id	sid	tid	token	lemma	pos
ajst-2551	1	1	academic	academic	ADJ
ajst-2551	1	2	journal	journal	NOUN
ajst-2551	1	3	of	of	ADP
ajst-2551	1	4	science	science	NOUN
ajst-2551	1	5	and	and	CCONJ
ajst-2551	1	6	technology	technology	NOUN
ajst-2551	1	7	issn	issn	NOUN
ajst-2551	1	8	:	:	PUNCT
ajst-2551	1	9	2771	2771	NUM
ajst-2551	1	10	-	-	SYM
ajst-2551	1	11	3032	3032	NUM
ajst-2551	1	12	|	|	NOUN
ajst-2551	1	13	vol	vol	NOUN
ajst-2551	1	14	.	.	PROPN
ajst-2551	2	1	3	3	NUM
ajst-2551	2	2	,	,	PUNCT
ajst-2551	2	3	no	no	INTJ
ajst-2551	2	4	.	.	NOUN
ajst-2551	2	5	3	3	NUM
ajst-2551	2	6	,	,	PUNCT
ajst-2551	2	7	2022	2022	NUM
ajst-2551	2	8	70	70	NUM
ajst-2551	2	9	research	research	NOUN
ajst-2551	2	10	on	on	ADP
ajst-2551	2	11	clustering	clustering	ADJ
ajst-2551	2	12	methods	method	NOUN
ajst-2551	2	13	for	for	ADP
ajst-2551	2	14	color	color	NOUN
ajst-2551	2	15	image	image	NOUN
ajst-2551	2	16	segmentation	segmentation	NOUN
ajst-2551	2	17	qingzhen	qingzhen	PROPN
ajst-2551	2	18	gong1	gong1	PROPN
ajst-2551	2	19	,	,	PUNCT
ajst-2551	2	20	2	2	NUM
ajst-2551	2	21	,	,	PUNCT
ajst-2551	2	22	*	*	PUNCT
ajst-2551	2	23	1	1	NUM
ajst-2551	2	24	school	school	NOUN
ajst-2551	2	25	of	of	ADP
ajst-2551	2	26	physics	physics	NOUN
ajst-2551	2	27	and	and	CCONJ
ajst-2551	2	28	electronic	electronic	ADJ
ajst-2551	2	29	information	information	NOUN
ajst-2551	2	30	engineering	engineering	NOUN
ajst-2551	2	31	,	,	PUNCT
ajst-2551	2	32	jining	jine	VERB
ajst-2551	2	33	normal	normal	ADJ
ajst-2551	2	34	university	university	NOUN
ajst-2551	2	35	,	,	PUNCT
ajst-2551	2	36	ulanqab	ulanqab	ADJ
ajst-2551	2	37	city	city	NOUN
ajst-2551	2	38	,	,	PUNCT
ajst-2551	2	39	inner	inner	PROPN
ajst-2551	2	40	mongolia	mongolia	PROPN
ajst-2551	2	41	,	,	PUNCT
ajst-2551	2	42	012000	012000	NUM
ajst-2551	2	43	,	,	PUNCT
ajst-2551	2	44	china	china	PROPN
ajst-2551	2	45	2	2	NUM
ajst-2551	2	46	center	center	NOUN
ajst-2551	2	47	for	for	ADP
ajst-2551	2	48	international	international	ADJ
ajst-2551	2	49	education	education	NOUN
ajst-2551	2	50	,	,	PUNCT
ajst-2551	2	51	philippine	philippine	ADJ
ajst-2551	2	52	christian	christian	PROPN
ajst-2551	2	53	university	university	PROPN
ajst-2551	2	54	,	,	PUNCT
ajst-2551	2	55	manila	manila	PROPN
ajst-2551	2	56	city	city	PROPN
ajst-2551	2	57	,	,	PUNCT
ajst-2551	2	58	1004	1004	NUM
ajst-2551	2	59	metro	metro	PROPN
ajst-2551	2	60	manila	manila	PROPN
ajst-2551	2	61	,	,	PUNCT
ajst-2551	2	62	philippines	philippine	NOUN
ajst-2551	2	63	*	*	PUNCT
ajst-2551	2	64	corresponding	correspond	VERB
ajst-2551	2	65	email	email	NOUN
ajst-2551	2	66	:	:	PUNCT
ajst-2551	2	67	xunuo1314_2012@163.com	xunuo1314_2012@163.com	X
ajst-2551	3	1	abstract	abstract	NOUN
ajst-2551	3	2	:	:	PUNCT
ajst-2551	3	3	the	the	DET
ajst-2551	3	4	research	research	NOUN
ajst-2551	3	5	of	of	ADP
ajst-2551	3	6	image	image	NOUN
ajst-2551	3	7	segmentation	segmentation	NOUN
ajst-2551	3	8	mainly	mainly	ADV
ajst-2551	3	9	includes	include	VERB
ajst-2551	3	10	:	:	PUNCT
ajst-2551	3	11	how	how	SCONJ
ajst-2551	3	12	to	to	PART
ajst-2551	3	13	select	select	VERB
ajst-2551	3	14	the	the	DET
ajst-2551	3	15	appropriate	appropriate	ADJ
ajst-2551	3	16	color	color	NOUN
ajst-2551	3	17	space	space	NOUN
ajst-2551	3	18	,	,	PUNCT
ajst-2551	3	19	reduce	reduce	VERB
ajst-2551	3	20	the	the	DET
ajst-2551	3	21	complexity	complexity	NOUN
ajst-2551	3	22	of	of	ADP
ajst-2551	3	23	segmentation	segmentation	NOUN
ajst-2551	3	24	algorithm	algorithm	NOUN
ajst-2551	3	25	,	,	PUNCT
ajst-2551	3	26	improve	improve	VERB
ajst-2551	3	27	the	the	DET
ajst-2551	3	28	noise	noise	NOUN
ajst-2551	3	29	resistance	resistance	NOUN
ajst-2551	3	30	and	and	CCONJ
ajst-2551	3	31	universality	universality	NOUN
ajst-2551	3	32	of	of	ADP
ajst-2551	3	33	segmentation	segmentation	NOUN
ajst-2551	3	34	algorithm	algorithm	NOUN
ajst-2551	3	35	,	,	PUNCT
ajst-2551	3	36	etc	etc	X
ajst-2551	3	37	.	.	X
ajst-2551	3	38	fuzzy	fuzzy	ADJ
ajst-2551	3	39	clustering	clustering	NOUN
ajst-2551	3	40	is	be	AUX
ajst-2551	3	41	an	an	DET
ajst-2551	3	42	unsupervised	unsupervised	ADJ
ajst-2551	3	43	classification	classification	NOUN
ajst-2551	3	44	method	method	NOUN
ajst-2551	3	45	,	,	PUNCT
ajst-2551	3	46	which	which	PRON
ajst-2551	3	47	can	can	AUX
ajst-2551	3	48	classify	classify	VERB
ajst-2551	3	49	samples	sample	NOUN
ajst-2551	3	50	with	with	ADP
ajst-2551	3	51	similar	similar	ADJ
ajst-2551	3	52	properties	property	NOUN
ajst-2551	3	53	without	without	ADP
ajst-2551	3	54	prior	prior	ADJ
ajst-2551	3	55	knowledge	knowledge	NOUN
ajst-2551	3	56	.	.	PUNCT
ajst-2551	4	1	this	this	DET
ajst-2551	4	2	paper	paper	NOUN
ajst-2551	4	3	briefly	briefly	NOUN
ajst-2551	4	4	describes	describe	VERB
ajst-2551	4	5	the	the	DET
ajst-2551	4	6	working	working	NOUN
ajst-2551	4	7	principle	principle	NOUN
ajst-2551	4	8	and	and	CCONJ
ajst-2551	4	9	performance	performance	NOUN
ajst-2551	4	10	comparison	comparison	NOUN
ajst-2551	4	11	of	of	ADP
ajst-2551	4	12	these	these	DET
ajst-2551	4	13	algorithms	algorithm	NOUN
ajst-2551	4	14	.	.	PUNCT
ajst-2551	5	1	keywords	keyword	NOUN
ajst-2551	5	2	:	:	PUNCT
ajst-2551	5	3	color	color	NOUN
ajst-2551	5	4	image	image	NOUN
ajst-2551	5	5	segmentation	segmentation	NOUN
ajst-2551	5	6	,	,	PUNCT
ajst-2551	5	7	fuzzy	fuzzy	ADJ
ajst-2551	5	8	clustering	clustering	NOUN
ajst-2551	5	9	,	,	PUNCT
ajst-2551	5	10	fuzzy	fuzzy	ADJ
ajst-2551	5	11	c	c	NOUN
ajst-2551	5	12	-	-	PUNCT
ajst-2551	5	13	means	mean	NOUN
ajst-2551	5	14	,	,	PUNCT
ajst-2551	5	15	k	k	NOUN
ajst-2551	5	16	-	-	PUNCT
ajst-2551	5	17	means	means	NOUN
ajst-2551	5	18	.	.	PUNCT
ajst-2551	6	1	1	1	X
ajst-2551	6	2	.	.	X
ajst-2551	6	3	introduction	introduction	NOUN
ajst-2551	6	4	on	on	ADP
ajst-2551	6	5	clustering	clustering	NOUN
ajst-2551	6	6	and	and	CCONJ
ajst-2551	6	7	segmentation	segmentation	NOUN
ajst-2551	6	8	is	be	AUX
ajst-2551	6	9	a	a	DET
ajst-2551	6	10	basic	basic	ADJ
ajst-2551	6	11	step	step	NOUN
ajst-2551	6	12	of	of	ADP
ajst-2551	6	13	image	image	NOUN
ajst-2551	6	14	processing	processing	NOUN
ajst-2551	6	15	.	.	PUNCT
ajst-2551	7	1	the	the	DET
ajst-2551	7	2	purpose	purpose	NOUN
ajst-2551	7	3	of	of	ADP
ajst-2551	7	4	this	this	DET
ajst-2551	7	5	operation	operation	NOUN
ajst-2551	7	6	is	be	AUX
ajst-2551	7	7	to	to	PART
ajst-2551	7	8	separate	separate	VERB
ajst-2551	7	9	different	different	ADJ
ajst-2551	7	10	homogeneous	homogeneous	ADJ
ajst-2551	7	11	areas	area	NOUN
ajst-2551	7	12	in	in	ADP
ajst-2551	7	13	the	the	DET
ajst-2551	7	14	image	image	NOUN
ajst-2551	7	15	,	,	PUNCT
ajst-2551	7	16	so	so	SCONJ
ajst-2551	7	17	as	as	SCONJ
ajst-2551	7	18	to	to	PART
ajst-2551	7	19	organize	organize	VERB
ajst-2551	7	20	objects	object	NOUN
ajst-2551	7	21	into	into	ADP
ajst-2551	7	22	groups	group	NOUN
ajst-2551	7	23	(	(	PUNCT
ajst-2551	7	24	clusters	cluster	NOUN
ajst-2551	7	25	)	)	PUNCT
ajst-2551	7	26	whose	whose	DET
ajst-2551	7	27	members	member	NOUN
ajst-2551	7	28	have	have	VERB
ajst-2551	7	29	different	different	ADJ
ajst-2551	7	30	common	common	ADJ
ajst-2551	7	31	attributes	attribute	NOUN
ajst-2551	7	32	(	(	PUNCT
ajst-2551	7	33	intensity	intensity	NOUN
ajst-2551	7	34	,	,	PUNCT
ajst-2551	7	35	color	color	NOUN
ajst-2551	7	36	,	,	PUNCT
ajst-2551	7	37	texture	texture	NOUN
ajst-2551	7	38	,	,	PUNCT
ajst-2551	7	39	etc	etc	X
ajst-2551	7	40	.	.	X
ajst-2551	7	41	)	)	PUNCT
ajst-2551	7	42	.	.	PUNCT
ajst-2551	8	1	segmentation	segmentation	NOUN
ajst-2551	8	2	methods	method	NOUN
ajst-2551	8	3	can	can	AUX
ajst-2551	8	4	be	be	AUX
ajst-2551	8	5	divided	divide	VERB
ajst-2551	8	6	into	into	ADP
ajst-2551	8	7	two	two	NUM
ajst-2551	8	8	categories	category	NOUN
ajst-2551	8	9	:	:	PUNCT
ajst-2551	8	10	fuzzy	fuzzy	ADJ
ajst-2551	8	11	c	c	NOUN
ajst-2551	8	12	-	-	PUNCT
ajst-2551	8	13	means	mean	NOUN
ajst-2551	8	14	and	and	CCONJ
ajst-2551	8	15	k	k	NOUN
ajst-2551	8	16	-	-	PUNCT
ajst-2551	8	17	means	mean	NOUN
ajst-2551	8	18	.	.	PUNCT
ajst-2551	9	1	firstly	firstly	ADV
ajst-2551	9	2	,	,	PUNCT
ajst-2551	9	3	the	the	DET
ajst-2551	9	4	algorithms	algorithm	NOUN
ajst-2551	9	5	of	of	ADP
ajst-2551	9	6	these	these	DET
ajst-2551	9	7	two	two	NUM
ajst-2551	9	8	methods	method	NOUN
ajst-2551	9	9	and	and	CCONJ
ajst-2551	9	10	their	their	PRON
ajst-2551	9	11	characteristics	characteristic	NOUN
ajst-2551	9	12	are	be	AUX
ajst-2551	9	13	introduced	introduce	VERB
ajst-2551	9	14	.	.	PUNCT
ajst-2551	10	1	secondly	secondly	ADV
ajst-2551	10	2	,	,	PUNCT
ajst-2551	10	3	the	the	DET
ajst-2551	10	4	difficulties	difficulty	NOUN
ajst-2551	10	5	and	and	CCONJ
ajst-2551	10	6	defects	defect	NOUN
ajst-2551	10	7	of	of	ADP
ajst-2551	10	8	fuzzy	fuzzy	ADJ
ajst-2551	10	9	c	c	NOUN
ajst-2551	10	10	-	-	PUNCT
ajst-2551	10	11	means	means	NOUN
ajst-2551	10	12	algorithm	algorithm	NOUN
ajst-2551	10	13	in	in	ADP
ajst-2551	10	14	image	image	NOUN
ajst-2551	10	15	segmentation	segmentation	NOUN
ajst-2551	10	16	are	be	AUX
ajst-2551	10	17	analyzed	analyze	VERB
ajst-2551	10	18	.	.	PUNCT
ajst-2551	11	1	finally	finally	ADV
ajst-2551	11	2	,	,	PUNCT
ajst-2551	11	3	we	we	PRON
ajst-2551	11	4	will	will	AUX
ajst-2551	11	5	implement	implement	VERB
ajst-2551	11	6	these	these	DET
ajst-2551	11	7	two	two	NUM
ajst-2551	11	8	algorithms	algorithm	NOUN
ajst-2551	11	9	through	through	ADP
ajst-2551	11	10	a	a	DET
ajst-2551	11	11	series	series	NOUN
ajst-2551	11	12	of	of	ADP
ajst-2551	11	13	examples	example	NOUN
ajst-2551	11	14	of	of	ADP
ajst-2551	11	15	testing	testing	NOUN
ajst-2551	11	16	functions	function	NOUN
ajst-2551	11	17	realized	realize	VERB
ajst-2551	11	18	by	by	ADP
ajst-2551	11	19	matlab	matlab	PROPN
ajst-2551	11	20	.	.	PROPN
ajst-2551	12	1	2	2	NUM
ajst-2551	12	2	.	.	X
ajst-2551	12	3	algorithm	algorithm	NOUN
ajst-2551	12	4	description	description	NOUN
ajst-2551	12	5	fuzzy	fuzzy	ADJ
ajst-2551	12	6	c	c	NOUN
ajst-2551	12	7	-	-	PUNCT
ajst-2551	12	8	means	means	NOUN
ajst-2551	12	9	is	be	AUX
ajst-2551	12	10	the	the	DET
