	NOUN
fis-5022	63	9	,	,	PUNCT
fis-5022	63	10	in	in	ADP
fis-5022	63	11	particular	particular	ADJ
fis-5022	63	12	,	,	PUNCT
fis-5022	63	13	when	when	SCONJ
fis-5022	63	14	locations	location	NOUN
fis-5022	63	15	of	of	ADP
fis-5022	63	16	defects	defect	NOUN
fis-5022	63	17	are	be	AUX
fis-5022	63	18	not	not	PART
fis-5022	63	19	a	a	DET
fis-5022	63	20	priori	priori	ADV
fis-5022	63	21	known	know	VERB
fis-5022	63	22	.	.	PUNCT
fis-5022	64	1	in	in	ADP
fis-5022	64	2	[	[	X
fis-5022	64	3	26	26	NUM
fis-5022	64	4	]	]	X
fis-5022	64	5	,	,	PUNCT
fis-5022	64	6	an	an	DET
fis-5022	64	7	automated	automate	VERB
fis-5022	64	8	method	method	NOUN
fis-5022	64	9	for	for	ADP
fis-5022	64	10	identifying	identify	VERB
fis-5022	64	11	a	a	DET
fis-5022	64	12	reference	reference	NOUN
fis-5022	64	13	zone	zone	NOUN
fis-5022	64	14	was	be	AUX
fis-5022	64	15	introduced	introduce	VERB
fis-5022	64	16	being	be	AUX
fis-5022	64	17	based	base	VERB
fis-5022	64	18	on	on	ADP
fis-5022	64	19	the	the	DET
fis-5022	64	20	determination	determination	NOUN
fis-5022	64	21	of	of	ADP
fis-5022	64	22	a	a	DET
fis-5022	64	23	minimal	minimal	ADJ
fis-5022	64	24	value	value	NOUN
fis-5022	64	25	of	of	ADP
fis-5022	64	26	the	the	DET
fis-5022	64	27	integral	integral	ADJ
fis-5022	64	28	involving	involve	VERB
fis-5022	64	29	the	the	DET
fis-5022	64	30	t	t	PROPN
fis-5022	64	31	t	t	NOUN
fis-5022	64	32	function	function	NOUN
fis-5022	64	33	.	.	PUNCT
fis-5022	65	1	since	since	SCONJ
fis-5022	65	2	a	a	DET
fis-5022	65	3	reference	reference	NOUN
fis-5022	65	4	(	(	PUNCT
fis-5022	65	5	non	non	ADJ
fis-5022	65	6	-	-	ADJ
fis-5022	65	7	defect	defect	ADJ
fis-5022	65	8	)	)	PUNCT
fis-5022	65	9	area	area	NOUN
fis-5022	65	10	is	be	AUX
fis-5022	65	11	determined	determine	VERB
fis-5022	65	12	,	,	PUNCT
fis-5022	65	13	the	the	DET
fis-5022	65	14	dimensionless	dimensionless	NOUN
fis-5022	65	15	running	running	NOUN
fis-5022	65	16	contrast	contrast	NOUN
fis-5022	65	17	can	can	AUX
fis-5022	65	18	be	be	AUX
fis-5022	65	19	obtained	obtain	VERB
fis-5022	65	20	as	as	ADP
fis-5022	65	21	follows	follow	VERB
fis-5022	65	22	:	:	PUNCT
fis-5022	65	23	run	run	VERB
fis-5022	65	24	d	d	PROPN
fis-5022	65	25	nd	nd	INTJ
fis-5022	65	26	nd	nd	NOUN
fis-5022	65	27	t	t	PROPN
fis-5022	65	28	t	t	PROPN
fis-5022	65	29	c	c	PROPN
fis-5022	65	30	t	t	PROPN
fis-5022	65	31			PROPN
fis-5022	65	32			PROPN
fis-5022	65	33	(	(	PUNCT
fis-5022	65	34	4	4	NUM
fis-5022	65	35	)	)	PUNCT
fis-5022	65	36	the	the	DET
fis-5022	65	37	pulse	pulse	NOUN
fis-5022	65	38	phase	phase	NOUN
fis-5022	65	39	thermography	thermography	NOUN
fis-5022	65	40	(	(	PUNCT
fis-5022	65	41	ppt	ppt	NOUN
fis-5022	65	42	)	)	PUNCT
fis-5022	65	43	technique	technique	NOUN
fis-5022	65	44	,	,	PUNCT
fis-5022	65	45	initially	initially	ADV
fis-5022	65	46	proposed	propose	VERB
fis-5022	65	47	by	by	ADP
fis-5022	65	48	maldague	maldague	NOUN
fis-5022	65	49	and	and	CCONJ
fis-5022	65	50	marinetti	marinetti	NOUN
fis-5022	65	51	[	[	X
fis-5022	65	52	27	27	NUM
fis-5022	65	53	]	]	PUNCT
fis-5022	65	54	,	,	PUNCT
fis-5022	65	55	combines	combine	VERB
fis-5022	65	56	advantages	advantage	NOUN
fis-5022	65	57	of	of	ADP
fis-5022	65	58	pulsed	pulsed	ADJ
fis-5022	65	59	and	and	CCONJ
fis-5022	65	60	thermal	thermal	ADJ
fis-5022	65	61	wave	wave	NOUN
fis-5022	65	62	tndt	tndt	NOUN
fis-5022	65	63	.	.	PUNCT
fis-5022	66	1	in	in	ADP
fis-5022	66	2	fact	fact	NOUN
fis-5022	66	3	,	,	PUNCT
fis-5022	66	4	any	any	DET
fis-5022	66	5	form	form	NOUN
fis-5022	66	6	of	of	ADP
fis-5022	66	7	thermal	thermal	ADJ
fis-5022	66	8	stimulation	stimulation	NOUN
fis-5022	66	9	,	,	PUNCT
fis-5022	66	10	be	be	AUX
fis-5022	66	11	it	it	PRON
fis-5022	66	12	a	a	DET
fis-5022	66	13	flash	flash	NOUN
fis-5022	66	14	or	or	CCONJ
fis-5022	66	15	pulse	pulse	NOUN
fis-5022	66	16	of	of	ADP
fis-5022	66	17	a	a	DET
fis-5022	66	18	certain	certain	ADJ
fis-5022	66	19	duration	duration	NOUN
fis-5022	66	20	,	,	PUNCT
fis-5022	66	21	can	can	AUX
fis-5022	66	22	be	be	AUX
fis-5022	66	23	represented	represent	VERB
fis-5022	66	24	as	as	ADP
fis-5022	66	25	a	a	DET
fis-5022	66	26	combination	combination	NOUN
fis-5022	66	27	of	of	ADP
fis-5022	66	28	harmonic	harmonic	ADJ
fis-5022	66	29	thermal	thermal	ADJ
fis-5022	66	30	waves	wave	NOUN
fis-5022	66	31	,	,	PUNCT
fis-5022	66	32	therefore	therefore	ADV
fis-5022	66	33	,	,	PUNCT
fis-5022	66	34	it	it	PRON
fis-5022	66	35	is	be	AUX
fis-5022	66	36	fruitful	fruitful	ADJ
fis-5022	66	37	to	to	PART
fis-5022	66	38	examine	examine	VERB
fis-5022	66	39	the	the	DET
fis-5022	66	40	propagation	propagation	NOUN
fis-5022	66	41	of	of	ADP
fis-5022	66	42	individual	individual	ADJ
fis-5022	66	43	waves	wave	NOUN
fis-5022	66	44	within	within	ADP
fis-5022	66	45	a	a	DET
fis-5022	66	46	solid	solid	ADJ
fis-5022	66	47	material	material	NOUN
fis-5022	66	48	and	and	CCONJ
fis-5022	66	49	their	their	PRON
fis-5022	66	50	interaction	interaction	NOUN
fis-5022	66	51	with	with	ADP
fis-5022	66	52	structural	structural	ADJ
fis-5022	66	53	inhomogeneities	inhomogeneity	NOUN
fis-5022	66	54	,	,	PUNCT
fis-5022	66	55	or	or	CCONJ
fis-5022	66	56	defects	defect	NOUN
fis-5022	66	57	.	.	PUNCT
fis-5022	67	1	the	the	DET
fis-5022	67	2	process	process	NOUN
fis-5022	67	3	involves	involve	VERB
fis-5022	67	4	monitoring	monitor	VERB
fis-5022	67	5	the	the	DET
fis-5022	67	6	surface	surface	NOUN
fis-5022	67	7	temperature	temperature	NOUN
fis-5022	67	8	with	with	ADP
fis-5022	67	9	an	an	DET
fis-5022	67	10	ir	ir	PROPN
fis-5022	67	11	camera	camera	NOUN
fis-5022	67	12	after	after	SCONJ
fis-5022	67	13	the	the	DET
fis-5022	67	14	heat	heat	NOUN
fis-5022	67	15	pulse	pulse	NOUN
fis-5022	67	16	was	be	AUX
fis-5022	67	17	delivered	deliver	VERB
fis-5022	67	18	onto	onto	ADP
fis-5022	67	19	sample	sample	NOUN
fis-5022	67	20	surface	surface	NOUN
fis-5022	67	21	.	.	PUNCT
fis-5022	68	1	subsequently	subsequently	ADV
fis-5022	68	2	,	,	PUNCT
fis-5022	68	3	the	the	DET
fis-5022	68	4	discrete	discrete	ADJ
fis-5022	68	5	fourier	fourier	NOUN
fis-5022	68	6	transform	transform	NOUN
fis-5022	68	7	is	be	AUX
fis-5022	68	8	applied	apply	VERB
fis-5022	68	9	to	to	ADP
fis-5022	68	10	the	the	DET
fis-5022	68	11	(	(	PUNCT
fis-5022	68	12	)	)	PUNCT
fis-5022	68	13	t	t	NOUN
fis-5022	68	14	t	t	PROPN
fis-5022	68	15	data	data	PROPN
fis-5022	68	16	,	,	PUNCT
fis-5022	68	17	resulting	result	VERB
fis-5022	68	18	in	in	ADP
fis-5022	68	19	calculation	calculation	NOUN
fis-5022	68	20	of	of	ADP
fis-5022	68	21	signal	signal	ADJ
fis-5022	68	22	phases	phase	NOUN
fis-5022	68	23	as	as	ADP
fis-5022	68	24	a.	a.	NOUN
fis-5022	68	25	chulkov	chulkov	PROPN
fis-5022	68	26	et	et	PROPN
fis-5022	68	27	alii	alii	PROPN
fis-5022	68	28	,	,	PUNCT
fis-5022	68	29	frattura	frattura	PROPN
fis-5022	68	30	ed	ed	PROPN
fis-5022	68	31	integrità	integrità	PROPN
fis-5022	68	32	strutturale	strutturale	PROPN
fis-5022	68	33	,	,	PUNCT
fis-5022	68	34	70	70	NUM
fis-5022	68	35	(	(	PUNCT
fis-5022	68	36	2024	2024	NUM
fis-5022	68	37	)	)	PUNCT
fis-5022	68	38	177	177	NUM
fis-5022	68	39	-	-	SYM
fis-5022	68	40	191	191	NUM
fis-5022	68	41	;	;	PUNCT
fis-5022	68	42	doi	doi	NOUN
fis-5022	68	43	:	:	PUNCT
fis-5022	68	44	10.3221	10.3221	NUM
fis-5022	68	45	/	/	SYM
fis-5022	68	46	igf	igf	NOUN
fis-5022	68	47	-	-	ADJ
fis-5022	68	48	esis.70.10	esis.70.10	ADJ
fis-5022	68	49	180	180	NUM
fis-5022	68	50	a	a	DET
fis-5022	68	51	function	function	NOUN
fis-5022	68	52	of	of	ADP
fis-5022	68	53	frequency	frequency	NOUN
fis-5022	68	54	(	(	PUNCT
fis-5022	68	55	)	)	PUNCT
fis-5022	68	56	f	f	NUM
fis-5022	68	57	.	.	PUNCT
fis-5022	69	1	the	the	DET
fis-5022	69	2	detection	detection	NOUN
fis-5022	69	3	of	of	ADP
fis-5022	69	4	subsurface	subsurface	NOUN
fis-5022	69	5	defects	defect	NOUN
fis-5022	69	6	is	be	AUX
fis-5022	69	7	based	base	VERB
fis-5022	69	8	on	on	ADP
fis-5022	69	9	observing	observe	VERB
fis-5022	69	10	the	the	DET
fis-5022	69	11	phase	phase	NOUN
fis-5022	69	12	difference	difference	NOUN
fis-5022	69	13			X
fis-5022	69	14	between	between	ADP
fis-5022	69	15	defect	defect	NOUN
fis-5022	69	16	and	and	CCONJ
fis-5022	69	17	non	non	ADJ
fis-5022	69	18	-	-	ADJ
fis-5022	69	19	defect	defect	ADJ
fis-5022	69	20	areas	area	NOUN
fis-5022	69	21	that	that	PRON
fis-5022	69	22	are	be	AUX
fis-5022	69	23	identified	identify	VERB
fis-5022	69	24	in	in	ADP
fis-5022	69	25	phase	phase	NOUN
fis-5022	69	26	images	image	NOUN
fis-5022	69	27	(	(	PUNCT
fis-5022	69	28	phasegrams	phasegram	NOUN
fis-5022	69	29	)	)	PUNCT
fis-5022	69	30	.	.	PUNCT
fis-5022	70	1	tsr	tsr	PROPN
fis-5022	70	2	is	be	AUX
fis-5022	70	3	a	a	DET
fis-5022	70	4	well	well	ADV
fis-5022	70	5	-	-	PUNCT
fis-5022	70	6	established	establish	VERB
fis-5022	70	7	method	method	NOUN
fis-5022	70	8	proposed	propose	VERB
fis-5022	70	9	by	by	ADP
fis-5022	70	10	shepard	shepard	NOUN
fis-5022	70	11	for	for	ADP
fis-5022	70	12	processing	process	VERB
fis-5022	70	13	pixel	pixel	PROPN
fis-5022	70	14	-	-	PUNCT
fis-5022	70	15	based	base	VERB
fis-5022	70	16	temperature	temperature	NOUN
fis-5022	70	17	evolutions	evolution	NOUN
fis-5022	70	18	[	[	X
fis-5022	70	19	28	28	NUM
fis-5022	70	20	,	,	PUNCT
fis-5022	70	21	29	29	NUM
fis-5022	70	22	]	]	PUNCT
fis-5022	70	23	.	.	PUNCT
fis-5022	71	1	the	the	DET
fis-5022	71	2	technique	technique	NOUN
fis-5022	71	3	is	be	AUX
fis-5022	71	4	based	base	VERB
fis-5022	71	5	on	on	ADP
fis-5022	71	6	the	the	DET
fis-5022	71	7	polynomial	polynomial	ADJ
fis-5022	71	8	fitting	fitting	NOUN
fis-5022	71	9	of	of	ADP
fis-5022	71	10	experimental	experimental	ADJ
fis-5022	71	11	temperature	temperature	NOUN
fis-5022	71	12	data	datum	NOUN
fis-5022	71	13	in	in	ADP
fis-5022	71	14	the	the	DET
fis-5022	71	15	log	log	NOUN
fis-5022	71	16	-	-	PUNCT
fis-5022	71	17	log	log	NOUN
fis-5022	71	18	scale	scale	NOUN
fis-5022	71	19	.	.	PUNCT
fis-5022	72	1	the	the	DET
fis-5022	72	2	fitting	fitting	ADJ
fis-5022	72	3	procedure	procedure	NOUN
fis-5022	72	4	effectively	effectively	ADV
fis-5022	72	5	replaces	replace	VERB
fis-5022	72	6	a	a	DET
fis-5022	72	7	raw	raw	ADJ
fis-5022	72	8	set	set	NOUN
fis-5022	72	9	of	of	ADP
fis-5022	72	10	temperature	temperature	NOUN
fis-5022	72	11	data	datum	NOUN
fis-5022	72	12	with	with	ADP
fis-5022	72	13	a	a	DET
fis-5022	72	14	series	series	NOUN
fis-5022	72	15	representing	represent	VERB
fis-5022	72	16	polynomial	polynomial	ADJ
fis-5022	72	17	coefficients	coefficient	NOUN
fis-5022	72	18	.	.	PUNCT
fis-5022	73	1	such	such	ADJ
fis-5022	73	2	approach	approach	NOUN
fis-5022	73	3	facilitates	facilitate	VERB
fis-5022	73	4	reconstruction	reconstruction	NOUN
fis-5022	73	5	of	of	ADP
fis-5022	73	6	initial	initial	ADJ
fis-5022	73	7	thermographic	thermographic	ADJ
fis-5022	73	8	data	datum	NOUN
fis-5022	73	9	to	to	PART
fis-5022	73	10	effectively	effectively	ADV
fis-5022	73	11	discriminate	discriminate	VERB
fis-5022	73	12	defect	defect	NOUN
fis-5022	73	13	and	and	CCONJ
fis-5022	73	14	non	non	ADJ
fis-5022	73	15	-	-	ADJ
fis-5022	73	16	defect	defect	ADJ
fis-5022	73	17	areas	area	NOUN
fis-5022	73	18	.	.	PUNCT
fis-5022	74	1	subsequently	subsequently	ADV
fis-5022	74	2	,	,	PUNCT
fis-5022	74	3	the	the	DET
fis-5022	74	4	first	first	ADJ
fis-5022	74	5	and	and	CCONJ
fis-5022	74	6	second	second	ADJ
fis-5022	74	7	derivatives	derivative	NOUN
fis-5022	74	8	of	of	ADP
fis-5022	74	9	logarithmic	logarithmic	ADJ
fis-5022	74	10	temperature	temperature	NOUN
fis-5022	74	11	are	be	AUX
fis-5022	74	12	analyzed	analyze	VERB
fis-5022	74	13	thus	thus	ADV
fis-5022	74	14	contributing	contribute	VERB
fis-5022	74	15	to	to	ADP
fis-5022	74	16	enhancing	enhance	VERB
fis-5022	74	17	the	the	DET
fis-5022	74	18	signal	signal	NOUN
fis-5022	74	19	-	-	PUNCT
fis-5022	74	20	to	to	ADP
fis-5022	74	21	-	-	PUNCT
fis-5022	74	22	noise	noise	NOUN
fis-5022	74	23	ratio	ratio	NOUN
fis-5022	74	24	and	and	CCONJ
fis-5022	74	25	producing	produce	VERB
fis-5022	74	26	sharp	sharp	ADJ
fis-5022	74	27	images	image	NOUN
fis-5022	74	28	of	of	ADP
fis-5022	74	29	subsurface	subsurface	NOUN
fis-5022	74	30	defects	defect	NOUN
fis-5022	74	31	.	.	PUNCT
fis-5022	75	1	also	also	ADV
fis-5022	75	2	,	,	PUNCT
fis-5022	75	3	the	the	DET
fis-5022	75	4	derivative	derivative	ADJ
fis-5022	75	5	analysis	analysis	NOUN
fis-5022	75	6	is	be	AUX
fis-5022	75	7	efficient	efficient	ADJ
fis-5022	75	8	in	in	ADP
fis-5022	75	9	characterizing	characterize	VERB
fis-5022	75	10	defect	defect	NOUN
fis-5022	75	11	depth	depth	NOUN
fis-5022	75	12	.	.	PUNCT
fis-5022	76	1	machine	machine	NOUN
fis-5022	76	2	learning	learn	VERB
fis-5022	76	3	machine	machine	NOUN
fis-5022	76	4	learning	learning	NOUN
fis-5022	76	5	techniques	technique	NOUN
fis-5022	76	6	have	have	AUX
fis-5022	76	7	gained	gain	VERB
fis-5022	76	8	popularity	popularity	NOUN
fis-5022	76	9	in	in	ADP
fis-5022	76	10	ir	ir	PROPN
fis-5022	76	11	thermography	thermography	NOUN
fis-5022	76	12	due	due	ADP
fis-5022	76	13	to	to	ADP
fis-5022	76	14	their	their	PRON
fis-5022	76	15	ability	ability	NOUN
fis-5022	76	16	to	to	PART
fis-5022	76	17	automatically	automatically	ADV
fis-5022	76	18	learn	learn	VERB
fis-5022	76	19	and	and	CCONJ
fis-5022	76	20	adapt	adapt	VERB
fis-5022	76	21	from	from	ADP
fis-5022	76	22	data	datum	NOUN
fis-5022	76	23	.	.	PUNCT
fis-5022	77	1	they	they	PRON
fis-5022	77	2	can	can	AUX
fis-5022	77	3	enhance	enhance	VERB
fis-5022	77	4	defect	defect	NOUN
fis-5022	77	5	detection	detection	NOUN
fis-5022	77	6	by	by	ADP
fis-5022	77	7	recognizing	recognize	VERB
fis-5022	77	8	subtle	subtle	ADJ
fis-5022	77	9	patterns	pattern	NOUN
fis-5022	77	10	,	,	PUNCT
fis-5022	77	11	extracting	extract	VERB
fis-5022	77	12	features	feature	NOUN
fis-5022	77	13	and	and	CCONJ
fis-5022	77	14	making	make	VERB
fis-5022	77	15	decisions	decision	NOUN
fis-5022	77	16	based	base	VERB
fis-5022	77	17	on	on	ADP
fis-5022	77	18	a	a	DET
fis-5022	77	19	learned	learn	VERB
fis-5022	77	20	knowledge	knowledge	NOUN
fis-5022	77	21	[	[	X
fis-5022	77	22	30	30	NUM
fis-5022	77	23	]	]	PUNCT
fis-5022	77	24	.	.	PUNCT
fis-5022	78	1	in	in	ADP
fis-5022	78	2	supervised	supervised	ADJ
fis-5022	78	3	learning	learning	NOUN
fis-5022	78	4	,	,	PUNCT
fis-5022	78	5	machine	machine	NOUN
fis-5022	78	6	learning	learning	NOUN
fis-5022	78	7	models	model	NOUN
fis-5022	78	8	are	be	AUX
fis-5022	78	9	trained	train	VERB
fis-5022	78	10	on	on	ADP
fis-5022	78	11	labeled	label	VERB
fis-5022	78	12	datasets	dataset	NOUN
fis-5022	78	13	containing	contain	VERB
fis-5022	78	14	examples	example	NOUN
fis-5022	78	15	of	of	ADP
fis-5022	78	16	both	both	CCONJ
fis-5022	78	17	defect	defect	VERB
fis-5022	78	18	and	and	CCONJ
fis-5022	78	19	non	non	ADJ
fis-5022	78	20	-	-	ADJ
fis-5022	78	21	defect	defect	ADJ
fis-5022	78	22	thermographic	thermographic	ADJ
fis-5022	78	23	data	datum	NOUN
fis-5022	78	24	.	.	PUNCT
fis-5022	79	1	these	these	DET
fis-5022	79	2	models	model	NOUN
fis-5022	79	3	learn	learn	VERB
fis-5022	79	4	to	to	PART
fis-5022	79	5	distinguish	distinguish	VERB
fis-5022	79	6	between	between	ADP
fis-5022	79	7	the	the	DET
fis-5022	79	8	two	two	NUM
fis-5022	79	9	input	input	NOUN
fis-5022	79	10	classes	class	NOUN
fis-5022	79	11	enabling	enable	VERB
fis-5022	79	12	them	they	PRON
fis-5022	79	13	to	to	PART
fis-5022	79	14	identify	identify	VERB
fis-5022	79	15	defects	defect	NOUN
fis-5022	79	16	in	in	ADP
fis-5022	79	17	new	new	ADJ
fis-5022	79	18	,	,	PUNCT
fis-5022	79	19	unlabeled	unlabeled	ADJ
fis-5022	79	20	data	datum	NOUN
fis-5022	79	21	.	.	PUNCT
fis-5022	80	1	machine	machine	NOUN
fis-5022	80	2	learning	learning	NOUN
fis-5022	80	3	models	model	NOUN
fis-5022	80	4	can	can	AUX
fis-5022	80	5	be	be	AUX
fis-5022	80	6	applied	apply	VERB
fis-5022	80	7	to	to	PART
fis-5022	80	8	defect	defect	VERB
fis-5022	80	9	detection	detection	NOUN
fis-5022	80	10	as	as	ADP
fis-5022	80	11	classification	classification	NOUN
fis-5022	80	12	tasks	task	NOUN
fis-5022	80	13	(	(	PUNCT
fis-5022	80	14	e.g.	e.g.	ADV
fis-5022	80	15	,	,	PUNCT
fis-5022	80	16	identifying	identify	VERB
fis-5022	80	17	whether	whether	SCONJ
fis-5022	80	18	an	an	DET
fis-5022	80	19	image	image	NOUN
fis-5022	80	20	contains	contain	VERB
fis-5022	80	21	a	a	DET
fis-5022	80	22	defect	defect	NOUN
fis-5022	80	23	)	)	PUNCT
fis-5022	80	24	or	or	CCONJ
fis-5022	80	25	regression	regression	NOUN
fis-5022	80	26	tasks	task	NOUN
fis-5022	80	27	(	(	PUNCT
fis-5022	80	28	e.g.	e.g.	ADV
fis-5022	80	29	,	,	PUNCT
fis-5022	80	30	estimating	estimate	VERB
fis-5022	80	31	the	the	DET
fis-5022	80	32	size	size	NOUN
fis-5022	80	33	or	or	CCONJ
fis-5022	80	34	depth	depth	NOUN
fis-5022	80	35	of	of	ADP
fis-5022	80	36	defects	defect	NOUN
fis-5022	80	37	)	)	PUNCT
fis-5022	80	38	.	.	PUNCT
fis-5022	81	1	in	in	ADP
fis-5022	81	2	this	this	DET
fis-5022	81	3	study	study	NOUN
fis-5022	81	4	,	,	PUNCT
fis-5022	81	5	the	the	DET
fis-5022	81	6	emphasis	emphasis	NOUN
fis-5022	81	7	is	be	AUX
fis-5022	81	8	made	make	VERB
fis-5022	81	9	on	on	ADP
fis-5022	81	10	the	the	DET
fis-5022	81	11	binary	binary	ADJ
fis-5022	81	12	classification	classification	NOUN
fis-5022	81	13	task	task	NOUN
fis-5022	81	14	and	and	CCONJ
fis-5022	81	15	pixel	pixel	PROPN
fis-5022	81	16	-	-	PUNCT
fis-5022	81	17	by	by	ADP
fis-5022	81	18	-	-	PUNCT
fis-5022	81	19	pixel	pixel	NOUN
fis-5022	81	20	analysis	analysis	NOUN
fis-5022	81	21	of	of	ADP
fis-5022	81	22	temperature	temperature	NOUN
fis-5022	81	23	evolutions	evolution	NOUN
fis-5022	81	24	that	that	PRON
fis-5022	81	25	allows	allow	VERB
fis-5022	81	26	classification	classification	NOUN
fis-5022	81	27	of	of	ADP
fis-5022	81	28	points	point	NOUN
fis-5022	81	29	in	in	ADP
fis-5022	81	30	thermographic	thermographic	ADJ
fis-5022	81	31	images	image	NOUN
fis-5022	81	32	as	as	ADP
fis-5022	81	33	belonging	belong	VERB
fis-5022	81	34	to	to	ADP
fis-5022	81	35	either	either	CCONJ
fis-5022	81	36	defect	defect	VERB
fis-5022	81	37	or	or	CCONJ
fis-5022	81	38	non	non	ADJ
fis-5022	81	39	-	-	ADJ
fis-5022	81	40	defect	defect	ADJ
fis-5022	81	41	areas	area	NOUN
fis-5022	81	42	.	.	PUNCT
fis-5022	82	1	some	some	DET
fis-5022	82	2	relatively	relatively	ADV
fis-5022	82	3	simple	simple	ADJ
fis-5022	82	4	models	model	NOUN
fis-5022	82	5	,	,	PUNCT
fis-5022	82	6	such	such	ADJ
fis-5022	82	7	as	as	ADP
fis-5022	82	8	svm	svm	ADJ
fis-5022	82	9	and	and	CCONJ
fis-5022	82	10	bagged	bagged	ADJ
fis-5022	82	11	trees	tree	NOUN
fis-5022	82	12	,	,	PUNCT
fis-5022	82	13	were	be	AUX
fis-5022	82	14	chosen	choose	VERB
fis-5022	82	15	to	to	PART
fis-5022	82	16	focus	focus	VERB
fis-5022	82	17	on	on	ADP
fis-5022	82	18	how	how	SCONJ
fis-5022	82	19	the	the	DET
fis-5022	82	20	variability	variability	NOUN
fis-5022	82	21	in	in	ADP
fis-5022	82	22	the	the	DET
fis-5022	82	23	training	training	NOUN
fis-5022	82	24	datasets	dataset	NOUN
fis-5022	82	25	influences	influence	VERB
fis-5022	82	26	the	the	DET
fis-5022	82	27	model	model	NOUN
fis-5022	82	28	performance	performance	NOUN
fis-5022	82	29	.	.	PUNCT
fis-5022	83	1	by	by	ADP
fis-5022	83	2	using	use	VERB
fis-5022	83	3	these	these	DET
fis-5022	83	4	models	model	NOUN
fis-5022	83	5	,	,	PUNCT
fis-5022	83	6	it	it	PRON
fis-5022	83	7	became	become	VERB
fis-5022	83	8	possible	possible	ADJ
fis-5022	83	9	to	to	PART
fis-5022	83	10	systematically	systematically	ADV
fis-5022	83	11	analyze	analyze	VERB
fis-5022	83	12	the	the	DET
fis-5022	83	13	impact	impact	NOUN
fis-5022	83	14	of	of	ADP
fis-5022	83	15	dataset	dataset	ADJ
fis-5022	83	16	variability	variability	NOUN
fis-5022	83	17	on	on	ADP
fis-5022	83	18	defect	defect	NOUN
fis-5022	83	19	detection	detection	NOUN
fis-5022	83	20	accuracy	accuracy	NOUN
fis-5022	83	21	without	without	ADP
fis-5022	83	22	the	the	DET
fis-5022	83	23	added	add	VERB
fis-5022	83	24	complexity	complexity	NOUN
fis-5022	83	25	of	of	ADP
fis-5022	83	26	more	more	ADV
fis-5022	83	27	advanced	advanced	ADJ
fis-5022	83	28	and	and	CCONJ
fis-5022	83	29	computationallyintensive	computationallyintensive	ADJ
fis-5022	83	30	algorithms	algorithm	NOUN
fis-5022	83	31	.	.	PUNCT
fis-5022	84	1	it	it	PRON
fis-5022	84	2	is	be	AUX
fis-5022	84	3	worth	worth	ADJ
fis-5022	84	4	mentioning	mention	VERB
fis-5022	84	5	that	that	SCONJ
fis-5022	84	6	these	these	DET
fis-5022	84	7	models	model	NOUN
fis-5022	84	8	have	have	AUX
fis-5022	84	9	also	also	ADV
fis-5022	84	10	demonstrated	demonstrate	VERB
fis-5022	84	11	good	good	ADJ
fis-5022	84	12	performance	performance	NOUN
fis-5022	84	13	in	in	ADP
fis-5022	84	14	ir	ir	PROPN
fis-5022	84	15	thermography	thermography	NOUN
fis-5022	84	16	applications	application	NOUN
fis-5022	84	17	in	in	ADP
fis-5022	84	18	plentiful	plentiful	ADJ
fis-5022	84	19	previous	previous	ADJ
fis-5022	84	20	studies	study	NOUN
fis-5022	84	21	[	[	X
fis-5022	84	22	31	31	NUM
fis-5022	84	23	,	,	PUNCT
fis-5022	84	24	32	32	NUM
fis-5022	84	25	,	,	PUNCT
fis-5022	84	26	33	33	NUM
fis-5022	84	27	]	]	PUNCT
fis-5022	84	28	.	.	PUNCT
fis-5022	85	1	the	the	DET
fis-5022	85	2	svm	svm	PROPN
fis-5022	85	3	model	model	NOUN
fis-5022	85	4	has	have	AUX
fis-5022	85	5	been	be	AUX
fis-5022	85	6	chosen	choose	VERB
fis-5022	85	7	because	because	SCONJ
fis-5022	85	8	it	it	PRON
fis-5022	85	9	has	have	AUX
fis-5022	85	10	demonstrated	demonstrate	VERB
fis-5022	85	11	a	a	DET
fis-5022	85	12	good	good	ADJ
fis-5022	85	13	performance	performance	NOUN
fis-5022	85	14	in	in	ADP
fis-5022	85	15	defect	defect	NOUN
fis-5022	85	16	classification	classification	NOUN
fis-5022	85	17	when	when	SCONJ
fis-5022	85	18	processing	process	VERB
fis-5022	85	19	raw	raw	ADJ
fis-5022	85	20	temperature	temperature	NOUN
fis-5022	85	21	data	datum	NOUN
fis-5022	85	22	.	.	PUNCT
fis-5022	86	1	its	its	PRON
fis-5022	86	2	theoretical	theoretical	ADJ
fis-5022	86	3	foundation	foundation	NOUN
fis-5022	86	4	is	be	AUX
fis-5022	86	5	rooted	root	VERB
fis-5022	86	6	in	in	ADP
fis-5022	86	7	the	the	DET
fis-5022	86	8	concept	concept	NOUN
fis-5022	86	9	of	of	ADP
fis-5022	86	10	finding	find	VERB
fis-5022	86	11	an	an	DET
fis-5022	86	12	optimal	optimal	ADJ
fis-5022	86	13	hyperplane	hyperplane	NOUN
fis-5022	86	14	in	in	ADP
fis-5022	86	15	a	a	DET
fis-5022	86	16	highdimensional	highdimensional	ADJ
fis-5022	86	17	feature	feature	NOUN
fis-5022	86	18	space	space	NOUN
fis-5022	86	19	to	to	PART
fis-5022	86	20	best	good	ADJ
fis-5022	86	21	separate	separate	ADJ
fis-5022	86	22	data	datum	NOUN
fis-5022	86	23	points	point	NOUN
fis-5022	86	24	belonging	belong	VERB
fis-5022	86	25	to	to	ADP
fis-5022	86	26	different	different	ADJ
fis-5022	86	27	classes	class	NOUN
fis-5022	86	28	[	[	X
fis-5022	86	29	34	34	NUM
fis-5022	86	30	]	]	PUNCT
fis-5022	86	31	.	.	PUNCT
fis-5022	87	1	the	the	DET
fis-5022	87	2	svm	svm	ADJ
fis-5022	87	3	concept	concept	NOUN
fis-5022	87	4	is	be	AUX
fis-5022	87	5	to	to	PART
fis-5022	87	6	identify	identify	VERB
fis-5022	87	7	a	a	DET
fis-5022	87	8	hyperplane	hyperplane	NOUN
fis-5022	87	9	that	that	PRON
fis-5022	87	10	maximizes	maximize	VERB
fis-5022	87	11	the	the	DET
fis-5022	87	12	margin	margin	NOUN
fis-5022	87	13	,	,	PUNCT
fis-5022	87	14	which	which	PRON
fis-5022	87	15	represents	represent	VERB
fis-5022	87	16	the	the	DET
fis-5022	87	17	distance	distance	NOUN
fis-5022	87	18	between	between	ADP
fis-5022	87	19	the	the	DET
fis-5022	87	20	hyperplane	hyperplane	NOUN
fis-5022	87	21	and	and	CCONJ
fis-5022	87	22	the	the	DET
fis-5022	87	23	nearest	near	ADJ
fis-5022	87	24	data	data	NOUN
fis-5022	87	25	points	point	NOUN
fis-5022	87	26	(	(	PUNCT
fis-5022	87	27	called	call	VERB
fis-5022	87	28	support	support	NOUN
fis-5022	87	29	vectors	vector	NOUN
fis-5022	87	30	)	)	PUNCT
fis-5022	87	31	from	from	ADP
fis-5022	87	32	each	each	DET
fis-5022	87	33	class	class	NOUN
fis-5022	87	34	.	.	PUNCT
fis-5022	88	1	this	this	DET
fis-5022	88	2	margin	margin	NOUN
fis-5022	88	3	maximization	maximization	NOUN
fis-5022	88	4	not	not	PART
fis-5022	88	5	only	only	ADV
fis-5022	88	6	leads	lead	VERB
fis-5022	88	7	to	to	ADP
fis-5022	88	8	a	a	DET
fis-5022	88	9	better	well	ADJ
fis-5022	88	10	generalization	generalization	NOUN
fis-5022	88	11	but	but	CCONJ
fis-5022	88	12	also	also	ADV
fis-5022	88	13	improves	improve	VERB
fis-5022	88	14	the	the	DET
fis-5022	88	15	model	model	NOUN
fis-5022	88	16	robustness	robustness	NOUN
fis-5022	88	17	toward	toward	ADP
fis-5022	88	18	outliers	outlier	NOUN
fis-5022	88	19	.	.	PUNCT
fis-5022	89	1	svms	svms	NOUN
fis-5022	89	2	are	be	AUX
fis-5022	89	3	powerful	powerful	ADJ
fis-5022	89	4	machine	machine	NOUN
fis-5022	89	5	learning	learning	NOUN
fis-5022	89	6	models	model	NOUN
fis-5022	89	7	that	that	PRON
fis-5022	89	8	excel	excel	VERB
fis-5022	89	9	in	in	ADP
fis-5022	89	10	finding	find	VERB
fis-5022	89	11	optimal	optimal	ADJ
fis-5022	89	12	decision	decision	NOUN
fis-5022	89	13	boundaries	boundary	NOUN
fis-5022	89	14	for	for	ADP
fis-5022	89	15	both	both	CCONJ
fis-5022	89	16	linearly	linearly	ADV
fis-5022	89	17	and	and	CCONJ
fis-5022	89	18	nonlinearly	nonlinearly	ADV
fis-5022	89	19	separable	separable	ADJ
fis-5022	89	20	data	datum	NOUN
fis-5022	89	21	.	.	PUNCT
fis-5022	90	1	they	they	PRON
fis-5022	90	2	are	be	AUX
fis-5022	90	3	widely	widely	ADV
fis-5022	90	4	used	use	VERB
fis-5022	90	5	in	in	ADP
fis-5022	90	6	various	various	ADJ
fis-5022	90	7	applications	application	NOUN
fis-5022	90	8	including	include	VERB
fis-5022	90	9	image	image	NOUN
fis-5022	90	10	and	and	CCONJ
fis-5022	90	11	text	text	NOUN
fis-5022	90	12	classification	classification	NOUN
fis-5022	90	13	,	,	PUNCT
fis-5022	90	14	anomaly	anomaly	NOUN
fis-5022	90	15	detection	detection	NOUN
fis-5022	90	16	,	,	PUNCT
fis-5022	90	17	etc	etc	X
fis-5022	90	18	.	.	X
fis-5022	90	19	,	,	PUNCT
fis-5022	90	20	thanks	thank	NOUN
fis-5022	90	21	to	to	ADP
fis-5022	90	22	their	their	PRON
fis-5022	90	23	robust	robust	ADJ
fis-5022	90	24	theoretical	theoretical	ADJ
fis-5022	90	25	foundation	foundation	NOUN
fis-5022	90	26	and	and	CCONJ
fis-5022	90	27	versatility	versatility	NOUN
fis-5022	90	28	.	.	PUNCT
fis-5022	91	1	ensemble	ensemble	ADJ
fis-5022	91	2	machine	machine	NOUN
fis-5022	91	3	learning	learning	NOUN
fis-5022	91	4	models	model	NOUN
fis-5022	91	5	aggregate	aggregate	VERB
fis-5022	91	6	predictions	prediction	NOUN
fis-5022	91	7	from	from	ADP
fis-5022	91	8	multiple	multiple	ADJ
fis-5022	91	9	base	base	NOUN
fis-5022	91	10	models	model	NOUN
fis-5022	91	11	to	to	PART
fis-5022	91	12	create	create	VERB
fis-5022	91	13	a	a	DET
fis-5022	91	14	final	final	ADJ
fis-5022	91	15	prediction	prediction	NOUN
fis-5022	91	16	.	.	PUNCT
fis-5022	92	1	the	the	DET
fis-5022	92	2	bagged	bag	VERB
fis-5022	92	3	trees	tree	NOUN
fis-5022	92	4	ensemble	ensemble	ADJ
fis-5022	92	5	method	method	NOUN
fis-5022	92	6	involves	involve	VERB
fis-5022	92	7	training	train	VERB
fis-5022	92	8	multiple	multiple	ADJ
fis-5022	92	9	decision	decision	NOUN
fis-5022	92	10	trees	tree	NOUN
fis-5022	92	11	on	on	ADP
fis-5022	92	12	different	different	ADJ
fis-5022	92	13	subsets	subset	NOUN
fis-5022	92	14	of	of	ADP
fis-5022	92	15	training	training	NOUN
fis-5022	92	16	data	datum	NOUN
fis-5022	92	17	and	and	CCONJ
fis-5022	92	18	combining	combine	VERB
fis-5022	92	19	their	their	PRON
fis-5022	92	20	predictions	prediction	NOUN
fis-5022	92	21	.	.	PUNCT
fis-5022	93	1	this	this	DET
fis-5022	93	2	approach	approach	NOUN
fis-5022	93	3	significantly	significantly	ADV
fis-5022	93	4	reduces	reduce	VERB
fis-5022	93	5	overfitting	overfitte	VERB
fis-5022	93	6	,	,	PUNCT
fis-5022	93	7	a	a	DET
fis-5022	93	8	common	common	ADJ
fis-5022	93	9	challenge	challenge	NOUN
fis-5022	93	10	in	in	ADP
fis-5022	93	11	machine	machine	NOUN
fis-5022	93	12	learning	learning	NOUN
fis-5022	93	13	,	,	PUNCT
fis-5022	93	14	especially	especially	ADV
fis-5022	93	15	when	when	SCONJ
fis-5022	93	16	dealing	deal	VERB
fis-5022	93	17	with	with	ADP
fis-5022	93	18	varied	varied	ADJ
fis-5022	93	19	and	and	CCONJ
fis-5022	93	20	noisy	noisy	ADJ
fis-5022	93	21	data	datum	NOUN
fis-5022	93	22	.	.	PUNCT
fis-5022	94	1	bagged	bagged	ADJ
fis-5022	94	2	trees	tree	NOUN
fis-5022	94	3	have	have	AUX
fis-5022	94	4	shown	show	VERB
fis-5022	94	5	effectiveness	effectiveness	NOUN
fis-5022	94	6	in	in	ADP
fis-5022	94	7	numerous	numerous	ADJ
fis-5022	94	8	studies	study	NOUN
fis-5022	94	9	,	,	PUNCT
fis-5022	94	10	providing	provide	VERB
fis-5022	94	11	robust	robust	ADJ
fis-5022	94	12	and	and	CCONJ
fis-5022	94	13	reliable	reliable	ADJ
fis-5022	94	14	results	result	NOUN
fis-5022	94	15	across	across	ADP
fis-5022	94	16	different	different	ADJ
fis-5022	94	17	applications	application	NOUN
fis-5022	94	18	.	.	PUNCT
fis-5022	95	1	by	by	ADP
fis-5022	95	2	choosing	choose	VERB
fis-5022	95	3	the	the	DET
fis-5022	95	4	models	model	NOUN
fis-5022	95	5	above	above	ADV
fis-5022	95	6	,	,	PUNCT
fis-5022	95	7	this	this	DET
fis-5022	95	8	study	study	NOUN
fis-5022	95	9	aimed	aim	VERB
fis-5022	95	10	to	to	PART
fis-5022	95	11	ensure	ensure	VERB
fis-5022	95	12	transparency	transparency	NOUN
fis-5022	95	13	and	and	CCONJ
fis-5022	95	14	interpretability	interpretability	NOUN
fis-5022	95	15	in	in	ADP
fis-5022	95	16	analyzing	analyze	VERB
fis-5022	95	17	the	the	DET
fis-5022	95	18	crucial	crucial	ADJ
fis-5022	95	19	role	role	NOUN
fis-5022	95	20	of	of	ADP
fis-5022	95	21	dataset	dataset	ADJ
fis-5022	95	22	composition	composition	NOUN
fis-5022	95	23	in	in	ADP
fis-5022	95	24	machine	machine	NOUN
fis-5022	95	25	learning	learning	NOUN
fis-5022	95	26	-	-	PUNCT
fis-5022	95	27	based	base	VERB
fis-5022	95	28	defect	defect	NOUN
fis-5022	95	29	detection	detection	NOUN
fis-5022	95	30	systems	system	NOUN
fis-5022	95	31	.	.	PUNCT
fis-5022	96	1	the	the	DET
fis-5022	96	2	focus	focus	NOUN
fis-5022	96	3	on	on	ADP
fis-5022	96	4	dataset	dataset	ADJ
fis-5022	96	5	variability	variability	NOUN
fis-5022	96	6	is	be	AUX
fis-5022	96	7	essential	essential	ADJ
fis-5022	96	8	for	for	ADP
fis-5022	96	9	understanding	understanding	NOUN
fis-5022	96	10	and	and	CCONJ
fis-5022	96	11	improving	improve	VERB
fis-5022	96	12	generalizability	generalizability	NOUN
fis-5022	96	13	and	and	CCONJ
fis-5022	96	14	accuracy	accuracy	NOUN
fis-5022	96	15	of	of	ADP
fis-5022	96	16	defect	defect	ADJ
fis-5022	96	17	detection	detection	NOUN
fis-5022	96	18	methods	method	NOUN
fis-5022	96	19	.	.	PUNCT
fis-5022	97	1	numerical	numerical	PROPN
fis-5022	97	2	simulation	simulation	PROPN
fis-5022	97	3	n	n	PROPN
fis-5022	97	4	this	this	DET
fis-5022	97	5	study	study	NOUN
fis-5022	97	6	,	,	PUNCT
fis-5022	97	7	the	the	DET
fis-5022	97	8	viability	viability	NOUN
fis-5022	97	9	of	of	ADP
fis-5022	97	10	training	training	NOUN
fis-5022	97	11	defect	defect	NOUN
fis-5022	97	12	detection	detection	NOUN
fis-5022	97	13	models	model	NOUN
fis-5022	97	14	by	by	ADP
fis-5022	97	15	using	use	VERB
fis-5022	97	16	ir	ir	PROPN
fis-5022	97	17	thermographic	thermographic	ADJ
fis-5022	97	18	data	datum	NOUN
fis-5022	97	19	derived	derive	VERB
fis-5022	97	20	from	from	ADP
fis-5022	97	21	numerical	numerical	ADJ
fis-5022	97	22	simulations	simulation	NOUN
fis-5022	97	23	will	will	AUX
fis-5022	97	24	be	be	AUX
fis-5022	97	25	assessed	assess	VERB
fis-5022	97	26	.	.	PUNCT
fis-5022	98	1	the	the	DET
fis-5022	98	2	accent	accent	NOUN
fis-5022	98	3	is	be	AUX
fis-5022	98	4	made	make	VERB
fis-5022	98	5	on	on	ADP
fis-5022	98	6	a	a	DET
fis-5022	98	7	thorough	thorough	ADJ
fis-5022	98	8	examination	examination	NOUN
fis-5022	98	9	of	of	ADP
fis-5022	98	10	the	the	DET
fis-5022	98	11	impact	impact	NOUN
fis-5022	98	12	of	of	ADP
fis-5022	98	13	model	model	NOUN
fis-5022	98	14	parameters	parameter	NOUN
fis-5022	98	15	and	and	CCONJ
fis-5022	98	16	dataset	dataset	ADJ
fis-5022	98	17	size	size	NOUN
fis-5022	98	18	on	on	ADP
fis-5022	98	19	the	the	DET
fis-5022	98	20	performance	performance	NOUN
fis-5022	98	21	of	of	ADP
fis-5022	98	22	the	the	DET
fis-5022	98	23	models	model	NOUN
fis-5022	98	24	,	,	PUNCT
fis-5022	98	25	which	which	PRON
fis-5022	98	26	are	be	AUX
fis-5022	98	27	applied	apply	VERB
fis-5022	98	28	to	to	ADP
fis-5022	98	29	previously	previously	ADV
fis-5022	98	30	unobserved	unobserved	ADJ
fis-5022	98	31	data	datum	NOUN
fis-5022	98	32	.	.	PUNCT
fis-5022	99	1	to	to	PART
fis-5022	99	2	achieve	achieve	VERB
fis-5022	99	3	this	this	DET
fis-5022	99	4	objective	objective	NOUN
fis-5022	99	5	,	,	PUNCT
fis-5022	99	6	some	some	DET
fis-5022	99	7	multiple	multiple	ADJ
fis-5022	99	8	sets	set	NOUN
fis-5022	99	9	of	of	ADP
fis-5022	99	10	training	training	NOUN
fis-5022	99	11	and	and	CCONJ
fis-5022	99	12	testing	testing	NOUN
fis-5022	99	13	datasets	dataset	NOUN
fis-5022	99	14	,	,	PUNCT
fis-5022	99	15	each	each	PRON
fis-5022	99	16	characterized	characterize	VERB
fis-5022	99	17	by	by	ADP
fis-5022	99	18	different	different	ADJ
fis-5022	99	19	model	model	NOUN
fis-5022	99	20	parameters	parameter	NOUN
fis-5022	99	21	,	,	PUNCT
fis-5022	99	22	were	be	AUX
fis-5022	99	23	generated	generate	VERB
fis-5022	99	24	.	.	PUNCT
fis-5022	100	1	these	these	DET
fis-5022	100	2	models	model	NOUN
fis-5022	100	3	were	be	AUX
fis-5022	100	4	designed	design	VERB
fis-5022	100	5	by	by	ADP
fis-5022	100	6	using	use	VERB
fis-5022	100	7	the	the	DET
fis-5022	100	8	thermocalc-3d	thermocalc-3d	PROPN
fis-5022	100	9	software	software	NOUN
fis-5022	100	10	,	,	PUNCT
fis-5022	100	11	a	a	DET
fis-5022	100	12	specialized	specialized	ADJ
fis-5022	100	13	tool	tool	NOUN
fis-5022	100	14	developed	develop	VERB
fis-5022	100	15	by	by	ADP
fis-5022	100	16	tomsk	tomsk	PROPN
fis-5022	100	17	polytechnic	polytechnic	PROPN
fis-5022	100	18	university	university	PROPN
fis-5022	100	19	for	for	ADP
fis-5022	100	20	simulating	simulate	VERB
fis-5022	100	21	heat	heat	NOUN
fis-5022	100	22	transfer	transfer	NOUN
fis-5022	100	23	processes	process	NOUN
fis-5022	100	24	in	in	ADP
fis-5022	100	25	solid	solid	ADJ
fis-5022	100	26	materials	material	NOUN
fis-5022	100	27	with	with	ADP
fis-5022	100	28	defects	defect	NOUN
fis-5022	100	29	by	by	ADP
fis-5022	100	30	using	use	VERB
fis-5022	100	31	the	the	DET
fis-5022	100	32	finite	finite	ADJ
fis-5022	100	33	difference	difference	NOUN
fis-5022	100	34	method	method	NOUN
fis-5022	100	35	.	.	PUNCT
fis-5022	101	1	i	i	PRON
fis-5022	101	2	a.	a.	NOUN
fis-5022	101	3	chulkov	chulkov	PROPN
fis-5022	101	4	et	et	PROPN
fis-5022	101	5	alii	alii	PROPN
fis-5022	101	6	,	,	PUNCT
fis-5022	101	7	frattura	frattura	PROPN
fis-5022	101	8	ed	ed	PROPN
fis-5022	101	9	integrità	integrità	PROPN
fis-5022	101	10	strutturale	strutturale	PROPN
fis-5022	101	11	,	,	PUNCT
fis-5022	101	12	70	70	NUM
fis-5022	101	13	(	(	PUNCT
fis-5022	101	14	2024	2024	NUM
fis-5022	101	15	)	)	PUNCT
fis-5022	101	16	177	177	NUM
fis-5022	101	17	-	-	SYM
fis-5022	101	18	191	191	NUM
fis-5022	101	19	;	;	PUNCT
fis-5022	101	20	doi	doi	NOUN
fis-5022	101	21	:	:	PUNCT
fis-5022	101	22	10.3221	10.3221	NUM
fis-5022	101	23	/	/	SYM
fis-5022	101	24	igf	igf	NOUN
fis-5022	101	25	-	-	PUNCT
fis-5022	101	26	esis.70.10	esis.70.10	ADJ
fis-5022	101	27	181	181	NUM
fis-5022	101	28	the	the	DET
fis-5022	101	29	numerical	numerical	PROPN
fis-5022	101	30	simulation	simulation	NOUN
fis-5022	101	31	of	of	ADP
fis-5022	101	32	3d	3d	PROPN
fis-5022	101	33	heat	heat	NOUN
fis-5022	101	34	conduction	conduction	NOUN
fis-5022	101	35	problems	problem	NOUN
fis-5022	101	36	yields	yield	VERB
fis-5022	101	37	temporal	temporal	ADJ
fis-5022	101	38	evolutions	evolution	NOUN
fis-5022	101	39	at	at	ADP
fis-5022	101	40	all	all	DET
fis-5022	101	41	surface	surface	NOUN
fis-5022	101	42	points	point	NOUN
fis-5022	101	43	of	of	ADP
fis-5022	101	44	a	a	DET
fis-5022	101	45	solid	solid	ADJ
fis-5022	101	46	body	body	NOUN
fis-5022	101	47	subjected	subject	VERB
fis-5022	101	48	to	to	ADP
fis-5022	101	49	uniform	uniform	NOUN
fis-5022	101	50	or	or	CCONJ
fis-5022	101	51	uneven	uneven	ADJ
fis-5022	101	52	heating	heating	NOUN
fis-5022	101	53	.	.	PUNCT
fis-5022	102	1	the	the	DET
fis-5022	102	2	model	model	NOUN
fis-5022	102	3	used	use	VERB
fis-5022	102	4	represents	represent	VERB
fis-5022	102	5	a	a	DET
