id	sid	tid	token	lemma	pos
ap-5377	1	1	acta	acta	PROPN
ap-5377	1	2	polytechnica	polytechnica	PROPN
ap-5377	1	3	doi:10.14311	doi:10.14311	PROPN
ap-5377	1	4	/	/	SYM
ap-5377	1	5	ap.2019.59.0498	ap.2019.59.0498	PROPN
ap-5377	1	6	acta	acta	PROPN
ap-5377	1	7	polytechnica	polytechnica	PROPN
ap-5377	1	8	59(5):498–509	59(5):498–509	PROPN
ap-5377	1	9	,	,	PUNCT
ap-5377	1	10	2019	2019	NUM
ap-5377	1	11	©	©	PROPN
ap-5377	1	12	czech	czech	PROPN
ap-5377	1	13	technical	technical	PROPN
ap-5377	1	14	university	university	PROPN
ap-5377	1	15	in	in	ADP
ap-5377	1	16	prague	prague	PROPN
ap-5377	1	17	,	,	PUNCT
ap-5377	1	18	2019	2019	NUM
ap-5377	1	19	available	available	ADJ
ap-5377	1	20	online	online	ADV
ap-5377	1	21	at	at	ADP
ap-5377	1	22	https://ojs.cvut.cz/ojs/index.php/ap	https://ojs.cvut.cz/ojs/index.php/ap	PROPN
ap-5377	1	23	automatic	automatic	ADJ
ap-5377	1	24	eeg	eeg	NOUN
ap-5377	1	25	classification	classification	NOUN
ap-5377	1	26	using	use	VERB
ap-5377	1	27	density	density	NOUN
ap-5377	1	28	based	base	VERB
ap-5377	1	29	algorithms	algorithm	NOUN
ap-5377	1	30	dbscan	dbscan	NOUN
ap-5377	1	31	and	and	CCONJ
ap-5377	1	32	denclue	denclue	PROPN
ap-5377	1	33	marek	marek	PROPN
ap-5377	1	34	pioreckýa	pioreckýa	PROPN
ap-5377	1	35	,	,	PUNCT
ap-5377	1	36	b,∗	b,∗	PROPN
ap-5377	1	37	,	,	PUNCT
ap-5377	1	38	jan	jan	PROPN
ap-5377	1	39	štrobla	štrobla	PROPN
ap-5377	1	40	,	,	PUNCT
ap-5377	1	41	b	b	PROPN
ap-5377	1	42	,	,	PUNCT
ap-5377	1	43	vladimír	vladimír	NOUN
ap-5377	1	44	krajčaa	krajčaa	PROPN
ap-5377	1	45	,	,	PUNCT
ap-5377	1	46	b	b	PROPN
ap-5377	1	47	a	a	DET
ap-5377	1	48	czech	czech	PROPN
ap-5377	1	49	technical	technical	PROPN
ap-5377	1	50	university	university	PROPN
ap-5377	1	51	in	in	ADP
ap-5377	1	52	prague	prague	PROPN
ap-5377	1	53	,	,	PUNCT
ap-5377	1	54	faculty	faculty	NOUN
ap-5377	1	55	of	of	ADP
ap-5377	1	56	biomedical	biomedical	ADJ
ap-5377	1	57	engineering	engineering	NOUN
ap-5377	1	58	,	,	PUNCT
ap-5377	1	59	department	department	NOUN
ap-5377	1	60	of	of	ADP
ap-5377	1	61	biomedical	biomedical	ADJ
ap-5377	1	62	technology	technology	NOUN
ap-5377	1	63	,	,	PUNCT
ap-5377	1	64	nám	nám	PROPN
ap-5377	1	65	.	.	PUNCT
ap-5377	2	1	sítná	sítná	PROPN
ap-5377	2	2	3105	3105	NUM
ap-5377	2	3	,	,	PUNCT
ap-5377	2	4	27201	27201	NUM
ap-5377	2	5	kladno	kladno	PROPN
ap-5377	2	6	,	,	PUNCT
ap-5377	2	7	czech	czech	PROPN
ap-5377	2	8	republic	republic	PROPN
ap-5377	2	9	b	b	PROPN
ap-5377	2	10	national	national	PROPN
ap-5377	2	11	institute	institute	PROPN
ap-5377	2	12	of	of	ADP
ap-5377	2	13	mental	mental	PROPN
ap-5377	2	14	health	health	NOUN
ap-5377	2	15	,	,	PUNCT
ap-5377	2	16	topolova	topolova	NOUN
ap-5377	2	17	748	748	NUM
ap-5377	2	18	,	,	PUNCT
ap-5377	2	19	25067	25067	NUM
ap-5377	2	20	klecany	klecany	NOUN
ap-5377	2	21	,	,	PUNCT
ap-5377	2	22	czech	czech	PROPN
ap-5377	2	23	republic	republic	NOUN
ap-5377	2	24	∗	∗	NOUN
ap-5377	2	25	corresponding	correspond	VERB
ap-5377	2	26	author	author	NOUN
ap-5377	2	27	:	:	PUNCT
ap-5377	2	28	marek.piorecky@fbmi.cvut.cz	marek.piorecky@fbmi.cvut.cz	PROPN
ap-5377	2	29	abstract	abstract	PROPN
ap-5377	2	30	.	.	PUNCT
ap-5377	3	1	electroencephalograph	electroencephalograph	PROPN
ap-5377	3	2	(	(	PUNCT
ap-5377	3	3	eeg	eeg	PROPN
ap-5377	3	4	)	)	PUNCT
ap-5377	3	5	is	be	AUX
ap-5377	3	6	a	a	DET
ap-5377	3	7	commonly	commonly	ADV
ap-5377	3	8	used	use	VERB
ap-5377	3	9	method	method	NOUN
ap-5377	3	10	in	in	ADP
ap-5377	3	11	neurological	neurological	ADJ
ap-5377	3	12	practice	practice	NOUN
ap-5377	3	13	.	.	PUNCT
ap-5377	4	1	automatic	automatic	ADJ
ap-5377	4	2	classifiers	classifier	NOUN
ap-5377	4	3	(	(	PUNCT
ap-5377	4	4	algorithms	algorithm	NOUN
ap-5377	4	5	)	)	PUNCT
ap-5377	4	6	highlight	highlight	VERB
ap-5377	4	7	signal	signal	NOUN
ap-5377	4	8	sections	section	NOUN
ap-5377	4	9	with	with	ADP
ap-5377	4	10	interesting	interesting	ADJ
ap-5377	4	11	activity	activity	NOUN
ap-5377	4	12	and	and	CCONJ
ap-5377	4	13	assist	assist	VERB
ap-5377	4	14	an	an	DET
ap-5377	4	15	expert	expert	NOUN
ap-5377	4	16	with	with	ADP
ap-5377	4	17	record	record	NOUN
ap-5377	4	18	scoring	scoring	NOUN
ap-5377	4	19	.	.	PUNCT
ap-5377	5	1	algorithm	algorithm	PROPN
ap-5377	5	2	k	k	NOUN
ap-5377	5	3	-	-	PUNCT
ap-5377	5	4	means	means	NOUN
ap-5377	5	5	is	be	AUX
ap-5377	5	6	one	one	NUM
ap-5377	5	7	of	of	ADP
ap-5377	5	8	the	the	DET
ap-5377	5	9	most	most	ADV
ap-5377	5	10	commonly	commonly	ADV
ap-5377	5	11	used	use	VERB
ap-5377	5	12	methods	method	NOUN
ap-5377	5	13	for	for	ADP
ap-5377	5	14	eeg	eeg	NOUN
ap-5377	5	15	inspection	inspection	NOUN
ap-5377	5	16	.	.	PUNCT
ap-5377	6	1	in	in	ADP
ap-5377	6	2	this	this	DET
ap-5377	6	3	paper	paper	NOUN
ap-5377	6	4	,	,	PUNCT
ap-5377	6	5	we	we	PRON
ap-5377	6	6	propose	propose	VERB
ap-5377	6	7	/	/	PUNCT
ap-5377	6	8	apply	apply	VERB
ap-5377	6	9	a	a	DET
ap-5377	6	10	method	method	NOUN
ap-5377	6	11	based	base	VERB
ap-5377	6	12	on	on	ADP
ap-5377	6	13	density	density	NOUN
ap-5377	6	14	-	-	PUNCT
ap-5377	6	15	oriented	orient	VERB
ap-5377	6	16	algorithms	algorithm	NOUN
ap-5377	6	17	dbscan	dbscan	NOUN
ap-5377	6	18	and	and	CCONJ
ap-5377	6	19	denclue	denclue	NOUN
ap-5377	6	20	.	.	PUNCT
ap-5377	7	1	dbscan	dbscan	PROPN
ap-5377	7	2	and	and	CCONJ
ap-5377	7	3	denclue	denclue	VERB
ap-5377	7	4	separate	separate	VERB
ap-5377	7	5	the	the	DET
ap-5377	7	6	nested	nested	ADJ
ap-5377	7	7	clusters	cluster	NOUN
ap-5377	7	8	against	against	ADP
ap-5377	7	9	k	k	X
ap-5377	7	10	-	-	PUNCT
ap-5377	7	11	means	mean	NOUN
ap-5377	7	12	.	.	PUNCT
ap-5377	8	1	all	all	DET
ap-5377	8	2	three	three	NUM
ap-5377	8	3	algorithms	algorithm	NOUN
ap-5377	8	4	were	be	AUX
ap-5377	8	5	validated	validate	VERB
ap-5377	8	6	on	on	ADP
ap-5377	8	7	a	a	DET
ap-5377	8	8	testing	testing	NOUN
ap-5377	8	9	dataset	dataset	NOUN
ap-5377	8	10	and	and	CCONJ
ap-5377	8	11	after	after	SCONJ
ap-5377	8	12	that	that	PRON
ap-5377	8	13	adapted	adapt	VERB
ap-5377	8	14	for	for	ADP
ap-5377	8	15	a	a	DET
ap-5377	8	16	real	real	ADJ
ap-5377	8	17	eeg	eeg	NOUN
ap-5377	8	18	records	record	NOUN
ap-5377	8	19	classification	classification	NOUN
ap-5377	8	20	.	.	PUNCT
ap-5377	9	1	24	24	NUM
ap-5377	9	2	dimensions	dimension	NOUN
ap-5377	9	3	eeg	eeg	NOUN
ap-5377	9	4	feature	feature	NOUN
ap-5377	9	5	space	space	NOUN
ap-5377	9	6	were	be	AUX
ap-5377	9	7	classified	classify	VERB
ap-5377	9	8	into	into	ADP
ap-5377	9	9	5	5	NUM
ap-5377	9	10	classes	class	NOUN
ap-5377	9	11	(	(	PUNCT
ap-5377	9	12	physiological	physiological	ADJ
ap-5377	9	13	,	,	PUNCT
ap-5377	9	14	epileptic	epileptic	ADJ
ap-5377	9	15	,	,	PUNCT
ap-5377	9	16	eog	eog	PROPN
ap-5377	9	17	,	,	PUNCT
ap-5377	9	18	electrode	electrode	NOUN
ap-5377	9	19	,	,	PUNCT
ap-5377	9	20	and	and	CCONJ
ap-5377	9	21	emg	emg	NOUN
ap-5377	9	22	artefact	artefact	PROPN
ap-5377	9	23	)	)	PUNCT
ap-5377	9	24	.	.	PUNCT
ap-5377	10	1	modified	modify	VERB
ap-5377	10	2	dbscan	dbscan	NOUN
ap-5377	10	3	and	and	CCONJ
ap-5377	10	4	denclue	denclue	NOUN
ap-5377	10	5	create	create	VERB
ap-5377	10	6	more	more	ADJ
ap-5377	10	7	than	than	ADP
ap-5377	10	8	two	two	NUM
ap-5377	10	9	homogeneous	homogeneous	ADJ
ap-5377	10	10	classes	class	NOUN
ap-5377	10	11	of	of	ADP
ap-5377	10	12	the	the	DET
ap-5377	10	13	epileptic	epileptic	ADJ
ap-5377	10	14	eeg	eeg	PROPN
ap-5377	10	15	data	datum	NOUN
ap-5377	10	16	.	.	PUNCT
ap-5377	11	1	the	the	DET
ap-5377	11	2	results	result	NOUN
ap-5377	11	3	offer	offer	VERB
ap-5377	11	4	an	an	DET
ap-5377	11	5	opportunity	opportunity	NOUN
ap-5377	11	6	for	for	ADP
ap-5377	11	7	the	the	DET
ap-5377	11	8	eeg	eeg	NOUN
ap-5377	11	9	scoring	scoring	NOUN
ap-5377	11	10	in	in	ADP
ap-5377	11	11	clinical	clinical	ADJ
ap-5377	11	12	practice	practice	NOUN
ap-5377	11	13	.	.	PUNCT
ap-5377	12	1	the	the	DET
ap-5377	12	2	big	big	ADJ
ap-5377	12	3	advantage	advantage	NOUN
ap-5377	12	4	of	of	ADP
ap-5377	12	5	the	the	DET
ap-5377	12	6	proposed	propose	VERB
ap-5377	12	7	algorithms	algorithms	NOUN
ap-5377	12	8	is	be	AUX
ap-5377	12	9	the	the	DET
ap-5377	12	10	high	high	ADJ
ap-5377	12	11	homogeneity	homogeneity	NOUN
ap-5377	12	12	of	of	ADP
ap-5377	12	13	the	the	DET
ap-5377	12	14	epileptic	epileptic	ADJ
ap-5377	12	15	class	class	NOUN
ap-5377	12	16	.	.	PUNCT
ap-5377	13	1	keywords	keyword	NOUN
ap-5377	13	2	:	:	PUNCT
ap-5377	13	3	eeg	eeg	NOUN
ap-5377	13	4	,	,	PUNCT
ap-5377	13	5	dbscan	dbscan	NOUN
ap-5377	13	6	,	,	PUNCT
ap-5377	13	7	denclue	denclue	NOUN
ap-5377	13	8	,	,	PUNCT
ap-5377	13	9	automatic	automatic	ADJ
ap-5377	13	10	classification	classification	NOUN
ap-5377	13	11	,	,	PUNCT
ap-5377	13	12	epilepsy	epilepsy	NOUN
ap-5377	13	13	.	.	PUNCT
ap-5377	14	1	1	1	X
ap-5377	14	2	.	.	X
ap-5377	14	3	introduction	introduction	NOUN
ap-5377	14	4	electroencephalograph	electroencephalograph	PROPN
ap-5377	14	5	(	(	PUNCT
ap-5377	14	6	eeg	eeg	NOUN
ap-5377	14	7	)	)	PUNCT
ap-5377	14	8	represents	represent	VERB
ap-5377	14	9	the	the	DET
ap-5377	14	10	electric	electric	ADJ
ap-5377	14	11	activity	activity	NOUN
ap-5377	14	12	of	of	ADP
ap-5377	14	13	the	the	DET
ap-5377	14	14	brain	brain	NOUN
ap-5377	14	15	.	.	PUNCT
ap-5377	15	1	brain	brain	NOUN
ap-5377	15	2	activity	activity	NOUN
ap-5377	15	3	is	be	AUX
ap-5377	15	4	most	most	ADV
ap-5377	15	5	often	often	ADV
ap-5377	15	6	recorded	record	VERB
ap-5377	15	7	on	on	ADP
ap-5377	15	8	the	the	DET
ap-5377	15	9	scalp	scalp	NOUN
ap-5377	15	10	.	.	PUNCT
ap-5377	16	1	eeg	eeg	PROPN
ap-5377	16	2	is	be	AUX
ap-5377	16	3	a	a	DET
ap-5377	16	4	commonly	commonly	ADV
ap-5377	16	5	used	use	VERB
ap-5377	16	6	method	method	NOUN
ap-5377	16	7	in	in	ADP
ap-5377	16	8	clinical	clinical	ADJ
ap-5377	16	9	practice	practice	NOUN
ap-5377	16	10	(	(	PUNCT
ap-5377	16	11	for	for	ADP
ap-5377	16	12	example	example	NOUN
ap-5377	16	13	,	,	PUNCT
ap-5377	16	14	for	for	ADP
ap-5377	16	15	detection	detection	NOUN
ap-5377	16	16	of	of	ADP
ap-5377	16	17	epilepsy	epilepsy	NOUN
ap-5377	16	18	,	,	PUNCT
ap-5377	16	19	schizophrenia	schizophrenia	NOUN
ap-5377	16	20	,	,	PUNCT
ap-5377	16	21	etc	etc	X
ap-5377	16	22	.	.	X
ap-5377	16	23	)	)	PUNCT
ap-5377	17	1	[	[	X
ap-5377	17	2	1	1	NUM
ap-5377	17	3	,	,	PUNCT
ap-5377	17	4	2	2	NUM
ap-5377	17	5	]	]	PUNCT
ap-5377	17	6	.	.	PUNCT
ap-5377	18	1	the	the	DET
ap-5377	18	2	measured	measure	VERB
ap-5377	18	3	signal	signal	NOUN
ap-5377	18	4	depends	depend	VERB
ap-5377	18	5	on	on	ADP
ap-5377	18	6	the	the	DET
ap-5377	18	7	type	type	NOUN
ap-5377	18	8	of	of	ADP
ap-5377	18	9	the	the	DET
ap-5377	18	10	electrode	electrode	NOUN
ap-5377	18	11	used	use	VERB
ap-5377	18	12	,	,	PUNCT
ap-5377	18	13	their	their	PRON
ap-5377	18	14	number	number	NOUN
ap-5377	18	15	,	,	PUNCT
ap-5377	18	16	location	location	NOUN
ap-5377	18	17	,	,	PUNCT
ap-5377	18	18	and	and	CCONJ
ap-5377	18	19	on	on	ADP
ap-5377	18	20	many	many	ADJ
ap-5377	18	21	other	other	ADJ
ap-5377	18	22	influences	influence	NOUN
ap-5377	18	23	.	.	PUNCT
ap-5377	19	1	the	the	DET
ap-5377	19	2	raw	raw	ADJ
ap-5377	19	3	signal	signal	NOUN
ap-5377	19	4	represents	represent	VERB
ap-5377	19	5	a	a	DET
ap-5377	19	6	changing	change	VERB
ap-5377	19	7	voltage	voltage	NOUN
ap-5377	19	8	on	on	ADP
ap-5377	19	9	each	each	DET
ap-5377	19	10	electrode	electrode	NOUN
ap-5377	19	11	,	,	PUNCT
ap-5377	19	12	in	in	ADP
ap-5377	19	13	time	time	NOUN
ap-5377	19	14	.	.	PUNCT
ap-5377	20	1	we	we	PRON
ap-5377	20	2	are	be	AUX
ap-5377	20	3	not	not	PART
ap-5377	20	4	able	able	ADJ
ap-5377	20	5	to	to	PART
ap-5377	20	6	measure	measure	VERB
ap-5377	20	7	the	the	DET
ap-5377	20	8	half	half	ADJ
ap-5377	20	9	-	-	PUNCT
ap-5377	20	10	cell	cell	NOUN
ap-5377	20	11	potential	potential	NOUN
ap-5377	20	12	,	,	PUNCT
ap-5377	20	13	therefore	therefore	ADV
ap-5377	20	14	,	,	PUNCT
ap-5377	20	15	the	the	DET
ap-5377	20	16	resulting	result	VERB
ap-5377	20	17	voltage	voltage	NOUN
ap-5377	20	18	is	be	AUX
ap-5377	20	19	given	give	VERB
ap-5377	20	20	by	by	ADP
ap-5377	20	21	the	the	DET
ap-5377	20	22	difference	difference	NOUN
ap-5377	20	23	of	of	ADP
ap-5377	20	24	the	the	DET
ap-5377	20	25	potentials	potential	NOUN
ap-5377	20	26	of	of	ADP
ap-5377	20	27	the	the	DET
ap-5377	20	28	two	two	NUM
ap-5377	20	29	electrodes	electrode	NOUN
ap-5377	20	30	.	.	PUNCT
ap-5377	21	1	standard	standard	ADJ
ap-5377	21	2	pre	pre	ADJ
ap-5377	21	3	-	-	ADJ
ap-5377	21	4	processing	processing	ADJ
ap-5377	21	5	consists	consist	NOUN
ap-5377	21	6	of	of	ADP
ap-5377	21	7	montage	montage	NOUN
ap-5377	21	8	,	,	PUNCT
ap-5377	21	9	filtration	filtration	NOUN
ap-5377	21	10	,	,	PUNCT
ap-5377	21	11	and	and	CCONJ
ap-5377	21	12	segmentation	segmentation	NOUN
ap-5377	21	13	.	.	PUNCT
ap-5377	22	1	segments	segment	NOUN
ap-5377	22	2	are	be	AUX
ap-5377	22	3	characterized	characterize	VERB
ap-5377	22	4	by	by	ADP
ap-5377	22	5	features	feature	NOUN
ap-5377	22	6	,	,	PUNCT
ap-5377	22	7	with	with	ADP
ap-5377	22	8	each	each	DET
ap-5377	22	9	feature	feature	NOUN
ap-5377	22	10	describing	describe	VERB
ap-5377	22	11	a	a	DET
ap-5377	22	12	mathematical	mathematical	ADJ
ap-5377	22	13	characteristic	characteristic	NOUN
ap-5377	22	14	(	(	PUNCT
ap-5377	22	15	amplitude	amplitude	NOUN
ap-5377	22	16	,	,	PUNCT
ap-5377	22	17	frequency	frequency	NOUN
ap-5377	22	18	,	,	PUNCT
ap-5377	22	19	etc	etc	X
ap-5377	22	20	.	.	X
ap-5377	22	21	)	)	PUNCT
ap-5377	22	22	.	.	PUNCT
ap-5377	23	1	unsupervised	unsupervised	ADJ
ap-5377	23	2	methods	method	NOUN
ap-5377	23	3	do	do	AUX
ap-5377	23	4	not	not	PART
ap-5377	23	5	require	require	VERB
ap-5377	23	6	any	any	DET
ap-5377	23	7	user	user	NOUN
ap-5377	23	8	input	input	NOUN
ap-5377	23	9	,	,	PUNCT
ap-5377	23	10	so	so	SCONJ
ap-5377	23	11	they	they	PRON
ap-5377	23	12	should	should	AUX
ap-5377	23	13	be	be	AUX
ap-5377	23	14	more	more	ADV
ap-5377	23	15	objective	objective	ADJ
ap-5377	23	16	and	and	CCONJ
ap-5377	23	17	less	less	ADV
ap-5377	23	18	timeconsuming	timeconsuming	ADJ
ap-5377	23	19	.	.	PUNCT
ap-5377	24	1	the	the	DET
ap-5377	24	2	density	density	NOUN
ap-5377	24	3	-	-	PUNCT
ap-5377	24	4	based	base	VERB
ap-5377	24	5	clustering	clustering	ADJ
ap-5377	24	6	algorithm	algorithm	NOUN
ap-5377	24	7	is	be	AUX
ap-5377	24	8	used	use	VERB
ap-5377	24	9	to	to	PART
ap-5377	24	10	find	find	VERB
ap-5377	24	11	non	non	ADJ
ap-5377	24	12	-	-	ADJ
ap-5377	24	13	linear	linear	ADJ
ap-5377	24	14	shapes	shape	NOUN
ap-5377	24	15	structure	structure	NOUN
ap-5377	24	16	based	base	VERB
ap-5377	24	17	on	on	ADP
ap-5377	24	18	the	the	DET
ap-5377	24	19	density	density	NOUN
ap-5377	24	20	.	.	PUNCT
ap-5377	25	1	density	density	NOUN
ap-5377	25	2	-	-	PUNCT
ap-5377	25	3	based	base	VERB
ap-5377	25	4	spatial	spatial	ADJ
ap-5377	25	5	clustering	clustering	NOUN
ap-5377	25	6	of	of	ADP
ap-5377	25	7	applications	application	NOUN
ap-5377	25	8	with	with	ADP
ap-5377	25	9	noise	noise	NOUN
ap-5377	25	10	(	(	PUNCT
ap-5377	25	11	dbscan	dbscan	NOUN
ap-5377	25	12	)	)	PUNCT
ap-5377	26	1	[	[	X
ap-5377	26	2	3	3	X
ap-5377	26	3	]	]	PUNCT
ap-5377	26	4	is	be	AUX
ap-5377	26	5	not	not	PART
ap-5377	26	6	used	use	VERB
ap-5377	26	7	to	to	PART
ap-5377	26	8	classify	classify	VERB
ap-5377	26	9	an	an	DET
ap-5377	26	10	eeg	eeg	NOUN
ap-5377	26	11	record	record	NOUN
ap-5377	26	12	in	in	ADP
ap-5377	26	13	common	common	ADJ
ap-5377	26	14	practice	practice	NOUN
ap-5377	26	15	,	,	PUNCT
ap-5377	26	16	although	although	SCONJ
ap-5377	26	17	it	it	PRON
ap-5377	26	18	is	be	AUX
ap-5377	26	19	an	an	DET
ap-5377	26	20	algorithm	algorithm	NOUN
ap-5377	26	21	that	that	PRON
ap-5377	26	22	is	be	AUX
ap-5377	26	23	used	use	VERB
ap-5377	26	24	in	in	ADP
ap-5377	26	25	many	many	ADJ
ap-5377	26	26	software	software	NOUN
ap-5377	26	27	applications	application	NOUN
ap-5377	26	28	in	in	ADP
ap-5377	26	29	many	many	ADJ
ap-5377	26	30	modifications	modification	NOUN
ap-5377	26	31	.	.	PUNCT
ap-5377	27	1	density	density	NOUN
ap-5377	27	2	-	-	PUNCT
ap-5377	27	3	based	base	VERB
ap-5377	27	4	clustering	clustering	NOUN
ap-5377	27	5	(	(	PUNCT
ap-5377	27	6	denclue	denclue	NOUN
ap-5377	27	7	)	)	PUNCT
ap-5377	28	1	[	[	X
ap-5377	28	2	4	4	X
ap-5377	28	3	]	]	PUNCT
ap-5377	28	4	is	be	AUX
ap-5377	28	5	a	a	DET
ap-5377	28	6	younger	young	ADJ
ap-5377	28	7	density	density	NOUN
ap-5377	28	8	-	-	PUNCT
ap-5377	28	9	based	base	VERB
ap-5377	28	10	method	method	NOUN
ap-5377	28	11	working	work	VERB
ap-5377	28	12	on	on	ADP
ap-5377	28	13	statistical	statistical	ADJ
ap-5377	28	14	principle	principle	NOUN
ap-5377	28	15	,	,	PUNCT
ap-5377	28	16	see	see	VERB
ap-5377	28	17	section2	section2	PROPN
ap-5377	28	18	,	,	PUNCT
ap-5377	28	19	which	which	PRON
ap-5377	28	20	is	be	AUX
ap-5377	28	21	not	not	PART
ap-5377	28	22	generally	generally	ADV
ap-5377	28	23	used	use	VERB
ap-5377	28	24	to	to	PART
ap-5377	28	25	classify	classify	VERB
ap-5377	28	26	an	an	DET
ap-5377	28	27	eeg	eeg	NOUN
ap-5377	28	28	record	record	NOUN
ap-5377	28	29	yet	yet	ADV
ap-5377	28	30	.	.	PUNCT
ap-5377	29	1	[	[	X
ap-5377	29	2	3	3	NUM
ap-5377	29	3	,	,	PUNCT
ap-5377	29	4	4	4	NUM
ap-5377	29	5	]	]	PUNCT
ap-5377	29	6	epilepsy	epilepsy	NOUN
ap-5377	29	7	is	be	AUX
ap-5377	29	8	a	a	DET
ap-5377	29	9	serious	serious	ADJ
ap-5377	29	10	neurological	neurological	ADJ
ap-5377	29	11	disorder	disorder	NOUN
ap-5377	29	12	that	that	PRON
ap-5377	29	13	is	be	AUX
ap-5377	29	14	manifested	manifest	VERB
ap-5377	29	15	by	by	ADP
ap-5377	29	16	seizures	seizure	NOUN
ap-5377	29	17	.	.	PUNCT
ap-5377	30	1	in	in	ADP
ap-5377	30	2	the	the	DET
ap-5377	30	3	eeg	eeg	NOUN
ap-5377	30	4	curve	curve	NOUN
ap-5377	30	5	,	,	PUNCT
ap-5377	30	6	the	the	DET
ap-5377	30	7	epileptic	epileptic	ADJ
ap-5377	30	8	attack	attack	NOUN
ap-5377	30	9	is	be	AUX
ap-5377	30	10	observable	observable	ADJ
ap-5377	30	11	with	with	ADP
ap-5377	30	12	the	the	DET
ap-5377	30	13	spike	spike	ADJ
ap-5377	30	14	wave	wave	NOUN
ap-5377	30	15	complex	complex	NOUN
ap-5377	30	16	.	.	PUNCT
ap-5377	31	1	an	an	DET
ap-5377	31	2	eeg	eeg	NOUN
ap-5377	31	3	record	record	NOUN
ap-5377	31	4	in	in	ADP
ap-5377	31	5	a	a	DET
ap-5377	31	6	regular	regular	ADJ
ap-5377	31	7	clinical	clinical	ADJ
ap-5377	31	8	examination	examination	NOUN
ap-5377	31	9	contains	contain	VERB
ap-5377	31	10	thousands	thousand	NOUN
ap-5377	31	11	of	of	ADP
ap-5377	31	12	segments	segment	NOUN
ap-5377	31	13	.	.	PUNCT
ap-5377	32	1	automatic	automatic	ADJ
ap-5377	32	2	classification	classification	NOUN
ap-5377	32	3	methods	method	NOUN
ap-5377	32	4	are	be	AUX
ap-5377	32	5	often	often	ADV
ap-5377	32	6	binary	binary	NOUN
ap-5377	32	7	aimed	aim	VERB
ap-5377	32	8	at	at	ADP
ap-5377	32	9	detecting	detect	VERB
ap-5377	32	10	only	only	ADV
ap-5377	32	11	epileptogenic	epileptogenic	ADJ
ap-5377	32	12	activity	activity	NOUN
ap-5377	32	13	,	,	PUNCT
ap-5377	32	14	for	for	ADP
ap-5377	32	15	example	example	NOUN
ap-5377	32	16	[	[	X
ap-5377	32	17	5	5	NUM
ap-5377	32	18	,	,	PUNCT
ap-5377	32	19	6	6	NUM
ap-5377	32	20	]	]	PUNCT
ap-5377	32	21	.	.	PUNCT
ap-5377	33	1	[	[	X
ap-5377	33	2	7	7	X
ap-5377	33	3	]	]	X
ap-5377	33	4	many	many	ADJ
ap-5377	33	5	studies	study	NOUN
ap-5377	33	6	processed	process	VERB
ap-5377	33	7	non	non	ADJ
ap-5377	33	8	-	-	ADJ
ap-5377	33	9	epileptic	epileptic	ADJ
ap-5377	33	10	eegs	eeg	NOUN
ap-5377	33	11	(	(	PUNCT
ap-5377	33	12	see	see	VERB
ap-5377	33	13	for	for	ADP
ap-5377	33	14	example	example	NOUN
ap-5377	33	15	[	[	X
ap-5377	33	16	8	8	NUM
ap-5377	33	17	]	]	NUM
ap-5377	33	18	)	)	PUNCT
ap-5377	33	19	.	.	PUNCT
ap-5377	34	1	study	study	VERB
ap-5377	34	2	[	[	X
ap-5377	34	3	9	9	NUM
ap-5377	34	4	]	]	PUNCT
ap-5377	34	5	,	,	PUNCT
ap-5377	34	6	processes	process	VERB
ap-5377	34	7	the	the	DET
ap-5377	34	8	epileptic	epileptic	ADJ
ap-5377	34	9	eeg	eeg	NOUN
ap-5377	34	10	records	record	NOUN
ap-5377	34	11	using	use	VERB
ap-5377	34	12	unsupervised	unsupervised	ADJ
ap-5377	34	13	kohonen	kohonen	PROPN
ap-5377	34	14	’s	’s	PART
ap-5377	34	15	self	self	NOUN
ap-5377	34	16	-	-	PUNCT
ap-5377	34	17	organizing	organize	VERB
ap-5377	34	18	maps	map	NOUN
ap-5377	34	19	,	,	PUNCT
ap-5377	34	20	although	although	SCONJ
ap-5377	34	21	the	the	DET
ap-5377	34	22	authors	author	NOUN
ap-5377	34	23	divide	divide	VERB
ap-5377	34	24	the	the	DET
ap-5377	34	25	signal	signal	NOUN
ap-5377	34	26	into	into	ADP
ap-5377	34	27	only	only	ADV
ap-5377	34	28	two	two	NUM
ap-5377	34	29	classes	class	NOUN
ap-5377	34	30	(	(	PUNCT
ap-5377	34	31	epileptic	epileptic	ADJ
ap-5377	34	32	and	and	CCONJ
ap-5377	34	33	non	non	ADJ
ap-5377	34	34	-	-	ADJ
ap-5377	34	35	epileptic	epileptic	ADJ
ap-5377	34	36	segments	segment	NOUN
ap-5377	34	37	)	)	PUNCT
ap-5377	34	38	.	.	PUNCT
ap-5377	35	1	only	only	ADV
ap-5377	35	2	two	two	NUM
ap-5377	35	3	classes	class	NOUN
ap-5377	35	4	are	be	AUX
ap-5377	35	5	made	make	VERB
ap-5377	35	6	,	,	PUNCT
ap-5377	35	7	for	for	ADP
ap-5377	35	8	example	example	NOUN
ap-5377	35	9	,	,	PUNCT
ap-5377	35	10	in	in	ADP
ap-5377	35	11	studies	study	NOUN
ap-5377	35	12	[	[	X
ap-5377	35	13	10	10	NUM
ap-5377	35	14	]	]	PUNCT
ap-5377	35	15	and	and	CCONJ
ap-5377	35	16	[	[	X
ap-5377	35	17	11	11	NUM
ap-5377	35	18	]	]	PUNCT
ap-5377	35	19	.	.	PUNCT
ap-5377	36	1	the	the	DET
ap-5377	36	2	study	study	NOUN
ap-5377	36	3	[	[	X
ap-5377	36	4	12	12	NUM
ap-5377	36	5	]	]	PUNCT
ap-5377	36	6	used	use	VERB
ap-5377	36	7	five	five	NUM
ap-5377	36	8	unsupervised	unsupervised	ADJ
ap-5377	36	9	algorithms	algorithm	NOUN
ap-5377	36	10	(	(	PUNCT
ap-5377	36	11	among	among	ADP
ap-5377	36	12	other	other	ADJ
ap-5377	36	13	things	thing	NOUN
ap-5377	36	14	k	k	NOUN
ap-5377	36	15	-	-	PUNCT
ap-5377	36	16	means	mean	NOUN
ap-5377	36	17	and	and	CCONJ
ap-5377	36	18	k	k	NOUN
ap-5377	36	19	-	-	NOUN
ap-5377	36	20	medoid	medoid	NOUN
ap-5377	36	21	)	)	PUNCT
ap-5377	36	22	for	for	ADP
ap-5377	36	23	the	the	DET
ap-5377	36	24	automatic	automatic	ADJ
ap-5377	36	25	classification	classification	NOUN
ap-5377	36	26	of	of	ADP
ap-5377	36	27	childhood	childhood	NOUN
ap-5377	36	28	epileptic	epileptic	NOUN
ap-5377	36	29	’s	’s	PART
ap-5377	36	30	eegs	eeg	NOUN
ap-5377	36	31	.	.	PUNCT
ap-5377	37	1	the	the	DET
ap-5377	37	2	results	result	NOUN
ap-5377	37	3	of	of	ADP
ap-5377	37	4	this	this	DET
ap-5377	37	5	study	study	NOUN
ap-5377	37	6	show	show	VERB
ap-5377	37	7	that	that	SCONJ
ap-5377	37	8	k	k	NOUN
ap-5377	37	9	-	-	PUNCT
ap-5377	37	10	means	means	NOUN
ap-5377	37	11	is	be	AUX
ap-5377	37	12	suitable	suitable	ADJ
ap-5377	37	13	for	for	ADP
ap-5377	37	14	clinical	clinical	ADJ
ap-5377	37	15	practice	practice	NOUN
ap-5377	37	16	,	,	PUNCT
ap-5377	37	17	although	although	SCONJ
ap-5377	37	18	the	the	DET
ap-5377	37	19	number	number	NOUN
ap-5377	37	20	of	of	ADP
ap-5377	37	21	searched	searched	ADJ
ap-5377	37	22	classes	class	NOUN
ap-5377	37	23	in	in	ADP
ap-5377	37	24	this	this	DET
ap-5377	37	25	study	study	NOUN
ap-5377	37	26	was	be	AUX
ap-5377	37	27	also	also	ADV
ap-5377	37	28	two	two	NUM
ap-5377	37	29	(	(	PUNCT
ap-5377	37	30	seizer	seizer	X
ap-5377	37	31	and	and	CCONJ
ap-5377	37	32	non	non	ADJ
ap-5377	37	33	-	-	ADJ
ap-5377	37	34	seizer	seizer	ADJ
ap-5377	37	35	class	class	NOUN
ap-5377	37	36	)	)	PUNCT
ap-5377	37	37	.	.	PUNCT
ap-5377	38	1	k	k	X
ap-5377	38	2	-	-	PUNCT
ap-5377	38	3	means	means	PROPN
ap-5377	38	4	is	be	AUX
ap-5377	38	5	the	the	DET
ap-5377	38	6	commonly	commonly	ADV
ap-5377	38	7	used	use	VERB
ap-5377	38	8	method	method	NOUN
ap-5377	38	9	in	in	ADP
ap-5377	38	10	practice	practice	NOUN
ap-5377	38	11	[	[	X
ap-5377	38	12	13	13	NUM
ap-5377	38	13	]	]	PUNCT
ap-5377	38	14	.	.	PUNCT
ap-5377	39	1	in	in	ADP
ap-5377	39	2	the	the	DET
ap-5377	39	3	study	study	NOUN
ap-5377	39	4	[	[	X
ap-5377	39	5	14	14	NUM
ap-5377	39	6	]	]	PUNCT
ap-5377	39	7	,	,	PUNCT
ap-5377	39	8	support	support	NOUN
ap-5377	39	9	vector	vector	NOUN
ap-5377	39	10	machine	machine	NOUN
ap-5377	39	11	and	and	CCONJ
ap-5377	39	12	k	k	NOUN
ap-5377	39	13	-	-	PUNCT
ap-5377	39	14	means	means	NOUN
ap-5377	39	15	with	with	ADP
ap-5377	39	16	multiscale	multiscale	ADJ
ap-5377	39	17	k	k	X
ap-5377	39	18	-	-	PUNCT
ap-5377	39	19	means	means	PROPN
ap-5377	39	20	(	(	PUNCT
ap-5377	39	21	msk	msk	PROPN
ap-5377	39	22	-	-	PUNCT
ap-5377	39	23	means	mean	NOUN
ap-5377	39	24	)	)	PUNCT
ap-5377	39	25	were	be	AUX
ap-5377	39	26	compared	compare	VERB
ap-5377	39	27	.	.	PUNCT
ap-5377	40	1	two	two	NUM
ap-5377	40	2	classes	class	NOUN
ap-5377	40	3	were	be	AUX
ap-5377	40	4	detected	detect	VERB
ap-5377	40	5	(	(	PUNCT
ap-5377	40	6	epileptic	epileptic	ADJ
ap-5377	40	7	and	and	CCONJ
ap-5377	40	8	non	non	ADJ
ap-5377	40	9	-	-	ADJ
ap-5377	40	10	epileptic	epileptic	ADJ
ap-5377	40	11	)	)	PUNCT
ap-5377	40	12	with	with	ADP
ap-5377	40	13	the	the	DET
ap-5377	40	14	best	good	ADJ
ap-5377	40	15	results	result	NOUN
ap-5377	40	16	for	for	ADP
ap-5377	40	17	msk	msk	PROPN
ap-5377	40	18	-	-	PUNCT
ap-5377	40	19	means	mean	NOUN
ap-5377	40	20	.	.	PUNCT
ap-5377	41	1	three	three	NUM
ap-5377	41	2	classes	class	NOUN
ap-5377	41	3	were	be	AUX
ap-5377	41	4	searched	search	VERB
ap-5377	41	5	in	in	ADP
ap-5377	41	6	the	the	DET
ap-5377	41	7	study	study	NOUN
ap-5377	41	8	[	[	X
ap-5377	41	9	15	15	NUM
ap-5377	41	10	]	]	PUNCT
ap-5377	41	11	using	use	VERB
ap-5377	41	12	four	four	NUM
ap-5377	41	13	algorithms	algorithm	NOUN
ap-5377	41	14	(	(	PUNCT
ap-5377	41	15	one	one	NUM
ap-5377	41	16	algorithm	algorithm	NOUN
ap-5377	41	17	was	be	AUX
ap-5377	41	18	unsupervised	unsupervised	ADJ
ap-5377	41	19	k	k	NOUN
ap-5377	41	20	-	-	PUNCT
ap-5377	41	21	means	mean	NOUN
ap-5377	41	22	)	)	PUNCT
ap-5377	41	23	.	.	PUNCT
ap-5377	42	1	however	however	ADV
ap-5377	42	2	,	,	PUNCT
ap-5377	42	3	classes	class	NOUN
ap-5377	42	4	were	be	AUX
ap-5377	42	5	only	only	ADV
ap-5377	42	6	healthy	healthy	ADJ
ap-5377	42	7	,	,	PUNCT
ap-5377	42	8	ictal	ictal	ADJ
ap-5377	42	9	,	,	PUNCT
ap-5377	42	10	and	and	CCONJ
ap-5377	42	11	interictal	interictal	ADJ
ap-5377	42	12	parts	part	NOUN
ap-5377	42	13	of	of	ADP
ap-5377	42	14	the	the	DET
ap-5377	42	15	signal	signal	NOUN
ap-5377	42	16	,	,	PUNCT
ap-5377	42	17	where	where	SCONJ
ap-5377	42	18	eeg	eeg	NOUN
ap-5377	42	19	graphoelements	graphoelement	NOUN
ap-5377	42	20	(	(	PUNCT
ap-5377	42	21	for	for	ADP
ap-5377	42	22	example	example	NOUN
ap-5377	42	23	emg	emg	NOUN
ap-5377	42	24	artifect	artifect	PROPN
ap-5377	42	25	)	)	PUNCT
ap-5377	42	26	were	be	AUX
ap-5377	42	27	not	not	PART
ap-5377	42	28	detected	detect	VERB
ap-5377	42	29	.	.	PUNCT
ap-5377	43	1	unsupervised	unsupervised	ADJ
ap-5377	43	2	k	k	ADJ
ap-5377	43	3	-	-	PUNCT
ap-5377	43	4	means	means	NOUN
ap-5377	43	5	algorithm	algorithm	NOUN
ap-5377	43	6	and	and	CCONJ
ap-5377	43	7	supervised	supervise	VERB
ap-5377	43	8	k	k	PROPN
ap-5377	43	9	-	-	PUNCT
ap-5377	43	10	nn	nn	ADJ
ap-5377	43	11	algorithm	algorithm	NOUN
ap-5377	43	12	were	be	AUX
ap-5377	43	13	compared	compare	VERB
ap-5377	43	14	for	for	ADP
ap-5377	43	15	classifying	classify	VERB
ap-5377	43	16	the	the	DET
ap-5377	43	17	eeg	eeg	NOUN
ap-5377	43	18	graphoelement	graphoelement	NOUN
ap-5377	43	19	in	in	ADP
ap-5377	43	20	the	the	DET
ap-5377	43	21	study	study	NOUN
ap-5377	43	22	[	[	X
ap-5377	43	23	16	16	NUM
ap-5377	43	24	]	]	PUNCT
ap-5377	43	25	.	.	PUNCT
ap-5377	44	1	here	here	ADV
ap-5377	44	2	the	the	DET
ap-5377	44	3	k	k	PROPN
ap-5377	44	4	-	-	PUNCT
ap-5377	44	5	nn	nn	ADJ
ap-5377	44	6	algorithm	algorithm	NOUN
ap-5377	44	7	showed	show	VERB
ap-5377	44	8	better	well	ADJ
ap-5377	44	9	results	result	NOUN
ap-5377	44	10	than	than	ADP
ap-5377	44	11	k	k	NOUN
ap-5377	44	12	-	-	PUNCT
ap-5377	44	13	means	means	NOUN
ap-5377	44	14	.	.	PUNCT
ap-5377	45	1	our	our	PRON
ap-5377	45	2	aim	aim	NOUN
ap-5377	45	3	is	be	AUX
ap-5377	45	4	to	to	PART
ap-5377	45	5	classify	classify	VERB
ap-5377	45	6	all	all	DET
ap-5377	45	7	artefacts	artefact	NOUN
ap-5377	45	8	(	(	PUNCT
ap-5377	45	9	parts	part	NOUN
ap-5377	45	10	of	of	ADP
ap-5377	45	11	the	the	DET
ap-5377	45	12	eeg	eeg	NOUN
ap-5377	45	13	signal	signal	NOUN
ap-5377	45	14	,	,	PUNCT
ap-5377	45	15	which	which	PRON
ap-5377	45	16	do	do	AUX
ap-5377	45	17	not	not	PART
ap-5377	45	18	have	have	VERB
ap-5377	45	19	a	a	DET
ap-5377	45	20	source	source	NOUN
ap-5377	45	21	in	in	ADP
ap-5377	45	22	the	the	DET
ap-5377	45	23	brain	brain	NOUN
ap-5377	45	24	)	)	PUNCT
ap-5377	45	25	,	,	PUNCT
ap-5377	45	26	physiological	physiological	ADJ
ap-5377	45	27	and	and	CCONJ
ap-5377	45	28	pathological	pathological	ADJ
ap-5377	45	29	segments	segment	NOUN
ap-5377	45	30	of	of	ADP
ap-5377	45	31	the	the	DET
ap-5377	45	32	eeg	eeg	NOUN
ap-5377	45	33	record	record	NOUN
ap-5377	45	34	.	.	PUNCT
ap-5377	46	1	we	we	PRON
ap-5377	46	2	create	create	VERB
ap-5377	46	3	a	a	DET
ap-5377	46	4	plugin	plugin	NOUN
ap-5377	46	5	compatible	compatible	ADJ
ap-5377	46	6	with	with	ADP
ap-5377	46	7	the	the	DET
ap-5377	46	8	wavefinder	wavefinder	NOUN
ap-5377	46	9	498	498	NUM
ap-5377	46	10	https://doi.org/10.14311/ap.2019.59.0498	https://doi.org/10.14311/ap.2019.59.0498	PRON
ap-5377	46	11	https://ojs.cvut.cz/ojs/index.php/ap	https://ojs.cvut.cz/ojs/index.php/ap	PROPN
ap-5377	46	12	vol	vol	NOUN
ap-5377	46	13	.	.	PUNCT
ap-5377	47	1	59	59	NUM
ap-5377	47	2	no	no	NOUN
ap-5377	47	3	.	.	PUNCT
ap-5377	48	1	5/2019	5/2019	NUM
ap-5377	48	2	automatic	automatic	ADJ
ap-5377	48	3	eeg	eeg	NOUN
ap-5377	48	4	classification	classification	NOUN
ap-5377	48	5	using	use	VERB
ap-5377	48	6	dbscan	dbscan	NOUN
ap-5377	48	7	and	and	CCONJ
ap-5377	48	8	denclue	denclue	PROPN
ap-5377	48	9	software	software	NOUN
ap-5377	48	10	.	.	PUNCT
ap-5377	49	1	this	this	DET
ap-5377	49	2	software	software	NOUN
ap-5377	49	3	is	be	AUX
ap-5377	49	4	used	use	VERB
ap-5377	49	5	to	to	PART
ap-5377	49	6	describe	describe	VERB
ap-5377	49	7	and	and	CCONJ
ap-5377	49	8	display	display	VERB
ap-5377	49	9	data	datum	NOUN
ap-5377	49	10	at	at	ADP
ap-5377	49	11	the	the	DET
ap-5377	49	12	national	national	PROPN
ap-5377	49	13	institute	institute	PROPN
ap-5377	49	14	of	of	ADP
ap-5377	49	15	mental	mental	ADJ
ap-5377	49	16	health	health	NOUN
ap-5377	49	17	.	.	PUNCT
ap-5377	50	1	the	the	DET
ap-5377	50	2	plugin	plugin	NOUN
ap-5377	50	3	should	should	AUX
ap-5377	50	4	help	help	VERB
ap-5377	50	5	the	the	DET
ap-5377	50	6	physician	physician	NOUN
ap-5377	50	7	to	to	PART
ap-5377	50	8	more	more	ADV
ap-5377	50	9	accurately	accurately	ADV
ap-5377	50	10	estimate	estimate	VERB
ap-5377	50	11	the	the	DET
ap-5377	50	12	interesting	interesting	ADJ
ap-5377	50	13	parts	part	NOUN
ap-5377	50	14	of	of	ADP
ap-5377	50	15	long	long	ADJ
ap-5377	50	16	-	-	PUNCT
ap-5377	50	17	term	term	NOUN
ap-5377	50	18	signals	signal	NOUN
ap-5377	50	19	and	and	CCONJ
ap-5377	50	20	possibly	possibly	ADV
ap-5377	50	21	serve	serve	VERB
ap-5377	50	22	as	as	ADP
ap-5377	50	23	a	a	DET
ap-5377	50	24	tool	tool	NOUN
ap-5377	50	25	for	for	ADP
ap-5377	50	26	the	the	DET
ap-5377	50	27	creation	creation	NOUN
ap-5377	50	28	of	of	ADP
ap-5377	50	29	ethalons	ethalon	NOUN
ap-5377	50	30	.	.	PUNCT
ap-5377	51	1	2	2	X
ap-5377	51	2	.	.	X
ap-5377	51	3	methods	method	NOUN
ap-5377	51	4	2.1	2.1	NUM
ap-5377	51	5	.	.	PUNCT
ap-5377	52	1	data	datum	NOUN
ap-5377	52	2	data	data	PROPN
ap-5377	52	3	simulation	simulation	NOUN
ap-5377	52	4	was	be	AUX
ap-5377	52	5	the	the	DET
ap-5377	52	6	first	first	ADJ
ap-5377	52	7	step	step	NOUN
ap-5377	52	8	of	of	ADP
ap-5377	52	9	the	the	DET
ap-5377	52	10	algorithms	algorithms	NOUN
ap-5377	52	11	testing	test	VERB
ap-5377	52	12	.	.	PUNCT
ap-5377	53	1	our	our	PRON
ap-5377	53	2	simulated	simulated	ADJ
ap-5377	53	3	data	datum	NOUN
ap-5377	53	4	are	be	AUX
ap-5377	53	5	numerical	numerical	ADJ
ap-5377	53	6	values	value	NOUN
ap-5377	53	7	that	that	PRON
ap-5377	53	8	characterize	characterize	VERB
ap-5377	53	9	segments	segment	NOUN
ap-5377	53	10	of	of	ADP
ap-5377	53	11	signal	signal	NOUN
ap-5377	53	12	in	in	ADP
ap-5377	53	13	the	the	DET
ap-5377	53	14	feature	feature	NOUN
ap-5377	53	15	space	space	NOUN
ap-5377	53	16	.	.	PUNCT
ap-5377	54	1	we	we	PRON
ap-5377	54	2	created	create	VERB
ap-5377	54	3	2d	2d	NUM
ap-5377	54	4	training	training	NOUN
ap-5377	54	5	data	datum	NOUN
ap-5377	54	6	in	in	ADP
ap-5377	54	7	matlab	matlab	PROPN
ap-5377	54	8	r2015a	r2015a	PROPN
ap-5377	54	9	.	.	PUNCT
ap-5377	55	1	this	this	DET
ap-5377	55	2	data	data	NOUN
ap-5377	55	3	consists	consist	VERB
ap-5377	55	4	of	of	ADP
ap-5377	55	5	nested	nest	VERB
ap-5377	55	6	and	and	CCONJ
ap-5377	55	7	separated	separate	VERB
ap-5377	55	8	clusters	cluster	NOUN
ap-5377	55	9	.	.	PUNCT
ap-5377	56	1	figure	figure	NOUN
ap-5377	56	2	1	1	NUM
ap-5377	56	3	shows	show	VERB
ap-5377	56	4	four	four	NUM
ap-5377	56	5	examples	example	NOUN
ap-5377	56	6	of	of	ADP
ap-5377	56	7	our	our	PRON
ap-5377	56	8	simulated	simulated	ADJ
ap-5377	56	9	data	datum	NOUN
ap-5377	56	10	.	.	PUNCT
ap-5377	57	1	the	the	DET
ap-5377	57	2	labels	label	NOUN
ap-5377	57	3	are	be	AUX
ap-5377	57	4	made	make	VERB
ap-5377	57	5	optically	optically	ADV
ap-5377	57	6	in	in	ADP
ap-5377	57	7	this	this	DET
ap-5377	57	8	data	data	NOUN
ap-5377	57	9	sets	set	NOUN
ap-5377	57	10	are	be	AUX
ap-5377	57	11	visually	visually	ADV
ap-5377	57	12	separable	separable	ADJ
ap-5377	57	13	.	.	PUNCT
ap-5377	58	1	we	we	PRON
ap-5377	58	2	assumed	assume	VERB
ap-5377	58	3	that	that	SCONJ
ap-5377	58	4	the	the	DET
ap-5377	58	5	eeg	eeg	PROPN
ap-5377	58	6	space	space	NOUN
ap-5377	58	7	contains	contain	VERB
ap-5377	58	8	nested	nested	ADJ
ap-5377	58	9	clusters	cluster	NOUN
ap-5377	58	10	[	[	X
ap-5377	58	11	17	17	NUM
ap-5377	58	12	]	]	PUNCT
ap-5377	58	13	,	,	PUNCT
ap-5377	58	14	therefore	therefore	ADV
ap-5377	58	15	,	,	PUNCT
ap-5377	58	16	we	we	PRON
ap-5377	58	17	tested	test	VERB
ap-5377	58	18	the	the	DET
ap-5377	58	19	ability	ability	NOUN
ap-5377	58	20	of	of	ADP
ap-5377	58	21	algorithms	algorithm	NOUN
ap-5377	58	22	to	to	PART
ap-5377	58	23	separate	separate	VERB
ap-5377	58	24	such	such	ADJ
ap-5377	58	25	spatial	spatial	ADJ
ap-5377	58	26	clusters	cluster	NOUN
ap-5377	58	27	.	.	PUNCT
ap-5377	59	1	training	training	NOUN
ap-5377	59	2	sets	set	NOUN
ap-5377	59	3	demonstrate	demonstrate	VERB
ap-5377	59	4	the	the	DET
ap-5377	59	5	disadvantages	disadvantage	NOUN
ap-5377	59	6	of	of	ADP
ap-5377	59	7	k	k	NOUN
ap-5377	59	8	-	-	PUNCT
ap-5377	59	9	means	mean	VERB
ap-5377	59	10	classification	classification	NOUN
ap-5377	59	11	and	and	CCONJ
ap-5377	59	12	their	their	PRON
ap-5377	59	13	compensation	compensation	NOUN
ap-5377	59	14	using	use	VERB
ap-5377	59	15	dbscan	dbscan	NOUN
ap-5377	59	16	and	and	CCONJ
ap-5377	59	17	denclue	denclue	NOUN
ap-5377	59	18	methods	method	NOUN
ap-5377	59	19	.	.	PUNCT
ap-5377	60	1	real	real	ADJ
ap-5377	60	2	eeg	eeg	PROPN
ap-5377	60	3	records	record	NOUN
ap-5377	60	4	were	be	AUX
ap-5377	60	5	tested	test	VERB
ap-5377	60	6	by	by	ADP
ap-5377	60	7	the	the	DET
ap-5377	60	8	selected	select	VERB
ap-5377	60	9	algorithms	algorithm	NOUN
ap-5377	60	10	in	in	ADP
ap-5377	60	11	the	the	DET
ap-5377	60	12	second	second	ADJ
ap-5377	60	13	part	part	NOUN
ap-5377	60	14	of	of	ADP
ap-5377	60	15	our	our	PRON
ap-5377	60	16	study	study	NOUN
ap-5377	60	17	.	.	PUNCT
ap-5377	61	1	the	the	DET
ap-5377	61	2	data	datum	NOUN
ap-5377	61	3	were	be	AUX
ap-5377	61	4	obtained	obtain	VERB
ap-5377	61	5	from	from	ADP
ap-5377	61	6	patients	patient	NOUN
ap-5377	61	7	from	from	ADP
ap-5377	61	8	bulovka	bulovka	PROPN
ap-5377	61	9	hospital	hospital	NOUN
ap-5377	61	10	in	in	ADP
ap-5377	61	11	prague	prague	PROPN
ap-5377	61	12	.	.	PUNCT
ap-5377	62	1	they	they	PRON
ap-5377	62	2	were	be	AUX
ap-5377	62	3	obtained	obtain	VERB
ap-5377	62	4	on	on	ADP
ap-5377	62	5	the	the	DET
ap-5377	62	6	basis	basis	NOUN
ap-5377	62	7	of	of	ADP
ap-5377	62	8	the	the	DET
ap-5377	62	9	project	project	NOUN
ap-5377	62	10	proposal	proposal	NOUN
ap-5377	62	11	,	,	PUNCT
ap-5377	62	12	which	which	PRON
ap-5377	62	13	was	be	AUX
ap-5377	62	14	approved	approve	VERB
ap-5377	62	15	by	by	ADP
ap-5377	62	16	the	the	DET
ap-5377	62	17	ethics	ethic	NOUN
ap-5377	62	18	committee	committee	PROPN
ap-5377	62	19	of	of	ADP
ap-5377	62	20	bulovka	bulovka	PROPN
ap-5377	62	21	hospital	hospital	NOUN
ap-5377	62	22	on	on	ADP
ap-5377	62	23	the	the	DET
ap-5377	62	24	day	day	NOUN
ap-5377	62	25	28	28	NUM
ap-5377	62	26	.	.	PUNCT
ap-5377	63	1	6	6	NUM
ap-5377	63	2	.	.	NOUN
ap-5377	63	3	2011	2011	NUM
ap-5377	63	4	.	.	PUNCT
ap-5377	64	1	these	these	PRON
ap-5377	64	2	are	be	AUX
ap-5377	64	3	clinical	clinical	ADJ
ap-5377	64	4	examinations	examination	NOUN
ap-5377	64	5	ranging	range	VERB
ap-5377	64	6	from	from	ADP
ap-5377	64	7	15	15	NUM
ap-5377	64	8	to	to	PART
ap-5377	64	9	30	30	NUM
ap-5377	64	10	minutes	minute	NOUN
ap-5377	64	11	(	(	PUNCT
ap-5377	64	12	the	the	DET
ap-5377	64	13	dataset	dataset	NOUN
ap-5377	64	14	was	be	AUX
ap-5377	64	15	not	not	PART
ap-5377	64	16	targeted	target	VERB
ap-5377	64	17	for	for	ADP
ap-5377	64	18	this	this	DET
ap-5377	64	19	study	study	NOUN
ap-5377	64	20	)	)	PUNCT
ap-5377	64	21	.	.	PUNCT
ap-5377	65	1	test	test	NOUN
ap-5377	65	2	data	datum	NOUN
ap-5377	65	3	were	be	AUX
ap-5377	65	4	measured	measure	VERB
ap-5377	65	5	on	on	ADP
ap-5377	65	6	patients	patient	NOUN
ap-5377	65	7	who	who	PRON
ap-5377	65	8	were	be	AUX
ap-5377	65	9	diagnosed	diagnose	VERB
ap-5377	65	10	with	with	ADP
ap-5377	65	11	suspected	suspect	VERB
ap-5377	65	12	epilepsy	epilepsy	NOUN
ap-5377	65	13	disease	disease	NOUN
ap-5377	65	14	(	(	PUNCT
ap-5377	65	15	epileptic	epileptic	ADJ
ap-5377	65	16	attack	attack	NOUN
ap-5377	65	17	did	do	AUX
ap-5377	65	18	not	not	PART
ap-5377	65	19	have	have	VERB
ap-5377	65	20	to	to	PART
ap-5377	65	21	be	be	AUX
ap-5377	65	22	present	present	ADJ
ap-5377	65	23	during	during	ADP
ap-5377	65	24	the	the	DET
ap-5377	65	25	recording	recording	NOUN
