id	sid	tid	token	lemma	pos
ajst-7782	1	1	academic	academic	ADJ
ajst-7782	1	2	journal	journal	NOUN
ajst-7782	1	3	of	of	ADP
ajst-7782	1	4	science	science	NOUN
ajst-7782	1	5	and	and	CCONJ
ajst-7782	1	6	technology	technology	NOUN
ajst-7782	1	7	issn	issn	NOUN
ajst-7782	1	8	:	:	PUNCT
ajst-7782	1	9	2771	2771	NUM
ajst-7782	1	10	-	-	SYM
ajst-7782	1	11	3032	3032	NUM
ajst-7782	1	12	|	|	NOUN
ajst-7782	1	13	vol	vol	NOUN
ajst-7782	1	14	.	.	PROPN
ajst-7782	2	1	5	5	NUM
ajst-7782	2	2	,	,	PUNCT
ajst-7782	2	3	no	no	INTJ
ajst-7782	2	4	.	.	NOUN
ajst-7782	2	5	3	3	NUM
ajst-7782	2	6	,	,	PUNCT
ajst-7782	2	7	2023	2023	NUM
ajst-7782	2	8	85	85	NUM
ajst-7782	2	9	study	study	NOUN
ajst-7782	2	10	on	on	ADP
ajst-7782	2	11	nitrite	nitrite	NOUN
ajst-7782	2	12	nitrogen	nitrogen	NOUN
ajst-7782	2	13	based	base	VERB
ajst-7782	2	14	on	on	ADP
ajst-7782	2	15	ultraviolet	ultraviolet	ADJ
ajst-7782	2	16	visible	visible	ADJ
ajst-7782	2	17	absorption	absorption	NOUN
ajst-7782	2	18	spectrometry	spectrometry	NOUN
ajst-7782	2	19	li	li	PROPN
ajst-7782	2	20	zhang	zhang	PROPN
ajst-7782	2	21	,	,	PUNCT
ajst-7782	2	22	yitong	yitong	NOUN
ajst-7782	2	23	yin	yin	PROPN
ajst-7782	2	24	and	and	CCONJ
ajst-7782	2	25	jinrui	jinrui	PROPN
ajst-7782	2	26	zeng	zeng	PROPN
ajst-7782	2	27	school	school	PROPN
ajst-7782	2	28	of	of	ADP
ajst-7782	2	29	chongqing	chongqing	PROPN
ajst-7782	2	30	university	university	PROPN
ajst-7782	2	31	of	of	ADP
ajst-7782	2	32	posts	post	NOUN
ajst-7782	2	33	and	and	CCONJ
ajst-7782	2	34	telecommunications	telecommunication	NOUN
ajst-7782	2	35	,	,	PUNCT
ajst-7782	2	36	chongqing	chongqe	VERB
ajst-7782	2	37	400065	400065	NUM
ajst-7782	2	38	,	,	PUNCT
ajst-7782	2	39	china	china	PROPN
ajst-7782	2	40	abstract	abstract	PROPN
ajst-7782	2	41	:	:	PUNCT
ajst-7782	2	42	in	in	ADP
ajst-7782	2	43	order	order	NOUN
ajst-7782	2	44	to	to	PART
ajst-7782	2	45	improve	improve	VERB
ajst-7782	2	46	the	the	DET
ajst-7782	2	47	accuracy	accuracy	NOUN
ajst-7782	2	48	of	of	ADP
ajst-7782	2	49	nitrite	nitrite	NOUN
ajst-7782	2	50	nitrogen	nitrogen	NOUN
ajst-7782	2	51	detection	detection	NOUN
ajst-7782	2	52	,	,	PUNCT
ajst-7782	2	53	this	this	DET
ajst-7782	2	54	template	template	NOUN
ajst-7782	2	55	proposed	propose	VERB
ajst-7782	2	56	a	a	DET
ajst-7782	2	57	method	method	NOUN
ajst-7782	2	58	for	for	ADP
ajst-7782	2	59	rapid	rapid	ADJ
ajst-7782	2	60	determination	determination	NOUN
ajst-7782	2	61	of	of	ADP
ajst-7782	2	62	nitrite	nitrite	NOUN
ajst-7782	2	63	nitrogen	nitrogen	NOUN
ajst-7782	2	64	in	in	ADP
ajst-7782	2	65	water	water	NOUN
ajst-7782	2	66	based	base	VERB
ajst-7782	2	67	on	on	ADP
ajst-7782	2	68	ultraviolet	ultraviolet	ADJ
ajst-7782	2	69	visible	visible	ADJ
ajst-7782	2	70	absorption	absorption	NOUN
ajst-7782	2	71	spectroscopy	spectroscopy	NOUN
ajst-7782	2	72	.	.	PUNCT
ajst-7782	3	1	the	the	DET
ajst-7782	3	2	experimental	experimental	ADJ
ajst-7782	3	3	object	object	NOUN
ajst-7782	3	4	is	be	AUX
ajst-7782	3	5	the	the	DET
ajst-7782	3	6	absorption	absorption	NOUN
ajst-7782	3	7	spectrum	spectrum	NOUN
ajst-7782	3	8	of	of	ADP
ajst-7782	3	9	sodium	sodium	NOUN
ajst-7782	3	10	nitrite	nitrite	NOUN
ajst-7782	3	11	standard	standard	ADJ
ajst-7782	3	12	solution	solution	NOUN
ajst-7782	3	13	with	with	ADP
ajst-7782	3	14	a	a	DET
ajst-7782	3	15	concentration	concentration	NOUN
ajst-7782	3	16	range	range	NOUN
ajst-7782	3	17	of	of	ADP
ajst-7782	3	18	0.1	0.1	NUM
ajst-7782	3	19	to	to	PART
ajst-7782	3	20	17	17	NUM
ajst-7782	3	21	mg·l-1	mg·l-1	PROPN
ajst-7782	3	22	,	,	PUNCT
ajst-7782	3	23	the	the	DET
ajst-7782	3	24	continuous	continuous	ADJ
ajst-7782	3	25	projection	projection	NOUN
ajst-7782	3	26	algorithm	algorithm	NOUN
ajst-7782	3	27	spa	spa	NOUN
ajst-7782	3	28	(	(	PUNCT
ajst-7782	3	29	continuous	continuous	ADJ
ajst-7782	3	30	projections	projection	NOUN
ajst-7782	3	31	algorithm	algorithm	NOUN
ajst-7782	3	32	)	)	PUNCT
ajst-7782	3	33	is	be	AUX
ajst-7782	3	34	used	use	VERB
ajst-7782	3	35	to	to	PART
ajst-7782	3	36	screen	screen	VERB
ajst-7782	3	37	out	out	ADP
ajst-7782	3	38	the	the	DET
ajst-7782	3	39	characteristic	characteristic	ADJ
ajst-7782	3	40	wavelengths	wavelength	NOUN
ajst-7782	3	41	related	relate	VERB
ajst-7782	3	42	to	to	ADP
ajst-7782	3	43	nitrite	nitrite	NOUN
ajst-7782	3	44	nitrogen	nitrogen	NOUN
ajst-7782	3	45	.	.	PUNCT
ajst-7782	4	1	the	the	DET
ajst-7782	4	2	absorbance	absorbance	NOUN
ajst-7782	4	3	at	at	ADP
ajst-7782	4	4	the	the	DET
ajst-7782	4	5	characteristic	characteristic	ADJ
ajst-7782	4	6	wavelengths	wavelength	NOUN
ajst-7782	4	7	and	and	CCONJ
ajst-7782	4	8	the	the	DET
ajst-7782	4	9	sample	sample	NOUN
ajst-7782	4	10	concentration	concentration	NOUN
ajst-7782	4	11	are	be	AUX
ajst-7782	4	12	fitted	fit	VERB
ajst-7782	4	13	using	use	VERB
ajst-7782	4	14	support	support	NOUN
ajst-7782	4	15	vector	vector	NOUN
ajst-7782	4	16	regression	regression	NOUN
ajst-7782	4	17	(	(	PUNCT
ajst-7782	4	18	svr	svr	PROPN
ajst-7782	4	19	)	)	PUNCT
ajst-7782	4	20	to	to	PART
ajst-7782	4	21	establish	establish	VERB
ajst-7782	4	22	a	a	DET
ajst-7782	4	23	regression	regression	NOUN
ajst-7782	4	24	model	model	NOUN
ajst-7782	4	25	for	for	ADP
ajst-7782	4	26	nitrite	nitrite	NOUN
ajst-7782	4	27	nitrogen	nitrogen	NOUN
ajst-7782	4	28	,	,	PUNCT
ajst-7782	4	29	the	the	DET
ajst-7782	4	30	decision	decision	NOUN
ajst-7782	4	31	coefficient	coefficient	NOUN
ajst-7782	4	32	r2	r2	NOUN
ajst-7782	4	33	and	and	CCONJ
ajst-7782	4	34	root	root	NOUN
ajst-7782	4	35	mean	mean	ADJ
ajst-7782	4	36	square	square	ADJ
ajst-7782	4	37	error	error	NOUN
ajst-7782	4	38	rmse	rmse	NOUN
ajst-7782	4	39	are	be	AUX
ajst-7782	4	40	used	use	VERB
ajst-7782	4	41	as	as	ADP
ajst-7782	4	42	the	the	DET
ajst-7782	4	43	evaluation	evaluation	NOUN
ajst-7782	4	44	indicators	indicator	NOUN
ajst-7782	4	45	of	of	ADP
ajst-7782	4	46	the	the	DET
ajst-7782	4	47	model	model	NOUN
ajst-7782	4	48	.	.	PUNCT
ajst-7782	5	1	the	the	DET
ajst-7782	5	2	experiment	experiment	NOUN
ajst-7782	5	3	found	find	VERB
ajst-7782	5	4	that	that	SCONJ
ajst-7782	5	5	the	the	DET
ajst-7782	5	6	r2	r2	PROPN
ajst-7782	5	7	and	and	CCONJ
ajst-7782	5	8	rmse	rmse	NOUN
ajst-7782	5	9	of	of	ADP
ajst-7782	5	10	the	the	DET
ajst-7782	5	11	mixed	mixed	ADJ
ajst-7782	5	12	prediction	prediction	NOUN
ajst-7782	5	13	model	model	NOUN
ajst-7782	5	14	established	establish	VERB
ajst-7782	5	15	using	use	VERB
ajst-7782	5	16	the	the	DET
ajst-7782	5	17	continuous	continuous	ADJ
ajst-7782	5	18	projection	projection	NOUN
ajst-7782	5	19	algorithm	algorithm	NOUN
ajst-7782	5	20	support	support	NOUN
ajst-7782	5	21	vector	vector	NOUN
ajst-7782	5	22	regression	regression	NOUN
ajst-7782	5	23	(	(	PUNCT
ajst-7782	5	24	spa	spa	NOUN
ajst-7782	5	25	-	-	PUNCT
ajst-7782	5	26	svr	svr	NOUN
ajst-7782	5	27	)	)	PUNCT
ajst-7782	5	28	modeling	modeling	NOUN
ajst-7782	5	29	method	method	NOUN
ajst-7782	5	30	were	be	AUX
ajst-7782	5	31	0.999654	0.999654	NUM
ajst-7782	5	32	and	and	CCONJ
ajst-7782	5	33	0.000479	0.000479	NUM
ajst-7782	5	34	mg·l1	mg·l1	ADJ
ajst-7782	5	35	respectively	respectively	ADV
ajst-7782	5	36	,	,	PUNCT
ajst-7782	5	37	and	and	CCONJ
ajst-7782	5	38	their	their	PRON
ajst-7782	5	39	modeling	modeling	NOUN
ajst-7782	5	40	effects	effect	NOUN
ajst-7782	5	41	were	be	AUX
ajst-7782	5	42	better	well	ADJ
ajst-7782	5	43	than	than	ADP
ajst-7782	5	44	those	those	PRON
ajst-7782	5	45	of	of	ADP
ajst-7782	5	46	the	the	DET
ajst-7782	5	47	three	three	NUM
ajst-7782	5	48	mixed	mixed	ADJ
ajst-7782	5	49	prediction	prediction	NOUN
ajst-7782	5	50	models	model	NOUN
ajst-7782	5	51	,	,	PUNCT
ajst-7782	5	52	kpca	kpca	NOUN
ajst-7782	5	53	-	-	PUNCT
ajst-7782	5	54	svr	svr	PROPN
ajst-7782	5	55	,	,	PUNCT
ajst-7782	5	56	pca	pca	NOUN
ajst-7782	5	57	-	-	PUNCT
ajst-7782	5	58	svr	svr	PROPN
ajst-7782	5	59	,	,	PUNCT
ajst-7782	5	60	and	and	CCONJ
ajst-7782	5	61	lasso	lasso	NOUN
ajst-7782	5	62	-	-	PUNCT
ajst-7782	5	63	svr	svr	NOUN
ajst-7782	5	64	,	,	PUNCT
ajst-7782	5	65	achieving	achieve	VERB
ajst-7782	5	66	rapid	rapid	ADJ
ajst-7782	5	67	and	and	CCONJ
ajst-7782	5	68	accurate	accurate	ADJ
ajst-7782	5	69	measurement	measurement	NOUN
ajst-7782	5	70	of	of	ADP
ajst-7782	5	71	nitrite	nitrite	NOUN
ajst-7782	5	72	nitrogen	nitrogen	NOUN
ajst-7782	5	73	.	.	PUNCT
ajst-7782	6	1	keywords	keyword	NOUN
ajst-7782	6	2	:	:	PUNCT
ajst-7782	6	3	nitrite	nitrite	NOUN
ajst-7782	6	4	nitrogen	nitrogen	NOUN
ajst-7782	6	5	,	,	PUNCT
ajst-7782	6	6	absorption	absorption	NOUN
ajst-7782	6	7	spectrum	spectrum	NOUN
ajst-7782	6	8	,	,	PUNCT
ajst-7782	6	9	water	water	NOUN
ajst-7782	6	10	quality	quality	NOUN
ajst-7782	6	11	detecting	detecting	NOUN
ajst-7782	6	12	.	.	PUNCT
ajst-7782	7	1	1	1	X
ajst-7782	7	2	.	.	X
ajst-7782	7	3	introduction	introduction	NOUN
ajst-7782	7	4	with	with	ADP
ajst-7782	7	5	the	the	DET
ajst-7782	7	6	continuous	continuous	ADJ
ajst-7782	7	7	improvement	improvement	NOUN
ajst-7782	7	8	of	of	ADP
ajst-7782	7	9	contemporary	contemporary	ADJ
ajst-7782	7	10	human	human	ADJ
ajst-7782	7	11	living	living	NOUN
ajst-7782	7	12	standards	standard	NOUN
ajst-7782	7	13	and	and	CCONJ
ajst-7782	7	14	the	the	DET
ajst-7782	7	15	rapid	rapid	ADJ
ajst-7782	7	16	development	development	NOUN
ajst-7782	7	17	of	of	ADP
ajst-7782	7	18	society	society	NOUN
ajst-7782	7	19	,	,	PUNCT
ajst-7782	7	20	the	the	DET
ajst-7782	7	21	problem	problem	NOUN
ajst-7782	7	22	of	of	ADP
ajst-7782	7	23	water	water	NOUN
ajst-7782	7	24	pollution	pollution	NOUN
ajst-7782	7	25	is	be	AUX
ajst-7782	7	26	becoming	become	VERB
ajst-7782	7	27	increasingly	increasingly	ADV
ajst-7782	7	28	serious	serious	ADJ
ajst-7782	7	29	,	,	PUNCT
ajst-7782	7	30	and	and	CCONJ
ajst-7782	7	31	its	its	PRON
ajst-7782	7	32	detection	detection	NOUN
ajst-7782	7	33	and	and	CCONJ
ajst-7782	7	34	remediation	remediation	NOUN
ajst-7782	7	35	has	have	AUX
ajst-7782	7	36	become	become	VERB
ajst-7782	7	37	a	a	DET
ajst-7782	7	38	social	social	ADJ
ajst-7782	7	39	hotspot	hotspot	NOUN
ajst-7782	7	40	.	.	PUNCT
ajst-7782	8	1	when	when	SCONJ
ajst-7782	8	2	the	the	DET
ajst-7782	8	3	nitrogen	nitrogen	NOUN
ajst-7782	8	4	content	content	NOUN
ajst-7782	8	5	in	in	ADP
ajst-7782	8	6	the	the	DET
ajst-7782	8	7	water	water	NOUN
ajst-7782	8	8	body	body	NOUN
ajst-7782	8	9	is	be	AUX
ajst-7782	8	10	too	too	ADV
ajst-7782	8	11	high	high	ADJ
ajst-7782	8	12	,	,	PUNCT
ajst-7782	8	13	eutrophication	eutrophication	NOUN
ajst-7782	8	14	will	will	AUX
ajst-7782	8	15	occur	occur	VERB
ajst-7782	8	16	in	in	ADP
ajst-7782	8	17	the	the	DET
ajst-7782	8	18	water	water	NOUN
ajst-7782	8	19	body	body	NOUN
ajst-7782	8	20	,	,	PUNCT
ajst-7782	8	21	resulting	result	VERB
ajst-7782	8	22	in	in	ADP
ajst-7782	8	23	excessive	excessive	ADJ
ajst-7782	8	24	algae	algae	NOUN
ajst-7782	8	25	,	,	PUNCT
ajst-7782	8	26	thereby	thereby	ADV
ajst-7782	8	27	reducing	reduce	VERB
ajst-7782	8	28	the	the	DET
ajst-7782	8	29	dissolved	dissolve	VERB
ajst-7782	8	30	oxygen	oxygen	NOUN
ajst-7782	8	31	content	content	NOUN
ajst-7782	8	32	in	in	ADP
ajst-7782	8	33	the	the	DET
ajst-7782	8	34	water[1	water[1	PROPN
ajst-7782	8	35	]	]	X
ajst-7782	8	36	.	.	PUNCT
ajst-7782	9	1	when	when	SCONJ
ajst-7782	9	2	excessive	excessive	ADJ
ajst-7782	9	3	nitrite	nitrite	NOUN
ajst-7782	9	4	enters	enter	VERB
ajst-7782	9	5	the	the	DET
ajst-7782	9	6	human	human	ADJ
ajst-7782	9	7	body	body	NOUN
ajst-7782	9	8	,	,	PUNCT
ajst-7782	9	9	it	it	PRON
ajst-7782	9	10	can	can	AUX
ajst-7782	9	11	harm	harm	VERB
ajst-7782	9	12	human	human	ADJ
ajst-7782	9	13	organs	organ	NOUN
ajst-7782	9	14	and	and	CCONJ
ajst-7782	9	15	ultimately	ultimately	ADV
ajst-7782	9	16	cause	cause	VERB
ajst-7782	9	17	serious	serious	ADJ
ajst-7782	9	18	damage[2	damage[2	NOUN
ajst-7782	9	19	]	]	PUNCT
ajst-7782	9	20	.	.	PUNCT
ajst-7782	10	1	therefore	therefore	ADV
ajst-7782	10	2	,	,	PUNCT
ajst-7782	10	3	it	it	PRON
ajst-7782	10	4	is	be	AUX
ajst-7782	10	5	necessary	necessary	ADJ
ajst-7782	10	6	to	to	PART
ajst-7782	10	7	quickly	quickly	ADV
ajst-7782	10	8	and	and	CCONJ
ajst-7782	10	9	accurately	accurately	ADV
ajst-7782	10	10	detect	detect	VERB
ajst-7782	10	11	nitrite	nitrite	NOUN
ajst-7782	10	12	nitrogen	nitrogen	NOUN
ajst-7782	10	13	in	in	ADP
ajst-7782	10	14	water	water	NOUN
ajst-7782	10	15	.	.	PUNCT
ajst-7782	11	1	for	for	ADP
ajst-7782	11	2	the	the	DET
ajst-7782	11	3	detection	detection	NOUN
ajst-7782	11	4	of	of	ADP
ajst-7782	11	5	nitrite	nitrite	NOUN
ajst-7782	11	6	nitrogen	nitrogen	NOUN
ajst-7782	11	7	,	,	PUNCT
ajst-7782	11	8	traditional	traditional	ADJ
ajst-7782	11	9	methods	method	NOUN
ajst-7782	11	10	mainly	mainly	ADV
ajst-7782	11	11	include	include	VERB
ajst-7782	11	12	chromatography	chromatography	NOUN
ajst-7782	11	13	,	,	PUNCT
ajst-7782	11	14	chemiluminescence	chemiluminescence	NOUN
ajst-7782	11	15	,	,	PUNCT
ajst-7782	11	16	spectrophotometry	spectrophotometry	NOUN
ajst-7782	11	17	,	,	PUNCT
ajst-7782	11	18	electrochemical	electrochemical	ADJ
ajst-7782	11	19	methods	method	NOUN
ajst-7782	11	20	,	,	PUNCT
ajst-7782	11	21	etc.[3	etc.[3	PROPN
ajst-7782	11	22	]	]	PUNCT
ajst-7782	11	23	.	.	PUNCT
ajst-7782	12	1	traditional	traditional	ADJ
ajst-7782	12	2	methods	method	NOUN
ajst-7782	12	3	have	have	VERB
ajst-7782	12	4	shortcomings	shortcoming	NOUN
ajst-7782	12	5	such	such	ADJ
ajst-7782	12	6	as	as	ADP
ajst-7782	12	7	long	long	ADJ
ajst-7782	12	8	experimental	experimental	ADJ
ajst-7782	12	9	cycles	cycle	NOUN
ajst-7782	12	10	,	,	PUNCT
ajst-7782	12	11	harsh	harsh	ADJ
ajst-7782	12	12	experimental	experimental	ADJ
ajst-7782	12	13	conditions	condition	NOUN
ajst-7782	12	14	,	,	PUNCT
ajst-7782	12	15	and	and	CCONJ
ajst-7782	12	16	environmental	environmental	ADJ
ajst-7782	12	17	damage	damage	NOUN
ajst-7782	12	18	.	.	PUNCT
ajst-7782	13	1	compared	compare	VERB
ajst-7782	13	2	to	to	ADP
ajst-7782	13	3	traditional	traditional	ADJ
ajst-7782	13	4	detection	detection	NOUN
ajst-7782	13	5	methods	method	NOUN
ajst-7782	13	6	,	,	PUNCT
ajst-7782	13	7	spectral	spectral	ADJ
