id	sid	tid	token	lemma	pos
app01-11101	1	1	acta	acta	PROPN
app01-11101	1	2	polytechnica	polytechnica	PROPN
app01-11101	1	3	ctu	ctu	PROPN
app01-11101	1	4	proceedings	proceeding	NOUN
app01-11101	1	5	https://doi.org/10.14311/app.2025.54.0079	https://doi.org/10.14311/app.2025.54.0079	PROPN
app01-11101	1	6	acta	acta	PROPN
app01-11101	1	7	polytechnica	polytechnica	PROPN
app01-11101	1	8	ctu	ctu	NOUN
app01-11101	1	9	proceedings	proceeding	NOUN
app01-11101	1	10	54:79–84	54:79–84	NOUN
app01-11101	1	11	,	,	PUNCT
app01-11101	1	12	2025	2025	NUM
app01-11101	1	13	©	©	ADP
app01-11101	1	14	2025	2025	NUM
app01-11101	1	15	the	the	DET
app01-11101	1	16	author(s	author(s	NOUN
app01-11101	1	17	)	)	PUNCT
app01-11101	1	18	.	.	PUNCT
app01-11101	2	1	licensed	license	VERB
app01-11101	2	2	under	under	ADP
app01-11101	2	3	a	a	DET
app01-11101	2	4	cc	cc	NOUN
app01-11101	2	5	-	-	PUNCT
app01-11101	2	6	by	by	ADP
app01-11101	2	7	4.0	4.0	NUM
app01-11101	2	8	licence	licence	NOUN
app01-11101	2	9	published	publish	VERB
app01-11101	2	10	by	by	ADP
app01-11101	2	11	the	the	DET
app01-11101	2	12	czech	czech	PROPN
app01-11101	2	13	technical	technical	PROPN
app01-11101	2	14	university	university	PROPN
app01-11101	2	15	in	in	ADP
app01-11101	2	16	prague	prague	PROPN
app01-11101	2	17	deep	deep	ADJ
app01-11101	2	18	learning	learning	NOUN
app01-11101	2	19	-	-	PUNCT
app01-11101	2	20	based	base	VERB
app01-11101	2	21	modeling	modeling	NOUN
app01-11101	2	22	and	and	CCONJ
app01-11101	2	23	simulation	simulation	NOUN
app01-11101	2	24	of	of	ADP
app01-11101	2	25	heat	heat	NOUN
app01-11101	2	26	conduction	conduction	NOUN
app01-11101	2	27	ondřej	ondřej	NOUN
app01-11101	2	28	šperl	šperl	PROPN
app01-11101	2	29	,	,	PUNCT
app01-11101	2	30	jan	jan	PROPN
app01-11101	2	31	sýkora∗	sýkora∗	PROPN
app01-11101	2	32	czech	czech	PROPN
app01-11101	2	33	technical	technical	PROPN
app01-11101	2	34	university	university	PROPN
app01-11101	2	35	in	in	ADP
app01-11101	2	36	prague	prague	PROPN
app01-11101	2	37	,	,	PUNCT
app01-11101	2	38	faculty	faculty	NOUN
app01-11101	2	39	of	of	ADP
app01-11101	2	40	civil	civil	ADJ
app01-11101	2	41	engineering	engineering	NOUN
app01-11101	2	42	,	,	PUNCT
app01-11101	2	43	department	department	NOUN
app01-11101	2	44	of	of	ADP
app01-11101	2	45	mechanics	mechanic	NOUN
app01-11101	2	46	,	,	PUNCT
app01-11101	2	47	thákurova	thákurova	PROPN
app01-11101	2	48	2077/7	2077/7	NUM
app01-11101	2	49	,	,	PUNCT
app01-11101	2	50	160	160	NUM
app01-11101	2	51	00	00	NUM
app01-11101	2	52	prague	prague	PROPN
app01-11101	2	53	6	6	NUM
app01-11101	2	54	–	–	PUNCT
app01-11101	2	55	dejvice	dejvice	NOUN
app01-11101	2	56	,	,	PUNCT
app01-11101	2	57	czech	czech	PROPN
app01-11101	2	58	republic	republic	NOUN
app01-11101	2	59	∗	∗	NOUN
app01-11101	2	60	corresponding	correspond	VERB
app01-11101	2	61	author	author	NOUN
app01-11101	2	62	:	:	PUNCT
app01-11101	2	63	jan.sykora.1@fsv.cvut.cz	jan.sykora.1@fsv.cvut.cz	NOUN
app01-11101	2	64	abstract	abstract	ADJ
app01-11101	2	65	.	.	PUNCT
app01-11101	3	1	the	the	DET
app01-11101	3	2	present	present	ADJ
app01-11101	3	3	study	study	NOUN
app01-11101	3	4	focuses	focus	VERB
app01-11101	3	5	on	on	ADP
app01-11101	3	6	applying	apply	VERB
app01-11101	3	7	deep	deep	ADJ
app01-11101	3	8	neural	neural	ADJ
app01-11101	3	9	networks	network	NOUN
app01-11101	3	10	(	(	PUNCT
app01-11101	3	11	dnns	dnn	NOUN
app01-11101	3	12	)	)	PUNCT
app01-11101	3	13	to	to	PART
app01-11101	3	14	surrogate	surrogate	VERB
app01-11101	3	15	modeling	modeling	NOUN
app01-11101	3	16	of	of	ADP
app01-11101	3	17	heat	heat	NOUN
app01-11101	3	18	conduction	conduction	NOUN
app01-11101	3	19	problems	problem	NOUN
app01-11101	3	20	.	.	PUNCT
app01-11101	4	1	deep	deep	ADJ
app01-11101	4	2	learning	learning	NOUN
app01-11101	4	3	algorithms	algorithm	NOUN
app01-11101	4	4	,	,	PUNCT
app01-11101	4	5	valued	value	VERB
app01-11101	4	6	for	for	ADP
app01-11101	4	7	their	their	PRON
app01-11101	4	8	ability	ability	NOUN
app01-11101	4	9	to	to	PART
app01-11101	4	10	learn	learn	VERB
app01-11101	4	11	hierarchical	hierarchical	ADJ
app01-11101	4	12	data	datum	NOUN
app01-11101	4	13	representations	representation	NOUN
app01-11101	4	14	through	through	ADP
app01-11101	4	15	multi	multi	ADJ
app01-11101	4	16	-	-	ADJ
app01-11101	4	17	layered	layered	ADJ
app01-11101	4	18	networks	network	NOUN
app01-11101	4	19	,	,	PUNCT
app01-11101	4	20	excel	excel	VERB
app01-11101	4	21	at	at	ADP
app01-11101	4	22	identifying	identify	VERB
app01-11101	4	23	complex	complex	ADJ
app01-11101	4	24	patterns	pattern	NOUN
app01-11101	4	25	.	.	PUNCT
app01-11101	5	1	in	in	ADP
app01-11101	5	2	this	this	DET
app01-11101	5	3	work	work	NOUN
app01-11101	5	4	,	,	PUNCT
app01-11101	5	5	the	the	DET
app01-11101	5	6	u	u	ADJ
app01-11101	5	7	-	-	ADJ
app01-11101	5	8	net	net	ADJ
app01-11101	5	9	architecture	architecture	NOUN
app01-11101	5	10	–	–	PUNCT
app01-11101	5	11	widely	widely	ADV
app01-11101	5	12	recognized	recognize	VERB
app01-11101	5	13	for	for	ADP
app01-11101	5	14	its	its	PRON
app01-11101	5	15	effectiveness	effectiveness	NOUN
app01-11101	5	16	in	in	ADP
app01-11101	5	17	image	image	NOUN
app01-11101	5	18	segmentation	segmentation	NOUN
app01-11101	5	19	–	–	PUNCT
app01-11101	5	20	is	be	AUX
app01-11101	5	21	adapted	adapt	VERB
app01-11101	5	22	to	to	PART
app01-11101	5	23	model	model	VERB
app01-11101	5	24	stationary	stationary	ADJ
app01-11101	5	25	heat	heat	NOUN
app01-11101	5	26	transfer	transfer	NOUN
app01-11101	5	27	,	,	PUNCT
app01-11101	5	28	providing	provide	VERB
app01-11101	5	29	a	a	DET
app01-11101	5	30	novel	novel	ADJ
app01-11101	5	31	approach	approach	NOUN
app01-11101	5	32	to	to	ADP
app01-11101	5	33	a	a	DET
app01-11101	5	34	critical	critical	ADJ
app01-11101	5	35	challenge	challenge	NOUN
app01-11101	5	36	in	in	ADP
app01-11101	5	37	engineering	engineering	NOUN
app01-11101	5	38	and	and	CCONJ
app01-11101	5	39	physics	physics	NOUN
app01-11101	5	40	.	.	PUNCT
app01-11101	6	1	specifically	specifically	ADV
app01-11101	6	2	,	,	PUNCT
app01-11101	6	3	we	we	PRON
app01-11101	6	4	propose	propose	VERB
app01-11101	6	5	a	a	DET
app01-11101	6	6	deep	deep	ADJ
app01-11101	6	7	learning	learning	NOUN
app01-11101	6	8	-	-	PUNCT
app01-11101	6	9	based	base	VERB
app01-11101	6	10	surrogate	surrogate	ADJ
app01-11101	6	11	model	model	NOUN
app01-11101	6	12	to	to	PART
app01-11101	6	13	predict	predict	VERB
app01-11101	6	14	stationary	stationary	ADJ
app01-11101	6	15	temperature	temperature	NOUN
app01-11101	6	16	fields	field	NOUN
app01-11101	6	17	in	in	ADP
app01-11101	6	18	2d	2d	NUM
app01-11101	6	19	rectangular	rectangular	ADJ
app01-11101	6	20	domains	domain	NOUN
app01-11101	6	21	representing	represent	VERB
app01-11101	6	22	two	two	NUM
app01-11101	6	23	-	-	PUNCT
app01-11101	6	24	phase	phase	NOUN
app01-11101	6	25	heterogeneous	heterogeneous	ADJ
app01-11101	6	26	materials	material	NOUN
app01-11101	6	27	.	.	PUNCT
app01-11101	7	1	keywords	keyword	NOUN
app01-11101	7	2	:	:	PUNCT
app01-11101	7	3	stationary	stationary	ADJ
app01-11101	7	4	heat	heat	NOUN
app01-11101	7	5	transport	transport	NOUN
app01-11101	7	6	,	,	PUNCT
app01-11101	7	7	convolutional	convolutional	ADJ
app01-11101	7	8	neural	neural	ADJ
app01-11101	7	9	network	network	NOUN
app01-11101	7	10	,	,	PUNCT
app01-11101	7	11	u	u	NOUN
app01-11101	7	12	-	-	ADJ
app01-11101	7	13	net	net	ADJ
app01-11101	7	14	architecture	architecture	NOUN
app01-11101	7	15	.	.	PUNCT
app01-11101	8	1	1	1	X
app01-11101	8	2	.	.	X
app01-11101	8	3	introduction	introduction	NOUN
app01-11101	8	4	surrogate	surrogate	ADJ
app01-11101	8	5	modeling	modeling	NOUN
app01-11101	8	6	is	be	AUX
app01-11101	8	7	a	a	DET
app01-11101	8	8	popular	popular	ADJ
app01-11101	8	9	computational	computational	ADJ
app01-11101	8	10	strategy	strategy	NOUN
app01-11101	8	11	employed	employ	VERB
app01-11101	8	12	to	to	PART
app01-11101	8	13	approximate	approximate	ADJ
app01-11101	8	14	complex	complex	ADJ
app01-11101	8	15	,	,	PUNCT
app01-11101	8	16	high	high	ADJ
app01-11101	8	17	-	-	PUNCT
app01-11101	8	18	fidelity	fidelity	NOUN
app01-11101	8	19	models	model	NOUN
app01-11101	8	20	with	with	ADP
app01-11101	8	21	simpler	simple	ADJ
app01-11101	8	22	,	,	PUNCT
app01-11101	8	23	more	more	ADV
app01-11101	8	24	efficient	efficient	ADJ
app01-11101	8	25	representations	representation	NOUN
app01-11101	8	26	,	,	PUNCT
app01-11101	8	27	while	while	SCONJ
app01-11101	8	28	aiming	aim	VERB
app01-11101	8	29	to	to	PART
app01-11101	8	30	preserve	preserve	VERB
app01-11101	8	31	the	the	DET
app01-11101	8	32	essential	essential	ADJ
app01-11101	8	33	characteristics	characteristic	NOUN
app01-11101	8	34	of	of	ADP
app01-11101	8	35	the	the	DET
app01-11101	8	36	original	original	ADJ
app01-11101	8	37	forward	forward	ADJ
app01-11101	8	38	model	model	NOUN
app01-11101	8	39	[	[	X
app01-11101	8	40	1	1	NUM
app01-11101	8	41	]	]	PUNCT
app01-11101	8	42	.	.	PUNCT
app01-11101	9	1	this	this	DET
app01-11101	9	2	approach	approach	NOUN
app01-11101	9	3	is	be	AUX
app01-11101	9	4	particularly	particularly	ADV
app01-11101	9	5	advantageous	advantageous	ADJ
app01-11101	9	6	in	in	ADP
app01-11101	9	7	scenarios	scenario	NOUN
app01-11101	9	8	where	where	SCONJ
app01-11101	9	9	the	the	DET
app01-11101	9	10	original	original	ADJ
app01-11101	9	11	model	model	NOUN
app01-11101	9	12	is	be	AUX
app01-11101	9	13	computationally	computationally	ADV
app01-11101	9	14	intensive	intensive	ADJ
app01-11101	9	15	,	,	PUNCT
app01-11101	9	16	making	make	VERB
app01-11101	9	17	it	it	PRON
app01-11101	9	18	impractical	impractical	ADJ
app01-11101	9	19	for	for	ADP
app01-11101	9	20	tasks	task	NOUN
app01-11101	9	21	such	such	ADJ
app01-11101	9	22	as	as	ADP
app01-11101	9	23	optimization	optimization	NOUN
app01-11101	9	24	,	,	PUNCT
app01-11101	9	25	uncertainty	uncertainty	NOUN
app01-11101	9	26	quantification	quantification	NOUN
app01-11101	9	27	,	,	PUNCT
app01-11101	9	28	or	or	CCONJ
app01-11101	9	29	real	real	ADJ
app01-11101	9	30	-	-	PUNCT
app01-11101	9	31	time	time	NOUN
app01-11101	9	32	simulations	simulation	NOUN
app01-11101	9	33	.	.	PUNCT
app01-11101	10	1	the	the	DET
app01-11101	10	2	primary	primary	ADJ
app01-11101	10	3	objective	objective	NOUN
app01-11101	10	4	of	of	ADP
app01-11101	10	5	surrogate	surrogate	ADJ
app01-11101	10	6	modeling	modeling	NOUN
app01-11101	10	7	is	be	AUX
app01-11101	10	8	to	to	PART
app01-11101	10	9	achieve	achieve	VERB
app01-11101	10	10	a	a	DET
app01-11101	10	11	balance	balance	NOUN
app01-11101	10	12	between	between	ADP
app01-11101	10	13	accuracy	accuracy	NOUN
app01-11101	10	14	and	and	CCONJ
app01-11101	10	15	computational	computational	ADJ
app01-11101	10	16	efficiency	efficiency	NOUN
app01-11101	10	17	,	,	PUNCT
app01-11101	10	18	thereby	thereby	ADV
app01-11101	10	19	facilitating	facilitate	VERB
app01-11101	10	20	more	more	ADV
app01-11101	10	21	rapid	rapid	ADJ
app01-11101	10	22	and	and	CCONJ
app01-11101	10	23	cost	cost	NOUN
app01-11101	10	24	-	-	PUNCT
app01-11101	10	25	effective	effective	ADJ
app01-11101	10	26	analyses	analysis	NOUN
app01-11101	10	27	.	.	PUNCT
app01-11101	11	1	surrogate	surrogate	ADJ
app01-11101	11	2	modeling	modeling	NOUN
app01-11101	11	3	has	have	AUX
app01-11101	11	4	found	find	VERB
app01-11101	11	5	widespread	widespread	ADJ
app01-11101	11	6	application	application	NOUN
app01-11101	11	7	across	across	ADP
app01-11101	11	8	various	various	ADJ
app01-11101	11	9	scientific	scientific	ADJ
app01-11101	11	10	and	and	CCONJ
app01-11101	11	11	engineering	engineering	NOUN
app01-11101	11	12	disciplines	discipline	NOUN
app01-11101	11	13	,	,	PUNCT
app01-11101	11	14	including	include	VERB
app01-11101	11	15	aerospace	aerospace	NOUN
app01-11101	11	16	[	[	X
app01-11101	11	17	2	2	NUM
app01-11101	11	18	]	]	PUNCT
app01-11101	11	19	,	,	PUNCT
app01-11101	11	20	civil	civil	ADJ
app01-11101	11	21	engineering	engineering	NOUN
app01-11101	11	22	[	[	X
app01-11101	11	23	3	3	NUM
app01-11101	11	24	]	]	PUNCT
app01-11101	11	25	,	,	PUNCT
app01-11101	11	26	materials	material	NOUN
app01-11101	11	27	science	science	NOUN
app01-11101	11	28	[	[	X
app01-11101	11	29	4	4	NUM
app01-11101	11	30	]	]	PUNCT
app01-11101	11	31	,	,	PUNCT
app01-11101	11	32	and	and	CCONJ
app01-11101	11	33	chemistry	chemistry	NOUN
app01-11101	12	1	[	[	X
app01-11101	12	2	5	5	NUM
app01-11101	12	3	]	]	PUNCT
app01-11101	12	4	.	.	PUNCT
app01-11101	13	1	there	there	PRON
app01-11101	13	2	are	be	VERB
app01-11101	13	3	various	various	ADJ
app01-11101	13	4	types	type	NOUN
app01-11101	13	5	of	of	ADP
app01-11101	13	6	surrogate	surrogate	ADJ
app01-11101	13	7	models	model	NOUN
app01-11101	13	8	,	,	PUNCT
app01-11101	13	9	each	each	PRON
app01-11101	13	10	characterized	characterize	VERB
app01-11101	13	11	by	by	ADP
app01-11101	13	12	distinct	distinct	ADJ
app01-11101	13	13	advantages	advantage	NOUN
app01-11101	13	14	and	and	CCONJ
app01-11101	13	15	tailored	tailor	VERB
app01-11101	13	16	to	to	ADP
app01-11101	13	17	specific	specific	ADJ
app01-11101	13	18	application	application	NOUN
app01-11101	13	19	domains	domain	NOUN
app01-11101	13	20	.	.	PUNCT
app01-11101	14	1	polynomial	polynomial	ADJ
app01-11101	14	2	response	response	NOUN
app01-11101	14	3	surfaces	surface	NOUN
app01-11101	14	4	[	[	X
app01-11101	14	5	6	6	NUM
app01-11101	14	6	]	]	X
app01-11101	14	7	,	,	PUNCT
app01-11101	14	8	such	such	ADJ
app01-11101	14	9	as	as	ADP
app01-11101	14	10	quadratic	quadratic	ADJ
app01-11101	14	11	or	or	CCONJ
app01-11101	14	12	cubic	cubic	ADJ
app01-11101	14	13	models	model	NOUN
app01-11101	14	14	,	,	PUNCT
app01-11101	14	15	are	be	AUX
app01-11101	14	16	simple	simple	ADJ
app01-11101	14	17	and	and	CCONJ
app01-11101	14	18	efficient	efficient	ADJ
app01-11101	14	19	but	but	CCONJ
app01-11101	14	20	may	may	AUX
app01-11101	14	21	struggle	struggle	VERB
app01-11101	14	22	with	with	ADP
app01-11101	14	23	highly	highly	ADV
app01-11101	14	24	nonlinear	nonlinear	ADJ
app01-11101	14	25	systems	system	NOUN
app01-11101	14	26	.	.	PUNCT
app01-11101	15	1	radial	radial	ADJ
app01-11101	15	2	basis	basis	NOUN
app01-11101	15	3	functions	function	NOUN
app01-11101	15	4	[	[	X
app01-11101	15	5	7	7	X
app01-11101	15	6	]	]	PUNCT
app01-11101	15	7	and	and	CCONJ
app01-11101	15	8	kriging	krige	VERB
app01-11101	15	9	[	[	X
app01-11101	15	10	8	8	NUM
app01-11101	15	11	]	]	PUNCT
app01-11101	15	12	(	(	PUNCT
app01-11101	15	13	or	or	CCONJ
app01-11101	15	14	gaussian	gaussian	ADJ
app01-11101	15	15	processes	process	NOUN
app01-11101	15	16	)	)	PUNCT
app01-11101	15	17	offer	offer	VERB
app01-11101	15	18	more	more	ADJ
app01-11101	15	19	flexibility	flexibility	NOUN
app01-11101	15	20	in	in	ADP
app01-11101	15	21	capturing	capture	VERB
app01-11101	15	22	complex	complex	ADJ
app01-11101	15	23	behaviors	behavior	NOUN
app01-11101	15	24	but	but	CCONJ
app01-11101	15	25	can	can	AUX
app01-11101	15	26	be	be	AUX
app01-11101	15	27	more	more	ADV
app01-11101	15	28	computationally	computationally	ADV
app01-11101	15	29	demanding	demanding	ADJ
app01-11101	15	30	.	.	PUNCT
app01-11101	16	1	artificial	artificial	ADJ
app01-11101	16	2	neural	neural	ADJ
app01-11101	16	3	networks	network	NOUN
app01-11101	16	4	[	[	X
app01-11101	16	5	9	9	NUM
app01-11101	16	6	]	]	PUNCT
app01-11101	16	7	and	and	CCONJ
app01-11101	16	8	support	support	VERB
app01-11101	16	9	vector	vector	NOUN
app01-11101	16	10	machines	machine	NOUN
app01-11101	16	11	[	[	X
app01-11101	16	12	10	10	NUM
app01-11101	16	13	]	]	PUNCT
app01-11101	16	14	are	be	AUX
app01-11101	16	15	powerful	powerful	ADJ
app01-11101	16	16	tools	tool	NOUN
app01-11101	16	17	for	for	ADP
app01-11101	16	18	high	high	ADV
app01-11101	16	19	-	-	PUNCT
app01-11101	16	20	dimensional	dimensional	ADJ
app01-11101	16	21	and	and	CCONJ
app01-11101	16	22	nonlinear	nonlinear	ADJ
app01-11101	16	23	problems	problem	NOUN
app01-11101	16	24	,	,	PUNCT
app01-11101	16	25	though	though	SCONJ
app01-11101	16	26	they	they	PRON
app01-11101	16	27	require	require	VERB
app01-11101	16	28	careful	careful	ADJ
app01-11101	16	29	tuning	tuning	NOUN
app01-11101	16	30	and	and	CCONJ
app01-11101	16	31	can	can	AUX
app01-11101	16	32	be	be	AUX
app01-11101	16	33	data	datum	NOUN
app01-11101	16	34	-	-	PUNCT
app01-11101	16	35	intensive	intensive	ADJ
app01-11101	16	36	.	.	PUNCT
app01-11101	17	1	polynomial	polynomial	ADJ
app01-11101	17	2	chaos	chaos	NOUN
app01-11101	17	3	expansions	expansion	NOUN