fis-5022	102	6	rectangular	rectangular	ADJ
fis-5022	102	7	plate	plate	NOUN
fis-5022	102	8	containing	contain	VERB
fis-5022	102	9	air	air	NOUN
fis-5022	102	10	-	-	PUNCT
fis-5022	102	11	filled	fill	VERB
fis-5022	102	12	parallelepipedlike	parallelepipedlike	ADJ
fis-5022	102	13	defects	defect	NOUN
fis-5022	102	14	.	.	PUNCT
fis-5022	103	1	a	a	DET
fis-5022	103	2	visual	visual	ADJ
fis-5022	103	3	presentation	presentation	NOUN
fis-5022	103	4	of	of	ADP
fis-5022	103	5	the	the	DET
fis-5022	103	6	model	model	NOUN
fis-5022	103	7	is	be	AUX
fis-5022	103	8	shown	show	VERB
fis-5022	103	9	in	in	ADP
fis-5022	103	10	fig	fig	NOUN
fis-5022	103	11	.	.	PUNCT
fis-5022	104	1	1	1	X
fis-5022	104	2	.	.	X
fis-5022	104	3	the	the	DET
fis-5022	104	4	example	example	NOUN
fis-5022	104	5	of	of	ADP
fis-5022	104	6	calculated	calculate	VERB
fis-5022	104	7	temperature	temperature	NOUN
fis-5022	104	8	distributions	distribution	NOUN
fis-5022	104	9	is	be	AUX
fis-5022	104	10	given	give	VERB
fis-5022	104	11	in	in	ADP
fis-5022	104	12	fig	fig	NOUN
fis-5022	104	13	.	.	PUNCT
fis-5022	105	1	2	2	X
fis-5022	105	2	.	.	X
fis-5022	105	3	figure	figure	NOUN
fis-5022	105	4	1	1	NUM
fis-5022	105	5	:	:	PUNCT
fis-5022	105	6	tndt	tndt	PROPN
fis-5022	105	7	3d	3d	PROPN
fis-5022	105	8	numerical	numerical	PROPN
fis-5022	105	9	model	model	PROPN
fis-5022	105	10	.	.	PUNCT
fis-5022	106	1	the	the	DET
fis-5022	106	2	general	general	ADJ
fis-5022	106	3	mathematical	mathematical	ADJ
fis-5022	106	4	formulation	formulation	NOUN
fis-5022	106	5	of	of	ADP
fis-5022	106	6	the	the	DET
fis-5022	106	7	3d	3d	PROPN
fis-5022	106	8	model	model	NOUN
fis-5022	106	9	of	of	ADP
fis-5022	106	10	non	non	ADJ
fis-5022	106	11	-	-	ADJ
fis-5022	106	12	adiabatic	adiabatic	ADJ
fis-5022	106	13	heat	heat	NOUN
fis-5022	106	14	conduction	conduction	NOUN
fis-5022	106	15	in	in	ADP
fis-5022	106	16	a	a	DET
fis-5022	106	17	multilayer	multilayer	ADJ
fis-5022	106	18	body	body	NOUN
fis-5022	106	19	with	with	ADP
fis-5022	106	20	defects	defect	NOUN
fis-5022	106	21	accepted	accept	VERB
fis-5022	106	22	in	in	ADP
fis-5022	106	23	thermocalc-3d	thermocalc-3d	PROPN
fis-5022	106	24	is	be	AUX
fis-5022	106	25	as	as	SCONJ
fis-5022	106	26	follows	follow	VERB
fis-5022	106	27	(	(	PUNCT
fis-5022	106	28	fig	fig	NOUN
fis-5022	106	29	.	.	PUNCT
fis-5022	107	1	1	1	NUM
fis-5022	107	2	):	):	PUNCT
fis-5022	107	3	2	2	NUM
fis-5022	107	4	2	2	NUM
fis-5022	107	5	2	2	NUM
fis-5022	107	6	2	2	NUM
fis-5022	107	7	2	2	NUM
fis-5022	107	8	2	2	NUM
fis-5022	107	9	(	(	PUNCT
fis-5022	107	10	,	,	PUNCT
fis-5022	107	11	,	,	PUNCT
fis-5022	107	12	,	,	PUNCT
fis-5022	107	13	)	)	PUNCT
fis-5022	107	14	(	(	PUNCT
fis-5022	107	15	,	,	PUNCT
fis-5022	107	16	,	,	PUNCT
fis-5022	107	17	,	,	PUNCT
fis-5022	107	18	)	)	PUNCT
fis-5022	107	19	(	(	PUNCT
fis-5022	107	20	,	,	PUNCT
fis-5022	107	21	,	,	PUNCT
fis-5022	107	22	,	,	PUNCT
fis-5022	107	23	)	)	PUNCT
fis-5022	107	24	(	(	PUNCT
fis-5022	107	25	,	,	PUNCT
fis-5022	107	26	,	,	PUNCT
fis-5022	107	27	,	,	PUNCT
fis-5022	107	28	)	)	PUNCT
fis-5022	107	29	x	x	X
fis-5022	108	1	y	y	NOUN
fis-5022	108	2	zi	zi	NOUN
fis-5022	109	1	i	i	INTJ
fis-5022	109	2	i	i	PRON
fis-5022	110	1	i	i	PRON
fis-5022	110	2	i	i	PRON
fis-5022	111	1	i	i	PRON
fis-5022	112	1	i	i	PRON
fis-5022	112	2	t	t	VERB
fis-5022	112	3	x	x	PUNCT
fis-5022	113	1	y	y	PROPN
fis-5022	113	2	z	z	PROPN
fis-5022	113	3	t	t	PROPN
fis-5022	113	4	x	x	PUNCT
fis-5022	114	1	y	y	PROPN
fis-5022	114	2	z	z	PROPN
fis-5022	114	3	t	t	PROPN
fis-5022	114	4	x	x	PUNCT
fis-5022	114	5	y	y	PROPN
fis-5022	114	6	z	z	PROPN
fis-5022	114	7	t	t	PROPN
fis-5022	114	8	x	x	PUNCT
fis-5022	114	9	y	y	PROPN
fis-5022	114	10	z	z	NOUN
fis-5022	114	11	x	x	SYM
fis-5022	115	1	y	y	PROPN
fis-5022	115	2	z	z	PROPN
fis-5022	115	3			ADJ
fis-5022	115	4			NOUN
fis-5022	115	5			ADJ
fis-5022	115	6			NOUN
fis-5022	115	7			ADJ
fis-5022	115	8			NOUN
fis-5022	115	9			PROPN
fis-5022	115	10			VERB
fis-5022	115	11			NOUN
fis-5022	115	12			X
fis-5022	115	13			ADP
fis-5022	115	14			ADJ
fis-5022	115	15			ADJ
fis-5022	115	16			PROPN
fis-5022	115	17			PROPN
fis-5022	115	18			PROPN
fis-5022	115	19			ADJ
fis-5022	115	20			NUM
fis-5022	115	21			ADJ
fis-5022	115	22			PROPN
fis-5022	115	23	(	(	PUNCT
fis-5022	115	24	5	5	NUM
fis-5022	115	25	)	)	PUNCT
fis-5022	115	26	1	1	NUM
fis-5022	115	27	76	76	NUM
fis-5022	115	28	(	(	PUNCT
fis-5022	115	29	36	36	NUM
fis-5022	115	30	40	40	NUM
fis-5022	115	31	)	)	PUNCT
fis-5022	115	32	(	(	PUNCT
fis-5022	115	33	0)i	0)i	ADJ
fis-5022	115	34	in	in	ADP
fis-5022	115	35	i	i	PROPN
fis-5022	115	36	layers	layer	VERB
fis-5022	115	37	defects	defect	NOUN
fis-5022	115	38	t	t	PROPN
fis-5022	115	39	t	t	PROPN
fis-5022	115	40			PROPN
fis-5022	115	41			PROPN
fis-5022	115	42			VERB
fis-5022	116	1			PROPN
fis-5022	116	2			NOUN
fis-5022	116	3	(	(	PUNCT
fis-5022	116	4	6	6	NUM
fis-5022	116	5	)	)	SYM
fis-5022	116	6	1	1	NUM
fis-5022	116	7	1	1	NUM
fis-5022	116	8	1	1	NUM
fis-5022	116	9	(	(	PUNCT
fis-5022	116	10	,	,	PUNCT
fis-5022	116	11	,	,	PUNCT
fis-5022	116	12	0	0	NUM
fis-5022	116	13	,	,	PUNCT
fis-5022	116	14	)	)	PUNCT
fis-5022	116	15	(	(	PUNCT
fis-5022	116	16	,	,	PUNCT
fis-5022	116	17	,	,	PUNCT
fis-5022	116	18	)	)	PUNCT
fis-5022	116	19	[	[	PUNCT
fis-5022	116	20	(	(	PUNCT
fis-5022	116	21	,	,	PUNCT
fis-5022	116	22	,	,	PUNCT
fis-5022	116	23	,	,	PUNCT
fis-5022	116	24	)	)	PUNCT
fis-5022	116	25	]	]	X
fis-5022	116	26	z	z	X
fis-5022	116	27	f	f	PROPN
fis-5022	116	28	amb	amb	PROPN
fis-5022	116	29	t	t	PROPN
fis-5022	116	30	x	x	PUNCT
fis-5022	116	31	y	y	PROPN
fis-5022	116	32	z	z	PROPN
fis-5022	116	33	k	k	NOUN
fis-5022	116	34	q	q	PUNCT
fis-5022	116	35	x	x	PUNCT
fis-5022	116	36	y	y	NOUN
fis-5022	116	37	h	h	NOUN
fis-5022	116	38	t	t	PROPN
fis-5022	116	39	x	x	PUNCT
fis-5022	116	40	y	y	PROPN
fis-5022	116	41	z	z	PROPN
fis-5022	116	42	t	t	PROPN
fis-5022	116	43	z	z	PROPN
fis-5022	116	44			ADJ
fis-5022	116	45			NOUN
fis-5022	116	46			NOUN
fis-5022	116	47			NOUN
fis-5022	116	48			ADJ
fis-5022	116	49			PROPN
fis-5022	116	50			PROPN
fis-5022	116	51			NUM
fis-5022	116	52			NUM
fis-5022	116	53			NOUN
fis-5022	116	54			VERB
fis-5022	116	55			NOUN
fis-5022	116	56	(	(	PUNCT
fis-5022	116	57	7	7	NUM
fis-5022	116	58	)	)	SYM
fis-5022	116	59	3	3	NUM
fis-5022	116	60	3	3	NUM
fis-5022	116	61	(	(	PUNCT
fis-5022	116	62	,	,	PUNCT
fis-5022	116	63	,	,	PUNCT
fis-5022	116	64	,	,	PUNCT
fis-5022	116	65	)	)	PUNCT
fis-5022	116	66	[	[	PUNCT
fis-5022	116	67	(	(	PUNCT
fis-5022	116	68	,	,	PUNCT
fis-5022	116	69	,	,	PUNCT
fis-5022	116	70	,	,	PUNCT
fis-5022	116	71	)	)	PUNCT
fis-5022	117	1	]	]	X
fis-5022	117	2	zz	zz	X
fis-5022	117	3	m	m	VERB
fis-5022	117	4	r	r	NOUN
fis-5022	117	5	amb	amb	PROPN
fis-5022	118	1	t	t	PROPN
fis-5022	118	2	x	x	PUNCT
fis-5022	118	3	y	y	PROPN
fis-5022	118	4	z	z	PROPN
fis-5022	118	5	l	l	NOUN
fis-5022	119	1	k	k	NOUN
fis-5022	119	2	h	h	NOUN
fis-5022	119	3	t	t	NOUN
fis-5022	119	4	x	x	PUNCT
fis-5022	119	5	y	y	PROPN
fis-5022	119	6	z	z	PROPN
fis-5022	119	7	t	t	PROPN
fis-5022	119	8	z	z	PROPN
fis-5022	119	9			ADJ
fis-5022	119	10			NOUN
fis-5022	119	11			NOUN
fis-5022	119	12			PROPN
fis-5022	119	13			ADJ
fis-5022	119	14			NUM
fis-5022	119	15			NUM
fis-5022	119	16			NOUN
fis-5022	119	17			VERB
fis-5022	119	18			NOUN
fis-5022	119	19	(	(	PUNCT
fis-5022	119	20	8)	8)	NUM
fis-5022	119	21	(	(	PUNCT
fis-5022	119	22	,	,	PUNCT
fis-5022	119	23	,	,	PUNCT
fis-5022	119	24	,	,	PUNCT
fis-5022	119	25	)	)	PUNCT
fis-5022	119	26	0	0	PUNCT
fis-5022	120	1	for	for	ADP
fis-5022	120	2	0	0	NUM
fis-5022	120	3	,	,	PUNCT
fis-5022	120	4	0	0	NUM
fis-5022	120	5	;	;	PUNCT
fis-5022	120	6	,	,	PUNCT
fis-5022	120	7	0	0	NUM
fis-5022	120	8	(	(	PUNCT
fis-5022	120	9	,	,	PUNCT
fis-5022	120	10	,	,	PUNCT
fis-5022	120	11	,	,	PUNCT
fis-5022	120	12	)	)	PUNCT
fis-5022	120	13	0	0	PUNCT
fis-5022	120	14	for	for	ADP
fis-5022	120	15	0	0	NUM
fis-5022	120	16	,	,	PUNCT
fis-5022	120	17	0	0	NUM
fis-5022	120	18	;	;	PUNCT
fis-5022	120	19	,	,	PUNCT
fis-5022	120	20	0	0	PUNCT
fis-5022	120	21	i	i	NOUN
fis-5022	120	22	y	y	VERB
fis-5022	120	23	x	x	VERB
fis-5022	120	24	y	y	VERB
fis-5022	120	25	i	i	NOUN
fis-5022	120	26	x	x	VERB
fis-5022	120	27	y	y	VERB
fis-5022	120	28	x	x	SYM
fis-5022	120	29	t	t	NOUN
fis-5022	120	30	x	x	X
fis-5022	120	31	y	y	PROPN
fis-5022	120	32	z	z	NOUN
fis-5022	120	33	x	x	PUNCT
fis-5022	120	34	y	y	NOUN
fis-5022	120	35	l	l	NOUN
fis-5022	120	36	x	x	PUNCT
fis-5022	120	37	l	l	NOUN
fis-5022	120	38	y	y	NOUN
fis-5022	120	39	l	l	NOUN
fis-5022	120	40	x	x	PUNCT
fis-5022	120	41	t	t	X
fis-5022	120	42	x	x	X
fis-5022	120	43	y	y	PROPN
fis-5022	120	44	z	z	PROPN
fis-5022	120	45	y	y	PROPN
fis-5022	120	46	x	x	X
fis-5022	120	47	l	l	NOUN
fis-5022	120	48	y	y	NOUN
fis-5022	120	49	l	l	NOUN
fis-5022	120	50	x	x	X
fis-5022	120	51	l	l	X
fis-5022	120	52	y	y	PROPN
fis-5022	120	53			ADJ
fis-5022	120	54			PROPN
fis-5022	120	55			ADJ
fis-5022	120	56			ADJ
fis-5022	120	57			NOUN
fis-5022	120	58			PROPN
fis-5022	120	59			NUM
fis-5022	121	1			NUM
fis-5022	122	1			PROPN
fis-5022	122	2			NOUN
fis-5022	122	3			PROPN
fis-5022	122	4			PROPN
fis-5022	122	5			NOUN
fis-5022	122	6			NUM
fis-5022	122	7			NUM
fis-5022	122	8			PROPN
fis-5022	122	9			NOUN
fis-5022	122	10			PROPN
fis-5022	122	11			PROPN
fis-5022	122	12			NOUN
fis-5022	122	13	(	(	PUNCT
fis-5022	122	14	9	9	NUM
fis-5022	122	15	)	)	SYM
fis-5022	122	16	1	1	NUM
fis-5022	122	17	(	(	PUNCT
fis-5022	122	18	,	,	PUNCT
fis-5022	122	19	,	,	PUNCT
fis-5022	122	20	,	,	PUNCT
fis-5022	122	21	)	)	PUNCT
fis-5022	122	22	(	(	PUNCT
fis-5022	122	23	,	,	PUNCT
fis-5022	122	24	,	,	PUNCT
fis-5022	122	25	,	,	PUNCT
fis-5022	122	26	)	)	PUNCT
fis-5022	122	27	i	i	PRON
fis-5022	122	28	it	it	PRON
fis-5022	122	29	x	x	VERB
fis-5022	122	30	y	y	NOUN
fis-5022	122	31	z	z	NOUN
fis-5022	122	32	t	t	PROPN
fis-5022	122	33	x	x	X
fis-5022	122	34	y	y	PROPN
fis-5022	122	35	z	z	INTJ
fis-5022	122	36			PROPN
fis-5022	122	37	and	and	CCONJ
fis-5022	122	38	1	1	NUM
fis-5022	122	39	1	1	NUM
fis-5022	122	40	(	(	PUNCT
fis-5022	122	41	,	,	PUNCT
fis-5022	122	42	,	,	PUNCT
fis-5022	122	43	,	,	PUNCT
fis-5022	122	44	)	)	PUNCT
fis-5022	122	45	(	(	PUNCT
fis-5022	122	46	,	,	PUNCT
fis-5022	122	47	,	,	PUNCT
fis-5022	122	48	,	,	PUNCT
fis-5022	122	49	)	)	PUNCT
fis-5022	122	50	j	j	PROPN
fis-5022	122	51	jq	jq	PROPN
fis-5022	122	52	gi	gi	INTJ
fis-5022	122	53	i	i	PRON
fis-5022	123	1	i	i	PRON
fis-5022	124	1	i	i	PRON
fis-5022	124	2	j	j	PROPN
fis-5022	125	1	j	j	PROPN
fis-5022	125	2	t	t	PROPN
fis-5022	125	3	x	x	PROPN
fis-5022	125	4	y	y	PROPN
fis-5022	125	5	z	z	PROPN
fis-5022	125	6	t	t	PROPN
fis-5022	125	7	x	x	PUNCT
fis-5022	126	1	y	y	PROPN
fis-5022	126	2	z	z	PROPN
fis-5022	126	3	k	k	PROPN
fis-5022	127	1	k	k	X
fis-5022	127	2	q	q	X
fis-5022	127	3	q	q	NOUN
fis-5022	127	4			ADJ
fis-5022	127	5			NOUN
fis-5022	127	6			ADJ
fis-5022	127	7			NOUN
fis-5022	127	8			ADJ
fis-5022	127	9			PROPN
fis-5022	127	10			PROPN
fis-5022	127	11			PROPN
fis-5022	127	12			PROPN
fis-5022	127	13			PROPN
fis-5022	127	14	(	(	PUNCT
fis-5022	127	15	10	10	NUM
fis-5022	127	16	)	)	PUNCT
fis-5022	127	17	a.	a.	NOUN
fis-5022	127	18	chulkov	chulkov	PROPN
fis-5022	127	19	et	et	PROPN
fis-5022	127	20	alii	alii	PROPN
fis-5022	127	21	,	,	PUNCT
fis-5022	127	22	frattura	frattura	PROPN
fis-5022	127	23	ed	ed	PROPN
fis-5022	127	24	integrità	integrità	PROPN
fis-5022	127	25	strutturale	strutturale	PROPN
fis-5022	127	26	,	,	PUNCT
fis-5022	127	27	70	70	NUM
fis-5022	127	28	(	(	PUNCT
fis-5022	127	29	2024	2024	NUM
fis-5022	127	30	)	)	PUNCT
fis-5022	127	31	177	177	NUM
fis-5022	127	32	-	-	SYM
fis-5022	127	33	191	191	NUM
fis-5022	127	34	;	;	PUNCT
fis-5022	127	35	doi	doi	NOUN
fis-5022	127	36	:	:	PUNCT
fis-5022	127	37	10.3221	10.3221	NUM
fis-5022	127	38	/	/	SYM
fis-5022	127	39	igf	igf	NOUN
fis-5022	127	40	-	-	ADJ
fis-5022	127	41	esis.70.10	esis.70.10	ADJ
fis-5022	127	42	182	182	NUM
fis-5022	127	43	here	here	ADV
fis-5022	127	44	:	:	PUNCT
fis-5022	127	45	it	it	PRON
fis-5022	127	46	is	be	AUX
fis-5022	127	47	the	the	DET
fis-5022	127	48	temperature	temperature	NOUN
fis-5022	127	49	in	in	ADP
fis-5022	127	50	the	the	DET
fis-5022	127	51	i	i	PROPN
fis-5022	127	52	-	-	PUNCT
fis-5022	127	53	th	th	PROPN
fis-5022	127	54	region	region	NOUN
fis-5022	127	55	counted	count	VERB
fis-5022	127	56	from	from	ADP
fis-5022	127	57	the	the	DET
fis-5022	127	58	initial	initial	ADJ
fis-5022	127	59	object	object	NOUN
fis-5022	127	60	temperature	temperature	NOUN
fis-5022	127	61	(	(	PUNCT
fis-5022	127	62	i	i	NOUN
fis-5022	127	63	=	=	NOUN
fis-5022	127	64	1	1	NUM
fis-5022	127	65	-	-	SYM
fis-5022	127	66	36	36	NUM
fis-5022	127	67	corresponds	correspond	NOUN
fis-5022	127	68	to	to	ADP
fis-5022	127	69	36	36	NUM
fis-5022	127	70	specimen	speciman	NOUN
fis-5022	127	71	layers	layer	NOUN
fis-5022	127	72	,	,	PUNCT
fis-5022	127	73	i	i	PRON
fis-5022	127	74	=	=	NOUN
fis-5022	127	75	37	37	NUM
fis-5022	127	76	-	-	SYM
fis-5022	127	77	76	76	NUM
fis-5022	127	78	corresponds	correspond	NOUN
fis-5022	127	79	to	to	ADP
fis-5022	127	80	40	40	NUM
fis-5022	127	81	defects	defect	NOUN
fis-5022	127	82	)	)	PUNCT
fis-5022	127	83	;	;	PUNCT
fis-5022	127	84	int	int	NOUN
fis-5022	127	85	is	be	AUX
fis-5022	127	86	the	the	DET
fis-5022	127	87	specimen	speciman	NOUN
fis-5022	127	88	initial	initial	ADJ
fis-5022	127	89	temperature	temperature	NOUN
fis-5022	127	90	;	;	PUNCT
fis-5022	127	91	,	,	PUNCT
fis-5022	127	92	j	j	PROPN
fis-5022	127	93	jq	jq	PROPN
fis-5022	127	94	q	q	PROPN
fis-5022	128	1	i	i	PRON
fis-5022	128	2	ik	ik	VERB
fis-5022	128	3	are	be	AUX
fis-5022	128	4	the	the	DET
fis-5022	128	5	thermal	thermal	ADJ
fis-5022	128	6	diffusivity	diffusivity	NOUN
fis-5022	128	7	and	and	CCONJ
fis-5022	128	8	the	the	DET
fis-5022	128	9	thermal	thermal	ADJ
fis-5022	128	10	conductivity	conductivity	NOUN
fis-5022	128	11	in	in	ADP
fis-5022	128	12	the	the	DET
fis-5022	128	13	i	i	PROPN
fis-5022	128	14	-	-	PUNCT
fis-5022	128	15	th	th	VERB
fis-5022	128	16	region	region	NOUN
fis-5022	128	17	by	by	ADP
fis-5022	128	18	the	the	DET
fis-5022	128	19	coordinate	coordinate	NOUN
fis-5022	128	20	jq	jq	PROPN
fis-5022	128	21	;	;	PUNCT
fis-5022	128	22	,	,	PUNCT
fis-5022	128	23	,	,	PUNCT
fis-5022	128	24	x	x	X
fis-5022	128	25	y	y	PROPN
fis-5022	128	26	z	z	PROPN
fis-5022	128	27	are	be	AUX
fis-5022	128	28	the	the	DET
fis-5022	128	29	cartesian	cartesian	ADJ
fis-5022	128	30	coordinates	coordinate	NOUN
fis-5022	128	31	;	;	PUNCT
fis-5022	128	32	jq	jq	PROPN
fis-5022	128	33	is	be	AUX
fis-5022	128	34	one	one	NUM
fis-5022	128	35	of	of	ADP
fis-5022	128	36	the	the	DET
fis-5022	128	37	cartesian	cartesian	ADJ
fis-5022	128	38	coordinates	coordinate	NOUN
fis-5022	128	39	,	,	PUNCT
fis-5022	128	40	x	x	PROPN
fis-5022	128	41	y	y	PROPN
fis-5022	128	42	or	or	CCONJ
fis-5022	128	43	z	z	PROPN
fis-5022	128	44	(	(	PUNCT
fis-5022	128	45	j	j	PROPN
fis-5022	128	46	=	=	NOUN
fis-5022	128	47	1	1	NUM
fis-5022	128	48	-	-	SYM
fis-5022	128	49	3	3	NUM
fis-5022	128	50	)	)	PUNCT
fis-5022	128	51	;	;	PUNCT
fis-5022	128	52			NOUN
fis-5022	128	53	is	be	AUX
fis-5022	128	54	the	the	DET
fis-5022	128	55	time	time	NOUN
fis-5022	128	56	;	;	PUNCT
fis-5022	128	57	(	(	PUNCT
fis-5022	128	58	,	,	PUNCT
fis-5022	128	59	,	,	PUNCT
fis-5022	128	60	)	)	PUNCT
fis-5022	128	61	q	q	X
fis-5022	129	1	x	x	X
fis-5022	129	2	y	y	NOUN
fis-5022	129	3			NOUN
fis-5022	129	4	is	be	AUX
fis-5022	129	5	the	the	DET
fis-5022	129	6	power	power	NOUN
fis-5022	129	7	density	density	NOUN
fis-5022	129	8	of	of	ADP
fis-5022	129	9	the	the	DET
fis-5022	129	10	absorbed	absorb	VERB
fis-5022	129	11	heat	heat	NOUN
fis-5022	129	12	flux	flux	NOUN
fis-5022	129	13	that	that	PRON
fis-5022	129	14	,	,	PUNCT
fis-5022	129	15	in	in	ADP
fis-5022	129	16	a	a	DET
fis-5022	129	17	general	general	ADJ
fis-5022	129	18	case	case	NOUN
fis-5022	129	19	,	,	PUNCT
fis-5022	129	20	varies	vary	VERB
fis-5022	129	21	in	in	ADP
fis-5022	129	22	both	both	DET
fis-5022	129	23	time	time	NOUN
fis-5022	129	24	and	and	CCONJ
fis-5022	129	25	space	space	NOUN
fis-5022	129	26	;	;	PUNCT
fis-5022	129	27	,	,	PUNCT
fis-5022	129	28	f	f	PROPN
fis-5022	129	29	rh	rh	PROPN
fis-5022	129	30	h	h	PROPN
fis-5022	129	31	are	be	AUX
fis-5022	129	32	the	the	DET
fis-5022	129	33	heat	heat	NOUN
fis-5022	129	34	exchange	exchange	NOUN
fis-5022	129	35	coefficients	coefficient	NOUN
fis-5022	129	36	on	on	ADP
fis-5022	129	37	a	a	DET
fis-5022	129	38	front	front	ADJ
fis-5022	129	39	and	and	CCONJ
fis-5022	129	40	rear	rear	ADJ
fis-5022	129	41	surface	surface	NOUN
fis-5022	129	42	respectively	respectively	ADV
fis-5022	129	43	;	;	PUNCT
fis-5022	129	44	these	these	DET
fis-5022	129	45	coefficients	coefficient	NOUN
fis-5022	129	46	combine	combine	VERB
fis-5022	129	47	both	both	CCONJ
fis-5022	129	48	the	the	DET
fis-5022	129	49	radiation	radiation	NOUN
fis-5022	129	50	and	and	CCONJ
fis-5022	129	51	convection	convection	NOUN
fis-5022	129	52	phenomenon	phenomenon	NOUN
fis-5022	129	53	;	;	PUNCT
fis-5022	129	54	m	m	VERB
fis-5022	129	55	is	be	AUX
fis-5022	129	56	the	the	DET
fis-5022	129	57	number	number	NOUN
fis-5022	129	58	of	of	ADP
fis-5022	129	59	layers	layer	NOUN
fis-5022	129	60	(	(	PUNCT
fis-5022	129	61	m	m	NOUN
fis-5022	129	62	=	=	NOUN
fis-5022	129	63	36	36	NUM
fis-5022	129	64	)	)	PUNCT
fis-5022	129	65	,	,	PUNCT
fis-5022	129	66	ambt	ambt	NOUN
fis-5022	129	67	is	be	AUX
fis-5022	129	68	the	the	DET
fis-5022	129	69	ambient	ambient	ADJ
fis-5022	129	70	temperature	temperature	NOUN
fis-5022	129	71	;	;	PUNCT
fis-5022	129	72	,	,	PUNCT
fis-5022	129	73	,	,	PUNCT
fis-5022	129	74	x	x	PROPN
fis-5022	129	75	y	y	PROPN
fis-5022	129	76	zl	zl	X
fis-5022	129	77	l	l	X
fis-5022	129	78	l	l	NOUN
fis-5022	129	79	are	be	AUX
fis-5022	129	80	the	the	DET
fis-5022	129	81	specimen	speciman	NOUN
fis-5022	129	82	dimensions	dimension	NOUN
fis-5022	129	83	.	.	PUNCT
fis-5022	130	1	eqn	eqn	PROPN
fis-5022	130	2	.	.	PUNCT
fis-5022	131	1	(	(	PUNCT
fis-5022	131	2	5	5	X
fis-5022	131	3	)	)	PUNCT
fis-5022	131	4	is	be	AUX
fis-5022	131	5	the	the	DET
fis-5022	131	6	3d	3d	NUM
fis-5022	131	7	parabolic	parabolic	NOUN
fis-5022	131	8	equation	equation	NOUN
fis-5022	131	9	of	of	ADP
fis-5022	131	10	heat	heat	NOUN
fis-5022	131	11	conduction	conduction	NOUN
fis-5022	131	12	;	;	PUNCT
fis-5022	131	13	eqn	eqn	PROPN
fis-5022	131	14	.	.	PUNCT
fis-5022	132	1	(	(	PUNCT
fis-5022	132	2	6	6	NUM
fis-5022	132	3	)	)	PUNCT
fis-5022	132	4	is	be	AUX
fis-5022	132	5	the	the	DET
fis-5022	132	6	initial	initial	ADJ
fis-5022	132	7	condition	condition	NOUN
fis-5022	132	8	;	;	PUNCT
fis-5022	132	9	eqn	eqn	PROPN
fis-5022	132	10	.	.	PUNCT
fis-5022	133	1	(	(	PUNCT
fis-5022	133	2	7	7	X
fis-5022	133	3	)	)	PUNCT
fis-5022	133	4	is	be	AUX
fis-5022	133	5	the	the	DET
fis-5022	133	6	boundary	boundary	ADJ
fis-5022	133	7	condition	condition	NOUN
fis-5022	133	8	on	on	ADP
fis-5022	133	9	a	a	DET
fis-5022	133	10	front	front	ADJ
fis-5022	133	11	surface	surface	NOUN
fis-5022	133	12	(	(	PUNCT
fis-5022	133	13	heating	heating	NOUN
fis-5022	133	14	and	and	CCONJ
fis-5022	133	15	cooling	cooling	NOUN
fis-5022	133	16	)	)	PUNCT
fis-5022	133	17	;	;	PUNCT
fis-5022	133	18	eqn	eqn	PROPN
fis-5022	133	19	.	.	PUNCT
fis-5022	134	1	(	(	PUNCT
fis-5022	134	2	8)	8)	NUM
fis-5022	134	3	is	be	AUX
fis-5022	134	4	the	the	DET
fis-5022	134	5	boundary	boundary	ADJ
fis-5022	134	6	condition	condition	NOUN
fis-5022	134	7	on	on	ADP
fis-5022	134	8	a	a	DET
fis-5022	134	9	rear	rear	ADJ
fis-5022	134	10	surface	surface	NOUN
fis-5022	134	11	(	(	PUNCT
fis-5022	134	12	cooling	cool	VERB
fis-5022	134	13	only	only	ADV
fis-5022	134	14	)	)	PUNCT
fis-5022	134	15	;	;	PUNCT
fis-5022	134	16	eqns	eqns	PROPN
fis-5022	134	17	.	.	PUNCT
fis-5022	135	1	(	(	PUNCT
fis-5022	135	2	9	9	X
fis-5022	135	3	)	)	PUNCT
fis-5022	135	4	are	be	AUX
fis-5022	135	5	the	the	DET
fis-5022	135	6	adiabatic	adiabatic	ADJ
fis-5022	135	7	conditions	condition	NOUN
fis-5022	135	8	on	on	ADP
fis-5022	135	9	side	side	NOUN
fis-5022	135	10	surfaces	surface	NOUN
fis-5022	135	11	by	by	ADP
fis-5022	135	12	the	the	DET
fis-5022	135	13	coordinates	coordinate	NOUN
fis-5022	135	14	x	x	PUNCT
fis-5022	135	15	and	and	CCONJ
fis-5022	135	16	y	y	PROPN
fis-5022	135	17	;	;	PUNCT
fis-5022	135	18	eqns	eqns	PROPN
fis-5022	135	19	.	.	PUNCT
fis-5022	136	1	(	(	PUNCT
fis-5022	136	2	10	10	NUM
fis-5022	136	3	)	)	PUNCT
fis-5022	136	4	are	be	AUX
fis-5022	136	5	the	the	DET
fis-5022	136	6	temperature	temperature	NOUN
fis-5022	136	7	and	and	CCONJ
fis-5022	136	8	heat	heat	NOUN
fis-5022	136	9	flux	flux	NOUN
fis-5022	136	10	continuity	continuity	NOUN
fis-5022	136	11	conditions	condition	NOUN
fis-5022	136	12	on	on	ADP
fis-5022	136	13	the	the	DET
fis-5022	136	14	boundaries	boundary	NOUN
fis-5022	136	15	between	between	ADP
fis-5022	136	16	layers	layer	NOUN
fis-5022	136	17	and	and	CCONJ
fis-5022	136	18	between	between	ADP
fis-5022	136	19	layers	layer	NOUN
fis-5022	136	20	and	and	CCONJ
fis-5022	136	21	defects	defect	NOUN
fis-5022	136	22	.	.	PUNCT
fis-5022	137	1	note	note	VERB
fis-5022	137	2	that	that	SCONJ
fis-5022	137	3	the	the	DET
fis-5022	137	4	thermocalc-3d	thermocalc-3d	NUM
fis-5022	137	5	allows	allow	VERB
fis-5022	137	6	modeling	model	VERB
fis-5022	137	7	a	a	DET
fis-5022	137	8	36	36	NUM
fis-5022	137	9	-	-	PUNCT
fis-5022	137	10	layer	layer	NOUN
fis-5022	137	11	plate	plate	NOUN
fis-5022	137	12	containing	contain	VERB
fis-5022	137	13	up	up	ADP
fis-5022	137	14	to	to	PART
fis-5022	137	15	40	40	NUM
fis-5022	137	16	parallelepiped	parallelepipe	VERB
fis-5022	137	17	-	-	PUNCT
fis-5022	137	18	like	like	ADJ
fis-5022	137	19	defects	defect	NOUN
fis-5022	137	20	.	.	PUNCT
fis-5022	138	1	in	in	ADP
fis-5022	138	2	this	this	DET
fis-5022	138	3	study	study	NOUN
fis-5022	138	4	,	,	PUNCT
fis-5022	138	5	a	a	DET
fis-5022	138	6	classical	classical	ADJ
fis-5022	138	7	1	1	NUM
fis-5022	138	8	-	-	PUNCT
fis-5022	138	9	layer	layer	NOUN
fis-5022	138	10	plate	plate	NOUN
fis-5022	138	11	with	with	ADP
fis-5022	138	12	4	4	NUM
fis-5022	138	13	defects	defect	NOUN
fis-5022	138	14	was	be	AUX
fis-5022	138	15	modeled	model	VERB
fis-5022	138	16	,	,	PUNCT
fis-5022	138	17	see	see	VERB
fis-5022	138	18	fig	fig	NOUN
fis-5022	138	19	.	.	PUNCT
fis-5022	139	1	1	1	X
fis-5022	139	2	.	.	PUNCT
fis-5022	139	3	by	by	ADP
fis-5022	139	4	using	use	VERB
fis-5022	139	5	a	a	DET
fis-5022	139	6	numerical	numerical	ADJ
fis-5022	139	7	grid	grid	NOUN
fis-5022	139	8	including	include	VERB
fis-5022	139	9	up	up	ADP
fis-5022	139	10	to	to	ADP
fis-5022	139	11	several	several	ADJ
fis-5022	139	12	million	million	NUM
fis-5022	139	13	nodes	node	NOUN
fis-5022	139	14	,	,	PUNCT
fis-5022	139	15	thermocalc-3d	thermocalc-3d	PRON
fis-5022	139	16	ensures	ensure	VERB
fis-5022	139	17	accuracy	accuracy	NOUN
fis-5022	139	18	of	of	ADP
fis-5022	139	19	calculating	calculate	VERB
fis-5022	139	20	non	non	ADJ
fis-5022	139	21	-	-	ADJ
fis-5022	139	22	defect	defect	ADJ
fis-5022	139	23	temperatures	temperature	NOUN
fis-5022	139	24	under	under	ADP
fis-5022	139	25	0.5	0.5	NUM
fis-5022	139	26	%	%	NOUN
fis-5022	139	27	and	and	CCONJ
fis-5022	139	28	defect	defect	VERB
fis-5022	139	29	temperatures	temperature	NOUN
fis-5022	139	30	under	under	ADP
fis-5022	139	31	3	3	NUM
fis-5022	139	32	%	%	NOUN
fis-5022	139	33	compared	compare	VERB
fis-5022	139	34	to	to	ADP
fis-5022	139	35	known	know	VERB
fis-5022	139	36	1d	1d	NUM
fis-5022	139	37	analytical	analytical	ADJ
fis-5022	139	38	solutions	solution	NOUN
fis-5022	139	39	.	.	PUNCT
fis-5022	140	1	the	the	DET
fis-5022	140	2	following	follow	VERB
fis-5022	140	3	model	model	NOUN
fis-5022	140	4	parameters	parameter	NOUN
fis-5022	140	5	were	be	AUX
fis-5022	140	6	chosen	choose	VERB
fis-5022	140	7	:	:	PUNCT
fis-5022	140	8	plate	plate	NOUN
fis-5022	140	9	lateral	lateral	ADJ
fis-5022	140	10	size	size	NOUN
fis-5022	140	11	50	50	NUM
fis-5022	140	12	x	x	SYM
fis-5022	140	13	50	50	NUM
fis-5022	140	14	mm	mm	NOUN
fis-5022	140	15	,	,	PUNCT
fis-5022	140	16	number	number	NOUN
fis-5022	140	17	of	of	ADP
fis-5022	140	18	numerical	numerical	ADJ
fis-5022	140	19	grid	grid	NOUN
fis-5022	140	20	steps	step	NOUN
fis-5022	140	21	by	by	ADP
fis-5022	140	22	x	x	PROPN
fis-5022	140	23	,	,	PUNCT
fis-5022	140	24	y	y	PROPN
fis-5022	140	25	,	,	PUNCT
fis-5022	140	26	z	z	NOUN
fis-5022	140	27	–	–	PUNCT
fis-5022	140	28	axes	axis	NOUN
fis-5022	140	29	50	50	NUM
fis-5022	140	30	x	x	SYM
fis-5022	140	31	50	50	NUM
fis-5022	140	32	x	x	SYM
fis-5022	140	33	100	100	NUM
fis-5022	140	34	,	,	PUNCT
fis-5022	140	35	lateral	lateral	ADJ
fis-5022	140	36	size	size	NOUN
fis-5022	140	37	of	of	ADP
fis-5022	140	38	defects	defect	NOUN
fis-5022	140	39	10	10	NUM
fis-5022	140	40	x	x	SYM
fis-5022	140	41	10	10	NUM
fis-5022	140	42	mm	mm	NOUN
fis-5022	140	43	;	;	PUNCT
fis-5022	140	44	defect	defect	VERB
fis-5022	140	45	thermal	thermal	ADJ
fis-5022	140	46	properties	property	NOUN
fis-5022	140	47	(	(	PUNCT
fis-5022	140	48	air	air	NOUN
fis-5022	140	49	):	):	PUNCT
fis-5022	141	1	k	k	PROPN
fis-5022	141	2	=	=	SYM
fis-5022	141	3	0.07	0.07	NUM
fis-5022	141	4	w.m-1.k-1	w.m-1.k-1	ADP
fis-5022	141	5	,	,	PUNCT
fis-5022	141	6			ADP
fis-5022	141	7	=	=	NUM
fis-5022	141	8	1.3	1.3	NUM
fis-5022	141	9	kg.m-3	kg.m-3	NOUN
fis-5022	141	10	,	,	PUNCT
fis-5022	141	11	c	c	X
fis-5022	141	12	=	=	PUNCT
fis-5022	141	13	928.4	928.4	NUM
fis-5022	141	14	j.kg-1.k-1	j.kg-1.k-1	NOUN
fis-5022	141	15	,	,	PUNCT
fis-5022	141	16	heat	heat	NOUN
fis-5022	141	17	time	time	NOUN
fis-5022	141	18	0.02	0.02	NUM
fis-5022	141	19	s	s	NOUN
fis-5022	141	20	(	(	PUNCT
fis-5022	141	21	square	square	ADJ
fis-5022	141	22	pulse	pulse	NOUN
fis-5022	141	23	)	)	PUNCT
fis-5022	141	24	,	,	PUNCT
fis-5022	141	25	time	time	NOUN
fis-5022	141	26	step	step	NOUN
fis-5022	141	27	0.02	0.02	NUM
fis-5022	141	28	s	s	NOUN
fis-5022	141	29	,	,	PUNCT
fis-5022	141	30	number	number	NOUN
fis-5022	141	31	of	of	ADP
fis-5022	141	32	collected	collect	VERB
fis-5022	141	33	frames	frame	NOUN
fis-5022	141	34	250	250	NUM
fis-5022	141	35	,	,	PUNCT
fis-5022	141	36	ambient	ambient	ADJ
fis-5022	141	37	and	and	CCONJ
fis-5022	141	38	initial	initial	ADJ
fis-5022	141	39	temperature	temperature	NOUN
fis-5022	141	40	0	0	NUM
fis-5022	141	41	°	°	NOUN
fis-5022	141	42	c	c	NOUN
fis-5022	141	43	,	,	PUNCT
fis-5022	141	44	and	and	CCONJ
fis-5022	141	45	spatial	spatial	ADJ
fis-5022	141	46	distribution	distribution	NOUN
fis-5022	141	47	of	of	ADP
fis-5022	141	48	the	the	DET
fis-5022	141	49	heat	heat	NOUN
fis-5022	141	50	pulse	pulse	NOUN
fis-5022	141	51	is	be	AUX
fis-5022	141	52	gaussian	gaussian	ADJ
fis-5022	141	53	:	:	PUNCT
fis-5022	141	54	2	2	NUM
fis-5022	141	55	2(x	2(x	NUM
fis-5022	141	56	x	x	X
fis-5022	141	57	)	)	PUNCT
fis-5022	141	58	(	(	PUNCT
fis-5022	141	59	y	y	PROPN
fis-5022	141	60	y)x	y)x	NOUN
fis-5022	142	1	o	o	PROPN
fis-5022	142	2	y	y	PROPN
fis-5022	142	3	o	o	INTJ
fis-5022	142	4	oq	oq	INTJ
fis-5022	142	5	q	q	PROPN
fis-5022	142	6	e	e	PROPN
fis-5022	142	7			PROPN
fis-5022	142	8			PROPN
fis-5022	142	9			PROPN
fis-5022	142	10			PROPN
fis-5022	142	11			PROPN
fis-5022	142	12	(	(	PUNCT
fis-5022	142	13	11	11	NUM
fis-5022	142	14	)	)	PUNCT
fis-5022	142	15	where	where	SCONJ
fis-5022	142	16	,	,	PUNCT
fis-5022	142	17	x	x	SYM
fis-5022	142	18	y	y	ADJ
fis-5022	142	19			NUM
fis-5022	142	20	coefficients	coefficient	NOUN
fis-5022	142	21	of	of	ADP
fis-5022	142	22	spatial	spatial	ADJ
fis-5022	142	23	distribution	distribution	NOUN
fis-5022	142	24	of	of	ADP
fis-5022	142	25	heat	heat	NOUN
fis-5022	142	26	pulse	pulse	NOUN
fis-5022	142	27	,	,	PUNCT
fis-5022	142	28	m-2	m-2	NOUN
fis-5022	142	29	,	,	PUNCT
fis-5022	142	30	o	o	PROPN
fis-5022	142	31	ox	ox	NOUN
fis-5022	142	32	y	y	PROPN
fis-5022	142	33			NOUN
fis-5022	142	34	25	25	NUM
fis-5022	142	35	mm	mm	PROPN
fis-5022	142	36	coordinates	coordinate	NOUN
fis-5022	142	37	of	of	ADP
fis-5022	142	38	heat	heat	NOUN
fis-5022	142	39	source	source	NOUN
fis-5022	142	40	center	center	NOUN
fis-5022	142	41	(	(	PUNCT
fis-5022	142	42	sample	sample	NOUN
fis-5022	142	43	center	center	NOUN
fis-5022	142	44	)	)	PUNCT
fis-5022	142	45	.	.	PUNCT
fis-5022	143	1	some	some	DET
fis-5022	143	2	model	model	NOUN
fis-5022	143	3	parameters	parameter	NOUN
fis-5022	143	4	presented	present	VERB
fis-5022	143	5	in	in	ADP
fis-5022	143	6	tab	tab	NOUN
fis-5022	143	7	.	.	PUNCT
fis-5022	143	8	1	1	NUM
fis-5022	143	9	varied	varied	ADJ
fis-5022	143	10	to	to	PART
fis-5022	143	11	produce	produce	VERB
fis-5022	143	12	different	different	ADJ
fis-5022	143	13	datasets	dataset	NOUN
fis-5022	143	14	.	.	PUNCT
fis-5022	144	1	the	the	DET
fis-5022	144	2	train	train	NOUN
fis-5022	144	3	1	1	NUM
fis-5022	144	4	-	-	SYM
fis-5022	144	5	6	6	NUM
fis-5022	144	6	datasets	dataset	NOUN
fis-5022	144	7	include	include	VERB
fis-5022	144	8	changeable	changeable	ADJ
fis-5022	144	9	model	model	NOUN
fis-5022	144	10	parameters	parameter	NOUN
fis-5022	144	11	,	,	PUNCT
fis-5022	144	12	such	such	ADJ
fis-5022	144	13	as	as	ADP
fis-5022	144	14	material	material	ADJ
fis-5022	144	15	thermal	thermal	ADJ
fis-5022	144	16	properties	property	NOUN
fis-5022	144	17	,	,	PUNCT
fis-5022	144	18	specimen	speciman	NOUN
fis-5022	144	19	thickness	thickness	NOUN
fis-5022	144	20	and	and	CCONJ
fis-5022	144	21	heating	heating	NOUN
fis-5022	144	22	power	power	NOUN
fis-5022	144	23	.	.	PUNCT
fis-5022	145	1	although	although	SCONJ
fis-5022	145	2	not	not	PART
fis-5022	145	3	all	all	DET
fis-5022	145	4	combinations	combination	NOUN
fis-5022	145	5	of	of	ADP
fis-5022	145	6	the	the	DET
fis-5022	145	7	parameters	parameter	NOUN
fis-5022	145	8	were	be	AUX
fis-5022	145	9	calculated	calculate	VERB
fis-5022	145	10	,	,	PUNCT
fis-5022	145	11	the	the	DET
fis-5022	145	12	total	total	ADJ
fis-5022	145	13	number	number	NOUN
fis-5022	145	14	of	of	ADP
fis-5022	145	15	datasets	dataset	NOUN
fis-5022	145	16	used	use	VERB
fis-5022	145	17	for	for	ADP
fis-5022	145	18	training	training	NOUN
fis-5022	145	19	reached	reach	VERB
fis-5022	145	20	63	63	NUM
fis-5022	145	21	.	.	PUNCT
fis-5022	146	1	the	the	DET
fis-5022	146	2	first	first	ADJ
fis-5022	146	3	training	training	NOUN
fis-5022	146	4	dataset	dataset	NOUN
fis-5022	146	5	(	(	PUNCT
fis-5022	146	6	train	train	NOUN
fis-5022	146	7	1	1	NUM
fis-5022	146	8	)	)	PUNCT
fis-5022	146	9	represented	represent	VERB
fis-5022	146	10	a	a	DET
fis-5022	146	11	particular	particular	ADJ
fis-5022	146	12	numerical	numerical	ADJ
fis-5022	146	13	model	model	NOUN
fis-5022	146	14	with	with	ADP
fis-5022	146	15	thermal	thermal	ADJ
fis-5022	146	16	properties	property	NOUN
fis-5022	146	17	corresponding	correspond	VERB
fis-5022	146	18	to	to	ADP
fis-5022	146	19	those	those	PRON
fis-5022	146	20	of	of	ADP
fis-5022	146	21	cfrp	cfrp	PROPN
fis-5022	146	22	.	.	PUNCT
fis-5022	147	1	train	train	NOUN
fis-5022	147	2	2	2	NUM
fis-5022	147	3	incorporated	incorporate	VERB
fis-5022	147	4	variations	variation	NOUN
fis-5022	147	5	in	in	ADP
fis-5022	147	6	heat	heat	NOUN
fis-5022	147	7	pulse	pulse	NOUN
fis-5022	147	8	energy	energy	NOUN
fis-5022	147	9	and	and	CCONJ
fis-5022	147	10	spatial	spatial	ADJ
fis-5022	147	11	distribution	distribution	NOUN
fis-5022	147	12	.	.	PUNCT
fis-5022	148	1	in	in	ADP
fis-5022	148	2	the	the	DET
fis-5022	148	3	train	train	NOUN
fis-5022	148	4	3	3	NUM
fis-5022	148	5	dataset	dataset	NOUN
fis-5022	148	6	,	,	PUNCT
fis-5022	148	7	sample	sample	NOUN
fis-5022	148	8	thickness	thickness	NOUN
fis-5022	148	9	,	,	PUNCT
fis-5022	148	10	heat	heat	NOUN
fis-5022	148	11	pulse	pulse	NOUN
fis-5022	148	12	power	power	NOUN
fis-5022	148	13	and	and	CCONJ
fis-5022	148	14	spatial	spatial	ADJ
fis-5022	148	15	distribution	distribution	NOUN
fis-5022	148	16	varied	varied	ADJ
fis-5022	148	17	.	.	PUNCT
fis-5022	149	1	as	as	SCONJ
fis-5022	149	2	mentioned	mention	VERB
fis-5022	149	3	above	above	ADV
fis-5022	149	4	,	,	PUNCT
fis-5022	149	5	not	not	PART
fis-5022	149	6	all	all	DET
fis-5022	149	7	combinations	combination	NOUN
fis-5022	149	8	of	of	ADP
fis-5022	149	9	input	input	NOUN
fis-5022	149	10	data	datum	NOUN
fis-5022	149	11	were	be	AUX
fis-5022	149	12	calculated	calculate	VERB
fis-5022	149	13	but	but	CCONJ
fis-5022	149	14	each	each	DET
fis-5022	149	15	parameter	parameter	NOUN
fis-5022	149	16	value	value	NOUN
fis-5022	149	17	occurred	occur	VERB
fis-5022	149	18	at	at	ADP
fis-5022	149	19	least	least	ADJ
fis-5022	149	20	once	once	ADV
fis-5022	149	21	.	.	PUNCT
fis-5022	150	1	for	for	ADP
fis-5022	150	2	instance	instance	NOUN
fis-5022	150	3	,	,	PUNCT
fis-5022	150	4	for	for	ADP
fis-5022	150	5	a	a	DET
fis-5022	150	6	sample	sample	NOUN
fis-5022	150	7	thickness	thickness	NOUN
fis-5022	150	8	of	of	ADP
fis-5022	150	9	1	1	NUM
fis-5022	150	10	mm	mm	NOUN
fis-5022	150	11	,	,	PUNCT
fis-5022	150	12	the	the	DET
fis-5022	150	13	heat	heat	NOUN
fis-5022	150	14	power	power	NOUN
fis-5022	150	15	was	be	AUX
fis-5022	150	16	set	set	VERB
fis-5022	150	17	at	at	ADP
fis-5022	150	18	200,000	200,000	NUM
fis-5022	150	19	w	w	NOUN
fis-5022	150	20	/	/	SYM
fis-5022	150	21	m²	m²	PROPN
fis-5022	150	22	,	,	PUNCT
fis-5022	150	23	and	and	CCONJ
fis-5022	150	24	the	the	DET
fis-5022	150	25	spatial	spatial	ADJ
fis-5022	150	26	distribution	distribution	NOUN
fis-5022	150	27	coefficients	coefficient	NOUN
fis-5022	150	28	were	be	AUX
fis-5022	150	29	50	50	NUM
fis-5022	150	30	m-2	m-2	NOUN
fis-5022	150	31	.	.	PUNCT
fis-5022	151	1	train	train	NOUN
fis-5022	151	2	4	4	NUM
fis-5022	151	3	introduced	introduce	VERB
fis-5022	151	4	variations	variation	NOUN
fis-5022	151	5	in	in	ADP
fis-5022	151	6	thermal	thermal	ADJ
fis-5022	151	7	conductivity	conductivity	NOUN
fis-5022	151	8	,	,	PUNCT
fis-5022	151	9	heat	heat	NOUN
fis-5022	151	10	power	power	NOUN
fis-5022	151	11	and	and	CCONJ
fis-5022	151	12	spatial	spatial	ADJ
fis-5022	151	13	distribution	distribution	NOUN
fis-5022	151	14	,	,	PUNCT
fis-5022	151	15	while	while	SCONJ
fis-5022	151	16	in	in	ADP
fis-5022	151	17	the	the	DET
fis-5022	151	18	train	train	NOUN
fis-5022	151	19	5	5	NUM
fis-5022	151	20	dataset	dataset	NOUN
fis-5022	151	21	,	,	PUNCT
fis-5022	151	22	there	there	PRON
fis-5022	151	23	were	be	VERB
fis-5022	151	24	three	three	NUM
fis-5022	151	25	combinations	combination	NOUN
fis-5022	151	26	of	of	ADP
fis-5022	151	27	sample	sample	NOUN
fis-5022	151	28	thickness	thickness	NOUN
fis-5022	151	29	,	,	PUNCT
fis-5022	151	30	two	two	NUM
fis-5022	151	31	combinations	combination	NOUN
fis-5022	151	32	of	of	ADP
fis-5022	151	33	heat	heat	NOUN
fis-5022	151	34	capacity	capacity	NOUN
fis-5022	151	35	and	and	CCONJ
fis-5022	151	36	density	density	NOUN
fis-5022	151	37	,	,	PUNCT
fis-5022	151	38	as	as	ADV
fis-5022	151	39	well	well	ADV
fis-5022	151	40	as	as	ADP
fis-5022	151	41	variations	variation	NOUN
fis-5022	151	42	in	in	ADP
fis-5022	151	43	thermal	thermal	ADJ
fis-5022	151	44	conductivity	conductivity	NOUN
fis-5022	151	45	,	,	PUNCT
fis-5022	151	46	heat	heat	NOUN
fis-5022	151	47	power	power	NOUN
fis-5022	151	48	and	and	CCONJ
fis-5022	151	49	spatial	spatial	ADJ
fis-5022	151	50	distribution	distribution	NOUN
fis-5022	151	51	.	.	PUNCT
fis-5022	152	1	the	the	DET
fis-5022	152	2	train	train	NOUN
fis-5022	152	3	6	6	NUM
fis-5022	152	4	dataset	dataset	NOUN
fis-5022	152	5	was	be	AUX
fis-5022	152	6	the	the	DET
fis-5022	152	7	most	most	ADV
fis-5022	152	8	comprehensive	comprehensive	ADJ
fis-5022	152	9	including	include	VERB
fis-5022	152	10	wide	wide	ADJ
fis-5022	152	11	-	-	PUNCT
fis-5022	152	12	range	range	NOUN
fis-5022	152	13	variations	variation	NOUN
fis-5022	152	14	in	in	ADP
fis-5022	152	15	sample	sample	NOUN
fis-5022	152	16	thickness	thickness	NOUN
fis-5022	152	17	,	,	PUNCT
fis-5022	152	18	thermal	thermal	ADJ
fis-5022	152	19	properties	property	NOUN
fis-5022	152	20	and	and	CCONJ
fis-5022	152	21	heat	heat	NOUN
fis-5022	152	22	power	power	NOUN
fis-5022	152	23	.	.	PUNCT
fis-5022	153	1	furthermore	furthermore	ADV
fis-5022	153	2	,	,	PUNCT