ajst-2551	12	11	most	most	ADV
ajst-2551	12	12	commonly	commonly	ADV
ajst-2551	12	13	used	use	VERB
ajst-2551	12	14	image	image	NOUN
ajst-2551	12	15	segmentation	segmentation	NOUN
ajst-2551	12	16	method	method	NOUN
ajst-2551	12	17	based	base	VERB
ajst-2551	12	18	on	on	ADP
ajst-2551	12	19	fuzzy	fuzzy	ADJ
ajst-2551	12	20	theory	theory	NOUN
ajst-2551	12	21	and	and	CCONJ
ajst-2551	12	22	cluster	cluster	NOUN
ajst-2551	12	23	analysis	analysis	NOUN
ajst-2551	12	24	.	.	PUNCT
ajst-2551	13	1	it	it	PRON
ajst-2551	13	2	is	be	AUX
ajst-2551	13	3	a	a	DET
ajst-2551	13	4	clustering	cluster	VERB
ajst-2551	13	5	method	method	NOUN
ajst-2551	13	6	based	base	VERB
ajst-2551	13	7	on	on	ADP
ajst-2551	13	8	the	the	DET
ajst-2551	13	9	idea	idea	NOUN
ajst-2551	13	10	of	of	ADP
ajst-2551	13	11	partition	partition	NOUN
ajst-2551	13	12	,	,	PUNCT
ajst-2551	13	13	which	which	PRON
ajst-2551	13	14	makes	make	VERB
ajst-2551	13	15	the	the	DET
ajst-2551	13	16	samples	sample	NOUN
ajst-2551	13	17	belonging	belong	VERB
ajst-2551	13	18	to	to	ADP
ajst-2551	13	19	the	the	DET
ajst-2551	13	20	same	same	ADJ
ajst-2551	13	21	area	area	NOUN
ajst-2551	13	22	have	have	VERB
ajst-2551	13	23	the	the	DET
ajst-2551	13	24	greatest	great	ADJ
ajst-2551	13	25	similarity	similarity	NOUN
ajst-2551	13	26	through	through	ADP
ajst-2551	13	27	partition	partition	NOUN
ajst-2551	13	28	,	,	PUNCT
ajst-2551	13	29	while	while	SCONJ
ajst-2551	13	30	the	the	DET
ajst-2551	13	31	samples	sample	NOUN
ajst-2551	13	32	divided	divide	VERB
ajst-2551	13	33	into	into	ADP
ajst-2551	13	34	different	different	ADJ
ajst-2551	13	35	areas	area	NOUN
ajst-2551	13	36	are	be	AUX
ajst-2551	13	37	the	the	DET
ajst-2551	13	38	ones	one	NOUN
ajst-2551	13	39	with	with	ADP
ajst-2551	13	40	the	the	DET
ajst-2551	13	41	smallest	small	ADJ
ajst-2551	13	42	similarity	similarity	NOUN
ajst-2551	13	43	.	.	PUNCT
ajst-2551	14	1	2.1	2.1	NUM
ajst-2551	14	2	.	.	PUNCT
ajst-2551	15	1	k	k	X
ajst-2551	15	2	-	-	PUNCT
ajst-2551	15	3	means	means	NOUN
ajst-2551	15	4	means	mean	VERB
ajst-2551	15	5	algorithm	algorithm	NOUN
ajst-2551	15	6	is	be	AUX
ajst-2551	15	7	fuzzy	fuzzy	ADJ
ajst-2551	15	8	c	c	NOUN
ajst-2551	15	9	-	-	PUNCT
ajst-2551	15	10	means	mean	NOUN
ajst-2551	15	11	.	.	PUNCT
ajst-2551	16	1	the	the	DET
ajst-2551	16	2	main	main	ADJ
ajst-2551	16	3	idea	idea	NOUN
ajst-2551	16	4	of	of	ADP
ajst-2551	16	5	this	this	DET
ajst-2551	16	6	algorithm	algorithm	NOUN
ajst-2551	16	7	is	be	AUX
ajst-2551	16	8	to	to	PART
ajst-2551	16	9	divide	divide	VERB
ajst-2551	16	10	n	n	PRON
ajst-2551	16	11	samples	sample	NOUN
ajst-2551	16	12	xj(1,2	xj(1,2	ADJ
ajst-2551	16	13	...	...	PUNCT
ajst-2551	16	14	,n	,n	NOUN
ajst-2551	16	15	)	)	PUNCT
ajst-2551	16	16	into	into	ADP
ajst-2551	16	17	c	c	NOUN
ajst-2551	16	18	groups	group	NOUN
ajst-2551	16	19	gi(i=1,2	gi(i=1,2	NOUN
ajst-2551	16	20	...	...	PUNCT
ajst-2551	16	21	,c	,c	NUM
ajst-2551	16	22	)	)	PUNCT
ajst-2551	16	23	,	,	PUNCT
ajst-2551	16	24	so	so	SCONJ
ajst-2551	16	25	as	as	SCONJ
ajst-2551	16	26	to	to	PART
ajst-2551	16	27	minimize	minimize	VERB
ajst-2551	16	28	the	the	DET
ajst-2551	16	29	objective	objective	ADJ
ajst-2551	16	30	function	function	NOUN
ajst-2551	16	31	and	and	CCONJ
ajst-2551	16	32	obtain	obtain	VERB
ajst-2551	16	33	the	the	DET
ajst-2551	16	34	cluster	cluster	NOUN
ajst-2551	16	35	center	center	NOUN
ajst-2551	16	36	ci	ci	NOUN
ajst-2551	16	37	of	of	ADP
ajst-2551	16	38	each	each	DET
ajst-2551	16	39	group	group	NOUN
ajst-2551	16	40	.	.	PUNCT
ajst-2551	17	1	usually	usually	ADV
ajst-2551	17	2	,	,	PUNCT
ajst-2551	17	3	the	the	DET
ajst-2551	17	4	function	function	NOUN
ajst-2551	17	5	d(xk	d(xk	PROPN
ajst-2551	17	6	,	,	PUNCT
ajst-2551	17	7	ci	ci	NOUN
ajst-2551	17	8	)	)	PUNCT
ajst-2551	17	9	is	be	AUX
ajst-2551	17	10	used	use	VERB
ajst-2551	17	11	to	to	PART
ajst-2551	17	12	represent	represent	VERB
ajst-2551	17	13	the	the	DET
ajst-2551	17	14	dissimilarity	dissimilarity	NOUN
ajst-2551	17	15	between	between	ADP
ajst-2551	17	16	samples	sample	NOUN
ajst-2551	17	17	,	,	PUNCT
ajst-2551	17	18	and	and	CCONJ
ajst-2551	17	19	the	the	DET
ajst-2551	17	20	objective	objective	ADJ
ajst-2551	17	21	function	function	NOUN
ajst-2551	17	22	is	be	AUX
ajst-2551	17	23	defined	define	VERB
ajst-2551	17	24	as	as	ADP
ajst-2551	17	25	:	:	PUNCT
ajst-2551	17	26			X
ajst-2551	18	1			ADV
ajst-2551	18	2			VERB
ajst-2551	18	3			X
ajst-2551	18	4			NUM
ajst-2551	18	5	c	c	PROPN
ajst-2551	19	1	i	i	PRON
ajst-2551	19	2	xk	xk	INTJ
ajst-2551	20	1	c	c	VERB
ajst-2551	20	2	i	i	PRON
ajst-2551	20	3	k	k	PROPN
ajst-2551	20	4	ik	ik	X
ajst-2551	20	5	cxdjij	cxdjij	VERB
ajst-2551	20	6	1	1	NUM
ajst-2551	20	7	g,1	g,1	NUM
ajst-2551	20	8	)	)	PUNCT
ajst-2551	20	9	)	)	PUNCT
ajst-2551	21	1	(	(	PUNCT
ajst-2551	21	2	(	(	PUNCT
ajst-2551	21	3	i	i	PRON
ajst-2551	21	4	(	(	PUNCT
ajst-2551	21	5	1	1	NUM
ajst-2551	21	6	)	)	PUNCT
ajst-2551	21	7	when	when	SCONJ
ajst-2551	21	8	the	the	DET
ajst-2551	21	9	value	value	NOUN
ajst-2551	21	10	of	of	ADP
ajst-2551	21	11	the	the	DET
ajst-2551	21	12	function	function	NOUN
ajst-2551	21	13	d(xk	d(xk	PROPN
ajst-2551	21	14	,	,	PUNCT
ajst-2551	21	15	ci	ci	NOUN
ajst-2551	21	16	)	)	PUNCT
ajst-2551	21	17	is	be	AUX
ajst-2551	21	18	the	the	DET
ajst-2551	21	19	euclidean	euclidean	ADJ
ajst-2551	21	20	distance	distance	NOUN
ajst-2551	21	21	between	between	ADP
ajst-2551	21	22	the	the	DET
ajst-2551	21	23	sample	sample	NOUN
ajst-2551	21	24	xk	xk	PROPN
ajst-2551	21	25	in	in	ADP
ajst-2551	21	26	group	group	PROPN
ajst-2551	21	27	i	i	PROPN
ajst-2551	21	28	and	and	CCONJ
ajst-2551	21	29	the	the	DET
ajst-2551	21	30	cluster	cluster	NOUN
ajst-2551	21	31	center	center	NOUN
ajst-2551	21	32	ci	ci	NOUN
ajst-2551	21	33	of	of	ADP
ajst-2551	21	34	the	the	DET
ajst-2551	21	35	category	category	NOUN
ajst-2551	21	36	to	to	PART
ajst-2551	21	37	which	which	PRON
ajst-2551	21	38	it	it	PRON
ajst-2551	21	39	belongs	belong	VERB
ajst-2551	21	40	,	,	PUNCT
ajst-2551	21	41	the	the	DET
ajst-2551	21	42	objective	objective	ADJ
ajst-2551	21	43	function	function	NOUN
ajst-2551	21	44	can	can	AUX
ajst-2551	21	45	be	be	AUX
ajst-2551	21	46	expressed	express	VERB
ajst-2551	21	47	as	as	ADP
ajst-2551	21	48	:	:	PUNCT
ajst-2551	21	49			X
ajst-2551	21	50			ADV
ajst-2551	21	51			VERB
ajst-2551	21	52			X
ajst-2551	21	53			NUM
ajst-2551	21	54	c	c	PROPN
ajst-2551	22	1	i	i	PRON
ajst-2551	22	2	xk	xk	INTJ
ajst-2551	23	1	c	c	VERB
ajst-2551	23	2	i	i	PRON
ajst-2551	23	3	k	k	PROPN
ajst-2551	23	4	ik	ik	PROPN
ajst-2551	23	5	cxjij	cxjij	NOUN
ajst-2551	23	6	1	1	NUM
ajst-2551	23	7	g	g	NOUN
ajst-2551	23	8	,	,	PUNCT
ajst-2551	23	9	2	2	NUM
ajst-2551	23	10	1	1	NUM
ajst-2551	23	11	i	i	NOUN
ajst-2551	23	12	)	)	PUNCT
ajst-2551	23	13	(	(	PUNCT
ajst-2551	23	14	(	(	PUNCT
ajst-2551	23	15	2	2	X
ajst-2551	23	16	)	)	PUNCT
ajst-2551	23	17	if	if	SCONJ
ajst-2551	23	18	ci	ci	PROPN
ajst-2551	23	19	is	be	AUX
ajst-2551	23	20	the	the	DET
ajst-2551	23	21	nearest	near	ADJ
ajst-2551	23	22	cluster	cluster	NOUN
ajst-2551	23	23	center	center	NOUN
ajst-2551	23	24	to	to	ADP
ajst-2551	23	25	the	the	DET
ajst-2551	23	26	sample	sample	NOUN
ajst-2551	23	27	xj	xj	PROPN
ajst-2551	23	28	,	,	PUNCT
ajst-2551	23	29	then	then	ADV
ajst-2551	23	30	xj	xj	PROPN
ajst-2551	23	31	belongs	belong	VERB
ajst-2551	23	32	to	to	ADP
ajst-2551	23	33	the	the	DET
ajst-2551	23	34	i	i	PROPN
ajst-2551	23	35	-	-	PUNCT
ajst-2551	23	36	th	th	PROPN
ajst-2551	23	37	group	group	NOUN
ajst-2551	23	38	.	.	PUNCT
ajst-2551	24	1	the	the	DET
ajst-2551	24	2	divided	divide	VERB
ajst-2551	24	3	group	group	NOUN
ajst-2551	24	4	can	can	AUX
ajst-2551	24	5	be	be	AUX
ajst-2551	24	6	represented	represent	VERB
ajst-2551	24	7	by	by	ADP
ajst-2551	24	8	a	a	DET
ajst-2551	24	9	c×n	c×n	PROPN
ajst-2551	24	10	two	two	NUM
ajst-2551	24	11	-	-	PUNCT
ajst-2551	24	12	dimensional	dimensional	ADJ
ajst-2551	24	13	membership	membership	NOUN
ajst-2551	24	14	matrix	matrix	NOUN
ajst-2551	24	15	u.	u.	VERB
ajst-2551	24	16	when	when	SCONJ
ajst-2551	24	17	the	the	DET
ajst-2551	24	18	sample	sample	NOUN
ajst-2551	24	19	xj	xj	PROPN
ajst-2551	24	20	belongs	belong	VERB
ajst-2551	24	21	to	to	ADP
ajst-2551	24	22	the	the	DET
ajst-2551	24	23	i	i	PROPN
ajst-2551	24	24	-	-	PUNCT
ajst-2551	24	25	th	th	PROPN
ajst-2551	24	26	group	group	NOUN
ajst-2551	24	27	,	,	PUNCT
ajst-2551	24	28	the	the	DET
ajst-2551	24	29	element	element	NOUN
ajst-2551	24	30	uij	uij	PRON
ajst-2551	24	31	in	in	ADP
ajst-2551	24	32	u	u	PROPN
ajst-2551	24	33	is	be	AUX
ajst-2551	24	34	1	1	NUM
ajst-2551	24	35	,	,	PUNCT
ajst-2551	24	36	otherwise	otherwise	ADV
ajst-2551	24	37	it	it	PRON
ajst-2551	24	38	takes	take	VERB
ajst-2551	24	39	0	0	NUM
ajst-2551	24	40	,	,	PUNCT
ajst-2551	24	41	which	which	PRON
ajst-2551	24	42	can	can	AUX
ajst-2551	24	43	make	make	VERB
ajst-2551	24	44	the	the	DET
ajst-2551	24	45	objective	objective	ADJ
ajst-2551	24	46	function	function	NOUN
ajst-2551	24	47	j	j	PROPN
ajst-2551	24	48	reach	reach	VERB
ajst-2551	24	49	the	the	DET
ajst-2551	24	50	minimum	minimum	ADJ
ajst-2551	24	51	value	value	NOUN
ajst-2551	24	52	.	.	PUNCT
ajst-2551	25	1	if	if	SCONJ
ajst-2551	25	2	the	the	DET
ajst-2551	25	3	cluster	cluster	NOUN
ajst-2551	25	4	center	center	NOUN
ajst-2551	25	5	ci	ci	PROPN
ajst-2551	25	6	is	be	AUX
ajst-2551	25	7	determined	determine	VERB
ajst-2551	25	8	,	,	PUNCT
ajst-2551	25	9	u	u	NOUN
ajst-2551	25	10	is	be	AUX
ajst-2551	25	11	determined	determine	VERB
ajst-2551	25	12	according	accord	VERB
ajst-2551	25	13	to	to	ADP
ajst-2551	25	14	the	the	DET
ajst-2551	25	15	following	follow	VERB
ajst-2551	25	16	formula	formula	NOUN
ajst-2551	25	17	:	:	PUNCT
ajst-2551	25	18			NOUN
ajst-2551	25	19			NOUN
ajst-2551	25	20			ADP
ajst-2551	26	1			NUM
ajst-2551	26	2	0	0	NUM
ajst-2551	26	3	1	1	NUM
ajst-2551	26	4	jiu	jiu	NOUN
ajst-2551	26	5	else	else	ADV
ajst-2551	26	6	cxcxik	cxcxik	PROPN
ajst-2551	26	7	kjij	kjij	PROPN
