id	sid	tid	token	lemma	pos
fcis-31661	1	1	frontiers	frontier	NOUN
fcis-31661	1	2	in	in	ADP
fcis-31661	1	3	computing	computing	NOUN
fcis-31661	1	4	and	and	CCONJ
fcis-31661	1	5	intelligent	intelligent	ADJ
fcis-31661	1	6	systems	system	NOUN
fcis-31661	1	7	issn	issn	VERB
fcis-31661	1	8	:	:	PUNCT
fcis-31661	1	9	2832	2832	NUM
fcis-31661	1	10	-	-	SYM
fcis-31661	1	11	6024	6024	NUM
fcis-31661	1	12	|	|	NOUN
fcis-31661	1	13	vol	vol	NOUN
fcis-31661	1	14	.	.	PROPN
fcis-31661	2	1	13	13	NUM
fcis-31661	2	2	,	,	PUNCT
fcis-31661	2	3	no	no	INTJ
fcis-31661	2	4	.	.	NOUN
fcis-31661	2	5	2	2	NUM
fcis-31661	2	6	,	,	PUNCT
fcis-31661	2	7	2025	2025	NUM
fcis-31661	2	8	89	89	NUM
fcis-31661	2	9	research	research	NOUN
fcis-31661	2	10	on	on	ADP
fcis-31661	2	11	apple	apple	NOUN
fcis-31661	2	12	internal	internal	ADJ
fcis-31661	2	13	quality	quality	NOUN
fcis-31661	2	14	classification	classification	NOUN
fcis-31661	2	15	based	base	VERB
fcis-31661	2	16	on	on	ADP
fcis-31661	2	17	near‐infrared	near‐infrared	ADJ
fcis-31661	2	18	spectroscopy	spectroscopy	NOUN
fcis-31661	2	19	zhipeng	zhipeng	PROPN
fcis-31661	2	20	li	li	PROPN
fcis-31661	3	1	*	*	PUNCT
fcis-31661	3	2	school	school	NOUN
fcis-31661	3	3	of	of	ADP
fcis-31661	3	4	electronic	electronic	ADJ
fcis-31661	3	5	information	information	NOUN
fcis-31661	3	6	,	,	PUNCT
fcis-31661	3	7	xijing	xijing	PROPN
fcis-31661	3	8	university	university	PROPN
fcis-31661	3	9	,	,	PUNCT
fcis-31661	3	10	xi	xi	ADP
fcis-31661	3	11	'	'	PUNCT
fcis-31661	3	12	an	an	INTJ
fcis-31661	3	13	,	,	PUNCT
fcis-31661	3	14	shaanxi	shaanxi	PROPN
fcis-31661	3	15	,	,	PUNCT
fcis-31661	3	16	china	china	PROPN
fcis-31661	3	17	*	*	PUNCT
fcis-31661	3	18	corresponding	correspond	VERB
fcis-31661	3	19	author	author	NOUN
fcis-31661	3	20	email	email	NOUN
fcis-31661	3	21	:	:	PUNCT
fcis-31661	3	22	3473326046@qq.com	3473326046@qq.com	NUM
fcis-31661	3	23	abstract	abstract	NOUN
fcis-31661	3	24	:	:	PUNCT
fcis-31661	3	25	in	in	ADP
fcis-31661	3	26	this	this	DET
fcis-31661	3	27	study	study	NOUN
fcis-31661	3	28	,	,	PUNCT
fcis-31661	3	29	luochuan	luochuan	PROPN
fcis-31661	3	30	red	red	PROPN
fcis-31661	3	31	fuji	fuji	PROPN
fcis-31661	3	32	apple	apple	PROPN
fcis-31661	3	33	in	in	ADP
fcis-31661	3	34	shaanxi	shaanxi	PROPN
fcis-31661	3	35	province	province	PROPN
fcis-31661	3	36	was	be	AUX
fcis-31661	3	37	taken	take	VERB
fcis-31661	3	38	as	as	ADP
fcis-31661	3	39	the	the	DET
fcis-31661	3	40	experimental	experimental	ADJ
fcis-31661	3	41	object	object	NOUN
fcis-31661	3	42	,	,	PUNCT
fcis-31661	3	43	and	and	CCONJ
fcis-31661	3	44	the	the	DET
fcis-31661	3	45	sugar	sugar	NOUN
fcis-31661	3	46	content	content	NOUN
fcis-31661	3	47	and	and	CCONJ
fcis-31661	3	48	spectral	spectral	ADJ
fcis-31661	3	49	data	datum	NOUN
fcis-31661	3	50	were	be	AUX
fcis-31661	3	51	measured	measure	VERB
fcis-31661	3	52	and	and	CCONJ
fcis-31661	3	53	averaged	average	VERB
fcis-31661	3	54	at	at	ADP
fcis-31661	3	55	three	three	NUM
fcis-31661	3	56	locations	location	NOUN
fcis-31661	3	57	at	at	ADP
fcis-31661	3	58	the	the	DET
fcis-31661	3	59	upper	upper	ADJ
fcis-31661	3	60	distance	distance	NOUN
fcis-31661	3	61	of	of	ADP
fcis-31661	3	62	the	the	DET
fcis-31661	3	63	equator	equator	NOUN
fcis-31661	3	64	.	.	PUNCT
fcis-31661	4	1	spxy	spxy	PROPN
fcis-31661	4	2	method	method	NOUN
fcis-31661	4	3	was	be	AUX
fcis-31661	4	4	used	use	VERB
fcis-31661	4	5	to	to	PART
fcis-31661	4	6	divide	divide	VERB
fcis-31661	4	7	the	the	DET
fcis-31661	4	8	data	datum	NOUN
fcis-31661	4	9	set	set	VERB
fcis-31661	4	10	,	,	PUNCT
fcis-31661	4	11	mas	mas	PROPN
fcis-31661	4	12	,	,	PUNCT
fcis-31661	4	13	snv	snv	PROPN
fcis-31661	4	14	,	,	PUNCT
fcis-31661	4	15	mc	mc	PROPN
fcis-31661	4	16	three	three	NUM
fcis-31661	4	17	data	datum	NOUN
fcis-31661	4	18	preprocessing	preprocessing	NOUN
fcis-31661	4	19	methods	method	NOUN
fcis-31661	4	20	were	be	AUX
fcis-31661	4	21	used	use	VERB
fcis-31661	4	22	,	,	PUNCT
fcis-31661	4	23	and	and	CCONJ
fcis-31661	4	24	cars	car	NOUN
fcis-31661	4	25	were	be	AUX
fcis-31661	4	26	used	use	VERB
fcis-31661	4	27	to	to	PART
fcis-31661	4	28	select	select	VERB
fcis-31661	4	29	the	the	DET
fcis-31661	4	30	characteristic	characteristic	ADJ
fcis-31661	4	31	wavelength	wavelength	NOUN
fcis-31661	4	32	,	,	PUNCT
fcis-31661	4	33	and	and	CCONJ
fcis-31661	4	34	three	three	NUM
fcis-31661	4	35	classification	classification	NOUN
fcis-31661	4	36	models	model	NOUN
fcis-31661	4	37	svc	svc	PROPN
fcis-31661	4	38	,	,	PUNCT
fcis-31661	4	39	dt	dt	PUNCT
fcis-31661	4	40	and	and	CCONJ
fcis-31661	4	41	knn	knn	PROPN
fcis-31661	4	42	were	be	AUX
fcis-31661	4	43	established	establish	VERB
fcis-31661	4	44	.	.	PUNCT
fcis-31661	5	1	the	the	DET
fcis-31661	5	2	results	result	NOUN
fcis-31661	5	3	show	show	VERB
fcis-31661	5	4	that	that	SCONJ
fcis-31661	5	5	spxy	spxy	VERB
fcis-31661	5	6	+	+	CCONJ
fcis-31661	5	7	mc	mc	PROPN
fcis-31661	5	8	+	+	NUM
fcis-31661	5	9	cars	car	NOUN
fcis-31661	5	10	+	+	CCONJ
fcis-31661	5	11	dt	dt	NOUN
fcis-31661	5	12	model	model	NOUN
fcis-31661	5	13	has	have	VERB
fcis-31661	5	14	the	the	DET
fcis-31661	5	15	best	good	ADJ
fcis-31661	5	16	classification	classification	NOUN
fcis-31661	5	17	results	result	NOUN
fcis-31661	5	18	,	,	PUNCT
fcis-31661	5	19	and	and	CCONJ
fcis-31661	5	20	the	the	DET
fcis-31661	5	21	accuracy	accuracy	NOUN
fcis-31661	5	22	rate	rate	NOUN
fcis-31661	5	23	,	,	PUNCT
fcis-31661	5	24	accuracy	accuracy	NOUN
fcis-31661	5	25	rate	rate	NOUN
fcis-31661	5	26	,	,	PUNCT
fcis-31661	5	27	recall	recall	NOUN
fcis-31661	5	28	rate	rate	NOUN
fcis-31661	5	29	and	and	CCONJ
fcis-31661	5	30	f1	f1	NOUN
fcis-31661	5	31	score	score	NOUN
fcis-31661	5	32	reach	reach	VERB
fcis-31661	5	33	0.955	0.955	NUM
fcis-31661	5	34	respectively	respectively	ADV
fcis-31661	5	35	.	.	PUNCT
fcis-31661	6	1	in	in	ADP
fcis-31661	6	2	summary	summary	NOUN
fcis-31661	6	3	,	,	PUNCT
fcis-31661	6	4	the	the	DET
fcis-31661	6	5	use	use	NOUN
fcis-31661	6	6	of	of	ADP
fcis-31661	6	7	near	near	ADV
fcis-31661	6	8	-	-	PUNCT
fcis-31661	6	9	infrared	infrared	ADJ
fcis-31661	6	10	spectroscopy	spectroscopy	NOUN
fcis-31661	6	11	technology	technology	NOUN
fcis-31661	6	12	can	can	AUX
fcis-31661	6	13	be	be	AUX
fcis-31661	6	14	used	use	VERB
fcis-31661	6	15	in	in	ADP
fcis-31661	6	16	apple	apple	NOUN
fcis-31661	6	17	's	's	PART
fcis-31661	6	18	internal	internal	ADJ
fcis-31661	6	19	quality	quality	NOUN
fcis-31661	6	20	classification	classification	NOUN
fcis-31661	6	21	,	,	PUNCT
fcis-31661	6	22	which	which	PRON
fcis-31661	6	23	improves	improve	VERB
fcis-31661	6	24	the	the	DET
fcis-31661	6	25	basis	basis	NOUN
fcis-31661	6	26	and	and	CCONJ
fcis-31661	6	27	reference	reference	NOUN
fcis-31661	6	28	for	for	ADP
fcis-31661	6	29	the	the	DET
fcis-31661	6	30	application	application	NOUN
fcis-31661	6	31	of	of	ADP
fcis-31661	6	32	apple	apple	NOUN
fcis-31661	6	33	's	's	PART
fcis-31661	6	34	non	non	ADJ
fcis-31661	6	35	-	-	ADJ
fcis-31661	6	36	destructive	destructive	ADJ
fcis-31661	6	37	testing	testing	NOUN
fcis-31661	6	38	technology	technology	NOUN
fcis-31661	6	39	.	.	PUNCT
fcis-31661	7	1	keywords	keyword	NOUN
fcis-31661	7	2	:	:	PUNCT
fcis-31661	7	3	apple	apple	NOUN
fcis-31661	7	4	;	;	PUNCT
fcis-31661	7	5	near	near	ADP
fcis-31661	7	6	infrared	infrared	ADJ
fcis-31661	7	7	spectroscopy	spectroscopy	NOUN
fcis-31661	7	8	;	;	PUNCT
fcis-31661	7	9	nondestructive	nondestructive	ADJ
fcis-31661	7	10	testing	testing	NOUN
fcis-31661	7	11	;	;	PUNCT
fcis-31661	7	12	internal	internal	ADJ
fcis-31661	7	13	quality	quality	NOUN
fcis-31661	7	14	;	;	PUNCT
fcis-31661	7	15	classification	classification	NOUN
fcis-31661	7	16	model	model	NOUN
fcis-31661	7	17	.	.	PUNCT
fcis-31661	8	1	1	1	X
fcis-31661	8	2	.	.	X
fcis-31661	8	3	introduction	introduction	NOUN
fcis-31661	8	4	with	with	ADP
fcis-31661	8	5	the	the	DET
fcis-31661	8	6	improvement	improvement	NOUN
fcis-31661	8	7	of	of	ADP
fcis-31661	8	8	people	people	NOUN
fcis-31661	8	9	's	's	PART
fcis-31661	8	10	living	living	NOUN
fcis-31661	8	11	standards	standard	NOUN
fcis-31661	8	12	and	and	CCONJ
fcis-31661	8	13	the	the	DET
fcis-31661	8	14	development	development	NOUN
fcis-31661	8	15	and	and	CCONJ
fcis-31661	8	16	progress	progress	NOUN
fcis-31661	8	17	of	of	ADP
fcis-31661	8	18	society	society	NOUN
fcis-31661	8	19	,	,	PUNCT
fcis-31661	8	20	more	more	ADJ
fcis-31661	8	21	and	and	CCONJ
fcis-31661	8	22	more	more	ADJ
fcis-31661	8	23	consumers	consumer	NOUN
fcis-31661	8	24	are	be	AUX
fcis-31661	8	25	constantly	constantly	ADV
fcis-31661	8	26	raising	raise	VERB
fcis-31661	8	27	their	their	PRON
fcis-31661	8	28	requirements	requirement	NOUN
fcis-31661	8	29	for	for	ADP
fcis-31661	8	30	the	the	DET
fcis-31661	8	31	quality	quality	NOUN
fcis-31661	8	32	of	of	ADP
fcis-31661	8	33	food	food	NOUN
fcis-31661	8	34	.	.	PUNCT
fcis-31661	9	1	apples	apple	NOUN
fcis-31661	9	2	are	be	AUX
fcis-31661	9	3	a	a	DET
fcis-31661	9	4	kind	kind	NOUN
fcis-31661	9	5	of	of	ADP
fcis-31661	9	6	fruit	fruit	NOUN
fcis-31661	9	7	rich	rich	ADJ
fcis-31661	9	8	in	in	ADP
fcis-31661	9	9	various	various	ADJ
fcis-31661	9	10	vitamins	vitamin	NOUN
fcis-31661	9	11	and	and	CCONJ
fcis-31661	9	12	minerals	mineral	NOUN
fcis-31661	9	13	.	.	PUNCT
fcis-31661	10	1	they	they	PRON
fcis-31661	10	2	are	be	AUX
fcis-31661	10	3	highly	highly	ADV
fcis-31661	10	4	nutritious	nutritious	ADJ
fcis-31661	10	5	and	and	CCONJ
fcis-31661	10	6	beneficial	beneficial	ADJ
fcis-31661	10	7	to	to	ADP
fcis-31661	10	8	human	human	ADJ
fcis-31661	10	9	health	health	NOUN
fcis-31661	10	10	,	,	PUNCT
fcis-31661	10	11	and	and	CCONJ
fcis-31661	10	12	are	be	AUX
fcis-31661	10	13	deeply	deeply	ADV
fcis-31661	10	14	loved	love	VERB
fcis-31661	10	15	by	by	ADP
fcis-31661	10	16	consumers	consumer	NOUN
fcis-31661	10	17	.	.	PUNCT
fcis-31661	11	1	all	all	ADV
fcis-31661	11	2	along	along	ADV
fcis-31661	11	3	,	,	PUNCT
fcis-31661	11	4	the	the	DET
fcis-31661	11	5	external	external	ADJ
fcis-31661	11	6	quality	quality	NOUN
fcis-31661	11	7	of	of	ADP
fcis-31661	11	8	apples	apple	NOUN
fcis-31661	11	9	has	have	AUX
fcis-31661	11	10	always	always	ADV
fcis-31661	11	11	been	be	AUX
fcis-31661	11	12	the	the	DET
fcis-31661	11	13	focus	focus	NOUN
fcis-31661	11	14	of	of	ADP
fcis-31661	11	15	people	people	NOUN
fcis-31661	11	16	's	's	PART
fcis-31661	11	17	attention	attention	NOUN
fcis-31661	11	18	when	when	SCONJ
fcis-31661	11	19	purchasing	purchase	VERB
fcis-31661	11	20	,	,	PUNCT
fcis-31661	11	21	but	but	CCONJ
fcis-31661	11	22	the	the	DET
fcis-31661	11	23	internal	internal	ADJ
fcis-31661	11	24	quality	quality	NOUN
fcis-31661	11	25	is	be	AUX
fcis-31661	11	26	often	often	ADV
fcis-31661	11	27	the	the	DET
fcis-31661	11	28	decisive	decisive	ADJ
fcis-31661	11	29	factor	factor	NOUN
fcis-31661	11	30	determining	determine	VERB
fcis-31661	11	31	the	the	DET
fcis-31661	11	32	taste	taste	NOUN
fcis-31661	11	33	and	and	CCONJ
fcis-31661	11	34	nutritional	nutritional	ADJ
fcis-31661	11	35	value	value	NOUN
fcis-31661	11	36	of	of	ADP
fcis-31661	11	37	apples	apple	NOUN
fcis-31661	11	38	.	.	PUNCT
fcis-31661	12	1	throughout	throughout	ADP
fcis-31661	12	2	the	the	DET
fcis-31661	12	3	entire	entire	ADJ
fcis-31661	12	4	growth	growth	NOUN
fcis-31661	12	5	process	process	NOUN
fcis-31661	12	6	of	of	ADP
fcis-31661	12	7	the	the	DET
fcis-31661	12	8	fruit	fruit	NOUN
fcis-31661	12	9	,	,	PUNCT
fcis-31661	12	10	the	the	DET
fcis-31661	12	11	soluble	soluble	ADJ
fcis-31661	12	12	solids	solid	NOUN
fcis-31661	12	13	in	in	ADP
fcis-31661	12	14	apples	apple	NOUN
fcis-31661	12	15	are	be	AUX
fcis-31661	12	16	the	the	DET
fcis-31661	12	17	key	key	NOUN
fcis-31661	12	18	to	to	ADP
fcis-31661	12	19	determining	determine	VERB
fcis-31661	12	20	the	the	DET
fcis-31661	12	21	internal	internal	ADJ
fcis-31661	12	22	quality	quality	NOUN
fcis-31661	12	23	and	and	CCONJ
fcis-31661	12	24	play	play	VERB
fcis-31661	12	25	a	a	DET
fcis-31661	12	26	crucial	crucial	ADJ
fcis-31661	12	27	role	role	NOUN
fcis-31661	12	28	in	in	ADP
fcis-31661	12	29	the	the	DET
fcis-31661	12	30	market	market	NOUN
fcis-31661	12	31	value	value	NOUN
fcis-31661	12	32	of	of	ADP
fcis-31661	12	33	apples	apple	NOUN
fcis-31661	12	34	.	.	PUNCT
fcis-31661	13	1	soluble	soluble	ADJ
fcis-31661	13	2	solids	solid	NOUN
