id	sid	tid	token	lemma	pos
cana-1006	1	1	communications	communication	NOUN
cana-1006	1	2	on	on	ADP
cana-1006	1	3	applied	apply	VERB
cana-1006	1	4	nonlinear	nonlinear	ADJ
cana-1006	1	5	analysis	analysis	NOUN
cana-1006	1	6	issn	issn	NOUN
cana-1006	1	7	:	:	PUNCT
cana-1006	1	8	1074	1074	NUM
cana-1006	1	9	-	-	PUNCT
cana-1006	1	10	133x	133x	NUM
cana-1006	1	11	vol	vol	NOUN
cana-1006	1	12	31	31	NUM
cana-1006	1	13	no	no	NOUN
cana-1006	1	14	.	.	PUNCT
cana-1006	2	1	5s	5s	NUM
cana-1006	2	2	(	(	PUNCT
cana-1006	2	3	2024	2024	NUM
cana-1006	2	4	)	)	PUNCT
cana-1006	2	5	118	118	NUM
cana-1006	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	2	7	hybrid	hybrid	ADJ
cana-1006	2	8	model	model	NOUN
cana-1006	2	9	for	for	ADP
cana-1006	2	10	intrusion	intrusion	NOUN
cana-1006	2	11	detection	detection	NOUN
cana-1006	2	12	in	in	ADP
cana-1006	2	13	wireless	wireless	ADJ
cana-1006	2	14	sensor	sensor	NOUN
cana-1006	2	15	network	network	NOUN
cana-1006	2	16	:	:	PUNCT
cana-1006	2	17	an	an	DET
cana-1006	2	18	improved	improved	ADJ
cana-1006	2	19	class	class	NOUN
cana-1006	2	20	imbalance	imbalance	NOUN
cana-1006	2	21	processing	process	VERB
cana-1006	2	22	sravanthi	sravanthi	ADJ
cana-1006	2	23	godala1	godala1	NOUN
cana-1006	2	24	,	,	PUNCT
cana-1006	2	25	dr	dr	PROPN
cana-1006	2	26	.	.	PROPN
cana-1006	2	27	m.	m.	PROPN
cana-1006	2	28	sunil	sunil	PROPN
cana-1006	2	29	kumar2	kumar2	PROPN
cana-1006	3	1	1research	1research	NUM
cana-1006	3	2	scholar	scholar	NOUN
cana-1006	3	3	,	,	PUNCT
cana-1006	3	4	department	department	NOUN
cana-1006	3	5	of	of	ADP
cana-1006	3	6	cse	cse	PROPN
cana-1006	3	7	,	,	PUNCT
cana-1006	3	8	jntua	jntua	PROPN
cana-1006	3	9	,	,	PUNCT
cana-1006	3	10	ananthapuramu	ananthapuramu	ADJ
cana-1006	3	11	515002	515002	NUM
cana-1006	3	12	,	,	PUNCT
cana-1006	3	13	ap	ap	PROPN
cana-1006	3	14	,	,	PUNCT
cana-1006	3	15	india	india	PROPN
cana-1006	3	16	email:vmsravanthi@gmail.com	email:vmsravanthi@gmail.com	PROPN
cana-1006	3	17	2professor	2professor	NUM
cana-1006	3	18	,	,	PUNCT
cana-1006	3	19	department	department	NOUN
cana-1006	3	20	of	of	ADP
cana-1006	3	21	cse	cse	PROPN
cana-1006	3	22	,	,	PUNCT
cana-1006	3	23	sree	sree	PROPN
cana-1006	3	24	vidyanikethan	vidyanikethan	PROPN
cana-1006	3	25	engineering	engineering	PROPN
cana-1006	3	26	college	college	PROPN
cana-1006	3	27	(	(	PUNCT
cana-1006	3	28	autonomous	autonomous	ADJ
cana-1006	3	29	)	)	PUNCT
cana-1006	3	30	,	,	PUNCT
cana-1006	3	31	tirupati	tirupati	PROPN
cana-1006	3	32	517102,ap	517102,ap	NUM
cana-1006	3	33	,	,	PUNCT
cana-1006	3	34	india	india	PROPN
cana-1006	3	35	.	.	PUNCT
cana-1006	4	1	email:sunilmalchi1@gmail.com	email:sunilmalchi1@gmail.com	PROPN
cana-1006	4	2	article	article	NOUN
cana-1006	4	3	history	history	NOUN
cana-1006	4	4	:	:	PUNCT
cana-1006	4	5	received	receive	VERB
cana-1006	4	6	:	:	PUNCT
cana-1006	4	7	15	15	NUM
cana-1006	4	8	-	-	SYM
cana-1006	4	9	05	05	NUM
cana-1006	4	10	-	-	PUNCT
cana-1006	4	11	2024	2024	NUM
cana-1006	4	12	revised	revise	VERB
cana-1006	4	13	:	:	PUNCT
cana-1006	4	14	20	20	NUM
cana-1006	4	15	-	-	SYM
cana-1006	4	16	06	06	NUM
cana-1006	4	17	-	-	PUNCT
cana-1006	4	18	2024	2024	NUM
cana-1006	4	19	accepted	accept	VERB
cana-1006	4	20	:	:	PUNCT
cana-1006	4	21	01	01	NUM
cana-1006	4	22	-	-	SYM
cana-1006	4	23	07	07	NUM
cana-1006	4	24	-	-	PUNCT
cana-1006	4	25	2024	2024	NUM
cana-1006	4	26	abstract	abstract	NOUN
cana-1006	4	27	a	a	DET
cana-1006	4	28	significant	significant	ADJ
cana-1006	4	29	difficulty	difficulty	NOUN
cana-1006	4	30	in	in	ADP
cana-1006	4	31	wsn	wsn	PROPN
cana-1006	4	32	settings	setting	NOUN
cana-1006	4	33	is	be	AUX
cana-1006	4	34	recognizing	recognize	VERB
cana-1006	4	35	the	the	DET
cana-1006	4	36	abnormalities	abnormality	NOUN
cana-1006	4	37	as	as	SCONJ
cana-1006	4	38	security	security	NOUN
cana-1006	4	39	threats	threat	NOUN
cana-1006	4	40	become	become	VERB
cana-1006	4	41	divergent	divergent	ADJ
cana-1006	4	42	in	in	ADP
cana-1006	4	43	various	various	ADJ
cana-1006	4	44	fields	field	NOUN
cana-1006	4	45	.	.	PUNCT
cana-1006	5	1	the	the	DET
cana-1006	5	2	major	major	ADJ
cana-1006	5	3	drawbacks	drawback	NOUN
cana-1006	5	4	of	of	ADP
cana-1006	5	5	wsn	wsn	NOUN
cana-1006	5	6	including	include	VERB
cana-1006	5	7	insufficient	insufficient	ADJ
cana-1006	5	8	memory	memory	NOUN
cana-1006	5	9	,	,	PUNCT
cana-1006	5	10	limited	limited	ADJ
cana-1006	5	11	energy	energy	NOUN
cana-1006	5	12	,	,	PUNCT
cana-1006	5	13	and	and	CCONJ
cana-1006	5	14	low	low	ADJ
cana-1006	5	15	compute	compute	NOUN
cana-1006	5	16	power	power	NOUN
cana-1006	5	17	,	,	PUNCT
cana-1006	5	18	and	and	CCONJ
cana-1006	5	19	a	a	DET
cana-1006	5	20	small	small	ADJ
cana-1006	5	21	communication	communication	NOUN
cana-1006	5	22	range	range	NOUN
cana-1006	5	23	.	.	PUNCT
cana-1006	6	1	thus	thus	ADV
cana-1006	6	2	,	,	PUNCT
cana-1006	6	3	enhancing	enhance	VERB
cana-1006	6	4	the	the	DET
cana-1006	6	5	detection	detection	NOUN
cana-1006	6	6	accuracy	accuracy	NOUN
cana-1006	6	7	of	of	ADP
cana-1006	6	8	intrusion	intrusion	NOUN
cana-1006	6	9	detection	detection	NOUN
cana-1006	6	10	in	in	ADP
cana-1006	6	11	such	such	ADJ
cana-1006	6	12	contexts	context	NOUN
cana-1006	6	13	is	be	AUX
cana-1006	6	14	critical	critical	ADJ
cana-1006	6	15	.	.	PUNCT
cana-1006	7	1	however	however	ADV
cana-1006	7	2	,	,	PUNCT
cana-1006	7	3	this	this	DET
cana-1006	7	4	work	work	NOUN
cana-1006	7	5	intends	intend	VERB
cana-1006	7	6	to	to	PART
cana-1006	7	7	propose	propose	VERB
cana-1006	7	8	intrusion	intrusion	NOUN
cana-1006	7	9	detection	detection	NOUN
cana-1006	7	10	in	in	ADP
cana-1006	7	11	wsn	wsn	PROPN
cana-1006	7	12	with	with	ADP
cana-1006	7	13	improved	improved	ADJ
cana-1006	7	14	class	class	NOUN
cana-1006	7	15	imbalance	imbalance	NOUN
cana-1006	7	16	processing	processing	NOUN
cana-1006	7	17	.	.	PUNCT
cana-1006	8	1	the	the	DET
cana-1006	8	2	input	input	NOUN
cana-1006	8	3	data	data	NOUN
cana-1006	8	4	is	be	AUX
cana-1006	8	5	pre	pre	VERB
cana-1006	8	6	-	-	VERB
cana-1006	8	7	processed	process	VERB
cana-1006	8	8	to	to	PART
cana-1006	8	9	balance	balance	VERB
cana-1006	8	10	the	the	DET
cana-1006	8	11	data	datum	NOUN
cana-1006	8	12	with	with	ADP
cana-1006	8	13	modified	modified	ADJ
cana-1006	8	14	class	class	NOUN
cana-1006	8	15	imbalance	imbalance	NOUN
cana-1006	8	16	process	process	NOUN
cana-1006	8	17	.	.	PUNCT
cana-1006	9	1	here	here	ADV
cana-1006	9	2	,	,	PUNCT
cana-1006	9	3	the	the	DET
cana-1006	9	4	smote	smote	NOUN
cana-1006	9	5	-	-	PUNCT
cana-1006	9	6	enn	enn	PROPN
cana-1006	9	7	and	and	CCONJ
cana-1006	9	8	tomek	tomek	PROPN
cana-1006	9	9	link	link	NOUN
cana-1006	9	10	algorithm	algorithm	PROPN
cana-1006	9	11	is	be	AUX
cana-1006	9	12	employed	employ	VERB
cana-1006	9	13	to	to	ADP
cana-1006	9	14	pre	pre	VERB
cana-1006	9	15	-	-	VERB
cana-1006	9	16	process	process	VERB
cana-1006	9	17	the	the	DET
cana-1006	9	18	raw	raw	ADJ
cana-1006	9	19	data	datum	NOUN
cana-1006	9	20	.	.	PUNCT
cana-1006	10	1	then	then	ADV
cana-1006	10	2	the	the	DET
cana-1006	10	3	entropy	entropy	NOUN
cana-1006	10	4	and	and	CCONJ
cana-1006	10	5	improved	improved	ADJ
cana-1006	10	6	correlation	correlation	NOUN
cana-1006	10	7	based	base	VERB
cana-1006	10	8	features	feature	NOUN
cana-1006	10	9	are	be	AUX
cana-1006	10	10	retrieved	retrieve	VERB
cana-1006	10	11	from	from	ADP
cana-1006	10	12	the	the	DET
cana-1006	10	13	balanced	balanced	ADJ
cana-1006	10	14	data	datum	NOUN
cana-1006	10	15	.	.	PUNCT
cana-1006	11	1	later	later	ADV
cana-1006	11	2	,	,	PUNCT
cana-1006	11	3	these	these	DET
cana-1006	11	4	features	feature	NOUN
cana-1006	11	5	are	be	AUX
cana-1006	11	6	trained	train	VERB
cana-1006	11	7	by	by	ADP
cana-1006	11	8	subjecting	subject	VERB
cana-1006	11	9	those	those	DET
cana-1006	11	10	features	feature	NOUN
cana-1006	11	11	into	into	ADP
cana-1006	11	12	the	the	DET
cana-1006	11	13	hybrid	hybrid	ADJ
cana-1006	11	14	model	model	NOUN
cana-1006	11	15	that	that	PRON
cana-1006	11	16	includes	include	VERB
cana-1006	11	17	deep	deep	ADJ
cana-1006	11	18	maxout	maxout	NOUN
cana-1006	11	19	and	and	CCONJ
cana-1006	11	20	bi	bi	NOUN
cana-1006	11	21	-	-	PROPN
cana-1006	11	22	gru	gru	NOUN
cana-1006	11	23	model	model	NOUN
cana-1006	11	24	and	and	CCONJ
cana-1006	11	25	then	then	ADV
cana-1006	11	26	the	the	DET
cana-1006	11	27	final	final	ADJ
cana-1006	11	28	detection	detection	NOUN
cana-1006	11	29	is	be	AUX
cana-1006	11	30	predicted	predict	VERB
cana-1006	11	31	with	with	ADP
cana-1006	11	32	the	the	DET
cana-1006	11	33	classifier	classifier	NOUN
cana-1006	11	34	outcomes	outcome	NOUN
cana-1006	11	35	.	.	PUNCT
cana-1006	12	1	further	far	ADV
cana-1006	12	2	,	,	PUNCT
cana-1006	12	3	at	at	ADP
cana-1006	12	4	the	the	DET
cana-1006	12	5	training	training	NOUN
cana-1006	12	6	rate	rate	NOUN
cana-1006	12	7	90	90	NUM
cana-1006	12	8	%	%	NOUN
cana-1006	12	9	,	,	PUNCT
cana-1006	12	10	the	the	DET
cana-1006	12	11	proposed	propose	VERB
cana-1006	12	12	yielded	yield	VERB
cana-1006	12	13	the	the	DET
cana-1006	12	14	least	least	ADJ
cana-1006	12	15	fpr	fpr	NOUN
cana-1006	12	16	rate	rate	NOUN
cana-1006	12	17	(	(	PUNCT
cana-1006	12	18	0.1038	0.1038	NUM
cana-1006	12	19	)	)	PUNCT
cana-1006	12	20	than	than	ADP
cana-1006	12	21	the	the	DET
cana-1006	12	22	other	other	ADJ
cana-1006	12	23	60	60	NUM
cana-1006	12	24	,	,	PUNCT
cana-1006	12	25	70	70	NUM
cana-1006	12	26	and	and	CCONJ
cana-1006	12	27	80	80	NUM
cana-1006	12	28	training	training	NOUN
cana-1006	12	29	percentages	percentage	NOUN
cana-1006	12	30	.	.	PUNCT
cana-1006	13	1	keywords	keyword	NOUN
cana-1006	13	2	:	:	PUNCT
cana-1006	13	3	intrusion	intrusion	NOUN
cana-1006	13	4	detection	detection	NOUN
cana-1006	13	5	,	,	PUNCT
cana-1006	13	6	wsn	wsn	PROPN
cana-1006	13	7	,	,	PUNCT
cana-1006	13	8	smote	smote	ADJ
cana-1006	13	9	,	,	PUNCT
cana-1006	13	10	improved	improved	ADJ
cana-1006	13	11	correlation	correlation	NOUN
cana-1006	13	12	,	,	PUNCT
cana-1006	13	13	and	and	CCONJ
cana-1006	13	14	entropy	entropy	NOUN
cana-1006	13	15	features	feature	NOUN
cana-1006	13	16	.	.	PUNCT
cana-1006	14	1	1	1	X
cana-1006	14	2	.	.	X
cana-1006	14	3	introduction	introduction	NOUN
cana-1006	14	4	wsns	wsns	NOUN
cana-1006	14	5	play	play	VERB
cana-1006	14	6	a	a	DET
cana-1006	14	7	major	major	ADJ
cana-1006	14	8	role	role	NOUN
cana-1006	14	9	that	that	PRON
cana-1006	14	10	connects	connect	VERB
cana-1006	14	11	the	the	DET
cana-1006	14	12	digital	digital	NOUN
cana-1006	14	13	with	with	ADP
cana-1006	14	14	the	the	DET
cana-1006	14	15	physical	physical	ADJ
cana-1006	14	16	worlds	world	NOUN
cana-1006	14	17	.	.	PUNCT
cana-1006	15	1	wsns	wsns	PROPN
cana-1006	15	2	allow	allow	VERB
cana-1006	15	3	us	we	PRON
cana-1006	15	4	to	to	PART
cana-1006	15	5	research	research	VERB
cana-1006	15	6	physical	physical	ADJ
cana-1006	15	7	world	world	NOUN
cana-1006	15	8	environmental	environmental	ADJ
cana-1006	15	9	phenomena	phenomenon	NOUN
cana-1006	15	10	by	by	ADP
cana-1006	15	11	utilizing	utilize	VERB
cana-1006	15	12	a	a	DET
cana-1006	15	13	large	large	ADJ
cana-1006	15	14	number	number	NOUN
cana-1006	15	15	of	of	ADP
cana-1006	15	16	sensors	sensor	NOUN
cana-1006	15	17	that	that	PRON
cana-1006	15	18	gather	gather	VERB
cana-1006	15	19	information	information	NOUN
cana-1006	15	20	in	in	ADP
cana-1006	15	21	digital	digital	ADJ
cana-1006	15	22	format	format	NOUN
cana-1006	15	23	to	to	PART
cana-1006	15	24	be	be	AUX
cana-1006	15	25	processed	process	VERB
cana-1006	15	26	and	and	CCONJ
cana-1006	15	27	transported	transport	VERB
cana-1006	15	28	through	through	ADP
cana-1006	15	29	network	network	NOUN
cana-1006	15	30	and	and	CCONJ
cana-1006	15	31	then	then	ADV
cana-1006	15	32	preserved	preserve	VERB
cana-1006	15	33	and	and	CCONJ
cana-1006	15	34	examined	examine	VERB
cana-1006	15	35	in	in	ADP
cana-1006	15	36	fog	fog	NOUN
cana-1006	15	37	nodes	node	NOUN
cana-1006	15	38	[	[	X
cana-1006	15	39	3	3	X
cana-1006	15	40	]	]	X
cana-1006	15	41	[	[	X
cana-1006	15	42	7	7	NUM
cana-1006	15	43	]	]	PUNCT
cana-1006	15	44	.	.	PUNCT
cana-1006	16	1	wsn	wsn	PROPN
cana-1006	16	2	is	be	AUX
cana-1006	16	3	made	make	VERB
cana-1006	16	4	up	up	ADP
cana-1006	16	5	of	of	ADP
cana-1006	16	6	a	a	DET
cana-1006	16	7	multitude	multitude	NOUN
cana-1006	16	8	of	of	ADP
cana-1006	16	9	low	low	ADJ
cana-1006	16	10	-	-	PUNCT
cana-1006	16	11	power	power	NOUN
cana-1006	16	12	,	,	PUNCT
cana-1006	16	13	low	low	ADJ
cana-1006	16	14	-	-	PUNCT
cana-1006	16	15	cost	cost	NOUN
cana-1006	16	16	,	,	PUNCT
cana-1006	16	17	self	self	NOUN
cana-1006	16	18	-	-	PUNCT
cana-1006	16	19	organizing	organize	VERB
cana-1006	16	20	wireless	wireless	ADJ
cana-1006	16	21	nodes	node	NOUN
cana-1006	16	22	that	that	PRON
cana-1006	16	23	are	be	AUX
cana-1006	16	24	used	use	VERB
cana-1006	16	25	to	to	PART
cana-1006	16	26	manage	manage	VERB
cana-1006	16	27	and	and	CCONJ
cana-1006	16	28	monitor	monitor	VERB
cana-1006	16	29	the	the	DET
cana-1006	16	30	environment	environment	NOUN
cana-1006	16	31	.	.	PUNCT
cana-1006	17	1	furthermore	furthermore	ADV
cana-1006	17	2	,	,	PUNCT
cana-1006	17	3	wsns	wsns	PROPN
cana-1006	17	4	may	may	AUX
cana-1006	17	5	be	be	AUX
cana-1006	17	6	employed	employ	VERB
cana-1006	17	7	in	in	ADP
cana-1006	17	8	a	a	DET
cana-1006	17	9	variety	variety	NOUN
cana-1006	17	10	of	of	ADP
cana-1006	17	11	applications	application	NOUN
cana-1006	17	12	such	such	ADJ
cana-1006	17	13	as	as	ADP
cana-1006	17	14	earthquake	earthquake	NOUN
cana-1006	17	15	monitoring	monitoring	NOUN
cana-1006	17	16	,	,	PUNCT
cana-1006	17	17	ocean	ocean	NOUN
cana-1006	17	18	monitoring	monitoring	NOUN
cana-1006	17	19	,	,	PUNCT
cana-1006	17	20	machine	machine	NOUN
cana-1006	17	21	performance	performance	NOUN
cana-1006	17	22	monitoring	monitoring	NOUN
cana-1006	17	23	,	,	PUNCT
cana-1006	17	24	and	and	CCONJ
cana-1006	17	25	a	a	DET
cana-1006	17	26	variety	variety	NOUN
cana-1006	17	27	of	of	ADP
cana-1006	17	28	military	military	ADJ
cana-1006	17	29	applications	application	NOUN
cana-1006	17	30	[	[	X
cana-1006	17	31	5	5	NUM
cana-1006	17	32	]	]	PUNCT
cana-1006	17	33	.	.	PUNCT
cana-1006	18	1	furthermore	furthermore	ADV
cana-1006	18	2	,	,	PUNCT
cana-1006	18	3	advanced	advanced	ADJ
cana-1006	18	4	uses	use	VERB
cana-1006	18	5	like	like	ADP
cana-1006	18	6	pollution	pollution	NOUN
cana-1006	18	7	observing	observe	VERB
cana-1006	18	8	,	,	PUNCT
cana-1006	18	9	building	build	VERB
cana-1006	18	10	security	security	NOUN
cana-1006	18	11	,	,	PUNCT
cana-1006	18	12	highway	highway	NOUN
cana-1006	18	13	traffic	traffic	NOUN
cana-1006	18	14	,	,	PUNCT
cana-1006	18	15	and	and	CCONJ
cana-1006	18	16	water	water	NOUN
cana-1006	18	17	quality	quality	NOUN
cana-1006	18	18	observing	observe	VERB
cana-1006	18	19	are	be	AUX
cana-1006	18	20	involved	involve	VERB
cana-1006	18	21	in	in	ADP
cana-1006	18	22	the	the	DET
cana-1006	18	23	idea	idea	NOUN
cana-1006	18	24	of	of	ADP
cana-1006	18	25	wsn	wsn	PROPN
cana-1006	18	26	architecture	architecture	NOUN
cana-1006	18	27	.	.	PUNCT
cana-1006	19	1	furthermore	furthermore	ADV
cana-1006	19	2	,	,	PUNCT
cana-1006	19	3	five	five	NUM
cana-1006	19	4	key	key	ADJ
cana-1006	19	5	features	feature	NOUN
cana-1006	19	6	must	must	AUX
cana-1006	19	7	be	be	AUX
cana-1006	19	8	addressed	address	VERB
cana-1006	19	9	while	while	SCONJ
cana-1006	19	10	developing	develop	VERB
cana-1006	19	11	a	a	DET
cana-1006	19	12	wsn	wsn	NOUN
cana-1006	19	13	:	:	PUNCT
cana-1006	19	14	they	they	PRON
cana-1006	19	15	are	be	AUX
cana-1006	19	16	dependability	dependability	NOUN
cana-1006	19	17	,	,	PUNCT
cana-1006	19	18	self	self	NOUN
cana-1006	19	19	-	-	PUNCT
cana-1006	19	20	healing	healing	NOUN
cana-1006	19	21	,	,	PUNCT
cana-1006	19	22	robustness	robustness	NOUN
cana-1006	19	23	,	,	PUNCT
cana-1006	19	24	scalability	scalability	NOUN
cana-1006	19	25	,	,	PUNCT
cana-1006	19	26	and	and	CCONJ
cana-1006	19	27	security	security	NOUN
cana-1006	20	1	[	[	X
cana-1006	20	2	1	1	X
cana-1006	20	3	]	]	X
cana-1006	21	1	[	[	X
cana-1006	21	2	6	6	NUM
cana-1006	21	3	]	]	PUNCT
cana-1006	21	4	.	.	PUNCT
cana-1006	22	1	it	it	PRON
cana-1006	22	2	is	be	AUX
cana-1006	22	3	necessary	necessary	ADJ
cana-1006	22	4	for	for	ADP
cana-1006	22	5	vital	vital	ADJ
cana-1006	22	6	programs	program	NOUN
cana-1006	22	7	that	that	PRON
cana-1006	22	8	make	make	VERB
cana-1006	22	9	use	use	NOUN
cana-1006	22	10	of	of	ADP
cana-1006	22	11	wsn	wsn	PROPN
cana-1006	22	12	to	to	PART
cana-1006	22	13	have	have	VERB
cana-1006	22	14	a	a	DET
cana-1006	22	15	high	high	ADJ
cana-1006	22	16	level	level	NOUN
cana-1006	22	17	of	of	ADP
cana-1006	22	18	assurance	assurance	NOUN
cana-1006	22	19	in	in	ADP
cana-1006	22	20	order	order	NOUN
cana-1006	22	21	to	to	PART
cana-1006	22	22	safeguard	safeguard	VERB
cana-1006	22	23	their	their	PRON
cana-1006	22	24	information	information	NOUN
cana-1006	22	25	as	as	ADV
cana-1006	22	26	well	well	ADV
cana-1006	22	27	as	as	ADP
cana-1006	22	28	their	their	PRON
cana-1006	22	29	systems	system	NOUN
cana-1006	22	30	contrary	contrary	ADJ
cana-1006	22	31	to	to	ADP
cana-1006	22	32	attacks	attack	NOUN
cana-1006	22	33	.	.	PUNCT
cana-1006	23	1	ids	id	NOUN
cana-1006	23	2	ought	ought	AUX
cana-1006	23	3	to	to	PART
cana-1006	23	4	be	be	AUX
cana-1006	23	5	employed	employ	VERB
cana-1006	23	6	to	to	PART
cana-1006	23	7	identify	identify	VERB
cana-1006	23	8	abnormal	abnormal	ADJ
cana-1006	23	9	behaviours	behaviour	NOUN
cana-1006	23	10	and	and	CCONJ
cana-1006	23	11	incursions	incursion	NOUN
cana-1006	23	12	.	.	PUNCT
cana-1006	24	1	sensors	sensor	NOUN
cana-1006	24	2	in	in	ADP
cana-1006	24	3	wsn	wsn	PROPN
cana-1006	24	4	collect	collect	VERB
cana-1006	24	5	information	information	NOUN
cana-1006	24	6	from	from	ADP
cana-1006	24	7	the	the	DET
cana-1006	24	8	environment	environment	NOUN
cana-1006	24	9	in	in	ADP
cana-1006	24	10	which	which	PRON
cana-1006	24	11	they	they	PRON
cana-1006	24	12	are	be	AUX
cana-1006	24	13	deployed	deploy	VERB
cana-1006	24	14	and	and	CCONJ
cana-1006	24	15	relay	relay	VERB
cana-1006	24	16	it	it	PRON
cana-1006	24	17	to	to	ADP
cana-1006	24	18	the	the	DET
cana-1006	24	19	base	base	NOUN
cana-1006	24	20	station	station	NOUN
cana-1006	24	21	node	node	NOUN
cana-1006	24	22	[	[	X
cana-1006	24	23	2	2	NUM
cana-1006	24	24	]	]	PUNCT
cana-1006	24	25	.	.	PUNCT
cana-1006	25	1	with	with	ADP
cana-1006	25	2	the	the	DET
cana-1006	25	3	cryptographic	cryptographic	ADJ
cana-1006	25	4	security	security	NOUN
cana-1006	25	5	measures	measure	NOUN
cana-1006	25	6	the	the	DET
cana-1006	25	7	confidential	confidential	ADJ
cana-1006	25	8	information	information	NOUN
cana-1006	25	9	was	be	AUX
cana-1006	25	10	secured	secure	VERB
cana-1006	25	11	but	but	CCONJ
cana-1006	25	12	it	it	PRON
cana-1006	25	13	is	be	AUX
cana-1006	25	14	insufficient	insufficient	ADJ
cana-1006	25	15	to	to	PART
cana-1006	25	16	safeguard	safeguard	VERB
cana-1006	25	17	the	the	DET
cana-1006	25	18	data	datum	NOUN
cana-1006	25	19	.	.	PUNCT
cana-1006	26	1	thereby	thereby	ADV
cana-1006	26	2	,	,	PUNCT
cana-1006	26	3	the	the	DET
cana-1006	26	4	another	another	DET
cana-1006	26	5	functionality	functionality	NOUN
cana-1006	26	6	of	of	ADP
cana-1006	26	7	defensive	defensive	ADJ
cana-1006	26	8	technique	technique	NOUN
cana-1006	26	9	referred	refer	VERB
cana-1006	26	10	as	as	ADP
cana-1006	26	11	ids	id	NOUN
cana-1006	26	12	,	,	PUNCT
cana-1006	26	13	is	be	AUX
cana-1006	26	14	mailto:vmsravanthi@gmail.com	mailto:vmsravanthi@gmail.com	X
cana-1006	26	15	mailto:sunilmalchi1@gmail.com	mailto:sunilmalchi1@gmail.com	NOUN
cana-1006	26	16	communications	communication	NOUN
cana-1006	26	17	on	on	ADP
cana-1006	26	18	applied	apply	VERB
cana-1006	26	19	nonlinear	nonlinear	ADJ
cana-1006	26	20	analysis	analysis	NOUN
cana-1006	26	21	issn	issn	NOUN
cana-1006	26	22	:	:	PUNCT
cana-1006	26	23	1074	1074	NUM
cana-1006	26	24	-	-	PUNCT