ajst-2551	26	8	22	22	NUM
ajst-2551	26	9	,	,	PUNCT
ajst-2551	26	10			ADJ
ajst-2551	26	11	(	(	PUNCT
ajst-2551	26	12	3	3	NUM
ajst-2551	26	13	)	)	PUNCT
ajst-2551	27	1	since	since	SCONJ
ajst-2551	27	2	each	each	DET
ajst-2551	27	3	sample	sample	NOUN
ajst-2551	27	4	can	can	AUX
ajst-2551	27	5	only	only	ADV
ajst-2551	27	6	belong	belong	VERB
ajst-2551	27	7	to	to	ADP
ajst-2551	27	8	one	one	NUM
ajst-2551	27	9	group	group	NOUN
ajst-2551	27	10	,	,	PUNCT
ajst-2551	27	11	uij	uij	PRON
ajst-2551	27	12	should	should	AUX
ajst-2551	27	13	satisfy	satisfy	VERB
ajst-2551	27	14	the	the	DET
ajst-2551	27	15	following	follow	VERB
ajst-2551	27	16	two	two	NUM
ajst-2551	27	17	formulas	formula	NOUN
ajst-2551	27	18	:	:	PUNCT
ajst-2551	27	19	,	,	PUNCT
ajst-2551	27	20	1	1	NUM
ajst-2551	27	21	1	1	NUM
ajst-2551	27	22			NOUN
ajst-2551	28	1			NUM
ajst-2551	28	2	c	c	NOUN
ajst-2551	29	1	i	i	PRON
ajst-2551	29	2	iju	iju	PROPN
ajst-2551	29	3	nj	nj	PROPN
ajst-2551	29	4	,	,	PUNCT
ajst-2551	29	5	...	...	PUNCT
ajst-2551	29	6	,	,	PUNCT
ajst-2551	29	7	1	1	NUM
ajst-2551	29	8	(	(	PUNCT
ajst-2551	29	9	4	4	NUM
ajst-2551	29	10	)	)	PUNCT
ajst-2551	29	11	nu	nu	NOUN
ajst-2551	29	12	c	c	NOUN
ajst-2551	30	1	i	i	PRON
ajst-2551	30	2	n	n	VERB
ajst-2551	30	3	j	j	PROPN
ajst-2551	30	4	ij	ij	X
ajst-2551	30	5			VERB
ajst-2551	30	6			NOUN
ajst-2551	30	7	1	1	NUM
ajst-2551	30	8	1	1	NUM
ajst-2551	30	9	(	(	PUNCT
ajst-2551	30	10	5	5	NUM
ajst-2551	30	11	)	)	PUNCT
ajst-2551	30	12	if	if	SCONJ
ajst-2551	30	13	the	the	DET
ajst-2551	30	14	membership	membership	NOUN
ajst-2551	30	15	matrix	matrix	NOUN
ajst-2551	30	16	u	u	NOUN
ajst-2551	30	17	is	be	AUX
ajst-2551	30	18	determined	determine	VERB
ajst-2551	30	19	,	,	PUNCT
ajst-2551	30	20	then	then	ADV
ajst-2551	30	21	the	the	DET
ajst-2551	30	22	cluster	cluster	NOUN
ajst-2551	30	23	center	center	NOUN
ajst-2551	30	24	ci	ci	NOUN
ajst-2551	30	25	of	of	ADP
ajst-2551	30	26	each	each	DET
ajst-2551	30	27	group	group	NOUN
ajst-2551	30	28	that	that	PRON
ajst-2551	30	29	minimizes	minimize	VERB
ajst-2551	30	30	the	the	DET
ajst-2551	30	31	objective	objective	ADJ
ajst-2551	30	32	function	function	NOUN
ajst-2551	30	33	j	j	PROPN
ajst-2551	30	34	is	be	AUX
ajst-2551	30	35	the	the	DET
ajst-2551	30	36	average	average	ADJ
ajst-2551	30	37	value	value	NOUN
ajst-2551	30	38	of	of	ADP
ajst-2551	30	39	the	the	DET
ajst-2551	30	40	samples	sample	NOUN
ajst-2551	30	41	in	in	ADP
ajst-2551	30	42	the	the	DET
ajst-2551	30	43	i	i	PROPN
ajst-2551	30	44	-	-	PUNCT
ajst-2551	30	45	th	th	PROPN
ajst-2551	30	46	group	group	NOUN
ajst-2551	30	47	expressed	express	VERB
ajst-2551	30	48	by	by	ADP
ajst-2551	30	49	the	the	DET
ajst-2551	30	50	following	follow	VERB
ajst-2551	30	51	formula	formula	NOUN
ajst-2551	30	52	.	.	PUNCT
ajst-2551	31	1			PROPN
ajst-2551	31	2			PROPN
ajst-2551	31	3			PROPN
ajst-2551	32	1	ik	ik	PROPN
ajst-2551	32	2	k	k	PROPN
ajst-2551	33	1	i	i	PRON
ajst-2551	33	2	i	i	PRON
ajst-2551	33	3	gxk	gxk	VERB
ajst-2551	33	4	x	x	VERB
ajst-2551	33	5	g	g	PROPN
ajst-2551	33	6	c	c	PROPN
ajst-2551	33	7	,	,	PUNCT
ajst-2551	33	8	1	1	NUM
ajst-2551	33	9	(	(	PUNCT
ajst-2551	33	10	6	6	NUM
ajst-2551	33	11	)	)	PUNCT
ajst-2551	33	12	where	where	SCONJ
ajst-2551	33	13	|gi|	|gi|	PROPN
ajst-2551	33	14	is	be	AUX
ajst-2551	33	15	the	the	DET
ajst-2551	33	16	number	number	NOUN
ajst-2551	33	17	of	of	ADP
ajst-2551	33	18	samples	sample	NOUN
ajst-2551	33	19	in	in	ADP
ajst-2551	33	20	group	group	NOUN
ajst-2551	33	21	i	i	PRON
ajst-2551	33	22	of	of	ADP
ajst-2551	33	23	the	the	DET
ajst-2551	33	24	following	follow	VERB
ajst-2551	33	25	formula	formula	NOUN
ajst-2551	33	26	.	.	PUNCT
ajst-2551	34	1			X
ajst-2551	35	1			NUM
ajst-2551	36	1			NOUN
ajst-2551	36	2	n	n	CCONJ
ajst-2551	36	3	j	j	PROPN
ajst-2551	36	4	iji	iji	VERB
ajst-2551	36	5	ug	ug	ADP
ajst-2551	36	6	1	1	NUM
ajst-2551	36	7	(	(	PUNCT
ajst-2551	36	8	7	7	NUM
ajst-2551	36	9	)	)	SYM
ajst-2551	36	10	71	71	NUM
ajst-2551	36	11	means	mean	VERB
ajst-2551	36	12	algorithm	algorithm	NOUN
ajst-2551	36	13	is	be	AUX
ajst-2551	36	14	to	to	PART
ajst-2551	36	15	repeatedly	repeatedly	ADV
ajst-2551	36	16	iterate	iterate	VERB
ajst-2551	36	17	the	the	DET
ajst-2551	36	18	above	above	ADJ
ajst-2551	36	19	process	process	NOUN
ajst-2551	36	20	,	,	PUNCT
ajst-2551	36	21	namely	namely	ADV
ajst-2551	36	22	:	:	PUNCT
ajst-2551	36	23	step1	step1	NOUN
ajst-2551	36	24	:	:	PUNCT
ajst-2551	36	25	selecting	select	VERB
ajst-2551	36	26	c	c	NOUN
ajst-2551	36	27	values	value	NOUN
ajst-2551	36	28	from	from	ADP
ajst-2551	36	29	a	a	DET
ajst-2551	36	30	sample	sample	NOUN
ajst-2551	36	31	space	space	NOUN
ajst-2551	36	32	as	as	ADP
ajst-2551	36	33	initial	initial	ADJ
ajst-2551	36	34	clustering	clustering	ADJ
ajst-2551	36	35	centers	center	NOUN
ajst-2551	36	36	;	;	PUNCT
ajst-2551	36	37	step	step	NOUN
ajst-2551	36	38	2	2	NUM
ajst-2551	36	39	:	:	PUNCT
ajst-2551	36	40	calculate	calculate	VERB
ajst-2551	36	41	the	the	DET
ajst-2551	36	42	membership	membership	NOUN
ajst-2551	36	43	matrix	matrix	NOUN
ajst-2551	36	44	u	u	NOUN
ajst-2551	36	45	by	by	ADP
ajst-2551	36	46	formula	formula	NOUN
ajst-2551	36	47	23	23	NUM
ajst-2551	36	48	;	;	PUNCT
ajst-2551	36	49	step	step	NOUN
ajst-2551	36	50	3	3	NUM
ajst-2551	36	51	:	:	PUNCT
ajst-2551	36	52	find	find	VERB
ajst-2551	36	53	the	the	DET
ajst-2551	36	54	objective	objective	ADJ
ajst-2551	36	55	function	function	NOUN
ajst-2551	36	56	j	j	PROPN
ajst-2551	36	57	from	from	ADP
ajst-2551	36	58	formula	formula	NOUN
ajst-2551	36	59	2	2	NUM
ajst-2551	36	60	-	-	SYM
ajst-2551	36	61	2	2	NUM
ajst-2551	36	62	,	,	PUNCT
ajst-2551	36	63	and	and	CCONJ
ajst-2551	36	64	when	when	SCONJ
ajst-2551	36	65	its	its	PRON
ajst-2551	36	66	change	change	NOUN
ajst-2551	36	67	is	be	AUX
ajst-2551	36	68	less	less	ADJ
ajst-2551	36	69	than	than	ADP
ajst-2551	36	70	a	a	DET
ajst-2551	36	71	certain	certain	ADJ
ajst-2551	36	72	threshold	threshold	NOUN
ajst-2551	36	73	,	,	PUNCT
ajst-2551	36	74	the	the	DET
ajst-2551	36	75	iteration	iteration	NOUN
ajst-2551	36	76	ends	end	VERB
ajst-2551	36	77	;	;	PUNCT
ajst-2551	36	78	step	step	NOUN
ajst-2551	36	79	4	4	NUM
ajst-2551	36	80	:	:	PUNCT
ajst-2551	36	81	get	get	VERB
ajst-2551	36	82	a	a	DET
ajst-2551	36	83	new	new	ADJ
ajst-2551	36	84	cluster	cluster	NOUN
ajst-2551	36	85	center	center	NOUN
ajst-2551	36	86	from	from	ADP
ajst-2551	36	87	formula	formula	NOUN
ajst-2551	36	88	2	2	NUM
ajst-2551	36	89	-	-	SYM
ajst-2551	36	90	6	6	NUM
ajst-2551	36	91	,	,	PUNCT
ajst-2551	36	92	and	and	CCONJ
ajst-2551	36	93	go	go	VERB
ajst-2551	36	94	to	to	PART
ajst-2551	36	95	step	step	VERB
ajst-2551	36	96	2	2	NUM
ajst-2551	36	97	.	.	X
ajst-2551	36	98	2.2	2.2	NUM
ajst-2551	36	99	.	.	PUNCT
ajst-2551	37	1	fuzzy	fuzzy	ADJ
ajst-2551	37	2	c	c	NOUN
ajst-2551	37	3	-	-	PUNCT
ajst-2551	37	4	means	mean	VERB
ajst-2551	37	5	fuzzy	fuzzy	ADJ
ajst-2551	37	6	c	c	NOUN
ajst-2551	37	7	-	-	PUNCT
ajst-2551	37	8	means	means	NOUN
ajst-2551	37	9	algorithm	algorithm	NOUN
ajst-2551	37	10	divides	divide	VERB
ajst-2551	37	11	n	n	PRON
ajst-2551	37	12	samples	sample	NOUN
ajst-2551	37	13	xj(1,2	xj(1,2	ADJ
ajst-2551	37	14	...	...	PUNCT
ajst-2551	37	15	,n	,n	NOUN
ajst-2551	37	16	)	)	PUNCT
ajst-2551	37	17	into	into	ADP
ajst-2551	37	18	c	c	NOUN
ajst-2551	37	19	fuzzy	fuzzy	ADJ
ajst-2551	37	20	groups	group	NOUN
ajst-2551	37	21	gi(i=1,2,	gi(i=1,2,	VERB
ajst-2551	37	22	...	...	PUNCT
ajst-2551	37	23	,c	,c	PUNCT
ajst-2551	37	24	)	)	PUNCT
ajst-2551	37	25	to	to	PART
ajst-2551	37	26	minimize	minimize	VERB
ajst-2551	37	27	the	the	DET
ajst-2551	37	28	objective	objective	ADJ
ajst-2551	37	29	function	function	NOUN
ajst-2551	37	30	and	and	CCONJ
ajst-2551	37	31	obtain	obtain	VERB
ajst-2551	37	32	the	the	DET
ajst-2551	37	33	cluster	cluster	NOUN
ajst-2551	37	34	center	center	NOUN
ajst-2551	37	35	ci	ci	NOUN
ajst-2551	37	36	of	of	ADP
ajst-2551	37	37	each	each	DET
ajst-2551	37	38	group	group	NOUN
ajst-2551	37	39	.	.	PUNCT
ajst-2551	38	1	the	the	DET
ajst-2551	38	2	difference	difference	NOUN
ajst-2551	38	3	between	between	ADP
ajst-2551	38	4	it	it	PRON
ajst-2551	38	5	and	and	CCONJ
ajst-2551	38	6	hard	hard	ADJ
ajst-2551	38	7	c	c	PROPN
ajst-2551	38	8	partition	partition	NOUN
ajst-2551	38	9	is	be	AUX
ajst-2551	38	10	that	that	SCONJ
ajst-2551	38	11	the	the	DET
ajst-2551	38	12	fuzzy	fuzzy	ADJ
ajst-2551	38	13	cmeans	cmean	NOUN
ajst-2551	38	14	algorithm	algorithm	PROPN
ajst-2551	38	15	uses	use	VERB
ajst-2551	38	16	the	the	DET
ajst-2551	38	17	value	value	NOUN
ajst-2551	38	18	in	in	ADP
ajst-2551	38	19	the	the	DET
ajst-2551	38	20	interval	interval	NOUN
ajst-2551	38	21	[	[	X
ajst-2551	38	22	0,1	0,1	NUM
ajst-2551	38	23	]	]	PUNCT
ajst-2551	38	24	to	to	PART
ajst-2551	38	25	indicate	indicate	VERB
ajst-2551	38	26	the	the	DET
ajst-2551	38	27	degree	degree	NOUN
ajst-2551	38	28	to	to	PART
ajst-2551	38	29	which	which	PRON
ajst-2551	38	30	each	each	DET
ajst-2551	38	31	sample	sample	NOUN
ajst-2551	38	32	belongs	belong	VERB
ajst-2551	38	33	to	to	ADP
ajst-2551	38	34	a	a	DET
ajst-2551	38	35	certain	certain	ADJ
ajst-2551	38	36	group	group	NOUN
ajst-2551	38	37	,	,	PUNCT
ajst-2551	38	38	but	but	CCONJ
ajst-2551	38	39	the	the	DET
ajst-2551	38	40	sum	sum	NOUN
ajst-2551	38	41	of	of	ADP
ajst-2551	38	42	a	a	DET
ajst-2551	38	43	sample	sample	NOUN
ajst-2551	38	44	's	's	PART
ajst-2551	38	45	membership	membership	NOUN
ajst-2551	38	46	degree	degree	NOUN
ajst-2551	38	47	to	to	ADP
ajst-2551	38	48	each	each	DET
ajst-2551	38	49	group	group	NOUN
ajst-2551	38	50	must	must	AUX
ajst-2551	38	51	be	be	AUX
ajst-2551	38	52	1	1	NUM
ajst-2551	38	53	,	,	PUNCT
ajst-2551	38	54	as	as	SCONJ
ajst-2551	38	55	follows	follow	VERB
ajst-2551	38	56	:	:	PUNCT
ajst-2551	38	57	njij	njij	PROPN
ajst-2551	38	58	c	c	NOUN
ajst-2551	39	1	i	i	PRON
ajst-2551	39	2	u	u	INTJ
ajst-2551	39	3	,	,	PUNCT
ajst-2551	39	4	...	...	PUNCT
ajst-2551	39	5	,	,	PUNCT
ajst-2551	39	6	1,1	1,1	NUM