fcis-31661	13	3	are	be	AUX
fcis-31661	13	4	one	one	NUM
fcis-31661	13	5	of	of	ADP
fcis-31661	13	6	the	the	DET
fcis-31661	13	7	main	main	ADJ
fcis-31661	13	8	factors	factor	NOUN
fcis-31661	13	9	reflecting	reflect	VERB
fcis-31661	13	10	the	the	DET
fcis-31661	13	11	internal	internal	ADJ
fcis-31661	13	12	quality	quality	NOUN
fcis-31661	13	13	and	and	CCONJ
fcis-31661	13	14	maturity	maturity	NOUN
fcis-31661	13	15	of	of	ADP
fcis-31661	13	16	apples	apple	NOUN
fcis-31661	13	17	,	,	PUNCT
fcis-31661	13	18	among	among	ADP
fcis-31661	13	19	which	which	PRON
fcis-31661	13	20	sugar	sugar	NOUN
fcis-31661	13	21	content	content	NOUN
fcis-31661	13	22	is	be	AUX
fcis-31661	13	23	the	the	DET
fcis-31661	13	24	most	most	ADV
fcis-31661	13	25	crucial	crucial	ADJ
fcis-31661	13	26	indicator	indicator	NOUN
fcis-31661	13	27	of	of	ADP
fcis-31661	13	28	soluble	soluble	ADJ
fcis-31661	13	29	solids	solid	NOUN
fcis-31661	13	30	.	.	PUNCT
fcis-31661	14	1	therefore	therefore	ADV
fcis-31661	14	2	,	,	PUNCT
fcis-31661	14	3	determining	determine	VERB
fcis-31661	14	4	the	the	DET
fcis-31661	14	5	sugar	sugar	NOUN
fcis-31661	14	6	content	content	NOUN
fcis-31661	14	7	of	of	ADP
fcis-31661	14	8	apples	apple	NOUN
fcis-31661	14	9	and	and	CCONJ
fcis-31661	14	10	classifying	classify	VERB
fcis-31661	14	11	them	they	PRON
fcis-31661	14	12	based	base	VERB
fcis-31661	14	13	on	on	ADP
fcis-31661	14	14	their	their	PRON
fcis-31661	14	15	internal	internal	ADJ
fcis-31661	14	16	quality	quality	NOUN
fcis-31661	14	17	is	be	AUX
fcis-31661	14	18	of	of	ADP
fcis-31661	14	19	great	great	ADJ
fcis-31661	14	20	significance	significance	NOUN
fcis-31661	14	21	for	for	ADP
fcis-31661	14	22	the	the	DET
fcis-31661	14	23	post	post	ADJ
fcis-31661	14	24	-	-	ADJ
fcis-31661	14	25	harvest	harvest	ADJ
fcis-31661	14	26	grading	grade	VERB
fcis-31661	14	27	processing	processing	NOUN
fcis-31661	14	28	of	of	ADP
fcis-31661	14	29	apples	apple	NOUN
fcis-31661	14	30	and	and	CCONJ
fcis-31661	14	31	improving	improve	VERB
fcis-31661	14	32	commercial	commercial	ADJ
fcis-31661	14	33	benefits	benefit	NOUN
fcis-31661	14	34	.	.	PUNCT
fcis-31661	15	1	2	2	X
fcis-31661	15	2	.	.	X
fcis-31661	15	3	experimental	experimental	ADJ
fcis-31661	15	4	materials	material	NOUN
fcis-31661	15	5	and	and	CCONJ
fcis-31661	15	6	methods	method	NOUN
fcis-31661	15	7	2.1	2.1	NUM
fcis-31661	15	8	.	.	PUNCT
fcis-31661	16	1	materials	material	NOUN
fcis-31661	16	2	and	and	CCONJ
fcis-31661	16	3	instruments	instrument	NOUN
fcis-31661	16	4	a	a	DET
fcis-31661	16	5	total	total	NOUN
fcis-31661	16	6	of	of	ADP
fcis-31661	16	7	112	112	NUM
fcis-31661	16	8	red	red	ADJ
fcis-31661	16	9	fuji	fuji	PROPN
fcis-31661	16	10	apples	apple	NOUN
fcis-31661	16	11	from	from	ADP
fcis-31661	16	12	luochuan	luochuan	PROPN
fcis-31661	16	13	,	,	PUNCT
fcis-31661	16	14	shaanxi	shaanxi	PROPN
fcis-31661	16	15	province	province	PROPN
fcis-31661	16	16	,	,	PUNCT
fcis-31661	16	17	with	with	ADP
fcis-31661	16	18	uniform	uniform	ADJ
fcis-31661	16	19	color	color	NOUN
fcis-31661	16	20	,	,	PUNCT
fcis-31661	16	21	consistent	consistent	ADJ
fcis-31661	16	22	size	size	NOUN
fcis-31661	16	23	and	and	CCONJ
fcis-31661	16	24	no	no	DET
fcis-31661	16	25	external	external	ADJ
fcis-31661	16	26	damage	damage	NOUN
fcis-31661	16	27	,	,	PUNCT
fcis-31661	16	28	were	be	AUX
fcis-31661	16	29	selected	select	VERB
fcis-31661	16	30	as	as	ADP
fcis-31661	16	31	experimental	experimental	ADJ
fcis-31661	16	32	samples	sample	NOUN
fcis-31661	16	33	.	.	PUNCT
fcis-31661	17	1	all	all	DET
fcis-31661	17	2	apple	apple	NOUN
fcis-31661	17	3	samples	sample	NOUN
fcis-31661	17	4	completed	complete	VERB
fcis-31661	17	5	spectral	spectral	ADJ
fcis-31661	17	6	data	datum	NOUN
fcis-31661	17	7	collection	collection	NOUN
fcis-31661	17	8	and	and	CCONJ
fcis-31661	17	9	sugar	sugar	NOUN
fcis-31661	17	10	content	content	NOUN
fcis-31661	17	11	determination	determination	NOUN
fcis-31661	17	12	at	at	ADP
fcis-31661	17	13	the	the	DET
fcis-31661	17	14	same	same	ADJ
fcis-31661	17	15	experimental	experimental	ADJ
fcis-31661	17	16	site	site	NOUN
fcis-31661	17	17	on	on	ADP
fcis-31661	17	18	the	the	DET
fcis-31661	17	19	same	same	ADJ
fcis-31661	17	20	day	day	NOUN
fcis-31661	17	21	.	.	PUNCT
fcis-31661	18	1	the	the	DET
fcis-31661	18	2	near	near	ADV
fcis-31661	18	3	-	-	PUNCT
fcis-31661	18	4	infrared	infrared	ADJ
fcis-31661	18	5	spectral	spectral	ADJ
fcis-31661	18	6	data	datum	NOUN
fcis-31661	18	7	of	of	ADP
fcis-31661	18	8	apple	apple	NOUN
fcis-31661	18	9	samples	sample	NOUN
fcis-31661	18	10	were	be	AUX
fcis-31661	18	11	collected	collect	VERB
fcis-31661	18	12	using	use	VERB
fcis-31661	18	13	a	a	DET
fcis-31661	18	14	near	near	ADV
fcis-31661	18	15	-	-	PUNCT
fcis-31661	18	16	infrared	infrared	ADJ
fcis-31661	18	17	spectrometer	spectrometer	NOUN
fcis-31661	18	18	(	(	PUNCT
fcis-31661	18	19	model	model	PROPN
fcis-31661	18	20	atp8600	atp8600	PROPN
fcis-31661	18	21	,	,	PUNCT
fcis-31661	18	22	wavelength	wavelength	NOUN
fcis-31661	18	23	range	range	NOUN
fcis-31661	18	24	997	997	NUM
fcis-31661	18	25	-	-	SYM
fcis-31661	18	26	1708	1708	NUM
fcis-31661	18	27	nm	nm	NOUN
fcis-31661	18	28	,	,	PUNCT
fcis-31661	18	29	optiancheng	optiancheng	NOUN
fcis-31661	18	30	company	company	NOUN
fcis-31661	18	31	)	)	PUNCT
fcis-31661	18	32	,	,	PUNCT
fcis-31661	18	33	as	as	SCONJ
fcis-31661	18	34	shown	show	VERB
fcis-31661	18	35	in	in	ADP
fcis-31661	18	36	figure	figure	NOUN
fcis-31661	18	37	1	1	NUM
fcis-31661	18	38	.	.	PUNCT
fcis-31661	19	1	the	the	DET
fcis-31661	19	2	sugar	sugar	NOUN
fcis-31661	19	3	content	content	NOUN
fcis-31661	19	4	values	value	NOUN
fcis-31661	19	5	of	of	ADP
fcis-31661	19	6	apple	apple	NOUN
fcis-31661	19	7	samples	sample	NOUN
fcis-31661	19	8	were	be	AUX
fcis-31661	19	9	collected	collect	VERB
fcis-31661	19	10	using	use	VERB
fcis-31661	19	11	a	a	DET
fcis-31661	19	12	handheld	handheld	ADJ
fcis-31661	19	13	refractometer	refractometer	NOUN
fcis-31661	19	14	(	(	PUNCT
fcis-31661	19	15	atago	atago	PROPN
fcis-31661	19	16	palbx|acid8	palbx|acid8	PROPN
fcis-31661	19	17	,	,	PUNCT
fcis-31661	19	18	with	with	ADP
fcis-31661	19	19	a	a	DET
fcis-31661	19	20	detection	detection	NOUN
fcis-31661	19	21	range	range	NOUN
fcis-31661	19	22	of	of	ADP
fcis-31661	19	23	soluble	soluble	ADJ
fcis-31661	19	24	sugar	sugar	NOUN
fcis-31661	19	25	from	from	ADP
fcis-31661	19	26	0.0	0.0	NUM
fcis-31661	19	27	to	to	PART
fcis-31661	19	28	90	90	NUM
fcis-31661	19	29	%	%	NOUN
fcis-31661	19	30	,	,	PUNCT
fcis-31661	19	31	an	an	DET
fcis-31661	19	32	accuracy	accuracy	NOUN
fcis-31661	19	33	of	of	ADP
fcis-31661	19	34	±0.2	±0.2	PROPN
fcis-31661	19	35	%	%	NOUN
fcis-31661	19	36	,	,	PUNCT
fcis-31661	19	37	and	and	CCONJ
fcis-31661	19	38	a	a	DET
fcis-31661	19	39	suitable	suitable	ADJ
fcis-31661	19	40	temperature	temperature	NOUN
fcis-31661	19	41	range	range	NOUN
fcis-31661	19	42	of	of	ADP
fcis-31661	19	43	9.0	9.0	NUM
fcis-31661	19	44	to	to	PART
fcis-31661	19	45	99.9	99.9	NUM
fcis-31661	19	46	℃	℃	PROPN
fcis-31661	19	47	)	)	PUNCT
fcis-31661	19	48	,	,	PUNCT
fcis-31661	19	49	as	as	SCONJ
fcis-31661	19	50	shown	show	VERB
fcis-31661	19	51	in	in	ADP
fcis-31661	19	52	figure	figure	NOUN
fcis-31661	19	53	2	2	NUM
fcis-31661	19	54	.	.	PUNCT
fcis-31661	19	55	fig	fig	NOUN
fcis-31661	19	56	1	1	NUM
fcis-31661	19	57	.	.	PUNCT
fcis-31661	19	58	near	near	ADV
fcis-31661	19	59	-	-	PUNCT
fcis-31661	19	60	infrared	infrare	VERB
fcis-31661	19	61	spectrometer	spectrometer	NOUN
fcis-31661	19	62	fig	fig	NOUN
fcis-31661	19	63	2	2	NUM
fcis-31661	19	64	.	.	PUNCT
fcis-31661	19	65	handheld	handheld	ADJ
fcis-31661	19	66	refractometer	refractometer	NOUN
fcis-31661	19	67	2.2	2.2	NUM
fcis-31661	19	68	.	.	PUNCT
fcis-31661	20	1	experimental	experimental	ADJ
fcis-31661	20	2	method	method	NOUN
fcis-31661	20	3	2.2.1	2.2.1	NUM
fcis-31661	20	4	.	.	PUNCT
fcis-31661	21	1	experimental	experimental	ADJ
fcis-31661	21	2	data	datum	NOUN
fcis-31661	21	3	collection	collection	NOUN
fcis-31661	21	4	(	(	PUNCT
fcis-31661	21	5	1	1	X
fcis-31661	21	6	)	)	PUNCT
fcis-31661	21	7	sample	sample	NOUN
fcis-31661	21	8	marking	mark	VERB
fcis-31661	21	9	at	at	ADP
fcis-31661	21	10	the	the	DET
fcis-31661	21	11	circumequatorial	circumequatorial	ADJ
fcis-31661	21	12	position	position	NOUN
fcis-31661	21	13	of	of	ADP
fcis-31661	21	14	the	the	DET
fcis-31661	21	15	apple	apple	NOUN
fcis-31661	21	16	,	,	PUNCT
fcis-31661	21	17	select	select	VERB
fcis-31661	21	18	a	a	DET
fcis-31661	21	19	collection	collection	NOUN
fcis-31661	21	20	point	point	NOUN
fcis-31661	21	21	at	at	ADP
fcis-31661	21	22	equal	equal	ADJ
fcis-31661	21	23	intervals	interval	NOUN
fcis-31661	21	24	of	of	ADP
fcis-31661	21	25	60	60	NUM
fcis-31661	21	26	degrees	degree	NOUN
fcis-31661	21	27	and	and	CCONJ
fcis-31661	21	28	mark	mark	VERB
fcis-31661	21	29	it	it	PRON
fcis-31661	21	30	.	.	PUNCT
fcis-31661	22	1	a	a	DET
fcis-31661	22	2	total	total	NOUN
fcis-31661	22	3	of	of	ADP
fcis-31661	22	4	three	three	NUM
fcis-31661	22	5	points	point	NOUN
fcis-31661	22	6	is	be	AUX
fcis-31661	22	7	marked	mark	VERB
fcis-31661	22	8	as	as	ADP
fcis-31661	22	9	the	the	DET
fcis-31661	22	10	data	data	NOUN
fcis-31661	22	11	collection	collection	NOUN
fcis-31661	22	12	positions	position	NOUN
fcis-31661	22	13	.	.	PUNCT
fcis-31661	23	1	(	(	PUNCT
fcis-31661	23	2	2	2	X
fcis-31661	23	3	)	)	PUNCT
fcis-31661	23	4	collect	collect	VERB
fcis-31661	23	5	spectral	spectral	ADJ
fcis-31661	23	6	data	datum	NOUN
fcis-31661	23	7	set	set	VERB
fcis-31661	23	8	up	up	ADP
fcis-31661	23	9	the	the	DET
fcis-31661	23	10	spectral	spectral	ADJ
fcis-31661	23	11	equipment	equipment	NOUN
fcis-31661	23	12	;	;	PUNCT
fcis-31661	23	13	adjust	adjust	VERB
fcis-31661	23	14	the	the	DET
fcis-31661	23	15	optical	optical	ADJ
fcis-31661	23	16	path	path	NOUN
fcis-31661	23	17	and	and	CCONJ
fcis-31661	23	18	use	use	VERB
fcis-31661	23	19	the	the	DET
fcis-31661	23	20	calibration	calibration	NOUN
fcis-31661	23	21	whiteboard	whiteboard	NOUN
fcis-31661	23	22	to	to	PART
fcis-31661	23	23	collect	collect	VERB
fcis-31661	23	24	the	the	DET
fcis-31661	23	25	reference	reference	NOUN
fcis-31661	23	26	90	90	NUM
fcis-31661	23	27	spectrum	spectrum	NOUN
fcis-31661	23	28	;	;	PUNCT
fcis-31661	23	29	start	start	VERB
fcis-31661	23	30	collecting	collect	VERB
fcis-31661	23	31	the	the	DET
fcis-31661	23	32	spectral	spectral	ADJ
fcis-31661	23	33	data	datum	NOUN
fcis-31661	23	34	of	of	ADP
fcis-31661	23	35	the	the	DET
fcis-31661	23	36	experimental	experimental	ADJ
fcis-31661	23	37	sample	sample	NOUN
fcis-31661	23	38	.	.	PUNCT
fcis-31661	24	1	collect	collect	VERB
fcis-31661	24	2	the	the	DET
fcis-31661	24	3	data	datum	NOUN
fcis-31661	24	4	three	three	NUM
fcis-31661	24	5	times	time	NOUN
fcis-31661	24	6	for	for	ADP
fcis-31661	24	7	each	each	DET
fcis-31661	24	8	apple	apple	NOUN
fcis-31661	24	9	sample	sample	NOUN
fcis-31661	24	10	and	and	CCONJ
fcis-31661	24	11	calculate	calculate	VERB
fcis-31661	24	12	the	the	DET
fcis-31661	24	13	average	average	NOUN
fcis-31661	24	14	as	as	ADP
fcis-31661	24	15	the	the	DET
fcis-31661	24	16	original	original	ADJ
fcis-31661	24	17	spectral	spectral	ADJ
fcis-31661	24	18	data	datum	NOUN
fcis-31661	24	19	of	of	ADP
fcis-31661	24	20	the	the	DET
fcis-31661	24	21	sample	sample	NOUN
fcis-31661	24	22	,	,	PUNCT
fcis-31661	24	23	and	and	CCONJ
fcis-31661	24	24	save	save	VERB
fcis-31661	24	25	it	it	PRON
fcis-31661	24	26	in	in	ADP
fcis-31661	24	27	an	an	DET
fcis-31661	24	28	excel	excel	NOUN
fcis-31661	24	29	table	table	NOUN
fcis-31661	24	30	;	;	PUNCT
fcis-31661	24	31	after	after	SCONJ
fcis-31661	24	32	the	the	DET
fcis-31661	24	33	spectral	spectral	ADJ
fcis-31661	24	34	data	datum	NOUN
fcis-31661	24	35	collection	collection	NOUN
fcis-31661	24	36	is	be	AUX
fcis-31661	24	37	completed	complete	VERB
fcis-31661	24	38	,	,	PUNCT
fcis-31661	24	39	export	export	VERB
fcis-31661	24	40	the	the	DET
fcis-31661	24	41	spectral	spectral	ADJ
fcis-31661	24	42	data	datum	NOUN
fcis-31661	24	43	.	.	PUNCT
fcis-31661	25	1	(	(	PUNCT
fcis-31661	25	2	3	3	X
fcis-31661	25	3	)	)	PUNCT
fcis-31661	25	4	collect	collect	VERB
fcis-31661	25	5	sugar	sugar	NOUN
fcis-31661	25	6	content	content	NOUN
fcis-31661	25	7	data	datum	NOUN