app01-11101	17	4	[	[	X
app01-11101	17	5	11	11	NUM
app01-11101	17	6	]	]	PUNCT
app01-11101	17	7	are	be	AUX
app01-11101	17	8	particularly	particularly	ADV
app01-11101	17	9	useful	useful	ADJ
app01-11101	17	10	for	for	ADP
app01-11101	17	11	uncertainty	uncertainty	NOUN
app01-11101	17	12	quantification	quantification	NOUN
app01-11101	17	13	problems	problem	NOUN
app01-11101	17	14	,	,	PUNCT
app01-11101	17	15	as	as	SCONJ
app01-11101	17	16	they	they	PRON
app01-11101	17	17	provide	provide	VERB
app01-11101	17	18	a	a	DET
app01-11101	17	19	structured	structured	ADJ
app01-11101	17	20	way	way	NOUN
app01-11101	17	21	to	to	PART
app01-11101	17	22	represent	represent	VERB
app01-11101	17	23	uncertainty	uncertainty	NOUN
app01-11101	17	24	in	in	ADP
app01-11101	17	25	the	the	DET
app01-11101	17	26	model	model	NOUN
app01-11101	17	27	outputs	output	NOUN
app01-11101	17	28	.	.	PUNCT
app01-11101	18	1	there	there	PRON
app01-11101	18	2	has	have	AUX
app01-11101	18	3	been	be	AUX
app01-11101	18	4	extensive	extensive	ADJ
app01-11101	18	5	research	research	NOUN
app01-11101	18	6	on	on	ADP
app01-11101	18	7	constructing	construct	VERB
app01-11101	18	8	surrogate	surrogate	ADJ
app01-11101	18	9	models	model	NOUN
app01-11101	18	10	based	base	VERB
app01-11101	18	11	on	on	ADP
app01-11101	18	12	the	the	DET
app01-11101	18	13	deep	deep	ADJ
app01-11101	18	14	learning	learning	NOUN
app01-11101	18	15	approach	approach	NOUN
app01-11101	18	16	.	.	PUNCT
app01-11101	19	1	these	these	PRON
app01-11101	19	2	can	can	AUX
app01-11101	19	3	be	be	AUX
app01-11101	19	4	generally	generally	ADV
app01-11101	19	5	classified	classify	VERB
app01-11101	19	6	into	into	ADP
app01-11101	19	7	physics	physics	NOUN
app01-11101	19	8	-	-	PUNCT
app01-11101	19	9	based	base	VERB
app01-11101	19	10	,	,	PUNCT
app01-11101	19	11	see	see	VERB
app01-11101	19	12	[	[	X
app01-11101	19	13	12	12	NUM
app01-11101	19	14	,	,	PUNCT
app01-11101	19	15	13	13	NUM
app01-11101	19	16	]	]	PUNCT
app01-11101	19	17	,	,	PUNCT
app01-11101	19	18	and	and	CCONJ
app01-11101	19	19	data	datum	NOUN
app01-11101	19	20	-	-	PUNCT
app01-11101	19	21	driven	drive	VERB
app01-11101	19	22	surrogate	surrogate	ADJ
app01-11101	19	23	models	model	NOUN
app01-11101	19	24	[	[	X
app01-11101	19	25	14	14	NUM
app01-11101	19	26	]	]	PUNCT
app01-11101	19	27	.	.	PUNCT
app01-11101	20	1	physics	physics	NOUN
app01-11101	20	2	-	-	PUNCT
app01-11101	20	3	based	base	VERB
app01-11101	20	4	surrogate	surrogate	ADJ
app01-11101	20	5	models	model	NOUN
app01-11101	20	6	rely	rely	VERB
app01-11101	20	7	on	on	ADP
app01-11101	20	8	mathematical	mathematical	ADJ
app01-11101	20	9	equations	equation	NOUN
app01-11101	20	10	derived	derive	VERB
app01-11101	20	11	from	from	ADP
app01-11101	20	12	physical	physical	ADJ
app01-11101	20	13	laws	law	NOUN
app01-11101	20	14	to	to	PART
app01-11101	20	15	describe	describe	VERB
app01-11101	20	16	system	system	NOUN
app01-11101	20	17	behavior	behavior	NOUN
app01-11101	20	18	,	,	PUNCT
app01-11101	20	19	requiring	require	VERB
app01-11101	20	20	less	less	ADJ
app01-11101	20	21	data	datum	NOUN
app01-11101	20	22	and	and	CCONJ
app01-11101	20	23	offering	offer	VERB
app01-11101	20	24	greater	great	ADJ
app01-11101	20	25	interpretability	interpretability	NOUN
app01-11101	20	26	but	but	CCONJ
app01-11101	20	27	potentially	potentially	ADV
app01-11101	20	28	struggling	struggle	VERB
app01-11101	20	29	with	with	ADP
app01-11101	20	30	complex	complex	ADJ
app01-11101	20	31	,	,	PUNCT
app01-11101	20	32	nonlinear	nonlinear	ADJ
app01-11101	20	33	phenomena	phenomenon	NOUN
app01-11101	20	34	.	.	PUNCT
app01-11101	21	1	in	in	ADP
app01-11101	21	2	contrast	contrast	NOUN
app01-11101	21	3	,	,	PUNCT
app01-11101	21	4	data	data	NOUN
app01-11101	21	5	-	-	PUNCT
app01-11101	21	6	driven	drive	VERB
app01-11101	21	7	surrogate	surrogate	ADJ
app01-11101	21	8	models	model	NOUN
app01-11101	21	9	use	use	VERB
app01-11101	21	10	statistical	statistical	ADJ
app01-11101	21	11	and	and	CCONJ
app01-11101	21	12	machine	machine	NOUN
app01-11101	21	13	learning	learn	VERB
app01-11101	21	14	techniques	technique	NOUN
app01-11101	21	15	to	to	PART
app01-11101	21	16	learn	learn	VERB
app01-11101	21	17	from	from	ADP
app01-11101	21	18	large	large	ADJ
app01-11101	21	19	datasets	dataset	NOUN
app01-11101	21	20	,	,	PUNCT
app01-11101	21	21	providing	provide	VERB
app01-11101	21	22	rapid	rapid	ADJ
app01-11101	21	23	predictions	prediction	NOUN
app01-11101	21	24	and	and	CCONJ
app01-11101	21	25	good	good	ADJ
app01-11101	21	26	generalization	generalization	NOUN
app01-11101	21	27	.	.	PUNCT
app01-11101	22	1	here	here	ADV
app01-11101	22	2	,	,	PUNCT
app01-11101	22	3	we	we	PRON
app01-11101	22	4	concentrate	concentrate	VERB
app01-11101	22	5	on	on	ADP
app01-11101	22	6	the	the	DET
app01-11101	22	7	construction	construction	NOUN
app01-11101	22	8	of	of	ADP
app01-11101	22	9	datadriven	datadriven	ADJ
app01-11101	22	10	surrogate	surrogate	ADJ
app01-11101	22	11	models	model	NOUN
app01-11101	22	12	utilizing	utilize	VERB
app01-11101	22	13	deep	deep	ADJ
app01-11101	22	14	neural	neural	ADJ
app01-11101	22	15	networks	network	NOUN
app01-11101	22	16	.	.	PUNCT
app01-11101	23	1	each	each	DET
app01-11101	23	2	dnn	dnn	PROPN
app01-11101	23	3	contains	contain	VERB
app01-11101	23	4	multiple	multiple	ADJ
app01-11101	23	5	layers	layer	NOUN
app01-11101	23	6	of	of	ADP
app01-11101	23	7	interconnected	interconnected	ADJ
app01-11101	23	8	nodes	node	NOUN
app01-11101	23	9	enabling	enable	VERB
app01-11101	23	10	one	one	NUM
app01-11101	23	11	to	to	PART
app01-11101	23	12	learn	learn	VERB
app01-11101	23	13	complex	complex	ADJ
app01-11101	23	14	data	datum	NOUN
app01-11101	23	15	representations	representation	NOUN
app01-11101	23	16	by	by	ADP
app01-11101	23	17	identifying	identify	VERB
app01-11101	23	18	hierarchical	hierarchical	ADJ
app01-11101	23	19	patterns	pattern	NOUN
app01-11101	23	20	and	and	CCONJ
app01-11101	23	21	features	feature	NOUN
app01-11101	23	22	,	,	PUNCT
app01-11101	23	23	as	as	SCONJ
app01-11101	23	24	detailed	detailed	ADJ
app01-11101	23	25	in	in	ADP
app01-11101	23	26	[	[	X
app01-11101	23	27	14	14	NUM
app01-11101	23	28	]	]	PUNCT
app01-11101	23	29	.	.	PUNCT
app01-11101	24	1	a	a	DET
app01-11101	24	2	typical	typical	ADJ
app01-11101	24	3	dnn	dnn	PROPN
app01-11101	24	4	consists	consist	VERB
app01-11101	24	5	of	of	ADP
app01-11101	24	6	three	three	NUM
app01-11101	24	7	types	type	NOUN
app01-11101	24	8	of	of	ADP
app01-11101	24	9	layers	layer	NOUN
app01-11101	24	10	:	:	PUNCT
app01-11101	24	11	(	(	PUNCT
app01-11101	24	12	1	1	X
app01-11101	24	13	.	.	PUNCT
app01-11101	24	14	)	)	PUNCT
app01-11101	25	1	an	an	DET
app01-11101	25	2	input	input	NOUN
app01-11101	25	3	layer	layer	NOUN
app01-11101	25	4	that	that	PRON
app01-11101	25	5	processes	process	VERB
app01-11101	25	6	input	input	NOUN
app01-11101	25	7	data	datum	NOUN
app01-11101	25	8	into	into	ADP
app01-11101	25	9	the	the	DET
app01-11101	25	10	model	model	NOUN
app01-11101	25	11	,	,	PUNCT
app01-11101	25	12	(	(	PUNCT
app01-11101	25	13	2	2	NUM
app01-11101	25	14	.	.	PUNCT
app01-11101	25	15	)	)	PUNCT
app01-11101	25	16	hidden	hide	VERB
app01-11101	25	17	layers	layer	NOUN
app01-11101	25	18	that	that	PRON
app01-11101	25	19	constitute	constitute	VERB
app01-11101	25	20	the	the	DET
app01-11101	25	21	core	core	NOUN
app01-11101	25	22	of	of	ADP
app01-11101	25	23	the	the	DET
app01-11101	25	24	dnn	dnn	PROPN
app01-11101	25	25	,	,	PUNCT
app01-11101	25	26	applying	apply	VERB
app01-11101	25	27	weights	weight	NOUN
app01-11101	25	28	to	to	ADP
app01-11101	25	29	the	the	DET
app01-11101	25	30	inputs	input	NOUN
app01-11101	25	31	and	and	CCONJ
app01-11101	25	32	passing	pass	VERB
app01-11101	25	33	them	they	PRON
app01-11101	25	34	through	through	ADP
app01-11101	25	35	the	the	DET
app01-11101	25	36	activation	activation	NOUN
app01-11101	25	37	functions	function	NOUN
app01-11101	25	38	to	to	PART
app01-11101	25	39	generate	generate	VERB
app01-11101	25	40	outputs	output	NOUN
app01-11101	25	41	,	,	PUNCT
app01-11101	25	42	and	and	CCONJ
app01-11101	25	43	(	(	PUNCT
app01-11101	25	44	3	3	NUM
app01-11101	25	45	.	.	PUNCT
app01-11101	25	46	)	)	PUNCT
app01-11101	26	1	an	an	DET
app01-11101	26	2	output	output	NOUN
app01-11101	26	3	layer	layer	NOUN
app01-11101	26	4	that	that	PRON
app01-11101	26	5	computes	compute	VERB
app01-11101	26	6	the	the	DET
app01-11101	26	7	final	final	ADJ
app01-11101	26	8	probability	probability	NOUN
app01-11101	26	9	scores	score	NOUN
app01-11101	26	10	of	of	ADP
app01-11101	26	11	the	the	DET
app01-11101	26	12	desired	desire	VERB
app01-11101	26	13	outputs	output	NOUN
app01-11101	26	14	.	.	PUNCT
app01-11101	27	1	a	a	DET
app01-11101	27	2	specialized	specialized	ADJ
app01-11101	27	3	form	form	NOUN
app01-11101	27	4	of	of	ADP
app01-11101	27	5	dnn	dnn	PROPN
app01-11101	27	6	is	be	AUX
app01-11101	27	7	the	the	DET
app01-11101	27	8	convolutional	convolutional	ADJ
app01-11101	27	9	neural	neural	ADJ
app01-11101	27	10	network	network	NOUN
app01-11101	27	11	(	(	PUNCT
app01-11101	27	12	cnn	cnn	PROPN
app01-11101	27	13	)	)	PUNCT
app01-11101	27	14	,	,	PUNCT
app01-11101	27	15	designed	design	VERB
app01-11101	27	16	for	for	ADP
app01-11101	27	17	image	image	NOUN
app01-11101	27	18	classification	classification	NOUN
app01-11101	27	19	and	and	CCONJ
app01-11101	27	20	visual	visual	ADJ
app01-11101	27	21	data	datum	NOUN
app01-11101	27	22	interpretation	interpretation	NOUN
app01-11101	27	23	[	[	X
app01-11101	27	24	15	15	NUM
app01-11101	27	25	]	]	PUNCT
app01-11101	27	26	.	.	PUNCT
app01-11101	28	1	cnns	cnns	PROPN
app01-11101	28	2	operate	operate	VERB
app01-11101	28	3	on	on	ADP
app01-11101	28	4	the	the	DET
app01-11101	28	5	principles	principle	NOUN
app01-11101	28	6	of	of	ADP
app01-11101	28	7	mathematical	mathematical	ADJ
app01-11101	28	8	convolution	convolution	NOUN
app01-11101	28	9	,	,	PUNCT
app01-11101	28	10	extracting	extract	VERB
app01-11101	28	11	salient	salient	NOUN
app01-11101	28	12	features	feature	NOUN
app01-11101	28	13	from	from	ADP
app01-11101	28	14	images	image	NOUN
app01-11101	28	15	using	use	VERB
app01-11101	28	16	learnable	learnable	ADJ
app01-11101	28	17	filters	filter	NOUN
app01-11101	28	18	.	.	PUNCT
app01-11101	29	1	they	they	PRON
app01-11101	29	2	are	be	AUX
app01-11101	29	3	primarily	primarily	ADV
app01-11101	29	4	composed	compose	VERB
app01-11101	29	5	of	of	ADP
app01-11101	29	6	convolutional	convolutional	ADJ
app01-11101	29	7	layers	layer	NOUN
app01-11101	29	8	and	and	CCONJ
app01-11101	29	9	max	max	PROPN
app01-11101	29	10	pooling	pool	VERB
app01-11101	29	11	layers	layer	NOUN
app01-11101	29	12	,	,	PUNCT
app01-11101	29	13	which	which	PRON
app01-11101	29	14	reduce	reduce	VERB
app01-11101	29	15	the	the	DET
app01-11101	29	16	number	number	NOUN
app01-11101	29	17	of	of	ADP
app01-11101	29	18	weights	weight	NOUN
app01-11101	29	19	in	in	ADP
app01-11101	29	20	the	the	DET
app01-11101	29	21	neural	neural	ADJ
app01-11101	29	22	network	network	NOUN
app01-11101	29	23	.	.	PUNCT
app01-11101	30	1	surrogate	surrogate	ADJ
app01-11101	30	2	models	model	NOUN
app01-11101	30	3	founded	found	VERB
app01-11101	30	4	on	on	ADP
app01-11101	30	5	the	the	DET
app01-11101	30	6	principles	principle	NOUN
app01-11101	30	7	of	of	ADP
app01-11101	30	8	dnn	dnn	PROPN
app01-11101	30	9	and	and	CCONJ
app01-11101	30	10	cnn	cnn	PROPN
app01-11101	30	11	architectures	architecture	NOUN
app01-11101	30	12	and	and	CCONJ
app01-11101	30	13	constructed	construct	VERB
app01-11101	30	14	for	for	ADP
app01-11101	30	15	heat	heat	NOUN
app01-11101	30	16	transfer	transfer	NOUN
app01-11101	30	17	modeling	modeling	NOUN
app01-11101	30	18	represent	represent	VERB
app01-11101	30	19	the	the	DET
app01-11101	30	20	main	main	ADJ
app01-11101	30	21	idea	idea	NOUN
app01-11101	30	22	of	of	ADP
app01-11101	30	23	this	this	DET
app01-11101	30	24	contribution	contribution	NOUN
app01-11101	30	25	.	.	PUNCT
app01-11101	31	1	our	our	PRON
app01-11101	31	2	framework	framework	NOUN
app01-11101	31	3	extends	extend	VERB
app01-11101	31	4	the	the	DET
app01-11101	31	5	work	work	NOUN
app01-11101	31	6	detailed	detail	VERB
app01-11101	31	7	in	in	ADP
app01-11101	31	8	[	[	X
app01-11101	31	9	16	16	NUM
app01-11101	31	10	,	,	PUNCT
app01-11101	31	11	17	17	NUM
app01-11101	31	12	]	]	PUNCT
app01-11101	31	13	,	,	PUNCT
app01-11101	31	14	examining	examine	VERB
app01-11101	31	15	this	this	DET
app01-11101	31	16	aspect	aspect	NOUN
app01-11101	31	17	from	from	ADP
app01-11101	31	18	various	various	ADJ
app01-11101	31	19	perspectives	perspective	NOUN
app01-11101	31	20	.	.	PUNCT
app01-11101	32	1	the	the	DET
app01-11101	32	2	paper	paper	NOUN
app01-11101	32	3	is	be	AUX
app01-11101	32	4	structured	structure	VERB
app01-11101	32	5	as	as	SCONJ
app01-11101	32	6	follows	follow	VERB
app01-11101	32	7	:	:	PUNCT
app01-11101	32	8	the	the	DET
app01-11101	32	9	79	79	NUM
app01-11101	32	10	https://doi.org/10.14311/app.2025.54.0079	https://doi.org/10.14311/app.2025.54.0079	PROPN
app01-11101	32	11	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
app01-11101	32	12	https://www.cvut.cz/en	https://www.cvut.cz/en	PROPN
app01-11101	32	13	ondřej	ondřej	NOUN
app01-11101	32	14	šperl	šperl	PROPN
app01-11101	32	15	,	,	PUNCT
app01-11101	32	16	jan	jan	PROPN
app01-11101	32	17	sýkora	sýkora	PROPN
app01-11101	32	18	acta	acta	PROPN
app01-11101	32	19	polytechnica	polytechnica	PROPN
app01-11101	32	20	ctu	ctu	PROPN
app01-11101	32	21	proceedings	proceeding	NOUN
app01-11101	32	22	methodology	methodology	NOUN
app01-11101	32	23	section	section	NOUN
app01-11101	32	24	2	2	NUM
app01-11101	32	25	concisely	concisely	ADV
app01-11101	32	26	outline	outline	VERB
app01-11101	32	27	the	the	DET
app01-11101	32	28	fundamentals	fundamental	NOUN
app01-11101	32	29	of	of	ADP
app01-11101	32	30	non	non	ADJ
app01-11101	32	31	-	-	ADJ
app01-11101	32	32	stationary	stationary	ADJ
app01-11101	32	33	heat	heat	NOUN
app01-11101	32	34	transport	transport	NOUN
app01-11101	32	35	and	and	CCONJ
app01-11101	32	36	the	the	DET
app01-11101	32	37	subsequent	subsequent	ADJ
app01-11101	32	38	discretization	discretization	NOUN
app01-11101	32	39	using	use	VERB
app01-11101	32	40	the	the	DET
app01-11101	32	41	finite	finite	ADJ
app01-11101	32	42	element	element	NOUN
app01-11101	32	43	method	method	NOUN
app01-11101	32	44	.	.	PUNCT
app01-11101	33	1	the	the	DET
app01-11101	33	2	effectiveness	effectiveness	NOUN
app01-11101	33	3	of	of	ADP
app01-11101	33	4	the	the	DET
app01-11101	33	5	proposed	propose	VERB
app01-11101	33	6	dnn	dnn	PROPN
app01-11101	33	7	-	-	PUNCT
app01-11101	33	8	based	base	VERB
app01-11101	33	9	surrogate	surrogate	ADJ
app01-11101	33	10	model	model	NOUN
app01-11101	33	11	is	be	AUX
app01-11101	33	12	evaluated	evaluate	VERB
app01-11101	33	13	in	in	ADP
app01-11101	33	14	section	section	NOUN
app01-11101	33	15	3	3	NUM
app01-11101	33	16	through	through	ADP
app01-11101	33	17	its	its	PRON
app01-11101	33	18	application	application	NOUN
app01-11101	33	19	to	to	ADP
app01-11101	33	20	the	the	DET
app01-11101	33	21	stationary	stationary	ADJ
app01-11101	33	22	heat	heat	NOUN
app01-11101	33	23	conduction	conduction	NOUN
app01-11101	33	24	problem	problem	NOUN
app01-11101	33	25	with	with	ADP
app01-11101	33	26	dirichlet	dirichlet	PROPN
app01-11101	33	27	boundary	boundary	PROPN
app01-11101	33	28	conditions	condition	NOUN
app01-11101	33	29	.	.	PUNCT
app01-11101	34	1	our	our	PRON
app01-11101	34	2	conclusions	conclusion	NOUN
app01-11101	34	3	will	will	AUX
app01-11101	34	4	be	be	AUX
app01-11101	34	5	summarized	summarize	VERB
app01-11101	34	6	in	in	ADP
app01-11101	34	7	the	the	DET
app01-11101	34	8	final	final	ADJ
app01-11101	34	9	section	section	NOUN
app01-11101	34	10	4	4	NUM
app01-11101	34	11	.	.	NOUN
app01-11101	34	12	2	2	NUM
app01-11101	34	13	.	.	X
app01-11101	34	14	methodology	methodology	NOUN
app01-11101	34	15	initially	initially	ADV
app01-11101	34	16	,	,	PUNCT
app01-11101	34	17	we	we	PRON
app01-11101	34	18	consider	consider	VERB
app01-11101	34	19	a	a	DET
app01-11101	34	20	bounded	bounded	ADJ
app01-11101	34	21	body	body	NOUN
app01-11101	34	22	d	d	PROPN
app01-11101	34	23	⊂	⊂	PROPN
app01-11101	34	24	r3	r3	PROPN
app01-11101	34	25	(	(	PUNCT
app01-11101	34	26	reference	reference	NOUN
app01-11101	34	27	configuration	configuration	NOUN