cana-1006	26	25	133x	133x	NUM
cana-1006	26	26	vol	vol	NOUN
cana-1006	26	27	31	31	NUM
cana-1006	26	28	no	no	NOUN
cana-1006	26	29	.	.	PUNCT
cana-1006	27	1	5s	5s	NUM
cana-1006	27	2	(	(	PUNCT
cana-1006	27	3	2024	2024	NUM
cana-1006	27	4	)	)	PUNCT
cana-1006	27	5	119	119	NUM
cana-1006	28	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	28	2	necessary	necessary	ADJ
cana-1006	28	3	.	.	PUNCT
cana-1006	29	1	because	because	SCONJ
cana-1006	29	2	of	of	ADP
cana-1006	29	3	the	the	DET
cana-1006	29	4	benefits	benefit	NOUN
cana-1006	29	5	of	of	ADP
cana-1006	29	6	categorization	categorization	NOUN
cana-1006	29	7	,	,	PUNCT
cana-1006	29	8	selflearning	selflearning	NOUN
cana-1006	29	9	,	,	PUNCT
cana-1006	29	10	and	and	CCONJ
cana-1006	29	11	resilience	resilience	NOUN
cana-1006	29	12	,	,	PUNCT
cana-1006	29	13	nns	nns	PROPN
cana-1006	29	14	have	have	AUX
cana-1006	29	15	drawn	draw	VERB
cana-1006	29	16	a	a	DET
cana-1006	29	17	significant	significant	ADJ
cana-1006	29	18	number	number	NOUN
cana-1006	29	19	of	of	ADP
cana-1006	29	20	academics	academic	NOUN
cana-1006	29	21	to	to	PART
cana-1006	29	22	explore	explore	VERB
cana-1006	29	23	the	the	DET
cana-1006	29	24	intrusion	intrusion	NOUN
cana-1006	29	25	detection	detection	NOUN
cana-1006	29	26	algorithm	algorithm	NOUN
cana-1006	29	27	based	base	VERB
cana-1006	29	28	on	on	ADP
cana-1006	29	29	neural	neural	ADJ
cana-1006	29	30	network	network	NOUN
cana-1006	29	31	and	and	CCONJ
cana-1006	29	32	have	have	AUX
cana-1006	29	33	produced	produce	VERB
cana-1006	29	34	very	very	ADV
cana-1006	29	35	good	good	ADJ
cana-1006	29	36	results	result	NOUN
cana-1006	29	37	[	[	X
cana-1006	29	38	4	4	X
cana-1006	29	39	]	]	X
cana-1006	29	40	[	[	X
cana-1006	29	41	8	8	NUM
cana-1006	29	42	]	]	PUNCT
cana-1006	29	43	.	.	PUNCT
cana-1006	30	1	the	the	DET
cana-1006	30	2	effectiveness	effectiveness	NOUN
cana-1006	30	3	of	of	ADP
cana-1006	30	4	ml	ml	NOUN
cana-1006	30	5	and	and	CCONJ
cana-1006	30	6	dl	dl	PROPN
cana-1006	30	7	models	model	NOUN
cana-1006	30	8	in	in	ADP
cana-1006	30	9	satisfying	satisfy	VERB
cana-1006	30	10	security	security	NOUN
cana-1006	30	11	requirements	requirement	NOUN
cana-1006	30	12	has	have	AUX
cana-1006	30	13	been	be	AUX
cana-1006	30	14	established	establish	VERB
cana-1006	30	15	.	.	PUNCT
cana-1006	31	1	furthermore	furthermore	ADV
cana-1006	31	2	,	,	PUNCT
cana-1006	31	3	ml	ml	NOUN
cana-1006	31	4	techniques	technique	NOUN
cana-1006	31	5	find	find	VERB
cana-1006	31	6	patterns	pattern	NOUN
cana-1006	31	7	using	use	VERB
cana-1006	31	8	statistical	statistical	ADJ
cana-1006	31	9	ideas	idea	NOUN
cana-1006	31	10	.	.	PUNCT
cana-1006	32	1	dl	dl	PROPN
cana-1006	32	2	is	be	AUX
cana-1006	32	3	a	a	DET
cana-1006	32	4	more	more	ADV
cana-1006	32	5	sophisticated	sophisticated	ADJ
cana-1006	32	6	variation	variation	NOUN
cana-1006	32	7	of	of	ADP
cana-1006	32	8	ml	ml	NOUN
cana-1006	32	9	that	that	PRON
cana-1006	32	10	has	have	VERB
cana-1006	32	11	its	its	PRON
cana-1006	32	12	foundation	foundation	NOUN
cana-1006	32	13	on	on	ADP
cana-1006	32	14	ann	ann	PROPN
cana-1006	32	15	.	.	PUNCT
cana-1006	33	1	the	the	DET
cana-1006	33	2	dl	dl	PROPN
cana-1006	33	3	technique	technique	NOUN
cana-1006	33	4	is	be	AUX
cana-1006	33	5	an	an	DET
cana-1006	33	6	important	important	ADJ
cana-1006	33	7	process	process	NOUN
cana-1006	33	8	in	in	ADP
cana-1006	33	9	ai	ai	NOUN
cana-1006	33	10	that	that	PRON
cana-1006	33	11	is	be	AUX
cana-1006	33	12	used	use	VERB
cana-1006	33	13	to	to	PART
cana-1006	33	14	extract	extract	VERB
cana-1006	33	15	characteristics	characteristic	NOUN
cana-1006	33	16	from	from	ADP
cana-1006	33	17	data	datum	NOUN
cana-1006	33	18	[	[	X
cana-1006	33	19	9	9	NUM
cana-1006	33	20	]	]	PUNCT
cana-1006	33	21	.	.	PUNCT
cana-1006	34	1	to	to	PART
cana-1006	34	2	avoid	avoid	VERB
cana-1006	34	3	these	these	DET
cana-1006	34	4	difficulties	difficulty	NOUN
cana-1006	34	5	,	,	PUNCT
cana-1006	34	6	numerous	numerous	ADJ
cana-1006	34	7	idss	idss	NOUN
cana-1006	34	8	have	have	AUX
cana-1006	34	9	been	be	AUX
cana-1006	34	10	implemented	implement	VERB
cana-1006	34	11	to	to	PART
cana-1006	34	12	identify	identify	VERB
cana-1006	34	13	attacks	attack	NOUN
cana-1006	34	14	in	in	ADP
cana-1006	34	15	wsn	wsn	NOUN
cana-1006	34	16	including	include	VERB
cana-1006	34	17	maximum	maximum	ADJ
cana-1006	34	18	false	false	ADJ
cana-1006	34	19	alarm	alarm	NOUN
cana-1006	34	20	alert	alert	NOUN
cana-1006	34	21	,	,	PUNCT
cana-1006	34	22	low	low	ADJ
cana-1006	34	23	detection	detection	NOUN
cana-1006	34	24	accuracy	accuracy	NOUN
cana-1006	34	25	,	,	PUNCT
cana-1006	34	26	as	as	ADV
cana-1006	34	27	well	well	ADV
cana-1006	34	28	as	as	ADP
cana-1006	34	29	maximum	maximum	ADJ
cana-1006	34	30	processing	processing	NOUN
cana-1006	34	31	time	time	NOUN
cana-1006	34	32	,	,	PUNCT
cana-1006	34	33	still	still	ADV
cana-1006	34	34	they	they	PRON
cana-1006	34	35	are	be	AUX
cana-1006	34	36	suffering	suffer	VERB
cana-1006	34	37	.	.	PUNCT
cana-1006	35	1	moreover	moreover	ADV
cana-1006	35	2	,	,	PUNCT
cana-1006	35	3	the	the	DET
cana-1006	35	4	most	most	ADV
cana-1006	35	5	important	important	ADJ
cana-1006	35	6	restrictions	restriction	NOUN
cana-1006	35	7	in	in	ADP
cana-1006	35	8	wsns	wsns	NOUN
cana-1006	35	9	are	be	AUX
cana-1006	35	10	storage	storage	NOUN
cana-1006	35	11	space	space	NOUN
cana-1006	35	12	,	,	PUNCT
cana-1006	35	13	bandwidth	bandwidth	NOUN
cana-1006	35	14	,	,	PUNCT
cana-1006	35	15	and	and	CCONJ
cana-1006	35	16	power	power	NOUN
cana-1006	35	17	consumption	consumption	NOUN
cana-1006	35	18	.	.	PUNCT
cana-1006	36	1	mostly	mostly	ADV
cana-1006	36	2	,	,	PUNCT
cana-1006	36	3	the	the	DET
cana-1006	36	4	sensors	sensor	NOUN
cana-1006	36	5	are	be	AUX
cana-1006	36	6	placed	place	VERB
cana-1006	36	7	in	in	ADP
cana-1006	36	8	an	an	DET
cana-1006	36	9	unattended	unattended	ADJ
cana-1006	36	10	position	position	NOUN
cana-1006	36	11	where	where	SCONJ
cana-1006	36	12	the	the	DET
cana-1006	36	13	battery	battery	NOUN
cana-1006	36	14	recharge	recharge	NOUN
cana-1006	36	15	or	or	CCONJ
cana-1006	36	16	replacement	replacement	NOUN
cana-1006	36	17	becomes	become	VERB
cana-1006	36	18	impossible	impossible	ADJ
cana-1006	36	19	[	[	X
cana-1006	36	20	10	10	NUM
cana-1006	36	21	]	]	PUNCT
cana-1006	36	22	.	.	PUNCT
cana-1006	37	1	hence	hence	ADV
cana-1006	37	2	,	,	PUNCT
cana-1006	37	3	this	this	DET
cana-1006	37	4	research	research	NOUN
cana-1006	37	5	proposes	propose	VERB
cana-1006	37	6	novel	novel	ADJ
cana-1006	37	7	intrusion	intrusion	NOUN
cana-1006	37	8	detection	detection	NOUN
cana-1006	37	9	in	in	ADP
cana-1006	37	10	wsn	wsn	PROPN
cana-1006	37	11	with	with	ADP
cana-1006	37	12	improved	improved	ADJ
cana-1006	37	13	class	class	NOUN
cana-1006	37	14	imbalance	imbalance	NOUN
cana-1006	37	15	processing	processing	NOUN
cana-1006	37	16	.	.	PUNCT
cana-1006	38	1	the	the	DET
cana-1006	38	2	main	main	ADJ
cana-1006	38	3	contribution	contribution	NOUN
cana-1006	38	4	of	of	ADP
cana-1006	38	5	this	this	DET
cana-1006	38	6	work	work	NOUN
cana-1006	38	7	is	be	AUX
cana-1006	38	8	as	as	SCONJ
cana-1006	38	9	follows	follow	VERB
cana-1006	38	10	:	:	PUNCT
cana-1006	38	11	▪	▪	NOUN
cana-1006	38	12	proposing	propose	VERB
cana-1006	38	13	improved	improved	ADJ
cana-1006	38	14	data	datum	NOUN
cana-1006	38	15	imbalance	imbalance	NOUN
cana-1006	38	16	process	process	NOUN
cana-1006	38	17	to	to	PART
cana-1006	38	18	balance	balance	VERB
cana-1006	38	19	the	the	DET
cana-1006	38	20	data	datum	NOUN
cana-1006	38	21	with	with	ADP
cana-1006	38	22	smote	smote	ADJ
cana-1006	38	23	-	-	PUNCT
cana-1006	38	24	enn	enn	PROPN
cana-1006	38	25	and	and	CCONJ
cana-1006	38	26	tomek	tomek	PROPN
cana-1006	38	27	link	link	NOUN
cana-1006	38	28	algorithm	algorithm	NOUN
cana-1006	38	29	.	.	PUNCT
cana-1006	39	1	▪	▪	NOUN
cana-1006	39	2	proposing	propose	VERB
cana-1006	39	3	improved	improved	ADJ
cana-1006	39	4	correlation	correlation	NOUN
cana-1006	39	5	based	base	VERB
cana-1006	39	6	features	feature	NOUN
cana-1006	39	7	to	to	PART
cana-1006	39	8	extract	extract	VERB
cana-1006	39	9	the	the	DET
cana-1006	39	10	features	feature	NOUN
cana-1006	39	11	from	from	ADP
cana-1006	39	12	the	the	DET
cana-1006	39	13	pre	pre	ADJ
cana-1006	39	14	-	-	ADJ
cana-1006	39	15	processed	processed	ADJ
cana-1006	39	16	data	datum	NOUN
cana-1006	39	17	accompanied	accompany	VERB
cana-1006	39	18	with	with	ADP
cana-1006	39	19	entropy	entropy	NOUN
cana-1006	39	20	based	base	VERB
cana-1006	39	21	features	feature	NOUN
cana-1006	39	22	is	be	AUX
cana-1006	39	23	extracted	extract	VERB
cana-1006	39	24	.	.	PUNCT
cana-1006	40	1	the	the	DET
cana-1006	40	2	remaining	remain	VERB
cana-1006	40	3	part	part	NOUN
cana-1006	40	4	of	of	ADP
cana-1006	40	5	this	this	DET
cana-1006	40	6	research	research	NOUN
cana-1006	40	7	including	include	VERB
cana-1006	40	8	literature	literature	NOUN
cana-1006	40	9	review	review	NOUN
cana-1006	40	10	on	on	ADP
cana-1006	40	11	existing	exist	VERB
cana-1006	40	12	methods	method	NOUN
cana-1006	40	13	correspond	correspond	VERB
cana-1006	40	14	to	to	ADP
cana-1006	40	15	intrusion	intrusion	NOUN
cana-1006	40	16	detection	detection	NOUN
cana-1006	40	17	in	in	ADP
cana-1006	40	18	wsn	wsn	PROPN
cana-1006	40	19	are	be	AUX
cana-1006	40	20	explained	explain	VERB
cana-1006	40	21	in	in	ADP
cana-1006	40	22	section	section	NOUN
cana-1006	40	23	2	2	NUM
cana-1006	40	24	.	.	PUNCT
cana-1006	41	1	then	then	ADV
cana-1006	41	2	the	the	DET
cana-1006	41	3	proposed	propose	VERB
cana-1006	41	4	model	model	NOUN
cana-1006	41	5	of	of	ADP
cana-1006	41	6	intrusion	intrusion	NOUN
cana-1006	41	7	detection	detection	NOUN
cana-1006	41	8	in	in	ADP
cana-1006	41	9	wsn	wsn	PROPN
cana-1006	41	10	with	with	ADP
cana-1006	41	11	improved	improved	ADJ
cana-1006	41	12	class	class	NOUN
cana-1006	41	13	imbalance	imbalance	NOUN
cana-1006	41	14	processing	processing	NOUN
cana-1006	41	15	is	be	AUX
cana-1006	41	16	described	describe	VERB
cana-1006	41	17	in	in	ADP
cana-1006	41	18	section	section	NOUN
cana-1006	41	19	3	3	NUM
cana-1006	41	20	.	.	PUNCT
cana-1006	42	1	next	next	ADV
cana-1006	42	2	,	,	PUNCT
cana-1006	42	3	the	the	DET
cana-1006	42	4	results	result	NOUN
cana-1006	42	5	are	be	AUX
cana-1006	42	6	discussed	discuss	VERB
cana-1006	42	7	by	by	ADP
cana-1006	42	8	conducting	conduct	VERB
cana-1006	42	9	various	various	ADJ
cana-1006	42	10	experiments	experiment	NOUN
cana-1006	42	11	are	be	AUX
cana-1006	42	12	analyzed	analyze	VERB
cana-1006	42	13	in	in	ADP
cana-1006	42	14	section	section	NOUN
cana-1006	42	15	4	4	NUM
cana-1006	42	16	.	.	PUNCT
cana-1006	42	17	further	far	ADV
cana-1006	42	18	,	,	PUNCT
cana-1006	42	19	the	the	DET
cana-1006	42	20	conclusion	conclusion	NOUN
cana-1006	42	21	part	part	NOUN
cana-1006	42	22	is	be	AUX
cana-1006	42	23	concluded	conclude	VERB
cana-1006	42	24	in	in	ADP
cana-1006	42	25	section	section	NOUN
cana-1006	42	26	5	5	NUM
cana-1006	42	27	relevant	relevant	ADJ
cana-1006	42	28	to	to	ADP
cana-1006	42	29	proposed	propose	VERB
cana-1006	42	30	model	model	NOUN
cana-1006	42	31	.	.	PUNCT
cana-1006	43	1	2	2	X
cana-1006	43	2	.	.	X
cana-1006	43	3	literature	literature	NOUN
cana-1006	43	4	review	review	NOUN
cana-1006	43	5	in	in	ADP
cana-1006	43	6	2021	2021	NUM
cana-1006	43	7	,	,	PUNCT
cana-1006	43	8	safaldin	safaldin	ADJ
cana-1006	43	9	,	,	PUNCT
cana-1006	43	10	m.	m.	NOUN
cana-1006	43	11	,	,	PUNCT
cana-1006	43	12	et	et	NOUN
cana-1006	43	13	al	al	PROPN
cana-1006	44	1	[	[	X
cana-1006	44	2	1	1	X
cana-1006	44	3	]	]	PUNCT
cana-1006	44	4	have	have	AUX
cana-1006	44	5	suggested	suggest	VERB
cana-1006	44	6	improved	improved	ADJ
cana-1006	44	7	ids	id	NOUN
cana-1006	44	8	with	with	ADP
cana-1006	44	9	modified	modify	VERB
cana-1006	44	10	gwosvm	gwosvm	NOUN
cana-1006	44	11	.	.	PUNCT
cana-1006	45	1	the	the	DET
cana-1006	45	2	proposed	propose	VERB
cana-1006	45	3	model	model	NOUN
cana-1006	45	4	intended	intend	VERB
cana-1006	45	5	to	to	PART
cana-1006	45	6	enhance	enhance	VERB
cana-1006	45	7	attack	attack	NOUN
cana-1006	45	8	detection	detection	NOUN
cana-1006	45	9	reliability	reliability	NOUN
cana-1006	45	10	and	and	CCONJ
cana-1006	45	11	rate	rate	NOUN
cana-1006	45	12	of	of	ADP
cana-1006	45	13	identification	identification	NOUN
cana-1006	45	14	while	while	SCONJ
cana-1006	45	15	decreasing	decrease	VERB
cana-1006	45	16	the	the	DET
cana-1006	45	17	duration	duration	NOUN
cana-1006	45	18	of	of	ADP
cana-1006	45	19	processing	processing	NOUN
cana-1006	45	20	in	in	ADP
cana-1006	45	21	the	the	DET
cana-1006	45	22	wsn	wsn	PROPN
cana-1006	45	23	system	system	NOUN
cana-1006	45	24	.	.	PUNCT
cana-1006	46	1	this	this	PRON
cana-1006	46	2	can	can	AUX
cana-1006	46	3	be	be	AUX
cana-1006	46	4	performed	perform	VERB
cana-1006	46	5	by	by	ADP
cana-1006	46	6	lowering	lower	VERB
cana-1006	46	7	false	false	ADJ
cana-1006	46	8	alarm	alarm	NOUN
cana-1006	46	9	rates	rate	NOUN
cana-1006	46	10	and	and	CCONJ
cana-1006	46	11	the	the	DET
cana-1006	46	12	features	feature	NOUN
cana-1006	46	13	set	set	VERB
cana-1006	46	14	generated	generate	VERB
cana-1006	46	15	through	through	ADP
cana-1006	46	16	idss	idss	NOUN
cana-1006	46	17	in	in	ADP
cana-1006	46	18	the	the	DET
cana-1006	46	19	wsn	wsn	PROPN
cana-1006	46	20	scenario	scenario	NOUN
cana-1006	46	21	.	.	PUNCT
cana-1006	47	1	as	as	ADP
cana-1006	47	2	a	a	DET
cana-1006	47	3	result	result	NOUN
cana-1006	47	4	,	,	PUNCT
cana-1006	47	5	the	the	DET
cana-1006	47	6	presented	present	VERB
cana-1006	47	7	model	model	NOUN
cana-1006	47	8	gwosvmids	gwosvmid	NOUN
cana-1006	47	9	outperformed	outperform	VERB
cana-1006	47	10	every	every	DET
cana-1006	47	11	one	one	NUM
cana-1006	47	12	of	of	ADP
cana-1006	47	13	the	the	DET
cana-1006	47	14	presented	present	VERB
cana-1006	47	15	and	and	CCONJ
cana-1006	47	16	scrutinized	scrutinize	VERB
cana-1006	47	17	algorithms	algorithm	NOUN
cana-1006	47	18	.	.	PUNCT
cana-1006	48	1	in	in	ADP
cana-1006	48	2	2021	2021	NUM
cana-1006	48	3	,	,	PUNCT
cana-1006	48	4	maheswari	maheswari	PROPN
cana-1006	48	5	,	,	PUNCT
cana-1006	48	6	m.	m.	NOUN
cana-1006	48	7	,	,	PUNCT
cana-1006	48	8	&	&	CCONJ
cana-1006	48	9	karthika	karthika	PROPN
cana-1006	48	10	,	,	PUNCT
cana-1006	48	11	r.a	r.a	PROPN
cana-1006	48	12	.	.	PROPN
cana-1006	48	13	,	,	PUNCT
cana-1006	48	14	[	[	X
cana-1006	48	15	2	2	X
cana-1006	48	16	]	]	PUNCT
cana-1006	48	17	have	have	AUX
cana-1006	48	18	developed	develop	VERB
cana-1006	48	19	a	a	DET
cana-1006	48	20	revolutionary	revolutionary	ADJ
cana-1006	48	21	safe	safe	ADJ
cana-1006	48	22	uneven	uneven	ADJ
cana-1006	48	23	clustering	clustering	NOUN
cana-1006	48	24	technique	technique	NOUN
cana-1006	48	25	with	with	ADP
cana-1006	48	26	detection	detection	NOUN
cana-1006	48	27	of	of	ADP
cana-1006	48	28	intrusion	intrusion	NOUN
cana-1006	48	29	that	that	PRON
cana-1006	48	30	accomplished	accomplish	VERB
cana-1006	48	31	qos	qos	NOUN
cana-1006	48	32	metrics	metric	NOUN
cana-1006	48	33	such	such	ADJ
cana-1006	48	34	as	as	ADP
cana-1006	48	35	longevity	longevity	NOUN
cana-1006	48	36	,	,	PUNCT
cana-1006	48	37	energy	energy	NOUN
cana-1006	48	38	,	,	PUNCT
cana-1006	48	39	and	and	CCONJ
cana-1006	48	40	security	security	NOUN
cana-1006	48	41	.	.	PUNCT
cana-1006	49	1	moreover	moreover	ADV
cana-1006	49	2	,	,	PUNCT
cana-1006	49	3	an	an	DET
cana-1006	49	4	adaptive	adaptive	ADJ
cana-1006	49	5	neural	neural	ADJ
cana-1006	49	6	fcm	fcm	PROPN
cana-1006	49	7	was	be	AUX
cana-1006	49	8	employed	employ	VERB
cana-1006	49	9	to	to	PART
cana-1006	49	10	select	select	VERB
cana-1006	49	11	the	the	DET
cana-1006	49	12	tchs	tch	NOUN
cana-1006	49	13	based	base	VERB
cana-1006	49	14	on	on	ADP
cana-1006	49	15	three	three	NUM
cana-1006	49	16	constraints	constraint	NOUN
cana-1006	49	17	comprises	comprise	NOUN
cana-1006	49	18	of	of	ADP
cana-1006	49	19	distance	distance	NOUN
cana-1006	49	20	to	to	ADP
cana-1006	49	21	bs	bs	NOUN
cana-1006	49	22	,	,	PUNCT
cana-1006	49	23	distance	distance	NOUN
cana-1006	49	24	to	to	ADP
cana-1006	49	25	neighbours	neighbour	NOUN
cana-1006	49	26	,	,	PUNCT
cana-1006	49	27	and	and	CCONJ
cana-1006	49	28	residual	residual	ADJ
cana-1006	49	29	energy	energy	NOUN
cana-1006	49	30	.	.	PUNCT
cana-1006	50	1	further	far	ADV
cana-1006	50	2	,	,	PUNCT
cana-1006	50	3	the	the	DET
cana-1006	50	4	tchs	tch	NOUN
cana-1006	50	5	then	then	ADV
cana-1006	50	6	contend	contend	VERB
cana-1006	50	7	for	for	ADP
cana-1006	50	8	the	the	DET
cana-1006	50	9	position	position	NOUN
cana-1006	50	10	of	of	ADP
cana-1006	50	11	chs	ch	NOUN
cana-1006	50	12	,	,	PUNCT
cana-1006	50	13	and	and	CCONJ
cana-1006	50	14	optimal	optimal	ADJ
cana-1006	50	15	chs	ch	NOUN
cana-1006	50	16	were	be	AUX
cana-1006	50	17	picked	pick	VERB
cana-1006	50	18	via	via	ADP
cana-1006	50	19	dho	dho	PROPN
cana-1006	50	20	method	method	PROPN
cana-1006	50	21	.	.	PUNCT
cana-1006	51	1	in	in	ADP
cana-1006	51	2	2022	2022	NUM
cana-1006	51	3	,	,	PUNCT
cana-1006	51	4	zhang	zhang	PROPN
cana-1006	51	5	,	,	PUNCT
cana-1006	51	6	t.	t.	PROPN
cana-1006	51	7	,	,	PUNCT
cana-1006	51	8	et	et	PROPN
cana-1006	51	9	al	al	PROPN
cana-1006	52	1	[	[	X
cana-1006	52	2	3	3	X
cana-1006	52	3	]	]	PUNCT
cana-1006	52	4	have	have	AUX
cana-1006	52	5	implemented	implement	VERB
cana-1006	52	6	the	the	DET
cana-1006	52	7	tvpipso	tvpipso	PROPN
cana-1006	52	8	technique	technique	NOUN
cana-1006	52	9	,	,	PUNCT
cana-1006	52	10	an	an	DET
cana-1006	52	11	evolutionary	evolutionary	ADJ
cana-1006	52	12	based	base	VERB
cana-1006	52	13	strategy	strategy	NOUN
cana-1006	52	14	for	for	ADP
cana-1006	52	15	low	low	ADJ
cana-1006	52	16	complexity	complexity	NOUN
cana-1006	52	17	intrusion	intrusion	NOUN
cana-1006	52	18	detection	detection	NOUN
cana-1006	52	19	in	in	ADP
cana-1006	52	20	wsn	wsn	PROPN
cana-1006	52	21	.	.	PUNCT
cana-1006	53	1	furthermore	furthermore	ADV
cana-1006	53	2	,	,	PUNCT
cana-1006	53	3	the	the	DET
cana-1006	53	4	pca	pca	NOUN
cana-1006	53	5	was	be	AUX
cana-1006	53	6	used	use	VERB
cana-1006	53	7	to	to	PART
cana-1006	53	8	minimize	minimize	VERB
cana-1006	53	9	size	size	NOUN
cana-1006	53	10	of	of	ADP
cana-1006	53	11	the	the	DET
cana-1006	53	12	dataset	dataset	NOUN
cana-1006	53	13	with	with	ADP
cana-1006	53	14	suppressing	suppress	VERB
cana-1006	53	15	the	the	DET
cana-1006	53	16	data	datum	NOUN
cana-1006	53	17	to	to	PART
cana-1006	53	18	save	save	VERB
cana-1006	53	19	energy	energy	NOUN
cana-1006	53	20	.	.	PUNCT
cana-1006	54	1	also	also	ADV
cana-1006	54	2	,	,	PUNCT
cana-1006	54	3	high	high	ADJ
cana-1006	54	4	detection	detection	NOUN
cana-1006	54	5	accuracy	accuracy	NOUN
cana-1006	54	6	was	be	AUX
cana-1006	54	7	assured	assure	VERB
cana-1006	54	8	with	with	ADP
cana-1006	54	9	an	an	DET
cana-1006	54	10	ids	id	NOUN
cana-1006	54	11	based	base	VERB
cana-1006	54	12	on	on	ADP
cana-1006	54	13	svm	svm	PROPN
cana-1006	54	14	.	.	PROPN
cana-1006	55	1	besides	besides	SCONJ
cana-1006	55	2	,	,	PUNCT
cana-1006	55	3	the	the	DET
cana-1006	55	4	convergences	convergence	NOUN
cana-1006	55	5	speed	speed	NOUN
cana-1006	55	6	of	of	ADP
cana-1006	55	7	the	the	DET
cana-1006	55	8	ids	id	NOUN
cana-1006	55	9	was	be	AUX
cana-1006	55	10	progressed	progress	VERB
cana-1006	55	11	with	with	ADP
cana-1006	55	12	the	the	DET
cana-1006	55	13	suggested	suggest	VERB
cana-1006	55	14	model	model	NOUN
cana-1006	55	15	.	.	PUNCT
cana-1006	56	1	in	in	ADP
cana-1006	56	2	2023	2023	NUM
cana-1006	56	3	,	,	PUNCT
cana-1006	56	4	salmi	salmi	PROPN
cana-1006	56	5	,	,	PUNCT
cana-1006	56	6	s.	s.	PROPN
cana-1006	56	7	,	,	PUNCT
cana-1006	56	8	&	&	CCONJ
cana-1006	56	9	oughdir	oughdir	PROPN
cana-1006	56	10	,	,	PUNCT
cana-1006	56	11	l.	l.	PROPN
cana-1006	56	12	,	,	PUNCT
cana-1006	56	13	[	[	X
cana-1006	56	14	4	4	X
cana-1006	56	15	]	]	PUNCT
cana-1006	56	16	have	have	AUX
cana-1006	56	17	introduced	introduce	VERB
cana-1006	56	18	deep	deep	ADJ