ajst-7782	13	8	methods	method	NOUN
ajst-7782	13	9	have	have	VERB
ajst-7782	13	10	the	the	DET
ajst-7782	13	11	advantages	advantage	NOUN
ajst-7782	13	12	of	of	ADP
ajst-7782	13	13	simple	simple	ADJ
ajst-7782	13	14	operation	operation	NOUN
ajst-7782	13	15	,	,	PUNCT
ajst-7782	13	16	continuous	continuous	ADJ
ajst-7782	13	17	detection	detection	NOUN
ajst-7782	13	18	,	,	PUNCT
ajst-7782	13	19	and	and	CCONJ
ajst-7782	13	20	no	no	DET
ajst-7782	13	21	pollution	pollution	NOUN
ajst-7782	13	22	.	.	PUNCT
ajst-7782	14	1	therefore	therefore	ADV
ajst-7782	14	2	,	,	PUNCT
ajst-7782	14	3	this	this	DET
ajst-7782	14	4	method	method	NOUN
ajst-7782	14	5	has	have	AUX
ajst-7782	14	6	been	be	AUX
ajst-7782	14	7	a	a	DET
ajst-7782	14	8	hot	hot	ADJ
ajst-7782	14	9	spot	spot	NOUN
ajst-7782	14	10	in	in	ADP
ajst-7782	14	11	the	the	DET
ajst-7782	14	12	field	field	NOUN
ajst-7782	14	13	of	of	ADP
ajst-7782	14	14	water	water	NOUN
ajst-7782	14	15	detection	detection	NOUN
ajst-7782	14	16	since	since	SCONJ
ajst-7782	14	17	its	its	PRON
ajst-7782	14	18	inception	inception	NOUN
ajst-7782	14	19	[	[	X
ajst-7782	14	20	4	4	NUM
ajst-7782	14	21	]	]	PUNCT
ajst-7782	14	22	.	.	PUNCT
ajst-7782	15	1	wang[5	wang[5	NOUN
ajst-7782	15	2	]	]	PUNCT
ajst-7782	15	3	et	et	PROPN
ajst-7782	15	4	al	al	PROPN
ajst-7782	15	5	.	.	PROPN
ajst-7782	15	6	determined	determine	VERB
ajst-7782	15	7	nitrite	nitrite	NOUN
ajst-7782	15	8	nitrogen	nitrogen	NOUN
ajst-7782	15	9	in	in	ADP
ajst-7782	15	10	water	water	NOUN
ajst-7782	15	11	through	through	ADP
ajst-7782	15	12	second	second	ADJ
ajst-7782	15	13	derivative	derivative	ADJ
ajst-7782	15	14	analysis	analysis	NOUN
ajst-7782	15	15	of	of	ADP
ajst-7782	15	16	uv	uv	NOUN
ajst-7782	15	17	absorption	absorption	NOUN
ajst-7782	15	18	spectrum	spectrum	NOUN
ajst-7782	15	19	,	,	PUNCT
ajst-7782	15	20	but	but	CCONJ
ajst-7782	15	21	its	its	PRON
ajst-7782	15	22	standard	standard	ADJ
ajst-7782	15	23	color	color	NOUN
ajst-7782	15	24	scale	scale	NOUN
ajst-7782	15	25	is	be	AUX
ajst-7782	15	26	unstable	unstable	ADJ
ajst-7782	15	27	and	and	CCONJ
ajst-7782	15	28	its	its	PRON
ajst-7782	15	29	sensitivity	sensitivity	NOUN
ajst-7782	15	30	is	be	AUX
ajst-7782	15	31	low	low	ADJ
ajst-7782	15	32	.	.	PUNCT
ajst-7782	16	1	li	li	PROPN
ajst-7782	17	1	qingbo[6	qingbo[6	AUX
ajst-7782	17	2	]	]	PUNCT
ajst-7782	17	3	and	and	CCONJ
ajst-7782	17	4	others	other	NOUN
ajst-7782	17	5	used	use	VERB
ajst-7782	17	6	partial	partial	ADJ
ajst-7782	17	7	least	least	ADJ
ajst-7782	17	8	square	square	ADJ
ajst-7782	17	9	regression	regression	NOUN
ajst-7782	17	10	to	to	PART
ajst-7782	17	11	detect	detect	VERB
ajst-7782	17	12	the	the	DET
ajst-7782	17	13	content	content	NOUN
ajst-7782	17	14	of	of	ADP
ajst-7782	17	15	nitrite	nitrite	NOUN
ajst-7782	17	16	in	in	ADP
ajst-7782	17	17	surface	surface	NOUN
ajst-7782	17	18	water	water	NOUN
ajst-7782	17	19	,	,	PUNCT
ajst-7782	17	20	but	but	CCONJ
ajst-7782	17	21	the	the	DET
ajst-7782	17	22	sample	sample	NOUN
ajst-7782	17	23	size	size	NOUN
ajst-7782	17	24	is	be	AUX
ajst-7782	17	25	too	too	ADV
ajst-7782	17	26	small	small	ADJ
ajst-7782	17	27	,	,	PUNCT
ajst-7782	17	28	and	and	CCONJ
ajst-7782	17	29	the	the	DET
ajst-7782	17	30	relative	relative	ADJ
ajst-7782	17	31	error	error	NOUN
ajst-7782	17	32	of	of	ADP
ajst-7782	17	33	low	low	ADJ
ajst-7782	17	34	concentration	concentration	NOUN
ajst-7782	17	35	is	be	AUX
ajst-7782	17	36	large	large	ADJ
ajst-7782	17	37	.	.	PUNCT
ajst-7782	17	38	uusheimo[7	uusheimo[7	PRON
ajst-7782	17	39	]	]	PUNCT
ajst-7782	17	40	et	et	PROPN
ajst-7782	17	41	al	al	PROPN
ajst-7782	17	42	.	.	PROPN
ajst-7782	17	43	used	use	VERB
ajst-7782	17	44	ultraviolet	ultraviolet	ADJ
ajst-7782	17	45	visible	visible	ADJ
ajst-7782	17	46	spectroscopic	spectroscopic	NOUN
ajst-7782	17	47	sensors	sensor	NOUN
ajst-7782	17	48	with	with	ADP
ajst-7782	17	49	two	two	NUM
ajst-7782	17	50	different	different	ADJ
ajst-7782	17	51	optical	optical	ADJ
ajst-7782	17	52	paths	path	NOUN
ajst-7782	17	53	of	of	ADP
ajst-7782	17	54	5	5	NUM
ajst-7782	17	55	nm	nm	NOUN
ajst-7782	17	56	and	and	CCONJ
ajst-7782	17	57	35	35	NUM
ajst-7782	17	58	nm	nm	NOUN
ajst-7782	17	59	to	to	PART
ajst-7782	17	60	detect	detect	VERB
ajst-7782	17	61	cold	cold	ADJ
ajst-7782	17	62	water	water	NOUN
ajst-7782	17	63	dissolved	dissolve	VERB
ajst-7782	17	64	in	in	ADP
ajst-7782	17	65	nitrate	nitrate	NOUN
ajst-7782	17	66	nitrogen	nitrogen	NOUN
ajst-7782	17	67	,	,	PUNCT
ajst-7782	17	68	nitrite	nitrite	NOUN
ajst-7782	17	69	nitrogen	nitrogen	NOUN
ajst-7782	17	70	,	,	PUNCT
ajst-7782	17	71	and	and	CCONJ
ajst-7782	17	72	organic	organic	ADJ
ajst-7782	17	73	carbon	carbon	NOUN
ajst-7782	17	74	.	.	PUNCT
ajst-7782	18	1	due	due	ADP
ajst-7782	18	2	to	to	ADP
ajst-7782	18	3	insufficient	insufficient	ADJ
ajst-7782	18	4	use	use	NOUN
ajst-7782	18	5	of	of	ADP
ajst-7782	18	6	useful	useful	ADJ
ajst-7782	18	7	spectral	spectral	ADJ
ajst-7782	18	8	information	information	NOUN
ajst-7782	18	9	,	,	PUNCT
ajst-7782	18	10	measurement	measurement	NOUN
ajst-7782	18	11	accuracy	accuracy	NOUN
ajst-7782	18	12	is	be	AUX
ajst-7782	18	13	limited	limited	ADJ
ajst-7782	18	14	.	.	PUNCT
ajst-7782	19	1	in	in	ADP
ajst-7782	19	2	order	order	NOUN
ajst-7782	19	3	to	to	PART
ajst-7782	19	4	improve	improve	VERB
ajst-7782	19	5	the	the	DET
ajst-7782	19	6	detection	detection	NOUN
ajst-7782	19	7	accuracy	accuracy	NOUN
ajst-7782	19	8	of	of	ADP
ajst-7782	19	9	nitrite	nitrite	NOUN
ajst-7782	19	10	nitrogen	nitrogen	NOUN
ajst-7782	19	11	in	in	ADP
ajst-7782	19	12	water	water	NOUN
ajst-7782	19	13	,	,	PUNCT
ajst-7782	19	14	a	a	DET
ajst-7782	19	15	hybrid	hybrid	ADJ
ajst-7782	19	16	prediction	prediction	NOUN
ajst-7782	19	17	model	model	NOUN
ajst-7782	19	18	based	base	VERB
ajst-7782	19	19	on	on	ADP
ajst-7782	19	20	uv	uv	PROPN
ajst-7782	19	21	visible	visible	ADJ
ajst-7782	19	22	absorption	absorption	NOUN
ajst-7782	19	23	spectroscopy	spectroscopy	NOUN
ajst-7782	19	24	,	,	PUNCT
ajst-7782	19	25	continuous	continuous	ADJ
ajst-7782	19	26	projections	projection	NOUN
ajst-7782	19	27	algorithm	algorithm	NOUN
ajst-7782	19	28	support	support	NOUN
ajst-7782	19	29	vector	vector	NOUN
ajst-7782	19	30	regression	regression	NOUN
ajst-7782	19	31	(	(	PUNCT
ajst-7782	19	32	spa	spa	NOUN
ajst-7782	19	33	-	-	PUNCT
ajst-7782	19	34	svr	svr	NOUN
ajst-7782	19	35	)	)	PUNCT
ajst-7782	19	36	,	,	PUNCT
ajst-7782	19	37	is	be	AUX
ajst-7782	19	38	proposed	propose	VERB
ajst-7782	19	39	in	in	ADP
ajst-7782	19	40	this	this	DET
ajst-7782	19	41	paper	paper	NOUN
ajst-7782	19	42	.	.	PUNCT
ajst-7782	20	1	first	first	ADV
ajst-7782	20	2	,	,	PUNCT
ajst-7782	20	3	perform	perform	VERB
ajst-7782	20	4	sg	sg	ADP
ajst-7782	20	5	filtering	filter	VERB
ajst-7782	20	6	on	on	ADP
ajst-7782	20	7	the	the	DET
ajst-7782	20	8	original	original	ADJ
ajst-7782	20	9	spectrum	spectrum	NOUN
ajst-7782	20	10	,	,	PUNCT
ajst-7782	20	11	then	then	ADV
ajst-7782	20	12	select	select	VERB
ajst-7782	20	13	the	the	DET
ajst-7782	20	14	characteristic	characteristic	ADJ
ajst-7782	20	15	wavelength	wavelength	NOUN
ajst-7782	20	16	of	of	ADP
ajst-7782	20	17	the	the	DET
ajst-7782	20	18	spectral	spectral	ADJ
ajst-7782	20	19	data	datum	NOUN
ajst-7782	20	20	using	use	VERB
ajst-7782	20	21	the	the	DET
ajst-7782	20	22	continuous	continuous	ADJ
ajst-7782	20	23	projections	projection	NOUN
ajst-7782	20	24	algorithm	algorithm	NOUN
ajst-7782	20	25	(	(	PUNCT
ajst-7782	20	26	spa	spa	NOUN
ajst-7782	20	27	)	)	PUNCT
ajst-7782	20	28	,	,	PUNCT
ajst-7782	20	29	and	and	CCONJ
ajst-7782	20	30	then	then	ADV
ajst-7782	20	31	use	use	VERB
ajst-7782	20	32	the	the	DET
ajst-7782	20	33	support	support	NOUN
ajst-7782	20	34	vector	vector	NOUN
ajst-7782	20	35	regression	regression	NOUN
ajst-7782	20	36	(	(	PUNCT
ajst-7782	20	37	svr	svr	PROPN
ajst-7782	20	38	)	)	PUNCT
ajst-7782	20	39	algorithm	algorithm	NOUN
ajst-7782	20	40	to	to	PART
ajst-7782	20	41	establish	establish	VERB
ajst-7782	20	42	a	a	DET
ajst-7782	20	43	regression	regression	NOUN
ajst-7782	20	44	model	model	NOUN
ajst-7782	20	45	to	to	PART
ajst-7782	20	46	analyze	analyze	VERB
ajst-7782	20	47	a	a	DET
ajst-7782	20	48	series	series	NOUN
ajst-7782	20	49	of	of	ADP
ajst-7782	20	50	concentrations	concentration	NOUN
ajst-7782	20	51	of	of	ADP
ajst-7782	20	52	nitrite	nitrite	NOUN
ajst-7782	20	53	nitrogen	nitrogen	NOUN
ajst-7782	20	54	solutions	solution	NOUN
ajst-7782	20	55	,	,	PUNCT
ajst-7782	20	56	achieving	achieve	VERB
ajst-7782	20	57	rapid	rapid	ADJ
ajst-7782	20	58	and	and	CCONJ
ajst-7782	20	59	real	real	ADJ
ajst-7782	20	60	-	-	PUNCT
ajst-7782	20	61	time	time	NOUN
ajst-7782	20	62	detection	detection	NOUN
ajst-7782	20	63	of	of	ADP
ajst-7782	20	64	nitrite	nitrite	NOUN
ajst-7782	20	65	nitrogen	nitrogen	NOUN
ajst-7782	20	66	.	.	PUNCT
ajst-7782	21	1	2	2	X
ajst-7782	21	2	.	.	X
ajst-7782	21	3	experiment	experiment	NOUN
ajst-7782	21	4	2.1	2.1	NUM
ajst-7782	21	5	.	.	PUNCT
ajst-7782	22	1	experimental	experimental	ADJ
ajst-7782	22	2	device	device	NOUN
ajst-7782	22	3	an	an	DET
ajst-7782	22	4	experimental	experimental	ADJ
ajst-7782	22	5	platform	platform	NOUN
ajst-7782	22	6	for	for	ADP
ajst-7782	22	7	ultraviolet	ultraviolet	ADJ
ajst-7782	22	8	visible	visible	ADJ
ajst-7782	22	9	absorption	absorption	NOUN
ajst-7782	22	10	spectroscopy	spectroscopy	NOUN
ajst-7782	22	11	was	be	AUX
ajst-7782	22	12	established	establish	VERB
ajst-7782	22	13	,	,	PUNCT
ajst-7782	22	14	mainly	mainly	ADV
ajst-7782	22	15	including	include	VERB
ajst-7782	22	16	light	light	ADJ
ajst-7782	22	17	sources	source	NOUN
ajst-7782	22	18	,	,	PUNCT
ajst-7782	22	19	sample	sample	NOUN
ajst-7782	22	20	cells	cell	NOUN
ajst-7782	22	21	,	,	PUNCT
ajst-7782	22	22	fiber	fiber	NOUN
ajst-7782	22	23	optic	optic	ADJ
ajst-7782	22	24	collimators	collimator	NOUN
ajst-7782	22	25	,	,	PUNCT
ajst-7782	22	26	spectrometers	spectrometer	NOUN
ajst-7782	22	27	,	,	PUNCT
ajst-7782	22	28	and	and	CCONJ
ajst-7782	22	29	computers	computer	NOUN
ajst-7782	22	30	,	,	PUNCT
ajst-7782	22	31	as	as	SCONJ
ajst-7782	22	32	shown	show	VERB
ajst-7782	22	33	in	in	ADP
ajst-7782	22	34	figure	figure	NOUN
ajst-7782	22	35	1	1	NUM
ajst-7782	22	36	.	.	PUNCT
ajst-7782	23	1	the	the	DET
ajst-7782	23	2	deuterium	deuterium	PROPN
ajst-7782	23	3	halide	halide	PROPN
ajst-7782	23	4	lamp	lamp	PROPN
ajst-7782	23	5	(	(	PUNCT
ajst-7782	23	6	wenyi	wenyi	NOUN
ajst-7782	23	7	optoelectronics	optoelectronic	NOUN
ajst-7782	23	8	,	,	PUNCT
ajst-7782	23	9	dh	dh	NOUN
ajst-7782	23	10	-	-	PUNCT
ajst-7782	23	11	mini	mini	ADJ
ajst-7782	23	12	compact	compact	ADJ
ajst-7782	23	13	type	type	NOUN
ajst-7782	23	14	)	)	PUNCT
ajst-7782	23	15	is	be	AUX
ajst-7782	23	16	used	use	VERB
ajst-7782	23	17	as	as	ADP
ajst-7782	23	18	the	the	DET
ajst-7782	23	19	light	light	ADJ
ajst-7782	23	20	source	source	NOUN
ajst-7782	23	21	for	for	ADP
ajst-7782	23	22	the	the	DET
ajst-7782	23	23	uv	uv	NOUN
ajst-7782	23	24	visible	visible	ADJ
ajst-7782	23	25	absorption	absorption	NOUN
ajst-7782	23	26	spectrum	spectrum	NOUN
ajst-7782	23	27	.	.	PUNCT
ajst-7782	24	1	the	the	DET
ajst-7782	24	2	light	light	NOUN
ajst-7782	24	3	emitted	emit	VERB
ajst-7782	24	4	by	by	ADP
ajst-7782	24	5	the	the	DET
ajst-7782	24	6	light	light	ADJ
ajst-7782	24	7	source	source	NOUN
ajst-7782	24	8	is	be	AUX
ajst-7782	24	9	coupled	couple	VERB
ajst-7782	24	10	through	through	ADP
ajst-7782	24	11	optical	optical	ADJ
ajst-7782	24	12	fibers	fiber	NOUN
ajst-7782	24	13	,	,	PUNCT
ajst-7782	24	14	and	and	CCONJ
ajst-7782	24	15	then	then	ADV
ajst-7782	24	16	emitted	emit	VERB
ajst-7782	24	17	to	to	ADP
ajst-7782	24	18	the	the	DET
ajst-7782	24	19	sample	sample	NOUN
ajst-7782	24	20	pool	pool	NOUN
ajst-7782	24	21	through	through	ADP
ajst-7782	24	22	an	an	DET
ajst-7782	24	23	optical	optical	ADJ
ajst-7782	24	24	fiber	fiber	NOUN
ajst-7782	24	25	collimator	collimator	NOUN
ajst-7782	24	26	(	(	PUNCT
ajst-7782	24	27	wenyi	wenyi	NOUN
ajst-7782	24	28	optoelectronics	optoelectronic	NOUN
ajst-7782	24	29	,	,	PUNCT
ajst-7782	24	30	74uv	74uv	NOUN
ajst-7782	24	31	)	)	PUNCT
ajst-7782	24	32	.	.	PUNCT
ajst-7782	25	1	the	the	DET
ajst-7782	25	2	generated	generate	VERB
ajst-7782	25	3	output	output	NOUN
ajst-7782	25	4	light	light	NOUN
ajst-7782	25	5	is	be	AUX
ajst-7782	25	6	collected	collect	VERB
ajst-7782	25	7	through	through	ADP
ajst-7782	25	8	the	the	DET
ajst-7782	25	9	collimator	collimator	NOUN
ajst-7782	25	10	,	,	PUNCT
ajst-7782	25	11	and	and	CCONJ
ajst-7782	25	12	received	receive	VERB
ajst-7782	25	13	by	by	ADP
ajst-7782	25	14	a	a	DET
ajst-7782	25	15	spectrometer	spectrometer	NOUN
ajst-7782	25	16	(	(	PUNCT
ajst-7782	25	17	shared	share	VERB
ajst-7782	25	18	optics	optic	NOUN
ajst-7782	25	19	,	,	PUNCT
ajst-7782	25	20	pg2000	pg2000	NOUN
ajst-7782	25	21	pro	pro	X
ajst-7782	25	22	)	)	PUNCT
ajst-7782	25	23	through	through	ADP
ajst-7782	25	24	optical	optical	ADJ
ajst-7782	25	25	fibers	fiber	NOUN
ajst-7782	25	26	.	.	PUNCT
ajst-7782	26	1	finally	finally	ADV
ajst-7782	26	2	,	,	PUNCT
ajst-7782	26	3	the	the	DET
ajst-7782	26	4	collected	collect	VERB
ajst-7782	26	5	data	datum	NOUN
ajst-7782	26	6	is	be	AUX
ajst-7782	26	7	stored	store	VERB
ajst-7782	26	8	,	,	PUNCT
ajst-7782	26	9	processed	process	VERB
ajst-7782	26	10	,	,	PUNCT
ajst-7782	26	11	and	and	CCONJ
ajst-7782	26	12	modeled	model	VERB
ajst-7782	26	13	on	on	ADP
ajst-7782	26	14	the	the	DET
ajst-7782	26	15	computer	computer	NOUN
ajst-7782	26	16	side	side	NOUN
ajst-7782	26	17	.	.	PUNCT
ajst-7782	27	1	2.2	2.2	NUM
ajst-7782	27	2	.	.	PUNCT
ajst-7782	28	1	sample	sample	NOUN
ajst-7782	28	2	preparation	preparation	NOUN
ajst-7782	28	3	this	this	DET
ajst-7782	28	4	article	article	NOUN
ajst-7782	28	5	uses	use	VERB
ajst-7782	28	6	the	the	DET
ajst-7782	28	7	standard	standard	ADJ
ajst-7782	28	8	substance	substance	NOUN
ajst-7782	28	9	for	for	ADP
ajst-7782	28	10	nitrite	nitrite	NOUN
ajst-7782	28	11	nitrogen	nitrogen	NOUN
ajst-7782	28	12	solution	solution	NOUN