app01-11101	34	28	)	)	PUNCT
app01-11101	34	29	with	with	ADP
app01-11101	34	30	a	a	DET
app01-11101	34	31	piecewise	piecewise	NOUN
app01-11101	34	32	smooth	smooth	ADJ
app01-11101	34	33	boundary	boundary	PROPN
app01-11101	34	34	γ	γ	X
app01-11101	34	35	.	.	PROPN
app01-11101	34	36	specifically	specifically	ADV
app01-11101	34	37	,	,	PUNCT
app01-11101	34	38	the	the	DET
app01-11101	34	39	dirichlet	dirichlet	PROPN
app01-11101	34	40	,	,	PUNCT
app01-11101	34	41	neumann	neumann	PROPN
app01-11101	34	42	,	,	PUNCT
app01-11101	34	43	and	and	CCONJ
app01-11101	34	44	robin	robin	PROPN
app01-11101	34	45	boundary	boundary	PROPN
app01-11101	34	46	conditions	condition	NOUN
app01-11101	34	47	are	be	AUX
app01-11101	34	48	applied	apply	VERB
app01-11101	34	49	to	to	ADP
app01-11101	34	50	γd	γd	ADP
app01-11101	34	51	⊂	⊂	PROPN
app01-11101	34	52	γ	γ	X
app01-11101	34	53	,	,	PUNCT
app01-11101	34	54	γn	γn	ADP
app01-11101	34	55	⊂	⊂	PROPN
app01-11101	34	56	γ	γ	X
app01-11101	34	57	,	,	PUNCT
app01-11101	34	58	and	and	CCONJ
app01-11101	34	59	γr	γr	PROPN
app01-11101	34	60	⊂	⊂	PROPN
app01-11101	34	61	γ	γ	PROPN
app01-11101	34	62	,	,	PUNCT
app01-11101	34	63	respectively	respectively	ADV
app01-11101	34	64	,	,	PUNCT
app01-11101	34	65	such	such	ADJ
app01-11101	34	66	that	that	SCONJ
app01-11101	34	67	γ	γ	PROPN
app01-11101	34	68	=	=	SYM
app01-11101	34	69	γd	γd	ADP
app01-11101	34	70	∪γn	∪γn	NOUN
app01-11101	34	71	∪γr	∪γr	NOUN
app01-11101	34	72	.	.	PUNCT
app01-11101	35	1	to	to	PART
app01-11101	35	2	analyze	analyze	VERB
app01-11101	35	3	the	the	DET
app01-11101	35	4	temporal	temporal	ADJ
app01-11101	35	5	behavior	behavior	NOUN
app01-11101	35	6	of	of	ADP
app01-11101	35	7	d	d	PROPN
app01-11101	35	8	,	,	PUNCT
app01-11101	35	9	we	we	PRON
app01-11101	35	10	consider	consider	VERB
app01-11101	35	11	a	a	DET
app01-11101	35	12	time	time	NOUN
app01-11101	35	13	interval	interval	NOUN
app01-11101	35	14	[	[	X
app01-11101	35	15	0	0	NUM
app01-11101	35	16	,	,	PUNCT
app01-11101	35	17	ts	ts	ADP
app01-11101	35	18	]	]	X
app01-11101	36	1	⊂	⊂	X
app01-11101	36	2	r+	r+	PROPN
app01-11101	36	3	.	.	PUNCT
app01-11101	37	1	the	the	DET
app01-11101	37	2	temperature	temperature	NOUN
app01-11101	37	3	evolution	evolution	NOUN
app01-11101	37	4	in	in	ADP
app01-11101	37	5	d	d	PROPN
app01-11101	37	6	is	be	AUX
app01-11101	37	7	given	give	VERB
app01-11101	37	8	by	by	ADP
app01-11101	37	9	the	the	DET
app01-11101	37	10	function	function	NOUN
app01-11101	37	11	θ	θ	NOUN
app01-11101	37	12	:	:	PUNCT
app01-11101	38	1	d	d	X
app01-11101	38	2	×	×	NOUN
app01-11101	39	1	[	[	X
app01-11101	39	2	0	0	NUM
app01-11101	39	3	,	,	PUNCT
app01-11101	39	4	ts	ts	ADP
app01-11101	39	5	]	]	PUNCT
app01-11101	39	6	→	→	SYM
app01-11101	39	7	r3	r3	PROPN
app01-11101	39	8	,	,	PUNCT
app01-11101	39	9	(	(	PUNCT
app01-11101	39	10	1	1	X
app01-11101	39	11	)	)	PUNCT
app01-11101	39	12	where	where	SCONJ
app01-11101	39	13	θ	θ	PROPN
app01-11101	39	14	(	(	PUNCT
app01-11101	39	15	in	in	ADP
app01-11101	39	16	degrees	degree	NOUN
app01-11101	39	17	celsius	celsius	NOUN
app01-11101	39	18	)	)	PUNCT
app01-11101	39	19	represents	represent	VERB
app01-11101	39	20	the	the	DET
app01-11101	39	21	temperature	temperature	NOUN
app01-11101	39	22	.	.	PUNCT
app01-11101	40	1	the	the	DET
app01-11101	40	2	heat	heat	NOUN
app01-11101	40	3	transport	transport	NOUN
app01-11101	40	4	is	be	AUX
app01-11101	40	5	then	then	ADV
app01-11101	40	6	governed	govern	VERB
app01-11101	40	7	by	by	ADP
app01-11101	40	8	the	the	DET
app01-11101	40	9	transient	transient	ADJ
app01-11101	40	10	heat	heat	NOUN
app01-11101	40	11	balance	balance	NOUN
app01-11101	40	12	equation	equation	NOUN
app01-11101	40	13	with	with	ADP
app01-11101	40	14	initial	initial	ADJ
app01-11101	40	15	and	and	CCONJ
app01-11101	40	16	boundary	boundary	ADJ
app01-11101	40	17	conditions	condition	NOUN
app01-11101	40	18	.	.	PUNCT
app01-11101	41	1			PROPN
app01-11101	41	2	cv(x)∂θ	cv(x)∂θ	PROPN
app01-11101	42	1	∂t	∂t	PROPN
app01-11101	42	2	(	(	PUNCT
app01-11101	42	3	x	x	PROPN
app01-11101	42	4	,	,	PUNCT
app01-11101	42	5	t	t	PROPN
app01-11101	42	6	)	)	PUNCT
app01-11101	42	7	−	−	PROPN
app01-11101	42	8	∇	∇	X
app01-11101	42	9	·	·	PUNCT
app01-11101	42	10	(	(	PUNCT
app01-11101	42	11	λ(x)∇θ(x	λ(x)∇θ(x	PROPN
app01-11101	42	12	,	,	PUNCT
app01-11101	42	13	t	t	PROPN
app01-11101	42	14	)	)	PUNCT
app01-11101	42	15	)	)	PUNCT
app01-11101	43	1	=	=	PUNCT
app01-11101	43	2	0	0	NUM
app01-11101	43	3	,	,	PUNCT
app01-11101	43	4	x	x	X
app01-11101	43	5	∈	∈	PROPN
app01-11101	43	6	d	d	PROPN
app01-11101	43	7	,	,	PUNCT
app01-11101	43	8	t	t	PROPN
app01-11101	43	9	∈	∈	PROPN
app01-11101	43	10	(	(	PUNCT
app01-11101	43	11	0	0	NUM
app01-11101	43	12	,	,	PUNCT
app01-11101	43	13	ts	ts	NOUN
app01-11101	43	14	)	)	PUNCT
app01-11101	43	15	,	,	PUNCT
app01-11101	43	16	θ(x	θ(x	PROPN
app01-11101	43	17	,	,	PUNCT
app01-11101	43	18	t	t	PROPN
app01-11101	43	19	)	)	PUNCT
app01-11101	43	20	=	=	PUNCT
app01-11101	43	21	θd(x	θd(x	PROPN
app01-11101	43	22	,	,	PUNCT
app01-11101	43	23	t	t	PROPN
app01-11101	43	24	)	)	PUNCT
app01-11101	43	25	,	,	PUNCT
app01-11101	43	26	x	x	PUNCT
app01-11101	43	27	∈	∈	PROPN
app01-11101	43	28	γd	γd	ADP
app01-11101	43	29	,	,	PUNCT
app01-11101	43	30	t	t	PROPN
app01-11101	43	31	∈	∈	PROPN
app01-11101	43	32	(	(	PUNCT
app01-11101	43	33	0	0	NUM
app01-11101	43	34	,	,	PUNCT
app01-11101	43	35	ts	ts	NOUN
app01-11101	43	36	)	)	PUNCT
app01-11101	43	37	,	,	PUNCT
app01-11101	43	38	λ(x	λ(x	X
app01-11101	43	39	)	)	PUNCT
app01-11101	44	1	∂θ	∂θ	PROPN
app01-11101	45	1	∂n	∂n	PROPN
app01-11101	45	2	(	(	PUNCT
app01-11101	45	3	x	x	X
app01-11101	45	4	,	,	PUNCT
app01-11101	45	5	t	t	PROPN
app01-11101	45	6	)	)	PUNCT
app01-11101	45	7	=	=	SYM
app01-11101	46	1	qn	qn	INTJ
app01-11101	46	2	(	(	PUNCT
app01-11101	46	3	x	x	PROPN
app01-11101	46	4	,	,	PUNCT
app01-11101	46	5	t	t	PROPN
app01-11101	46	6	)	)	PUNCT
app01-11101	46	7	,	,	PUNCT
app01-11101	46	8	x	x	PUNCT
app01-11101	46	9	∈	∈	NOUN
app01-11101	46	10	γn	γn	NOUN
app01-11101	46	11	,	,	PUNCT
app01-11101	46	12	t	t	PROPN
app01-11101	46	13	∈	∈	PROPN
app01-11101	46	14	(	(	PUNCT
app01-11101	46	15	0	0	NUM
app01-11101	46	16	,	,	PUNCT
app01-11101	46	17	ts	ts	NOUN
app01-11101	46	18	)	)	PUNCT
app01-11101	46	19	,	,	PUNCT
app01-11101	47	1	α(θ(x	α(θ(x	PROPN
app01-11101	47	2	,	,	PUNCT
app01-11101	47	3	t	t	PROPN
app01-11101	47	4	)	)	PUNCT
app01-11101	47	5	−	−	PROPN
app01-11101	47	6	θ∞(x	θ∞(x	PROPN
app01-11101	47	7	,	,	PUNCT
app01-11101	47	8	t	t	PROPN
app01-11101	47	9	)	)	PUNCT
app01-11101	47	10	)	)	PUNCT
app01-11101	48	1	=	=	SYM
app01-11101	48	2	λ(x	λ(x	X
app01-11101	48	3	)	)	PUNCT
app01-11101	49	1	∂θ	∂θ	PROPN
app01-11101	50	1	∂n	∂n	PROPN
app01-11101	50	2	(	(	PUNCT
app01-11101	50	3	x	x	X
app01-11101	50	4	,	,	PUNCT
app01-11101	50	5	t	t	PROPN
app01-11101	50	6	)	)	PUNCT
app01-11101	50	7	,	,	PUNCT
app01-11101	50	8	x	x	PUNCT
app01-11101	50	9	∈	∈	PROPN
app01-11101	50	10	γr	γr	PROPN
app01-11101	50	11	,	,	PUNCT
app01-11101	50	12	t	t	PROPN
app01-11101	50	13	∈	∈	PROPN
app01-11101	50	14	(	(	PUNCT
app01-11101	50	15	0	0	NUM
app01-11101	50	16	,	,	PUNCT
app01-11101	50	17	ts	ts	NOUN
app01-11101	50	18	)	)	PUNCT
app01-11101	50	19	,	,	PUNCT
app01-11101	50	20	θ(x	θ(x	PROPN
app01-11101	50	21	,	,	PUNCT
app01-11101	50	22	0	0	NUM
app01-11101	50	23	)	)	PUNCT
app01-11101	50	24	=	=	SYM
app01-11101	50	25	θin(x	θin(x	PROPN
app01-11101	50	26	)	)	PUNCT
app01-11101	50	27	,	,	PUNCT
app01-11101	50	28	x	x	PROPN
app01-11101	50	29	∈	∈	PROPN
app01-11101	50	30	d.	d.	NOUN
app01-11101	50	31	(	(	PUNCT
app01-11101	50	32	2	2	X
app01-11101	50	33	)	)	PUNCT
app01-11101	50	34	the	the	DET
app01-11101	50	35	equations	equation	NOUN
app01-11101	50	36	involve	involve	VERB
app01-11101	50	37	several	several	ADJ
app01-11101	50	38	key	key	ADJ
app01-11101	50	39	parameters	parameter	NOUN
app01-11101	50	40	to	to	PART
app01-11101	50	41	define	define	VERB
app01-11101	50	42	the	the	DET
app01-11101	50	43	thermal	thermal	ADJ
app01-11101	50	44	behavior	behavior	NOUN
app01-11101	50	45	of	of	ADP
app01-11101	50	46	the	the	DET
app01-11101	50	47	system	system	NOUN
app01-11101	50	48	.	.	PUNCT
app01-11101	51	1	the	the	DET
app01-11101	51	2	thermal	thermal	ADJ
app01-11101	51	3	conductivity	conductivity	NOUN
app01-11101	51	4	is	be	AUX
app01-11101	51	5	represented	represent	VERB
app01-11101	51	6	by	by	ADP
app01-11101	51	7	λ(x	λ(x	PROPN
app01-11101	51	8	)	)	PUNCT
app01-11101	52	1	[	[	X
app01-11101	52	2	w	w	X
app01-11101	52	3	m−1	m−1	PROPN
app01-11101	52	4	k−1	k−1	PROPN
app01-11101	52	5	]	]	PUNCT
app01-11101	52	6	,	,	PUNCT
app01-11101	52	7	while	while	SCONJ
app01-11101	52	8	the	the	DET
app01-11101	52	9	volumetric	volumetric	NOUN
app01-11101	52	10	heat	heat	NOUN
app01-11101	52	11	capacity	capacity	NOUN
app01-11101	52	12	,	,	PUNCT
app01-11101	52	13	cv(x	cv(x	X
app01-11101	52	14	)	)	PUNCT
app01-11101	53	1	[	[	X
app01-11101	53	2	j	j	PROPN
app01-11101	53	3	m−3	m−3	PROPN
app01-11101	53	4	k−1	k−1	PROPN
app01-11101	53	5	]	]	PUNCT
app01-11101	53	6	,	,	PUNCT
app01-11101	53	7	is	be	AUX
app01-11101	53	8	derived	derive	VERB
app01-11101	53	9	as	as	ADP
app01-11101	53	10	the	the	DET
app01-11101	53	11	product	product	NOUN
app01-11101	53	12	of	of	ADP
app01-11101	53	13	the	the	DET
app01-11101	53	14	volumetric	volumetric	NOUN
app01-11101	53	15	mass	mass	NOUN
app01-11101	53	16	density	density	NOUN
app01-11101	53	17	ρs(x	ρs(x	PROPN
app01-11101	53	18	)	)	PUNCT
app01-11101	54	1	[	[	X
app01-11101	54	2	kg	kg	X
app01-11101	54	3	m−3	m−3	NOUN
app01-11101	54	4	]	]	PUNCT
app01-11101	54	5	and	and	CCONJ
app01-11101	54	6	the	the	DET
app01-11101	54	7	specific	specific	ADJ
app01-11101	54	8	heat	heat	NOUN
app01-11101	54	9	capacity	capacity	NOUN
app01-11101	54	10	cp(x	cp(x	NOUN
app01-11101	54	11	)	)	PUNCT
app01-11101	55	1	[	[	X
app01-11101	55	2	j	j	X
app01-11101	55	3	kg−1	kg−1	PROPN
app01-11101	55	4	k−1	k−1	PROPN
app01-11101	55	5	]	]	PUNCT
app01-11101	55	6	,	,	PUNCT
app01-11101	55	7	expressed	express	VERB
app01-11101	55	8	as	as	ADP
app01-11101	55	9	cv(x	cv(x	X
app01-11101	55	10	)	)	PUNCT
app01-11101	55	11	=	=	SYM
app01-11101	55	12	ρs(x)cp(x	ρs(x)cp(x	PROPN
app01-11101	55	13	)	)	PUNCT
app01-11101	55	14	.	.	PUNCT
app01-11101	56	1	the	the	DET
app01-11101	56	2	final	final	ADJ
app01-11101	56	3	simulation	simulation	NOUN
app01-11101	56	4	time	time	NOUN
app01-11101	56	5	is	be	AUX
app01-11101	56	6	denoted	denote	VERB
app01-11101	56	7	by	by	ADP
app01-11101	56	8	ts	ts	ADP
app01-11101	57	1	[	[	X
app01-11101	57	2	s	s	X
app01-11101	57	3	]	]	X
app01-11101	57	4	,	,	PUNCT
app01-11101	57	5	and	and	CCONJ
app01-11101	57	6	the	the	DET
app01-11101	57	7	ambient	ambient	ADJ
app01-11101	57	8	temperature	temperature	NOUN
app01-11101	57	9	is	be	AUX
app01-11101	57	10	given	give	VERB
app01-11101	57	11	by	by	ADP
app01-11101	57	12	θ∞(x	θ∞(x	PROPN
app01-11101	57	13	,	,	PUNCT
app01-11101	57	14	t	t	PROPN
app01-11101	57	15	)	)	PUNCT
app01-11101	58	1	[	[	X
app01-11101	58	2	◦	◦	NOUN
app01-11101	58	3	c	c	X
app01-11101	58	4	]	]	PUNCT
app01-11101	58	5	.	.	PUNCT
app01-11101	59	1	furthermore	furthermore	ADV
app01-11101	59	2	,	,	PUNCT
app01-11101	59	3	the	the	DET
app01-11101	59	4	heat	heat	NOUN
app01-11101	59	5	transfer	transfer	NOUN
app01-11101	59	6	coefficient	coefficient	NOUN
app01-11101	59	7	is	be	AUX
app01-11101	59	8	α	α	NOUN
app01-11101	60	1	[	[	X
app01-11101	60	2	w	w	PROPN
app01-11101	60	3	m−2	m−2	PROPN
app01-11101	60	4	k−1	k−1	PROPN
app01-11101	60	5	]	]	PUNCT
app01-11101	60	6	,	,	PUNCT
app01-11101	60	7	with	with	ADP
app01-11101	60	8	θd(x	θd(x	PROPN
app01-11101	60	9	,	,	PUNCT
app01-11101	60	10	t	t	PROPN
app01-11101	60	11	)	)	PUNCT
app01-11101	61	1	[	[	X
app01-11101	61	2	◦	◦	NOUN
app01-11101	61	3	c	c	X
app01-11101	61	4	]	]	PUNCT
app01-11101	61	5	and	and	CCONJ
app01-11101	61	6	qn	qn	X
app01-11101	61	7	[	[	X
app01-11101	61	8	w	w	PROPN
app01-11101	61	9	m−2	m−2	NOUN
app01-11101	61	10	]	]	PUNCT
app01-11101	61	11	representing	represent	VERB
app01-11101	61	12	the	the	DET
app01-11101	61	13	prescribed	prescribed	ADJ
app01-11101	61	14	temperature	temperature	NOUN
app01-11101	61	15	and	and	CCONJ
app01-11101	61	16	the	the	DET
app01-11101	61	17	heat	heat	NOUN
app01-11101	61	18	flux	flux	NOUN
app01-11101	61	19	,	,	PUNCT
app01-11101	61	20	respectively	respectively	ADV
app01-11101	61	21	.	.	PUNCT
app01-11101	62	1	we	we	PRON
app01-11101	62	2	begin	begin	VERB
app01-11101	62	3	by	by	ADP
app01-11101	62	4	restricting	restrict	VERB
app01-11101	62	5	our	our	PRON
app01-11101	62	6	analysis	analysis	NOUN
app01-11101	62	7	to	to	ADP
app01-11101	62	8	the	the	DET
app01-11101	62	9	stationary	stationary	ADJ
app01-11101	62	10	case	case	NOUN
app01-11101	62	11	,	,	PUNCT
app01-11101	62	12	which	which	PRON
app01-11101	62	13	significantly	significantly	ADV
app01-11101	62	14	simplifies	simplify	VERB
app01-11101	62	15	data	datum	NOUN
app01-11101	62	16	management	management	NOUN
app01-11101	62	17	in	in	ADP
app01-11101	62	18	the	the	DET
app01-11101	62	19	neural	neural	ADJ
app01-11101	62	20	network	network	NOUN
app01-11101	62	21	training	training	NOUN
app01-11101	62	22	process	process	NOUN
app01-11101	62	23	.	.	PUNCT
app01-11101	63	1	this	this	DET
app01-11101	63	2	approach	approach	NOUN
app01-11101	63	3	allows	allow	VERB
app01-11101	63	4	us	we	PRON
app01-11101	63	5	to	to	PART
app01-11101	63	6	focus	focus	VERB
app01-11101	63	7	on	on	ADP
app01-11101	63	8	a	a	DET
app01-11101	63	9	comprehensive	comprehensive	ADJ
app01-11101	63	10	and	and	CCONJ
app01-11101	63	11	detailed	detailed	ADJ
app01-11101	63	12	investigation	investigation	NOUN
app01-11101	63	13	of	of	ADP
app01-11101	63	14	the	the	DET
app01-11101	63	15	problem	problem	NOUN
app01-11101	63	16	.	.	PUNCT
app01-11101	64	1	the	the	DET
app01-11101	64	2	governing	govern	VERB
app01-11101	64	3	equation	equation	NOUN
app01-11101	64	4	for	for	ADP
app01-11101	64	5	the	the	DET
app01-11101	64	6	stationary	stationary	ADJ
app01-11101	64	7	heat	heat	NOUN
app01-11101	64	8	problem	problem	NOUN
app01-11101	64	9	is	be	AUX
app01-11101	64	10	given	give	VERB
app01-11101	64	11	by	by	ADP
app01-11101	64	12	:	:	PUNCT
app01-11101	64	13			X
app01-11101	64	14	∇	∇	X
app01-11101	64	15	·	·	PUNCT
app01-11101	64	16	(	(	PUNCT
app01-11101	64	17	λ(x)∇θ(x	λ(x)∇θ(x	PROPN
app01-11101	64	18	)	)	PUNCT
app01-11101	64	19	)	)	PUNCT
app01-11101	65	1	=	=	SYM
app01-11101	65	2	0	0	NUM
app01-11101	65	3	,	,	PUNCT
app01-11101	65	4	x	x	X
app01-11101	65	5	∈	∈	PROPN
app01-11101	65	6	d	d	PROPN
app01-11101	65	7	,	,	PUNCT
app01-11101	65	8	θ(x	θ(x	PROPN
app01-11101	65	9	)	)	PUNCT
app01-11101	65	10	=	=	PUNCT
app01-11101	65	11	θd(x	θd(x	X
app01-11101	65	12	)	)	PUNCT
app01-11101	65	13	,	,	PUNCT
app01-11101	65	14	x	x	PUNCT
app01-11101	65	15	∈	∈	PROPN
app01-11101	65	16	γd	γd	ADP
app01-11101	65	17	,	,	PUNCT
app01-11101	65	18	λ(x	λ(x	PROPN
app01-11101	65	19	)	)	PUNCT
app01-11101	66	1	∂θ	∂θ	PROPN
app01-11101	66	2	∂n	∂n	PROPN
app01-11101	66	3	(	(	PUNCT
app01-11101	66	4	x	x	X
app01-11101	66	5	)	)	PUNCT
app01-11101	66	6	=	=	SYM
app01-11101	66	7	qn	qn	INTJ
app01-11101	66	8	(	(	PUNCT
app01-11101	66	9	x	x	NOUN
app01-11101	66	10	)	)	PUNCT
app01-11101	66	11	,	,	PUNCT
app01-11101	66	12	x	x	PUNCT
app01-11101	66	13	∈	∈	NOUN
app01-11101	66	14	γn	γn	NOUN
app01-11101	66	15	,	,	PUNCT
app01-11101	66	16	α(θ(x	α(θ(x	PROPN
app01-11101	66	17	)	)	PUNCT
app01-11101	66	18	−	−	PROPN
app01-11101	66	19	θ∞(x	θ∞(x	NOUN
app01-11101	66	20	)	)	PUNCT
app01-11101	66	21	)	)	PUNCT
app01-11101	67	1	=	=	SYM
app01-11101	67	2	λ(x	λ(x	X
app01-11101	67	3	)	)	PUNCT
app01-11101	68	1	∂θ	∂θ	PROPN
app01-11101	68	2	∂n	∂n	PROPN
app01-11101	68	3	(	(	PUNCT
app01-11101	68	4	x	x	NOUN
app01-11101	68	5	)	)	PUNCT
app01-11101	68	6	,	,	PUNCT
app01-11101	68	7	x	x	PUNCT
app01-11101	68	8	∈	∈	PROPN
app01-11101	68	9	γr	γr	PROPN
app01-11101	68	10	.	.	PUNCT
app01-11101	68	11	(	(	PUNCT
app01-11101	68	12	3	3	X
app01-11101	68	13	)	)	PUNCT
app01-11101	68	14	the	the	DET
app01-11101	68	15	finite	finite	PROPN
app01-11101	68	16	element	element	NOUN
app01-11101	68	17	method	method	NOUN
app01-11101	68	18	(	(	PUNCT
app01-11101	68	19	fem	fem	NOUN
app01-11101	68	20	)	)	PUNCT
app01-11101	68	21	is	be	AUX
app01-11101	68	22	a	a	DET
app01-11101	68	23	powerful	powerful	ADJ
app01-11101	68	24	numerical	numerical	ADJ
app01-11101	68	25	technique	technique	NOUN