cana-1006	56	19	learning	learning	NOUN
cana-1006	56	20	based	base	VERB
cana-1006	56	21	intrusion	intrusion	NOUN
cana-1006	56	22	detection	detection	NOUN
cana-1006	56	23	systems	system	NOUN
cana-1006	56	24	.	.	PUNCT
cana-1006	57	1	communications	communication	NOUN
cana-1006	57	2	on	on	ADP
cana-1006	57	3	applied	apply	VERB
cana-1006	57	4	nonlinear	nonlinear	ADJ
cana-1006	57	5	analysis	analysis	NOUN
cana-1006	57	6	issn	issn	NOUN
cana-1006	57	7	:	:	PUNCT
cana-1006	57	8	1074	1074	NUM
cana-1006	57	9	-	-	PUNCT
cana-1006	57	10	133x	133x	NUM
cana-1006	57	11	vol	vol	NOUN
cana-1006	57	12	31	31	NUM
cana-1006	57	13	no	no	NOUN
cana-1006	57	14	.	.	PUNCT
cana-1006	58	1	5s	5s	NUM
cana-1006	58	2	(	(	PUNCT
cana-1006	58	3	2024	2024	NUM
cana-1006	58	4	)	)	PUNCT
cana-1006	58	5	120	120	NUM
cana-1006	58	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	58	7	these	these	DET
cana-1006	58	8	systems	system	NOUN
cana-1006	58	9	were	be	AUX
cana-1006	58	10	trained	train	VERB
cana-1006	58	11	on	on	ADP
cana-1006	58	12	a	a	DET
cana-1006	58	13	wsn	wsn	ADJ
cana-1006	58	14	-	-	ADJ
cana-1006	58	15	ds	ds	ADJ
cana-1006	58	16	specific	specific	ADJ
cana-1006	58	17	dataset	dataset	NOUN
cana-1006	58	18	to	to	PART
cana-1006	58	19	detect	detect	VERB
cana-1006	58	20	four	four	NUM
cana-1006	58	21	forms	form	NOUN
cana-1006	58	22	of	of	ADP
cana-1006	58	23	dos	do	NOUN
cana-1006	58	24	assaults	assault	NOUN
cana-1006	58	25	that	that	PRON
cana-1006	58	26	affect	affect	VERB
cana-1006	58	27	wsns	wsns	NOUN
cana-1006	58	28	.	.	PUNCT
cana-1006	59	1	the	the	DET
cana-1006	59	2	grayhole	grayhole	PROPN
cana-1006	59	3	,	,	PUNCT
cana-1006	59	4	blackhole	blackhole	NOUN
cana-1006	59	5	,	,	PUNCT
cana-1006	59	6	flooding	flooding	NOUN
cana-1006	59	7	,	,	PUNCT
cana-1006	59	8	and	and	CCONJ
cana-1006	59	9	scheduling	scheduling	NOUN
cana-1006	59	10	assaults	assault	NOUN
cana-1006	59	11	were	be	AUX
cana-1006	59	12	among	among	ADP
cana-1006	59	13	them	they	PRON
cana-1006	59	14	.	.	PUNCT
cana-1006	60	1	finally	finally	ADV
cana-1006	60	2	,	,	PUNCT
cana-1006	60	3	the	the	DET
cana-1006	60	4	proposed	propose	VERB
cana-1006	60	5	approach	approach	NOUN
cana-1006	60	6	assessed	assess	VERB
cana-1006	60	7	and	and	CCONJ
cana-1006	60	8	contrasted	contrast	VERB
cana-1006	60	9	the	the	DET
cana-1006	60	10	outcomes	outcome	NOUN
cana-1006	60	11	and	and	CCONJ
cana-1006	60	12	discussed	discuss	VERB
cana-1006	60	13	potential	potential	ADJ
cana-1006	60	14	future	future	ADJ
cana-1006	60	15	projects	project	NOUN
cana-1006	60	16	.	.	PUNCT
cana-1006	61	1	in	in	ADP
cana-1006	61	2	2020	2020	NUM
cana-1006	61	3	,	,	PUNCT
cana-1006	61	4	zhang	zhang	PROPN
cana-1006	61	5	,	,	PUNCT
cana-1006	61	6	w.	w.	PROPN
cana-1006	61	7	,	,	PUNCT
cana-1006	61	8	et	et	PROPN
cana-1006	61	9	al	al	PROPN
cana-1006	62	1	[	[	X
cana-1006	62	2	5	5	NUM
cana-1006	62	3	]	]	PUNCT
cana-1006	62	4	have	have	AUX
cana-1006	62	5	proposed	propose	VERB
cana-1006	62	6	an	an	DET
cana-1006	62	7	organizational	organizational	ADJ
cana-1006	62	8	intrusion	intrusion	NOUN
cana-1006	62	9	detection	detection	NOUN
cana-1006	62	10	approach	approach	NOUN
cana-1006	62	11	that	that	SCONJ
cana-1006	62	12	groups	group	NOUN
cana-1006	62	13	nodes	nod	VERB
cana-1006	62	14	in	in	ADP
cana-1006	62	15	a	a	DET
cana-1006	62	16	wsn	wsn	NOUN
cana-1006	62	17	based	base	VERB
cana-1006	62	18	on	on	ADP
cana-1006	62	19	their	their	PRON
cana-1006	62	20	roles	role	NOUN
cana-1006	62	21	.	.	PUNCT
cana-1006	63	1	furthermore	furthermore	ADV
cana-1006	63	2	,	,	PUNCT
cana-1006	63	3	in	in	ADP
cana-1006	63	4	order	order	NOUN
cana-1006	63	5	to	to	PART
cana-1006	63	6	increase	increase	VERB
cana-1006	63	7	the	the	DET
cana-1006	63	8	detection	detection	NOUN
cana-1006	63	9	precision	precision	NOUN
cana-1006	63	10	of	of	ADP
cana-1006	63	11	unusual	unusual	ADJ
cana-1006	63	12	activities	activity	NOUN
cana-1006	63	13	in	in	ADP
cana-1006	63	14	ids	id	NOUN
cana-1006	63	15	while	while	SCONJ
cana-1006	63	16	lowering	lower	VERB
cana-1006	63	17	the	the	DET
cana-1006	63	18	false	false	ADJ
cana-1006	63	19	alarm	alarm	NOUN
cana-1006	63	20	rate	rate	NOUN
cana-1006	63	21	,	,	PUNCT
cana-1006	63	22	the	the	DET
cana-1006	63	23	use	use	NOUN
cana-1006	63	24	of	of	ADP
cana-1006	63	25	the	the	DET
cana-1006	63	26	classification	classification	NOUN
cana-1006	63	27	algorithm	algorithm	NOUN
cana-1006	63	28	of	of	ADP
cana-1006	63	29	k	k	PROPN
cana-1006	63	30	-	-	PROPN
cana-1006	63	31	elm	elm	PROPN
cana-1006	63	32	,	,	PUNCT
cana-1006	63	33	based	base	VERB
cana-1006	63	34	on	on	ADP
cana-1006	63	35	the	the	DET
cana-1006	63	36	mercer	mercer	PROPN
cana-1006	63	37	property	property	NOUN
cana-1006	63	38	,	,	PUNCT
cana-1006	63	39	was	be	AUX
cana-1006	63	40	considered	consider	VERB
cana-1006	63	41	in	in	ADP
cana-1006	63	42	research	research	NOUN
cana-1006	63	43	to	to	PART
cana-1006	63	44	synthesize	synthesize	VERB
cana-1006	63	45	multikernel	multikernel	ADJ
cana-1006	63	46	functions	function	NOUN
cana-1006	63	47	.	.	PUNCT
cana-1006	64	1	by	by	ADP
cana-1006	64	2	evaluating	evaluate	VERB
cana-1006	64	3	and	and	CCONJ
cana-1006	64	4	implementing	implement	VERB
cana-1006	64	5	the	the	DET
cana-1006	64	6	multikernel	multikernel	PROPN
cana-1006	64	7	function	function	NOUN
cana-1006	64	8	,	,	PUNCT
cana-1006	64	9	the	the	DET
cana-1006	64	10	proposed	propose	VERB
cana-1006	64	11	model	model	NOUN
cana-1006	64	12	achieved	achieve	VERB
cana-1006	64	13	the	the	DET
cana-1006	64	14	best	good	ADJ
cana-1006	64	15	linear	linear	ADJ
cana-1006	64	16	combination	combination	NOUN
cana-1006	64	17	and	and	CCONJ
cana-1006	64	18	created	create	VERB
cana-1006	64	19	a	a	DET
cana-1006	64	20	multi	multi	ADJ
cana-1006	64	21	-	-	ADJ
cana-1006	64	22	k	k	NOUN
cana-1006	64	23	-	-	NOUN
cana-1006	64	24	elm	elm	NOUN
cana-1006	64	25	for	for	ADP
cana-1006	64	26	ids	id	NOUN
cana-1006	64	27	.	.	PUNCT
cana-1006	65	1	3	3	X
cana-1006	65	2	.	.	X
cana-1006	65	3	implementing	implement	VERB
cana-1006	65	4	a	a	DET
cana-1006	65	5	novel	novel	ADJ
cana-1006	65	6	intrusion	intrusion	NOUN
cana-1006	65	7	detection	detection	NOUN
cana-1006	65	8	in	in	ADP
cana-1006	65	9	wsn	wsn	PROPN
cana-1006	65	10	with	with	ADP
cana-1006	65	11	improved	improved	ADJ
cana-1006	65	12	class	class	NOUN
cana-1006	65	13	imbalance	imbalance	NOUN
cana-1006	65	14	process	process	NOUN
cana-1006	65	15	a.	a.	NOUN
cana-1006	65	16	proposed	propose	VERB
cana-1006	65	17	architect	architect	NOUN
cana-1006	65	18	of	of	ADP
cana-1006	65	19	intrusion	intrusion	NOUN
cana-1006	65	20	detection	detection	NOUN
cana-1006	65	21	in	in	ADP
cana-1006	65	22	wsn	wsn	PROPN
cana-1006	65	23	wsns	wsns	PROPN
cana-1006	65	24	are	be	AUX
cana-1006	65	25	a	a	DET
cana-1006	65	26	heterogeneous	heterogeneous	ADJ
cana-1006	65	27	system	system	NOUN
cana-1006	65	28	made	make	VERB
cana-1006	65	29	up	up	ADP
cana-1006	65	30	of	of	ADP
cana-1006	65	31	tiny	tiny	ADJ
cana-1006	65	32	actuators	actuator	NOUN
cana-1006	65	33	and	and	CCONJ
cana-1006	65	34	sensors	sensor	NOUN
cana-1006	65	35	with	with	ADP
cana-1006	65	36	general	general	ADJ
cana-1006	65	37	-	-	PUNCT
cana-1006	65	38	purpose	purpose	NOUN
cana-1006	65	39	computer	computer	NOUN
cana-1006	65	40	units	unit	NOUN
cana-1006	65	41	.	.	PUNCT
cana-1006	66	1	wsns	wsns	PROPN
cana-1006	66	2	offer	offer	VERB
cana-1006	66	3	several	several	ADJ
cana-1006	66	4	advantages	advantage	NOUN
cana-1006	66	5	,	,	PUNCT
cana-1006	66	6	mainly	mainly	ADV
cana-1006	66	7	,	,	PUNCT
cana-1006	66	8	the	the	DET
cana-1006	66	9	capability	capability	NOUN
cana-1006	66	10	of	of	ADP
cana-1006	66	11	transforming	transform	VERB
cana-1006	66	12	raw	raw	ADJ
cana-1006	66	13	data	datum	NOUN
cana-1006	66	14	into	into	ADP
cana-1006	66	15	understandable	understandable	ADJ
cana-1006	66	16	categorized	categorize	VERB
cana-1006	66	17	information	information	NOUN
cana-1006	66	18	.	.	PUNCT
cana-1006	67	1	moreover	moreover	ADV
cana-1006	67	2	,	,	PUNCT
cana-1006	67	3	while	while	SCONJ
cana-1006	67	4	modelling	model	VERB
cana-1006	67	5	the	the	DET
cana-1006	67	6	wsn	wsn	NOUN
cana-1006	67	7	,	,	PUNCT
cana-1006	67	8	the	the	DET
cana-1006	67	9	key	key	PROPN
cana-1006	67	10	b.	b.	PROPN
cana-1006	67	11	pre	pre	ADJ
cana-1006	67	12	-	-	ADJ
cana-1006	67	13	processing	processing	NOUN
cana-1006	67	14	consider	consider	VERB
cana-1006	67	15	the	the	DET
cana-1006	67	16	input	input	NOUN
cana-1006	67	17	data	data	NOUN
cana-1006	67	18	d	d	NOUN
cana-1006	67	19	is	be	AUX
cana-1006	67	20	subjected	subject	VERB
cana-1006	67	21	to	to	ADP
cana-1006	67	22	the	the	DET
cana-1006	67	23	preprocessing	preprocessing	NOUN
cana-1006	67	24	phase	phase	NOUN
cana-1006	67	25	to	to	PART
cana-1006	67	26	obtain	obtain	VERB
cana-1006	67	27	error	error	NOUN
cana-1006	67	28	free	free	ADJ
cana-1006	67	29	and	and	CCONJ
cana-1006	67	30	denoised	denoised	ADJ
cana-1006	67	31	data	datum	NOUN
cana-1006	67	32	.	.	PUNCT
cana-1006	68	1	in	in	ADP
cana-1006	68	2	this	this	DET
cana-1006	68	3	work	work	NOUN
cana-1006	68	4	,	,	PUNCT
cana-1006	68	5	improved	improve	VERB
cana-1006	68	6	class	class	NOUN
cana-1006	68	7	imbalance	imbalance	NOUN
cana-1006	68	8	process	process	NOUN
cana-1006	68	9	is	be	AUX
cana-1006	68	10	employs	employ	NOUN
cana-1006	68	11	to	to	PART
cana-1006	68	12	balance	balance	VERB
cana-1006	68	13	the	the	DET
cana-1006	68	14	raw	raw	ADJ
cana-1006	68	15	data	datum	NOUN
cana-1006	68	16	.	.	PUNCT
cana-1006	69	1	for	for	ADP
cana-1006	69	2	the	the	DET
cana-1006	69	3	improved	improved	ADJ
cana-1006	69	4	class	class	NOUN
cana-1006	69	5	imbalance	imbalance	NOUN
cana-1006	69	6	process	process	NOUN
cana-1006	69	7	,	,	PUNCT
cana-1006	69	8	a	a	DET
cana-1006	69	9	novel	novel	ADJ
cana-1006	69	10	smote	smote	NOUN
cana-1006	69	11	-	-	PUNCT
cana-1006	69	12	enn	enn	PROPN
cana-1006	69	13	and	and	CCONJ
cana-1006	69	14	tomek	tomek	PROPN
cana-1006	69	15	link	link	NOUN
cana-1006	69	16	algorithm	algorithm	PROPN
cana-1006	69	17	is	be	AUX
cana-1006	69	18	deployed	deploy	VERB
cana-1006	69	19	.	.	PUNCT
cana-1006	70	1	fig	fig	NOUN
cana-1006	70	2	.	.	PUNCT
cana-1006	71	1	1	1	X
cana-1006	71	2	.	.	X
cana-1006	71	3	entire	entire	ADJ
cana-1006	71	4	process	process	NOUN
cana-1006	71	5	of	of	ADP
cana-1006	71	6	proposed	propose	VERB
cana-1006	71	7	model	model	NOUN
cana-1006	71	8	communications	communication	NOUN
cana-1006	71	9	on	on	ADP
cana-1006	71	10	applied	apply	VERB
cana-1006	71	11	nonlinear	nonlinear	ADJ
cana-1006	71	12	analysis	analysis	NOUN
cana-1006	71	13	issn	issn	NOUN
cana-1006	71	14	:	:	PUNCT
cana-1006	71	15	1074	1074	NUM
cana-1006	71	16	-	-	PUNCT
cana-1006	71	17	133x	133x	NUM
cana-1006	71	18	vol	vol	NOUN
cana-1006	71	19	31	31	NUM
cana-1006	71	20	no	no	NOUN
cana-1006	71	21	.	.	PUNCT
cana-1006	72	1	5s	5s	NUM
cana-1006	72	2	(	(	PUNCT
cana-1006	72	3	2024	2024	NUM
cana-1006	72	4	)	)	PUNCT
cana-1006	72	5	121	121	NUM
cana-1006	72	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	72	7	1	1	NUM
cana-1006	72	8	)	)	PUNCT
cana-1006	72	9	smote	smote	NOUN
cana-1006	72	10	-	-	PUNCT
cana-1006	72	11	enn	enn	PROPN
cana-1006	72	12	and	and	CCONJ
cana-1006	72	13	tomek	tomek	PROPN
cana-1006	72	14	link	link	PROPN
cana-1006	72	15	algorithm	algorithm	PROPN
cana-1006	72	16	the	the	DET
cana-1006	72	17	input	input	NOUN
cana-1006	72	18	data	data	NOUN
cana-1006	72	19	d	d	NOUN
cana-1006	72	20	is	be	AUX
cana-1006	72	21	subjected	subject	VERB
cana-1006	72	22	to	to	ADP
cana-1006	72	23	the	the	DET
cana-1006	72	24	smote	smote	NOUN
cana-1006	72	25	-	-	PUNCT
cana-1006	72	26	enn	enn	PROPN
cana-1006	72	27	and	and	CCONJ
cana-1006	72	28	tomek	tomek	PROPN
cana-1006	72	29	link	link	NOUN
cana-1006	72	30	algorithm	algorithm	NOUN
cana-1006	73	1	[	[	X
cana-1006	73	2	12	12	NUM
cana-1006	73	3	]	]	PUNCT
cana-1006	73	4	,	,	PUNCT
cana-1006	73	5	in	in	ADP
cana-1006	73	6	which	which	PRON
cana-1006	73	7	the	the	DET
cana-1006	73	8	following	follow	VERB
cana-1006	73	9	processes	process	NOUN
cana-1006	73	10	are	be	AUX
cana-1006	73	11	performed	perform	VERB
cana-1006	73	12	.	.	PUNCT
cana-1006	74	1	let	let	VERB
cana-1006	74	2	f	f	NOUN
cana-1006	74	3	(	(	PUNCT
cana-1006	74	4	d)be	d)be	NOUN
cana-1006	74	5	the	the	DET
cana-1006	74	6	function	function	NOUN
cana-1006	74	7	,	,	PUNCT
cana-1006	74	8	which	which	PRON
cana-1006	74	9	resolves	resolve	VERB
cana-1006	74	10	the	the	DET
cana-1006	74	11	order	order	NOUN
cana-1006	74	12	.	.	PUNCT
cana-1006	75	1	initially	initially	ADV
cana-1006	75	2	,	,	PUNCT
cana-1006	75	3	the	the	DET
cana-1006	75	4	degree	degree	NOUN
cana-1006	75	5	of	of	ADP
cana-1006	75	6	noise	noise	NOUN
cana-1006	75	7	and	and	CCONJ
cana-1006	75	8	overlapping	overlapping	NOUN
cana-1006	75	9	is	be	AUX
cana-1006	75	10	computed	compute	VERB
cana-1006	75	11	with	with	ADP
cana-1006	75	12	kdn	kdn	NOUN
cana-1006	75	13	and	and	CCONJ
cana-1006	75	14	lda	lda	PROPN
cana-1006	75	15	,	,	PUNCT
cana-1006	75	16	respectively	respectively	ADV
cana-1006	75	17	.	.	PUNCT
cana-1006	76	1	then	then	ADV
cana-1006	76	2	it	it	PRON
cana-1006	76	3	finalize	finalize	VERB
cana-1006	76	4	the	the	DET
cana-1006	76	5	outcome	outcome	NOUN
cana-1006	76	6	based	base	VERB
cana-1006	76	7	on	on	ADP
cana-1006	76	8	noise	noise	NOUN
cana-1006	76	9	and	and	CCONJ
cana-1006	76	10	overlap	overlap	NOUN
cana-1006	76	11	value	value	NOUN
cana-1006	76	12	.	.	PUNCT
cana-1006	77	1	when	when	SCONJ
cana-1006	77	2	the	the	DET
cana-1006	77	3	noise	noise	NOUN
cana-1006	77	4	is	be	AUX
cana-1006	77	5	higher	high	ADJ
cana-1006	77	6	than	than	ADP
cana-1006	77	7	the	the	DET
cana-1006	77	8	overlap	overlap	NOUN
cana-1006	77	9	,	,	PUNCT
cana-1006	77	10	then	then	ADV
cana-1006	77	11	the	the	DET
cana-1006	77	12	function	function	NOUN
cana-1006	77	13	of	of	ADP
cana-1006	77	14	order	order	NOUN
cana-1006	77	15	decision	decision	NOUN
cana-1006	77	16	is	be	AUX
cana-1006	77	17	resultant	resultant	VERB
cana-1006	77	18	as	as	ADP
cana-1006	77	19	1	1	NUM
cana-1006	77	20	.	.	PUNCT
cana-1006	78	1	on	on	ADP
cana-1006	78	2	the	the	DET
cana-1006	78	3	other	other	ADJ
cana-1006	78	4	hand	hand	NOUN
cana-1006	78	5	,	,	PUNCT
cana-1006	78	6	when	when	SCONJ
cana-1006	78	7	the	the	DET
cana-1006	78	8	noise	noise	NOUN
cana-1006	78	9	is	be	AUX
cana-1006	78	10	lesser	less	ADJ
cana-1006	78	11	than	than	ADP
cana-1006	78	12	the	the	DET
cana-1006	78	13	overlap	overlap	NOUN
cana-1006	78	14	,	,	PUNCT
cana-1006	78	15	it	it	PRON
cana-1006	78	16	is	be	AUX
cana-1006	78	17	resultant	resultant	VERB
cana-1006	78	18	as	as	ADP
cana-1006	78	19	0	0	NUM
cana-1006	78	20	.	.	PUNCT
cana-1006	79	1	then	then	ADV
cana-1006	79	2	the	the	DET
cana-1006	79	3	resampling	resample	VERB
cana-1006	79	4	method	method	NOUN
cana-1006	79	5	with	with	ADP
cana-1006	79	6	their	their	PRON
cana-1006	79	7	ratio	ratio	NOUN
cana-1006	79	8	and	and	CCONJ
cana-1006	79	9	order	order	NOUN
cana-1006	79	10	are	be	AUX
cana-1006	79	11	computed	compute	VERB
cana-1006	79	12	according	accord	VERB
cana-1006	79	13	to	to	ADP
cana-1006	79	14	the	the	DET
cana-1006	79	15	measured	measured	ADJ
cana-1006	79	16	values	value	NOUN
cana-1006	79	17	.	.	PUNCT
cana-1006	80	1	let	let	VERB
cana-1006	80	2	rm	rm	NOUN
cana-1006	80	3	(	(	PUNCT
cana-1006	80	4	d	d	AUX
cana-1006	80	5	)	)	PUNCT
cana-1006	80	6	be	be	AUX
cana-1006	80	7	the	the	DET
cana-1006	80	8	ratio	ratio	NOUN
cana-1006	80	9	of	of	ADP
cana-1006	80	10	resampling	resample	VERB
cana-1006	80	11	method	method	NOUN
cana-1006	80	12	,	,	PUNCT
cana-1006	80	13	which	which	PRON
cana-1006	80	14	are	be	AUX
cana-1006	80	15	determined	determine	VERB
cana-1006	80	16	with	with	ADP
cana-1006	80	17	enn	enn	PROPN
cana-1006	80	18	and	and	CCONJ
cana-1006	80	19	r	r	NOUN
cana-1006	80	20	n	n	PROPN
cana-1006	80	21	(	(	PUNCT
cana-1006	80	22	d	d	X
cana-1006	80	23	)	)	PUNCT
cana-1006	80	24	be	be	AUX
cana-1006	80	25	the	the	DET
cana-1006	80	26	ratio	ratio	NOUN
cana-1006	80	27	of	of	ADP
cana-1006	80	28	resampling	resample	VERB
cana-1006	80	29	method	method	NOUN
cana-1006	80	30	,	,	PUNCT
cana-1006	80	31	whichare	whichare	AUX
cana-1006	80	32	determined	determine	VERB
cana-1006	80	33	with	with	ADP
cana-1006	80	34	tomek	tomek	PROPN
cana-1006	80	35	links	link	NOUN
cana-1006	80	36	.	.	PUNCT
cana-1006	81	1	if	if	SCONJ
cana-1006	81	2	the	the	DET
cana-1006	81	3	resultant	resultant	NOUN
cana-1006	81	4	is	be	AUX
cana-1006	81	5	1	1	NUM
cana-1006	81	6	,	,	PUNCT
cana-1006	81	7	then	then	ADV
cana-1006	81	8	the	the	DET
cana-1006	81	9	smote	smote	NOUN
cana-1006	81	10	determines	determine	VERB
cana-1006	81	11	the	the	DET
cana-1006	81	12	imbalance	imbalance	NOUN
cana-1006	81	13	by	by	ADP
cana-1006	81	14	accomplishing	accomplish	VERB
cana-1006	81	15	the	the	DET
cana-1006	81	16	low	low	ADJ
cana-1006	81	17	level	level	NOUN
cana-1006	81	18	instances	instance	NOUN
cana-1006	81	19	and	and	CCONJ
cana-1006	81	20	also	also	ADV
cana-1006	81	21	,	,	PUNCT
cana-1006	81	22	the	the	DET
cana-1006	81	23	noise	noise	NOUN
cana-1006	81	24	can	can	AUX
cana-1006	81	25	be	be	AUX
cana-1006	81	26	suppressed	suppress	VERB
cana-1006	81	27	with	with	ADP
cana-1006	81	28	enn	enn	PROPN
cana-1006	81	29	and	and	CCONJ
cana-1006	81	30	eventually	eventually	ADV
cana-1006	81	31	,	,	PUNCT
cana-1006	81	32	the	the	DET
cana-1006	81	33	overlap	overlap	NOUN
cana-1006	81	34	is	be	AUX
cana-1006	81	35	also	also	ADV
cana-1006	81	36	suppressed	suppress	VERB
cana-1006	81	37	with	with	ADP
cana-1006	81	38	tomek	tomek	PROPN
cana-1006	81	39	link	link	NOUN
cana-1006	81	40	.	.	PUNCT
cana-1006	82	1	moreover	moreover	ADV
cana-1006	82	2	,	,	PUNCT
cana-1006	82	3	based	base	VERB
cana-1006	82	4	on	on	ADP
cana-1006	82	5	the	the	DET
cana-1006	82	6	ratio	ratio	NOUN
cana-1006	82	7	of	of	ADP
cana-1006	82	8	rm(d	rm(d	NUM
cana-1006	82	9	)	)	PUNCT
cana-1006	82	10	and	and	CCONJ
cana-1006	82	11	rn(d	rn(d	NOUN
cana-1006	82	12	)	)	PUNCT
cana-1006	82	13	,	,	PUNCT
cana-1006	82	14	the	the	DET
cana-1006	82	15	enn	enn	PROPN
cana-1006	82	16	and	and	CCONJ
cana-1006	82	17	tomek	tomek	PROPN
cana-1006	82	18	link	link	NOUN
cana-1006	82	19	ratio	ratio	NOUN
cana-1006	82	20	is	be	AUX
cana-1006	82	21	evaluated	evaluate	VERB
cana-1006	82	22	with	with	ADP
cana-1006	82	23	the	the	DET
cana-1006	82	24	ratio	ratio	NOUN
cana-1006	82	25	determination	determination	NOUN
cana-1006	82	26	function	function	NOUN
cana-1006	82	27	.	.	PUNCT
cana-1006	83	1	traditionally	traditionally	ADV
cana-1006	83	2	,	,	PUNCT
cana-1006	83	3	the	the	DET
cana-1006	83	4	ratio	ratio	NOUN
cana-1006	83	5	of	of	ADP
cana-1006	83	6	enn	enn	PROPN
cana-1006	83	7	and	and	CCONJ
cana-1006	83	8	tomek	tomek	PROPN
cana-1006	83	9	link	link	NOUN
cana-1006	83	10	is	be	AUX
cana-1006	83	11	computed	compute	VERB
cana-1006	83	12	with	with	ADP
cana-1006	83	13	ratio	ratio	NOUN
cana-1006	83	14	determination	determination	NOUN
cana-1006	83	15	function	function	NOUN
cana-1006	83	16	but	but	CCONJ
cana-1006	83	17	in	in	ADP
cana-1006	83	18	this	this	DET
cana-1006	83	19	proposed	propose	VERB
cana-1006	83	20	work	work	NOUN
cana-1006	83	21	,	,	PUNCT
cana-1006	83	22	information	information	NOUN
cana-1006	83	23	ratio	ratio	NOUN
cana-1006	83	24	is	be	AUX
cana-1006	83	25	deployed	deploy	VERB
cana-1006	83	26	instead	instead	ADV
cana-1006	83	27	of	of	ADP
cana-1006	83	28	ratio	ratio	NOUN
cana-1006	83	29	determination	determination	NOUN
cana-1006	83	30	function	function	NOUN
cana-1006	83	31	that	that	PRON
cana-1006	83	32	can	can	AUX
cana-1006	83	33	be	be	AUX
cana-1006	83	34	stated	state	VERB
cana-1006	83	35	as	as	ADP
cana-1006	83	36	in	in	ADP
cana-1006	83	37	eq	eq	ADP
cana-1006	83	38	.	.	PUNCT
cana-1006	84	1	(	(	PUNCT
cana-1006	84	2	1	1	NUM
cana-1006	84	3	)	)	PUNCT
cana-1006	84	4	.	.	PUNCT
cana-1006	85	1	here	here	ADV
cana-1006	85	2	,	,	PUNCT
cana-1006	85	3	for	for	ADP