ajst-7782	28	13	(	(	PUNCT
ajst-7782	28	14	1000	1000	NUM
ajst-7782	28	15	mg·l-1	mg·l-1	PROPN
ajst-7782	28	16	,	,	PUNCT
ajst-7782	28	17	northern	northern	ADJ
ajst-7782	28	18	weiye	weiye	NOUN
ajst-7782	28	19	)	)	PUNCT
ajst-7782	28	20	as	as	ADP
ajst-7782	28	21	an	an	DET
ajst-7782	28	22	experimental	experimental	ADJ
ajst-7782	28	23	sample	sample	NOUN
ajst-7782	28	24	,	,	PUNCT
ajst-7782	28	25	and	and	CCONJ
ajst-7782	28	26	prepares	prepare	VERB
ajst-7782	28	27	a	a	DET
ajst-7782	28	28	series	series	NOUN
ajst-7782	28	29	of	of	ADP
ajst-7782	28	30	concentration	concentration	NOUN
ajst-7782	28	31	gradient	gradient	NOUN
ajst-7782	28	32	solutions	solution	NOUN
ajst-7782	28	33	through	through	ADP
ajst-7782	28	34	gradual	gradual	ADJ
ajst-7782	28	35	dilution	dilution	NOUN
ajst-7782	28	36	.	.	PUNCT
ajst-7782	29	1	the	the	DET
ajst-7782	29	2	concentration	concentration	NOUN
ajst-7782	29	3	range	range	NOUN
ajst-7782	29	4	is	be	AUX
ajst-7782	29	5	0.1~17	0.1~17	PROPN
ajst-7782	29	6	mg·l-1	mg·l-1	PROPN
ajst-7782	29	7	,	,	PUNCT
ajst-7782	29	8	and	and	CCONJ
ajst-7782	29	9	in	in	ADP
ajst-7782	29	10	the	the	DET
ajst-7782	29	11	range	range	NOUN
ajst-7782	29	12	of	of	ADP
ajst-7782	29	13	0.1~2	0.1~2	NOUN
ajst-7782	29	14	mg·l-1	mg·l-1	PROPN
ajst-7782	29	15	,	,	PUNCT
ajst-7782	29	16	the	the	DET
ajst-7782	29	17	concentration	concentration	NOUN
ajst-7782	29	18	gradient	gradient	NOUN
ajst-7782	29	19	is	be	AUX
ajst-7782	29	20	0.1	0.1	NUM
ajst-7782	29	21	mg·l-1	mg·l-1	PROPN
ajst-7782	29	22	;	;	PUNCT
ajst-7782	29	23	in	in	ADP
ajst-7782	29	24	the	the	DET
ajst-7782	29	25	range	range	NOUN
ajst-7782	29	26	of	of	ADP
ajst-7782	29	27	2	2	NUM
ajst-7782	29	28	-	-	SYM
ajst-7782	29	29	5	5	NUM
ajst-7782	29	30	mg·l1	mg·l1	ADJ
ajst-7782	29	31	,	,	PUNCT
ajst-7782	29	32	the	the	DET
ajst-7782	29	33	concentration	concentration	NOUN
ajst-7782	29	34	gradient	gradient	NOUN
ajst-7782	29	35	is	be	AUX
ajst-7782	29	36	0.25	0.25	NUM
ajst-7782	29	37	mg·l-1	mg·l-1	NOUN
ajst-7782	29	38	;	;	PUNCT
ajst-7782	29	39	in	in	ADP
ajst-7782	29	40	the	the	DET
ajst-7782	29	41	range	range	NOUN
ajst-7782	29	42	of	of	ADP
ajst-7782	29	43	5	5	NUM
ajst-7782	29	44	to	to	PART
ajst-7782	29	45	17	17	NUM
ajst-7782	29	46	mg·l-1	mg·l-1	PROPN
ajst-7782	29	47	,	,	PUNCT
ajst-7782	29	48	the	the	DET
ajst-7782	29	49	concentration	concentration	NOUN
ajst-7782	29	50	gradient	gradient	NOUN
ajst-7782	29	51	is	be	AUX
ajst-7782	29	52	1	1	NUM
ajst-7782	29	53	mg·l-1	mg·l-1	PROPN
ajst-7782	29	54	.	.	PUNCT
ajst-7782	30	1	using	use	VERB
ajst-7782	30	2	the	the	DET
ajst-7782	30	3	experimental	experimental	ADJ
ajst-7782	30	4	device	device	NOUN
ajst-7782	30	5	built	build	VERB
ajst-7782	30	6	in	in	ADP
ajst-7782	30	7	the	the	DET
ajst-7782	30	8	laboratory	laboratory	NOUN
ajst-7782	30	9	,	,	PUNCT
ajst-7782	30	10	set	set	VERB
ajst-7782	30	11	the	the	DET
ajst-7782	30	12	spectrometer	spectrometer	NOUN
ajst-7782	30	13	integration	integration	NOUN
ajst-7782	30	14	time	time	NOUN
ajst-7782	30	15	to	to	ADP
ajst-7782	30	16	45	45	NUM
ajst-7782	30	17	ms	ms	PROPN
ajst-7782	30	18	,	,	PUNCT
ajst-7782	30	19	the	the	DET
ajst-7782	30	20	average	average	ADJ
ajst-7782	30	21	number	number	NOUN
ajst-7782	30	22	of	of	ADP
ajst-7782	30	23	times	time	NOUN
ajst-7782	30	24	is	be	AUX
ajst-7782	30	25	11	11	NUM
ajst-7782	30	26	,	,	PUNCT
ajst-7782	30	27	and	and	CCONJ
ajst-7782	30	28	the	the	DET
ajst-7782	30	29	smoothness	smoothness	NOUN
ajst-7782	30	30	is	be	AUX
ajst-7782	30	31	4	4	NUM
ajst-7782	30	32	.	.	PUNCT
ajst-7782	30	33	complete	complete	VERB
ajst-7782	30	34	the	the	DET
ajst-7782	30	35	collection	collection	NOUN
ajst-7782	30	36	of	of	ADP
ajst-7782	30	37	the	the	DET
ajst-7782	30	38	absorption	absorption	NOUN
ajst-7782	30	39	spectrum	spectrum	NOUN
ajst-7782	30	40	of	of	ADP
ajst-7782	30	41	nitrite	nitrite	NOUN
ajst-7782	30	42	nitrogen	nitrogen	NOUN
ajst-7782	30	43	solution	solution	NOUN
ajst-7782	30	44	,	,	PUNCT
ajst-7782	30	45	and	and	CCONJ
ajst-7782	30	46	the	the	DET
ajst-7782	30	47	obtained	obtain	VERB
ajst-7782	30	48	absorption	absorption	NOUN
ajst-7782	30	49	spectrum	spectrum	NOUN
ajst-7782	30	50	of	of	ADP
ajst-7782	30	51	nitrite	nitrite	NOUN
ajst-7782	30	52	nitrogen	nitrogen	NOUN
ajst-7782	30	53	solution	solution	NOUN
ajst-7782	30	54	is	be	AUX
ajst-7782	30	55	shown	show	VERB
ajst-7782	30	56	in	in	ADP
ajst-7782	30	57	figure	figure	NOUN
ajst-7782	30	58	2	2	NUM
ajst-7782	30	59	.	.	X
ajst-7782	30	60	86	86	NUM
ajst-7782	30	61	figure	figure	NOUN
ajst-7782	30	62	1	1	NUM
ajst-7782	30	63	.	.	PUNCT
ajst-7782	30	64	experimental	experimental	ADJ
ajst-7782	30	65	device	device	NOUN
ajst-7782	30	66	diagram	diagram	NOUN
ajst-7782	30	67	figure	figure	NOUN
ajst-7782	30	68	2	2	NUM
ajst-7782	30	69	.	.	PUNCT
ajst-7782	30	70	ultraviolet	ultraviolet	ADJ
ajst-7782	30	71	absorption	absorption	NOUN
ajst-7782	30	72	spectrogram	spectrogram	NOUN
ajst-7782	30	73	of	of	ADP
ajst-7782	30	74	nitrite	nitrite	NOUN
ajst-7782	30	75	nitrogen	nitrogen	NOUN
ajst-7782	30	76	standard	standard	ADJ
ajst-7782	30	77	solution	solution	NOUN
ajst-7782	30	78	as	as	SCONJ
ajst-7782	30	79	can	can	AUX
ajst-7782	30	80	be	be	AUX
ajst-7782	30	81	seen	see	VERB
ajst-7782	30	82	from	from	ADP
ajst-7782	30	83	figure	figure	NOUN
ajst-7782	30	84	2	2	NUM
ajst-7782	30	85	,	,	PUNCT
ajst-7782	30	86	the	the	DET
ajst-7782	30	87	absorption	absorption	NOUN
ajst-7782	30	88	signal	signal	NOUN
ajst-7782	30	89	of	of	ADP
ajst-7782	30	90	nitrite	nitrite	NOUN
ajst-7782	30	91	nitrogen	nitrogen	NOUN
ajst-7782	30	92	solution	solution	NOUN
ajst-7782	30	93	is	be	AUX
ajst-7782	30	94	mainly	mainly	ADV
ajst-7782	30	95	concentrated	concentrate	VERB
ajst-7782	30	96	in	in	ADP
ajst-7782	30	97	the	the	DET
ajst-7782	30	98	range	range	NOUN
ajst-7782	30	99	of	of	ADP
ajst-7782	30	100	190	190	NUM
ajst-7782	30	101	to	to	PART
ajst-7782	30	102	250	250	NUM
ajst-7782	30	103	nm	nm	NOUN
ajst-7782	30	104	.	.	PUNCT
ajst-7782	31	1	as	as	ADP
ajst-7782	31	2	the	the	DET
ajst-7782	31	3	concentration	concentration	NOUN
ajst-7782	31	4	increases	increase	NOUN
ajst-7782	31	5	,	,	PUNCT
ajst-7782	31	6	its	its	PRON
ajst-7782	31	7	absorbance	absorbance	NOUN
ajst-7782	31	8	increases	increase	NOUN
ajst-7782	31	9	,	,	PUNCT
ajst-7782	31	10	and	and	CCONJ
ajst-7782	31	11	the	the	DET
ajst-7782	31	12	absorption	absorption	NOUN
ajst-7782	31	13	peak	peak	NOUN
ajst-7782	31	14	position	position	NOUN
ajst-7782	31	15	exhibits	exhibit	VERB
ajst-7782	31	16	a	a	DET
ajst-7782	31	17	red	red	ADJ
ajst-7782	31	18	shift	shift	NOUN
ajst-7782	31	19	phenomenon	phenomenon	NOUN
ajst-7782	31	20	.	.	PUNCT
ajst-7782	32	1	after	after	ADP
ajst-7782	32	2	8	8	NUM
ajst-7782	32	3	mg·l-1	mg·l-1	PROPN
ajst-7782	32	4	,	,	PUNCT
ajst-7782	32	5	as	as	ADP
ajst-7782	32	6	the	the	DET
ajst-7782	32	7	concentration	concentration	NOUN
ajst-7782	32	8	increases	increase	NOUN
ajst-7782	32	9	,	,	PUNCT
ajst-7782	32	10	the	the	DET
ajst-7782	32	11	absorbance	absorbance	NOUN
ajst-7782	32	12	increases	increase	VERB
ajst-7782	32	13	slowly	slowly	ADV
ajst-7782	32	14	and	and	CCONJ
ajst-7782	32	15	a	a	DET
ajst-7782	32	16	saturation	saturation	NOUN
ajst-7782	32	17	state	state	NOUN
ajst-7782	32	18	begins	begin	VERB
ajst-7782	32	19	to	to	PART
ajst-7782	32	20	appear	appear	VERB
ajst-7782	32	21	.	.	PUNCT
ajst-7782	33	1	3	3	X
ajst-7782	33	2	.	.	X
ajst-7782	33	3	data	datum	NOUN
ajst-7782	33	4	processing	process	VERB
ajst-7782	33	5	the	the	DET
ajst-7782	33	6	spectral	spectral	ADJ
ajst-7782	33	7	data	data	NOUN
ajst-7782	33	8	processing	processing	NOUN
ajst-7782	33	9	process	process	NOUN
ajst-7782	33	10	is	be	AUX
ajst-7782	33	11	shown	show	VERB
ajst-7782	33	12	in	in	ADP
ajst-7782	33	13	figure	figure	NOUN
ajst-7782	33	14	3	3	NUM
ajst-7782	33	15	.	.	PUNCT
ajst-7782	34	1	firstly	firstly	ADV
ajst-7782	34	2	,	,	PUNCT
ajst-7782	34	3	the	the	DET
ajst-7782	34	4	collected	collect	VERB
ajst-7782	34	5	spectral	spectral	ADJ
ajst-7782	34	6	data	datum	NOUN
ajst-7782	34	7	is	be	AUX
ajst-7782	34	8	subjected	subject	VERB
ajst-7782	34	9	to	to	ADP
ajst-7782	34	10	sg	sg	ADP
ajst-7782	34	11	filtering	filter	VERB
ajst-7782	34	12	processing	processing	NOUN
ajst-7782	34	13	to	to	PART
ajst-7782	34	14	remove	remove	VERB
ajst-7782	34	15	various	various	ADJ
ajst-7782	34	16	noises	noise	NOUN
ajst-7782	34	17	associated	associate	VERB
ajst-7782	34	18	with	with	ADP
ajst-7782	34	19	the	the	DET
ajst-7782	34	20	original	original	ADJ
ajst-7782	34	21	spectrum	spectrum	NOUN
ajst-7782	34	22	.	.	PUNCT
ajst-7782	35	1	then	then	ADV
ajst-7782	35	2	,	,	PUNCT
ajst-7782	35	3	spa	spa	NOUN
ajst-7782	35	4	is	be	AUX
ajst-7782	35	5	used	use	VERB
ajst-7782	35	6	to	to	PART
ajst-7782	35	7	extract	extract	VERB
ajst-7782	35	8	the	the	DET
ajst-7782	35	9	characteristic	characteristic	ADJ
ajst-7782	35	10	wavelengths	wavelength	NOUN
ajst-7782	35	11	to	to	PART
ajst-7782	35	12	obtain	obtain	VERB
ajst-7782	35	13	three	three	NUM
ajst-7782	35	14	characteristic	characteristic	ADJ
ajst-7782	35	15	wavelengths	wavelength	NOUN
ajst-7782	35	16	,	,	PUNCT
ajst-7782	35	17	while	while	SCONJ
ajst-7782	35	18	effectively	effectively	ADV
ajst-7782	35	19	eliminating	eliminate	VERB
ajst-7782	35	20	redundant	redundant	ADJ
ajst-7782	35	21	data	datum	NOUN
ajst-7782	35	22	information	information	NOUN
ajst-7782	35	23	.	.	PUNCT
ajst-7782	36	1	then	then	ADV
ajst-7782	36	2	,	,	PUNCT
ajst-7782	36	3	based	base	VERB
ajst-7782	36	4	on	on	ADP
ajst-7782	36	5	the	the	DET
ajst-7782	36	6	cross	cross	NOUN
ajst-7782	36	7	validation	validation	NOUN
ajst-7782	36	8	of	of	ADP
ajst-7782	36	9	the	the	DET
ajst-7782	36	10	retention	retention	NOUN
ajst-7782	36	11	method	method	NOUN
ajst-7782	36	12	,	,	PUNCT
ajst-7782	36	13	a	a	DET
ajst-7782	36	14	regression	regression	NOUN
ajst-7782	36	15	model	model	NOUN
ajst-7782	36	16	for	for	ADP
ajst-7782	36	17	nitrite	nitrite	NOUN
ajst-7782	36	18	nitrogen	nitrogen	NOUN
ajst-7782	36	19	was	be	AUX
ajst-7782	36	20	established	establish	VERB
ajst-7782	36	21	using	use	VERB
ajst-7782	36	22	svr	svr	PROPN
ajst-7782	36	23	.	.	PUNCT
ajst-7782	37	1	finally	finally	ADV
ajst-7782	37	2	,	,	PUNCT
ajst-7782	37	3	the	the	DET
ajst-7782	37	4	regression	regression	NOUN
ajst-7782	37	5	model	model	NOUN
ajst-7782	37	6	was	be	AUX
ajst-7782	37	7	evaluated	evaluate	VERB
ajst-7782	37	8	through	through	ADP
ajst-7782	37	9	the	the	DET
ajst-7782	37	10	determination	determination	NOUN
ajst-7782	37	11	coefficient	coefficient	NOUN
ajst-7782	37	12	r2	r2	PROPN
ajst-7782	37	13	and	and	CCONJ
ajst-7782	37	14	root	root	NOUN
ajst-7782	37	15	mean	mean	ADJ
ajst-7782	37	16	square	square	ADJ
ajst-7782	37	17	error	error	NOUN
ajst-7782	37	18	rmse	rmse	NOUN
ajst-7782	37	19	.	.	PUNCT
ajst-7782	38	1	figure	figure	VERB
ajst-7782	38	2	3	3	NUM
ajst-7782	38	3	.	.	PUNCT
ajst-7782	38	4	data	datum	NOUN
ajst-7782	38	5	processing	processing	NOUN
ajst-7782	38	6	flow	flow	NOUN
ajst-7782	38	7	chart	chart	NOUN
ajst-7782	38	8	180	180	NUM
ajst-7782	38	9	190	190	NUM
ajst-7782	38	10	200	200	NUM
ajst-7782	38	11	210	210	NUM
ajst-7782	38	12	220	220	NUM
ajst-7782	38	13	230	230	NUM
ajst-7782	38	14	240	240	NUM
ajst-7782	38	15	250	250	NUM
ajst-7782	38	16	0.0	0.0	NUM
ajst-7782	38	17	0.2	0.2	NUM
ajst-7782	38	18	0.4	0.4	NUM
ajst-7782	38	19	0.6	0.6	NUM
ajst-7782	38	20	0.8	0.8	NUM
ajst-7782	38	21	1.0	1.0	NUM
ajst-7782	38	22	1.2	1.2	NUM
ajst-7782	38	23	1.4	1.4	NUM
ajst-7782	38	24	1.6	1.6	NUM
ajst-7782	38	25	1.8	1.8	NUM
ajst-7782	38	26	a	a	DET
ajst-7782	38	27	bs	bs	NOUN
ajst-7782	38	28	or	or	CCONJ
ajst-7782	38	29	ba	ba	PROPN
ajst-7782	38	30	nc	nc	PROPN
ajst-7782	39	1	e/	e/	PROPN
ajst-7782	39	2	(	(	PUNCT
ajst-7782	39	3	a	a	DET
ajst-7782	39	4	.u	.u	NOUN
ajst-7782	39	5	.	.	PUNCT
ajst-7782	39	6	)	)	PUNCT
ajst-7782	40	1	wavelength	wavelength	NOUN
ajst-7782	40	2	/	/	SYM
ajst-7782	40	3	nm	nm	ADJ
ajst-7782	40	4	87	87	NUM
ajst-7782	40	5	3.1	3.1	NUM
ajst-7782	40	6	.	.	PUNCT
ajst-7782	41	1	sg	sg	ADP
ajst-7782	41	2	filtering	filter	VERB
ajst-7782	41	3	the	the	DET
ajst-7782	41	4	collected	collect	VERB
ajst-7782	41	5	spectral	spectral	ADJ
ajst-7782	41	6	data	datum	NOUN
ajst-7782	41	7	is	be	AUX
ajst-7782	41	8	usually	usually	ADV
ajst-7782	41	9	accompanied	accompany	VERB
ajst-7782	41	10	by	by	ADP
ajst-7782	41	11	highfrequency	highfrequency	NOUN
ajst-7782	41	12	noise	noise	NOUN
ajst-7782	41	13	and	and	CCONJ
ajst-7782	41	14	random	random	ADJ
ajst-7782	41	15	noise	noise	NOUN
ajst-7782	41	16	,	,	PUNCT
ajst-7782	41	17	so	so	SCONJ
ajst-7782	41	18	it	it	PRON
ajst-7782	41	19	is	be	AUX
ajst-7782	41	20	necessary	necessary	ADJ
ajst-7782	41	21	to	to	PART
ajst-7782	41	22	conduct	conduct	VERB
ajst-7782	41	23	noise	noise	NOUN
ajst-7782	41	24	reduction	reduction	NOUN
ajst-7782	41	25	processing	processing	NOUN
ajst-7782	41	26	.	.	PUNCT
ajst-7782	42	1	there	there	PRON
ajst-7782	42	2	are	be	VERB
ajst-7782	42	3	many	many	ADJ
ajst-7782	42	4	processing	processing	NOUN
ajst-7782	42	5	methods	method	NOUN
ajst-7782	42	6	for	for	ADP
ajst-7782	42	7	noise	noise	NOUN
ajst-7782	42	8	reduction	reduction	NOUN
ajst-7782	42	9	of	of	ADP
ajst-7782	42	10	spectral	spectral	ADJ
ajst-7782	42	11	data	datum	NOUN
ajst-7782	42	12	,	,	PUNCT
ajst-7782	42	13	among	among	ADP
ajst-7782	42	14	which	which	PRON
ajst-7782	42	15	the	the	DET
ajst-7782	42	16	most	most	ADV
ajst-7782	42	17	common	common	ADJ
ajst-7782	42	18	and	and	CCONJ
ajst-7782	42	19	effective	effective	ADJ
ajst-7782	42	20	method	method	NOUN
ajst-7782	42	21	is	be	AUX
ajst-7782	42	22	smooth	smooth	ADJ
ajst-7782	42	23	filtering	filter	VERB
ajst-7782	42	24	(	(	PUNCT
ajst-7782	42	25	savitzky	savitzky	NOUN
ajst-7782	42	26	golay	golay	NOUN
ajst-7782	42	27	,	,	PUNCT
ajst-7782	42	28	sg	sg	PROPN
ajst-7782	42	29	)	)	PUNCT
ajst-7782	42	30	.	.	PUNCT
ajst-7782	43	1	the	the	DET
ajst-7782	43	2	biggest	big	ADJ
ajst-7782	43	3	advantage	advantage	NOUN
ajst-7782	43	4	of	of	ADP