app01-11101	68	26	used	use	VERB
app01-11101	68	27	to	to	PART
app01-11101	68	28	approximate	approximate	VERB
app01-11101	68	29	solutions	solution	NOUN
app01-11101	68	30	to	to	ADP
app01-11101	68	31	complex	complex	ADJ
app01-11101	68	32	partial	partial	ADJ
app01-11101	68	33	differential	differential	NOUN
app01-11101	68	34	equations	equation	NOUN
app01-11101	68	35	.	.	PUNCT
app01-11101	69	1	it	it	PRON
app01-11101	69	2	works	work	VERB
app01-11101	69	3	by	by	ADP
app01-11101	69	4	transforming	transform	VERB
app01-11101	69	5	continuous	continuous	ADJ
app01-11101	69	6	functions	function	NOUN
app01-11101	69	7	into	into	ADP
app01-11101	69	8	discrete	discrete	ADJ
app01-11101	69	9	vectors	vector	NOUN
app01-11101	69	10	,	,	PUNCT
app01-11101	69	11	making	make	VERB
app01-11101	69	12	them	they	PRON
app01-11101	69	13	easier	easy	ADJ
app01-11101	69	14	to	to	PART
app01-11101	69	15	handle	handle	VERB
app01-11101	69	16	with	with	ADP
app01-11101	69	17	numerical	numerical	ADJ
app01-11101	69	18	tools	tool	NOUN
app01-11101	69	19	.	.	PUNCT
app01-11101	70	1	one	one	NUM
app01-11101	70	2	of	of	ADP
app01-11101	70	3	the	the	DET
app01-11101	70	4	most	most	ADV
app01-11101	70	5	common	common	ADJ
app01-11101	70	6	fem	fem	NOUN
app01-11101	70	7	approaches	approach	NOUN
app01-11101	70	8	is	be	AUX
app01-11101	70	9	the	the	DET
app01-11101	70	10	galerkin	galerkin	ADJ
app01-11101	70	11	method	method	NOUN
app01-11101	70	12	,	,	PUNCT
app01-11101	70	13	which	which	PRON
app01-11101	70	14	we	we	PRON
app01-11101	70	15	use	use	VERB
app01-11101	70	16	in	in	ADP
app01-11101	70	17	this	this	DET
app01-11101	70	18	context	context	NOUN
app01-11101	70	19	to	to	PART
app01-11101	70	20	discretize	discretize	VERB
app01-11101	70	21	the	the	DET
app01-11101	70	22	stationary	stationary	ADJ
app01-11101	70	23	heat	heat	NOUN
app01-11101	70	24	conduction	conduction	NOUN
app01-11101	70	25	equation	equation	NOUN
app01-11101	70	26	,	,	PUNCT
app01-11101	70	27	see	see	VERB
app01-11101	70	28	[	[	X
app01-11101	70	29	18	18	NUM
app01-11101	70	30	]	]	PUNCT
app01-11101	70	31	.	.	PUNCT
app01-11101	71	1	the	the	DET
app01-11101	71	2	method	method	NOUN
app01-11101	71	3	’s	’s	PART
app01-11101	71	4	core	core	ADJ
app01-11101	71	5	idea	idea	NOUN
app01-11101	71	6	is	be	AUX
app01-11101	71	7	to	to	PART
app01-11101	71	8	minimize	minimize	VERB
app01-11101	71	9	the	the	DET
app01-11101	71	10	error	error	NOUN
app01-11101	71	11	between	between	ADP
app01-11101	71	12	the	the	DET
app01-11101	71	13	exact	exact	ADJ
app01-11101	71	14	and	and	CCONJ
app01-11101	71	15	approximate	approximate	ADJ
app01-11101	71	16	solutions	solution	NOUN
app01-11101	71	17	by	by	ADP
app01-11101	71	18	ensuring	ensure	VERB
app01-11101	71	19	the	the	DET
app01-11101	71	20	residual	residual	ADJ
app01-11101	71	21	–	–	PUNCT
app01-11101	71	22	the	the	DET
app01-11101	71	23	difference	difference	NOUN
app01-11101	71	24	between	between	ADP
app01-11101	71	25	them	they	PRON
app01-11101	71	26	–	–	PUNCT
app01-11101	71	27	is	be	AUX
app01-11101	71	28	orthogonal	orthogonal	ADJ
app01-11101	71	29	to	to	ADP
app01-11101	71	30	the	the	DET
app01-11101	71	31	chosen	choose	VERB
app01-11101	71	32	finite	finite	ADJ
app01-11101	71	33	-	-	ADJ
app01-11101	71	34	dimensional	dimensional	ADJ
app01-11101	71	35	space	space	NOUN
app01-11101	71	36	.	.	PUNCT
app01-11101	72	1	the	the	DET
app01-11101	72	2	galerkin	galerkin	PROPN
app01-11101	72	3	method	method	NOUN
app01-11101	72	4	’s	’s	PART
app01-11101	72	5	orthogonality	orthogonality	NOUN
app01-11101	72	6	condition	condition	NOUN
app01-11101	72	7	for	for	ADP
app01-11101	72	8	the	the	DET
app01-11101	72	9	residual	residual	ADJ
app01-11101	72	10	guarantees	guarantee	NOUN
app01-11101	72	11	that	that	SCONJ
app01-11101	72	12	the	the	DET
app01-11101	72	13	approximation	approximation	NOUN
app01-11101	72	14	error	error	NOUN
app01-11101	72	15	is	be	AUX
app01-11101	72	16	minimized	minimize	VERB
app01-11101	72	17	,	,	PUNCT
app01-11101	72	18	yielding	yield	VERB
app01-11101	72	19	a	a	DET
app01-11101	72	20	mathematically	mathematically	ADV
app01-11101	72	21	consistent	consistent	ADJ
app01-11101	72	22	solution	solution	NOUN
app01-11101	72	23	,	,	PUNCT
app01-11101	72	24	see	see	VERB
app01-11101	72	25	[	[	X
app01-11101	72	26	19	19	NUM
app01-11101	72	27	]	]	PUNCT
app01-11101	72	28	.	.	PUNCT
app01-11101	73	1	2.1	2.1	NUM
app01-11101	73	2	.	.	PUNCT
app01-11101	74	1	dnn	dnn	PROPN
app01-11101	74	2	-	-	PUNCT
app01-11101	74	3	based	base	VERB
app01-11101	74	4	surrogate	surrogate	ADJ
app01-11101	74	5	models	model	NOUN
app01-11101	74	6	generally	generally	ADV
app01-11101	74	7	,	,	PUNCT
app01-11101	74	8	the	the	DET
app01-11101	74	9	process	process	NOUN
app01-11101	74	10	of	of	ADP
app01-11101	74	11	constructing	construct	VERB
app01-11101	74	12	a	a	DET
app01-11101	74	13	data	data	NOUN
app01-11101	74	14	-	-	PUNCT
app01-11101	74	15	driven	drive	VERB
app01-11101	74	16	surrogate	surrogate	ADJ
app01-11101	74	17	model	model	NOUN
app01-11101	74	18	involves	involve	VERB
app01-11101	74	19	several	several	ADJ
app01-11101	74	20	key	key	ADJ
app01-11101	74	21	steps	step	NOUN
app01-11101	74	22	.	.	PUNCT
app01-11101	75	1	initially	initially	ADV
app01-11101	75	2	,	,	PUNCT
app01-11101	75	3	a	a	DET
app01-11101	75	4	set	set	NOUN
app01-11101	75	5	of	of	ADP
app01-11101	75	6	design	design	NOUN
app01-11101	75	7	points	point	NOUN
app01-11101	75	8	is	be	AUX
app01-11101	75	9	sampled	sample	VERB
app01-11101	75	10	–	–	PUNCT
app01-11101	75	11	usually	usually	ADV
app01-11101	75	12	from	from	ADP
app01-11101	75	13	the	the	DET
app01-11101	75	14	multidimensional	multidimensional	ADJ
app01-11101	75	15	parameter	parameter	NOUN
app01-11101	75	16	space	space	NOUN
app01-11101	75	17	–	–	PUNCT
app01-11101	75	18	often	often	ADV
app01-11101	75	19	using	use	VERB
app01-11101	75	20	techniques	technique	NOUN
app01-11101	75	21	like	like	ADP
app01-11101	75	22	latin	latin	ADJ
app01-11101	75	23	hypercube	hypercube	NOUN
app01-11101	75	24	sampling	sample	VERB
app01-11101	75	25	or	or	CCONJ
app01-11101	75	26	sobol	sobol	NOUN
app01-11101	75	27	sequences	sequence	NOUN
app01-11101	75	28	to	to	PART
app01-11101	75	29	ensure	ensure	VERB
app01-11101	75	30	a	a	DET
app01-11101	75	31	representative	representative	ADJ
app01-11101	75	32	distribution	distribution	NOUN
app01-11101	75	33	.	.	PUNCT
app01-11101	76	1	this	this	DET
app01-11101	76	2	set	set	NOUN
app01-11101	76	3	of	of	ADP
app01-11101	76	4	design	design	NOUN
app01-11101	76	5	points	point	NOUN
app01-11101	76	6	is	be	AUX
app01-11101	76	7	then	then	ADV
app01-11101	76	8	evaluated	evaluate	VERB
app01-11101	76	9	using	use	VERB
app01-11101	76	10	the	the	DET
app01-11101	76	11	highfidelity	highfidelity	NOUN
app01-11101	76	12	fem	fem	NOUN
app01-11101	76	13	-	-	PUNCT
app01-11101	76	14	based	base	VERB
app01-11101	76	15	model	model	NOUN
app01-11101	76	16	to	to	PART
app01-11101	76	17	generate	generate	VERB
app01-11101	76	18	corresponding	corresponding	ADJ
app01-11101	76	19	output	output	NOUN
app01-11101	76	20	/	/	SYM
app01-11101	76	21	sampled	sample	VERB
app01-11101	76	22	data	datum	NOUN
app01-11101	76	23	.	.	PUNCT
app01-11101	77	1	the	the	DET
app01-11101	77	2	input	input	NOUN
app01-11101	77	3	-	-	PUNCT
app01-11101	77	4	output	output	NOUN
app01-11101	77	5	(	(	PUNCT
app01-11101	77	6	labelled	label	VERB
app01-11101	77	7	)	)	PUNCT
app01-11101	77	8	pairs	pair	NOUN
app01-11101	77	9	are	be	AUX
app01-11101	77	10	subsequently	subsequently	ADV
app01-11101	77	11	used	use	VERB
app01-11101	77	12	to	to	PART
app01-11101	77	13	train	train	VERB
app01-11101	77	14	the	the	DET
app01-11101	77	15	specific	specific	ADJ
app01-11101	77	16	type	type	NOUN
app01-11101	77	17	of	of	ADP
app01-11101	77	18	surrogate	surrogate	ADJ
app01-11101	77	19	model	model	NOUN
app01-11101	77	20	.	.	PUNCT
app01-11101	78	1	however	however	ADV
app01-11101	78	2	,	,	PUNCT
app01-11101	78	3	the	the	DET
app01-11101	78	4	generation	generation	NOUN
app01-11101	78	5	of	of	ADP
app01-11101	78	6	this	this	DET
app01-11101	78	7	synthetic	synthetic	NOUN
app01-11101	78	8	dataset	dataset	VERB
app01-11101	78	9	through	through	ADP
app01-11101	78	10	high	high	ADJ
app01-11101	78	11	-	-	PUNCT
app01-11101	78	12	fidelity	fidelity	NOUN
app01-11101	78	13	fem	fem	NOUN
app01-11101	78	14	simulations	simulation	NOUN
app01-11101	78	15	often	often	ADV
app01-11101	78	16	represents	represent	VERB
app01-11101	78	17	the	the	DET
app01-11101	78	18	most	most	ADV
app01-11101	78	19	computationally	computationally	ADV
app01-11101	78	20	expensive	expensive	ADJ
app01-11101	78	21	bottleneck	bottleneck	NOUN
app01-11101	78	22	in	in	ADP
app01-11101	78	23	the	the	DET
app01-11101	78	24	workflow	workflow	NOUN
app01-11101	78	25	,	,	PUNCT
app01-11101	78	26	and	and	CCONJ
app01-11101	78	27	the	the	DET
app01-11101	78	28	proper	proper	ADJ
app01-11101	78	29	size	size	NOUN
app01-11101	78	30	of	of	ADP
app01-11101	78	31	the	the	DET
app01-11101	78	32	dataset	dataset	NOUN
app01-11101	78	33	needs	need	VERB
app01-11101	78	34	to	to	PART
app01-11101	78	35	be	be	AUX
app01-11101	78	36	carefully	carefully	ADV
app01-11101	78	37	considered	consider	VERB
app01-11101	78	38	.	.	PUNCT
app01-11101	79	1	the	the	DET
app01-11101	79	2	surrogate	surrogate	ADJ
app01-11101	79	3	models	model	NOUN
app01-11101	79	4	proposed	propose	VERB
app01-11101	79	5	here	here	ADV
app01-11101	79	6	are	be	AUX
app01-11101	79	7	based	base	VERB
app01-11101	79	8	on	on	ADP
app01-11101	79	9	the	the	DET
app01-11101	79	10	cnn	cnn	PROPN
app01-11101	79	11	architecture	architecture	NOUN
app01-11101	79	12	,	,	PUNCT
app01-11101	79	13	with	with	ADP
app01-11101	79	14	the	the	DET
app01-11101	79	15	u	u	ADJ
app01-11101	79	16	-	-	ADJ
app01-11101	79	17	net	net	ADJ
app01-11101	79	18	architecture	architecture	NOUN
app01-11101	79	19	chosen	choose	VERB
app01-11101	79	20	as	as	ADP
app01-11101	79	21	the	the	DET
app01-11101	79	22	most	most	ADV
app01-11101	79	23	suitable	suitable	ADJ
app01-11101	79	24	option	option	NOUN
app01-11101	79	25	for	for	ADP
app01-11101	79	26	further	further	ADJ
app01-11101	79	27	development	development	NOUN
app01-11101	79	28	.	.	PUNCT
app01-11101	80	1	introduced	introduce	VERB
app01-11101	80	2	by	by	ADP
app01-11101	80	3	ronneberger	ronneberger	NOUN
app01-11101	80	4	et	et	PROPN
app01-11101	80	5	al	al	PROPN
app01-11101	80	6	.	.	PUNCT
app01-11101	81	1	[	[	X
app01-11101	81	2	17	17	NUM
app01-11101	81	3	]	]	PUNCT
app01-11101	81	4	,	,	PUNCT
app01-11101	81	5	the	the	DET
app01-11101	81	6	u	u	NOUN
app01-11101	81	7	-	-	ADJ
app01-11101	81	8	net	net	ADJ
app01-11101	81	9	builds	build	VERB
app01-11101	81	10	on	on	ADP
app01-11101	81	11	the	the	DET
app01-11101	81	12	fully	fully	ADV
app01-11101	81	13	convolutional	convolutional	ADJ
app01-11101	81	14	network	network	NOUN
app01-11101	81	15	framework	framework	NOUN
app01-11101	81	16	proposed	propose	VERB
app01-11101	81	17	by	by	ADP
app01-11101	81	18	long	long	ADV
app01-11101	81	19	et	et	PROPN
app01-11101	81	20	al	al	PROPN
app01-11101	81	21	.	.	PUNCT
app01-11101	82	1	[	[	X
app01-11101	82	2	20	20	NUM
app01-11101	82	3	]	]	PUNCT
app01-11101	82	4	.	.	PUNCT
app01-11101	83	1	its	its	PRON
app01-11101	83	2	innovation	innovation	NOUN
app01-11101	83	3	lies	lie	VERB
app01-11101	83	4	in	in	ADP
app01-11101	83	5	augmenting	augment	VERB
app01-11101	83	6	the	the	DET
app01-11101	83	7	standard	standard	ADJ
app01-11101	83	8	contracting	contracting	NOUN
app01-11101	83	9	network	network	NOUN
app01-11101	83	10	with	with	ADP
app01-11101	83	11	upsampling	upsample	VERB
app01-11101	83	12	layers	layer	NOUN
app01-11101	83	13	,	,	PUNCT
app01-11101	83	14	replacing	replace	VERB
app01-11101	83	15	pooling	pool	VERB
app01-11101	83	16	operations	operation	NOUN
app01-11101	83	17	to	to	PART
app01-11101	83	18	progressively	progressively	ADV
app01-11101	83	19	increase	increase	VERB
app01-11101	83	20	output	output	NOUN
app01-11101	83	21	resolution	resolution	NOUN
app01-11101	83	22	.	.	PUNCT
app01-11101	84	1	this	this	DET
app01-11101	84	2	design	design	NOUN
app01-11101	84	3	allows	allow	VERB
app01-11101	84	4	convolutional	convolutional	ADJ
app01-11101	84	5	layers	layer	NOUN
app01-11101	84	6	to	to	PART
app01-11101	84	7	produce	produce	VERB
app01-11101	84	8	precise	precise	ADJ
app01-11101	84	9	outputs	output	NOUN
app01-11101	84	10	by	by	ADP
app01-11101	84	11	leveraging	leverage	VERB
app01-11101	84	12	contextual	contextual	ADJ
app01-11101	84	13	information	information	NOUN
app01-11101	84	14	.	.	PUNCT
app01-11101	85	1	a	a	DET
app01-11101	85	2	key	key	ADJ
app01-11101	85	3	feature	feature	NOUN
app01-11101	85	4	is	be	AUX
app01-11101	85	5	the	the	DET
app01-11101	85	6	use	use	NOUN
app01-11101	85	7	of	of	ADP
app01-11101	85	8	extensive	extensive	ADJ
app01-11101	85	9	feature	feature	NOUN
app01-11101	85	10	channels	channel	NOUN
app01-11101	85	11	during	during	ADP
app01-11101	85	12	upsampling	upsample	VERB
app01-11101	85	13	,	,	PUNCT
app01-11101	85	14	which	which	PRON
app01-11101	85	15	ensures	ensure	VERB
app01-11101	85	16	effective	effective	ADJ
app01-11101	85	17	context	context	NOUN
app01-11101	85	18	propagation	propagation	NOUN
app01-11101	85	19	to	to	ADP
app01-11101	85	20	higher	high	ADJ
app01-11101	85	21	-	-	PUNCT
app01-11101	85	22	resolution	resolution	NOUN
app01-11101	85	23	layers	layer	NOUN
app01-11101	85	24	.	.	PUNCT
app01-11101	86	1	the	the	DET
app01-11101	86	2	resulting	result	VERB
app01-11101	86	3	architecture	architecture	NOUN
app01-11101	86	4	is	be	AUX
app01-11101	86	5	nearly	nearly	ADV
app01-11101	86	6	symmetrical	symmetrical	ADJ
app01-11101	86	7	,	,	PUNCT
app01-11101	86	8	forming	form	VERB
app01-11101	86	9	its	its	PRON
app01-11101	86	10	characteristic	characteristic	ADJ
app01-11101	86	11	“	"	PUNCT
app01-11101	86	12	u	u	NOUN
app01-11101	86	13	”	"	PUNCT
app01-11101	86	14	shape	shape	NOUN
app01-11101	86	15	.	.	PUNCT
app01-11101	87	1	the	the	DET
app01-11101	87	2	specific	specific	ADJ
app01-11101	87	3	implementation	implementation	NOUN
app01-11101	87	4	for	for	ADP
app01-11101	87	5	our	our	PRON
app01-11101	87	6	numerical	numerical	ADJ
app01-11101	87	7	example	example	NOUN
app01-11101	87	8	is	be	AUX
app01-11101	87	9	depicted	depict	VERB
app01-11101	87	10	in	in	ADP
app01-11101	87	11	figure	figure	NOUN
app01-11101	87	12	1	1	NUM
app01-11101	87	13	.	.	NOUN
app01-11101	87	14	80	80	NUM
app01-11101	87	15	vol	vol	NOUN
app01-11101	87	16	.	.	PUNCT
app01-11101	88	1	54/2025	54/2025	NUM
app01-11101	88	2	deep	deep	ADJ
app01-11101	88	3	learning	learning	NOUN
app01-11101	88	4	-	-	PUNCT
app01-11101	88	5	based	base	VERB
app01-11101	88	6	modeling	modeling	NOUN
app01-11101	88	7	and	and	CCONJ
app01-11101	88	8	simulation	simulation	NOUN
app01-11101	88	9	of	of	ADP
app01-11101	88	10	heat	heat	NOUN
app01-11101	88	11	conduction	conduction	NOUN
app01-11101	88	12	figure	figure	NOUN
app01-11101	88	13	1	1	NUM
app01-11101	88	14	.	.	PUNCT
app01-11101	89	1	this	this	DET
app01-11101	89	2	u	u	ADJ
app01-11101	89	3	-	-	ADJ
app01-11101	89	4	net	net	ADJ
app01-11101	89	5	diagram	diagram	NOUN
app01-11101	89	6	illustrates	illustrate	VERB
app01-11101	89	7	a	a	DET
app01-11101	89	8	convolutional	convolutional	ADJ
app01-11101	89	9	network	network	NOUN
app01-11101	89	10	that	that	PRON
app01-11101	89	11	downsamples	downsample	VERB
app01-11101	89	12	the	the	DET
app01-11101	89	13	input	input	NOUN
app01-11101	89	14	in	in	ADP
app01-11101	89	15	the	the	DET
app01-11101	89	16	encoder	encoder	NOUN
app01-11101	89	17	via	via	ADP
app01-11101	89	18	pooling	pooling	NOUN
app01-11101	89	19	and	and	CCONJ
app01-11101	89	20	convolutions	convolution	NOUN
app01-11101	89	21	,	,	PUNCT
app01-11101	89	22	then	then	ADV
app01-11101	89	23	upsamples	upsample	VERB
app01-11101	89	24	it	it	PRON
app01-11101	89	25	in	in	ADP
app01-11101	89	26	the	the	DET
app01-11101	89	27	decoder	decoder	NOUN
app01-11101	89	28	using	use	VERB
app01-11101	89	29	up	up	ADP
app01-11101	89	30	-	-	PUNCT
app01-11101	89	31	convolutions	convolution	NOUN
app01-11101	89	32	.	.	PUNCT
app01-11101	90	1	skip	skip	ADJ
app01-11101	90	2	connections	connection	NOUN
app01-11101	90	3	bridge	bridge	PROPN
app01-11101	90	4	corresponding	correspond	VERB
app01-11101	90	5	encoder	encoder	NOUN
app01-11101	90	6	and	and	CCONJ
app01-11101	90	7	decoder	decoder	NOUN