ap-5377	65	26	)	)	PUNCT
ap-5377	65	27	.	.	PUNCT
ap-5377	66	1	12	12	NUM
ap-5377	66	2	whole	whole	ADJ
ap-5377	66	3	datasets	dataset	NOUN
ap-5377	66	4	were	be	AUX
ap-5377	66	5	tested	test	VERB
ap-5377	66	6	.	.	PUNCT
ap-5377	67	1	the	the	DET
ap-5377	67	2	tested	test	VERB
ap-5377	67	3	patients	patient	NOUN
ap-5377	67	4	were	be	AUX
ap-5377	67	5	men	man	NOUN
ap-5377	67	6	and	and	CCONJ
ap-5377	67	7	women	woman	NOUN
ap-5377	67	8	aged	age	VERB
ap-5377	67	9	between	between	ADP
ap-5377	67	10	26	26	NUM
ap-5377	67	11	and	and	CCONJ
ap-5377	67	12	60	60	NUM
ap-5377	67	13	years	year	NOUN
ap-5377	67	14	.	.	PUNCT
ap-5377	68	1	the	the	DET
ap-5377	68	2	localization	localization	NOUN
ap-5377	68	3	of	of	ADP
ap-5377	68	4	epilepsy	epilepsy	NOUN
ap-5377	68	5	and	and	CCONJ
ap-5377	68	6	its	its	PRON
ap-5377	68	7	characteristics	characteristic	NOUN
ap-5377	68	8	differed	differ	VERB
ap-5377	68	9	between	between	ADP
ap-5377	68	10	patients	patient	NOUN
ap-5377	68	11	,	,	PUNCT
ap-5377	68	12	we	we	PRON
ap-5377	68	13	expected	expect	VERB
ap-5377	68	14	automatic	automatic	ADJ
ap-5377	68	15	detection	detection	NOUN
ap-5377	68	16	based	base	VERB
ap-5377	68	17	on	on	ADP
ap-5377	68	18	the	the	DET
ap-5377	68	19	occurrence	occurrence	NOUN
ap-5377	68	20	of	of	ADP
ap-5377	68	21	a	a	DET
ap-5377	68	22	different	different	ADJ
ap-5377	68	23	kinds	kind	NOUN
ap-5377	68	24	of	of	ADP
ap-5377	68	25	spikewave	spikewave	NOUN
ap-5377	68	26	complex	complex	NOUN
ap-5377	69	1	[	[	X
ap-5377	69	2	18	18	NUM
ap-5377	69	3	]	]	PUNCT
ap-5377	69	4	.	.	PUNCT
ap-5377	70	1	the	the	DET
ap-5377	70	2	data	datum	NOUN
ap-5377	70	3	were	be	AUX
ap-5377	70	4	analysed	analyse	VERB
ap-5377	70	5	anonymously	anonymously	ADV
ap-5377	70	6	without	without	ADP
ap-5377	70	7	any	any	DET
ap-5377	70	8	assumptions	assumption	NOUN
ap-5377	70	9	about	about	ADP
ap-5377	70	10	the	the	DET
ap-5377	70	11	nature	nature	NOUN
ap-5377	70	12	of	of	ADP
ap-5377	70	13	the	the	DET
ap-5377	70	14	failures	failure	NOUN
ap-5377	70	15	.	.	PUNCT
ap-5377	71	1	2.2	2.2	NUM
ap-5377	71	2	.	.	PUNCT
ap-5377	72	1	preprocessing	preprocesse	VERB
ap-5377	72	2	the	the	DET
ap-5377	72	3	eeg	eeg	NOUN
ap-5377	72	4	signals	signal	NOUN
ap-5377	72	5	were	be	AUX
ap-5377	72	6	recorded	record	VERB
ap-5377	72	7	in	in	ADP
ap-5377	72	8	a	a	DET
ap-5377	72	9	10	10	NUM
ap-5377	72	10	-	-	SYM
ap-5377	72	11	20	20	NUM
ap-5377	72	12	system	system	NOUN
ap-5377	72	13	with	with	ADP
ap-5377	72	14	19	19	NUM
ap-5377	72	15	investigated	investigate	VERB
ap-5377	72	16	channels	channel	NOUN
ap-5377	72	17	with	with	ADP
ap-5377	72	18	a	a	DET
ap-5377	72	19	uni	uni	ADJ
ap-5377	72	20	-	-	ADJ
ap-5377	72	21	polar	polar	ADJ
ap-5377	72	22	connection	connection	NOUN
ap-5377	72	23	(	(	PUNCT
ap-5377	72	24	using	use	VERB
ap-5377	72	25	an	an	DET
ap-5377	72	26	average	average	ADJ
ap-5377	72	27	reference	reference	NOUN
ap-5377	72	28	montage	montage	NOUN
ap-5377	72	29	of	of	ADP
ap-5377	72	30	all	all	DET
ap-5377	72	31	channels	channel	NOUN
ap-5377	72	32	)	)	PUNCT
ap-5377	72	33	on	on	ADP
ap-5377	72	34	the	the	DET
ap-5377	72	35	brainquick	brainquick	NOUN
ap-5377	72	36	system	system	NOUN
ap-5377	72	37	.	.	PUNCT
ap-5377	73	1	the	the	DET
ap-5377	73	2	signal	signal	NOUN
ap-5377	73	3	was	be	AUX
ap-5377	73	4	filtered	filter	VERB
ap-5377	73	5	by	by	ADP
ap-5377	73	6	the	the	DET
ap-5377	73	7	conventional	conventional	ADJ
ap-5377	73	8	analogue	analogue	NOUN
ap-5377	73	9	filter	filter	NOUN
ap-5377	73	10	of	of	ADP
ap-5377	73	11	0	0	NUM
ap-5377	73	12	70hz	70hz	NOUN
ap-5377	73	13	.	.	PUNCT
ap-5377	74	1	the	the	DET
ap-5377	74	2	data	datum	NOUN
ap-5377	74	3	were	be	AUX
ap-5377	74	4	sampled	sample	VERB
ap-5377	74	5	at	at	ADP
ap-5377	74	6	128hz	128hz	NOUN
ap-5377	74	7	and	and	CCONJ
ap-5377	74	8	converted	convert	VERB
ap-5377	74	9	using	use	VERB
ap-5377	74	10	a	a	DET
ap-5377	74	11	12	12	NUM
ap-5377	74	12	bit	bit	NOUN
ap-5377	74	13	converter	converter	NOUN
ap-5377	74	14	.	.	PUNCT
ap-5377	75	1	[	[	X
ap-5377	75	2	19	19	NUM
ap-5377	75	3	]	]	X
ap-5377	75	4	we	we	PRON
ap-5377	75	5	used	use	VERB
ap-5377	75	6	the	the	DET
ap-5377	75	7	program	program	NOUN
ap-5377	75	8	wave	wave	NOUN
ap-5377	75	9	-	-	PUNCT
ap-5377	75	10	finder	finder	NOUN
ap-5377	75	11	(	(	PUNCT
ap-5377	75	12	wf	wf	PROPN
ap-5377	75	13	)	)	PUNCT
ap-5377	76	1	[	[	X
ap-5377	76	2	20	20	NUM
ap-5377	76	3	]	]	PUNCT
ap-5377	76	4	to	to	PART
ap-5377	76	5	segment	segment	VERB
ap-5377	76	6	a	a	DET
ap-5377	76	7	signal	signal	NOUN
ap-5377	76	8	,	,	PUNCT
ap-5377	76	9	compute	compute	VERB
ap-5377	76	10	the	the	DET
ap-5377	76	11	features	feature	NOUN
ap-5377	76	12	for	for	ADP
ap-5377	76	13	individual	individual	ADJ
ap-5377	76	14	segments	segment	NOUN
ap-5377	76	15	,	,	PUNCT
ap-5377	76	16	and	and	CCONJ
ap-5377	76	17	for	for	ADP
ap-5377	76	18	the	the	DET
ap-5377	76	19	visualization	visualization	NOUN
ap-5377	76	20	of	of	ADP
ap-5377	76	21	results	result	NOUN
ap-5377	76	22	.	.	PUNCT
ap-5377	77	1	the	the	DET
ap-5377	77	2	wavefinder	wavefinder	NOUN
ap-5377	77	3	program	program	NOUN
ap-5377	77	4	uses	use	VERB
ap-5377	77	5	adaptive	adaptive	ADJ
ap-5377	77	6	segmentation	segmentation	NOUN
ap-5377	77	7	(	(	PUNCT
ap-5377	77	8	for	for	ADP
ap-5377	77	9	more	more	ADJ
ap-5377	77	10	information	information	NOUN
ap-5377	77	11	about	about	ADP
ap-5377	77	12	the	the	DET
ap-5377	77	13	method	method	NOUN
ap-5377	77	14	,	,	PUNCT
ap-5377	77	15	see	see	VERB
ap-5377	77	16	this	this	DET
ap-5377	77	17	study	study	NOUN
ap-5377	77	18	[	[	X
ap-5377	77	19	21	21	NUM
ap-5377	77	20	]	]	PUNCT
ap-5377	77	21	)	)	PUNCT
ap-5377	77	22	.	.	PUNCT
ap-5377	78	1	the	the	DET
ap-5377	78	2	adaptive	adaptive	ADJ
ap-5377	78	3	segmentation	segmentation	NOUN
ap-5377	78	4	creates	create	VERB
ap-5377	78	5	segments	segment	NOUN
ap-5377	78	6	(	(	PUNCT
ap-5377	78	7	parts	part	NOUN
ap-5377	78	8	of	of	ADP
ap-5377	78	9	the	the	DET
ap-5377	78	10	eeg	eeg	NOUN
ap-5377	78	11	signal	signal	NOUN
ap-5377	78	12	)	)	PUNCT
ap-5377	78	13	with	with	ADP
ap-5377	78	14	different	different	ADJ
ap-5377	78	15	segment	segment	NOUN
ap-5377	78	16	lengths	length	NOUN
ap-5377	78	17	.	.	PUNCT
ap-5377	79	1	every	every	DET
ap-5377	79	2	segment	segment	NOUN
ap-5377	79	3	should	should	AUX
ap-5377	79	4	contain	contain	VERB
ap-5377	79	5	only	only	ADV
ap-5377	79	6	part	part	NOUN
ap-5377	79	7	of	of	ADP
ap-5377	79	8	the	the	DET
ap-5377	79	9	eeg	eeg	NOUN
ap-5377	79	10	signal	signal	NOUN
ap-5377	79	11	with	with	ADP
ap-5377	79	12	the	the	DET
ap-5377	79	13	same	same	ADJ
ap-5377	79	14	characteristic	characteristic	NOUN
ap-5377	79	15	(	(	PUNCT
ap-5377	79	16	for	for	ADP
ap-5377	79	17	example	example	NOUN
ap-5377	79	18	epileptic	epileptic	ADJ
ap-5377	79	19	parameter	parameter	NOUN
ap-5377	79	20	setting	set	VERB
ap-5377	79	21	window	window	NOUN
ap-5377	79	22	length	length	NOUN
ap-5377	79	23	128	128	NUM
ap-5377	79	24	samples	sample	NOUN
ap-5377	79	25	g	g	ADP
ap-5377	79	26	window	window	NOUN
ap-5377	79	27	length	length	NOUN
ap-5377	79	28	15	15	NUM
ap-5377	79	29	samples	sample	NOUN
ap-5377	79	30	step	step	NOUN
ap-5377	79	31	1	1	NUM
ap-5377	79	32	sample	sample	NOUN
ap-5377	79	33	optim	optim	VERB
ap-5377	79	34	1	1	NUM
ap-5377	79	35	[	[	X
ap-5377	79	36	-	-	PUNCT
ap-5377	79	37	]	]	X
ap-5377	79	38	minlength	minlength	NOUN
ap-5377	79	39	64	64	NUM
ap-5377	79	40	samples	sample	NOUN
ap-5377	79	41	number	number	NOUN
ap-5377	79	42	of	of	ADP
ap-5377	79	43	scan	scan	ADJ
ap-5377	79	44	pts	pt	NOUN
ap-5377	79	45	15	15	NUM
ap-5377	79	46	samples	sample	NOUN
ap-5377	79	47	treshold	treshold	VERB
ap-5377	79	48	81	81	NUM
ap-5377	80	1	[	[	X
ap-5377	80	2	-	-	PUNCT
ap-5377	80	3	]	]	X
ap-5377	80	4	max	max	PROPN
ap-5377	80	5	segm	segm	PROPN
ap-5377	80	6	length	length	PROPN
ap-5377	80	7	1024	1024	NUM
ap-5377	80	8	samples	sample	NOUN
ap-5377	80	9	table	table	NOUN
ap-5377	80	10	1	1	NUM
ap-5377	80	11	.	.	PUNCT
ap-5377	81	1	setting	set	VERB
ap-5377	81	2	segmentation	segmentation	NOUN
ap-5377	81	3	parameters	parameter	NOUN
ap-5377	81	4	:	:	PUNCT
ap-5377	81	5	the	the	DET
ap-5377	81	6	parameter	parameter	NOUN
ap-5377	81	7	window	window	NOUN
ap-5377	81	8	length	length	NOUN
ap-5377	81	9	specifies	specify	VERB
ap-5377	81	10	the	the	DET
ap-5377	81	11	length	length	NOUN
ap-5377	81	12	of	of	ADP
ap-5377	81	13	the	the	DET
ap-5377	81	14	associated	associated	ADJ
ap-5377	81	15	window	window	NOUN
ap-5377	81	16	used	use	VERB
ap-5377	81	17	in	in	ADP
ap-5377	81	18	the	the	DET
ap-5377	81	19	adaptive	adaptive	ADJ
ap-5377	81	20	segmentation	segmentation	NOUN
ap-5377	81	21	.	.	PUNCT
ap-5377	82	1	g	g	NOUN
ap-5377	82	2	window	window	NOUN
ap-5377	82	3	length	length	NOUN
ap-5377	82	4	is	be	AUX
ap-5377	82	5	the	the	DET
ap-5377	82	6	length	length	NOUN
ap-5377	82	7	of	of	ADP
ap-5377	82	8	the	the	DET
ap-5377	82	9	window	window	NOUN
ap-5377	82	10	in	in	ADP
ap-5377	82	11	which	which	PRON
ap-5377	82	12	the	the	DET
ap-5377	82	13	exact	exact	ADJ
ap-5377	82	14	position	position	NOUN
ap-5377	82	15	of	of	ADP
ap-5377	82	16	the	the	DET
ap-5377	82	17	maximum	maximum	ADJ
ap-5377	82	18	(	(	PUNCT
ap-5377	82	19	minimum	minimum	NOUN
ap-5377	82	20	is	be	AUX
ap-5377	82	21	3	3	NUM
ap-5377	82	22	points	point	NOUN
ap-5377	82	23	)	)	PUNCT
ap-5377	82	24	is	be	AUX
ap-5377	82	25	searched	search	VERB
ap-5377	82	26	for	for	ADP
ap-5377	82	27	.	.	PUNCT
ap-5377	83	1	the	the	DET
ap-5377	83	2	parameter	parameter	NOUN
ap-5377	83	3	optim	optim	VERB
ap-5377	83	4	turns	turn	VERB
ap-5377	83	5	on	on	ADP
ap-5377	83	6	and	and	CCONJ
ap-5377	83	7	off	off	ADV
ap-5377	83	8	is	be	AUX
ap-5377	83	9	the	the	DET
ap-5377	83	10	optimization	optimization	NOUN
ap-5377	83	11	of	of	ADP
ap-5377	83	12	the	the	DET
ap-5377	83	13	segment	segment	NOUN
ap-5377	83	14	boundary	boundary	NOUN
ap-5377	83	15	.	.	PUNCT
ap-5377	84	1	it	it	PRON
ap-5377	84	2	is	be	AUX
ap-5377	84	3	at	at	ADP
ap-5377	84	4	the	the	DET
ap-5377	84	5	lowest	low	ADJ
ap-5377	84	6	point	point	NOUN
ap-5377	84	7	nearby	nearby	ADV
ap-5377	84	8	.	.	PUNCT
ap-5377	85	1	number	number	NOUN
ap-5377	85	2	of	of	ADP
ap-5377	85	3	scan	scan	PROPN
ap-5377	85	4	pts	pts	X
ap-5377	85	5	is	be	AUX
ap-5377	85	6	the	the	DET
ap-5377	85	7	number	number	NOUN
ap-5377	85	8	of	of	ADP
ap-5377	85	9	points	point	NOUN
ap-5377	85	10	we	we	PRON
ap-5377	85	11	look	look	VERB
ap-5377	85	12	at	at	ADP
ap-5377	85	13	on	on	ADP
ap-5377	85	14	each	each	DET
ap-5377	85	15	side	side	NOUN
ap-5377	85	16	to	to	PART
ap-5377	85	17	obtain	obtain	VERB
ap-5377	85	18	the	the	DET
ap-5377	85	19	minimum	minimum	NOUN
ap-5377	85	20	.	.	PUNCT
ap-5377	86	1	threshold	threshold	NOUN
ap-5377	86	2	specifies	specify	VERB
ap-5377	86	3	the	the	DET
ap-5377	86	4	threshold	threshold	NOUN
ap-5377	86	5	for	for	ADP
ap-5377	86	6	segmentation	segmentation	NOUN
ap-5377	86	7	boundary	boundary	ADJ
ap-5377	86	8	detection	detection	NOUN
ap-5377	86	9	.	.	PUNCT
ap-5377	87	1	minlength	minlength	NOUN
ap-5377	87	2	is	be	AUX
ap-5377	87	3	the	the	DET
ap-5377	87	4	smallest	small	ADJ
ap-5377	87	5	possible	possible	ADJ
ap-5377	87	6	length	length	NOUN
ap-5377	87	7	of	of	ADP
ap-5377	87	8	the	the	DET
ap-5377	87	9	segment	segment	NOUN
ap-5377	87	10	.	.	PUNCT
ap-5377	88	1	activity	activity	NOUN
ap-5377	88	2	)	)	PUNCT
ap-5377	88	3	.	.	PUNCT
ap-5377	89	1	if	if	SCONJ
ap-5377	89	2	one	one	NUM
ap-5377	89	3	segment	segment	NOUN
ap-5377	89	4	contains	contain	VERB
ap-5377	89	5	parts	part	NOUN
ap-5377	89	6	of	of	ADP
ap-5377	89	7	the	the	DET
ap-5377	89	8	eeg	eeg	NOUN
ap-5377	89	9	signal	signal	NOUN
ap-5377	89	10	with	with	ADP
ap-5377	89	11	different	different	ADJ
ap-5377	89	12	characteristic	characteristic	NOUN
ap-5377	89	13	,	,	PUNCT
ap-5377	89	14	it	it	PRON
ap-5377	89	15	is	be	AUX
ap-5377	89	16	marked	mark	VERB
ap-5377	89	17	as	as	ADP
ap-5377	89	18	a	a	DET
ap-5377	89	19	wrongly	wrongly	ADV
ap-5377	89	20	segmented	segment	VERB
ap-5377	89	21	part	part	NOUN
ap-5377	89	22	of	of	ADP
ap-5377	89	23	the	the	DET
ap-5377	89	24	signal	signal	NOUN
ap-5377	89	25	.	.	PUNCT
ap-5377	90	1	the	the	DET
ap-5377	90	2	settings	setting	NOUN
ap-5377	90	3	of	of	ADP
ap-5377	90	4	the	the	DET
ap-5377	90	5	adaptive	adaptive	ADJ
ap-5377	90	6	segmentation	segmentation	NOUN
ap-5377	90	7	used	use	VERB
ap-5377	90	8	in	in	ADP
ap-5377	90	9	this	this	DET
ap-5377	90	10	study	study	NOUN
ap-5377	90	11	can	can	AUX
ap-5377	90	12	be	be	AUX
ap-5377	90	13	seen	see	VERB
ap-5377	90	14	in	in	ADP
ap-5377	90	15	the	the	DET
ap-5377	90	16	table	table	NOUN
ap-5377	90	17	1	1	NUM
ap-5377	90	18	.	.	PUNCT
ap-5377	91	1	the	the	DET
ap-5377	91	2	segments	segment	NOUN
ap-5377	91	3	were	be	AUX
ap-5377	91	4	made	make	VERB
ap-5377	91	5	up	up	ADP
ap-5377	91	6	of	of	ADP
ap-5377	91	7	whole	whole	ADJ
ap-5377	91	8	records	record	NOUN
ap-5377	91	9	and	and	CCONJ
ap-5377	91	10	each	each	DET
ap-5377	91	11	record	record	NOUN
ap-5377	91	12	entered	enter	VERB
ap-5377	91	13	the	the	DET
ap-5377	91	14	classification	classification	NOUN
ap-5377	91	15	separately	separately	ADV
ap-5377	91	16	.	.	PUNCT
ap-5377	92	1	segments	segment	NOUN
ap-5377	92	2	were	be	AUX
ap-5377	92	3	evaluated	evaluate	VERB
ap-5377	92	4	by	by	ADP
ap-5377	92	5	an	an	DET
ap-5377	92	6	expert	expert	NOUN
ap-5377	92	7	.	.	PUNCT
ap-5377	93	1	features	feature	NOUN
ap-5377	93	2	,	,	PUNCT
ap-5377	93	3	which	which	PRON
ap-5377	93	4	we	we	PRON
ap-5377	93	5	are	be	AUX
ap-5377	93	6	using	use	VERB
ap-5377	93	7	,	,	PUNCT
ap-5377	93	8	are	be	AUX
ap-5377	93	9	described	describe	VERB
ap-5377	93	10	in	in	ADP
ap-5377	93	11	the	the	DET
ap-5377	93	12	book	book	NOUN
ap-5377	93	13	[	[	X
ap-5377	93	14	22	22	NUM
ap-5377	93	15	]	]	PUNCT
ap-5377	93	16	.	.	PUNCT
ap-5377	94	1	the	the	DET
ap-5377	94	2	calculation	calculation	NOUN
ap-5377	94	3	of	of	ADP
ap-5377	94	4	these	these	DET
ap-5377	94	5	features	feature	NOUN
ap-5377	94	6	is	be	AUX
ap-5377	94	7	implemented	implement	VERB
ap-5377	94	8	in	in	ADP
ap-5377	94	9	wf	wf	PROPN
ap-5377	94	10	and	and	CCONJ
ap-5377	94	11	they	they	PRON
ap-5377	94	12	are	be	AUX
ap-5377	94	13	used	use	VERB
ap-5377	94	14	in	in	ADP
ap-5377	94	15	clinical	clinical	ADJ
ap-5377	94	16	practice	practice	NOUN
ap-5377	94	17	.	.	PUNCT
ap-5377	95	1	there	there	PRON
ap-5377	95	2	are	be	VERB
ap-5377	95	3	24	24	NUM
ap-5377	95	4	features	feature	NOUN
ap-5377	95	5	which	which	PRON
ap-5377	95	6	are	be	AUX
ap-5377	95	7	normalized	normalize	VERB
ap-5377	95	8	in	in	ADP
ap-5377	95	9	the	the	DET
ap-5377	95	10	interval	interval	NOUN
ap-5377	95	11	〈	〈	PROPN
ap-5377	95	12	0;1	0;1	PROPN
ap-5377	95	13	〉	〉	PROPN
ap-5377	95	14	.	.	PUNCT
ap-5377	96	1	see	see	VERB
ap-5377	96	2	table	table	NOUN
ap-5377	96	3	2	2	NUM
ap-5377	96	4	,	,	PUNCT
ap-5377	96	5	which	which	PRON
ap-5377	96	6	shows	show	VERB
ap-5377	96	7	the	the	DET
ap-5377	96	8	features	feature	NOUN
ap-5377	96	9	that	that	PRON
ap-5377	96	10	are	be	AUX
ap-5377	96	11	specified	specify	VERB
ap-5377	96	12	below	below	ADV
ap-5377	96	13	.	.	PUNCT
ap-5377	97	1	features	feature	NOUN
ap-5377	97	2	create	create	VERB
ap-5377	97	3	a	a	DET
ap-5377	97	4	multidimensional	multidimensional	ADJ
ap-5377	97	5	space	space	NOUN
ap-5377	97	6	that	that	PRON
ap-5377	97	7	is	be	AUX
ap-5377	97	8	counted	count	VERB
ap-5377	97	9	for	for	ADP
ap-5377	97	10	each	each	DET
ap-5377	97	11	eeg	eeg	NOUN
ap-5377	97	12	segment	segment	NOUN
ap-5377	97	13	.	.	PUNCT
ap-5377	98	1	apos	apos	PROPN
ap-5377	98	2	and	and	CCONJ
ap-5377	98	3	aneg	aneg	PROPN
ap-5377	98	4	are	be	AUX
ap-5377	98	5	the	the	DET
ap-5377	98	6	extremes	extreme	NOUN
ap-5377	98	7	of	of	ADP
ap-5377	98	8	an	an	DET
ap-5377	98	9	amplitude	amplitude	NOUN
ap-5377	98	10	for	for	ADP
ap-5377	98	11	a	a	DET
ap-5377	98	12	specific	specific	ADJ
ap-5377	98	13	segment	segment	NOUN
ap-5377	98	14	.	.	PUNCT
ap-5377	99	1	they	they	PRON
ap-5377	99	2	give	give	VERB
ap-5377	99	3	a	a	DET
ap-5377	99	4	value	value	NOUN
ap-5377	99	5	of	of	ADP
ap-5377	99	6	real	real	ADJ
ap-5377	99	7	voltage	voltage	NOUN
ap-5377	99	8	after	after	ADP
ap-5377	99	9	subtracting	subtract	VERB
ap-5377	99	10	the	the	DET
ap-5377	99	11	dc	dc	PROPN
ap-5377	99	12	component	component	NOUN
ap-5377	99	13	(	(	PUNCT
ap-5377	99	14	adc	adc	PROPN
ap-5377	99	15	)	)	PUNCT
ap-5377	99	16	,	,	PUNCT
ap-5377	99	17	shown	show	VERB
ap-5377	99	18	in	in	ADP
ap-5377	99	19	equation	equation	NOUN
ap-5377	99	20	1	1	NUM
ap-5377	100	1	[	[	X
ap-5377	100	2	22	22	NUM
ap-5377	100	3	]	]	SYM
ap-5377	100	4	:	:	PUNCT
ap-5377	100	5	adc	adc	PROPN
ap-5377	101	1	=	=	PUNCT
ap-5377	101	2	∑l	∑l	PROPN
ap-5377	101	3	i=1	i=1	PROPN
ap-5377	101	4	yi	yi	PROPN
ap-5377	101	5	l	l	NOUN
ap-5377	101	6	,	,	PUNCT
ap-5377	101	7	(	(	PUNCT
ap-5377	101	8	1	1	X
ap-5377	101	9	)	)	PUNCT
ap-5377	101	10	where	where	SCONJ
ap-5377	101	11	l	l	NOUN
ap-5377	101	12	is	be	AUX
ap-5377	101	13	the	the	DET
ap-5377	101	14	length	length	NOUN
ap-5377	101	15	of	of	ADP
ap-5377	101	16	the	the	DET
ap-5377	101	17	segment	segment	NOUN
ap-5377	101	18	and	and	CCONJ
ap-5377	101	19	yi	yi	PROPN
ap-5377	101	20	is	be	AUX
ap-5377	101	21	an	an	DET
ap-5377	101	22	i	i	NOUN
ap-5377	101	23	-	-	PUNCT
ap-5377	101	24	th	th	VERB
ap-5377	101	25	amplitude	amplitude	NOUN
ap-5377	101	26	sample	sample	NOUN
ap-5377	101	27	in	in	ADP
ap-5377	101	28	the	the	DET
ap-5377	101	29	segment	segment	NOUN
ap-5377	101	30	.	.	PUNCT
ap-5377	102	1	max1d	max1d	X
ap-5377	102	2	(	(	PUNCT
ap-5377	102	3	equation	equation	NOUN
ap-5377	102	4	no	no	NOUN
ap-5377	102	5	.	.	NOUN
ap-5377	102	6	2	2	NUM
ap-5377	102	7	)	)	PUNCT
ap-5377	102	8	and	and	CCONJ
ap-5377	102	9	md1	md1	NOUN
ap-5377	102	10	(	(	PUNCT
ap-5377	102	11	equation	equation	NOUN
ap-5377	102	12	no	no	NOUN
ap-5377	102	13	.	.	NOUN
ap-5377	102	14	3	3	X
ap-5377	102	15	)	)	PUNCT
ap-5377	102	16	determine	determine	VERB
ap-5377	102	17	maximum	maximum	ADJ
ap-5377	102	18	and	and	CCONJ
ap-5377	102	19	average	average	ADJ
ap-5377	102	20	slope	slope	NOUN
ap-5377	102	21	of	of	ADP
ap-5377	102	22	the	the	DET
ap-5377	102	23	signal	signal	ADJ
ap-5377	102	24	curve	curve	NOUN
ap-5377	102	25	[	[	X
ap-5377	102	26	22	22	NUM
ap-5377	102	27	]	]	X
ap-5377	102	28	:	:	PUNCT
ap-5377	102	29	max1d	max1d	NUM
ap-5377	102	30	=	=	PUNCT
ap-5377	102	31	max(yi+1	max(yi+1	NOUN
ap-5377	102	32	−	−	PROPN
ap-5377	102	33	yi	yi	NOUN
ap-5377	102	34	)	)	PUNCT
ap-5377	102	35	,	,	PUNCT
ap-5377	102	36	(	(	PUNCT
ap-5377	102	37	2	2	X
ap-5377	102	38	)	)	PUNCT
ap-5377	102	39	md1	md1	NOUN
ap-5377	102	40	=	=	SYM
ap-5377	102	41	n∑	n∑	NOUN
ap-5377	102	42	i=1	i=1	PROPN
ap-5377	103	1	(	(	PUNCT
ap-5377	103	2	yi+1	yi+1	PROPN
ap-5377	103	3	−	−	PROPN
ap-5377	104	1	yi	yi	PROPN
ap-5377	104	2	)	)	PUNCT
ap-5377	104	3	n	n	CCONJ
ap-5377	104	4	,	,	PUNCT
ap-5377	104	5	(	(	PUNCT
ap-5377	104	6	3	3	X
ap-5377	104	7	)	)	PUNCT
ap-5377	104	8	where	where	SCONJ
ap-5377	104	9	yi	yi	PROPN
ap-5377	104	10	is	be	AUX
ap-5377	104	11	an	an	DET
ap-5377	104	12	i	i	NOUN
ap-5377	104	13	-	-	PUNCT
ap-5377	104	14	th	th	VERB
ap-5377	104	15	amplitude	amplitude	NOUN
ap-5377	104	16	sample	sample	NOUN
ap-5377	104	17	in	in	ADP
ap-5377	104	18	the	the	DET
ap-5377	104	19	segment	segment	NOUN
ap-5377	104	20	and	and	CCONJ
ap-5377	104	21	n	n	NOUN
ap-5377	104	22	is	be	AUX
ap-5377	104	23	a	a	DET
ap-5377	104	24	number	number	NOUN
ap-5377	104	25	of	of	ADP
ap-5377	104	26	segments	segment	NOUN
ap-5377	104	27	.	.	PUNCT
ap-5377	105	1	499	499	NUM
ap-5377	105	2	m.	m.	NOUN
ap-5377	105	3	piorecký	piorecký	NOUN
ap-5377	105	4	,	,	PUNCT
ap-5377	105	5	j.	j.	PROPN
ap-5377	105	6	štrobl	štrobl	PROPN
ap-5377	105	7	,	,	PUNCT
ap-5377	105	8	v.	v.	ADP
ap-5377	105	9	krajča	krajča	PROPN
ap-5377	105	10	acta	acta	PROPN
ap-5377	105	11	polytechnica	polytechnica	PROPN
ap-5377	105	12	feature	feature	NOUN
ap-5377	105	13	x	x	PUNCT
ap-5377	106	1	[	[	X
ap-5377	106	2	-	-	X
ap-5377	106	3	]	]	X
ap-5377	106	4	0	0	NUM
ap-5377	106	5	0.2	0.2	NUM
ap-5377	106	6	0.4	0.4	NUM
ap-5377	106	7	0.6	0.6	NUM
ap-5377	106	8	0.8	0.8	NUM
ap-5377	106	9	1	1	NUM
ap-5377	106	10	f	f	SYM
ap-5377	106	11	ea	ea	X
ap-5377	106	12	tu	tu	X
ap-5377	106	13	re	re	X
ap-5377	106	14	y	y	PROPN
ap-5377	107	1	[	[	X
ap-5377	107	2	]	]	X
ap-5377	107	3	0	0	NUM
ap-5377	107	4	0.2	0.2	NUM
ap-5377	107	5	0.4	0.4	NUM
ap-5377	107	6	0.6	0.6	NUM
ap-5377	107	7	0.8	0.8	NUM
ap-5377	107	8	1	1	NUM
ap-5377	107	9	feature	feature	NOUN
ap-5377	107	10	x	x	SYM
ap-5377	108	1	[	[	X
ap-5377	108	2	-	-	X
ap-5377	108	3	]	]	X
ap-5377	108	4	0	0	NUM
ap-5377	108	5	0.2	0.2	NUM
ap-5377	108	6	0.4	0.4	NUM
ap-5377	108	7	0.6	0.6	NUM
ap-5377	108	8	0.8	0.8	NUM
ap-5377	108	9	1	1	NUM
ap-5377	108	10	f	f	SYM
ap-5377	108	11	ea	ea	X
ap-5377	108	12	tu	tu	X
ap-5377	108	13	re	re	X
ap-5377	108	14	y	y	PROPN
ap-5377	109	1	[	[	X
ap-5377	109	2	]	]	X
ap-5377	109	3	0	0	NUM
ap-5377	109	4	0.2	0.2	NUM
ap-5377	109	5	0.4	0.4	NUM
ap-5377	109	6	0.6	0.6	NUM
ap-5377	109	7	0.8	0.8	NUM
ap-5377	109	8	1	1	NUM
ap-5377	109	9	feature	feature	NOUN
ap-5377	109	10	x	x	SYM
ap-5377	110	1	[	[	X
ap-5377	110	2	-	-	X
ap-5377	110	3	]	]	X
ap-5377	110	4	0	0	NUM
ap-5377	110	5	0.2	0.2	NUM
ap-5377	110	6	0.4	0.4	NUM
ap-5377	110	7	0.6	0.6	NUM
ap-5377	110	8	0.8	0.8	NUM
ap-5377	110	9	1	1	NUM
ap-5377	110	10	f	f	SYM
ap-5377	110	11	ea	ea	X
ap-5377	110	12	tu	tu	X
ap-5377	110	13	re	re	X
ap-5377	110	14	y	y	PROPN
ap-5377	111	1	[	[	X
ap-5377	111	2	]	]	X
ap-5377	111	3	0	0	NUM
ap-5377	111	4	0.2	0.2	NUM
ap-5377	111	5	0.4	0.4	NUM
ap-5377	111	6	0.6	0.6	NUM
ap-5377	111	7	0.8	0.8	NUM
ap-5377	111	8	1	1	NUM
ap-5377	111	9	feature	feature	NOUN
ap-5377	111	10	x	x	SYM
ap-5377	112	1	[	[	X
ap-5377	112	2	-	-	X
ap-5377	112	3	]	]	X
ap-5377	112	4	0	0	NUM
ap-5377	112	5	0.2	0.2	NUM
ap-5377	112	6	0.4	0.4	NUM
ap-5377	112	7	0.6	0.6	NUM
ap-5377	112	8	0.8	0.8	NUM
ap-5377	112	9	1	1	NUM
ap-5377	112	10	f	f	SYM
ap-5377	112	11	ea	ea	X
ap-5377	112	12	tu	tu	X
ap-5377	112	13	re	re	X
ap-5377	112	14	y	y	PROPN
ap-5377	113	1	[	[	X
ap-5377	113	2	]	]	X
ap-5377	113	3	0	0	NUM
ap-5377	113	4	0.2	0.2	NUM
ap-5377	113	5	0.4	0.4	NUM
ap-5377	113	6	0.6	0.6	NUM
ap-5377	113	7	0.8	0.8	NUM
ap-5377	113	8	1	1	NUM
ap-5377	113	9	figure	figure	NOUN
ap-5377	113	10	1	1	NUM
ap-5377	113	11	.	.	PUNCT
ap-5377	113	12	examples	example	NOUN
ap-5377	113	13	of	of	ADP
ap-5377	113	14	2d	2d	NUM
ap-5377	113	15	simulated	simulate	VERB
ap-5377	113	16	data	datum	NOUN
ap-5377	113	17	in	in	ADP
ap-5377	113	18	the	the	DET
ap-5377	113	19	feature	feature	NOUN
ap-5377	113	20	space	space	NOUN
ap-5377	113	21	used	use	VERB
ap-5377	113	22	in	in	ADP
ap-5377	113	23	this	this	DET
ap-5377	113	24	study	study	NOUN
ap-5377	113	25	to	to	PART
ap-5377	113	26	test	test	VERB
ap-5377	113	27	an	an	DET
ap-5377	113	28	algorithms	algorithm	NOUN
ap-5377	113	29	.	.	PUNCT
ap-5377	114	1	features	feature	VERB
ap-5377	114	2	description	description	NOUN
ap-5377	114	3	sigm	sigm	PROPN
ap-5377	114	4	signal	signal	PROPN
ap-5377	114	5	variability	variability	NOUN
ap-5377	114	6	apos	apos	NOUN
ap-5377	114	7	maximal	maximal	ADJ
ap-5377	114	8	positive	positive	ADJ
ap-5377	114	9	value	value	NOUN
ap-5377	114	10	aneg	aneg	NOUN
ap-5377	114	11	maximal	maximal	ADJ
ap-5377	114	12	negative	negative	ADJ
ap-5377	114	13	value	value	NOUN
ap-5377	114	14	delt1	delt1	NOUN
ap-5377	114	15	part	part	NOUN
ap-5377	114	16	of	of	ADP
ap-5377	114	17	the	the	DET
ap-5377	114	18	delta	delta	NOUN
ap-5377	114	19	(	(	PUNCT
ap-5377	114	20	0.5hz	0.5hz	NUM
ap-5377	115	1	−	−	NUM
ap-5377	115	2	1.5hz	1.5hz	NUM
ap-5377	115	3	)	)	PUNCT
ap-5377	115	4	delt2	delt2	NOUN
ap-5377	115	5	part	part	NOUN
ap-5377	115	6	of	of	ADP
ap-5377	115	7	the	the	DET
ap-5377	115	8	delta	delta	NOUN
ap-5377	115	9	(	(	PUNCT
ap-5377	115	10	2.0hz	2.0hz	PROPN
ap-5377	115	11	−	−	PROPN
ap-5377	115	12	3.5hz	3.5hz	NUM
ap-5377	115	13	)	)	PUNCT
ap-5377	115	14	thet1	thet1	ADP
ap-5377	115	15	part	part	NOUN
ap-5377	115	16	of	of	ADP
ap-5377	115	17	the	the	DET
ap-5377	115	18	theta	theta	NOUN
ap-5377	115	19	(	(	PUNCT
ap-5377	115	20	4.0hz	4.0hz	PROPN
ap-5377	115	21	−	−	NOUN
ap-5377	115	22	5.5hz	5.5hz	NUM
ap-5377	115	23	)	)	PUNCT
ap-5377	115	24	thet2	thet2	NOUN
ap-5377	115	25	part	part	NOUN
ap-5377	115	26	of	of	ADP
ap-5377	115	27	the	the	DET
ap-5377	115	28	theta	theta	NOUN
ap-5377	115	29	(	(	PUNCT
ap-5377	115	30	6.0hz	6.0hz	PROPN
ap-5377	115	31	−	−	NOUN
ap-5377	115	32	7.5hz	7.5hz	NUM
ap-5377	115	33	)	)	PUNCT
ap-5377	115	34	alph1	alph1	NOUN
ap-5377	115	35	part	part	NOUN
ap-5377	115	36	of	of	ADP
ap-5377	115	37	the	the	DET
ap-5377	115	38	alpha	alpha	NOUN
ap-5377	115	39	(	(	PUNCT
ap-5377	115	40	8.0hz	8.0hz	PROPN
ap-5377	115	41	−	−	PROPN
ap-5377	115	42	10.0hz	10.0hz	NUM
ap-5377	115	43	)	)	PUNCT
ap-5377	115	44	alph2	alph2	NOUN
ap-5377	116	1	part	part	NOUN
ap-5377	116	2	of	of	ADP
ap-5377	116	3	the	the	DET
ap-5377	116	4	alpha	alpha	NOUN
ap-5377	116	5	(	(	PUNCT
ap-5377	116	6	10.5hz	10.5hz	NUM
ap-5377	116	7	−	−	PROPN
ap-5377	116	8	13.0hz	13.0hz	NUM
ap-5377	116	9	)	)	PUNCT
ap-5377	116	10	sigma	sigma	VERB
ap-5377	116	11	part	part	NOUN
ap-5377	116	12	of	of	ADP
ap-5377	116	13	the	the	DET
ap-5377	116	14	sigma	sigma	NOUN
ap-5377	116	15	(	(	PUNCT
ap-5377	116	16	18.0hz	18.0hz	PROPN
ap-5377	116	17	−	−	PROPN
ap-5377	116	18	29.0hz	29.0hz	NUM
ap-5377	116	19	)	)	PUNCT
ap-5377	116	20	beta	beta	ADJ
ap-5377	116	21	part	part	NOUN
ap-5377	116	22	of	of	ADP
ap-5377	116	23	the	the	DET
ap-5377	116	24	beta	beta	NOUN
ap-5377	116	25	(	(	PUNCT
ap-5377	116	26	13.5hz	13.5hz	NUM
ap-5377	116	27	−	−	NOUN
ap-5377	116	28	29.0hz	29.0hz	NUM
ap-5377	116	29	)	)	PUNCT
ap-5377	116	30	max1d	max1d	X
ap-5377	117	1	maximum	maximum	NOUN
ap-5377	117	2	of	of	ADP
ap-5377	117	3	the	the	DET
ap-5377	117	4	first	first	ADJ
ap-5377	117	5	derivation	derivation	NOUN
ap-5377	117	6	max2d	max2d	NOUN
ap-5377	117	7	maximum	maximum	NOUN
ap-5377	117	8	of	of	ADP
ap-5377	117	9	the	the	DET
ap-5377	117	10	second	second	ADJ
ap-5377	117	11	derivation	derivation	NOUN
ap-5377	117	12	mf	mf	VERB
ap-5377	117	13	medium	medium	ADJ
ap-5377	117	14	frequency	frequency	NOUN
ap-5377	117	15	md1	md1	NOUN
ap-5377	117	16	medium	medium	NOUN
ap-5377	117	17	of	of	ADP
ap-5377	117	18	the	the	DET
ap-5377	117	19	first	first	ADJ
ap-5377	117	20	derivation	derivation	NOUN
ap-5377	117	21	md2	md2	PROPN
ap-5377	117	22	medium	medium	NOUN
ap-5377	117	23	of	of	ADP
ap-5377	117	24	the	the	DET
ap-5377	117	25	second	second	ADJ
ap-5377	117	26	derivation	derivation	NOUN
ap-5377	117	27	mob	mob	NOUN
ap-5377	117	28	hjorths	hjorth	NOUN
ap-5377	117	29	parameter	parameter	PROPN
ap-5377	117	30	mobility	mobility	PROPN
ap-5377	117	31	comp	comp	PROPN
ap-5377	117	32	hjorths	hjorth	NOUN
ap-5377	117	33	parameter	parameter	PROPN
ap-5377	117	34	complexity	complexity	PROPN
ap-5377	117	35	act	act	PROPN
ap-5377	117	36	hjorths	hjorth	NOUN
ap-5377	117	37	parameter	parameter	NOUN
ap-5377	117	38	activity	activity	NOUN
ap-5377	117	39	lofc	lofc	VERB
ap-5377	117	40	length	length	NOUN
ap-5377	117	41	of	of	ADP
ap-5377	117	42	the	the	DET
ap-5377	117	43	curve	curve	NOUN
ap-5377	117	44	nline	nline	VERB
ap-5377	117	45	a	a	DET
ap-5377	117	46	nonlinear	nonlinear	ADJ
ap-5377	117	47	energy	energy	NOUN
ap-5377	117	48	zc	zc	NOUN
ap-5377	117	49	number	number	NOUN
ap-5377	117	50	of	of	ADP
ap-5377	117	51	the	the	DET
ap-5377	117	52	passes	pass	NOUN
ap-5377	117	53	by	by	ADP
ap-5377	117	54	zero	zero	NUM
ap-5377	117	55	peaks	peak	NOUN
ap-5377	117	56	the	the	DET
ap-5377	117	57	maximum	maximum	ADJ
ap-5377	117	58	peak	peak	NOUN
ap-5377	117	59	frequency	frequency	NOUN
ap-5377	117	60	in	in	ADP
ap-5377	117	61	the	the	DET
ap-5377	117	62	spectrum	spectrum	NOUN
ap-5377	117	63	infp	infp	PROPN
ap-5377	117	64	inflex	inflex	NOUN
ap-5377	117	65	point	point	NOUN
ap-5377	117	66	table	table	NOUN
ap-5377	117	67	2	2	NUM
ap-5377	117	68	.	.	PUNCT
ap-5377	118	1	features	feature	NOUN
ap-5377	118	2	used	use	VERB
ap-5377	118	3	for	for	ADP
ap-5377	118	4	classification	classification	NOUN
ap-5377	118	5	of	of	ADP
ap-5377	118	6	eeg	eeg	NOUN
ap-5377	118	7	segments	segment	NOUN
ap-5377	118	8	in	in	ADP
ap-5377	118	9	this	this	DET
ap-5377	118	10	study	study	NOUN
ap-5377	118	11	.	.	PUNCT
ap-5377	119	1	max2d	max2d	PROPN
ap-5377	119	2	(	(	PUNCT
ap-5377	119	3	equation	equation	NOUN
ap-5377	119	4	no	no	NOUN
ap-5377	119	5	.	.	NOUN
ap-5377	119	6	4	4	NUM
ap-5377	119	7	)	)	PUNCT
ap-5377	119	8	and	and	CCONJ
ap-5377	119	9	md2	md2	PROPN
ap-5377	119	10	(	(	PUNCT
ap-5377	119	11	equation	equation	NOUN
ap-5377	119	12	no	no	NOUN
ap-5377	119	13	.	.	NOUN
ap-5377	119	14	5	5	NUM
ap-5377	119	15	)	)	PUNCT
ap-5377	119	16	determine	determine	VERB
ap-5377	119	17	the	the	DET
ap-5377	119	18	curvature	curvature	NOUN
ap-5377	119	19	of	of	ADP
ap-5377	119	20	the	the	DET
ap-5377	119	21	curve	curve	NOUN
ap-5377	119	22	[	[	X
ap-5377	119	23	22	22	NUM
ap-5377	119	24	]	]	PUNCT
ap-5377	119	25	:	:	PUNCT
ap-5377	119	26	max2d	max2d	PROPN
ap-5377	119	27	=	=	PUNCT
ap-5377	119	28	max(xi+4	max(xi+4	PROPN
ap-5377	120	1	−	−	NUM
ap-5377	120	2	2xi+2	2xi+2	NUM
ap-5377	120	3	+	+	CCONJ
ap-5377	120	4	xi	xi	NUM
ap-5377	120	5	)	)	PUNCT
ap-5377	120	6	,	,	PUNCT
ap-5377	120	7	(	(	PUNCT
ap-5377	120	8	4	4	X
ap-5377	120	9	)	)	PUNCT
ap-5377	120	10	md2	md2	PROPN
ap-5377	121	1	=	=	PUNCT
ap-5377	121	2	n∑	n∑	PROPN
ap-5377	121	3	i=1	i=1	PROPN
ap-5377	121	4	xi+4	xi+4	PROPN
ap-5377	122	1	−	−	NUM
ap-5377	122	2	2xi+2	2xi+2	PROPN
ap-5377	123	1	+	+	CCONJ
ap-5377	123	2	xi	xi	X
ap-5377	123	3	n	n	PROPN
ap-5377	123	4	,	,	PUNCT
ap-5377	123	5	(	(	PUNCT
ap-5377	123	6	5	5	X
ap-5377	123	7	)	)	PUNCT
ap-5377	123	8	where	where	SCONJ
ap-5377	123	9	yi	yi	PROPN
ap-5377	123	10	is	be	AUX
ap-5377	123	11	an	an	DET
ap-5377	123	12	i	i	NOUN
ap-5377	123	13	-	-	PUNCT
ap-5377	123	14	th	th	VERB
ap-5377	123	15	amplitude	amplitude	NOUN
ap-5377	123	16	sample	sample	NOUN
ap-5377	123	17	in	in	ADP
ap-5377	123	18	the	the	DET
ap-5377	123	19	segment	segment	NOUN
ap-5377	123	20	and	and	CCONJ
ap-5377	123	21	n	n	NOUN
ap-5377	123	22	is	be	AUX
ap-5377	123	23	a	a	DET
ap-5377	123	24	number	number	NOUN
ap-5377	123	25	of	of	ADP
ap-5377	123	26	segments	segment	NOUN
ap-5377	123	27	.	.	PUNCT
ap-5377	124	1	hjorth	hjorth	NOUN
ap-5377	124	2	parameters	parameter	NOUN
ap-5377	124	3	are	be	AUX
ap-5377	124	4	indicators	indicator	NOUN
ap-5377	124	5	of	of	ADP
ap-5377	124	6	statistical	statistical	ADJ
ap-5377	124	7	properties	property	NOUN
ap-5377	124	8	used	use	VERB
ap-5377	124	9	to	to	PART
ap-5377	124	10	process	process	VERB
ap-5377	124	11	signals	signal	NOUN
ap-5377	124	12	from	from	ADP
ap-5377	124	13	the	the	DET
ap-5377	124	14	time	time	NOUN
ap-5377	124	15	domain	domain	NOUN
ap-5377	124	16	.	.	PUNCT
ap-5377	125	1	we	we	PRON
ap-5377	125	2	use	use	VERB
ap-5377	125	3	three	three	NUM
ap-5377	125	4	hjorth	hjorth	NOUN
ap-5377	125	5	parameters	parameter	NOUN
ap-5377	125	6	,	,	PUNCT
ap-5377	125	7	activity	activity	NOUN
ap-5377	125	8	,	,	PUNCT
ap-5377	125	9	mobility	mobility	NOUN
ap-5377	125	10	,	,	PUNCT
ap-5377	125	11	and	and	CCONJ
ap-5377	125	12	complexity	complexity	NOUN
ap-5377	125	13	.	.	PUNCT
ap-5377	126	1	activity	activity	NOUN
ap-5377	126	2	represents	represent	VERB
ap-5377	126	3	a	a	DET
ap-5377	126	4	signal	signal	ADJ
ap-5377	126	5	strength	strength	NOUN
ap-5377	126	6	,	,	PUNCT
ap-5377	126	7	scatter	scatter	NOUN
ap-5377	126	8	of	of	ADP
ap-5377	126	9	a	a	DET
ap-5377	126	10	time	time	NOUN
ap-5377	126	11	function	function	NOUN
ap-5377	126	12	[	[	X
ap-5377	126	13	23	23	NUM
ap-5377	126	14	]	]	NOUN
ap-5377	126	15	:	:	PUNCT
ap-5377	126	16	activity	activity	NOUN
ap-5377	126	17	=	=	SYM
ap-5377	126	18	var(y(t	var(y(t	PROPN
ap-5377	126	19	)	)	PUNCT
ap-5377	126	20	)	)	PUNCT
ap-5377	126	21	,	,	PUNCT
ap-5377	126	22	(	(	PUNCT
ap-5377	126	23	6	6	NUM
ap-5377	126	24	)	)	PUNCT
ap-5377	126	25	where	where	SCONJ
ap-5377	126	26	(	(	PUNCT
ap-5377	126	27	y(t	y(t	NOUN
ap-5377	126	28	)	)	PUNCT
ap-5377	126	29	)	)	PUNCT
ap-5377	126	30	represents	represent	VERB
ap-5377	126	31	the	the	DET
ap-5377	126	32	signal	signal	NOUN
ap-5377	126	33	.	.	PUNCT
ap-5377	127	1	mobility	mobility	NOUN
ap-5377	127	2	represents	represent	VERB
ap-5377	127	3	the	the	DET
ap-5377	127	4	mean	mean	ADJ
ap-5377	127	5	frequency	frequency	NOUN
ap-5377	127	6	the	the	DET
ap-5377	127	7	share	share	NOUN
ap-5377	127	8	of	of	ADP
ap-5377	127	9	the	the	DET
ap-5377	127	10	standard	standard	ADJ
ap-5377	127	11	deviation	deviation	NOUN
ap-5377	127	12	of	of	ADP
ap-5377	127	13	the	the	DET
ap-5377	127	14	power	power	NOUN
ap-5377	127	15	spectrum	spectrum	NOUN
ap-5377	127	16	[	[	X
ap-5377	127	17	23	23	NUM
ap-5377	127	18	]	]	X
ap-5377	127	19	:	:	PUNCT
ap-5377	127	20	mobility	mobility	NOUN
ap-5377	127	21	=	=	SYM
ap-5377	127	22	√√√√var	√√√√var	NOUN
ap-5377	127	23	(	(	PUNCT
ap-5377	127	24	y(t	y(t	PROPN
ap-5377	127	25	)	)	PUNCT
ap-5377	127	26	·	·	PUNCT
ap-5377	127	27	dydt	dydt	ADJ
ap-5377	127	28	)	)	PUNCT
ap-5377	127	29	var	var	NOUN
ap-5377	127	30	(	(	PUNCT
ap-5377	127	31	y(t	y(t	NOUN
ap-5377	127	32	)	)	PUNCT
ap-5377	127	33	)	)	PUNCT
ap-5377	127	34	,	,	PUNCT
ap-5377	127	35	(	(	PUNCT
ap-5377	127	36	7	7	X
ap-5377	127	37	)	)	PUNCT
ap-5377	127	38	where	where	SCONJ
ap-5377	127	39	var(y(t	var(y(t	PROPN
ap-5377	127	40	)	)	PUNCT
ap-5377	127	41	)	)	PUNCT
ap-5377	127	42	is	be	AUX
ap-5377	127	43	hjorth	hjorth	NOUN
ap-5377	127	44	parametr	parametr	NOUN
ap-5377	127	45	of	of	ADP
ap-5377	127	46	activity	activity	NOUN
ap-5377	127	47	,	,	PUNCT
ap-5377	127	48	dydt	dydt	NOUN
ap-5377	127	49	is	be	AUX
ap-5377	127	50	the	the	DET
ap-5377	127	51	derivation	derivation	NOUN
ap-5377	127	52	of	of	ADP
ap-5377	127	53	the	the	DET
ap-5377	127	54	amplitude	amplitude	NOUN
ap-5377	127	55	of	of	ADP
ap-5377	127	56	a	a	DET
ap-5377	127	57	segment	segment	NOUN
ap-5377	127	58	in	in	ADP
ap-5377	127	59	time	time	NOUN
ap-5377	127	60	and	and	CCONJ
ap-5377	127	61	y(t	y(t	NUM
ap-5377	127	62	)	)	PUNCT
ap-5377	127	63	is	be	AUX
ap-5377	127	64	the	the	DET
ap-5377	127	65	size	size	NOUN
ap-5377	127	66	of	of	ADP
ap-5377	127	67	the	the	DET
ap-5377	127	68	amplitude	amplitude	NOUN
ap-5377	127	69	.	.	PUNCT
ap-5377	128	1	complexity	complexity	NOUN
ap-5377	128	2	represents	represent	VERB
ap-5377	128	3	a	a	DET
ap-5377	128	4	change	change	NOUN
ap-5377	128	5	in	in	ADP
ap-5377	128	6	frequency	frequency	NOUN
ap-5377	128	7	compared	compare	VERB
ap-5377	128	8	to	to	ADP
ap-5377	128	9	a	a	DET
ap-5377	128	10	pure	pure	ADJ
ap-5377	128	11	sine	sine	ADJ
ap-5377	128	12	wave	wave	NOUN
ap-5377	129	1	[	[	X
ap-5377	129	2	23	23	NUM
ap-5377	129	3	]	]	SYM
ap-5377	129	4	:	:	PUNCT
ap-5377	129	5	complexity	complexity	NOUN
ap-5377	129	6	=	=	SYM
ap-5377	129	7	mobility	mobility	NOUN
ap-5377	129	8	(	(	PUNCT
ap-5377	129	9	y(t	y(t	PROPN
ap-5377	129	10	)	)	PUNCT
ap-5377	129	11	·	·	PUNCT
ap-5377	129	12	dydt	dydt	NOUN
ap-5377	129	13	)	)	PUNCT
ap-5377	129	14	mobility	mobility	NOUN
ap-5377	129	15	(	(	PUNCT
ap-5377	129	16	y(t	y(t	NOUN
ap-5377	129	17	)	)	PUNCT
ap-5377	129	18	)	)	PUNCT
ap-5377	129	19	,	,	PUNCT
ap-5377	129	20	(	(	PUNCT
ap-5377	129	21	8)	8)	NUM
ap-5377	129	22	500	500	NUM
ap-5377	129	23	vol	vol	NOUN
ap-5377	129	24	.	.	PUNCT
ap-5377	130	1	59	59	NUM
ap-5377	130	2	no	no	NOUN
ap-5377	130	3	.	.	PUNCT
ap-5377	131	1	5/2019	5/2019	NUM
ap-5377	131	2	automatic	automatic	ADJ
ap-5377	131	3	eeg	eeg	NOUN
ap-5377	131	4	classification	classification	NOUN
ap-5377	131	5	using	use	VERB
ap-5377	131	6	dbscan	dbscan	NOUN
ap-5377	131	7	and	and	CCONJ
ap-5377	131	8	denclue	denclue	PROPN
ap-5377	131	9	wheremobility	wheremobility	NOUN
ap-5377	131	10	is	be	AUX
ap-5377	131	11	hjorth	hjorth	NOUN
ap-5377	131	12	parametr	parametr	NOUN
ap-5377	131	13	,	,	PUNCT
ap-5377	131	14	dy(t	dy(t	PUNCT
ap-5377	131	15	)	)	PUNCT
ap-5377	131	16	dt	dt	PUNCT
ap-5377	131	17	is	be	AUX
ap-5377	131	18	the	the	DET
ap-5377	131	19	derivation	derivation	NOUN
ap-5377	131	20	of	of	ADP
ap-5377	131	21	amplitudes	amplitude	NOUN
ap-5377	131	22	of	of	ADP
ap-5377	131	23	a	a	DET
ap-5377	131	24	segment	segment	NOUN
ap-5377	131	25	in	in	ADP
ap-5377	131	26	time	time	NOUN
ap-5377	131	27	and	and	CCONJ
ap-5377	131	28	y(t	y(t	NUM
ap-5377	131	29	)	)	PUNCT
ap-5377	131	30	is	be	AUX
ap-5377	131	31	the	the	DET
ap-5377	131	32	amplitude	amplitude	NOUN
ap-5377	131	33	.	.	PUNCT
ap-5377	132	1	lofc	lofc	PROPN
ap-5377	132	2	is	be	AUX
ap-5377	132	3	length	length	NOUN
ap-5377	132	4	of	of	ADP
ap-5377	132	5	the	the	DET
ap-5377	132	6	curve	curve	NOUN
ap-5377	132	7	if	if	SCONJ
ap-5377	132	8	we	we	PRON
ap-5377	132	9	unpack	unpack	VERB
ap-5377	132	10	it	it	PRON
ap-5377	132	11	l	l	NOUN
ap-5377	133	1	=	=	PUNCT
ap-5377	133	2	ns∑	ns∑	NOUN
ap-5377	133	3	i=1	i=1	PROPN
ap-5377	133	4	abs[y(i)−	abs[y(i)−	PROPN
ap-5377	133	5	y(i+	y(i+	NUM
ap-5377	133	6	1	1	NUM
ap-5377	133	7	)	)	PUNCT
ap-5377	133	8	]	]	PUNCT
ap-5377	133	9	,	,	PUNCT
ap-5377	133	10	(	(	PUNCT
ap-5377	133	11	9	9	X
ap-5377	133	12	)	)	PUNCT
ap-5377	133	13	where	where	SCONJ
ap-5377	133	14	ns	ns	ADJ
ap-5377	133	15	is	be	AUX
ap-5377	133	16	a	a	DET
ap-5377	133	17	number	number	NOUN
ap-5377	133	18	of	of	ADP
ap-5377	133	19	samples	sample	NOUN
ap-5377	133	20	in	in	ADP
ap-5377	133	21	the	the	DET
ap-5377	133	22	segment	segment	NOUN
ap-5377	133	23	and	and	CCONJ
ap-5377	133	24	y(i	y(i	PROPN
ap-5377	133	25	)	)	PUNCT
ap-5377	133	26	is	be	AUX
ap-5377	133	27	i	i	PRON
ap-5377	133	28	-	-	PUNCT
ap-5377	133	29	th	th	VERB
ap-5377	133	30	amplitude	amplitude	NOUN
ap-5377	133	31	sample	sample	NOUN
ap-5377	133	32	in	in	ADP
ap-5377	133	33	the	the	DET
ap-5377	133	34	segment	segment	NOUN