ajst-7782	43	5	this	this	DET
ajst-7782	43	6	method	method	NOUN
ajst-7782	43	7	is	be	AUX
ajst-7782	43	8	that	that	SCONJ
ajst-7782	43	9	it	it	PRON
ajst-7782	43	10	can	can	AUX
ajst-7782	43	11	maintain	maintain	VERB
ajst-7782	43	12	the	the	DET
ajst-7782	43	13	trend	trend	NOUN
ajst-7782	43	14	and	and	CCONJ
ajst-7782	43	15	characteristics	characteristic	NOUN
ajst-7782	43	16	of	of	ADP
ajst-7782	43	17	the	the	DET
ajst-7782	43	18	original	original	ADJ
ajst-7782	43	19	spectrum	spectrum	NOUN
ajst-7782	43	20	while	while	SCONJ
ajst-7782	43	21	eliminating	eliminate	VERB
ajst-7782	43	22	noise	noise	NOUN
ajst-7782	43	23	,	,	PUNCT
ajst-7782	43	24	and	and	CCONJ
ajst-7782	43	25	can	can	AUX
ajst-7782	43	26	achieve	achieve	VERB
ajst-7782	43	27	good	good	ADJ
ajst-7782	43	28	results	result	NOUN
ajst-7782	43	29	even	even	ADV
ajst-7782	43	30	in	in	ADP
ajst-7782	43	31	the	the	DET
ajst-7782	43	32	case	case	NOUN
ajst-7782	43	33	of	of	ADP
ajst-7782	43	34	large	large	ADJ
ajst-7782	43	35	noise	noise	NOUN
ajst-7782	43	36	.	.	PUNCT
ajst-7782	44	1	when	when	SCONJ
ajst-7782	44	2	using	use	VERB
ajst-7782	44	3	sg	sg	ADP
ajst-7782	44	4	filtering	filter	VERB
ajst-7782	44	5	,	,	PUNCT
ajst-7782	44	6	it	it	PRON
ajst-7782	44	7	is	be	AUX
ajst-7782	44	8	necessary	necessary	ADJ
ajst-7782	44	9	to	to	PART
ajst-7782	44	10	select	select	VERB
ajst-7782	44	11	the	the	DET
ajst-7782	44	12	appropriate	appropriate	ADJ
ajst-7782	44	13	window	window	NOUN
ajst-7782	44	14	size	size	NOUN
ajst-7782	44	15	and	and	CCONJ
ajst-7782	44	16	polynomial	polynomial	ADJ
ajst-7782	44	17	order	order	NOUN
ajst-7782	44	18	.	.	PUNCT
ajst-7782	45	1	larger	large	ADJ
ajst-7782	45	2	windows	window	NOUN
ajst-7782	45	3	can	can	AUX
ajst-7782	45	4	better	well	ADV
ajst-7782	45	5	smooth	smooth	VERB
ajst-7782	45	6	the	the	DET
ajst-7782	45	7	signal	signal	NOUN
ajst-7782	45	8	,	,	PUNCT
ajst-7782	45	9	but	but	CCONJ
ajst-7782	45	10	may	may	AUX
ajst-7782	45	11	lose	lose	VERB
ajst-7782	45	12	details	detail	NOUN
ajst-7782	45	13	,	,	PUNCT
ajst-7782	45	14	especially	especially	ADV
ajst-7782	45	15	for	for	ADP
ajst-7782	45	16	rapidly	rapidly	ADV
ajst-7782	45	17	changing	change	VERB
ajst-7782	45	18	signals	signal	NOUN
ajst-7782	45	19	,	,	PUNCT
ajst-7782	45	20	while	while	SCONJ
ajst-7782	45	21	smaller	small	ADJ
ajst-7782	45	22	windows	window	NOUN
ajst-7782	45	23	can	can	AUX
ajst-7782	45	24	better	well	ADV
ajst-7782	45	25	preserve	preserve	VERB
ajst-7782	45	26	the	the	DET
ajst-7782	45	27	details	detail	NOUN
ajst-7782	45	28	of	of	ADP
ajst-7782	45	29	the	the	DET
ajst-7782	45	30	signal	signal	NOUN
ajst-7782	45	31	,	,	PUNCT
ajst-7782	45	32	but	but	CCONJ
ajst-7782	45	33	may	may	AUX
ajst-7782	45	34	generate	generate	VERB
ajst-7782	45	35	noise	noise	NOUN
ajst-7782	45	36	or	or	CCONJ
ajst-7782	45	37	spurious	spurious	ADJ
ajst-7782	45	38	peaks	peak	NOUN
ajst-7782	45	39	.	.	PUNCT
ajst-7782	46	1	typically	typically	ADV
ajst-7782	46	2	,	,	PUNCT
ajst-7782	46	3	the	the	DET
ajst-7782	46	4	selection	selection	NOUN
ajst-7782	46	5	window	window	NOUN
ajst-7782	46	6	size	size	NOUN
ajst-7782	46	7	depends	depend	VERB
ajst-7782	46	8	on	on	ADP
ajst-7782	46	9	the	the	DET
ajst-7782	46	10	number	number	NOUN
ajst-7782	46	11	and	and	CCONJ
ajst-7782	46	12	width	width	NOUN
ajst-7782	46	13	of	of	ADP
ajst-7782	46	14	peaks	peak	NOUN
ajst-7782	46	15	in	in	ADP
ajst-7782	46	16	the	the	DET
ajst-7782	46	17	data	datum	NOUN
ajst-7782	46	18	,	,	PUNCT
ajst-7782	46	19	as	as	ADV
ajst-7782	46	20	well	well	ADV
ajst-7782	46	21	as	as	ADP
ajst-7782	46	22	the	the	DET
ajst-7782	46	23	level	level	NOUN
ajst-7782	46	24	of	of	ADP
ajst-7782	46	25	smoothing	smoothing	NOUN
ajst-7782	46	26	required	require	VERB
ajst-7782	46	27	.	.	PUNCT
ajst-7782	47	1	from	from	ADP
ajst-7782	47	2	figure	figure	NOUN
ajst-7782	47	3	2	2	NUM
ajst-7782	47	4	,	,	PUNCT
ajst-7782	47	5	it	it	PRON
ajst-7782	47	6	can	can	AUX
ajst-7782	47	7	be	be	AUX
ajst-7782	47	8	seen	see	VERB
ajst-7782	47	9	that	that	SCONJ
ajst-7782	47	10	the	the	DET
ajst-7782	47	11	original	original	ADJ
ajst-7782	47	12	spectrum	spectrum	NOUN
ajst-7782	47	13	of	of	ADP
ajst-7782	47	14	nitrite	nitrite	NOUN
ajst-7782	47	15	nitrogen	nitrogen	NOUN
ajst-7782	47	16	solution	solution	NOUN
ajst-7782	47	17	has	have	VERB
ajst-7782	47	18	fewer	few	ADJ
ajst-7782	47	19	burrs	burr	NOUN
ajst-7782	47	20	.	.	PUNCT
ajst-7782	48	1	therefore	therefore	ADV
ajst-7782	48	2	,	,	PUNCT
ajst-7782	48	3	the	the	DET
ajst-7782	48	4	window	window	NOUN
ajst-7782	48	5	size	size	NOUN
ajst-7782	48	6	set	set	VERB
ajst-7782	48	7	for	for	ADP
ajst-7782	48	8	this	this	DET
ajst-7782	48	9	experiment	experiment	NOUN
ajst-7782	48	10	is	be	AUX
ajst-7782	48	11	5	5	NUM
ajst-7782	48	12	,	,	PUNCT
ajst-7782	48	13	and	and	CCONJ
ajst-7782	48	14	the	the	DET
ajst-7782	48	15	order	order	NOUN
ajst-7782	48	16	of	of	ADP
ajst-7782	48	17	the	the	DET
ajst-7782	48	18	polynomial	polynomial	NOUN
ajst-7782	48	19	is	be	AUX
ajst-7782	48	20	3	3	NUM
ajst-7782	48	21	.	.	PUNCT
ajst-7782	49	1	the	the	DET
ajst-7782	49	2	filtered	filter	VERB
ajst-7782	49	3	absorption	absorption	NOUN
ajst-7782	49	4	spectrum	spectrum	NOUN
ajst-7782	49	5	is	be	AUX
ajst-7782	49	6	obtained	obtain	VERB
ajst-7782	49	7	as	as	SCONJ
ajst-7782	49	8	shown	show	VERB
ajst-7782	49	9	in	in	ADP
ajst-7782	49	10	figure	figure	NOUN
ajst-7782	49	11	4	4	NUM
ajst-7782	49	12	.	.	PUNCT
ajst-7782	50	1	as	as	SCONJ
ajst-7782	50	2	can	can	AUX
ajst-7782	50	3	be	be	AUX
ajst-7782	50	4	seen	see	VERB
ajst-7782	50	5	from	from	ADP
ajst-7782	50	6	figure	figure	NOUN
ajst-7782	50	7	4	4	NUM
ajst-7782	50	8	,	,	PUNCT
ajst-7782	50	9	after	after	ADP
ajst-7782	50	10	sg	sg	ADP
ajst-7782	50	11	smoothing	smooth	VERB
ajst-7782	50	12	filtering	filtering	NOUN
ajst-7782	50	13	,	,	PUNCT
ajst-7782	50	14	the	the	DET
ajst-7782	50	15	noise	noise	NOUN
ajst-7782	50	16	in	in	ADP
ajst-7782	50	17	the	the	DET
ajst-7782	50	18	original	original	ADJ
ajst-7782	50	19	spectrum	spectrum	NOUN
ajst-7782	50	20	has	have	AUX
ajst-7782	50	21	been	be	AUX
ajst-7782	50	22	effectively	effectively	ADV
ajst-7782	50	23	suppressed	suppress	VERB
ajst-7782	50	24	,	,	PUNCT
ajst-7782	50	25	indicating	indicate	VERB
ajst-7782	50	26	that	that	SCONJ
ajst-7782	50	27	using	use	VERB
ajst-7782	50	28	sg	sg	NOUN
ajst-7782	50	29	filtering	filter	VERB
ajst-7782	50	30	as	as	ADP
ajst-7782	50	31	a	a	DET
ajst-7782	50	32	preprocessing	preprocessing	NOUN
ajst-7782	50	33	method	method	NOUN
ajst-7782	50	34	is	be	AUX
ajst-7782	50	35	effective	effective	ADJ
ajst-7782	50	36	.	.	PUNCT
ajst-7782	51	1	figure	figure	NOUN
ajst-7782	51	2	4	4	NUM
ajst-7782	51	3	.	.	PUNCT
ajst-7782	52	1	absorption	absorption	NOUN
ajst-7782	52	2	spectrum	spectrum	NOUN
ajst-7782	52	3	after	after	ADP
ajst-7782	52	4	sg	sg	ADP
ajst-7782	52	5	filtering	filter	VERB
ajst-7782	52	6	3.2	3.2	NUM
ajst-7782	52	7	.	.	PUNCT
ajst-7782	53	1	selection	selection	NOUN
ajst-7782	53	2	of	of	ADP
ajst-7782	53	3	characteristic	characteristic	ADJ
ajst-7782	53	4	wavelength	wavelength	NOUN
ajst-7782	53	5	the	the	DET
ajst-7782	53	6	collected	collect	VERB
ajst-7782	53	7	spectral	spectral	ADJ
ajst-7782	53	8	data	datum	NOUN
ajst-7782	53	9	are	be	AUX
ajst-7782	53	10	all	all	ADV
ajst-7782	53	11	high	high	ADJ
ajst-7782	53	12	-	-	PUNCT
ajst-7782	53	13	dimensional	dimensional	ADJ
ajst-7782	53	14	data	datum	NOUN
ajst-7782	53	15	,	,	PUNCT
ajst-7782	53	16	including	include	VERB
ajst-7782	53	17	both	both	CCONJ
ajst-7782	53	18	useful	useful	ADJ
ajst-7782	53	19	spectral	spectral	ADJ
ajst-7782	53	20	information	information	NOUN
ajst-7782	53	21	and	and	CCONJ
ajst-7782	53	22	redundant	redundant	ADJ
ajst-7782	53	23	and	and	CCONJ
ajst-7782	53	24	useless	useless	ADJ
ajst-7782	53	25	information	information	NOUN
ajst-7782	53	26	.	.	PUNCT
ajst-7782	54	1	if	if	SCONJ
ajst-7782	54	2	not	not	PART
ajst-7782	54	3	processed	process	VERB
ajst-7782	54	4	,	,	PUNCT
ajst-7782	54	5	it	it	PRON
ajst-7782	54	6	will	will	AUX
ajst-7782	54	7	affect	affect	VERB
ajst-7782	54	8	the	the	DET
ajst-7782	54	9	subsequent	subsequent	ADJ
ajst-7782	54	10	modeling	modeling	NOUN
ajst-7782	54	11	effect	effect	NOUN
ajst-7782	54	12	,	,	PUNCT
ajst-7782	54	13	so	so	ADV
ajst-7782	54	14	dimensionality	dimensionality	NOUN
ajst-7782	54	15	reduction	reduction	NOUN
ajst-7782	54	16	processing	processing	NOUN
ajst-7782	54	17	is	be	AUX
ajst-7782	54	18	required	require	VERB
ajst-7782	54	19	.	.	PUNCT
ajst-7782	55	1	this	this	DET
ajst-7782	55	2	paper	paper	NOUN
ajst-7782	55	3	uses	use	VERB
ajst-7782	55	4	the	the	DET
ajst-7782	55	5	continuous	continuous	ADJ
ajst-7782	55	6	projections	projection	NOUN
ajst-7782	55	7	algorithm	algorithm	NOUN
ajst-7782	55	8	(	(	PUNCT
ajst-7782	55	9	spa	spa	NOUN
ajst-7782	55	10	)	)	PUNCT
ajst-7782	55	11	to	to	PART
ajst-7782	55	12	reduce	reduce	VERB
ajst-7782	55	13	the	the	DET
ajst-7782	55	14	dimension	dimension	NOUN
ajst-7782	55	15	of	of	ADP
ajst-7782	55	16	spectral	spectral	ADJ
ajst-7782	55	17	data	datum	NOUN
ajst-7782	55	18	.	.	PUNCT
ajst-7782	56	1	spa	spa	NOUN
ajst-7782	56	2	determines	determine	VERB
ajst-7782	56	3	the	the	DET
ajst-7782	56	4	most	most	ADV
ajst-7782	56	5	representative	representative	ADJ
ajst-7782	56	6	characteristic	characteristic	ADJ
ajst-7782	56	7	wavelength	wavelength	NOUN
ajst-7782	56	8	by	by	ADP
ajst-7782	56	9	projecting	project	VERB
ajst-7782	56	10	the	the	DET
ajst-7782	56	11	vector	vector	NOUN
ajst-7782	56	12	at	at	ADP
ajst-7782	56	13	each	each	DET
ajst-7782	56	14	wavelength	wavelength	NOUN
ajst-7782	56	15	point	point	NOUN
ajst-7782	56	16	onto	onto	ADP
ajst-7782	56	17	the	the	DET
ajst-7782	56	18	vector	vector	NOUN
ajst-7782	56	19	at	at	ADP
ajst-7782	56	20	other	other	ADJ
ajst-7782	56	21	wavelength	wavelength	NOUN
ajst-7782	56	22	points	point	NOUN
ajst-7782	56	23	and	and	CCONJ
ajst-7782	56	24	comparing	compare	VERB
ajst-7782	56	25	the	the	DET
ajst-7782	56	26	size	size	NOUN
ajst-7782	56	27	of	of	ADP
ajst-7782	56	28	the	the	DET
ajst-7782	56	29	projection	projection	NOUN
ajst-7782	56	30	vector	vector	NOUN
ajst-7782	56	31	.	.	PUNCT
ajst-7782	57	1	these	these	DET
ajst-7782	57	2	characteristic	characteristic	ADJ
ajst-7782	57	3	wavelengths	wavelength	NOUN
ajst-7782	57	4	have	have	VERB
ajst-7782	57	5	strong	strong	ADJ
ajst-7782	57	6	explanatory	explanatory	ADJ
ajst-7782	57	7	power	power	NOUN
ajst-7782	57	8	and	and	CCONJ
ajst-7782	57	9	can	can	AUX
ajst-7782	57	10	represent	represent	VERB
ajst-7782	57	11	all	all	DET
ajst-7782	57	12	useful	useful	ADJ
ajst-7782	57	13	information	information	NOUN
ajst-7782	57	14	in	in	ADP
ajst-7782	57	15	the	the	DET
ajst-7782	57	16	spectrum	spectrum	NOUN
ajst-7782	57	17	.	.	PUNCT
ajst-7782	58	1	extracting	extract	VERB
ajst-7782	58	2	these	these	DET
ajst-7782	58	3	characteristic	characteristic	ADJ
ajst-7782	58	4	wavelengths	wavelength	NOUN
ajst-7782	58	5	using	use	VERB
ajst-7782	58	6	spa	spa	NOUN
ajst-7782	58	7	algorithm	algorithm	NOUN
ajst-7782	58	8	can	can	AUX
ajst-7782	58	9	significantly	significantly	ADV
ajst-7782	58	10	improve	improve	VERB
ajst-7782	58	11	the	the	DET
ajst-7782	58	12	performance	performance	NOUN
ajst-7782	58	13	and	and	CCONJ
ajst-7782	58	14	running	run	VERB
ajst-7782	58	15	speed	speed	NOUN
ajst-7782	58	16	of	of	ADP
ajst-7782	58	17	the	the	DET
ajst-7782	58	18	model	model	NOUN
ajst-7782	58	19	.	.	PUNCT
ajst-7782	59	1	at	at	ADP
ajst-7782	59	2	the	the	DET
ajst-7782	59	3	same	same	ADJ
ajst-7782	59	4	time	time	NOUN
ajst-7782	59	5	,	,	PUNCT
ajst-7782	59	6	the	the	DET
ajst-7782	59	7	spa	spa	NOUN
ajst-7782	59	8	algorithm	algorithm	NOUN
ajst-7782	59	9	can	can	AUX
ajst-7782	59	10	also	also	ADV
ajst-7782	59	11	be	be	AUX
ajst-7782	59	12	optimized	optimize	VERB
ajst-7782	59	13	based	base	VERB
ajst-7782	59	14	on	on	ADP
ajst-7782	59	15	the	the	DET
ajst-7782	59	16	correction	correction	NOUN
ajst-7782	59	17	model	model	NOUN
ajst-7782	59	18	to	to	PART
ajst-7782	59	19	obtain	obtain	VERB
ajst-7782	59	20	more	more	ADV
ajst-7782	59	21	accurate	accurate	ADJ
ajst-7782	59	22	characteristic	characteristic	ADJ
ajst-7782	59	23	wavelengths	wavelength	NOUN
ajst-7782	59	24	.	.	PUNCT
ajst-7782	60	1	the	the	DET
ajst-7782	60	2	final	final	ADJ
ajst-7782	60	3	selected	select	VERB
ajst-7782	60	4	characteristic	characteristic	ADJ
ajst-7782	60	5	wavelengths	wavelength	NOUN
ajst-7782	60	6	in	in	ADP
ajst-7782	60	7	this	this	DET
ajst-7782	60	8	article	article	NOUN
ajst-7782	60	9	are	be	AUX
ajst-7782	60	10	190.46	190.46	NUM
ajst-7782	60	11	nm	nm	NOUN
ajst-7782	60	12	,	,	PUNCT
ajst-7782	60	13	203.39	203.39	NUM
ajst-7782	60	14	nm	nm	NOUN
ajst-7782	60	15	,	,	PUNCT
ajst-7782	60	16	and	and	CCONJ
ajst-7782	60	17	215.82	215.82	NUM
ajst-7782	60	18	nm	nm	NOUN
ajst-7782	60	19	,	,	PUNCT
ajst-7782	60	20	as	as	SCONJ
ajst-7782	60	21	shown	show	VERB
ajst-7782	60	22	in	in	ADP
ajst-7782	60	23	figure	figure	NOUN
ajst-7782	60	24	5	5	NUM
ajst-7782	60	25	.	.	PUNCT
ajst-7782	60	26	figure	figure	NOUN
ajst-7782	60	27	5	5	NUM
ajst-7782	60	28	.	.	PUNCT
ajst-7782	61	1	characteristic	characteristic	ADJ
ajst-7782	61	2	wavelength	wavelength	NOUN
ajst-7782	61	3	points	point	NOUN
ajst-7782	61	4	extracted	extract	VERB
ajst-7782	61	5	by	by	ADP
ajst-7782	61	6	spa	spa	NOUN
ajst-7782	61	7	3.3	3.3	NUM
ajst-7782	61	8	.	.	PUNCT
ajst-7782	62	1	establishment	establishment	NOUN
ajst-7782	62	2	of	of	ADP
ajst-7782	62	3	regression	regression	NOUN
ajst-7782	62	4	model	model	NOUN
ajst-7782	62	5	support	support	NOUN
ajst-7782	62	6	vector	vector	NOUN
ajst-7782	62	7	regression	regression	NOUN
ajst-7782	62	8	(	(	PUNCT
ajst-7782	62	9	svr	svr	PROPN
ajst-7782	62	10	)	)	PUNCT
ajst-7782	62	11	has	have	VERB
ajst-7782	62	12	advantages	advantage	NOUN
ajst-7782	62	13	in	in	ADP
ajst-7782	62	14	solving	solve	VERB
ajst-7782	62	15	small	small	ADJ
ajst-7782	62	16	sample	sample	NOUN
ajst-7782	62	17	,	,	PUNCT
ajst-7782	62	18	nonlinear	nonlinear	ADJ
ajst-7782	62	19	,	,	PUNCT