app01-11101	90	8	layers	layer	NOUN
app01-11101	90	9	,	,	PUNCT
app01-11101	90	10	preserving	preserve	VERB
app01-11101	90	11	spatial	spatial	ADJ
app01-11101	90	12	information	information	NOUN
app01-11101	90	13	lost	lose	VERB
app01-11101	90	14	during	during	ADP
app01-11101	90	15	downsampling	downsample	VERB
app01-11101	90	16	.	.	PUNCT
app01-11101	91	1	3	3	X
app01-11101	91	2	.	.	X
app01-11101	91	3	example	example	NOUN
app01-11101	91	4	we	we	PRON
app01-11101	91	5	investigate	investigate	VERB
app01-11101	91	6	a	a	DET
app01-11101	91	7	2d	2d	NUM
app01-11101	91	8	rectangular	rectangular	ADJ
app01-11101	91	9	domain	domain	NOUN
app01-11101	91	10	representing	represent	VERB
app01-11101	91	11	two	two	NUM
app01-11101	91	12	-	-	PUNCT
app01-11101	91	13	phase	phase	NOUN
app01-11101	91	14	heterogeneous	heterogeneous	ADJ
app01-11101	91	15	materials	material	NOUN
app01-11101	91	16	under	under	ADP
app01-11101	91	17	dirichlet	dirichlet	PROPN
app01-11101	91	18	boundary	boundary	ADJ
app01-11101	91	19	conditions	condition	NOUN
app01-11101	91	20	,	,	PUNCT
app01-11101	91	21	with	with	ADP
app01-11101	91	22	the	the	DET
app01-11101	91	23	left	left	ADJ
app01-11101	91	24	and	and	CCONJ
app01-11101	91	25	right	right	ADJ
app01-11101	91	26	boundaries	boundary	NOUN
app01-11101	91	27	held	hold	VERB
app01-11101	91	28	at	at	ADP
app01-11101	91	29	20	20	NUM
app01-11101	91	30	°	°	ADP
app01-11101	91	31	c	c	NOUN
app01-11101	91	32	and	and	CCONJ
app01-11101	91	33	5	5	NUM
app01-11101	91	34	°	°	NOUN
app01-11101	91	35	c	c	NOUN
app01-11101	91	36	,	,	PUNCT
app01-11101	91	37	respectively	respectively	ADV
app01-11101	91	38	.	.	PUNCT
app01-11101	92	1	the	the	DET
app01-11101	92	2	domain	domain	NOUN
app01-11101	92	3	is	be	AUX
app01-11101	92	4	meshed	mesh	VERB
app01-11101	92	5	into	into	ADP
app01-11101	92	6	quadrilateral	quadrilateral	ADJ
app01-11101	92	7	finite	finite	ADJ
app01-11101	92	8	elements	element	NOUN
app01-11101	92	9	,	,	PUNCT
app01-11101	92	10	where	where	SCONJ
app01-11101	92	11	each	each	DET
app01-11101	92	12	element	element	NOUN
app01-11101	92	13	corresponds	correspond	VERB
app01-11101	92	14	to	to	ADP
app01-11101	92	15	a	a	DET
app01-11101	92	16	pixel	pixel	NOUN
app01-11101	92	17	of	of	ADP
app01-11101	92	18	a	a	DET
app01-11101	92	19	specific	specific	ADJ
app01-11101	92	20	material	material	NOUN
app01-11101	92	21	phase	phase	NOUN
app01-11101	92	22	.	.	PUNCT
app01-11101	93	1	the	the	DET
app01-11101	93	2	domain	domain	NOUN
app01-11101	93	3	includes	include	VERB
app01-11101	93	4	two	two	NUM
app01-11101	93	5	material	material	NOUN
app01-11101	93	6	phases	phase	NOUN
app01-11101	93	7	with	with	ADP
app01-11101	93	8	thermal	thermal	ADJ
app01-11101	93	9	conductivities	conductivity	NOUN
app01-11101	93	10	of	of	ADP
app01-11101	93	11	λ1	λ1	PROPN
app01-11101	93	12	=	=	PUNCT
app01-11101	93	13	1.0	1.0	NUM
app01-11101	93	14	w	w	VERB
app01-11101	93	15	m−1	m−1	PROPN
app01-11101	93	16	k−1	k−1	PROPN
app01-11101	93	17	and	and	CCONJ
app01-11101	93	18	λ2	λ2	NOUN
app01-11101	93	19	=	=	PUNCT
app01-11101	93	20	5.0	5.0	NUM
app01-11101	93	21	w	w	VERB
app01-11101	93	22	m−1	m−1	PROPN
app01-11101	93	23	k−1	k−1	PROPN
app01-11101	93	24	.	.	PUNCT
app01-11101	94	1	heterogeneity	heterogeneity	PROPN
app01-11101	94	2	is	be	AUX
app01-11101	94	3	introduced	introduce	VERB
app01-11101	94	4	by	by	ADP
app01-11101	94	5	randomly	randomly	ADV
app01-11101	94	6	distributing	distribute	VERB
app01-11101	94	7	overlapping	overlap	VERB
app01-11101	94	8	λ1	λ1	ADJ
app01-11101	94	9	circles	circle	NOUN
app01-11101	94	10	within	within	ADP
app01-11101	94	11	the	the	DET
app01-11101	94	12	predominantly	predominantly	ADV
app01-11101	94	13	λ2	λ2	NOUN
app01-11101	94	14	domain	domain	NOUN
app01-11101	94	15	,	,	PUNCT
app01-11101	94	16	as	as	SCONJ
app01-11101	94	17	depicted	depict	VERB
app01-11101	94	18	in	in	ADP
app01-11101	94	19	figure	figure	NOUN
app01-11101	94	20	2	2	NUM
app01-11101	94	21	.	.	PUNCT
app01-11101	94	22	figure	figure	NOUN
app01-11101	94	23	2	2	NUM
app01-11101	94	24	.	.	PUNCT
app01-11101	94	25	one	one	NUM
app01-11101	94	26	particular	particular	ADJ
app01-11101	94	27	sample	sample	NOUN
app01-11101	94	28	from	from	ADP
app01-11101	94	29	fem	fem	NOUN
app01-11101	94	30	-	-	PUNCT
app01-11101	94	31	based	base	VERB
app01-11101	94	32	dataset	dataset	NOUN
app01-11101	94	33	depicting	depict	VERB
app01-11101	94	34	the	the	DET
app01-11101	94	35	morphology	morphology	NOUN
app01-11101	94	36	of	of	ADP
app01-11101	94	37	a	a	DET
app01-11101	94	38	heterogeneous	heterogeneous	ADJ
app01-11101	94	39	material	material	NOUN
app01-11101	94	40	.	.	PUNCT
app01-11101	95	1	a	a	DET
app01-11101	95	2	well	well	ADV
app01-11101	95	3	-	-	PUNCT
app01-11101	95	4	constructed	construct	VERB
app01-11101	95	5	synthetic	synthetic	ADJ
app01-11101	95	6	dataset	dataset	NOUN
app01-11101	95	7	is	be	AUX
app01-11101	95	8	vital	vital	ADJ
app01-11101	95	9	for	for	ADP
app01-11101	95	10	training	train	VERB
app01-11101	95	11	neural	neural	ADJ
app01-11101	95	12	networks	network	NOUN
app01-11101	95	13	effectively	effectively	ADV
app01-11101	95	14	,	,	PUNCT
app01-11101	95	15	ensuring	ensure	VERB
app01-11101	95	16	both	both	PRON
app01-11101	95	17	efficient	efficient	ADJ
app01-11101	95	18	learning	learning	NOUN
app01-11101	95	19	and	and	CCONJ
app01-11101	95	20	high	high	ADJ
app01-11101	95	21	performance	performance	NOUN
app01-11101	95	22	.	.	PUNCT
app01-11101	96	1	we	we	PRON
app01-11101	96	2	generated	generate	VERB
app01-11101	96	3	a	a	DET
app01-11101	96	4	dataset	dataset	NOUN
app01-11101	96	5	of	of	ADP
app01-11101	96	6	20	20	NUM
app01-11101	96	7	000	000	NUM
app01-11101	96	8	fem	fem	NOUN
app01-11101	96	9	simulations	simulation	NOUN
app01-11101	96	10	with	with	ADP
app01-11101	96	11	randomly	randomly	ADV
app01-11101	96	12	created	create	VERB
app01-11101	96	13	domain	domain	NOUN
app01-11101	96	14	morphologies	morphology	NOUN
app01-11101	96	15	to	to	PART
app01-11101	96	16	capture	capture	VERB
app01-11101	96	17	critical	critical	ADJ
app01-11101	96	18	features	feature	NOUN
app01-11101	96	19	.	.	PUNCT
app01-11101	97	1	given	give	VERB
app01-11101	97	2	the	the	DET
app01-11101	97	3	simplicity	simplicity	NOUN
app01-11101	97	4	of	of	ADP
app01-11101	97	5	the	the	DET
app01-11101	97	6	problem	problem	NOUN
app01-11101	97	7	,	,	PUNCT
app01-11101	97	8	managing	manage	VERB
app01-11101	97	9	this	this	DET
app01-11101	97	10	large	large	ADJ
app01-11101	97	11	number	number	NOUN
app01-11101	97	12	of	of	ADP
app01-11101	97	13	simulations	simulation	NOUN
app01-11101	97	14	was	be	AUX
app01-11101	97	15	straightforward	straightforward	ADJ
app01-11101	97	16	,	,	PUNCT
app01-11101	97	17	allowing	allow	VERB
app01-11101	97	18	the	the	DET
app01-11101	97	19	network	network	NOUN
app01-11101	97	20	to	to	PART
app01-11101	97	21	model	model	VERB
app01-11101	97	22	complex	complex	ADJ
app01-11101	97	23	relationships	relationship	NOUN
app01-11101	97	24	and	and	CCONJ
app01-11101	97	25	adapt	adapt	VERB
app01-11101	97	26	to	to	ADP
app01-11101	97	27	various	various	ADJ
app01-11101	97	28	material	material	NOUN
app01-11101	97	29	fields	field	NOUN
app01-11101	97	30	.	.	PUNCT
app01-11101	98	1	since	since	SCONJ
app01-11101	98	2	the	the	DET
app01-11101	98	3	data	data	NOUN
app01-11101	98	4	preprocessing	preprocessing	NOUN
app01-11101	98	5	is	be	AUX
app01-11101	98	6	almost	almost	ADV
app01-11101	98	7	the	the	DET
app01-11101	98	8	most	most	ADV
app01-11101	98	9	important	important	ADJ
app01-11101	98	10	part	part	NOUN
app01-11101	98	11	of	of	ADP
app01-11101	98	12	machine	machine	NOUN
app01-11101	98	13	learning	learning	NOUN
app01-11101	98	14	,	,	PUNCT
app01-11101	98	15	the	the	DET
app01-11101	98	16	fem	fem	NOUN
app01-11101	98	17	-	-	PUNCT
app01-11101	98	18	based	base	VERB
app01-11101	98	19	dataset	dataset	NOUN
app01-11101	98	20	is	be	AUX
app01-11101	98	21	further	far	ADV
app01-11101	98	22	normalized	normalize	VERB
app01-11101	98	23	to	to	ADP
app01-11101	98	24	temperatures	temperature	NOUN
app01-11101	98	25	varying	vary	VERB
app01-11101	98	26	between	between	ADP
app01-11101	98	27	0	0	NUM
app01-11101	98	28	°	°	NUM
app01-11101	98	29	c	c	NOUN
app01-11101	98	30	and	and	CCONJ
app01-11101	98	31	1	1	NUM
app01-11101	98	32	°	°	NOUN
app01-11101	98	33	c	c	NOUN
app01-11101	98	34	.	.	PUNCT
app01-11101	99	1	this	this	DET
app01-11101	99	2	normalization	normalization	NOUN
app01-11101	99	3	offers	offer	VERB
app01-11101	99	4	several	several	ADJ
app01-11101	99	5	advantages	advantage	NOUN
app01-11101	99	6	for	for	ADP
app01-11101	99	7	neural	neural	ADJ
app01-11101	99	8	networks	network	NOUN
app01-11101	99	9	:	:	PUNCT
app01-11101	99	10	it	it	PRON
app01-11101	99	11	accelerates	accelerate	VERB
app01-11101	99	12	learning	learn	VERB
app01-11101	99	13	for	for	ADP
app01-11101	99	14	gradient	gradient	NOUN
app01-11101	99	15	-	-	PUNCT
app01-11101	99	16	based	base	VERB
app01-11101	99	17	algorithms	algorithm	NOUN
app01-11101	99	18	,	,	PUNCT
app01-11101	99	19	helps	help	VERB
app01-11101	99	20	mitigate	mitigate	VERB
app01-11101	99	21	the	the	DET
app01-11101	99	22	issue	issue	NOUN
app01-11101	99	23	of	of	ADP
app01-11101	99	24	local	local	ADJ
app01-11101	99	25	minima	minima	NOUN
app01-11101	99	26	that	that	PRON
app01-11101	99	27	can	can	AUX
app01-11101	99	28	trap	trap	VERB
app01-11101	99	29	neural	neural	ADJ
app01-11101	99	30	networks	network	NOUN
app01-11101	99	31	during	during	ADP
app01-11101	99	32	optimization	optimization	NOUN
app01-11101	99	33	,	,	PUNCT
app01-11101	99	34	enhances	enhance	VERB
app01-11101	99	35	model	model	NOUN
app01-11101	99	36	performance	performance	NOUN
app01-11101	99	37	by	by	ADP
app01-11101	99	38	accommodating	accommodate	VERB
app01-11101	99	39	the	the	DET
app01-11101	99	40	scale	scale	NOUN
app01-11101	99	41	sensitivity	sensitivity	NOUN
app01-11101	99	42	of	of	ADP
app01-11101	99	43	activation	activation	NOUN
app01-11101	99	44	functions	function	NOUN
app01-11101	99	45	,	,	PUNCT
app01-11101	99	46	reduces	reduce	VERB
app01-11101	99	47	overfitting	overfitte	VERB
app01-11101	99	48	by	by	ADP
app01-11101	99	49	promoting	promote	VERB
app01-11101	99	50	better	well	ADJ
app01-11101	99	51	generalization	generalization	NOUN
app01-11101	99	52	and	and	CCONJ
app01-11101	99	53	lower	low	ADJ
app01-11101	99	54	sensitivity	sensitivity	NOUN
app01-11101	99	55	to	to	ADP
app01-11101	99	56	specific	specific	ADJ
app01-11101	99	57	input	input	NOUN
app01-11101	99	58	feature	feature	NOUN
app01-11101	99	59	values	value	NOUN
app01-11101	99	60	,	,	PUNCT
app01-11101	99	61	and	and	CCONJ
app01-11101	99	62	ensures	ensure	VERB
app01-11101	99	63	numerical	numerical	ADJ
app01-11101	99	64	stability	stability	NOUN
app01-11101	99	65	by	by	ADP
app01-11101	99	66	preventing	prevent	VERB
app01-11101	99	67	computational	computational	ADJ
app01-11101	99	68	issues	issue	NOUN
app01-11101	99	69	related	relate	VERB
app01-11101	99	70	to	to	ADP
app01-11101	99	71	extremely	extremely	ADV
app01-11101	99	72	large	large	ADJ
app01-11101	99	73	or	or	CCONJ
app01-11101	99	74	small	small	ADJ
app01-11101	99	75	numbers	number	NOUN
app01-11101	99	76	.	.	PUNCT
app01-11101	100	1	after	after	ADP
app01-11101	100	2	normalization	normalization	NOUN
app01-11101	100	3	,	,	PUNCT
app01-11101	100	4	the	the	DET
app01-11101	100	5	dataset	dataset	NOUN
app01-11101	100	6	is	be	AUX
app01-11101	100	7	divided	divide	VERB
app01-11101	100	8	into	into	ADP
app01-11101	100	9	training	training	NOUN
app01-11101	100	10	,	,	PUNCT
app01-11101	100	11	validation	validation	NOUN
app01-11101	100	12	,	,	PUNCT
app01-11101	100	13	and	and	CCONJ
app01-11101	100	14	testing	testing	NOUN
app01-11101	100	15	subsets	subset	NOUN
app01-11101	100	16	to	to	PART
app01-11101	100	17	ensure	ensure	VERB
app01-11101	100	18	the	the	DET
app01-11101	100	19	development	development	NOUN
app01-11101	100	20	of	of	ADP
app01-11101	100	21	a	a	DET
app01-11101	100	22	robust	robust	ADJ
app01-11101	100	23	and	and	CCONJ
app01-11101	100	24	generalizable	generalizable	ADJ
app01-11101	100	25	deep	deep	ADJ
app01-11101	100	26	learning	learning	NOUN
app01-11101	100	27	model	model	NOUN
app01-11101	100	28	.	.	PUNCT
app01-11101	101	1	this	this	DET
app01-11101	101	2	partitioning	partitioning	NOUN
app01-11101	101	3	is	be	AUX
app01-11101	101	4	essential	essential	ADJ
app01-11101	101	5	for	for	ADP
app01-11101	101	6	several	several	ADJ
app01-11101	101	7	reasons	reason	NOUN
app01-11101	101	8	:	:	PUNCT
app01-11101	101	9	it	it	PRON
app01-11101	101	10	enables	enable	VERB
app01-11101	101	11	an	an	DET
app01-11101	101	12	unbiased	unbiased	ADJ
app01-11101	101	13	assessment	assessment	NOUN
app01-11101	101	14	of	of	ADP
app01-11101	101	15	model	model	NOUN
app01-11101	101	16	performance	performance	NOUN
app01-11101	101	17	on	on	ADP
app01-11101	101	18	unseen	unseen	ADJ
app01-11101	101	19	data	datum	NOUN
app01-11101	101	20	(	(	PUNCT
app01-11101	101	21	testing	testing	NOUN
app01-11101	101	22	set	set	NOUN
app01-11101	101	23	)	)	PUNCT
app01-11101	101	24	,	,	PUNCT
app01-11101	101	25	helps	help	VERB
app01-11101	101	26	prevent	prevent	VERB
app01-11101	101	27	overfitting	overfitting	NOUN
app01-11101	101	28	by	by	ADP
app01-11101	101	29	monitoring	monitor	VERB
app01-11101	101	30	training	training	NOUN
app01-11101	101	31	progress	progress	NOUN
app01-11101	101	32	,	,	PUNCT
app01-11101	101	33	and	and	CCONJ
app01-11101	101	34	identifies	identify	VERB
app01-11101	101	35	if	if	SCONJ
app01-11101	101	36	the	the	DET
app01-11101	101	37	model	model	NOUN
app01-11101	101	38	is	be	AUX
app01-11101	101	39	memorizing	memorize	VERB
app01-11101	101	40	noise	noise	NOUN
app01-11101	101	41	or	or	CCONJ
app01-11101	101	42	outliers	outlier	NOUN
app01-11101	101	43	.	.	PUNCT
app01-11101	102	1	in	in	ADP
app01-11101	102	2	addition	addition	NOUN
app01-11101	102	3	,	,	PUNCT
app01-11101	102	4	the	the	DET
app01-11101	102	5	validation	validation	NOUN
app01-11101	102	6	set	set	NOUN
app01-11101	102	7	is	be	AUX
app01-11101	102	8	critical	critical	ADJ
app01-11101	102	9	for	for	ADP
app01-11101	102	10	optimizing	optimize	VERB
app01-11101	102	11	hyperparameters	hyperparameter	NOUN
app01-11101	102	12	–	–	PUNCT
app01-11101	102	13	such	such	ADJ
app01-11101	102	14	as	as	ADP
app01-11101	102	15	learning	learn	VERB
app01-11101	102	16	rate	rate	NOUN
app01-11101	102	17	,	,	PUNCT
app01-11101	102	18	batch	batch	NOUN
app01-11101	102	19	size	size	NOUN
app01-11101	102	20	,	,	PUNCT
app01-11101	102	21	or	or	CCONJ
app01-11101	102	22	network	network	NOUN
app01-11101	102	23	architecture	architecture	NOUN
app01-11101	102	24	–	–	PUNCT
app01-11101	102	25	and	and	CCONJ
app01-11101	102	26	for	for	ADP
app01-11101	102	27	comparing	compare	VERB
app01-11101	102	28	different	different	ADJ
app01-11101	102	29	models	model	NOUN
app01-11101	102	30	or	or	CCONJ
app01-11101	102	31	algorithms	algorithm	NOUN
app01-11101	102	32	.	.	PUNCT
app01-11101	103	1	for	for	ADP
app01-11101	103	2	these	these	DET
app01-11101	103	3	reasons	reason	NOUN
app01-11101	103	4	,	,	PUNCT
app01-11101	103	5	our	our	PRON
app01-11101	103	6	dataset	dataset	NOUN
app01-11101	103	7	is	be	AUX
app01-11101	103	8	split	split	VERB
app01-11101	103	9	into	into	ADP
app01-11101	103	10	three	three	NUM
app01-11101	103	11	distinct	distinct	ADJ
app01-11101	103	12	parts	part	NOUN
app01-11101	103	13	:	:	PUNCT
app01-11101	103	14	15	15	NUM
app01-11101	103	15	000	000	NUM
app01-11101	103	16	samples	sample	NOUN
app01-11101	103	17	for	for	ADP
app01-11101	103	18	training	training	NOUN
app01-11101	103	19	,	,	PUNCT
app01-11101	103	20	2	2	NUM
app01-11101	103	21	500	500	NUM
app01-11101	103	22	for	for	ADP
app01-11101	103	23	validation	validation	NOUN
app01-11101	103	24	,	,	PUNCT
app01-11101	103	25	and	and	CCONJ
app01-11101	103	26	2	2	NUM
app01-11101	103	27	500	500	NUM
app01-11101	103	28	for	for	ADP
app01-11101	103	29	testing	testing	NOUN
app01-11101	103	30	.	.	PUNCT
app01-11101	104	1	during	during	ADP
app01-11101	104	2	the	the	DET
app01-11101	104	3	training	training	NOUN
app01-11101	104	4	process	process	NOUN
app01-11101	104	5	,	,	PUNCT
app01-11101	104	6	the	the	DET
app01-11101	104	7	unknown	unknown	ADJ
app01-11101	104	8	parameters	parameter	NOUN
app01-11101	104	9	of	of	ADP
app01-11101	104	10	the	the	DET
app01-11101	104	11	dnn	dnn	PROPN