cana-1006	85	4	calculating	calculate	VERB
cana-1006	85	5	r	r	NOUN
cana-1006	85	6	m	m	PROPN
cana-1006	85	7	,	,	PUNCT
cana-1006	85	8	the	the	DET
cana-1006	85	9	r	r	NOUN
cana-1006	85	10	p	p	NOUN
cana-1006	85	11	takes	take	VERB
cana-1006	85	12	d	d	NOUN
cana-1006	85	13	'	'	PUNCT
cana-1006	85	14	and	and	CCONJ
cana-1006	85	15	rb	rb	PROPN
cana-1006	85	16	takes	take	VERB
cana-1006	85	17	d	d	NOUN
cana-1006	85	18	'	'	PUNCT
cana-1006	85	19	value	value	NOUN
cana-1006	85	20	and	and	CCONJ
cana-1006	85	21	then	then	ADV
cana-1006	85	22	for	for	ADP
cana-1006	85	23	calculating	calculate	VERB
cana-1006	85	24	rn	rn	PROPN
cana-1006	85	25	,	,	PUNCT
cana-1006	85	26	the	the	DET
cana-1006	85	27	rp	rp	NOUN
cana-1006	85	28	,	,	PUNCT
cana-1006	85	29	takes	take	VERB
cana-1006	85	30	d	d	NOUN
cana-1006	85	31	value	value	NOUN
cana-1006	85	32	and	and	CCONJ
cana-1006	85	33	b	b	NOUN
cana-1006	85	34	takes	take	NOUN
cana-1006	85	35	d	d	NOUN
cana-1006	85	36	value	value	NOUN
cana-1006	85	37	.	.	PUNCT
cana-1006	86	1	(	(	PUNCT
cana-1006	86	2	1	1	NUM
cana-1006	86	3	)	)	SYM
cana-1006	86	4	2	2	NUM
cana-1006	86	5	)	)	PUNCT
cana-1006	86	6	pseudo	pseudo	NOUN
cana-1006	86	7	-	-	NOUN
cana-1006	86	8	code	code	NOUN
cana-1006	86	9	of	of	ADP
cana-1006	86	10	proposed	propose	VERB
cana-1006	86	11	algorithm	algorithm	NOUN
cana-1006	86	12	algorithm	algorithm	NOUN
cana-1006	86	13	1	1	NUM
cana-1006	86	14	:	:	PUNCT
cana-1006	86	15	smote	smote	NOUN
cana-1006	86	16	-	-	PUNCT
cana-1006	86	17	enn	enn	PROPN
cana-1006	86	18	and	and	CCONJ
cana-1006	86	19	tomek	tomek	PROPN
cana-1006	86	20	link	link	NOUN
cana-1006	86	21	algorithm	algorithm	NOUN
cana-1006	86	22	input	input	NOUN
cana-1006	86	23	:	:	PUNCT
cana-1006	86	24	d	d	PART
cana-1006	86	25	evaluate	evaluate	VERB
cana-1006	86	26	kdn	kdn	NOUN
cana-1006	86	27	(	(	PUNCT
cana-1006	86	28	d	d	NOUN
cana-1006	86	29	)	)	PUNCT
cana-1006	86	30	evaluate	evaluate	VERB
cana-1006	86	31	lda(d	lda(d	NOUN
cana-1006	86	32	)	)	PUNCT
cana-1006	86	33	if	if	SCONJ
cana-1006	86	34	kdn	kdn	X
cana-1006	86	35	(	(	PUNCT
cana-1006	86	36	d	d	NOUN
cana-1006	86	37	)	)	PUNCT
cana-1006	87	1	−	−	PROPN
cana-1006	87	2	lda(d	lda(d	PROPN
cana-1006	87	3	)	)	PUNCT
cana-1006	87	4			NUM
cana-1006	87	5	0	0	PUNCT
cana-1006	88	1	then	then	ADV
cana-1006	88	2	f	f	X
cana-1006	88	3	(	(	PUNCT
cana-1006	88	4	d	d	NOUN
cana-1006	88	5	)	)	PUNCT
cana-1006	88	6	1	1	PROPN
cana-1006	88	7	else	else	ADV
cana-1006	88	8	f	f	PROPN
cana-1006	88	9	(	(	PUNCT
cana-1006	88	10	d	d	NOUN
cana-1006	88	11	)	)	PUNCT
cana-1006	88	12			NOUN
cana-1006	88	13	0	0	NUM
cana-1006	88	14	end	end	NOUN
cana-1006	88	15	if	if	SCONJ
cana-1006	88	16	evaluate	evaluate	VERB
cana-1006	88	17	r	r	NOUN
cana-1006	88	18	m	m	VERB
cana-1006	88	19	(	(	PUNCT
cana-1006	88	20	d	d	NOUN
cana-1006	88	21	)	)	PUNCT
cana-1006	88	22	and	and	CCONJ
cana-1006	88	23	r	r	NOUN
cana-1006	88	24	n	n	PROPN
cana-1006	88	25	(	(	PUNCT
cana-1006	88	26	d	d	NOUN
cana-1006	88	27	)	)	PUNCT
cana-1006	88	28	if	if	SCONJ
cana-1006	88	29	f	f	PROPN
cana-1006	88	30	(	(	PUNCT
cana-1006	88	31	d	d	NOUN
cana-1006	88	32	)	)	PUNCT
cana-1006	88	33			NUM
cana-1006	89	1	1then	1then	PUNCT
cana-1006	89	2	d	d	NOUN
cana-1006	89	3	'	'	CCONJ
cana-1006	89	4			NOUN
cana-1006	89	5	smote	smote	NOUN
cana-1006	89	6	(	(	PUNCT
cana-1006	89	7	d	d	NOUN
cana-1006	89	8	)	)	PUNCT
cana-1006	89	9	d	d	NOUN
cana-1006	89	10	''	''	PUNCT
cana-1006	89	11			PROPN
cana-1006	89	12	enn	enn	PROPN
cana-1006	89	13	(	(	PUNCT
cana-1006	89	14	d	d	NOUN
cana-1006	89	15	'	'	PUNCT
cana-1006	89	16	)	)	PUNCT
cana-1006	89	17	.	.	PUNCT
cana-1006	90	1	r	r	NOUN
cana-1006	90	2	(	(	PUNCT
cana-1006	90	3	d	d	NOUN
cana-1006	90	4	)	)	PUNCT
cana-1006	90	5	m	m	PROPN
cana-1006	90	6	d	d	NOUN
cana-1006	90	7	'	'	PUNCT
cana-1006	90	8	''	''	PUNCT
cana-1006	90	9			PROPN
cana-1006	90	10	tomek	tomek	PROPN
cana-1006	90	11	link	link	NOUN
cana-1006	90	12	(	(	PUNCT
cana-1006	90	13	d	d	NOUN
cana-1006	90	14	''	''	PUNCT
cana-1006	90	15	)	)	PUNCT
cana-1006	90	16	.	.	PUNCT
cana-1006	91	1	r	r	NOUN
cana-1006	91	2	(	(	PUNCT
cana-1006	91	3	d	d	NOUN
cana-1006	91	4	)	)	PUNCT
cana-1006	91	5	n	n	CCONJ
cana-1006	91	6	else	else	ADV
cana-1006	91	7	d	d	NOUN
cana-1006	91	8	'	'	CCONJ
cana-1006	91	9			NOUN
cana-1006	91	10	smote	smote	NOUN
cana-1006	91	11	(	(	PUNCT
cana-1006	91	12	d	d	NOUN
cana-1006	91	13	)	)	PUNCT
cana-1006	91	14	a	a	ADV
cana-1006	91	15	−	−	PROPN
cana-1006	91	16	b	b	NOUN
cana-1006	91	17	communications	communication	NOUN
cana-1006	91	18	on	on	ADP
cana-1006	91	19	applied	apply	VERB
cana-1006	91	20	nonlinear	nonlinear	ADJ
cana-1006	91	21	analysis	analysis	NOUN
cana-1006	91	22	issn	issn	NOUN
cana-1006	91	23	:	:	PUNCT
cana-1006	91	24	1074	1074	NUM
cana-1006	91	25	-	-	PUNCT
cana-1006	91	26	133x	133x	NUM
cana-1006	91	27	vol	vol	NOUN
cana-1006	91	28	31	31	NUM
cana-1006	91	29	no	no	NOUN
cana-1006	91	30	.	.	PUNCT
cana-1006	92	1	5s	5s	NUM
cana-1006	92	2	(	(	PUNCT
cana-1006	92	3	2024	2024	NUM
cana-1006	92	4	)	)	PUNCT
cana-1006	92	5	122	122	NUM
cana-1006	92	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	92	7	d	d	NOUN
cana-1006	92	8	''	''	PUNCT
cana-1006	92	9			PROPN
cana-1006	92	10	tomek	tomek	PROPN
cana-1006	92	11	link	link	NOUN
cana-1006	92	12	(	(	PUNCT
cana-1006	92	13	d	d	NOUN
cana-1006	92	14	'	'	PUNCT
cana-1006	92	15	)	)	PUNCT
cana-1006	92	16	.	.	PUNCT
cana-1006	93	1	r	r	NOUN
cana-1006	93	2	(	(	PUNCT
cana-1006	93	3	d	d	NOUN
cana-1006	93	4	)	)	PUNCT
cana-1006	93	5	m	m	PROPN
cana-1006	93	6	d	d	NOUN
cana-1006	93	7	''	''	PUNCT
cana-1006	93	8	'	'	PUNCT
cana-1006	93	9			X
cana-1006	93	10	enn	enn	PROPN
cana-1006	93	11	(	(	PUNCT
cana-1006	93	12	d	d	NOUN
cana-1006	93	13	''	''	PUNCT
cana-1006	93	14	)	)	PUNCT
cana-1006	93	15	.	.	PUNCT
cana-1006	94	1	r	r	NOUN
cana-1006	94	2	(	(	PUNCT
cana-1006	94	3	d	d	NOUN
cana-1006	94	4	)	)	PUNCT
cana-1006	94	5	n	n	NOUN
cana-1006	94	6	end	end	VERB
cana-1006	94	7	if	if	SCONJ
cana-1006	94	8	return	return	VERB
cana-1006	94	9	output	output	NOUN
cana-1006	94	10	:	:	PUNCT
cana-1006	94	11	d	d	X
cana-1006	94	12	''	''	PUNCT
cana-1006	94	13	'	'	PUNCT
cana-1006	94	14	c.	c.	NOUN
cana-1006	94	15	an	an	DET
cana-1006	94	16	overview	overview	NOUN
cana-1006	94	17	on	on	ADP
cana-1006	94	18	retrieving	retrieve	VERB
cana-1006	94	19	features	feature	NOUN
cana-1006	94	20	including	include	VERB
cana-1006	94	21	entropy	entropy	NOUN
cana-1006	94	22	and	and	CCONJ
cana-1006	94	23	improved	improved	ADJ
cana-1006	94	24	correlation	correlation	NOUN
cana-1006	94	25	-	-	PUNCT
cana-1006	94	26	based	base	VERB
cana-1006	94	27	feature	feature	NOUN
cana-1006	94	28	1	1	NUM
cana-1006	94	29	)	)	PUNCT
cana-1006	94	30	entropy	entropy	NOUN
cana-1006	94	31	based	base	VERB
cana-1006	94	32	feature	feature	NOUN
cana-1006	94	33	:	:	PUNCT
cana-1006	94	34	the	the	DET
cana-1006	94	35	entropy	entropy	NOUN
cana-1006	94	36	based	base	VERB
cana-1006	94	37	feature	feature	NOUN
cana-1006	94	38	[	[	X
cana-1006	94	39	11	11	NUM
cana-1006	94	40	]	]	PUNCT
cana-1006	94	41	is	be	AUX
cana-1006	94	42	extracted	extract	VERB
cana-1006	94	43	from	from	ADP
cana-1006	94	44	the	the	DET
cana-1006	94	45	pre	pre	ADJ
cana-1006	94	46	-	-	ADJ
cana-1006	94	47	processed	process	VERB
cana-1006	94	48	data	datum	NOUN
cana-1006	94	49	d	d	NOUN
cana-1006	94	50	to	to	PART
cana-1006	94	51	evaluate	evaluate	VERB
cana-1006	94	52	the	the	DET
cana-1006	94	53	dissimilarity	dissimilarity	NOUN
cana-1006	94	54	of	of	ADP
cana-1006	94	55	nonlinear	nonlinear	ADJ
cana-1006	94	56	and	and	CCONJ
cana-1006	94	57	non	non	ADJ
cana-1006	94	58	-	-	ADJ
cana-1006	94	59	stationary	stationary	ADJ
cana-1006	94	60	time	time	NOUN
cana-1006	94	61	sequence	sequence	NOUN
cana-1006	94	62	.	.	PUNCT
cana-1006	95	1	the	the	DET
cana-1006	95	2	traditional	traditional	ADJ
cana-1006	95	3	entropy	entropy	NOUN
cana-1006	95	4	can	can	AUX
cana-1006	95	5	be	be	AUX
cana-1006	95	6	formulated	formulate	VERB
cana-1006	95	7	as	as	ADP
cana-1006	95	8	in	in	ADP
cana-1006	95	9	eq	eq	NOUN
cana-1006	95	10	.	.	PUNCT
cana-1006	96	1	(	(	PUNCT
cana-1006	96	2	2	2	NUM
cana-1006	96	3	)	)	PUNCT
cana-1006	96	4	.	.	PUNCT
cana-1006	97	1	here	here	ADV
cana-1006	97	2	,	,	PUNCT
cana-1006	97	3	dpre	dpre	PROPN
cana-1006	97	4	specifies	specifie	NOUN
cana-1006	97	5	pre	pre	ADJ
cana-1006	97	6	-	-	ADJ
cana-1006	97	7	processed	processed	ADJ
cana-1006	97	8	data	datum	NOUN
cana-1006	97	9	,	,	PUNCT
cana-1006	97	10	and	and	CCONJ
cana-1006	97	11	p	p	X
cana-1006	97	12	(	(	PUNCT
cana-1006	97	13	d	d	NOUN
cana-1006	97	14	pre	pre	X
cana-1006	97	15	)	)	PUNCT
cana-1006	97	16	specifies	specify	VERB
cana-1006	97	17	probability	probability	NOUN
cana-1006	97	18	of	of	ADP
cana-1006	97	19	pre	pre	ADJ
cana-1006	97	20	-	-	ADJ
cana-1006	97	21	processed	processed	ADJ
cana-1006	97	22	data	datum	NOUN
cana-1006	97	23	.	.	PUNCT
cana-1006	98	1	2	2	X
cana-1006	98	2	)	)	PUNCT
cana-1006	98	3	improved	improve	VERB
cana-1006	98	4	correlation	correlation	NOUN
cana-1006	98	5	based	base	VERB
cana-1006	98	6	feature	feature	NOUN
cana-1006	98	7	correlation	correlation	NOUN
cana-1006	98	8	is	be	AUX
cana-1006	98	9	a	a	DET
cana-1006	98	10	measure	measure	NOUN
cana-1006	98	11	that	that	PRON
cana-1006	98	12	quantifies	quantify	VERB
cana-1006	98	13	the	the	DET
cana-1006	98	14	strength	strength	NOUN
cana-1006	98	15	of	of	ADP
cana-1006	98	16	the	the	DET
cana-1006	98	17	association	association	NOUN
cana-1006	98	18	or	or	CCONJ
cana-1006	98	19	relationship	relationship	NOUN
cana-1006	98	20	between	between	ADP
cana-1006	98	21	two	two	NUM
cana-1006	98	22	features	feature	NOUN
cana-1006	98	23	from	from	ADP
cana-1006	98	24	the	the	DET
cana-1006	98	25	pre	pre	ADJ
cana-1006	98	26	-	-	ADJ
cana-1006	98	27	processed	process	VERB
cana-1006	98	28	data	datum	NOUN
cana-1006	98	29	d	d	NOUN
cana-1006	98	30	.	.	PUNCT
cana-1006	99	1	it	it	PRON
cana-1006	99	2	can	can	AUX
cana-1006	99	3	be	be	AUX
cana-1006	99	4	used	use	VERB
cana-1006	99	5	to	to	PART
cana-1006	99	6	predict	predict	VERB
cana-1006	99	7	one	one	NUM
cana-1006	99	8	feature	feature	NOUN
cana-1006	99	9	from	from	ADP
cana-1006	99	10	the	the	DET
cana-1006	99	11	other	other	ADJ
cana-1006	99	12	feature	feature	NOUN
cana-1006	99	13	.	.	PUNCT
cana-1006	100	1	the	the	DET
cana-1006	100	2	tradition	tradition	NOUN
cana-1006	100	3	pearson	pearson	NOUN
cana-1006	100	4	correlation	correlation	NOUN
cana-1006	100	5	can	can	AUX
cana-1006	100	6	be	be	AUX
cana-1006	100	7	formulated	formulate	VERB
cana-1006	100	8	as	as	ADP
cana-1006	100	9	in	in	ADP
cana-1006	100	10	eq	eq	NOUN
cana-1006	100	11	.	.	PUNCT
cana-1006	101	1	(	(	PUNCT
cana-1006	101	2	3	3	NUM
cana-1006	101	3	)	)	PUNCT
cana-1006	101	4	.	.	PUNCT
cana-1006	102	1	the	the	DET
cana-1006	102	2	above	above	ADP
cana-1006	102	3	eq	eq	PROPN
cana-1006	102	4	.	.	PUNCT
cana-1006	103	1	(	(	PUNCT
cana-1006	103	2	3	3	X
cana-1006	103	3	)	)	PUNCT
cana-1006	103	4	is	be	AUX
cana-1006	103	5	improved	improve	VERB
cana-1006	103	6	to	to	PART
cana-1006	103	7	correlate	correlate	VERB
cana-1006	103	8	the	the	DET
cana-1006	103	9	best	good	ADJ
cana-1006	103	10	features	feature	NOUN
cana-1006	103	11	highly	highly	ADV
cana-1006	103	12	for	for	ADP
cana-1006	103	13	detecting	detect	VERB
cana-1006	103	14	the	the	DET
cana-1006	103	15	intrusion	intrusion	NOUN
cana-1006	103	16	efficiently	efficiently	ADV
cana-1006	103	17	.	.	PUNCT
cana-1006	104	1	then	then	ADV
cana-1006	104	2	the	the	DET
cana-1006	104	3	improved	improved	ADJ
cana-1006	104	4	correlation	correlation	NOUN
cana-1006	104	5	can	can	AUX
cana-1006	104	6	be	be	AUX
cana-1006	104	7	formulated	formulate	VERB
cana-1006	104	8	as	as	ADP
cana-1006	104	9	in	in	ADP
cana-1006	104	10	eq	eq	NOUN
cana-1006	104	11	.	.	PUNCT
cana-1006	105	1	(	(	PUNCT
cana-1006	105	2	4	4	NUM
cana-1006	105	3	)	)	PUNCT
cana-1006	105	4	.	.	PUNCT
cana-1006	106	1	here	here	ADV
cana-1006	106	2	,	,	PUNCT
cana-1006	106	3	u	u	NOUN
cana-1006	106	4	specifies	specify	VERB
cana-1006	106	5	u	u	NOUN
cana-1006	106	6	values	value	NOUN
cana-1006	106	7	,	,	PUNCT
cana-1006	106	8	v	v	X
cana-1006	106	9	specifies	specifie	NOUN
cana-1006	106	10	v	v	ADP
cana-1006	106	11	values	value	NOUN
cana-1006	106	12	,	,	PUNCT
cana-1006	106	13	mu	mu	PROPN
cana-1006	106	14	refers	refer	VERB
cana-1006	106	15	to	to	PART
cana-1006	106	16	mean	mean	VERB
cana-1006	106	17	of	of	ADP
cana-1006	106	18	u	u	NOUN
cana-1006	106	19	values	value	NOUN
cana-1006	106	20	,	,	PUNCT
cana-1006	106	21	and	and	CCONJ
cana-1006	106	22	mv	mv	PROPN
cana-1006	106	23	refers	refer	VERB
cana-1006	106	24	to	to	PART
cana-1006	106	25	mean	mean	VERB
cana-1006	106	26	of	of	ADP
cana-1006	106	27	v	v	NOUN
cana-1006	106	28	values	value	NOUN
cana-1006	106	29	.	.	PUNCT
cana-1006	107	1	further	far	ADV
cana-1006	107	2	,	,	PUNCT
cana-1006	107	3	cv	cv	PROPN
cana-1006	107	4	function	function	NOUN
cana-1006	107	5	is	be	AUX
cana-1006	107	6	evaluated	evaluate	VERB
cana-1006	107	7	with	with	ADP
cana-1006	107	8	the	the	DET
cana-1006	107	9	coefficient	coefficient	NOUN
cana-1006	107	10	of	of	ADP
cana-1006	107	11	variation	variation	NOUN
cana-1006	107	12	can	can	AUX
cana-1006	107	13	be	be	AUX
cana-1006	107	14	formulated	formulate	VERB
cana-1006	107	15	as	as	ADP
cana-1006	107	16	in	in	ADP
cana-1006	107	17	eq	eq	NOUN
cana-1006	107	18	.	.	PUNCT
cana-1006	108	1	(	(	PUNCT
cana-1006	108	2	5	5	NUM
cana-1006	108	3	)	)	PUNCT
cana-1006	108	4	.	.	PUNCT
cana-1006	109	1	here	here	ADV
cana-1006	109	2	,	,	PUNCT
cana-1006	109	3	specifies	specify	VERB
cana-1006	109	4	standard	standard	ADJ
cana-1006	109	5	deviation	deviation	NOUN
cana-1006	109	6	of	of	ADP
cana-1006	109	7	pre	pre	ADJ
cana-1006	109	8	-	-	ADJ
cana-1006	109	9	processed	process	VERB
cana-1006	109	10	data	datum	NOUN
cana-1006	109	11	and	and	CCONJ
cana-1006	109	12	specifies	specifie	NOUN
cana-1006	109	13	mean	mean	VERB
cana-1006	109	14	of	of	ADP
cana-1006	109	15	pre	pre	ADJ
cana-1006	109	16	-	-	ADJ
cana-1006	109	17	processed	processed	ADJ
cana-1006	109	18	data	datum	NOUN
cana-1006	109	19	.	.	PUNCT
cana-1006	110	1	(	(	PUNCT
cana-1006	110	2	5	5	X
cana-1006	110	3	)	)	PUNCT
cana-1006	110	4	thereby	thereby	ADV
cana-1006	110	5	,	,	PUNCT
cana-1006	110	6	the	the	DET
cana-1006	110	7	entropy	entropy	NOUN
cana-1006	110	8	and	and	CCONJ
cana-1006	110	9	correlation	correlation	NOUN
cana-1006	110	10	based	base	VERB
cana-1006	110	11	features	feature	NOUN
cana-1006	110	12	retrieved	retrieve	VERB
cana-1006	110	13	from	from	ADP
cana-1006	110	14	the	the	DET
cana-1006	110	15	balanced	balanced	ADJ
cana-1006	110	16	data	datum	NOUN
cana-1006	110	17	can	can	AUX
cana-1006	110	18	be	be	AUX
cana-1006	110	19	represented	represent	VERB
cana-1006	110	20	as	as	ADP
cana-1006	110	21	2	2	NUM
cana-1006	110	22	communications	communication	NOUN
cana-1006	110	23	on	on	ADP
cana-1006	110	24	applied	apply	VERB
cana-1006	110	25	nonlinear	nonlinear	ADJ
cana-1006	110	26	analysis	analysis	NOUN
cana-1006	110	27	issn	issn	NOUN
cana-1006	110	28	:	:	PUNCT
cana-1006	110	29	1074	1074	NUM
cana-1006	110	30	-	-	PUNCT
cana-1006	110	31	133x	133x	NUM
cana-1006	110	32	vol	vol	NOUN
cana-1006	110	33	31	31	NUM
cana-1006	110	34	no	no	NOUN
cana-1006	110	35	.	.	PUNCT
cana-1006	111	1	5s	5s	NUM
cana-1006	111	2	(	(	PUNCT
cana-1006	111	3	2024	2024	NUM
cana-1006	111	4	)	)	PUNCT
cana-1006	111	5	123	123	NUM
cana-1006	111	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	111	7	d.	d.	PROPN
cana-1006	111	8	intrusion	intrusion	PROPN
cana-1006	111	9	detection	detection	NOUN
cana-1006	111	10	in	in	ADP
cana-1006	111	11	the	the	DET
cana-1006	111	12	intrusion	intrusion	NOUN
cana-1006	111	13	detection	detection	NOUN
cana-1006	111	14	phase	phase	NOUN
cana-1006	111	15	,	,	PUNCT
cana-1006	111	16	the	the	DET
cana-1006	111	17	retrieved	retrieve	VERB
cana-1006	111	18	features	feature	NOUN
cana-1006	111	19	ext	ext	PROPN
cana-1006	111	20	f	f	PROPN
cana-1006	111	21	is	be	AUX
cana-1006	111	22	subjected	subject	VERB
cana-1006	111	23	to	to	ADP
cana-1006	111	24	the	the	DET
cana-1006	111	25	hybrid	hybrid	ADJ
cana-1006	111	26	model	model	NOUN
cana-1006	111	27	of	of	ADP
cana-1006	111	28	classifier	classifier	NOUN
cana-1006	111	29	to	to	PART
cana-1006	111	30	speed	speed	VERB
cana-1006	111	31	up	up	ADP
cana-1006	111	32	the	the	DET
cana-1006	111	33	detection	detection	NOUN
cana-1006	111	34	processing	processing	NOUN
cana-1006	111	35	time	time	NOUN
cana-1006	111	36	that	that	SCONJ
cana-1006	111	37	including	include	VERB
cana-1006	111	38	deep	deep	ADJ
cana-1006	111	39	maxout	maxout	NOUN
cana-1006	111	40	and	and	CCONJ
cana-1006	111	41	bi	bi	NOUN
cana-1006	111	42	-	-	PROPN
cana-1006	111	43	gru	gru	NOUN
cana-1006	111	44	models	model	NOUN
cana-1006	111	45	.	.	PUNCT
cana-1006	112	1	these	these	DET
cana-1006	112	2	features	feature	NOUN
cana-1006	112	3	ext	ext	NOUN
cana-1006	112	4	are	be	AUX
cana-1006	112	5	fed	feed	VERB
cana-1006	112	6	into	into	ADP
cana-1006	112	7	both	both	DET
cana-1006	112	8	classifiers	classifier	NOUN
cana-1006	112	9	to	to	PART
cana-1006	112	10	train	train	VERB
cana-1006	112	11	the	the	DET
cana-1006	112	12	feature	feature	NOUN
cana-1006	112	13	set	set	VERB
cana-1006	112	14	.	.	PUNCT
cana-1006	113	1	after	after	SCONJ
cana-1006	113	2	train	train	VERB
cana-1006	113	3	the	the	DET
cana-1006	113	4	features	feature	NOUN
cana-1006	113	5	,	,	PUNCT
cana-1006	113	6	the	the	DET
cana-1006	113	7	average	average	ADJ
cana-1006	113	8	outcome	outcome	NOUN
cana-1006	113	9	of	of	ADP
cana-1006	113	10	both	both	DET
cana-1006	113	11	classifiers	classifier	NOUN
cana-1006	113	12	determines	determine	VERB
cana-1006	113	13	the	the	DET
cana-1006	113	14	final	final	ADJ
cana-1006	113	15	detection	detection	NOUN
cana-1006	113	16	.	.	PUNCT
cana-1006	114	1	1	1	X
cana-1006	114	2	)	)	PUNCT
cana-1006	114	3	deep	deep	ADJ
cana-1006	114	4	maxout	maxout	NOUN
cana-1006	114	5	the	the	DET
cana-1006	114	6	deep	deep	ADJ
cana-1006	114	7	maxout	maxout	NOUN
cana-1006	114	8	model	model	NOUN
cana-1006	114	9	[	[	X
cana-1006	114	10	13	13	NUM
cana-1006	114	11	]	]	PUNCT
cana-1006	114	12	is	be	AUX
cana-1006	114	13	a	a	DET
cana-1006	114	14	multilayer	multilayer	ADJ
cana-1006	114	15	perceptron	perceptron	NOUN
cana-1006	114	16	that	that	PRON
cana-1006	114	17	deploys	deploy	VERB
cana-1006	114	18	a	a	DET
cana-1006	114	19	maxout	maxout	NOUN
cana-1006	114	20	unit	unit	NOUN
cana-1006	114	21	,	,	PUNCT
cana-1006	114	22	which	which	PRON
cana-1006	114	23	is	be	AUX
cana-1006	114	24	a	a	DET
cana-1006	114	25	kind	kind	NOUN
cana-1006	114	26	of	of	ADP
cana-1006	114	27	activation	activation	NOUN
cana-1006	114	28	function	function	NOUN
cana-1006	114	29	.	.	PUNCT
cana-1006	115	1	the	the	DET
cana-1006	115	2	maxout	maxout	NOUN
cana-1006	115	3	hidden	hide	VERB
cana-1006	115	4	layer	layer	NOUN
cana-1006	115	5	employs	employ	VERB
cana-1006	115	6	the	the	DET
cana-1006	115	7	function	function	NOUN
cana-1006	115	8	to	to	PART
cana-1006	115	9	generate	generate	VERB
cana-1006	115	10	maximum	maximum	ADJ
cana-1006	115	11	output	output	NOUN
cana-1006	115	12	function	function	NOUN
cana-1006	115	13	with	with	ADP
cana-1006	115	14	the	the	DET
cana-1006	115	15	given	give	VERB
cana-1006	115	16	retrieved	retrieve	VERB
cana-1006	115	17	features	feature	NOUN
cana-1006	115	18	ext	ext	PROPN
cana-1006	115	19	f	f	PROPN
cana-1006	115	20	can	can	AUX
cana-1006	115	21	be	be	AUX
cana-1006	115	22	stated	state	VERB
cana-1006	115	23	as	as	ADP
cana-1006	115	24	in	in	ADP
cana-1006	115	25	eq	eq	ADP
cana-1006	115	26	.	.	PUNCT
cana-1006	116	1	(	(	PUNCT
cana-1006	116	2	6	6	NUM
cana-1006	116	3	)	)	PUNCT
cana-1006	116	4	.	.	PUNCT
cana-1006	117	1	are	be	AUX
cana-1006	117	2	the	the	DET
cana-1006	117	3	learned	learn	VERB
cana-1006	117	4	constraints	constraint	NOUN
cana-1006	117	5	.	.	PUNCT
