id	sid	tid	token	lemma	pos
ispiv-163	1	1	data	datum	NOUN
ispiv-163	1	2	reconstruction	reconstruction	NOUN
ispiv-163	1	3	of	of	ADP
ispiv-163	1	4	homogeneous	homogeneous	ADJ
ispiv-163	1	5	turbulence	turbulence	NOUN
ispiv-163	1	6	using	use	VERB
ispiv-163	1	7	lagrangian	lagrangian	ADJ
ispiv-163	1	8	particle	particle	NOUN
ispiv-163	1	9	tracking	tracking	NOUN
ispiv-163	1	10	with	with	ADP
ispiv-163	1	11	shake	shake	NOUN
ispiv-163	1	12	-	-	PUNCT
ispiv-163	1	13	the	the	DET
ispiv-163	1	14	-	-	PUNCT
ispiv-163	1	15	box	box	NOUN
ispiv-163	1	16	and	and	CCONJ
ispiv-163	1	17	machine	machine	NOUN
ispiv-163	1	18	learning	learn	VERB
ispiv-163	1	19	dong	dong	PROPN
ispiv-163	1	20	kim	kim	PROPN
ispiv-163	1	21	,	,	PUNCT
ispiv-163	1	22	kyung	kyung	PROPN
ispiv-163	1	23	chun	chun	PROPN
ispiv-163	1	24	kim	kim	PROPN
ispiv-163	1	25	school	school	PROPN
ispiv-163	1	26	of	of	ADP
ispiv-163	1	27	mechanical	mechanical	ADJ
ispiv-163	1	28	engineering	engineering	NOUN
ispiv-163	1	29	,	,	PUNCT
ispiv-163	1	30	pusan	pusan	PROPN
ispiv-163	1	31	national	national	PROPN
ispiv-163	1	32	university	university	PROPN
ispiv-163	1	33	,	,	PUNCT
ispiv-163	1	34	46241	46241	NUM
ispiv-163	1	35	busan	busan	PROPN
ispiv-163	1	36	,	,	PUNCT
ispiv-163	1	37	south	south	PROPN
ispiv-163	1	38	korea	korea	PROPN
ispiv-163	1	39	this	this	DET
ispiv-163	1	40	paper	paper	NOUN
ispiv-163	1	41	proposes	propose	VERB
ispiv-163	1	42	a	a	DET
ispiv-163	1	43	data	data	NOUN
ispiv-163	1	44	reconstruction	reconstruction	NOUN
ispiv-163	1	45	of	of	ADP
ispiv-163	1	46	homogeneous	homogeneous	ADJ
ispiv-163	1	47	turbulent	turbulent	ADJ
ispiv-163	1	48	flow	flow	NOUN
ispiv-163	1	49	combined	combine	VERB
ispiv-163	1	50	machine	machine	NOUN
ispiv-163	1	51	learning	learning	NOUN
ispiv-163	1	52	(	(	PUNCT
ispiv-163	1	53	ml	ml	NOUN
ispiv-163	1	54	)	)	PUNCT
ispiv-163	1	55	approach	approach	NOUN
ispiv-163	1	56	using	use	VERB
ispiv-163	1	57	experimental	experimental	ADJ
ispiv-163	1	58	lagrangian	lagrangian	ADJ
ispiv-163	1	59	particle	particle	NOUN
ispiv-163	1	60	tracking	tracking	NOUN
ispiv-163	1	61	(	(	PUNCT
ispiv-163	1	62	lpt	lpt	PROPN
ispiv-163	1	63	)	)	PUNCT
ispiv-163	1	64	data	datum	NOUN
ispiv-163	1	65	with	with	ADP
ispiv-163	1	66	shake	shake	NOUN
ispiv-163	1	67	-	-	PUNCT
ispiv-163	1	68	the	the	DET
ispiv-163	1	69	-	-	PUNCT
ispiv-163	1	70	box	box	NOUN
ispiv-163	1	71	(	(	PUNCT
ispiv-163	1	72	stb	stb	PROPN
ispiv-163	1	73	)	)	PUNCT
ispiv-163	1	74	.	.	PUNCT
ispiv-163	2	1	the	the	DET
ispiv-163	2	2	lpt	lpt	PROPN
ispiv-163	2	3	with	with	ADP
ispiv-163	2	4	stb	stb	PROPN
ispiv-163	2	5	was	be	AUX
ispiv-163	2	6	adopted	adopt	VERB
ispiv-163	2	7	to	to	PART
ispiv-163	2	8	measure	measure	VERB
ispiv-163	2	9	a	a	DET
ispiv-163	2	10	von	von	PROPN
ispiv-163	2	11	kármán	kármán	PROPN
ispiv-163	2	12	flow	flow	VERB
ispiv-163	2	13	with	with	ADP
ispiv-163	2	14	a	a	DET
ispiv-163	2	15	homogeneous	homogeneous	ADJ
ispiv-163	2	16	turbulent	turbulent	ADJ
ispiv-163	2	17	region	region	NOUN
ispiv-163	2	18	in	in	ADP
ispiv-163	2	19	the	the	DET
ispiv-163	2	20	center	center	NOUN
ispiv-163	2	21	[	[	X
ispiv-163	2	22	1	1	NUM
ispiv-163	2	23	]	]	PUNCT
ispiv-163	2	24	.	.	PUNCT
ispiv-163	3	1	the	the	DET
ispiv-163	3	2	stb	stb	PROPN
ispiv-163	3	3	results	result	NOUN
ispiv-163	3	4	have	have	AUX
ispiv-163	3	5	been	be	AUX
ispiv-163	3	6	stored	store	VERB
ispiv-163	3	7	and	and	CCONJ
ispiv-163	3	8	a	a	DET
ispiv-163	3	9	temporal	temporal	ADJ