app01-11101	104	12	-	-	PUNCT
app01-11101	104	13	based	base	VERB
app01-11101	104	14	surrogate	surrogate	ADJ
app01-11101	104	15	model	model	NOUN
app01-11101	104	16	are	be	AUX
app01-11101	104	17	determined	determine	VERB
app01-11101	104	18	using	use	VERB
app01-11101	104	19	an	an	DET
app01-11101	104	20	optimization	optimization	NOUN
app01-11101	104	21	solver	solver	NOUN
app01-11101	104	22	based	base	VERB
app01-11101	104	23	on	on	ADP
app01-11101	104	24	the	the	DET
app01-11101	104	25	training	training	NOUN
app01-11101	104	26	dataset	dataset	NOUN
app01-11101	104	27	.	.	PUNCT
app01-11101	105	1	simultaneously	simultaneously	ADV
app01-11101	105	2	,	,	PUNCT
app01-11101	105	3	the	the	DET
app01-11101	105	4	loss	loss	NOUN
app01-11101	105	5	is	be	AUX
app01-11101	105	6	evaluated	evaluate	VERB
app01-11101	105	7	on	on	ADP
app01-11101	105	8	the	the	DET
app01-11101	105	9	validation	validation	NOUN
app01-11101	105	10	dataset	dataset	NOUN
app01-11101	105	11	to	to	PART
app01-11101	105	12	monitor	monitor	VERB
app01-11101	105	13	overfitting	overfitte	VERB
app01-11101	105	14	and	and	CCONJ
app01-11101	105	15	underfitting	underfitte	VERB
app01-11101	105	16	issues	issue	NOUN
app01-11101	105	17	and	and	CCONJ
app01-11101	105	18	to	to	PART
app01-11101	105	19	estimate	estimate	VERB
app01-11101	105	20	the	the	DET
app01-11101	105	21	appropriate	appropriate	ADJ
app01-11101	105	22	number	number	NOUN
app01-11101	105	23	of	of	ADP
app01-11101	105	24	training	training	NOUN
app01-11101	105	25	epochs	epoch	NOUN
app01-11101	105	26	.	.	PUNCT
app01-11101	106	1	the	the	DET
app01-11101	106	2	loss	loss	NOUN
app01-11101	106	3	values	value	NOUN
app01-11101	106	4	for	for	ADP
app01-11101	106	5	both	both	CCONJ
app01-11101	106	6	the	the	DET
app01-11101	106	7	training	training	NOUN
app01-11101	106	8	and	and	CCONJ
app01-11101	106	9	validation	validation	NOUN
app01-11101	106	10	datasets	dataset	NOUN
app01-11101	106	11	in	in	ADP
app01-11101	106	12	our	our	PRON
app01-11101	106	13	specific	specific	ADJ
app01-11101	106	14	example	example	NOUN
app01-11101	106	15	are	be	AUX
app01-11101	106	16	illustrated	illustrate	VERB
app01-11101	106	17	in	in	ADP
app01-11101	106	18	figure	figure	NOUN
app01-11101	106	19	3	3	NUM
app01-11101	106	20	.	.	PUNCT
app01-11101	107	1	the	the	DET
app01-11101	107	2	close	close	ADJ
app01-11101	107	3	alignment	alignment	NOUN
app01-11101	107	4	between	between	ADP
app01-11101	107	5	the	the	DET
app01-11101	107	6	two	two	NUM
app01-11101	107	7	curves	curve	NOUN
app01-11101	107	8	suggests	suggest	VERB
app01-11101	107	9	that	that	SCONJ
app01-11101	107	10	the	the	DET
app01-11101	107	11	model	model	NOUN
app01-11101	107	12	is	be	AUX
app01-11101	107	13	neither	neither	CCONJ
app01-11101	107	14	underfitting	underfitte	VERB
app01-11101	107	15	nor	nor	CCONJ
app01-11101	107	16	overfitting	overfitte	VERB
app01-11101	107	17	,	,	PUNCT
app01-11101	107	18	achieving	achieve	VERB
app01-11101	107	19	a	a	DET
app01-11101	107	20	stable	stable	ADJ
app01-11101	107	21	and	and	CCONJ
app01-11101	107	22	reliable	reliable	ADJ
app01-11101	107	23	81	81	NUM
app01-11101	107	24	ondřej	ondřej	NOUN
app01-11101	107	25	šperl	šperl	NOUN
app01-11101	107	26	,	,	PUNCT
app01-11101	107	27	jan	jan	PROPN
app01-11101	107	28	sýkora	sýkora	PROPN
app01-11101	107	29	acta	acta	PROPN
app01-11101	107	30	polytechnica	polytechnica	PROPN
app01-11101	107	31	ctu	ctu	PROPN
app01-11101	107	32	proceedings	proceeding	NOUN
app01-11101	107	33	figure	figure	VERB
app01-11101	107	34	3	3	NUM
app01-11101	107	35	.	.	PUNCT
app01-11101	107	36	convergence	convergence	NOUN
app01-11101	107	37	graph	graph	NOUN
app01-11101	107	38	.	.	PUNCT
app01-11101	108	1	performance	performance	NOUN
app01-11101	108	2	by	by	ADP
app01-11101	108	3	the	the	DET
app01-11101	108	4	end	end	NOUN
app01-11101	108	5	of	of	ADP
app01-11101	108	6	the	the	DET
app01-11101	108	7	training	training	NOUN
app01-11101	108	8	.	.	PUNCT
app01-11101	109	1	the	the	DET
app01-11101	109	2	presented	present	VERB
app01-11101	109	3	graph	graph	NOUN
app01-11101	109	4	indicates	indicate	VERB
app01-11101	109	5	that	that	SCONJ
app01-11101	109	6	achieving	achieve	VERB
app01-11101	109	7	a	a	DET
app01-11101	109	8	relatively	relatively	ADV
app01-11101	109	9	well	well	ADV
app01-11101	109	10	-	-	PUNCT
app01-11101	109	11	trained	train	VERB
app01-11101	109	12	model	model	NOUN
app01-11101	109	13	requires	require	VERB
app01-11101	109	14	an	an	DET
app01-11101	109	15	epoch	epoch	NOUN
app01-11101	109	16	count	count	NOUN
app01-11101	109	17	exceeding	exceed	VERB
app01-11101	109	18	10	10	NUM
app01-11101	109	19	.	.	PUNCT
app01-11101	110	1	once	once	ADV
app01-11101	110	2	,	,	PUNCT
app01-11101	110	3	dnn	dnn	PROPN
app01-11101	110	4	-	-	PUNCT
app01-11101	110	5	based	base	VERB
app01-11101	110	6	surrogate	surrogate	ADJ
app01-11101	110	7	model	model	NOUN
app01-11101	110	8	is	be	AUX
app01-11101	110	9	trained	train	VERB
app01-11101	110	10	,	,	PUNCT
app01-11101	110	11	a	a	DET
app01-11101	110	12	qualitative	qualitative	ADJ
app01-11101	110	13	assessment	assessment	NOUN
app01-11101	110	14	can	can	AUX
app01-11101	110	15	be	be	AUX
app01-11101	110	16	conducted	conduct	VERB
app01-11101	110	17	using	use	VERB
app01-11101	110	18	unseen	unseen	ADJ
app01-11101	110	19	data	datum	NOUN
app01-11101	110	20	.	.	PUNCT
app01-11101	111	1	prior	prior	ADV
app01-11101	111	2	to	to	ADP
app01-11101	111	3	this	this	DET
app01-11101	111	4	assessment	assessment	NOUN
app01-11101	111	5	,	,	PUNCT
app01-11101	111	6	figure	figure	VERB
app01-11101	111	7	4	4	NUM
app01-11101	111	8	illustrates	illustrate	VERB
app01-11101	111	9	the	the	DET
app01-11101	111	10	temperature	temperature	NOUN
app01-11101	111	11	fields	field	NOUN
app01-11101	111	12	corresponding	correspond	VERB
app01-11101	111	13	to	to	ADP
app01-11101	111	14	a	a	DET
app01-11101	111	15	particular	particular	ADJ
app01-11101	111	16	thermal	thermal	ADJ
app01-11101	111	17	conductivity	conductivity	NOUN
app01-11101	111	18	field	field	NOUN
app01-11101	111	19	from	from	ADP
app01-11101	111	20	the	the	DET
app01-11101	111	21	unseen	unseen	ADJ
app01-11101	111	22	dataset	dataset	NOUN
app01-11101	111	23	.	.	PUNCT
app01-11101	112	1	figure	figure	NOUN
app01-11101	112	2	4a	4a	NOUN
app01-11101	112	3	presents	present	VERB
app01-11101	112	4	the	the	DET
app01-11101	112	5	ground	ground	NOUN
app01-11101	112	6	truth	truth	NOUN
app01-11101	112	7	temperature	temperature	NOUN
app01-11101	112	8	field	field	NOUN
app01-11101	112	9	obtained	obtain	VERB
app01-11101	112	10	through	through	ADP
app01-11101	112	11	the	the	DET
app01-11101	112	12	fem	fem	NOUN
app01-11101	112	13	simulation	simulation	NOUN
app01-11101	112	14	,	,	PUNCT
app01-11101	112	15	whereas	whereas	SCONJ
app01-11101	112	16	figure	figure	VERB
app01-11101	112	17	4b	4b	PROPN
app01-11101	112	18	displays	display	VERB
app01-11101	112	19	the	the	DET
app01-11101	112	20	temperature	temperature	NOUN
app01-11101	112	21	field	field	NOUN
app01-11101	112	22	predicted	predict	VERB
app01-11101	112	23	by	by	ADP
app01-11101	112	24	the	the	DET
app01-11101	112	25	dnn	dnn	PROPN
app01-11101	112	26	-	-	PUNCT
app01-11101	112	27	based	base	VERB
app01-11101	112	28	surrogate	surrogate	ADJ
app01-11101	112	29	model	model	NOUN
app01-11101	112	30	.	.	PUNCT
app01-11101	113	1	upon	upon	SCONJ
app01-11101	113	2	visual	visual	ADJ
app01-11101	113	3	comparison	comparison	NOUN
app01-11101	113	4	,	,	PUNCT
app01-11101	113	5	the	the	DET
app01-11101	113	6	two	two	NUM
app01-11101	113	7	results	result	NOUN
app01-11101	113	8	appear	appear	VERB
app01-11101	113	9	nearly	nearly	ADV
app01-11101	113	10	identical	identical	ADJ
app01-11101	113	11	.	.	PUNCT
app01-11101	114	1	however	however	ADV
app01-11101	114	2	,	,	PUNCT
app01-11101	114	3	when	when	SCONJ
app01-11101	114	4	the	the	DET
app01-11101	114	5	error	error	NOUN
app01-11101	114	6	values	value	NOUN
app01-11101	114	7	are	be	AUX
app01-11101	114	8	visualized	visualize	VERB
app01-11101	114	9	in	in	ADP
app01-11101	114	10	figure	figure	NOUN
app01-11101	114	11	4c	4c	NOUN
app01-11101	114	12	,	,	PUNCT
app01-11101	114	13	differences	difference	NOUN
app01-11101	114	14	ranging	range	VERB
app01-11101	114	15	from	from	ADP
app01-11101	114	16	−0.2	−0.2	PROPN
app01-11101	114	17	◦	◦	NOUN
app01-11101	114	18	c	c	NOUN
app01-11101	114	19	to	to	ADP
app01-11101	114	20	0.3	0.3	NUM
app01-11101	114	21	◦	◦	NOUN
app01-11101	114	22	c	c	NOUN
app01-11101	114	23	become	become	VERB
app01-11101	114	24	evident	evident	ADJ
app01-11101	114	25	.	.	PUNCT
app01-11101	115	1	the	the	DET
app01-11101	115	2	evaluation	evaluation	NOUN
app01-11101	115	3	across	across	ADP
app01-11101	115	4	the	the	DET
app01-11101	115	5	entire	entire	ADJ
app01-11101	115	6	unseen	unseen	ADJ
app01-11101	115	7	dataset	dataset	NOUN
app01-11101	115	8	is	be	AUX
app01-11101	115	9	presented	present	VERB
app01-11101	115	10	in	in	ADP
app01-11101	115	11	figure	figure	NOUN
app01-11101	115	12	5	5	NUM
app01-11101	115	13	,	,	PUNCT
app01-11101	115	14	which	which	PRON
app01-11101	115	15	displays	display	VERB
app01-11101	115	16	the	the	DET
app01-11101	115	17	mean	mean	NOUN
app01-11101	115	18	(	(	PUNCT
app01-11101	115	19	figure	figure	NOUN
app01-11101	115	20	5a	5a	NUM
app01-11101	115	21	)	)	PUNCT
app01-11101	115	22	,	,	PUNCT
app01-11101	115	23	standard	standard	ADJ
app01-11101	115	24	deviation	deviation	NOUN
app01-11101	115	25	(	(	PUNCT
app01-11101	115	26	figure	figure	NOUN
app01-11101	115	27	5b	5b	NUM
app01-11101	115	28	)	)	PUNCT
app01-11101	115	29	,	,	PUNCT
app01-11101	115	30	and	and	CCONJ
app01-11101	115	31	maximum	maximum	ADJ
app01-11101	115	32	value	value	NOUN
app01-11101	115	33	of	of	ADP
app01-11101	115	34	errors	error	NOUN
app01-11101	115	35	(	(	PUNCT
app01-11101	115	36	figure	figure	VERB
app01-11101	115	37	5c	5c	NUM
app01-11101	115	38	)	)	PUNCT
app01-11101	115	39	.	.	PUNCT
app01-11101	116	1	these	these	DET
app01-11101	116	2	graphs	graph	NOUN
app01-11101	116	3	are	be	AUX
app01-11101	116	4	derived	derive	VERB
app01-11101	116	5	from	from	ADP
app01-11101	116	6	the	the	DET
app01-11101	116	7	dataset	dataset	NOUN
app01-11101	116	8	comprising	comprise	VERB
app01-11101	116	9	the	the	DET
app01-11101	116	10	absolute	absolute	ADJ
app01-11101	116	11	temperature	temperature	NOUN
app01-11101	116	12	differences	difference	NOUN
app01-11101	116	13	between	between	ADP
app01-11101	116	14	the	the	DET
app01-11101	116	15	fembased	fembase	VERB
app01-11101	116	16	simulations	simulation	NOUN
app01-11101	116	17	and	and	CCONJ
app01-11101	116	18	the	the	DET
app01-11101	116	19	predictions	prediction	NOUN
app01-11101	116	20	generated	generate	VERB
app01-11101	116	21	by	by	ADP
app01-11101	116	22	the	the	DET
app01-11101	116	23	dnn	dnn	PROPN
app01-11101	116	24	-	-	PUNCT
app01-11101	116	25	based	base	VERB
app01-11101	116	26	surrogate	surrogate	ADJ
app01-11101	116	27	model	model	NOUN
app01-11101	116	28	.	.	PUNCT
app01-11101	117	1	the	the	DET
app01-11101	117	2	graph	graph	NOUN
app01-11101	117	3	of	of	ADP
app01-11101	117	4	average	average	ADJ
app01-11101	117	5	absolute	absolute	ADJ
app01-11101	117	6	error	error	NOUN
app01-11101	117	7	(	(	PUNCT
app01-11101	117	8	figure	figure	NOUN
app01-11101	117	9	5a	5a	NUM
app01-11101	117	10	)	)	PUNCT
app01-11101	117	11	demonstrates	demonstrate	VERB
app01-11101	117	12	that	that	SCONJ
app01-11101	117	13	the	the	DET
app01-11101	117	14	proposed	propose	VERB
app01-11101	117	15	dnn	dnn	PROPN
app01-11101	117	16	-	-	PUNCT
app01-11101	117	17	based	base	VERB
app01-11101	117	18	surrogate	surrogate	ADJ
app01-11101	117	19	model	model	NOUN
app01-11101	117	20	achieves	achieve	VERB
app01-11101	117	21	a	a	DET
app01-11101	117	22	relatively	relatively	ADV
app01-11101	117	23	high	high	ADJ
app01-11101	117	24	degree	degree	NOUN
app01-11101	117	25	of	of	ADP
app01-11101	117	26	accuracy	accuracy	NOUN
app01-11101	117	27	.	.	PUNCT
app01-11101	118	1	this	this	DET
app01-11101	118	2	observation	observation	NOUN
app01-11101	118	3	is	be	AUX
app01-11101	118	4	supported	support	VERB
app01-11101	118	5	by	by	ADP
app01-11101	118	6	the	the	DET
app01-11101	118	7	second	second	ADJ
app01-11101	118	8	graph	graph	NOUN
app01-11101	118	9	(	(	PUNCT
app01-11101	118	10	figure	figure	NOUN
app01-11101	118	11	5b	5b	NUM
app01-11101	118	12	)	)	PUNCT
app01-11101	118	13	,	,	PUNCT
app01-11101	118	14	which	which	PRON
app01-11101	118	15	illustrates	illustrate	VERB
app01-11101	118	16	the	the	DET
app01-11101	118	17	standard	standard	ADJ
app01-11101	118	18	deviation	deviation	NOUN
app01-11101	118	19	of	of	ADP
app01-11101	118	20	the	the	DET
app01-11101	118	21	absolute	absolute	ADJ
app01-11101	118	22	error	error	NOUN
app01-11101	118	23	and	and	CCONJ
app01-11101	118	24	shows	show	VERB
app01-11101	118	25	that	that	SCONJ
app01-11101	118	26	it	it	PRON
app01-11101	118	27	remains	remain	VERB
app01-11101	118	28	consistently	consistently	ADV
app01-11101	118	29	within	within	ADP
app01-11101	118	30	similar	similar	ADJ
app01-11101	118	31	bounds	bound	NOUN
app01-11101	118	32	.	.	PUNCT
app01-11101	119	1	4	4	X
app01-11101	119	2	.	.	X
app01-11101	119	3	conclusion	conclusion	NOUN
app01-11101	119	4	this	this	DET
app01-11101	119	5	study	study	NOUN
app01-11101	119	6	demonstrates	demonstrate	VERB
app01-11101	119	7	the	the	DET
app01-11101	119	8	efficiency	efficiency	NOUN
app01-11101	119	9	of	of	ADP
app01-11101	119	10	a	a	DET
app01-11101	119	11	dnnbased	dnnbase	VERB
app01-11101	119	12	surrogate	surrogate	ADJ
app01-11101	119	13	model	model	NOUN
app01-11101	119	14	in	in	ADP
app01-11101	119	15	predicting	predict	VERB
app01-11101	119	16	stationary	stationary	ADJ
app01-11101	119	17	temperature	temperature	NOUN
app01-11101	119	18	fields	field	NOUN
app01-11101	119	19	within	within	ADP
app01-11101	119	20	a	a	DET
app01-11101	119	21	heterogeneous	heterogeneous	ADJ
app01-11101	119	22	2d	2d	NUM
app01-11101	119	23	rectangular	rectangular	ADJ
app01-11101	119	24	domain	domain	NOUN
app01-11101	119	25	subjected	subject	VERB
app01-11101	119	26	to	to	ADP
app01-11101	119	27	dirichlet	dirichlet	PROPN
app01-11101	119	28	boundary	boundary	ADJ
app01-11101	119	29	conditions	condition	NOUN
app01-11101	119	30	.	.	PUNCT
app01-11101	120	1	the	the	DET
app01-11101	120	2	model	model	NOUN
app01-11101	120	3	was	be	AUX
app01-11101	120	4	trained	train	VERB
app01-11101	120	5	using	use	VERB
app01-11101	120	6	an	an	DET
app01-11101	120	7	extensive	extensive	ADJ
app01-11101	120	8	dataset	dataset	NOUN
app01-11101	120	9	of	of	ADP
app01-11101	120	10	15	15	NUM
app01-11101	120	11	000	000	NUM
app01-11101	120	12	fem	fem	NOUN
app01-11101	120	13	simulations	simulation	NOUN
app01-11101	120	14	,	,	PUNCT
app01-11101	120	15	with	with	ADP
app01-11101	120	16	careful	careful	ADJ
app01-11101	120	17	attention	attention	NOUN
app01-11101	120	18	paid	pay	VERB
app01-11101	120	19	(	(	PUNCT
app01-11101	120	20	a	a	NOUN
app01-11101	120	21	)	)	PUNCT
app01-11101	120	22	.	.	PUNCT
app01-11101	121	1	fem	fem	PROPN
app01-11101	121	2	-	-	PUNCT
app01-11101	121	3	based	base	VERB
app01-11101	121	4	temperature	temperature	NOUN
app01-11101	121	5	field	field	NOUN
app01-11101	121	6	.	.	PUNCT
app01-11101	122	1	(	(	PUNCT
app01-11101	122	2	b	b	NOUN
app01-11101	122	3	)	)	PUNCT
app01-11101	122	4	.	.	PUNCT
app01-11101	123	1	temperature	temperature	NOUN
app01-11101	123	2	field	field	NOUN
app01-11101	123	3	predicted	predict	VERB
app01-11101	123	4	from	from	ADP
app01-11101	123	5	the	the	DET
app01-11101	123	6	dnn	dnn	PROPN
app01-11101	123	7	-	-	PUNCT
app01-11101	123	8	based	base	VERB
app01-11101	123	9	surrogate	surrogate	ADJ
app01-11101	123	10	model	model	NOUN
app01-11101	123	11	.	.	PUNCT
app01-11101	124	1	(	(	PUNCT
app01-11101	124	2	c	c	NOUN
app01-11101	124	3	)	)	PUNCT
app01-11101	124	4	.	.	PUNCT
app01-11101	125	1	difference	difference	NOUN
app01-11101	125	2	between	between	ADP
app01-11101	125	3	fem	fem	NOUN
app01-11101	125	4	-	-	PUNCT
app01-11101	125	5	based	base	VERB
app01-11101	125	6	and	and	CCONJ
app01-11101	125	7	surrogate	surrogate	ADJ
app01-11101	125	8	modelbased	modelbase	VERB
app01-11101	125	9	temperature	temperature	NOUN
app01-11101	125	10	fields	field	NOUN
app01-11101	125	11	.	.	PUNCT
app01-11101	126	1	figure	figure	VERB
app01-11101	126	2	4	4	NUM
app01-11101	126	3	.	.	NOUN