cana-1006	118	1	a	a	DET
cana-1006	118	2	maxout	maxout	NOUN
cana-1006	118	3	feature	feature	NOUN
cana-1006	118	4	map	map	NOUN
cana-1006	118	5	is	be	AUX
cana-1006	118	6	implemented	implement	VERB
cana-1006	118	7	with	with	ADP
cana-1006	118	8	the	the	DET
cana-1006	118	9	consideration	consideration	NOUN
cana-1006	118	10	of	of	ADP
cana-1006	118	11	maximum	maximum	ADJ
cana-1006	118	12	over	over	ADP
cana-1006	118	13	k	k	PROPN
cana-1006	118	14	affine	affine	PROPN
cana-1006	118	15	kernel	kernel	PROPN
cana-1006	118	16	map	map	NOUN
cana-1006	118	17	in	in	ADP
cana-1006	118	18	the	the	DET
cana-1006	118	19	convolutional	convolutional	ADJ
cana-1006	118	20	network	network	NOUN
cana-1006	118	21	.	.	PUNCT
cana-1006	119	1	also	also	ADV
cana-1006	119	2	,	,	PUNCT
cana-1006	119	3	the	the	DET
cana-1006	119	4	element	element	ADJ
cana-1006	119	5	-	-	PUNCT
cana-1006	119	6	wise	wise	ADJ
cana-1006	119	7	multiplication	multiplication	NOUN
cana-1006	119	8	is	be	AUX
cana-1006	119	9	applied	apply	VERB
cana-1006	119	10	in	in	ADP
cana-1006	119	11	the	the	DET
cana-1006	119	12	dropout	dropout	NOUN
cana-1006	119	13	layer	layer	NOUN
cana-1006	119	14	at	at	ADP
cana-1006	119	15	the	the	DET
cana-1006	119	16	time	time	NOUN
cana-1006	119	17	of	of	ADP
cana-1006	119	18	training	train	VERB
cana-1006	119	19	the	the	DET
cana-1006	119	20	dropout	dropout	NOUN
cana-1006	119	21	.	.	PUNCT
cana-1006	120	1	a	a	DET
cana-1006	120	2	piecewise	piecewise	NOUN
cana-1006	120	3	linear	linear	NOUN
cana-1006	120	4	approximation	approximation	NOUN
cana-1006	120	5	is	be	AUX
cana-1006	120	6	performed	perform	VERB
cana-1006	120	7	for	for	ADP
cana-1006	120	8	each	each	DET
cana-1006	120	9	maxout	maxout	NOUN
cana-1006	120	10	function	function	NOUN
cana-1006	120	11	,	,	PUNCT
cana-1006	120	12	which	which	PRON
cana-1006	120	13	makes	make	VERB
cana-1006	120	14	the	the	DET
cana-1006	120	15	connection	connection	NOUN
cana-1006	120	16	between	between	ADP
cana-1006	120	17	the	the	DET
cana-1006	120	18	activation	activation	NOUN
cana-1006	120	19	function	function	NOUN
cana-1006	120	20	of	of	ADP
cana-1006	120	21	hidden	hidden	ADJ
cana-1006	120	22	layers	layer	NOUN
cana-1006	120	23	.	.	PUNCT
cana-1006	121	1	2	2	X
cana-1006	121	2	)	)	PUNCT
cana-1006	121	3	bi	bi	NOUN
cana-1006	121	4	-	-	NOUN
cana-1006	121	5	gru	gru	PROPN
cana-1006	121	6	in	in	ADP
cana-1006	121	7	ann	ann	PROPN
cana-1006	121	8	,	,	PUNCT
cana-1006	121	9	a	a	DET
cana-1006	121	10	gating	gate	VERB
cana-1006	121	11	mechanism	mechanism	NOUN
cana-1006	121	12	is	be	AUX
cana-1006	121	13	referred	refer	VERB
cana-1006	121	14	as	as	ADP
cana-1006	121	15	gru	gru	PROPN
cana-1006	121	16	,	,	PUNCT
cana-1006	121	17	which	which	PRON
cana-1006	121	18	is	be	AUX
cana-1006	121	19	equivalent	equivalent	ADJ
cana-1006	121	20	to	to	ADP
cana-1006	121	21	lstm	lstm	NOUN
cana-1006	121	22	framework	framework	NOUN
cana-1006	121	23	.	.	PUNCT
cana-1006	122	1	the	the	DET
cana-1006	122	2	difference	difference	NOUN
cana-1006	122	3	from	from	ADP
cana-1006	122	4	lstm	lstm	NOUN
cana-1006	122	5	network	network	NOUN
cana-1006	122	6	is	be	AUX
cana-1006	122	7	this	this	DET
cana-1006	122	8	gru	gru	NOUN
cana-1006	122	9	analysis	analysis	NOUN
cana-1006	122	10	and	and	CCONJ
cana-1006	122	11	provides	provide	VERB
cana-1006	122	12	better	well	ADJ
cana-1006	122	13	performance	performance	NOUN
cana-1006	122	14	while	while	SCONJ
cana-1006	122	15	considering	consider	VERB
cana-1006	122	16	low	low	ADJ
cana-1006	122	17	to	to	ADP
cana-1006	122	18	medium	medium	ADJ
cana-1006	122	19	level	level	NOUN
cana-1006	122	20	dataset	dataset	NOUN
cana-1006	122	21	.	.	PUNCT
cana-1006	123	1	in	in	ADP
cana-1006	123	2	this	this	DET
cana-1006	123	3	work	work	NOUN
cana-1006	123	4	,	,	PUNCT
cana-1006	123	5	the	the	DET
cana-1006	123	6	gru	gru	NOUN
cana-1006	123	7	deploys	deploy	VERB
cana-1006	123	8	to	to	PART
cana-1006	123	9	train	train	VERB
cana-1006	123	10	the	the	DET
cana-1006	123	11	retrieved	retrieve	VERB
cana-1006	123	12	feature	feature	NOUN
cana-1006	123	13	ext	ext	PROPN
cana-1006	123	14	f.	f.	PROPN
cana-1006	123	15	the	the	DET
cana-1006	123	16	gru	gru	PROPN
cana-1006	123	17	is	be	AUX
cana-1006	123	18	implemented	implement	VERB
cana-1006	123	19	with	with	ADP
cana-1006	123	20	the	the	DET
cana-1006	123	21	following	follow	VERB
cana-1006	123	22	equations	equation	NOUN
cana-1006	123	23	that	that	PRON
cana-1006	123	24	can	can	AUX
cana-1006	123	25	be	be	AUX
cana-1006	123	26	formulated	formulate	VERB
cana-1006	123	27	as	as	ADP
cana-1006	123	28	in	in	ADP
cana-1006	123	29	eq	eq	NOUN
cana-1006	123	30	.	.	PUNCT
cana-1006	124	1	(	(	PUNCT
cana-1006	124	2	7	7	NUM
cana-1006	124	3	)	)	PUNCT
cana-1006	124	4	.	.	PUNCT
cana-1006	125	1	here	here	ADV
cana-1006	125	2	,	,	PUNCT
cana-1006	125	3	ht	ht	PROPN
cana-1006	125	4	indicates	indicate	VERB
cana-1006	125	5	hidden	hidden	ADJ
cana-1006	125	6	state	state	NOUN
cana-1006	125	7	,	,	PUNCT
cana-1006	125	8	u	u	PRON
cana-1006	125	9	indicates	indicate	VERB
cana-1006	125	10	update	update	NOUN
cana-1006	125	11	gate	gate	NOUN
cana-1006	125	12	,	,	PUNCT
cana-1006	125	13	indicates	indicate	NOUN
cana-1006	125	14	element	element	ADJ
cana-1006	125	15	-	-	ADJ
cana-1006	125	16	wise	wise	ADJ
cana-1006	125	17	multiplication	multiplication	NOUN
cana-1006	125	18	,	,	PUNCT
cana-1006	125	19	indicates	indicate	VERB
cana-1006	125	20	candidate	candidate	NOUN
cana-1006	125	21	gate	gate	NOUN
cana-1006	125	22	,	,	PUNCT
cana-1006	125	23	ht-1	ht-1	PUNCT
cana-1006	125	24	indicates	indicate	VERB
cana-1006	125	25	specifies	specifie	NOUN
cana-1006	125	26	hidden	hide	VERB
cana-1006	125	27	state	state	NOUN
cana-1006	125	28	input	input	NOUN
cana-1006	125	29	in	in	ADP
cana-1006	125	30	the	the	DET
cana-1006	125	31	previous	previous	ADJ
cana-1006	125	32	layer	layer	NOUN
cana-1006	125	33	,	,	PUNCT
cana-1006	125	34			PROPN
cana-1006	125	35	refers	refer	VERB
cana-1006	125	36	to	to	ADP
cana-1006	125	37	sigmoid	sigmoid	NOUN
cana-1006	125	38	function	function	NOUN
cana-1006	125	39	,	,	PUNCT
cana-1006	125	40			PROPN
cana-1006	125	41	refers	refer	VERB
cana-1006	125	42	to	to	ADP
cana-1006	125	43	weight	weight	NOUN
cana-1006	125	44	,	,	PUNCT
cana-1006	125	45	b	b	PROPN
cana-1006	125	46	refers	refer	VERB
cana-1006	125	47	to	to	PART
cana-1006	125	48	bias	bias	VERB
cana-1006	125	49	vector	vector	NOUN
cana-1006	125	50	,	,	PUNCT
cana-1006	125	51	rg	rg	PROPN
cana-1006	125	52	specifies	specifie	NOUN
cana-1006	125	53	reset	reset	NOUN
cana-1006	125	54	gate	gate	NOUN
cana-1006	125	55	and	and	CCONJ
cana-1006	125	56	tanh	tanh	PROPN
cana-1006	125	57	indicates	indicate	VERB
cana-1006	125	58	hyperbolic	hyperbolic	ADJ
cana-1006	125	59	tangent	tangent	NOUN
cana-1006	125	60	function	function	NOUN
cana-1006	125	61	.	.	PUNCT
cana-1006	126	1	in	in	ADP
cana-1006	126	2	bi	bi	PROPN
cana-1006	126	3	-	-	PROPN
cana-1006	126	4	gru	gru	NOUN
cana-1006	126	5	model	model	NOUN
cana-1006	126	6	[	[	X
cana-1006	126	7	14	14	NUM
cana-1006	126	8	]	]	PUNCT
cana-1006	126	9	,	,	PUNCT
cana-1006	126	10	the	the	DET
cana-1006	126	11	input	input	NOUN
cana-1006	126	12	of	of	ADP
cana-1006	126	13	prior	prior	ADJ
cana-1006	126	14	and	and	CCONJ
cana-1006	126	15	further	further	ADJ
cana-1006	126	16	available	available	ADJ
cana-1006	126	17	series	series	NOUN
cana-1006	126	18	are	be	AUX
cana-1006	126	19	given	give	VERB
cana-1006	126	20	as	as	ADP
cana-1006	126	21	input	input	NOUN
cana-1006	126	22	to	to	ADP
cana-1006	126	23	the	the	DET
cana-1006	126	24	model	model	NOUN
cana-1006	126	25	,	,	PUNCT
cana-1006	126	26	which	which	PRON
cana-1006	126	27	has	have	VERB
cana-1006	126	28	two	two	NUM
cana-1006	126	29	cell	cell	NOUN
cana-1006	126	30	in	in	ADP
cana-1006	126	31	terms	term	NOUN
cana-1006	126	32	of	of	ADP
cana-1006	126	33	both	both	CCONJ
cana-1006	126	34	forward	forward	ADJ
cana-1006	126	35	and	and	CCONJ
cana-1006	126	36	backward	backward	ADJ
cana-1006	126	37	processing	processing	NOUN
cana-1006	126	38	of	of	ADP
cana-1006	126	39	input	input	NOUN
cana-1006	126	40	series	series	NOUN
cana-1006	126	41	.	.	PUNCT
cana-1006	127	1	that	that	PRON
cana-1006	127	2	is	be	AUX
cana-1006	127	3	,	,	PUNCT
cana-1006	127	4	the	the	DET
cana-1006	127	5	one	one	NUM
cana-1006	127	6	cell	cell	NOUN
cana-1006	127	7	considers	consider	VERB
cana-1006	127	8	the	the	DET
cana-1006	127	9	input	input	NOUN
cana-1006	127	10	in	in	ADP
cana-1006	127	11	usual	usual	ADJ
cana-1006	127	12	form	form	NOUN
cana-1006	127	13	of	of	ADP
cana-1006	127	14	sequence	sequence	NOUN
cana-1006	127	15	whereas	whereas	SCONJ
cana-1006	127	16	,	,	PUNCT
cana-1006	127	17	the	the	DET
cana-1006	127	18	other	other	ADJ
cana-1006	127	19	cell	cell	NOUN
cana-1006	127	20	considers	consider	VERB
cana-1006	127	21	the	the	DET
cana-1006	127	22	input	input	NOUN
cana-1006	127	23	in	in	ADP
cana-1006	127	24	reverse	reverse	ADJ
cana-1006	127	25	form	form	NOUN
cana-1006	127	26	.	.	PUNCT
cana-1006	128	1	communications	communication	NOUN
cana-1006	128	2	on	on	ADP
cana-1006	128	3	applied	apply	VERB
cana-1006	128	4	nonlinear	nonlinear	ADJ
cana-1006	128	5	analysis	analysis	NOUN
cana-1006	128	6	issn	issn	NOUN
cana-1006	128	7	:	:	PUNCT
cana-1006	128	8	1074	1074	NUM
cana-1006	128	9	-	-	PUNCT
cana-1006	128	10	133x	133x	NUM
cana-1006	128	11	vol	vol	NOUN
cana-1006	128	12	31	31	NUM
cana-1006	128	13	no	no	NOUN
cana-1006	128	14	.	.	PUNCT
cana-1006	129	1	5s	5s	NUM
cana-1006	129	2	(	(	PUNCT
cana-1006	129	3	2024	2024	NUM
cana-1006	129	4	)	)	PUNCT
cana-1006	129	5	124	124	NUM
cana-1006	129	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	129	7	4	4	X
cana-1006	129	8	.	.	NOUN
cana-1006	129	9	results	result	NOUN
cana-1006	129	10	and	and	CCONJ
cana-1006	129	11	discussion	discussion	NOUN
cana-1006	129	12	a.	a.	NOUN
cana-1006	129	13	simulation	simulation	NOUN
cana-1006	129	14	procedure	procedure	NOUN
cana-1006	129	15	the	the	DET
cana-1006	129	16	proposed	propose	VERB
cana-1006	129	17	intrusion	intrusion	NOUN
cana-1006	129	18	detection	detection	NOUN
cana-1006	129	19	in	in	ADP
cana-1006	129	20	wsn	wsn	PROPN
cana-1006	129	21	was	be	AUX
cana-1006	129	22	implemented	implement	VERB
cana-1006	129	23	in	in	ADP
cana-1006	129	24	python	python	NOUN
cana-1006	129	25	and	and	CCONJ
cana-1006	129	26	the	the	DET
cana-1006	129	27	wsn	wsn	ADJ
cana-1006	129	28	-	-	ADJ
cana-1006	129	29	ds	ds	ADJ
cana-1006	129	30	dataset	dataset	NOUN
cana-1006	129	31	was	be	AUX
cana-1006	129	32	gathered	gather	VERB
cana-1006	129	33	from	from	ADP
cana-1006	129	34	[	[	X
cana-1006	129	35	15	15	NUM
cana-1006	129	36	]	]	PUNCT
cana-1006	129	37	.	.	PUNCT
cana-1006	130	1	in	in	ADP
cana-1006	130	2	order	order	NOUN
cana-1006	130	3	to	to	PART
cana-1006	130	4	express	express	VERB
cana-1006	130	5	the	the	DET
cana-1006	130	6	efficiency	efficiency	NOUN
cana-1006	130	7	of	of	ADP
cana-1006	130	8	the	the	DET
cana-1006	130	9	proposed	propose	VERB
cana-1006	130	10	model	model	NOUN
cana-1006	130	11	,	,	PUNCT
cana-1006	130	12	it	it	PRON
cana-1006	130	13	analyses	analyse	VERB
cana-1006	130	14	the	the	DET
cana-1006	130	15	performance	performance	NOUN
cana-1006	130	16	with	with	ADP
cana-1006	130	17	benchmarking	benchmarke	VERB
cana-1006	130	18	the	the	DET
cana-1006	130	19	existing	exist	VERB
cana-1006	130	20	classifiers	classifier	NOUN
cana-1006	130	21	like	like	ADP
cana-1006	130	22	deep	deep	ADJ
cana-1006	130	23	maxout	maxout	NOUN
cana-1006	130	24	,	,	PUNCT
cana-1006	130	25	lstm	lstm	PROPN
cana-1006	130	26	,	,	PUNCT
cana-1006	130	27	rnn	rnn	NOUN
cana-1006	130	28	and	and	CCONJ
cana-1006	130	29	dbn	dbn	PROPN
cana-1006	130	30	.	.	PUNCT
cana-1006	131	1	also	also	ADV
cana-1006	131	2	,	,	PUNCT
cana-1006	131	3	it	it	PRON
cana-1006	131	4	is	be	AUX
cana-1006	131	5	examined	examine	VERB
cana-1006	131	6	with	with	ADP
cana-1006	131	7	the	the	DET
cana-1006	131	8	consideration	consideration	NOUN
cana-1006	131	9	of	of	ADP
cana-1006	131	10	sensitivity	sensitivity	NOUN
cana-1006	131	11	,	,	PUNCT
cana-1006	131	12	npv	npv	NOUN
cana-1006	131	13	,	,	PUNCT
cana-1006	131	14	accuracy	accuracy	NOUN
cana-1006	131	15	,	,	PUNCT
cana-1006	131	16	fpr	fpr	NOUN
cana-1006	131	17	and	and	CCONJ
cana-1006	131	18	other	other	ADJ
cana-1006	131	19	measures	measure	NOUN
cana-1006	131	20	for	for	ADP
cana-1006	131	21	distinct	distinct	ADJ
cana-1006	131	22	number	number	NOUN
cana-1006	131	23	of	of	ADP
cana-1006	131	24	learning	learn	VERB
cana-1006	131	25	percentages	percentage	NOUN
cana-1006	131	26	.	.	PUNCT
cana-1006	132	1	b.	b.	PROPN
cana-1006	132	2	wsn	wsn	PROPN
cana-1006	132	3	-	-	ADJ
cana-1006	132	4	ds	ds	ADJ
cana-1006	132	5	dataset	dataset	NOUN
cana-1006	132	6	description	description	NOUN
cana-1006	132	7	the	the	DET
cana-1006	132	8	wsn	wsn	ADJ
cana-1006	132	9	-	-	ADJ
cana-1006	132	10	ds	ds	ADJ
cana-1006	132	11	dataset	dataset	NOUN
cana-1006	132	12	has	have	AUX
cana-1006	132	13	been	be	AUX
cana-1006	132	14	defined	define	VERB
cana-1006	132	15	to	to	PART
cana-1006	132	16	gather	gather	VERB
cana-1006	132	17	data	datum	NOUN
cana-1006	132	18	from	from	ADP
cana-1006	132	19	network	network	NOUN
cana-1006	132	20	simulator	simulator	NOUN
cana-1006	132	21	2	2	NUM
cana-1006	132	22	(	(	PUNCT
cana-1006	132	23	ns-2	ns-2	NUM
cana-1006	132	24	)	)	PUNCT
cana-1006	132	25	and	and	CCONJ
cana-1006	132	26	then	then	ADV
cana-1006	132	27	processed	process	VERB
cana-1006	132	28	to	to	PART
cana-1006	132	29	produce	produce	VERB
cana-1006	132	30	23	23	NUM
cana-1006	132	31	features	feature	NOUN
cana-1006	132	32	,	,	PUNCT
cana-1006	132	33	such	such	ADJ
cana-1006	132	34	as	as	ADP
cana-1006	132	35	,	,	PUNCT
cana-1006	132	36	join	join	NOUN
cana-1006	132	37	-	-	PUNCT
cana-1006	132	38	req	req	NOUN
cana-1006	132	39	-	-	PUNCT
cana-1006	132	40	rcvd	rcvd	NOUN
cana-1006	132	41	,	,	PUNCT
cana-1006	132	42	joinreq	joinreq	NOUN
cana-1006	132	43	-	-	PUNCT
cana-1006	132	44	sent	send	VERB
cana-1006	132	45	,	,	PUNCT
cana-1006	132	46	and	and	CCONJ
cana-1006	132	47	so	so	ADV
cana-1006	132	48	on	on	ADV
cana-1006	132	49	.	.	PUNCT
cana-1006	133	1	the	the	DET
cana-1006	133	2	collected	collect	VERB
cana-1006	133	3	dataset	dataset	NOUN
cana-1006	133	4	has	have	AUX
cana-1006	133	5	been	be	AUX
cana-1006	133	6	trained	train	VERB
cana-1006	133	7	to	to	PART
cana-1006	133	8	classify	classify	VERB
cana-1006	133	9	different	different	ADJ
cana-1006	133	10	dos	do	NOUN
cana-1006	133	11	attacks	attack	NOUN
cana-1006	133	12	,	,	PUNCT
cana-1006	133	13	including	include	VERB
cana-1006	133	14	,	,	PUNCT
cana-1006	133	15	grayhole	grayhole	NOUN
cana-1006	133	16	,	,	PUNCT
cana-1006	133	17	blackhole	blackhole	NOUN
cana-1006	133	18	,	,	PUNCT
cana-1006	133	19	scheduling	scheduling	NOUN
cana-1006	133	20	attacks	attack	NOUN
cana-1006	133	21	and	and	CCONJ
cana-1006	133	22	flooding	flooding	NOUN
cana-1006	133	23	.	.	PUNCT
cana-1006	134	1	c.	c.	PROPN
cana-1006	134	2	intrusion	intrusion	PROPN
cana-1006	134	3	detection	detection	NOUN
cana-1006	134	4	analysis	analysis	NOUN
cana-1006	134	5	on	on	ADP
cana-1006	134	6	proposed	propose	VERB
cana-1006	134	7	and	and	CCONJ
cana-1006	134	8	traditional	traditional	ADJ
cana-1006	134	9	methods	method	NOUN
cana-1006	134	10	correspond	correspond	VERB
cana-1006	134	11	to	to	ADP
cana-1006	134	12	positive	positive	ADJ
cana-1006	134	13	metric	metric	NOUN
cana-1006	134	14	the	the	DET
cana-1006	134	15	assessment	assessment	NOUN
cana-1006	134	16	on	on	ADP
cana-1006	134	17	proposed	propose	VERB
cana-1006	134	18	is	be	AUX
cana-1006	134	19	compared	compare	VERB
cana-1006	134	20	to	to	ADP
cana-1006	134	21	the	the	DET
cana-1006	134	22	deep	deep	ADJ
cana-1006	134	23	maxout	maxout	NOUN
cana-1006	134	24	,	,	PUNCT
cana-1006	134	25	lstm	lstm	PROPN
cana-1006	134	26	,	,	PUNCT
cana-1006	134	27	rnn	rnn	VERB
cana-1006	134	28	and	and	CCONJ
cana-1006	134	29	dbn	dbn	PROPN
cana-1006	134	30	with	with	ADP
cana-1006	134	31	considering	consider	VERB
cana-1006	134	32	the	the	DET
cana-1006	134	33	specificity	specificity	NOUN
cana-1006	134	34	,	,	PUNCT
cana-1006	134	35	precision	precision	NOUN
cana-1006	134	36	,	,	PUNCT
cana-1006	134	37	accuracy	accuracy	NOUN
cana-1006	134	38	and	and	CCONJ
cana-1006	134	39	sensitivity	sensitivity	NOUN
cana-1006	134	40	for	for	ADP
cana-1006	134	41	detecting	detect	VERB
cana-1006	134	42	the	the	DET
cana-1006	134	43	intrusion	intrusion	NOUN
cana-1006	134	44	in	in	ADP
cana-1006	134	45	wsn	wsn	PROPN
cana-1006	134	46	framework	framework	NOUN
cana-1006	134	47	is	be	AUX
cana-1006	134	48	displayed	display	VERB
cana-1006	134	49	in	in	ADP
cana-1006	134	50	fig	fig	NOUN
cana-1006	134	51	2	2	NUM
cana-1006	134	52	.	.	PUNCT
cana-1006	135	1	for	for	ADP
cana-1006	135	2	the	the	DET
cana-1006	135	3	exact	exact	ADJ
cana-1006	135	4	detection	detection	NOUN
cana-1006	135	5	of	of	ADP
cana-1006	135	6	intrusion	intrusion	NOUN
cana-1006	135	7	,	,	PUNCT
cana-1006	135	8	the	the	DET
cana-1006	135	9	model	model	NOUN
cana-1006	135	10	needs	need	VERB
cana-1006	135	11	maximal	maximal	ADJ
cana-1006	135	12	positive	positive	ADJ
cana-1006	135	13	metric	metric	ADJ
cana-1006	135	14	ratings	rating	NOUN
cana-1006	135	15	.	.	PUNCT
cana-1006	136	1	considering	consider	VERB
cana-1006	136	2	the	the	DET
cana-1006	136	3	fig	fig	NOUN
cana-1006	136	4	2(a	2(a	NUM
cana-1006	136	5	)	)	PUNCT
cana-1006	136	6	,	,	PUNCT
cana-1006	136	7	the	the	DET
cana-1006	136	8	proposed	propose	VERB
cana-1006	136	9	generated	generate	VERB
cana-1006	136	10	the	the	DET
cana-1006	136	11	greatest	great	ADJ
cana-1006	136	12	precision	precision	NOUN
cana-1006	136	13	of	of	ADP
cana-1006	136	14	0.9102	0.9102	NUM
cana-1006	136	15	in	in	ADP
cana-1006	136	16	the	the	DET
cana-1006	136	17	learning	learning	NOUN
cana-1006	136	18	rate	rate	NOUN
cana-1006	136	19	60	60	NUM
cana-1006	136	20	%	%	NOUN
cana-1006	136	21	,	,	PUNCT
cana-1006	136	22	whilst	whilst	SCONJ
cana-1006	136	23	the	the	DET
cana-1006	136	24	deep	deep	ADJ
cana-1006	136	25	maxout	maxout	NOUN
cana-1006	136	26	,	,	PUNCT
cana-1006	136	27	lstm	lstm	PROPN
cana-1006	136	28	,	,	PUNCT
cana-1006	136	29	rnn	rnn	VERB
cana-1006	136	30	and	and	CCONJ
cana-1006	136	31	dbn	dbn	PROPN
cana-1006	136	32	scored	score	VERB
cana-1006	136	33	the	the	DET
cana-1006	136	34	least	least	ADJ
cana-1006	136	35	precision	precision	NOUN
cana-1006	136	36	rates	rate	NOUN
cana-1006	136	37	of	of	ADP
cana-1006	136	38	0.8638	0.8638	NUM
cana-1006	136	39	,	,	PUNCT
cana-1006	136	40	0.7865	0.7865	NUM
cana-1006	136	41	,	,	PUNCT
cana-1006	136	42	0.8917	0.8917	NUM
cana-1006	136	43	and	and	CCONJ
cana-1006	136	44	0.8816	0.8816	NUM
cana-1006	136	45	,	,	PUNCT
cana-1006	136	46	respectively	respectively	ADV
cana-1006	136	47	.	.	PUNCT
cana-1006	137	1	subsequently	subsequently	ADV
cana-1006	137	2	,	,	PUNCT
cana-1006	137	3	the	the	DET
cana-1006	137	4	specificity	specificity	NOUN
cana-1006	137	5	of	of	ADP
cana-1006	137	6	the	the	DET
cana-1006	137	7	proposed	propose	VERB
cana-1006	137	8	work	work	NOUN
cana-1006	137	9	is	be	AUX
cana-1006	137	10	higher	high	ADJ
cana-1006	137	11	(	(	PUNCT
cana-1006	137	12	0.9401	0.9401	NUM
cana-1006	137	13	)	)	PUNCT
cana-1006	137	14	over	over	ADP
cana-1006	137	15	the	the	DET
cana-1006	137	16	deep	deep	ADJ
cana-1006	137	17	maxout	maxout	NOUN
cana-1006	137	18	,	,	PUNCT
cana-1006	137	19	lstm	lstm	PROPN
cana-1006	137	20	,	,	PUNCT
cana-1006	137	21	rnn	rnn	NOUN
cana-1006	137	22	and	and	CCONJ
cana-1006	137	23	dbn	dbn	PROPN
cana-1006	137	24	,	,	PUNCT
cana-1006	137	25	as	as	ADP
cana-1006	137	26	per	per	ADP
cana-1006	137	27	fig	fig	NOUN
cana-1006	137	28	1(b	1(b	NUM
cana-1006	137	29	)	)	PUNCT
cana-1006	137	30	.	.	PUNCT
cana-1006	138	1	additionally	additionally	ADV
cana-1006	138	2	,	,	PUNCT
cana-1006	138	3	the	the	DET
cana-1006	138	4	detection	detection	NOUN