ispiv-163	3	10	filter	filter	NOUN
ispiv-163	3	11	using	use	VERB
ispiv-163	3	12	3rd	3rd	ADJ
ispiv-163	3	13	order	order	NOUN
ispiv-163	3	14	b	b	X
ispiv-163	3	15	-	-	PUNCT
ispiv-163	3	16	splines	spline	NOUN
ispiv-163	3	17	has	have	AUX
ispiv-163	3	18	been	be	AUX
ispiv-163	3	19	applied	apply	VERB
ispiv-163	3	20	with	with	ADP
ispiv-163	3	21	optimal	optimal	ADJ
ispiv-163	3	22	weighting	weighting	NOUN
ispiv-163	3	23	coefficients	coefficient	NOUN
ispiv-163	3	24	to	to	PART
ispiv-163	3	25	be	be	AUX
ispiv-163	3	26	used	use	VERB
ispiv-163	3	27	as	as	ADP
ispiv-163	3	28	input	input	NOUN
ispiv-163	3	29	for	for	ADP
ispiv-163	3	30	flowfit	flowfit	NOUN
ispiv-163	3	31	data	datum	NOUN
ispiv-163	3	32	assimilation	assimilation	NOUN
ispiv-163	3	33	method	method	NOUN
ispiv-163	3	34	[	[	X
ispiv-163	3	35	2	2	NUM
ispiv-163	3	36	]	]	PUNCT
ispiv-163	3	37	.	.	PUNCT
ispiv-163	4	1	flowfit	flowfit	PROPN
ispiv-163	4	2	data	datum	NOUN
ispiv-163	4	3	was	be	AUX
ispiv-163	4	4	used	use	VERB
ispiv-163	4	5	as	as	ADP
ispiv-163	4	6	ground	ground	NOUN
ispiv-163	4	7	truth	truth	NOUN
ispiv-163	4	8	to	to	PART
ispiv-163	4	9	train	train	VERB
ispiv-163	4	10	ml	ml	PROPN
ispiv-163	4	11	algorithm	algorithm	PROPN
ispiv-163	4	12	.	.	PUNCT
ispiv-163	5	1	the	the	DET
ispiv-163	5	2	low	low	ADV
ispiv-163	5	3	-	-	PUNCT
ispiv-163	5	4	resolved	resolve	VERB
ispiv-163	5	5	data	datum	NOUN
ispiv-163	5	6	of	of	ADP
ispiv-163	5	7	the	the	DET
ispiv-163	5	8	velocity	velocity	NOUN
ispiv-163	5	9	and	and	CCONJ
ispiv-163	5	10	acceleration	acceleration	NOUN
ispiv-163	5	11	field	field	NOUN
ispiv-163	5	12	was	be	AUX
ispiv-163	5	13	reconstructed	reconstruct	VERB
ispiv-163	5	14	using	use	VERB
ispiv-163	5	15	an	an	DET
ispiv-163	5	16	adaptive	adaptive	ADJ
ispiv-163	5	17	neuro	neuro	NOUN
ispiv-163	5	18	-	-	PUNCT
ispiv-163	5	19	fuzzy	fuzzy	ADJ
ispiv-163	5	20	inference	inference	NOUN
ispiv-163	5	21	system	system	NOUN
ispiv-163	5	22	(	(	PUNCT
ispiv-163	5	23	anfis	anfi	VERB
ispiv-163	5	24	)	)	PUNCT
ispiv-163	5	25	with	with	ADP
ispiv-163	5	26	the	the	DET
ispiv-163	5	27	downsampled	downsample	VERB
ispiv-163	5	28	lpt	lpt	PROPN
ispiv-163	5	29	data	datum	NOUN
ispiv-163	5	30	as	as	ADP
ispiv-163	5	31	an	an	DET
ispiv-163	5	32	input	input	NOUN
ispiv-163	5	33	to	to	PART
ispiv-163	5	34	predict	predict	VERB
ispiv-163	5	35	homogeneous	homogeneous	ADJ
ispiv-163	5	36	turbulent	turbulent	ADJ
ispiv-163	5	37	flow	flow	NOUN
ispiv-163	5	38	[	[	X
ispiv-163	5	39	3	3	NUM
ispiv-163	5	40	]	]	PUNCT
ispiv-163	5	41	.	.	PUNCT
ispiv-163	6	1	the	the	DET
ispiv-163	6	2	training	training	NOUN
ispiv-163	6	3	process	process	NOUN
ispiv-163	6	4	can	can	AUX
ispiv-163	6	5	be	be	AUX
ispiv-163	6	6	mathematically	mathematically	ADV
ispiv-163	6	7	regarded	regard	VERB
ispiv-163	6	8	as	as	ADP
ispiv-163	6	9	an	an	DET
ispiv-163	6	10	optimization	optimization	NOUN
ispiv-163	6	11	problem	problem	NOUN
ispiv-163	6	12	to	to	PART
ispiv-163	6	13	determine	determine	VERB
ispiv-163	6	14	the	the	DET
ispiv-163	6	15	weighting	weighting	NOUN
ispiv-163	6	16	factor	factor	NOUN
ispiv-163	6	17	.	.	PUNCT
ispiv-163	7	1	fig	fig	NOUN
ispiv-163	7	2	.	.	PUNCT
ispiv-163	8	1	1	1	NUM
ispiv-163	8	2	data	datum	NOUN
ispiv-163	8	3	reconstruction	reconstruction	NOUN
ispiv-163	8	4	methods	method	NOUN
ispiv-163	8	5	and	and	CCONJ
ispiv-163	8	6	anfis	anfis	VERB
ispiv-163	8	7	learning	learn	VERB
ispiv-163	8	8	structure	structure	NOUN