ajst-7782	62	20	and	and	CCONJ
ajst-7782	62	21	high	high	ADV
ajst-7782	62	22	-	-	PUNCT
ajst-7782	62	23	dimensional	dimensional	ADJ
ajst-7782	62	24	problems[8	problems[8	PROPN
ajst-7782	62	25	]	]	PUNCT
ajst-7782	62	26	.	.	PUNCT
ajst-7782	63	1	unlike	unlike	ADP
ajst-7782	63	2	traditional	traditional	ADJ
ajst-7782	63	3	linear	linear	ADJ
ajst-7782	63	4	or	or	CCONJ
ajst-7782	63	5	polynomial	polynomial	ADJ
ajst-7782	63	6	regression	regression	NOUN
ajst-7782	63	7	,	,	PUNCT
ajst-7782	63	8	svr	svr	PROPN
ajst-7782	63	9	models	model	VERB
ajst-7782	63	10	nonlinear	nonlinear	ADJ
ajst-7782	63	11	relationships	relationship	NOUN
ajst-7782	63	12	by	by	ADP
ajst-7782	63	13	mapping	map	VERB
ajst-7782	63	14	data	datum	NOUN
ajst-7782	63	15	into	into	ADP
ajst-7782	63	16	a	a	DET
ajst-7782	63	17	high	high	ADJ
ajst-7782	63	18	-	-	PUNCT
ajst-7782	63	19	dimensional	dimensional	ADJ
ajst-7782	63	20	space	space	NOUN
ajst-7782	63	21	and	and	CCONJ
ajst-7782	63	22	fitting	fitting	NOUN
ajst-7782	63	23	in	in	ADP
ajst-7782	63	24	that	that	PRON
ajst-7782	63	25	space[9	space[9	PROPN
ajst-7782	63	26	]	]	PUNCT
ajst-7782	63	27	.	.	PUNCT
ajst-7782	64	1	in	in	ADP
ajst-7782	64	2	svr	svr	PROPN
ajst-7782	64	3	,	,	PUNCT
ajst-7782	64	4	we	we	PRON
ajst-7782	64	5	first	first	ADV
ajst-7782	64	6	need	need	VERB
ajst-7782	64	7	to	to	PART
ajst-7782	64	8	determine	determine	VERB
ajst-7782	64	9	a	a	DET
ajst-7782	64	10	kernel	kernel	NOUN
ajst-7782	64	11	function	function	NOUN
ajst-7782	64	12	that	that	PRON
ajst-7782	64	13	maps	map	VERB
ajst-7782	64	14	low	low	ADJ
ajst-7782	64	15	dimensional	dimensional	ADJ
ajst-7782	64	16	data	datum	NOUN
ajst-7782	64	17	into	into	ADP
ajst-7782	64	18	high	high	ADJ
ajst-7782	64	19	dimensional	dimensional	ADJ
ajst-7782	64	20	space	space	NOUN
ajst-7782	64	21	.	.	PUNCT
ajst-7782	65	1	common	common	ADJ
ajst-7782	65	2	kernel	kernel	NOUN
ajst-7782	65	3	functions	function	NOUN
ajst-7782	65	4	include	include	VERB
ajst-7782	65	5	linear	linear	NOUN
ajst-7782	65	6	,	,	PUNCT
ajst-7782	65	7	polynomial	polynomial	ADJ
ajst-7782	65	8	,	,	PUNCT
ajst-7782	65	9	and	and	CCONJ
ajst-7782	65	10	radial	radial	ADJ
ajst-7782	65	11	basis	basis	NOUN
ajst-7782	65	12	functions	function	NOUN
ajst-7782	65	13	.	.	PUNCT
ajst-7782	66	1	next	next	ADJ
ajst-7782	66	2	,	,	PUNCT
ajst-7782	66	3	search	search	NOUN
ajst-7782	66	4	for	for	ADP
ajst-7782	66	5	an	an	DET
ajst-7782	66	6	optimal	optimal	ADJ
ajst-7782	66	7	hyperplane	hyperplane	NOUN
ajst-7782	66	8	in	in	ADP
ajst-7782	66	9	a	a	DET
ajst-7782	66	10	high	high	ADJ
ajst-7782	66	11	-	-	PUNCT
ajst-7782	66	12	dimensional	dimensional	ADJ
ajst-7782	66	13	space	space	NOUN
ajst-7782	66	14	to	to	PART
ajst-7782	66	15	minimize	minimize	VERB
ajst-7782	66	16	the	the	DET
ajst-7782	66	17	sum	sum	NOUN
ajst-7782	66	18	of	of	ADP
ajst-7782	66	19	distances	distance	NOUN
ajst-7782	66	20	from	from	ADP
ajst-7782	66	21	all	all	DET
ajst-7782	66	22	data	datum	NOUN
ajst-7782	66	23	points	point	NOUN
ajst-7782	66	24	to	to	ADP
ajst-7782	66	25	the	the	DET
ajst-7782	66	26	hyperplane	hyperplane	NOUN
ajst-7782	66	27	.	.	PUNCT
ajst-7782	67	1	this	this	DET
ajst-7782	67	2	hyperplane	hyperplane	NOUN
ajst-7782	67	3	is	be	AUX
ajst-7782	67	4	called	call	VERB
ajst-7782	67	5	the	the	DET
ajst-7782	67	6	"	"	PUNCT
ajst-7782	67	7	maximum	maximum	ADJ
ajst-7782	67	8	boundary	boundary	ADJ
ajst-7782	67	9	hyperplane	hyperplane	NOUN
ajst-7782	67	10	.	.	PUNCT
ajst-7782	68	1	"	"	PUNCT
ajst-7782	68	2	.	.	PUNCT
ajst-7782	69	1	similar	similar	ADJ
ajst-7782	69	2	to	to	ADP
ajst-7782	69	3	classification	classification	NOUN
ajst-7782	69	4	issues	issue	NOUN
ajst-7782	69	5	,	,	PUNCT
ajst-7782	69	6	svr	svr	PROPN
ajst-7782	69	7	also	also	ADV
ajst-7782	69	8	needs	need	VERB
ajst-7782	69	9	to	to	PART
ajst-7782	69	10	consider	consider	VERB
ajst-7782	69	11	balancing	balance	VERB
ajst-7782	69	12	within	within	ADP
ajst-7782	69	13	the	the	DET
ajst-7782	69	14	error	error	NOUN
ajst-7782	69	15	range	range	NOUN
ajst-7782	69	16	.	.	PUNCT
ajst-7782	70	1	therefore	therefore	ADV
ajst-7782	70	2	,	,	PUNCT
ajst-7782	70	3	in	in	ADP
ajst-7782	70	4	addition	addition	NOUN
ajst-7782	70	5	to	to	ADP
ajst-7782	70	6	the	the	DET
ajst-7782	70	7	maximum	maximum	ADJ
ajst-7782	70	8	boundary	boundary	ADJ
ajst-7782	70	9	hyperplane	hyperplane	NOUN
ajst-7782	70	10	,	,	PUNCT
ajst-7782	70	11	two	two	NUM
ajst-7782	70	12	other	other	ADJ
ajst-7782	70	13	parallel	parallel	ADJ
ajst-7782	70	14	hyperplanes	hyperplane	NOUN
ajst-7782	70	15	need	need	VERB
ajst-7782	70	16	to	to	PART
ajst-7782	70	17	be	be	AUX
ajst-7782	70	18	considered	consider	VERB
ajst-7782	70	19	.	.	PUNCT
ajst-7782	71	1	these	these	DET
ajst-7782	71	2	three	three	NUM
ajst-7782	71	3	hyperplanes	hyperplane	NOUN
ajst-7782	71	4	identify	identify	VERB
ajst-7782	71	5	a	a	DET
ajst-7782	71	6	region	region	NOUN
ajst-7782	71	7	called	call	VERB
ajst-7782	71	8	a	a	DET
ajst-7782	71	9	"	"	PUNCT
ajst-7782	71	10	support	support	NOUN
ajst-7782	71	11	vector	vector	NOUN
ajst-7782	71	12	,	,	PUNCT
ajst-7782	71	13	"	"	PUNCT
ajst-7782	71	14	which	which	PRON
ajst-7782	71	15	means	mean	VERB
ajst-7782	71	16	that	that	SCONJ
ajst-7782	71	17	all	all	DET
ajst-7782	71	18	sample	sample	NOUN
ajst-7782	71	19	points	point	NOUN
ajst-7782	71	20	located	locate	VERB
ajst-7782	71	21	within	within	ADP
ajst-7782	71	22	the	the	DET
ajst-7782	71	23	region	region	NOUN
ajst-7782	71	24	are	be	AUX
ajst-7782	71	25	considered	consider	VERB
ajst-7782	71	26	vectors	vector	NOUN
ajst-7782	71	27	that	that	PRON
ajst-7782	71	28	play	play	VERB
ajst-7782	71	29	an	an	DET
ajst-7782	71	30	important	important	ADJ
ajst-7782	71	31	role	role	NOUN
ajst-7782	71	32	in	in	ADP
ajst-7782	71	33	model	model	NOUN
ajst-7782	71	34	construction	construction	NOUN
ajst-7782	71	35	.	.	PUNCT
ajst-7782	72	1	during	during	ADP
ajst-7782	72	2	model	model	NOUN
ajst-7782	72	3	training	training	NOUN
ajst-7782	72	4	,	,	PUNCT
ajst-7782	72	5	svr	svr	PROPN
ajst-7782	72	6	will	will	AUX
ajst-7782	72	7	maximize	maximize	VERB
ajst-7782	72	8	the	the	DET
ajst-7782	72	9	distance	distance	NOUN
ajst-7782	72	10	between	between	ADP
ajst-7782	72	11	support	support	NOUN
ajst-7782	72	12	vectors	vector	NOUN
ajst-7782	72	13	as	as	ADV
ajst-7782	72	14	much	much	ADV
ajst-7782	72	15	as	as	ADP
ajst-7782	72	16	possible	possible	ADJ
ajst-7782	72	17	to	to	PART
ajst-7782	72	18	obtain	obtain	VERB
ajst-7782	72	19	better	well	ADJ
ajst-7782	72	20	generalization	generalization	NOUN
ajst-7782	72	21	capabilities	capability	NOUN
ajst-7782	72	22	.	.	PUNCT
ajst-7782	73	1	the	the	DET
ajst-7782	73	2	characteristic	characteristic	NOUN
ajst-7782	73	3	of	of	ADP
ajst-7782	73	4	svr	svr	PROPN
ajst-7782	73	5	is	be	AUX
ajst-7782	73	6	that	that	SCONJ
ajst-7782	73	7	it	it	PRON
ajst-7782	73	8	is	be	AUX
ajst-7782	73	9	not	not	PART
ajst-7782	73	10	only	only	ADV
ajst-7782	73	11	suitable	suitable	ADJ
ajst-7782	73	12	for	for	ADP
ajst-7782	73	13	linearly	linearly	ADV
ajst-7782	73	14	separable	separable	ADJ
ajst-7782	73	15	datasets	dataset	NOUN
ajst-7782	73	16	,	,	PUNCT
ajst-7782	73	17	but	but	CCONJ
ajst-7782	73	18	also	also	ADV
ajst-7782	73	19	capable	capable	ADJ
ajst-7782	73	20	of	of	ADP
ajst-7782	73	21	processing	process	VERB
ajst-7782	73	22	non	non	ADJ
ajst-7782	73	23	-	-	ADJ
ajst-7782	73	24	linear	linear	ADJ
ajst-7782	73	25	datasets	dataset	NOUN
ajst-7782	73	26	.	.	PUNCT
ajst-7782	74	1	in	in	ADP
ajst-7782	74	2	addition	addition	NOUN
ajst-7782	74	3	,	,	PUNCT
ajst-7782	74	4	svr	svr	PROPN
ajst-7782	74	5	has	have	VERB
ajst-7782	74	6	a	a	DET
ajst-7782	74	7	strong	strong	ADJ
ajst-7782	74	8	generalization	generalization	NOUN
ajst-7782	74	9	ability	ability	NOUN
ajst-7782	74	10	and	and	CCONJ
ajst-7782	74	11	can	can	AUX
ajst-7782	74	12	have	have	VERB
ajst-7782	74	13	a	a	DET
ajst-7782	74	14	certain	certain	ADJ
ajst-7782	74	15	tolerance	tolerance	NOUN
ajst-7782	74	16	for	for	ADP
ajst-7782	74	17	noise	noise	NOUN
ajst-7782	74	18	.	.	PUNCT
ajst-7782	75	1	in	in	ADP
ajst-7782	75	2	this	this	DET
ajst-7782	75	3	article	article	NOUN
ajst-7782	75	4	,	,	PUNCT
ajst-7782	75	5	any	any	DET
ajst-7782	75	6	one	one	NUM
ajst-7782	75	7	of	of	ADP
ajst-7782	75	8	the	the	DET
ajst-7782	75	9	training	training	NOUN
ajst-7782	75	10	data	datum	NOUN
ajst-7782	75	11	is	be	AUX
ajst-7782	75	12	selected	select	VERB
ajst-7782	75	13	as	as	ADP
ajst-7782	75	14	a	a	DET
ajst-7782	75	15	test	test	NOUN
ajst-7782	75	16	set	set	NOUN
ajst-7782	75	17	,	,	PUNCT
ajst-7782	75	18	and	and	CCONJ
ajst-7782	75	19	the	the	DET
ajst-7782	75	20	remaining	remain	VERB
ajst-7782	75	21	data	datum	NOUN
ajst-7782	75	22	is	be	AUX
ajst-7782	75	23	used	use	VERB
ajst-7782	75	24	as	as	ADP
ajst-7782	75	25	a	a	DET
ajst-7782	75	26	training	training	NOUN
ajst-7782	75	27	set	set	NOUN
ajst-7782	75	28	for	for	ADP
ajst-7782	75	29	cross	cross	NOUN
ajst-7782	75	30	validation	validation	NOUN
ajst-7782	75	31	.	.	PUNCT
ajst-7782	76	1	repeat	repeat	VERB
ajst-7782	76	2	until	until	SCONJ
ajst-7782	76	3	all	all	DET
ajst-7782	76	4	the	the	DET
ajst-7782	76	5	training	training	NOUN
ajst-7782	76	6	data	datum	NOUN
ajst-7782	76	7	have	have	AUX
ajst-7782	76	8	been	be	AUX
ajst-7782	76	9	selected	select	VERB
ajst-7782	76	10	as	as	ADP
ajst-7782	76	11	a	a	DET
ajst-7782	76	12	test	test	NOUN
ajst-7782	76	13	set	set	NOUN
ajst-7782	76	14	.	.	PUNCT
ajst-7782	77	1	the	the	DET
ajst-7782	77	2	parameter	parameter	NOUN
ajst-7782	77	3	with	with	ADP
ajst-7782	77	4	the	the	DET
ajst-7782	77	5	smallest	small	ADJ
ajst-7782	77	6	mean	mean	ADJ
ajst-7782	77	7	square	square	ADJ
ajst-7782	77	8	error	error	NOUN
ajst-7782	77	9	is	be	AUX
ajst-7782	77	10	input	input	VERB
ajst-7782	77	11	into	into	ADP
ajst-7782	77	12	the	the	DET
ajst-7782	77	13	svr	svr	PROPN
ajst-7782	77	14	model	model	NOUN
ajst-7782	77	15	.	.	PUNCT
ajst-7782	78	1	3.4	3.4	NUM
ajst-7782	78	2	.	.	PUNCT
ajst-7782	78	3	model	model	NOUN
ajst-7782	78	4	evaluation	evaluation	NOUN
ajst-7782	78	5	indicators	indicator	NOUN
ajst-7782	78	6	the	the	DET
ajst-7782	78	7	commonly	commonly	ADV
ajst-7782	78	8	used	use	VERB
ajst-7782	78	9	indicators	indicator	NOUN
ajst-7782	78	10	for	for	ADP
ajst-7782	78	11	evaluating	evaluate	VERB
ajst-7782	78	12	models	model	NOUN
ajst-7782	78	13	include	include	VERB
ajst-7782	78	14	the	the	DET
ajst-7782	78	15	determination	determination	NOUN
ajst-7782	78	16	coefficient	coefficient	NOUN
ajst-7782	78	17	r2	r2	PROPN
ajst-7782	78	18	,	,	PUNCT
ajst-7782	78	19	the	the	DET
ajst-7782	78	20	root	root	NOUN
ajst-7782	78	21	mean	mean	VERB
ajst-7782	78	22	square	square	ADJ
ajst-7782	78	23	error	error	NOUN
ajst-7782	78	24	rmse	rmse	NOUN
ajst-7782	78	25	,	,	PUNCT
ajst-7782	78	26	and	and	CCONJ
ajst-7782	78	27	the	the	DET
ajst-7782	78	28	correlation	correlation	NOUN
ajst-7782	78	29	coefficient	coefficient	NOUN
ajst-7782	78	30	r[10	r[10	PROPN
ajst-7782	78	31	]	]	PUNCT
ajst-7782	78	32	.	.	PUNCT
ajst-7782	79	1	in	in	ADP
ajst-7782	79	2	this	this	DET
ajst-7782	79	3	paper	paper	NOUN
ajst-7782	79	4	,	,	PUNCT
ajst-7782	79	5	the	the	DET
ajst-7782	79	6	determination	determination	NOUN
ajst-7782	79	7	coefficient	coefficient	NOUN
ajst-7782	79	8	r2	r2	PROPN
ajst-7782	79	9	and	and	CCONJ
ajst-7782	79	10	the	the	DET
ajst-7782	79	11	root	root	NOUN
ajst-7782	79	12	mean	mean	VERB
ajst-7782	79	13	square	square	ADJ
ajst-7782	79	14	error	error	NOUN
ajst-7782	79	15	rmse	rmse	NOUN
ajst-7782	79	16	are	be	AUX
ajst-7782	79	17	used	use	VERB
ajst-7782	79	18	to	to	PART
ajst-7782	79	19	evaluate	evaluate	VERB
ajst-7782	79	20	the	the	DET
ajst-7782	79	21	performance	performance	NOUN
ajst-7782	79	22	of	of	ADP
ajst-7782	79	23	the	the	DET
ajst-7782	79	24	model	model	NOUN
ajst-7782	79	25	.	.	PUNCT
ajst-7782	80	1	the	the	DET
ajst-7782	80	2	expressions	expression	NOUN
ajst-7782	80	3	for	for	ADP
ajst-7782	80	4	r2	r2	PROPN
ajst-7782	80	5	and	and	CCONJ
ajst-7782	80	6	rmse	rmse	NOUN
ajst-7782	80	7	are	be	AUX
ajst-7782	80	8	shown	show	VERB
ajst-7782	80	9	in	in	ADP
ajst-7782	80	10	equations	equation	NOUN
ajst-7782	80	11	(	(	PUNCT
ajst-7782	80	12	1	1	NUM
ajst-7782	80	13	)	)	PUNCT
ajst-7782	80	14	and	and	CCONJ
ajst-7782	80	15	(	(	PUNCT
ajst-7782	80	16	2	2	NUM
ajst-7782	80	17	)	)	PUNCT
ajst-7782	80	18	.	.	PUNCT
ajst-7782	81	1	180	180	NUM
ajst-7782	81	2	190	190	NUM
ajst-7782	81	3	200	200	NUM
ajst-7782	81	4	210	210	NUM
ajst-7782	81	5	220	220	NUM
ajst-7782	81	6	230	230	NUM
ajst-7782	81	7	240	240	NUM
ajst-7782	81	8	250	250	NUM
ajst-7782	81	9	wavelength	wavelength	NOUN
ajst-7782	81	10	/	/	SYM
ajst-7782	81	11	nm	nm	NOUN
ajst-7782	81	12	0	0	NUM
ajst-7782	81	13	0.5	0.5	NUM
ajst-7782	81	14	1	1	NUM
ajst-7782	81	15	1.5	1.5	NUM
ajst-7782	81	16	2	2	NUM
ajst-7782	81	17	180	180	NUM
ajst-7782	81	18	190	190	NUM
ajst-7782	81	19	200	200	NUM
ajst-7782	81	20	210	210	NUM
ajst-7782	81	21	220	220	NUM
ajst-7782	81	22	230	230	NUM
ajst-7782	81	23	240	240	NUM
ajst-7782	81	24	250	250	NUM
ajst-7782	81	25	0.0	0.0	NUM
ajst-7782	81	26	0.2	0.2	NUM
ajst-7782	81	27	0.4	0.4	NUM
ajst-7782	81	28	0.6	0.6	NUM
ajst-7782	81	29	0.8	0.8	NUM
ajst-7782	81	30	1.0	1.0	NUM
ajst-7782	81	31	1.2	1.2	NUM
ajst-7782	81	32	1.4	1.4	NUM
ajst-7782	81	33	1.6	1.6	NUM
ajst-7782	81	34	1.8	1.8	NUM
ajst-7782	81	35	a	a	DET
ajst-7782	81	36	bs	bs	NOUN
ajst-7782	81	37	or	or	CCONJ
ajst-7782	81	38	ba	ba	PROPN
ajst-7782	81	39	nc	nc	PROPN
ajst-7782	81	40	e/	e/	PROPN
ajst-7782	81	41	(	(	PUNCT
ajst-7782	81	42	a	a	DET
ajst-7782	81	43	.u	.u	NOUN
ajst-7782	81	44	.	.	PUNCT
ajst-7782	81	45	)	)	PUNCT
ajst-7782	82	1	wavelength	wavelength	NOUN
ajst-7782	82	2	/	/	SYM
ajst-7782	82	3	nm	nm	NOUN
ajst-7782	82	4	88	88	NUM
ajst-7782	82	5	𝑅	𝑅	PROPN
ajst-7782	82	6	∑	∑	NOUN
ajst-7782	82	7	̅	̅	PROPN
ajst-7782	82	8	∗	∗	NOUN
ajst-7782	82	9	∑	∑	NOUN
ajst-7782	82	10	̅	̅	NOUN
ajst-7782	82	11	∑	∑	PUNCT
ajst-7782	82	12	(	(	PUNCT
ajst-7782	82	13	1	1	NUM
ajst-7782	82	14	)	)	PUNCT
ajst-7782	82	15	𝑅𝑀𝑆𝐸	𝑅𝑀𝑆𝐸	NOUN