cana-1006	138	5	accuracy	accuracy	NOUN
cana-1006	138	6	attained	attain	VERB
cana-1006	138	7	by	by	ADP
cana-1006	138	8	the	the	DET
cana-1006	138	9	proposed	propose	VERB
cana-1006	138	10	is	be	AUX
cana-1006	138	11	maximal	maximal	ADJ
cana-1006	138	12	in	in	ADP
cana-1006	138	13	almost	almost	ADV
cana-1006	138	14	all	all	DET
cana-1006	138	15	the	the	DET
cana-1006	138	16	learning	learning	NOUN
cana-1006	138	17	percentages	percentage	NOUN
cana-1006	138	18	.	.	PUNCT
cana-1006	139	1	more	more	ADV
cana-1006	139	2	particularly	particularly	ADV
cana-1006	139	3	,	,	PUNCT
cana-1006	139	4	while	while	SCONJ
cana-1006	139	5	fixing	fix	VERB
cana-1006	139	6	the	the	DET
cana-1006	139	7	training	training	NOUN
cana-1006	139	8	percentage	percentage	NOUN
cana-1006	139	9	to	to	ADP
cana-1006	139	10	90	90	NUM
cana-1006	139	11	%	%	NOUN
cana-1006	139	12	,	,	PUNCT
cana-1006	139	13	the	the	DET
cana-1006	139	14	proposed	propose	VERB
cana-1006	139	15	obtained	obtain	VERB
cana-1006	139	16	the	the	DET
cana-1006	139	17	accuracy	accuracy	NOUN
cana-1006	139	18	rate	rate	NOUN
cana-1006	139	19	of	of	ADP
cana-1006	139	20	0.9498	0.9498	NUM
cana-1006	139	21	,	,	PUNCT
cana-1006	139	22	thought	think	VERB
cana-1006	139	23	is	be	AUX
cana-1006	139	24	higher	high	ADJ
cana-1006	139	25	than	than	ADP
cana-1006	139	26	the	the	DET
cana-1006	139	27	deep	deep	ADJ
cana-1006	139	28	maxout=0.8027	maxout=0.8027	NOUN
cana-1006	139	29	,	,	PUNCT
cana-1006	139	30	bigru=0.8667	bigru=0.8667	NOUN
cana-1006	139	31	,	,	PUNCT
cana-1006	139	32	lstm=0.8420	lstm=0.8420	NOUN
cana-1006	139	33	,	,	PUNCT
cana-1006	139	34	rnn=0.8267	rnn=0.8267	NOUN
cana-1006	139	35	and	and	CCONJ
cana-1006	139	36	dbn=0.8165	dbn=0.8165	NOUN
cana-1006	139	37	,	,	PUNCT
cana-1006	139	38	correspondingly	correspondingly	ADV
cana-1006	139	39	.	.	PUNCT
cana-1006	140	1	in	in	ADP
cana-1006	140	2	addition	addition	NOUN
cana-1006	140	3	,	,	PUNCT
cana-1006	140	4	the	the	DET
cana-1006	140	5	sensitivity	sensitivity	NOUN
cana-1006	140	6	of	of	ADP
cana-1006	140	7	the	the	DET
cana-1006	140	8	proposed	propose	VERB
cana-1006	140	9	is	be	AUX
cana-1006	140	10	much	much	ADV
cana-1006	140	11	greater	great	ADJ
cana-1006	140	12	in	in	ADP
cana-1006	140	13	the	the	DET
cana-1006	140	14	entire	entire	ADJ
cana-1006	140	15	learning	learning	NOUN
cana-1006	140	16	percentages	percentage	NOUN
cana-1006	140	17	.	.	PUNCT
cana-1006	141	1	thus	thus	ADV
cana-1006	141	2	,	,	PUNCT
cana-1006	141	3	the	the	DET
cana-1006	141	4	proposed	propose	VERB
cana-1006	141	5	affirmed	affirm	VERB
cana-1006	141	6	that	that	SCONJ
cana-1006	141	7	their	their	PRON
cana-1006	141	8	results	result	NOUN
cana-1006	141	9	are	be	AUX
cana-1006	141	10	more	more	ADV
cana-1006	141	11	precise	precise	ADJ
cana-1006	141	12	and	and	CCONJ
cana-1006	141	13	achieve	achieve	VERB
cana-1006	141	14	the	the	DET
cana-1006	141	15	highest	high	ADJ
cana-1006	141	16	level	level	NOUN
cana-1006	141	17	of	of	ADP
cana-1006	141	18	detecting	detect	VERB
cana-1006	141	19	accuracy	accuracy	NOUN
cana-1006	141	20	.	.	PUNCT
cana-1006	142	1	this	this	DET
cana-1006	142	2	enhancement	enhancement	NOUN
cana-1006	142	3	is	be	AUX
cana-1006	142	4	made	make	VERB
cana-1006	142	5	possible	possible	ADJ
cana-1006	142	6	by	by	ADP
cana-1006	142	7	the	the	DET
cana-1006	142	8	improved	improve	VERB
cana-1006	142	9	correlation	correlation	NOUN
cana-1006	142	10	based	base	VERB
cana-1006	142	11	feature	feature	NOUN
cana-1006	142	12	extraction	extraction	NOUN
cana-1006	142	13	as	as	ADV
cana-1006	142	14	well	well	ADV
cana-1006	142	15	as	as	ADP
cana-1006	142	16	the	the	DET
cana-1006	142	17	hybrid	hybrid	NOUN
cana-1006	142	18	model	model	NOUN
cana-1006	142	19	like	like	ADP
cana-1006	142	20	deep	deep	ADJ
cana-1006	142	21	maxout	maxout	NOUN
cana-1006	142	22	and	and	CCONJ
cana-1006	142	23	bi	bi	PROPN
cana-1006	142	24	-	-	PROPN
cana-1006	142	25	gru	gru	PROPN
cana-1006	142	26	.	.	PUNCT
cana-1006	143	1	d.	d.	PROPN
cana-1006	143	2	intrusion	intrusion	PROPN
cana-1006	143	3	detection	detection	NOUN
cana-1006	143	4	analysis	analysis	NOUN
cana-1006	143	5	on	on	ADP
cana-1006	143	6	proposed	propose	VERB
cana-1006	143	7	and	and	CCONJ
cana-1006	143	8	traditional	traditional	ADJ
cana-1006	143	9	methods	method	NOUN
cana-1006	143	10	correspond	correspond	VERB
cana-1006	143	11	to	to	ADP
cana-1006	143	12	negative	negative	ADJ
cana-1006	143	13	metric	metric	ADJ
cana-1006	143	14	the	the	DET
cana-1006	143	15	negative	negative	ADJ
cana-1006	143	16	measure	measure	NOUN
cana-1006	143	17	evaluation	evaluation	NOUN
cana-1006	143	18	on	on	ADP
cana-1006	143	19	proposed	propose	VERB
cana-1006	143	20	and	and	CCONJ
cana-1006	143	21	the	the	DET
cana-1006	143	22	established	establish	VERB
cana-1006	143	23	approach	approach	NOUN
cana-1006	143	24	detecting	detect	VERB
cana-1006	143	25	the	the	DET
cana-1006	143	26	intrusion	intrusion	NOUN
cana-1006	143	27	in	in	ADP
cana-1006	143	28	wsn	wsn	PROPN
cana-1006	143	29	is	be	AUX
cana-1006	143	30	shown	show	VERB
cana-1006	143	31	in	in	ADP
cana-1006	143	32	fig	fig	NOUN
cana-1006	143	33	3	3	NUM
cana-1006	143	34	.	.	PUNCT
cana-1006	144	1	also	also	ADV
cana-1006	144	2	,	,	PUNCT
cana-1006	144	3	the	the	DET
cana-1006	144	4	proposed	propose	VERB
cana-1006	144	5	is	be	AUX
cana-1006	144	6	compared	compare	VERB
cana-1006	144	7	with	with	ADP
cana-1006	144	8	the	the	DET
cana-1006	144	9	models	model	NOUN
cana-1006	144	10	like	like	ADP
cana-1006	144	11	deep	deep	ADJ
cana-1006	144	12	maxout	maxout	NOUN
cana-1006	144	13	,	,	PUNCT
cana-1006	144	14	lstm	lstm	PROPN
cana-1006	144	15	,	,	PUNCT
cana-1006	144	16	bigru	bigru	NOUN
cana-1006	144	17	,	,	PUNCT
cana-1006	144	18	dbn	dbn	PROPN
cana-1006	144	19	and	and	CCONJ
cana-1006	144	20	rnn	rnn	VERB
cana-1006	144	21	in	in	ADP
cana-1006	144	22	terms	term	NOUN
cana-1006	144	23	of	of	ADP
cana-1006	144	24	fnr	fnr	PROPN
cana-1006	144	25	and	and	CCONJ
cana-1006	144	26	fpr	fpr	NOUN
cana-1006	144	27	.	.	PUNCT
cana-1006	145	1	mainly	mainly	ADV
cana-1006	145	2	,	,	PUNCT
cana-1006	145	3	the	the	DET
cana-1006	145	4	proposed	propose	VERB
cana-1006	145	5	offered	offer	VERB
cana-1006	145	6	least	least	ADJ
cana-1006	145	7	negative	negative	ADJ
cana-1006	145	8	measure	measure	NOUN
cana-1006	145	9	ratings	rating	NOUN
cana-1006	145	10	over	over	ADP
cana-1006	145	11	extant	extant	ADJ
cana-1006	145	12	strategies	strategy	NOUN
cana-1006	145	13	.	.	PUNCT
cana-1006	146	1	in	in	ADP
cana-1006	146	2	particular	particular	ADJ
cana-1006	146	3	,	,	PUNCT
cana-1006	146	4	the	the	DET
cana-1006	146	5	fpr	fpr	NOUN
cana-1006	146	6	of	of	ADP
cana-1006	146	7	the	the	DET
cana-1006	146	8	proposed	propose	VERB
cana-1006	146	9	approach	approach	NOUN
cana-1006	146	10	is	be	AUX
cana-1006	146	11	0.0987	0.0987	NUM
cana-1006	146	12	,	,	PUNCT
cana-1006	146	13	whereas	whereas	SCONJ
cana-1006	146	14	the	the	DET
cana-1006	146	15	deep	deep	ADJ
cana-1006	146	16	maxout	maxout	NOUN
cana-1006	146	17	,	,	PUNCT
cana-1006	146	18	bi	bi	PROPN
cana-1006	146	19	-	-	NOUN
cana-1006	146	20	gru	gru	PROPN
cana-1006	146	21	,	,	PUNCT
cana-1006	146	22	lstm	lstm	PROPN
cana-1006	146	23	,	,	PUNCT
cana-1006	146	24	rnn	rnn	VERB
cana-1006	146	25	and	and	CCONJ
cana-1006	146	26	dbn	dbn	PROPN
cana-1006	146	27	hold	hold	VERB
cana-1006	146	28	the	the	DET
cana-1006	146	29	minimized	minimized	ADJ
cana-1006	146	30	fpr	fpr	NOUN
cana-1006	146	31	of	of	ADP
cana-1006	146	32	0.1991	0.1991	NUM
cana-1006	146	33	,	,	PUNCT
cana-1006	146	34	0.2937	0.2937	NUM
cana-1006	146	35	,	,	PUNCT
cana-1006	146	36	0.1568	0.1568	NUM
cana-1006	146	37	,	,	PUNCT
cana-1006	146	38	0.1739	0.1739	NUM
cana-1006	146	39	and	and	CCONJ
cana-1006	146	40	0.2543	0.2543	NUM
cana-1006	146	41	,	,	PUNCT
cana-1006	146	42	respectively	respectively	ADV
cana-1006	146	43	.	.	PUNCT
cana-1006	147	1	further	far	ADV
cana-1006	147	2	,	,	PUNCT
cana-1006	147	3	at	at	ADP
cana-1006	147	4	the	the	DET
cana-1006	147	5	training	training	NOUN
cana-1006	147	6	rate	rate	NOUN
cana-1006	147	7	90	90	NUM
cana-1006	147	8	%	%	NOUN
cana-1006	147	9	,	,	PUNCT
cana-1006	147	10	the	the	DET
cana-1006	147	11	proposed	propose	VERB
cana-1006	147	12	yielded	yield	VERB
cana-1006	147	13	the	the	DET
cana-1006	147	14	least	least	ADJ
cana-1006	147	15	fpr	fpr	NOUN
cana-1006	147	16	rate	rate	NOUN
cana-1006	147	17	(	(	PUNCT
cana-1006	147	18	0.1038	0.1038	NUM
cana-1006	147	19	)	)	PUNCT
cana-1006	147	20	than	than	ADP
cana-1006	147	21	the	the	DET
cana-1006	147	22	other	other	ADJ
cana-1006	147	23	60	60	NUM
cana-1006	147	24	,	,	PUNCT
cana-1006	147	25	70	70	NUM
cana-1006	147	26	and	and	CCONJ
cana-1006	147	27	80	80	NUM
cana-1006	147	28	training	training	NOUN
cana-1006	147	29	percentages	percentage	NOUN
cana-1006	147	30	.	.	PUNCT
cana-1006	148	1	as	as	SCONJ
cana-1006	148	2	we	we	PRON
cana-1006	148	3	have	have	AUX
cana-1006	148	4	performed	perform	VERB
cana-1006	148	5	intrusion	intrusion	NOUN
cana-1006	148	6	detection	detection	NOUN
cana-1006	148	7	using	use	VERB
cana-1006	148	8	the	the	DET
cana-1006	148	9	enhanced	enhanced	ADJ
cana-1006	148	10	derivation	derivation	NOUN
cana-1006	148	11	of	of	ADP
cana-1006	148	12	feature	feature	NOUN
cana-1006	148	13	with	with	ADP
cana-1006	148	14	hybrid	hybrid	ADJ
cana-1006	148	15	classifiers	classifier	NOUN
cana-1006	148	16	including	include	VERB
cana-1006	148	17	deep	deep	ADJ
cana-1006	148	18	maxout	maxout	NOUN
cana-1006	148	19	and	and	CCONJ
cana-1006	148	20	bi	bi	PROPN
cana-1006	148	21	-	-	PROPN
cana-1006	148	22	gru	gru	PROPN
cana-1006	148	23	have	have	AUX
cana-1006	148	24	accomplished	accomplish	VERB
cana-1006	148	25	superior	superior	ADJ
cana-1006	148	26	negative	negative	ADJ
cana-1006	148	27	metric	metric	ADJ
cana-1006	148	28	findings	finding	NOUN
cana-1006	148	29	.	.	PUNCT
cana-1006	149	1	thus	thus	ADV
cana-1006	149	2	,	,	PUNCT
cana-1006	149	3	the	the	DET
cana-1006	149	4	hybrid	hybrid	ADJ
cana-1006	149	5	algorithm	algorithm	NOUN
cana-1006	149	6	's	's	PART
cana-1006	149	7	successful	successful	ADJ
cana-1006	149	8	performing	perform	VERB
cana-1006	149	9	the	the	DET
cana-1006	149	10	functions	function	NOUN
cana-1006	149	11	and	and	CCONJ
cana-1006	149	12	ensured	ensure	VERB
cana-1006	149	13	to	to	PART
cana-1006	149	14	increase	increase	VERB
cana-1006	149	15	other	other	ADJ
cana-1006	149	16	metrics	metric	NOUN
cana-1006	149	17	through	through	ADP
cana-1006	149	18	an	an	DET
cana-1006	149	19	improved	improved	ADJ
cana-1006	149	20	correlation	correlation	NOUN
cana-1006	149	21	communications	communication	NOUN
cana-1006	149	22	on	on	ADP
cana-1006	149	23	applied	apply	VERB
cana-1006	149	24	nonlinear	nonlinear	ADJ
cana-1006	149	25	analysis	analysis	NOUN
cana-1006	149	26	issn	issn	NOUN
cana-1006	149	27	:	:	PUNCT
cana-1006	149	28	1074	1074	NUM
cana-1006	149	29	-	-	PUNCT
cana-1006	149	30	133x	133x	NUM
cana-1006	149	31	vol	vol	NOUN
cana-1006	149	32	31	31	NUM
cana-1006	149	33	no	no	NOUN
cana-1006	149	34	.	.	PUNCT
cana-1006	150	1	5s	5s	NUM
cana-1006	150	2	(	(	PUNCT
cana-1006	150	3	2024	2024	NUM
cana-1006	150	4	)	)	PUNCT
cana-1006	150	5	125	125	NUM
cana-1006	150	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	150	7	feature	feature	NOUN
cana-1006	150	8	extraction	extraction	NOUN
cana-1006	150	9	method	method	NOUN
cana-1006	150	10	,	,	PUNCT
cana-1006	150	11	which	which	PRON
cana-1006	150	12	is	be	AUX
cana-1006	150	13	much	much	ADV
cana-1006	150	14	successful	successful	ADJ
cana-1006	150	15	in	in	ADP
cana-1006	150	16	detecting	detect	VERB
cana-1006	150	17	the	the	DET
cana-1006	150	18	intrusions	intrusion	NOUN
cana-1006	150	19	.	.	PUNCT
cana-1006	151	1	e.	e.	PROPN
cana-1006	151	2	intrusion	intrusion	PROPN
cana-1006	151	3	detection	detection	NOUN
cana-1006	151	4	analysis	analysis	NOUN
cana-1006	151	5	on	on	ADP
cana-1006	151	6	proposed	propose	VERB
cana-1006	151	7	and	and	CCONJ
cana-1006	151	8	traditional	traditional	ADJ
cana-1006	151	9	approach	approach	NOUN
cana-1006	151	10	correspond	correspond	VERB
cana-1006	151	11	to	to	ADP
cana-1006	151	12	other	other	ADJ
cana-1006	151	13	metric	metric	ADJ
cana-1006	151	14	fig	fig	NOUN
cana-1006	151	15	4	4	NUM
cana-1006	151	16	explains	explain	VERB
cana-1006	151	17	the	the	DET
cana-1006	151	18	other	other	ADJ
cana-1006	151	19	measure	measure	NOUN
cana-1006	151	20	assessment	assessment	NOUN
cana-1006	151	21	on	on	ADP
cana-1006	151	22	proposed	propose	VERB
cana-1006	151	23	over	over	ADP
cana-1006	151	24	the	the	DET
cana-1006	151	25	deep	deep	ADJ
cana-1006	151	26	maxout	maxout	NOUN
cana-1006	151	27	,	,	PUNCT
cana-1006	151	28	rnn	rnn	PROPN
cana-1006	151	29	,	,	PUNCT
cana-1006	151	30	bi	bi	PROPN
cana-1006	151	31	-	-	NOUN
cana-1006	151	32	gru	gru	PROPN
cana-1006	151	33	,	,	PUNCT
cana-1006	151	34	lstm	lstm	ADJ
cana-1006	151	35	,	,	PUNCT
cana-1006	151	36	and	and	CCONJ
cana-1006	151	37	dbn	dbn	PROPN
cana-1006	151	38	for	for	ADP
cana-1006	151	39	intrusion	intrusion	NOUN
cana-1006	151	40	detection	detection	NOUN
cana-1006	151	41	in	in	ADP
cana-1006	151	42	wsn	wsn	PROPN
cana-1006	151	43	.	.	PUNCT
cana-1006	152	1	the	the	DET
cana-1006	152	2	other	other	ADJ
cana-1006	152	3	measure	measure	NOUN
cana-1006	152	4	needs	need	VERB
cana-1006	152	5	to	to	PART
cana-1006	152	6	be	be	AUX
cana-1006	152	7	increased	increase	VERB
cana-1006	152	8	for	for	ADP
cana-1006	152	9	the	the	DET
cana-1006	152	10	appropriate	appropriate	ADJ
cana-1006	152	11	detection	detection	NOUN
cana-1006	152	12	of	of	ADP
cana-1006	152	13	intrusion	intrusion	NOUN
cana-1006	152	14	in	in	ADP
cana-1006	152	15	wsn	wsn	PROPN
cana-1006	152	16	framework	framework	NOUN
cana-1006	152	17	.	.	PUNCT
cana-1006	153	1	further	far	ADV
cana-1006	153	2	,	,	PUNCT
cana-1006	153	3	for	for	ADP
cana-1006	153	4	the	the	DET
cana-1006	153	5	training	training	NOUN
cana-1006	153	6	percentage	percentage	NOUN
cana-1006	153	7	70	70	NUM
cana-1006	153	8	%	%	NOUN
cana-1006	153	9	,	,	PUNCT
cana-1006	153	10	the	the	DET
cana-1006	153	11	proposed	propose	VERB
cana-1006	153	12	accomplished	accomplish	VERB
cana-1006	153	13	the	the	DET
cana-1006	153	14	f	f	NOUN
cana-1006	153	15	-	-	PUNCT
cana-1006	153	16	measure	measure	NOUN
cana-1006	153	17	of	of	ADP
cana-1006	153	18	0.9243	0.9243	NUM
cana-1006	153	19	,	,	PUNCT
cana-1006	153	20	mean	mean	VERB
cana-1006	153	21	while	while	SCONJ
cana-1006	153	22	the	the	DET
cana-1006	153	23	deep	deep	ADJ
cana-1006	153	24	maxout	maxout	NOUN
cana-1006	153	25	is	be	AUX
cana-1006	153	26	0.8504	0.8504	NUM
cana-1006	153	27	,	,	PUNCT
cana-1006	153	28	bi	bi	NOUN
cana-1006	153	29	-	-	NOUN
cana-1006	153	30	gru	gru	PROPN
cana-1006	153	31	is	be	AUX
cana-1006	153	32	0.8127	0.8127	NUM
cana-1006	153	33	,	,	PUNCT
cana-1006	153	34	lstm	lstm	NOUN
cana-1006	153	35	is	be	AUX
cana-1006	153	36	0.8869	0.8869	NUM
cana-1006	153	37	,	,	PUNCT
cana-1006	153	38	rnn	rnn	VERB
cana-1006	153	39	is	be	AUX
cana-1006	153	40	0.8722	0.8722	NUM
cana-1006	153	41	and	and	CCONJ
cana-1006	153	42	dbn	dbn	PROPN
cana-1006	153	43	is	be	AUX
cana-1006	153	44	0.8438	0.8438	NUM
cana-1006	153	45	,	,	PUNCT
cana-1006	153	46	respectively	respectively	ADV
cana-1006	153	47	.	.	PUNCT
cana-1006	154	1	concerning	concern	VERB
cana-1006	154	2	the	the	DET
cana-1006	154	3	fig	fig	NOUN
cana-1006	154	4	4(b	4(b	NOUN
cana-1006	154	5	)	)	PUNCT
cana-1006	154	6	,	,	PUNCT
cana-1006	154	7	the	the	DET
cana-1006	154	8	npv	npv	NOUN
cana-1006	154	9	of	of	ADP
cana-1006	154	10	the	the	DET
cana-1006	154	11	proposed	propose	VERB
cana-1006	154	12	for	for	ADP
cana-1006	154	13	the	the	DET
cana-1006	154	14	training	training	NOUN
cana-1006	154	15	rate	rate	NOUN
cana-1006	154	16	90	90	NUM
cana-1006	154	17	%	%	NOUN
cana-1006	154	18	is	be	AUX
cana-1006	154	19	0.9378	0.9378	NUM
cana-1006	154	20	with	with	ADP
cana-1006	154	21	accurate	accurate	ADJ
cana-1006	154	22	detection	detection	NOUN
cana-1006	154	23	of	of	ADP
cana-1006	154	24	intrusion	intrusion	NOUN
cana-1006	154	25	in	in	ADP
cana-1006	154	26	wsn	wsn	PROPN
cana-1006	154	27	system	system	NOUN
cana-1006	154	28	.	.	PUNCT
cana-1006	155	1	f.	f.	PROPN
cana-1006	155	2	impact	impact	PROPN
cana-1006	155	3	on	on	ADP
cana-1006	155	4	proposed	propose	VERB
cana-1006	155	5	,	,	PUNCT
cana-1006	155	6	model	model	NOUN
cana-1006	155	7	with	with	ADP
cana-1006	155	8	devoid	devoid	ADJ
cana-1006	155	9	of	of	ADP
cana-1006	155	10	improved	improved	ADJ
cana-1006	155	11	correlation	correlation	NOUN
cana-1006	155	12	and	and	CCONJ
cana-1006	155	13	model	model	NOUN
cana-1006	155	14	with	with	ADP
cana-1006	155	15	devoid	devoid	ADJ
cana-1006	155	16	of	of	ADP
cana-1006	155	17	feature	feature	NOUN
cana-1006	155	18	extraction	extraction	NOUN
cana-1006	155	19	for	for	ADP
cana-1006	155	20	intrusion	intrusion	NOUN
cana-1006	155	21	detection	detection	NOUN
cana-1006	155	22	in	in	ADP
cana-1006	155	23	wsn	wsn	PROPN
cana-1006	155	24	table	table	NOUN
cana-1006	155	25	i	i	PRON
cana-1006	155	26	explain	explain	VERB
cana-1006	155	27	the	the	DET
cana-1006	155	28	impact	impact	NOUN
cana-1006	155	29	on	on	ADP
cana-1006	155	30	model	model	NOUN
cana-1006	155	31	with	with	ADP
cana-1006	155	32	devoid	devoid	ADJ
cana-1006	155	33	of	of	ADP
cana-1006	155	34	improved	improved	ADJ
cana-1006	155	35	correlation	correlation	NOUN
cana-1006	155	36	,	,	PUNCT
cana-1006	155	37	model	model	NOUN
cana-1006	155	38	with	with	ADP
cana-1006	155	39	devoid	devoid	ADJ
cana-1006	155	40	of	of	ADP
cana-1006	155	41	feature	feature	NOUN
cana-1006	155	42	extraction	extraction	NOUN
cana-1006	155	43	and	and	CCONJ
cana-1006	155	44	proposed	propose	VERB
cana-1006	155	45	for	for	ADP
cana-1006	155	46	the	the	DET
cana-1006	155	47	intrusion	intrusion	NOUN
cana-1006	155	48	detection	detection	NOUN
cana-1006	155	49	in	in	ADP
cana-1006	155	50	wsn	wsn	PROPN
cana-1006	155	51	framework	framework	NOUN
cana-1006	155	52	.	.	PUNCT
cana-1006	156	1	here	here	ADV
cana-1006	156	2	,	,	PUNCT
cana-1006	156	3	the	the	DET
cana-1006	156	4	proposed	propose	VERB
cana-1006	156	5	with	with	ADP
cana-1006	156	6	improved	improved	ADJ
cana-1006	156	7	correlation	correlation	NOUN
cana-1006	156	8	based	base	VERB
cana-1006	156	9	feature	feature	NOUN
cana-1006	156	10	extraction	extraction	NOUN
cana-1006	156	11	have	have	AUX
cana-1006	156	12	provided	provide	VERB
cana-1006	156	13	superior	superior	ADJ
cana-1006	156	14	outcomes	outcome	NOUN
cana-1006	156	15	with	with	ADP
cana-1006	156	16	exact	exact	ADJ
cana-1006	156	17	detection	detection	NOUN
cana-1006	156	18	of	of	ADP
cana-1006	156	19	intrusion	intrusion	NOUN
cana-1006	156	20	in	in	ADP
cana-1006	156	21	wsn	wsn	PROPN
cana-1006	156	22	framework	framework	NOUN
cana-1006	156	23	.	.	PUNCT
cana-1006	157	1	for	for	ADP
cana-1006	157	2	instance	instance	NOUN
cana-1006	157	3	,	,	PUNCT
cana-1006	157	4	the	the	DET
cana-1006	157	5	accuracy	accuracy	NOUN
cana-1006	157	6	of	of	ADP
cana-1006	157	7	the	the	DET
cana-1006	157	8	proposed	propose	VERB
cana-1006	157	9	is	be	AUX
cana-1006	157	10	0.9366	0.9366	NUM
cana-1006	157	11	,	,	PUNCT
cana-1006	157	12	model	model	NOUN
cana-1006	157	13	with	with	ADP
cana-1006	157	14	devoid	devoid	ADJ
cana-1006	157	15	of	of	ADP
cana-1006	157	16	improved	improved	ADJ
cana-1006	157	17	correlation	correlation	NOUN
cana-1006	157	18	is	be	AUX
cana-1006	157	19	0.8976	0.8976	NUM
cana-1006	157	20	and	and	CCONJ
cana-1006	157	21	model	model	NOUN
cana-1006	157	22	with	with	ADP
cana-1006	157	23	devoid	devoid	ADJ
cana-1006	157	24	of	of	ADP
cana-1006	157	25	feature	feature	NOUN
cana-1006	157	26	extraction	extraction	NOUN
cana-1006	157	27	is	be	AUX
cana-1006	157	28	0.8274	0.8274	NUM
cana-1006	157	29	.	.	PUNCT
cana-1006	158	1	additionally	additionally	ADV
cana-1006	158	2	,	,	PUNCT
cana-1006	158	3	the	the	DET
cana-1006	158	4	fnr	fnr	NOUN
cana-1006	158	5	obtained	obtain	VERB