ap-5377	133	35	.	.	PUNCT
ap-5377	134	1	number	number	NOUN
ap-5377	134	2	of	of	ADP
ap-5377	134	3	passes	pass	NOUN
ap-5377	134	4	by	by	ADP
ap-5377	134	5	zero	zero	NUM
ap-5377	134	6	indicates	indicate	VERB
ap-5377	134	7	how	how	SCONJ
ap-5377	134	8	many	many	ADJ
ap-5377	134	9	times	time	NOUN
ap-5377	134	10	the	the	DET
ap-5377	134	11	curve	curve	NOUN
ap-5377	134	12	passed	pass	VERB
ap-5377	134	13	from	from	ADP
ap-5377	134	14	positive	positive	ADJ
ap-5377	134	15	to	to	ADP
ap-5377	134	16	negative	negative	ADJ
ap-5377	134	17	and	and	CCONJ
ap-5377	134	18	vice	vice	ADV
ap-5377	134	19	versa	versa	ADV
ap-5377	134	20	.	.	PUNCT
ap-5377	135	1	peaks	peak	NOUN
ap-5377	135	2	indicates	indicate	VERB
ap-5377	135	3	the	the	DET
ap-5377	135	4	number	number	NOUN
ap-5377	135	5	of	of	ADP
ap-5377	135	6	peaks	peak	NOUN
ap-5377	135	7	in	in	ADP
ap-5377	135	8	the	the	DET
ap-5377	135	9	specific	specific	ADJ
ap-5377	135	10	segment	segment	NOUN
ap-5377	135	11	.	.	PUNCT
ap-5377	136	1	nline	nline	PROPN
ap-5377	136	2	characterizes	characterize	VERB
ap-5377	136	3	the	the	DET
ap-5377	136	4	signal	signal	NOUN
ap-5377	136	5	in	in	ADP
ap-5377	136	6	terms	term	NOUN
ap-5377	136	7	of	of	ADP
ap-5377	136	8	energy	energy	NOUN
ap-5377	136	9	.	.	PUNCT
ap-5377	137	1	it	it	PRON
ap-5377	137	2	indicates	indicate	VERB
ap-5377	137	3	the	the	DET
ap-5377	137	4	average	average	ADJ
ap-5377	137	5	power	power	NOUN
ap-5377	137	6	in	in	ADP
ap-5377	137	7	the	the	DET
ap-5377	137	8	band	band	NOUN
ap-5377	137	9	where	where	SCONJ
ap-5377	137	10	the	the	DET
ap-5377	137	11	80	80	NUM
ap-5377	137	12	%	%	NOUN
ap-5377	137	13	of	of	ADP
ap-5377	137	14	the	the	DET
ap-5377	137	15	total	total	ADJ
ap-5377	137	16	energy	energy	NOUN
ap-5377	137	17	of	of	ADP
ap-5377	137	18	the	the	DET
ap-5377	137	19	spectrum	spectrum	NOUN
ap-5377	137	20	is	be	AUX
ap-5377	137	21	concentrated	concentrate	VERB
ap-5377	137	22	[	[	X
ap-5377	137	23	24	24	NUM
ap-5377	137	24	]	]	SYM
ap-5377	137	25	:	:	PUNCT
ap-5377	137	26	nline(i	nline(i	NUM
ap-5377	137	27	)	)	PUNCT
ap-5377	137	28	=	=	SYM
ap-5377	137	29	y2(i)−	y2(i)−	NUM
ap-5377	137	30	y(i−	y(i−	PROPN
ap-5377	137	31	1)y(i+	1)y(i+	PROPN
ap-5377	137	32	1	1	NUM
ap-5377	137	33	)	)	PUNCT
ap-5377	137	34	,	,	PUNCT
ap-5377	137	35	(	(	PUNCT
ap-5377	137	36	10	10	NUM
ap-5377	137	37	)	)	PUNCT
ap-5377	137	38	where	where	SCONJ
ap-5377	137	39	y(i	y(i	NOUN
ap-5377	137	40	)	)	PUNCT
ap-5377	137	41	is	be	AUX
ap-5377	137	42	the	the	DET
ap-5377	137	43	amplitude	amplitude	NOUN
ap-5377	137	44	in	in	ADP
ap-5377	137	45	the	the	DET
ap-5377	137	46	i	i	PROPN
ap-5377	137	47	-	-	PUNCT
ap-5377	137	48	th	th	X
ap-5377	137	49	sample	sample	NOUN
ap-5377	137	50	in	in	ADP
ap-5377	137	51	a	a	DET
ap-5377	137	52	segment	segment	NOUN
ap-5377	137	53	.	.	PUNCT
ap-5377	138	1	all	all	PRON
ap-5377	138	2	of	of	ADP
ap-5377	138	3	the	the	DET
ap-5377	138	4	features	feature	NOUN
ap-5377	138	5	were	be	AUX
ap-5377	138	6	normalized	normalize	VERB
ap-5377	138	7	to	to	PART
ap-5377	138	8	create	create	VERB
ap-5377	138	9	a	a	DET
ap-5377	138	10	single	single	ADJ
ap-5377	138	11	feature	feature	NOUN
ap-5377	138	12	space	space	NOUN
ap-5377	138	13	for	for	ADP
ap-5377	138	14	the	the	DET
ap-5377	138	15	classification	classification	NOUN
ap-5377	138	16	.	.	PUNCT
ap-5377	139	1	normalization	normalization	NOUN
ap-5377	139	2	was	be	AUX
ap-5377	139	3	realized	realize	VERB
ap-5377	139	4	by	by	ADP
ap-5377	139	5	the	the	DET
ap-5377	139	6	minimum	minimum	NOUN
ap-5377	139	7	and	and	CCONJ
ap-5377	139	8	maximum	maximum	ADJ
ap-5377	139	9	by	by	ADP
ap-5377	139	10	the	the	DET
ap-5377	139	11	following	follow	VERB
ap-5377	139	12	equation	equation	NOUN
ap-5377	139	13	:	:	PUNCT
ap-5377	140	1	y	y	PROPN
ap-5377	140	2	(	(	PUNCT
ap-5377	140	3	i	i	NOUN
ap-5377	140	4	)	)	PUNCT
ap-5377	140	5	=	=	SYM
ap-5377	140	6	x(i)−min(x	x(i)−min(x	NUM
ap-5377	140	7	)	)	PUNCT
ap-5377	140	8	max(x)−min(x	max(x)−min(x	NUM
ap-5377	140	9	)	)	PUNCT
ap-5377	140	10	,	,	PUNCT
ap-5377	140	11	(	(	PUNCT
ap-5377	140	12	11	11	NUM
ap-5377	140	13	)	)	PUNCT
ap-5377	140	14	where	where	SCONJ
ap-5377	140	15	min	min	NOUN
ap-5377	140	16	and	and	CCONJ
ap-5377	140	17	max	max	PROPN
ap-5377	140	18	are	be	AUX
ap-5377	140	19	the	the	DET
ap-5377	140	20	minimum	minimum	ADJ
ap-5377	140	21	and	and	CCONJ
ap-5377	140	22	maximum	maximum	ADJ
ap-5377	140	23	values	value	NOUN
ap-5377	140	24	in	in	ADP
ap-5377	140	25	x	x	SYM
ap-5377	140	26	dataset	dataset	NOUN
ap-5377	140	27	.	.	PUNCT
ap-5377	141	1	2.3	2.3	NUM
ap-5377	141	2	.	.	PUNCT
ap-5377	142	1	k	k	X
ap-5377	142	2	-	-	PUNCT
ap-5377	142	3	means	mean	VERB
ap-5377	142	4	we	we	PRON
ap-5377	142	5	used	use	VERB
ap-5377	142	6	the	the	DET
ap-5377	142	7	k	k	NOUN
ap-5377	142	8	-	-	PUNCT
ap-5377	142	9	means	means	NOUN
ap-5377	142	10	algorithm	algorithm	NOUN
ap-5377	142	11	like	like	ADP
ap-5377	142	12	a	a	DET
ap-5377	142	13	commonly	commonly	ADV
ap-5377	142	14	used	use	VERB
ap-5377	142	15	(	(	PUNCT
ap-5377	142	16	on	on	ADP
ap-5377	142	17	the	the	DET
ap-5377	142	18	eeg	eeg	PROPN
ap-5377	142	19	data	data	NOUN
ap-5377	142	20	classification	classification	NOUN
ap-5377	142	21	in	in	ADP
ap-5377	142	22	clinical	clinical	ADJ
ap-5377	142	23	practice	practice	NOUN
ap-5377	142	24	)	)	PUNCT
ap-5377	142	25	unsupervised	unsupervised	ADJ
ap-5377	142	26	method	method	NOUN
ap-5377	142	27	for	for	ADP
ap-5377	142	28	a	a	DET
ap-5377	142	29	comparison	comparison	NOUN
ap-5377	142	30	with	with	ADP
ap-5377	142	31	testing	testing	NOUN
ap-5377	142	32	algorithms	algorithm	NOUN
ap-5377	142	33	.	.	PUNCT
ap-5377	143	1	the	the	DET
ap-5377	143	2	unsupervised	unsupervised	ADJ
ap-5377	143	3	algorithm	algorithm	NOUN
ap-5377	143	4	was	be	AUX
ap-5377	143	5	chosen	choose	VERB
ap-5377	143	6	because	because	SCONJ
ap-5377	143	7	dbscan	dbscan	NOUN
ap-5377	143	8	and	and	CCONJ
ap-5377	143	9	denclue	denclue	NOUN
ap-5377	143	10	are	be	AUX
ap-5377	143	11	also	also	ADV
ap-5377	143	12	unsupervised	unsupervised	ADJ
ap-5377	143	13	.	.	PUNCT
ap-5377	144	1	the	the	DET
ap-5377	144	2	k	k	NOUN
ap-5377	144	3	-	-	PUNCT
ap-5377	144	4	means	means	NOUN
ap-5377	144	5	algorithm	algorithm	NOUN
ap-5377	144	6	separate	separate	ADJ
ap-5377	144	7	segments	segment	NOUN
ap-5377	144	8	to	to	ADP
ap-5377	144	9	the	the	DET
ap-5377	144	10	classes	class	NOUN
ap-5377	144	11	using	use	VERB
ap-5377	144	12	distance	distance	NOUN
ap-5377	144	13	computing	computing	NOUN
ap-5377	144	14	.	.	PUNCT
ap-5377	145	1	you	you	PRON
ap-5377	145	2	can	can	AUX
ap-5377	145	3	see	see	VERB
ap-5377	145	4	,	,	PUNCT
ap-5377	145	5	for	for	ADP
ap-5377	145	6	example	example	NOUN
ap-5377	145	7	,	,	PUNCT
ap-5377	145	8	[	[	X
ap-5377	145	9	25	25	NUM
ap-5377	145	10	]	]	PUNCT
ap-5377	145	11	for	for	ADP
ap-5377	145	12	more	more	ADJ
ap-5377	145	13	details	detail	NOUN
ap-5377	145	14	about	about	ADP
ap-5377	145	15	the	the	DET
ap-5377	145	16	k	k	NOUN
ap-5377	145	17	-	-	PUNCT
ap-5377	145	18	means	mean	VERB
ap-5377	145	19	principle	principle	NOUN
ap-5377	145	20	.	.	PUNCT
ap-5377	146	1	we	we	PRON
ap-5377	146	2	used	use	VERB
ap-5377	146	3	the	the	DET
ap-5377	146	4	k	k	NOUN
ap-5377	146	5	-	-	PUNCT
ap-5377	146	6	means	means	NOUN
ap-5377	146	7	matlab	matlab	PROPN
ap-5377	146	8	r2015a	r2015a	NOUN
ap-5377	146	9	function	function	NOUN
ap-5377	146	10	for	for	ADP
ap-5377	146	11	simulated	simulated	ADJ
ap-5377	146	12	data	datum	NOUN
ap-5377	146	13	in	in	ADP
ap-5377	146	14	this	this	DET
ap-5377	146	15	study	study	NOUN
ap-5377	146	16	.	.	PUNCT
ap-5377	147	1	the	the	DET
ap-5377	147	2	k	k	NOUN
ap-5377	147	3	-	-	PUNCT
ap-5377	147	4	means	means	NOUN
ap-5377	147	5	from	from	ADP
ap-5377	147	6	wf	wf	PROPN
ap-5377	147	7	program	program	NOUN
ap-5377	147	8	was	be	AUX
ap-5377	147	9	used	use	VERB
ap-5377	147	10	for	for	ADP
ap-5377	147	11	the	the	DET
ap-5377	147	12	automatic	automatic	ADJ
ap-5377	147	13	classification	classification	NOUN
ap-5377	147	14	of	of	ADP
ap-5377	147	15	a	a	DET
ap-5377	147	16	real	real	ADJ
ap-5377	147	17	eeg	eeg	NOUN
ap-5377	147	18	record	record	NOUN
ap-5377	147	19	in	in	ADP
ap-5377	147	20	this	this	DET
ap-5377	147	21	study	study	NOUN
ap-5377	147	22	.	.	PUNCT
ap-5377	148	1	the	the	DET
ap-5377	148	2	program	program	NOUN
ap-5377	148	3	wf	wf	PROPN
ap-5377	148	4	exploits	exploit	VERB
ap-5377	148	5	k	k	NOUN
ap-5377	148	6	-	-	PUNCT
ap-5377	148	7	means	means	NOUN
ap-5377	148	8	in	in	ADP
ap-5377	148	9	clinical	clinical	ADJ
ap-5377	148	10	practice	practice	NOUN
ap-5377	148	11	and	and	CCONJ
ap-5377	148	12	we	we	PRON
ap-5377	148	13	can	can	AUX
ap-5377	148	14	use	use	VERB
ap-5377	148	15	them	they	PRON
ap-5377	148	16	to	to	PART
ap-5377	148	17	compare	compare	VERB
ap-5377	148	18	k	k	NOUN
ap-5377	148	19	-	-	PUNCT
ap-5377	148	20	means	means	NOUN
ap-5377	148	21	with	with	ADP
ap-5377	148	22	density	density	NOUN
ap-5377	148	23	based	base	VERB
ap-5377	148	24	algorithms	algorithm	NOUN
ap-5377	148	25	.	.	PUNCT
ap-5377	149	1	2.4	2.4	NUM
ap-5377	149	2	.	.	PUNCT
ap-5377	150	1	dbscan	dbscan	PROPN
ap-5377	150	2	density	density	NOUN
ap-5377	150	3	based	base	VERB
ap-5377	150	4	algorithms	algorithm	NOUN
ap-5377	150	5	take	take	VERB
ap-5377	150	6	advantage	advantage	NOUN
ap-5377	150	7	of	of	ADP
ap-5377	150	8	different	different	ADJ
ap-5377	150	9	density	density	NOUN
ap-5377	150	10	distributions	distribution	NOUN
ap-5377	150	11	of	of	ADP
ap-5377	150	12	classified	classified	ADJ
ap-5377	150	13	objects	object	NOUN
ap-5377	150	14	in	in	ADP
ap-5377	150	15	space	space	NOUN
ap-5377	150	16	to	to	PART
ap-5377	150	17	separate	separate	VERB
ap-5377	150	18	individual	individual	ADJ
ap-5377	150	19	datasets	dataset	NOUN
ap-5377	150	20	.	.	PUNCT
ap-5377	151	1	objects	object	NOUN
ap-5377	151	2	are	be	AUX
ap-5377	151	3	,	,	PUNCT
ap-5377	151	4	in	in	ADP
ap-5377	151	5	our	our	PRON
ap-5377	151	6	case	case	NOUN
ap-5377	151	7	,	,	PUNCT
ap-5377	151	8	the	the	DET
ap-5377	151	9	segments	segment	NOUN
ap-5377	151	10	of	of	ADP
ap-5377	151	11	eeg	eeg	NOUN
ap-5377	151	12	signals	signal	NOUN
ap-5377	151	13	.	.	PUNCT
ap-5377	152	1	dbscan	dbscan	PROPN
ap-5377	152	2	classifies	classify	VERB
ap-5377	152	3	objects	object	NOUN
ap-5377	152	4	based	base	VERB
ap-5377	152	5	on	on	ADP
ap-5377	152	6	density	density	NOUN
ap-5377	152	7	,	,	PUNCT
ap-5377	152	8	so	so	SCONJ
ap-5377	152	9	a	a	DET
ap-5377	152	10	range	range	NOUN
ap-5377	152	11	of	of	ADP
ap-5377	152	12	objects	object	NOUN
ap-5377	152	13	with	with	ADP
ap-5377	152	14	a	a	DET
ap-5377	152	15	similar	similar	ADJ
ap-5377	152	16	density	density	NOUN
ap-5377	152	17	distribution	distribution	NOUN
ap-5377	152	18	is	be	AUX
ap-5377	152	19	classified	classify	VERB
ap-5377	152	20	in	in	ADP
ap-5377	152	21	the	the	DET
ap-5377	152	22	same	same	ADJ
ap-5377	152	23	class	class	NOUN
ap-5377	152	24	.	.	PUNCT
ap-5377	153	1	density	density	NOUN
ap-5377	153	2	means	mean	VERB
ap-5377	153	3	the	the	DET
ap-5377	153	4	number	number	NOUN
ap-5377	153	5	of	of	ADP
ap-5377	153	6	points	point	NOUN
ap-5377	153	7	in	in	ADP
ap-5377	153	8	the	the	DET
ap-5377	153	9	unit	unit	NOUN
ap-5377	153	10	area	area	NOUN
ap-5377	153	11	of	of	ADP
ap-5377	153	12	the	the	DET
ap-5377	153	13	feature	feature	NOUN
ap-5377	153	14	space	space	NOUN
ap-5377	153	15	.	.	PUNCT
ap-5377	154	1	in	in	ADP
ap-5377	154	2	order	order	NOUN
ap-5377	154	3	to	to	PART
ap-5377	154	4	avoid	avoid	VERB
ap-5377	154	5	classifying	classify	VERB
ap-5377	154	6	object	object	NOUN
ap-5377	154	7	regions	region	NOUN
ap-5377	154	8	from	from	ADP
ap-5377	154	9	each	each	DET
ap-5377	154	10	other	other	ADJ
ap-5377	154	11	in	in	ADP
ap-5377	154	12	a	a	DET
ap-5377	154	13	very	very	ADV
ap-5377	154	14	distant	distant	ADJ
ap-5377	154	15	space	space	NOUN
ap-5377	154	16	,	,	PUNCT
ap-5377	154	17	the	the	DET
ap-5377	154	18	dbscan	dbscan	NOUN
ap-5377	154	19	defines	define	VERB
ap-5377	154	20	a	a	DET
ap-5377	154	21	cluster	cluster	NOUN
ap-5377	154	22	as	as	ADP
ap-5377	154	23	a	a	DET
ap-5377	154	24	high	high	ADJ
ap-5377	154	25	dot	dot	NOUN
ap-5377	154	26	density	density	NOUN
ap-5377	154	27	region	region	NOUN
ap-5377	154	28	that	that	PRON
ap-5377	154	29	is	be	AUX
ap-5377	154	30	separated	separate	VERB
ap-5377	154	31	by	by	ADP
ap-5377	154	32	a	a	DET
ap-5377	154	33	low	low	ADJ
ap-5377	154	34	density	density	NOUN
ap-5377	154	35	location	location	NOUN
ap-5377	154	36	.	.	PUNCT
ap-5377	155	1	the	the	DET
ap-5377	155	2	input	input	NOUN
ap-5377	155	3	parameters	parameter	NOUN
ap-5377	155	4	of	of	ADP
ap-5377	155	5	the	the	DET
ap-5377	155	6	algorithm	algorithm	NOUN
ap-5377	155	7	are	be	AUX
ap-5377	155	8	the	the	DET
ap-5377	155	9	radius	radius	NOUN
ap-5377	155	10	(	(	PUNCT
ap-5377	155	11	eps	eps	PROPN
ap-5377	155	12	)	)	PUNCT
ap-5377	155	13	and	and	CCONJ
ap-5377	155	14	the	the	DET
ap-5377	155	15	number	number	NOUN
ap-5377	155	16	of	of	ADP
ap-5377	155	17	objects	object	NOUN
ap-5377	155	18	in	in	ADP
ap-5377	155	19	it	it	PRON
ap-5377	155	20	(	(	PUNCT
ap-5377	155	21	npts	npt	NOUN
ap-5377	155	22	)	)	PUNCT
ap-5377	155	23	.	.	PUNCT
ap-5377	156	1	compared	compare	VERB
ap-5377	156	2	to	to	ADP
ap-5377	156	3	the	the	DET
ap-5377	156	4	k	k	NOUN
ap-5377	156	5	-	-	PUNCT
ap-5377	156	6	means	means	NOUN
ap-5377	156	7	algorithm	algorithm	NOUN
ap-5377	156	8	,	,	PUNCT
ap-5377	156	9	the	the	DET
ap-5377	156	10	number	number	NOUN
ap-5377	156	11	of	of	ADP
ap-5377	156	12	clusters	cluster	NOUN
ap-5377	156	13	is	be	AUX
ap-5377	156	14	the	the	DET
ap-5377	156	15	default	default	NOUN
ap-5377	156	16	rather	rather	ADV
ap-5377	156	17	than	than	ADP
ap-5377	156	18	the	the	DET
ap-5377	156	19	input	input	NOUN
ap-5377	156	20	parameter	parameter	NOUN
ap-5377	156	21	.	.	PUNCT
ap-5377	157	1	it	it	PRON
ap-5377	157	2	also	also	ADV
ap-5377	157	3	depends	depend	VERB
ap-5377	157	4	on	on	ADP
ap-5377	157	5	the	the	DET
ap-5377	157	6	initiation	initiation	NOUN
ap-5377	157	7	site	site	NOUN
ap-5377	157	8	,	,	PUNCT
ap-5377	157	9	in	in	ADP
ap-5377	157	10	a	a	DET
ap-5377	157	11	similar	similar	ADJ
ap-5377	157	12	way	way	NOUN
ap-5377	157	13	as	as	SCONJ
ap-5377	157	14	we	we	PRON
ap-5377	157	15	perform	perform	VERB
ap-5377	157	16	a	a	DET
ap-5377	157	17	count	count	NOUN
ap-5377	157	18	with	with	ADP
ap-5377	157	19	the	the	DET
ap-5377	157	20	random	random	ADJ
ap-5377	157	21	centre	centre	NOUN
ap-5377	157	22	of	of	ADP
ap-5377	157	23	clusters	cluster	NOUN
ap-5377	157	24	in	in	ADP
ap-5377	157	25	the	the	DET
ap-5377	157	26	case	case	NOUN
ap-5377	157	27	of	of	ADP
ap-5377	157	28	k	k	NOUN
ap-5377	157	29	-	-	PUNCT
ap-5377	157	30	means	mean	NOUN
ap-5377	157	31	.	.	PUNCT
ap-5377	158	1	dbscan	dbscan	PROPN
ap-5377	158	2	searches	search	NOUN
ap-5377	158	3	in	in	ADP
ap-5377	158	4	the	the	DET
ap-5377	158	5	specified	specified	ADJ
ap-5377	158	6	radius	radius	NOUN
ap-5377	158	7	of	of	ADP
ap-5377	158	8	the	the	DET
ap-5377	158	9	objects	object	NOUN
ap-5377	158	10	that	that	PRON
ap-5377	158	11	fall	fall	VERB
ap-5377	158	12	into	into	ADP
ap-5377	158	13	it	it	PRON
ap-5377	158	14	.	.	PUNCT
ap-5377	159	1	the	the	DET
ap-5377	159	2	number	number	NOUN
ap-5377	159	3	of	of	ADP
ap-5377	159	4	object	object	NOUN
ap-5377	159	5	in	in	ADP
ap-5377	159	6	its	its	PRON
ap-5377	159	7	radius	radius	NOUN
ap-5377	159	8	makes	make	VERB
ap-5377	159	9	it	it	PRON
ap-5377	159	10	possible	possible	ADJ
ap-5377	159	11	to	to	PART
ap-5377	159	12	classify	classify	VERB
ap-5377	159	13	an	an	DET
ap-5377	159	14	object	object	NOUN
ap-5377	159	15	into	into	ADP
ap-5377	159	16	three	three	NUM
ap-5377	159	17	groups	group	NOUN
ap-5377	159	18	:	:	PUNCT
ap-5377	159	19	a	a	DET
ap-5377	159	20	noisy	noisy	ADJ
ap-5377	159	21	,	,	PUNCT
ap-5377	159	22	a	a	DET
ap-5377	159	23	marginal	marginal	ADJ
ap-5377	159	24	,	,	PUNCT
ap-5377	159	25	a	a	DET
ap-5377	159	26	centre	centre	NOUN
ap-5377	159	27	object	object	NOUN
ap-5377	159	28	.	.	PUNCT
ap-5377	160	1	[	[	X
ap-5377	160	2	3	3	NUM
ap-5377	160	3	,	,	PUNCT
ap-5377	160	4	26	26	NUM
ap-5377	160	5	,	,	PUNCT
ap-5377	160	6	27	27	NUM
ap-5377	160	7	]	]	PUNCT
ap-5377	160	8	the	the	DET
ap-5377	160	9	algorithm	algorithm	NOUN
ap-5377	160	10	starts	start	VERB
ap-5377	160	11	with	with	ADP
ap-5377	160	12	any	any	DET
ap-5377	160	13	data	data	NOUN
ap-5377	160	14	object	object	NOUN
ap-5377	160	15	(	(	PUNCT
ap-5377	160	16	initialization	initialization	NOUN
ap-5377	160	17	object	object	NOUN
ap-5377	160	18	)	)	PUNCT
ap-5377	160	19	.	.	PUNCT
ap-5377	161	1	we	we	PRON
ap-5377	161	2	find	find	VERB
ap-5377	161	3	all	all	DET
ap-5377	161	4	the	the	DET
ap-5377	161	5	objects	object	NOUN
ap-5377	161	6	that	that	PRON
ap-5377	161	7	fall	fall	VERB
ap-5377	161	8	within	within	ADP
ap-5377	161	9	its	its	PRON
ap-5377	161	10	radius	radius	NOUN
ap-5377	161	11	.	.	PUNCT
ap-5377	162	1	on	on	ADP
ap-5377	162	2	the	the	DET
ap-5377	162	3	basis	basis	NOUN
ap-5377	162	4	of	of	ADP
ap-5377	162	5	the	the	DET
ap-5377	162	6	number	number	NOUN
ap-5377	162	7	of	of	ADP
ap-5377	162	8	them	they	PRON
ap-5377	162	9	,	,	PUNCT
ap-5377	162	10	the	the	DET
ap-5377	162	11	object	object	NOUN
ap-5377	162	12	is	be	AUX
ap-5377	162	13	the	the	DET
ap-5377	162	14	initial	initial	ADJ
ap-5377	162	15	object	object	NOUN
ap-5377	162	16	classified	classify	VERB
ap-5377	162	17	into	into	ADP
ap-5377	162	18	one	one	NUM
ap-5377	162	19	of	of	ADP
ap-5377	162	20	the	the	DET
ap-5377	162	21	three	three	NUM
ap-5377	162	22	classes	class	NOUN
ap-5377	162	23	:	:	PUNCT
ap-5377	162	24	centre	centre	NOUN
ap-5377	162	25	,	,	PUNCT
ap-5377	162	26	marginal	marginal	ADJ
ap-5377	162	27	,	,	PUNCT
ap-5377	162	28	or	or	CCONJ
ap-5377	162	29	placed	place	VERB
ap-5377	162	30	in	in	ADP
ap-5377	162	31	the	the	DET
ap-5377	162	32	class	class	NOUN
ap-5377	162	33	of	of	ADP
ap-5377	162	34	distant	distant	ADJ
ap-5377	162	35	noise	noise	NOUN
ap-5377	162	36	objects	object	NOUN
ap-5377	162	37	.	.	PUNCT
ap-5377	163	1	gradually	gradually	ADV
ap-5377	163	2	,	,	PUNCT
ap-5377	163	3	for	for	ADP
ap-5377	163	4	each	each	PRON
ap-5377	163	5	of	of	ADP
ap-5377	163	6	these	these	DET
ap-5377	163	7	objects	object	NOUN
ap-5377	163	8	(	(	PUNCT
ap-5377	163	9	in	in	ADP
ap-5377	163	10	the	the	DET
ap-5377	163	11	initial	initial	ADJ
ap-5377	163	12	objects	object	NOUN
ap-5377	163	13	radius	radius	NOUN
ap-5377	163	14	)	)	PUNCT
ap-5377	163	15	,	,	PUNCT
ap-5377	163	16	we	we	PRON
ap-5377	163	17	look	look	VERB
ap-5377	163	18	for	for	ADP
ap-5377	163	19	the	the	DET
ap-5377	163	20	number	number	NOUN
ap-5377	163	21	of	of	ADP
ap-5377	163	22	objects	object	NOUN
ap-5377	163	23	in	in	ADP
ap-5377	163	24	its	its	PRON
ap-5377	163	25	radius	radius	NOUN
ap-5377	163	26	,	,	PUNCT
ap-5377	163	27	and	and	CCONJ
ap-5377	163	28	by	by	ADP
ap-5377	163	29	its	its	PRON
ap-5377	163	30	number	number	NOUN
ap-5377	163	31	we	we	PRON
ap-5377	163	32	classify	classify	VERB
ap-5377	163	33	an	an	DET
ap-5377	163	34	object	object	NOUN
ap-5377	163	35	.	.	PUNCT
ap-5377	164	1	if	if	SCONJ
ap-5377	164	2	it	it	PRON
ap-5377	164	3	is	be	AUX
ap-5377	164	4	a	a	DET
ap-5377	164	5	centre	centre	ADJ
ap-5377	164	6	object	object	NOUN
ap-5377	164	7	(	(	PUNCT
ap-5377	164	8	it	it	PRON
ap-5377	164	9	has	have	VERB
ap-5377	164	10	a	a	DET
ap-5377	164	11	sufficient	sufficient	ADJ
ap-5377	164	12	number	number	NOUN
ap-5377	164	13	of	of	ADP
ap-5377	164	14	objects	object	NOUN
ap-5377	164	15	in	in	ADP
ap-5377	164	16	its	its	PRON
ap-5377	164	17	radius	radius	NOUN
ap-5377	164	18	)	)	PUNCT
ap-5377	164	19	,	,	PUNCT
ap-5377	164	20	we	we	PRON
ap-5377	164	21	assign	assign	VERB
ap-5377	164	22	this	this	DET
ap-5377	164	23	object	object	NOUN
ap-5377	164	24	and	and	CCONJ
ap-5377	164	25	all	all	DET
ap-5377	164	26	the	the	DET
ap-5377	164	27	objects	object	NOUN
ap-5377	164	28	that	that	PRON
ap-5377	164	29	fall	fall	VERB
ap-5377	164	30	within	within	ADP
ap-5377	164	31	its	its	PRON
ap-5377	164	32	radius	radius	NOUN
ap-5377	164	33	to	to	ADP
ap-5377	164	34	the	the	DET
ap-5377	164	35	centre	centre	NOUN
ap-5377	164	36	of	of	ADP
ap-5377	164	37	the	the	DET
ap-5377	164	38	object	object	NOUN
ap-5377	164	39	class	class	NOUN
ap-5377	164	40	.	.	PUNCT
ap-5377	165	1	we	we	PRON
ap-5377	165	2	repeat	repeat	VERB
ap-5377	165	3	the	the	DET
ap-5377	165	4	previous	previous	ADJ
ap-5377	165	5	steps	step	NOUN
ap-5377	165	6	for	for	ADP
ap-5377	165	7	all	all	DET
ap-5377	165	8	objects	object	NOUN
ap-5377	165	9	that	that	PRON
ap-5377	165	10	belonged	belong	VERB
ap-5377	165	11	to	to	ADP
ap-5377	165	12	the	the	DET
ap-5377	165	13	radius	radius	NOUN
ap-5377	165	14	of	of	ADP
ap-5377	165	15	the	the	DET
ap-5377	165	16	starting	start	VERB
ap-5377	165	17	object	object	NOUN
ap-5377	165	18	.	.	PUNCT
ap-5377	166	1	if	if	SCONJ
ap-5377	166	2	we	we	PRON
ap-5377	166	3	exhaust	exhaust	VERB
ap-5377	166	4	all	all	PRON
ap-5377	166	5	of	of	ADP
ap-5377	166	6	the	the	DET
ap-5377	166	7	objects	object	NOUN
ap-5377	166	8	from	from	ADP
ap-5377	166	9	the	the	DET
ap-5377	166	10	vicinity	vicinity	NOUN
ap-5377	166	11	of	of	ADP
ap-5377	166	12	the	the	DET
ap-5377	166	13	initiation	initiation	NOUN
ap-5377	166	14	object	object	NOUN
ap-5377	166	15	,	,	PUNCT
ap-5377	166	16	we	we	PRON
ap-5377	166	17	automatically	automatically	ADV
ap-5377	166	18	go	go	VERB
ap-5377	166	19	to	to	ADP
ap-5377	166	20	the	the	DET
ap-5377	166	21	next	next	ADJ
ap-5377	166	22	non	non	ADJ
ap-5377	166	23	-	-	ADJ
ap-5377	166	24	classified	classified	ADJ
ap-5377	166	25	object	object	NOUN
ap-5377	166	26	in	in	ADP
ap-5377	166	27	the	the	DET
ap-5377	166	28	algorithm	algorithm	NOUN
ap-5377	166	29	.	.	PUNCT
ap-5377	167	1	the	the	DET
ap-5377	167	2	entire	entire	ADJ
ap-5377	167	3	process	process	NOUN
ap-5377	167	4	continues	continue	VERB
ap-5377	167	5	until	until	SCONJ
ap-5377	167	6	every	every	DET
ap-5377	167	7	single	single	ADJ
ap-5377	167	8	object	object	NOUN
ap-5377	167	9	is	be	AUX
ap-5377	167	10	assigned	assign	VERB
ap-5377	167	11	to	to	ADP
ap-5377	167	12	one	one	NUM
ap-5377	167	13	of	of	ADP
ap-5377	167	14	the	the	DET
ap-5377	167	15	three	three	NUM
ap-5377	167	16	classes	class	NOUN
ap-5377	167	17	.	.	PUNCT
ap-5377	168	1	the	the	DET
ap-5377	168	2	formula	formula	NOUN
ap-5377	168	3	for	for	ADP
ap-5377	168	4	the	the	DET
ap-5377	168	5	automatic	automatic	ADJ
ap-5377	168	6	calculation	calculation	NOUN
ap-5377	168	7	of	of	ADP
ap-5377	168	8	the	the	DET
ap-5377	168	9	eps	eps	PROPN
ap-5377	168	10	value	value	NOUN
ap-5377	168	11	can	can	AUX
ap-5377	168	12	be	be	AUX
ap-5377	168	13	found	find	VERB
ap-5377	168	14	in	in	ADP
ap-5377	168	15	article	article	NOUN
ap-5377	168	16	[	[	X
ap-5377	168	17	28	28	NUM
ap-5377	168	18	]	]	X
ap-5377	168	19	:	:	PUNCT
ap-5377	168	20	eps	eps	PROPN
ap-5377	168	21	=	=	SYM
ap-5377	168	22	(	(	PUNCT
ap-5377	168	23	(	(	PUNCT
ap-5377	168	24	πmax(x)−min(x	πmax(x)−min(x	X
ap-5377	168	25	)	)	PUNCT
ap-5377	168	26	i=1	i=1	PROPN
ap-5377	168	27	i	i	PROPN
ap-5377	168	28	)	)	PUNCT
ap-5377	168	29	·	·	PUNCT
ap-5377	168	30	minpts·γ·(0,5·n+1	minpts·γ·(0,5·n+1	NUM
ap-5377	168	31	)	)	PUNCT
ap-5377	169	1	m	m	PROPN
ap-5377	169	2	·	·	PUNCT
ap-5377	169	3	√	√	NUM
ap-5377	169	4	πn	πn	X
ap-5377	169	5	)	)	PUNCT
ap-5377	169	6	1	1	NUM
ap-5377	169	7	n	n	NOUN
ap-5377	169	8	,	,	PUNCT
ap-5377	169	9	(	(	PUNCT
ap-5377	169	10	12	12	NUM
ap-5377	169	11	)	)	PUNCT
ap-5377	169	12	where	where	SCONJ
ap-5377	169	13	x	x	PRON
ap-5377	169	14	are	be	AUX
ap-5377	169	15	the	the	DET
ap-5377	169	16	data	datum	NOUN
ap-5377	169	17	in	in	ADP
ap-5377	169	18	the	the	DET
ap-5377	169	19	form	form	NOUN
ap-5377	169	20	of	of	ADP
ap-5377	169	21	the	the	DET
ap-5377	169	22	matrix	matrix	NOUN
ap-5377	169	23	(	(	PUNCT
ap-5377	169	24	m	m	NOUN
ap-5377	169	25	,	,	PUNCT
ap-5377	169	26	n	n	CCONJ
ap-5377	169	27	)	)	PUNCT
ap-5377	169	28	,	,	PUNCT
ap-5377	169	29	where	where	SCONJ
ap-5377	169	30	m	m	NOUN
ap-5377	169	31	represents	represent	VERB
ap-5377	169	32	the	the	DET
ap-5377	169	33	number	number	NOUN
ap-5377	169	34	of	of	ADP
ap-5377	169	35	segments	segment	NOUN
ap-5377	169	36	and	and	CCONJ
ap-5377	169	37	n	n	CCONJ
ap-5377	169	38	the	the	DET
ap-5377	169	39	number	number	NOUN
ap-5377	169	40	of	of	ADP
ap-5377	169	41	flags	flag	NOUN
ap-5377	169	42	,	,	PUNCT
ap-5377	169	43	npts	npt	NOUN
ap-5377	169	44	is	be	AUX
ap-5377	169	45	the	the	DET
ap-5377	169	46	number	number	NOUN
ap-5377	169	47	of	of	ADP
ap-5377	169	48	objects	object	NOUN
ap-5377	169	49	in	in	ADP
ap-5377	169	50	radius	radius	NOUN
ap-5377	169	51	and	and	CCONJ
ap-5377	169	52	γ	γ	NOUN
ap-5377	169	53	is	be	AUX
ap-5377	169	54	the	the	DET
ap-5377	169	55	interpolation	interpolation	NOUN
ap-5377	169	56	coefficient	coefficient	NOUN
ap-5377	169	57	.	.	PUNCT
ap-5377	170	1	according	accord	VERB
ap-5377	170	2	to	to	ADP
ap-5377	170	3	ali	ali	PROPN
ap-5377	170	4	’s	’s	PART
ap-5377	170	5	touhk	touhk	PROPN
ap-5377	170	6	’s	’s	PART
ap-5377	170	7	[	[	X
ap-5377	170	8	29	29	NUM
ap-5377	170	9	]	]	X
ap-5377	170	10	design	design	NOUN
ap-5377	170	11	,	,	PUNCT
ap-5377	170	12	we	we	PRON
ap-5377	170	13	obtain	obtain	VERB
ap-5377	170	14	the	the	DET
ap-5377	170	15	number	number	NOUN
ap-5377	170	16	of	of	ADP
ap-5377	170	17	objects	object	NOUN
ap-5377	170	18	in	in	ADP
ap-5377	170	19	the	the	DET
ap-5377	170	20	radius	radius	NOUN
ap-5377	170	21	by	by	ADP
ap-5377	170	22	sequentially	sequentially	ADV
ap-5377	170	23	testing	test	VERB
ap-5377	170	24	npts	npt	NOUN
ap-5377	170	25	values	value	NOUN
ap-5377	170	26	(	(	PUNCT
ap-5377	170	27	from	from	ADP
ap-5377	170	28	1	1	NUM
ap-5377	170	29	to	to	ADP
ap-5377	170	30	n	n	PRON
ap-5377	170	31	number	number	NOUN
ap-5377	170	32	of	of	ADP
ap-5377	170	33	all	all	DET
ap-5377	170	34	objects	object	NOUN
ap-5377	170	35	)	)	PUNCT
ap-5377	170	36	and	and	CCONJ
ap-5377	170	37	compiling	compile	VERB
ap-5377	170	38	the	the	DET
ap-5377	170	39	graphs	graph	NOUN
ap-5377	170	40	from	from	ADP
ap-5377	170	41	these	these	DET
ap-5377	170	42	values	value	NOUN
ap-5377	170	43	.	.	PUNCT
ap-5377	171	1	each	each	DET
ap-5377	171	2	graph	graph	NOUN
ap-5377	171	3	describes	describe	VERB
ap-5377	171	4	a	a	DET
ap-5377	171	5	set	set	NOUN
ap-5377	171	6	of	of	ADP
ap-5377	171	7	test	test	NOUN
ap-5377	171	8	data	datum	NOUN
ap-5377	171	9	,	,	PUNCT
ap-5377	171	10	for	for	ADP
ap-5377	171	11	example	example	NOUN
ap-5377	171	12	,	,	PUNCT
ap-5377	171	13	see	see	VERB
ap-5377	171	14	2	2	NUM
ap-5377	171	15	.	.	PUNCT
ap-5377	172	1	the	the	DET
ap-5377	172	2	average	average	ADJ
ap-5377	172	3	value	value	NOUN
ap-5377	172	4	of	of	ADP
ap-5377	172	5	the	the	DET
ap-5377	172	6	pooled	pool	VERB
ap-5377	172	7	objects	object	NOUN
ap-5377	172	8	,	,	PUNCT
ap-5377	172	9	which	which	PRON
ap-5377	172	10	are	be	AUX
ap-5377	172	11	in	in	ADP
ap-5377	172	12	one	one	NUM
ap-5377	172	13	cluster	cluster	NOUN
ap-5377	172	14	,	,	PUNCT
ap-5377	172	15	is	be	AUX
ap-5377	172	16	on	on	SCONJ
ap-5377	172	17	the	the	DET
ap-5377	172	18	x	x	PUNCT
ap-5377	172	19	axis	axis	NOUN
ap-5377	172	20	is	be	AUX
ap-5377	172	21	.	.	PUNCT
ap-5377	173	1	the	the	DET
ap-5377	173	2	y	y	PROPN
ap-5377	173	3	axis	axis	NOUN
ap-5377	173	4	is	be	AUX
ap-5377	173	5	the	the	DET
ap-5377	173	6	npts	npt	NOUN
ap-5377	173	7	value	value	NOUN
ap-5377	173	8	for	for	ADP
ap-5377	173	9	which	which	PRON
ap-5377	173	10	we	we	PRON
ap-5377	173	11	get	get	VERB
ap-5377	173	12	the	the	DET
ap-5377	173	13	number	number	NOUN
ap-5377	173	14	of	of	ADP
ap-5377	173	15	clusters	cluster	NOUN
ap-5377	173	16	.	.	PUNCT
ap-5377	174	1	we	we	PRON
ap-5377	174	2	get	get	VERB
ap-5377	174	3	a	a	DET
ap-5377	174	4	npts	npt	NOUN
ap-5377	174	5	span	span	NOUN
ap-5377	174	6	from	from	ADP
ap-5377	174	7	each	each	DET
ap-5377	174	8	graph	graph	NOUN
ap-5377	174	9	,	,	PUNCT
ap-5377	174	10	which	which	PRON
ap-5377	174	11	provides	provide	VERB
ap-5377	174	12	the	the	DET
ap-5377	174	13	required	require	VERB
ap-5377	174	14	number	number	NOUN
ap-5377	174	15	of	of	ADP
ap-5377	174	16	classes	class	NOUN
ap-5377	174	17	.	.	PUNCT
ap-5377	175	1	we	we	PRON
ap-5377	175	2	choose	choose	VERB
ap-5377	175	3	the	the	DET
ap-5377	175	4	ideal	ideal	ADJ
ap-5377	175	5	value	value	NOUN
ap-5377	175	6	across	across	ADP
ap-5377	175	7	all	all	DET
ap-5377	175	8	charts	chart	NOUN
ap-5377	175	9	.	.	PUNCT
ap-5377	176	1	based	base	VERB
ap-5377	176	2	on	on	ADP
ap-5377	176	3	the	the	DET
ap-5377	176	4	results	result	NOUN
ap-5377	176	5	from	from	ADP
ap-5377	176	6	all	all	DET
ap-5377	176	7	tested	test	VERB
ap-5377	176	8	graphs	graph	NOUN
ap-5377	176	9	,	,	PUNCT
ap-5377	176	10	we	we	PRON
ap-5377	176	11	chose	choose	VERB
ap-5377	176	12	npts	npt	NOUN
ap-5377	176	13	=	=	SYM
ap-5377	176	14	15	15	NUM
ap-5377	176	15	.	.	PUNCT
ap-5377	177	1	the	the	DET
ap-5377	177	2	above	above	ADJ
ap-5377	177	3	calculation	calculation	NOUN
ap-5377	177	4	of	of	ADP
ap-5377	177	5	eps	eps	PROPN
ap-5377	177	6	is	be	AUX
ap-5377	177	7	adequate	adequate	ADJ
ap-5377	177	8	for	for	ADP
ap-5377	177	9	2d	2d	PROPN
ap-5377	177	10	data	datum	NOUN
ap-5377	177	11	.	.	PUNCT
ap-5377	178	1	it	it	PRON
ap-5377	178	2	does	do	AUX
ap-5377	178	3	not	not	PART
ap-5377	178	4	give	give	VERB
ap-5377	178	5	adequate	adequate	ADJ
ap-5377	178	6	results	result	NOUN
ap-5377	178	7	on	on	ADP
ap-5377	178	8	multidimensional	multidimensional	ADJ
ap-5377	178	9	data	datum	NOUN
ap-5377	178	10	.	.	PUNCT
ap-5377	179	1	we	we	PRON
ap-5377	179	2	assume	assume	VERB
ap-5377	179	3	an	an	DET
ap-5377	179	4	uneven	uneven	ADJ
ap-5377	179	5	layout	layout	NOUN
ap-5377	179	6	of	of	ADP
ap-5377	179	7	data	datum	NOUN
ap-5377	179	8	in	in	ADP
ap-5377	179	9	the	the	DET
ap-5377	179	10	space	space	NOUN
ap-5377	179	11	for	for	ADP
ap-5377	179	12	dbscan	dbscan	PROPN
ap-5377	179	13	modification	modification	NOUN
ap-5377	179	14	.	.	PUNCT
ap-5377	180	1	therefore	therefore	ADV
ap-5377	180	2	,	,	PUNCT
ap-5377	180	3	501	501	NUM
ap-5377	180	4	m.	m.	NOUN
ap-5377	180	5	piorecký	piorecký	NOUN
ap-5377	180	6	,	,	PUNCT
ap-5377	180	7	j.	j.	PROPN
ap-5377	180	8	štrobl	štrobl	PROPN
ap-5377	180	9	,	,	PUNCT
ap-5377	180	10	v.	v.	ADP
ap-5377	180	11	krajča	krajča	PROPN
ap-5377	180	12	acta	acta	PROPN
ap-5377	180	13	polytechnica	polytechnica	PROPN
ap-5377	180	14	figure	figure	NOUN
ap-5377	180	15	2	2	NUM
ap-5377	180	16	.	.	PUNCT
ap-5377	180	17	optimal	optimal	ADJ
ap-5377	180	18	number	number	NOUN
ap-5377	180	19	of	of	ADP
ap-5377	180	20	npts	npt	NOUN
ap-5377	180	21	.	.	PUNCT
ap-5377	181	1	we	we	PRON
ap-5377	181	2	used	use	VERB
ap-5377	181	3	the	the	DET
ap-5377	181	4	dynamic	dynamic	ADJ
ap-5377	181	5	method	method	NOUN
ap-5377	181	6	for	for	ADP
ap-5377	181	7	discovering	discover	VERB
ap-5377	181	8	density	density	NOUN
ap-5377	181	9	varied	varied	ADJ
ap-5377	181	10	clusters	cluster	NOUN
ap-5377	181	11	(	(	PUNCT
ap-5377	181	12	dmdbscan	dmdbscan	ADJ
ap-5377	181	13	)	)	PUNCT
ap-5377	181	14	principle	principle	NOUN
ap-5377	181	15	and	and	CCONJ
ap-5377	181	16	calculate	calculate	VERB
ap-5377	181	17	the	the	DET
ap-5377	181	18	radius	radius	NOUN
ap-5377	181	19	from	from	ADP
ap-5377	181	20	the	the	DET
ap-5377	181	21	curve	curve	NOUN
ap-5377	181	22	of	of	ADP
ap-5377	181	23	the	the	DET
ap-5377	181	24	nearest	near	ADJ
ap-5377	181	25	neighbours	neighbour	NOUN
ap-5377	181	26	.	.	PUNCT
ap-5377	182	1	we	we	PRON
ap-5377	182	2	count	count	VERB
ap-5377	182	3	the	the	DET
ap-5377	182	4	distance	distance	NOUN
ap-5377	182	5	of	of	ADP
ap-5377	182	6	all	all	DET
ap-5377	182	7	objects	object	NOUN
ap-5377	182	8	to	to	ADP
ap-5377	182	9	each	each	DET
ap-5377	182	10	object	object	NOUN
ap-5377	182	11	in	in	ADP
ap-5377	182	12	the	the	DET
ap-5377	182	13	file	file	NOUN
ap-5377	182	14	.	.	PUNCT
ap-5377	183	1	these	these	DET
ap-5377	183	2	values	value	NOUN
ap-5377	183	3	are	be	AUX
ap-5377	183	4	ranked	rank	VERB
ap-5377	183	5	ascending	ascend	VERB
ap-5377	183	6	.	.	PUNCT
ap-5377	184	1	for	for	ADP
ap-5377	184	2	each	each	DET
ap-5377	184	3	object	object	NOUN
ap-5377	184	4	,	,	PUNCT
ap-5377	184	5	we	we	PRON
ap-5377	184	6	select	select	VERB
ap-5377	184	7	its	its	PRON
ap-5377	184	8	first	first	ADJ
ap-5377	184	9	three	three	NUM
ap-5377	184	10	neighbours	neighbour	NOUN
ap-5377	184	11	and	and	CCONJ
ap-5377	184	12	make	make	VERB
ap-5377	184	13	an	an	DET
ap-5377	184	14	average	average	NOUN
ap-5377	184	15	of	of	ADP
ap-5377	184	16	them	they	PRON
ap-5377	184	17	[	[	X
ap-5377	184	18	30	30	NUM
ap-5377	184	19	]	]	PUNCT
ap-5377	184	20	.	.	PUNCT
ap-5377	185	1	the	the	DET
ap-5377	185	2	study	study	NOUN
ap-5377	185	3	showed	show	VERB
ap-5377	185	4	that	that	SCONJ
ap-5377	185	5	from	from	ADP
ap-5377	185	6	the	the	DET
ap-5377	185	7	4th	4th	ADJ
ap-5377	185	8	neighbour	neighbour	NOUN
ap-5377	185	9	,	,	PUNCT
ap-5377	185	10	the	the	DET
ap-5377	185	11	results	result	NOUN
ap-5377	185	12	are	be	AUX
ap-5377	185	13	no	no	ADV
ap-5377	185	14	different	different	ADJ
ap-5377	185	15	[	[	X
ap-5377	185	16	31	31	NUM
ap-5377	185	17	]	]	PUNCT
ap-5377	185	18	.	.	PUNCT
ap-5377	186	1	these	these	DET
ap-5377	186	2	values	value	NOUN
ap-5377	186	3	are	be	AUX
ap-5377	186	4	ranked	rank	VERB
ap-5377	186	5	in	in	ADP
ap-5377	186	6	an	an	DET
ap-5377	186	7	ascendant	ascendant	ADJ
ap-5377	186	8	order	order	NOUN
ap-5377	186	9	according	accord	VERB
ap-5377	186	10	to	to	ADP
ap-5377	186	11	size	size	NOUN
ap-5377	186	12	and	and	CCONJ
ap-5377	186	13	we	we	PRON
ap-5377	186	14	create	create	VERB
ap-5377	186	15	a	a	DET
ap-5377	186	16	curve	curve	NOUN
ap-5377	186	17	.	.	PUNCT
ap-5377	187	1	in	in	ADP
ap-5377	187	2	the	the	DET
ap-5377	187	3	elbow	elbow	NOUN
ap-5377	187	4	of	of	ADP
ap-5377	187	5	this	this	DET
ap-5377	187	6	curve	curve	NOUN
ap-5377	187	7	,	,	PUNCT
ap-5377	187	8	the	the	DET
ap-5377	187	9	values	value	NOUN
ap-5377	187	10	are	be	AUX
ap-5377	187	11	appropriate	appropriate	ADJ
ap-5377	187	12	for	for	ADP
ap-5377	187	13	the	the	DET
ap-5377	187	14	radius	radius	NOUN
ap-5377	187	15	of	of	ADP
ap-5377	187	16	the	the	DET
ap-5377	187	17	given	give	VERB
ap-5377	187	18	data	datum	NOUN
ap-5377	187	19	set	set	VERB
ap-5377	187	20	.	.	PUNCT
ap-5377	188	1	the	the	DET
ap-5377	188	2	evaluation	evaluation	NOUN
ap-5377	188	3	was	be	AUX
ap-5377	188	4	made	make	VERB
ap-5377	188	5	visually	visually	ADV
ap-5377	188	6	here	here	ADV
ap-5377	188	7	.	.	PUNCT
ap-5377	189	1	[	[	X
ap-5377	189	2	26	26	NUM
ap-5377	189	3	,	,	PUNCT
ap-5377	189	4	32	32	NUM
ap-5377	189	5	]	]	PUNCT
ap-5377	189	6	for	for	ADP
ap-5377	189	7	the	the	DET
ap-5377	189	8	tested	test	VERB
ap-5377	189	9	eeg	eeg	NOUN
ap-5377	189	10	records	record	NOUN
ap-5377	189	11	,	,	PUNCT
ap-5377	189	12	the	the	DET
ap-5377	189	13	curve	curve	NOUN
ap-5377	189	14	never	never	ADV
ap-5377	189	15	contained	contain	VERB
ap-5377	189	16	more	more	ADJ
ap-5377	189	17	than	than	ADP
ap-5377	189	18	one	one	NUM
ap-5377	189	19	knee	knee	NOUN
ap-5377	189	20	,	,	PUNCT
ap-5377	189	21	as	as	ADV
ap-5377	189	22	well	well	ADV
ap-5377	189	23	as	as	ADP
ap-5377	189	24	in	in	ADP
ap-5377	189	25	a	a	DET
ap-5377	189	26	study	study	NOUN
ap-5377	189	27	[	[	X
ap-5377	189	28	32	32	NUM
ap-5377	189	29	]	]	PUNCT
ap-5377	189	30	.	.	PUNCT
ap-5377	190	1	inflection	inflection	NOUN
ap-5377	190	2	objects	object	NOUN
ap-5377	190	3	on	on	ADP
ap-5377	190	4	the	the	DET
ap-5377	190	5	curve	curve	NOUN
ap-5377	190	6	can	can	AUX
ap-5377	190	7	only	only	ADV
ap-5377	190	8	be	be	AUX
ap-5377	190	9	obtained	obtain	VERB
ap-5377	190	10	at	at	ADP
ap-5377	190	11	npts	npt	NOUN
ap-5377	190	12	>	>	X
ap-5377	190	13	50	50	NUM
ap-5377	190	14	(	(	PUNCT
ap-5377	190	15	in	in	ADP
ap-5377	190	16	our	our	PRON
ap-5377	190	17	24	24	NUM
ap-5377	190	18	-	-	PUNCT
ap-5377	190	19	d	d	NOUN
ap-5377	190	20	space	space	NOUN
ap-5377	190	21	)	)	PUNCT
ap-5377	190	22	.	.	PUNCT
ap-5377	191	1	if	if	SCONJ
ap-5377	191	2	we	we	PRON
ap-5377	191	3	reduce	reduce	VERB
ap-5377	191	4	the	the	DET
ap-5377	191	5	number	number	NOUN
ap-5377	191	6	of	of	ADP
ap-5377	191	7	dimensions	dimension	NOUN
ap-5377	191	8	,	,	PUNCT
ap-5377	191	9	we	we	PRON
ap-5377	191	10	get	get	VERB
ap-5377	191	11	inflection	inflection	NOUN
ap-5377	191	12	objects	object	NOUN
ap-5377	191	13	at	at	ADP
ap-5377	191	14	npts	npt	NOUN
ap-5377	191	15	=	=	SYM
ap-5377	191	16	30	30	NUM
ap-5377	191	17	.	.	PUNCT
ap-5377	192	1	another	another	DET
ap-5377	192	2	solution	solution	NOUN
ap-5377	192	3	to	to	ADP
ap-5377	192	4	this	this	DET
ap-5377	192	5	situation	situation	NOUN
ap-5377	192	6	is	be	AUX
ap-5377	192	7	offered	offer	VERB
ap-5377	192	8	by	by	ADP
ap-5377	192	9	other	other	ADJ
ap-5377	192	10	modifications	modification	NOUN
ap-5377	192	11	:	:	PUNCT
ap-5377	192	12	gridbscan	gridbscan	PROPN
ap-5377	192	13	.	.	PUNCT
ap-5377	193	1	gridbscan	gridbscan	PROPN
ap-5377	193	2	is	be	AUX
ap-5377	193	3	a	a	DET
ap-5377	193	4	merger	merger	NOUN
ap-5377	193	5	of	of	ADP
ap-5377	193	6	several	several	ADJ
ap-5377	193	7	algorithms	algorithm	NOUN
ap-5377	193	8	.	.	PUNCT
ap-5377	194	1	the	the	DET
ap-5377	194	2	basic	basic	ADJ
ap-5377	194	3	idea	idea	NOUN
ap-5377	194	4	is	be	AUX
ap-5377	194	5	that	that	SCONJ
ap-5377	194	6	it	it	PRON
ap-5377	194	7	is	be	AUX
ap-5377	194	8	possible	possible	ADJ
ap-5377	194	9	to	to	PART
ap-5377	194	10	divide	divide	VERB
ap-5377	194	11	space	space	NOUN
ap-5377	194	12	into	into	ADP
ap-5377	194	13	cells	cell	NOUN
ap-5377	194	14	(	(	PUNCT
ap-5377	194	15	see	see	VERB
ap-5377	194	16	figure	figure	NOUN
ap-5377	194	17	3	3	NUM
ap-5377	194	18	)	)	PUNCT
ap-5377	194	19	that	that	PRON
ap-5377	194	20	evenly	evenly	ADV
ap-5377	194	21	distributes	distribute	VERB
ap-5377	194	22	space	space	NOUN
ap-5377	194	23	[	[	X