ajst-7782	82	16	∑	∑	X
ajst-7782	82	17	.	.	PUNCT
ajst-7782	83	1	(	(	PUNCT
ajst-7782	83	2	2	2	X
ajst-7782	83	3	)	)	PUNCT
ajst-7782	83	4	in	in	ADP
ajst-7782	83	5	the	the	DET
ajst-7782	83	6	formula	formula	NOUN
ajst-7782	83	7	,	,	PUNCT
ajst-7782	83	8	𝑛	𝑛	PROPN
ajst-7782	83	9	,	,	PUNCT
ajst-7782	83	10	𝑜	𝑜	NOUN
ajst-7782	83	11	,	,	PUNCT
ajst-7782	83	12	�	�	PROPN
ajst-7782	83	13	̅	̅	NOUN
ajst-7782	83	14	�	�	PROPN
ajst-7782	83	15	,	,	PUNCT
ajst-7782	83	16	𝑝	𝑝	NOUN
ajst-7782	83	17	,	,	PUNCT
ajst-7782	83	18	𝑝	𝑝	PROPN
ajst-7782	83	19	are	be	AUX
ajst-7782	83	20	respectively	respectively	ADV
ajst-7782	83	21	the	the	DET
ajst-7782	83	22	number	number	NOUN
ajst-7782	83	23	of	of	ADP
ajst-7782	83	24	samples	sample	NOUN
ajst-7782	83	25	,	,	PUNCT
ajst-7782	83	26	sample	sample	NOUN
ajst-7782	83	27	concentration	concentration	NOUN
ajst-7782	83	28	,	,	PUNCT
ajst-7782	83	29	mean	mean	ADJ
ajst-7782	83	30	value	value	NOUN
ajst-7782	83	31	of	of	ADP
ajst-7782	83	32	sample	sample	NOUN
ajst-7782	83	33	concentration	concentration	NOUN
ajst-7782	83	34	,	,	PUNCT
ajst-7782	83	35	sample	sample	NOUN
ajst-7782	83	36	predicted	predict	VERB
ajst-7782	83	37	value	value	NOUN
ajst-7782	83	38	,	,	PUNCT
ajst-7782	83	39	and	and	CCONJ
ajst-7782	83	40	mean	mean	ADJ
ajst-7782	83	41	value	value	NOUN
ajst-7782	83	42	of	of	ADP
ajst-7782	83	43	sample	sample	NOUN
ajst-7782	83	44	predicted	predict	VERB
ajst-7782	83	45	value	value	NOUN
ajst-7782	83	46	.	.	PUNCT
ajst-7782	84	1	the	the	DET
ajst-7782	84	2	closer	close	ADJ
ajst-7782	84	3	r2	r2	NOUN
ajst-7782	84	4	is	be	AUX
ajst-7782	84	5	to	to	ADP
ajst-7782	84	6	1	1	NUM
ajst-7782	84	7	,	,	PUNCT
ajst-7782	84	8	the	the	PRON
ajst-7782	84	9	better	well	ADJ
ajst-7782	84	10	the	the	DET
ajst-7782	84	11	fitting	fitting	ADJ
ajst-7782	84	12	effect	effect	NOUN
ajst-7782	84	13	of	of	ADP
ajst-7782	84	14	the	the	DET
ajst-7782	84	15	nitrite	nitrite	NOUN
ajst-7782	84	16	nitrogen	nitrogen	NOUN
ajst-7782	84	17	solution	solution	NOUN
ajst-7782	84	18	is	be	AUX
ajst-7782	84	19	.	.	PUNCT
ajst-7782	85	1	the	the	DET
ajst-7782	85	2	closer	close	ADJ
ajst-7782	85	3	rmse	rmse	NOUN
ajst-7782	85	4	is	be	AUX
ajst-7782	85	5	to	to	ADP
ajst-7782	85	6	0	0	NUM
ajst-7782	85	7	,	,	PUNCT
ajst-7782	85	8	the	the	PRON
ajst-7782	85	9	smaller	small	ADJ
ajst-7782	85	10	the	the	DET
ajst-7782	85	11	error	error	NOUN
ajst-7782	85	12	between	between	ADP
ajst-7782	85	13	the	the	DET
ajst-7782	85	14	actual	actual	ADJ
ajst-7782	85	15	value	value	NOUN
ajst-7782	85	16	of	of	ADP
ajst-7782	85	17	the	the	DET
ajst-7782	85	18	nitrite	nitrite	NOUN
ajst-7782	85	19	nitrogen	nitrogen	NOUN
ajst-7782	85	20	solution	solution	NOUN
ajst-7782	85	21	in	in	ADP
ajst-7782	85	22	the	the	DET
ajst-7782	85	23	water	water	NOUN
ajst-7782	85	24	and	and	CCONJ
ajst-7782	85	25	the	the	DET
ajst-7782	85	26	predicted	predict	VERB
ajst-7782	85	27	value	value	NOUN
ajst-7782	85	28	of	of	ADP
ajst-7782	85	29	the	the	DET
ajst-7782	85	30	model	model	NOUN
ajst-7782	85	31	is	be	AUX
ajst-7782	85	32	,	,	PUNCT
ajst-7782	85	33	indicating	indicate	VERB
ajst-7782	85	34	that	that	SCONJ
ajst-7782	85	35	the	the	DET
ajst-7782	85	36	prediction	prediction	NOUN
ajst-7782	85	37	effect	effect	NOUN
ajst-7782	85	38	of	of	ADP
ajst-7782	85	39	the	the	DET
ajst-7782	85	40	model	model	NOUN
ajst-7782	85	41	is	be	AUX
ajst-7782	85	42	better	well	ADJ
ajst-7782	85	43	.	.	PUNCT
ajst-7782	86	1	4	4	X
ajst-7782	86	2	.	.	NOUN
ajst-7782	86	3	results	result	NOUN
ajst-7782	86	4	and	and	CCONJ
ajst-7782	86	5	discussion	discussion	NOUN
ajst-7782	86	6	after	after	ADP
ajst-7782	86	7	establishing	establish	VERB
ajst-7782	86	8	a	a	DET
ajst-7782	86	9	spa	spa	NOUN
ajst-7782	86	10	-	-	PUNCT
ajst-7782	86	11	svr	svr	NOUN
ajst-7782	86	12	mixed	mixed	ADJ
ajst-7782	86	13	prediction	prediction	NOUN
ajst-7782	86	14	model	model	NOUN
ajst-7782	86	15	,	,	PUNCT
ajst-7782	86	16	the	the	DET
ajst-7782	86	17	prediction	prediction	NOUN
ajst-7782	86	18	results	result	NOUN
ajst-7782	86	19	of	of	ADP
ajst-7782	86	20	spectral	spectral	ADJ
ajst-7782	86	21	data	datum	NOUN
ajst-7782	86	22	under	under	ADP
ajst-7782	86	23	this	this	DET
ajst-7782	86	24	model	model	NOUN
ajst-7782	86	25	are	be	AUX
ajst-7782	86	26	shown	show	VERB
ajst-7782	86	27	in	in	ADP
ajst-7782	86	28	table	table	NOUN
ajst-7782	86	29	1	1	NUM
ajst-7782	86	30	.	.	PUNCT
ajst-7782	86	31	table	table	NOUN
ajst-7782	86	32	1	1	NUM
ajst-7782	86	33	lists	list	VERB
ajst-7782	86	34	the	the	DET
ajst-7782	86	35	true	true	ADJ
ajst-7782	86	36	values	value	NOUN
ajst-7782	86	37	,	,	PUNCT
ajst-7782	86	38	predicted	predict	VERB
ajst-7782	86	39	values	value	NOUN
ajst-7782	86	40	,	,	PUNCT
ajst-7782	86	41	and	and	CCONJ
ajst-7782	86	42	relative	relative	ADJ
ajst-7782	86	43	errors	error	NOUN
ajst-7782	86	44	of	of	ADP
ajst-7782	86	45	the	the	DET
ajst-7782	86	46	samples	sample	NOUN
ajst-7782	86	47	.	.	PUNCT
ajst-7782	87	1	from	from	ADP
ajst-7782	87	2	the	the	DET
ajst-7782	87	3	table	table	NOUN
ajst-7782	87	4	,	,	PUNCT
ajst-7782	87	5	it	it	PRON
ajst-7782	87	6	can	can	AUX
ajst-7782	87	7	be	be	AUX
ajst-7782	87	8	seen	see	VERB
ajst-7782	87	9	that	that	SCONJ
ajst-7782	87	10	when	when	SCONJ
ajst-7782	87	11	the	the	DET
ajst-7782	87	12	sample	sample	NOUN
ajst-7782	87	13	concentration	concentration	NOUN
ajst-7782	87	14	is	be	AUX
ajst-7782	87	15	0.1	0.1	NUM
ajst-7782	87	16	mg·l-1	mg·l-1	PROPN
ajst-7782	87	17	,	,	PUNCT
ajst-7782	87	18	the	the	DET
ajst-7782	87	19	relative	relative	ADJ
ajst-7782	87	20	error	error	NOUN
ajst-7782	87	21	is	be	AUX
ajst-7782	87	22	7.67	7.67	NUM
ajst-7782	87	23	%	%	NOUN
ajst-7782	87	24	,	,	PUNCT
ajst-7782	87	25	not	not	PART
ajst-7782	87	26	more	more	ADJ
ajst-7782	87	27	than	than	ADP
ajst-7782	87	28	10	10	NUM
ajst-7782	87	29	%	%	NOUN
ajst-7782	87	30	,	,	PUNCT
ajst-7782	87	31	and	and	CCONJ
ajst-7782	87	32	the	the	DET
ajst-7782	87	33	relative	relative	ADJ
ajst-7782	87	34	error	error	NOUN
ajst-7782	87	35	is	be	AUX
ajst-7782	87	36	within	within	ADP
ajst-7782	87	37	5	5	NUM
ajst-7782	87	38	%	%	NOUN
ajst-7782	87	39	at	at	ADP
ajst-7782	87	40	other	other	ADJ
ajst-7782	87	41	concentrations	concentration	NOUN
ajst-7782	87	42	.	.	PUNCT
ajst-7782	88	1	this	this	PRON
ajst-7782	88	2	indicates	indicate	VERB
ajst-7782	88	3	that	that	SCONJ
ajst-7782	88	4	the	the	DET
ajst-7782	88	5	modeling	modeling	NOUN
ajst-7782	88	6	method	method	NOUN
ajst-7782	88	7	used	use	VERB
ajst-7782	88	8	in	in	ADP
ajst-7782	88	9	this	this	DET
ajst-7782	88	10	article	article	NOUN
ajst-7782	88	11	is	be	AUX
ajst-7782	88	12	correct	correct	ADJ
ajst-7782	88	13	,	,	PUNCT
ajst-7782	88	14	and	and	CCONJ
ajst-7782	88	15	the	the	DET
ajst-7782	88	16	applicability	applicability	NOUN
ajst-7782	88	17	of	of	ADP
ajst-7782	88	18	the	the	DET
ajst-7782	88	19	model	model	NOUN
ajst-7782	88	20	is	be	AUX
ajst-7782	88	21	high	high	ADJ
ajst-7782	88	22	,	,	PUNCT
ajst-7782	88	23	enabling	enable	VERB
ajst-7782	88	24	accurate	accurate	ADJ
ajst-7782	88	25	measurement	measurement	NOUN
ajst-7782	88	26	of	of	ADP
ajst-7782	88	27	nitrite	nitrite	NOUN
ajst-7782	88	28	nitrogen	nitrogen	NOUN
ajst-7782	88	29	table	table	NOUN
ajst-7782	88	30	1	1	NUM
ajst-7782	88	31	.	.	PUNCT
ajst-7782	89	1	predicted	predict	VERB
ajst-7782	89	2	values	value	NOUN
ajst-7782	89	3	of	of	ADP
ajst-7782	89	4	nitrite	nitrite	NOUN
ajst-7782	89	5	nitrogen	nitrogen	PROPN
ajst-7782	89	6	spa	spa	PROPN
ajst-7782	89	7	-	-	PUNCT
ajst-7782	89	8	svr	svr	NOUN
ajst-7782	89	9	mixed	mixed	ADJ
ajst-7782	89	10	model	model	NOUN
ajst-7782	89	11	sample	sample	NOUN
ajst-7782	89	12	number	number	NOUN
ajst-7782	89	13	predicted	predict	VERB
ajst-7782	89	14	value/(mg·l-1	value/(mg·l-1	NOUN
ajst-7782	89	15	)	)	PUNCT
ajst-7782	89	16	true	true	ADJ
ajst-7782	89	17	value/(mg·l-1	value/(mg·l-1	NOUN
ajst-7782	89	18	)	)	PUNCT
ajst-7782	89	19	relative	relative	ADJ
ajst-7782	89	20	error/%	error/%	NOUN
ajst-7782	89	21	1	1	NUM
ajst-7782	89	22	0.10	0.10	NUM
ajst-7782	89	23	0.1	0.1	NUM
ajst-7782	89	24	7.67	7.67	NUM
ajst-7782	89	25	2	2	NUM
ajst-7782	89	26	0.20	0.20	NUM
ajst-7782	89	27	0.2	0.2	NUM
ajst-7782	89	28	0.73	0.73	NUM
ajst-7782	89	29	3	3	NUM
ajst-7782	89	30	0.29	0.29	NUM
ajst-7782	89	31	0.3	0.3	NUM
ajst-7782	89	32	1.29	1.29	NUM
ajst-7782	89	33	4	4	NUM
ajst-7782	89	34	0.41	0.41	NUM
ajst-7782	89	35	0.4	0.4	NUM
ajst-7782	89	36	3.99	3.99	NUM
ajst-7782	89	37	5	5	NUM
ajst-7782	89	38	0.49	0.49	NUM
ajst-7782	89	39	0.5	0.5	NUM
ajst-7782	89	40	0.96	0.96	NUM
ajst-7782	89	41	6	6	NUM
ajst-7782	89	42	0.59	0.59	NUM
ajst-7782	89	43	0.6	0.6	NUM
ajst-7782	89	44	0.80	0.80	NUM
ajst-7782	89	45	…	…	PUNCT
ajst-7782	89	46	…	…	PUNCT
ajst-7782	89	47	…	…	PUNCT
ajst-7782	89	48	…	…	PUNCT
ajst-7782	89	49	…	…	PUNCT
ajst-7782	89	50	…	…	PUNCT
ajst-7782	89	51	…	…	PUNCT
ajst-7782	89	52	…	…	PUNCT
ajst-7782	89	53	43	43	NUM
ajst-7782	89	54	16.05	16.05	NUM
ajst-7782	89	55	16	16	NUM
ajst-7782	89	56	0.37	0.37	NUM
ajst-7782	89	57	44	44	NUM
ajst-7782	89	58	16.86	16.86	NUM
ajst-7782	89	59	17	17	NUM
ajst-7782	89	60	0.80	0.80	NUM
ajst-7782	89	61	in	in	ADP
ajst-7782	89	62	order	order	NOUN
ajst-7782	89	63	to	to	PART
ajst-7782	89	64	verify	verify	VERB
ajst-7782	89	65	the	the	DET
ajst-7782	89	66	effectiveness	effectiveness	NOUN
ajst-7782	89	67	of	of	ADP
ajst-7782	89	68	the	the	DET
ajst-7782	89	69	prediction	prediction	NOUN
ajst-7782	89	70	model	model	NOUN
ajst-7782	89	71	,	,	PUNCT
ajst-7782	89	72	three	three	NUM
ajst-7782	89	73	other	other	ADJ
ajst-7782	89	74	models	model	NOUN
ajst-7782	89	75	,	,	PUNCT
ajst-7782	89	76	namely	namely	ADV
ajst-7782	89	77	kpca	kpca	NOUN
ajst-7782	89	78	-	-	PUNCT
ajst-7782	89	79	svr	svr	PROPN
ajst-7782	89	80	,	,	PUNCT
ajst-7782	89	81	pca	pca	NOUN
ajst-7782	89	82	-	-	PUNCT
ajst-7782	89	83	svr	svr	PROPN
ajst-7782	89	84	,	,	PUNCT
ajst-7782	89	85	and	and	CCONJ
ajst-7782	89	86	lasso	lasso	NOUN
ajst-7782	89	87	-	-	PUNCT
ajst-7782	89	88	svr	svr	PROPN
ajst-7782	89	89	,	,	PUNCT
ajst-7782	89	90	were	be	AUX
ajst-7782	89	91	established	establish	VERB
ajst-7782	89	92	and	and	CCONJ
ajst-7782	89	93	compared	compare	VERB
ajst-7782	89	94	with	with	ADP
ajst-7782	89	95	the	the	DET
ajst-7782	89	96	above	above	ADJ
ajst-7782	89	97	spa	spa	NOUN
ajst-7782	89	98	-	-	PUNCT
ajst-7782	89	99	svr	svr	PROPN
ajst-7782	89	100	model	model	NOUN
ajst-7782	89	101	.	.	PUNCT
ajst-7782	90	1	the	the	DET
ajst-7782	90	2	specific	specific	ADJ
ajst-7782	90	3	situation	situation	NOUN
ajst-7782	90	4	is	be	AUX
ajst-7782	90	5	shown	show	VERB
ajst-7782	90	6	in	in	ADP
ajst-7782	90	7	figure	figure	NOUN
ajst-7782	90	8	6	6	NUM
ajst-7782	90	9	.	.	PUNCT
ajst-7782	90	10	figure	figure	VERB
ajst-7782	90	11	6	6	NUM
ajst-7782	90	12	.	.	PUNCT
ajst-7782	90	13	relative	relative	ADJ
ajst-7782	90	14	error	error	NOUN
ajst-7782	90	15	diagram	diagram	NOUN
ajst-7782	90	16	of	of	ADP
ajst-7782	90	17	different	different	ADJ
ajst-7782	90	18	models	model	NOUN
ajst-7782	90	19	from	from	ADP
ajst-7782	90	20	figure	figure	NOUN
ajst-7782	90	21	6	6	NUM
ajst-7782	90	22	,	,	PUNCT
ajst-7782	90	23	it	it	PRON
ajst-7782	90	24	can	can	AUX
ajst-7782	90	25	be	be	AUX
ajst-7782	90	26	seen	see	VERB
ajst-7782	90	27	that	that	SCONJ
ajst-7782	90	28	the	the	DET
ajst-7782	90	29	spa	spa	NOUN
ajst-7782	90	30	-	-	PUNCT
ajst-7782	90	31	svr	svr	PROPN
ajst-7782	90	32	model	model	NOUN
ajst-7782	90	33	has	have	VERB
ajst-7782	90	34	the	the	DET
ajst-7782	90	35	smallest	small	ADJ
ajst-7782	90	36	fluctuations	fluctuation	NOUN
ajst-7782	90	37	,	,	PUNCT
ajst-7782	90	38	and	and	CCONJ
ajst-7782	90	39	the	the	DET
ajst-7782	90	40	average	average	ADJ
ajst-7782	90	41	relative	relative	ADJ
ajst-7782	90	42	errors	error	NOUN
ajst-7782	90	43	of	of	ADP
ajst-7782	90	44	the	the	DET
ajst-7782	90	45	four	four	NUM
ajst-7782	90	46	models	model	NOUN
ajst-7782	90	47	are	be	AUX
ajst-7782	90	48	1.33	1.33	NUM
ajst-7782	90	49	%	%	NOUN
ajst-7782	90	50	,	,	PUNCT
ajst-7782	90	51	1.93	1.93	NUM
ajst-7782	90	52	%	%	NOUN
ajst-7782	90	53	,	,	PUNCT
ajst-7782	90	54	3.00	3.00	NUM
ajst-7782	90	55	%	%	NOUN
ajst-7782	90	56	,	,	PUNCT
ajst-7782	90	57	and	and	CCONJ
ajst-7782	90	58	3.21	3.21	NUM
ajst-7782	90	59	%	%	NOUN
ajst-7782	90	60	,	,	PUNCT
ajst-7782	90	61	respectively	respectively	ADV
ajst-7782	90	62	.	.	PUNCT
ajst-7782	91	1	therefore	therefore	ADV
ajst-7782	91	2	,	,	PUNCT
ajst-7782	91	3	the	the	DET
ajst-7782	91	4	spa	spa	NOUN
ajst-7782	91	5	-	-	PUNCT
ajst-7782	91	6	svr	svr	PROPN
ajst-7782	91	7	model	model	NOUN
ajst-7782	91	8	is	be	AUX
ajst-7782	91	9	superior	superior	ADJ
ajst-7782	91	10	to	to	ADP
ajst-7782	91	11	the	the	DET
ajst-7782	91	12	other	other	ADJ
ajst-7782	91	13	three	three	NUM
ajst-7782	91	14	models	model	NOUN
ajst-7782	91	15	.	.	PUNCT
ajst-7782	92	1	table	table	NOUN
ajst-7782	92	2	2	2	NUM
ajst-7782	92	3	compares	compare	VERB
ajst-7782	92	4	these	these	DET
ajst-7782	92	5	four	four	NUM
ajst-7782	92	6	models	model	NOUN
ajst-7782	92	7	in	in	ADP
ajst-7782	92	8	terms	term	NOUN
ajst-7782	92	9	of	of	ADP
ajst-7782	92	10	r2	r2	PROPN
ajst-7782	92	11	and	and	CCONJ
ajst-7782	92	12	rmse	rmse	ADJ
ajst-7782	92	13	parameters	parameter	NOUN
ajst-7782	92	14	.	.	PUNCT
ajst-7782	93	1	the	the	DET
ajst-7782	93	2	r2	r2	PROPN
ajst-7782	93	3	of	of	ADP
ajst-7782	93	4	the	the	DET
ajst-7782	93	5	spa	spa	NOUN
ajst-7782	93	6	-	-	PUNCT
ajst-7782	93	7	svr	svr	PROPN
ajst-7782	93	8	model	model	NOUN
ajst-7782	93	9	is	be	AUX
ajst-7782	93	10	0.999654	0.999654	NUM
ajst-7782	93	11	,	,	PUNCT
ajst-7782	93	12	and	and	CCONJ
ajst-7782	93	13	the	the	DET
ajst-7782	93	14	rmse	rmse	NOUN
ajst-7782	93	15	is	be	AUX
ajst-7782	93	16	0.000479	0.000479	NUM
ajst-7782	93	17	mg·l-1	mg·l-1	NOUN
ajst-7782	93	18	.	.	PUNCT
ajst-7782	94	1	compared	compare	VERB
ajst-7782	94	2	to	to	ADP
ajst-7782	94	3	the	the	DET
ajst-7782	94	4	other	other	ADJ
ajst-7782	94	5	three	three	NUM
ajst-7782	94	6	models	model	NOUN
ajst-7782	94	7	,	,	PUNCT
ajst-7782	94	8	the	the	DET