ajst-2551	39	7	1	1	NUM
ajst-2551	39	8			NOUN
ajst-2551	39	9			NUM
ajst-2551	39	10			X
ajst-2551	39	11	(	(	PUNCT
ajst-2551	39	12	8)	8)	NUM
ajst-2551	39	13	the	the	DET
ajst-2551	39	14	objective	objective	ADJ
ajst-2551	39	15	function	function	NOUN
ajst-2551	39	16	is	be	AUX
ajst-2551	39	17	changed	change	VERB
ajst-2551	39	18	from	from	ADP
ajst-2551	39	19	formula	formula	NOUN
ajst-2551	39	20	2	2	NUM
ajst-2551	39	21	-	-	SYM
ajst-2551	39	22	2	2	NUM
ajst-2551	39	23	to	to	ADP
ajst-2551	39	24	the	the	DET
ajst-2551	39	25	following	follow	VERB
ajst-2551	39	26	formula	formula	NOUN
ajst-2551	39	27	:	:	PUNCT
ajst-2551	40	1			PROPN
ajst-2551	40	2			NUM
ajst-2551	40	3			NUM
ajst-2551	40	4			NUM
ajst-2551	40	5	c	c	X
ajst-2551	40	6	i	i	PRON
ajst-2551	40	7	n	n	CCONJ
ajst-2551	40	8	j	j	PROPN
ajst-2551	40	9	ij	ij	INTJ
ajst-2551	40	10	m	m	ADJ
ajst-2551	40	11	ij	ij	INTJ
ajst-2551	40	12	c	c	INTJ
ajst-2551	41	1	i	i	PRON
ajst-2551	41	2	i	i	PRON
ajst-2551	41	3	dujccuj	dujccuj	VERB
ajst-2551	41	4	1	1	NUM
ajst-2551	41	5	1	1	NUM
ajst-2551	41	6	2	2	NUM
ajst-2551	41	7	1	1	NUM
ajst-2551	41	8	21	21	NUM
ajst-2551	41	9	)	)	PUNCT
ajst-2551	41	10	,	,	PUNCT
ajst-2551	41	11	...	...	PUNCT
ajst-2551	41	12	,	,	PUNCT
ajst-2551	41	13	,	,	PUNCT
ajst-2551	41	14	(	(	PUNCT
ajst-2551	41	15	(	(	PUNCT
ajst-2551	41	16	9	9	X
ajst-2551	41	17	)	)	PUNCT
ajst-2551	41	18	where	where	SCONJ
ajst-2551	41	19	dij=||ci	dij=||ci	VERB
ajst-2551	41	20	-	-	PUNCT
ajst-2551	41	21	xj||	xj||	PROPN
ajst-2551	41	22	is	be	AUX
ajst-2551	41	23	the	the	DET
ajst-2551	41	24	euclidean	euclidean	ADJ
ajst-2551	41	25	distance	distance	NOUN
ajst-2551	41	26	between	between	ADP
ajst-2551	41	27	the	the	DET
ajst-2551	41	28	j	j	PROPN
ajst-2551	41	29	-	-	PUNCT
ajst-2551	41	30	th	th	VERB
ajst-2551	41	31	sample	sample	NOUN
ajst-2551	41	32	xj	xj	PROPN
ajst-2551	41	33	and	and	CCONJ
ajst-2551	41	34	the	the	DET
ajst-2551	41	35	i	i	PROPN
ajst-2551	41	36	-	-	PUNCT
ajst-2551	41	37	th	th	PROPN
ajst-2551	41	38	cluster	cluster	NOUN
ajst-2551	41	39	center	center	NOUN
ajst-2551	41	40	ci	ci	PROPN
ajst-2551	41	41	;	;	PUNCT
ajst-2551	41	42	the	the	DET
ajst-2551	41	43	value	value	NOUN
ajst-2551	41	44	of	of	ADP
ajst-2551	41	45	uij	uij	PRON
ajst-2551	41	46	is	be	AUX
ajst-2551	41	47	in	in	ADP
ajst-2551	41	48	the	the	DET
ajst-2551	41	49	interval	interval	NOUN
ajst-2551	41	50	[	[	X
ajst-2551	41	51	0,1	0,1	NUM
ajst-2551	41	52	]	]	PUNCT
ajst-2551	41	53	;	;	PUNCT
ajst-2551	41	54	the	the	DET
ajst-2551	41	55	weighted	weight	VERB
ajst-2551	41	56	index	index	NOUN
ajst-2551	41	57	m=2	m=2	PROPN
ajst-2551	41	58	is	be	AUX
ajst-2551	41	59	usually	usually	ADV
ajst-2551	41	60	taken	take	VERB
ajst-2551	41	61	.	.	PUNCT
ajst-2551	42	1	find	find	VERB
ajst-2551	42	2	each	each	DET
ajst-2551	42	3	cluster	cluster	NOUN
ajst-2551	42	4	center	center	NOUN
ajst-2551	42	5	ci	ci	NOUN
ajst-2551	42	6	and	and	CCONJ
ajst-2551	42	7	each	each	DET
ajst-2551	42	8	element	element	NOUN
ajst-2551	42	9	uij	uij	PRON
ajst-2551	42	10	in	in	ADP
ajst-2551	42	11	the	the	DET
ajst-2551	42	12	membership	membership	NOUN
ajst-2551	42	13	matrix	matrix	NOUN
ajst-2551	42	14	u	u	NOUN
ajst-2551	42	15	with	with	ADP
ajst-2551	42	16	the	the	DET
ajst-2551	42	17	minimum	minimum	ADJ
ajst-2551	42	18	value	value	NOUN
ajst-2551	42	19	of	of	ADP
ajst-2551	42	20	the	the	DET
ajst-2551	42	21	objective	objective	ADJ
ajst-2551	42	22	function	function	NOUN
ajst-2551	42	23	j	j	PROPN
ajst-2551	42	24	through	through	ADP
ajst-2551	42	25	the	the	DET
ajst-2551	42	26	functions	function	NOUN
ajst-2551	42	27	in	in	ADP
ajst-2551	42	28	the	the	DET
ajst-2551	42	29	following	follow	VERB
ajst-2551	42	30	construction	construction	NOUN
ajst-2551	42	31	formula	formula	NOUN
ajst-2551	42	32	.	.	PUNCT
ajst-2551	43	1			X
ajst-2551	43	2			X
ajst-2551	44	1			NUM
ajst-2551	45	1			NUM
ajst-2551	45	2			PRON
ajst-2551	45	3	n	n	NOUN
ajst-2551	46	1	j	j	NOUN
ajst-2551	46	2	c	c	NOUN
ajst-2551	46	3	i	i	PRON
ajst-2551	46	4	ijjcnc	ijjcnc	VERB
ajst-2551	46	5	uccujccuj	uccujccuj	NOUN
ajst-2551	46	6	1	1	NUM
ajst-2551	46	7	1	1	NUM
ajst-2551	46	8	111	111	NUM
ajst-2551	46	9	)	)	PUNCT
ajst-2551	46	10	1	1	NUM
ajst-2551	46	11	(	(	PUNCT
ajst-2551	46	12	)	)	PUNCT
ajst-2551	46	13	,	,	PUNCT
ajst-2551	46	14	...	...	PUNCT
ajst-2551	46	15	,	,	PUNCT
ajst-2551	46	16	,	,	PUNCT
ajst-2551	46	17	(	(	PUNCT
ajst-2551	46	18	)	)	PUNCT
ajst-2551	46	19	,	,	PUNCT
ajst-2551	46	20	...	...	PUNCT
ajst-2551	46	21	,	,	PUNCT
ajst-2551	46	22	,	,	PUNCT
ajst-2551	46	23	,	,	PUNCT
ajst-2551	46	24	...	...	PUNCT
ajst-2551	46	25	,	,	PUNCT
ajst-2551	46	26	,	,	PUNCT
ajst-2551	46	27	(	(	PUNCT
ajst-2551	46	28			X
ajst-2551	46	29			X
ajst-2551	46	30			PROPN
ajst-2551	46	31			NUM
ajst-2551	46	32			NUM
ajst-2551	46	33			NOUN
ajst-2551	46	34	n	n	PRON
ajst-2551	46	35	j	j	NOUN
ajst-2551	47	1	c	c	NOUN
ajst-2551	48	1	i	i	PRON
ajst-2551	48	2	ijjij	ijjij	VERB
ajst-2551	48	3	c	c	VERB
ajst-2551	49	1	i	i	PRON
ajst-2551	49	2	n	n	VERB
ajst-2551	49	3	j	j	NOUN
ajst-2551	49	4	m	m	VERB
ajst-2551	49	5	ij	ij	INTJ
ajst-2551	49	6	udu	udu	NOUN
ajst-2551	49	7	1	1	NUM
ajst-2551	49	8	1	1	NUM
ajst-2551	49	9	2	2	NUM
ajst-2551	49	10	1	1	NUM
ajst-2551	49	11	)	)	PUNCT
ajst-2551	49	12	1(	1(	NUM
ajst-2551	49	13	(	(	PUNCT
ajst-2551	49	14	10	10	NUM
ajst-2551	49	15	)	)	PUNCT
ajst-2551	49	16	where	where	SCONJ
ajst-2551	49	17	j	j	PROPN
ajst-2551	49	18	(	(	PUNCT
ajst-2551	49	19	j=1	j=1	NOUN
ajst-2551	49	20	...	...	PUNCT
ajst-2551	49	21	n	n	CCONJ
ajst-2551	49	22	)	)	PUNCT
ajst-2551	49	23	is	be	AUX
ajst-2551	49	24	n	n	PRON
ajst-2551	49	25	lagrangian	lagrangian	ADJ
ajst-2551	49	26	factors	factor	NOUN
ajst-2551	49	27	,	,	PUNCT
ajst-2551	49	28	and	and	CCONJ
ajst-2551	49	29	we	we	PRON
ajst-2551	49	30	find	find	VERB
ajst-2551	49	31	the	the	DET
ajst-2551	49	32	conditions	condition	NOUN
ajst-2551	49	33	for	for	ADP
ajst-2551	49	34	varying	vary	VERB
ajst-2551	49	35	the	the	DET
ajst-2551	49	36	input	input	NOUN
ajst-2551	49	37	parameters	parameter	NOUN
ajst-2551	49	38	to	to	PART
ajst-2551	49	39	obtain	obtain	VERB
ajst-2551	49	40	the	the	DET
ajst-2551	49	41	minimum	minimum	ADJ
ajst-2551	49	42	value	value	NOUN
ajst-2551	49	43	of	of	ADP
ajst-2551	49	44	j	j	PROPN
ajst-2551	49	45	,	,	PUNCT
ajst-2551	49	46	that	that	PRON
ajst-2551	49	47	is	be	AUX
ajst-2551	49	48	:	:	PUNCT
ajst-2551	49	49			X
ajst-2551	49	50			X
ajst-2551	49	51			NUM
ajst-2551	49	52			NUM
ajst-2551	49	53	n	n	PROPN
ajst-2551	49	54	j	j	PROPN
ajst-2551	49	55	m	m	VERB
ajst-2551	49	56	ij	ij	INTJ
ajst-2551	49	57	n	n	CCONJ
ajst-2551	50	1	j	j	PROPN
ajst-2551	51	1	j	j	PROPN
ajst-2551	51	2	m	m	VERB
ajst-2551	51	3	ij	ij	INTJ
ajst-2551	52	1	i	i	PRON
ajst-2551	52	2	u	u	NOUN
ajst-2551	53	1	xu	xu	INTJ
ajst-2551	53	2	c	c	NOUN
ajst-2551	53	3	1	1	NUM
ajst-2551	53	4	1	1	NUM
ajst-2551	53	5	(	(	PUNCT
ajst-2551	53	6	11	11	NUM
ajst-2551	53	7	)	)	PUNCT
ajst-2551	53	8			X
ajst-2551	54	1			NUM
ajst-2551	54	2			NOUN
ajst-2551	54	3			CCONJ
ajst-2551	54	4			NOUN
ajst-2551	54	5			PRON
ajst-2551	54	6			PROPN
ajst-2551	55	1			PROPN
ajst-2551	55	2	c	c	NOUN
ajst-2551	56	1	k	k	NOUN
ajst-2551	56	2	m	m	VERB
ajst-2551	56	3	kj	kj	X
ajst-2551	57	1	ij	ij	INTJ
ajst-2551	57	2	ij	ij	INTJ
ajst-2551	57	3	d	d	X
ajst-2551	57	4	d	d	X
ajst-2551	57	5	u	u	NOUN
ajst-2551	57	6	1	1	NUM
ajst-2551	57	7	)	)	PUNCT
ajst-2551	57	8	1/(2	1/(2	NUM
ajst-2551	57	9	1	1	NUM
ajst-2551	57	10	(	(	PUNCT
ajst-2551	57	11	12	12	NUM
ajst-2551	57	12	)	)	PUNCT
ajst-2551	57	13	fuzzy	fuzzy	ADJ
ajst-2551	57	14	c	c	NOUN
ajst-2551	57	15	-	-	PUNCT
ajst-2551	57	16	means	means	NOUN
ajst-2551	57	17	algorithm	algorithm	NOUN
ajst-2551	57	18	steps	step	NOUN
ajst-2551	57	19	are	be	AUX
ajst-2551	57	20	similar	similar	ADJ
ajst-2551	57	21	to	to	ADP
ajst-2551	57	22	k	k	X
ajst-2551	57	23	-	-	PUNCT
ajst-2551	57	24	means	mean	NOUN
ajst-2551	57	25	.	.	PUNCT
ajst-2551	58	1	step	step	NOUN
ajst-2551	58	2	1	1	NUM
ajst-2551	58	3	:	:	PUNCT
ajst-2551	58	4	initializing	initialize	VERB
ajst-2551	58	5	the	the	DET
ajst-2551	58	6	membership	membership	NOUN
ajst-2551	58	7	matrix	matrix	NOUN
ajst-2551	58	8	u	u	NOUN
ajst-2551	58	9	,	,	PUNCT
ajst-2551	58	10	and	and	CCONJ
ajst-2551	58	11	taking	take	VERB
ajst-2551	58	12	any	any	DET
ajst-2551	58	13	value	value	NOUN
ajst-2551	58	14	in	in	ADP
ajst-2551	58	15	the	the	DET
ajst-2551	58	16	interval	interval	NOUN
ajst-2551	58	17	[	[	X
ajst-2551	58	18	0,1	0,1	X
ajst-2551	58	19	]	]	PUNCT
ajst-2551	58	20	for	for	ADP
ajst-2551	58	21	the	the	DET
ajst-2551	58	22	elements	element	NOUN
ajst-2551	58	23	in	in	ADP
ajst-2551	58	24	u	u	NOUN
ajst-2551	58	25	,	,	PUNCT
ajst-2551	58	26	while	while	SCONJ
ajst-2551	58	27	meeting	meet	VERB
ajst-2551	58	28	the	the	DET
ajst-2551	58	29	requirements	requirement	NOUN
ajst-2551	58	30	of	of	ADP
ajst-2551	58	31	2	2	NUM
ajst-2551	58	32	-	-	SYM
ajst-2551	58	33	8	8	NUM
ajst-2551	58	34	;	;	PUNCT
ajst-2551	58	35	step	step	NOUN
ajst-2551	58	36	2	2	NUM
ajst-2551	58	37	:	:	PUNCT
ajst-2551	58	38	calculating	calculate	VERB
ajst-2551	58	39	the	the	DET
ajst-2551	58	40	ci	ci	NOUN
ajst-2551	58	41	of	of	ADP
ajst-2551	58	42	each	each	DET
ajst-2551	58	43	cluster	cluster	NOUN
ajst-2551	58	44	center	center	NOUN
ajst-2551	58	45	from	from	ADP
ajst-2551	58	46	2	2	NUM
ajst-2551	58	47	to	to	ADP
ajst-2551	58	48	11	11	NUM
ajst-2551	58	49	;	;	PUNCT
ajst-2551	58	50	step	step	NOUN
ajst-2551	58	51	3	3	NUM
ajst-2551	58	52	:	:	PUNCT
ajst-2551	58	53	find	find	VERB
ajst-2551	58	54	the	the	DET
ajst-2551	58	55	objective	objective	ADJ
ajst-2551	58	56	function	function	NOUN
ajst-2551	58	57	j	j	PROPN
ajst-2551	58	58	from	from	ADP
ajst-2551	58	59	2	2	NUM
ajst-2551	58	60	-	-	SYM
ajst-2551	58	61	9	9	NUM
ajst-2551	58	62	,	,	PUNCT
ajst-2551	58	63	and	and	CCONJ
ajst-2551	58	64	when	when	SCONJ
ajst-2551	58	65	its	its	PRON
ajst-2551	58	66	change	change	NOUN
ajst-2551	58	67	is	be	AUX