fis-5022	153	3	in	in	ADP
fis-5022	153	4	order	order	NOUN
fis-5022	153	5	to	to	PART
fis-5022	153	6	evaluate	evaluate	VERB
fis-5022	153	7	the	the	DET
fis-5022	153	8	training	training	NOUN
fis-5022	153	9	datasets	dataset	NOUN
fis-5022	153	10	,	,	PUNCT
fis-5022	153	11	three	three	NUM
fis-5022	153	12	additional	additional	ADJ
fis-5022	153	13	datasets	dataset	NOUN
fis-5022	153	14	of	of	ADP
fis-5022	153	15	varying	vary	VERB
fis-5022	153	16	complexity	complexity	NOUN
fis-5022	153	17	were	be	AUX
fis-5022	153	18	calculated	calculate	VERB
fis-5022	153	19	.	.	PUNCT
fis-5022	154	1	test	test	NOUN
fis-5022	154	2	1	1	NUM
fis-5022	154	3	represented	represent	VERB
fis-5022	154	4	the	the	DET
fis-5022	154	5	simplest	simple	ADJ
fis-5022	154	6	variant	variant	NOUN
fis-5022	154	7	comprising	comprise	VERB
fis-5022	154	8	a	a	DET
fis-5022	154	9	1	1	NUM
fis-5022	154	10	mm	mm	NOUN
fis-5022	154	11	-	-	PUNCT
fis-5022	154	12	thick	thick	ADJ
fis-5022	154	13	plate	plate	NOUN
fis-5022	154	14	(	(	PUNCT
fis-5022	154	15	similar	similar	ADJ
fis-5022	154	16	to	to	ADP
fis-5022	154	17	the	the	DET
fis-5022	154	18	training	training	NOUN
fis-5022	154	19	models	model	NOUN
fis-5022	154	20	)	)	PUNCT
fis-5022	154	21	but	but	CCONJ
fis-5022	154	22	with	with	ADP
fis-5022	154	23	slight	slight	ADJ
fis-5022	154	24	differences	difference	NOUN
fis-5022	154	25	in	in	ADP
fis-5022	154	26	thermal	thermal	ADJ
fis-5022	154	27	conductivity	conductivity	NOUN
fis-5022	154	28	,	,	PUNCT
fis-5022	154	29	defect	defect	NOUN
fis-5022	154	30	depth	depth	NOUN
fis-5022	154	31	and	and	CCONJ
fis-5022	154	32	heat	heat	NOUN
fis-5022	154	33	power	power	NOUN
fis-5022	154	34	,	,	PUNCT
fis-5022	154	35	to	to	PART
fis-5022	154	36	compare	compare	VERB
fis-5022	154	37	to	to	ADP
fis-5022	154	38	the	the	DET
fis-5022	154	39	first	first	ADJ
fis-5022	154	40	training	training	NOUN
fis-5022	154	41	dataset	dataset	NOUN
fis-5022	154	42	.	.	PUNCT
fis-5022	155	1	the	the	DET
fis-5022	155	2	second	second	ADJ
fis-5022	155	3	test	test	NOUN
fis-5022	155	4	2	2	NUM
fis-5022	155	5	dataset	dataset	NOUN
fis-5022	155	6	differed	differ	VERB
fis-5022	155	7	from	from	ADP
fis-5022	155	8	the	the	DET
fis-5022	155	9	respective	respective	ADJ
fis-5022	155	10	training	training	NOUN
fis-5022	155	11	model	model	NOUN
fis-5022	155	12	by	by	ADP
fis-5022	155	13	defect	defect	NOUN
fis-5022	155	14	depth	depth	NOUN
fis-5022	155	15	and	and	CCONJ
fis-5022	155	16	material	material	NOUN
fis-5022	155	17	thermal	thermal	ADJ
fis-5022	155	18	properties	property	NOUN
fis-5022	155	19	that	that	PRON
fis-5022	155	20	corresponded	correspond	VERB
fis-5022	155	21	to	to	ADP
fis-5022	155	22	1	1	NUM
fis-5022	155	23	mmthick	mmthick	NOUN
fis-5022	155	24	glass	glass	NOUN
fis-5022	155	25	fiber	fiber	NOUN
fis-5022	155	26	and	and	CCONJ
fis-5022	155	27	polyamide	polyamide	NOUN
fis-5022	155	28	composites	composite	NOUN
fis-5022	155	29	.	.	PUNCT
fis-5022	156	1	the	the	DET
fis-5022	156	2	test	test	NOUN
fis-5022	156	3	3	3	NUM
fis-5022	156	4	dataset	dataset	NOUN
fis-5022	156	5	was	be	AUX
fis-5022	156	6	most	most	ADV
fis-5022	156	7	complex	complex	ADJ
fis-5022	156	8	additionally	additionally	ADV
fis-5022	156	9	including	include	VERB
fis-5022	156	10	varying	vary	VERB
fis-5022	156	11	material	material	ADJ
fis-5022	156	12	thickness	thickness	NOUN
fis-5022	156	13	.	.	PUNCT
fis-5022	157	1	each	each	DET
fis-5022	157	2	pixel	pixel	NOUN
fis-5022	157	3	of	of	ADP
fis-5022	157	4	the	the	DET
fis-5022	157	5	calculated	calculate	VERB
fis-5022	157	6	ir	ir	NOUN
fis-5022	157	7	images	image	NOUN
fis-5022	157	8	was	be	AUX
fis-5022	157	9	categorized	categorize	VERB
fis-5022	157	10	as	as	ADP
fis-5022	157	11	related	relate	VERB
fis-5022	157	12	to	to	ADP
fis-5022	157	13	either	either	CCONJ
fis-5022	157	14	defect	defect	VERB
fis-5022	157	15	or	or	CCONJ
fis-5022	157	16	defect	defect	NOUN
fis-5022	157	17	-	-	PUNCT
fis-5022	157	18	free	free	ADJ
fis-5022	157	19	area	area	NOUN
fis-5022	157	20	.	.	PUNCT
fis-5022	158	1	the	the	DET
fis-5022	158	2	obtained	obtain	VERB
fis-5022	158	3	3d	3d	PROPN
fis-5022	158	4	ir	ir	PROPN
fis-5022	158	5	thermographic	thermographic	ADJ
fis-5022	158	6	sequences	sequence	NOUN
fis-5022	158	7	were	be	AUX
fis-5022	158	8	then	then	ADV
fis-5022	158	9	transformed	transform	VERB
fis-5022	158	10	into	into	ADP
fis-5022	158	11	2d	2d	NUM
fis-5022	158	12	matrices	matrix	NOUN
fis-5022	158	13	of	of	ADP
fis-5022	158	14	feature	feature	NOUN
fis-5022	158	15	vectors	vector	NOUN
fis-5022	158	16	for	for	ADP
fis-5022	158	17	model	model	NOUN
fis-5022	158	18	training	training	NOUN
fis-5022	158	19	and	and	CCONJ
fis-5022	158	20	testing	testing	NOUN
fis-5022	158	21	purposes	purpose	NOUN
fis-5022	158	22	.	.	PUNCT
fis-5022	159	1	each	each	DET
fis-5022	159	2	feature	feature	NOUN
fis-5022	159	3	vector	vector	NOUN
fis-5022	159	4	encapsulated	encapsulate	VERB
fis-5022	159	5	the	the	DET
fis-5022	159	6	temperature	temperature	NOUN
fis-5022	159	7	evolution	evolution	NOUN
fis-5022	159	8	of	of	ADP
fis-5022	159	9	an	an	DET
fis-5022	159	10	individual	individual	ADJ
fis-5022	159	11	pixel	pixel	NOUN
fis-5022	159	12	.	.	PUNCT
fis-5022	160	1	fig	fig	NOUN
fis-5022	160	2	.	.	PUNCT
fis-5022	161	1	2	2	NUM
fis-5022	161	2	represents	represent	VERB
fis-5022	161	3	the	the	DET
fis-5022	161	4	examples	example	NOUN
fis-5022	161	5	of	of	ADP
fis-5022	161	6	the	the	DET
fis-5022	161	7	simulated	simulate	VERB
fis-5022	161	8	thermograms	thermogram	NOUN
fis-5022	161	9	for	for	ADP
fis-5022	161	10	the	the	DET
fis-5022	161	11	train	train	NOUN
fis-5022	161	12	1	1	NUM
fis-5022	161	13	model	model	NOUN
fis-5022	161	14	.	.	PUNCT
fis-5022	162	1	a.	a.	PROPN
fis-5022	162	2	chulkov	chulkov	PROPN
fis-5022	162	3	et	et	PROPN
fis-5022	162	4	alii	alii	PROPN
fis-5022	162	5	,	,	PUNCT
fis-5022	162	6	frattura	frattura	PROPN
fis-5022	162	7	ed	ed	PROPN
fis-5022	162	8	integrità	integrità	PROPN
fis-5022	162	9	strutturale	strutturale	PROPN
fis-5022	162	10	,	,	PUNCT
fis-5022	162	11	70	70	NUM
fis-5022	162	12	(	(	PUNCT
fis-5022	162	13	2024	2024	NUM
fis-5022	162	14	)	)	PUNCT
fis-5022	162	15	177	177	NUM
fis-5022	162	16	-	-	SYM
fis-5022	162	17	191	191	NUM
fis-5022	162	18	;	;	PUNCT
fis-5022	162	19	doi	doi	NOUN
fis-5022	162	20	:	:	PUNCT
fis-5022	162	21	10.3221	10.3221	NUM
fis-5022	162	22	/	/	SYM
fis-5022	162	23	igf	igf	NOUN
fis-5022	162	24	-	-	ADJ
fis-5022	162	25	esis.70.10	esis.70.10	ADJ
fis-5022	162	26	183	183	NUM
fis-5022	162	27	dataset	dataset	NOUN
fis-5022	162	28	sample	sample	NOUN
fis-5022	162	29	thickness	thickness	NOUN
fis-5022	162	30	,	,	PUNCT
fis-5022	162	31	mm	mm	PROPN
fis-5022	162	32	density	density	NOUN
fis-5022	162	33	,	,	PUNCT
fis-5022	162	34	kg.m-3	kg.m-3	PROPN
fis-5022	162	35	,	,	PUNCT
fis-5022	162	36	and	and	CCONJ
fis-5022	162	37	heat	heat	NOUN
fis-5022	162	38	capacity	capacity	NOUN
fis-5022	162	39	,	,	PUNCT
fis-5022	162	40	j.kg-1.k-1	j.kg-1.k-1	ADP
fis-5022	162	41	conductivity	conductivity	NOUN
fis-5022	162	42	in	in	ADP
fis-5022	162	43	zdirection	zdirection	NOUN
fis-5022	162	44	,	,	PUNCT
fis-5022	162	45	w.m-1.k1	w.m-1.k1	PROPN
fis-5022	162	46	defect	defect	NOUN
fis-5022	162	47	depth	depth	NOUN
fis-5022	162	48	,	,	PUNCT
fis-5022	162	49	mm	mm	PROPN
fis-5022	162	50	defect	defect	NOUN
fis-5022	162	51	thickness	thickness	NOUN
fis-5022	162	52	,	,	PUNCT
fis-5022	162	53	mm	mm	NUM
fis-5022	162	54	heat	heat	NOUN
fis-5022	162	55	pulse	pulse	NOUN
fis-5022	162	56	spatial	spatial	ADJ
fis-5022	162	57	distribution	distribution	NOUN
fis-5022	162	58	,	,	PUNCT
fis-5022	162	59	x	x	SYM
fis-5022	162	60	y	y	PROPN
fis-5022	162	61			NUM
fis-5022	162	62	,	,	PUNCT
fis-5022	162	63	m-2	m-2	NOUN
fis-5022	162	64	maximum	maximum	PROPN
fis-5022	162	65	heat	heat	PROPN
fis-5022	162	66	pulse	pulse	NOUN
fis-5022	162	67	density	density	NOUN
fis-5022	162	68	,	,	PUNCT
fis-5022	162	69	w.m2	w.m2	NOUN
fis-5022	162	70	train	train	VERB
fis-5022	162	71	1	1	NUM
fis-5022	162	72	1	1	NUM
fis-5022	162	73	500	500	NUM
fis-5022	162	74	,	,	PUNCT
fis-5022	162	75	2462	2462	NUM
fis-5022	162	76	0.64	0.64	NUM
fis-5022	162	77	0.2	0.2	NUM
fis-5022	162	78	0.4	0.4	NUM
fis-5022	162	79	0.6	0.6	NUM
fis-5022	162	80	0.7	0.7	NUM
fis-5022	162	81	0.05	0.05	NUM
fis-5022	162	82	100	100	NUM
fis-5022	162	83	,	,	PUNCT
fis-5022	162	84	50	50	NUM
fis-5022	162	85	200	200	NUM
fis-5022	162	86	000	000	NUM
fis-5022	162	87	train	train	NOUN
fis-5022	162	88	2	2	NUM
fis-5022	162	89	1	1	NUM
fis-5022	162	90	500	500	NUM
fis-5022	162	91	,	,	PUNCT
fis-5022	162	92	2462	2462	NUM
fis-5022	162	93	0.64	0.64	NUM
fis-5022	162	94	0.2	0.2	NUM
fis-5022	162	95	0.4	0.4	NUM
fis-5022	162	96	0.6	0.6	NUM
fis-5022	162	97	0.7	0.7	NUM
fis-5022	162	98	0.05	0.05	NUM
fis-5022	162	99	50	50	NUM
fis-5022	162	100	,	,	PUNCT
fis-5022	162	101	50	50	NUM
fis-5022	162	102	100	100	NUM
fis-5022	162	103	,	,	PUNCT
fis-5022	162	104	100	100	NUM
fis-5022	162	105	150	150	NUM
fis-5022	162	106	000	000	NUM
fis-5022	162	107	200	200	NUM
fis-5022	162	108	000	000	NUM
fis-5022	162	109	250	250	NUM
fis-5022	162	110	000	000	NUM
fis-5022	162	111	300	300	NUM
fis-5022	162	112	000	000	NUM
fis-5022	162	113	350	350	NUM
fis-5022	162	114	000	000	NUM
fis-5022	162	115	400	400	NUM
fis-5022	162	116	000	000	NUM
fis-5022	162	117	train	train	VERB
fis-5022	162	118	3	3	NUM
fis-5022	162	119	1	1	NUM
fis-5022	162	120	2	2	NUM
fis-5022	162	121	3	3	NUM
fis-5022	162	122	4	4	NUM
fis-5022	162	123	5	5	NUM
fis-5022	162	124	10	10	NUM
fis-5022	162	125	15	15	NUM
fis-5022	162	126	500	500	NUM
fis-5022	162	127	,	,	PUNCT
fis-5022	162	128	2462	2462	NUM
fis-5022	162	129	0.64	0.64	NUM
fis-5022	162	130	0.2	0.2	NUM
fis-5022	162	131	0.4	0.4	NUM
fis-5022	162	132	0.6	0.6	NUM
fis-5022	162	133	0.7	0.7	NUM
fis-5022	162	134	0.05	0.05	NUM
fis-5022	162	135	50	50	NUM
fis-5022	162	136	,	,	PUNCT
fis-5022	162	137	50	50	NUM
fis-5022	162	138	100	100	NUM
fis-5022	162	139	,	,	PUNCT
fis-5022	162	140	100	100	NUM
fis-5022	162	141	150	150	NUM
fis-5022	162	142	000	000	NUM
fis-5022	162	143	200	200	NUM
fis-5022	162	144	000	000	NUM
fis-5022	162	145	250	250	NUM
fis-5022	162	146	000	000	NUM
fis-5022	162	147	300	300	NUM
fis-5022	162	148	000	000	NUM
fis-5022	162	149	350	350	NUM
fis-5022	162	150	000	000	NUM
fis-5022	162	151	400	400	NUM
fis-5022	162	152	000	000	NUM
fis-5022	162	153	train	train	VERB
fis-5022	162	154	4	4	NUM
fis-5022	162	155	1	1	NUM
fis-5022	162	156	500	500	NUM
fis-5022	162	157	,	,	PUNCT
fis-5022	162	158	2462	2462	NUM
fis-5022	162	159	0.1	0.1	NUM
fis-5022	162	160	0.3	0.3	NUM
fis-5022	162	161	0.5	0.5	NUM
fis-5022	162	162	0.7	0.7	NUM
fis-5022	162	163	0.9	0.9	NUM
fis-5022	162	164	1.1	1.1	NUM
fis-5022	162	165	0.2	0.2	NUM
fis-5022	162	166	0.4	0.4	NUM
fis-5022	162	167	0.6	0.6	NUM
fis-5022	162	168	0.7	0.7	NUM
fis-5022	162	169	0.05	0.05	NUM
fis-5022	162	170	50	50	NUM
fis-5022	162	171	,	,	PUNCT
fis-5022	162	172	50	50	NUM
fis-5022	162	173	100	100	NUM
fis-5022	162	174	,	,	PUNCT
fis-5022	162	175	100	100	NUM
fis-5022	162	176	150	150	NUM
fis-5022	162	177	000	000	NUM
fis-5022	162	178	200	200	NUM
fis-5022	162	179	000	000	NUM
fis-5022	162	180	250	250	NUM
fis-5022	162	181	000	000	NUM
fis-5022	162	182	300	300	NUM
fis-5022	162	183	000	000	NUM
fis-5022	162	184	350	350	NUM
fis-5022	162	185	000	000	NUM
fis-5022	162	186	400	400	NUM
fis-5022	162	187	000	000	NUM
fis-5022	162	188	train	train	VERB
fis-5022	162	189	5	5	NUM
fis-5022	162	190	1	1	NUM
fis-5022	162	191	3	3	NUM
fis-5022	162	192	5	5	NUM
fis-5022	162	193	500	500	NUM
fis-5022	162	194	,	,	PUNCT
fis-5022	162	195	2462	2462	NUM
fis-5022	162	196	2100	2100	NUM
fis-5022	162	197	,	,	PUNCT
fis-5022	162	198	800	800	NUM
fis-5022	162	199	0.1	0.1	NUM
fis-5022	162	200	0.3	0.3	NUM
fis-5022	162	201	0.5	0.5	NUM
fis-5022	162	202	0.7	0.7	NUM
fis-5022	162	203	0.9	0.9	NUM
fis-5022	162	204	0.2	0.2	NUM
fis-5022	162	205	0.4	0.4	NUM
fis-5022	162	206	0.6	0.6	NUM
fis-5022	162	207	0.7	0.7	NUM
fis-5022	162	208	0.05	0.05	NUM
fis-5022	162	209	0.1	0.1	NUM
fis-5022	162	210	50	50	NUM
fis-5022	162	211	,	,	PUNCT
fis-5022	162	212	50	50	NUM
fis-5022	162	213	100	100	NUM
fis-5022	162	214	,	,	PUNCT
fis-5022	162	215	100	100	NUM
fis-5022	162	216	150	150	NUM
fis-5022	162	217	000	000	NUM
fis-5022	162	218	200	200	NUM
fis-5022	162	219	000	000	NUM
fis-5022	162	220	250	250	NUM
fis-5022	162	221	000	000	NUM
fis-5022	162	222	300	300	NUM
fis-5022	162	223	000	000	NUM
fis-5022	162	224	350	350	NUM
fis-5022	162	225	000	000	NUM
fis-5022	162	226	400	400	NUM
fis-5022	162	227	000	000	NUM
fis-5022	162	228	train	train	VERB
fis-5022	162	229	6	6	NUM
fis-5022	162	230	1	1	NUM
fis-5022	162	231	3	3	NUM
fis-5022	162	232	5	5	NUM
fis-5022	162	233	7	7	NUM
fis-5022	162	234	10	10	NUM
fis-5022	162	235	500	500	NUM
fis-5022	162	236	,	,	PUNCT
fis-5022	162	237	2462	2462	NUM
fis-5022	162	238	800	800	NUM
fis-5022	162	239	,	,	PUNCT
fis-5022	162	240	2100	2100	NUM
fis-5022	162	241	800	800	NUM
fis-5022	162	242	,	,	PUNCT
fis-5022	162	243	3000	3000	NUM
fis-5022	162	244	900	900	NUM
fis-5022	162	245	,	,	PUNCT
fis-5022	162	246	4000	4000	NUM
fis-5022	162	247	0.1	0.1	NUM
fis-5022	162	248	0.3	0.3	NUM
fis-5022	162	249	0.5	0.5	NUM
fis-5022	162	250	0.9	0.9	NUM
fis-5022	162	251	1.2	1.2	NUM
fis-5022	162	252	1.5	1.5	NUM
fis-5022	162	253	0.2	0.2	NUM
fis-5022	162	254	0.4	0.4	NUM
fis-5022	162	255	0.6	0.6	NUM
fis-5022	162	256	0.7	0.7	NUM
fis-5022	162	257	0.05	0.05	NUM
fis-5022	162	258	0.1	0.1	NUM
fis-5022	162	259	50	50	NUM
fis-5022	162	260	,	,	PUNCT
fis-5022	162	261	50	50	NUM
fis-5022	162	262	100	100	NUM
fis-5022	162	263	,	,	PUNCT
fis-5022	162	264	100	100	NUM
fis-5022	162	265	150	150	NUM
fis-5022	162	266	000	000	NUM
fis-5022	162	267	200	200	NUM
fis-5022	162	268	000	000	NUM
fis-5022	162	269	250	250	NUM
fis-5022	162	270	000	000	NUM
fis-5022	162	271	300	300	NUM
fis-5022	162	272	000	000	NUM
fis-5022	162	273	350	350	NUM
fis-5022	162	274	000	000	NUM
fis-5022	162	275	400	400	NUM
fis-5022	162	276	000	000	NUM
fis-5022	162	277	test	test	NOUN
fis-5022	162	278	1	1	NUM
fis-5022	162	279	1	1	NUM
fis-5022	162	280	500	500	NUM
fis-5022	162	281	,	,	PUNCT
fis-5022	162	282	2462	2462	NUM
fis-5022	162	283	0.65	0.65	NUM
fis-5022	162	284	0.15	0.15	NUM
fis-5022	162	285	0.35	0.35	NUM
fis-5022	162	286	0.55	0.55	NUM
fis-5022	162	287	0.05	0.05	NUM
fis-5022	162	288	70	70	NUM
fis-5022	162	289	,	,	PUNCT
fis-5022	163	1	70	70	NUM
fis-5022	163	2	280	280	NUM
fis-5022	163	3	000	000	NUM
fis-5022	163	4	0.8	0.8	NUM
fis-5022	163	5	0.25	0.25	NUM
fis-5022	163	6	0.45	0.45	NUM
fis-5022	163	7	0.65	0.65	NUM
fis-5022	163	8	0.05	0.05	NUM
fis-5022	163	9	70	70	NUM
fis-5022	163	10	,	,	PUNCT
fis-5022	163	11	70	70	NUM
fis-5022	163	12	270	270	NUM
fis-5022	163	13	000	000	NUM
fis-5022	163	14	test	test	NOUN
fis-5022	163	15	2	2	NUM
fis-5022	163	16	1	1	NUM
fis-5022	163	17	1240	1240	NUM
fis-5022	163	18	,	,	PUNCT
fis-5022	163	19	1800	1800	NUM
fis-5022	163	20	0.13	0.13	NUM
fis-5022	163	21	0.15	0.15	NUM
fis-5022	163	22	0.35	0.35	NUM
fis-5022	163	23	0.55	0.55	NUM
fis-5022	163	24	0.1	0.1	NUM
fis-5022	163	25	70	70	NUM
fis-5022	163	26	,	,	PUNCT
fis-5022	163	27	70	70	NUM
fis-5022	163	28	270	270	NUM
fis-5022	163	29	000	000	NUM
fis-5022	163	30	1	1	NUM
fis-5022	163	31	1900	1900	NUM
fis-5022	163	32	,	,	PUNCT
fis-5022	163	33	1200	1200	NUM
fis-5022	163	34	0.3	0.3	NUM
fis-5022	163	35	0.15	0.15	NUM
fis-5022	163	36	0.35	0.35	NUM
fis-5022	163	37	0.55	0.55	NUM
fis-5022	163	38	0.05	0.05	NUM
fis-5022	163	39	70	70	NUM
fis-5022	163	40	,	,	PUNCT
fis-5022	163	41	70	70	NUM
fis-5022	163	42	230	230	NUM
fis-5022	163	43	000	000	NUM
fis-5022	163	44	test	test	NOUN
fis-5022	163	45	3	3	NUM
fis-5022	163	46	5	5	NUM
fis-5022	163	47	1240	1240	NUM
fis-5022	163	48	,	,	PUNCT
fis-5022	163	49	1800	1800	NUM
fis-5022	163	50	0.13	0.13	NUM
fis-5022	163	51	0.15	0.15	NUM
fis-5022	163	52	0.35	0.35	NUM
fis-5022	163	53	0.55	0.55	NUM
fis-5022	163	54	0.1	0.1	NUM
fis-5022	163	55	70	70	NUM
fis-5022	163	56	,	,	PUNCT
fis-5022	163	57	70	70	NUM
fis-5022	163	58	270	270	NUM
fis-5022	163	59	000	000	NUM
fis-5022	163	60	3	3	NUM
fis-5022	163	61	1900	1900	NUM
fis-5022	163	62	,	,	PUNCT
fis-5022	163	63	1200	1200	NUM
fis-5022	163	64	0.13	0.13	NUM
fis-5022	163	65	0.2	0.2	NUM
fis-5022	163	66	0.4	0.4	NUM
fis-5022	163	67	0.6	0.6	NUM
fis-5022	163	68	0.1	0.1	NUM
fis-5022	163	69	70	70	NUM
fis-5022	163	70	,	,	PUNCT
fis-5022	163	71	70	70	NUM
fis-5022	163	72	290	290	NUM
fis-5022	163	73	000	000	NUM
fis-5022	163	74	1.5	1.5	NUM
fis-5022	163	75	1240	1240	NUM
fis-5022	163	76	,	,	PUNCT
fis-5022	163	77	1800	1800	NUM
fis-5022	163	78	0.2	0.2	NUM
fis-5022	163	79	0.1	0.1	NUM
fis-5022	163	80	0.3	0.3	NUM
fis-5022	163	81	0.5	0.5	NUM
fis-5022	163	82	0.1	0.1	NUM
fis-5022	163	83	70	70	NUM
fis-5022	163	84	,	,	PUNCT
fis-5022	163	85	70	70	NUM
fis-5022	163	86	290	290	NUM
fis-5022	163	87	000	000	NUM
fis-5022	163	88	2	2	NUM
fis-5022	163	89	1900	1900	NUM
fis-5022	163	90	,	,	PUNCT
fis-5022	163	91	1200	1200	NUM
fis-5022	163	92	0.3	0.3	NUM
fis-5022	163	93	0.2	0.2	NUM
fis-5022	163	94	0.4	0.4	NUM
fis-5022	163	95	0.6	0.6	NUM
fis-5022	163	96	0.1	0.1	NUM
fis-5022	163	97	70	70	NUM
fis-5022	163	98	,	,	PUNCT
fis-5022	163	99	70	70	NUM
fis-5022	163	100	290	290	NUM
fis-5022	163	101	000	000	NUM
fis-5022	163	102	table	table	NOUN
fis-5022	163	103	1	1	NUM
fis-5022	163	104	:	:	PUNCT
fis-5022	163	105	numerical	numerical	ADJ
fis-5022	163	106	model	model	PROPN
fis-5022	163	107	parameters	parameter	NOUN
fis-5022	163	108	.	.	PUNCT
fis-5022	164	1	a.	a.	PROPN
fis-5022	164	2	chulkov	chulkov	PROPN
fis-5022	164	3	et	et	PROPN
fis-5022	164	4	alii	alii	PROPN
fis-5022	164	5	,	,	PUNCT
fis-5022	164	6	frattura	frattura	PROPN
fis-5022	164	7	ed	ed	PROPN
fis-5022	164	8	integrità	integrità	PROPN
fis-5022	164	9	strutturale	strutturale	PROPN
fis-5022	164	10	,	,	PUNCT
fis-5022	164	11	70	70	NUM
fis-5022	164	12	(	(	PUNCT
fis-5022	164	13	2024	2024	NUM
fis-5022	164	14	)	)	PUNCT
fis-5022	164	15	177	177	NUM
fis-5022	164	16	-	-	SYM
fis-5022	164	17	191	191	NUM
fis-5022	164	18	;	;	PUNCT
fis-5022	164	19	doi	doi	NOUN
fis-5022	164	20	:	:	PUNCT
fis-5022	164	21	10.3221	10.3221	NUM
fis-5022	164	22	/	/	SYM
fis-5022	164	23	igf	igf	NOUN
fis-5022	164	24	-	-	PUNCT
fis-5022	164	25	esis.70.10	esis.70.10	ADJ
fis-5022	164	26	184	184	NUM
fis-5022	164	27	a	a	NOUN
fis-5022	164	28	)	)	PUNCT
fis-5022	164	29	b	b	NOUN
fis-5022	164	30	)	)	PUNCT
fis-5022	164	31	c	c	NOUN
fis-5022	164	32	)	)	PUNCT
fis-5022	164	33	d	d	NOUN
fis-5022	164	34	)	)	PUNCT
fis-5022	164	35	figure	figure	NOUN
fis-5022	164	36	2	2	NUM
fis-5022	164	37	:	:	PUNCT
fis-5022	164	38	simulated	simulated	ADJ
fis-5022	164	39	thermograms	thermogram	NOUN
fis-5022	164	40	(	(	PUNCT
fis-5022	164	41	train	train	NOUN
fis-5022	164	42	1	1	NUM
fis-5022	164	43	dataset	dataset	NOUN
fis-5022	164	44	)	)	PUNCT
fis-5022	164	45	at	at	ADP
fis-5022	164	46	times	time	NOUN
fis-5022	164	47	0.3	0.3	NUM
fis-5022	164	48	s	s	PART
fis-5022	164	49	(	(	PUNCT
fis-5022	164	50	a	a	NOUN
fis-5022	164	51	)	)	PUNCT
fis-5022	164	52	,	,	PUNCT
fis-5022	164	53	0.7	0.7	NUM
fis-5022	164	54	s	s	NOUN
fis-5022	164	55	(	(	PUNCT
fis-5022	164	56	b	b	NOUN
fis-5022	164	57	)	)	PUNCT
fis-5022	164	58	,	,	PUNCT
fis-5022	164	59	1.5	1.5	NUM
fis-5022	164	60	s	s	PART
fis-5022	164	61	(	(	PUNCT
fis-5022	164	62	c	c	NOUN
fis-5022	164	63	)	)	PUNCT
fis-5022	164	64	and	and	CCONJ
fis-5022	164	65	5	5	NUM
fis-5022	164	66	s	s	NOUN
fis-5022	164	67	after	after	ADP
fis-5022	164	68	heating	heat	VERB
fis-5022	164	69	.	.	PUNCT
fis-5022	165	1	the	the	DET
fis-5022	165	2	temperature	temperature	NOUN
fis-5022	165	3	evolutions	evolution	NOUN
fis-5022	165	4	at	at	ADP
fis-5022	165	5	defect	defect	NOUN
fis-5022	165	6	and	and	CCONJ
fis-5022	165	7	non	non	ADJ
fis-5022	165	8	-	-	ADJ
fis-5022	165	9	defect	defect	ADJ
fis-5022	165	10	points	point	NOUN
fis-5022	165	11	are	be	AUX
fis-5022	165	12	presented	present	VERB
fis-5022	165	13	in	in	ADP
fis-5022	165	14	fig	fig	NOUN
fis-5022	165	15	.	.	PUNCT
fis-5022	166	1	3	3	NUM
fis-5022	166	2	in	in	ADP
fis-5022	166	3	the	the	DET
fis-5022	166	4	log	log	NOUN
fis-5022	166	5	-	-	PUNCT
fis-5022	166	6	log	log	NOUN
fis-5022	166	7	scale	scale	NOUN
fis-5022	166	8	.	.	PUNCT
fis-5022	167	1	the	the	DET
fis-5022	167	2	blue	blue	ADJ
fis-5022	167	3	curves	curve	NOUN
fis-5022	167	4	represent	represent	VERB
fis-5022	167	5	temperature	temperature	NOUN
fis-5022	167	6	evolutions	evolution	NOUN
fis-5022	167	7	over	over	ADP
fis-5022	167	8	the	the	DET
fis-5022	167	9	defect	defect	NOUN
fis-5022	167	10	centers	center	NOUN
fis-5022	167	11	.	.	PUNCT
fis-5022	168	1	the	the	DET
fis-5022	168	2	red	red	ADJ
fis-5022	168	3	curves	curve	NOUN
fis-5022	168	4	represent	represent	VERB
fis-5022	168	5	non	non	ADJ
fis-5022	168	6	-	-	ADJ
fis-5022	168	7	defect	defect	ADJ
fis-5022	168	8	temperature	temperature	NOUN
fis-5022	168	9	evolutions	evolution	NOUN
fis-5022	168	10	at	at	ADP
fis-5022	168	11	the	the	DET
fis-5022	168	12	corner	corner	NOUN
fis-5022	168	13	points	point	NOUN
fis-5022	168	14	,	,	PUNCT
fis-5022	168	15	in	in	ADP
fis-5022	168	16	the	the	DET
fis-5022	168	17	middle	middle	NOUN
fis-5022	168	18	of	of	ADP
fis-5022	168	19	the	the	DET
fis-5022	168	20	sample	sample	NOUN
fis-5022	168	21	and	and	CCONJ
fis-5022	168	22	between	between	ADP
fis-5022	168	23	the	the	DET
fis-5022	168	24	defects	defect	NOUN
fis-5022	168	25	.	.	PUNCT
fis-5022	169	1	figure	figure	VERB
fis-5022	169	2	3	3	NUM
fis-5022	169	3	:	:	PUNCT
fis-5022	169	4	modelled	model	VERB
fis-5022	169	5	temperature	temperature	NOUN
fis-5022	169	6	evolutions	evolution	NOUN
fis-5022	169	7	at	at	ADP
fis-5022	169	8	defect	defect	NOUN
fis-5022	169	9	(	(	PUNCT
fis-5022	169	10	blue	blue	ADJ
fis-5022	169	11	)	)	PUNCT
fis-5022	169	12	and	and	CCONJ
fis-5022	169	13	non	non	ADJ
fis-5022	169	14	-	-	ADJ
fis-5022	169	15	defect	defect	ADJ
fis-5022	169	16	(	(	PUNCT
fis-5022	169	17	red	red	ADJ
fis-5022	169	18	)	)	PUNCT
fis-5022	169	19	points	point	NOUN
fis-5022	169	20	(	(	PUNCT
fis-5022	169	21	log	log	NOUN
fis-5022	169	22	t	t	PROPN
fis-5022	169	23	vs.	vs.	X
fis-5022	169	24	log	log	PROPN
fis-5022	169	25	t	t	PROPN
fis-5022	169	26	)	)	PUNCT
fis-5022	169	27	.	.	PUNCT
fis-5022	170	1	a.	a.	PROPN
fis-5022	170	2	chulkov	chulkov	PROPN
fis-5022	170	3	et	et	PROPN
fis-5022	170	4	alii	alii	PROPN
fis-5022	170	5	,	,	PUNCT
fis-5022	170	6	frattura	frattura	PROPN
fis-5022	170	7	ed	ed	PROPN
fis-5022	170	8	integrità	integrità	PROPN
fis-5022	170	9	strutturale	strutturale	PROPN
fis-5022	170	10	,	,	PUNCT
fis-5022	170	11	70	70	NUM
fis-5022	170	12	(	(	PUNCT
fis-5022	170	13	2024	2024	NUM
fis-5022	170	14	)	)	PUNCT
fis-5022	170	15	177	177	NUM
fis-5022	170	16	-	-	SYM
fis-5022	170	17	191	191	NUM
fis-5022	170	18	;	;	PUNCT
fis-5022	170	19	doi	doi	NOUN
fis-5022	170	20	:	:	PUNCT
fis-5022	170	21	10.3221	10.3221	NUM
fis-5022	170	22	/	/	SYM
fis-5022	170	23	igf	igf	NOUN
fis-5022	170	24	-	-	ADJ
fis-5022	170	25	esis.70.10	esis.70.10	ADJ
fis-5022	170	26	185	185	NUM
fis-5022	170	27	evaluation	evaluation	NOUN
fis-5022	170	28	of	of	ADP
fis-5022	170	29	datasets	dataset	NOUN
fis-5022	170	30	and	and	CCONJ
fis-5022	170	31	models	model	NOUN
fis-5022	170	32	performance	performance	NOUN
fis-5022	170	33	gaussian	gaussian	ADJ
fis-5022	170	34	svm	svm	NOUN
fis-5022	170	35	and	and	CCONJ
fis-5022	170	36	bagged	bag	VERB
fis-5022	170	37	trees	tree	NOUN
fis-5022	170	38	models	model	NOUN
fis-5022	170	39	were	be	AUX
fis-5022	170	40	trained	train	VERB
fis-5022	170	41	using	use	VERB
fis-5022	170	42	the	the	DET
fis-5022	170	43	six	six	NUM
fis-5022	170	44	datasets	dataset	NOUN
fis-5022	170	45	(	(	PUNCT
fis-5022	170	46	train	train	NOUN
fis-5022	170	47	1	1	NUM
fis-5022	170	48	-	-	SYM
fis-5022	170	49	6	6	NUM
fis-5022	170	50	)	)	PUNCT
fis-5022	170	51	,	,	PUNCT
fis-5022	170	52	and	and	CCONJ
fis-5022	170	53	their	their	PRON
fis-5022	170	54	performance	performance	NOUN
fis-5022	170	55	was	be	AUX
fis-5022	170	56	assessed	assess	VERB
fis-5022	170	57	by	by	ADP
fis-5022	170	58	using	use	VERB
fis-5022	170	59	the	the	DET
fis-5022	170	60	validation	validation	NOUN
fis-5022	170	61	data	datum	NOUN
fis-5022	170	62	and	and	CCONJ
fis-5022	170	63	three	three	NUM
fis-5022	170	64	distinct	distinct	ADJ
fis-5022	170	65	test	test	NOUN
fis-5022	170	66	datasets	dataset	NOUN
fis-5022	170	67	(	(	PUNCT
fis-5022	170	68	test	test	NOUN
fis-5022	170	69	1	1	NUM
fis-5022	170	70	-	-	SYM
fis-5022	170	71	3	3	NUM
fis-5022	170	72	)	)	PUNCT
fis-5022	170	73	.	.	PUNCT
fis-5022	171	1	the	the	DET
fis-5022	171	2	validation	validation	NOUN
fis-5022	171	3	data	datum	NOUN
fis-5022	171	4	was	be	AUX
fis-5022	171	5	used	use	VERB
fis-5022	171	6	to	to	PART
fis-5022	171	7	evaluate	evaluate	VERB
fis-5022	171	8	the	the	DET
fis-5022	171	9	model	model	NOUN
fis-5022	171	10	at	at	ADP
fis-5022	171	11	the	the	DET
fis-5022	171	12	training	training	NOUN
fis-5022	171	13	phase	phase	NOUN
fis-5022	171	14	.	.	PUNCT
fis-5022	172	1	this	this	DET
fis-5022	172	2	data	datum	NOUN
fis-5022	172	3	was	be	AUX
fis-5022	172	4	not	not	PART
fis-5022	172	5	used	use	VERB
fis-5022	172	6	in	in	ADP
fis-5022	172	7	the	the	DET
fis-5022	172	8	very	very	ADJ
fis-5022	172	9	training	training	NOUN
fis-5022	172	10	process	process	NOUN
fis-5022	172	11	,	,	PUNCT
fis-5022	172	12	but	but	CCONJ
fis-5022	172	13	it	it	PRON
fis-5022	172	14	helped	help	VERB
fis-5022	172	15	to	to	PART
fis-5022	172	16	tune	tune	VERB
fis-5022	172	17	hyperparameters	hyperparameter	NOUN
fis-5022	172	18	and	and	CCONJ
fis-5022	172	19	prevent	prevent	VERB
fis-5022	172	20	overfitting	overfitting	NOUN
fis-5022	172	21	.	.	PUNCT
fis-5022	173	1	the	the	DET
fis-5022	173	2	models	model	NOUN
fis-5022	173	3	were	be	AUX
fis-5022	173	4	trained	train	VERB
fis-5022	173	5	by	by	ADP
fis-5022	173	6	a	a	DET
fis-5022	173	7	5	5	NUM
fis-5022	173	8	-	-	PUNCT
fis-5022	173	9	folds	fold	NOUN
fis-5022	173	10	cross	cross	ADJ
fis-5022	173	11	-	-	ADJ
fis-5022	173	12	validation	validation	ADJ
fis-5022	173	13	scheme	scheme	NOUN
fis-5022	173	14	.	.	PUNCT
fis-5022	174	1	this	this	PRON
fis-5022	174	2	means	mean	VERB
fis-5022	174	3	that	that	SCONJ
fis-5022	174	4	each	each	DET
fis-5022	174	5	train	train	NOUN
fis-5022	174	6	dataset	dataset	NOUN
fis-5022	174	7	was	be	AUX
fis-5022	174	8	randomly	randomly	ADV
fis-5022	174	9	divided	divide	VERB
fis-5022	174	10	into	into	ADP
fis-5022	174	11	5	5	NUM
fis-5022	174	12	subsets	subset	NOUN
fis-5022	174	13	of	of	ADP
fis-5022	174	14	approximately	approximately	ADV
fis-5022	174	15	equal	equal	ADJ
fis-5022	174	16	size	size	NOUN
fis-5022	174	17	.	.	PUNCT
fis-5022	175	1	each	each	DET
fis-5022	175	2	subset	subset	NOUN
fis-5022	175	3	represented	represent	VERB
fis-5022	175	4	a	a	DET
fis-5022	175	5	fold	fold	NOUN
fis-5022	175	6	.	.	PUNCT
fis-5022	176	1	the	the	DET
fis-5022	176	2	model	model	NOUN
fis-5022	176	3	was	be	AUX
fis-5022	176	4	trained	train	VERB
fis-5022	176	5	and	and	CCONJ
fis-5022	176	6	evaluated	evaluate	VERB
fis-5022	176	7	5	5	NUM
fis-5022	176	8	times	time	NOUN
fis-5022	176	9	,	,	PUNCT
fis-5022	176	10	each	each	DET
fis-5022	176	11	time	time	NOUN
fis-5022	176	12	using	use	VERB
fis-5022	176	13	a	a	DET
fis-5022	176	14	different	different	ADJ
fis-5022	176	15	fold	fold	NOUN
fis-5022	176	16	as	as	ADP
fis-5022	176	17	the	the	DET
fis-5022	176	18	validation	validation	NOUN
fis-5022	176	19	set	set	NOUN
fis-5022	176	20	and	and	CCONJ
fis-5022	176	21	the	the	DET
fis-5022	176	22	remaining	remain	VERB
fis-5022	176	23	4	4	NUM
fis-5022	176	24	folds	fold	NOUN
fis-5022	176	25	served	serve	VERB
fis-5022	176	26	as	as	ADP
fis-5022	176	27	the	the	DET
fis-5022	176	28	training	training	NOUN
fis-5022	176	29	set	set	NOUN
fis-5022	176	30	.	.	PUNCT
fis-5022	177	1	after	after	ADP
fis-5022	177	2	having	having	AUX
fis-5022	177	3	performed	perform	VERB
fis-5022	177	4	training	training	NOUN
fis-5022	177	5	on	on	ADP
fis-5022	177	6	the	the	DET
fis-5022	177	7	training	training	NOUN
fis-5022	177	8	set	set	NOUN
fis-5022	177	9	,	,	PUNCT
fis-5022	177	10	the	the	DET
fis-5022	177	11	model	model	NOUN
fis-5022	177	12	performance	performance	NOUN
fis-5022	177	13	was	be	AUX
fis-5022	177	14	evaluated	evaluate	VERB
fis-5022	177	15	on	on	ADP
fis-5022	177	16	the	the	DET
fis-5022	177	17	validation	validation	NOUN
fis-5022	177	18	set	set	NOUN
fis-5022	177	19	(	(	PUNCT
fis-5022	177	20	the	the	DET
fis-5022	177	21	remaining	remain	VERB
fis-5022	177	22	fold	fold	NOUN
fis-5022	177	23	)	)	PUNCT
fis-5022	177	24	to	to	PART
fis-5022	177	25	estimate	estimate	VERB
fis-5022	177	26	how	how	SCONJ
fis-5022	177	27	well	well	ADV
fis-5022	177	28	it	it	PRON
fis-5022	177	29	responded	respond	VERB
fis-5022	177	30	to	to	ADP
fis-5022	177	31	unseen	unseen	ADJ
fis-5022	177	32	data	datum	NOUN
fis-5022	177	33	.	.	PUNCT
fis-5022	178	1	finally	finally	ADV
fis-5022	178	2	,	,	PUNCT
fis-5022	178	3	the	the	DET
fis-5022	178	4	performance	performance	NOUN
fis-5022	178	5	metrics	metric	NOUN
fis-5022	178	6	(	(	PUNCT
fis-5022	178	7	true	true	ADJ
fis-5022	178	8	positive	positive	ADJ
fis-5022	178	9	rate	rate	NOUN
fis-5022	178	10	-	-	PUNCT
fis-5022	178	11	tpr	tpr	NOUN
fis-5022	178	12	and	and	CCONJ
fis-5022	178	13	true	true	ADJ
fis-5022	178	14	negative	negative	ADJ
fis-5022	178	15	rate	rate	NOUN
fis-5022	178	16	-	-	PUNCT
fis-5022	178	17	tnr	tnr	PROPN
fis-5022	178	18	)	)	PUNCT
fis-5022	178	19	obtained	obtain	VERB
fis-5022	178	20	from	from	ADP
fis-5022	178	21	5	5	NUM
fis-5022	178	22	iterations	iteration	NOUN
fis-5022	178	23	(	(	PUNCT
fis-5022	178	24	5	5	NUM
fis-5022	178	25	validation	validation	NOUN
fis-5022	178	26	sets	set	NOUN
fis-5022	178	27	)	)	PUNCT
fis-5022	178	28	were	be	AUX
fis-5022	178	29	averaged	average	VERB
fis-5022	178	30	to	to	PART
fis-5022	178	31	provide	provide	VERB
fis-5022	178	32	an	an	DET
fis-5022	178	33	overall	overall	ADJ
fis-5022	178	34	assessment	assessment	NOUN
fis-5022	178	35	of	of	ADP
fis-5022	178	36	the	the	DET
fis-5022	178	37	model	model	NOUN
fis-5022	178	38	performance	performance	NOUN
fis-5022	178	39	.	.	PUNCT
fis-5022	179	1	then	then	ADV
fis-5022	179	2	models	model	NOUN
fis-5022	179	3	were	be	AUX
fis-5022	179	4	trained	train	VERB
fis-5022	179	5	on	on	ADP
fis-5022	179	6	all	all	DET
fis-5022	179	7	train	train	NOUN
fis-5022	179	8	datasets	dataset	NOUN
fis-5022	179	9	and	and	CCONJ
fis-5022	179	10	evaluated	evaluate	VERB
fis-5022	179	11	by	by	ADP
fis-5022	179	12	test	test	NOUN
fis-5022	179	13	datasets	dataset	NOUN
fis-5022	179	14	.	.	PUNCT
fis-5022	180	1	to	to	PART
fis-5022	180	2	summarize	summarize	VERB
fis-5022	180	3	,	,	PUNCT
fis-5022	180	4	the	the	DET
fis-5022	180	5	validation	validation	NOUN
fis-5022	180	6	data	datum	NOUN
fis-5022	180	7	was	be	AUX
fis-5022	180	8	used	use	VERB
fis-5022	180	9	during	during	ADP
fis-5022	180	10	the	the	DET
fis-5022	180	11	training	training	NOUN
fis-5022	180	12	phase	phase	NOUN
fis-5022	180	13	to	to	PART
fis-5022	180	14	adjust	adjust	VERB
fis-5022	180	15	model	model	NOUN
fis-5022	180	16	parameters	parameter	NOUN
fis-5022	180	17	or	or	CCONJ
fis-5022	180	18	hyperparameters	hyperparameter	NOUN
fis-5022	180	19	and	and	CCONJ
fis-5022	180	20	also	also	ADV
fis-5022	180	21	prevent	prevent	VERB
fis-5022	180	22	overfitting	overfitting	NOUN
fis-5022	180	23	.	.	PUNCT
fis-5022	181	1	this	this	PRON
fis-5022	181	2	can	can	AUX
fis-5022	181	3	indirectly	indirectly	ADV
fis-5022	181	4	influence	influence	VERB
fis-5022	181	5	the	the	DET
fis-5022	181	6	performance	performance	NOUN
fis-5022	181	7	of	of	ADP
fis-5022	181	8	the	the	DET
fis-5022	181	9	model	model	NOUN
fis-5022	181	10	,	,	PUNCT
fis-5022	181	11	while	while	SCONJ
fis-5022	181	12	the	the	DET
fis-5022	181	13	test	test	NOUN
fis-5022	181	14	data	datum	NOUN
fis-5022	181	15	provided	provide	VERB
fis-5022	181	16	an	an	DET
fis-5022	181	17	independent	independent	ADJ
fis-5022	181	18	evaluation	evaluation	NOUN
fis-5022	181	19	of	of	ADP
fis-5022	181	20	the	the	DET
fis-5022	181	21	final	final	ADJ
fis-5022	181	22	model	model	NOUN
fis-5022	181	23	performance	performance	NOUN
fis-5022	181	24	on	on	ADP
fis-5022	181	25	new	new	ADJ
fis-5022	181	26	,	,	PUNCT
fis-5022	181	27	unseen	unseen	ADJ
fis-5022	181	28	data	datum	NOUN
fis-5022	181	29	.	.	PUNCT
fis-5022	182	1	the	the	DET
fis-5022	182	2	performance	performance	NOUN
fis-5022	182	3	of	of	ADP
fis-5022	182	4	two	two	NUM
fis-5022	182	5	machine	machine	NOUN
fis-5022	182	6	learning	learning	NOUN
fis-5022	182	7	models	model	NOUN
fis-5022	182	8	,	,	PUNCT
fis-5022	182	9	namely	namely	ADV
fis-5022	182	10	,	,	PUNCT
fis-5022	182	11	svm	svm	ADJ
fis-5022	182	12	and	and	CCONJ
fis-5022	182	13	bagged	bag	VERB
fis-5022	182	14	trees	tree	NOUN
fis-5022	182	15	ensemble	ensemble	ADJ
fis-5022	182	16	,	,	PUNCT
fis-5022	182	17	was	be	AUX
fis-5022	182	18	evaluated	evaluate	VERB
fis-5022	182	19	by	by	ADP
fis-5022	182	20	analyzing	analyze	VERB
fis-5022	182	21	different	different	ADJ
fis-5022	182	22	training	training	NOUN
fis-5022	182	23	and	and	CCONJ
fis-5022	182	24	testing	testing	NOUN
fis-5022	182	25	datasets	dataset	NOUN
fis-5022	182	26	.	.	PUNCT
fis-5022	183	1	the	the	DET
fis-5022	183	2	used	use	VERB
fis-5022	183	3	evaluation	evaluation	NOUN
fis-5022	183	4	metrics	metric	NOUN
fis-5022	183	5	included	include	VERB
fis-5022	183	6	sensitivity	sensitivity	NOUN
fis-5022	183	7	(	(	PUNCT
fis-5022	183	8	true	true	ADJ
fis-5022	183	9	positive	positive	ADJ
fis-5022	183	10	rate	rate	NOUN
fis-5022	183	11	,	,	PUNCT
fis-5022	183	12	tpr	tpr	NOUN
fis-5022	183	13	)	)	PUNCT
fis-5022	183	14	,	,	PUNCT
fis-5022	183	15	specificity	specificity	NOUN
fis-5022	183	16	(	(	PUNCT
fis-5022	183	17	true	true	ADJ
fis-5022	183	18	negative	negative	ADJ
fis-5022	183	19	rate	rate	NOUN
fis-5022	183	20	,	,	PUNCT
fis-5022	183	21	tnr	tnr	PROPN
fis-5022	183	22	)	)	PUNCT
fis-5022	183	23	,	,	PUNCT
fis-5022	183	24	and	and	CCONJ
fis-5022	183	25	precision	precision	NOUN
fis-5022	183	26	(	(	PUNCT
fis-5022	183	27	positive	positive	ADJ
fis-5022	183	28	predictive	predictive	ADJ
fis-5022	183	29	value	value	NOUN
fis-5022	183	30	,	,	PUNCT
fis-5022	183	31	ppv	ppv	NOUN
fis-5022	183	32	)	)	PUNCT
fis-5022	183	33	.	.	PUNCT
fis-5022	184	1	these	these	DET
fis-5022	184	2	metrics	metric	NOUN
fis-5022	184	3	were	be	AUX
fis-5022	184	4	chosen	choose	VERB
fis-5022	184	5	to	to	PART
fis-5022	184	6	give	give	VERB
fis-5022	184	7	a	a	DET
fis-5022	184	8	comprehensive	comprehensive	ADJ
fis-5022	184	9	understanding	understanding	NOUN
fis-5022	184	10	of	of	ADP
fis-5022	184	11	the	the	DET
fis-5022	184	12	model	model	NOUN
fis-5022	184	13	performance	performance	NOUN
fis-5022	184	14	in	in	ADP
fis-5022	184	15	detecting	detect	VERB
fis-5022	184	16	defects	defect	NOUN
fis-5022	184	17	.	.	PUNCT
fis-5022	185	1	the	the	DET
fis-5022	185	2	results	result	NOUN
fis-5022	185	3	are	be	AUX
fis-5022	185	4	presented	present	VERB
fis-5022	185	5	in	in	ADP
fis-5022	185	6	tabs	tab	NOUN
fis-5022	185	7	.	.	PUNCT
fis-5022	186	1	2	2	NUM
fis-5022	186	2	and	and	CCONJ
fis-5022	186	3	3	3	NUM
fis-5022	186	4	,	,	PUNCT
fis-5022	186	5	illustrating	illustrate	VERB
fis-5022	186	6	the	the	DET
fis-5022	186	7	model	model	NOUN
fis-5022	186	8	performance	performance	NOUN
fis-5022	186	9	across	across	ADP
fis-5022	186	10	various	various	ADJ
fis-5022	186	11	datasets	dataset	NOUN
fis-5022	186	12	.	.	PUNCT
fis-5022	187	1	since	since	SCONJ
fis-5022	187	2	in	in	ADP
fis-5022	187	3	many	many	ADJ
fis-5022	187	4	cases	case	NOUN
fis-5022	187	5	the	the	DET
fis-5022	187	6	tpr	tpr	NOUN
fis-5022	187	7	was	be	AUX
fis-5022	187	8	small	small	ADJ
fis-5022	187	9	,	,	PUNCT
fis-5022	187	10	some	some	DET
fis-5022	187	11	models	model	NOUN
fis-5022	187	12	classified	classify	VERB
fis-5022	187	13	all	all	DET
fis-5022	187	14	data	datum	NOUN
fis-5022	187	15	as	as	ADP
fis-5022	187	16	corresponding	correspond	VERB
fis-5022	187	17	to	to	ADP