ajst-7782	94	9	r2	r2	PROPN
ajst-7782	94	10	has	have	AUX
ajst-7782	94	11	increased	increase	VERB
ajst-7782	94	12	,	,	PUNCT
ajst-7782	94	13	while	while	SCONJ
ajst-7782	94	14	the	the	DET
ajst-7782	94	15	rmse	rmse	NOUN
ajst-7782	94	16	has	have	AUX
ajst-7782	94	17	decreased	decrease	VERB
ajst-7782	94	18	,	,	PUNCT
ajst-7782	94	19	indicating	indicate	VERB
ajst-7782	94	20	that	that	SCONJ
ajst-7782	94	21	the	the	DET
ajst-7782	94	22	model	model	NOUN
ajst-7782	94	23	is	be	AUX
ajst-7782	94	24	superior	superior	ADJ
ajst-7782	94	25	to	to	ADP
ajst-7782	94	26	the	the	DET
ajst-7782	94	27	other	other	ADJ
ajst-7782	94	28	three	three	NUM
ajst-7782	94	29	models	model	NOUN
ajst-7782	94	30	.	.	PUNCT
ajst-7782	95	1	table	table	NOUN
ajst-7782	95	2	2	2	NUM
ajst-7782	95	3	.	.	PUNCT
ajst-7782	95	4	comparison	comparison	NOUN
ajst-7782	95	5	of	of	ADP
ajst-7782	95	6	evaluation	evaluation	NOUN
ajst-7782	95	7	parameters	parameter	NOUN
ajst-7782	95	8	of	of	ADP
ajst-7782	95	9	different	different	ADJ
ajst-7782	95	10	analysis	analysis	NOUN
ajst-7782	95	11	models	model	NOUN
ajst-7782	95	12	modeling	model	VERB
ajst-7782	95	13	methods	method	NOUN
ajst-7782	95	14	model	model	NOUN
ajst-7782	95	15	evaluation	evaluation	NOUN
ajst-7782	95	16	r2	r2	PROPN
ajst-7782	95	17	rmse/(mg·l-1	rmse/(mg·l-1	NOUN
ajst-7782	95	18	)	)	PUNCT
ajst-7782	95	19	spa	spa	NOUN
ajst-7782	95	20	-	-	PUNCT
ajst-7782	95	21	svr	svr	NOUN
ajst-7782	95	22	0.999654	0.999654	NUM
ajst-7782	95	23	0.000479	0.000479	NUM
ajst-7782	95	24	kpca	kpca	NOUN
ajst-7782	95	25	-	-	PUNCT
ajst-7782	95	26	svr	svr	NOUN
ajst-7782	95	27	0.999604	0.999604	NUM
ajst-7782	95	28	0.004186	0.004186	NUM
ajst-7782	95	29	pca	pca	NOUN
ajst-7782	95	30	-	-	NOUN
ajst-7782	95	31	svr	svr	NOUN
ajst-7782	95	32	0.999596	0.999596	NUM
ajst-7782	95	33	0.004469	0.004469	NUM
ajst-7782	95	34	lasso	lasso	NOUN
ajst-7782	95	35	-	-	PUNCT
ajst-7782	95	36	svr	svr	NOUN
ajst-7782	95	37	0.999504	0.999504	NUM
ajst-7782	95	38	0.004798	0.004798	NUM
ajst-7782	95	39	0	0	NUM
ajst-7782	95	40	10	10	NUM
ajst-7782	95	41	20	20	NUM
ajst-7782	95	42	30	30	NUM
ajst-7782	95	43	40	40	NUM
ajst-7782	95	44	50	50	NUM
ajst-7782	95	45	0	0	NUM
ajst-7782	95	46	4	4	NUM
ajst-7782	95	47	8	8	NUM
ajst-7782	95	48	12	12	NUM
ajst-7782	95	49	r	r	NOUN
ajst-7782	95	50	el	el	PROPN
ajst-7782	95	51	at	at	ADP
ajst-7782	95	52	iv	iv	NUM
ajst-7782	95	53	e	e	PROPN
ajst-7782	95	54	e	e	X
ajst-7782	95	55	rr	rr	NOUN
ajst-7782	95	56	or	or	CCONJ
ajst-7782	95	57	/%	/%	PRON
ajst-7782	95	58	sample	sample	NOUN
ajst-7782	95	59	number	number	NOUN
ajst-7782	95	60	spa	spa	PROPN
ajst-7782	95	61	-	-	PUNCT
ajst-7782	95	62	svr	svr	PROPN
ajst-7782	95	63	kpca	kpca	PROPN
ajst-7782	95	64	-	-	PUNCT
ajst-7782	95	65	svr	svr	PROPN
ajst-7782	95	66	pca	pca	PROPN
ajst-7782	95	67	-	-	PUNCT
ajst-7782	95	68	svr	svr	PROPN
ajst-7782	95	69	lasso	lasso	NOUN
ajst-7782	95	70	-	-	PUNCT
ajst-7782	95	71	svr	svr	PROPN
ajst-7782	95	72	89	89	NUM
ajst-7782	95	73	in	in	ADP
ajst-7782	95	74	order	order	NOUN
ajst-7782	95	75	to	to	PART
ajst-7782	95	76	verify	verify	VERB
ajst-7782	95	77	the	the	DET
ajst-7782	95	78	impact	impact	NOUN
ajst-7782	95	79	of	of	ADP
ajst-7782	95	80	this	this	DET
ajst-7782	95	81	mixed	mixed	ADJ
ajst-7782	95	82	prediction	prediction	NOUN
ajst-7782	95	83	model	model	NOUN
ajst-7782	95	84	on	on	ADP
ajst-7782	95	85	the	the	DET
ajst-7782	95	86	stability	stability	NOUN
ajst-7782	95	87	of	of	ADP
ajst-7782	95	88	measured	measure	VERB
ajst-7782	95	89	nitrite	nitrite	NOUN
ajst-7782	95	90	nitrogen	nitrogen	NOUN
ajst-7782	95	91	,	,	PUNCT
ajst-7782	95	92	under	under	ADP
ajst-7782	95	93	this	this	DET
ajst-7782	95	94	optimal	optimal	ADJ
ajst-7782	95	95	model	model	NOUN
ajst-7782	95	96	,	,	PUNCT
ajst-7782	95	97	eight	eight	NUM
ajst-7782	95	98	measurements	measurement	NOUN
ajst-7782	95	99	were	be	AUX
ajst-7782	95	100	conducted	conduct	VERB
ajst-7782	95	101	on	on	ADP
ajst-7782	95	102	a	a	DET
ajst-7782	95	103	nitrite	nitrite	NOUN
ajst-7782	95	104	nitrogen	nitrogen	NOUN
ajst-7782	95	105	standard	standard	ADJ
ajst-7782	95	106	solution	solution	NOUN
ajst-7782	95	107	with	with	ADP
ajst-7782	95	108	a	a	DET
ajst-7782	95	109	concentration	concentration	NOUN
ajst-7782	95	110	of	of	ADP
ajst-7782	95	111	10	10	NUM
ajst-7782	95	112	mg·l-1	mg·l-1	PROPN
ajst-7782	95	113	.	.	PUNCT
ajst-7782	96	1	the	the	DET
ajst-7782	96	2	measured	measure	VERB
ajst-7782	96	3	results	result	NOUN
ajst-7782	96	4	are	be	AUX
ajst-7782	96	5	shown	show	VERB
ajst-7782	96	6	in	in	ADP
ajst-7782	96	7	table	table	NOUN
ajst-7782	96	8	3	3	NUM
ajst-7782	96	9	:	:	PUNCT
ajst-7782	96	10	table	table	NOUN
ajst-7782	96	11	3	3	NUM
ajst-7782	96	12	.	.	PUNCT
ajst-7782	96	13	measured	measure	VERB
ajst-7782	96	14	values	value	NOUN
ajst-7782	96	15	of	of	ADP
ajst-7782	96	16	nitrite	nitrite	NOUN
ajst-7782	96	17	nitrogen	nitrogen	NOUN
ajst-7782	96	18	solution	solution	NOUN
ajst-7782	96	19	at	at	ADP
ajst-7782	96	20	10	10	NUM
ajst-7782	96	21	mg	mg	NUM
ajst-7782	96	22	·	·	PUNCT
ajst-7782	96	23	l-1	l-1	NUM
ajst-7782	96	24	for	for	ADP
ajst-7782	96	25	multiple	multiple	ADJ
ajst-7782	96	26	tests	test	NOUN
ajst-7782	96	27	sample	sample	NOUN
ajst-7782	96	28	number	number	NOUN
ajst-7782	96	29	predicted	predict	VERB
ajst-7782	96	30	value/(mg·l-1	value/(mg·l-1	NOUN
ajst-7782	96	31	)	)	PUNCT
ajst-7782	96	32	true	true	ADJ
ajst-7782	96	33	value/(mg·l-1	value/(mg·l-1	NOUN
ajst-7782	96	34	)	)	PUNCT
ajst-7782	96	35	relative	relative	ADJ
ajst-7782	96	36	error/%	error/%	NOUN
ajst-7782	96	37	1	1	NUM
ajst-7782	96	38	10.75	10.75	NUM
ajst-7782	96	39	10.00	10.00	NUM
ajst-7782	96	40	7.5	7.5	NUM
ajst-7782	96	41	2	2	NUM
ajst-7782	96	42	10.75	10.75	NUM
ajst-7782	96	43	10.00	10.00	NUM
ajst-7782	96	44	7.6	7.6	NUM
ajst-7782	96	45	3	3	NUM
ajst-7782	96	46	10.74	10.74	NUM
ajst-7782	96	47	10.00	10.00	NUM
ajst-7782	96	48	7.4	7.4	NUM
ajst-7782	96	49	4	4	NUM
ajst-7782	96	50	10.75	10.75	NUM
ajst-7782	96	51	10.00	10.00	NUM
ajst-7782	96	52	7.5	7.5	NUM
ajst-7782	96	53	5	5	NUM
ajst-7782	96	54	10.77	10.77	NUM
ajst-7782	96	55	10.00	10.00	NUM
ajst-7782	96	56	7.7	7.7	NUM
ajst-7782	96	57	6	6	NUM
ajst-7782	96	58	10.79	10.79	NUM
ajst-7782	96	59	10.00	10.00	NUM
ajst-7782	96	60	8.0	8.0	NUM
ajst-7782	96	61	7	7	NUM
ajst-7782	96	62	10.78	10.78	NUM
ajst-7782	96	63	10.00	10.00	NUM
ajst-7782	96	64	7.9	7.9	NUM
ajst-7782	96	65	8	8	NUM
ajst-7782	96	66	10.80	10.80	NUM
ajst-7782	96	67	10.00	10.00	NUM
ajst-7782	96	68	8.1	8.1	NUM
ajst-7782	96	69	average	average	ADJ
ajst-7782	96	70	value	value	NOUN
ajst-7782	96	71	10.77	10.77	NUM
ajst-7782	96	72	7.7	7.7	NUM
ajst-7782	96	73	as	as	SCONJ
ajst-7782	96	74	can	can	AUX
ajst-7782	96	75	be	be	AUX
ajst-7782	96	76	seen	see	VERB
ajst-7782	96	77	from	from	ADP
ajst-7782	96	78	table	table	NOUN
ajst-7782	96	79	3	3	NUM
ajst-7782	96	80	,	,	PUNCT
ajst-7782	96	81	the	the	DET
ajst-7782	96	82	relative	relative	ADJ
ajst-7782	96	83	error	error	NOUN
ajst-7782	96	84	between	between	ADP
ajst-7782	96	85	the	the	DET
ajst-7782	96	86	single	single	ADJ
ajst-7782	96	87	measurement	measurement	NOUN
ajst-7782	96	88	value	value	NOUN
ajst-7782	96	89	and	and	CCONJ
ajst-7782	96	90	the	the	DET
ajst-7782	96	91	actual	actual	ADJ
ajst-7782	96	92	value	value	NOUN
ajst-7782	96	93	is	be	AUX
ajst-7782	96	94	within	within	ADP
ajst-7782	96	95	10	10	NUM
ajst-7782	96	96	%	%	NOUN
ajst-7782	96	97	,	,	PUNCT
ajst-7782	96	98	and	and	CCONJ
ajst-7782	96	99	the	the	DET
ajst-7782	96	100	average	average	ADJ
ajst-7782	96	101	value	value	NOUN
ajst-7782	96	102	of	of	ADP
ajst-7782	96	103	the	the	DET
ajst-7782	96	104	relative	relative	ADJ
ajst-7782	96	105	error	error	NOUN
ajst-7782	96	106	for	for	ADP
ajst-7782	96	107	eight	eight	NUM
ajst-7782	96	108	measurements	measurement	NOUN
ajst-7782	96	109	is	be	AUX
ajst-7782	96	110	7.7	7.7	NUM
ajst-7782	96	111	%	%	NOUN
ajst-7782	96	112	,	,	PUNCT
ajst-7782	96	113	indicating	indicate	VERB
ajst-7782	96	114	that	that	SCONJ
ajst-7782	96	115	using	use	VERB
ajst-7782	96	116	the	the	DET
ajst-7782	96	117	spa	spa	NOUN
ajst-7782	96	118	-	-	PUNCT
ajst-7782	96	119	svr	svr	NOUN
ajst-7782	96	120	mixed	mixed	ADJ
ajst-7782	96	121	prediction	prediction	NOUN
ajst-7782	96	122	model	model	NOUN
ajst-7782	96	123	to	to	PART
ajst-7782	96	124	measure	measure	VERB
ajst-7782	96	125	nitrite	nitrite	NOUN
ajst-7782	96	126	nitrogen	nitrogen	NOUN
ajst-7782	96	127	solution	solution	NOUN
ajst-7782	96	128	has	have	VERB
ajst-7782	96	129	good	good	ADJ
ajst-7782	96	130	stability	stability	NOUN
ajst-7782	96	131	.	.	PUNCT
ajst-7782	97	1	5	5	X
ajst-7782	97	2	.	.	X
ajst-7782	97	3	summary	summary	NOUN
ajst-7782	97	4	this	this	DET
ajst-7782	97	5	paper	paper	NOUN
ajst-7782	97	6	proposes	propose	VERB
ajst-7782	97	7	a	a	DET
ajst-7782	97	8	spa	spa	NOUN
ajst-7782	97	9	-	-	PUNCT
ajst-7782	97	10	svr	svr	NOUN
ajst-7782	97	11	mixing	mix	VERB
ajst-7782	97	12	research	research	NOUN
ajst-7782	97	13	model	model	NOUN
ajst-7782	97	14	based	base	VERB
ajst-7782	97	15	on	on	ADP
ajst-7782	97	16	nitrite	nitrite	NOUN
ajst-7782	97	17	nitrogen	nitrogen	NOUN
ajst-7782	97	18	standard	standard	ADJ
ajst-7782	97	19	solution	solution	NOUN
ajst-7782	97	20	,	,	PUNCT
ajst-7782	97	21	and	and	CCONJ
ajst-7782	97	22	compares	compare	VERB
ajst-7782	97	23	it	it	PRON
ajst-7782	97	24	with	with	ADP
ajst-7782	97	25	three	three	NUM
ajst-7782	97	26	other	other	ADJ
ajst-7782	97	27	mixing	mixing	NOUN
ajst-7782	97	28	models	model	NOUN
ajst-7782	97	29	:	:	PUNCT
ajst-7782	97	30	kpca	kpca	PROPN
ajst-7782	97	31	-	-	PUNCT
ajst-7782	97	32	svr	svr	PROPN
ajst-7782	97	33	,	,	PUNCT
ajst-7782	97	34	pca	pca	NOUN
ajst-7782	97	35	-	-	PUNCT
ajst-7782	97	36	svr	svr	PROPN
ajst-7782	97	37	,	,	PUNCT
ajst-7782	97	38	and	and	CCONJ
ajst-7782	97	39	lasso	lasso	NOUN
ajst-7782	97	40	-	-	PUNCT
ajst-7782	97	41	svr	svr	PROPN
ajst-7782	97	42	.	.	PUNCT
ajst-7782	98	1	the	the	DET
ajst-7782	98	2	research	research	NOUN
ajst-7782	98	3	results	result	NOUN
ajst-7782	98	4	show	show	VERB
ajst-7782	98	5	that	that	SCONJ
ajst-7782	98	6	the	the	DET
ajst-7782	98	7	decision	decision	NOUN
ajst-7782	98	8	coefficient	coefficient	NOUN
ajst-7782	98	9	r2	r2	NOUN
ajst-7782	98	10	of	of	ADP
ajst-7782	98	11	the	the	DET
ajst-7782	98	12	spa	spa	NOUN
ajst-7782	98	13	-	-	PUNCT
ajst-7782	98	14	svr	svr	NOUN
ajst-7782	98	15	hybrid	hybrid	NOUN
ajst-7782	98	16	prediction	prediction	NOUN
ajst-7782	98	17	model	model	NOUN
ajst-7782	98	18	is	be	AUX
ajst-7782	98	19	0.999654	0.999654	NUM
ajst-7782	98	20	,	,	PUNCT
ajst-7782	98	21	which	which	PRON
ajst-7782	98	22	is	be	AUX
ajst-7782	98	23	0.0050	0.0050	NUM
ajst-7782	98	24	%	%	NOUN
ajst-7782	98	25	,	,	PUNCT
ajst-7782	98	26	0.0058	0.0058	NUM
ajst-7782	98	27	%	%	NOUN
ajst-7782	98	28	,	,	PUNCT
ajst-7782	98	29	and	and	CCONJ
ajst-7782	98	30	0.0150	0.0150	NUM
ajst-7782	98	31	%	%	NOUN
ajst-7782	98	32	higher	high	ADJ
ajst-7782	98	33	than	than	ADP
ajst-7782	98	34	the	the	DET
ajst-7782	98	35	other	other	ADJ
ajst-7782	98	36	three	three	NUM
ajst-7782	98	37	hybrid	hybrid	ADJ
ajst-7782	98	38	models	model	NOUN
ajst-7782	98	39	,	,	PUNCT
ajst-7782	98	40	respectively	respectively	ADV
ajst-7782	98	41	;	;	PUNCT
ajst-7782	98	42	the	the	DET
ajst-7782	98	43	root	root	NOUN
ajst-7782	98	44	mean	mean	VERB
ajst-7782	98	45	square	square	ADJ
ajst-7782	98	46	error	error	NOUN
ajst-7782	98	47	(	(	PUNCT
ajst-7782	98	48	rmse	rmse	NOUN
ajst-7782	98	49	)	)	PUNCT
ajst-7782	98	50	is	be	AUX
ajst-7782	98	51	0.0004798	0.0004798	NUM
ajst-7782	98	52	mg·l-1	mg·l-1	PROPN
ajst-7782	98	53	,	,	PUNCT
ajst-7782	98	54	which	which	PRON
ajst-7782	98	55	is	be	AUX
ajst-7782	98	56	88.54	88.54	NUM
ajst-7782	98	57	%	%	NOUN
ajst-7782	98	58	,	,	PUNCT
ajst-7782	98	59	89.26	89.26	NUM
ajst-7782	98	60	%	%	NOUN
ajst-7782	98	61	,	,	PUNCT
ajst-7782	98	62	and	and	CCONJ
ajst-7782	98	63	90	90	NUM
ajst-7782	98	64	%	%	NOUN
ajst-7782	98	65	lower	low	ADJ
ajst-7782	98	66	than	than	ADP
ajst-7782	98	67	the	the	DET
ajst-7782	98	68	other	other	ADJ
ajst-7782	98	69	three	three	NUM
ajst-7782	98	70	models	model	NOUN
ajst-7782	98	71	,	,	PUNCT
ajst-7782	98	72	respectively	respectively	ADV
ajst-7782	98	73	.	.	PUNCT
ajst-7782	99	1	in	in	ADP
ajst-7782	99	2	addition	addition	NOUN
ajst-7782	99	3	,	,	PUNCT
ajst-7782	99	4	based	base	VERB
ajst-7782	99	5	on	on	ADP
ajst-7782	99	6	the	the	DET
ajst-7782	99	7	mixed	mixed	ADJ
ajst-7782	99	8	prediction	prediction	NOUN
ajst-7782	99	9	model	model	NOUN
ajst-7782	99	10	,	,	PUNCT
ajst-7782	99	11	the	the	DET
ajst-7782	99	12	measurement	measurement	NOUN
ajst-7782	99	13	stability	stability	NOUN
ajst-7782	99	14	of	of	ADP
ajst-7782	99	15	nitrite	nitrite	NOUN
ajst-7782	99	16	is	be	AUX
ajst-7782	99	17	7.7	7.7	NUM
ajst-7782	99	18	%	%	NOUN
ajst-7782	99	19	,	,	PUNCT
ajst-7782	99	20	which	which	PRON
ajst-7782	99	21	indicates	indicate	VERB
ajst-7782	99	22	that	that	SCONJ
ajst-7782	99	23	the	the	DET
ajst-7782	99	24	spa	spa	NOUN
ajst-7782	99	25	-	-	PUNCT
ajst-7782	99	26	svr	svr	NOUN
ajst-7782	99	27	mixed	mixed	ADJ
ajst-7782	99	28	model	model	NOUN
ajst-7782	99	29	proposed	propose	VERB
ajst-7782	99	30	in	in	ADP
ajst-7782	99	31	this	this	DET
ajst-7782	99	32	article	article	NOUN
ajst-7782	99	33	can	can	AUX
ajst-7782	99	34	provide	provide	VERB
ajst-7782	99	35	a	a	DET
ajst-7782	99	36	new	new	ADJ
ajst-7782	99	37	solution	solution	NOUN
ajst-7782	99	38	for	for	ADP
ajst-7782	99	39	rapid	rapid	ADJ
ajst-7782	99	40	and	and	CCONJ
ajst-7782	99	41	pollution	pollution	NOUN
ajst-7782	99	42	-	-	PUNCT
ajst-7782	99	43	free	free	ADJ
ajst-7782	99	44	monitoring	monitoring	NOUN
ajst-7782	99	45	of	of	ADP
ajst-7782	99	46	nitrite	nitrite	NOUN
ajst-7782	99	47	in	in	ADP
ajst-7782	99	48	water	water	NOUN
ajst-7782	99	49	.	.	PUNCT
ajst-7782	100	1	acknowledgment	acknowledgment	NOUN
ajst-7782	100	2	national	national	PROPN
ajst-7782	100	3	natural	natural	PROPN
ajst-7782	100	4	science	science	PROPN
ajst-7782	100	5	foundation	foundation	PROPN