ajst-2551	58	68	less	less	ADJ
ajst-2551	58	69	than	than	ADP
ajst-2551	58	70	a	a	DET
ajst-2551	58	71	certain	certain	ADJ
ajst-2551	58	72	threshold	threshold	NOUN
ajst-2551	58	73	,	,	PUNCT
ajst-2551	58	74	the	the	DET
ajst-2551	58	75	iteration	iteration	NOUN
ajst-2551	58	76	ends	end	VERB
ajst-2551	58	77	;	;	PUNCT
ajst-2551	58	78	step	step	NOUN
ajst-2551	58	79	4	4	NUM
ajst-2551	58	80	:	:	PUNCT
ajst-2551	58	81	get	get	VERB
ajst-2551	58	82	a	a	DET
ajst-2551	58	83	new	new	ADJ
ajst-2551	58	84	membership	membership	NOUN
ajst-2551	58	85	matrix	matrix	NOUN
ajst-2551	58	86	u	u	NOUN
ajst-2551	58	87	from	from	ADP
ajst-2551	58	88	2	2	NUM
ajst-2551	58	89	-	-	SYM
ajst-2551	58	90	12	12	NUM
ajst-2551	58	91	,	,	PUNCT
ajst-2551	58	92	and	and	CCONJ
ajst-2551	58	93	go	go	VERB
ajst-2551	58	94	to	to	PART
ajst-2551	58	95	step	step	VERB
ajst-2551	58	96	2	2	NUM
ajst-2551	58	97	.	.	NOUN
ajst-2551	58	98	3	3	X
ajst-2551	58	99	.	.	PUNCT
ajst-2551	59	1	algorithm	algorithm	PROPN
ajst-2551	59	2	characteristics	characteristic	VERB
ajst-2551	59	3	k	k	NOUN
ajst-2551	59	4	-	-	PUNCT
ajst-2551	59	5	means	mean	NOUN
ajst-2551	59	6	advantages	advantage	NOUN
ajst-2551	59	7	:	:	PUNCT
ajst-2551	59	8	k	k	X
ajst-2551	59	9	-	-	PUNCT
ajst-2551	59	10	means	means	NOUN
ajst-2551	59	11	algorithm	algorithm	NOUN
ajst-2551	59	12	is	be	AUX
ajst-2551	59	13	a	a	DET
ajst-2551	59	14	classical	classical	ADJ
ajst-2551	59	15	algorithm	algorithm	NOUN
ajst-2551	59	16	to	to	PART
ajst-2551	59	17	solve	solve	VERB
ajst-2551	59	18	clustering	clustering	ADJ
ajst-2551	59	19	problems	problem	NOUN
ajst-2551	59	20	,	,	PUNCT
ajst-2551	59	21	which	which	PRON
ajst-2551	59	22	is	be	AUX
ajst-2551	59	23	simple	simple	ADJ
ajst-2551	59	24	and	and	CCONJ
ajst-2551	59	25	fast	fast	ADV
ajst-2551	59	26	;	;	PUNCT
ajst-2551	59	27	for	for	ADP
ajst-2551	59	28	large	large	ADJ
ajst-2551	59	29	data	datum	NOUN
ajst-2551	59	30	sets	set	NOUN
ajst-2551	59	31	,	,	PUNCT
ajst-2551	59	32	the	the	DET
ajst-2551	59	33	algorithm	algorithm	NOUN
ajst-2551	59	34	is	be	AUX
ajst-2551	59	35	relatively	relatively	ADV
ajst-2551	59	36	scalable	scalable	ADJ
ajst-2551	59	37	and	and	CCONJ
ajst-2551	59	38	efficient	efficient	ADJ
ajst-2551	59	39	,	,	PUNCT
ajst-2551	59	40	because	because	SCONJ
ajst-2551	59	41	its	its	PRON
ajst-2551	59	42	complexity	complexity	NOUN
ajst-2551	59	43	is	be	AUX
ajst-2551	59	44	about	about	ADP
ajst-2551	59	45	o(nkt	o(nkt	NOUN
ajst-2551	59	46	)	)	PUNCT
ajst-2551	59	47	,	,	PUNCT
ajst-2551	59	48	where	where	SCONJ
ajst-2551	59	49	n	n	PRON
ajst-2551	59	50	is	be	AUX
ajst-2551	59	51	the	the	DET
ajst-2551	59	52	number	number	NOUN
ajst-2551	59	53	of	of	ADP
ajst-2551	59	54	all	all	DET
ajst-2551	59	55	objects	object	NOUN
ajst-2551	59	56	,	,	PUNCT
ajst-2551	59	57	k	k	X
ajst-2551	59	58	is	be	AUX
ajst-2551	59	59	the	the	DET
ajst-2551	59	60	number	number	NOUN
ajst-2551	59	61	of	of	ADP
ajst-2551	59	62	clusters	cluster	NOUN
ajst-2551	59	63	,	,	PUNCT
ajst-2551	59	64	and	and	CCONJ
ajst-2551	59	65	t	t	PROPN
ajst-2551	59	66	is	be	AUX
ajst-2551	59	67	the	the	DET
ajst-2551	59	68	number	number	NOUN
ajst-2551	59	69	of	of	ADP
ajst-2551	59	70	iterations	iteration	NOUN
ajst-2551	59	71	.	.	PUNCT
ajst-2551	60	1	generally	generally	ADV
ajst-2551	60	2	k	k	X
ajst-2551	60	3	<	<	X
ajst-2551	60	4	n	n	NUM
ajst-2551	60	5	.	.	PUNCT
ajst-2551	61	1	this	this	DET
ajst-2551	61	2	algorithm	algorithm	NOUN
ajst-2551	61	3	often	often	ADV
ajst-2551	61	4	ends	end	VERB
ajst-2551	61	5	in	in	ADP
ajst-2551	61	6	local	local	ADJ
ajst-2551	61	7	optimum	optimum	NOUN
ajst-2551	61	8	;	;	PUNCT
ajst-2551	61	9	the	the	DET
ajst-2551	61	10	algorithm	algorithm	NOUN
ajst-2551	61	11	tries	try	VERB
ajst-2551	61	12	to	to	PART
ajst-2551	61	13	find	find	VERB
ajst-2551	61	14	out	out	ADP
ajst-2551	61	15	k	k	PROPN
ajst-2551	61	16	partitions	partition	NOUN
ajst-2551	61	17	that	that	PRON
ajst-2551	61	18	minimize	minimize	VERB
ajst-2551	61	19	the	the	DET
ajst-2551	61	20	square	square	ADJ
ajst-2551	61	21	error	error	NOUN
ajst-2551	61	22	function	function	NOUN
ajst-2551	61	23	value	value	NOUN
ajst-2551	61	24	.	.	PUNCT
ajst-2551	62	1	when	when	SCONJ
ajst-2551	62	2	clusters	cluster	NOUN
ajst-2551	62	3	are	be	AUX
ajst-2551	62	4	dense	dense	ADJ
ajst-2551	62	5	,	,	PUNCT
ajst-2551	62	6	spherical	spherical	ADJ
ajst-2551	62	7	or	or	CCONJ
ajst-2551	62	8	clustered	clustered	ADJ
ajst-2551	62	9	,	,	PUNCT
ajst-2551	62	10	and	and	CCONJ
ajst-2551	62	11	the	the	DET
ajst-2551	62	12	difference	difference	NOUN
ajst-2551	62	13	between	between	ADP
ajst-2551	62	14	clusters	cluster	NOUN
ajst-2551	62	15	is	be	AUX
ajst-2551	62	16	obvious	obvious	ADJ
ajst-2551	62	17	,	,	PUNCT
ajst-2551	62	18	its	its	PRON
ajst-2551	62	19	clustering	clustering	ADJ
ajst-2551	62	20	effect	effect	NOUN
ajst-2551	62	21	is	be	AUX
ajst-2551	62	22	very	very	ADV
ajst-2551	62	23	good	good	ADJ
ajst-2551	62	24	.	.	PUNCT
ajst-2551	63	1	disadvantages	disadvantage	VERB
ajst-2551	63	2	:	:	PUNCT
ajst-2551	63	3	it	it	PRON
ajst-2551	63	4	is	be	AUX
ajst-2551	63	5	necessary	necessary	ADJ
ajst-2551	63	6	to	to	PART
ajst-2551	63	7	define	define	VERB
ajst-2551	63	8	the	the	DET
ajst-2551	63	9	mean	mean	ADJ
ajst-2551	63	10	value	value	NOUN
ajst-2551	63	11	;	;	PUNCT
ajst-2551	64	1	specify	specify	VERB
ajst-2551	64	2	the	the	DET
ajst-2551	64	3	number	number	NOUN
ajst-2551	64	4	to	to	ADP
ajst-2551	64	5	cluster	cluster	NOUN
ajst-2551	64	6	;	;	PUNCT
ajst-2551	64	7	some	some	DET
ajst-2551	64	8	excessive	excessive	ADJ
ajst-2551	64	9	outliers	outlier	NOUN
ajst-2551	64	10	will	will	AUX
ajst-2551	64	11	have	have	VERB
ajst-2551	64	12	great	great	ADJ
ajst-2551	64	13	influence	influence	NOUN
ajst-2551	64	14	;	;	PUNCT
ajst-2551	64	15	the	the	DET
ajst-2551	64	16	algorithm	algorithm	NOUN
ajst-2551	64	17	is	be	AUX
ajst-2551	64	18	sensitive	sensitive	ADJ
ajst-2551	64	19	to	to	ADP
ajst-2551	64	20	initial	initial	ADJ
ajst-2551	64	21	value	value	NOUN
ajst-2551	64	22	selection	selection	NOUN
ajst-2551	64	23	;	;	PUNCT
ajst-2551	64	24	suitable	suitable	ADJ
ajst-2551	64	25	for	for	ADP
ajst-2551	64	26	spherical	spherical	ADJ
ajst-2551	64	27	clustering	clustering	NOUN
ajst-2551	64	28	.	.	PUNCT
ajst-2551	65	1	fuzzy	fuzzy	ADJ
ajst-2551	65	2	c	c	NOUN
ajst-2551	65	3	-	-	PUNCT
ajst-2551	65	4	means	mean	NOUN
ajst-2551	65	5	advantages	advantage	NOUN
ajst-2551	65	6	:	:	PUNCT
ajst-2551	65	7	fuzzy	fuzzy	ADJ
ajst-2551	65	8	c	c	NOUN
ajst-2551	65	9	-	-	PUNCT
ajst-2551	65	10	means	means	NOUN
ajst-2551	65	11	functional	functional	ADJ
ajst-2551	65	12	jm	jm	PROPN
ajst-2551	65	13	is	be	AUX
ajst-2551	65	14	still	still	ADV
ajst-2551	65	15	a	a	DET
ajst-2551	65	16	natural	natural	ADJ
ajst-2551	65	17	extension	extension	NOUN
ajst-2551	65	18	of	of	ADP
ajst-2551	65	19	traditional	traditional	ADJ
ajst-2551	65	20	hard	hard	ADJ
ajst-2551	65	21	c	c	NOUN
ajst-2551	65	22	-	-	PUNCT
ajst-2551	65	23	means	mean	VERB
ajst-2551	65	24	functional	functional	ADJ
ajst-2551	65	25	j1	j1	PROPN
ajst-2551	65	26	.	.	PUNCT
ajst-2551	66	1	j1	j1	PROPN
ajst-2551	66	2	is	be	AUX
ajst-2551	66	3	a	a	DET
ajst-2551	66	4	widely	widely	ADV
ajst-2551	66	5	used	use	VERB
ajst-2551	66	6	clustering	clustering	NOUN
ajst-2551	66	7	criterion	criterion	NOUN
ajst-2551	66	8	,	,	PUNCT
ajst-2551	66	9	and	and	CCONJ
ajst-2551	66	10	its	its	PRON
ajst-2551	66	11	theoretical	theoretical	ADJ
ajst-2551	66	12	research	research	NOUN
ajst-2551	66	13	has	have	AUX
ajst-2551	66	14	been	be	AUX
ajst-2551	66	15	quite	quite	ADV
ajst-2551	66	16	perfect	perfect	ADJ
ajst-2551	66	17	,	,	PUNCT
ajst-2551	66	18	which	which	PRON
ajst-2551	66	19	provides	provide	VERB
ajst-2551	66	20	good	good	ADJ
ajst-2551	66	21	conditions	condition	NOUN
ajst-2551	66	22	for	for	ADP
ajst-2551	66	23	the	the	DET
ajst-2551	66	24	research	research	NOUN
ajst-2551	66	25	of	of	ADP
ajst-2551	66	26	jm	jm	PROPN
ajst-2551	66	27	.	.	PUNCT
ajst-2551	67	1	this	this	DET
ajst-2551	67	2	algorithm	algorithm	NOUN
ajst-2551	67	3	has	have	AUX
ajst-2551	67	4	not	not	PART
ajst-2551	67	5	only	only	ADV
ajst-2551	67	6	been	be	AUX
ajst-2551	67	7	successfully	successfully	ADV
ajst-2551	67	8	applied	apply	VERB
ajst-2551	67	9	in	in	ADP
ajst-2551	67	10	many	many	ADJ
ajst-2551	67	11	fields	field	NOUN
ajst-2551	67	12	,	,	PUNCT
ajst-2551	67	13	but	but	CCONJ
ajst-2551	67	14	also	also	ADV
ajst-2551	67	15	based	base	VERB
ajst-2551	67	16	on	on	ADP
ajst-2551	67	17	this	this	DET
ajst-2551	67	18	algorithm	algorithm	NOUN
ajst-2551	67	19	,	,	PUNCT
ajst-2551	67	20	fuzzy	fuzzy	ADJ
ajst-2551	67	21	clustering	clustering	ADJ
ajst-2551	67	22	algorithms	algorithm	NOUN
ajst-2551	67	23	based	base	VERB
ajst-2551	67	24	on	on	ADP
ajst-2551	67	25	other	other	ADJ
ajst-2551	67	26	prototypes	prototype	NOUN
ajst-2551	67	27	have	have	AUX
ajst-2551	67	28	been	be	AUX
ajst-2551	67	29	put	put	VERB
ajst-2551	67	30	forward	forward	ADV
ajst-2551	67	31	,	,	PUNCT
ajst-2551	67	32	forming	form	VERB
ajst-2551	67	33	a	a	DET
ajst-2551	67	34	number	number	NOUN
ajst-2551	67	35	of	of	ADP
ajst-2551	67	36	fuzzy	fuzzy	ADJ
ajst-2551	67	37	c	c	NOUN
ajst-2551	67	38	-	-	PUNCT
ajst-2551	67	39	means	mean	NOUN
ajst-2551	67	40	algorithms	algorithm	NOUN
ajst-2551	67	41	,	,	PUNCT
ajst-2551	67	42	such	such	ADJ
ajst-2551	67	43	as	as	ADP
ajst-2551	67	44	fuzzy	fuzzy	ADJ
ajst-2551	67	45	c	c	NOUN
ajst-2551	67	46	-	-	PUNCT
ajst-2551	67	47	line(fcl	line(fcl	ADJ
ajst-2551	67	48	)	)	PUNCT
ajst-2551	67	49	,	,	PUNCT
ajst-2551	67	50	fuzzy	fuzzy	ADJ
ajst-2551	67	51	c	c	NOUN
ajst-2551	67	52	-	-	PUNCT
ajst-2551	67	53	plane	plane	NOUN
ajst-2551	67	54	(	(	PUNCT
ajst-2551	67	55	fcp	fcp	PROPN
ajst-2551	67	56	)	)	PUNCT
ajst-2551	67	57	,	,	PUNCT
ajst-2551	67	58	fuzzy	fuzzy	ADJ
ajst-2551	67	59	cshell	cshell	NOUN
ajst-2551	67	60	(	(	PUNCT
ajst-2551	67	61	fcs	fcs	PROPN
ajst-2551	67	62	)	)	PUNCT
ajst-2551	67	63	,	,	PUNCT
ajst-2551	67	64	etc	etc	X