fcis-31661	25	8	before	before	ADP
fcis-31661	25	9	measurement	measurement	NOUN
fcis-31661	25	10	,	,	PUNCT
fcis-31661	25	11	calibrate	calibrate	VERB
fcis-31661	25	12	the	the	DET
fcis-31661	25	13	refractometer	refractometer	NOUN
fcis-31661	25	14	with	with	ADP
fcis-31661	25	15	a	a	DET
fcis-31661	25	16	sucrose	sucrose	NOUN
fcis-31661	25	17	solution	solution	NOUN
fcis-31661	25	18	.	.	PUNCT
fcis-31661	26	1	when	when	SCONJ
fcis-31661	26	2	collecting	collect	VERB
fcis-31661	26	3	sugar	sugar	NOUN
fcis-31661	26	4	content	content	NOUN
fcis-31661	26	5	data	datum	NOUN
fcis-31661	26	6	,	,	PUNCT
fcis-31661	26	7	peel	peel	VERB
fcis-31661	26	8	the	the	DET
fcis-31661	26	9	apples	apple	NOUN
fcis-31661	26	10	,	,	PUNCT
fcis-31661	26	11	take	take	VERB
fcis-31661	26	12	small	small	ADJ
fcis-31661	26	13	samples	sample	NOUN
fcis-31661	26	14	at	at	ADP
fcis-31661	26	15	the	the	DET
fcis-31661	26	16	marked	mark	VERB
fcis-31661	26	17	positions	position	NOUN
fcis-31661	26	18	with	with	ADP
fcis-31661	26	19	a	a	DET
fcis-31661	26	20	clean	clean	ADJ
fcis-31661	26	21	fruit	fruit	NOUN
fcis-31661	26	22	knife	knife	NOUN
fcis-31661	26	23	,	,	PUNCT
fcis-31661	26	24	extract	extract	VERB
fcis-31661	26	25	the	the	DET
fcis-31661	26	26	juice	juice	NOUN
fcis-31661	26	27	,	,	PUNCT
fcis-31661	26	28	filter	filter	VERB
fcis-31661	26	29	it	it	PRON
fcis-31661	26	30	,	,	PUNCT
fcis-31661	26	31	and	and	CCONJ
fcis-31661	26	32	titrate	titrate	VERB
fcis-31661	26	33	it	it	PRON
fcis-31661	26	34	into	into	ADP
fcis-31661	26	35	the	the	DET
fcis-31661	26	36	measurement	measurement	NOUN
fcis-31661	26	37	area	area	NOUN
fcis-31661	26	38	of	of	ADP
fcis-31661	26	39	the	the	DET
fcis-31661	26	40	refractometer	refractometer	NOUN
fcis-31661	26	41	.	.	PUNCT
fcis-31661	27	1	take	take	VERB
fcis-31661	27	2	the	the	DET
fcis-31661	27	3	average	average	ADJ
fcis-31661	27	4	value	value	NOUN
fcis-31661	27	5	of	of	ADP
fcis-31661	27	6	the	the	DET
fcis-31661	27	7	three	three	NUM
fcis-31661	27	8	measurement	measurement	NOUN
fcis-31661	27	9	positions	position	NOUN
fcis-31661	27	10	of	of	ADP
fcis-31661	27	11	the	the	DET
fcis-31661	27	12	apples	apple	NOUN
fcis-31661	27	13	as	as	ADP
fcis-31661	27	14	the	the	DET
fcis-31661	27	15	sugar	sugar	NOUN
fcis-31661	27	16	content	content	NOUN
fcis-31661	27	17	value	value	NOUN
fcis-31661	27	18	of	of	ADP
fcis-31661	27	19	the	the	DET
fcis-31661	27	20	sample	sample	NOUN
fcis-31661	27	21	.	.	PUNCT
fcis-31661	28	1	2.2.2	2.2.2	X
fcis-31661	28	2	.	.	PUNCT
fcis-31661	28	3	spectral	spectral	ADJ
fcis-31661	28	4	data	datum	NOUN
fcis-31661	28	5	preprocessing	preprocesse	VERB
fcis-31661	28	6	to	to	PART
fcis-31661	28	7	suppress	suppress	VERB
fcis-31661	28	8	the	the	DET
fcis-31661	28	9	influence	influence	NOUN
fcis-31661	28	10	of	of	ADP
fcis-31661	28	11	noise	noise	NOUN
fcis-31661	28	12	on	on	ADP
fcis-31661	28	13	spectral	spectral	ADJ
fcis-31661	28	14	data	datum	NOUN
fcis-31661	28	15	and	and	CCONJ
fcis-31661	28	16	improve	improve	VERB
fcis-31661	28	17	the	the	DET
fcis-31661	28	18	accuracy	accuracy	NOUN
fcis-31661	28	19	of	of	ADP
fcis-31661	28	20	the	the	DET
fcis-31661	28	21	classification	classification	NOUN
fcis-31661	28	22	model	model	NOUN
fcis-31661	28	23	.	.	PUNCT
fcis-31661	29	1	the	the	DET
fcis-31661	29	2	experiment	experiment	NOUN
fcis-31661	29	3	selected	select	VERB
fcis-31661	29	4	three	three	NUM
fcis-31661	29	5	data	datum	NOUN
fcis-31661	29	6	preprocessing	preprocessing	NOUN
fcis-31661	29	7	methods	method	NOUN
fcis-31661	29	8	,	,	PUNCT
fcis-31661	29	9	namely	namely	ADV
fcis-31661	29	10	moving	move	VERB
fcis-31661	29	11	average	average	ADJ
fcis-31661	29	12	smoothing	smoothing	NOUN
fcis-31661	29	13	(	(	PUNCT
fcis-31661	29	14	mas	mas	PROPN
fcis-31661	29	15	)	)	PUNCT
fcis-31661	29	16	,	,	PUNCT
fcis-31661	29	17	standard	standard	ADJ
fcis-31661	29	18	normal	normal	ADJ
fcis-31661	29	19	variate	variate	NOUN
fcis-31661	29	20	(	(	PUNCT
fcis-31661	29	21	snv	snv	PROPN
fcis-31661	29	22	)	)	PUNCT
fcis-31661	29	23	,	,	PUNCT
fcis-31661	29	24	and	and	CCONJ
fcis-31661	29	25	mean	mean	VERB
fcis-31661	29	26	centering	center	VERB
fcis-31661	29	27	(	(	PUNCT
fcis-31661	29	28	mc	mc	PROPN
fcis-31661	29	29	)	)	PUNCT
fcis-31661	29	30	,	,	PUNCT
fcis-31661	29	31	to	to	PART
fcis-31661	29	32	preprocess	preprocess	VERB
fcis-31661	29	33	the	the	DET
fcis-31661	29	34	original	original	ADJ
fcis-31661	29	35	spectral	spectral	ADJ
fcis-31661	29	36	data	datum	NOUN
fcis-31661	29	37	respectively	respectively	ADV
fcis-31661	29	38	.	.	PUNCT
fcis-31661	30	1	(	(	PUNCT
fcis-31661	30	2	1	1	X
fcis-31661	30	3	)	)	PUNCT
fcis-31661	30	4	moving	move	VERB
fcis-31661	30	5	average	average	ADJ
fcis-31661	30	6	smoothing	smooth	VERB
fcis-31661	30	7	the	the	DET
fcis-31661	30	8	moving	move	VERB
fcis-31661	30	9	average	average	ADJ
fcis-31661	30	10	smoothing	smooth	VERB
fcis-31661	30	11	algorithm	algorithm	NOUN
fcis-31661	30	12	(	(	PUNCT
fcis-31661	30	13	mas	mas	PROPN
fcis-31661	30	14	)	)	PUNCT
fcis-31661	30	15	works	work	VERB
fcis-31661	30	16	by	by	ADP
fcis-31661	30	17	using	use	VERB
fcis-31661	30	18	a	a	DET
fcis-31661	30	19	smoothing	smooth	VERB
fcis-31661	30	20	window	window	NOUN
fcis-31661	30	21	of	of	ADP
fcis-31661	30	22	a	a	DET
fcis-31661	30	23	specific	specific	ADJ
fcis-31661	30	24	window	window	NOUN
fcis-31661	30	25	width	width	NOUN
fcis-31661	31	1	[	[	X
fcis-31661	31	2	1	1	NUM
fcis-31661	31	3	]	]	PUNCT
fcis-31661	31	4	,	,	PUNCT
fcis-31661	31	5	where	where	SCONJ
fcis-31661	31	6	the	the	DET
fcis-31661	31	7	wavelength	wavelength	NOUN
fcis-31661	31	8	points	point	VERB
fcis-31661	31	9	within	within	ADP
fcis-31661	31	10	a	a	DET
fcis-31661	31	11	single	single	ADJ
fcis-31661	31	12	window	window	NOUN
fcis-31661	31	13	are	be	AUX
fcis-31661	31	14	all	all	PRON
fcis-31661	31	15	odd	odd	ADJ
fcis-31661	31	16	.	.	PUNCT
fcis-31661	32	1	the	the	DET
fcis-31661	32	2	average	average	NOUN
fcis-31661	32	3	of	of	ADP
fcis-31661	32	4	the	the	DET
fcis-31661	32	5	measurement	measurement	NOUN
fcis-31661	32	6	values	value	NOUN
fcis-31661	32	7	at	at	ADP
fcis-31661	32	8	the	the	DET
fcis-31661	32	9	center	center	NOUN
fcis-31661	32	10	wavelength	wavelength	NOUN
fcis-31661	32	11	point	point	NOUN
fcis-31661	32	12	k	k	PROPN
fcis-31661	32	13	and	and	CCONJ
fcis-31661	32	14	the	the	DET
fcis-31661	32	15	x	x	ADJ
fcis-31661	32	16	points	point	NOUN
fcis-31661	32	17	before	before	ADV
fcis-31661	32	18	and	and	CCONJ
fcis-31661	32	19	after	after	ADP
fcis-31661	32	20	in	in	ADP
fcis-31661	32	21	the	the	DET
fcis-31661	32	22	window	window	NOUN
fcis-31661	32	23	is	be	AUX
fcis-31661	32	24	used	use	VERB
fcis-31661	32	25	to	to	PART
fcis-31661	32	26	replace	replace	VERB
fcis-31661	32	27	the	the	DET
fcis-31661	32	28	measurement	measurement	NOUN
fcis-31661	32	29	values	value	NOUN
fcis-31661	32	30	at	at	ADP
fcis-31661	32	31	the	the	DET
fcis-31661	32	32	wavelength	wavelength	NOUN
fcis-31661	32	33	points	point	NOUN
fcis-31661	32	34	.	.	PUNCT
fcis-31661	33	1	the	the	DET
fcis-31661	33	2	algorithm	algorithm	NOUN
fcis-31661	33	3	is	be	AUX
fcis-31661	33	4	moved	move	VERB
fcis-31661	33	5	from	from	ADP
fcis-31661	33	6	left	leave	VERB
fcis-31661	33	7	to	to	ADP
fcis-31661	33	8	right	right	NOUN
fcis-31661	33	9	by	by	ADP
fcis-31661	33	10	k	k	PROPN
fcis-31661	33	11	to	to	PART
fcis-31661	33	12	smooth	smooth	VERB
fcis-31661	33	13	all	all	DET
fcis-31661	33	14	the	the	DET
fcis-31661	33	15	points	point	NOUN
fcis-31661	33	16	.	.	PUNCT
fcis-31661	34	1	(	(	PUNCT
fcis-31661	34	2	2	2	X
fcis-31661	34	3	)	)	PUNCT
fcis-31661	34	4	standard	standard	ADJ
fcis-31661	34	5	normal	normal	ADJ
fcis-31661	34	6	variate	variate	NOUN
fcis-31661	34	7	the	the	DET
fcis-31661	34	8	main	main	ADJ
fcis-31661	34	9	purpose	purpose	NOUN
fcis-31661	34	10	of	of	ADP
fcis-31661	34	11	the	the	DET
fcis-31661	34	12	standard	standard	ADJ
fcis-31661	34	13	normal	normal	ADJ
fcis-31661	34	14	variate	variate	NOUN
fcis-31661	34	15	(	(	PUNCT
fcis-31661	34	16	snv	snv	PROPN
fcis-31661	34	17	)	)	PUNCT
fcis-31661	34	18	is	be	AUX
fcis-31661	34	19	to	to	PART
fcis-31661	34	20	eliminate	eliminate	VERB
fcis-31661	34	21	the	the	DET
fcis-31661	34	22	influence	influence	NOUN
fcis-31661	34	23	of	of	ADP
fcis-31661	34	24	the	the	DET
fcis-31661	34	25	size	size	NOUN
fcis-31661	34	26	of	of	ADP
fcis-31661	34	27	solid	solid	ADJ
fcis-31661	34	28	particles	particle	NOUN
fcis-31661	34	29	and	and	CCONJ
fcis-31661	34	30	the	the	DET
fcis-31661	34	31	changes	change	NOUN
fcis-31661	34	32	in	in	ADP
fcis-31661	34	33	the	the	DET
fcis-31661	34	34	optical	optical	ADJ
fcis-31661	34	35	path	path	NOUN
fcis-31661	34	36	of	of	ADP
fcis-31661	34	37	surface	surface	NOUN
fcis-31661	34	38	scattering	scattering	NOUN
fcis-31661	34	39	of	of	ADP
fcis-31661	34	40	the	the	DET
fcis-31661	34	41	sample	sample	NOUN
fcis-31661	34	42	on	on	ADP
fcis-31661	34	43	the	the	DET
fcis-31661	34	44	near	near	ADV
fcis-31661	34	45	-	-	PUNCT
fcis-31661	34	46	infrared	infrared	ADJ
fcis-31661	34	47	diffuse	diffuse	NOUN
fcis-31661	34	48	reflection	reflection	NOUN
fcis-31661	34	49	spectrum	spectrum	NOUN
fcis-31661	34	50	[	[	X
fcis-31661	34	51	2	2	NUM
fcis-31661	34	52	]	]	PUNCT
fcis-31661	34	53	.	.	PUNCT
fcis-31661	35	1	the	the	DET
fcis-31661	35	2	main	main	ADJ
fcis-31661	35	3	principle	principle	NOUN
fcis-31661	35	4	of	of	ADP
fcis-31661	35	5	snv	snv	PROPN
fcis-31661	35	6	is	be	AUX
fcis-31661	35	7	to	to	PART
fcis-31661	35	8	eliminate	eliminate	VERB
fcis-31661	35	9	the	the	DET
fcis-31661	35	10	background	background	NOUN
fcis-31661	35	11	noise	noise	NOUN
fcis-31661	35	12	of	of	ADP
fcis-31661	35	13	the	the	DET
fcis-31661	35	14	sample	sample	NOUN
fcis-31661	35	15	by	by	ADP
fcis-31661	35	16	changing	change	VERB
fcis-31661	35	17	the	the	DET
fcis-31661	35	18	scale	scale	NOUN
fcis-31661	35	19	range	range	NOUN
fcis-31661	35	20	and	and	CCONJ
fcis-31661	35	21	intensity	intensity	NOUN
fcis-31661	35	22	of	of	ADP
fcis-31661	35	23	the	the	DET
fcis-31661	35	24	spectral	spectral	ADJ
fcis-31661	35	25	signal	signal	NOUN
fcis-31661	35	26	.	.	PUNCT
fcis-31661	36	1	(	(	PUNCT
fcis-31661	36	2	3	3	X
fcis-31661	36	3	)	)	PUNCT
fcis-31661	36	4	mean	mean	NOUN
fcis-31661	36	5	centering	center	VERB
fcis-31661	36	6	mean	mean	NOUN
fcis-31661	36	7	centering	center	VERB
fcis-31661	36	8	(	(	PUNCT
fcis-31661	36	9	mc	mc	NOUN
fcis-31661	36	10	)	)	PUNCT
fcis-31661	36	11	is	be	AUX
fcis-31661	36	12	centered	center	VERB
fcis-31661	36	13	on	on	ADP
fcis-31661	36	14	calculating	calculate	VERB
fcis-31661	36	15	the	the	DET
fcis-31661	36	16	average	average	ADJ
fcis-31661	36	17	spectrum	spectrum	NOUN
fcis-31661	36	18	of	of	ADP
fcis-31661	36	19	the	the	DET
fcis-31661	36	20	entire	entire	ADJ
fcis-31661	36	21	dataset	dataset	NOUN
fcis-31661	36	22	and	and	CCONJ
fcis-31661	36	23	subtracting	subtract	VERB
fcis-31661	36	24	the	the	DET
fcis-31661	36	25	average	average	ADJ
fcis-31661	36	26	spectrum	spectrum	NOUN
fcis-31661	36	27	from	from	ADP
fcis-31661	36	28	each	each	DET
fcis-31661	36	29	sample	sample	NOUN
fcis-31661	36	30	,	,	PUNCT
fcis-31661	36	31	thereby	thereby	ADV
fcis-31661	36	32	eliminating	eliminate	VERB
fcis-31661	36	33	the	the	DET
fcis-31661	36	34	overall	overall	ADJ
fcis-31661	36	35	offset	offset	NOUN
fcis-31661	36	36	and	and	CCONJ
fcis-31661	36	37	bias	bias	NOUN
fcis-31661	36	38	caused	cause	VERB
fcis-31661	36	39	by	by	ADP
fcis-31661	36	40	the	the	DET
fcis-31661	36	41	data	datum	NOUN
fcis-31661	36	42	[	[	X
fcis-31661	36	43	3	3	NUM
fcis-31661	36	44	]	]	PUNCT
fcis-31661	36	45	.	.	PUNCT
fcis-31661	37	1	this	this	DET
fcis-31661	37	2	process	process	NOUN
fcis-31661	37	3	adjusts	adjust	VERB
fcis-31661	37	4	the	the	DET
fcis-31661	37	5	mean	mean	NOUN
fcis-31661	37	6	of	of	ADP
fcis-31661	37	7	the	the	DET
fcis-31661	37	8	data	datum	NOUN
fcis-31661	37	9	to	to	ADP
fcis-31661	37	10	zero	zero	NUM
fcis-31661	37	11	,	,	PUNCT
fcis-31661	37	12	causing	cause	VERB
fcis-31661	37	13	the	the	DET
fcis-31661	37	14	spectral	spectral	ADJ
fcis-31661	37	15	data	datum	NOUN
fcis-31661	37	16	to	to	PART
fcis-31661	37	17	fluctuate	fluctuate	VERB
fcis-31661	37	18	around	around	ADP
fcis-31661	37	19	the	the	DET
fcis-31661	37	20	zero	zero	NUM