ispiv-163	8	9	.	.	PUNCT
ispiv-163	9	1	given	give	VERB
ispiv-163	9	2	the	the	DET
ispiv-163	9	3	input	input	NOUN
ispiv-163	9	4	data	datum	NOUN
ispiv-163	9	5	set	set	VERB
ispiv-163	9	6	𝑥	𝑥	PROPN
ispiv-163	9	7	(	(	PUNCT
ispiv-163	9	8	low	low	ADJ
ispiv-163	9	9	resolved	resolved	ADJ
ispiv-163	9	10	stb	stb	PROPN
ispiv-163	9	11	data	data	PROPN
ispiv-163	9	12	)	)	PUNCT
ispiv-163	9	13	and	and	CCONJ
ispiv-163	9	14	the	the	DET
ispiv-163	9	15	desired	desire	VERB
ispiv-163	9	16	output	output	NOUN
ispiv-163	9	17	data	datum	NOUN
ispiv-163	9	18	set	set	VERB
ispiv-163	9	19	𝑦	𝑦	PRON
ispiv-163	9	20	(	(	PUNCT
ispiv-163	9	21	flowfit	flowfit	NOUN
ispiv-163	9	22	results	result	NOUN
ispiv-163	9	23	)	)	PUNCT
ispiv-163	9	24	,	,	PUNCT
ispiv-163	9	25	we	we	PRON
ispiv-163	9	26	aim	aim	VERB
ispiv-163	9	27	to	to	PART
ispiv-163	9	28	find	find	VERB
ispiv-163	9	29	the	the	DET
ispiv-163	9	30	optimal	optimal	ADJ
ispiv-163	9	31	weight	weight	NOUN
ispiv-163	9	32	𝑤	𝑤	NOUN
ispiv-163	9	33	in	in	ADP
ispiv-163	9	34	a	a	DET
ispiv-163	9	35	machine	machine	NOUN
ispiv-163	9	36	-	-	PUNCT
ispiv-163	9	37	learned	learn	VERB
ispiv-163	9	38	model	model	NOUN
ispiv-163	9	39	𝐹	𝐹	PROPN
ispiv-163	9	40	that	that	PRON
ispiv-163	9	41	acts	act	VERB
ispiv-163	9	42	as	as	ADP
ispiv-163	9	43	a	a	DET
ispiv-163	9	44	nonlinear	nonlinear	ADJ
ispiv-163	9	45	regression	regression	NOUN
ispiv-163	9	46	function	function	NOUN
ispiv-163	9	47	such	such	ADJ
ispiv-163	9	48	that	that	SCONJ
ispiv-163	9	49	𝐹(𝑥	𝐹(𝑥	NUM
ispiv-163	9	50	;	;	PUNCT
ispiv-163	9	51	𝑤	𝑤	X
ispiv-163	9	52	)	)	PUNCT
ispiv-163	10	1	≈	≈	PROPN
ispiv-163	10	2	𝑦.	𝑦.	PROPN
ispiv-163	10	3	in	in	ADP
ispiv-163	10	4	the	the	DET
ispiv-163	10	5	present	present	ADJ
ispiv-163	10	6	case	case	NOUN
ispiv-163	10	7	,	,	PUNCT
ispiv-163	10	8	𝑥	𝑥	PROPN
ispiv-163	10	9	and	and	CCONJ
ispiv-163	10	10	𝐹(𝑥	𝐹(𝑥	NUM
ispiv-163	10	11	;	;	PUNCT
ispiv-163	10	12	𝑤	𝑤	X
ispiv-163	10	13	)	)	PUNCT
ispiv-163	10	14	represent	represent	VERB
ispiv-163	10	15	the	the	DET
ispiv-163	10	16	lowresolution	lowresolution	NOUN
ispiv-163	10	17	and	and	CCONJ
ispiv-163	10	18	reconstructed	reconstruct	VERB
ispiv-163	10	19	high	high	ADJ
ispiv-163	10	20	-	-	PUNCT
ispiv-163	10	21	resolution	resolution	NOUN
ispiv-163	10	22	data	datum	NOUN
ispiv-163	10	23	,	,	PUNCT
ispiv-163	10	24	respectively	respectively	ADV
ispiv-163	10	25	.	.	PUNCT
ispiv-163	11	1	the	the	DET
ispiv-163	11	2	weight	weight	NOUN
ispiv-163	11	3	𝑤	𝑤	NOUN
ispiv-163	11	4	is	be	AUX
ispiv-163	11	5	optimized	optimize	VERB
ispiv-163	11	6	between	between	ADP
ispiv-163	11	7	the	the	DET
ispiv-163	11	8	desired	desire	VERB
ispiv-163	11	9	high	high	ADJ
ispiv-163	11	10	-	-	PUNCT
ispiv-163	11	11	resolution	resolution	NOUN
ispiv-163	11	12	output	output	NOUN
ispiv-163	11	13	𝑦	𝑦	NOUN
ispiv-163	11	14	and	and	CCONJ
ispiv-163	11	15	the	the	DET
ispiv-163	11	16	ml	ml	PROPN
ispiv-163	11	17	model	model	PROPN
ispiv-163	11	18	output	output	NOUN
ispiv-163	11	19	𝐹(𝑥;𝑤	𝐹(𝑥;𝑤	PROPN
ispiv-163	11	20	)	)	PUNCT
ispiv-163	11	21	is	be	AUX
ispiv-163	11	22	minimized	minimize	VERB
ispiv-163	11	23	.	.	PUNCT
ispiv-163	12	1	the	the	DET
ispiv-163	12	2	anfisbased	anfisbase	VERB
ispiv-163	12	3	data	data	NOUN
ispiv-163	12	4	assimilation	assimilation	NOUN
ispiv-163	12	5	was	be	AUX
ispiv-163	12	6	first	first	ADV
ispiv-163	12	7	trained	train	VERB
ispiv-163	12	8	with	with	ADP
ispiv-163	12	9	flowfit	flowfit	NOUN
ispiv-163	12	10	data	datum	NOUN