ajst-2551	67	65	.	.	X
ajst-2551	67	66	,	,	PUNCT
ajst-2551	67	67	which	which	PRON
ajst-2551	67	68	respectively	respectively	ADV
ajst-2551	67	69	realize	realize	VERB
ajst-2551	67	70	linear	linear	NOUN
ajst-2551	67	71	,	,	PUNCT
ajst-2551	67	72	hyperplane	hyperplane	NOUN
ajst-2551	67	73	and	and	CCONJ
ajst-2551	67	74	"	"	PUNCT
ajst-2551	67	75	thin	thin	ADJ
ajst-2551	67	76	shell	shell	NOUN
ajst-2551	67	77	"	"	PUNCT
ajst-2551	67	78	clustering	clustering	NOUN
ajst-2551	67	79	.	.	PUNCT
ajst-2551	68	1	disadvantages	disadvantage	VERB
ajst-2551	68	2	:	:	PUNCT
ajst-2551	68	3	although	although	SCONJ
ajst-2551	68	4	fuzzy	fuzzy	ADJ
ajst-2551	68	5	clustering	clustering	NOUN
ajst-2551	68	6	is	be	AUX
ajst-2551	68	7	an	an	DET
ajst-2551	68	8	unsupervised	unsupervised	ADJ
ajst-2551	68	9	classification	classification	NOUN
ajst-2551	68	10	,	,	PUNCT
ajst-2551	68	11	fcm	fcm	ADJ
ajst-2551	68	12	-	-	PUNCT
ajst-2551	68	13	type	type	NOUN
ajst-2551	68	14	algorithm	algorithm	NOUN
ajst-2551	68	15	needs	need	VERB
ajst-2551	68	16	to	to	PART
ajst-2551	68	17	apply	apply	VERB
ajst-2551	68	18	the	the	DET
ajst-2551	68	19	prior	prior	ADJ
ajst-2551	68	20	knowledge	knowledge	NOUN
ajst-2551	68	21	of	of	ADP
ajst-2551	68	22	clustering	clustering	ADJ
ajst-2551	68	23	prototype	prototype	NOUN
ajst-2551	68	24	,	,	PUNCT
ajst-2551	68	25	otherwise	otherwise	ADV
ajst-2551	68	26	the	the	DET
ajst-2551	68	27	algorithm	algorithm	NOUN
ajst-2551	68	28	will	will	AUX
ajst-2551	68	29	be	be	AUX
ajst-2551	68	30	misleading	misleading	ADJ
ajst-2551	68	31	,	,	PUNCT
ajst-2551	68	32	thus	thus	ADV
ajst-2551	68	33	destroying	destroy	VERB
ajst-2551	68	34	the	the	DET
ajst-2551	68	35	unsupervised	unsupervised	ADJ
ajst-2551	68	36	and	and	CCONJ
ajst-2551	68	37	automated	automate	VERB
ajst-2551	68	38	algorithm	algorithm	NOUN
ajst-2551	68	39	.	.	PUNCT
ajst-2551	69	1	4	4	X
ajst-2551	69	2	.	.	X
ajst-2551	69	3	testing	testing	NOUN
ajst-2551	69	4	on	on	ADP
ajst-2551	69	5	matlab	matlab	PROPN
ajst-2551	69	6	the	the	DET
ajst-2551	69	7	tests	test	NOUN
ajst-2551	69	8	are	be	AUX
ajst-2551	69	9	carried	carry	VERB
ajst-2551	69	10	out	out	ADP
ajst-2551	69	11	under	under	ADP
ajst-2551	69	12	matlab	matlab	PROPN
ajst-2551	69	13	,	,	PUNCT
ajst-2551	69	14	we	we	PRON
ajst-2551	69	15	compare	compare	VERB
ajst-2551	69	16	the	the	DET
ajst-2551	69	17	two	two	NUM
ajst-2551	69	18	algorithms	algorithm	NOUN
ajst-2551	69	19	by	by	ADP
ajst-2551	69	20	the	the	DET
ajst-2551	69	21	result	result	NOUN
ajst-2551	69	22	image.the	image.the	DET
ajst-2551	69	23	tests	test	NOUN
ajst-2551	69	24	were	be	AUX
ajst-2551	69	25	carried	carry	VERB
ajst-2551	69	26	out	out	ADP
ajst-2551	69	27	with	with	ADP
ajst-2551	69	28	a	a	DET
ajst-2551	69	29	number	number	NOUN
ajst-2551	69	30	k	k	NOUN
ajst-2551	69	31	of	of	ADP
ajst-2551	69	32	clusters	cluster	NOUN
ajst-2551	69	33	systematically	systematically	ADV
ajst-2551	69	34	worth	worth	ADJ
ajst-2551	69	35	2	2	NUM
ajst-2551	69	36	,	,	PUNCT
ajst-2551	69	37	3	3	NUM
ajst-2551	69	38	,	,	PUNCT
ajst-2551	69	39	5	5	NUM
ajst-2551	69	40	and	and	CCONJ
ajst-2551	69	41	10	10	NUM
ajst-2551	69	42	.	.	PUNCT
ajst-2551	70	1	we	we	PRON
ajst-2551	70	2	observed	observe	VERB
ajst-2551	70	3	that	that	SCONJ
ajst-2551	70	4	the	the	DET
ajst-2551	70	5	best	good	ADJ
ajst-2551	70	6	result	result	NOUN
ajst-2551	70	7	,	,	PUNCT
ajst-2551	70	8	both	both	CCONJ
ajst-2551	70	9	from	from	ADP
ajst-2551	70	10	a	a	DET
ajst-2551	70	11	point	point	NOUN
ajst-2551	70	12	of	of	ADP
ajst-2551	70	13	character	character	NOUN
ajst-2551	70	14	detection	detection	NOUN
ajst-2551	70	15	view	view	NOUN
ajst-2551	70	16	than	than	ADP
ajst-2551	70	17	from	from	ADP
ajst-2551	70	18	a	a	DET
ajst-2551	70	19	time	time	NOUN
ajst-2551	70	20	point	point	NOUN
ajst-2551	70	21	of	of	ADP
ajst-2551	70	22	view	view	NOUN
ajst-2551	70	23	calculation	calculation	NOUN
ajst-2551	70	24	,	,	PUNCT
ajst-2551	70	25	generally	generally	ADV
ajst-2551	70	26	corresponds	correspond	VERB
ajst-2551	70	27	to	to	ADP
ajst-2551	70	28	the	the	DET
ajst-2551	70	29	detection	detection	NOUN
ajst-2551	70	30	of	of	ADP
ajst-2551	70	31	2	2	NUM
ajst-2551	70	32	clusters	cluster	NOUN
ajst-2551	70	33	.	.	PUNCT
ajst-2551	71	1	he	he	PRON
ajst-2551	71	2	seems	seem	VERB
ajst-2551	71	3	quite	quite	ADV
ajst-2551	71	4	logical	logical	ADJ
ajst-2551	71	5	that	that	SCONJ
ajst-2551	71	6	this	this	DET
ajst-2551	71	7	value	value	NOUN
ajst-2551	71	8	of	of	ADP
ajst-2551	71	9	k	k	PROPN
ajst-2551	71	10	is	be	AUX
ajst-2551	71	11	the	the	DET
ajst-2551	71	12	most	most	ADV
ajst-2551	71	13	adequate	adequate	ADJ
ajst-2551	71	14	,	,	PUNCT
ajst-2551	71	15	since	since	SCONJ
ajst-2551	71	16	it	it	PRON
ajst-2551	71	17	will	will	AUX
ajst-2551	71	18	be	be	AUX
ajst-2551	71	19	seen	see	VERB
ajst-2551	71	20	in	in	ADP
ajst-2551	71	21	all	all	DET
ajst-2551	71	22	the	the	DET
ajst-2551	71	23	images	image	NOUN
ajst-2551	71	24	tested	test	VERB
ajst-2551	71	25	,	,	PUNCT
ajst-2551	71	26	that	that	SCONJ
ajst-2551	71	27	there	there	PRON
ajst-2551	71	28	are	be	VERB
ajst-2551	71	29	essentially	essentially	ADV
ajst-2551	71	30	two	two	NUM
ajst-2551	71	31	objects	object	NOUN
ajst-2551	71	32	:	:	PUNCT
ajst-2551	71	33	the	the	DET
ajst-2551	71	34	background	background	NOUN
ajst-2551	71	35	and	and	CCONJ
ajst-2551	71	36	the	the	DET
ajst-2551	71	37	characters	character	NOUN
ajst-2551	71	38	(	(	PUNCT
ajst-2551	71	39	numbers	number	NOUN
ajst-2551	71	40	and	and	CCONJ
ajst-2551	71	41	words	word	NOUN
ajst-2551	71	42	)	)	PUNCT
ajst-2551	71	43	.	.	PUNCT
ajst-2551	72	1	the	the	DET
ajst-2551	72	2	first	first	ADJ
ajst-2551	72	3	image	image	NOUN
ajst-2551	72	4	consists	consist	VERB
ajst-2551	72	5	of	of	ADP
ajst-2551	72	6	130x42	130x42	NUM
ajst-2551	72	7	pixels	pixel	NOUN
ajst-2551	72	8	.	.	PUNCT
ajst-2551	73	1	the	the	DET
ajst-2551	73	2	characters	character	NOUN
ajst-2551	73	3	that	that	PRON
ajst-2551	73	4	form	form	VERB
ajst-2551	73	5	the	the	DET
ajst-2551	73	6	word	word	NOUN
ajst-2551	73	7	"	"	PUNCT
ajst-2551	73	8	study	study	NOUN
ajst-2551	73	9	"	"	PUNCT
ajst-2551	73	10	contain	contain	VERB
ajst-2551	73	11	mostly	mostly	ADV
ajst-2551	73	12	green	green	ADJ
ajst-2551	73	13	.	.	PUNCT
ajst-2551	74	1	the	the	DET
ajst-2551	74	2	background	background	NOUN
ajst-2551	74	3	of	of	ADP
ajst-2551	74	4	the	the	DET
ajst-2551	74	5	image	image	NOUN
ajst-2551	74	6	consists	consist	VERB
ajst-2551	74	7	of	of	ADP
ajst-2551	74	8	seve	seve	ADJ
ajst-2551	74	9	ral	ral	ADJ
ajst-2551	74	10	shades	shade	NOUN
ajst-2551	74	11	of	of	ADP
ajst-2551	74	12	blue	blue	NOUN
ajst-2551	74	13	.	.	PUNCT
ajst-2551	75	1	the	the	DET
ajst-2551	75	2	tests	test	NOUN
ajst-2551	75	3	on	on	ADP
ajst-2551	75	4	this	this	DET
ajst-2551	75	5	image	image	NOUN
ajst-2551	75	6	give	give	VERB
ajst-2551	75	7	the	the	DET
ajst-2551	75	8	following	follow	VERB
ajst-2551	75	9	results	result	NOUN
ajst-2551	75	10	:	:	PUNCT
ajst-2551	75	11	72	72	NUM
ajst-2551	75	12	figure	figure	NOUN
ajst-2551	75	13	1	1	NUM
ajst-2551	75	14	.	.	PUNCT
ajst-2551	75	15	original	original	ADJ
ajst-2551	75	16	image	image	NOUN
ajst-2551	75	17	(	(	PUNCT
ajst-2551	75	18	above	above	ADV
ajst-2551	75	19	)	)	PUNCT
ajst-2551	75	20	,	,	PUNCT
ajst-2551	75	21	application	application	NOUN
ajst-2551	75	22	of	of	ADP
ajst-2551	75	23	fuzzy	fuzzy	ADJ
ajst-2551	75	24	cmeans	cmean	NOUN
ajst-2551	75	25	(	(	PUNCT
ajst-2551	75	26	left	leave	VERB
ajst-2551	75	27	)	)	PUNCT
ajst-2551	75	28	and	and	CCONJ
ajst-2551	75	29	k	k	X
ajst-2551	75	30	-	-	PUNCT
ajst-2551	75	31	means	means	NOUN
ajst-2551	75	32	(	(	PUNCT
ajst-2551	75	33	right	right	NOUN
ajst-2551	75	34	)	)	PUNCT
ajst-2551	75	35	with	with	ADP
ajst-2551	75	36	k=2	k=2	PROPN
ajst-2551	75	37	the	the	DET
ajst-2551	75	38	second	second	ADJ
ajst-2551	75	39	(	(	PUNCT
ajst-2551	75	40	75x55	75x55	NUM
ajst-2551	75	41	pixels	pixel	NOUN
ajst-2551	75	42	)	)	PUNCT
ajst-2551	75	43	consists	consist	VERB
ajst-2551	75	44	of	of	ADP
ajst-2551	75	45	the	the	DET
ajst-2551	75	46	numbers	number	NOUN
ajst-2551	75	47	“	"	PUNCT
ajst-2551	75	48	22	22	NUM
ajst-2551	75	49	”	"	PUNCT
ajst-2551	75	50	.	.	PUNCT
ajst-2551	76	1	we	we	PRON
ajst-2551	76	2	see	see	VERB
ajst-2551	76	3	that	that	SCONJ
ajst-2551	76	4	the	the	DET
ajst-2551	76	5	contours	contours	NOUN
ajst-2551	76	6	of	of	ADP
ajst-2551	76	7	the	the	DET
ajst-2551	76	8	figures	figure	NOUN
ajst-2551	76	9	are	be	AUX
ajst-2551	76	10	very	very	ADV
ajst-2551	76	11	blurred	blurred	ADJ
ajst-2551	76	12	and	and	CCONJ
ajst-2551	76	13	the	the	DET
ajst-2551	76	14	part	part	NOUN
ajst-2551	76	15	top	top	NOUN
ajst-2551	76	16	of	of	ADP
ajst-2551	76	17	image	image	NOUN
ajst-2551	76	18	is	be	AUX
ajst-2551	76	19	slightly	slightly	ADV
ajst-2551	76	20	dark	dark	ADJ
ajst-2551	76	21	.	.	PUNCT
ajst-2551	77	1	figure	figure	NOUN
ajst-2551	77	2	2	2	NUM
ajst-2551	77	3	.	.	PUNCT
ajst-2551	77	4	original	original	ADJ
ajst-2551	77	5	image	image	NOUN
ajst-2551	77	6	(	(	PUNCT
ajst-2551	77	7	above	above	ADV
ajst-2551	77	8	)	)	PUNCT
ajst-2551	77	9	,	,	PUNCT
ajst-2551	77	10	application	application	NOUN
ajst-2551	77	11	of	of	ADP
ajst-2551	77	12	fuzzy	fuzzy	ADJ
ajst-2551	77	13	cmeans	cmean	NOUN
ajst-2551	77	14	(	(	PUNCT
ajst-2551	77	15	left	leave	VERB
ajst-2551	77	16	)	)	PUNCT
ajst-2551	77	17	and	and	CCONJ
ajst-2551	77	18	k	k	X
ajst-2551	77	19	-	-	PUNCT
ajst-2551	77	20	means	means	NOUN
ajst-2551	77	21	(	(	PUNCT
ajst-2551	77	22	right	right	NOUN
ajst-2551	77	23	)	)	PUNCT
ajst-2551	77	24	with	with	ADP
ajst-2551	77	25	k=2	k=2	PROPN
ajst-2551	77	26	figure	figure	NOUN
ajst-2551	77	27	3	3	NUM
ajst-2551	77	28	.	.	PUNCT
ajst-2551	77	29	fuzzy	fuzzy	ADJ
ajst-2551	77	30	c	c	NOUN
ajst-2551	77	31	-	-	PUNCT
ajst-2551	77	32	means	means	NOUN
ajst-2551	77	33	(	(	PUNCT
ajst-2551	77	34	left	left	ADJ
ajst-2551	77	35	)	)	PUNCT
ajst-2551	77	36	and	and	CCONJ
ajst-2551	77	37	k	k	X
ajst-2551	77	38	-	-	PUNCT