ajst-7782	100	6	of	of	ADP
ajst-7782	100	7	china	china	PROPN
ajst-7782	100	8	(	(	PUNCT
ajst-7782	100	9	61805030	61805030	NUM
ajst-7782	100	10	)	)	PUNCT
ajst-7782	100	11	,	,	PUNCT
ajst-7782	100	12	chongqing	chongqe	VERB
ajst-7782	100	13	basic	basic	ADJ
ajst-7782	100	14	and	and	CCONJ
ajst-7782	100	15	frontier	frontier	NOUN
ajst-7782	100	16	technology	technology	NOUN
ajst-7782	100	17	research	research	NOUN
ajst-7782	100	18	project	project	NOUN
ajst-7782	100	19	(	(	PUNCT
ajst-7782	100	20	cstc2020jcyj	cstc2020jcyj	NOUN
ajst-7782	100	21	-	-	PUNCT
ajst-7782	100	22	msxmx0147	msxmx0147	PROPN
ajst-7782	100	23	)	)	PUNCT
ajst-7782	101	1	,	,	PUNCT
ajst-7782	101	2	chongqing	chongqe	VERB
ajst-7782	101	3	education	education	NOUN
ajst-7782	101	4	commission	commission	PROPN
ajst-7782	101	5	science	science	NOUN
ajst-7782	101	6	and	and	CCONJ
ajst-7782	101	7	technology	technology	NOUN
ajst-7782	101	8	project	project	NOUN
ajst-7782	101	9	(	(	PUNCT
ajst-7782	101	10	kjqn202000640	kjqn202000640	PROPN
ajst-7782	101	11	,	,	PUNCT
ajst-7782	101	12	kjzd	kjzd	NOUN
ajst-7782	101	13	-	-	PUNCT
ajst-7782	101	14	m202200602	m202200602	NOUN
ajst-7782	101	15	)	)	PUNCT
ajst-7782	101	16	references	reference	NOUN
ajst-7782	101	17	[	[	X
ajst-7782	101	18	1	1	NUM
ajst-7782	101	19	]	]	X
ajst-7782	101	20	lu	lu	NOUN
ajst-7782	101	21	h	h	NOUN
ajst-7782	101	22	,	,	PUNCT
ajst-7782	101	23	peng	peng	PROPN
ajst-7782	101	24	m	m	PROPN
ajst-7782	101	25	,	,	PUNCT
ajst-7782	101	26	zhang	zhang	PROPN
ajst-7782	101	27	g	g	PROPN
ajst-7782	101	28	,	,	PUNCT
ajst-7782	102	1	et	et	PROPN
ajst-7782	102	2	al	al	PROPN
ajst-7782	102	3	.	.	PROPN
ajst-7782	102	4	biokinetic	biokinetic	PROPN
ajst-7782	102	5	and	and	CCONJ
ajst-7782	102	6	biotransformation	biotransformation	NOUN
ajst-7782	102	7	of	of	ADP
ajst-7782	102	8	nitrogen	nitrogen	NOUN
ajst-7782	102	9	during	during	ADP
ajst-7782	102	10	photosynthetic	photosynthetic	ADJ
ajst-7782	102	11	becteria	becteria	PROPN
ajst-7782	102	12	wastewater	wastewater	PROPN
ajst-7782	102	13	treatment[j	treatment[j	PROPN
ajst-7782	102	14	]	]	PUNCT
ajst-7782	102	15	.	.	PUNCT
ajst-7782	103	1	environmental	environmental	ADJ
ajst-7782	103	2	technology	technology	NOUN
ajst-7782	103	3	,	,	PUNCT
ajst-7782	103	4	2018	2018	NUM
ajst-7782	103	5	,	,	PUNCT
ajst-7782	103	6	41(15	41(15	NUM
ajst-7782	103	7	):	):	PUNCT
ajst-7782	103	8	1	1	NUM
ajst-7782	103	9	-	-	SYM
ajst-7782	103	10	28	28	NUM
ajst-7782	103	11	.	.	PUNCT
ajst-7782	104	1	[	[	X
ajst-7782	104	2	2	2	X
ajst-7782	104	3	]	]	PUNCT
ajst-7782	104	4	wang	wang	PROPN
ajst-7782	104	5	c	c	PROPN
ajst-7782	104	6	,	,	PUNCT
ajst-7782	104	7	wang	wang	PROPN
ajst-7782	104	8	b	b	PROPN
ajst-7782	104	9	,	,	PUNCT
ajst-7782	104	10	ji	ji	PROPN
ajst-7782	104	11	t	t	PROPN
ajst-7782	104	12	,	,	PUNCT
ajst-7782	104	13	et	et	PROPN
ajst-7782	104	14	al	al	PROPN
ajst-7782	104	15	.	.	PROPN
ajst-7782	104	16	simulated	simulate	VERB
ajst-7782	104	17	estimation	estimation	NOUN
ajst-7782	104	18	of	of	ADP
ajst-7782	104	19	nitrite	nitrite	NOUN
ajst-7782	104	20	content	content	NOUN
ajst-7782	104	21	in	in	ADP
ajst-7782	104	22	water	water	NOUN
ajst-7782	104	23	using	use	VERB
ajst-7782	104	24	transmission	transmission	NOUN
ajst-7782	104	25	spectroscopy[j	spectroscopy[j	NOUN
ajst-7782	104	26	]	]	PUNCT
ajst-7782	104	27	spectroscopy	spectroscopy	NOUN
ajst-7782	104	28	and	and	CCONJ
ajst-7782	104	29	spectral	spectral	ADJ
ajst-7782	104	30	analysis	analysis	NOUN
ajst-7782	104	31	,	,	PUNCT
ajst-7782	104	32	2022	2022	NUM
ajst-7782	104	33	,	,	PUNCT
ajst-7782	104	34	42(7	42(7	NUM
ajst-7782	104	35	):	):	PUNCT
ajst-7782	104	36	2181	2181	NUM
ajst-7782	104	37	-	-	SYM
ajst-7782	104	38	2186	2186	NUM
ajst-7782	104	39	.	.	PUNCT
ajst-7782	105	1	[	[	X
ajst-7782	105	2	3	3	X
ajst-7782	105	3	]	]	X
ajst-7782	105	4	alahi	alahi	NOUN
ajst-7782	105	5	m	m	PROPN
ajst-7782	105	6	,	,	PUNCT
ajst-7782	105	7	mukhopadhyay	mukhopadhyay	PROPN
ajst-7782	105	8	s.	s.	PROPN
ajst-7782	105	9	detection	detection	PROPN
ajst-7782	105	10	methods	method	NOUN
ajst-7782	105	11	of	of	ADP
ajst-7782	105	12	nitrate	nitrate	NOUN
ajst-7782	105	13	in	in	ADP
ajst-7782	105	14	water	water	NOUN
ajst-7782	105	15	:	:	PUNCT
ajst-7782	105	16	a	a	DET
ajst-7782	105	17	review[j	review[j	PROPN
ajst-7782	105	18	]	]	PUNCT
ajst-7782	105	19	.	.	PUNCT
ajst-7782	106	1	sensors	sensor	NOUN
ajst-7782	106	2	and	and	CCONJ
ajst-7782	106	3	actuators	actuator	NOUN
ajst-7782	106	4	:	:	PUNCT
ajst-7782	106	5	a.	a.	NOUN
ajst-7782	106	6	physical	physical	PROPN
ajst-7782	106	7	,	,	PUNCT
ajst-7782	106	8	2018	2018	NUM
ajst-7782	106	9	,	,	PUNCT
ajst-7782	106	10	280	280	NUM
ajst-7782	106	11	:	:	SYM
ajst-7782	106	12	210	210	NUM
ajst-7782	106	13	-	-	SYM
ajst-7782	106	14	221	221	NUM
ajst-7782	106	15	.	.	PUNCT
ajst-7782	107	1	[	[	X
ajst-7782	107	2	4	4	X
ajst-7782	107	3	]	]	X
ajst-7782	107	4	singh	singh	PROPN
ajst-7782	107	5	p	p	X
ajst-7782	107	6	,	,	PUNCT
ajst-7782	107	7	singh	singh	PROPN
ajst-7782	107	8	m	m	NOUN
ajst-7782	107	9	k	k	NOUN
ajst-7782	107	10	,	,	PUNCT
ajst-7782	107	11	beg	beg	VERB
ajst-7782	107	12	y	y	PROPN
ajst-7782	107	13	r	r	PROPN
ajst-7782	107	14	,	,	PUNCT
ajst-7782	107	15	et	et	PROPN
ajst-7782	107	16	al	al	PROPN
ajst-7782	107	17	.	.	PUNCT
ajst-7782	108	1	a	a	DET
ajst-7782	108	2	review	review	NOUN
ajst-7782	108	3	on	on	ADP
ajst-7782	108	4	spectroscopic	spectroscopic	ADJ
ajst-7782	108	5	methods	method	NOUN
ajst-7782	108	6	for	for	ADP
ajst-7782	108	7	determination	determination	NOUN
ajst-7782	108	8	of	of	ADP
ajst-7782	108	9	nitrite	nitrite	NOUN
ajst-7782	108	10	and	and	CCONJ
ajst-7782	108	11	nitrate	nitrate	NOUN
ajst-7782	108	12	in	in	ADP
ajst-7782	108	13	environmental	environmental	ADJ
ajst-7782	108	14	samples[j	samples[j	PROPN
ajst-7782	108	15	]	]	PUNCT
ajst-7782	108	16	.	.	PUNCT
ajst-7782	109	1	talanta	talanta	PROPN
ajst-7782	109	2	,	,	PUNCT
ajst-7782	109	3	2019	2019	NUM
ajst-7782	109	4	,	,	PUNCT
ajst-7782	109	5	4(11	4(11	NUM
ajst-7782	109	6	):	):	PUNCT
ajst-7782	109	7	364	364	NUM
ajst-7782	109	8	-	-	SYM
ajst-7782	109	9	381	381	NUM
ajst-7782	109	10	.	.	PUNCT
ajst-7782	110	1	[	[	X
ajst-7782	110	2	5	5	X
ajst-7782	110	3	]	]	PUNCT
ajst-7782	110	4	wang	wang	PROPN
ajst-7782	110	5	j	j	PROPN
ajst-7782	110	6	,	,	PUNCT
ajst-7782	110	7	zhang	zhang	PROPN
ajst-7782	110	8	j	j	PROPN
ajst-7782	110	9	,	,	PUNCT
ajst-7782	110	10	zhang	zhang	PROPN
ajst-7782	110	11	z.	z.	PROPN
ajst-7782	110	12	rapid	rapid	ADJ
ajst-7782	110	13	determination	determination	NOUN
ajst-7782	110	14	of	of	ADP
ajst-7782	110	15	nitrate	nitrate	NOUN
ajst-7782	110	16	nitrogen	nitrogen	NOUN
ajst-7782	110	17	and	and	CCONJ
ajst-7782	110	18	nitrite	nitrite	NOUN
ajst-7782	110	19	nitrogen	nitrogen	NOUN
ajst-7782	110	20	by	by	ADP
ajst-7782	110	21	second	second	ADJ
ajst-7782	110	22	derivative	derivative	ADJ
ajst-7782	110	23	spectrophotometry[j	spectrophotometry[j	NOUN
ajst-7782	110	24	]	]	PUNCT
ajst-7782	110	25	.	.	PUNCT
ajst-7782	111	1	spectroscopy	spectroscopy	NOUN
ajst-7782	111	2	and	and	CCONJ
ajst-7782	111	3	spectral	spectral	ADJ
ajst-7782	111	4	analysis	analysis	NOUN
ajst-7782	111	5	,	,	PUNCT
ajst-7782	111	6	2019	2019	NUM
ajst-7782	111	7	,	,	PUNCT
ajst-7782	111	8	39(1	39(1	NUM
ajst-7782	111	9	):	):	PUNCT
ajst-7782	111	10	161	161	NUM
ajst-7782	111	11	-	-	SYM
ajst-7782	111	12	165	165	NUM
ajst-7782	111	13	.	.	PUNCT
ajst-7782	112	1	[	[	X
ajst-7782	112	2	6	6	NUM
ajst-7782	112	3	]	]	X
ajst-7782	112	4	li	li	PROPN
ajst-7782	113	1	q	q	PROPN
ajst-7782	113	2	,	,	PUNCT
ajst-7782	113	3	he	he	PRON
ajst-7782	113	4	l	l	NOUN
ajst-7782	113	5	,	,	PUNCT
ajst-7782	113	6	cui	cui	PROPN
ajst-7782	113	7	h	h	PROPN
ajst-7782	113	8	,	,	PUNCT
ajst-7782	113	9	et	et	PROPN
ajst-7782	113	10	al	al	PROPN
ajst-7782	113	11	.	.	PROPN
ajst-7782	113	12	basic	basic	ADJ
ajst-7782	113	13	research	research	NOUN
ajst-7782	113	14	on	on	ADP
ajst-7782	113	15	ultraviolet	ultraviolet	ADJ
ajst-7782	113	16	visible	visible	ADJ
ajst-7782	113	17	spectral	spectral	ADJ
ajst-7782	113	18	detection	detection	NOUN
ajst-7782	113	19	method	method	NOUN
ajst-7782	113	20	for	for	ADP
ajst-7782	113	21	nitrite	nitrite	NOUN
ajst-7782	113	22	nitrogen	nitrogen	NOUN
ajst-7782	113	23	concentration	concentration	NOUN
ajst-7782	113	24	in	in	ADP
ajst-7782	113	25	surface	surface	NOUN
ajst-7782	113	26	water	water	NOUN
ajst-7782	114	1	[	[	X
ajst-7782	114	2	j	j	X
ajst-7782	114	3	]	]	X
ajst-7782	114	4	.	.	PUNCT
ajst-7782	115	1	spectroscopy	spectroscopy	NOUN
ajst-7782	115	2	and	and	CCONJ
ajst-7782	115	3	spectral	spectral	ADJ
ajst-7782	115	4	analysis	analysis	NOUN
ajst-7782	115	5	2020	2020	NUM
ajst-7782	115	6	,	,	PUNCT
ajst-7782	115	7	40(04	40(04	NUM
ajst-7782	115	8	):	):	PUNCT
ajst-7782	115	9	1127	1127	NUM
ajst-7782	115	10	-	-	SYM
ajst-7782	115	11	1131	1131	NUM
ajst-7782	115	12	.	.	PUNCT
ajst-7782	116	1	[	[	X
ajst-7782	116	2	7	7	NUM
ajst-7782	116	3	]	]	X
ajst-7782	116	4	uusheimo	uusheimo	PROPN
ajst-7782	116	5	s	s	PROPN
ajst-7782	116	6	,	,	PUNCT
ajst-7782	116	7	tulonen	tulonen	PROPN
ajst-7782	116	8	t	t	PROPN
ajst-7782	116	9	,	,	PUNCT
ajst-7782	116	10	arvo	arvo	PROPN
ajst-7782	116	11	-	-	PUNCT
ajst-7782	116	12	la	la	X
ajst-7782	116	13	l	l	NOUN
ajst-7782	116	14	,	,	PUNCT
ajst-7782	116	15	et	et	PROPN
ajst-7782	116	16	al	al	PROPN
ajst-7782	116	17	.	.	PUNCT
ajst-7782	117	1	organic	organic	ADJ
ajst-7782	117	2	carbon	carbon	NOUN
ajst-7782	117	3	causes	cause	VERB
ajst-7782	117	4	interference	interference	NOUN
ajst-7782	117	5	with	with	ADP
ajst-7782	117	6	nitrate	nitrate	NOUN
ajst-7782	117	7	and	and	CCONJ
ajst-7782	117	8	nitrite	nitrite	NOUN
ajst-7782	117	9	measurements	measurement	NOUN
ajst-7782	117	10	by	by	ADP
ajst-7782	117	11	uv	uv	NOUN
ajst-7782	117	12	/	/	SYM
ajst-7782	117	13	vis	vis	X
ajst-7782	117	14	spectrometers	spectrometer	NOUN
ajst-7782	117	15	:	:	PUNCT
ajst-7782	117	16	the	the	DET
ajst-7782	117	17	importance	importance	NOUN
ajst-7782	117	18	of	of	ADP
ajst-7782	117	19	local	local	ADJ
ajst-7782	117	20	calibration[j	calibration[j	PROPN
ajst-7782	117	21	]	]	PUNCT
ajst-7782	117	22	.	.	PUNCT
ajst-7782	118	1	environmental	environmental	ADJ
ajst-7782	118	2	monitoring	monitoring	NOUN
ajst-7782	118	3	and	and	CCONJ
ajst-7782	118	4	assessment	assessment	NOUN
ajst-7782	118	5	,	,	PUNCT
ajst-7782	118	6	2017	2017	NUM
ajst-7782	118	7	,	,	PUNCT
ajst-7782	118	8	189(7	189(7	NUM
ajst-7782	118	9	):	):	PUNCT
ajst-7782	118	10	357	357	NUM
ajst-7782	118	11	.	.	PUNCT
ajst-7782	119	1	[	[	X
ajst-7782	119	2	8	8	NUM
ajst-7782	119	3	]	]	PUNCT
ajst-7782	119	4	tharwat	tharwat	ADJ
ajst-7782	119	5	a.	a.	NOUN
ajst-7782	119	6	parameter	parameter	PROPN
ajst-7782	119	7	investigation	investigation	NOUN
ajst-7782	119	8	of	of	ADP
ajst-7782	119	9	support	support	NOUN
ajst-7782	119	10	vector	vector	NOUN
ajst-7782	119	11	machine	machine	NOUN
ajst-7782	119	12	classifier	classifier	NOUN
ajst-7782	119	13	with	with	ADP
ajst-7782	119	14	kernel	kernel	PROPN
ajst-7782	119	15	functions[j	functions[j	PROPN
ajst-7782	119	16	]	]	PUNCT
ajst-7782	119	17	.	.	PUNCT
ajst-7782	120	1	knowledge	knowledge	NOUN
ajst-7782	120	2	and	and	CCONJ
ajst-7782	120	3	information	information	NOUN
ajst-7782	120	4	systems	system	NOUN
ajst-7782	120	5	,	,	PUNCT
ajst-7782	120	6	2019	2019	NUM
ajst-7782	120	7	,	,	PUNCT
ajst-7782	120	8	61(3	61(3	NUM
ajst-7782	120	9	):	):	PUNCT
ajst-7782	120	10	1269	1269	NUM
ajst-7782	120	11	-	-	SYM
ajst-7782	120	12	1302	1302	NUM
ajst-7782	120	13	.	.	PUNCT
ajst-7782	121	1	[	[	X
ajst-7782	121	2	9	9	NUM
ajst-7782	121	3	]	]	X
ajst-7782	121	4	kang	kang	PROPN
ajst-7782	121	5	w.	w.	PROPN
ajst-7782	121	6	research	research	PROPN
ajst-7782	121	7	on	on	ADP
ajst-7782	121	8	the	the	DET
ajst-7782	121	9	detection	detection	NOUN
ajst-7782	121	10	of	of	ADP
ajst-7782	121	11	pollutants	pollutant	NOUN
ajst-7782	121	12	in	in	ADP
ajst-7782	121	13	water	water	NOUN
ajst-7782	121	14	based	base	VERB
ajst-7782	121	15	on	on	ADP
ajst-7782	121	16	sers	ser	NOUN
ajst-7782	121	17	technology	technology	PROPN
ajst-7782	121	18	and	and	CCONJ
ajst-7782	121	19	gwo	gwo	PROPN
ajst-7782	121	20	-	-	ADJ
ajst-7782	121	21	svr	svr	PROPN
ajst-7782	121	22	algorithm	algorithm	NOUN
ajst-7782	121	23	[	[	X
ajst-7782	121	24	d	d	X
ajst-7782	121	25	]	]	X
ajst-7782	121	26	hebei	hebei	PROPN
ajst-7782	121	27	:	:	PUNCT
ajst-7782	121	28	yanshan	yanshan	PROPN
ajst-7782	121	29	university	university	NOUN
ajst-7782	121	30	,	,	PUNCT
ajst-7782	121	31	2021	2021	NUM
ajst-7782	121	32	.	.	PUNCT
ajst-7782	122	1	[	[	X
ajst-7782	122	2	10	10	NUM
ajst-7782	122	3	]	]	X
ajst-7782	122	4	zheng	zheng	PROPN
ajst-7782	122	5	h	h	PROPN
ajst-7782	122	6	,	,	PUNCT
ajst-7782	122	7	yan	yan	PROPN
ajst-7782	123	1	z	z	PROPN
ajst-7782	123	2	,	,	PUNCT
ajst-7782	123	3	chen	chen	PROPN
ajst-7782	123	4	j	j	PROPN
ajst-7782	123	5	,	,	PUNCT
ajst-7782	123	6	et	et	PROPN
ajst-7782	123	7	al	al	PROPN
ajst-7782	123	8	.	.	PUNCT
ajst-7782	124	1	seasonal	seasonal	ADJ
ajst-7782	124	2	variations	variation	NOUN
ajst-7782	124	3	of	of	ADP
ajst-7782	124	4	dissolved	dissolve	VERB
ajst-7782	124	5	organic	organic	ADJ
ajst-7782	124	6	matter	matter	NOUN
ajst-7782	124	7	in	in	ADP
ajst-7782	124	8	the	the	DET
ajst-7782	124	9	east	east	PROPN
ajst-7782	124	10	china	china	PROPN
ajst-7782	124	11	sea	sea	PROPN
ajst-7782	124	12	using	use	VERB
ajst-7782	124	13	eemparafac	eemparafac	NOUN
ajst-7782	124	14	and	and	CCONJ
ajst-7782	124	15	implications	implication	NOUN
ajst-7782	124	16	for	for	ADP
ajst-7782	124	17	carbon	carbon	NOUN
ajst-7782	124	18	and	and	CCONJ
ajst-7782	124	19	nutrient	nutrient	NOUN
ajst-7782	124	20	cycling[j	cycling[j	NOUN
ajst-7782	124	21	]	]	PUNCT
ajst-7782	124	22	.	.	PUNCT
ajst-7782	125	1	sustainability	sustainability	NOUN
ajst-7782	125	2	,	,	PUNCT
ajst-7782	125	3	2018	2018	NUM
ajst-7782	125	4	,	,	PUNCT
ajst-7782	125	5	10(5	10(5	NUM
ajst-7782	125	6	):	):	PUNCT
ajst-7782	125	7	1444	1444	NUM
ajst-7782	125	8	.	.	PUNCT