ap-5377	194	24	33	33	NUM
ap-5377	194	25	,	,	PUNCT
ap-5377	194	26	34	34	NUM
ap-5377	194	27	]	]	PUNCT
ap-5377	194	28	.	.	PUNCT
ap-5377	195	1	in	in	ADP
ap-5377	195	2	the	the	DET
ap-5377	195	3	first	first	ADJ
ap-5377	195	4	step	step	NOUN
ap-5377	195	5	,	,	PUNCT
ap-5377	195	6	the	the	DET
ap-5377	195	7	cells	cell	NOUN
ap-5377	195	8	are	be	AUX
ap-5377	195	9	divided	divide	VERB
ap-5377	195	10	into	into	ADP
ap-5377	195	11	over	over	ADP
ap-5377	195	12	-	-	PUNCT
ap-5377	195	13	limit	limit	NOUN
ap-5377	195	14	(	(	PUNCT
ap-5377	195	15	objects	object	VERB
ap-5377	195	16	further	far	ADV
ap-5377	195	17	classified	classify	VERB
ap-5377	195	18	)	)	PUNCT
ap-5377	195	19	and	and	CCONJ
ap-5377	195	20	under	under	NOUN
ap-5377	195	21	-	-	PUNCT
ap-5377	195	22	limit	limit	NOUN
ap-5377	195	23	(	(	PUNCT
ap-5377	195	24	noise	noise	NOUN
ap-5377	195	25	)	)	PUNCT
ap-5377	195	26	.	.	PUNCT
ap-5377	196	1	if	if	SCONJ
ap-5377	196	2	an	an	DET
ap-5377	196	3	oversized	oversized	ADJ
ap-5377	196	4	cell	cell	NOUN
ap-5377	196	5	is	be	AUX
ap-5377	196	6	adjacent	adjacent	ADJ
ap-5377	196	7	to	to	ADP
ap-5377	196	8	an	an	DET
ap-5377	196	9	already	already	ADV
ap-5377	196	10	identified	identify	VERB
ap-5377	196	11	cell	cell	NOUN
ap-5377	196	12	,	,	PUNCT
ap-5377	196	13	it	it	PRON
ap-5377	196	14	is	be	AUX
ap-5377	196	15	assigned	assign	VERB
ap-5377	196	16	to	to	ADP
ap-5377	196	17	the	the	DET
ap-5377	196	18	same	same	ADJ
ap-5377	196	19	class	class	NOUN
ap-5377	196	20	.	.	PUNCT
ap-5377	197	1	if	if	SCONJ
ap-5377	197	2	a	a	DET
ap-5377	197	3	gradual	gradual	ADJ
ap-5377	197	4	shift	shift	NOUN
ap-5377	197	5	across	across	ADP
ap-5377	197	6	the	the	DET
ap-5377	197	7	cell	cell	NOUN
ap-5377	197	8	gets	get	VERB
ap-5377	197	9	to	to	ADP
ap-5377	197	10	one	one	NUM
ap-5377	197	11	that	that	PRON
ap-5377	197	12	is	be	AUX
ap-5377	197	13	not	not	PART
ap-5377	197	14	adjacent	adjacent	ADJ
ap-5377	197	15	to	to	ADP
ap-5377	197	16	any	any	DET
ap-5377	197	17	classified	classified	ADJ
ap-5377	197	18	,	,	PUNCT
ap-5377	197	19	a	a	DET
ap-5377	197	20	new	new	ADJ
ap-5377	197	21	class	class	NOUN
ap-5377	197	22	is	be	AUX
ap-5377	197	23	created	create	VERB
ap-5377	197	24	[	[	PUNCT
ap-5377	197	25	34	34	NUM
ap-5377	197	26	]	]	PUNCT
ap-5377	197	27	.	.	PUNCT
ap-5377	198	1	in	in	ADP
ap-5377	198	2	this	this	DET
ap-5377	198	3	case	case	NOUN
ap-5377	198	4	,	,	PUNCT
ap-5377	198	5	there	there	PRON
ap-5377	198	6	is	be	VERB
ap-5377	198	7	a	a	DET
ap-5377	198	8	problem	problem	NOUN
ap-5377	198	9	in	in	ADP
ap-5377	198	10	dividing	divide	VERB
ap-5377	198	11	the	the	DET
ap-5377	198	12	multidimensional	multidimensional	ADJ
ap-5377	198	13	eeg	eeg	NOUN
ap-5377	198	14	space	space	NOUN
ap-5377	198	15	,	,	PUNCT
ap-5377	198	16	because	because	SCONJ
ap-5377	198	17	,	,	PUNCT
ap-5377	198	18	with	with	ADP
ap-5377	198	19	a	a	DET
ap-5377	198	20	higher	high	ADJ
ap-5377	198	21	number	number	NOUN
ap-5377	198	22	of	of	ADP
ap-5377	198	23	cells	cell	NOUN
ap-5377	198	24	,	,	PUNCT
ap-5377	198	25	the	the	DET
ap-5377	198	26	filling	filling	NOUN
ap-5377	198	27	becomes	become	VERB
ap-5377	198	28	smaller	small	ADJ
ap-5377	198	29	and	and	CCONJ
ap-5377	198	30	the	the	DET
ap-5377	198	31	classification	classification	NOUN
ap-5377	198	32	quality	quality	NOUN
ap-5377	198	33	decreases	decrease	VERB
ap-5377	198	34	.	.	PUNCT
ap-5377	199	1	in	in	ADP
ap-5377	199	2	the	the	DET
ap-5377	199	3	study	study	NOUN
ap-5377	199	4	[	[	X
ap-5377	199	5	35	35	NUM
ap-5377	199	6	]	]	PUNCT
ap-5377	199	7	,	,	PUNCT
ap-5377	199	8	they	they	PRON
ap-5377	199	9	used	use	VERB
ap-5377	199	10	a	a	DET
ap-5377	199	11	grid	grid	NOUN
ap-5377	199	12	that	that	PRON
ap-5377	199	13	is	be	AUX
ap-5377	199	14	composed	compose	VERB
ap-5377	199	15	of	of	ADP
ap-5377	199	16	cells	cell	NOUN
ap-5377	199	17	with	with	ADP
ap-5377	199	18	small	small	ADJ
ap-5377	199	19	overlaps	overlap	NOUN
ap-5377	199	20	.	.	PUNCT
ap-5377	200	1	the	the	DET
ap-5377	200	2	dbscan	dbscan	PROPN
ap-5377	200	3	algorithm	algorithm	NOUN
ap-5377	200	4	runs	run	VERB
ap-5377	200	5	in	in	ADP
ap-5377	200	6	each	each	DET
ap-5377	200	7	cell	cell	NOUN
ap-5377	200	8	separately	separately	ADV
ap-5377	200	9	.	.	PUNCT
ap-5377	201	1	in	in	ADP
ap-5377	201	2	the	the	DET
ap-5377	201	3	overlapping	overlap	VERB
ap-5377	201	4	area	area	NOUN
ap-5377	201	5	,	,	PUNCT
ap-5377	201	6	objects	object	NOUN
ap-5377	201	7	are	be	AUX
ap-5377	201	8	classified	classify	VERB
ap-5377	201	9	multiple	multiple	ADJ
ap-5377	201	10	times	time	NOUN
ap-5377	201	11	(	(	PUNCT
ap-5377	201	12	depending	depend	VERB
ap-5377	201	13	on	on	ADP
ap-5377	201	14	the	the	DET
ap-5377	201	15	cell	cell	NOUN
ap-5377	201	16	)	)	PUNCT
ap-5377	201	17	.	.	PUNCT
ap-5377	202	1	the	the	DET
ap-5377	202	2	interconnection	interconnection	NOUN
ap-5377	202	3	of	of	ADP
ap-5377	202	4	clusters	cluster	NOUN
ap-5377	202	5	of	of	ADP
ap-5377	202	6	neighbour	neighbour	ADJ
ap-5377	202	7	cells	cell	NOUN
ap-5377	202	8	occurs	occur	VERB
ap-5377	202	9	just	just	ADV
ap-5377	202	10	above	above	ADP
ap-5377	202	11	these	these	DET
ap-5377	202	12	objects	object	NOUN
ap-5377	202	13	.	.	PUNCT
ap-5377	203	1	the	the	DET
ap-5377	203	2	clusters	cluster	NOUN
ap-5377	203	3	that	that	PRON
ap-5377	203	4	have	have	AUX
ap-5377	203	5	been	be	AUX
ap-5377	203	6	assigned	assign	VERB
ap-5377	203	7	to	to	ADP
ap-5377	203	8	their	their	PRON
ap-5377	203	9	cells	cell	NOUN
ap-5377	203	10	are	be	AUX
ap-5377	203	11	combined	combine	VERB
ap-5377	203	12	in	in	ADP
ap-5377	203	13	one	one	NUM
ap-5377	203	14	.	.	PUNCT
ap-5377	204	1	data	datum	NOUN
ap-5377	204	2	:	:	PUNCT
ap-5377	204	3	border	border	NOUN
ap-5377	204	4	,	,	PUNCT
ap-5377	204	5	featurematrix	featurematrix	NOUN
ap-5377	204	6	result	result	NOUN
ap-5377	204	7	:	:	PUNCT
ap-5377	204	8	classification	classification	NOUN
ap-5377	204	9	of	of	ADP
ap-5377	204	10	segments	segment	NOUN
ap-5377	204	11	for	for	ADP
ap-5377	204	12	1	1	NUM
ap-5377	204	13	:	:	PUNCT
ap-5377	204	14	numbercells	numbercell	NOUN
ap-5377	204	15	do	do	AUX
ap-5377	204	16	border	border	NOUN
ap-5377	204	17	=	=	NOUN
ap-5377	204	18	border	border	NOUN
ap-5377	204	19	of	of	ADP
ap-5377	204	20	cell	cell	NOUN
ap-5377	204	21	objets	objet	NOUN
ap-5377	204	22	=	=	PUNCT
ap-5377	204	23	objects	object	VERB
ap-5377	204	24	belonging	belong	VERB
ap-5377	204	25	to	to	ADP
ap-5377	204	26	the	the	DET
ap-5377	204	27	cell	cell	NOUN
ap-5377	204	28	if	if	SCONJ
ap-5377	204	29	objects	object	VERB
ap-5377	204	30	=	=	PRON
ap-5377	204	31	!	!	NOUN
ap-5377	204	32	0	0	PUNCT
ap-5377	205	1	then	then	ADV
ap-5377	205	2	[	[	X
ap-5377	205	3	classpoint	classpoint	NOUN
ap-5377	205	4	,	,	PUNCT
ap-5377	205	5	class	class	NOUN
ap-5377	205	6	,	,	PUNCT
ap-5377	205	7	type	type	NOUN
ap-5377	205	8	]	]	X
ap-5377	205	9	=	=	SYM
ap-5377	205	10	dbscan(segments	dbscan(segments	PROPN
ap-5377	205	11	)	)	PUNCT
ap-5377	205	12	numbercells	numbercell	NOUN
ap-5377	205	13	=	=	PUNCT
ap-5377	205	14	recalculated	recalculate	VERB
ap-5377	205	15	number	number	NOUN
ap-5377	205	16	of	of	ADP
ap-5377	205	17	cell	cell	NOUN
ap-5377	205	18	matrix	matrix	NOUN
ap-5377	205	19	=	=	PUNCT
ap-5377	206	1	[	[	X
ap-5377	206	2	data	datum	NOUN
ap-5377	206	3	,	,	PUNCT
ap-5377	206	4	numbercells	numbercell	NOUN
ap-5377	206	5	,	,	PUNCT
ap-5377	206	6	class	class	NOUN
ap-5377	206	7	,	,	PUNCT
ap-5377	206	8	type	type	NOUN
ap-5377	206	9	]	]	PUNCT
ap-5377	206	10	end	end	NOUN
ap-5377	206	11	end	end	NOUN
ap-5377	206	12	for	for	ADP
ap-5377	206	13	1	1	NUM
ap-5377	206	14	:	:	PUNCT
ap-5377	206	15	numberrecurringobjects	numberrecurringobject	NOUN
ap-5377	206	16	do	do	VERB
ap-5377	206	17	if	if	SCONJ
ap-5377	206	18	centerobject	centerobject	ADJ
ap-5377	206	19	then	then	ADV
ap-5377	206	20	numbercluster	numbercluster	ADJ
ap-5377	206	21	=	=	VERB
ap-5377	206	22	numbers	number	NOUN
ap-5377	206	23	of	of	ADP
ap-5377	206	24	occurrence	occurrence	NOUN
ap-5377	206	25	classes	class	NOUN
ap-5377	206	26	fn	fn	NOUN
ap-5377	206	27	=	=	SYM
ap-5377	206	28	min(numbercluster	min(numbercluster	NOUN
ap-5377	206	29	)	)	PUNCT
ap-5377	206	30	numbercells	numbercell	NOUN
ap-5377	206	31	=	=	PUNCT
ap-5377	206	32	recalculated	recalculate	VERB
ap-5377	206	33	number	number	NOUN
ap-5377	206	34	of	of	ADP
ap-5377	206	35	cell	cell	NOUN
ap-5377	206	36	for	for	ADP
ap-5377	206	37	1	1	NUM
ap-5377	206	38	:	:	PUNCT
ap-5377	206	39	numbercluster	numbercluster	ADJ
ap-5377	206	40	do	do	AUX
ap-5377	206	41	matrix2	matrix2	NOUN
ap-5377	206	42	=	=	PUNCT
ap-5377	206	43	all	all	DET
ap-5377	206	44	objects	object	NOUN
ap-5377	206	45	will	will	AUX
ap-5377	206	46	be	be	AUX
ap-5377	206	47	overwritten	overwrite	VERB
ap-5377	206	48	to	to	PART
ap-5377	206	49	fn	fn	NOUN
ap-5377	206	50	end	end	NOUN
ap-5377	206	51	end	end	NOUN
ap-5377	206	52	end	end	NOUN
ap-5377	206	53	for	for	ADP
ap-5377	206	54	1	1	NUM
ap-5377	206	55	:	:	PUNCT
ap-5377	206	56	number	number	NOUN
ap-5377	206	57	of	of	ADP
ap-5377	206	58	rows	row	NOUN
ap-5377	206	59	of	of	ADP
ap-5377	206	60	matrix2	matrix2	NOUN
ap-5377	206	61	do	do	AUX
ap-5377	206	62	repeatedly	repeatedly	ADV
ap-5377	206	63	=	=	PUNCT
ap-5377	206	64	repeating	repeat	VERB
ap-5377	206	65	objects	object	NOUN
ap-5377	206	66	result	result	VERB
ap-5377	206	67	=	=	PUNCT
ap-5377	206	68	stores	store	NOUN
ap-5377	206	69	only	only	ADV
ap-5377	206	70	one	one	NUM
ap-5377	206	71	object	object	NOUN
ap-5377	206	72	(	(	PUNCT
ap-5377	206	73	with	with	ADP
ap-5377	206	74	the	the	DET
ap-5377	206	75	lowest	low	ADJ
ap-5377	206	76	class	class	NOUN
ap-5377	206	77	number	number	NOUN
ap-5377	206	78	)	)	PUNCT
ap-5377	206	79	end	end	NOUN
ap-5377	206	80	algorithm	algorithm	NOUN
ap-5377	206	81	1	1	NUM
ap-5377	206	82	:	:	PUNCT
ap-5377	206	83	general	general	ADJ
ap-5377	206	84	algorithm	algorithm	NOUN
ap-5377	206	85	of	of	ADP
ap-5377	206	86	modified	modify	VERB
ap-5377	206	87	dbscan	dbscan	NOUN
ap-5377	206	88	which	which	PRON
ap-5377	206	89	we	we	PRON
ap-5377	206	90	used	use	VERB
ap-5377	206	91	in	in	ADP
ap-5377	206	92	this	this	DET
ap-5377	206	93	study	study	NOUN
ap-5377	206	94	.	.	PUNCT
ap-5377	207	1	2.5	2.5	NUM
ap-5377	207	2	.	.	PUNCT
ap-5377	208	1	denclue	denclue	PROPN
ap-5377	208	2	denclue	denclue	NOUN
ap-5377	208	3	was	be	AUX
ap-5377	208	4	the	the	DET
ap-5377	208	5	second	second	ADJ
ap-5377	208	6	algorithm	algorithm	NOUN
ap-5377	208	7	that	that	PRON
ap-5377	208	8	we	we	PRON
ap-5377	208	9	tested	test	VERB
ap-5377	208	10	.	.	PUNCT
ap-5377	209	1	denclue	denclue	NOUN
ap-5377	209	2	is	be	AUX
ap-5377	209	3	also	also	ADV
ap-5377	209	4	a	a	DET
ap-5377	209	5	density	density	NOUN
ap-5377	209	6	based	base	VERB
ap-5377	209	7	algorithm	algorithm	NOUN
ap-5377	209	8	.	.	PUNCT
ap-5377	210	1	the	the	DET
ap-5377	210	2	algorithm	algorithm	NOUN
ap-5377	210	3	is	be	AUX
ap-5377	210	4	created	create	VERB
ap-5377	210	5	for	for	ADP
ap-5377	210	6	large	large	ADJ
ap-5377	210	7	datasets	dataset	NOUN
ap-5377	210	8	in	in	ADP
ap-5377	210	9	a	a	DET
ap-5377	210	10	multidimensional	multidimensional	ADJ
ap-5377	210	11	space	space	NOUN
ap-5377	210	12	[	[	X
ap-5377	210	13	36	36	NUM
ap-5377	210	14	]	]	PUNCT
ap-5377	210	15	.	.	PUNCT
ap-5377	211	1	the	the	DET
ap-5377	211	2	number	number	NOUN
ap-5377	211	3	of	of	ADP
ap-5377	211	4	clusters	cluster	NOUN
ap-5377	211	5	is	be	AUX
ap-5377	211	6	estimated	estimate	VERB
ap-5377	211	7	automatically	automatically	ADV
ap-5377	211	8	,	,	PUNCT
ap-5377	211	9	like	like	ADP
ap-5377	211	10	with	with	ADP
ap-5377	211	11	dbscan	dbscan	NOUN
ap-5377	211	12	.	.	PUNCT
ap-5377	212	1	the	the	DET
ap-5377	212	2	initial	initial	ADJ
ap-5377	212	3	computing	computing	NOUN
ap-5377	212	4	segment	segment	NOUN
ap-5377	212	5	is	be	AUX
ap-5377	212	6	not	not	PART
ap-5377	212	7	random	random	ADJ
ap-5377	212	8	,	,	PUNCT
ap-5377	212	9	compared	compare	VERB
ap-5377	212	10	to	to	ADP
ap-5377	212	11	the	the	DET
ap-5377	212	12	dbscan	dbscan	NOUN
ap-5377	212	13	and	and	CCONJ
ap-5377	212	14	k	k	ADJ
ap-5377	212	15	-	-	PUNCT
ap-5377	212	16	means	mean	VERB
ap-5377	212	17	algorithms	algorithm	NOUN
ap-5377	212	18	.	.	PUNCT
ap-5377	213	1	the	the	DET
ap-5377	213	2	denclue	denclue	NOUN
ap-5377	213	3	algorithm	algorithm	NOUN
ap-5377	213	4	used	use	VERB
ap-5377	213	5	two	two	NUM
ap-5377	213	6	initial	initial	ADJ
ap-5377	213	7	coefficients	coefficient	NOUN
ap-5377	213	8	,	,	PUNCT
ap-5377	213	9	the	the	DET
ap-5377	213	10	smoothness	smoothness	ADJ
ap-5377	213	11	coefficient	coefficient	NOUN
ap-5377	213	12	h	h	NOUN
ap-5377	213	13	and	and	CCONJ
ap-5377	213	14	the	the	DET
ap-5377	213	15	noise	noise	NOUN
ap-5377	213	16	coefficient	coefficient	NOUN
ap-5377	213	17	ξ	ξ	PROPN
ap-5377	213	18	.	.	PUNCT
ap-5377	214	1	the	the	DET
ap-5377	214	2	main	main	ADJ
ap-5377	214	3	difference	difference	NOUN
ap-5377	214	4	between	between	ADP
ap-5377	214	5	denclue	denclue	NOUN
ap-5377	214	6	and	and	CCONJ
ap-5377	214	7	dbscan	dbscan	NOUN
ap-5377	214	8	is	be	AUX
ap-5377	214	9	that	that	DET
ap-5377	214	10	denclue	denclue	NOUN
ap-5377	214	11	is	be	AUX
ap-5377	214	12	based	base	VERB
ap-5377	214	13	on	on	ADP
ap-5377	214	14	a	a	DET
ap-5377	214	15	statistical	statistical	ADJ
ap-5377	214	16	bases	basis	NOUN
ap-5377	214	17	.	.	PUNCT
ap-5377	215	1	specifically	specifically	ADV
ap-5377	215	2	,	,	PUNCT
ap-5377	215	3	denclue	denclue	NOUN
ap-5377	215	4	is	be	AUX
ap-5377	215	5	based	base	VERB
ap-5377	215	6	on	on	ADP
ap-5377	215	7	kernel	kernel	PROPN
ap-5377	215	8	density	density	PROPN
ap-5377	215	9	estimation	estimation	PROPN
ap-5377	215	10	(	(	PUNCT
ap-5377	215	11	kde	kde	NOUN
ap-5377	215	12	)	)	PUNCT
ap-5377	215	13	.	.	PUNCT
ap-5377	216	1	[	[	X
ap-5377	216	2	4	4	NUM
ap-5377	216	3	,	,	PUNCT
ap-5377	216	4	37	37	NUM
ap-5377	216	5	]	]	PUNCT
ap-5377	216	6	the	the	DET
ap-5377	216	7	basic	basic	ADJ
ap-5377	216	8	idea	idea	NOUN
ap-5377	216	9	of	of	ADP
ap-5377	216	10	kde	kde	NOUN
ap-5377	216	11	is	be	AUX
ap-5377	216	12	that	that	SCONJ
ap-5377	216	13	we	we	PRON
ap-5377	216	14	can	can	AUX
ap-5377	216	15	describe	describe	VERB
ap-5377	216	16	the	the	DET
ap-5377	216	17	influence	influence	NOUN
ap-5377	216	18	of	of	ADP
ap-5377	216	19	each	each	DET
ap-5377	216	20	object	object	NOUN
ap-5377	216	21	in	in	ADP
ap-5377	216	22	its	its	PRON
ap-5377	216	23	neighbourhoods	neighbourhood	NOUN
ap-5377	216	24	by	by	ADP
ap-5377	216	25	kernel	kernel	PROPN
ap-5377	216	26	function	function	PROPN
ap-5377	216	27	.	.	PUNCT
ap-5377	217	1	we	we	PRON
ap-5377	217	2	can	can	AUX
ap-5377	217	3	calculate	calculate	VERB
ap-5377	217	4	the	the	DET
ap-5377	217	5	total	total	ADJ
ap-5377	217	6	density	density	NOUN
ap-5377	217	7	function	function	NOUN
ap-5377	217	8	in	in	ADP
ap-5377	217	9	an	an	DET
ap-5377	217	10	object	object	NOUN
ap-5377	217	11	x	x	PUNCT
ap-5377	217	12	by	by	ADP
ap-5377	217	13	summing	sum	VERB
ap-5377	217	14	this	this	DET
ap-5377	217	15	mathematical	mathematical	ADJ
ap-5377	217	16	function	function	NOUN
ap-5377	217	17	,	,	PUNCT
ap-5377	217	18	as	as	SCONJ
ap-5377	217	19	you	you	PRON
ap-5377	217	20	can	can	AUX
ap-5377	217	21	see	see	VERB
ap-5377	217	22	in	in	ADP
ap-5377	217	23	the	the	DET
ap-5377	217	24	next	next	ADJ
ap-5377	217	25	equation	equation	NOUN
ap-5377	217	26	[	[	X
ap-5377	217	27	4	4	NUM
ap-5377	217	28	]	]	PUNCT
ap-5377	217	29	:	:	PUNCT
ap-5377	217	30	fd	fd	X
ap-5377	217	31	(	(	PUNCT
ap-5377	217	32	x	x	X
ap-5377	217	33	)	)	PUNCT
ap-5377	217	34	=	=	SYM
ap-5377	217	35	1	1	NUM
ap-5377	217	36	nhd	nhd	PROPN
ap-5377	217	37	n∑	n∑	PROPN
ap-5377	217	38	i=1	i=1	PROPN
ap-5377	217	39	fk	fk	INTJ
ap-5377	217	40	(	(	PUNCT
ap-5377	217	41	1	1	NUM
ap-5377	217	42	h	h	NOUN
ap-5377	217	43	(	(	PUNCT
ap-5377	217	44	x−	x−	PROPN
ap-5377	217	45	xi	xi	PROPN
ap-5377	217	46	)	)	PUNCT
ap-5377	217	47	)	)	PUNCT
ap-5377	217	48	,	,	PUNCT
ap-5377	217	49	(	(	PUNCT
ap-5377	217	50	13	13	NUM
ap-5377	217	51	)	)	PUNCT
ap-5377	217	52	where	where	SCONJ
ap-5377	217	53	fd	fd	X
ap-5377	217	54	(	(	PUNCT
ap-5377	217	55	x	x	X
ap-5377	217	56	)	)	PUNCT
ap-5377	217	57	is	be	AUX
ap-5377	217	58	the	the	DET
ap-5377	217	59	total	total	ADJ
ap-5377	217	60	density	density	NOUN
ap-5377	217	61	function	function	NOUN
ap-5377	217	62	in	in	ADP
ap-5377	217	63	an	an	DET
ap-5377	217	64	object	object	NOUN
ap-5377	217	65	x	x	X
ap-5377	217	66	,	,	PUNCT
ap-5377	217	67	h	h	PROPN
ap-5377	217	68	is	be	AUX
ap-5377	217	69	the	the	DET
ap-5377	217	70	smoothness	smoothness	ADJ
ap-5377	217	71	coefficient	coefficient	NOUN
ap-5377	217	72	,	,	PUNCT
ap-5377	217	73	n	n	PRON
ap-5377	217	74	is	be	AUX
ap-5377	217	75	the	the	DET
ap-5377	217	76	number	number	NOUN
ap-5377	217	77	of	of	ADP
ap-5377	217	78	objects	object	NOUN
ap-5377	217	79	,	,	PUNCT
ap-5377	217	80	d	d	X
ap-5377	217	81	is	be	AUX
ap-5377	217	82	the	the	DET
ap-5377	217	83	size	size	NOUN
ap-5377	217	84	dimensions	dimension	NOUN
ap-5377	217	85	of	of	ADP
ap-5377	217	86	feature	feature	NOUN
ap-5377	217	87	space	space	NOUN
ap-5377	217	88	and	and	CCONJ
ap-5377	217	89	fk	fk	INTJ
ap-5377	217	90	is	be	AUX
ap-5377	217	91	the	the	DET
ap-5377	217	92	specific	specific	ADJ
ap-5377	217	93	kernel	kernel	NOUN
ap-5377	217	94	function	function	NOUN
ap-5377	217	95	.	.	PUNCT
ap-5377	218	1	502	502	NUM
ap-5377	218	2	vol	vol	NOUN
ap-5377	218	3	.	.	PUNCT
ap-5377	219	1	59	59	NUM
ap-5377	219	2	no	no	NOUN
ap-5377	219	3	.	.	PUNCT
ap-5377	220	1	5/2019	5/2019	NUM
ap-5377	220	2	automatic	automatic	ADJ
ap-5377	220	3	eeg	eeg	NOUN
ap-5377	220	4	classification	classification	NOUN
ap-5377	220	5	using	use	VERB
ap-5377	220	6	dbscan	dbscan	NOUN
ap-5377	220	7	and	and	CCONJ
ap-5377	220	8	denclue	denclue	NOUN
ap-5377	220	9	overlay	overlay	NOUN
ap-5377	220	10	cell	cell	NOUN
ap-5377	220	11	space	space	NOUN
ap-5377	220	12	(	(	PUNCT
ap-5377	220	13	grid	grid	NOUN
ap-5377	220	14	)	)	PUNCT
ap-5377	220	15	segments	segment	NOUN
ap-5377	220	16	shift	shift	VERB
ap-5377	220	17	feature	feature	NOUN
ap-5377	220	18	space	space	NOUN
ap-5377	220	19	figure	figure	NOUN
ap-5377	220	20	3	3	NUM
ap-5377	220	21	.	.	PUNCT
ap-5377	220	22	cell	cell	NOUN
ap-5377	220	23	space	space	NOUN
ap-5377	220	24	approximation	approximation	NOUN
ap-5377	220	25	in	in	ADP
ap-5377	220	26	gridbscan	gridbscan	PROPN
ap-5377	220	27	classification	classification	NOUN
ap-5377	220	28	.	.	PUNCT
ap-5377	221	1	the	the	DET
ap-5377	221	2	dashed	dash	VERB
ap-5377	221	3	lines	line	NOUN
ap-5377	221	4	indicate	indicate	VERB
ap-5377	221	5	the	the	DET
ap-5377	221	6	shift	shift	NOUN
ap-5377	221	7	in	in	ADP
ap-5377	221	8	the	the	DET
ap-5377	221	9	space	space	NOUN
ap-5377	221	10	with	with	ADP
ap-5377	221	11	the	the	DET
ap-5377	221	12	overlap	overlap	NOUN
ap-5377	221	13	in	in	ADP
ap-5377	221	14	which	which	PRON
ap-5377	221	15	the	the	DET
ap-5377	221	16	clusters	cluster	NOUN
ap-5377	221	17	in	in	ADP
ap-5377	221	18	the	the	DET
ap-5377	221	19	individual	individual	ADJ
ap-5377	221	20	cells	cell	NOUN
ap-5377	221	21	are	be	AUX
ap-5377	221	22	interconnected	interconnect	VERB
ap-5377	221	23	.	.	PUNCT
ap-5377	222	1	the	the	DET
ap-5377	222	2	smoothness	smoothness	ADJ
ap-5377	222	3	coefficient	coefficient	NOUN
ap-5377	222	4	controls	control	VERB
ap-5377	222	5	the	the	DET
ap-5377	222	6	influence	influence	NOUN
ap-5377	222	7	of	of	ADP
ap-5377	222	8	object	object	NOUN
ap-5377	222	9	neighbourhoods	neighbourhood	NOUN
ap-5377	222	10	on	on	ADP
ap-5377	222	11	the	the	DET
ap-5377	222	12	output	output	NOUN
ap-5377	222	13	of	of	ADP
ap-5377	222	14	the	the	DET
ap-5377	222	15	total	total	ADJ
ap-5377	222	16	density	density	NOUN
ap-5377	222	17	function	function	NOUN
ap-5377	222	18	.	.	PUNCT
ap-5377	223	1	the	the	DET
ap-5377	223	2	higher	high	ADJ
ap-5377	223	3	smoothness	smoothness	ADJ
ap-5377	223	4	coefficient	coefficient	NOUN
ap-5377	223	5	leads	lead	VERB
ap-5377	223	6	to	to	ADP
ap-5377	223	7	a	a	DET
ap-5377	223	8	lesser	less	ADJ
ap-5377	223	9	influence	influence	NOUN
ap-5377	223	10	of	of	ADP
ap-5377	223	11	the	the	DET
ap-5377	223	12	objects	object	NOUN
ap-5377	223	13	’	'	PUNCT
ap-5377	223	14	distances	distance	NOUN
ap-5377	223	15	and	and	CCONJ
ap-5377	223	16	higher	high	ADJ
ap-5377	223	17	smoothness	smoothness	NOUN
ap-5377	223	18	of	of	ADP
ap-5377	223	19	the	the	DET
ap-5377	223	20	total	total	ADJ
ap-5377	223	21	density	density	NOUN
ap-5377	223	22	function	function	NOUN
ap-5377	223	23	.	.	PUNCT
ap-5377	224	1	this	this	PRON
ap-5377	224	2	means	mean	VERB
ap-5377	224	3	that	that	SCONJ
ap-5377	224	4	the	the	DET
ap-5377	224	5	higher	high	ADJ
ap-5377	224	6	smoothness	smoothness	ADJ
ap-5377	224	7	coefficient	coefficient	NOUN
ap-5377	224	8	will	will	AUX
ap-5377	224	9	reduce	reduce	VERB
ap-5377	224	10	the	the	DET
ap-5377	224	11	number	number	NOUN
ap-5377	224	12	of	of	ADP
ap-5377	224	13	result	result	NOUN
ap-5377	224	14	clusters	cluster	NOUN
ap-5377	224	15	.	.	PUNCT
ap-5377	225	1	we	we	PRON
ap-5377	225	2	can	can	AUX
ap-5377	225	3	use	use	VERB
ap-5377	225	4	several	several	ADJ
ap-5377	225	5	kernel	kernel	NOUN
ap-5377	225	6	functions	function	NOUN
ap-5377	225	7	fk	fk	INTJ
ap-5377	225	8	.	.	PUNCT
ap-5377	226	1	[	[	X
ap-5377	226	2	4	4	NUM
ap-5377	226	3	,	,	PUNCT
ap-5377	226	4	37	37	NUM
ap-5377	226	5	]	]	PUNCT
ap-5377	226	6	we	we	PRON
ap-5377	226	7	used	use	VERB
ap-5377	226	8	the	the	DET
ap-5377	226	9	triangle	triangle	NOUN
ap-5377	226	10	kernel	kernel	NOUN
ap-5377	226	11	in	in	ADP
ap-5377	226	12	our	our	PRON
ap-5377	226	13	article	article	NOUN
ap-5377	226	14	,	,	PUNCT
ap-5377	226	15	see	see	VERB
ap-5377	226	16	equation	equation	NOUN
ap-5377	226	17	14	14	NUM
ap-5377	227	1	[	[	X
ap-5377	227	2	38	38	NUM
ap-5377	227	3	]	]	PUNCT
ap-5377	227	4	:	:	PUNCT
ap-5377	227	5	fk	fk	INTJ
ap-5377	227	6	(	(	PUNCT
ap-5377	227	7	x	x	X
ap-5377	227	8	)	)	PUNCT
ap-5377	227	9	=	=	SYM
ap-5377	228	1	1−	1−	NUM
ap-5377	228	2	|x|	|x|	PROPN
ap-5377	228	3	x	x	X
ap-5377	228	4	ε	ε	PROPN
ap-5377	228	5	(	(	PUNCT
ap-5377	228	6	−1	−1	NOUN
ap-5377	228	7	,	,	PUNCT
ap-5377	228	8	1	1	NUM
ap-5377	228	9	)	)	PUNCT
ap-5377	228	10	,	,	PUNCT
ap-5377	228	11	(	(	PUNCT
ap-5377	228	12	14	14	NUM
ap-5377	228	13	)	)	PUNCT
ap-5377	228	14	where	where	SCONJ
ap-5377	228	15	fk	fk	INTJ
ap-5377	228	16	(	(	PUNCT
ap-5377	228	17	x	x	X
ap-5377	228	18	)	)	PUNCT
ap-5377	228	19	is	be	AUX
ap-5377	228	20	kernel	kernel	NOUN
ap-5377	228	21	function	function	NOUN
ap-5377	228	22	in	in	ADP
ap-5377	228	23	an	an	DET
ap-5377	228	24	object	object	NOUN
ap-5377	228	25	x.	x.	NOUN
ap-5377	229	1	the	the	DET
ap-5377	229	2	disadvantage	disadvantage	NOUN
ap-5377	229	3	of	of	ADP
ap-5377	229	4	kde	kde	NOUN
ap-5377	229	5	is	be	AUX
ap-5377	229	6	in	in	ADP
ap-5377	229	7	its	its	PRON
ap-5377	229	8	high	high	ADJ
ap-5377	229	9	computational	computational	ADJ
ap-5377	229	10	complexity	complexity	NOUN
ap-5377	229	11	.	.	PUNCT
ap-5377	230	1	the	the	DET
ap-5377	230	2	denclue	denclue	NOUN
ap-5377	230	3	algorithm	algorithm	NOUN
ap-5377	230	4	reduces	reduce	VERB
ap-5377	230	5	the	the	DET
ap-5377	230	6	computational	computational	ADJ
ap-5377	230	7	complexity	complexity	NOUN
ap-5377	230	8	by	by	ADP
ap-5377	230	9	using	use	VERB
ap-5377	230	10	the	the	DET
ap-5377	230	11	average	average	ADJ
ap-5377	230	12	shifted	shift	VERB
ap-5377	230	13	histogram	histogram	NOUN
ap-5377	230	14	(	(	PUNCT
ap-5377	230	15	ash	ash	NOUN
ap-5377	230	16	)	)	PUNCT
ap-5377	230	17	.	.	PUNCT
ap-5377	231	1	because	because	SCONJ
ap-5377	231	2	we	we	PRON
ap-5377	231	3	compute	compute	VERB
ap-5377	231	4	only	only	ADV
ap-5377	231	5	with	with	ADP
ap-5377	231	6	occupied	occupy	VERB
ap-5377	231	7	cells	cell	NOUN
ap-5377	231	8	in	in	ADP
ap-5377	231	9	ash	ash	NOUN
ap-5377	231	10	.	.	PUNCT
ap-5377	232	1	the	the	DET
ap-5377	232	2	histogram	histogram	NOUN
ap-5377	232	3	is	be	AUX
ap-5377	232	4	very	very	ADV
ap-5377	232	5	sensitive	sensitive	ADJ
ap-5377	232	6	to	to	AUX
ap-5377	232	7	origin	origin	VERB
ap-5377	232	8	and	and	CCONJ
ap-5377	232	9	that	that	PRON
ap-5377	232	10	is	be	AUX
ap-5377	232	11	a	a	DET
ap-5377	232	12	principle	principle	NOUN
ap-5377	232	13	of	of	ADP
ap-5377	232	14	ash	ash	NOUN
ap-5377	232	15	.	.	PUNCT
ap-5377	233	1	we	we	PRON
ap-5377	233	2	have	have	VERB
ap-5377	233	3	several	several	ADJ
ap-5377	233	4	histograms	histogram	NOUN
ap-5377	233	5	with	with	ADP
ap-5377	233	6	different	different	ADJ
ap-5377	233	7	origins	origin	NOUN
ap-5377	233	8	(	(	PUNCT
ap-5377	233	9	shifted	shift	VERB
ap-5377	233	10	histograms	histogram	NOUN
ap-5377	233	11	)	)	PUNCT
ap-5377	233	12	.	.	PUNCT
ap-5377	234	1	when	when	SCONJ
ap-5377	234	2	a	a	DET
ap-5377	234	3	number	number	NOUN
ap-5377	234	4	of	of	ADP
ap-5377	234	5	shifting	shift	VERB
ap-5377	234	6	histograms	histogram	NOUN
ap-5377	234	7	are	be	AUX
ap-5377	234	8	approaching	approach	VERB
ap-5377	234	9	infinity	infinity	NOUN
ap-5377	234	10	,	,	PUNCT
ap-5377	234	11	the	the	DET
ap-5377	234	12	result	result	NOUN
ap-5377	234	13	of	of	ADP
ap-5377	234	14	ash	ash	NOUN
ap-5377	234	15	is	be	AUX
ap-5377	234	16	similarly	similarly	ADV
ap-5377	234	17	to	to	ADP
ap-5377	234	18	the	the	DET
ap-5377	234	19	result	result	NOUN
ap-5377	234	20	of	of	ADP
ap-5377	234	21	a	a	DET
ap-5377	234	22	kde	kde	NOUN
ap-5377	234	23	[	[	X
ap-5377	234	24	39	39	NUM
ap-5377	234	25	]	]	PUNCT
ap-5377	234	26	.	.	PUNCT
ap-5377	235	1	for	for	ADP
ap-5377	235	2	more	more	ADJ
ap-5377	235	3	information	information	NOUN
ap-5377	235	4	,	,	PUNCT
ap-5377	235	5	see	see	VERB
ap-5377	235	6	,	,	PUNCT
ap-5377	235	7	for	for	ADP
ap-5377	235	8	example	example	NOUN
ap-5377	235	9	,	,	PUNCT
ap-5377	235	10	[	[	X
ap-5377	235	11	40	40	NUM
ap-5377	235	12	,	,	PUNCT
ap-5377	235	13	41	41	NUM
ap-5377	235	14	]	]	PUNCT
ap-5377	235	15	.	.	PUNCT
ap-5377	236	1	the	the	DET
ap-5377	236	2	occupancy	occupancy	NOUN
ap-5377	236	3	of	of	ADP
ap-5377	236	4	histogram	histogram	NOUN
ap-5377	236	5	cells	cell	NOUN
ap-5377	236	6	decreases	decrease	VERB
ap-5377	236	7	with	with	ADP
ap-5377	236	8	a	a	DET
ap-5377	236	9	rising	rise	VERB
ap-5377	236	10	dimension	dimension	NOUN
ap-5377	236	11	of	of	ADP
ap-5377	236	12	feature	feature	NOUN
ap-5377	236	13	space	space	NOUN
ap-5377	236	14	.	.	PUNCT
ap-5377	237	1	this	this	DET
ap-5377	237	2	problem	problem	NOUN
ap-5377	237	3	also	also	ADV
ap-5377	237	4	improves	improve	VERB
ap-5377	237	5	ash	ash	NOUN
ap-5377	237	6	.	.	PUNCT
ap-5377	238	1	we	we	PRON
ap-5377	238	2	used	use	VERB
ap-5377	238	3	2+d	2+d	NUM
ap-5377	238	4	shifted	shift	VERB
ap-5377	238	5	histograms	histogram	NOUN
ap-5377	238	6	in	in	ADP
ap-5377	238	7	denclue	denclue	NOUN
ap-5377	238	8	,	,	PUNCT
ap-5377	238	9	where	where	SCONJ
ap-5377	238	10	d	d	NOUN
ap-5377	238	11	is	be	AUX
ap-5377	238	12	the	the	DET
ap-5377	238	13	number	number	NOUN
ap-5377	238	14	of	of	ADP
ap-5377	238	15	dimensions	dimension	NOUN
ap-5377	238	16	in	in	ADP
ap-5377	238	17	feature	feature	NOUN
ap-5377	238	18	space	space	NOUN
ap-5377	238	19	.	.	PUNCT
ap-5377	239	1	[	[	X
ap-5377	239	2	4	4	NUM
ap-5377	239	3	,	,	PUNCT
ap-5377	239	4	40	40	NUM
ap-5377	239	5	]	]	PUNCT
ap-5377	239	6	the	the	DET
ap-5377	239	7	second	second	ADJ
ap-5377	239	8	part	part	NOUN
ap-5377	239	9	of	of	ADP
ap-5377	239	10	the	the	DET
ap-5377	239	11	denclue	denclue	NOUN
ap-5377	239	12	algorithm	algorithm	NOUN
ap-5377	239	13	is	be	AUX
ap-5377	239	14	a	a	DET
ap-5377	239	15	distribution	distribution	NOUN
ap-5377	239	16	of	of	ADP
ap-5377	239	17	objects	object	NOUN
ap-5377	239	18	in	in	ADP
ap-5377	239	19	clusters	cluster	NOUN
ap-5377	239	20	.	.	PUNCT
ap-5377	240	1	the	the	DET
ap-5377	240	2	denclue	denclue	NOUN
ap-5377	240	3	algorithm	algorithm	NOUN
ap-5377	240	4	is	be	AUX
ap-5377	240	5	looking	look	VERB
ap-5377	240	6	for	for	ADP
ap-5377	240	7	the	the	DET
ap-5377	240	8	local	local	ADJ
ap-5377	240	9	maximum	maximum	NOUN
ap-5377	240	10	of	of	ADP
ap-5377	240	11	the	the	DET
ap-5377	240	12	density	density	NOUN
ap-5377	240	13	function	function	NOUN
ap-5377	240	14	,	,	PUNCT
ap-5377	240	15	which	which	PRON
ap-5377	240	16	was	be	AUX
ap-5377	240	17	created	create	VERB
ap-5377	240	18	using	use	VERB
ap-5377	240	19	ash	ash	NOUN
ap-5377	240	20	.	.	PUNCT
ap-5377	241	1	multicentre	multicentre	ADJ
ap-5377	241	2	definition	definition	NOUN
ap-5377	241	3	of	of	ADP
ap-5377	241	4	the	the	DET
ap-5377	241	5	cluster	cluster	NOUN
ap-5377	241	6	can	can	AUX
ap-5377	241	7	be	be	AUX
ap-5377	241	8	used	use	VERB
ap-5377	241	9	in	in	ADP
ap-5377	241	10	denclue	denclue	NOUN
ap-5377	241	11	to	to	PART
ap-5377	241	12	distinguish	distinguish	VERB
ap-5377	241	13	nested	nested	ADJ
ap-5377	241	14	clusters	cluster	NOUN
ap-5377	241	15	.	.	PUNCT
ap-5377	242	1	we	we	PRON
ap-5377	242	2	will	will	AUX
ap-5377	242	3	go	go	VERB
ap-5377	242	4	on	on	ADP
ap-5377	242	5	to	to	PART
ap-5377	242	6	describe	describe	VERB
ap-5377	242	7	this	this	DET
ap-5377	242	8	definition	definition	NOUN
ap-5377	242	9	of	of	ADP
ap-5377	242	10	the	the	DET
ap-5377	242	11	cluster	cluster	NOUN
ap-5377	242	12	.	.	PUNCT
ap-5377	243	1	the	the	DET
ap-5377	243	2	denclue	denclue	NOUN
ap-5377	243	3	algorithm	algorithm	NOUN
ap-5377	243	4	finds	find	VERB
ap-5377	243	5	an	an	DET
ap-5377	243	6	object	object	NOUN
ap-5377	243	7	(	(	PUNCT
ap-5377	243	8	cell	cell	NOUN
ap-5377	243	9	containing	contain	VERB
ap-5377	243	10	objects	object	NOUN
ap-5377	243	11	)	)	PUNCT
ap-5377	243	12	on	on	ADP
ap-5377	243	13	the	the	DET
ap-5377	243	14	position	position	NOUN
ap-5377	243	15	of	of	ADP
ap-5377	243	16	the	the	DET
ap-5377	243	17	local	local	ADJ
ap-5377	243	18	maximum	maximum	NOUN
ap-5377	243	19	of	of	ADP
ap-5377	243	20	the	the	DET
ap-5377	243	21	density	density	NOUN
ap-5377	243	22	function	function	NOUN
ap-5377	243	23	and	and	CCONJ
ap-5377	243	24	determine	determine	VERB
ap-5377	243	25	,	,	PUNCT
ap-5377	243	26	if	if	SCONJ
ap-5377	243	27	the	the	DET
ap-5377	243	28	local	local	ADJ
ap-5377	243	29	maximum	maximum	NOUN
ap-5377	243	30	is	be	AUX
ap-5377	243	31	higher	high	ADJ
ap-5377	243	32	than	than	ADP
ap-5377	243	33	the	the	DET
ap-5377	243	34	noise	noise	NOUN
ap-5377	243	35	coefficient	coefficient	NOUN
ap-5377	243	36	.	.	PUNCT
ap-5377	244	1	if	if	SCONJ
ap-5377	244	2	the	the	DET
ap-5377	244	3	local	local	ADJ
ap-5377	244	4	maximum	maximum	NOUN
ap-5377	244	5	is	be	AUX
ap-5377	244	6	higher	high	ADJ
ap-5377	244	7	than	than	ADP
ap-5377	244	8	the	the	DET
ap-5377	244	9	noise	noise	NOUN
ap-5377	244	10	coefficient	coefficient	NOUN
ap-5377	244	11	,	,	PUNCT
ap-5377	244	12	the	the	DET
ap-5377	244	13	object	object	NOUN
ap-5377	244	14	in	in	ADP
ap-5377	244	15	the	the	DET
ap-5377	244	16	data	datum	NOUN
ap-5377	244	17	:	:	PUNCT
ap-5377	244	18	objects	object	NOUN
ap-5377	244	19	in	in	ADP
ap-5377	244	20	feature	feature	NOUN
ap-5377	244	21	space	space	NOUN
ap-5377	244	22	,	,	PUNCT
ap-5377	244	23	h	h	NOUN
ap-5377	244	24	,	,	PUNCT
ap-5377	244	25	ξ	ξ	PROPN
ap-5377	244	26	result	result	NOUN
ap-5377	244	27	:	:	PUNCT
ap-5377	244	28	objects	object	VERB
ap-5377	244	29	distributed	distribute	VERB
ap-5377	244	30	to	to	ADP
ap-5377	244	31	clusters	cluster	NOUN
ap-5377	244	32	loading	loading	NOUN
ap-5377	244	33	of	of	ADP
ap-5377	244	34	objects	object	NOUN
ap-5377	244	35	for	for	ADP
ap-5377	244	36	i=1	i=1	NOUN
ap-5377	244	37	:	:	PUNCT
ap-5377	244	38	numberofobjects	numberofobject	NOUN
ap-5377	245	1	+	+	CCONJ
ap-5377	245	2	2	2	NUM
ap-5377	245	3	do	do	AUX
ap-5377	245	4	creation	creation	NOUN
ap-5377	245	5	of	of	ADP
ap-5377	245	6	histograms	histogram	NOUN
ap-5377	245	7	cells	cell	NOUN
ap-5377	245	8	(	(	PUNCT
ap-5377	245	9	using	use	VERB
ap-5377	245	10	the	the	DET
ap-5377	245	11	h	h	NOUN
ap-5377	245	12	)	)	PUNCT
ap-5377	245	13	execution	execution	NOUN
ap-5377	245	14	of	of	ADP
ap-5377	245	15	i	i	PROPN
ap-5377	245	16	-	-	PUNCT
ap-5377	245	17	th	th	X
ap-5377	245	18	shifts	shift	NOUN
ap-5377	245	19	distribution	distribution	NOUN
ap-5377	245	20	of	of	ADP
ap-5377	245	21	objects	object	NOUN
ap-5377	245	22	to	to	ADP
ap-5377	245	23	cell	cell	NOUN
ap-5377	245	24	of	of	ADP
ap-5377	245	25	histograms	histogram	NOUN
ap-5377	245	26	end	end	VERB
ap-5377	245	27	creation	creation	NOUN
ap-5377	245	28	of	of	ADP
ap-5377	245	29	ash	ash	NOUN
ap-5377	245	30	from	from	ADP
ap-5377	245	31	histograms	histogram	NOUN
ap-5377	245	32	finds	find	VERB
ap-5377	245	33	local	local	ADJ
ap-5377	245	34	maxima	maxima	NOUN
ap-5377	245	35	of	of	ADP
ap-5377	245	36	ash	ash	NOUN
ap-5377	245	37	for	for	ADP
ap-5377	245	38	j=1	j=1	PROPN
ap-5377	245	39	:	:	PUNCT
ap-5377	245	40	numberoflocalmaxima	numberoflocalmaxima	NOUN
ap-5377	245	41	do	do	VERB
ap-5377	245	42	if	if	SCONJ
ap-5377	245	43	amplitude	amplitude	NOUN
ap-5377	245	44	of	of	ADP
ap-5377	245	45	j	j	PROPN
ap-5377	245	46	-	-	PUNCT
ap-5377	245	47	th	th	X
ap-5377	245	48	maximum	maximum	NOUN
ap-5377	245	49	>	>	X
ap-5377	245	50	ξ	ξ	X
ap-5377	245	51	then	then	ADV
ap-5377	245	52	center	center	NOUN
ap-5377	245	53	of	of	ADP
ap-5377	245	54	new	new	ADJ
ap-5377	245	55	cluster	cluster	NOUN
ap-5377	245	56	is	be	AUX
ap-5377	245	57	j	j	PROPN
ap-5377	245	58	-	-	PUNCT
ap-5377	245	59	th	th	VERB
ap-5377	245	60	maximum	maximum	ADJ
ap-5377	245	61	objects	object	NOUN
ap-5377	245	62	attracted	attract	VERB
ap-5377	245	63	to	to	ADP
ap-5377	245	64	i	i	PROPN
ap-5377	245	65	-	-	PUNCT
ap-5377	245	66	th	th	X
ap-5377	245	67	max	max	PROPN
ap-5377	245	68	.	.	PUNCT
ap-5377	246	1	=	=	SYM
ap-5377	246	2	same	same	ADJ
ap-5377	246	3	cluster	cluster	NOUN
ap-5377	246	4	else	else	ADV
ap-5377	246	5	assignment	assignment	NOUN
ap-5377	246	6	of	of	ADP
ap-5377	246	7	j	j	PROPN
ap-5377	246	8	-	-	PUNCT
ap-5377	246	9	th	th	X
ap-5377	246	10	max	max	PROPN
ap-5377	246	11	.	.	PUNCT
ap-5377	247	1	to	to	ADP
ap-5377	247	2	the	the	DET
ap-5377	247	3	noise	noise	NOUN
ap-5377	247	4	cluster	cluster	NOUN
ap-5377	247	5	objects	object	NOUN
ap-5377	247	6	attracted	attract	VERB
ap-5377	247	7	to	to	ADP
ap-5377	247	8	i	i	PROPN
ap-5377	247	9	-	-	PUNCT
ap-5377	247	10	th	th	X
ap-5377	247	11	max	max	PROPN
ap-5377	247	12	.	.	PUNCT
ap-5377	248	1	=	=	NOUN
ap-5377	248	2	noise	noise	NOUN
ap-5377	248	3	cluster	cluster	NOUN
ap-5377	248	4	end	end	NOUN
ap-5377	248	5	end	end	NOUN
ap-5377	248	6	if	if	SCONJ
ap-5377	248	7	ε	ε	PROPN
ap-5377	248	8	path	path	NOUN
ap-5377	248	9	between	between	ADP
ap-5377	248	10	2	2	NUM
ap-5377	248	11	local	local	ADJ
ap-5377	248	12	maxima	maxima	NOUN
ap-5377	248	13	>	>	X
ap-5377	248	14	ξ	ξ	PROPN
ap-5377	248	15	then	then	ADV
ap-5377	248	16	local	local	ADJ
ap-5377	248	17	maxima	maxima	NOUN
ap-5377	248	18	are	be	AUX
ap-5377	248	19	from	from	ADP
ap-5377	248	20	same	same	ADJ
ap-5377	248	21	cluster	cluster	NOUN
ap-5377	248	22	end	end	NOUN
ap-5377	248	23	algorithm	algorithm	NOUN
ap-5377	248	24	2	2	NUM
ap-5377	248	25	:	:	PUNCT
ap-5377	248	26	general	general	ADJ
ap-5377	248	27	of	of	ADP
ap-5377	248	28	denclue	denclue	NOUN
ap-5377	248	29	algorithm	algorithm	NOUN
ap-5377	248	30	used	use	VERB
ap-5377	248	31	in	in	ADP
ap-5377	248	32	this	this	DET
ap-5377	248	33	study	study	NOUN
ap-5377	248	34	with	with	ADP
ap-5377	248	35	the	the	DET
ap-5377	248	36	smoothness	smoothness	ADJ
ap-5377	248	37	coefficient	coefficient	NOUN
ap-5377	248	38	h	h	NOUN
ap-5377	248	39	and	and	CCONJ
ap-5377	248	40	the	the	DET
ap-5377	248	41	noise	noise	NOUN
ap-5377	248	42	coefficient	coefficient	NOUN
ap-5377	248	43	ξ	ξ	PROPN
ap-5377	248	44	.	.	PUNCT
ap-5377	248	45	local	local	ADJ
ap-5377	248	46	maximum	maximum	ADJ
ap-5377	248	47	forms	form	NOUN
ap-5377	248	48	the	the	DET
ap-5377	248	49	centre	centre	NOUN
ap-5377	248	50	of	of	ADP
ap-5377	248	51	the	the	DET
ap-5377	248	52	new	new	ADJ
ap-5377	248	53	cluster	cluster	NOUN
ap-5377	248	54	.	.	PUNCT
ap-5377	249	1	if	if	SCONJ
ap-5377	249	2	the	the	DET
ap-5377	249	3	local	local	ADJ
ap-5377	249	4	maximum	maximum	NOUN
ap-5377	249	5	is	be	AUX
ap-5377	249	6	lower	low	ADJ
ap-5377	249	7	than	than	ADP
ap-5377	249	8	the	the	DET
ap-5377	249	9	noise	noise	NOUN
ap-5377	249	10	coefficient	coefficient	NOUN
ap-5377	249	11	,	,	PUNCT
ap-5377	249	12	the	the	DET
ap-5377	249	13	object	object	NOUN
ap-5377	249	14	in	in	ADP
ap-5377	249	15	the	the	DET
ap-5377	249	16	local	local	ADJ
ap-5377	249	17	maximum	maximum	NOUN
ap-5377	249	18	is	be	AUX
ap-5377	249	19	included	include	VERB
ap-5377	249	20	in	in	ADP
ap-5377	249	21	the	the	DET
ap-5377	249	22	noise	noise	NOUN
ap-5377	249	23	cluster	cluster	NOUN
ap-5377	249	24	.	.	PUNCT
ap-5377	250	1	every	every	DET
ap-5377	250	2	object	object	NOUN
ap-5377	250	3	attracted	attract	VERB
ap-5377	250	4	to	to	ADP
ap-5377	250	5	this	this	DET
ap-5377	250	6	maximum	maximum	NOUN
ap-5377	250	7	includes	include	VERB
ap-5377	250	8	to	to	ADP
ap-5377	250	9	the	the	DET
ap-5377	250	10	same	same	ADJ
ap-5377	250	11	cluster	cluster	NOUN
ap-5377	250	12	as	as	ADP
ap-5377	250	13	their	their	PRON
ap-5377	250	14	attractor	attractor	NOUN
ap-5377	250	15	.	.	PUNCT
ap-5377	251	1	the	the	DET
ap-5377	251	2	local	local	ADJ
ap-5377	251	3	maximum	maximum	NOUN
ap-5377	251	4	includes	include	VERB
ap-5377	251	5	the	the	DET
ap-5377	251	6	same	same	ADJ
ap-5377	251	7	cluster	cluster	NOUN
ap-5377	251	8	,	,	PUNCT
ap-5377	251	9	if	if	SCONJ
ap-5377	251	10	there	there	PRON
ap-5377	251	11	is	be	VERB
ap-5377	251	12	a	a	DET
ap-5377	251	13	path	path	NOUN
ap-5377	251	14	higher	high	ADJ
ap-5377	251	15	than	than	ADP
ap-5377	251	16	the	the	DET
ap-5377	251	17	noise	noise	NOUN
ap-5377	251	18	coefficient	coefficient	NOUN
ap-5377	251	19	between	between	ADP
ap-5377	251	20	them	they	PRON
ap-5377	251	21	.	.	PUNCT
ap-5377	252	1	the	the	DET