ispiv-163	12	11	assimilation	assimilation	NOUN
ispiv-163	12	12	result	result	VERB
ispiv-163	12	13	as	as	ADP
ispiv-163	12	14	ground	ground	NOUN
ispiv-163	12	15	truth	truth	NOUN
ispiv-163	12	16	.	.	PUNCT
ispiv-163	13	1	four	four	NUM
ispiv-163	13	2	anfis	anfis	ADJ
ispiv-163	13	3	training	training	NOUN
ispiv-163	13	4	inputs	input	NOUN
ispiv-163	13	5	on	on	ADP
ispiv-163	13	6	the	the	DET
ispiv-163	13	7	x	x	PROPN
ispiv-163	13	8	,	,	PUNCT
ispiv-163	13	9	y	y	PROPN
ispiv-163	13	10	,	,	PUNCT
ispiv-163	13	11	z	z	NOUN
ispiv-163	13	12	coordinates	coordinate	NOUN
ispiv-163	13	13	,	,	PUNCT
ispiv-163	13	14	and	and	CCONJ
ispiv-163	13	15	time	time	NOUN
ispiv-163	13	16	t	t	PROPN
ispiv-163	13	17	of	of	ADP
ispiv-163	13	18	flowfit	flowfit	PROPN
ispiv-163	13	19	results	result	NOUN
ispiv-163	13	20	were	be	AUX
ispiv-163	13	21	assigned	assign	VERB
ispiv-163	13	22	to	to	ADP
ispiv-163	13	23	1st	1st	ADJ
ispiv-163	13	24	layer	layer	NOUN
ispiv-163	13	25	of	of	ADP
ispiv-163	13	26	anfis	anfis	ADJ
ispiv-163	13	27	algorithm	algorithm	NOUN
ispiv-163	13	28	.	.	PUNCT
ispiv-163	14	1	the	the	DET
ispiv-163	14	2	training	training	NOUN
ispiv-163	14	3	targets	target	NOUN
ispiv-163	14	4	on	on	ADP
ispiv-163	14	5	velocity	velocity	NOUN
ispiv-163	14	6	,	,	PUNCT
ispiv-163	14	7	acceleration	acceleration	NOUN
ispiv-163	14	8	components	component	NOUN
ispiv-163	14	9	were	be	AUX
ispiv-163	14	10	assigned	assign	VERB
ispiv-163	14	11	to	to	ADP
ispiv-163	14	12	final	final	ADJ
ispiv-163	14	13	layer	layer	NOUN
ispiv-163	14	14	of	of	ADP
ispiv-163	14	15	anfis	anfis	ADJ
ispiv-163	14	16	algorithm	algorithm	NOUN
ispiv-163	14	17	to	to	PART
ispiv-163	14	18	get	get	VERB
ispiv-163	14	19	weighting	weighting	NOUN
ispiv-163	14	20	factor	factor	NOUN
ispiv-163	14	21	.	.	PUNCT
ispiv-163	15	1	the	the	DET
ispiv-163	15	2	computations	computation	NOUN
ispiv-163	15	3	were	be	AUX
ispiv-163	15	4	performed	perform	VERB
ispiv-163	15	5	on	on	ADP
ispiv-163	15	6	a	a	DET
ispiv-163	15	7	computer	computer	NOUN
ispiv-163	15	8	with	with	ADP
ispiv-163	15	9	an	an	DET
ispiv-163	15	10	intel	intel	ADJ
ispiv-163	15	11	®	®	NOUN
ispiv-163	15	12	core	core	NOUN
ispiv-163	15	13	™	™	VERB
ispiv-163	15	14	i5	i5	NOUN
ispiv-163	15	15	-	-	PUNCT
ispiv-163	15	16	8250u	8250u	NUM
ispiv-163	15	17	cpu	cpu	NOUN
ispiv-163	15	18	@	@	ADP
ispiv-163	15	19	1.60	1.60	NUM
ispiv-163	15	20	ghz	ghz	NOUN
ispiv-163	15	21	1.80	1.80	NUM
ispiv-163	15	22	ghz	ghz	NOUN
ispiv-163	15	23	and	and	CCONJ
ispiv-163	15	24	8.0	8.0	NUM
ispiv-163	15	25	gb	gb	NOUN
ispiv-163	15	26	of	of	ADP
ispiv-163	15	27	ram	ram	NOUN
ispiv-163	15	28	.	.	PUNCT
ispiv-163	16	1	with	with	ADP
ispiv-163	16	2	300	300	NUM
ispiv-163	16	3	epochs	epoch	NOUN
ispiv-163	16	4	and	and	CCONJ
ispiv-163	16	5	4	4	NUM
ispiv-163	16	6	input	input	NOUN
ispiv-163	16	7	membership	membership	NOUN
ispiv-163	16	8	functions	function	NOUN
ispiv-163	16	9	,	,	PUNCT
ispiv-163	16	10	the	the	DET
ispiv-163	16	11	anfis	anfis	ADJ
ispiv-163	16	12	training	training	NOUN
ispiv-163	16	13	satisfied	satisfy	VERB
ispiv-163	16	14	the	the	DET
ispiv-163	16	15	convergence	convergence	NOUN
ispiv-163	16	16	criterion	criterion	NOUN
ispiv-163	16	17	of	of	ADP
ispiv-163	16	18	rmse	rmse	NOUN
ispiv-163	16	19	<	<	X
ispiv-163	16	20	0.01	0.01	NUM
ispiv-163	16	21	.	.	PUNCT
ispiv-163	17	1	the	the	DET
ispiv-163	17	2	training	training	NOUN
ispiv-163	17	3	time	time	NOUN
ispiv-163	17	4	takes	take	VERB