fis-5022	187	18	defects	defect	NOUN
fis-5022	187	19	,	,	PUNCT
fis-5022	187	20	leading	lead	VERB
fis-5022	187	21	to	to	ADP
fis-5022	187	22	tpr	tpr	PROPN
fis-5022	187	23	and	and	CCONJ
fis-5022	187	24	tnr	tnr	PROPN
fis-5022	187	25	values	value	NOUN
fis-5022	187	26	of	of	ADP
fis-5022	187	27	100	100	NUM
fis-5022	187	28	and	and	CCONJ
fis-5022	187	29	0	0	NUM
fis-5022	187	30	,	,	PUNCT
fis-5022	187	31	respectively	respectively	ADV
fis-5022	187	32	.	.	PUNCT
fis-5022	188	1	in	in	ADP
fis-5022	188	2	these	these	DET
fis-5022	188	3	cases	case	NOUN
fis-5022	188	4	,	,	PUNCT
fis-5022	188	5	the	the	DET
fis-5022	188	6	tables	table	NOUN
fis-5022	188	7	indicate	indicate	VERB
fis-5022	188	8	zero	zero	NUM
fis-5022	188	9	values	value	NOUN
fis-5022	188	10	,	,	PUNCT
fis-5022	188	11	thus	thus	ADV
fis-5022	188	12	indicating	indicate	VERB
fis-5022	188	13	that	that	SCONJ
fis-5022	188	14	the	the	DET
fis-5022	188	15	model	model	NOUN
fis-5022	188	16	is	be	AUX
fis-5022	188	17	not	not	PART
fis-5022	188	18	appropriate	appropriate	ADJ
fis-5022	188	19	.	.	PUNCT
fis-5022	189	1	it	it	PRON
fis-5022	189	2	is	be	AUX
fis-5022	189	3	important	important	ADJ
fis-5022	189	4	to	to	PART
fis-5022	189	5	note	note	VERB
fis-5022	189	6	that	that	DET
fis-5022	189	7	accuracy	accuracy	NOUN
fis-5022	189	8	is	be	AUX
fis-5022	189	9	not	not	PART
fis-5022	189	10	a	a	DET
fis-5022	189	11	representative	representative	ADJ
fis-5022	189	12	metric	metric	NOUN
fis-5022	189	13	in	in	ADP
fis-5022	189	14	this	this	DET
fis-5022	189	15	context	context	NOUN
fis-5022	189	16	because	because	SCONJ
fis-5022	189	17	it	it	PRON
fis-5022	189	18	does	do	AUX
fis-5022	189	19	not	not	PART
fis-5022	189	20	account	account	VERB
fis-5022	189	21	for	for	ADP
fis-5022	189	22	the	the	DET
fis-5022	189	23	imbalance	imbalance	NOUN
fis-5022	189	24	between	between	ADP
fis-5022	189	25	defect	defect	NOUN
fis-5022	189	26	and	and	CCONJ
fis-5022	189	27	defect	defect	NOUN
fis-5022	189	28	-	-	PUNCT
fis-5022	189	29	free	free	ADJ
fis-5022	189	30	cases	case	NOUN
fis-5022	189	31	.	.	PUNCT
fis-5022	190	1	instead	instead	ADV
fis-5022	190	2	,	,	PUNCT
fis-5022	190	3	the	the	DET
fis-5022	190	4	metrics	metric	NOUN
fis-5022	190	5	like	like	ADP
fis-5022	190	6	tpr	tpr	PROPN
fis-5022	190	7	,	,	PUNCT
fis-5022	190	8	tnr	tnr	PROPN
fis-5022	190	9	,	,	PUNCT
fis-5022	190	10	and	and	CCONJ
fis-5022	190	11	precision	precision	NOUN
fis-5022	190	12	(	(	PUNCT
fis-5022	190	13	ppv	ppv	NOUN
fis-5022	190	14	)	)	PUNCT
fis-5022	190	15	provide	provide	VERB
fis-5022	190	16	a	a	DET
fis-5022	190	17	clearer	clear	ADJ
fis-5022	190	18	picture	picture	NOUN
fis-5022	190	19	of	of	ADP
fis-5022	190	20	model	model	NOUN
fis-5022	190	21	performance	performance	NOUN
fis-5022	190	22	in	in	ADP
fis-5022	190	23	detecting	detect	VERB
fis-5022	190	24	defects	defect	NOUN
fis-5022	190	25	.	.	PUNCT
fis-5022	191	1	sensitivity	sensitivity	NOUN
fis-5022	191	2	(	(	PUNCT
fis-5022	191	3	tpr)/	tpr)/	NOUN
fis-5022	191	4	specificity	specificity	NOUN
fis-5022	191	5	(	(	PUNCT
fis-5022	191	6	tnr)/precision	tnr)/precision	NOUN
fis-5022	191	7	(	(	PUNCT
fis-5022	191	8	ppv	ppv	NOUN
fis-5022	191	9	)	)	PUNCT
fis-5022	191	10	%	%	NOUN
fis-5022	191	11	dataset	dataset	NOUN
fis-5022	191	12	train	train	NOUN
fis-5022	191	13	1	1	NUM
fis-5022	191	14	train	train	NOUN
fis-5022	191	15	2	2	NUM
fis-5022	191	16	train	train	NOUN
fis-5022	191	17	3	3	NUM
fis-5022	191	18	train	train	NOUN
fis-5022	191	19	4	4	NUM
fis-5022	191	20	train	train	NOUN
fis-5022	191	21	5	5	NUM
fis-5022	191	22	train	train	NOUN
fis-5022	191	23	6	6	NUM
fis-5022	191	24	validation	validation	NOUN
fis-5022	191	25	99.8/100/99.9	99.8/100/99.9	NUM
fis-5022	192	1	78.4/99.9/93.2	78.4/99.9/93.2	NOUN
fis-5022	193	1	45.9/100/84.5	45.9/100/84.5	NUM
fis-5022	194	1	96.4/100/99.1	96.4/100/99.1	NUM
fis-5022	194	2	87.2/100/96.9	87.2/100/96.9	NUM
fis-5022	195	1	69/99.2/92.7	69/99.2/92.7	NUM
fis-5022	195	2	test	test	VERB
fis-5022	195	3	1	1	NUM
fis-5022	195	4	100/0/100	100/0/100	NUM
fis-5022	195	5	*	*	SYM
fis-5022	195	6	98/99.5/99.3	98/99.5/99.3	NUM
fis-5022	195	7	87.3/99.7/95.9	87.3/99.7/95.9	NUM
fis-5022	195	8	0/100/79.7	0/100/79.7	NOUN
fis-5022	196	1	86.6/100/95.6	86.6/100/95.6	NUM
fis-5022	196	2	62.5/100/88.7	62.5/100/88.7	NUM
fis-5022	196	3	test	test	NOUN
fis-5022	196	4	2	2	NUM
fis-5022	196	5	100/0/100	100/0/100	NUM
fis-5022	196	6	100/0/100	100/0/100	NUM
fis-5022	196	7	100/33.9/100	100/33.9/100	NUM
fis-5022	196	8	0/100/79.7	0/100/79.7	NOUN
fis-5022	196	9	82.5/99.6/95.7	82.5/99.6/95.7	PROPN
fis-5022	197	1	96.5/97.1/99.1	96.5/97.1/99.1	PROPN
fis-5022	197	2	test	test	NOUN
fis-5022	197	3	3	3	NUM
fis-5022	197	4	100/0/100	100/0/100	NUM
fis-5022	197	5	100/0/100	100/0/100	NUM
fis-5022	197	6	100/0/100	100/0/100	NUM
fis-5022	197	7	0/100/79.7	0/100/79.7	NOUN
fis-5022	197	8	75.9/90/91.7	75.9/90/91.7	NUM
fis-5022	198	1	84/80.3/93.6	84/80.3/93.6	NUM
fis-5022	198	2	table	table	NOUN
fis-5022	198	3	2	2	NUM
fis-5022	198	4	:	:	PUNCT
fis-5022	198	5	svm	svm	ADJ
fis-5022	198	6	model	model	NOUN
fis-5022	198	7	performance	performance	NOUN
fis-5022	198	8	for	for	ADP
fis-5022	198	9	different	different	ADJ
fis-5022	198	10	datasets	dataset	NOUN
fis-5022	198	11	.	.	PUNCT
fis-5022	199	1	sensitivity	sensitivity	NOUN
fis-5022	199	2	(	(	PUNCT
fis-5022	199	3	tpr)/	tpr)/	NOUN
fis-5022	199	4	specificity	specificity	NOUN
fis-5022	199	5	(	(	PUNCT
fis-5022	199	6	tnr)/precision	tnr)/precision	NOUN
fis-5022	199	7	(	(	PUNCT
fis-5022	199	8	ppv	ppv	NOUN
fis-5022	199	9	)	)	PUNCT
fis-5022	199	10	%	%	NOUN
fis-5022	199	11	dataset	dataset	NOUN
fis-5022	199	12	train	train	NOUN
fis-5022	199	13	1	1	NUM
fis-5022	199	14	train	train	NOUN
fis-5022	199	15	2	2	NUM
fis-5022	199	16	train	train	NOUN
fis-5022	199	17	3	3	NUM
fis-5022	199	18	train	train	NOUN
fis-5022	199	19	4	4	NUM
fis-5022	199	20	train	train	NOUN
fis-5022	199	21	5	5	NUM
fis-5022	199	22	train	train	NOUN
fis-5022	199	23	6	6	NUM
fis-5022	199	24	validation	validation	NOUN
fis-5022	199	25	99.5/99.8/99.8	99.5/99.8/99.8	PROPN
fis-5022	199	26	98.9/99.9/99.6	98.9/99.9/99.6	PROPN
fis-5022	199	27	99/99.8/99.6	99/99.8/99.6	NUM
fis-5022	199	28	99.8/100/99.9	99.8/100/99.9	NUM
fis-5022	199	29	99.4/100/99.9	99.4/100/99.9	NUM
fis-5022	199	30	96.9/99.4/99.2	96.9/99.4/99.2	PROPN
fis-5022	199	31	test	test	NOUN
fis-5022	199	32	1	1	NUM
fis-5022	199	33	100/0/100	100/0/100	NUM
fis-5022	199	34	26.5/68.8/73.2	26.5/68.8/73.2	PROPN
fis-5022	199	35	30.4/67.2/74	30.4/67.2/74	NUM
fis-5022	199	36	0/100/79.7	0/100/79.7	NOUN
fis-5022	199	37	55.6/52.5/77.7	55.6/52.5/77.7	PROPN
fis-5022	199	38	37/57.1/72.8	37/57.1/72.8	PROPN
fis-5022	199	39	test	test	VERB
fis-5022	199	40	2	2	NUM
fis-5022	199	41	100/1.6/100	100/1.6/100	NUM
fis-5022	199	42	100/0/100	100/0/100	NUM
fis-5022	199	43	100/0/100	100/0/100	NUM
fis-5022	199	44	0/100/79.7	0/100/79.7	NOUN
fis-5022	200	1	50/57.9/82	50/57.9/82	NOUN
fis-5022	200	2	100/6.4/100	100/6.4/100	NUM
fis-5022	200	3	test	test	NOUN
fis-5022	200	4	3	3	NUM
fis-5022	200	5	100/0/100	100/0/100	NUM
fis-5022	200	6	100/0/100	100/0/100	NUM
fis-5022	200	7	100/0/100	100/0/100	NUM
fis-5022	200	8	0/100/79.7	0/100/79.7	NOUN
fis-5022	201	1	82.6/40.9/87.4	82.6/40.9/87.4	NUM
fis-5022	201	2	87.7/40/90.5	87.7/40/90.5	NUM
fis-5022	201	3	table	table	NOUN
fis-5022	201	4	3	3	NUM
fis-5022	201	5	:	:	PUNCT
fis-5022	201	6	bagged	bag	VERB
fis-5022	201	7	trees	tree	NOUN
fis-5022	201	8	ensemble	ensemble	ADJ
fis-5022	201	9	model	model	NOUN
fis-5022	201	10	performance	performance	NOUN
fis-5022	201	11	for	for	ADP
fis-5022	201	12	different	different	ADJ
fis-5022	201	13	datasets	dataset	NOUN
fis-5022	201	14	.	.	PUNCT
fis-5022	202	1	the	the	DET
fis-5022	202	2	tables	table	NOUN
fis-5022	202	3	allow	allow	VERB
fis-5022	202	4	evaluating	evaluate	VERB
fis-5022	202	5	model	model	NOUN
fis-5022	202	6	performance	performance	NOUN
fis-5022	202	7	by	by	ADP
fis-5022	202	8	using	use	VERB
fis-5022	202	9	different	different	ADJ
fis-5022	202	10	training	training	NOUN
fis-5022	202	11	datasets	dataset	NOUN
fis-5022	202	12	.	.	PUNCT
fis-5022	203	1	the	the	DET
fis-5022	203	2	model	model	NOUN
fis-5022	203	3	trained	train	VERB
fis-5022	203	4	on	on	ADP
fis-5022	203	5	the	the	DET
fis-5022	203	6	results	result	NOUN
fis-5022	203	7	of	of	ADP
fis-5022	203	8	the	the	DET
fis-5022	203	9	single	single	ADJ
fis-5022	203	10	simulation	simulation	NOUN
fis-5022	203	11	with	with	ADP
fis-5022	203	12	the	the	DET
fis-5022	203	13	fixed	fix	VERB
fis-5022	203	14	parameters	parameter	NOUN
fis-5022	203	15	(	(	PUNCT
fis-5022	203	16	train	train	NOUN
fis-5022	203	17	1	1	NUM
fis-5022	203	18	)	)	PUNCT
fis-5022	203	19	failed	fail	VERB
fis-5022	203	20	on	on	ADP
fis-5022	203	21	all	all	DET
fis-5022	203	22	test	test	NOUN
fis-5022	203	23	datasets	dataset	NOUN
fis-5022	203	24	.	.	PUNCT
fis-5022	204	1	the	the	DET
fis-5022	204	2	introduction	introduction	NOUN
fis-5022	204	3	of	of	ADP
fis-5022	204	4	heat	heat	NOUN
fis-5022	204	5	power	power	NOUN
fis-5022	204	6	variations	variation	NOUN
fis-5022	204	7	in	in	ADP
fis-5022	204	8	the	the	DET
fis-5022	204	9	model	model	NOUN
fis-5022	204	10	yielded	yield	VERB
fis-5022	204	11	the	the	DET
fis-5022	204	12	best	good	ADJ
fis-5022	204	13	results	result	NOUN
fis-5022	204	14	for	for	ADP
fis-5022	204	15	the	the	DET
fis-5022	204	16	test	test	NOUN
fis-5022	204	17	1	1	NUM
fis-5022	204	18	dataset	dataset	VERB
fis-5022	204	19	with	with	ADP
fis-5022	204	20	slight	slight	ADJ
fis-5022	204	21	differences	difference	NOUN
fis-5022	204	22	in	in	ADP
fis-5022	204	23	the	the	DET
fis-5022	204	24	parameters	parameter	NOUN
fis-5022	204	25	,	,	PUNCT
fis-5022	204	26	but	but	CCONJ
fis-5022	204	27	it	it	PRON
fis-5022	204	28	failed	fail	VERB
fis-5022	204	29	to	to	PART
fis-5022	204	30	identify	identify	VERB
fis-5022	204	31	defects	defect	NOUN
fis-5022	204	32	in	in	ADP
fis-5022	204	33	more	more	ADJ
fis-5022	204	34	complex	complex	ADJ
fis-5022	204	35	cases	case	NOUN
fis-5022	204	36	(	(	PUNCT
fis-5022	204	37	test	test	NOUN
fis-5022	204	38	2	2	NUM
fis-5022	204	39	and	and	CCONJ
fis-5022	204	40	3	3	NUM
fis-5022	204	41	)	)	PUNCT
fis-5022	204	42	.	.	PUNCT
fis-5022	205	1	surprisingly	surprisingly	ADV
fis-5022	205	2	,	,	PUNCT
fis-5022	205	3	introducing	introduce	VERB
fis-5022	205	4	variations	variation	NOUN
fis-5022	205	5	in	in	ADP
fis-5022	205	6	plate	plate	NOUN
fis-5022	205	7	thickness	thickness	NOUN
fis-5022	205	8	(	(	PUNCT
fis-5022	205	9	train	train	NOUN
fis-5022	205	10	3	3	NUM
fis-5022	205	11	)	)	PUNCT
fis-5022	205	12	from	from	ADP
fis-5022	205	13	1	1	NUM
fis-5022	205	14	to	to	PART
fis-5022	205	15	15	15	NUM
fis-5022	205	16	mm	mm	NOUN
fis-5022	205	17	produced	produce	VERB
fis-5022	205	18	an	an	DET
fis-5022	205	19	adverse	adverse	ADJ
fis-5022	205	20	effect	effect	NOUN
fis-5022	205	21	,	,	PUNCT
fis-5022	205	22	causing	cause	VERB
fis-5022	205	23	the	the	DET
fis-5022	205	24	model	model	NOUN
fis-5022	205	25	to	to	PART
fis-5022	205	26	perform	perform	VERB
fis-5022	205	27	worse	bad	ADJ
fis-5022	205	28	even	even	ADV
fis-5022	205	29	on	on	ADP
fis-5022	205	30	the	the	DET
fis-5022	205	31	validation	validation	NOUN
fis-5022	205	32	dataset	dataset	NOUN
fis-5022	205	33	.	.	PUNCT
fis-5022	206	1	a	a	DET
fis-5022	206	2	a.	a.	NOUN
fis-5022	206	3	chulkov	chulkov	NOUN
fis-5022	206	4	et	et	PROPN
fis-5022	206	5	alii	alii	PROPN
fis-5022	206	6	,	,	PUNCT
fis-5022	206	7	frattura	frattura	PROPN
fis-5022	206	8	ed	ed	PROPN
fis-5022	206	9	integrità	integrità	PROPN
fis-5022	206	10	strutturale	strutturale	PROPN
fis-5022	206	11	,	,	PUNCT
fis-5022	206	12	70	70	NUM
fis-5022	206	13	(	(	PUNCT
fis-5022	206	14	2024	2024	NUM
fis-5022	206	15	)	)	PUNCT
fis-5022	206	16	177	177	NUM
fis-5022	206	17	-	-	SYM
fis-5022	206	18	191	191	NUM
fis-5022	206	19	;	;	PUNCT
fis-5022	206	20	doi	doi	NOUN
fis-5022	206	21	:	:	PUNCT
fis-5022	206	22	10.3221	10.3221	NUM
fis-5022	206	23	/	/	SYM
fis-5022	206	24	igf	igf	NOUN
fis-5022	206	25	-	-	PUNCT
fis-5022	206	26	esis.70.10	esis.70.10	ADJ
fis-5022	206	27	186	186	NUM
fis-5022	206	28	similarly	similarly	ADV
fis-5022	206	29	,	,	PUNCT
fis-5022	206	30	the	the	DET
fis-5022	206	31	introduction	introduction	NOUN
fis-5022	206	32	of	of	ADP
fis-5022	206	33	variations	variation	NOUN
fis-5022	206	34	in	in	ADP
fis-5022	206	35	thermal	thermal	ADJ
fis-5022	206	36	conductivity	conductivity	NOUN
fis-5022	206	37	(	(	PUNCT
fis-5022	206	38	train	train	NOUN
fis-5022	206	39	4	4	NUM
fis-5022	206	40	)	)	PUNCT
fis-5022	206	41	did	do	AUX
fis-5022	206	42	not	not	PART
fis-5022	206	43	improve	improve	VERB
fis-5022	206	44	model	model	NOUN
fis-5022	206	45	performance	performance	NOUN
fis-5022	206	46	not	not	PART
fis-5022	206	47	only	only	ADV
fis-5022	206	48	on	on	ADP
fis-5022	206	49	test	test	NOUN
fis-5022	206	50	1	1	NUM
fis-5022	206	51	dataset	dataset	VERB
fis-5022	206	52	1	1	NUM
fis-5022	206	53	but	but	CCONJ
fis-5022	206	54	also	also	ADV
fis-5022	206	55	failed	fail	VERB
fis-5022	206	56	to	to	PART
fis-5022	206	57	identify	identify	VERB
fis-5022	206	58	defects	defect	NOUN
fis-5022	206	59	in	in	ADP
fis-5022	206	60	test	test	NOUN
fis-5022	206	61	2	2	NUM
fis-5022	206	62	and	and	CCONJ
fis-5022	206	63	3	3	NUM
fis-5022	206	64	datasets	dataset	NOUN
fis-5022	206	65	.	.	PUNCT
fis-5022	207	1	this	this	PRON
fis-5022	207	2	shows	show	VERB
fis-5022	207	3	that	that	SCONJ
fis-5022	207	4	varying	vary	VERB
fis-5022	207	5	only	only	ADJ
fis-5022	207	6	thermal	thermal	ADJ
fis-5022	207	7	conductivity	conductivity	NOUN
fis-5022	207	8	is	be	AUX
fis-5022	207	9	not	not	PART
fis-5022	207	10	sufficient	sufficient	ADJ
fis-5022	207	11	to	to	PART
fis-5022	207	12	generalize	generalize	VERB
fis-5022	207	13	the	the	DET
fis-5022	207	14	model	model	NOUN
fis-5022	207	15	onto	onto	ADP
fis-5022	207	16	different	different	ADJ
fis-5022	207	17	materials	material	NOUN
fis-5022	207	18	,	,	PUNCT
fis-5022	207	19	see	see	VERB
fis-5022	207	20	train	train	NOUN
fis-5022	207	21	2	2	NUM
fis-5022	207	22	.	.	PUNCT
fis-5022	208	1	the	the	DET
fis-5022	208	2	most	most	ADV
fis-5022	208	3	promising	promising	ADJ
fis-5022	208	4	results	result	NOUN
fis-5022	208	5	were	be	AUX
fis-5022	208	6	achieved	achieve	VERB
fis-5022	208	7	by	by	ADP
fis-5022	208	8	training	train	VERB
fis-5022	208	9	the	the	DET
fis-5022	208	10	model	model	NOUN
fis-5022	208	11	on	on	ADP
fis-5022	208	12	the	the	DET
fis-5022	208	13	train	train	NOUN
fis-5022	208	14	5	5	NUM
fis-5022	208	15	dataset	dataset	NOUN
fis-5022	208	16	,	,	PUNCT
fis-5022	208	17	which	which	PRON
fis-5022	208	18	included	include	VERB
fis-5022	208	19	slight	slight	ADJ
fis-5022	208	20	variations	variation	NOUN
fis-5022	208	21	in	in	ADP
fis-5022	208	22	sample	sample	NOUN
fis-5022	208	23	thickness	thickness	NOUN
fis-5022	208	24	(	(	PUNCT
fis-5022	208	25	from	from	ADP
fis-5022	208	26	1	1	NUM
fis-5022	208	27	to	to	PART
fis-5022	208	28	5	5	NUM
fis-5022	208	29	mm	mm	NOUN
fis-5022	208	30	)	)	PUNCT
fis-5022	208	31	and	and	CCONJ
fis-5022	208	32	thermal	thermal	ADJ
fis-5022	208	33	conductivity	conductivity	NOUN
fis-5022	208	34	(	(	PUNCT
fis-5022	208	35	from	from	ADP
fis-5022	208	36	0.2	0.2	NUM
fis-5022	208	37	to	to	ADP
fis-5022	208	38	0.7	0.7	NUM
fis-5022	208	39	w.m-1.k-1	w.m-1.k-1	NOUN
fis-5022	208	40	)	)	PUNCT
fis-5022	208	41	.	.	PUNCT
fis-5022	209	1	additionally	additionally	ADV
fis-5022	209	2	,	,	PUNCT
fis-5022	209	3	it	it	PRON
fis-5022	209	4	introduced	introduce	VERB
fis-5022	209	5	the	the	DET
fis-5022	209	6	combination	combination	NOUN
fis-5022	209	7	of	of	ADP
fis-5022	209	8	density	density	NOUN
fis-5022	209	9	and	and	CCONJ
fis-5022	209	10	heat	heat	NOUN
fis-5022	209	11	capacity	capacity	NOUN
fis-5022	209	12	not	not	PART
fis-5022	209	13	present	present	ADJ
fis-5022	209	14	in	in	ADP
fis-5022	209	15	the	the	DET
fis-5022	209	16	test	test	NOUN
fis-5022	209	17	data	datum	NOUN
fis-5022	209	18	.	.	PUNCT
fis-5022	210	1	this	this	DET
fis-5022	210	2	model	model	NOUN
fis-5022	210	3	effectively	effectively	ADV
fis-5022	210	4	identified	identify	VERB
fis-5022	210	5	most	most	ADJ
fis-5022	210	6	of	of	ADP
fis-5022	210	7	defects	defect	NOUN
fis-5022	210	8	across	across	ADP
fis-5022	210	9	all	all	DET
fis-5022	210	10	test	test	NOUN
fis-5022	210	11	datasets	dataset	NOUN
fis-5022	210	12	.	.	PUNCT
fis-5022	211	1	however	however	ADV
fis-5022	211	2	,	,	PUNCT
fis-5022	211	3	the	the	DET
fis-5022	211	4	use	use	NOUN
fis-5022	211	5	of	of	ADP
fis-5022	211	6	the	the	DET
fis-5022	211	7	training	training	NOUN
fis-5022	211	8	dataset	dataset	VERB
fis-5022	211	9	with	with	ADP
fis-5022	211	10	a	a	DET
fis-5022	211	11	greater	great	ADJ
fis-5022	211	12	variability	variability	NOUN
fis-5022	211	13	in	in	ADP
fis-5022	211	14	model	model	NOUN
fis-5022	211	15	parameters	parameter	NOUN
fis-5022	211	16	(	(	PUNCT
fis-5022	211	17	train	train	NOUN
fis-5022	211	18	6	6	NUM
fis-5022	211	19	)	)	PUNCT
fis-5022	211	20	resulted	result	VERB
fis-5022	211	21	in	in	ADP
fis-5022	211	22	a	a	DET
fis-5022	211	23	worse	bad	ADJ
fis-5022	211	24	performance	performance	NOUN
fis-5022	211	25	for	for	ADP
fis-5022	211	26	validation	validation	NOUN
fis-5022	211	27	and	and	CCONJ
fis-5022	211	28	test	test	NOUN
fis-5022	211	29	1	1	NUM
fis-5022	211	30	datasets	dataset	NOUN
fis-5022	211	31	.	.	PUNCT
fis-5022	212	1	tab	tab	NOUN
fis-5022	212	2	.	.	PUNCT
fis-5022	213	1	2	2	NUM
fis-5022	213	2	demonstrates	demonstrate	VERB
fis-5022	213	3	that	that	SCONJ
fis-5022	213	4	increasing	increase	VERB
fis-5022	213	5	the	the	DET
fis-5022	213	6	size	size	NOUN
fis-5022	213	7	and	and	CCONJ
fis-5022	213	8	variation	variation	NOUN
fis-5022	213	9	of	of	ADP
fis-5022	213	10	the	the	DET
fis-5022	213	11	training	training	NOUN
fis-5022	213	12	data	datum	NOUN
fis-5022	213	13	can	can	AUX
fis-5022	213	14	negatively	negatively	ADV
fis-5022	213	15	affect	affect	VERB
fis-5022	213	16	the	the	DET
fis-5022	213	17	results	result	NOUN
fis-5022	213	18	obtained	obtain	VERB
fis-5022	213	19	on	on	ADP
fis-5022	213	20	both	both	CCONJ
fis-5022	213	21	the	the	DET
fis-5022	213	22	validation	validation	NOUN
fis-5022	213	23	data	datum	NOUN
fis-5022	213	24	and	and	CCONJ
fis-5022	213	25	the	the	DET
fis-5022	213	26	data	datum	NOUN
fis-5022	213	27	not	not	PART
fis-5022	213	28	very	very	ADV
fis-5022	213	29	different	different	ADJ
fis-5022	213	30	from	from	ADP
fis-5022	213	31	the	the	DET
fis-5022	213	32	training	training	NOUN
fis-5022	213	33	one	one	NUM
fis-5022	213	34	(	(	PUNCT
fis-5022	213	35	test	test	NOUN
fis-5022	213	36	1	1	NUM
fis-5022	213	37	)	)	PUNCT
fis-5022	213	38	.	.	PUNCT
fis-5022	214	1	the	the	DET
fis-5022	214	2	bagged	bag	VERB
fis-5022	214	3	trees	tree	NOUN
fis-5022	214	4	ensemble	ensemble	ADJ
fis-5022	214	5	model	model	NOUN
fis-5022	214	6	shows	show	VERB
fis-5022	214	7	poor	poor	ADJ
fis-5022	214	8	performance	performance	NOUN
fis-5022	214	9	for	for	ADP
fis-5022	214	10	test	test	NOUN
fis-5022	214	11	1	1	NUM
fis-5022	214	12	,	,	PUNCT
fis-5022	214	13	test	test	NOUN
fis-5022	214	14	2	2	NUM
fis-5022	214	15	and	and	CCONJ
fis-5022	214	16	test	test	VERB
fis-5022	214	17	3	3	NUM
fis-5022	214	18	with	with	ADP
fis-5022	214	19	train	train	NOUN
fis-5022	214	20	1	1	NUM
fis-5022	214	21	,	,	PUNCT
fis-5022	214	22	train	train	NOUN
fis-5022	214	23	2	2	NUM
fis-5022	214	24	,	,	PUNCT
fis-5022	214	25	and	and	CCONJ
fis-5022	214	26	train	train	NOUN
fis-5022	214	27	3	3	NUM
fis-5022	214	28	,	,	PUNCT
fis-5022	214	29	reflecting	reflect	VERB
fis-5022	214	30	a	a	DET
fis-5022	214	31	high	high	ADJ
fis-5022	214	32	false	false	ADJ
fis-5022	214	33	positive	positive	ADJ
fis-5022	214	34	rate	rate	NOUN
fis-5022	214	35	(	(	PUNCT
fis-5022	214	36	specificity	specificity	NOUN
fis-5022	214	37	at	at	ADP
fis-5022	214	38	0	0	NUM
fis-5022	214	39	%	%	NOUN
fis-5022	214	40	in	in	ADP
fis-5022	214	41	most	most	ADJ
fis-5022	214	42	cases	case	NOUN
fis-5022	214	43	)	)	PUNCT
fis-5022	214	44	.	.	PUNCT
fis-5022	215	1	the	the	DET
fis-5022	215	2	model	model	NOUN
fis-5022	215	3	performs	perform	VERB
fis-5022	215	4	better	well	ADV
fis-5022	215	5	with	with	ADP
fis-5022	215	6	train	train	NOUN
fis-5022	215	7	5	5	NUM
fis-5022	215	8	and	and	CCONJ
fis-5022	215	9	train	train	VERB
fis-5022	215	10	6	6	NUM
fis-5022	215	11	indicating	indicate	VERB
fis-5022	215	12	that	that	SCONJ
fis-5022	215	13	less	less	ADJ
fis-5022	215	14	variability	variability	NOUN
fis-5022	215	15	in	in	ADP
fis-5022	215	16	training	training	NOUN
fis-5022	215	17	data	datum	NOUN
fis-5022	215	18	improves	improve	VERB
fis-5022	215	19	the	the	DET
fis-5022	215	20	generalizability	generalizability	NOUN
fis-5022	215	21	.	.	PUNCT
fis-5022	216	1	the	the	DET
fis-5022	216	2	svm	svm	PROPN
fis-5022	216	3	model	model	NOUN
fis-5022	216	4	struggles	struggle	VERB
fis-5022	216	5	with	with	ADP
fis-5022	216	6	overfitting	overfitte	VERB
fis-5022	216	7	when	when	SCONJ
fis-5022	216	8	trained	train	VERB
fis-5022	216	9	on	on	ADP
fis-5022	216	10	highly	highly	ADV
fis-5022	216	11	variable	variable	ADJ
fis-5022	216	12	datasets	dataset	NOUN
fis-5022	216	13	,	,	PUNCT
fis-5022	216	14	as	as	SCONJ
fis-5022	216	15	evidenced	evidence	VERB
fis-5022	216	16	by	by	ADP
fis-5022	216	17	the	the	DET
fis-5022	216	18	poor	poor	ADJ
fis-5022	216	19	specificity	specificity	NOUN
fis-5022	216	20	in	in	ADP
fis-5022	216	21	certain	certain	ADJ
fis-5022	216	22	test	test	NOUN
fis-5022	216	23	cases	case	NOUN
fis-5022	216	24	.	.	PUNCT
fis-5022	217	1	the	the	DET
fis-5022	217	2	bagged	bag	VERB
fis-5022	217	3	trees	tree	NOUN
fis-5022	217	4	ensemble	ensemble	ADJ
fis-5022	217	5	model	model	NOUN
fis-5022	217	6	,	,	PUNCT
fis-5022	217	7	while	while	SCONJ
fis-5022	217	8	showing	show	VERB
fis-5022	217	9	robust	robust	ADJ
fis-5022	217	10	validation	validation	NOUN
fis-5022	217	11	performance	performance	NOUN
fis-5022	217	12	,	,	PUNCT
fis-5022	217	13	also	also	ADV
fis-5022	217	14	encounters	encounter	VERB
fis-5022	217	15	the	the	DET
fis-5022	217	16	problem	problem	NOUN
fis-5022	217	17	of	of	ADP
fis-5022	217	18	overfitting	overfitte	VERB
fis-5022	217	19	,	,	PUNCT
fis-5022	217	20	especially	especially	ADV
fis-5022	217	21	with	with	ADP
fis-5022	217	22	training	training	NOUN
fis-5022	217	23	datasets	dataset	NOUN
fis-5022	217	24	of	of	ADP
fis-5022	217	25	high	high	ADJ
fis-5022	217	26	variability	variability	NOUN
fis-5022	217	27	.	.	PUNCT
fis-5022	218	1	both	both	DET
fis-5022	218	2	models	model	NOUN
fis-5022	218	3	benefit	benefit	VERB
fis-5022	218	4	from	from	ADP
fis-5022	218	5	training	train	VERB
fis-5022	218	6	datasets	dataset	NOUN
fis-5022	218	7	with	with	ADP
fis-5022	218	8	controlled	control	VERB
fis-5022	218	9	variability	variability	NOUN
fis-5022	218	10	(	(	PUNCT
fis-5022	218	11	train	train	NOUN
fis-5022	218	12	5	5	NUM
fis-5022	218	13	and	and	CCONJ
fis-5022	218	14	train	train	VERB
fis-5022	218	15	6	6	NUM
fis-5022	218	16	)	)	PUNCT
fis-5022	218	17	thus	thus	ADV
fis-5022	218	18	enhancing	enhance	VERB
fis-5022	218	19	their	their	PRON
fis-5022	218	20	generalization	generalization	NOUN
fis-5022	218	21	ability	ability	NOUN
fis-5022	218	22	in	in	ADP
fis-5022	218	23	respect	respect	NOUN
fis-5022	218	24	to	to	ADP
fis-5022	218	25	unseen	unseen	ADJ
fis-5022	218	26	test	test	NOUN
fis-5022	218	27	data	datum	NOUN
fis-5022	218	28	.	.	PUNCT
fis-5022	219	1	the	the	DET
fis-5022	219	2	performance	performance	NOUN
fis-5022	219	3	generally	generally	ADV
fis-5022	219	4	improves	improve	VERB
fis-5022	219	5	with	with	ADP
fis-5022	219	6	the	the	DET
fis-5022	219	7	variability	variability	NOUN
fis-5022	219	8	of	of	ADP
fis-5022	219	9	numerical	numerical	ADJ
fis-5022	219	10	model	model	NOUN
fis-5022	219	11	parameters	parameter	NOUN
fis-5022	219	12	in	in	ADP
fis-5022	219	13	training	training	NOUN
fis-5022	219	14	sets	set	NOUN
fis-5022	219	15	1	1	NUM
fis-5022	219	16	through	through	ADP
fis-5022	219	17	5	5	NUM
fis-5022	219	18	.	.	PUNCT
fis-5022	220	1	however	however	ADV
fis-5022	220	2	,	,	PUNCT
fis-5022	220	3	the	the	DET
fis-5022	220	4	performance	performance	NOUN
fis-5022	220	5	decreases	decrease	VERB
fis-5022	220	6	with	with	ADP
fis-5022	220	7	too	too	ADV
fis-5022	220	8	much	much	ADJ
fis-5022	220	9	variability	variability	NOUN
fis-5022	220	10	,	,	PUNCT
fis-5022	220	11	as	as	SCONJ
fis-5022	220	12	shown	show	VERB
fis-5022	220	13	by	by	ADP
fis-5022	220	14	train	train	NOUN
fis-5022	220	15	6	6	NUM
fis-5022	220	16	.	.	PUNCT
fis-5022	221	1	this	this	PRON
fis-5022	221	2	demonstrates	demonstrate	VERB
fis-5022	221	3	the	the	DET
fis-5022	221	4	need	need	NOUN
fis-5022	221	5	to	to	PART
fis-5022	221	6	find	find	VERB
fis-5022	221	7	an	an	DET
fis-5022	221	8	optimal	optimal	ADJ
fis-5022	221	9	balance	balance	NOUN
fis-5022	221	10	in	in	ADP
fis-5022	221	11	training	training	NOUN
fis-5022	221	12	data	datum	NOUN
fis-5022	221	13	variability	variability	NOUN
fis-5022	221	14	to	to	PART
fis-5022	221	15	achieve	achieve	VERB
fis-5022	221	16	the	the	DET
fis-5022	221	17	best	good	ADJ
fis-5022	221	18	model	model	NOUN
fis-5022	221	19	performance	performance	NOUN
fis-5022	221	20	.	.	PUNCT
fis-5022	222	1	to	to	PART
fis-5022	222	2	conclude	conclude	VERB
fis-5022	222	3	,	,	PUNCT
fis-5022	222	4	the	the	DET
fis-5022	222	5	proposed	propose	VERB
fis-5022	222	6	machine	machine	NOUN
fis-5022	222	7	learning	learning	NOUN
fis-5022	222	8	models	model	NOUN
fis-5022	222	9	has	have	AUX
fis-5022	222	10	proven	prove	VERB
fis-5022	222	11	to	to	PART
fis-5022	222	12	be	be	AUX
fis-5022	222	13	efficient	efficient	ADJ
fis-5022	222	14	in	in	ADP
fis-5022	222	15	the	the	DET
fis-5022	222	16	case	case	NOUN
fis-5022	222	17	of	of	ADP
fis-5022	222	18	varying	vary	VERB
fis-5022	222	19	heat	heat	NOUN
fis-5022	222	20	power	power	NOUN
fis-5022	222	21	and	and	CCONJ
fis-5022	222	22	spatial	spatial	ADJ
fis-5022	222	23	distribution	distribution	NOUN
fis-5022	222	24	when	when	SCONJ
fis-5022	222	25	applied	apply	VERB
fis-5022	222	26	to	to	ADP
fis-5022	222	27	materials	material	NOUN
fis-5022	222	28	with	with	ADP
fis-5022	222	29	similar	similar	ADJ
fis-5022	222	30	thermal	thermal	ADJ
fis-5022	222	31	properties	property	NOUN
fis-5022	222	32	and	and	CCONJ
fis-5022	222	33	thickness	thickness	NOUN
fis-5022	222	34	.	.	PUNCT
fis-5022	223	1	nevertheless	nevertheless	ADV
fis-5022	223	2	,	,	PUNCT
fis-5022	223	3	to	to	PART
fis-5022	223	4	enhance	enhance	VERB
fis-5022	223	5	the	the	DET
fis-5022	223	6	model	model	NOUN
fis-5022	223	7	generalizability	generalizability	NOUN
fis-5022	223	8	by	by	ADP
fis-5022	223	9	involving	involve	VERB
fis-5022	223	10	different	different	ADJ
fis-5022	223	11	materials	material	NOUN
fis-5022	223	12	and	and	CCONJ
fis-5022	223	13	thicknesses	thickness	NOUN
fis-5022	223	14	,	,	PUNCT
fis-5022	223	15	training	training	NOUN
fis-5022	223	16	data	datum	NOUN
fis-5022	223	17	parameters	parameter	NOUN
fis-5022	223	18	are	be	AUX
fis-5022	223	19	carefully	carefully	ADV
fis-5022	223	20	to	to	PART
fis-5022	223	21	be	be	AUX
fis-5022	223	22	chosen	choose	VERB
fis-5022	223	23	.	.	PUNCT
fis-5022	224	1	for	for	ADP
fis-5022	224	2	example	example	NOUN
fis-5022	224	3	,	,	PUNCT
fis-5022	224	4	excessive	excessive	ADJ
fis-5022	224	5	variability	variability	NOUN
fis-5022	224	6	in	in	ADP
fis-5022	224	7	the	the	DET
fis-5022	224	8	training	training	NOUN
fis-5022	224	9	data	datum	NOUN
fis-5022	224	10	may	may	AUX
fis-5022	224	11	compromise	compromise	VERB
fis-5022	224	12	model	model	NOUN
fis-5022	224	13	performance	performance	NOUN
fis-5022	224	14	producing	produce	VERB
fis-5022	224	15	worse	bad	ADJ
fis-5022	224	16	evaluation	evaluation	NOUN
fis-5022	224	17	results	result	NOUN
fis-5022	224	18	and	and	CCONJ
fis-5022	224	19	failing	fail	VERB
fis-5022	224	20	to	to	PART
fis-5022	224	21	improve	improve	VERB
fis-5022	224	22	overall	overall	ADJ
fis-5022	224	23	generalizability	generalizability	NOUN
fis-5022	224	24	.	.	PUNCT
fis-5022	225	1	learning	learn	VERB
fis-5022	225	2	curve	curve	NOUN
fis-5022	225	3	evaluation	evaluation	NOUN
fis-5022	225	4	in	in	ADP
fis-5022	225	5	this	this	DET
fis-5022	225	6	section	section	NOUN
fis-5022	225	7	,	,	PUNCT
fis-5022	225	8	a	a	DET
fis-5022	225	9	comprehensive	comprehensive	ADJ
fis-5022	225	10	evaluation	evaluation	NOUN
fis-5022	225	11	of	of	ADP
fis-5022	225	12	the	the	DET
fis-5022	225	13	svm	svm	ADJ
fis-5022	225	14	machine	machine	NOUN
fis-5022	225	15	learning	learning	NOUN
fis-5022	225	16	model	model	NOUN
fis-5022	225	17	performance	performance	NOUN
fis-5022	225	18	is	be	AUX
fis-5022	225	19	presented	present	VERB
fis-5022	225	20	through	through	ADP
fis-5022	225	21	the	the	DET
fis-5022	225	22	analysis	analysis	NOUN
fis-5022	225	23	of	of	ADP
fis-5022	225	24	learning	learn	VERB
fis-5022	225	25	curves	curve	NOUN
fis-5022	225	26	.	.	PUNCT
fis-5022	226	1	learning	learn	VERB
fis-5022	226	2	curves	curve	NOUN
fis-5022	226	3	are	be	AUX
fis-5022	226	4	crucial	crucial	ADJ
fis-5022	226	5	diagnostic	diagnostic	ADJ
fis-5022	226	6	tools	tool	NOUN
fis-5022	226	7	,	,	PUNCT
fis-5022	226	8	which	which	PRON
fis-5022	226	9	illustrate	illustrate	VERB
fis-5022	226	10	the	the	DET
fis-5022	226	11	model	model	NOUN
fis-5022	226	12	learning	learning	NOUN
fis-5022	226	13	process	process	NOUN
fis-5022	226	14	by	by	ADP
fis-5022	226	15	plotting	plot	VERB
fis-5022	226	16	the	the	DET
fis-5022	226	17	training	training	NOUN
fis-5022	226	18	and	and	CCONJ
fis-5022	226	19	validation	validation	NOUN
fis-5022	226	20	errors	error	NOUN
fis-5022	226	21	against	against	ADP
fis-5022	226	22	different	different	ADJ
fis-5022	226	23	training	training	NOUN
fis-5022	226	24	set	set	NOUN
fis-5022	226	25	sizes	size	NOUN
fis-5022	226	26	.	.	PUNCT
fis-5022	227	1	learning	learn	VERB
fis-5022	227	2	curves	curve	NOUN
fis-5022	227	3	provide	provide	VERB
fis-5022	227	4	valuable	valuable	ADJ
fis-5022	227	5	insights	insight	NOUN
fis-5022	227	6	into	into	ADP
fis-5022	227	7	the	the	DET
fis-5022	227	8	model	model	NOUN
fis-5022	227	9	performance	performance	NOUN
fis-5022	227	10	and	and	CCONJ
fis-5022	227	11	behavior	behavior	NOUN
fis-5022	227	12	during	during	ADP
fis-5022	227	13	training	training	NOUN
fis-5022	227	14	.	.	PUNCT
fis-5022	228	1	they	they	PRON
fis-5022	228	2	help	help	VERB
fis-5022	228	3	to	to	PART
fis-5022	228	4	understand	understand	VERB
fis-5022	228	5	how	how	SCONJ
fis-5022	228	6	well	well	ADV
fis-5022	228	7	the	the	DET
fis-5022	228	8	model	model	NOUN
fis-5022	228	9	is	be	AUX
fis-5022	228	10	being	be	AUX
fis-5022	228	11	learned	learn	VERB
fis-5022	228	12	from	from	ADP
fis-5022	228	13	the	the	DET
fis-5022	228	14	data	datum	NOUN
fis-5022	228	15	and	and	CCONJ
fis-5022	228	16	whether	whether	SCONJ
fis-5022	228	17	it	it	PRON
fis-5022	228	18	generalizes	generalize	VERB
fis-5022	228	19	well	well	ADV
fis-5022	228	20	to	to	ADP
fis-5022	228	21	new	new	ADJ
fis-5022	228	22	,	,	PUNCT
fis-5022	228	23	unseen	unseen	ADJ
fis-5022	228	24	data	datum	NOUN
fis-5022	228	25	.	.	PUNCT
fis-5022	229	1	even	even	ADV
fis-5022	229	2	with	with	ADP
fis-5022	229	3	different	different	ADJ
fis-5022	229	4	training	training	NOUN
fis-5022	229	5	and	and	CCONJ
fis-5022	229	6	testing	testing	NOUN
fis-5022	229	7	datasets	dataset	NOUN
fis-5022	229	8	aimed	aim	VERB
fis-5022	229	9	at	at	ADP
fis-5022	229	10	evaluating	evaluate	VERB
fis-5022	229	11	generalizability	generalizability	NOUN
fis-5022	229	12	,	,	PUNCT
fis-5022	229	13	learning	learn	VERB
fis-5022	229	14	curves	curve	NOUN
fis-5022	229	15	can	can	AUX
fis-5022	229	16	still	still	ADV
fis-5022	229	17	offer	offer	VERB
fis-5022	229	18	meaningful	meaningful	ADJ
fis-5022	229	19	information	information	NOUN
fis-5022	229	20	.	.	PUNCT
fis-5022	230	1	the	the	DET
fis-5022	230	2	particular	particular	ADJ
fis-5022	230	3	learning	learning	NOUN
fis-5022	230	4	curves	curve	NOUN
fis-5022	230	5	have	have	AUX
fis-5022	230	6	been	be	AUX
fis-5022	230	7	constructed	construct	VERB
fis-5022	230	8	using	use	VERB
fis-5022	230	9	two	two	NUM
fis-5022	230	10	distinct	distinct	ADJ
fis-5022	230	11	training	training	NOUN
fis-5022	230	12	datasets	dataset	NOUN
fis-5022	230	13	:	:	PUNCT
fis-5022	230	14	one	one	NUM
fis-5022	230	15	with	with	ADP
fis-5022	230	16	a	a	DET
fis-5022	230	17	higher	high	ADJ
fis-5022	230	18	variability	variability	NOUN
fis-5022	230	19	in	in	ADP
fis-5022	230	20	properties	property	NOUN
fis-5022	230	21	and	and	CCONJ
fis-5022	230	22	parameters	parameter	NOUN
fis-5022	230	23	(	(	PUNCT
fis-5022	230	24	train	train	NOUN
fis-5022	230	25	6	6	NUM
fis-5022	230	26	)	)	PUNCT
fis-5022	230	27	and	and	CCONJ
fis-5022	230	28	another	another	PRON
fis-5022	230	29	with	with	ADP
fis-5022	230	30	a	a	DET
fis-5022	230	31	lower	low	ADJ
fis-5022	230	32	variability	variability	NOUN
fis-5022	230	33	(	(	PUNCT
fis-5022	230	34	train	train	NOUN
fis-5022	230	35	5	5	NUM
fis-5022	230	36	)	)	PUNCT
fis-5022	230	37	,	,	PUNCT
fis-5022	230	38	see	see	VERB
fis-5022	230	39	fig	fig	NOUN
fis-5022	230	40	.	.	PUNCT
fis-5022	231	1	4	4	X
fis-5022	231	2	.	.	PUNCT
fis-5022	231	3	this	this	DET
fis-5022	231	4	comparison	comparison	NOUN
fis-5022	231	5	between	between	ADP
fis-5022	231	6	the	the	DET
fis-5022	231	7	two	two	NUM
fis-5022	231	8	training	training	NOUN
fis-5022	231	9	datasets	dataset	NOUN
fis-5022	231	10	highlights	highlight	VERB
fis-5022	231	11	the	the	DET
fis-5022	231	12	impact	impact	NOUN
fis-5022	231	13	of	of	ADP
fis-5022	231	14	dataset	dataset	ADJ
fis-5022	231	15	variability	variability	NOUN
fis-5022	231	16	on	on	ADP
fis-5022	231	17	the	the	DET
fis-5022	231	18	model	model	NOUN
fis-5022	231	19	performance	performance	NOUN
fis-5022	231	20	thus	thus	ADV
fis-5022	231	21	illustrating	illustrate	VERB
fis-5022	231	22	the	the	DET
fis-5022	231	23	differences	difference	NOUN
fis-5022	231	24	between	between	ADP
fis-5022	231	25	a	a	DET
fis-5022	231	26	sufficiently	sufficiently	ADV
fis-5022	231	27	comprehensive	comprehensive	ADJ
fis-5022	231	28	dataset	dataset	NOUN
fis-5022	231	29	and	and	CCONJ
fis-5022	231	30	one	one	NUM
fis-5022	231	31	that	that	PRON
fis-5022	231	32	might	might	AUX
fis-5022	231	33	be	be	AUX
fis-5022	231	34	an	an	DET
fis-5022	231	35	overly	overly	ADV
fis-5022	231	36	variable	variable	ADJ
fis-5022	231	37	.	.	PUNCT
fis-5022	232	1	it	it	PRON
fis-5022	232	2	is	be	AUX
fis-5022	232	3	important	important	ADJ
fis-5022	232	4	stressing	stress	VERB
fis-5022	232	5	that	that	SCONJ
fis-5022	232	6	a	a	DET
fis-5022	232	7	training	training	NOUN
fis-5022	232	8	curve	curve	NOUN
fis-5022	232	9	shows	show	VERB
fis-5022	232	10	how	how	SCONJ
fis-5022	232	11	the	the	DET
fis-5022	232	12	model	model	NOUN
fis-5022	232	13	performance	performance	NOUN
fis-5022	232	14	evolves	evolve	VERB
fis-5022	232	15	on	on	ADP
fis-5022	232	16	the	the	DET
fis-5022	232	17	training	training	NOUN
fis-5022	232	18	data	datum	NOUN
fis-5022	232	19	as	as	ADP
fis-5022	232	20	the	the	DET
fis-5022	232	21	number	number	NOUN
fis-5022	232	22	of	of	ADP
fis-5022	232	23	training	training	NOUN
fis-5022	232	24	examples	example	NOUN
fis-5022	232	25	increases	increase	NOUN
fis-5022	232	26	.	.	PUNCT
fis-5022	233	1	in	in	ADP
fis-5022	233	2	its	its	PRON
fis-5022	233	3	turn	turn	NOUN
fis-5022	233	4	,	,	PUNCT
fis-5022	233	5	the	the	DET
fis-5022	233	6	validation	validation	NOUN
fis-5022	233	7	curve	curve	NOUN
fis-5022	233	8	shows	show	VERB
fis-5022	233	9	how	how	SCONJ
fis-5022	233	10	the	the	DET
fis-5022	233	11	model	model	NOUN
fis-5022	233	12	performance	performance	NOUN
fis-5022	233	13	evolves	evolve	VERB
fis-5022	233	14	on	on	ADP
fis-5022	233	15	the	the	DET
fis-5022	233	16	validation	validation	NOUN
fis-5022	233	17	or	or	CCONJ
fis-5022	233	18	test	test	NOUN
fis-5022	233	19	data	datum	NOUN
fis-5022	233	20	.	.	PUNCT
fis-5022	234	1	if	if	SCONJ
fis-5022	234	2	the	the	DET
fis-5022	234	3	training	training	NOUN
fis-5022	234	4	accuracy	accuracy	NOUN