ap-5377	252	2	noise	noise	NOUN
ap-5377	252	3	coefficient	coefficient	NOUN
ap-5377	252	4	decreases	decrease	VERB
ap-5377	252	5	the	the	DET
ap-5377	252	6	computing	computing	NOUN
ap-5377	252	7	complexity	complexity	NOUN
ap-5377	252	8	of	of	ADP
ap-5377	252	9	the	the	DET
ap-5377	252	10	algorithm	algorithm	NOUN
ap-5377	252	11	,	,	PUNCT
ap-5377	252	12	allowing	allow	VERB
ap-5377	252	13	creation	creation	NOUN
ap-5377	252	14	of	of	ADP
ap-5377	252	15	the	the	DET
ap-5377	252	16	spatially	spatially	ADV
ap-5377	252	17	entwined	entwine	VERB
ap-5377	252	18	clusters	cluster	NOUN
ap-5377	252	19	and	and	CCONJ
ap-5377	252	20	the	the	DET
ap-5377	252	21	located	locate	VERB
ap-5377	252	22	noise	noise	NOUN
ap-5377	252	23	objects	object	NOUN
ap-5377	252	24	.	.	PUNCT
ap-5377	253	1	[	[	X
ap-5377	253	2	4	4	X
ap-5377	253	3	]	]	PUNCT
ap-5377	253	4	the	the	DET
ap-5377	253	5	denclue	denclue	NOUN
ap-5377	253	6	algorithm	algorithm	NOUN
ap-5377	253	7	was	be	AUX
ap-5377	253	8	programmed	program	VERB
ap-5377	253	9	in	in	ADP
ap-5377	253	10	matlab	matlab	PROPN
ap-5377	253	11	r2015a	r2015a	PROPN
ap-5377	253	12	and	and	CCONJ
ap-5377	253	13	had	have	VERB
ap-5377	253	14	to	to	PART
ap-5377	253	15	be	be	AUX
ap-5377	253	16	modified	modify	VERB
ap-5377	253	17	for	for	ADP
ap-5377	253	18	the	the	DET
ap-5377	253	19	503	503	NUM
ap-5377	253	20	m.	m.	NOUN
ap-5377	253	21	piorecký	piorecký	NOUN
ap-5377	253	22	,	,	PUNCT
ap-5377	253	23	j.	j.	PROPN
ap-5377	253	24	štrobl	štrobl	PROPN
ap-5377	253	25	,	,	PUNCT
ap-5377	253	26	v.	v.	ADP
ap-5377	253	27	krajča	krajča	PROPN
ap-5377	253	28	acta	acta	PROPN
ap-5377	253	29	polytechnica	polytechnica	PROPN
ap-5377	253	30	eeg	eeg	PROPN
ap-5377	253	31	record	record	NOUN
ap-5377	253	32	.	.	PUNCT
ap-5377	254	1	the	the	DET
ap-5377	254	2	problem	problem	NOUN
ap-5377	254	3	can	can	AUX
ap-5377	254	4	be	be	AUX
ap-5377	254	5	that	that	SCONJ
ap-5377	254	6	there	there	PRON
ap-5377	254	7	are	be	VERB
ap-5377	254	8	many	many	ADJ
ap-5377	254	9	more	more	ADJ
ap-5377	254	10	segments	segment	NOUN
ap-5377	254	11	of	of	ADP
ap-5377	254	12	physiological	physiological	ADJ
ap-5377	254	13	activity	activity	NOUN
ap-5377	254	14	compared	compare	VERB
ap-5377	254	15	with	with	ADP
ap-5377	254	16	other	other	ADJ
ap-5377	254	17	segments	segment	NOUN
ap-5377	254	18	in	in	ADP
ap-5377	254	19	the	the	DET
ap-5377	254	20	eeg	eeg	NOUN
ap-5377	254	21	record	record	NOUN
ap-5377	254	22	.	.	PUNCT
ap-5377	255	1	therefore	therefore	ADV
ap-5377	255	2	,	,	PUNCT
ap-5377	255	3	the	the	DET
ap-5377	255	4	denclue	denclue	NOUN
ap-5377	255	5	algorithm	algorithm	NOUN
ap-5377	255	6	had	have	VERB
ap-5377	255	7	two	two	NUM
ap-5377	255	8	parts	part	NOUN
ap-5377	255	9	in	in	ADP
ap-5377	255	10	this	this	DET
ap-5377	255	11	modification	modification	NOUN
ap-5377	255	12	.	.	PUNCT
ap-5377	256	1	segments	segment	NOUN
ap-5377	256	2	of	of	ADP
ap-5377	256	3	the	the	DET
ap-5377	256	4	physiological	physiological	ADJ
ap-5377	256	5	activity	activity	NOUN
ap-5377	256	6	are	be	AUX
ap-5377	256	7	separated	separate	VERB
ap-5377	256	8	from	from	ADP
ap-5377	256	9	other	other	ADJ
ap-5377	256	10	segments	segment	NOUN
ap-5377	256	11	in	in	ADP
ap-5377	256	12	the	the	DET
ap-5377	256	13	first	first	ADJ
ap-5377	256	14	part	part	NOUN
ap-5377	256	15	.	.	PUNCT
ap-5377	257	1	separation	separation	NOUN
ap-5377	257	2	is	be	AUX
ap-5377	257	3	done	do	VERB
ap-5377	257	4	by	by	ADP
ap-5377	257	5	the	the	DET
ap-5377	257	6	noise	noise	NOUN
ap-5377	257	7	coefficient	coefficient	NOUN
ap-5377	257	8	where	where	SCONJ
ap-5377	257	9	every	every	DET
ap-5377	257	10	others	other	NOUN
ap-5377	257	11	segments	segment	NOUN
ap-5377	257	12	should	should	AUX
ap-5377	257	13	be	be	AUX
ap-5377	257	14	included	include	VERB
ap-5377	257	15	in	in	ADP
ap-5377	257	16	a	a	DET
ap-5377	257	17	noise	noise	NOUN
ap-5377	257	18	cluster	cluster	NOUN
ap-5377	257	19	.	.	PUNCT
ap-5377	258	1	the	the	DET
ap-5377	258	2	smoothness	smoothness	ADJ
ap-5377	258	3	coefficient	coefficient	NOUN
ap-5377	258	4	had	have	VERB
ap-5377	258	5	a	a	DET
ap-5377	258	6	value	value	NOUN
ap-5377	258	7	of	of	ADP
ap-5377	258	8	0.0083	0.0083	NUM
ap-5377	258	9	and	and	CCONJ
ap-5377	258	10	the	the	DET
ap-5377	258	11	noise	noise	NOUN
ap-5377	258	12	coefficient	coefficient	NOUN
ap-5377	258	13	had	have	VERB
ap-5377	258	14	a	a	DET
ap-5377	258	15	value	value	NOUN
ap-5377	258	16	of	of	ADP
ap-5377	258	17	750	750	NUM
ap-5377	258	18	in	in	ADP
ap-5377	258	19	the	the	DET
ap-5377	258	20	first	first	ADJ
ap-5377	258	21	part	part	NOUN
ap-5377	258	22	of	of	ADP
ap-5377	258	23	the	the	DET
ap-5377	258	24	modified	modify	VERB
ap-5377	258	25	algorithm	algorithm	NOUN
ap-5377	258	26	.	.	PUNCT
ap-5377	259	1	segments	segment	NOUN
ap-5377	259	2	from	from	ADP
ap-5377	259	3	the	the	DET
ap-5377	259	4	noise	noise	NOUN
ap-5377	259	5	cluster	cluster	NOUN
ap-5377	259	6	are	be	AUX
ap-5377	259	7	divided	divide	VERB
ap-5377	259	8	in	in	ADP
ap-5377	259	9	the	the	DET
ap-5377	259	10	second	second	ADJ
ap-5377	259	11	part	part	NOUN
ap-5377	259	12	of	of	ADP
ap-5377	259	13	the	the	DET
ap-5377	259	14	modified	modify	VERB
ap-5377	259	15	algorithm	algorithm	NOUN
ap-5377	259	16	.	.	PUNCT
ap-5377	260	1	the	the	DET
ap-5377	260	2	smoothness	smoothness	ADJ
ap-5377	260	3	coefficient	coefficient	NOUN
ap-5377	260	4	had	have	VERB
ap-5377	260	5	a	a	DET
ap-5377	260	6	value	value	NOUN
ap-5377	260	7	of	of	ADP
ap-5377	260	8	0.0625	0.0625	NUM
ap-5377	260	9	and	and	CCONJ
ap-5377	260	10	the	the	DET
ap-5377	260	11	noise	noise	NOUN
ap-5377	260	12	coefficient	coefficient	NOUN
ap-5377	260	13	had	have	VERB
ap-5377	260	14	a	a	DET
ap-5377	260	15	value	value	NOUN
ap-5377	260	16	of	of	ADP
ap-5377	260	17	35	35	NUM
ap-5377	260	18	during	during	ADP
ap-5377	260	19	the	the	DET
ap-5377	260	20	second	second	ADJ
ap-5377	260	21	run	run	NOUN
ap-5377	260	22	of	of	ADP
ap-5377	260	23	the	the	DET
ap-5377	260	24	denclue	denclue	NOUN
ap-5377	260	25	algorithm	algorithm	NOUN
ap-5377	260	26	.	.	PUNCT
ap-5377	261	1	2.6	2.6	NUM
ap-5377	261	2	.	.	PUNCT
ap-5377	262	1	statistical	statistical	ADJ
ap-5377	262	2	analysis	analysis	NOUN
ap-5377	262	3	we	we	PRON
ap-5377	262	4	divided	divide	VERB
ap-5377	262	5	the	the	DET
ap-5377	262	6	segments	segment	NOUN
ap-5377	262	7	of	of	ADP
ap-5377	262	8	the	the	DET
ap-5377	262	9	tested	test	VERB
ap-5377	262	10	eeg	eeg	NOUN
ap-5377	262	11	records	record	NOUN
ap-5377	262	12	into	into	ADP
ap-5377	262	13	five	five	NUM
ap-5377	262	14	classes	class	NOUN
ap-5377	262	15	,	,	PUNCT
ap-5377	262	16	concretely	concretely	ADV
ap-5377	262	17	:	:	PUNCT
ap-5377	262	18	physiological	physiological	ADJ
ap-5377	262	19	activity	activity	NOUN
ap-5377	262	20	(	(	PUNCT
ap-5377	262	21	phy	phy	NOUN
ap-5377	262	22	)	)	PUNCT
ap-5377	262	23	,	,	PUNCT
ap-5377	262	24	emg	emg	NOUN
ap-5377	262	25	artefacts	artefact	NOUN
ap-5377	262	26	(	(	PUNCT
ap-5377	262	27	emg	emg	NOUN
ap-5377	262	28	)	)	PUNCT
ap-5377	262	29	,	,	PUNCT
ap-5377	262	30	epileptic	epileptic	ADJ
ap-5377	262	31	activity	activity	NOUN
ap-5377	262	32	(	(	PUNCT
ap-5377	262	33	epi	epi	NOUN
ap-5377	262	34	)	)	PUNCT
ap-5377	262	35	,	,	PUNCT
ap-5377	262	36	slow	slow	ADJ
ap-5377	262	37	eye	eye	NOUN
ap-5377	262	38	artefacts	artefact	NOUN
ap-5377	262	39	(	(	PUNCT
ap-5377	262	40	slow	slow	ADJ
ap-5377	262	41	)	)	PUNCT
ap-5377	262	42	,	,	PUNCT
ap-5377	262	43	and	and	CCONJ
ap-5377	262	44	artefacts	artefact	NOUN
ap-5377	262	45	from	from	ADP
ap-5377	262	46	poor	poor	ADJ
ap-5377	262	47	electrode	electrode	NOUN
ap-5377	262	48	contact	contact	NOUN
ap-5377	262	49	electrode	electrode	NOUN
ap-5377	262	50	pop	pop	NOUN
ap-5377	262	51	(	(	PUNCT
ap-5377	262	52	pop	pop	NOUN
ap-5377	262	53	)	)	PUNCT
ap-5377	262	54	.	.	PUNCT
ap-5377	263	1	figure	figure	VERB
ap-5377	263	2	4	4	NUM
ap-5377	263	3	.	.	PUNCT
ap-5377	264	1	we	we	PRON
ap-5377	264	2	include	include	VERB
ap-5377	264	3	waves	wave	NOUN
ap-5377	264	4	with	with	ADP
ap-5377	264	5	sinus	sinus	NOUN
ap-5377	264	6	characteristics	characteristic	NOUN
ap-5377	264	7	among	among	ADP
ap-5377	264	8	the	the	DET
ap-5377	264	9	physiological	physiological	ADJ
ap-5377	264	10	activity	activity	NOUN
ap-5377	264	11	.	.	PUNCT
ap-5377	265	1	figure	figure	NOUN
ap-5377	265	2	5	5	NUM
ap-5377	265	3	.	.	PUNCT
ap-5377	265	4	segments	segment	NOUN
ap-5377	265	5	from	from	ADP
ap-5377	265	6	eye	eye	NOUN
ap-5377	265	7	movement	movement	NOUN
ap-5377	265	8	and	and	CCONJ
ap-5377	265	9	blinking	blink	VERB
ap-5377	265	10	are	be	AUX
ap-5377	265	11	included	include	VERB
ap-5377	265	12	in	in	ADP
ap-5377	265	13	the	the	DET
ap-5377	265	14	class	class	NOUN
ap-5377	265	15	slow	slow	ADJ
ap-5377	265	16	eye	eye	NOUN
ap-5377	265	17	artefacts	artefact	NOUN
ap-5377	265	18	.	.	PUNCT
ap-5377	266	1	figure	figure	NOUN
ap-5377	266	2	6	6	NUM
ap-5377	266	3	.	.	PUNCT
ap-5377	267	1	epileptic	epileptic	ADJ
ap-5377	267	2	activity	activity	NOUN
ap-5377	267	3	with	with	ADP
ap-5377	267	4	high	high	ADJ
ap-5377	267	5	amplitude	amplitude	NOUN
ap-5377	267	6	of	of	ADP
ap-5377	267	7	the	the	DET
ap-5377	267	8	apex	apex	NOUN
ap-5377	267	9	.	.	PUNCT
ap-5377	268	1	figure	figure	NOUN
ap-5377	268	2	7	7	NUM
ap-5377	268	3	.	.	PUNCT
ap-5377	268	4	emg	emg	NOUN
ap-5377	268	5	artefacts	artefact	NOUN
ap-5377	268	6	is	be	AUX
ap-5377	268	7	in	in	ADP
ap-5377	268	8	the	the	DET
ap-5377	268	9	classroom	classroom	NOUN
ap-5377	268	10	,	,	PUNCT
ap-5377	268	11	which	which	PRON
ap-5377	268	12	includes	include	VERB
ap-5377	268	13	shaded	shaded	ADJ
ap-5377	268	14	segments	segment	NOUN
ap-5377	268	15	with	with	ADP
ap-5377	268	16	a	a	DET
ap-5377	268	17	line	line	NOUN
ap-5377	268	18	noise	noise	NOUN
ap-5377	268	19	,	,	PUNCT
ap-5377	268	20	when	when	SCONJ
ap-5377	268	21	the	the	DET
ap-5377	268	22	noise	noise	NOUN
ap-5377	268	23	completely	completely	ADV
ap-5377	268	24	distorts	distort	VERB
ap-5377	268	25	the	the	DET
ap-5377	268	26	original	original	ADJ
ap-5377	268	27	signal	signal	NOUN
ap-5377	268	28	.	.	PUNCT
ap-5377	269	1	figure	figure	NOUN
ap-5377	269	2	8	8	NUM
ap-5377	269	3	.	.	PUNCT
ap-5377	270	1	the	the	DET
ap-5377	270	2	wrong	wrong	ADJ
ap-5377	270	3	contact	contact	NOUN
ap-5377	270	4	of	of	ADP
ap-5377	270	5	the	the	DET
ap-5377	270	6	electrode	electrode	NOUN
ap-5377	270	7	is	be	AUX
ap-5377	270	8	manifested	manifest	VERB
ap-5377	270	9	by	by	ADP
ap-5377	270	10	a	a	DET
ap-5377	270	11	narrow	narrow	ADJ
ap-5377	270	12	positive	positive	ADJ
ap-5377	270	13	point	point	NOUN
ap-5377	270	14	with	with	ADP
ap-5377	270	15	a	a	DET
ap-5377	270	16	high	high	ADJ
ap-5377	270	17	amplitude	amplitude	NOUN
ap-5377	270	18	.	.	PUNCT
ap-5377	271	1	these	these	DET
ap-5377	271	2	artefacts	artefact	NOUN
ap-5377	271	3	usually	usually	ADV
ap-5377	271	4	occur	occur	VERB
ap-5377	271	5	only	only	ADV
ap-5377	271	6	in	in	ADP
ap-5377	271	7	one	one	NUM
ap-5377	271	8	channel	channel	NOUN
ap-5377	271	9	.	.	PUNCT
ap-5377	272	1	we	we	PRON
ap-5377	272	2	tested	test	VERB
ap-5377	272	3	the	the	DET
ap-5377	272	4	efficiency	efficiency	NOUN
ap-5377	272	5	of	of	ADP
ap-5377	272	6	algorithms	algorithm	NOUN
ap-5377	272	7	using	use	VERB
ap-5377	272	8	the	the	DET
ap-5377	272	9	roc	roc	PROPN
ap-5377	272	10	analysis	analysis	NOUN
ap-5377	272	11	,	,	PUNCT
ap-5377	272	12	which	which	PRON
ap-5377	272	13	is	be	AUX
ap-5377	272	14	suitable	suitable	ADJ
ap-5377	272	15	for	for	ADP
ap-5377	272	16	binary	binary	ADJ
ap-5377	272	17	data	datum	NOUN
ap-5377	272	18	evaluation	evaluation	NOUN
ap-5377	272	19	and	and	CCONJ
ap-5377	272	20	was	be	AUX
ap-5377	272	21	used	use	VERB
ap-5377	272	22	for	for	ADP
ap-5377	272	23	an	an	DET
ap-5377	272	24	evaluation	evaluation	NOUN
ap-5377	272	25	of	of	ADP
ap-5377	272	26	eeg	eeg	PROPN
ap-5377	272	27	[	[	X
ap-5377	272	28	42	42	NUM
ap-5377	272	29	]	]	PUNCT
ap-5377	272	30	.	.	PUNCT
ap-5377	273	1	data	datum	NOUN
ap-5377	273	2	is	be	AUX
ap-5377	273	3	divided	divide	VERB
ap-5377	273	4	into	into	ADP
ap-5377	273	5	two	two	NUM
ap-5377	273	6	groups	group	NOUN
ap-5377	273	7	:	:	PUNCT
ap-5377	273	8	correct	correct	ADJ
ap-5377	273	9	assignment	assignment	NOUN
ap-5377	273	10	to	to	ADP
ap-5377	273	11	a	a	DET
ap-5377	273	12	given	give	VERB
ap-5377	273	13	cluster	cluster	NOUN
ap-5377	273	14	,	,	PUNCT
ap-5377	273	15	and	and	CCONJ
ap-5377	273	16	bad	bad	ADJ
ap-5377	273	17	segment	segment	NOUN
ap-5377	273	18	classification	classification	NOUN
ap-5377	273	19	.	.	PUNCT
ap-5377	274	1	we	we	PRON
ap-5377	274	2	created	create	VERB
ap-5377	274	3	five	five	NUM
ap-5377	274	4	binary	binary	ADJ
ap-5377	274	5	confusion	confusion	NOUN
ap-5377	274	6	matrices	matrix	NOUN
ap-5377	274	7	for	for	ADP
ap-5377	274	8	five	five	NUM
ap-5377	274	9	different	different	ADJ
ap-5377	274	10	classes	class	NOUN
ap-5377	274	11	evaluated	evaluate	VERB
ap-5377	274	12	in	in	ADP
ap-5377	274	13	this	this	DET
ap-5377	274	14	study	study	NOUN
ap-5377	274	15	.	.	PUNCT
ap-5377	275	1	the	the	DET
ap-5377	275	2	confusion	confusion	NOUN
ap-5377	275	3	matrix	matrix	NOUN
ap-5377	275	4	contains	contain	VERB
ap-5377	275	5	information	information	NOUN
ap-5377	275	6	about	about	ADP
ap-5377	275	7	the	the	DET
ap-5377	275	8	real	real	ADJ
ap-5377	275	9	classification	classification	NOUN
ap-5377	275	10	into	into	ADP
ap-5377	275	11	the	the	DET
ap-5377	275	12	class	class	NOUN
ap-5377	275	13	(	(	PUNCT
ap-5377	275	14	expertly	expertly	ADV
ap-5377	275	15	evaluated	evaluate	VERB
ap-5377	275	16	)	)	PUNCT
ap-5377	275	17	and	and	CCONJ
ap-5377	275	18	predicted	predict	VERB
ap-5377	275	19	distribution	distribution	NOUN
ap-5377	275	20	(	(	PUNCT
ap-5377	275	21	classification	classification	NOUN
ap-5377	275	22	by	by	ADP
ap-5377	275	23	algorithms	algorithm	NOUN
ap-5377	275	24	)	)	PUNCT
ap-5377	275	25	.	.	PUNCT
ap-5377	276	1	segments	segment	NOUN
ap-5377	276	2	are	be	AUX
ap-5377	276	3	labelled	label	VERB
ap-5377	276	4	on	on	ADP
ap-5377	276	5	the	the	DET
ap-5377	276	6	basis	basis	NOUN
ap-5377	276	7	of	of	ADP
ap-5377	276	8	this	this	DET
ap-5377	276	9	information	information	NOUN
ap-5377	276	10	.	.	PUNCT
ap-5377	277	1	true	true	ADJ
ap-5377	277	2	positive	positive	ADJ
ap-5377	277	3	(	(	PUNCT
ap-5377	277	4	tp	tp	NOUN
ap-5377	277	5	)	)	PUNCT
ap-5377	277	6	are	be	AUX
ap-5377	277	7	correctly	correctly	ADV
ap-5377	277	8	classified	classified	ADJ
ap-5377	277	9	segments	segment	NOUN
ap-5377	277	10	,	,	PUNCT
ap-5377	277	11	false	false	ADJ
ap-5377	277	12	positive	positive	ADJ
ap-5377	277	13	(	(	PUNCT
ap-5377	277	14	fp	fp	INTJ
ap-5377	277	15	)	)	PUNCT
ap-5377	277	16	are	be	AUX
ap-5377	277	17	mismatched	mismatch	VERB
ap-5377	277	18	segments	segment	NOUN
ap-5377	277	19	that	that	PRON
ap-5377	277	20	do	do	AUX
ap-5377	277	21	not	not	PART
ap-5377	277	22	belong	belong	VERB
ap-5377	277	23	to	to	ADP
ap-5377	277	24	the	the	DET
ap-5377	277	25	cluster	cluster	NOUN
ap-5377	277	26	.	.	PUNCT
ap-5377	278	1	false	false	ADJ
ap-5377	278	2	negative	negative	ADJ
ap-5377	278	3	(	(	PUNCT
ap-5377	278	4	fn	fn	NOUN
ap-5377	278	5	)	)	PUNCT
ap-5377	278	6	are	be	AUX
ap-5377	278	7	segments	segment	NOUN
ap-5377	278	8	that	that	PRON
ap-5377	278	9	belong	belong	VERB
ap-5377	278	10	to	to	ADP
ap-5377	278	11	the	the	DET
ap-5377	278	12	cluster	cluster	NOUN
ap-5377	278	13	but	but	CCONJ
ap-5377	278	14	were	be	AUX
ap-5377	278	15	mistakenly	mistakenly	ADV
ap-5377	278	16	assigned	assign	VERB
ap-5377	278	17	to	to	ADP
ap-5377	278	18	another	another	DET
ap-5377	278	19	cluster	cluster	NOUN
ap-5377	278	20	,	,	PUNCT
ap-5377	278	21	true	true	ADJ
ap-5377	278	22	negative	negative	ADJ
ap-5377	278	23	(	(	PUNCT
ap-5377	278	24	tn	tn	NOUN
ap-5377	278	25	)	)	PUNCT
ap-5377	278	26	are	be	AUX
ap-5377	278	27	the	the	DET
ap-5377	278	28	segments	segment	NOUN
ap-5377	278	29	correctly	correctly	ADV
ap-5377	278	30	assigned	assign	VERB
ap-5377	278	31	to	to	ADP
ap-5377	278	32	a	a	DET
ap-5377	278	33	different	different	ADJ
ap-5377	278	34	class	class	NOUN
ap-5377	278	35	.	.	PUNCT
ap-5377	279	1	then	then	ADV
ap-5377	279	2	,	,	PUNCT
ap-5377	279	3	we	we	PRON
ap-5377	279	4	calculated	calculate	VERB
ap-5377	279	5	specificity	specificity	NOUN
ap-5377	279	6	,	,	PUNCT
ap-5377	279	7	which	which	PRON
ap-5377	279	8	shows	show	VERB
ap-5377	279	9	the	the	DET
ap-5377	279	10	likelihood	likelihood	NOUN
ap-5377	279	11	of	of	ADP
ap-5377	279	12	the	the	DET
ap-5377	279	13	segments	segment	NOUN
ap-5377	279	14	belonging	belong	VERB
ap-5377	279	15	to	to	ADP
ap-5377	279	16	the	the	DET
ap-5377	279	17	cluster	cluster	NOUN
ap-5377	279	18	will	will	AUX
ap-5377	279	19	not	not	PART
ap-5377	279	20	be	be	AUX
ap-5377	279	21	included	include	VERB
ap-5377	279	22	into	into	ADP
ap-5377	279	23	another	another	PRON
ap-5377	279	24	(	(	PUNCT
ap-5377	279	25	see	see	VERB
ap-5377	279	26	equation	equation	NOUN
ap-5377	279	27	15	15	NUM
ap-5377	279	28	)	)	PUNCT
ap-5377	279	29	.	.	PUNCT
ap-5377	280	1	sensitivity	sensitivity	NOUN
ap-5377	280	2	determines	determine	VERB
ap-5377	280	3	the	the	DET
ap-5377	280	4	probability	probability	NOUN
ap-5377	280	5	of	of	ADP
ap-5377	280	6	a	a	DET
ap-5377	280	7	successful	successful	ADJ
ap-5377	280	8	detection	detection	NOUN
ap-5377	280	9	,	,	PUNCT
ap-5377	280	10	which	which	PRON
ap-5377	280	11	means	mean	VERB
ap-5377	280	12	finding	find	VERB
ap-5377	280	13	all	all	DET
ap-5377	280	14	the	the	DET
ap-5377	280	15	segments	segment	NOUN
ap-5377	280	16	belonging	belong	VERB
ap-5377	280	17	to	to	ADP
ap-5377	280	18	the	the	DET
ap-5377	280	19	cluster	cluster	NOUN
ap-5377	280	20	(	(	PUNCT
ap-5377	280	21	see	see	VERB
ap-5377	280	22	equation	equation	NOUN
ap-5377	280	23	16	16	NUM
ap-5377	280	24	)	)	PUNCT
ap-5377	280	25	.	.	PUNCT
ap-5377	281	1	positive	positive	ADJ
ap-5377	281	2	predictive	predictive	ADJ
ap-5377	281	3	value	value	NOUN
ap-5377	281	4	(	(	PUNCT
ap-5377	281	5	ppv	ppv	NOUN
ap-5377	281	6	)	)	PUNCT
ap-5377	281	7	is	be	AUX
ap-5377	281	8	the	the	DET
ap-5377	281	9	most	most	ADV
ap-5377	281	10	telling	telling	NOUN
ap-5377	281	11	parameter	parameter	NOUN
ap-5377	281	12	in	in	ADP
ap-5377	281	13	our	our	PRON
ap-5377	281	14	case	case	NOUN
ap-5377	281	15	,	,	PUNCT
ap-5377	281	16	we	we	PRON
ap-5377	281	17	can	can	AUX
ap-5377	281	18	compare	compare	VERB
ap-5377	281	19	it	it	PRON
ap-5377	281	20	to	to	ADP
ap-5377	281	21	the	the	DET
ap-5377	281	22	homogeneity	homogeneity	NOUN
ap-5377	281	23	of	of	ADP
ap-5377	281	24	the	the	DET
ap-5377	281	25	class	class	NOUN
ap-5377	281	26	(	(	PUNCT
ap-5377	281	27	see	see	VERB
ap-5377	281	28	equation	equation	NOUN
ap-5377	281	29	17	17	NUM
ap-5377	281	30	)	)	PUNCT
ap-5377	282	1	[	[	X
ap-5377	282	2	43	43	NUM
ap-5377	282	3	]	]	NOUN
ap-5377	282	4	:	:	PUNCT
ap-5377	282	5	specificity	specificity	NOUN
ap-5377	282	6	=	=	SYM
ap-5377	282	7	tn	tn	PROPN
ap-5377	282	8	tn	tn	PROPN
ap-5377	283	1	+	+	CCONJ
ap-5377	283	2	fp	fp	INTJ
ap-5377	283	3	,	,	PUNCT
ap-5377	283	4	(	(	PUNCT
ap-5377	283	5	15	15	NUM
ap-5377	283	6	)	)	PUNCT
ap-5377	283	7	where	where	SCONJ
ap-5377	283	8	tn	tn	NOUN
ap-5377	283	9	is	be	AUX
ap-5377	283	10	a	a	DET
ap-5377	283	11	true	true	ADJ
ap-5377	283	12	negative	negative	NOUN
ap-5377	283	13	and	and	CCONJ
ap-5377	283	14	fp	fp	X
ap-5377	283	15	is	be	AUX
ap-5377	283	16	a	a	DET
ap-5377	283	17	false	false	ADJ
ap-5377	283	18	positive	positive	ADJ
ap-5377	283	19	value	value	NOUN
ap-5377	283	20	.	.	PUNCT
ap-5377	284	1	sensitivity	sensitivity	NOUN
ap-5377	284	2	=	=	PUNCT
ap-5377	284	3	tp	tp	NOUN
ap-5377	284	4	tp	tp	NOUN
ap-5377	284	5	+	+	CCONJ
ap-5377	284	6	fn	fn	INTJ
ap-5377	284	7	,	,	PUNCT
ap-5377	284	8	(	(	PUNCT
ap-5377	284	9	16	16	NUM
ap-5377	284	10	)	)	PUNCT
ap-5377	284	11	where	where	SCONJ
ap-5377	284	12	tp	tp	NOUN
ap-5377	284	13	is	be	AUX
ap-5377	284	14	a	a	DET
ap-5377	284	15	true	true	ADJ
ap-5377	284	16	positive	positive	ADJ
ap-5377	284	17	and	and	CCONJ
ap-5377	284	18	fn	fn	NOUN
ap-5377	284	19	is	be	AUX
ap-5377	284	20	a	a	DET
ap-5377	284	21	false	false	ADJ
ap-5377	284	22	negative	negative	ADJ
ap-5377	284	23	value	value	NOUN
ap-5377	284	24	.	.	PUNCT
ap-5377	285	1	ppv	ppv	NOUN
ap-5377	286	1	=	=	NOUN
ap-5377	286	2	tp	tp	NOUN
ap-5377	286	3	tp	tp	ADP
ap-5377	286	4	+	+	CCONJ
ap-5377	286	5	fp	fp	INTJ
ap-5377	286	6	,	,	PUNCT
ap-5377	286	7	(	(	PUNCT
ap-5377	286	8	17	17	NUM
ap-5377	286	9	)	)	PUNCT
ap-5377	286	10	where	where	SCONJ
ap-5377	286	11	ppv	ppv	NOUN
ap-5377	286	12	is	be	AUX
ap-5377	286	13	a	a	DET
ap-5377	286	14	positive	positive	ADJ
ap-5377	286	15	predictive	predictive	ADJ
ap-5377	286	16	value	value	NOUN
ap-5377	286	17	,	,	PUNCT
ap-5377	286	18	tp	tp	NOUN
ap-5377	286	19	is	be	AUX
ap-5377	286	20	a	a	DET
ap-5377	286	21	true	true	ADJ
ap-5377	286	22	positive	positive	ADJ
ap-5377	286	23	and	and	CCONJ
ap-5377	286	24	fp	fp	PROPN
ap-5377	286	25	is	be	AUX
ap-5377	286	26	a	a	DET
ap-5377	286	27	false	false	ADJ
ap-5377	286	28	positive	positive	ADJ
ap-5377	286	29	value	value	NOUN
ap-5377	286	30	.	.	PUNCT
ap-5377	287	1	3	3	X
ap-5377	287	2	.	.	X
ap-5377	287	3	results	result	VERB
ap-5377	287	4	3.1	3.1	NUM
ap-5377	287	5	.	.	PUNCT
ap-5377	287	6	test	test	NOUN
ap-5377	287	7	data	datum	NOUN
ap-5377	287	8	the	the	DET
ap-5377	287	9	tests	test	NOUN
ap-5377	287	10	data	datum	NOUN
ap-5377	287	11	were	be	AUX
ap-5377	287	12	created	create	VERB
ap-5377	287	13	to	to	PART
ap-5377	287	14	verify	verify	VERB
ap-5377	287	15	the	the	DET
ap-5377	287	16	accuracy	accuracy	NOUN
ap-5377	287	17	of	of	ADP
ap-5377	287	18	the	the	DET
ap-5377	287	19	proposed	propose	VERB
ap-5377	287	20	algorithms	algorithm	NOUN
ap-5377	287	21	.	.	PUNCT
ap-5377	288	1	we	we	PRON
ap-5377	288	2	verified	verify	VERB
ap-5377	288	3	the	the	DET
ap-5377	288	4	good	good	ADJ
ap-5377	288	5	proposítion	proposítion	NOUN
ap-5377	288	6	of	of	ADP
ap-5377	288	7	the	the	DET
ap-5377	288	8	algorithms	algorithm	NOUN
ap-5377	288	9	.	.	PUNCT
ap-5377	289	1	therefore	therefore	ADV
ap-5377	289	2	,	,	PUNCT
ap-5377	289	3	the	the	DET
ap-5377	289	4	test	test	NOUN
ap-5377	289	5	data	datum	NOUN
ap-5377	289	6	represent	represent	VERB
ap-5377	289	7	the	the	DET
ap-5377	289	8	basic	basic	ADJ
ap-5377	289	9	features	feature	NOUN
ap-5377	289	10	that	that	SCONJ
ap-5377	289	11	these	these	DET
ap-5377	289	12	algorithms	algorithm	VERB
ap-5377	289	13	504	504	NUM
ap-5377	289	14	vol	vol	NOUN
ap-5377	289	15	.	.	PUNCT
ap-5377	290	1	59	59	NUM
ap-5377	290	2	no	no	NOUN
ap-5377	290	3	.	.	PUNCT
ap-5377	291	1	5/2019	5/2019	NUM
ap-5377	291	2	automatic	automatic	ADJ
ap-5377	291	3	eeg	eeg	NOUN
ap-5377	291	4	classification	classification	NOUN
ap-5377	291	5	using	use	VERB
ap-5377	291	6	dbscan	dbscan	NOUN
ap-5377	291	7	and	and	CCONJ
ap-5377	291	8	denclue	denclue	PROPN
ap-5377	291	9	algor	algor	VERB
ap-5377	291	10	.	.	PUNCT
ap-5377	292	1	sensitivity	sensitivity	NOUN
ap-5377	292	2	[	[	X
ap-5377	292	3	-	-	PUNCT
ap-5377	292	4	]	]	X
ap-5377	292	5	epi	epi	NOUN
ap-5377	292	6	emg	emg	NOUN
ap-5377	292	7	slow	slow	ADJ
ap-5377	292	8	phy	phy	NOUN
ap-5377	292	9	pop	pop	NOUN
ap-5377	292	10	k	k	X
ap-5377	292	11	-	-	PUNCT
ap-5377	292	12	means	mean	VERB
ap-5377	292	13	0.851	0.851	NUM
ap-5377	292	14	0.803	0.803	NUM
ap-5377	292	15	0.725	0.725	NUM
ap-5377	292	16	0.427	0.427	NUM
ap-5377	292	17	0.944	0.944	NUM
ap-5377	292	18	dc	dc	PROPN
ap-5377	292	19	0.827	0.827	NUM
ap-5377	292	20	0.639	0.639	NUM
ap-5377	292	21	0.986	0.986	NUM
ap-5377	292	22	0.931	0.931	NUM
ap-5377	292	23	db	db	ADP
ap-5377	292	24	0.896	0.896	NUM
ap-5377	292	25	0.094	0.094	NUM
ap-5377	292	26	0.997	0.997	NUM
ap-5377	292	27	0.909	0.909	NUM
ap-5377	292	28	table	table	NOUN
ap-5377	292	29	3	3	NUM
ap-5377	292	30	.	.	PUNCT
ap-5377	293	1	the	the	DET
ap-5377	293	2	sensitivity	sensitivity	NOUN
ap-5377	293	3	parameter	parameter	NOUN
ap-5377	293	4	of	of	ADP
ap-5377	293	5	the	the	DET
ap-5377	293	6	classes	class	NOUN
ap-5377	293	7	epileptic	epileptic	ADJ
ap-5377	293	8	activity	activity	NOUN
ap-5377	293	9	(	(	PUNCT
ap-5377	293	10	epi	epi	NOUN
ap-5377	293	11	)	)	PUNCT
ap-5377	293	12	,	,	PUNCT
ap-5377	293	13	emg	emg	NOUN
ap-5377	293	14	artefacts	artefact	NOUN
ap-5377	293	15	(	(	PUNCT
ap-5377	293	16	emg	emg	NOUN
ap-5377	293	17	)	)	PUNCT
ap-5377	293	18	,	,	PUNCT
ap-5377	293	19	slow	slow	ADJ
ap-5377	293	20	eye	eye	NOUN
ap-5377	293	21	artefacts	artefact	NOUN
ap-5377	293	22	(	(	PUNCT
ap-5377	293	23	slow	slow	ADJ
ap-5377	293	24	)	)	PUNCT
ap-5377	293	25	,	,	PUNCT
ap-5377	293	26	physiological	physiological	ADJ
ap-5377	293	27	activity	activity	NOUN
ap-5377	293	28	(	(	PUNCT
ap-5377	293	29	phy	phy	NOUN
ap-5377	293	30	)	)	PUNCT
ap-5377	293	31	and	and	CCONJ
ap-5377	293	32	artefacts	artefact	NOUN
ap-5377	293	33	from	from	ADP
ap-5377	293	34	poor	poor	ADJ
ap-5377	293	35	electrode	electrode	NOUN
ap-5377	293	36	contact	contact	NOUN
ap-5377	293	37	(	(	PUNCT
ap-5377	293	38	pop	pop	NOUN
ap-5377	293	39	)	)	PUNCT
ap-5377	293	40	identified	identify	VERB
ap-5377	293	41	in	in	ADP
ap-5377	293	42	the	the	DET
ap-5377	293	43	eeg	eeg	NOUN
ap-5377	293	44	signal	signal	NOUN
ap-5377	293	45	for	for	ADP
ap-5377	293	46	the	the	DET
ap-5377	293	47	tested	test	VERB
ap-5377	293	48	algorithms	algorithms	NOUN
ap-5377	293	49	denclue	denclue	NOUN
ap-5377	293	50	(	(	PUNCT
ap-5377	293	51	dc	dc	PROPN
ap-5377	293	52	)	)	PUNCT
ap-5377	293	53	,	,	PUNCT
ap-5377	293	54	dbscan	dbscan	NOUN
ap-5377	293	55	(	(	PUNCT
ap-5377	293	56	db	db	PROPN
ap-5377	293	57	)	)	PUNCT
ap-5377	293	58	,	,	PUNCT
ap-5377	293	59	and	and	CCONJ
ap-5377	293	60	k	k	X
ap-5377	293	61	-	-	PUNCT
ap-5377	293	62	means	means	NOUN
ap-5377	293	63	.	.	PUNCT
ap-5377	294	1	(	(	PUNCT
ap-5377	294	2	in	in	ADP
ap-5377	294	3	correct	correct	ADJ
ap-5377	294	4	proposition	proposition	NOUN
ap-5377	294	5	)	)	PUNCT
ap-5377	294	6	should	should	AUX
ap-5377	294	7	be	be	AUX
ap-5377	294	8	/	/	PUNCT
ap-5377	294	9	should	should	AUX
ap-5377	294	10	not	not	PART
ap-5377	294	11	be	be	AUX
ap-5377	294	12	able	able	ADJ
ap-5377	294	13	to	to	PART
ap-5377	294	14	distinguish	distinguish	VERB
ap-5377	294	15	.	.	PUNCT
ap-5377	295	1	two	two	NUM
ap-5377	295	2	types	type	NOUN
ap-5377	295	3	of	of	ADP
ap-5377	295	4	test	test	NOUN
ap-5377	295	5	data	datum	NOUN
ap-5377	295	6	were	be	AUX
ap-5377	295	7	created	create	VERB
ap-5377	295	8	from	from	ADP
ap-5377	295	9	nested	nested	ADJ
ap-5377	295	10	clusters	cluster	NOUN
ap-5377	295	11	,	,	PUNCT
ap-5377	295	12	one	one	NUM
ap-5377	295	13	type	type	NOUN
ap-5377	295	14	of	of	ADP
ap-5377	295	15	test	test	NOUN
ap-5377	295	16	data	datum	NOUN
ap-5377	295	17	contained	contain	VERB
ap-5377	295	18	outliers	outlier	NOUN
ap-5377	295	19	and	and	CCONJ
ap-5377	295	20	the	the	DET
ap-5377	295	21	last	last	ADJ
ap-5377	295	22	type	type	NOUN
ap-5377	295	23	of	of	ADP
ap-5377	295	24	test	test	NOUN
ap-5377	295	25	data	datum	NOUN
ap-5377	295	26	was	be	AUX
ap-5377	295	27	formed	form	VERB
ap-5377	295	28	by	by	ADP
ap-5377	295	29	two	two	NUM
ap-5377	295	30	good	good	ADJ
ap-5377	295	31	separated	separate	VERB
ap-5377	295	32	clusters	cluster	NOUN
ap-5377	295	33	.	.	PUNCT
ap-5377	296	1	all	all	DET
ap-5377	296	2	three	three	NUM
ap-5377	296	3	algorithms	algorithm	NOUN
ap-5377	296	4	(	(	PUNCT
ap-5377	296	5	dbscan	dbscan	NOUN
ap-5377	296	6	,	,	PUNCT
ap-5377	296	7	denclue	denclue	NOUN
ap-5377	296	8	,	,	PUNCT
ap-5377	296	9	and	and	CCONJ
ap-5377	296	10	kmeans	kmean	NOUN
ap-5377	296	11	)	)	PUNCT
ap-5377	296	12	were	be	AUX
ap-5377	296	13	verified	verify	VERB
ap-5377	296	14	with	with	ADP
ap-5377	296	15	test	test	NOUN
ap-5377	296	16	data	datum	NOUN
ap-5377	296	17	.	.	PUNCT
ap-5377	297	1	every	every	DET
ap-5377	297	2	algorithm	algorithm	NOUN
ap-5377	297	3	assigns	assign	VERB
ap-5377	297	4	different	different	ADJ
ap-5377	297	5	class	class	NOUN
ap-5377	297	6	numbers	number	NOUN
ap-5377	297	7	to	to	ADP
ap-5377	297	8	the	the	DET
ap-5377	297	9	same	same	ADJ
ap-5377	297	10	data	datum	NOUN
ap-5377	297	11	.	.	PUNCT
ap-5377	298	1	the	the	DET
ap-5377	298	2	sorting	sorting	NOUN
ap-5377	298	3	of	of	ADP
ap-5377	298	4	the	the	DET
ap-5377	298	5	classes	class	NOUN
ap-5377	298	6	by	by	ADP
ap-5377	298	7	maximum	maximum	ADJ
ap-5377	298	8	amplitude	amplitude	NOUN
ap-5377	298	9	was	be	AUX
ap-5377	298	10	then	then	ADV
ap-5377	298	11	used	use	VERB
ap-5377	298	12	for	for	ADP
ap-5377	298	13	real	real	ADJ
ap-5377	298	14	eeg	eeg	PROPN
ap-5377	298	15	data	datum	NOUN
ap-5377	298	16	.	.	PUNCT
ap-5377	299	1	in	in	ADP
ap-5377	299	2	this	this	DET
ap-5377	299	3	section	section	NOUN
ap-5377	299	4	,	,	PUNCT
ap-5377	299	5	we	we	PRON
ap-5377	299	6	tested	test	VERB
ap-5377	299	7	the	the	DET
ap-5377	299	8	correct	correct	ADJ
ap-5377	299	9	design	design	NOUN
ap-5377	299	10	of	of	ADP
ap-5377	299	11	algorithms	algorithm	NOUN
ap-5377	299	12	and	and	CCONJ
ap-5377	299	13	sorting	sorting	NOUN
ap-5377	299	14	of	of	ADP
ap-5377	299	15	the	the	DET
ap-5377	299	16	classes	class	NOUN
ap-5377	299	17	is	be	AUX
ap-5377	299	18	a	a	DET
ap-5377	299	19	simple	simple	ADJ
ap-5377	299	20	separate	separate	ADJ
ap-5377	299	21	step	step	NOUN
ap-5377	299	22	same	same	ADJ
ap-5377	299	23	for	for	ADP
ap-5377	299	24	all	all	DET
ap-5377	299	25	tested	test	VERB
ap-5377	299	26	algorithms	algorithm	NOUN
ap-5377	299	27	.	.	PUNCT
ap-5377	300	1	therefore	therefore	ADV
ap-5377	300	2	,	,	PUNCT
ap-5377	300	3	the	the	DET
ap-5377	300	4	sorting	sorting	NOUN
ap-5377	300	5	of	of	ADP
ap-5377	300	6	the	the	DET
ap-5377	300	7	classes	class	NOUN
ap-5377	300	8	is	be	AUX
ap-5377	300	9	not	not	PART
ap-5377	300	10	used	use	VERB
ap-5377	300	11	for	for	ADP
ap-5377	300	12	the	the	DET
ap-5377	300	13	testing	testing	NOUN
ap-5377	300	14	data	datum	NOUN
ap-5377	300	15	.	.	PUNCT
ap-5377	301	1	we	we	PRON
ap-5377	301	2	are	be	AUX
ap-5377	301	3	only	only	ADV
ap-5377	301	4	viewing	view	VERB
ap-5377	301	5	a	a	DET
ap-5377	301	6	correct	correct	ADJ
ap-5377	301	7	separation	separation	NOUN
ap-5377	301	8	of	of	ADP
ap-5377	301	9	the	the	DET
ap-5377	301	10	data	datum	NOUN
ap-5377	301	11	.	.	PUNCT
ap-5377	302	1	density	density	NOUN
ap-5377	302	2	based	base	VERB
ap-5377	302	3	algorithms	algorithm	NOUN
ap-5377	302	4	had	have	VERB
ap-5377	302	5	the	the	DET
ap-5377	302	6	same	same	ADJ
ap-5377	302	7	results	result	NOUN
ap-5377	302	8	for	for	ADP
ap-5377	302	9	the	the	DET
ap-5377	302	10	test	test	NOUN
ap-5377	302	11	data	datum	NOUN
ap-5377	302	12	.	.	PUNCT
ap-5377	303	1	for	for	ADP
ap-5377	303	2	this	this	DET
ap-5377	303	3	reason	reason	NOUN
ap-5377	303	4	,	,	PUNCT
ap-5377	303	5	examples	example	NOUN
ap-5377	303	6	of	of	ADP
ap-5377	303	7	test	test	NOUN
ap-5377	303	8	data	datum	NOUN
ap-5377	303	9	results	result	NOUN
ap-5377	303	10	for	for	ADP
ap-5377	303	11	both	both	DET
ap-5377	303	12	density	density	NOUN
ap-5377	303	13	based	base	VERB
ap-5377	303	14	algorithms	algorithm	NOUN
ap-5377	303	15	are	be	AUX
ap-5377	303	16	shown	show	VERB
ap-5377	303	17	in	in	ADP
ap-5377	303	18	figure	figure	NOUN
ap-5377	303	19	9	9	NUM
ap-5377	303	20	.	.	PUNCT
ap-5377	304	1	the	the	DET
ap-5377	304	2	results	result	NOUN
ap-5377	304	3	of	of	ADP
ap-5377	304	4	algorithm	algorithm	NOUN
ap-5377	304	5	k	k	NOUN
ap-5377	304	6	-	-	PUNCT
ap-5377	304	7	means	means	NOUN
ap-5377	304	8	for	for	ADP
ap-5377	304	9	the	the	DET
ap-5377	304	10	test	test	NOUN
ap-5377	304	11	data	datum	NOUN
ap-5377	304	12	are	be	AUX
ap-5377	304	13	displayed	display	VERB
ap-5377	304	14	in	in	ADP
ap-5377	304	15	figure	figure	NOUN
ap-5377	304	16	10	10	NUM
ap-5377	304	17	.	.	PUNCT
ap-5377	305	1	3.2	3.2	NUM
ap-5377	305	2	.	.	PUNCT
ap-5377	306	1	real	real	ADJ
ap-5377	306	2	eeg	eeg	PROPN
ap-5377	306	3	data	datum	NOUN
ap-5377	306	4	the	the	DET
ap-5377	306	5	expert	expert	NOUN
ap-5377	306	6	classified	classify	VERB
ap-5377	306	7	49.554	49.554	NUM
ap-5377	306	8	segments	segment	NOUN
ap-5377	306	9	from	from	ADP
ap-5377	306	10	all	all	DET
ap-5377	306	11	eeg	eeg	NOUN
ap-5377	306	12	records	record	NOUN
ap-5377	306	13	.	.	PUNCT
ap-5377	307	1	segments	segment	NOUN
ap-5377	307	2	included	include	VERB
ap-5377	307	3	physiological	physiological	ADJ
ap-5377	307	4	activity	activity	NOUN
ap-5377	307	5	(	(	PUNCT
ap-5377	307	6	phy	phy	NOUN
ap-5377	307	7	)	)	PUNCT
ap-5377	307	8	,	,	PUNCT
ap-5377	307	9	epileptic	epileptic	ADJ
ap-5377	307	10	activity	activity	NOUN
ap-5377	307	11	(	(	PUNCT
ap-5377	307	12	epi	epi	NOUN
ap-5377	307	13	)	)	PUNCT
ap-5377	307	14	,	,	PUNCT
ap-5377	307	15	emg	emg	NOUN
ap-5377	307	16	artefacts	artefact	NOUN
ap-5377	307	17	(	(	PUNCT
ap-5377	307	18	emg	emg	NOUN
ap-5377	307	19	)	)	PUNCT
ap-5377	307	20	,	,	PUNCT
ap-5377	307	21	artefacts	artefact	VERB
ap-5377	307	22	from	from	ADP
ap-5377	307	23	poor	poor	ADJ
ap-5377	307	24	electrode	electrode	NOUN
ap-5377	307	25	contact	contact	NOUN
ap-5377	307	26	(	(	PUNCT
ap-5377	307	27	pop	pop	NOUN
ap-5377	307	28	)	)	PUNCT
ap-5377	307	29	,	,	PUNCT
ap-5377	307	30	slow	slow	ADJ
ap-5377	307	31	eye	eye	NOUN
ap-5377	307	32	artefacts	artefact	NOUN
ap-5377	307	33	(	(	PUNCT
ap-5377	307	34	slow	slow	ADJ
ap-5377	307	35	)	)	PUNCT
ap-5377	307	36	and	and	CCONJ
ap-5377	307	37	wrong	wrong	ADJ
ap-5377	307	38	segmented	segment	VERB
ap-5377	307	39	parts	part	NOUN
ap-5377	307	40	of	of	ADP
ap-5377	307	41	the	the	DET
ap-5377	307	42	signal	signal	NOUN
ap-5377	307	43	.	.	PUNCT
ap-5377	308	1	adaptive	adaptive	ADJ
ap-5377	308	2	segmentation	segmentation	NOUN
ap-5377	308	3	used	use	VERB
ap-5377	308	4	for	for	ADP
ap-5377	308	5	signal	signal	ADJ
ap-5377	308	6	pre	pre	ADJ
ap-5377	308	7	-	-	ADJ
ap-5377	308	8	processing	processing	ADJ
ap-5377	308	9	(	(	PUNCT
ap-5377	308	10	see	see	VERB
ap-5377	308	11	section	section	NOUN
ap-5377	308	12	2.2	2.2	NUM
ap-5377	308	13	)	)	PUNCT
ap-5377	308	14	sometimes	sometimes	ADV
ap-5377	308	15	rank	rank	VERB
ap-5377	308	16	part	part	NOUN
ap-5377	308	17	of	of	ADP
ap-5377	308	18	the	the	DET
ap-5377	308	19	signal	signal	NOUN
ap-5377	308	20	,	,	PUNCT
ap-5377	308	21	where	where	SCONJ
ap-5377	308	22	the	the	DET
ap-5377	308	23	transition	transition	NOUN
ap-5377	308	24	between	between	ADP
ap-5377	308	25	two	two	NUM
ap-5377	308	26	classes	class	NOUN
ap-5377	308	27	occurs	occur	VERB
ap-5377	308	28	,	,	PUNCT
ap-5377	308	29	into	into	ADP
ap-5377	308	30	one	one	NUM
ap-5377	308	31	segment	segment	NOUN
ap-5377	308	32	.	.	PUNCT
ap-5377	309	1	these	these	DET
ap-5377	309	2	wrong	wrong	ADJ
ap-5377	309	3	segmented	segment	VERB
ap-5377	309	4	parts	part	NOUN
ap-5377	309	5	of	of	ADP
ap-5377	309	6	the	the	DET
ap-5377	309	7	signal	signal	NOUN
ap-5377	309	8	were	be	AUX
ap-5377	309	9	removed	remove	VERB
ap-5377	309	10	from	from	ADP
ap-5377	309	11	the	the	DET
ap-5377	309	12	statistical	statistical	ADJ
ap-5377	309	13	analysis	analysis	NOUN
ap-5377	309	14	,	,	PUNCT
ap-5377	309	15	which	which	PRON
ap-5377	309	16	has	have	AUX
ap-5377	309	17	prevented	prevent	VERB
ap-5377	309	18	it	it	PRON
ap-5377	309	19	from	from	ADP
ap-5377	309	20	affecting	affect	VERB
ap-5377	309	21	the	the	DET
ap-5377	309	22	results	result	NOUN
ap-5377	309	23	.	.	PUNCT
ap-5377	310	1	individual	individual	ADJ
ap-5377	310	2	tables	table	NOUN
ap-5377	310	3	show	show	VERB
ap-5377	310	4	successive	successive	ADJ
ap-5377	310	5	results	result	NOUN
ap-5377	310	6	of	of	ADP
ap-5377	310	7	sensitivity	sensitivity	NOUN
ap-5377	310	8	(	(	PUNCT
ap-5377	310	9	see	see	VERB
ap-5377	310	10	table	table	NOUN
ap-5377	310	11	3	3	NUM
ap-5377	310	12	)	)	PUNCT
ap-5377	310	13	,	,	PUNCT
ap-5377	310	14	specificity	specificity	NOUN
ap-5377	310	15	(	(	PUNCT
ap-5377	310	16	see	see	VERB
ap-5377	310	17	table	table	NOUN
ap-5377	310	18	4	4	NUM
ap-5377	310	19	)	)	PUNCT
ap-5377	310	20	,	,	PUNCT
ap-5377	310	21	and	and	CCONJ
ap-5377	310	22	ppv	ppv	NOUN
ap-5377	310	23	(	(	PUNCT
ap-5377	310	24	see	see	VERB
ap-5377	310	25	table	table	NOUN
ap-5377	310	26	5	5	NUM
ap-5377	310	27	)	)	PUNCT
ap-5377	310	28	for	for	ADP
ap-5377	310	29	all	all	DET
ap-5377	310	30	three	three	NUM
ap-5377	310	31	tested	test	VERB
ap-5377	310	32	algorithms	algorithm	NOUN
ap-5377	310	33	.	.	PUNCT
ap-5377	311	1	4	4	X
ap-5377	311	2	.	.	X
ap-5377	311	3	discussion	discussion	NOUN
ap-5377	311	4	in	in	ADP
ap-5377	311	5	this	this	DET
ap-5377	311	6	study	study	NOUN
ap-5377	311	7	,	,	PUNCT
ap-5377	311	8	we	we	PRON
ap-5377	311	9	tested	test	VERB
ap-5377	311	10	the	the	DET
ap-5377	311	11	utilization	utilization	NOUN
ap-5377	311	12	of	of	ADP
ap-5377	311	13	the	the	DET
ap-5377	311	14	density	density	NOUN
ap-5377	311	15	based	base	VERB
ap-5377	311	16	algorithms	algorithm	NOUN
ap-5377	311	17	dbscan	dbscan	NOUN
ap-5377	311	18	and	and	CCONJ
ap-5377	311	19	denclue	denclue	VERB
ap-5377	311	20	on	on	ADP
ap-5377	311	21	the	the	DET
ap-5377	311	22	eeg	eeg	PROPN
ap-5377	311	23	signal	signal	NOUN
ap-5377	311	24	classification	classification	NOUN
ap-5377	311	25	.	.	PUNCT
ap-5377	312	1	the	the	DET
ap-5377	312	2	aim	aim	NOUN
ap-5377	312	3	of	of	ADP
ap-5377	312	4	this	this	DET
ap-5377	312	5	classification	classification	NOUN
ap-5377	312	6	was	be	AUX
ap-5377	312	7	to	to	PART
ap-5377	312	8	assist	assist	VERB
ap-5377	312	9	to	to	ADP
ap-5377	312	10	an	an	DET
ap-5377	312	11	expert	expert	NOUN
ap-5377	312	12	with	with	ADP
ap-5377	312	13	a	a	DET
ap-5377	312	14	scoring	scoring	NOUN
ap-5377	312	15	of	of	ADP
ap-5377	312	16	the	the	DET
ap-5377	312	17	eeg	eeg	NOUN
ap-5377	312	18	signal	signal	NOUN
ap-5377	312	19	.	.	PUNCT
ap-5377	313	1	algorithms	algorithm	NOUN
ap-5377	313	2	should	should	AUX
ap-5377	313	3	be	be	AUX
ap-5377	313	4	able	able	ADJ
ap-5377	313	5	to	to	PART
ap-5377	313	6	identify	identify	VERB