app01-11101	126	4	comparison	comparison	NOUN
app01-11101	126	5	of	of	ADP
app01-11101	126	6	temperature	temperature	NOUN
app01-11101	126	7	fields	field	NOUN
app01-11101	126	8	computed	compute	VERB
app01-11101	126	9	for	for	ADP
app01-11101	126	10	one	one	NUM
app01-11101	126	11	specific	specific	ADJ
app01-11101	126	12	thermal	thermal	ADJ
app01-11101	126	13	field	field	NOUN
app01-11101	126	14	.	.	PUNCT
app01-11101	127	1	to	to	ADP
app01-11101	127	2	data	data	NOUN
app01-11101	127	3	preprocessing	preprocessing	NOUN
app01-11101	127	4	and	and	CCONJ
app01-11101	127	5	normalization	normalization	NOUN
app01-11101	127	6	to	to	PART
app01-11101	127	7	enhance	enhance	VERB
app01-11101	127	8	learning	learning	NOUN
app01-11101	127	9	and	and	CCONJ
app01-11101	127	10	generalization	generalization	NOUN
app01-11101	127	11	.	.	PUNCT
app01-11101	128	1	the	the	DET
app01-11101	128	2	evaluation	evaluation	NOUN
app01-11101	128	3	of	of	ADP
app01-11101	128	4	the	the	DET
app01-11101	128	5	model	model	NOUN
app01-11101	128	6	on	on	ADP
app01-11101	128	7	unseen	unseen	ADJ
app01-11101	128	8	data	datum	NOUN
app01-11101	128	9	revealed	reveal	VERB
app01-11101	128	10	a	a	DET
app01-11101	128	11	high	high	ADJ
app01-11101	128	12	degree	degree	NOUN
app01-11101	128	13	of	of	ADP
app01-11101	128	14	accuracy	accuracy	NOUN
app01-11101	128	15	,	,	PUNCT
app01-11101	128	16	with	with	ADP
app01-11101	128	17	average	average	ADJ
app01-11101	128	18	absolute	absolute	ADJ
app01-11101	128	19	errors	error	NOUN
app01-11101	128	20	remaining	remain	VERB
app01-11101	128	21	consistently	consistently	ADV
app01-11101	128	22	low	low	ADJ
app01-11101	128	23	and	and	CCONJ
app01-11101	128	24	standard	standard	ADJ
app01-11101	128	25	deviations	deviation	NOUN
app01-11101	128	26	within	within	ADP
app01-11101	128	27	acceptable	acceptable	ADJ
app01-11101	128	28	bounds	bound	NOUN
app01-11101	128	29	.	.	PUNCT
app01-11101	129	1	the	the	DET
app01-11101	129	2	successful	successful	ADJ
app01-11101	129	3	application	application	NOUN
app01-11101	129	4	of	of	ADP
app01-11101	129	5	dnn	dnn	PROPN
app01-11101	129	6	-	-	PUNCT
app01-11101	129	7	based	base	VERB
app01-11101	129	8	surrogate	surrogate	ADJ
app01-11101	129	9	model	model	NOUN
app01-11101	129	10	highlights	highlight	VERB
app01-11101	129	11	its	its	PRON
app01-11101	129	12	potential	potential	NOUN
app01-11101	129	13	for	for	ADP
app01-11101	129	14	efficient	efficient	ADJ
app01-11101	129	15	and	and	CCONJ
app01-11101	129	16	accurate	accurate	ADJ
app01-11101	129	17	prediction	prediction	NOUN
app01-11101	129	18	of	of	ADP
app01-11101	129	19	complex	complex	ADJ
app01-11101	129	20	physical	physical	ADJ
app01-11101	129	21	phenomena	phenomenon	NOUN
app01-11101	129	22	,	,	PUNCT
app01-11101	129	23	offering	offer	VERB
app01-11101	129	24	a	a	DET
app01-11101	129	25	promising	promising	ADJ
app01-11101	129	26	alternative	alternative	NOUN
app01-11101	129	27	to	to	ADP
app01-11101	129	28	computationally	computationally	ADV
app01-11101	129	29	intensive	intensive	ADJ
app01-11101	129	30	fem	fem	NOUN
app01-11101	129	31	simulations	simulation	NOUN
app01-11101	129	32	.	.	PUNCT
app01-11101	130	1	82	82	NUM
app01-11101	130	2	vol	vol	NOUN
app01-11101	130	3	.	.	PUNCT
app01-11101	131	1	54/2025	54/2025	NUM
app01-11101	131	2	deep	deep	ADJ
app01-11101	131	3	learning	learning	NOUN
app01-11101	131	4	-	-	PUNCT
app01-11101	131	5	based	base	VERB
app01-11101	131	6	modeling	modeling	NOUN
app01-11101	131	7	and	and	CCONJ
app01-11101	131	8	simulation	simulation	NOUN
app01-11101	131	9	of	of	ADP
app01-11101	131	10	heat	heat	NOUN
app01-11101	131	11	conduction	conduction	NOUN
app01-11101	131	12	(	(	PUNCT
app01-11101	131	13	a	a	NOUN
app01-11101	131	14	)	)	PUNCT
app01-11101	131	15	.	.	PUNCT
app01-11101	132	1	average	average	ADJ
app01-11101	132	2	absolute	absolute	ADJ
app01-11101	132	3	error	error	NOUN
app01-11101	132	4	of	of	ADP
app01-11101	132	5	temperature	temperature	NOUN
app01-11101	132	6	in	in	ADP
app01-11101	132	7	[	[	NOUN
app01-11101	132	8	°	°	ADP
app01-11101	132	9	c	c	NOUN
app01-11101	132	10	]	]	PUNCT
app01-11101	132	11	.	.	PUNCT
app01-11101	133	1	(	(	PUNCT
app01-11101	133	2	b	b	NOUN
app01-11101	133	3	)	)	PUNCT
app01-11101	133	4	.	.	PUNCT
app01-11101	134	1	standard	standard	ADJ
app01-11101	134	2	deviation	deviation	NOUN
app01-11101	134	3	of	of	ADP
app01-11101	134	4	the	the	DET
app01-11101	134	5	absolute	absolute	ADJ
app01-11101	134	6	error	error	NOUN
app01-11101	134	7	in	in	ADP
app01-11101	134	8	[	[	X
app01-11101	134	9	°	°	ADP
app01-11101	134	10	c	c	NOUN
app01-11101	134	11	]	]	PUNCT
app01-11101	134	12	.	.	PUNCT
app01-11101	135	1	(	(	PUNCT
app01-11101	135	2	c	c	NOUN
app01-11101	135	3	)	)	PUNCT
app01-11101	135	4	.	.	PUNCT
app01-11101	136	1	maximum	maximum	ADJ
app01-11101	136	2	value	value	NOUN
app01-11101	136	3	of	of	ADP
app01-11101	136	4	errors	error	NOUN
app01-11101	136	5	in	in	ADP
app01-11101	136	6	[	[	NOUN
app01-11101	136	7	°	°	ADP
app01-11101	136	8	c	c	NOUN
app01-11101	136	9	]	]	PUNCT
app01-11101	136	10	.	.	PUNCT
app01-11101	137	1	figure	figure	NOUN
app01-11101	137	2	5	5	NUM
app01-11101	137	3	.	.	PUNCT
app01-11101	137	4	qualitative	qualitative	ADJ
app01-11101	137	5	assessment	assessment	NOUN
app01-11101	137	6	of	of	ADP
app01-11101	137	7	dnn	dnn	PROPN
app01-11101	137	8	-	-	PUNCT
app01-11101	137	9	based	base	VERB
app01-11101	137	10	surrogate	surrogate	ADJ
app01-11101	137	11	model	model	NOUN
app01-11101	137	12	conducted	conduct	VERB
app01-11101	137	13	using	use	VERB
app01-11101	137	14	unseen	unseen	ADJ
app01-11101	137	15	dataset	dataset	NOUN
app01-11101	137	16	.	.	PUNCT
app01-11101	138	1	acknowledgements	acknowledgement	NOUN
app01-11101	138	2	the	the	DET
app01-11101	138	3	authors	author	NOUN
app01-11101	138	4	are	be	AUX
app01-11101	138	5	thankful	thankful	ADJ
app01-11101	138	6	for	for	ADP
app01-11101	138	7	financial	financial	ADJ
app01-11101	138	8	support	support	NOUN
app01-11101	138	9	from	from	ADP
app01-11101	138	10	the	the	DET
app01-11101	138	11	student	student	NOUN
app01-11101	138	12	grant	grant	NOUN
app01-11101	138	13	competition	competition	NOUN
app01-11101	138	14	of	of	ADP
app01-11101	138	15	ctu	ctu	NOUN
app01-11101	138	16	,	,	PUNCT
app01-11101	138	17	project	project	NOUN
app01-11101	138	18	no	no	NOUN
app01-11101	138	19	.	.	PUNCT
app01-11101	139	1	sgs23/152	sgs23/152	PROPN
app01-11101	139	2	/	/	SYM
app01-11101	140	1	ohk1/3t/11	ohk1/3t/11	PROPN
app01-11101	140	2	and	and	CCONJ
app01-11101	140	3	the	the	DET
app01-11101	140	4	czech	czech	PROPN
app01-11101	140	5	science	science	PROPN
app01-11101	140	6	foundation	foundation	PROPN
app01-11101	140	7	,	,	PUNCT
app01-11101	140	8	project	project	VERB
app01-11101	140	9	no	no	NOUN
app01-11101	140	10	.	.	NOUN
app01-11101	141	1	22	22	NUM
app01-11101	141	2	-	-	PUNCT
app01-11101	141	3	35755k	35755k	NUM
app01-11101	141	4	.	.	PUNCT
app01-11101	142	1	references	reference	NOUN
app01-11101	142	2	[	[	X
app01-11101	142	3	1	1	NUM
app01-11101	142	4	]	]	X
app01-11101	142	5	b.	b.	PROPN
app01-11101	142	6	sudret	sudret	PROPN
app01-11101	142	7	,	,	PUNCT
app01-11101	142	8	s.	s.	PROPN
app01-11101	142	9	marelli	marelli	PROPN
app01-11101	142	10	,	,	PUNCT
app01-11101	142	11	j.	j.	PROPN
app01-11101	142	12	wiart	wiart	PROPN
app01-11101	142	13	.	.	PUNCT
app01-11101	143	1	surrogate	surrogate	ADJ
app01-11101	143	2	models	model	NOUN
app01-11101	143	3	for	for	ADP
app01-11101	143	4	uncertainty	uncertainty	NOUN
app01-11101	143	5	quantification	quantification	NOUN
app01-11101	143	6	:	:	PUNCT
app01-11101	143	7	an	an	DET
app01-11101	143	8	overview	overview	NOUN
app01-11101	143	9	.	.	PUNCT
app01-11101	144	1	in	in	ADP
app01-11101	144	2	2017	2017	NUM
app01-11101	144	3	11th	11th	ADJ
app01-11101	144	4	european	european	ADJ
app01-11101	144	5	conference	conference	NOUN
app01-11101	144	6	on	on	ADP
app01-11101	144	7	antennas	antenna	NOUN
app01-11101	144	8	and	and	CCONJ
app01-11101	144	9	propagation	propagation	NOUN
app01-11101	144	10	(	(	PUNCT
app01-11101	144	11	eucap	eucap	NOUN
app01-11101	144	12	)	)	PUNCT
app01-11101	144	13	,	,	PUNCT
app01-11101	144	14	pp	pp	ADP
app01-11101	144	15	.	.	PUNCT
app01-11101	145	1	793–797	793–797	NUM
app01-11101	145	2	.	.	PUNCT
app01-11101	145	3	ieee	ieee	PROPN
app01-11101	145	4	,	,	PUNCT
app01-11101	145	5	2017	2017	NUM
app01-11101	145	6	.	.	PUNCT
app01-11101	146	1	https://doi.org/10.23919/eucap.2017.7928679	https://doi.org/10.23919/eucap.2017.7928679	PROPN
app01-11101	147	1	[	[	X
app01-11101	147	2	2	2	NUM
app01-11101	147	3	]	]	PUNCT
app01-11101	147	4	a.	a.	NOUN
app01-11101	147	5	prabhakar	prabhakar	PROPN
app01-11101	147	6	,	,	PUNCT
app01-11101	147	7	j.	j.	PROPN
app01-11101	147	8	fisher	fisher	PROPN
app01-11101	147	9	,	,	PUNCT
app01-11101	147	10	r.	r.	PROPN
app01-11101	147	11	bhattacharya	bhattacharya	PROPN
app01-11101	147	12	.	.	PUNCT
app01-11101	148	1	polynomial	polynomial	ADJ
app01-11101	148	2	chaos	chaos	NOUN
app01-11101	148	3	-	-	PUNCT
app01-11101	148	4	based	base	VERB
app01-11101	148	5	analysis	analysis	NOUN
app01-11101	148	6	of	of	ADP
app01-11101	148	7	probabilistic	probabilistic	ADJ
app01-11101	148	8	uncertainty	uncertainty	NOUN
app01-11101	148	9	in	in	ADP
app01-11101	148	10	hypersonic	hypersonic	ADJ
app01-11101	148	11	flight	flight	NOUN
app01-11101	148	12	dynamics	dynamic	NOUN
app01-11101	148	13	.	.	PUNCT
app01-11101	149	1	journal	journal	PROPN
app01-11101	149	2	of	of	ADP
app01-11101	149	3	guidance	guidance	NOUN
app01-11101	149	4	,	,	PUNCT
app01-11101	149	5	control	control	NOUN
app01-11101	149	6	,	,	PUNCT
app01-11101	149	7	and	and	CCONJ
app01-11101	149	8	dynamics	dynamic	NOUN
app01-11101	149	9	33(1):222–234	33(1):222–234	NUM
app01-11101	149	10	,	,	PUNCT
app01-11101	149	11	2010	2010	NUM
app01-11101	149	12	.	.	PUNCT
app01-11101	150	1	https://doi.org/10.2514/1.41551	https://doi.org/10.2514/1.41551	X
app01-11101	151	1	[	[	X
app01-11101	151	2	3	3	NUM
app01-11101	151	3	]	]	PUNCT
app01-11101	151	4	a.	a.	NOUN
app01-11101	151	5	kučerová	kučerová	PROPN
app01-11101	151	6	,	,	PUNCT
app01-11101	151	7	j.	j.	PROPN
app01-11101	151	8	sýkora	sýkora	PROPN
app01-11101	151	9	,	,	PUNCT
app01-11101	151	10	p.	p.	PROPN
app01-11101	151	11	havlásek	havlásek	PROPN
app01-11101	151	12	,	,	PUNCT
app01-11101	151	13	et	et	PROPN
app01-11101	152	1	al	al	PROPN
app01-11101	152	2	.	.	PROPN
app01-11101	152	3	efficient	efficient	PROPN
app01-11101	152	4	probabilistic	probabilistic	ADJ
app01-11101	152	5	multi	multi	ADJ
app01-11101	152	6	-	-	ADJ
app01-11101	152	7	fidelity	fidelity	ADJ
app01-11101	152	8	calibration	calibration	NOUN
app01-11101	152	9	of	of	ADP
app01-11101	152	10	a	a	DET
app01-11101	152	11	damageplastic	damageplastic	ADJ
app01-11101	152	12	model	model	NOUN
app01-11101	152	13	for	for	ADP
app01-11101	152	14	confined	confine	VERB
app01-11101	152	15	concrete	concrete	NOUN
app01-11101	152	16	.	.	PUNCT
app01-11101	153	1	computer	computer	NOUN
app01-11101	153	2	methods	method	NOUN
app01-11101	153	3	in	in	ADP
app01-11101	153	4	applied	applied	ADJ
app01-11101	153	5	mechanics	mechanic	NOUN
app01-11101	153	6	and	and	CCONJ
app01-11101	153	7	engineering	engineering	NOUN
app01-11101	153	8	412:116099	412:116099	NUM
app01-11101	153	9	,	,	PUNCT
app01-11101	153	10	2023	2023	NUM
app01-11101	153	11	.	.	PUNCT
app01-11101	154	1	https://doi.org/10.1016/j.cma.2023.116099	https://doi.org/10.1016/j.cma.2023.116099	PUNCT
app01-11101	154	2	[	[	X
app01-11101	154	3	4	4	X
app01-11101	154	4	]	]	X
app01-11101	154	5	y.	y.	NOUN
app01-11101	154	6	m.	m.	PROPN
app01-11101	154	7	marzouk	marzouk	PROPN
app01-11101	154	8	,	,	PUNCT
app01-11101	154	9	h.	h.	PROPN
app01-11101	154	10	n.	n.	PROPN
app01-11101	154	11	najm	najm	PROPN
app01-11101	154	12	.	.	PUNCT
app01-11101	155	1	dimensionality	dimensionality	NOUN
app01-11101	155	2	reduction	reduction	NOUN
app01-11101	155	3	and	and	CCONJ
app01-11101	155	4	polynomial	polynomial	ADJ
app01-11101	155	5	chaos	chaos	NOUN
app01-11101	155	6	acceleration	acceleration	NOUN
app01-11101	155	7	of	of	ADP
app01-11101	155	8	bayesian	bayesian	NOUN
app01-11101	155	9	inference	inference	NOUN
app01-11101	155	10	in	in	ADP
app01-11101	155	11	inverse	inverse	NOUN
app01-11101	155	12	problems	problem	NOUN
app01-11101	155	13	.	.	PUNCT
app01-11101	156	1	journal	journal	NOUN
app01-11101	156	2	of	of	ADP
app01-11101	156	3	computational	computational	ADJ
app01-11101	156	4	physics	physics	PROPN
app01-11101	156	5	228(6):1862–1902	228(6):1862–1902	PROPN
app01-11101	156	6	,	,	PUNCT
app01-11101	156	7	2009	2009	NUM
app01-11101	156	8	.	.	PUNCT
app01-11101	157	1	https://doi.org/10.1016/j.jcp.2008.11.024	https://doi.org/10.1016/j.jcp.2008.11.024	NOUN
app01-11101	157	2	[	[	X
app01-11101	157	3	5	5	NUM
app01-11101	157	4	]	]	PUNCT
app01-11101	157	5	k.	k.	PROPN
app01-11101	157	6	mcbride	mcbride	PROPN
app01-11101	157	7	,	,	PUNCT
app01-11101	157	8	k.	k.	PROPN
app01-11101	157	9	sundmacher	sundmacher	PROPN
app01-11101	157	10	.	.	PUNCT
app01-11101	158	1	overview	overview	NOUN
app01-11101	158	2	of	of	ADP
app01-11101	158	3	surrogate	surrogate	ADJ
app01-11101	158	4	modeling	modeling	NOUN
app01-11101	158	5	in	in	ADP
app01-11101	158	6	chemical	chemical	NOUN
app01-11101	158	7	process	process	NOUN
app01-11101	158	8	engineering	engineering	NOUN
app01-11101	158	9	.	.	PUNCT
app01-11101	159	1	chemie	chemie	PROPN
app01-11101	159	2	ingenieur	ingenieur	PROPN
app01-11101	159	3	technik	technik	PROPN
app01-11101	159	4	91(3):228–239	91(3):228–239	PROPN
app01-11101	159	5	,	,	PUNCT
app01-11101	159	6	2019	2019	NUM
app01-11101	159	7	.	.	PUNCT
app01-11101	160	1	https://doi.org/10.1002/cite.201800091	https://doi.org/10.1002/cite.201800091	NOUN
app01-11101	160	2	[	[	X
app01-11101	160	3	6	6	NUM
app01-11101	160	4	]	]	PUNCT
app01-11101	160	5	a.	a.	NOUN
app01-11101	160	6	i.	i.	PROPN
app01-11101	160	7	khuri	khuri	PROPN
app01-11101	160	8	,	,	PUNCT
app01-11101	160	9	s.	s.	PROPN
app01-11101	160	10	mukhopadhyay	mukhopadhyay	PROPN
app01-11101	160	11	.	.	PUNCT
app01-11101	161	1	response	response	NOUN
app01-11101	161	2	surface	surface	NOUN
app01-11101	161	3	methodology	methodology	NOUN
app01-11101	161	4	.	.	PUNCT
app01-11101	162	1	wiley	wiley	PROPN
app01-11101	162	2	interdisciplinary	interdisciplinary	ADJ
app01-11101	162	3	reviews	review	NOUN
app01-11101	162	4	:	:	PUNCT
app01-11101	162	5	computational	computational	ADJ
app01-11101	162	6	statistics	statistic	NOUN
app01-11101	162	7	2(2):128–149	2(2):128–149	NUM
app01-11101	162	8	,	,	PUNCT
app01-11101	162	9	2010	2010	NUM
app01-11101	162	10	.	.	PUNCT
app01-11101	162	11	https://doi.org/10.1002/wics.73	https://doi.org/10.1002/wics.73	PUNCT
app01-11101	163	1	[	[	X
app01-11101	163	2	7	7	X
app01-11101	163	3	]	]	PUNCT
app01-11101	163	4	m.	m.	NOUN
app01-11101	163	5	d.	d.	PROPN
app01-11101	163	6	buhmann	buhmann	PROPN
app01-11101	163	7	.	.	PUNCT
app01-11101	164	1	radial	radial	ADJ
app01-11101	164	2	basis	basis	NOUN
app01-11101	164	3	functions	function	NOUN
app01-11101	164	4	.	.	PUNCT
app01-11101	165	1	acta	acta	PROPN
app01-11101	165	2	numerica	numerica	PROPN
app01-11101	165	3	9:1–38	9:1–38	PROPN
app01-11101	165	4	,	,	PUNCT
app01-11101	165	5	2000	2000	NUM
app01-11101	165	6	.	.	PUNCT
app01-11101	166	1	https://doi.org/10.1017/s0962492900000015	https://doi.org/10.1017/s0962492900000015	NUM
app01-11101	167	1	[	[	NOUN
app01-11101	167	2	8	8	NUM
app01-11101	167	3	]	]	PUNCT
app01-11101	167	4	m.	m.	NOUN
app01-11101	167	5	a.	a.	PROPN
app01-11101	167	6	oliver	oliver	PROPN
app01-11101	167	7	,	,	PUNCT
app01-11101	167	8	r.	r.	PROPN
app01-11101	167	9	webster	webster	PROPN
app01-11101	167	10	.	.	PUNCT
app01-11101	168	1	kriging	krige	VERB
app01-11101	168	2	:	:	PUNCT
app01-11101	168	3	a	a	DET
app01-11101	168	4	method	method	NOUN
app01-11101	168	5	of	of	ADP
app01-11101	168	6	interpolation	interpolation	NOUN
app01-11101	168	7	for	for	ADP
app01-11101	168	8	geographical	geographical	ADJ
app01-11101	168	9	information	information	NOUN
app01-11101	168	10	systems	system	NOUN
app01-11101	168	11	.	.	PUNCT
app01-11101	169	1	international	international	ADJ
app01-11101	169	2	journal	journal	NOUN
app01-11101	169	3	of	of	ADP
app01-11101	169	4	geographical	geographical	ADJ
app01-11101	169	5	information	information	NOUN
app01-11101	169	6	system	system	NOUN