fcis-31661	37	21	point	point	NOUN
fcis-31661	37	22	.	.	PUNCT
fcis-31661	38	1	mean	mean	ADJ
fcis-31661	38	2	centralization	centralization	NOUN
fcis-31661	38	3	can	can	AUX
fcis-31661	38	4	simplify	simplify	VERB
fcis-31661	38	5	the	the	DET
fcis-31661	38	6	data	data	NOUN
fcis-31661	38	7	structure	structure	NOUN
fcis-31661	38	8	,	,	PUNCT
fcis-31661	38	9	enhance	enhance	VERB
fcis-31661	38	10	the	the	DET
fcis-31661	38	11	interpretability	interpretability	NOUN
fcis-31661	38	12	of	of	ADP
fcis-31661	38	13	the	the	DET
fcis-31661	38	14	model	model	NOUN
fcis-31661	38	15	,	,	PUNCT
fcis-31661	38	16	and	and	CCONJ
fcis-31661	38	17	improve	improve	VERB
fcis-31661	38	18	the	the	DET
fcis-31661	38	19	performance	performance	NOUN
fcis-31661	38	20	of	of	ADP
fcis-31661	38	21	the	the	DET
fcis-31661	38	22	analysis	analysis	NOUN
fcis-31661	38	23	method	method	NOUN
fcis-31661	38	24	simultaneously	simultaneously	ADV
fcis-31661	38	25	.	.	PUNCT
fcis-31661	39	1	2.2.3	2.2.3	X
fcis-31661	39	2	.	.	PUNCT
fcis-31661	40	1	dataset	dataset	NOUN
fcis-31661	40	2	partitioning	partition	VERB
fcis-31661	40	3	before	before	ADP
fcis-31661	40	4	establishing	establish	VERB
fcis-31661	40	5	the	the	DET
fcis-31661	40	6	model	model	NOUN
fcis-31661	40	7	,	,	PUNCT
fcis-31661	40	8	the	the	DET
fcis-31661	40	9	sample	sample	NOUN
fcis-31661	40	10	set	set	VERB
fcis-31661	40	11	partitioning	partitioning	NOUN
fcis-31661	40	12	based	base	VERB
fcis-31661	40	13	on	on	ADP
fcis-31661	40	14	joint	joint	ADJ
fcis-31661	40	15	x	x	PROPN
fcis-31661	40	16	-	-	PROPN
fcis-31661	40	17	y	y	ADJ
fcis-31661	40	18	distance	distance	NOUN
fcis-31661	40	19	(	(	PUNCT
fcis-31661	40	20	spxy	spxy	NOUN
fcis-31661	40	21	)	)	PUNCT
fcis-31661	40	22	dataset	dataset	NOUN
fcis-31661	40	23	division	division	NOUN
fcis-31661	40	24	method	method	NOUN
fcis-31661	40	25	was	be	AUX
fcis-31661	40	26	adopted	adopt	VERB
fcis-31661	40	27	,	,	PUNCT
fcis-31661	40	28	and	and	CCONJ
fcis-31661	40	29	the	the	DET
fcis-31661	40	30	sample	sample	NOUN
fcis-31661	40	31	set	set	NOUN
fcis-31661	40	32	was	be	AUX
fcis-31661	40	33	divided	divide	VERB
fcis-31661	40	34	into	into	ADP
fcis-31661	40	35	89	89	NUM
fcis-31661	40	36	training	training	NOUN
fcis-31661	40	37	sets	set	NOUN
fcis-31661	40	38	and	and	CCONJ
fcis-31661	40	39	23	23	NUM
fcis-31661	40	40	prediction	prediction	NOUN
fcis-31661	40	41	sets	set	NOUN
fcis-31661	40	42	at	at	ADP
fcis-31661	40	43	a	a	DET
fcis-31661	40	44	ratio	ratio	NOUN
fcis-31661	40	45	of	of	ADP
fcis-31661	40	46	4:1	4:1	NUM
fcis-31661	40	47	.	.	PUNCT
fcis-31661	41	1	the	the	DET
fcis-31661	41	2	divided	divide	VERB
fcis-31661	41	3	training	training	NOUN
fcis-31661	41	4	set	set	NOUN
fcis-31661	41	5	is	be	AUX
fcis-31661	41	6	used	use	VERB
fcis-31661	41	7	to	to	PART
fcis-31661	41	8	fit	fit	VERB
fcis-31661	41	9	the	the	DET
fcis-31661	41	10	data	datum	NOUN
fcis-31661	41	11	to	to	PART
fcis-31661	41	12	establish	establish	VERB
fcis-31661	41	13	a	a	DET
fcis-31661	41	14	classification	classification	NOUN
fcis-31661	41	15	model	model	NOUN
fcis-31661	41	16	.	.	PUNCT
fcis-31661	42	1	the	the	DET
fcis-31661	42	2	prediction	prediction	NOUN
fcis-31661	42	3	set	set	NOUN
fcis-31661	42	4	does	do	AUX
fcis-31661	42	5	not	not	PART
fcis-31661	42	6	participate	participate	VERB
fcis-31661	42	7	in	in	ADP
fcis-31661	42	8	the	the	DET
fcis-31661	42	9	model	model	NOUN
fcis-31661	42	10	training	training	NOUN
fcis-31661	42	11	and	and	CCONJ
fcis-31661	42	12	is	be	AUX
fcis-31661	42	13	used	use	VERB
fcis-31661	42	14	to	to	PART
fcis-31661	42	15	evaluate	evaluate	VERB
fcis-31661	42	16	the	the	DET
fcis-31661	42	17	actual	actual	ADJ
fcis-31661	42	18	effect	effect	NOUN
fcis-31661	42	19	of	of	ADP
fcis-31661	42	20	the	the	DET
fcis-31661	42	21	model	model	NOUN
fcis-31661	42	22	established	establish	VERB
fcis-31661	42	23	by	by	ADP
fcis-31661	42	24	the	the	DET
fcis-31661	42	25	training	training	NOUN
fcis-31661	42	26	set	set	NOUN
fcis-31661	42	27	.	.	PUNCT
fcis-31661	43	1	the	the	DET
fcis-31661	43	2	spxy	spxy	NOUN
fcis-31661	43	3	algorithm	algorithm	NOUN
fcis-31661	43	4	is	be	AUX
fcis-31661	43	5	a	a	DET
fcis-31661	43	6	sample	sample	NOUN
fcis-31661	43	7	partitioning	partitioning	NOUN
fcis-31661	43	8	method	method	NOUN
fcis-31661	43	9	based	base	VERB
fcis-31661	43	10	on	on	ADP
fcis-31661	43	11	statistical	statistical	ADJ
fcis-31661	43	12	principles	principle	NOUN
fcis-31661	43	13	[	[	X
fcis-31661	43	14	4	4	NUM
fcis-31661	43	15	]	]	PUNCT
fcis-31661	43	16	.	.	PUNCT
fcis-31661	44	1	due	due	ADP
fcis-31661	44	2	to	to	ADP
fcis-31661	44	3	its	its	PRON
fcis-31661	44	4	efficient	efficient	ADJ
fcis-31661	44	5	coverage	coverage	NOUN
fcis-31661	44	6	ability	ability	NOUN
fcis-31661	44	7	in	in	ADP
fcis-31661	44	8	the	the	DET
fcis-31661	44	9	multi	multi	ADJ
fcis-31661	44	10	-	-	ADJ
fcis-31661	44	11	dimensional	dimensional	ADJ
fcis-31661	44	12	vector	vector	NOUN
fcis-31661	44	13	space	space	NOUN
fcis-31661	44	14	,	,	PUNCT
fcis-31661	44	15	it	it	PRON
fcis-31661	44	16	can	can	AUX
fcis-31661	44	17	significantly	significantly	ADV
fcis-31661	44	18	improve	improve	VERB
fcis-31661	44	19	the	the	DET
fcis-31661	44	20	prediction	prediction	NOUN
fcis-31661	44	21	accuracy	accuracy	NOUN
fcis-31661	44	22	of	of	ADP
fcis-31661	44	23	the	the	DET
fcis-31661	44	24	established	establish	VERB
fcis-31661	44	25	model	model	NOUN
fcis-31661	44	26	.	.	PUNCT
fcis-31661	45	1	2.2.4	2.2.4	NUM
fcis-31661	45	2	.	.	PUNCT
fcis-31661	45	3	characteristic	characteristic	ADJ
fcis-31661	45	4	wavelength	wavelength	NOUN
fcis-31661	45	5	selection	selection	NOUN
fcis-31661	45	6	the	the	DET
fcis-31661	45	7	competitive	competitive	ADJ
fcis-31661	45	8	adaptive	adaptive	ADJ
fcis-31661	45	9	reweighted	reweighte	VERB
fcis-31661	45	10	sampling	sample	VERB
fcis-31661	45	11	algorithm	algorithm	NOUN
fcis-31661	45	12	(	(	PUNCT
fcis-31661	45	13	cars	car	NOUN
fcis-31661	45	14	)	)	PUNCT
fcis-31661	45	15	is	be	AUX
fcis-31661	45	16	a	a	DET
fcis-31661	45	17	feature	feature	NOUN
fcis-31661	45	18	selection	selection	NOUN
fcis-31661	45	19	method	method	NOUN
fcis-31661	45	20	based	base	VERB
fcis-31661	45	21	on	on	ADP
fcis-31661	45	22	monte	monte	PROPN
fcis-31661	45	23	carlo	carlo	PROPN
fcis-31661	45	24	sampling	sampling	NOUN
fcis-31661	45	25	and	and	CCONJ
fcis-31661	45	26	partial	partial	ADJ
fcis-31661	45	27	least	least	ADJ
fcis-31661	45	28	squares	square	NOUN
fcis-31661	45	29	regression	regression	NOUN
fcis-31661	45	30	,	,	PUNCT
fcis-31661	45	31	which	which	PRON
fcis-31661	45	32	is	be	AUX
fcis-31661	45	33	used	use	VERB
fcis-31661	45	34	to	to	PART
fcis-31661	45	35	screen	screen	VERB
fcis-31661	45	36	out	out	ADP
fcis-31661	45	37	the	the	DET
fcis-31661	45	38	feature	feature	NOUN
fcis-31661	45	39	bands	band	NOUN
fcis-31661	45	40	that	that	PRON
fcis-31661	45	41	contribute	contribute	VERB
fcis-31661	45	42	the	the	DET
fcis-31661	45	43	most	most	ADJ
fcis-31661	45	44	to	to	ADP
fcis-31661	45	45	the	the	DET
fcis-31661	45	46	model	model	NOUN
fcis-31661	45	47	prediction	prediction	NOUN
fcis-31661	45	48	from	from	ADP
fcis-31661	45	49	the	the	DET
fcis-31661	45	50	high	high	ADJ
fcis-31661	45	51	-	-	PUNCT
fcis-31661	45	52	order	order	NOUN
fcis-31661	45	53	spectral	spectral	ADJ
fcis-31661	45	54	data	datum	NOUN
fcis-31661	45	55	[	[	X
fcis-31661	45	56	5	5	NUM
fcis-31661	45	57	]	]	PUNCT
fcis-31661	45	58	.	.	PUNCT
fcis-31661	46	1	the	the	DET
fcis-31661	46	2	core	core	NOUN
fcis-31661	46	3	principle	principle	NOUN
fcis-31661	46	4	is	be	AUX
fcis-31661	46	5	to	to	PART
fcis-31661	46	6	dynamically	dynamically	ADV
fcis-31661	46	7	adjust	adjust	VERB
fcis-31661	46	8	the	the	DET
fcis-31661	46	9	selection	selection	NOUN
fcis-31661	46	10	probability	probability	NOUN
fcis-31661	46	11	of	of	ADP
fcis-31661	46	12	each	each	DET
fcis-31661	46	13	band	band	NOUN
fcis-31661	46	14	by	by	ADP
fcis-31661	46	15	using	use	VERB
fcis-31661	46	16	the	the	DET
fcis-31661	46	17	exponential	exponential	ADJ
fcis-31661	46	18	attenuation	attenuation	NOUN
fcis-31661	46	19	function	function	NOUN
fcis-31661	46	20	,	,	PUNCT
fcis-31661	46	21	and	and	CCONJ
fcis-31661	46	22	gradually	gradually	ADV
fcis-31661	46	23	propose	propose	VERB
fcis-31661	46	24	the	the	DET
fcis-31661	46	25	unimportant	unimportant	ADJ
fcis-31661	46	26	bands	band	NOUN
fcis-31661	46	27	based	base	VERB
fcis-31661	46	28	on	on	ADP
fcis-31661	46	29	the	the	DET
fcis-31661	46	30	absolute	absolute	ADJ
fcis-31661	46	31	value	value	NOUN
fcis-31661	46	32	weights	weight	NOUN
fcis-31661	46	33	of	of	ADP
fcis-31661	46	34	the	the	DET
fcis-31661	46	35	regression	regression	NOUN
fcis-31661	46	36	coefficients	coefficient	NOUN
fcis-31661	46	37	.	.	PUNCT
fcis-31661	47	1	2.2.5	2.2.5	X
fcis-31661	47	2	.	.	X
fcis-31661	47	3	establishment	establishment	NOUN
fcis-31661	47	4	of	of	ADP
fcis-31661	47	5	classification	classification	NOUN
fcis-31661	47	6	model	model	NOUN
fcis-31661	47	7	(	(	PUNCT
fcis-31661	47	8	1	1	X
fcis-31661	47	9	)	)	PUNCT
fcis-31661	47	10	support	support	NOUN
fcis-31661	47	11	vector	vector	NOUN
fcis-31661	47	12	classification	classification	NOUN
fcis-31661	47	13	support	support	NOUN
fcis-31661	47	14	vector	vector	NOUN
fcis-31661	47	15	classification	classification	NOUN
fcis-31661	47	16	(	(	PUNCT
fcis-31661	47	17	svc	svc	PROPN
fcis-31661	47	18	)	)	PUNCT
fcis-31661	47	19	is	be	AUX
fcis-31661	47	20	a	a	DET
fcis-31661	47	21	supervised	supervised	ADJ
fcis-31661	47	22	learning	learn	VERB
fcis-31661	47	23	classification	classification	NOUN
fcis-31661	47	24	algorithm	algorithm	NOUN
fcis-31661	47	25	.	.	PUNCT
fcis-31661	48	1	its	its	PRON
fcis-31661	48	2	core	core	NOUN
fcis-31661	48	3	is	be	AUX
fcis-31661	48	4	to	to	PART
fcis-31661	48	5	maximize	maximize	VERB
fcis-31661	48	6	the	the	DET
fcis-31661	48	7	intervals	interval	NOUN
fcis-31661	48	8	between	between	ADP
fcis-31661	48	9	data	datum	NOUN
fcis-31661	48	10	points	point	NOUN
fcis-31661	48	11	of	of	ADP
fcis-31661	48	12	different	different	ADJ
fcis-31661	48	13	categories	category	NOUN
fcis-31661	48	14	through	through	ADP
fcis-31661	48	15	an	an	DET
fcis-31661	48	16	optimal	optimal	ADJ
fcis-31661	48	17	hyperplane	hyperplane	NOUN
fcis-31661	48	18	,	,	PUNCT
fcis-31661	48	19	and	and	CCONJ
fcis-31661	48	20	at	at	ADP
fcis-31661	48	21	the	the	DET
fcis-31661	48	22	same	same	ADJ
fcis-31661	48	23	time	time	NOUN
fcis-31661	48	24	use	use	VERB
fcis-31661	48	25	support	support	NOUN
fcis-31661	48	26	vectors	vector	NOUN
fcis-31661	48	27	(	(	PUNCT
fcis-31661	48	28	the	the	DET
fcis-31661	48	29	points	point	NOUN
fcis-31661	48	30	closest	close	ADJ
fcis-31661	48	31	to	to	ADP
fcis-31661	48	32	the	the	DET
fcis-31661	48	33	hyperplane	hyperplane	NOUN
fcis-31661	48	34	)	)	PUNCT
fcis-31661	48	35	to	to	PART
fcis-31661	48	36	determine	determine	VERB
fcis-31661	48	37	the	the	DET
fcis-31661	48	38	position	position	NOUN
fcis-31661	48	39	and	and	CCONJ
fcis-31661	48	40	direction	direction	NOUN
fcis-31661	48	41	of	of	ADP
fcis-31661	48	42	the	the	DET
fcis-31661	48	43	hyperplane	hyperplane	NOUN
fcis-31661	48	44	,	,	PUNCT
fcis-31661	48	45	separating	separate	VERB
fcis-31661	48	46	data	datum	NOUN
fcis-31661	48	47	points	point	NOUN
fcis-31661	48	48	of	of	ADP
fcis-31661	48	49	different	different	ADJ
fcis-31661	48	50	categories	category	NOUN
fcis-31661	48	51	as	as	ADV
fcis-31661	48	52	much	much	ADV
fcis-31661	48	53	as	as	ADP
fcis-31661	48	54	possible	possible	ADJ
fcis-31661	48	55	.	.	PUNCT
fcis-31661	49	1	(	(	PUNCT
fcis-31661	49	2	2	2	X
fcis-31661	49	3	)	)	PUNCT
fcis-31661	49	4	decision	decision	NOUN
fcis-31661	49	5	tree	tree	NOUN
fcis-31661	49	6	decision	decision	NOUN
fcis-31661	49	7	tree	tree	NOUN
fcis-31661	49	8	(	(	PUNCT
fcis-31661	49	9	dt	dt	NOUN
fcis-31661	49	10	)	)	PUNCT
fcis-31661	49	11	is	be	AUX
fcis-31661	49	12	a	a	DET
fcis-31661	49	13	classification	classification	NOUN
fcis-31661	49	14	algorithm	algorithm	NOUN
fcis-31661	49	15	based	base	VERB
fcis-31661	49	16	on	on	ADP
fcis-31661	49	17	tree	tree	NOUN
fcis-31661	49	18	structure	structure	NOUN
fcis-31661	49	19	.	.	PUNCT
fcis-31661	50	1	it	it	PRON
fcis-31661	50	2	divides	divide	VERB
fcis-31661	50	3	the	the	DET
fcis-31661	50	4	data	datum	NOUN