ispiv-163	17	5	2	2	NUM
ispiv-163	17	6	hours	hour	NOUN
ispiv-163	17	7	.	.	PUNCT
ispiv-163	18	1	figure	figure	NOUN
ispiv-163	18	2	2	2	NUM
ispiv-163	18	3	shows	show	VERB
ispiv-163	18	4	the	the	DET
ispiv-163	18	5	spatial	spatial	ADJ
ispiv-163	18	6	data	data	NOUN
ispiv-163	18	7	reconstruction	reconstruction	NOUN
ispiv-163	18	8	of	of	ADP
ispiv-163	18	9	anfis	anfis	ADJ
ispiv-163	18	10	model	model	NOUN
ispiv-163	18	11	with	with	ADP
ispiv-163	18	12	different	different	ADJ
ispiv-163	18	13	ratio	ratio	NOUN
ispiv-163	18	14	of	of	ADP
ispiv-163	18	15	raw	raw	ADJ
ispiv-163	18	16	particle	particle	NOUN
ispiv-163	18	17	density	density	NOUN
ispiv-163	18	18	,	,	PUNCT
ispiv-163	18	19	𝜌𝑝.	𝜌𝑝.	X
ispiv-163	18	20	the	the	DET
ispiv-163	18	21	particle	particle	NOUN
ispiv-163	18	22	density	density	NOUN
ispiv-163	18	23	was	be	AUX
ispiv-163	18	24	downsampled	downsample	VERB
ispiv-163	18	25	by	by	ADP
ispiv-163	18	26	random	random	ADJ
ispiv-163	18	27	reduction	reduction	NOUN
ispiv-163	18	28	from	from	ADP
ispiv-163	18	29	raw	raw	ADJ
ispiv-163	18	30	stb	stb	PROPN
ispiv-163	18	31	data	datum	NOUN
ispiv-163	18	32	(	(	PUNCT
ispiv-163	18	33	~100,000	~100,000	X
ispiv-163	18	34	particles	particle	NOUN
ispiv-163	18	35	to	to	ADP
ispiv-163	18	36	75	75	NUM
ispiv-163	18	37	,	,	PUNCT
ispiv-163	18	38	50	50	NUM
ispiv-163	18	39	)	)	PUNCT
ispiv-163	18	40	.	.	PUNCT
ispiv-163	19	1	compared	compare	VERB
ispiv-163	19	2	to	to	ADP
ispiv-163	19	3	flowfit	flowfit	VERB
ispiv-163	19	4	,	,	PUNCT
ispiv-163	19	5	anfis	anfi	VERB
ispiv-163	19	6	model	model	NOUN
ispiv-163	19	7	can	can	AUX
ispiv-163	19	8	be	be	AUX
ispiv-163	19	9	well	well	ADV
ispiv-163	19	10	reconstructed	reconstruct	VERB
ispiv-163	19	11	above	above	ADP
ispiv-163	19	12	50	50	NUM
ispiv-163	19	13	%	%	NOUN
ispiv-163	19	14	particle	particle	NOUN
ispiv-163	19	15	density	density	NOUN
ispiv-163	19	16	.	.	PUNCT
ispiv-163	20	1	it	it	PRON
ispiv-163	20	2	revealed	reveal	VERB
ispiv-163	20	3	much	much	ADV
ispiv-163	20	4	more	more	ADJ
ispiv-163	20	5	small	small	ADJ
ispiv-163	20	6	-	-	PUNCT
ispiv-163	20	7	scale	scale	NOUN
ispiv-163	20	8	vortical	vortical	ADJ
ispiv-163	20	9	structures	structure	NOUN
ispiv-163	20	10	.	.	PUNCT
ispiv-163	21	1	machine	machine	NOUN
ispiv-163	21	2	learning	learning	NOUN
ispiv-163	21	3	based	base	VERB
ispiv-163	21	4	data	datum	NOUN
ispiv-163	21	5	assimilation	assimilation	NOUN
ispiv-163	21	6	provide	provide	VERB
ispiv-163	21	7	a	a	DET
ispiv-163	21	8	better	well	ADJ
ispiv-163	21	9	understanding	understanding	NOUN
ispiv-163	21	10	of	of	ADP
ispiv-163	21	11	the	the	DET
ispiv-163	21	12	small	small	ADJ
ispiv-163	21	13	turbulence	turbulence	NOUN
ispiv-163	21	14	structures	structure	NOUN
ispiv-163	21	15	and	and	CCONJ
ispiv-163	21	16	allow	allow	VERB
ispiv-163	21	17	for	for	ADP
ispiv-163	21	18	more	more	ADJ
ispiv-163	21	19	in	in	ADP
ispiv-163	21	20	-	-	PUNCT
ispiv-163	21	21	depth	depth	NOUN
ispiv-163	21	22	analysis	analysis	NOUN
ispiv-163	21	23	by	by	ADP
ispiv-163	21	24	recovering	recover	VERB
ispiv-163	21	25	data	datum	NOUN
ispiv-163	21	26	due	due	ADP
ispiv-163	21	27	to	to	ADP
ispiv-163	21	28	the	the	DET
ispiv-163	21	29	resolution	resolution	NOUN
ispiv-163	21	30	limit	limit	NOUN
ispiv-163	21	31	of	of	ADP
ispiv-163	21	32	the	the	DET
ispiv-163	21	33	experiment	experiment	NOUN
ispiv-163	21	34	.	.	PUNCT
ispiv-163	22	1	to	to	PART
ispiv-163	22	2	provide	provide	VERB
ispiv-163	22	3	a	a	DET