ap-5377	313	7	individual	individual	ADJ
ap-5377	313	8	elements	element	NOUN
ap-5377	313	9	occurring	occur	VERB
ap-5377	313	10	in	in	ADP
ap-5377	313	11	the	the	DET
ap-5377	313	12	eeg	eeg	NOUN
ap-5377	313	13	record	record	NOUN
ap-5377	313	14	.	.	PUNCT
ap-5377	314	1	this	this	PRON
ap-5377	314	2	should	should	AUX
ap-5377	314	3	make	make	VERB
ap-5377	314	4	it	it	PRON
ap-5377	314	5	easier	easy	ADJ
ap-5377	314	6	for	for	SCONJ
ap-5377	314	7	the	the	DET
ap-5377	314	8	expert	expert	NOUN
ap-5377	314	9	to	to	PART
ap-5377	314	10	find	find	VERB
ap-5377	314	11	important	important	ADJ
ap-5377	314	12	parts	part	NOUN
ap-5377	314	13	of	of	ADP
ap-5377	314	14	the	the	DET
ap-5377	314	15	eeg	eeg	NOUN
ap-5377	314	16	signal	signal	NOUN
ap-5377	314	17	and	and	CCONJ
ap-5377	314	18	then	then	ADV
ap-5377	314	19	evaluate	evaluate	VERB
ap-5377	314	20	it	it	PRON
ap-5377	314	21	.	.	PUNCT
ap-5377	315	1	we	we	PRON
ap-5377	315	2	algor	algor	VERB
ap-5377	315	3	.	.	PUNCT
ap-5377	316	1	specificity	specificity	NOUN
ap-5377	316	2	[	[	X
ap-5377	316	3	-	-	PUNCT
ap-5377	316	4	]	]	X
ap-5377	316	5	epi	epi	NOUN
ap-5377	316	6	emg	emg	NOUN
ap-5377	316	7	slow	slow	ADJ
ap-5377	316	8	phy	phy	NOUN
ap-5377	316	9	pop	pop	NOUN
ap-5377	316	10	k	k	X
ap-5377	316	11	-	-	PUNCT
ap-5377	316	12	means	mean	VERB
ap-5377	316	13	0.956	0.956	NUM
ap-5377	316	14	0.966	0.966	NUM
ap-5377	316	15	0.782	0.782	NUM
ap-5377	316	16	0.984	0.984	NUM
ap-5377	316	17	0.999	0.999	NUM
ap-5377	316	18	dc	dc	PROPN
ap-5377	316	19	0.983	0.983	NUM
ap-5377	316	20	0.999	0.999	NUM
ap-5377	316	21	0.826	0.826	NUM
ap-5377	316	22	1.000	1.000	NUM
ap-5377	316	23	db	db	ADP
ap-5377	316	24	0.997	0.997	NUM
ap-5377	316	25	0.999	0.999	NUM
ap-5377	316	26	0.804	0.804	NUM
ap-5377	316	27	0.999	0.999	NUM
ap-5377	316	28	table	table	NOUN
ap-5377	316	29	4	4	NUM
ap-5377	316	30	.	.	PUNCT
ap-5377	317	1	the	the	DET
ap-5377	317	2	specificity	specificity	NOUN
ap-5377	317	3	parameter	parameter	NOUN
ap-5377	317	4	of	of	ADP
ap-5377	317	5	the	the	DET
ap-5377	317	6	classes	class	NOUN
ap-5377	317	7	epileptic	epileptic	ADJ
ap-5377	317	8	activity	activity	NOUN
ap-5377	317	9	(	(	PUNCT
ap-5377	317	10	epi	epi	NOUN
ap-5377	317	11	)	)	PUNCT
ap-5377	317	12	,	,	PUNCT
ap-5377	317	13	emg	emg	NOUN
ap-5377	317	14	artefacts	artefact	NOUN
ap-5377	317	15	(	(	PUNCT
ap-5377	317	16	emg	emg	NOUN
ap-5377	317	17	)	)	PUNCT
ap-5377	317	18	,	,	PUNCT
ap-5377	317	19	slow	slow	ADJ
ap-5377	317	20	eye	eye	NOUN
ap-5377	317	21	artefacts	artefact	NOUN
ap-5377	317	22	(	(	PUNCT
ap-5377	317	23	slow	slow	ADJ
ap-5377	317	24	)	)	PUNCT
ap-5377	317	25	,	,	PUNCT
ap-5377	317	26	physiological	physiological	ADJ
ap-5377	317	27	activity	activity	NOUN
ap-5377	317	28	(	(	PUNCT
ap-5377	317	29	phy	phy	NOUN
ap-5377	317	30	)	)	PUNCT
ap-5377	317	31	and	and	CCONJ
ap-5377	317	32	artefacts	artefact	NOUN
ap-5377	317	33	from	from	ADP
ap-5377	317	34	poor	poor	ADJ
ap-5377	317	35	electrode	electrode	NOUN
ap-5377	317	36	contact	contact	NOUN
ap-5377	317	37	(	(	PUNCT
ap-5377	317	38	pop	pop	NOUN
ap-5377	317	39	)	)	PUNCT
ap-5377	317	40	identified	identify	VERB
ap-5377	317	41	in	in	ADP
ap-5377	317	42	the	the	DET
ap-5377	317	43	eeg	eeg	NOUN
ap-5377	317	44	signal	signal	NOUN
ap-5377	317	45	for	for	ADP
ap-5377	317	46	the	the	DET
ap-5377	317	47	tested	test	VERB
ap-5377	317	48	algorithms	algorithms	NOUN
ap-5377	317	49	denclue	denclue	NOUN
ap-5377	317	50	(	(	PUNCT
ap-5377	317	51	dc	dc	PROPN
ap-5377	317	52	)	)	PUNCT
ap-5377	317	53	,	,	PUNCT
ap-5377	317	54	dbscan	dbscan	NOUN
ap-5377	317	55	(	(	PUNCT
ap-5377	317	56	db	db	PROPN
ap-5377	317	57	)	)	PUNCT
ap-5377	317	58	,	,	PUNCT
ap-5377	317	59	and	and	CCONJ
ap-5377	317	60	k	k	X
ap-5377	317	61	-	-	PUNCT
ap-5377	317	62	means	mean	NOUN
ap-5377	317	63	.	.	PUNCT
ap-5377	318	1	algor	algor	VERB
ap-5377	318	2	.	.	PUNCT
ap-5377	319	1	ppv	ppv	NOUN
ap-5377	320	1	[	[	X
ap-5377	320	2	-	-	PUNCT
ap-5377	320	3	]	]	X
ap-5377	320	4	epi	epi	NOUN
ap-5377	320	5	emg	emg	NOUN
ap-5377	320	6	slow	slow	ADJ
ap-5377	320	7	phy	phy	NOUN
ap-5377	320	8	pop	pop	NOUN
ap-5377	320	9	k	k	X
ap-5377	320	10	-	-	PUNCT
ap-5377	320	11	means	mean	VERB
ap-5377	320	12	0.641	0.641	NUM
ap-5377	320	13	0.178	0.178	NUM
ap-5377	320	14	0.010	0.010	NUM
ap-5377	320	15	0.996	0.996	NUM
ap-5377	320	16	0.932	0.932	NUM
ap-5377	320	17	dc	dc	PROPN
ap-5377	320	18	0.813	0.813	NUM
ap-5377	320	19	0.941	0.941	NUM
ap-5377	320	20	0.979	0.979	NUM
ap-5377	320	21	0.998	0.998	NUM
ap-5377	320	22	db	db	PROPN
ap-5377	320	23	0.969	0.969	NUM
ap-5377	320	24	0.333	0.333	NUM
ap-5377	320	25	0.970	0.970	NUM
ap-5377	320	26	0.942	0.942	NUM
ap-5377	320	27	table	table	NOUN
ap-5377	320	28	5	5	NUM
ap-5377	320	29	.	.	PUNCT
ap-5377	321	1	the	the	DET
ap-5377	321	2	ppv	ppv	NOUN
ap-5377	321	3	parameter	parameter	NOUN
ap-5377	321	4	of	of	ADP
ap-5377	321	5	the	the	DET
ap-5377	321	6	classes	class	NOUN
ap-5377	321	7	epileptic	epileptic	ADJ
ap-5377	321	8	activity	activity	NOUN
ap-5377	321	9	(	(	PUNCT
ap-5377	321	10	epi	epi	NOUN
ap-5377	321	11	)	)	PUNCT
ap-5377	321	12	,	,	PUNCT
ap-5377	321	13	emg	emg	NOUN
ap-5377	321	14	artefacts	artefact	NOUN
ap-5377	321	15	(	(	PUNCT
ap-5377	321	16	emg	emg	NOUN
ap-5377	321	17	)	)	PUNCT
ap-5377	321	18	,	,	PUNCT
ap-5377	321	19	slow	slow	ADJ
ap-5377	321	20	eye	eye	NOUN
ap-5377	321	21	artefacts	artefact	NOUN
ap-5377	321	22	(	(	PUNCT
ap-5377	321	23	slow	slow	ADJ
ap-5377	321	24	)	)	PUNCT
ap-5377	321	25	,	,	PUNCT
ap-5377	321	26	physiological	physiological	ADJ
ap-5377	321	27	activity	activity	NOUN
ap-5377	321	28	(	(	PUNCT
ap-5377	321	29	phy	phy	NOUN
ap-5377	321	30	)	)	PUNCT
ap-5377	321	31	and	and	CCONJ
ap-5377	321	32	artefacts	artefact	NOUN
ap-5377	321	33	from	from	ADP
ap-5377	321	34	poor	poor	ADJ
ap-5377	321	35	electrode	electrode	NOUN
ap-5377	321	36	contact	contact	NOUN
ap-5377	321	37	(	(	PUNCT
ap-5377	321	38	pop	pop	NOUN
ap-5377	321	39	)	)	PUNCT
ap-5377	321	40	identified	identify	VERB
ap-5377	321	41	in	in	ADP
ap-5377	321	42	the	the	DET
ap-5377	321	43	eeg	eeg	NOUN
ap-5377	321	44	signal	signal	NOUN
ap-5377	321	45	for	for	ADP
ap-5377	321	46	the	the	DET
ap-5377	321	47	tested	test	VERB
ap-5377	321	48	algorithms	algorithms	NOUN
ap-5377	321	49	denclue	denclue	NOUN
ap-5377	321	50	(	(	PUNCT
ap-5377	321	51	dc	dc	PROPN
ap-5377	321	52	)	)	PUNCT
ap-5377	321	53	,	,	PUNCT
ap-5377	321	54	dbscan	dbscan	NOUN
ap-5377	321	55	(	(	PUNCT
ap-5377	321	56	db	db	PROPN
ap-5377	321	57	)	)	PUNCT
ap-5377	321	58	,	,	PUNCT
ap-5377	321	59	and	and	CCONJ
ap-5377	321	60	k	k	X
ap-5377	321	61	-	-	PUNCT
ap-5377	321	62	means	mean	NOUN
ap-5377	321	63	.	.	PUNCT
ap-5377	321	64	tested	test	VERB
ap-5377	321	65	whether	whether	SCONJ
ap-5377	321	66	the	the	DET
ap-5377	321	67	algorithms	algorithm	NOUN
ap-5377	321	68	can	can	AUX
ap-5377	321	69	identify	identify	VERB
ap-5377	321	70	epileptic	epileptic	ADJ
ap-5377	321	71	activity	activity	NOUN
ap-5377	321	72	(	(	PUNCT
ap-5377	321	73	specifically	specifically	ADV
ap-5377	321	74	spike	spike	ADJ
ap-5377	321	75	and	and	CCONJ
ap-5377	321	76	wave	wave	NOUN
ap-5377	321	77	complex	complex	NOUN
ap-5377	321	78	)	)	PUNCT
ap-5377	321	79	and	and	CCONJ
ap-5377	321	80	physiological	physiological	ADJ
ap-5377	321	81	activity	activity	NOUN
ap-5377	321	82	.	.	PUNCT
ap-5377	322	1	we	we	PRON
ap-5377	322	2	also	also	ADV
ap-5377	322	3	tested	test	VERB
ap-5377	322	4	the	the	DET
ap-5377	322	5	ability	ability	NOUN
ap-5377	322	6	to	to	PART
ap-5377	322	7	classify	classify	VERB
ap-5377	322	8	artefacts	artefact	NOUN
ap-5377	322	9	,	,	PUNCT
ap-5377	322	10	because	because	SCONJ
ap-5377	322	11	these	these	DET
ap-5377	322	12	parts	part	NOUN
ap-5377	322	13	of	of	ADP
ap-5377	322	14	the	the	DET
ap-5377	322	15	eeg	eeg	NOUN
ap-5377	322	16	assist	assist	NOUN
ap-5377	322	17	in	in	ADP
ap-5377	322	18	the	the	DET
ap-5377	322	19	overall	overall	ADJ
ap-5377	322	20	view	view	NOUN
ap-5377	322	21	of	of	ADP
ap-5377	322	22	the	the	DET
ap-5377	322	23	signal	signal	NOUN
ap-5377	322	24	.	.	PUNCT
ap-5377	323	1	we	we	PRON
ap-5377	323	2	compared	compare	VERB
ap-5377	323	3	testing	test	VERB
ap-5377	323	4	algorithms	algorithm	NOUN
ap-5377	323	5	with	with	ADP
ap-5377	323	6	the	the	DET
ap-5377	323	7	k	k	NOUN
ap-5377	323	8	-	-	PUNCT
ap-5377	323	9	means	means	NOUN
ap-5377	323	10	algorithm	algorithm	NOUN
ap-5377	323	11	.	.	PUNCT
ap-5377	324	1	the	the	DET
ap-5377	324	2	k	k	NOUN
ap-5377	324	3	-	-	PUNCT
ap-5377	324	4	means	means	NOUN
ap-5377	324	5	algorithm	algorithm	NOUN
ap-5377	324	6	is	be	AUX
ap-5377	324	7	a	a	DET
ap-5377	324	8	relatively	relatively	ADV
ap-5377	324	9	old	old	ADJ
ap-5377	324	10	unsupervised	unsupervised	ADJ
ap-5377	324	11	algorithm	algorithm	NOUN
ap-5377	324	12	,	,	PUNCT
ap-5377	324	13	although	although	SCONJ
ap-5377	324	14	it	it	PRON
ap-5377	324	15	is	be	AUX
ap-5377	324	16	still	still	ADV
ap-5377	324	17	being	be	AUX
ap-5377	324	18	commonly	commonly	ADV
ap-5377	324	19	used	use	VERB
ap-5377	324	20	in	in	ADP
ap-5377	324	21	recent	recent	ADJ
ap-5377	324	22	studies	study	NOUN
ap-5377	324	23	into	into	ADP
ap-5377	324	24	eeg	eeg	NOUN
ap-5377	324	25	classification	classification	NOUN
ap-5377	324	26	(	(	PUNCT
ap-5377	324	27	for	for	ADP
ap-5377	324	28	example	example	NOUN
ap-5377	324	29	,	,	PUNCT
ap-5377	324	30	studies	study	NOUN
ap-5377	324	31	[	[	X
ap-5377	324	32	12	12	NUM
ap-5377	324	33	]	]	PUNCT
ap-5377	324	34	and	and	CCONJ
ap-5377	324	35	[	[	X
ap-5377	324	36	44	44	NUM
ap-5377	324	37	]	]	NUM
ap-5377	324	38	)	)	PUNCT
ap-5377	324	39	.	.	PUNCT
ap-5377	325	1	many	many	ADJ
ap-5377	325	2	other	other	ADJ
ap-5377	325	3	supervised	supervised	ADJ
ap-5377	325	4	algorithms	algorithm	NOUN
ap-5377	325	5	are	be	AUX
ap-5377	325	6	also	also	ADV
ap-5377	325	7	used	use	VERB
ap-5377	325	8	in	in	ADP
ap-5377	325	9	clinical	clinical	ADJ
ap-5377	325	10	practice	practice	NOUN
ap-5377	325	11	(	(	PUNCT
ap-5377	325	12	for	for	ADP
ap-5377	325	13	example	example	NOUN
ap-5377	325	14	k	k	PROPN
ap-5377	325	15	-	-	PUNCT
ap-5377	325	16	nn	nn	ADJ
ap-5377	325	17	,	,	PUNCT
ap-5377	325	18	neuronal	neuronal	ADJ
ap-5377	325	19	network	network	NOUN
ap-5377	325	20	,	,	PUNCT
ap-5377	325	21	or	or	CCONJ
ap-5377	325	22	support	support	VERB
ap-5377	325	23	vector	vector	NOUN
ap-5377	325	24	machine	machine	NOUN
ap-5377	325	25	)	)	PUNCT
ap-5377	325	26	.	.	PUNCT
ap-5377	326	1	supervised	supervised	ADJ
ap-5377	326	2	algorithms	algorithm	NOUN
ap-5377	326	3	have	have	VERB
ap-5377	326	4	their	their	PRON
ap-5377	326	5	advantages	advantage	NOUN
ap-5377	326	6	(	(	PUNCT
ap-5377	326	7	better	well	ADJ
ap-5377	326	8	results	result	NOUN
ap-5377	326	9	in	in	ADP
ap-5377	326	10	the	the	DET
ap-5377	326	11	case	case	NOUN
ap-5377	326	12	of	of	ADP
ap-5377	326	13	the	the	DET
ap-5377	326	14	best	good	ADJ
ap-5377	326	15	learning	learning	NOUN
ap-5377	326	16	process	process	NOUN
ap-5377	326	17	)	)	PUNCT
ap-5377	326	18	and	and	CCONJ
ap-5377	326	19	disadvantages	disadvantage	NOUN
ap-5377	326	20	(	(	PUNCT
ap-5377	326	21	the	the	DET
ap-5377	326	22	need	need	NOUN
ap-5377	326	23	to	to	PART
ap-5377	326	24	create	create	VERB
ap-5377	326	25	a	a	DET
ap-5377	326	26	training	training	NOUN
ap-5377	326	27	set	set	NOUN
ap-5377	326	28	)	)	PUNCT
ap-5377	326	29	.	.	PUNCT
ap-5377	327	1	we	we	PRON
ap-5377	327	2	tested	test	VERB
ap-5377	327	3	unsupervised	unsupervised	ADJ
ap-5377	327	4	algorithms	algorithm	NOUN
ap-5377	327	5	dbscan	dbscan	NOUN
ap-5377	327	6	and	and	CCONJ
ap-5377	327	7	denclue	denclue	NOUN
ap-5377	327	8	and	and	CCONJ
ap-5377	327	9	it	it	PRON
ap-5377	327	10	is	be	AUX
ap-5377	327	11	necessary	necessary	ADJ
ap-5377	327	12	to	to	PART
ap-5377	327	13	compare	compare	VERB
ap-5377	327	14	their	their	PRON
ap-5377	327	15	results	result	NOUN
ap-5377	327	16	to	to	ADP
ap-5377	327	17	another	another	DET
ap-5377	327	18	unsupervised	unsupervised	ADJ
ap-5377	327	19	algorithm	algorithm	NOUN
ap-5377	327	20	.	.	PUNCT
ap-5377	328	1	the	the	DET
ap-5377	328	2	results	result	NOUN
ap-5377	328	3	are	be	AUX
ap-5377	328	4	,	,	PUNCT
ap-5377	328	5	therefore	therefore	ADV
ap-5377	328	6	,	,	PUNCT
ap-5377	328	7	not	not	PART
ap-5377	328	8	distorted	distort	VERB
ap-5377	328	9	by	by	ADP
ap-5377	328	10	the	the	DET
ap-5377	328	11	difference	difference	NOUN
ap-5377	328	12	between	between	ADP
ap-5377	328	13	unsupervised	unsupervised	ADJ
ap-5377	328	14	and	and	CCONJ
ap-5377	328	15	supervised	supervised	ADJ
ap-5377	328	16	algorithms	algorithm	NOUN
ap-5377	328	17	in	in	ADP
ap-5377	328	18	principle	principle	NOUN
ap-5377	328	19	.	.	PUNCT
ap-5377	329	1	first	first	ADV
ap-5377	329	2	,	,	PUNCT
ap-5377	329	3	we	we	PRON
ap-5377	329	4	have	have	AUX
ap-5377	329	5	verified	verify	VERB
ap-5377	329	6	the	the	DET
ap-5377	329	7	main	main	ADJ
ap-5377	329	8	advantages	advantage	NOUN
ap-5377	329	9	and	and	CCONJ
ap-5377	329	10	disadvantages	disadvantage	NOUN
ap-5377	329	11	of	of	ADP
ap-5377	329	12	the	the	DET
ap-5377	329	13	proposed	propose	VERB
ap-5377	329	14	algorithms	algorithm	NOUN
ap-5377	329	15	and	and	CCONJ
ap-5377	329	16	the	the	DET
ap-5377	329	17	kmeans	kmeans	PROPN
ap-5377	329	18	algorithm	algorithm	NOUN
ap-5377	329	19	on	on	ADP
ap-5377	329	20	the	the	DET
ap-5377	329	21	testing	testing	NOUN
ap-5377	329	22	dataset	dataset	NOUN
ap-5377	329	23	.	.	PUNCT
ap-5377	330	1	the	the	DET
ap-5377	330	2	tested	test	VERB
ap-5377	330	3	data	datum	NOUN
ap-5377	330	4	were	be	AUX
ap-5377	330	5	created	create	VERB
ap-5377	330	6	only	only	ADV
ap-5377	330	7	for	for	ADP
ap-5377	330	8	a	a	DET
ap-5377	330	9	verification	verification	NOUN
ap-5377	330	10	of	of	ADP
ap-5377	330	11	the	the	DET
ap-5377	330	12	basic	basic	ADJ
ap-5377	330	13	properties	property	NOUN
ap-5377	330	14	of	of	ADP
ap-5377	330	15	algorithms	algorithm	NOUN
ap-5377	330	16	.	.	PUNCT
ap-5377	331	1	if	if	SCONJ
ap-5377	331	2	the	the	DET
ap-5377	331	3	algorithms	algorithm	NOUN
ap-5377	331	4	are	be	AUX
ap-5377	331	5	correctly	correctly	ADV
ap-5377	331	6	designed	design	VERB
ap-5377	331	7	,	,	PUNCT
ap-5377	331	8	the	the	DET
ap-5377	331	9	expected	expect	VERB
ap-5377	331	10	behaviour	behaviour	NOUN
ap-5377	331	11	of	of	ADP
ap-5377	331	12	the	the	DET
ap-5377	331	13	algorithms	algorithms	NOUN
ap-5377	331	14	is	be	AUX
ap-5377	331	15	confirmed	confirm	VERB
ap-5377	331	16	.	.	PUNCT
ap-5377	332	1	according	accord	VERB
ap-5377	332	2	to	to	ADP
ap-5377	332	3	the	the	DET
ap-5377	332	4	assumptions	assumption	NOUN
ap-5377	332	5	,	,	PUNCT
ap-5377	332	6	all	all	DET
ap-5377	332	7	three	three	NUM
ap-5377	332	8	algorithms	algorithm	NOUN
ap-5377	332	9	presented	present	VERB
ap-5377	332	10	good	good	ADJ
ap-5377	332	11	results	result	NOUN
ap-5377	332	12	for	for	ADP
ap-5377	332	13	the	the	DET
ap-5377	332	14	testing	testing	NOUN
ap-5377	332	15	data	datum	NOUN
ap-5377	332	16	with	with	ADP
ap-5377	332	17	two	two	NUM
ap-5377	332	18	good	good	ADJ
ap-5377	332	19	separated	separate	VERB
ap-5377	332	20	clusters	cluster	NOUN
ap-5377	332	21	.	.	PUNCT
ap-5377	333	1	both	both	DET
ap-5377	333	2	density	density	NOUN
ap-5377	333	3	based	base	VERB
ap-5377	333	4	algorithms	algorithm	NOUN
ap-5377	333	5	dbscan	dbscan	NOUN
ap-5377	333	6	and	and	CCONJ
ap-5377	333	7	denclue	denclue	NOUN
ap-5377	333	8	displayed	display	VERB
ap-5377	333	9	good	good	ADJ
ap-5377	333	10	results	result	NOUN
ap-5377	333	11	for	for	ADP
ap-5377	333	12	the	the	DET
ap-5377	333	13	testing	testing	NOUN
ap-5377	333	14	data	datum	NOUN
ap-5377	333	15	with	with	ADP
ap-5377	333	16	nested	nested	ADJ
ap-5377	333	17	505	505	NUM
ap-5377	333	18	m.	m.	NOUN
ap-5377	333	19	piorecký	piorecký	NOUN
ap-5377	333	20	,	,	PUNCT
ap-5377	333	21	j.	j.	PROPN
ap-5377	333	22	štrobl	štrobl	PROPN
ap-5377	333	23	,	,	PUNCT
ap-5377	333	24	v.	v.	ADP
ap-5377	333	25	krajča	krajča	PROPN
ap-5377	333	26	acta	acta	PROPN
ap-5377	333	27	polytechnica	polytechnica	PROPN
ap-5377	333	28	feature	feature	NOUN
ap-5377	333	29	x	x	PUNCT
ap-5377	334	1	[	[	X
ap-5377	334	2	-	-	X
ap-5377	334	3	]	]	X
ap-5377	334	4	0	0	NUM
ap-5377	334	5	0.2	0.2	NUM
ap-5377	334	6	0.4	0.4	NUM
ap-5377	334	7	0.6	0.6	NUM
ap-5377	334	8	0.8	0.8	NUM
ap-5377	334	9	1	1	NUM
ap-5377	334	10	f	f	SYM
ap-5377	334	11	ea	ea	X
ap-5377	334	12	tu	tu	X
ap-5377	334	13	re	re	X
ap-5377	334	14	y	y	PROPN
ap-5377	335	1	[	[	X
ap-5377	335	2	]	]	X
ap-5377	335	3	0	0	NUM
ap-5377	335	4	0.2	0.2	NUM
ap-5377	335	5	0.4	0.4	NUM
ap-5377	335	6	0.6	0.6	NUM
ap-5377	335	7	0.8	0.8	NUM
ap-5377	335	8	1	1	NUM
ap-5377	335	9	feature	feature	NOUN
ap-5377	335	10	x	x	SYM
ap-5377	336	1	[	[	X
ap-5377	336	2	-	-	X
ap-5377	336	3	]	]	X
ap-5377	336	4	0	0	NUM
ap-5377	336	5	0.2	0.2	NUM
ap-5377	336	6	0.4	0.4	NUM
ap-5377	336	7	0.6	0.6	NUM
ap-5377	336	8	0.8	0.8	NUM
ap-5377	336	9	1	1	NUM
ap-5377	336	10	f	f	SYM
ap-5377	336	11	ea	ea	X
ap-5377	336	12	tu	tu	X
ap-5377	336	13	re	re	X
ap-5377	336	14	y	y	PROPN
ap-5377	337	1	[	[	X
ap-5377	337	2	]	]	X
ap-5377	337	3	0	0	NUM
ap-5377	337	4	0.2	0.2	NUM
ap-5377	337	5	0.4	0.4	NUM
ap-5377	337	6	0.6	0.6	NUM
ap-5377	337	7	0.8	0.8	NUM
ap-5377	337	8	1	1	NUM
ap-5377	337	9	feature	feature	NOUN
ap-5377	337	10	x	x	SYM
ap-5377	338	1	[	[	X
ap-5377	338	2	-	-	X
ap-5377	338	3	]	]	X
ap-5377	338	4	0	0	NUM
ap-5377	338	5	0.2	0.2	NUM
ap-5377	338	6	0.4	0.4	NUM
ap-5377	338	7	0.6	0.6	NUM
ap-5377	338	8	0.8	0.8	NUM
ap-5377	338	9	1	1	NUM
ap-5377	338	10	f	f	SYM
ap-5377	338	11	ea	ea	X
ap-5377	338	12	tu	tu	X
ap-5377	338	13	re	re	X
ap-5377	338	14	y	y	PROPN
ap-5377	339	1	[	[	X
ap-5377	339	2	]	]	X
ap-5377	339	3	0	0	NUM
ap-5377	339	4	0.2	0.2	NUM
ap-5377	339	5	0.4	0.4	NUM
ap-5377	339	6	0.6	0.6	NUM
ap-5377	339	7	0.8	0.8	NUM
ap-5377	339	8	1	1	NUM
ap-5377	339	9	feature	feature	NOUN
ap-5377	339	10	x	x	SYM
ap-5377	340	1	[	[	X
ap-5377	340	2	-	-	X
ap-5377	340	3	]	]	X
ap-5377	340	4	0	0	NUM
ap-5377	340	5	0.2	0.2	NUM
ap-5377	340	6	0.4	0.4	NUM
ap-5377	340	7	0.6	0.6	NUM
ap-5377	340	8	0.8	0.8	NUM
ap-5377	340	9	1	1	NUM
ap-5377	340	10	f	f	SYM
ap-5377	340	11	ea	ea	X
ap-5377	340	12	tu	tu	X
ap-5377	340	13	re	re	X
ap-5377	340	14	y	y	PROPN
ap-5377	341	1	[	[	X
ap-5377	341	2	]	]	X
ap-5377	341	3	0	0	NUM
ap-5377	341	4	0.2	0.2	NUM
ap-5377	341	5	0.4	0.4	NUM
ap-5377	341	6	0.6	0.6	NUM
ap-5377	341	7	0.8	0.8	NUM
ap-5377	341	8	1	1	NUM
ap-5377	341	9	figure	figure	NOUN
ap-5377	341	10	9	9	NUM
ap-5377	341	11	.	.	NOUN
ap-5377	341	12	example	example	NOUN
ap-5377	341	13	of	of	ADP
ap-5377	341	14	the	the	DET
ap-5377	341	15	classification	classification	NOUN
ap-5377	341	16	of	of	ADP
ap-5377	341	17	simulated	simulate	VERB
ap-5377	341	18	data	datum	NOUN
ap-5377	341	19	by	by	ADP
ap-5377	341	20	algorithms	algorithm	NOUN
ap-5377	341	21	dbscan	dbscan	NOUN
ap-5377	341	22	and	and	CCONJ
ap-5377	341	23	denclue	denclue	NOUN
ap-5377	341	24	.	.	PUNCT
ap-5377	342	1	different	different	ADJ
ap-5377	342	2	classes	class	NOUN
ap-5377	342	3	are	be	AUX
ap-5377	342	4	represented	represent	VERB
ap-5377	342	5	by	by	ADP
ap-5377	342	6	different	different	ADJ
ap-5377	342	7	shades	shade	NOUN
ap-5377	342	8	of	of	ADP
ap-5377	342	9	grey	grey	PROPN
ap-5377	342	10	.	.	PUNCT
ap-5377	343	1	feature	feature	NOUN
ap-5377	343	2	x	x	PUNCT
ap-5377	344	1	[	[	X
ap-5377	344	2	-	-	X
ap-5377	344	3	]	]	X
ap-5377	344	4	0	0	NUM
ap-5377	344	5	0.2	0.2	NUM
ap-5377	344	6	0.4	0.4	NUM
ap-5377	344	7	0.6	0.6	NUM
ap-5377	344	8	0.8	0.8	NUM
ap-5377	344	9	1	1	NUM
ap-5377	344	10	f	f	SYM
ap-5377	344	11	ea	ea	X
ap-5377	344	12	tu	tu	X
ap-5377	344	13	re	re	X
ap-5377	344	14	y	y	PROPN
ap-5377	345	1	[	[	X
ap-5377	345	2	]	]	X
ap-5377	345	3	0	0	NUM
ap-5377	345	4	0.2	0.2	NUM
ap-5377	345	5	0.4	0.4	NUM
ap-5377	345	6	0.6	0.6	NUM
ap-5377	345	7	0.8	0.8	NUM
ap-5377	345	8	1	1	NUM
ap-5377	345	9	feature	feature	NOUN
ap-5377	345	10	x	x	SYM
ap-5377	346	1	[	[	X
ap-5377	346	2	-	-	X
ap-5377	346	3	]	]	X
ap-5377	346	4	0	0	NUM
ap-5377	346	5	0.2	0.2	NUM
ap-5377	346	6	0.4	0.4	NUM
ap-5377	346	7	0.6	0.6	NUM
ap-5377	346	8	0.8	0.8	NUM
ap-5377	346	9	1	1	NUM
ap-5377	346	10	f	f	SYM
ap-5377	346	11	ea	ea	X
ap-5377	346	12	tu	tu	X
ap-5377	346	13	re	re	X
ap-5377	346	14	y	y	PROPN
ap-5377	347	1	[	[	X
ap-5377	347	2	]	]	X
ap-5377	347	3	0	0	NUM
ap-5377	347	4	0.2	0.2	NUM
ap-5377	347	5	0.4	0.4	NUM
ap-5377	347	6	0.6	0.6	NUM
ap-5377	347	7	0.8	0.8	NUM
ap-5377	347	8	1	1	NUM
ap-5377	347	9	feature	feature	NOUN
ap-5377	347	10	x	x	SYM
ap-5377	348	1	[	[	X
ap-5377	348	2	-	-	X
ap-5377	348	3	]	]	X
ap-5377	348	4	0	0	NUM
ap-5377	348	5	0.2	0.2	NUM
ap-5377	348	6	0.4	0.4	NUM
ap-5377	348	7	0.6	0.6	NUM
ap-5377	348	8	0.8	0.8	NUM
ap-5377	348	9	1	1	NUM
ap-5377	348	10	f	f	SYM
ap-5377	348	11	ea	ea	X
ap-5377	348	12	tu	tu	X
ap-5377	348	13	re	re	X
ap-5377	348	14	y	y	PROPN
ap-5377	349	1	[	[	X
ap-5377	349	2	]	]	X
ap-5377	349	3	0	0	NUM
ap-5377	349	4	0.2	0.2	NUM
ap-5377	349	5	0.4	0.4	NUM
ap-5377	349	6	0.6	0.6	NUM
ap-5377	349	7	0.8	0.8	NUM
ap-5377	349	8	1	1	NUM
ap-5377	349	9	feature	feature	NOUN
ap-5377	349	10	x	x	SYM
ap-5377	350	1	[	[	X
ap-5377	350	2	-	-	X
ap-5377	350	3	]	]	X
ap-5377	350	4	0	0	NUM
ap-5377	350	5	0.2	0.2	NUM
ap-5377	350	6	0.4	0.4	NUM
ap-5377	350	7	0.6	0.6	NUM
ap-5377	350	8	0.8	0.8	NUM
ap-5377	350	9	1	1	NUM
ap-5377	350	10	f	f	SYM
ap-5377	350	11	ea	ea	X
ap-5377	350	12	tu	tu	X
ap-5377	350	13	re	re	X
ap-5377	350	14	y	y	PROPN
ap-5377	351	1	[	[	X
ap-5377	351	2	]	]	X
ap-5377	351	3	0	0	NUM
ap-5377	351	4	0.2	0.2	NUM
ap-5377	351	5	0.4	0.4	NUM
ap-5377	351	6	0.6	0.6	NUM
ap-5377	351	7	0.8	0.8	NUM
ap-5377	351	8	1	1	NUM
ap-5377	351	9	figure	figure	NOUN
ap-5377	351	10	10	10	NUM
ap-5377	351	11	.	.	PUNCT
ap-5377	351	12	example	example	NOUN
ap-5377	351	13	of	of	ADP
ap-5377	351	14	classification	classification	NOUN
ap-5377	351	15	of	of	ADP
ap-5377	351	16	simulated	simulate	VERB
ap-5377	351	17	data	datum	NOUN
ap-5377	351	18	by	by	ADP
ap-5377	351	19	algorithm	algorithm	NOUN
ap-5377	351	20	k	k	NOUN
ap-5377	351	21	-	-	PUNCT
ap-5377	351	22	means	mean	NOUN
ap-5377	351	23	.	.	PUNCT
ap-5377	352	1	different	different	ADJ
ap-5377	352	2	classes	class	NOUN
ap-5377	352	3	are	be	AUX
ap-5377	352	4	displayed	display	VERB
ap-5377	352	5	by	by	ADP
ap-5377	352	6	different	different	ADJ
ap-5377	352	7	shades	shade	NOUN
ap-5377	352	8	of	of	ADP
ap-5377	352	9	grey	grey	NOUN
ap-5377	352	10	.	.	PUNCT
ap-5377	353	1	506	506	NUM
ap-5377	353	2	vol	vol	NOUN
ap-5377	353	3	.	.	PUNCT
ap-5377	354	1	59	59	NUM
ap-5377	354	2	no	no	NOUN
ap-5377	354	3	.	.	PUNCT
ap-5377	355	1	5/2019	5/2019	NUM
ap-5377	355	2	automatic	automatic	ADJ
ap-5377	355	3	eeg	eeg	NOUN
ap-5377	355	4	classification	classification	NOUN
ap-5377	355	5	using	use	VERB
ap-5377	355	6	dbscan	dbscan	NOUN
ap-5377	355	7	and	and	CCONJ
ap-5377	355	8	denclue	denclue	NOUN
ap-5377	355	9	figure	figure	NOUN
ap-5377	355	10	11	11	NUM
ap-5377	355	11	.	.	PUNCT
ap-5377	356	1	work	work	NOUN
ap-5377	356	2	motivation	motivation	NOUN
ap-5377	356	3	:	:	PUNCT
ap-5377	356	4	highlighting	highlight	VERB
ap-5377	356	5	the	the	DET
ap-5377	356	6	eeg	eeg	NOUN
ap-5377	356	7	record	record	NOUN
ap-5377	356	8	sections	section	NOUN
ap-5377	356	9	to	to	PART
ap-5377	356	10	which	which	PRON
ap-5377	356	11	the	the	DET
ap-5377	356	12	physician	physician	NOUN
ap-5377	356	13	should	should	AUX
ap-5377	356	14	pay	pay	VERB
ap-5377	356	15	attention	attention	NOUN
ap-5377	356	16	.	.	PUNCT
ap-5377	357	1	clusters	cluster	NOUN
ap-5377	357	2	(	(	PUNCT
ap-5377	357	3	see	see	VERB
ap-5377	357	4	figure	figure	NOUN
ap-5377	357	5	9	9	NUM
ap-5377	357	6	)	)	PUNCT
ap-5377	357	7	,	,	PUNCT
ap-5377	357	8	which	which	PRON
ap-5377	357	9	is	be	AUX
ap-5377	357	10	their	their	PRON
ap-5377	357	11	main	main	ADJ
ap-5377	357	12	advantage	advantage	NOUN
ap-5377	357	13	.	.	PUNCT
ap-5377	358	1	conversely	conversely	ADV
ap-5377	358	2	,	,	PUNCT
ap-5377	358	3	the	the	DET
ap-5377	358	4	k	k	NOUN
ap-5377	358	5	-	-	PUNCT
ap-5377	358	6	means	means	NOUN
ap-5377	358	7	algorithm	algorithm	NOUN
ap-5377	358	8	was	be	AUX
ap-5377	358	9	unable	unable	ADJ
ap-5377	358	10	to	to	PART
ap-5377	358	11	separate	separate	VERB
ap-5377	358	12	nested	nested	ADJ
ap-5377	358	13	clusters	cluster	NOUN
ap-5377	358	14	and	and	CCONJ
ap-5377	358	15	also	also	ADV
ap-5377	358	16	had	have	VERB
ap-5377	358	17	problems	problem	NOUN
ap-5377	358	18	with	with	ADP
ap-5377	358	19	the	the	DET
ap-5377	358	20	classification	classification	NOUN
ap-5377	358	21	of	of	ADP
ap-5377	358	22	the	the	DET
ap-5377	358	23	outliers	outlier	NOUN
ap-5377	358	24	(	(	PUNCT
ap-5377	358	25	see	see	VERB
ap-5377	358	26	figure	figure	NOUN
ap-5377	358	27	10	10	NUM
ap-5377	358	28	)	)	PUNCT
ap-5377	358	29	.	.	PUNCT
ap-5377	359	1	the	the	DET
ap-5377	359	2	results	result	NOUN
ap-5377	359	3	of	of	ADP
ap-5377	359	4	the	the	DET
ap-5377	359	5	testing	testing	NOUN
ap-5377	359	6	dataset	dataset	NOUN
ap-5377	359	7	are	be	AUX
ap-5377	359	8	in	in	ADP
ap-5377	359	9	line	line	NOUN
ap-5377	359	10	with	with	ADP
ap-5377	359	11	the	the	DET
ap-5377	359	12	assumptions	assumption	NOUN
ap-5377	359	13	.	.	PUNCT
ap-5377	360	1	algorithms	algorithm	NOUN
ap-5377	360	2	were	be	AUX
ap-5377	360	3	used	use	VERB
ap-5377	360	4	on	on	ADP
ap-5377	360	5	the	the	DET
ap-5377	360	6	real	real	ADJ
ap-5377	360	7	eeg	eeg	NOUN
ap-5377	360	8	data	datum	NOUN
ap-5377	360	9	after	after	ADP
ap-5377	360	10	their	their	PRON
ap-5377	360	11	verifying	verifying	NOUN
ap-5377	360	12	on	on	ADP
ap-5377	360	13	the	the	DET
ap-5377	360	14	testing	testing	NOUN
ap-5377	360	15	data	datum	NOUN
ap-5377	360	16	.	.	PUNCT
ap-5377	361	1	we	we	PRON
ap-5377	361	2	divided	divide	VERB
ap-5377	361	3	the	the	DET
ap-5377	361	4	eeg	eeg	NOUN
ap-5377	361	5	data	datum	NOUN
ap-5377	361	6	into	into	ADP
ap-5377	361	7	five	five	NUM
ap-5377	361	8	clusters	cluster	NOUN
ap-5377	361	9	according	accord	VERB
ap-5377	361	10	to	to	ADP
ap-5377	361	11	the	the	DET
ap-5377	361	12	clinical	clinical	ADJ
ap-5377	361	13	significance	significance	NOUN
ap-5377	361	14	of	of	ADP
ap-5377	361	15	the	the	DET
ap-5377	361	16	eeg	eeg	NOUN
ap-5377	361	17	segments	segment	NOUN
ap-5377	361	18	.	.	PUNCT
ap-5377	362	1	these	these	DET
ap-5377	362	2	classes	class	NOUN
ap-5377	362	3	represent	represent	VERB
ap-5377	362	4	the	the	DET
ap-5377	362	5	important	important	ADJ
ap-5377	362	6	parts	part	NOUN
ap-5377	362	7	of	of	ADP
ap-5377	362	8	the	the	DET
ap-5377	362	9	epileptic	epileptic	ADJ
ap-5377	362	10	eeg	eeg	PROPN
ap-5377	362	11	signal	signal	NOUN
ap-5377	362	12	(	(	PUNCT
ap-5377	362	13	physiological	physiological	ADJ
ap-5377	362	14	activity	activity	NOUN
ap-5377	362	15	,	,	PUNCT
ap-5377	362	16	epileptic	epileptic	ADJ
ap-5377	362	17	activity	activity	NOUN
ap-5377	362	18	,	,	PUNCT
ap-5377	362	19	emg	emg	NOUN
ap-5377	362	20	artefacts	artefact	NOUN
ap-5377	362	21	,	,	PUNCT
ap-5377	362	22	slow	slow	ADJ
ap-5377	362	23	eye	eye	NOUN
ap-5377	362	24	artefacts	artefact	NOUN
ap-5377	362	25	,	,	PUNCT
ap-5377	362	26	and	and	CCONJ
ap-5377	362	27	technical	technical	ADJ
ap-5377	362	28	artefacts	artefact	NOUN
ap-5377	362	29	from	from	ADP
ap-5377	362	30	a	a	DET
ap-5377	362	31	poor	poor	ADJ
ap-5377	362	32	electrode	electrode	NOUN
ap-5377	362	33	contact	contact	NOUN
ap-5377	362	34	)	)	PUNCT
ap-5377	362	35	.	.	PUNCT
ap-5377	363	1	for	for	ADP
ap-5377	363	2	all	all	DET
ap-5377	363	3	three	three	NUM
ap-5377	363	4	tested	test	VERB
ap-5377	363	5	algorithms	algorithm	NOUN
ap-5377	363	6	,	,	PUNCT
ap-5377	363	7	five	five	NUM
ap-5377	363	8	classes	class	NOUN
ap-5377	363	9	were	be	AUX
ap-5377	363	10	computed	compute	VERB
ap-5377	363	11	:	:	PUNCT
ap-5377	363	12	sensitivity	sensitivity	NOUN
ap-5377	363	13	,	,	PUNCT
ap-5377	363	14	specificity	specificity	NOUN
ap-5377	363	15	,	,	PUNCT
ap-5377	363	16	and	and	CCONJ
ap-5377	363	17	positive	positive	ADJ
ap-5377	363	18	predictive	predictive	ADJ
ap-5377	363	19	value	value	NOUN
ap-5377	363	20	(	(	PUNCT
ap-5377	363	21	ppv	ppv	NOUN
ap-5377	363	22	)	)	PUNCT
ap-5377	363	23	.	.	PUNCT
ap-5377	364	1	the	the	DET
ap-5377	364	2	class	class	NOUN
ap-5377	364	3	of	of	ADP
ap-5377	364	4	the	the	DET
ap-5377	364	5	epileptic	epileptic	ADJ
ap-5377	364	6	activity	activity	NOUN
ap-5377	364	7	is	be	AUX
ap-5377	364	8	very	very	ADV
ap-5377	364	9	important	important	ADJ
ap-5377	364	10	for	for	ADP
ap-5377	364	11	an	an	DET
ap-5377	364	12	expert	expert	NOUN
ap-5377	364	13	in	in	ADP
ap-5377	364	14	clinical	clinical	ADJ
ap-5377	364	15	practice	practice	NOUN
ap-5377	364	16	.	.	PUNCT
ap-5377	365	1	all	all	DET
ap-5377	365	2	algorithms	algorithm	NOUN
ap-5377	365	3	have	have	VERB
ap-5377	365	4	high	high	ADJ
ap-5377	365	5	specificity	specificity	NOUN
ap-5377	365	6	for	for	ADP
ap-5377	365	7	this	this	DET
ap-5377	365	8	class	class	NOUN
ap-5377	365	9	(	(	PUNCT
ap-5377	365	10	see	see	VERB
ap-5377	365	11	table	table	NOUN
ap-5377	365	12	4	4	NUM
ap-5377	365	13	)	)	PUNCT
ap-5377	365	14	.	.	PUNCT
ap-5377	366	1	this	this	PRON
ap-5377	366	2	means	mean	VERB
ap-5377	366	3	that	that	SCONJ
ap-5377	366	4	all	all	DET
ap-5377	366	5	tested	test	VERB
ap-5377	366	6	algorithms	algorithm	NOUN
ap-5377	366	7	correctly	correctly	ADV
ap-5377	366	8	do	do	AUX
ap-5377	366	9	not	not	PART
ap-5377	366	10	include	include	VERB
ap-5377	366	11	segments	segment	NOUN
ap-5377	366	12	that	that	PRON
ap-5377	366	13	do	do	AUX
ap-5377	366	14	not	not	PART
ap-5377	366	15	belong	belong	VERB
ap-5377	366	16	in	in	ADP
ap-5377	366	17	the	the	DET
ap-5377	366	18	observed	observed	ADJ
ap-5377	366	19	class	class	NOUN
ap-5377	366	20	of	of	ADP
ap-5377	366	21	the	the	DET
ap-5377	366	22	epileptic	epileptic	ADJ
ap-5377	366	23	activity	activity	NOUN
ap-5377	366	24	.	.	PUNCT
ap-5377	367	1	the	the	DET
ap-5377	367	2	class	class	NOUN
ap-5377	367	3	of	of	ADP
ap-5377	367	4	epilepsy	epilepsy	NOUN
ap-5377	367	5	activity	activity	NOUN
ap-5377	367	6	also	also	ADV
ap-5377	367	7	had	have	VERB
ap-5377	367	8	higher	high	ADJ
ap-5377	367	9	values	value	NOUN
ap-5377	367	10	for	for	ADP
ap-5377	367	11	all	all	DET
ap-5377	367	12	algorithms	algorithm	NOUN
ap-5377	367	13	for	for	ADP
ap-5377	367	14	the	the	DET
ap-5377	367	15	sensitivity	sensitivity	NOUN
ap-5377	367	16	parameter	parameter	NOUN
ap-5377	367	17	(	(	PUNCT
ap-5377	367	18	see	see	VERB
ap-5377	367	19	table	table	NOUN
ap-5377	367	20	3	3	NUM
ap-5377	367	21	)	)	PUNCT
ap-5377	367	22	,	,	PUNCT
ap-5377	367	23	so	so	CCONJ
ap-5377	367	24	the	the	DET
ap-5377	367	25	tested	test	VERB
ap-5377	367	26	algorithms	algorithm	NOUN
ap-5377	367	27	found	find	VERB
ap-5377	367	28	most	most	ADJ
ap-5377	367	29	of	of	ADP
ap-5377	367	30	the	the	DET
ap-5377	367	31	epilepsy	epilepsy	NOUN
ap-5377	367	32	segments	segment	NOUN
ap-5377	367	33	.	.	PUNCT
ap-5377	368	1	the	the	DET
ap-5377	368	2	dbscan	dbscan	PROPN
ap-5377	368	3	algorithm	algorithm	PROPN
ap-5377	368	4	had	have	VERB
ap-5377	368	5	the	the	DET
ap-5377	368	6	highest	high	ADJ
ap-5377	368	7	ppv	ppv	NOUN
ap-5377	368	8	for	for	ADP
ap-5377	368	9	the	the	DET
ap-5377	368	10	class	class	NOUN
ap-5377	368	11	of	of	ADP
ap-5377	368	12	an	an	DET
ap-5377	368	13	epilepsy	epilepsy	NOUN
ap-5377	368	14	activity	activity	NOUN
ap-5377	368	15	.	.	PUNCT
ap-5377	369	1	the	the	DET
ap-5377	369	2	denclue	denclue	NOUN
ap-5377	369	3	algorithm	algorithm	NOUN
ap-5377	369	4	had	have	VERB
ap-5377	369	5	ppv	ppv	NOUN
ap-5377	369	6	0.813	0.813	NUM
ap-5377	369	7	,	,	PUNCT
ap-5377	369	8	although	although	SCONJ
ap-5377	369	9	the	the	DET
ap-5377	369	10	k	k	NOUN
ap-5377	369	11	-	-	PUNCT
ap-5377	369	12	means	means	NOUN
ap-5377	369	13	algorithm	algorithm	NOUN
ap-5377	369	14	had	have	VERB
ap-5377	369	15	ppv	ppv	NOUN
ap-5377	369	16	value	value	NOUN
ap-5377	369	17	of	of	ADP
ap-5377	369	18	the	the	DET
ap-5377	369	19	class	class	NOUN
ap-5377	369	20	of	of	ADP
ap-5377	369	21	the	the	DET
ap-5377	369	22	epilepsy	epilepsy	NOUN
ap-5377	369	23	activity	activity	NOUN
ap-5377	369	24	only	only	ADV
ap-5377	369	25	0.641	0.641	NUM
ap-5377	369	26	(	(	PUNCT
ap-5377	369	27	see	see	VERB
ap-5377	369	28	table	table	NOUN
ap-5377	369	29	5	5	NUM
ap-5377	369	30	)	)	PUNCT
ap-5377	369	31	.	.	PUNCT
ap-5377	370	1	the	the	DET
ap-5377	370	2	k	k	NOUN
ap-5377	370	3	-	-	PUNCT
ap-5377	370	4	means	means	NOUN
ap-5377	370	5	algorithm	algorithm	NOUN
ap-5377	370	6	creates	create	VERB
ap-5377	370	7	a	a	DET
ap-5377	370	8	class	class	NOUN
ap-5377	370	9	of	of	ADP
ap-5377	370	10	the	the	DET
ap-5377	370	11	epilepsy	epilepsy	NOUN
ap-5377	370	12	activity	activity	NOUN
ap-5377	370	13	,	,	PUNCT
ap-5377	370	14	including	include	VERB
ap-5377	370	15	segments	segment	NOUN
ap-5377	370	16	from	from	ADP
ap-5377	370	17	other	other	ADJ
ap-5377	370	18	classes	class	NOUN
ap-5377	370	19	.	.	PUNCT
ap-5377	371	1	the	the	DET
ap-5377	371	2	class	class	NOUN
ap-5377	371	3	of	of	ADP
ap-5377	371	4	the	the	DET
ap-5377	371	5	physiological	physiological	ADJ
ap-5377	371	6	activity	activity	NOUN
ap-5377	371	7	had	have	VERB
ap-5377	371	8	a	a	DET
ap-5377	371	9	high	high	ADJ
ap-5377	371	10	ppv	ppv	NOUN
ap-5377	371	11	and	and	CCONJ
ap-5377	371	12	specificity	specificity	NOUN
ap-5377	371	13	for	for	ADP
ap-5377	371	14	all	all	DET
ap-5377	371	15	tested	test	VERB
ap-5377	371	16	algorithms	algorithm	NOUN
ap-5377	371	17	(	(	PUNCT
ap-5377	371	18	see	see	VERB
ap-5377	371	19	tables	table	NOUN
ap-5377	371	20	5	5	NUM
ap-5377	371	21	and	and	CCONJ
ap-5377	371	22	4	4	NUM
ap-5377	371	23	)	)	PUNCT
ap-5377	371	24	.	.	PUNCT
ap-5377	372	1	the	the	DET
ap-5377	372	2	reason	reason	NOUN
ap-5377	372	3	is	be	AUX
ap-5377	372	4	a	a	DET
ap-5377	372	5	much	much	ADV
ap-5377	372	6	larger	large	ADJ
ap-5377	372	7	number	number	NOUN
ap-5377	372	8	of	of	ADP
ap-5377	372	9	physiological	physiological	ADJ
ap-5377	372	10	segments	segment	NOUN
ap-5377	372	11	contained	contain	VERB
ap-5377	372	12	in	in	ADP
ap-5377	372	13	the	the	DET
ap-5377	372	14	eeg	eeg	NOUN
ap-5377	372	15	signals	signal	NOUN
ap-5377	372	16	than	than	ADP
ap-5377	372	17	segments	segment	NOUN
ap-5377	372	18	of	of	ADP
ap-5377	372	19	other	other	ADJ
ap-5377	372	20	classes	class	NOUN
ap-5377	372	21	.	.	PUNCT
ap-5377	373	1	the	the	DET
ap-5377	373	2	k	k	NOUN
ap-5377	373	3	-	-	PUNCT
ap-5377	373	4	means	means	NOUN
ap-5377	373	5	algorithm	algorithm	NOUN
ap-5377	373	6	has	have	VERB
ap-5377	373	7	a	a	DET
ap-5377	373	8	predetermined	predetermine	VERB
ap-5377	373	9	number	number	NOUN
ap-5377	373	10	of	of	ADP
ap-5377	373	11	clusters	cluster	NOUN
ap-5377	373	12	.	.	PUNCT
ap-5377	374	1	we	we	PRON
ap-5377	374	2	used	use	VERB
ap-5377	374	3	seven	seven	NUM
ap-5377	374	4	clusters	cluster	NOUN
ap-5377	374	5	in	in	ADP
ap-5377	374	6	our	our	PRON
ap-5377	374	7	study	study	NOUN
ap-5377	374	8	.	.	PUNCT
ap-5377	375	1	this	this	DET
ap-5377	375	2	number	number	NOUN
ap-5377	375	3	of	of	ADP
ap-5377	375	4	clusters	cluster	NOUN
ap-5377	375	5	is	be	AUX
ap-5377	375	6	taken	take	VERB
ap-5377	375	7	from	from	ADP
ap-5377	375	8	settings	setting	NOUN
ap-5377	375	9	for	for	ADP
ap-5377	375	10	the	the	DET
ap-5377	375	11	clinical	clinical	ADJ
ap-5377	375	12	practice	practice	NOUN
ap-5377	375	13	of	of	ADP
ap-5377	375	14	the	the	DET
ap-5377	375	15	program	program	NOUN
ap-5377	375	16	wave	wave	NOUN
ap-5377	375	17	-	-	PUNCT
ap-5377	375	18	finder	finder	NOUN
ap-5377	375	19	and	and	CCONJ
ap-5377	375	20	is	be	AUX
ap-5377	375	21	selected	select	VERB
ap-5377	375	22	to	to	PART
ap-5377	375	23	better	well	ADV
ap-5377	375	24	detect	detect	VERB
ap-5377	375	25	the	the	DET
ap-5377	375	26	clinically	clinically	ADV
ap-5377	375	27	significant	significant	ADJ
ap-5377	375	28	epilepsy	epilepsy	ADJ
ap-5377	375	29	segments	segment	NOUN
ap-5377	375	30	.	.	PUNCT
ap-5377	376	1	the	the	DET
ap-5377	376	2	problem	problem	NOUN
ap-5377	376	3	of	of	ADP
ap-5377	376	4	the	the	DET
ap-5377	376	5	k	k	NOUN
ap-5377	376	6	-	-	PUNCT
ap-5377	376	7	means	means	NOUN
ap-5377	376	8	algorithm	algorithm	NOUN
ap-5377	376	9	is	be	AUX
ap-5377	376	10	that	that	SCONJ
ap-5377	376	11	segments	segment	NOUN
ap-5377	376	12	of	of	ADP
ap-5377	376	13	physiological	physiological	ADJ
ap-5377	376	14	activity	activity	NOUN
ap-5377	376	15	are	be	AUX
ap-5377	376	16	divided	divide	VERB
ap-5377	376	17	into	into	ADP
ap-5377	376	18	more	more	ADJ
ap-5377	376	19	classes	class	NOUN
ap-5377	376	20	,	,	PUNCT
ap-5377	376	21	this	this	PRON
ap-5377	376	22	causes	cause	VERB
ap-5377	376	23	a	a	DET
ap-5377	376	24	low	low	ADJ
ap-5377	376	25	sensitivity	sensitivity	NOUN
ap-5377	376	26	of	of	ADP
ap-5377	376	27	the	the	DET
ap-5377	376	28	k	k	NOUN
ap-5377	376	29	-	-	PUNCT
ap-5377	376	30	means	means	NOUN
ap-5377	376	31	algorithm	algorithm	NOUN
ap-5377	376	32	for	for	ADP
ap-5377	376	33	segments	segment	NOUN
ap-5377	376	34	of	of	ADP
ap-5377	376	35	the	the	DET
ap-5377	376	36	physiological	physiological	ADJ
ap-5377	376	37	activity	activity	NOUN
ap-5377	376	38	.	.	PUNCT
ap-5377	377	1	the	the	DET
ap-5377	377	2	dbscan	dbscan	NOUN
ap-5377	377	3	and	and	CCONJ
ap-5377	377	4	denclue	denclue	NOUN
ap-5377	377	5	algorithms	algorithm	NOUN
ap-5377	377	6	had	have	VERB
ap-5377	377	7	the	the	DET
ap-5377	377	8	sensitivity	sensitivity	NOUN
ap-5377	377	9	for	for	ADP
ap-5377	377	10	these	these	DET
ap-5377	377	11	segments	segment	NOUN
ap-5377	377	12	higher	high	ADJ
ap-5377	377	13	than	than	ADP
ap-5377	377	14	0.98	0.98	NUM
ap-5377	377	15	(	(	PUNCT
ap-5377	377	16	see	see	VERB
ap-5377	377	17	table	table	NOUN
ap-5377	377	18	3	3	NUM
ap-5377	377	19	)	)	PUNCT
ap-5377	377	20	.	.	PUNCT
ap-5377	378	1	the	the	DET
ap-5377	378	2	denclue	denclue	NOUN
ap-5377	378	3	algorithm	algorithm	NOUN
ap-5377	378	4	could	could	AUX
ap-5377	378	5	not	not	PART
ap-5377	378	6	find	find	VERB