fcis-31661	50	5	set	set	VERB
fcis-31661	50	6	into	into	ADP
fcis-31661	50	7	smaller	small	ADJ
fcis-31661	50	8	subsets	subset	NOUN
fcis-31661	50	9	by	by	ADP
fcis-31661	50	10	recursively	recursively	ADV
fcis-31661	50	11	selecting	select	VERB
fcis-31661	50	12	the	the	DET
fcis-31661	50	13	optimal	optimal	ADJ
fcis-31661	50	14	features	feature	NOUN
fcis-31661	50	15	to	to	PART
fcis-31661	50	16	construct	construct	VERB
fcis-31661	50	17	the	the	DET
fcis-31661	50	18	model	model	NOUN
fcis-31661	50	19	.	.	PUNCT
fcis-31661	51	1	the	the	DET
fcis-31661	51	2	partitioning	partitioning	ADJ
fcis-31661	51	3	effect	effect	NOUN
fcis-31661	51	4	of	of	ADP
fcis-31661	51	5	features	feature	NOUN
fcis-31661	51	6	is	be	AUX
fcis-31661	51	7	measured	measure	VERB
fcis-31661	51	8	by	by	ADP
fcis-31661	51	9	indicators	indicator	NOUN
fcis-31661	51	10	such	such	ADJ
fcis-31661	51	11	as	as	ADP
fcis-31661	51	12	information	information	NOUN
fcis-31661	51	13	gain	gain	NOUN
fcis-31661	51	14	.	.	PUNCT
fcis-31661	52	1	the	the	DET
fcis-31661	52	2	features	feature	NOUN
fcis-31661	52	3	that	that	PRON
fcis-31661	52	4	maximize	maximize	VERB
fcis-31661	52	5	the	the	DET
fcis-31661	52	6	improvement	improvement	NOUN
fcis-31661	52	7	of	of	ADP
fcis-31661	52	8	data	datum	NOUN
fcis-31661	52	9	purity	purity	NOUN
fcis-31661	52	10	are	be	AUX
fcis-31661	52	11	selected	select	VERB
fcis-31661	52	12	for	for	ADP
fcis-31661	52	13	node	node	ADJ
fcis-31661	52	14	splitting	splitting	NOUN
fcis-31661	52	15	until	until	SCONJ
fcis-31661	52	16	the	the	DET
fcis-31661	52	17	stopping	stopping	NOUN
fcis-31661	52	18	condition	condition	NOUN
fcis-31661	52	19	is	be	AUX
fcis-31661	52	20	met	meet	VERB
fcis-31661	52	21	.	.	PUNCT
fcis-31661	53	1	(	(	PUNCT
fcis-31661	53	2	3	3	X
fcis-31661	53	3	)	)	PUNCT
fcis-31661	53	4	k	k	NOUN
fcis-31661	53	5	-	-	PUNCT
fcis-31661	53	6	nearest	near	ADJ
fcis-31661	53	7	neighbor	neighbor	NOUN
fcis-31661	53	8	algorithm	algorithm	NOUN
fcis-31661	53	9	the	the	DET
fcis-31661	53	10	k	k	NOUN
fcis-31661	53	11	-	-	PUNCT
fcis-31661	53	12	nearest	near	ADJ
fcis-31661	53	13	neighbor	neighbor	NOUN
fcis-31661	53	14	algorithm	algorithm	NOUN
fcis-31661	53	15	(	(	PUNCT
fcis-31661	53	16	knn	knn	PROPN
fcis-31661	53	17	)	)	PUNCT
fcis-31661	53	18	is	be	AUX
fcis-31661	53	19	a	a	DET
fcis-31661	53	20	simple	simple	ADJ
fcis-31661	53	21	and	and	CCONJ
fcis-31661	53	22	intuitive	intuitive	ADJ
fcis-31661	53	23	classification	classification	NOUN
fcis-31661	53	24	method	method	NOUN
fcis-31661	53	25	.	.	PUNCT
fcis-31661	54	1	its	its	PRON
fcis-31661	54	2	core	core	ADJ
fcis-31661	54	3	idea	idea	NOUN
fcis-31661	54	4	is	be	AUX
fcis-31661	54	5	to	to	PART
fcis-31661	54	6	calculate	calculate	VERB
fcis-31661	54	7	the	the	DET
fcis-31661	54	8	distance	distance	NOUN
fcis-31661	54	9	between	between	ADP
fcis-31661	54	10	the	the	DET
fcis-31661	54	11	sample	sample	NOUN
fcis-31661	54	12	to	to	PART
fcis-31661	54	13	be	be	AUX
fcis-31661	54	14	classified	classify	VERB
fcis-31661	54	15	and	and	CCONJ
fcis-31661	54	16	the	the	DET
fcis-31661	54	17	samples	sample	NOUN
fcis-31661	54	18	of	of	ADP
fcis-31661	54	19	known	know	VERB
fcis-31661	54	20	categories	category	NOUN
fcis-31661	54	21	,	,	PUNCT
fcis-31661	54	22	find	find	VERB
fcis-31661	54	23	the	the	DET
fcis-31661	54	24	k	k	PROPN
fcis-31661	54	25	samples	sample	NOUN
fcis-31661	54	26	with	with	ADP
fcis-31661	54	27	the	the	DET
fcis-31661	54	28	closest	close	ADJ
fcis-31661	54	29	distance	distance	NOUN
fcis-31661	54	30	,	,	PUNCT
fcis-31661	54	31	and	and	CCONJ
fcis-31661	54	32	then	then	ADV
fcis-31661	54	33	determine	determine	VERB
fcis-31661	54	34	the	the	DET
fcis-31661	54	35	category	category	NOUN
fcis-31661	54	36	of	of	ADP
fcis-31661	54	37	the	the	DET
fcis-31661	54	38	sample	sample	NOUN
fcis-31661	54	39	to	to	PART
fcis-31661	54	40	be	be	AUX
fcis-31661	54	41	classified	classify	VERB
fcis-31661	54	42	through	through	ADP
fcis-31661	54	43	voting	voting	NOUN
fcis-31661	54	44	or	or	CCONJ
fcis-31661	54	45	weighted	weight	VERB
fcis-31661	54	46	voting	voting	NOUN
fcis-31661	54	47	based	base	VERB
fcis-31661	54	48	on	on	ADP
fcis-31661	54	49	the	the	DET
fcis-31661	54	50	category	category	NOUN
fcis-31661	54	51	information	information	NOUN
fcis-31661	54	52	of	of	ADP
fcis-31661	54	53	such	such	ADJ
fcis-31661	54	54	samples	sample	NOUN
fcis-31661	54	55	.	.	PUNCT
fcis-31661	55	1	2.3	2.3	NUM
fcis-31661	55	2	.	.	PUNCT
fcis-31661	55	3	evaluation	evaluation	NOUN
fcis-31661	55	4	index	index	NOUN
fcis-31661	55	5	in	in	ADP
fcis-31661	55	6	the	the	DET
fcis-31661	55	7	experiment	experiment	NOUN
fcis-31661	55	8	,	,	PUNCT
fcis-31661	55	9	the	the	DET
fcis-31661	55	10	training	training	NOUN
fcis-31661	55	11	results	result	NOUN
fcis-31661	55	12	of	of	ADP
fcis-31661	55	13	the	the	DET
fcis-31661	55	14	three	three	NUM
fcis-31661	55	15	classification	classification	NOUN
fcis-31661	55	16	models	model	NOUN
fcis-31661	55	17	were	be	AUX
fcis-31661	55	18	evaluated	evaluate	VERB
fcis-31661	55	19	through	through	ADP
fcis-31661	55	20	four	four	NUM
fcis-31661	55	21	evaluation	evaluation	NOUN
fcis-31661	55	22	indicators	indicator	NOUN
fcis-31661	55	23	:	:	PUNCT
fcis-31661	55	24	accuracy	accuracy	NOUN
fcis-31661	55	25	rate	rate	NOUN
fcis-31661	55	26	,	,	PUNCT
fcis-31661	55	27	precision	precision	NOUN
fcis-31661	55	28	rate	rate	NOUN
fcis-31661	55	29	,	,	PUNCT
fcis-31661	55	30	recall	recall	NOUN
fcis-31661	55	31	rate	rate	NOUN
fcis-31661	55	32	and	and	CCONJ
fcis-31661	55	33	f1	f1	NOUN
fcis-31661	55	34	score	score	NOUN
fcis-31661	55	35	.	.	PUNCT
fcis-31661	56	1	2.3.1	2.3.1	NUM
fcis-31661	56	2	.	.	PUNCT
fcis-31661	56	3	accuracy	accuracy	NOUN
fcis-31661	56	4	accuracy	accuracy	NOUN
fcis-31661	56	5	is	be	AUX
fcis-31661	56	6	an	an	DET
fcis-31661	56	7	important	important	ADJ
fcis-31661	56	8	metric	metric	NOUN
fcis-31661	56	9	to	to	PART
fcis-31661	56	10	measure	measure	VERB
fcis-31661	56	11	the	the	DET
fcis-31661	56	12	performance	performance	NOUN
fcis-31661	56	13	of	of	ADP
fcis-31661	56	14	a	a	DET
fcis-31661	56	15	model	model	NOUN
fcis-31661	56	16	.	.	PUNCT
fcis-31661	57	1	it	it	PRON
fcis-31661	57	2	describes	describe	VERB
fcis-31661	57	3	how	how	SCONJ
fcis-31661	57	4	much	much	ADJ
fcis-31661	57	5	of	of	ADP
fcis-31661	57	6	the	the	DET
fcis-31661	57	7	model	model	NOUN
fcis-31661	57	8	's	's	PART
fcis-31661	57	9	predictions	prediction	NOUN
fcis-31661	57	10	agree	agree	VERB
fcis-31661	57	11	with	with	ADP
fcis-31661	57	12	the	the	DET
fcis-31661	57	13	true	true	ADJ
fcis-31661	57	14	results	result	NOUN
fcis-31661	57	15	.	.	PUNCT
fcis-31661	58	1	that	that	PRON
fcis-31661	58	2	is	is	ADV
fcis-31661	58	3	,	,	PUNCT
fcis-31661	58	4	the	the	DET
fcis-31661	58	5	proportion	proportion	NOUN
fcis-31661	58	6	of	of	ADP
fcis-31661	58	7	the	the	DET
fcis-31661	58	8	total	total	ADJ
fcis-31661	58	9	number	number	NOUN
fcis-31661	58	10	of	of	ADP
fcis-31661	58	11	samples	sample	NOUN
fcis-31661	58	12	that	that	PRON
fcis-31661	58	13	the	the	DET
fcis-31661	58	14	model	model	NOUN
fcis-31661	58	15	correctly	correctly	ADV
fcis-31661	58	16	classified	classified	ADJ
fcis-31661	58	17	.	.	PUNCT
fcis-31661	59	1	accuracy	accuracy	NOUN
fcis-31661	59	2	is	be	AUX
fcis-31661	59	3	intuitive	intuitive	ADJ
fcis-31661	59	4	and	and	CCONJ
fcis-31661	59	5	easy	easy	ADJ
fcis-31661	59	6	to	to	PART
fcis-31661	59	7	interpret	interpret	VERB
fcis-31661	59	8	and	and	CCONJ
fcis-31661	59	9	understand	understand	VERB
fcis-31661	59	10	.	.	PUNCT
fcis-31661	60	1	calculate	calculate	NOUN
fcis-31661	60	2	according	accord	VERB
fcis-31661	60	3	to	to	ADP
fcis-31661	60	4	equation	equation	NOUN
fcis-31661	60	5	(	(	PUNCT
fcis-31661	60	6	1	1	NUM
fcis-31661	60	7	)	)	PUNCT
fcis-31661	60	8	accuracy	accuracy	NOUN
fcis-31661	60	9	(	(	PUNCT
fcis-31661	60	10	1	1	NUM
fcis-31661	60	11	)	)	PUNCT
fcis-31661	60	12	tp	tp	NOUN
fcis-31661	60	13	(	(	PUNCT
fcis-31661	60	14	true	true	ADJ
fcis-31661	60	15	positive	positive	ADJ
fcis-31661	60	16	)	)	PUNCT
fcis-31661	60	17	is	be	AUX
fcis-31661	60	18	the	the	DET
fcis-31661	60	19	number	number	NOUN
fcis-31661	60	20	of	of	ADP
fcis-31661	60	21	samples	sample	NOUN
fcis-31661	60	22	predicted	predict	VERB
fcis-31661	60	23	as	as	ADP
fcis-31661	60	24	positive	positive	ADJ
fcis-31661	60	25	by	by	ADP
fcis-31661	60	26	the	the	DET
fcis-31661	60	27	model	model	NOUN
fcis-31661	60	28	.	.	PUNCT
fcis-31661	61	1	tn	tn	PROPN
fcis-31661	61	2	(	(	PUNCT
fcis-31661	61	3	true	true	ADJ
fcis-31661	61	4	negative	negative	ADJ
fcis-31661	61	5	)	)	PUNCT
fcis-31661	61	6	is	be	AUX
fcis-31661	61	7	the	the	DET
fcis-31661	61	8	number	number	NOUN
fcis-31661	61	9	of	of	ADP
fcis-31661	61	10	examples	example	NOUN
fcis-31661	61	11	that	that	PRON
fcis-31661	61	12	the	the	DET
fcis-31661	61	13	model	model	NOUN
fcis-31661	61	14	predicts	predict	VERB
fcis-31661	61	15	to	to	PART
fcis-31661	61	16	be	be	AUX
fcis-31661	61	17	negative	negative	ADJ
fcis-31661	61	18	.	.	PUNCT
fcis-31661	62	1	fp	fp	X
fcis-31661	62	2	(	(	PUNCT
fcis-31661	62	3	false	false	ADJ
fcis-31661	62	4	positive	positive	ADJ
fcis-31661	62	5	)	)	PUNCT
fcis-31661	62	6	represents	represent	VERB
fcis-31661	62	7	the	the	DET
fcis-31661	62	8	number	number	NOUN
fcis-31661	62	9	of	of	ADP
fcis-31661	62	10	samples	sample	NOUN
fcis-31661	62	11	that	that	PRON
fcis-31661	62	12	the	the	DET
fcis-31661	62	13	model	model	NOUN
fcis-31661	62	14	incorrectly	incorrectly	ADV
fcis-31661	62	15	predicted	predict	VERB
fcis-31661	62	16	as	as	ADP
fcis-31661	62	17	positive	positive	ADJ
fcis-31661	62	18	.	.	PUNCT
fcis-31661	63	1	fn	fn	INTJ
fcis-31661	63	2	(	(	PUNCT
fcis-31661	63	3	false	false	ADJ
fcis-31661	63	4	negative	negative	NOUN
fcis-31661	63	5	)	)	PUNCT
fcis-31661	63	6	represents	represent	VERB
fcis-31661	63	7	the	the	DET
fcis-31661	63	8	number	number	NOUN
fcis-31661	63	9	of	of	ADP
fcis-31661	63	10	samples	sample	NOUN
fcis-31661	63	11	that	that	PRON
fcis-31661	63	12	the	the	DET
fcis-31661	63	13	model	model	NOUN
fcis-31661	63	14	incorrectly	incorrectly	ADV
fcis-31661	63	15	predicted	predict	VERB
fcis-31661	63	16	as	as	ADP
fcis-31661	63	17	negative	negative	ADJ
fcis-31661	63	18	class	class	NOUN
fcis-31661	63	19	.	.	PUNCT
fcis-31661	64	1	2.3.2	2.3.2	NUM
fcis-31661	64	2	.	.	PUNCT
fcis-31661	64	3	precision	precision	NOUN
fcis-31661	64	4	precision	precision	NOUN
fcis-31661	64	5	,	,	PUNCT
fcis-31661	64	6	also	also	ADV
fcis-31661	64	7	known	know	VERB
fcis-31661	64	8	as	as	ADP
fcis-31661	64	9	precision	precision	NOUN
fcis-31661	64	10	,	,	PUNCT
fcis-31661	64	11	is	be	AUX
fcis-31661	64	12	the	the	DET
fcis-31661	64	13	fraction	fraction	NOUN
fcis-31661	64	14	of	of	ADP
fcis-31661	64	15	examples	example	NOUN
fcis-31661	64	16	that	that	PRON
fcis-31661	64	17	the	the	DET
fcis-31661	64	18	model	model	NOUN
fcis-31661	64	19	predicts	predict	VERB
fcis-31661	64	20	to	to	PART
fcis-31661	64	21	be	be	AUX
fcis-31661	64	22	positive	positive	ADJ
fcis-31661	64	23	that	that	PRON
fcis-31661	64	24	are	be	AUX
fcis-31661	64	25	also	also	ADV
fcis-31661	64	26	positive	positive	ADJ
fcis-31661	64	27	.	.	PUNCT
fcis-31661	65	1	calculate	calculate	NOUN
fcis-31661	65	2	according	accord	VERB
fcis-31661	65	3	to	to	ADP
fcis-31661	65	4	equation	equation	NOUN
fcis-31661	65	5	(	(	PUNCT
fcis-31661	65	6	2	2	NUM
fcis-31661	65	7	)	)	SYM
fcis-31661	65	8	91	91	NUM
fcis-31661	65	9	precision	precision	NOUN
fcis-31661	65	10	(	(	PUNCT
fcis-31661	65	11	2	2	NUM
fcis-31661	65	12	)	)	PUNCT
fcis-31661	65	13	2.3.3	2.3.3	NUM
fcis-31661	65	14	.	.	PUNCT
fcis-31661	66	1	recall	recall	PROPN
fcis-31661	66	2	recall	recall	PROPN
fcis-31661	66	3	,	,	PUNCT
fcis-31661	66	4	also	also	ADV
fcis-31661	66	5	known	know	VERB
fcis-31661	66	6	as	as	ADP
fcis-31661	66	7	recall	recall	NOUN
fcis-31661	66	8	,	,	PUNCT
fcis-31661	66	9	is	be	AUX
fcis-31661	66	10	the	the	DET
fcis-31661	66	11	fraction	fraction	NOUN
fcis-31661	66	12	of	of	ADP
fcis-31661	66	13	examples	example	NOUN
fcis-31661	66	14	that	that	PRON
fcis-31661	66	15	are	be	AUX
fcis-31661	66	16	actually	actually	ADV
fcis-31661	66	17	positive	positive	ADJ
fcis-31661	66	18	that	that	PRON
fcis-31661	66	19	are	be	AUX
fcis-31661	66	20	correctly	correctly	ADV
fcis-31661	66	21	predicted	predict	VERB