ispiv-163	22	4	full	full	ADJ
ispiv-163	22	5	turbulence	turbulence	NOUN
ispiv-163	22	6	spectrum	spectrum	NOUN
ispiv-163	22	7	,	,	PUNCT
ispiv-163	22	8	full	full	ADJ
ispiv-163	22	9	time	time	NOUN
ispiv-163	22	10	-	-	PUNCT
ispiv-163	22	11	series	series	NOUN
ispiv-163	22	12	of	of	ADP
ispiv-163	22	13	stb	stb	PROPN
ispiv-163	22	14	results	result	NOUN
ispiv-163	22	15	will	will	AUX
ispiv-163	22	16	later	later	ADV
ispiv-163	22	17	be	be	AUX
ispiv-163	22	18	trained	train	VERB
ispiv-163	22	19	and	and	CCONJ
ispiv-163	22	20	in	in	ADP
ispiv-163	22	21	-	-	PUNCT
ispiv-163	22	22	depth	depth	NOUN
ispiv-163	22	23	analyzed	analyze	VERB
ispiv-163	22	24	for	for	ADP
ispiv-163	22	25	anfis	anfis	ADJ
ispiv-163	22	26	training	training	NOUN
ispiv-163	22	27	.	.	PUNCT
ispiv-163	23	1	fig	fig	NOUN
ispiv-163	23	2	.	.	PUNCT
ispiv-163	24	1	2	2	NUM
ispiv-163	24	2	(	(	PUNCT
ispiv-163	24	3	top	top	NOUN
ispiv-163	24	4	)	)	PUNCT
ispiv-163	24	5	(	(	PUNCT
ispiv-163	24	6	a	a	X
ispiv-163	24	7	)	)	PUNCT
ispiv-163	24	8	raw	raw	ADJ
ispiv-163	24	9	stb	stb	NOUN
ispiv-163	24	10	result	result	NOUN
ispiv-163	24	11	(	(	PUNCT
ispiv-163	24	12	b	b	X
ispiv-163	24	13	,	,	PUNCT
ispiv-163	24	14	c	c	NOUN
ispiv-163	24	15	)	)	PUNCT
ispiv-163	24	16	downsampled	downsample	VERB
ispiv-163	24	17	stb	stb	PROPN
ispiv-163	24	18	data	datum	NOUN
ispiv-163	24	19	as	as	ADP
ispiv-163	24	20	input	input	NOUN
ispiv-163	24	21	.	.	PUNCT
ispiv-163	25	1	(	(	PUNCT
ispiv-163	25	2	bottom	bottom	ADJ
ispiv-163	25	3	)	)	PUNCT
ispiv-163	25	4	contour	contour	NOUN
ispiv-163	25	5	colored	color	VERB
ispiv-163	25	6	by	by	ADP
ispiv-163	25	7	xcomponent	xcomponent	NOUN
ispiv-163	25	8	of	of	ADP
ispiv-163	25	9	acceleration	acceleration	NOUN
ispiv-163	25	10	and	and	CCONJ
ispiv-163	25	11	iso	iso	NOUN
ispiv-163	25	12	-	-	PUNCT
ispiv-163	25	13	surface	surface	NOUN
ispiv-163	25	14	of	of	ADP
ispiv-163	25	15	q	q	NOUN
ispiv-163	25	16	-	-	PUNCT
ispiv-163	25	17	criterion	criterion	NOUN
ispiv-163	25	18	,	,	PUNCT
ispiv-163	25	19	q	q	NOUN
ispiv-163	25	20	=	=	SYM
ispiv-163	25	21	5,000	5,000	NUM
ispiv-163	25	22	s-2	s-2	NOUN
ispiv-163	25	23	from	from	ADP
ispiv-163	25	24	(	(	PUNCT
ispiv-163	25	25	a	a	PRON
ispiv-163	25	26	)	)	PUNCT
ispiv-163	25	27	flowfit	flowfit	NOUN
ispiv-163	25	28	and	and	CCONJ
ispiv-163	25	29	(	(	PUNCT
ispiv-163	25	30	b	b	NOUN
ispiv-163	25	31	,	,	PUNCT
ispiv-163	25	32	c	c	NOUN
ispiv-163	25	33	)	)	PUNCT
ispiv-163	25	34	anfis	anfis	PROPN
ispiv-163	25	35	.	.	PUNCT
ispiv-163	26	1	acknowledgements	acknowledgement	NOUN
ispiv-163	26	2	this	this	DET
ispiv-163	26	3	research	research	NOUN
ispiv-163	26	4	was	be	AUX
ispiv-163	26	5	supported	support	VERB
ispiv-163	26	6	by	by	ADP
ispiv-163	26	7	basic	basic	ADJ
ispiv-163	26	8	science	science	NOUN
ispiv-163	26	9	research	research	NOUN
ispiv-163	26	10	program	program	NOUN
ispiv-163	26	11	through	through	ADP
ispiv-163	26	12	the	the	DET
ispiv-163	26	13	national	national	PROPN
ispiv-163	26	14	research	research	PROPN
ispiv-163	26	15	foundation	foundation	PROPN
ispiv-163	26	16	of	of	ADP
ispiv-163	26	17	korea	korea	PROPN
ispiv-163	26	18	(	(	PUNCT
ispiv-163	26	19	nrf	nrf	NOUN
ispiv-163	26	20	)	)	PUNCT
ispiv-163	26	21	funded	fund	VERB
ispiv-163	26	22	by	by	ADP
ispiv-163	26	23	the	the	DET
ispiv-163	26	24	ministry	ministry	PROPN
ispiv-163	26	25	of	of	ADP
ispiv-163	26	26	education	education	PROPN
ispiv-163	26	27	(	(	PUNCT
ispiv-163	26	28	2020r1a6a3a03038341	2020r1a6a3a03038341	NUM