cana-1006	158	6	by	by	ADP
cana-1006	158	7	the	the	DET
cana-1006	158	8	proposed=0.0889	proposed=0.0889	ADJ
cana-1006	158	9	,	,	PUNCT
cana-1006	158	10	model	model	NOUN
cana-1006	158	11	without	without	ADP
cana-1006	158	12	improved	improved	ADJ
cana-1006	158	13	correlation=0.1887	correlation=0.1887	PUNCT
cana-1006	158	14	and	and	CCONJ
cana-1006	158	15	model	model	NOUN
cana-1006	158	16	with	with	ADP
cana-1006	158	17	devoid	devoid	ADJ
cana-1006	158	18	of	of	ADP
cana-1006	158	19	feature	feature	NOUN
cana-1006	158	20	extraction=0.1980	extraction=0.1980	NOUN
cana-1006	158	21	,	,	PUNCT
cana-1006	158	22	correspondingly	correspondingly	ADV
cana-1006	158	23	.	.	PUNCT
cana-1006	159	1	consequently	consequently	ADV
cana-1006	159	2	,	,	PUNCT
cana-1006	159	3	the	the	DET
cana-1006	159	4	proposed	propose	VERB
cana-1006	159	5	acquired	acquire	VERB
cana-1006	159	6	the	the	DET
cana-1006	159	7	greatest	great	ADJ
cana-1006	159	8	mcc	mcc	NOUN
cana-1006	159	9	(	(	PUNCT
cana-1006	159	10	0.9300	0.9300	NUM
cana-1006	159	11	)	)	PUNCT
cana-1006	159	12	,	,	PUNCT
cana-1006	159	13	sensitivity	sensitivity	NOUN
cana-1006	159	14	(	(	PUNCT
cana-1006	159	15	0.9230	0.9230	NUM
cana-1006	159	16	)	)	PUNCT
cana-1006	159	17	and	and	CCONJ
cana-1006	159	18	npv	npv	NOUN
cana-1006	159	19	(	(	PUNCT
cana-1006	159	20	0.9198	0.9198	NUM
cana-1006	159	21	)	)	PUNCT
cana-1006	159	22	.	.	PUNCT
cana-1006	160	1	altogether	altogether	ADV
cana-1006	160	2	,	,	PUNCT
cana-1006	160	3	the	the	DET
cana-1006	160	4	improved	improved	ADJ
cana-1006	160	5	correlation	correlation	NOUN
cana-1006	160	6	based	base	VERB
cana-1006	160	7	feature	feature	NOUN
cana-1006	160	8	extraction	extraction	NOUN
cana-1006	160	9	with	with	ADP
cana-1006	160	10	hybrid	hybrid	ADJ
cana-1006	160	11	classifiers	classifier	NOUN
cana-1006	160	12	method	method	NOUN
cana-1006	160	13	allows	allow	VERB
cana-1006	160	14	the	the	DET
cana-1006	160	15	proposed	propose	VERB
cana-1006	160	16	to	to	PART
cana-1006	160	17	detect	detect	VERB
cana-1006	160	18	the	the	DET
cana-1006	160	19	intrusion	intrusion	NOUN
cana-1006	160	20	more	more	ADV
cana-1006	160	21	appropriately	appropriately	ADV
cana-1006	160	22	.	.	PUNCT
cana-1006	161	1	(	(	PUNCT
cana-1006	161	2	a	a	X
cana-1006	161	3	)	)	PUNCT
cana-1006	161	4	(	(	PUNCT
cana-1006	161	5	b	b	X
cana-1006	161	6	)	)	PUNCT
cana-1006	161	7	(	(	PUNCT
cana-1006	161	8	c	c	X
cana-1006	161	9	)	)	PUNCT
cana-1006	161	10	(	(	PUNCT
cana-1006	161	11	d	d	X
cana-1006	161	12	)	)	PUNCT
cana-1006	161	13	fig	fig	NOUN
cana-1006	161	14	.	.	PUNCT
cana-1006	162	1	2	2	NUM
cana-1006	162	2	.	.	X
cana-1006	162	3	positive	positive	ADJ
cana-1006	162	4	measure	measure	NOUN
cana-1006	162	5	evaluation	evaluation	NOUN
cana-1006	162	6	on	on	ADP
cana-1006	162	7	proposed	propose	VERB
cana-1006	162	8	and	and	CCONJ
cana-1006	162	9	conventional	conventional	ADJ
cana-1006	162	10	schemes	scheme	NOUN
cana-1006	162	11	for	for	ADP
cana-1006	162	12	intrusion	intrusion	NOUN
cana-1006	162	13	detection	detection	NOUN
cana-1006	162	14	in	in	ADP
cana-1006	162	15	wsn	wsn	PROPN
cana-1006	162	16	communications	communication	NOUN
cana-1006	162	17	on	on	ADP
cana-1006	162	18	applied	apply	VERB
cana-1006	162	19	nonlinear	nonlinear	ADJ
cana-1006	162	20	analysis	analysis	NOUN
cana-1006	162	21	issn	issn	NOUN
cana-1006	162	22	:	:	PUNCT
cana-1006	162	23	1074	1074	NUM
cana-1006	162	24	-	-	PUNCT
cana-1006	162	25	133x	133x	NUM
cana-1006	162	26	vol	vol	NOUN
cana-1006	162	27	31	31	NUM
cana-1006	162	28	no	no	NOUN
cana-1006	162	29	.	.	PUNCT
cana-1006	163	1	5s	5s	NUM
cana-1006	163	2	(	(	PUNCT
cana-1006	163	3	2024	2024	NUM
cana-1006	163	4	)	)	PUNCT
cana-1006	163	5	126	126	NUM
cana-1006	164	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	164	2	g.	g.	NOUN
cana-1006	164	3	statistical	statistical	ADJ
cana-1006	164	4	evaluation	evaluation	NOUN
cana-1006	164	5	on	on	ADP
cana-1006	164	6	proposed	propose	VERB
cana-1006	164	7	and	and	CCONJ
cana-1006	164	8	the	the	DET
cana-1006	164	9	existing	exist	VERB
cana-1006	164	10	methods	method	NOUN
cana-1006	164	11	for	for	ADP
cana-1006	164	12	intrusion	intrusion	NOUN
cana-1006	164	13	detection	detection	NOUN
cana-1006	164	14	in	in	ADP
cana-1006	164	15	wsn	wsn	PROPN
cana-1006	164	16	framework	framework	NOUN
cana-1006	164	17	with	with	ADP
cana-1006	164	18	respect	respect	NOUN
cana-1006	164	19	to	to	PART
cana-1006	164	20	accuracy	accuracy	VERB
cana-1006	164	21	the	the	DET
cana-1006	164	22	statistical	statistical	ADJ
cana-1006	164	23	study	study	NOUN
cana-1006	164	24	on	on	ADP
cana-1006	164	25	proposed	propose	VERB
cana-1006	164	26	over	over	ADP
cana-1006	164	27	the	the	DET
cana-1006	164	28	rnn	rnn	NOUN
cana-1006	164	29	,	,	PUNCT
cana-1006	164	30	deep	deep	ADJ
cana-1006	164	31	maxout	maxout	NOUN
cana-1006	164	32	,	,	PUNCT
cana-1006	164	33	bi	bi	PROPN
cana-1006	164	34	-	-	NOUN
cana-1006	164	35	gru	gru	PROPN
cana-1006	164	36	,	,	PUNCT
cana-1006	164	37	lstm	lstm	ADJ
cana-1006	164	38	,	,	PUNCT
cana-1006	164	39	and	and	CCONJ
cana-1006	164	40	dbn	dbn	PROPN
cana-1006	164	41	for	for	ADP
cana-1006	164	42	detecting	detect	VERB
cana-1006	164	43	the	the	DET
cana-1006	164	44	intrusion	intrusion	NOUN
cana-1006	164	45	in	in	ADP
cana-1006	164	46	wsn	wsn	PROPN
cana-1006	164	47	framework	framework	NOUN
cana-1006	164	48	is	be	AUX
cana-1006	164	49	illustrated	illustrate	VERB
cana-1006	164	50	in	in	ADP
cana-1006	164	51	table	table	NOUN
cana-1006	164	52	ii	ii	PROPN
cana-1006	164	53	.	.	PUNCT
cana-1006	165	1	besides	besides	ADV
cana-1006	165	2	,	,	PUNCT
cana-1006	165	3	it	it	PRON
cana-1006	165	4	is	be	AUX
cana-1006	165	5	assessed	assess	VERB
cana-1006	165	6	in	in	ADP
cana-1006	165	7	terms	term	NOUN
cana-1006	165	8	of	of	ADP
cana-1006	165	9	accuracy	accuracy	NOUN
cana-1006	165	10	under	under	ADP
cana-1006	165	11	numerous	numerous	ADJ
cana-1006	165	12	kinds	kind	NOUN
cana-1006	165	13	of	of	ADP
cana-1006	165	14	statistical	statistical	ADJ
cana-1006	165	15	measures	measure	NOUN
cana-1006	165	16	.	.	PUNCT
cana-1006	166	1	table	table	NOUN
cana-1006	166	2	i.	i.	NOUN
cana-1006	166	3	impact	impact	NOUN
cana-1006	166	4	on	on	ADP
cana-1006	166	5	proposed	propose	VERB
cana-1006	166	6	,	,	PUNCT
cana-1006	166	7	model	model	NOUN
cana-1006	166	8	without	without	ADP
cana-1006	166	9	improved	improved	ADJ
cana-1006	166	10	correlation	correlation	NOUN
cana-1006	166	11	and	and	CCONJ
cana-1006	166	12	model	model	NOUN
cana-1006	166	13	without	without	ADP
cana-1006	166	14	feature	feature	NOUN
cana-1006	166	15	extraction	extraction	NOUN
cana-1006	166	16	for	for	ADP
cana-1006	166	17	intrusion	intrusion	NOUN
cana-1006	166	18	detection	detection	NOUN
cana-1006	166	19	in	in	ADP
cana-1006	166	20	wsn	wsn	PROPN
cana-1006	166	21	measures	measure	NOUN
cana-1006	166	22	model	model	NOUN
cana-1006	166	23	without	without	ADP
cana-1006	166	24	improved	improve	VERB
cana-1006	166	25	correlation	correlation	NOUN
cana-1006	166	26	model	model	NOUN
cana-1006	166	27	without	without	ADP
cana-1006	166	28	feature	feature	NOUN
cana-1006	166	29	extraction	extraction	NOUN
cana-1006	166	30	proposed	propose	VERB
cana-1006	166	31	sensitivity	sensitivity	NOUN
cana-1006	166	32	0.8468	0.8468	NUM
cana-1006	166	33	0.8368	0.8368	NUM
cana-1006	166	34	0.9230	0.9230	NUM
cana-1006	166	35	fnr	fnr	NOUN
cana-1006	166	36	0.1887	0.1887	NUM
cana-1006	166	37	0.1980	0.1980	NUM
cana-1006	166	38	0.0889	0.0889	NUM
cana-1006	166	39	f	f	X
cana-1006	166	40	-	-	PUNCT
cana-1006	166	41	measure	measure	NOUN
cana-1006	166	42	0.8177	0.8177	NUM
cana-1006	166	43	0.8347	0.8347	NUM
cana-1006	166	44	0.9244	0.9244	NUM
cana-1006	166	45	accuracy	accuracy	NOUN
cana-1006	166	46	0.8976	0.8976	NOUN
cana-1006	166	47	0.8274	0.8274	NUM
cana-1006	166	48	0.9498	0.9498	NUM
cana-1006	166	49	fpr	fpr	VERB
cana-1006	166	50	0.2032	0.2032	NUM
cana-1006	166	51	0.1726	0.1726	NUM
cana-1006	166	52	0.0987	0.0987	NUM
cana-1006	166	53	precision	precision	NOUN
cana-1006	166	54	0.8977	0.8977	NUM
cana-1006	166	55	0.8918	0.8918	NUM
cana-1006	166	56	0.9268	0.9268	NUM
cana-1006	166	57	mcc	mcc	NOUN
cana-1006	166	58	0.8848	0.8848	NUM
cana-1006	166	59	0.8668	0.8668	NUM
cana-1006	166	60	0.9300	0.9300	NUM
cana-1006	166	61	npv	npv	NOUN
cana-1006	166	62	0.7976	0.7976	NUM
cana-1006	166	63	0.8282	0.8282	NUM
cana-1006	166	64	0.9198	0.9198	NUM
cana-1006	166	65	specificity	specificity	NOUN
cana-1006	166	66	0.8219	0.8219	NUM
cana-1006	166	67	0.8737	0.8737	NUM
cana-1006	166	68	0.9250	0.9250	NUM
cana-1006	166	69	(	(	PUNCT
cana-1006	166	70	a	a	NOUN
cana-1006	166	71	)	)	PUNCT
cana-1006	166	72	(	(	PUNCT
cana-1006	166	73	b	b	X
cana-1006	166	74	)	)	PUNCT
cana-1006	166	75	fig	fig	NOUN
cana-1006	166	76	.	.	PUNCT
cana-1006	167	1	3	3	X
cana-1006	167	2	.	.	NOUN
cana-1006	167	3	negative	negative	ADJ
cana-1006	167	4	measure	measure	NOUN
cana-1006	167	5	evaluation	evaluation	NOUN
cana-1006	167	6	on	on	ADP
cana-1006	167	7	proposed	propose	VERB
cana-1006	167	8	and	and	CCONJ
cana-1006	167	9	conventional	conventional	ADJ
cana-1006	167	10	schemes	scheme	NOUN
cana-1006	167	11	for	for	ADP
cana-1006	167	12	intrusion	intrusion	NOUN
cana-1006	167	13	detection	detection	NOUN
cana-1006	167	14	in	in	ADP
cana-1006	167	15	wsn	wsn	PROPN
cana-1006	167	16	(	(	PUNCT
cana-1006	167	17	a	a	NOUN
cana-1006	167	18	)	)	PUNCT
cana-1006	167	19	(	(	PUNCT
cana-1006	167	20	b	b	X
cana-1006	167	21	)	)	PUNCT
cana-1006	167	22	communications	communication	NOUN
cana-1006	167	23	on	on	ADP
cana-1006	167	24	applied	apply	VERB
cana-1006	167	25	nonlinear	nonlinear	ADJ
cana-1006	167	26	analysis	analysis	NOUN
cana-1006	167	27	issn	issn	NOUN
cana-1006	167	28	:	:	PUNCT
cana-1006	167	29	1074	1074	NUM
cana-1006	167	30	-	-	PUNCT
cana-1006	167	31	133x	133x	NUM
cana-1006	167	32	vol	vol	NOUN
cana-1006	167	33	31	31	NUM
cana-1006	167	34	no	no	NOUN
cana-1006	167	35	.	.	PUNCT
cana-1006	168	1	5s	5s	NUM
cana-1006	168	2	(	(	PUNCT
cana-1006	168	3	2024	2024	NUM
cana-1006	168	4	)	)	PUNCT
cana-1006	168	5	127	127	NUM
cana-1006	168	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	168	7	(	(	PUNCT
cana-1006	168	8	c	c	NOUN
cana-1006	168	9	)	)	PUNCT
cana-1006	168	10	fig	fig	NOUN
cana-1006	168	11	.	.	PUNCT
cana-1006	169	1	4	4	X
cana-1006	169	2	.	.	X
cana-1006	169	3	other	other	ADJ
cana-1006	169	4	measure	measure	NOUN
cana-1006	169	5	evaluation	evaluation	NOUN
cana-1006	169	6	on	on	ADP
cana-1006	169	7	proposed	propose	VERB
cana-1006	169	8	and	and	CCONJ
cana-1006	169	9	conventional	conventional	ADJ
cana-1006	169	10	schemes	scheme	NOUN
cana-1006	169	11	for	for	ADP
cana-1006	169	12	intrusion	intrusion	NOUN
cana-1006	169	13	detection	detection	NOUN
cana-1006	169	14	in	in	ADP
cana-1006	169	15	wsn	wsn	PROPN
cana-1006	169	16	in	in	ADP
cana-1006	169	17	particular	particular	ADJ
cana-1006	169	18	,	,	PUNCT
cana-1006	169	19	the	the	DET
cana-1006	169	20	proposed	propose	VERB
cana-1006	169	21	obtained	obtain	VERB
cana-1006	169	22	the	the	DET
cana-1006	169	23	accuracy	accuracy	NOUN
cana-1006	169	24	ratings	rating	NOUN
cana-1006	169	25	of	of	ADP
cana-1006	169	26	0.9295	0.9295	NUM
cana-1006	169	27	at	at	ADP
cana-1006	169	28	the	the	DET
cana-1006	169	29	minimum	minimum	ADJ
cana-1006	169	30	statistical	statistical	ADJ
cana-1006	169	31	measure	measure	NOUN
cana-1006	169	32	,	,	PUNCT
cana-1006	169	33	this	this	PRON
cana-1006	169	34	is	be	AUX
cana-1006	169	35	considerable	considerable	ADJ
cana-1006	169	36	greater	great	ADJ
cana-1006	169	37	than	than	ADP
cana-1006	169	38	deep	deep	ADJ
cana-1006	169	39	maxout=0.9295	maxout=0.9295	NOUN
cana-1006	169	40	,	,	PUNCT
cana-1006	169	41	bigru=0.7963	bigru=0.7963	NOUN
cana-1006	169	42	,	,	PUNCT
cana-1006	169	43	lstm=0.8421	lstm=0.8421	ADP
cana-1006	169	44	,	,	PUNCT
cana-1006	169	45	rnn=0.8249	rnn=0.8249	PROPN
cana-1006	169	46	and	and	CCONJ
cana-1006	169	47	dbn=0.8166	dbn=0.8166	PROPN
cana-1006	169	48	,	,	PUNCT
cana-1006	169	49	respectively	respectively	ADV
cana-1006	169	50	.	.	PUNCT
cana-1006	170	1	additionally	additionally	ADV
cana-1006	170	2	,	,	PUNCT
cana-1006	170	3	evaluating	evaluate	VERB
cana-1006	170	4	the	the	DET
cana-1006	170	5	median	median	ADJ
cana-1006	170	6	statistical	statistical	ADJ
cana-1006	170	7	measure	measure	NOUN
cana-1006	170	8	,	,	PUNCT
cana-1006	170	9	the	the	DET
cana-1006	170	10	accuracy	accuracy	NOUN
cana-1006	170	11	of	of	ADP
cana-1006	170	12	the	the	DET
cana-1006	170	13	proposed	propose	VERB
cana-1006	170	14	is	be	AUX
cana-1006	170	15	0.9389	0.9389	NUM
cana-1006	170	16	,	,	PUNCT
cana-1006	170	17	whereas	whereas	SCONJ
cana-1006	170	18	the	the	DET
cana-1006	170	19	deep	deep	ADJ
cana-1006	170	20	maxout	maxout	NOUN
cana-1006	170	21	,	,	PUNCT
cana-1006	170	22	bi	bi	PROPN
cana-1006	170	23	-	-	NOUN
cana-1006	170	24	gru	gru	PROPN
cana-1006	170	25	,	,	PUNCT
cana-1006	170	26	lstm	lstm	PROPN
cana-1006	170	27	,	,	PUNCT
cana-1006	170	28	rnn	rnn	VERB
cana-1006	170	29	and	and	CCONJ
cana-1006	170	30	dbn	dbn	PROPN
cana-1006	170	31	hold	hold	VERB
cana-1006	170	32	the	the	DET
cana-1006	170	33	least	least	ADJ
cana-1006	170	34	accuracy	accuracy	NOUN
cana-1006	170	35	ratings	rating	NOUN
cana-1006	170	36	.	.	PUNCT
cana-1006	171	1	finally	finally	ADV
cana-1006	171	2	,	,	PUNCT
cana-1006	171	3	under	under	ADP
cana-1006	171	4	the	the	DET
cana-1006	171	5	statistical	statistical	ADJ
cana-1006	171	6	measure	measure	NOUN
cana-1006	171	7	analysis	analysis	NOUN
cana-1006	171	8	,	,	PUNCT
cana-1006	171	9	the	the	DET
cana-1006	171	10	proposed	propose	VERB
cana-1006	171	11	determined	determine	VERB
cana-1006	171	12	to	to	PART
cana-1006	171	13	be	be	AUX
cana-1006	171	14	more	more	ADV
cana-1006	171	15	effective	effective	ADJ
cana-1006	171	16	than	than	ADP
cana-1006	171	17	the	the	DET
cana-1006	171	18	conventional	conventional	ADJ
cana-1006	171	19	methods	method	NOUN
cana-1006	171	20	for	for	ADP
cana-1006	171	21	intrusion	intrusion	NOUN
cana-1006	171	22	detection	detection	NOUN
cana-1006	171	23	in	in	ADP
cana-1006	171	24	wsn	wsn	PROPN
cana-1006	171	25	framework	framework	NOUN
cana-1006	171	26	.	.	PUNCT
cana-1006	172	1	table	table	PROPN
cana-1006	172	2	ii	ii	PROPN
cana-1006	172	3	.	.	PUNCT
cana-1006	173	1	statistical	statistical	ADJ
cana-1006	173	2	analysis	analysis	NOUN
cana-1006	173	3	on	on	ADP
cana-1006	173	4	proposed	propose	VERB
cana-1006	173	5	and	and	CCONJ
cana-1006	173	6	the	the	DET
cana-1006	173	7	extant	extant	ADJ
cana-1006	173	8	strategies	strategy	NOUN
cana-1006	173	9	with	with	ADP
cana-1006	173	10	regard	regard	NOUN
cana-1006	173	11	to	to	ADP
cana-1006	173	12	accuracy	accuracy	NOUN
cana-1006	173	13	for	for	ADP
cana-1006	173	14	intrusion	intrusion	NOUN
cana-1006	173	15	detection	detection	NOUN
cana-1006	173	16	in	in	ADP
cana-1006	173	17	wsn	wsn	PROPN
cana-1006	173	18	statistical	statistical	ADJ
cana-1006	173	19	measures	measure	NOUN
cana-1006	173	20	proposed	propose	VERB
cana-1006	173	21	deep	deep	ADJ
cana-1006	173	22	maxout	maxout	NOUN
cana-1006	173	23	bi	bi	PROPN
cana-1006	173	24	-	-	PROPN
cana-1006	173	25	gru	gru	PROPN
cana-1006	173	26	lstm	lstm	PROPN
cana-1006	173	27	rnn	rnn	VERB
cana-1006	173	28	dbn	dbn	PROPN
cana-1006	173	29	mean	mean	VERB
cana-1006	173	30	0.9393	0.9393	NUM
cana-1006	173	31	0.8001	0.8001	NUM
cana-1006	173	32	0.8607	0.8607	NUM
cana-1006	173	33	0.8435	0.8435	NUM
cana-1006	173	34	0.8257	0.8257	NUM
cana-1006	173	35	0.8409	0.8409	NUM
cana-1006	173	36	median	median	NOUN
cana-1006	173	37	0.9389	0.9389	NUM
cana-1006	173	38	0.8007	0.8007	NUM
cana-1006	173	39	0.8657	0.8657	NUM
cana-1006	173	40	0.8434	0.8434	NUM
cana-1006	173	41	0.8256	0.8256	NUM
cana-1006	173	42	0.8272	0.8272	NUM
cana-1006	173	43	stand	stand	VERB
cana-1006	173	44	ard	ard	NOUN
cana-1006	173	45	deviation	deviation	NOUN
cana-1006	173	46	0.0074	0.0074	NUM
cana-1006	173	47	0.0023	0.0023	NUM
cana-1006	173	48	0.0150	0.0150	NUM
cana-1006	173	49	0.0011	0.0011	NUM
cana-1006	173	50	0.0008	0.0008	NUM
cana-1006	173	51	0.0309	0.0309	NUM
cana-1006	173	52	minimum	minimum	NOUN
cana-1006	173	53	0.9295	0.9295	NUM
cana-1006	173	54	0.7963	0.7963	NUM
cana-1006	173	55	0.8358	0.8358	NUM
cana-1006	173	56	0.8421	0.8421	NUM
cana-1006	173	57	0.8249	0.8249	NUM
cana-1006	174	1	0.8166	0.8166	NUM
cana-1006	174	2	maximum	maximum	ADJ
cana-1006	174	3	0.9498	0.9498	NUM
cana-1006	174	4	0.8027	0.8027	NUM
cana-1006	174	5	0.8757	0.8757	NUM
cana-1006	174	6	0.8451	0.8451	NUM
cana-1006	174	7	0.8268	0.8268	NUM
cana-1006	174	8	0.8927	0.8927	NUM
cana-1006	174	9	5	5	NUM
cana-1006	174	10	.	.	PUNCT
cana-1006	175	1	conclusion	conclusion	NOUN
cana-1006	175	2	this	this	DET
cana-1006	175	3	paper	paper	NOUN
cana-1006	175	4	proposed	propose	VERB
cana-1006	175	5	intrusion	intrusion	NOUN
cana-1006	175	6	detection	detection	NOUN
cana-1006	175	7	in	in	ADP
cana-1006	175	8	wsn	wsn	PROPN
cana-1006	175	9	with	with	ADP
cana-1006	175	10	improved	improved	ADJ
cana-1006	175	11	class	class	NOUN
cana-1006	175	12	imbalance	imbalance	NOUN
cana-1006	175	13	processing	processing	NOUN
cana-1006	175	14	.	.	PUNCT
cana-1006	176	1	initially	initially	ADV
cana-1006	176	2	,	,	PUNCT
cana-1006	176	3	the	the	DET
cana-1006	176	4	input	input	NOUN
cana-1006	176	5	data	datum	NOUN
cana-1006	176	6	was	be	AUX
cana-1006	176	7	pre	pre	VERB
cana-1006	176	8	-	-	VERB
cana-1006	176	9	processed	process	VERB
cana-1006	176	10	to	to	PART
cana-1006	176	11	balance	balance	VERB
cana-1006	176	12	the	the	DET
cana-1006	176	13	data	datum	NOUN
cana-1006	176	14	with	with	ADP
cana-1006	176	15	improved	improved	ADJ
cana-1006	176	16	imbalance	imbalance	NOUN
cana-1006	176	17	process	process	NOUN
cana-1006	176	18	,	,	PUNCT
cana-1006	176	19	in	in	SCONJ
cana-1006	176	20	which	which	DET
cana-1006	176	21	smote	smote	ADJ
cana-1006	176	22	-	-	PUNCT
cana-1006	176	23	enn	enn	PROPN
cana-1006	176	24	-	-	PUNCT
cana-1006	176	25	tomek	tomek	PROPN
cana-1006	176	26	technique	technique	NOUN
cana-1006	176	27	was	be	AUX
cana-1006	176	28	employed	employ	VERB
cana-1006	176	29	.	.	PUNCT
cana-1006	177	1	then	then	ADV
cana-1006	177	2	the	the	DET
cana-1006	177	3	features	feature	NOUN
cana-1006	177	4	such	such	ADJ
cana-1006	177	5	as	as	ADP
cana-1006	177	6	entropy	entropy	NOUN
cana-1006	177	7	and	and	CCONJ
cana-1006	177	8	improved	improved	ADJ
cana-1006	177	9	correlation	correlation	NOUN
cana-1006	177	10	based	base	VERB
cana-1006	177	11	features	feature	NOUN
cana-1006	177	12	were	be	AUX
cana-1006	177	13	retrieved	retrieve	VERB
cana-1006	177	14	from	from	ADP
cana-1006	177	15	the	the	DET
cana-1006	177	16	pre	pre	ADJ
cana-1006	177	17	-	-	ADJ
cana-1006	177	18	processed	processed	ADJ
cana-1006	177	19	data	datum	NOUN
cana-1006	177	20	.	.	PUNCT
cana-1006	178	1	further	far	ADV
cana-1006	178	2	,	,	PUNCT
cana-1006	178	3	these	these	DET
cana-1006	178	4	features	feature	NOUN
cana-1006	178	5	were	be	AUX
cana-1006	178	6	subjected	subject	VERB
cana-1006	178	7	to	to	ADP
cana-1006	178	8	the	the	DET
cana-1006	178	9	hybrid	hybrid	ADJ
cana-1006	178	10	model	model	NOUN
cana-1006	178	11	,	,	PUNCT
cana-1006	178	12	which	which	PRON
cana-1006	178	13	including	include	VERB
cana-1006	178	14	deep	deep	ADJ
cana-1006	178	15	maxout	maxout	NOUN
cana-1006	178	16	and	and	CCONJ
cana-1006	178	17	bigru	bigru	NOUN
cana-1006	178	18	classifiers	classifier	NOUN
cana-1006	178	19	and	and	CCONJ
cana-1006	178	20	then	then	ADV
cana-1006	178	21	the	the	DET
cana-1006	178	22	classifiers	classifier	NOUN
cana-1006	178	23	outcome	outcome	VERB
cana-1006	178	24	predicted	predict	VERB
cana-1006	178	25	the	the	DET
cana-1006	178	26	attack	attack	NOUN
cana-1006	178	27	detection	detection	NOUN
cana-1006	178	28	.	.	PUNCT
cana-1006	179	1	more	more	ADV
cana-1006	179	2	particularly	particularly	ADV
cana-1006	179	3	,	,	PUNCT