fcis-31661	66	22	to	to	PART
fcis-31661	66	23	be	be	AUX
fcis-31661	66	24	positive	positive	ADJ
fcis-31661	66	25	by	by	ADP
fcis-31661	66	26	the	the	DET
fcis-31661	66	27	model	model	NOUN
fcis-31661	66	28	.	.	PUNCT
fcis-31661	67	1	calculate	calculate	NOUN
fcis-31661	67	2	according	accord	VERB
fcis-31661	67	3	to	to	ADP
fcis-31661	67	4	equation	equation	NOUN
fcis-31661	67	5	(	(	PUNCT
fcis-31661	67	6	3	3	X
fcis-31661	67	7	)	)	PUNCT
fcis-31661	67	8	recall	recall	NOUN
fcis-31661	67	9	(	(	PUNCT
fcis-31661	67	10	3	3	NUM
fcis-31661	67	11	)	)	PUNCT
fcis-31661	67	12	2.3.4	2.3.4	NUM
fcis-31661	67	13	.	.	PUNCT
fcis-31661	68	1	f1	f1	NOUN
fcis-31661	68	2	score	score	NOUN
fcis-31661	68	3	the	the	DET
fcis-31661	68	4	f1	f1	ADJ
fcis-31661	68	5	score	score	NOUN
fcis-31661	68	6	is	be	AUX
fcis-31661	68	7	the	the	DET
fcis-31661	68	8	harmonic	harmonic	ADJ
fcis-31661	68	9	mean	mean	NOUN
fcis-31661	68	10	of	of	ADP
fcis-31661	68	11	precision	precision	NOUN
fcis-31661	68	12	and	and	CCONJ
fcis-31661	68	13	recall	recall	NOUN
fcis-31661	68	14	and	and	CCONJ
fcis-31661	68	15	is	be	AUX
fcis-31661	68	16	used	use	VERB
fcis-31661	68	17	to	to	PART
fcis-31661	68	18	strike	strike	VERB
fcis-31661	68	19	a	a	DET
fcis-31661	68	20	balance	balance	NOUN
fcis-31661	68	21	between	between	ADP
fcis-31661	68	22	precision	precision	NOUN
fcis-31661	68	23	and	and	CCONJ
fcis-31661	68	24	recall	recall	NOUN
fcis-31661	68	25	.	.	PUNCT
fcis-31661	69	1	the	the	DET
fcis-31661	69	2	f1	f1	PROPN
fcis-31661	69	3	score	score	NOUN
fcis-31661	69	4	is	be	AUX
fcis-31661	69	5	a	a	DET
fcis-31661	69	6	useful	useful	ADJ
fcis-31661	69	7	performance	performance	NOUN
fcis-31661	69	8	metric	metric	ADJ
fcis-31661	69	9	when	when	SCONJ
fcis-31661	69	10	both	both	DET
fcis-31661	69	11	precision	precision	NOUN
fcis-31661	69	12	and	and	CCONJ
fcis-31661	69	13	recall	recall	NOUN
fcis-31661	69	14	are	be	AUX
fcis-31661	69	15	important	important	ADJ
fcis-31661	69	16	.	.	PUNCT
fcis-31661	70	1	the	the	DET
fcis-31661	70	2	f1	f1	PROPN
fcis-31661	70	3	score	score	NOUN
fcis-31661	70	4	ranges	range	VERB
fcis-31661	70	5	from	from	ADP
fcis-31661	70	6	0	0	NUM
fcis-31661	70	7	to	to	ADP
fcis-31661	70	8	1	1	NUM
fcis-31661	70	9	,	,	PUNCT
fcis-31661	70	10	with	with	ADP
fcis-31661	70	11	higher	high	ADJ
fcis-31661	70	12	values	value	NOUN
fcis-31661	70	13	indicating	indicate	VERB
fcis-31661	70	14	better	well	ADJ
fcis-31661	70	15	model	model	NOUN
fcis-31661	70	16	training	training	NOUN
fcis-31661	70	17	results	result	NOUN
fcis-31661	70	18	.	.	PUNCT
fcis-31661	71	1	calculate	calculate	NOUN
fcis-31661	71	2	according	accord	VERB
fcis-31661	71	3	to	to	ADP
fcis-31661	71	4	equation	equation	NOUN
fcis-31661	71	5	(	(	PUNCT
fcis-31661	71	6	4	4	NUM
fcis-31661	71	7	)	)	PUNCT
fcis-31661	71	8	f1	f1	NOUN
fcis-31661	71	9	score	score	NOUN
fcis-31661	71	10	2	2	NUM
fcis-31661	71	11	(	(	PUNCT
fcis-31661	71	12	4	4	NUM
fcis-31661	71	13	)	)	PUNCT
fcis-31661	71	14	3	3	NUM
fcis-31661	71	15	.	.	NOUN
fcis-31661	72	1	results	result	NOUN
fcis-31661	72	2	and	and	CCONJ
fcis-31661	72	3	analysis	analysis	NOUN
fcis-31661	72	4	3.1	3.1	NUM
fcis-31661	72	5	.	.	PUNCT
fcis-31661	73	1	comparison	comparison	NOUN
fcis-31661	73	2	of	of	ADP
fcis-31661	73	3	preprocessing	preprocesse	VERB
fcis-31661	73	4	methods	method	NOUN
fcis-31661	73	5	for	for	ADP
fcis-31661	73	6	the	the	DET
fcis-31661	73	7	original	original	ADJ
fcis-31661	73	8	near	near	ADV
fcis-31661	73	9	-	-	PUNCT
fcis-31661	73	10	infrared	infrared	ADJ
fcis-31661	73	11	spectral	spectral	ADJ
fcis-31661	73	12	data	datum	NOUN
fcis-31661	73	13	,	,	PUNCT
fcis-31661	73	14	there	there	PRON
fcis-31661	73	15	is	be	VERB
fcis-31661	73	16	a	a	DET
fcis-31661	73	17	lot	lot	NOUN
fcis-31661	73	18	of	of	ADP
fcis-31661	73	19	redundant	redundant	ADJ
fcis-31661	73	20	information	information	NOUN
fcis-31661	73	21	in	in	ADP
fcis-31661	73	22	the	the	DET
fcis-31661	73	23	spectral	spectral	ADJ
fcis-31661	73	24	band	band	NOUN
fcis-31661	73	25	that	that	PRON
fcis-31661	73	26	has	have	VERB
fcis-31661	73	27	nothing	nothing	PRON
fcis-31661	73	28	to	to	PART
fcis-31661	73	29	do	do	VERB
fcis-31661	73	30	with	with	ADP
fcis-31661	73	31	the	the	DET
fcis-31661	73	32	sample	sample	NOUN
fcis-31661	73	33	itself	itself	PRON
fcis-31661	73	34	,	,	PUNCT
fcis-31661	73	35	which	which	PRON
fcis-31661	73	36	will	will	AUX
fcis-31661	73	37	affect	affect	VERB
fcis-31661	73	38	the	the	DET
fcis-31661	73	39	training	training	NOUN
fcis-31661	73	40	and	and	CCONJ
fcis-31661	73	41	prediction	prediction	NOUN
fcis-31661	73	42	effect	effect	NOUN
fcis-31661	73	43	of	of	ADP
fcis-31661	73	44	the	the	DET
fcis-31661	73	45	established	establish	VERB
fcis-31661	73	46	model	model	NOUN
fcis-31661	73	47	.	.	PUNCT
fcis-31661	74	1	in	in	ADP
fcis-31661	74	2	order	order	NOUN
fcis-31661	74	3	to	to	PART
fcis-31661	74	4	improve	improve	VERB
fcis-31661	74	5	the	the	DET
fcis-31661	74	6	spectral	spectral	ADJ
fcis-31661	74	7	signal	signal	NOUN
fcis-31661	74	8	-	-	PUNCT
fcis-31661	74	9	to	to	ADP
fcis-31661	74	10	-	-	PUNCT
fcis-31661	74	11	noise	noise	NOUN
fcis-31661	74	12	ratio	ratio	NOUN
fcis-31661	74	13	and	and	CCONJ
fcis-31661	74	14	the	the	DET
fcis-31661	74	15	prediction	prediction	NOUN
fcis-31661	74	16	effect	effect	NOUN
fcis-31661	74	17	of	of	ADP
fcis-31661	74	18	the	the	DET
fcis-31661	74	19	model	model	NOUN
fcis-31661	74	20	,	,	PUNCT
fcis-31661	74	21	the	the	DET
fcis-31661	74	22	data	data	NOUN
fcis-31661	74	23	preprocessing	preprocessing	NOUN
fcis-31661	74	24	method	method	NOUN
fcis-31661	74	25	is	be	AUX
fcis-31661	74	26	used	use	VERB
fcis-31661	74	27	to	to	PART
fcis-31661	74	28	reduce	reduce	VERB
fcis-31661	74	29	the	the	DET
fcis-31661	74	30	error	error	NOUN
fcis-31661	74	31	in	in	ADP
fcis-31661	74	32	the	the	DET
fcis-31661	74	33	model	model	NOUN
fcis-31661	74	34	training	training	NOUN
fcis-31661	74	35	process	process	NOUN
fcis-31661	74	36	.	.	PUNCT
fcis-31661	75	1	the	the	DET
fcis-31661	75	2	spectrograms	spectrogram	NOUN
fcis-31661	75	3	processed	process	VERB
fcis-31661	75	4	by	by	ADP
fcis-31661	75	5	different	different	ADJ
fcis-31661	75	6	preprocessing	preprocessing	NOUN
fcis-31661	75	7	methods	method	NOUN
fcis-31661	75	8	are	be	AUX
fcis-31661	75	9	shown	show	VERB
fcis-31661	75	10	in	in	ADP
fcis-31661	75	11	fig	fig	NOUN
fcis-31661	75	12	3	3	NUM
fcis-31661	75	13	.	.	PUNCT
fcis-31661	76	1	(	(	PUNCT
fcis-31661	76	2	b	b	X
fcis-31661	76	3	)	)	PUNCT
fcis-31661	76	4	(	(	PUNCT
fcis-31661	76	5	d	d	NOUN
fcis-31661	76	6	)	)	PUNCT
fcis-31661	76	7	,	,	PUNCT
fcis-31661	76	8	and	and	CCONJ
fcis-31661	76	9	from	from	ADP
fcis-31661	76	10	the	the	DET
fcis-31661	76	11	original	original	ADJ
fcis-31661	76	12	spectrogram	spectrogram	NOUN
fcis-31661	76	13	(	(	PUNCT
fcis-31661	76	14	a	a	NOUN
fcis-31661	76	15	)	)	PUNCT
fcis-31661	76	16	,	,	PUNCT
fcis-31661	76	17	it	it	PRON
fcis-31661	76	18	can	can	AUX
fcis-31661	76	19	be	be	AUX
fcis-31661	76	20	seen	see	VERB
fcis-31661	76	21	that	that	SCONJ
fcis-31661	76	22	the	the	DET
fcis-31661	76	23	overall	overall	ADJ
fcis-31661	76	24	trend	trend	NOUN
fcis-31661	76	25	of	of	ADP
fcis-31661	76	26	the	the	DET
fcis-31661	76	27	spectra	spectra	NOUN
fcis-31661	76	28	after	after	ADP
fcis-31661	76	29	the	the	DET
fcis-31661	76	30	preprocessing	preprocessing	NOUN
fcis-31661	76	31	methods	method	NOUN
fcis-31661	76	32	is	be	AUX
fcis-31661	76	33	basically	basically	ADV
fcis-31661	76	34	consistent	consistent	ADJ
fcis-31661	76	35	with	with	ADP
fcis-31661	76	36	the	the	DET
fcis-31661	76	37	original	original	ADJ
fcis-31661	76	38	spectra	spectra	NOUN
fcis-31661	76	39	.	.	PUNCT
fcis-31661	77	1	a	a	DET
fcis-31661	77	2	original	original	ADJ
fcis-31661	77	3	spectrogram	spectrogram	NOUN
fcis-31661	77	4	b	b	NOUN
fcis-31661	77	5	spectra	spectra	NOUN
fcis-31661	77	6	after	after	ADP
fcis-31661	77	7	moving	move	VERB
fcis-31661	77	8	average	average	ADJ
fcis-31661	77	9	smoothing	smoothing	NOUN
fcis-31661	77	10	c	c	NOUN
fcis-31661	77	11	spectra	spectra	NOUN
fcis-31661	77	12	after	after	ADP
fcis-31661	77	13	standard	standard	ADJ
fcis-31661	77	14	normal	normal	ADJ
fcis-31661	77	15	variate	variate	NOUN
fcis-31661	77	16	d	d	PROPN
fcis-31661	77	17	spectra	spectra	NOUN
fcis-31661	77	18	after	after	ADP
fcis-31661	77	19	mean	mean	ADV
fcis-31661	77	20	centering	center	VERB
fcis-31661	77	21	fig	fig	NOUN
fcis-31661	77	22	3	3	NUM
fcis-31661	77	23	.	.	PUNCT
fcis-31661	78	1	the	the	DET
fcis-31661	78	2	spectrograms	spectrogram	NOUN
fcis-31661	78	3	processed	process	VERB
fcis-31661	78	4	by	by	ADP
fcis-31661	78	5	different	different	ADJ
fcis-31661	78	6	preprocessing	preprocessing	NOUN
fcis-31661	78	7	methods	method	NOUN
fcis-31661	78	8	according	accord	VERB
fcis-31661	78	9	to	to	ADP
fcis-31661	78	10	the	the	DET
fcis-31661	78	11	preprocessed	preprocesse	VERB
fcis-31661	78	12	result	result	NOUN
fcis-31661	78	13	figure	figure	NOUN
fcis-31661	78	14	,	,	PUNCT
fcis-31661	78	15	msc	msc	PROPN
fcis-31661	78	16	significantly	significantly	ADV
fcis-31661	78	17	reduces	reduce	VERB
fcis-31661	78	18	the	the	DET
fcis-31661	78	19	noise	noise	NOUN
fcis-31661	78	20	level	level	NOUN
fcis-31661	78	21	,	,	PUNCT
fcis-31661	78	22	and	and	CCONJ
fcis-31661	78	23	the	the	DET
fcis-31661	78	24	processed	process	VERB
fcis-31661	78	25	spectral	spectral	ADJ
fcis-31661	78	26	curve	curve	NOUN
fcis-31661	78	27	is	be	AUX
fcis-31661	78	28	clearer	clear	ADJ
fcis-31661	78	29	and	and	CCONJ
fcis-31661	78	30	smoother	smooth	ADJ
fcis-31661	78	31	,	,	PUNCT
fcis-31661	78	32	while	while	SCONJ
fcis-31661	78	33	retaining	retain	VERB
fcis-31661	78	34	important	important	ADJ
fcis-31661	78	35	spectral	spectral	ADJ
fcis-31661	78	36	features	feature	NOUN
fcis-31661	78	37	such	such	ADJ
fcis-31661	78	38	as	as	ADP
fcis-31661	78	39	peaks	peak	NOUN
fcis-31661	78	40	and	and	CCONJ
fcis-31661	78	41	valleys	valley	NOUN
fcis-31661	78	42	,	,	PUNCT
fcis-31661	78	43	which	which	PRON
fcis-31661	78	44	improves	improve	VERB
fcis-31661	78	45	the	the	DET
fcis-31661	78	46	overall	overall	ADJ
fcis-31661	78	47	quality	quality	NOUN
fcis-31661	78	48	of	of	ADP
fcis-31661	78	49	the	the	DET
fcis-31661	78	50	data	datum	NOUN
fcis-31661	78	51	while	while	SCONJ
fcis-31661	78	52	retaining	retain	VERB
fcis-31661	78	53	all	all	DET
fcis-31661	78	54	the	the	DET
fcis-31661	78	55	information	information	NOUN
fcis-31661	78	56	points	point	NOUN
fcis-31661	78	57	of	of	ADP
fcis-31661	78	58	the	the	DET
fcis-31661	78	59	original	original	ADJ
fcis-31661	78	60	data	datum	NOUN
fcis-31661	78	61	.	.	PUNCT
fcis-31661	79	1	svn	svn	NOUN
fcis-31661	79	2	scales	scale	VERB
fcis-31661	79	3	the	the	DET
fcis-31661	79	4	absorption	absorption	NOUN
fcis-31661	79	5	value	value	NOUN
fcis-31661	79	6	to	to	ADP
fcis-31661	79	7	a	a	DET
fcis-31661	79	8	smaller	small	ADJ
fcis-31661	79	9	and	and	CCONJ
fcis-31661	79	10	uniform	uniform	ADJ
fcis-31661	79	11	range	range	NOUN
fcis-31661	79	12	,	,	PUNCT
fcis-31661	79	13	reduces	reduce	VERB
fcis-31661	79	14	the	the	DET
fcis-31661	79	15	intensity	intensity	NOUN
fcis-31661	79	16	variation	variation	NOUN
fcis-31661	79	17	caused	cause	VERB
fcis-31661	79	18	by	by	ADP
fcis-31661	79	19	the	the	DET
fcis-31661	79	20	light	light	ADJ
fcis-31661	79	21	scattering	scatter	VERB
fcis-31661	79	22	effect	effect	NOUN
fcis-31661	79	23	,	,	PUNCT
fcis-31661	79	24	improves	improve	VERB
fcis-31661	79	25	the	the	DET
fcis-31661	79	26	data	datum	NOUN
fcis-31661	79	27	signal	signal	VERB
fcis-31661	79	28	-	-	PUNCT
fcis-31661	79	29	to	to	ADP
fcis-31661	79	30	-	-	PUNCT
fcis-31661	79	31	noise	noise	NOUN
fcis-31661	79	32	ratio	ratio	NOUN
fcis-31661	79	33	,	,	PUNCT
fcis-31661	79	34	and	and	CCONJ
fcis-31661	79	35	makes	make	VERB
fcis-31661	79	36	the	the	DET
fcis-31661	79	37	comparison	comparison	NOUN
fcis-31661	79	38	between	between	ADP
fcis-31661	79	39	different	different	ADJ
fcis-31661	79	40	samples	sample	NOUN
fcis-31661	79	41	more	more	ADV
fcis-31661	79	42	accurate	accurate	ADJ
fcis-31661	79	43	.	.	PUNCT
fcis-31661	80	1	after	after	ADP
fcis-31661	80	2	mc	mc	PROPN
fcis-31661	80	3	preprocessing	preprocessing	PROPN
fcis-31661	80	4	,	,	PUNCT
fcis-31661	80	5	the	the	DET