ispiv-163	26	29	)	)	PUNCT
ispiv-163	26	30	and	and	CCONJ
ispiv-163	26	31	the	the	DET
ispiv-163	26	32	korean	korean	ADJ
ispiv-163	26	33	government	government	NOUN
ispiv-163	26	34	(	(	PUNCT
ispiv-163	26	35	msit	msit	PROPN
ispiv-163	26	36	)	)	PUNCT
ispiv-163	26	37	(	(	PUNCT
ispiv-163	26	38	2021r1c1c2011538	2021r1c1c2011538	NUM
ispiv-163	26	39	)	)	PUNCT
ispiv-163	26	40	.	.	PUNCT
ispiv-163	27	1	we	we	PRON
ispiv-163	27	2	acknowledge	acknowledge	VERB
ispiv-163	27	3	daniel	daniel	PROPN
ispiv-163	27	4	schanz	schanz	PROPN
ispiv-163	27	5	,	,	PUNCT
ispiv-163	27	6	florian	florian	PROPN
ispiv-163	27	7	huhn	huhn	PROPN
ispiv-163	27	8	,	,	PUNCT
ispiv-163	27	9	sebastian	sebastian	PROPN
ispiv-163	27	10	gesemann	gesemann	PROPN
ispiv-163	27	11	and	and	CCONJ
ispiv-163	27	12	andreras	andrera	NOUN
ispiv-163	27	13	schröder	schröder	NOUN
ispiv-163	27	14	(	(	PUNCT
ispiv-163	27	15	german	german	ADJ
ispiv-163	27	16	aerospace	aerospace	NOUN
ispiv-163	27	17	center	center	NOUN
ispiv-163	27	18	)	)	PUNCT
ispiv-163	27	19	for	for	ADP
ispiv-163	27	20	providing	provide	VERB
ispiv-163	27	21	the	the	DET
ispiv-163	27	22	lpt	lpt	PROPN
ispiv-163	27	23	and	and	CCONJ
ispiv-163	27	24	flowfit	flowfit	PROPN
ispiv-163	27	25	data	data	PROPN
ispiv-163	27	26	,	,	PUNCT
ispiv-163	27	27	daniel	daniel	PROPN
ispiv-163	27	28	garaboa	garaboa	PROPN
ispiv-163	27	29	-	-	PUNCT
ispiv-163	27	30	paz	paz	NOUN
ispiv-163	27	31	(	(	PUNCT
ispiv-163	27	32	university	university	NOUN
ispiv-163	27	33	of	of	ADP
ispiv-163	27	34	santiago	santiago	PROPN
ispiv-163	27	35	de	de	X
ispiv-163	27	36	compostella	compostella	PROPN
ispiv-163	27	37	)	)	PUNCT
ispiv-163	27	38	and	and	CCONJ
ispiv-163	27	39	eberhard	eberhard	NOUN
ispiv-163	27	40	bodenschatz	bodenschatz	NOUN
ispiv-163	27	41	(	(	PUNCT
ispiv-163	27	42	max	max	PROPN
ispiv-163	27	43	-	-	PUNCT
ispiv-163	27	44	planck	planck	NOUN
ispiv-163	27	45	institute	institute	NOUN
ispiv-163	27	46	for	for	ADP
ispiv-163	27	47	dynamics	dynamic	NOUN
ispiv-163	27	48	and	and	CCONJ
ispiv-163	27	49	self	self	NOUN
ispiv-163	27	50	-	-	PUNCT
ispiv-163	27	51	organization	organization	NOUN
ispiv-163	27	52	)	)	PUNCT
ispiv-163	27	53	are	be	AUX
ispiv-163	27	54	acknowledged	acknowledge	VERB
ispiv-163	27	55	for	for	ADP
ispiv-163	27	56	their	their	PRON
ispiv-163	27	57	contributions	contribution	NOUN
ispiv-163	27	58	to	to	ADP
ispiv-163	27	59	the	the	DET
ispiv-163	27	60	experiment	experiment	NOUN
ispiv-163	27	61	references	reference	NOUN
ispiv-163	27	62	[	[	X
ispiv-163	27	63	1	1	NUM
ispiv-163	27	64	]	]	X
ispiv-163	27	65	schröder	schröder	NOUN
ispiv-163	27	66	,	,	PUNCT
ispiv-163	27	67	a.	a.	PROPN
ispiv-163	27	68	,	,	PUNCT
ispiv-163	27	69	et	et	PROPN
ispiv-163	27	70	al	al	PROPN
ispiv-163	27	71	.	.	PROPN
ispiv-163	28	1	(	(	PUNCT
ispiv-163	28	2	2019	2019	NUM
ispiv-163	28	3	)	)	PUNCT
ispiv-163	28	4	measuring	measure	VERB
ispiv-163	28	5	the	the	DET
ispiv-163	28	6	full	full	ADJ
ispiv-163	28	7	velocity	velocity	NOUN
ispiv-163	28	8	gradient	gradient	NOUN
ispiv-163	28	9	and	and	CCONJ
ispiv-163	28	10	dissipation	dissipation	NOUN
ispiv-163	28	11	rate	rate	NOUN
ispiv-163	28	12	tensor	tensor	NOUN
ispiv-163	28	13	in	in	ADP
ispiv-163	28	14	homogeneous	homogeneous	ADJ
ispiv-163	28	15	turbulence	turbulence	NOUN
ispiv-163	28	16	using	use	VERB
ispiv-163	28	17	shake	shake	NOUN
ispiv-163	28	18	-	-	PUNCT
ispiv-163	28	19	the	the	DET