ap-5377	378	7	segments	segment	NOUN
ap-5377	378	8	of	of	ADP
ap-5377	378	9	the	the	DET
ap-5377	378	10	slow	slow	ADJ
ap-5377	378	11	eye	eye	NOUN
ap-5377	378	12	artefacts	artefact	NOUN
ap-5377	378	13	.	.	PUNCT
ap-5377	379	1	the	the	DET
ap-5377	379	2	k	k	NOUN
ap-5377	379	3	-	-	PUNCT
ap-5377	379	4	means	means	NOUN
ap-5377	379	5	algorithm	algorithm	NOUN
ap-5377	379	6	also	also	ADV
ap-5377	379	7	had	have	VERB
ap-5377	379	8	problems	problem	NOUN
ap-5377	379	9	with	with	ADP
ap-5377	379	10	these	these	DET
ap-5377	379	11	segments	segment	NOUN
ap-5377	379	12	because	because	SCONJ
ap-5377	379	13	its	its	PRON
ap-5377	379	14	ppv	ppv	NOUN
ap-5377	379	15	is	be	AUX
ap-5377	379	16	only	only	ADV
ap-5377	379	17	0.010	0.010	NUM
ap-5377	379	18	.	.	PUNCT
ap-5377	380	1	the	the	DET
ap-5377	380	2	dbscan	dbscan	PROPN
ap-5377	380	3	algorithm	algorithm	PROPN
ap-5377	380	4	formed	form	VERB
ap-5377	380	5	classes	class	NOUN
ap-5377	380	6	of	of	ADP
ap-5377	380	7	the	the	DET
ap-5377	380	8	slow	slow	ADJ
ap-5377	380	9	eye	eye	NOUN
ap-5377	380	10	artefacts	artefact	NOUN
ap-5377	380	11	,	,	PUNCT
ap-5377	380	12	although	although	SCONJ
ap-5377	380	13	it	it	PRON
ap-5377	380	14	did	do	AUX
ap-5377	380	15	not	not	PART
ap-5377	380	16	find	find	VERB
ap-5377	380	17	most	most	ADJ
ap-5377	380	18	of	of	ADP
ap-5377	380	19	the	the	DET
ap-5377	380	20	segments	segment	NOUN
ap-5377	380	21	of	of	ADP
ap-5377	380	22	this	this	DET
ap-5377	380	23	class	class	NOUN
ap-5377	380	24	(	(	PUNCT
ap-5377	380	25	sensitivity	sensitivity	NOUN
ap-5377	380	26	was	be	AUX
ap-5377	380	27	only	only	ADV
ap-5377	380	28	0.094	0.094	NUM
ap-5377	380	29	)	)	PUNCT
ap-5377	380	30	.	.	PUNCT
ap-5377	381	1	the	the	DET
ap-5377	381	2	dbscan	dbscan	PROPN
ap-5377	381	3	algorithm	algorithm	PROPN
ap-5377	381	4	did	do	AUX
ap-5377	381	5	not	not	PART
ap-5377	381	6	find	find	VERB
ap-5377	381	7	segments	segment	NOUN
ap-5377	381	8	of	of	ADP
ap-5377	381	9	the	the	DET
ap-5377	381	10	emg	emg	NOUN
ap-5377	381	11	artefacts	artefact	VERB
ap-5377	381	12	.	.	PUNCT
ap-5377	382	1	the	the	DET
ap-5377	382	2	denclue	denclue	NOUN
ap-5377	382	3	algorithm	algorithm	NOUN
ap-5377	382	4	had	have	VERB
ap-5377	382	5	the	the	DET
ap-5377	382	6	highest	high	ADJ
ap-5377	382	7	ppv	ppv	NOUN
ap-5377	382	8	for	for	ADP
ap-5377	382	9	segments	segment	NOUN
ap-5377	382	10	of	of	ADP
ap-5377	382	11	the	the	DET
ap-5377	382	12	emg	emg	NOUN
ap-5377	382	13	artefacts	artefact	VERB
ap-5377	382	14	,	,	PUNCT
ap-5377	382	15	so	so	SCONJ
ap-5377	382	16	it	it	PRON
ap-5377	382	17	formed	form	VERB
ap-5377	382	18	a	a	DET
ap-5377	382	19	homogeneous	homogeneous	ADJ
ap-5377	382	20	class	class	NOUN
ap-5377	382	21	of	of	ADP
ap-5377	382	22	these	these	DET
ap-5377	382	23	segments	segment	NOUN
ap-5377	382	24	.	.	PUNCT
ap-5377	383	1	however	however	ADV
ap-5377	383	2	,	,	PUNCT
ap-5377	383	3	the	the	DET
ap-5377	383	4	denclue	denclue	NOUN
ap-5377	383	5	algorithm	algorithm	NOUN
ap-5377	383	6	did	do	AUX
ap-5377	383	7	not	not	PART
ap-5377	383	8	find	find	VERB
ap-5377	383	9	segments	segment	NOUN
ap-5377	383	10	of	of	ADP
ap-5377	383	11	the	the	DET
ap-5377	383	12	emg	emg	NOUN
ap-5377	383	13	artefact	artefact	NOUN
ap-5377	383	14	(	(	PUNCT
ap-5377	383	15	the	the	DET
ap-5377	383	16	sensitivity	sensitivity	NOUN
ap-5377	383	17	for	for	ADP
ap-5377	383	18	the	the	DET
ap-5377	383	19	denclue	denclue	NOUN
ap-5377	383	20	algorithm	algorithm	NOUN
ap-5377	383	21	was	be	AUX
ap-5377	383	22	0.6394	0.6394	NUM
ap-5377	383	23	)	)	PUNCT
ap-5377	383	24	.	.	PUNCT
ap-5377	384	1	all	all	DET
ap-5377	384	2	algorithms	algorithm	NOUN
ap-5377	384	3	were	be	AUX
ap-5377	384	4	able	able	ADJ
ap-5377	384	5	to	to	PART
ap-5377	384	6	identify	identify	VERB
ap-5377	384	7	segments	segment	NOUN
ap-5377	384	8	of	of	ADP
ap-5377	384	9	the	the	DET
ap-5377	384	10	artefacts	artefact	NOUN
ap-5377	384	11	from	from	ADP
ap-5377	384	12	the	the	DET
ap-5377	384	13	poor	poor	ADJ
ap-5377	384	14	electrode	electrode	NOUN
ap-5377	384	15	contact	contact	NOUN
ap-5377	384	16	(	(	PUNCT
ap-5377	384	17	see	see	VERB
ap-5377	384	18	tables	table	NOUN
ap-5377	384	19	3	3	NUM
ap-5377	384	20	,	,	PUNCT
ap-5377	384	21	4	4	NUM
ap-5377	384	22	and	and	CCONJ
ap-5377	384	23	5	5	NUM
ap-5377	384	24	)	)	PUNCT
ap-5377	384	25	.	.	PUNCT
ap-5377	385	1	5	5	X
ap-5377	385	2	.	.	X
ap-5377	385	3	conclusion	conclusion	NOUN
ap-5377	385	4	we	we	PRON
ap-5377	385	5	have	have	AUX
ap-5377	385	6	investigated	investigate	VERB
ap-5377	385	7	the	the	DET
ap-5377	385	8	efficiency	efficiency	NOUN
ap-5377	385	9	of	of	ADP
ap-5377	385	10	the	the	DET
ap-5377	385	11	densitybased	densitybase	VERB
ap-5377	385	12	denclue	denclue	NOUN
ap-5377	385	13	and	and	CCONJ
ap-5377	385	14	dbscan	dbscan	VERB
ap-5377	385	15	algorithms	algorithm	NOUN
ap-5377	385	16	for	for	ADP
ap-5377	385	17	a	a	DET
ap-5377	385	18	classification	classification	NOUN
ap-5377	385	19	of	of	ADP
ap-5377	385	20	the	the	DET
ap-5377	385	21	eeg	eeg	NOUN
ap-5377	385	22	segments	segment	NOUN
ap-5377	385	23	to	to	PART
ap-5377	385	24	clinically	clinically	ADV
ap-5377	385	25	relevant	relevant	ADJ
ap-5377	385	26	classes	class	NOUN
ap-5377	385	27	.	.	PUNCT
ap-5377	386	1	the	the	DET
ap-5377	386	2	k	k	NOUN
ap-5377	386	3	-	-	PUNCT
ap-5377	386	4	means	means	NOUN
ap-5377	386	5	algorithm	algorithm	NOUN
ap-5377	386	6	was	be	AUX
ap-5377	386	7	used	use	VERB
ap-5377	386	8	as	as	ADP
ap-5377	386	9	a	a	DET
ap-5377	386	10	comparison	comparison	NOUN
ap-5377	386	11	algorithm	algorithm	NOUN
ap-5377	386	12	used	use	VERB
ap-5377	386	13	in	in	ADP
ap-5377	386	14	clinical	clinical	ADJ
ap-5377	386	15	practice	practice	NOUN
ap-5377	386	16	.	.	PUNCT
ap-5377	387	1	densitybased	densitybase	VERB
ap-5377	387	2	algorithms	algorithm	NOUN
ap-5377	387	3	displayed	display	VERB
ap-5377	387	4	good	good	ADJ
ap-5377	387	5	results	result	NOUN
ap-5377	387	6	for	for	ADP
ap-5377	387	7	clinically	clinically	ADV
ap-5377	387	8	very	very	ADV
ap-5377	387	9	important	important	ADJ
ap-5377	387	10	classes	class	NOUN
ap-5377	387	11	of	of	ADP
ap-5377	387	12	the	the	DET
ap-5377	387	13	epilepsy	epilepsy	NOUN
ap-5377	387	14	activity	activity	NOUN
ap-5377	387	15	and	and	CCONJ
ap-5377	387	16	physiological	physiological	ADJ
ap-5377	387	17	activity	activity	NOUN
ap-5377	387	18	.	.	PUNCT
ap-5377	388	1	all	all	DET
ap-5377	388	2	algorithms	algorithm	NOUN
ap-5377	388	3	had	have	VERB
ap-5377	388	4	problems	problem	NOUN
ap-5377	388	5	with	with	ADP
ap-5377	388	6	the	the	DET
ap-5377	388	7	identification	identification	NOUN
ap-5377	388	8	of	of	ADP
ap-5377	388	9	the	the	DET
ap-5377	388	10	segments	segment	NOUN
ap-5377	388	11	of	of	ADP
ap-5377	388	12	the	the	DET
ap-5377	388	13	slow	slow	ADJ
ap-5377	388	14	eye	eye	NOUN
ap-5377	388	15	artefacts	artefact	NOUN
ap-5377	388	16	.	.	PUNCT
ap-5377	389	1	the	the	DET
ap-5377	389	2	dbscan	dbscan	PROPN
ap-5377	389	3	algorithm	algorithm	PROPN
ap-5377	389	4	created	create	VERB
ap-5377	389	5	the	the	DET
ap-5377	389	6	most	most	ADV
ap-5377	389	7	homogeneous	homogeneous	ADJ
ap-5377	389	8	classes	class	NOUN
ap-5377	389	9	with	with	ADP
ap-5377	389	10	the	the	DET
ap-5377	389	11	exception	exception	NOUN
ap-5377	389	12	of	of	ADP
ap-5377	389	13	the	the	DET
ap-5377	389	14	class	class	NOUN
ap-5377	389	15	of	of	ADP
ap-5377	389	16	the	the	DET
ap-5377	389	17	emg	emg	NOUN
ap-5377	389	18	artefacts	artefact	NOUN
ap-5377	389	19	,	,	PUNCT
ap-5377	389	20	which	which	PRON
ap-5377	389	21	could	could	AUX
ap-5377	389	22	not	not	PART
ap-5377	389	23	be	be	AUX
ap-5377	389	24	identified	identify	VERB
ap-5377	389	25	.	.	PUNCT
ap-5377	390	1	conversely	conversely	ADV
ap-5377	390	2	,	,	PUNCT
ap-5377	390	3	the	the	DET
ap-5377	390	4	denclue	denclue	NOUN
ap-5377	390	5	algorithm	algorithm	NOUN
ap-5377	390	6	forms	form	VERB
ap-5377	390	7	the	the	DET
ap-5377	390	8	homogeneous	homogeneous	ADJ
ap-5377	390	9	class	class	NOUN
ap-5377	390	10	of	of	ADP
ap-5377	390	11	the	the	DET
ap-5377	390	12	emg	emg	NOUN
ap-5377	390	13	artefacts	artefact	VERB
ap-5377	390	14	.	.	PUNCT
ap-5377	391	1	the	the	DET
ap-5377	391	2	results	result	NOUN
ap-5377	391	3	suggest	suggest	VERB
ap-5377	391	4	that	that	SCONJ
ap-5377	391	5	the	the	DET
ap-5377	391	6	use	use	NOUN
ap-5377	391	7	of	of	ADP
ap-5377	391	8	algorithms	algorithm	NOUN
ap-5377	391	9	,	,	PUNCT
ap-5377	391	10	especially	especially	ADV
ap-5377	391	11	for	for	ADP
ap-5377	391	12	the	the	DET
ap-5377	391	13	creation	creation	NOUN
ap-5377	391	14	of	of	ADP
ap-5377	391	15	homogeneous	homogeneous	ADJ
ap-5377	391	16	classes	class	NOUN
ap-5377	391	17	,	,	PUNCT
ap-5377	391	18	is	be	AUX
ap-5377	391	19	promising	promise	VERB
ap-5377	391	20	,	,	PUNCT
ap-5377	391	21	although	although	SCONJ
ap-5377	391	22	there	there	PRON
ap-5377	391	23	is	be	VERB
ap-5377	391	24	a	a	DET
ap-5377	391	25	need	need	NOUN
ap-5377	391	26	for	for	ADP
ap-5377	391	27	further	further	ADJ
ap-5377	391	28	testing	testing	NOUN
ap-5377	391	29	of	of	ADP
ap-5377	391	30	the	the	DET
ap-5377	391	31	algorithms	algorithm	NOUN
ap-5377	391	32	.	.	PUNCT
ap-5377	392	1	acknowledgements	acknowledgement	NOUN
ap-5377	392	2	this	this	DET
ap-5377	392	3	work	work	NOUN
ap-5377	392	4	was	be	AUX
ap-5377	392	5	supported	support	VERB
ap-5377	392	6	by	by	ADP
ap-5377	392	7	the	the	DET
ap-5377	392	8	grant	grant	PROPN
ap-5377	392	9	agency	agency	NOUN
ap-5377	392	10	of	of	ADP
ap-5377	392	11	the	the	DET
ap-5377	392	12	czech	czech	PROPN
ap-5377	392	13	technical	technical	PROPN
ap-5377	392	14	university	university	PROPN
ap-5377	392	15	in	in	ADP
ap-5377	392	16	prague	prague	NOUN
ap-5377	392	17	with	with	ADP
ap-5377	392	18	the	the	DET
ap-5377	392	19	topic	topic	NOUN
ap-5377	392	20	:	:	PUNCT
ap-5377	392	21	feature	feature	VERB
ap-5377	392	22	507	507	NUM
ap-5377	392	23	m.	m.	NOUN
ap-5377	392	24	piorecký	piorecký	NOUN
ap-5377	392	25	,	,	PUNCT
ap-5377	392	26	j.	j.	PROPN
ap-5377	392	27	štrobl	štrobl	PROPN
ap-5377	392	28	,	,	PUNCT
ap-5377	392	29	v.	v.	ADP
ap-5377	392	30	krajča	krajča	PROPN
ap-5377	392	31	acta	acta	PROPN
ap-5377	392	32	polytechnica	polytechnica	PROPN
ap-5377	392	33	space	space	NOUN
ap-5377	392	34	analysis	analysis	NOUN
ap-5377	392	35	using	use	VERB
ap-5377	392	36	linear	linear	PROPN
ap-5377	392	37	and	and	CCONJ
ap-5377	392	38	non	non	ADJ
ap-5377	392	39	-	-	ADJ
ap-5377	392	40	linear	linear	ADJ
ap-5377	392	41	reduction	reduction	NOUN
ap-5377	392	42	of	of	ADP
ap-5377	392	43	eeg	eeg	NOUN
ap-5377	392	44	space	space	NOUN
ap-5377	392	45	dimensions	dimension	NOUN
ap-5377	392	46	,	,	PUNCT
ap-5377	392	47	grant	grant	VERB
ap-5377	392	48	no	no	NOUN
ap-5377	392	49	.	.	PUNCT
ap-5377	393	1	sgs18/159	sgs18/159	NOUN
ap-5377	393	2	/	/	SYM
ap-5377	393	3	ohk4/2t/17	ohk4/2t/17	NOUN
ap-5377	393	4	;	;	PUNCT
ap-5377	393	5	and	and	CCONJ
ap-5377	393	6	by	by	ADP
ap-5377	393	7	the	the	DET
ap-5377	393	8	grant	grant	PROPN
ap-5377	393	9	agency	agency	PROPN
ap-5377	393	10	of	of	ADP
ap-5377	393	11	czech	czech	PROPN
ap-5377	393	12	republic	republic	NOUN
ap-5377	393	13	with	with	ADP
ap-5377	393	14	topic	topic	NOUN
ap-5377	393	15	:	:	PUNCT
ap-5377	393	16	temporal	temporal	ADJ
ap-5377	393	17	context	context	NOUN
ap-5377	393	18	in	in	ADP
ap-5377	393	19	analysis	analysis	NOUN
ap-5377	393	20	of	of	ADP
ap-5377	393	21	long	long	ADJ
ap-5377	393	22	-	-	PUNCT
ap-5377	393	23	term	term	NOUN
ap-5377	393	24	non	non	ADJ
ap-5377	393	25	-	-	ADJ
ap-5377	393	26	stationary	stationary	ADJ
ap-5377	393	27	multidimensional	multidimensional	ADJ
ap-5377	393	28	signal	signal	NOUN
ap-5377	393	29	,	,	PUNCT
ap-5377	393	30	register	register	VERB
ap-5377	393	31	no	no	DET
ap-5377	393	32	.	.	NOUN
ap-5377	393	33	17	17	NUM
ap-5377	393	34	-	-	SYM
ap-5377	393	35	20480s	20480s	NUM
ap-5377	393	36	.	.	PUNCT
ap-5377	394	1	we	we	PRON
ap-5377	394	2	thank	thank	VERB
ap-5377	394	3	to	to	ADP
ap-5377	394	4	mudr	mudr	PROPN
ap-5377	394	5	.	.	PUNCT
ap-5377	395	1	svojmil	svojmil	PROPN
ap-5377	395	2	petranek	petranek	NOUN
ap-5377	395	3	and	and	CCONJ
ap-5377	395	4	bulovka	bulovka	NOUN
ap-5377	395	5	hospital	hospital	NOUN
ap-5377	395	6	in	in	ADP
ap-5377	395	7	prague	prague	PROPN
ap-5377	395	8	,	,	PUNCT
ap-5377	395	9	department	department	NOUN
ap-5377	395	10	of	of	ADP
ap-5377	395	11	neurology	neurology	NOUN
ap-5377	395	12	,	,	PUNCT
ap-5377	395	13	prague	prague	PROPN
ap-5377	395	14	,	,	PUNCT
ap-5377	395	15	czech	czech	PROPN
ap-5377	395	16	republic	republic	NOUN
ap-5377	395	17	.	.	PUNCT
ap-5377	396	1	references	reference	NOUN
ap-5377	396	2	[	[	X
ap-5377	396	3	1	1	NUM
ap-5377	396	4	]	]	PUNCT
ap-5377	396	5	z.	z.	PROPN
ap-5377	396	6	dvey	dvey	PROPN
ap-5377	396	7	-	-	PUNCT
ap-5377	396	8	aharon	aharon	PROPN
ap-5377	396	9	,	,	PUNCT
ap-5377	396	10	n.	n.	PROPN
ap-5377	396	11	fogelson	fogelson	PROPN
ap-5377	396	12	,	,	PUNCT
ap-5377	396	13	a.	a.	PROPN
ap-5377	396	14	peled	pele	VERB
ap-5377	396	15	,	,	PUNCT
ap-5377	396	16	et	et	PROPN
ap-5377	396	17	al	al	PROPN
ap-5377	396	18	.	.	PUNCT
ap-5377	396	19	schizophrenia	schizophrenia	PROPN
ap-5377	396	20	detection	detection	NOUN
ap-5377	396	21	and	and	CCONJ
ap-5377	396	22	classification	classification	NOUN
ap-5377	396	23	by	by	ADP
ap-5377	396	24	advanced	advanced	ADJ
ap-5377	396	25	analysis	analysis	NOUN
ap-5377	396	26	of	of	ADP
ap-5377	396	27	eeg	eeg	NOUN
ap-5377	396	28	recordings	recording	NOUN
ap-5377	396	29	using	use	VERB
ap-5377	396	30	a	a	DET
ap-5377	396	31	single	single	ADJ
ap-5377	396	32	electrode	electrode	NOUN
ap-5377	396	33	approach	approach	NOUN
ap-5377	396	34	.	.	PUNCT
ap-5377	397	1	plos	plos	PROPN
ap-5377	397	2	one	one	NUM
ap-5377	397	3	10(4	10(4	NUM
ap-5377	397	4	)	)	PUNCT
ap-5377	397	5	,	,	PUNCT
ap-5377	397	6	2015	2015	NUM
ap-5377	397	7	-	-	SYM
ap-5377	397	8	4	4	NUM
ap-5377	397	9	-	-	SYM
ap-5377	397	10	2	2	NUM
ap-5377	397	11	.	.	PUNCT
ap-5377	397	12	doi:10.1371	doi:10.1371	PROPN
ap-5377	397	13	/	/	SYM
ap-5377	398	1	journal.pone.0123033	journal.pone.0123033	PROPN
ap-5377	398	2	.	.	PUNCT
ap-5377	399	1	[	[	X
ap-5377	399	2	2	2	X
ap-5377	399	3	]	]	PUNCT
ap-5377	399	4	s.	s.	PROPN
ap-5377	399	5	j.	j.	PROPN
ap-5377	399	6	m.	m.	PROPN
ap-5377	399	7	smith	smith	PROPN
ap-5377	399	8	.	.	PUNCT
ap-5377	399	9	eeg	eeg	PROPN
ap-5377	399	10	in	in	ADP
ap-5377	399	11	the	the	DET
ap-5377	399	12	diagnosis	diagnosis	NOUN
ap-5377	399	13	,	,	PUNCT
ap-5377	399	14	classification	classification	NOUN
ap-5377	399	15	,	,	PUNCT
ap-5377	399	16	and	and	CCONJ
ap-5377	399	17	management	management	NOUN
ap-5377	399	18	of	of	ADP
ap-5377	399	19	patients	patient	NOUN
ap-5377	399	20	with	with	ADP
ap-5377	399	21	epilepsy	epilepsy	PROPN
ap-5377	399	22	.	.	PUNCT
ap-5377	400	1	journal	journal	PROPN
ap-5377	400	2	of	of	ADP
ap-5377	400	3	neurology	neurology	NOUN
ap-5377	400	4	,	,	PUNCT
ap-5377	400	5	neurosurgery	neurosurgery	NOUN
ap-5377	400	6	and	and	CCONJ
ap-5377	400	7	psychiatry	psychiatry	NOUN
ap-5377	400	8	76	76	NUM
ap-5377	400	9	:	:	PUNCT
ap-5377	400	10	ii2	ii2	PROPN
ap-5377	400	11	–	–	PUNCT
ap-5377	400	12	ii7	ii7	NOUN
ap-5377	400	13	,	,	PUNCT
ap-5377	400	14	2005	2005	NUM
ap-5377	400	15	-	-	SYM
ap-5377	400	16	06	06	NUM
ap-5377	400	17	-	-	PUNCT
ap-5377	400	18	01	01	NUM
ap-5377	400	19	.	.	PUNCT
ap-5377	401	1	doi:10.1136	doi:10.1136	PROPN
ap-5377	401	2	/	/	SYM
ap-5377	401	3	jnnp.2005.069245	jnnp.2005.069245	PROPN
ap-5377	401	4	.	.	PUNCT
ap-5377	402	1	[	[	X
ap-5377	402	2	3	3	X
ap-5377	402	3	]	]	X
ap-5377	402	4	k.	k.	PROPN
ap-5377	402	5	khan	khan	PROPN
ap-5377	402	6	,	,	PUNCT
ap-5377	402	7	s.	s.	PROPN
ap-5377	402	8	u.	u.	PROPN
ap-5377	402	9	rehman	rehman	PROPN
ap-5377	402	10	,	,	PUNCT
ap-5377	402	11	k.	k.	PROPN
ap-5377	402	12	aziz	aziz	PROPN
ap-5377	402	13	,	,	PUNCT
ap-5377	403	1	et	et	PROPN
ap-5377	403	2	al	al	PROPN
ap-5377	403	3	.	.	PROPN
ap-5377	403	4	dbscan	dbscan	PROPN
ap-5377	403	5	:	:	PUNCT
ap-5377	404	1	past	past	ADJ
ap-5377	404	2	,	,	PUNCT
ap-5377	404	3	present	present	ADJ
ap-5377	404	4	and	and	CCONJ
ap-5377	404	5	future	future	ADJ
ap-5377	404	6	.	.	PUNCT
ap-5377	405	1	in	in	ADP
ap-5377	405	2	applications	application	NOUN
ap-5377	405	3	of	of	ADP
ap-5377	405	4	digital	digital	ADJ
ap-5377	405	5	information	information	NOUN
ap-5377	405	6	and	and	CCONJ
ap-5377	405	7	web	web	NOUN
ap-5377	405	8	technologies	technology	NOUN
ap-5377	405	9	(	(	PUNCT
ap-5377	405	10	icadiwt	icadiwt	NOUN
ap-5377	405	11	)	)	PUNCT
ap-5377	405	12	,	,	PUNCT
ap-5377	405	13	vol	vol	NOUN
ap-5377	405	14	.	.	PROPN
ap-5377	405	15	5	5	NUM
ap-5377	405	16	,	,	PUNCT
ap-5377	405	17	pp	pp	ADJ
ap-5377	405	18	.	.	PUNCT
ap-5377	406	1	232–238	232–238	NUM
ap-5377	406	2	.	.	X
ap-5377	406	3	ieee	ieee	NOUN
ap-5377	406	4	,	,	PUNCT
ap-5377	406	5	2014	2014	NUM
ap-5377	406	6	.	.	PUNCT
ap-5377	407	1	doi:10.1109	doi:10.1109	VERB
ap-5377	407	2	/	/	SYM
ap-5377	407	3	icadiwt.2014.6814687	icadiwt.2014.6814687	NOUN
ap-5377	407	4	.	.	PUNCT
ap-5377	408	1	[	[	X
ap-5377	408	2	4	4	NUM
ap-5377	408	3	]	]	PUNCT
ap-5377	408	4	a.	a.	NOUN
ap-5377	408	5	hinneburg	hinneburg	PROPN
ap-5377	408	6	,	,	PUNCT
ap-5377	408	7	d.	d.	PROPN
ap-5377	408	8	a.	a.	NOUN
ap-5377	408	9	keim	keim	PROPN
ap-5377	408	10	.	.	PUNCT
ap-5377	409	1	a	a	DET
ap-5377	409	2	general	general	ADJ
ap-5377	409	3	approach	approach	NOUN
ap-5377	409	4	to	to	ADP
ap-5377	409	5	clustering	cluster	VERB
ap-5377	409	6	in	in	ADP
ap-5377	409	7	large	large	ADJ
ap-5377	409	8	databases	database	NOUN
ap-5377	409	9	with	with	ADP
ap-5377	409	10	noise	noise	NOUN
ap-5377	409	11	.	.	PUNCT
ap-5377	410	1	knowledge	knowledge	NOUN
ap-5377	410	2	and	and	CCONJ
ap-5377	410	3	information	information	NOUN
ap-5377	410	4	systems	system	NOUN
ap-5377	410	5	5(4):387–415	5(4):387–415	NOUN
ap-5377	410	6	,	,	PUNCT
ap-5377	410	7	2003	2003	NUM
ap-5377	410	8	.	.	PUNCT
ap-5377	411	1	doi:10.1007	doi:10.1007	VERB
ap-5377	411	2	/	/	SYM
ap-5377	411	3	s10115	s10115	PROPN
ap-5377	411	4	-	-	PUNCT
ap-5377	411	5	003	003	NUM
ap-5377	411	6	-	-	PUNCT
ap-5377	411	7	0086	0086	NUM
ap-5377	411	8	-	-	PUNCT
ap-5377	411	9	9	9	NUM
ap-5377	411	10	.	.	PUNCT
ap-5377	412	1	[	[	X
ap-5377	412	2	5	5	NUM
ap-5377	412	3	]	]	PUNCT
ap-5377	412	4	r.	r.	PROPN
ap-5377	412	5	sharma	sharma	PROPN
ap-5377	412	6	,	,	PUNCT
ap-5377	412	7	r.	r.	PROPN
ap-5377	412	8	b.	b.	PROPN
ap-5377	412	9	pachori	pachori	PROPN
ap-5377	412	10	.	.	PUNCT
ap-5377	413	1	classification	classification	NOUN
ap-5377	413	2	of	of	ADP
ap-5377	413	3	epileptic	epileptic	ADJ
ap-5377	413	4	seizures	seizure	NOUN
ap-5377	413	5	in	in	ADP
ap-5377	413	6	eeg	eeg	NOUN
ap-5377	413	7	signals	signal	NOUN
ap-5377	413	8	based	base	VERB
ap-5377	413	9	on	on	ADP
ap-5377	413	10	phase	phase	NOUN
ap-5377	413	11	space	space	NOUN
ap-5377	413	12	representation	representation	NOUN
ap-5377	413	13	of	of	ADP
ap-5377	413	14	intrinsic	intrinsic	ADJ
ap-5377	413	15	mode	mode	NOUN
ap-5377	413	16	functions	function	NOUN
ap-5377	413	17	.	.	PUNCT
ap-5377	414	1	expert	expert	NOUN
ap-5377	414	2	systems	system	NOUN
ap-5377	414	3	with	with	ADP
ap-5377	414	4	applications	application	NOUN
ap-5377	414	5	42(3):1106–1117	42(3):1106–1117	NUM
ap-5377	414	6	,	,	PUNCT
ap-5377	414	7	2015	2015	NUM
ap-5377	414	8	.	.	PUNCT
ap-5377	415	1	doi:10.1016	doi:10.1016	PROPN
ap-5377	415	2	/	/	SYM
ap-5377	415	3	j.eswa.2014.08.030	j.eswa.2014.08.030	PROPN
ap-5377	415	4	.	.	PUNCT
ap-5377	416	1	[	[	X
ap-5377	416	2	6	6	NUM
ap-5377	416	3	]	]	X
ap-5377	416	4	u.	u.	PROPN
ap-5377	416	5	r.	r.	PROPN
ap-5377	416	6	acharya	acharya	PROPN
ap-5377	416	7	,	,	PUNCT
ap-5377	416	8	h.	h.	PROPN
ap-5377	416	9	fujita	fujita	PROPN
ap-5377	416	10	,	,	PUNCT
ap-5377	416	11	v.	v.	PROPN
ap-5377	416	12	k.	k.	PROPN
ap-5377	416	13	sudarshan	sudarshan	PROPN
ap-5377	416	14	,	,	PUNCT
ap-5377	416	15	et	et	PROPN
ap-5377	416	16	al	al	PROPN
ap-5377	416	17	.	.	PUNCT
ap-5377	416	18	application	application	NOUN
ap-5377	416	19	of	of	ADP
ap-5377	416	20	entropies	entropy	NOUN
ap-5377	416	21	for	for	ADP
ap-5377	416	22	automated	automated	ADJ
ap-5377	416	23	diagnosis	diagnosis	NOUN
ap-5377	416	24	of	of	ADP
ap-5377	416	25	epilepsy	epilepsy	NOUN
ap-5377	416	26	using	use	VERB
ap-5377	416	27	eeg	eeg	NOUN
ap-5377	416	28	signals	signal	NOUN
ap-5377	416	29	.	.	PUNCT
ap-5377	417	1	knowledge	knowledge	NOUN
ap-5377	417	2	-	-	PUNCT
ap-5377	417	3	based	base	VERB
ap-5377	417	4	systems	system	NOUN
ap-5377	417	5	88:85–96	88:85–96	NUM
ap-5377	417	6	,	,	PUNCT
ap-5377	417	7	2015	2015	NUM
ap-5377	417	8	.	.	PUNCT
ap-5377	418	1	doi:10.1016	doi:10.1016	PROPN
ap-5377	418	2	/	/	SYM
ap-5377	418	3	j.knosys.2015.08.004	j.knosys.2015.08.004	PROPN
ap-5377	418	4	.	.	PUNCT
ap-5377	419	1	[	[	X
ap-5377	419	2	7	7	X
ap-5377	419	3	]	]	X
ap-5377	419	4	f.	f.	PROPN
ap-5377	419	5	lotte	lotte	PROPN
ap-5377	419	6	,	,	PUNCT
ap-5377	419	7	m.	m.	NOUN
ap-5377	419	8	congedo	congedo	PROPN
ap-5377	419	9	,	,	PUNCT
ap-5377	419	10	a.	a.	PROPN
ap-5377	419	11	lecuyer	lecuyer	PROPN
ap-5377	419	12	,	,	PUNCT
ap-5377	419	13	et	et	PROPN
ap-5377	419	14	al	al	PROPN
ap-5377	419	15	.	.	PUNCT
ap-5377	420	1	a	a	DET
ap-5377	420	2	review	review	NOUN
ap-5377	420	3	of	of	ADP
ap-5377	420	4	classification	classification	NOUN
ap-5377	420	5	algorithms	algorithm	NOUN
ap-5377	420	6	for	for	ADP
ap-5377	420	7	eeg	eeg	NOUN
ap-5377	420	8	based	base	VERB
ap-5377	420	9	brain	brain	NOUN
ap-5377	420	10	computer	computer	NOUN
ap-5377	420	11	interfaces	interface	NOUN
ap-5377	420	12	.	.	PUNCT
ap-5377	421	1	journal	journal	NOUN
ap-5377	421	2	of	of	ADP
ap-5377	421	3	neural	neural	ADJ
ap-5377	421	4	engineering	engineering	NOUN
ap-5377	421	5	4(2):r1	4(2):r1	NOUN
ap-5377	421	6	–	–	PUNCT
ap-5377	421	7	r13	r13	NOUN
ap-5377	421	8	,	,	PUNCT
ap-5377	421	9	2007	2007	NUM
ap-5377	421	10	-	-	SYM
ap-5377	421	11	06	06	NUM
ap-5377	421	12	-	-	PUNCT
ap-5377	421	13	01	01	NUM
ap-5377	421	14	.	.	PUNCT
ap-5377	422	1	doi:10.1088/1741	doi:10.1088/1741	NOUN
ap-5377	422	2	-	-	PUNCT
ap-5377	422	3	2560/4/2	2560/4/2	NUM
ap-5377	422	4	/	/	SYM
ap-5377	422	5	r01	r01	NOUN
ap-5377	422	6	.	.	PUNCT
ap-5377	423	1	[	[	X
ap-5377	423	2	8	8	NUM
ap-5377	423	3	]	]	X
ap-5377	423	4	i.	i.	PROPN
ap-5377	423	5	mporas	mporas	PROPN
ap-5377	423	6	,	,	PUNCT
ap-5377	423	7	a.	a.	NOUN
ap-5377	423	8	efstathiou	efstathiou	PROPN
ap-5377	423	9	,	,	PUNCT
ap-5377	423	10	v.	v.	ADP
ap-5377	423	11	megalooikonomou	megalooikonomou	NOUN
ap-5377	423	12	.	.	PUNCT
ap-5377	424	1	sleep	sleep	VERB
ap-5377	424	2	stages	stage	NOUN
ap-5377	424	3	classification	classification	NOUN
ap-5377	424	4	from	from	ADP
ap-5377	424	5	electroencephalographic	electroencephalographic	ADJ
ap-5377	424	6	signals	signal	NOUN
ap-5377	424	7	based	base	VERB
ap-5377	424	8	on	on	ADP
ap-5377	424	9	unsupervised	unsupervised	ADJ
ap-5377	424	10	feature	feature	NOUN
ap-5377	424	11	space	space	NOUN
ap-5377	424	12	clustering	cluster	VERB
ap-5377	424	13	.	.	PUNCT
ap-5377	425	1	in	in	ADP
ap-5377	425	2	brain	brain	NOUN
ap-5377	425	3	informatics	informatic	NOUN
ap-5377	425	4	and	and	CCONJ
ap-5377	425	5	health	health	NOUN
ap-5377	425	6	,	,	PUNCT
ap-5377	425	7	pp	pp	ADJ
ap-5377	425	8	.	.	PUNCT
ap-5377	426	1	77–85	77–85	X
ap-5377	426	2	.	.	PUNCT
ap-5377	427	1	springer	springer	NOUN
ap-5377	427	2	international	international	ADJ
ap-5377	427	3	publishing	publishing	NOUN
ap-5377	427	4	,	,	PUNCT
ap-5377	427	5	cham	cham	NOUN
ap-5377	427	6	,	,	PUNCT
ap-5377	427	7	2015	2015	NUM
ap-5377	427	8	.	.	PUNCT
ap-5377	428	1	doi:10.1007/978	doi:10.1007/978	NOUN
ap-5377	428	2	-	-	PUNCT
ap-5377	428	3	3	3	NUM
ap-5377	428	4	-	-	NUM
ap-5377	428	5	319	319	NUM
ap-5377	428	6	-	-	PUNCT
ap-5377	428	7	23344	23344	NUM
ap-5377	428	8	-	-	SYM
ap-5377	428	9	4_8	4_8	NUM
ap-5377	428	10	.	.	PUNCT
ap-5377	429	1	[	[	X
ap-5377	429	2	9	9	NUM
ap-5377	429	3	]	]	PUNCT
ap-5377	429	4	c.	c.	PROPN
ap-5377	429	5	r.	r.	PROPN
ap-5377	429	6	azevedo	azevedo	PROPN
ap-5377	429	7	,	,	PUNCT
ap-5377	429	8	c.	c.	PROPN
ap-5377	429	9	f.	f.	PROPN
ap-5377	429	10	boos	boos	PROPN
ap-5377	429	11	,	,	PUNCT
ap-5377	429	12	f.	f.	PROPN
ap-5377	429	13	m.	m.	PROPN
ap-5377	429	14	de	de	PROPN
ap-5377	429	15	azevedo	azevedo	PROPN
ap-5377	429	16	.	.	PUNCT
ap-5377	430	1	classification	classification	NOUN
ap-5377	430	2	of	of	ADP
ap-5377	430	3	epileptiform	epileptiform	NOUN
ap-5377	430	4	events	event	NOUN
ap-5377	430	5	in	in	ADP
ap-5377	430	6	eeg	eeg	NOUN
ap-5377	430	7	signals	signal	NOUN
ap-5377	430	8	using	use	VERB
ap-5377	430	9	neural	neural	ADJ
ap-5377	430	10	classifier	classifier	NOUN
ap-5377	430	11	based	base	VERB
ap-5377	430	12	on	on	ADP
ap-5377	430	13	som	som	PROPN
ap-5377	430	14	.	.	PUNCT
ap-5377	431	1	in	in	ADP
ap-5377	431	2	2015	2015	NUM
ap-5377	431	3	international	international	ADJ
ap-5377	431	4	conference	conference	NOUN
ap-5377	431	5	on	on	ADP
ap-5377	431	6	electrical	electrical	ADJ
ap-5377	431	7	engineering	engineering	NOUN
ap-5377	431	8	and	and	CCONJ
ap-5377	431	9	information	information	NOUN
ap-5377	431	10	communication	communication	NOUN
ap-5377	431	11	technology	technology	NOUN
ap-5377	431	12	(	(	PUNCT
ap-5377	431	13	iceeict	iceeict	PROPN
ap-5377	431	14	)	)	PUNCT
ap-5377	431	15	,	,	PUNCT
ap-5377	431	16	pp	pp	ADP
ap-5377	431	17	.	.	PUNCT
ap-5377	432	1	1–5	1–5	X
ap-5377	432	2	.	.	X
ap-5377	432	3	ieee	ieee	PROPN
ap-5377	432	4	,	,	PUNCT
ap-5377	432	5	2015	2015	NUM
ap-5377	432	6	.	.	PUNCT
ap-5377	433	1	doi:10.1109	doi:10.1109	VERB
ap-5377	433	2	/	/	SYM
ap-5377	433	3	iceeict.2015.7307340	iceeict.2015.7307340	NUM
ap-5377	433	4	.	.	PUNCT
ap-5377	434	1	[	[	X
ap-5377	434	2	10	10	NUM
ap-5377	434	3	]	]	X
ap-5377	434	4	s.	s.	PROPN
ap-5377	434	5	belhadj	belhadj	PROPN
ap-5377	434	6	,	,	PUNCT
ap-5377	434	7	a.	a.	NOUN
ap-5377	434	8	attia	attia	PROPN
ap-5377	434	9	,	,	PUNCT
ap-5377	434	10	a.	a.	PROPN
ap-5377	434	11	b.	b.	PROPN
ap-5377	434	12	adnane	adnane	PROPN
ap-5377	434	13	,	,	PUNCT
ap-5377	434	14	et	et	PROPN
ap-5377	434	15	al	al	PROPN
ap-5377	434	16	.	.	PROPN
ap-5377	435	1	whole	whole	ADJ
ap-5377	435	2	brain	brain	NOUN
ap-5377	435	3	epileptic	epileptic	ADJ
ap-5377	435	4	seizure	seizure	NOUN
ap-5377	435	5	detection	detection	NOUN
ap-5377	435	6	using	use	VERB
ap-5377	435	7	unsupervised	unsupervised	ADJ
ap-5377	435	8	classification	classification	NOUN
ap-5377	435	9	.	.	PUNCT
ap-5377	436	1	in	in	ADP
ap-5377	436	2	2016	2016	NUM
ap-5377	436	3	8th	8th	ADJ
ap-5377	436	4	international	international	ADJ
ap-5377	436	5	conference	conference	NOUN
ap-5377	436	6	on	on	ADP
ap-5377	436	7	modelling	modelling	NOUN
ap-5377	436	8	,	,	PUNCT
ap-5377	436	9	identification	identification	NOUN
ap-5377	436	10	and	and	CCONJ
ap-5377	436	11	control	control	NOUN
ap-5377	436	12	(	(	PUNCT
ap-5377	436	13	icmic	icmic	ADJ
ap-5377	436	14	)	)	PUNCT
ap-5377	436	15	,	,	PUNCT
ap-5377	436	16	pp	pp	PROPN
ap-5377	436	17	.	.	PUNCT
ap-5377	437	1	977	977	NUM
ap-5377	437	2	–	–	PUNCT
ap-5377	437	3	982	982	NUM
ap-5377	437	4	.	.	PUNCT
ap-5377	437	5	ieee	ieee	PROPN
ap-5377	437	6	,	,	PUNCT
ap-5377	437	7	2016	2016	NUM
ap-5377	437	8	.	.	PUNCT
ap-5377	438	1	doi:10.1109	doi:10.1109	PROPN
ap-5377	438	2	/	/	SYM
ap-5377	438	3	icmic.2016.7804256	icmic.2016.7804256	PROPN
ap-5377	438	4	.	.	PUNCT
ap-5377	439	1	[	[	X
ap-5377	439	2	11	11	NUM
ap-5377	439	3	]	]	PUNCT
ap-5377	439	4	j.	j.	PROPN
ap-5377	439	5	m.	m.	PROPN
ap-5377	439	6	del	del	PROPN
ap-5377	439	7	rincon	rincon	PROPN
ap-5377	439	8	,	,	PUNCT
ap-5377	439	9	m.	m.	PROPN
ap-5377	439	10	j.	j.	PROPN
ap-5377	439	11	santofimia	santofimia	PROPN
ap-5377	439	12	,	,	PUNCT
ap-5377	439	13	x.	x.	PROPN
ap-5377	439	14	del	del	PROPN
ap-5377	439	15	toro	toro	PROPN
ap-5377	439	16	,	,	PUNCT
ap-5377	439	17	et	et	PROPN
ap-5377	439	18	al	al	PROPN
ap-5377	439	19	.	.	PUNCT
ap-5377	440	1	non	non	ADJ
ap-5377	440	2	-	-	ADJ
ap-5377	440	3	linear	linear	ADJ
ap-5377	440	4	classifiers	classifier	NOUN
ap-5377	440	5	applied	apply	VERB
ap-5377	440	6	to	to	ADP
ap-5377	440	7	eeg	eeg	NOUN
ap-5377	440	8	analysis	analysis	NOUN
ap-5377	440	9	for	for	ADP
ap-5377	440	10	epilepsy	epilepsy	NOUN
ap-5377	440	11	seizure	seizure	NOUN
ap-5377	440	12	detection	detection	NOUN
ap-5377	440	13	.	.	PUNCT
ap-5377	441	1	expert	expert	NOUN
ap-5377	441	2	systems	system	NOUN
ap-5377	441	3	with	with	ADP
ap-5377	441	4	applications	application	NOUN
ap-5377	441	5	86:99–112	86:99–112	NUM
ap-5377	441	6	,	,	PUNCT
ap-5377	441	7	2017	2017	NUM
ap-5377	441	8	.	.	PUNCT
ap-5377	442	1	doi:10.1016	doi:10.1016	PROPN
ap-5377	442	2	/	/	SYM
ap-5377	442	3	j.eswa.2017.05.052	j.eswa.2017.05.052	PROPN
ap-5377	442	4	.	.	PUNCT
ap-5377	443	1	[	[	X
ap-5377	443	2	12	12	NUM
ap-5377	443	3	]	]	X
ap-5377	443	4	o.	o.	NOUN
ap-5377	443	5	smart	smart	PROPN
ap-5377	443	6	,	,	PUNCT
ap-5377	443	7	m.	m.	NOUN
ap-5377	443	8	chen	chen	PROPN
ap-5377	443	9	.	.	PUNCT
ap-5377	444	1	semi	semi	ADJ
ap-5377	444	2	-	-	ADJ
ap-5377	444	3	automated	automated	ADJ
ap-5377	444	4	patient	patient	NOUN
ap-5377	444	5	-	-	PUNCT
ap-5377	444	6	specific	specific	ADJ
ap-5377	444	7	scalp	scalp	NOUN
ap-5377	444	8	eeg	eeg	NOUN
ap-5377	444	9	seizure	seizure	NOUN
ap-5377	444	10	detection	detection	NOUN
ap-5377	444	11	with	with	ADP
ap-5377	444	12	unsupervised	unsupervised	ADJ
ap-5377	444	13	machine	machine	NOUN
ap-5377	444	14	learning	learning	NOUN
ap-5377	444	15	.	.	PUNCT
ap-5377	445	1	in	in	ADP
ap-5377	445	2	2015	2015	NUM
ap-5377	445	3	ieee	ieee	NOUN
ap-5377	445	4	conference	conference	NOUN
ap-5377	445	5	on	on	ADP
ap-5377	445	6	computational	computational	ADJ
ap-5377	445	7	intelligence	intelligence	NOUN
ap-5377	445	8	in	in	ADP
ap-5377	445	9	bioinformatics	bioinformatics	NOUN
ap-5377	445	10	and	and	CCONJ
ap-5377	445	11	computational	computational	ADJ
ap-5377	445	12	biology	biology	NOUN
ap-5377	445	13	(	(	PUNCT
ap-5377	445	14	cibcb	cibcb	NOUN
ap-5377	445	15	)	)	PUNCT
ap-5377	445	16	,	,	PUNCT
ap-5377	445	17	pp	pp	PROPN
ap-5377	445	18	.	.	PUNCT
ap-5377	446	1	1–7	1–7	X
ap-5377	446	2	.	.	PUNCT
ap-5377	446	3	ieee	ieee	PROPN
ap-5377	446	4	,	,	PUNCT
ap-5377	446	5	2015	2015	NUM
ap-5377	446	6	.	.	PUNCT
ap-5377	447	1	doi:10.1109	doi:10.1109	VERB
ap-5377	447	2	/	/	SYM
ap-5377	447	3	cibcb.2015.7300286	cibcb.2015.7300286	NOUN
ap-5377	447	4	.	.	PUNCT
ap-5377	448	1	[	[	X
ap-5377	448	2	13	13	NUM
ap-5377	448	3	]	]	X
ap-5377	448	4	h.	h.	PROPN
ap-5377	448	5	rajaguru	rajaguru	PROPN
ap-5377	448	6	,	,	PUNCT
ap-5377	448	7	s.	s.	PROPN
ap-5377	448	8	k.	k.	PROPN
ap-5377	448	9	prabhakar	prabhakar	PROPN
ap-5377	448	10	.	.	PUNCT
ap-5377	449	1	knn	knn	PROPN
ap-5377	449	2	classifier	classifier	PROPN
ap-5377	449	3	and	and	CCONJ
ap-5377	449	4	k	k	NOUN
ap-5377	449	5	-	-	PUNCT
ap-5377	449	6	means	means	NOUN
ap-5377	449	7	clustering	cluster	VERB
ap-5377	449	8	for	for	ADP
ap-5377	449	9	robust	robust	ADJ
ap-5377	449	10	classification	classification	NOUN
ap-5377	449	11	of	of	ADP
ap-5377	449	12	epilepsy	epilepsy	NOUN
ap-5377	449	13	from	from	ADP
ap-5377	449	14	eeg	eeg	NOUN
ap-5377	449	15	signals	signal	NOUN
ap-5377	449	16	.	.	PUNCT
ap-5377	450	1	a	a	DET
ap-5377	450	2	detailed	detailed	ADJ
ap-5377	450	3	analysis	analysis	NOUN
ap-5377	450	4	.	.	PUNCT
ap-5377	451	1	anchor	anchor	PROPN
ap-5377	451	2	academic	academic	ADJ
ap-5377	451	3	publishing	publishing	NOUN
ap-5377	451	4	,	,	PUNCT
ap-5377	451	5	2017	2017	NUM
ap-5377	451	6	.	.	PUNCT
ap-5377	452	1	[	[	X
ap-5377	452	2	14	14	NUM
ap-5377	452	3	]	]	X
ap-5377	452	4	g.	g.	PROPN
ap-5377	452	5	zhu	zhu	PROPN
ap-5377	452	6	,	,	PUNCT
ap-5377	452	7	y.	y.	PROPN
ap-5377	452	8	li	li	PROPN
ap-5377	452	9	,	,	PUNCT
ap-5377	452	10	p.	p.	PROPN
ap-5377	452	11	wen	wen	PROPN
ap-5377	452	12	,	,	PUNCT
ap-5377	452	13	et	et	PROPN
ap-5377	452	14	al	al	PROPN
ap-5377	452	15	.	.	PROPN
ap-5377	453	1	unsupervised	unsupervised	ADJ
ap-5377	453	2	classification	classification	NOUN
ap-5377	453	3	of	of	ADP
ap-5377	453	4	epileptic	epileptic	ADJ
ap-5377	453	5	eeg	eeg	NOUN
ap-5377	453	6	signals	signal	NOUN
ap-5377	453	7	with	with	ADP
ap-5377	453	8	multi	multi	ADJ
ap-5377	453	9	scale	scale	NOUN
ap-5377	453	10	k	k	NOUN
ap-5377	453	11	-	-	PUNCT
ap-5377	453	12	means	means	NOUN
ap-5377	453	13	algorithm	algorithm	NOUN
ap-5377	453	14	.	.	PUNCT
ap-5377	454	1	in	in	ADP
ap-5377	454	2	brain	brain	NOUN
ap-5377	454	3	and	and	CCONJ
ap-5377	454	4	health	health	NOUN
ap-5377	454	5	informatics	informatic	NOUN
ap-5377	454	6	,	,	PUNCT
ap-5377	454	7	pp	pp	ADP
ap-5377	454	8	.	.	PUNCT
ap-5377	455	1	158–167	158–167	NUM
ap-5377	455	2	.	.	PUNCT
ap-5377	455	3	springer	springer	NOUN
ap-5377	455	4	international	international	ADJ
ap-5377	455	5	publishing	publishing	NOUN
ap-5377	455	6	,	,	PUNCT
ap-5377	455	7	cham	cham	PROPN
ap-5377	455	8	,	,	PUNCT
ap-5377	455	9	2013	2013	NUM
ap-5377	455	10	.	.	PUNCT
ap-5377	456	1	doi:10.1007/978	doi:10.1007/978	ADJ
ap-5377	456	2	-	-	PUNCT
ap-5377	456	3	3	3	NUM
ap-5377	456	4	-	-	NUM
ap-5377	456	5	319	319	NUM
ap-5377	456	6	-	-	PUNCT
ap-5377	456	7	02753	02753	NUM
ap-5377	456	8	-	-	SYM
ap-5377	456	9	1_16	1_16	NUM
ap-5377	456	10	.	.	PUNCT
ap-5377	457	1	[	[	X
ap-5377	457	2	15	15	NUM
ap-5377	457	3	]	]	X
ap-5377	457	4	s.	s.	PROPN
ap-5377	457	5	ghosh	ghosh	PROPN
ap-5377	457	6	-	-	PUNCT
ap-5377	457	7	dastidar	dastidar	PROPN
ap-5377	457	8	,	,	PUNCT
ap-5377	457	9	h.	h.	PROPN
ap-5377	457	10	adeli	adeli	PROPN
ap-5377	457	11	,	,	PUNCT
ap-5377	457	12	n.	n.	PROPN
ap-5377	457	13	dadmehr	dadmehr	PROPN
ap-5377	457	14	.	.	PUNCT
ap-5377	458	1	mixed	mix	VERB
ap-5377	458	2	-	-	PUNCT
ap-5377	458	3	band	band	NOUN
ap-5377	458	4	wavelet	wavelet	NOUN
ap-5377	458	5	-	-	PUNCT
ap-5377	458	6	chaos	chaos	NOUN
ap-5377	458	7	-	-	PUNCT
ap-5377	458	8	neural	neural	ADJ
ap-5377	458	9	network	network	NOUN
ap-5377	458	10	methodology	methodology	NOUN
ap-5377	458	11	for	for	ADP
ap-5377	458	12	epilepsy	epilepsy	NOUN
ap-5377	458	13	and	and	CCONJ
ap-5377	458	14	epileptic	epileptic	ADJ
ap-5377	458	15	seizure	seizure	NOUN
ap-5377	458	16	detection	detection	NOUN
ap-5377	458	17	.	.	PUNCT
ap-5377	459	1	ieee	ieee	NOUN
ap-5377	459	2	transactions	transaction	NOUN
ap-5377	459	3	on	on	ADP
ap-5377	459	4	biomedical	biomedical	ADJ
ap-5377	459	5	engineering	engineering	NOUN
ap-5377	459	6	54(9):1545	54(9):1545	NUM
ap-5377	459	7	–	–	PUNCT
ap-5377	459	8	1551	1551	NUM
ap-5377	459	9	,	,	PUNCT
ap-5377	459	10	2007	2007	NUM
ap-5377	459	11	.	.	PUNCT
ap-5377	460	1	doi:10.1109	doi:10.1109	VERB
ap-5377	460	2	/	/	PUNCT
ap-5377	460	3	tbme.2007.891945	tbme.2007.891945	ADP
ap-5377	460	4	.	.	PUNCT
ap-5377	461	1	[	[	X
ap-5377	461	2	16	16	NUM
ap-5377	461	3	]	]	X
ap-5377	461	4	h.	h.	PROPN
ap-5377	461	5	schaabova	schaabova	PROPN
ap-5377	461	6	,	,	PUNCT
ap-5377	461	7	v.	v.	PROPN
ap-5377	461	8	krajca	krajca	NOUN
ap-5377	461	9	,	,	PUNCT
ap-5377	461	10	v.	v.	PROPN
ap-5377	461	11	sedlmajerova	sedlmajerova	PROPN
ap-5377	461	12	,	,	PUNCT
ap-5377	461	13	et	et	PROPN
ap-5377	461	14	al	al	PROPN
ap-5377	461	15	.	.	PROPN
ap-5377	461	16	supervised	supervised	ADJ
ap-5377	461	17	learning	learning	NOUN
ap-5377	461	18	used	use	VERB
ap-5377	461	19	in	in	ADP
ap-5377	461	20	automatic	automatic	ADJ
ap-5377	461	21	eeg	eeg	NOUN
ap-5377	461	22	graphoelements	graphoelement	NOUN
ap-5377	461	23	classification	classification	NOUN
ap-5377	461	24	.	.	PUNCT
ap-5377	462	1	in	in	ADP
ap-5377	462	2	2015	2015	NUM
ap-5377	462	3	e	e	NOUN
ap-5377	462	4	-	-	NOUN
ap-5377	462	5	health	health	NOUN
ap-5377	462	6	and	and	CCONJ
ap-5377	462	7	bioengineering	bioengineering	NOUN
ap-5377	462	8	conference	conference	NOUN
ap-5377	462	9	(	(	PUNCT
ap-5377	462	10	ehb	ehb	PROPN
ap-5377	462	11	)	)	PUNCT
ap-5377	462	12	,	,	PUNCT
ap-5377	462	13	pp	pp	ADP
ap-5377	462	14	.	.	PUNCT
ap-5377	463	1	1–4	1–4	PROPN
ap-5377	463	2	.	.	PUNCT
ap-5377	463	3	ieee	ieee	PROPN
ap-5377	463	4	,	,	PUNCT
ap-5377	463	5	2015	2015	NUM
ap-5377	463	6	.	.	PUNCT
ap-5377	464	1	doi:10.1109	doi:10.1109	VERB
ap-5377	464	2	/	/	SYM
ap-5377	464	3	ehb.2015.7391470	ehb.2015.7391470	NUM
ap-5377	464	4	.	.	PUNCT
ap-5377	465	1	[	[	X
ap-5377	465	2	17	17	NUM
ap-5377	465	3	]	]	PUNCT
ap-5377	465	4	m.	m.	NOUN
ap-5377	465	5	piorecky	piorecky	PROPN
ap-5377	465	6	,	,	PUNCT
ap-5377	465	7	e.	e.	PROPN
ap-5377	465	8	cerna	cerna	PROPN
ap-5377	465	9	,	,	PUNCT
ap-5377	465	10	v.	v.	PROPN
ap-5377	465	11	piorecka	piorecka	PROPN
ap-5377	465	12	,	,	PUNCT
ap-5377	465	13	et	et	PROPN
ap-5377	465	14	al	al	PROPN
ap-5377	465	15	.	.	PROPN
ap-5377	465	16	simulation	simulation	PROPN
ap-5377	465	17	,	,	PUNCT
ap-5377	465	18	modification	modification	NOUN
ap-5377	465	19	and	and	CCONJ
ap-5377	465	20	dimension	dimension	NOUN
ap-5377	465	21	reduction	reduction	NOUN
ap-5377	465	22	of	of	ADP
ap-5377	465	23	eeg	eeg	NOUN
ap-5377	465	24	feature	feature	NOUN
ap-5377	465	25	space	space	NOUN
ap-5377	465	26	.	.	PUNCT
ap-5377	466	1	in	in	ADP
ap-5377	466	2	world	world	PROPN
ap-5377	466	3	congress	congress	PROPN
ap-5377	466	4	on	on	ADP
ap-5377	466	5	medical	medical	ADJ
ap-5377	466	6	physics	physics	NOUN
ap-5377	466	7	and	and	CCONJ
ap-5377	466	8	biomedical	biomedical	ADJ
ap-5377	466	9	engineering	engineering	NOUN
ap-5377	466	10	2018	2018	NUM
ap-5377	466	11	,	,	PUNCT
ap-5377	466	12	pp	pp	ADJ
ap-5377	466	13	.	.	PUNCT
ap-5377	467	1	425–429	425–429	NUM
ap-5377	467	2	.	.	PUNCT
ap-5377	467	3	springer	springer	PROPN
ap-5377	467	4	singapore	singapore	PROPN
ap-5377	467	5	,	,	PUNCT
ap-5377	467	6	singapore	singapore	PROPN
ap-5377	467	7	,	,	PUNCT
ap-5377	467	8	2019	2019	NUM
ap-5377	467	9	.	.	PUNCT
ap-5377	468	1	doi:10.1007/978	doi:10.1007/978	PROPN
ap-5377	468	2	-	-	PUNCT