fcis-31661	80	6	features	feature	NOUN
fcis-31661	80	7	in	in	ADP
fcis-31661	80	8	the	the	DET
fcis-31661	80	9	spectra	spectra	NOUN
fcis-31661	80	10	are	be	AUX
fcis-31661	80	11	more	more	ADV
fcis-31661	80	12	obvious	obvious	ADJ
fcis-31661	80	13	,	,	PUNCT
fcis-31661	80	14	the	the	DET
fcis-31661	80	15	main	main	ADJ
fcis-31661	80	16	features	feature	NOUN
fcis-31661	80	17	and	and	CCONJ
fcis-31661	80	18	original	original	ADJ
fcis-31661	80	19	distribution	distribution	NOUN
fcis-31661	80	20	characteristics	characteristic	NOUN
fcis-31661	80	21	of	of	ADP
fcis-31661	80	22	the	the	DET
fcis-31661	80	23	spectral	spectral	ADJ
fcis-31661	80	24	data	datum	NOUN
fcis-31661	80	25	are	be	AUX
fcis-31661	80	26	preserved	preserve	VERB
fcis-31661	80	27	,	,	PUNCT
fcis-31661	80	28	the	the	DET
fcis-31661	80	29	baseline	baseline	NOUN
fcis-31661	80	30	of	of	ADP
fcis-31661	80	31	the	the	DET
fcis-31661	80	32	spectra	spectra	NOUN
fcis-31661	80	33	is	be	AUX
fcis-31661	80	34	more	more	ADV
fcis-31661	80	35	stable	stable	ADJ
fcis-31661	80	36	,	,	PUNCT
fcis-31661	80	37	and	and	CCONJ
fcis-31661	80	38	the	the	DET
fcis-31661	80	39	baseline	baseline	PROPN
fcis-31661	80	40	drift	drift	NOUN
fcis-31661	80	41	caused	cause	VERB
fcis-31661	80	42	by	by	ADP
fcis-31661	80	43	the	the	DET
fcis-31661	80	44	measurement	measurement	NOUN
fcis-31661	80	45	conditions	condition	NOUN
fcis-31661	80	46	or	or	CCONJ
fcis-31661	80	47	sample	sample	NOUN
fcis-31661	80	48	differences	difference	NOUN
fcis-31661	80	49	is	be	AUX
fcis-31661	80	50	reduced	reduce	VERB
fcis-31661	80	51	.	.	PUNCT
fcis-31661	81	1	3.2	3.2	NUM
fcis-31661	81	2	.	.	PUNCT
fcis-31661	81	3	comparison	comparison	NOUN
fcis-31661	81	4	of	of	ADP
fcis-31661	81	5	modeling	model	VERB
fcis-31661	81	6	methods	method	NOUN
fcis-31661	81	7	in	in	ADP
fcis-31661	81	8	the	the	DET
fcis-31661	81	9	experiment	experiment	NOUN
fcis-31661	81	10	,	,	PUNCT
fcis-31661	81	11	the	the	DET
fcis-31661	81	12	performance	performance	NOUN
fcis-31661	81	13	of	of	ADP
fcis-31661	81	14	dt	dt	PROPN
fcis-31661	81	15	,	,	PUNCT
fcis-31661	81	16	svc	svc	PROPN
fcis-31661	81	17	and	and	CCONJ
fcis-31661	81	18	knn	knn	VERB
fcis-31661	81	19	classification	classification	NOUN
fcis-31661	81	20	models	model	NOUN
fcis-31661	81	21	under	under	ADP
fcis-31661	81	22	mas	mas	PROPN
fcis-31661	81	23	,	,	PUNCT
fcis-31661	81	24	snv	snv	PROPN
fcis-31661	81	25	and	and	CCONJ
fcis-31661	81	26	mc	mc	PROPN
fcis-31661	81	27	preprocessing	preprocessing	NOUN
fcis-31661	81	28	methods	method	NOUN
fcis-31661	81	29	are	be	AUX
fcis-31661	81	30	compared	compare	VERB
fcis-31661	81	31	,	,	PUNCT
fcis-31661	81	32	and	and	CCONJ
fcis-31661	81	33	the	the	DET
fcis-31661	81	34	experimental	experimental	ADJ
fcis-31661	81	35	results	result	NOUN
fcis-31661	81	36	are	be	AUX
fcis-31661	81	37	shown	show	VERB
fcis-31661	81	38	in	in	ADP
fcis-31661	81	39	table	table	NOUN
fcis-31661	81	40	1	1	NUM
fcis-31661	81	41	.	.	PUNCT
fcis-31661	82	1	the	the	DET
fcis-31661	82	2	results	result	NOUN
fcis-31661	82	3	show	show	VERB
fcis-31661	82	4	that	that	SCONJ
fcis-31661	82	5	the	the	DET
fcis-31661	82	6	preprocessing	preprocessing	NOUN
fcis-31661	82	7	method	method	NOUN
fcis-31661	82	8	has	have	VERB
fcis-31661	82	9	a	a	DET
fcis-31661	82	10	significant	significant	ADJ
fcis-31661	82	11	impact	impact	NOUN
fcis-31661	82	12	on	on	ADP
fcis-31661	82	13	the	the	DET
fcis-31661	82	14	model	model	NOUN
fcis-31661	82	15	performance	performance	NOUN
fcis-31661	82	16	.	.	PUNCT
fcis-31661	83	1	dt	dt	PROPN
fcis-31661	83	2	performs	perform	VERB
fcis-31661	83	3	best	well	ADV
fcis-31661	83	4	under	under	ADP
fcis-31661	83	5	mc	mc	PROPN
fcis-31661	83	6	preprocessing	preprocessing	NOUN
fcis-31661	83	7	,	,	PUNCT
fcis-31661	83	8	with	with	ADP
fcis-31661	83	9	the	the	DET
fcis-31661	83	10	accuracy	accuracy	NOUN
fcis-31661	83	11	,	,	PUNCT
fcis-31661	83	12	precision	precision	NOUN
fcis-31661	83	13	,	,	PUNCT
fcis-31661	83	14	recall	recall	NOUN
fcis-31661	83	15	and	and	CCONJ
fcis-31661	83	16	f1	f1	NOUN
fcis-31661	83	17	score	score	NOUN
fcis-31661	83	18	all	all	PRON
fcis-31661	83	19	reaching	reach	VERB
fcis-31661	83	20	0.955	0.955	NUM
fcis-31661	83	21	.	.	PUNCT
fcis-31661	84	1	the	the	DET
fcis-31661	84	2	performance	performance	NOUN
fcis-31661	84	3	of	of	ADP
fcis-31661	84	4	svc	svc	PROPN
fcis-31661	84	5	is	be	AUX
fcis-31661	84	6	improved	improve	VERB
fcis-31661	84	7	to	to	ADP
fcis-31661	84	8	0.864	0.864	NUM
fcis-31661	84	9	after	after	ADP
fcis-31661	84	10	mas	mas	PROPN
fcis-31661	84	11	and	and	CCONJ
fcis-31661	84	12	snv	snv	PROPN
fcis-31661	84	13	preprocessing	preprocessing	NOUN
fcis-31661	84	14	,	,	PUNCT
fcis-31661	84	15	and	and	CCONJ
fcis-31661	84	16	the	the	DET
fcis-31661	84	17	performance	performance	NOUN
fcis-31661	84	18	of	of	ADP
fcis-31661	84	19	knn	knn	PROPN
fcis-31661	84	20	is	be	AUX
fcis-31661	84	21	improved	improve	VERB
fcis-31661	84	22	to	to	ADP
fcis-31661	84	23	0.91	0.91	NUM
fcis-31661	84	24	after	after	ADP
fcis-31661	84	25	mc	mc	PROPN
fcis-31661	84	26	preprocessing	preprocessing	PROPN
fcis-31661	84	27	.	.	PUNCT
fcis-31661	85	1	the	the	DET
fcis-31661	85	2	cars	car	NOUN
fcis-31661	85	3	feature	feature	VERB
fcis-31661	85	4	selection	selection	NOUN
fcis-31661	85	5	method	method	NOUN
fcis-31661	85	6	adaptively	adaptively	ADV
fcis-31661	85	7	adjusts	adjust	VERB
fcis-31661	85	8	the	the	DET
fcis-31661	85	9	selection	selection	NOUN
fcis-31661	85	10	92	92	NUM
fcis-31661	85	11	probability	probability	NOUN
fcis-31661	85	12	of	of	ADP
fcis-31661	85	13	each	each	DET
fcis-31661	85	14	band	band	NOUN
fcis-31661	85	15	through	through	ADP
fcis-31661	85	16	monte	monte	PROPN
fcis-31661	85	17	carlo	carlo	PROPN
fcis-31661	85	18	sampling	sampling	NOUN
fcis-31661	85	19	and	and	CCONJ
fcis-31661	85	20	exponential	exponential	ADJ
fcis-31661	85	21	decay	decay	NOUN
fcis-31661	85	22	function	function	NOUN
fcis-31661	85	23	,	,	PUNCT
fcis-31661	85	24	and	and	CCONJ
fcis-31661	85	25	finally	finally	ADV
fcis-31661	85	26	selects	select	VERB
fcis-31661	85	27	the	the	DET
fcis-31661	85	28	optimal	optimal	ADJ
fcis-31661	85	29	band	band	NOUN
fcis-31661	85	30	combination	combination	NOUN
fcis-31661	85	31	that	that	PRON
fcis-31661	85	32	contributes	contribute	VERB
fcis-31661	85	33	the	the	DET
fcis-31661	85	34	most	most	ADJ
fcis-31661	85	35	to	to	ADP
fcis-31661	85	36	the	the	DET
fcis-31661	85	37	modeling	modeling	NOUN
fcis-31661	85	38	performance	performance	NOUN
fcis-31661	85	39	.	.	PUNCT
fcis-31661	86	1	under	under	ADP
fcis-31661	86	2	different	different	ADJ
fcis-31661	86	3	models	model	NOUN
fcis-31661	86	4	and	and	CCONJ
fcis-31661	86	5	preprocessing	preprocessing	NOUN
fcis-31661	86	6	methods	method	NOUN
fcis-31661	86	7	,	,	PUNCT
fcis-31661	86	8	cars	car	NOUN
fcis-31661	86	9	have	have	VERB
fcis-31661	86	10	a	a	DET
fcis-31661	86	11	certain	certain	ADJ
fcis-31661	86	12	impact	impact	NOUN
fcis-31661	86	13	on	on	ADP
fcis-31661	86	14	the	the	DET
fcis-31661	86	15	performance	performance	NOUN
fcis-31661	86	16	,	,	PUNCT
fcis-31661	86	17	but	but	CCONJ
fcis-31661	86	18	the	the	DET
fcis-31661	86	19	effect	effect	NOUN
fcis-31661	86	20	depends	depend	VERB
fcis-31661	86	21	on	on	ADP
fcis-31661	86	22	the	the	DET
fcis-31661	86	23	specific	specific	ADJ
fcis-31661	86	24	model	model	NOUN
fcis-31661	86	25	and	and	CCONJ
fcis-31661	86	26	preprocessing	preprocessing	NOUN
fcis-31661	86	27	method	method	NOUN
fcis-31661	86	28	.	.	PUNCT
fcis-31661	87	1	in	in	ADP
fcis-31661	87	2	general	general	ADJ
fcis-31661	87	3	,	,	PUNCT
fcis-31661	87	4	dt	dt	ADJ
fcis-31661	87	5	under	under	ADP
fcis-31661	87	6	mc	mc	PROPN
fcis-31661	87	7	preprocessing	preprocesse	VERB
fcis-31661	87	8	combined	combine	VERB
fcis-31661	87	9	with	with	ADP
fcis-31661	87	10	cars	car	NOUN
fcis-31661	87	11	feature	feature	NOUN
fcis-31661	87	12	selection	selection	NOUN
fcis-31661	87	13	performs	perform	VERB
fcis-31661	87	14	best	well	ADV
fcis-31661	87	15	,	,	PUNCT
fcis-31661	87	16	and	and	CCONJ
fcis-31661	87	17	the	the	DET
fcis-31661	87	18	classification	classification	NOUN
fcis-31661	87	19	effect	effect	NOUN
fcis-31661	87	20	is	be	AUX
fcis-31661	87	21	the	the	DET
fcis-31661	87	22	best	good	ADJ
fcis-31661	87	23	.	.	PUNCT
fcis-31661	88	1	table	table	NOUN
fcis-31661	88	2	1	1	NUM
fcis-31661	88	3	.	.	PUNCT
fcis-31661	89	1	classification	classification	NOUN
fcis-31661	89	2	results	result	NOUN
fcis-31661	89	3	of	of	ADP
fcis-31661	89	4	different	different	ADJ
fcis-31661	89	5	models	model	NOUN
fcis-31661	89	6	preprocessing	preprocesse	VERB
fcis-31661	89	7	model	model	NOUN
fcis-31661	89	8	feature	feature	NOUN
fcis-31661	89	9	extraction	extraction	NOUN
fcis-31661	89	10	accuracy	accuracy	NOUN
fcis-31661	89	11	precision	precision	NOUN
fcis-31661	89	12	recall	recall	NOUN
fcis-31661	89	13	f1	f1	PROPN
fcis-31661	89	14	score	score	NOUN
fcis-31661	89	15	no	no	DET
fcis-31661	89	16	dt	dt	NOUN
fcis-31661	89	17	cars	car	NOUN
fcis-31661	89	18	0.73	0.73	NUM
fcis-31661	89	19	0.73	0.73	NUM
fcis-31661	89	20	0.73	0.73	NUM
fcis-31661	89	21	0.73	0.73	NUM
fcis-31661	89	22	mas	mas	NOUN
fcis-31661	89	23	0.73	0.73	NUM
fcis-31661	89	24	0.73	0.73	NUM
fcis-31661	89	25	0.73	0.73	NUM
fcis-31661	89	26	0.73	0.73	NUM
fcis-31661	89	27	snv	snv	NOUN
fcis-31661	89	28	0.64	0.64	NUM
fcis-31661	89	29	0.64	0.64	NUM
fcis-31661	89	30	0.64	0.64	NUM
fcis-31661	89	31	0.64	0.64	NUM
fcis-31661	89	32	mc	mc	NOUN
fcis-31661	89	33	0.955	0.955	NUM
fcis-31661	89	34	0.955	0.955	NUM
fcis-31661	89	35	0.955	0.955	NUM
fcis-31661	89	36	0.955	0.955	NUM
fcis-31661	89	37	no	no	DET
fcis-31661	89	38	svc	svc	NOUN
fcis-31661	89	39	cars	car	VERB
fcis-31661	89	40	0.773	0.773	NUM
fcis-31661	89	41	0.773	0.773	NUM
fcis-31661	89	42	0.773	0.773	NUM
fcis-31661	89	43	0.773	0.773	NUM
fcis-31661	90	1	mas	mas	NOUN
fcis-31661	90	2	0.864	0.864	NUM
fcis-31661	90	3	0.864	0.864	NUM
fcis-31661	90	4	0.864	0.864	NUM
fcis-31661	90	5	0.864	0.864	NUM
fcis-31661	90	6	snv	snv	NOUN
fcis-31661	90	7	0.864	0.864	NUM
fcis-31661	90	8	0.864	0.864	NUM
fcis-31661	90	9	0.864	0.864	NUM
fcis-31661	90	10	0.864	0.864	NUM
fcis-31661	90	11	mc	mc	NOUN
fcis-31661	90	12	0.773	0.773	NUM
fcis-31661	90	13	0.773	0.773	NUM
fcis-31661	90	14	0.773	0.773	NUM
fcis-31661	90	15	0.773	0.773	NUM
fcis-31661	91	1	no	no	DET
fcis-31661	91	2	knn	knn	NOUN
fcis-31661	91	3	cars	car	NOUN
fcis-31661	91	4	0.73	0.73	NUM
fcis-31661	91	5	0.73	0.73	NUM
fcis-31661	91	6	0.73	0.73	NUM
fcis-31661	91	7	0.73	0.73	NUM
fcis-31661	91	8	mas	mas	NOUN
fcis-31661	91	9	0.682	0.682	NUM
fcis-31661	91	10	0.682	0.682	NUM
fcis-31661	91	11	0.682	0.682	NUM
fcis-31661	91	12	0.682	0.682	NUM
fcis-31661	91	13	snv	snv	NOUN
fcis-31661	91	14	0.82	0.82	NUM
fcis-31661	91	15	0.82	0.82	NUM
fcis-31661	91	16	0.82	0.82	NUM
fcis-31661	91	17	0.82	0.82	NUM
fcis-31661	91	18	mc	mc	PROPN
fcis-31661	91	19	0.91	0.91	NUM
fcis-31661	91	20	0.91	0.91	NUM
fcis-31661	91	21	0.91	0.91	NUM
fcis-31661	91	22	0.91	0.91	NUM
fcis-31661	91	23	4	4	NUM
fcis-31661	91	24	.	.	PUNCT
fcis-31661	92	1	summary	summary	VERB
fcis-31661	92	2	this	this	DET
fcis-31661	92	3	paper	paper	NOUN
fcis-31661	92	4	discusses	discuss	VERB
fcis-31661	92	5	the	the	DET
fcis-31661	92	6	internal	internal	ADJ
fcis-31661	92	7	quality	quality	NOUN
fcis-31661	92	8	classification	classification	NOUN
fcis-31661	92	9	research	research	NOUN
fcis-31661	92	10	of	of	ADP
fcis-31661	92	11	shaanxi	shaanxi	PROPN
fcis-31661	92	12	luochuan	luochuan	PROPN
fcis-31661	92	13	red	red	PROPN
fcis-31661	92	14	fuji	fuji	PROPN
fcis-31661	92	15	apple	apple	PROPN
fcis-31661	92	16	,	,	PUNCT
fcis-31661	92	17	using	use	VERB
fcis-31661	92	18	near	near	ADP
fcis-31661	92	19	infrared	infrared	ADJ
fcis-31661	92	20	spectroscopy	spectroscopy	NOUN
fcis-31661	92	21	technology	technology	NOUN
fcis-31661	92	22	combined	combine	VERB
fcis-31661	92	23	with	with	ADP
fcis-31661	92	24	spxy	spxy	NOUN
fcis-31661	92	25	data	datum	NOUN
fcis-31661	92	26	set	set	VERB
fcis-31661	92	27	division	division	NOUN
fcis-31661	92	28	method	method	NOUN
fcis-31661	92	29	,	,	PUNCT
fcis-31661	92	30	as	as	ADV
fcis-31661	92	31	well	well	ADV
fcis-31661	92	32	as	as	ADP
fcis-31661	92	33	mas	mas	PROPN