fis-5022	234	5	is	be	AUX
fis-5022	234	6	high	high	ADJ
fis-5022	234	7	but	but	CCONJ
fis-5022	234	8	the	the	DET
fis-5022	234	9	validation	validation	NOUN
fis-5022	234	10	accuracy	accuracy	NOUN
fis-5022	234	11	is	be	AUX
fis-5022	234	12	low	low	ADJ
fis-5022	234	13	,	,	PUNCT
fis-5022	234	14	the	the	DET
fis-5022	234	15	model	model	NOUN
fis-5022	234	16	is	be	AUX
fis-5022	234	17	likely	likely	ADV
fis-5022	234	18	overfitting	overfitte	VERB
fis-5022	234	19	.	.	PUNCT
fis-5022	235	1	if	if	SCONJ
fis-5022	235	2	both	both	CCONJ
fis-5022	235	3	the	the	DET
fis-5022	235	4	training	training	NOUN
fis-5022	235	5	and	and	CCONJ
fis-5022	235	6	validation	validation	NOUN
fis-5022	235	7	accuracies	accuracy	NOUN
fis-5022	235	8	are	be	AUX
fis-5022	235	9	low	low	ADJ
fis-5022	235	10	,	,	PUNCT
fis-5022	235	11	the	the	DET
fis-5022	235	12	model	model	NOUN
fis-5022	235	13	is	be	AUX
fis-5022	235	14	likely	likely	ADV
fis-5022	235	15	underfitting	underfitting	ADJ
fis-5022	235	16	.	.	PUNCT
fis-5022	236	1	while	while	SCONJ
fis-5022	236	2	considering	consider	VERB
fis-5022	236	3	training	training	NOUN
fis-5022	236	4	error	error	NOUN
fis-5022	236	5	curves	curve	NOUN
fis-5022	236	6	,	,	PUNCT
fis-5022	236	7	in	in	ADP
fis-5022	236	8	the	the	DET
fis-5022	236	9	case	case	NOUN
fis-5022	236	10	of	of	ADP
fis-5022	236	11	the	the	DET
fis-5022	236	12	lower	low	ADJ
fis-5022	236	13	variability	variability	NOUN
fis-5022	236	14	dataset	dataset	NOUN
fis-5022	236	15	(	(	PUNCT
fis-5022	236	16	train	train	NOUN
fis-5022	236	17	5	5	NUM
fis-5022	236	18	)	)	PUNCT
fis-5022	236	19	,	,	PUNCT
fis-5022	236	20	the	the	DET
fis-5022	236	21	training	training	NOUN
fis-5022	236	22	error	error	NOUN
fis-5022	236	23	starts	start	VERB
fis-5022	236	24	as	as	ADV
fis-5022	236	25	high	high	ADJ
fis-5022	236	26	as	as	ADP
fis-5022	236	27	21.97	21.97	NUM
fis-5022	236	28	%	%	NOUN
fis-5022	236	29	but	but	CCONJ
fis-5022	236	30	then	then	ADV
fis-5022	236	31	drops	drop	VERB
fis-5022	236	32	sharply	sharply	ADV
fis-5022	236	33	to	to	ADP
fis-5022	236	34	2.23	2.23	NUM
fis-5022	236	35	%	%	NOUN
fis-5022	236	36	.	.	PUNCT
fis-5022	237	1	this	this	PRON
fis-5022	237	2	suggests	suggest	VERB
fis-5022	237	3	that	that	SCONJ
fis-5022	237	4	the	the	DET
fis-5022	237	5	model	model	NOUN
fis-5022	237	6	learns	learn	VERB
fis-5022	237	7	more	more	ADV
fis-5022	237	8	quickly	quickly	ADV
fis-5022	237	9	when	when	SCONJ
fis-5022	237	10	the	the	DET
fis-5022	237	11	variability	variability	NOUN
fis-5022	237	12	in	in	ADP
fis-5022	237	13	the	the	DET
fis-5022	237	14	training	training	NOUN
fis-5022	237	15	data	datum	NOUN
fis-5022	237	16	is	be	AUX
fis-5022	237	17	lower	low	ADJ
fis-5022	237	18	.	.	PUNCT
fis-5022	238	1	in	in	ADP
fis-5022	238	2	the	the	DET
fis-5022	238	3	case	case	NOUN
fis-5022	238	4	of	of	ADP
fis-5022	238	5	the	the	DET
fis-5022	238	6	higher	high	ADJ
fis-5022	238	7	variability	variability	NOUN
fis-5022	238	8	dataset	dataset	NOUN
fis-5022	238	9	(	(	PUNCT
fis-5022	238	10	train	train	NOUN
fis-5022	238	11	6	6	NUM
fis-5022	238	12	)	)	PUNCT
fis-5022	238	13	,	,	PUNCT
fis-5022	238	14	the	the	DET
fis-5022	238	15	training	training	NOUN
fis-5022	238	16	error	error	NOUN
fis-5022	238	17	decreases	decrease	VERB
fis-5022	238	18	steadily	steadily	ADV
fis-5022	238	19	from	from	ADP
fis-5022	238	20	18.06	18.06	NUM
fis-5022	238	21	%	%	NOUN
fis-5022	238	22	to	to	ADP
fis-5022	238	23	5.98	5.98	NUM
fis-5022	238	24	%	%	NOUN
fis-5022	238	25	,	,	PUNCT
fis-5022	238	26	showing	show	VERB
fis-5022	238	27	a	a	DET
fis-5022	238	28	gradual	gradual	ADJ
fis-5022	238	29	improvement	improvement	NOUN
fis-5022	238	30	as	as	SCONJ
fis-5022	238	31	more	more	ADJ
fis-5022	238	32	data	datum	NOUN
fis-5022	238	33	is	be	AUX
fis-5022	238	34	used	use	VERB
fis-5022	238	35	for	for	ADP
fis-5022	238	36	training	training	NOUN
fis-5022	238	37	.	.	PUNCT
fis-5022	239	1	validation	validation	NOUN
fis-5022	239	2	error	error	NOUN
fis-5022	239	3	curves	curve	NOUN
fis-5022	239	4	were	be	AUX
fis-5022	239	5	first	first	ADV
fis-5022	239	6	evaluated	evaluate	VERB
fis-5022	239	7	on	on	ADP
fis-5022	239	8	test	test	NOUN
fis-5022	239	9	1	1	NUM
fis-5022	239	10	set	set	NOUN
fis-5022	239	11	.	.	PUNCT
fis-5022	240	1	in	in	ADP
fis-5022	240	2	the	the	DET
fis-5022	240	3	case	case	NOUN
fis-5022	240	4	of	of	ADP
fis-5022	240	5	the	the	DET
fis-5022	240	6	lower	low	ADJ
fis-5022	240	7	variability	variability	NOUN
fis-5022	240	8	,	,	PUNCT
fis-5022	240	9	the	the	DET
fis-5022	240	10	validation	validation	NOUN
fis-5022	240	11	error	error	NOUN
fis-5022	240	12	starts	start	VERB
fis-5022	240	13	at	at	ADP
fis-5022	240	14	25.33	25.33	NUM
fis-5022	240	15	%	%	NOUN
fis-5022	240	16	but	but	CCONJ
fis-5022	240	17	shows	show	VERB
fis-5022	240	18	a	a	DET
fis-5022	240	19	significant	significant	ADJ
fis-5022	240	20	drop	drop	NOUN
fis-5022	240	21	to	to	ADP
fis-5022	240	22	3.21	3.21	NUM
fis-5022	240	23	%	%	NOUN
fis-5022	240	24	with	with	ADP
fis-5022	240	25	some	some	DET
fis-5022	240	26	fluctuations	fluctuation	NOUN
fis-5022	240	27	.	.	PUNCT
fis-5022	241	1	it	it	PRON
fis-5022	241	2	suggests	suggest	VERB
fis-5022	241	3	the	the	DET
fis-5022	241	4	better	well	ADJ
fis-5022	241	5	performance	performance	NOUN
fis-5022	241	6	on	on	ADP
fis-5022	241	7	this	this	DET
fis-5022	241	8	dataset	dataset	NOUN
fis-5022	241	9	,	,	PUNCT
fis-5022	241	10	especially	especially	ADV
fis-5022	241	11	with	with	ADP
fis-5022	241	12	higher	high	ADJ
fis-5022	241	13	training	training	NOUN
fis-5022	241	14	sizes	size	NOUN
fis-5022	241	15	.	.	PUNCT
fis-5022	242	1	in	in	ADP
fis-5022	242	2	the	the	DET
fis-5022	242	3	case	case	NOUN
fis-5022	242	4	of	of	ADP
fis-5022	242	5	the	the	DET
fis-5022	242	6	higher	high	ADJ
fis-5022	242	7	variability	variability	NOUN
fis-5022	242	8	,	,	PUNCT
fis-5022	242	9	the	the	DET
fis-5022	242	10	validation	validation	NOUN
fis-5022	242	11	error	error	NOUN
fis-5022	242	12	decreases	decrease	VERB
fis-5022	242	13	from	from	ADP
fis-5022	242	14	25.33	25.33	NUM
fis-5022	242	15	%	%	NOUN
fis-5022	242	16	to	to	PART
fis-5022	242	17	9.50	9.50	NUM
fis-5022	242	18	%	%	NOUN
fis-5022	242	19	showing	show	VERB
fis-5022	242	20	good	good	ADJ
fis-5022	242	21	generalizability	generalizability	NOUN
fis-5022	242	22	to	to	ADP
fis-5022	242	23	this	this	DET
fis-5022	242	24	set	set	NOUN
fis-5022	242	25	.	.	PUNCT
fis-5022	243	1	a.	a.	PROPN
fis-5022	243	2	chulkov	chulkov	PROPN
fis-5022	243	3	et	et	PROPN
fis-5022	243	4	alii	alii	PROPN
fis-5022	243	5	,	,	PUNCT
fis-5022	243	6	frattura	frattura	PROPN
fis-5022	243	7	ed	ed	PROPN
fis-5022	243	8	integrità	integrità	PROPN
fis-5022	243	9	strutturale	strutturale	PROPN
fis-5022	243	10	,	,	PUNCT
fis-5022	243	11	70	70	NUM
fis-5022	243	12	(	(	PUNCT
fis-5022	243	13	2024	2024	NUM
fis-5022	243	14	)	)	PUNCT
fis-5022	243	15	177	177	NUM
fis-5022	243	16	-	-	SYM
fis-5022	243	17	191	191	NUM
fis-5022	243	18	;	;	PUNCT
fis-5022	243	19	doi	doi	NOUN
fis-5022	243	20	:	:	PUNCT
fis-5022	243	21	10.3221	10.3221	NUM
fis-5022	243	22	/	/	SYM
fis-5022	243	23	igf	igf	NOUN
fis-5022	243	24	-	-	PUNCT
fis-5022	243	25	esis.70.10	esis.70.10	ADJ
fis-5022	243	26	187	187	NUM
fis-5022	243	27	the	the	DET
fis-5022	243	28	results	result	NOUN
fis-5022	243	29	obtained	obtain	VERB
fis-5022	243	30	on	on	ADP
fis-5022	243	31	the	the	DET
fis-5022	243	32	test	test	NOUN
fis-5022	243	33	2	2	NUM
fis-5022	243	34	set	set	NOUN
fis-5022	243	35	show	show	VERB
fis-5022	243	36	that	that	SCONJ
fis-5022	243	37	,	,	PUNCT
fis-5022	243	38	in	in	ADP
fis-5022	243	39	the	the	DET
fis-5022	243	40	case	case	NOUN
fis-5022	243	41	of	of	ADP
fis-5022	243	42	the	the	DET
fis-5022	243	43	lower	low	ADJ
fis-5022	243	44	variability	variability	NOUN
fis-5022	243	45	,	,	PUNCT
fis-5022	243	46	the	the	DET
fis-5022	243	47	validation	validation	NOUN
fis-5022	243	48	error	error	NOUN
fis-5022	243	49	starts	start	VERB
fis-5022	243	50	at	at	ADP
fis-5022	243	51	20.28	20.28	NUM
fis-5022	243	52	%	%	NOUN
fis-5022	243	53	and	and	CCONJ
fis-5022	243	54	decreases	decrease	VERB
fis-5022	243	55	to	to	ADP
fis-5022	243	56	3.55	3.55	NUM
fis-5022	243	57	%	%	NOUN
fis-5022	243	58	with	with	ADP
fis-5022	243	59	slight	slight	ADJ
fis-5022	243	60	fluctuations	fluctuation	NOUN
fis-5022	243	61	.	.	PUNCT
fis-5022	244	1	the	the	DET
fis-5022	244	2	model	model	NOUN
fis-5022	244	3	performs	perform	VERB
fis-5022	244	4	well	well	ADV
fis-5022	244	5	but	but	CCONJ
fis-5022	244	6	not	not	PART
fis-5022	244	7	as	as	ADV
fis-5022	244	8	consistently	consistently	ADV
fis-5022	244	9	as	as	ADP
fis-5022	244	10	with	with	ADP
fis-5022	244	11	the	the	DET
fis-5022	244	12	higher	high	ADJ
fis-5022	244	13	variability	variability	NOUN
fis-5022	244	14	data	datum	NOUN
fis-5022	244	15	.	.	PUNCT
fis-5022	245	1	a	a	DET
fis-5022	245	2	)	)	PUNCT
fis-5022	245	3	b	b	NOUN
fis-5022	245	4	)	)	PUNCT
fis-5022	245	5	figure	figure	NOUN
fis-5022	245	6	4	4	NUM
fis-5022	245	7	:	:	PUNCT
fis-5022	245	8	learning	learn	VERB
fis-5022	245	9	curves	curve	NOUN
fis-5022	245	10	for	for	ADP
fis-5022	245	11	gaussian	gaussian	ADJ
fis-5022	245	12	svm	svm	ADJ
fis-5022	245	13	model	model	NOUN
fis-5022	245	14	trained	train	VERB
fis-5022	245	15	on	on	ADP
fis-5022	245	16	train	train	NOUN
fis-5022	245	17	5	5	NUM
fis-5022	245	18	(	(	PUNCT
fis-5022	245	19	a	a	NOUN
fis-5022	245	20	)	)	PUNCT
fis-5022	245	21	and	and	CCONJ
fis-5022	245	22	train	train	VERB
fis-5022	245	23	6	6	NUM
fis-5022	245	24	(	(	PUNCT
fis-5022	245	25	b	b	NOUN
fis-5022	245	26	)	)	PUNCT
fis-5022	245	27	datasets	dataset	NOUN
fis-5022	245	28	.	.	PUNCT
fis-5022	246	1	while	while	SCONJ
fis-5022	246	2	considering	consider	VERB
fis-5022	246	3	the	the	DET
fis-5022	246	4	higher	high	ADJ
fis-5022	246	5	variability	variability	NOUN
fis-5022	246	6	of	of	ADP
fis-5022	246	7	the	the	DET
fis-5022	246	8	data	datum	NOUN
fis-5022	246	9	,	,	PUNCT
fis-5022	246	10	the	the	DET
fis-5022	246	11	validation	validation	NOUN
fis-5022	246	12	error	error	NOUN
fis-5022	246	13	decreases	decrease	VERB
fis-5022	246	14	from	from	ADP
fis-5022	246	15	20.28	20.28	NUM
fis-5022	246	16	%	%	NOUN
fis-5022	246	17	to	to	PART
fis-5022	246	18	2.84	2.84	NUM
fis-5022	246	19	%	%	NOUN
fis-5022	246	20	indicating	indicate	VERB
fis-5022	246	21	good	good	ADJ
fis-5022	246	22	generalization	generalization	NOUN
fis-5022	246	23	to	to	ADP
fis-5022	246	24	different	different	ADJ
fis-5022	246	25	thermal	thermal	ADJ
fis-5022	246	26	properties	property	NOUN
fis-5022	246	27	and	and	CCONJ
fis-5022	246	28	defect	defect	ADJ
fis-5022	246	29	depths	depth	NOUN
fis-5022	246	30	.	.	PUNCT
fis-5022	247	1	finally	finally	ADV
fis-5022	247	2	,	,	PUNCT
fis-5022	247	3	the	the	DET
fis-5022	247	4	test	test	NOUN
fis-5022	247	5	3	3	NUM
fis-5022	247	6	set	set	NOUN
fis-5022	247	7	was	be	AUX
fis-5022	247	8	evaluated	evaluate	VERB
fis-5022	247	9	to	to	PART
fis-5022	247	10	reveal	reveal	VERB
fis-5022	247	11	that	that	SCONJ
fis-5022	247	12	,	,	PUNCT
fis-5022	247	13	in	in	ADP
fis-5022	247	14	the	the	DET
fis-5022	247	15	case	case	NOUN
fis-5022	247	16	of	of	ADP
fis-5022	247	17	the	the	DET
fis-5022	247	18	lower	low	ADJ
fis-5022	247	19	variability	variability	NOUN
fis-5022	247	20	,	,	PUNCT
fis-5022	247	21	the	the	DET
fis-5022	247	22	validation	validation	NOUN
fis-5022	247	23	error	error	NOUN
fis-5022	247	24	starts	start	VERB
fis-5022	247	25	at	at	ADP
fis-5022	247	26	25.33	25.33	NUM
fis-5022	247	27	%	%	NOUN
fis-5022	247	28	and	and	CCONJ
fis-5022	247	29	diminishes	diminish	VERB
fis-5022	247	30	to	to	ADP
fis-5022	247	31	around	around	ADP
fis-5022	247	32	13.55	13.55	NUM
fis-5022	247	33	%	%	NOUN
fis-5022	247	34	with	with	ADP
fis-5022	247	35	a	a	DET
fis-5022	247	36	better	well	ADJ
fis-5022	247	37	consistency	consistency	NOUN
fis-5022	247	38	than	than	ADP
fis-5022	247	39	in	in	ADP
fis-5022	247	40	the	the	DET
fis-5022	247	41	case	case	NOUN
fis-5022	247	42	of	of	ADP
fis-5022	247	43	the	the	DET
fis-5022	247	44	higher	high	ADJ
fis-5022	247	45	variability	variability	NOUN
fis-5022	247	46	data	datum	NOUN
fis-5022	247	47	but	but	CCONJ
fis-5022	247	48	still	still	ADV
fis-5022	247	49	showing	show	VERB
fis-5022	247	50	significant	significant	ADJ
fis-5022	247	51	fluctuations	fluctuation	NOUN
fis-5022	247	52	.	.	PUNCT
fis-5022	248	1	if	if	SCONJ
fis-5022	248	2	the	the	DET
fis-5022	248	3	data	datum	NOUN
fis-5022	248	4	is	be	AUX
fis-5022	248	5	characterized	characterize	VERB
fis-5022	248	6	by	by	ADP
fis-5022	248	7	the	the	DET
fis-5022	248	8	higher	high	ADJ
fis-5022	248	9	variability	variability	NOUN
fis-5022	248	10	,	,	PUNCT
fis-5022	248	11	the	the	DET
fis-5022	248	12	validation	validation	NOUN
fis-5022	248	13	error	error	NOUN
fis-5022	248	14	fluctuates	fluctuate	VERB
fis-5022	248	15	between	between	ADP
fis-5022	248	16	13.92	13.92	NUM
fis-5022	248	17	%	%	NOUN
fis-5022	248	18	and	and	CCONJ
fis-5022	248	19	20.23	20.23	NUM
fis-5022	248	20	%	%	NOUN
fis-5022	248	21	thus	thus	ADV
fis-5022	248	22	showing	show	VERB
fis-5022	248	23	that	that	SCONJ
fis-5022	248	24	the	the	DET
fis-5022	248	25	model	model	NOUN
fis-5022	248	26	struggles	struggle	VERB
fis-5022	248	27	with	with	ADP
fis-5022	248	28	the	the	DET
fis-5022	248	29	diverse	diverse	ADJ
fis-5022	248	30	conditions	condition	NOUN
fis-5022	248	31	in	in	ADP
fis-5022	248	32	this	this	DET
fis-5022	248	33	dataset	dataset	NOUN
fis-5022	248	34	.	.	PUNCT
fis-5022	249	1	the	the	DET
fis-5022	249	2	analysis	analysis	NOUN
fis-5022	249	3	of	of	ADP
fis-5022	249	4	model	model	NOUN
fis-5022	249	5	performance	performance	NOUN
fis-5022	249	6	shows	show	VERB
fis-5022	249	7	that	that	SCONJ
fis-5022	249	8	the	the	DET
fis-5022	249	9	model	model	NOUN
fis-5022	249	10	trained	train	VERB
fis-5022	249	11	on	on	ADP
fis-5022	249	12	the	the	DET
fis-5022	249	13	lower	low	ADJ
fis-5022	249	14	variability	variability	NOUN
fis-5022	249	15	dataset	dataset	NOUN
fis-5022	249	16	shows	show	VERB
fis-5022	249	17	the	the	DET
fis-5022	249	18	steeper	steep	ADJ
fis-5022	249	19	decrease	decrease	NOUN
fis-5022	249	20	in	in	ADP
fis-5022	249	21	the	the	DET
fis-5022	249	22	training	training	NOUN
fis-5022	249	23	error	error	NOUN
fis-5022	249	24	,	,	PUNCT
fis-5022	249	25	indicating	indicate	VERB
fis-5022	249	26	faster	fast	ADV
fis-5022	249	27	learning	learning	NOUN
fis-5022	249	28	.	.	PUNCT
fis-5022	250	1	the	the	DET
fis-5022	250	2	validation	validation	NOUN
fis-5022	250	3	errors	error	NOUN
fis-5022	250	4	for	for	ADP
fis-5022	250	5	the	the	DET
fis-5022	250	6	lower	low	ADJ
fis-5022	250	7	variability	variability	NOUN
fis-5022	250	8	datasets	dataset	NOUN
fis-5022	250	9	are	be	AUX
fis-5022	250	10	generally	generally	ADV
fis-5022	250	11	lower	low	ADJ
fis-5022	250	12	,	,	PUNCT
fis-5022	250	13	suggesting	suggest	VERB
fis-5022	250	14	the	the	DET
fis-5022	250	15	better	well	ADJ
fis-5022	250	16	performance	performance	NOUN
fis-5022	250	17	and	and	CCONJ
fis-5022	250	18	generalizability	generalizability	NOUN
fis-5022	250	19	.	.	PUNCT
fis-5022	251	1	considering	consider	VERB
fis-5022	251	2	generalizability	generalizability	NOUN
fis-5022	251	3	leads	lead	VERB
fis-5022	251	4	to	to	ADP
fis-5022	251	5	the	the	DET
fis-5022	251	6	following	following	ADJ
fis-5022	251	7	conclusions	conclusion	NOUN
fis-5022	251	8	.	.	PUNCT
fis-5022	252	1	the	the	DET
fis-5022	252	2	model	model	NOUN
fis-5022	252	3	trained	train	VERB
fis-5022	252	4	on	on	ADP
fis-5022	252	5	the	the	DET
fis-5022	252	6	higher	high	ADJ
fis-5022	252	7	variability	variability	NOUN
fis-5022	252	8	dataset	dataset	NOUN
fis-5022	252	9	performs	perform	VERB
fis-5022	252	10	well	well	ADV
fis-5022	252	11	on	on	ADP
fis-5022	252	12	the	the	DET
fis-5022	252	13	test	test	NOUN
fis-5022	252	14	1	1	NUM
fis-5022	252	15	and	and	CCONJ
fis-5022	252	16	2	2	NUM
fis-5022	252	17	sets	set	NOUN
fis-5022	252	18	but	but	CCONJ
fis-5022	252	19	struggles	struggle	VERB
fis-5022	252	20	with	with	ADP
fis-5022	252	21	the	the	DET
fis-5022	252	22	diverse	diverse	ADJ
fis-5022	252	23	conditions	condition	NOUN
fis-5022	252	24	in	in	ADP
fis-5022	252	25	the	the	DET
fis-5022	252	26	test	test	NOUN
fis-5022	252	27	3	3	NUM
fis-5022	252	28	set	set	NOUN
fis-5022	252	29	.	.	PUNCT
fis-5022	253	1	the	the	DET
fis-5022	253	2	model	model	NOUN
fis-5022	253	3	trained	train	VERB
fis-5022	253	4	on	on	ADP
fis-5022	253	5	the	the	DET
fis-5022	253	6	lower	low	ADJ
fis-5022	253	7	variability	variability	NOUN
fis-5022	253	8	dataset	dataset	NOUN
fis-5022	253	9	performs	perform	VERB
fis-5022	253	10	better	well	ADV
fis-5022	253	11	on	on	ADP
fis-5022	253	12	all	all	DET
fis-5022	253	13	three	three	NUM
fis-5022	253	14	validation	validation	NOUN
fis-5022	253	15	sets	set	NOUN
fis-5022	253	16	with	with	ADP
fis-5022	253	17	errors	error	NOUN
fis-5022	253	18	being	be	AUX
fis-5022	253	19	lower	low	ADJ
fis-5022	253	20	and	and	CCONJ
fis-5022	253	21	more	more	ADV
fis-5022	253	22	consistent	consistent	ADJ
fis-5022	253	23	.	.	PUNCT
fis-5022	254	1	training	training	NOUN
fis-5022	254	2	with	with	ADP
fis-5022	254	3	lower	low	ADJ
fis-5022	254	4	variability	variability	NOUN
fis-5022	254	5	data	datum	NOUN
fis-5022	254	6	may	may	AUX
fis-5022	254	7	help	help	VERB
fis-5022	254	8	the	the	DET
fis-5022	254	9	model	model	NOUN
fis-5022	254	10	to	to	PART
fis-5022	254	11	learn	learn	VERB
fis-5022	254	12	more	more	ADV
fis-5022	254	13	quickly	quickly	ADV
fis-5022	254	14	and	and	CCONJ
fis-5022	254	15	perform	perform	VERB
fis-5022	254	16	better	well	ADV
fis-5022	254	17	on	on	ADP
fis-5022	254	18	similar	similar	ADJ
fis-5022	254	19	validation	validation	NOUN
fis-5022	254	20	sets	set	NOUN
fis-5022	254	21	.	.	PUNCT
fis-5022	255	1	for	for	ADP
fis-5022	255	2	datasets	dataset	NOUN
fis-5022	255	3	with	with	ADP
fis-5022	255	4	higher	high	ADJ
fis-5022	255	5	variability	variability	NOUN
fis-5022	255	6	,	,	PUNCT
fis-5022	255	7	more	more	ADV
fis-5022	255	8	sophisticated	sophisticated	ADJ
fis-5022	255	9	models	model	NOUN
fis-5022	255	10	or	or	CCONJ
fis-5022	255	11	additional	additional	ADJ
fis-5022	255	12	training	training	NOUN
fis-5022	255	13	data	datum	NOUN
fis-5022	255	14	may	may	AUX
fis-5022	255	15	be	be	AUX
fis-5022	255	16	required	require	VERB
fis-5022	255	17	to	to	PART
fis-5022	255	18	improve	improve	VERB
fis-5022	255	19	generalizability	generalizability	NOUN
fis-5022	255	20	.	.	PUNCT
fis-5022	256	1	overall	overall	ADV
fis-5022	256	2	,	,	PUNCT
fis-5022	256	3	the	the	DET
fis-5022	256	4	model	model	NOUN
fis-5022	256	5	trained	train	VERB
fis-5022	256	6	on	on	ADP
fis-5022	256	7	the	the	DET
fis-5022	256	8	lower	low	ADJ
fis-5022	256	9	variability	variability	NOUN
fis-5022	256	10	dataset	dataset	NOUN
fis-5022	256	11	shows	show	VERB
fis-5022	256	12	better	well	ADJ
fis-5022	256	13	performance	performance	NOUN
fis-5022	256	14	and	and	CCONJ
fis-5022	256	15	generalizability	generalizability	NOUN
fis-5022	256	16	indicating	indicate	VERB
fis-5022	256	17	that	that	SCONJ
fis-5022	256	18	reducing	reduce	VERB
fis-5022	256	19	variability	variability	NOUN
fis-5022	256	20	in	in	ADP
fis-5022	256	21	training	training	NOUN
fis-5022	256	22	data	datum	NOUN
fis-5022	256	23	may	may	AUX
fis-5022	256	24	lead	lead	VERB
fis-5022	256	25	to	to	ADP
fis-5022	256	26	more	more	ADV
fis-5022	256	27	robust	robust	ADJ
fis-5022	256	28	models	model	NOUN
fis-5022	256	29	.	.	PUNCT
fis-5022	257	1	assessing	assess	VERB
fis-5022	257	2	robustness	robustness	NOUN
fis-5022	257	3	to	to	ADP
fis-5022	257	4	noise	noise	NOUN
fis-5022	257	5	tab	tab	NOUN
fis-5022	257	6	.	.	PUNCT
fis-5022	257	7	4	4	NUM
fis-5022	257	8	demonstrates	demonstrate	VERB
fis-5022	257	9	the	the	DET
fis-5022	257	10	resistance	resistance	NOUN
fis-5022	257	11	of	of	ADP
fis-5022	257	12	the	the	DET
fis-5022	257	13	model	model	NOUN
fis-5022	257	14	toward	toward	ADP
fis-5022	257	15	noise	noise	NOUN
fis-5022	257	16	of	of	ADP
fis-5022	257	17	two	two	NUM
fis-5022	257	18	types	type	NOUN
fis-5022	257	19	.	.	PUNCT
fis-5022	258	1	additive	additive	VERB
fis-5022	258	2	and	and	CCONJ
fis-5022	258	3	multiplicative	multiplicative	ADJ
fis-5022	258	4	gaussian	gaussian	ADJ
fis-5022	258	5	-	-	PUNCT
fis-5022	258	6	type	type	NOUN
fis-5022	258	7	noise	noise	NOUN
fis-5022	258	8	with	with	ADP
fis-5022	258	9	varying	vary	VERB
fis-5022	258	10	standard	standard	ADJ
fis-5022	258	11	deviations	deviation	NOUN
fis-5022	258	12	(	(	PUNCT
fis-5022	258	13	std	std	NOUN
fis-5022	258	14	)	)	PUNCT
fis-5022	258	15	was	be	AUX
fis-5022	258	16	introduced	introduce	VERB
fis-5022	258	17	into	into	ADP
fis-5022	258	18	the	the	DET
fis-5022	258	19	test	test	NOUN
fis-5022	258	20	2	2	NUM
fis-5022	258	21	dataset	dataset	NOUN
fis-5022	258	22	,	,	PUNCT
fis-5022	258	23	and	and	CCONJ
fis-5022	258	24	the	the	DET
fis-5022	258	25	performance	performance	NOUN
fis-5022	258	26	of	of	ADP
fis-5022	258	27	the	the	DET
fis-5022	258	28	optimal	optimal	ADJ
fis-5022	258	29	model	model	NOUN
fis-5022	258	30	(	(	PUNCT
fis-5022	258	31	trained	train	VERB
fis-5022	258	32	on	on	ADP
fis-5022	258	33	the	the	DET
fis-5022	258	34	train	train	NOUN
fis-5022	258	35	5	5	NUM
fis-5022	258	36	dataset	dataset	NOUN
fis-5022	258	37	)	)	PUNCT
fis-5022	258	38	was	be	AUX
fis-5022	258	39	subsequently	subsequently	ADV
fis-5022	258	40	evaluated	evaluate	VERB
fis-5022	258	41	.	.	PUNCT
fis-5022	259	1	it	it	PRON
fis-5022	259	2	is	be	AUX
fis-5022	259	3	worth	worth	ADJ
fis-5022	259	4	reminding	remind	VERB
fis-5022	259	5	that	that	SCONJ
fis-5022	259	6	additive	additive	ADJ
fis-5022	259	7	noise	noise	NOUN
fis-5022	259	8	is	be	AUX
fis-5022	259	9	conditioned	condition	VERB
fis-5022	259	10	by	by	ADP
fis-5022	259	11	background	background	NOUN
fis-5022	259	12	thermal	thermal	ADJ
fis-5022	259	13	reflections	reflection	NOUN
fis-5022	259	14	and	and	CCONJ
fis-5022	259	15	ultimately	ultimately	ADV
fis-5022	259	16	represents	represent	VERB
fis-5022	259	17	a	a	DET
fis-5022	259	18	random	random	ADJ
fis-5022	259	19	noise	noise	NOUN
fis-5022	259	20	of	of	ADP
fis-5022	259	21	an	an	DET
fis-5022	259	22	ir	ir	NOUN
fis-5022	259	23	detector	detector	NOUN
fis-5022	259	24	;	;	PUNCT
fis-5022	259	25	in	in	ADP
fis-5022	259	26	the	the	DET
fis-5022	259	27	most	most	ADJ
fis-5022	259	28	ir	ir	NOUN
fis-5022	259	29	imagers	imager	NOUN
fis-5022	259	30	this	this	DET
fis-5022	259	31	kind	kind	NOUN
fis-5022	259	32	of	of	ADP
fis-5022	259	33	noise	noise	NOUN
fis-5022	259	34	can	can	AUX
fis-5022	259	35	be	be	AUX
fis-5022	259	36	assumed	assume	VERB
fis-5022	259	37	0.01	0.01	NUM
fis-5022	259	38	-	-	PUNCT
fis-5022	259	39	0.1oc	0.1oc	PROPN
fis-5022	259	40	.	.	PUNCT
fis-5022	260	1	additive	additive	ADJ
fis-5022	260	2	noise	noise	NOUN
fis-5022	260	3	is	be	AUX
fis-5022	260	4	added	add	VERB
fis-5022	260	5	to	to	ADP
fis-5022	260	6	temperature	temperature	NOUN
fis-5022	260	7	evolutions	evolution	NOUN
fis-5022	260	8	recorded	record	VERB
fis-5022	260	9	in	in	ADP
fis-5022	260	10	tndt	tndt	ADP
fis-5022	260	11	tests	test	NOUN
fis-5022	260	12	.	.	PUNCT
fis-5022	261	1	in	in	ADP
fis-5022	261	2	its	its	PRON
fis-5022	261	3	turn	turn	NOUN
fis-5022	261	4	,	,	PUNCT
fis-5022	261	5	multiplicative	multiplicative	ADJ
fis-5022	261	6	noise	noise	NOUN
fis-5022	261	7	is	be	AUX
fis-5022	261	8	mainly	mainly	ADV
fis-5022	261	9	determined	determine	VERB
fis-5022	261	10	by	by	ADP
fis-5022	261	11	material	material	NOUN
fis-5022	261	12	surface	surface	NOUN
fis-5022	261	13	clutter	clutter	NOUN
fis-5022	261	14	,	,	PUNCT
fis-5022	261	15	such	such	ADJ
fis-5022	261	16	as	as	ADP
fis-5022	261	17	natural	natural	ADJ
fis-5022	261	18	inhomogeneities	inhomogeneity	NOUN
fis-5022	261	19	in	in	ADP
fis-5022	261	20	absorptivity/	absorptivity/	NUM
fis-5022	261	21	emissivity	emissivity	NOUN
fis-5022	261	22	,	,	PUNCT
fis-5022	261	23	and	and	CCONJ
fis-5022	261	24	it	it	PRON
fis-5022	261	25	is	be	AUX
fis-5022	261	26	proportional	proportional	ADJ
fis-5022	261	27	to	to	ADP
fis-5022	261	28	the	the	DET
fis-5022	261	29	sample	sample	NOUN
fis-5022	261	30	excess	excess	ADJ
fis-5022	261	31	temperature	temperature	NOUN
fis-5022	261	32	;	;	PUNCT
fis-5022	261	33	the	the	DET
fis-5022	261	34	minimum	minimum	ADJ
fis-5022	261	35	amplitude	amplitude	NOUN
fis-5022	261	36	of	of	ADP
fis-5022	261	37	multiplicative	multiplicative	ADJ
fis-5022	261	38	noise	noise	NOUN
fis-5022	261	39	is	be	AUX
fis-5022	261	40	about	about	ADV
fis-5022	261	41	2	2	NUM
fis-5022	261	42	-	-	SYM
fis-5022	261	43	4	4	NUM
fis-5022	261	44	%	%	NOUN
fis-5022	261	45	for	for	ADP
fis-5022	261	46	black	black	ADJ
fis-5022	261	47	body	body	NOUN
fis-5022	261	48	-	-	PUNCT
fis-5022	261	49	like	like	ADJ
fis-5022	261	50	materials	material	NOUN
fis-5022	261	51	[	[	X
fis-5022	261	52	23	23	NUM
fis-5022	261	53	]	]	PUNCT
fis-5022	261	54	.	.	PUNCT
fis-5022	262	1	for	for	ADP
fis-5022	262	2	additive	additive	ADJ
fis-5022	262	3	noise	noise	NOUN
fis-5022	262	4	with	with	ADP
fis-5022	262	5	a	a	DET
fis-5022	262	6	standard	standard	ADJ
fis-5022	262	7	deviation	deviation	NOUN
fis-5022	262	8	of	of	ADP
fis-5022	262	9	up	up	ADP
fis-5022	262	10	to	to	ADP
fis-5022	262	11	0.2oc	0.2oc	NUM
fis-5022	262	12	and	and	CCONJ
fis-5022	262	13	multiplicative	multiplicative	ADJ
fis-5022	262	14	noise	noise	NOUN
fis-5022	262	15	up	up	ADP
fis-5022	262	16	to	to	PART
fis-5022	262	17	2	2	NUM
fis-5022	262	18	%	%	NOUN
fis-5022	262	19	,	,	PUNCT
fis-5022	262	20	the	the	DET
fis-5022	262	21	model	model	NOUN
fis-5022	262	22	quality	quality	NOUN
fis-5022	262	23	metrics	metric	NOUN
fis-5022	262	24	have	have	AUX
fis-5022	262	25	demonstrated	demonstrate	VERB
fis-5022	262	26	only	only	ADJ
fis-5022	262	27	marginal	marginal	ADJ
fis-5022	262	28	reductions	reduction	NOUN
fis-5022	262	29	.	.	PUNCT
fis-5022	263	1	with	with	ADP
fis-5022	263	2	the	the	DET
fis-5022	263	3	additive	additive	ADJ
fis-5022	263	4	noise	noise	NOUN
fis-5022	263	5	increased	increase	VERB
fis-5022	263	6	to	to	ADP
fis-5022	263	7	0.7oc	0.7oc	NUM
fis-5022	263	8	,	,	PUNCT
fis-5022	263	9	the	the	DET
fis-5022	263	10	true	true	ADJ
fis-5022	263	11	positive	positive	ADJ
fis-5022	263	12	rate	rate	NOUN
fis-5022	263	13	(	(	PUNCT
fis-5022	263	14	tpr	tpr	NOUN
fis-5022	263	15	)	)	PUNCT
fis-5022	263	16	has	have	AUX
fis-5022	263	17	revealed	reveal	VERB
fis-5022	263	18	a	a	DET
fis-5022	263	19	minor	minor	ADJ
fis-5022	263	20	decline	decline	NOUN
fis-5022	263	21	,	,	PUNCT
fis-5022	263	22	while	while	SCONJ
fis-5022	263	23	the	the	DET
fis-5022	263	24	negative	negative	ADJ
fis-5022	263	25	predictive	predictive	ADJ
fis-5022	263	26	value	value	NOUN
fis-5022	263	27	(	(	PUNCT
fis-5022	263	28	npv	npv	NOUN
fis-5022	263	29	)	)	PUNCT
fis-5022	263	30	has	have	AUX
fis-5022	263	31	demonstrated	demonstrate	VERB
fis-5022	263	32	a	a	DET
fis-5022	263	33	more	more	ADV
fis-5022	263	34	significant	significant	ADJ
fis-5022	263	35	reduction	reduction	NOUN
fis-5022	263	36	thus	thus	ADV
fis-5022	263	37	indicating	indicate	VERB
fis-5022	263	38	an	an	DET
fis-5022	263	39	increase	increase	NOUN
fis-5022	263	40	in	in	ADP
fis-5022	263	41	false	false	ADJ
fis-5022	263	42	positive	positive	ADJ
fis-5022	263	43	indications	indication	NOUN
fis-5022	263	44	.	.	PUNCT
fis-5022	264	1	it	it	PRON
fis-5022	264	2	is	be	AUX
fis-5022	264	3	interesting	interesting	ADJ
fis-5022	264	4	that	that	SCONJ
fis-5022	264	5	the	the	DET
fis-5022	264	6	introduction	introduction	NOUN
fis-5022	264	7	of	of	ADP
fis-5022	264	8	the	the	DET
fis-5022	264	9	additive	additive	ADJ
fis-5022	264	10	noise	noise	NOUN
fis-5022	264	11	with	with	ADP
fis-5022	264	12	std=1oc	std=1oc	PROPN
fis-5022	264	13	has	have	AUX
fis-5022	264	14	resulted	result	VERB
fis-5022	264	15	in	in	ADP
fis-5022	264	16	the	the	DET
fis-5022	264	17	slightly	slightly	ADV
fis-5022	264	18	higher	high	ADJ
fis-5022	264	19	tpr	tpr	NOUN
fis-5022	264	20	but	but	CCONJ
fis-5022	264	21	significantly	significantly	ADV
fis-5022	264	22	diminished	diminish	VERB
fis-5022	264	23	the	the	DET
fis-5022	264	24	npv	npv	NOUN
fis-5022	264	25	down	down	ADV
fis-5022	264	26	to	to	ADP
fis-5022	264	27	49.3	49.3	NUM
fis-5022	264	28	%	%	NOUN
fis-5022	264	29	.	.	PUNCT
fis-5022	265	1	this	this	PRON
fis-5022	265	2	can	can	AUX
fis-5022	265	3	be	be	AUX
fis-5022	265	4	explained	explain	VERB
fis-5022	265	5	by	by	ADP
fis-5022	265	6	the	the	DET
fis-5022	265	7	0	0	NUM
fis-5022	265	8	2000	2000	NUM
fis-5022	265	9	4000	4000	NUM
fis-5022	265	10	6000	6000	NUM
fis-5022	265	11	8000	8000	NUM
fis-5022	265	12	10000	10000	NUM
fis-5022	265	13	12000	12000	NUM
fis-5022	265	14	14000	14000	NUM
fis-5022	265	15	training	training	NOUN
fis-5022	265	16	set	set	NOUN
fis-5022	265	17	size	size	NOUN
fis-5022	265	18	0	0	NUM
fis-5022	265	19	0.05	0.05	NUM
fis-5022	265	20	0.1	0.1	NUM
fis-5022	265	21	0.15	0.15	NUM
fis-5022	265	22	0.2	0.2	NUM
fis-5022	265	23	0.25	0.25	NUM
fis-5022	265	24	0.3	0.3	NUM
fis-5022	265	25	0.35	0.35	NUM
fis-5022	265	26	0.4	0.4	NUM
fis-5022	265	27	0.45	0.45	NUM
fis-5022	265	28	learning	learn	VERB
fis-5022	265	29	curves	curve	NOUN
fis-5022	265	30	for	for	ADP
fis-5022	265	31	gaussian	gaussian	ADJ
fis-5022	265	32	svm	svm	ADJ
fis-5022	265	33	training	training	NOUN
fis-5022	265	34	error	error	NOUN
fis-5022	265	35	validation	validation	NOUN
fis-5022	265	36	error	error	NOUN
fis-5022	265	37	test	test	NOUN
fis-5022	265	38	set	set	VERB
fis-5022	265	39	1	1	NUM
fis-5022	265	40	validation	validation	NOUN
fis-5022	265	41	error	error	NOUN
fis-5022	265	42	test	test	NOUN
fis-5022	265	43	set	set	VERB
fis-5022	265	44	2	2	NUM
fis-5022	265	45	validation	validation	NOUN
fis-5022	265	46	error	error	NOUN
fis-5022	265	47	test	test	NOUN
fis-5022	265	48	set	set	VERB
fis-5022	265	49	3	3	NUM
fis-5022	265	50	0	0	NUM
fis-5022	265	51	0.2	0.2	NUM
fis-5022	265	52	0.4	0.4	NUM
fis-5022	265	53	0.6	0.6	NUM
fis-5022	265	54	0.8	0.8	NUM
fis-5022	265	55	1	1	NUM
fis-5022	265	56	1.2	1.2	NUM
fis-5022	265	57	1.4	1.4	NUM
fis-5022	265	58	1.6	1.6	NUM
fis-5022	265	59	1.8	1.8	NUM
fis-5022	265	60	2	2	NUM
fis-5022	265	61	2.2	2.2	NUM
fis-5022	265	62	training	training	NOUN
fis-5022	265	63	set	set	NOUN
fis-5022	265	64	size	size	NOUN
fis-5022	265	65	104	104	NUM
fis-5022	265	66	0	0	NUM
fis-5022	265	67	0.05	0.05	NUM
fis-5022	265	68	0.1	0.1	NUM
fis-5022	265	69	0.15	0.15	NUM
fis-5022	265	70	0.2	0.2	NUM
fis-5022	265	71	0.25	0.25	NUM
fis-5022	265	72	0.3	0.3	NUM
fis-5022	265	73	learning	learn	VERB
fis-5022	265	74	curves	curve	NOUN
fis-5022	265	75	for	for	ADP
fis-5022	265	76	gaussian	gaussian	ADJ
fis-5022	265	77	svm	svm	ADJ
fis-5022	265	78	training	training	NOUN
fis-5022	265	79	error	error	NOUN
fis-5022	265	80	validation	validation	NOUN
fis-5022	265	81	error	error	NOUN
fis-5022	265	82	test	test	NOUN
fis-5022	265	83	set	set	VERB
fis-5022	265	84	1	1	NUM
fis-5022	265	85	validation	validation	NOUN
fis-5022	265	86	error	error	NOUN
fis-5022	265	87	test	test	NOUN
fis-5022	265	88	set	set	VERB
fis-5022	265	89	2	2	NUM
fis-5022	265	90	validation	validation	NOUN
fis-5022	265	91	error	error	NOUN
fis-5022	265	92	test	test	NOUN
fis-5022	265	93	set	set	VERB
fis-5022	265	94	3	3	NUM
fis-5022	265	95	a.	a.	NOUN
fis-5022	265	96	chulkov	chulkov	NOUN
fis-5022	265	97	et	et	PROPN
fis-5022	265	98	alii	alii	PROPN
fis-5022	265	99	,	,	PUNCT
fis-5022	265	100	frattura	frattura	PROPN
fis-5022	265	101	ed	ed	PROPN
fis-5022	265	102	integrità	integrità	PROPN
fis-5022	265	103	strutturale	strutturale	PROPN
fis-5022	265	104	,	,	PUNCT
fis-5022	265	105	70	70	NUM
fis-5022	265	106	(	(	PUNCT
fis-5022	265	107	2024	2024	NUM
fis-5022	265	108	)	)	PUNCT
fis-5022	265	109	177	177	NUM
fis-5022	265	110	-	-	SYM
fis-5022	265	111	191	191	NUM
fis-5022	265	112	;	;	PUNCT
fis-5022	265	113	doi	doi	NOUN
fis-5022	265	114	:	:	PUNCT
fis-5022	265	115	10.3221	10.3221	NUM
fis-5022	265	116	/	/	SYM
fis-5022	265	117	igf	igf	NOUN
fis-5022	265	118	-	-	PUNCT
fis-5022	265	119	esis.70.10	esis.70.10	ADJ
fis-5022	265	120	188	188	NUM
fis-5022	265	121	complicated	complicated	ADJ
fis-5022	265	122	combinations	combination	NOUN
fis-5022	265	123	of	of	ADP
fis-5022	265	124	defect	defect	NOUN
fis-5022	265	125	and	and	CCONJ
fis-5022	265	126	noise	noise	NOUN
fis-5022	265	127	signals	signal	NOUN
fis-5022	265	128	,	,	PUNCT
fis-5022	265	129	which	which	PRON
fis-5022	265	130	may	may	AUX
fis-5022	265	131	appear	appear	VERB
fis-5022	265	132	in	in	ADP
fis-5022	265	133	some	some	DET
fis-5022	265	134	particular	particular	ADJ
fis-5022	265	135	cases	case	NOUN
fis-5022	265	136	.	.	PUNCT
fis-5022	266	1	it	it	PRON
fis-5022	266	2	seems	seem	VERB
fis-5022	266	3	that	that	SCONJ
fis-5022	266	4	,	,	PUNCT
fis-5022	266	5	with	with	ADP
fis-5022	266	6	noise	noise	NOUN
fis-5022	266	7	added	add	VERB
fis-5022	266	8	,	,	PUNCT
fis-5022	266	9	some	some	DET
fis-5022	266	10	“	"	PUNCT
fis-5022	266	11	defect	defect	NOUN
fis-5022	266	12	”	"	PUNCT
fis-5022	266	13	pixels	pixel	NOUN
fis-5022	266	14	not	not	PART
fis-5022	266	15	found	find	VERB
fis-5022	266	16	in	in	ADP
fis-5022	266	17	the	the	DET
fis-5022	266	18	raw	raw	ADJ
fis-5022	266	19	data	datum	NOUN
fis-5022	266	20	may	may	AUX
fis-5022	266	21	be	be	AUX
fis-5022	266	22	correctly	correctly	ADV
fis-5022	266	23	identified	identify	VERB
fis-5022	266	24	.	.	PUNCT
fis-5022	267	1	respectively	respectively	ADV
fis-5022	267	2	,	,	PUNCT
fis-5022	267	3	the	the	DET
fis-5022	267	4	tpr	tpr	NOUN
fis-5022	267	5	may	may	AUX
fis-5022	267	6	grow	grow	VERB
fis-5022	267	7	up	up	ADP
fis-5022	267	8	,	,	PUNCT
fis-5022	267	9	but	but	CCONJ
fis-5022	267	10	the	the	DET
fis-5022	267	11	number	number	NOUN
fis-5022	267	12	of	of	ADP
fis-5022	267	13	false	false	ADJ
fis-5022	267	14	positive	positive	ADJ
fis-5022	267	15	indications	indication	NOUN
fis-5022	267	16	also	also	ADV
fis-5022	267	17	increases	increase	VERB
fis-5022	267	18	.	.	PUNCT
fis-5022	268	1	the	the	DET
fis-5022	268	2	results	result	NOUN
fis-5022	268	3	in	in	ADP
fis-5022	268	4	tab	tab	NOUN
fis-5022	268	5	.	.	PUNCT
fis-5022	268	6	4	4	NUM
fis-5022	268	7	show	show	VERB
fis-5022	268	8	that	that	SCONJ
fis-5022	268	9	additive	additive	ADJ
fis-5022	268	10	noise	noise	NOUN
fis-5022	268	11	has	have	AUX
fis-5022	268	12	corrupted	corrupt	VERB
fis-5022	268	13	the	the	DET
fis-5022	268	14	model	model	NOUN
fis-5022	268	15	performance	performance	NOUN
fis-5022	268	16	more	more	ADJ
fis-5022	268	17	than	than	ADP
fis-5022	268	18	multiplicative	multiplicative	ADJ
fis-5022	268	19	noise	noise	NOUN
fis-5022	268	20	.	.	PUNCT
fis-5022	269	1	this	this	PRON
fis-5022	269	2	can	can	AUX
fis-5022	269	3	probably	probably	ADV
fis-5022	269	4	be	be	AUX
fis-5022	269	5	explained	explain	VERB
fis-5022	269	6	by	by	ADP
fis-5022	269	7	relatively	relatively	ADV
fis-5022	269	8	low	low	ADJ
fis-5022	269	9	amplitudes	amplitude	NOUN
fis-5022	269	10	of	of	ADP
fis-5022	269	11	the	the	DET
fis-5022	269	12	multiplicative	multiplicative	ADJ
fis-5022	269	13	noise	noise	NOUN
fis-5022	269	14	(	(	PUNCT
fis-5022	269	15	not	not	PART
fis-5022	269	16	higher	high	ADJ
fis-5022	269	17	than	than	ADP
fis-5022	269	18	4	4	NUM
fis-5022	269	19	%	%	NOUN
fis-5022	269	20	)	)	PUNCT
fis-5022	269	21	.	.	PUNCT
fis-5022	270	1	std	std	NOUN
fis-5022	270	2	of	of	ADP
fis-5022	270	3	additive	additive	ADJ
fis-5022	270	4	noise	noise	NOUN
fis-5022	270	5	,	,	PUNCT
fis-5022	270	6	°	°	ADP
fis-5022	270	7	c	c	NOUN
fis-5022	270	8	std	std	NOUN
fis-5022	270	9	of	of	ADP
fis-5022	270	10	multiplicative	multiplicative	ADJ
fis-5022	270	11	noise	noise	NOUN
fis-5022	270	12	,	,	PUNCT
fis-5022	270	13	%	%	NOUN
fis-5022	270	14	sensitivity	sensitivity	NOUN
fis-5022	270	15	(	(	PUNCT
fis-5022	270	16	tpr	tpr	NOUN
fis-5022	270	17	)	)	PUNCT
fis-5022	270	18	,	,	PUNCT
fis-5022	270	19	%	%	INTJ
fis-5022	270	20	specificity	specificity	NOUN
fis-5022	270	21	(	(	PUNCT
fis-5022	270	22	tnr	tnr	PROPN
fis-5022	270	23	)	)	PUNCT
fis-5022	270	24	,	,	PUNCT
fis-5022	270	25	%	%	NOUN
fis-5022	270	26	precision	precision	NOUN
fis-5022	270	27	(	(	PUNCT