app01-11101	169	7	4(3):313–332	4(3):313–332	PROPN
app01-11101	169	8	,	,	PUNCT
app01-11101	169	9	1990	1990	NUM
app01-11101	169	10	.	.	PUNCT
app01-11101	170	1	https://doi.org/10.1080/02693799008941549	https://doi.org/10.1080/02693799008941549	PRON
app01-11101	171	1	[	[	X
app01-11101	171	2	9	9	NUM
app01-11101	171	3	]	]	PUNCT
app01-11101	171	4	j.	j.	PROPN
app01-11101	171	5	zou	zou	PROPN
app01-11101	171	6	,	,	PUNCT
app01-11101	171	7	y.	y.	PROPN
app01-11101	171	8	han	han	PROPN
app01-11101	171	9	,	,	PUNCT
app01-11101	171	10	s.-s	s.-	NOUN
app01-11101	171	11	.	.	PUNCT
app01-11101	172	1	so	so	ADV
app01-11101	172	2	.	.	PUNCT
app01-11101	173	1	overview	overview	NOUN
app01-11101	173	2	of	of	ADP
app01-11101	173	3	artificial	artificial	ADJ
app01-11101	173	4	neural	neural	ADJ
app01-11101	173	5	networks	network	NOUN
app01-11101	173	6	.	.	PUNCT
app01-11101	174	1	in	in	ADP
app01-11101	174	2	artificial	artificial	ADJ
app01-11101	174	3	neural	neural	ADJ
app01-11101	174	4	networks	network	NOUN
app01-11101	174	5	:	:	PUNCT
app01-11101	174	6	methods	method	NOUN
app01-11101	174	7	and	and	CCONJ
app01-11101	174	8	applications	application	NOUN
app01-11101	174	9	,	,	PUNCT
app01-11101	174	10	pp	pp	ADJ
app01-11101	174	11	.	.	PUNCT
app01-11101	175	1	14–22	14–22	NUM
app01-11101	175	2	.	.	PUNCT
app01-11101	176	1	humana	humana	PROPN
app01-11101	176	2	press	press	PROPN
app01-11101	176	3	,	,	PUNCT
app01-11101	176	4	2008	2008	NUM
app01-11101	176	5	.	.	PUNCT
app01-11101	177	1	https://doi.org/10.1007/978-1-60327-101-1_2	https://doi.org/10.1007/978-1-60327-101-1_2	X
app01-11101	178	1	[	[	X
app01-11101	178	2	10	10	NUM
app01-11101	178	3	]	]	PUNCT
app01-11101	178	4	m.	m.	NOUN
app01-11101	178	5	pecha	pecha	PROPN
app01-11101	178	6	,	,	PUNCT
app01-11101	178	7	d.	d.	PROPN
app01-11101	178	8	horák	horák	PROPN
app01-11101	178	9	.	.	PUNCT
app01-11101	179	1	analyzing	analyze	VERB
app01-11101	179	2	l1	l1	PROPN
app01-11101	179	3	-	-	PUNCT
app01-11101	179	4	loss	loss	NOUN
app01-11101	179	5	and	and	CCONJ
app01-11101	179	6	l2	l2	NOUN
app01-11101	179	7	-	-	PUNCT
app01-11101	179	8	loss	loss	NOUN
app01-11101	179	9	support	support	NOUN
app01-11101	179	10	vector	vector	NOUN
app01-11101	179	11	machines	machine	NOUN
app01-11101	179	12	implemented	implement	VERB
app01-11101	179	13	in	in	ADP
app01-11101	179	14	permon	permon	PROPN
app01-11101	179	15	toolbox	toolbox	NOUN
app01-11101	179	16	.	.	PUNCT
app01-11101	180	1	in	in	ADP
app01-11101	180	2	aeta	aeta	PROPN
app01-11101	180	3	2018	2018	NUM
app01-11101	180	4	-	-	PUNCT
app01-11101	180	5	recent	recent	ADJ
app01-11101	180	6	advances	advance	NOUN
app01-11101	180	7	in	in	ADP
app01-11101	180	8	electrical	electrical	ADJ
app01-11101	180	9	engineering	engineering	NOUN
app01-11101	180	10	and	and	CCONJ
app01-11101	180	11	related	related	ADJ
app01-11101	180	12	sciences	science	NOUN
app01-11101	180	13	:	:	PUNCT
app01-11101	180	14	theory	theory	NOUN
app01-11101	180	15	and	and	CCONJ
app01-11101	180	16	application	application	NOUN
app01-11101	180	17	,	,	PUNCT
app01-11101	180	18	pp	pp	ADJ
app01-11101	180	19	.	.	PUNCT
app01-11101	181	1	13–23	13–23	X
app01-11101	181	2	.	.	PUNCT
app01-11101	181	3	springer	springer	NOUN
app01-11101	181	4	,	,	PUNCT
app01-11101	181	5	2020	2020	NUM
app01-11101	181	6	.	.	PUNCT
app01-11101	181	7	https://doi.org/10.1007/978-3-030-14907-9_2	https://doi.org/10.1007/978-3-030-14907-9_2	PUNCT
app01-11101	182	1	[	[	X
app01-11101	182	2	11	11	NUM
app01-11101	182	3	]	]	X
app01-11101	182	4	e.	e.	PROPN
app01-11101	182	5	janouchová	janouchová	PROPN
app01-11101	182	6	,	,	PUNCT
app01-11101	182	7	j.	j.	PROPN
app01-11101	182	8	sýkora	sýkora	PROPN
app01-11101	182	9	,	,	PUNCT
app01-11101	182	10	a.	a.	PROPN
app01-11101	182	11	kučerová	kučerová	PROPN
app01-11101	182	12	.	.	PUNCT
app01-11101	183	1	polynomial	polynomial	ADJ
app01-11101	183	2	chaos	chaos	NOUN
app01-11101	183	3	in	in	ADP
app01-11101	183	4	evaluating	evaluate	VERB
app01-11101	183	5	failure	failure	NOUN
app01-11101	183	6	probability	probability	NOUN
app01-11101	183	7	:	:	PUNCT
app01-11101	183	8	a	a	DET
app01-11101	183	9	comparative	comparative	ADJ
app01-11101	183	10	study	study	NOUN
app01-11101	183	11	.	.	PUNCT
app01-11101	184	1	applications	application	NOUN
app01-11101	184	2	of	of	ADP
app01-11101	184	3	mathematics	mathematic	NOUN
app01-11101	184	4	63(6):713–737	63(6):713–737	PROPN
app01-11101	184	5	,	,	PUNCT
app01-11101	184	6	2018	2018	NUM
app01-11101	184	7	.	.	PUNCT
app01-11101	185	1	https://doi.org/10.21136/am.2018.0335-17	https://doi.org/10.21136/am.2018.0335-17	NOUN
app01-11101	186	1	[	[	X
app01-11101	186	2	12	12	NUM
app01-11101	186	3	]	]	X
app01-11101	186	4	g.	g.	PROPN
app01-11101	186	5	e.	e.	PROPN
app01-11101	186	6	karniadakis	karniadakis	PROPN
app01-11101	186	7	,	,	PUNCT
app01-11101	186	8	i.	i.	PROPN
app01-11101	186	9	g.	g.	PROPN
app01-11101	186	10	kevrekidis	kevrekidis	PROPN
app01-11101	186	11	,	,	PUNCT
app01-11101	186	12	l.	l.	PROPN
app01-11101	186	13	lu	lu	PROPN
app01-11101	186	14	,	,	PUNCT
app01-11101	186	15	et	et	PROPN
app01-11101	186	16	al	al	PROPN
app01-11101	186	17	.	.	PUNCT
app01-11101	186	18	physics	physics	NOUN
app01-11101	186	19	-	-	PUNCT
app01-11101	186	20	informed	inform	VERB
app01-11101	186	21	machine	machine	NOUN
app01-11101	186	22	learning	learning	NOUN
app01-11101	186	23	.	.	PUNCT
app01-11101	187	1	nature	nature	NOUN
app01-11101	187	2	reviews	reviews	PROPN
app01-11101	187	3	physics	physics	PROPN
app01-11101	187	4	3(6):422–440	3(6):422–440	NUM
app01-11101	187	5	,	,	PUNCT
app01-11101	187	6	2021	2021	NUM
app01-11101	187	7	.	.	PUNCT
app01-11101	187	8	https://doi.org/10.1038/s42254-021-00314-5	https://doi.org/10.1038/s42254-021-00314-5	NUM
app01-11101	188	1	[	[	X
app01-11101	188	2	13	13	NUM
app01-11101	188	3	]	]	PUNCT
app01-11101	188	4	m.	m.	NOUN
app01-11101	188	5	raissi	raissi	NOUN
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app01-11101	188	7	p.	p.	NOUN
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app01-11101	189	6	:	:	PUNCT
app01-11101	189	7	a	a	DET
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app01-11101	189	13	forward	forward	ADV
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app01-11101	189	15	inverse	inverse	NOUN
app01-11101	189	16	problems	problem	NOUN
app01-11101	189	17	involving	involve	VERB
app01-11101	189	18	nonlinear	nonlinear	ADJ
app01-11101	189	19	partial	partial	ADJ
app01-11101	189	20	differential	differential	NOUN
app01-11101	189	21	equations	equation	NOUN
app01-11101	189	22	.	.	PUNCT
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app01-11101	190	4	physics	physic	NOUN
app01-11101	190	5	378:686–707	378:686–707	NUM
app01-11101	190	6	,	,	PUNCT
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app01-11101	190	8	.	.	PUNCT
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app01-11101	192	3	]	]	X
app01-11101	192	4	f.	f.	PROPN
app01-11101	192	5	chollet	chollet	PROPN
app01-11101	192	6	.	.	PUNCT
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app01-11101	193	2	learning	learning	NOUN
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app01-11101	193	4	python	python	PROPN
app01-11101	193	5	.	.	PUNCT
app01-11101	194	1	simon	simon	PROPN
app01-11101	194	2	and	and	CCONJ
app01-11101	194	3	schuster	schuster	PROPN
app01-11101	194	4	,	,	PUNCT
app01-11101	194	5	2021	2021	NUM
app01-11101	194	6	.	.	PUNCT
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app01-11101	196	1	https://doi.org/10.1017/s0962492900000015	https://doi.org/10.1017/s0962492900000015	NUM
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app01-11101	197	1	https://doi.org/10.1007/978-1-60327-101-1_2	https://doi.org/10.1007/978-1-60327-101-1_2	PROPN
app01-11101	197	2	https://doi.org/10.1007/978-3-030-14907-9_2	https://doi.org/10.1007/978-3-030-14907-9_2	PUNCT
app01-11101	197	3	https://doi.org/10.21136/am.2018.0335-17	https://doi.org/10.21136/am.2018.0335-17	NOUN
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app01-11101	197	5	https://doi.org/10.1016/j.jcp.2018.10.045	https://doi.org/10.1016/j.jcp.2018.10.045	PROPN
app01-11101	197	6	ondřej	ondřej	NOUN
app01-11101	197	7	šperl	šperl	PROPN
app01-11101	197	8	,	,	PUNCT
app01-11101	197	9	jan	jan	PROPN
app01-11101	197	10	sýkora	sýkora	PROPN
app01-11101	197	11	acta	acta	PROPN
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app01-11101	197	14	proceedings	proceeding	NOUN
app01-11101	197	15	[	[	X
app01-11101	197	16	15	15	X
app01-11101	197	17	]	]	X
app01-11101	197	18	j.	j.	PROPN
app01-11101	197	19	gu	gu	PROPN
app01-11101	197	20	,	,	PUNCT
app01-11101	197	21	z.	z.	PROPN
app01-11101	197	22	wang	wang	PROPN
app01-11101	197	23	,	,	PUNCT
app01-11101	197	24	j.	j.	PROPN
app01-11101	197	25	kuen	kuen	PROPN
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app01-11101	197	29	.	.	PUNCT
app01-11101	198	1	recent	recent	ADJ
app01-11101	198	2	advances	advance	NOUN
app01-11101	198	3	in	in	ADP
app01-11101	198	4	convolutional	convolutional	ADJ
app01-11101	198	5	neural	neural	ADJ
app01-11101	198	6	networks	network	NOUN
app01-11101	198	7	.	.	PUNCT
app01-11101	199	1	pattern	pattern	NOUN
app01-11101	199	2	recognition	recognition	NOUN
app01-11101	199	3	77:354–377	77:354–377	NOUN
app01-11101	199	4	,	,	PUNCT
app01-11101	199	5	2018	2018	NUM
app01-11101	199	6	.	.	PUNCT
app01-11101	200	1	https://doi.org/10.1016/j.patcog.2017.10.013	https://doi.org/10.1016/j.patcog.2017.10.013	NOUN
app01-11101	201	1	[	[	X
app01-11101	201	2	16	16	NUM
app01-11101	201	3	]	]	X
app01-11101	201	4	y.	y.	PROPN
app01-11101	201	5	wang	wang	PROPN
app01-11101	201	6	,	,	PUNCT
app01-11101	201	7	j.	j.	PROPN
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app01-11101	201	9	,	,	PUNCT
app01-11101	201	10	q.	q.	PROPN
app01-11101	201	11	ren	ren	PROPN
app01-11101	201	12	,	,	PUNCT
app01-11101	201	13	et	et	PROPN
app01-11101	201	14	al	al	PROPN
app01-11101	201	15	.	.	PROPN
app01-11101	201	16	3	3	NUM
app01-11101	201	17	-	-	SYM
app01-11101	201	18	d	d	ADV
app01-11101	201	19	steady	steady	ADJ
app01-11101	201	20	heat	heat	NOUN
app01-11101	201	21	conduction	conduction	NOUN
app01-11101	201	22	solver	solver	VERB
app01-11101	201	23	via	via	ADP
app01-11101	201	24	deep	deep	ADJ
app01-11101	201	25	learning	learning	NOUN
app01-11101	201	26	.	.	PUNCT
app01-11101	202	1	ieee	ieee	PROPN
app01-11101	202	2	journal	journal	PROPN
app01-11101	202	3	on	on	ADP
app01-11101	202	4	multiscale	multiscale	PROPN
app01-11101	202	5	and	and	CCONJ
app01-11101	202	6	multiphysics	multiphysics	PROPN
app01-11101	202	7	computational	computational	ADJ
app01-11101	202	8	techniques	technique	NOUN
app01-11101	202	9	6:100–108	6:100–108	PROPN
app01-11101	202	10	,	,	PUNCT
app01-11101	202	11	2021	2021	NUM
app01-11101	202	12	.	.	PUNCT
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app01-11101	204	2	17	17	NUM
app01-11101	204	3	]	]	X
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app01-11101	204	5	ronneberger	ronneberger	NOUN
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app01-11101	204	9	,	,	PUNCT
app01-11101	204	10	t.	t.	PROPN
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app01-11101	205	2	-	-	NOUN
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app01-11101	205	4	:	:	PUNCT
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app01-11101	205	6	networks	network	NOUN
app01-11101	205	7	for	for	ADP
app01-11101	205	8	biomedical	biomedical	ADJ
app01-11101	205	9	image	image	NOUN
app01-11101	205	10	segmentation	segmentation	NOUN
app01-11101	205	11	.	.	PUNCT
app01-11101	206	1	in	in	ADP
app01-11101	206	2	medical	medical	ADJ
app01-11101	206	3	image	image	NOUN
app01-11101	206	4	computing	computing	NOUN
app01-11101	206	5	and	and	CCONJ
app01-11101	206	6	computerassisted	computerassiste	VERB
app01-11101	206	7	intervention	intervention	NOUN
app01-11101	206	8	–	–	PUNCT
app01-11101	206	9	miccai	miccai	NOUN
app01-11101	206	10	2015	2015	NUM
app01-11101	206	11	:	:	PUNCT
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app01-11101	206	13	international	international	ADJ
app01-11101	206	14	conference	conference	NOUN
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app01-11101	206	16	munich	munich	PROPN
app01-11101	206	17	,	,	PUNCT
app01-11101	206	18	germany	germany	PROPN
app01-11101	206	19	,	,	PUNCT
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app01-11101	206	21	5	5	NUM
app01-11101	206	22	-	-	SYM
app01-11101	206	23	9	9	NUM
app01-11101	206	24	,	,	PUNCT
app01-11101	206	25	2015	2015	NUM
app01-11101	206	26	,	,	PUNCT
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app01-11101	206	32	,	,	PUNCT
app01-11101	206	33	pp	pp	ADJ
app01-11101	206	34	.	.	PUNCT
app01-11101	207	1	234–241	234–241	NUM
app01-11101	207	2	.	.	PUNCT
app01-11101	207	3	springer	springer	NOUN
app01-11101	207	4	,	,	PUNCT
app01-11101	207	5	2015	2015	NUM
app01-11101	207	6	.	.	PUNCT
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app01-11101	209	2	18	18	NUM
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app01-11101	209	4	j.	j.	PROPN
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app01-11101	209	7	j.	j.	PROPN
app01-11101	209	8	sýkora	sýkora	PROPN
app01-11101	209	9	.	.	PUNCT
app01-11101	210	1	application	application	NOUN
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app01-11101	210	3	calderón	calderón	NOUN
app01-11101	210	4	’s	’s	PART
app01-11101	210	5	inverse	inverse	ADJ
app01-11101	210	6	problem	problem	NOUN
app01-11101	210	7	in	in	ADP
app01-11101	210	8	civil	civil	ADJ
app01-11101	210	9	engineering	engineering	NOUN
app01-11101	210	10	.	.	PUNCT
app01-11101	211	1	applications	application	NOUN
app01-11101	211	2	of	of	ADP
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app01-11101	211	5	,	,	PUNCT
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app01-11101	212	4	]	]	X
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app01-11101	212	10	l.	l.	PROPN
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app01-11101	212	12	.	.	PUNCT
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app01-11101	213	2	finite	finite	PROPN
app01-11101	213	3	element	element	PROPN
app01-11101	213	4	method	method	NOUN
app01-11101	213	5	set	set	VERB
app01-11101	213	6	.	.	PUNCT
app01-11101	214	1	elsevier	elsevier	NOUN
app01-11101	214	2	,	,	PUNCT
app01-11101	214	3	2005	2005	NUM
app01-11101	214	4	.	.	PUNCT
app01-11101	215	1	[	[	X
app01-11101	215	2	20	20	NUM
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app01-11101	215	10	t.	t.	PROPN
app01-11101	215	11	darrell	darrell	PROPN
app01-11101	215	12	.	.	PUNCT
app01-11101	216	1	fully	fully	ADV
app01-11101	216	2	convolutional	convolutional	ADJ
app01-11101	216	3	networks	network	NOUN
app01-11101	216	4	for	for	ADP
app01-11101	216	5	semantic	semantic	ADJ
app01-11101	216	6	segmentation	segmentation	NOUN
app01-11101	216	7	.	.	PUNCT
app01-11101	217	1	ieee	ieee	NOUN
app01-11101	217	2	transactions	transaction	NOUN
app01-11101	217	3	on	on	ADP
app01-11101	217	4	pattern	pattern	NOUN
app01-11101	217	5	analysis	analysis	NOUN
app01-11101	217	6	and	and	CCONJ
app01-11101	217	7	machine	machine	NOUN
app01-11101	217	8	intelligence	intelligence	NOUN
app01-11101	217	9	39(4):640–651	39(4):640–651	PROPN
app01-11101	217	10	,	,	PUNCT
app01-11101	217	11	2016	2016	NUM
app01-11101	217	12	.	.	PUNCT
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app01-11101	218	2	84	84	NUM
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app01-11101	218	8	acta	acta	PROPN
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app01-11101	218	10	ctu	ctu	NOUN
app01-11101	218	11	proceedings	proceeding	NOUN
app01-11101	218	12	54:79–84	54:79–84	NOUN
app01-11101	218	13	,	,	PUNCT
app01-11101	218	14	2025	2025	NUM
app01-11101	218	15	1	1	NUM
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app01-11101	218	17	2	2	NUM
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app01-11101	218	21	-	-	PUNCT
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app01-11101	218	23	surrogate	surrogate	ADJ
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app01-11101	218	27	4	4	NUM
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app01-11101	218	29	acknowledgements	acknowledgement	NOUN
app01-11101	218	30	references	reference	NOUN