ajst-2551	77	39	means	means	NOUN
ajst-2551	77	40	(	(	PUNCT
ajst-2551	77	41	right	right	ADJ
ajst-2551	77	42	)	)	PUNCT
ajst-2551	77	43	with	with	ADP
ajst-2551	77	44	k=3	k=3	X
ajst-2551	77	45	the	the	DET
ajst-2551	77	46	dark	dark	ADJ
ajst-2551	77	47	part	part	NOUN
ajst-2551	77	48	of	of	ADP
ajst-2551	77	49	the	the	DET
ajst-2551	77	50	image	image	NOUN
ajst-2551	77	51	makes	make	VERB
ajst-2551	77	52	the	the	DET
ajst-2551	77	53	use	use	NOUN
ajst-2551	77	54	of	of	ADP
ajst-2551	77	55	both	both	CCONJ
ajst-2551	77	56	different	different	ADJ
ajst-2551	77	57	algorithms	algorithm	NOUN
ajst-2551	77	58	;	;	PUNCT
ajst-2551	77	59	on	on	ADP
ajst-2551	77	60	the	the	DET
ajst-2551	77	61	one	one	NUM
ajst-2551	77	62	hand	hand	NOUN
ajst-2551	77	63	,	,	PUNCT
ajst-2551	77	64	with	with	ADP
ajst-2551	77	65	k=2	k=2	PROPN
ajst-2551	77	66	(	(	PUNCT
ajst-2551	77	67	figure	figure	NOUN
ajst-2551	77	68	2	2	NUM
ajst-2551	77	69	)	)	PUNCT
ajst-2551	77	70	,	,	PUNCT
ajst-2551	77	71	we	we	PRON
ajst-2551	77	72	do	do	AUX
ajst-2551	77	73	not	not	PART
ajst-2551	77	74	clearly	clearly	ADV
ajst-2551	77	75	distinguish	distinguish	VERB
ajst-2551	77	76	the	the	DET
ajst-2551	77	77	upper	upper	ADJ
ajst-2551	77	78	part	part	NOUN
ajst-2551	77	79	of	of	ADP
ajst-2551	77	80	"	"	PUNCT
ajst-2551	77	81	22	22	NUM
ajst-2551	77	82	"	"	PUNCT
ajst-2551	77	83	and	and	CCONJ
ajst-2551	77	84	on	on	ADP
ajst-2551	77	85	the	the	DET
ajst-2551	77	86	other	other	ADJ
ajst-2551	77	87	hand	hand	NOUN
ajst-2551	77	88	,	,	PUNCT
ajst-2551	77	89	when	when	SCONJ
ajst-2551	77	90	we	we	PRON
ajst-2551	77	91	increase	increase	VERB
ajst-2551	77	92	the	the	DET
ajst-2551	77	93	number	number	NOUN
ajst-2551	77	94	of	of	ADP
ajst-2551	77	95	clusters	cluster	NOUN
ajst-2551	77	96	(	(	PUNCT
ajst-2551	77	97	example	example	NOUN
ajst-2551	77	98	with	with	ADP
ajst-2551	77	99	k=3	k=3	PROPN
ajst-2551	77	100	in	in	ADP
ajst-2551	77	101	figure	figure	NOUN
ajst-2551	77	102	3	3	NUM
ajst-2551	77	103	)	)	PUNCT
ajst-2551	77	104	,	,	PUNCT
ajst-2551	77	105	we	we	PRON
ajst-2551	77	106	solve	solve	VERB
ajst-2551	77	107	this	this	DET
ajst-2551	77	108	problem	problem	NOUN
ajst-2551	77	109	but	but	CCONJ
ajst-2551	77	110	we	we	PRON
ajst-2551	77	111	then	then	ADV
ajst-2551	77	112	loses	lose	VERB
ajst-2551	77	113	detection	detection	NOUN
ajst-2551	77	114	of	of	ADP
ajst-2551	77	115	the	the	DET
ajst-2551	77	116	lower	low	ADJ
ajst-2551	77	117	part	part	NOUN
ajst-2551	77	118	of	of	ADP
ajst-2551	77	119	the	the	DET
ajst-2551	77	120	"	"	PUNCT
ajst-2551	77	121	22	22	NUM
ajst-2551	77	122	"	"	PUNCT
ajst-2551	77	123	.	.	PUNCT
ajst-2551	78	1	this	this	DET
ajst-2551	78	2	example	example	NOUN
ajst-2551	78	3	illustrates	illustrate	VERB
ajst-2551	78	4	that	that	SCONJ
ajst-2551	78	5	the	the	DET
ajst-2551	78	6	objects	object	NOUN
ajst-2551	78	7	to	to	PART
ajst-2551	78	8	be	be	AUX
ajst-2551	78	9	segmented	segment	VERB
ajst-2551	78	10	must	must	AUX
ajst-2551	78	11	have	have	VERB
ajst-2551	78	12	a	a	DET
ajst-2551	78	13	sufficiently	sufficiently	ADV
ajst-2551	78	14	uniform	uniform	ADJ
ajst-2551	78	15	color	color	NOUN
ajst-2551	78	16	so	so	SCONJ
ajst-2551	78	17	that	that	SCONJ
ajst-2551	78	18	the	the	DET
ajst-2551	78	19	detection	detection	NOUN
ajst-2551	78	20	is	be	AUX
ajst-2551	78	21	possible	possible	ADJ
ajst-2551	78	22	.	.	PUNCT
ajst-2551	79	1	in	in	ADP
ajst-2551	79	2	general	general	ADJ
ajst-2551	79	3	,	,	PUNCT
ajst-2551	79	4	the	the	DET
ajst-2551	79	5	two	two	NUM
ajst-2551	79	6	algorithms	algorithm	NOUN
ajst-2551	79	7	studied	study	VERB
ajst-2551	79	8	give	give	VERB
ajst-2551	79	9	a	a	DET
ajst-2551	79	10	good	good	ADJ
ajst-2551	79	11	result	result	NOUN
ajst-2551	79	12	but	but	CCONJ
ajst-2551	79	13	have	have	VERB
ajst-2551	79	14	two	two	NUM
ajst-2551	79	15	drawbacks	drawback	NOUN
ajst-2551	79	16	:	:	PUNCT
ajst-2551	79	17	on	on	ADP
ajst-2551	79	18	the	the	DET
ajst-2551	79	19	one	one	NUM
ajst-2551	79	20	hand	hand	NOUN
ajst-2551	79	21	,	,	PUNCT
ajst-2551	79	22	they	they	PRON
ajst-2551	79	23	require	require	VERB
ajst-2551	79	24	the	the	DET
ajst-2551	79	25	prior	prior	ADJ
ajst-2551	79	26	choice	choice	NOUN
ajst-2551	79	27	of	of	ADP
ajst-2551	79	28	the	the	DET
ajst-2551	79	29	number	number	NOUN
ajst-2551	79	30	k	k	PROPN
ajst-2551	79	31	of	of	ADP
ajst-2551	79	32	clusters	cluster	NOUN
ajst-2551	79	33	,	,	PUNCT
ajst-2551	79	34	which	which	PRON
ajst-2551	79	35	makes	make	VERB
ajst-2551	79	36	it	it	PRON
ajst-2551	79	37	impossible	impossible	ADJ
ajst-2551	79	38	to	to	PART
ajst-2551	79	39	automate	automate	VERB
ajst-2551	79	40	the	the	DET
ajst-2551	79	41	method	method	NOUN
ajst-2551	79	42	;	;	PUNCT
ajst-2551	79	43	on	on	ADP
ajst-2551	79	44	the	the	DET
ajst-2551	79	45	other	other	ADJ
ajst-2551	79	46	hand	hand	NOUN
ajst-2551	79	47	,	,	PUNCT
ajst-2551	79	48	they	they	PRON
ajst-2551	79	49	require	require	VERB
ajst-2551	79	50	computation	computation	NOUN
ajst-2551	79	51	time	time	NOUN
ajst-2551	79	52	often	often	ADV
ajst-2551	79	53	high	high	ADJ
ajst-2551	79	54	,	,	PUNCT
ajst-2551	79	55	due	due	ADP
ajst-2551	79	56	to	to	ADP
ajst-2551	79	57	their	their	PRON
ajst-2551	79	58	iterative	iterative	NOUN
ajst-2551	79	59	nature	nature	NOUN
ajst-2551	79	60	.	.	PUNCT
ajst-2551	80	1	we	we	PRON
ajst-2551	80	2	have	have	AUX
ajst-2551	80	3	seen	see	VERB
ajst-2551	80	4	that	that	SCONJ
ajst-2551	80	5	these	these	DET
ajst-2551	80	6	two	two	NUM
ajst-2551	80	7	algorithms	algorithm	NOUN
ajst-2551	80	8	turn	turn	VERB
ajst-2551	80	9	out	out	ADP
ajst-2551	80	10	to	to	PART
ajst-2551	80	11	be	be	AUX
ajst-2551	80	12	effective	effective	ADJ
ajst-2551	80	13	when	when	SCONJ
ajst-2551	80	14	the	the	DET
ajst-2551	80	15	objects	object	NOUN
ajst-2551	80	16	in	in	ADP
ajst-2551	80	17	the	the	DET
ajst-2551	80	18	image	image	NOUN
ajst-2551	80	19	(	(	PUNCT
ajst-2551	80	20	essentially	essentially	ADV
ajst-2551	80	21	the	the	DET
ajst-2551	80	22	background	background	NOUN
ajst-2551	80	23	and	and	CCONJ
ajst-2551	80	24	characters	character	NOUN
ajst-2551	80	25	)	)	PUNCT
ajst-2551	80	26	are	be	AUX
ajst-2551	80	27	clearly	clearly	ADV
ajst-2551	80	28	separated	separate	VERB
ajst-2551	80	29	.	.	PUNCT
ajst-2551	81	1	we	we	PRON
ajst-2551	81	2	measured	measure	VERB
ajst-2551	81	3	the	the	DET
ajst-2551	81	4	execution	execution	NOUN
ajst-2551	81	5	time	time	NOUN
ajst-2551	81	6	of	of	ADP
ajst-2551	81	7	the	the	DET
ajst-2551	81	8	two	two	NUM
ajst-2551	81	9	algorithms	algorithm	NOUN
ajst-2551	81	10	for	for	ADP
ajst-2551	81	11	each	each	DET
ajst-2551	81	12	image	image	NOUN
ajst-2551	81	13	and	and	CCONJ
ajst-2551	81	14	it	it	PRON
ajst-2551	81	15	appears	appear	VERB
ajst-2551	81	16	that	that	PRON
ajst-2551	81	17	fcm	fcm	VERB
ajst-2551	81	18	is	be	AUX
ajst-2551	81	19	faster	fast	ADJ
ajst-2551	81	20	for	for	ADP
ajst-2551	81	21	high	high	ADJ
ajst-2551	81	22	resolution	resolution	NOUN
ajst-2551	81	23	images	image	NOUN
ajst-2551	81	24	and	and	CCONJ
ajst-2551	81	25	that	that	SCONJ
ajst-2551	81	26	k	k	PROPN
ajst-2551	81	27	means	mean	VERB
ajst-2551	81	28	is	be	AUX
ajst-2551	81	29	mo	mo	PROPN
ajst-2551	81	30	re	re	NOUN
ajst-2551	81	31	appropriate	appropriate	ADJ
ajst-2551	81	32	in	in	ADP
ajst-2551	81	33	the	the	DET
ajst-2551	81	34	case	case	NOUN
ajst-2551	81	35	of	of	ADP
ajst-2551	81	36	low	low	ADJ
ajst-2551	81	37	resolution	resolution	NOUN
ajst-2551	81	38	images	image	NOUN
ajst-2551	81	39	.	.	PUNCT
ajst-2551	82	1	note	note	VERB
ajst-2551	82	2	that	that	SCONJ
ajst-2551	82	3	the	the	DET
ajst-2551	82	4	computation	computation	NOUN
ajst-2551	82	5	time	time	NOUN
ajst-2551	82	6	is	be	AUX
ajst-2551	82	7	never	never	ADV
ajst-2551	82	8	the	the	DET
ajst-2551	82	9	same	same	ADJ
ajst-2551	82	10	for	for	ADP
ajst-2551	82	11	each	each	DET
ajst-2551	82	12	application	application	NOUN
ajst-2551	82	13	of	of	ADP
ajst-2551	82	14	the	the	DET
ajst-2551	82	15	algorithms	algorithm	NOUN
ajst-2551	82	16	,	,	PUNCT
ajst-2551	82	17	given	give	VERB
ajst-2551	82	18	that	that	SCONJ
ajst-2551	82	19	it	it	PRON
ajst-2551	82	20	is	be	AUX
ajst-2551	82	21	influenced	influence	VERB
ajst-2551	82	22	by	by	ADP
ajst-2551	82	23	the	the	DET
ajst-2551	82	24	initial	initial	ADJ
ajst-2551	82	25	position	position	NOUN
ajst-2551	82	26	of	of	ADP
ajst-2551	82	27	the	the	DET
ajst-2551	82	28	centroids	centroid	NOUN
ajst-2551	82	29	,	,	PUNCT
ajst-2551	82	30	which	which	PRON
ajst-2551	82	31	is	be	AUX
ajst-2551	82	32	calculated	calculate	VERB
ajst-2551	82	33	randomly	randomly	ADV
ajst-2551	82	34	.	.	PUNCT
ajst-2551	83	1	5	5	X
ajst-2551	83	2	.	.	X
ajst-2551	83	3	conclusion	conclusion	NOUN
ajst-2551	83	4	we	we	PRON
ajst-2551	83	5	tested	test	VERB
ajst-2551	83	6	the	the	DET
ajst-2551	83	7	fuzzy	fuzzy	ADJ
ajst-2551	83	8	c	c	NOUN
ajst-2551	83	9	-	-	PUNCT
ajst-2551	83	10	means	mean	NOUN
ajst-2551	83	11	and	and	CCONJ
ajst-2551	83	12	k	k	ADJ
ajst-2551	83	13	-	-	PUNCT
ajst-2551	83	14	means	mean	VERB
ajst-2551	83	15	segmentations	segmentation	NOUN
ajst-2551	83	16	on	on	ADP
ajst-2551	83	17	a	a	DET
ajst-2551	83	18	series	series	NOUN
ajst-2551	83	19	of	of	ADP
ajst-2551	83	20	color	color	NOUN
ajst-2551	83	21	images	image	NOUN
ajst-2551	83	22	,	,	PUNCT
ajst-2551	83	23	using	use	VERB
ajst-2551	83	24	matlab.we	matlab.we	PROPN
ajst-2551	83	25	found	find	VERB
ajst-2551	83	26	that	that	SCONJ
ajst-2551	83	27	the	the	DET
ajst-2551	83	28	two	two	NUM
ajst-2551	83	29	algorithms	algorithm	NOUN
ajst-2551	83	30	require	require	VERB
ajst-2551	83	31	prior	prior	ADJ
ajst-2551	83	32	knowledge	knowledge	NOUN
ajst-2551	83	33	of	of	ADP
ajst-2551	83	34	the	the	DET
ajst-2551	83	35	number	number	NOUN
ajst-2551	83	36	of	of	ADP
ajst-2551	83	37	clusters	cluster	NOUN
ajst-2551	83	38	to	to	PART
ajst-2551	83	39	be	be	AUX
ajst-2551	83	40	determined	determine	VERB
ajst-2551	83	41	,	,	PUNCT
ajst-2551	83	42	which	which	PRON
ajst-2551	83	43	makes	make	VERB