cana-1006	179	4	while	while	SCONJ
cana-1006	179	5	fixing	fix	VERB
cana-1006	179	6	the	the	DET
cana-1006	179	7	training	training	NOUN
cana-1006	179	8	percentage	percentage	NOUN
cana-1006	179	9	to	to	ADP
cana-1006	179	10	90	90	NUM
cana-1006	179	11	%	%	NOUN
cana-1006	179	12	,	,	PUNCT
cana-1006	179	13	the	the	DET
cana-1006	179	14	proposed	propose	VERB
cana-1006	179	15	obtained	obtain	VERB
cana-1006	179	16	the	the	DET
cana-1006	179	17	accuracy	accuracy	NOUN
cana-1006	179	18	rate	rate	NOUN
cana-1006	179	19	of	of	ADP
cana-1006	179	20	0.9498	0.9498	NUM
cana-1006	179	21	,	,	PUNCT
cana-1006	179	22	thought	think	VERB
cana-1006	179	23	is	be	AUX
cana-1006	179	24	higher	high	ADJ
cana-1006	179	25	than	than	ADP
cana-1006	179	26	the	the	DET
cana-1006	179	27	deep	deep	ADJ
cana-1006	179	28	maxout=0.8027	maxout=0.8027	NOUN
cana-1006	179	29	,	,	PUNCT
cana-1006	179	30	bi	bi	NOUN
cana-1006	179	31	-	-	NOUN
cana-1006	179	32	gru=0.8667	gru=0.8667	NOUN
cana-1006	179	33	,	,	PUNCT
cana-1006	179	34	lstm=0.8420	lstm=0.8420	NOUN
cana-1006	179	35	,	,	PUNCT
cana-1006	179	36	rnn=0.8267	rnn=0.8267	NOUN
cana-1006	179	37	and	and	CCONJ
cana-1006	179	38	dbn=0.8165	dbn=0.8165	NOUN
cana-1006	179	39	,	,	PUNCT
cana-1006	179	40	correspondingly	correspondingly	ADV
cana-1006	179	41	.	.	PUNCT
cana-1006	180	1	references	reference	NOUN
cana-1006	180	2	[	[	X
cana-1006	180	3	1	1	NUM
cana-1006	180	4	]	]	X
cana-1006	180	5	safaldin	safaldin	ADJ
cana-1006	180	6	,	,	PUNCT
cana-1006	180	7	m.	m.	NOUN
cana-1006	180	8	,	,	PUNCT
cana-1006	180	9	otair	otair	NOUN
cana-1006	180	10	,	,	PUNCT
cana-1006	180	11	m.	m.	NOUN
cana-1006	180	12	&	&	CCONJ
cana-1006	180	13	abualigah	abualigah	PROPN
cana-1006	180	14	,	,	PUNCT
cana-1006	180	15	l.	l.	PROPN
cana-1006	180	16	,	,	PUNCT
cana-1006	180	17	“	"	PUNCT
cana-1006	180	18	improved	improve	VERB
cana-1006	180	19	binary	binary	ADJ
cana-1006	180	20	gray	gray	ADJ
cana-1006	180	21	wolf	wolf	NOUN
cana-1006	180	22	optimizer	optimizer	NOUN
cana-1006	180	23	and	and	CCONJ
cana-1006	180	24	svm	svm	VERB
cana-1006	180	25	for	for	ADP
cana-1006	180	26	intrusion	intrusion	NOUN
cana-1006	180	27	detection	detection	NOUN
cana-1006	180	28	system	system	NOUN
cana-1006	180	29	in	in	ADP
cana-1006	180	30	wireless	wireless	ADJ
cana-1006	180	31	sensor	sensor	NOUN
cana-1006	180	32	networks	network	NOUN
cana-1006	180	33	”	"	PUNCT
cana-1006	180	34	,	,	PUNCT
cana-1006	180	35	j	j	PROPN
cana-1006	180	36	ambient	ambient	PROPN
cana-1006	180	37	intell	intell	PROPN
cana-1006	180	38	human	human	ADJ
cana-1006	180	39	comput	comput	NOUN
cana-1006	180	40	,	,	PUNCT
cana-1006	180	41	vol	vol	NOUN
cana-1006	180	42	.	.	PROPN
cana-1006	180	43	12	12	NUM
cana-1006	180	44	,	,	PUNCT
cana-1006	180	45	pp	pp	ADJ
cana-1006	180	46	.	.	PUNCT
cana-1006	180	47	1559–1576	1559–1576	NUM
cana-1006	180	48	,	,	PUNCT
cana-1006	180	49	2021	2021	NUM
cana-1006	180	50	.	.	PUNCT
cana-1006	181	1	https://doi.org/10.1007/s12652-020-02228-z	https://doi.org/10.1007/s12652-020-02228-z	PROPN
cana-1006	182	1	[	[	X
cana-1006	182	2	2	2	NUM
cana-1006	182	3	]	]	PUNCT
cana-1006	182	4	maheswari	maheswari	PROPN
cana-1006	182	5	,	,	PUNCT
cana-1006	182	6	m.	m.	NOUN
cana-1006	182	7	,	,	PUNCT
cana-1006	182	8	&	&	CCONJ
cana-1006	182	9	karthika	karthika	PROPN
cana-1006	182	10	,	,	PUNCT
cana-1006	182	11	r.a	r.a	PROPN
cana-1006	182	12	.	.	PROPN
cana-1006	182	13	,	,	PUNCT
cana-1006	182	14	“	"	PUNCT
cana-1006	182	15	a	a	DET
cana-1006	182	16	novel	novel	ADJ
cana-1006	182	17	qos	qos	NOUN
cana-1006	182	18	based	base	VERB
cana-1006	182	19	secure	secure	ADJ
cana-1006	182	20	unequal	unequal	ADJ
cana-1006	182	21	clustering	clustering	ADJ
cana-1006	182	22	protocol	protocol	NOUN
cana-1006	182	23	with	with	ADP
cana-1006	182	24	intrusion	intrusion	NOUN
cana-1006	182	25	detection	detection	NOUN
cana-1006	182	26	system	system	NOUN
cana-1006	182	27	in	in	ADP
cana-1006	182	28	wireless	wireless	ADJ
cana-1006	182	29	sensor	sensor	NOUN
cana-1006	182	30	networks	network	NOUN
cana-1006	182	31	”	"	PUNCT
cana-1006	182	32	,	,	PUNCT
cana-1006	182	33	wireless	wireless	ADJ
cana-1006	182	34	pers	per	NOUN
cana-1006	182	35	commun	commun	PROPN
cana-1006	182	36	,	,	PUNCT
cana-1006	182	37	vol	vol	NOUN
cana-1006	182	38	.	.	PROPN
cana-1006	182	39	118	118	NUM
cana-1006	182	40	,	,	PUNCT
cana-1006	182	41	pp	pp	ADJ
cana-1006	182	42	.	.	PUNCT
cana-1006	182	43	1535–1557	1535–1557	NUM
cana-1006	182	44	,	,	PUNCT
cana-1006	182	45	2021	2021	NUM
cana-1006	182	46	.	.	PUNCT
cana-1006	183	1	https://doi.org/10.1007/s11277-021-08101-2	https://doi.org/10.1007/s11277-021-08101-2	NUM
cana-1006	184	1	[	[	X
cana-1006	184	2	3	3	NUM
cana-1006	184	3	]	]	X
cana-1006	184	4	zhang	zhang	PROPN
cana-1006	184	5	,	,	PUNCT
cana-1006	184	6	t.	t.	PROPN
cana-1006	184	7	,	,	PUNCT
cana-1006	184	8	han	han	PROPN
cana-1006	184	9	,	,	PUNCT
cana-1006	184	10	d.	d.	PROPN
cana-1006	184	11	,	,	PUNCT
cana-1006	184	12	marino	marino	PROPN
cana-1006	184	13	,	,	PUNCT
cana-1006	184	14	m.d	m.d	PROPN
cana-1006	184	15	.	.	PROPN
cana-1006	184	16	,	,	PUNCT
cana-1006	184	17	lin	lin	PROPN
cana-1006	184	18	wang	wang	PROPN
cana-1006	184	19	&	&	CCONJ
cana-1006	184	20	kuan	kuan	PROPN
cana-1006	184	21	-	-	PUNCT
cana-1006	184	22	ching	ching	PROPN
cana-1006	184	23	li	li	PROPN
cana-1006	184	24	,	,	PUNCT
cana-1006	184	25	"	"	PUNCT
cana-1006	184	26	an	an	DET
cana-1006	184	27	evolutionary	evolutionary	ADJ
cana-1006	184	28	-	-	PUNCT
cana-1006	184	29	based	base	VERB
cana-1006	184	30	approach	approach	NOUN
cana-1006	184	31	for	for	ADP
cana-1006	184	32	lowhttps://doi.org/10.1007/s11277-021-08101-2	lowhttps://doi.org/10.1007/s11277-021-08101-2	NUM
cana-1006	184	33	communications	communication	NOUN
cana-1006	184	34	on	on	ADP
cana-1006	184	35	applied	apply	VERB
cana-1006	184	36	nonlinear	nonlinear	ADJ
cana-1006	184	37	analysis	analysis	NOUN
cana-1006	184	38	issn	issn	NOUN
cana-1006	184	39	:	:	PUNCT
cana-1006	184	40	1074	1074	NUM
cana-1006	184	41	-	-	PUNCT
cana-1006	184	42	133x	133x	NUM
cana-1006	184	43	vol	vol	NOUN
cana-1006	184	44	31	31	NUM
cana-1006	184	45	no	no	NOUN
cana-1006	184	46	.	.	PUNCT
cana-1006	185	1	5s	5s	NUM
cana-1006	185	2	(	(	PUNCT
cana-1006	185	3	2024	2024	NUM
cana-1006	185	4	)	)	PUNCT
cana-1006	185	5	128	128	NUM
cana-1006	185	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1006	185	7	complexity	complexity	NOUN
cana-1006	185	8	intrusion	intrusion	NOUN
cana-1006	185	9	detection	detection	NOUN
cana-1006	185	10	in	in	ADP
cana-1006	185	11	wireless	wireless	ADJ
cana-1006	185	12	sensor	sensor	NOUN
cana-1006	185	13	networks	network	NOUN
cana-1006	185	14	”	"	PUNCT
cana-1006	185	15	,	,	PUNCT
cana-1006	185	16	wireless	wireless	NOUN
cana-1006	185	17	pers	per	NOUN
cana-1006	185	18	commun	commun	VERB
cana-1006	185	19	.	.	PUNCT
cana-1006	185	20	,	,	PUNCT
cana-1006	185	21	vol	vol	NOUN
cana-1006	185	22	.	.	PROPN
cana-1006	186	1	126	126	NUM
cana-1006	186	2	,	,	PUNCT
cana-1006	186	3	pp	pp	ADJ
cana-1006	186	4	.	.	PUNCT
cana-1006	187	1	2019–2042	2019–2042	NUM
cana-1006	187	2	,	,	PUNCT
cana-1006	187	3	2022	2022	NUM
cana-1006	187	4	.	.	PUNCT
cana-1006	188	1	https://doi.org/10.1007/s11277-021-08757-w	https://doi.org/10.1007/s11277-021-08757-w	PROPN
cana-1006	189	1	[	[	X
cana-1006	189	2	4	4	NUM
cana-1006	189	3	]	]	X
cana-1006	189	4	salmi	salmi	NOUN
cana-1006	189	5	,	,	PUNCT
cana-1006	189	6	s.	s.	PROPN
cana-1006	189	7	,	,	PUNCT
cana-1006	189	8	&	&	CCONJ
cana-1006	189	9	oughdir	oughdir	PROPN
cana-1006	189	10	,	,	PUNCT
cana-1006	189	11	l.	l.	PROPN
cana-1006	189	12	,	,	PUNCT
cana-1006	189	13	“	"	PUNCT
cana-1006	189	14	performance	performance	NOUN
cana-1006	189	15	evaluation	evaluation	NOUN
cana-1006	189	16	of	of	ADP
cana-1006	189	17	deep	deep	ADJ
cana-1006	189	18	learning	learning	NOUN
cana-1006	189	19	techniques	technique	NOUN
cana-1006	189	20	for	for	ADP
cana-1006	189	21	dos	do	NOUN
cana-1006	189	22	attacks	attack	NOUN
cana-1006	189	23	detection	detection	NOUN
cana-1006	189	24	in	in	ADP
cana-1006	189	25	wireless	wireless	ADJ
cana-1006	189	26	sensor	sensor	NOUN
cana-1006	189	27	network	network	NOUN
cana-1006	189	28	”	"	PUNCT
cana-1006	189	29	,	,	PUNCT
cana-1006	189	30	j	j	PROPN
cana-1006	189	31	big	big	PROPN
cana-1006	189	32	data	data	PROPN
cana-1006	189	33	,	,	PUNCT
cana-1006	189	34	vol	vol	NOUN
cana-1006	189	35	.	.	PROPN
cana-1006	189	36	10	10	NUM
cana-1006	189	37	,	,	PUNCT
cana-1006	189	38	2023	2023	NUM
cana-1006	189	39	.	.	PUNCT
cana-1006	190	1	https://doi.org/10.1186/s40537-023-00692-w	https://doi.org/10.1186/s40537-023-00692-w	PROPN
cana-1006	190	2	,	,	PUNCT
cana-1006	190	3	[	[	X
cana-1006	190	4	5	5	NUM
cana-1006	190	5	]	]	X
cana-1006	190	6	zhang	zhang	PROPN
cana-1006	190	7	,	,	PUNCT
cana-1006	190	8	w.	w.	PROPN
cana-1006	190	9	,	,	PUNCT
cana-1006	190	10	han	han	PROPN
cana-1006	190	11	,	,	PUNCT
cana-1006	190	12	d.	d.	PROPN
cana-1006	190	13	,	,	PUNCT
cana-1006	190	14	li	li	PROPN
cana-1006	190	15	,	,	PUNCT
cana-1006	190	16	kc	kc	PROPN
cana-1006	190	17	.	.	PROPN
cana-1006	190	18	,	,	PUNCT
cana-1006	190	19	&	&	CCONJ
cana-1006	190	20	francisco	francisco	PROPN
cana-1006	190	21	isidro	isidro	PROPN
cana-1006	190	22	massetto	massetto	PROPN
cana-1006	190	23	,	,	PUNCT
cana-1006	190	24	"	"	PUNCT
cana-1006	190	25	wireless	wireless	ADJ
cana-1006	190	26	sensor	sensor	NOUN
cana-1006	190	27	network	network	NOUN
cana-1006	190	28	intrusion	intrusion	NOUN
cana-1006	190	29	detection	detection	NOUN
cana-1006	190	30	system	system	NOUN
cana-1006	190	31	based	base	VERB
cana-1006	190	32	on	on	ADP
cana-1006	190	33	mk	mk	PROPN
cana-1006	190	34	-	-	PUNCT
cana-1006	190	35	elm	elm	PROPN
cana-1006	190	36	”	"	PUNCT
cana-1006	190	37	,	,	PUNCT
cana-1006	190	38	soft	soft	ADJ
cana-1006	190	39	comput	comput	NOUN
cana-1006	190	40	.	.	PUNCT
cana-1006	190	41	,	,	PUNCT
cana-1006	190	42	vol	vol	NOUN
cana-1006	190	43	.	.	PROPN
cana-1006	190	44	24	24	NUM
cana-1006	190	45	,	,	PUNCT
cana-1006	190	46	pp	pp	ADJ
cana-1006	190	47	.	.	PUNCT
cana-1006	191	1	12361–12374	12361–12374	NUM
cana-1006	191	2	,	,	PUNCT
cana-1006	191	3	2020.https://doi.org/10.1007/s00500-020-04678-1	2020.https://doi.org/10.1007/s00500-020-04678-1	PROPN
cana-1006	191	4	[	[	X
cana-1006	191	5	6	6	NUM
cana-1006	191	6	]	]	X
cana-1006	191	7	umarani	umarani	PROPN
cana-1006	191	8	,	,	PUNCT
cana-1006	191	9	c.	c.	PROPN
cana-1006	191	10	,	,	PUNCT
cana-1006	191	11	kannan	kannan	PROPN
cana-1006	191	12	,	,	PUNCT
cana-1006	191	13	s.	s.	PROPN
cana-1006	191	14	,	,	PUNCT
cana-1006	191	15	“	"	PUNCT
cana-1006	191	16	intrusion	intrusion	NOUN
cana-1006	191	17	detection	detection	NOUN
cana-1006	191	18	system	system	NOUN
cana-1006	191	19	using	use	VERB
cana-1006	191	20	hybrid	hybrid	ADJ
cana-1006	191	21	tissue	tissue	NOUN
cana-1006	191	22	growing	grow	VERB
cana-1006	191	23	algorithm	algorithm	NOUN
cana-1006	191	24	for	for	ADP
cana-1006	191	25	wireless	wireless	ADJ
cana-1006	191	26	sensor	sensor	NOUN
cana-1006	191	27	network	network	NOUN
cana-1006	191	28	”	"	PUNCT
cana-1006	191	29	,	,	PUNCT
cana-1006	191	30	peer	peer	NOUN
cana-1006	191	31	-	-	PUNCT
cana-1006	191	32	to	to	ADP
cana-1006	191	33	-	-	PUNCT
cana-1006	191	34	peer	peer	NOUN
cana-1006	191	35	netw	netw	NOUN
cana-1006	191	36	.	.	PUNCT
cana-1006	192	1	appl	appl	PROPN
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cana-1006	192	3	,	,	PUNCT
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cana-1006	192	5	.	.	PROPN
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cana-1006	192	7	,	,	PUNCT
cana-1006	192	8	pp	pp	ADJ
cana-1006	192	9	.	.	PUNCT
cana-1006	193	1	752–761	752–761	NUM
cana-1006	193	2	,	,	PUNCT
cana-1006	193	3	2020	2020	NUM
cana-1006	193	4	.	.	PUNCT
cana-1006	194	1	https://doi.org/10.1007/s12083-019-00781-9	https://doi.org/10.1007/s12083-019-00781-9	NUM
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cana-1006	195	6	d.	d.	PROPN
cana-1006	195	7	,	,	PUNCT
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cana-1006	195	9	,	,	PUNCT
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cana-1006	195	11	,	,	PUNCT
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cana-1006	195	13	,	,	PUNCT
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cana-1006	195	24	discounted	discount	VERB
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cana-1006	195	26	games	game	NOUN
cana-1006	195	27	and	and	CCONJ
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cana-1006	195	37	:	:	PUNCT
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cana-1006	195	40	—	—	PUNCT
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cana-1006	195	43	,	,	PUNCT
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cana-1006	197	4	.	.	PUNCT
cana-1006	198	1	,	,	PUNCT
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cana-1006	198	3	.	.	PROPN
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cana-1006	199	2	,	,	PUNCT
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cana-1006	199	4	.	.	PUNCT
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cana-1006	200	2	,	,	PUNCT
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cana-1006	200	4	.	.	PUNCT
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cana-1006	201	5	,	,	PUNCT
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cana-1006	201	17	technique	technique	NOUN
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cana-1006	201	20	wsn	wsn	PROPN
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cana-1006	201	34	(	(	PUNCT
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cana-1006	201	36	)	)	PUNCT
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cana-1006	201	39	,	,	PUNCT
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cana-1006	201	42	.	.	PUNCT
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cana-1006	201	45	.	.	PROPN
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cana-1006	202	2	,	,	PUNCT
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cana-1006	202	4	.	.	PUNCT
cana-1006	203	1	6860	6860	NUM
cana-1006	203	2	–	–	PUNCT
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cana-1006	203	4	,	,	PUNCT
cana-1006	203	5	2020	2020	NUM
cana-1006	203	6	.	.	PUNCT
cana-1006	204	1	https://doi.org/10.1007/s11227-019-03131-x	https://doi.org/10.1007/s11227-019-03131-x	NOUN
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cana-1006	205	2	9	9	NUM
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cana-1006	205	5	,	,	PUNCT
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cana-1006	205	9	,	,	PUNCT
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cana-1006	205	33	”	"	PUNCT
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cana-1006	205	38	.	.	PUNCT
cana-1006	205	39	,	,	PUNCT
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cana-1006	205	45	.	.	PUNCT
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cana-1006	206	2	,	,	PUNCT
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cana-1006	206	4	.	.	PUNCT
cana-1006	207	1	https://doi.org/10.1007/s11277019-06969-9	https://doi.org/10.1007/s11277019-06969-9	PROPN
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cana-1006	207	10	,	,	PUNCT
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cana-1006	207	14	,	,	PUNCT
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cana-1006	207	31	dos	dos	PROPN
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cana-1006	207	39	”	"	PUNCT
cana-1006	207	40	,	,	PUNCT
cana-1006	207	41	j	j	PROPN
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cana-1006	207	43	intell	intell	PROPN
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cana-1006	207	46	.	.	PUNCT
cana-1006	207	47	,	,	PUNCT
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cana-1006	207	49	.	.	PUNCT
cana-1006	208	1	https://doi.org/10.1007/s12652-020-02763-9	https://doi.org/10.1007/s12652-020-02763-9	NUM
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cana-1006	209	34	"	"	PUNCT
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cana-1006	209	42	,	,	PUNCT
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cana-1006	209	44	.	.	PUNCT
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cana-1006	210	25	"	"	PUNCT
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cana-1006	210	41	,	,	PUNCT
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cana-1006	210	43	.	.	PROPN
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cana-1006	210	45	,	,	PUNCT
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cana-1006	210	47	.	.	PUNCT
cana-1006	211	1	[	[	X
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cana-1006	211	27	"	"	PUNCT
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cana-1006	211	31	vol	vol	NOUN
cana-1006	211	32	.	.	PROPN
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cana-1006	211	34	,	,	PUNCT
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cana-1006	211	36	.	.	PUNCT
cana-1006	212	1	https://doi.org/10.3390/electronics11244137	https://doi.org/10.3390/electronics11244137	PROPN
cana-1006	213	1	[	[	X
cana-1006	213	2	14	14	NUM
cana-1006	213	3	]	]	X
cana-1006	213	4	medari	medari	ADJ
cana-1006	213	5	janai	janai	NOUN
cana-1006	213	6	tham	tham	PROPN
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cana-1006	213	8	“	"	PUNCT
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cana-1006	213	11	for	for	ADP
cana-1006	213	12	shallow	shallow	ADJ
cana-1006	213	13	parsing	parsing	NOUN
cana-1006	213	14	"	"	PUNCT
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cana-1006	213	20	science	science	NOUN
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cana-1006	213	23	,	,	PUNCT
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cana-1006	213	27	,	,	PUNCT
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cana-1006	213	29	.	.	PUNCT
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cana-1006	214	2	-	-	SYM
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cana-1006	214	4	,	,	PUNCT
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cana-1006	214	6	.	.	PUNCT
cana-1006	215	1	doi:10.21817	doi:10.21817	NOUN
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cana-1006	215	29	in	in	ADP
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cana-1006	215	32	networks	network	NOUN
cana-1006	215	33	"	"	PUNCT
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cana-1006	215	38	,	,	PUNCT
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cana-1006	215	40	.	.	PUNCT
cana-1006	216	1	https://doi.org/10.1007/s11277-021-08757-w	https://doi.org/10.1007/s11277-021-08757-w	PROPN
cana-1006	216	2	https://doi.org/10.1007/s11277-021-08757-w	https://doi.org/10.1007/s11277-021-08757-w	PROPN
cana-1006	216	3	https://doi.org/10.1186/s40537-023-00692-w	https://doi.org/10.1186/s40537-023-00692-w	PROPN
cana-1006	216	4	https://doi.org/10.1007/s00500-020-04678-1	https://doi.org/10.1007/s00500-020-04678-1	NUM
cana-1006	216	5	https://doi.org/10.1007/s12083-019-00781-9	https://doi.org/10.1007/s12083-019-00781-9	NUM
cana-1006	216	6	https://doi.org/10.1007/s12083-019-00781-9	https://doi.org/10.1007/s12083-019-00781-9	NUM
cana-1006	216	7	https://doi.org/10.1007/s13160-019-00397-9	https://doi.org/10.1007/s13160-019-00397-9	NOUN
cana-1006	216	8	https://doi.org/10.1007/s11227-019-03131-x	https://doi.org/10.1007/s11227-019-03131-x	PROPN
cana-1006	216	9	https://doi.org/10.1007/s11277-019-06969-9	https://doi.org/10.1007/s11277-019-06969-9	NUM
cana-1006	216	10	https://doi.org/10.1007/s11277-019-06969-9	https://doi.org/10.1007/s11277-019-06969-9	NUM
cana-1006	216	11	https://doi.org/10.1007/s12652-020-02763-9	https://doi.org/10.1007/s12652-020-02763-9	NUM
cana-1006	216	12	https://doi.org/10.3390/electronics11244137	https://doi.org/10.3390/electronics11244137	NOUN