fcis-31661	92	34	,	,	PUNCT
fcis-31661	92	35	snv	snv	PROPN
fcis-31661	92	36	,	,	PUNCT
fcis-31661	92	37	mc	mc	PROPN
fcis-31661	92	38	three	three	NUM
fcis-31661	92	39	data	datum	NOUN
fcis-31661	92	40	preprocessing	preprocessing	NOUN
fcis-31661	92	41	methods	method	NOUN
fcis-31661	92	42	,	,	PUNCT
fcis-31661	92	43	using	use	VERB
fcis-31661	92	44	cars	car	NOUN
fcis-31661	92	45	algorithm	algorithm	NOUN
fcis-31661	92	46	for	for	ADP
fcis-31661	92	47	data	datum	NOUN
fcis-31661	92	48	feature	feature	NOUN
fcis-31661	92	49	wavelength	wavelength	NOUN
fcis-31661	92	50	selection	selection	NOUN
fcis-31661	92	51	,	,	PUNCT
fcis-31661	92	52	based	base	VERB
fcis-31661	92	53	on	on	ADP
fcis-31661	92	54	svc	svc	PROPN
fcis-31661	92	55	,	,	PUNCT
fcis-31661	92	56	dt	dt	PROPN
fcis-31661	92	57	,	,	PUNCT
fcis-31661	92	58	knn	knn	PROPN
fcis-31661	92	59	algorithm	algorithm	PROPN
fcis-31661	92	60	to	to	PART
fcis-31661	92	61	establish	establish	VERB
fcis-31661	92	62	the	the	DET
fcis-31661	92	63	internal	internal	ADJ
fcis-31661	92	64	quality	quality	NOUN
fcis-31661	92	65	classification	classification	NOUN
fcis-31661	92	66	model	model	NOUN
fcis-31661	92	67	of	of	ADP
fcis-31661	92	68	apple	apple	NOUN
fcis-31661	92	69	.	.	PUNCT
fcis-31661	93	1	in	in	ADP
fcis-31661	93	2	the	the	DET
fcis-31661	93	3	constructed	construct	VERB
fcis-31661	93	4	classification	classification	NOUN
fcis-31661	93	5	model	model	NOUN
fcis-31661	93	6	,	,	PUNCT
fcis-31661	93	7	the	the	DET
fcis-31661	93	8	best	good	ADJ
fcis-31661	93	9	apple	apple	NOUN
fcis-31661	93	10	internal	internal	ADJ
fcis-31661	93	11	quality	quality	NOUN
fcis-31661	93	12	classification	classification	NOUN
fcis-31661	93	13	model	model	NOUN
fcis-31661	93	14	based	base	VERB
fcis-31661	93	15	on	on	ADP
fcis-31661	93	16	near	near	ADP
fcis-31661	93	17	infrared	infrared	ADJ
fcis-31661	93	18	spectroscopy	spectroscopy	NOUN
fcis-31661	93	19	is	be	AUX
fcis-31661	93	20	spxy	spxy	ADJ
fcis-31661	94	1	+	+	CCONJ
fcis-31661	94	2	mc	mc	PROPN
fcis-31661	94	3	+	+	NUM
fcis-31661	94	4	cars	car	NOUN
fcis-31661	94	5	+	+	CCONJ
fcis-31661	94	6	dt	dt	NOUN
fcis-31661	94	7	model	model	NOUN
fcis-31661	94	8	,	,	PUNCT
fcis-31661	94	9	which	which	PRON
fcis-31661	94	10	has	have	VERB
fcis-31661	94	11	an	an	DET
fcis-31661	94	12	accuracy	accuracy	NOUN
fcis-31661	94	13	of	of	ADP
fcis-31661	94	14	0.955	0.955	NUM
fcis-31661	94	15	,	,	PUNCT
fcis-31661	94	16	a	a	DET
fcis-31661	94	17	precision	precision	NOUN
fcis-31661	94	18	of	of	ADP
fcis-31661	94	19	0.955	0.955	NUM
fcis-31661	94	20	,	,	PUNCT
fcis-31661	94	21	a	a	DET
fcis-31661	94	22	recall	recall	NOUN
fcis-31661	94	23	of	of	ADP
fcis-31661	94	24	0.955	0.955	NUM
fcis-31661	94	25	,	,	PUNCT
fcis-31661	94	26	and	and	CCONJ
fcis-31661	94	27	an	an	DET
fcis-31661	94	28	f1	f1	ADJ
fcis-31661	94	29	score	score	NOUN
fcis-31661	94	30	of	of	ADP
fcis-31661	94	31	0.955	0.955	NUM
fcis-31661	94	32	.	.	PUNCT
fcis-31661	95	1	the	the	DET
fcis-31661	95	2	experimental	experimental	ADJ
fcis-31661	95	3	results	result	NOUN
fcis-31661	95	4	show	show	VERB
fcis-31661	95	5	that	that	SCONJ
fcis-31661	95	6	the	the	DET
fcis-31661	95	7	nir	nir	ADJ
fcis-31661	95	8	spectroscopy	spectroscopy	NOUN
fcis-31661	95	9	method	method	NOUN
fcis-31661	95	10	can	can	AUX
fcis-31661	95	11	effectively	effectively	ADV
fcis-31661	95	12	classify	classify	VERB
fcis-31661	95	13	the	the	DET
fcis-31661	95	14	internal	internal	ADJ
fcis-31661	95	15	quality	quality	NOUN
fcis-31661	95	16	of	of	ADP
fcis-31661	95	17	apples	apple	NOUN
fcis-31661	95	18	,	,	PUNCT
fcis-31661	95	19	which	which	PRON
fcis-31661	95	20	can	can	AUX
fcis-31661	95	21	be	be	AUX
fcis-31661	95	22	used	use	VERB
fcis-31661	95	23	to	to	PART
fcis-31661	95	24	guide	guide	VERB
fcis-31661	95	25	the	the	DET
fcis-31661	95	26	classification	classification	NOUN
fcis-31661	95	27	processing	processing	NOUN
fcis-31661	95	28	of	of	ADP
fcis-31661	95	29	apples	apple	NOUN
fcis-31661	95	30	after	after	ADP
fcis-31661	95	31	harvest	harvest	NOUN
fcis-31661	95	32	,	,	PUNCT
fcis-31661	95	33	and	and	CCONJ
fcis-31661	95	34	can	can	AUX
fcis-31661	95	35	also	also	ADV
fcis-31661	95	36	provide	provide	VERB
fcis-31661	95	37	theoretical	theoretical	ADJ
fcis-31661	95	38	basis	basis	NOUN
fcis-31661	95	39	for	for	ADP
fcis-31661	95	40	the	the	DET
fcis-31661	95	41	classification	classification	NOUN
fcis-31661	95	42	processing	processing	NOUN
fcis-31661	95	43	of	of	ADP
fcis-31661	95	44	different	different	ADJ
fcis-31661	95	45	varieties	variety	NOUN
fcis-31661	95	46	of	of	ADP
fcis-31661	95	47	fruits	fruit	NOUN
fcis-31661	95	48	after	after	ADP
fcis-31661	95	49	harvest	harvest	NOUN
fcis-31661	95	50	.	.	PUNCT
fcis-31661	96	1	with	with	ADP
fcis-31661	96	2	the	the	DET
fcis-31661	96	3	research	research	NOUN
fcis-31661	96	4	and	and	CCONJ
fcis-31661	96	5	development	development	NOUN
fcis-31661	96	6	of	of	ADP
fcis-31661	96	7	the	the	DET
fcis-31661	96	8	near	near	ADV
fcis-31661	96	9	-	-	PUNCT
fcis-31661	96	10	infrared	infrared	ADJ
fcis-31661	96	11	spectroscopy	spectroscopy	NOUN
fcis-31661	96	12	model	model	NOUN
fcis-31661	96	13	,	,	PUNCT
fcis-31661	96	14	the	the	DET
fcis-31661	96	15	advantages	advantage	NOUN
fcis-31661	96	16	of	of	ADP
fcis-31661	96	17	the	the	DET
fcis-31661	96	18	model	model	NOUN
fcis-31661	96	19	for	for	ADP
fcis-31661	96	20	fruit	fruit	NOUN
fcis-31661	96	21	internal	internal	ADJ
fcis-31661	96	22	quality	quality	NOUN
fcis-31661	96	23	classification	classification	NOUN
fcis-31661	96	24	can	can	AUX
fcis-31661	96	25	be	be	AUX
fcis-31661	96	26	further	far	ADV
fcis-31661	96	27	optimized	optimize	VERB
fcis-31661	96	28	in	in	ADP
fcis-31661	96	29	the	the	DET
fcis-31661	96	30	future	future	NOUN
fcis-31661	96	31	,	,	PUNCT
fcis-31661	96	32	so	so	SCONJ
fcis-31661	96	33	as	as	SCONJ
fcis-31661	96	34	to	to	PART
fcis-31661	96	35	improve	improve	VERB
fcis-31661	96	36	the	the	DET
fcis-31661	96	37	robustness	robustness	NOUN
fcis-31661	96	38	and	and	CCONJ
fcis-31661	96	39	practicability	practicability	NOUN
fcis-31661	96	40	of	of	ADP
fcis-31661	96	41	the	the	DET
fcis-31661	96	42	detection	detection	NOUN
fcis-31661	96	43	technology	technology	NOUN
fcis-31661	96	44	.	.	PUNCT
fcis-31661	97	1	references	reference	NOUN
fcis-31661	97	2	[	[	X
fcis-31661	97	3	1	1	NUM
fcis-31661	97	4	]	]	X
fcis-31661	97	5	guo	guo	PROPN
fcis-31661	97	6	z	z	PROPN
fcis-31661	97	7	,	,	PUNCT
fcis-31661	97	8	chen	chen	PROPN
fcis-31661	97	9	x	x	PROPN
fcis-31661	97	10	,	,	PUNCT
fcis-31661	97	11	zhang	zhang	PROPN
fcis-31661	97	12	y	y	PROPN
fcis-31661	97	13	,	,	PUNCT
fcis-31661	97	14	et	et	PROPN
fcis-31661	97	15	al.dynamic	al.dynamic	ADJ
fcis-31661	97	16	nondestructive	nondestructive	ADJ
fcis-31661	97	17	detection	detection	NOUN
fcis-31661	97	18	models	model	NOUN
fcis-31661	97	19	of	of	ADP
fcis-31661	97	20	apple	apple	NOUN
fcis-31661	97	21	quality	quality	NOUN
fcis-31661	97	22	in	in	ADP
fcis-31661	97	23	critical	critical	ADJ
fcis-31661	97	24	harvest	harvest	NOUN
fcis-31661	97	25	period	period	NOUN
fcis-31661	97	26	based	base	VERB
fcis-31661	97	27	on	on	ADP
fcis-31661	97	28	near	near	ADV
fcis-31661	97	29	-	-	PUNCT
fcis-31661	97	30	infrared	infrared	ADJ
fcis-31661	97	31	spectroscopy	spectroscopy	NOUN
fcis-31661	97	32	and	and	CCONJ
fcis-31661	97	33	intelligent	intelligent	ADJ
fcis-31661	97	34	algorithms	algorithm	NOUN
fcis-31661	97	35	[	[	X
fcis-31661	97	36	j].foods,2024,13(11	j].foods,2024,13(11	NOUN
fcis-31661	97	37	)	)	PUNCT
fcis-31661	97	38	.	.	PUNCT
fcis-31661	98	1	[	[	X
fcis-31661	98	2	2	2	X
fcis-31661	98	3	]	]	PUNCT
fcis-31661	98	4	sanqing	sanqe	VERB
fcis-31661	98	5	l	l	NOUN
fcis-31661	98	6	,	,	PUNCT
fcis-31661	98	7	shuxiang	shuxiang	PROPN
fcis-31661	98	8	f	f	PROPN
fcis-31661	98	9	,	,	PUNCT
fcis-31661	98	10	lin	lin	PROPN
fcis-31661	98	11	l	l	PROPN
fcis-31661	98	12	,	,	PUNCT
fcis-31661	98	13	et	et	PROPN
fcis-31661	98	14	al.an	al.an	PROPN
fcis-31661	98	15	improved	improve	VERB
fcis-31661	98	16	method	method	NOUN
fcis-31661	98	17	for	for	ADP
fcis-31661	98	18	predicting	predict	VERB
fcis-31661	98	19	soluble	soluble	ADJ
fcis-31661	98	20	solids	solid	NOUN
fcis-31661	98	21	content	content	NOUN
fcis-31661	98	22	in	in	ADP
fcis-31661	98	23	apples	apple	NOUN
fcis-31661	98	24	by	by	ADP
fcis-31661	98	25	heterogeneous	heterogeneous	ADJ
fcis-31661	98	26	transfer	transfer	NOUN
fcis-31661	98	27	learning	learning	NOUN
fcis-31661	98	28	and	and	CCONJ
fcis-31661	98	29	near	near	ADV
fcis-31661	98	30	-	-	PUNCT
fcis-31661	98	31	infrared	infrared	ADJ
fcis-31661	98	32	spectroscopy	spectroscopy	NOUN
fcis-31661	98	33	[	[	X
fcis-31661	98	34	j].computers	j].computer	NOUN
fcis-31661	98	35	and	and	CCONJ
fcis-31661	98	36	electronics	electronic	NOUN
fcis-31661	98	37	in	in	ADP
fcis-31661	98	38	agriculture,2022,203	agriculture,2022,203	NOUN
fcis-31661	98	39	.	.	PUNCT
fcis-31661	99	1	[	[	X
fcis-31661	99	2	3	3	NUM
fcis-31661	99	3	]	]	X
fcis-31661	99	4	zhao	zhao	PROPN
fcis-31661	99	5	c	c	PROPN
fcis-31661	99	6	,	,	PUNCT
fcis-31661	99	7	yin	yin	PROPN
fcis-31661	99	8	z	z	PROPN
fcis-31661	99	9	,	,	PUNCT
fcis-31661	99	10	zhang	zhang	PROPN
fcis-31661	99	11	w	w	PROPN
fcis-31661	99	12	,	,	PUNCT
fcis-31661	99	13	et	et	PROPN
fcis-31661	99	14	al.identification	al.identification	NOUN
fcis-31661	99	15	of	of	ADP
fcis-31661	99	16	apple	apple	NOUN
fcis-31661	99	17	watercore	watercore	NOUN
fcis-31661	99	18	based	base	VERB
fcis-31661	99	19	on	on	ADP
fcis-31661	99	20	convnext	convnext	NOUN
fcis-31661	99	21	and	and	CCONJ
fcis-31661	99	22	vis	vis	X
fcis-31661	99	23	/	/	SYM
fcis-31661	99	24	nir	nir	ADJ
fcis-31661	99	25	spectra[j].infrared	spectra[j].infrare	VERB
fcis-31661	99	26	physics	physics	NOUN
fcis-31661	99	27	and	and	CCONJ
fcis-31661	99	28	technology,2024	technology,2024	NOUN
fcis-31661	99	29	.	.	PUNCT
fcis-31661	100	1	[	[	X
fcis-31661	100	2	4	4	NUM
fcis-31661	100	3	]	]	X
fcis-31661	100	4	tian	tian	ADJ
fcis-31661	100	5	h	h	NOUN
fcis-31661	100	6	,	,	PUNCT
fcis-31661	100	7	zhang	zhang	PROPN
fcis-31661	100	8	l	l	PROPN
fcis-31661	100	9	,	,	PUNCT
fcis-31661	100	10	li	li	PROPN
fcis-31661	100	11	m	m	PROPN
fcis-31661	100	12	,	,	PUNCT
fcis-31661	100	13	et	et	PROPN
fcis-31661	100	14	al.weighted	al.weighte	VERB
fcis-31661	100	15	spxy	spxy	NOUN
fcis-31661	100	16	method	method	NOUN
fcis-31661	100	17	for	for	ADP
fcis-31661	100	18	calibration	calibration	NOUN
fcis-31661	100	19	set	set	VERB
fcis-31661	100	20	selection	selection	NOUN
fcis-31661	100	21	for	for	ADP
fcis-31661	100	22	composition	composition	NOUN
fcis-31661	100	23	analysis	analysis	NOUN
fcis-31661	100	24	based	base	VERB
fcis-31661	100	25	on	on	ADP
fcis-31661	100	26	near	near	ADV
fcis-31661	100	27	-	-	PUNCT
fcis-31661	100	28	infrared	infrare	VERB
fcis-31661	100	29	spectroscopy[j].infrared	spectroscopy[j].infrare	VERB
fcis-31661	100	30	physics	physics	NOUN
fcis-31661	100	31	and	and	CCONJ
fcis-31661	100	32	technology	technology	NOUN
fcis-31661	100	33	,	,	PUNCT
fcis-31661	100	34	2018	2018	NUM
fcis-31661	100	35	.	.	PUNCT
fcis-31661	101	1	[	[	X
fcis-31661	101	2	5	5	NUM
fcis-31661	101	3	]	]	PUNCT
fcis-31661	101	4	run	run	NOUN
fcis-31661	101	5	c.	c.	NOUN
fcis-31661	101	6	determination	determination	NOUN
fcis-31661	101	7	of	of	ADP
fcis-31661	101	8	fatty	fatty	NOUN
fcis-31661	101	9	acid	acid	NOUN
fcis-31661	101	10	of	of	ADP
fcis-31661	101	11	wheat	wheat	NOUN
fcis-31661	101	12	by	by	ADP
fcis-31661	101	13	near	near	ADV
fcis-31661	101	14	-	-	PUNCT
fcis-31661	101	15	infrared	infrared	ADJ
fcis-31661	101	16	spectroscopy	spectroscopy	NOUN
fcis-31661	101	17	with	with	ADP
fcis-31661	101	18	combined	combine	VERB
fcis-31661	101	19	feature	feature	NOUN
fcis-31661	101	20	selection	selection	NOUN
fcis-31661	101	21	based	base	VERB
fcis-31661	101	22	on	on	ADP
fcis-31661	101	23	cars	car	NOUN
fcis-31661	101	24	and	and	CCONJ
fcis-31661	101	25	nsga	nsga	NOUN
fcis-31661	101	26	-	-	PUNCT
fcis-31661	101	27	iii[j	iii[j	NOUN
fcis-31661	101	28	]	]	PUNCT
fcis-31661	101	29	.	.	PUNCT
fcis-31661	102	1	infrared	infrared	PROPN
fcis-31661	102	2	physics	physics	PROPN
fcis-31661	102	3	and	and	CCONJ
fcis-31661	102	4	technology,2023,129	technology,2023,129	PROPN
fcis-31661	102	5	.	.	PUNCT