ispiv-163	28	20	-	-	PUNCT
ispiv-163	28	21	box	box	NOUN
ispiv-163	28	22	and	and	CCONJ
ispiv-163	28	23	flowfit	flowfit	NOUN
ispiv-163	28	24	.	.	PUNCT
ispiv-163	29	1	17th	17th	ADJ
ispiv-163	29	2	etc	etc	X
ispiv-163	29	3	,	,	PUNCT
ispiv-163	29	4	torino	torino	PROPN
ispiv-163	29	5	,	,	PUNCT
ispiv-163	29	6	italy	italy	PROPN
ispiv-163	29	7	.	.	PUNCT
ispiv-163	30	1	[	[	X
ispiv-163	30	2	2	2	NUM
ispiv-163	30	3	]	]	X
ispiv-163	30	4	gesemann	gesemann	PROPN
ispiv-163	30	5	,	,	PUNCT
ispiv-163	30	6	s.	s.	PROPN
ispiv-163	30	7	,	,	PUNCT
ispiv-163	30	8	huhn	huhn	PROPN
ispiv-163	30	9	,	,	PUNCT
ispiv-163	30	10	f.	f.	PROPN
ispiv-163	30	11	,	,	PUNCT
ispiv-163	30	12	schanz	schanz	PROPN
ispiv-163	30	13	,	,	PUNCT
ispiv-163	30	14	d.	d.	PROPN
ispiv-163	30	15	,	,	PUNCT
ispiv-163	30	16	&	&	CCONJ
ispiv-163	30	17	schröder	schröder	PROPN
ispiv-163	30	18	,	,	PUNCT
ispiv-163	30	19	a.	a.	NOUN
ispiv-163	30	20	(	(	PUNCT
ispiv-163	30	21	2016	2016	NUM
ispiv-163	30	22	)	)	PUNCT
ispiv-163	30	23	from	from	ADP
ispiv-163	30	24	noisy	noisy	ADJ
ispiv-163	30	25	particle	particle	NOUN
ispiv-163	30	26	tracks	track	NOUN
ispiv-163	30	27	to	to	ADP
ispiv-163	30	28	velocity	velocity	NOUN
ispiv-163	30	29	,	,	PUNCT
ispiv-163	30	30	acceleration	acceleration	NOUN
ispiv-163	30	31	and	and	CCONJ
ispiv-163	30	32	pressure	pressure	NOUN
ispiv-163	30	33	fields	field	NOUN
ispiv-163	30	34	using	use	VERB
ispiv-163	30	35	b	b	NOUN
ispiv-163	30	36	-	-	PUNCT
ispiv-163	30	37	splines	spline	NOUN
ispiv-163	30	38	and	and	CCONJ
ispiv-163	30	39	penalties	penalty	NOUN
ispiv-163	30	40	.	.	PUNCT
ispiv-163	31	1	in	in	ADP
ispiv-163	31	2	18th	18th	ADJ
ispiv-163	31	3	lxlaser	lxlaser	NOUN
ispiv-163	31	4	,	,	PUNCT
ispiv-163	31	5	lisbon	lisbon	PROPN
ispiv-163	31	6	,	,	PUNCT
ispiv-163	31	7	portugal	portugal	PROPN
ispiv-163	31	8	,	,	PUNCT
ispiv-163	31	9	4	4	NUM
ispiv-163	31	10	-	-	SYM
ispiv-163	31	11	7	7	NUM
ispiv-163	31	12	.	.	PUNCT
ispiv-163	32	1	[	[	X
ispiv-163	32	2	3	3	X
ispiv-163	32	3	]	]	X
ispiv-163	32	4	kim	kim	PROPN
ispiv-163	32	5	,	,	PUNCT
ispiv-163	32	6	d.	d.	PROPN
ispiv-163	32	7	,	,	PUNCT
ispiv-163	32	8	safdari	safdari	PROPN
ispiv-163	32	9	,	,	PUNCT
ispiv-163	32	10	a.	a.	NOUN
ispiv-163	32	11	,	,	PUNCT
ispiv-163	32	12	&	&	CCONJ
ispiv-163	32	13	kim	kim	PROPN
ispiv-163	32	14	,	,	PUNCT
ispiv-163	32	15	k.	k.	PROPN
ispiv-163	32	16	c.	c.	PROPN
ispiv-163	32	17	(	(	PUNCT
ispiv-163	32	18	2021	2021	NUM
ispiv-163	32	19	)	)	PUNCT
ispiv-163	32	20	sound	sound	NOUN
ispiv-163	32	21	pressure	pressure	NOUN
ispiv-163	32	22	level	level	NOUN
ispiv-163	32	23	spectrum	spectrum	NOUN
ispiv-163	32	24	analysis	analysis	NOUN
ispiv-163	32	25	by	by	ADP
ispiv-163	32	26	combination	combination	NOUN
ispiv-163	32	27	of	of	ADP
ispiv-163	32	28	4d	4d	NUM
ispiv-163	32	29	ptv	ptv	NOUN
ispiv-163	32	30	and	and	CCONJ
ispiv-163	32	31	anfis	anfi	VERB
ispiv-163	32	32	method	method	NOUN
ispiv-163	32	33	around	around	ADP
ispiv-163	32	34	automotive	automotive	ADJ
ispiv-163	32	35	side	side	NOUN
ispiv-163	32	36	-	-	PUNCT
ispiv-163	32	37	view	view	NOUN
ispiv-163	32	38	mirror	mirror	NOUN
ispiv-163	32	39	models	model	NOUN
ispiv-163	32	40	.	.	PUNCT
ispiv-163	33	1	scientific	scientific	ADJ
ispiv-163	33	2	reports	report	NOUN
ispiv-163	33	3	,	,	PUNCT
ispiv-163	33	4	11(1	11(1	NUM
ispiv-163	33	5	)	)	PUNCT
ispiv-163	33	6	,	,	PUNCT
ispiv-163	33	7	1	1	NUM
ispiv-163	33	8	-	-	SYM
ispiv-163	33	9	15	15	NUM
ispiv-163	33	10	.	.	PUNCT