ap-5377	468	3	981	981	NUM
ap-5377	468	4	-	-	PUNCT
ap-5377	468	5	10	10	NUM
ap-5377	468	6	-	-	PUNCT
ap-5377	468	7	9038	9038	NUM
ap-5377	468	8	-	-	SYM
ap-5377	468	9	7_80	7_80	NUM
ap-5377	468	10	.	.	PUNCT
ap-5377	469	1	[	[	X
ap-5377	469	2	18	18	NUM
ap-5377	469	3	]	]	X
ap-5377	469	4	e.	e.	PROPN
ap-5377	469	5	niedermeyer	niedermeyer	PROPN
ap-5377	469	6	,	,	PUNCT
ap-5377	469	7	f.	f.	PROPN
ap-5377	469	8	h.	h.	PROPN
ap-5377	469	9	l.	l.	PROPN
ap-5377	469	10	da	da	PROPN
ap-5377	469	11	silva	silva	PROPN
ap-5377	469	12	.	.	PUNCT
ap-5377	470	1	electroencephalography	electroencephalography	NOUN
ap-5377	470	2	,	,	PUNCT
ap-5377	470	3	basic	basic	ADJ
ap-5377	470	4	principles	principle	NOUN
ap-5377	470	5	,	,	PUNCT
ap-5377	470	6	clinical	clinical	ADJ
ap-5377	470	7	applications	application	NOUN
ap-5377	470	8	,	,	PUNCT
ap-5377	470	9	and	and	CCONJ
ap-5377	470	10	related	related	ADJ
ap-5377	470	11	fields	field	NOUN
ap-5377	470	12	.	.	PUNCT
ap-5377	471	1	urban	urban	PROPN
ap-5377	471	2	&	&	CCONJ
ap-5377	471	3	schwarzenberg	schwarzenberg	PROPN
ap-5377	471	4	,	,	PUNCT
ap-5377	471	5	baltimore	baltimore	PROPN
ap-5377	471	6	,	,	PUNCT
ap-5377	471	7	1982	1982	NUM
ap-5377	471	8	.	.	PUNCT
ap-5377	472	1	[	[	X
ap-5377	472	2	19	19	NUM
ap-5377	472	3	]	]	X
ap-5377	472	4	s.	s.	PROPN
ap-5377	472	5	r.	r.	PROPN
ap-5377	472	6	sinha	sinha	PROPN
ap-5377	472	7	,	,	PUNCT
ap-5377	472	8	l.	l.	PROPN
ap-5377	472	9	sullivan	sullivan	PROPN
ap-5377	472	10	,	,	PUNCT
ap-5377	472	11	d.	d.	PROPN
ap-5377	472	12	sabau	sabau	PROPN
ap-5377	472	13	,	,	PUNCT
ap-5377	472	14	et	et	PROPN
ap-5377	472	15	al	al	PROPN
ap-5377	472	16	.	.	PUNCT
ap-5377	472	17	american	american	PROPN
ap-5377	472	18	clinical	clinical	ADJ
ap-5377	472	19	neurophysiology	neurophysiology	NOUN
ap-5377	472	20	society	society	NOUN
ap-5377	472	21	guideline	guideline	NOUN
ap-5377	472	22	1	1	NUM
ap-5377	472	23	.	.	PUNCT
ap-5377	472	24	journal	journal	NOUN
ap-5377	472	25	of	of	ADP
ap-5377	472	26	clinical	clinical	ADJ
ap-5377	472	27	neurophysiology	neurophysiology	NOUN
ap-5377	472	28	33(4):303–307	33(4):303–307	PROPN
ap-5377	472	29	,	,	PUNCT
ap-5377	472	30	2016	2016	NUM
ap-5377	472	31	.	.	PUNCT
ap-5377	473	1	doi:10.1097	doi:10.1097	PROPN
ap-5377	473	2	/	/	SYM
ap-5377	473	3	wnp.0000000000000308	wnp.0000000000000308	PROPN
ap-5377	473	4	.	.	PUNCT
ap-5377	474	1	[	[	X
ap-5377	474	2	20	20	NUM
ap-5377	474	3	]	]	PUNCT
ap-5377	474	4	v.	v.	CCONJ
ap-5377	474	5	krajča	krajča	PROPN
ap-5377	474	6	,	,	PUNCT
ap-5377	474	7	s.	s.	PROPN
ap-5377	474	8	petránek	petránek	PROPN
ap-5377	474	9	,	,	PUNCT
ap-5377	474	10	t.	t.	NOUN
ap-5377	474	11	pietilä	pietilä	NOUN
ap-5377	474	12	,	,	PUNCT
ap-5377	474	13	h.	h.	PROPN
ap-5377	474	14	freay	freay	PROPN
ap-5377	474	15	.	.	PUNCT
ap-5377	475	1	"	"	PUNCT
ap-5377	475	2	wavefinder	wavefinder	NOUN
ap-5377	475	3	"	"	PUNCT
ap-5377	475	4	:	:	PUNCT
ap-5377	475	5	a	a	DET
ap-5377	475	6	new	new	ADJ
ap-5377	475	7	system	system	NOUN
ap-5377	475	8	for	for	ADP
ap-5377	475	9	automatic	automatic	ADJ
ap-5377	475	10	processing	processing	NOUN
ap-5377	475	11	of	of	ADP
ap-5377	475	12	long	long	ADJ
ap-5377	475	13	term	term	NOUN
ap-5377	475	14	eeg	eeg	NOUN
ap-5377	475	15	recording	recording	NOUN
ap-5377	475	16	.	.	PUNCT
ap-5377	476	1	quantitative	quantitative	ADJ
ap-5377	476	2	eeg	eeg	PROPN
ap-5377	476	3	analysis	analysis	NOUN
ap-5377	476	4	-	-	PUNCT
ap-5377	476	5	clinical	clinical	ADJ
ap-5377	476	6	utility	utility	NOUN
ap-5377	476	7	and	and	CCONJ
ap-5377	476	8	new	new	ADJ
ap-5377	476	9	methods	method	NOUN
ap-5377	476	10	pp	pp	X
ap-5377	476	11	.	.	PUNCT
ap-5377	477	1	103–106	103–106	NUM
ap-5377	477	2	,	,	PUNCT
ap-5377	477	3	1993	1993	NUM
ap-5377	477	4	.	.	PUNCT
ap-5377	478	1	[	[	X
ap-5377	478	2	21	21	NUM
ap-5377	478	3	]	]	X
ap-5377	478	4	d.	d.	PROPN
ap-5377	478	5	kala	kala	PROPN
ap-5377	478	6	,	,	PUNCT
ap-5377	478	7	v.	v.	PROPN
ap-5377	478	8	krajca	krajca	PROPN
ap-5377	478	9	,	,	PUNCT
ap-5377	478	10	h.	h.	PROPN
ap-5377	478	11	schaabova	schaabova	PROPN
ap-5377	478	12	,	,	PUNCT
ap-5377	478	13	et	et	PROPN
ap-5377	478	14	al	al	PROPN
ap-5377	478	15	.	.	PUNCT
ap-5377	478	16	optimal	optimal	ADJ
ap-5377	478	17	parameters	parameter	NOUN
ap-5377	478	18	of	of	ADP
ap-5377	478	19	adaptive	adaptive	ADJ
ap-5377	478	20	segmentation	segmentation	NOUN
ap-5377	478	21	for	for	ADP
ap-5377	478	22	epileptic	epileptic	ADJ
ap-5377	478	23	graphoelements	graphoelement	NOUN
ap-5377	478	24	recognition	recognition	NOUN
ap-5377	478	25	.	.	PUNCT
ap-5377	479	1	radioengineering	radioengineere	VERB
ap-5377	479	2	26(1):323–329	26(1):323–329	PROPN
ap-5377	479	3	,	,	PUNCT
ap-5377	479	4	2017	2017	NUM
ap-5377	479	5	-	-	SYM
ap-5377	479	6	04	04	NUM
ap-5377	479	7	-	-	PUNCT
ap-5377	479	8	14	14	NUM
ap-5377	479	9	.	.	PUNCT
ap-5377	479	10	doi:10.13164	doi:10.13164	NOUN
ap-5377	479	11	/	/	SYM
ap-5377	479	12	re.2017.0323	re.2017.0323	NOUN
ap-5377	479	13	.	.	PUNCT
ap-5377	480	1	[	[	X
ap-5377	480	2	22	22	NUM
ap-5377	480	3	]	]	PUNCT
ap-5377	480	4	v.	v.	CCONJ
ap-5377	480	5	krajča	krajča	PROPN
ap-5377	480	6	,	,	PUNCT
ap-5377	480	7	j.	j.	PROPN
ap-5377	480	8	mohylová	mohylová	PROPN
ap-5377	480	9	.	.	PUNCT
ap-5377	481	1	číslicové	číslicové	PROPN
ap-5377	481	2	zpracování	zpracování	PROPN
ap-5377	481	3	neurofyziologických	neurofyziologických	PROPN
ap-5377	481	4	signálů	signálů	PROPN
ap-5377	481	5	.	.	PUNCT
ap-5377	482	1	české	české	PROPN
ap-5377	482	2	vysoké	vysoké	PROPN
ap-5377	482	3	učení	učení	PROPN
ap-5377	482	4	technické	technické	NOUN
ap-5377	482	5	v	v	ADP
ap-5377	482	6	praze	praze	NOUN
ap-5377	482	7	,	,	PUNCT
ap-5377	482	8	2011	2011	NUM
ap-5377	482	9	.	.	PUNCT
ap-5377	483	1	[	[	X
ap-5377	483	2	23	23	NUM
ap-5377	483	3	]	]	PUNCT
ap-5377	483	4	s.	s.	PROPN
ap-5377	483	5	t.-b	t.-b	PROPN
ap-5377	483	6	.	.	PUNCT
ap-5377	484	1	hamida	hamida	PROPN
ap-5377	484	2	,	,	PUNCT
ap-5377	484	3	b.	b.	PROPN
ap-5377	484	4	ahmed	ahmed	PROPN
ap-5377	484	5	,	,	PUNCT
ap-5377	484	6	t.	t.	PROPN
ap-5377	484	7	penzel	penzel	PROPN
ap-5377	484	8	.	.	PUNCT
ap-5377	485	1	a	a	DET
ap-5377	485	2	novel	novel	ADJ
ap-5377	485	3	insomnia	insomnia	NOUN
ap-5377	485	4	identification	identification	NOUN
ap-5377	485	5	method	method	NOUN
ap-5377	485	6	based	base	VERB
ap-5377	485	7	on	on	ADP
ap-5377	485	8	hjorth	hjorth	NOUN
ap-5377	485	9	parameters	parameter	NOUN
ap-5377	485	10	.	.	PUNCT
ap-5377	486	1	in	in	ADP
ap-5377	486	2	2015	2015	NUM
ap-5377	486	3	ieee	ieee	NOUN
ap-5377	486	4	international	international	ADJ
ap-5377	486	5	symposium	symposium	NOUN
ap-5377	486	6	on	on	ADP
ap-5377	486	7	signal	signal	NOUN
ap-5377	486	8	processing	processing	NOUN
ap-5377	486	9	and	and	CCONJ
ap-5377	486	10	information	information	NOUN
ap-5377	486	11	technology	technology	NOUN
ap-5377	486	12	(	(	PUNCT
ap-5377	486	13	isspit	isspit	ADJ
ap-5377	486	14	)	)	PUNCT
ap-5377	486	15	,	,	PUNCT
ap-5377	486	16	pp	pp	ADP
ap-5377	486	17	.	.	PUNCT
ap-5377	487	1	548–552	548–552	NUM
ap-5377	487	2	.	.	PUNCT
ap-5377	487	3	ieee	ieee	NOUN
ap-5377	487	4	,	,	PUNCT
ap-5377	487	5	2015	2015	NUM
ap-5377	487	6	.	.	PUNCT
ap-5377	488	1	doi:10.1109	doi:10.1109	VERB
ap-5377	488	2	/	/	SYM
ap-5377	488	3	isspit.2015.7394397	isspit.2015.7394397	NUM
ap-5377	488	4	.	.	PUNCT
ap-5377	489	1	[	[	X
ap-5377	489	2	24	24	NUM
ap-5377	489	3	]	]	X
ap-5377	489	4	h.	h.	PROPN
ap-5377	489	5	qu	qu	PROPN
ap-5377	489	6	,	,	PUNCT
ap-5377	489	7	j.	j.	PROPN
ap-5377	489	8	gotman	gotman	PROPN
ap-5377	489	9	.	.	PUNCT
ap-5377	490	1	a	a	DET
ap-5377	490	2	patient	patient	NOUN
ap-5377	490	3	-	-	PUNCT
ap-5377	490	4	specific	specific	ADJ
ap-5377	490	5	algorithm	algorithm	NOUN
ap-5377	490	6	for	for	ADP
ap-5377	490	7	the	the	DET
ap-5377	490	8	detection	detection	NOUN
ap-5377	490	9	of	of	ADP
ap-5377	490	10	seizure	seizure	NOUN
ap-5377	490	11	onset	onset	NOUN
ap-5377	490	12	in	in	ADP
ap-5377	490	13	long	long	ADJ
ap-5377	490	14	-	-	PUNCT
ap-5377	490	15	term	term	NOUN
ap-5377	490	16	eeg	eeg	NOUN
ap-5377	490	17	monitoring	monitoring	NOUN
ap-5377	490	18	.	.	PUNCT
ap-5377	491	1	ieee	ieee	NOUN
ap-5377	491	2	transactions	transaction	NOUN
ap-5377	491	3	on	on	ADP
ap-5377	491	4	biomedical	biomedical	ADJ
ap-5377	491	5	engineering	engineering	NOUN
ap-5377	491	6	44(2):115–122	44(2):115–122	NOUN
ap-5377	491	7	,	,	PUNCT
ap-5377	491	8	1997	1997	NUM
ap-5377	491	9	.	.	PUNCT
ap-5377	492	1	doi:10.1109/10.552241	doi:10.1109/10.552241	VERB
ap-5377	492	2	.	.	PUNCT
ap-5377	493	1	508	508	NUM
ap-5377	493	2	http://dx.doi.org/10.1371/journal.pone.0123033	http://dx.doi.org/10.1371/journal.pone.0123033	PROPN
ap-5377	493	3	http://dx.doi.org/10.1136/jnnp.2005.069245	http://dx.doi.org/10.1136/jnnp.2005.069245	PROPN
ap-5377	493	4	http://dx.doi.org/10.1109/icadiwt.2014.6814687	http://dx.doi.org/10.1109/icadiwt.2014.6814687	PROPN
ap-5377	493	5	http://dx.doi.org/10.1007/s10115-003-0086-9	http://dx.doi.org/10.1007/s10115-003-0086-9	PROPN
ap-5377	494	1	http://dx.doi.org/10.1016/j.eswa.2014.08.030	http://dx.doi.org/10.1016/j.eswa.2014.08.030	PROPN
ap-5377	494	2	http://dx.doi.org/10.1016/j.knosys.2015.08.004	http://dx.doi.org/10.1016/j.knosys.2015.08.004	VERB
ap-5377	494	3	http://dx.doi.org/10.1088/1741-2560/4/2/r01	http://dx.doi.org/10.1088/1741-2560/4/2/r01	PROPN
ap-5377	494	4	http://dx.doi.org/10.1007/978-3-319-23344-4_8	http://dx.doi.org/10.1007/978-3-319-23344-4_8	ADP
ap-5377	494	5	http://dx.doi.org/10.1109/iceeict.2015.7307340	http://dx.doi.org/10.1109/iceeict.2015.7307340	PROPN
ap-5377	494	6	http://dx.doi.org/10.1109/icmic.2016.7804256	http://dx.doi.org/10.1109/icmic.2016.7804256	ADJ
ap-5377	495	1	http://dx.doi.org/10.1016/j.eswa.2017.05.052	http://dx.doi.org/10.1016/j.eswa.2017.05.052	PROPN
ap-5377	495	2	http://dx.doi.org/10.1109/cibcb.2015.7300286	http://dx.doi.org/10.1109/cibcb.2015.7300286	ADJ
ap-5377	495	3	http://dx.doi.org/10.1007/978-3-319-02753-1_16	http://dx.doi.org/10.1007/978-3-319-02753-1_16	NOUN
ap-5377	495	4	http://dx.doi.org/10.1109/tbme.2007.891945	http://dx.doi.org/10.1109/tbme.2007.891945	NOUN
ap-5377	495	5	http://dx.doi.org/10.1109/ehb.2015.7391470	http://dx.doi.org/10.1109/ehb.2015.7391470	ADV
ap-5377	495	6	http://dx.doi.org/10.1007/978-981-10-9038-7_80	http://dx.doi.org/10.1007/978-981-10-9038-7_80	INTJ
ap-5377	495	7	http://dx.doi.org/10.1097/wnp.0000000000000308	http://dx.doi.org/10.1097/wnp.0000000000000308	PROPN
ap-5377	495	8	http://dx.doi.org/10.13164/re.2017.0323	http://dx.doi.org/10.13164/re.2017.0323	PROPN
ap-5377	495	9	http://dx.doi.org/10.1109/isspit.2015.7394397	http://dx.doi.org/10.1109/isspit.2015.7394397	ADJ
ap-5377	495	10	http://dx.doi.org/10.1109/10.552241	http://dx.doi.org/10.1109/10.552241	X
ap-5377	495	11	vol	vol	NOUN
ap-5377	495	12	.	.	PROPN
ap-5377	496	1	59	59	NUM
ap-5377	496	2	no	no	NOUN
ap-5377	496	3	.	.	PUNCT
ap-5377	497	1	5/2019	5/2019	NUM
ap-5377	497	2	automatic	automatic	ADJ
ap-5377	497	3	eeg	eeg	NOUN
ap-5377	497	4	classification	classification	NOUN
ap-5377	497	5	using	use	VERB
ap-5377	497	6	dbscan	dbscan	NOUN
ap-5377	497	7	and	and	CCONJ
ap-5377	497	8	denclue	denclue	VERB
ap-5377	497	9	[	[	X
ap-5377	497	10	25	25	NUM
ap-5377	497	11	]	]	PUNCT
ap-5377	497	12	m.	m.	PROPN
ap-5377	497	13	r.	r.	PROPN
ap-5377	497	14	anderberg	anderberg	PROPN
ap-5377	497	15	.	.	PUNCT
ap-5377	498	1	cluster	cluster	NOUN
ap-5377	498	2	analysis	analysis	NOUN
ap-5377	498	3	for	for	ADP
ap-5377	498	4	classification	classification	NOUN
ap-5377	498	5	.	.	PUNCT
ap-5377	499	1	academic	academic	ADJ
ap-5377	499	2	press	press	PROPN
ap-5377	499	3	,	,	PUNCT
ap-5377	499	4	inc	inc	PROPN
ap-5377	499	5	.	.	PROPN
ap-5377	499	6	london	london	PROPN
ap-5377	499	7	,	,	PUNCT
ap-5377	499	8	1973	1973	NUM
ap-5377	499	9	.	.	PUNCT
ap-5377	500	1	[	[	X
ap-5377	500	2	26	26	NUM
ap-5377	500	3	]	]	X
ap-5377	500	4	e.	e.	PROPN
ap-5377	500	5	schubert	schubert	PROPN
ap-5377	500	6	,	,	PUNCT
ap-5377	500	7	j.	j.	PROPN
ap-5377	500	8	sander	sander	PROPN
ap-5377	500	9	,	,	PUNCT
ap-5377	500	10	m.	m.	NOUN
ap-5377	500	11	ester	ester	NOUN
ap-5377	500	12	,	,	PUNCT
ap-5377	500	13	et	et	PROPN
ap-5377	500	14	al	al	PROPN
ap-5377	500	15	.	.	PROPN
ap-5377	500	16	dbscan	dbscan	PROPN
ap-5377	500	17	revisited	revisit	VERB
ap-5377	500	18	,	,	PUNCT
ap-5377	500	19	revisited	revisit	VERB
ap-5377	500	20	.	.	PUNCT
ap-5377	501	1	acm	acm	PROPN
ap-5377	501	2	transactions	transaction	NOUN
ap-5377	501	3	on	on	ADP
ap-5377	501	4	database	database	NOUN
ap-5377	501	5	systems	system	NOUN
ap-5377	501	6	42(3):1–21	42(3):1–21	NUM
ap-5377	501	7	,	,	PUNCT
ap-5377	501	8	2017	2017	NUM
ap-5377	501	9	-	-	SYM
ap-5377	501	10	08	08	NUM
ap-5377	501	11	-	-	SYM
ap-5377	501	12	24	24	NUM
ap-5377	501	13	.	.	PUNCT
ap-5377	501	14	doi:10.1145/3068335	doi:10.1145/3068335	PROPN
ap-5377	501	15	.	.	PUNCT
ap-5377	502	1	[	[	X
ap-5377	502	2	27	27	NUM
ap-5377	502	3	]	]	X
ap-5377	502	4	v.	v.	CCONJ
ap-5377	502	5	s.	s.	PROPN
ap-5377	502	6	ware	ware	PROPN
ap-5377	502	7	,	,	PUNCT
ap-5377	502	8	h.	h.	PROPN
ap-5377	502	9	n.	n.	PROPN
ap-5377	502	10	bharathi	bharathi	PROPN
ap-5377	502	11	.	.	PUNCT
ap-5377	503	1	study	study	NOUN
ap-5377	503	2	of	of	ADP
ap-5377	503	3	density	density	NOUN
ap-5377	503	4	based	base	VERB
ap-5377	503	5	algorihms	algorihm	NOUN
ap-5377	503	6	.	.	PUNCT
ap-5377	504	1	journal	journal	PROPN
ap-5377	504	2	of	of	ADP
ap-5377	504	3	computer	computer	NOUN
ap-5377	504	4	applocations	applocation	NOUN
ap-5377	504	5	32(8):68–75	32(8):68–75	NUM
ap-5377	504	6	,	,	PUNCT
ap-5377	504	7	1999	1999	NUM
ap-5377	504	8	.	.	PUNCT
ap-5377	505	1	doi:10.5120/12132	doi:10.5120/12132	X
ap-5377	505	2	-	-	PUNCT
ap-5377	505	3	8235	8235	NUM
ap-5377	505	4	.	.	PUNCT
ap-5377	506	1	[	[	X
ap-5377	506	2	28	28	NUM
ap-5377	506	3	]	]	X
ap-5377	506	4	a.	a.	NOUN
ap-5377	506	5	karami	karami	PROPN
ap-5377	506	6	,	,	PUNCT
ap-5377	506	7	r.	r.	PROPN
ap-5377	506	8	johansson	johansson	PROPN
ap-5377	506	9	,	,	PUNCT
ap-5377	506	10	r.	r.	PROPN
ap-5377	506	11	choosing	choosing	NOUN
ap-5377	506	12	.	.	PUNCT
ap-5377	507	1	choosing	choose	VERB
ap-5377	507	2	dbscan	dbscan	PROPN
ap-5377	507	3	parameters	parameter	NOUN
ap-5377	507	4	automatically	automatically	ADV
ap-5377	507	5	using	use	VERB
ap-5377	507	6	differential	differential	ADJ
ap-5377	507	7	evolution	evolution	NOUN
ap-5377	507	8	.	.	PUNCT
ap-5377	508	1	international	international	ADJ
ap-5377	508	2	journal	journal	PROPN
ap-5377	508	3	of	of	ADP
ap-5377	508	4	computer	computer	NOUN
ap-5377	508	5	applications	application	NOUN
ap-5377	508	6	91(7	91(7	PROPN
ap-5377	508	7	)	)	PUNCT
ap-5377	508	8	,	,	PUNCT
ap-5377	508	9	2014	2014	NUM
ap-5377	508	10	.	.	PUNCT
ap-5377	509	1	doi:10.5120/15890	doi:10.5120/15890	ADJ
ap-5377	509	2	-	-	SYM
ap-5377	509	3	5059	5059	NUM
ap-5377	509	4	.	.	PUNCT
ap-5377	510	1	[	[	X
ap-5377	510	2	29	29	NUM
ap-5377	510	3	]	]	PUNCT
ap-5377	510	4	a.	a.	NOUN
ap-5377	510	5	thouka	thouka	PROPN
ap-5377	510	6	.	.	PUNCT
ap-5377	511	1	choosing	choose	VERB
ap-5377	511	2	parameters	parameter	NOUN
ap-5377	511	3	of	of	ADP
ap-5377	511	4	dbsccan	dbsccan	ADJ
ap-5377	511	5	algorithm	algorithm	PROPN
ap-5377	511	6	.	.	PUNCT
ap-5377	512	1	,	,	PUNCT
ap-5377	513	1	2012	2012	NUM
ap-5377	513	2	.	.	PUNCT
ap-5377	514	1	[	[	X
ap-5377	514	2	30	30	NUM
ap-5377	514	3	]	]	X
ap-5377	514	4	m.	m.	NOUN
ap-5377	514	5	t.	t.	PROPN
ap-5377	514	6	h.	h.	PROPN
ap-5377	514	7	elbatta	elbatta	PROPN
ap-5377	514	8	,	,	PUNCT
ap-5377	514	9	w.	w.	PROPN
ap-5377	514	10	m.	m.	PROPN
ap-5377	514	11	ashour	ashour	PROPN
ap-5377	514	12	.	.	PUNCT
ap-5377	515	1	a	a	DET
ap-5377	515	2	dynamic	dynamic	ADJ
ap-5377	515	3	method	method	NOUN
ap-5377	515	4	for	for	ADP
ap-5377	515	5	discovering	discover	VERB
ap-5377	515	6	density	density	NOUN
ap-5377	515	7	varied	varied	ADJ
ap-5377	515	8	clusters	cluster	NOUN
ap-5377	515	9	.	.	PUNCT
ap-5377	516	1	inf	inf	PROPN
ap-5377	516	2	journal	journal	PROPN
ap-5377	516	3	of	of	ADP
ap-5377	516	4	signal	signal	PROPN
ap-5377	516	5	processing	processing	NOUN
ap-5377	516	6	,	,	PUNCT
ap-5377	516	7	image	image	NOUN
ap-5377	516	8	processing	processing	NOUN
ap-5377	516	9	and	and	CCONJ
ap-5377	516	10	pattern	pattern	NOUN
ap-5377	516	11	recognition	recognition	NOUN
ap-5377	516	12	6(1):123–134	6(1):123–134	NUM
ap-5377	516	13	,	,	PUNCT
ap-5377	516	14	2013	2013	NUM
ap-5377	516	15	.	.	PUNCT
ap-5377	517	1	[	[	X
ap-5377	517	2	31	31	NUM
ap-5377	517	3	]	]	PUNCT
ap-5377	517	4	m.	m.	NOUN
ap-5377	517	5	ester	ester	NOUN
ap-5377	517	6	,	,	PUNCT
ap-5377	517	7	h.	h.	PROPN
ap-5377	517	8	p.	p.	PROPN
ap-5377	517	9	kriegel	kriegel	PROPN
ap-5377	517	10	,	,	PUNCT
ap-5377	517	11	j.	j.	PROPN
ap-5377	517	12	sander	sander	PROPN
ap-5377	517	13	,	,	PUNCT
ap-5377	517	14	x.	x.	PROPN
ap-5377	517	15	xu	xu	PROPN
ap-5377	517	16	.	.	PUNCT
ap-5377	518	1	a	a	DET
ap-5377	518	2	dentsity	dentsity	NOUN
ap-5377	518	3	based	base	VERB
ap-5377	518	4	algorithm	algorithm	NOUN
ap-5377	518	5	for	for	ADP
ap-5377	518	6	discovering	discover	VERB
ap-5377	518	7	clusters	cluster	NOUN
ap-5377	518	8	in	in	ADP
ap-5377	518	9	large	large	ADJ
ap-5377	518	10	spatial	spatial	ADJ
ap-5377	518	11	databases	database	NOUN
ap-5377	518	12	with	with	ADP
ap-5377	518	13	noise	noise	NOUN
ap-5377	518	14	.	.	PUNCT
ap-5377	519	1	in	in	ADP
ap-5377	519	2	kdd	kdd	PROPN
ap-5377	519	3	,	,	PUNCT
ap-5377	519	4	vol	vol	NOUN
ap-5377	519	5	.	.	PROPN
ap-5377	519	6	96	96	NUM
ap-5377	519	7	,	,	PUNCT
ap-5377	519	8	pp	pp	ADJ
ap-5377	519	9	.	.	PUNCT
ap-5377	520	1	226–231	226–231	NUM
ap-5377	520	2	.	.	PUNCT
ap-5377	520	3	1996	1996	NUM
ap-5377	520	4	.	.	PUNCT
ap-5377	521	1	doi:10.5120/739	doi:10.5120/739	NOUN
ap-5377	521	2	-	-	NOUN
ap-5377	521	3	1038	1038	NUM
ap-5377	521	4	.	.	PUNCT
ap-5377	522	1	[	[	X
ap-5377	522	2	32	32	NUM
ap-5377	522	3	]	]	X
ap-5377	522	4	n.	n.	PROPN
ap-5377	522	5	rahman	rahman	PROPN
ap-5377	522	6	,	,	PUNCT
ap-5377	522	7	i.	i.	PROPN
ap-5377	522	8	s.	s.	PROPN
ap-5377	522	9	sitanggang	sitanggang	PROPN
ap-5377	522	10	.	.	PUNCT
ap-5377	523	1	determination	determination	NOUN
ap-5377	523	2	of	of	ADP
ap-5377	523	3	optimal	optimal	ADJ
ap-5377	523	4	epsilon	epsilon	PROPN
ap-5377	523	5	(	(	PUNCT
ap-5377	523	6	eps	eps	PROPN
ap-5377	523	7	)	)	PUNCT
ap-5377	523	8	value	value	NOUN
ap-5377	523	9	on	on	ADP
ap-5377	523	10	dbscan	dbscan	ADJ
ap-5377	523	11	algorithm	algorithm	NOUN
ap-5377	523	12	to	to	ADP
ap-5377	523	13	clustering	cluster	VERB
ap-5377	523	14	data	datum	NOUN
ap-5377	523	15	on	on	ADP
ap-5377	523	16	peatland	peatland	NOUN
ap-5377	523	17	hotspots	hotspot	NOUN
ap-5377	523	18	in	in	ADP
ap-5377	523	19	sumatra	sumatra	PROPN
ap-5377	523	20	.	.	PUNCT
ap-5377	524	1	in	in	ADP
ap-5377	524	2	iop	iop	PROPN
ap-5377	524	3	conference	conference	NOUN
ap-5377	524	4	series	series	NOUN
ap-5377	524	5	:	:	PUNCT
ap-5377	524	6	earth	earth	NOUN
ap-5377	524	7	an	an	DET
ap-5377	524	8	environmental	environmental	ADJ
ap-5377	524	9	science	science	NOUN
ap-5377	524	10	,	,	PUNCT
ap-5377	524	11	vol	vol	NOUN
ap-5377	524	12	.	.	PROPN
ap-5377	524	13	31	31	NUM
ap-5377	524	14	.	.	X
ap-5377	524	15	2016	2016	NUM
ap-5377	524	16	.	.	PUNCT
ap-5377	525	1	doi:10.1088/1755	doi:10.1088/1755	NOUN
ap-5377	525	2	-	-	SYM
ap-5377	525	3	1315/31/1/012012	1315/31/1/012012	NUM
ap-5377	525	4	.	.	PUNCT
ap-5377	526	1	[	[	X
ap-5377	526	2	33	33	NUM
ap-5377	526	3	]	]	PUNCT
ap-5377	526	4	c.	c.	PROPN
ap-5377	526	5	j.	j.	PROPN
ap-5377	526	6	pang	pang	PROPN
ap-5377	526	7	.	.	PUNCT
ap-5377	527	1	research	research	NOUN
ap-5377	527	2	of	of	ADP
ap-5377	527	3	grid	grid	NOUN
ap-5377	527	4	-	-	PUNCT
ap-5377	527	5	similarity	similarity	NOUN
ap-5377	527	6	-	-	PUNCT
ap-5377	527	7	based	base	VERB
ap-5377	527	8	clustering	clustering	ADJ
ap-5377	527	9	algorithm	algorithm	NOUN
ap-5377	527	10	.	.	PUNCT
ap-5377	528	1	in	in	ADP
ap-5377	528	2	wase	wase	PROPN
ap-5377	528	3	international	international	ADJ
ap-5377	528	4	conference	conference	NOUN
ap-5377	528	5	on	on	ADP
ap-5377	528	6	information	information	NOUN
ap-5377	528	7	engineering	engineering	NOUN
ap-5377	528	8	(	(	PUNCT
ap-5377	528	9	icie’09	icie’09	PROPN
ap-5377	528	10	)	)	PUNCT
ap-5377	528	11	,	,	PUNCT
ap-5377	528	12	vol	vol	NOUN
ap-5377	528	13	.	.	PROPN
ap-5377	528	14	2	2	NUM
ap-5377	528	15	,	,	PUNCT
ap-5377	528	16	pp	pp	ADJ
ap-5377	528	17	.	.	PUNCT
ap-5377	529	1	33–36	33–36	NUM
ap-5377	529	2	.	.	PUNCT
ap-5377	530	1	2009	2009	NUM
ap-5377	530	2	.	.	PUNCT
ap-5377	531	1	doi:10.109	doi:10.109	PROPN
ap-5377	531	2	-	-	PUNCT
ap-5377	531	3	icie.2019.202	icie.2019.202	PROPN
ap-5377	531	4	.	.	PUNCT
ap-5377	532	1	[	[	X
ap-5377	532	2	34	34	NUM
ap-5377	532	3	]	]	X
ap-5377	532	4	c.	c.	PROPN
ap-5377	532	5	f.	f.	PROPN
ap-5377	532	6	tsai	tsai	PROPN
ap-5377	532	7	,	,	PUNCT
ap-5377	532	8	j.	j.	PROPN
ap-5377	532	9	h.	h.	PROPN
ap-5377	532	10	zhang	zhang	PROPN
ap-5377	532	11	.	.	PUNCT
ap-5377	533	1	grid	grid	PROPN
ap-5377	533	2	clustering	cluster	VERB
ap-5377	533	3	algorithm	algorithm	NOUN
ap-5377	533	4	with	with	ADP
ap-5377	533	5	simple	simple	ADJ
ap-5377	533	6	leaping	leaping	ADJ
ap-5377	533	7	search	search	NOUN
ap-5377	533	8	technique	technique	NOUN
ap-5377	533	9	.	.	PUNCT
ap-5377	534	1	in	in	ADP
ap-5377	534	2	internatioanl	internatioanl	NOUN
ap-5377	534	3	symposium	symposium	NOUN
ap-5377	534	4	on	on	ADP
ap-5377	534	5	computer	computer	NOUN
ap-5377	534	6	,	,	PUNCT
ap-5377	534	7	consumer	consumer	NOUN
ap-5377	534	8	and	and	CCONJ
ap-5377	534	9	control	control	NOUN
ap-5377	534	10	(	(	PUNCT
ap-5377	534	11	is3c	is3c	PROPN
ap-5377	534	12	)	)	PUNCT
ap-5377	534	13	,	,	PUNCT
ap-5377	534	14	pp	pp	ADP
ap-5377	534	15	.	.	PUNCT
ap-5377	535	1	938–941	938–941	NUM
ap-5377	535	2	.	.	PUNCT
ap-5377	535	3	2012	2012	NUM
ap-5377	535	4	.	.	PUNCT
ap-5377	536	1	doi:10.1109	doi:10.1109	VERB
ap-5377	536	2	/	/	SYM
ap-5377	536	3	is3c.2012.244	is3c.2012.244	PROPN
ap-5377	536	4	.	.	PUNCT
ap-5377	537	1	[	[	X
ap-5377	537	2	35	35	NUM
ap-5377	537	3	]	]	X
ap-5377	537	4	s.	s.	PROPN
ap-5377	537	5	mahran	mahran	PROPN
ap-5377	537	6	,	,	PUNCT
ap-5377	537	7	k.	k.	PROPN
ap-5377	537	8	mahar	mahar	PROPN
ap-5377	537	9	.	.	PUNCT
ap-5377	538	1	using	use	VERB
ap-5377	538	2	grid	grid	NOUN
ap-5377	538	3	for	for	ADP
ap-5377	538	4	accelerating	accelerate	VERB
ap-5377	538	5	density	density	NOUN
ap-5377	538	6	-	-	PUNCT
ap-5377	538	7	based	base	VERB
ap-5377	538	8	clustering	clustering	NOUN
ap-5377	538	9	.	.	PUNCT
ap-5377	539	1	in	in	ADP
ap-5377	539	2	8th	8th	ADJ
ap-5377	539	3	ieee	ieee	NOUN
ap-5377	539	4	international	international	ADJ
ap-5377	539	5	conference	conference	NOUN
ap-5377	539	6	on	on	ADP
ap-5377	539	7	computer	computer	NOUN
ap-5377	539	8	and	and	CCONJ
ap-5377	539	9	information	information	NOUN
ap-5377	539	10	technology	technology	NOUN
ap-5377	539	11	,	,	PUNCT
ap-5377	539	12	pp	pp	ADJ
ap-5377	539	13	.	.	PUNCT
ap-5377	540	1	35–40	35–40	NUM
ap-5377	540	2	.	.	X
ap-5377	540	3	2008	2008	NUM
ap-5377	540	4	.	.	PUNCT
ap-5377	541	1	doi:10.1109	doi:10.1109	VERB
ap-5377	541	2	/	/	SYM
ap-5377	541	3	cit.2018.4594646	cit.2018.4594646	PROPN
ap-5377	541	4	.	.	PUNCT
ap-5377	542	1	[	[	X
ap-5377	542	2	36	36	NUM
ap-5377	542	3	]	]	PUNCT
ap-5377	542	4	a.	a.	NOUN
ap-5377	542	5	hinneburg	hinneburg	PROPN
ap-5377	542	6	,	,	PUNCT
ap-5377	542	7	d.	d.	PROPN
ap-5377	542	8	a.	a.	PROPN
ap-5377	542	9	keim	keim	PROPN
ap-5377	542	10	.	.	PUNCT
ap-5377	543	1	an	an	DET
ap-5377	543	2	efficient	efficient	ADJ
ap-5377	543	3	approach	approach	NOUN
ap-5377	543	4	to	to	ADP
ap-5377	543	5	clustering	cluster	VERB
ap-5377	543	6	in	in	ADP
ap-5377	543	7	large	large	ADJ
ap-5377	543	8	multimedia	multimedia	NOUN
ap-5377	543	9	databases	database	NOUN
ap-5377	543	10	with	with	ADP
ap-5377	543	11	noise	noise	NOUN
ap-5377	543	12	.	.	PUNCT
ap-5377	544	1	in	in	ADP
ap-5377	544	2	proceedings	proceeding	NOUN
ap-5377	544	3	of	of	ADP
ap-5377	544	4	the	the	DET
ap-5377	544	5	4th	4th	ADJ
ap-5377	544	6	international	international	ADJ
ap-5377	544	7	conference	conference	NOUN
ap-5377	544	8	on	on	ADP
ap-5377	544	9	knowledge	knowledge	NOUN
ap-5377	544	10	discovery	discovery	NOUN
ap-5377	544	11	and	and	CCONJ
ap-5377	544	12	datamining	datamine	VERB
ap-5377	544	13	(	(	PUNCT
ap-5377	544	14	kdd’98	kdd’98	PROPN
ap-5377	544	15	)	)	PUNCT
ap-5377	544	16	,	,	PUNCT
ap-5377	544	17	pp	pp	ADJ
ap-5377	544	18	.	.	PUNCT
ap-5377	545	1	58–65	58–65	NUM
ap-5377	545	2	.	.	PUNCT
ap-5377	546	1	1998	1998	NUM
ap-5377	546	2	.	.	PUNCT
ap-5377	547	1	[	[	X
ap-5377	547	2	37	37	NUM
ap-5377	547	3	]	]	PUNCT
ap-5377	547	4	a.	a.	NOUN
ap-5377	547	5	hinneburg	hinneburg	PROPN
ap-5377	547	6	,	,	PUNCT
ap-5377	547	7	h.-h	h.-h	NOUN
ap-5377	547	8	.	.	PUNCT
ap-5377	548	1	gabriel	gabriel	PROPN
ap-5377	548	2	.	.	PUNCT
ap-5377	549	1	fast	fast	ADJ
ap-5377	549	2	clustering	clustering	NOUN
ap-5377	549	3	based	base	VERB
ap-5377	549	4	on	on	ADP
ap-5377	549	5	kernel	kernel	PROPN
ap-5377	549	6	density	density	PROPN
ap-5377	549	7	estimation	estimation	NOUN
ap-5377	549	8	.	.	PUNCT
ap-5377	550	1	in	in	ADP
ap-5377	550	2	advances	advance	NOUN
ap-5377	550	3	in	in	ADP
ap-5377	550	4	intelligent	intelligent	ADJ
ap-5377	550	5	data	datum	NOUN
ap-5377	550	6	analysis	analysis	NOUN
ap-5377	550	7	vii	vii	PROPN
ap-5377	550	8	,	,	PUNCT
ap-5377	550	9	pp	pp	ADJ
ap-5377	550	10	.	.	PUNCT
ap-5377	551	1	70–80	70–80	NUM
ap-5377	551	2	.	.	PUNCT
ap-5377	552	1	springer	springer	PROPN
ap-5377	552	2	berlin	berlin	PROPN
ap-5377	552	3	heidelberg	heidelberg	PROPN
ap-5377	552	4	,	,	PUNCT
ap-5377	552	5	2007	2007	NUM
ap-5377	552	6	.	.	PUNCT
ap-5377	553	1	doi:10.1007/978	doi:10.1007/978	ADJ
ap-5377	553	2	-	-	PUNCT
ap-5377	553	3	3	3	NUM
ap-5377	553	4	-	-	PUNCT
ap-5377	553	5	540	540	NUM
ap-5377	553	6	-	-	PUNCT
ap-5377	553	7	74825	74825	NUM
ap-5377	553	8	-	-	PUNCT
ap-5377	553	9	0_7	0_7	NUM
ap-5377	553	10	.	.	PUNCT
ap-5377	554	1	[	[	X
ap-5377	554	2	38	38	NUM
ap-5377	554	3	]	]	X
ap-5377	554	4	d.	d.	PROPN
ap-5377	554	5	w.	w.	PROPN
ap-5377	554	6	scott	scott	PROPN
ap-5377	554	7	,	,	PUNCT
ap-5377	554	8	s.	s.	PROPN
ap-5377	554	9	r.	r.	PROPN
ap-5377	554	10	sain	sain	PROPN
ap-5377	554	11	.	.	PUNCT
ap-5377	555	1	multidimensional	multidimensional	ADJ
ap-5377	555	2	density	density	NOUN
ap-5377	555	3	estimation	estimation	NOUN
ap-5377	555	4	.	.	PUNCT
ap-5377	556	1	in	in	ADP
ap-5377	556	2	data	data	NOUN
ap-5377	556	3	mining	mining	NOUN
ap-5377	556	4	and	and	CCONJ
ap-5377	556	5	data	datum	NOUN
ap-5377	556	6	visualization	visualization	NOUN
ap-5377	556	7	,	,	PUNCT
ap-5377	556	8	pp	pp	ADJ
ap-5377	556	9	.	.	PUNCT
ap-5377	557	1	229–261	229–261	NUM
ap-5377	557	2	.	.	PUNCT
ap-5377	558	1	elsevier	elsevier	PROPN
ap-5377	558	2	,	,	PUNCT
ap-5377	558	3	2005	2005	NUM
ap-5377	558	4	.	.	PUNCT
ap-5377	559	1	doi:10.1016	doi:10.1016	PROPN
ap-5377	559	2	/	/	SYM
ap-5377	559	3	s0169	s0169	PROPN
ap-5377	559	4	-	-	PUNCT
ap-5377	559	5	7161(04)24009	7161(04)24009	NUM
ap-5377	559	6	-	-	PUNCT
ap-5377	559	7	3	3	NUM
ap-5377	559	8	.	.	PUNCT
ap-5377	560	1	[	[	X
ap-5377	560	2	39	39	NUM
ap-5377	560	3	]	]	PUNCT
ap-5377	560	4	d.	d.	PROPN
ap-5377	560	5	w.	w.	PROPN
ap-5377	560	6	scott	scott	PROPN
ap-5377	560	7	.	.	PROPN
ap-5377	561	1	averaged	average	VERB
ap-5377	561	2	shifted	shifted	ADJ
ap-5377	561	3	histograms	histogram	NOUN
ap-5377	561	4	:	:	PUNCT
ap-5377	561	5	effective	effective	ADJ
ap-5377	561	6	nonparametric	nonparametric	NOUN
ap-5377	561	7	density	density	NOUN
ap-5377	561	8	estimators	estimator	NOUN
ap-5377	561	9	in	in	ADP
ap-5377	561	10	several	several	ADJ
ap-5377	561	11	dimensions	dimension	NOUN
ap-5377	561	12	.	.	PUNCT
ap-5377	562	1	the	the	DET
ap-5377	562	2	annals	annal	NOUN
ap-5377	562	3	of	of	ADP
ap-5377	562	4	statistics	statistic	NOUN
ap-5377	562	5	13(3):1024–1040	13(3):1024–1040	NUM
ap-5377	562	6	,	,	PUNCT
ap-5377	562	7	1985	1985	NUM
ap-5377	562	8	.	.	PUNCT
ap-5377	563	1	doi:10.1214	doi:10.1214	PROPN
ap-5377	563	2	/	/	SYM
ap-5377	563	3	aos/1176349654	aos/1176349654	NOUN
ap-5377	563	4	.	.	PUNCT
ap-5377	564	1	[	[	X
ap-5377	564	2	40	40	NUM
ap-5377	564	3	]	]	PUNCT
ap-5377	564	4	d.	d.	PROPN
ap-5377	564	5	w.	w.	PROPN
ap-5377	564	6	scott	scott	PROPN
ap-5377	564	7	.	.	PUNCT
ap-5377	565	1	multivariate	multivariate	NOUN
ap-5377	565	2	density	density	NOUN
ap-5377	565	3	estimation	estimation	NOUN
ap-5377	565	4	:	:	PUNCT
ap-5377	565	5	theory	theory	NOUN
ap-5377	565	6	,	,	PUNCT
ap-5377	565	7	practice	practice	NOUN
ap-5377	565	8	,	,	PUNCT
ap-5377	565	9	and	and	CCONJ
ap-5377	565	10	visualization	visualization	NOUN
ap-5377	565	11	.	.	PUNCT
ap-5377	566	1	john	john	PROPN
ap-5377	566	2	wiley	wiley	PROPN
ap-5377	566	3	&	&	CCONJ
ap-5377	566	4	sons	son	NOUN
ap-5377	566	5	,	,	PUNCT
ap-5377	566	6	2015	2015	NUM
ap-5377	566	7	.	.	PUNCT
ap-5377	567	1	[	[	X
ap-5377	567	2	41	41	NUM
ap-5377	567	3	]	]	X
ap-5377	567	4	d.	d.	PROPN
ap-5377	567	5	w.	w.	PROPN
ap-5377	567	6	scott	scott	PROPN
ap-5377	567	7	.	.	PROPN
ap-5377	568	1	averaged	average	VERB
ap-5377	568	2	shifted	shift	VERB
ap-5377	568	3	histogram	histogram	NOUN
ap-5377	568	4	.	.	PUNCT
ap-5377	569	1	wiley	wiley	PROPN
ap-5377	569	2	interdisciplinary	interdisciplinary	ADJ
ap-5377	569	3	reviews	review	NOUN
ap-5377	569	4	:	:	PUNCT
ap-5377	569	5	computational	computational	ADJ
ap-5377	569	6	statistics	statistic	NOUN
ap-5377	569	7	2(2):160–164	2(2):160–164	NUM
ap-5377	569	8	,	,	PUNCT
ap-5377	569	9	2010	2010	NUM
ap-5377	569	10	.	.	PUNCT
ap-5377	570	1	doi:10.1002	doi:10.1002	NOUN
ap-5377	570	2	/	/	SYM
ap-5377	570	3	wics.54	wics.54	NOUN
ap-5377	570	4	.	.	PUNCT
ap-5377	571	1	[	[	X
ap-5377	571	2	42	42	NUM
ap-5377	571	3	]	]	PUNCT
ap-5377	571	4	m.	m.	NOUN
ap-5377	571	5	a.	a.	PROPN
ap-5377	571	6	sovierzoski	sovierzoski	PROPN
ap-5377	571	7	,	,	PUNCT
ap-5377	571	8	f.	f.	PROPN
ap-5377	571	9	m.	m.	PROPN
ap-5377	571	10	de	de	PROPN
ap-5377	571	11	azevedo	azevedo	PROPN
ap-5377	571	12	,	,	PUNCT
ap-5377	571	13	i.	i.	PROPN
ap-5377	571	14	f.	f.	PROPN
ap-5377	571	15	m.	m.	PROPN
ap-5377	571	16	arqoud	arqoud	PROPN
ap-5377	571	17	.	.	PUNCT
ap-5377	572	1	performance	performance	NOUN
ap-5377	572	2	evaluation	evaluation	NOUN
ap-5377	572	3	of	of	ADP
ap-5377	572	4	an	an	DET
ap-5377	572	5	ann	ann	PROPN
ap-5377	572	6	ff	ff	NOUN
ap-5377	572	7	classifier	classifier	NOUN
ap-5377	572	8	of	of	ADP
ap-5377	572	9	raw	raw	ADJ
ap-5377	572	10	eeg	eeg	PROPN
ap-5377	572	11	data	datum	NOUN
ap-5377	572	12	using	use	VERB
ap-5377	572	13	roc	roc	PROPN
ap-5377	572	14	analysis	analysis	NOUN
ap-5377	572	15	.	.	PUNCT
ap-5377	573	1	in	in	ADP
ap-5377	573	2	international	international	ADJ
ap-5377	573	3	conference	conference	NOUN
ap-5377	573	4	on	on	ADP
ap-5377	573	5	biomedical	biomedical	ADJ
ap-5377	573	6	engineering	engineering	NOUN
ap-5377	573	7	and	and	CCONJ
ap-5377	573	8	informatics	informatics	PROPN
ap-5377	573	9	(	(	PUNCT
ap-5377	573	10	bmei	bmei	PROPN
ap-5377	573	11	)	)	PUNCT
ap-5377	573	12	,	,	PUNCT
ap-5377	573	13	vol	vol	NOUN
ap-5377	573	14	.	.	PROPN
ap-5377	573	15	1	1	NUM
ap-5377	573	16	,	,	PUNCT
ap-5377	573	17	pp	pp	ADJ
ap-5377	573	18	.	.	PUNCT
ap-5377	574	1	332–336	332–336	NUM
ap-5377	574	2	.	.	PUNCT
ap-5377	575	1	2008	2008	NUM
ap-5377	575	2	.	.	PUNCT
ap-5377	576	1	doi:10.1109	doi:10.1109	VERB
ap-5377	576	2	/	/	SYM
ap-5377	576	3	bmei.2008.220	bmei.2008.220	PROPN
ap-5377	576	4	.	.	PUNCT
ap-5377	577	1	[	[	X
ap-5377	577	2	43	43	NUM
ap-5377	577	3	]	]	X
ap-5377	577	4	c.	c.	PROPN
ap-5377	577	5	o’reilly	o’reilly	PROPN
ap-5377	577	6	,	,	PUNCT
ap-5377	577	7	t.	t.	PROPN
ap-5377	577	8	nielsen	nielsen	PROPN
ap-5377	577	9	.	.	PUNCT
ap-5377	578	1	revisiting	revisit	VERB
ap-5377	578	2	the	the	DET
ap-5377	578	3	roc	roc	PROPN
ap-5377	578	4	curve	curve	NOUN
ap-5377	578	5	for	for	ADP
ap-5377	578	6	diagnostic	diagnostic	ADJ
ap-5377	578	7	applications	application	NOUN
ap-5377	578	8	with	with	ADP
ap-5377	578	9	an	an	DET
ap-5377	578	10	unbalanced	unbalanced	ADJ
ap-5377	578	11	class	class	NOUN
ap-5377	578	12	distribution	distribution	NOUN
ap-5377	578	13	.	.	PUNCT
ap-5377	579	1	in	in	ADP
ap-5377	579	2	2013	2013	NUM
ap-5377	579	3	8th	8th	ADJ
ap-5377	579	4	international	international	ADJ
ap-5377	579	5	workshop	workshop	NOUN
ap-5377	579	6	on	on	ADP
ap-5377	579	7	systems	system	NOUN
ap-5377	579	8	,	,	PUNCT
ap-5377	579	9	signal	signal	NOUN
ap-5377	579	10	processing	processing	NOUN
ap-5377	579	11	and	and	CCONJ
ap-5377	579	12	their	their	PRON
ap-5377	579	13	applications	application	NOUN
ap-5377	579	14	(	(	PUNCT
ap-5377	579	15	wosspa	wosspa	NOUN
ap-5377	579	16	)	)	PUNCT
ap-5377	579	17	,	,	PUNCT
ap-5377	579	18	pp	pp	ADP
ap-5377	579	19	.	.	PUNCT
ap-5377	580	1	413–420	413–420	NUM
ap-5377	580	2	.	.	PUNCT
ap-5377	581	1	ieee	ieee	NOUN
ap-5377	581	2	,	,	PUNCT
ap-5377	581	3	2013	2013	NUM
ap-5377	581	4	.	.	PUNCT
ap-5377	582	1	doi:10.1109	doi:10.1109	VERB
ap-5377	582	2	/	/	SYM
ap-5377	582	3	wosspa.2013.6602401	wosspa.2013.6602401	PROPN
ap-5377	582	4	.	.	PUNCT
ap-5377	583	1	[	[	X
ap-5377	583	2	44	44	NUM
ap-5377	583	3	]	]	PUNCT
ap-5377	583	4	k.	k.	PROPN
ap-5377	583	5	rai	rai	PROPN
ap-5377	583	6	,	,	PUNCT
ap-5377	583	7	v.	v.	PROPN
ap-5377	583	8	bajaj	bajaj	PROPN
ap-5377	583	9	,	,	PUNCT
ap-5377	583	10	a.	a.	PROPN
ap-5377	583	11	kumar	kumar	PROPN
ap-5377	583	12	.	.	PROPN
ap-5377	583	13	novel	novel	ADJ
ap-5377	583	14	feature	feature	NOUN
ap-5377	583	15	for	for	ADP
ap-5377	583	16	identification	identification	NOUN
ap-5377	583	17	of	of	ADP
ap-5377	583	18	focal	focal	ADJ
ap-5377	583	19	eeg	eeg	NOUN
ap-5377	583	20	signals	signal	NOUN
ap-5377	583	21	with	with	ADP
ap-5377	583	22	k	k	NOUN
ap-5377	583	23	-	-	PUNCT
ap-5377	583	24	means	mean	NOUN
ap-5377	583	25	and	and	CCONJ
ap-5377	583	26	fuzzy	fuzzy	ADJ
ap-5377	583	27	c	c	NOUN
ap-5377	583	28	-	-	PUNCT
ap-5377	583	29	means	mean	VERB
ap-5377	583	30	algorithms	algorithm	NOUN
ap-5377	583	31	.	.	PUNCT
ap-5377	584	1	in	in	ADP
ap-5377	584	2	2015	2015	NUM
ap-5377	584	3	ieee	ieee	NOUN
ap-5377	584	4	international	international	ADJ
ap-5377	584	5	conference	conference	NOUN
ap-5377	584	6	on	on	ADP
ap-5377	584	7	digital	digital	ADJ
ap-5377	584	8	signal	signal	NOUN
ap-5377	584	9	processing	processing	NOUN
ap-5377	584	10	(	(	PUNCT
ap-5377	584	11	dsp	dsp	NOUN
ap-5377	584	12	)	)	PUNCT
ap-5377	584	13	,	,	PUNCT
ap-5377	584	14	pp	pp	ADP
ap-5377	584	15	.	.	PUNCT
ap-5377	585	1	412–416	412–416	NUM
ap-5377	585	2	.	.	PUNCT
ap-5377	585	3	ieee	ieee	NOUN
ap-5377	585	4	,	,	PUNCT
ap-5377	585	5	2015	2015	NUM
ap-5377	585	6	.	.	PUNCT
ap-5377	586	1	doi:10.1109	doi:10.1109	PROPN
ap-5377	586	2	/	/	SYM
ap-5377	586	3	icdsp.2015.7251904	icdsp.2015.7251904	PROPN
ap-5377	586	4	.	.	PUNCT
ap-5377	587	1	509	509	NUM
ap-5377	587	2	http://dx.doi.org/10.1145/3068335	http://dx.doi.org/10.1145/3068335	NOUN
ap-5377	587	3	http://dx.doi.org/10.5120/12132-8235	http://dx.doi.org/10.5120/12132-8235	PROPN
ap-5377	587	4	http://dx.doi.org/10.5120/15890-5059	http://dx.doi.org/10.5120/15890-5059	PROPN
ap-5377	587	5	http://dx.doi.org/10.5120/739-1038	http://dx.doi.org/10.5120/739-1038	PROPN
ap-5377	587	6	http://dx.doi.org/10.1088/1755-1315/31/1/012012	http://dx.doi.org/10.1088/1755-1315/31/1/012012	PROPN
ap-5377	588	1	http://dx.doi.org/10.109-icie.2019.202	http://dx.doi.org/10.109-icie.2019.202	PROPN
ap-5377	588	2	http://dx.doi.org/10.1109/is3c.2012.244	http://dx.doi.org/10.1109/is3c.2012.244	NUM
ap-5377	588	3	http://dx.doi.org/10.1109/cit.2018.4594646	http://dx.doi.org/10.1109/cit.2018.4594646	NOUN
ap-5377	588	4	http://dx.doi.org/10.1007/978-3-540-74825-0_7	http://dx.doi.org/10.1007/978-3-540-74825-0_7	ADP
ap-5377	588	5	http://dx.doi.org/10.1016/s0169-7161(04)24009-3	http://dx.doi.org/10.1016/s0169-7161(04)24009-3	PRON
ap-5377	588	6	http://dx.doi.org/10.1214/aos/1176349654	http://dx.doi.org/10.1214/aos/1176349654	PROPN
ap-5377	588	7	http://dx.doi.org/10.1002/wics.54	http://dx.doi.org/10.1002/wics.54	X
ap-5377	588	8	http://dx.doi.org/10.1109/bmei.2008.220	http://dx.doi.org/10.1109/bmei.2008.220	VERB
ap-5377	588	9	http://dx.doi.org/10.1109/wosspa.2013.6602401	http://dx.doi.org/10.1109/wosspa.2013.6602401	PROPN
ap-5377	588	10	http://dx.doi.org/10.1109/icdsp.2015.7251904	http://dx.doi.org/10.1109/icdsp.2015.7251904	PROPN
ap-5377	588	11	acta	acta	PROPN
ap-5377	588	12	polytechnica	polytechnica	PROPN
ap-5377	588	13	59(5):498–509	59(5):498–509	PROPN
ap-5377	588	14	,	,	PUNCT
ap-5377	588	15	2019	2019	NUM
ap-5377	588	16	1	1	NUM
ap-5377	588	17	introduction	introduction	NOUN
ap-5377	588	18	2	2	NUM
ap-5377	588	19	methods	method	NOUN
ap-5377	588	20	2.1	2.1	NUM
ap-5377	588	21	data	datum	NOUN
ap-5377	588	22	2.2	2.2	NUM
ap-5377	588	23	preprocessing	preprocesse	VERB
ap-5377	588	24	2.3	2.3	NUM
ap-5377	588	25	k	k	NOUN
ap-5377	588	26	-	-	PUNCT
ap-5377	588	27	means	mean	VERB
ap-5377	588	28	2.4	2.4	NUM
ap-5377	588	29	dbscan	dbscan	NOUN
ap-5377	588	30	2.5	2.5	NUM
ap-5377	588	31	denclue	denclue	NOUN
ap-5377	588	32	2.6	2.6	NUM
ap-5377	588	33	statistical	statistical	ADJ
ap-5377	588	34	analysis	analysis	NOUN
ap-5377	588	35	3	3	NUM
ap-5377	588	36	results	result	VERB
ap-5377	588	37	3.1	3.1	NUM
ap-5377	588	38	test	test	NOUN
ap-5377	588	39	data	datum	NOUN
ap-5377	588	40	3.2	3.2	NUM
ap-5377	588	41	real	real	ADJ
ap-5377	588	42	eeg	eeg	PROPN
ap-5377	588	43	data	datum	NOUN
ap-5377	588	44	4	4	NUM
ap-5377	588	45	discussion	discussion	NOUN
ap-5377	588	46	5	5	NUM
ap-5377	588	47	conclusion	conclusion	NOUN
ap-5377	588	48	acknowledgements	acknowledgement	NOUN
ap-5377	588	49	references	reference	NOUN