fis-5022	270	28	positive	positive	ADJ
fis-5022	270	29	predictive	predictive	ADJ
fis-5022	270	30	value	value	NOUN
fis-5022	270	31	,	,	PUNCT
fis-5022	270	32	ppv	ppv	NOUN
fis-5022	270	33	)	)	PUNCT
fis-5022	270	34	,	,	PUNCT
fis-5022	270	35	%	%	X
fis-5022	270	36	negative	negative	ADJ
fis-5022	270	37	predictive	predictive	ADJ
fis-5022	270	38	value	value	NOUN
fis-5022	270	39	(	(	PUNCT
fis-5022	270	40	npv	npv	NOUN
fis-5022	270	41	)	)	PUNCT
fis-5022	270	42	,	,	PUNCT
fis-5022	270	43	%	%	NOUN
fis-5022	271	1	0.1	0.1	NUM
fis-5022	271	2	0	0	NUM
fis-5022	271	3	82.3	82.3	NUM
fis-5022	271	4	99.6	99.6	NUM
fis-5022	271	5	95.7	95.7	NUM
fis-5022	271	6	98.3	98.3	NUM
fis-5022	271	7	0.2	0.2	NUM
fis-5022	271	8	0	0	NUM
fis-5022	272	1	81.7	81.7	NUM
fis-5022	272	2	99.0	99.0	NUM
fis-5022	272	3	95.5	95.5	NUM
fis-5022	272	4	95.4	95.4	NUM
fis-5022	272	5	0.5	0.5	NUM
fis-5022	272	6	0	0	NUM
fis-5022	273	1	80.5	80.5	NUM
fis-5022	274	1	94.1	94.1	NUM
fis-5022	274	2	95.0	95.0	NUM
fis-5022	274	3	77.6	77.6	NUM
fis-5022	274	4	0.7	0.7	NUM
fis-5022	274	5	0	0	NUM
fis-5022	274	6	80.5	80.5	NUM
fis-5022	274	7	88.1	88.1	NUM
fis-5022	274	8	94.7	94.7	NUM
fis-5022	274	9	63.2	63.2	NUM
fis-5022	274	10	1	1	NUM
fis-5022	274	11	0	0	NUM
fis-5022	274	12	82.7	82.7	NUM
fis-5022	274	13	78.3	78.3	NUM
fis-5022	274	14	94.7	94.7	NUM
fis-5022	274	15	49.3	49.3	NUM
fis-5022	274	16	0	0	NUM
fis-5022	274	17	2	2	NUM
fis-5022	274	18	81.7	81.7	NUM
fis-5022	274	19	99.3	99.3	NUM
fis-5022	274	20	95.5	95.5	NUM
fis-5022	274	21	96.8	96.8	NUM
fis-5022	274	22	0.2	0.2	NUM
fis-5022	274	23	2	2	NUM
fis-5022	274	24	81.1	81.1	NUM
fis-5022	274	25	98.5	98.5	NUM
fis-5022	274	26	95.3	95.3	NUM
fis-5022	274	27	93.1	93.1	NUM
fis-5022	274	28	0.5	0.5	NUM
fis-5022	274	29	2	2	NUM
fis-5022	274	30	80.7	80.7	NUM
fis-5022	274	31	92.3	92.3	NUM
fis-5022	274	32	94.7	94.7	NUM
fis-5022	274	33	72.7	72.7	NUM
fis-5022	274	34	0	0	NUM
fis-5022	274	35	4	4	NUM
fis-5022	274	36	79.6	79.6	NUM
fis-5022	274	37	97.0	97.0	NUM
fis-5022	274	38	94.9	94.9	NUM
fis-5022	274	39	87.2	87.2	NUM
fis-5022	274	40	0.2	0.2	NUM
fis-5022	274	41	4	4	NUM
fis-5022	274	42	79.6	79.6	NUM
fis-5022	274	43	96.4	96.4	NUM
fis-5022	274	44	94.9	94.9	NUM
fis-5022	274	45	85.1	85.1	NUM
fis-5022	274	46	0.5	0.5	NUM
fis-5022	274	47	4	4	NUM
fis-5022	274	48	79.6	79.6	NUM
fis-5022	274	49	92.4	92.4	NUM
fis-5022	274	50	94.7	94.7	NUM
fis-5022	274	51	72.6	72.6	NUM
fis-5022	274	52	table	table	NOUN
fis-5022	274	53	4	4	NUM
fis-5022	274	54	:	:	PUNCT
fis-5022	274	55	model	model	NOUN
fis-5022	274	56	resistance	resistance	NOUN
fis-5022	274	57	toward	toward	ADP
fis-5022	274	58	noise	noise	NOUN
fis-5022	274	59	.	.	PUNCT
fis-5022	275	1	thermographic	thermographic	ADJ
fis-5022	275	2	data	datum	NOUN
fis-5022	275	3	processing	process	VERB
fis-5022	275	4	this	this	DET
fis-5022	275	5	section	section	NOUN
fis-5022	275	6	explores	explore	VERB
fis-5022	275	7	efficiency	efficiency	NOUN
fis-5022	275	8	of	of	ADP
fis-5022	275	9	some	some	DET
fis-5022	275	10	known	know	VERB
fis-5022	275	11	data	datum	NOUN
fis-5022	275	12	processing	processing	NOUN
fis-5022	275	13	algorithms	algorithm	NOUN
fis-5022	275	14	,	,	PUNCT
fis-5022	275	15	namely	namely	ADV
fis-5022	275	16	,	,	PUNCT
fis-5022	275	17	thermographic	thermographic	ADJ
fis-5022	275	18	signal	signal	NOUN
fis-5022	275	19	reconstruction	reconstruction	NOUN
fis-5022	275	20	(	(	PUNCT
fis-5022	275	21	tsr	tsr	PROPN
fis-5022	275	22	)	)	PUNCT
fis-5022	275	23	,	,	PUNCT
fis-5022	275	24	pulse	pulse	NOUN
fis-5022	275	25	phase	phase	NOUN
fis-5022	275	26	thermography	thermography	NOUN
fis-5022	275	27	(	(	PUNCT
fis-5022	275	28	fourier	fourier	NOUN
fis-5022	275	29	transform	transform	NOUN
fis-5022	275	30	)	)	PUNCT
fis-5022	275	31	,	,	PUNCT
fis-5022	275	32	and	and	CCONJ
fis-5022	275	33	temperature	temperature	NOUN
fis-5022	275	34	contrast	contrast	NOUN
fis-5022	275	35	.	.	PUNCT
fis-5022	276	1	tab	tab	NOUN
fis-5022	276	2	.	.	PUNCT
fis-5022	276	3	5	5	NUM
fis-5022	276	4	shows	show	VERB
fis-5022	276	5	the	the	DET
fis-5022	276	6	quality	quality	NOUN
fis-5022	276	7	metrics	metric	NOUN
fis-5022	276	8	of	of	ADP
fis-5022	276	9	the	the	DET
fis-5022	276	10	model	model	NOUN
fis-5022	276	11	(	(	PUNCT
fis-5022	276	12	the	the	DET
fis-5022	276	13	minimum	minimum	ADJ
fis-5022	276	14	value	value	NOUN
fis-5022	276	15	between	between	ADP
fis-5022	276	16	tpr	tpr	PROPN
fis-5022	276	17	and	and	CCONJ
fis-5022	276	18	tnr	tnr	PROPN
fis-5022	276	19	)	)	PUNCT
fis-5022	276	20	,	,	PUNCT
fis-5022	276	21	which	which	PRON
fis-5022	276	22	was	be	AUX
fis-5022	276	23	trained	train	VERB
fis-5022	276	24	on	on	ADP
fis-5022	276	25	the	the	DET
fis-5022	276	26	train	train	NOUN
fis-5022	276	27	5	5	NUM
fis-5022	276	28	dataset	dataset	NOUN
fis-5022	276	29	processed	process	VERB
fis-5022	276	30	by	by	ADP
fis-5022	276	31	using	use	VERB
fis-5022	276	32	the	the	DET
fis-5022	276	33	abovementioned	abovementioned	ADJ
fis-5022	276	34	algorithms	algorithm	NOUN
fis-5022	276	35	.	.	PUNCT
fis-5022	277	1	dataset	dataset	NOUN
fis-5022	277	2	efficiency	efficiency	NOUN
fis-5022	277	3	raw	raw	ADJ
fis-5022	277	4	temperature	temperature	NOUN
fis-5022	277	5	data	datum	NOUN
fis-5022	277	6	fourier	fourier	NOUN
fis-5022	277	7	phase	phase	NOUN
fis-5022	277	8	tsr	tsr	PROPN
fis-5022	277	9	,	,	PUNCT
fis-5022	277	10	1st	1st	ADJ
fis-5022	277	11	derivative	derivative	ADJ
fis-5022	277	12	contrast	contrast	NOUN
fis-5022	277	13	validation	validation	NOUN
fis-5022	277	14	94.4	94.4	NUM
fis-5022	277	15	89.6	89.6	NUM
fis-5022	277	16	97.0	97.0	NUM
fis-5022	277	17	99.6	99.6	NUM
fis-5022	277	18	test	test	NOUN
fis-5022	277	19	1	1	NUM
fis-5022	277	20	86.6	86.6	NUM
fis-5022	277	21	87.5	87.5	NUM
fis-5022	277	22	87.5	87.5	NUM
fis-5022	277	23	99.9	99.9	NUM
fis-5022	277	24	test	test	NOUN
fis-5022	277	25	2	2	NUM
fis-5022	277	26	82.5	82.5	NUM
fis-5022	277	27	50.0	50.0	NUM
fis-5022	277	28	99.2	99.2	NUM
fis-5022	277	29	98.1	98.1	NUM
fis-5022	277	30	test	test	NOUN
fis-5022	277	31	3	3	NUM
fis-5022	277	32	75.9	75.9	NUM
fis-5022	277	33	37.5	37.5	NUM
fis-5022	277	34	80.8	80.8	NUM
fis-5022	277	35	98.4	98.4	NUM
fis-5022	277	36	table	table	NOUN
fis-5022	277	37	5	5	NUM
fis-5022	277	38	:	:	PUNCT
fis-5022	277	39	data	datum	NOUN
fis-5022	277	40	processing	processing	NOUN
fis-5022	277	41	efficiency	efficiency	NOUN
fis-5022	277	42	(	(	PUNCT
fis-5022	277	43	machine	machine	NOUN
fis-5022	277	44	learning	learning	NOUN
fis-5022	277	45	model	model	NOUN
fis-5022	277	46	)	)	PUNCT
fis-5022	277	47	.	.	PUNCT
fis-5022	278	1	the	the	DET
fis-5022	278	2	table	table	NOUN
fis-5022	278	3	illustrates	illustrate	VERB
fis-5022	278	4	that	that	SCONJ
fis-5022	278	5	the	the	DET
fis-5022	278	6	use	use	NOUN
fis-5022	278	7	of	of	ADP
fis-5022	278	8	fourier	fourier	NOUN
fis-5022	278	9	phasegrams	phasegram	NOUN
fis-5022	278	10	as	as	ADP
fis-5022	278	11	input	input	NOUN
fis-5022	278	12	images	image	NOUN
fis-5022	278	13	has	have	AUX
fis-5022	278	14	surprisingly	surprisingly	ADV
fis-5022	278	15	corrupted	corrupt	VERB
fis-5022	278	16	the	the	DET
fis-5022	278	17	model	model	NOUN
fis-5022	278	18	performance	performance	NOUN
fis-5022	278	19	making	make	VERB
fis-5022	278	20	it	it	PRON
fis-5022	278	21	inappropriate	inappropriate	ADJ
fis-5022	278	22	for	for	ADP
fis-5022	278	23	detecting	detect	VERB
fis-5022	278	24	defects	defect	NOUN
fis-5022	278	25	in	in	ADP
fis-5022	278	26	the	the	DET
fis-5022	278	27	test	test	NOUN
fis-5022	278	28	2	2	NUM
fis-5022	278	29	,	,	PUNCT
fis-5022	278	30	3	3	NUM
fis-5022	278	31	datasets	dataset	NOUN
fis-5022	278	32	.	.	PUNCT
fis-5022	279	1	on	on	ADP
fis-5022	279	2	the	the	DET
fis-5022	279	3	contrary	contrary	NOUN
fis-5022	279	4	,	,	PUNCT
fis-5022	279	5	the	the	DET
fis-5022	279	6	use	use	NOUN
fis-5022	279	7	of	of	ADP
fis-5022	279	8	the	the	DET
fis-5022	279	9	first	first	ADJ
fis-5022	279	10	derivative	derivative	NOUN
fis-5022	279	11	and	and	CCONJ
fis-5022	279	12	contrast	contrast	NOUN
fis-5022	279	13	data	datum	NOUN
fis-5022	279	14	has	have	AUX
fis-5022	279	15	led	lead	VERB
fis-5022	279	16	to	to	ADP
fis-5022	279	17	a	a	DET
fis-5022	279	18	notable	notable	ADJ
fis-5022	279	19	enhancement	enhancement	NOUN
fis-5022	279	20	of	of	ADP
fis-5022	279	21	the	the	DET
fis-5022	279	22	model	model	NOUN
fis-5022	279	23	quality	quality	NOUN
fis-5022	279	24	.	.	PUNCT
fis-5022	280	1	for	for	ADP
fis-5022	280	2	example	example	NOUN
fis-5022	280	3	,	,	PUNCT
fis-5022	280	4	in	in	ADP
fis-5022	280	5	the	the	DET
fis-5022	280	6	case	case	NOUN
fis-5022	280	7	of	of	ADP
fis-5022	280	8	contrast	contrast	NOUN
fis-5022	280	9	,	,	PUNCT
fis-5022	280	10	the	the	DET
fis-5022	280	11	sensitivity	sensitivity	NOUN
fis-5022	280	12	values	value	NOUN
fis-5022	280	13	consistently	consistently	ADV
fis-5022	280	14	surpassed	surpass	VERB
fis-5022	280	15	98	98	NUM
fis-5022	280	16	%	%	NOUN
fis-5022	280	17	across	across	ADP
fis-5022	280	18	all	all	DET
fis-5022	280	19	test	test	NOUN
fis-5022	280	20	datasets	dataset	NOUN
fis-5022	280	21	.	.	PUNCT
fis-5022	281	1	fig	fig	NOUN
fis-5022	281	2	.	.	PUNCT
fis-5022	282	1	5	5	NUM
fis-5022	282	2	provides	provide	VERB
fis-5022	282	3	the	the	DET
fis-5022	282	4	illustrations	illustration	NOUN
fis-5022	282	5	to	to	ADP
fis-5022	282	6	the	the	DET
fis-5022	282	7	model	model	NOUN
fis-5022	282	8	efficiency	efficiency	NOUN
fis-5022	282	9	while	while	SCONJ
fis-5022	282	10	using	use	VERB
fis-5022	282	11	various	various	ADJ
fis-5022	282	12	types	type	NOUN
fis-5022	282	13	of	of	ADP
fis-5022	282	14	the	the	DET
fis-5022	282	15	training	training	NOUN
fis-5022	282	16	models	model	NOUN
fis-5022	282	17	,	,	PUNCT
fis-5022	282	18	which	which	PRON
fis-5022	282	19	are	be	AUX
fis-5022	282	20	applied	apply	VERB
fis-5022	282	21	to	to	ADP
fis-5022	282	22	one	one	NUM
fis-5022	282	23	of	of	ADP
fis-5022	282	24	the	the	DET
fis-5022	282	25	sequences	sequence	NOUN
fis-5022	282	26	related	relate	VERB
fis-5022	282	27	to	to	ADP
fis-5022	282	28	the	the	DET
fis-5022	282	29	test	test	NOUN
fis-5022	282	30	3	3	NUM
fis-5022	282	31	dataset	dataset	NOUN
fis-5022	282	32	.	.	PUNCT
fis-5022	283	1	fig	fig	NOUN
fis-5022	283	2	.	.	PUNCT
fis-5022	284	1	5a	5a	NUM
fis-5022	284	2	shows	show	VERB
fis-5022	284	3	that	that	SCONJ
fis-5022	284	4	the	the	DET
fis-5022	284	5	deepest	deep	ADJ
fis-5022	284	6	defect	defect	NOUN
fis-5022	284	7	was	be	AUX
fis-5022	284	8	not	not	PART
fis-5022	284	9	detected	detect	VERB
fis-5022	284	10	when	when	SCONJ
fis-5022	284	11	using	use	VERB
fis-5022	284	12	raw	raw	ADJ
fis-5022	284	13	temperature	temperature	NOUN
fis-5022	284	14	data	datum	NOUN
fis-5022	284	15	.	.	PUNCT
fis-5022	285	1	the	the	DET
fis-5022	285	2	same	same	ADJ
fis-5022	285	3	results	result	NOUN
fis-5022	285	4	but	but	CCONJ
fis-5022	285	5	with	with	ADP
fis-5022	285	6	some	some	DET
fis-5022	285	7	noisy	noisy	ADJ
fis-5022	285	8	indications	indication	NOUN
fis-5022	285	9	and	and	CCONJ
fis-5022	285	10	more	more	ADV
fis-5022	285	11	distorted	distorted	ADJ
fis-5022	285	12	defect	defect	NOUN
fis-5022	285	13	patterns	pattern	NOUN
fis-5022	285	14	were	be	AUX
fis-5022	285	15	provided	provide	VERB
fis-5022	285	16	by	by	ADP
fis-5022	285	17	the	the	DET
fis-5022	285	18	model	model	NOUN
fis-5022	285	19	where	where	SCONJ
fis-5022	285	20	the	the	DET
fis-5022	285	21	raw	raw	ADJ
fis-5022	285	22	data	datum	NOUN
fis-5022	285	23	was	be	AUX
fis-5022	285	24	corrupted	corrupt	VERB
fis-5022	285	25	by	by	ADP
fis-5022	285	26	the	the	DET
fis-5022	285	27	gaussian	gaussian	ADJ
fis-5022	285	28	noise	noise	NOUN
fis-5022	285	29	(	(	PUNCT
fis-5022	285	30	fig	fig	NOUN
fis-5022	285	31	.	.	PUNCT
fis-5022	286	1	5b	5b	NUM
fis-5022	286	2	)	)	PUNCT
fis-5022	286	3	.	.	PUNCT
fis-5022	287	1	finally	finally	ADV
fis-5022	287	2	,	,	PUNCT
fis-5022	287	3	all	all	DET
fis-5022	287	4	defects	defect	NOUN
fis-5022	287	5	were	be	AUX
fis-5022	287	6	detected	detect	VERB
fis-5022	287	7	when	when	SCONJ
fis-5022	287	8	the	the	DET
fis-5022	287	9	machine	machine	NOUN
fis-5022	287	10	learning	learning	NOUN
fis-5022	287	11	model	model	NOUN
fis-5022	287	12	was	be	AUX
fis-5022	287	13	trained	train	VERB
fis-5022	287	14	on	on	ADP
fis-5022	287	15	the	the	DET
fis-5022	287	16	contrast	contrast	NOUN
fis-5022	287	17	data	datum	NOUN
fis-5022	287	18	(	(	PUNCT
fis-5022	287	19	fig	fig	NOUN
fis-5022	287	20	.	.	PUNCT
fis-5022	287	21	5c	5c	NUM
fis-5022	287	22	)	)	PUNCT
fis-5022	287	23	.	.	PUNCT
fis-5022	288	1	a.	a.	PROPN
fis-5022	288	2	chulkov	chulkov	PROPN
fis-5022	288	3	et	et	PROPN
fis-5022	288	4	alii	alii	PROPN
fis-5022	288	5	,	,	PUNCT
fis-5022	288	6	frattura	frattura	PROPN
fis-5022	288	7	ed	ed	PROPN
fis-5022	288	8	integrità	integrità	PROPN
fis-5022	288	9	strutturale	strutturale	PROPN
fis-5022	288	10	,	,	PUNCT
fis-5022	288	11	70	70	NUM
fis-5022	288	12	(	(	PUNCT
fis-5022	288	13	2024	2024	NUM
fis-5022	288	14	)	)	PUNCT
fis-5022	288	15	177	177	NUM
fis-5022	288	16	-	-	SYM
fis-5022	288	17	191	191	NUM
fis-5022	288	18	;	;	PUNCT
fis-5022	288	19	doi	doi	NOUN
fis-5022	288	20	:	:	PUNCT
fis-5022	288	21	10.3221	10.3221	NUM
fis-5022	288	22	/	/	SYM
fis-5022	288	23	igf	igf	NOUN
fis-5022	288	24	-	-	PUNCT
fis-5022	288	25	esis.70.10	esis.70.10	ADJ
fis-5022	288	26	189	189	NUM
fis-5022	288	27	a	a	NOUN
fis-5022	288	28	)	)	PUNCT
fis-5022	288	29	b	b	NOUN
fis-5022	288	30	)	)	PUNCT
fis-5022	288	31	c	c	NOUN
fis-5022	288	32	)	)	PUNCT
fis-5022	288	33	figure	figure	NOUN
fis-5022	288	34	5	5	NUM
fis-5022	288	35	:	:	PUNCT
fis-5022	288	36	applying	apply	VERB
fis-5022	288	37	machine	machine	NOUN
fis-5022	288	38	learning	learning	NOUN
fis-5022	288	39	model	model	NOUN
fis-5022	288	40	:	:	PUNCT
fis-5022	288	41	a	a	X
fis-5022	288	42	)	)	PUNCT
fis-5022	288	43	raw	raw	ADJ
fis-5022	288	44	data	datum	NOUN
fis-5022	288	45	training	training	NOUN
fis-5022	288	46	;	;	PUNCT
fis-5022	288	47	b	b	X
fis-5022	288	48	)	)	PUNCT
fis-5022	288	49	raw	raw	ADJ
fis-5022	288	50	data	datum	NOUN
fis-5022	288	51	training	training	NOUN
fis-5022	288	52	,	,	PUNCT
fis-5022	288	53	gaussian	gaussian	ADJ
fis-5022	288	54	noise	noise	NOUN
fis-5022	288	55	(	(	PUNCT
fis-5022	288	56	std=0.5	std=0.5	NUM
fis-5022	288	57	°	°	PROPN
fis-5022	288	58	с	с	PROPN
fis-5022	288	59	)	)	PUNCT
fis-5022	288	60	;	;	PUNCT
fis-5022	288	61	c	c	X
fis-5022	288	62	)	)	PUNCT
fis-5022	288	63	contrast	contrast	VERB
fis-5022	288	64	data	datum	NOUN
fis-5022	288	65	training	training	NOUN
fis-5022	288	66	.	.	PUNCT
fis-5022	289	1	discussion	discussion	NOUN
fis-5022	289	2	on	on	ADP
fis-5022	289	3	merits	merit	NOUN
fis-5022	289	4	and	and	CCONJ
fis-5022	289	5	limitations	limitation	NOUN
fis-5022	289	6	this	this	DET
fis-5022	289	7	study	study	NOUN
fis-5022	289	8	provides	provide	VERB
fis-5022	289	9	a	a	DET
fis-5022	289	10	detailed	detailed	ADJ
fis-5022	289	11	analysis	analysis	NOUN
fis-5022	289	12	of	of	ADP
fis-5022	289	13	how	how	SCONJ
fis-5022	289	14	variability	variability	NOUN
fis-5022	289	15	in	in	ADP
fis-5022	289	16	training	training	NOUN
fis-5022	289	17	datasets	dataset	NOUN
fis-5022	289	18	impacts	impact	VERB
fis-5022	289	19	the	the	DET
fis-5022	289	20	performance	performance	NOUN
fis-5022	289	21	of	of	ADP
fis-5022	289	22	machine	machine	NOUN
fis-5022	289	23	learning	learning	NOUN
fis-5022	289	24	models	model	NOUN
fis-5022	289	25	for	for	ADP
fis-5022	289	26	defect	defect	NOUN
fis-5022	289	27	detection	detection	NOUN
fis-5022	289	28	using	use	VERB
fis-5022	289	29	ir	ir	PROPN
fis-5022	289	30	thermographic	thermographic	ADJ
fis-5022	289	31	data	datum	NOUN
fis-5022	289	32	.	.	PUNCT
fis-5022	290	1	by	by	ADP
fis-5022	290	2	incorporating	incorporate	VERB
fis-5022	290	3	different	different	ADJ
fis-5022	290	4	training	training	NOUN
fis-5022	290	5	and	and	CCONJ
fis-5022	290	6	testing	testing	NOUN
fis-5022	290	7	datasets	dataset	NOUN
fis-5022	290	8	,	,	PUNCT
fis-5022	290	9	this	this	DET
fis-5022	290	10	research	research	NOUN
fis-5022	290	11	systematically	systematically	ADV
fis-5022	290	12	evaluates	evaluate	VERB
fis-5022	290	13	model	model	NOUN
fis-5022	290	14	generalizability	generalizability	NOUN
fis-5022	290	15	and	and	CCONJ
fis-5022	290	16	robustness	robustness	NOUN
fis-5022	290	17	.	.	PUNCT
fis-5022	291	1	the	the	DET
fis-5022	291	2	choice	choice	NOUN
fis-5022	291	3	of	of	ADP
fis-5022	291	4	relatively	relatively	ADV
fis-5022	291	5	simple	simple	ADJ
fis-5022	291	6	yet	yet	CCONJ
fis-5022	291	7	effective	effective	ADJ
fis-5022	291	8	models	model	NOUN
fis-5022	291	9	,	,	PUNCT
fis-5022	291	10	such	such	ADJ
fis-5022	291	11	as	as	ADP
fis-5022	291	12	svm	svm	ADJ
fis-5022	291	13	and	and	CCONJ
fis-5022	291	14	bagged	bagged	ADJ
fis-5022	291	15	trees	tree	NOUN
fis-5022	291	16	ensemble	ensemble	ADJ
fis-5022	291	17	,	,	PUNCT
fis-5022	291	18	allows	allow	VERB
fis-5022	291	19	a	a	DET
fis-5022	291	20	clear	clear	ADJ
fis-5022	291	21	understanding	understanding	NOUN
fis-5022	291	22	of	of	ADP
fis-5022	291	23	how	how	SCONJ
fis-5022	291	24	dataset	dataset	ADJ
fis-5022	291	25	variability	variability	NOUN
fis-5022	291	26	influences	influence	VERB
fis-5022	291	27	model	model	NOUN
fis-5022	291	28	performance	performance	NOUN
fis-5022	291	29	.	.	PUNCT
fis-5022	292	1	these	these	DET
fis-5022	292	2	models	model	NOUN
fis-5022	292	3	have	have	AUX
fis-5022	292	4	demonstrated	demonstrate	VERB
fis-5022	292	5	effectiveness	effectiveness	NOUN
fis-5022	292	6	in	in	ADP
fis-5022	292	7	other	other	ADJ
fis-5022	292	8	studies	study	NOUN
fis-5022	292	9	,	,	PUNCT
fis-5022	292	10	thus	thus	ADV
fis-5022	292	11	reinforcing	reinforce	VERB
fis-5022	292	12	their	their	PRON
fis-5022	292	13	suitability	suitability	NOUN
fis-5022	292	14	for	for	ADP
fis-5022	292	15	particular	particular	ADJ
fis-5022	292	16	applications	application	NOUN
fis-5022	292	17	.	.	PUNCT
fis-5022	293	1	the	the	DET
fis-5022	293	2	study	study	NOUN
fis-5022	293	3	design	design	NOUN
fis-5022	293	4	,	,	PUNCT
fis-5022	293	5	which	which	PRON
fis-5022	293	6	implements	implement	VERB
fis-5022	293	7	multiple	multiple	ADJ
fis-5022	293	8	training	training	NOUN
fis-5022	293	9	and	and	CCONJ
fis-5022	293	10	testing	testing	NOUN
fis-5022	293	11	scenarios	scenario	NOUN
fis-5022	293	12	,	,	PUNCT
fis-5022	293	13	facilitates	facilitate	VERB
fis-5022	293	14	the	the	DET
fis-5022	293	15	understanding	understanding	NOUN
fis-5022	293	16	of	of	ADP
fis-5022	293	17	the	the	DET
fis-5022	293	18	model	model	NOUN
fis-5022	293	19	generalizability	generalizability	NOUN
fis-5022	293	20	.	.	PUNCT
fis-5022	294	1	by	by	ADP
fis-5022	294	2	testing	test	VERB
fis-5022	294	3	the	the	DET
fis-5022	294	4	accepted	accept	VERB
fis-5022	294	5	models	model	NOUN
fis-5022	294	6	on	on	ADP
fis-5022	294	7	unseen	unseen	ADJ
fis-5022	294	8	datasets	dataset	NOUN
fis-5022	294	9	,	,	PUNCT
fis-5022	294	10	this	this	DET
fis-5022	294	11	research	research	NOUN
fis-5022	294	12	assesses	assess	VERB
fis-5022	294	13	how	how	SCONJ
fis-5022	294	14	well	well	ADV
fis-5022	294	15	the	the	DET
fis-5022	294	16	models	model	NOUN
fis-5022	294	17	can	can	AUX
fis-5022	294	18	adapt	adapt	VERB
fis-5022	294	19	to	to	ADP
fis-5022	294	20	new	new	ADJ
fis-5022	294	21	data	datum	NOUN
fis-5022	294	22	,	,	PUNCT
fis-5022	294	23	that	that	PRON
fis-5022	294	24	is	be	AUX
fis-5022	294	25	crucial	crucial	ADJ
fis-5022	294	26	for	for	ADP
fis-5022	294	27	practical	practical	ADJ
fis-5022	294	28	deployment	deployment	NOUN
fis-5022	294	29	.	.	PUNCT
fis-5022	295	1	however	however	ADV
fis-5022	295	2	,	,	PUNCT
fis-5022	295	3	some	some	DET
fis-5022	295	4	limitations	limitation	NOUN
fis-5022	295	5	of	of	ADP
fis-5022	295	6	the	the	DET
fis-5022	295	7	technique	technique	NOUN
fis-5022	295	8	under	under	ADP
fis-5022	295	9	discussion	discussion	NOUN
fis-5022	295	10	should	should	AUX
fis-5022	295	11	be	be	AUX
fis-5022	295	12	mentioned	mention	VERB
fis-5022	295	13	.	.	PUNCT
fis-5022	296	1	model	model	NOUN
fis-5022	296	2	complexity	complexity	NOUN
fis-5022	296	3	:	:	PUNCT
fis-5022	296	4	while	while	SCONJ
fis-5022	296	5	the	the	DET
fis-5022	296	6	use	use	NOUN
fis-5022	296	7	of	of	ADP
fis-5022	296	8	simple	simple	ADJ
fis-5022	296	9	models	model	NOUN
fis-5022	296	10	like	like	ADP
fis-5022	296	11	svms	svms	NOUN
fis-5022	296	12	and	and	CCONJ
fis-5022	296	13	bagged	bag	VERB
fis-5022	296	14	trees	tree	NOUN
fis-5022	296	15	ensemble	ensemble	ADJ
fis-5022	296	16	allows	allow	VERB
fis-5022	296	17	for	for	ADP
fis-5022	296	18	the	the	DET
fis-5022	296	19	clear	clear	ADJ
fis-5022	296	20	analysis	analysis	NOUN
fis-5022	296	21	,	,	PUNCT
fis-5022	296	22	it	it	PRON
fis-5022	296	23	may	may	AUX
fis-5022	296	24	limit	limit	VERB
fis-5022	296	25	the	the	DET
fis-5022	296	26	exploration	exploration	NOUN
fis-5022	296	27	of	of	ADP
fis-5022	296	28	more	more	ADJ
fis-5022	296	29	complex	complex	ADJ
fis-5022	296	30	relationships	relationship	NOUN
fis-5022	296	31	within	within	ADP
fis-5022	296	32	the	the	DET
fis-5022	296	33	data	datum	NOUN
fis-5022	296	34	;	;	PUNCT
fis-5022	296	35	advanced	advanced	ADJ
fis-5022	296	36	models	model	NOUN
fis-5022	296	37	such	such	ADJ
fis-5022	296	38	as	as	ADP
fis-5022	296	39	deep	deep	ADJ
fis-5022	296	40	learning	learning	NOUN
fis-5022	296	41	algorithms	algorithm	NOUN
fis-5022	296	42	could	could	AUX
fis-5022	296	43	potentially	potentially	ADV
fis-5022	296	44	capture	capture	VERB
fis-5022	296	45	more	more	ADV
fis-5022	296	46	intricate	intricate	ADJ
fis-5022	296	47	patterns	pattern	NOUN
fis-5022	296	48	,	,	PUNCT
fis-5022	296	49	but	but	CCONJ
fis-5022	296	50	they	they	PRON
fis-5022	296	51	are	be	AUX
fis-5022	296	52	not	not	PART
fis-5022	296	53	considered	consider	VERB
fis-5022	296	54	in	in	ADP
fis-5022	296	55	this	this	DET
fis-5022	296	56	study	study	NOUN
fis-5022	296	57	.	.	PUNCT
fis-5022	297	1	dataset	dataset	ADJ
fis-5022	297	2	limitations	limitation	NOUN
fis-5022	297	3	:	:	PUNCT
fis-5022	297	4	the	the	DET
fis-5022	297	5	study	study	NOUN
fis-5022	297	6	relies	rely	VERB
fis-5022	297	7	on	on	ADP
fis-5022	297	8	numerically	numerically	ADV
fis-5022	297	9	simulated	simulate	VERB
fis-5022	297	10	datasets	dataset	NOUN
fis-5022	297	11	,	,	PUNCT
fis-5022	297	12	which	which	PRON
fis-5022	297	13	,	,	PUNCT
fis-5022	297	14	while	while	SCONJ
fis-5022	297	15	controlled	control	VERB
fis-5022	297	16	,	,	PUNCT
fis-5022	297	17	may	may	AUX
fis-5022	297	18	not	not	PART
fis-5022	297	19	fully	fully	ADV
fis-5022	297	20	capture	capture	VERB
fis-5022	297	21	the	the	DET
fis-5022	297	22	complexity	complexity	NOUN
fis-5022	297	23	and	and	CCONJ
fis-5022	297	24	variability	variability	NOUN
fis-5022	297	25	of	of	ADP
fis-5022	297	26	real	real	ADJ
fis-5022	297	27	data	datum	NOUN
fis-5022	297	28	;	;	PUNCT
fis-5022	297	29	future	future	ADJ
fis-5022	297	30	work	work	NOUN
fis-5022	297	31	could	could	AUX
fis-5022	297	32	include	include	VERB
fis-5022	297	33	experimental	experimental	ADJ
fis-5022	297	34	data	datum	NOUN
fis-5022	297	35	to	to	PART
fis-5022	297	36	further	far	ADV
fis-5022	297	37	validate	validate	VERB
fis-5022	297	38	the	the	DET
fis-5022	297	39	findings	finding	NOUN
fis-5022	297	40	.	.	PUNCT
fis-5022	298	1	overfitting	overfitte	VERB
fis-5022	298	2	concerns	concern	NOUN
fis-5022	298	3	:	:	PUNCT
fis-5022	298	4	although	although	SCONJ
fis-5022	298	5	cross	cross	ADJ
fis-5022	298	6	-	-	ADJ
fis-5022	298	7	validation	validation	NOUN
fis-5022	298	8	was	be	AUX
fis-5022	298	9	used	use	VERB
fis-5022	298	10	to	to	PART
fis-5022	298	11	mitigate	mitigate	VERB
fis-5022	298	12	overfitting	overfitting	NOUN
fis-5022	298	13	,	,	PUNCT
fis-5022	298	14	the	the	DET
fis-5022	298	15	performance	performance	NOUN
fis-5022	298	16	of	of	ADP
fis-5022	298	17	the	the	DET
fis-5022	298	18	models	model	NOUN
fis-5022	298	19	on	on	ADP
fis-5022	298	20	highly	highly	ADV
fis-5022	298	21	variable	variable	ADJ
fis-5022	298	22	datasets	dataset	NOUN
fis-5022	298	23	(	(	PUNCT
fis-5022	298	24	train	train	NOUN
fis-5022	298	25	6	6	NUM
fis-5022	298	26	)	)	PUNCT
fis-5022	298	27	indicates	indicate	VERB
fis-5022	298	28	potential	potential	ADJ
fis-5022	298	29	overfitting	overfitting	NOUN
fis-5022	298	30	;	;	PUNCT
fis-5022	298	31	this	this	PRON
fis-5022	298	32	suggests	suggest	VERB
fis-5022	298	33	that	that	SCONJ
fis-5022	298	34	while	while	SCONJ
fis-5022	298	35	the	the	DET
fis-5022	298	36	models	model	NOUN
fis-5022	298	37	perform	perform	VERB
fis-5022	298	38	well	well	ADV
fis-5022	298	39	on	on	ADP
fis-5022	298	40	less	less	ADJ
fis-5022	298	41	variable	variable	ADJ
fis-5022	298	42	datasets	dataset	NOUN
fis-5022	298	43	,	,	PUNCT
fis-5022	298	44	their	their	PRON
fis-5022	298	45	robustness	robustness	NOUN
fis-5022	298	46	on	on	ADP
fis-5022	298	47	more	more	ADJ
fis-5022	298	48	complex	complex	ADJ
fis-5022	298	49	datasets	dataset	NOUN
fis-5022	298	50	could	could	AUX
fis-5022	298	51	be	be	AUX
fis-5022	298	52	improved	improve	VERB
fis-5022	298	53	.	.	PUNCT
fis-5022	299	1	conclusion	conclusion	NOUN
fis-5022	299	2	n	n	ADP
fis-5022	299	3	this	this	DET
fis-5022	299	4	study	study	NOUN
fis-5022	299	5	,	,	PUNCT
fis-5022	299	6	the	the	DET
fis-5022	299	7	possibility	possibility	NOUN
fis-5022	299	8	of	of	ADP
fis-5022	299	9	enhancing	enhance	VERB
fis-5022	299	10	defect	defect	NOUN
fis-5022	299	11	evaluation	evaluation	NOUN
fis-5022	299	12	in	in	ADP
fis-5022	299	13	ir	ir	PROPN
fis-5022	299	14	thermographic	thermographic	PROPN
fis-5022	299	15	ndt	ndt	PROPN
fis-5022	299	16	through	through	ADP
fis-5022	299	17	the	the	DET
fis-5022	299	18	application	application	NOUN
fis-5022	299	19	of	of	ADP
fis-5022	299	20	machine	machine	NOUN
fis-5022	299	21	learning	learning	NOUN
fis-5022	299	22	models	model	NOUN
fis-5022	299	23	has	have	AUX
fis-5022	299	24	been	be	AUX
fis-5022	299	25	explored	explore	VERB
fis-5022	299	26	.	.	PUNCT
fis-5022	300	1	the	the	DET
fis-5022	300	2	suggested	suggest	VERB
fis-5022	300	3	svm	svm	NOUN
fis-5022	300	4	and	and	CCONJ
fis-5022	300	5	bagged	bag	VERB
fis-5022	300	6	trees	tree	NOUN
fis-5022	300	7	ensemble	ensemble	ADJ
fis-5022	300	8	models	model	NOUN
fis-5022	300	9	were	be	AUX
fis-5022	300	10	trained	train	VERB
fis-5022	300	11	on	on	ADP
fis-5022	300	12	the	the	DET
fis-5022	300	13	data	datum	NOUN
fis-5022	300	14	derived	derive	VERB
fis-5022	300	15	from	from	ADP
fis-5022	300	16	numerical	numerical	ADJ
fis-5022	300	17	simulations	simulation	NOUN
fis-5022	300	18	.	.	PUNCT
fis-5022	301	1	the	the	DET
fis-5022	301	2	number	number	NOUN
fis-5022	301	3	of	of	ADP
fis-5022	301	4	model	model	NOUN
fis-5022	301	5	parameters	parameter	NOUN
fis-5022	301	6	,	,	PUNCT
fis-5022	301	7	including	include	VERB
fis-5022	301	8	material	material	NOUN
fis-5022	301	9	thermal	thermal	ADJ
fis-5022	301	10	properties	property	NOUN
fis-5022	301	11	,	,	PUNCT
fis-5022	301	12	specimen	speciman	NOUN
fis-5022	301	13	thickness	thickness	NOUN
fis-5022	301	14	and	and	CCONJ
fis-5022	301	15	heating	heating	NOUN
fis-5022	301	16	parameters	parameter	NOUN
fis-5022	301	17	,	,	PUNCT
fis-5022	301	18	were	be	AUX
fis-5022	301	19	analyzed	analyze	VERB
fis-5022	301	20	in	in	ADP
fis-5022	301	21	order	order	NOUN
fis-5022	301	22	to	to	PART
fis-5022	301	23	evaluate	evaluate	VERB
fis-5022	301	24	how	how	SCONJ
fis-5022	301	25	general	general	ADJ
fis-5022	301	26	can	can	AUX
fis-5022	301	27	be	be	AUX
fis-5022	301	28	a	a	DET
fis-5022	301	29	model	model	NOUN
fis-5022	301	30	to	to	PART
fis-5022	301	31	be	be	AUX
fis-5022	301	32	used	use	VERB
fis-5022	301	33	in	in	ADP
fis-5022	301	34	machine	machine	NOUN
fis-5022	301	35	learning	learning	NOUN
fis-5022	301	36	.	.	PUNCT
fis-5022	302	1	it	it	PRON
fis-5022	302	2	was	be	AUX
fis-5022	302	3	demonstrated	demonstrate	VERB
fis-5022	302	4	that	that	SCONJ
fis-5022	302	5	the	the	DET
fis-5022	302	6	models	model	NOUN
fis-5022	302	7	trained	train	VERB
fis-5022	302	8	on	on	ADP
fis-5022	302	9	datasets	dataset	NOUN
fis-5022	302	10	with	with	ADP
fis-5022	302	11	fixed	fix	VERB
fis-5022	302	12	parameters	parameter	NOUN
fis-5022	302	13	yielded	yield	VERB
fis-5022	302	14	limited	limited	ADJ
fis-5022	302	15	defect	defect	NOUN
fis-5022	302	16	detection	detection	NOUN
fis-5022	302	17	capabilities	capability	NOUN
fis-5022	302	18	.	.	PUNCT
fis-5022	303	1	introducing	introduce	VERB
fis-5022	303	2	variations	variation	NOUN
fis-5022	303	3	in	in	ADP
fis-5022	303	4	heating	heating	NOUN
fis-5022	303	5	parameters	parameter	NOUN
fis-5022	303	6	proved	prove	VERB
fis-5022	303	7	to	to	PART
fis-5022	303	8	be	be	AUX
fis-5022	303	9	promising	promise	VERB
fis-5022	303	10	for	for	ADP
fis-5022	303	11	detecting	detect	VERB
fis-5022	303	12	defects	defect	NOUN
fis-5022	303	13	with	with	ADP
fis-5022	303	14	minor	minor	ADJ
fis-5022	303	15	parameter	parameter	NOUN
fis-5022	303	16	differences	difference	NOUN
fis-5022	303	17	,	,	PUNCT
fis-5022	303	18	but	but	CCONJ
fis-5022	303	19	it	it	PRON
fis-5022	303	20	appeared	appear	VERB
fis-5022	303	21	unsuccessful	unsuccessful	ADJ
fis-5022	303	22	in	in	ADP
fis-5022	303	23	cases	case	NOUN
fis-5022	303	24	that	that	PRON
fis-5022	303	25	are	be	AUX
fis-5022	303	26	more	more	ADV
fis-5022	303	27	complicated	complicated	ADJ
fis-5022	303	28	.	.	PUNCT
fis-5022	304	1	it	it	PRON
fis-5022	304	2	is	be	AUX
fis-5022	304	3	worth	worth	ADJ
fis-5022	304	4	noting	note	VERB
fis-5022	304	5	that	that	SCONJ
fis-5022	304	6	the	the	DET
fis-5022	304	7	introducing	introducing	NOUN
fis-5022	304	8	of	of	ADP
fis-5022	304	9	variations	variation	NOUN
fis-5022	304	10	in	in	ADP
fis-5022	304	11	specimen	speciman	NOUN
fis-5022	304	12	thickness	thickness	NOUN
fis-5022	304	13	and	and	CCONJ
fis-5022	304	14	thermal	thermal	ADJ
fis-5022	304	15	conductivity	conductivity	NOUN
fis-5022	304	16	worsened	worsen	VERB
fis-5022	304	17	the	the	DET
fis-5022	304	18	model	model	NOUN
fis-5022	304	19	performance	performance	NOUN
fis-5022	304	20	.	.	PUNCT
fis-5022	305	1	the	the	DET
fis-5022	305	2	train	train	NOUN
fis-5022	305	3	5	5	NUM
fis-5022	305	4	dataset	dataset	NOUN
fis-5022	305	5	,	,	PUNCT
fis-5022	305	6	which	which	PRON
fis-5022	305	7	included	include	VERB
fis-5022	305	8	subtle	subtle	ADJ
fis-5022	305	9	variations	variation	NOUN
fis-5022	305	10	in	in	ADP
fis-5022	305	11	specimen	speciman	NOUN
fis-5022	305	12	thickness	thickness	NOUN
fis-5022	305	13	,	,	PUNCT
fis-5022	305	14	thermal	thermal	ADJ
fis-5022	305	15	conductivity	conductivity	NOUN
fis-5022	305	16	,	,	PUNCT
fis-5022	305	17	as	as	ADV
fis-5022	305	18	well	well	ADV
fis-5022	305	19	as	as	ADP
fis-5022	305	20	various	various	ADJ
fis-5022	305	21	combinations	combination	NOUN
fis-5022	305	22	of	of	ADP
fis-5022	305	23	material	material	NOUN
fis-5022	305	24	density	density	NOUN
fis-5022	305	25	and	and	CCONJ
fis-5022	305	26	heat	heat	NOUN
fis-5022	305	27	capacity	capacity	NOUN
fis-5022	305	28	,	,	PUNCT
fis-5022	305	29	provided	provide	VERB
fis-5022	305	30	the	the	DET
fis-5022	305	31	best	good	ADJ
fis-5022	305	32	results	result	NOUN
fis-5022	305	33	and	and	CCONJ
fis-5022	305	34	a	a	DET
fis-5022	305	35	noticeable	noticeable	ADJ
fis-5022	305	36	ability	ability	NOUN
fis-5022	305	37	to	to	PART
fis-5022	305	38	identify	identify	VERB
fis-5022	305	39	defects	defect	NOUN
fis-5022	305	40	in	in	ADP
fis-5022	305	41	all	all	DET
fis-5022	305	42	test	test	NOUN
fis-5022	305	43	datasets	dataset	NOUN
fis-5022	305	44	.	.	PUNCT
fis-5022	306	1	furthermore	furthermore	ADV
fis-5022	306	2	,	,	PUNCT
fis-5022	306	3	the	the	DET
fis-5022	306	4	model	model	NOUN
fis-5022	306	5	robustness	robustness	NOUN
fis-5022	306	6	in	in	ADP
fis-5022	306	7	regard	regard	NOUN
fis-5022	306	8	to	to	ADP
fis-5022	306	9	noise	noise	NOUN
fis-5022	306	10	was	be	AUX
fis-5022	306	11	explored	explore	VERB
fis-5022	306	12	to	to	PART
fis-5022	306	13	demonstrate	demonstrate	VERB
fis-5022	306	14	its	its	PRON
fis-5022	306	15	ability	ability	NOUN
fis-5022	306	16	to	to	PART
fis-5022	306	17	withstand	withstand	VERB
fis-5022	306	18	additive	additive	VERB
fis-5022	306	19	and	and	CCONJ
fis-5022	306	20	multiplicative	multiplicative	ADJ
fis-5022	306	21	random	random	ADJ
fis-5022	306	22	noise	noise	NOUN
fis-5022	306	23	with	with	ADP
fis-5022	306	24	a	a	DET
fis-5022	306	25	standard	standard	ADJ
fis-5022	306	26	deviation	deviation	NOUN
fis-5022	306	27	up	up	ADP
fis-5022	306	28	to	to	PART
fis-5022	306	29	0.5	0.5	NUM
fis-5022	306	30	°	°	NOUN
fis-5022	306	31	c	c	NOUN
fis-5022	306	32	for	for	ADP
fis-5022	306	33	additive	additive	NOUN
fis-5022	306	34	and	and	CCONJ
fis-5022	306	35	2	2	NUM
fis-5022	306	36	%	%	NOUN
fis-5022	306	37	for	for	ADP
fis-5022	306	38	multiplicative	multiplicative	ADJ
fis-5022	306	39	noise	noise	NOUN
fis-5022	306	40	.	.	PUNCT
fis-5022	307	1	however	however	ADV
fis-5022	307	2	,	,	PUNCT
fis-5022	307	3	with	with	ADP
fis-5022	307	4	noise	noise	NOUN
fis-5022	307	5	greater	great	ADJ
fis-5022	307	6	than	than	ADP
fis-5022	307	7	the	the	DET
fis-5022	307	8	above	above	ADV
fis-5022	307	9	-	-	PUNCT
fis-5022	307	10	mentioned	mention	VERB
fis-5022	307	11	thresholds	threshold	NOUN
fis-5022	307	12	,	,	PUNCT
fis-5022	307	13	the	the	DET
fis-5022	307	14	model	model	NOUN
fis-5022	307	15	performance	performance	NOUN
fis-5022	307	16	deteriorated	deteriorate	VERB
fis-5022	307	17	increasing	increase	VERB
fis-5022	307	18	false	false	ADJ
fis-5022	307	19	negative	negative	ADJ
fis-5022	307	20	indications	indication	NOUN
fis-5022	307	21	.	.	PUNCT
fis-5022	308	1	i	i	PRON
fis-5022	308	2	a.	a.	NOUN
fis-5022	308	3	chulkov	chulkov	PROPN
fis-5022	308	4	et	et	PROPN
fis-5022	308	5	alii	alii	PROPN
fis-5022	308	6	,	,	PUNCT
fis-5022	308	7	frattura	frattura	PROPN
fis-5022	308	8	ed	ed	PROPN
fis-5022	308	9	integrità	integrità	PROPN
fis-5022	308	10	strutturale	strutturale	PROPN
fis-5022	308	11	,	,	PUNCT
fis-5022	308	12	70	70	NUM
fis-5022	308	13	(	(	PUNCT
fis-5022	308	14	2024	2024	NUM
fis-5022	308	15	)	)	PUNCT
fis-5022	308	16	177	177	NUM
fis-5022	308	17	-	-	SYM
fis-5022	308	18	191	191	NUM
fis-5022	308	19	;	;	PUNCT
fis-5022	308	20	doi	doi	NOUN
fis-5022	308	21	:	:	PUNCT
fis-5022	308	22	10.3221	10.3221	NUM
fis-5022	308	23	/	/	SYM
fis-5022	308	24	igf	igf	NOUN
fis-5022	308	25	-	-	PUNCT
fis-5022	308	26	esis.70.10	esis.70.10	ADJ
fis-5022	308	27	190	190	NUM
fis-5022	308	28	the	the	DET
fis-5022	308	29	potentials	potential	NOUN
fis-5022	308	30	of	of	ADP
fis-5022	308	31	some	some	DET
fis-5022	308	32	known	know	VERB
fis-5022	308	33	techniques	technique	NOUN
fis-5022	308	34	of	of	ADP
fis-5022	308	35	thermographic	thermographic	ADJ
fis-5022	308	36	data	datum	NOUN
fis-5022	308	37	processing	processing	NOUN
fis-5022	308	38	,	,	PUNCT
fis-5022	308	39	such	such	ADJ
fis-5022	308	40	as	as	ADP
fis-5022	308	41	tsr	tsr	PROPN
fis-5022	308	42	,	,	PUNCT
fis-5022	308	43	fast	fast	ADJ
fis-5022	308	44	fourier	fourier	NOUN
fis-5022	308	45	transform	transform	NOUN
fis-5022	308	46	and	and	CCONJ
fis-5022	308	47	temperature	temperature	NOUN
fis-5022	308	48	contrast	contrast	NOUN
fis-5022	308	49	,	,	PUNCT
fis-5022	308	50	were	be	AUX
fis-5022	308	51	examined	examine	VERB
fis-5022	308	52	.	.	PUNCT
fis-5022	309	1	while	while	SCONJ
fis-5022	309	2	the	the	DET
fis-5022	309	3	efficiency	efficiency	NOUN
fis-5022	309	4	of	of	ADP
fis-5022	309	5	pulse	pulse	NOUN
fis-5022	309	6	phase	phase	NOUN
fis-5022	309	7	thermography	thermography	NOUN
fis-5022	309	8	(	(	PUNCT
fis-5022	309	9	fourier	fourier	NOUN
fis-5022	309	10	transform	transform	NOUN
fis-5022	309	11	)	)	PUNCT
fis-5022	309	12	was	be	AUX
fis-5022	309	13	surprisingly	surprisingly	ADV
fis-5022	309	14	low	low	ADJ
fis-5022	309	15	,	,	PUNCT
fis-5022	309	16	the	the	DET
fis-5022	309	17	use	use	NOUN
fis-5022	309	18	of	of	ADP
fis-5022	309	19	the	the	DET
fis-5022	309	20	first	first	ADJ
fis-5022	309	21	derivatives	derivative	NOUN
fis-5022	309	22	(	(	PUNCT
fis-5022	309	23	tsr	tsr	PROPN
fis-5022	309	24	)	)	PUNCT