ajst-2551	83	44	it	it	PRON
ajst-2551	83	45	impossible	impossible	ADJ
ajst-2551	83	46	to	to	ADP
ajst-2551	83	47	possible	possible	ADJ
ajst-2551	83	48	automation	automation	NOUN
ajst-2551	83	49	of	of	ADP
ajst-2551	83	50	the	the	DET
ajst-2551	83	51	process	process	NOUN
ajst-2551	83	52	.	.	PUNCT
ajst-2551	84	1	by	by	ADP
ajst-2551	84	2	their	their	PRON
ajst-2551	84	3	character	character	NOUN
ajst-2551	84	4	iterative	iterative	NOUN
ajst-2551	84	5	,	,	PUNCT
ajst-2551	84	6	they	they	PRON
ajst-2551	84	7	turn	turn	VERB
ajst-2551	84	8	out	out	ADP
ajst-2551	84	9	to	to	PART
ajst-2551	84	10	be	be	AUX
ajst-2551	84	11	inefficient	inefficient	ADJ
ajst-2551	84	12	when	when	SCONJ
ajst-2551	84	13	the	the	DET
ajst-2551	84	14	number	number	NOUN
ajst-2551	84	15	of	of	ADP
ajst-2551	84	16	clusters	cluster	NOUN
ajst-2551	84	17	becomes	become	VERB
ajst-2551	84	18	important	important	ADJ
ajst-2551	84	19	.	.	PUNCT
ajst-2551	85	1	we	we	PRON
ajst-2551	85	2	can	can	AUX
ajst-2551	85	3	therefore	therefore	ADV
ajst-2551	85	4	conclude	conclude	VERB
ajst-2551	85	5	that	that	SCONJ
ajst-2551	85	6	the	the	DET
ajst-2551	85	7	fuzzy	fuzzy	ADJ
ajst-2551	85	8	c	c	NOUN
ajst-2551	85	9	-	-	PUNCT
ajst-2551	85	10	means	mean	NOUN
ajst-2551	85	11	and	and	CCONJ
ajst-2551	85	12	kmeans	kmean	NOUN
ajst-2551	85	13	algorithms	algorithm	NOUN
ajst-2551	85	14	are	be	AUX
ajst-2551	85	15	efficient	efficient	ADJ
ajst-2551	85	16	for	for	ADP
ajst-2551	85	17	the	the	DET
ajst-2551	85	18	detection	detection	NOUN
ajst-2551	85	19	of	of	ADP
ajst-2551	85	20	characters	character	NOUN
ajst-2551	85	21	,	,	PUNCT
ajst-2551	85	22	but	but	CCONJ
ajst-2551	85	23	are	be	AUX
ajst-2551	85	24	not	not	PART
ajst-2551	85	25	appropriate	appropriate	ADJ
ajst-2551	85	26	for	for	ADP
ajst-2551	85	27	images	image	NOUN
ajst-2551	85	28	containing	contain	VERB
ajst-2551	85	29	a	a	DET
ajst-2551	85	30	large	large	ADJ
ajst-2551	85	31	number	number	NOUN
ajst-2551	85	32	of	of	ADP
ajst-2551	85	33	objects	object	NOUN
ajst-2551	85	34	.	.	PUNCT
ajst-2551	86	1	from	from	ADP
ajst-2551	86	2	a	a	DET
ajst-2551	86	3	computation	computation	NOUN
ajst-2551	86	4	time	time	NOUN
ajst-2551	86	5	point	point	NOUN
ajst-2551	86	6	of	of	ADP
ajst-2551	86	7	view	view	NOUN
ajst-2551	86	8	,	,	PUNCT
ajst-2551	86	9	fcm	fcm	AUX
ajst-2551	86	10	turns	turn	VERB
ajst-2551	86	11	out	out	ADP
ajst-2551	86	12	to	to	PART
ajst-2551	86	13	be	be	AUX
ajst-2551	86	14	more	more	ADV
ajst-2551	86	15	efficient	efficient	ADJ
ajst-2551	86	16	for	for	ADP
ajst-2551	86	17	high	high	ADJ
ajst-2551	86	18	resolution	resolution	NOUN
ajst-2551	86	19	images	image	NOUN
ajst-2551	86	20	.	.	PUNCT
ajst-2551	87	1	resolution	resolution	NOUN
ajst-2551	87	2	while	while	SCONJ
ajst-2551	87	3	k	k	NOUN
ajst-2551	87	4	-	-	PUNCT
ajst-2551	87	5	means	means	NOUN
ajst-2551	87	6	is	be	AUX
ajst-2551	87	7	more	more	ADV
ajst-2551	87	8	suitable	suitable	ADJ
ajst-2551	87	9	for	for	ADP
ajst-2551	87	10	images	image	NOUN
ajst-2551	87	11	of	of	ADP
ajst-2551	87	12	low	low	ADJ
ajst-2551	87	13	resolution	resolution	NOUN
ajst-2551	87	14	.	.	PUNCT
ajst-2551	88	1	references	reference	NOUN
ajst-2551	88	2	[	[	X
ajst-2551	88	3	1	1	NUM
ajst-2551	88	4	]	]	PUNCT
ajst-2551	88	5	fu	fu	NOUN
ajst-2551	88	6	zhongliang.threshold	zhongliang.threshold	NUM
ajst-2551	88	7	selection	selection	NOUN
ajst-2551	88	8	method	method	NOUN
ajst-2551	88	9	based	base	VERB
ajst-2551	88	10	on	on	ADP
ajst-2551	88	11	image	image	NOUN
ajst-2551	88	12	gap	gap	NOUN
ajst-2551	88	13	measurement	measurement	NOUN
ajst-2551	89	1	[	[	X
ajst-2551	89	2	j	j	X
ajst-2551	89	3	]	]	X
ajst-2551	89	4	.	.	PUNCT
ajst-2551	90	1	beijing	beijing	PROPN
ajst-2551	90	2	:	:	PUNCT
ajst-2551	90	3	computer	computer	NOUN
ajst-2551	90	4	research	research	NOUN
ajst-2551	90	5	and	and	CCONJ
ajst-2551	90	6	development	development	NOUN
ajst-2551	90	7	,	,	PUNCT
ajst-2551	90	8	2010	2010	NUM
ajst-2551	90	9	,	,	PUNCT
ajst-2551	90	10	38(5	38(5	NUM
ajst-2551	90	11	):	):	PUNCT
ajst-2551	90	12	563	563	NUM
ajst-2551	90	13	-	-	SYM
ajst-2551	90	14	567.2	567.2	NUM
ajst-2551	90	15	.	.	PUNCT
ajst-2551	91	1	[	[	X
ajst-2551	91	2	2	2	NUM
ajst-2551	91	3	]	]	PUNCT
ajst-2551	91	4	rosefeld	rosefeld	NOUN
ajst-2551	91	5	a	a	PRON
ajst-2551	91	6	,	,	PUNCT
ajst-2551	91	7	torre	torre	PROPN
ajst-2551	91	8	p	p	PROPN
ajst-2551	91	9	de	de	X
ajst-2551	91	10	la	la	PROPN
ajst-2551	91	11	.	.	PUNCT
ajst-2551	91	12	hsitogram	hsitogram	PROPN
ajst-2551	91	13	concavity	concavity	NOUN
ajst-2551	91	14	analysis	analysis	NOUN
ajst-2551	91	15	as	as	ADP
ajst-2551	91	16	an	an	DET
ajst-2551	91	17	aid	aid	NOUN
ajst-2551	91	18	in	in	ADP
ajst-2551	91	19	threshold	threshold	NOUN
ajst-2551	91	20	selection	selection	NOUN
ajst-2551	91	21	.	.	PUNCT
ajst-2551	92	1	ieee	ieee	PROPN
ajst-2551	92	2	trans	trans	PROPN
ajst-2551	92	3	.	.	PUNCT
ajst-2551	93	1	smc	smc	PROPN
ajst-2551	93	2	,	,	PUNCT
ajst-2551	93	3	1983	1983	NUM
ajst-2551	93	4	,	,	PUNCT
ajst-2551	93	5	13(2):231	13(2):231	NUM
ajst-2551	93	6	-	-	SYM
ajst-2551	93	7	235	235	NUM
ajst-2551	93	8	.	.	PUNCT
ajst-2551	94	1	[	[	X
ajst-2551	94	2	3	3	X
ajst-2551	94	3	]	]	X
ajst-2551	94	4	zhang	zhang	PROPN
ajst-2551	94	5	c	c	PROPN
ajst-2551	94	6	,	,	PUNCT
ajst-2551	94	7	wang	wang	PROPN
ajst-2551	94	8	p.	p.	PROPN
ajst-2551	94	9	a	a	DET
ajst-2551	94	10	new	new	ADJ
ajst-2551	94	11	method	method	NOUN
ajst-2551	94	12	of	of	ADP
ajst-2551	94	13	color	color	NOUN
ajst-2551	94	14	image	image	NOUN
ajst-2551	94	15	segmentation	segmentation	NOUN
ajst-2551	94	16	based	base	VERB
ajst-2551	94	17	on	on	ADP
ajst-2551	94	18	intensity	intensity	NOUN
ajst-2551	94	19	and	and	CCONJ
ajst-2551	94	20	hue	hue	NOUN
ajst-2551	94	21	clustering	clustering	NOUN
ajst-2551	94	22	.	.	PUNCT
ajst-2551	95	1	proceedings	proceeding	NOUN
ajst-2551	95	2	of	of	ADP
ajst-2551	95	3	15th	15th	ADJ
ajst-2551	95	4	international	international	ADJ
ajst-2551	95	5	conference	conference	NOUN
ajst-2551	95	6	on	on	ADP
ajst-2551	95	7	pattern	pattern	NOUN
ajst-2551	95	8	recognition	recognition	NOUN
ajst-2551	95	9	,	,	PUNCT
ajst-2551	95	10	barcelona	barcelona	PROPN
ajst-2551	95	11	spain.2011	spain.2011	PROPN
ajst-2551	95	12	,	,	PUNCT
ajst-2551	95	13	3:613	3:613	PROPN
ajst-2551	95	14	-	-	SYM
ajst-2551	95	15	616	616	NUM
ajst-2551	95	16	.	.	PUNCT
ajst-2551	96	1	[	[	X
ajst-2551	96	2	4	4	X
ajst-2551	96	3	]	]	X
ajst-2551	96	4	zhang	zhang	PROPN
ajst-2551	96	5	yan	yan	PROPN
ajst-2551	96	6	.	.	PUNCT
ajst-2551	97	1	a	a	DET
ajst-2551	97	2	color	color	NOUN
ajst-2551	97	3	image	image	NOUN
ajst-2551	97	4	segmentation	segmentation	NOUN
ajst-2551	97	5	method	method	NOUN
ajst-2551	97	6	based	base	VERB
ajst-2551	97	7	on	on	ADP
ajst-2551	97	8	genetic	genetic	ADJ
ajst-2551	97	9	algorithm	algorithm	NOUN
ajst-2551	98	1	[	[	X
ajst-2551	98	2	j	j	X
ajst-2551	98	3	]	]	X
ajst-2551	98	4	.	.	PUNCT
ajst-2551	99	1	computer	computer	NOUN
ajst-2551	99	2	application	application	NOUN
ajst-2551	99	3	and	and	CCONJ
ajst-2551	99	4	software	software	NOUN
ajst-2551	99	5	,	,	PUNCT
ajst-2551	99	6	2011	2011	NUM
ajst-2551	99	7	,	,	PUNCT
ajst-2551	99	8	(	(	PUNCT
ajst-2551	99	9	03	03	NUM
ajst-2551	99	10	)	)	PUNCT
ajst-2551	99	11	.	.	PUNCT
ajst-2551	100	1	[	[	X
ajst-2551	100	2	5	5	X
ajst-2551	100	3	]	]	PUNCT
ajst-2551	100	4	udupa	udupa	ADJ
ajst-2551	100	5	j	j	PROPN
ajst-2551	100	6	k	k	PROPN
ajst-2551	100	7	,	,	PUNCT
ajst-2551	100	8	punam	punam	PROPN
ajst-2551	100	9	k	k	PROPN
ajst-2551	100	10	,	,	PUNCT
ajst-2551	100	11	saba	saba	PROPN
ajst-2551	100	12	p	p	PROPN
ajst-2551	100	13	k	k	PROPN
ajst-2551	100	14	et	et	PROPN
ajst-2551	100	15	al	al	PROPN
ajst-2551	100	16	.	.	PROPN
ajst-2551	100	17	relative	relative	ADJ
ajst-2551	100	18	fuzzy	fuzzy	ADJ
ajst-2551	100	19	connectedness	connectedness	NOUN
ajst-2551	100	20	and	and	CCONJ
ajst-2551	100	21	object	object	VERB
ajst-2551	100	22	definition	definition	NOUN
ajst-2551	100	23	:	:	PUNCT
ajst-2551	100	24	theory	theory	NOUN
ajst-2551	100	25	,	,	PUNCT
ajst-2551	100	26	algorithms	algorithm	NOUN
ajst-2551	100	27	,	,	PUNCT
ajst-2551	100	28	and	and	CCONJ
ajst-2551	100	29	applications	application	NOUN
ajst-2551	100	30	in	in	ADP
ajst-2551	100	31	image	image	NOUN
ajst-2551	100	32	segmentation	segmentation	NOUN
ajst-2551	100	33	.	.	PUNCT
ajst-2551	101	1	ieee	ieee	NOUN
ajst-2551	101	2	trans	trans	PROPN
ajst-2551	101	3	on	on	ADP
ajst-2551	101	4	analysis	analysis	NOUN
ajst-2551	101	5	and	and	CCONJ
ajst-2551	101	6	machine	machine	NOUN
ajst-2551	101	7	intelligence	intelligence	NOUN
ajst-2551	101	8	,	,	PUNCT
ajst-2551	101	9	2010	2010	NUM
ajst-2551	101	10	,	,	PUNCT
ajst-2551	101	11	24(11):1485	24(11):1485	NUM
ajst-2551	101	12	-	-	SYM
ajst-2551	101	13	1500	1500	NUM
ajst-2551	101	14	.	.	PUNCT
ajst-2551	102	1	[	[	X
ajst-2551	102	2	6	6	NUM
ajst-2551	102	3	]	]	PUNCT
ajst-2551	102	4	boskovitz	boskovitz	PROPN
ajst-2551	102	5	victor	victor	PROPN
ajst-2551	102	6	,	,	PUNCT
ajst-2551	102	7	guterman	guterman	PROPN
ajst-2551	102	8	hugo	hugo	PROPN
ajst-2551	102	9	.	.	PUNCT
ajst-2551	103	1	an	an	DET
ajst-2551	103	2	adaptive	adaptive	ADJ
ajst-2551	103	3	neuro	neuro	NOUN
ajst-2551	103	4	-	-	PUNCT
ajst-2551	103	5	fuzzy	fuzzy	ADJ
ajst-2551	103	6	system	system	NOUN
ajst-2551	103	7	for	for	ADP
ajst-2551	103	8	automatic	automatic	ADJ
ajst-2551	103	9	image	image	NOUN
ajst-2551	103	10	segmentation	segmentation	NOUN
ajst-2551	103	11	and	and	CCONJ
ajst-2551	103	12	edge	edge	NOUN
ajst-2551	103	13	detection	detection	NOUN
ajst-2551	103	14	.	.	PUNCT
ajst-2551	104	1	ieee	ieee	NOUN
ajst-2551	104	2	transactions	transaction	NOUN
ajst-2551	104	3	on	on	ADP
ajst-2551	104	4	fuzzy	fuzzy	ADJ
ajst-2551	104	5	systems	system	NOUN
ajst-2551	104	6	,	,	PUNCT
ajst-2551	104	7	2010	2010	NUM
ajst-2551	104	8	,	,	PUNCT
ajst-2551	104	9	10(2):247	10(2):247	PROPN
ajst-2551	104	10	-	-	SYM
ajst-2551	104	11	262	262	NUM
ajst-2551	104	12	.	.	PUNCT