fis-5022	309	25	and	and	CCONJ
fis-5022	309	26	contrast	contrast	VERB
fis-5022	309	27	data	datum	NOUN
fis-5022	309	28	significantly	significantly	ADV
fis-5022	309	29	improved	improve	VERB
fis-5022	309	30	the	the	DET
fis-5022	309	31	model	model	NOUN
fis-5022	309	32	efficiency	efficiency	NOUN
fis-5022	309	33	.	.	PUNCT
fis-5022	310	1	in	in	ADP
fis-5022	310	2	particular	particular	ADJ
fis-5022	310	3	,	,	PUNCT
fis-5022	310	4	the	the	DET
fis-5022	310	5	use	use	NOUN
fis-5022	310	6	of	of	ADP
fis-5022	310	7	temperature	temperature	NOUN
fis-5022	310	8	contrast	contrast	NOUN
fis-5022	310	9	data	datum	NOUN
fis-5022	310	10	ensured	ensure	VERB
fis-5022	310	11	sensitivity	sensitivity	NOUN
fis-5022	310	12	(	(	PUNCT
fis-5022	310	13	tpr	tpr	NOUN
fis-5022	310	14	)	)	PUNCT
fis-5022	310	15	better	well	ADJ
fis-5022	310	16	than	than	ADP
fis-5022	310	17	98	98	NUM
fis-5022	310	18	%	%	NOUN
fis-5022	310	19	across	across	ADP
fis-5022	310	20	all	all	DET
fis-5022	310	21	test	test	NOUN
fis-5022	310	22	datasets	dataset	NOUN
fis-5022	310	23	.	.	PUNCT
fis-5022	311	1	in	in	ADP
fis-5022	311	2	conclusion	conclusion	NOUN
fis-5022	311	3	,	,	PUNCT
fis-5022	311	4	this	this	DET
fis-5022	311	5	study	study	NOUN
fis-5022	311	6	has	have	AUX
fis-5022	311	7	revealed	reveal	VERB
fis-5022	311	8	that	that	SCONJ
fis-5022	311	9	machine	machine	NOUN
fis-5022	311	10	-	-	PUNCT
fis-5022	311	11	learning	learn	VERB
fis-5022	311	12	models	model	NOUN
fis-5022	311	13	exhibit	exhibit	VERB
fis-5022	311	14	a	a	DET
fis-5022	311	15	substantial	substantial	ADJ
fis-5022	311	16	potential	potential	NOUN
fis-5022	311	17	for	for	ADP
fis-5022	311	18	enhancing	enhance	VERB
fis-5022	311	19	defect	defect	NOUN
fis-5022	311	20	detection	detection	NOUN
fis-5022	311	21	in	in	ADP
fis-5022	311	22	ir	ir	PROPN
fis-5022	311	23	thermographic	thermographic	PROPN
fis-5022	311	24	ndt	ndt	PROPN
fis-5022	311	25	.	.	PUNCT
fis-5022	312	1	however	however	ADV
fis-5022	312	2	,	,	PUNCT
fis-5022	312	3	further	far	ADV
fis-5022	312	4	expanding	expand	VERB
fis-5022	312	5	results	result	NOUN
fis-5022	312	6	onto	onto	ADP
fis-5022	312	7	different	different	ADJ
fis-5022	312	8	materials	material	NOUN
fis-5022	312	9	and	and	CCONJ
fis-5022	312	10	sample	sample	NOUN
fis-5022	312	11	thicknesses	thickness	NOUN
fis-5022	312	12	requires	require	VERB
fis-5022	312	13	careful	careful	ADJ
fis-5022	312	14	selection	selection	NOUN
fis-5022	312	15	of	of	ADP
fis-5022	312	16	training	training	NOUN
fis-5022	312	17	data	datum	NOUN
fis-5022	312	18	parameters	parameter	NOUN
fis-5022	312	19	,	,	PUNCT
fis-5022	312	20	as	as	SCONJ
fis-5022	312	21	excessive	excessive	ADJ
fis-5022	312	22	variability	variability	NOUN
fis-5022	312	23	in	in	ADP
fis-5022	312	24	the	the	DET
fis-5022	312	25	training	training	NOUN
fis-5022	312	26	data	datum	NOUN
fis-5022	312	27	may	may	AUX
fis-5022	312	28	lead	lead	VERB
fis-5022	312	29	to	to	ADP
fis-5022	312	30	worsened	worsen	VERB
fis-5022	312	31	results	result	NOUN
fis-5022	312	32	.	.	PUNCT
fis-5022	313	1	additionally	additionally	ADV
fis-5022	313	2	,	,	PUNCT
fis-5022	313	3	by	by	ADP
fis-5022	313	4	performing	perform	VERB
fis-5022	313	5	proper	proper	ADJ
fis-5022	313	6	data	datum	NOUN
fis-5022	313	7	processing	processing	NOUN
fis-5022	313	8	,	,	PUNCT
fis-5022	313	9	in	in	ADP
fis-5022	313	10	particular	particular	ADJ
fis-5022	313	11	,	,	PUNCT
fis-5022	313	12	determining	determine	VERB
fis-5022	313	13	temperature	temperature	NOUN
fis-5022	313	14	contrast	contrast	NOUN
fis-5022	313	15	,	,	PUNCT
fis-5022	313	16	one	one	PRON
fis-5022	313	17	may	may	AUX
fis-5022	313	18	significantly	significantly	ADV
fis-5022	313	19	enhance	enhance	VERB
fis-5022	313	20	model	model	NOUN
fis-5022	313	21	performance	performance	NOUN
fis-5022	313	22	.	.	PUNCT
fis-5022	314	1	a	a	DET
fis-5022	314	2	deeper	deep	ADJ
fis-5022	314	3	insight	insight	NOUN
fis-5022	314	4	in	in	ADP
fis-5022	314	5	this	this	DET
fis-5022	314	6	research	research	NOUN
fis-5022	314	7	area	area	NOUN
fis-5022	314	8	is	be	AUX
fis-5022	314	9	a	a	DET
fis-5022	314	10	topic	topic	NOUN
fis-5022	314	11	of	of	ADP
fis-5022	314	12	further	further	ADJ
fis-5022	314	13	research	research	NOUN
fis-5022	314	14	.	.	PUNCT
fis-5022	315	1	references	reference	NOUN
fis-5022	315	2	[	[	X
fis-5022	315	3	1	1	NUM
fis-5022	315	4	]	]	PUNCT
fis-5022	315	5	maldague	maldague	NOUN
fis-5022	315	6	,	,	PUNCT
fis-5022	315	7	x.	x.	NOUN
fis-5022	315	8	(	(	PUNCT
fis-5022	315	9	2001	2001	NUM
fis-5022	315	10	)	)	PUNCT
fis-5022	315	11	.	.	PUNCT
fis-5022	316	1	theory	theory	NOUN
fis-5022	316	2	and	and	CCONJ
fis-5022	316	3	practice	practice	NOUN
fis-5022	316	4	of	of	ADP
fis-5022	316	5	infrared	infrared	ADJ
fis-5022	316	6	technology	technology	NOUN
fis-5022	316	7	for	for	ADP
fis-5022	316	8	nondestructive	nondestructive	ADJ
fis-5022	316	9	testing	testing	NOUN
fis-5022	316	10	,	,	PUNCT
fis-5022	316	11	new	new	PROPN
fis-5022	316	12	york	york	PROPN
fis-5022	316	13	,	,	PUNCT
fis-5022	316	14	wileyinterscience	wileyinterscience	NOUN
fis-5022	316	15	.	.	PUNCT
fis-5022	317	1	[	[	X
fis-5022	317	2	2	2	NUM
fis-5022	317	3	]	]	X
fis-5022	317	4	deane	deane	PROPN
fis-5022	317	5	,	,	PUNCT
fis-5022	317	6	s.	s.	PROPN
fis-5022	317	7	,	,	PUNCT
fis-5022	317	8	avdelidis	avdelidis	PROPN
fis-5022	317	9	,	,	PUNCT
fis-5022	317	10	n.p	n.p	PROPN
fis-5022	317	11	.	.	PROPN
fis-5022	317	12	,	,	PUNCT
fis-5022	317	13	ibarra	ibarra	PROPN
fis-5022	317	14	-	-	PUNCT
fis-5022	317	15	castanedo	castanedo	PROPN
fis-5022	317	16	,	,	PUNCT
fis-5022	317	17	c.	c.	PROPN
fis-5022	317	18	,	,	PUNCT
fis-5022	317	19	zhang	zhang	PROPN
fis-5022	317	20	,	,	PUNCT
fis-5022	317	21	h.	h.	PROPN
fis-5022	317	22	,	,	PUNCT
fis-5022	317	23	nezhad	nezhad	VERB
fis-5022	317	24	,	,	PUNCT
fis-5022	317	25	h.y	h.y	PROPN
fis-5022	317	26	.	.	PROPN
fis-5022	317	27	,	,	PUNCT
fis-5022	317	28	williamson	williamson	PROPN
fis-5022	317	29	,	,	PUNCT
fis-5022	317	30	a.a	a.a	PROPN
fis-5022	317	31	.	.	PROPN
fis-5022	317	32	,	,	PUNCT
fis-5022	317	33	mackley	mackley	PROPN
fis-5022	317	34	,	,	PUNCT
fis-5022	317	35	t.	t.	PROPN
fis-5022	317	36	,	,	PUNCT
fis-5022	317	37	davis	davis	PROPN
fis-5022	317	38	,	,	PUNCT
fis-5022	317	39	m.	m.	NOUN
fis-5022	317	40	,	,	PUNCT
fis-5022	317	41	j.	j.	PROPN
fis-5022	317	42	,	,	PUNCT
fis-5022	317	43	maldague	maldague	NOUN
fis-5022	317	44	x.	x.	NOUN
fis-5022	317	45	and	and	CCONJ
fis-5022	317	46	tsourdos	tsourdo	NOUN
fis-5022	317	47	,	,	PUNCT
fis-5022	317	48	a.	a.	NOUN
fis-5022	317	49	(	(	PUNCT
fis-5022	317	50	2019	2019	NUM
fis-5022	317	51	)	)	PUNCT
fis-5022	317	52	.	.	PUNCT
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fis-5022	318	3	ndt	ndt	PROPN
fis-5022	318	4	thermographic	thermographic	ADJ
fis-5022	318	5	imaging	imaging	NOUN
fis-5022	318	6	of	of	ADP
fis-5022	318	7	aerospace	aerospace	NOUN
fis-5022	318	8	structures	structure	NOUN
fis-5022	318	9	,	,	PUNCT
fis-5022	318	10	infr	infr	PROPN
fis-5022	318	11	.	.	PUNCT
fis-5022	319	1	phys	phy	NOUN
fis-5022	319	2	.	.	PUNCT
fis-5022	320	1	technol	technol	PROPN
fis-5022	320	2	.	.	PROPN
fis-5022	320	3	,	,	PUNCT
fis-5022	320	4	97	97	NUM
fis-5022	320	5	,	,	PUNCT
fis-5022	320	6	pp	pp	ADJ
fis-5022	320	7	.	.	PUNCT
fis-5022	321	1	456	456	NUM
fis-5022	321	2	-	-	SYM
fis-5022	321	3	466	466	NUM
fis-5022	321	4	.	.	PUNCT
fis-5022	322	1	doi	doi	NOUN
fis-5022	322	2	:	:	PUNCT
fis-5022	322	3	10.1016	10.1016	NUM
fis-5022	322	4	/	/	SYM
fis-5022	322	5	j.infrared.2019.02.002	j.infrared.2019.02.002	NOUN
fis-5022	322	6	.	.	PUNCT
fis-5022	323	1	[	[	X
fis-5022	323	2	3	3	NUM
fis-5022	323	3	]	]	X
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fis-5022	323	5	,	,	PUNCT
fis-5022	323	6	n.p	n.p	PROPN
fis-5022	323	7	.	.	PROPN
fis-5022	323	8	,	,	PUNCT
fis-5022	323	9	almond	almond	PROPN
fis-5022	323	10	,	,	PUNCT
fis-5022	323	11	d.p	d.p	PROPN
fis-5022	323	12	.	.	PROPN
fis-5022	323	13	,	,	PUNCT
fis-5022	323	14	dobbinson	dobbinson	PROPN
fis-5022	323	15	,	,	PUNCT
fis-5022	323	16	a.	a.	PROPN
fis-5022	323	17	,	,	PUNCT
fis-5022	323	18	hawtin	hawtin	PROPN
fis-5022	323	19	,	,	PUNCT
fis-5022	323	20	b.c	b.c	PROPN
fis-5022	323	21	.	.	PROPN
fis-5022	323	22	,	,	PUNCT
fis-5022	323	23	ibarra	ibarra	PROPN
fis-5022	323	24	-	-	PUNCT
fis-5022	323	25	castanedo	castanedo	PROPN
fis-5022	323	26	,	,	PUNCT
fis-5022	323	27	c.	c.	PROPN
fis-5022	323	28	and	and	CCONJ
fis-5022	323	29	maldague	maldague	PROPN
fis-5022	323	30	,	,	PUNCT
fis-5022	323	31	x.	x.	NOUN
fis-5022	323	32	(	(	PUNCT
fis-5022	323	33	2004	2004	NUM
fis-5022	323	34	)	)	PUNCT
fis-5022	323	35	.	.	PUNCT
fis-5022	324	1	aircraft	aircraft	NOUN
fis-5022	324	2	composites	composites	PROPN
fis-5022	324	3	assessment	assessment	NOUN
fis-5022	324	4	by	by	ADP
fis-5022	324	5	means	mean	NOUN
fis-5022	324	6	of	of	ADP
fis-5022	324	7	transient	transient	ADJ
fis-5022	324	8	thermal	thermal	ADJ
fis-5022	324	9	ndt	ndt	PROPN
fis-5022	324	10	,	,	PUNCT
fis-5022	324	11	prog	prog	NOUN
fis-5022	324	12	.	.	PUNCT
fis-5022	325	1	aerosp	aerosp	PROPN
fis-5022	325	2	.	.	PUNCT
fis-5022	326	1	sci	sci	PROPN
fis-5022	326	2	.	.	PROPN
fis-5022	326	3	,	,	PUNCT
fis-5022	326	4	40	40	NUM
fis-5022	326	5	,	,	PUNCT
fis-5022	326	6	pp	pp	ADJ
fis-5022	326	7	.	.	PUNCT
fis-5022	327	1	143–62	143–62	NUM
fis-5022	327	2	.	.	PUNCT
fis-5022	328	1	doi	doi	NOUN
fis-5022	328	2	:	:	PUNCT
fis-5022	328	3	10.1016	10.1016	NUM
fis-5022	328	4	/	/	SYM
fis-5022	328	5	j.paerosci.2004.03.001	j.paerosci.2004.03.001	PROPN
fis-5022	328	6	.	.	PUNCT
fis-5022	329	1	[	[	X
fis-5022	329	2	4	4	NUM
fis-5022	329	3	]	]	SYM
fis-5022	329	4	yang	yang	PROPN
fis-5022	329	5	,	,	PUNCT
fis-5022	329	6	r.	r.	PROPN
fis-5022	329	7	,	,	PUNCT
fis-5022	329	8	he	he	PRON
fis-5022	329	9	,	,	PUNCT
fis-5022	329	10	y.	y.	PROPN
fis-5022	329	11	and	and	CCONJ
fis-5022	329	12	zhang	zhang	PROPN
fis-5022	329	13	,	,	PUNCT
fis-5022	329	14	h.	h.	PROPN
fis-5022	329	15	(	(	PUNCT
fis-5022	329	16	2016	2016	NUM
fis-5022	329	17	)	)	PUNCT
fis-5022	329	18	.	.	PUNCT
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fis-5022	329	20	and	and	CCONJ
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fis-5022	329	22	in	in	ADP
fis-5022	329	23	nondestructive	nondestructive	ADJ
fis-5022	329	24	testing	testing	NOUN
fis-5022	329	25	and	and	CCONJ
fis-5022	329	26	evaluation	evaluation	NOUN
fis-5022	329	27	for	for	ADP
fis-5022	329	28	wind	wind	NOUN
fis-5022	329	29	turbine	turbine	NOUN
fis-5022	329	30	composite	composite	ADJ
fis-5022	329	31	blade	blade	NOUN
fis-5022	329	32	,	,	PUNCT
fis-5022	329	33	renew	renew	VERB
fis-5022	329	34	sustain	sustain	NOUN
fis-5022	329	35	.	.	PUNCT
fis-5022	330	1	energy	energy	NOUN
fis-5022	330	2	rev	rev	PROPN
fis-5022	330	3	.	.	PROPN
fis-5022	330	4	,	,	PUNCT
fis-5022	330	5	60	60	NUM
fis-5022	330	6	,	,	PUNCT
fis-5022	330	7	pp	pp	ADJ
fis-5022	330	8	.	.	PUNCT
fis-5022	331	1	1225–50	1225–50	NOUN
fis-5022	331	2	.	.	PUNCT
fis-5022	332	1	doi	doi	NOUN
fis-5022	332	2	:	:	PUNCT
fis-5022	332	3	10.1016	10.1016	NUM
fis-5022	332	4	/	/	SYM
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fis-5022	332	6	.	.	PUNCT
fis-5022	333	1	[	[	X
fis-5022	333	2	5	5	NUM
fis-5022	333	3	]	]	SYM
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fis-5022	333	5	,	,	PUNCT
fis-5022	333	6	b.	b.	PROPN
fis-5022	333	7	,	,	PUNCT
fis-5022	333	8	zhang	zhang	PROPN
fis-5022	333	9	,	,	PUNCT
fis-5022	333	10	l.	l.	PROPN
fis-5022	333	11	,	,	PUNCT
fis-5022	333	12	zhang	zhang	PROPN
fis-5022	333	13	,	,	PUNCT
fis-5022	333	14	w.	w.	PROPN
fis-5022	333	15	and	and	CCONJ
fis-5022	333	16	ai	ai	VERB
fis-5022	333	17	,	,	PUNCT
fis-5022	333	18	y.	y.	PROPN
fis-5022	333	19	(	(	PUNCT
fis-5022	333	20	2013	2013	NUM
fis-5022	333	21	)	)	PUNCT
fis-5022	333	22	.	.	PUNCT
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fis-5022	334	2	-	-	ADJ
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fis-5022	334	4	testing	testing	NOUN
fis-5022	334	5	of	of	ADP
fis-5022	334	6	wind	wind	NOUN
fis-5022	334	7	turbine	turbine	NOUN
fis-5022	334	8	blades	blade	NOUN
fis-5022	334	9	using	use	VERB
fis-5022	334	10	an	an	DET
fis-5022	334	11	infrared	infrared	ADJ
fis-5022	334	12	thermography	thermography	NOUN
fis-5022	334	13	:	:	PUNCT
fis-5022	334	14	a	a	DET
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fis-5022	334	16	.	.	PUNCT
fis-5022	335	1	intern	intern	PROPN
fis-5022	335	2	.	.	PUNCT
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fis-5022	335	4	.	.	PUNCT
fis-5022	336	1	mater	mater	PROPN
fis-5022	336	2	.	.	PUNCT
fis-5022	337	1	for	for	SCONJ
fis-5022	337	2	renew	renew	NOUN
fis-5022	337	3	.	.	PUNCT
fis-5022	337	4	energy	energy	NOUN
fis-5022	337	5	and	and	CCONJ
fis-5022	337	6	environ	environ	PROPN
fis-5022	337	7	.	.	PROPN
fis-5022	337	8	,	,	PUNCT
fis-5022	337	9	chengdu	chengdu	PROPN
fis-5022	337	10	,	,	PUNCT
fis-5022	337	11	china	china	PROPN
fis-5022	337	12	,	,	PUNCT
fis-5022	337	13	pp	pp	ADJ
fis-5022	337	14	.	.	PUNCT
fis-5022	338	1	407	407	NUM
fis-5022	338	2	-	-	SYM
fis-5022	338	3	410	410	NUM
fis-5022	338	4	.	.	PUNCT
fis-5022	339	1	doi	doi	NOUN
fis-5022	339	2	:	:	PUNCT
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fis-5022	339	4	/	/	SYM
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fis-5022	339	6	[	[	X
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fis-5022	339	8	]	]	X
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fis-5022	339	10	,	,	PUNCT
fis-5022	339	11	s.	s.	PROPN
fis-5022	339	12	,	,	PUNCT
fis-5022	339	13	cicone	cicone	PROPN
fis-5022	339	14	,	,	PUNCT
fis-5022	339	15	a.	a.	NOUN
fis-5022	339	16	,	,	PUNCT
fis-5022	339	17	yousefi	yousefi	PROPN
fis-5022	339	18	,	,	PUNCT
fis-5022	339	19	b.	b.	PROPN
fis-5022	339	20	,	,	PUNCT
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fis-5022	339	22	,	,	PUNCT
fis-5022	339	23	s.	s.	PROPN
fis-5022	339	24	,	,	PUNCT
fis-5022	339	25	robol	robol	PROPN
fis-5022	339	26	,	,	PUNCT
fis-5022	339	27	l.	l.	PROPN
fis-5022	339	28	and	and	CCONJ
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fis-5022	339	30	,	,	PUNCT
fis-5022	339	31	x.p.v	x.p.v	PROPN
fis-5022	339	32	.	.	PUNCT
fis-5022	340	1	(	(	PUNCT
fis-5022	340	2	2022	2022	NUM
fis-5022	340	3	)	)	PUNCT
fis-5022	340	4	.	.	PUNCT
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fis-5022	341	2	the	the	DET
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fis-5022	341	4	of	of	ADP
fis-5022	341	5	thermal	thermal	ADJ
fis-5022	341	6	imprints	imprint	NOUN
fis-5022	341	7	in	in	ADP
fis-5022	341	8	civil	civil	ADJ
fis-5022	341	9	engineering	engineering	NOUN
fis-5022	341	10	composites	composite	NOUN
fis-5022	341	11	via	via	ADP
fis-5022	341	12	numerical	numerical	ADJ
fis-5022	341	13	and	and	CCONJ
fis-5022	341	14	thermographic	thermographic	ADJ
fis-5022	341	15	results	result	NOUN
fis-5022	341	16	pre	pre	VERB
fis-5022	341	17	-	-	VERB
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fis-5022	341	19	by	by	ADP
fis-5022	341	20	a	a	DET
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fis-5022	341	23	approach	approach	NOUN
fis-5022	341	24	,	,	PUNCT
fis-5022	341	25	int	int	NOUN
fis-5022	341	26	.	.	PUNCT
fis-5022	342	1	j.	j.	PROPN
fis-5022	342	2	therm	therm	PROPN
fis-5022	342	3	.	.	PUNCT
fis-5022	343	1	sci	sci	PROPN
fis-5022	343	2	.	.	PROPN
fis-5022	343	3	,	,	PUNCT
fis-5022	343	4	177	177	NUM
fis-5022	343	5	,	,	PUNCT
fis-5022	343	6	pp	pp	ADJ
fis-5022	343	7	.	.	PUNCT
fis-5022	343	8	107553	107553	NUM
fis-5022	343	9	.	.	PUNCT
fis-5022	344	1	doi	doi	NOUN
fis-5022	344	2	:	:	PUNCT
fis-5022	344	3	10.1016	10.1016	NUM
fis-5022	344	4	/	/	SYM
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fis-5022	344	6	.	.	PUNCT
fis-5022	345	1	[	[	X
fis-5022	345	2	7	7	NUM
fis-5022	345	3	]	]	PUNCT
fis-5022	345	4	gholizadeh	gholizadeh	NOUN
fis-5022	345	5	,	,	PUNCT
fis-5022	345	6	s.	s.	PROPN
fis-5022	345	7	a	a	DET
fis-5022	345	8	review	review	NOUN
fis-5022	345	9	of	of	ADP
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fis-5022	345	11	-	-	ADJ
fis-5022	345	12	destructive	destructive	ADJ
fis-5022	345	13	testing	testing	NOUN
fis-5022	345	14	methods	method	NOUN
fis-5022	345	15	of	of	ADP
fis-5022	345	16	composite	composite	ADJ
fis-5022	345	17	materials	material	NOUN
fis-5022	345	18	.	.	PUNCT
fis-5022	346	1	(	(	PUNCT
fis-5022	346	2	2016	2016	NUM
fis-5022	346	3	)	)	PUNCT
fis-5022	346	4	.	.	PUNCT
fis-5022	347	1	procedia	procedia	PROPN
fis-5022	347	2	.	.	PUNCT
fis-5022	347	3	struct	struct	NOUN
fis-5022	347	4	.	.	PUNCT
fis-5022	348	1	integr	integr	PROPN
fis-5022	348	2	.	.	PUNCT
fis-5022	348	3	,	,	PUNCT
fis-5022	348	4	1	1	NUM
fis-5022	348	5	,	,	PUNCT
fis-5022	348	6	pp	pp	ADJ
fis-5022	348	7	.	.	PUNCT
fis-5022	349	1	50–57	50–57	NUM
fis-5022	349	2	.	.	PUNCT
fis-5022	350	1	doi	doi	NOUN
fis-5022	350	2	:	:	PUNCT
fis-5022	350	3	10.1016	10.1016	NUM
fis-5022	350	4	/	/	SYM
fis-5022	350	5	j.prostr.2016.02.008	j.prostr.2016.02.008	PROPN
fis-5022	350	6	.	.	PUNCT
fis-5022	351	1	[	[	X
fis-5022	351	2	8	8	NUM
fis-5022	351	3	]	]	X
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fis-5022	351	5	,	,	PUNCT
fis-5022	351	6	s.m	s.m	PROPN
fis-5022	351	7	.	.	PROPN
fis-5022	351	8	(	(	PUNCT
fis-5022	351	9	2007	2007	NUM
fis-5022	351	10	)	)	PUNCT
fis-5022	351	11	.	.	PUNCT
fis-5022	352	1	flash	flash	NOUN
fis-5022	352	2	thermography	thermography	NOUN
fis-5022	352	3	of	of	ADP
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fis-5022	352	5	composites	composite	NOUN
fis-5022	352	6	.	.	PUNCT
fis-5022	353	1	iv	iv	NUM
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fis-5022	353	3	panamericana	panamericana	PROPN
fis-5022	353	4	de	de	PROPN
fis-5022	353	5	end	end	PROPN
fis-5022	353	6	,	,	PUNCT
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fis-5022	353	9	,	,	PUNCT
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fis-5022	353	11	.	.	PUNCT
fis-5022	354	1	[	[	X
fis-5022	354	2	9	9	NUM
fis-5022	354	3	]	]	X
fis-5022	354	4	liu	liu	PROPN
fis-5022	354	5	,	,	PUNCT
fis-5022	354	6	y.	y.	PROPN
fis-5022	354	7	and	and	CCONJ
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fis-5022	354	9	,	,	PUNCT
fis-5022	354	10	y.	y.	PROPN
fis-5022	354	11	(	(	PUNCT
fis-5022	354	12	2022	2022	NUM
fis-5022	354	13	)	)	PUNCT
fis-5022	354	14	.	.	PUNCT
fis-5022	355	1	review	review	NOUN
fis-5022	355	2	on	on	ADP
fis-5022	355	3	automated	automate	VERB
fis-5022	355	4	condition	condition	NOUN
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fis-5022	355	6	of	of	ADP
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fis-5022	355	11	,	,	PUNCT
fis-5022	355	12	adv	adv	PROPN
fis-5022	355	13	.	.	PUNCT
fis-5022	356	1	eng	eng	PROPN
fis-5022	356	2	.	.	PUNCT
fis-5022	357	1	informatics	informatics	PROPN
fis-5022	357	2	,	,	PUNCT
fis-5022	357	3	53	53	NUM
fis-5022	357	4	,	,	PUNCT
fis-5022	357	5	pp	pp	ADJ
fis-5022	357	6	.	.	PUNCT
fis-5022	357	7	101687	101687	NUM
fis-5022	357	8	.	.	PUNCT
fis-5022	358	1	doi	doi	NOUN
fis-5022	358	2	:	:	PUNCT
fis-5022	358	3	10.1016	10.1016	NUM
fis-5022	358	4	/	/	SYM
fis-5022	358	5	j.aei.2022.101687	j.aei.2022.101687	NOUN
fis-5022	358	6	.	.	PUNCT
fis-5022	359	1	[	[	X
fis-5022	359	2	10	10	NUM
fis-5022	359	3	]	]	SYM
fis-5022	359	4	niccolai	niccolai	NOUN
fis-5022	359	5	,	,	PUNCT
fis-5022	359	6	a.	a.	PROPN
fis-5022	359	7	,	,	PUNCT
fis-5022	359	8	caputo	caputo	PROPN
fis-5022	359	9	,	,	PUNCT
fis-5022	359	10	d.	d.	PROPN
fis-5022	359	11	,	,	PUNCT
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fis-5022	359	13	,	,	PUNCT
fis-5022	359	14	l	l	NOUN
fis-5022	359	15	,	,	PUNCT
fis-5022	359	16	grimaccia	grimaccia	NOUN
fis-5022	359	17	,	,	PUNCT
fis-5022	359	18	f.	f.	PROPN
fis-5022	359	19	and	and	CCONJ
fis-5022	359	20	mussetta	mussetta	NOUN
fis-5022	359	21	,	,	PUNCT
fis-5022	359	22	m.	m.	NOUN
fis-5022	359	23	(	(	PUNCT
fis-5022	359	24	2021	2021	NUM
fis-5022	359	25	)	)	PUNCT
fis-5022	359	26	.	.	PUNCT
fis-5022	360	1	machine	machine	NOUN
fis-5022	360	2	learning	learning	NOUN
fis-5022	360	3	-	-	PUNCT
fis-5022	360	4	based	base	VERB
fis-5022	360	5	detection	detection	NOUN
fis-5022	360	6	technique	technique	NOUN
fis-5022	360	7	for	for	ADP
fis-5022	360	8	ndt	ndt	PROPN
fis-5022	360	9	in	in	ADP
fis-5022	360	10	industrial	industrial	ADJ
fis-5022	360	11	manufacturing	manufacturing	NOUN
fis-5022	360	12	,	,	PUNCT
fis-5022	360	13	mathematics	mathematic	NOUN
fis-5022	360	14	,	,	PUNCT
fis-5022	360	15	9	9	NUM
fis-5022	360	16	,	,	PUNCT
fis-5022	360	17	p.	p.	NOUN
fis-5022	360	18	1251	1251	NUM
fis-5022	360	19	.	.	PUNCT
fis-5022	361	1	doi	doi	NOUN
fis-5022	361	2	:	:	PUNCT
fis-5022	361	3	10.3390	10.3390	NUM
fis-5022	361	4	/	/	SYM
fis-5022	361	5	math9111251	math9111251	PROPN
fis-5022	361	6	.	.	PUNCT
fis-5022	362	1	[	[	X
fis-5022	362	2	11	11	NUM
fis-5022	362	3	]	]	SYM
fis-5022	362	4	westphal	westphal	PROPN
fis-5022	362	5	,	,	PUNCT
fis-5022	362	6	e.	e.	PROPN
fis-5022	362	7	and	and	CCONJ
fis-5022	362	8	seitz	seitz	PROPN
fis-5022	362	9	,	,	PUNCT
fis-5022	362	10	h.	h.	PROPN
fis-5022	362	11	(	(	PUNCT
fis-5022	362	12	2021	2021	NUM
fis-5022	362	13	)	)	PUNCT
fis-5022	362	14	.	.	PUNCT
fis-5022	363	1	a	a	DET
fis-5022	363	2	machine	machine	NOUN
fis-5022	363	3	learning	learn	VERB
fis-5022	363	4	method	method	NOUN
fis-5022	363	5	for	for	ADP
fis-5022	363	6	defect	defect	NOUN
fis-5022	363	7	detection	detection	NOUN
fis-5022	363	8	and	and	CCONJ
fis-5022	363	9	visualization	visualization	NOUN
fis-5022	363	10	in	in	ADP
fis-5022	363	11	selective	selective	ADJ
fis-5022	363	12	laser	laser	NOUN
fis-5022	363	13	sintering	sintering	NOUN
fis-5022	363	14	based	base	VERB
fis-5022	363	15	on	on	ADP
fis-5022	363	16	convolutional	convolutional	ADJ
fis-5022	363	17	neural	neural	ADJ
fis-5022	363	18	networks	network	NOUN
fis-5022	363	19	,	,	PUNCT
fis-5022	363	20	addit	addit	NOUN
fis-5022	363	21	.	.	PUNCT
fis-5022	364	1	manuf	manuf	PROPN
fis-5022	364	2	.	.	PROPN
fis-5022	364	3	,	,	PUNCT
fis-5022	364	4	41	41	NUM
fis-5022	364	5	,	,	PUNCT
fis-5022	364	6	p.	p.	NOUN
fis-5022	364	7	101965	101965	NUM
fis-5022	364	8	.	.	PUNCT
fis-5022	365	1	doi	doi	NOUN
fis-5022	365	2	:	:	PUNCT
fis-5022	365	3	10.1016	10.1016	NUM
fis-5022	365	4	/	/	SYM
fis-5022	365	5	j.addma.2021.101965	j.addma.2021.101965	NOUN
fis-5022	365	6	.	.	PUNCT
fis-5022	366	1	[	[	X
fis-5022	366	2	12	12	NUM
fis-5022	366	3	]	]	X
fis-5022	366	4	khodayar	khodayar	PROPN
fis-5022	366	5	f.	f.	PROPN
fis-5022	366	6	,	,	PUNCT
fis-5022	366	7	sajasi	sajasi	PROPN
fis-5022	366	8	s.	s.	PROPN
fis-5022	366	9	and	and	CCONJ
fis-5022	366	10	maldague	maldague	PROPN
fis-5022	366	11	x.	x.	NOUN
fis-5022	366	12	(	(	PUNCT
fis-5022	366	13	2016	2016	NUM
fis-5022	366	14	)	)	PUNCT
fis-5022	366	15	.	.	PUNCT
fis-5022	367	1	infrared	infrared	ADJ
fis-5022	367	2	thermography	thermography	NOUN
fis-5022	367	3	and	and	CCONJ
fis-5022	367	4	ndt	ndt	PROPN
fis-5022	367	5	:	:	PUNCT
fis-5022	367	6	2050	2050	NUM
fis-5022	367	7	horizon	horizon	NOUN
fis-5022	367	8	,	,	PUNCT
fis-5022	367	9	quantit	quantit	PROPN
fis-5022	367	10	.	.	PUNCT
fis-5022	368	1	infrared	infrared	PROPN
fis-5022	368	2	thermogr	thermogr	PROPN
fis-5022	368	3	.	.	PUNCT
fis-5022	369	1	j.	j.	PROPN
fis-5022	369	2	,	,	PUNCT
fis-5022	369	3	13(2	13(2	PROPN
fis-5022	369	4	)	)	PUNCT
fis-5022	369	5	,	,	PUNCT
fis-5022	369	6	p.	p.	NOUN
fis-5022	369	7	210	210	NUM
fis-5022	369	8	-	-	SYM
fis-5022	369	9	231	231	NUM
fis-5022	369	10	.	.	PUNCT
fis-5022	370	1	[	[	X
fis-5022	370	2	13	13	NUM
fis-5022	370	3	]	]	X
fis-5022	370	4	jiuxiang	jiuxiang	PROPN
fis-5022	370	5	gu	gu	PROPN
fis-5022	370	6	,	,	PUNCT
fis-5022	370	7	zhenhuan	zhenhuan	PROPN
fis-5022	370	8	wang	wang	PROPN
fis-5022	370	9	,	,	PUNCT
fis-5022	370	10	kuen	kuen	PROPN
fis-5022	370	11	j.	j.	PROPN
fis-5022	370	12	,	,	PUNCT
fis-5022	370	13	lianyang	lianyang	PROPN
fis-5022	370	14	ma	ma	PROPN
fis-5022	370	15	,	,	PUNCT
fis-5022	370	16	shahroudy	shahroudy	PROPN
fis-5022	370	17	a.	a.	PROPN
fis-5022	370	18	,	,	PUNCT
fis-5022	370	19	bing	bing	NOUN
fis-5022	370	20	shuai	shuai	PROPN
fis-5022	370	21	,	,	PUNCT
fis-5022	370	22	ting	ting	PROPN
fis-5022	370	23	liu	liu	PROPN
fis-5022	370	24	,	,	PUNCT
fis-5022	370	25	xingxing	xingxing	PROPN
fis-5022	370	26	wang	wang	PROPN
fis-5022	370	27	,	,	PUNCT
fis-5022	370	28	gang	gang	PROPN
fis-5022	370	29	wang	wang	PROPN
fis-5022	370	30	,	,	PUNCT
fis-5022	370	31	jianfei	jianfei	PROPN
fis-5022	370	32	cai	cai	PROPN
fis-5022	370	33	and	and	CCONJ
fis-5022	370	34	tsuhan	tsuhan	INTJ
fis-5022	370	35	chen	chen	PROPN
fis-5022	370	36	.	.	PUNCT
fis-5022	371	1	recent	recent	ADJ
fis-5022	371	2	advances	advance	NOUN
fis-5022	371	3	in	in	ADP
fis-5022	371	4	convolutional	convolutional	ADJ
fis-5022	371	5	neural	neural	ADJ
fis-5022	371	6	networks	network	NOUN
fis-5022	371	7	.	.	PUNCT
fis-5022	372	1	(	(	PUNCT
fis-5022	372	2	2018	2018	NUM
fis-5022	372	3	)	)	PUNCT
fis-5022	372	4	.	.	PUNCT
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fis-5022	373	2	recognition	recognition	NOUN
fis-5022	373	3	,	,	PUNCT
fis-5022	373	4	77	77	NUM
fis-5022	373	5	,	,	PUNCT
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fis-5022	373	7	.	.	PUNCT
fis-5022	374	1	354	354	NUM
fis-5022	374	2	-	-	SYM
fis-5022	374	3	377	377	NUM
fis-5022	374	4	.	.	PUNCT
fis-5022	375	1	[	[	X
fis-5022	375	2	14	14	NUM
fis-5022	375	3	]	]	PUNCT
fis-5022	375	4	yunze	yunze	NOUN
fis-5022	375	5	he	he	PRON
fis-5022	375	6	,	,	PUNCT
fis-5022	375	7	baoyuan	baoyuan	PROPN
fis-5022	375	8	deng	deng	PROPN
fis-5022	375	9	,	,	PUNCT
fis-5022	375	10	hongjing	hongje	VERB
fis-5022	375	11	wang	wang	PROPN
fis-5022	375	12	,	,	PUNCT
fis-5022	375	13	liang	liang	PROPN
fis-5022	375	14	cheng	cheng	PROPN
fis-5022	375	15	,	,	PUNCT
fis-5022	375	16	ke	ke	PROPN
fis-5022	375	17	zhou	zhou	PROPN
fis-5022	375	18	,	,	PUNCT
fis-5022	375	19	siyan	siyan	X
fis-5022	375	20	cai	cai	X
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fis-5022	375	22	ciampa	ciampa	PROPN
fis-5022	375	23	,	,	PUNCT
fis-5022	375	24	f.	f.	PROPN
fis-5022	375	25	(	(	PUNCT
fis-5022	375	26	2021	2021	NUM
fis-5022	375	27	)	)	PUNCT
fis-5022	375	28	.	.	PUNCT
fis-5022	376	1	infrared	infrared	ADJ
fis-5022	376	2	machine	machine	NOUN
fis-5022	376	3	vision	vision	NOUN
fis-5022	376	4	and	and	CCONJ
fis-5022	376	5	infrared	infrared	ADJ
fis-5022	376	6	thermography	thermography	NOUN
fis-5022	376	7	with	with	ADP
fis-5022	376	8	deep	deep	ADJ
fis-5022	376	9	learning	learning	NOUN
fis-5022	376	10	:	:	PUNCT
fis-5022	376	11	a	a	DET
fis-5022	376	12	review	review	NOUN
fis-5022	376	13	.	.	PUNCT
fis-5022	377	1	infr	infr	PROPN
fis-5022	377	2	.	.	PUNCT
fis-5022	378	1	phys	phys	PROPN
fis-5022	378	2	.	.	PUNCT
fis-5022	378	3	&	&	CCONJ
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fis-5022	378	5	.	.	PROPN
fis-5022	378	6	,	,	PUNCT
fis-5022	378	7	116	116	NUM
fis-5022	378	8	,	,	PUNCT
fis-5022	378	9	p.	p.	NOUN
fis-5022	378	10	103754	103754	NUM
fis-5022	378	11	.	.	PUNCT
fis-5022	379	1	[	[	X
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fis-5022	379	3	]	]	X
fis-5022	379	4	yousefi	yousefi	PROPN
fis-5022	379	5	,	,	PUNCT
fis-5022	379	6	b.	b.	PROPN
fis-5022	379	7	,	,	PUNCT
fis-5022	379	8	kalhor	kalhor	PROPN
fis-5022	379	9	,	,	PUNCT
fis-5022	379	10	d.	d.	PROPN
fis-5022	379	11	,	,	PUNCT
fis-5022	379	12	usamentiaga	usamentiaga	PROPN
fis-5022	379	13	,	,	PUNCT
fis-5022	379	14	r.	r.	PROPN
fis-5022	379	15	,	,	PUNCT
fis-5022	379	16	lei	lei	PROPN
fis-5022	379	17	,	,	PUNCT
fis-5022	379	18	l.	l.	PROPN
fis-5022	379	19	,	,	PUNCT
fis-5022	379	20	ibarra	ibarra	PROPN
fis-5022	379	21	-	-	PUNCT
fis-5022	379	22	castanedo	castanedo	PROPN
fis-5022	379	23	,	,	PUNCT
fis-5022	379	24	c.	c.	PROPN
fis-5022	379	25	and	and	CCONJ
fis-5022	379	26	maldague	maldague	NOUN
fis-5022	379	27	,	,	PUNCT
fis-5022	379	28	x.p.v	x.p.v	PROPN
fis-5022	379	29	.	.	PUNCT
fis-5022	379	30	(	(	PUNCT
fis-5022	379	31	2018	2018	NUM
fis-5022	379	32	)	)	PUNCT
fis-5022	379	33	.	.	PUNCT
fis-5022	380	1	application	application	NOUN
fis-5022	380	2	of	of	ADP
fis-5022	380	3	deep	deep	ADJ
fis-5022	380	4	learning	learning	NOUN
fis-5022	380	5	in	in	ADP
fis-5022	380	6	infrared	infrared	ADJ
fis-5022	380	7	nondestructive	nondestructive	ADJ
fis-5022	380	8	testing	testing	NOUN
fis-5022	380	9	.	.	PUNCT
fis-5022	381	1	conf	conf	NOUN
fis-5022	381	2	.	.	PUNCT
fis-5022	382	1	2018	2018	NUM
fis-5022	382	2	quantitative	quantitative	ADJ
fis-5022	382	3	infrared	infrared	ADJ
fis-5022	382	4	thermography	thermography	NOUN
fis-5022	382	5	,	,	PUNCT
fis-5022	382	6	pp	pp	PROPN
fis-5022	382	7	.	.	PUNCT
fis-5022	383	1	97	97	NUM
fis-5022	383	2	-	-	SYM
fis-5022	383	3	105	105	NUM
fis-5022	383	4	.	.	PUNCT
fis-5022	384	1	doi	doi	NOUN
fis-5022	384	2	:	:	PUNCT
fis-5022	384	3	10.21611	10.21611	NUM
fis-5022	384	4	/	/	SYM
fis-5022	384	5	qirt.2018.p27	qirt.2018.p27	NOUN
fis-5022	384	6	.	.	PUNCT
fis-5022	385	1	[	[	X
fis-5022	385	2	16	16	NUM
fis-5022	385	3	]	]	X
fis-5022	385	4	haiyi	haiyi	PROPN
fis-5022	385	5	wu	wu	PROPN
fis-5022	385	6	,	,	PUNCT
fis-5022	385	7	hongwei	hongwei	PROPN
fis-5022	385	8	zhang	zhang	PROPN
fis-5022	385	9	,	,	PUNCT
fis-5022	385	10	guoqing	guoqe	VERB
fis-5022	385	11	hu	hu	PROPN
fis-5022	385	12	and	and	CCONJ
fis-5022	385	13	rui	rui	PROPN
fis-5022	385	14	qiao	qiao	PROPN
fis-5022	385	15	.	.	PUNCT
fis-5022	386	1	deep	deep	ADJ
fis-5022	386	2	learning	learning	NOUN
fis-5022	386	3	based	base	VERB
fis-5022	386	4	reconstruction	reconstruction	NOUN
fis-5022	386	5	of	of	ADP
fis-5022	386	6	the	the	DET
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fis-5022	386	8	of	of	ADP
fis-5022	386	9	heterogeneous	heterogeneous	ADJ
fis-5022	386	10	composites	composite	NOUN
fis-5022	386	11	from	from	ADP
fis-5022	386	12	their	their	PRON
fis-5022	386	13	temperature	temperature	NOUN
fis-5022	386	14	fields	field	NOUN
fis-5022	386	15	.	.	PUNCT
fis-5022	387	1	(	(	PUNCT
fis-5022	387	2	april	april	PROPN
fis-5022	387	3	2020	2020	NUM
fis-5022	387	4	)	)	PUNCT
fis-5022	387	5	.	.	PUNCT
fis-5022	388	1	aip	aip	PROPN
fis-5022	388	2	advances	advance	NOUN
fis-5022	388	3	,	,	PUNCT
fis-5022	388	4	10(4	10(4	NUM
fis-5022	388	5	)	)	PUNCT
fis-5022	388	6	,	,	PUNCT
fis-5022	388	7	p.	p.	NOUN
fis-5022	388	8	045037	045037	NUM
fis-5022	388	9	.	.	PUNCT
fis-5022	389	1	doi	doi	NOUN
fis-5022	389	2	:	:	PUNCT
fis-5022	389	3	10.1063/5.0004631	10.1063/5.0004631	NUM
fis-5022	389	4	[	[	X
fis-5022	389	5	17	17	NUM
fis-5022	389	6	]	]	X
fis-5022	389	7	qiang	qiang	PROPN
fis-5022	389	8	fang	fang	PROPN
fis-5022	389	9	,	,	PUNCT
fis-5022	389	10	ibarra	ibarra	NOUN
fis-5022	389	11	-	-	PUNCT
fis-5022	389	12	castanedo	castanedo	PROPN
fis-5022	389	13	,	,	PUNCT
fis-5022	389	14	c.	c.	PROPN
fis-5022	389	15	,	,	PUNCT
fis-5022	389	16	garrido	garrido	PROPN
fis-5022	389	17	,	,	PUNCT
fis-5022	389	18	i.	i.	PROPN
fis-5022	389	19	,	,	PUNCT
fis-5022	389	20	yuxia	yuxia	PROPN
fis-5022	389	21	duan	duan	PROPN
fis-5022	389	22	and	and	CCONJ
fis-5022	389	23	maldague	maldague	PROPN
fis-5022	389	24	,	,	PUNCT
fis-5022	389	25	x.	x.	NOUN
fis-5022	389	26	automatic	automatic	ADJ
fis-5022	389	27	detection	detection	NOUN
fis-5022	389	28	and	and	CCONJ
fis-5022	389	29	identification	identification	NOUN
fis-5022	389	30	of	of	ADP
fis-5022	389	31	defect	defect	NOUN
fis-5022	389	32	by	by	ADP
fis-5022	389	33	deep	deep	ADJ
fis-5022	389	34	learning	learning	NOUN
fis-5022	389	35	algorithms	algorithm	NOUN
fis-5022	389	36	from	from	ADP
fis-5022	389	37	pulsed	pulse	VERB
fis-5022	389	38	thermography	thermography	NOUN
fis-5022	389	39	data	datum	NOUN
fis-5022	389	40	.	.	PUNCT
fis-5022	390	1	(	(	PUNCT
fis-5022	390	2	2023	2023	NUM
fis-5022	390	3	)	)	PUNCT
fis-5022	390	4	.	.	PUNCT
fis-5022	391	1	sensors	sensor	NOUN
fis-5022	391	2	,	,	PUNCT
fis-5022	391	3	23(9	23(9	NUM
fis-5022	391	4	)	)	PUNCT
fis-5022	391	5	,	,	PUNCT
fis-5022	391	6	p.	p.	NOUN
fis-5022	391	7	4444	4444	NUM
fis-5022	391	8	.	.	PUNCT
fis-5022	392	1	a.	a.	NOUN
fis-5022	392	2	chulkov	chulkov	PROPN
fis-5022	392	3	et	et	PROPN
fis-5022	392	4	alii	alii	PROPN
fis-5022	392	5	,	,	PUNCT
fis-5022	392	6	frattura	frattura	PROPN
fis-5022	392	7	ed	ed	PROPN
fis-5022	392	8	integrità	integrità	PROPN
fis-5022	392	9	strutturale	strutturale	PROPN
fis-5022	392	10	,	,	PUNCT
fis-5022	392	11	70	70	NUM
fis-5022	392	12	(	(	PUNCT
fis-5022	392	13	2024	2024	NUM
fis-5022	392	14	)	)	PUNCT
fis-5022	392	15	177	177	NUM
fis-5022	392	16	-	-	SYM
fis-5022	392	17	191	191	NUM
fis-5022	392	18	;	;	PUNCT
fis-5022	392	19	doi	doi	NOUN
fis-5022	392	20	:	:	PUNCT
fis-5022	392	21	10.3221	10.3221	NUM
fis-5022	392	22	/	/	SYM
fis-5022	392	23	igf	igf	NOUN
fis-5022	392	24	-	-	ADJ
fis-5022	392	25	esis.70.10	esis.70.10	ADJ
fis-5022	392	26	191	191	NUM
fis-5022	392	27	doi	doi	NOUN
fis-5022	392	28	:	:	PUNCT
fis-5022	392	29	10.3390	10.3390	NUM
fis-5022	392	30	/	/	SYM
fis-5022	392	31	s23094444	s23094444	ADJ
fis-5022	392	32	.	.	PUNCT
fis-5022	393	1	[	[	X
fis-5022	393	2	18	18	NUM
fis-5022	393	3	]	]	X
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fis-5022	393	5	,	,	PUNCT
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fis-5022	393	7	,	,	PUNCT
fis-5022	393	8	mamoudan	mamoudan	PROPN
fis-5022	393	9	,	,	PUNCT
fis-5022	393	10	f.	f.	PROPN
fis-5022	393	11	,	,	PUNCT
fis-5022	393	12	ibarra	ibarra	PROPN
fis-5022	393	13	castanedo	castanedo	PROPN
fis-5022	393	14	,	,	PUNCT
fis-5022	393	15	c.	c.	PROPN
fis-5022	393	16	and	and	CCONJ
fis-5022	393	17	maldague	maldague	PROPN
fis-5022	393	18	,	,	PUNCT
fis-5022	393	19	x.	x.	NOUN
fis-5022	393	20	(	(	PUNCT
fis-5022	393	21	2020	2020	NUM
fis-5022	393	22	)	)	PUNCT
fis-5022	393	23	.	.	PUNCT
fis-5022	393	24	defect	defect	ADJ
fis-5022	393	25	depth	depth	NOUN
fis-5022	393	26	estimation	estimation	NOUN
fis-5022	393	27	in	in	ADP
fis-5022	393	28	infrared	infrared	ADJ
fis-5022	393	29	thermography	thermography	NOUN
fis-5022	393	30	with	with	ADP
fis-5022	393	31	deep	deep	ADJ
fis-5022	393	32	learning	learning	NOUN
fis-5022	393	33	.	.	PUNCT
fis-5022	394	1	virtual	virtual	ADJ
fis-5022	394	2	:	:	PUNCT
fis-5022	394	3	3rd	3rd	ADJ
fis-5022	394	4	international	international	ADJ
fis-5022	394	5	symposium	symposium	NOUN
fis-5022	394	6	on	on	ADP
fis-5022	394	7	structural	structural	ADJ
fis-5022	394	8	health	health	NOUN
fis-5022	394	9	monitoring	monitoring	NOUN
fis-5022	394	10	and	and	CCONJ
fis-5022	394	11	nondestructive	nondestructive	ADJ
fis-5022	394	12	testing	testing	NOUN
fis-5022	394	13	25	25	NUM
fis-5022	394	14	-	-	SYM
fis-5022	394	15	26	26	NUM
fis-5022	394	16	nov	nov	PROPN
fis-5022	394	17	2020	2020	NUM
fis-5022	394	18	,	,	PUNCT
fis-5022	394	19	quebec	quebec	PROPN
fis-5022	394	20	,	,	PUNCT
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fis-5022	394	22	.	.	PUNCT
fis-5022	395	1	e	e	X
fis-5022	395	2	-	-	NOUN
fis-5022	395	3	journal	journal	NOUN
fis-5022	395	4	of	of	ADP
fis-5022	395	5	nondestructive	nondestructive	ADJ
fis-5022	395	6	testing	testing	NOUN
fis-5022	395	7	,	,	PUNCT
fis-5022	395	8	25(12	25(12	NUM
fis-5022	395	9	)	)	PUNCT
fis-5022	395	10	.	.	PUNCT
fis-5022	396	1	https://www.ndt.net/?id=25550	https://www.ndt.net/?id=25550	PROPN
fis-5022	396	2	.	.	PUNCT
fis-5022	397	1	[	[	X
fis-5022	397	2	19	19	NUM
fis-5022	397	3	]	]	X
fis-5022	397	4	alhammad	alhammad	ADJ
fis-5022	397	5	,	,	PUNCT
fis-5022	397	6	m.	m.	NOUN
fis-5022	397	7	,	,	PUNCT
fis-5022	397	8	avdelidis	avdelidi	NOUN
fis-5022	397	9	,	,	PUNCT
fis-5022	397	10	n.p	n.p	PROPN
fis-5022	397	11	.	.	PROPN
fis-5022	397	12	,	,	PUNCT
fis-5022	397	13	ibarra	ibarra	PROPN
fis-5022	397	14	-	-	PUNCT
fis-5022	397	15	castanedo	castanedo	PROPN
fis-5022	397	16	,	,	PUNCT
fis-5022	397	17	c.	c.	PROPN
fis-5022	397	18	,	,	PUNCT
fis-5022	397	19	torbali	torbali	PROPN
fis-5022	397	20	,	,	PUNCT
fis-5022	397	21	m.e	m.e	PROPN
fis-5022	397	22	.	.	PROPN
fis-5022	397	23	,	,	PUNCT
fis-5022	397	24	genest	genest	PROPN
fis-5022	397	25	,	,	PUNCT
fis-5022	397	26	m.	m.	PROPN
fis-5022	397	27	,	,	PUNCT
fis-5022	397	28	zhang	zhang	PROPN
fis-5022	397	29	,	,	PUNCT
fis-5022	397	30	h.	h.	PROPN
fis-5022	397	31	,	,	PUNCT
fis-5022	397	32	zolotas	zolotas	PROPN
fis-5022	397	33	,	,	PUNCT
fis-5022	397	34	a.	a.	NOUN
fis-5022	397	35	and	and	CCONJ
fis-5022	397	36	maldague	maldague	NOUN
fis-5022	397	37	,	,	PUNCT
fis-5022	397	38	x.p.v	x.p.v	PROPN
fis-5022	397	39	.	.	PUNCT
fis-5022	397	40	(	(	PUNCT
fis-5022	397	41	2022	2022	NUM
fis-5022	397	42	)	)	PUNCT
fis-5022	397	43	.	.	PUNCT
fis-5022	398	1	automated	automate	VERB
fis-5022	398	2	impact	impact	NOUN
fis-5022	398	3	damage	damage	NOUN
fis-5022	398	4	detection	detection	NOUN
fis-5022	398	5	technique	technique	NOUN
fis-5022	398	6	for	for	ADP
fis-5022	398	7	composites	composite	NOUN
fis-5022	398	8	based	base	VERB
fis-5022	398	9	on	on	ADP
fis-5022	398	10	thermographic	thermographic	ADJ
fis-5022	398	11	image	image	NOUN
fis-5022	398	12	processing	processing	NOUN
fis-5022	398	13	and	and	CCONJ
fis-5022	398	14	machine	machine	NOUN
fis-5022	398	15	learning	learn	VERB
fis-5022	398	16	classification	classification	NOUN
fis-5022	398	17	,	,	PUNCT
fis-5022	398	18	sensors	sensor	NOUN
fis-5022	398	19	,	,	PUNCT
fis-5022	398	20	22	22	NUM
fis-5022	398	21	,	,	PUNCT
fis-5022	398	22	p.	p.	NOUN
fis-5022	398	23	9031	9031	NUM
fis-5022	398	24	.	.	PUNCT
fis-5022	399	1	doi	doi	NOUN
fis-5022	399	2	:	:	PUNCT
fis-5022	399	3	10.3390	10.3390	NUM
fis-5022	399	4	/	/	SYM
fis-5022	399	5	s22239031	s22239031	NOUN
fis-5022	399	6	.	.	PUNCT
fis-5022	400	1	[	[	X
fis-5022	400	2	20	20	NUM
fis-5022	400	3	]	]	PUNCT
fis-5022	400	4	chulkov	chulkov	NOUN
fis-5022	400	5	,	,	PUNCT
fis-5022	400	6	a.o	a.o	PROPN
fis-5022	400	7	.	.	PROPN
fis-5022	400	8	,	,	PUNCT
fis-5022	400	9	nesteruk	nesteruk	ADV
fis-5022	400	10	,	,	PUNCT
fis-5022	400	11	d.a	d.a	PROPN
fis-5022	400	12	.	.	PROPN
fis-5022	400	13	,	,	PUNCT
fis-5022	400	14	vavilov	vavilov	PROPN
fis-5022	400	15	,	,	PUNCT
fis-5022	400	16	v.p	v.p	PROPN
fis-5022	400	17	.	.	PROPN
fis-5022	400	18	,	,	PUNCT
fis-5022	400	19	moskovchenko	moskovchenko	ADJ
fis-5022	400	20	,	,	PUNCT
fis-5022	400	21	a.i	a.i	PROPN
fis-5022	400	22	.	.	PROPN
fis-5022	400	23	,	,	PUNCT
fis-5022	400	24	saeed	saeed	PROPN
fis-5022	400	25	,	,	PUNCT
fis-5022	400	26	n.	n.	PROPN
fis-5022	400	27	and	and	CCONJ
fis-5022	400	28	omar	omar	PROPN
fis-5022	400	29	m.	m.	NOUN
fis-5022	400	30	(	(	PUNCT
fis-5022	400	31	2019	2019	NUM
fis-5022	400	32	)	)	PUNCT
fis-5022	400	33	.	.	PUNCT
fis-5022	401	1	optimizing	optimize	VERB
fis-5022	401	2	input	input	NOUN
fis-5022	401	3	data	datum	NOUN
fis-5022	401	4	for	for	ADP
fis-5022	401	5	training	train	VERB
fis-5022	401	6	an	an	DET
fis-5022	401	7	artificial	artificial	ADJ
fis-5022	401	8	neural	neural	ADJ
fis-5022	401	9	network	network	NOUN
fis-5022	401	10	used	use	VERB
fis-5022	401	11	for	for	ADP
fis-5022	401	12	evaluating	evaluate	VERB
fis-5022	401	13	defect	defect	ADJ
fis-5022	401	14	depth	depth	NOUN
fis-5022	401	15	in	in	ADP
fis-5022	401	16	infrared	infrared	ADJ
fis-5022	401	17	thermographic	thermographic	ADJ
fis-5022	401	18	nondestructive	nondestructive	ADJ
fis-5022	401	19	testing	testing	NOUN
fis-5022	401	20	,	,	PUNCT
fis-5022	401	21	infr	infr	PROPN
fis-5022	401	22	.	.	PUNCT
fis-5022	402	1	phys	phy	NOUN
fis-5022	402	2	.	.	PUNCT
fis-5022	403	1	technol	technol	PROPN
fis-5022	403	2	.	.	PROPN
fis-5022	403	3	,	,	PUNCT
fis-5022	403	4	102(3	102(3	NUM
fis-5022	403	5	)	)	PUNCT
fis-5022	403	6	,	,	PUNCT
fis-5022	403	7	p.	p.	NOUN
fis-5022	403	8	103047	103047	NUM
fis-5022	403	9	.	.	PUNCT
fis-5022	404	1	doi	doi	NOUN
fis-5022	404	2	:	:	PUNCT
fis-5022	404	3	10.1016	10.1016	NUM
fis-5022	404	4	/	/	SYM
fis-5022	404	5	j.infrared.2019.103047	j.infrared.2019.103047	NOUN
fis-5022	404	6	.	.	PUNCT
fis-5022	405	1	[	[	X
fis-5022	405	2	21	21	NUM
fis-5022	405	3	]	]	X
fis-5022	405	4	marinetti	marinetti	PROPN
fis-5022	405	5	,	,	PUNCT
fis-5022	405	6	s.	s.	PROPN
fis-5022	405	7	,	,	PUNCT
fis-5022	405	8	plotnikov	plotnikov	PROPN
fis-5022	405	9	,	,	PUNCT
fis-5022	405	10	y.a	y.a	PROPN
fis-5022	405	11	.	.	PROPN
fis-5022	405	12	,	,	PUNCT
fis-5022	405	13	winfree	winfree	PROPN
fis-5022	405	14	,	,	PUNCT
fis-5022	405	15	w.p	w.p	PROPN
fis-5022	405	16	.	.	PROPN
fis-5022	405	17	and	and	CCONJ
fis-5022	405	18	braggiotti	braggiotti	PROPN
fis-5022	405	19	,	,	PUNCT
fis-5022	405	20	a.	a.	NOUN
fis-5022	405	21	(	(	PUNCT
fis-5022	405	22	1999	1999	NUM
fis-5022	405	23	)	)	PUNCT
fis-5022	405	24	.	.	PUNCT
fis-5022	406	1	pulse	pulse	NOUN
fis-5022	406	2	phase	phase	NOUN
fis-5022	406	3	thermography	thermography	NOUN
fis-5022	406	4	for	for	ADP
fis-5022	406	5	defect	defect	NOUN
fis-5022	406	6	detection	detection	NOUN
fis-5022	406	7	and	and	CCONJ
fis-5022	406	8	visualization	visualization	NOUN
fis-5022	406	9	.	.	PUNCT
fis-5022	407	1	in	in	ADP
fis-5022	407	2	:	:	PUNCT
fis-5022	407	3	proc	proc	NOUN
fis-5022	407	4	.	.	PUNCT
fis-5022	408	1	spie	spie	ADJ
fis-5022	408	2	nondestructive	nondestructive	ADJ
fis-5022	408	3	evaluation	evaluation	NOUN
fis-5022	408	4	of	of	ADP
fis-5022	408	5	aging	age	VERB
fis-5022	408	6	aircraft	aircraft	NOUN
fis-5022	408	7	,	,	PUNCT
fis-5022	408	8	airports	airport	NOUN
fis-5022	408	9	,	,	PUNCT
fis-5022	408	10	and	and	CCONJ
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fis-5022	408	12	hardware	hardware	NOUN
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fis-5022	408	14	,	,	PUNCT
fis-5022	408	15	3586	3586	NUM
fis-5022	408	16	,	,	PUNCT
fis-5022	408	17	pp	pp	ADV
fis-5022	408	18	.	.	PUNCT
fis-5022	409	1	230–238	230–238	NUM
fis-5022	409	2	.	.	PUNCT
fis-5022	409	3	doi	doi	NOUN
fis-5022	409	4	:	:	PUNCT
fis-5022	409	5	10.1117/12.339890	10.1117/12.339890	NUM
fis-5022	409	6	.	.	PUNCT
fis-5022	410	1	[	[	X
fis-5022	410	2	22	22	NUM
fis-5022	410	3	]	]	PUNCT
fis-5022	410	4	carslaw	carslaw	NOUN
fis-5022	410	5	,	,	PUNCT
fis-5022	410	6	h.s	h.s	PROPN
fis-5022	410	7	.	.	PROPN
fis-5022	410	8	and	and	CCONJ
fis-5022	410	9	jaeger	jaeger	PROPN
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fis-5022	410	11	j.c	j.c	PROPN
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fis-5022	410	13	(	(	PUNCT
fis-5022	410	14	1959	1959	NUM
fis-5022	410	15	)	)	PUNCT
fis-5022	410	16	.	.	PUNCT
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fis-5022	411	2	of	of	ADP
fis-5022	411	3	heat	heat	NOUN
fis-5022	411	4	in	in	ADP
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fis-5022	411	6	,	,	PUNCT
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fis-5022	411	8	,	,	PUNCT
fis-5022	411	9	oxford	oxford	PROPN
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fis-5022	411	11	.	.	PUNCT
fis-5022	412	1	press	press	PROPN
fis-5022	412	2	.	.	PUNCT
fis-5022	412	3	,	,	PUNCT
fis-5022	412	4	uk	uk	PROPN
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fis-5022	413	1	[	[	X
fis-5022	413	2	23	23	NUM
fis-5022	413	3	]	]	X
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fis-5022	413	5	,	,	PUNCT
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fis-5022	413	10	,	,	PUNCT
fis-5022	413	11	d.d	d.d	PROPN
fis-5022	413	12	.	.	PROPN
fis-5022	413	13	(	(	PUNCT
fis-5022	413	14	2015	2015	NUM
fis-5022	413	15	)	)	PUNCT
fis-5022	413	16	.	.	PUNCT
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fis-5022	414	2	of	of	ADP
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fis-5022	414	6	:	:	PUNCT
fis-5022	414	7	physical	physical	ADJ
fis-5022	414	8	principles	principle	NOUN
fis-5022	414	9	,	,	PUNCT
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fis-5022	414	11	and	and	CCONJ
fis-5022	414	12	data	datum	NOUN
fis-5022	414	13	processing	processing	NOUN
fis-5022	414	14	.	.	PUNCT
fis-5022	415	1	ndt	ndt	PROPN
fis-5022	415	2	&	&	CCONJ
fis-5022	415	3	e	e	PROPN
fis-5022	415	4	int	int	PROPN
fis-5022	415	5	.	.	PUNCT
fis-5022	415	6	,	,	PUNCT
fis-5022	415	7	73	73	NUM
fis-5022	415	8	,	,	PUNCT
fis-5022	415	9	pp	pp	ADJ
fis-5022	415	10	.	.	PUNCT
fis-5022	416	1	28–52	28–52	X
fis-5022	416	2	.	.	PUNCT
fis-5022	417	1	doi	doi	NOUN
fis-5022	417	2	:	:	PUNCT
fis-5022	417	3	10.1016	10.1016	NUM
fis-5022	417	4	/	/	SYM
fis-5022	417	5	j.ndteint.2015.03.003	j.ndteint.2015.03.003	PROPN
fis-5022	417	6	.	.	PUNCT
fis-5022	418	1	[	[	X
fis-5022	418	2	24	24	NUM
fis-5022	418	3	]	]	X
fis-5022	418	4	almond	almond	NOUN
fis-5022	418	5	,	,	PUNCT
fis-5022	418	6	d.p	d.p	PROPN
fis-5022	418	7	.	.	PROPN
fis-5022	419	1	and	and	CCONJ
fis-5022	419	2	patel	patel	PROPN
fis-5022	419	3	,	,	PUNCT
fis-5022	419	4	p.m.	p.m.	PROPN
fis-5022	419	5	(	(	PUNCT
fis-5022	419	6	1996	1996	NUM
fis-5022	419	7	)	)	PUNCT
fis-5022	419	8	.	.	PUNCT
fis-5022	420	1	photothermal	photothermal	ADJ
fis-5022	420	2	science	science	NOUN
fis-5022	420	3	and	and	CCONJ
fis-5022	420	4	techniques	technique	NOUN
fis-5022	420	5	.	.	PUNCT
fis-5022	421	1	chapman	chapman	PROPN
fis-5022	421	2	&	&	CCONJ
fis-5022	421	3	hall	hall	PROPN
fis-5022	421	4	series	series	PROPN
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fis-5022	421	7	and	and	CCONJ
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fis-5022	421	9	,	,	PUNCT
fis-5022	421	10	physics	physics	NOUN
fis-5022	421	11	and	and	CCONJ
fis-5022	421	12	its	its	PRON
fis-5022	421	13	applications	application	NOUN
fis-5022	421	14	,	,	PUNCT
fis-5022	421	15	10	10	NUM
fis-5022	421	16	,	,	PUNCT
fis-5022	421	17	p.	p.	NOUN
fis-5022	421	18	241	241	NUM
fis-5022	421	19	.	.	PUNCT
fis-5022	422	1	[	[	X
fis-5022	422	2	25	25	NUM
fis-5022	422	3	]	]	PUNCT
fis-5022	422	4	vavilov	vavilov	PROPN
fis-5022	422	5	,	,	PUNCT
fis-5022	422	6	v.p	v.p	PROPN
fis-5022	422	7	.	.	PROPN
fis-5022	422	8	(	(	PUNCT
fis-5022	422	9	2007	2007	NUM
fis-5022	422	10	)	)	PUNCT
fis-5022	422	11	.	.	PUNCT
fis-5022	423	1	pulsed	pulse	VERB
fis-5022	423	2	thermal	thermal	ADJ
fis-5022	423	3	ndt	ndt	PROPN
fis-5022	423	4	of	of	ADP
fis-5022	423	5	materials	material	NOUN
fis-5022	423	6	:	:	PUNCT
fis-5022	423	7	back	back	ADV
fis-5022	423	8	to	to	ADP
fis-5022	423	9	the	the	DET
fis-5022	423	10	basics	basic	NOUN
fis-5022	423	11	,	,	PUNCT
fis-5022	423	12	nondestruct	nondestruct	NOUN
fis-5022	423	13	.	.	PUNCT
fis-5022	424	1	test	test	NOUN
fis-5022	424	2	.	.	PUNCT
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fis-5022	425	2	.	.	PUNCT
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fis-5022	425	7	.	.	PUNCT
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fis-5022	426	2	.	.	PUNCT
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fis-5022	432	7	.	.	PUNCT
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fis-5022	435	5	,	,	PUNCT
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fis-5022	435	12	,	,	PUNCT
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fis-5022	435	15	.	.	PUNCT
fis-5022	436	1	doi	doi	NOUN
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fis-5022	436	4	.	.	PUNCT
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fis-5022	437	3	]	]	X
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fis-5022	444	8	.	.	PUNCT
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fis-5022	445	30	.	.	PUNCT
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fis-5022	448	2	.	.	PUNCT
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fis-5022	450	25	.	.	PUNCT
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fis-5022	452	7	)	)	PUNCT
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fis-5022	452	11	.	.	PUNCT
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fis-5022	454	47	image	image	NOUN
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fis-5022	455	3	)	)	PUNCT
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fis-5022	461	2	thermogr	thermogr	PROPN
fis-5022	461	3	.	.	PUNCT
fis-5022	462	1	j.	j.	PROPN
fis-5022	462	2	,	,	PUNCT
fis-5022	462	3	21(1	21(1	NUM
fis-5022	462	4	)	)	PUNCT
fis-5022	462	5	,	,	PUNCT
fis-5022	462	6	p.	p.	NOUN
fis-5022	462	7	3	3	NUM
fis-5022	462	8	-	-	SYM
fis-5022	462	9	29	29	NUM
fis-5022	462	10	.	.	PUNCT
fis-5022	463	1	doi	doi	NOUN
fis-5022	463	2	:	:	PUNCT
fis-5022	463	3	10.1080/17686733.2022.2126638	10.1080/17686733.2022.2126638	NUM
fis-5022	463	4	.	.	PUNCT
fis-5022	464	1	[	[	X
fis-5022	464	2	34	34	NUM
fis-5022	464	3	]	]	PUNCT
fis-5022	464	4	pisner	pisner	NOUN
fis-5022	464	5	,	,	PUNCT
fis-5022	464	6	d.a	d.a	PROPN
fis-5022	464	7	.	.	PROPN
fis-5022	464	8	and	and	CCONJ
fis-5022	464	9	schnyer	schnyer	NOUN
fis-5022	464	10	,	,	PUNCT
fis-5022	464	11	d.m	d.m	PROPN
fis-5022	464	12	.	.	PUNCT
fis-5022	464	13	support	support	NOUN
fis-5022	464	14	vector	vector	NOUN
fis-5022	464	15	machine	machine	NOUN
fis-5022	464	16	.	.	PUNCT
fis-5022	465	1	mach	mach	PROPN
fis-5022	465	2	.	.	PUNCT
fis-5022	466	1	learn	learn	VERB
fis-5022	466	2	.	.	PROPN
fis-5022	466	3	,	,	PUNCT
fis-5022	466	4	elsevier	elsevier	NOUN
fis-5022	466	5	;	;	PUNCT
fis-5022	466	6	2020	2020	NUM
fis-5022	466	7	,	,	PUNCT
fis-5022	466	8	pp	pp	ADV
fis-5022	466	9	.	.	PUNCT
fis-5022	467	1	101–121	101–121	NUM
fis-5022	467	2	.	.	PUNCT
fis-5022	468	1	doi	doi	NOUN
fis-5022	468	2	:	:	PUNCT
fis-5022	468	3	10.1016	10.1016	NUM
fis-5022	468	4	/	/	SYM
fis-5022	468	5	b978	b978	NUM
fis-5022	468	6	-	-	PUNCT
fis-5022	468	7	0	0	NUM
fis-5022	468	8	-	-	PUNCT
fis-5022	468	9	12	12	NUM
fis-5022	468	10	-	-	PUNCT
fis-5022	468	11	815739	815739	NUM
fis-5022	468	12	-	-	PUNCT
fis-5022	468	13	8.00006	8.00006	NUM
fis-5022	468	14	-	-	SYM
fis-5022	468	15	7	7	NUM
fis-5022	468	16	.	.	PUNCT
fis-5022	469	1	<	<	X
fis-5022	469	2	<	<	X
fis-5022	469	3	/ascii85encodepages	/ascii85encodepage	NOUN
fis-5022	469	4	false	false	ADJ
fis-5022	469	5	/allowtransparency	/allowtransparency	NOUN
fis-5022	469	6	false	false	ADJ
fis-5022	469	7	/autopositionepsfiles	/autopositionepsfile	NOUN
fis-5022	469	8	true	true	ADJ
fis-5022	469	9	/autorotatepages	/autorotatepage	NOUN
fis-5022	469	10	/none	/none	PUNCT
fis-5022	469	11	/binding	/binding	PUNCT
fis-5022	469	12	/left	/left	ADJ
fis-5022	470	1	/calgrayprofile	/calgrayprofile	VERB
fis-5022	470	2	(	(	PUNCT
fis-5022	470	3	dot	dot	NOUN
fis-5022	470	4	gain	gain	NOUN
fis-5022	470	5	20	20	NUM
fis-5022	470	6	%	%	NOUN
fis-5022	470	7	)	)	PUNCT
fis-5022	470	8	/calrgbprofile	/calrgbprofile	PUNCT
fis-5022	471	1	(	(	PUNCT
fis-5022	471	2	srgb	srgb	PROPN
fis-5022	471	3	iec61966	iec61966	NOUN
fis-5022	471	4	-	-	PUNCT
fis-5022	471	5	2.1	2.1	NUM
fis-5022	471	6	)	)	PUNCT
fis-5022	471	7	/calcmykprofile	/calcmykprofile	PUNCT
fis-5022	472	1	(	(	PUNCT
fis-5022	472	2	u.s	u.s	PROPN
fis-5022	472	3	.	.	PROPN
fis-5022	472	4	web	web	NOUN
fis-5022	472	5	coated	coat	VERB
fis-5022	472	6	\050swop\051	\050swop\051	ADJ
fis-5022	472	7	v2	v2	NOUN
fis-5022	472	8	)	)	PUNCT
fis-5022	472	9	/srgbprofile	/srgbprofile	PUNCT
fis-5022	472	10	(	(	PUNCT
fis-5022	472	11	srgb	srgb	PROPN
fis-5022	472	12	iec61966	iec61966	NOUN
fis-5022	472	13	-	-	PUNCT
fis-5022	472	14	2.1	2.1	NUM
fis-5022	472	15	)	)	PUNCT
fis-5022	472	16	/cannotembedfontpolicy	/cannotembedfontpolicy	PUNCT
fis-5022	473	1	/error	/error	INTJ
fis-5022	473	2	/compatibilitylevel	/compatibilitylevel	NOUN
fis-5022	474	1	1.4	1.4	NUM
fis-5022	474	2	/compressobjects	/compressobject	NOUN
fis-5022	474	3	/tags	/tag	VERB
fis-5022	474	4	/compresspages	/compresspage	NOUN
fis-5022	474	5	true	true	ADJ
fis-5022	474	6	/convertimagestoindexed	/convertimagestoindexed	ADJ
fis-5022	474	7	true	true	ADJ
fis-5022	474	8	/passthroughjpegimages	/passthroughjpegimage	NOUN
fis-5022	474	9	true	true	ADJ
fis-5022	474	10	/createjobticket	/createjobticket	NOUN
fis-5022	474	11	false	false	ADJ
fis-5022	474	12	/defaultrenderingintent	/defaultrenderingintent	NOUN
fis-5022	474	13	/default	/default	PUNCT
fis-5022	474	14	/detectblends	/detectblend	NOUN
fis-5022	474	15	true	true	ADJ
fis-5022	474	16	/detectcurves	/detectcurve	VERB
fis-5022	475	1	0.0000	0.0000	NUM
fis-5022	475	2	/colorconversionstrategy	/colorconversionstrategy	NOUN
fis-5022	475	3	/cmyk	/cmyk	PUNCT
fis-5022	476	1	/dothumbnails	/dothumbnail	VERB
fis-5022	477	1	false	false	ADJ
fis-5022	477	2	/embedallfonts	/embedallfont	NOUN
fis-5022	477	3	true	true	ADJ
fis-5022	477	4	/embedopentype	/embedopentype	PUNCT
fis-5022	477	5	false	false	ADJ
fis-5022	477	6	/parseiccprofilesincomments	/parseiccprofilesincomment	NOUN
fis-5022	477	7	true	true	ADJ
fis-5022	477	8	/embedjoboptions	/embedjoboption	NOUN
fis-5022	477	9	true	true	ADJ
fis-5022	477	10	/dscreportinglevel	/dscreportinglevel	NOUN
fis-5022	477	11	0	0	NUM
fis-5022	477	12	/emitdscwarnings	/emitdscwarning	NOUN
fis-5022	477	13	false	false	ADJ
fis-5022	477	14	/endpage	/endpage	NOUN
fis-5022	477	15	-1	-1	NOUN
fis-5022	477	16	/imagememory	/imagememory	NUM
fis-5022	477	17	1048576	1048576	NUM
fis-5022	477	18	/lockdistillerparams	/lockdistillerparams	NOUN
fis-5022	477	19	false	false	ADJ
fis-5022	477	20	/maxsubsetpct	/maxsubsetpct	ADJ
fis-5022	477	21	100	100	NUM
fis-5022	477	22	/optimize	/optimize	NOUN
fis-5022	477	23	true	true	ADJ
fis-5022	477	24	/opm	/opm	NOUN
fis-5022	477	25	1	1	NUM
fis-5022	477	26	/parsedsccomments	/parsedsccomment	NOUN
fis-5022	477	27	true	true	ADJ
fis-5022	477	28	/parsedsccommentsfordocinfo	/parsedsccommentsfordocinfo	VERB
fis-5022	477	29	true	true	ADJ
fis-5022	477	30	/preservecopypage	/preservecopypage	NOUN
fis-5022	477	31	true	true	ADJ
fis-5022	477	32	/preservedicmykvalues	/preservedicmykvalue	NOUN
fis-5022	477	33	true	true	ADJ
fis-5022	477	34	/preserveepsinfo	/preserveepsinfo	NOUN
fis-5022	477	35	true	true	ADJ
fis-5022	477	36	/preserveflatness	/preserveflatness	NOUN
fis-5022	477	37	true	true	ADJ
fis-5022	477	38	/preservehalftoneinfo	/preservehalftoneinfo	PUNCT
fis-5022	477	39	false	false	ADJ
fis-5022	477	40	/preserveopicomments	/preserveopicomment	NOUN
fis-5022	477	41	true	true	ADJ
fis-5022	477	42	/preserveoverprintsettings	/preserveoverprintsetting	NOUN
fis-5022	477	43	true	true	ADJ
fis-5022	477	44	/startpage	/startpage	NOUN
fis-5022	477	45	1	1	NUM
fis-5022	477	46	/subsetfonts	/subsetfont	NOUN
fis-5022	477	47	true	true	ADJ
fis-5022	477	48	/transferfunctioninfo	/transferfunctioninfo	PUNCT
fis-5022	477	49	/apply	/apply	PUNCT
fis-5022	477	50	/ucrandbginfo	/ucrandbginfo	PUNCT
fis-5022	478	1	/preserve	/preserve	NOUN
fis-5022	478	2	/useprologue	/useprologue	NOUN
fis-5022	478	3	false	false	ADJ
fis-5022	478	4	/colorsettingsfile	/colorsettingsfile	NOUN
fis-5022	478	5	(	(	PUNCT
fis-5022	478	6	)	)	PUNCT
fis-5022	478	7	/alwaysembed	/alwaysembe	VERB
fis-5022	478	8	[	[	PUNCT
fis-5022	478	9	true	true	ADJ
fis-5022	478	10	]	]	PUNCT
fis-5022	478	11	/neverembed	/neverembed	PUNCT
fis-5022	479	1	[	[	PUNCT
fis-5022	479	2	true	true	ADJ
fis-5022	479	3	]	]	PUNCT
fis-5022	479	4	/antialiascolorimages	/antialiascolorimages	X
fis-5022	479	5	false	false	ADJ
fis-5022	479	6	/cropcolorimages	/cropcolorimages	PUNCT
fis-5022	479	7	true	true	ADJ
fis-5022	479	8	/colorimageminresolution	/colorimageminresolution	PUNCT
fis-5022	479	9	300	300	NUM
fis-5022	479	10	/colorimageminresolutionpolicy	/colorimageminresolutionpolicy	NOUN
fis-5022	479	11	/ok	/ok	ADJ
fis-5022	480	1	/downsamplecolorimages	/downsamplecolorimage	VERB
fis-5022	481	1	true	true	ADJ
fis-5022	481	2	/colorimagedownsampletype	/colorimagedownsampletype	PUNCT
fis-5022	481	3	/bicubic	/bicubic	NOUN
fis-5022	481	4	/colorimageresolution	/colorimageresolution	NOUN
fis-5022	482	1	300	300	NUM
fis-5022	482	2	/colorimagedepth	/colorimagedepth	PRON
fis-5022	482	3	-1	-1	INTJ
fis-5022	482	4	/colorimagemindownsampledepth	/colorimagemindownsampledepth	SYM
fis-5022	482	5	1	1	NUM
fis-5022	482	6	/colorimagedownsamplethreshold	/colorimagedownsamplethreshold	SYM
fis-5022	482	7	1.50000	1.50000	NUM
fis-5022	482	8	/encodecolorimages	/encodecolorimage	NOUN
fis-5022	482	9	true	true	ADJ
fis-5022	482	10	/colorimagefilter	/colorimagefilter	PUNCT
fis-5022	482	11	/dctencode	/dctencode	PUNCT
fis-5022	483	1	/autofiltercolorimages	/autofiltercolorimage	NOUN
fis-5022	483	2	true	true	ADJ
fis-5022	483	3	/colorimageautofilterstrategy	/colorimageautofilterstrategy	PUNCT
fis-5022	483	4	/jpeg	/jpeg	PUNCT
fis-5022	483	5	/coloracsimagedict	/coloracsimagedict	PUNCT
fis-5022	484	1	<	<	X
fis-5022	484	2	<	<	X
fis-5022	484	3	/qfactor	/qfactor	NOUN
fis-5022	484	4	0.15	0.15	NUM
fis-5022	484	5	/hsamples	/hsample	NOUN
fis-5022	485	1	[	[	X
fis-5022	485	2	1	1	NUM
fis-5022	485	3	1	1	NUM
fis-5022	485	4	1	1	NUM
fis-5022	485	5	1	1	NUM
fis-5022	485	6	]	]	PUNCT
fis-5022	485	7	/vsamples	/vsample	NOUN
fis-5022	486	1	[	[	X
fis-5022	486	2	1	1	NUM
fis-5022	486	3	1	1	NUM
fis-5022	486	4	1	1	NUM
fis-5022	486	5	1	1	NUM
fis-5022	486	6	]	]	PUNCT
fis-5022	486	7	>	>	PUNCT
fis-5022	486	8	>	>	X
fis-5022	486	9	/colorimagedict	/colorimagedict	PUNCT
fis-5022	487	1	<	<	X
fis-5022	487	2	<	<	X
fis-5022	487	3	/qfactor	/qfactor	NOUN
fis-5022	487	4	0.15	0.15	NUM
fis-5022	487	5	/hsamples	/hsample	NOUN
fis-5022	488	1	[	[	X
fis-5022	488	2	1	1	NUM
fis-5022	488	3	1	1	NUM
fis-5022	488	4	1	1	NUM
fis-5022	488	5	1	1	NUM
fis-5022	488	6	]	]	PUNCT
fis-5022	488	7	/vsamples	/vsample	NOUN
fis-5022	489	1	[	[	X
fis-5022	489	2	1	1	NUM
fis-5022	489	3	1	1	NUM
fis-5022	489	4	1	1	NUM
fis-5022	489	5	1	1	NUM
fis-5022	489	6	]	]	PUNCT
fis-5022	489	7	>	>	PUNCT
fis-5022	489	8	>	>	X
fis-5022	489	9	/jpeg2000coloracsimagedict	/jpeg2000coloracsimagedict	PUNCT
fis-5022	490	1	<	<	X
fis-5022	490	2	<	<	X
fis-5022	490	3	/tilewidth	/tilewidth	PUNCT
fis-5022	490	4	256	256	NUM
fis-5022	490	5	/tileheight	/tileheight	NUM
fis-5022	490	6	256	256	NUM
fis-5022	490	7	/quality	/quality	NOUN
fis-5022	490	8	30	30	NUM
fis-5022	490	9	>	>	PUNCT
fis-5022	490	10	>	>	X
fis-5022	490	11	/jpeg2000colorimagedict	/jpeg2000colorimagedict	PUNCT
fis-5022	490	12	<	<	X
fis-5022	490	13	<	<	X
fis-5022	490	14	/tilewidth	/tilewidth	PUNCT
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fis-5022	490	16	/tileheight	/tileheight	NUM
fis-5022	490	17	256	256	NUM
fis-5022	490	18	/quality	/quality	NOUN
fis-5022	490	19	30	30	NUM
fis-5022	490	20	>	>	PUNCT
fis-5022	490	21	>	>	X
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fis-5022	490	23	false	false	ADJ
fis-5022	490	24	/cropgrayimages	/cropgrayimage	NOUN
fis-5022	490	25	true	true	ADJ
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fis-5022	490	27	300	300	NUM
fis-5022	490	28	/grayimageminresolutionpolicy	/grayimageminresolutionpolicy	NOUN
fis-5022	490	29	/ok	/ok	ADJ
fis-5022	490	30	/downsamplegrayimages	/downsamplegrayimages	PUNCT
fis-5022	491	1	true	true	ADJ
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fis-5022	491	3	/bicubic	/bicubic	NOUN
fis-5022	491	4	/grayimageresolution	/grayimageresolution	NOUN
fis-5022	491	5	300	300	NUM
fis-5022	491	6	/grayimagedepth	/grayimagedepth	PUNCT
fis-5022	491	7	-1	-1	PUNCT
fis-5022	491	8	/grayimagemindownsampledepth	/grayimagemindownsampledepth	PUNCT
fis-5022	492	1	2	2	NUM
fis-5022	492	2	/grayimagedownsamplethreshold	/grayimagedownsamplethreshold	NUM
fis-5022	492	3	1.50000	1.50000	NUM
fis-5022	492	4	/encodegrayimages	/encodegrayimage	NOUN
fis-5022	492	5	true	true	ADJ
fis-5022	492	6	/grayimagefilter	/grayimagefilter	NOUN
fis-5022	492	7	/dctencode	/dctencode	PUNCT
fis-5022	493	1	/autofiltergrayimages	/autofiltergrayimages	VERB
fis-5022	493	2	true	true	ADJ
fis-5022	493	3	/grayimageautofilterstrategy	/grayimageautofilterstrategy	INTJ
fis-5022	493	4	/jpeg	/jpeg	PUNCT
fis-5022	493	5	/grayacsimagedict	/grayacsimagedict	PUNCT
fis-5022	494	1	<	<	X
fis-5022	494	2	<	<	X
fis-5022	494	3	/qfactor	/qfactor	NOUN
fis-5022	494	4	0.15	0.15	NUM
fis-5022	494	5	/hsamples	/hsample	NOUN
fis-5022	495	1	[	[	X
fis-5022	495	2	1	1	NUM
fis-5022	495	3	1	1	NUM
fis-5022	495	4	1	1	NUM
fis-5022	495	5	1	1	NUM
fis-5022	495	6	]	]	PUNCT
fis-5022	495	7	/vsamples	/vsample	NOUN
fis-5022	496	1	[	[	X
fis-5022	496	2	1	1	NUM
fis-5022	496	3	1	1	NUM
fis-5022	496	4	1	1	NUM
fis-5022	496	5	1	1	NUM
fis-5022	496	6	]	]	PUNCT
fis-5022	496	7	>	>	PUNCT
fis-5022	496	8	>	>	X
fis-5022	496	9	/grayimagedict	/grayimagedict	PUNCT
fis-5022	497	1	<	<	X
fis-5022	497	2	<	<	X
fis-5022	497	3	/qfactor	/qfactor	NOUN
fis-5022	497	4	0.15	0.15	NUM
fis-5022	497	5	/hsamples	/hsample	NOUN
fis-5022	498	1	[	[	X
fis-5022	498	2	1	1	NUM
fis-5022	498	3	1	1	NUM
fis-5022	498	4	1	1	NUM
fis-5022	498	5	1	1	NUM
fis-5022	498	6	]	]	PUNCT
fis-5022	498	7	/vsamples	/vsample	NOUN
fis-5022	499	1	[	[	X
fis-5022	499	2	1	1	NUM
fis-5022	499	3	1	1	NUM
fis-5022	499	4	1	1	NUM
fis-5022	499	5	1	1	NUM
fis-5022	499	6	]	]	PUNCT
fis-5022	499	7	>	>	X
fis-5022	499	8	>	>	X
fis-5022	499	9	/jpeg2000grayacsimagedict	/jpeg2000grayacsimagedict	PUNCT
fis-5022	500	1	<	<	X
fis-5022	500	2	<	<	X
fis-5022	500	3	/tilewidth	/tilewidth	PUNCT
fis-5022	500	4	256	256	NUM
fis-5022	500	5	/tileheight	/tileheight	NUM
fis-5022	500	6	256	256	NUM
fis-5022	500	7	/quality	/quality	NOUN
fis-5022	500	8	30	30	NUM
fis-5022	500	9	>	>	PUNCT
fis-5022	500	10	>	>	X
fis-5022	500	11	/jpeg2000grayimagedict	/jpeg2000grayimagedict	PUNCT
fis-5022	500	12	<	<	X
fis-5022	500	13	<	<	X
fis-5022	500	14	/tilewidth	/tilewidth	PUNCT
fis-5022	500	15	256	256	NUM
fis-5022	500	16	/tileheight	/tileheight	NUM
fis-5022	500	17	256	256	NUM
fis-5022	500	18	/quality	/quality	NOUN
fis-5022	500	19	30	30	NUM
fis-5022	500	20	>	>	PUNCT
fis-5022	500	21	>	>	X
fis-5022	500	22	/antialiasmonoimages	/antialiasmonoimage	NOUN
fis-5022	500	23	false	false	ADJ
fis-5022	500	24	/cropmonoimages	/cropmonoimage	NOUN
fis-5022	500	25	true	true	ADJ
fis-5022	500	26	/monoimageminresolution	/monoimageminresolution	NUM
fis-5022	500	27	1200	1200	NUM
fis-5022	500	28	/monoimageminresolutionpolicy	/monoimageminresolutionpolicy	PUNCT
fis-5022	501	1	/ok	/ok	PROPN
fis-5022	501	2	/downsamplemonoimages	/downsamplemonoimage	VERB
fis-5022	502	1	true	true	ADJ
fis-5022	502	2	/monoimagedownsampletype	/monoimagedownsampletype	PUNCT
fis-5022	502	3	/bicubic	/bicubic	NOUN
fis-5022	502	4	/monoimageresolution	/monoimageresolution	NOUN
fis-5022	502	5	1200	1200	NUM
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fis-5022	502	7	-1	-1	PUNCT
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fis-5022	516	3	>	>	X
fis-5022	516	4	/gre	/gre	PUNCT
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fis-5022	516	7	>	>	X
fis-5022	516	8	/heb	/heb	X
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fis-5022	516	11	>	>	X
fis-5022	516	12	/hrv	/hrv	PROPN
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fis-5022	517	2	za	za	PROPN
fis-5022	517	3	stvaranje	stvaranje	PROPN
fis-5022	517	4	adobe	adobe	PROPN
fis-5022	517	5	pdf	pdf	PROPN
fis-5022	517	6	dokumenata	dokumenata	PROPN
fis-5022	517	7	najpogodnijih	najpogodnijih	PROPN
fis-5022	517	8	za	za	PROPN
fis-5022	517	9	visokokvalitetni	visokokvalitetni	VERB
fis-5022	517	10	ispis	ispis	ADJ
fis-5022	517	11	prije	prije	NOUN
fis-5022	517	12	tiskanja	tiskanja	PROPN
fis-5022	517	13	koristite	koristite	PROPN
fis-5022	517	14	ove	ove	NOUN
fis-5022	517	15	postavke	postavke	NOUN
fis-5022	517	16	.	.	PUNCT
fis-5022	518	1	stvoreni	stvoreni	ADJ
fis-5022	518	2	pdf	pdf	NOUN
fis-5022	518	3	dokumenti	dokumenti	PROPN
fis-5022	518	4	mogu	mogu	PROPN
fis-5022	518	5	se	se	X
fis-5022	518	6	otvoriti	otvoriti	PROPN
fis-5022	518	7	acrobat	acrobat	PROPN
fis-5022	519	1	i	i	PRON
fis-5022	519	2	adobe	adobe	PROPN
fis-5022	519	3	reader	reader	PROPN
fis-5022	519	4	5.0	5.0	NUM
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fis-5022	519	6	kasnijim	kasnijim	VERB
fis-5022	519	7	verzijama	verzijama	NOUN
fis-5022	519	8	.	.	PUNCT
fis-5022	519	9	)	)	PUNCT
fis-5022	520	1	/hun	/hun	PUNCT
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fis-5022	521	3	>	>	X
fis-5022	521	4	/ita	/ita	PUNCT
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fis-5022	522	3	>	>	X
fis-5022	522	4	/jpn	/jpn	PROPN
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fis-5022	523	3	>	>	X
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fis-5022	524	3	>	>	X
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fis-5022	526	3	>	>	X
fis-5022	526	4	/nld	/nld	PUNCT
fis-5022	527	1	(	(	PUNCT
fis-5022	527	2	gebruik	gebruik	NOUN
fis-5022	527	3	deze	deze	PROPN
fis-5022	527	4	instellingen	instellingen	PROPN
fis-5022	527	5	om	om	PROPN
fis-5022	527	6	adobe	adobe	PROPN
fis-5022	527	7	pdf	pdf	PROPN
fis-5022	527	8	-	-	PUNCT
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fis-5022	533	13	<	<	X
fis-5022	533	14	feff04120438043a043e0440043804410442043e043204430439044204350020044604560020043f043004400430043c043504420440043800200434043b044f0020044104420432043e04400435043d043d044f00200434043e043a0443043c0435043d044204560432002000410064006f006200650020005000440046002c0020044f043a04560020043d04300439043a04400430044904350020043f045604340445043e0434044f0442044c00200434043b044f0020043204380441043e043a043e044f043a04560441043d043e0433043e0020043f0435044004350434043404400443043a043e0432043e0433043e0020043404400443043a0443002e00200020042104420432043e04400435043d045600200434043e043a0443043c0435043d0442043800200050004400460020043c043e0436043d04300020043204560434043a0440043804420438002004430020004100630072006f006200610074002004420430002000410064006f00620065002000520065006100640065007200200035002e0030002004300431043e0020043f04560437043d04560448043e04570020043204350440044104560457002e	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	X
fis-5022	533	15	>	>	X
fis-5022	533	16	/enu	/enu	PUNCT
fis-5022	533	17	(	(	PUNCT
fis-5022	533	18	use	use	VERB
fis-5022	533	19	these	these	DET
fis-5022	533	20	settings	setting	NOUN
fis-5022	533	21	to	to	PART
fis-5022	533	22	create	create	VERB
fis-5022	533	23	adobe	adobe	PROPN
fis-5022	533	24	pdf	pdf	PROPN
fis-5022	533	25	documents	document	NOUN
fis-5022	533	26	best	well	ADV
fis-5022	533	27	suited	suit	VERB
fis-5022	533	28	for	for	ADP
fis-5022	533	29	high	high	ADJ
fis-5022	533	30	-	-	PUNCT
fis-5022	533	31	quality	quality	NOUN
fis-5022	533	32	prepress	prepress	NOUN
fis-5022	533	33	printing	printing	NOUN
fis-5022	533	34	.	.	PUNCT
fis-5022	534	1	created	create	VERB
fis-5022	534	2	pdf	pdf	NOUN
fis-5022	534	3	documents	document	NOUN
fis-5022	534	4	can	can	AUX
fis-5022	534	5	be	be	AUX
fis-5022	534	6	opened	open	VERB
fis-5022	534	7	with	with	ADP
fis-5022	534	8	acrobat	acrobat	PROPN
fis-5022	534	9	and	and	CCONJ
fis-5022	534	10	adobe	adobe	PROPN
fis-5022	534	11	reader	reader	PROPN
fis-5022	534	12	5.0	5.0	NUM
fis-5022	534	13	and	and	CCONJ
fis-5022	534	14	later	later	ADV
fis-5022	534	15	.	.	PUNCT
fis-5022	534	16	)	)	PUNCT
fis-5022	535	1	>	>	PUNCT
fis-5022	535	2	>	>	X
fis-5022	535	3	/namespace	/namespace	PUNCT
fis-5022	536	1	[	[	PUNCT
fis-5022	536	2	(	(	PUNCT
fis-5022	536	3	adobe	adobe	PROPN
fis-5022	536	4	)	)	PUNCT
fis-5022	536	5	(	(	PUNCT
fis-5022	536	6	common	common	ADJ
fis-5022	536	7	)	)	PUNCT
fis-5022	536	8	(	(	PUNCT
fis-5022	536	9	1.0	1.0	NUM
fis-5022	536	10	)	)	PUNCT
fis-5022	536	11	]	]	PUNCT
fis-5022	537	1	/othernamespaces	/othernamespace	VERB
fis-5022	537	2	[	[	PUNCT
fis-5022	537	3	<	<	X
fis-5022	537	4	<	<	X
fis-5022	537	5	/asreaderspreads	/asreaderspreads	X
fis-5022	537	6	false	false	ADJ
fis-5022	537	7	/cropimagestoframes	/cropimagestoframe	NOUN
fis-5022	537	8	true	true	ADJ
fis-5022	537	9	/errorcontrol	/errorcontrol	NOUN
fis-5022	538	1	/warnandcontinue	/warnandcontinue	PUNCT
fis-5022	538	2	/flattenerignorespreadoverrides	/flattenerignorespreadoverride	NOUN
fis-5022	538	3	false	false	ADJ
fis-5022	538	4	/includeguidesgrids	/includeguidesgrid	NOUN
fis-5022	538	5	false	false	ADJ
fis-5022	538	6	/includenonprinting	/includenonprinting	NOUN
fis-5022	538	7	false	false	ADJ
fis-5022	538	8	/includeslug	/includeslug	INTJ
fis-5022	538	9	false	false	ADJ
fis-5022	538	10	/namespace	/namespace	NOUN
fis-5022	539	1	[	[	PUNCT
fis-5022	539	2	(	(	PUNCT
fis-5022	539	3	adobe	adobe	PROPN
fis-5022	539	4	)	)	PUNCT
fis-5022	539	5	(	(	PUNCT
fis-5022	539	6	indesign	indesign	NOUN
fis-5022	539	7	)	)	PUNCT
fis-5022	539	8	(	(	PUNCT
fis-5022	539	9	4.0	4.0	NUM
fis-5022	539	10	)	)	PUNCT
fis-5022	539	11	]	]	PUNCT
fis-5022	539	12	/omitplacedbitmaps	/omitplacedbitmaps	PUNCT
fis-5022	540	1	false	false	ADJ
fis-5022	540	2	/omitplacedeps	/omitplacedeps	INTJ
fis-5022	540	3	false	false	ADJ
fis-5022	540	4	/omitplacedpdf	/omitplacedpdf	PUNCT
fis-5022	540	5	false	false	ADJ
fis-5022	540	6	/simulateoverprint	/simulateoverprint	NOUN
fis-5022	540	7	/legacy	/legacy	PUNCT
fis-5022	541	1	>	>	PUNCT
fis-5022	541	2	>	>	X
fis-5022	542	1	<	<	X
fis-5022	542	2	<	<	X
fis-5022	542	3	/addbleedmarks	/addbleedmarks	X
fis-5022	542	4	false	false	ADJ
fis-5022	542	5	/addcolorbars	/addcolorbars	INTJ
fis-5022	542	6	false	false	ADJ
fis-5022	542	7	/addcropmarks	/addcropmarks	PUNCT
fis-5022	542	8	false	false	ADJ
fis-5022	542	9	/addpageinfo	/addpageinfo	INTJ
fis-5022	542	10	false	false	ADJ
fis-5022	542	11	/addregmarks	/addregmark	NOUN
fis-5022	542	12	false	false	ADJ
fis-5022	542	13	/convertcolors	/convertcolor	NOUN
fis-5022	542	14	/converttocmyk	/converttocmyk	INTJ
fis-5022	542	15	/destinationprofilename	/destinationprofilename	PUNCT
fis-5022	542	16	(	(	PUNCT
fis-5022	542	17	)	)	PUNCT
fis-5022	542	18	/destinationprofileselector	/destinationprofileselector	NOUN
fis-5022	542	19	/documentcmyk	/documentcmyk	PUNCT
fis-5022	542	20	/downsample16bitimages	/downsample16bitimage	NOUN
fis-5022	542	21	true	true	ADJ
fis-5022	542	22	/flattenerpreset	/flattenerpreset	PUNCT
fis-5022	543	1	<	<	X
fis-5022	543	2	<	<	X
fis-5022	543	3	/presetselector	/presetselector	X
fis-5022	543	4	/mediumresolution	/mediumresolution	NOUN
fis-5022	543	5	>	>	PUNCT
fis-5022	543	6	>	>	X
fis-5022	543	7	/formelements	/formelement	NOUN
fis-5022	544	1	false	false	ADJ
fis-5022	544	2	/generatestructure	/generatestructure	PUNCT
fis-5022	544	3	false	false	ADJ
fis-5022	544	4	/includebookmarks	/includebookmark	NOUN
fis-5022	544	5	false	false	ADJ
fis-5022	544	6	/includehyperlinks	/includehyperlinks	INTJ
fis-5022	544	7	false	false	ADJ
fis-5022	544	8	/includeinteractive	/includeinteractive	ADJ
fis-5022	544	9	false	false	ADJ
fis-5022	544	10	/includelayers	/includelayer	NOUN
fis-5022	544	11	false	false	ADJ
fis-5022	544	12	/includeprofiles	/includeprofiles	INTJ
fis-5022	544	13	false	false	ADJ
fis-5022	544	14	/multimediahandling	/multimediahandling	NOUN
fis-5022	545	1	/useobjectsettings	/useobjectsettings	PRON
fis-5022	546	1	/namespace	/namespace	PUNCT
fis-5022	547	1	[	[	PUNCT
fis-5022	547	2	(	(	PUNCT
fis-5022	547	3	adobe	adobe	PROPN
fis-5022	547	4	)	)	PUNCT
fis-5022	547	5	(	(	PUNCT
fis-5022	547	6	creativesuite	creativesuite	NOUN
fis-5022	547	7	)	)	PUNCT
fis-5022	547	8	(	(	PUNCT
fis-5022	547	9	2.0	2.0	NUM
fis-5022	547	10	)	)	PUNCT
fis-5022	547	11	]	]	PUNCT
fis-5022	548	1	/pdfxoutputintentprofileselector	/pdfxoutputintentprofileselector	INTJ
fis-5022	548	2	/documentcmyk	/documentcmyk	PUNCT
fis-5022	549	1	/preserveediting	/preserveedite	VERB
fis-5022	549	2	true	true	ADJ
fis-5022	549	3	/untaggedcmykhandling	/untaggedcmykhandling	NOUN
fis-5022	549	4	/leaveuntagged	/leaveuntagge	VERB
fis-5022	549	5	/untaggedrgbhandling	/untaggedrgbhandling	NOUN
fis-5022	549	6	/usedocumentprofile	/usedocumentprofile	INTJ
fis-5022	549	7	/usedocumentbleed	/usedocumentbleed	NOUN
fis-5022	550	1	false	false	ADJ
fis-5022	550	2	>	>	PUNCT
fis-5022	550	3	>	>	X
fis-5022	550	4	]	]	PUNCT
fis-5022	550	5	>	>	PUNCT
fis-5022	550	6	>	>	X
fis-5022	550	7	setdistillerparams	setdistillerparam	NOUN
fis-5022	551	1	<	<	X
fis-5022	551	2	<	<	X
fis-5022	551	3	/hwresolution	/hwresolution	NOUN
fis-5022	552	1	[	[	X
fis-5022	552	2	2400	2400	NUM
fis-5022	552	3	2400	2400	NUM
fis-5022	552	4	]	]	PUNCT
fis-5022	552	5	/pagesize	/pagesize	X
fis-5022	553	1	[	[	X
fis-5022	553	2	612.000	612.000	NUM
fis-5022	553	3	792.000	792.000	NUM
fis-5022	553	4	]	]	PUNCT
fis-5022	553	5	>	>	PUNCT
fis-5022	553	6	>	>	X
fis-5022	553	7	setpagedevice	setpagedevice	PROPN